Accumulating evidence from experimental studies suggests that air pollution may have a deleterious impact on the central nervous system, including chronic inflammation of the brain, disruption of the blood–brain barrier, microglia activation, and white matter injury.1 Air pollutants, especially particulate matter (PM) and its soluble components, may deposit in the alveolar region and translocate to the systemic circulation and thus reach other organs such as the brain.1 A general effect on the brain or more specific damage to specific areas such as the frontal cortex, hippocampus, striatum, and substantia nigra observed after air pollution exposure1 could lead to cognitive or psychomotor functioning impairment, 2 of the main brain functional domains.2 The potential neurotoxic effects of air pollution on brain functioning are of particular interest in fetuses and infants because the relatively immature detoxification mechanisms in early life make the developing brain more vulnerable to environmental toxicants.1,3
Some animal studies have examined the effects of diesel exhaust particles exposure during fetal life on cognitive function. Mice exposed to diesel exhaust particles in utero had reduced performance in the passive avoidance learning test,4 whereas another study found no effect on learning and memory tasks.5 Four studies have showed that diesel exhaust particles, black carbon, or NO2 exposure during pregnancy can decrease motor function in the offspring mice.6–9 Few human studies have looked for effects of air pollution exposure during fetal life on brain function. Air pollution exposure during pregnancy (especially exposure to polycyclic aromatic hydrocarbons [PAHs] levels and gas cooking) may reduce general cognitive function, but results are inconsistent for language development, nonverbal cognitive function, or psychomotor development in children.10–17
The purpose of the current study was to assess whether air pollution exposure during pregnancy affects cognitive and psychomotor development in childhood. As improvement upon previous studies, we used data from 6 European birth cohort studies that include a large sample size of almost 10,000 children with wide generalizability. Moreover, all of these studies performed a standardized assessment at the individual level for the entire pregnancy of a large number of air pollutants, including NO2 and PM; they also performed prospective assessment of cognitive and psychomotor development during childhood and collected information on potentially confounding socioeconomic and lifestyle variables.
Population and Study Design
This study was part of the European Study of Cohorts for Air Pollution Effects (ESCAPE), in which the association between exposure to outdoor air pollution and health is being investigated within prospective cohort studies (www.escapeproject.eu). We included 6 European population-based birth cohorts: GENERATION R (The Netherlands),18 DUISBURG (Germany),19 EDEN (France, 2 regions),20 GASPII (Italy),21,22 RHEA (Greece),23,24 and INMA (Spain, 5 regions)25 (Table 1). Mother–child pairs were recruited from 1997 to 2008. A total of 9482 children (67% of the children at birth) had data on exposures, outcomes, and potential confounders and were included in this analysis. Ethical approval was obtained from the local authorized Institutional Review Boards.
Air Pollution Exposure
Air pollution concentrations at the participants’ birth home addresses were estimated by land-use regression models following a standardized procedure described elsewhere26,27 (eAppendix 1, http://links.lww.com/EDE/A802). Briefly, air pollution monitoring campaigns in the study regions were performed mostly between October 2008 and January 2011, except for EDEN (done in 2002 and 2005). In all regions, NO2 and NOx were measured at least 3 times for a 2-week period within 1 year. In a subgroup of regions, simultaneous measurements were made of PM2.5 absorbance (determined as the reflectance of PM2.5 filters) and PM with aerodynamic diameters of <10 μm (PM10), <2.5 μm (PM2.5), and 2.5–10 μm (PMcoarse) (Table 1).28,29 Land-use regression models were developed for each pollutant metric using all measurement sites. Ambient air pollution concentration was estimated at the participants’ home addresses at the time of birth. We used a back-extrapolation procedure to estimate the concentrations during each pregnancy of each woman30,31 in order to assess if pregnancy period is a relevant exposure period. Traffic intensity on the nearest road and total traffic load (intensity × length) on all major roads within a 100-m buffer were available for some regions (Dutch, German, French, and Italian cohorts).
Cognitive and Psychomotor Development
Cognitive and psychomotor development was measured in each participating region by neuropsychological tests administered by psychologists or pediatricians, or by questionnaires answered by the parents (Table 1). For each region, we selected the tests and questionnaires with continuous scores in order to be comparable (eAppendix 2, eFigure 1, http://links.lww.com/EDE/A802). Cognitive scales were divided into those assessing general cognition and those assessing only language development. All psychomotor scales measured global psychomotor development; some also differentiated between fine and gross psychomotor development. When the test was performed by psychologists, those tests with uncertain quality due to less-than-optimal cooperation were flagged, and models were adjusted for this variable. All raw scores were converted into standard deviation units (z-score equals raw score subtracted from mean and divided by the standard deviation) and then standardized to a mean of 100 and a standard deviation of 15 (new score = 100 + (15 × z)) to homogenize the scales. Higher scores represented better general cognition, language, or psychomotor development.
Potential confounding variables were defined as similarly as possible among the regions, given the information available. Information on maternal age at delivery (continuous in years), maternal educational level (low, medium, high), maternal country of birth (country of the region, foreign country), maternal smoking during pregnancy (yes, no), and parity (0, 1, ≥2) was collected by questionnaires during pregnancy or at birth. For maternal education level, cohort-specific categories were standardized to create a common variable (eTable 1, http://links.lww.com/EDE/A802). Maternal height and pre-pregnancy weight were obtained in the first or second trimester of pregnancy or self-reported in the first trimester or at birth. Pre-pregnancy body mass index was calculated (kg/m2). Child’s sex and date of birth (from which season at birth was estimated) were obtained from hospital registries or self-reported at birth. Child’s age and evaluator for cognitive and psychomotor development assessment were also recorded. Urbanicity at child’s birth address (urban, rural) was determined by each local study team. Information was also collected on changes in residence between birth and the cognitive or psychomotor development assessment.
We used linear regression analyses to assess the association between the exposure to each air pollutant and each cognitive and psychomotor development scale. First, models were adjusted for child’s age at cognitive or psychomotor development assessment and child’s sex (minimally adjusted models). When child’s age did not have a linear relationship with the cognitive or psychomotor development scale, we used the best transformation of the age found using fractional polynomials.32 Secondly, models were additionally adjusted for all covariates described in the preceding paragraph (fully adjusted models). Generalized additive models were used to assess the linearity of the relationship between each air pollutant and each cognitive and psychomotor development scale, using the fully adjusted models by graphical examination and deviance comparison. Because linear function provided a good fit in almost all the cases, air pollution variables were not transformed. Outliers or influential points (studentized residuals ≥ 4 or Cook’s distance > 1, respectively) were identified, and fully adjusted models were repeated excluding these data points; results remained similar (data not shown). We applied a 2-stage approach to assess the effect of exposure to each air pollutant during pregnancy on cognitive and psychomotor development in children. First, associations were analyzed separately for each region. Second, region-specific effect estimates were combined using random-effects meta-analysis.33 When the same outcome was measured at multiple ages in a region, the score at the oldest age was taken into account in the meta-analyses. We assessed heterogeneity in the estimates using the Cochran Q test and the I2 statistic.34
To determine the influence of a particular cohort, meta-analyses were repeated omitting 1 cohort at the time. Because PM measurements were available in fewer regions, we also performed meta-analyses restricted to regions with information on both NO2 and PM. Associations between non-back-extrapolated air pollution exposure and cognition and psychomotor development were assessed. We reported meta-analyses in specific population subgroups characterized by a stable residence from birth until the cognitive or psychomotor development assessment or by a good-quality cognitive or psychomotor development assessment according to the psychologist. Meta-analyses were repeated including the younger ages among the regions where the outcomes were measured at different ages. Because early tests of motor development might be sensitive to the child’s age of walking, meta-analyses of psychomotor development were repeated evaluating early (≤2 years) versus later assessment. Meta-analyses were also repeated stratifying for those cohorts where cognitive and psychomotor development test was administered by a psychologist and those based on maternal reports. Spatial clustering of observations was explored by adding random region-level intercepts (Dutch cohort, neighborhood; German cohort, zip code; French cohort, commune; Italian cohort, census area; Greek and Spanish cohorts, no region-level variable available) to fully adjusted models without the air pollution data. Spatial clustering was found only for global psychomotor development in the Dutch cohort. Meta-analysis of global psychomotor development was repeated using linear mixed effects model (random region-level intercepts) for the Dutch cohort, rather than linear regression model, and results were similar. We therefore conducted all analysis without including the spatial clustering component. Because cognitive development assessment was available in fewer regions than psychomotor development, limiting comparability, meta-analyses for all outcomes were repeated restricting to regions with information on both cognitive and psychomotor development. Statistical analyses were conducted using STATA (version 12.0; StataCorporation, College Station, TX).
Child and maternal characteristics are presented in Table 2. The proportion of less-educated mothers was higher in the Valencia and Sabadell regions of the Spanish cohort and in the Poitiers region of the French cohort, compared with the other regions. More than 85% of mothers in all regions were born in the country of the study, except for the Dutch cohort in which only 58% of mothers were born in the Netherlands. Mean maternal age at delivery varied from 30 years (Nancy region of the French cohort) to 33 years (Italian cohort). The percentage of mothers who smoked during pregnancy ranged from 11% (Italian cohort) to 40% (Valencia region of the Spanish cohort), whereas mean maternal pre-pregnancy body mass index ranged from 22.2 kg/m2 (Italian cohort) to 24.4 kg/m2 (Dutch cohort).
The levels of each air pollutant during pregnancy are shown in Figure 1. Median levels of NO2 among regions ranged from 11.5 μg/m3 (Greek cohort) to 43.9 μg/m3 (Sabadell region of the Spanish cohort). Levels of PM2.5 ranged from 13.4 μg/m3 (Greek cohort) to 22.3 μg/m3 (Italian cohort). Different correlation patterns between air pollutants were found in the different regions, although, in general, the correlation among air pollutants was strong and the correlation between air pollutants and traffic indicator variables was moderate or low (eTable 2, http://links.lww.com/EDE/A802).
Neither general cognition nor language development was associated with any of the air pollutants (Table 3, eFigures 2 and 3, and eTable 3, http://links.lww.com/EDE/A802). In contrast, global psychomotor development was reduced, with increased exposure to all air pollutants (Table 3, Figure 2, eFigure 4, http://links.lww.com/EDE/A802). Global psychomotor development score was reduced by 0.68 points (95% confidence interval [CI] = −1.25 to −0.11) for each 10 μg/m3 increase in NO2 and was reduced by 1.64 points (−3.47 to 0.18) for each 5 μg/m3 increase in PM2.5. As shown in Figure 2, associations of the various pollutants with global psychomotor development were generally negative in most of the separate regions. When cohorts were excluded one by one, results were similar, particularly after excluding the Dutch cohort that represented the largest group (−0.82 points [−1.45 to −0.19] per each increase of 10 μg/m3 in NO2). Meta-analysis of the association between NO2 and global psychomotor development restricted to those regions with information on both NO2 and PM showed attenuated results (−0.36 points [−1.06 to 0.35]). Results for fine and gross psychomotor development were comparable with the findings obtained for global psychomotor development (eFigures 5 and 6, http://links.lww.com/EDE/A802). No associations were found between traffic indicator variables and any of the cognitive or psychomotor development variables (eTable 4, http://links.lww.com/EDE/A802).
Associations of non-back-extrapolated air pollutants with general cognition and with language development did not differ from the main analysis, whereas the associations with these air pollution measures were slightly attenuated for global psychomotor development (eTable 5, http://links.lww.com/EDE/A802). Restricting the analysis to children with stable residence from birth until the psychomotor development assessment, we found similar effects on global psychomotor development for all pollutants (eTable 6, http://links.lww.com/EDE/A802). Results remained similar when analyses were restricted to children with a good quality psychomotor development test or when scores were restricted to measurements conducted at an earlier age (eTable 6, http://links.lww.com/EDE/A802). Meta-analyses of psychomotor development evaluating early (≤2 years) versus later assessment showed similar results (data not shown). Meta-analyses repeated stratifying for those cohorts where cognitive and psychomotor development test was administered by a psychologist and those based on maternal reports showed materially unchangeable results (data not shown). Meta-analyses for all outcomes restricting to regions with information on both cognitive and psychomotor development showed similar results (data now shown).
We assessed the relationship between exposure to air pollution during pregnancy and childhood cognitive and psychomotor development, based on 6 European birth cohort studies with a total of almost 10,000 children. Air pollution exposure during pregnancy, particularly NO2 (for which motorized traffic is a major source), was negatively associated with psychomotor development—but not with cognitive development—in children assessed between 1 and 6 years of age.
The main strengths of our study are the large sample size (almost 10,000 children in 6 European countries), use of a standardized air pollution assessment in all the regions,26,27 assessment at the individual level of a large number of air pollutants (including NO2 and PM), prospective assessment of cognitive and psychomotor development during childhood using standardized and validated neuropsychological tests and questionnaires, and centralized statistical analysis following a consensus protocol. In addition, we adjusted for many socioeconomic and lifestyle variables known to be associated with air pollution exposure during pregnancy and with child cognitive and psychomotor development, although residual confounding (mainly related to socioeconomic position of the families) cannot be completely ruled out.
The main limitation of our study was the heterogeneity of instruments, evaluators, and ages used to assess cognitive and psychomotor functions. Although the selected tests were designed for assessing these functions, they measured in some cases different characteristics of the function or a different level of development. However, we found consistently adverse effects of air pollution exposure during pregnancy, particularly for the effect of NO2 on psychomotor development, regardless of type of instrument, type of evaluator, or age at assessment. Several sensitivity analyses were performed in order to assess the validity of the overall findings. When maternal report was compared with psychologist assessment, results were similar. Psychomotor development tests administered at early ages might be less valid and reliable because they are highly affected by the child’s time of walking. However, results remained after stratifying the analysis based on age (less vs. more than 2 years old). The Dutch cohort is the largest study region (with half of the population included in the meta-analysis) and could have a large influence in the overall results. Nevertheless, the exclusion of this cohort from the global meta-analysis showed similar results. Although associations are quite consistent among regions, we observed some heterogeneity in the association between NO2, NOx, and PM2.5 absorbance and psychomotor development. This heterogeneity was not present for other pollutants, was not related to the type of instrument, type of evaluator, or age of the assessment, and was not related to the levels of air pollution. Air pollution mixtures may be different among the study regions, which could be a potential explanation for the heterogeneity of the effects.
Another limitation of our study is related to exposure assessment. Air pollution levels were back-extrapolated to the pregnancy period using routine background monitoring network sites but monitoring data were not available for all pollutants in all study regions, particularly for PM. Although background monitoring network sites of other pollutants were used in the cases of missing information, this method could lead to a nondifferential misclassification of the exposure, especially for PM because monitoring data were poorer than for NO2. Nevertheless, non-back-extrapolated results were mainly unchanged. Associations between air pollutants and global psychomotor development were found only for NO2. This finding could be due to the fact that back-extrapolated levels of NO2 were more robust or that PM data were not available in all study regions. When we restricted the analysis of NO2 to the regions with available PM data, results were attenuated, indicating that the lack of association between PM and global psychomotor development could be driven by the selection of the regions. Finally, road traffic noise exposure was not measured in this study and might be a potential confounder because it is related to motor vehicle traffic and could be associated (as has been shown for airport noise) with impaired cognitive development among school-aged children.35,36
We observed an adverse association of air pollution exposure during pregnancy, particularly for NO2 and childhood psychomotor development. Some animal studies have found that diesel exhaust particles, black carbon, or NO2 exposure during pregnancy decreased the motor function in the offspring mice.6–9 One study suggested that the observed impairment of the motor activity was more likely due to an indirect effect caused by maternal inflammation during pregnancy.8 Some others suggested that spontaneous motor function impairment could be due to a facilitated release of dopamine in the prefrontal cortex7 or in the striatum,6,7 triggered by the diesel exhaust particle exposure during pregnancy. Dopamine and noradrenaline systems in the prefrontal cortex have an important role in the control of motor activity.37 In humans, a double-blind randomized crossover study was carried out, in which volunteers were exposed to dilute diesel exhaust or filtered air for 1 hour.38 There was increased activity of the frontal cortex during and after diesel exhaust exposure.38 The frontal cortex controls the actions of the body through its motor areas such as the primary motor or the premotor cortex.
Previous epidemiologic studies assessing exposure to air pollution during pregnancy and childhood psychomotor development are scarce and have contradictory results.10,13 Levels of PAHs were collected in a small sample of nonsmoking pregnancy women from New York City during 2 days in the third trimester of pregnancy.10 No association was found with childhood psychomotor development assessed at the ages of 1, 2, and 3 years.10
In another study carried out in Tongliang (China) where a seasonal coal-fired power plant was operating, prenatal PAH exposure measured by PAH–DNA adducts in umbilical cord blood was associated with an impairment in childhood psychomotor development at the age of 2 years.13 It is difficult to compare directly the magnitude of our findings with those previous studies, mainly due to the different treatment of the exposure variables in the statistical analyses (ie, increase of 10 μg/m3 in NO2 levels in our study; high/low PAH levels dichotomized at the 4th quartile in Perera et al10; high/low PAH levels dichotomized at the median in Perera et al11 and Edward et al12). Previous epidemiologic studies adjusted their models for several potential confounding variables similarly to our study. Moreover, the tests applied to assess psychomotor development were comparable with those applied in our study, and the assignment of the exposure was done mainly at the individual level. However, exposure mixtures may vary among study regions.
Two other studies assessed the relation between postnatal air pollution exposure and child psychomotor development with a cross-sectional approach, showing inconsistent results.39,40 A tendency toward an adverse association was found between postnatal NO2 exposure and psychomotor development at 4 years of age in the Granada region of the Spanish cohort included in the present study—in which we instead observed a positive association between prenatal NO2 exposure and psychomotor development.39 Possible reasons for these varying findings may be the assessment of exposure in a different period of child development (prenatal vs. postnatal), the various adjustments of the association models, or the different NO2 exposure assessment including different number of measurement sites (14 in our study vs. 70 in the previous study), different duration of the air pollution measurement periods (three 2-week measurements in our study vs. two 1-week measurements in the previous study), or different land-use regression models (R2 = 0.77 in our study vs. R2 = 0.45 for urban area and R2 = 0.75 for nonurban area in the previous study). In another study, children who attended a school in a highly polluted area of the Fujian province (China) showed worse performance in a psychomotor test at 8–10 years of age compared with children who attended a school in a less polluted area of the same province.40
We found no association between exposure during pregnancy to NO2 and PM and childhood cognitive development. A possible explanation is that children were assessed at an early stage of development, before 2 years of age in most of the centers. Cognitive development continues until young adulthood,41 and its assessment in early life might indicate an intermediate stage of development, when the measurement has more variability. Studies at older ages are warranted because children develop more cognitive abilities over the years, and these abilities can be assessed with more specific instruments at older ages. However, although previous epidemiologic studies carried out in children showed mixed results,10–15 some of them have found an association between air pollution exposure during pregnancy, especially PAH exposure, and childhood cognitive development at very young ages.10–14 Some other studies assessed postnatal exposure to air pollutants and child cognitive development with a cross-sectional design.39,40,42,43 Some of these studies found an association.42,43 Similar to previous studies on psychomotor development, these studies were adjusted for several potential confounders and applied cognitive tests comparable with those in our study. However, the 2 studies that found an association between postnatal exposure to air pollution and cognitive development assessed children at older ages. In our study, when we restricted the analysis to those children who did not change residence from birth until the cognitive development assessment, our results were unchanged. Further analyses are warranted to disentangle the effect of prenatal versus postnatal air pollutants, as well as to follow children to older ages.
Air pollution is a complex mixture that includes PM and NOx. Based on experimental models, it has been hypothesized that among the major contributors to the neurological effects of air pollution are PM-soluble components, very small particulate fragments, or ultrafine PM (PM with diameter of <0.1 μm) because they may translocate from the respiratory tract into the systemic circulation and reach the brain.1 In a postmortem study, presence of PM in the human brain and early disruption of the blood–brain barrier were observed in subjects from a large polluted city.44 PM is rich in organic carbon content, as well as in prooxidative PAH that promotes oxidative stress and inflammation.1 In our study, although all measures of PM were negatively associated with childhood psychomotor development, only NO2 exposure showed a strong relationship. This difference in the findings may be due to the fact that PM was measured only in 5 of the 11 regions, and thus we had low power to detect associations with PM. Also, back-extrapolation of PM to the pregnancy period was limited because routine background monitoring network sites for PM were not always available in all the regions, which increases the chances of an underestimation and also decreases the statistical power. In our study, NO2 and PM are markers of traffic air pollution, but also sources such as space heating, because small-scale traffic and population/household density variables were the most frequently used predictors in the land-use regression models.26,27 Moreover, due to the high correlation between pollutants, it is difficult to acertain which set of pollutants is responsible for the observed effects. However, because the trace-metal content of PM (such as lead and manganese, as well as PAH) has been found to be among the most neurotoxic components of air pollution,1 further studies on the relationship of these components with child cognitive and motor development are warranted.
In the present study, we found a decrease of 0.7 points on a psychomotor development scale for each 10 μg/m3 increase in pregnancy average NO2 levels. There is a large literature on the public impact of a 1-point loss of a neuropsychological scale, most are based on effects of lead exposure on intelligence quotient.3 Although a seemingly small change of a 1-point decrease in intelligence quotient score might not be relevant at the individual level, at the population level, this will shift the distribution of intelligence quotient to the left and increase the number of persons below the normal range.45 Further research is needed on long-term consequences of decreased psychomotor development score in childhood, as well as whether air pollution effects on psychomotor development are persistent at older ages.46
In sum, we found an association between air pollution exposure during pregnancy (particularly NO2, for which motorized traffic is a major source) and psychomotor development assessed between 1 and 6 years of age. Cognitive development measured at similar ages was not related to air pollution exposure during pregnancy.
We thank all participants for their generous collaboration.
GENERATION R. The Generation R Study is conducted by the Erasmus Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University Rotterdam, the Municipal Health Service Rotterdam area, Rotterdam, the Rotterdam Homecare Foundation, Rotterdam, and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-MDC), Rotterdam. We gratefully acknowledge the contribution of children and parents, general practitioners, hospitals, midwives, and pharmacies in Rotterdam. The Generation R Study is supported by the Erasmus Medical Center, Rotterdam, the Erasmus University Rotterdam, the Netherlands Organization for Health Research and Development (ZonMw), the Netherlands Organization for Scientific Research (NWO), and the Ministry of Health, Welfare and Sport. TNO received funding from the Netherlands Ministry of Infrastructure and the Environment to support exposure assessment. V.W.V. J. received an additional grant from the Netherlands Organization for Health Research and Development (ZonMw 90700303, 916.10159). The work by A.G. was supported by a research grant from the European Community’s 7th Framework Programme (FP7/2008-2013) under grant agreement 212652 (NUTRIMENTHE project, “The Effect of Diet on the Mental Performance of Children”).
DUISBURG. The Duisburg cohort study was financially supported and coordinated by the North Rhine-Westphalia State Agency for Nature, Environment and Consumer Protection (LANUV NRW), Germany. Additional financial support was given by the Federal Ministry of Environment, Nature Conservation, and Radioprotection (Bonn).
EDEN. Funding sources for the EDEN study are Fondation pour la Recherche Médicale (FRM), French Ministry of Research: IFR and Cohort program, INSERM Nutrition Research Program, French Ministry of Health Perinatality Program, French Agency for Environment Security (ANSES), French National Institute for Population Health Surveillance (INVS), Paris–Sud University, French National Institute for Health Education (INPES), Nestlé, Mutuelle Générale de l’Education Nationale (MGEN), French-speaking association for the study of diabetes and metabolism (Alfediam), National Agency for Research (ANR nonthematic program), National Institute for Research in Public Health (IRESP: TGIR cohorte santé 2008 program).
A list of the main EDEN investigators can be found at http://eden.vjf.inserm.fr/index.php/fr/organisation-d-eden.
GASPII. This study was funded by a grant from the Italian Ministry of Health (ex art.12, 2001).
RHEA. Rhea project was supported by European projects (EU FP6-2003-Food-3-A NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7-2008-ENV-220.127.116.11 Envirogenomarkers, EU FP7-HEALTH-2009- single-stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO) and the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011–2014). We thank Vicky Patelarou and Mina Iakovides who participated in the exposure assessment, and Katerina Koutra for her contribution in the neurodevelopment assessment.
INMA. This study was funded by grants from Instituto de Salud Carlos III (Red INMA G03/176 and CB06/02/0041 FIS-FEDER 03/1615, 04/1509, 04/1112, 04/1931, 05/1079, 05/1052, 06/1213, 07/0314, 09/02647 FIS-PI041436, FIS-PI081151, FISS-PI042018, FISS-PI09/02311, FIS-PI06/0867 FIS-PS09/00090, and FIS-07/0252), Generalitat de Catalunya-CIRIT 1999SGR 00241, La Fundació La Marató de TV3 (090430), Conselleria de Sanitat Generalitat Valenciana, Department of Health of the Basque Government (2005111093 and 2009111069), Provincial Government of Gipuzkoa (DFG06/004 and DFG08/001), Obra Social Cajastur, Universidad de Oviedo, EU Commission (QLK4-1999-01422, QLK4-2002-00603, and CONTAMED FP7-ENV-212502), Consejería de Salud de la Junta de Andalucía (grant number 183/07), and Fundación Roger Torné. A full roster of the INMA Project Investigators can be found at http://www.proyectoinma.org/presentacion-inma/listado-investigadores/en_listado-investigadores.html.
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