Maternal exposure to ambient air pollutants and risk of congenital anomalies

ARTICLE IN PRESS Environmental Research 109 (2009) 181–187

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Maternal exposure to ambient air pollutants and risk of congenital anomalies$ Judith Rankin a,, Tom Chadwick a, Malathi Natarajan b, Denise Howel a, Mark S. Pearce a, Tanja Pless-Mulloli a a b

Institute of Health and Society, Newcastle University, Framlington Place, Newcastle upon Tyne NE2 4HH, UK Newcastle Primary Care Trust, Newcastle upon Tyne, UK

a r t i c l e in fo

abstract

Article history: Received 10 July 2008 Received in revised form 30 October 2008 Accepted 17 November 2008

Studies have suggested an association between maternal exposure to ambient air pollution and risk of congenital anomaly. The aim of this study is to investigate the association between exposure to black smoke (BS; particulate matter with aerodynamic diameter o4 mg/m3) and sulphur dioxide (SO2) during the first trimester of pregnancy and risk of congenital anomalies. We used a case–control study design among deliveries to mothers resident in the UK Northern health region during 1985–1990. Case data were ascertained from the population-based Northern Congenital Abnormality Survey and control data from national data on all births. Data on BS and SO2 from ambient air monitoring stations were used to average the total pollutant exposure during the first trimester of pregnancy over the daily readings from all monitors within 10 km of the mother’s residence. Logistic regression models estimated the association via odds ratios. A significant but weak positive association was found between nervous system anomalies and BS (OR ¼ 1.10 per increase of 1000 mg/m3 total BS; 95% CI: 1.03, 1.18), but not with other anomaly subtypes. For SO2, a significant negative association was found with congenital heart disease combined and patent ductus arteriosus: OR significantly o1 for all quartiles relative to the first quartile. The relationship between SO2 levels and other anomaly subtypes was less clear cut: there were either no significant associations or a suggestion of a U-shaped relationship (OR significantly o1 for moderate compared to lowest levels, but not with high SO2 levels). Overall, maternal exposure to BS and SO2 in the Northern region had limited impact on congenital anomaly risk. Studies with detailed exposure assessment are needed to further investigate this relationship. & 2008 Elsevier Inc. All rights reserved.

Keywords: Air pollution Particulate matter Sulphur dioxide Congenital anomalies Non-chromosomal anomalies Cardiovascular anomalies Environmental public health

1. Introduction Evidence reporting associations between maternal exposure to ambient air pollutants and adverse fetal development, in particular growth restriction, pre-term birth, and infant survival due to postneonatal respiratory mortality, has been growing rapidly in recent years (Glinianaia et al., 2004a, b; Sram et al., 2005). The association between maternal exposure to ambient air pollution and the risk of congenital anomalies, on the other hand, has been less well studied. Congenital anomalies are a significant cause of stillbirth and infant mortality, and are important contributors to childhood morbidity. The precise aetiology of most congenital anomalies is not fully

$ Funding: NorCAS is funded by the UK Department of Health Policy Research Programme and JR by a Personal Award Scheme Career Scientist Award from the National Institute of Health Research.  Corresponding author. Fax: +44 191 222 8211. E-mail address: [email protected] (J. Rankin).

0013-9351/$ - see front matter & 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.envres.2008.11.007

understood but is likely to involve both genetic and environmental factors. To date, only five studies have investigated the association of maternal exposure to air pollution and congenital anomaly risk (Antipenko and Kogut, 1993; Ritz et al., 2002; Gilboa et al., 2005; Kim et al., 2007; Dolk H, unpublished data). Although the epidemiological evidence is limited at present, these studies suggest an increase in congenital anomaly risk, particularly cardiovascular anomalies, with maternal exposure to air pollution. We have used a case–control study design to investigate whether maternal exposure to black smoke (BS; particulate matter with aerodynamic diameter of 4 mg/m3 or less) and sulphur dioxide (SO2) is associated with an increase in risk for selected congenital anomalies in a cohort of infants and fetuses delivered in the Northern Region during 1985–1990. Data was extracted from a population-based register of congenital anomalies, the Northern Congenital Abnormality Survey (NorCAS), from national data on registered births and from the network of

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ambient air pollution monitoring stations in the Northern region of the UK.

2. Materials and methods 2.1. Study population All cases of congenital anomaly delivered between 1 January 1985 and 31 December 1990 were abstracted from the NorCAS. The NorCAS is a voluntary collaborative survey which collects data prospectively on all congenital anomalies arising within the population of about three million living in the former Northern National Health Service (NHS) Health Region of England (as defined by 1972 NHS boundaries) and an average of 36,000 annual births during the study period. This region comprises the counties of Cleveland, Durham, North Cumbria, Northumberland and Tyne and Wear, with two main urban conurbations and extended rural areas (Fig. 1).

2.2. Case definition, classification, and ascertainment The NorCAS collects data on all congenital anomalies arising within the population of the Northern region whether occurring as late miscarriages (gestational ageX20 weeks), terminations of pregnancy for fetal anomaly following prenatal diagnosis or registered births (live and stillbirths) and whether diagnosed antenatally or not. This applies to all cases born to mothers resident at birth within the boundaries of the former Northern Region even if they were delivered outside the region. Cases are notified to the register from multiple sources including antenatal ultrasound, fetal medicine records, cytogenetic laboratories, the regional cardiology centre, pathology departments and paediatric surgery to ensure a high case ascertainment. All cases of congenital heart disease (CHD) are confirmed by autopsy, surgery, echocardiography, or cardiac catheterization. Once notified, cases are checked for duplication and then entered onto the register. Further details of data collection have been published previously (Richmond and Atkins, 2005). The age limit for registration onto NorCAS during the study period was 16 years. NorCAS records up to six congenital anomalies per case and adopts the exclusion criteria for minor anomalies employed by the

Fig. 1. Map of the UK Northern Health region.

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European Surveillance of Congenital Anomalies (EUROCAT) (www.eurocat.ulst. ac.uk). NorCAS is a member of the British Isles Network of Congenital Anomaly Registers (BINOCAR) (Rankin, 2007) and the EUROCAT. All anomalies are coded using the WHO’s International Classification of Disease version 10 (ICD 10). Cases were classified into chromosomal (that is a condition resulting from a change in the normal structure or number of chromosomes e.g. trisomy 21) and non-chromosomal anomalies (that is structural anomalies). Non-chromosomal anomalies were further divided into the following groups: nervous system, CHD, respiratory tract, eye, ear, face and neck, digestive system, internal urogenital system, musculoskeletal and miscellaneous. As a case can have more than one anomaly, it can be included in more than one grouping. As the previous studies have reported associations with CHD (Ritz et al., 2002; Gilboa et al., 2005; Dolk H, unpublished data) and oral clefts (Ritz et al., 2002; Gilboa et al., 2005), these groups were further divided into six CHD subtypes (atrio-ventricular septal defects (AVSD), tetralogy of Fallot, hypoplastic left heart, coarctation of aorta, patent ductus arteriosus and VSD) and one subtype for oral clefts (cleft lip and palate). No further subtype analysis was performed due to the small number of cases within the subtypes. The study period ended in 1990 as NorCAS data from 1991 to 1999 contributed to a national study (Dolk H, unpublished data). Controls were obtained from national data on all registered births (live and stillbirths) in the region for the years 1985–1990.

unaffected by replacing missing data as detailed above. Subsequent analysis confirmed that odds ratios (ORs) were not sensitive to either the choice of missing, replaced or complete case datasets or the choice of full or limited random sample control data. The statistical analysis was performed on exposure data gathered from the first trimester (91 days) of the mothers’ pregnancy. Where gestational age was not known at birth (primarily for the control data) this was assumed to be 40 weeks. It was considered that birth weight values below 500 g may be incorrect and, as a conservative approach, these observations were excluded from the analysis; this had the effect of removing a total of 1400 (0.6%) deliveries. Except where indicated, the missing-data-replaced estimates of exposure are used in the analysis.

2.3. Exposure measurement

3. Results

2.3.1. Exposure assessment The Northern region has an extensive network of ambient air pollution monitoring stations. Air pollutant data from these stations are available from the UK National Air Quality Information Archive website. (www.airquality.co.uk/ archive/index.php) These provide daily readings of the pollutant level for 365 days per year. Levels of BS and SO2 are available from this website back to 1985. The distance from each of the 62 available monitors during the study period to each maternal residence was calculated for cases and controls. The number of monitors recording at any individual time was substantially fewer than this. Exposures to BS and SO2 during the first trimester, the most vulnerable period of pregnancy for congenital anomalies, were calculated for each birth by summing the pollutant exposure during the first trimester over the daily readings from all monitors within 10 km of the mother’s residence. Data were missing from monitors at times during the study period. For each birth, each monitor was considered individually and up to 10 missing values during a mother’s first trimester were replaced by the mean value for the monitor over that period. These missing daily readings could be either consecutive or spread throughout the trimester. This yielded a gain of approximately 5% of total data depending on the exposure measure in use.

A total of 3197 cases of congenital anomaly occurring within the 6 years were analysed; 2714 (84.9%) were non-chromosomal and 483 (15.1%) chromosomal anomalies. Table 1 shows some basic characteristics of the cases and controls (all controls and the random sample are presented to illustrate their similarity). Fiftyone per cent of controls and 53% of cases were male. Mean birth weight was higher amongst all controls (random sample 3.32 kg) than cases (2.93 kg), and mean deprivation scores were higher (that is more deprived) for cases (1.30) than controls (0.91). Table 2 shows summary statistics for BS and SO2 exposure throughout the first trimester. The median and quartile values for the case and control groups show that the distributions of both BS and SO2 are slightly lower when all cases are compared with controls. The small case group of eye, ear, face and neck anomalies and the CHD subtype AVSD are the only ones where the distribution of both BS and SO2 is higher than controls. Some case groups have a lower distribution of BS and SO2 than controls, for example CHD and musculoskeletal (Table 2). For non-chromosomal anomalies combined, there was no significant association with BS (Table 3). Among non-chromosomal subtypes, a statistically significant association was found between increasing BS and increased odds of nervous system anomalies (OR ¼ 1.10 per increase of 1000 mg/m3 units total BS in the first trimester; 95% CI 1.03, 1.18). There was no significant association with maternal exposure to BS for any other congenital anomaly group or CHD subtype. A statistically significant negative association was found across all SO2 quartiles relative to the first quartile for CHD combined and patent ductus arteriosus (Table 3). The relationship between SO2 levels and other anomaly subgroups was less clear cut. There was a suggestion of a weak U-shaped relationship with OR significantly o1 for moderate compared to lowest levels, but not with high SO2 levels for non-chromosomal anomalies, coarctation of aorta, nervous system, ventricular septal defect, digestive system and musculoskeletal anomalies. Although not statistically significant, the only groups for which there is a suggestion of a positive relationship with SO2 exposure was respiratory tract anomalies and eye, ear, face and neck anomalies. There was no significant association between SO2 exposure and chromosomal anomalies combined and with the remaining case subgroups.

2.4. Statistical analysis Analyses were carried out using STATA software, versions 8 and 9 (StataCorp, College Station, Texas). The final analysis used separate unconditional logistic regression models for each congenital anomaly group and subtype and BS and SO2 separately to assess how exposure to the pollutants was associated with the odds of being a case; both models adjusted for birth weight, sex and material deprivation. The variables considered for the logistic regression were those both available and reliable for both cases and controls. For instance, maternal age was available for the cases but not the controls, and so could not be used. Material deprivation was measured using the Townsend deprivation scores (TDS) derived from the maternal residential postcode. These are unique alphanumeric geographical identifiers for delivery of mail that cover around 15–20 residential addresses, a smaller number of multiple occupancy dwellings or a single commercial address. Postcode was complete for 100% of cases and 99.9% for controls. TDS were based on the 1991 census data on unemployment, car ownership, overcrowding and housing tenure (Townsend et al., 1988) at the enumeration district (ED; about 450 people in 200 households) level. TDS was included in the regression analyses as a linear term. There was a non-linear relationship between the odds of being a case and birth weight. Consequently, a functional form involving the square-root, squared reciprocal and exponential of birth weight were added to the regression to accurately model this relationship. A linear function was used to model the relationship between BS exposure and the odds of being a case. The relationship with SO2 was non-linear: the odds of being a case appeared lower with moderate but not high SO2 levels. Therefore, quartiles of exposure (from the full dataset) were chosen as appropriate categorical variables to express this relationship. For convenience and consistency, the analyses of the various anomaly groups relative to the controls used the same logistic regression model developed for the all-anomaly data together with the limited random sample of controls. Model development took place using a random sample of 15,000 controls (from the full 242,628 available). Subsequent comparisons showed that the models were not sensitive to this limiting of the number of controls. Both complete case and missing–replaced exposure datasets were used to develop the model. This process confirmed that the relation between exposure and case/control status was

2.5. Ethical approval The NorCAS has been granted exemption by the Patient Information Advisory Group from a requirement for consent for inclusion on the register under section 60 of the UK Health and Social Care Act (2001) and has ethics approval (04/MRE04/ 25) as part of the BINOCAR network to undertake studies involving the use of the data.

4. Discussion This population-based study describes the relationship between maternal exposure to BS and SO2 and the risk of a

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Table 1 Basic characteristics of controls and cases by congenital anomaly subtype in the Northern Region, 1985–1990a.

All controls Controls (random sample) All congenital anomaly Non-chromosomal Nervous system Congenital heart disease Atrio-ventricular septal defect Tetralogy of fallot Hypoplastic left heart Coarctation of aorta Patent ductus arteriosus Ventricular septal defect Respiratory tract Cleft lip and palate Eye, ear, face and neck Digestive system Internal urogenital system Musculoskeletal Miscellaneous Chromosomal a

Overall

Infant sex

Birth weight

Deprivation

N

Na

% Male

Na

Mean (SD)

Na

Mean (SD)

242628 15000

242628 15000

51 51

241344 14909

3.31 (0.57) 3.32 (0.57)

242327 14982

0.89 (3.44) 0.91 (3.45)

3197 2714 548 1286 61 58 30 80 112 488 89 215 47 222 316 419 147 483

3140 2659 512 687 61 58 30 80 111 487 88 212 43 220 311 409 144 481

53 54 46 54 48 60 60 60 50 52 60 50 63 60 58 55 49 50

2700 2337 280 1247 59 55 28 80 112 475 82 195 41 214 274 364 128 363

2.93 2.96 2.59 3.03 2.82 3.03 2.64 3.09 2.98 3.07 2.26 3.01 2.79 2.74 2.65 2.73 2.69 2.75

(0.80) (0.80) (1.01) (0.71) (0.71) (0.70) (0.93) (0.63) (0.73) (0.73) (0.93) (0.82) (0.85) (0.83) (1.00) (0.84) (0.80) (0.77)

3195 2712 547 1285 61 58 30 80 112 487 89 215 47 222 316 419 147 483

1.30 1.38 1.57 1.35 1.71 1.21 1.83 1.16 1.13 1.25 0.83 0.86 0.91 1.40 1.36 1.35 1.14 0.87

(3.50) (3.49) (3.39) (3.55) (3.25) (3.98) (4.30) (3.79) (3.78) (3.55) (3.60) (3.53) (3.69) (3.46) (3.49) (3.39) (3.54) (3.49)

Numbers of cases and controls with data on each item vary owing to missing data.

Table 2 Distribution of total black smoke and sulphur dioxide exposurea during the first trimester, 1985–1990b across case and control groups. Black smoke

Controlsc Controlsd Controls (random sample) Casesc Casesd Congenital anomaly Non-chromosomal Nervous system Congenital heart disease Atrio-ventricular septal defect Tetralogy of fallot Hypoplastic left heart Coarctation of aorta Patent ductus arteriosus Ventricular septal defect Respiratory tract Cleft lip and palate Eye, ear, face and neck Digestive system Internal urogenital system Musculoskeletal Miscellaneous Chromosomal

Sulphur dioxide

N

Median (Q1, Q3)

N

Median (Q1, Q3)

176805 164156 11910 2779 2600

1668 1651 1725 1643 1620

(1135, 2796) (1092, 2677) (1182, 2775) (1103, 2751) (1059, 2614)

176187 158186 11969 2781 2515

3645 3579 3558 3608 3505

(2713, 4493) (2713, 4484) (2847, 4338) (2675, 4434) (2667, 4371)

2373 503 1099 53 46 29 68 98 414 79 195 38 209 273 370 131 406

1644 1680 1609 1754 1553 1630 1529 1492 1556 1609 1706 2299 1735 1520 1544 1750 1637

(1100, 2793) (1127, 3007) (1082, 2612) (1291, 2540) (1200, 2058) (899, 2197) (1039, 2876) (1005, 2448) (1074, 2616) (1168, 2720) (1173, 2397) (1205, 3601) (1153, 2876) (1004, 2818) (1065, 2818) (1148, 2864) (1144, 2697)

2376 503 1097 52 46 29 69 95 415 78 195 38 207 274 373 134 405

3595 3691 3523 3694 3535 3300 3343 3306 3483 3684 3585 4141 3828 3681 3554 3523 3655

(2662, 4454) (2660, 4505) (2615, 4397) (2923, 4624) (2702, 4383) (2652, 4518) (2616, 4705) (2424, 4013) (2638, 4362) (3026, 4398) (2772, 4515) (3193, 4853) (2619, 4531) (2760, 4561) (2696, 4428) (2790, 4448) (2737, 4335)

a

Individual exposures were the mean of daily readings in the first trimester. Numbers of cases and controls with data on each item vary owing to missing data. c Missing exposure data replaced where possible. d Subset for which no exposure data was missing. b

pregnancy being affected by selected congenital anomalies over a 6-year period in the Northern region of the UK. We found a weak positive association between maternal exposure to BS and nervous system anomalies; the excess risk was in the order of 10%. No other associations were found between BS and any other congenital anomaly group or CHD subtype. For SO2, there was a negative association with all CHD combined and patent ductus

arteriosus. The form of the relationship with other case subgroups was less clear cut, sometimes showing a significant association with moderate SO2 levels, but not with higher levels. Although these associations are interesting, we view these findings with caution given that we have analysed 17 congenital anomaly groups/subtypes and two air pollutants, one of which was divided into quartiles. With such a large number of comparisons, we

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b

a

1 [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 177883 [159701] 13949 12147 12967 11941 11937 11918 11960 11985 12299 11963 12068 11925 12089 12130 12216 12008 12215 0.97, 1.02 [0.96, 1.01] 0.97, 1.03 1.03, 1.18 0.92, 1.00 0.77, 1.14 0.73, 1.12 0.71, 1.22 0.89, 1.19 0.78, 1.05 0.89, 1.02 0.82, 1.12 0.88, 1.07 0.93, 1.34 0.94, 1.12 0.96, 1.13 0.94, 1.08 0.95, 1.18 0.91, 1.05 178508 [165755] 13891 12092 12913 11885 11880 11861 11902 11931 12242 11907 12011 11868 12034 12071 12156 11948 12159 All congenital anomalies [complete exposure only] Non-chromosomal Nervous system Congenital heart disease (overall) Atrio-ventricular septal defect Tetralogy of Fallot Hypoplastic left heart Coarctation of aorta Patent ductus arteriosus Ventricular septal defect Respiratory tract Cleft lip and palate Eye, ear, face and neck Digestive system Internal urogenital system Musculoskeletal Miscellaneous Chromosomal

1.00 [0.98] 1.00 1.10 0.96 0.94, 0.90, 0.93, 1.03, 0.91, 0.95, 0.96, 0.97, 1.12, 1.02, 1.04, 1.01, 1.06, 0.98,

95% CI OR

Adjusted for birthweight, infant sex, deprivation. For all except the ‘‘All congenital anomalies’’ data a random sample of 15,000 controls was used rather than the full 242,628. N (overall) gives the absolute number of cases and controls (combined) that were able to be used in fitting the logistic regression model; allowing for the missing data on all considered variables.

0.86, 1.08 [0.8], [1..03] 0.82, 1.08 0.89, 1.82 0.68, 0.98 0.60, 3.05 0.38, 1.99 0.35, 2.54 0.55, 1.80 0.19, 0.69 0.58, 1.04 0.60, 2.83 0.71, 1.67 0.59, 5.29 0.65, 1.43 0.81, 1.71 0.74, 1.40 0.79, 2.40 0.61, 1.22 0.97 [0.91] 0.94, 1.27 0.82 1.35 0.87 0.94 0.99 0.36 0.78 1.30 1.09 1.76 0.97 1.17 1.02, 1.38 0.86 0.87, 1.09 [0.84, 1.07] 0.67, 0.89 0.62, 1.31 0.61, 0.88 0.42, 2.26 0.29, 1.56 0.23, 1.91 0.13, 0.68 0.28, 0.85 0.60, 1.05 0.78, 3.39 0.55, 1.33 0.56, 4.83 0.55, 1.21 0.58, 1.26 0.61, 1.16 0.62, 1.92 0.84, 1.56 0.98, [0.95] 0.77 0.90, 0.73, 0.97, 0.67, 0.66, 0.30, 0.49, 0.80, 1.63, 0.85, 1.64, 0.82 0.85, 0.84, 1.09, 1.14, 0.90, 1.13 [0.91, 1.15] 0.56, 0.73 0.44, 0.94 0.50, 0.72 0.39, 1.98 0.30, 1.47 0.14, 1.31 0.26, 0.94 0.27, 0.76 0.51, 0.88 0.61, 2.56 0.52, 1.21 0.44, 3.76 0.34, 0.78 0.46, 1.00 0.46, 0.87 0.63, 1.85 0.53, 1.01 1.01 [1.03,] 0.64 0.64, 0.60, 0.87, 0.67, 0.43, 0.50, 0.45, 0.67, 1.25, 0.79, 1.28, 0.51, 0.68, 0.63, 1.08, 0.73,

95% CI OR 95% CI OR 95% CI OR 95% CI OR

SO2 4th quartile SO2 3rd quartile SO2 2nd quartile SO2 1st quartile Sulphur dioxide (SO2) N (overall) Black smoke N (overall)b N (overall) Congenital anomaly

Table 3 Odds ratio (95% confidence interval)a for an increase of 1000 mg/m3 in total black smoke exposure and using quartiles of sulphur dioxide exposure (relative to the lowest quartile) during the first 3 months of pregnancy by congenital anomaly subtype, 1985–1990.

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expect some significant association to occur by chance. Thus the association between BS and nervous system anomalies may be a chance finding. The U-shaped/non-linear association with SO2 noted for certain congenital anomaly groups/subtypes is difficult to explain. We interpret this with caution given that the number of cases in certain groups was small, and the study may have had limited statistical power in these groups to detect a difference, e.g. for hypoplastic left heart and tetralogy of Fallot. We have used data from a long-standing, high quality register of congenital anomalies. The NorCAS belongs to established UK and European networks which use similar inclusion criteria, and have a consistent approach to data collection, coding and recording. The use of multiple source notifications, of consistent inclusion criteria and data collection methods, ensures a high case ascertainment. The NorCAS undertakes regular comparative exercises with other registries through the EUROCAT network confirming high levels of ascertainment. We have included congenital anomalies arising within livebirths, stillbirths, termination of pregnancy for fetal anomaly following prenatal diagnosis and late miscarriages thus reducing ascertainment bias. As the NorCAS includes all cases diagnosed up to 16 years of age, those congenital anomalies that are only detectable well after birth have also been captured. We have also restricted our analyses to a range of selected, major congenital anomalies that are well-defined and ascertained. The use of an efficient registration system of congenital anomalies on a population base meets the necessary criteria for a robust epidemiological study in this field, as proposed in a recent review by Ritz and Wilhelm (2008). The literature on the relationship between maternal exposure to ambient air pollutants and congenital anomaly risk is very sparse. Data from Eastern Europe in areas of high industrial pollution have suggested an association between exposure and cardiovascular anomalies (Antipenko and Kogut, 1993). A case– control study in Los Angeles, California, found a positive association of VSD with increasing CO exposure and between valvular, aortic and conutruncal anomalies and O3 exposure, all during the second gestational month (Ritz et al., 2002). A second US study in Texas found a significant, positive association between CO and tetralogy of Fallot, PM10 and isolated atrial septal defects and negative association between SO2 and isolated VSD (Gilboa et al., 2005). There was limited associations of exposure to air pollutants with oral clefts, and negative associations were found between CO and isolated ASDs and between O3 and isolated VSDs (Gilboa et al., 2005). A study in Korea reported an increased risk of congenital anomalies following exposure to PM10 in the second trimester (Kim et al., 2007). The only other UK study, which used data from four regional congenital anomaly registers and averaged pollution estimates over one year only, found a significant association between tetralogy of Fallot and SO2 exposure (Dolk H, unpublished data). Our register-based study was limited to routinely collected data. Thus, information on some key data items which are known to increase the risk of congenital anomalies was not available to the study. We did not have information on maternal smoking for cases or controls. However, the established link between material deprivation and smoking exposure (Kleinschmidt et al., 1995) means that the measure of deprivation determined from the residential postcode is likely to be indicative of the level of smoking and deprivation in the area. Thus, residential postcode can be considered a proxy for both smoking status and material deprivation. We also did not have information on ethnicity. However, as less than 2% of the population in the Northern region belong to an ethnic minority group, this is unlikely to impact on our results.

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Information was not available on maternal diet or occupation. The nutritional status of a woman during pregnancy is an established risk factor for many reproductive outcomes, for example the well established link between folic acid, a vitamin B9 derivative, intake during the periconceptional period and the occurrence of neural tube defects (Medical Research Council Vitamin Study Research Group, 1991). Including information on occupational exposures during pregnancy would have limited the possibility of any increased risk resulting from exposure to known occupational teratogens rather than as a result of an increased exposure to ambient air pollutants. Such information would only be available from undertaking a prospective study. Further studies are needed to establish whether there is an association between maternal exposure to air pollution and the occurrence of congenital anomalies before undertaking such costly prospective work. However, Ritz and colleagues in their University of California Los Angeles Environment and Pregnancy Outcome Survey in which they collected information on potential risk factors, found that adjustment for occupation, income, maternal smoking and environmental tobacco smoke, alcohol drinking changed the odds ratio by less than 5% (Ritz et al., 2007). Although gestational age was available for cases, it was unavailable for controls as it is not routinely collected by UK national statistics. Therefore, each control was assigned a gestational age of 40 weeks. This may have led to first trimester dates (and therefore pollutant exposure) being estimated incorrectly, but this should not have biased exposure estimates. We classified maternal exposure to air pollutants by averaging the pollutant exposure during the first trimester over the daily readings from all monitors within 10 km of the mother’s residence. The two previous US studies also classified maternal exposure to pollutants by assigning each mother to the nearest air pollution monitor (Ritz et al., 2002; Gilboa et al., 2005). The use of fixed-site outdoor monitors as surrogate estimates of personal exposure to air pollutants is a well established and validated approach to measuring exposure to air pollutants: for example, a recent US Health Effects Institute Report showed significant correlations between ambient PM concentrations and personal exposure over time (Koutrakis et al., 2005). However, this approach is unable to consider local spatial variation in air pollutant levels and may lead to exposure inaccuracies. Some unavoidable exposure inaccuracy will have occurred from the assumption that mothers’ residence at birth reflects exposure for the full duration of the pregnancy. Several studies on populations in North America have indicated that pregnant women are a highly mobile group, with reports of 20–32% of women moving house between conception and delivery (Khoury et al., 1988; Shaw and Malcoe, 1992; Zender et al., 2001). However, this is unlikely to be of major concern in the current study due to low mobility in our study population; about 9% of mothers notified to the NorCAS moved between the time of booking and delivery with the majority moving locally (Hodgson S, personal communication). Even if this is an underestimate, residential mobility is likely to be non-differential and would therefore not bias the risk estimates. In our study, maternal exposure was averaged over the first trimester of pregnancy. As this is the most vulnerable period of pregnancy for the development of congenital anomalies, this exposure interval was felt to be the most relevant for the particular outcome under study. We were only able to examine the relationship between maternal exposure to BS and SO2 as routine data was not available for this study period for other air pollutants such as CO or O3. As with the other studies, the main source of BS in the Northern region during the study period was vehicle traffic. However, there may be heterogeneity between the study areas in particle composition which would explain the

differences in study findings, in that the relative contribution of traffic, industry and domestic coal burning will be different in the different study locations. We were not able to investigate the relationship between other air pollutants (CO, O3) and congenital anomaly risk, nor can we comment on the potential contribution of multiple pollutant exposure to congenital anomaly risk or the exact timing of susceptibility during the first trimester. Whilst the association between increased mortality and morbidity with exposure to air pollutants is well established, its underlying biological mechanism is still not clear. Adult studies currently suggest three possible mechanisms of action: (i) the induction of a systemic oxidative stress and inflammatory response which alters blood coagulation and endothelial function (Seaton et al., 1995, 1999; Donaldson et al., 2001); (ii) alterations in cardiac autonomic function resulting in haemodynamic responses (Pope et al., 1999; Holguı´n et al., 2003; Vallejo et al., 2006) and (iii) the initiation of an allergic immune response (Hadnagy et al., 1996; Stiller-Winkler et al., 1996). These mechanisms may be interrelated as reported in a recent paper investigating the effect of air pollution on inflammation, oxidative stress, coagulation and autonomic dysfunction in young adults (Chuang et al., 2007). For perinatal and infant health outcomes, even fewer studies have investigated the potential biological pathways by which air pollution may lead to adverse outcomes, although researchers agree that the biologic mechanisms suggested in adult studies may also be relevant to the fetus (Glinianaia et al., 2004a, b; Kannan et al., 2006; Slama et al., 2008). Although the epidemiological evidence is limited at present, studies to date suggest that exposure to BS has limited or no association with congenital anomaly risk but the relationship with other air pollutants (SO2, CO, NO, O3) remains to be determined. The developing fetus is particularly vulnerable to environmental exposures. The fetal programming hypothesis suggests that delays to fetal growth impact not only on subsequent child development but may be an important risk factor for the major diseases of middle age: diabetes, hypertension and cardiovascular disease (Barker, 2004). These wider implications necessitate further research using accurate information on individual exposures and birth circumstances and of sufficient size to allow the examination of the range of air pollutants and congenital anomaly subtypes, to investigate the relationship between maternal exposure to air pollutants and congenital anomaly risk.

Acknowledgments We thank the Link Clinicians in the Northern region for their support of the NorCAS and Mary Bythell, NorCAS data manager.

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