Slow Processing Speed Predicts Falls in Older Adults With a Falls History: 1-Year Prospective Cohort Study
| Autor: | Stephen R. Lord, Winnie Cheung, Kim Delbaere, Larry Dian, Wency Chan, Jennifer C. Davis, Karim M. Khan, Chun Liang Hsu, Teresa Liu-Ambrose, John R. Best |
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| Rok vydání: | 2017 |
| Předmět: |
Male
Gerontology Falls in older adults Emotional functioning Neuropsychological Tests Risk Assessment 03 medical and health sciences 0302 clinical medicine Humans Medicine Prospective Studies 030212 general & internal medicine Prospective cohort study Geriatric Assessment Aged Aged 80 and over British Columbia business.industry Incidence Incidence (epidemiology) Regression analysis Fall risk Regression Accidental Falls Female Geriatrics and Gerontology Epidemiologic data business 030217 neurology & neurosurgery |
| Zdroj: | Journal of the American Geriatrics Society. 65:916-923 |
| ISSN: | 0002-8614 |
| Popis: | Background/Objectives A previous fall is a strong predictor of future falls. Recent epidemiologic data suggest that deficits in processing speed predict future injurious falls. Our primary objective was to determine a parsimonious predictive model of future falls among older adults who experienced ≥1 fall in the past 12 months based on the following categories: counts of (1) total, (2) indoor, (3) outdoor or (4) non-injurious falls; (5) one mild or severe injury fall (yes vs no); (6) an injurious instead of a non-injurious fall; and (7) an outdoor instead of an indoor fall. Design 12-month prospective cohort study. Setting Vancouver Falls Prevention Clinic, Canada (www.fallsclinic.ca). Participants Two-hundred and eighty-eight community-dwelling older adults aged ≥70 years with a history of ≥1 fall resulting in medical attention in the previous 12 months. Measurements We employed principal component analysis to reduce the baseline predictor variables to a smaller set of five factors (i.e., processing speed, working memory, emotional functioning, physical functioning and body composition/fall risk profile). Second, we used the extracted five factors as predictors in regression models predicting the incidence of falls over a 12-month prospective observation period. We conducted regression analyses for the seven falls-related categories (defined above). Results Among older adults with a falls history, processing speed was the most consistent predictor of future falls; poorer processing speed predicted a greater number of total, indoor, outdoor, and non-injurious falls, and a greater likelihood of experiencing at least one mild or severe injurious fall (all P values |
| Databáze: | OpenAIRE |
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