Assessing the association between air pollution and child development in São Paulo, Brazil.

BACKGROUND: Outdoor air pollution is increasingly recognised as a key threat to population health globally, with particularly high risks for urban residents. In this study, we assessed the association between residential nitrogen dioxide (NO2) exposure and children's cognitive and behavioural development using data from São Paulo Brazil, one of the largest urban agglomerations in the world. METHODS: We used data from the São Paulo Western Region Birth Cohort, a longitudinal cohort study aiming to examine determinants as well as long-term implications of early childhood development. Cross-sectional data from the 72-month follow-up was analysed. Data on NO2 concentration in the study area was collected at 80 locations in 2019, and land use regression modelling was used to estimate annual NO2 concentration at children's homes. Associations between predicted NO2 exposure and children's cognitive development as well as children's behavioural problems were estimated using linear regression models adjusted for an extensive set of confounders. All results were expressed per 10 µg/m3 increase in NO2. RESULTS: 1143 children were included in the analysis. We found no association between NO2 and children's cognitive development (beta -0.05, 95% CI [-0.20; 0.10]) or behavioural problems (beta 0.02, 95% CI [-0.80; 0.12]). CONCLUSION: No association between child cognition or child behaviour and NO2 was found in this cross-sectional analysis. Further research will be necessary to understand the extent to which these null results reflect a true absence of association or other statistical, biological or adaptive factors not addressed in this paper.

Association between community noise and children's cognitive and behavioral development: A prospective cohort study.

BACKGROUND: Noise exposure has been associated with adverse cognitive and behavioral outcomes in children, but evidence on longitudinal associations between community noise and child development in low- and middle-income countries is rare. We investigated associations between community noise and behavioral and cognitive development in preschool children in São Paulo. METHODS: We linked child development data from the São Paulo Western Region Birth Cohort with average (Lden) and night-time (Lnight) community noise exposure at children's home, estimated by means of a land use regression model using various predictors (roads, schools, greenness, residential and informal settlements). Outcomes were the Strengths and Difficulties Questionnaire (SDQ) and Regional Project on Child Development Indicators (PRIDI) at 3 years of age and the Child Behavior Checklist (CBCL) and International Development and Early Learning Assessment (IDELA) at 6 years of age. We investigated the relationship between noise exposure and development using cross-sectional and longitudinal regression models. RESULTS: Data from 3385 children at 3 years of age and 1546 children at 6 years of age were analysed. Mean Lden and Lnight levels were 70.3 dB and 61.2 dB, respectively. In cross-sectional analyses a 10 dB increase of Lden above 70 dB was associated with a 32% increase in the odds of borderline or abnormal SDQ total difficulties score (OR = 1.32, 95% CI: 1.04; 1.68) and 0.72 standard deviation (SD) increase in the CBCL total problems z-score (95% CI: 0.55; 0.88). No cross-sectional association was found for cognitive development. In longitudinal analyses, each 10 dB increase was associated with a 0.52 SD increase in behavioral problems (95% CI: 0.28; 0.77) and a 0.27 SD decrease in cognition (95%-CI: 0.55; 0.00). Results for Lnight above 60 dB were similar. DISCUSSION: Our findings suggest that community noise exposure above Lden of 70 dB and Lnight of 60 dB may impair behavioral and cognitive development of preschool children.

Land use regression modelling of community noise in São Paulo, Brazil.

Noise pollution has negative health consequences, which becomes increasingly relevant with rapid urbanization. In low- and middle-income countries research on health effects of noise is hampered by scarce exposure data and noise maps. In this study, we developed land use regression (LUR) models to assess spatial variability of community noise in the Western Region of São Paulo, Brazil.We measured outdoor noise levels continuously at 42 homes once or twice for one week in the summer and the winter season. These measurements were integrated with various geographic information system variables to develop LUR models for predicting average A-weighted (dB(A)) day-evening-night equivalent sound levels (Lden) and night sound levels (Lnight). A supervised mixed linear regression analysis was conducted to test potential noise predictors for various buffer sizes and distances between home and noise source. Noise exposure levels in the study area were high with a site average Lden of 69.3 dB(A) ranging from 60.3 to 82.3 dB(A), and a site average Lnight of 59.9 dB(A) ranging from 50.7 to 76.6 dB(A). LUR models had a good fit with a R2 of 0.56 for Lden and 0.63 for Lnight in a leave-one-site-out cross validation. Main predictors of noise were the inverse distance to medium roads, count of educational facilities within a 400 m buffer, mean Normalized Difference Vegetation Index (NDVI) within a 100 m buffer, residential areas within a 50 m (Lden) or 25 m (Lnight) buffer and slum areas within a 400 m buffer. Our study suggests that LUR modelling with geographic predictor data is a promising and efficient approach for noise exposure assessment in low- and middle-income countries, where noise maps are not available.