{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T17:57:27Z","timestamp":1791482247704,"version":"4.3.4"},"reference-count":37,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Child stunting remains a major public health challenge in the Democratic Republic of the Congo (DRC), reflecting persistent inequalities in child nutrition and health outcomes. This study examines the distribution and spatial variation of height-for-age z-scores (HAZ) among children under five, while also assessing the influence of selected demographic and socioeconomic factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data were obtained from the 2023\u20132024 Demographic and Health Survey (DHS-8). A structured additive regression model was then applied to assess the effects of child age and maternal education, allowing for nonlinear relationships through smooth functions. To capture geographic heterogeneity, spatial effects were decomposed into structured (spatially correlated) and unstructured (area-specific random) components, enabling the identification of regional clustering and residual province-level variation in stunting.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Geographic analysis reveals substantial regional disparities in stunting prevalence across the 26 provinces of the DRC. The province of Kwilu emerges as a major hotspot with very high levels of stunting, while several provinces fall within medium to high prevalence categories, indicating that stunting is a widespread issue across the country. Model results highlight important nonlinear relationships for certain predictors. Child\u2019s age shows a strong negative trend with stunting risk: younger children have higher log-odds of stunting, and the risk decreases sharply with age. Maternal education displays a weaker and nonlinear association, with generally small effects across most education levels and greater uncertainty at higher levels of schooling. Spatial modeling further demonstrates that geographic factors significantly contribute to variation in stunting outcomes. Both structured spatial effects, indicating regional clustering, and unstructured spatial effects, reflecting province-specific deviations, contribute to the observed patterns. The combined spatial effect suggests persistent geographic disparities even after adjusting for covariates, although uncertainty varies across regions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The findings underscore the importance of geographic context and early childhood factors in shaping stunting outcomes in the DRC, highlighting the need for targeted, context-specific interventions to address persistent nutritional inequalities.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0360056","type":"journal-article","created":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T17:39:06Z","timestamp":1791481146000},"page":"e0360056","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Child malnutrition in the Democratic Republic of the Congo: A Bayesian Gaussian regression analysis using the 2023\u201324 demographic and health survey"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7977-1689","authenticated-orcid":true,"given":"Zacharie","family":"Tsala Dimbuene","sequence":"first","affiliation":[{"name":"University of Kinshasa","place":["Kinshasa, Democratic Republic of the Congo"],"department":["School of Population and Development Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hugues","family":"Sampasa-Kanyinga","sequence":"additional","affiliation":[{"name":"University of Kinshasa","place":["Kinshasa, Democratic Republic of Congo"],"department":["Faculty of Medicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,10,8]]},"reference":[{"key":"pone.0360056.ref001","author":"UNICEF, WHO, World Bank","year":"2024"},{"key":"pone.0360056.ref002","author":"World Health Organization","year":"2006"},{"key":"pone.0360056.ref003","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1111\/mcn.12231","article-title":"Childhood stunting: a global perspective","author":"M de Onis","year":"2016","journal-title":"Matern Child Nutr"},{"issue":"9609","key":"pone.0360056.ref004","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/S0140-6736(07)61692-4","article-title":"Maternal and child undernutrition: consequences for adult health and human capital","volume":"371","author":"CG Victora","year":"2008","journal-title":"Lancet"},{"issue":"9890","key":"pone.0360056.ref005","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/S0140-6736(13)60937-X","article-title":"Maternal and child undernutrition and overweight in low-income and middle-income countries","volume":"382","author":"RE Black","year":"2013","journal-title":"Lancet"},{"key":"pone.0360056.ref006","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1111\/mcn.12080","article-title":"The economic rationale for investing in stunting reduction","author":"J Hoddinott","year":"2013","journal-title":"Matern Child Nutr"},{"issue":"9555","key":"pone.0360056.ref007","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/S0140-6736(07)60032-4","article-title":"Developmental potential in the first 5 years for children in developing countries","volume":"369","author":"S Grantham-McGregor","year":"2007","journal-title":"Lancet"},{"key":"pone.0360056.ref008","first-page":"15","article-title":"Stunting and severe stunting among children under-5 years in Nigeria: A multilevel analysis. BMC","volume":"17","author":"BJ Akombi","year":"2017","journal-title":"Pediatrics"},{"key":"pone.0360056.ref009","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1186\/1471-2458-11-261","article-title":"Malnutrition among children under the age of five in the Democratic Republic of Congo (DRC): Does geographic location matter?","volume":"11","author":"N-B Kandala","year":"2011","journal-title":"BMC Public Health"},{"key":"pone.0360056.ref010","author":"UNICEF","year":"2023"},{"key":"pone.0360056.ref011","author":"World Bank","year":"2024"},{"key":"pone.0360056.ref012","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.worlddev.2014.11.014","article-title":"Reducing Child Undernutrition: Past Drivers and Priorities for the Post-MDG Era","volume":"68","author":"LC Smith","year":"2015","journal-title":"World Development"},{"issue":"7694","key":"pone.0360056.ref013","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/nature25760","article-title":"Mapping child growth failure in Africa between 2000 and 2015","volume":"555","author":"A Osgood-Zimmerman","year":"2018","journal-title":"Nature"},{"key":"pone.0360056.ref014","doi-asserted-by":"crossref","first-page":"2947","DOI":"10.1080\/10095020.2025.2459133","article-title":"Hybridizing spatial machine learning to explore the fine-scale heterogeneity between stunting prevalence and its associated risk determinants in Rwanda","volume":"28","author":"G Nduwayezu","year":"2025","journal-title":"Geo-spatial Information Science"},{"issue":"1","key":"pone.0360056.ref015","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/1467-9876.00385","article-title":"Geoadditive Models","volume":"52","author":"EE Kammann","year":"2003","journal-title":"J Royal Statistical Society Series C: Applied Statistics"},{"issue":"2","key":"pone.0360056.ref016","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1111\/1467-9876.00229","article-title":"Bayesian inference for generalized additive mixed models based on markov random field priors","volume":"50","author":"L Fahrmeir","year":"2001","journal-title":"Journal of the Royal Statistical Society Series C: Applied Statistics"},{"key":"pone.0360056.ref017","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1186\/1476-072X-10-28","article-title":"Geoadditive models to assess spatial variation of HIV infections among women in local communities of Durban, South Africa","volume":"10","author":"H Wand","year":"2011","journal-title":"Int J Health Geogr"},{"issue":"2","key":"pone.0360056.ref018","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1080\/00343404.2013.779656","article-title":"The spatial distribution of self-employment in India: Evidence from semiparametric geoadditive models","volume":"49","author":"JP Tamvada","year":"2013","journal-title":"Regional Studies"},{"issue":"1","key":"pone.0360056.ref019","doi-asserted-by":"crossref","first-page":"6215","DOI":"10.1038\/s41598-024-55850-8","article-title":"Mapping the spatial disparities of HIV prevalence in Ethiopian zones using the generalized additive model","volume":"14","author":"SA Yilema","year":"2024","journal-title":"Sci Rep"},{"key":"pone.0360056.ref020","doi-asserted-by":"crossref","first-page":"1559140","DOI":"10.3389\/fped.2025.1559140","article-title":"Mapping the covariate-adjusted spatial effects of childhood anemia in Ethiopia using a semi-parametric additive model","volume":"13","author":"SA Yilema","year":"2025","journal-title":"Front Pediatr"},{"key":"pone.0360056.ref021","author":"Institut National de la Statistique I, ICF","year":"2024"},{"key":"pone.0360056.ref022","unstructured":"United Nations Office for the Coordination of Humanitarian Affairs. Democratic Republic of the Congo: Humanitarian needs overview 2024. 2024."},{"key":"pone.0360056.ref023","author":"Integrated Food Security Phase Classification (IPC)","year":"2024"},{"key":"pone.0360056.ref024","author":"Development Initiatives","year":"2024"},{"key":"pone.0360056.ref025","doi-asserted-by":"crossref","first-page":"100352","DOI":"10.1016\/j.ssmph.2019.100352","article-title":"Temporal stability of child growth associations in Demographic and Health Surveys in 25 countries","volume":"7","author":"M Rieger","year":"2019","journal-title":"SSM Popul Health"},{"issue":"1","key":"pone.0360056.ref026","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/s12937-021-00677-6","article-title":"Maternal factors associated with moderate and severe stunting in Ethiopian children: analysis of some environmental factors based on 2016 demographic health survey","volume":"20","author":"ND Amaha","year":"2021","journal-title":"Nutr J"},{"key":"pone.0360056.ref027","doi-asserted-by":"crossref","DOI":"10.1093\/ajcn\/nqaa159","article-title":"Stunting in childhood: an overview of global burden, trends, determinants, and drivers of decline","volume":"112","author":"T Vaivada","year":"2020","journal-title":"Am J Clin Nutr"},{"issue":"1","key":"pone.0360056.ref028","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1186\/s13690-023-01090-7","article-title":"Longitudinal trends and determinants of stunting among children aged 1-15 years","volume":"81","author":"SK Wake","year":"2023","journal-title":"Arch Public Health"},{"issue":"11","key":"pone.0360056.ref029","doi-asserted-by":"crossref","DOI":"10.18637\/jss.v014.i11","article-title":"BayesX: Analyzing Bayesian Structured Additive Regression Models","volume":"14","author":"A Brezger","year":"2005","journal-title":"J Stat Soft"},{"issue":"4","key":"pone.0360056.ref030","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1016\/j.csda.2004.10.011","article-title":"Generalized structured additive regression based on Bayesian P-splines","volume":"50","author":"A Brezger","year":"2006","journal-title":"Computational Statistics & Data Analysis"},{"key":"pone.0360056.ref031","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v063.i21","article-title":"Structured additive regression models: An R interface to bayesX","volume":"63","author":"N Umlauf","year":"2015","journal-title":"J Statistical Software"},{"issue":"1","key":"pone.0360056.ref032","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.csda.2008.05.032","article-title":"Simultaneous selection of variables and smoothing parameters in structured additive regression models","volume":"53","author":"C Belitz","year":"2008","journal-title":"Computational Statistics & Data Analysis"},{"issue":"6","key":"pone.0360056.ref033","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0325812","article-title":"Spatial distribution of stunting among breast feeding children in Sub-Sahara Africa","volume":"20","author":"B Girma","year":"2025","journal-title":"PLoS One"},{"key":"pone.0360056.ref034","doi-asserted-by":"crossref","first-page":"1502018","DOI":"10.3389\/fpubh.2024.1502018","article-title":"Spatial heterogeneity and predictors of stunting among under five children in Mozambique: A geographically weighted regression","volume":"12","author":"TT Tamir","year":"2024","journal-title":"Front Public Health"},{"key":"pone.0360056.ref035","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1186\/s12887-016-0587-9","article-title":"Exploring spatial variations and factors associated with childhood stunting in Ethiopia: Spatial and multilevel analysis","volume":"16","author":"D Haile","year":"2016","journal-title":"BMC Pediatr"},{"issue":"9890","key":"pone.0360056.ref036","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1016\/S0140-6736(13)60996-4","article-title":"Evidence-based interventions for improvement of maternal and child nutrition: what can be done and at what cost?","volume":"382","author":"ZA Bhutta","year":"2013","journal-title":"Lancet"},{"key":"pone.0360056.ref037","doi-asserted-by":"crossref","DOI":"10.1016\/j.ajcnut.2025.03.004","article-title":"What works for reducing stunting in low-income and middle-income countries? Cumulative learnings from the Global Stunting Exemplars Project","volume":"121","author":"ZA Bhutta","year":"2025","journal-title":"Am J Clinical Nutrition"}],"container-title":["PLOS One"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0360056","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T17:39:12Z","timestamp":1791481152000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0360056"}},"subtitle":[],"editor":[{"given":"Md. Moyazzem","family":"Hossain","sequence":"first","affiliation":[{"name":"Jahangirnagar University","place":["BANGLADESH"]}],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026,10,8]]},"references-count":37,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2026,10,8]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0360056","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,8]]}}}