Self-Empowerment and Health Outcomes in Obese Adults with Type 2 Diabetes Following Completion of a Multi-Disciplinary Metabolic Rehabilitation Program

RH, Bishay

doi:10.15406/emij.2017.05.00117

Cited by 1 publication

(3 citation statements)

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“…Women with secondary or higher education had higher odds of being overweight, while being employed was identified as a predictor of overweight/obesity in Nigeria and South Africa. Our findings also agree with these earlier studies, as socio-economic status is one of the major predictors of overweight/obesity in both countries [ 51 , 64 , 68 , 69 ]. In addition, research indications have revealed that higher education attainment is associated with the better health status of the community, owing to an improvement in socio-economic status [ 68 , 69 ], health literacy and health behaviors [ 65 , 66 ], and self-control and empowerment [ 51 , 64 , 69 ].…”

Section: Discussionsupporting

confidence: 94%

“…Our findings also agree with these earlier studies, as socio-economic status is one of the major predictors of overweight/obesity in both countries [ 51 , 64 , 68 , 69 ]. In addition, research indications have revealed that higher education attainment is associated with the better health status of the community, owing to an improvement in socio-economic status [ 68 , 69 ], health literacy and health behaviors [ 65 , 66 ], and self-control and empowerment [ 51 , 64 , 69 ]. This is not always the case in less developed and developing countries such as Nigeria and South Africa, where those with higher education are more likely to be overweight or obese [ 37 , 38 , 41 , 44 ].…”

Section: Discussionsupporting

confidence: 94%

“…These study findings are in line with other studies conducted in South Asian [ 49 , 51 , 52 ] and other African countries [ 39 , 40 , 59 ]. Studies have documented that the upturn in women’s employment is an important contributing factor to the direct causes of undernutrition such as feeding practices and ill health, and more distinct bases of undernutrition (such as income, food security, and education) have a greater prospect to improve women’s nutritional status [ 64 , 65 , 66 ].…”

Section: Discussionmentioning

confidence: 99%

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Multilevel Analysis of Urban–Rural Variations of Body Weights and Individual-Level Factors among Women of Childbearing Age in Nigeria and South Africa: A Cross-Sectional Survey

Akokuwebe

Idemudia

2021

IJERPH

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Background: An unhealthy body weight is an adverse effect of malnutrition associated with morbidity among women of childbearing age. While there is increasing attention being paid to the body weights of children and adolescents in Nigeria and South Africa, a major surge of unhealthy body weight in women has received less attention in both countries despite its predominance. The purpose of this study was to explore the prevalence of body weights (underweight, normal, overweight, and obese) and individual-level factors among women of childbearing age by urban–rural variations in Nigeria and South Africa. Methods: This study used the 2018 Nigeria Demographic Health Survey data (n = 41,821) and 2016 South Africa Demographic Health Survey (n = 8514). Bivariate, multilevel, and intracluster correlation coefficient analyses were used to determine individual-level factors associated with body weights across urban–rural variations. Results: The prevalence of being overweight or obese among women was 28.2% and 44.9%, respectively, in South Africa and 20.2% and 11.4% in Nigeria. A majority, 6.8%, of underweight women were rural residents in Nigeria compared to 0.8% in South Africa. The odds of being underweight were higher among women in Nigeria who were unemployed, with regional differences and according to breastfeeding status, while higher odds of being underweight were found among women from poorer households, with differences between provinces and according to cigarette smoking status in South Africa. On the other hand, significant odds of being overweight or obese among women in both Nigeria and South Africa were associated with increasing age, higher education, higher wealth index, weight above average, and traditional/modern contraceptive use. Unhealthy body weights were higher among women in clustering areas in Nigeria who were underweight (intracluster correlation coefficient (ICC = 0.0127), overweight (ICC = 0.0289), and obese (ICC = 0.1040). Similarly, women of childbearing age in clustering areas in South Africa had a lower risk of experiencing underweight (ICC = 0.0102), overweight (ICC = 0.0127), and obesity (ICC = 0.0819). Conclusions: These findings offer a deeper understanding of the close connection between body weights variations and individual factors. Addressing unhealthy body weights among women of childbearing age in Nigeria and South Africa is important in preventing disease burdens associated with body weights in promoting Sustainable Development Goal 3. Strategies for developing preventive sensitization interventions are imperative to extend the perspectives of the clustering effect of body weights on a country level when establishing social and behavioral modifications for body weight concerns in both countries.

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