Geocoding and spatio-temporal modeling of long-term PM2.5 and NO2 exposure: the Mexican Teachers´ Cohort

Karla Cervantes-Martinez,Jorge Octavio Acosta-Montes,Dalia Stern,Hortensia Moreno-Macías,Carlos Díaz-Avalos,José Luis Texcalac-Sangrador,Ruy López-Ridaura,Horacio Riojas-Rodríguez

doi:10.20937/atm.53110

Karla Cervantes-Martinez, Jorge Octavio Acosta-Montes + Show 6 more

Open Access

https://doi.org/10.20937/atm.53110

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Abstract

Epidemiological studies on air pollution in Mexico often use the environmental concentrations of pollutants as measured by monitors closest to the home of participants as exposure proxies, yet this approach does not account for the space gradients of pollutants and ignores intra-city human mobility. This study aimed to develop high-resolution spatial and temporal models for predicting long-term exposure to PM2.5 and NO2 in ~16,500 participants from the Mexican Teachers’ Cohort study. We geocoded the home and work addresses of participants, and used secondary source information on geographical and meteorological variables as well as other pollutants to fit two generalized additive models capable of predicting monthly PM2.5 and NO2 concentrations during the 2004-2019 period. Both models were evaluated through 10-fold cross-validation, and showed high predictive accuracy with out-of-sample data and no overfitting (CV-RMSE=0.102 for PM2.5 and CV-RMSE=4.497 for NO2). Participants were exposed to a monthly average of 24.38 (6.78) mg/m3 of PM2.5 and 28.21 (8.00) ppb of NO2 during the study period. These models offer a promising alternative for estimating PM2.5 and NO2 exposure with high spatio-temporal resolution for epidemiological studies in the Mexico City Metropolitan Area.

Highlights

In 2015, the World Health Organization (WHO) recognized ambient air pollutant exposure and its effects on human health as a public health priority requiring further study (WHO, 2015)
This study is nested within a larger study known as the Mexican Teachers’ Cohort (MTC): an ongoing prospective observational study established in 2006 -2008 which includes 115,314 female public-school teachers from 12 Mexican states, with a median age at enrollment of 44 years
It is crucial for environmental epidemiology to apply methods for the estimation of ambient air pollutant exposure which can overcome limited data availability: a relevant factor in developing countries

Summary

Introduction

In 2015, the World Health Organization (WHO) recognized ambient air pollutant exposure and its effects on human health as a public health priority requiring further study (WHO, 2015). Epidemiological studies have shown that chronic exposure to ambient PM2.5 and NO2 is associated with health outcomes including increased mortality (Beelen et al, 2014), cardiovascular disease (Dockery, 2001; Hoek et al, 2013), lung cancer (Pope et al, 2002; Chen et al, 2008; Hamra et al, 2014), cardiopulmonary conditions (Krewski et al, 2009) and diabetes (Li et al., 2014). These studies which have used a variety of methods to estimate air pollutant exposure, have developed deterministic and/or probabilistic models as the cornerstone of their analyses.

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