Skip to main content

Table 6 Mediational effects of health measurements on the associations between ever WS exposure and all-cause mortality

From: Wood smoke exposure affects lung aging, quality of life, and all-cause mortality in New Mexican smokers

Potential mediator Ever WS exposurea Mediational effect size (%)b Ppermc
C (P = 0.0003) C' (all Ps < 0.005)
SGRQ score     
 Symptom 0.42 (0.12) 0.37 (0.12) 12.0 0.03
 Activity 0.42 (0.12) 0.35 (0.12) 17.0  < 0.005
 Impact 0.42 (0.12) 0.35 (0.12) 17.9  < 0.005
 Total 0.42 (0.12) 0.33 (0.12) 21.1  < 0.005
SF-36 score     
 Physical functioning 0.42 (0.12) 0.33 (0.12) 20.9  < 0.005
 Role physical 0.42 (0.12) 0.39 (0.12) 7.4 0.03
 Role emotional 0.42 (0.12) 0.40 (0.12) 4.1 0.03
 Social functioning 0.42 (0.12) 0.41 (0.12) 2.5 0.21
 Mental health 0.42 (0.12) 0.39 (0.12) 6.8 0.02
 Vitality 0.42 (0.12) 0.40 (0.12) 5.5 0.055
 General health perceptions 0.42 (0.12) 0.36 (0.12) 15.5  < 0.005
 Bodily pain 0.42 (0.12) 0.39 (0.12) 6.6 0.015
 Spirometry     
 FEV1 0.42 (0.12) 0.34 (0.12) 18.8  < 0.005
 FEV1/FVC ratio 0.42 (0.12) 0.38 (0.12) 10.2  < 0.005
  1. WS woodsmoke
  2. aCox proportional hazards model assessed the impact of WS exposure on all-cause mortality. Baseline values of age, smoking status, packyears, and annual income, education, sex, and ethnicity were included in Cox proportional hazards model for covariate adjustment. C was the estimate for WS exposure in model without individual potential mediators. C' was the estimate for WS exposure in model with individual potential mediators.
  3. bMediational effect size (%) was calculated as ([C–C'] × 100)/C
  4. cPperm was calculated using permutation based method. The relationship between survival data (survival time and censor status) and the vector of independent variables was permuted for 200 times. Each permutated database allowed the association analysis of all-cause mortality with ever WS exposure and other covariates without and with including individual potential mediators to calculate the C and C'. Permutation was conducted for 200 times to generate the distribution of C–C' under null hypothesis of no mediation. Value of C–C' calculated using observed data was compared to the distribution generated by permutation and Pperm was calculated as the number of permuted databases generating a C–C' that exceeded the observed value divided by 500