Although estimates differed within subgroups, the BRFSS provided national estimates comparable to those of the NHIS. BRFSS national data could provide rapidly available information to guide national policy and program decisions.

Background Data on risk factors for COVID-19-associated hospitalization are needed to guide prevention efforts and clinical care. We sought to identify factors independently associated with COVID-19-associated hospitalizations Methods U.S. community-dwelling adults (≥18 years) hospitalized with laboratory-confirmed COVID-19 during March 1–June 23, 2020 were identified from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), a multi-state surveillance system. To calculate hospitalization rates by age, sex, and race/ethnicity strata, COVID-NET data served as the numerator and Behavioral Risk Factor Surveillance System estimates served as the population denominator for characteristics of interest. Underlying medical conditions examined included hypertension, coronary artery disease, history of stroke, diabetes, obesity [BMI ≥30 kg/m 2], severe obesity [BMI≥40 kg/m 2], chronic kidney disease, asthma, and chronic obstructive pulmonary disease. Generalized Poisson regression models were used to calculate adjusted rate ratios (aRR) for hospitalization Results Among 5,416 adults, hospitalization rates were higher among those with ≥3 underlying conditions (versus without)(aRR: 5.0; 95%CI: 3.9, 6.3), severe obesity (aRR:4.4; 95%CI: 3.4, 5.7), chronic kidney disease (aRR:4.0; 95%CI: 3.0, 5.2), diabetes (aRR:3.2; 95%CI: 2.5, 4.1), obesity (aRR:2.9; 95%CI: 2.3, 3.5), hypertension (aRR:2.8; 95%CI: 2.3, 3.4), and asthma (aRR:1.4; 95%CI: 1.1, 1.7), after adjusting for age, sex, and race/ethnicity. Adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults aged ≥65, 45-64 (versus 18-44 years), males (versus females), and non-Hispanic black and other race/ethnicities (versus non-Hispanic whites) Conclusion Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions

Problem/ConditionAs a result of the 2010 Patient Protection and Affordable Care Act, millions of U.S. adults attained health insurance coverage. However, millions of adults remain uninsured or underinsured. Compared with adults without barriers to health care, adults who lack health insurance coverage, have coverage gaps, or skip or delay care because of limited personal finances might face increased risk for poor physical and mental health and premature mortality.Period Covered2014.Description of SystemThe Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, landline- and cellular-telephone survey of noninstitutionalized adults aged ≥18 years residing in the United States. Data are collected from states, the District of Columbia, and participating U.S. territories on health risk behaviors, chronic health conditions, health care access, and use of clinical preventive services (CPS). An optional Health Care Access module was included in the 2014 BRFSS.This report summarizes 2014 BRFSS data from all 50 states and the District of Columbia on health care access and use of selected CPS recommended by the U.S. Preventive Services Task Force or the Advisory Committee on Immunization Practices among working-aged adults (aged 18–64 years), by state, state Medicaid expansion status, expanded geographic region, and federal poverty level (FPL). This report also provides analysis of primary type of health insurance coverage at the time of interview, continuity of health insurance coverage during the preceding 12 months, and other health care access measures (i.e., unmet health care need because of cost, unmet prescription need because of cost, medical debt [medical bills being paid off over time], number of health care visits during the preceding year, and satisfaction with received health care) from 43 states that included questions from the optional BRFSS Health Care Access module.ResultsIn 2014, health insurance coverage and other health care access measures varied substantially by state, state Medicaid expansion status, expanded geographic region (i.e., states categorized geographically into nine regions), and FPL category. The following proportions refer to the range of estimated prevalence for health insurance and other health care access measures by examined geographical unit (unless otherwise specified), as reported by respondents. Among adults with health insurance coverage, the range was 70.8%–94.5% for states, 78.8%–94.5% for Medicaid expansion states, 70.8%–89.1% for nonexpansion states, 73.3%–91.0% for expanded geographic regions, and 64.2%–95.8% for FPL categories. Among adults who had a usual source of health care, the range was 57.2%–86.6% for states, 57.2%–86.6% for Medicaid expansion states, 61.8%–83.9% for nonexpansion states, 64.4%–83.6% for expanded geographic regions, and 61.0%–81.6% for FPL categories. Among adults who received a routine checkup, the range was 52.1%–75.5% for states, 56.0%–75.5% for Medicaid expansion states, 52.1%–71.1% for nonexpansion states, 56.8%–70.2% for...

No abstract

No abstract

ProblemChronic conditions and disorders (e.g., diabetes, cardiovascular diseases, arthritis, and depression) are leading causes of morbidity and mortality in the United States. Healthy behaviors (e.g., physical activity, avoiding cigarette use, and refraining from binge drinking) and preventive practices (e.g., visiting a doctor for a routine check-up, tracking blood pressure, and monitoring blood cholesterol) might help prevent or successfully manage these chronic conditions. Monitoring chronic diseases, health-risk behaviors, and access to and use of health care are fundamental to the development of effective public health programs and policies at the state and local levels.Reporting PeriodJanuary–December 2015.Description of the SystemThe Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, random-digit–dialed landline- and cellular-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 and use of health care, and use of preventive health services related to the leading causes of death and disability. This report presents results for all 50 states, the District of Columbia, the Commonwealth of Puerto Rico (Puerto Rico), and Guam and for 130 metropolitan and micropolitan statistical areas (MMSAs) (N = 441,456 respondents) for 2015.ResultsThe age-adjusted prevalence estimates of health-risk behaviors, self-reported chronic health conditions, access to and use of health care, and use of preventive health services varied substantially by state, territory, and MMSA in 2015. Results are summarized for selected BRFSS measures. Each set of proportions refers to the median (range) of age-adjusted prevalence estimates for health-risk behaviors, self-reported chronic diseases or conditions, or use of preventive health care services by geographic jurisdiction, as reported by survey respondents. Adults with good or better health: 84.6% (65.9%–88.8%) for states and territories and 85.2% (66.9%–91.3%) for MMSAs. Adults with ≥14 days of poor physical health in the past 30 days: 10.9% (8.2%–17.2%) for states and territories and 10.9% (6.6%–19.1%) for MMSAs. Adults with ≥14 days of poor mental health in the past 30 days: 11.3% (7.3%–15.8%) for states and territories and 11.4% (5.6%–20.5%) for MMSAs. Adults aged 18–64 years with health care coverage: 86.8% (72.0%–93.8%) for states and territories and 86.8% (63.2%–95.7%) for MMSAs. Adults who received a routine physical checkup during the preceding 12 months: 69.0% (58.1%–79.8%) for states and territories and 69.4% (57.1%–81.1%) for MMSAs. Adults who ever had their blood cholesterol checked: 79.1% (73.3%–86.7%) for states and territories and 79.5% (65.1%–87.3%) for MMSAs. Current cigarette smoking among adults: 17.7% (9.0%–27.2%) for states and territories and 17.3% (4.5%–29.5%) for MMSAs. Binge drinking among adults during the preceding 30 days: 17.2% (11.2%–26.0%) for states and territories and 17.4% (5.5%–24.5%) for MMSAs. Ad...

BackgroundThe Behavioral Risk Factor Surveillance System (BRFSS) is a network of health-related telephone surveys--conducted by all 50 states, the District of Columbia, and participating US territories—that receive technical assistance from CDC. Data users often aggregate BRFSS state samples for national estimates without accounting for state-level sampling, a practice that could introduce bias because the weighted distributions of the state samples do not always adhere to national demographic distributions.MethodsThis article examines six methods of reweighting, which are then compared with key health indicator estimates from the National Health Interview Survey (NHIS) based on 2013 data.ResultsCompared to the usual stacking approach, all of the six new methods reduce the variance of weights and design effect at the national level, and some also reduce the estimated bias. This article also provides a comparison of the methods based on the variances induced by unequal weighting as well as the bias reduction induced by raking at the national level, and recommends a preferred method.ConclusionsThe new method leads to weighted distributions that more accurately reproduce national demographic characteristics. While the empirical results for key estimates were limited to a few health indicators, they also suggest reduction in potential bias and mean squared error. To the extent that survey outcomes are associated with these demographic characteristics, matching the national distributions will reduce bias in estimates of these outcomes at the national level.

BackgroundIdentification of risk factors for COVID-19-associated hospitalization is needed to guide prevention and clinical care.ObjectiveTo examine if age, sex, race/ethnicity, and underlying medical conditions is independently associated with COVID-19-associated hospitalizations.DesignCross-sectional.Setting70 counties within 12 states participating in the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network (COVID-NET) and a population-based sample of non-hospitalized adults residing in the COVID-NET catchment area from the Behavioral Risk Factor Surveillance System.ParticipantsU.S. community-dwelling adults (≥18 years) with laboratory-confirmed COVID-19-associated hospitalizations, March 1- June 23, 2020.MeasurementsAdjusted rate ratios (aRR) of hospitalization by age, sex, race/ethnicity and underlying medical conditions (hypertension, coronary artery disease, history of stroke, diabetes, obesity [BMI ≥30 kg/m2], severe obesity [BMI≥40 kg/m2], chronic kidney disease, asthma, and chronic obstructive pulmonary disease).ResultsOur sample included 5,416 adults with COVID-19-associated hospitalizations. Adults with (versus without) severe obesity (aRR:4.4; 95%CI: 3.4, 5.7), chronic kidney disease (aRR:4.0; 95%CI: 3.0, 5.2), diabetes (aRR:3.2; 95%CI: 2.5, 4.1), obesity (aRR:2.9; 95%CI: 2.3, 3.5), hypertension (aRR:2.8; 95%CI: 2.3, 3.4), and asthma (aRR:1.4; 95%CI: 1.1, 1.7) had higher rates of hospitalization, after adjusting for age, sex, and race/ethnicity. In models adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults ≥65 years, 45-64 years (versus 18-44 years), males (versus females), and non-Hispanic black and other race/ethnicities (versus non-Hispanic whites).LimitationsInterim analysis limited to hospitalizations with underlying medical condition data.ConclusionOur findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions.