Association of anthropometric measures of obesity and physical activity with cardio-vascular diseases among older adults: Evidence from a cross-sectional survey, 2017–18

Abstract

Background With the increase in elderly population, the risk of cardiovascular diseases (CVD) among Indian older adults is also increasing. The present paper tries to assess how different anthropometric measures of obesity and physical activity affects cardiovascular disease risk among older adults in India. Methods The data from Longitudinal Ageing Study in India (LASI) has been used. The total sample size for the present study is 31,464 older adults aged 60 years and above. Chi-square test and binary logistic regression has been used to measure the association of obesity measures and CVD prevalence. Results About 35.2% (n = 11,058) of the older adults suffered from CVD. Moreover, 22.2% (n = 6,217) of the older adults were obese/overweight, 23.7% (n = 6,651) had high risk waist circumference and 77.0% (n = 21,593) had high risk waist-Hip ratio. The likelihood of CVD was 60%, 50%, and 34% significantly higher among older adults who were obese/overweight [Adjusted odds ratio (AOR): 1.60; CI: 1.48–1.72], had high risk waist circumference [AOR: 1.50; CI: 1.39–1.62] and high risk waist-Hip ratio [AOR: 1.34; CI: 1.25–1.44], respectively compared to older adults with normal BMI and those who do not have a high risk waist circumference and high risk waist hip ratio. Moreover, older adults who never did physical activity had 22 per cent higher risk of CVD than those who did frequent [AOR: 1.22; CI: 1.13–1.32] physical activity. Conclusion The burden of overweight and obesity along with physical inactivity increases the risk of CVD in older adults. These findings highlight the urgent need for framing direct and indirect strategies to control obesity in order to reduce the burden of CVD among older adults in India.

Associations of general and central adiposity with hypertension and cardiovascular disease among South Asian populations: a systematic review and meta-analysis

“…The number of participants in included studies varied between 140 and 59 037 24 25. There were 25 (83.3%) included studies in India19 24–47 and three (10%) in Bangladesh 48–50. The remaining two studies were conducted in Mauritian51 and Pakistani52 populations, respectively.…”

“…The remaining two studies were conducted in Mauritian51 and Pakistani52 populations, respectively. The final analyses included two prospective cohort studies (one looking at HTN26 and one looking at CVD mortality51), four case-control studies44–47 (looking at CVD outcomes) and 24 cross-sectional studies19 24 25 27–43 48–50 52 (looking at HTN outcomes). In terms of exposure variables, 29 studies included BMI, 27 studies used WC, 21 studies used WHR and ten studies additionally used other measures, including WHtR (n=6) and hip circumference (n=2).…”

“…In terms of exposure variables, 29 studies included BMI, 27 studies used WC, 21 studies used WHR and ten studies additionally used other measures, including WHtR (n=6) and hip circumference (n=2). Overall, 18 studies looked at HTN,24 26 28–38 40 41 48–50 with or without blood pressure, eight looked at CVD,25 42–47 52 three looked at blood pressure alone19 27 39 and one study looked at CVD mortality 51…”

“…The analyses of non-fatal and fatal CVD included one cohort, four cross-sectional and four case–control studies. Four studies concluded that there was a stronger association of high BMI than of high WC and WHR with risk of CVD and CVD mortality 25 42 43 47. The remaining five studies concluded that measures of central adiposity, namely WC and/or WHR, showed stronger associations with CVD and CVD mortality than BMI 44–46 51 52.…”

Relationship between Framingham Cardiovascular Risk Score and cognitive performance among ageing rural Indian participants: a cross-sectional analysis

“…A very large cohort study from India with a sample size of around 65 000 people demonstrated that the prevalence of CVD is high in India and women when compared with men have a higher risk of developing CVD 26. Results from the same cohort study revealed that physical inactivity and obesity increased the likelihood of CVD by 22% and 60%, respectively 27. Lifestyle-based interventions are the need of the hour to address these risk factors so that their impact on cognitive performance can be reduced.…”