Adverse birth outcomes in the vicinity of industrial installations in Spain 2004–2008

Abstract

Industrial activity is one of the main sources of ambient pollution in developed countries. However, research analyzing its effect on birth outcomes is inconclusive. We analyzed the association between proximity of mother's municipality of residence to industries from 24 different activity groups and risk of very (VPTB) and moderate (MPTB) preterm birth, very (VLBW) and moderate (MLBW) low birth weight, and small for gestational age (SGA) in Spain, 2004-2008. An ecological study was defined, and a "near vs. far" analysis (3.5 km threshold) was carried out using Hierarchical Bayesian models implemented via Integrated Nested Laplace Approximation. VPTB risk was higher for mothers living near pharmaceutical companies. Proximity to galvanization and hazardous waste management industries increased the risk of MPTB. Risk of VLBW was higher for mothers residing near pharmaceutical and non-hazardous or animal waste management industries. For MLBW many associations were found, being notable the proximity to mining, biocides and animal waste management plants. The strongest association for SGA was found with proximity to management animal waste plants. These results highlight the importance of further research on the relationship between proximity to industrial sites and the occurrence of adverse birth outcomes especially for the case of pharmaceutical and animal waste management activities.

Modeling spatial effects of PM2.5 on term low birth weight in Los Angeles County

“…In fitting the model, we took advantage of the computational efficiency of Integrated Nested Laplace Approximations (INLA, version 0.0-1420281647) estimation techniques as implemented in the well-established R-INLA package (Rue et al, 2015), which has been used in several recent studies of large dimensions (Bennett et al, 2014;Castelló et al, 2013;Lee et al, 2013;Lee and Mitchell, 2014). The INLA approach avoids the computational burden related to typical Markov Chain Monte Carlo techniques (Gilks et al, 1998) often used to fit Bayesian spatial models and allows accurate approximations to posterior marginal distributions of the model parameters (Grilli et al, 2014).…”

“…Some air pollution and birth outcome studies have accounted for spatial dependency in the residuals, but still assume a global effect due to exposure (Berrocal et al, 2011;Castelló et al, 2013;Thompson et al, 2014;Williams et al, 2007). A spatial correlated autoregressive (CAR) model has been applied by (Berrocal et al, 2011) to examine the effect of CT-level PM 2.5 on continuous birth weight in North Carolina.…”

“…This study, however, used aggregated outcomes for a given geographic area and did not include individual-level air pollution estimates of exposure. A study conducted in Spain that examined municipal-level risks of PTB and LBW with proximity to different types of industries modeled spatially varying effects using Poisson regression with a spatial error term and an unstructured error term (Castelló et al, 2013). A major difference in the Castelló et al (2013) study is that these researchers, again, used aggregated outcome data and did not relate birth outcomes with individual-level estimates of air pollutant exposures.…”

“…A study conducted in Spain that examined municipal-level risks of PTB and LBW with proximity to different types of industries modeled spatially varying effects using Poisson regression with a spatial error term and an unstructured error term (Castelló et al, 2013). A major difference in the Castelló et al (2013) study is that these researchers, again, used aggregated outcome data and did not relate birth outcomes with individual-level estimates of air pollutant exposures. A study by Williams et al (2007) applied a linear hierarchical random effects model with spatially unstructured random coefficients and found substantial variation across census tracts regarding the estimated effects of maternal residential proximity to hazardous air pollution sites for reducing average birth weight.…”

Geographical variations in the risk of adverse birth outcomes in Spain

“…However, it has been shown that local factors other than socioeconomic may be important when identifying risks factors for prematurity and low birth weight (Crosse et al 1997;Walsh et al 2010). On the other hand, some studies have suggested a possible association between residential proximity to industries and adverse birth outcomes (Morgan et al 2004;Ahern et al 2011;Castello et al 2013). In this sense, it could be useful to consider the remarkable disparity between Asturias and Murcia in terms of industrial activity to assess the significance of the differences found and potential risk factors associated.…”