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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.