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Table 3 Results of linear mixed regression models predicting the frailty index (FI) from difference-based methylation age acceleration

From: Frailty is associated with the epigenetic clock but not with telomere length in a German cohort

Covariables

Dataset 1

Dataset 2

Overall

p a

None

−0.023 (−0.208, 0.162)

0.087 (−0.107, 0.281)

0.039 (−0.092, 0.170)

0.56

Age

0.167 (−0.019, 0.353)

0.214 ( 0.021, 0.407)

0.183 ( 0.053, 0.313)

0.0059

Age, sex

0.183 (−0.005, 0.371)

0.242 ( 0.046, 0.439)

0.201 ( 0.069, 0.333)

0.0028

Age, sex, leukocyte distribution (LD)

0.250 ( 0.047, 0.453)

0.274 ( 0.068, 0.481)

0.255 ( 0.115, 0.396)

0.0004

Age, sex, LD, smoking

0.243 (0.038, 0.448)

0.282 (0.074, 0.491)

0.256 (0.113, 0.398)

0.0004

Age, sex, LD, alcohol

0.289 (0.080, 0.497)

0.280 (0.070, 0.490)

0.277 (0.133, 0.421)

0.0002

Age, sex, LD, history of cancer

0.234 (0.030, 0.437)

0.275 (0.067, 0.484)

0.250 (0.108, 0.391)

0.0006

Age, sex, LD, interaction (age accel. with sex)

 Estimate in females

0.304 ( 0.036, 0.572)

0.246 (−0.026, 0.519)

0.269 (0.082, 0.455)

0.0048

 Estimate in males

0.190 (−0.089, 0.469)

0.307 ( 0.013, 0.601)

0.241 (0.046, 0.436)

0.016

  1. Shown is the estimated change (95 % confidence interval) in FI (expressed in %) per year of age acceleration. All models are adjusted for the methylation array batch using a random effect
  2. a p values refer to t distribution tests of the estimates obtained by multiple imputation in the overall model