{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T13:21:34Z","timestamp":1783344094892,"version":"3.54.6"},"reference-count":80,"publisher":"BMJ","issue":"12","license":[{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"content-version":"unspecified","delay-in-days":4,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2025,10,21]]},"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Although the WHO and the Centers for Disease Control and Prevention (CDC) classify preconception health risks (PCHRs) into biomedical, behavioural and social categories, this classification remains theoretical, mainly inconsistent and lacks a scientifically robust framework. Data-driven clustering techniques may help clarify this complexity for policymakers and healthcare providers. This study aimed to assess the status of PCHRs and identify latent classes of these risks among women preparing for pregnancy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design and methods<\/jats:title>\n                    <jats:p>This community-based cross-sectional study was conducted from 31 July to 16 August 2024 in Tigray, Ethiopia, among 865 married women planning to conceive within the next 6\u2009months. Data were gathered through face-to-face interviews using a structured questionnaire. Risk factor indicators covering lifestyle behaviours, substance use, nutritional risks and related factors were developed based on guidelines from the WHO, the CDC and national recommendations. Latent class analysis (LCA) was employed to identify distinct classes of PCHRs, with the optimal number of classes determined using statistical fit indices, adequacy criteria and interpretability. The study also evaluated the overall distribution of PCHRs among participants.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting and participants<\/jats:title>\n                    <jats:p>The study took place in Tigray, Ethiopia, among married women intending to become pregnant within 6\u2009months.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Outcome<\/jats:title>\n                    <jats:p>Burden of PCHRs and identified distinct latent classes of these risks within the participants.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>All participants were exposed to at least four PCHRs, with 84.2% experiencing between 6 and 12 risk factors. The optimal LCA model identified four distinct classes of PCHRs: lifestyle behavioural risks (n=458, 52.9%), reproductive health risks and chronic medical conditions (n=106, 12.25%), nutritional risks and environmental exposure (n=149, 17.23%) and social determinants of health (n=152, 17.57%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our study reveals a high baseline level of PCHRs, with all participants exhibiting multiple risk factors for adverse pregnancy outcomes. The identification of four distinct risk profiles underscores the need for tailored risk-specific interventions, particularly in conflict-affected settings. Our findings point out the need for targeted preconception care and risk stratification in national health strategies to improve maternal and child health outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2025-106712","type":"journal-article","created":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T06:30:27Z","timestamp":1765175427000},"page":"e106712","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Preconception health risk profiles among women planning pregnancy in northern Ethiopia: a latent class analysis"],"prefix":"10.1136","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9180-6162","authenticated-orcid":false,"given":"Gebremedhin Gebreegziabher","family":"Gebretsadik","sequence":"first","affiliation":[{"name":"College of Medicine and Health Sciences, Adigrat University, Adigrat, Tigray, Ethiopia"},{"name":"School of Public Health, College of Health Sciences, Mekelle University, Mekelle, Tigray, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andargachew Kassa","family":"Biratu","sequence":"additional","affiliation":[{"name":"School of Public Health, College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alemayehu Bayray","family":"Kahsay","sequence":"additional","affiliation":[{"name":"School of Public Health, College of Health Sciences, Mekelle University, Mekelle, Tigray, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Afework","family":"Mulugeta","sequence":"additional","affiliation":[{"name":"School of Public Health, College of Health Sciences, Mekelle University, Mekelle, Tigray, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amanuel","family":"Gessessew","sequence":"additional","affiliation":[{"name":"School of Medicine, College of Health Sciences, Mekelle University, Mekelle, Tigray, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5350-6334","authenticated-orcid":false,"given":"Zohra","family":"S Lassi","sequence":"additional","affiliation":[{"name":"School of Public Health, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia"},{"name":"School of Public Health, Robinson Research Institute, University of Adelaide, Adelaide, South Australia, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2025,12,7]]},"reference":[{"key":"2026010703471656000_15.12.e106712.1","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1186\/s12889-023-15335-1","article-title":"Paternal preconception modifiable risk factors for adverse pregnancy and offspring outcomes: a review of contemporary evidence from observational studies","volume":"23","author":"Carter","year":"2023","journal-title":"BMC Public Health"},{"key":"2026010703471656000_15.12.e106712.2","doi-asserted-by":"crossref","first-page":"2167","DOI":"10.4172\/2167-0420.1000296","article-title":"Prevalence of Periconception Risk Factors for Adverse Pregnancy Outcomes in a Cohort of Urban Indian Women: Implications for Preconception Health Education","volume":"05","author":"Gund","year":"2016","journal-title":"J Women\u2019s Health Care"},{"key":"2026010703471656000_15.12.e106712.3","first-page":"5","article-title":"Preconception Risk Factors and Preconception Care Practices in a Hospital Based Turkish Sample","volume":"29","author":"Gurkan","year":"2021","journal-title":"Age (years)"},{"key":"2026010703471656000_15.12.e106712.4","doi-asserted-by":"crossref","first-page":"21","DOI":"10.3389\/fsoc.2020.00021","article-title":"\u201cIt\u2019s Never Too Early\u201d: Preconception Care and Postgenomic Models of Life","volume":"5","author":"Pentecost","year":"2020","journal-title":"Front Sociol"},{"key":"2026010703471656000_15.12.e106712.5","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1002\/ijgo.12955","article-title":"Do the concepts of \u201clife course approach\u201d and \u201cdevelopmental origins of health and disease\u201d underpin current maternity care? 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