Regional and socio-demographic variation in laboratory-based predictions of 10-year cardiovascular disease risk among adults in north and south India.

OBJECTIVE: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in India. There is no laboratory-based CVD risk data among Indians from different regions and backgrounds. This study estimated laboratory-based 10-year CVD risk across different population sub-groups. METHODS: Data from UDAY derived from cross-sectional surveys of rural and urban populations of northern (Haryana) and southern (Andhra Pradesh) India were analysed. World Health Organization/International Society of Hypertension laboratory-based equations calculated 10-year CVD risk among participants without CVD history. Wilcoxon rank sum test analyzed average CVD risk across subgroups. Chi-square test compared population proportions in different CVD risk categories. Regression analysis assessed the association between CVD risk and participant characteristics. RESULTS: The mean (SD) age of the participants (n = 8448) was 53.2 (9.2) years. Males in Haryana had increased CVD risk compared to those in Andhra Pradesh (p < 0.01). In both states, female gender was shown to have a protective effect on CVD risk (p < 0.01). Age correlated with increased risk (p < 0.01). Education level did not affect CVD risk however employment status may have. Hypertension, diabetes, hyperlipidemia, smoking, and insufficient exercise were associated with increased CVD risk (p < 0.01). Residence (urban versus rural) and wealth index did not largely affect CVD risk. CONCLUSION: Minor differences exist in the distribution of laboratory-based CVD risk across Indian population cohorts. CVD risk was similar in urban wealthy participants and rural poor and working-class communities in northern and southern India. Public health efforts need to target all major segments of the Indian population to curb the CVD epidemic.

Rationale, Design and Baseline Characteristics of a Randomized Controlled Trial of a Cardiovascular Quality Improvement Strategy in India: The C-QIP Trial.

BACKGROUND: Quality of chronic care for cardiovascular disease (CVD) remains suboptimal worldwide. The Collaborative Quality ImProvement (C-QIP) trial aims to develop and test the feasibility and clinical effect of a multicomponent strategy among patients with prevalent CVD in India. METHODS: The C-QIP is a clinic-based, open randomized trial of a multicomponent intervention versus usual care that was locally developed and adapted for use in Indian settings through rigorous formative research guided by Consolidated Framework for Implementation Research (CFIR). The C-QIP intervention consisted of 5 components: 1) electronic health records and decision support system for clinicians, 2) trained non-physician health workers (NPHW), 3) text-message based lifestyle reminders, 4) patient education materials, 5) quarterly audit and feedback reports. Patients with CVD (ischemic heart disease, ischemic stroke, or heart failure) attending outpatient CVD clinics were recruited from September 2022 to September 2023 and were randomized to the intervention or usual care arm for at least 12 months follow-up. The co-primary outcomes are implementation feasibility, fidelity (i.e., dose delivered and dose received), acceptability, adoption and appropriateness, measured at multiple levels: patient, provider and clinic site-level, The secondary outcomes include prescription of guideline directed medical therapy (GDMT) (provider-level), and adherence to prescribed therapy, change in mean blood pressure (BP) and LDL-cholesterol between the intervention and control groups (patient-level). In addition, a trial-based process and economic evaluations will be performed using standard guidelines. RESULTS: We recruited 410 socio-demographically diverse patients with CVD from four hospitals in India. Mean (SD) age was 57.5 (11.7) years, and 73.0% were males. Self-reported history of hypertension (48.5%) and diabetes (41.5%) was common. At baseline, mean (SD) BP was 127.9 (18.2) /76.2 (11.6) mm Hg, mean (SD) LDLc: 80.3 (37.3) mg/dl and mean (SD) HbA1c: 6.8% (1.6%). At baseline, the GDMT varied from 62.4% for patients with ischemic heart disease, 48.6% for ischemic stroke and 36.1% for heart failure. CONCLUSION: This study will establish the feasibility of delivering contextually relevant, and evidence-based C-QIP strategy and assess whether it is acceptable to the target populations. The study results will inform a larger scale confirmatory trial of a comprehensive CVD care model in low-resource settings. TRIAL REGISTRATION: Clinical Trials Registry India: CTRI/2022/04/041847; Clinicaltrials.gov number: NCT05196659.

Novel genomic variants related to visceral adiposity index (VAI) and body adiposity index (BAI) in Indian sib-pairs.

BACKGROUND: Obesity is among the leading public health threats globally. Over the last few years, visceral adiposity index (VAI), and body adiposity index (BAI), derived from anthropometric, and biochemical measures, have gained importance as a measure of obesity. However, unlike other common indices like body mass index, and waist circumference, the genetic predisposition of VAI, and BAI under-examined. METHODS: 2265 sib-pairs from Indian Migration Study were used for examining the association of genetic variants from the Cardio-Metabochip array with VAI, and BAI. Mixed linear regression models were run, and all inferences were based on the within-sib component of the Fulker's association models. Gene-environment/lifestyle interaction analyses were also undertaken. RESULTS: rs6659428 at LOC400796 | SEC16B (ß = 0.26, SE = 0.05), and rs7611535 at DRD3 | LOC645180 (ß = 0.18, SE = 0.04) were associated with VAI at suggestive significance value of <8.21 × 10-6. For BAI, rs73300702 at JAZF1-AS1 (ß = 0.27, SE = 0.06), was the top hit at p value < 8.21 × 10-6. Further, rs6659428 showed marginal effect modification with rural/urban location (ß = 0.26, SE = 0.13, p value = 0.047), and rs73300702 with physical activity (ß = -0.29,SE = 0.14, p value = 0.034). CONCLUSION: We report three novel genetic loci for VAI, and BAI in Indians that are important indicators of adiposity. These findings need to be replicated and validated with larger samples from different ethnicities. Further, functional studies for understanding the biological mechanisms of these adiposity indices need to be undertaken to understand the underlying pathophysiology.

Ambient air pollution and daily mortality in ten cities of India: a causal modelling study.

BACKGROUND: The evidence for acute effects of air pollution on mortality in India is scarce, despite the extreme concentrations of air pollution observed. This is the first multi-city study in India that examines the association between short-term exposure to PM2·5 and daily mortality using causal methods that highlight the importance of locally generated air pollution. METHODS: We applied a time-series analysis to ten cities in India between 2008 and 2019. We assessed city-wide daily PM2·5 concentrations using a novel hybrid nationwide spatiotemporal model and estimated city-specific effects of PM2·5 using a generalised additive Poisson regression model. City-specific results were then meta-analysed. We applied an instrumental variable causal approach (including planetary boundary layer height, wind speed, and atmospheric pressure) to evaluate the causal effect of locally generated air pollution on mortality. We obtained an integrated exposure-response curve through a multivariate meta-regression of the city-specific exposure-response curve and calculated the fraction of deaths attributable to air pollution concentrations exceeding the current WHO 24 h ambient PM2·5 guideline of 15 µg/m3. To explore the shape of the exposure-response curve at lower exposures, we further limited the analyses to days with concentrations lower than the current Indian standard (60 µg/m3). FINDINGS: We observed that a 10 µg/m3 increase in 2-day moving average of PM2·5 was associated with 1·4% (95% CI 0·7-2·2) higher daily mortality. In our causal instrumental variable analyses representing the effect of locally generated air pollution, we observed a stronger association with daily mortality (3·6% [2·1-5·0]) than our overall estimate. Our integrated exposure-response curve suggested steeper slopes at lower levels of exposure and an attenuation of the slope at high exposure levels. We observed two times higher risk of death per 10 µg/m3 increase when restricting our analyses to observations below the Indian air quality standard (2·7% [1·7-3·6]). Using the integrated exposure-response curve, we observed that 7·2% (4·2%-10·1%) of all daily deaths were attributed to PM2·5 concentrations higher than the WHO guidelines. INTERPRETATION: Short-term PM2·5 exposure was associated with a high risk of death in India, even at concentrations well below the current Indian PM2·5 standard. These associations were stronger for locally generated air pollutants quantified through causal modelling methods than conventional time-series analysis, further supporting a plausible causal link. FUNDING: Swedish Research Council for Sustainable Development.

Potential Mediating Role of Iron Biomarkers in the Association of Sex With Glucose, Insulin, and Type 2 Diabetes.

Context: Sex-specific prevalence and incidence of type 2 diabetes (T2D) have been reported, but the underlying mechanisms are uncertain. Objective: In this study, we aimed to investigate whether iron biomarkers mediate the association between biological sex and glucose metabolism and the incidence of T2D. Methods: We used data from the general population enrolled in the prospective Prevention of REnal and Vascular ENd-stage Disease study in Groningen, The Netherlands. We measured ferritin, transferrin saturation (TSAT), hepcidin, soluble transferrin receptor (sTfR), fasting plasma glucose (FPG), fasting plasma insulin (FPI) levels, and incidence of T2D. We used multivariable regression and mediation analyses to investigate our hypothesis. All iron biomarkers, FPG, and FPI were log-transformed. Results: The mean (SD) age of the 5312 (51.3% female) individuals was 52.2 (11.6) years. Compared with males, females had lower FPG (ß = -.01; 95% CI -0.02, -0.01) and FPI (ß = -.03; 95% CI -0.05, -0.02) levels. Ferritin, hepcidin, and sTfR showed potential mediating effects on the association between sex and FPG, 21%, 5%, and 7.1%, respectively. Furthermore, these variables mediated 48.6%, 5.7%, and 3.1% of the association between sex and FPI, respectively. Alternatively, TSAT had a suppressive mediating role in the association of sex with FPG and FPI. The incidence of T2D was lower in females than in males (hazard ratio 0.58; 95% CI 0.44, 0.77), with 19.2% of this difference being mediated by ferritin. Conclusion: Iron biomarkers may partially mediate the association between sex and glucose homeostasis. Future studies addressing the causality of our findings are needed.

Establishing Apolipoprotein-B and non-high-density-lipoprotein-C goals in Indian population: A Cross-sectional study.

BACKGROUND: Defining lipid goals solely on low-density lipoprotein-cholesterol (LDL-C) levels in Indian population may cause misclassification due to high prevalence of hypertriglyceridemia and small dense LDL-C particles. International guidelines now recommend Apoliporotein-B (Apo-B) and non-high-density lipoprotein-cholesterol (non-HDL-C) levels as alternative targets. In this study, we used a cross-sectional representative population database to determine Apo-B and non-HDL-C cut-offs corresponding to identified LDL-C targets and compared them to international guidelines. METHODS: A community-based survey carried out in urban Delhi and adjacent rural Ballabhgarh provided lipid values for 3047 individuals. The Spearman correlation coefficient was used to evaluate the degree of relationship between Apo-B and LDL-C and non-HDL-C. Cut-off values for Apo-B and non-HDL-C were established using receiver operator curve analysis correlating with guideline-recommended LDL-C targets. RESULTS: Spearman's rank correlations between Apo-B and LDL-C (0.82) and non-HDL-C and LDL-C (0.93) were significant (p < 0.05). Proposed corresponding cut-off values for LDL-C of 55, 70,100,130 and 160 mg/dl for Apo-B and non-HDL-C in our population were 75.3, 75.5, 91.3, 107.6, 119.4 mg/dL and 92.5,96.5, 123.5, 154.5, 179.5 mg/dL respectively. However, in those with triglycerides >150 mg/dl the corresponding Apo-B and non-HDL-C values were 85.1, 92.7, 103.5, 117.5 and 135 mg/dL and 124.5, 126.5, 147.5, 167.5 and 190.5 mg/L respectively. CONCLUSION: Based on this study we provide Apo-B and non-HDL cut-offs corresponding to target LDL-C values in Indian patients with and without high triglycerides. It is noted that in individuals with triglycerides ≥ 150 mg/dl, the Apo-B levels are much higher than the values recommended by guidelines.

Development of a risk prediction model for postpartum onset of type 2 diabetes mellitus, following gestational diabetes; the lifestyle InterVention in gestational diabetes (LIVING) study.

AIMS: This study aimed to develop a prediction model for identifying a woman with gestational diabetes mellitus (GDM) at high risk of type 2 diabetes (T2DM) post-birth. METHODS: Utilising data from 1299 women in the Lifestyle Intervention IN Gestational Diabetes (LIVING) study, two models were developed: one for pregnancy and another for postpartum. Key predictors included glucose test results, medical history, and biometric indicators. RESULTS: Of the initial cohort, 124 women developed T2DM within three years. The study identified seven predictors for the antenatal T2DM risk prediction model and four for the postnatal one. The models demonstrated good to excellent predictive ability, with Area under the ROC Curve (AUC) values of 0.76 (95% CI: 0.72 to 0.80) and 0.85 (95% CI: 0.81 to 0.88) for the antenatal and postnatal models, respectively. Both models underwent rigorous validation, showing minimal optimism in predictive capability. Antenatal model, considering the Youden index optimal cut-off point of 0.096, sensitivity, specificity, and accuracy were measured as 70.97%, 70.81%, and 70.82%, respectively. For the postnatal model, considering the cut-off point 0.086, sensitivity, specificity, and accuracy were measured as 81.40%, 75.60%, and 76.10%, respectively. CONCLUSIONS: These models are effective for predicting T2DM risk in women with GDM, although external validation is recommended before widespread application.

Effect of a multicomponent quality improvement strategy on sustained achievement of diabetes care goals and macrovascular and microvascular complications in South Asia at 6.5 years follow-up: Post hoc analyses of the CARRS randomized clinical trial.

BACKGROUND: Diabetes control is poor globally and leads to burdensome microvascular and macrovascular complications. We aimed to assess post hoc between-group differences in sustained risk factor control and macrovascular and microvascular endpoints at 6.5 years in the Center for cArdiovascular Risk Reduction in South Asia (CARRS) randomized trial. METHODS AND FINDINGS: This parallel group individual randomized clinical trial was performed at 10 outpatient diabetes clinics in India and Pakistan from January 2011 through September 2019. A total of 1,146 patients with poorly controlled type 2 diabetes (HbA1c ≥8% and systolic BP ≥140 mm Hg and/or LDL-cholesterol ≥130 mg/dL) were randomized to a multicomponent quality improvement (QI) strategy (trained nonphysician care coordinator to facilitate care for patients and clinical decision support system for physicians) or usual care. At 2.5 years, compared to usual care, those receiving the QI strategy were significantly more likely to achieve multiple risk factor control. Six clinics continued, while 4 clinics discontinued implementing the QI strategy for an additional 4-year follow-up (overall median 6.5 years follow-up). In this post hoc analysis, using intention-to-treat, we examined between-group differences in multiple risk factor control (HbA1c <7% plus BP <130/80 mm Hg and/or LDL-cholesterol <100 mg/dL) and first macrovascular endpoints (nonfatal myocardial infarction, nonfatal stroke, death, revascularization [angioplasty or coronary artery bypass graft]), which were co-primary outcomes. We also examined secondary outcomes, namely, single risk factor control, first microvascular endpoints (retinopathy, nephropathy, neuropathy), and composite first macrovascular plus microvascular events (which also included amputation and all-cause mortality) by treatment group and whether QI strategy implementation was continued over 6.5 years. At 6.5 years, assessment data were available for 854 participants (74.5%; n = 417 [intervention]; n = 437 [usual care]). In terms of sociodemographic and clinical characteristics, participants in the intervention and usual care groups were similar and participants at sites that continued were no different to participants at sites that discontinued intervention implementation. Patients in the intervention arm were more likely to exhibit sustained multiple risk factor control than usual care (relative risk: 1.77; 95% confidence interval [CI], 1.45, 2.16), p < 0.001. Cumulatively, there were 233 (40.5%) first microvascular and macrovascular events in intervention and 274 (48.0%) in usual care patients (absolute risk reduction: 7.5% [95% CI: -13.2, -1.7], p = 0.01; hazard ratio [HR] = 0.72 [95% CI: 0.61, 0.86]), p < 0.001. Patients in the intervention arm experienced lower incidence of first microvascular endpoints (HR = 0.68 [95% CI: 0.56, 0.83), p < 0.001, but there was no evidence of between-group differences in first macrovascular events. Beneficial effects on microvascular and composite vascular outcomes were observed in sites that continued, but not sites that discontinued the intervention. CONCLUSIONS: In urban South Asian clinics, a multicomponent QI strategy led to sustained multiple risk factor control and between-group differences in microvascular, but not macrovascular, endpoints. Between-group reductions in vascular outcomes at 6.5 years were observed only at sites that continued the QI intervention, suggesting that practice change needs to be maintained for better population health of people with diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT01212328.

Effect of Yoga-Based Cardiac Rehabilitation Program on Endothelial Function, Oxidative Stress, and Inflammatory Markers in Acute Myocardial Infarction: A Randomized Controlled Trial.

Aims: The aim of this study was to evaluate the effects of yoga-based cardiac rehabilitation (Yoga-CaRe) on the endothelial system, oxidative stress, and inflammatory markers in patients with acute myocardial infarction (MI). Methods: A sub-study was conducted in two clinical sites of the Yoga-CaRe trial (a multicenter randomized controlled trial). Participants with acute MI were randomized and allocated to either the Yoga-CaRe program (13 sessions with encouragement to home practice) or enhanced standard care (three educational sessions). Endothelial function, oxidative stress, and inflammatory biomarkers were assessed using biomarkers such as asymmetric dimethylarginine (ADMA), endothelial nitric oxide synthase (eNOS), endothelin-1 (ET-1), E-selectin, P-selectin, vascular cell adhesion molecule (VCAM), intercellular cell-adhesion molecule-1, total nitric oxide concentration (NOx), oxidized low-density lipoprotein (Oxd-LDL), superoxide dismutase, total antioxidant capacity (TAOC), tumor necrosis factor-alpha (TNFα), and C-reactive protein (CRP) at baseline and 12 weeks. Laboratory and statistical analysis were done by staff blinded to group allocation. Results: Eighty-two patients (of the 110 patients recruited) completed the study. The mean age was 53.1 ± 10.6 and 51.9 ± 10.7 years in enhanced standard care and Yoga-CaRe group, respectively. At 12 weeks, Yoga-CaRe significantly reduced ADMA, ET-1, and ICMA-1 than the enhanced standard care group. Although E-selectin and VCAM at 12 weeks were reduced in both groups, enhanced standard care had a significantly higher reduction than the Yoga-CaRe group. Among markers of oxidative stress, TAOC increased in the Yoga-CaRe group. We found no difference in eNOS, NOx, P-selectin, TNFα, CRP, and Oxd-LDL between the two groups. Conclusion: Yoga-CaRe improved the endothelial function (through a reduction in ET-1 and modulating adhesion molecules) and enhanced antioxidant capacity.

Antenatal oral glucose tolerance test abnormalities in the prediction of future risk of postpartum diabetes in women with gestational diabetes: Results from the LIVING study.

OBJECTIVES: To explore associations between type and number of abnormal glucose values on antenatal oral glucose tolerance test (OGTT) with postpartum diabetes in South Asian women diagnosed with gestational diabetes (GDM) using International Association of the Diabetes and Pregnancy Study Groups criteria. METHODS: This post-hoc evaluation of the Lifestyle Intervention IN Gestational Diabetes (LIVING) study, a randomized controlled trial, was conducted among women with GDM in the index pregnancy, across 19 centers in Bangladesh, India, and Sri Lanka. Postpartum diabetes (outcome) was defined on OGTT, using American Diabetes Association (ADA) criteria. RESULTS: We report data on 1468 women with GDM, aged 30.9 (5.0) years, and with median (interquartile range) follow-up period of 1.8 (1.4-2.4) years after childbirth following the index pregnancy. We found diabetes in 213 (14.5%) women with an incidence of 8.7 (7.6-10.0)/100 women-years. The lowest incidence rate was 3.8/100 women years, in those with an isolated fasting plasma glucose (FPG) abnormality, and highest was 19.0/100 women years in participants with three abnormal values. The adjusted hazard ratios for two and three abnormal values compared to one abnormal value were 1.73 (95% confidence interval [CI], 1.18-2.54; p = .005) and 3.56 (95% CI, 2.46-5.16; p < .001) respectively. The adjusted hazard ratio for the combined (combination of fasting and postglucose load) abnormalities was 2.61 (95% CI, 1.70-4.00; p < .001), compared to isolated abnormal FPG. CONCLUSIONS: Risk of diabetes varied significantly depending upon the type and number of abnormal values on antenatal OGTT. These data may inform future precision medicine approaches such as risk prediction models in identifying women at higher risk and may guide future targeted interventions.

Greater Disease Severity and Worse Clinical Outcomes in Patients Hospitalised with COVID-19 in Africa.

Background: COVID-19 cardiovascular research from Africa is limited. This study describes cardiovascular risk factors, manifestations, and outcomes of patients hospitalised with COVID-19 in the African region, with an overarching goal to investigate whether important differences exist between African and other populations, which may inform health policies. Methods: A multinational prospective cohort study was conducted on adults hospitalised with confirmed COVID-19, consecutively admitted to 40 hospitals across 23 countries, 6 of which were African countries. Of the 5,313 participants enrolled globally, 948 were from African sites (n = 9). Data on demographics, pre-existing conditions, clinical outcomes in hospital (major adverse cardiovascular events (MACE), renal failure, neurological events, pulmonary outcomes, and death), 30-day vitality status and re-hospitalization were assessed, comparing African to non-African participants. Results: Access to specialist care at African sites was significantly lower than the global average (71% vs. 95%), as were ICU admissions (19.4% vs. 34.0%) and COVID-19 vaccination rates (0.6% vs. 7.4%). The African cohort was slightly younger than the non-African cohort (55.0 vs. 57.5 years), with higher rates of hypertension (48.8% vs. 46.9%), HIV (5.9% vs. 0.3%), and Tuberculosis (3.6% vs. 0.3%). In African sites, a higher proportion of patients suffered cardiac arrest (7.5% vs. 5.1%) and acute kidney injury (12.7% vs. 7.2%), with acute kidney injury (AKI) appearing to be one of the strongest predictors of MACE and death in African populations compared to other populations. The overall mortality rate was significantly higher among African participants (18.2% vs. 14.2%). Conclusions: Overall, hospitalised African patients with COVID-19 had a higher mortality despite a lower mean age, contradicting literature that had previously reported a lower mortality attributed to COVID-19 in Africa. African sites had lower COVID-19 vaccination rates and higher AKI rates, which were positively associated with increased mortality. In conclusion, African patients were hospitalized with more severe COVID-19 cases and had poorer outcomes.

Pancreatic Beta Cell Function in Infants Varies by Maternal Weight.

The Asian Indian Beta Cell function (ABCs) in Infants Study examined the associations of maternal weight on infant pancreatic beta cell function across 7 months postpartum. Pregnant women aged 18-35 years were recruited in Hyderabad, India. Women were classified by first trimester weight as underweight (UW), BMI < 18.5 kg/m2; normal weight (NW), BMI 18.5-22.9 kg/m2; or overweight (OW), BMI 23.0 through <28.5 kg/m2. At age > 7 months, infants had an oral glucose tolerance test (OGTT, 1.75 g glucose/kg bodyweight) following a 3 h fast. Infant blood samples were assayed for C-peptide and glucose. Infant beta cell function (HOMA2-B; disposition index, DI) and insulin resistance (HOMA2-IR) were compared across maternal weight groups. Mothers (UW n = 63; NW n = 43; OW n = 29) had similar age at delivery and second trimester 50 g glucose challenge test results. Cord HOMA2-B values were 51% greater for IUW (83.5, SD 55.2) and 44% greater for IOW (79.9, SD 60.8) vs. INW (55.4, SD 51.5), forming a U-shaped relationship between maternal weight and HOMA2-B. No qualitative differences in HOMA2-IR were found at birth. However, at 7 months postpartum, HOMA2-IR changed most within IUW (-64% median reduction) and changed the least in IOW (-7% median reduction). At seven months postpartum, DI was higher in IUW vs. the other groups (geometric mean IUW 1.9 SD 2.5; INW 1.3 SD 2.6 or vs. IOW mean 1.2 SD 3.7), reflecting a +49% difference in DI. Evidence from this study illustrates adaptations in the pancreatic functional response of infants associated with the maternal nutritional environment.

Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities.

Background: Exposure to ambient PM2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM2.5 and distinct lipid profiles, is sparse. Methods: Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders. Results: The mean annual exposure in Chennai and Delhi was 40 and 102 µg/m3 respectively. Elevated ambient PM2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m3 in both cities and beyond 125 µg/m3 in Delhi. TRIG levels in Chennai increased until 40 µg/m3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m3 in Delhi. Conclusion: These findings demonstrate diverse associations between a wide range of ambient PM2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

Apolipoprotein B - An ideal biomarker for atherosclerosis?

This review article describes the pathophysiological mechanisms linking Apolipoprotein B (Apo-B) and atherosclerosis, summarizes the existing evidence on Apo B as a predictor of atherosclerotic cardiovascular disease and recommendations of (inter)national treatment guidelines regarding Apo B in dyslipidemia management. A single Apo B molecule is present in every particle of very low-density lipoprotein, intermediate density lipoprotein, low density lipoprotein, and lipoprotein(a). This unique single Apo B per particle ratio makes plasma Apo B concentration a direct measure of the number of circulating atherogenic lipoproteins. This review of global evidence on Apo B as a biomarker for atherosclerosis confirms that Apo B is a single atherogenic lipid marker present in all lipids sub-fractions except HDL-C, and thus, Apo B integrates and extends the information from triglycerides and cholesterol, which could simplify and improve care for atherosclerotic cardiovascular disease.

Natural History of Type 2 Diabetes in Indians: Time to Progression.

OBJECTIVE: To describe the natural history of diabetes in Indians. RESEARCH DESIGN AND METHODS: Data are from participants older than 20 years in the Centre for Cardiometabolic Risk Reduction in South Asia longitudinal study. Glycemic states were defined per American Diabetes Association criteria. Markov models were used to estimate annual transition probabilities and sojourn time through states. RESULTS: Among 2,714 diabetes-free participants, 641 had isolated impaired fasting glucose (iIFG), and 341 had impaired glucose tolerance (IGT). The annual transition to diabetes for those with IGT was 13.9% (95% CI 12.0, 15.9) versus 8.6% (7.3, 9.8) for iIFG. In the normoglycemia ↔ iIFG → diabetes model, mean sojourn time in normoglycemia was 40.3 (34.6, 48.2) years, and sojourn time in iIFG was 9.7 (8.4, 11.4) years. For the normoglycemia ↔ IGT → diabetes model, mean sojourn time in normoglycemia was 34.5 (29.5, 40.8) years, and sojourn time in IGT was 6.1 (5.3, 7.1) years. CONCLUSIONS: Individuals reside in normoglycemia for 35-40 years; however, progression from prediabetes to diabetes is rapid.

Fixed-dose combination therapy for the prevention of atherosclerotic cardiovascular disease.

Fixed-dose combination (FDC) therapy, also known as polypill therapy, targets risk factors for atherosclerotic cardiovascular disease (ASCVD) and has been proposed as a strategy to reduce global ASCVD burden. Here we conducted a systematic search for relevant studies from 2016-2022 to assess the effects of FDC therapy for prevention of ASCVD. The studies selected include randomized trials evaluating FDC therapy with at least one blood pressure-lowering drug and one lipid-lowering drug. The study data were independently extracted, the quality of evidence was appraised by multiple reviewers and effect estimates were pooled using a fixed-effect meta-analysis when statistical heterogeneity was low to moderate. The main outcomes of the analysis were all-cause mortality, fatal and nonfatal ASCVD events, adverse events, systolic blood pressure, low-density lipoprotein cholesterol and adherence. Among 26 trials (n = 27,317 participants, 43.2% female and mean age range 52.9-76.0), FDC therapy was associated with lower low-density lipoprotein cholesterol and systolic blood pressure, with higher rates of adherence and adverse events in both primary and mixed secondary prevention populations. For studies with a mostly primary prevention population, FDC therapy was associated with lower risk of all-cause mortality by 11% (5.6% versus 6.3%; relative risk (risk ratio) of 0.89; 95% confidence interval 0.78 to 1.00; I2 = 0%; four trials and 16,278 participants) and risk of fatal and nonfatal ASCVD events by 29% (6.1% versus 8.4%; relative risk (risk ratio) of 0.71; 95% confidence interval 0.63 to 0.79; I2 = 0%; five trials and 15,503 participants). One adequately powered trial in an exclusively secondary prevention population showed that FDC therapy reduced the risk of major adverse cardiovascular events by 24%. These findings support adoption and implementation of polypills to lower risk for all-cause mortality and ASCVD.

Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 µg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 µg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 µg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 µg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

Association of pro-inflammatory cytokines, adipokines and hepatokine with incident diabetes in India: a nested case-control study within CARRS cohort.

AIMS: To study the association of pro-inflammatory markers with incident diabetes in India. METHODS: We did a nested case-control study within the CARRS (Centre for Ardiometabolic Risk Reduction in South Asia) cohort. Of the 5739 diabetes-free individuals at the baseline, 216 participants with incident diabetes and 432 age-, gender- and city-matched controls at 2-year follow-up were included. We measured high sensitive C-reactive protein (hsCRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 ( MCP-1), adiponectin, leptin and fetuin-A in the stored baseline blood samples. We did multivariate conditional logistic regression to estimate association of inflammatory markers (as quartiles) and incident diabetes. Covariates were baseline fasting plasma glucose (FPG) and lipids, body mass index (BMI), family history of diabetes, smoking and alcohol use. RESULTS: Baseline hsCRP and TNF-α were higher, and IL-6 and adiponectin were lower among cases vs. controls. In multivariate conditional logistic regression models, only quartile-3 (odds ratio [OR]: 2.96 [95% CI:1.39, 6.30]) and quartile-4 (OR: 2.58 [95% CI: 1.15, 5.79]) of TNF-α and quartile-4 of MCP-1 (OR: 2.55 [95% CI: 1.06, 6.16]) were positively associated with diabetes after adjusting for baseline FPG and BMI. These associations did not remain after adjusting for family history. High level (quartile-4) of IL-6 was negatively associated with diabetes after adjusting for all factors (OR: 0.18 [95% CI: 0.06, 0.55]). CONCLUSIONS: Higher TNF-α and MCP-1 levels and lower IL-6 were associated with higher risk of developing diabetes. Better understanding and potential methods of addressing these biomarkers, especially in relation to family history, are needed to address diabetes in South Asians.

Impact of heatwaves on all-cause mortality in India: A comprehensive multi-city study.

BACKGROUND: Heatwaves are expected to increase with climate change, posing a significant threat to population health. In India, with the world's largest population, heatwaves occur annually but have not been comprehensively studied. Accordingly, we evaluated the association between heatwaves and all-cause mortality and quantifying the attributable mortality fraction in India. METHODS: We obtained all-cause mortality counts for ten cities in India (2008-2019) and estimated daily mean temperatures from satellite data. Our main extreme heatwave was defined as two-consecutive days with an intensity above the 97th annual percentile. We estimated city-specific heatwave associations through generalised additive Poisson regression models, and meta-analysed the associations. We reported effects as the percentage change in daily mortality, with 95% confidence intervals (CI), comparing heatwave vs non-heatwave days. We further evaluated heatwaves using different percentiles (95th, 97th, 99th) for one, two, three and five-consecutive days. We also evaluated the influence of heatwave duration, intensity and timing in the summer season on heatwave mortality, and estimated the number of heatwave-related deaths. FINDINGS: Among âˆ¼ 3.6 million deaths, we observed that temperatures above 97th percentile for 2-consecutive days was associated with a 14.7 % (95 %CI, 10.3; 19.3) increase in daily mortality. Alternative heatwave definitions with higher percentiles and longer duration resulted in stronger relative risks. Furthermore, we observed stronger associations between heatwaves and mortality with higher heatwave intensity. We estimated that around 1116 deaths annually (95 %CI, 861; 1361) were attributed to heatwaves. Shorter and less intense definitions of heatwaves resulted in a higher estimated burden of heatwave-related deaths. CONCLUSIONS: We found strong evidence of heatwave impacts on daily mortality. Longer and more intense heatwaves were linked to an increased mortality risk, however, resulted in a lower burden of heatwave-related deaths. Both definitions and the burden associated with each heatwave definition should be incorporated into planning and decision-making processes for policymakers.