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Table 3 Standardized estimations of the conditional LGM analysis

From: Modeling the change trajectory of sleep duration and its associated factors: based on an 11-year longitudinal survey in China

 

β

CI (95%)

S.E.

p

 

lower

upper

Time-invariant covariates

 Sex → I

0.134*

0.019

0.249

0.059

0.023

 Sex → S

−0.265***

−0.423

− 0.108

0.080

0.001

 Residence → I

0.002*

0.000

0.004

0.001

0.020

 Residence → S

−0.003**

− 0.006

−0.001

0.001

0.005

 Age(T1) → I

−0.218***

−0.314

− 0.123

0.049

0.000

 Age(T1) → S

0.161*

0.037

0.285

0.063

0.011

 BMI (T1) → I

0.000***

0.000

0.001

0.000

0.000

 BMI (T1) → S

0.000

−0.001

0.000

0.000

0.145

 Chronic disease → I

0.001

0.000

0.001

0.000

0.182

 Chronic disease → S

0.000

−0.001

0.001

0.000

0.372

Time-varying covariates

 Smoking → sleep duration

0.001***

0.001

0.001

0.000

0.000

 Alcohol-drinking → sleep duration

0.001***

0.000

0.001

0.000

0.000

  1. β, standardized regression coefficient; I, intercept factor indicating the initial level; S, slope factor indicating the change rate. CI, centered interval; S.E., standard error
  2. Time-varying covariate effects were set to be stable at different waves
  3. *, p < 0.05; **, p < 0.01; ***, p < 0.001