Juliana S Oliveira1, Catherine Sherrington2, Chris Rissel3, Dafna Merom4, James Wickham5, Stephen R Lord6, Judy M Simpson3, Anne Tiedemann2. 1. Institute for Musculoskeletal Health, The University of Sydney and Sydney Local Health District, Sydney, Australia; School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia. Electronic address: juliana.oliveira@sydney.edu.au. 2. Institute for Musculoskeletal Health, The University of Sydney and Sydney Local Health District, Sydney, Australia; School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia. 3. School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia. 4. School of Science and Health, Western Sydney University, Sydney, New South Wales, Australia. 5. School of Biomedical Sciences, Charles Sturt University, Orange, New South Wales, Australia. 6. Neuroscience Research Australia, University of New South Wales, Sydney, Australia.
Abstract
BACKGROUND: This statistical analysis plan details the Coaching for Healthy AGEing (CHAnGE) trial analysis methodology. OBJECTIVE: To investigate the effect of a combined physical activity and fall prevention program on physical activity and falls compared to a healthy eating among people aged 60 years and over. METHODS: The CHAnGE trial is a pragmatic parallel-group cluster-randomised controlled trial with allocation concealment and blinded assessors. Clusters are allocated to either (1) a physical activity and fall prevention intervention or (2) to a healthy eating intervention. The primary outcomes are: objectively measured physical activity at 12 months post-randomisation, and self-reported falls throughout the 12-month trial period. Secondary outcomes include the proportion of participants reporting a fall, the proportion of participants meeting the Australian physical activity guidelines, body mass index, eating habits, mobility goal attainment, mobility-related confidence, quality of life, fear of falling, risk-taking behaviour, mood, well-being, self-reported physical activity, disability, and use of health and community services. ANALYSIS: We will follow the intention-to-treat principle. All analysis will allow for cluster randomisation using a generalised estimating equation approach. The between-group difference in the number of falls per person-year will be analysed using negative binomial regression models. For the continuously scored primary and secondary outcome measures, linear regression models adjusted for corresponding baseline scores will assess the effect of group allocation. Analyses will take into account cluster randomisation and will be adjusted for baseline scores. A subgroup analysis will assess differential effects of the intervention by baseline physical activity levels and history of falls.
BACKGROUND: This statistical analysis plan details the Coaching for Healthy AGEing (CHAnGE) trial analysis methodology. OBJECTIVE: To investigate the effect of a combined physical activity and fall prevention program on physical activity and falls compared to a healthy eating among people aged 60 years and over. METHODS: The CHAnGE trial is a pragmatic parallel-group cluster-randomised controlled trial with allocation concealment and blinded assessors. Clusters are allocated to either (1) a physical activity and fall prevention intervention or (2) to a healthy eating intervention. The primary outcomes are: objectively measured physical activity at 12 months post-randomisation, and self-reported falls throughout the 12-month trial period. Secondary outcomes include the proportion of participants reporting a fall, the proportion of participants meeting the Australian physical activity guidelines, body mass index, eating habits, mobility goal attainment, mobility-related confidence, quality of life, fear of falling, risk-taking behaviour, mood, well-being, self-reported physical activity, disability, and use of health and community services. ANALYSIS: We will follow the intention-to-treat principle. All analysis will allow for cluster randomisation using a generalised estimating equation approach. The between-group difference in the number of falls per person-year will be analysed using negative binomial regression models. For the continuously scored primary and secondary outcome measures, linear regression models adjusted for corresponding baseline scores will assess the effect of group allocation. Analyses will take into account cluster randomisation and will be adjusted for baseline scores. A subgroup analysis will assess differential effects of the intervention by baseline physical activity levels and history of falls.
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