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Open Access Study protocol

A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes

Manuel C Ribeiro1*, Maria J Pereira1, Amílcar Soares1, Cristina Branquinho2, Sofia Augusto2, Esteve Llop2, Susana Fonseca3, Joaquim G Nave3, António B Tavares4, Carlos M Dias5, Ana Silva6, Ismael Selemane7, Joaquin de Toro8, Mário J Santos8 and Fernanda Santos6

Author Affiliations

1 Centro de Recursos Naturais e Ambiente, Instituto Superior Técnico, Universidade Técnica de Lisboa, Lisboa, Portugal

2 Centro de Biologia Ambiental, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal

3 Department of Sociology, Instituto Universitário de Lisboa, Lisboa, Portugal

4 Department of Environmental Health, Instituto Nacional de Saúde Ricardo Jorge, Lisboa, Portugal

5 Department of Epidemiology, Instituto Nacional de Saúde Ricardo Jorge, Lisboa, Portugal

6 Centro de Saúde de Sines, Administração Regional de Saúde do Alentejo, Sines, Portugal

7 Centro de Saúde de Grândola, Administração Regional de Saúde do Alentejo, Grândola, Portugal

8 Centro de Saúde de Santiago do Cacém, Administração Regional de Saúde do Alentejo, Santiago do Cacém, Portugal

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BMC Public Health 2010, 10:613  doi:10.1186/1471-2458-10-613

Published: 15 October 2010

Abstract

Background

The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design.

Methods/Design

Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models.

Discussion

Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at geocoded addresses will improve knowledge on variability of exposures, improving therefore validity of individual exposures to input in posterior statistical analysis.