Titre :
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Time Trends and Seasonal Patterns of Health-Related Quality of Life Among U.S. Adults. (2009)
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Auteurs :
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HAOMIAO JIA (.) : USA. Department of Biostatistics. Mailman School of Public Health and School of Nursing. Columbia University. New York. NY. ;
LUBETKIN (Erica-I) : USA. Department of Community Health and Social Medicine. Sophie Davis School of Biomedical Education at the City College of New York Medical School. New York. NY.
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Type de document :
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Article
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Dans :
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Public health reports (vol. 124, n° 5, 2009)
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Pagination :
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692-701
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Langues:
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Anglais
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Mots-clés :
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Tendance séculaire
;
Variation saisonnière
;
Adulte
;
Homme
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Résumé :
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[BDSP. Notice produite par INIST-CNRS R0x9p9ss. Diffusion soumise à autorisation]. Objectives. Although numerous studies have examined health-related quality of life (HRQOL) longitudinally, little is known about the impact of seasonality on HRQOL. We examined trend and seasonal variations of population HRQOL. Methods. We used data from the monthly Behavioral Risk Factor Surveillance System (BRFSS). We examined monthly observed mean physically and mentally unhealthy days from January 1993 to December 2006, using the structural time-series model to estimate the trend and seasonality of HRQOL. Results. We found overall worsening physical and mental health during the time period and a significant and regular seasonal pattern in both physical and mental health. The worst physical health was during the winter and the best physical health was during the summer. The mean number of physically unhealthy days in January was 0.63 days higher than in July. The worst mental health occurred during the spring and fall, but the magnitude of the seasonal effect was much smaller. The difference between the best and worst months of mentally unhealthy days was approximately 0.23 days. We found significant differences in unadjusted and season-adjusted unhealthy days in many counties. Conclusions. Our findings can be used to examine time-varying causal factors and the impact of interventions, such as policies designed to improve population health. Our findings also demonstrated the need for calculating season-adjusted HRQOL scores when examining cross-sectional factors on the population HRQOL measures for continuous surveys or longitudinal data.
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