Sleep insufficiency and life expectancy at the state-county level in the United States, 2019–2025

The U.S. Preventive Services Task Force recommends that men aged 55-69years undergo shared decision-making (SDM) regarding prostate cancer (PCa) screening, and routine screening is not recommended for older men or those with limited life expectancy. We evaluated the association between individual life expectancy and the receipt and content of SDM. We identified male respondents aged ≥ 50years and older without a history of PCa within the 2020 Behavioral Risk Factor Surveillance System survey. SDM was defined as whether a healthcare professional had ever discussed the advantages and/or disadvantages of a prostate-specific antigen test with the respondent. Life expectancy was estimated based on a validated index incorporating respondent age, comorbidities, and activities of daily living. Adjusted odds ratios (aOR) were estimated for the associations between respondent age, life expectancy, and receipt of SDM, accounting for healthcare access and utilization-related factors. Reported receipt of any SDM was highest among 70-74-year-old men (62.6%, 95% CI 60.5-64.6%). In multivariable models, those with the lowest life expectancy were modestly less likely to receive SDM (aOR = 0.84, 95% CI 0.71-0.99, Q4 vs Q1) compared to those with the greatest life expectancy. SDM discussing only the advantages of screening was the most common form of SDM; the content of SDM conversations did not differ by age or life expectancy, and 14.5% of men who were recently screened reported no prior SDM whatsoever. Life expectancy appears to be inadequately incorporated into decision-making regarding PCa screening. Additional tools are needed to support SDM conversations to improve the population benefits-harms of PCa screening.

Individual-level characteristics are associated with eye care use. The influence of contextual factors on vision and eye health, as well as health behavior, is unknown. To examine the association between county-level characteristics and eye care use after accounting for individual-level characteristics using a conceptual framework. This investigation was a cross-sectional study of respondents 40 years and older participating in the Behavioral Risk Factor Surveillance System surveys between 2006 and 2010 from 22 states that used the Visual Impairment and Access to Eye Care module. Multilevel regressions were used to examine the association between county-level characteristics and eye care use after adjusting for individual-level characteristics (age, sex, race/ethnicity, educational attainment, annual household income, employment status, health care insurance coverage, eye care insurance coverage, personal established physician, poor vision or eye health, and diabetes status). Data analysis was performed from March 23, 2014, to June 7, 2016. Eye care visit and receipt of a dilated eye examination in the past year. Among 117 295 respondents who resided in 828 counties, individual-level data were obtained from the Behavioral Risk Factor Surveillance System surveys. All county-level variables were aggregated at the county level from the Behavioral Risk Factor Surveillance System surveys except for a high geographic density of eye care professionals, which was obtained from the 2010 Area Health Resource File. After controlling for individual-level characteristics, the odds of reporting an eye care visit in the past year were significantly higher among people living in counties with high percentages of black individuals (adjusted odds ratio [aOR], 1.12; 95% CI, 1.01-1.24; P = .04) or low-income households (aOR, 1.12; 95% CI, 1.00-1.25; P = .045) or with a high density of eye care professionals (aOR, 1.18; 95% CI, 1.07-1.29; P < .001) than among those living in counties with the lowest tertile of each county-level characteristic. The odds of reporting receipt of a dilated eye examination in the past year were also higher among people living in counties with the highest percentages of black individuals (aOR, 1.20; 95% CI, 1.07-1.34; P = .002) or low-income households (aOR, 1.17; 95% CI, 1.04-1.32; P = .01). However, the odds of reported receipt of a dilated eye examination in the past year were lower in counties with the highest percentages of people with poor vision and eye health compared with counties with lower percentages (aOR, 0.85; 95% CI, 0.77-0.94; P = .002). Contextual factors, measured at the county level, were associated with eye care use independent of individual-level characteristics. The findings suggest that, while individual characteristics influence health care use, it is also important to address contextual factors to improve eye care use and ultimately vision health.

Associations of Smoking, Physical Inactivity, Heavy Drinking, and Obesity with Quality-Adjusted Life Expectancy among US Adults with Depression

BackgroundOver the past 50 years, the average sleep duration for adults in the United States has decreased while the prevalence of obesity and associated outcomes has increased. The objective of this study was to determine whether perceived insufficient sleep was associated with body mass index (BMI) in a national sample.MethodsWe analyzed data from the 2008 Behavioral Risk Factor Surveillance System (BRFSS) survey (N = 384,541) in which respondents were asked, "During the past 30 days, for about how many days have you felt you did not get enough rest or sleep?" We divided respondents into six BMI categories and used multivariable linear regression and logistic regression analyses to assess the association between BMI categories and days of insufficient sleep after adjusting for sociodemographic variables, smoking, physical activity, and frequent mental distress.ResultsAdjusted mean days of insufficient sleep ranged from 7.9 (95% confidence interval [CI]: 7.8, 8.0) days for people of normal weight to 10.5 (95% CI: 10.2, 10.9) days for those in the highest weight category (BMI ≥ 40). Days of perceived insufficient sleep followed a linear trend across BMI categories. The likelihood of reporting ≥14 days of insufficient sleep in the previous 30 days was higher for respondents in the highest weight category than for those who were normal weight (34.9% vs. 25.2%; adjusted odds ratio = 1.7 (95% CI: 1.5, 1.8]).ConclusionAmong U.S. adults, days of insufficient rest or sleep strongly correlated with BMI. Sleep sufficiency should be an important consideration in the assessment of the health of overweight and obese people and should be considered by developers of weight-reduction programs.

Sleep insufficiency and the natural environment: Results from the US Behavioral Risk Factor Surveillance System survey

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

Associations between recommended levels of physical activity and health-related quality of life Findings from the 2001 Behavioral Risk Factor Surveillance System (BRFSS) survey

Background Sleep plays an integrated role in health maintenance including cardiovascular (CV) health. Sleep Insufficiency (SI) is a common modifiable risk condition that is strongly linked to major adverse CV events and mortality. However, data on the overall impact and related disparities of SI on CV mortality (CVM), at nationwide level and within different patient groups, are scarce and uncertain. Purpose Herein, we aim to study the independent relationship between county level SI and CVM in overall population and within various age, sex, and race/ethnic subgroups. Methods Using the Behavioral risk Factors Surveillance System (BRFSS), SI county levels were assessed as the percentage of adults who report fewer than the recommended level of optimal sleep duration (&amp;lt;7 hours). Age-adjusted CVM rates (ACVM) between 2016 to 2019, were obtained using wide-ranging online data for epidemiologic research tool of Centers for Disease and Prevention (CDC). BRFSS, CDC diabetes interactive atlas, census population estimates, environmental public network, and county health rankings databases, were utilized to acquire county data of demographics, CV risk, socio-environmental, and health care access factors. Poisson multivariate generalized linear mixed models were employed to assess incidence rate ratios (IRR). To evaluate the absolute impact of SI on ACVM, additional yearly deaths per 100,000 individuals (AYD) were calculated. Results Among 3143 US counties, 2853 counties who had data on SI and ACVM, were analyzed. Of 321,625,744 residents (50.8% women, 12.4% non-Hispanic blacks, 15% aged ≥65) lived at 2853 US counties in 2016, total 3,408,047 (1.1%) CV deaths occurred between 2016–2019. In fully adjusted analysis*, SI significantly associated with overall ACVM (IRR: 1.021; 95% CI: 1.013 to 1.029), that translated to 4.6 AYD. In additional subgroup analysis, SI significantly associated with higher ACVM among middle aged adults [45 to 64] (IRR: 1.024; 95% CI: 1.010 to 1.038), elderly [≥65] (IRR: 1.022; 95% CI: 1.014 to 1.030), males (IRR: 1.019; 95% CI: 1.010 to 1.028), females (IRR: 1.023; 95% CI: 1.013 to 1.033), and in non-Hispanic whites (IRR: 1.024; 95% CI: 1.016 to 1.033). Notably, this association remained significant in the (≥65) aged subgroup of males, and females, as well as in both age subgroups of the non-Hispanic whites, (Figure). Conclusion County level SI is robustly related to high ACVM, and that relationship is most apparent amongst both age and sex subgroups as well as non-Hispanic whites. Moreover, this association is significantly independent of potential confounders that have a plausible association with CVM, such as demographics, socioeconomic, environmental, health care access, and cardiovascular risk factors. Therefore, tailored population-level strategies to promote healthy sleep pattern and reduce the prevalence of SI, are imperative for preventing CVM, especially in the most impacted communities and patient subgroups. Funding Acknowledgement Type of funding sources: None.

The rising rates of uterine cancer in Hispanic women of reproductive age in the United States (444)

COPD Surveillance—United States, 1999-2011

It has become increasingly recognized that insufficient sleep is associated with adverse health outcomes. Studies have observed that sleep duration and daytime sleepiness varies by sex and marital status. Few studies have examined the impact of the number of children on sleep. To evaluate the association of marital status and number of children with insufficient sleep and in a large national sample. We analyzed data from the 2008 Behavioral Risk Factor Surveillance System (BRFSS) survey, a population-based telephone survey of non-institutionalized US adults (N=395,407), in which respondents were asked, "During the past 30days, for about how many days have you felt you did not get enough rest or sleep?" We used sex-specific, multivariate logistic regression analyses to assess the associations of marital status (married, previously married, never married) and the number of children in the household with frequent insufficient sleep (≥14days in past 30days) after adjusting for age, race/ethnicity, and education. In this study population, 23% were never married, 60% were married, and 17% were previously married. Forty-three percent reported having children aged <18years in the household. Married men (24.3%) were less likely to report frequent insufficient sleep than never married men (28.0%) or previously married men (28.8%). Never married women (33.4%) were more likely to report frequent insufficient sleep than currently married (29.0%) or previously married women (29.0%). The likelihood of frequent insufficient sleep increased in a linear fashion with the number of children in the household for all subgroups (P<0.05) except among never married men. These findings suggest that the presence of children in the household often increases the frequency of insufficient rest or sleep among the adults with whom they reside. Thus, health care providers may wish to consider the presence of children under 18years of age a potential "risk factor" for insufficient sleep when counseling adults in the household about the importance of sleep to overall health.

Coordinated Efforts Needed to Reduce Obesity in the United States

Social capital or vulnerability: Which has the stronger connection with selected U.S. health outcomes?

The goals of the current study were to assess the concurrent validity of a single-item measure of general mental distress with established, multi-item mental health measures used in population-level surveillance and to establish the optimal cutpoint for determining psychological distress (previously identified as frequent mental distress) using recently available data from the Behavioral Risk Factor Surveillance System survey. Data for this study were obtained from the core questionnaire and two optional modules available as part of the 2006 and 2007 Behavioral Risk Factor Surveillance System (BRFSS) surveys. Frequent mental distress (FMD) was identified by the number of days of self-reported poor mental health during the last 30 days. Comparisons of the number of days with poor mental health and positive scores for measures of depression and serious mental illness were calculated to identify the most efficient cutpoint for establishing FMD. Comparisons of results obtained from ROC analyses using the PHQ-8 and K6 reported 0.867 (95% CI 0.861-0.872) and 0.840 (95% CI 0.836-0.845) of the area under the curve, respectively, suggesting good accuracy. Using the Youden index, 6 days of poor mental health in the past 30 days, rather than the existing 14-day standard, was identified as the point at which the sum of the sensitivity and specificity was greatest. Results from this study suggest that a 6-day standard (FMD-6) can be used as a valid and reliable indicator of generalized mental distress with strong associations to both diagnosable depressive symptomology and serious mental illness.

E-cigarette use is associated with a self-reported diagnosis of prediabetes in never cigarette smokers: Results from the behavioral risk factor surveillance system survey