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Epidemiology:
doi: 10.1097/EDE.0000000000000107
Air Pollution

Residential Proximity to Major Roads and Term Low Birth Weight: The Roles of Air Pollution, Heat, Noise, and Road-Adjacent Trees

Dadvand, Payama,b; Ostro, Bartc; Figueras, Francescd; Foraster, Mariaa,b,e; Basagaña, Xaviera,b; Valentín, Antòniaa,b; Martinez, Davida,b; Beelen, Robf; Cirach, Martaa,b; Hoek, Gerardf; Jerrett, Michaelg; Brunekreef, Bertf,h; Nieuwenhuijsen, Mark J.a,b

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Author Information

From the aCentre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; bCIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain; cOffice of Environmental Health Hazard Assessment, California Environmental Protection Agency, Oakland, CA; dDepartment of Maternal-Foetal Medicine, ICGON, Hospital Clinic-IDIBAPS, University of Barcelona, Barcelona, Spain; eUniversitat Pompeu Fabra (UPF), Barcelona, Spain; fInstitute for Risk Assessment Sciences, Division Environmental Epidemiology, Utrecht University, Utrecht, The Netherlands; gSchool of Public Health, University of California Berkeley, Berkeley, CA; and hJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.

Submitted 4 April 2013; accepted 28 January 2014; posted 30 April 2014.

The authors report no conflicts of interest.

This study was funded by an FIS grant (grant no. PI081109) from the Instituto de Salud Carlos III FEDER. The research leading to the modeling framework for the air pollution exposure assessment in this study has received funding from the European Community’s Seventh Framework Program (FP7/2007–2011) under grant agreement number: 211250. The assessment of road-adjacent tree coverage was carried out as part of European Community’s Seventh Framework Program-funded project PHENOTYPE (grant no. 282996). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. P.D. is funded by a Ramón y Cajal fellowship (RYC-2012-10995) awarded by the Spanish Ministry of Economy and Competitiveness. M.F. is funded by a Instituto de Salud Carlos III predoctoral fellowship.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article ( www.epidem.com). This content is not peer-reviewed or copy-edited; it is the sole responsibility of the author.

Editors’ note: A commentary on this article appears on page 526.

Correspondence: Payam Dadvand, CREAL, Barcelona Biomedical Research Park, Dr. Aiguader, 88, 08003 Barcelona, Spain; E-mail: pdadvad@creal.cat.

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Abstract

Background:

Maternal residential proximity to roads has been associated with adverse pregnancy outcomes. However, there is no study investigating mediators or buffering effects of road-adjacent trees on this association. We investigated the association between mothers’ residential proximity to major roads and term low birth weight (LBW), while exploring possible mediating roles of air pollution (PM2.5, PM2.5–10, PM10, PM2.5 absorbance, nitrogen dioxide, and nitrogen oxides), heat, and noise and buffering effect of road-adjacent trees on this association.

Methods:

This cohort study was based on 6438 singleton term births in Barcelona, Spain (2001–2005). Road proximity was measured as both continuous distance to and living within 200 m from a major road. We assessed individual exposures to air pollution, noise, and heat using, respectively, temporally adjusted land-use regression models, annual averages of 24-hour noise levels across 50 m and 250 m, and average of satellite-derived land-surface temperature in a 50-m buffer around each residential address. We used vegetation continuous fields to abstract tree coverage in a 200-m buffer around major roads.

Results:

Living within 200 m of major roads was associated with a 46% increase in term LBW risk; an interquartile range increase in heat exposure with an 18% increase; and third-trimester exposure to PM2.5, PM2.5–10, and PM10 with 24%, 25%, and 26% increases, respectively. Air pollution and heat exposures together explained about one-third of the association between residential proximity to major roads and term LBW. Our observations on the buffering of this association by road-adjacent trees were not consistent between our 2 measures of proximity to major roads.

Conclusion:

An increased risk of term LBW associated with proximity to major roads was partly mediated by air pollution and heat exposures.

The developing fetus is known to be susceptible to environmental insults.1 A growing body of evidence has associated maternal residential proximity to major roads with a number of adverse pregnancy outcomes, including low birth weight (LBW, birth weight <2,500 g), assuming that proximity to major roads is a surrogate for exposure to traffic-related air pollution.2–7 However, there is no available study quantifying the contribution of air pollution to such an association. Furthermore, residential proximity to major roads can be accompanied by higher exposure to environmental factors other than air pollution. For example, traffic is a main source of noise,8 and the road network is a major contributor to heat island effects in urban environments.9 Although noise and heat may be relevant to pregnancy outcomes, there is no report on their contribution to the association between residential proximity to major roads and adverse pregnancy outcomes. This apportionment of the health effects of road proximity to more specific exposures, such as air pollution, noise, and heat, is of importance because an effect of road proximity itself cannot be explained biologically. A recent review of the literature on the health effects of residential proximity to major roads has highlighted the lack of evidence on underlying mechanisms for such effects.10

Road-adjacent trees are reported to reduce traffic-related air pollution, noise, and heat island effect.11–13 Although road-adjacent trees might buffer the adverse impact of residential proximity to major roads on pregnancy outcomes, there is no published evidence of such a buffering effect.

This study aimed to explore the association of maternal residential proximity to major roads and term LBW, possible mediation of this association by air pollution, noise, and heat, and possible buffering by road-adjacent trees.

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METHODS

Study Population

This study was based on a cohort of singleton term births (ie, gestational age at delivery ≥37 weeks) occurring at the obstetrics department of the Hospital Clinic de Barcelona between January 2001 and June 2005 to mothers residing in the city of Barcelona. Hospital Clinic de Barcelona is a major university hospital covering Barcelona city, with a catchment area of about one million inhabitants.14 The hospital records detailed a wide range of prospectively collected data on maternal and fetal characteristics, together with clinical data on pregnancy and delivery, including ultrasound measures of gestational age for all pregnancies.14

Ethics approval (No. 2008/3115/I) was obtained from the Clinical Research Ethical Committee of the Parc de Salut MAR, Barcelona, Spain, to carry out this study.

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Residential Proximity to Major Roads

Street network geocoding was used to geocode the residence address of each study participant at the time of her delivery, based on postal code, street name, and house number. Major roads were determined according to the European Study of Cohorts for Air Pollution Effects guidelines.15 We used 2 measures of proximity to major roads: (1) residential distance to a major road (hereafter referred to as “continuous distance”) and (2) living within 200 m of a major road (hereafter referred to as “binary distance”). The selection of a 200-m distance was consistent with previous studies2,3,16–18 and was informed by the Special Report 17 of the Health Effects Institute,19 which suggested that after 200 m the levels of some air pollutants (eg, nitrogen dioxide) reduce to background levels—as it did in our study setting (eTable 1, http://links.lww.com/EDE/A790). We used EuroStreets map (version 3.1), which is a 1:10,000 digital road network based on the TeleAtlas MultiNet (’s-Hertogenbosch, Netherlands).15

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Exposure to Air Pollution, Noise, and Heat and Road-Adjacent Tree Coverage

The description of our applied methodologies to assess exposure to air pollution, noise, and heat and estimating road-adjacent tree coverage has been detailed in supplementary materials (eAppendix I, eTable 2, eFigures 1–4, http://links.lww.com/EDE/A790). In brief, we estimated the ambient levels of nitrogen dioxides (NO2), nitrogen oxides (NOx), particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5), 2.5–10 μm (PM2.5–10), and ≤10 μm (PM10), and PM2.5 light absorption (hereafter referred to as PM2.5 absorbance) at the home address of each participant for each week of her pregnancy, using temporally adjusted land-use regression models.15,20–22 We then averaged these exposure levels over the entire pregnancy, as well as each trimester of pregnancy. Exposure to noise was defined as the average of the long-term mean noise-level indicator for the 24-hour period (Lden, in dB(A)) within 50 m23 and 250 m24 of each home address, based on Barcelona’s strategic noise map.25 We assessed exposure to heat as the average of land-surface temperature within 50 m around each home address, based on 3 land-surface temperature maps derived from the Landsat 5 Thematic Mapper data. We abstracted the road-adjacent tree coverage as the average of percent tree coverage within 200 m on each side of that road, based on vegetation continuous field maps derived from data collected by the Moderate Resolution Imaging Spectroradiometer aboard the Terra satellite.26

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Statistical Analyses
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Risk Estimates

We first used generalized additive models to explore the linearity of the associations (in the logit scale) between term LBW and continuous distance and mediators (air pollution, noise, and heat) that did not show any notable nonlinearity of associations (eFigure 5, http://links.lww.com/EDE/A790). We then developed logistic regression models with term LBW (yes/no) as the outcome and indicators of proximity to major roads and exposures to air pollution, heat, and noise exposure (one at a time) as predictors. To facilitate comparisons among these exposures, we reported the results for 1 interquartile range (IQR) increase in each exposure level. The analyses were adjusted for neighborhood socioeconomic status (MEDEA index),27 ethnicity (white/non-white/mixed), education level (none or primary/secondary/university), marital status (single mother: yes/no), age, smoking during pregnancy (yes/no), alcohol consumption during pregnancy (yes/no), body mass index (BMI) less than 20 kg/m2 (yes/no) at the time of admission, diabetes (gestational or pregestational: yes/no), infection (Rubella, Group B streptococci, Toxoplasma gondii, sexually transmitted diseases, or bacteriuria; yes/no), parity (0/1/2+), sex of baby (female/male), season of conception (summer/winter), and year of conception.

Of 6438 registered participants, 1,093 had one or more missing values for the covariates (mostly maternal education and BMI) for which the analyses were adjusted (Table 1). We conducted multiple imputation for missing data as described in eTable 3 ( http://links.lww.com/EDE/A790) and analyzed the resulting 100 data sets following the standard combination rules for multiple imputations.28

TABLE 1.
TABLE 1.
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Mediating Role of Air Pollution, Heat, and Noise

We calculated the percentage of the association between proximity to major roads and term LBW explained by each of the mediators as (1 − [βpm/βp]) × 100%, where βpm was the regression coefficient for proximity to major roads in the fully adjusted model including mediator (joint model) and βp was the regression coefficient for the proximity to major roads in the fully adjusted model without including any mediator.29 This measure can lead to values greater than 100% if the regression coefficient for proximity after including the mediator is negative, and it can lead to negative values if the regression coefficient for proximity after including the mediator is greater than the coefficient obtained when the mediator is not included. We used bootstrap to obtain percentile-based 95% confidence intervals for this measure of mediation.

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Buffering Effect of Road-Adjacent Tree Coverage

We stratified the analysis of the association between residential proximity to major roads and term LBW according to the terciles of road-adjacent tree coverage to compare the associations across levels of road-adjacent tree coverage. We also checked the significance of the multiplicative interaction term of proximity to major roads with terciles of road-adjacent tree coverage by comparing models with and without interaction terms, using the likelihood ratio test.

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Further Analysis

We defined small for gestational age (SGA) as birth weight below the 10th percentile for the gestational age and sex according to national growth curves.30 We repeated the aforementioned analyses using SGA as outcome (instead of term LBW) and removing sex as the covariate.

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RESULTS

Study Population

During the course of the study, 6,438 singleton term births with mothers residing in the city of Barcelona were enrolled in the cohort. Of these, 190 (3%) were term LBW. Descriptive statistics of the characteristics of the study participants are presented in Table 1.

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Exposure Assessment

The median residential distance to major roads was 145 m (IQR = 216 m). About two-thirds of participants (n = 3,980) lived within 200 m of a major road. Participants living ≤200 m from a major road and those living farther away were similar with regard to all covariates except ethnicity and MEDEA index of neighborhood deprivation, with those living closer to a major road tending to be less deprived.

Summary statistics of estimates for exposure to air pollutants during each window period are shown in eTable 4 ( http://links.lww.com/EDE/A790). As presented in eTable 5 ( http://links.lww.com/EDE/A790), the trimester-specific exposures were weakly to moderately correlated. The correlation between exposures to air pollutants, noise, and heat and road-adjacent tree coverage is reported in eTable 6 ( http://links.lww.com/EDE/A790). As presented in eTable 7 ( http://links.lww.com/EDE/A790), those participants living within 200 m of a major road had higher median levels of exposure to air pollution, heat, and noise compared with those living farther away. Proximity to major roads could explain no more than 40% of the variation in fine particulate pollutants measured by the monitoring stations; for the other pollutants explained, the variation by major road proximity was less than 20% (eTable 8, http://links.lww.com/EDE/A790). The land-use regression models previously developed for these pollutants used more refined geographic information system variables and explained much larger percentages of variance.21,31 The median percentage of road-adjacent tree coverage in a buffer of 200 m around the major road was 3% (IQR = 1%).

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Term Low Birth Weight
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Risk Estimates

Living within 200 m of a major road was associated with a 46% increase in the risk of term LBW (Table 2). Consistently, longer distance to a major road was associated with a reduction in term LBW risk (Table 2). Although exposure to heat was associated with increased risk of term LBW, our findings for the noise exposure were not conclusive (Table 2). We also observed increased risk of term LBW associated with the third-trimester exposure to particulate air pollutants, except PM2.5 absorbance (Table 3). After including exposures to PM2.5 (third-trimester), heat, and noise (50 m buffer) in a fully adjusted model without any indicator of residential proximity to a major road, exposures to PM2.5 and heat were associated with increased risk of term LBW (Table 2). These risk estimates were robust to the exclusion of subjects with missing data (complete case analysis).

TABLE 2.
TABLE 2.
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TABLE 3.
TABLE 3.
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Mediating Role of Air Pollution, Heat, and Noise

For air pollutants, we checked the mediating role of those exposure windows for which we found the strongest association with term LBW (ie, first trimester for NO2, NOx, and PM2.5 absorbance and third trimester for PM2.5, PM2.5–10, and PM10). The risk estimates for mediators and proximity to major roads in the joint models are presented in Table 4. As shown in Table 5, the percentages of the association between the major road proximity-term LBW that could be explained by the mediators were generally higher when continuous distance was used. The largest percentage of the association between major road proximity and term LBW explained by air pollutants was due to exposure to PM2.5 (Table 5). Exposure to heat could also explain about 8% of this association, whereas exposure to noise explained none. Exposure to heat and PM2.5 could jointly explain one-fourth of this association when the binary distance was used and more than one-third when continuous distance was used (Table 5).

TABLE 4.
TABLE 4.
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TABLE 5.
TABLE 5.
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Buffering Effect of Road-Adjacent Tree Coverage

We observed the suggestion of a tree-related trend in odds ratios (ORs) for the association of term LBW with binary distance; the risk of term LBW associated with proximity to the greenest major roads was about one-third of that associated with proximity to the least green major roads (Table 6). There was no evidence for trend with continuous distance (Table 6). For the multiplicative interaction term of proximity to major roads with terciles of road-adjacent tree coverage, P = 0.24 for binary distance and P = 0.35 for continuous distance.

TABLE 6.
TABLE 6.
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Small Size for Gestational Age

There were 803 (12%) newborns identified as SGA in our data set. As presented in eTables 9 and 10 ( http://links.lww.com/EDE/A790), the direction of associations between SGA and residential proximity to a major road—as well as exposure to air pollution, heat, and noise—was consistent with those of term LBW; however, the associations for SGA were generally weaker (except for noise). Exposure to air pollution, noise, and heat (separately) could explain 2–14% of the association between maternal residential proximity to major roads and SGA (eTable 11, http://links.lww.com/EDE/A790). Exposure to heat and noise and the third-trimester exposure to PM2.5 could jointly explain about one-fourth of this association (eTable 11, http://links.lww.com/EDE/A790). The OR for SGA associated with proximity to major roads with the highest tree coverage was half of that associated with proximity to major roads with the lowest tree coverage; however, there was no clear trend for associations across the strata of tree coverage (eTable 12, http://links.lww.com/EDE/A790).

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DISCUSSION

This study provides a comprehensive view of the association between residential proximity to major roads and adverse pregnancy outcomes, quantifying the contributions of air pollution, heat, and noise exposures to such an association. It also investigated the buffering effect of road-adjacent tree coverage on this association. We found increased risk of term LBW in association with maternal residential proximity to major roads, as well as with heat exposure and third-trimester exposure to PM2.5, PM2.5–10, and PM10. Up to one-third of the association between residential proximity to major roads and term LBW could be explained by exposure to air pollution and heat. There were also some indications that road-adjacent trees could buffer the impact of residential proximity to major roads on term LBW, although our findings were not consistent between our indicators of proximity to major roads. Our findings for SGA were less conclusive.

The increased risk of term LBW associated with residential proximity to major roads in our study was in-line with findings of other studies reporting increased placenta/birth weight ratio3 (a marker of the placental transport dysfunction) and increased risk of LBW associated with residential proximity to major roads.2,4,5 We also observed increased risk of term LBW associated with exposure to particulate air pollution (excluding PM2.5 absorbance) consistent with other evidence.32,33 Because of high correlation between the second- and third-trimester exposures to PM2.5 (Spearman’s ρ = 0.77), it was not possible to determine which trimester is the most relevant for this exposure. However, our observation for other particulate air pollutants showing the strongest associations with third-trimester exposures, without a high correlation between the second and trimester exposures, could give more confidence about the relevance of the third-trimester exposure for PM2.5.

We found increased risk of term LBW associated with heat exposure. Given the expected larger temporal variability compared with spatial variability in temperature, our observed small difference in heat-term LBW associations in the unadjusted (ie, not adjusted for season) and adjusted models (ie, adjusted for season) might suggest that the land-surface temperature could have been a surrogate for some other spatially varying exposure. However, our observed increase in the risk of term LBW associated with heat exposure is in-line with those of studies reporting seasonality in birth weight and LBW and associating heat with reduction in birth weight.34 Heat stress is a function of the interaction between internal heat production, ability for heat loss to the environment, and environmental heat load.35 During pregnancy, the increase in fat deposition and decrease in the ratio of body surface area to body mass (due to weight gain) result in less capacity for heat loss to the environment,35–37 making pregnant women more vulnerable to heat stress due to environmental heat load.35 Heat stress leads to the release of heat shock proteins (HSP) including HSP-70 in humans.38 Increased levels of HSP-70 have been linked to a range of adverse pregnancy outcomes, including reduction in birth weight.39 This reduction in birth weight is consistent with the suggested role of heat stress in the natural selection of body size and shape, in that reduction in birth weight could be an adaptation response to environmental heat load.35

Our findings for noise exposure were not conclusive. The available evidence on the impact of noise exposure on birth weight is based primarily on exposure to occupational or aircraft noise.40 Studies on the association between traffic-related noise exposure and term LBW are scarce and generally do not support such an association.41,42

Our observed associations for SGA were consistent with those of term LBW in terms of direction, but they were generally weaker for SGA. Although the use of SGA could result in a larger number of cases (ie, higher statistical power) compared with term LBW, applying SGA as an indicator of impaired fetal growth has been a source of concern.43 By definition, SGA is dependent on the applied growth curve. We used the only available growth curve applicable to our study sample, which was relatively old and did not have an ethnic composition that was comparable to our study population. Considering the descriptive nature of the SGA definition, SGA cases may include those who are genetically small compared with the rest of population.43 Furthermore, SGA relies on the weight distribution of infants born at a specific gestational age instead of the weight distribution of all fetuses at that gestational age.43 In our study population, the median gestational age for cases of term LBW (273 days) was shorter than that of cases of term SGA (282 days).

We are unaware of any previous report on the combined contribution of air pollution, heat, and noise or the buffering effect of road-adjacent tree coverage on the health effects of residential proximity to major roads in general or on pregnancy outcomes in particular. It is therefore not possible to compare these findings with others. Our measures of noise exposure did not seem to mediate the association between residential proximity to major roads and term LBW. Exposure to heat explained up to 8% of this association, whereas exposure to selected air pollutants explained up to about one-fourth of this association. These exposures jointly explained about one-third of this association, indicating that there should be potential mediator(s) other than those included in our analysis. The contribution of other mediators remains an open question for future studies. These mediators may include other air pollutants that are routinely monitored (eg, carbon monoxide) or those that are not routinely monitored (eg, ultrafine particles, volatile organic compounds, or polycyclic aromatic hydrocarbons), physical activity levels, or diet patterns, for which we did not have data. In addition to other possible mediators, the unexplained part our observed association between residential proximity to major roads and term LBW could be from possible misclassification of exposure, as discussed below.

We found some indications for a buffering effect of road-adjacent trees on the association between proximity to major roads and term LBW when we used binary distance. Such a buffering effect was not apparent when we applied continuous distance. Therefore, our findings regarding this buffering effect should be interpreted with caution. Hypothetically, such a buffering effect could be explained, at least in part, by the ability of road-adjacent trees to mitigate the traffic-related air pollution and heat11–13,44–46 (both of which we found to be associated with term LBW and to mediate our observed association between proximity to major roads and term LBW). However, the available evidence on the mitigating effect of road-adjacent trees on air pollution is not consistent, and there are some other reports that do not support such an effect.47,48

Our study faced some limitations, and our findings therefore require further confirmation by future studies. The number of cases of term LBW (n = 208) was relatively small. Our exposure assessments were based on ambient levels of air pollution, noise, and heat, which could overlook the potential variation between ambient and personal exposure levels. Our assessment of noise exposure, for example, was based on total ambient levels of noise, which overlooks the contribution of factors such as acoustic insulation of homes and the location of bedrooms. Furthermore, our assessment of exposure to air pollution, noise, and heat was based on the home address at the time of delivery, which did not account for possible maternal residential mobility during pregnancy. A study of 4 Spanish birth cohorts during 2003–2008 has reported a mobility rate between 1% and 6%.49

Using heat and noise maps and spatial estimates of air pollutant levels generated by land-use regression models, we effectively assumed that the city spatial surface and the spatial distribution of heat, noise, and air pollutants remained constant over the study period. There are some reports supporting the stability of the spatial contrasts for noise and air pollution in Europe and North America over a long period.50–54 Furthermore, to our knowledge, there was no major change in land use, emissions profiles, or traffic flow (eg, construction of new major roads and implementing new traffic rules) between the year of land-use regression model construction and the years of our study.

To assess exposure to heat, we used 3 land-surface temperature maps based on a Landsat 5 Thematic Mapper images. The lack of temporal component in our assessment of exposure to heat could have resulted in exposure misclassification; however, the adjustment of analyses for the season of conception should have, at least in part, addressed the temporal variability in exposure to heat. Furthermore, to investigate the impact of potential change in the spatial contrast of the heat over the study period (2001–2005) on our findings, we generated another land-surface temperature map using a Landsat 7 Enhanced Thematic Mapper Plus images captured on 26 June 2001 and included it in our measure of heat exposure. We repeated the analysis of the association between heat exposure and term LBW using this alternative measure of heat exposure (based on 4 land-surface temperature maps) and observed an OR of 1.16 (95% confidence interval = 0.96–1.41) for term LBW associated with an IQR increase (1.7°C) in exposure to heat.

In addition, there could be a difference in the degree of misclassification of exposures to our studied mediators. This difference could affect our findings of the mediating role of these exposures, in that those mediators with better exposure classification might explain more of the association compared with mediators with greater misclassification. Moreover, all our land-use regression models included some traffic-related predictors, which could have interfered in our analyses of mediator effect of air pollutants.

Our study showed an increased risk of term LBW associated with maternal residential proximity to major roads; this increased risk was partly mediated by exposure to air pollution and heat but not noise. There were some indications of a buffering effect of road-adjacent trees on the association between residential proximity to major roads and term LBW when we used binary distance, which should be interpreted with caution as these findings were not replicated using continuous distance. The results suggest that future studies of the health effects of residential proximity to major road should take account of potential exposures other than air pollution (eg, heat) and the potential buffering effect of road-adjacent trees. Moreover, our findings for heat exposure are relevant for assessing the possible health effects of predicted changes in future climate. Further studies are required to confirm our findings in other settings and to investigate the possible contribution of other mediators.

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REFERENCES

1. Nieuwenhuijsen MJ, Dadvand P, Grellier J, Martinez D, Vrijheid M. Environmental risk factors of pregnancy outcomes: a summary of recent meta-analyses of epidemiological studies. Environ Health. 2013; 12:6

2. Généreux M, Auger N, Goneau M, Daniel M. Neighbourhood socioeconomic status, maternal education and adverse birth outcomes among mothers living near highways. J Epidemiol Community Health. 2008; 62:695–700

3. Yorifuji T, Naruse H, Kashima S, et al. Residential proximity to major roads and placenta/birth weight ratio. Sci Total Environ. 2012; 414:98–102

4. Brauer M, Lencar C, Tamburic L, Koehoorn M, Demers P, Karr C. A cohort study of traffic-related air pollution impacts on birth outcomes. Environ Health Perspect. 2008; 116:680–686

5. Wilhelm M, Ritz B. Residential proximity to traffic and adverse birth outcomes in Los Angeles county, California, 1994-1996. Environ Health Perspect. 2003; 111:207–216

6. van den Hooven EH, Jaddoe VW, de Kluizenaar Y, et al. Residential traffic exposure and pregnancy-related outcomes: a prospective birth cohort study. Environ Health. 2009; 8:59

7. Kashima S, Naruse H, Yorifuji T, et al. Residential proximity to heavy traffic and birth weight in Shizuoka, Japan. Environ Res. 2011; 111:377–387

8. Moudon AV. Real noise from the urban environment: how ambient community noise affects health and what can be done about it. Am J Prev Med. 2009; 37:167–171

9. Asimakopoulos DN, Assimakopoulos VD, Chrisomallidou N, et al. Energy and Climate in the Urban Built Environment. 2001; London, UK James & James Ltd.

10. Boothe VL, Shendell DG. Potential health effects associated with residential proximity to freeways and primary roads: review of scientific literature, 1999-2006. J Environ Health. 2008; 70:33–41, 55

11. Nilsson K, Sangster M, Gallis C, et al. Forests, Trees and Human Health. Forests, Trees and Human Health. 2011; New York Springer

12. Baldauf R, Watkins N, Heist D, et al. Near-road air quality monitoring: factors affecting network design and interpretation of data. Air Qual Atmos Health. 2009; 2:1–9

13. Park M, Hagishima A, Tanimoto J, Narita K-I. Effect of urban vegetation on outdoor thermal environment: field measurement at a scale model site. Building Environ. 2012; 56:38–46

14. Figueras F, Meler E, Iraola A, et al. Customized birthweight standards for a Spanish population. Eur J Obstet Gynecol. 2008; 136:20–24

15. Beelen R, Hoek G. European Study of Cohorts for Air Pollution Effects (ESCAPE) Manuals. 2010; Utrecht

Available at: http://www.escapeproject.eu/manuals/index.php. Accessed 14 June 2012.


16. Yorifuji T, Naruse H, Kashima S, et al. Residential proximity to major roads and preterm births. Epidemiology. 2011; 22:74–80

17. Hoffmann B, Moebus S, Möhlenkamp S, et al. Residential exposure to traffic is associated with coronary atherosclerosis. Circulation. 2007; 116:489–496

18. Gilbert NL, Woodhouse S, Stieb DM, Brook JR. Ambient nitrogen dioxide and distance from a major highway. Sci Total Environ. 2003; 312:43–46

19. HEI Panel on the Health Effects of Traffic-Related Air Pollution Traffic-Related Air Pollution: A Critical Review of the Literature on Emissions, Exposure, and Health Effects. Special Report. 2010; Boston, Mass Health Effects Institute

20. Dadvand P, Figueras F, Basagaña X, et al. Ambient air pollution and preeclampsia: a spatiotemporal analysis. Environ Health Perspect. 2013; 121:1365–1371

21. Beelen R, Hoek G, Vienneau D, et al. Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe—the ESCAPE project. Atmos Environ. 2013; 72:10–23

22. Eeftens M, Tsai M-Y, Ampe C, et al. Spatial variation of PM2.5, PM10, PM2.5 absorbance and PM coarse concentrations between and within 20 European study areas and the relationship with NO2—results of the ESCAPE project. Atmos Environ. 2012; 62:303–317

23. Birk M, Ivina O, von Klot S, Babisch W, Heinrich J. Road traffic noise: self-reported noise annoyance versus GIS modelled road traffic noise exposure. J Environ Monit. 2011; 13:3237–3245

24. Havard S, Reich BJ, Bean K, Chaix B. Social inequalities in residential exposure to road traffic noise: an environmental justice analysis based on the RECORD Cohort Study. Occup Environ Med. 2011; 68:366–374

25. Departamento Control i Reducció de la Contaminació Acústica. Mapa Estratègic de Soroll de Barcelona. 2007; Barcelona, Spain Ajuntament de Barcelona

26. Townshend JRG, Carroll M, Dimiceli C, et al. Vegetation Continuous Fields MOD44B, 2002 Percent Tree Cover, Collection 5. 2001; College Park, Md University of Maryland

Available at: https://lpdaac.usgs.gov/sites/default/files/public/modis/docs/VCF_C5_UserGuide_Dec2011.pdf. Accessed 15 January 2013


27. Domínguez-Berjón MF, Borrell C, Cano-Serral G, et al. Construcción de un índice de privación a partir de datos censales en grandes ciudades españolas (Proyecto MEDEA) [Spanish]. Gac Sanit. 2008; 22:179–187

28. Spratt M, Carpenter J, Sterne JA, et al. Strategies for multiple imputation in longitudinal studies. Am J Epidemiol. 2010; 172:478–487

29. Vanderweele TJ, Vansteelandt S. Odds ratios for mediation analysis for a dichotomous outcome. Am J Epidemiol. 2010; 172:1339–1348

30. Carrascosa A, Yeste D, Copil A, et al. [Anthropometric growth patterns of preterm and full-term newborns (24–42 weeks’ gestational age) at the Hospital Materno-Infantil Vall d’Hebron (Barcelona)(1997–2002]. An Pediatr (Barc). 2004; 60:406–416

31. Eeftens M, Beelen R, de Hoogh K, et al. Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project. Environ Sci Technol. 2012; 46:11195–11205

32. Sapkota A, Chelikowsky AP, Nachman KE, Cohen AJ, Ritz B. Exposure to particulate matter and adverse birth outcomes: a comprehensive review and meta-analysis. Air Qual Atmos Health. 2012; 5:369–381

33. Dadvand P, Parker J, Bell M, et al. Particulate air pollution and fetal growth: a multi-country evaluation of effect and heterogeneity. Environ Health Perspect. 2013; 121:267–373

34. Strand LB, Barnett AG, Tong S. The influence of season and ambient temperature on birth outcomes: a review of the epidemiological literature. Environ Res. 2011; 111:451–462

35. Wells JC, Cole TJ. Birth weight and environmental heat load: a between-population analysis. Am J Phys Anthropol. 2002; 119:276–282

36. Falk B. Effects of thermal stress during rest and exercise in the paediatric population. Sports Medicine. 1998; 25:221–240

37. Wells JC. Thermal environment and human birth weight. J Theor Biol. 2002; 214:413–425

38. Daugaard M, Rohde M, Jäättelä M. The heat shock protein 70 family: highly homologous proteins with overlapping and distinct functions. FEBS Lett. 2007; 581:3702–3710

39. Hnat MD, Meadows JW, Brockman DE, et al. Heat shock protein-70 and 4-hydroxy-2-nonenal adducts in human placental villous tissue of normotensive, preeclamptic and intrauterine growth restricted pregnancies. Am J Obstetr Gynecol. 2005; 193:836–840

40. Figà-Talamanca I. Occupational risk factors and reproductive health of women. Occup Med. 2006; 56:521–531

41. Wu T-N, Chen L-J, Lai J-S, et al. Prospective study of noise exposure during pregnancy on birth weight. Am J Epidemiol. 1996; 143:792–796

42. Hohmann C, Grabenhenrich L, de Kluizenaar Y, et al. Health effects of chronic noise exposure in pregnancy and childhood: a systematic review initiated by ENRIECO. Int J Hyg Environ Health. 2013; 216:217–229

43. Ritz B, Wilhelm M. Ambient air pollution and adverse birth outcomes: methodologic issues in an emerging field. Basic Clin Pharmacol Toxicol. 2008; 102:182–190

44. Givoni B. Impact of planted areas on urban environmental quality: a review. Atmos Environ. 1991; 25:289–299

45. Amorim JH, Valente J, Cascão P, et al. Pedestrian exposure to air pollution in cities: modeling the effect of roadside trees. Advan Meteorol. 2013;

46. Dadvand P, de Nazelle A, Triguero-Mas M, et al. Surrounding greenness and exposure to air pollution during pregnancy: an analysis of personal monitoring data. Environ Health Perspect. 2012; 120:1286–1290

47. Baldauf R, Jackson L, Hagler G, et al. The role of vegetation in mitigating air quality impacts from traffic emissions. EM. 2011; 1–3

48. Hagler GS, Lin MY, Khlystov A, et al. Field investigation of roadside vegetative and structural barrier impact on near-road ultrafine particle concentrations under a variety of wind conditions. Sci Total Environ. 2012; 419:7–15

49. Estarlich M, Ballester F, Aguilera I, et al. Residential exposure to outdoor air pollution during pregnancy and anthropometric measures at birth in a multicenter cohort in Spain. Environ Health Perspect. 2011; 119:1333–1338

50. Eeftens M, Beelen R, Fischer P, Brunekreef B, Meliefste K, Hoek G. Stability of measured and modelled spatial contrasts in NO(2) over time. Occup Environ Med. 2011; 68:765–770

51. Cesaroni G, Porta D, Badaloni C, et al. Nitrogen dioxide levels estimated from land use regression models several years apart and association with mortality in a large cohort study. Environ Health. 2012; 11:48

52. Babisch W. Transportation noise and cardiovascular risk: updated review and synthesis of epidemiological studies indicate that the evidence has increased. Noise Health. 2006; 8:1–29

53. Gulliver J, de Hoogh K, Hansell A, Vienneau D. Development and back-extrapolation of NO2 land use regression models for historic exposure assessment in Great Britain. Environ Sci Technol. 2013; 47:7804–7811

54. Wang R, Henderson SB, Sbihi H, Allen RW, Brauer M. Temporal stability of land use regression models for traffic-related air pollution. Atmos Environ. 2013; 64:312–319

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