锥度指数、肌肉脂肪量、BMI预测疾病的能力

No abstract

High prevalence of CI existed among rural elderly women. Significant correlation existed between CI and different CVD risk factors as well as some of the components of MS indicating a possible coexistence of different CVD risks.

Background: Obesity has been identified as a major risk factor for cardiovascular disease. Objective: To evaluate the association of central obesity with the incidence of cardiovascular diseases and risk factors. Methods: This was a cross-sectional study, carried out with patients treated at a metabolic syndrome outpatient clinic, with body mass index ≥ 24.9 kg/m2. Nutritional status, laboratory tests (lipid and glycemic profile) and blood pressure status were analyzed. Participants were stratified into groups regarding the presence or absence of risk factors: diabetes, hypertension, and dyslipidemia. Results: Women (n = 39), mean age of 44.18 ± 14.42 years, of which 70% were obese and 38% were hypertensive, corresponded to most of the studied sample. Abdominal circumference was 110.19 cm ± 15.88 cm; levels of triglycerides were 153.72 mg/dL ± 7.07 mg/dL; and fasting glycemia was 188.6 mg/dL ± 116 mg/dL. A significant association was found between the waist/height ratio and the findings of hypertension (p = 0.007); between visceral fat volume and diabetes (p = 0.01); between the conicity index and the findings of hypertension (p = 0.009) and diabetes (p = 0.006). No significant association was found between body mass index and waist circumference with findings of hypertension, diabetes and dyslipidemia. Conclusion: Central obesity was associated with a higher incidence of development of risk factors related to cardiovascular diseases.

This study aimed to investigate the performance of innovative and traditional cardiometabolic indices, including body mass index (BMI), waist circumference (WC), Chinese visceral adiposity index (CVAI), visceral adiposity index, lipid accumulation product, a body shape index (ABSI), body roundness index, conicity index (CI), triglyceride-glucose (TyG) index, TyG-BMI, and TyG-WC, in estimating atherosclerotic cardiovascular disease (ASCVD) risk in 3143 Taiwanese adults aged 20-79 years. Elevated 10-year ASCVD risk was defined as ≥7.5% using the Pooled Cohort Equations. The performance of different indices in estimating elevated ASCVD risk was assessed by receiver operating characteristic (ROC) curves. In multivariate-adjusted logistic regression analyses, all cardiometabolic indices (<i>p</i>-value < 0.001) were significantly associated with elevated ASCVD risk in both genders, except for ABSI and CI in women. In particular, CVAI had the largest area under the curve (AUC) in men (0.721) and women (0.883) in the ROC analyses. BMI had the lowest AUC in men (0.617), while ABSI had the lowest AUC in women (0.613). The optimal cut-off value for CVAI was 83.7 in men and 70.8 in women. CVAI performed best among various cardiometabolic indices in estimating elevated ASCVD risk. CVAI may be a reliable index for identifying people at increased risk of ASCVD.

No abstract

Obesity and fat patterns are important predictors of coronary heart disease risk. The relations of abdominal height (sagittal diameter) and various obesity measures to coronary heart disease risk factors were examined in a community-based sample of 409 Blacks and 1,011 Whites aged 20-38 years in Bogalusa, Louisiana (1995-1996). Obesity measures used included weight, waist circumference, waist:hip ratio, waist:height ratio, abdominal height, triceps and subscapular skinfold thicknesses, body mass index, and conicity index. Abdominal height was highly correlated with other obesity measures, especially waist circumference (0.937-0.944, p < 0.001), and was least correlated with height. In multivariate analysis, abdominal height was an independent predictor of levels of total cholesterol, triglycerides, very low density lipoprotein cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol, glucose, and insulin and of systolic and diastolic blood pressures (p < 0.05 to p < 0.001), with total R2 values ranging from 0.13 to 0.52. Abdominal height contributed more to the prediction of blood pressure than did other measures of central obesity. In canonical analysis, abdominal height was correlated more strongly with the coronary disease risk factor variables as a group than were other obesity measures. These results suggest that abdominal height adds another dimension to measures of obesity in that it may help to assess a component of visceral fat that other measures miss.

No abstract

The association of central obesity measures and food patterns with metabolic risk factors for coronary heart disease (CHD) were studied among middle aged (>or =30 years) Bengalee Hindu men of Calcutta, India. CHD risk factors included total cholesterol (TC), fasting triglyceride (FTG), fasting plasma glucose (FPG), high density lipoprotein cholesterol (HDL-c), low density lipoprotein cholesterol (LDL-c) and very low density lipoprotein cholesterol (VLDL-c). The total sample size in the study was 212 male individuals. Anthropometric measurements, metabolic and food pattern variables were collected from each participant. The relative role of central obesity measures and food pattern variables in explaining metabolic risk factors of CHD were also made in this study. The results revealed that body mass index (BMI) had no significant relation with any of the metabolic risk factors of CHD. Whereas almost all-central obesity measures, namely waist circumference (WC), waist-hip ratio (WHR), and conicity index (CI) were significantly and positively related with TC, FTG, FPG and VLDL-c. Of the food pattern variables, only the frequency of egg, fried snacks and Bengalee sweets consumption were positively and significantly related with all central obesity measures. In contrast, frequency of chicken and fish consumption was negatively associated with central obesity measures. Conicity index (CI) was found to be the most consistent in explaining metabolic variables of CHD. Percent of variance explained by central obesity measures and food patterns were TC (10%), FPG (16%), FTG (6.6%) and VLDL-c (6.7%). Significant negative association of chicken and fish consumption with central obesity measures indicates the beneficial effect of both these items in this population.

Obesity is an important risk factor for the development of diseases including diabetes, hypertension, and cardiovascular disease. However, few reports have investigated the relationships between these obesity-related indices and diabetic nephropathy. The aim of this study was to evaluate associations between obesity-related markers with albuminuria and advanced kidney disease in patients with type 2 diabetes mellitus (DM). Obesity-related indices including body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body roundness index (BRI), conicity index (CI), lipid accumulation product (LAP), visceral adiposity index (VAI), body adiposity index (BAI), abdominal volume index (AVI), body shape index (BSI), and triglyceride glucose (TyG) index were measured. Albuminuria was defined as a urine albumin/creatinine ratio of ≥30 mg/g. Advanced kidney disease was defined as an estimated glomerular filtration rate (eGFR) <30 ml/min/1.73 m2. A total of 1872 patients with type 2 DM (mean age 64.0 ± 11.3 years, 809 males and 1063 females) were enrolled. In multivariable analysis, 11 high obesity-related indices (BMI, WHR, WHtR, LAP, BRI, CI, VAI, BAI, AVI, ABSI, and TyG index) were significantly associated with albuminuria. In addition, high BMI, WHR, WHtR, LAP, BRI, CI, VAI, and AVI were significantly associated with eGFR <30 ml/min/1.73 m2. The results of this study showed that various obesity-related indices were significantly associated with albuminuria and advanced kidney disease in patients with type 2 DM. Screening may be considered in public health programs to recognize and take appropriate steps to prevent subsequent complications.

Obesity is not only associated with the development of diabetes and hypertension, but is also a known risk factor for chronic kidney disease (CKD) and is a risk factor for progressive renal function loss. Abdominal obesity is especially related to incident CKD and mortality. The decline in fat mass over time has also been related to mortality in this population. In patients on peritoneal dialysis, intra-abdominal fat accumulation has been related to cardiovascular morbidity and mortality. The body mass index is a simple method to estimate fat mass in dialysis patients. Maximum abdominal circumference, triceps and subscapular skinfolds, and arm circumference have been proposed as alternative methods in assessing subcutaneous adipose tissue to overcome the altered hydration status associated with dialysis. Waist-to-hip ratio, waist-to-height ratio and the conicity index are used to estimate abdominal fat deposits. Dual-energy X-ray absorptiometry, bioelectrical impedance analysis, computed tomography and magnetic resonance imaging are more precise and reliable methods to estimate body composition in dialysis patients. Adipose tissue is the source of a novel group of hormonally active substances known as adipokines. Patients with CKD exhibit an increase in serum concentration of most of these substances. Besides, the kidney plays an important role in the regulation of adipokines, and altered renal handling of these substances might contribute to an increase in the uraemia-associated increased risk of cardiovascular disease and mortality. In particular, pro-inflammatory adipokines, such as leptin, tumour necrosis factor-alpha and inteleukin-6, have been associated with an increased risk of mortality, whereas the link between adiponectin, an antiatherogenic adipokine, and survival is controversial in patients with CKD.

The relationship of body mass index (BMI), conicity index (CI) and waist circumference to four coronary heart disease (CHD) risk factors (systolic and diastolic blood pressures, total cholesterol and high-density lipoprotein (HDL) cholesterol levels) was examined in urban (n = 110) and rural (n = 102) men aged > or = 20 years, drawn from the 'Reddy' population of Southern Andhra Pradesh, India. Using ANCOVA we found significant difference (< 0.01) for systolic blood pressure, total cholesterol and HDL cholesterol between the urban and rural samples. The Pearson's correlation coefficients suggest that BMI and waist circumference had significant relationships with most of the risk factors in both the populations. The CI did not significantly influence any of the risk factors in the urban population; however, in the rural population, CI did show a significant positive relationship with both of the blood pressures and with TC. Even after controlling for age, smoking and physical activity (partial correlations), the relations remained constant. In multiple linear regression, BMI showed significant positive association with systolic and diastolic blood pressures (<0.01) and HDL cholesterol (<0.05) in the rural population only. However, the Cl showed a significant association with HDL cholesterol, and waist circumference with total cholesterol and HDL cholesterol in the rural population. The results of the present study revealed that BMI and waist circumference had a greater influence on the CHD risk factors, and that the influence was more conspicuous in the rural sample. Comparing the association of abdominal obesity measures (CI and waist circumference) with CHD risk factors, waist circumference better correlated with most of the risk factors. Hence the present study suggests that BMI and waist circumference are better indicators of CHD risk factors. However, the importance of Cl has to be further studied in South Asian populations.

No abstract

In menopause, changes in body fat distribution lead to increasing risk of cardiovascular disease and metabolic disorders. The aim of this study was to assess the association of adiposity using the conicity index (CI), body mass index (BMI) and waist circumference (WC) with cardiovascular risk factors (hypertension, diabetes and dyslipidaemia). The sample of this cross-sectional study was collected from June to October 2010 and 165 consecutive menopausal women who had attended the Health and Treatment Centre and Endocrine Research Centre of Firoozgar Hospital in Tehran, Iran were assessed. Age, weight, height, WC, waist-hip ratio (WHR), CI and fat mass were measured. Systolic and diastolic blood pressure (SBP and DBP), fasting blood glucose, insulin, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and total cholesterol (TC) levels were also determined. All statistical analyses were performed by SPSS version 17 (SPSS Inc, Chicago, IL, USA). Results showed that BMI was positively and significantly associated with SBP (r = 0.21; p = 0.009). WC was positively and significantly correlated with SBP (r = 0.26; p = 0.02) and DBP (r = 0.16; p = 0.05). WHR was also significantly and positively associated with SBP (r = 0.29; p = 0.001). Age and WC were associated with CI quartiles at the 0.05 significance level. The correlation of CI quartiles with SBP and weight were at the 0.01 significance level. We showed a significant association of WC with SBP and DBP, and that BMI could be an important determining factor of SBP. For assessing the association between CI and cardiovascular risk factors, future studies with larger sample sizes are recommended.

Background: Cardiovascular disease (CVD) is one of the debilitating consequences of polycystic ovary syndrome (PCOS). Early diagnosis of metabolic syndrome (MetS) with a simple but accurate method can reduce the risk of progression to CVD in PCOS. Aims: This study aimed to determine the accuracy of various anthropometric indices and lipid accumulation product (LAP), in assessing the risk of MetS in PCOS. Settings and Design: This is a cross-sectional study including 150 PCOS women and 100 control subjects. Materials and Methods: Anthropometric parameters were measured and calculated. Lipid profile, fasting plasma glucose (FPG), and insulin were estimated. MetS was detected according to the International Diabetes Federation criteria. Statistical Analysis: Logistic regression and receiver operating characteristic curve analysis were applied to determine the potential association of anthropometric indices such as body mass index, waist circumference (WC), waist-to-hip ratio, waist-to-height ratio, conicity index (CI), visceral adiposity index (VAI), abdominal volume index (AVI), body adiposity index (BAI), and a body shape index (ABSI) and LAP with MetS. Results: In our study of PCOS women of the south Indian population, the prevalence of MetS was 59.3%, which was higher than other populations and the cutoff values of VAI and LAP were 6.05 and 53, respectively. VAI showed the strongest association with MetS, followed by diastolic blood pressure BP, FPG, and LAP. Conclusions: We recommend VAI and LAP as new indices for MetS diagnosis. As these indices exhibit population specificity, it is imperative that independent cutoffs are determined for every demographic population.

A comparative study of abdominal adiposity, total cholesterol (TC), systolic (SBP) and diastolic blood pressure (DBP) in middle-aged European (n = 262) and mainly migrant Pakistani (n = 100) men of Mirpuri (Kashmiri) origin found no significant ethnic difference in mean body mass index (BMI), waist-hip ratio (WHR) and conicity index (CI). However, Pakistanis had significantly lower mean TC (p < 0.0001) and SBP (p < 0.005) but significantly higher mean (p < 0.05) DBP. Correlations of WHR and CI with age, BMI, TC, SBP and DBP were not significantly different within and between the two ethnic groups. However, multiple regression analysis revealed that Pakistanis had significantly lower cholesterol and systolic blood pressure for any given CI or WHR but no ethnic difference was observed for diastolic blood pressure. There is no evidence from this study that CI shows any advantage over WHR, as a surrogate for abdominal adiposity, in cross-sectional epidemiological investigation of risk factors for coronary heart disease (CHD) in ethnic groups like South Asians.

The interrelation between metabolic syndrome (MetS) (the revised National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) and International Diabetes Federation (IDF)) and obesity indices in predicting clinical severity and prognosis of acute ST-elevation myocardial infarction (STEMI) is insufficiently known. Material and methods: This prospective study included 250 acute STEMI patients treated with primary percutaneous coronary intervention. The patients with/without MetS were analyzed by baseline (medical history, demography and obesity indices: overall -body mass index (BMI) vs. central -body adiposity index (BAI), conicity index (Cindex), visceral adiposity index (VAI), waist circumference (WC), waist-to-hip (WHR) and waist-to-height ratio (WHtR)), severity (clinical presentation, laboratory, echocardiography, coronary angiography and in-hospital complications) and prognostic parameters (major adverse cardiovascular events and sick leave duration during 12-month follow-up). Results: There were 136 (54.4%) and 147 (58.8%) patients with MetS (NCEP-ATP III) and MetS (IDF), respectively. MetS (NCEP-ATP III) increased the risk of > 1 significantly stenosed coronary artery (CA), very high BAI increased the risk of dyspnea, Cindex > 1.25/1.18 increased the risk of total in-hospital complications, increased VAI increased the risk of coronary segment 3 significant stenosis, WHR 0.90/0.85 increased the risk of proximal/middle coronary segments (especially of segment 1) significant stenosis, WHtR 63/58 increased the risk of heart failure, and the number of significantly stenosed CAs increased the risk of total MACE (p < 0.05). Conclusions: MetS (NCEP-ATP III) and several central obesity indices are superior to BMI in predicting acute STEMI severity (clinical presentation, in-hospital complications, severity of coronary disease), while WC and MetS (IDF) have no influence on it. They all have no influence on prognosis.

Obesity is increasingly becoming a prevalent health concern among adolescents, leading to significant risks like cardiometabolic diseases (CMDs). The early discovery and diagnosis of CMD is essential for better outcomes. This study aims to build a reliable artificial intelligence model that can predict CMD using various machine learning techniques. Support vector machines (SVMs), K-Nearest neighbor (KNN), Logistic Regression (LR), Random Forest (RF), and Gradient Boosting are five robust classifiers that are compared in this study. A novel “risk level” feature, derived through fuzzy logic applied to the Conicity Index, as a novel feature, which was previously unused, is introduced to enhance the interpretability and discriminatory properties of the proposed models. As the Conicity Index scores indicate CMD risk, two separate models are developed to address each gender individually. The performance of the proposed models is assessed using two datasets obtained from 295 records of undergraduate students in Saudi Arabia. The dataset comprises 121 male and 174 female students with diverse risk levels. Notably, Logistic Regression emerges as the top performer among males, achieving an accuracy score of 91%, while Gradient Boosting lags with a score of 72%. Among females, both Support Vector Machine and Logistic Regression lead with an accuracy score of 87%, while Random Forest performs least optimally with a score of 80%.

The incidence of many chronic diseases is high among people who are obese. Therefore, identifying the association of obesity indices and cardiovascular risk factors among nurses can be useful in the advancement of public health policy and ensuring quality of life for frontline healthcare workers. The present study examines the association of obesity indices and cardiovascular disease risk factors among nurses in Trinidad and Tobago. This cross-sectional study was conducted among nurses attending the Excellence in Nursing Practice Workshop in Port of Spain, Trinidad and Tobago in June 2017. Trained nurses collected data about age, body mass index, waist circumference, conicity index, systolic and diastolic blood pressure and fasting blood glucose. The associations between obesity indices and cardiovascular risk factors were explored with Pearson’s correlation coefficient and One-way analysis of variance (ANOVA). Participants included 99 female nurses recruited by a convenient sampling method. Body mass index was positively and significantly related to systolic blood pressure. Waist circumference was positively and significantly correlated with systolic blood pressure and diastolic blood pressure. Conicity index was positively and significantly associated with systolic blood pressure, diastolic blood pressure, and fasting blood glucose. Age, weight and systolic blood pressure were correlated with conicity index quartiles. There was association between conicity index quartiles and waist circumference. The observed associations between obesity indices and cardiovascular disease risk factors suggest the importance of prevention and control of these causes of morbidity and mortality.

Conicity index (C index), an index of abdominal obesity that was developed based on a model of geometric reasoning, proved to be a sensitive and better than the waist to hip ratio indicator of risk for hyperlipidemia in Western populations. To evaluate comparatively the C index and the Waist-to-Hip Ratio (WHR) as predictors of blood pressure levels, insulin and triglyceride concentrations, we performed a cross-sectional study on 280 healthy women, 18-24 year-old. C index was found to be within the expected range (0.95 to 1.73) and significantly correlated with WHR (r = 0.562, p = 0.0001) and body weight (r = 0.312, p = 0.0001). Additionally, C index correlated with fasting insulin levels (r = 0.13, p = 0.03), and systolic blood pressure (r = 0.14, p = 0.02). WHR correlated with fasting insulin levels (r = 0.12, p = 0.05), systolic blood pressure (r = 0.12, p = 0.13) and triglycerides (r = 0.22, p = 0.0006). C index and WHR are equally good, albeit weak, predictors of fasting insulin and blood pressure levels, while WHR proved to be a better than C index predictor of triglyceride concentrations in this population of healthy premenopausal Greek women. Further epidemiologic studies to comparatively evaluate the two indexes as predictors of risk for the development of metabolic disorders and cardiovascular disease in various populations are needed.

The incidence of diabetes, atherosclerosis and sudden cardiac death is high among obese individuals, with significant metabolic and cardiovascular adverse effects being observed when obesity is centered in the abdominal region. The objective of this study was to determine which of the anthropometric indicators of abdominal obesity commonly used show the highest predictive power to discriminate a high coronary risk (HCR) and to propose cut-off values for their use in clinical practice and in population studies on Brazilian adults. The studies publi-shed by the research group on non-transmissible chronic diseases of the Public Health Institute (PHI), Federal University of Bahia (UFBA), that compare different anthropometric indicators as predictors of HCR were analyzed. The evidence provided by the studies analyzed suggests the use of the conicity index for the evaluation of abdominal obesity in clinical practice, with cut-off values of 1.25 for men and of 1.18 and 1.22 for women ≤ 49 years and &gt; 50 years, respectively. The waist-height ratio should be used in population studies, with the recommendation that waist should not exceed half the height of a particular subject.

The Brazil, as well as the world, is in a transition process, with changes in the nutritional, epidemiological and lifestyle profiles. At the same time, a progressive increase in life expectancy and the growth of chronic non-communicable diseases (NCDs) have been observed in recent decades. Among them are cardiovascular diseases whose main risk factor is obesity. In this scenario, anthropometric indicators are essential for the early identification of obesity, especially obesity accumulated in the abdominal region. The conicity index is one of the recommended tools for identifying the distribution of body fat, as it is associated with cardiovascular and metabolic complications in the population, especially in individuals with NCDs. Therefore, the use of the anthropometric indicator as a screening tool both in primary care and in epidemiological studies is recommended for the early identification of abdominal obesity.

Overweight and obesity have become a significant health hazard among adolescents on account of quick growth in its occurrence rate and its common comorbidities like cardiometabolic disease (CMD). The aim of this study was to evaluate the prevalence of adiposity and assess the risk of CMD among university students in Eastern Province, Saudi Arabia. A cross-sectional study was conducted during the academic year 2017-2018, in a sample of 310 subjects (127 males; 183 females). The measurements were taken using standardized instruments including Body Mass Index (BMI), Fat Mass Index (FMI), Body Fat Percentage BFP), Mass of Body Fat (MBF), Visceral Fat Area (VFA), Waist Circumference (WC), and Waist to Hip Ratio (WHR). Moreover, CMD risk indicators were calculated by Conicity index (C index), WC, and WHR. The findings showed that the majority was overweight and obese (16.8% and 21.6%, respectively). While evaluating obesity indicators, males were found to have higher adiposity (obese students 34.6%) compared to female students (12.6%; <i>p</i> < 0.001). Additionally, FMI showed that the mean was significantly higher among males (8.65 ± 6.06) compared to females (7.26 ± 3.30; <i>p</i> < 0.019). Analysis of the predictors' indices for cardiometabolic risk score highlighted a significantly higher percentage of WC, WHR, and C index among male students (50, 38.5, 59) compared to females (16.9, 14.2, 34; <i>p</i> < 0.001). Significant positive correlations were observed between C index quartiles and BMI with the other cardiometabolic indices (<i>p</i> < 0.001). This study highlighted a high prevalence of adiposity and CMD risk among university students. The prediction of CMD in early age is quite helpful in preventing adiposity related health issues. Decision makers need to spread awareness about healthy consumption as well as the relationship between physical inactivity and chronic diseases.

No abstract

Hypertension is a major risk factor for stroke, atherosclerosis, and other cardiovascular diseases, and obesity is a major risk factor for hypertension. The aim of this longitudinal study was to investigate sex differences in the correlations among obesity-related indices and incident hypertension in a large Taiwanese cohort. We included 21,466 enrollees in the Taiwan Biobank and followed them for 4 years. Of the 21,466 patients enrolled in this study, 6899 (mean age, 49.6 ± 10.9 years) were male and 14,567 (mean age, 49.7 ± 10.0 years) were female. Data on visceral adiposity index (VAI), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), lipid accumulation product (LAP), conicity index (CI), body roundness index (BRI), body mass index (BMI), body adiposity index (BAI), and abdominal volume index (AVI) were collected and analyzed. The results showed that all of the studied obesity-related indices were significantly associated with incident hypertension. Among them, WHtR was the strongest predictor of hypertension in both sexes. In addition, interactions between VAI, LAP, CI, BMI, and AVI with sex on incident hypertension were also statistically significant. CI and AVI were more strongly associated with hypertension in the men than in the women, while VAI, LAP, and BMI were more strongly associated with hypertension in the women. In conclusion, the studied obesity-related indices were found to be predictors of incident hypertension, and there were differences in the associations between the male and female participants. Our findings may imply that reducing body weight may be associated with a lower risk of developing hypertension.

The obesity paradox, referring to the association of high body mass index (BMI) with low all-cause mortality risk, is found in patients with chronic kidney disease (CKD). Central obesity is associated with metabolic syndrome and may have better prognostic value than BMI for all-cause mortality. Whether central obesity is associated with all-cause mortality in cases of obesity paradox in CKD patients remains unknown. We included 3262 patients with stage 3-5 CKD, grouped into five quintiles (Q1-5) by waist-to-hip ratio (WHR). Low WHR and BMI were associated with malnutrition and inflammation. In Cox regression, high BMI was not associated with all-cause mortality, but BMI < 22.5 kg/m² increased the mortality risk. A U-shaped association between central obesity and all-cause mortality was found: WHR Q1, Q4, and Q5 had higher risk for all-cause mortality. The hazard ratio (95% confidence interval) of WHR Q5 and Q1 for all-cause mortality was 1.39 (1.03-1.87) and 1.53 (1.13-2.05) in male and 1.42 (1.02-1.99) and 1.28 (0.88-1.85) in female, respectively. Waist-to-height ratio and conicity index showed similar results. Low WHR or low BMI and high WHR, but not high BMI, are associated with all-cause mortality in advanced CKD.

No abstract

No abstract

Introduction:Visceral obesity is associated with an increased risk of metabolic disorders and occurrence of chronic diseases.The quantification of the visceral fat becomes necessary and advantageous in clinical practice, especially through accurate and precise methods in replacement of imaging methods as computed tomography (CT).Objective:To present the use of anthropometric indicators that have been linked to visceral fat. Methods:The selection of items was taken in from Scopus, Scielo, Lilacs, CAPES journals, PubMed/ MEDLINE and Google Scholar, in the period between 2007 and 2014.Anthropometric and clinical indicators as waist circumference (WC), waist-to-height ratio (WHtR), waist-to-thigh ratio (WTR), waist-to-hip ratio (WRH), sagittal abdominal diameter (SAD), abdominal diameter height index (SAD/ Height), abdominal diameter index (ADI), conicity index (CI), visceral adiposity index (VAI) and the lipid accumulation production (LAP) were investigated for their relationship with visceral fat measured by CT.Results: Most indicators have strong correlation (r>0.70) with visceral fat.It was observed that there are few recent studies evaluating this relationship, especially with the indices derived of the WC and the SAD, besides the LAP and the VAI.Most studies investigated the relationship between these indicators with the diseases that are consequent of the visceral obesity. Conclusion:The clinical anthropometric indicators are accurate in estimating visceral obesity, easy to use and has low cost enabling clinical nutritional assessment able to intervene earlier and more effectively in the prevention and/or treatment of this obesity.

No abstract

Introduction: Abdominal deposition of fat has been described as the type of obesity that offers the greatest risk for the health of individuals, and is associated with increased mortality, and morbidity. Conicity index (Ci), Body mass index (BMI), and waist hip ratio (WHR) are used to predict the risk of obesity related diseases. However, it has not been ex amined whether these indicators can predict the comorbidities in hemodialysis subjects in Lebanon. Objective: to determine the effect of central obesity on comorbidities in hemodialysis patients in Lebanon. Material and Method: This is a cross-sectional study of obesity in 60 hemodialysis subjects in Lebanon. A linear regression analysis was used to determine the relationship between BMI, Ci, WHR, and comorbidities measured by Charlson (CCI) and Davies comorbidities indexes. Results: Ci values were significantly associated with age, and CCI; the abdominal fat deposition evaluated by the conicity index and WHR were a predictor of the comorbidities according to CCI (= 2.96; p = 0.01), and Davies comorbidity index (= 1.19; p = 0.05) scores. BMI was a weak predictor of comorbidity. Conclusion: Abdominal obesity by using simple anthropometric measurements e.g. Ci, and WHR values can similarly predict the presence of comorbidities in hemodialysis patients. Maintaining appropriate Ci and WHR values might be important to improve outcome in hemodialysis patients.

The hyperandrogenism in polycystic ovary syndrome (PCOS) is associated with the risk for the future development of the cardiovascular disease. The objective of the study is to verify whether different androgens have the same harmful effect. This cross-sectional study enrolled 823 women with PCOS: 627 (76.2%) with biochemical hyperandrogenism and 196 (23.8%) with normal androgen levels. The role of individual androgen was evaluated using univariate and multivariate logistic regression. In normoandrogenemic PCOS (NA-PCOS), free androgen index (FAI) predicted significant abnormality in visceral adipose index (VAI, OR=9.2, p=0.002) and dehydroepiandrosterone (DHEA) predicted against alteration in β-cell function (OR=0.5, p=0.007). In hyperandrogenemic PCOS (HA-PCOS), FAI predicted derangements in waist triglyceride index (WTI), VAI, and lipid accumulation product (LAP) (OR ranging from 1.6 to 5.8, p<0.05). DHEA weakly predicted against VAI (OR 0.7, p=0.018), dehydroepiandrosterone sulfate (DHEAS) tended to predict against the conicity index (OR=0.7, p=0.037). After multiple regression, FAI retained significant strength to predict various anthropometric and metabolic abnormalities (OR ranging from 1.1 to 3.0, p<0.01), DHEA was kept as a protector factor against WTI, LAP, and VAI (OR ranging from 0.6 to 0.9; p<0.01) and DHEAS against the conicity index (OR=0.5, p<0.001). In conclusion, the free androgen index was the most powerful predictor of anthropometric and metabolic abnormalities of polycystic ovary syndrome. Conversely, DHEA and DHEAS demonstrated protective effects against disorders in some markers of obesity and abnormal metabolism.

The incidence of diabetes, atherosclerosis and sudden cardiac death is high among obese individuals, with significant metabolic and cardiovascular adverse effects being observed when obesity is centered in the abdominal region. The objective of this study was to determine which of the anthropometric indicators of abdominal obesity commonly used show the highest predictive power to discriminate a high coronary risk (HCR) and to propose cut-off values for their use in clinical practice and in population studies on Brazilian adults. The studies publi-shed by the research group on non-transmissible chronic diseases of the Public Health Institute (PHI), Federal University of Bahia (UFBA), that compare different anthropometric indicators as predictors of HCR were analyzed. The evidence provided by the studies analyzed suggests the use of the conicity index for the evaluation of abdominal obesity in clinical practice, with cut-off values of 1.25 for men and of 1.18 and 1.22 for women ≤ 49 years and &amp;gt; 50 years, respectively. The waist-height ratio should be used in population studies, with the recommendation that waist should not exceed half the height of a particular subject.

The controlled attenuation parameter (CAP) measurement obtained from FibroScan^® is a low-risk method of assessing fatty liver. This study investigated the association between the FibroScan^® CAP values and nine anthropometric indicators, including the abdominal volume index (AVI), body fat percentage (BFP), body mass index (BMI), conicity index (CI), ponderal index (PI), relative fat mass (RFM), waist circumference (WC), waist-hip ratio (WHR), and waist-to-height ratio (WHtR), and risk of non-alcoholic fatty liver disease (fatty liver). We analyzed the medical records of adult patients who had FibroScan^® CAP results. CAP values <238 dB/m were coded as 0 (non- fatty liver) and ≥238 dB/m as 1 (fatty liver). An individual is considered to have class 1 obesity when their body mass index (BMI) ranges from 30 kg/m² to 34.9 kg/m². Class 2 obesity is defined by a BMI ranging from 35 kg/m² to 39.9 kg/m², while class 3 obesity is designated by a BMI of 40 kg/m² or higher. Out of 1763 subjects, 908 (51.5%) had fatty liver. The BMI, WHtR, and PI were found to be more strongly correlated with the CAP by the cluster dendrogram with correlation coefficients of 0.58, 0.54, and 0.54, respectively (all <i>p</i> < 0.0001). We found that 28.3% of the individuals without obesity had fatty liver, and 28.2% of the individuals with obesity did not have fatty liver. The BMI, CI, and PI were significant predictors of fatty liver. The BMI, PI, and WHtR demonstrated better predictive ability, indicated by AUC values of 0.72, 0.68, and 0.68, respectively, a finding that was echoed in our cluster group analysis that showed interconnected clustering with the CAP. Therefore, of the nine anthropometric indicators we studied, the BMI, CI, PI, and WHtR were found to be more effective in predicting the CAP score, i.e., fatty liver.

Introduction and Objective: Obesity is a major risk factor for cardiovascular disease. This study was designed to assess whether the conicity index (CI), body mass index (BMI) and waist circumference (WC) can be used as predictors of coronary artery disease (CAD) and mortality in a middle-aged population of the north-western region of Rio Grande do Sul, Brazil. Methods: This was a retrospective, longitudinal cohort study, based on the medical records of patients seen in a cardiology institution in a rural area of Rio Grande do Sul. The sample consisted of 2396 individuals. The primary endpoint was diagnosis of CAD, with mortality as the secondary endpoint. CI, BMI and WC were assessed using logistic regression, Cox regression and receiver operating characteristic curve analysis. Results: The study showed that none of the anthropometric measures could be considered independent factors for either a diagnosis of CAD or mortality. Female gender was associated with a significantly lower risk of CAD (odds ratio [OR]: 0.31; 95% confidence interval [CI]: 0.22-0.44), as was absence of diabetes (OR: 0.52; 95% CI: 0.33-0.82), while there was a significantly higher risk of mortality associated with the presence of CAD (OR: 3.56; 95% CI: 2.00-6.32) and alcohol consumption (OR: 3.55; 95% CI: 1.60-7.90). Conclusions: These anthropometric measures were not independent predictive factors for CAD diagnosis or mortality in a population in southern Brazil. Our results support the conclusion that determination of CI, BMI and WC alone is insufficient to assess the risk of CAD and mortality in the general population. Resumo: Introdução e objetivo: A obesidade é um importante fator de risco para doenças cardiovasculares. O objetivo deste estudo foi avaliar se o índice de conicidade (IC), índice de massa corporal (IMC) e circunferência abdominal (CA) podem ser usados como preditores de doença arterial coronariana (DAC) e mortalidade em uma população de meia-idade da região noroeste do Rio Grande do Sul, Brasil. Métodos: Estudo de coorte retrospectiva, longitudinal, realizado com o registro dos prontuários de indivíduos atendidos em uma instituição cardiológica do interior do Rio Grande do Sul, Brasil. A amostra constou de 2396 indivíduos. Foram consideradas como variáveis de desfecho primário o diagnóstico de DAC e secundário a mortalidade. O IC, IMC e CA foram analisados através de regressão logística, regressão de Cox e curva ROC. Resultados: O estudo mostrou que nenhuma das medidas antropométricas pôde ser considerada como fatores independentes, tanto para o diagnóstico de DAC, quanto para a mortalidade. Houve uma redução significativa do risco para DAC associada com o sexo feminino (odds ratio [OR]: 0,31; intervalo de confiança [IC95%]: 0,22-0,44) e ausência de diabetes mellitus (OR: 0,52; IC95%: 0,33-0,82) e um aumento significativo do risco de mortalidade associada à presença de DAC (OR: 3,56; IC95%: 2,00-6,32) e etilismo (OR: 3,55; IC95%: 1,60-7,90). Conclusão: As medidas antropométricas não se mostraram importantes como fator preditivo independente para o diagnóstico de DAC e mortalidade em uma população estudada no sul do Brasil. Nossos resultados suportam o conceito de que a mensuração isolada do IC, IMC e CA não são suficientes na avaliação do risco de DAC e mortalidade na população geral. Keywords: Cardiovascular disease, Risk factors, Abdominal obesity, Mortality, Population, Palavras-chave: Doenças cardiovasculares, Fatores de risco, Obesidade abdominal, Mortalidade, População

Abstract Funding Acknowledgements Type of funding sources: None. Background Cardiovascular disease (CVD) is the leading cause of death globally and one of the most frequent causes of disability. Therefore, the complete and correct evaluation of cardiovascular risk factors is essential to timely prevent CVD. Once central obesity is related with the amount of visceral adipose tissue - an independent predictor of CVD risk - its assessment may play an important role in 10-year CVD prediction. The conicity index (C-Index) assesses central adiposity but there is limited data regarding its role in 10-year CVD risk prediction. Purpose To evaluate the role of C-Index in predicting 10-year risk of fatal and non-fatal CVD according to SCORE2 and SCORE2-OP models in a moderate-risk country population. Methods We conducted a cross-sectional study in a Portuguese population sample. Individuals aged 40-90 years without known established Atherosclerotic Cardiovascular Disease, Diabetes mellitus, Chronic Kidney Disease or Familial Hypercholesterolemia were included in the study through a local cardiovascular (CV) screening event in Portugal, during May 2022. The C-Index was calculated for each individual according to the Valdez’s formula. For CVD risk assessment, we used the cut-offs values proposed by Pitanga et al. 1.18 for women and 1.25 for men. The population was divided into two groups according to the C-Index (risk high versus low). The 10-year risk of fatal and non-fatal CVD was calculated using SCORE2 and SCORE2-OP models. Results A total of 431 individuals were enrolled in this study. Median age was 71 years (Q1-Q3: 65-75) and 66.8% of were women. A total of 48.1% had hypertension, 38.3% dyslipidemia, 25.5% obesity and 6.6% were active smokers. Overall, 387 (90.2%) individuals were found to have elevated C-Index (SCORE2/2-OP mean± DP: 14.99± 7.56 versus 09.81± 3.37), of which 259 were female. In the univariate analysis, there was a correlation between C-Index and estimation of the Risk Cardiovascular Disease according to SCORE2/2-OP but was not statistically significant (Exp (beta) 95 % (CI):2.52 (-2.06-7.10, p=0.28)). However, in the multivariable linear regression analyzes the variable waist circumference (Exp (beta) 95 % (CI)18.47 (4.69 – 32.24, p&amp;lt;0.001)) was independent predictive factor related to the Risk of Cardiovascular Disease according to SCORE2 and SCORE2-OP. Conclusions In the present study most of the patients were categorized into high-risk category. Conicity index was not significantly correlated with estimation of the Risk of Cardiovascular Disease according to SCORE2 and SCORE2-OP models, but the variable waist circumference (Exp (beta) 95 % (CI)18.47 (4.69 – 32.24, p&amp;lt;0.001)) was an independent predictive factor related. More studies are needed to assess the role of C-Index in CVD risk prediction.

Background: Obesity in children is often expressed by indicators like Body Mass Index, Waist Circumference, Waist-to-Hip ratio etc. Each of these has its own merits and demerits. Among these, BMI is commonly used to assess overweight/obesity but the central obesity is more important than the body mass as it has shown strong association with risk for coronary heart disease, adverse lipid profile and hyper insulinaemia in children. The objectives were to assess the validity of waist-hip ratio, waist-to-height ratio, conicity index as indicators of central obesity in children as measured by waist circumference.Methods: This is a cross sectional study conducted on 4663 students who were enrolled in 8th to 10th standard of government and private schools of Mandya city. Weight, height, waist and hip circumference are measured following WHO guidelines. The data was analyzed using mean, standard deviation, proportion, cut off, sensitivity, and specificity. ROC curves were drawn to assess the validity of the anthropometric measurements.Results: Using the WC percentiles given by Kuriyan R, the prevalence of overweight/obesity was found to be 7.59% with 8.85% in girls and 6.03% in boys. Waist-to-Height ratio performed significantly better than waist-to-hip ratio and conicity index in identifying central obesity in both girls and boys as indicated by the AUCs.Conclusions: The age and sex specific cut off points for waist-to-hip ratio, waist-to-height ratio and conicity index can be used to detect overweight/obesity in Indian Children aged 11-16 years.

Obesity is the main risk factor for obstructive sleep apnea syndrome (OSAS) and genetic patterns can modulate the pathogenesis of the disease. The aim of this study is to describe the anthropometrics and dermatoglyphics features among OSAS carriers. We collected information on Body Mass Index (BMI), Conicity Index (CI), Body Fat Mass (BFM), somatotype and fingerprints. Thirty-one cases of OSAS were compared to an equal number of controls. Membership to the obese category is based on observed BMI and BFM. The CI distribution among cases shows a strong central obesity component. The endomorph-mesomorph somatotype category predominates among cases showing high adiposity and relative muscle-skeletic development, such as relative linearity of great mass per unit of height. Increased morbidity, as given by more serious indices of apnea, correlates positively with higher mesomorphic predominance in the body composition. Analysis of dermatoglyphic data does not show significant statistical differences between OSAS--patients and controls.

Abstract High blood pressure is a leading cause of mortality worldwide and a risk factor for several diseases. The aim of this study was to determine the predictive power of anthropometric indicators of obesity and establish their cutoff points as discriminators of hypertension and identify the anthropometric indicator of obesity that best discriminates high blood pressure in the elderly. This is a cross-sectional study with a sample of 300 older adults, 167 (56.5%) women. The following anthropometric indicators of obesity were measured: body mass index (BMI), waist circumference (WC), waist / height ratio (WHtR) and conicity index. Moreover, systolic and diastolic blood pressure measurements were collected. To identify hypertension predictors, the analysis of receiver operating curves (ROC) with 95% confidence interval was adopted. Subsequently, cutoff points with their respective sensitivities and specificities were identified. Analyses were carried out considering 5% significance level. It was observed that some anthropometric indicators of obesity showed area under the curve (AUC) significant with BMI = 0.60 (0.50 to 0.70); WHtR = 0.61 (0.51 to 0.71); conicity index = 0.58 (0.58 to 0.68) in men. The different cutoff points of anthropometric indicators with better predictive power and their respective sensitivities and specificities were identified. The best areas under the ROC curve were for BMI, WHtR and conicity index for men; however, such measures were not satisfactory to predict high blood pressure in women.

Ten per cent of the world's school-aged children are estimated to be carrying excess body fat (Fig. 1), with an increased risk for developing chronic disease. Of these overweight children, a quarter are obese, with a significant likelihood of some having multiple risk factors for type 2 diabetes, heart disease and a variety of other co-morbidities before or during early adulthood. The prevalence of overweight is dramatically higher in economically developed regions, but is rising significantly in most parts of the world. Prevalence of overweight and obesity among school-age children in global regions. Overweight and obesity defined by IOTF criteria. Children aged 5–17 years. Based on surveys in different years after 1990. Source: IOTF (1). In many countries the problem of childhood obesity is worsening at a dramatic rate. Surveys during the 1990s show that in Brazil and the USA, an additional 0.5% of the entire child population became overweight each year. In Canada, Australia and parts of Europe the rates were higher, with an additional 1% of all children becoming overweight each year. The burden upon the health services cannot yet be estimated. Although childhood obesity brings a number of additional problems in its train – hyperinsulinaemia, poor glucose tolerance and a raised risk of type 2 diabetes, hypertension, sleep apnoea, social exclusion and depression – the greatest health problems will be seen in the next generation of adults as the present childhood obesity epidemic passes through to adulthood. Greatly increased rates of heart disease, diabetes, certain cancers, gall bladder disease, osteoarthritis, endocrine disorders and other obesity-related conditions will be found in young adult populations, and their need for medical treatment may last for their remaining life-times. The costs to the health services, the losses to society and the burdens carried by the individuals involved will be great. The present report has been written to focus attention on the issue and to urge policy-makers to consider taking action before it is too late. Specifically, the report: reviews the measurement of obesity in young people and the need to agree on standardized methods for assessing children and adolescents, and to compare populations and monitor trends; reviews the global and regional trends in childhood obesity and overweight and the implications of these trends for understanding the factors that underlie childhood obesity; notes the increased risk of health problems that obese children and adolescents are likely to experience and examines the associated costs; considers the treatment and management options and their effectiveness for controlling childhood obesity; emphasizes the need for prevention as the only feasible solution for developed and developing countries alike. This document reflects contributions from experts working in a wide range of circumstances with a diversity of approaches, but with many shared opinions. The report has been endorsed by the Federation of International Societies for Paediatric Gastroenterology, Hepatology and Nutrition (FISPGHAN) and the International Paediatric Association (IPA). Health professionals are aware that the rising trends in excess weight among children and adolescents will put a heavy burden on health services (for example, 10% of young people with type 2 diabetes are likely to develop renal failure by the time they enter adulthood, requiring hospitalization followed by life-long dialysis treatment (2). Health services, especially in developing countries, may not easily bear these costs, and the result could be a significant fall in life expectancy. In industrially developed countries, children in lower-income families are particularly vulnerable because of poor diet and limited opportunities for physical activity. There may also be an ethnic component; for example, in the USA the prevalence of overweight among children aged 4–12 years rose twice as fast in Hispanic and African–American groups compared with white groups over the period 1986–1998 (3). In developing nations child obesity is most prevalent in wealthier sections of the population. However, child obesity is also rising among the urban poor in these countries, possibly due to their exposure to Westernized diets co-inciding with a history of undernutrition. Such rapid changes in the numbers of obese children within a relatively stable population indicate that genetic factors are not the primary reason for change. Some migration of populations may account for a proportion of the epidemic, but cannot account for it all. Although studies of twins brought up in separate environments have shown that a genetic predisposition to gain weight could account for 60–85% of the variation in obesity (4), for most of these children the genes for overweight are expressed where the environment allows and encourages their expression. These obesity-promoting environmental factors are sometimes referred to as ‘obesogenic’ (or ‘obesigenic’). Put graphically, a child's genetic make-up ‘loads the gun’ while their environment ‘pulls the trigger’ (5). A genetic predisposition to accumulate weight is a significant element in the equation, but its importance might best be viewed from another perspective: the genes that predispose for obesity are likely to be commonplace, with only a small proportion of children able to resist gaining weight in an obesogenic environment. The changing nature of the environment towards greater inducement of obesity has been described in WHO Technical Report (6) on chronic disease as follows: ‘Changes in the world food economy have contributed to shifting dietary patterns, for example, increased consumption of energy-dense diets high in fat, particularly saturated fat, and low in unrefined carbohydrates. These patterns are combined with a decline in energy expenditure that is associated with a sedentary lifestyle—motorized transport, labour-saving devices at home, the phasing out of physically demanding manual tasks in the workplace, and leisure time that is preponderantly devoted to physically undemanding pastimes.’ (pp. 1–2) This emphasis on the environmental causes of obesity leads to certain conclusions: first that the treatment for obesity is unlikely to succeed if we deal only with the child and not with the child's prevailing environment, and second that the prevention of obesity – short of genetically engineering each child to resist weight gain – will require a broad-based, public health programme. A doctor presented with an obese child must nevertheless attempt some form of remedial intervention to prevent the child's health deteriorating. The aim is to stabilize and hopefully reduce that child's accumulation of body fat, using a range of approaches discussed in the next few paragraphs. For a great majority of obese patients, the first point of contact is with a primary care physician or a public health nurse. Yet the relevant training in bariatric methods (methods related to the assessment, prevention and treatment of obesity) at the undergraduate level remains inadequate. Two national surveys in the USA conducted over 10 years, indicated that paediatric obesity was the most wanted topic for continuing medical education (7). For children who are moderately overweight, measures to prevent further weight gain, combined with normal growth in height, can be expected to lead to a decrease in BMI – i.e. children may be able to ‘grow into’ their weight. For the more seriously obese child, treatment regimes are largely palliative and designed to manage and control rather than resolve the problem. Weight control and improved self-esteem may be achieved, but the child is likely to remain seriously overweight and at risk of chronic disease throughout his or her life. The clinical management of obese children may require an extended amount of time and the assembly of a professional team including a dietitian, exercise physiologist and psychologist in addition to the physician. As paediatric obesity becomes more common, patient management may not be restricted to obesity clinics and other forms of management may be developed. Obesity clinics may be necessary for morbid obesity, but less severe forms of obesity may be better managed in primary care settings by a range of health practitioners. Obesity control in adults relies on a range of options: improvements in nutritional habits, raised levels of physical activity, behavioural modification and psychotherapy, pharmaceutical treatment and as a last resort, surgery. These options can be used alone or in combination. For children, neither surgery nor drug therapy can currently be recommended unless within a closely monitored research study (8). Of the remaining choices, no single method will ensure success, although some consensus exists. For example, reducing the time engaged in sedentary activities (such as watching television or playing computer and video games) has been shown to facilitate better treatment outcome (9). Dietary interventions in combination with exercise programmes have been reported to have better outcomes than dietary modulation alone. Exercise programmes alone without dietary modification are unlikely to be effective, because increased energy expenditure is likely to be matched by increased energy intake (10). A whole-family approach also appears vital, with several studies showing that outcomes are improved if the parents are engaged in the process, or even are the key instigators of the process, at least for younger children (11). Very strict dietary limitations were reported to have better short-term results than moderate dietary limitations. However, strictly modified diets cannot be maintained for long periods of time. More marked rebound effects are observed after the discontinuation of strict diets than after moderate dietary modifications. Two additional concerns regarding strict dietary limitations are: (1) the risk of not meeting basic nutrient requirements and thus adversely affecting growth; and (2) the risk of inducing adverse psychological effects, including appetite or eating disorders, feelings of stigmatization, anxiety and low self-esteem, especially if the intervention is not successful or the child has prior psychological problems (12, 13). Many questions regarding what constitutes the best treatment remain unanswered: there have been few sufficiently large multicentre clinical trials to test the efficacy and safety of well-defined obesity treatment programmes. Such trials may reveal which non-pharmacological and non-surgical interventions can help manage obesity over the long term. Losing weight over the short term, but then experiencing a rebound gain in weight, remains the usual experience for the majority of obese children and adolescents. The importance of further research cannot be over stated, but it is not uncommon for research and treatment to compete for limited financial resources, with research frequently being more successful in securing financial support. The lack of paediatric obesity clinics at many well-respected academic institutions illustrates this point. If the current approach to treatment is largely aimed at bringing the problem under control, rather than effecting a cure, and if this aim is only successful when a multi-disciplinary and intensive regimen is mounted, then managing the obesity epidemic will be vastly expensive and probably unaffordable for most countries. Pharmaceutical approaches may assist, but cannot replace, the multi-disciplinary management of obesity. Prevention is the only feasible option and is essential for all affected countries. Yet effective techniques for prevention have also proved elusive. Programmes to prevent obesity in children may start by identifying those children at greatest risk, but there are problems with this approach. Although screening for obesity potential may help target resources where they are most needed, such screening also creates stigma among the children identified if they are singled out for special attention. Furthermore, genetic studies suggest that most children are at risk of weight gain, and that strategies to prevent obesity in a child population – such as encouraging healthful diets and plentiful physical activity – will benefit the health of all children, whether at risk of obesity or not. The most logical settings for preventive interventions are school settings and home-based settings. A number of interventions have been tried at these levels, and these are reviewed in the present report, but success has been hard to demonstrate. A Cochrane review of those trials of sufficient duration to detect the effects of intervention concluded that there was little evidence of success (14). It suggested that a more reliable evidence base is needed in order to determine the most cost-effective and health promoting strategies that have sustainable results and can be generalized to other situations. As shown in the present report, there are several examples of interventions designed to prevent the rising levels of obesity – such as the school-based ‘Trim and Fit’ programme in Singapore and the ‘Agita Sao Paulo’ programme in Sao Paulo, Brazil. Favourable outcomes have been shown with small-scale interventions, modifying children's TV watching behaviour and promoting consumption of healthier foods by establishing a price differential. Although the beneficial results of such interventions may be detectable and significant, they are small compared with the size of the problem. Moreover, the improvements tend to decline after the intervention ends. It must be concluded that interventions at the family or school level will need to be matched by changes in the social and cultural context so that the benefits can be sustained and enhanced. Such prevention strategies will require a co-ordinated effort between the medical community, health administrators, teachers, parents, food producers and processors, retailers and caterers, advertisers and the media, recreation and sport planners, urban architects, city planners, politicians and legislators. This report highlights the underlying social changes that have led to rising levels of obesity in both the adult and child populations. These underlying factors, as listed below, are often a part of, or a consequence of social development and urbanization. Such development based on economic growth to enhance consumption is generally regarded in a positive light and, especially in developing countries as they emerge from poverty, may be aspired to. Increase in use of motorized transport, e.g. to school. Increase in traffic hazards for walkers and cyclists. Fall in opportunities for recreational physical activity. Increased sedentary recreation. Multiple TV channels around the clock. Greater quantities and variety of energy dense foods available. Rising levels of promotion and marketing of energy-dense foods. More frequent and widespread food purchasing opportunities. More use of restaurants and fast food stores. Larger portions of food offering better ‘value’ for money. Increased frequency of eating occasions. Rising use of soft drinks to replace water, e.g. in schools. Changes in these social trends may require increased awareness by countries of the health consequences of the pattern of consumption as the first step in a strategy to promote healthier diets and more active lives. Several authors 15-18) have suggested that efforts to prevent obesity should include measures involving a wide range of social actions, such as: public funding of quality physical education and sports facilities; the protection of open urban spaces, provision of safer pavements, parks, playgrounds and pedestrian zones, creation of more cycling paths; taxes on unhealthy foods and subsidies for the promotion of healthy, nutritious foods; dietary standards for school lunch programmes; elimination or displacement of soft drinks and confectionery from vending machines in schools and offering healthier choices (i.e. low-fat dairy products, fruits and vegetables); clear food labelling and controls on inconsistent health messages; controls on the political contributions given by the food industry; restrictions or bans on the advertising of foods to children; limits on other forms of marketing of foods to children; assessment of food industry initiatives to improve formulations and marketing strategies. It is clear from these suggestions that policies and actions will be needed at a variety of levels, some local and individually based, some national or internationally based. All of them will require the support and involvement of departments across the broad range of government and may include education, social and welfare services, environment and planning, transport, food production and marketing, advertising and media, and international trading and standard-setting bodies. Obesity prevention will involve work at all levels of the obesogenic environment. As Fig. 2illustrates, attempts to improve the environment at one level, for example the school, may be undermined by a failure to improve the environment at another level, be it below in the home, or above in the social and cultural context involving food marketing and advertising, lost recreational facilities or unsafe streets. The opportunities for influencing a child's environment. Children are vulnerable to the social and environmental pressures that raise the risk of obesity. Although they can be encouraged to increase their self-control in the face of temptation, and although they can be given knowledge and skills to help understand the context of their choices, children cannot be expected to bear the full burden of responsibility for preventing excess weight gain. The prevention of childhood obesity requires: improving the family’s ability to support a child in making changes, which in turn needs support from the school and community, for example . . . ensuring the school has health-promoting policies on diet and physical activity, and that peer group beliefs are helping the child, which in turn requires that . . . the cultural norms, skills and traditional practices transmitted by the school are conducive to health promotion, and that the community a environment, such as . . . policies for and and recreation and ensuring to food which in turn requires that . . . at and regional level are such e.g. for and improved food through and that . . . national and international that standards and services are encouraging better public and practices promote choices, which in turn may require . . . and support to ensure that strategies for obesity are and and control measures are and that these are not by other government and that . . . government and activities in all including education, transport, the environment and social welfare policies are for their health and food e.g. for for the and schools and other involved in public are with health and The present report is to health social and in a to at national and international level, by a to the problems and an of the policies needed to It is written in the context of the Health work on the prevention of chronic and the development of strategies to promote physical activity and The document (6) the development of with health with other and to develop relevant programmes and The document for positive such as measures to support the greater of nutrient dense to reduce on motorized transport, to increase to recreation facilities and to ensure health is and easily and health are relevant and The WHO has the restrictions on countries by international such as those that and marketing The WHO can a in public health when these This upon political which in part upon from the medical and from The present report is designed to to that The International Obesity upon the WHO to countries to develop Obesity and to childhood obesity prevention within those of might be clear and e.g. on food food to more nutritious foods for children; develop for advertising that healthier improve and of facilities and local schools to and physical activity medical and health professionals to in the development of public health programmes. The International Obesity is to the WHO in developing these childhood obesity will require and but the world's children no suggest that of body fat should be in its of body with small measurement in of and of to the and with further that all these of in children and adolescents in a range of using a range of In this both and methods for assessing and are described and the and of these different methods used for population and clinical are measures of body an of body fat and of Such techniques include or and energy The methods are used for research and in care but may be used as a to measures of body the measures of or are and other and from and weight such as or the and All to some on the of the and their as a of must be a of The primary for overweight and obesity are to health and to between populations. with a need to be that where should that best these For the have been based on with and BMI being the most used both and in population Although not health weight for have a of assessing populations of children, especially those aged under years, and are used to both and weight for is and low weight for is found as a consequence of disease. A high weight for is overweight and high weight for is The use of weight for has the of not requiring knowledge of the child's which may be hard to in less developed but it should not be used as a for for or weight for as all measures different in In the use of weight for was recommended by WHO for children below the of 10 years, but a WHO review found that use of the for Health should not be recommended especially as it not account of between and children The WHO may consider standards based on studies of children showing growth The weight for is on a based on a which a based on the between the observed and the of a standardized the of the population. a of is to the or a of is to the and a of is The use of a weight for allows a more of an or a and between populations can also be and trends over time can be the in an require skills or programmes. In of overweight and obese the are based only on rather than a health In a study of young people aged 5–17 years, that fat as by was associated with an adverse and A high has also been shown to Although have been described for the for high or low health have not been may be in clinical as a of a child or to weight control In it may be used to a population in of fat and to determine the prevalence of risk cannot be used to a child as being at a high or low As suggested in 2 BMI is significantly associated with in childhood and and is the most of BMI with and It during the first after after the first and around the of this second is sometimes referred to as examples of childhood BMI by and A given of BMI needs to be and Several countries, including the and the have developed their using local In the USA, by from in the early have been used and were recommended for children years or by a WHO in More the for Health has based on from national health from although to an of the weight and BMI from the most were for children over the of years The of using is that a child can be described as being above or below certain (for example the or which can be in a clinical are from a single and an as overweight or obese that the is to that population. Furthermore, may the as an when the may in from a population with a high prevalence of obesity, such as the USA The that those children with a BMI greater than or to the be as and those children with a BMI between the and be as risk of In some children at or above the are referred to as and in to children above the As with the use of measures compared with populations, BMI can be compared with a and reported as A BMI is

The prevalence of overweight and obesity is increasing worldwide.1 A comparison of data from 1976–802 with that from 1999–2000 shows that the prevalence of overweight (defined as body mass index, BMI, of 25–29.9 kg/m2) increased from 46% to 64.5%, and the prevalence of obesity (BMI ⩾ 30 kg/m2) doubled to 30.5%. The epidemic of obesity is not just isolated to the US, but is worldwide,3,,4 including less affluent countries.4 Obesity and overweight have many causes, including genetic, metabolic, behavioural and environmental. The rapid increase in prevalence suggests that behavioural and environmental influences predominate, rather than biological changes. We summarize data from many studies evaluating the impact of obesity on mortality and morbidity, discuss some controversies and provide practical guidelines for managing obese patients. Direct associations between obesity and several diseases, including diabetes mellitus, hypertension, dyslipidaemia and ischaemic heart disease, are well recognized. Despite this, the relationship between body weight and all-cause mortality is more controversial. A very high degree of obesity (BMI ⩾35 kg/m2) seems to be linked to higher mortality rates,5 but the relationship between more modest degrees of overweight and mortality is unclear. Initial data from actuarial studies of more than 4 million men and women showed a direct positive association between body weight and overall mortality rates.6 Subsequent studies confirmed increased mortality risk above a certain threshold, but found a U-shaped association between weight and mortality.7,,8 In the Build study,9 there was a higher mortality in lean subjects, but there was no adjustment for smoking. The American Cancer Society found a much stronger association between leanness and mortality, specifically cancer mortality, in the group of smokers compared to non-smokers.10 The Harvard Alumni Study11 was a prospective cohort study of more than 19 000 middle-aged … Address correspondence to Dr S.D.H. Malnick, Department of Internal Medicine C, Kaplan Medical Centre, Rehovot 76100, Israel. email: stevash{at}trendline.co.il

Dual-energy x-ray absorptiometry (DXA) can provide accurate measurements of body composition. Few studies have compared the relative validity of DXA measures with anthropometric measures such as body mass index (BMI) and waist circumference (WC). The authors compared correlations of DXA measurements of total fat mass and fat mass percent in the whole body and trunk, BMI, and WC with obesity-related biologic factors, including blood pressure and levels of plasma lipids, C-reactive protein, and fasting insulin and glucose, among 8,773 adults in the National Health and Nutrition Examination Survey (1999-2004). Overall, the magnitudes of correlations of BMI and WC with the obesity-related biologic factors were similar to those of fat mass or fat mass percent in the whole body and trunk, respectively. These observations were largely consistent across different age, gender, and ethnic groups. In addition, in both men and women, BMI and WC demonstrated similar abilities to distinguish between participants with and without the metabolic syndrome in comparison with corresponding DXA measurements. These data indicate that the validity of simple anthropometric measures such as BMI and WC is comparable to that of DXA measurements of fat mass and fat mass percent, as evaluated by their associations with obesity-related biomarkers and prevalence of metabolic syndrome.

The growing worldwide prevalence of type 2 diabetes mellitus in the young, as underlined by an earlier International Diabetes Federation (IDF) Consensus Statement 1, has highlighted a significant shortfall of data on the epidemiology of the disorder and the identification and treatment of children and adolescents at risk of progression to this disease. Urbanization, unhealthy diets, and increasingly sedentary lifestyles have contributed to increase the prevalence of childhood obesity, particularly in developing countries 2. Current treatment initiatives include school-based programs addressing physical activity and diet, which have been conducted with mixed success in reducing adiposity. There are limited safety data supporting the use of drugs for the treatment of obesity and related conditions such as type 2 diabetes in children and adolescents, and non-compliance in this population suggests that pharmacotherapy is unlikely to be effective long term 1. Although criteria have now been developed for bariatric surgery in teenagers 3, there are few evidence-based data available to support the increasing use of this modality in adolescents. Governments and society in general must be made more aware of the problems associated with obesity and the likelihood of progression to the metabolic syndrome in children and adolescents. Obesity, particularly in the central (abdominal) region, has been determined as a key factor in the etiology of type 2 diabetes 2. The prediction of health risks associated with obesity in youth is improved by the additional inclusion of waist circumference (WC) measure to the body mass index (BMI) percentile 4, 5. Such observations reinforce the importance of including WC in the assessment of childhood obesity to identify those at increased metabolic risk as a result of excess abdominal fat 5. The role of obesity can clearly be demonstrated in Japan, where a parallel increase in type 2 diabetes and obesity in children has occurred over the past few decades 6. Central (abdominal) obesity is also a key component in the IDF definition of metabolic syndrome in adults 2. The link between obesity, metabolic syndrome, and type 2 diabetes has already been characterized in adult populations 2. At present, 50–80% of almost 250 million adults worldwide with diabetes 7 are at risk of death from cardiovascular disease. Those with the metabolic syndrome are also at increased risk being twice as likely to die from, and three times as likely to have, cardiovascular complications as compared with those without the syndrome 8, 9. In addition, adults with the metabolic syndrome have a fivefold greater risk of developing type 2 diabetes 10. Already, one-quarter of the world’s adult population have metabolic syndrome 11, 12, and this condition is appearing with increasing frequency in children and adolescents, driven by the growing obesity epidemic in this young population 13-15. In 2004, the World Health Organization (WHO) reported that an estimated 22 million children younger than 5 yr of age and 10% of school-aged children, between 5 and 17 yr, were overweight or obese 16. WHO predicts that the prevalence of childhood obesity in developed and developing countries will continue to increase as has been seen in recent years. For example, from 1985 to 1997, in young Australians, the prevalence of overweight and obesity combined doubled and that of obesity trebled 17. In Thailand, the prevalence of obesity in those aged 5–12 yr increased from 12.2 to 15.6% in just 2 yr 18. In 2003–2004, 17.1% of children aged 2–19 yr in the USA were obese 19. Obesity is associated with an increase in cardiovascular risk factors (also indicators of metabolic syndrome) 20, and the persistence of these indicators from childhood and adolescence to young adulthood has been shown in several studies, including the Quebec Family Study 21, 22. Recently, the IDF released its guidelines for defining and diagnosing the metabolic syndrome in adults 2. The intention was to rationalize the existing multiple definitions of the syndrome and to avoid the confusion that arose as a result of conflicting opinions on the value of each set of criteria. The use of a single unified definition makes it possible to estimate the global prevalence of metabolic syndrome and make valid comparisons between nations. However, to date, there has not been a unified definition that can be used to assess risk in children and adolescents, and existing adult-based definitions of the metabolic syndrome may not be appropriate to address the problem in this age group. A study of adolescents using modified National Cholesterol Education Program (NCEP) [Adult Treatment Panel III (ATP III)] criteria 23 identified that 12% of the study group had the metabolic syndrome 24. When the ≥95th percentile of BMI was used as a cutoff point in the same study group, 31.3% were identified as having the syndrome, more than double of those previously found to be at risk. Duncan et al. 25 studied 991 adolescents (aged 12–19 yr) from National Health and Nutrition Examination Study (NHANES) 1999–2000 and used the ATP III definition modified for age. The overall prevalence of a metabolic syndrome phenotype among US adolescents increased from 4.2% in NHANES III (1988–1992) to 6.4% in NHANES 1999–2000. Based on population-weighted estimates, they estimated that more than 2 million US adolescents currently have a metabolic syndrome phenotype. In a population-based study of a Canadian Qji-Cree community involving 236 children aged 10–19 yr, Retnakaran et al. reported that 18.6% of the children met the criteria for the metabolic syndrome based on a pediatric metabolic syndrome definition based on the ATP III definition, and they used the ATP III definition modified for age and gender 26. Goodman et al. reported on a school-based, cross-sectional study of 1513 black, white, and Hispanic teenagers 27. Overall, the prevalence of ATP III-defined metabolic syndrome was 4.2% and that of the WHO-defined metabolic syndrome was 8.4%. The metabolic syndrome was found almost exclusively among obese teenagers in whom prevalence of the ATP III-defined metabolic syndrome was 19.5% and prevalence of WHO-defined metabolic syndrome 28 was 38.9%. No race or sex differences were present for ATP III definition. However, non-white teenagers were more likely to have metabolic syndrome by WHO criteria, and it was more common among girls if the WHO definition was used. Chi et al. have recently undertaken a literature review on definitions of the metabolic syndrome in children and adolescents published in the past decade 29. They noted that the prevalence of metabolic syndrome in pre-adolescent girls varies widely because of disagreement among proposed definitions of metabolic syndrome in pediatrics. They called for a consensus definition for the metabolic syndrome in children, which would allow researchers to make better temporal, biological, environmental, and social comparisons between data sets. The American College of Endocrinology definition 30 is not ideal in pediatric subjects as WC is rarely measured in children, and nomograms have only recently become available 31 for some ethnic groups but are not available for all. A recent paper has suggested yet another set of criteria with age- and gender-specific cutoff points 32. The variety of cutoff points used for the different components in this paper underlines the need for a single consistent definition with easily measurable components. Therefore, to date, no formal definition for the diagnosis of the metabolic syndrome in children and adolescents has been developed. The rapid increase in obesity highlights the urgency for a definition that could be used to further understand who is at high risk and to distinguish them from those with ‘simple’ uncomplicated obesity. The metabolic syndrome in adults is defined as a cluster of cardiovascular and diabetes risk factors including abdominal obesity, dyslipidemia, glucose intolerance, and hypertension 2. While the danger associated with clustering of components of the metabolic syndrome has been demonstrated in adults, where the presence of three or more components significantly increases the risk for coronary heart disease death/non-fatal myocardial infarction and the onset of new diabetes 33, few, if any, outcome data in children exist. While one definition, although with gender- and ethnicity-specific cutoff points, is suitable for use in the at-risk adult population 2, transposing a single definition to children and adolescents is problematic. Blood pressure, lipid levels, and anthropometric variables change with age and pubertal development. Puberty impacts on fat distribution and is known to cause a decrease both in insulin sensitivity, of approximately 30% with a complementary increase in insulin secretion 34, and in adiponectin levels 35. Therefore, single cutoff points cannot be used to define abnormalities in children. Instead, values above the 90th, 95th, or 97th percentile for gender and age are used. However, there has not been universal agreement as to which level to use for the criteria for the metabolic syndrome. The importance of the early identification of children at risk of developing the metabolic syndrome and subsequently progressing to type 2 diabetes and cardiovascular disease in later life must not be underestimated. From birth and before, circumstances can predispose a child to conditions such as obesity or dysglycemia. The presence of maternal gestational diabetes 36, low birth weight 37, infant feeding practices 38, early adiposity rebound 39, and genetic factors may all contribute to a child’s future level of risk. Being raised in an ‘obesogenic’ environment can also have a strong impact, as can the influence of socioeconomic factors 40, with weight gain often being observed as a positive correlate to affluence in developing countries. Longitudinal outcome studies and further research on the progression and etiology of the metabolic syndrome are urgently required to ascertain the long-term outcomes of abdominal obesity and clustering of the components of metabolic syndrome in at-risk children and to help improve future definitions of the syndrome. This new IDF definition of metabolic syndrome in children and adolescents was developed during a consensus workshop that brought together experts in the field of the metabolic syndrome and pediatrics. The purpose of the new definition of metabolic syndrome in children and adolescents is to expand on the IDF recommendations for managing type 2 diabetes in the young 1 and to provide a useful and unified tool for identifying those at risk. A clinically accessible diagnostic tool, avoiding measurements that may only be available in research settings, is needed to identify the metabolic syndrome in children and adolescents globally. This need has prompted the IDF to develop a definition that has used the limited data available from existing studies in youth. As with the adult criteria, we look on these new criteria as a starting point. As new information emerges, they can be modified. Inspired, in part, by the IDF worldwide definition of metabolic syndrome in adults 2, this new definition builds on previous studies investigating the prevalence of metabolic syndrome in children and adolescents, which have used modified adult criteria with varying cutoff points 12-14, 41, 42 (Table 1). The wide variety of cutoff points used has emphasized the need for a single consistent set of criteria, which is easily measurable and can be used as the basis for future work 29. Because of the developmental challenges presented by the age-related differences in children and adolescents, the new IDF definition of metabolic syndrome has been divided according to the following age groups: 6 to <10, 10 to <16, and ≥16 yr (Table 2). In all the three age groups, abdominal obesity is the ‘sine qua non’. We suggest that below the age of 10 yr, the metabolic syndrome as an entity is not diagnosed, although a strong message for weight reduction will be made for these children. At the age of 10 yr and more, a diagnosis of metabolic syndrome can be made. It requires the presence of abdominal obesity plus the presence of two or more of the other components (elevated triglycerides, low high-density lipoprotein (HDL)-cholesterol, high blood pressure, and elevated plasma glucose). The IDF adult criteria 2 can be used for adolescents aged ≥16 yr, while a modified version of these criteria will be applied to those aged 10 to <16 yr (use 90th percentile cutoff point for waist and <40 mg/dL of HDL for both sexes). On the basis of emerging new data, these criteria may change in the future. In adults, insulin resistance and abdominal obesity are considered to be significant causative factors in the development of the metabolic syndrome 9, 43, 44. The link between obesity, insulin resistance, and the risk of developing the metabolic syndrome has also been described in children 22, 27. With measurement of insulin resistance considered to be impractical for clinical use, abdominal adiposity was positioned as the ‘sine qua non’ in the IDF definition of metabolic syndrome in adults 2 and is recognized to be an independent risk factor for the development of cardiovascular disease in adults 45. Abdominal obesity can be easily assessed using the simple measure of WC, which is known to correlate more strongly with visceral adipose tissue (VAT) than BMI in adults 46 and is a strong predictor of cardiovascular disease risk factors in children 47. The correlation between WC and VAT has also been more recently demonstrated in children 48, further strengthening the existing evidence that WC is an effective measure of abdominal obesity 49 in the youth population. In children and adolescents, a number of studies have demonstrated a similar link between childhood obesity and elevated cardiovascular risk in later life. The Bogalusa Heart study showed that childhood overweight is related to the development of adverse risk factors (BMI, lipids, insulin, diabetes mellitus, and blood pressure) in adulthood and is attributable to the strong persistence of weight status from childhood to adulthood 50. Of the overweight children in the Bogalusa Heart study (BMI ≥95th percentile), 77% remained obese in adulthood. Furthermore, the Muscatine study demonstrated that in young adults, excess weight was the earliest predictor of coronary artery calcification 51. The ATP III definition, applied to a cohort of individuals aged 12–19 yr (NHANES III), identified that 4% of those studied were found to have the metabolic syndrome, with 80% of those meeting the criteria of being overweight 13. Using a modified version of the ATP III definition, metabolic syndrome in adolescents has also been linked to high levels of C-reactive protein, a pro-inflammatory marker. Of the five components of metabolic syndrome, C-reactive protein was higher only among those with abdominal obesity 41. Waist circumference in children is an independent predictor of insulin resistance, lipid levels, and blood pressure 4, 52-54– all components of metabolic syndrome. Moreover, in obese youth with similar BMI, insulin sensitivity is lower in those with high VAT and high waist/hip ratio 53, 54. Furthermore, insulin sensitivity decreases and insulin levels increase with increasing WC percentiles 3. These data, combined with the unequivocal evidence of the dangers of abdominal obesity in adulthood, support the use of abdominal obesity as the ‘sine qua non’ for the diagnosis of metabolic syndrome in children and adolescents. Percentiles rather than absolute values of WC have been used in the new criteria to compensate for varying degrees of development and ethnicity in the youth population. WC percentile data are becoming increasingly available worldwide 31, 55-58. Children with a WC >90th percentile are more likely to have multiple risk factors than those with a WC below this level 59. Several studies attempting to estimate the prevalence of metabolic syndrome in children and adolescents have already used the 90th percentile as a cutoff point for WC 13, 14, 41. We have also chosen to use the 90th percentile as a cutoff point for WC based on this existing evidence and aim to reassess criteria and cutoff points in 5 yr and modify the guidelines, if necessary, based on the new outcome data. Previous studies investigating the metabolic syndrome in children and adolescents have used a range of cutoff points primarily based on ATP III criteria for categorizing additional components of the syndrome, i.e., triglycerides, HDL-cholesterol, blood pressure, and fasting glucose (Table 1) 12-14, 41, 42. Other definitive sources include the National High Blood Pressure Education Program, which recommends blood pressure cutoff points of >90th or >95th percentile adjusted for height, age, and gender to identify ‘high normal’ blood pressure or prehypertension and high blood pressure or hypertension in children and adolescents 60. Cutoff points for impaired fasting glucose have previously followed recommendations by the American Diabetes Association (ADA) [100–125 mg/dL (≥5.6–6.9 mmol/L)] 61 and the NCEP/ATP III in adults [≥110 mg/dL (6.1 mmol/L)] 23, although the latter has recently changed to the lower ADA recommended levels 62. Criteria for defining lipid (triglyceride and HDL-cholesterol) imbalances are even less consistent in the youth population, with recommendations by the NCEP/ATP III (age specific), NHANES III (age and gender specific), and the National Growth and Health Study (age, gender, and ethnic specific), employing either absolute value or percentile cutoff points. In view of this lack of consistency, we believe that use of the adult levels for the present is wise until further information is available. We recommend the following topics as priorities for future research: Develop a better understanding of the relationship between body fat and its distribution in children and adolescents, e.g., dual energy X-ray absorptiometry (DEXA), WC, BMI, and height and weight percentiles; a) Explore whether early growth patterns predict future adiposity and features of the metabolic syndrome, diabetes, and cardiovascular disease and b) explore whether low birth weight predicts future metabolic syndrome, diabetes, and cardiovascular disease; Perform factor analysis in children and adolescents to establish grouping of metabolic characteristics – adiposity, dyslipidemia, hyperinsulinemia, hypoadiponectinemia, and insulin resistance; Investigate how should obesity in children could be better defined, e.g., weight/height, WC etc.; Develop ethnic-specific normal ranges for WC, ideally based on healthy values; Perform ethnic-specific studies of WC etc. vs. abdominal (truncal) fat based on magnetic resonance imaging and DEXA; Support studies of adiponectin, leptin, etc. in children and adolescents to determine if they may be predictors of metabolic syndrome in adulthood; Initiate long-term studies of multi-ethnic cohorts followed into adulthood to determine the natural history and effectiveness of intervention strategies, particularly lifestyle. In conclusion, to combat any conflict that could arise from these multiple interpretations of the metabolic syndrome in children and adolescents, the IDF consensus group has aimed primarily at developing a simple, easy-to-apply definition to begin using in the clinical setting. In the absence of definitive research findings at this time, the proposed IDF definition of the metabolic syndrome in children and adolescents (Table 2) adheres to the absolute values presented in the adult definition 2, with the exception of WC. As described previously, until such time that outcome data from studies in children and adolescents indicate otherwise, WC percentiles are recommended for use. Early detection, followed by treatment in the form of lifestyle intervention and possibly pharmacotherapy, if its safety has been clearly demonstrated, is vital in halting the progression of this syndrome pathway in the adolescent population. It is likely that this will reduce morbidity and mortality in adulthood, as well as minimize the global socioeconomic burden of cardiovascular disease and type 2 diabetes. The workshop was sponsored by an unrestricted educational grant to the IDF Task Force on Epidemiology and Prevention from sanofi-aventis.

In the last decade of the 20th century, cardiovascular disease was the leading cause of death in China, accounting for one-third of the total deaths. In comparison with western populations, the mean body weight or body mass index (BMI) of the Chinese population was lower, but showed an increasing trend. Whether the variation within lower levels of BMI or waist circumference was associated with other risk factors of cardiovascular disease, and whether they contribute independently to the risk of cardiovascular disease in the Chinese population, was investigated in this study. In keeping with a uniform study design, in each of 14 study populations at different geographical locations and with different characteristics, the incidence rates of stroke, coronary heart disease (CHD) and the causes of death were monitored in approximately/= 100000 residents from 1991 to 1995 using the MONICA procedure. Risk factors were surveyed in a random cluster sample of 1000 subjects (35-59 years of age) from each population under surveillance using internationally standardized methods and a centralized system to ensure quality control. Among the risk factors, body weight, height, and waist and hip circumferences were measured. Cross-sectional stratified analyses were used to analyse the relationship of BMI (kg m(-2)) or waist circumference to other metabolic risk factors. Ten cohorts among the 14 study populations with 24734 participants were surveyed from 1982 to 1985 as a baseline for further study and were followed-up for 9 years taking the events of stroke, CHD and different causes of death as end-points. Cox regression models were used to explore the association of BMI with the relative risks of stroke, CHD and total death. The survey in 14 random samples with a total number of 19 741 subjects showed that the mean BMI (20.8-25.1) and waist circumference (67.8-86.7 cm) were much lower than those of western populations. There was, however, variation in the anthropometric measurements among populations within China. Thus, rates of overweight varied from 2.7% to 48.1% and obesity from 0% to 9.5% on the basis of the World Health Organization (WHO) classification, but these values were lower than those found in western populations. Data from the 10 cohort samples compared with baseline data in the early 1980s showed that the mean BMIs increased significantly in eight populations during the early 1990s with the differences ranging from 0.5 to 2.5 kg m(-2). Despite the lower level of BMI and the lower rate of overweight, cross-sectional analyses showed that the prevalence of hypertension, high fasting serum glucose, high serum total cholesterol and low high-density lipoprotein cholesterol (HDL-C) and their clustering were all raised with increases in BMI or waist circumference. The prospective cohort study showed that the BMI was one of the independent risk factors for stroke and CHD in Chinese populations. Hence, in a Chinese population characterized by lower levels of BMI and great variability in rates of overweight, variation of BMI was significantly related to the prevalence of other metabolic risk factors and their clustering. Overweight was one of the independent risk factors for stroke and CHD, both at population and individual levels. Given the increasing trends of BMI in the last 10 years, during the period of economic transition there is a need to encourage the population to adopt healthy dietary habits and to increase their physical activity. Health education and health promotion are important for the prevention and non-pharmacological therapy of cardiovascular disease in China.

No abstract

HomeCirculationVol. 142, No. 1Obesity Is a Risk Factor for Severe COVID-19 Infection Free AccessArticle CommentaryPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessArticle CommentaryPDF/EPUBObesity Is a Risk Factor for Severe COVID-19 InfectionMultiple Potential Mechanisms Naveed Sattar, Iain B. McInnes and John J.V. McMurray Naveed SattarNaveed Sattar Naveed Sattar, MD, Institute of Cardiovascular and Medical Sciences, British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, 126 University Place, Glasgow G12 8TA, United Kingdom. Email E-mail Address: [email protected] https://orcid.org/0000-0002-1604-2593 Institute of Cardiovascular and Medical Sciences (N.S., J.J.V.M.), University of Glasgow, United Kingdom. , Iain B. McInnesIain B. McInnes Institute of Infection, Immunity and Inflammation (I.B.M.), University of Glasgow, United Kingdom. and John J.V. McMurrayJohn J.V. McMurray Institute of Cardiovascular and Medical Sciences (N.S., J.J.V.M.), University of Glasgow, United Kingdom. Originally published22 Apr 2020https://doi.org/10.1161/CIRCULATIONAHA.120.047659Circulation. 2020;142:4–6Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: April 22, 2020: Ahead of Print The coronavirus disease 2019 (COVID-19) pandemic has led to worldwide research efforts to identify people at greatest risk of developing critical illness and dying. Initial data pointed toward older individuals being particularly vulnerable, as well as those with diabetes mellitus or cardiovascular (including hypertension), respiratory, or kidney disease. These problems are often concentrated in certain racial groups (eg, African Americans and Asians), which also appear to be more prone to worse COVID-19 outcomes.1 Increasing numbers of reports have linked obesity to more severe COVID-19 illness and death.1–3 In a French study, the risk for invasive mechanical ventilation in patients with COVID-19 infection admitted to the intensive treatment unit was more than 7-fold higher for those with body mass index (BMI) >35 compared with BMI <25 kg/m2.2 Among individuals with COVID-19 who were <60 years of age in New York City, those with a BMI between 30 to 34 kg/m2 and >35 kg/m2 were 1.8 times and 3.6 times more likely to be admitted to critical care, respectively, than individuals with a BMI <30 kg/m2.3We suggest obesity or excess ectopic fat deposition may be a unifying risk factor for severe COVID-19 infection, reducing protective cardiorespiratory reserve as well as potentiating the immune dysregulation that appears, at least in part, to mediate the progression to critical illness and organ failure in a proportion of patients with COVID-19 (Figure). Whether obesity is an independent risk factor for susceptibility to infection requires further research.Download figureDownload PowerPointFigure. Pathways potentially linking obesity or excess ectopic fat to more severe coronavirus disease 2019 (COVID-19) illness. There are multiple pathways by which obesity (or excess ectopic fat) may increase the effect of COVID-19 infection. These include underlying impairments in cardiovascular, respiratory, metabolic, and thrombotic pathways in relation to obesity, all of which reduce reserve and ability to cope with COVID-19 infection and the secondary immune reaction to it. At the same time, there are several reasons why obese individuals may have amplified or dysregulated immune response, linked both to greater viral exposure, as well as the possibility that excess adipose tissue potentiates the immune response. BP indicates blood pressure; COVID-19, coronavirus disease 2019; CV, cardiovascular; FEV1, forced expiratory volume; FVC, forced vital capacity; and SES, socioeconomic status.From a cardiovascular perspective, trial and genetic evidence conclusively show that obesity (and excess fat mass) are causally related to hypertension, diabetes mellitus, coronary heart disease, stroke, atrial fibrillation, renal disease, and heart failure. Obesity potentiates multiple cardiovascular risk factors, the premature development of cardiovascular disease, and adverse cardiorenal outcomes. There is also a metabolic concern. In individuals with diabetes mellitus, or at high risk of diabetes mellitus, obesity and excess ectopic fat lead to impairment of insulin resistance and reduced β-cell function. Both the latter limit ability to evoke an appropriate metabolic response on immunologic challenge, leading some patients with diabetes mellitus to require substantial amounts of insulin during severe infections. Overall, the integrated regulation of metabolism required for the complex cellular interactions, and for effective host defense, is lost, leading to functional immunologic deficit. COVID-19 may also directly disrupt pancreatic β-cell function through an interaction with angiotensin-converting enzyme 2. Furthermore, obesity enhances thrombosis, which is relevant given the association between severe COVID-19 and prothrombotic disseminated intravascular coagulation and high rates of venous thromboembolism.Beyond cardiometabolic and thrombotic consequences, obesity has detrimental effects on lung function, diminishing forced expiratory volume and forced vital capacity (Figure). Higher relative fat mass is also linked to such adverse changes, perhaps relevant to emerging reports of greater critical illness from COVID-19 in certain ethnicities, eg, Asians.1 Asians often display lower cardiorespiratory fitness and carry proportionally more fat tissue at lower BMIs. With extreme obesity (eg, BMI >40 kg/m2), care for individuals admitted to intensive therapy units is often impeded as these patients are more difficult to image, ventilate, nurse, and rehabilitate.With respect to the immune response, there is a clear association between obesity and basal inflammatory status characterized by higher circulating interleukin 6 and C-reactive protein levels. Adipose tissue in obesity is "proinflammatory," with increased expression of cytokines and particularly adipokines. There is also dysregulated tissue leukocyte expression, and inflammatory macrophage (and innate lymphoid) subsets replace tissue regulatory (M2) phenotypic cells. Obesity per se is an independent and causal risk factor for the development of immune-mediated disease, eg, psoriasis,4 suggesting that such adipose state may have systemic immune consequence on additional environmental provocation. In terms of host defense, obesity impairs adaptive immune responses to influenza virus5 and conceivably could do so in COVID-19. Obese individuals may exhibit greater viral shedding, suggesting potential for great viral exposure, especially if several family members are overweight. This may be aggravated in overcrowded multigenerational households, which are more common in the socioeconomically deprived communities in which obesity is prevalent. All these observations point toward a potential for obesity to give rise to a more adverse virus versus host immune response relationship in COVID-19. Poorer nutritional status and hyperglycemia may further aggravate the situation in some obese individuals.Much of the focus of COVID-19 has been on older people. However, it is important to remember that weight and muscle mass start to decline at advanced age but relative fat mass increases, particularly in those with comorbid diseases such as cardiovascular and respiratory conditions. Older age is also associated with more hypertension and diabetes mellitus because of stiffer vessels and impaired metabolic efficiency, respectively. People who are older (eg, >70 years of age), similar to younger obese individuals, have less cardiorespiratory reserve to cope with COVID-19 infection. Immune senescence is well recognized, as is the concept of inflammaging, and both may influence virus–host dynamics in the elderly and infection outcomes.What are the implications of these emerging observations for future research and public health messaging? With respect to research, predictive instruments for those most at risk of severe outcomes should consider BMI. Mechanistic understanding of the relationship between obesity and COVID-19 may suggest therapeutic interventions (eg, proven weight loss drugs, low-calorie diets) to potentially reduce the risk of developing severe COVID-19 illness. With respect to public health, it is important to communicate risks without causing anxiety. People worldwide should be encouraged to improve their lifestyle to lessen risk both in the current and subsequent waves of COVID-19. In addition to increasing activity levels, there should be improved messaging on better diet, focusing on simpler advice to help people adopt sustainable changes. This is particularly challenging with current stay-at-home rules limiting activity levels—the lockdown cost of weight gain. Even more worrying is that the resultant economic downturn may worsen obesity, especially in the most vulnerable individuals, a risk that governments need to address after the current pandemic. Indeed, this pandemic has highlighted that more—not less—must be done to tackle and prevent obesity in societies for the prevention of chronic disease and greater adverse reactions to viral pandemics.AcknowledgmentsThe authors thank Liz Coyle from the University of Glasgow for her excellent technical assistance in the preparation of this article.Sources of FundingThe work in this study is supported by the British Heart Foundation Center of Research Excellence Grant RE/18/6/34217.DisclosuresDr Sattar reports personal fees from Amgen, AstraZeneca, Eli Lilly, Novo Nordisk, Pfizer, and Sanofi and personal fees and research grants from Boehringer Ingelheim outside the submitted work. Drs McInnes and McMurray report no conflicts.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.https://www.ahajournals.org/journal/circNaveed Sattar, MD, Institute of Cardiovascular and Medical Sciences, British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, 126 University Place, Glasgow G12 8TA, United Kingdom. Email naveed.sattar@glasgow.ac.ukReferences1. Petrilli CM, Jones SA, Yang J, Rajagopalan H, O'Donnell LF, Chernyak Y, Tobin K, Cerfolio RJ, Francois F, Horwitz LI. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study.BMJ2020; 369:m1966. doi: 10.1136/bmj.m1966CrossrefMedlineGoogle Scholar2. Simonnet A, Chetboun M, Poissy J, Raverdy V, Noulette J, Duhamel A, Labreuche J, Mathieu D, Pattou F, Jourdain M, Lille Intensive Care COVID-19 and Obesity Study Group. High prevalence of obesity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation [published online April 9, 2020].Obesity (Silver Spring). doi: 10.1002/oby.22831. https://onlinelibrary.wiley.com/doi/10.1002/oby.22831Google Scholar3. Lighter J, Phillips M, Hochman S, Sterling S, Johnson D, Francois F, Stachel A. Obesity in patients younger than 60 years is a risk factor for COVID-19 hospital admission [published online April 9, 2020].Clin Infect Dis. 2020. doi:10.1093/cid/ciaa415. https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa415/5818333CrossrefGoogle Scholar4. Budu-Aggrey A, Brumpton B, Tyrrell J, Watkins S, Modalsli EH, Celis-Morales C, Ferguson LD, Vie GÅ, Palmer T, Fritsche LG, et al. Evidence of a causal relationship between body mass index and psoriasis: a mendelian randomization study.PLoS Med. 2019; 16:e1002739. doi: 10.1371/journal.pmed.1002739CrossrefMedlineGoogle Scholar5. Green WD, Beck MA. Obesity impairs the adaptive immune response to influenza virus.Ann Am Thorac Soc. 2017; 14(suppl 5):S406–S409. doi: 10.1513/AnnalsATS.201706-447AWCrossrefMedlineGoogle Scholar eLetters(0)eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetailsCited ByMartin S, Aday A, Almarzooq Z, Anderson C, Arora P, Avery C, Baker-Smith C, Barone Gibbs B, Beaton A, Boehme A, Commodore-Mensah Y, Currie M, Elkind M, Evenson K, Generoso G, Heard D, Hiremath S, Johansen M, Kalani R, Kazi D, Ko D, Liu J, Magnani J, Michos E, Mussolino M, Navaneethan S, Parikh N, Perman S, Poudel R, Rezk-Hanna M, Roth G, Shah N, St-Onge M, Thacker E, Tsao C, Urbut S, Van Spall H, Voeks J, Wang N, Wong N, Wong S, Yaffe K and Palaniappan L (2024) 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association, Circulation, 149:8, (e347-e913), Online publication date: 20-Feb-2024. da Costa Ribeiro Quintans I, Pandolfi V, Gaudencio do Rêgo T, Neto J, A.R. Ramos T and Adhikary D (2024) Genome Designing for Nutritional Quality in Amaranthus Compendium of Crop Genome Designing for Nutraceuticals, 10.1007/978-981-19-3627-2_56-2, (1-33), . Aktiz Bıçak E and Oğlak S (2023) Clinical characterisation and management outcome of obstetric patients following intensive care unit admission for COVID-19 pneumonia, Journal of Obstetrics and Gynaecology, 10.1080/01443615.2023.2218915, 43:2, Online publication date: 8-Dec-2023. Nganabashaka J, Niyibizi J, Umwali G, Rulisa S, M. Bavuma C, Byiringiro J, Ntawuyirushintege S, Niyomugabo P, Izerimana L, Tumusiime D and Keetile M (2023) The effects of COVID-19 mitigation measures on physical activity (PA) participation among adults in Rwanda: An online cross-sectional survey, PLOS ONE, 10.1371/journal.pone.0293231, 18:11, (e0293231) Moll-Bernardes R, Ferreira J, Sousa A, Tortelly M, Pimentel A, Figueiredo A, Schaustz E, Secco J, Sales A, Terzi F, Xavier de Brito A, Sarmento R, Noya-Rabelo M, Fortier S, Matos e Silva F, Vera N, Conde L, Cabral-Castro M, Albuquerque D, Rosado de-Castro P, Camargo G, Pinheiro M, Souza O, Bozza F, Luiz R and Medei E (2023) Impact of the immune profiles of hypertensive patients with and without obesity on COVID-19 severity, International Journal of Obesity, 10.1038/s41366-023-01407-0 Onyango T, Zhou F, Bredholt G, Brokstad K, Lartey S, Mohn K, Özgümüs T, Kittang B, Linchausen D, Shafiani S, Elyanow R, Blomberg B, Langeland N and Cox R (2023) SARS-CoV-2 specific immune responses in overweight and obese COVID-19 patients, Frontiers in Immunology, 10.3389/fimmu.2023.1287388, 14 Chenchula S, Sharma S, Tripathi M, Chavan M, Misra A and Rangari G (2023) Prevalence of overweight and obesity and their effect on COVID‐19 severity and hospitalization among younger than 50 years versus older than 50 years population: A systematic review and meta‐analysis, Obesity Reviews, 10.1111/obr.13616, 24:11, Online publication date: 1-Nov-2023. Boutari C, Kokkorakis M, Stefanakis K, Valenzuela-Vallejo L, Axarloglou E, Volčanšek Š, Chakhtoura M and Mantzoros C (2023) Recent research advances in metabolism, clinical and experimental, Metabolism, 10.1016/j.metabol.2023.155722, (155722), Online publication date: 1-Nov-2023. Woodward-Lopez G, Esaryk E, Rauzon S, Hewawitharana S, Thompson H, Cordon I and Whetstone L (2023) Associations between Changes in Food Acquisition Behaviors, Dietary Intake, and Bodyweight during the COVID-19 Pandemic among Low-Income Parents in California, Nutrients, 10.3390/nu15214618, 15:21, (4618) Zhang Y, Li J, Feng L, Luo Y, Pang W, Qiu K, Mao M, Song Y, Cheng D, Rao Y, Wang X, Hu Y, Ying Z, Pu X, Lin S, Huang S, Liu G, Zhang W, Xu W, Zhao Y and Ren J (2023) A Population-Based Outcome-Wide Association Study of the Comorbidities and Sequelae Following COVID-19 Infection, Journal of Epidemiology and Global Health, 10.1007/s44197-023-00161-w Jeong S, Yun S, Park S and Mun S (2023) Understanding cross-data dynamics of individual and social/environmental factors through a public health lens: explainable machine learning approaches, Frontiers in Public Health, 10.3389/fpubh.2023.1257861, 11 Cosentino F, Verma S, Ambery P, Treppendahl M, van Eickels M, Anker S, Cecchini M, Fioretto P, Groop P, Hess D, Khunti K, Lam C, Richard-Lordereau I, Lund L, McGreavy P, Newsome P, Sattar N, Solomon S, Weidinger F, Zannad F and Zeiher A (2023) Cardiometabolic risk management: insights from a European Society of Cardiology Cardiovascular Round Table, European Heart Journal, 10.1093/eurheartj/ehad445, 44:39, (4141-4156), Online publication date: 14-Oct-2023. ATUK KAHRAMAN T and YILMAZ M (2023) Comparison of The Nutritional Habits of Individuals With and Without a COVID-19 Diagnosis: An Online Cross-Sectional Study From TürkiyeCOVID-19 Tanısı Alan ve Almayan Bireylerin Beslenme Alışkanlıklarının Karşılaştırılması: Türkiye'den Çevrimiçi Kesitsel Bir Çalışma, İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi, 10.61399/ikcusbfd.1244702, 8:3, (1009-1017) Sprockel Díaz J, Coral Zuñiga V, Angarita Gonzalez E, Tabares Rodríguez S, Carrillo Ayerbe M, Acuña Cortes I, Montoya Rumpf R, Martínez Arias L, Parra J and Diaztagle Fernández J (2023) Obesity and the obesity paradox in patients with severe COVID-19, Medicina Intensiva (English Edition), 10.1016/j.medine.2023.03.009, 47:10, Online publication date: Sprockel Díaz J, Coral Zuñiga V, Angarita Gonzalez E, Tabares Rodríguez S, Carrillo Ayerbe M, Acuña Cortes I, Montoya Rumpf R, Martínez Arias L, Parra J and Diaztagle Fernández J (2023) Obesity and the obesity paradox in patients with severe COVID-19, Medicina 47:10, Online publication date: T, C and S (2023) The COVID-19, Cardiovascular and a Online publication date: B, K, C, Lin W, Y, T, Lin M and (2023) in the of COVID-19, International Journal of Sciences, van J, J, S, L, van M, M, S, R, van A, A, M, Y, A and (2023) of with SARS-CoV-2 after of H, M, H, M, A, M, M, M, S, W, A, M, I, M, M and (2023) as a Factor in A Infection and E, R, S and related to an Journal of Online publication date: de M, C, D, Silva C, J, T, F, M, I, D, J, T, E, da L, R, F and (2023) The T regulatory with infection and outcome in COVID-19 patients mechanical Scientific A, P, E, G and K (2023) the Risk for Clinical in with A A, M, T, J, S, J, S, Li G, J, N, J, R, G and S (2023) of COVID-19 on Care Online publication date: L, Z, T, A, M, D, M, D and A (2023) as a of COVID-19 of the prospective study, Online publication date: T, K, S, K, H, K, N and J (2023) Impact of body on after infection, PLOS ONE, K, A, T, T, K, M, T, A, and J (2023) Association between obesity and in COVID-19 patients requiring invasive mechanical a study, Scientific M, S, S, A, M, R, and S (2023) Association of body mass index with COVID-19 outcome in a hospital in de Online publication date: P, A, R, R and A Impact of pandemic on development and in and International Journal of Online publication date: C, Y, R, M, R and S status of in a COVID-19 and R (2023) Obesity and of Online publication date: W, E, L, D, M, K, J, J, Figueiredo J, J, A, S, A and M (2023) and Risk of Disease The American Journal of Online publication date: A, V, I, Y, A and A (2023) and immune response coronavirus infection on the of obesity and Obesity and metabolism, A, F, N, A, S, R, M and N (2023) C and inflammatory factors related to COVID-19 consequences, K, O, J, A and (2023) SARS-CoV-2 Infection to and in N, G, H, C, E, G, J, and T (2023) inflammatory syndrome in cohort study of risk factors, S, S and T (2023) The associated with lifestyle risk factors and nutritional status for COVID-19 patients in the Journal of Public in V, N, N, I, M, I, V, T, M, M, A, D and M (2023) and as of in COVID-19 Ko Y, Z, R and S (2023) Association among and Risk Factors with SARS-CoV-2 Infection, and Online publication date: B, T, S and L of a complex to reduce metabolic syndrome in with Online publication date: Y, N, Yang J, C, Zhang A, B, E and C A in the of Online publication date: I, O, I, M, A, R and (2023) is the of adipose tissue in metabolic and future in the Online publication date: G, F, A, R, M, F, Johansen M, F, G, G, N, P, T, I, A, P, G, C and S (2023) and of COVID-19 associated therapeutic Journal of Li C, J, Huang J and (2023) the coronavirus disease New and New Online publication date: A, S, B, Z, A and C (2023) COVID-19 Medical Tsao C, Aday A, Almarzooq Z, Anderson C, Arora P, Avery C, Baker-Smith C, Beaton A, Boehme A, A, Commodore-Mensah Y, Elkind M, Evenson K, C, S, Generoso G, Heard D, Hiremath S, J, Kalani R, Kazi D, Ko D, D, Liu J, J, Magnani J, Michos E, Mussolino M, Navaneethan S, Parikh N, Poudel R, Rezk-Hanna M, Roth G, Shah N, St-Onge M, Thacker E, S, Voeks J, Wang N, Wong N, Wong S, Yaffe K and S (2023) Heart Disease and Stroke A Report From the American Heart Association, Circulation, Online publication date: R, S, A and D of obesity among from and lifestyle perspective, British Food Journal, Online publication date: M, X, H, and J (2023) The of obesity and thrombotic and Frontiers in Cardiovascular A, A, A, S, I, E, N, N, A, H, A, A, R, R, A, M, A, M, M, E, S, S and S (2023) The Impact of and Obesity on the of and Obesity, G, J, A, V, P, K, C, A, F, D, F, M and I (2023) SARS-CoV-2 infection adipose tissue in D, H, M, and M in older the of of the Online publication date: D, B, E, X, M, J, and J (2023) of COVID-19 infection in people with diabetes mellitus or obesity in the care in A cohort study of the Care Online publication date: S, M, M, M, Z, A, A and K (2023) The of and A A, F, A, M, G, X, E, S and G (2023) of D for and H, T, Y, T, M, M, S, K and M (2023) Clinical and the risk of hospitalization of patients with coronavirus disease 2019 in a

This study was undertaken to review the links between maternal nutrition, offspring's birth weight and the propensity to early insulin resistance and high diabetes rates in Indian adults. Studies included a comparison of maternal size and nutrition with birth weights in Pune, India, and Southampton, UK. In Pune, the growth, insulin resistance and blood pressure of four-year-old children were assessed. Adults >40 years of age, who were resident in rural areas, were compared with adults living in urban areas for size, glucose handling, lipid status and blood pressure. Newly diagnosed diabetic adults living in urban areas were also monitored. Height, weight, head, waist and hip circumferences, skin-fold measurements and blood pressure were routinely measured. Fasting glucose, insulin, total and high-density lipoprotein cholesterol and triglycerides were linked to the glucose and insulin responses during glucose tolerance tests. Cytokine levels were measured in plasma samples of urban and rural adults. Indian babies were lighter, thinner, shorter and had a relatively lower lean tissue mass than the Caucasian babies. However, the subcutaneous fat measurements of these babies were comparable to those of the white Caucasian babies. The Indian mothers were small, but relatively fat mothers produced larger babies. Maternal intake of green vegetables, fruit and milk, and their circulating folate and vitamin C levels, predicted larger fetal size. Rapid childhood growth promoted insulin resistance and higher blood pressure. Rural adults were thin, with a 4% prevalence of diabetes and a 14% prevalence of hypertension, but the risks increased within the normal body mass index (BMI) range. Type 2 diabetes was common in urban adults younger than 35 years of age. Although the average BMI was 23.9 kg m(-2), central obesity and thin limbs were noteworthy. Levels of interleukin-6 and tumour necrosis factor-a were markedly increased in urban dwellers. Hence, there is evidence of a remarkably powerful, intergenerational effect on body size and total and central adiposity. Indians are highly susceptible to insulin resistance and cardiovascular risks, with babies being born small but relatively fat. Insulin resistance is amplified by rapid childhood growth. Dietary factors seem to have profound long-term metabolic influences in pregnancy. Overcrowding with infections and central obesity may amplify cytokine-induced insulin resistance and early diabetes in Indian adults with a low BMI.

The aim of this study is to test the hypotheses that: 1) diagnosing the metabolic syndrome does not effectively identify insulin-resistant (IR) individuals; and 2) waist circumference (WC) is no better than body mass index (BMI) in predicting insulin resistance or the components of the metabolic syndrome (MetS). Measurements of BMI, WC, blood pressure, and fasting plasma glucose, insulin (FPI), triglycerides (TG), and HDL-cholesterol (HDL-C) concentrations were made in 1,300 adults, without known cardiovascular disease (CVD) or drug treatment of hypertension or diabetes. Receiver operating characteristic curves were used to determine the ability of the MetS, and its components, to identify IR individuals. In addition, comparisons were made of CVD risk factors following division of the population into quartiles of FPI concentrations, and univariate and multiple regression analysis used to compare the ability of WC, BMI, and FPI as predictors of MetS components. The MetS was no more effective in identifying IR individuals than several individual components (sensitivity~40%), and IR individuals not identified were at significantly increased CVD risk. FPI concentration was the best predictor of an abnormal glucose, TG, and HDL-C, whereas the adiposity indices were better predictors of abnormal blood pressure. The relationship between BMI and WC with the MetS and its components seemed comparable.

No abstract

The rapid increase in the prevalence and disease burden of elevated BMI highlights the need for continued focus on surveillance of BMI and identification, implementation, and evaluation of evidence-based interventions to address this problem. (Funded by the Bill and Melinda Gates Foundation.).

Gestational diabetes mellitus (GDM) is a strong predictor of glucose intolerance later in life. Former GDM (n = 145) and control (n = 41) subjects were studied 3-4 yr after the index pregnancy. They were subjected to a 75-g oral glucose tolerance test (OGTT) with measurements of insulin, C-peptide, and proinsulin in the basal state and every 30 min for 180 min. In the former GDM group, 5 subjects (3.4%) had developed non-insulin-dependent diabetes mellitus (NIDDM), and 32 (22%) had developed impaired glucose tolerance (IGT; by World Health Organization criteria). In the control group, 2 (4%) had IGT. In the GDM group, IGT or NIDDM was significantly associated with obesity (body mass index [BMI] greater than or equal to 25 kg/m2) and earlier diagnosis of GDM during pregnancy (P less than 0.001). Nonobese (BMI less than 25 kg/m2) GDM subjects with normal glucose tolerance at follow-up had significantly higher mean glucose (P less than 0.01), insulin (P less than 0.05), and proinsulin (P less than 0.001) values during the OGTT than control subjects, whereas there was no significant difference in C-peptide values. A comparison between control subjects with normal OGTT and BMI less than 25 kg/m2 (n = 39) and GDM subjects (n = 39) selected to have a comparable area under the glucose curve, BMI, and age demonstrated no group differences in glucose, C-peptide, or insulin levels, whereas the proinsulin levels were significantly higher (P less than 0.001) during the glucose load. The molar ratio between proinsulin and insulin was also significantly higher among the former GDM subjects.(ABSTRACT TRUNCATED AT 250 WORDS)

No abstract

No abstract

The triglyceride glucose-body mass index (TyG-BMI) has been considered an alternative marker of insulin resistance (IR). This cross-sectional study was designed to mainly investigate the association between TyG-BMI, triglyceride glucose combined with body mass index, and hypertension in Chinese adults. The relationship between TyG-BMI and hypertension was examined by multivariate logistic regression and restricted cubic spline model. Multiple logistic regression models were also performed to examine the associations between the individual components of TyG-BMI (BMI, TyG index, TG and FBG) and hypertension. The incremental ability of TyG-BMI versus its individual components for hypertension discrimination was evaluated by C-statistic and net reclassification index. Subgroup analysis was performed to examine potential interactions. A total of 92,545 participants (38.9% men, mean age 53.7 years) were included for final analysis. Logistic regression models showed TyG-BMI and its individual components were all significantly associated with the odds of hypertension (p for trend < .001). The restricted cubic spline regression manifested a linear association between TyG-BMI and hypertension (p for non-linear = .062). The addition of TyG-BMI, in comparison with each individual component, exhibited the maximum incremental value for the discrimination of hypertension on the basis of base model (C-statistic: 0.679, 95% CI: 0.675-0.683 for base model vs. 0.695, 95% CI: 0.691-0.699 for base model + TyG-BMI; net reclassification index: 0.226, 95% CI: 0.215-0.234). TyG-BMI was significantly associated with the odds of hypertension and can be a better discriminator of hypertension.

One hundred and fifty infertile polycystic ovary syndrome (PCOS) women were classified into four phenotypes on the basis of Rotterdam criteria. Homeostatic model assessment of insulin resistance (HOMA-IR) with a cutoff ≥2.5 was considered as a measure of insulin resistance (IR). Maximum number of patients, 57 (38%) in our cohort belonged to phenotype A or the classical phenotype with all 3 features of Rotterdam criteria. Mean body mass index (BMI) in all phenotypes was more than 25 kg/m² and the highest was seen in phenotype B. According to BMI categories in the four phenotypes, more number of women was in the obese category in phenotype A (24.5%) and B (56.5%) in comparison to phenotype C (18.2%) and D (10.8%) (<i>p</i><.001). There was no difference in median HOMA-IR among different phenotype categories (<i>p</i>=.718). The median value of anti-mullerian hormone (AMH) was highest in phenotype A (11.68 ng/ml [7.94-16.46]) and significantly more in comparison to B phenotype (Kruskal-Wallis, <i>p</i>=.018). Thus there is heterogeneity in AMH levels and BMI in different PCOS phenotypes with higher levels in the most severe phenotypes. There is, however, no correlation of IR among the different phenotype groups and further investigation is needed to characterize its role in phenotypic classification.

No abstract

Insulin resistance (IR) in the context of highly active antiretroviral therapy (HAART) is becoming more common in HIV-infected patients. Patients with chronic hepatitis C virus (HCV) infection have an increased risk of IR and type 2 diabetes mellitus. A cross-sectional study was performed to investigate whether chronic HCV infection constitutes a risk factor for IR in HIV-HCV-coinfected patients undergoing HAART. Inclusion criteria were positive HCV viremia and a sustained increase of alanine aminotransferase of at least twice the normal value. A total of 29 HIV-HCV patients, 76 HIV patients, and 121 HCV controls were tested for IR and body mass index (BMI). IR was measured using the homeostasis model assessment. In HIV-HCV and HIV patients, fat redistribution and lipid profile were assessed. There was no significant difference in age, CD4 cell count, HIV viral load, or duration of HAART between the HIV-HCV and HIV groups. HIV-HCV patients and HCV controls had a significant increase in IR when compared with HIV patients (0.25 +/- 0.28 and 0.21 +/- 0.34 versus 0.04 +/- 0.37; p =.01 and p =.003, respectively). Lipoatrophy was observed more frequently in HIV-HCV patients in comparison with HIV patients (41% versus 14%; p =.003). In HIV-HCV patients, total cholesterol and triglyceride levels were significantly lower than in HIV patients. In multivariate analysis, IR, BMI, triglyceride levels, and peripheral fat wasting were the independent variables associated with HCV infection. Our findings suggest that chronic HCV infection is a significant factor associated with the development of metabolic abnormalities and with modifications in body composition in HIV patients receiving antiretroviral treatment.

Maternal dietary patterns before and during pregnancy play important roles in the development of gestational diabetes mellitus (GDM). We aimed to identify dietary patterns during pregnancy that are associated with GDM risk in pregnant U.S. women. From a 24 h dietary recall of 253 pregnant women (16-41 years) included in the National Health and Nutrition Examination Survey (NHANES) 2003-2012, food items were aggregated into 28 food groups based on Food Patterns Equivalents Database. Three dietary patterns were identified by reduced rank regression with responses including prepregnancy body mass index (BMI), dietary fiber, and ratio of poly- and monounsaturated fatty acids to saturated fatty acid: "high refined grains, fats, oils and fruit juice", "high nuts, seeds, fat and soybean; low milk and cheese", and "high added sugar and organ meats; low fruits, vegetables and seafood". GDM was diagnosed using fasting plasma glucose levels ≥5.1 mmol/L for gestation <24 weeks. Multivariable logistic regression models were used to estimate adjusted odds ratio (AOR) and 95% confidence intervals (CIs) for GDM, after controlling for maternal age, race/ethnicity, education, family poverty income ratio, marital status, prepregnancy BMI, gestational weight gain, energy intake, physical activity, and log-transformed C-reactive protein (CRP). All statistical analyses accounted for the appropriate survey design and sample weights of the NHANES. Of 249 pregnant women, 34 pregnant women (14%) had GDM. Multivariable AOR (95% CIs) of GDM for comparisons between the highest vs. lowest tertiles were 4.9 (1.4-17.0) for "high refined grains, fats, oils and fruit juice" pattern, 7.5 (1.8-32.3) for "high nuts, seeds, fat and soybean; low milk and cheese" pattern, and 22.3 (3.9-127.4) for "high added sugar and organ meats; low fruits, vegetables and seafood" pattern after controlling for maternal sociodemographic variables, prepregnancy BMI, gestational weight gain, energy intake and log-transformed CRP. These findings suggest that dietary patterns during pregnancy are associated with risk of GDM after controlling for potential confounders. The observed connection between a high consumption of refined grains, fat, added sugars and low intake of fruits and vegetables during pregnancy with higher odds for GDM, are consistent with general health benefits of healthy diets, but warrants further research to understand underlying pathophysiology of GDM associated with dietary behaviors during pregnancy.

RFM provides high predictability for dyslipidemias and metabolic syndrome.

There is currently substantial confusion between the conceptual definition of the metabolic syndrome and the clinical screening parameters and cut-off values proposed by various organizations (NCEP-ATP III, IDF, WHO, etc) to identify individuals with the metabolic syndrome. Although it is clear that in vivo insulin resistance is a key abnormality associated with an atherogenic, prothrombotic, and inflammatory profile which has been named by some the "metabolic syndrome" or by others "syndrome X" or "insulin resistance syndrome", it is more and more recognized that the most prevalent form of this constellation of metabolic abnormalities linked to insulin resistance is found in patients with abdominal obesity, especially with an excess of intra-abdominal or visceral adipose tissue. We have previously proposed that visceral obesity may represent a clinical intermediate phenotype reflecting the relative inability of subcutaneous adipose tissue to act as a protective metabolic sink for the clearance and storage of the extra energy derived from dietary triglycerides, leading to ectopic fat deposition in visceral adipose depots, skeletal muscle, liver, heart, etc. Thus, visceral obesity may partly be a marker of a dysmetabolic state and partly a cause of the metabolic syndrome. Although waist circumference is a better marker of abdominal fat accumulation than the body mass index, an elevated waistline alone is not sufficient to diagnose visceral obesity and we have proposed that an elevated fasting triglyceride concentration could represent, when waist circumference is increased, a simple clinical marker of excess visceral/ectopic fat. Finally, a clinical diagnosis of visceral obesity, insulin resistance, or of the metabolic syndrome is not sufficient to assess global risk of cardiovascular disease. To achieve this goal, physicians should first pay attention to the classical risk factors while also considering the additional risk resulting from the presence of abdominal obesity and the metabolic syndrome, such global risk being defined as cardiometabolic risk.

No abstract

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in the world. Presentation of the disease ranges from simple steatosis to non-alcoholic steatohepatitis (NASH). NAFLD is a hepatic manifestation of metabolic syndrome that includes central abdominal obesity along with other components. Up to 80% of patients with NAFLD are obese, defined as a body mass index (BMI) > 30 kg/m(2). However, the distribution of fat tissue plays a greater role in insulin resistance than the BMI. The large amount of visceral adipose tissue (VAT) in morbidly obese (BMI > 40 kg/m(2)) individuals contributes to a high prevalence of NAFLD. Free fatty acids derived from VAT tissue, as well as from dietary sources and de novo lipogenesis, are released to the portal venous system. Excess free fatty acids and chronic low-grade inflammation from VAT are considered to be two of the most important factors contributing to liver injury progression in NAFLD. In addition, secretion of adipokines from VAT as well as lipid accumulation in the liver further promotes inflammation through nuclear factor kappa B signaling pathways, which are also activated by free fatty acids, and contribute to insulin resistance. Most NAFLD patients are asymptomatic on clinical presentation, even though some may present with fatigue, dyspepsia, dull pain in the liver and hepatosplenomegaly. Treatment for NAFLD and NASH involves weight reduction through lifestyle modifications, anti-obesity medication and bariatric surgery. This article reviews the available information on the biochemical and metabolic phenotypes associated with obesity and fatty liver disease. The relative contribution of visceral and liver fat to insulin resistance is discussed, and recommendations for clinical evaluation of affected individuals is provided.

Article1 July 1967The Relation of Adiposity to Blood Pressure and Development of HypertensionThe Framingham StudyWILLIAM B. KANNEL, M.D., F.A.C.P., NAPHTALI BRAND, M.D., JOHN J. SKINNER JR., M.D., THOMAS R. DAWBER, M.D., F.A.C.P., PATRICIA M. MCNAMARA, A.B.WILLIAM B. KANNEL, M.D., F.A.C.P.Search for more papers by this author, NAPHTALI BRAND, M.D.Search for more papers by this author, JOHN J. SKINNER JR., M.D.Search for more papers by this author, THOMAS R. DAWBER, M.D., F.A.C.P.Search for more papers by this author, PATRICIA M. MCNAMARA, A.B.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-67-1-48 SectionsAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail ExcerptThe existence of a relationship between hypertension and excess body weight has long been recognized (1, 2). This relationship has been demonstrated largely in cross-sectional studies observing the relation between the blood pressure level and the body weight measured at that time. Very little prospective data exist, particularly in general population samples concerning the relation between antecedent body weight and the subsequent development of hypertension. Whether it is adiposity per se or some other associated factor that is primarily responsible for the elevated blood pressure observed in the obese has not been established. The obesity-blood pressure relationship has been further...References1. PICKERING GW: High Blood Pressure. Churchill, London, 1955. Google Scholar2. SMIRK FH: High Arterial Pressure. Blackwell Scientific Publications, Oxford, 1957. Google Scholar3. DAWBERMOOREMANN TRFEGV: Coronary heart disease in Framingham Study. Amer. J. Public Health 47: 4, 1957. CrossrefGoogle Scholar4. DAWBERKANNEL TRWB: An epidemiological study of heart disease: Framingham Study. Nutr. Rev. 16: 1, 1958. CrossrefMedlineGoogle Scholar5. KAGANGORDONKANNELDAWBER ATWBTR: Blood pressure and its relation to coronary heart disease in Framingham Study. Proc. Council High Blood Pressure Res. 7: 53, 1959. Google Scholar6. KANNELDAWBERKAGANREVOTSKIESTOKES WBTRANJ: Factors of risk in the development of coronary heart disease—six year follow-up experience. The Framingham study. Ann. Intern. Med. 55: 33, 1961. LinkGoogle Scholar7. PERERA GA: Primary hypertension. Circulation 13: 321, 1956. CrossrefMedlineGoogle Scholar8. TROUTBERTRANDWILLIAMS KWCAMH: Measurement of blood pressure in obese persons. JAMA 162: 970, 1956. CrossrefMedlineGoogle Scholar9. RAGANBORDLEY GJ: The accuracy of clinical measurements of arterial blood pressure. Bull. Hopkins Hosp. 69: 504, 1941. Google Scholar10. BERLINERFUJIYLEEYILDIZGARNIER KHDHMB: Blood pressure measurements in obese persons. Comparison of intra-arterial and auscultatory measurements. Amer. J. Cardiol. 8: 10, 1961. CrossrefGoogle Scholar11. BERLINERFUJIYHO LEEYILDIZGARNIER KHDMB: The accuracy of blood pressure determinations: a comparison of direct and indirect measurements. Cardiologia 37: 118, 1960. CrossrefGoogle Scholar12. BORDLEYCONNORHAMILTONKEERWIGGERS JCAWFWJCJ: Recommendation for human blood pressure determinations by sphygmomanometers. Circulation 4: 503, 1951. CrossrefMedlineGoogle Scholar13. STEELE JM: Comparison of simultaneous indirect and direct measurements of arterial pressure in man. J. Mount Sinai Hosp. N. Y. 8: 1042, 1942. Google Scholar14. ROBERTSSMILEYMANNING LNJRGW: A comparison for direct and indirect blood pressure determinations. Circulation 8: 232, 1953. CrossrefMedlineGoogle Scholar15. DAMONGOLDMAN ARF: Predicting fat from body measurements: densitometric validation of ten anthropometric equations. Hum. Biol. 36: 32, 1964. MedlineGoogle Scholar16. PICKERINGROBERTSSOWRY GWJAGS: The effect of correcting for arm circumference on the growth rate of arterial pressure with age. Clin. Sci. 13: 267, 1954. MedlineGoogle Scholar17. THOMSONDOUPE AEJ: Cause of error in auscultatory blood pressure measurements. Rev. Canad. Biol. 8: 337, 1949. Google Scholar18. WHYTE HM: Blood pressure and obesity. Circulation 19: 511, 1959. CrossrefMedlineGoogle Scholar19. EPSTEINSIMPSONBOAS FHREP: The epidemiology of atherosclerosis among random sample of clothing workers of different ethnic origin in New York City. II. Association between manifest atherosclerosis, serum lipid levels, blood pressure, overweight, and some other variables. J. Chronic Dis. 5: 329, 1957. CrossrefMedlineGoogle Scholar20. ROBINSONBRUCERMASS SCMJ: Hypertension and obesity. J. Lab. Clin. Med. 25: 807, 1940. Google Scholar21. THOMASCOHEN CBBH: The familial occurrence of hypertension and coronary artery disease, with observations concerning obesity and diabetes. Ann. Intern. Med. 42: 90, 1955. LinkGoogle Scholar22. BJERKEDAL T: Overweight and hypertension. Acta Med. Scand. 159: 13, 1951. CrossrefGoogle Scholar23. LEVYWHITESTROUDHILLMAN RLPDWDCC: Overweight: its prognostic significance in relation to hypertension and cardiovascular renal diseases. JAMA 131: 951, 1946. CrossrefMedlineGoogle Scholar24. FLETCHER AP: The effect of weight reduction upon the blood pressure of obese hypertensive women. Quart. J. Med. 23: 331, 1959. Google Scholar This content is PDF only. To continue reading please click on the PDF icon. Author, Article, and Disclosure InformationAuthors: WILLIAM B. KANNEL, M.D., F.A.C.P.; NAPHTALI BRAND, M.D.; JOHN J. SKINNERJR., M.D.; THOMAS R. DAWBER, M.D., F.A.C.P.; PATRICIA M. MCNAMARA, A.B.Affiliations: Framingham, Massachusetts, and Bethesda, MarylandFrom the Heart Disease Epidemiology Study, Framingham, Mass., and the National Heart Institute, National Institutes of Health, Bethesda, Md.Requests for reprints should be addressed to William B. Kannel, M.D., Medical Director, Heart Disease Epidemiology Study, 123 Lincoln St., Framingham, Mass. 01701. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics Cited byThe Mediating Effect of Central Obesity on the Association between Dietary Quality, Dietary Inflammation Level and Low-Grade Inflammation-Related Serum Inflammatory Markers in AdultsPrevalence of patients at risk for developing obstructive sleep apnea based on the STOP‐BANG questionnaire at King Abdulaziz University Faculty of DentistryComparative analysis of the association between traditional and lipid-related obesity indicators and isolated systolic hypertensionPre-pregnancy blood pressure and pregnancy outcomes: a nationwide population-based studyBody composition and anthropometric indicators as predictors of blood pressure: a cross-sectional study conducted in young Algerian adultsProtective role of vitamin D against radiation hazards in rats fed on high fat dietImpact of Obesity Severity on Achieving a Minimum Clinically Important Difference Following Minimally Invasive Transforaminal Lumbar Interbody FusionYoga and ObesityPerceptions of obesity pharmacotherapy by nurse practitionersMetabolic risk factors in patients with comorbidity in Ufa primary health careVascular Endothelial Glycocalyx Plays a Role in the Obesity Paradox According to Intravital ObservationWhole- and Refined-Grain Consumption and Longitudinal Changes in Cardiometabolic Risk Factors in the Framingham Offspring CohortEvaluation on Auto-segmentation of the Clinical Target Volume (CTV) for Graves' Ophthalmopathy (GO) with a Fully Convolutional Network (FCN) on CT ImagesResting Heart Rate as a Cardiovascular Risk Factor in Hypertensive Patients: An UpdateVascular Extracellular Matrix Remodeling and HypertensionSTRESS-THE SILENT KILLER OF SAVIORS?INTERDISCIPLINARY CLINICAL PRACTICE GUIDELINES "MANAGEMENT OF OBESITY AND ITS COMORBIDITIES"A modern view on the prevention and treatment of arterial hypertension in obesityStudy of Correlation of Hypertension and Anthropometric Measurements in Obese Vs Non – Obese IndividualsAssociation between cardiovascular risk factors and stage 1 hypertension defined by the 2017 ACC/AHA guidelinesThe “Weight” of Obesity on Arterial HypertensionMediation effect of BMI on the relationship between age at menarche and hypertension: The Henan Rural Cohort StudyMetabolites and Hypertension: Insights into Hypertension as a Metabolic DisorderPresión arterial central en la obesidad mórbida y tras la cirugía bariátricaCentral blood pressure in morbid obesity and after bariatric surgeryWeight gain and blood pressurePrimary HypertensionCellular and Molecular Mechanisms Contributing to Cardiac Hypertrophy in Obesity and Obesity-Related HypertensionThe NEW-HOPE study and emerging therapies for difficult-to-control and resistant hypertensionAnalysis of Dose-response Relationship between BMI and Hypertension in Northeastern China Using Restricted Cubic Spline FunctionsThe cardiovascular phenotype of adult patients with phenylketonuriaUric Acid and Potassium Serum Levels Are Independent Predictors of Blood Pressure Non-Dipping in Overweight or Obese SubjectsBlood pressure response to treatment of obese vs non‐obese adults with sleep apneaEfficacy and Safety of Firibastat, A First-in-Class Brain Aminopeptidase A Inhibitor, in Hypertensive Overweight Patients of Multiple Ethnic OriginsImpact of body mass index and waist circumference on blood pressure: A cross-sectional survey in a population living in the Vietnam northern mountainousThe renin–angiotensin system in the arcuate nucleus controls resting metabolic rateObesity-Hypertension Physiopathology and Treatment: A Forty-Year RetrospectAssociations of social and economic and pregnancy exposures with blood pressure in UK White British and Pakistani children age 4/5Obesity, Visceral Fat, and Hypertension-Related ComplicationsInteraction between angiotensin II and glucose sensing at the subfornical organEarly menarche and blood pressure in adulthood: systematic review and meta-analysisDialogue between primary and secondary health care providers in a Brazilian hypertensive populationDietary sodium intake and its relationship to adiposity in young black and white adults: The African-PREDICT studyA variante genética c825t da subunidade β3 da proteína G associa‐se com a hipertensão arterial numa população portuguesaThe genetic variant C825T of the beta 3 subunit of G protein is associated with hypertension in a Portuguese populationPharmacotherapeutic strategies for treating hypertension in patients with obesityAnti-Inflammatory Effects of Melatonin in Obesity and HypertensionAssociation of Body Fat Mass and Fat Distribution With the Incidence of Hypertension in a Population‐Based Chinese Cohort: A 22‐Year Follow‐UpApplication of Single-Nucleotide Polymorphism-Related Risk Estimates in Identification of Increased Genetic Susceptibility to Cardiovascular Diseases: A Literature ReviewOBSOLETE: Obesity and The Obesity Paradox in Heart FailureEndocrine HypertensionObesity and the Obesity Paradox in Heart FailureObesityObesity and Cardiovascular Disease PreventionCardiorespiratory Fitness and Blood Pressure: A Longitudinal AnalysisThe relationship between obesity and hypertension: an updated comprehensive overview on vicious twinsNeck circumference associated with arterial blood pressures and hypertension: A cross-sectional community-based study in northern Han ChinesePerioperative management of the obese surgical patientChallenges in Treatment of Obesity in the ElderlyThe Interaction of Cardiorespiratory Fitness With Obesity and the Obesity Paradox in Cardiovascular DiseaseCardiac telomere length in heart development, function, and diseaseEffect of gender and adiposity on in vivo vascular function in young African AmericansWeight loss and alterations in co-morbidities after revisional gastric bypass: A case-matched study from the Scandinavian Obesity Surgery RegistryRole of Perivascular Adipose Tissue in Vascular Physiology and PathologyObesityComparative assessment of some white blood cell and platelet parameters among normotensive and hypertensive subjects in Port Harcourt, NigeriaObesity and hypertensive heart disease: focus on body composition and sex differencesImpact of body fat changes in mediating the effects of antiretroviral therapy on blood pressure in HIV-infected persons in a sub-Saharan African settingThe Interactive Association of General Obesity and Central Obesity with Prevalent Hypertension in Rural Lanzhou, ChinaRegional Fat Distribution and Blood Pressure Level and VariabilityHigher serum uric acid level increases risk of prehypertension in subjects with normal glucose tolerance, but not pre-diabetes and diabetesAchieving Weight Loss and Hypertension Control Among Obese Adults: A US Multidisciplinary Group Practice Observational StudyDoes metformin reduce excess birthweight in offspring of obese pregnant women? A randomised controlled trial of efficacy, exploration of mechanisms and evaluation of other pregnancy complicationsElevated BP after AKIFollow-Up of the Hypertensive Patients with Cardiovascular DiseaseObesityThe toll of the gridiron: damage‐associated molecular patterns and hypertension in American footballCalcium intake and hypertension among obese adults in United States: associations and implications exploredSex, Adiposity, and Hypertension Status Modify the Inverse Effect of Marine Food Intake on Blood Pressure in Alaska Native (Yup’ik) PeopleCardiorenal Metabolic Syndrome and Diabetes in African Americans: Adding to the Risk of HypertensionGender Issues in Chronic Kidney DiseaseIndependent Influence of Overweight and Obesity on the Regression of Left Ventricular Hypertrophy in Hypertensive PatientsEvaluation of leptin and leptin receptor gene 3′ UTR polymorphisms in essential hypertensionNovel mechanisms of Na + retention in obesity: phosphorylation of NKCC2 and regulation of SPAK/OSR1 by AMPKThe pathophysiology of hypertension in patients with obesityIncreased Aldosterone: Mechanism of Hypertension in ObesityPhysiological changes induced by salt intake in female Spontaneously Diabetic Torii- Lepr fa (SDT fatty) rat, a novel obese type 2 diabetic modelCardiovascular risk in overweight/obese and lean hypertensive patientsCardiovascular risk in overweight/obese and lean hypertensive patientsInterplay of overweight and insulin resistance on hypertension developmentVascular damage in obese female rats with hypoestrogenismLaparoscopy in the Morbidly Obese: Physiologic Considerations and Surgical Techniques to Optimize SuccessMetabolic syndrome in children with chronic kidney disease and after renal transplantationVisceral Fat and Hypertension: Sex DifferencesIs the metabolic syndrome a useful clinical concept in dogs? A review of the evidenceClustering of the Metabolic Syndrome Components in Adolescence: Role of Visceral FatHeart Rate and the Cardiometabolic RiskThe confounding effect of cryptic relatedness for environmental risks of systolic blood pressure on cohort studiesEffects of living at two ambient temperatures on 24-h blood pressure and neuroendocrine function among obese and non-obese humans: a pilot studyImpact of obesity on cardiovascular healthA sympathetic view of human obesityObesity-related hypertension: Pathogenesis, cardiovascular risk, and treatment-A position paper of the The Obesity Society and the American Society of HypertensionPTP1B in Obesity-Related Cardiovascular FunctionObesity-Associated HypertensionHypertension in WomenObesity-Related Hypertension: Pathogenesis, Cardiovascular Risk, and TreatmentCardiac Remodeling in ObesityIncreasing Peripheral Insulin Sensitivity by Protein Tyrosine Phosphatase 1B Deletion Improves Control of Blood Pressure in ObesityClinical management of obesity in pregnancyA brain leptin-renin angiotensin system interaction in the regulation of sympathetic nerve activityPrevalence of Persistent Prehypertension in AdolescentsSex Differences in the Contributions of Visceral and Total Body Fat to Blood Pressure in AdolescenceEl sedentarismo es un factor predictor de hipertrigliceridemia, obesidad central y sobrepesoWeight Loss Is Still an Essential Intervention in Obesity and its Complications: A ReviewAntenatal physical activity: Investigating the effects on postpartum depressionThe effect of high-fat diet-induced obesity on cardiovascular toxicity in wistar albino ratsImpact of Leptin-Mediated Sympatho-Activation on Cardiovascular Function in Obese MiceObesity can break your heart and more so when you are a womanRevised guidelines for cardiovascular risk management — time to stop medication? A practice-based intervention studyNatriuretic peptide system: A link between fat mass and cardiac hypertrophy and hypertension in fat-fed female ratsChildhood Obesity and Blood Pressure RegulationObesitySodium and water handling after gastric bypass surgery in a rat modelPreoperative Evaluation of the Adult OutpatientThe Contribution of the Framingham Heart Study to the Prevention of Cardiovascular Disease: A Global PerspectiveHaemodynamical Variables Versus Endothelial Hormones in Hypertensive and Type 2 Diabetic Patients With Endothelial DysfunctionIron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseasesThe complex interaction between overweight, hypertension, and sympathetic overactivityBariatric surgery and hypertensionRelationship Between Blood Pressure and Anthropometry in a Cohort of Brazilian Men: A Cross-Sectional StudyProtein Tyrosine Phosphatase 1B, a Major Regulator of Leptin-Mediated Control of Cardiovascular FunctionAssociation between obesity indices and blood pressure or hypertension: which index is the best?Association between refractory hypertension and obstructive sleep apneaThe role of cardiac autonomic function in hypertension and cardiovascular diseaseObesity and Hypertension: Mechanisms, Cardio-Renal Consequences, and Therapeutic ApproachesHypertension artérielle chez les patients obèses : physiopathologie et prise en chargeThe role of obesity in the pathogenesis of hypertensionObesity and HypertensionWeight Loss Interventions to Control Blood Pressure in an Increasingly Overweight, Multi-ethnic SocietyPatologías asociadas a la obesidadPrehypertension and Cardiovascular Risk Factor Clustering Among Mongolian Population in Rural and Animal Husbandry Area, Inner Mongolia, ChinaIncreases in Weight and Body Size Increase the Odds for Hypertension During 7 Years of Follow-upDoes socioeconomic status affect blood pressure goal achievement?High-Circulating Leptin Levels Are Associated with Greater Risk of Hypertension in Men Independently of Body Mass and Insulin Resistance: Results of an Eight-Year Follow-Up StudyThe Relationship of Body Mass Index and Waist-Hip Ratio on the 9-Year Incidence of Diabetes and Hypertension in a Predominantly African-origin PopulationVisceral Fat and Prevalence of Hypertension Among African Americans and Hispanic Americans: Findings From the IRAS Family StudyTreatment Resistant HypertensionDifferent BMI cardiovascular risk thresholds as markers of organ damage and metabolic syndrome in primary hypertensionImprovement in comorbid illness after placement of the Swedish Adjustable Gastric BandThe treatment of hypertension in obese patientsNationwide survey of prevalence and risk factors of prehypertension and hypertension in Iranian adultsThe Sympatho-Adrenal System in the Metabolic SyndromeSíndrome metabólico en pacientes en hemodiálisisSíndrome metabólico en pacientes en hemodiálisisThe ‐2548G/A LEP polymorphism is associated with blood pressure in Tunisian obese patientsCauses and Mechanisms of Nondipping HypertensionPrognostic impact of body mass index and effect of overweight and obesity on surgical and adjuvant treatment in early-stage epithelial ovarian cancerIncidence of Hypertension in Individuals with Abdominal Obesity in a Rural Japanese Population: The Tanno and Sobetsu StudyThe relationship between body mass index and in a Brazilian adult a cross-sectional of with hypertension among in a general Japanese of obese a follow-up study of National Health in to hypertension and management impact of different of adiposity on markers of of with or on weight body blood pressure and glucose in Syndrome Patients with Overweight and Hypertension in a Japanese of on the Mechanism of and of and Blood Pressure Control in a Hypertension between Visceral Fat and Cardiovascular Disease Risk The Tanno and Sobetsu of risk factors for hypertension the of on markers and insulin in obese hypertensive of association between the polymorphism in the of the leptin gene and hypertension in obese Obesity in of prehypertension and hypertension in a National Health and acid 1 in the from rats fed a high-fat complex role of in renal in obesity: a at as predictor for and cardiovascular disease: implications of obstructive sleep and management of hypertension in of on coronary heart disease risk Comparison of in and in of origin in impact of obesity on surgery in a Hypertension in Independently of the arterial y effect of leptin on in diabetic Effect of High Obesity on Cardiovascular and and in Differences in the Association between Anthropometric of Obesity and Blood Pressure in of Insulin on A of of between of and blood pressure in in body mass index and its impact on blood pressure: a prospective population of HypertensionThe System in and Chronic Blood Pressure Obesity in Prevalence of Obesity and its Relationship with Factors in mass index in primary and secondary of obesity and its implications for coronary heart gain and of metabolic and to in patients with of Blood Pressure to changes and and of hypertension in the Results of two nationwide cross-sectional in and gene in kidney and of obese hypertensive and in obese regulation of gene and protein in rat Obesity and Blood Pressure de la arterial en la obesidad mórbida tras de and Cardiovascular in the on and leptin and in an diet-induced and the impact of subsequent Control in of salt on hypertension and in a rat of diet-induced of associated with weight effects of and on blood pressure, insulin and sympathetic in obese hypertensive Associated with in Obese body mass index is a risk factor in humans: role of and of weight loss and changes in fat with the of hypertension in a the Risk in implications for regulation of arterial pressure and body and cardiac in patients with de obesidad y Leptin and Blood Pressure in Men: Association Independent of Body Mass and Fat and cardiovascular for the and therapies of of the obese rat to Body Blood Pressure in review on impact of clinical obesity on the management of and Blood Pressure During leptin a concept in leptin with cardiovascular relationship between body mass index and pressure in adults with isolated systolic hypertension and the sympathetic Considerations in the Treatment of Obesity HypertensionThe Medical of and response in diet-induced obese of Obese between weight gain and hypertension in a the Risk in Effect on Endothelial Is as a risk factor in coronary artery is in growth and blood pressure and hypertension: or of a of syndrome the to sympathetic nerve in Blood Pressure in Obesity by of and Insulin between body weight and cardiovascular disease risk factors in Estimates of Obesity in With and HypertensionObesity and Coronary Heart and the of overweight and obesity in a population and with and cardiovascular the system and blood pressure in obese in a of in hypertension: A risk factor for cardiovascular between Blood Pressure and Insulin in Obese Weight Loss and Weight of a on Cardiovascular Risk Factors in the effects on cardiovascular and renal the obese risk factor of hypertension in a analysis of body weight and blood pressures of from to in and in of body in and living in New role of leptin in of Hypertension in a of and receptor hipertensão arterial of and effect of weight loss with or on artery in obese of overweight and obesity: and AND and sympathetic nerve is with of in of in Patients With of Blood Pressure and the Incidence of Hypertension in Men and an sympathetic system and in hypertension and OF

Survivors of childhood cancer have been reported to have a severalfold increased risk of death from cardiovascular disease. A cluster of metabolic abnormalities, including obesity, insulin resistance, hyperinsulinemia, glucose intolerance, hypertension, and dyslipidemia, have been designated as forming a metabolic syndrome that is associated with increased cardiovascular mortality. We studied 50 survivors (23 males) of childhood cancer, aged 10.5-31.2 yr, an average of 12.6 yr (range, 7.9-21.3 yr) after their diagnosis and compared them with 50 age- and sex-matched controls for signs of the metabolic syndrome by examining clinical and anthropometric measures, serum lipid profile, and fasting plasma insulin and glucose concentrations. Spontaneous nocturnal GH secretion was also evaluated in the cancer survivors. The patients had increased relative weight (P = 0.03) and body fat mass (P < 0.001), decreased serum high density lipoprotein (HDL) cholesterol (P < 0.001), and a reduced ratio of HDL to total cholesterol (P = 0.01). Fasting plasma glucose and insulin levels were higher (P < 0.001 and P = 0.003, respectively) in the cancer survivors than in the controls. The patients had an increased risk [odds ratio (OR), 4.5; 95% confidence interval (CI), 1.3-15.8; P = 0.01] of obesity (relative weight, > 120%), fasting hyperinsulinemia ( > 111 pmol/L; OR, 3.0; 95% CI, 1.0-8.6; P = 0.04), and reduced HDL cholesterol ( < 1.07 mmol/L; OR, 7.9; 95% CI, 2.2 to 29.6; P < 0.001). A combination of obesity, hyperinsulinemia, and low HDL cholesterol was seen in eight cancer survivors (16%), but in none of the controls (P = 0.01). This high risk group was characterized by reduced spontaneous GH secretion (P = 0.02). Long term survivors of childhood cancer appear to have an increased risk of manifestations of the metabolic syndrome. Decreased GH secretion may contribute to these metabolic abnormalities.

No abstract

Anthropometric, endocrine and metabolic variables, were examined in women with polycystic ovarian syndrome (PCO), and in normal control women. Obese women with PCO had higher plasma insulin values than non obese women with PCO, but lean body mass, glucose tolerance, plasma triglycerides and blood pressure were not different in spite of almost twice the body fat mass in the obese PCO women. However, in comparisons between non-obese PCO and control women, with equal body fat mass, the PCO women had higher blood pressure, plasma triglycerides and insulin, as well as a tendency to increased lean body mass. Both PCO groups had a high waist/hip ratio and larger abdominal fat cells than controls, indicating a preferential abdominal accumulation of adipose tissue. In comparison with abdominal adipocytes, femoral adipocytes were larger and had higher lipoprotein lipase activity in the control women, while in the PCO women these regional differences were not found. Basal and norepinephrine stimulated lipolysis were higher in the abdominal than femoral adipocytes in all groups. Substitution of the PCO women with ethinyl estradiol plus desogestrel during 6 months resulted in a regression of clinical androgenic symptoms as well as a normalization of plasma concentrations of free testosterone and sex hormone binding globulin. However, neither body composition nor metabolism were normalized. It was concluded that body fat distribution is more closely related to hypertension and metabolic derangements than total fat mass in the PCO syndrome. It is suggested that the relative paucity of femoral adipose tissue is due to a lack of specific effects of progesterone on adipocytes in this region.

The European Working Group on Sarcopenia in Older People (EWGSOP) developed a practical clinical definition and consensus diagnostic criteria for age-related sarcopenia. EWGSOP included representatives from four participant organisations, i.e. the European Geriatric Medicine Society, the European Society for Clinical Nutrition and Metabolism, the International Association of Gerontology and Geriatrics-European Region and the International Association of Nutrition and Aging. These organisations endorsed the findings in the final document. The group met and addressed the following questions, using the medical literature to build evidence-based answers: (i) What is sarcopenia? (ii) What parameters define sarcopenia? (iii) What variables reflect these parameters, and what measurement tools and cut-off points can be used? (iv) How does sarcopenia relate to cachexia, frailty and sarcopenic obesity? For the diagnosis of sarcopenia, EWGSOP recommends using the presence of both low muscle mass + low muscle function (strength or performance). EWGSOP variously applies these characteristics to further define conceptual stages as 'presarcopenia', 'sarcopenia' and 'severe sarcopenia'. EWGSOP reviewed a wide range of tools that can be used to measure the specific variables of muscle mass, muscle strength and physical performance. Our paper summarises currently available data defining sarcopenia cut-off points by age and gender; suggests an algorithm for sarcopenia case finding in older individuals based on measurements of gait speed, grip strength and muscle mass; and presents a list of suggested primary and secondary outcome domains for research. Once an operational definition of sarcopenia is adopted and included in the mainstream of comprehensive geriatric assessment, the next steps are to define the natural course of sarcopenia and to develop and define effective treatment.

The metabolic syndrome has received increased attention in the past few years. This statement from the American Heart Association (AHA) and the National Heart, Lung, and Blood Institute (NHLBI) is intended to provide up-to-date guidance for professionals on the diagnosis and management of the metabolic syndrome in adults. The metabolic syndrome is a constellation of interrelated risk factors of metabolic origin— metabolic risk factors —that appear to directly promote the development of atherosclerotic cardiovascular disease (ASCVD).1 Patients with the metabolic syndrome also are at increased risk for developing type 2 diabetes mellitus. Another set of conditions, the underlying risk factors , give rise to the metabolic risk factors. In the past few years, several expert groups have attempted to set forth simple diagnostic criteria to be used in clinical practice to identify patients who manifest the multiple components of the metabolic syndrome. These criteria have varied somewhat in specific elements, but in general they include a combination of both underlying and metabolic risk factors. The most widely recognized of the metabolic risk factors are atherogenic dyslipidemia, elevated blood pressure, and elevated plasma glucose. Individuals with these characteristics commonly manifest a prothrombotic state and a pro-inflammatory state as well. Atherogenic dyslipidemia consists of an aggregation of lipoprotein abnormalities including elevated serum triglyceride and apolipoprotein B (apoB), increased small LDL particles, and a reduced level of HDL cholesterol (HDL-C). The metabolic syndrome is often referred to as if it were a discrete entity with a single cause. Available data suggest that it truly is a syndrome, ie, a grouping of ASCVD risk factors, but one that probably has more than one cause. Regardless of cause, the syndrome identifies individuals at an elevated risk for ASCVD. The magnitude of the increased risk can vary according to which components of the syndrome are …

No abstract

No abstract

The insulin resistance syndrome X is related to excess intra-abdominal adipose tissue. With lipectomy of >50% of subcutaneous adipose tissue (SQAT) in nonhibernating, adult female Syrian hamsters on high-fat (HF; 50 calorie%) diet and measurements of oral glucose tolerance, oral [(14)C]oleic acid disposal, serum triglycerides, serum leptin, liver fat, perirenal (PR) adipose tissue cellularity, and body composition, we studied the role of SQAT. Sham-operated (S) animals on HF or low-fat (LF; 12.5 calorie%) diets served as controls. After 3 mo there was no visible regrowth of SQAT but HF diet led to similar levels of body weight and body fat in lipectomized and sham-operated animals. Lipectomized (L) animals had more intra-abdominal fat as a percentage of total body fat, higher insulinemic index, a strong trend toward increased liver fat content, and markedly elevated serum triglycerides compared with S-HF and S-LF. Liver and PR adipose tissue uptake of fatty acid were similar in L-HF and S-HF but reduced vs. S-LF, and were inversely correlated with liver fat content and insulin sums during the oral glucose tolerance test. In summary, lipectomy of SQAT led to compensatory fat accumulation implying regulation of total body fat mass. In conjunction with HF diet these lipectomized hamsters developed a metabolic syndrome with significant hypertriglyceridemia, relative increase in intra-abdominal fat, and insulin resistance. We propose that SQAT, via disposal and storage of excess ingested energy, acts as a metabolic sink and protects against the metabolic syndrome of obesity.

Obesity exacerbates the reproductive and metabolic manifestations of polycystic ovary syndrome (PCOS). The symptoms of PCOS often begin in adolescence, and the rising prevalence of peripubertal obesity has prompted concern that the prevalence and severity of adolescent PCOS is increasing in parallel. Recent data have disclosed a high prevalence of hyperandrogenemia among peripubertal adolescents with obesity, suggesting that such girls are indeed at risk for developing PCOS. Obesity may impact the risk of PCOS via insulin resistance and compensatory hyperinsulinemia, which augments ovarian/adrenal androgen production and suppresses sex hormone-binding globulin (SHBG), thereby increasing androgen bioavailability. Altered luteinizing hormone (LH) secretion plays an important role in the pathophysiology of PCOS, and although obesity is generally associated with relative reductions of LH, higher LH appears to be the best predictor of increased free testosterone among peripubertal girls with obesity. Other potential mechanisms of obesity-associated hyperandrogenemia include enhanced androgen production in an expanded fat mass and potential effects of abnormal adipokine/cytokine levels. Adolescents with PCOS are at risk for comorbidities such as metabolic syndrome and impaired glucose tolerance, and concomitant obesity compounds these risks. For all of these reasons, weight loss represents an important therapeutic target in obese adolescents with PCOS.

Abdominally obese individuals with the metabolic syndrome often have excess fat deposition both intra-abdominally (IA) and in the liver, but the relative contribution of these two deposits to variation in components of the metabolic syndrome remains unclear. We determined the mutually independent quantitative contributions of IA and liver fat to components of the syndrome, fasting serum (fS) insulin, and liver enzymes and measures of hepatic insulin sensitivity in 356 subjects (mean age 42 years, mean BMI 29.7 kg/m²) in whom liver fat and abdominal fat volumes were measured. IA and liver fat contents were correlated (r = 0.65, P < 0.0001). In multivariate linear regression analyses including either liver or IA fat, liver fat or IA fat explained variation in fS-triglyceride (TG) and high-density lipoprotein (HDL) cholesterol, plasma glucose, insulin and liver enzyme concentrations, and hepatic insulin sensitivity independent of age, gender, subcutaneous (SC) fat, and/or lean body mass (LBM). Including both liver and IA fat, liver and IA fat both explained variation in TG, HDL cholesterol, insulin and hepatic insulin sensitivity independent of each other and of age, gender, SC fat, and LBM. Liver fat independently predicted glucose and liver enzymes. SC fat and age explained variation in blood pressure. In conclusion, both IA and liver fat independently of each other explain variation in serum TG, HDL cholesterol, insulin concentrations and hepatic insulin sensitivity, thus supporting that both fat depots are important predictors of these components of the metabolic syndrome.

The in utero maternal metabolic environment is important relative to both short and long term development of the offspring. Although poor fetal growth remains a significant factor relative to long-term outcome, fetal overgrowth is assuming greater importance because of the increase in obesity in the world's populations. Maternal obesity and gestational diabetes are the most common metabolic complications of pregnancy related to fetal overgrowth and more specifically adiposity. Women with gestational diabetes have increased insulin resistance and inadequate insulin response compared with weight-matched controls. Gestational diabetes increases the risk of maternal hypertensive disease (preeclampsia) as well as cesarean delivery. At birth the neonate has increased adiposity and is at risk for birth injury. Multiple studies have reported that children of women with gestational diabetes have a greater prevalence childhood obesity and glucose intolerance; even at glucose concentrations less than currently used to define gestational diabetes, compared with normoglycemic women. Obese women also have increased insulin resistance, insulin response and inflammatory cytokines compared with average weight women both before and during pregnancy. They too are at increased risk for the metabolic syndrome-like disorders during pregnancy that is hypertension, hyperlipidemia, glucose intolerance and coagulation disorders. Analogous to women with gestational diabetes, neonates of obese women are heavier at delivery because of increased fat and not lean body mass. Similarly, these children have an increased risk of childhood adiposity and metabolic dysregulation. Hence, the preconceptional and perinatal period offers a unique opportunity to modify both short and long term risks for both the woman and her offspring.

Japanese-Americans have an increased prevalence of non-insulin-dependent diabetes mellitus and coronary heart disease when compared to native Japanese. This increase has been associated with fasting hyperinsulinemia, hypertriglyceridemia, and low plasma levels of high-density lipoprotein (HDL) cholesterol. The purpose of this study was to examine the relationship of both visceral adiposity and insulin resistance to this metabolic syndrome and to the presence of a predominance of small, dense low-density lipoprotein (LDL) particles (LDL subclass phenotype B) that has been associated with increased atherogenic risk. Six Japanese-American men with non-insulin-dependent diabetes, each receiving an oral sulfonylurea, were selected. One or 2 nondiabetic Japanese-American men, matched by age and body mass index, were selected for each diabetic subject, giving a total of 9 nondiabetic men. Diabetic subjects had significantly higher fasting plasma glucose (p=0.0007) and lower insulin sensitivity (SI, p=0.018) using the minimal model technique than nondiabetic subjects matched for body mass index. Six men (2 with diabetes) had LDL phenotype A and 8 (4 with diabetes) had phenotype B. One nondiabetic subject had an intermediate low-density lipoprotein pattern. Significantly greater amounts of intra-abdominal fat (p=0.045) measured by computed tomography were found in the men with phenotype B while fasting insulin (p=0.070) and triglycerides (p=0.051) tended to be higher. free fatty acids (r=0.677), LDL density (relative flotation rate, r=-0.803), and plasma HDL-cholesterol (r=-0.717). SI was significantly correlated only with plasma free fatty acids (r=-0.546) and tended to be correlated with hepatic lipase activity (r=-0.512, p=0.061). In conclusion, these observations indicate that in non-obese Japanese-American men, the metabolic features of the so-called insulin resistance syndrome, including LDL phenotype B, are more strongly correlated with visceral adiposity than with SI. It may therefore be more appropriate to call this the visceral adiposity syndrome. Although questions concerning mechanisms still remain, we postulate that visceral adiposity plays a central role in the development of many of the metabolic abnormalities, including LDL subclass phenotype B, that occur in this metabolic syndrome.

Patients with congenital adrenal hyperplasia attributable to 21-hydroxylase deficiency are treated with glucocorticoids. Glucocorticoid administration, even in substitution doses, may cause decreased bone mineral density (BMD) and obesity. The purpose of this study was to determine BMD, lean mass, and fat mass in young adult male (M, n = 15) and female (F, n = 15) patients with 21-hydroxylase deficiency, who had been treated with currently recommended low doses of glucocorticoids. Measurements were performed with dual-x-ray absorptiometry. In addition, calcaneal ultrasound measurements were performed (broadband ultrasound attenuation and speed of sound). Results were compared with those in age- and sex-matched controls; to adjust for height, lean and fat mass were divided by (height)(2). M and F patients [M, 21.7 +/- 2.4; F, 20.6 +/- 2.9 yr old (mean +/- SD)] were shorter than the controls (M, P < 0.001; F, P < 0.003) and their body mass indices were higher [M patients (25.0 +/- 3.6) vs. controls (22.3 +/- 1.9 kg/m(2)) (P < 0.02); F patients (25.5 +/- 4.5) vs. controls (21.9 +/- 2.3 kg/m(2)) (P < 0.02)]. BMD values (lumbar spine L1-L4, femoral neck, and total body) were not different from controls. Calcaneal ultrasound measurements showed that M patients had higher speed of sound values [M patients (1564 +/- 38) vs. controls (1529 +/- 29 m/sec) (P < 0.01)]. Lean mass in M and F patients was not different from controls when adjusted for height. Fat mass was higher in M and F patients when adjusted for height [M patients 5.6 +/- 2.9 vs. controls 2.7 median (1.7-7.0 min-max) kg/m(2) (P < 0.04); F patients 8.7 +/- 2.8 vs. controls 5.8 (4.3-10.7) kg/m(2) (P < 0.02)]. Relative fat mass (fat mass as a percentage of the total body mass) was higher in patients, compared with controls [M patients 22.0 +/- 9.1 vs. controls 12.8 (8.5-27.0)% (P < 0.04); F patients 34.1 +/- 5.0 vs. controls 29.0 +/- 5.1% (P < 0.02)]; this resulted from increased fat mass, not from decreased lean mass. Fat distribution over the body was not different in patients and controls. No significant correlations were found between cumulative glucocorticoid doses in the last 0.5, 2, or 5 yr or mean salivary morning levels of 17-hydroxyprogesterone and androstenedione in the last 5 yr on one hand and bone parameters, lean mass, or fat mass on the other hand. We conclude that, at prevailing low-dose glucocorticoid regimens, young adult patients with 21-hydroxylase deficiency have normal BMD. Their lean mass is in accordance with height, but fat mass is increased, with a normal distribution over the body. This results in a higher fat percentage of the total body and a higher body mass index than in healthy peers. Because overweight and increased fat mass are associated with the metabolic syndrome and increased cardiovascular risk, weight management should have appropriate attention in the follow-up of congenital adrenal hyperplasia patients, to prevent overweight-associated morbidity.

A large body of experimental and epidemiological evidence has established an association between visceral obesity and the metabolic syndrome, which retains its power throughout the spectrum of adiposity and is still clinically meaningful in severe obesity. The association may be due to an overload of liver free fatty acids (FFA) produced by the high lipolytic activity of omental fat. A substantial improvement in all aspects of the metabolic syndrome with only a moderate degree of weight loss has been observed in a large number of randomised controlled studies and can also be obtained in severe obesity, despite the fact that the patients remain obese. The reasons for this apparent dissociation between weight loss and metabolic improvement are not yet clearly understood, but may involve the relationship between visceral fat and metabolic alterations. The results of some studies suggest that the favourable metabolic changes observed in obese patients with weight loss may be directly attributable to a reduction in visceral fat, and other studies have recently shown that a rapid and preferential reduction in visceral fat mass occurs during the first phase of weight loss in morbidly obese patients possibly as a result of sympathetic nervous system activation. It is therefore possible that the apparent dissociation between weight loss and metabolic improvement is partially due to a difference in the responsiveness of visceral and subcutaneous adipose tissue to energy restriction: i.e. the fact that the metabolic profile of patients with visceral obesity may substantially improve after the loss of only a few kilograms of body weight could be related to a greater relative reduction in the amount of visceral rather than other fat. In this respect, the characteristically high rate of visceral fat mobilisation can also be seen as a good target for interventions aimed at reducing cardiovascular risk factors.

In a cohort of 190,599 participants from The National Health Insurance Service-National Health Screening (NHIS-HEALS) study, we investigated the association of changes in the predicted body composition and metabolic profiles with the risk of metabolic syndrome (MetS) in the general population, which was hitherto incompletely elucidated. At baseline and follow-up examinations, the body composition, including lean body mass (LBM), body fat mass (BFM), and appendicular skeletal mass (ASM), were estimated using a prediction equation, and the risk of MetS was analyzed according to relative body composition changes. An increase in relative LBM and ASM decreased the risk of MetS in men and women (adjusted odds ratio (aOR), 0.78 and 0.80; 95% confidence interval (CI), 0.77-0.79 and 0.79-0.81, respectively; all <i>p</i> < 0.001). As relative LBM and ASM increased, the risk of MetS was more significantly reduced in the group with higher baseline BMI and body fat mass index (BFMI)(all <i>p</i>-trend < 0.001). In men, when the relative LBM increased (aOR, 0.68; 95% CI, 0.63-0.73), the risk of MetS was low despite increased BMI. Thus, our findings suggested that an increase in the relative LBM and ASM reduced the risk of MetS, whereas an increase in the relative BFMI increased the risk of MetS; this result was consistent in men despite an increase in BMI.

The purpose of this study was to investigate the effect of a 12-week circuit training program on health-related physical fitness and metabolic syndrome risk factors in obese female college students. Twenty subjects with over 30% of accumulated body fat voluntarily participated and were randomly allocated to the control group (n=10) or circuit training group (n=10). The circuit training program consisted of 10 types of resistance and aerobic exercise and was performed 3 times per week for 12 weeks. Health-related physical fitness and metabolic syndrome risk factors were analyzed to elucidate the effect of the circuit training. Significant differences between groups were determined with two-way repeated analysis of variance and paired <i>t</i>-test. As a result of this study, body weight, % body fat, and body mass index in the circuit training group was significantly decreased compared to the control group. All health-related physical fitness indicators such as back strength, sit-up, sit-and-reach, and 1,600 m running time showed relative effects between groups or over time. Among the metabolic syndrome risk factors, waist measurement, triglyceride, and total cholesterol were significantly decreased but blood glucose, high-density lipo-protein cholesterol and low-density lipoprotein cholesterol did not show any significant difference. Therefore, the present data suggested that circuit training for 12 weeks may be effective in improving physical fitness and preventing metabolic diseases.

No abstract

ESPEN and EASO, as well as the expert international panel, advocate that the proposed SO definition and diagnostic criteria be implemented into routine clinical practice. The panel also encourages prospective studies in addition to secondary analysis of existing data sets, to study the predictive value, treatment efficacy and clinical impact of this SO definition.

No abstract

In patients with HFrEF, alternative anthropometric measurements showed no evidence for an 'obesity-survival paradox'. Newer indices that do not incorporate weight showed that greater adiposity was clearly associated with a higher risk of HF hospitalization.

The relationship between the total cholesterol/high-density lipoprotein cholesterol (TC/HDL) and TC/HDL with the combination of obesity indicators and obstructive sleep apnea (OSA) remains unclear. Therefore, we aimed to explore the associations between TC/HDL-related indices and OSA as well as clinical outcomes. This study enrolled 20,076 patients from the National Health and Nutrition Examination Survey (2005-2008 and 2015-2018). Three indicators were constructed including TC/HDL index, TC/HDL combining with relative fat mass (TC/HDL-RFM), and TC/HDL combining with body mass index (TC/HDL-BMI). We performed multivariable logistic regression and generalized additive models to evaluate the association between TC/HDL-related indices and OSA. Multivariable Cox proportional hazards regression models with restricted cubic splines were performed to assess the relationships between TC/HDL-related indices and mortality. Stratified analyses were conducted to further investigate population-specific differences. The multivariable logistic regression analyses showed that high levels of TC/HDL-related indices were significantly associated with increased prevalences of OSA (TC/HDL: odds ratio [OR] per 1 standard deviation [SD] increase: 1.1, 95% confidence interval [CI]: 1.07-1.14, P < .001; TC/HDL-RFM: OR per 1SD increase: 1.22, 95% CI: 1.18-1.27, P < .001; TC/HDL-BMI: OR per 1SD increase: 1.28, 95% CI: 1.23-1.33, P < .001). Inverted U-shaped curves were depicted between TC/HDL-related indices and OSA. During a mean follow-up of 91 months, 1917 (9.5%) all-cause deaths occurred, and 567 (2.8%) were contributed to cardiovascular deaths. Meanwhile, the TC/HDL-related indices were associated with cardiovascular mortality, but not with all-cause mortality. Subgroup analyses showed that the strength of this relationship was found to be more pronounced in participants with OSA. The TC/HDL-related indices were independent predictors of OSA and cardiovascular mortality. Our study indicated that TC/HDL-related indices can assist clinicians in making more informed clinical decisions for patients with OSA and help reduce the risk of cardiovascular mortality.

Obesity is characterized by the accumulation of an excessive amount of fat mass (FM) in the adipose tissue, subcutaneous, or inside certain organs. The risk does not lie so much in the amount of fat accumulated as in its distribution. Abdominal obesity (central or visceral) is an important risk factor for cardiovascular diseases, diabetes, and cancer, having an important role in the so-called metabolic syndrome. Therefore, it is necessary to prevent, detect, and appropriately treat obesity. The diagnosis is based on anthropometric indices that have been associated with adiposity and its distribution. Indices themselves, or a combination of some of them, conform to a big picture with different values to establish risk. Anthropometric indices can be used for risk identification, intervention, or impact evaluation on nutritional status or health; therefore, they will be called anthropometric health indicators (AHIs). We have found 17 AHIs that can be obtained or estimated from 3D human shapes, being a noninvasive alternative compared to X-ray-based systems, and more accessible than high-cost equipment. A literature review has been conducted to analyze the following information for each indicator: definition; main calculation or obtaining methods used; health aspects associated with the indicator (among others, obesity, metabolic syndrome, or diabetes); criteria to classify the population by means of percentiles or cutoff points, and based on variables such as sex, age, ethnicity, or geographic area, and limitations.

No abstract

No abstract

This external validation proved that the performance of the RFM equation used in this study to estimate FM% was more consistent than BMI in this Mexican population, showing a stronger correlation with DXA than with the other body composition methods.

No abstract

The use of a surrogate for whole-body fat percentage revealed a much higher prevalence of general obesity in the USA from 1999 to 2020, particularly among women, than that estimated using BMI, and detected a disproportionate higher prevalence of general obesity in older adults and Mexican Americans.

C-index and RFM are strongly associated with new-onset T2DM and could be used to identify the risk of diabetes in large-scale epidemiological studies.

Loss of muscle mass and waning in muscle strength are common in older adults, and inflammation may play a key role in pathogenesis. This study aimed to examine associations of C-reactive protein (CRP) and systemic immune-inflammation index (SII) with sarcopenia and sarcopenic obesity in older adults with chronic comorbidities. Cross-sectional data from the National Health and Nutrition Examination Survey (1999-2006) were obtained for participants aged ≥60 years. Sarcopenia was defined by a lean mass and body height (males < 7.26 kg/m², females < 5.45 kg/m²). Sarcopenic obesity was defined by the concurrent presence of sarcopenia and obesity (defined by relative fat mass). Logistic regression was used to assess the associations of CRP and SII with sarcopenia and sarcopenic obesity. The dose-response relationship was examined via restricted cubic splines. Of the participants (<i>n</i> = 2483), 23.1% (<i>n</i> = 574) and 7.7% (<i>n</i> = 190) had sarcopenia and sarcopenic obesity, respectively. The multivariable logistic regression models suggested a positive association of SII with sarcopenia and sarcopenic obesity, but a positive statistically significant association was not consistently observed for CRP. Dose-response curves suggested similar association patterns for these biomarkers. In clinical practice, measures to prevent sarcopenia and sarcopenic obesity are needed for older vulnerable people with high systemic inflammation.

No abstract

RFM can be a powerful indictor for predicting incident hypertension in Chinese population, but it does not show superiority over BMI, WC and WHtR in predictive power.

RFM was significantly associated with prevalent NAFLD and CVD in Chinese adults and might be considered a simple tool for disease prediction. Further large longitudinal studies are needed to verify our findings.

No abstract

LAP is closely related to the occurrence of NAFLD and could be an efficient screening and treatment tool for NAFLD in the elderly people. <i>Lay Summary</i>. We conducted a screening and study of nonalcoholic fatty liver disease in the elderly population by determining the association between obesity indexes and nonalcoholic fatty liver disease. We found that LAP is practical, easy-to-measure tool for screening and studying NAFLD in the high-risk community elderly population, making it a valuable indicator in research.

In the general population, a higher RFM was significantly associated with mortality risk, whereas a higher BMI was not. Adjusting for total muscle mass increased the strength of associations of both RFM and BMI with all-cause mortality.

Although studies have examined the association of the Relative Fat Mass (RFM, a novel anthropometric index used as a surrogate for whole-body fat percentage) with all-cause mortality, the association of RFM with diabetes-related mortality and heart disease mortality has not been thoroughly investigated. In addition, no study has compared the associations of RFM and waist circumference (a surrogate for intra-abdominal fat) with cause-specific mortality and all-cause mortality. In the present study, we addressed these knowledge gaps. We used data from the US National Health and Nutrition Examination Survey (NHANES) 1999-2018. NHANES III was used for validation. Analyses included 46,535 adults (mean age 46.5 years). During a median follow-up time of 9.7 years, 6,101 participants died (743 from diabetes; 1,514 from heart disease). Compared with BMI and WC, RFM was more strongly associated with diabetes-related mortality in both women and men, adjusting for age, ethnicity, education, and smoking status. All anthropometric measures were similarly strongly associated with heart disease mortality and all-cause mortality. RFM showed greater predictive discrimination of mortality. Similar results were found in NHANES III (n = 14,448). In conclusion, RFM is strongly associated with diabetes-related mortality, heart disease mortality, and all-cause mortality, and outperforms conventional adiposity measures for prediction of mortality.

Frailty is influenced by numerous genetic and environmental factors. However, sex differences in how these factors affect frailty, and the gene-environment interplay among frailty and two of its well-established risk factors, unhealthy body mass index (BMI) and low education, are less clear. In a large sample of 42,994 Swedish twins, we used structural equation models to estimate the genetic (heritability) and environmental sources of variance in frailty, defined as the frailty index (FI), separately in men and women. Genetic and individual-specific environmental factors contributed approximately equally to the FI variance. The heritability of FI was slightly, but significantly, higher in women (52%) than in men (45%), yet we found only weak-to-no indication of different sources of genetic variance influencing frailty across sexes. We observed a small-to-moderate genetic overlap between FI and BMI, and that the correlation between FI and education was largely explained by environmental factors common to twins in a pair. Additionally, genetic factors accounted for more of FI variation at both low and high BMI levels, with similar patterns in both sexes. In conclusion, the twin-based heritability of frailty is higher in women than in men, and different mechanisms may underlie the associations of frailty with BMI and education.

RFM, BRI, BMI, WC, LAP, and CMI were essential indicators for recognizing gallstones. By comparison, we realized that RFM was a better predictor of gallstones.

An unfavourable body fat distribution may cause metabolic abnormalities including diabetes and dyslipidemia. These effects may be mediated by alterations in sex hormones. In women the available data suggest that upper body adiposity is related to increased androgenicity (especially as indicated by low concentrations of sex hormone binding globulin). Few data, however, are available on these relationships in men. We therefore examined the association of total testosterone, free testosterone, oestradiol, dehydroepiandrosterone sulphate (DHEA-SO4) and sex hormone binding globulin (SHBG) to waist-to-hip ratio (WHR) and conicity index in 178 men from the San Antonio Heart Study, a population-based study of diabetes and cardiovascular disease. The conicity index is equal to the abdominal circumference divided by 0.109 x the square root of (weight/height). The conicity index and WHR were significantly inversely related to DHEA-SO4 and free testosterone. SHBG was only weakly associated with body mass index (r = -0.18, P < 0.05). After adjustment for age and body mass index, DHEA-SO4 remained inversely correlated with WHR (r = -0.22, P < 0.01) and conicity index (r = -0.31, P < 0.001) and free testosterone remained inversely associated with conicity index (r = -0.21, P < 0.01). Thus, in men, the association between unfavourable body fat distribution and increased androgenicity is inverse in contrast to the situation in women.

Hyperuricemia has been linked with the development of diabetes, gout, kidney, and cardiovascular diseases. Although obesity is associated with hyperuricemia, data on sex differences in this association are scarce. Therefore, this study was conducted to explore sex differences in the correlations among various indices of obesity with hyperuricemia in Taiwan. Data were obtained from the Taiwan Biobank and included 122,067 participants. After excluding 179 participants with missing data, the remaining 121,888 participants (men: 43,790; women: 78,098) were enrolled. The prevalence rates of hyperuricemia (defined as serum uric acid >7.0/6.0 mg/dL in men/women) were 29.8% and 13.6%, respectively (<i>p</i> < 0.001). Multivariable analysis revealed high values of body shape index (ABSI), waist-to-height ratio (WHtR), waist-hip ratio (WHR), lipid accumulation product (LAP), conicity index (CI), visceral adiposity index (VAI), body adiposity index (BAI), abdominal volume index (AVI), body mass index (BMI), and body roundness index (BRI) were significantly associated with hyperuricemia in both the male and female participants (all <i>p</i> < 0.001). The interactions between sex and all 10 of these indices were significant (all <i>p</i> < 0.001) for hyperuricemia. In men, LAP had the highest area under the curve (0.669), followed by BMI (0.655), VAI (0.645), AVI (0.642), BRI (0.640), WHtR (0.633), BAI (0.605), WHR (0.599), CI (0.574), and ABSI (0.510). In women, LAP also had the highest area under the curve (0.754), followed by BMI (0.728), VAI (0.724), WHtR (0.721), BRI (0.720), AVI (0.713), WHR (0.676), BAI (0.673), CI (0.626), and ABSI (0.544). In conclusion, obesity-related indices were associated with hyperuricemia in this large Taiwanese study, and sex differences were found in these associations, with stronger associations in women than in men.

A survey of 320 (175 male, 155 female) 19 year-old medical students showed that male students of South Asian origin in the top tertile for body weight or body mass index had a significantly greater conicity index than European males in these top tertiles. This difference in conicity was not significant in the group as a whole, or when ethnic pairs were matched for body weight or body mass index. However, females of South Asian descent had a significantly higher conicity index than females of European descent irrespective of how the groups were compared. The trend towards higher conicity (i.e. abdominal obesity) in young Asians may help explain the higher incidence of diabetes and cardiovascular disease seen in elderly Asians living in the United Kingdom.

Waist circumference as well as subscapular and triceps skinfolds may be helpful parameters in identifying prepubertal children with an adverse blood-lipids profile and hypertension. However, waist circumference, which is easy to measure and more easily reproducible than skinfolds, may be considered in clinical practice. Children with a waist circumference greater than the 90th percentile are more likely to have multiple risk factors than children with a waist circumference that is less than or equal to the 90th percentile.

Obesity is generally defined as a body mass index (BMI) of 30 kg/m2 and higher. Overweight is defined as a BMI between 25 and 30 kg/m2. The prevalence varies considerably between countries, and between regions within countries. It is estimated that more than half of adults aged 35-65 living in Europe are either overweight or obese. Overweight is more common among men than among women but obesity is more common among women. The prevalence of obesity in Europe is probably in the order of 10-20% in men and 15-25% in adult women. In most European countries who have reliable data on time-trends the prevalence of obesity seems to be increasing. In most European countries, obesity is usually inversely associated with socio-economic status, particularly among women. New classifications of overweight may be based on cut-off points for simple anthropometric measures which reflects both total adiposity as well as abdominal fatness.

Background Visceral obesity is associated with increased risk of metabolic disorders and cardiovascular disease, hence, diagnosing visceral fat is indispensable in clinical practice. However, the diagnostic capacity of waist–hip ratio (WHR), conicity index (CI), and abdominal volume index (AVI) to predict visceral obesity in patients with type 2 diabetes remains unclear. This study was designed to evaluate the performance of WHR, CI, and AVI in predicting visceral fat among patients with type 2 diabetes in Ho municipality.Methods A hospital-based cross-sectional survey involved 221 patients with type 2 diabetes. A questionnaire was designed to collect data on demography and other relevant variables. Anthropometric measurements were obtained using standard methods. Visceral fat was measured using bioelectrical impedance analysis (BIA). The diagnostic performance of WHR, CI, and AVI in predicting visceral fat was evaluated based on receiver operating characteristics (ROC) curve analyses. Pearson correlation analysis was used to determine the relationship between adiposity indices and visceral fat.Results Among men, the optimal threshold for AVI, >15.56, demonstrated the highest sensitivity, 87.5% and specificity, 80.71% compared to CI and WHR while among women, the optimal cutoff value for AVI, >18.49, produced the highest sensitivity, 77.05% and specificity, 85.29%. Likewise, AVI showed a better discriminatory ability in the diagnosis of visceral fat (AUC: 0.89; p < 0.001) compared to CI (AUC: 0.68; p < 0.003), and WHR (AUC: 0.73; p < 0.001) in men and AUC: 0.89; p < 0.001 compared to CI (AUC: 0.62; p < 0.023), and WHR (AUC: 0.59; p < 0.066) in women. Similarly, the strongest positive correlation was observed between visceral fat and AVI after adjustment for age (male r = 0.787, p < 0.01; female r = 0.770, p < 0.01).Conclusion AVI appeared to have outperformed CI and WHR in the diagnosis of visceral fat. Therefore, it could be a better predictive tool for visceral obesity among patients with type 2 diabetes in low-resource settings.

<title>Abstract</title> <bold>Background:</bold> Diabetes mellitus is a common chronic disease. Dyslipidemia and hypertension are two complications that may develop in diabetic patients if hyperglycemia, insulin resistance, and weight gain are not controlled. This study investigated the effects of melatonin supplementation on some cardiovascular disease risk factors and anthropometric indices in patients with type 2 diabetes mellitus (T2DM).<bold>Materials and Methods: </bold>In this double-blind, randomized, placebo-controlled trial, 50 T2DM patients were randomly allocated to intervention and control groups which received two tablets of either melatonin or placebo (250 mg) once a day for eight weeks. Mean arterial pressure (MAP), pulse pressure (PP), the atherogenic index of plasma (AIP), weight, body mass index (BMI), waist and hip circumference (WC, HC), body shape index (ABSI), abdominal volume index (AVI), body adiposity index (BAI), lipid accumulation product (LAP), conicity index, and waist-to-height ratio (WHR) were evaluated in all the patients pre- and post-intervention.<bold>Results: </bold>Melatonin supplementation for eight weeks significantly decreased the mean levels of MAP, PP, weight, BMI, WC, HC, BAI, AVI, conicity index, and WHR post-intervention (<italic>p</italic>&lt;0.05). Also, the median changes of MAP, PP, weight, BMI, WC, HC BAI, AVI, and conicity index were<bold> </bold>significantly lower in the intervention group compared with the control group (<italic>p</italic>&lt;0.05). A significant increase (<italic>p</italic>&lt;0.001) was observed in the mean levels of ABSI in the intervention group. The median changes of ABSI were significantly greater in the intervention group compared with the control group (<italic>p</italic>&lt;0.001).<bold>Conclusions:</bold> Consumption of melatonin supplement may be effective in controlling arterial pressure and anthropometric indices (as predictors of obesity) in T2DM patients.<bold>Trial registration:</bold> This trial was registered in the Iranian Registry of Clinical Trials website at 2019/5/17. (IRCT20190303042905N1).

NC measurement is a simple and time-saving screening measure that can be used to identify overweight and obese patients. Men with NC <37 cm and women with NC <34 cm are not to be considered overweight. Patients with NC > or =37 cm for men and > or =34 cm for women require additional evaluation of overweight or obesity status.

Background: Obesity and overweight, the fifth noticeable reason for worldwide mortality, has been found directly related to cardiovascular illness and sudden death. This study aimed to evaluate anthropometric measurements including; a Body Shape Index (ABSI), Waist-Height Ratio (WHtR), Abdominal Volume Index (AVI) and Conicity Index (CI), the risk factors for cardiovascular diseases. Methods: This case-control study was conducted at BMSI, Jinnah Post Graduate Hospital from March ‎2019 to September 2020. Participants selected (n=105 adults, aged 30-50 years) were divided into three groups (35 each). Group A: patients with diabetes &lt;5 years without microalbuminuria, Group B: patients &gt; 5 years of diabetes with microalbuminuria and Group C: healthy individuals. All measurements were estimated twice. Data was analyzed by SPSS and the mean difference was found by ANOVA. Linear regression was applied to predict variables and p&lt;0.05 was considered significant. Results: The body mass index (BMI) among Group A, B and C was 25.1±0.04 kg/m2, 26.4±1.91 kg/m2 and 23.7±1.9 kg/m2 respectively. Statistically significant (p=0.000) mean difference for weight, BMI, WHtR, AVI and CI were observed among groups. A highly strong negative relationship between BMI with RPI and strong positive relationship of WHtR with AVI (r=0.887), BAI(r=0.929), CI(r=0.890), WWI(r=0.870), was found. However, highly strong positive relationship between ABSI with WWI and CI with WWI, was also observed. Conclusion: Predictors found related to cardiovascular health were BRI, BAI, and ABSI (p=0.000). However, neither the BRI, ABSI nor BAI showed ‎superior predictive power to WC, BMI, CI, WHtR and Conicity index. Keywords: Cardiovascular Abnormalities; Body Mass Index; Waist-Height Ratio (WHtR); Waist-Hip Ratio.

In this trial, we aimed to define arterial stiffness (AS) parameters in patients with type 2 diabetes mellitus (DM) without any known coronary heart disease and compare our results with the incidence of complications of type 2 DM like abdominal obesity, nephropathy and retinopathy in our study population. Patients and methods: We included 110 type 2 DM patients between the ages of 30-80, without any coronary heart disease with estimated glomerular filtration rate (eGFR) value of above 30 m/min/1.73 m 2 to our study. We recorded patients', body weight, body mass indexes (BMI), conicity indexes (CI), waist circumferences, onset of diabetes, smoking habits, fundus evaluation, hypertension and hyperlipidemia background. Moderately increased albuminuria was used as a marker to identify the diabetic nephropathy. We measured the pulse wave velocity (PWV), augmentation index (AIx), arterial blood pressure of patients by using Mobil-O-Graph ARC solver algorithm" device. Results: PWV values were positively associated with CI, onset of type 2 DM, and systolic blood pressure. PWV values were negatively associated with eGFR. AIx values were positively associated with BMI, systolic blood pressure and heart rate. AIx values were negatively associated with hemoglobin level. Hypertension was positively associated with PWV. Smoking habits was negatively associated with AIx. There were no statistically association among complications of diabetes such as nephropathy, retinopathy and PWV, AIx values. Conclusion: There were associations between AS and CI, eGFR, hemoglobin level, onset of diabetes, arterial blood pressure values of type 2 DM patients. There were no association between AS and nephropathy, retinopathy rates of type 2 DM patients. We assume that AS is an independent novel cardiovascular risk factor for patients diagnosed with obesity, anemia, hypertension and type 2 DM.

WSR was stronger than BMI in association with diabetes, but these indicators were equally strongly associated with hypertension in Asians.

No abstract

The present study indicated that these different indices derived from anthropometric parameters have different discriminatory abilities for MetS. Although WC did not have the largest area under the ROC curve for diagnosing and predicting MetS, it may remain a better index of MetS status and risk because of its simplicity and wide use.

No abstract

WHTR is a simple, easy, accurate, and non-age-dependent index with high applicability to screening overweight and obesity in children and adolescents. The use of WHTR in the general childhood population has been justified by this study.

Both the anthropometric indicators, C Index and WHtR, as well as LAP and VAI had high accuracy in visceral obesity discrimination. So, they are effective in cardiovascular risk assessment and in the follow-up for individual and collective clinical practice.

No abstract

The global epidemic of obesity in children will see a rise in the number of cases of metabolic syndrome, which is a clustering of CVD risk factors, including atherogenic levels of blood lipids, hyperinsulinaemia and raised blood pressure. Rather than excess general fatness (assessed by BMI), more specifically it is excess abdominal fatness, quantified by waist circumference measurement, which is a better measure of risk for these metabolic abnormalities in children of all ages. Insulin resistance, a consequence of excess visceral fat, is understood to be the driving force underpinning the metabolic syndrome. Consequently, assessment of abdominal fatness in children is proving to be more clinically useful. Waist circumference centile charts have now been developed for the UK and other paediatric populations to assist in this process. Furthermore, studies in the UK and elsewhere have shown that abdominal fatness has increased in infants, children and adolescents to a greater extent than overall fatness over the past 10-20 years, suggesting that obesity prevalence may be underestimated when based entirely on BMI. Additionally, ethnic differences in fat distribution have been demonstrated in children, with those from south Asian backgrounds having a greater abdominal distribution compared with Caucasian children and consequently having a much greater risk for type 2 diabetes. The information that can be provided by waist circumference measurement in children, as in adults, together with the recent changes in body fat distribution should provide the impetus for its measurement to be standardised and routinely taken in clinical and epidemiological settings.

BACKGROUND : Obstructive sleep apnea syndrome (OSAS) is a comorbidity of obesity. OSAS is also an independent risk factor for type 2 diabetes (T2DM). OSAS promotes incident major adverse cardiovascular events (MACE). The prevalence of OSAS and its association with MACE are poorly documented in T2DM, a high-risk population. METHODS : We analyzed 580 consecutive male T2DM outpatients in whom OSAS was diagnosed through combined evaluation, including (hetero)anamnesis, Epworth's Sleepiness Scale (ESS), overnight oximetry, and confirmed by polysomnography. OSAS (+) (n=66) were compared to OSAS (–) (n=514) regarding cardiovascular (CV) risk factors, microvascular complications, MACE, and UKPDS 10-year absolute CVD risk. RESULTS : Mean (1 SD) age was 63 (11) years, diabetes duration 13 (9) years. Metabolic syndrome (MetS) prevalence was 77%, and HbA 7.5 (1.5)%. OSAS prevalence was 11.4%. There were no differences in age, diabetes duration, smoking, blood pressure (BP), and lipids (except for triglycerides) between OSAS (+) and (–). There were significant differences in the ESS score, BMI, waist, relative/absolute fat, skeletal muscle, conicity index, and visceral fat, all significantly higher in OSAS (+). Micro- and macrovascular complication prevalences were high, though not significantly different, in both groups, except for stroke prevalence, which was doubled in OSAS (+): 15 vs 7%; P=.05). Fasting triglycerides and cystatin-C levels were significantly higher in OSAS (+), the increase in the latter being unrelated to differences in eGFR between groups. UKPDS Risk Engine input variables and predicted risk were all similar in both groups, with a 10-year risk for CAD 20% and 22%, respectively in OSAS (–) and OSAS (+) patients (NS). CONCLUSIONS : OSAS is frequent in male T2DM patients who exhibit a high-risk cardiometabolic phenotype characterized by severe MetS score and prevalence, central fat accretion, insulin resistance, hypertriglyceridemia, and raised cystatin-C. The data indicate an association between OSAS and stroke prevalence. Using the T2DM-specific UKPDS Risk Engine, absolute 10-year CVD risk estimates were elevated, though not significantly different, between OSAS subgroups in primary CV prevention.

Anthropometry and blood pressure predict risk of cardiovascular disease in diabetics Introduction: Diabetes mellitus (DM) is characterized by chronic hyperglycemia and is associated with complications, such as cardiovascular disease (CVD). Anthropometric measures can help prevent the risk of both diseases. Objective: To evaluate the risk for cardiovascular diseases in diabetic patients. Casuistry and methods: The study included 42 patients, adults and elderly, self-reported DM, and were assessed by anthropometry, socioeconomic questionnaire, that also contained clinical variables, physical activity and medications. Results: Most patients (85.71%) were overweight /obese. According to the risk parameters for CVD (conicity index, waist-height, waist circumference) it was found a risk in majority of the sample (97.62%). Blood pressure was considered high with the criteris evaluated (78.57%). Conclusion: It was observed high risk for CVD before all the variables, blood pressure was altered and they were also overweight/obese. This condition can result in a decreased quality of life for them as well as a worse prognosis.

Those results show that C and WHCR indexes are the best indexes of obesity to discriminate HCR. WC has intermediate discriminatory power and the BMI was the least suitable anthropometric index of obesity to discriminate HCR. Those data suggest that the indexes of abdominal obesity are better to discriminate HCR than the indexes of general obesity.

The OMA CPS regarding "Obesity Definition, Diagnosis, Bias, Standard Operating Procedures (SOPs), and Telehealth" is one in a series of OMA CPSs designed to assist clinicians care for patients with the disease of obesity.

The 21st annual World Congress on Insulin Resistance, Diabetes and Cardiovascular Disease, held in Los Angeles, California on December 7–9, 2023, included 69 presentations spanning a myriad of aspects of diabetes and its complications, atherosclerosis, renal disease, liver disease, and novel therapeutic approaches. This second summary focuses on presentations at the meeting pertaining to obesity. Philipp Scherer (Dallas, Texas) noted that, similarly to the importance of fibrosis in metabolic dysfunction-associated fatty liver disease (MAFLD), which may persist after steatosis has been treated and which underlies the development of cirrhosis, obesity is associated with increased localized fibrosis and disrupted angiogenesis in adipose tissue, mediated by low levels of adiponectin and increased production of leptin, steroid hormones, and inflammatory mediators.1 Scherer highlighted the role of endotrophin, a cleavage product of collagen that may mediate fibrosis in the liver, kidneys, and heart. Development of agents to neutralize this peptide might have therapeutic benefits. He also showed studies suggesting that the greater clinical potency of tirzepatide than of the glucagon-like peptide (GLP)-1 receptor agonist (RA) semaglutide may be an effect of glucose-dependent insulinotropic polypeptide (GIP) receptor activation in increasing energy expenditure. Richard Bergman (Los Angeles, California) discussed the use of the body mass index (BMI) in quantitating obesity, explaining that the measure derives from the work of Adolphe Quetelet, who developed the concept of the “Average Man” in the nineteenth century. He proposed use of an index based on the observation that weight varied in proportion to the square of height. During the twentieth century the term BMI was popularized by Ancel Keys, based on studies showing that the Quetelet index correlated with direct measurements of body fat. The BMI does not, however, give information about fat distribution, and Bergman suggested that it is not a good measure of body fat, giving no information about the mechanisms operative in a given individual. Measurement of skinfold thicknesses, the use of BMI in conjunction with waist circumference, underwater weighing, and the more recent body adiposity index (calculated as hip/height^1.48) have been proposed. Bergman reviewed his work in population studies with dual-energy X-ray absorptiometry measurement of fat mass. Analysis of a variety of possible relationships between sex, height, weight, and waist circumference led Bergman to propose a new measure, relative fat mass (RFM), calculated as: RFM = 64 – (20*Height/WC) + (12*sex), with sex = 0 in men and sex = 1 (women).2, 3 Bergman reviewed studies showing good prediction of risks of diabetes, heart failure, and coronary disease with this measure. Samuel Klein (St. Louis, Missouri) discussed the complex relationships between BMI and cardiovascular disease, pointing out the concepts of metabolically healthy vs unhealthy normal weight, overweight, and obesity, with a metabolically unhealthy person having greater improvement than the metabolically healthy one from a given degree of weight loss,4 so that obesity may not itself be the mediator of adverse outcomes. Among people with relatively early type 2 diabetes (T2D), diet can effectively lead to remission,5 with progressively greater degrees of weight loss leading to progressively greater improvement in insulin sensitivity,6 leading Klein to argue that the “primary first step should be aggressive weight loss management.” Klein reviewed the Swedish Obesity Study, which showed lower mortality, and fewer cardiovascular (CV) and malignancy outcomes beginning 6 years after bariatric surgery than those seen in persons not electing to have such surgery,7 and the more recent study showing that high-risk persons with obesity had fewer adverse CV outcomes when treated with semaglutide than with lifestyle intervention alone.8 The Look AHEAD trial of persons with T2D showed, however, that despite progressive improvement in CV risk factors with greater weight loss CV outcome benefit was not demonstrated,9 so that lifestyle approaches to weight loss management are probably insufficient for the majority of persons with obesity. Eric Ravussin (Baton Rouge, Louisiana) discussed calorie restriction with intermittent fasting, reviewing the use of time-restricted eating as a strategy to restrict calories, pointing out that in interviews people report eating over a period of 12 hrs per day and that smartphone data actually suggest 15 hrs to be more accurate. The principle underlying intermittent fasting is reversing to 15–16 hrs per day of not eating. A comparison of eating equivalent quantities over 6 rather than 12 h showed improvement in insulin sensitivity, blood pressure, and oxidative stress.10 A meta-analysis of time-restricted eating showed, however, that there was short- but not long-term weight loss with this approach.11 Of note, a poster at the American Heart Association's scientific meeting in March 2024 analyzing dietary patterns among 43 849 participants in the National Health and Nutrition Examination Surveys from 2003 to 2018 showed an increase in CV mortality among those reporting eating duration <8 h/day,12 further suggesting the need for caution in advising this approach. Related approaches include alternate day fasting, 1-day-per-week fasting, and alternate day modified fasting. Ravussin discussed a “new thing on the horizon,” precision nutrition based on predicting a given individual's responses to different foods and to different dietary patterns based on genomic and food intake analysis. Ania Jastreboff (New Haven, Connecticut) and Richard Pratley (Orlando, Florida) reviewed developments in use of nutrient-stimulated hormone-based therapies for obesity, with potential agents being developed based on peptide YY, oxyntomodulin, amylin, and glucagon as well as GIP and GLP-1 (Table 1). All show promising weight loss effects, with the goal being to move beyond weight reduction to optimizing health outcomes. Animal models have shown a variety of potential actions of these agents on inflammation and on the kidney, lungs, brain, liver, and adipocytes. A number of agents are under study,13 including the amylin receptor agonist, cagrilintide, combined with the GLP-1RA semaglutide,14 survodutide, a glucagon/GLP-1 receptor dual agonist,15 and retatrutide,16 a single peptide with agonist activity at the GIP, GLP-1, and glucagon receptors. Oral agents being developed include orforglipron, a nonpeptide GLP-1 receptor agonist,17 and high-dose oral semaglutide.18 Maridebart cafraglutide is being developed as a monthly injection, acting as a GLP-1 RA and an antagonist of the GIP receptor.19 A hypothesis being advanced to explain potential benefit of GIP receptor antagonism is that chronic GIP receptor agonism actually downregulates GIP response, acting as an antagonist.20 Retatrutide Obesity increases liver fat accumulation, with Rohit Loomba (La Jolla, California) noting that steatotic liver disease (SLD) is the new “umbrella term,” including metabolic dysfunction-associated SLD (MASLD), metabolic dysfunction associated steatohepatitis (MASH), alcohol-associated liver disease (ALD), and MASLD associated with increased alcohol intake (MetALD). Globally, MASLD affects 25% of the adult population and 65% of persons with T2D, with 14% of those with T2D having advanced fibrosis and 6% having cirrhosis. Loomba reviewed his study of risk factors for advanced fibrosis among relatives of persons with MASLD: age, male sex, diabetes, and advanced fibrosis in a relative.21 Loomba reviewed treatment approaches, lifestyle approaches including avoidance of excess heavy alcohol use, persons with fibrosis completely eliminating alcohol, with the interesting observation that drinking at least two cups of coffee daily may be beneficial. A variety of pharmacologic approaches have been studied, including pioglitazone., vitamin E, and statins. The farnesoid X-activated receptor agonist obetocholic acid is used in treatment of primary biliary cholangitis but was found not to significantly improve MAFLD, with the important side effects of increasing low-density lipoprotein cholesterol and causing cholestatis, leading to pruritus and increased gallstone formation. Semaglutide 2.4 mg weekly improves MASH but does not reverse cirrhosis, although studies in stage 2 and Stage 3 fibrosis are in progress. The fibroblast growth factor 21 analog pegozafermin significantly improved MASH and fibrosis in a phase 2b trial,22 with further studies in progress. A final agent is resmetirom, a thyroid hormone receptor-beta agonist, which has just received conditional Food and Drug Administration approval (pending confirmatory trials) for use in MASH with stages F2 and F3 fibrosis, based on a Stage 3 trial showing improvement in fibrosis.23 A recent meta-analysis suggested efficacy for SLD (but not for fibrosis) of the milk thistle-derived supplement silymarin.24

Various indicators have been suggested as replacements of body mass index (BMI) for estimating body fat percentage, including the recently introduced relative fat mass (RFM). However, RFM has not been assessed in different ethnicities; therefore, we evaluated whether RFM can be used to estimate body fat percentage in Korean adults and whether RFM is a useful indicator of obesity. Based on the Korea National Health and Nutrition Examination Survey (KNHANES) 2008-2011, we analyzed a total of 18,706 individuals (7,970 men, 10,643 women) aged ≥20 years who underwent dual-energy X-ray absorptiometry. We compared obesity (body fat ≥25% for men, 35% for women) misclassification rate of RFM (≥25 for men, 35 for women) and BMI (≥25 kg/m²). Diagnostic accuracy and optimal cut-offs of BMI and RFM were verified by comparing area under the receiver operating characteristic curve (AUC). RFM and BMI misclassification rates were similar obesity diagnosis based on body fat percentage (27.9% vs. 27.8%) among men. RFM misclassification rate was lower than that of BMI (22% vs. 45%) in women. AUC of RFM was higher in men (AUC: 0.79 vs. 0.78; p = 0.004) and lower in women (AUC: 0.80 vs. 0.83) than those of BMI (p < 0.001). In this study, RFM showed diagnostic accuracy for detecting excess body fat percentage, comparable to that of BMI. Using RFM with BMI could be beneficial in improving the diagnostic accuracy of obesity assessment in women.

People with type 2 diabetes are disproportionately affected by cardiovascular disease (CVD), compared with those without diabetes. Traditional risk factors do not fully explain this excess risk, and other "nontraditional" risk factors may be important. This review will highlight the importance of nontraditional risk factors for CVD in the setting of type 2 diabetes and discuss their role in the pathogenesis of the excess CVD morbidity and mortality in these patients. We will also discuss the impact of various therapies used in patients with diabetes on nontraditional risk factors.

We identified two GRSs composed of BMI and WHR-associated SNPs with significant impact on weight loss after RYGB surgery using random forest analysis as a SNP selection tool. The GRS may be useful to pre-surgically evaluate the risks for patients undergoing RYGB surgery.

No abstract

We investigated the relationship between the basal metabolic rate (BMR) and muscle strength through measurement of handgrip strength. We conducted a cross-sectional study of a population representative of older Korean from the 2014-2016 Korean National Health and Nutrition Examination Survey. A total of 2512 community-dwelling men and women aged 65 years and older were included. The BMR was calculated with the Singapore equation and handgrip strength was measured using a digital dynamometer. The patients were categorized into handgrip strength quartiles and a weighted one-way analysis of variance (ANOVA) for continuous variables and a weighted chi-squared test for categorical variables were performed. Pearson, Spearman correlation analysis, univariate, and multivariate linear regression were performed. Analysis of covariance (ANCOVA) was also performed to determine the association between basal metabolic rate and handgrip strength quartiles after adjusting for confounding factors. The BMR increased according to handgrip strength quartile after adjusting for age, BMI, relative fat mass, comorbidity number, resistance exercise, aerobic physical activity, household income, educational level, smoking status, and alcohol ingestion in both sexes (<i>p</i> < 0.001). Handgrip strength has a positive association with the BMR in older Korean people. Therefore, muscle strength exercises should be considered for regulating the BMR in the older people.

The final models included hand thickness, and the female model was dependent on waist circumference and two of the skinfold measures, while the male model used hip and thigh circumferences, along with three skinfold measures. By including the skinfold measurements separately, instead of only as sums like previous models have done, these models can account for the different relative contributions of each site to total body fat.

This review summarizes body circumference-based anthropometrics that are in common use for research and in some cases clinical application. These include waist and hip circumference-based central body indices to predict cardiometabolic risk: waist circumference, waist-to-hip ratio, waist-to-height ratio, waist-to-thigh ratio, body adiposity index, a body shape index (ABSI), hip index (HI), and body roundness index (BRI). Limb circumference measurements are most often used to assess sarcopenia and include: thigh circumference, calf circumference, and mid-arm circumference. Additionally, this review presents fascinating recent developments in optic-based imaging technologies that have elucidated changes over the last decades in average body size and shape in European populations. The classical apple and pear shape concepts of body shape difference remain useful, but novel and exciting 3-D optical "e-taper" measurements provide a potentially powerful new future vista in anthropometrics.

The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.

Proposed cut-offs for relative fat mass were more reliable indices than the usual cut-offs for body mass index for identifying individuals at heightened cardiovascular risk. Our findings support the role of anthropometric measures in evaluating body composition and the associated metabolic and cardiovascular conditions in older adults.

The Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) on History, Physical Exam, Body Composition and Energy Expenditure is one of a series of OMA CPSs designed to assist clinicians in the care of patients with the disease of pre-obesity/obesity.

No abstract

<title>Abstract</title> Background Anthropometry is a reliable method to assess obesity status, and previous studies have shown the association of several dietary quality scores with obesity using anthropometric indices. This study aimed to evaluate the association between LLDS and anthropometric measurements. Methods A total of 217 women between the ages of 18 and 48 participated in the study. Anthropometric values, biochemical tests, and body composition were assessed for each participant using standard protocols and methods. The LLDS was determined based on 12 components using a reliable and valid food frequency questionnaire (FFQ) that contained 147 items. Results We detected a marginally significant inverse association between the LLDS and VAI scores in the second tertile. Study participants in the second tertile of LLDS had lower odds of having high VAI than those in the reference tertile after adjusting for age, energy intake, physical activity, education, and economic status (<italic>OR: -0.16; 95% CI: -0.8, 0.06; P = 0.06</italic>). There was no statistically significant trend for the association between LLDS and all assessed anthropometric indices, including BRI, ABSI, VAI, and BAI, across tertiles of LLDS in the crude and all adjusted models (<italic>P-trend &gt; 0.05</italic>). Conclusions There was no significant association between LLDS and some novel anthropometric indices, including BRI, ABSI, VAI, and BAI. However, after adjusting for probable confounders, a marginally significant inverse association between LLDS and VAI was detected.

BRI and ABSI have discriminatory power for hypertension in adult women and men from different populations. Although, WHtR and WC provided the best performance when assessing hypertension, no significant differences were found for BRI. Finally, BRI was significantly better predictor of hypertension than ABSI.

No abstract

No abstract

The body mass index (BMI) and waist circumference (WC) are commonly used anthropometric measures for predicting cardiovascular diseases risk factors, but it is uncertain which specific measure might be the most appropriate predictor of a cluster of cardiometabolic abnormalities (CMA) in Chinese adults. A body shape index (ABSI) and body roundness index (BRI) have been recently developed as alternative anthropometric indices that may better reflect health status. The main aims of this study were to investigate the predictive capacity of ABSI and BRI in identifying various CMA compared to BMI, WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), and to determine whether there exists a best single predictor of all CMA.We used data from the 2009 wave of the China Health and Nutrition Survey, and the final analysis included 8126 adults aged 18 to 85 years with available fasting blood samples and anthropometric measurements. Receiver-operating characteristic (ROC) analyses were conducted to assess the best anthropometric indices to predict the risk of hypertension, diabetes, dyslipidemia, hyperuricemia, and metabolic syndrome (MetS). Logistic regression models were fit to evaluate the OR of each CMA according to anthropometric indices.In women, the ROC analysis showed that BRI and WHtR had the best predictive capability in identifying all of CMA (area under the curves [AUCs] ranged from 0.658 to 0.721). In men, BRI and WHtR were better predictor of hypertension, diabetes, and at least 1 CMA (AUC: 0.668, 0.708, and 0.698, respectively), whereas BMI and WC were more sensitive predictor of dyslipidemia, hyperuricemia, and MetS. Furthermore, the ABSI showed the lowest AUCs for each CMA. According to the multivariate logistic regression analysis, BRI and WHtR were superior in discriminating hyperuricemia and at least 1 CMA while BMI performed better in predicting hypertension, diabetes, and MetS in women. In men, WC and BRI were the 2 best predictor of all CMA except MetS, and the ABSI was the worst.Our results showed the novel index BRI could be used as a single suitable anthropometric measure in simultaneously identifying a cluster of CMA compared to BMI and WHtR, especially in Chinese women, whereas the ABSI showed the weakest discriminative power.

We found that BRI and WHR were superior to other indices for predicting CVD risk factors, except CKD or hypercholesterolemia, among the Chinese.

Abstract Background Branched chain amino acids (BCAAs, Valine, Leucine, and Isoleucine) are indispensable for skeletal muscle metabolism. However, the association between BCAA and anthropometry is still controversial. Aims To assess the associations between BCAA levels and different anthropometric markers, including leptin and adiponectin levels, in a sample of healthy, non-obese participants. Methods Cross-sectional study using data from the CoLaus|PsyCoLaus study in our city. Anthropometric markers included conicity index (CI), Body roundness index (BRI), A Body shape index (ABSI), body mass index (BMI), and waist circumference, among others. Grip strength was used as a proxy for muscle mass. Results Data from 1929 participants (845 men, 53.2±8.5 years old, BMI&amp;lt;30 kg/m2) Using bivariate analysis, most anthropometric markers were positively correlated with BCAA, while adiponectin levels were negatively correlated with BCAA. The correlations were stronger in men compared to women, except for Conicity index, ABSI, and adiponectin. After multivariable analysis, weight and BMI had the strongest association with BCAA in men, while in women the strongest associations were found for waist and waist to height ratio (table). No significant associations were found between the ABSI and BCAA levels in men, and between grip strength and BCAA levels in women. Stepwise linear regression identified BMI in men and waist in women as the anthropometric markers most associated with BCAA. Conclusion We found a significant gender difference in the anthropometric markers associated with BCAA levels. BMI was the anthropometric marker most associated in men, and waist was the anthropometric marker most associated in women.

Although VAI might not be very cost-beneficial compared to IDF, our study showed VAI is a better predictor of MetS than BRI in adults. ABSI was not a suitable predictor for MetS.

No abstract

No abstract

Frequently reported poor dietary habits of young adults increase their risk of metabolic syndrome (MetS). Excess adiposity is the most established predictor of MetS, and numerous anthropometric measures have been proposed as proxy indicators of adiposity. We aimed to assess prevalence of MetS in young adult population and to make comparison between weight- and shape-oriented measures of adiposity to identify the best index in association with measured body fat and as a risk predictor for MetS. Healthy males and females aged 18-25 years from the Northwest of England were recruited using convenience sampling (<i>n</i>=550). As part of the assessment of the overall health of young adults, the biochemical variables and adiposity measures BMI, waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), new BMI, Body Adiposity Index (BAI), Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), and A Body Shape Index (ABSI) were assessed. Linear regression analysis was used to investigate the association between the proxy indices of adiposity and measured percentage body fat. The odds ratio with 95% confidence interval was used to investigate the relationship between cardiometabolic (CM) risk factors and proxy measures of adiposity. The discriminatory power of these measures for diagnosis of MetS was investigated using area under the receiver operating characteristic curve. Body weight-related indicators of adiposity, particularly CUN-BAE, had stronger association with measured body fat compared with body shape-related indices. In relation with MetS, body shape-related indices, particularly elevated WC and WHtR, had stronger associations with CM risk compared with body weight-related measures. Amongst all indices, the best predictor for CM risk was WHtR, while ABSI had the weakest correlation with body fat, MetS, and CM risk. Indices directly associated with WC and specifically WHtR had greater diagnostic power in detection of CM risk in young adults.

WHtR and AVI showed the highest AUC to diagnose metabolic syndrome and were better associated with metabolic diseases.

No abstract

No abstract

BMI√WC and WHT.5R were significantly positively associated with MetS, and AVI and WHT.5R could be useful screening tools for identifying MetS in both sexes.

WC was a good predictor for one/two or three/more categories of abnormal serum lipid indices in men. However, BRI and WHtR were good predictors for one/two or three/more categories of abnormal serum lipid indices in women. ABSI showed the weakest predictive power.

The most effective anthropometric indicator for the identification of MetS varied across sex and age subgroups.

Metabolic syndrome (MetS) is prevalent in Taiwan; however, the association between MetS and cognitive function is unclear. The aim of this study was to explore the associations between MetS, its components, and obesity-related indices with cognitive function in a large Taiwanese cohort. We enrolled a total of 28,486 participants who completed the Mini-Mental State Examination (MMSE) questionnaire, which was used to evaluate cognitive function. MetS was defined according to the NCEP-ATP III guidelines and modified criteria for Asians. Ten obesity-related indices were also evaluated: body mass index (BMI), abdominal volume index (AVI), body adiposity index (BAI), waist−hip ratio (WHR), a body shape index (ABSI), lipid accumulation product, waist-to-height ratio (WHtR), conicity index (CI), body roundness index (BRI), and triglyceride glucose index. The prevalence of MetS and its components (except for hypertriglyceridemia) and the number of MetS components increased while the cognitive impairment worsened (from MMSE ≥ 24, 18−23 to 0−17). In addition, increases in all obesity-related index values were associated with a decline in cognitive function (from MMSE ≥ 24, 18−23 to 0−17, ANOVA p < 0.001). Multivariable analysis showed that MetS (p = 0.002), abdominal obesity (p < 0.001), low high-density lipoprotein cholesterol (p = 0.004), and hyperglycemia (p = 0.012) were significantly associated with a low MMSE score. Further, participants with high BMI (p = 0.001), WHR (p < 0.001), WHtR (p < 0.001), BRI (p < 0.001), CI (p < 0.001), BAI (p < 0.001), AVI (p < 0.001), and ABSI (p < 0.001) values were significantly associated with a low MMSE score. Our results show that MetS and its components (except for hypertriglyceridemia and high blood pressure) may lead to cognitive impairment, and that high values of obesity-related indices were associated with poor cognitive function.

No abstract

No abstract

Recent studies have shown that using international guidelines to diagnose metabolic syndrome (MetS) may underestimate its prevalence in different Asian populations. This study aims to determine the validity of anthropometric indicators and appropriate cut-off values to predict MetS for Vietnamese adults. We analyzed data on 4701 adults across four regions of Vietnam. Four conventional and five novel anthropometric indexes were calculated. The area under a receiver operating characteristic (ROC) curve (AUC) and Youden's J statistic were applied to evaluate the diagnostic ability and optimal cut-off values. Regardless of diagnostic criteria and gender, Abdominal volume index (AVI), Body roundness index (BRI), and Waist-height ratio (WHtR) had the highest AUC values, followed by Body mass index (BMI) and Waist-hip ratio (WHR). However, it was seen that differences among the AUC values of most indices were minor. In men, using International Diabetes Federation (IDF) criteria, the threshold of indices was 3.86 for BRI, 16.20 for AVI, 0.53 for WHtR, 22.40 for BMI, and 0.90 for WHR. In women, the threshold for these figures were 3.60, 12.80, 0.51, 23.58, and 0.85, respectively. It is recommended that health personnel in Vietnam should apply appropriate thresholds of anthropometry, which are lower than current international guidelines, for MetS screening to avoid under-diagnosis.

The study underscores the importance of anthropometric indices, particularly ABSI, in predicting the 10-year risk of ASCVD. These findings suggest that ABSI, along with other indices, can be instrumental in identifying individuals at higher risk for ASCVD, thereby aiding in early intervention and prevention strategies.

No abstract

While the %BF, CUN-BAE, BMI, WC, WHtR, BRI, CI and CUN-BAE could predict MetS among South African male taxi drivers, these indices were less effective in predicting the individual MetS risk factors such as TG, BP, and FBG.

<b>Background:</b> The aim of this study was to investigate the associations among obesity-related indices and MetS in diabetic patients, and explore sex differences in these associations. <b>Methods:</b> Patients with type 2 DM were included from two hospitals in southern Taiwan. The Adult Treatment Panel III criteria for an Asian population were used to define MetS. In addition, the following obesity-related indices were evaluated: waist-to-height ratio, waist-hip ratio (WHR), conicity index (CI), body mass index (BMI), body roundness index, body adiposity index, lipid accumulation product (LAP), abdominal volume index, visceral adiposity index (VAI), abdominal volume index and triglyceride-glucose index. <b>Results:</b> A total of 1,872 patients with type 2 DM (mean age 64.0 ± 11.3 years, 808 males and 1,064 females) were enrolled. The prevalence rates of MetS were 59.8% and 76.4% in the males and female (<i>p</i> < 0.001), respectively. All of the obesity-related indices were associated with MetS in both sex (all <i>p</i> < 0.001). LAP and BMI had the greatest areas under the receiver operating characteristic curves in both sex. In addition, the interactions between BMI and sex (<i>p</i> = 0.036), WHR and sex (<i>p</i> = 0.016), and CI and sex (<i>p</i> = 0.026) on MetS were statistically significant. <b>Conclusions:</b> In conclusion, this study demonstrated significant relationships between obesity-related indices and MetS among patients with type 2 DM. LAP and VAI were powerful predictors in both sex. The associations of BMI, WHR and CI on MetS were more significant in the men than in the women.

AVI and BRI were better predictors of NAFLD than BMI.

Hypertension (HTN) is the leading cause of cardiovascular diseases. Nevertheless, most individuals in developing countries are unaware of their blood pressure status. We determined the prevalence of unrecognized hypertension and its association with lifestyle factors and new obesity indices among the adult population. This community-based study was conducted among 1288 apparently healthy adults aged 18-80 years in the Ablekuma North Municipality, Ghana. Sociodemographic, lifestyle characteristics, blood pressure and anthropometric indices were obtained. The prevalence of unrecognized HTN was 18.4% (237 / 1288). The age groups 45-54 years [aOR = 2.29, 95% CI (1.33-3.95), p = 0.003] and 55-79 years [aOR = 3.25, 95% CI (1.61-6.54), p = 0.001], being divorced [aOR = 3.02 95% CI (1.33-6.90), p = 0.008], weekly [aOR = 4.10, 95% CI (1.77-9.51), p = 0.001] and daily alcohol intake [aOR = 5.62, 95% CI (1.26-12.236), p = 0.028] and no exercise or at most once a week [aOR = 2.25, 95% CI (1.56-3.66), p = 0.001] were independently associated with HTN. Among males, the fourth quartile (Q4) of both body roundness index (BRI) and waist to height ratio (WHtR) [aOR = 5.19, 95% CI (1.05-25.50), p = 0.043] were independent determinants of unrecognized HTN. Among females, the third quartile (Q3) [aOR = 7.96, 95% CI (1.51-42.52), p = 0.015] and Q4 [aOR = 9.87 95% CI (1.92-53.31), p = 0.007] of abdominal volume index (AVI), the Q3 of both BRI and WHtR [aOR = 6.07, 95% CI (1.05-34.94), p = 0.044] and Q4 of both BRI and WHtR [aOR = 9.76, 95% CI (1.74-54.96), p = 0.010] were independent risk factors of HTN. Overall, BRI (AUC = 0.724) and WHtR (AUC = 0.724) for males and AVI (AUC = 0.728), WHtR (AUC = 0.703) and BRI (AUC = 0.703) for females yielded a better discriminatory power for predicting unrecognized HTN. Unrecognized hypertension is common among the apparently healthy adults. Increased awareness of its risk factors, screening, and promoting lifestyle modification is needed to prevent the onset of hypertension.

No abstract

No abstract

ABSI was deemed useful for BMI-independently identifying Japanese patients with overweight/obese at high risk of CVD based on having multiple MetS components and skeletal muscle loss. Clinical trials (the unique trial number and the name of the registry) ID: UMIN000042726.

Body roundness index was more effective compared to the other seven indices for predicting metabolic syndrome in the elderly population in Turkey.

Our findings showed that WHtR, AVI, and BRI were independently positively associated with asymptomatic hyperuricemia and could be good predictors.

Metabolic syndrome (MetS) is closely associated with adverse cardiometabolic outcomes. The objective of this study was to identify practical methods that could enable the effective identification of MetS based on anthropometric indices. The basis of our study involved retrospective database obtained from routine medical prophylactic examinations. This was a cross-sectional study on the health status of male workers employed in hazardous working conditions at industrial enterprises in the Ural region conducted in 2019. A total of 347 male workers employed under hazardous working conditions were investigated. The presence of MetS was established by a healthcare professional in accordance with the guidelines of the International Diabetes Federation (IDF). Simple linear regression was used to evaluate the associations between anthropometric indices and MetS incidence. Logistic regression was used to determine the odds ratios of MetS in relation to increases in anthropometric indices. ROC curves were calculated to compare the ability of each anthropometric index to predict MetS and to determine the diagnostic thresholds of the indicators considered. According to the IDF criteria, 36.3% of the workers had MetS. A direct relationship was found between the individual components of MetS and the anthropometric indices studied. The highest OR was shown by the Body Roundness Index (BRI) of 2.235 (95% CI 1.796-2.781). For different age quartiles, the optimal cut-off values for predicting MetS were as follows: BRI, 4.1-4.4 r.u.; body shape index (ABSI), 0.080-0.083 m^11/6 kg^-2/3; and lipid accumulation product (LAP), 49.7-70.5 cm mmol/l. The most significant associations with MetS were observed where the values were greater than these cut-off points (Se = 97.4%). The results of this study demonstrated the rapid use of new anthropometric indicators, which have shown good predictive ability and are quite easy to use.

No abstract

The conicity index is an important anthropometric indicator to estimate abdominal obesity in individuals with chronic kidney disease on hemodialysis.

CI is an independent predictor of systemic inflammation, cardiovascular risk, and GFR in patients during the pre-dialysis period.

Abdominal obesity is a major risk factor of chronic kidney disease (CKD). Conventional obesity-related indicators, included body mass index (BMI), waist circumference (WC), and conicity index (C-index), have some limitations. We examined the usefulness of trunk/body fat mass ratio (T/Br) to predict negative effect of abnormal fat distribution on excretory kidney function. We analyzed anthropometric, biochemical and densitometric data from a nation-wide, population-based, case-control study (the Korean National Health and Nutrition Examination Survey [KNHANES] IV and V). A total of 11,319 participants were divided into 2 groups according to estimated glomerular filtration rate (eGFR, mL·min⁻¹·1.73 m⁻²) as follows: Group I (n = 7,980), eGFR ≥ 90 and ≤ 120; and group II (n = 3,339), eGFR ≥ 60 and < 90. Linear regression analysis revealed that T/Br was closely related to eGFR (β = -0.3173, P < 0.001), and the correlation remained significant after adjustment for age, gender, BMI, WC, C-index, systolic blood pressure (BP), hemoglobin, and smoking amount (β = -0.0987, P < 0.001). Logistic regression analysis showed that T/Br (odds ratio [OR] = 1.046; 95% confidence interval [CI] = 1.039-1.054) was significantly associated with early decline of kidney function, and adjustment for age, gender, BMI, C-index, systolic BP, hemoglobin, serum glucose level, high-density lipoprotein (HDL)-cholesterol, and smoking amount did not reduce the association (OR = 1.020; 95% CI = 1.007-1.033). T/Br is useful in estimating the negative impact of abdominal obesity on the kidney function.

Abdominal fat deposition in haemodialysis patients is linked to both inflammation and PEW, resulting in an increased mortality risk. Our results support the idea that regional differences in adiposity accumulation may have diverse implications on patient outcome.

Our data showed that prehypertension/hypertension is a major health problem in Iran. Focusing on identifying risk factors to hypertension, regular drug intake, good nutrition, physical activity, and changing lifestyles of patients with hypertension are essential.

Anthropometric measurements including BMI, WtHR, CI, ABSI, BRI and LAP are closely associated with hypertension risk in the present study. For better prevention and treatment of hypertension, more attention should be paid to anthropometric indices, especially novel anthropometric indices.

Advanced renal insufficiency, also termed end-stage renal disease (ESRD) kidney failure or stage 5 chronic kidney disease (CKD), has long been considered as a prototypical condition of protein–energy wasting, and the dialysis patient has often been portrayed as a Caravaggio’s Saint Jerome. This perception reflected a dominant phenotype in the dialysis population from the 1970s to the 1990s. Though still frequent, this phenotype has been gradually replaced by the overweight and obese phenotype [1]. By 2002, according to the United States Renal Data System (USRDS), the prevalence of obesity in patients with ESRD in the USA had reached more than 25% [2]. Cross-sectional analyses performed in 2005 in the USRDS database showed that only 17.6% of American dialysis patients had a body mass index (BMI) below 22.5 (i.e. the threshold below which protein–energy wasting is likely), whereas the majority were either overweight (28%), obese (25%) or severely obese (7%) (H. Kramer, personal communication) (Fig. 1). Distribution of body mass index in the USRDS database in 2005. Data were kindly provided by Dr. Holly Kramer (personal communication). As in other chronic diseases such as heart failure or coronary heart disease, BMI is inversely associated with survival in ESRD. Thus, at first sight, the obesity epidemic in patients with ESRD might not appear to be of great concern. However, a high BMI per se cannot be considered as a protective factor for two reasons. First, because ‘obese sarcopenia’ (i.e. a high body mass in the face of protein–energy wasting) underlies a high risk of death in patients with ESRD [3]. Second, because recent studies have shown that abdominal obesity as measured by waist circumference [4] or by the conicity index [5] is directly associated with the risk of death in this population. As in proportional terms visceral fat represents a higher fraction of body mass in patients with ESRD than in individuals without CKD, the negative effect of excessive visceral fat in ESRD might be even greater than that in the general population. Although of major aetiological and prognostic interest, investigation of the biological relevance of fat excess and of fat compartmentalization (subcutaneous vs visceral fat) has been limited in patients with renal insufficiency. A pro-inflammatory profile associated with excessive adiposity has been described in patients with CKD [5], but there is little evidence to support a causal role of fat excess in inflammation and in metabolic disturbances in this population. In this issue of the Journal of Internal Medicine, Witasp et al. [6] report a case–control study comparing the gene expression of 21 cytokines in abdominal subcutaneous adipose tissue in 37 predialysis stage 5 CKD patients and in a small group (n = 9) of age- and sex-matched individuals with no evidence of CKD. Genes were selected on the basis of a credible ‘a priori’ and included a large series of pro-inflammatory adipokines, insulin-signalling molecules, glucose transporters and proteins involved in generation of reactive oxygen species (ROS). Abdominal subcutaneous fat in patients with CKD exhibited a threefold increase in the expression of interleukin (IL)-6 gene associated with a similar upregulation (2.5-fold) of suppressor of cytokine signalling-3 gene expression and a downregulation of leptin and the oxidative stress genes uncoupling protein (UCP)-2 and cytochrome b-245, alpha polypeptide (CYBA), compared to controls. Although differences between patients and control subjects were insensitive to adjustment for BMI, adjustment for diabetes and background cardiovascular involvement substantially attenuated these differences so that only UCP2 and CYBA (both downregulated) maintained statistical significance in fully adjusted analyses. Witasp et al. point out the problems of multivariate analysis when applied to test for aetiology and conclude that CKD per se rather than associated comorbidities determines the observed differences in the expression of inflammation genes between patients with stage 5 CKD and controls. Overall, this study is the best attempt so far to provide a biological insight at the cellular level (adipose tissue) with regard to an issue that has hitherto been explored mainly by relating circulating levels of biomarkers of inflammation and oxidative stress and anthropometric measurements. In this commentary, I will first focus on the most robust data, i.e. those concerning downregulation of two key proteins implicated in oxidative stress (UCP2 and CYBA), and then discuss inflammation and pro-inflammatory mechanism(s). UCP2 is a member of the mitochondrial UCP family. Like other UCPs, it serves to uncouple oxidative phosphorylation from ATP synthesis, a phenomenon associated with energy dissipation. The main action of UCPs is anion transport from the inner to the outer mitochondrial membrane coupled with transfer of protons in the reverse direction. UCP2 activity appears to be important in patients undergoing peritoneal dialysis because individuals homozygous for the del/del polymorphism of the UCP2 gene display a higher risk of total and truncal fat accumulation during the first year of dialysis [7]. UCP2 inhibition in adipocytes in vitro not only increases production of ROS but also impairs insulin-stimulated glucose uptake and suppresses insulin signal transduction, via hyperactivation of c-Jun N-terminal kinase, and the accompanying serine phosphorylation of insulin receptor substrate-1 [8]. These clinical and biological data clearly suggest that UCP2 may have a role in insulin resistance and in the metabolic response to chronic exposure to glucose overload in peritoneal dialysis patients. Therefore, the UCP2 pathway, which is a complex pathway encompassing oxidative stress and regulation of glucose metabolism, rather than primary alterations in insulin-signalling genes and glucose transporters (all of which are unaltered in the study by Witasp et al.), appears to be at cross-road of fat-dependent alterations in insulin sensitivity in patients with advanced CKD. Cytochrome b is composed of a light chain (α) and a heavy chain (β). The α subunit is a primary component of the microbicidal oxidase system of phagocytes. Of note, the corresponding gene (CYBA) encodes the p22phox subunit of the mitochondrial nicotinamide adenine dinucleotide phosphate (NADPH)-oxidase complex, which is a major pro-oxidant system in various cell types. The relevance of this gene in microbicidal activity is highlighted by the fact that mutations in CYBA determine autosomal recessive chronic granulomatous disease, a severe disease characterized by severe infections [9]. The prototypical cell of the innate immunity system, the macrophage, shows similarities to the adipocyte [10]; it expresses gene products typical of the adipocyte, such as the cytoplasmic fatty-acid-binding protein adipocyte lipid-binding protein 2 and peroxisome proliferator-activated receptor gamma. Furthermore, like adipocytes, macrophages have lipid-storage capabilities, and preadipocytes may differentiate into fully functional macrophages. It is important to note that in obese patients, these two cell types, the macrophage and the adipocyte, co-localize in adipose tissue forming an integrated system that is involved in the innate immune response and in metabolic regulation. Thus, the reduced expression of CYBA in the adipose tissue of patients with stage 5 CKD may be part of a systemic disorder of the reticulo-histiocitary system. If confirmed in parallel studies in circulating macrophages, CYBA downregulation in CKD might have an important role in the high rate of infection and death secondary to infection in this population. Uraemia induces complex changes in the innate and adaptive immune responses through impaired endocytosis, amplification of IL-12p70 production, and proliferation of allogenic T-cells [11] and the proportion of circulating monocytes that actively synthesise IL-6 [12]. Given the biological homologies between cells of the monocyte lineage and the adipocyte, the 3-fold increase in the expression of IL-6 levels observed by Witasp et al. is consistent with previous data on circulating monocytes in haemodialysis patients. However, because of the potential confounding effect of diabetes and concomitant atherosclerotic complications, this finding should be interpreted with caution. IL-6 levels are elevated in insulin-resistant states, such as obesity and type-2 diabetes, and high concentrations of insulin specifically stimulate IL-6 synthesis in adipocytes in vitro [13]. The low BMI in patients with stage 5 CKD is another relevant confounder with regard to the interpretation of high IL-6 expression in adipocytes in these patients. Indeed, a low BMI may entail protein–energy wasting, a condition that is a strong stimulus for IL-6 synthesis, as is the case in patients with heart or liver failure. Statistical adjustment for BMI may not eliminate potential confounding because both protein–energy wasting and excess weight/obesity are associated with high IL-6 expression. Thus, further studies in patients with CKD perfectly matched for subcutaneous fat mass or BMI are still needed to confirm the intriguing observations made in this study. In the only study in female haemodialysis patients reported to date, no difference in IL-6 gene expression was noted between patients and healthy subjects [14]. Subcutaneous fat and visceral fat represent substantially different compartments of fat mass with regard to their relationship with metabolic risk factors. Studies including the evaluation of visceral fat should be performed to complete the characterization of the association between adipose tissue and inflammation in CKD. In conclusion, the rising epidemic of CKD attributable to excess weight/obesity and the high prevalence of obesity in the dialysis population demand specific studies to determine the health implications of fat excess in patients with CKD. The intriguing observations by Witasp et al. suggest that downregulation of two oxidative stress proteins, UCP2 and CYBA, may have an important role in insulin resistance and in alterations in innate immunity and the response to infectious agents in patients with CKD. Further studies are needed to ascertain whether uraemia amplifies adipocyte production of IL-6, a cytokine unanimously recognized as critical in inflammation in patients with CKD. No conflict of interest was declared.

Anthropomorphic measurements that include a measure of central fat deposition are related to more key risk factors in CKD stage 3 patients than BMI. Central fat deposition may be of greater importance as a risk factor in CKD than BMI and reliance on BMI alone may therefore underestimate the associated risk.

A higher BRI trajectory was associated with an increased risk of CVD. The BRI can be included as a predictive factor for CVD incidence.

Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS.

The cooccurrence of diabetes mellitus and metabolic syndrome potentiates the cardiovascular risk associated with each of the conditions; therefore characterizing metabolic syndrome among people with type 2 diabetes is beneficial for the purpose of cardiovascular disease prevention. This study aims at evaluating the prevalence of metabolic syndrome and its components among 162 patients with type 2 diabetes attending the diabetic clinic of the Ho Municipal Hospital, Ghana. Data obtained included anthropometric indices, blood pressure, serum lipids, glucose, and sociodemographics and clinical information. The overall prevalence of metabolic syndrome among the study population was 43.83%, 63.58%, and 69.14% using the NCEP-ATP III, the WHO, and the IDF criteria, respectively. The most predominant component among the study population was high blood pressure using the NCEP-ATP III (108 (66.67%)) and WHO (102 (62.96)) criteria and abdominal obesity (112 (69.14%)) for IDF criteria. High blood pressure was the most prevalent component among the males while abdominal obesity was the principal component among the females. In this population with type 2 diabetes, high prevalence of metabolic syndrome exists. Gender vulnerability to metabolic syndrome and multiple cluster components were skewed towards the female subpopulation with type 2 diabetes.

No abstract

Anthropometric variables are important predictors of cardiovascular risk; however, their assessments should be performed independently, according to sex and age group.

To investigate the prediction of long-term cardiometabolic risk using anthropometric and central obesity parameters. Methods: A total of 390 Saudi subjects (men 42.8%) aged 18-50 years were enrolled in a cross-sectional study in King Saud University, Riyadh, Kingdom of Saudi Arabia between August 2014 and January 2016. All participants were instructed to fast for 12 hours before taking blood samples for glucose and lipid panel analyses. A full anthropometric measurement and bioelectric impedance analysis was performed. The anthropometric and central obesity parameters were used for correlation with 30-year Framingham and life-time American College of Cardiology/American Heart Association risk scores. We used receiver operator characteristic curves to select the best predictors with the highest sensitivity and specificity. Results: The best discriminators of the long-term cardiometabolic risk among all the studied variables in men were the visceral adiposity index (VAI) (AUC=0.767), conicity index (CI) (AUC=0.817), and mid-arm muscular area (MAMA) (AUC=0.639). The best predictors for women were body mass index (AUC=0.912), waist circumference (AUC=0.752), and lipid accumulation product (AUC=0.632). The Kappa coefficient and 95% confidence interval ranged from 0.1 to 0.35, which suggests that there is a poor to fair agreement between these indices and cardiovascular risk scores. Conclusion: Long-term cardiometabolic risk can be predicted using simple anthropometric and central obesity indices, and these discriminators were not the same in Saudi men and women.

In the present study, we showed that those anthropometric indices were significantly associated with MAFLD in United States adults. Besides, the association of HSI, BRI, AVI, and WHtR with MAFLD was more obvious in men than in women. LAP may be a sensitive marker for diagnosing MAFLD in U.S. adults.

This study supports the positive association between various anthropometric indicators and gallstones, recommending that newer anthropometric indices be considered more extensively to enhance gallstone prevention and treatment strategies.

CVAI was linearly associated with risk of CVD, heart disease, and stroke and had best performance for predicting incident CVD. Our findings indicate CVAI as a reliable and applicable obesity index to identify higher risk of CVD.

A quick and precise AVT estimate, especially for men, can be obtained using only AC, WHpR, and CI for men, and age, SD, CI, and NC for women. These equations can be used as a clinical and epidemiological tool for overweight individuals.

No abstract

No abstract

Fatty acid (FA) composition is a determinant of the physiological effects of dietary oils. This study investigated the effects of vegetable oil supplementation with different FA compositions on anthropometric and biochemical parameters in obese women on a hypocaloric diet with lifestyle modifications. Seventy-five women (body mass index, BMI, 30⁻39.9kg/m²) were randomized based on 8-week oil supplementation into four experimental groups: the coconut oil group (CoG, <i>n</i> = 18), the safflower oil group (SafG, <i>n</i> = 19), the chia oil group (ChG, <i>n</i> = 19), and the soybean oil placebo group (PG, <i>n</i> = 19). Pre- and post-supplementation weight, anthropometric parameters, and body fat (%BF), and lean mass percentages (%LM) were evaluated, along with biochemical parameters related to lipid and glycidemic profiles. In the anthropometric evaluation, the CoG showed greater weight loss (Δ% = -8.54 ± 2.38), and reduced BMI (absolute variation, Δabs = -2.86 ± 0.79), waist circumference (Δabs = -6.61 ± 0.85), waist-to-height ratio (Δabs = -0.041 ± 0.006), conicity index (Δabs = -0.03 ± 0.016), and %BF (Δabs = -2.78 ± 0.46), but increased %LM (Δabs = 2.61 ± 1.40) (<i>p</i> < 0.001). Moreover, the CoG showed a higher reduction in biochemical parameters of glycemia (Δabs = -24.71 ± 8.13) and glycated hemoglobin (Δabs = -0.86 ± 0.28) (<i>p</i> < 0.001). The ChG showed a higher reduction in cholesterol (Δabs = -45.36 ± 0.94), low-density lipoprotein cholesterol (LDLc; Δabs = -42.53 ± 22.65), and triglycerides (Δabs = -49.74 ± 26.3), but an increase in high-density lipoprotein cholesterol (HDLc; abs = 3.73 ± 1.24, <i>p</i> = 0.007). Coconut oil had a more pronounced effect on abdominal adiposity and glycidic profile, whereas chia oil had a higher effect on improving the lipid profile. Indeed, supplementation with different fatty acid compositions resulted in specific responses.

In Chinese adults, WHtR and BRI showed a superior predictive power for MetS in both sexes, which can be used as simple and effective screening tools for cardiometabolic risks and MetS in clinical practice.

Abdominal fat deposit indices, CI and ABSI, predicted CV outcomes and all-cause mortality, and were significantly associated with the inflammatory status in CKD patients.

No abstract

No abstract