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      Longitudinal Research on Aging Drivers (LongROAD): study design and methods

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          Abstract

          Background

          As an important indicator of mobility, driving confers a host of social and health benefits to older adults. Despite the importance of safe mobility as the population ages, longitudinal data are lacking about the natural history and determinants of driving safety in older adults.

          Methods

          The Longitudinal Research on Aging Drivers (LongROAD) project is a multisite prospective cohort study designed to generate empirical data for understanding the role of medical, behavioral, environmental and technological factors in driving safety during the process of aging.

          Results

          A total of 2990 active drivers aged 65–79 years at baseline have been recruited through primary care clinics or health care systems in five study sites located in California, Colorado, Maryland, Michigan, and New York. Consented participants were assessed at baseline with standardized research protocols and instruments, including vehicle inspection, functional performance tests, and “brown-bag review” of medications. The primary vehicle of each participant was instrumented with a small data collection device that records detailed driving data whenever the vehicle is operating and detects when a participant is driving. Annual follow-up is being conducted for up to three years with a telephone questionnaire at 12 and 36 months and in-person assessment at 24 months. Medical records are reviewed annually to collect information on clinical diagnoses and healthcare utilization. Driving records, including crashes and violations, are collected annually from state motor vehicle departments. Pilot testing was conducted on 56 volunteers during March–May 2015. Recruitment and enrollment were completed between July 2015 and March 2017.

          Conclusions

          Results of the LongROAD project will generate much-needed evidence for formulating public policy and developing intervention programs to maintain safe mobility while ensuring well-being for older adults.

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          Most cited references 72

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          Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability.

          Functional assessment is an important part of the evaluation of elderly persons. We conducted this study to determine whether objective measures of physical function can predict subsequent disability in older persons. This prospective cohort study included men and women 71 years of age or older who were living in the community, who reported no disability in the activities of daily living, and who reported that they were able to walk one-half mile (0.8 km) and climb stairs without assistance. The subjects completed a short battery of physical-performance tests and participated in a follow-up interview four years later. The tests included an assessment of standing balance, a timed 8-ft (2.4-m) walk at a normal pace, and a timed test of five repetitions of rising from a chair and sitting down. Among the 1122 subjects who were not disabled at base line and who participated in the four-year follow-up, lower scores on the base-line performance tests were associated with a statistically significant, graduated increase in the frequency of disability in the activities of daily living and mobility-related disability at follow-up. After adjustment for age, sex, and the presence of chronic disease, those with the lowest scores on the performance tests were 4.2 to 4.9 times as likely to have disability at four years as those with the highest performance scores, and those with intermediate performance scores were 1.6 to 1.8 times as likely to have disability. Among nondisabled older persons living in the community, objective measures of lower-extremity function were highly predictive of subsequent disability. Measures of physical performance may identify older persons with a preclinical stage of disability who may benefit from interventions to prevent the development of frank disability.
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            Causes and prevalence of visual impairment among adults in the United States.

            To estimate the cause-specific prevalence and distribution of blindness and low vision in the United States by age, race/ethnicity, and gender, and to estimate the change in these prevalence figures over the next 20 years. Summary prevalence estimates of blindness (both according to the US definition of < or =6/60 [< or =20/200] best-corrected visual acuity in the better-seeing eye and the World Health Organization standard of < 6/120 [< 20/400]) and low vision (< 6/12 [< 20/40] best-corrected vision in the better-seeing eye) were prepared separately for black, Hispanic, and white persons in 5-year age intervals starting at 40 years. The estimated prevalences were based on recent population-based studies in the United States, Australia, and Europe. These estimates were applied to 2000 US Census data, and to projected US population figures for 2020, to estimate the number of Americans with visual impairment. Cause-specific prevalences of blindness and low vision were also estimated for the different racial/ethnic groups. Based on demographics from the 2000 US Census, an estimated 937 000 (0.78%) Americans older than 40 years were blind (US definition). An additional 2.4 million Americans (1.98%) had low vision. The leading cause of blindness among white persons was age-related macular degeneration (54.4% of the cases), while among black persons, cataract and glaucoma accounted for more than 60% of blindness. Cataract was the leading cause of low vision, responsible for approximately 50% of bilateral vision worse than 6/12 (20/40) among white, black, and Hispanic persons. The number of blind persons in the US is projected to increase by 70% to 1.6 million by 2020, with a similar rise projected for low vision. Blindness or low vision affects approximately 1 in 28 Americans older than 40 years. The specific causes of visual impairment, and especially blindness, vary greatly by race/ethnicity. The prevalence of visual disabilities will increase markedly during the next 20 years, owing largely to the aging of the US population.
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              Prevalence of Dementia in the United States: The Aging, Demographics, and Memory Study

              Aim: To estimate the prevalence of Alzheimer’s disease (AD) and other dementias in the USA using a nationally representative sample. Methods: The Aging, Demographics, and Memory Study sample was composed of 856 individuals aged 71 years and older from the nationally representative Health and Retirement Study (HRS) who were evaluated for dementia using a comprehensive in-home assessment. An expert consensus panel used this information to assign a diagnosis of normal cognition, cognitive impairment but not demented, or dementia (and dementia subtype). Using sampling weights derived from the HRS, we estimated the national prevalence of dementia, AD and vascular dementia by age and gender. Results: The prevalence of dementia among individuals aged 71 and older was 13.9%, comprising about 3.4 million individuals in the USA in 2002. The corresponding values for AD were 9.7% and 2.4 million individuals. Dementia prevalence increased with age, from 5.0% of those aged 71–79 years to 37.4% of those aged 90 and older. Conclusions: Dementia prevalence estimates from this first nationally representative population-based study of dementia in the USA to include subjects from all regions of the country can provide essential information for effective planning for the impending healthcare needs of the large and increasing number of individuals at risk for dementia as our population ages.
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                Author and article information

                Contributors
                gl2240@cumc.columbia.edu
                Journal
                Inj Epidemiol
                Inj Epidemiol
                Injury Epidemiology
                Springer International Publishing (Cham )
                2197-1714
                1 August 2017
                1 August 2017
                December 2017
                : 4
                Affiliations
                [1 ]ISNI 0000000419368729, GRID grid.21729.3f, Department of Epidemiology, Mailman School of Public Health, , Columbia University, ; New York, NY USA
                [2 ]ISNI 0000000419368729, GRID grid.21729.3f, Department of Anesthesiology, College of Physicians and Surgeons, , Columbia University, ; New York, NY USA
                [3 ]ISNI 0000000086837370, GRID grid.214458.e, , University of Michigan Transportation Research Institute and the Center for Advancing Transportation Leadership and Safety (ATLAS Center), ; Ann Arbor, MI USA
                [4 ]ISNI 0000 0001 2248 1931, GRID grid.56362.34, , The Urban Institute, ; Washington, DC USA
                [5 ]GRID grid.414265.0, , Bassett Research Institute, ; Cooperstown, NY USA
                [6 ]ISNI 0000 0001 0703 675X, GRID grid.430503.1, Department of Emergency Medicine, School of Medicine, , University of Colorado Anschutz Medical Campus, ; Aurora, CO USA
                [7 ]ISNI 0000 0001 0703 675X, GRID grid.430503.1, Department of Epidemiology, Colorado School of Public Health, , University of Colorado Anschutz Medical Campus, ; Aurora, CO USA
                [8 ]ISNI 0000000086837370, GRID grid.214458.e, , Institute for Social Research, University of Michigan, ; Ann Arbor, MI USA
                [9 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Health, Behavior and Society, Bloomberg School of Public Health, , Johns Hopkins University, ; Baltimore, MD USA
                [10 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Medicine, School of Medicine, , Johns Hopkins University, ; Baltimore, MD USA
                [11 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Department of Family and Preventive Medicine, , University of California San Diego, ; La Jolla, CA USA
                [12 ]ISNI 0000 0004 1936 8753, GRID grid.137628.9, Division of Trauma, Emergency Surgery and Surgical Critical Care, , New York University School of Medicine, ; New York, NY USA
                [13 ]ISNI 0000000419368729, GRID grid.21729.3f, Department of Psychiatry, College of Physicians and Surgeons, , Columbia University, ; New York, NY USA
                [14 ]ISNI 0000000419368729, GRID grid.21729.3f, Department of Biostatistics, Mailman School of Public Health, , Columbia University, ; New York, NY USA
                [15 ]ISNI 0000 0001 2285 2675, GRID grid.239585.0, , Center for Injury Epidemiology and Prevention, Columbia University Medical Center, ; 722 West 168th Street, Room 524, New York, NY 10032 USA
                Article
                121
                10.1186/s40621-017-0121-z
                5537138
                28736796
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100003550, AAA Foundation for Traffic Safety;
                Categories
                Research Methods
                Custom metadata
                © The Author(s) 2017

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