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Using Household Socioeconomic Indicators to Predict the Utilization of Maternal and Child Health Services Among Reproductive-Aged Women in Rural Yemen
Using principal component analysis (PCA) and integrating both individual and household factors, we had previously derived and proposed 3 socioeconomic indices (namely, wealth index, educational index, and housing quality index) that can be used to classify rural Yemeni women into different socioecon...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686312/ https://www.ncbi.nlm.nih.gov/pubmed/31431905 http://dx.doi.org/10.1177/2333794X19868926 |
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author | Alosaimi, Abdullah Nagi Nwaru, Bright Luoto, Riitta Al Serouri, Abdul Wahed Mouniri, Halima |
author_facet | Alosaimi, Abdullah Nagi Nwaru, Bright Luoto, Riitta Al Serouri, Abdul Wahed Mouniri, Halima |
author_sort | Alosaimi, Abdullah Nagi |
collection | PubMed |
description | Using principal component analysis (PCA) and integrating both individual and household factors, we had previously derived and proposed 3 socioeconomic indices (namely, wealth index, educational index, and housing quality index) that can be used to classify rural Yemeni women into different socioeconomic statuses (SES). In the current article, we examined whether the PCA-derived indices can be used to predict the use of maternal and child health care services in rural Yemen. We used data from subnational representative multistage sampling cross-sectional household survey conducted in rural Yemen in 2008-2009 among women (N = 6907) who had given birth. The resulting component scores for each SES index were divided into tertiles. Logistic regression was used to study the associations between the SES indices and 4 indicators of maternal health care use. Higher tertiles of each socioeconomic index increased the likelihood of adequate antenatal care use, delivery assistance, and contraceptive use, but decreased the likelihood of unmet need for contraception. Key maternal health indicators can be determined by socioeconomic indicators. Therefore, in planning maternal and child health interventions, considering disparities of care by socioeconomic factors should be taken into account. |
format | Online Article Text |
id | pubmed-6686312 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-66863122019-08-20 Using Household Socioeconomic Indicators to Predict the Utilization of Maternal and Child Health Services Among Reproductive-Aged Women in Rural Yemen Alosaimi, Abdullah Nagi Nwaru, Bright Luoto, Riitta Al Serouri, Abdul Wahed Mouniri, Halima Glob Pediatr Health Original Article Using principal component analysis (PCA) and integrating both individual and household factors, we had previously derived and proposed 3 socioeconomic indices (namely, wealth index, educational index, and housing quality index) that can be used to classify rural Yemeni women into different socioeconomic statuses (SES). In the current article, we examined whether the PCA-derived indices can be used to predict the use of maternal and child health care services in rural Yemen. We used data from subnational representative multistage sampling cross-sectional household survey conducted in rural Yemen in 2008-2009 among women (N = 6907) who had given birth. The resulting component scores for each SES index were divided into tertiles. Logistic regression was used to study the associations between the SES indices and 4 indicators of maternal health care use. Higher tertiles of each socioeconomic index increased the likelihood of adequate antenatal care use, delivery assistance, and contraceptive use, but decreased the likelihood of unmet need for contraception. Key maternal health indicators can be determined by socioeconomic indicators. Therefore, in planning maternal and child health interventions, considering disparities of care by socioeconomic factors should be taken into account. SAGE Publications 2019-08-06 /pmc/articles/PMC6686312/ /pubmed/31431905 http://dx.doi.org/10.1177/2333794X19868926 Text en © The Author(s) 2019 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Article Alosaimi, Abdullah Nagi Nwaru, Bright Luoto, Riitta Al Serouri, Abdul Wahed Mouniri, Halima Using Household Socioeconomic Indicators to Predict the Utilization of Maternal and Child Health Services Among Reproductive-Aged Women in Rural Yemen |
title | Using Household Socioeconomic Indicators to Predict the Utilization
of Maternal and Child Health Services Among Reproductive-Aged Women in Rural
Yemen |
title_full | Using Household Socioeconomic Indicators to Predict the Utilization
of Maternal and Child Health Services Among Reproductive-Aged Women in Rural
Yemen |
title_fullStr | Using Household Socioeconomic Indicators to Predict the Utilization
of Maternal and Child Health Services Among Reproductive-Aged Women in Rural
Yemen |
title_full_unstemmed | Using Household Socioeconomic Indicators to Predict the Utilization
of Maternal and Child Health Services Among Reproductive-Aged Women in Rural
Yemen |
title_short | Using Household Socioeconomic Indicators to Predict the Utilization
of Maternal and Child Health Services Among Reproductive-Aged Women in Rural
Yemen |
title_sort | using household socioeconomic indicators to predict the utilization
of maternal and child health services among reproductive-aged women in rural
yemen |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686312/ https://www.ncbi.nlm.nih.gov/pubmed/31431905 http://dx.doi.org/10.1177/2333794X19868926 |
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