Presentation on theme: "Exploring Multiple Dimensions of Asthma Disparities Using the Behavioral Risk Factor Surveillance System Kirsti Bocskay, PhD, MPH Office of Epidemiology."— Presentation transcript:
Exploring Multiple Dimensions of Asthma Disparities Using the Behavioral Risk Factor Surveillance System Kirsti Bocskay, PhD, MPH Office of Epidemiology Chicago Department of Public Health
Disclosure of Conflict of Interest Information I have no existing conflict of information to disclose. Disclosure information stated above is current as of November 14, 2006.
Background Risk factors for asthma prevalence include race/ethnicity, gender, weight (obesity), poverty, smoking, urban residence and health care use (Rose et al., 2006; Shanawani, 2006; Ford & McCaffrey, 2006; Cohen et al., 2006; Chen et al., 2002; Lugogo & Kraft, 2006; Litonjua et al., 1999; Redd, 2002; Gold & Wright, 2005) Few studies on variations in asthma prevalence by race/ethnicity and socioeconomic status (SES) in adults, most have focused on children (Chen et al., 2002; Rose et al., 2006; Harvard 2005) Racial/ethnic disparities concentrated among very poor only in childhood asthma (Smith et al., 2005) Poverty or SES accounts for differences in asthma prevalence among racial/ethnic groups in adults (Rose et al., 2006; Litonjua et al., 1999)
Objective Examine the association of race/ethnicity, gender, age, socioeconomic status and health insurance (disparities) with the prevalence of ever having been diagnosed with asthma (Ever Asthma) and still having asthma now (Current Asthma)
Methods: Data Source Behavioral Risk Factor Surveillance System (BRFSS) –State-based, random-digit-dialed survey of the non- institutionalized, civilian population age 18 and older –Collects information about modifiable risk factors for chronic diseases and other leading causes of death –Asthma questions added to questionnaire in 1999 Have you ever been told by a doctor, nurse or other health professional that you have asthma? Do you still have asthma? –For this study, survey data for 2001-2005 was combined
Methods: Variables Race/Ethnicity Gender Age Socioeconomic Status –Household income –Employment –Education Health Plan Smoking Status Weight Year of Survey Ever Asthma Current Asthma
Methods: Statistical Analyses Bivariate analysis using chi-square statistics –Compare total study population to ever asthma population and current asthma population –Compare had asthma population to current asthma population Multiple logistic regression –Adjusted odd ratios (ORs) and 95% Confidence Intervals (CI) Persons who were “missing” data for any independent or dependent variable were excluded.
Prevalence of Ever or Current Asthma did not significantly change from 2001-2005 Asthma (Ever and Current) prevalence highest for NH Blacks, NH Others and females in this study population; slighter higher in 18-24 age group Subjects in the lowest household income bracket, have not graduated high school and unable to work also have the highest asthma prevalence (Ever and Current) in this study population
Prevalence of Ever or Current Asthma slightly higher for subjects without health insurance, former and non-smokers and the obese Bivariate analysis demonstrated that asthma prevalence (Ever and Current) is significantly different among racial/ethnic (Current Asthma only), gender, household income, employment, education (Current Asthma only) and weight (obesity) groups compared to the total study population
Multiple logistic regression revealed that only gender, weight and income significantly effect asthma prevalence (ever and current) Racial/ethnic differences exist at the lowest income brackets, but decrease/disappear as income increases Gender and socioeconomic status are different for persons who had asthma and still have asthma; Subjects who had asthma are significantly healthier than those who still have asthma.
Limitations Data not weighted, so may not be applicable to Chicago population Hispanic population is not sub-divided (can not account for intra-group differences) Small sample size for NH Others People without a landline phone are not included Number of persons excluded due to missing data Cross-sectional (what came first?)