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Socio-demographic predictors of obesity among women in Mukono Central Division in Central Uganda: a cross-sectional study

BACKGROUND: There is a steadily increasing trend in obesity globally and in Sub-Saharan Africa that disproportionately affects women in most places. This is not different in Uganda, where the Uganda Demographic and Health Survey indicated an increase in obesity among women of reproductive age as mea...

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Detalles Bibliográficos
Autores principales: Athieno, Justine, Seera, Georgina, Mayanja Namayengo, Faith Muyonga, Galabuzi, Joweria Nambooze, Namasaba, Mariam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10629151/
https://www.ncbi.nlm.nih.gov/pubmed/37932691
http://dx.doi.org/10.1186/s12905-023-02679-4
Descripción
Sumario:BACKGROUND: There is a steadily increasing trend in obesity globally and in Sub-Saharan Africa that disproportionately affects women in most places. This is not different in Uganda, where the Uganda Demographic and Health Survey indicated an increase in obesity among women of reproductive age as measured by the body mass index (BMI). However, studies on the predictors of obesity in women are still limited. Particularly, studies using specific indicators of body fat are scant. This study explored the socio-demographic predictors of obesity as indicated by total body fat percentage among women in the age range of 18 to 69 years old living in Mukono Central Division in Central Uganda. METHODS: A cross sectional study design using quantitative methods was employed. A total of 384 women between 18 and 69 years old from Mukono Central Division in Central Uganda were randomly recruited. A structured questionnaire was used to collect socio-demographic data including age, level of education, marital status, childbearing status, household expenditure, household size and employment status. Total body fat percentage, the indicator for obesity was measured using the body composition meter from TANITA. The data was analyzed using multinomial logistic regression analysis using SPSS version 20. RESULTS: 155 women, nearly two fifths (40.4% CI 95% 38.4–42.4) were classified as obese. Age, marital status, childbearing status, and employment status were the factors that were associated with obesity among these women. Employment status was the only variable that remained significantly associated with obesity among the women after adjusting for other factors. Unemployed women were nearly two times more likely to be obese than the employed women (AOR 1.9; 95% CI 1.1–3.1). The prevalence of obesity among the unemployed and employed women was 48.2% and 34.4% respectively. CONCLUSIONS: Obesity in women was predicted by employment status. An in-depth study on factors that predispose unemployed women to obesity, will be instrumental in guiding interventions to curb the emerging obesity epidemic in Uganda. In the same vein, strategies to reduce levels of unemployment among women living in urban Uganda are essential for protecting public health from the dimension of reducing obesity levels.