Table 2 .
Results of the adjustment of longitudinal multilevel models for the trajectory of LSA in older adults at risk of sarcopenia (RS)
| Parameter | Model 1 | Model 2 | Model 3 | Model 4 | ||
|---|---|---|---|---|---|---|
| Fixed effects | ||||||
| Initial LSA, p0i | Intercept | γ00 | 30,71 (1,91)*** | 27,70 (1,899)*** | 26,36 (2,056)*** | 64,43 (6,25)*** |
| Sex (ref: men) | – | |||||
| Women | γ01 | − 19,78 (5,74)*** | ||||
| Age (ref: 60—69 years) | – | |||||
| (70–79 years) | γ02 | − 7,77 (3,67)* | ||||
| (80–89 years) | γ03 | − 14,08 (3,19)*** | ||||
| BOMFAQ (ref: none or mild) | – | |||||
| (moderate to severe) | γ04 | − 17,73 (5,40)** | ||||
| Total walk (ref: active) | – | |||||
| (inactive) | γ05 | − 12,01 (3,28)*** | ||||
| (insufficiently active) | γ06 | − 0,148 (3,21) | ||||
| Sex*BOMFAQ (men* none or mild) | – | |||||
| (women * moderate to severe) | γ07 | 13,32 (5,84)* | ||||
| LSA rate of change, p1i | Intercept | γ10 | 0,431 (0,122)*** | 3,020 (0,966)** | 2,50 (0,966)* | |
| Quadratic term, p2 | π2 | − 0,476 (0,161)** | − 0,419 (0,161)** | |||
| Cubic term, p3 | π3 | 0,020 (0,007)** | 0,018 (0,007)** | |||
| Variance components | ||||||
| Intra-individuals | σe2 | 273,59 | 127,41 | 120,86 | 114,52 | |
| Between individuals: in the initial LSA | σ02 | 157,93 | 234,86 | 238,63 | 87,248 | |
| Between individuals: at the rate of change | σ12 | 0,424 | 0,468 | 0,494 | ||
| Fit quality statistics | ||||||
| AIC | 2901,7 | 2882 | 2877 | 2808 | ||
| BIC | 2913,2 | 2905 | 2908 | 2865 | ||
| TRV (model a, Model a-1) | – | 25,64*** | 9,07* | 83,15*** |
These models predict the LSA between baseline and the fourth survey wave (0–16 months) as a function of time (level 1) and covariates (level 2). BOMFAQ Brazilian OARS Multidimensional Functional Assessment Questionnaire; score of four points or more refers to the presence of moderate to severe functional limitation; LSA Life-Space Assessment; AIC Akaike Information Criterion. BIC Bayesian Information Criterion. LRT Likelihood Ratio Test
Obs.: Run in NLME package of Software R, estimator = ML
~ p < 0,10; * p < 0,05; ** p < 0,01; *** p < 0,001