The prevalence and associated factors of underweight and overweight/obesity among adults in kenya: Evidence from a national cross-sectional community survey - Supa Pengpid (2020)
© Supa Pengpid et al. Pan African Medical Journal. Introduction: the study aimed to investigate the prevalence and factors associated with underweight and overweight or obesity in an adult population in Kenya. Methods: data from a cross-sectional nationally representative community-based study in Kenya (N=4283, 18-69 years) conducted in 2015 was utilized. Assessments included anthropometric, interview, blood pressure and biochemistry mesures. Multinomial logistic regression was used to assess the determinants of underweight and overweight or obesity relative to normal weight. Results: in all, 11.9% of the study sample was underweight (BMI <18.5kg/m²), 60.1% had normal weight (BMI 18.5-24.9kg/m²), 18.9% overweight (25.0-29.9kg/m²) and 9.1% obesity (BMI ≥30.0kg/m²). In adjusted multinomial logistic regression, male sex (adjusted relative risk ratio-ARRR: 1.47, confidence interval-CI: 1.01, 2.13), lower education (ARRR: 0.63, CI: 0.46, 0.88), lower wealth status (ARRR: 0.47, CI: 0.29, 0.78), inadequate fruit and vegetable consumption (ARRR: 1.79, CI: 1.19, 2.70), adding daily sugar into beverages (ARRR: 1.49, CI: 1.01, 2.22) and having no hypertension (ARRR: 0.54, CI: 0.40, 0.74) were associated with underweight. Factors associated with overweight or obesity were middle and older age (ARRR: 2.15, CI: 1.46, 3.80), being female (ARRR: 0.30, CI: 0.22, 0.41), higher education (ARRR: 1.61, CI: 1.26, 2.24), greater wealth (ARRR: 2.38, CI: 1.41, 3.50), being a Kikuyu by ethnic group (ARRR: 1.68, CI: 1.19, 2.37), urban residence (ARRR: 1.45, CI: 1.06, 1.99), no current tobacco use (ARRR: 0.39, CI: 0.24, 0.54), low physical activity (ARRR: 1.49, CI: 1.02, 2.18) and having hypertension (ARRR: 1.96, CI: 1.54, 2.50). Conclusion: more than one in ten were underweight and almost three in ten were overweight or obese among adults in Kenya. Several risk factors, including sociodemographic, lifestyle and health status risk variables, were identified for underweight and overweight or obesity, which can assist in developing intervention strategies targeting both these conditions.