Neighborhood environmental vulnerability and pediatric asthma morbidity in US metropolitan areas.

BACKGROUND: Research suggests demographic, economic, residential, and health-related factors influence vulnerability to environmental exposures. Greater environmental vulnerability may exacerbate environmentally related health outcomes. We developed a neighborhood environmental vulnerability index (NEVI) to operationalize environmental vulnerability on a neighborhood level. OBJECTIVE: We explored the relationship between NEVI and pediatric asthma emergency department (ED) visits (2014-19) in 3 US metropolitan areas: Los Angeles County, Calif; Fulton County, Ga; and New York City, NY. METHODS: We performed separate linear regression analyses examining the association between overall NEVI score and domain-specific NEVI scores (demographic, economic, residential, health status) with pediatric asthma ED visits (per 10,000) across each area. RESULTS: Linear regression analyses suggest that higher overall and domain-specific NEVI scores were associated with higher annual pediatric asthma ED visits. Adjusted R2 values suggest that overall NEVI scores explained at least 40% of the variance in pediatric asthma ED visits. Overall NEVI scores explained more of the variance in pediatric asthma ED visits in Fulton County. NEVI scores for the demographic, economic, and health status domains explained more of the variance in pediatric asthma ED visits in each area compared to the NEVI score for the residential domain. CONCLUSION: Greater neighborhood environmental vulnerability was associated with greater pediatric asthma ED visits in each area. The relationship differed in effect size and variance explained across the areas. Future studies can use NEVI to identify populations in need of greater resources to mitigate the severity of environmentally related outcomes, such as pediatric asthma.

The association between early country-level COVID-19 testing capacity and later COVID-19 mortality outcomes.

BACKGROUND: The COVID-19 pandemic has overrun hospital systems while exacerbating economic hardship and food insecurity on a global scale. In an effort to understand how early action to find and control the virus is associated with cumulative outcomes, we explored how country-level testing capacity affects later COVID-19 mortality. METHODS: We used the Our World in Data database to explore testing and mortality records in 27 countries from December 31, 2019, to September 30, 2020; we applied Cox proportional hazards regression to determine the relationship between early COVID-19 testing capacity (cumulative tests per case) and later COVID-19 mortality (time to specified mortality thresholds), adjusting for country-level confounders, including median age, GDP, hospital bed capacity, population density, and nonpharmaceutical interventions. RESULTS: Higher early testing implementation, as indicated by more cumulative tests per case when mortality was still low, was associated with a lower risk for higher per capita deaths. A sample finding indicated that a higher cumulative number of tests administered per case at the time of six deaths per million persons was associated with a lower risk of reaching 15 deaths per million persons, after adjustment for all confounders (HR = 0.909; P = 0.0001). CONCLUSIONS: Countries that developed stronger COVID-19 testing capacity at early timepoints, as measured by tests administered per case identified, experienced a slower increase of deaths per capita. Thus, this study operationalizes the value of testing and provides empirical evidence that stronger testing capacity at early timepoints is associated with reduced mortality and improved pandemic control.

The Association of Pain Levels and Low Physical Activity among Older Women.

There is an integral research gap regarding whether there is a relationship between pain levels and low physical activity among older women. This is a secondary analysis of a longitudinal cohort study, the Women's Health and Aging Study (WHAS) II. Our analyses included 436 community-dwelling women between the ages of 70 and 79, who were followed for 10.5 years. We employed marginal structural modeling, which controls for time-dependent confounding, with the aim of assessing the potential direct association between pain levels and low physical activity and assess a graded relationship. Compared to women with no pain, those with widespread pain were nearly half as likely to be moderately active versus low active (aOR: 0.46, 95% confidence interval (CI): 0.22, 0.96). A graded association was observed across the four pain levels (no pain or mild pain, other pain, moderate or severe lower extremity pain, and widespread pain) on low physical activity. Our findings indicate that reducing chronic widespread pain in older women may increase moderate physical activity, and therefore reduce the downstream health risks of low physical activity, including morbidity and mortality risk.

Adapted Stopping Elderly Accidents, Deaths, and Injuries Questions for Falls Risk Screening: Predictive Ability in Older Drivers.

INTRODUCTION: Fall fatality rates among U.S. older adults increased 30% from 2007 to 2016. In response, the Centers for Disease Control and Prevention developed the Stopping Elderly Accidents, Deaths, and Injuries algorithm for fall risk screening, assessment, and intervention. The current Stopping Elderly Accidents, Deaths, and Injuries algorithm with 2 levels (at risk and not at risk) was adapted to an existing cohort of older adult drivers. METHODS: A U.S. multisite prospective cohort (N=2,990) of drivers (aged 65-79 years), from 2015 to 2017, was used for these analyses completed in January 2020-October 2020. To measure the adapted Stopping Elderly Accidents, Deaths, and Injuries key questions for fall risk screening performance in predicting future falls, adjusted logistic regression determined the area of the receiver operating characteristic curve. An adjusted mixed logistic regression modeled the association between the adapted Stopping Elderly Accidents, Deaths, and Injuries key questions and future falls. RESULTS: The adapted Stopping Elderly Accidents, Deaths, and Injuries key questions yielded an area under the curve of 0.65 in determining any fall over 2 years. The adjusted mixed logistic regression model suggests that those at risk for falls at baseline were associated with 2.37 times higher odds of any fall (95% CI=2.00, 2.80) and 3.60 times higher odds of multiple falls (95% CI=2.88, 4.51) over 2 years. CONCLUSIONS: The adapted Stopping Elderly Accidents, Deaths, and Injuries key questions for fall risk screening yielded fair predictive ability for falls over 2 years and were strongly associated with future falls for older adult drivers. The adapted Stopping Elderly Accidents, Deaths, and Injuries key questions can be applied to existing data in nonclinical settings to strengthen fall screening and prevention at a population level.

Patterns of Self-Care Behaviors and Their Influence on Maintaining Independence: The National Health and Aging Trends Study.

Importance: Few studies have addressed the combined effects of health-promoting and self-care behaviors among older adults. Thus, new research is needed to assess the potential for behavior change to prolong independence in later life. Objectives: To determine the relationships between self-care behaviors and risks of mobility and activities of daily living (ADLs) over time. Design: Longitudinal data was used from the National Health and Aging Trends Study (NHATS) cohort. Eight baseline self-care behaviors were summarized using latent class analysis. Separately, longitudinal latent classes of mobility and ADLs were created. Setting: Annual in-person interviews conducted for a nationally representative sample. Participants: The baseline study sample included 7,609 Medicare beneficiaries aged ≥65 from NHATS who were living in community or residential care settings, with a 71% response rate. The average age was 75, with 57% female, 81% white and 78% high school graduates or higher. Approximately, 80% (n = 6,064) completed 5 years of follow-up. Exposures: Favorable vs. unfavorable self-care latent classes measured at baseline. Main outcomes and Measures: Associations were measured between baseline classes and longitudinal classes of mobility and ADLs difficulty. Among decedents, 5-year associations were measured between baseline classes and years of overall, healthy, able, and healthy/able life. Results: Two habitual baseline self-care behavioral patterns (46% favorable; 54% unfavorable) and three trajectories of change in mobility and ADLs disability (maintaining independence; shifting to accommodation/difficulty; shifting to assistance) emerged over time. Participants with a favorable baseline pattern had 92% (0.90-0.94) reduced risk in shifting to assistance class and 70% (0.64-0.76) reduced risk for shifting to accommodation/difficulty class for mobility disability. Participants with a favorable baseline pattern had 86% (0.83-0.89) reduced risk in shifting to assistance class and 24% (0.11-0.36) reduced risk in shifting to accommodation/difficulty class for ADLs disability. Those with an unfavorable pattern had 2.54 times greater risk of mortality by the end of the 5-year follow-up compared to those with a favorable pattern. Conclusion: Self-care behaviors in older age represent a habitual pattern. A favorable self-care behavioral pattern decreased the risk of moving towards a more disabled profile and added years of life. Interventions should encourage self-care behaviors constituting a favorable pattern.

Evaluating a Two-Level vs. Three-Level Fall Risk Screening Algorithm for Predicting Falls Among Older Adults.

Background and Objectives: Falls account for the highest proportion of preventable injury among older adults. Thus, the United States' Centers for Disease Control and Prevention (CDC) developed the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) algorithm to screen for fall risk. We referred to our STEADI algorithm adaptation as "Quick-STEADI" and compared the predictive abilities of the three-level (low, moderate, and high risk) and two-level (at-risk and not at-risk) Quick-STEADI algorithms. We additionally assessed the qualitative implementation of the Quick-STEADI algorithm in clinical settings. Research Design and Methods: We followed a prospective cohort (N = 200) of adults (65+ years) in the Bassett Healthcare Network (Cooperstown, NY) for 6 months in 2019. We conducted a generalized linear mixed model, adjusting for sociodemographic variables, to determine how baseline fall risk predicted subsequent daily falls. We plotted receiver operating characteristic (ROC) curves and measured the area under the curve (AUC) to determine the predictive ability of the Quick-STEADI algorithm. We identified a participant sample (N = 8) to gauge the experience of the screening process and a screener sample (N = 3) to evaluate the screening implementation. Results: For the three-level Quick-STEADI algorithm, participants at low and moderate risk for falls had a reduced likelihood of daily falls compared to those at high risk (-1.09, p = 0.04; -0.99, p = 0.04). For the two-level Quick-STEADI algorithm, participants not at risk for falls were not associated with a reduced likelihood of daily falls compared to those at risk (-0.89, p = 0.13). The discriminatory ability of the three-level and two-level Quick-STEADI algorithm demonstrated similar predictability of daily falls, based on AUC (0.653; 0.6570). Furthermore, participants and screeners found the Quick-STEADI algorithm to be efficient and viable. Discussion and Implications: The Quick-STEADI is a suitable, alternative fall risk screening algorithm. Qualitative assessments of the Quick-STEADI algorithm demonstrated feasibility in integrating a falls screening program in a clinical setting. Future research should address the validation and the implementation of the Quick-STEADI algorithm in community health settings to determine if falls screening and prevention can be streamlined in these settings. This may increase engagement in fall prevention programs and decrease overall fall risk among older adults.

Associations of Frailty Status with Low-Mileage Driving and Driving Cessation in a Cohort of Older Drivers.

The US older adult population is projected to considerably increase in the future, and continued driving mobility is important for health aspects in populations with fewer transportation alternatives. This study evaluated whether frailty is associated with low-mileage driving (<1865 miles per year) and driving cessation among older adults. Baseline demographics and health data were collected for 2990 older drivers via in-person assessments and questionnaires, with 2964 reporting baseline frailty data. Multivariable log-binomial regression models were used to evaluate the association between baseline frailty status and low-mileage driving. Multivariable Cox proportional hazards regression were used to evaluate the association between baseline frailty status and driving cessation. For every unit increase in frailty, the estimated adjusted risk of driving fewer than 1865 miles/year increased by 138% (adjusted risk ratio: 2.38, 95% CI: 1.63-3.46). Relative to older drivers who were not frail, the adjusted hazard ratios of driving cessation were 4.15 (95% CI: 1.89-9.10) for those classified as prefrail and 6.08 (95% CI: 1.36-27.26) for those classified as frail. Frailty is positively associated with low-mileage driving status and driving cessation in a dose-response fashion. Public health interventions that reduce frailty, such as physical activity, may help older drivers maintain safe and independent mobility.

Global reach of ageism on older persons' health: A systematic review.

OBJECTIVE: Although there is anecdotal evidence of ageism occurring at both the structural level (in which societal institutions reinforce systematic bias against older persons) and individual level (in which older persons take in the negative views of aging of their culture), previous systematic reviews have not examined how both levels simultaneously influence health. Thus, the impact of ageism may be underestimated. We hypothesized that a comprehensive systematic review would reveal that these ageism levels adversely impact the health of older persons across geography, health outcomes, and time. METHOD: A literature search was performed using 14 databases with no restrictions on region, language, and publication type. The systematic search yielded 13,691 papers for screening, 638 for full review, and 422 studies for analyses. Sensitivity analyses that adjusted for sample size and study quality were conducted using standardized tools. The study protocol is registered (PROSPERO CRD42018090857). RESULTS: Ageism led to significantly worse health outcomes in 95.5% of the studies and 74.0% of the 1,159 ageism-health associations examined. The studies reported ageism effects in all 45 countries, 11 health domains, and 25 years studied, with the prevalence of significant findings increasing over time (p < .0001). A greater prevalence of significant ageism-health findings was found in less-developed countries than more-developed countries (p = .0002). Older persons who were less educated were particularly likely to experience adverse health effects of ageism. Evidence of ageism was found across the age, sex, and race/ethnicity of the targeters (i.e., persons perpetrating ageism). CONCLUSION: The current analysis which included over 7 million participants is the most comprehensive review of health consequences of ageism to date. Considering that the analysis revealed that the detrimental impact of ageism on older persons' health has been occurring simultaneously at the structural and individual level in five continents, our systematic review demonstrates the pernicious reach of ageism.

Ageism Amplifies Cost and Prevalence of Health Conditions.

BACKGROUND AND OBJECTIVES: The persistent status of ageism as one of the least acknowledged forms of prejudice may be due in part to an absence of quantifying its costs in economic terms. In this study, we calculated the costs of ageism on health conditions for all persons aged 60 years or older in the United States during 1 year. RESEARCH DESIGN AND MATERIALS: The ageism predictors were discrimination aimed at older persons, negative age stereotypes, and negative self-perceptions of aging. Health care costs of ageism were computed by combining analyses of the impact of the predictors with comprehensive health care spending data in 1 year for the eight most-expensive health conditions, among all Americans aged 60 years or older. As a secondary analysis, we computed the number of these health conditions experienced due to ageism. RESULTS: It was found that the 1-year cost of ageism was $63 billion, or one of every seven dollars spent on the 8 health conditions (15.4%), after adjusting for age and sex as well as removing overlapping costs from the three predictors. Also according to our model, ageism resulted in 17.04 million cases of these health conditions. DISCUSSION AND IMPLICATIONS: This is the first study to identify the economic cost that ageism imposes on health. The findings suggest that a reduction of ageism would not only have a monetary benefit for society, but also have a health benefit for older persons.

Building an Informed Consent Tool Starting with the Patient: The Patient-Centered Virtual Multimedia Interactive Informed Consent (VIC).

Patient safety and quality of care are at risk if the informed consent process does not emphasize patient comprehension. In this paper, we describe how we designed, developed, and evaluated an mHealth tool for advancing the informed consent process. Our tool enables the informed consent process to be performed on tablets (e.g., iPads) utilizing virtual coaching with text-to-speech automated translation as well as an interactive multimedia elements (e.g., graphics, video clips, animations, presentations, etc.). We designed our tool to enhance patient comprehension and quality of care, while improving the efficiency of obtaining patient consent. We present the Used-Centered Design approach we adopted to develop the tool and the results of the different methods we used during the development of the tool. Also, we describe the results of the usability study which we conducted to evaluate the effectiveness, efficiency, and user satisfaction with our mHealth App to enhance the informed consent process. Using the UCD approach we were able to design, develop, and evaluate a highly interactive mHealth App to deliver the informed consent process.