Prevalence and risk factors for Anemia severity and type in malawian men and women: urban and rural differences
Open accessAbstract
BACKGROUND: The global burden of anemia is large especially in sub-Saharan Africa, where HIV is common and lifestyles are changing rapidly with urbanization. The effects of these changes are unknown. Studies of anemia usually focus on pregnant women or children, among whom the burden is greatest. We describe prevalence and risk factors for anemia among rural and urban men and women of all ages in Malawi. METHODS: We analyzed data from a population-wide cross-sectional survey of adults conducted in two sites, Karonga (rural) and Lilongwe (urban), commencing in May 2013. We used multinomial logistic regression models, stratified by sex to identify risk factors for mild and moderate-to-severe anemia. RESULTS: Anemia prevalence was assessed among 8,926 men (age range 18-100 years) and 14,978 women (age range: 18-103 years). Weighted prevalence levels for all, mild, and moderate-to-severe anemia were 8.2, 6.7 and 1.2% in rural men; 19.4, 12.0 and 7.4% in rural women; 5.9, 5.1 and 0.8% in urban men; and 23.4, 13.6 and 10.1% in urban women. Among women, the odds of anemia were higher among urban residents and those with higher socioeconomic status. Increasing age was associated with higher anemia prevalence in men. Among both men and women, HIV infection was a consistent risk factor for severity of anemia, though its relative effect was stronger on moderate-to-severe anemia. CONCLUSIONS: The drivers of anemia in this population are complex, include both socioeconomic and biological factors and are affecting men and women differently. The associations with urban lifestyle and HIV indicate opportunities for targeted intervention.
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Frequent or prolonged bleeds add to girls' and women's risk of anaemia, particularly for those who are nutritionally compromised or have comorbidities such as HIV.
“Physically, frequent or prolonged bleeds add to girls and women’s risk of anaemia, particularly for those who are nutritionally compromised, or having comorbidities such as HIV.24”
From Beyond menstrual hygiene: addressing vaginal bleeding throughout the life course in low and middle-income countries (2017) · cites this paper as [24]
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- Authors
- Adamu, A. L., Crampin, A., Kayuni, N., Amberbir, A., Koole, O., Phiri, A., Nyirenda, M., & Fine, P.
- Affiliations
- Bayero University Kano (NG)
- London School of Hygiene & Tropical Medicine (GB)
- Malawi Epidemiology and Intervention Research Unit (MW)
- Corresponding author
- Adamu, Aishatu L.
- Venue
- Population Health Metrics
- Published
- 2017-03-29
- Volume
- 15
- Issue
- 1
- Pages
- 12-12
- ISSN
- 1478-7954 (ISSN-L)
- PMC
- PMC5371260
- OpenAlex
- W2598653401
- Cited by
- 114
- References
- 52
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 14 · 2023: 14 · 2022: 16 · 2021: 20 · 2020: 21 · 2019: 5 · 2018: 5 · 2017: 4
- FWCI
- 7.35
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Population Health Metrics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Greater South Information System
- Funders
- Wellcome Trust
- Topics
- Health Sciences › Medicine › Hematology › Iron Metabolism and Disorders
- Health Sciences › Medicine › Genetics › Hemoglobinopathies and Related Disorders
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
- Keywords
- anemia, anemia severity, anemia prevalence, risk factors, HIV infection, urbanization, urban-rural differences, sex differences, socioeconomic status, adults, Malawi
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Anemia, Cross-Sectional Studies, Female, Humans, Malawi, Male, Middle Aged, Risk Factors, Rural Population, Severity of Illness Index, Sex Factors, Socioeconomic Factors, Urban Population, HIV Infections, Prevalence, Logistic Models, Young Adult
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