Diabetes mellitus and hard braking events in older adult drivers.

BACKGROUND: Diabetes mellitus (DM) can impair driving safety due to hypoglycemia, hyperglycemia, diabetic peripheral neuropathy, and diabetic eye diseases. However, few studies have examined the association between DM and driving safety in older adults based on naturalistic driving data. METHODS: Data for this study came from a multisite naturalistic driving study of drivers aged 65-79 years at baseline. Driving data for the study participants were recorded by in-vehicle recording devices for up to 44 months. We used multivariable negative binomial modeling to estimate adjusted incidence rate ratios (aIRRs) and 95% confidence intervals (CIs) of hard braking events (HBEs, defined as maneuvers with deceleration rates ≥ 0.4 g) associated with DM. RESULTS: Of the 2856 study participants eligible for this analysis, 482 (16.9%) reported having DM at baseline, including 354 (12.4%) insulin non-users and 128 (4.5%) insulin users. The incidence rates of HBEs per 1000 miles were 1.13 for drivers without DM, 1.15 for drivers with DM not using insulin, and 1.77 for drivers with DM using insulin. Compared to drivers without DM, the risk of HBEs was 48% higher for drivers with DM using insulin (aIRR 1.48; 95% CI: 1.43, 1.53). CONCLUSION: Older adult drivers with DM using insulin appear to be at increased proneness to vehicular crashes. Driving safety should be taken into consideration in DM care and management.

Frailty and poor physical functioning as risk factors for driving cessation.

Introduction: Frailty and low physical performance are modifiable factors and, therefore, targets for interventions aimed at delaying driving cessation (DC). The objective was to determine the impact of frailty and physical performance on DC. Methods: Multisite prospective cohort of older drivers. The key inclusion criteria are as follows: active driver age 65-79 years, possessing a valid driver's license, without significant cognitive impairment, and driving a 1996 car or a newer model car. Of the 2,990 enrolled participants, 2,986 (99.9%) had at least one frailty or Short Physical Performance Battery (SPPB) measure and were included in this study. In total, 42% of participants were aged 65-69 years, 86% were non-Hispanic white, 53% were female, 63% were married, and 41% had a high degree of education. The Fried Frailty Phenotype and the Expanded Short Physical Performance Battery (SPPB) from the National Health and Aging Trends Study were utilized. At each annual visit, DC was assessed by the participant notifying the study team or self-reporting after no driving activity for at least 30 days, verified via GPS. Cox proportional hazard models, including time-varying covariates, were used to examine the impact of the SPPB and frailty scores on time to DC. This assessment included examining interactions by sex. Results: Seventy-three participants (2.4%) stopped driving by the end of year 5. Among women with a fair SPPB score, the adjusted hazard ratio (HR) of DC was 0.26 (95% confidence interval (CI) 0.10-0.65) compared to those with a poor SPPB score. For those with a good SPPB score, the adjusted HR of DC had a p-value of <0.001. Among men with a fair SPPB score, the adjusted hazard ratio (HR) of DC was 0.45 (95% CI 0.25-0.81) compared to those with a poor SPPB score. For men with a good SPPB score, the adjusted HR of DC was 0.19 (95% CI 0.10-0.36). Sex was not an effect modifier between frailty and DC. For those who were categorized into pre-frail or frail, the adjusted ratio of HR to DC was 6.1 (95% CI 2.7-13.8) compared to those who were not frail. Conclusion and relevance: Frailty and poor physical functioning are major risk factors for driving cessation. Staying physically active may help older adults to extend their driving life expectancy and mobility.

Association between polypharmacy and hard braking events in older adult drivers.

BACKGROUND: Polypharmacy (i.e., simultaneous use of two or more medications) poses a serious safety concern for older drivers. This study assesses the association between polypharmacy and hard braking events in older adult drivers. METHODS: Data for this study came from a naturalistic driving study of 2990 older adults. Information about medications was collected through the "brown-bag review" method. Primary vehicles of the study participants were instrumented with data recording devices for up to 44 months. Multivariable negative binomial model was used to estimate the adjusted incidence rate ratios (aIRRs) and 95 % confidence intervals (CIs) of hard-braking events (i.e., maneuvers with linear deceleration rates ≥0.4 g) associated with polypharmacy. RESULTS: Of the 2990 participants, 2872 (96.1 %) were eligible for this analysis. At the time of enrollment, 157 (5.5 %) drivers were taking fewer than two medications, 904 (31.5 %) were taking 2-5 medications, 895 (31.2 %) were taking 6-9 medications, 571 (19.9 %) were taking 10-13 medications, and 345 (12.0 %) were taking 14 or more medications. Compared to drivers using fewer than two medications, the risk of hard-braking events increased 8 % (aIRR 1.08, 95 % CI 1.04, 1.13) for users of 2-5 medications, 12 % (aIRR 1.12, 95 % CI 1.08, 1.16) for users of 6-9 medications, 19 % (aIRR 1.19, 95 % CI 1.15, 1.24) for users of 10-13 medications, and 34 % (aIRR 1.34, 95 % CI 1.29, 1.40) for users of 14 or more medications. CONCLUSIONS: Polypharmacy in older adult drivers is associated with significantly increased incidence of hard-braking events in a dose-response fashion. Effective interventions to reduce polypharmacy use may help improve driving safety in older adults.

Impact of driving cessation on health-related quality of life trajectories.

BACKGROUND: Trajectories of health-related quality of life (HRQoL) after driving cessation (DC) are thought to decline steeply, but for some, HRQoL may improve after DC. Our objective is to examine trajectories of HRQoL for individuals before and after DC. We hypothesize that for urban drivers, volunteers and those who access alternative transportation participants' health may remain unchanged or improve. METHODS: This study uses data from the AAA Longitudinal Research on Aging Drivers (LongROAD) study, a prospective cohort of 2,990 older drivers (ages 65-79 at enrollment). The LongROAD study is a five-year multisite study and data collection ended October 31, 2022. Participants were recruited using a convenience sample from the health centers roster. The number of participants approached were 40,806 with 7.3% enrolling in the study. Sixty-one participants stopped driving permanently by year five and had data before and after DC. The PROMIS®-29 Adult Profile was utilized and includes: 1) Depression, 2) Anxiety, 3) Ability to Participate in Social Roles and Activities, 4) Physical Function, 5) Fatigue, 6) Pain Interference, 7) Sleep Disturbance, and 8) Numeric Pain Rating Scale. Adjusted (age, education and gender) individual growth models with 2989 participants with up to six observations from baseline to year 5 in the models (ranging from n = 15,041 to 15,300) were utilized. RESULTS: Ability to participate in social roles and activities after DC improved overall. For those who volunteered, social roles and activities declined not supporting our hypothesis. For those who accessed alternative transportation, fatigue had an initial large increase immediately following DC thus not supporting our hypothesis. Urban residents had worse function and more symptoms after DC compared to rural residents (not supporting our hypothesis) except for social roles and activities that declined steeply (supporting our hypothesis). CONCLUSIONS: Educating older adults that utilizing alternative transportation may cause initial fatigue after DC is recommended. Accessing alternative transportation to maintain social roles and activities is paramount for rural older adults after DC especially for older adults who like to volunteer.

Migraine headaches are associated with motor vehicle crashes and driving habits among older drivers: Prospective cohort study.

BACKGROUND: Migraine headache is common in older adults, often causing symptoms that may affect driving safety. This study examined associations of migraine with motor vehicle crashes (MVCs) and driving habits in older drivers and assessed modification of associations by medication use. METHODS: In a multi-site, prospective cohort study of active drivers aged 65-79 (53% female), we assessed prevalent migraine (i.e., ever had migraine, reported at enrollment), incident migraine (diagnosis first reported at a follow-up visit), and medications typically used for migraine prophylaxis and treatment. During 2-year follow-up, we recorded self-reported MVCs and measured driving habits using in-vehicle GPS devices. Associations of prevalent migraine with driving outcomes were estimated in multivariable mixed models. Using a matched design, associations of incident migraine with MVCs in the subsequent year were estimated with conditional logistic regression. Interactions between migraine and medications were tested in all models. RESULTS: Of 2589 drivers, 324 (12.5%) reported prevalent migraine and 34 (1.3%) incident migraine. Interactions between migraine and medications were not statistically significant in any models. Prevalent migraine was not associated with MVCs in the subsequent 2 years (adjusted OR [aOR] = 0.98; 95% CI: 0.72, 1.35), whereas incident migraine significantly increased the odds of having an MVC within 1 year (aOR = 3.27; 1.21, 8.82). Prevalent migraine was associated with small reductions in driving days and trips per month and increases in hard braking events in adjusted models. CONCLUSION: Our results suggest substantially increased likelihood of MVCs in the year after newly diagnosed migraine, indicating a potential need for driving safety interventions in these patients. We found little evidence for MVC risk or substantial changes in driving habits associated with prevalent migraine. Future research should examine timing, frequency, and severity of migraine diagnosis and symptoms, and use of medications specifically prescribed for migraine, in relation to driving outcomes.

Motor Vehicle Crash Risk in Older Adult Drivers With Attention-Deficit/Hyperactivity Disorder.

Importance: Symptoms of attention-deficit/hyperactivity disorder (ADHD), such as inattentiveness and impulsivity, could affect daily functioning and driving performance throughout the life span. Previous research on ADHD and driving safety is largely limited to adolescents and young adults. Objective: To examine the prevalence of ADHD and the association between ADHD and crash risk among older adult drivers. Design, Setting, and Participants: This prospective cohort study collected data from primary care clinics and residential communities in 5 US sites (Ann Arbor, Michigan; Baltimore, Maryland; Cooperstown, New York; Denver, Colorado; and San Diego, California) between July 6, 2015, and March 31, 2019. Participants were active drivers aged 65 to 79 years at baseline enrolled in the Longitudinal Research on Aging Drivers project who were studied for up to 44 months through in-vehicle data recording devices and annual assessments. The data analysis was performed between July 15, 2022, and August 14, 2023. Exposure: Lifetime ADHD based on an affirmative response to the question of whether the participant had ever had ADHD or had ever been told by a physician or other health professional that he or she had ADHD. Main Outcomes and Measures: The main outcomes were hard-braking events defined as maneuvers with deceleration rates of 0.4g or greater, self-reported traffic ticket events, and self-reported vehicular crashes. Multivariable negative binomial modeling was used to estimate adjusted incidence rate ratios (aIRRs) and 95% CIs of outcomes according to exposure status. Results: Of the 2832 drivers studied, 1500 (53.0%) were women and 1332 (47.0%) were men with a mean (SD) age of 71 (4) years. The lifetime prevalence of ADHD in the study sample was 2.6%. Older adult drivers with ADHD had significantly higher incidence rates of hard-braking events per 1000 miles than those without ADHD (1.35 [95% CI, 1.30-1.41] vs 1.15 [95% CI, 1.14-1.16]), as well as self-reported traffic ticket events per 1 million miles (22.47 [95% CI, 16.06-31.45] vs 9.74 [95% CI, 8.99-10.55]) and self-reported vehicular crashes per 1 million miles (27.10 [95% CI, 19.95-36.80] vs 13.50 [95% CI, 12.61-14.46]). With adjustment for baseline characteristics, ADHD was associated with a significant 7% increased risk of hard-braking events (aIRR, 1.07; 95% CI, 1.02-1.12), a 102% increased risk of self-reported traffic ticket events (aIRR, 2.02; 95% CI, 1.42-2.88), and a 74% increased risk of self-reported vehicular crashes (aIRR, 1.74; 95% CI, 1.26-2.40). Conclusions and Relevance: As observed in this prospective cohort study, older adult drivers with ADHD may be at a significantly elevated crash risk compared with their counterparts without ADHD. These findings suggest that effective interventions to improve the diagnosis and clinical management of ADHD among older adults are warranted to promote safe mobility and healthy aging.

Interaction between benzodiazepines and prescription opioids on incidence of hard braking events in older drivers.

BACKGROUND: Polypharmacy use among older adults is of increasing concern for driving safety. This study assesses the individual and joint effects of benzodiazepines and prescription opioids on the incidence of hard braking events in older drivers. METHODS: Data for this study came from the Longitudinal Research on Aging Drivers project-a multisite, prospective cohort study of 2990 drivers aged 65-79 years at enrollment (2015-2017). Adjusted incidence rate ratios (aIRRs) and 95% confidence intervals (CIs) of hard braking events (defined as maneuvers with deceleration rates ≥0.4 g and commonly known as near-crashes) were estimated through multivariable negative binominal modeling. RESULTS: Of the 2929 drivers studied, 167 (5.7%) were taking benzodiazepines,  163 (5.6%) prescription opioids, and 23 (0.8%) both drugs at baseline. The incidence rates of hard braking events per 1000 miles driven were 1.14 (95% CI 1.10-1.18) for drivers using neither benzodiazepines nor prescription opioids, 1.25 (95% CI 1.07-1.43) for those using benzodiazepines only, 1.55 (95% CI 1.35-1.76) for those using prescription opioids only, and 1.63 (95% CI 1.11-2.16) for those using both medications. Multivariable modeling revealed that the use of prescription opioids was associated with a 19% increased risk of hard braking events (aIRR 1.19, 95% CI 1.03-1.36). There existed a positive interaction between the two drugs on the additive scale but not on the multiplicative scale. CONCLUSION: Concurrent use of benzodiazepines and prescription opioids by older drivers appears to affect driving safety through increased incidence of hard braking events.

Associations of cannabis use with motor vehicle crashes and traffic stops among older drivers: AAA LongROAD study.

BACKGROUND: Acute cannabis use is associated with a higher risk of motor vehicle crashes (MVC). This study aimed to determine if self-reported past-year cannabis use is associated with MVC or traffic stops among older drivers. METHODS: This cross-sectional analysis used data from a multi-center study enrolling active drivers aged 65-79 years. Data regarding cannabis use, MVC, and traffic stops (i.e., being pulled over by police, whether ticketed or not) within the previous 12 months were collected through participant interviews. Log-binomial regression models examined associations of past-year cannabis use with MVC and traffic stops, adjusting for site and sociodemographic and mental health characteristics. RESULTS: Of 2,095 participating older drivers, 186 (8.88%) used cannabis in the past year but only 10 (<0.5%) within an hour before driving in the last 30 days; 11.41% reported an MVC and 9.45% reported a traffic stop. Past-year cannabis users had a higher prevalence of MVC (adjusted prevalence ratio [aPR] = 1.38; 95%CI: 0.96, 2.00; p = 0.086) and traffic stops (aPR = 1.58; 1.06, 2.35; p = 0.024). CONCLUSIONS: Past-year cannabis use was associated with increased traffic stops, which are correlated modestly with increased MVC in past studies and may indicate impaired driving performance. We did not find a statistically significant association of past-year cannabis use with MVC, which may indicate limited sustained effects on driving performance from periodic use among older adults, who report rarely driving immediately after use.

Detecting mild cognitive impairment and dementia in older adults using naturalistic driving data and interaction-based classification from influence score.

Several recent studies indicate that atypical changes in driving behaviors appear to be early signs of mild cognitive impairment (MCI) and dementia. These studies, however, are limited by small sample sizes and short follow-up duration. This study aims to develop an interaction-based classification method building on a statistic named Influence Score (i.e., I-score) for prediction of MCI and dementia using naturalistic driving data collected from the Longitudinal Research on Aging Drivers (LongROAD) project. Naturalistic driving trajectories were collected through in-vehicle recording devices for up to 44 months from 2977 participants who were cognitively intact at the time of enrollment. These data were further processed and aggregated to generate 31 time-series driving variables. Because of high dimensional time-series features for driving variables, we used I-score for variable selection. I-score is a measure to evaluate variables' ability to predict and is proven to be effective in differentiating between noisy and predictive variables in big data. It is introduced here to select influential variable modules or groups that account for compound interactions among explanatory variables. It is explainable regarding to what extent variables and their interactions contribute to the predictiveness of a classifier. In addition, I-score boosts the performance of classifiers over imbalanced datasets due to its association with the F1 score. Using predictive variables selected by I-score, interaction-based residual blocks are constructed over top I-score modules to generate predictors and ensemble learning aggregates these predictors to boost the prediction of the overall classifier. Experiments using naturalistic driving data show that our proposed classification method achieves the best accuracy (96%) for predicting MCI and dementia, followed by random forest (93%) and logistic regression (88%). In terms of F1 score and AUC, our proposed classifier achieves 98% and 87%, respectively, followed by random forest (with an F1 score of 96% and an AUC of 79%) and logistic regression (with an F1 score of 92% and an AUC of 77%). The results indicate that incorporating I-score into machine learning algorithms could considerably improve the model performance for predicting MCI and dementia in older drivers. We also performed the feature importance analysis and found that the right to left turn ratio and the number of hard braking events are the most important driving variables to predict MCI and dementia.

Association of falls and fear of falling with objectively-measured driving habits among older drivers: LongROAD study.

OBJECTIVE: Falls in older adults are associated with increased motor vehicle crash risk, possibly mediated by driving behavior. We examined the relationship of falls and fear of falling (FOF) with subsequent objectively measured driving habits. METHODS: This multi-site, prospective cohort study enrolled 2990 active drivers aged 65-79 (53% female). At enrollment, we assessed falls in the past year and FOF (Short Falls Efficacy Scale-International). Driving outcomes included exposure, avoidance of difficult conditions, and unsafe driving during one-year follow-up, using in-vehicle Global Positioning System devices. RESULTS: Past-year falls were associated with more hard braking events (HBE). High FOF was associated with driving fewer days, miles, and trips, driving nearer home and more HBE. Differences were attenuated and not significant after accounting for health, function, medications and sociodemographics. DISCUSSION: Differences in objectively measured driving habits according to past-year fall history and FOF were largely accounted for by differences in health and medications. Rather than directly affecting driving, falls and FOF may serve as markers for crash risk and reduced community mobility due to age-related changes and poor health.

Central Obesity Is Associated With an Increased Rate of Multisite Pain in Older Adults.

Objective: Central obesity has been associated with several adverse health events, but little research exists about the longitudinal effects of central obesity on multisite pain. The purpose of this study was to assess if central obesity, as measured by waist circumference measurement, was associated with an increased rate of having multisite pain among older adults aged 65 years and older. Design: The National Health and Aging Trends Study is a longitudinal cohort study initiated in 2011 and intended to be representative of Medicare beneficiaries in the contiguous United States. Methods: There were 7,145 community-dwelling participants included in this study. Data for this study were collected annually between 2011 and 2018. Researchers assessed if waist circumference risk level was associated with an increased rate ratio of multisite pain. Weighted data were used in a multivariable generalized estimating equation model that used a log link specified with a Poisson distribution. Results: Participants with high-risk waist circumferences (98 cm or greater for women and 109 cm or greater for men) had a 11% higher rate of multisite pain than those with low-risk waist circumferences [rate ratio (RR) 1.11, 95% CI: 1.07-1.15] adjusting for gender, age, race, education, probable major depression, arthritis, and multimorbidity count. Conclusion: As measured by waist circumference, central adiposity is associated with multisite pain in older adults. While more research is needed, reducing waist circumference may prove beneficial in reducing the burden of multisite pain.

Associations of Self-Care Health Behaviors With Driving Cessation Among Older Drivers.

Older adults are at risk of driving cessation as they age, which can result in negative health outcomes including loss of independence. This study aimed to investigate the associations of self-care health behaviors with the risk of driving cessation. Demographics, health and driving characteristics were captured from healthcare systems in Denver, CO, San Diego, CA, Ann Arbor, MI, Baltimore, MD and Cooperstown, NY for 2,990 adults at baseline then followed from July 2015 to January 2021 via in-person assessments and questionnaires. The follow-up accumulated a total of 7,348 person-years and 46 driving cessations, yielding an incidence rate of 0.63 per 100 person-years. Multivariable Cox proportional hazards regression was used to evaluate the relationship between self-care behaviors and driving cessation, stratified by gender, and accounting for multiple failure events and clustering by study site. Ability to participate in social roles and activities was associated with an 8% reduction in the risk of driving cessation [adjusted hazard ratio (HR): 0.92; 95% CI: 0.89, 0.94]. Increased participation in social activities and relationships is associated with driving longevity in older adults and should be targeted for interventions to maintain driving mobility.

Correlates of caregiver well-being: The National Study of Caregivers.

Background: The literature demonstrates an association between aspects of caregiving and support with caregiver burden and differences by race. Our objective was to examine correlates of caregiver wellbeing, and if the effect is moderated by race. Methods: The National Study of Caregiving (NSOC) is a survey of unpaid and familial caregivers affiliated with participants in the National Health and Aging Trends Study, a nationally representative survey of Medicare beneficiaries. A total of 899 participants were examined cross-sectionally with logistic and multinomial logistic regression models to obtain adjusted odds ratios (aOR) and 95% confidence intervals (CI) for NSOC Round 3 (2017), stratified by race, to determine the association between aspects of caregiving and support variables with the two outcomes, three-level caregiving gains, and response to the statement "life has meaning and purpose." Results: Among black caregivers with no family or friends to help, there were lower gains compared to very high gains (aOR: 2.82, 95% CI: 1.18, 6.77). Black and white caregivers who endorsed lower ratings regarding being appreciated by the care recipient had lower gains for "life has meaning and purpose" (aOR: 2.46, 95% CI: 1.00, 6.02; aOR: 1.65, 95% CI: 1.06, 2.56). Black caregivers with lower ratings regarding being appreciated had lower gains compared to very high gains (aOR: 5.04, 95% CI: 1.48, 17.17). White caregivers endorsing lower ratings to the same question had lower gains compared to very high gains (aOR: 3.27, 95% CI: 1.77, 6.04), and those with more help had lower gains (aOR: 0.81, 95% CI: 0.70, 0.93). Conclusion: The relationship between various correlates and positive aspects of caregiving is moderated by black and white races. Further study on the impact of aspects of caregiving and support networks for caregivers may shed light on factors contributing to racial differences and areas for intervention.

Rate of Social Isolation by Geographic Location Among Older Adults: AAA LongROAD Study.

Introduction: Social isolation is a modifiable risk factor for negative health outcomes among older adults. This work assessed the relationship between geography (i.e., urban vs. non-urban residence) and social isolation in a cohort of older drivers. Methods: The AAA LongROAD cohort with 2,989 older adult drivers from across the country were included. Social isolation was measured at baseline and at two subsequent annual follow-ups using PROMIS v2.0 Social Isolation 4a. The effect of geographic location with social isolation was assessed through with multivariable regression using a generalized estimating equation model. Results: The rate of social isolation in urban areas was 21% lower (adjusted RR 0.79, 95% CI 0.46, 1.36) compared to non-urban areas after adjusting for covariates, though not significant. Discussion: Social isolation is a predictor of poor health outcomes and geographic considerations have been lacking in the literature. The panel data in this analysis provides more evidence for causality though the under-representation of non-urban areas potentially reduces the power for the results. Conclusions: It is important to understand the needs and risk of social isolation in various geographic settings to ensure resources and interventions are appropriately modified for a greater public health impact.

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.

Using Naturalistic Driving Data to Predict Mild Cognitive Impairment and Dementia: Preliminary Findings from the Longitudinal Research on Aging Drivers (LongROAD) Study.

Emerging evidence suggests that atypical changes in driving behaviors may be early signals of mild cognitive impairment (MCI) and dementia. This study aims to assess the utility of naturalistic driving data and machine learning techniques in predicting incident MCI and dementia in older adults. Monthly driving data captured by in-vehicle recording devices for up to 45 months from 2977 participants of the Longitudinal Research on Aging Drivers study were processed to generate 29 variables measuring driving behaviors, space and performance. Incident MCI and dementia cases (n = 64) were ascertained from medical record reviews and annual interviews. Random forests were used to classify the participant MCI/dementia status during the follow-up. The F1 score of random forests in discriminating MCI/dementia status was 29% based on demographic characteristics (age, sex, race/ethnicity and education) only, 66% based on driving variables only, and 88% based on demographic characteristics and driving variables. Feature importance analysis revealed that age was most predictive of MCI and dementia, followed by the percentage of trips traveled within 15 miles of home, race/ethnicity, minutes per trip chain (i.e., length of trips starting and ending at home), minutes per trip, and number of hard braking events with deceleration rates ≥ 0.35 g. If validated, the algorithms developed in this study could provide a novel tool for early detection and management of MCI and dementia in older drivers.

Potentially Inappropriate Medication Use and Hard Braking Events in Older Drivers.

Potentially inappropriate medications (PIMs) identified by the American Geriatrics Society should generally be avoided by older adults because of ineffectiveness or excess risk of adverse effects. Few studies have examined the effects of PIMs on driving safety measured by prospectively and objectively collected driving data. Data for this study came from the Longitudinal Research on Aging Drivers study, a multisite naturalistic driving study of older adults. Multivariable negative binominal modeling was used to estimate incidence rate ratios and 95% confidence intervals of hard braking events (proxies for unsafe driving behavior defined as events with a deceleration rate ≥0.4 g) associated with PIM use among older drivers. The study sample consisted of 2932 drivers aged 65-79 years at baseline, including 542 (18.5%) who used at least one PIM. These drivers were followed through an in-vehicle recording device for up to 44 months. The overall incidence of hard braking events was 1.16 per 1000 miles. Use of PIMs was associated with a 10% increased risk of hard braking events. Compared to drivers who were not using PIMs, the risk of hard braking events increased 6% for those using one PIM, and 24% for those using two or more PIMs. Use of PIMs by older adult drivers is associated in a dose-response fashion with elevated risks of hard braking events. Reducing PIM use in older adults might help improve driving safety as well as health outcomes.

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.

Corrigendum to "Fall Risk Reduction Program Paired with a Transportation Program in an Underserved, Urban Minority Community: A Qualitative Evaluation".

[This corrects the article DOI: 10.1155/2019/2719290.].