Do ethnic inequalities in multimorbidity reflect ethnic differences in socioeconomic status? The HELIUS study
| Autor: | Bea Spek, Karien Stronks, Marieke B. Snijder, Irene G. M. van Valkengoed, Wim J G M Verest, Henrike Galenkamp |
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| Přispěvatelé: | Public and occupational health, Master Evidence Based Practice, APH - Methodology, APH - Health Behaviors & Chronic Diseases, APH - Aging & Later Life, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Adult
Male Adolescent Turkey Cross-sectional study Turkish Health Status Ethnic group Black People 030209 endocrinology & metabolism Social class Logistic regression Odds Helius Young Adult 03 medical and health sciences Sex Factors 0302 clinical medicine 5. Gender equality Surveys and Questionnaires Prevalence Humans Medicine Migration and Health 030212 general & internal medicine 10. No inequality Socioeconomic status Minority Groups Aged Netherlands Suriname biology business.industry Age Factors 1. No poverty Public Health Environmental and Occupational Health Multimorbidity Middle Aged biology.organism_classification language.human_language Morocco Cross-Sectional Studies Social Class language Educational Status Regression Analysis Female business Demography |
| Zdroj: | The European Journal of Public Health European journal of public health, 29(4), 687-693. Oxford University Press |
| ISSN: | 1101-1262 |
| Popis: | Background The burden of multimorbidity is likely higher in ethnic minority populations, as most individual diseases are more prevalent in minority groups. However, information is scarce. We examined ethnic inequalities in multimorbidity, and investigated to what extent they reflect differences in socioeconomic status (SES). Methods We included Healthy Life in an Urban Setting study participants of Dutch (N = 4582), South-Asian Surinamese (N = 3258), African Surinamese (N = 4267), Ghanaian (N = 2282), Turkish (N = 3879) and Moroccan (N = 4094) origin (aged 18–70 years). Educational level, employment status, income situation and multimorbidity were defined based on questionnaires. We described the prevalence and examined age-adjusted ethnic inequalities in multimorbidity with logistic regression analyses. To assess the contribution of SES, we added SES indicators to the age-adjusted model. Results The prevalence of multimorbidity ranged from 27.1 to 53.4% in men and from 38.5 to 69.6% in women. The prevalence of multimorbidity in most ethnic minority groups was comparable to the prevalence among Dutch participants who were 1–3 decades older. After adjustment for SES, the odds of multimorbidity remained significantly higher in ethnic minority groups. For instance, age-adjusted OR for multimorbidity for the Turkish compared to the Dutch changed from 4.43 (3.84–5.13) to 2.34 (1.99–2.75) in men and from 5.35 (4.69–6.10) to 2.94 (2.54–3.41) in women after simultaneous adjustment for all SES indicators. Conclusions We found a significantly higher prevalence of multimorbidity in ethnic minority men and women compared to Dutch, and results pointed to an earlier onset of multimorbidity in ethnic minority groups. These inequalities in multimorbidity were not fully accounted for by differences in SES. |
| Databáze: | OpenAIRE |
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