The prevalence of bilateral hearing loss in the United States in 2019: a small area estimation modelling approach for obtaining national, state, and county level estimates by demographic subgroup.

Background: The goal of this study was to re-estimate rates of bilateral hearing loss Nationally, and create new estimates of hearing loss prevalence at the U.S. State and County levels. Methods: We developed small area estimation models of mild, and moderate or worse bilateral hearing loss in the U.S. using data from the National Health and Nutrition Examination Survey (2001-2012, 2015-2018), the American Community Survey (2019), Census County Business Patterns (2019); Social Security Administration Data (2019); Medicare Fee-for-Service and Advantage claims data (2019); the Area Health Resources File (2019), and other sources. We defined hearing loss as mild (>25 dB through 40 dB), moderate or worse (>40 dB), or any (>25 dB) in the better hearing ear based on a 4-frequency pure-tone-average threshold, and created estimates by age group (0-4, 5-17, 18-34, 35-64, 65-74, 75+), gender, race and ethnicity, state, and county. Findings: We estimated that 37.9 million (95% Uncertainty Interval [U.I.] 36.6-39.1) Americans experienced any bilateral hearing loss; 24.9 million (95% U.I. 23.6-26.0) with mild and 13.0 million (95% U.I. 12.1-13.9) with moderate or worse. The prevalence rate of any hearing loss was 11.6% (95% U.I. 11.2%-12.0%). Hearing loss increased with age. Men were more likely to have hearing loss than women after age 35, and non-Hispanic Whites had higher rates of hearing loss than other races and ethnicities. Higher hearing loss prevalence was associated with smaller population size. West Virginia, Alaska, Wyoming, Oklahoma, and Arkansas had the highest standardised rate of bilateral hearing loss, and Washington D.C., New Jersey, New York, Maryland, and Connecticut had the lowest. Interpretation: Bilateral Hearing loss varies by State and County, with variation associated with population age, race and ethnicity, and population size. Geographic estimates can be used to raise local awareness of hearing loss as a problem, to prioritize areas for hearing loss prevention, identification, and treatment, and to guide future research on the hearing loss risk factors that contribute to these differences. Funding: CDC's National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health.

Older adults' knowledge and perception of fall risk and prevention: a scoping review.

BACKGROUND: Falls are a leading cause of injury and mortality among older adults. While multiple strategies are effective at reducing fall risk, uptake is low. Understanding how older adults think about fall risk and prevention activities can inform outreach initiatives and engagement. METHODS: We systematically searched PubMed, SCOPUS and Google Scholar for articles published between January 2015 and April 2023. Studies were eligible if they reported on knowledge or perception of fall risk and/or prevention among community-dwelling older adults. RESULTS: We included 53 studies from 20 different countries. Over half of the studies used qualitative methods, 19 used quantitative, and three used mixed methods. Most of the older adults could identify some fall risk factors and the consequences of falls. However, many older adults did not view themselves as at-risk for falls. Some older adults consider falls an inevitable part of ageing, while others believe that falls can be prevented. Cultural context may play a role in shaping these beliefs. Several studies reported on older adults' experiences and the perceived barriers and facilitators of participating in fall prevention activities. CONCLUSION: Improving the accuracy of older adults' perceptions of their own fall risk and highlighting the fact that many falls are preventable are two key messages that may help motivate older adults to take action to prevent falls. Older adults cite their healthcare provider as a trusted source of prevention information, and clinicians can leverage this opportunity to inform and motivate older adult patients about fall prevention.

The effect of occupational status on health: Putting the social in socioeconomic status.

High status occupations support positive health outcomes through providing access to both material and psychosocial resources. However, common measures of occupational status such as occupational prestige scores fail to capture cultural esteem that certain occupations can provide because they are primarily associated with the material dimensions of status, like income. Drawing on Weberian conceptions of status and a body of social psychological research on the measurement of cultural meaning, we argue that measuring people's ratings of their occupations on three dimensions-evaluation (good/bad), potency (powerful/weak), and activity (active/inactive)-provides an occupational status indicator that more fully captures psychosocial resources like esteem that are associated with health than more commonly used occupational prestige scores. Using a nationally representative longitudinal health and wellbeing survey of 940 American law enforcement officers collected between 2020 and 2022, we evaluate the predictive ability of evaluation, potency, and activity (EPA) ratings across thirteen measures of health and wellbeing. We find that EPA ratings were significant and positive predictors of eleven of thirteen outcomes with stronger effects for mental health outcomes compared to physical health outcomes. EPA ratings were more predictive than more commonly used occupational prestige scores. We conclude that EPA ratings are better predictors of health outcomes than occupational prestige scores and so may allow health researchers to better understand the relationship between occupational status and health.

Association Between Social Determinants of Health and Examination-Based Vision Loss vs Self-reported Vision Measures.

Importance: Recent evidence suggests that social determinants of health (SDOH) affect vision loss, but it is unclear whether estimated associations differ between clinically evaluated and self-reported vision loss. Objective: To identify associations between SDOH and evaluated vision impairment and to assess whether these associations hold when examining self-reported vision loss. Design, Setting, and Participants: This population-based cross-sectional comparison included participants 12 years and older in the 2005 to 2008 National Health and Nutrition Examination Survey (NHANES), participants of all ages (infants and older) in the 2019 American Community Survey (ACS), and adults 18 years and older in the 2019 Behavioral Risk Factor Surveillance System (BRFSS). Exposures: Five domains of SDOH that are based on Healthy People 2030: economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context. Main Outcomes and Measures: Presenting vision impairment of 20/40 or worse in the better-seeing eye (NHANES) and self-reported blindness or serious difficulty seeing, even with glasses (ACS and BRFSS). Results: Of 3 649 085 included participants, 1 873 893 were female (51.1%) and 2 504 206 were White (64.4%). SDOH across domains of economic stability, educational attainment, health care access and quality, neighborhood and built environment, and social context were significant predictors of poor vision. For example, higher income (poverty to income ratio [NHANES]: OR, 0.91; 95% CI, 0.85-0.98; [ACS]: OR, 0.93; 95% CI, 0.93-0.94; categorical income [BRFSS:<$15 000 reference]: $15 000-$24 999; OR, 0.91; 95% CI, 0.91-0.91; $25 000-$34 999: OR, 0.80; 95% CI, 0.80-0.80; $35 000-$49 999: OR, 0.71; 95% CI, 0.71-0.72; ≥$50 000: OR, 0.49; 95% CI, 0.49-0.49), employment (BRFSS: OR, 0.66; 95% CI, 0.66-0.66; ACS: OR, 0.55; 95% CI, 0.54-0.55), and owning a home (NHANES: OR, 0.85; 95% CI, 0.73-1.00; BRFSS: OR, 0.82; 95% CI, 0.82-0.82; ACS: OR, 0.79; 95% CI, 0.79-0.79) were associated with lower odds of vision loss. The study team identified no differences in the general direction of the associations when using either clinically evaluated or self-reported vision measures. Conclusions and Relevance: The study team found evidence that associations between SDOH and vision impairment track together when using either clinically evaluated or self-reported vision loss. These findings support the use of self-reported vision data in a surveillance system to track trends in SDOH and vision health outcomes within subnational geographies.

SNAP and Cardiometabolic Risk in Youth.

Increasing numbers of children and adolescents have unhealthy cardiometabolic risk factors and show signs of developing metabolic syndrome (MetS). Low-income populations tend to have higher levels of risk factors associated with MetS. The Supplemental Nutrition Assistance Program (SNAP) has the potential to reduce poverty and food insecurity, but little is known about how the program affects MetS. We examine the relationship between SNAP and the cardiometabolic risk factors in children and adolescents using regression discontinuity to control for unobserved differences between participants and nonparticipants. We find that SNAP-eligible youth who experience food insecurity have significantly healthier outcomes compared to food-insecure youth just over the income-eligibility threshold. Our findings suggest that SNAP may be most beneficial to the most disadvantaged households. Policy makers should consider the broad range of potential health benefits of SNAP.