Determinants of access to healthcare by older persons in Uganda: a cross-sectional study
Identifieur interne : 000E19 ( Pmc/Checkpoint ); précédent : 000E18; suivant : 000E20Determinants of access to healthcare by older persons in Uganda: a cross-sectional study
Auteurs : Stephen Ojiambo Wandera [Ouganda, Kenya] ; Betty Kwagala [Ouganda] ; James Ntozi [Ouganda]Source :
- International Journal for Equity in Health [ 1475-9276 ] ; 2015.
Abstract
Older persons report poor health status and greater need for healthcare. However, there is limited research on older persons’ healthcare disparities in Uganda. Therefore, this paper aimed at investigating factors associated with older persons’ healthcare access in Uganda, using a nationally representative sample.
We conducted secondary analysis of data from a sample of 1602 older persons who reported being sick in the last 30 days preceding the Uganda National Household Survey. We used frequency distributions for descriptive data analysis and chi-square tests to identify initial associations. We fit generalized linear models (GLM) with the poisson family and the log link function, to obtain incidence risk ratios (RR) of accessing healthcare in the last 30 days, by older persons in Uganda.
More than three quarters (76%) of the older persons accessed healthcare in the last 30 days. Access to healthcare in the last 30 days was reduced for older persons from poor households (RR = 0.91, 95% CI: 0.83-0.99); with some walking difficulty (RR = 0.90, 95% CI: 0.83-0.97); or with a lot of walking difficulty (RR = 0.84, 95% CI: 0.75-0.95). Conversely, accessing healthcare in the last 30 days for older persons increased for those who earned wages (RR = 1.08, 95% CI: 1.00-1.15) and missed work due to illness for 1–7 days (RR = 1.19, 95% CI: 1.10-1.30); and 8–14 days (RR = 1.19, 95% CI: 1.07-1.31). In addition, those who reported non-communicable diseases (NCDs) such as heart disease, hypertension or diabetes (RR = 1.09, 95% CI: 1.01-1.16); were more likely to access healthcare during the last 30 days.
In the Ugandan context, health need factors (self-reported NCDs, severity of illness and mobility limitations) and enabling factors (household wealth status and earning wages in particular) were the most important determinants of accessing healthcare in the last 30 days among older persons.
The online version of this article (doi:10.1186/s12939-015-0157-z) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12939-015-0157-z
PubMed: 25889558
PubMed Central: 4354736
Affiliations:
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Determinants of access to healthcare by older persons in Uganda: a cross-sectional study</title><author><name sortKey="Wandera, Stephen Ojiambo" sort="Wandera, Stephen Ojiambo" uniqKey="Wandera S" first="Stephen Ojiambo" last="Wandera">Stephen Ojiambo Wandera</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala, Uganda</nlm:aff><country xml:lang="fr">Ouganda</country><wicri:regionArea>Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala</wicri:regionArea><wicri:noRegion>Kampala</wicri:noRegion></affiliation><affiliation wicri:level="1"><nlm:aff id="Aff2">Consortium for Advanced Research Training in Africa (CARTA cohort 2) Fellow at the African Population and Health Research Centre (APHRC), Nairobi, Kenya</nlm:aff><country xml:lang="fr">Kenya</country><wicri:regionArea>Consortium for Advanced Research Training in Africa (CARTA cohort 2) Fellow at the African Population and Health Research Centre (APHRC), Nairobi</wicri:regionArea><wicri:noRegion>Nairobi</wicri:noRegion></affiliation></author><author><name sortKey="Kwagala, Betty" sort="Kwagala, Betty" uniqKey="Kwagala B" first="Betty" last="Kwagala">Betty Kwagala</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala, Uganda</nlm:aff><country xml:lang="fr">Ouganda</country><wicri:regionArea>Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala</wicri:regionArea><wicri:noRegion>Kampala</wicri:noRegion></affiliation></author><author><name sortKey="Ntozi, James" sort="Ntozi, James" uniqKey="Ntozi J" first="James" last="Ntozi">James Ntozi</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala, Uganda</nlm:aff><country xml:lang="fr">Ouganda</country><wicri:regionArea>Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala</wicri:regionArea><wicri:noRegion>Kampala</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25889558</idno><idno type="pmc">4354736</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354736</idno><idno type="RBID">PMC:4354736</idno><idno type="doi">10.1186/s12939-015-0157-z</idno><date when="2015">2015</date><idno type="wicri:Area/Pmc/Corpus">000894</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000894</idno><idno type="wicri:Area/Pmc/Curation">000893</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000893</idno><idno type="wicri:Area/Pmc/Checkpoint">000E19</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000E19</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Determinants of access to healthcare by older persons in Uganda: a cross-sectional study</title><author><name sortKey="Wandera, Stephen Ojiambo" sort="Wandera, Stephen Ojiambo" uniqKey="Wandera S" first="Stephen Ojiambo" last="Wandera">Stephen Ojiambo Wandera</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala, Uganda</nlm:aff><country xml:lang="fr">Ouganda</country><wicri:regionArea>Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala</wicri:regionArea><wicri:noRegion>Kampala</wicri:noRegion></affiliation><affiliation wicri:level="1"><nlm:aff id="Aff2">Consortium for Advanced Research Training in Africa (CARTA cohort 2) Fellow at the African Population and Health Research Centre (APHRC), Nairobi, Kenya</nlm:aff><country xml:lang="fr">Kenya</country><wicri:regionArea>Consortium for Advanced Research Training in Africa (CARTA cohort 2) Fellow at the African Population and Health Research Centre (APHRC), Nairobi</wicri:regionArea><wicri:noRegion>Nairobi</wicri:noRegion></affiliation></author><author><name sortKey="Kwagala, Betty" sort="Kwagala, Betty" uniqKey="Kwagala B" first="Betty" last="Kwagala">Betty Kwagala</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala, Uganda</nlm:aff><country xml:lang="fr">Ouganda</country><wicri:regionArea>Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala</wicri:regionArea><wicri:noRegion>Kampala</wicri:noRegion></affiliation></author><author><name sortKey="Ntozi, James" sort="Ntozi, James" uniqKey="Ntozi J" first="James" last="Ntozi">James Ntozi</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala, Uganda</nlm:aff><country xml:lang="fr">Ouganda</country><wicri:regionArea>Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala</wicri:regionArea><wicri:noRegion>Kampala</wicri:noRegion></affiliation></author></analytic><series><title level="j">International Journal for Equity in Health</title><idno type="eISSN">1475-9276</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Older persons report poor health status and greater need for healthcare. However, there is limited research on older persons’ healthcare disparities in Uganda. Therefore, this paper aimed at investigating factors associated with older persons’ healthcare access in Uganda, using a nationally representative sample.</p></sec><sec><title>Methods</title><p>We conducted secondary analysis of data from a sample of 1602 older persons who reported being sick in the last 30 days preceding the Uganda National Household Survey. We used frequency distributions for descriptive data analysis and chi-square tests to identify initial associations. We fit generalized linear models (GLM) with the poisson family and the log link function, to obtain incidence risk ratios (RR) of accessing healthcare in the last 30 days, by older persons in Uganda.</p></sec><sec><title>Results</title><p>More than three quarters (76%) of the older persons accessed healthcare in the last 30 days. Access to healthcare in the last 30 days was reduced for older persons from poor households (RR = 0.91, 95% CI: 0.83-0.99); with some walking difficulty (RR = 0.90, 95% CI: 0.83-0.97); or with a lot of walking difficulty (RR = 0.84, 95% CI: 0.75-0.95). Conversely, accessing healthcare in the last 30 days for older persons increased for those who earned wages (RR = 1.08, 95% CI: 1.00-1.15) and missed work due to illness for 1–7 days (RR = 1.19, 95% CI: 1.10-1.30); and 8–14 days (RR = 1.19, 95% CI: 1.07-1.31). In addition, those who reported non-communicable diseases (NCDs) such as heart disease, hypertension or diabetes (RR = 1.09, 95% CI: 1.01-1.16); were more likely to access healthcare during the last 30 days.</p></sec><sec><title>Conclusion</title><p>In the Ugandan context, health need factors (self-reported NCDs, severity of illness and mobility limitations) and enabling factors (household wealth status and earning wages in particular) were the most important determinants of accessing healthcare in the last 30 days among older persons.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/s12939-015-0157-z) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Ameh, S" uniqKey="Ameh S">S Ameh</name></author><author><name sortKey="G Mez Olive, Fx" uniqKey="G Mez Olive F">FX 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Int J Equity Health</journal-id><journal-id journal-id-type="iso-abbrev">Int J Equity Health</journal-id><journal-title-group><journal-title>International Journal for Equity in Health</journal-title></journal-title-group><issn pub-type="epub">1475-9276</issn><publisher><publisher-name>BioMed Central</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">25889558</article-id><article-id pub-id-type="pmc">4354736</article-id><article-id pub-id-type="publisher-id">157</article-id><article-id pub-id-type="doi">10.1186/s12939-015-0157-z</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research</subject></subj-group></article-categories><title-group><article-title>Determinants of access to healthcare by older persons in Uganda: a cross-sectional study</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Wandera</surname><given-names>Stephen Ojiambo</given-names></name><address><email>swandera@gmail.com</email></address><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author"><name><surname>Kwagala</surname><given-names>Betty</given-names></name><address><email>kkwagala@gmail.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Ntozi</surname><given-names>James</given-names></name><address><email>jntozi@gmail.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><aff id="Aff1"><label></label>Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, P.O. Box 7062, Kampala, Uganda</aff><aff id="Aff2"><label></label>Consortium for Advanced Research Training in Africa (CARTA cohort 2) Fellow at the African Population and Health Research Centre (APHRC), Nairobi, Kenya</aff></contrib-group><pub-date pub-type="epub"><day>7</day><month>3</month><year>2015</year></pub-date><pub-date pub-type="pmc-release"><day>7</day><month>3</month><year>2015</year></pub-date><pub-date pub-type="collection"><year>2015</year></pub-date><volume>14</volume><elocation-id>26</elocation-id><history><date date-type="received"><day>24</day><month>10</month><year>2014</year></date><date date-type="accepted"><day>24</day><month>2</month><year>2015</year></date></history><permissions><copyright-statement>© Wandera et al.; licensee BioMed Central. 2015</copyright-statement><license license-type="open-access"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0">http://creativecommons.org/licenses/by/4.0</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><abstract id="Abs1"><sec><title>Background</title><p>Older persons report poor health status and greater need for healthcare. However, there is limited research on older persons’ healthcare disparities in Uganda. Therefore, this paper aimed at investigating factors associated with older persons’ healthcare access in Uganda, using a nationally representative sample.</p></sec><sec><title>Methods</title><p>We conducted secondary analysis of data from a sample of 1602 older persons who reported being sick in the last 30 days preceding the Uganda National Household Survey. We used frequency distributions for descriptive data analysis and chi-square tests to identify initial associations. We fit generalized linear models (GLM) with the poisson family and the log link function, to obtain incidence risk ratios (RR) of accessing healthcare in the last 30 days, by older persons in Uganda.</p></sec><sec><title>Results</title><p>More than three quarters (76%) of the older persons accessed healthcare in the last 30 days. Access to healthcare in the last 30 days was reduced for older persons from poor households (RR = 0.91, 95% CI: 0.83-0.99); with some walking difficulty (RR = 0.90, 95% CI: 0.83-0.97); or with a lot of walking difficulty (RR = 0.84, 95% CI: 0.75-0.95). Conversely, accessing healthcare in the last 30 days for older persons increased for those who earned wages (RR = 1.08, 95% CI: 1.00-1.15) and missed work due to illness for 1–7 days (RR = 1.19, 95% CI: 1.10-1.30); and 8–14 days (RR = 1.19, 95% CI: 1.07-1.31). In addition, those who reported non-communicable diseases (NCDs) such as heart disease, hypertension or diabetes (RR = 1.09, 95% CI: 1.01-1.16); were more likely to access healthcare during the last 30 days.</p></sec><sec><title>Conclusion</title><p>In the Ugandan context, health need factors (self-reported NCDs, severity of illness and mobility limitations) and enabling factors (household wealth status and earning wages in particular) were the most important determinants of accessing healthcare in the last 30 days among older persons.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/s12939-015-0157-z) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Africa</kwd><kwd>Uganda</kwd><kwd>Utilization</kwd><kwd>Health care</kwd><kwd>Health services</kwd><kwd>Elderly</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© The Author(s) 2015</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc><affiliations><list><country><li>Kenya</li><li>Ouganda</li></country></list><tree><country name="Ouganda"><noRegion><name sortKey="Wandera, Stephen Ojiambo" sort="Wandera, Stephen Ojiambo" uniqKey="Wandera S" first="Stephen Ojiambo" last="Wandera">Stephen Ojiambo Wandera</name></noRegion><name sortKey="Kwagala, Betty" sort="Kwagala, Betty" uniqKey="Kwagala B" first="Betty" last="Kwagala">Betty Kwagala</name><name sortKey="Ntozi, James" sort="Ntozi, James" uniqKey="Ntozi J" first="James" last="Ntozi">James Ntozi</name></country><country name="Kenya"><noRegion><name sortKey="Wandera, Stephen Ojiambo" sort="Wandera, Stephen Ojiambo" uniqKey="Wandera S" first="Stephen Ojiambo" last="Wandera">Stephen Ojiambo Wandera</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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