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Table 3 Linear regression analysis for PSIQ score and methylation age acceleration between good and poor sleepers

From: The association between sleep quality and accelerated epigenetic aging with metabolic syndrome in Korean adults

Age accelerators

Good sleepers (N = 441)

Poor sleepers (N = 251)

êžµ

SE

p-value

êžµ

SE

p-value

Model 1

 HorvathAgeAccel

 − 0.098

0.122

0.422

0.085

0.083

0.307

 HannumAgeAccl

 − 0.126

0.107

0.238

0.137

0.077

0.079

 GrimAgeAccel

0.111

0.110

0.315

0.179

0.076

1.94 \(\times {10}^{-2}\)

 PhenoAgeAccel

0.016

0.151

0.918

0.114

0.106

0.285

 DunedinPACE

 − 0.002

0.003

0.533

0.006

0.002

5.54 \(\times {10}^{-3}\)

Model 2

 HorvathAgeAccel

0.082

0.107

0.446

0.071

0.085

0.402

 HannumAgeAccl

 − 0.118

0.108

0.273

0.100

0.076

0.188

 GrimAgeAccel

0.078

0.099

0.430

0.167

0.066

1.16 \(\times {10}^{-2}\)

 PhenoAgeAccel

0.022

0.154

0.887

0.082

0.107

0.446

 DunedinPACE

 − 0.001

0.003

0.960

0.004

0.002

3.63 \(\times {10}^{-2}\)

  1. Model 1 presents the results from linear regression model analysis of PSQI on methylation age accelerator (dependent variables) adjusted for sex. We additionally adjusted for chronological age, smoking status, drinking status, and BMI (Model2)
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Clinical Epigenetics

ISSN: 1868-7083

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