Adverse driving behaviors are associated with sleep apnea severity and age in cognitively normal older adults at risk for Alzheimer's disease

Driving among individuals with chronic conditions: A systematic review of applied research using kinematic driving sensors

BACKGROUND

Kinematic driving data studies are a novel methodology relevant to health care, but prior studies have considerable variance in their methods, populations, and findings suggesting a need for critical analysis and appraisal for feasibility and methodological guidelines.

METHODS

We assessed kinematic driving studies of adults with chronic conditions for study feasibility, characteristics, and key findings, to generate recommendations for future study designs, and to identify promising directions for applications of kinematic driving data. PRISMA was used to guide the review and searches included PubMed, CINAHL, and Compendex. Of 379 abstract/titles screened, 49 full-text articles were reviewed, and 29 articles met inclusion criteria of analyzing trip-level kinematic driving data from adult drivers with chronic conditions.

RESULTS

The predominant chronic conditions studied were Alzheimer's disease and related Dementias, obstructive sleep apnea, and diabetes mellitus. Study objectives included feasibility testing of kinematic driving data collection in the context of chronic conditions, comparisons of simulation with real-world kinematic driving behavior, assessments of driving behavior effects associated with chronic conditions, and prognostication or disease classification drawn from kinematic driving data. Across the studies, there was no consensus on devices, measures, or sampling parameters; however, studies showed evidence that driving behavior could reliably differentiate between adults with chronic conditions and healthy controls.

CONCLUSIONS

Vehicle sensors can provide driver-specific measures relevant to clinical assessment and interventions. Using kinematic driving data to assess and address driving measures of individuals with multiple chronic conditions is positioned to amplify a functional outcome measure that matters to patients.

Global rural health disparities in Alzheimer's disease and related dementias: State of the science

INTRODUCTION

Individuals living in rural communities are at heightened risk for Alzheimer's disease and related dementias (ADRD), which parallels other persistent place-based health disparities. Identifying multiple potentially modifiable risk factors specific to rural areas that contribute to ADRD is an essential first step in understanding the complex interplay between various barriers and facilitators.

METHODS

An interdisciplinary, international group of ADRD researchers convened to address the overarching question of: "What can be done to begin minimizing the rural health disparities that contribute uniquely to ADRD?" In this state of the science appraisal, we explore what is known about the biological, behavioral, sociocultural, and environmental influences on ADRD disparities in rural settings.

RESULTS

A range of individual, interpersonal, and community factors were identified, including strengths of rural residents in facilitating healthy aging lifestyle interventions.

DISCUSSION

A location dynamics model and ADRD-focused future directions are offered for guiding rural practitioners, researchers, and policymakers in mitigating rural disparities.

HIGHLIGHTS

Rural residents face heightened Alzheimer's disease and related dementia (ADRD) risks and burdens due to health disparities. Defining the unique rural barriers and facilitators to cognitive health yields insight. The strengths and resilience of rural residents can mitigate ADRD-related challenges. A novel "location dynamics" model guides assessment of rural-specific ADRD issues.

Review of Risk Factors Associated With Biomarkers for Alzheimer Disease

ABSTRACT

BACKGROUND: Alzheimer disease (AD) is a neurodegenerative disease with no cure. The number of individuals living with AD doubles every 5 years. The current clinical practice relies on clinical history, mental status tests, cerebrum imaging, and physical and neurological examinations; however, recent advances in the field of biomarkers have provided clues for the early detection of AD. High levels of tau and low levels of amyloid-β (Aβ) in cerebrospinal fluid are well-known biomarkers for AD. METHODS: A database search of PubMed, Ovid MEDLINE, and CINAHL was conducted to identify relevant articles published within the last 5 years. The search was limited to articles concerning adults 65 years or older and published in the English language. Twelve articles were included in the review. RESULTS: Risk factors of sleep disruption, depression, and motor function are implicated. Cerebrospinal fluid parameters for biomarkers of tau and Aβ were universally lower among Blacks compared with Whites, raising concern that norm reference may not be accurate for all populations. Older adults are more at risk for AD. Results are inconclusive regarding whether depression is related to Aβ and tau pathology. CONCLUSION: Nurses should screen for sleep architecture, depression, and motor function in their patients and educate them on good sleep hygiene. Sleep studies should be advocated for people with suspected sleep apnea to mitigate the risk factor related to abnormal Aβ and tau pathology. Falls and decreased motor function require screening because they may be early indicators of abnormal biomarkers leading to AD.

Adverse driving behaviors increase over time as a function of preclinical Alzheimer's disease biomarkers

INTRODUCTION

We investigated the relationship between preclinical Alzheimer's disease (AD) biomarkers and adverse driving behaviors in a longitudinal analysis of naturalistic driving data.

METHODS

Naturalistic driving data collected using in-vehicle dataloggers from 137 community-dwelling older adults (65+) were used to model driving behavior over time. Cerebrospinal fluid (CSF) biomarkers were used to identify individuals with preclinical AD. Additionally, hippocampal volume and cognitive biomarkers for AD were investigated in exploratory analyses.

RESULTS

CSF biomarkers predicted the longitudinal trajectory of the incidence of adverse driving behavior. Abnormal amyloid beta (Aβ42 /Aβ40 ) ratio was associated with an increase in adverse driving behaviors over time compared to ratios in the normal/lower range.

DISCUSSION

Preclinical AD is associated with increased adverse driving behavior over time that cannot be explained by cognitive changes. Driving behavior as a functional, neurobehavioral marker may serve as an early detection for decline in preclinical AD. Screening may also help prolong safe driving as older drivers age.

Predictors of Driving Cessation in Older Adults: A 12-year Population-based Study

BACKGROUND

Changes in physical health and cognition during aging can result in some older adults to stop driving. In this population-based longitudinal study, we describe potential predictors of driving cessation in older adults.

METHODS

Age-stratified random population cohort of 1982 adults aged 65 years and older drawn from voter registration lists. Participant characteristics were measured using demographics, physical and self-rated health, sleeping habits, driving status, cognitive screening, modified Center for Epidemiologic Studies-Depression scale, clinical dementia rating, and mini-mental state examination.

RESULTS

Over 12 years of follow-up, 390 participants stopped driving. These individuals were older, more likely to be women and to have a clinical dementia rating score ≥1, had worse self-reported health, and more symptoms of depression, compared with those who were still driving. In addition, individuals with lower test performance in all cognitive domains, loss of visual acuity and fields, and bilateral hearing loss were more likely to stop driving.

CONCLUSIONS

Age, sex, cognitive impairments, physical health, and depressive symptoms were associated with driving cessation in this cohort. By identifying potential driving cessation predictors, health care providers and families may better recognize these risk factors and begin the driving cessation discussion early.

Epidemiology, Physiology and Clinical Approach to Sleepiness at the Wheel in OSA Patients: A Narrative Review

Sleepiness at the wheel (SW) is recognized as an important factor contributing to road traffic accidents, since up to 30 percent of fatal accidents have been attributed to SW. Sleepiness-related motor vehicle accidents may occur both from falling asleep while driving and from behavior impairment attributable to sleepiness. SW can be caused by various sleep disorders but also by behavioral factors such as sleep deprivation, shift work and non-restorative sleep, as well as chronic disease or the treatment with drugs that negatively affect the level of vigilance. An association between obstructive sleep apnea (OSA) and motor vehicle accidents has been found, with an increasing risk in OSA patients up to sevenfold in comparison to the general population. Regular treatment with continuous positive airway pressure (CPAP) relieves excessive daytime sleepiness and reduces the crash risk. Open questions still remain about the physiological and clinical determinants of SW in OSA patients: the severity of OSA in terms of the frequency of respiratory events (apnea hypopnea index, AHI) or hypoxic load, the severity of daytime sleepiness, concomitant chronic sleep deprivation, comorbidities, the presence of depressive symptoms or chronic fatigue. Herein, we provide a review addressing the epidemiological, physiological and clinical aspects of SW, with a particular focus on the methods to recognize those patients at risk of SW.