<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>18(6)</volume><submitter>Hailegebreal S</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4> Annually, 30 million women in Africa become pregnant, with the majority of deliveries taking place at home without the assistance of skilled healthcare personnel. In Ethiopia the proportion of home birth is high with regional disparity. Also limited evidence on spatial regression and deriving predictors. Therefore, this study aimed to assess the predictors of home birth hot spots using geographically weighted regression in Ethiopia. &lt;h4>Methods&lt;/h4> This study used secondary data from the 2019 Ethiopian Mini Demographic and Health Survey. First, Moran’s I and Getis-OrdGi* statistics were used to examine the geographic variation in home births. Further, spatial regression was analyzed using ordinary least squares regression and geographically weighted regression to predi</pubmed_abstract><journal>PloS one</journal><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10243638</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Using geographically weighted regression analysis to assess predictors of home birth hot spots in Ethiopia</pubmed_title><pmcid>PMC10243638</pmcid><pubmed_authors>Haile Y</pubmed_authors><pubmed_authors>Hailegebreal S</pubmed_authors><pubmed_authors>Simegn A</pubmed_authors><pubmed_authors>Enyew E</pubmed_authors><pubmed_authors>Haile F</pubmed_authors></additional><is_claimable>false</is_claimable><name>Using geographically weighted regression analysis to assess predictors of home birth hot spots in Ethiopia</name><description>&lt;h4>Background&lt;/h4> Annually, 30 million women in Africa become pregnant, with the majority of deliveries taking place at home without the assistance of skilled healthcare personnel. In Ethiopia the proportion of home birth is high with regional disparity. Also limited evidence on spatial regression and deriving predictors. Therefore, this study aimed to assess the predictors of home birth hot spots using geographically weighted regression in Ethiopia. &lt;h4>Methods&lt;/h4> This study used secondary data from the 2019 Ethiopian Mini Demographic and Health Survey. First, Moran’s I and Getis-OrdGi* statistics were used to examine the geographic variation in home births. Further, spatial regression was analyzed using ordinary least squares regression and geographically weighted regression to predi</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Jan</publication><modification>2025-04-04T14:39:04.549Z</modification><creation>2025-04-04T14:39:04.549Z</creation></dates><accession>S-EPMC10243638</accession><cross_references/></HashMap>