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Gender differences in health-related quality-of-life are partly explained by sociodemographic and socioeconomic variation between adult men and women in the US: evidence from four US nationally representative data sets

PURPOSE: The purpose of this study was to describe gender differences in self-reported health-related quality-of-life (HRQoL) and to examine whether differences are explained by sociodemographic and socioeconomic status (SES) differentials between men and women. METHODS: Data were from four US natio...

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Detalles Bibliográficos
Autores principales: Cherepanov, Dasha, Palta, Mari, Fryback, Dennis G., Robert, Stephanie A.
Formato: Texto
Lenguaje:English
Publicado: Springer Netherlands 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2940034/
https://www.ncbi.nlm.nih.gov/pubmed/20496168
http://dx.doi.org/10.1007/s11136-010-9673-x
Descripción
Sumario:PURPOSE: The purpose of this study was to describe gender differences in self-reported health-related quality-of-life (HRQoL) and to examine whether differences are explained by sociodemographic and socioeconomic status (SES) differentials between men and women. METHODS: Data were from four US nationally representative surveys: US Valuation of the EuroQol EQ-5D Health States Survey (USVEQ), Medical Expenditure Panel Survey (MEPS), National Health Measurement Study (NHMS) and Joint Canada/US Survey of Health (JCUSH). Gender differences were estimated with and without adjustment for sociodemographic and SES indicators using regression within and across data sets with SF-6D, EQ-5D, HUI2, HUI3 and QWB-SA scores as outcomes. RESULTS: Women have lower HRQoL scores than men on all indexes prior to adjustment. Adjusting for age, race, marital status, education and income reduced but did not remove the gender differences, except with HUI3. Adjusting for marital status or income had the largest impact on estimated gender differences. CONCLUSIONS: There are clear gender differences in HRQoL in the United States. These differences are partly explained by sociodemographic and SES differentials.