| 1. |
- Jafta, N., et al.
(författare)
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Association of childhood pulmonary tuberculosis with exposure to indoor air pollution: a case control study
- 2019
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Ingår i: BMC Public Health. - : Springer Science and Business Media LLC. - 1471-2458. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundCrude 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.MethodsIn 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 PM10 over a 24-h period (n=105), and NO2 over a period of 2 to 3weeks (n=82). IAP concentrations of PM10 and NO2 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.ResultsOf the 234 participants, 107 were cases and 127 were controls. Pollutants concentrations (g/m(3)) for were PM10 median: 48 (range: 6.6-241) and NO2 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 PM10 and NO2.ConclusionOur 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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| 2. |
- Jafta, N., et al.
(författare)
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Childhood tuberculosis and exposure to indoor air pollution: a systematic review and meta-analysis
- 2015
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Ingår i: International Journal of Tuberculosis and Lung Disease. - : International Union Against Tuberculosis and Lung Disease. - 1027-3719 .- 1815-7920. ; 19:5, s. 596-602
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Indoor air pollution (IAP) from environmental tobacco smoke (ETS) and biomass fuel smoke (BMS) poses respiratory health risks, with children and women bearing the major burden. OBJECTIVES: We used a systematic review and meta-analysis to investigate the relation between childhood tuberculosis (TB) and exposure to ETS and BMS. METHODS: We searched three databases for epidemiological studies that investigated the association of childhood TB with exposure to ETS and BMS. We calculated pooled estimates and heterogeneity for studies eligible for inclusion in the meta-analysis and stratified studies on ETS by outcome. RESULTS: Five case-control and three cross-sectional studies were eligible for inclusion in the meta-analysis and quality assessment. Pooled effect estimates showed that exposure to ETS is associated with tuberculous infection and TB disease (OR 1.9, 95%CI 1.4-2.9) among exposed compared to non-exposed children. TB disease in ETS studies produced a pooled OR of 2.8 (95%CI 0.9-4.8), which was higher than the OR for tuberculous infection (OR 1.9, 95%CI 0.9-2.9) for children exposed to ETS compared to non-exposed children. Studies on BMS exposure were too few and too small to permit a conclusion. CONCLUSION: Exposure to ETS increases the risk of childhood TB disease or tuberculous infection.
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| 3. |
- Jafta, N., et al.
(författare)
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Indoor air quality of low and middle income urban households in Durban, South Africa
- 2017
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Ingår i: Environmental Research. - : Elsevier BV. - 0013-9351. ; 156, s. 47-56
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Elevated levels of indoor air pollutants may cause cardiopulmonary disease such as lower respiratory infection, chronic obstructive lung disease and lung cancer, but the association with tuberculosis (TB) is unclear. So far the risk estimates of TB infection or/and disease due to indoor air pollution (IAP) exposure are based on self-reported exposures rather than direct measurements of IAP, and these exposures have not been validated. Objective: The aim of this paper was to characterize and develop predictive models for concentrations of three air pollutants (PM10, NO2 and SO2) in homes of children participating in a childhood TB study. Methods: Children younger than 15 years living within the eThekwini Municipality in South Africa were recruited for a childhood TB case control study. The homes of these children (n=246) were assessed using a walkthrough checklist, and in 114 of them monitoring of three indoor pollutants was also performed (sampling period: 24 h for PM10, and 2-3 weeks for NO2 and SO2). Linear regression models were used to predict PM10 and NO2 concentrations from household characteristics, and these models were validated using leave out one cross validation (LOOCV). SO2 concentrations were not modeled as concentrations were very low. Results: Mean indoor concentrations of PM10 (n=105), NO2 (n=82) and SO2 (n=82) were 64 mu g/m(3) (range 6.6-241); 19 mu g/m(3) (range 4.5-55) and 0.6 mu g/m(3) (range 0.005-3.4) respectively with the distributions for all three pollutants being skewed to the right. Spearman correlations showed weak positive correlations between the three pollutants. The largest contributors to the PM10 predictive model were type of housing structure (formal or informal), number of smokers in the household, and type of primary fuel used in the household. The NO2 predictive model was influenced mostly by the primary fuel type and by distance from the major roadway. The coefficients of determination (R-2) for the models were 0.41 for PM10 and 0.31 for NO2. Spearman correlations were significant between measured vs. predicted PM10 and NO2 with coefficients of 0.66 and 0.55 respectively. Conclusion: Indoor PM10 levels were relatively high in these households. Both PM10 and NO2 can be modeled with a reasonable validity and these predictive models can decrease the necessary number of direct measurements that are expensive and time consuming.
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| 4. |
- Shezi, Busisiwe, et al.
(författare)
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Predictors of urban household variability of indoor PM2.5 in low socio-economic communities.
- 2020
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Ingår i: Environmental science. Processes & impacts. - : Royal Society of Chemistry (RSC). - 2050-7895 .- 2050-7887. ; 22, s. 1423-1433
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Tidskriftsartikel (refereegranskat)abstract
- In epidemiological studies, levels of PM2.5 need to be estimated over time and space. Because of logistical constraints, very few studies have been conducted to assess the variability within and across homes and the predictors of this variability. This study evaluated within- and between-home variability of indoor PM2.5 and identified predictors for PM2.5 in homes of mothers participating in the urban Mother and Child in the Environment birth cohort study in Durban, South Africa. Thirty homes were selected from 300 homes that were previously sampled for PM2.5. Two measurements of PM2.5 levels were conducted in each home within a 1 week interval in both warm and cold seasons (four samplings per home) using Airmetrics MiniVol samplers. A linear mixed-effect model was used to evaluate within- and between-home variability and to identify fixed effects (predictors) that result in reduced variability. The PM2.5 levels in the 30 homes ranged from 2 to 303 μg m-3. The within-home variability accounted for 94% of the total variability in the log-transformed PM2.5 levels for the 30 homes. The fixed effects extracted from the repeated samplings in the present study were used to improve a previously developed multivariable linear regression model for 300 homes, and thereby increased the R2 from 0.50 to 0.54. Inclusion of fixed-effects in multivariable linear regression models resulted in a reasonably robust model that can be used to predict PM2.5 levels in unmeasured homes of the cohort.
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