Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. Bill & Melinda Gates Foundation.

Introduction Concerns over the escalating burden of non-communicable diseases call for the redressal of behavioral risk factors like increased body mass index. Most studies have failed to quantify the contribution of socio-demographic characteristics in a linear trend. The present study aims to estimate the current prevalence of overweight and obesity in Indian adults and the contribution of different socio-demographic factors to the increasing prevalence. Methods We carried out a secondary data analysis of two National Family Health Survey (NFHS) rounds. The final sample includes 558,122 women and 84,477 men from round 4, and 574,099 women and 74,761 men were included from round 5, using a multi-stage stratified random sampling approach. Overweight/obesity was our primary dependent variable. Weighted bivariate analysis was used to ascertain the prevalence, and the adjusted odds ratios were computed to ascertain the potential predictors. The contribution of different factors towards rising burden over two time points was estimated using multivariate decomposition analysis for non-linear response models. Results Overall weighted prevalence of overweight and obesity in males and females per NFHS-5 was 44.02% and 41.16%, respectively, compared to 37.71% and 36.14% in NFHS-4. Decomposition analyses depict that the proportion of obesity increased by 6.37% and 5.10% points among men and women, respectively, over the two rounds. Compositional differences of participants (endowment) attributed to 16.54 and 49.90% differences, and the difference in coefficient or effect accounted for 83.46 and 50.10%, respectively, of the increase in the prevalence. The most significant factors contributing to increased prevalence were age, improving socio-economic status, smoking, unclean cooking fuel, and diabetes. Conclusions The incremental rise in such a short period, mainly attributed to the effect of socio-demographic variables, is concerning. Policy interventions should prioritize health advocacy programs and aggressively target behavioral modifications while preparing the health systems to manage the people living with obesity.

Background: Chronic disease burden among women leads to various detrimental consequences, impacting women’s health throughout their life course and off-springs. The present study explores the chronic disease profile among reproductive-aged women and analyzes the effects of various covariates on multimorbidity among reproductive-aged women in India. Here, multimorbidity is defined as an individual suffering from two or more chronic conditions. Methods: The present study employed the most recent National Family Health Survey round, 2019–2021. The study utilized information on 695,707 non-pregnant women aged 15–49 years. The study used descriptive, bivariate, and multivariable ordered logistic regression analysis to explore the burden of chronic non-communicable diseases and multimorbidity. Results: The mean age of women with single chronic condition-related morbidity is 30 years, whereas it was 35 years for those with multimorbidity. Approximately 28% of urban women suffered from multimorbidity. Further, significant factors that affect multimorbidity include age, educational attainment, working status, marital status, parity, menopause, religion, region, wealth index, tobacco use, alcohol consumption, and dietary patterns. Conclusions: The present study hints that women in the reproductive age group are at very high risk of developing multimorbidity in India. Most of the programs and policies are focused on the elderly population in terms of awareness and facilitating them with better health services. However, right now, one should also prioritize the emerging chronic condition related to chronic conditions other than hypertension, diabetes, and cancer among the study population, which is escalating as soon as women reach 30 years of age.

Background: Metabolic syndrome is on the rise in India and is primarily linked to obesogenic dietary habits. The synergy of both is a prominent risk factor for cardiovascular diseases (CVDs). Hence, the present study aims to unveil clusters at high risk of metabolic syndrome and ascertain cluster characteristics based on dietary patterns among adolescents aged 10–19 years.Data and methods: The study utilizes secondary data, i.e., Comprehensive National Nutrition Survey conducted in 2016-18. The study sample includes children and adolescents aged 10–19 years. An unsupervised learning algorithm was used to ascertain possible clusters in the data based on individuals’ dietary patterns. The k-means were used to cluster the data according to their dietary patterns. To determine the number of clusters elbow method was used, and appropriate validation indices were also obtained for the final k. Further, to ascertain the distribution of the obesogenic dietary patterns and metabolic conditions in each cluster was analysed. Bivariate descriptive analysis was used to draw further inferences.Results: The k-means clusters identified five optimum clusters based on 12,318 adolescents (6333 males (mean age:14.2 ± 2.8) and 5985 females (mean age:14.3 ± 2.8)) 17 dietary patterns. Clusters were named based on how prudent these were in terms of consuming a healthy diet. Cluster phenotypic characteristics were defined as follows: a cluster of obesogenic diets (24%) constituted the highest proportion of the total sample and was significantly suffering from obesity (p < 0.001), and greater proportions of lipid anomalies (p = 0.51) and hypertension (p = 0.44) but not statistically significant. In contrast, 21% of the sample comprised a plant-based diet cluster and suffered from all deficiencies but folate (p = 0.625), zinc (p = 0.132), and greater proportion from obesity (p = 0.19; not significant), and diabetes (p < 0.001). A cluster of “convenient” (20%) mainly suffered from lipid anomalies (p = 0.00), diabetes (p = 0.03), and a greater proportion from hypertension (p = 0.56) with deficiencies of all the essential vitamins and minerals but significantly from vitamin A (p < 0.001), folate (p < 0.001), and iron (p = 0.017). Lastly, the cluster of those who follow a “Western diet” (17%) was found to have lipid anomalies (p = 0.003), diabetes (p = 0.016), greater proportion of vitamin B12 (p = 0.136), D (p = 0.002), folate (p < 0.001), and iron deficiencies (p = 0.013).Conclusions and relevance: Adolescents in India show a strong association between obesogenic diet and metabolic syndrome. Therefore, the burden of metabolic syndrome at early ages can be prevented by controlling obesogenic dietary practices and addressing micronutrient deficiencies. This may be done by targeted health promotional campaigns in schools and college-going populations in India.

Background: The present study’s aim is to quantify the burden of lipid abnormalities (excessive non-high-density lipoprotein (non-HDL) cholesterol and low-density lipoprotein (LDL) cholesterol) among Indian adolescents. Which has emerged as a significant covariate of coronary heart disease (CHD). Methods: The present study aims to unearth the prevalence of any lipid anomalies, their level, and types of lipid profiles among adolescents in India using the Comprehensive National Nutrition Survey 2016–18 i.e., cross-sectional data. Descriptive and bivariate statistical analyses have been used to check the associations and significant differences between groups of individuals suffering from any type of lipid abnormalities. Results: A total of 35,830 adolescents aged between 10 and 19 years (mean age:14.36 yrs.; SD = 2.81 for males and 14.39 yrs.; SD = 2.78 for females) were included. Roughly 77 percent of the adolescents are suffering from any lipid anomalies. Their mean lipid levels are 140.6 (SD = 32.9), 84.1 (SD = 24.8), 47.3 (SD = 10.7), and 95.3 (SD = 50.0) for total cholesterol, LDL, HDL, and triglycerides, respectively. A higher proportion of adolescents suffered from lipid anomalies among those who were overweight or obese (89%, 95% CI 85, 92) and pre-diabetics (81%, 95% CI 78, 83) compared to each of their counterparts. Furthermore, a considerable proportion of samples with vitamin A (70%, 95% CI 68, 73), D (81%, 95% CI 79, 82), and B12 deficits (73%,95% CI 72, 75), as well as zinc (77%, 95% CI 76, 77), folate (76%, 95% CI 74, 77), and iron deficits (75%,95% CI 73, 77), were suffering from any lipid anomalies. Of individuals who consume an unhealthy diet, 77% (95% CI 76, 78) of them were suffering from any lipid anomalies than others. Conclusions: The study contends that preventing the increasing burden of lipid abnormalities among Indian adolescents is essential. Vitamin and mineral deficiencies and unhealthy dietary habits are significantly associated with high LDL and non-HDL levels. In the longer run, this might cause the early onset of hypertension, diabetes, and CHDs. Hence, appropriate interventions are needed to curtail these early onsets by primarily focusing on adolescents.

Purpose: According to the 4th and 5th rounds of National Family Health Survey (NFHS), there is high prevalence of hysterectomies in the three states of Andhra Pradesh Telangana and Bihar. The three said states have more than double the number of hysterectomies taking place than the national average. Our purpose is to analyse whether these rates are increasing, decreasing or have stabilized and their reasons thereof. Such an analyses will help the policy makers in recommending good clinical practices within their states.Material and methods: We used data from NFHS-4 (2015-16) and NFHS-5 (2019-2021) rounds. We calculated the differences in predicted probabilities for various factors, performed a Fairlie Decomposition analyses to quantify the positive and negative contributors in the prevalence of hysterectomy across the three states over two time points, and assessed the association of various socio-demographic characteristics to hysterectomy through a multilevel logistic regression model.Results and conclusion: The results show that out of a total of 80,976 eligible respondents from the states under study, 5826 respondents self-reported that they had a hysterectomy done. It was found that older age, living in rural areas, belonging to other backward classes and higher wealth quintile, and higher parity positively contributed to the increased prevalence of hysterectomies in the three states. Higher educational attainment and previous use of family planning methods acted as protective factors. Characteristics at the household level had the highest intra-class correlation value in the prevalence of hysterectomy among women, followed by the Primary Sampling Unit and District levels, indicating high clustering in the prevalence of hysterectomy at the household level in all three states. Heavy menstrual bleeding/pain was the leading cause of hysterectomies in all three states, followed by fibroids/cysts in Andhra Pradesh and Telangana and Uterine disorder/ prolapse in Bihar. Over 80% of hysterectomies took place in the private hospitals.Recommendations: The study recommends better, more efficient and accountable hysterectomy surveillance to ensure more sustainable woman’s reproductive health services in India. Government should adopt and implement standard regulatory guidelines to prevent provider-driven avoidable hysterectomies. Moreover, we recommend informing primary care professionals about the long-term health effects of hysterectomy and promoting alternate therapies for treating uterine fibroids and heavy bleeding.