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. 2023 Apr 14:12:100188.
doi: 10.1016/j.lansea.2023.100188. eCollection 2023 May.

Changing socioeconomic and geographic gradients in cardiovascular disease risk factors among Indians aged 15-49 years - evidence from nationally representative household surveys

Affiliations

Changing socioeconomic and geographic gradients in cardiovascular disease risk factors among Indians aged 15-49 years - evidence from nationally representative household surveys

Sarah Wetzel et al. Lancet Reg Health Southeast Asia. .

Abstract

Background: Cardiovascular diseases (CVDs) are the leading cause of death in most low- and middle-income countries (LMICs). CVDs and their metabolic risk factors have historically been concentrated among urban residents with higher socioeconomic status (SES) in LMICs such as India. However, as India develops, it is unclear whether these socioeconomic and geographic gradients will persist or change. Understanding these social dynamics in CVD risk is essential for mitigating the rising burden of CVDs and to reach those with the greatest needs.

Methods: Using nationally representative data with biomarker measurements from the fourth (2015-16) and fifth (2019-21) Indian National Family and Health Surveys, we investigated trends in the prevalence of four CVD risk factors: smoking (self-reported), unhealthy weight (BMI ≥25 kgm2), diabetes (random plasma glucose concentration ≥200 mg/dL or self-reported diabetes), and hypertension (one of: average systolic blood pressure ≥140 mmHg, average diastolic blood pressure ≥90 mmHg, self-reported past diagnosis, or self-reported current antihypertensive medication use) among adults aged 15-49 years. We first described changes at the national level and then trends stratified by place of residence (urban versus rural), geographic region (northern, northeastern, central, eastern, western, southern), regional level of development (Empowered Action Group member state or not), and two measures of socioeconomic status: level of education (no education, primary incomplete, primary complete, secondary incomplete, secondary complete, higher) and wealth (quintiles).

Findings: Unhealthy weight increased among all social and geographic groups but both the absolute and the relative changes were substantially higher among people with low SES (as measured by education or wealth) and in rural areas. For diabetes and hypertension, the prevalence increased for those from disadvantaged groups while staying constant or even decreasing among the wealthier and more educated. In contrast, smoking consumption declined for all social and geographic groups.

Interpretation: In 2015-16, CVD risk factors were higher among more advantaged subpopulations in India. However, between 2015-16 and 2019-21, the prevalence of these risk factors grew more rapidly for less wealthy and less educated subpopulations and those living in rural areas. These trends have resulted in CVD risk becoming far more widespread throughout the population; CVD can no longer be characterized as a wealthy urban phenomenon.

Funding: This work was supported by the Alexander von Humboldt Foundation (grant received by NS); the Stanford Diabetes Research Center [grant received by PG] and the Chan Zuckerberg Biohub [grant received by PG].

Keywords: Cardiovascular diseases; Diabetes; Hypertension; India; Obesity; Overweight; Risk factor; Smoking; Socioeconomic gradients; Socioeconomic status; Tobacco consumption.

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Conflict of interest statement

Outside the scope of the submitted manuscripts, Mohammed K. Ali received personal advisory board fees from Eli Lilly and Bayer and Emory University received a grant from Merck & Co. The other authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Age-standardized absolute change in each CVD risk factor among adults aged 15–49 by wealth quintile, level of education, and place of residence, National Family Health Survey 4 (2015–16) and 5 (2019–21), India.
Fig. 2
Fig. 2
Age-standardized relative change in each CVD risk factor among adults aged 15–49 by wealth quintile, level of education, and place of residence, National Family Health Survey 4 (2015–16) and 5 (2019–21), India.
Fig. 3
Fig. 3
Age-standardized absolute changes (percentage points) in the prevalence of CVD risk factors across Indian regions, National Family Health Survey 4 (2015–16) and 5 (2019–21), India.

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