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Health-care utilization and associated factors in Gauteng province, South Africa

Background: More than a billion people, mainly in low- and middle-income countries, are unable to access needed health-care services for a variety of reasons. Possible factors influencing health-care utilization include socio-demographic and economic factors such as age, sex, education, employment a...

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Autores principales: Abera Abaerei, Admas, Ncayiyana, Jabulani, Levin, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496078/
https://www.ncbi.nlm.nih.gov/pubmed/28574794
http://dx.doi.org/10.1080/16549716.2017.1305765
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author Abera Abaerei, Admas
Ncayiyana, Jabulani
Levin, Jonathan
author_facet Abera Abaerei, Admas
Ncayiyana, Jabulani
Levin, Jonathan
author_sort Abera Abaerei, Admas
collection PubMed
description Background: More than a billion people, mainly in low- and middle-income countries, are unable to access needed health-care services for a variety of reasons. Possible factors influencing health-care utilization include socio-demographic and economic factors such as age, sex, education, employment and income. However, different studies have showed mixed results. Moreover, there are limited studies on health-care utilization. Objective: This study aimed to determine health-care utilization and associated factors among all residents aged 18 or over in Gauteng province, South Africa. Methods: A cross-sectional study was conducted from data collected for a Quality of Life survey which was carried out by Gauteng City-Region Observatory in 2013. Simple random sampling was used to select participants. A total of 27,490 participants have been interviewed. Data were collected via a digital data collection instrument using an open source system called Formhub. Coarsened Exact Matching (CEM) was used to improve estimation of causal effects. Stepwise multiple logistic regression was employed to identify factors associated with health-care utilization. Results: Around 95.7% reported usually utilizing health-care services while the other 4.3% reported not having sought health-care services of any type. Around 75% of participants reported reduced quality of public health services as a major reason not to visit them. Higher odds of reported health-care utilization were associated with being female (OR = 2.18, 95% CI: 1.88–2.53; p < 0.001), being White compared to being African (OR = 2.28, 95% CI: 1.84–2.74; p < 0.001), and having medical insurance (OR = 5.41, 95% CI: 4.06–7.23; p < 0.001). Lower odds of seeking health-care were associated with being an immigrant (OR = 0.61, 95% CI: 0.53–0.70; p < 0.001). Conclusions: The results indicated that there is a need to improve the quality of public health-care services and perception towards them as improved health-care quality increases the choice of health-care providers.
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spelling pubmed-54960782017-07-11 Health-care utilization and associated factors in Gauteng province, South Africa Abera Abaerei, Admas Ncayiyana, Jabulani Levin, Jonathan Glob Health Action Original Article Background: More than a billion people, mainly in low- and middle-income countries, are unable to access needed health-care services for a variety of reasons. Possible factors influencing health-care utilization include socio-demographic and economic factors such as age, sex, education, employment and income. However, different studies have showed mixed results. Moreover, there are limited studies on health-care utilization. Objective: This study aimed to determine health-care utilization and associated factors among all residents aged 18 or over in Gauteng province, South Africa. Methods: A cross-sectional study was conducted from data collected for a Quality of Life survey which was carried out by Gauteng City-Region Observatory in 2013. Simple random sampling was used to select participants. A total of 27,490 participants have been interviewed. Data were collected via a digital data collection instrument using an open source system called Formhub. Coarsened Exact Matching (CEM) was used to improve estimation of causal effects. Stepwise multiple logistic regression was employed to identify factors associated with health-care utilization. Results: Around 95.7% reported usually utilizing health-care services while the other 4.3% reported not having sought health-care services of any type. Around 75% of participants reported reduced quality of public health services as a major reason not to visit them. Higher odds of reported health-care utilization were associated with being female (OR = 2.18, 95% CI: 1.88–2.53; p < 0.001), being White compared to being African (OR = 2.28, 95% CI: 1.84–2.74; p < 0.001), and having medical insurance (OR = 5.41, 95% CI: 4.06–7.23; p < 0.001). Lower odds of seeking health-care were associated with being an immigrant (OR = 0.61, 95% CI: 0.53–0.70; p < 0.001). Conclusions: The results indicated that there is a need to improve the quality of public health-care services and perception towards them as improved health-care quality increases the choice of health-care providers. Taylor & Francis 2017-06-02 /pmc/articles/PMC5496078/ /pubmed/28574794 http://dx.doi.org/10.1080/16549716.2017.1305765 Text en © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Abera Abaerei, Admas
Ncayiyana, Jabulani
Levin, Jonathan
Health-care utilization and associated factors in Gauteng province, South Africa
title Health-care utilization and associated factors in Gauteng province, South Africa
title_full Health-care utilization and associated factors in Gauteng province, South Africa
title_fullStr Health-care utilization and associated factors in Gauteng province, South Africa
title_full_unstemmed Health-care utilization and associated factors in Gauteng province, South Africa
title_short Health-care utilization and associated factors in Gauteng province, South Africa
title_sort health-care utilization and associated factors in gauteng province, south africa
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496078/
https://www.ncbi.nlm.nih.gov/pubmed/28574794
http://dx.doi.org/10.1080/16549716.2017.1305765
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