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However, a staggering 2 million stillbirths occur each year, equivalent to one every 16\u00a0s. Furthermore, approximately 98% of these stillbirths take place in developing countries, particularly in sub-Saharan Africa (SSA). In light of these statistics and the need to address the lack of data, methodological approaches, and population gaps, this study aims to assess the prevalence and determinants of stillbirths in SSA from 2016 to 2023, aligning with the SDGs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This study used data from the Demographic and Health Survey (DHS) conducted in SSA. The analysis included a weighted sample of 212,194 pregnancies of\u00a0at least 28\u00a0weeks' gestation collected\u00a0from 2016 to 2023, using R-4.4.0 software. Descriptive data, such as frequencies, were performed. Stillbirth prevalence was visualized using a forest plot. A multilevel modeling analysis was used by considering individual-level factors and community level factors. The multilevel model was employed to\u00a0account for clustering within countries and allow for the examination of both fixed and random effects that influence stillbirths. For the multivariable analysis, variables with a\n                      <jats:italic>p<\/jats:italic>\n                      value\u2009\u2264\u20090.2 in the bivariate analysis were considered. The Adjusted Odds Ratio (AOR) with a 95% Confidence Interval (CI) and a\n                      <jats:italic>p<\/jats:italic>\n                      value\u2009&lt;\u20090.05 were reported to indicate the statistical significance and the degree of association in the final model.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The pooled prevalence of stillbirths was found to be 1.54% per 100 [95% CI 1.19-2.01]. Factors positively associated with stillbirths in SSA included maternal age (25\u201334\u00a0years, 35\u201349\u00a0years), marital status (married, divorced or widowed), antenatal care visits, age at first birth (before age 20), short birth intervals, long birth intervals, birth order (second or third), residence in rural areas, country income level (lower middle income), and low literacy rate. Factors negatively associated with stillbirth mortality included maternal education (primary education, secondary or higher education), wealth index (higher economic status), access to mass media, access to improved drinking water, distance to health facilities, and country income level (upper middle income).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Stillbirth rates\u00a0fall significantly short of achieving Every Newborn Action Plan target by 2030 in SSA. The analysis of factors that affect stillbirth mortality reveals important connections. It is essential to improve maternal education, economic status, and healthcare infrastructure to decrease stillbirth\u00a0rates and enhance the health outcomes of mothers and children in the region. To effectively address these risks, efforts should concentrate on increasing access to antenatal care, raising awareness, and improving socio-economic conditions. By improving access to healthcare and education, these disparities could potentially lead to a decrease in stillbirth rates in the region.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s41256-024-00395-6","type":"journal-article","created":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T01:15:42Z","timestamp":1740618942000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Pooled prevalence and multilevel determinants of stillbirths in sub-Saharan African countries: implications for achieving sustainable development goal"],"prefix":"10.1016","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0063-0999","authenticated-orcid":false,"given":"Bewuketu","family":"Terefe","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahlet Moges","family":"Jembere","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nega Nigussie","family":"Abrha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dejen Kahsay","family":"Asgedom","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Solomon Keflie","family":"Assefa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nega Tezera","family":"Assimamaw","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","published-online":{"date-parts":[[2025,2,27]]},"reference":[{"issue":"3","key":"395_CR1","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/0378-3782(90)90182-I","volume":"22","author":"P Rantakallio","year":"1990","unstructured":"Rantakallio P, Oja H. 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This study was done based on secondary data from DHS. Issues related to informed consent, confidentiality, anonymity, and privacy of the study participants are already done ethically by the DHS office. We did not manipulate and apply the microdata other than in this study. There was no patient or public involvement in this study. Therefore, consent to the participants was not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declared that there are no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"11"}}