Statistical modelling of effects on health linked to indoor air pollution, based on kitchen exposure and with reference to a cross-sectional household survey conducted in Nepal

Exposure to suspended particulate matter and carbon monoxide from indoor kitchen air can have significant effects on respiratory health as demonstrated by statistical modelling. Chronic respiratory illnesses and respiratory symptoms are modelled using the techniques of principal component analysis and binary logistic regression. Estimated models are generated from a cross-sectional household survey data conducted in Nepal with 168 respondents who cook for daily meals. The models show that individuals exposed to high levels of indoor air pollution particularly associated with unprocessed solid biomass fuels along with aging, tobacco smoking and living in poorly constructed houses mainly with mud are vulnerable to respiratory disorders.