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Table 2 Coefficients for predictor variables from the log linear regression model (Equation 1) relating 24 hr kitchen area PM 2.5 concentrations with household variables

From: State and national household concentrations of PM2.5 from solid cookfuel use: Results from measurements and modeling in India for estimation of the global burden of disease

Parameters Estimate Std. Error P-value
Intercept -1.653 0.25008 0.000
Fuel: kerosene vs. LPG 0.194 0.17529 0.269
Fuel: dung vs. LPG 1.260 0.17166 0.000
Fuel: wood vs. LPG 0.969 0.11319 0.000
Kitchen: SOK vs. ODK -0.389 0.1579 0.014
Kitchen: IWPK vs. ODK -0.594 0.17807 0.001
Kitchen: IWOPK vs. ODK -0.262 0.18316 0.153
Ventilation: moderate vs. good -0.082 0.11155 0.461
Ventilation: poor vs. good -0.391 0.12616 0.002
Region: east vs. north -0.106 0.14243 0.457
Region: west vs. north -0.071 0.12362 0.565
Region: south vs. north -0.679 0.14001 0.000
Cooking hrs. 0.084 0.02181 0.000
  1. Note: Predictor variables were used in Equation 1 as follows E { log P M 2.5 } = β 0 + β F 1 I Fuel = Kerosene + β F 2 I ( Fuel = Dung ) + β F 3 I ( Fuel = Wood ) + β K 1 I Kit = SOK + β K 2 I ( Kit = IWPK ) + β K 3 I ( Kit = IWOPK ) + β V 1 I Vent = Moderate + β V 2 I ( Vent = Poor ) + β CH ( Cooking hours ) + β R 1 I Reg = East + β R 2 I ( Reg = West ) + β R 3 I ( Reg = South ) (1)
  2. SOK Separate outdoor kitchen, IWPK Indoor kitchen with partitions, IWOPK Indoor kitchens without partitions, Vent ventilation, Reg region. Reference categories included LPG for fuel, outdoor cooking for kitchen, good for ventilation and South for region.