Zhihui Lu1, Freddy M H Lam1,2, Jason C S Leung2, Timothy C Y Kwok1,2. 1. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, China. 2. Jockey Club Centre for Osteoporosis Care and Control, The Chinese University of Hong Kong, China.
Abstract
BACKGROUND: It remains uncertain whether the association between physical activity (PA) and falls is U-shaped, and few studies have explored the potential mediation of PA accumulation pattern. METHODS: We measured PA in 671 community-dwelling older adults (82.7 ± 3.8 years) using wrist-worn accelerometer for 7 days. PA was further classified to bouted PA (≥10 minutes bout length) and sporadic PA (<10 minutes bout length) for subanalysis. Fall incidence in the following 12-month was recorded through tri-monthly telephone interviews. Classification and Regression Tree analysis was used to identify two optimal cutoff values of each PA measurement to predict falls. Participants were then divided into "inactive," "moderately active," and "highly active" groups accordingly. Negative binomial regression models were used to estimate the association between the PA measures and fall incidence. RESULTS: Six hundred and thirty-nine participants completed 12-month follow-up. Ninety-three (14.6%) experienced a total of 118 falls. Inactive and highly active older adults had higher falls per person month relative to the moderately active group (inactive: incidence rate ratios [IRR] = 2.372, 95% confidence interval [CI] = 1.317-4.271; highly active: IRR = 2.731, 95% CI = 1.196-6.232). Subanalyses found similar significant finding with bouted PA (p < .001) but not sporadic PA (p ≥ .221). The association between bouted PA and falls remained significant even after adjusting fall incidence for bouted activity time (inactive: IRR = 3.636, 95% CI = 2.238-5.907; highly active: IRR = 1.823, 95% CI = 1.072-3.1). Further adjustments for fall-related risk factors did not meaningfully change the results. CONCLUSION: A U-shaped relationship was identified between bouted but not sporadic PA and fall incidence. There is an approximately twofold increase in fall rate in highly active older adults even after adjusting for activity time.
BACKGROUND: It remains uncertain whether the association between physical activity (PA) and falls is U-shaped, and few studies have explored the potential mediation of PA accumulation pattern. METHODS: We measured PA in 671 community-dwelling older adults (82.7 ± 3.8 years) using wrist-worn accelerometer for 7 days. PA was further classified to bouted PA (≥10 minutes bout length) and sporadic PA (<10 minutes bout length) for subanalysis. Fall incidence in the following 12-month was recorded through tri-monthly telephone interviews. Classification and Regression Tree analysis was used to identify two optimal cutoff values of each PA measurement to predict falls. Participants were then divided into "inactive," "moderately active," and "highly active" groups accordingly. Negative binomial regression models were used to estimate the association between the PA measures and fall incidence. RESULTS: Six hundred and thirty-nine participants completed 12-month follow-up. Ninety-three (14.6%) experienced a total of 118 falls. Inactive and highly active older adults had higher falls per person month relative to the moderately active group (inactive: incidence rate ratios [IRR] = 2.372, 95% confidence interval [CI] = 1.317-4.271; highly active: IRR = 2.731, 95% CI = 1.196-6.232). Subanalyses found similar significant finding with bouted PA (p < .001) but not sporadic PA (p ≥ .221). The association between bouted PA and falls remained significant even after adjusting fall incidence for bouted activity time (inactive: IRR = 3.636, 95% CI = 2.238-5.907; highly active: IRR = 1.823, 95% CI = 1.072-3.1). Further adjustments for fall-related risk factors did not meaningfully change the results. CONCLUSION: A U-shaped relationship was identified between bouted but not sporadic PA and fall incidence. There is an approximately twofold increase in fall rate in highly active older adults even after adjusting for activity time.
Authors: Wojtek J Chodzko-Zajko; David N Proctor; Maria A Fiatarone Singh; Christopher T Minson; Claudio R Nigg; George J Salem; James S Skinner Journal: Med Sci Sports Exerc Date: 2009-07 Impact factor: 5.411
Authors: Benjamin K S Chan; Lynn M Marshall; Kerri M Winters; Kimberly A Faulkner; Ann V Schwartz; Eric S Orwoll Journal: Am J Epidemiol Date: 2006-12-28 Impact factor: 4.897
Authors: Geoffrey J Hoffman; Jinkyung Ha; Neil B Alexander; Kenneth M Langa; Mary Tinetti; Lillian C Min Journal: J Am Geriatr Soc Date: 2018-04-17 Impact factor: 5.562
Authors: Annemarie Koster; Eric J Shiroma; Paolo Caserotti; Charles E Matthews; Kong Y Chen; Nancy W Glynn; Tamara B Harris Journal: Med Sci Sports Exerc Date: 2016-08 Impact factor: 5.411
Authors: Mona Abdo; Xingye Wu; Anjali Sharma; Katherine K Tassiopoulos; Todd T Brown; Susan L Koletar; Michael T Yin; Kristine M Erlandson Journal: AIDS Res Hum Retroviruses Date: 2022-02-02 Impact factor: 1.723