Refining the particulate matter airway deposition arising from indoor cooking-related biomass combustion for children in the Haramaya district in Ethiopia

Sammanfattning: Background: Air pollution, a global issue affecting millions of individuals, is linked to adverse health effects on the respiratory system, but also to e.g., cancer and cardiovascular ailments. In low-income countries, cooking is often conducted by biomass-combustion, causing women and children to be exposed to high levels of indoor air pollution. Method: A mathematical model has been developed in MATLAB to estimate the mass of particulate matter deposited in the respiratory tract, to study correlations between lung deposition of indoor air pollution and respiratory symptoms of children aged less than 5 years old in a cohort of Ethiopian individuals (using STATA), with the input variables time spent cooking and fuel type usage (in this case, wood, charcoal, and animal dung). Result: The model was able to portray a higher estimated deposition for individuals using more polluting biomass practices, where cow dung had the highest estimated deposited particulate matter mass and deposited particle number, while charcoal had the lowest, showing statistical significance. A statistically significant decrease in risk for respiratory symptoms were noticed for the children for higher mass deposition values, with an Odds ratio (OR) of < 1 for both the entire and alveolar respiratory tract. The result remained valid in multivariate analysis with similar OR and p-value, where a statistically significant confounder being smokers in the household as well as usage of animal dung as fuel compared to wood, both with an OR > 1, p-value < 0.05. Conclusion: The model presented in this report can produce mass and number estimates for particulate matter deposition, enabling estimates using few input variables, allowing for new analysis methods in low-income settings, showing differences in estimates depending on fuel type usage. However, it needs further development, likely focused on identifying more confounders, but also more in-data in the form of size distributions from more combustion events.