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Predictors of Self-rated Health Status Among Texas Residents

Overview
Specialty Public Health
Date 2005 Sep 17
PMID 16164816
Citations 39
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Abstract

Introduction: The purpose of this study was to investigate the predictors of self-rated health status for Texas adults using the current 2003 Behavioral Risk Factor Surveillance System data. Self-rated health is generally accepted as a valid measure of health status in population studies, and understanding its correlates may help public health professionals prioritize health-promotion and disease-prevention interventions.

Methods: The two research questions addressed by this study involved the predictors of self-rated health: 1) "Do demographic characteristics, health care coverage, leisure-time physical activity, and body mass index predict self-rated health status for Texas residents aged 18 to 64 years?" and 2) "Does choice of interview language (English vs Spanish) predict self-rated health status for Texas residents of Hispanic ethnicity aged 18 to 64 years?" Key analysis variables were identified, and descriptive statistics were used to describe the major variables and determine whether the number of respondents for each variable was sufficient for analysis. Multivariate regression analysis was used to assess the variables.

Results: Multiple logistic regression analysis (controlling for diabetes and arthritis) of the self-rated health predictors indicated that older age, lack of health care coverage, lack of a college education, being Hispanic, having a lower income, obesity, and not exercising explained 19.4% of the variance of fair and poor self-rated health. The interview language (English or Spanish), age, sex, education, income, obesity, health insurance coverage, and physical activity (controlling for chronic illness) explained 22.8% of the variance in fair and poor self-rated health for Hispanic respondents.

Conclusion: The results of this study suggest that a college education, a lower body mass index, non-Hispanic ethnicity, and participation in physical activity are associated with good, very good, or excellent self-rated health status. The finding that the interview language significantly predicted fair and poor self-rated health substantiates previous research and emphasizes the importance of culturally sensitive approaches to health care services.

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