{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T06:29:27Z","timestamp":1792650567846,"version":"4.5.0"},"reference-count":89,"publisher":"BMJ","issue":"2","license":[{"start":{"date-parts":[[2024,2,10]],"date-time":"2024-02-10T00:00:00Z","timestamp":1707523200000},"content-version":"unspecified","delay-in-days":9,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2024,1,22]]},"published-print":{"date-parts":[[2024,2]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Globally, malnutrition among women of reproductive age is on the rise and significantly contributing to non-communicable disease, deaths and disability. Even though the double burden of malnutrition (DBM) is a common problem among women in sub-Saharan Africa (SSA), there are limited studies examining the factors contributing to underweight, overweight, and obesity at the SSA level.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To determine the factors associated with the DBM, and their relative magnitude, among women of reproductive age in SSA.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Cross-sectional study design.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>33 SSA countries.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>240\u2009414\u2009women of reproductive age.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Primary and secondary outcome measures<\/jats:title>\n                    <jats:p>A multilevel multinomial logistic regression model was applied to identify factors associated with malnutrition. The adjusted relative risk ratio with 95% CI was used to declare the statistical significance of the association.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The pooled prevalence of underweight, overweight and obesity among women in SSA were 8.87%, 16.47% and 6.10%, respectively. Women who are from rural residence and smoke cigarettes were more likely to be underweight. Conversely, women between the age of 24\u201334 and 35\u201349, who have higher education, belong to a middle and rich household, are ever married, have high parity, use contraceptives, have media exposure and smoke cigarettes were more likely to be overweight and\/or obese.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The findings of our study suggest that certain factors such as residence, education status, wealth, marital status, occupation, cigarette smoking, and contraceptive use have a significant assocation with malnutrition among women. Therefore, it is important for public health programs aimed at preventing the double burden of malnutrition to focus on these factors through comprehensive public awareness and cost-effective operational health interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2023-073447","type":"journal-article","created":{"date-parts":[[2024,2,10]],"date-time":"2024-02-10T20:35:16Z","timestamp":1707597316000},"page":"e073447","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":23,"title":["Double burden of malnutrition and associated factors among women of reproductive age in sub-Saharan Africa: a multilevel multinomial logistic regression analysis"],"prefix":"10.1136","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9278-6826","authenticated-orcid":false,"given":"Beminate Lemma","family":"Seifu","sequence":"first","affiliation":[{"name":"Department of Public Health, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kusse Urmale","family":"Mare","sequence":"additional","affiliation":[{"name":"Department of Nursing, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6639-3060","authenticated-orcid":false,"given":"Bruck Tesfaye","family":"Legesse","sequence":"additional","affiliation":[{"name":"Department of Pediatrics and Neonatal Nursing, School of Nursing and Midwifery, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2911-2095","authenticated-orcid":false,"given":"Tsion Mulat","family":"Tebeje","sequence":"additional","affiliation":[{"name":"School of Public Health, College of health sciences and Medicine, Dilla University, Dilla, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2024,2,10]]},"reference":[{"key":"2025121422221124000_14.2.e073447.1","unstructured":"Abdullah A . 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