Trends in American Indian/Alaskan native self-reported stroke prevalence and associated modifiable risk factors in the United States from 2011-2021.

BACKGROUND: Stroke prevalence varies by race/ethnicity, as do the risk factors that elevate the risk of stroke. Prior analyses have suggested that American Indian/Alaskan Natives (AI/AN) have higher rates of stroke and vascular risk factors. METHODS: We included biyearly data from the 2011-2021 Behavioral Risk Factor Surveillance System (BRFSS) surveys of adults (age ≥18) in the United States. We describe survey-weighted prevalence of stroke per self-report by race and ethnicity. In patients with self-reported stroke (SRS), we also describe the prevalence of modifiable vascular risk factors. RESULTS: The weighted number of U.S. participants represented in BRFSS surveys increased from 237,486,646 in 2011 to 245,350,089 in 2021. SRS prevalence increased from 2.9% in 2011 to 3.3% in 2021 (p<0.001). Amongst all race/ethnicity groups, the prevalence of stroke was highest in AI/AN at 5.4% and 5.6% in 2011 and 2021, compared to 3.0% and 3.4% for White adults (p<0.001). AI/AN with SRS were also the most likely to have four or more vascular risk factors in both 2011 and 2021 at 23.9% and 26.4% compared to 18.2% and 19.6% in White adults (p<0.001). CONCLUSION: From 2011-2021 in the United States, AI/AN consistently had the highest prevalence of self-reported stroke and highest overall burden of modifiable vascular risk factors. This persistent health disparity leaves AI/AN more susceptible to both incident and recurrent stroke.

Engagement with Preventive Health Behaviors and Safe Firearm Storage Practices Using the 2017 Behavioral Risk Factor Surveillance System.

PURPOSE: "Behavioral bundling" is a theory that explains how some health behaviors reinforce one another. This study aims to investigate the relationship between preventive health behaviors (PHBs) and safe firearm storage. DESIGN: This study used a cross-sectional design using 2017 Behavioral Risk Factor Surveillance Survey data. SETTING: Survey participants resided in California, Idaho, Kansas, Oregon, Texas, and Utah. SUBJECTS: There were 12,817 people living in households with a firearm included in this study. MEASURES: We classified individuals' engagement in 5 PHBs: cholesterol screening, influenza immunization, physical activity, primary care, and seatbelt use. We defined safe firearm storage as storing a firearm unloaded, or loaded but locked. ANALYSIS: Using Poisson regression models, we calculated adjusted prevalence ratios (aPRs) to estimate the association between engagement in the five PHBs with safe firearm storage. RESULTS: Most firearm owners reported safe firearm storage (80.3%). The prevalence of safe firearm storage was 3% higher for each additional PHB engaged in (aPR = 1.03 [1.01, 1.05]). There was a higher prevalence of safe firearm storage among those who always wore a seatbelt while driving or riding in a car compared to those who did not (aPR = 1.12 [1.05, 1.18]). CONCLUSION: This study found preliminary evidence to suggest that engagement in seatbelt usage may be bundled with safe firearm storage, though we are not able to determine causality.

Impact of COVID-19 Pandemic on Health Behaviors and Outcomes by Age Group and Race Ethnicity: Results From Behavioral Risk Factor Surveillance System Data.

This study aimed to examine changes in health behaviors and outcomes during early-pandemic (2020) vs pre-pandemic (2019) years by age groups and race/ethnicity. Multivariable logistic regressions were conducted using Behavioral Risk Factor Surveillance System datasets from 2019 (n = 418 268) and 2020 (n = 401 958). All participants reported less likelihood to exercise (aOR, .78; 95% CI: .73-.83) and have poor physical health (aOR, .91; 95% CI: .86-.98) but more likelihood to have excellent general health (aOR, 1.33; 1.17-1.53) during 2020 vs 2019. Compared to 2019, during 2020 (i) Blacks were more likely to exercise (aOR, 1.24; 95% CI: 1.02-1.51) and have excellent general health (aOR, 1.69; 95% CI: 1.13-2.54); (ii) Hispanics were less likely to exercise (aOR, .80; 95% CI: .74-.88), but more likely to have excellent general health (aOR, 2.44; 95% CI: 1.79-3.33) and mental health (aOR, 1.41; 95% CI: 1.15-1.72); and (iii) Whites were less likely to exercise (aOR, .58; 95% CI: .50-.67) and have good physical health (aOR, 0.89; 95% CI: .82-.95). All age groups, except 18-24 years, were less likely to exercise by 18%-39% during 2020 vs 2019. Furthermore, the 55-64 years age-group was 36% more likely to report excellent general health but 14% less likely to have good physical health. Identifying the most vulnerable racial/ethnic and age groups is pivotal to prioritizing public health resources and interventions to mitigate the impact of health crises.

Rural/nonrural sleep duration patterns among adults in middle and older adulthood.

OBJECTIVES: To document sleep duration differences between rural and nonrural adults in middle/older adulthood. METHODS: Data consisted of adults aged 50-80 from the 2014, 2016, 2018, and 2020 Behavioral Risk Factor Surveillance System (n = 669,978). Hierarchical multinomial logistic regression models were fit predicting self-reported short (ie, 6 or fewer hours per 24-hour period) and long (ie, 9 or more hours per 24-hour period) compared to normal-sleep duration (ie, 7-8hours per 24-hour period). RESULTS: Rural adults aged 50+ had slightly but significantly lower levels of short sleep (30.0% vs. 30.8%), and slightly but significantly higher levels of long sleep (10.6% vs. 9.4%). In multinomial logistic models that accounted for demographics, rural adults had significantly higher levels of long sleep (OR 1.16, 95% CI 1.12-1.21). The long-sleep differences were explained by socioeconomic measures. CONCLUSIONS: Sleep researchers should continue to investigate and conceptualize sleeping patterns and heterogeneity among rural adults.

The relationship of cancer history and chronic disease status to colorectal cancer screening: A cross-sectional analysis of 2020-2021 Behavioral Risk Factor Surveillance System.

PURPOSE: We examined whether having a history of cancer and chronic diseases was associated with guideline-concordant colorectal cancer (CRC) screening utilization. METHODS: Self-reported data from the 2020 and 2021 Behavioral Risk Factor Surveillance System in Oregon and West Virginia were used. Guideline-concordant CRC screening was the outcome of interest. The exposure was having a personal history of cancer, chronic diseases, or both. Multivariable logistic regressions were applied to assess the abovementioned association. RESULTS: Among 10,373 respondents aged 45-75 years, 75.5% of those with a history of cancer and chronic diseases had guideline-concordant CRC screening use versus 52.8% of those without any history (p-value < 0.05). In multivariable analysis, having a history of cancer (OR 1.74; 95% CI 1.11-2.71), chronic diseases (OR 1.35; 95% CI 1.14-1.59), and both cancer and chronic diseases (OR 2.14; 95% CI 1.62-2.82) were positively associated with screening uptake compared to respondents without any history. Regardless of disease history, older age was associated with greater CRC screening uptake (p-value < 0.05). Among respondents with chronic diseases only or without any condition, those with a health care provider had 1.7-fold and 2.7-fold increased odds of receiving CRC screening, respectively. However, current smokers were 28% and 34% less likely to be screened for CRC among those with chronic diseases only and without any conditions, respectively. CONCLUSION: Having a personal history of cancer and chronic diseases appears to be positively associated with guideline-concordant CRC screening use. Effective implementation of patient-centered communication through primary care initiatives may increase adherence to CRC screening recommendations.

The Impact of Rurality and Age on Colorectal Cancer Screening Among Michigan Residents.

Background: Colorectal cancer (CRC) is a prevalent cause of cancer-related deaths in Michigan, but not all Michigan adults had appropriate CRC screening. Objective: To assess the relationship between rurality and age on CRC screenings to inform how pharmacists could focus their efforts to educate, facilitate, or offer CRC health screenings. Methods: This was a retrospective, cross-sectional study using 2018 Michigan Behavioral Risk Factor Surveillance System (MiBRFSS) survey data. Michigan participants aged ≥ 50 years were included. Outcomes included the utilization of stool-based tests, sigmoidoscopies, colonoscopies, and the most recent CRC screening. Demographic variables included age, sex, income, race/ethnicity, relationship status, education level, employment status, income, rurality, and health insurance. Representative sampling weights were used to adjust for the complex survey design. Descriptive statistics, chi-square, and multivariable logistic regression analyses were conducted. IBM SPSS version 28.0.1.0 was used and an a priori p-value of <0.05 was deemed significant. Results: A weighted total of 3,762,540 participants were included, of which 21.3% (n = 781,907) reported living in a rural area and approximately 70% (n = 2,616,646) were between the ages of 50-69 years old. Most participants reported being White, non-Hispanic (n = 3,104,117, 84.5%), having health insurance (n = 3,619,801, 96.4%), and having a colonoscopy (74.6%, n= 2,620,581). There was no difference based on rurality. Compared to those aged 50-59 years, adults 60-69 years (AOR = 1.97, 95% CI: 1.58,2.45), 70-79 years (AOR = 3.29, 95% CI: 2.40,4.51), and ≥ 80 years (AOR = 2.23, 95% CI: 1.54,3.24) had higher odds of receiving a colonoscopy. Lack of insurance was associated with lower odds of receiving a colonoscopy (AOR = 0.38, 95% CI: 0.23, 0.56). Conclusion: Most participants reported having a CRC screening but efforts to increase CRC screening in Michigan adults aged 50-59 are warranted.

Health Care Access and Cardiovascular Risk Factor Management Among Working-Age US Adults During the Pandemic.

BACKGROUND: Low-income working-age US adults disproportionately experienced health care disruptions at the onset of the coronavirus disease 2019 pandemic. Little is known about how health care access and cardiovascular risk factor management changed as the pandemic went on or if patterns differed by state Medicaid expansion status. METHODS: Cross-sectional data from the behavioral risk factor surveillance system were used to compare self-reported measures of health care access and cardiovascular risk factor management among US adults aged 18 to 64 years in 2021 (pandemic) to 2019 (prepandemic) using multivariable Poisson regression models. We assessed differential changes between low-income (<138% federal poverty level) and high-income (>400% federal poverty level) working-age adults by including an interaction term for income group and year. We then evaluated changes among low-income adults in Medicaid expansion versus nonexpansion states using a similar approach. RESULTS: The unweighted study population included 80 767 low-income and 184 136 high-income adults. Low-income adults experienced improvements in insurance coverage (relative risk [RR], 1.10 [95% CI, 1.08-1.12]), access to a provider (RR, 1.12 [95% CI, 1.09-1.14]), and ability to afford care (RR, 1.07 [95% CI, 1.05-1.09]) in 2021 compared with 2019. While these measures also improved for high-income adults, gains in coverage and ability to afford care were more pronounced among low-income adults. However, routine visits (RR, 0.96 [95% CI, 0.94-0.98]) and cholesterol testing (RR, 0.93 [95% CI, 0.91-0.96]) decreased for low-income adults, while diabetes screening (RR, 1.01 [95% CI, 0.95-1.08]) remained stable. Treatment for hypertension (RR, 1.05 [95% CI, 1.02-1.08]) increased, and diabetes-focused visits and insulin use remained stable. These patterns were similar for high-income adults. Across most outcomes, there were no differential changes between low-income adults residing in Medicaid expansion versus nonexpansion states. CONCLUSIONS: In this national study of working-age adults in the United States, measures of health care access improved for low- and high-income adults in 2021. However, routine outpatient visits and cardiovascular risk factor screening did not return to prepandemic levels, while risk factor treatment remained stable. As many coronavirus disease-era safety net policies come to an end, targeted strategies are needed to protect health care access and improve cardiovascular risk factor screening for working-age adults.

Analysis of Interview Breakoff in the Behavioral Risk Factor Surveillance System, 2018 and 2019.

Introduction: Survey breakoff is an important source of total survey error. Most studies of breakoff have been of web surveys-less is known about telephone surveys. In the past decade, the breakoff rate has increased in the Behavioral Risk Factor Surveillance System, the world's largest annual telephone survey. Analysis of breakoff in Behavioral Risk Factor Surveillance System can improve the quality of Behavioral Risk Factor Surveillance System. It will also provide evidence in research of total survey error on telephone surveys. Methods: We used data recorded as breakoff in the 2018 and 2019 Behavioral Risk Factor Surveillance System. We converted questions and modules to a time variable and applied Kaplan-Meier method and a proportional hazard model to estimate the conditional and cumulative probabilities of breakoff and study the potential risk factors associated with breakoff. Results: Cumulative probability of breakoffs up to the end of the core questionnaire was 7.03% in 2018 and 9.56% in 2019. The highest conditional probability of breakoffs in the core was 2.85% for the physical activity section. Cumulative probability of breakoffs up to the end of the core was higher among those states that inserted their own questions or optional modules than among those that did not in both years. The median risk ratio of breakoff among all states was 5.70 in 2018 and 3.01 in 2019. Survey breakoff was associated with the length of the questionnaire, the extent of expected recollection, and the location of questions. Conclusions: Breakoff is not an ignorable component of total survey error and should be considered in Behavioral Risk Factor Surveillance System data analyses when variables have higher breakoff rates.

Outcomes of Population Surveillance Data Collection Pilots and the Behavioral Risk Factor Surveillance System: What Happens in Texas.

Declining response rates and rising costs have prompted the search for alternatives to traditional random-digit dialing (RDD) interviews. In 2021, three Behavioral Risk Factor Surveillance System (BRFSS) pilots were conducted in Texas: data collection using an RDD short message service (RDD SMS) text-messaging push-to-web pilot, an address-based push-to-web pilot, and an internet panel pilot. We used data from the three pilots and from the concurrent Texas BRFSS Computer Assisted Telephone Interview (CATI). We compared unweighted data from these four sources to demographic information from the American Community Survey (ACS) for Texas, comparing respondents' health information across the protocols as well as cost and response rates. Non-Hispanic White adults and college graduates disproportionately responded in all survey protocols. Comparing costs across protocols was difficult due to the differences in methods and overhead, but some cost comparisons could be made. The cost per complete for BRFSS/CATI ranged from $75 to $100, compared with costs per complete for address-based sampling ($31 to $39), RDD SMS ($12 to $20), and internet panel (approximately $25). There were notable differences among survey protocols and the ACS in age, race/ethnicity, education, and marital status. We found minimal differences in respondents' answers to heart disease-related questions; however, responses to flu vaccination questions differed by protocol. Comparable responses were encouraging. Properly weighted web-based data collection may help use data collected by new protocols as a supplement to future BRFSS efforts.

Electronic cigarette use and cigarette smoking associated with inadequate sleep duration among U.S. young adults.

OBJECTIVE: Nicotine use can influence inadequate sleep, but less is known about the associations of exclusive and dual use of electronic cigarettes (e-cigarettes) with combustible cigarettes in U.S. young adults. This study assessed the associations between current exclusive e-cigarette use, exclusive cigarette smoking, and dual e-cigarette and combustible cigarette use and inadequate sleep duration among U.S. young adults. METHODS: We performed a secondary analysis of 2020 Behavioral Risk Factor Surveillance System (BRFSS) data including 13,978 U.S. young adults ages 18-24 years. Inadequate sleep duration was assessed categorically using the National Sleep Foundation's age-specific recommendations that define <7 h as inadequate sleep. Weighted logistic regression models were performed while adjusting for participants' sex, race/ethnicity, education level, annual household income level, body mass index, current physical activity, mental health status, disability status, current alcohol use, and current smokeless tobacco use. RESULTS: Concerning use patterns, 11.8% of young adults were exclusive e-cigarette users, 4.7% were exclusive cigarette smokers, and 3.8% were dual e-cigarette and combustible cigarette users. Exclusive e-cigarette users (adjusted odds ratio [AOR] = 1.41, 95% confidence interval [CI] = 1.16-1.72), exclusive cigarette smokers (AOR = 1.63, 95%CI = 1.22-2.18), and dual product users (AOR = 2.03, 95%CI = 1.44-2.86) were at increased odds of having inadequate sleep duration compared to non-users, while adjusting for the covariates. Additionally, dual product users were at increased odds (AOR = 1.52, 95%CI = 1.06-2.19) of reporting inadequate sleep duration compared to exclusive e-cigarette users, while adjusting for the covariates. CONCLUSIONS: Current e-cigarette and cigarette use may influence inadequate sleep among U.S. young adults. Tobacco cessation efforts may encourage increased sleep health.

Social and racial inequalities in diabetes and cancer in the United States.

Background: Cancer and diabetes are among the leading causes of morbidity and mortality worldwide. Several studies have reported diabetes as a risk factor for developing cancer, a relationship that may be explained by associated factors shared with both diseases such as age, sex, body weight, smoking, and alcohol consumption. Social factors referred to as social determinants of health (SDOH) were shown to be associated with the risk of developing cancer and diabetes. Despite that diabetes and social factors were identified as significant determinants of cancer, no studies examined their combined effect on the risk of developing cancer. In this study, we aim at filling this gap in the literature by triangulating the association between diabetes, indices of SDOH, and the risk of developing cancer. Methods: We have conducted a quantitative study using data from the Behavioral Risk Factor Surveillance System (BRFSS), whereby information was collected nationally from residents in the United States (US) with respect to their health-related risk behaviors, chronic health conditions, and the use of preventive services. Data analysis using weighted regressions was conducted on 389,158 study participants. Results: Our findings indicated that diabetes is a risk factor that increases the likelihood of cancer by 13% (OR 1.13; 95%CI: 1.05-1.21). People of White race had higher odds for cancer compared to African Americans (OR 0.44; 95%CI: 0.39-0.49), Asians (OR 0.27; 95%CI: 0.20-0.38), and other races (OR 0.56; 95%CI: 0.46-0.69). The indices of SDOH that were positively associated with having cancer encompassed unemployment (OR 1.78; 95%CI: 1.59-1.99), retirement (OR 1.54; 95%CI: 1.43-1.67), higher income levels with ORs ranging between 1.16-1.38, college education (OR 1.10; 95%CI: 1.02-1.18), college graduates (OR 1.31; 95%CI: 1.21-1.40), and healthcare coverage (OR 1.44; 95%CI: 1.22-1.71). On the other hand, the indices of SDOH that were protective against having cancer were comprised of renting a home (OR 0.86; 95%CI: 0.79-0.93) and never married (OR 0.73; 95%CI: 0.65-0.81). Conclusion: This study offers a novel social dimension for the association between diabetes and cancer that could guide setting strategies for addressing social inequities in disease prevention and access to healthcare.

Skin cancer diagnosis over the lifetime in persons with different disabilities.

Persons with disabilities globally experience barriers to medical care, preventative screening, and experience disparate health outcomes compared to those without disabilities. The prevalence of skin cancer in persons with different disabilities is not known. The Behavioral Risk Factor Surveillance System (BRFSS) data from 2017 to 2021 was analyzed to study skin cancer across the lifetime in patients with disabilities related to hearing, vision, ambulation, cognition, independent living, and self-care. Of the 10% of BRFSS respondents with a history of skin cancer, the unadjusted prevalence in those with any disability (9.2%) was higher than those without (5.1%). Patients with hearing (adjusted odds ratio (aOR) 1.29, 95% CI 1.26-1.33) and cognitive disabilities (aOR 1.27, 95% CI 1.24-1.31) had higher odds of skin cancer than those with visual, ambulatory, selfcare, and independent living disabilities. Every disability subgroup had an elevated odds of skin cancer and this was maintained in age-stratified analysis. The elevated odds of a skin cancer diagnosis in Americans with different disabilities may be explained by differences in healthcare utilization but further research is needed to understand this association and propose proactive interventions.

Variation in hysterectomy prevalence and trends among U.S. States and Territories-Behavioral Risk Factor Surveillance System, 2012-2020.

PURPOSE: We estimated up-to-date state- and territory-level hysterectomy prevalence and trends, which can help correct the population at risk denominator and calculate more accurate uterine and cervical cancer rates. METHODS: We analyzed self-reported data for a population-based sample of 1,267,013 U.S. women aged ≥ 18 years who participated in the Behavioral Risk Factor Surveillance System surveys from 2012 to 2020. Estimates were age-standardized and stratified by sociodemographic characteristics and geography. Trends were assessed by testing for any differences in hysterectomy prevalence across years. RESULTS: Hysterectomy prevalence was highest among women aged 70-79 years (46.7%) and ≥ 80 years (48.8%). Prevalence was also higher among women who were non-Hispanic (NH) Black (21.3%), NH American Indian and Alaska Native (21.1%), and from the South (21.1%). Hysterectomy prevalence declined by 1.9 percentage points from 18.9% in 2012 to 17.0% in 2020. CONCLUSIONS: Approximately one in five U.S. women overall and half of U.S. women aged ≥ 70 years reported undergoing a hysterectomy. Our findings reveal large variations in hysterectomy prevalence within and between each of the four census regions and by race and other sociodemographic characteristics, underscoring the importance of adjusting epidemiologic measures of uterine and cervical cancers for hysterectomy status.

Trends in colorectal cancer screening in the United States, 2012 to 2020.

OBJECTIVES: Despite recommendations to increase the uptake of colorectal cancer (CRC) screening, trends in CRC screening vary with sociodemographic status. We aimed to evaluate trends in CRC screening in the US population and subpopulations. METHODS: A total of 1,082,924 participants aged 50 to 75 from five cycles (2012, 2014, 2016, 2018, and 2020) of the Behavioral Risk Factor Surveillance System were involved. Multivariable logistic regression models were performed to evaluate linear trends in CRC screening utilization from 2012 to 2018. Rao-Scott chi-square tests were used to assess the differences in CRC screening utilization between 2018 and 2020. RESULTS: The estimated percentage reporting up-to-date with CRC screening increased significantly (P for trend <0.001), from 62.8% (95% CI, 62.4%-63.2%) in 2012 to 66.7% (95% CI, 66.3%-67.2%) in 2018 and 70.4% (95% CI, 69.8%-71.0%) in 2020, in accordance with 2008 US Preventive Services Task Force recommendations. Trends followed similar patterns in most subgroups, although with different magnitudes in several subgroups, primarily those underweight showed a stable percentage over time (P for trend = 0.170). In 2020, 72.4% of participants reported they were up to date with CRC screening, including the utilization of stool DNA tests and virtual colonoscopy. Colonoscopy was the most commonly used test in 2020 (64.5%), followed by FOBT (12.6%), stool DNA test (5.8%), sigmoidoscopy (3.8%), and virtual colonoscopy (2.7%). CONCLUSIONS: In this nationally representative survey of the US population from 2012 through 2020, the percentage reporting up to date with CRC screening has increased, but not equally among all subgroups.

Small-area models to assess the geographical distribution of tobacco consumption by sex and age in Spain.

INTRODUCTION: Complete and accurate data on smoking prevalence at a local level would enable health authorities to plan context-dependent smoking interventions. However, national health surveys do not generally provide direct estimates of smoking prevalence by sex and age groups at the subnational level. This study uses a small-area model-based methodology to obtain precise estimations of smoking prevalence by sex, age group and region, from a population-based survey. METHODS: The areas targeted for analysis consisted of 180 groups based on a combination of sex, age group (15-34, 35-54, 55-64, 65-74, and ≥75 years), and Autonomous Region. Data on tobacco use came from the 2017 Spanish National Health Survey (2017 SNHS). In each of the 180 groups, we estimated the prevalence of smokers (S), ex-smokers (ExS) and never smokers (NS), as well as their coefficients of variation (CV), using a weighted ratio estimator (direct estimator) and a multinomial logistic model with random area effects. RESULTS: When smoking prevalence was estimated using the small-area model, the precision of direct estimates improved; the CV of S and ExS decreased on average by 26%, and those of NS by 25%. The range of S prevalence was 11-46% in men and 4-37% in women, excluding the group aged ≥75 years. CONCLUSIONS: This study proposes a methodology for obtaining reliable estimates of smoking prevalence in groups or areas not covered in the survey design. The model applied is a good alternative for enhancing the precision of estimates at a detailed level, at a much lower cost than that involved in conducting large-scale surveys. This method could be easily integrated into routine data processing of population health surveys. Having such estimates directly after completing a health survey would help characterize the tobacco epidemic and/or any other risk factor more precisely.

Cannabis use among cancer survivors in 22 states: Results from the Behavioral Risk Factor Surveillance System, 2020.

BACKGROUND: This study identified factors associated with recent cannabis use and cannabis use for medical purposes among cancer survivors relative to individuals without a history of cancer. METHODS: Data from the Behavioral Risk Factor Surveillance System were analyzed for the 22 states completing the optional cannabis module in 2020. Weighted multiple logistic regression was performed to explore variables associated with past 30-day cannabis use and cannabis use for medical purposes, stratified by history of cancer. Covariates included state-level cannabis policy, sociodemographic characteristics, health status indicators, and substance use. RESULTS: Cannabis use was lower among cancer survivors compared to individuals with no history of cancer (7.57% vs. 10.83%). However, a higher proportion of cancer survivors reported use for medical purposes (82.23% vs. 62.58%). After adjusting for state-level policy, biological sex, age, educational attainment, self-reported race/ethnicity, home ownership, mental health status and physical health status, current smoking (odds ratio [OR], 5.14 vs. 3.74) and binge drinking (OR, 2.71 vs. 2.69) were associated with cannabis use in both groups. Characteristics associated with medical cannabis use varied for the two groups; however, daily use (20-30 days; OR, 1.72 vs. 2.43) was associated with cannabis use for medical purposes in both groups after adjusting for other variables in the model. CONCLUSIONS: A high proportion of individuals report cannabis use for medical purposes with higher rates among cancer survivors. Findings support the urgent need for ongoing cannabis research to better understand and inform its use for medical purposes, as well as the development of high-quality standardized education materials and clinical practice guidelines.

Determinants of influenza vaccine uptake among pregnant women: Demographics and medical care access.

OBJECTIVE: To investigate how sociodemographic and medical care access variables are associated with influenza vaccine uptake among pregnant women in the USA. METHODS: This is an observational study using 2015-2019 data from the US Behavioral Risk Factor Surveillance System. Pregnant women aged 18-49 years were included. Weighted χ2 tests and weighted logistic regression models were performed using the software SAS. RESULTS: A total of 9149 pregnant women were included, of whom 39.9% received the influenza vaccine. Age, income, education and race/ethnicity were significantly associated with influenza vaccination. The following medical access factors were associated with a higher likelihood of receiving the influenza vaccine: having insurance (odds ratio [OR] 1.43, 95% confidence interval [CI] 1.04-1.97), having had a checkup in the past year (OR 1.69, 95% CI 1.40-2.03), and having a primary care provider (OR 1.45, 95% CI 1.18-1.78). In subgroup analysis by race/ethnicity, non-Hispanic black women had the least difference in influenza vaccine uptake between those with medical care access and those without. CONCLUSION: Our findings suggest that the influenza vaccine uptake level was far from optimal among pregnant women. Influenza vaccine uptake was associated with social demographics and medical care access among pregnant women.

Association between mental health and self-care behavior among older adults with diabetes according to Behavioral Risk Factor Surveillance System 2019.

AIM: To assess the association of mental health burden with diabetes-related self-care behaviors and healthcare utilization among older adults. METHOD: This cross-sectional 2019 Behavioral Risk Factor Surveillance System (BRFSS) study included ≥ 65 years old adults with self-reported diabetes. Three groups were used based on the number of days in the past month affected by mental health: 0 days (no burden), 1-13 days (occasional burden), and 14-30 days (frequent burden). Primary outcome was performing ≥ 3 of 5 diabetes-related self-care behaviors. Secondary outcome was performing ≥ 3 of 5 healthcare utilization behaviors. Multivariable logistic regression was used in Stata/SE 15.1. RESULTS: Of 14,217 included individuals, 10.2 % reported frequent mental health burden. Compared to 'no burden', 'occasional' and 'frequent burden' groups included more female, obese, not married persons with younger age of diabetes diagnosis, and reported more comorbidities, insulin use, cost-related barriers to see doctors, and diabetes-related eye issues (p < 0.05). 'Occasional/frequent burden' groups reported less self-care and healthcare utilization behaviors, except 30 % higher healthcare utilization was observed in the 'occasional burden' group compared to no burden (aOR 1.30, 95 %CI 1.08-1.58, p = 0.006). CONCLUSIONS: Overall, mental health burden was associated with reduced participation in diabetes-related self-care and healthcare utilization behaviors in a stepwise manner, except occasional burden was associated with higher healthcare utilization.

Long-Term Impact of Medicaid Expansion on Colorectal Cancer Screening in Its Targeted Population.

INTRODUCTION: Colorectal cancer screening continuously decreased its mortality and incidence. In 2010, the Affordable Care Act extended Medicaid eligibility to low-income and childless adults. Some states elected to adopt Medicaid at different times while others chose not to. Past studies on the effects of Medicaid expansion on colorectal cancer screening showed equivocal results based on short-term data following expansion. AIMS: To examine the long-term impact of Medicaid expansion on colorectal cancer screening among its targeted population at its decade mark. METHODS: Behavioral Risk Factor Surveillance System data were extracted for childless adults below 138% federal poverty level in states with different Medicaid expansion statuses from 2012 to 2020. States were stratified into very early expansion states, early expansion states, late expansion states, and non-expansion states. Colorectal cancer screening prevalence was determined for eligible respondents. Difference-in-differences analyses were used to examine the effect of Medicaid expansion on colorectal cancer screening in states with different expansion statuses. RESULTS: Colorectal cancer screening prevalence in very early, early, late, and non-expansion states all increased during the study period (40.45% vs. 48.14%, 47.52% vs 61.06%, 46.06% vs 58.92%, and 43.44% vs 56.70%). Difference-in-differences analysis showed significantly increased CRC screening prevalence in very early expansion states during 2016 compared to non-expansion states (Crude difference-in-differences + 16.45%, p = 0.02, Adjusted difference-in-differences + 15.9%, p = 0.03). No statistical significance was observed among other years and groups. CONCLUSIONS: Colorectal cancer screening increased between 2012 and 2020 in all states regardless of expansion status. However, Medicaid expansion is not associated with long-term increased colorectal cancer screening prevalence.

Disparate Cardiovascular Hospitalization Trends Among Young and Middle-Aged Adults Within and Across Race and Ethnicity Groups in Four States in the United States.

Background Inpatient hospitalizations for cardiovascular disease (CVD) decreased nationally in the past decade. However, data are lacking on whether national declines represent trends within and across race and ethnicity populations from different US regions. Methods and Results Using State Inpatient Databases, Census Bureau and Behavioral Risk Factor Surveillance System data for Florida, Kentucky, New Jersey, and North Carolina, we identified all CVD hospitalizations and population characteristics for adults aged 18 to 64 years between January 1, 2009 and December 31, 2018. We calculated yearly CVD hospitalization rates for each state for the overall population, by sex, race, and ethnicity. We modeled yearly trends in age-adjusted CVD hospitalization rate in each state using negative binomial regression. State base populations were similar by age (mean age: 40-42 years) and sex (50%-51% female) throughout the study period. There were 314 973 and 288 843 total CVD hospitalizations among the 4 states in 2009 and 2018, respectively. Crude hospitalization rates declined in all states (age 18-44 years NJ: -33.4%; KY: -17.0%; FL: -11.9%; NC: -11.2%; age 45-64 years NJ: -29.8%; KY: -20.3%; FL: -12.2%; NC: -11.6%) over the study period. In age-adjusted models, overall hospitalization rates declined significantly in NJ -2.5%/y (95% CI, -2.9 to -2.1) and in KY -1.6%/y (-1.9 to -1.2) with no significant declining trend in FL and NC. Similar findings were present by sex. Among non-Hispanic White populations, mean yearly decline in hospitalization rate was significant in all states except FL, with the greatest declines in NJ (-3.8%/y [-4.4 to -3.2], P values for state-year interaction <0.0001). By contrast, a significant declining trend was present for non-Hispanic Black and Hispanic populations only in NJ (P values for state-year interaction <0.001). We found similar differences in trend between states in sensitivity analyses incorporating additional demographic and comorbid characteristics. Conclusions Decreases in CVD hospitalization rates in the past decade among nonelderly adults varied considerably by state and appeared largely driven by declines among non-Hispanic White populations. Overall declines did not represent divergent trends between states within non-Hispanic Black and Hispanic populations. Recognition of differences not just between but also within race and ethnicity populations should inform national and local policy initiatives aimed at reducing disparities in CVD outcomes.