Behavioral and Sociodemographic Determinants of Influenza Vaccination Among Caregivers During the COVID-19 Pandemic.

Binge drinking among adults, by select characteristics and state — United States, 2018

176 Background: Breast cancer research has identified certain risk factors over the years, which influence a woman's chance of getting the disease. While factors such as personal history of breast abnormalities, age and the occurrence of breast cancer among first-degree relatives have been identified as estimation factors for breast cancer risk, other factors are less conclusive. Increasingly, obesity is being analyzed as a significant risk factor for many cancers and, after tobacco use, may be one of the most modifiable behavioral cancer risk factors. Interestingly when comparing the incidence rate of breast cancer to the obesity rate nationwide many states show a disparity in the two. It may be that other behavioral risk factors are of greater importance. Methods: The US States Mississippi and West Virginia display the highest rates of obesity (over 29.4% of their population display a BMI over 30.0) and the lowest rates in breast cancer incidence nationwide (under 113.9 and 113.5 people per 100.00. residents are diagnosed with cancer each year respectively). We set out to look at various behavioral risk factors to possibly detect an underlying pattern for breast cancer. Using selected metropolitan/micropolitan area risk trend data from the Behavioral Risk Factor Surveillance System from the CDC, we compared median percentages of the following risk factors: health status, exercise, diabetes, flu vaccination, current smoking, binge drinking and obesity. Results: Both states displayed higher percentages in all risk factors compared to the national average except for one in which they were below the national average: binge drinking. Rhode Island and Connecticut, the two states with the highest incidence rates in breast cancer, in turn displayed slightly higher rates of binge drinking compared to the national average. Conclusions: It appears that binge drinking might weigh more than other behavioral factors in terms of risk associated to breast cancer. Future research will need to analyze the interplay and patterns of the various risk factors as well as evaluate the association of mammographic density and alcohol drinking to further investigate the role of alcohol and binge drinking in the development of breast cancer.

Surveillance for Health Care Access and Health Services Use, Adults Aged 18-64 Years - Behavioral Risk Factor Surveillance System, United States, 2014.

BackgroundChildhood cancer survivors (CCS) are subject to a substantial burden of treatment-related morbidity. Engaging in health protective behaviors and eliminating risk behaviors are critical to preventing chronic diseases and premature deaths. This study is aimed to provide updated information on currently smoking, physical inactivity, binge drinking patterns and associated factors among CCS using a nationwide dataset.MethodsWe constructed a sample of CCS (cancer diagnosis at ages < 21y) and healthy controls (matched on age, sex, residency, race/ethnicity) using 2020 Behavioral Risk Factor Surveillance System. We used Chi-square tests and Wilcoxon rank-sum test to examine differences in sociodemographics and clinical characteristics between two groups. Logistic, ordinal regression and multivariable models (conditional models for matching) were used to determine factors associated with risk behaviors.ResultsThe final sample (18-80y) included 372 CCS and 1107 controls. Compared to controls, CCS had a similar proportion of binge drinking (~ 18%) but higher prevalence of currently smoking (26.6% vs. 14.4%, p < 0.001), physical inactivity (23.7% vs. 17.7%, p = 0.012), and of having 2-or-3 risk behaviors (17.2% vs. 8.1%, p < 0.001). Younger age, lower educational attainment, and having multiple chronic health conditions were associated with engaging in more risk behaviors among CCS. Females, compared to male counterparts, had lower odds of binge drinking (adjusted odds ratio (aOR) = 0.30, 95% confidence interval (CI): 0.16–0.57) among CCS but not in all sample. Having multiple chronic health conditions increased odds of both currently smoking (aOR = 3.52 95%CI: 1.76–7.02) and binge drinking (aOR = 2.13 95%CI: 1.11–4.08) among CCS while it only increased odds of currently smoking in all sample.DiscussionOur study provided risk behavior information for wide age-range CCS, which is currently lacking. Every one in four CCS was currently smoking. Interventions targeting risk behavior reduction should focus on CCS with multiple chronic health conditions.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12885-024-11894-7.

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. Adults who reported no leisure-time physical activity during the preceding month: 25.5% (17.6%–47.1%) for states and territories and 24.5% (16.1%–47.3%) for MMSAs. Adults who reported consuming fruit less than once per day during the preceding month: 40.5% (33.3%–55.5%) for states and territories and 40.3% (30.1%–57.3%) for MMSAs. Adults who reported consuming vegetables less than once per day during the preceding month: 22.4% (16.6%–31.3%) for states and territories and 22.3% (13.6%–32.0%) for MMSAs. Adults who have obesity: 29.5% (19.9%–36.0%) for states and territories and 28.5% (17.8%–41.6%) for MMSAs. Adults aged ≥45 years with diagnosed diabetes: 15.9% (11.2%–26.8%) for states and territories and 15.7% (10.5%–27.6%) for MMSAs. Adults aged ≥18 years with a form of arthritis: 22.7% (17.2%–33.6%) for states and territories and 23.2% (12.3%–33.9%) for MMSAs. Adults having had a depressive disorder: 19.0% (9.6%–27.0%) for states and territories and 19.2% (9.9%–27.2%) for MMSAs. Adults with high blood pressure: 29.1% (24.2%–39.9%) for states and territories and 29.0% (19.7%–41.0%) for MMSAs. Adults with high blood cholesterol: 31.8% (27.1%–37.3%) for states and territories and 31.4% (23.2%–42.0%) for MMSAs. Adults aged ≥45 years who have had coronary heart disease: 10.3% (7.2%–16.8%) for states and territories and 10.1% (4.7%–17.8%) for MMSAs. Adults aged ≥45 years who have had a stroke: 4.9% (2.5%–7.5%) for states and territories and 4.7% (2.1%–8.4%) for MMSAs.InterpretationThe prevalence of health care access and use, health-risk behaviors, and chronic health conditions varied by state, territory, and MMSA. The data in this report underline the importance of continuing to monitor chronic diseases, health-risk behaviors, and access to and use of health care in order to assist in the planning and evaluation of public health programs and policies at the state, territory, and MMSA level.Public Health ActionState and local health departments and agencies and others interested in health and health care can continue to use BRFSS data to identify groups with or at high risk for chronic conditions, unhealthy behaviors, and limited health care access and use. BRFSS data also can be used to help design, implement, monitor, and evaluate health-related programs and policies.

This study examined the impact of the COVID-19 pandemic on adult vaccination uptake, specifically recombinant zoster vaccine (RZV), influenza (FLU), and pneumococcal vaccines (PnV), and explored factors influencing COVID-19 vaccine receipt in US adults. We conducted a retrospective analysis of nationally representative cross-sectional data from the 2019 and 2022 Behavioral Risk Factor Surveillance Systems (n=777,807). Multivariable regression models assessed vaccination status for COVID-19, RZV, FLU, and PnV, adjusting for sociodemographic factors, geography, and healthcare coverage. Among insured adults, RZV vaccination increased from 31.9% in 2019 to 41.5% in 2022, and FLU vaccination increased from 42.7% to 45.0%. Among uninsured individuals, FLU vaccination rates declined 3.2%, while RZV remained unchanged. PnV rates remained stable among the insured but decreased by 15.4% among the uninsured. Individuals with healthcare coverage were 2.9 times more likely (95% confidence interval, 2.6-3.2) to have received ≥1 dose of the COVID- 19 vaccine. Minorities reported higher uptake for 1 to 2 doses of the COVID-19 vaccine but lower uptake for FLU, RZV, and PnV than non-Hispanic Whites, who had higher rates of >4 doses of COVID-19 vaccine. Despite free access to the COVID-19 vaccine, healthcare coverage significantly influenced its uptake. Increases in RZV and FLU vaccination among the insured, in contrast to minimal changes or decreases among the uninsured, highlight the critical role of healthcare access. While RZV and FLU uptake improved post-pandemic, PnV uptake remained stable. We found no evidence that COVID-19 vaccine safety affected RZV, FLU, and PnV vaccination rates.

Influenza vaccination and use of lipid lowering therapies in adults with atherosclerotic cardiovascular disease: An analysis of the Behavioral Risk Factor Surveillance System (BRFSS)

State-specific prevalence of selected chronic disease-related characteristics--Behavioral Risk Factor Surveillance System, 2001.

Health-care access and uptake of influenza vaccination among pregnant women in the USA: a cross-sectional survey

Health-related risk behaviors among myocardial infarction survivors in the United States: A propensity score matched study.

Healthcare access by disability and race among United States Adults: Behavioral Risk Factor Surveillance System 2019 to 2021.

BackgroundIn 2024, North Carolina (NC) had a smoking rate of 17.2% and a higher-than-average rate of binge and heavy drinking. These behaviors often cluster with other health risks such as hypertension, hypercholesterolemia, and diabetes, thus leading to significant disparities in cardiovascular, physical, and mental health outcomes across the state. However, limited research has examined these clustering patterns within North Carolina.ObjectiveThis study seeks to investigate the associations between latent class membership, defined by clustering of behavioral and chronic health risk factors, and cardiovascular disease, self-reported health status, physical health status, and mental health status.MethodsWe conducted a cross-sectional analysis using the 2017, 2019, and 2021 North Carolina Behavioral Risk Factor Surveillance System (BRFSS) data. A latent class analysis (LCA) was used to identify distinct health risk profiles among adults based on smoking, alcohol use, physical activity, fruit and vegetable intake, hypertension, elevated cholesterol, and diabetes status. Multivariable logistic regression models were used to examine associations between latent class membership and four outcomes: cardiovascular disease (CVD), self-reported general health, physical health status, and mental health status. Analyses were adjusted for sociodemographic variables, and age-stratified analyses were conducted.ResultsThe LCA identified two distinct classes: “Moderate drinking overweight non-smokers” (Class 1) and “High behavioral and chronic risk profile” (Class 2). Class 1 was characterized by moderate alcohol consumption, overweight status, and low smoking prevalence, while Class 2 reflected a higher prevalence of smoking, binge drinking, hypertension, diabetes, and elevated cholesterol. Membership in Class 2 was significantly associated with increased odds of CVD (OR = 1.93; 95% CI: 1.60–2.34), poor self-reported health (OR = 1.69; 95% CI: 1.46–1.96), ≥14 days of poor physical health (OR = 1.82; 95% CI: 1.55–2.15), and ≥14 days of poor mental health (OR = 1.68; 95% CI: 1.43–1.97). In age-stratified analyses, the strongest associations were observed among young adults (18–39 years), with significantly higher odds of CVD (OR = 6.84; 95% CI: 2.79–16.72), poor physical health (OR = 2.32; 95% CI: 1.58–3.40), and poor mental health (OR = 2.12; 95% CI: 1.60–2.81). Similar but attenuated associations were observed among adults aged 40–59 and ≥60 years.ConclusionThese findings support the importance of targeted public health efforts in North Carolina that address the co-occurrence of behavioral and chronic health risk factors, especially among younger populations. Syndemic-informed interventions which focus on behavioral and proximal chronic disease risk factors may help reduce CVD burden and improve the population health.

BackgroundInfluenza immunization is a highly effective method of reducing illness, hospitalization and mortality from this disease. However, influenza vaccination rates in the U.S. remain below public health targets and persistent structural inequities reduce the likelihood that Black, American Indian and Alaska Native, Latina/o, Asian groups, and populations of low socioeconomic status will receive the influenza vaccine.MethodsWe analyzed correlates of influenza vaccination rates using the 2019 Behavioral Risk Factor Surveillance System (BRFSS) in the year 2020. Our analysis compared influenza vaccination as the outcome of interest with the variables age, sex, race, education, income, geographic location, health insurance status, access to primary care, history of delaying care due to cost, and comorbidities such as: asthma, cardiovascular disease, hypertension, body mass index, cancer and diabetes.ResultsNon-Hispanic White (46.5%) and Asian (44.1%) participants are more likely to receive the influenza vaccine compared to Non-Hispanic Black (36.7%), Hispanic (33.9%), American Indian/Alaskan Native (36.6%), and Native Hawaiian/Other Pacific Islander (37.9%) participants. We found persistent structural inequities that predict influenza vaccination, within and across racial and ethnic groups, including not having health insurance [OR: 0.51 (0.47–0.55)], not having regular access to primary care [OR: 0.50 (0.48–0.52)], and the need to delay medical care due to cost [OR: 0.75 (0.71–0.79)].ConclusionAs COVID-19 vaccination efforts evolve, it is important for physicians and policymakers to identify the structural impediments to equitable U.S. influenza vaccination so that future vaccination campaigns are not impeded by these barriers to immunization.

BackgroundIt is estimated that 1.4 million people identify as transgender and over 700,000 people identify as non-binary in the United States, many of whom face significant health disparities impacting health care access. Although previous studies have reported greater vaccine uptake in women compared to men, national-level estimates of influenza vaccine uptake among transgender and non-binary people are unknown. This study aims to characterize differences in influenza vaccination by gender identity and examine associations between vaccination status and state-based gender equality policies.MethodsWe used cross-sectional data from adults aged 18 and older who participated in the 2015-2019 United States Behavioral Risk Factors Surveillance System surveys. Weighted prevalence differences (PDs) and associated confidence intervals (CIs) of being unvaccinated against influenza by self-reported gender identity were estimated using generalized linear regression models. We identified state policies on gender identity (Figure 1) as a potential effect modifier a priori and assessed through stratification.Figure 1.U.S. states implementing the SOGI module in Behavioral Risk Factors Surveillance System between 2015-2019, classified as having restrictive versus protective policies on gender equality (N = 38)ResultsA total of 1,016,012 individuals met the inclusion criteria. Compared to cisgender women (unvaccinated prevalence=57.3%), the prevalence of being unvaccinated was significantly higher among cisgender men (64.4%; PD=7.0 per 100, 95% CI: 6.7-7.4), transgender women (65.4%; PD=8.1 per 100, 95% CI: 4.0-12.2), transgender men (64.6%; PD=7.3 per 100, 95% CI: 2.7-11.8), and non-binary individuals (64.6%; PD=7.2 per 100, 95% CI: 1.3-13.2). This pattern was similar among individuals living in protective states with more favorable gender-related policies compared to restrictive states with less favorable policies (Figure 2).Figure 2.Weighted prevalence of U.S. adults unvaccinated against influenza by gender identity, Behavioral Risk Factors Surveillance System, 2015-2019ConclusionOur results provide evidence of a disparity in influenza vaccine uptake by gender identity. To improve vaccine uptake among transgender and non-binary individuals, future research should focus on identifying barriers to and facilitators of vaccination by gender identity. These findings could be used to inform policies and public health interventions to improve vaccine uptake co-designed and implemented in partnership with the transgender and non-binary communities.DisclosuresAll Authors: No reported disclosures.

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 states and territories and 6.2%–20.9% in MMSA. Adults aged ≥45 years who have had a stroke: 3.1%–7.5% in states and territories and 2.3%–9.4% in MMSA. Adults with high blood pressure: 25.2%–40.1% in states and territories and 22.2%–42.2% in MMSA. Adults with high blood cholesterol: 28.8%–38.4% in states and territories and 26.3%–39.6% in MMSA.The following are estimates for 2014. Adults reporting frequent physical distress: 7.8%–16.0% in states and territories and 6.2%–18.5% in MMSA. Women aged 21–65 years who had a Papanicolaou test during the past 3 years: 67.7%–87.8% in states and territories and 68.0%–94.3% in MMSA. Adults aged 50–75 years who received colorectal cancer screening on the basis of the 2008 U.S. Preventive Services Task Force recommendation: 42.8%–76.7% in states and territories and 49.1%–79.6% in MMSA. Adults with inadequate sleep: 28.4%–48.6% in states and territories and 25.4%–45.3% in MMSA. Adults reporting binge drinking during the past month: 10.7%–25.1% in states and territories and 6.7%–26.3% in MMSA. Adults aged ≥45 years who have had coronary heart disease: 8.0%–17.1% in states and territories and 7.6%–19.2% in MMSA. Adults aged ≥45 years with some form of arthritis: 31.2%–54.7% in states and territories and 28.4%–54.7% in MMSA. Adults with obesity: 21.0%–35.9% in states and territories and 19.7%–42.5% in MMSA.InterpretationPrevalence of certain chronic diseases and conditions, health risk behaviors, and use of preventive health services varies among states, territories, and MMSA. The findings of this report highlight the need for continued monitoring of health status, health care access, health behaviors, and chronic diseases and conditions at state and local levels.Public Health ActionState and local health departments and agencies can continue to use BRFSS data to identify populations at risk for certain unhealthy behaviors and chronic diseases and conditions. Data also can be used to design, monitor, and evaluate public health programs at state and local levels.