Slow Processing Speed Predicts Falls in Older Adults With a Falls History: 1‐Year Prospective Cohort Study. Issue 5 (8th April 2017)

• Record Type: Journal Article
• Authors: Davis, Jennifer C.; Best, John R.; Khan, Karim M.; Dian, Larry; Lord, Stephen; Delbaere, Kim; Hsu, Chun Liang; Cheung, Winnie; Chan, Wency; Liu‐Ambrose, Teresa
• Is Part Of: Journal of the American Geriatrics Society. Volume 65:Issue 5(2017:May)
• Page Start: 916
• Page End: 923
• Publication Date: 2017-04-08
• Subjects: falls -- older adults -- indoor fall -- outdoor fall -- injurious fall; Geriatrics -- Periodicals; 618.97
• DOI: 10.1111/jgs.14830
• Languages: English
• ISSNs: 0002-8614

Abstract

Abstract : 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 < .01). Conclusion: Poorer performance on the processing speed factor, a trainable factor, was independently associated with the most costly type of falls–injurious falls.