血浆动脉粥样硬化指数累积暴露与 新发高血压的关系

BACKGROUND AND AIM Recent research has shown a significant association between the atherogenic index of plasma (AIP) and hypertension. Nevertheless, it remains unclear whether the cumulative exposure to AIP influence the risk of hypertension. Therefore, we aimed to characterize the relationship between cumulative exposure to AIP and the risk of new-onset hypertension in a general population. METHODS AND RESULTS A total of 28,617 individuals sourced from the Kailuan study database were included in this study. Participants were stratified into four groups by the quartiles of cumulative AIP (cumAIP) or the duration of high AIP exposure. The association between the cumulative exposure to AIP and new-onset hypertension was assessed using Cox proportional hazard models by calculating hazard ratios (HRs) and 95 % confidence intervals (95 % CIs). In addition, subgroup analysis was performed after stratification by age, sex, and body mass index (BMI). A total of 13,177 cases of hypertension were recorded during a median follow-up of 11.04 years. Compared to quartile 1, the HRs (95 % CI) of quartiles 2-4 were 1.08 (1.02-1.14), 1.16 (1.10-1.23), and 1.21 (1.13-1.28), respectively. In addition, compared to 0-year high AIP exposure, the HRs (95 % CI) of 2-6 years of high AIP exposure were 1.09 (1.04-1.14), 1.15 (1.09-1.22), and 1.18 (1.10-1.27), respectively. In addition, our results showed that the association between cumulative exposure to AIP and new-onset hypertension was stronger in participants <60 years of age than in participants ≥60 years of age, stronger in females than in males, and stronger in participants with BMI ≥28 than in participants with BMI <28. CONCLUSIONS High cumAIP is associated with a higher risk of new-onset hypertension. Maintaining appropriate levels of cumAIP is important for the prevention of hypertension.

BACKGROUND AND AIM The atherogenic index of plasma (AIP), calculated as log10 (triglyceride/high-density lipoprotein cholesterol, TG/HDL-C), has been proposed as a reliable marker for evaluating lipid-related atherosclerotic risk. However, the association between AIP and new-onset hypertension (HTN) remains controversial. This study aimed to investigate the relationship between AIP and new-onset HTN and to explore the potential mediating role of body mass index (BMI). METHODS AND RESULTS This prospective cohort study included adult participants without HTN at baseline who were enrolled from a large community-based health screening program between 2014 and 2023. Baseline clinical characteristics, anthropometric parameters, and biochemical indices were collected. Restricted cubic spline (RCS) analysis was used to determine the inflection point of AIP for grouping participants into low- and high-AIP categories. Propensity score matching (PSM) was applied to balance baseline confounders between groups. The cumulative incidence of HTN was compared using cumulative risk curves and log-rank tests. Multivariate Cox proportional hazards models were employed to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs). Mediation analysis was performed to assess whether BMI mediated the relationship between AIP and new-onset HTN. The results showed participants with higher baseline or cumulative AIP values had a significantly higher risk of developing HTN (log-rank p < 0.001). After multivariable adjustment, individuals in the high-AIP group exhibited an elevated risk of new-onset HTN (HR = 1.42, 95 % CI 1.25-1.61, p < 0.001) compared with those in the low-AIP group. BMI partially mediated the association between AIP and HTN, accounting for approximately 5.76 % of the total effect (p < 0.001). CONCLUSIONS A high AIP increased the risk of new HTN. BMI potentially mediated the association between the AIP and new-onset HTN.

ABSTRACT Background The atherogenic index of plasma (AIP) is a novel metabolic biomarker of atherosclerosis. Nevertheless, the association between the AIP and new-onset hypertension has not been elucidated in the Chinese population. Methods Prospective data were obtained from 3150 participants aged ≥ 18 years in the China Health and Nutrition Survey from 2009 to 2015. The AIP is a logarithmically transformed ratio of triglycerides to high-density lipoprotein cholesterol in molar concentration. Cox regression analysis was used to determine the association of AIP index with new-onset hypertension. Results After the six-year follow-up, 1054 (33.4%) participants developed new-onset hypertension. The participants were divided into AIP quartile groups (Q1-Q4). Compared with those in Q1, subjects in Q3–4 had nearly 1.35 times the risk of new-onset hypertension after full adjustment [Q3: hazard ratio (HR): 1.35, 95% confidence interval (CI): 1.13–1.62; Q4: HR: 1.35, 95% CI: 1.13–1.64]. The risks of new-onset hypertension were nearly 1.30 times higher in subjects in Q2–4 than in subjects in Q1 (p < .01) after the full adjustment when we excluded subjects with diabetes and/or chronic kidney diseases. There was a significant difference [HR (CI): 1.27 (1.04–1.54) vs. 0.90 (0.69–1.18)] when subjects were divided into two groups according to body mass index (BMI) level (<24 vs. ≥24 kg/m2). Conclusions The present study suggested that individuals with a higher AIP index are associated with new-onset hypertension, independent of kidney function and glucose levels. The association was stronger in subjects with normal BMI, which may provide early screening of metabolomics in hypertension prevention.

Atherosclerosis is the underlying pathology of cardiovascular disease (CVD), including hypertension. Unfortunately, the association between the atherogenic index of plasma (AIP) and hypertension has not been reported in a large‐scale middle‐aged and elderly population. This study aimed to evaluate the association between AIP and hypertension in a representative middle‐aged and elderly population in China.

Background Atherosclerosis is recognized as a potential etiological factor for hypertension. However, evidence regarding the association between the Atherogenic Index of Plasma (AIP) and hypertension in Chinese middle-aged and older adults remains limited. This study aimed to examine the association between AIP and hypertension in this population. Methods This retrospective single-center cross-sectional study consecutively enrolled 5,254 participants undergoing routine health examinations at the Health Management Center of Union Hospital Affiliated to Huazhong University of Science and Technology (Wuhan, China) between January 2017 and December 2019. Among them, 1,799 were diagnosed with hypertension and 579 with diabetes mellitus. The association between AIP and hypertension was analyzed using logistic regression and restricted cubic splines (RCS). Stratified analyses were performed by diabetes status. Furthermore, mediation analysis was conducted to evaluate the mediating effect of body mass index (BMI) on the AIP and hypertension association. Results In this cross-sectional study of 5,254 participants, a positive association was observed between the atherogenic index of plasma (AIP) and hypertension. After adjusting for multifactorial confounders, each 1-unit increment in AIP was associated with a 14% higher odds of hypertension (aOR = 1.14, 95% CI: 1.02–1.27). Mediation analysis confirmed that body mass index (BMI) partially mediated this association, accounting for 55.62% of the total effect (p < 0.001). Conclusion These findings suggest that elevated AIP is independently and positively associated with hypertension prevalence in adults aged ≥45 years, with body mass index (BMI) mediating 55.62% of this association (p < 0.001).

BACKGROUD Although both the atherogenic index of plasma (AIP) and high-sensitivity C-reactive protein (hs-CRP) are recognized as risk markers for stroke, their combined effect has yet to be fully understood. To address this gap, we introduced the inflammatory atherogenic index (IAI), a composite measure incorporating AIP and hs-CRP, and investigated its potential in predicting stroke ris METHODS: We analyzed data from the China Health and Retirement Longitudinal Study (CHARLS). IAI was calculated using the formula: IAI = AIP × hs-CRP / 10. Cox proportional hazard models were used to estimate stroke risk associated with IAI. Mediation analysis using VanderWeele's method evaluated the mediating role of systolic and diastolic blood pressures. RESULTS The study included ​​9,687 participants​​ with a mean baseline age of ​​58.66 years (SD = 9.23)​​, of whom ​​4,542 (46.9%) were male​​. Over the ​​7-year follow-up period​​, ​​662 incident stroke cases (6.8%)​​ were recorded. After adjusting for all covariates, each ​​standard deviation (SD) increase in the inflammatory atherogenic index (IAI)​​ was linked to an ​​11.0% higher stroke risk​​ (HR = 1.11, 95% CI: 1.03-1.19). A nonlinear, inverted U-shaped relationship between IAI and stroke risk was observed (P = 0.015). Mediation analysis showed that systolic and diastolic blood pressures mediated 19.64% and 25.79% of the IAI-stroke association. Hs-CRP and AIP also interacted synergistically to increase stroke risk (synergy index = 1.35, 95% CI: 1.03-1.76). CONCLUSIONS IAI is associated with increased stroke risk, with mediation by blood pressure. This highlights the potential of IAI as a biomarker for stroke risk, with early intervention in patients with high IAI potentially reducing stroke risk.

The association between remnant cholesterol (RC) and the risk of developing hypertension remains poorly elucidated. We analyzed China Health and Retirement Longitudinal Study data (CHARLS, 2011–2020). RC was categorized into baseline RC, cumulative RC, and RC change. In Cohort 1 (n = 7474), baseline RC was measured at Wave 1, with incident hypertension identified during Waves 2–5. In Cohort 2 (n = 3956), cumulative RC was calculated using Waves 1 and 3 data, with hypertension assessed during Waves 4–5. Participants were divided into quartiles. Logistic regression was used to assess the association between RC and hypertension. Restricted cubic splines explored non-linear relationships. During follow-up, 2366 (31.7%) and 805 (20.3%) hypertension cases occurred in Cohorts 1 and 2, respectively. A non-linear association was found between baseline RC and hypertension, with an inflection point at 1.16 mmol/L. The highest RC quartile showed increased hypertension risk, with adjusted odds ratios (OR) of 1.52 (p < 0.001) for baseline RC and 1.39 (p = 0.004) for cumulative RC. RC change suggested potential increased risk, though not statistically significant. BMI and HbA1c partially mediated the RC-hypertension relationship, accounting for 36.94 and 7.2% of the total effect, respectively. These findings indicate that elevated baseline and cumulative RC levels are associated with an increased risk of new-onset hypertension in middle-aged and older adults, and that baseline RC levels and hypertension are non-linearly related, with an inflection point of 1.16 mmol/L. Additionally, this study found that BMI and HbA1c mediated the association between RC and incident hypertension.

To investigate the relationships of the dynamic changes in triglyceride glucose index-body mass index (TyG‑BMI) and cumulative TyG-BMI with the risk of hypertension among middle-aged and elderly Chinese. Data were used from the China Health and Retirement Longitudinal Study (CHARLS). Participants who participated in the baseline study (2011–2012) and in subsequent surveys (2015–2018) were included in this study. The primary exposures were changes in TyG-BMI and cumulative TyG-BMI from 2012 to 2015. Changes in TyG-BMI were categorized using k-means clustering methods, while cumulative TyG-BMI was categorized into quartiles. Cox proportional hazards regression models were performed to examine the association between changes in TyG-BMI and cumulative TyG-BMI with the incidence of hypertension. Linear regression analyzes were performed to examine the association between changes in TyG-BMI and cumulative TyG-BMI with cumulative systolic blood pressure (SBP) and cumulative diastolic blood pressure (DBP). Of a total of 2,561 participants aged 56.93 ± 8.08 years old at baseline, 253 individuals (9.9%) developed hypertension during the 7-year follow-up period. The hazard ratios (HR) and 95% confidence interval (CI) for hypertension were 1.50 (1.10–2.03) for class 2 (persistently medium class) and 2.35 (1.61–3.42) for class 3 (persistently high class), compared to class 1 (persistently low class). Additionally, class 2 showed increases of 7.70 mmHg (95% CI: 5.18–10.21) in cumulative SBP and 6.53 mmHg (95% CI: 4.68–8.38) in cumulative DBP, while class 3 exhibited increases of 14.10 mmHg (95% CI: 10.56–17.64) in cumulative SBP and 12.64 mmHg (95% CI: 10.03–15.25) in cumulative DBP, compared with class 1. Regarding cumulative TyG-BMI, the HR for hypertension were 1.75 (95% CI: 1.18–2.59) for quartile 3 and 2.15 (95% CI: 1.43–3.23) for quartile 4, compared with quartile 1. In quartile 2, cumulative SBP increased by 3.99 mmHg (95% CI: 0.88–7.11) and cumulative DBP by 2.74 mmHg (95% CI: 0.45–5.02). Quartile 3 showed increases of 8.32 mmHg (95% CI: 5.09–11.54) in cumulative SBP and 7.13 mmHg (95% CI: 4.76–9.49) in cumulative DBP. Quartile 4 exhibited the highest increases, with cumulative SBP rising by 13.15 mmHg (95% CI: 9.70–16.60) and cumulative DBP by 12.20 mmHg (95% CI: 9.67–14.74). Furthermore, a linear relationship was observed between cumulative TyG-BMI and the risk of hypertension. Changes in TyG-BMI and cumulative TyG-BMI were associated with an increased risk of hypertension, as well as higher cumulative SBP and DBP in Chinese middle-aged and elderly population.

No abstract available

To explore the association between lipid storage index (LAP) and the risk of new-onset hypertension in young and middle-aged people, and to seek new indicators for the prevention and treatment of hypertension in this population. Using the prospective cohort database of the Kailuan Study, the middle-aged and young population (age <65 years) who participated in the health checkup of Kailuan Group in 2006 was selected as the research subjects, and a total of 49,738 people were included in the retrospective cohort study. LAP was calculated according to the following formula: for men LAP = [waist circumference (cm) − 64.72] × triglycerides (mmol/L), for women LAP = [waist circumference (cm) − 52.99] × triglycerides (mmol/L). According to the LAP level in 2006 (LAP2006, cm·mmol/L), the subjects were divided into four groups by quartiles: group Q1 (n = 12,443, LAP2006 < 14.75); group Q2 (n = 12,429, LAP2006 14.75 to < 25.95); group Q3 (n = 12 441, LAP2006 25.95 to <45.67); and group Q4 (n = 12 435, LAP2006 ≥ 45.67). According to the quartiles of cumulative LAP (cLAP, unit: cm·mmol/L·year) exposure level, the subjects were divided into four groups: group Q1 (n = 10,004, cLAP < 68.97); group Q2 (n = 10,005, cLAP 68.97 to >111.14); group Q3 (n = 10 005, cLAP 111.14 to <182.48); Q4 group (n = 10,005, cLAP ≥ 182.48). The cumulative incidence curves of hypertension were plotted using the Kaplan–Meier method, and the differences between groups were compared using the log-rank test. The Cox proportional hazards regression model was used to analyze the effects of different LAP and cLAP levels on the incidence of new-onset hypertension in the middle-aged and young population. During a median follow-up of 9.6 (4.0, 14.8) years, a total of 16,529 subjects (33.23%) developed new-onset hypertension. The cumulative incidence rates of new-onset hypertension in the first to fourth quartiles of LAP2006 were 24.19%, 33.43%, 40.25%, and 47.39%, respectively. After adjusting for confounding factors, Cox regression analysis showed that compared with the first quartile of LAP2006, the HRs (95% CI) for new-onset hypertension in the second, third, and fourth quartiles were 1.28 (1.22–1.35), 1.52 (1.45–1.60), and 1.66 (1.57–1.76), respectively. Compared with the first quartile of cLAP, the HRs (95% CI) for new-onset hypertension in the second, third, and fourth quartiles were 1.30 (1.21–1.39), 1.57 (1.46–1.68), and 1.86 (1.73–1.98), respectively. The increase in LAP level is associated with an increased risk of new-onset hypertension in young and middle-aged people and is an independent predictor of new-onset hypertension in young and middle-aged people.

No abstract available

Deeply involved with dyslipidemia, cardiovascular disease has becoming the leading cause of mortality since the early twentieth century in the modern world. Whose correlation with metabolic syndrome (MetS), hypertension and type 2 diabetes mellitus (T2DM) has been well established. We conducted a 9-year longitudinal study to identify the association between easily measured lipid parameters, future MetS, hypertension and T2DM by gender and age distribution. Divided into three groups by age (young age: < 40, middle age: ≥ 40 and < 65 and old age: ≥ 65), 7670 participants, receiving standard medical inspection at Tri-Service General Hospital (TSGH) in Taiwan, had been enrolled in this study. Atherogenic index of plasma (AIP) was a logarithmically transformed ratio of triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C). Through multivariate regression analyses, the hazard ratio (HR) of AIP for MetS, hypertension and T2DM were illustrated. AIP revealed significant association with all the aforementioned diseases through the entire three models for both genders. Additionally, AIP revealed significant correlation which remained still after fully adjustment in MetS, hypertension, and T2DM groups for subjects aged 40–64-year-old. Nevertheless, for participants aged above 65-year-old, AIP only demonstrated significant association in MetS group. Our results explore the promising value of AIP to determine the high-risk subjects, especially meddle-aged ones, having MetS, hypertension, and T2DM in the present and the future.

Objective: The evidence regarding the associations of circulating metabolic biomarkers with hypertension risk is scarce. We aimed to examine the associations between circulating metabolites and risk of hypertension. Methods: We included 49 422 individuals free of hypertension at baseline with a mean (SD) age of 53.5 (8.0) years from the UK Biobank. Nuclear magnetic resonance spectroscopy was used to quantify 143 individual metabolites. Multivariable-adjusted Cox regression models were used to estimate hazard ratios and 95% confidence intervals (CIs). Results: During a mean (SD) follow-up of 11.2 (1.8) years, 2686 incident hypertension cases occurred. Out of 143 metabolites, 76 were associated with incident hypertension, among which phenylalanine (hazard ratio: 1.40; 95% CI: 1.24–1.58) and apolipoprotein A1 (hazard ratio: 0.76; 95% CI: 0.66–0.87) had the strongest association when comparing the highest to the lowest quintile. In general, very-low-density lipoprotein (VLDL) particles were positively, whereas high-density lipoprotein (HDL) particles were inversely associated with risk of hypertension. Similar patterns of cholesterol, phospholipids, and total lipids within VLDL and HDL particles were observed. Triglycerides within all lipoproteins were positively associated with hypertension risk. Other metabolites showed significant associations with risk of hypertension included amino acids, fatty acids, ketone bodies, fluid balance and inflammation markers. Adding 10 selected metabolic biomarkers to the traditional hypertension risk model modestly improved discrimination (C-statistic from 0.745 to 0.752, P < 0.001) for prediction of 10-year hypertension incidence. Conclusion: Among UK adults, disturbances in metabolic biomarkers are associated with incident hypertension. Comprehensive metabolomic profiling may provide potential novel biomarkers to identify high-risk individuals.

Prior research has established a positive association between the single-measured triglyceride-glucose (TyG) index and hypertension. Nevertheless, longitudinal studies addressing the enduring impact of TyG index on incident hypertension are lacking. This study sought to explore the association between cumulative TyG index (cum-TyG) and incident hypertension, especially obesity-related hypertension (ORHT). A total of 21,017 individuals [mean (SD) age: 48.5 ± 11.7 years, male (%): 14,544 (69.2)] without hypertension were recruited from the Kailuan Study. The cum-TyG was determined by multiplying the mean TyG index by the time intervals between successive visits. Multivariable Cox regression models were used to investigate the association of cum-TyG with incident hypertension, ORHT, and non-obesity-related hypertension (NORHT). Over a median follow-up of 9.59 years, 7556 individuals developed hypertension. Among them, 1505 cases were ORHT and 6051 cases were NORHT. After controlling for potential confounders, compared to the TyG Quartile 1, the adjusted hazard ratios (HR) and 95% confidential intervals (95% CIs) for hypertension were 1.06 (0.99 to 1.13), 1.09 (1.02 to 1.17) and 1.21 (1.13 to 1.30), respectively, for TyG Quartiles 2, 3, and 4 (P for trend < 0.001). Each 1-SD rise in cum-TyG was associated with a risk of 1.08 (95% CI: 1.05 to 1.11) for overall hypertension, 1.22 (95% CI: 1.16 to 1.28) for ORHT and 1.07 (95% CI: 1.04 to 1.10) for NORHT. In addition, longer exposure to elevated TyG was significantly associated with increased hypertension risk (P for trend < 0.001). Compared to the 0-year exposure period, the risks associated with the 6-year exposure period were 1.36 (95% CI: 1.26 to 1.47), 2.86 (95% CI: 2.47 to 3.32), and 1.22 (95% CI: 1.12 to 1.33), for overall hypertension, ORHT and NORHT, respectively. Elevated TyG index accumulation is positively associated with an increased risk of developing hypertension, especially obesity-related hypertension.

Abstract Introduction: Previous studies have reported a significant relationship between the baseline Chinese visceral adipose index (CVAI) and the risk of new-onset hypertension (NOH). However, the long-term effect of the CVAI and the risk of NOH remains uncertain. This study aimed to investigate the association between the cumulative CVAI and the risk of NOH. Methods: Data were obtained from the China Health and Retirement Longitudinal Study from 2011 to 2020. In total, 2,836 Chinese participants ≥45 years were included. Multivariable logistic regression analysis as well as restricted cubic spline regression analysis were performed to assess the association of the cumulative CVAI, visceral adiposity index (VAI), and lipid accumulation product (LAP) with the risk of NOH. Furthermore, receiver operating characteristic (ROC) curve analysis was used to determine the area under the ROC curves between the risk of NOH and the adiposity indices to compare the predictive powers of the cumulative CVAI, VAI, and LAP for NOH. Results: During the 5-year follow-up period, 433 cases of NOH were recorded. The cumulative CVAI, VAI, and LAP were positively associated with the risk of NOH. After adjusting for potential confounders, as compared to the lowest quartile of the cumulative CVAI, VAI, and LAP, the participants in the highest quartile had a significantly higher risk for NOH (odds ratio = 1.74, 1.46, and 1.95; 95% confidence interval = 1.25–2.42, 1.05–2.03, and 1.39–2.75, respectively). ROC analysis revealed that the cumulative CVAI had the highest relationship with the risk of NOH. Conclusion: The cumulative CVAI was positively associated with an increased risk of NOH in middle-aged and elderly Chinese populations. In addition, the performance of the cumulative CVAI to predict NOH was superior to other visceral obesity indices. Monitoring long-term changes to the CVAI may assist with early identification of individuals at high risk of NOH.

No abstract available

No abstract available

Background Previous studies have shown a sex difference in the association between hypertension and cardiovascular disease; however, the precise mechanism remains unclear. Because there are strong associations between metabolic risk factors (MRFs) and hypertension, a sex‐specific analysis of MRFs before hypertension onset could offer new insights and expand our understanding of sex differences in cardiovascular disease. We evaluated cumulative exposure to major MRFs and rate of change of those factors, including body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, fasting plasma glucose, total cholesterol, triglycerides, and high‐density lipoprotein cholesterol among individuals who did and did not develop hypertension at follow‐up. Methods and Results We included 5374 participants (2191 men) initially without hypertension with age range of 20–50 years at baseline who participated in the Tehran Lipid and Glucose Study, and had been examined at least 3 times during the study period (1999–2018). In both sexes, the cumulative exposure to all MRFs (except for fasting plasma glucose and high‐density lipoprotein cholesterol in men) were higher in those who developed hypertension, compared with those who did not develop hypertension. However, women experienced greater cumulative exposure to major MRFs, compared with their male counterparts. Also, they experienced a faster increase in waist circumference, systolic blood pressure, diastolic blood pressure, and high‐density lipoprotein cholesterol than men. Furthermore, rapid increase in systolic blood pressure began earlier in women than men, at the age of 30 years. We also found that those men who developed hypertension experienced unfavorable change in major MRFs during young adulthood (<50 years of age). Conclusions Women exhibited more metabolic disturbances than men before onset of hypertension, which may explain the stronger impact of hypertension for major types of cardiovascular disease in women, compared with men.

No abstract available

BACKGROUND Data are limited regarding differential and common impacts of cardiovascular risk factors on subclinical changes in vascular structure and function. We aimed to examine the relationships of life-course cumulative burdens of cardiovascular risk factors with adult arterial pulse wave velocity (PWV) and carotid intima-media thickness (CIMT) in a longitudinal cohort of the Bogalusa Heart Study. METHODS The cohort consisted of 900 subjects who had aortic-femoral PWV and CIMT measurements. These participants were examined 5-16 times for body mass index (BMI), blood pressure (BP), atherogenic index of plasma (AIP) and low-density lipoprotein cholesterol (LDLC) from childhood to adulthood. The area under the curve (AUC) was calculated as a measure of long-term burden of the risk factors. RESULTS Adjusting for covariates, adult PWV was associated with AUCs of BMI, SBP and AIP (standardized regression coefficients, β = 0.191, 0.321, 0.153, respectively; P < 0.001 for all). Adult CIMT was associated with AUCs of BMI, SBP, AIP and LDLC (β = 0.115, 0.202, 0.141, 0.152, respectively; P < 0.001 for all). Moreover, childhood BMI was associated with adult PWV and CIMT (β = 0.088 and 0.075, respectively; false discovery rate, FDR q-values < 0.05 for both), and childhood LDLC with adult CIMT (β = 0.079; FDR q-value < 0.05). These associations did not differ significantly between race and sex groups. CONCLUSION The life-course cumulative burden of BMI, SBP and AIP has common impacts on arterial wall stiffening and thickening, while LDLC is specifically associated with arterial wall thickness, and this impact starts in early life.

This study aimed to explore the potential association between the triglyceride–glucose index (TyG) and the atherogenic index of plasma (AIP)—both considered surrogate markers for atherosclerosis—and major adverse cardiovascular events (MACEs) in patients diagnosed with chronic coronary syndrome (CCS). We conducted a retrospective analysis, encompassing 715 consecutive patients with intermediate CCS risk, who presented at the outpatient clinic between June 2020 and August 2022. MACEs included non-fatal myocardial infarction, hospitalization for heart failure, cerebrovascular events, non-cardiac mortality, and cardiac mortality. The primary outcome was the composite occurrence of MACEs during the follow-up period. For time-to-event analysis of the primary outcome, we employed Kaplan–Meier plots and Cox proportional hazard models. The median age of the overall study population was 55 years, with a median follow-up duration of 17 months. Multivariate Cox regression analysis identified age, hypertension, Coronary Artery Disease–Reporting and Data System score, and TyG index as independent predictors of the primary outcome. Notably, individuals with high TyG levels exhibited a significantly higher primary outcome rate compared to those with low TyG levels (18.7% vs. 3.8%, p < 0.001). Similarly, patients with elevated TyG values demonstrated statistically higher rates of cerebrovascular events, hospitalizations for heart failure, non-fatal myocardial infarctions, non-cardiac mortality, and cardiac mortality. These findings suggest that TyG may serve as a predictive marker for adverse cardiovascular outcomes in patients with CCS.

Risk prediction models are frequently used to identify individuals at risk of developing hypertension. This study evaluates different machine learning algorithms and compares their predictive performance with the conventional Cox proportional hazards (PH) model to predict hypertension incidence using survival data. This study analyzed 18,322 participants on 24 candidate features from the large Alberta’s Tomorrow Project (ATP) to develop different prediction models. To select the top features, we applied five feature selection methods, including two filter-based: a univariate Cox p-value and C-index; two embedded-based: random survival forest and least absolute shrinkage and selection operator (Lasso); and one constraint-based: the statistically equivalent signature (SES). Five machine learning algorithms were developed to predict hypertension incidence: penalized regression Ridge, Lasso, Elastic Net (EN), random survival forest (RSF), and gradient boosting (GB), along with the conventional Cox PH model. The predictive performance of the models was assessed using C-index. The performance of machine learning algorithms was observed, similar to the conventional Cox PH model. Average C-indexes were 0.78, 0.78, 0.78, 0.76, 0.76, and 0.77 for Ridge, Lasso, EN, RSF, GB and Cox PH, respectively. Important features associated with each model were also presented. Our study findings demonstrate little predictive performance difference between machine learning algorithms and the conventional Cox PH regression model in predicting hypertension incidence. In a moderate dataset with a reasonable number of features, conventional regression-based models perform similar to machine learning algorithms with good predictive accuracy.

Background and aims Recent studies have suggested an interplay between conicity index (C-index)-related diabetes risk and lipid burden. It is plausible that the atherogenic index of plasma (AIP), fatty liver, and HbA1c mediate the association between C-index and diabetes risk, though this has not been fully explored. This study explored whether AIP, fatty liver, and HbA1c mediate the relationship between C-index and diabetes risk, as well as their combined effect. Methods Data from 15,453 participants in the NAGALA Cohort were analyzed (median follow-up 5.39 years). Restricted Cubic Spline (RCS) and univariate Cox regression models adjusted for risk factors were used to assess the role of AIP in modifying the C-index-diabetes relationship. Mediation analysis assessed the contributing factors, and predictive models for diabetes were established. Results Among normoglycemic individuals, the AIP and C-index remained significantly and positively associated with diabetes risk. Higher AIP levels strengthened the C-index-diabetes association, particularly in the AIP range of 0.11-≤1.21. In the initial model, hazard ratios (HRs) for those in the fourth quartile of the C-index distribution in this group showed a significant HR of 2.22 (1.37–3.59). As fatty liver and HbA1c levels were progressively adjusted, the HRs gradually decreased, but a significant HR of 1.70 (1.05–2.76) was retained in the fully adjusted model. No significant association was observed in the other AIP strata. Furthermore, AIP, fatty liver, and HbA1c mediated the relationship between C-index and diabetes risk, with mediation effects of 9.8%, 25.0%, and 13.4%, respectively. Notably, the combined model incorporating AIP, fatty liver, HbA1c, and the C-index achieved the highest predictive performance (AUC = 0.86), outperforming the C-index alone (AUC = 0.68). Conclusions C-index was significantly associated with diabetes risk, modified by AIP, fatty liver, and HbA1c. These findings emphas ize the importance of AIP along with the C-index, particularly in the context of fatty liver and HbA1c, for diabetes risk screening and management. Supplementary Information The online version contains supplementary material available at 10.1186/s12944-025-02546-1.

The relationship between changes in Atherogenic Index of Plasma (AIP) and cardiometabolic diseases (CMD) in middle-aged and elderly individuals remains unclear. This study aims to explore the association between changes in AIP and CMD. This study included 3,791 individuals aged over 45 years from CHARLS. Participants were divided into four groups using the K-Means clustering method. Cumulative AIP was used as a quantitative indicator reflecting changes in AIP. Differences in baseline data and CMD incidence rates among these four groups were compared. Multifactorial logistic regression models were used to assess the relationship between changes in AIP and CMD, and subgroup analysis and interaction tests were conducted to evaluate potential relationships between changes in AIP and CMD across different subgroups. Restricted cubic splines (RCS) were used to assess the dose-response relationship between cumulative AIP and CMD. Changes in AIP were independently and positively associated with CMD. In males, the risk significantly increased in class4 compared to class1 (OR 1.75, 95%CI 1.12-2.73). In females, changes in AIP were not significantly associated with CMD. Cumulative AIP was positively correlated with CMD (OR 1.15, 95%CI 1.01-1.30), with significant gender differences in males (OR 1.29, 95%CI 1.07-1.55) and females (OR 1.03, 95%CI 0.87-1.23) (p for interaction = 0.042). In addition, a linear relationship was observed between cumulative AIP and CMD in male. Substantial changes in AIP may increase the risk of CMD in middle-aged and elderly Chinese males. Dynamic monitoring of AIP is of significant importance for the prevention and treatment of CMD.

The prevalence of hypertension in children and adolescents is on the rise, highlighting the need to identify effective biomarkers for risk assessment. The Atherogenic Index of Plasma (AIP), which reflects dyslipidemia, has demonstrated predictive value in adult cardiovascular diseases. However, its association with hypertension in children and adolescents remains unclear. A total of 28,844 children and adolescents from 18 prefecture-level cities in Henan Province, China, were enrolled between 2023 and 2024. After screening, 27991 participants were included in the final analysis. Blood pressure was measured on three non-consecutive days. AIP was calculated as log₁₀ (triglycerides / high-density lipoprotein cholesterol). Multivariate logistic regression, restricted cubic splines, and mediation effect analysis were employed to explore the association between AIP and hypertension. 11 types of machine learning models were constructed to evaluate the predictive value of AIP: first, the dataset was split into a training set and a testing set; variable selection was performed using the Boruta algorithm only within the training set to avoid information leakage from the testing set, and SHAP (SHapley Additive exPlanations) analysis was further conducted to interpret the role of each variable. The AIP level in the hypertensive group was significantly higher than that in the non-hypertensive group (P<0.001). After adjustment by multiple models, participants in the 4th quartile (Q4) of AIP had a 20% higher risk of hypertension compared with those in the 1st quartile (Q1) (OR=1.20, P=0.027). The association was stronger in males (Q4 HR=2.38) than in females (Q4 HR=1.76), and there was a non-linear association between AIP and hypertension (P for non-linearity=0.007). Waist-to-height ratio (WHtR) (mediation proportion: 51.7%) and uric acid (UA) (mediation proportion: 20.7%) were identified as key mediators. The LightGBM model exhibited the relatively optimal predictive performance (AUC=0.7376), and SHAP analysis confirmed that AIP had an independent predictive value for hypertension. Elevated AIP is significantly associated with an increased risk of hypertension in children and adolescents, with gender differences and non-linear characteristics observed. AIP may serve as a potential biomarker for hypertension risk assessment in this population.

Although dyslipidemia and hypertension occur together more often than can be explained by chance, few studies have carefully explored the nature of the relationship between plasma lipid levels and the risk of developing hypertension. We conducted a prospective study of 16 130 middle-aged and older female health professionals in 1992 who provided baseline blood samples and had no history of high cholesterol level (no treatment or diagnosis) or hypertension (no treatment, diagnosis, or elevated blood pressure). Plasma lipid levels were measured, and baseline risk factors were collected. Incident hypertension included a new physician diagnosis, the initiation of antihypertensive treatment, systolic blood pressure of 140 mm Hg or greater, or diastolic blood pressure of 90 mm Hg or greater. During 10.8 years of follow-up, incident hypertension developed in 4593 women. In multivariate-adjusted models, the relative risks of development of hypertension from the lowest (referent) to the highest quintile of baseline total cholesterol level were 1.00, 0.96, 1.02, 1.09, and 1.12 (P = .002 for trend); for low-density lipoprotein cholesterol level, 1.00, 0.97, 1.00, 1.02, and 1.11 (P = .053 for trend); for high-density lipoprotein cholesterol level, 1.00, 0.93, 0.87, 0.87, and 0.81 (P < .001 for trend); for non-high-density lipoprotein cholesterol level, 1.00, 1.06, 1.11, 1.12, and 1.25 (P < .001 for trend); and for the ratio of total to high-density cholesterol, 1.00, 1.10, 1.14, 1.20, and 1.34 (P < .001 for trend). Similar relative risks were noted for Adult Treatment Panel III clinical cut points and after the exclusion of obese or diabetic women. In this large prospective cohort, atherogenic dyslipidemias were associated with the subsequent development of hypertension among healthy women.

To determine the association of atherogenic index of plasma (AIP), the logarithm of molar ratio of triglyceridemia to high-density lipoprotein cholesterol (TG/HDL-cholesterol) with cardiometabolic disorders was investigated in a sample of the Turkish population. A total of 2676 middle-aged adults were prospectively evaluated with a clinical examination and laboratory tests during 7.8 years' follow-up. AIP was significantly associated in multiple linear regression analyses with greater apolipoprotein B and lower low-density lipoprotein (LDL)-cholesterol levels, reflecting the presence of smaller LDL particle size. Whereas in men insulin levels, obesity, and nonHDL-cholesterol were major determinants, C-reactive protein (CRP) was the strongest determinant of AIP among women, independent of body mass index. Top quartiles of AIP predicted significantly age-adjusted incident coronary heart disease (CHD) in both sexes, more strongly in women, in whom quartile 3 also was a predictor with a greater than 2-fold relative risk. Associations remained significant after adjustment for CRP and traditional risk factors. AIP significantly predicted diabetes and high blood pressure in both sexes after adjustment for age and CRP. With regard to incident high blood pressure, the risk ratio in men was attenuated when body mass index also was adjusted. High AIP, a surrogate of small LDL particle size, reflects obesity and hyperinsulinemia in men and high CRP status in women. It predicts CHD independently, type 2 diabetes mediated by obesity in men and in women, high blood pressure, metabolic syndrome, and CHD potentially mediated by involvement in a proinflammatory status reflected by CRP.

Remnant-like lipoprotein particle cholesterol (RLP-C) is a highly atherogenic factor. RLP-C induces endothelial dysfunction and is associated with hyperinsulinemia. This study was designed to determine whether high plasma RLP-C levels predispose to the development of hypertension in subjects with normal blood pressure (BP). A total of 1,485 subjects aged >40 years in a Japanese Cohort of the Seven Countries Study received health examinations. We examined BP, anthropometric parameters, and blood chemistries, including fasting RLP-C levels. RLP-C levels were measured by an immune-separation method. We excluded from the analysis 676 subjects who had hypertension (BP ≥ 140/90mm Hg), or were on antihypertensive medication, and/or were on antihyperlipidemic medication at baseline. Ten years later, 681 subjects were re-examined. Of 681 normotensive subjects at baseline, 303 subjects had developed hypertension 10 years later. Baseline RLP-C level was significantly higher (P < 0.01) in the subjects who developed hypertension than in those who remained normotensive (3.7±1.9 vs. 3.3±1.6mg/dl). Multivariable logistic regression analysis demonstrated that baseline RLP-C was a significant factor for incident hypertension after adjustments for homeostasis model assessment index and other hypertension-related factors (odds ratio = 1.05, 95% CI = 1.00-1.10; P = 0.04). A high level of plasma RLP-C in normotensive subjects may predispose to the development of hypertension in a population of community-dwelling Japanese.

We sought to investigate the joint association of systemic inflammation and atherogenic dyslipidemia with cardiometabolic disease (CMD) and whether the temporal relationship between them is associated with risk of CMD. This prospective cohort study included 78,206 participants without history of cardiovascular disease and diabetes mellitus at study entry in 2006. Systemic inflammation and atherogenic dyslipidemia were evaluated by C-reactive protein (CRP) and atherogenic index of plasma (AIP), respectively. Participants were categorized into six groups according to their CRP level (<1, 1-3, or ≥3 mg/L) and AIP level (<0.1 or ≥0.1). We used Cox proportional hazard regression to calculate the hazard ratios and 95% confidence intervals (CI) for incident CMD. The temporal relationship between increased CRP and elevated AIP and the association of this temporal relationship with subsequent CMD risk were assessed by cross-lagged analysis and mediation analysis in the 53,713 participants who attended the resurvey in 2010. Increased CRP and elevated AIP were additively associated with a higher risk of CMD, where participants with a CRP of ≥3 mg/L and an AIP of ≥0.1 had 64% higher risk compared with those with low CRP and AIP values (adjusted HR: 1.64, 95% CI, 1.55-1.74). In the cross-lagged analysis, the standard regression coefficient from baseline CRP to follow-up AIP was 0.069 (95% CI, 0.061-0.077), which was greater than that from baseline AIP to follow-up CRP 0.014 (95% CI, 0.005-0.023). Furthermore, in the mediation analysis, 21.52% (95% CI 17.71-25.34) of the total association between CRP and incident CMD was mediated through AIP. Systemic inflammation and atherogenic dyslipidemia were jointly associated with increased risk of CMD. Systemic inflammation might precede atherogenic dyslipidemia, and atherogenic dyslipidemia partly mediated the association between systemic inflammation and incident CMD.

This study aimed to evaluate the impact of biologic disease-modifying antirheumatic drugs (bDMARDs) and targeted synthetic DMARDs (tsDMARDs) on lipid profile and atherogenic index of plasma (AIP) in rheumatoid arthritis (RA) patients and to compare the occurrence of dyslipidemia between patients using bDMARDs, tsDMARDs, or conventional DMARDs (cDMARDs). Data on lipid profile, AIP, and occurrence of dyslipidemia were collected from the Korean College of Rheumatology BIOlogics registry. A comparison was conducted between patients using bDMARDs (tumor necrosis factor (TNF)-α inhibitor, tocilizumab, abatacept), Janus kinase inhibitors (JAKis), and cDMARDs. The Kaplan-Meier method was used to compare the occurrence of dyslipidemia between groups, and hazard ratios (HR) were calculated using the cox proportional hazard method. The data of 917, 826, 789, 691, and 520 RA patients were eligible for analysis at the baseline, 1-year, 2-year, 3-year, and 4-year follow-ups, respectively. Baseline total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were higher in the cDMARDs group, whereas AIP was comparable. During the 4-year follow-up, AIP was comparable between the groups. The occurrence of dyslipidemia did not show a significant difference when comparing the bDMARDs/tsDMARDs and cDMARDs groups (P=0.06) or the TNF-α inhibitor, tocilizumab, abatacept, JAKi, and cDMARD user groups (P=0.3). In the multivariate cox proportional hazard model, older age (HR=1.03, P=0.005) and concomitant hypertension (HR=2.21, P=0.013) were significantly associated with dyslipidemia occurrence. Long-term use of bDMARDs and tsDMARDs is relatively safe with regard to lipid profile, AIP, and the occurrence of dyslipidemia in RA patients. Key Points • The use of bDMARDs and tsDMARDs did not increase the risk of dyslipidemia than cDMARDs use in patients with RA. • AIP was comparable between bDMARDs user, tsDMARDs user, and cDMARDs user group in 4-year follow-up data. • Based on the present study, the long-term use of bDMARDs or tsDMARDs did not significantly deteriorate atherogenic lipid profile nor an increased risk of dyslipidemia in patients with RA.

Cumulative lipid profile burden is designed to dynamically measure lipid accumulation, and its effect on hypertension has been poorly studied. Our main purpose was to investigate the effect of cumulative lipid profile burden on the incidence of essential hypertension (EH) and to investigate whether cumulative lipid burden mediates the pathogenesis of the effects of diet and obesity on EH. A total of 1295 participants were included in the study, which started in 2017. The average follow-up time was 2.98 years. A total of 240 EH patients occurred during the follow-up period. The HR (95% CI) of the highest quartile in cumulative Total cholesterol (TC), triglyceride (TG) and high density lipoprotein (HDL) burden were 1.747 (1.145 - 2.664), 1.502 (1.038 - 2.173), 0.615 (0.413 - 0.917) for incidence of EH respectively, compared to the respective reference groups. Participants with EH consumed more red meat and refined grains, and red meat was positively associated with cumulative TC burden. BMI and Waist-To-Height Ratio (WHtR) increased the incidence of EH, and obesity was positively correlated with cumulative TG burden. Mediating analysis showed that cumulative TG had a partial mediating effect in the causal relationship between obesity and EH, and Mendelian randomization (MR) also proved this result. Diet was not found to influence EHn through cumulative lipid profile burden. The cumulative TG burden partially mediates the effect of obesity on EH.

The atherogenic index of plasma (AIP) and cardiovascular disease (CVD) in participants with abnormal glucose metabolism have been linked in previous studies. However, it was unclear whether AIP control level affects the further CVD incidence among with diabetes and pre-diabetes. Therefore, our study aimed to investigate the association between AIP control level with risk of CVD in individuals with abnormal glucose metabolism. Participants with abnormal glucose metabolism were included from the China Health and Retirement Longitudinal Study. CVD was defined as self-reporting heart disease and/or stroke. Using k-means clustering analysis, AIP control level, which was the log-transformed ratio of triglyceride to high-density lipoprotein cholesterol in molar concentration, was divided into five classes. The association between AIP control level and incident CVD among individuals with abnormal glucose metabolism was investigated multivariable logistic regression analysis and application of restricted cubic spline analysis. 398 (14.97%) of 2,659 participants eventually progressed to CVD within 3 years. After adjusting for various confounding factors, comparing to class 1 with the best control of the AIP, the OR for class 2 with good control was 1.31 (95% CI, 0.90-1.90), the OR for class 3 with moderate control was 1.38 (95% CI, 0.99-1.93), the OR for class 4 with worse control was 1.46 (95% CI, 1.01-2.10), and the OR for class 5 with consistently high levels was 1.56 (95% CI, 1.03-2.37). In restricted cubic spline regression, the relationship between cumulative AIP index and CVD is linear. Further subgroup analysis demonstrated that the similar results were observed in the individuals with agricultural Hukou, history of smoking, diastolic blood pressure ≥ 80mmHg, and normal body mass index. In addition, there was no interaction between the AIP control level and the subgroup variables. In middle-aged and elderly participants with abnormal glucose metabolism, constant higher AIP with worst control may have a higher incidence of CVD. Monitoring long-term AIP change will contribute to early identification of high risk of CVD among individuals with abnormal glucose metabolism.

Objective: Inflammation and atherogenic dyslipidemia promote each other establishing a vicious circle. This study aimed to examine their joint association with cardiometabolic disease (CMD) and whether the temporal relationship between them is associated with risk of CMD. Design and method: This study included 78,211 participants without history of cardiovascular disease and diabetes mellitus at baseline in 2006. We categorized the participants into six groups according to their C-reactive protein (CRP, <1,1–3, or >=3 mg/L) level and atherogenic index of plasma (AIP, <-0.08 or >=-0.08). Incident CMD was defined as the first occurrence of a CMD event during follow-up, including cardiovascular disease (including myocardial infarction, coronary revascularization, heart failure, ischemic stroke, and hemorrhagic stroke) and type 2 diabetes mellitus (T2DM). Cox regression models were used to estimate the risk of CMD across CRP-AIP groups. The temporal relationship between CRP and AIP was assessed by cross-lagged analysis in the 53,715 participants who attended the resurvey in 2010. The association of this temporal relationship with subsequent CMD risk was examined by mediation analysis. Results: After adjusting for potential confounders, increased CRP and elevated AIP were cumulatively associated with a higher risk of CMD, where participants with a CRP of >=3 mg/L and an AIP of >=-0.08 had a hazard ratio of 1.63 (95% confidence interval [CI], 1.55–1.71) for CMD, 1.43 (95% CI, 1.33-1.55) for cardiovascular disease, and 1.71 (95% CI, 1.60-1.82) for T2DM, compared with those with low CRP and AIP values. (Table 1). In cross-lagged analysis, the standard regression coefficient from baseline CRP to follow-up AIP was greater than that from baseline AIP to follow-up CRP (0.069 [95% CI, 0.061–0.077] versus 0.014 [95% CI, 0.005–0.023], P difference <0.001) (Table 2). Furthermore, AIP partially mediated the effect of CRP on incident CMD. The mediation effect was 15.56% (95% CI, 12.87–18.25) for CMD, 10.03% (95% CI, 6.19–13.88) for cardiovascular disease, and 18.82% (95% CI, 15.36–22.28) for T2DM (Figure 1). Conclusions: CRP and AIP were additively associated with risk of CMD. Increased CRP might precede elevated AIP, and AIP partially mediated the association between CRP and incident CMD.

BACKGROUND AND AIMS The atherogenic index of plasma (AIP) has been linked to hypertension in general populations. However, the existing evidence concerning its association with preeclampsia risk remains limited. This study aimed to assess the relationship between first-trimester AIP level and preeclampsia risk. METHODS 6028 singleton pregnant women from a birth cohort, all under 14 weeks of gestation and without a history of hypertension, were included. AIP was calculated as log10 (triglycerides/high-density lipoprotein cholesterol). Generalized linear models and restricted cubic spline regression were utilized to estimate the associations between AIP and preeclampsia risk. A random forest model was employed to determine the relative importance of parameters for predicting preeclampsia risk. RESULTS 235 (3.90%) incident preeclampsia cases were confirmed. A linear relationship was found between AIP and preeclampsia risk, and each 1-standard deviation increase in AIP was associated with a 21% higher risk of preeclampsia (RR: 1.21, 95% CI: 1.06-1.38). A significant interaction was identified between AIP and uric acid (UA) level (P for interaction = 0.009). Elevated AIP was linked to an increased preeclampsia risk (RR: 1.32, 95% CI: 1.13-1.54) when UA level exceeded 198 μmol/L, and the highest combined level indicated the greatest risk. Moreover, AIP was identified as the strongest predictor among all variables in the prediction model. CONCLUSIONS Elevated first-trimester AIP was associated with an increased preeclampsia risk, particularly at the higher UA level. These findings highlight the clinical significance of pro-atherogenic dyslipidemia as both a risk marker and a potential target for early screening in preeclampsia prevention strategies.