Modifiable risk factors for anemia among women of childbearing age in sub-saharan Africa (2015–2023)
Abstract Background The Sustainable Development Goals Target 2.2 aims to eliminate all forms of malnutrition, including anemia, while the World Health Assembly targets a 50% reduction in anemia among women of childbearing age by 2025. Despite these efforts, global anemia prevalence among women has o...
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2025-01-01
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| Online Access: | https://doi.org/10.1186/s12889-025-21427-x |
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| author | Beminate Lemma Seifu Yohannes Mekuria Negussie Angwach Abrham Asnake Bezawit Melak Fente Zufan Alamrie Asmare Mamaru Melkam Meklit Melaku Bezie Alemayehu Kasu Gebrehana Sintayehu Simie Tsega Hiwot Atlaye Asebe |
| author_facet | Beminate Lemma Seifu Yohannes Mekuria Negussie Angwach Abrham Asnake Bezawit Melak Fente Zufan Alamrie Asmare Mamaru Melkam Meklit Melaku Bezie Alemayehu Kasu Gebrehana Sintayehu Simie Tsega Hiwot Atlaye Asebe |
| author_sort | Beminate Lemma Seifu |
| collection | DOAJ |
| description | Abstract Background The Sustainable Development Goals Target 2.2 aims to eliminate all forms of malnutrition, including anemia, while the World Health Assembly targets a 50% reduction in anemia among women of childbearing age by 2025. Despite these efforts, global anemia prevalence among women has only slightly decreased from 31% to 30% between 2000 and 2019. Therefore, identifying modifiable risk factors for anemia among women of childbearing age in Africa is crucial for developing evidence-based interventions and achieving these goals. Methods We conducted an analysis of the most recent Demographic and Health Surveys datasets from 21 Sub-Saharan Africa (SSA) countries, which were carried out between 2015 and 2023. Using multilevel multinomial regression models, we calculated the Adjusted Odds Ratio (AOR) with a 95% Confidence Interval, and subsequently estimated the Population Attributable Fraction (PAF) based on these AOR values. Results The study consisted of 168,417 women of childbearing age [–] (15-49) from 21 SSA. The highest proportion of moderate to severe anemia was linked to the type of contraceptive method used (PAF = 53.11%). This was followed by the lack of health insurance coverage (PAF = 37.92%). Other significant factors included poverty (PAF = 11.50%), no formal education (PAF = 18.01%), high parity (PAF = 5.78%), and the use of unimproved drinking water sources (PAF = 3.88%). These 5 modifiable risk factors were associated with 80.60% (95%CI, 77.60-83.40%) moderate/severe anemia in SSA. Conclusion In a cross-sectional study involving 21 SSA nations, we identified 5 modifiable risk factors associated with anemia among women of childbearing age in SSA. These factors should be a priority for policymakers when planning future interventions to address anemia in SSA’s women’s health. |
| format | Article |
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| institution | Kabale University |
| issn | 1471-2458 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-5e0012d2d7a641bc8c58a1ce30a3a7f72025-01-26T12:56:22ZengBMCBMC Public Health1471-24582025-01-0125111210.1186/s12889-025-21427-xModifiable risk factors for anemia among women of childbearing age in sub-saharan Africa (2015–2023)Beminate Lemma Seifu0Yohannes Mekuria Negussie1Angwach Abrham Asnake2Bezawit Melak Fente3Zufan Alamrie Asmare4Mamaru Melkam5Meklit Melaku Bezie6Alemayehu Kasu Gebrehana7Sintayehu Simie Tsega8Hiwot Atlaye Asebe9Department of Public Health, College of Medicine and Health Sciences, Samara UniversityDepartment of Medicine, Adama General Hospital and Medical CollegeDepartment of Epidemiology and Biostatistics, School of Public Health, College of Medicine and Health Sciences, Wolaita Sodo UniversityDepartment of General Midwifery, School of Midwifery, College of Medicine & Health Sciences, University of GondarDepartment of Ophthalmology, School of Medicine and Health Science, Debre Tabor UniversityCollege of Medicine and Health Science, Department of Psychiatry, University of GondarDepartment of Public Health Officer, Institute of Public Health, College of Medicine and Health Sciences, University of GondarDepartment of Midwifery, College of Health Sciences, Salale UniversityDepartment of Medical Nursing, School of Nursing, College of Medicine and Health Science, University of GondarDepartment of Public Health, College of Medicine and Health Sciences, Samara UniversityAbstract Background The Sustainable Development Goals Target 2.2 aims to eliminate all forms of malnutrition, including anemia, while the World Health Assembly targets a 50% reduction in anemia among women of childbearing age by 2025. Despite these efforts, global anemia prevalence among women has only slightly decreased from 31% to 30% between 2000 and 2019. Therefore, identifying modifiable risk factors for anemia among women of childbearing age in Africa is crucial for developing evidence-based interventions and achieving these goals. Methods We conducted an analysis of the most recent Demographic and Health Surveys datasets from 21 Sub-Saharan Africa (SSA) countries, which were carried out between 2015 and 2023. Using multilevel multinomial regression models, we calculated the Adjusted Odds Ratio (AOR) with a 95% Confidence Interval, and subsequently estimated the Population Attributable Fraction (PAF) based on these AOR values. Results The study consisted of 168,417 women of childbearing age [–] (15-49) from 21 SSA. The highest proportion of moderate to severe anemia was linked to the type of contraceptive method used (PAF = 53.11%). This was followed by the lack of health insurance coverage (PAF = 37.92%). Other significant factors included poverty (PAF = 11.50%), no formal education (PAF = 18.01%), high parity (PAF = 5.78%), and the use of unimproved drinking water sources (PAF = 3.88%). These 5 modifiable risk factors were associated with 80.60% (95%CI, 77.60-83.40%) moderate/severe anemia in SSA. Conclusion In a cross-sectional study involving 21 SSA nations, we identified 5 modifiable risk factors associated with anemia among women of childbearing age in SSA. These factors should be a priority for policymakers when planning future interventions to address anemia in SSA’s women’s health.https://doi.org/10.1186/s12889-025-21427-xAnemiaDemographic and health surveyPopulation attributable fractionSub-saharan AfricaWomen of childbearing age |
| spellingShingle | Beminate Lemma Seifu Yohannes Mekuria Negussie Angwach Abrham Asnake Bezawit Melak Fente Zufan Alamrie Asmare Mamaru Melkam Meklit Melaku Bezie Alemayehu Kasu Gebrehana Sintayehu Simie Tsega Hiwot Atlaye Asebe Modifiable risk factors for anemia among women of childbearing age in sub-saharan Africa (2015–2023) BMC Public Health Anemia Demographic and health survey Population attributable fraction Sub-saharan Africa Women of childbearing age |
| title | Modifiable risk factors for anemia among women of childbearing age in sub-saharan Africa (2015–2023) |
| title_full | Modifiable risk factors for anemia among women of childbearing age in sub-saharan Africa (2015–2023) |
| title_fullStr | Modifiable risk factors for anemia among women of childbearing age in sub-saharan Africa (2015–2023) |
| title_full_unstemmed | Modifiable risk factors for anemia among women of childbearing age in sub-saharan Africa (2015–2023) |
| title_short | Modifiable risk factors for anemia among women of childbearing age in sub-saharan Africa (2015–2023) |
| title_sort | modifiable risk factors for anemia among women of childbearing age in sub saharan africa 2015 2023 |
| topic | Anemia Demographic and health survey Population attributable fraction Sub-saharan Africa Women of childbearing age |
| url | https://doi.org/10.1186/s12889-025-21427-x |
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