Spatiotemporal distribution and determinants of overweight or obesity among urban women in Ethiopia: a multivariate decomposition analysis

Abstract

Background Overweight /obesity is a global public health concern. It is higher among women than men in most continents of the world. This study aimed to determine the spatiotemporal distribution and determinants of changes in overweight/obesity over time among urban women in Ethiopia. Methods We used data from three consecutive Demographic and Health Surveys in Ethiopia (2005, 2011, and 2016). The total weighted sample of 1112 in 2005, 3569 in 2011, and 3071 in 2016 urban women were included in the analysis. The primary outcome measure of this study was the spatiotemporal distribution and trends over time in overweight/obesity. Factors contributing to change in overweight/obesity were examined using a logit-based multivariate decomposition analysis. Results Overweight/obesity increased from 14.2% in 2005 to 21% in 2016. Approximately 61.3% of the overall increase in overweight/obesity among urban women was due to the difference in coefficient (difference in the effect of characteristics) across the surveys. Changes in the composition of women aged 25–49 years (β = 0.012, 95% CI 0.008, 0.015), married women (β = 0.010, 95% CI 0.006, 0.014), women with formal education (primary: β = 0.007, 95% CI 0.003, 0.011, higher education: β = 0.014, 95% CI 0.006, 0.022), women with formal employment (β = 0.006, 95% CI 0.001, 0.011), and women with informal employment (β = − 0.002, 95% CI − 0.003, − 0.0004) were factors contributing to the change in overweight/obesity from 2005 to 2016. The risk difference (RD) in women’s overweight/obesity significantly varied across regions in urban Ethiopia. Furthermore, a high proportion of overweight/obesity was found mainly in Tigray, Oromia, Amhara, and Addis Ababa. Conclusions The rate of overweight/obesity among women in urban Ethiopia has shown a significant increase over the last 11 years. This rate change was due to changes in the composition of women’s age, educational status, marital status, and employment status. Therefore, program interventions should be targeted at older (> 25 years), educated, married, Addis Ababa residents, and formally employed women.

Trabajo Informal en Mujeres Cabeza de Familia de la Ciudad de Medellín: Caso de Estudio

“…Asimismo, el análisis de Azanaw et al (2022) se centró en la distribución espaciotemporal del sobrepeso y la obesidad en mujeres urbanas en Etiopía. Aunque este estudio no abordó directamente la informalidad laboral, ambos estudios coinciden en la importancia de abordar los factores que afectan la calidad de vida de las mujeres en contextos urbanos, señalando así la relevancia de considerar múltiples aspectos para mejorar las condiciones laborales y de vida de las mujeres cabeza de hogar en contextos urbanos.…”

“…El trabajo informal se refiere a actividades económicas no reguladas ni protegidas por el Estado, lo que implica la ausencia de seguridad laboral, prestaciones sociales y acceso a derechos laborales básicos. Este tipo de empleo suele llevarse a cabo en el sector de comercio ambulante, trabajo doméstico no remunerado, venta de productos en las calles, entre otros, lo que ha suscitado interrogantes sobre las razones que llevan a las mujeres a elegir estas opciones laborales (Azanaw et al, 2022;Volchik et al, 2021).…”

Factors Contributing to the Change in Overweight/Obesity Prevalence Among Indian Adults: A multivariate decomposition analysis of data from the National Family Health Surveys

“…Further, about 90% and 60% increases were attributed to these changes only. A previous study from Ethiopia conducted only among women attributed about 39% to the compositional differences [ 21 ]. Major contributing variables included age, urban residence, wealth index, access to clean fuel, toilet facilities, and unhealthy diet.…”

Spatial distribution and associated factors of co-occurrence of overweight/obesity and Anemia among women in the reproductive age in sub-Saharan Africa: A multilevel analysis, DHS 2016–2021

“…Regarding factors associated with co-occurrence of OWOB and anemia: being older age, married and richer wealth status [ 16 , 17 ], urban residency [ 16 , 18 ], being separated/divorced, widowed, unemployed, level of educational attainment [ 17 ], were significantly associated with co-occurrence of overweight/obesity and anemia. Besides, television watching [ 19 , 20 ], higher education [ 21 ], not working [ 19 ], use of hormonal contraception [ 22 , 23 ], and type of toilet facility [ 24 ], were associated with overweight and obesity. These factors lead to the development of anemia but more often coexist, which can be an indicator of both nutrition and health status [ 25 ].…”