{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T14:17:17Z","timestamp":1788445037627,"version":"build-2803163510"},"reference-count":50,"publisher":"BMJ","issue":"3","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"unspecified","delay-in-days":64,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["bmjph"],"accepted":{"date-parts":[[2026,8,19]]},"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Maternal mortality remains persistently high in low- and middle-income countries, driven by inequities in access to and use of maternal healthcare. A life-course perspective offers critical insights into the underlying drivers of these disparities, linking historical, social and structural factors across women\u2019s lives to health outcomes. By contextualising maternal health within lifelong trajectories, the analysis aims to inform targeted strategies to reduce inequities and improve care access across generations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To analyse the generational differences in the maternal health services utilisation across the maternal life course and its social determinants in Kersa, Eastern Ethiopia.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study involved secondary analysis of pre-existing longitudinal health and demographic surveillance system (HDSS) data, comparing mothers born during three distinct historical periods. Reproductive-age women from three different generations, specifically those born in the 1970s, 1980s and 1990s. A linear mixed-effects modelling approach was used, employing the logit link function for the binomial family. The statistical analysis was done using RStudio. A 5% p value threshold and a 95% confidence level were used to assess the statistical significance of the findings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Prenatal care coverage was lowest among the 1970s cohort (29.6%), rising to 33.2% for the 1980s cohort and 36.2% for the 1990s cohort. Skilled birth care utilisation showed a similar generational gap: 27.2% (1970s), 26.4% (1980s) and 30.6% (1990s). Adjusted analyses revealed maternal education (adjusted OR (AOR) 1.66 (95%\u2009CI 1.443 to 1.916), husband\u2019s education and husband\u2019s unemployment (AOR 3.44 (95%\u2009CI 1.936 to 6.112)) as key predictors of prenatal care use. Younger age at first marriage (eg, &lt;16 years: AOR 0.747 (95%\u2009CI 0.594 to 0.872)) and unintended pregnancy reduced prenatal care utilisation. For skilled birth attendance, household wealth (highest vs lowest wealth: AOR 2.28 (95%\u2009CI 1.926 to 2.708)), prior prenatal care use (AOR 2.89 (95%\u2009CI 2.514 to 3.33)) and birth cohort (1980s vs 1990s: AOR 0.79 (95%\u2009CI 0.681 to 0.914)) were significant determinants. Early marriage (eg, &lt;24 years) and unintended pregnancy similarly decreased skilled care utilisation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The persistent generational disparities in maternal healthcare utilisation, with later-born cohorts (1990s) demonstrating improved coverage compared with earlier generations (1970s\u20131980s). These disparities are driven by intersecting generational differences in educational opportunity, employment patterns and technological modernisation. Key determinants include maternal and spousal education, household wealth, age at first marriage, pregnancy intention and generational differences in acceptance of modern healthcare. Addressing these disparities requires targeted policies to enhance educational access, economic equity and reproductive health autonomy, ensuring equitable maternal healthcare utilisation across generations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjph-2026-005346","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T13:50:18Z","timestamp":1788443418000},"page":"e005346","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Generational disparities in maternal healthcare: a life-course perspective on social determinants in Kersa, Eastern Ethiopia"],"prefix":"10.1136","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5682-6117","authenticated-orcid":false,"given":"Afework","family":"Tadele","sequence":"first","affiliation":[{"name":"Department of Population and Family Health, Jimma University, Jimma, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Merga","family":"Dheresa","sequence":"additional","affiliation":[{"name":"School of Nursing and Midwifery, Haramaya University, Dire Dawa, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muluemebet","family":"Abera","sequence":"additional","affiliation":[{"name":"Department of Population and Family Health, Jimma University, Jimma, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2026,9,3]]},"reference":[{"key":"2026090306501186000_4.3.e005346.1","unstructured":"Maternal mortality. 2025. 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