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Association between Ambient Air Pollution and Pregnancy Outcomes in Patients Undergoing In Vitro Fertilization in Chengdu, China: A retrospective study
Environmental Research 184 (2020) 109304
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Association between Ambient Air Pollution and Pregnancy Outcomes in Patients Undergoing In Vitro Fertilization in Chengdu, China: A retrospective study
T
Xun Zenga,b, Song Jina,b, Xiaolan Chenc,∗, Yang Qiud,∗ a
Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, China Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, China c Department of Economics, School of Economics, Sichuan University, Chengdu, China d Department of Environmental Sciences and Engineering, School of Architecture and Environmental Sciences, Sichuan University, Chengdu, China b
ARTICLE INFO
ABSTRACT
Keywords: In vitro fertilization/IVF Female reproduction Ambient air pollution Retrospective study
Ambient air pollution has been a major concern in China due to its effect on population health. Exposure to ambient air pollution has negative impact on animal reproduction and fertility, however, its effect on human reproduction has been inconclusive. We conducted a retrospective study on in vitro fertilization (IVF) patients from Chengdu, Sichuan Province in western China, a city with persistent ambient air pollution. We analyzed the medical records of 1139 patients who underwent first conventional IVF cycles during 2014–2019. The relationship between six atmospheric pollutants (PM2.5, PM10, O3, NO2, SO2, CO) and IVF pregnancy outcomes were assessed by 1) stratification of maternal age into three groups (< 35, 35–39, ≥40 years), and by 2) averaging pollutant concentration during different exposure windows. The results indicate that the association between ambient air pollution and IVF pregnancy outcomes (biochemical pregnancy and clinical pregnancy) is more significant for women in < 35 years age group. Concentrations of PM2.5, PM10, NO2, SO2 and CO are negatively associated with the odds of biochemical pregnancy and clinical pregnancy, and concentration of CO in particular is associated with the largest reduction in odds. Conversely, O3 concentration is positively associated with biochemical pregnancy and clinical pregnancy. Moreover, pollutant concentration during long-term exposure window is associated with larger magnitude of change in the odds of biochemical pregnancy and clinical pregnancy. Findings from this study suggest that exposure to ambient air pollution during any period within the IVF treatment timeline would influence IVF pregnancy outcomes, and such influence is more pronounced in younger women (< 35 years).
1. Introduction Exposure to ambient air pollution has been identified as one of the leading risk factors for population health. At the global level, air pollution is linked to respiratory diseases (Tomaskova et al., 2016), cardiovascular disorders (Pope et al., 2004; Shah et al., 2013), and increased risk of cancer (Loomis et al. 2013, 2014). In recent years, environmental epidemiology studies have found an association between air pollution and adverse perinatal outcomes such as intrauterine growth restriction (Lee et al., 2013), low birth weight (Estarlich et al., 2011; Pedersen et al., 2013) and prematurity (Fleischer et al., 2014). A growing number of studies have suggested that exposure to ambient air pollution is associated with reduced fertility and spontaneous fertility rate (Dejmek et al., 2000; Nieuwenhuijsen et al., 2014; Slama et al., 2013). *
Human reproduction process includes a number of developmental stages: gametogenesis, insemination, fertilization, cleavage, implantation, placentation, gastrulation, organogenesis and parturition (Atwood and Vadakkadath Meethal, 2016; Edwards, 2006; Hutt and Albertini, 2007; Jasienska et al., 2017). In fertile females, ovarian follicle growth is a lengthy process. In each cycle it takes a cohort of pre-antral follicles 85 days until the dominant follicle ovulates (Gougeon 1998, 2010). An exposure period of approximately 85 days is reasonably accepted as being of sufficient duration for detecting chronic impact on female reproductive function affecting oocyte quality and pre-implantation embryonic development. The advent of in vitro fertilization (IVF) provides a clinical timeline to observe reproductive and developmental events during the peri-implantation period and some early reproductive outcomes with well-defined exposure windows. Previous investigations on
Corresponding author. E-mail addresses: [email protected] (X. Chen), [email protected] (Y. Qiu).
https://doi.org/10.1016/j.envres.2020.109304 Received 27 August 2019; Received in revised form 2 February 2020; Accepted 24 February 2020 Available online 25 February 2020 0013-9351/ © 2020 Published by Elsevier Inc.
Environmental Research 184 (2020) 109304
X. Zeng, et al.
the relationship between ambient air pollution and IVF outcomes focused mainly on short-term exposure at cycle initiation during the follicular phase, sometimes producing inconsistent results based the analysis of singular pollutant (Choe et al., 2018; Legro et al., 2010; Perin et al., 2010a, Perin et al., 2010b). No known study to date has examined whether IVF outcomes is differentially associated with exposure to air pollution for different maternal age groups; investigating such differential association may advance the understanding of mechanisms underlying pollution effect on human reproduction. To further investigate the impact of ambient air pollution on female reproductivity in a city with high annual average ambient pollution, we conducted a retrospective study on women who received IVF treatment at Reproductive Center of West China Second University Hospital, Sichuan University in Chengdu, located in the Sichuan Basin. Chengdu is one of the biggest cities in southwest China with more than 17 million residents (China Statistical Yearbook, 2006–2016). Air pollution is a serious problem in this city due to local topography (Clean Air Asia, 2016; NDRC, 2017). This study aims to explore the associations between ambient air pollution and pregnancy outcomes during different stages of IVF treatment cycle, from pre-antral follicles to IVF endpoints. Findings from this study could advance the current knowledge on exposure windows during IVF cycle and provide more evidence for future studies on human reproduction.
ovarian response as assessed by follicular growth and estradiol levels. Ovulation was induced with human chorionic gonadotropin (HCG, Livzon, Zhuhai, China or Ovidrel, Serono) when two or more follicles ≥18 mm in diameter were observed. Oocyte retrieval was performed 35–36 hours later. IVF was performed for fertilization. Standard procedures were performed for gamete-embryo handling. Between one and three high-quality embryos was transferred three days after oocyte retrieval depending on the women's age, embryo quality and other health factors. The remaining available embryos were freeze-stored. For luteal phase support, daily transvaginal progesterone or injective progesterone was started on the day of oocyte retrieval. Biochemical pregnancy is defined as when serum β-HCG is greater than 30 mIU/ml at 14 days after embryo transfer. Clinical pregnancy is defined as the identification of an intrauterine gestational sac by ultrasound after five weeks (35 days) of embryo transfer (Einarsson et al., 2017; Shi et al., 2018; Yu et al., 2018). 2.3. Ambient air quality data Hourly data of six criteria air pollutants (PM2.5 in μg/m3, PM10 in μg/m3, SO2 in μg/m3, NO2 in μg/m3, CO in mg/m3, O3 in μg/m3) were obtained from ten monitor stations of the China National Environmental Monitoring Centre (CNEMC, 2019). During the study period, hourly pollutant concentrations were reported 24-hour nonstop from each monitoring stations. According to national environmental protection standard (HJ 663–2013), for each station, we adopted 24hour average for all pollutants except for O3, and took the arithmetical average of pollutant concentration across all monitoring stations within the same district to calculate district-level daily pollutant concentration (China Ministry of Ecology and Environment MEE, 2013). For O3, a daily maximum 8-hour rolling average concentrations were adopted for each station, then we took the maximum pollution level among all monitoring stations within the same district as the district average O3 level. For each district, we calculated average ambient air pollutant concentration for aforementioned criteria pollutants during different periods of the IVF cycle (Fig. 1): A1: average concentration from start of gonadotropin medication (Gn start) to oocyte retrieval, A2: average concentration between 85 days prior to oocyte retrieval and the day of oocyte retrieval, B: average concentration from oocyte retrieval to embryo transfer, C: average concentration from embryo transfer to serum HCG test, D: average concentration from embryo transfer to ultrasound sound test for pregnancy, E1: average concentration between Gn start to serum HCG test, E2: average concentration between 85 days prior to oocyte retrieval and serum HCG test, F1: average concentration between Gn start to ultrasound test for pregnancy, F2: average concentration between 85 days prior to oocyte retrieval and ultrasound sound test for pregnancy.
2. Materials and methods 2.1. Study population and clinical data Clinical data from 19526 patients admitted between January 1, 2014 and January 31, 2019 were obtained from Reproductive Center of West China Second University Hospital, Sichuan University. The key selection criterium for this study is the patient's residential location: the patient must live in Chengdu metropolitan where the reproductive center is located. We assumed that the patients did not relocate during the IVF treatment period. Our monitoring data included the following districts of Chengdu metropolitan: Qingyang District, Jinjiang District, Wuhou District, Chenghua District, Jinniu Distrct, Longquanyi District and Dujiangyan city.1 Self-reported addresses in clinical record were geocoded. Additional selection criteria include:1) patients underwent their first fresh cycle, 2) patients used the conventional IVF method, and 3) patients' complete medical record data were accessible. In total, we included 1139 women for analysis. The study was approved by the Institutional Review Board of West China Second University Hospital, Sichuan University. All data used in this study were anonymous and stripped of any identifier. 2.2. IVF procedure Briefly, the IVF process is generally divided into four steps: the beginning of controlled ovarian stimulation (COS), oocyte retrieval, embryo transfer, and pregnancy test. Patients were treated by three COS protocols depending on the women's age, body mass index (BMI) and ovarian reserve test. The long GnRH agonist protocol with triporelin injection (Decapeptyl, Ferring AG) during the mid-luteal phase; the short GnRH agonist protocol with triptorelin injection started on day two or three of the cycle, or the GnRH antagonist protocol where the ganirelix (Orgalutran 0.25®, Organon, Netherland) was initiated on day five or six of the stimulation. Recombinant daily follicle-stimulating hormone (rFSH, Gonal F, Serono) was started once the patient reached pituitary down-regulation criteria in the long protocol, or on day two or three of the cycle in the short agonist and antagonist protocol respectively (also known as gonadotropin medication start, or Gn start). Subsequent gonadotropin medication doses were adjusted based on the 1
2.4. Statistical analysis The association between ambient air pollution and IVF outcomes were assessed using logistic regression. Statistical analysis considered two pregnancy outcomes: biochemical pregnancy (1 = pregnancy, 0 = otherwise) and clinical pregnancy (1 = pregnancy, 0 = otherwise).Maternal age at time of IVF treatment was categorized into three groups: < 35, 35–39 and ≥ 40 years; regression analyses were conducted separately for each age category. Each regression included the following covariates: maternal age, BMI, education level, the number of embryo transferred, and residential district. Education was categorized as “Postgraduate”, “Graduate”, “College”, “Junior college”, “High school” and “less than high school”. All covariates were reported to be associated with fecundability in previous studies (Choe et al., 2018; Gaskins et al., 2018). All statistical analyses were conducted in STATA (StataCorp, 2017) and Rstudio (R Development Core Team, 2008).
Dujiangyan city is a county-level city under the supervision of Chengdu city. 2
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Fig. 1. Timeline of IVF stages defined for current study. Table 1 Summary statistics of study popultion and IVF outcomes. Characteristic
Full Sample (1139 Women, 100%)
< 35 Years Old (722 Women, 63.3%)
35–39 Years Old (294 Women, 25.81%)
≥40 Years Old (123 Women, 10.80%)
Age (years) BMI (kg/m2) Cigarette smoking status Smoker Non-smoker Education level Graduate degree College degree Junior college degree High school Less than high school Working status Current worker Unemployed No. of oocytes retrieved No. of embryos transferred 1 embryo 2 embryos 3 embryosa IVF outcomes Biochemical pregnancy Clinical pregnancy
33.50 ± 4.38 21.30 ± 2.53
30.81 ± 2.39 21.01 ± 2.49
36.57 ± 1.43 21.64 ± 2.56
41.90 ± 1.97 22.13 ± 2.43
9 (0.79) 1130 (99.21)
4 (0.55) 718 (99.45)
4 (1.36) 290 (98.64)
1 (0.81) 122 (99.19)
190 (16.68) 513 (45.04) 263 (23.09) 105 (9.22) 68 (5.97)
128 (17.73) 349 (48.34) 153 (21.19) 58 (8.03) 34 (4.71)
47 (15.99) 116 (39.46) 77 (26.19) 32 (10.88) 22 (7.48)
21 (14.48) 53(36.55) 35 (24.14) 19 (13.10) 17 (11.72)
1030 (90.43) 109 (9.57) 7.76 ± 4.03 1.88 ± 0.49 210 (18.44) 860 (75.50) 69 (6.06)
654 (90.58) 68 (9.42) 8.62 ± 3.90 1.87 ± 0.34 97 (13.43) 625 (86.57) 0 (0.00)
266 (90.48) 28 (9.52) 6.94 ± 3.92 1.94 ± 0.65 71 (24.15) 169 (57.48) 54 (18.37)
12 (99.19) 13 (0.81) 4.60 ± 2.96 1.78 ± 0.65 42 (34.15) 66 (53.66) 15 (12.20)
538 (47.23) 518 (45.48)
365 (50.55) 351 (48.61)
147 (50.00) 143 (48.64)
26 (21.14) 24 (19.51)
Values are mean ± SD or n (%). a China requires that only women older than 35 can receive up to three embryos transfer at once.
3. Results
pregnancy rate of the study population is 47.23%, while ultrasound examination shows the clinical pregnancy rate is 45.48%. Comparable numbers of IVF patients between 2015 and 2018 were included in this study (Table S1). The number of patients from 2014 to 2019 was less than other years because 1) the IVF clinic started a trial phase of electronic records in 2014 and had limited number of complete records, and 2) the study population only included patients up until January 2019.2 All study subjects were geocoded to seven districts of Chengdu metropolitan according to their self-reported residential address (Fig. 2 and Table S2).
3.1. Summary of study population and variability of air pollution in Chengdu metropolitan The descriptive statistics of study population can be found in Table 1. The average age of studied women was approximately 33.5 years old (SD = 4.38), with an average BMI of 21.30 (SD = 2.53). Almost all individuals in this population did not smoke (99.21%) and were employed (90.43%). This population was well-educated with 16.68% obtaining a graduate degree and 45.04% obtaining a college degree. Mean number of retrieved oocytes and transferred embryos was 7.76 and 1.88 respectively (SD = 4.03 and 0.49, respectively). The biochemical
2 The clinic relocated in the early Feburary 2019. In order to keep consistency, the cutoff date of study period was set January 31, 2019.
3
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Fig. 2. Number of IVF patients from seven districts in Chengdu < et between 2014 and 2019.
Annual pollutant concentrations between 2014 and 2018 illustrates a declining trend for PM2.5, PM10, NO2, SO2, and CO (Table 2) and there is little geographical difference among districts besides Longquanyi and Dujiangyan, which are located further outside of Chengdu metropolitan area (Table S3). Most air pollutants were positively correlated with each other, while O3 was negatively correlated with other pollutants (Table S4).
pregnancy. During E1, five out of the six pollutants (PM2.5, PM10, SO2, NO2, CO) are associated with reduced odds of biochemical pregnancy (−0.5%, −0.3%, −4.9%, −1.5% and −44% respectively), while O3 is associated with increased odds (0.4%). During exposure windows A2 (between 85 days prior to oocyte retrieval and the day of oocyte retrieval), C (embryo transfer to serum HCG test) and E2 (between 85 days before oocyte retrieval and serum HCG test), PM2.5, PM10, SO2, NO2, CO are significantly associated with reduced odds of biochemical pregnancy. These five pollutants are associated with more reduction in the odds of biochemical pregnancy during window E2 (-1.0%, -0.6%, -7.1%, -2% and -63.4%, respectively) than during window A2 (-0.8%, -0.5%, -6.9%, -1.5% and -57.9% respectively) and window C (-0.5%, -0.3%, -4.7%, -1.7 and -48.3% respectively). This suggests that the longer the exposure window, the bigger the effects. For window A1 (Gn start to oocyte retrieval), exposure to NO2 and exposure to SO2 are significantly associated with reduced odds in biochemical pregnancy (-0.8% and -4.3%, respectively). Exposure to O3 is associated with increased odds of biochemical pregnancy, however, the association is only significant for windows A1 and E1. Overall, exposure to CO is
3.2. Association between ambient air pollution and IVF outcomes The relationship between air pollution exposure and IVF outcomes was similar between biochemical pregnancy (Table 3) and clinical pregnancy (Table 4). The association between ambient air pollution and IVF pregnancy outcomes was most evident in the youngest age group (< 35 years). In this age group, association is significant for NO2 during all exposure windows leading to biochemical pregnancy and for CO, SO2, PM2.5 and PM10 during most exposure windows. Exposure to all six pollutants during exposure windows E1 (gonadotropin start to serum HCG test) exhibited significant association with biochemical
Table 2 Summary of annual ambient pollutant concentrationa in Chengdu metropolitan 2014–2018. Year
PM2.5 (Mean ± SD)
PM10 (Mean ± SD)
NO2 (Mean ± SD)
SO2 (Mean ± SD)
CO (Mean ± SD)
O3 (Mean ± SD)
2014 2015 2016 2017 2018
71.88 59.95 59.09 52.56 46.99
114.14 ± 75.24 100.7 ± 62.92 99.14 ± 60.91 84.61 ± 66.1 76.8 ± 50.35
51.59 47.74 48.81 47.55 42.83
17.96 ± 11.52 15.62 ± 7.65 14.78 ± 7.08 12.06 ± 5.79 9.49 ± 4.15
1.07 1.03 1.07 0.85 0.83
0.49 0.46 0.43 0.42 0.3
91.63 ± 49.61 101.01 ± 59.64 102.15 ± 54.03 98.83 ± 52.76 103.09 ± 54.84
Overall Area
58.5 ± 43.52
95.51 ± 64.81
47.77 ± 21.75
13.88 ± 8.26
0.97 ± 0.44
98.41 ± 54.56
a
± ± ± ± ±
55.26 41.29 36.53 44.89 32.29
± ± ± ± ±
23.82 19.8 19.66 22.04 21.87
Annual concentration is city-wide average based on all avaiable monitor stations. 4
± ± ± ± ±
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Table 3 Summary of odds ratio for univariate pollutant regression for biochemical pregnancy by age groups. A1 < 35 Years Old, 722 women PM2.5 0.997 (0.992,1.001) PM10 0.998 (0.995,1.002) O3 1.004*** (1.002,1.006) SO2 0.957*** (0.938,0.976) 0.992* NO2 (0.986,0.998) CO 0.686 (0.420,1.121) 35–39 Years Old, 294 women PM2.5 1.003 (0.988,1.018) PM10 1.001 (0.991,1.011) O3 0.998 (0.995,1.00) SO2 0.969 (0.908,1.034) NO2 0.996 (0.959,1.035) CO 1.009 (0.263,3.877) ≥40 Years Old, 123 women PM2.5 1.004 (0.993,1.015) PM10 1.001 (0.994,1.008) O3 0.996 (0.99,1.002) SO2 0.983 (0.923,1.047) NO2 1.036 (0.985,1.089) CO 1.287 (0.272,6.086)
A2
B
C
E1
E2
0.992*** (0.988,0.995) 0.995* (0.991,0.999) 1.004 (1.00,1.008) 0.931*** (0.901,0.960) 0.985*** (0.976,0.994) 0.421** (0.224,0.792)
0.995* (0.992,0.999) 0.997 (0.994,1) 1.002 (0.999,1.005) 0.979 (0.955,1.004) 0.988* (0.978,0.999) 0.624*** (0.495,0.787)
0.995** (0.992,0.998) 0.997** (0.994,0.999) 1.003 (0.999,1.007) 0.953*** (0.939,0.969) 0.983*** (0.977,0.989) 0.517*** (0.411,0.649)
0.995** (0.992,0.999) 0.997* (0.995,1) 1.004* (1.001,1.007) 0.951*** (0.937,0.966) 0.985*** (0.981,0.99) 0.56*** (0.417,0.754)
0.990*** (0.986,0.995) 0.994** (0.99,0.998) 1.004 (1.00,1.009) 0.929*** (0.900,0.957) 0.98*** (0.972,0.988) 0.366** (0.199,0.674)
0.992 (0.97,1.014) 0.994 (0.982,1.007) 0.998 (0.989,1.007) 0.935 (0.85,1.028) 0.977 (0.936,1.02) 0.362 (0.051,2.547)
1.004 (0.996,1.011) 1.001 (0.996,1.006) 0.998 (0.995,1.002) 0.999 (0.944,1.059) 1.004 (0.982,1.027) 0.864 (0.424,1.759)
1.002 (0.993,1.011) 1.001 (0.994,1.009) 0.998 (0.993,1.003) 0.952* (0.91,0.996) 0.997 (0.974,1.02) 1.134 (0.518,2.482)
1.004 (0.991,1.017) 1.001 (0.992,1.011) 0.997 (0.994,1.001) 0.966 (0.901,1.036) 0.997 (0.959,1.037) 1.044 (0.317,3.432)
0.994 (0.971,1.017) 0.996 (0.982,1.009) 0.998 (0.989,1.006) 0.940 (0.863,1.022) 0.980 (0.938,1.025) 0.419 (0.058,3.01)
1.013 (0.998,1.029) 1.007 (0.998,1.015) 0.988* (0.977,0.999) 0.887*** (0.829,0.948) 1.013 (0.967,1.061) 2.883 (0.597,13.943)
1.004 (0.993,1.015) 1.001 (0.995,1.008) 0.995 (0.987,1.002) 1.000 (0.945,1.059) 1.026 (0.996,1.058) 2.702 (0.579,12.629)
1.001 (0.995,1.006) 1.000 (0.996,1.004) 0.997 (0.99,1.004) 1.021 (0.926,1.125) 1.013*** (1.006,1.020) 0.627 (0.249,1.578)
1.004 (0.993,1.015) 1.001 (0.995,1.008) 0.996 (0.99,1.002) 1.009 (0.931,1.094) 1.035 (0.999,1.071) 1.210 (0.293,4.993)
1.013 (0.999,1.027) 1.006 (0.999,1.014) 0.989* (0.978,0.999) 0.908* (0.841,0.981) 1.018 (0.977,1.060) 2.609 (0.492,13.832)
PM2.5, PM10, O3, SO2, NO2 and CO were each included in regression model, with control variables: age, BMI, education level, number of embryos transferred, and district fixed effect. A1, A2, B, C, E1 and E2 denote different stages of the IVF timeline for this study outlined in Fig. 1. Robust standard error was used using district clustered standard error. Significance levels: * < 0.05, ** < 0.001, *** < 0.0001. 95% confidence interval in parentheses.
associated with the most reduction in odds compared to other pollutants. For clinical pregnancy in females under 35 years old (Table 4), all pollutants have significant association with the odds of clinical pregnancy during windows D (embryo transfer to ultrasound detection of intrauterine gestation), F1 (gonadotropin start to ultrasound detection of intrauterine gestation), and F2 (between 85 days before oocyte retrival and ultrasound detection of intrauterine gestation). Exposure to PM2.5, NO2 and CO are significantly associated with reduced odds in clinical pregnancy during windows A2, B, D, F1, F2, while PM10 is only significantly associated during windows D, F1, and F2. Exposure to SO2 is significantly associated with decreased odds during all windows except B. Similar with findings in Table 3, exposure to CO is associated with most reduction in the odds of clinical pregnancy compared to other pollutants (−51.3% in A2, −32.9% in B, −52.6% in D, −51.7% in F1 and -63.5% in F2 respectively). Exposure to O3 is associated with increased odds of clinical pregnancy, and the association is significant for windows A1, B, D, F1 and F2 (0.5%, 0.3%, 0.4%, 0.5% and 0.5% respectively). In women age 35–39 years, exposure to SO2 is significantly
associated with reduced odds for biochemical pregnancy during window C (−4.8%) and for clinical pregnancy during windows D, F1 and F2 (−6.1%, −5.9% and −7.2% respectively). In women age 40 years and older, decreased odds in biochemical pregnancy is significantly associated with exposure to SO2 during windows A2 and E2 (−11.3% and 9.2%, respectively). Similarly, decreased odds in clinical pregnancy is also associated with exposure to SO2 during the same two windows (−13.1% and −13.8% respectively). Exposure to PM2.5 during windows D and F2 is significantly associated with reduced odds in clinical pregnancy (−0.15% and −0.11%), while during A2 is significantly associated with increased odds (1.6%). Expsure to CO is significantly associated with decreased odds in clinical pregnancy during windows D and F1 (−85.5% and −76.3% respectively), while associated with increased odds during windows A2, B, and F2, although the association is not significant. Exposure to O3 during windows A2 and E2 is significantly associated with reduced odds in biochemical pregnancy (-1.2% and −1.1%, respectively). The heterogeneity in the direction of association for some pollutants might be indicative of statistical instability due to small sample size of the ≥40 years age group.
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Table 4 Summary of odds ratio for univariate pollutant regression for clinical pregnancy by age groups. A1 < 35 Years Old, 722 women PM2.5 0.997 (0.992,1.003) PM10 0.999 (0.995,1.003) O3 1.005*** (1.003,1.007) SO2 0.959*** (0.941,0.978) 0.995 NO2 (0.987,1.003) CO 0.712 (0.410,1.239) 35–39 Years Old, 294 women PM2.5 1.003 (0.988,1.019) PM10 1.001 (0.991,1.011) O3 0.998 (0.995,1.001) SO2 0.966 (0.899,1.036) NO2 0.996 (0.959,1.036) CO 1.002 (0.251,3.991) ≥40 Years Old, 123 women PM2.5 0.998 (0.989,1.007) PM10 0.997 (0.991,1.003) O3 1.000 (0.995,1.004) SO2 0.955 (0.839,1.088) NO2 1.027 (0.983,1.075) CO 0.758 (0.233,2.469)
A2
B
D
F1
F2
0.994*** (0.99,0.998) 0.996 (0.992,1.001) 1.004 (1.000,1.008) 0.939*** (0.912,0.968) 0.989** (0.982,0.997) 0.487* (0.262,0.905)
0.996** (0.994,0.999) 0.998 (0.996,1.00) 1.003* (1.001,1.005) 0.982 (0.961,1.004) 0.99* (0.982,0.998) 0.671*** (0.553,0.815)
0.994** (0.99,0.998) 0.996** (0.993,0.999) 1.004** (1.001,1.007) 0.946*** (0.919,0.974) 0.979*** (0.973,0.985) 0.474*** (0.358,0.626)
0.994* (0.99,0.999) 0.996* (0.993,1.000) 1.005*** (1.002,1.007) 0.946*** (0.922,0.969) 0.98*** (0.976,0.984) 0.483*** (0.333,0.700)
0.991** (0.985,0.997) 0.994* (0.989,1.000) 1.005* (1.001,1.010) 0.936*** (0.911,0.961) 0.979*** (0.973,0.984) 0.365** (0.196,0.680)
0.994 (0.972,1.017) 0.995 (0.982,1.009) 0.998 (0.988,1.008) 0.928 (0.839,1.025) 0.980 (0.938,1.024) 0.365 (0.047,2.849)
1.002 (0.995,1.010) 1.000 (0.994,1.005) 0.998 (0.995,1.001) 0.978 (0.924,1.037) 0.999 (0.977,1.021) 0.707 (0.291,1.718)
1.004 (0.996,1.012) 1.003 (0.997,1.008) 0.999 (0.994,1.004) 0.939* (0.893,0.987) 0.996 (0.978,1.014) 1.178 (0.562,2.469)
1.004 (0.993,1.015) 1.002 (0.994,1.010) 0.999 (0.995,1.003) 0.941* (0.885,1.000) 0.994 (0.964,1.025) 1.106 (0.357,3.421)
0.998 (0.976,1.021) 0.998 (0.984,1.011) 0.998 (0.989,1.006) 0.928* (0.863,0.996) 0.982 (0.94,1.025) 0.470 (0.06,3.691)
1.016* (1.001,1.033) 1.007 (0.999,1.014) 0.990 (0.98,1.001) 0.869* (0.78,0.969) 1.031 (0.961,1.106) 2.832 (0.329,24.361)
0.999 (0.991,1.007) 0.997 (0.994,1.001) 0.996 (0.989,1.003) 0.944 (0.887,1.005) 1.025 (0.988,1.063) 1.413 (0.331,6.044)
0.985* (0.972,0.998) 0.991 (0.981,1) 0.999 (0.986,1.013) 0.931 (0.811,1.068) 1.009 (0.963,1.057) 0.145* (0.033,0.638)
0.989* (0.979,0.999) 0.992* (0.985,1.000) 0.999 (0.988,1.010) 0.924 (0.82,1.042) 1.020 (0.977,1.065) 0.237* (0.06,0.928)
1.005 (0.995,1.015) 1.001 (0.994,1.008) 0.992 (0.984,1.000) 0.862** (0.783,0.95) 1.031 (0.972,1.093) 1.168 (0.086,15.784)
PM2.5, PM10, O3, SO2, NO2 and CO were each included in regression model, with control variables: age, BMI, education level, number of embryos transferred, and district fixed effect. A1, A2, B, D, F1 and F2 denotes different stages of the IVF timeline for this study outlined in Fig. 1. Robust standard error was used using district clustered standard error. Significance levels: * < 0.05, ** < 0.001, *** < 0.0001. 95% confidence interval in parentheses.
4. Discussion
2008). Oxidative stress has been suggested as a major contributor to chromosomal abnormalities (Igarashi et al., 2015; Tatone et al., 2006) and also the embryo fragmentation, resulting in negative impact on IVF outcomes (Agarwal et al. 2008, 2012). While age-related ovarian reserve decline might have played a dominant role in IVF outcomes among older women, effects of ambient air pollution might have contributed more to pregnancy outcomes in younger women. In other words, the effects of air pollutants on IVF outcomes in older people might be masked by agerelated effects. Additionally, older females in our population were welleducated working adults, who could have been more aware of air pollution consequences and might have adopted more protective lifestyle. Our study also finds that exposure to CO appears to be associated with the greatest reduction in the odds of biochemical and clinical pregnancy outcomes among females younger than 35 years. The inverse relationship between CO and intrauterine pregnancy confirms earlier findings by Choe and colleages (Choe et al., 2018. The relationship between O3 exposure and IVF pregnancy outcomes is opposite of that between exposure to other pollutants and IVF outcomes. O3 is a secondary air pollutant formed from precursor pollutants, such as NO2 and SO2 (Carter, 1994; Carter and Atkinson, 2017; Shao et al., 2009). The concentration of ground-level O3 is thus negatively correlated with the concentration of its precursors. In Chengdu, clear days with sunshine are reflective of overall better ambient air quality (lower concentration of
4.1. Maternal age, air pollution, and IVF outcomes In this retrospective study, we explored the differential association between ambient air pollution and IVF outcomes during different exposure windows for different maternal age categories. Maternal age is one of the most significant risk factors for fecundity and fertility impairment in the general female population, due to ovarian ageing including declines in oocyte yields and oocyte quality. Specifically, as age increases, the likelihood of oocytes chromosomal abnormality and cellular dysfunction increases, resulting in a decrease in oocyte quality (Igarashi et al., 2015; Vollenhoven and Hunt, 2018). Advanced maternal age has also been demonstrated to negatively influence IVF outcomes (Ryan et al., 2005; von Wolff et al., 2019). In our study, older women (> 40 years) have a much lower biochemical and clinical pregnancy rate than younger women (35–39, and < 35 years), suggesting that age-related biological condition may play an increasing role in pregnancy outcomes as women age. However, the effects of ambient air pollution differ by age groups, and younger women (< 35 years) were more vulnerable to ambient air pollution than older women. Air pollutants can act as reactive oxygen species or are capable of generating them, promoting oxidative stress and the inflammatory processes (Kampa and Castanas, 6
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precursor pollutants), a situation supported by the negative correlation coefficients between O3 and other five pollutants we observed in our study (Table S4). Therefore, the positive relationship between O3 exposure and IVF outcomes could be explained by viewing O3 concentration as a proxy for lower ambient air pollution. The relationship between ambient air pollution and IVF outcomes does not appear to vary during different exposure windows before or within the IVF treatment timeline, and women aged less than 35 years old were more vulnerable to air pollutants than women who are more than 40 years old and 35–39 years old. Additionally, exposure to CO appears to be associated with the largest reduction in odds for biochemical and clinical pregnancy, a finding that may point to the direction for future pollution control studies. Our results suggest that long-term exposure to ambient air pollution during the whole follicular growth period has negative association with IVF outcomes in younger women. Beyond the IVF population, women who conceive naturally may also face long-term exposure to ambient air pollution, therefore, our study results could point to the critical timeline for future studies on female reproduction.
other cities in China. Additionally, in calculating ambient pollution, we could only match air pollution level with residential address as we don't have information on patients' daily activities to quantify potential pollution level at other relevant locations. Using pollution at residential location does not reflect exposure occurring at work place and during transit, which could be major locations for personal exposure. 5. Conclusion We conducted a retrospective study to investigate the relationship between ambient air pollution and IVF outcomes in 1139 women from Chengdu metropolitan between 2014 and 2019. Our findings suggest significant inverse relationship between the exposure to ambient air pollution and IVF outcomes. This association is most pronounced for young women (< 35 years). Additionally, long-term exposure to PM2.5, SO2, NO2 and CO at multiple stages of the IVF timeline exhibited significant inverse association with biochemical and clinical pregnancy outcomes, whereas chronic exposure to O3 reported increased odds for clinical pregnancy outcome. Long-term exposure to ambient air pollution is a situation faced by all females during reproductive age in China. Our findings from this study could be applied for future studies on human reproduction beyond the IVF population.
4.2. Significance and Limitation To our knowledge, our study is the first to investigate the differential association between ambient air pollution and different age groups for IVF population. Our study also investigated in depth and suggested the potential impact of long-term exposure to ambient pollution, which is a situation faced by both IVF population and the general reproductive age female population in many Chinese cities. Additionally, our study results also help to advance the understanding of ambient air pollution and human reproduction by providing analysis on a population from rapidly urbanizing region in western China that has experienced elevated and high level ambient air pollution. Our study population was overall non-smoking, well-educated with college level and almost all reported full employment status, this may not be reflective of the female population at large for Chengdu and
Declaration of competing interest We have no conflict of interest to declare for our manuscript ER-S19-2601titled “Association between Ambient Air Pollution and Pregnancy Outcomes in Patients Undergoing In Vitro Fertilization in Chengdu, China: A Retrospective Study”. Acknowledgment This study was partially supported by the Sichuan "1000 Talent" Young Scholar Program.
Supplemental Information Table S1
Summary of annual IVF patient number 2014–2019a by different age groups. Year
Number of Patients (%)
< 35 Years Old (%)
35–39 Years Old (%)
≥40 Years Old (%)
2014 2015 2016 2017 2018 2019
33 (2.9) 273 (23.97) 296 (25.99) 301 (26.43) 219 (19.23) 17 (1.49)
27 (3.74) 165 (22.85) 191 (26.45) 179 (24.79) 150 (20.78) 10 (1.39)
4 (1.36) 80 (27.21) 71 (24.15) 82 (27.89) 51 (17.35) 6 (2.04)
2 (1.63) 28 (22.76) 34 (27.64) 40 (32.52) 18 (14.63) 1 (0.81)
Total
1139 (100)
722 (100)
294 (100)
123 (100)
a
Study period is March 5, 2014 to January 22, 2019.
Table S2
Summary of IVF patients number and pregnancy outcome by districts. Pregnancy Outcome (%)
District
No. of Patients (%)
No. of Biochemical Pregnancy (%)
Chenghua Wuhou Qingyang Jinniu Jinjiang Dujiangyan Longquanyi
167 (14.66) 250 (21.95) 59 (5.18) 233 (20.46) 154 (13.52) 241 (21.16) 35 (3.07)
74 (44.31) 127 (50.80) 23 (38.98) 115 (49.36) 79 (51.30) 105 (43.57) 15 (42.86)
70 (41.92) 123 (49.20) 22 (37.29) 113 (48.50) 77 (50.00) 98 (40.66) 15 (42.86)
Total Area
1139 (100)
538 (47.23)
518 (45.48)
7
No. of Clinical Pregnancy (%)
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Table S3
Summary of ambient air pollutant concentration by monitor stations in Chengdu metropolitan. District
PM2.5 (Mean ± SD)
PM10 (Mean ± SD)
NO2 (Mean ± SD)
SO2 (Mean ± SD)
CO (Mean ± SD)
O3 (Mean ± SD)
Chenghua Wuhou Qingyang Jinniu Jinjiang Dujiangyan Longquanyi
63.94 ± 46.7 61.23 ± 44.39 62.43 ± 44.11 65.69 ± 46.29 59.64 ± 45.63 40.3 ± 28.11 48 ± 31.37
107.57 ± 67.94 100.95 ± 66.77 101.31 ± 65.25 106.16 ± 67.44 97.06 ± 68.42 64.94 ± 41.87 72.73 ± 45.53
53.8 ± 19.14 57.77 ± 20.44 53.96 ± 19.22 52.07 ± 18.45 52.91 ± 17.4 20.7 ± 9.94 30.32 ± 12.99
13.65 ± 8.29 14.91 ± 8.7 14.07 ± 8.6 14.76 ± 8.43 12.35 ± 6.82 15.14 ± 8.66 7.83 ± 2.56
1.08 ± 0.4 1.07 ± 0.43 1.02 ± 0.39 1.1 ± 0.38 1.07 ± 0.41 0.49 ± 0.27 0.89 ± 0.23
96.28 ± 55.11 97.29 ± 55.39 97.92 ± 56.13 100.77 ± 58.75 84.08 ± 50.76 116.3 ± 47.96 90.95 ± 43.41
Total area
58.5 ± 43.52
95.51 ± 64.81
47.77 ± 21.75
13.88 ± 8.26
0.97 ± 0.44
98.41 ± 54.56
*Polluant concentration is district-wide average based on all avaiable monitor stations. Data period is December 10, 2013 to February 26, 2019, which includes the period of 85 days prior to the record offirst oocyte retrieval and 35 days post the record of last oocyte retrieval in the study.
Table S4
Correlation Among Ambient Air Pollutants in Chengdu 2013–2019a. PM2.5 PM2.5 PM10 NO2 SO2 CO O3
0.9435 0.6638 0.5086 0.7288 −0.2423
PM10
NO2
SO2
CO
O3
0.9509
0.6711 0.6949
0.4768 0.4945 0.3717
0.6798 0.6569 0.7036 0.3554
−0.2236 −0.1852 −0.2039 0.0318 −0.3002
0.6898 0.5159 0.7118 −0.2048
0.3789 0.7189 −0.1697
0.3985 −0.0156
−0.2892
Pearson's correlation coefficients are shown in the lower left triangle, while Spearman's rank correlations appear in the upper right triangle. a Data period is December 10, 2013 to February 26, 2019.
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Association between Ambient Air Pollution and Pregnancy Outcomes in Patients Undergoing In Vitro Fertilization in Chengdu, China: A retrospective study
T
Xun Zenga,b, Song Jina,b, Xiaolan Chenc,∗, Yang Qiud,∗ a
Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, China Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, China c Department of Economics, School of Economics, Sichuan University, Chengdu, China d Department of Environmental Sciences and Engineering, School of Architecture and Environmental Sciences, Sichuan University, Chengdu, China b
ARTICLE INFO
ABSTRACT
Keywords: In vitro fertilization/IVF Female reproduction Ambient air pollution Retrospective study
Ambient air pollution has been a major concern in China due to its effect on population health. Exposure to ambient air pollution has negative impact on animal reproduction and fertility, however, its effect on human reproduction has been inconclusive. We conducted a retrospective study on in vitro fertilization (IVF) patients from Chengdu, Sichuan Province in western China, a city with persistent ambient air pollution. We analyzed the medical records of 1139 patients who underwent first conventional IVF cycles during 2014–2019. The relationship between six atmospheric pollutants (PM2.5, PM10, O3, NO2, SO2, CO) and IVF pregnancy outcomes were assessed by 1) stratification of maternal age into three groups (< 35, 35–39, ≥40 years), and by 2) averaging pollutant concentration during different exposure windows. The results indicate that the association between ambient air pollution and IVF pregnancy outcomes (biochemical pregnancy and clinical pregnancy) is more significant for women in < 35 years age group. Concentrations of PM2.5, PM10, NO2, SO2 and CO are negatively associated with the odds of biochemical pregnancy and clinical pregnancy, and concentration of CO in particular is associated with the largest reduction in odds. Conversely, O3 concentration is positively associated with biochemical pregnancy and clinical pregnancy. Moreover, pollutant concentration during long-term exposure window is associated with larger magnitude of change in the odds of biochemical pregnancy and clinical pregnancy. Findings from this study suggest that exposure to ambient air pollution during any period within the IVF treatment timeline would influence IVF pregnancy outcomes, and such influence is more pronounced in younger women (< 35 years).
1. Introduction Exposure to ambient air pollution has been identified as one of the leading risk factors for population health. At the global level, air pollution is linked to respiratory diseases (Tomaskova et al., 2016), cardiovascular disorders (Pope et al., 2004; Shah et al., 2013), and increased risk of cancer (Loomis et al. 2013, 2014). In recent years, environmental epidemiology studies have found an association between air pollution and adverse perinatal outcomes such as intrauterine growth restriction (Lee et al., 2013), low birth weight (Estarlich et al., 2011; Pedersen et al., 2013) and prematurity (Fleischer et al., 2014). A growing number of studies have suggested that exposure to ambient air pollution is associated with reduced fertility and spontaneous fertility rate (Dejmek et al., 2000; Nieuwenhuijsen et al., 2014; Slama et al., 2013). *
Human reproduction process includes a number of developmental stages: gametogenesis, insemination, fertilization, cleavage, implantation, placentation, gastrulation, organogenesis and parturition (Atwood and Vadakkadath Meethal, 2016; Edwards, 2006; Hutt and Albertini, 2007; Jasienska et al., 2017). In fertile females, ovarian follicle growth is a lengthy process. In each cycle it takes a cohort of pre-antral follicles 85 days until the dominant follicle ovulates (Gougeon 1998, 2010). An exposure period of approximately 85 days is reasonably accepted as being of sufficient duration for detecting chronic impact on female reproductive function affecting oocyte quality and pre-implantation embryonic development. The advent of in vitro fertilization (IVF) provides a clinical timeline to observe reproductive and developmental events during the peri-implantation period and some early reproductive outcomes with well-defined exposure windows. Previous investigations on
Corresponding author. E-mail addresses: [email protected] (X. Chen), [email protected] (Y. Qiu).
https://doi.org/10.1016/j.envres.2020.109304 Received 27 August 2019; Received in revised form 2 February 2020; Accepted 24 February 2020 Available online 25 February 2020 0013-9351/ © 2020 Published by Elsevier Inc.
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the relationship between ambient air pollution and IVF outcomes focused mainly on short-term exposure at cycle initiation during the follicular phase, sometimes producing inconsistent results based the analysis of singular pollutant (Choe et al., 2018; Legro et al., 2010; Perin et al., 2010a, Perin et al., 2010b). No known study to date has examined whether IVF outcomes is differentially associated with exposure to air pollution for different maternal age groups; investigating such differential association may advance the understanding of mechanisms underlying pollution effect on human reproduction. To further investigate the impact of ambient air pollution on female reproductivity in a city with high annual average ambient pollution, we conducted a retrospective study on women who received IVF treatment at Reproductive Center of West China Second University Hospital, Sichuan University in Chengdu, located in the Sichuan Basin. Chengdu is one of the biggest cities in southwest China with more than 17 million residents (China Statistical Yearbook, 2006–2016). Air pollution is a serious problem in this city due to local topography (Clean Air Asia, 2016; NDRC, 2017). This study aims to explore the associations between ambient air pollution and pregnancy outcomes during different stages of IVF treatment cycle, from pre-antral follicles to IVF endpoints. Findings from this study could advance the current knowledge on exposure windows during IVF cycle and provide more evidence for future studies on human reproduction.
ovarian response as assessed by follicular growth and estradiol levels. Ovulation was induced with human chorionic gonadotropin (HCG, Livzon, Zhuhai, China or Ovidrel, Serono) when two or more follicles ≥18 mm in diameter were observed. Oocyte retrieval was performed 35–36 hours later. IVF was performed for fertilization. Standard procedures were performed for gamete-embryo handling. Between one and three high-quality embryos was transferred three days after oocyte retrieval depending on the women's age, embryo quality and other health factors. The remaining available embryos were freeze-stored. For luteal phase support, daily transvaginal progesterone or injective progesterone was started on the day of oocyte retrieval. Biochemical pregnancy is defined as when serum β-HCG is greater than 30 mIU/ml at 14 days after embryo transfer. Clinical pregnancy is defined as the identification of an intrauterine gestational sac by ultrasound after five weeks (35 days) of embryo transfer (Einarsson et al., 2017; Shi et al., 2018; Yu et al., 2018). 2.3. Ambient air quality data Hourly data of six criteria air pollutants (PM2.5 in μg/m3, PM10 in μg/m3, SO2 in μg/m3, NO2 in μg/m3, CO in mg/m3, O3 in μg/m3) were obtained from ten monitor stations of the China National Environmental Monitoring Centre (CNEMC, 2019). During the study period, hourly pollutant concentrations were reported 24-hour nonstop from each monitoring stations. According to national environmental protection standard (HJ 663–2013), for each station, we adopted 24hour average for all pollutants except for O3, and took the arithmetical average of pollutant concentration across all monitoring stations within the same district to calculate district-level daily pollutant concentration (China Ministry of Ecology and Environment MEE, 2013). For O3, a daily maximum 8-hour rolling average concentrations were adopted for each station, then we took the maximum pollution level among all monitoring stations within the same district as the district average O3 level. For each district, we calculated average ambient air pollutant concentration for aforementioned criteria pollutants during different periods of the IVF cycle (Fig. 1): A1: average concentration from start of gonadotropin medication (Gn start) to oocyte retrieval, A2: average concentration between 85 days prior to oocyte retrieval and the day of oocyte retrieval, B: average concentration from oocyte retrieval to embryo transfer, C: average concentration from embryo transfer to serum HCG test, D: average concentration from embryo transfer to ultrasound sound test for pregnancy, E1: average concentration between Gn start to serum HCG test, E2: average concentration between 85 days prior to oocyte retrieval and serum HCG test, F1: average concentration between Gn start to ultrasound test for pregnancy, F2: average concentration between 85 days prior to oocyte retrieval and ultrasound sound test for pregnancy.
2. Materials and methods 2.1. Study population and clinical data Clinical data from 19526 patients admitted between January 1, 2014 and January 31, 2019 were obtained from Reproductive Center of West China Second University Hospital, Sichuan University. The key selection criterium for this study is the patient's residential location: the patient must live in Chengdu metropolitan where the reproductive center is located. We assumed that the patients did not relocate during the IVF treatment period. Our monitoring data included the following districts of Chengdu metropolitan: Qingyang District, Jinjiang District, Wuhou District, Chenghua District, Jinniu Distrct, Longquanyi District and Dujiangyan city.1 Self-reported addresses in clinical record were geocoded. Additional selection criteria include:1) patients underwent their first fresh cycle, 2) patients used the conventional IVF method, and 3) patients' complete medical record data were accessible. In total, we included 1139 women for analysis. The study was approved by the Institutional Review Board of West China Second University Hospital, Sichuan University. All data used in this study were anonymous and stripped of any identifier. 2.2. IVF procedure Briefly, the IVF process is generally divided into four steps: the beginning of controlled ovarian stimulation (COS), oocyte retrieval, embryo transfer, and pregnancy test. Patients were treated by three COS protocols depending on the women's age, body mass index (BMI) and ovarian reserve test. The long GnRH agonist protocol with triporelin injection (Decapeptyl, Ferring AG) during the mid-luteal phase; the short GnRH agonist protocol with triptorelin injection started on day two or three of the cycle, or the GnRH antagonist protocol where the ganirelix (Orgalutran 0.25®, Organon, Netherland) was initiated on day five or six of the stimulation. Recombinant daily follicle-stimulating hormone (rFSH, Gonal F, Serono) was started once the patient reached pituitary down-regulation criteria in the long protocol, or on day two or three of the cycle in the short agonist and antagonist protocol respectively (also known as gonadotropin medication start, or Gn start). Subsequent gonadotropin medication doses were adjusted based on the 1
2.4. Statistical analysis The association between ambient air pollution and IVF outcomes were assessed using logistic regression. Statistical analysis considered two pregnancy outcomes: biochemical pregnancy (1 = pregnancy, 0 = otherwise) and clinical pregnancy (1 = pregnancy, 0 = otherwise).Maternal age at time of IVF treatment was categorized into three groups: < 35, 35–39 and ≥ 40 years; regression analyses were conducted separately for each age category. Each regression included the following covariates: maternal age, BMI, education level, the number of embryo transferred, and residential district. Education was categorized as “Postgraduate”, “Graduate”, “College”, “Junior college”, “High school” and “less than high school”. All covariates were reported to be associated with fecundability in previous studies (Choe et al., 2018; Gaskins et al., 2018). All statistical analyses were conducted in STATA (StataCorp, 2017) and Rstudio (R Development Core Team, 2008).
Dujiangyan city is a county-level city under the supervision of Chengdu city. 2
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Fig. 1. Timeline of IVF stages defined for current study. Table 1 Summary statistics of study popultion and IVF outcomes. Characteristic
Full Sample (1139 Women, 100%)
< 35 Years Old (722 Women, 63.3%)
35–39 Years Old (294 Women, 25.81%)
≥40 Years Old (123 Women, 10.80%)
Age (years) BMI (kg/m2) Cigarette smoking status Smoker Non-smoker Education level Graduate degree College degree Junior college degree High school Less than high school Working status Current worker Unemployed No. of oocytes retrieved No. of embryos transferred 1 embryo 2 embryos 3 embryosa IVF outcomes Biochemical pregnancy Clinical pregnancy
33.50 ± 4.38 21.30 ± 2.53
30.81 ± 2.39 21.01 ± 2.49
36.57 ± 1.43 21.64 ± 2.56
41.90 ± 1.97 22.13 ± 2.43
9 (0.79) 1130 (99.21)
4 (0.55) 718 (99.45)
4 (1.36) 290 (98.64)
1 (0.81) 122 (99.19)
190 (16.68) 513 (45.04) 263 (23.09) 105 (9.22) 68 (5.97)
128 (17.73) 349 (48.34) 153 (21.19) 58 (8.03) 34 (4.71)
47 (15.99) 116 (39.46) 77 (26.19) 32 (10.88) 22 (7.48)
21 (14.48) 53(36.55) 35 (24.14) 19 (13.10) 17 (11.72)
1030 (90.43) 109 (9.57) 7.76 ± 4.03 1.88 ± 0.49 210 (18.44) 860 (75.50) 69 (6.06)
654 (90.58) 68 (9.42) 8.62 ± 3.90 1.87 ± 0.34 97 (13.43) 625 (86.57) 0 (0.00)
266 (90.48) 28 (9.52) 6.94 ± 3.92 1.94 ± 0.65 71 (24.15) 169 (57.48) 54 (18.37)
12 (99.19) 13 (0.81) 4.60 ± 2.96 1.78 ± 0.65 42 (34.15) 66 (53.66) 15 (12.20)
538 (47.23) 518 (45.48)
365 (50.55) 351 (48.61)
147 (50.00) 143 (48.64)
26 (21.14) 24 (19.51)
Values are mean ± SD or n (%). a China requires that only women older than 35 can receive up to three embryos transfer at once.
3. Results
pregnancy rate of the study population is 47.23%, while ultrasound examination shows the clinical pregnancy rate is 45.48%. Comparable numbers of IVF patients between 2015 and 2018 were included in this study (Table S1). The number of patients from 2014 to 2019 was less than other years because 1) the IVF clinic started a trial phase of electronic records in 2014 and had limited number of complete records, and 2) the study population only included patients up until January 2019.2 All study subjects were geocoded to seven districts of Chengdu metropolitan according to their self-reported residential address (Fig. 2 and Table S2).
3.1. Summary of study population and variability of air pollution in Chengdu metropolitan The descriptive statistics of study population can be found in Table 1. The average age of studied women was approximately 33.5 years old (SD = 4.38), with an average BMI of 21.30 (SD = 2.53). Almost all individuals in this population did not smoke (99.21%) and were employed (90.43%). This population was well-educated with 16.68% obtaining a graduate degree and 45.04% obtaining a college degree. Mean number of retrieved oocytes and transferred embryos was 7.76 and 1.88 respectively (SD = 4.03 and 0.49, respectively). The biochemical
2 The clinic relocated in the early Feburary 2019. In order to keep consistency, the cutoff date of study period was set January 31, 2019.
3
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Fig. 2. Number of IVF patients from seven districts in Chengdu < et between 2014 and 2019.
Annual pollutant concentrations between 2014 and 2018 illustrates a declining trend for PM2.5, PM10, NO2, SO2, and CO (Table 2) and there is little geographical difference among districts besides Longquanyi and Dujiangyan, which are located further outside of Chengdu metropolitan area (Table S3). Most air pollutants were positively correlated with each other, while O3 was negatively correlated with other pollutants (Table S4).
pregnancy. During E1, five out of the six pollutants (PM2.5, PM10, SO2, NO2, CO) are associated with reduced odds of biochemical pregnancy (−0.5%, −0.3%, −4.9%, −1.5% and −44% respectively), while O3 is associated with increased odds (0.4%). During exposure windows A2 (between 85 days prior to oocyte retrieval and the day of oocyte retrieval), C (embryo transfer to serum HCG test) and E2 (between 85 days before oocyte retrieval and serum HCG test), PM2.5, PM10, SO2, NO2, CO are significantly associated with reduced odds of biochemical pregnancy. These five pollutants are associated with more reduction in the odds of biochemical pregnancy during window E2 (-1.0%, -0.6%, -7.1%, -2% and -63.4%, respectively) than during window A2 (-0.8%, -0.5%, -6.9%, -1.5% and -57.9% respectively) and window C (-0.5%, -0.3%, -4.7%, -1.7 and -48.3% respectively). This suggests that the longer the exposure window, the bigger the effects. For window A1 (Gn start to oocyte retrieval), exposure to NO2 and exposure to SO2 are significantly associated with reduced odds in biochemical pregnancy (-0.8% and -4.3%, respectively). Exposure to O3 is associated with increased odds of biochemical pregnancy, however, the association is only significant for windows A1 and E1. Overall, exposure to CO is
3.2. Association between ambient air pollution and IVF outcomes The relationship between air pollution exposure and IVF outcomes was similar between biochemical pregnancy (Table 3) and clinical pregnancy (Table 4). The association between ambient air pollution and IVF pregnancy outcomes was most evident in the youngest age group (< 35 years). In this age group, association is significant for NO2 during all exposure windows leading to biochemical pregnancy and for CO, SO2, PM2.5 and PM10 during most exposure windows. Exposure to all six pollutants during exposure windows E1 (gonadotropin start to serum HCG test) exhibited significant association with biochemical
Table 2 Summary of annual ambient pollutant concentrationa in Chengdu metropolitan 2014–2018. Year
PM2.5 (Mean ± SD)
PM10 (Mean ± SD)
NO2 (Mean ± SD)
SO2 (Mean ± SD)
CO (Mean ± SD)
O3 (Mean ± SD)
2014 2015 2016 2017 2018
71.88 59.95 59.09 52.56 46.99
114.14 ± 75.24 100.7 ± 62.92 99.14 ± 60.91 84.61 ± 66.1 76.8 ± 50.35
51.59 47.74 48.81 47.55 42.83
17.96 ± 11.52 15.62 ± 7.65 14.78 ± 7.08 12.06 ± 5.79 9.49 ± 4.15
1.07 1.03 1.07 0.85 0.83
0.49 0.46 0.43 0.42 0.3
91.63 ± 49.61 101.01 ± 59.64 102.15 ± 54.03 98.83 ± 52.76 103.09 ± 54.84
Overall Area
58.5 ± 43.52
95.51 ± 64.81
47.77 ± 21.75
13.88 ± 8.26
0.97 ± 0.44
98.41 ± 54.56
a
± ± ± ± ±
55.26 41.29 36.53 44.89 32.29
± ± ± ± ±
23.82 19.8 19.66 22.04 21.87
Annual concentration is city-wide average based on all avaiable monitor stations. 4
± ± ± ± ±
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Table 3 Summary of odds ratio for univariate pollutant regression for biochemical pregnancy by age groups. A1 < 35 Years Old, 722 women PM2.5 0.997 (0.992,1.001) PM10 0.998 (0.995,1.002) O3 1.004*** (1.002,1.006) SO2 0.957*** (0.938,0.976) 0.992* NO2 (0.986,0.998) CO 0.686 (0.420,1.121) 35–39 Years Old, 294 women PM2.5 1.003 (0.988,1.018) PM10 1.001 (0.991,1.011) O3 0.998 (0.995,1.00) SO2 0.969 (0.908,1.034) NO2 0.996 (0.959,1.035) CO 1.009 (0.263,3.877) ≥40 Years Old, 123 women PM2.5 1.004 (0.993,1.015) PM10 1.001 (0.994,1.008) O3 0.996 (0.99,1.002) SO2 0.983 (0.923,1.047) NO2 1.036 (0.985,1.089) CO 1.287 (0.272,6.086)
A2
B
C
E1
E2
0.992*** (0.988,0.995) 0.995* (0.991,0.999) 1.004 (1.00,1.008) 0.931*** (0.901,0.960) 0.985*** (0.976,0.994) 0.421** (0.224,0.792)
0.995* (0.992,0.999) 0.997 (0.994,1) 1.002 (0.999,1.005) 0.979 (0.955,1.004) 0.988* (0.978,0.999) 0.624*** (0.495,0.787)
0.995** (0.992,0.998) 0.997** (0.994,0.999) 1.003 (0.999,1.007) 0.953*** (0.939,0.969) 0.983*** (0.977,0.989) 0.517*** (0.411,0.649)
0.995** (0.992,0.999) 0.997* (0.995,1) 1.004* (1.001,1.007) 0.951*** (0.937,0.966) 0.985*** (0.981,0.99) 0.56*** (0.417,0.754)
0.990*** (0.986,0.995) 0.994** (0.99,0.998) 1.004 (1.00,1.009) 0.929*** (0.900,0.957) 0.98*** (0.972,0.988) 0.366** (0.199,0.674)
0.992 (0.97,1.014) 0.994 (0.982,1.007) 0.998 (0.989,1.007) 0.935 (0.85,1.028) 0.977 (0.936,1.02) 0.362 (0.051,2.547)
1.004 (0.996,1.011) 1.001 (0.996,1.006) 0.998 (0.995,1.002) 0.999 (0.944,1.059) 1.004 (0.982,1.027) 0.864 (0.424,1.759)
1.002 (0.993,1.011) 1.001 (0.994,1.009) 0.998 (0.993,1.003) 0.952* (0.91,0.996) 0.997 (0.974,1.02) 1.134 (0.518,2.482)
1.004 (0.991,1.017) 1.001 (0.992,1.011) 0.997 (0.994,1.001) 0.966 (0.901,1.036) 0.997 (0.959,1.037) 1.044 (0.317,3.432)
0.994 (0.971,1.017) 0.996 (0.982,1.009) 0.998 (0.989,1.006) 0.940 (0.863,1.022) 0.980 (0.938,1.025) 0.419 (0.058,3.01)
1.013 (0.998,1.029) 1.007 (0.998,1.015) 0.988* (0.977,0.999) 0.887*** (0.829,0.948) 1.013 (0.967,1.061) 2.883 (0.597,13.943)
1.004 (0.993,1.015) 1.001 (0.995,1.008) 0.995 (0.987,1.002) 1.000 (0.945,1.059) 1.026 (0.996,1.058) 2.702 (0.579,12.629)
1.001 (0.995,1.006) 1.000 (0.996,1.004) 0.997 (0.99,1.004) 1.021 (0.926,1.125) 1.013*** (1.006,1.020) 0.627 (0.249,1.578)
1.004 (0.993,1.015) 1.001 (0.995,1.008) 0.996 (0.99,1.002) 1.009 (0.931,1.094) 1.035 (0.999,1.071) 1.210 (0.293,4.993)
1.013 (0.999,1.027) 1.006 (0.999,1.014) 0.989* (0.978,0.999) 0.908* (0.841,0.981) 1.018 (0.977,1.060) 2.609 (0.492,13.832)
PM2.5, PM10, O3, SO2, NO2 and CO were each included in regression model, with control variables: age, BMI, education level, number of embryos transferred, and district fixed effect. A1, A2, B, C, E1 and E2 denote different stages of the IVF timeline for this study outlined in Fig. 1. Robust standard error was used using district clustered standard error. Significance levels: * < 0.05, ** < 0.001, *** < 0.0001. 95% confidence interval in parentheses.
associated with the most reduction in odds compared to other pollutants. For clinical pregnancy in females under 35 years old (Table 4), all pollutants have significant association with the odds of clinical pregnancy during windows D (embryo transfer to ultrasound detection of intrauterine gestation), F1 (gonadotropin start to ultrasound detection of intrauterine gestation), and F2 (between 85 days before oocyte retrival and ultrasound detection of intrauterine gestation). Exposure to PM2.5, NO2 and CO are significantly associated with reduced odds in clinical pregnancy during windows A2, B, D, F1, F2, while PM10 is only significantly associated during windows D, F1, and F2. Exposure to SO2 is significantly associated with decreased odds during all windows except B. Similar with findings in Table 3, exposure to CO is associated with most reduction in the odds of clinical pregnancy compared to other pollutants (−51.3% in A2, −32.9% in B, −52.6% in D, −51.7% in F1 and -63.5% in F2 respectively). Exposure to O3 is associated with increased odds of clinical pregnancy, and the association is significant for windows A1, B, D, F1 and F2 (0.5%, 0.3%, 0.4%, 0.5% and 0.5% respectively). In women age 35–39 years, exposure to SO2 is significantly
associated with reduced odds for biochemical pregnancy during window C (−4.8%) and for clinical pregnancy during windows D, F1 and F2 (−6.1%, −5.9% and −7.2% respectively). In women age 40 years and older, decreased odds in biochemical pregnancy is significantly associated with exposure to SO2 during windows A2 and E2 (−11.3% and 9.2%, respectively). Similarly, decreased odds in clinical pregnancy is also associated with exposure to SO2 during the same two windows (−13.1% and −13.8% respectively). Exposure to PM2.5 during windows D and F2 is significantly associated with reduced odds in clinical pregnancy (−0.15% and −0.11%), while during A2 is significantly associated with increased odds (1.6%). Expsure to CO is significantly associated with decreased odds in clinical pregnancy during windows D and F1 (−85.5% and −76.3% respectively), while associated with increased odds during windows A2, B, and F2, although the association is not significant. Exposure to O3 during windows A2 and E2 is significantly associated with reduced odds in biochemical pregnancy (-1.2% and −1.1%, respectively). The heterogeneity in the direction of association for some pollutants might be indicative of statistical instability due to small sample size of the ≥40 years age group.
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Table 4 Summary of odds ratio for univariate pollutant regression for clinical pregnancy by age groups. A1 < 35 Years Old, 722 women PM2.5 0.997 (0.992,1.003) PM10 0.999 (0.995,1.003) O3 1.005*** (1.003,1.007) SO2 0.959*** (0.941,0.978) 0.995 NO2 (0.987,1.003) CO 0.712 (0.410,1.239) 35–39 Years Old, 294 women PM2.5 1.003 (0.988,1.019) PM10 1.001 (0.991,1.011) O3 0.998 (0.995,1.001) SO2 0.966 (0.899,1.036) NO2 0.996 (0.959,1.036) CO 1.002 (0.251,3.991) ≥40 Years Old, 123 women PM2.5 0.998 (0.989,1.007) PM10 0.997 (0.991,1.003) O3 1.000 (0.995,1.004) SO2 0.955 (0.839,1.088) NO2 1.027 (0.983,1.075) CO 0.758 (0.233,2.469)
A2
B
D
F1
F2
0.994*** (0.99,0.998) 0.996 (0.992,1.001) 1.004 (1.000,1.008) 0.939*** (0.912,0.968) 0.989** (0.982,0.997) 0.487* (0.262,0.905)
0.996** (0.994,0.999) 0.998 (0.996,1.00) 1.003* (1.001,1.005) 0.982 (0.961,1.004) 0.99* (0.982,0.998) 0.671*** (0.553,0.815)
0.994** (0.99,0.998) 0.996** (0.993,0.999) 1.004** (1.001,1.007) 0.946*** (0.919,0.974) 0.979*** (0.973,0.985) 0.474*** (0.358,0.626)
0.994* (0.99,0.999) 0.996* (0.993,1.000) 1.005*** (1.002,1.007) 0.946*** (0.922,0.969) 0.98*** (0.976,0.984) 0.483*** (0.333,0.700)
0.991** (0.985,0.997) 0.994* (0.989,1.000) 1.005* (1.001,1.010) 0.936*** (0.911,0.961) 0.979*** (0.973,0.984) 0.365** (0.196,0.680)
0.994 (0.972,1.017) 0.995 (0.982,1.009) 0.998 (0.988,1.008) 0.928 (0.839,1.025) 0.980 (0.938,1.024) 0.365 (0.047,2.849)
1.002 (0.995,1.010) 1.000 (0.994,1.005) 0.998 (0.995,1.001) 0.978 (0.924,1.037) 0.999 (0.977,1.021) 0.707 (0.291,1.718)
1.004 (0.996,1.012) 1.003 (0.997,1.008) 0.999 (0.994,1.004) 0.939* (0.893,0.987) 0.996 (0.978,1.014) 1.178 (0.562,2.469)
1.004 (0.993,1.015) 1.002 (0.994,1.010) 0.999 (0.995,1.003) 0.941* (0.885,1.000) 0.994 (0.964,1.025) 1.106 (0.357,3.421)
0.998 (0.976,1.021) 0.998 (0.984,1.011) 0.998 (0.989,1.006) 0.928* (0.863,0.996) 0.982 (0.94,1.025) 0.470 (0.06,3.691)
1.016* (1.001,1.033) 1.007 (0.999,1.014) 0.990 (0.98,1.001) 0.869* (0.78,0.969) 1.031 (0.961,1.106) 2.832 (0.329,24.361)
0.999 (0.991,1.007) 0.997 (0.994,1.001) 0.996 (0.989,1.003) 0.944 (0.887,1.005) 1.025 (0.988,1.063) 1.413 (0.331,6.044)
0.985* (0.972,0.998) 0.991 (0.981,1) 0.999 (0.986,1.013) 0.931 (0.811,1.068) 1.009 (0.963,1.057) 0.145* (0.033,0.638)
0.989* (0.979,0.999) 0.992* (0.985,1.000) 0.999 (0.988,1.010) 0.924 (0.82,1.042) 1.020 (0.977,1.065) 0.237* (0.06,0.928)
1.005 (0.995,1.015) 1.001 (0.994,1.008) 0.992 (0.984,1.000) 0.862** (0.783,0.95) 1.031 (0.972,1.093) 1.168 (0.086,15.784)
PM2.5, PM10, O3, SO2, NO2 and CO were each included in regression model, with control variables: age, BMI, education level, number of embryos transferred, and district fixed effect. A1, A2, B, D, F1 and F2 denotes different stages of the IVF timeline for this study outlined in Fig. 1. Robust standard error was used using district clustered standard error. Significance levels: * < 0.05, ** < 0.001, *** < 0.0001. 95% confidence interval in parentheses.
4. Discussion
2008). Oxidative stress has been suggested as a major contributor to chromosomal abnormalities (Igarashi et al., 2015; Tatone et al., 2006) and also the embryo fragmentation, resulting in negative impact on IVF outcomes (Agarwal et al. 2008, 2012). While age-related ovarian reserve decline might have played a dominant role in IVF outcomes among older women, effects of ambient air pollution might have contributed more to pregnancy outcomes in younger women. In other words, the effects of air pollutants on IVF outcomes in older people might be masked by agerelated effects. Additionally, older females in our population were welleducated working adults, who could have been more aware of air pollution consequences and might have adopted more protective lifestyle. Our study also finds that exposure to CO appears to be associated with the greatest reduction in the odds of biochemical and clinical pregnancy outcomes among females younger than 35 years. The inverse relationship between CO and intrauterine pregnancy confirms earlier findings by Choe and colleages (Choe et al., 2018. The relationship between O3 exposure and IVF pregnancy outcomes is opposite of that between exposure to other pollutants and IVF outcomes. O3 is a secondary air pollutant formed from precursor pollutants, such as NO2 and SO2 (Carter, 1994; Carter and Atkinson, 2017; Shao et al., 2009). The concentration of ground-level O3 is thus negatively correlated with the concentration of its precursors. In Chengdu, clear days with sunshine are reflective of overall better ambient air quality (lower concentration of
4.1. Maternal age, air pollution, and IVF outcomes In this retrospective study, we explored the differential association between ambient air pollution and IVF outcomes during different exposure windows for different maternal age categories. Maternal age is one of the most significant risk factors for fecundity and fertility impairment in the general female population, due to ovarian ageing including declines in oocyte yields and oocyte quality. Specifically, as age increases, the likelihood of oocytes chromosomal abnormality and cellular dysfunction increases, resulting in a decrease in oocyte quality (Igarashi et al., 2015; Vollenhoven and Hunt, 2018). Advanced maternal age has also been demonstrated to negatively influence IVF outcomes (Ryan et al., 2005; von Wolff et al., 2019). In our study, older women (> 40 years) have a much lower biochemical and clinical pregnancy rate than younger women (35–39, and < 35 years), suggesting that age-related biological condition may play an increasing role in pregnancy outcomes as women age. However, the effects of ambient air pollution differ by age groups, and younger women (< 35 years) were more vulnerable to ambient air pollution than older women. Air pollutants can act as reactive oxygen species or are capable of generating them, promoting oxidative stress and the inflammatory processes (Kampa and Castanas, 6
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precursor pollutants), a situation supported by the negative correlation coefficients between O3 and other five pollutants we observed in our study (Table S4). Therefore, the positive relationship between O3 exposure and IVF outcomes could be explained by viewing O3 concentration as a proxy for lower ambient air pollution. The relationship between ambient air pollution and IVF outcomes does not appear to vary during different exposure windows before or within the IVF treatment timeline, and women aged less than 35 years old were more vulnerable to air pollutants than women who are more than 40 years old and 35–39 years old. Additionally, exposure to CO appears to be associated with the largest reduction in odds for biochemical and clinical pregnancy, a finding that may point to the direction for future pollution control studies. Our results suggest that long-term exposure to ambient air pollution during the whole follicular growth period has negative association with IVF outcomes in younger women. Beyond the IVF population, women who conceive naturally may also face long-term exposure to ambient air pollution, therefore, our study results could point to the critical timeline for future studies on female reproduction.
other cities in China. Additionally, in calculating ambient pollution, we could only match air pollution level with residential address as we don't have information on patients' daily activities to quantify potential pollution level at other relevant locations. Using pollution at residential location does not reflect exposure occurring at work place and during transit, which could be major locations for personal exposure. 5. Conclusion We conducted a retrospective study to investigate the relationship between ambient air pollution and IVF outcomes in 1139 women from Chengdu metropolitan between 2014 and 2019. Our findings suggest significant inverse relationship between the exposure to ambient air pollution and IVF outcomes. This association is most pronounced for young women (< 35 years). Additionally, long-term exposure to PM2.5, SO2, NO2 and CO at multiple stages of the IVF timeline exhibited significant inverse association with biochemical and clinical pregnancy outcomes, whereas chronic exposure to O3 reported increased odds for clinical pregnancy outcome. Long-term exposure to ambient air pollution is a situation faced by all females during reproductive age in China. Our findings from this study could be applied for future studies on human reproduction beyond the IVF population.
4.2. Significance and Limitation To our knowledge, our study is the first to investigate the differential association between ambient air pollution and different age groups for IVF population. Our study also investigated in depth and suggested the potential impact of long-term exposure to ambient pollution, which is a situation faced by both IVF population and the general reproductive age female population in many Chinese cities. Additionally, our study results also help to advance the understanding of ambient air pollution and human reproduction by providing analysis on a population from rapidly urbanizing region in western China that has experienced elevated and high level ambient air pollution. Our study population was overall non-smoking, well-educated with college level and almost all reported full employment status, this may not be reflective of the female population at large for Chengdu and
Declaration of competing interest We have no conflict of interest to declare for our manuscript ER-S19-2601titled “Association between Ambient Air Pollution and Pregnancy Outcomes in Patients Undergoing In Vitro Fertilization in Chengdu, China: A Retrospective Study”. Acknowledgment This study was partially supported by the Sichuan "1000 Talent" Young Scholar Program.
Supplemental Information Table S1
Summary of annual IVF patient number 2014–2019a by different age groups. Year
Number of Patients (%)
< 35 Years Old (%)
35–39 Years Old (%)
≥40 Years Old (%)
2014 2015 2016 2017 2018 2019
33 (2.9) 273 (23.97) 296 (25.99) 301 (26.43) 219 (19.23) 17 (1.49)
27 (3.74) 165 (22.85) 191 (26.45) 179 (24.79) 150 (20.78) 10 (1.39)
4 (1.36) 80 (27.21) 71 (24.15) 82 (27.89) 51 (17.35) 6 (2.04)
2 (1.63) 28 (22.76) 34 (27.64) 40 (32.52) 18 (14.63) 1 (0.81)
Total
1139 (100)
722 (100)
294 (100)
123 (100)
a
Study period is March 5, 2014 to January 22, 2019.
Table S2
Summary of IVF patients number and pregnancy outcome by districts. Pregnancy Outcome (%)
District
No. of Patients (%)
No. of Biochemical Pregnancy (%)
Chenghua Wuhou Qingyang Jinniu Jinjiang Dujiangyan Longquanyi
167 (14.66) 250 (21.95) 59 (5.18) 233 (20.46) 154 (13.52) 241 (21.16) 35 (3.07)
74 (44.31) 127 (50.80) 23 (38.98) 115 (49.36) 79 (51.30) 105 (43.57) 15 (42.86)
70 (41.92) 123 (49.20) 22 (37.29) 113 (48.50) 77 (50.00) 98 (40.66) 15 (42.86)
Total Area
1139 (100)
538 (47.23)
518 (45.48)
7
No. of Clinical Pregnancy (%)
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Table S3
Summary of ambient air pollutant concentration by monitor stations in Chengdu metropolitan. District
PM2.5 (Mean ± SD)
PM10 (Mean ± SD)
NO2 (Mean ± SD)
SO2 (Mean ± SD)
CO (Mean ± SD)
O3 (Mean ± SD)
Chenghua Wuhou Qingyang Jinniu Jinjiang Dujiangyan Longquanyi
63.94 ± 46.7 61.23 ± 44.39 62.43 ± 44.11 65.69 ± 46.29 59.64 ± 45.63 40.3 ± 28.11 48 ± 31.37
107.57 ± 67.94 100.95 ± 66.77 101.31 ± 65.25 106.16 ± 67.44 97.06 ± 68.42 64.94 ± 41.87 72.73 ± 45.53
53.8 ± 19.14 57.77 ± 20.44 53.96 ± 19.22 52.07 ± 18.45 52.91 ± 17.4 20.7 ± 9.94 30.32 ± 12.99
13.65 ± 8.29 14.91 ± 8.7 14.07 ± 8.6 14.76 ± 8.43 12.35 ± 6.82 15.14 ± 8.66 7.83 ± 2.56
1.08 ± 0.4 1.07 ± 0.43 1.02 ± 0.39 1.1 ± 0.38 1.07 ± 0.41 0.49 ± 0.27 0.89 ± 0.23
96.28 ± 55.11 97.29 ± 55.39 97.92 ± 56.13 100.77 ± 58.75 84.08 ± 50.76 116.3 ± 47.96 90.95 ± 43.41
Total area
58.5 ± 43.52
95.51 ± 64.81
47.77 ± 21.75
13.88 ± 8.26
0.97 ± 0.44
98.41 ± 54.56
*Polluant concentration is district-wide average based on all avaiable monitor stations. Data period is December 10, 2013 to February 26, 2019, which includes the period of 85 days prior to the record offirst oocyte retrieval and 35 days post the record of last oocyte retrieval in the study.
Table S4
Correlation Among Ambient Air Pollutants in Chengdu 2013–2019a. PM2.5 PM2.5 PM10 NO2 SO2 CO O3
0.9435 0.6638 0.5086 0.7288 −0.2423
PM10
NO2
SO2
CO
O3
0.9509
0.6711 0.6949
0.4768 0.4945 0.3717
0.6798 0.6569 0.7036 0.3554
−0.2236 −0.1852 −0.2039 0.0318 −0.3002
0.6898 0.5159 0.7118 −0.2048
0.3789 0.7189 −0.1697
0.3985 −0.0156
−0.2892
Pearson's correlation coefficients are shown in the lower left triangle, while Spearman's rank correlations appear in the upper right triangle. a Data period is December 10, 2013 to February 26, 2019.
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