Crystal Guo, Kristine E Ensrud, Jane A Cauley, Eric S Orwoll, Peggy M Cawthon
{"title":"老年男性的跌倒轨迹:不同年龄段的变化轨迹和未来跌倒风险的预测因素。","authors":"Crystal Guo, Kristine E Ensrud, Jane A Cauley, Eric S Orwoll, Peggy M Cawthon","doi":"10.1093/gerona/glae217","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Very little is known about specific trajectories or patterns of falls over time. Using the well-characterized cohort of the Osteoporotic Fractures in Men Study (MrOS), we classified individuals by fall trajectories across age and identified predictors of group assignment based on characteristics at baseline.</p><p><strong>Methods: </strong>Using an analysis sample of 5 976 MrOS participants and 15 years of follow-up data on incident falls, we used group-based trajectory models (PROC TRAJ in SAS) to identify trajectories of change. We assessed the association of baseline characteristics with group assignment using 1-way analysis of variance and chi-square tests. Multivariable logistic regression was used to analyze the outcome of the high-risk fall trajectory groups compared to the low-risk groups.</p><p><strong>Results: </strong>Changes in rates of falls were relatively constant or increasing with 5 distinct groups identified. Mean posterior probabilities for all 5 trajectories were similar and consistently above 0.8 indicating a reasonable model fit. Among the 5 fall trajectory groups, 2 were deemed high risk, those with steeply increasing fall risk and persistently high fall risk. Factors associated with fall risk included body mass index, use of central nervous agents, prior history of diabetes and Parkinson's disease, back pain, grip strength, and physical and mental health scores.</p><p><strong>Conclusions: </strong>Two distinct groups of high fall risk individuals were identified among 5 trajectory groups, those with steeply increasing fall risk and persistently high fall risk. Statistically significant characteristics for group assignment suggest that future fall risk of older men may be predictable at baseline.</p>","PeriodicalId":94243,"journal":{"name":"The journals of gerontology. Series A, Biological sciences and medical sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11512026/pdf/","citationCount":"0","resultStr":"{\"title\":\"Fall Trajectories in Older Men: Trajectories of Change by Age and Predictors for Future Fall Risk.\",\"authors\":\"Crystal Guo, Kristine E Ensrud, Jane A Cauley, Eric S Orwoll, Peggy M Cawthon\",\"doi\":\"10.1093/gerona/glae217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Very little is known about specific trajectories or patterns of falls over time. Using the well-characterized cohort of the Osteoporotic Fractures in Men Study (MrOS), we classified individuals by fall trajectories across age and identified predictors of group assignment based on characteristics at baseline.</p><p><strong>Methods: </strong>Using an analysis sample of 5 976 MrOS participants and 15 years of follow-up data on incident falls, we used group-based trajectory models (PROC TRAJ in SAS) to identify trajectories of change. We assessed the association of baseline characteristics with group assignment using 1-way analysis of variance and chi-square tests. Multivariable logistic regression was used to analyze the outcome of the high-risk fall trajectory groups compared to the low-risk groups.</p><p><strong>Results: </strong>Changes in rates of falls were relatively constant or increasing with 5 distinct groups identified. Mean posterior probabilities for all 5 trajectories were similar and consistently above 0.8 indicating a reasonable model fit. Among the 5 fall trajectory groups, 2 were deemed high risk, those with steeply increasing fall risk and persistently high fall risk. Factors associated with fall risk included body mass index, use of central nervous agents, prior history of diabetes and Parkinson's disease, back pain, grip strength, and physical and mental health scores.</p><p><strong>Conclusions: </strong>Two distinct groups of high fall risk individuals were identified among 5 trajectory groups, those with steeply increasing fall risk and persistently high fall risk. Statistically significant characteristics for group assignment suggest that future fall risk of older men may be predictable at baseline.</p>\",\"PeriodicalId\":94243,\"journal\":{\"name\":\"The journals of gerontology. 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Fall Trajectories in Older Men: Trajectories of Change by Age and Predictors for Future Fall Risk.
Background: Very little is known about specific trajectories or patterns of falls over time. Using the well-characterized cohort of the Osteoporotic Fractures in Men Study (MrOS), we classified individuals by fall trajectories across age and identified predictors of group assignment based on characteristics at baseline.
Methods: Using an analysis sample of 5 976 MrOS participants and 15 years of follow-up data on incident falls, we used group-based trajectory models (PROC TRAJ in SAS) to identify trajectories of change. We assessed the association of baseline characteristics with group assignment using 1-way analysis of variance and chi-square tests. Multivariable logistic regression was used to analyze the outcome of the high-risk fall trajectory groups compared to the low-risk groups.
Results: Changes in rates of falls were relatively constant or increasing with 5 distinct groups identified. Mean posterior probabilities for all 5 trajectories were similar and consistently above 0.8 indicating a reasonable model fit. Among the 5 fall trajectory groups, 2 were deemed high risk, those with steeply increasing fall risk and persistently high fall risk. Factors associated with fall risk included body mass index, use of central nervous agents, prior history of diabetes and Parkinson's disease, back pain, grip strength, and physical and mental health scores.
Conclusions: Two distinct groups of high fall risk individuals were identified among 5 trajectory groups, those with steeply increasing fall risk and persistently high fall risk. Statistically significant characteristics for group assignment suggest that future fall risk of older men may be predictable at baseline.