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Suarez D.,Autonomous University of Barcelona | Borras R.,Autonomous University of Barcelona | Basagana X.,Center for Research in Environmental Epidemiology | Basagana X.,Municipal Institute of Medical Research IMIM Hospital Del Mar | Basagana X.,CIBER ISCIII
Epidemiology | Year: 2011

Background: Marginal structural models were developed to address time-varying confounding in nonrandomized exposure effect studies. It is unclear how estimates from marginal structural models and conventional models might differ in real settings. Methods: We systematically reviewed the literature on marginal structural models since 2000. Results: Data to compare marginal structural models and conventional models were obtained from 65 papers reporting 164 exposureoutcome associations. In 58 (40%), estimates differed by at least 20%, and in 18 (11%), the 2 techniques resulted in estimates with opposite interpretations. In 88 papers, marginal structural models were used to analyze real data; only 53 (60%) papers reported the use of stabilized inverse-probability weights and only 28 (32%) reported that they verified that the mean of the stabilized inverseprobability weights was close to 1.0. Conclusions: We found important differences in results from marginal structural models and from conventional models in real studies. Furthermore, reporting of marginal structural models can be improved. © 2011 by Lippincott Williams & Wilkins.


Grazuleviciene R.,Vytautas Magnus University | Kapustinskiene V.,Vytautas Magnus University | Kapustinskiene V.,Lithuanian University of Health Sciences | Vencloviene J.,Vytautas Magnus University | And 4 more authors.
Occupational and Environmental Medicine | Year: 2013

Objectives Congenital anomalies have been inconsistently associated with maternal crude estimated exposure to drinking water trihalomethane (THM). We investigated the relationship between individual THM uptake during the first trimester of pregnancy and congenital anomalies. Methods We estimated maternal THM uptake for 3074 live births using residential tap water concentrations, drinking water ingestion, showering and bathing, and uptake factors of THM in the blood. Multiple logistic regression was used to investigate the association of THM exposure with congenital anomalies. Results We observed no statistically significant relationships between congenital anomalies and the total THM internal dose. We found little indication of a doseresponse relationship for brominated THM and congenital heart anomalies. The relationship was statistically significant for bromodichloromethane (BDCM) (OR=2.16, 95% CI 1.05 to 4.46, highest vs lowest tertile) during the first month of pregnancy. During the first trimester of pregnancy, the probability of developing heart anomalies increased for every 0.1 μg/d increase in the BDCM and for every 0.01 μg/d increase in the internal dibromochloromethane (DBCM) dose (OR 1.70, 95% CI 1.09 to 2.66, and OR 1.25, 95% CI 1.01 to 1.54, respectively). A dose-response relationship was evident for musculoskeletal anomalies and DBCM exposure during the first and second months of pregnancy, while BDCM exposure tended to increase the risk of urogenital anomalies. Conclusions This study shows some evidence for an association between the internal dose of THM and the risk of congenital anomalies. In particular, increased prenatal exposure to brominated THM might increase the risk of congenital heart and musculoskeletal anomalies.


Nazelle A.D.,University of North Carolina at Chapel Hill | Nazelle A.D.,Center for Research in Environmental Epidemiology | Nazelle A.D.,Municipal Institute of Medical Research IMIM Hospital Del Mar | Nazelle A.D.,CIBER ISCIII | And 2 more authors.
Environmental Science and Technology | Year: 2010

States in the USA are required to demonstrate future compliance of criteria air pollutant standards by using both air quality monitors and model outputs. In the case of ozone, the demonstration tests aim at relying heavily on measured values, due to their perceived objectivity and enforceable quality. Weight given to numerical models is diminished by integrating them in the calculations only in a relative sense. For unmonitored locations, the EPA has suggested the use of a spatial interpolation technique to assign current values. We demonstrate that this approach may lead to erroneous assignments of nonattainment and may make it difficult for States to establish future compliance. We propose a method that combines different sources of information to map air pollution, using the Bayesian Maximum Entropy (BME) Framework. The approach gives precedence to measured values and integrates modeled data as a function of model performance. We demonstrate this approach in North Carolina, using the States ozone monitoring network in combination with outputs from the Multiscale Air Quality Simulation Platform (MAQSIP) modeling system. We show that the BME data integration approach, compared to a spatial interpolation of measured data, improves the accuracy and the precision of ozone estimations across the State. © 2010 American Chemical Society.


Basagana X.,Center for Research in Environmental Epidemiology | Basagana X.,Municipal Institute of Medical Research IMIM Hospital Del Mar | Basagana X.,CIBER ISCIII | Spiegelman D.,Harvard University
Statistics in Medicine | Year: 2010

Existing study design formulas for longitudinal studies have assumed that the exposure is time-invariant. We derived sample size formulas for studies comparing rates of change by exposure when the exposure varies with time within a subject, focusing on observational studies where this variation is not controlled by the investigator. Two scenarios are considered, one assuming that the effect of exposure on the response is acute and the other assuming that it is cumulative. We show that accurate calculations can often be obtained by providing the intraclass correlation of exposure and the exposure prevalence at each time point. When comparing rates of change, studies with a time-varying exposure are, in general, less efficient than studies with a time-invariant one. We provide a public access program to perform the calculations described in the paper (http://www.hsph.harvard.edu/faculty/spiegelman/optitxs.html). Copyright © 2009 John Wiley & Sons, Ltd.


Carsin A.-E.,National Cancer Registry Ireland | Carsin A.-E.,Center for Research in Environmental Epidemiology | Carsin A.-E.,Municipal Institute of Medical Research IMIM Hospital Del Mar | Sharp L.,National Cancer Registry Ireland | Comber H.,National Cancer Registry Ireland
British Journal of Dermatology | Year: 2011

Background: Nonmelanoma skin cancer (NMSC) is the most common cancer in white populations worldwide. International comparisons in incidence are limited because few registries collect comprehensive population-based data. Objectives: We describe spatial, urban/rural and socioeconomic variations in NMSC incidence in Ireland, overall and for basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) separately. Methods: NMSC cases (n = 47 347) diagnosed during 1994-2003 were extracted from the National Cancer Registry. Each case was allocated to a small area (electoral district, ED) based on address at diagnosis. Standardized incidence ratios (SIRs) were calculated and smoothed using a Bayesian conditional autoregressive model. Associations between disease and census-derived area-based socioeconomic factors (unemployment, employment type, early school leavers, deprivation category, population density) were investigated using negative binomial regression. Results: The spatial and socioeconomic distributions differed by subtype, suggesting aetiological differences. For BCC, areas of higher risk were concentrated around the main cities, with small patches on the south and west coast. Higher risks for SCC were seen in the north-east, on the south, mid and north-west coast. BCC risk in males and females, and SCC in males, was significantly higher in those living in the least deprived areas. Risk of BCC and SCC in females was higher in the most densely populated areas. Conclusions: We observed striking geographical variation in NMSC incidence, which cannot be satisfactorily explained on the basis of known risk factors. Differences by deprivation category and population density may reflect better access to cancer surveillance or care, as well as differences in risk factor exposure. ©The Authors BJD ©British Association of Dermatologists 2011.

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