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The abundances of taxonomic groups were modelled with frailty as a predictor (Additional file 4: Table S4).
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To evaluate differences in standardized SF-36 scores between frailty groups, we used a multiple regression model with frailty variables.
In the majority of cases, the models without frailty estimated a smaller educational gradient than the models with frailty.
Each layer is modelled with an optimization model.
Why are we only fascinated with frailty?
All of our covariates were significantly associated with frailty when they were independently tested.
Several variables correlated strongly with frailty.
Mortality was positively associated with frailty.
Poor hearing was strongly associated with frailty, but not with pre-frailty status in our study.
Clinical OA is strongly associated with frailty and pre-frailty in older adults.
These loadings show how differently the frailty indicators correlate with frailty, compared to their specific factors.
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