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State and local health departments and agencies can continue to use BRFSS data to identify populations at high risk for unhealthy behaviors and chronic diseases or conditions, lack of health care access, and inadequate use of preventive care services. Additionally, states can use the data to design, implement, monitor, and evaluate public health programs and policies at state and local levels.

ProblemChronic diseases and conditions (e.g., heart diseases, stroke, arthritis, and diabetes) are the leading causes of morbidity and mortality in the United States. These conditions are costly to the U.S. economy, yet they are often preventable or controllable. Behavioral risk factors (e.g., excessive alcohol consumption, tobacco use, poor diet, frequent mental distress, and insufficient sleep) are linked to the leading causes of morbidity and mortality. Adopting positive health behaviors (e.g., staying physically active, quitting tobacco use, obtaining routine physical checkups, and checking blood pressure and cholesterol levels) can reduce morbidity and mortality from chronic diseases and conditions. Monitoring the health risk behaviors, chronic diseases and conditions, access to health care, and use of preventive health services at multilevel public health points (states, territories, and metropolitan and micropolitan statistical areas [MMSA]) can provide important information for development and evaluation of health intervention programs.Reporting Period2013 and 2014.Description of the SystemThe Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, random-digit–dialed telephone survey of noninstitutionalized adults aged ≥18 years residing in the United States. BRFSS collects data on health risk behaviors, chronic diseases and conditions, access to health care, and use of preventive health services and practices related to the leading causes of death and disability in the United States and participating territories. This is the first BRFSS report to include age-adjusted prevalence estimates. For 2013 and 2014, these age-adjusted prevalence estimates are presented for all 50 states, the District of Columbia, the Commonwealth of Puerto Rico, Guam, and selected MMSA.ResultsAge-adjusted prevalence estimates of health status indicators, health care access and preventive practices, health risk behaviors, chronic diseases and conditions, and cardiovascular conditions vary by state, territory, and MMSA. Each set of proportions presented refers to the range of age-adjusted prevalence estimates of selected BRFSS measures as reported by survey respondents.The following are estimates for 2013. Adults reporting frequent mental distress: 7.7%–15.2% in states and territories and 6.3%–19.4% in MMSA. Adults with inadequate sleep: 27.6%–49.2% in states and territories and 26.5%–44.4% in MMSA. Adults aged 18–64 years having health care coverage: 66.9%–92.4% in states and territories and 60.5%–97.6% in MMSA. Adults identifying as current cigarette smokers: 10.1%–28.8% in states and territories and 6.1%–33.6% in MMSA. Adults reporting binge drinking during the past month: 10.5%–25.2% in states and territories and 7.2%–25.3% in MMSA. Adults with obesity: 21.0%–35.2% in states and territories and 12.1%–37.1% in MMSA. Adults aged ≥45 years with some form of arthritis: 30.6%–51.0% in states and territories and 27.6%–52.4% in MMSA. Adults aged ≥45 years who have had coronary heart disease: 7.4%–17.5% in state...

Since 2011, the Behavioral Risk Factor Surveillance System (BRFSS) has been conducting telephone surveys using landline and cell phones from all U.S. states.Due to the portability of cell phones, residents in one state can retain cell phone numbers with area codes from other states. Protocol dictates that BRFSS must interview such out-of-state respondents to complete the core BRFSS interview and collected data must then be transferred to the state of current residence.We used cell phone data from 2014 BRFSS to compare the demographic factors, health care access, health behaviors, history of chronic disease, and chronic conditions among out-of-state interview (movers) with those respondents whose cell phone numbers matched their current state of residence (did not move).The estimated weighted population percentage of movers was 10% nationwide and ranged from 1.5% in Hawaii to 21.0% in Nevada (median: 5.8%). Compared with respondents who did not move, movers were significantly more likely to be younger, white non-Hispanic, college graduate, never married, and more likely to have health care coverage. After adjusting for demographics, movers were 16% less likely to report no leisure time physical activity, 17% less likely to smoke, 7% less likely to be overweight or obese, 33% less likely to report diabetes, and 12% less likely to report having arthritis than respondents who did not move. Persons who might be left out of cell phone samples due to moving in or out of state may therefore represent a potential for bias in estimation of health behaviors and chronic conditions where transfer of data across state lines is not possible.

Landline RDD surveys are facing a coverage problem due to increasing cell phone only households in the US. To address this issue, the Behavioral Risk Factor Surveillance System (BRFSS) included cell phone samples in 2009. BRFSS landline and cell phone data for 2009 were used to examine the differences between landline and cell phone data in several response measures, which included: response and cooperation rates, percent completed screening question, percent completed interview and percent refusal/break-off the interview. The completion rates and refusal/break-off rates are estimated overall and among those completed screening questions, for the total sample and by state. Cell phone samples were less likely to be answered than landline samples. The dispositions of cell phone calls were more likely to be noted as answering devices/ voicemail, no response or refusal/break-offs. Cell phone respondents were also less likely to complete screening questions. However, among respondents who completed screening questions, cell phone respondents were more likely to complete the survey and less likely to refuse or break-off, a pattern which was noted in the majority of states. Also, response and cooperation rates show different pictures in the landline and cell phone samples, where landlines had higher response rate than cell phones, and cell phones had higher cooperation rates than landlines. The results provide valuable information on the importance of pursuing better strategies to overcome barriers to higher completion of screening questions and success at the initial stage of the interview. Such effects could improve the overall response rate and under coverage bias in the landline.