Mohan Deepa

Background: Menopause marks a key reproductive milestone with significant implications for women’s long-term cardiometabolic health. However, the influence of cardiometabolic health during the reproductive years on the timing of menopause remains poorly understood. We prospectively examined the association between cardiometabolic health profiles and menopause onset in South Asian women, a population at high risk of early cardiometabolic dysfunction. Methods: We analyzed longitudinal data from menstruating women aged 30–50 years in the CARRS cohort from 2010 to 2024. Baseline cardiometabolic measures included overweight/obesity (body mass index ≥25 kg/m2), hypertension (systolic blood pressure ≥140 or diastolic blood pressure ≥90 mmHg, prior history, or medication use), diabetes (hemoglobin A1c ≥6.5%, physician diagnosis, or use of glucose-lowering medication), and non-high-density lipoprotein cholesterol (non-HDL-C ≥ 130 mg/dl). Using Cox proportional hazards models, we examined associations between baseline cardiometabolic status and time to natural menopause, adjusting for sociodemographic and reproductive factors. Results: Among 2225 women (median age 37 years; IQR: 33, 40), 44% reached natural menopause at a median age of 46 (IQR: 43, 49) years. Women with hypertension reached natural menopause approximately 1 year earlier than those without hypertension. In adjusted models, women with hypertension experienced relatively earlier natural menopause over follow-up (HR 1.34, 95% CI: 1.19–1.52). In contrast, the timing of natural menopause did not differ by baseline diabetes, weight, or non-HDL-C status. Conclusion: Hypertension was associated with earlier timing of menopause in South Asian women. Further research is needed to explore underlying mechanisms and long-term health implications.

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are among the most common medical complications in pregnancy, with prevalence rates of 10-25% and 3-9.4%, respectively. Both conditions are important causes of maternal and neonatal morbidity and pose considerable risks to maternal and fetal health. GDM and PE are traditionally viewed as distinct clinical entities. However, they share several common risk factors, including advanced maternal age, obesity, family history of metabolic disease, dyslipidemia and genetic predisposition. The two conditions also have overlapping pathophysiological pathways, particularly involving metabolic and vascular dysfunctions such as insulin resistance, chronic inflammation and endothelial dysfunction. This article reviews the prevalence of GDM and PE, the risk factors common to the two conditions and biomarkers that may aid in early identification of these disorders. The report also discusses clinical implications of the overlap between the two disorders, with a plea for integrated management strategies. Finally, the article also highlights potential preventive measures and underscores the importance of multidisciplinary approaches to improve pregnancy outcomes in those with GDM and PE.

Aims/hypothesis Beyond longer diabetes duration, uncertainty remains regarding the factors that contribute to a higher risk of developing complications in younger vs older people with type 2 diabetes. We investigated whether younger age was associated with a more adverse risk-factor profile compared with older age among people with type 2 diabetes. Methods We conducted cross-sectional analyses of demographic and clinical data from individuals with type 2 diabetes participating in national health surveys from four countries: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), the US National Health and Nutrition Examination Survey (NHANES), the Mauritius Non-Communicable Diseases Survey (Mauritius Survey), and the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study. Type 2 diabetes was defined according to each study’s criteria, including previously diagnosed and newly diagnosed (screen-detected) diabetes (NDM). Individuals with normal glucose tolerance (NGT) were included for comparison. Regression analyses with natural splines assessed association between age at survey and cardiometabolic risk factors in each cohort. Results There were 903 participants with type 2 diabetes from AusDiab, 7086 from NHANES, 2682 from the Mauritius Survey and 10,151 from ICMR-INDIAB. In three of the four studies (excluding ICMR-INDIAB), BMI decreased with increasing age. Younger individuals had higher low-density lipoprotein cholesterol (in NHANES and AusDiab) and lower high-density lipoprotein cholesterol (in all studies except ICMR-INDIAB) compared with older individuals. In AusDiab, NHANES and the Mauritius Survey, triglycerides were highest in younger adults, declining with age. In AusDiab, the Mauritius Survey and ICMR-INDIAB, fasting plasma glucose (FPG) increased with age until 45–55 years, after which it declined. In NHANES, younger individuals with diabetes had higher FPG than older individuals. In all four studies, haemoglobin A_1c (HbA_1c) increased with age, peaking around 50–60 years, before declining. In NDM, 2 h plasma glucose did not vary across age. Systolic blood pressure (SBP) and urinary albumin/creatinine ratio (UACR) were higher in older individuals. Comparing diabetes with NGT, differences in FPG, HbA_1c, triglycerides and diastolic blood pressure (DBP) were greater at younger than older ages in most cohorts. The same was observed for BMI and SBP, but only in two studies (AusDiab and NHANES). Conclusions/interpretation Younger individuals with type 2 diabetes have higher BMI and triglycerides (observed in three out of four studies) but lower SBP and UACR than older individuals with type 2 diabetes. FPG and HbA_1c peak in middle age. Differences relative to individuals without diabetes were more pronounced at younger than older ages for FPG, HbA_1c, triglycerides and DBP, and were possibly greater for BMI and SBP. These age-related patterns likely influence the overall risk of diabetes-related complications. Graphical Abstract The alternative text for this image may have been generated using AI.

Chronic conditions cause notable health and economic burdens. While health insurance enables access to healthcare, its effects on chronic care outcomes remain under-explored. To examine the association between health insurance coverage and cardiometabolic risk factors among people with chronic conditions in India. Data from the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) and Solan studies, including 2,926 adults with chronic conditions were analyzed using propensity score weighting to evaluate the associations between health insurance and cardiometabolic risk factors (HbA1c, low-density lipoprotein cholesterol [LDLc], and blood pressure [BP]) and self-reported health status (measured using European Quality of Life Visual Analogue Scale [EQ-VAS]). Mediation analysis evaluated healthcare visits as a potential mediator. Among 2,926 respondents meeting criteria, mean (SD) age was 54.6 years (11.8), and 1630 (55.7%) were women. Health insurance coverage was low (6.5%) and more prevalent among men, higher-income groups, and rural vs urban residents. Insured participants had lower mean diastolic BP (84.8 vs 86.0 mmHg), mean LDLc (113.3 vs 117.2 mg/dl), mean HbA1c (6.9% vs 7.5%), and higher health status (EQ-VAS: 74.6 vs 69.1) than uninsured participants, respectively (p < 0.05). Mediation analysis showed healthcare visits strongly mediated the relationship between insurance and BP and partially mediated effects on LDLc, HbA1c, and self-rated health. Health insurance coverage was associated with better cardiometabolic risk profiles and health status, largely mediated by increased healthcare utilization. Expanding insurance coverage to include outpatient chronic care services should be prioritized to improve health outcomes in low- and middle-income countries.

Introduction Physical inactivity contributes to non-communicable disease (NCD) health burden, making it essential to study and address this issue at a population level. The present research aims to explore the patterns of physical activity (PA) in Haryana through a subgroup analysis of the national Indian Council of Medical Research–India Diabetes (ICMR-INDIAB) study. Methods This study was conducted between December 2018 and July 2019 in Haryana and included 3918 adult participants. Physical activity was assessed using the validated MDRF Physical Activity Questionnaire (MPAQ), which has domain-wise assessments of PA. Weighted prevalence was estimated using state-specific sampling weights, and associations between PA, anthropometric and biochemical profiles were assessed using bivariate analysis done using Student’s unpaired t tests, one-way analysis of variance (ANOVA), or chi-square tests. Factors describing the likelihood of being active were ascertained using a multivariable nominal regression analysis. Results About 73% of the study participants were physically inactive, and only 27% were moderately to vigorously active. The time spent in different PA domains varied significantly across sociodemographic variables, including sex, education, region, occupation, and socioeconomic status. Participants from the middle socioeconomic class spent more time in work-related PA, compared to low and upper-class participants who spent more time in general and transport-related PA. There were significant statistical differences between active and non-active groups concerning their mean blood glucose levels, body mass index, waist circumference and systolic blood pressure, but the differences in the lipid profile were non-significant. However, regression analysis showed higher odds of being physically active among younger participants, men, residents in rural areas, and those having fewer years of education. Conclusion We highlight the alarmingly high prevalence of physical inactivity across different segments of society in Haryana with significant sociodemographic disparities. Considering the increasing prevalence of NCDs, it is high time to prioritise health promotion measures and inculcate more physical activity amongst the population to achieve health-related sustainable development goals.

Introduction: Air pollution presents a major public health threat to India, affecting more than three quarters of the country’s population. In the current project, GEOHealth Health Effects of Selected Environmental Exposomes Across the Life CourSe–India, we aim to study the effect of environmental exposomes—fine particulate matter (PM _2.5 ), nitrogen dioxide (NO ₂ ), ozone (O ₃ ) and extremes of temperature—on multiple health outcomes using a modified life course approach. The associated training grant aims to build capacity in India to address the unique environmental health problems. Methods and analysis: The project aims to (A) Develop exposure assessments in seven cities, namely Delhi, Chennai, Sonipat, Vizag, Pune, Hyderabad and Bikaner, for: (1) A fine-scale spatiotemporal model for multiple pollutants (PM _2.5 , NO ₂ , O _3, temperature); (2) Combined ground monitoring and modelling for major chemical species of ambient PM _2.5 at seven cities; and (3) Personal exposure assessment in a subsample from the six cities, except Pune, and (B) Conduct health association studies covering a range of chronic non-communicable diseases and their risk factors leveraging a unique approach using interdigitating cohorts. We have assembled existing pregnancy, child, adolescent, adult and older adult cohorts across India to explore health effects of exposomes using causal analyses. We propose to use Bayesian kernel machine regression to assess the effects of mixtures of all pollutants including species of PM _2.5 on health while accounting for potential non-linearities and interactions between exposures. This builds on earlier work that constructed a fine spatiotemporal model for PM _2.5 exposure to study health outcomes in two Indian cities. Ethics and dissemination: Ethical clearance for conduct of the study was obtained from the Institutional Ethics Committee (IEC) of the Centre for Chronic Disease Control, and all the participating institutes and organisations. National-level permission was provided by the Indian Council of Medical Research. The research findings will be disseminated through peer-reviewed publications, policy briefs, print and social media, and communicating with the participating communities and stakeholders. Training of Indian scientists will build the capacity to undertake research on selected adverse environmental exposures on population health in India.