Department of Survey Research and Data analytics, International Institute for Population Sciences(IIPS), Mumbai, India.
Department of Population and Development, International Institute for Population Sciences(IIPS), Mumbai, India.
Int J Public Health. 2023 Mar 29;68:1605595. doi: 10.3389/ijph.2023.1605595. eCollection 2023.
To determine the prevalence and predictors of combined BMI-WC disease risk categories among Indian adults. The study utilizes data from Longitudinal Ageing Study in India (LASI Wave 1) with an eligible sample of 66, 859 individuals. Bivariate analysis was done to get the proportion of individuals in different BMI-WC risk categories. Multinomial logistic regression was used to identify the predictors of BMI-WC risk categories. Poor self-rated health, female sex, urban place of residence, higher educational status, increasing MPCE quintile, and cardio-vascular disease increased with increasing BMI-WC disease risk level while increasing age, tobacco consumption, and engagement in physical activities was negatively associated with BMI-WC disease risk. Elderly persons in India have a considerable higher prevalence of BMI-WC disease risk categories which make them vulnerable to developing several disease. Findings emphasize the need of using combined BMI categories and waist circumference to assess the prevalence of obesity and associated disease risk. Finally, we recommend that intervention programs with an emphasis on urbanites wealthy women and those with a higher BMI-WC risk categories be implemented.
为了确定印度成年人中 BMI-WC 疾病风险类别联合出现的流行率和预测因素。本研究利用来自印度纵向老龄化研究(LASI 波 1)的数据,样本量为 66859 人。采用双变量分析获得不同 BMI-WC 风险类别的个体比例。采用多项逻辑回归来确定 BMI-WC 风险类别的预测因素。自我报告健康状况差、女性、城市居住地点、较高的教育程度、较高的 MPCE 五分位数以及心血管疾病随着 BMI-WC 疾病风险水平的增加而增加,而年龄增加、吸烟和身体活动的参与则与 BMI-WC 疾病风险呈负相关。印度的老年人中,BMI-WC 疾病风险类别的比例相当高,这使他们容易患上多种疾病。研究结果强调需要使用 BMI 类别和腰围来评估肥胖和相关疾病风险的流行率。最后,我们建议实施以城市居民、富裕女性和 BMI-WC 风险较高的人群为重点的干预计划。