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Table 2 Association of risk factors with HRQoL score based on mixed-effects linear regression analysis

From: Lifestyle-related behaviors and health-related quality of life among children and adolescents in China

Lifestyle-related behavior Mean (SD) Univariable modeld Multivariable modele
Mean difference 95% CI P Mean difference 95% CI P
Physical activitya        
 Sufficient 0.82 (0.15) Ref    Ref   
 Insufficient 0.77 (0.18) − 0.04 − 0.07, − 0.01 < 0.001 − 0.03 − 0.04, − 0.01 < 0.001
Screen time        
 < 2 h/day 0.78 (0.17) Ref    Ref   
 ≥ 2 h/day 0.73 (0.19) − 0.05 − 0.09, − 0.01 0.010 − 0.04 − 0.070, − 0.02 0.002
Sleeping timeb        
 Sufficient 0.84 (0.16) Ref    Ref   
 Insufficient 0.77 (0.17) − 0.10 − 0.15, − 0.05 < 0.001 − 0.06 − 0.07, − 0.04 < 0.001
Sugar-sweetened beverage consumptionc        
 No 0.79 (0.17) Ref    Ref   
 Yes 0.76 (0.17) − 0.02 − 0.05, 0.01 0.119 − 0.02 − 0.03, − 0.01 < 0.001
Fast food consumptionc        
 No 0.79 (0.17) Ref    ref   
 Yes 0.76 (0.18) − 0.03 − 0.06, 0.001 0.060 − 0.03 − 0.04, − 0.02 < 0.001
  1. aSufficient physical activity refers to at least 60 min/day moderate-vigorous intensity physical activity plus ≥ 3 days muscle/bone-strengthening; while insufficient physical activity means less than 60 min/day moderate-vigorous intensity physical activity or having no ≥ 3 days muscle/bone-strengthening
  2. bSleeping time: sufficient sleeping time was defined as 10 h/day for children aged 7–13, 9 h/day for children aged 13–16, and 8 h/day for those aged 16–19, based on guidelines for promotion of children and adolescents’ physical activity and fitness by The State Council of China
  3. cFF and SSB consumption was classified as “no” or “yes” based on the weekly consumption frequency, separately
  4. dModel 1: univariate mixed-effects model with school class as the random effect
  5. eModel 2: multivariate mixed-effects linear regression analysis with adjustment for age, gender, school type, residence, parental educational attainment, body weight status and class-level clustering effects