Human Reproduction Vol.18, No.3 pp. 638±643, 2003 DOI: 10.1093/humrep/deg102 Exposure to air pollution during different gestational phases contributes to risks of low birth weight B.E.Lee1, E.H.Ha1,5, H.S.Park1, Y.J.Kim2, Y.C.Hong3, H.Kim4 and J.T.Lee1 1 Department of Preventive Medicine, College of Medicine, Ewha Medical Research Center, Ewha Womans University, 2Department of Obstetrics and Gynecology, College of Medicine, Ewha Womans University, 3Department of Occupational and Environmental Medicine, College of Medicine, Inha University and 4Department of Epidemiology and Biostatistics and Institute of Health and Environmental Sciences, School of Public Health, Seoul National University, Korea 5 BACKGROUND: Although there have been growing concerns about the adverse effects of air pollution on birth outcomes, little is known about which speci®c exposure times of speci®c pollutants contribute to low birth weight (LBW). METHODS: We evaluated the relationships between LBW and air pollution exposure levels in Seoul, Korea. Using the air pollution data, we estimated the exposure during each trimester and also during each month of pregnancy on the basis of the gestational age and birth date of each newborn. Generalized additive logistic regression analyses were conducted considering infant sex, birth order, maternal age, parental education level, time trend, and gestational age. RESULTS: The monthly analyses suggested that the risks for LBW tended to increase with carbon monoxide (CO) exposure between months 2±5 of pregnancy, with exposure to particles <10 mm (PM10) in months 2 and 4, and for sulphur dioxide (SO2) and nitrogen dioxide (NO2) exposure between months 3±5. CONCLUSIONS: This study suggests that exposure to CO, PM10, SO2 and NO2 during early to mid pregnancy contribute to risks for LBW. Key words: air pollution/carbon monoxide/low birth weight/PM10/nitrogen dioxide/sulphur dioxide Introduction Low birth weight (LBW) increases not only infant mortality (Bobak and Leon, 1992; Woodruff et al., 1997; Loomis et al., 1999) but also the subsequent morbidity (Lin et al., 1999; Gouveia and Fletcher, 2000; Hack et al., 2002). The rates of LBW reach up to 50% in some developing countries (CDC, 2002), although they range from 5.0±7.9% in developed countries (Ventura et al., 1998). In recent years, air pollution is considered to be an important cause or risk factor for reproductive health. There have been growing concerns about the adverse effects of air pollution on birth outcomes such as LBW, intrauterine growth retardation (IUGR), preterm births and birth defects (Bobak and Leon, 1992; Dejmek et al., 1999; Bobak, 2000; Ritz et al., 2002). A lot of evidence for the effect of air pollution on LBW has been published, although there are many other risk factors such as infant sex and race, paternal weight and height, gestational weight gain, parity, caloric intake, maternal morbidity during pregnancy, cigarette smoking and alcohol consumption (Kramer, 1987). Studies conducted in China, the Czech Republic, and the United States reported a relationship between air pollution and LBW (Wang et al., 1997; Bobak, 2000; Maisonet et al., 2001). The results of these studies, however, are not consistent, particularly regarding the effect period of each air pollutant. 638 Some studies reported that exposure during the ®rst trimester was associated with an increased risk for LBW. In an animal study, the period shortly after conception was the most susceptible to the induction of developmental changes by air pollutants (Generoso et al., 1987; Rutledge, 1997). Human studies also suggested that initial changes leading to IUGR might be triggered in early pregnancy, around the time of implantation (Khong et al., 1986; Duvekot et al., 1995). A number of epidemiological studies indicated that the risk for LBW or IUGR is also increased in the ®rst trimester of pregnancy. Dejmek et al. (1999) found the risk of IUGR associated with exposure to particles <10 mm in aerodynamic diameter (PM10) during the ®rst month of pregnancy. Bobak (2000) also reported that air pollutants [sulphur dioxide (SO2) and total suspended particulate] had greater effects on LBW in the ®rst trimester than other trimesters. On the contrary, other studies have suggested that exposure to air pollution during the last trimester has greater effects on LBW. Gruenwald (1978) showed that the peak period for weight growth is around 33 weeks gestation. In terms of air pollution, third trimester exposure to total suspended particles (TSP) and SO2 was associated with increased risk of LBW in Beijing (Wang et al., 1997). In addition, carbon monoxide (CO) exposure during the third trimester was associated with LBW in Southern California (Ritz and Yu, 1999) and the North-Eastern United States (Maisonet et al., 2001). ã European Society of Human Reproduction and Embryology Downloaded from https://academic.oup.com/humrep/article/18/3/638/626053 by guest on 27 June 2022 To whom correspondence should be addressed at: Department of Preventive Medicine, College of Medicine, Ewha Womans University, 911±1, Mok-6-Dong, Yangcheon-Gu, Seoul, Korea (158±710). E-mail: eunheeha@ewha.ac.kr Air pollution and low birth weight These inconsistencies raise the issue of whether the peak effect period of air pollution on LBW differs across different populations and pollutants. Furthermore, previous studies investigated the relationship between air pollution and LBW using a broad range of exposure times. Thus, little is known about which speci®c exposure time of speci®c pollutants contributes to LBW. Therefore, we evaluated the speci®c timing of peak effects of air pollutants on LBW throughout the gestational period. Materials and methods Results Table I presents the demographic characteristics of infants delivered in Seoul from January 1, 1996 to December 31, 1998. The prevalence of LBW was 2.9% of singletons, but 4.6% when preterm births were included. The OR for LBW increased for female sex, fourth or higher order child, mothers <20 years of age and parents with low educational level. Table II lists the concentrations of air pollutants during the study period. Mean levels were 1.2 ppm (1.4 mg/m3) for CO, 71.1 mg/m3 for PM10, 12.1 ppb (47.5 mg/m3) for SO2 and 32.5 ppb (61.1 mg/m3) for NO2. No air pollutant exceeded the WHO recommended criteria. The correlations among the pollutants of each trimester are in Table III. The concentrations of CO, PM10, SO2 and NO2 were positively correlated with each other. The risks of LBW for exposure to air pollution during whole pregnancy and each trimester are presented in Table IV. Regarding the whole period of pregnancy exposures, all of the Table I. Demographic characteristics of infants delivered between 1996 and 1998 in Seoul Variables Sex of the infant Male Female Infant birth order First Second Third Fourth + Maternal age (years) 20 + <20 Maternal education University High school Middle school Paternal education University High school Middle school Mean birth weight % of low birth weight OR (95% CI)b 3357.3 3250.0 1.2 1.7 1 1.61 (1.55±1.68) 3291.0 3314.1 3368.2 3346.3 3.0 2.7 3.3 5.9 1 0.77 (0.74±0.80) 0.92 (0.85±0.99) 1.65 (1.36±2.00) 3248.2 3306.0 2.9 4.5 1 1.77 (1.47±2.13) 3300.4 3309.0 3301.3 2.7 3.0 3.8 1 1.19 (1.14±1.24) 1.56 (1.45±1.68) 3296.7 3306.5 3305.9 2.7 3.1 3.9 1 1.23 (1.18±1.28) 1.58 (1.47±1.70) aAdjusted date and gestational age; OR = odds ratio for LBW; CI = con®dence interval. 639 Downloaded from https://academic.oup.com/humrep/article/18/3/638/626053 by guest on 27 June 2022 In South Korea, birth certi®cate records were based on records compiled by doctors or nurses at delivery and registered with regional public health centres. These data included birth weight, sex, birth order, gestational age, maternal age, parental educational level and parental occupation. The gestational age was usually estimated based on maternal report for last menstrual period (LMP) and on ultrasound measurements by gynaecologists. We collected birth data in Seoul between January 1, 1996 and December 31, 1998 from the Korean National Birth Register. We excluded missing data (n = 3642) for any co-variates and preterm births (n = 13 835) which were de®ned as <37 weeks gestation (Wang et al., 1997; Ritz and Yu, 1999). The study subjects were restricted to mothers who delivered full-term singletons between 37 and 44 gestational weeks during the study period (n = 388 105). LBW was de®ned as <2500 g. We obtained air pollution data from the Department of the Environment regarding concentrations of PM10 (by b-ray absorption), SO2 (by ultraviolet ¯uorescence), CO (by non-dispersive infrared photometry) and nitrogen dioxide (NO2) by chemiluminescence between January 1, 1995 and December 31, 1998 in Seoul (Ministry of Environment and National Institute of Environmental Research, 1999). Exposure measurements during the study period were taken from 20 monitoring stations covering nearly all areas of the city. The major source of air pollution in the study area is automobile exhaust emissions. We averaged the hourly measurements arithmetically across all monitoring stations and calculated a 24 h average. These data were used to estimate the exposure during each trimester and each month of pregnancy on the basis of the gestational age and birth date of each newborn. We used a generalized additive model (GAM), which allowed regressions to include non-parametric smooth functions in order to control the potential non-linear dependence of each birth on date and season (Hastie and Tibshirani, 1996). First, we included a smoothing function for date and/or season in the model using LOESS, a moving regression smoother to control for seasonal and long-term trends (Cleveland and Devlin, 1988). The model ®tted well when the date only was entered into the model. The selection criterion for goodness of ®t was evaluated using Akaike's information criterion (AIC) (Akaike, 1973). We similarly chose the number of degrees of freedom for gestational age that lowered the AIC. Second, we controlled the co-variates, which are known as risk factors for LBW. We applied the model both with and without parental occupation, and obtained the better-®tted model for this analysis without parental occupation. Finally, the optimal model included indicator variables for infant sex, birth order, maternal age, parental education level, time trend and gestational age. We calculated average concentrations for each pollutant through the whole period, in each trimester (1st, 2nd and 3rd) and in each month of pregnancy. The gestational period was divided into three trimesters of ~3 calendar months (Cunningham et al., 2001). The air pollution data were analysed as both continuous and categorical variables. We categorized pollutant levels into quartiles. To assess an exposure± response relationship, we applied the models in which dummy variables were used to indicate categories based on quartiles of the pollutant concentrations. Exposure in the bottom quartile for each pollutant was used as the reference category. We present the risk magnitudes as odds ratios (OR) of LBW associated with the interquartile change of each pollutant. In order to clarify the speci®c effect period of air pollution exposure on LBW, we created two separate subgroups based on exposure levels during pregnancy and analysed the two separately. To assess the effect of exposure during the latter 5 months of pregnancy, we formed subgroup 1, which included only mothers who were at low exposure levels (<25th of each air pollutant level) during the ®rst 5 months of pregnancy. To assess the effect of exposure during the ®rst 5 months of pregnancy, we restricted subgroup 2 to those who were at low exposure levels during the latter 5 months of pregnancy. B.E.Lee et al. Table II. Descriptive statistics for air pollution, Seoul, 1995±1998 Pollutants Mean (SD) Min Q1 Med Q3 Max CO (ppm) PM10 (mg/m3) SO2 (ppb) NO2 (ppb) 1.2 (0.5) 71.1 (30.1) 12.1 (7.4) 32.5 (10.2) 0.4 18.4 3.0 10.2 0.9 47.4 6.8 25.0 1.1 67.6 9.8 31.4 1.4 89.3 15.6 39.7 3.4 236.9 46.0 65.1 SD = standard deviation; Min = minimum; Q1 = lower quartile; Med = median; Q3 = upper quartile; Max = maximum. Table III. Pearson correlation coef®cients between air pollutants in pregnancy trimesters First trimester PM10 SO2 NO2 Second trimester PM10 SO2 NO2 Third trimester PM10 SO2 NO2 CO PM10 SO2 0.47 0.79 0.77 0.78 0.66 0.75 0.68 0.86 0.78 0.82 0.81 0.77 0.69 0.86 0.82 0.85 0.80 0.76 trimester. Higher CO, PM10 and SO2 levels showed higher risks of LBW. When the exposure for each month of pregnancy was evaluated separately, the resulting OR for LBW are shown in Figure 2. We found that the risks for LBW tended to increase with CO exposure between months 2±5, and with PM10 exposure between months 2±4 compared with the latter 5 months. For SO2 and NO2, exposure between the months 3±5 of pregnancy was associated with LBW. These ®ndings suggest that air pollutants affect LBW in the earlier periods of pregnancy. Table V compares the OR changes of LBW between the periods of pregnancy before and after the 5th month. When mothers were exposed to low concentrations of PM10 and CO during the ®rst 5 months of pregnancy, the association between LBW and air pollution was not signi®cant regardless of exposure in the latter period of pregnancy. On the other hand, exposure during the ®rst 5 months of pregnancy was consistently associated with LBW even if the air pollution levels were low during the latter 5 months of pregnancy. This separate analysis suggests again that air pollution exposure during the earlier months of pregnancy is more important in the relationship between air pollutant and LBW. Discussion Research in several countries has shown that air pollution affects LBW (Table VI). Our previous study indicated that ambient CO, NO2, SO2, and TSP concentrations during the ®rst trimester of pregnancy were associated with LBW (Ha et al., 2001). In the current study, we extended the study period from 1996±1997 to 1996±1998 and focused more speci®cally on exposure during pregnancy. This study suggested that exposure to air pollution during the ®rst and second trimester was associated with an increased risk for LBW. More speci®cally, we found that the risks for LBW increased with CO exposure between months 2±5, and with SO2 and NO2 exposure between months 3±5 of pregnancy. PM10 exposure in the second and fourth months was associated with LBW. We found that exposure during the third trimester was negatively associated with LBW. Wang et al. (1997) suggested that it might be due to the pattern of air pollution whereby the concentration of air pollutants during the ®rst and second trimesters is almost inversely associated with that of the third trimester. We cannot explain it fully and further study is needed. Table IV. Odds ratios and their 95% con®dence intervals of LBW for interquartile range increases of air pollutants during pregnancya CO PM10 SO2 NO2 aAdjusted 640 First trimester Second trimester Third trimester All trimesters 1.04 1.03 1.02 1.02 1.03 1.04 1.06 1.03 0.96 1.00 0.96 0.98 1.05 1.06 1.14 1.04 (1.01±1.07) (1.00±1.07) (0.99±1.06) (0.99±1.04) (1.00±1.06) (1.00±1.08) (1.02±1.11) (1.01±1.06) (0.93±0.99) (0.95,1.04) (0.91±1.00) (0.96±1.00) (1.01±1.09) (1.01±1.10) (1.04±1.24) (1.00±1.08) for date, gestational age, infant sex, infant order, maternal age and parental education level. Downloaded from https://academic.oup.com/humrep/article/18/3/638/626053 by guest on 27 June 2022 pollutants exhibited hazardous effects on LBW. In terms of trimester-speci®c exposures, we found that ®rst-trimester CO exposure increased the risk for LBW (OR = 1.04, 95% CI = 1.01±1.07), as did second-trimester exposure to PM10 (OR = 1.04, 95% CI = 1.00±1.08), SO2 (OR = 1.06, 95% CI = 1.02±1.11), and NO2 (OR = 1.03, 95% CI = 1.01±1.06). On the other hand, these effects disappeared in the third trimester. In addition, interquartile changes of CO during the ®rst trimester decreased birth weight by 12.8 g. Furthermore, reduction of birth weight was 19.6, 14.6 and 21.5 g for interquartile increase of PM10, SO2, and NO2 respectively, in the second trimester (data not shown). Figure 1 shows the OR of LBW for each quartile of CO, PM10, SO2 and NO2 during each trimester of pregnancy. The risks of LBW were increased in infants with ®rst-trimester CO exposure in the 25±50th percentiles (RR = 1.011, 95% CI = 0.958±1.066), in the 50±75th percentiles (RR = 1.012, 95% CI = 0.957±1.069), and >75th percentile (RR = 1.060, 95% CI = 1.006±1.117). We found positive dose response relationships between LBW and CO during the ®rst trimester, and between LBW and PM10, SO2 during the second Air pollution and low birth weight Table V. Odds ratios and their 95% con®dence intervals for LBW with exposure before and after the 5th month of pregnancy Subgroup Subgroup 1a Subgroup 2b Exposure Last 5 months First 5 months Odds ratios (95% con®dence interval) PM10 CO 0.94 (0.85±1.05) 1.04 (1.01±1.08) 0.88 (0.79±0.99) 1.06 (0.98±1.14) aOnly mothers who were at low exposure levels during the ®rst 5 months of pregnancy were included. Odds ratios were calculated based on the interquartile range of air pollution levels during the last 5 months of pregnancy. bOnly mothers who were at low exposure levels during the last 5 months of pregnancy were included. Odds ratios were calculated based on the interquartile range of air pollution levels during the ®rst 5 months of pregnancy. Figure 2. Odds ratio of low birth weight for interquartile range change of air pollutants in each month of pregnancy. The biological mechanisms whereby air pollution might in¯uence birth weight remain to be explained. One hypothesized pathway is that placental in¯ammation may play an important role in the physiological pathway between air pollution exposure and LBW. It is possible that air pollution during pregnancy leads to placental in¯ammation, which impairs placental function (Dexter et al., 2000). Sala®a et al. (1995) reported that chronic in¯ammation brought about growth restriction, independently of placental vasculopathy. In the present study, PM10, SO2 and NO2 exposures from ®rst through second trimesters appeared to have the largest effect on LBW. In terms of the biological mechanism on LBW, it is reasonable to consider PM10, SO2, and NO2 together rather than separately because they represent ®ne particles that are believed to be a risk pollutant (Ha et al., 2001). In addition, these pollutants were correlated strongly with each other and exerted an effect on LBW within similar periods. Particle exposure in vitro and in exposed animals causes oxidative stress (Carter et al., 1997; Kadiiska et al., 1997) and can increase the permeability of lung epithelium (Li et al., 1994), allowing particles access to the endothelial cells and the blood (Donaldson et al., 2001). PM10 and gaseous pollutants such as SO2 and NO2 lead to pulmonary in¯ammation with a systemic release of cytokines (Walters et al., 2001; Nemmar et al., 2002) and increase blood viscosity (Peters et al., 1997; Prescott et al., 2000). Increased blood viscosity is associated with decreased oxygen diffusion (Zondervan et al., 1988) and may interfere with the supply of oxygen and nutrients to the fetus. In addition, some toxicants from air pollutants could cross the 641 Downloaded from https://academic.oup.com/humrep/article/18/3/638/626053 by guest on 27 June 2022 Figure 1. Odds ratio and 95% con®dence interval for low birth weight by quartiles of air pollutants in trimesters of pregnancy from logistic regression models adjusted for all covariates. B.E.Lee et al. Table VI. Air pollution and low birth weight in several published studies Study period Area Air pollutant Effect period Effect size Early 1970s (Williams et al., 1977) California LA CO ± 1988±1994 (Wang et al., 1997) Beijing SO2, TSP Third trimester 1989±1993 (Ritz and Yu, 1999) 1994±1996a (Dejmek et al., 1999) LA Teplice CO PM10 Third trimester First month 1991 (Bobak, 2000) Czech TSP, SO2 First trimester 1994±1996 (Maisonet et al., 2001) Northeastern United States CO, SO2 Third trimester Second trimester Decrease 314 g of mean birth weight in heavily polluted areas 100 mg/m3 increase SO2 1.11 (1.06±1.16) TSP 1.10 (1.05±1.14) CO > 5.5 ppm 1.22 (1.03±1.44) PM10 low (reference group) Medium 1.62 (1.07±2.50) High 2.64 (1.48±4.71) 50 mg/m3 increase TSP 1.20 (1.11±1.30) SO2 1.15 (1.07±1.24) CO 1 ppm increase 1.31 (1.06±1.62) SO2 25th centile (reference group) 25±<50th centile 1.21 (1.07±1.37) 50±<75th centile 1.20 (1.08±1.35) 75±<95th centile 1.21 (1.03±1.43) placenta with direct effects on fetal development (Dejmek et al., 1999). Alternatively, placental insuf®ciency may be an important pathway. Placental insuf®ciency reduces the oxygen and nourishment supplies to the fetus (Behrman, 1992) and leads to growth retardation (Cunningham et al., 2001a,b). Exposure to air pollution in early pregnancy could cause insuf®cient trophoblast formation, and lead to insuf®cient placental vascularization (Roberts et al., 1991; Duvekot et al., 1995). Chronic reductions of uteroplacental circulation due to the effects of air pollution could result in fetal hypoxia and IUGR (Wilson, 1971; Werler et al., 1985). A number of potential mechanisms for CO have been suggested. The fetus in the uterus may be particularly susceptible to hypoxia from CO exposure even if the maternal blood level of CO is non-toxic (Gabrielli et al., 1995). Therefore, exposure to low levels of ambient CO during pregnancy could result in tissue hypoxia by increasing maternal and fetal carboxyhaemoglobin concentrations and decreasing fetal O2 tensions or O2 carrying capacity (Longo, 1976). Furthermore, maternal CO inhalation can affect the fetus more severely than the mother in terms of oxygenation of tissues (Longo, 1977). This study has several limitations. We did not consider several potential risk factors for LBW, including parental weight and height, history of adverse pregnancy outcomes, maternal nutrition, gestational weight gain, cigarette smoking, alcohol consumption and occupational exposures (Paige and Davis, 1986; Kramer, 1987; Teitelman et al., 1990; Dejmek et al., 2002). However, because these factors are not expected to be correlated with daily air pollution levels (Schwartz and Morris, 1995), the estimated effects of air pollution are unlikely to be confounded by these factors. On the other hand, when two pollutants were evaluated together, the effects of CO on LBW in the ®rst trimester remained signi®cant. In the second trimester, PM10, SO2 and NO2 were associated with LBW after controlling for CO. However, it is dif®cult to interpret this result because of co-linearity among pollutants (Pitard and Viel, 1997). In addition, we used data from an ambient air monitoring station in exposure assessment and this may have 642 resulted in exposure misclassi®cation. However, recent studies have suggested that outdoor monitors can be used as surrogates for personal exposure (Janssen et al., 1998, 1999). Even if there is a measurement error, it would not much bias the estimates and used to underestimate the effect of air pollution (Schwartz and Levin, 1999; Zeger et al., 2000). On the other hand, our study had several strengths. We examined various speci®c exposure periods for air pollutants during pregnancy. 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