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Restricted cubic splines were used in mixed-effects logistic regression models to determine associations between each pollutant and NTD phenotype.
We used linear mixed models with random subject-specific intercepts to evaluate the association between each pollutant and natural log-transformed BNP concentrations.
Interaction between each pollutant and infant sex was evaluated by examining the statistical significance of their product term in each model (p < 0.05).
We fitted Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between each pollutant and the outcomes of interest.
We also observed a statistically significant dose response relationship between each pollutant and cervical dysplasia prevalence (p for trend ≤ 0.006 for benzene, PAHs, and DPM).
Last, we generated plots of the concentration response curves to examine the shape of the relationship between each pollutant and nonaccidental mortality using restricted cubic spline functions with two degrees of freedom.
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We fitted multivariate-adjusted linear models to examine the association between each air pollutant and each lymphocyte phenotype after controlling for potential confounders.
To evaluate the association between each single pollutant and wheeze, each regression contained a single pollutant term with a lagged (0 14 days) or moving-average (2 14 days) value.
In a second step, we performed a meta-analysis using random-effects models combining the estimates in each region of the association between each air pollutant and infant mental development.
Generalized additive models were used to assess the linearity of the relationship between each air pollutant and autistic trait scales by graphical examination and deviance comparison.
We used linear mixed-effects models (Verbeke and Molenberghs 2001) to estimate the association between each air pollutant and F eNO.
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