Measurement and decomposition of socioeconomic inequality in single and multimorbidity in older adults in China and Ghana: results from the WHO study on global AGEing and adult health (SAGE)
Identifieur interne : 000057 ( Main/Exploration ); précédent : 000056; suivant : 000058Measurement and decomposition of socioeconomic inequality in single and multimorbidity in older adults in China and Ghana: results from the WHO study on global AGEing and adult health (SAGE)
Auteurs : Rasha Kunna [Suède] ; Miguel San Sebastian [Suède] ; Jennifer Stewart Williams [Suède]Source :
- International Journal for Equity in Health [ 1475-9276 ] ; 2017.
Abstract
Globally people are living longer and enduring non-communicable diseases (NCDs) many of which co-occur as multimorbidity. Demographic and socioeconomic factors are determinants of inequalities and inequities in health. There is a need for country-specific evidence of NCD inequalities in developing countries where populations are ageing rapidly amid economic and social change. The study measures and decomposes socioeconomic inequality in single and multiple NCD morbidity in adults aged 50 and over in China and Ghana.
The data source is the World Health Organization Study on Global AGEing and Adult Health (SAGE) Wave 1 (2007–2010). Nationally representative cross-sectional data collected from adults in China (
In China, the prevalence of single and multiple NCD morbidity was 64.7% and 53.4%, compared with 65.9% and 55.5% respectively in Ghana. Inequalities were significant and more highly concentrated among the poor in China (single morbidity CI = −0.0365: 95% CI = −0.0689,–0.0040; multimorbidity CI = −0.0801: 95% CI = −0.1233,-0.0368;). In Ghana inequalities were significant and more highly concentrated among the rich (single morbidity CI = 0.1182; 95% CI = 0.0697, 0.1668; multimorbidity CI = 0.1453: 95% CI = 0.0794, 0.2083). In China, rural residence contributed most to inequality in single morbidity (36.4%) and the wealth quintiles contributed most to inequality in multimorbidity (39.0%). In Ghana, the wealth quintiles contributed 24.5% to inequality in single morbidity and body mass index contributed 16.2% to the inequality in multimorbidity.
The country comparison reflects different stages of economic development and social change in China and Ghana. More studies of this type are needed to inform policy-makers about the patterning of socioeconomic inequalities in health, particularly in developing countries undergoing rapid epidemiological and demographic transitions.
Url:
DOI: 10.1186/s12939-017-0578-y
PubMed: 28506233
PubMed Central: 5433064
Affiliations:
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xml:lang="en" level="a" type="main">Measurement and decomposition of socioeconomic inequality in single and multimorbidity in older adults in China and Ghana: results from the WHO study on global AGEing and adult health (SAGE)</title><author><name sortKey="Kunna, Rasha" sort="Kunna, Rasha" uniqKey="Kunna R" first="Rasha" last="Kunna">Rasha Kunna</name><affiliation wicri:level="1"><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="ISNI">0000 0001 1034 3451</institution-id><institution-id institution-id-type="GRID">grid.12650.30</institution-id><institution>Epidemiology and Global Health, Department of Public Health and Clinical Medicine,</institution><institution>Umeå University,</institution></institution-wrap>SE-901 87 Umeå, Sweden</nlm:aff><country xml:lang="fr">Suède</country><wicri:regionArea>SE-901 87 Umeå</wicri:regionArea></affiliation></author><author><name sortKey="San Sebastian, Miguel" sort="San Sebastian, Miguel" uniqKey="San Sebastian M" first="Miguel" last="San Sebastian">Miguel San Sebastian</name><affiliation wicri:level="1"><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="ISNI">0000 0001 1034 3451</institution-id><institution-id institution-id-type="GRID">grid.12650.30</institution-id><institution>Epidemiology and Global Health, Department of Public Health and Clinical Medicine,</institution><institution>Umeå University,</institution></institution-wrap>SE-901 87 Umeå, Sweden</nlm:aff><country xml:lang="fr">Suède</country><wicri:regionArea>SE-901 87 Umeå</wicri:regionArea></affiliation></author><author><name sortKey="Stewart Williams, Jennifer" sort="Stewart Williams, Jennifer" uniqKey="Stewart Williams J" first="Jennifer" last="Stewart Williams">Jennifer Stewart Williams</name><affiliation wicri:level="1"><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="ISNI">0000 0001 1034 3451</institution-id><institution-id institution-id-type="GRID">grid.12650.30</institution-id><institution>Epidemiology and Global Health, Department of Public Health and Clinical Medicine,</institution><institution>Umeå University,</institution></institution-wrap>SE-901 87 Umeå, Sweden</nlm:aff><country xml:lang="fr">Suède</country><wicri:regionArea>SE-901 87 Umeå</wicri:regionArea></affiliation><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="ISNI">0000 0000 8831 109X</institution-id><institution-id institution-id-type="GRID">grid.266842.c</institution-id><institution>Research Centre for Generational Health and Ageing Faculty of Health,</institution><institution>University of Newcastle,</institution></institution-wrap>New Lambton Heights, NSW 2305 Australia</nlm:aff><wicri:noCountry code="subfield">NSW 2305 Australia</wicri:noCountry></affiliation></author></analytic><series><title level="j">International Journal for Equity in Health</title><idno type="eISSN">1475-9276</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Globally people are living longer and enduring non-communicable diseases (NCDs) many of which co-occur as multimorbidity. Demographic and socioeconomic factors are determinants of inequalities and inequities in health. There is a need for country-specific evidence of NCD inequalities in developing countries where populations are ageing rapidly amid economic and social change. The study measures and decomposes socioeconomic inequality in single and multiple NCD morbidity in adults aged 50 and over in China and Ghana.</p></sec><sec><title>Methods</title><p>The data source is the World Health Organization Study on Global AGEing and Adult Health (SAGE) Wave 1 (2007–2010). Nationally representative cross-sectional data collected from adults in China (<italic>n</italic> = 11,814) and Ghana (<italic>n</italic> = 4,050) are analysed. Country populations are ranked by a socioeconomic index based on ownership of household assets. The study uses a decomposed concentration index (CI) of single and multiple NCD morbidity (multimorbidity) covering arthritis, diabetes, angina, stroke, asthma, depression, chronic lung disease and hypertension. The CI quantifies the extent of overall inequality on each morbidity measure. The decomposition utilises a regression-based approach to examine individual contributions of demographic and socioeconomic factors, or determinants, to the overall inequality.</p></sec><sec><title>Results</title><p>In China, the prevalence of single and multiple NCD morbidity was 64.7% and 53.4%, compared with 65.9% and 55.5% respectively in Ghana. Inequalities were significant and more highly concentrated among the poor in China (single morbidity CI = −0.0365: 95% CI = −0.0689,–0.0040; multimorbidity CI = −0.0801: 95% CI = −0.1233,-0.0368;). In Ghana inequalities were significant and more highly concentrated among the rich (single morbidity CI = 0.1182; 95% CI = 0.0697, 0.1668; multimorbidity CI = 0.1453: 95% CI = 0.0794, 0.2083). In China, rural residence contributed most to inequality in single morbidity (36.4%) and the wealth quintiles contributed most to inequality in multimorbidity (39.0%). In Ghana, the wealth quintiles contributed 24.5% to inequality in single morbidity and body mass index contributed 16.2% to the inequality in multimorbidity.</p></sec><sec><title>Conclusions</title><p>The country comparison reflects different stages of economic development and social change in China and Ghana. 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uniqKey="Nicholas S">S Nicholas</name></author><author><name sortKey="Lu, M" uniqKey="Lu M">M Lu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Saeed, Bi" uniqKey="Saeed B">BI Saeed</name></author><author><name sortKey="Abdul Aziz, Ar" uniqKey="Abdul Aziz A">AR Abdul-Aziz</name></author><author><name sortKey="Nguah, Sb" uniqKey="Nguah S">SB Nguah</name></author><author><name sortKey="Zhao, X" uniqKey="Zhao X">X Zhao</name></author></analytic></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>Suède</li></country></list><tree><country name="Suède"><noRegion><name sortKey="Kunna, Rasha" sort="Kunna, Rasha" uniqKey="Kunna R" first="Rasha" last="Kunna">Rasha Kunna</name></noRegion><name sortKey="San Sebastian, Miguel" sort="San Sebastian, Miguel" uniqKey="San Sebastian M" first="Miguel" last="San Sebastian">Miguel San Sebastian</name><name sortKey="Stewart Williams, Jennifer" sort="Stewart Williams, Jennifer" uniqKey="Stewart Williams J" first="Jennifer" last="Stewart Williams">Jennifer Stewart Williams</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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