An assessment of anthropometric indices and its association with NCDs among the older adults of India: evidence from LASI Wave-1

Abstract

Background The purpose of this study is to assess the status of physical body indices such as body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) among the older adults aged 45 and above in India. Further, to explore the association of anthropometric indices with various non-communicable morbidities. Methods The study uses secondary data of the Longitudinal Ageing Survey’s first wave in India (2017–18). The national representative sample for older adults 45 and above (65,662) considered for the analysis. The prevalence of the non-communicable diseases (NCDs) included in the study is based on the self-reporting of the participants. Diseases included are among the top ten causes of death, such as cancer, hypertension, stroke, chronic heart diseases, diabetes, chronic respiratory diseases, and multi-morbidity. Multi-morbidity is a case of having more than one of the morbidities mentioned above. BMI-obese indicates an individual having a BMI ≥30, and the critical threshold value for high-risk WC for men is ≥102 cm while for women is ≥88 cm. The critical limit for the high-risk WHR for men and women is ≥0.90 and ≥ 0.85, respectively. Descriptive statistics and multiple logistic regressions are used to assess the association BMI, WC, and WHR with non-communicable morbidities. Results Based on the multivariate-adjusted model, odds shows that an Indian older adult aged 45 and above is 2.3 times more likely (AOR: 2.33; 95% CI (2.2, 2.5)) by obesity, 61% more likely (AOR: 1.61; 95% CI (1.629, 1.631)) by high-risk WHR and 98% more likely (AOR: 1.98; 95% CI (1.9, 2.1)) by high-risk WC to develop CVDs than their normal counterparts. Similarly, significant positive associations of obesity, high-risk WC, and high-risk WHR were observed with other NCDs and multi-morbidity. Conclusion Our study shows that obesity, high-risk WC, and high-risk WHR are significant risks for developing NCDs and multi-morbidity among the older adults in India. There is a need for a multi-sectoral approach to reduce the share of the elderly population in high-risk groups of BMIs, WHR, and WC.

Gender differences in the association of obesity-related measures with multi-morbidity among older adults in India: evidence from LASI, Wave-1

“…Other population-based studies conducted in low and middle income countries also found relationships between multi-morbidity and measures of waist circumference and waist-to-hip ratio in older ages [ 22 , 49 ]. The finding is in agreement with a recent study in India that found that adults aged 45 and above with obesity and high-risk waist circumference or waist-hip ratio were more likely to develop cardiovascular diseases than their counterparts [ 50 ], and another study reporting that a higher BMI among general population is associated with a greater prevalence of chronic diseases [ 51 ].…”

Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study

“…Central obesity includes several established and novel indices. Waist circumference (WC) is a commonly used clinical indicator that is strongly associated with the development of CVD, diabetes, hypertension, cancer, and kidney diseases [14,15]. However, WC does not take into account differences in height and therefore may lead to overestimating the risk for taller people or underestimating the risk for shorter people.…”

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

“…On full-text assessment, most exclusions (n=85) were of studies performing only correlation analyses between anthropometric measures and CVD incidence. 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 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.…”