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Short-term Impact of Ambient Air Pollution and Air Temperature on Blood Pressure Among Pregnant Women

Hampel, Reginaa; Lepeule, Johannab,c; Schneider, Alexandraa; Bottagisi, Sébastienb,c; Charles, Marie-Alined,e; Ducimetière, Pierref; Peters, Annettea; Slama, Rémyb,c

doi: 10.1097/EDE.0b013e318226e8d6
Air Pollution

Background: Epidemiologic studies have reported inconsistent findings for the association between air pollution levels and blood pressure (BP), which has been studied mainly in elderly subjects. Short-term air pollution effects on BP have not been investigated in pregnant women, who may constitute a vulnerable population.

Methods: Between 2002 and 2006, 1500 pregnant women from a mother-child cohort study conducted in Nancy and Poitiers, France, underwent 11,220 repeated BP measurements (average, 7.5 measurements/woman). Nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter below 10 μm (PM10), and meteorologic variables were measured on an hourly basis at permanent monitoring sites. We studied changes of BP in relation to short-term variations of air pollution and temperature with mixed models adjusted for meteorologic and personal characteristics.

Results: A 10°C decrease in temperature led to an increase in systolic BP of 0.5% (95% confidence interval = 0.1% to 1.0%). Elevated NO2-levels 1 day, 5 days and averaged over 7 days before the BP measurement were associated with reduced systolic BP. The strongest decrease was observed for the 7-day NO2 average (−0.4% [−0.7% to −0.2%] change for an 11 μg/m3 increase in NO2). PM10 effects on systolic BP differed according to pregnancy trimester: PM10 concentration was associated with systolic BP increases during the first trimester and systolic BP decreases later in pregnancy.

Conclusions: We observed short-term associations of air pollution and of temperature with BP in pregnant women. Whether such changes in BP have clinical implications remains to be investigated.

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From the aHelmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany; bInserm, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Institut Albert Bonniot (U823), BP170, Grenoble, France; cGrenoble University, Institut Albert Bonniot, Grenoble, France; dINSERM, U1018, CESP Centre for research in Epidemiology and Population Health, Team “Epidemiology of obesity, diabetes and renal disease: lifelong approach” Villejuif, France; eUniversité Paris Sud 11, UMRS 1018, F-94807, Villejuif, France; and fINSERM Villejuif, France.

Submitted 16 November 2010; accepted 6 April 2011; posted 6 July 2011.

Supported by a grant from ANSES (French Agency for food, environment and occupation health safety, call EST-Environment Santé Travail, Eden-Air Plus project). The Eden cohort is funded by the Foundation for Medical Research (FRM), Inserm, IReSP, Nestlé, French Ministry of Health, National Research Agency (ANR), Univ. Paris-Sud, Institute of Health Monitoring (InVS), ANSES, MGEN, AFSSA. The team of Environmental Epidemiology (Inserm U823) is supported by an AVENIR grant from Inserm.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com).

Correspondence: Regina Hampel, Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology II, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany. E-mail: regina.hampel@helmholtz-muenchen.de.

There is evidence of an association between increased ambient air pollution levels and adverse cardiovascular health effects.1,2 As high blood pressure (BP) is a risk factor for cardiac diseases, researchers have also investigated the influence of air pollution on BP, but with inconsistent findings.3–7 Most of these epidemiologic studies were carried out in elderly participants, with or without underlying cardiovascular diseases. Very little attention has been given to effects on BP of pregnant women.8

Pregnant women may constitute a particularly susceptible population because of possible consequences for the fetus of any air pollution effect on maternal cardiovascular health.9 Pregnancy is associated with major changes in maternal cardiovascular and endothelial function. In particular, among primipara, by gestational week 34, plasma volume increases by 50%. The increase in red blood cell mass is more limited, resulting in a physiologic anemia and reduced blood viscosity that creates a lower resistance to blood flow, and a thrombophilic state is induced. Cardiac output increases, although not enough to counterbalance the physiologic vasodilatation, and so a reduction in BP usually occurs.9 Given these physiologic changes, the impact of air pollution on BP in pregnant women might differ from that among nonpregnant women. Furthermore, the sensitivity of the cardiovascular function of pregnant women to air pollution effects might vary during the course of pregnancy.

The question of air pollution effects on the cardiovascular function of pregnant women is also of interest in the context of the reported associations between air pollution and adverse pregnancy outcomes such as preterm birth and fetal growth.10,11 Changes in the BP of pregnant women may alter maternal-placental oxygen and nutrient exchanges, and thereby alter fetal growth, as previously hypothesized.12

The objective of our study was to analyze short-term effects of air pollution on BP in healthy pregnant women. As a secondary objective, we also aimed at characterizing possible effects of air temperature on BP during pregnancy.13,14

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METHODS

Study Population and Clinical Measurements

This study was conducted in a subgroup of the EDEN (study of pre- and early postnatal determinants of the child's development and health) mother–child cohort.11,15,16 The primary aim of this cohort is the investigation of prenatal and early postnatal nutritional, environmental, and social determinants of children's development and health. Between February 2003 and January 2006, pregnant women were recruited within 24 weeks of last menstrual period in obstetrical departments of the University Hospitals in Poitiers and Nancy, France. Exclusion criteria were multiple pregnancies, intention to deliver outside the University Hospital or to move out of the study region within the next 3 years, and inability to speak French. Among women who fulfilled these inclusion criteria, 55% agreed to participate (n = 2002). Between December 2002 and July 2006, 1871 of these women participated in up to 12 repeated antenatal visits as part of the normal follow-up of the pregnancy, and the corresponding information was extracted from the obstetric records. (Some of these visits took place before the start of the recruitment period.) Only women without hypertension before pregnancy and who had information on at least 2 visits were included in our analyses. Characteristics such as weight before pregnancy, number of previous pregnancies, disease, and smoking history were collected from the maternity records and by specific questionnaires during pregnancy. At each visit, systolic and diastolic BP were measured. Visit dates but not times were recorded. The study was approved by the relevant ethical committees (Comité Consultatif pour la Protection des Personnes dans la Recherche Biomédicale, Le Kremlin-Bicêtre University hospital, and Commission Nationale de l'Informatique et des Libertés). All women gave written consent.

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Meteorologic and Air Pollution Data

Meteorologic variables (air temperature, relative humidity, and barometric pressure) were assessed hourly at one central site in each city (Météo France). Nitrogen dioxide (NO2) and particulate matter with an aerodynamic diameter ≤10 μm (PM10) were measured on an hourly basis at 28 NO2 and 19 PM10 permanent background-monitoring sites (eFigure 1, http://links.lww.com/EDE/A490) by the air-quality-monitoring networks from Nancy (Airlor) and Poitiers (Atmo-PC). PM10 was measured by Tapered Element Oscillating Microbalance (TEOM) devices. Air pollution measurements of the monitoring station located closest to the woman's home address were used. Information on any residential move was available throughout the study period. Changes in home address were taken into account for exposure assessment. Analyses were restricted to women living less than 20 km from an air-quality-monitoring station. Twenty four-hour averages of air pollutants and meteorologic variables were calculated for the period before each BP measurement for each woman. We assumed that each visit took place at 8:00 am, and we averaged air pollution levels from 9:00 am one day before the visit up to 8:00 am on the day of the visit (lag 0). Additionally, averages 24 to 47 hours (lag 1), 48 to 71 hours (lag 2), 72 to 95 hours (lag 3), 96 to 119 hours (lag 4), 120 to 143 hours (lag 5), and 144 to 167 hours (lag 6) before 8:00 am on the day of the visit were estimated, as well as a 7-day average. In sensitivity analyses, we also tested the association between air pollution levels estimated by a dispersion model and BP. This model incorporated hourly meteorologic data, traffic, industrial, and other urban sources in Nancy and Poitiers urban areas, as well as hourly background air pollution levels measured from monitoring stations, and was implemented using ADMS-Urban software (CERC, Cambridge, United Kingdom).

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Statistical Analyses

The longitudinal data were analyzed with SAS statistical package (version 9.1; SAS Institute Inc, Cary, NC) using additive mixed regression models with a compound symmetry covariance structure and a random intercept accounting for variations in individual BP levels between women. Selection of adjustment factors was conducted separately for systolic BP and diastolic BP. The following patient characteristics were all included in regression models: age, body mass index (BMI) before pregnancy, gestational age, number of previous pregnancies (none, 1, ≥2), smoking, and passive smoking. We defined woman-specific variables for smoking or passive smoking in the first trimester of pregnancy, as well as visit-specific variables for smoking or passive smoking during the trimester when the visit took place. Variables for active smoking were coded linearly (number of smoked cigarettes), categorically (0, 1–10, 11–20, >20 cigarettes), or as an indicator (yes vs. no). Only single variables for smoking and passive smoking were entered in each regression model, selecting the variables that minimized Akaike's Information Criterion (AIC). Models on air pollutant effects were additionally adjusted for long-term time trends (counts of the days during the study period, to take into account seasonal variations in BP), air temperature, and relative humidity. Barometric pressure and day of the week were included only if they decreased AIC. For continuous confounders, the shape (linear, polynomial, or restricted cubic spline) and the lag (for meteorologic variables) that minimized AIC were chosen. When investigating the effects of temperature, we adjusted models for the same clinical characteristics and with the same shape of long-term time trend as used in the air pollution models. Additionally, we included relative humidity and barometric pressure with the same lag as the analyzed temperature lag. We tested the shape of the association between temperature and BP by coding temperature with restricted cubic splines. There was no evidence for a deviation from linearity for the relationship between temperature and BP so that temperature was included as a linear term in final models.

Linear effects of temperature and air pollution levels were estimated in adjusted mixed models, including one exposure lag at a time. For each monitoring station, interquartile ranges (IQR) of air pollution measurements during the study period and the median of these station-specific IQRs were calculated for NO2 and PM10 using 24-hour and 7-day averages. Associations are presented as percent changes of the outcome mean per median IQR increase in air pollutant or per 10°C decrease in temperature, as in previous studies of temperature effects on cardiovascular health.17,18

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Effect Modification

In further analyses, categorical interaction variables were added to the models to estimate whether temperature and air pollution effects were modified by specific characteristics. Potential effect modifiers were center (Nancy vs. Poitiers), smoking in the first trimester of pregnancy (yes vs. no), season (April–September vs. October–March), and trimester of pregnancy at the time of the examination (1st vs. 2nd vs. 3rd trimester). Trimester of pregnancy was considered a potential effect modifier because of the important changes in cardiovascular function throughout pregnancy.9

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Sensitivity Analyses

We repeated the estimation of temperature effects adjusting for NO2 or PM10 levels (with the same lag as the temperature lag). To check the robustness of the estimated air pollution effects, we conducted several sensitivity analyses: (1) Instead of using the time lags of meteorologic variables leading to the best model fit, we included meteorologic variables with the same lag as the analyzed air pollution lag. (2) We excluded visits that took place on the weekend, assuming that these were unplanned visits due to concerns of the women. (3) We excluded women who developed gestational diabetes. (4) We restricted our analyses to women living within 10 km, 5 km, or 1 km from the closest air-quality-monitoring station. (5) Instead of a mixed model with compound symmetry, we used a “spatial” covariance structure.19 The elements of this covariance matrix decrease with increasing elapsed time between 2 visits. (6) Instead of using the air pollution measurements of the station closest to the woman's home address, we used an alternative exposure metric that averaged measurements of several monitoring sites in 3 areas: the urban and the suburban background (20-km buffer around the center, excluding the urban area) of Nancy, and the urban background (20-km buffer around the center) of Poitiers. Missing values on the aggregated level were replaced as described by Berglind et al.20 Averages were calculated only for women living within 20 km from the city centers of Nancy or Poitiers. (7) In a further sensitivity analysis regarding exposure modeling, we characterized the association between 7-day averages of NO2 and PM10 levels estimated with a dispersion model and BP.

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RESULTS

Study Population and Clinical Measurements

Of the 1871 women with repeated antenatal visits, we excluded 37 women (2%) who had hypertension before pregnancy and 61 women (3%) with missing values in clinical characteristics. We also excluded 273 women (15%) because they lived more than 20 km from the closest PM10 and NO2 monitoring stations. The remaining 1500 women had 11,220 visits (mean: 7.5 visits/woman, 5th–95th percentiles: 4–11 visits/woman) with BP measurements. The time elapsed between 2 consecutive visits was on average 27 days (5th–95th percentiles: 5–43 days).

Table 1 describes the clinical characteristics of the participants. Average diastolic BP was lower in Nancy compared with Poitiers, whereas systolic BP was higher in Nancy. The differences in BP between the study centers remained after adjustment for patient characteristics and meteorologic variables (data not shown). Mean values of systolic and diastolic BP were 117.0 mm Hg (standard deviation (SD) = 12.9) and 64.9 mm Hg (9.2), respectively, in winter, and 116.3 mm Hg (12.3) and 65.1 mm Hg (9.2) in summer, respectively. Averaged systolic BP measurements were lower during the second trimester of pregnancy (mean = 115.4 mm Hg [SD = 12.2]) compared with the first (118.2 mm Hg [13.0]) and third trimesters (117.2 mm Hg [12.8]). The same pattern was observed for diastolic BP (data not shown).

TABLE 1

TABLE 1

Table

Table

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Meteorologic and Air Pollution Data

A description of the 24-hour averages of meteorologic and air pollution variables for each monitoring site can be found in eTable 1 (http://links.lww.com/EDE/A490). Medians of these site-specific descriptive measures are shown in Table 2. Mean temperature in summer was 16.5°C and in winter 5.4°C.

TABLE 2

TABLE 2

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Air Temperature and Blood Pressure

A 10°C decrease in temperature was associated with an immediate (lag 0) increase in systolic BP by 0.5% (95% confidence interval [CI = 0.1% to 1.0%]) and a delayed (lag 6) increase in systolic BP by 0.4% (0.0% to 0.9%) (Fig. 1A). These percent changes correspond to an immediate increase in systolic BP of 0.6 mm Hg (0.1 to 1.1 mm Hg) and a delayed increase of 0.5 mm Hg (0.0 to 1.0 mm Hg) in association with a 10°C decrease in temperature. When we additionally adjusted for NO2, the sample size decreased by about 10% but temperature effects were stronger for lags 1, 2, and 5 and for the 7-day average (Fig. 1A). Temperature effects on systolic BP were not affected by adjustment for PM10 (data not shown). For all time lags, temperature effects were much stronger in April–September than in October–March (Fig. 1B). We observed no main effects of temperature on diastolic BP, but interaction analyses revealed a statistically significant increase in diastolic BP in association with temperature decrements in summer (data not shown). Temperature effects were not modified by center, smoking, or trimester of pregnancy.

FIGURE 1.

FIGURE 1.

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Air Pollution and Blood Pressure

The medians of the station-specific interquartile ranges for 24-hour and 7-day averages were 14.4 and 11.4 μg/m3, respectively, for NO2 and 11.3 and 7.7 μg/m3 for PM10, respectively. Figure 2A shows the associations between NO2 and systolic BP, adjusted for the variables listed in eTable 2 (http://links.lww.com/EDE/A490). An IQR increase in NO2 in the 24 hours preceding the visit was associated with a change in systolic BP of −0.3% (−0.5% to −0.1%) or −0.4 mm Hg (−0.6 to −0.1 mm Hg). Similar decreases were also observed with lags of 1, 5, and 6 days. Increases in the 7-day average for both NO2 (−0.4% [−0.7% to −0.2%] or −0.5 mm Hg [0.8% to −0.2% mm Hg]) and PM10 (−0.3% [−0.5% to 0.0%] or −0.3 mm Hg [−0.6% to 0.0%]) were associated with the strongest reductions in SBP. Effect estimates for NO2 on systolic BP seemed to be stronger than PM10 effects in analyses considering pregnancy as a whole. We detected no clear associations between air pollutants and diastolic BP (Fig. 2B).

FIGURE 2.

FIGURE 2.

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Effect Modification of Air Pollution Effects

Air pollution effect estimates were similar for the 2 cities (eFigure 2, http://links.lww.com/EDE/A490). There was a consistent pattern of effect modification by season, with a tendency to weaker negative effects of air pollutants in the April–September, compared with the October–March periods (Fig. 3A–3B). This effect modification reached statistical significance only for PM10 concentrations with a 2-day lag (−0.3% [−0.7% to −0.0%] in October–March versus 0.1% [−0.2% to 0.5%] in April–September, P value of interaction = 0.04). NO2 effects on systolic BP tended to be more pronounced in nonsmoking compared with smoking women (lowest P value of interaction = 0.12; eFigure 3, http://links.lww.com/EDE/A490).

FIGURE 3.

FIGURE 3.

We detected a strong modification of PM10, but not of NO2 effects, on systolic BP by trimester of pregnancy (Fig. 3C–D). The strongest modification was observed with the 4-day lag, which showed a 1.0% (0.5% to 1.5%) change in systolic BP associated with PM10 during the first trimester and changes of −0.3% (−0.6% to 0.0%) and −0.2% (−0.6% to 0.2%) during the second and third trimesters, respectively (P value of interaction <0.001).

Increases in PM10 (lag 0) were associated with a positive change in diastolic BP during the first trimester (1.1% [0.3% to 1.8%]), little change during the second trimester (0.2% [−0.3% to 0.8%]), and a negative change during the third trimester (−0.5% [−0.9% to 0.0%]).

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Sensitivity Analyses

Air pollution effects were similar when we included meteorologic variables with the same lag as the analyzed air pollution lag, after the exclusion of visits during the weekend or of the 46 women who developed gestational hypertension (data not shown). NO2 effects (lags 0, 1, and 2) slightly strengthened when we reduced the study population to women living ≤10 km from the closest monitoring station (NO2 effects with a lag of 0, 1, and 2 days were −0.4% [−0.6% to −1.5%], −0.3% [−0.6% to −0.1%], and −0.3% [−0.5% to −0.0%], respectively) or within 5 km (−0.4% [−0.7% to −0.2%], −0.4% [−0.7% to −0.1%], and −0.4% [−0.6% to −0.1%]) (eFigure 4A, http:links.lww.com/EDE/A490). When we included only the 220 women (with 1439 systolic BP measurements) living within a radius of 1 km to the closest NO2 station, no associations were observed and CIs were considerably widened. PM10 effect estimates did not change when we included only women living closer to the next monitoring station, but CIs widened (not shown). The air pollution effects on systolic BP were not altered when we used a spatial instead of a compound symmetry covariance structure. In the case of diastolic BP, convergence problems occurred, and a comparison between the models with different covariance structures was not possible. Using averaged air pollution measurements of several monitoring stations resulted in a smaller sample size but similar air pollution effects (eFigure 4B, http://links.lww.com/EDE/A490). Dispersion model estimates were available for 1155 women (eFigure 5, http://links.lww.com/EDE/A490). Seven-day averages of NO2 estimated with the dispersion model exhibited a similar (somewhat weaker) association with BP than when estimated with the closest station approach, with wider CIs. When the entire duration of pregnancy was considered, the effect of PM10 on systolic BP was stronger with the dispersion approach compared with the closest-station approach (eFigure 6, http://links.lww.com/EDE/A490). We found no interaction between trimester and PM10 when using the dispersion model (P value of interaction = 0.37, compared with P < 0.001 using the closest-station approach).

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DISCUSSION

In our cohort of healthy pregnant women with no previous history of hypertension, we observed short-term reductions in systolic BP in association with increasing NO2 levels. This association was detected in all 3 trimesters of pregnancy. PM10 concentrations were positively associated with systolic and diastolic BP in the first trimester of pregnancy and tended to be negatively associated with both measures of BP later in pregnancy. This was not found with the alternative (dispersion) exposure model. We detected a short-term increase in systolic BP associated with decrements in temperature. These temperature effects persisted after adjustment for NO2, indicating at least partially independent associations of temperature and air pollution with systolic BP. The lack of associations between either temperature or air pollution and diastolic BP might be because diastolic BP is less accurately assessed than systolic BP.

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Air Temperature and Blood Pressure

Elderly participants exhibit a higher BP in winter than in summer.13,21 We observed a slightly higher systolic BP in winter among pregnant women; air temperature effects on BP were more pronounced in summer. Among adults aged 35–64 years, Barnett et al14 reported an increase in average systolic BP of 0.19 mm Hg in association with a 1°C decrease in temperature. We also observed an immediate but weaker increase in systolic BP of 0.06 mm Hg with a 1°C decrease in temperature. Halonen et al22 reported increases in systolic BP of 0.6%–1.3% associated with decreases in apparent temperature among elderly men living in Boston. Furthermore, they detected elevated diastolic BP levels associated with decreases in air temperature and apparent temperature. However, in these studies, effects of apparent temperature might also partly reflect the association between relative humidity (or air pollution) and BP. Temperature effects in our study were weaker, and we did not find an association with diastolic BP.

Seasonal variation in BP might be explained by changes in blood viscosity favoring a decreased systemic pressure in summer compared with colder seasons.23 Furthermore, exposure to cold temperatures may activate the sympathetic nervous system and increase secretion of catecholamine. This possibly results in an increased heart rate and peripheral vascular resistance, and thus to increased BP with lower temperature.13,23

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Air Pollution and Blood Pressure

The association between air pollution and BP has been characterized mainly in elderly participants5,24,25 and in people with underlying cardiovascular diseases.3,4,7 Findings are not consistent, perhaps due to misclassification of BP, differing confounder adjustment, or random associations because of multiple testing. Exposure misclassification and diversity in chemical composition of PM might also contribute to the inconsistent findings. Accordingly, Brook et al26 found no association of BP with PM2.5 estimated by ambient monitors, but did with personally measured PM2.5 levels. Only one study, based on Generation R cohort,8 has investigated the influence of air pollution on BP in pregnant women. BP was estimated once per trimester and exposure was averaged over each trimester of pregnancy. The Generation R study contrasts with ours by its focus on longer-term effects of air pollution, and on between-subject rather than within-subject variations in exposure. Van den Hooven and colleagues8 observed a positive association between trimester averages of PM10 and systolic BP only in the second and third trimesters of pregnancy; we observed a positive association with 1-day to 1-week PM10 averages only in the first trimester. Since the PM10 effect based on our dispersion model was not modified by trimester of pregnancy, the increase in systolic BP associated with first trimester PM10 levels from the closest station in our study should be considered with caution. Disregarding issues related to exposure misclassification, the gradual and profound changes in cardiovascular function during pregnancy27 make it plausible that environmental stressors could have different effects during different trimesters of pregnancy. Although we detected negative short-term NO2 effects on systolic BP, van den Hooven et al8 found an elevated systolic BP in association with trimester-specific NO2 increases. Differences in time scale and design make comparisons between these 2 studies difficult; taken together (and assuming that these findings cannot be explained by biases), these studies suggest that air pollutants could have different effects on the shorter- and longer-terms. Differences such as those between estimated effects of NO2 and PM10 are common in air pollution epidemiology. Such differences might be explained by the fact that these pollutants capture different dimensions of atmospheric pollutants, with PM10 coming in primarily from long-range pollution while NO2 levels come from predominantly local sources.

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Potential Mechanisms

A positive association between PM and BP could be mediated by an activation of the sympathetic nervous system due to a stimulation of nerve endings in the human airways by inhaled particles.2 Furthermore, PM might trigger a systemic inflammation and oxidative reactions promoting vascular dysfunction.2 An inhalation chamber study with 27 participants found an increase in the endothelium-dependent vasoconstrictor endothelin-1 induced by diesel exhaust particles.28 Ultrafine particles, which are usually highly correlated with NO2, can pass alveolar walls and might directly influence endothelial cell structure and endothelial function, possibly leading to vasoconstriction and increased BP.2,29

Other authors have raised alternative hypotheses to explain a negative association between air pollution levels and BP. Cheng et al,30 who found a decreased BP in hypertensive rats exposed to concentrated particles, suggested that particles may cause airway irritation leading to increases of parasympathetic tone of the heart and peripheral vascular system. This hypothesis is supported by Zareba et al,31 who exposed 12 participants to ultrafine particles and observed such changes in electrocardiogram parameters as QT-shortening and ST-elevation, indicating an increase in parasympathetic tone.

Whether one of these mechanisms could apply to pregnant women remains to be investigated. Indeed, pregnant women are a very specific population. Pregnancy-related changes include hormonal changes, increases in blood volume and heart rate over the course of pregnancy, and decreasing BP in the second trimester of pregnancy.27 For these reasons, pregnant women may have different susceptibility to air pollution than nonpregnant and elderly subjects, and our results cannot be generalized to the whole population. Additionally, these considerable cardiac and hormonal changes throughout pregnancy could modify air pollution effects throughout pregnancy, as supported by the possible effect modification of PM10 by trimester of pregnancy in our population.

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Implications

Changes in BP might act as an intermediate step between exposure to air pollution and adverse pregnancy outcomes, such as preterm birth and reduced fetal growth.11 Warland and McCutcheon32 reviewed the association between hypotension and poor pregnancy outcomes and concluded that low BP might result in preterm birth, perinatal mortality, and low birth weight. However, Zhang and Klebanoff33 suggested that the association between low BP during pregnancy and poor perinatal outcomes is due to confounding by other risk factors. Consequently, it is unclear whether the decreases in systolic BP reported in our study in association with air pollution could affect pregnancy outcome. High BP during pregnancy is a risk factor for preterm birth and low birth weight,34,35 and an increase in systolic BP in the first trimester associated with PM10 might have consequences for pregnancy outcomes.

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Strengths and Limitations

The main strength of our study is the large number of women who participated in repeated BP measurements. This enabled us to analyze intraindividual variations in BP, avoiding bias due to potential confounders constant over time. A further strength is the availability of clinical characteristics, allowing us to efficiently control for these variables and perform subgroup analyses. BP is a highly variable parameter which is affected by such characteristics as age, medication, smoking, and weather. However, we could control our models for most of these factors. Moreover, we performed several sensitivity analyses that did not change our findings. A limitation is the lack of information on the exact times of BP measurements. BP has its own diurnal rhythms. This is unlikely to have induced confounding but may have caused exposure misclassification. The extent of misclassification is probably limited for the 7-day exposure averages, because these averages are unlikely to differ strongly if they end at 8 am or, say, 3 pm on the visit day. Only ambient exposure was measured, although people usually spend a lot of time indoors. NO2 effects tended to vary according to the buffer size considered around monitoring stations. Because population size varied with buffer size, the relative contribution of exposure misclassification and selection effects to these variations in estimated NO2 effects cannot easily be determined.

In conclusion, we observed a reduced systolic BP in pregnant women in association with elevated levels of NO2 and third trimester PM10 levels, and an increased systolic BP with higher PM10 levels during the first trimester of pregnancy. The consequences of such BP effects on pregnancy-related outcomes require further investigations. Additionally, our study observed decreases in systolic BP with increasing temperatures.

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ACKNOWLEDGMENTS

We thank the midwife research assistants (L. Douhaud, S. Bedel, B. Lortholary, S. Gabriel, M. Rogeon, and M. Malinbaum) for data collection; P. Lavoine for checking, coding, and data entry; J. Cyrys and S. von Klot for advice in exposure assessment; and S. Breitner for support in statistical analyses. We also thank Agnès Hulin, Fabrice Caïni (Atmo Poitou-Charentes), and Julien Galineau (Airlor) for the implementation of the dispersion model; and Lise Giorgis-Allemand (INSERM) for her statistical help.

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