In low-resource settings, there is a need to develop models that can address contributions of household and outdoor sources to population exposures. The aim of the study was to model indoor PM using household characteristics, activities, and outdoor sources. Households belonging to participants in the Mother and Child in the Environment (MACE) birth cohort, in Durban, South Africa, were randomly selected. A structured walk-through identified variables likely to generate PM . MiniVol samplers were used to monitor PM for a period of 24 hours, followed by a post-activity questionnaire. Factor analysis was used as a variable reduction tool. Levels of PM in the south were higher than in the north of the city (P < .05); crowding and dwelling type, household emissions (incense, candles, cooking), and household smoking practices were factors associated with an increase in PM levels (P < .05), while room magnitude and natural ventilation factors were associated with a decrease in the PM levels (P < .05). A reasonably robust PM predictive model was obtained with model R of 50%. Recognizing the challenges in characterizing exposure in environmental epidemiological studies, particularly in resource-constrained settings, modeling provides an opportunity to reasonably estimate indoor pollutant levels in unmeasured homes.
Background
Crude measures of exposure to indicate indoor air pollution have been associated with the increased risk for acquiring tuberculosis. Our study aimed to determine an association between childhood pulmonary tuberculosis (PTB) and exposure to indoor air pollution (IAP), based on crude exposure predictors and directly sampled and modelled pollutant concentrations.
Methods
In this case control study, children diagnosed with PTB were compared to children without PTB. Questionnaires about children’s health; and house characteristics and activities (including household air pollution) and secondhand smoke (SHS) exposure were administered to caregivers of participants. A subset of the participants’ homes was sampled for measurements of PM
10
over a 24-h period (
n
= 105), and NO
2
over a period of 2 to 3 weeks (
n
= 82). IAP concentrations of PM
10
and NO
2
were estimated in the remaining homes using predictive models. Logistic regression was used to look for association between IAP concentrations, crude measures of IAP, and PTB.
Results
Of the 234 participants, 107 were cases and 127 were controls. Pollutants concentrations (μg/m
3
) for were PM
10
median: 48 (range: 6.6–241) and NO
2
median: 16.7 (range: 4.5–55). Day-to-day variability within- household was large. In multivariate models adjusted for age, sex, socioeconomic status, TB contact and HIV status, the crude exposure measures of pollution viz. cooking fuel type (clean or dirty fuel) and SHS showed positive non-significant associations with PTB. Presence of dampness in the household was a significant risk factor for childhood TB acquisition with aOR of 2.4 (95% CI: 1.1–5.0). The crude exposure predictors of indoor air pollution are less influenced by day-to-day variability. No risk was observed between pollutant concentrations and PTB in children for PM
10
and NO
2
.
Conclusion
Our study suggests increased risk of childhood tuberculosis disease when children are exposed to SHS, dirty cooking fuel, and dampness in their homes. Yet, HIV status, age and TB contact are the most important risk factors of childhood PTB in this population.
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