Type 2 diabetes (T2D) has attained the status of a global pandemic, spreading from affluent industrialized nations to the emerging economies of Asia, Latin America, and Africa. There is significant ...global variation in susceptibility to T2D, with Pacific Islanders, Asian Indians, and Native Americans being considerably more prone to develop the disorder. Although genetic factors may play a part, the rapidity with which diabetes prevalence has risen among these populations reflects the far-ranging and rapid socioeconomic changes to which they have been exposed over the past few decades. Traditionally, obesity and its correlate, insulin resistance, have been considered the major mediators of T2D risk; however, recent evidence shows that early loss of β-cell function plays an important role in the pathogenesis of T2D, especially in nonobese individuals such as South Asians. Knowledge of the modifiable risk factors of T2D is important, as it forms the basis for designing cost-effective preventive and therapeutic strategies to slow the epidemic in populations at increased risk. Lessons learned from randomized prevention trials need to be implemented with appropriate cultural adaptations, accompanied by empowerment of the community, if the diabetes epidemic is to be slowed or halted.
Previous studies have not adequately captured the heterogeneous nature of the diabetes epidemic in India. The aim of the ongoing national Indian Council of Medical Research-INdia DIABetes study is to ...estimate the national prevalence of diabetes and prediabetes in India by estimating the prevalence by state.
We used a stratified multistage design to obtain a community-based sample of 57 117 individuals aged 20 years or older. The sample population represented 14 of India's 28 states (eight from the mainland and six from the northeast of the country) and one union territory. States were sampled in a phased manner: phase I included Tamil Nadu, Chandigarh, Jharkhand, and Maharashtra, sampled between Nov 17, 2008, and April 16, 2010; phase II included Andhra Pradesh, Bihar, Gujarat, Karnataka, and Punjab, sampled between Sept 24, 2012, and July 26, 2013; and the northeastern phase included Assam, Mizoram, Arunachal Pradesh, Tripura, Manipur, and Meghalaya, with sampling done between Jan 5, 2012, and July 3, 2015. Capillary oral glucose tolerance tests were used to diagnose diabetes and prediabetes in accordance with WHO criteria. Our methods did not allow us to differentiate between type 1 and type 2 diabetes. The prevalence of diabetes in different states was assessed in relation to socioeconomic status (SES) of individuals and the per-capita gross domestic product (GDP) of each state. We used multiple logistic regression analysis to examine the association of various factors with the prevalence of diabetes and prediabetes.
The overall prevalence of diabetes in all 15 states of India was 7·3% (95% CI 7·0-7·5). The prevalence of diabetes varied from 4·3% in Bihar (95% CI 3·7-5·0) to 10·0% (8·7-11·2) in Punjab and was higher in urban areas (11·2%, 10·6-11·8) than in rural areas (5·2%, 4·9-5·4; p<0·0001) and higher in mainland states (8·3%, 7·9-8·7) than in the northeast (5·9%, 5·5-6·2; p<0·0001). Overall, 1862 (47·3%) of 3938 individuals identified as having diabetes had not been diagnosed previously. States with higher per-capita GDP seemed to have a higher prevalence of diabetes (eg, Chandigarh, which had the highest GDP of US$ 3433, had the highest prevalence of 13·6%, 12.8-15·2). In rural areas of all states, diabetes was more prevalent in individuals of higher SES. However, in urban areas of some of the more affluent states (Chandigarh, Maharashtra, and Tamil Nadu), diabetes prevalence was higher in people with lower SES. The overall prevalence of prediabetes in all 15 states was 10·3% (10·0-10·6). The prevalence of prediabetes varied from 6·0% (5·1-6·8) in Mizoram to 14·7% (13·6-15·9) in Tripura, and the prevalence of impaired fasting glucose was generally higher than the prevalence of impaired glucose tolerance. Age, male sex, obesity, hypertension, and family history of diabetes were independent risk factors for diabetes in both urban and rural areas.
There are large differences in diabetes prevalence between states in India. Our results show evidence of an epidemiological transition, with a higher prevalence of diabetes in low SES groups in the urban areas of the more economically developed states. The spread of diabetes to economically disadvantaged sections of society is a matter of great concern, warranting urgent preventive measures.
Indian Council of Medical Research and Department of Health Research, Ministry of Health and Family Welfare, Government of India.
In India there are very few population based data on prevalence of depression. The aim of the study was to determine the prevalence of depression in an urban south Indian population.
Subjects were ...recruited from the Chennai Urban Rural Epidemiology Study (CURES), involving 26,001 subjects randomly recruited from 46 of the 155 corporation wards of Chennai (formerly Madras) city in South India. 25,455 subjects participated in this study (response rate 97.9%). Depression was assessed using a self-reported and previously validated instrument, the Patient Health Questionnaire (PHQ) - 12. Age adjustment was made according to the 2001 census of India. The overall prevalence of depression was 15.1% (age-adjusted, 15.9%) and was higher in females (females 16.3% vs. males 13.9%, p<0.0001). The odds ratio (OR) for depression in female subjects was 1.20 Confidence Intervals (CI): 1.12-1.28, p<0.001 compared to male subjects. Depressed mood was the most common symptom (30.8%), followed by tiredness (30.0%) while more severe symptoms such as suicidal thoughts (12.4%) and speech and motor retardation (12.4%) were less common. There was an increasing trend in the prevalence of depression with age among both female (p<0.001) and male subjects (p<0.001). The prevalence of depression was higher in the low income group (19.3%) compared to the higher income group (5.9%, p<0.001). Prevalence of depression was also higher among divorced (26.5%) and widowed (20%) compared to currently married subjects (15.4%, p<0.001).
This is the largest population-based study from India to report on prevalence of depression and shows that among urban south Indians, the prevalence of depression was 15.1%. Age, female gender and lower socio-economic status are some of the factors associated with depression in this population.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Epidemiology of type 2 diabetes in India Pradeepa, Rajendra; Mohan, Viswanathan
Indian journal of ophthalmology,
11/2021, Letnik:
69, Številka:
11
Journal Article
Recenzirano
Odprti dostop
The burden of diabetes is high and increasing globally, and in developing economies like India, mainly fueled by the increasing prevalence of overweight/obesity and unhealthy lifestyles. The ...estimates in 2019 showed that 77 million individuals had diabetes in India, which is expected to rise to over 134 million by 2045. Approximately 57% of these individuals remain undiagnosed. Type 2 diabetes, which accounts for majority of the cases, can lead to multiorgan complications, broadly divided into microvascular and macrovascular complications. These complications are a significant cause for increased premature morbidity and mortality among individuals with diabetes, leading to reduced life expectancy and financial and other costs of diabetes leading to profound economic burden on the Indian health care system. The risk for diabetes is largely influence by ethnicity, age, obesity and physical inactivity, unhealthy diet, and behavioral habits in addition to genetics and family history. Good control of blood sugar blood pressure and blood lipid levels can prevent and/or delay the onset of diabetes complications. The prevention and management of diabetes and associated complications is a huge challenge in India due to several issues and barriers, including lack of multisectoral approach, surveillance data, awareness regarding diabetes, its risk factors and complications, access to health care settings, access to affordable medicines, etc. Thus, effective health promotion and primary prevention, at both, individual and population levels are the need of the hour to curb the diabetes epidemic and reduce diabetes-related complications in India.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aims/hypothesis
South Asians in general, and Asian Indians in particular, have higher risk of type 2 diabetes compared with white Europeans, and a younger age of onset. The reasons for the younger ...age of onset in relation to obesity, beta cell function and insulin sensitivity are under-explored.
Methods
Two cohorts of Asian Indians, the ICMR-INDIAB cohort (Indian Council of Medical Research-India Diabetes Study) and the DMDSC cohort (Dr Mohan’s Diabetes Specialties Centre), and one of white Europeans, the ESDC (East Scotland Diabetes Cohort), were used. Using a cross-sectional design, we examined the comparative prevalence of healthy, overweight and obese participants with young-onset diabetes, classified according to their BMI. We explored the role of clinically measured beta cell function in diabetes onset in Asian Indians. Finally, the comparative distribution of a partitioned polygenic score (pPS) for risk of diabetes due to poor beta cell function was examined. Replication of the genetic findings was sought using data from the UK Biobank.
Results
The prevalence of young-onset diabetes with normal BMI was 9.3% amongst white Europeans and 24–39% amongst Asian Indians. In Asian Indians with young-onset diabetes, after adjustment for family history of type 2 diabetes, sex, insulin sensitivity and HDL-cholesterol, stimulated C-peptide was 492 pmol/ml (IQR 353–616,
p
<0.0001) lower in lean compared with obese individuals. Asian Indians in our study, and South Asians from the UK Biobank, had a higher number of risk alleles than white Europeans. After weighting the pPS for beta cell function, Asian Indians have lower genetically determined beta cell function than white Europeans (
p
<0.0001). The pPS was associated with age of diagnosis in Asian Indians but not in white Europeans. The pPS explained 2% of the variation in clinically measured beta cell function, and 1.2%, 0.97%, and 0.36% of variance in age of diabetes amongst Asian Indians with normal BMI, or classified as overweight and obese BMI, respectively.
Conclusions/interpretation
The prevalence of lean BMI in young-onset diabetes is over two times higher in Asian Indians compared with white Europeans. This phenotype of lean, young-onset diabetes appears driven in part by lower beta cell function. We demonstrate that Asian Indians with diabetes also have lower genetically determined beta cell function.
Graphical abstract
To study the pattern and prevalence of dyslipidemia in a large representative sample of four selected regions in India.
Phase I of the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) ...study was conducted in a representative population of three states of India Tamil Nadu, Maharashtra and Jharkhand and one Union Territory Chandigarh, and covered a population of 213 million people using stratified multistage sampling design to recruit individuals ≥20 years of age. All the study subjects (n = 16,607) underwent anthropometric measurements and oral glucose tolerance tests were done using capillary blood (except in self-reported diabetes). In addition, in every 5th subject (n = 2042), a fasting venous sample was collected and assayed for lipids. Dyslipidemia was diagnosed using National Cholesterol Education Programme (NCEP) guidelines.
Of the subjects studied, 13.9% had hypercholesterolemia, 29.5% had hypertriglyceridemia, 72.3% had low HDL-C, 11.8% had high LDL-C levels and 79% had abnormalities in one of the lipid parameters. Regional disparity exists with the highest rates of hypercholesterolemia observed in Tamilnadu (18.3%), highest rates of hypertriglyceridemia in Chandigarh (38.6%), highest rates of low HDL-C in Jharkhand (76.8%) and highest rates of high LDL-C in Tamilnadu (15.8%). Except for low HDL-C and in the state of Maharashtra, in all other states, urban residents had the highest prevalence of lipid abnormalities compared to rural residents. Low HDL-C was the most common lipid abnormality (72.3%) in all the four regions studied; in 44.9% of subjects, it was present as an isolated abnormality. Common significant risk factors for dyslipidemia included obesity, diabetes, and dysglycemia.
The prevalence of dyslipidemia is very high in India, which calls for urgent lifestyle intervention strategies to prevent and manage this important cardiovascular risk factor.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aim. To review the available literature on burden of diabetes mellitus (DM) and hypertension (HTN) and its coexistence in Southeast Asian (SEA) and the African (AFR) regions and to suggest strategies ...to improve DM and HTN prevention and control in primary health care (PHC) in the two regions. Methods. A systematic review of the papers published on DM, HTN, and prevention/control of chronic diseases in SEA and AFR regions between 1980 and December 2012 was included. Results. In the year 2011, SEA region had the second largest number of people with DM (71.4 million), while the AFR region had the smallest number (14.7 million). Screening studies identified high proportions (>50%) of individuals with previously undiagnosed HTN and DM in both of the SEA and AFR regions. Studies from both regions have shown that DM and HTN coexist in type 2 DM ranging from 20.6% in India to 78.4% in Thailand in the SEA region and ranging from 9.7% in Nigeria to 70.4% in Morocco in the AFR region. There is evidence that by lifestyle modification both DM and HTN can be prevented. Conclusion. To meet the twin challenge of DM and HTN in developing countries, PHCs will have to be strengthened with a concerted and multipronged effort to provide promotive, preventive, curative, and rehabilitative services.
IntroductionType 2 diabetes is characterized by considerable heterogeneity in its etiopathogenesis and clinical presentation. We aimed to identify clusters of type 2 diabetes in Asian Indians and to ...look at the clinical implications and outcomes of this clustering.Research design and methodsFrom a network of 50 diabetes centers across nine states of India, we selected 19 084 individuals with type 2 diabetes (aged 10–97 years) with diabetes duration of less than 5 years at the time of first clinic visit and performed k-means clustering using the following variables: age at diagnosis, body mass index, waist circumference, glycated hemoglobin, serum triglycerides, serum high-density lipoprotein cholesterol and C peptide (fasting and stimulated). This was then validated in a national epidemiological data set of representative individuals from 15 states across India.ResultsWe identified four clusters of patients, differing in phenotypic characteristics as well as disease outcomes: cluster 1 (Severe Insulin Deficient Diabetes, SIDD), cluster 2 (Insulin Resistant Obese Diabetes, IROD), cluster 3 (Combined Insulin Resistant and Deficient Diabetes, CIRDD) and cluster 4 (Mild Age-Related Diabetes, MARD). While SIDD and MARD are similar to clusters reported in other populations, IROD and CIRDD are novel clusters. Cox proportional hazards showed that SIDD had the highest hazards for developing retinopathy, followed by CIRDD, while CIRDD had the highest hazards for kidney disease.ConclusionsCompared with previously reported clustering, we show two novel subgroups of type 2 diabetes in the Asian Indian population with important implications for prognosis and management. The coexistence of insulin deficiency and insulin resistance seems to be peculiar to the Asian Indian population and is associated with an increased risk of microvascular complications.
•A proportion of individuals may develop type 2 diabetes without overweight/obesity.•A large proportion of Asian Indians type 2 diabetes even with a low BMI.•This was not explained by differences in ...waist circumference, HOMA-IR, or HOMA-β.•Further studies should examine type 2 diabetes pathophysiology in lean individuals.
Type 2 diabetes in lean individuals has recently come to attention. We assessed type 2 diabetes prevalence and the associated risk factors in underweight and normal weight individuals in two ethnic populations.
We conducted cross-sectional analyses, using representative samples of 4930 Asian Indians from the CARRS-Chennai Study and 2868 Whites from the NHANES Survey. Diabetes was defined as use of glucose lowering medication, fasting glucose ≥126 mg/dl, or 2 h glucose ≥200 mg/dl. Body mass index (BMI) was classified using WHO standard criteria.
Prevalence of type 2 diabetes by BMI varied by ethnicity and sex. In men, type 2 diabetes prevalence was 5.4% and 23.5% in underweight and normal weight Asian Indians and 0.0% and 6.1% in underweight and normal weight Whites. In women, the prevalence was 5.6% and 13.6% in underweight and normal weight Asian Indians and 2.3% and 2.8% in underweight and normal weight Whites. Adjustment for waist circumference, insulin resistance, and insulin secretion did not explain the increased prevalence in Asian Indians.
These findings suggest significant ethnic differences in type 2 diabetes prevalence without overweight or obesity. Future studies should examine the pathophysiology of type 2 diabetes development in lean individuals.
Plasma omentin levels have been shown to be associated with circulating adiponectin concentrations and cardiometabolic disease-related outcomes. In this study, we aim to examine the association of ...omentin gene polymorphism with serum adiponectin levels and cardiometabolic health status using a genetic approach, and investigate whether these associations are modified by lifestyle factors.
The study included 945 normal glucose tolerant and 941 unrelated individuals with type 2 diabetes randomly selected from the Chennai Urban Rural Epidemiology Study (CURES), in southern India. Study participants were classified into cardiometabolically healthy and unhealthy, where cardiometabolically healthy were those without hypertension, diabetes, and dyslipidemia. Fasting serum adiponectin levels were measured by radioimmunoassay. The omentin A326T (rs2274907) single nucleotide polymorphism (SNP) was screened by polymerase chain reaction-restriction fragment length polymorphism and direct sequencing.
The 'A' allele of the omentin SNP was significantly associated with lower adiponectin concentrations after adjusting for age, sex, body mass index (BMI), waist circumference (WC) and cardiometabolic health status (p = 1.90 x 10-47). There was also a significant association between circulating adiponectin concentrations and cardiometabolic health status after adjusting for age, sex, BMI, WC and Omentin SNP (p = 7.47x10-10). However, after adjusting for age, sex, BMI, WC and adiponectin levels, the association of 'A' allele with cardiometabolic health status disappeared (p = 0.79) suggesting that adiponectin serves as a mediator of the association between omentin SNP and cardiometabolic health status. There were no significant interactions between the SNP and dietary factors on adiponectin levels and cardiometabolic health status (p>0.25, for all comparisons).
Our findings show that adiponectin might function as a mechanistic link between omentin SNP and increased risk of cardiometabolic diseases independent of common and central obesity in Asian Indians. Before strategies to promote adiponectin modulation could be implemented, further studies are required to confirm the molecular mechanisms involved in this triangular relationship between omentin gene, adiponectin and cardiometabolic diseases.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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