Spatial distribution of common childhood illnesses, healthcare utilisation and associated factors in Ethiopia: Evidence from 2016 Ethiopian Demographic and Health Survey
Childhood illnesses, such as acute respiratory illness, fever, and diarrhoea, continue to be public health problems in low-income countries. Detecting spatial variations of common childhood illnesses and service utilisation is essential for identifying inequities and call for targeted actions. This...
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| Veröffentlicht in: | PloS one 2023-03, Vol.18 (3), p.e0281606-e0281606 |
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| creator | Defar, Atkure B Okwaraji, Yemisrach Tigabu, Zemene Persson, Lars Åke Alemu, Kassahun |
| description | Childhood illnesses, such as acute respiratory illness, fever, and diarrhoea, continue to be public health problems in low-income countries. Detecting spatial variations of common childhood illnesses and service utilisation is essential for identifying inequities and call for targeted actions. This study aimed to assess the geographical distribution and associated factors for common childhood illnesses and service utilisation across Ethiopia based on the 2016 Demographic and Health Survey.
The sample was selected using a two-stage stratified sampling process. A total of 10,417 children under five years were included in this analysis. We linked data on their common illnesses during the last two weeks and healthcare utilisation were linked to Global Positioning System (GPS) information of their local area. The spatial data were created in ArcGIS10.1 for each study cluster. We applied a spatial autocorrelation model with Moran's index to determine the spatial clustering of the prevalence of childhood illnesses and healthcare utilisation. Ordinary Least Square (OLS) analysis was done to assess the association between selected explanatory variables and sick child health services utilisation. Hot and cold spot clusters for high or low utilisation were identified using Getis-Ord Gi*. Kriging interpolation was done to predict sick child healthcare utilisation in areas where study samples were not drawn. All statistical analyses were performed using Excel, STATA, and ArcGIS.
Overall, 23% (95CI: 21, 25) of children under five years had some illness during the last two weeks before the survey. Of these, 38% (95%CI: 34, 41) sought care from an appropriate provider. Illnesses and service utilisation were not randomly distributed across the country with a Moran's index 0.111, Z-score 6.22, P |
| doi_str_mv | 10.1371/journal.pone.0281606 |
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The sample was selected using a two-stage stratified sampling process. A total of 10,417 children under five years were included in this analysis. We linked data on their common illnesses during the last two weeks and healthcare utilisation were linked to Global Positioning System (GPS) information of their local area. The spatial data were created in ArcGIS10.1 for each study cluster. We applied a spatial autocorrelation model with Moran's index to determine the spatial clustering of the prevalence of childhood illnesses and healthcare utilisation. Ordinary Least Square (OLS) analysis was done to assess the association between selected explanatory variables and sick child health services utilisation. Hot and cold spot clusters for high or low utilisation were identified using Getis-Ord Gi*. Kriging interpolation was done to predict sick child healthcare utilisation in areas where study samples were not drawn. All statistical analyses were performed using Excel, STATA, and ArcGIS.
Overall, 23% (95CI: 21, 25) of children under five years had some illness during the last two weeks before the survey. Of these, 38% (95%CI: 34, 41) sought care from an appropriate provider. Illnesses and service utilisation were not randomly distributed across the country with a Moran's index 0.111, Z-score 6.22, P<0.001, and Moran's index = 0.0804, Z-score 4.498, P< 0.001, respectively. Wealth and reported distance to health facilities were associated with service utilisation. Prevalence of common childhood illnesses was higher in the North, while service utilisation was more likely to be on a low level in the Eastern, South-western, and the Northern parts of the country.
Our study provided evidence of geographic clustering of common childhood illnesses and health service utilisation when the child was sick. Areas with low service utilisation for childhood illnesses need priority, including actions to counteract barriers such as poverty and long distances to services.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0281606</identifier><identifier>PMID: 36897920</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Age ; Caregivers ; Child ; Child, Preschool ; Childhood ; Children ; Children & youth ; Childrens health ; Clustering ; Delivery of Health Care ; Demographics ; Demography ; Diarrhea ; Diseases ; Earth Sciences ; Ethiopia - epidemiology ; Fever ; Geographical distribution ; Geography ; Geospatial data ; Global positioning systems ; GPS ; Health aspects ; Health care ; Health care facilities ; Health facilities ; Health problems ; Health services ; Health services utilization ; Health Surveys ; Households ; Humans ; Illnesses ; Interpolation ; Kriging interpolation ; Low income areas ; Low level ; Medical care ; Medicine and Health Sciences ; Methods ; Mothers ; Patient Acceptance of Health Care ; People and Places ; Physical Sciences ; Poverty ; Public health ; Questionnaires ; Rural areas ; Sea level ; Spatial Analysis ; Spatial data ; Spatial distribution ; Spatial variations ; Statistical analysis ; Surveys ; Surveys and Questionnaires ; Utilization</subject><ispartof>PloS one, 2023-03, Vol.18 (3), p.e0281606-e0281606</ispartof><rights>Copyright: © 2023 Defar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Defar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 Defar et al 2023 Defar et al</rights><rights>2023 Defar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c693t-b633e26421e28e101effe32282a5f46c8c388d48133791e242cc77aa6fc96eb63</citedby><cites>FETCH-LOGICAL-c693t-b633e26421e28e101effe32282a5f46c8c388d48133791e242cc77aa6fc96eb63</cites><orcidid>0000-0001-9435-2135</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10004611/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10004611/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36897920$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Raushan, Rajesh</contributor><creatorcontrib>Defar, Atkure</creatorcontrib><creatorcontrib>B Okwaraji, Yemisrach</creatorcontrib><creatorcontrib>Tigabu, Zemene</creatorcontrib><creatorcontrib>Persson, Lars Åke</creatorcontrib><creatorcontrib>Alemu, Kassahun</creatorcontrib><title>Spatial distribution of common childhood illnesses, healthcare utilisation and associated factors in Ethiopia: Evidence from 2016 Ethiopian Demographic and Health Survey</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Childhood illnesses, such as acute respiratory illness, fever, and diarrhoea, continue to be public health problems in low-income countries. Detecting spatial variations of common childhood illnesses and service utilisation is essential for identifying inequities and call for targeted actions. This study aimed to assess the geographical distribution and associated factors for common childhood illnesses and service utilisation across Ethiopia based on the 2016 Demographic and Health Survey.
The sample was selected using a two-stage stratified sampling process. A total of 10,417 children under five years were included in this analysis. We linked data on their common illnesses during the last two weeks and healthcare utilisation were linked to Global Positioning System (GPS) information of their local area. The spatial data were created in ArcGIS10.1 for each study cluster. We applied a spatial autocorrelation model with Moran's index to determine the spatial clustering of the prevalence of childhood illnesses and healthcare utilisation. Ordinary Least Square (OLS) analysis was done to assess the association between selected explanatory variables and sick child health services utilisation. Hot and cold spot clusters for high or low utilisation were identified using Getis-Ord Gi*. Kriging interpolation was done to predict sick child healthcare utilisation in areas where study samples were not drawn. All statistical analyses were performed using Excel, STATA, and ArcGIS.
Overall, 23% (95CI: 21, 25) of children under five years had some illness during the last two weeks before the survey. Of these, 38% (95%CI: 34, 41) sought care from an appropriate provider. Illnesses and service utilisation were not randomly distributed across the country with a Moran's index 0.111, Z-score 6.22, P<0.001, and Moran's index = 0.0804, Z-score 4.498, P< 0.001, respectively. Wealth and reported distance to health facilities were associated with service utilisation. Prevalence of common childhood illnesses was higher in the North, while service utilisation was more likely to be on a low level in the Eastern, South-western, and the Northern parts of the country.
Our study provided evidence of geographic clustering of common childhood illnesses and health service utilisation when the child was sick. Areas with low service utilisation for childhood illnesses need priority, including actions to counteract barriers such as poverty and long distances to services.</description><subject>Age</subject><subject>Caregivers</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Childhood</subject><subject>Children</subject><subject>Children & youth</subject><subject>Childrens health</subject><subject>Clustering</subject><subject>Delivery of Health Care</subject><subject>Demographics</subject><subject>Demography</subject><subject>Diarrhea</subject><subject>Diseases</subject><subject>Earth Sciences</subject><subject>Ethiopia - epidemiology</subject><subject>Fever</subject><subject>Geographical distribution</subject><subject>Geography</subject><subject>Geospatial data</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>Health aspects</subject><subject>Health care</subject><subject>Health care facilities</subject><subject>Health facilities</subject><subject>Health problems</subject><subject>Health services</subject><subject>Health services utilization</subject><subject>Health Surveys</subject><subject>Households</subject><subject>Humans</subject><subject>Illnesses</subject><subject>Interpolation</subject><subject>Kriging interpolation</subject><subject>Low income areas</subject><subject>Low level</subject><subject>Medical care</subject><subject>Medicine and Health Sciences</subject><subject>Methods</subject><subject>Mothers</subject><subject>Patient Acceptance of Health Care</subject><subject>People and Places</subject><subject>Physical Sciences</subject><subject>Poverty</subject><subject>Public health</subject><subject>Questionnaires</subject><subject>Rural areas</subject><subject>Sea level</subject><subject>Spatial Analysis</subject><subject>Spatial data</subject><subject>Spatial distribution</subject><subject>Spatial variations</subject><subject>Statistical 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distribution of common childhood illnesses, healthcare utilisation and associated factors in Ethiopia: Evidence from 2016 Ethiopian Demographic and Health Survey</title><author>Defar, Atkure ; B Okwaraji, Yemisrach ; Tigabu, Zemene ; Persson, Lars Åke ; Alemu, Kassahun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c693t-b633e26421e28e101effe32282a5f46c8c388d48133791e242cc77aa6fc96eb63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Age</topic><topic>Caregivers</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Childhood</topic><topic>Children</topic><topic>Children & youth</topic><topic>Childrens health</topic><topic>Clustering</topic><topic>Delivery of Health Care</topic><topic>Demographics</topic><topic>Demography</topic><topic>Diarrhea</topic><topic>Diseases</topic><topic>Earth Sciences</topic><topic>Ethiopia - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Defar, Atkure</au><au>B Okwaraji, Yemisrach</au><au>Tigabu, Zemene</au><au>Persson, Lars Åke</au><au>Alemu, Kassahun</au><au>Raushan, Rajesh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatial distribution of common childhood illnesses, healthcare utilisation and associated factors in Ethiopia: Evidence from 2016 Ethiopian Demographic and Health Survey</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2023-03-10</date><risdate>2023</risdate><volume>18</volume><issue>3</issue><spage>e0281606</spage><epage>e0281606</epage><pages>e0281606-e0281606</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Childhood illnesses, such as acute respiratory illness, fever, and diarrhoea, continue to be public health problems in low-income countries. Detecting spatial variations of common childhood illnesses and service utilisation is essential for identifying inequities and call for targeted actions. This study aimed to assess the geographical distribution and associated factors for common childhood illnesses and service utilisation across Ethiopia based on the 2016 Demographic and Health Survey.
The sample was selected using a two-stage stratified sampling process. A total of 10,417 children under five years were included in this analysis. We linked data on their common illnesses during the last two weeks and healthcare utilisation were linked to Global Positioning System (GPS) information of their local area. The spatial data were created in ArcGIS10.1 for each study cluster. We applied a spatial autocorrelation model with Moran's index to determine the spatial clustering of the prevalence of childhood illnesses and healthcare utilisation. Ordinary Least Square (OLS) analysis was done to assess the association between selected explanatory variables and sick child health services utilisation. Hot and cold spot clusters for high or low utilisation were identified using Getis-Ord Gi*. Kriging interpolation was done to predict sick child healthcare utilisation in areas where study samples were not drawn. All statistical analyses were performed using Excel, STATA, and ArcGIS.
Overall, 23% (95CI: 21, 25) of children under five years had some illness during the last two weeks before the survey. Of these, 38% (95%CI: 34, 41) sought care from an appropriate provider. Illnesses and service utilisation were not randomly distributed across the country with a Moran's index 0.111, Z-score 6.22, P<0.001, and Moran's index = 0.0804, Z-score 4.498, P< 0.001, respectively. Wealth and reported distance to health facilities were associated with service utilisation. Prevalence of common childhood illnesses was higher in the North, while service utilisation was more likely to be on a low level in the Eastern, South-western, and the Northern parts of the country.
Our study provided evidence of geographic clustering of common childhood illnesses and health service utilisation when the child was sick. Areas with low service utilisation for childhood illnesses need priority, including actions to counteract barriers such as poverty and long distances to services.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>36897920</pmid><doi>10.1371/journal.pone.0281606</doi><tpages>e0281606</tpages><orcidid>https://orcid.org/0000-0001-9435-2135</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2023-03, Vol.18 (3), p.e0281606-e0281606 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2785633879 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Age Caregivers Child Child, Preschool Childhood Children Children & youth Childrens health Clustering Delivery of Health Care Demographics Demography Diarrhea Diseases Earth Sciences Ethiopia - epidemiology Fever Geographical distribution Geography Geospatial data Global positioning systems GPS Health aspects Health care Health care facilities Health facilities Health problems Health services Health services utilization Health Surveys Households Humans Illnesses Interpolation Kriging interpolation Low income areas Low level Medical care Medicine and Health Sciences Methods Mothers Patient Acceptance of Health Care People and Places Physical Sciences Poverty Public health Questionnaires Rural areas Sea level Spatial Analysis Spatial data Spatial distribution Spatial variations Statistical analysis Surveys Surveys and Questionnaires Utilization |
| title | Spatial distribution of common childhood illnesses, healthcare utilisation and associated factors in Ethiopia: Evidence from 2016 Ethiopian Demographic and Health Survey |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T01%3A51%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatial%20distribution%20of%20common%20childhood%20illnesses,%20healthcare%20utilisation%20and%20associated%20factors%20in%20Ethiopia:%20Evidence%20from%202016%20Ethiopian%20Demographic%20and%20Health%20Survey&rft.jtitle=PloS%20one&rft.au=Defar,%20Atkure&rft.date=2023-03-10&rft.volume=18&rft.issue=3&rft.spage=e0281606&rft.epage=e0281606&rft.pages=e0281606-e0281606&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0281606&rft_dat=%3Cgale_plos_%3EA740409030%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2785633879&rft_id=info:pmid/36897920&rft_galeid=A740409030&rft_doaj_id=oai_doaj_org_article_1adf5e62831f4379aa398ed0a5b8cd7e&rfr_iscdi=true |