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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To assess the effect of migration (rural-to-urban and vice versa) on prevalence of diabetes and metabolic disorders in Asian Indians participating in the Indian Council of Medical Research-India ...Diabetes (ICMR-INDIAB) study.
The ICMR–INDIAB study is a national study on diabetes and associated cardiometabolic disorders in individuals aged ≥20 years from 28 states and 2 union territories of India. Individuals who moved to a different place from their place of birth and had resided in the new location for at least one year were considered as migrants. Anthropometric measurements, blood pressure estimation and a capillary oral glucose tolerance test were performed.
Of the 113,043 participants, 66.4% were non-migrant rural dwellers, 19.4% non-migrant urban dwellers, 8.4% rural-urban migrants, 3.8% multiple migrants and 2.0% urban-rural migrants. Weighted prevalence of diabetes was highest in rural-urban migrants followed by urban dwellers, urban-rural migrants and rural dwellers 14.7%, 13.2%, 12.7% and 7.7% respectively (p < 0.001). Rural-urban migrants had highest prevalence of abdominal obesity (50.5%) compared to the other three groups. The risk for diabetes was 1.9 times higher in rural-urban migrants than among rural dwellers. Five risk factors hypertension, abdominal and generalized obesity, physical inactivity and low fruit and vegetable intake together explained 69.8% (partial population attributable risk) of diabetes among rural-urban migrants and 66.4% among non-migrant urban dwellers.
Rural-to-urban migration is associated with increased risk of developing diabetes and other cardiometabolic abnormalities. Adoption of healthier lifestyle patterns among migrants could help prevent/delay onset of these abnormalities in this population.
•Increased rural-urban migration in India during the last decade may increase the risk of diabetes,obesity, and hypertension.•Prevalence/risk of diabetes, obesity and hypertension are higher in non-migrant urban dwellers and rural-urban migrants.•Prevention programmes emphasizing healthy lifestyle for those living in the urban settings are the need of the hour!
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.
Non-communicable disease (NCD) rates are rapidly increasing in India with wide regional variations. We aimed to quantify the prevalence of metabolic NCDs in India and analyse interstate and ...inter-regional variations.
The Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study, a cross-sectional population-based survey, assessed a representative sample of individuals aged 20 years and older drawn from urban and rural areas of 31 states, union territories, and the National Capital Territory of India. We conducted the survey in multiple phases with a stratified multistage sampling design, using three-level stratification based on geography, population size, and socioeconomic status of each state. Diabetes and prediabetes were diagnosed using the WHO criteria, hypertension using the Eighth Joint National Committee guidelines, obesity (generalised and abdominal) using the WHO Asia Pacific guidelines, and dyslipidaemia using the National Cholesterol Education Program-Adult Treatment Panel III guidelines.
A total of 113 043 individuals (79 506 from rural areas and 33 537 from urban areas) participated in the ICMR-INDIAB study between Oct 18, 2008 and Dec 17, 2020. The overall weighted prevalence of diabetes was 11·4% (95% CI 10·2-12·5; 10 151 of 107 119 individuals), prediabetes 15·3% (13·9-16·6; 15 496 of 107 119 individuals), hypertension 35·5% (33·8-37·3; 35 172 of 111 439 individuals), generalised obesity 28·6% (26·9-30·3; 29 861 of 110 368 individuals), abdominal obesity 39·5% (37·7-41·4; 40 121 of 108 665 individuals), and dyslipidaemia 81·2% (77·9-84·5; 14 895 of 18 492 of 25 647). All metabolic NCDs except prediabetes were more frequent in urban than rural areas. In many states with a lower human development index, the ratio of diabetes to prediabetes was less than 1.
The prevalence of diabetes and other metabolic NCDs in India is considerably higher than previously estimated. While the diabetes epidemic is stabilising in the more developed states of the country, it is still increasing in most other states. Thus, there are serious implications for the nation, warranting urgent state-specific policies and interventions to arrest the rapidly rising epidemic of metabolic NCDs in India.
Indian Council of Medical Research and Department of Health Research, Ministry of Health and Family Welfare, Government of India.
There is little information on comprehensive diabetes care comprising glycaemic, lipid, and blood pressure control in India; therefore, we aimed to assess the achievement of treatment targets among ...adults with self-reported diabetes.
The Indian Council of Medical Research (ICMR)-India Diabetes (INDIAB) study is a cross-sectional, population-based survey of adults aged 20 years or older in all 30 states and union territories of India. We used a stratified multistage sampling design, sampling states in a phased manner, and selected villages in rural areas and census enumeration blocks in urban areas. We used a three-level stratification method on the basis of geography, population size, and socioeconomic status for each state. For the outcome assessment, good glycaemic control was defined as HbA
of less than 7·0% (A), blood pressure control was defined as less than 140/90 mm Hg (B), and the LDL cholesterol target was defined as less than 100 mg/dL (C). ABC control was defined as the proportion of individuals meeting glycaemic, blood pressure, and LDL cholesterol targets together. We also performed multiple logistic regression to assess the factors influencing achievement of diabetes treatment targets.
Between Oct 18, 2008, and Dec 17, 2020, 113 043 individuals (33 537 from urban areas and 79 506 from rural areas) participated in the ICMR-INDIAB study. For this analysis, 5789 adults (2633 in urban areas and 3156 in rural areas) with self-reported diabetes were included in the study population. The median age was 56·1 years (IQR 55·7-56·5). Overall, 1748 (weighted proportion 36·3%, 95% CI 34·7-37·9) of 4834 people with diabetes achieved good glycaemic control, 2819 (weighted proportion 48·8%, 47·2-50·3) of 5698 achieved blood pressure control, and 2043 (weighted proportion 41·5%, 39·9-43·1) of 4886 achieved good LDL cholesterol control. Only 419 (weighted proportion 7·7%) of 5297 individuals with self-reported diabetes achieved all three ABC targets, with significant heterogeneity between regions and states. Higher education, male sex, rural residence, and shorter duration of diabetes (<10 years) were associated with better achievement of combined ABC targets. Only 951 (weighted proportion 16·7%) of the study population and 227 (weighted proportion 36·9%) of those on insulin reported using self-monitoring of blood glucose.
Achievement of treatment targets and adoption of healthy behaviours remains suboptimal in India. Our results can help governments to adopt policies that prioritise improvement of diabetes care delivery and surveillance in India.
Indian Council of Medical Research and Department of Health Research, Ministry of Health and Family Welfare.
Introduction
Diabetes is a multifactorial disease with far-reaching consequences. Environmental factors, such as urban or rural residence, influence its prevalence and associated comorbidities. ...Haryana—a north Indian state—has undergone rapid urbanisation, and part of it is included in the National Capital Region (NCR). The primary aim of the study is to estimate the prevalence of diabetes in Haryana with urban–rural, NCR and non-NCR regional stratification and assess the factors affecting the likelihood of having diabetes among adults.
Methods
This sub-group analysis of the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study (a nationally representative cross-sectional population-based survey) was done for Haryana using data from 3722 participants. The dependent variable was diabetes, while residence in NCR/non-NCR and urban–rural areas were prime independent variables. Weighted prevalence was estimated using state-specific sampling weights and standardized using National Family Health Survey-5 (NFHS-5) study weights. Associations were depicted using bivariate analysis, and factors describing the likelihood of living with diabetes were explored using a multivariable binary logistic regression analysis approach.
Results
Overall, the weighted prevalence of diabetes in Haryana was higher than the national average (12.4% vs. 11.4%). The prevalence was higher in urban (17.9%) than in rural areas (9.5%). The prevalence of diabetes in rural areas was higher in the NCR region, while that of prediabetes was higher in rural non-NCR region. Urban–rural participants’ anthropometric measurements and biochemical profiles depicted non-significant differences. Urban–rural status, age and physical activity levels were the most significant factors that affected the likelihood of living with diabetes.
Conclusions
The current analysis provides robust prevalence estimates highlighting the urban–rural disparities. Urban areas continue to have a high prevalence of diabetes and prediabetes; rural areas depict a much higher prevalence of prediabetes than diabetes. With the economic transition rapidly bridging the gap between urban and rural populations, health policymakers should plan efficient strategies to tackle the diabetes epidemic.
This study estimated the levels of glycemic control among subjects with self-reported diabetes in urban and rural areas of four 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 covering a population of 213 million people. Using a stratified multistage sampling design, individuals ≥20 years of age were recruited. Glycemic control among subjects with self-reported diabetes was assessed by measurement of glycated hemoglobin (HbA1c), estimated by the Variant™ II Turbo method (Bio-Rad, Hercules, CA).
Among the 14,277 participants in Phase I of INDIAB, there were 480 subjects with self-reported diabetes (254 urban and 226 rural). The mean HbA1c levels were highest in Chandigarh (9.1±2.3%), followed by Tamil Nadu (8.2±2.0%), Jharkhand (8.2±2.4%), and Maharashtra (8.0±2.1%). Good glycemic control (HbA1c <7%) was observed only in 31.1% of urban and 30.8% of rural subjects. Only 22.4% of urban and 15.4% of rural subjects had reported having checked their HbA1c in the past year. Multiple logistic regression analysis revealed younger age, duration of diabetes, insulin use, and high triglyceride levels to be significantly associated with poor glycemic control.
The level of glycemic control among subjects with self-reported diabetes in India is poor. Urgent action is needed to remedy the situation.
Background & objectives: Screening of individuals for early detection and identification of undiagnosed diabetes can help in reducing the burden of diabetic complications. This study aimed to ...evaluate the performance of Madras Diabetes Research Foundation (MDRF)-Indian Diabetes Risk Score (IDRS) to screen for undiagnosed type 2 diabetes in a large representative population in India.
Methods: Data were acquired from the Indian Council of Medical Research-INdia DIABetes (ICMR-INDIAB) study, a large national survey that included both urban and rural populations from 30 states/union territories in India. Stratified multistage design was followed to obtain a sample of 113,043 individuals (94.2% response rate). MDRF-IDRS used four simple parameters, viz. age, waist circumference, family history of diabetes and physical activity to detect undiagnosed diabetes. Receiver operating characteristic (ROC) with area under the curve (AUC) was used to assess the performance of MDRF-IDRS.
Results: We identified that 32.4, 52.7 and 14.9 per cent of the general population were under high-, moderate- and low-risk category of diabetes. Among the newly diagnosed individuals with diabetes diagnosed by oral glucose tolerance test (OGTT), 60.2, 35.9 and 3.9 per cent were identified under high-, moderate- and low-risk categories of IDRS. The ROC-AUC for the identification of diabetes was 0.697 (95% confidence interval: 0.684-0.709) for urban population and 0.694 (0.684-0.704) for rural, as well as 0.693 (0.682-0.705) for males and 0.707 (0.697-0.718) for females. MDRF-IDRS performed well when the population were sub-categorized by state or by regions.
Interpretation & conclusions: Performance of MDRF-IDRS is evaluated across the nation and is found to be suitable for easy and effective screening of diabetes in Asian Indians.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aim
To report on glycated haemoglobin (HbA1c) values among individuals with normal glucose tolerance (NGT) at different age groups, using data acquired from a large national survey in India.
...Materials and methods
Data on glycaemic parameters at different age groups were obtained from the Indian Council of Medical Research–INdia DIABetes (ICMR–INDIAB) study, in adults aged ≥ 20 years representing all parts of India. Age-wise distribution of HbA1c was assessed among individuals with NGT (n = 14,222) confirmed by an oral glucose tolerance test using the World Health Organization (WHO) criteria. Results were validated in another large epidemiological study (n = 1077) conducted in Chennai, India.
Results
Among NGT individuals, HbA1c increased gradually with age from 5.16 ± 0.71% (33 mmol/mol) in the age group of 20–29 years to 5.49 ± 0.69% (37 mmol/mol) in those aged 70 + years. In the validation study, conducted in another study population, HbA1c was 5.35 ± 0.43% (35 mmol/mol) in age group of 20–29 years and 5.74 ± 0.50% (39 mmol/mol) in those aged 70 and above. In the INDIAB study, for every decadal increase in age, there is a 0.08% increase in HbA1c and this increase was more significant in females (females: 0.10% vs. males: 0.06%) and in urban (urban: 0.10% vs. rural: 0.08%) population.
Conclusions
HbA1c levels increase steadily with age. This suggests that age-specific cutoffs be used while utilizing HbA1c to diagnose diabetes and prediabetes, so as to minimize the risk of overdiagnosis and unnecessary initiation of treatment in elderly people who could have physiological increase in HbA1c levels.
A field study was conducted using 31 sorghum landraces and two improved varieties as yield checks under natural sodic soil conditions at Anbil Dharmalingam Agricultural College and Research ...Institute, Trichy during Kharif,2018. The study was aimed to assess the mean performance, genetic variability, heritability and diversity of key traits that would aid the selection of genotypes for sodicity tolerance. The experiment was laid out in randomized block design with two replications. Eight biometric traits viz., days to 50 percent flowering, plant height, number of tillers, number of leaves, leaf length, leaf width, panicle length and yield per plant were observed. The genotype ES1 was identified to be sodicity tolerant as it based on its overall per se performance. Based on PCA analysis, the characters panicle length, number of leaves and yield per plant were identified to contribute more towards the total divergence. These traits also showed higher PCV and GCV coupled with higher heritability and genetic advance as percent of mean. Hence, indirect selection for sodicity tolerance can be carried out through these traits for selection of genotypes with sodicity tolerance. Cluster analysis revealed the diverse genotypes (Cluster I and VI) that could be used in hybridization programmes for exploiting the maximum heterotic potential.