Socioeconomic status and cardiovascular risk in urban South Asia: The CARRS Study. (29th August 2020)

• Record Type: Journal Article
• Authors: Ali, Mohammed K; Bhaskarapillai, Binukumar; Shivashankar, Roopa; Mohan, Deepa; Fatmi, Zafar A; Pradeepa, Rajendra; Masood Kadir, M; Mohan, Viswanathan; Tandon, Nikhil; Venkat Narayan, KM; Prabhakaran, Dorairaj
• Is Part Of: European journal of preventive cardiology. Volume 23:Number 4(2016)
• Page Start: 408
• Page End: 419
• Publication Date: 2020-08-29
• Subjects: Cardiovascular risk factors -- South Asians -- socioeconomic status -- global cardiovascular health; Cardiovascular system -- Diseases -- Prevention -- Periodicals; Cardiac patients -- Rehabilitation -- Periodicals; 616.12
• DOI: 10.1177/2047487315580891
• Languages: English
• ISSNs: 2047-4873

Abstract

Abstract: Background: Although South Asians experience cardiovascular disease (CVD) and risk factors at an early age, the distribution of CVD risks across the socioeconomic spectrum remains unclear. Methods: We analysed the 2011 Centre for Cardiometabolic Risk Reduction in South Asia survey data including 16, 288 non-pregnant adults (≥20 years) that are representative of Chennai and Delhi, India, and Karachi, Pakistan. Socioeconomic status (SES) was defined by highest education (primary schooling, high/secondary schooling, college graduate or greater); wealth tertiles (low, middle, high household assets) and occupation (not working outside home, semi/unskilled, skilled, white-collar work). We estimated age and sex-standardized prevalence of behavioural (daily fruit/vegetables; tobacco use), weight (body mass index; waist-to-height ratio) and metabolic risk factors (diabetes, hypertension, hypercholesterolaemia; hypo-HDL; and hypertriglyceridaemia) by each SES category. Results: Across cities, 61.2% and 16.1% completed secondary and college educations, respectively; 52.8% reported not working, 22.9% were unskilled; 21.3% were skilled and 3.1% were white-collar workers. For behavioural risk factors, low fruit/vegetable intake, smoked and smokeless tobacco use were more prevalent in lowest education, wealthy and occupation (for men only) groups compared to higher SES counterparts, while weight-related risks (body mass index 25.0–29.9 and ≥30 kg/m 2 ; waist-to-height ratio ≥0.5) were more common in higher educated and wealthy groups, and technical/professional men. For metabolic risks, a higher prevalence of diabetes, hypertension and dyslipidaemias was observed in more educated and affluent groups, with unclear patterns across occupation groups. Conclusions: SES-CVD patterns are heterogeneous, suggesting customized interventions for different SES groups may be warranted. Different behavioural, weight, and metabolic risk factor prevalence patterns across SES indicators may signal on-going epidemiological transition in South Asia.