4.7 Article

The epidemiological landscape of anemia in women of reproductive age in sub-Saharan Africa

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SCIENTIFIC REPORTS
卷 11, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41598-021-91198-z

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The study found a positive association between anemia and factors such as malaria incidence and HIV prevalence in women of reproductive age in sub-Saharan Africa. Pregnant women or those under deworming medication, women aged 25-34 with low education and income, living in urban settings, and underweight women were at higher risk of anemia. Low education and wealth index were consistently associated with anemia across SSA, with increased risk in Central and Western Africa.
The role of geographical disparities of health-related risk factors with anemia are poorly documented for women of reproductive age in sub-Saharan Africa (SSA). We aimed to determine the contribution of potential factors and to identify areas at higher risk of anemia for women in reproductive age in SSA. Our study population comprised 27 nationally representative samples of women of reproductive age (15-49) who were enrolled in the Demographic and Health Surveys and conducted between 2010 and 2019 in SSA. Overall, we found a positive association between being anemic and the ecological exposure to malaria incidence [adjusted odds ratio (AOR)=1.02, 95% confidence interval (CI) 1.02-1.02], and HIV prevalence (AOR=1.01, CI 1.01-1.02). Women currently pregnant or under deworming medication for the last birth had 31% (AOR=1.31, CI 1.24-1.39) and 5% (AOR=1.05, CI 1.01-1.10) higher odds of having anemia, respectively. Similarly, women age 25-34 years old with low education, low income and living in urban settings had higher odds of having anemia. In addition, underweight women had 23% higher odds of suffering anemia (AOR = 1.23, CI 1.15-1.31). Females with low levels of education and wealth index were consistently associated with anemia across SSA. Spatial distribution shows increased risk of anemia in Central and Western Africa. Knowledge about the contribution of known major drivers and the spatial distribution of anemia risk can mitigate operational constraints and help to design geographically targeted intervention programs in SSA.

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