Operationalisation and data analysis
Frailty, Multimorbidity, depressed
REGRESSION, APPENDIX
All frailty domains were operationalised as intrinsic capacity [Multimorbidity: Measured by the number of clinical conditions listed in the Frailty IndexMuscle strength: Measured by grip strength (standard normalised, stratified by gender)Cognitive capacity: measured by MoCA.Mood alterations: measured by the anxiety-depression screening question in the EQ-5D-5 levels, given a value 1 for the answer “I am not anxious or depressed” and 5 to “I am extremely anxious or depressed”Functional capacity, measured by the limitations to perform activities of daily living (ADL) listed in the Frailty IndexTo measure activities of daily living, we created a score based on 16 disability-based questions from the Frailty Index. To measure the number of clinical conditions, we considered 21 of the morbidity related questions in the frailty index. Both scores were calculated in the same way, by summing 1 for each deficit and dividing by the number of valid answers. Therefore, bigger numbers represent more clinical conditions and more limitations to perform activities of daily living. The list of questions and their classification is available at the Appendix 1. All metrics were measured at baseline and repeated at 6 and 12 months. Only individuals alive at 12 months were considered for the analysis.The primary purpose of the analysis was to systematically identify the relationship between multimorbidity, muscle strength, cognitive capacity, mood and functional capacity over time. To that end, the study will answer three questions: (1) Are the metrics correlated at a population level? The between-individuals metric correlation at baseline was assessed using the Pearson correlation coefficient. (2) Are the metrics predictive of changes at 12 months, at a population level? To answer this question, we fitted a separate Generalised Least Squares linear regression for each of the five metrics as independent predictor and for each of the four remaining metrics as dependent outcome (20 models in total). The Generalised Least Square method was chosen due to the breach of the equality of variance assumption (Levene test result of 21.8, Summary statistics are presented as means, standard deviation and proportions. To account for multiple tests at baseline, we considered a 99% confidence interval (