Socioeconomic Gradients and Distribution of Diabetes, Hypertension, and Obesity in India

Corsi, Daniel J.; Subramanian, S. V.

doi:10.1001/jamanetworkopen.2019.0411

Cited by 105 publications

(94 citation statements)

References 30 publications

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“…Prevalence of diabetes was higher amongst higher socio-economic status groups [69][70][71][72] . Thus, higher wealth is an independent risk factor for diabetes 73 .…”

Section: Discussionmentioning

confidence: 91%

Prevalence of Diabetes Mellitus and Its Associated Factors in Bangladesh: Application of Two-level Logistic Regression Model

Talukder

Hossain

2020

Sci Rep

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this study intends to explore the prevalence of diabetes mellitus (DM) and its associated factors in Bangladesh. the necessary information was extracted from Bangladesh Demographic and Health Survey (BDHS) 2011. In bivariate analysis, Chi-square test was performed to assess the association between selected covariates and diabetes status. A two-level logistic regression model with a random intercept at each of the individual and regional level was considered to identify the risk factors of DM. A total of 7,535 individuals were included in this study. From the univariate analysis, the prevalence of DM was found to be 33.3% in 50-54 age group for instance. In bivariate setup, all the selected covariates except sex of the participants were found significant for DM (p < 0.05). According to the two-level logistic regression model, the chance of occurring DM increases as age of the participants' increases. It was observed that female participants were more likely to have DM. The occurrence of DM was 62% higher for higher educated participants, 42% higher for the individuals who came from rich family and 63% higher for the individuals having hypertension. The chance of developing diabetes among overweighed people was almost double. However, the individuals engaged in physical work had less chance to have DM. this study calls for greater attention of government and other concerned entities to come up with appropriate policy interventions to lower the risk of DM. The epidemic of the century-Diabetes Mellitus (DM), often referred as simply diabetes, is a set of metabolic disorder or syndrome recognized as chronic hyperglycemia (presence of high blood sugar) occurs due to imperfections in insulin action, insulin secretion, or both 1,2. It is now prevalent across the world with multiple complications 3-5. In 2014, around 422 million people were affected by DM and 1.5 million deaths were reported in 2012 6,7. According to WHO report, 2016, 8% (12.88 million) of total population of Bangladesh was affected by diabetes whereas 3% of total deaths of all-ages occurred due to diabetes 8. An increasing rate in the prevalence of DM among the Bangladeshi populace is also observed over time 9. Diabetes may result in a wide range of physiological as well as psychological problems including sexual disorder 10. The lower sexual functions or dysfunctions termed as loss of libido may be observed in both females and males as a consequence of DM 11-18. In addition, severe vision loss, acute renal diseases which may require dialysis or kidney transplant, myocardial infarction otherwise known as heart attack, cerebrovascular diseases like stroke, and hypertension are markedly observed 19-27. Due to the intensity of the adverse effects of diabetes, it is important to find out the determinants to address the issue in order to contribute to improving country health situation. Diabetes mellitus (DM) is a disease that relies on many factors and may vary over time and region. Accordingly, it requires to be screened on a constant basis. Previously, man...

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“…Prevalence of diabetes was higher amongst higher socio-economic status groups [69][70][71][72] . Thus, higher wealth is an independent risk factor for diabetes 73 .…”

Section: Discussionmentioning

confidence: 91%

Prevalence of Diabetes Mellitus and Its Associated Factors in Bangladesh: Application of Two-level Logistic Regression Model

Talukder

Hossain

2020

Sci Rep

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“…This is consistent with the strong direct association between adult socio-economic conditions and adiposity observed in India (compared to the weak association for blood pressure). 27…”

Section: Discussionmentioning

confidence: 99%

Childhood socio-economic conditions and risk of cardiovascular disease: results from a pooled sample of 14 011 adults from India

Mallinson

Lieber

Bhogadi

et al. 2020

J Epidemiol Community Health

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BackgroundSouth Asians are at an increased risk of premature cardiovascular disease, but the reasons for this are unclear. Poor socio-economic conditions in childhood are associated with an increased risk of cardiovascular disease in many high-income countries and may be particularly relevant to South Asia, where socio-economic deprivation is more prevalent and severe. However, evidence from South Asia is limited.MethodsWe pooled data from two large population-based studies in India to provide a geographically representative and adequately powered sample of Indian adults. We used multilevel linear regression models to assess associations between standard of living index (SLI) in childhood (measured by recalled household assets at age 10–12 years) and major cardiovascular risk factors including adiposity, blood pressure, and fasting blood lipids, glucose and insulin.ResultsData on 14 011 adults (median age 39 years, 56% men) were analysed. SLI in childhood was inversely associated with systolic and diastolic blood pressure, independent of socio-economic conditions in adulthood, with beta coefficients (95% CIs) of −0.70 mmHg (−1.17 to −0.23) and −0.56 mmHg (−0.91 to −0.22), respectively, per SD increase in SLI in childhood. There was no strong evidence for an association between SLI in childhood and other risk factors of cardiovascular disease.ConclusionsPoor socio-economic conditions in childhood may contribute to the increased risk of premature cardiovascular disease among South Asians by raising their blood pressure. Elucidating the mechanisms and improving socio-economic conditions for children in South Asia could provide major reductions in the burden of cardiovascular disease.

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“…We defined ‘self-report diabetes’ as all non-pregnant individuals who answered ‘yes’ to the question do you currently have diabetes. We defined ‘undiagnosed diabetes’ as participants who answered ‘no’ to the question do you currently have diabetes7 8 and following a laboratory assessment either had an opportunistic fasting glucose level ≥126 mg/dL (referred to as ‘fasting’) or had a random glucose level ≥200 mg/dL (referred to as ‘random’). We define ‘opportunistic fasting’ as individuals who self-reported that they had not eaten or had any calorie intake for 8 or more hours.…”

Section: Methodsmentioning

confidence: 99%

Characteristics of undiagnosed diabetes in men and women under the age of 50 years in the Indian subcontinent: the National Family Health Survey (NFHS-4)/Demographic Health Survey 2015–2016

Claypool

Chung

Deonarine

et al. 2020

BMJ Open Diab Res Care

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ObjectivePrior studies examining diabetes prevalence in India have found that nearly 50% of the diabetes population remains undiagnosed; however, the specific populations at risk are unclear.Research design and methodsFirst, we estimated the prevalence of undiagnosed diabetes in India for 750 924 persons between the ages of 15 years and 50 years who participated in the National Family Health Survey (NFHS-4)/Demographic Health Survey (2015–2016), a cross-sectional survey of all 29 states and 7 union territories of India. We defined ‘undiagnosed diabetes’ as individuals who did not know about their diabetes status but had high random (≥200 mg/dL) or fasting (≥126 mg/dL) blood glucose levels. Second, using Poisson regression, we associated 10 different factors, including the role of healthcare access, and undiagnosed diabetes. Third, we examined the association of undiagnosed diabetes with other potential comorbid conditions.ResultsThe crude prevalence of diabetes for women and men aged 15–50 years was 2.9%, 95% CI 2.9% to 3.1%, with self-reported diabetes prevalence at 1.7%, 95% CI 1.6 to 1.8. The overall prevalence of undiagnosed diabetes for 15–50 year olds was at 1.2%, 95% CI 1.2% to 1.3%. Forty-two per cent, 95% CI 40.7% to 43.4% of the individuals with high glucose levels were unaware of their diabetes status. Approximately 45%, 95% CI 42.9% to 46.4% of undiagnosed diabetes population had access to healthcare. Men, younger individuals, and those with lower levels of education were most at risk of being undiagnosed. Geographically, the Southern states in India had a significantly higher prevalence of undiagnosed diabetes despite having nearly universal access to healthcare. Risk factors combined with random glucose could predict undiagnosed diabetes (area under the curve of 97.8%, 95% CI 97.7% to 97.8%), Nagelkerke R2 of 66%).ConclusionClose to half (42%) of the people with diabetes in India are not aware of their disease status, and a large subset of these people are at risk of poor detection, despite having health insurance and/or having access to healthcare. Younger age groups and men are the most vulnerable.

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Socioeconomic Gradients and Distribution of Diabetes, Hypertension, and Obesity in India

Cited by 105 publications

References 30 publications

Prevalence of Diabetes Mellitus and Its Associated Factors in Bangladesh: Application of Two-level Logistic Regression Model

Prevalence of Diabetes Mellitus and Its Associated Factors in Bangladesh: Application of Two-level Logistic Regression Model

Childhood socio-economic conditions and risk of cardiovascular disease: results from a pooled sample of 14 011 adults from India

Characteristics of undiagnosed diabetes in men and women under the age of 50 years in the Indian subcontinent: the National Family Health Survey (NFHS-4)/Demographic Health Survey 2015–2016

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