Abstract MP68: Populations with Multiple Adverse Behavioral Factors

• Published in: Circulation (New York, N.Y.) N.Y.), 2016-03, Vol.133 (suppl_1)
• Main Authors: Eckstein, Thomas, Houghtaling, Laura, Quick, Mariah
• Format: Article
• Language: English
• ISSN: 0009-7322; 1524-4539
• DOI: 10.1161/circ.133.suppl_1.mp68

Abstract only Traditionally, population behavioral characteristics are reported at the individual level. However, just like diseases, the combination of multiple adverse risk factors, even though they are often highly correlated, presents a different challenge and impact on community health than examining these same behaviors in isolation. We analyzed 5 risk factors in the 2014 Behavioral Risk Factor Surveillance Survey; smoking (currently a smoker), inactivity (no physical activity outside of work), excessive alcohol consumption (for women, 4 or more drinks in one sitting or an average of greater than one drink per day; for men, 5 or more drinks in one sitting or an average of greater than two drinks per day), obesity (BMI >=30), and insufficient sleep (< 7 hours per night). These five measures were selected because of their strong association with heart and other disease. We studied the frequency of multiple factors by state, sex, race, urbanicity, educational attainment and income. The attached map illustrates the variation among states in the prevalence of 3 or more risk factors in the population. In Utah, Colorado, and California, less than 9% of the population has 3 or more; in Arkansas, Louisiana, Kentucky and Mississippi, 16% or more of the population has 3 or more of these risk factors. Among demographic subpopulations, differences also exist. For non-Hispanic Asian population 4.5% (CI:3.5%-5.4%) have 3 or more risk factors compared to 16% or more exhibiting 3 or more risk factors in the non-Hispanic black, non-Hispanic American Indian and Alaskan Native, and non-Hispanic multi-racial populations. The variation among these subpopulations within states was also explored. Understanding the distribution of multiple adverse risk factors within a state’s population can help guide the efforts of public health officials, policy makers, advocacy groups and others to focus on the most affected populations and develop interventions that address multiple related conditions.