The effect of maternal exposure to air pollutants on small for gestational age among infants in Xuzhou, China from 2018 to 2020: a cross sectional study

doi:10.21203/rs.3.rs-1464070/v1

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Research Article

The effect of maternal exposure to air pollutants on small for gestational age among infants in Xuzhou, China from 2018 to 2020: a cross sectional study

https://doi.org/10.21203/rs.3.rs-1464070/v1

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posted 25 Mar, 2022

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Background: Small for gestational age (SGA) defined as below 10th percent of birth weight of sex-specific gestational age, will bring large burden to the child. Large epidemiological studies have shown that exposure to air pollutants during pregnancy is associated with SGA, but the conclusions are inconsistent.

Objective: To further investigate the relationship between prenatal exposure to air pollutants and SGA in Xuzhou, China.

Methods: Our study included 2,039 pairs of mothers and their fetuses from January 1, 2018 to December 31, 2020 at the Affiliated Hospital of Xuzhou Medical University. A total of six air pollutants were acquired from the Xuzhou Department of Environmental Protection including particulate matter, nitrogen dioxide (NO₂), and sulfur dioxide (SO₂), ozone (O₃), carbon monoxide (CO). Adjusted for the confounders referring gestation, parity, gestational diabetes mellitus and Meteorological factors. We performed binomial logistic regression to test the odds ratio between air pollutants and the risk of SGA.

Results: We found strong positive association of exposure to SO₂ with SGA over the entire pregnancy and during the 1th, 2nd trimester (OR, 95% confidence interval: 1.204(1.091-1.328), 1.165(1.073-1.266), 1.110(1.033-1.193)). The other pollutants exception of O₃ and NO₂ were also found moderate relation with SGA over the entire pregnancy.

Conclusions: The SGA incidence in Xuzhou was still high and even exposure to low levels of SO₂ will pose a significant risk to infants. The government should focus on relevant policies to further improve air quality to reduce the burden of medical and health work and promote maternal health.

air pollutants

small for gestational age

logistic regression

adverse birth outcome

Small for gestational age(SGA) defined as below 10th percent of birth weight of sex-specific gestational age, a statistical rather than a pathological term, has become a significant indictor reflecting intrauterine undergrowth among infants although not all SGA infants are diagnosed unhealthy babies [1, 2]. Representing a kind of adverse birth outcome, it is mostly related to increased infants mortality and morbidity and will produce short or long term significant effects on the child, such as consistently affecting the nervous system development of the infants and producing insulin resistance、type 2 diabetes mellitus and respiratory system [3–6]. The increased trend of SGA incidence was performed by years, which reached up to 2.45% in 2016[7]. SGA infants will also persistently bring large burden referring to economical or psychological to their families and country. Although series of studies have been conducted to search for the risk factors of SGA during pregnancy, the conclusions were limited [8–12], including fetal growth restriction resulting infants fail to reach to intrinsic nutrition from placenta of which they needed and the ionizing radiation exposure and so on [13, 14].

Recent years a growing number of studies involved air pollutants were conducted to investigate the association between air pollutants and SGA during pregnancy using all kinds of statistical and exposure assessments methods [15–19]. A positive association of maternal exposure to fine particulate matter with aerodynamic diameter less than 10µm with risks of SGA was observed over the entire pregnancy, however, there was no relationship detected with SGA in another study at the same pregnancy period [20, 21]. Considering the risk factors of SGA not only includes environmental, but also refers to genetic and socioeconomic status. A retrospective study conducted in Belgium was observed a positive association in relation to exposure to fine particulate matter with aerodynamic diameter less than 10µm with the risk of SGA twins [22]. The third trimester was the significant susceptive exposure window of PM_2.5 in an American study, as well as NO₂ and CO, while in another state-wide birth cohort study, there was no sensitive exposure windows observed during pregnancy [5, 18]. Above all, in spite of various studies investigated the relationship between exposure to air pollutants and the risks of SGA, the conclusions were still inconsistent for the specific relation and the key exposure window.

Xuzhou, a prefecture level city, is also an industrial city in the north of Jiangsu province in china, indicating that air pollution should be attached great attention to reduce the morbidity of air pollutants-related disease [23, 24]. Fewer studies were conducted to investigate the relationship between air pollutants in under-developed countries with much higher polluted air concentration at present and the risks of SGA, also due to the heterogeneity of the air pollution level and other risk factors in all kind of cities, the conclusion produced by another city cannot be completely moved to other city. To our knowledge, there is no relevant research independently exploring the association of air pollution with risks of SGA of Xuzhou, a city in china. To further understand this knowledge difference, we conducted this study to precisely estimate the relationship of exposure to air pollutants with risks of SGA and determine the pivotal exposure window during pregnancy reducing the cost in public health in Xuzhou from 2018 to 2020.

2.1 Studying population

Our study subjects were obtained from Xuzhou Maternity and Child Health Care Hospital affiliated Xuzhou medical university from January 1, 2018 to December 31, 2020. We excluded pregnant women with twins to avoid the effect of genetic confounder. The pregnant woman were asked to complete the medical record information including maternal age, parity, gravidity, gestational age and whether they had history of hypertension and drug allergy at their first visit to the hospital. We also collected data on birth outcomes including 72-hour birth weight of each infant from the medial records. SGA was defined according to birth weight smaller than ten percent of special gestational age and sex. In the end, there were 2039 singleton infants included in our study.

2.2 Exposure assessment

In our study, we collected daily air pollutants from local air monitoring departments from January 1, 2017 to December 31, 2020 in Xuzhou city, including particulate matter less than or equal to 2.5µM in aerodynamic diameter (PM_2.5), particulate matter less than or equal to 10µM in aerodynamic diameter (PM₁₀), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂), ozone (O₃), carbon monoxide (CO). The full pregnancy were divided into three specific trimester: trimester 1 (1–12 weeks), trimester 2 (13–27 weeks), trimester 3 (28 weeks to delivery) [9]. The air pollutants concentration of trimester-specific were calculated according to prior daily air pollutants. The exposure matching methods were according to their residential address obtained from the medical records, we chose data from the air pollution monitoring site closest to their home as their exposure data. Finally, air pollutants exposure were acquired and integrated into entire trimester and trimester-specific level.

2.3 Covariates

During the time of information collecting, parity, gravidity, history of hypertension and drug allergy were observed as confounders to adjust the model, which are all binomial varieties. Pregnant women over the age of 35 were defined as elderly pregnant women.

2.4 Statistical analysis

For descriptive analyses, we calculated the minimum, maximum, mean, standard deviation, quartiles of the air pollutants and made a baseline survey compared infants of SGA and appropriate gestational age (AGA). Chi-square test was used for categorical variables and T test was used for quantitative variables. The changing trends of concentration of air pollutants over time were performed from 2018 to 2020.

For statistical analysis, we applied the logistic regression model to test the relationship between air pollutants and SGA according to their pregnancy periods. The model1 only including single pollutant was conducted to investigate the association of exposure to air pollutants with risks of SGA. To control the effect of known confounders, we designed model 2 adjusted parity, gravidity, hypertension and GDM to precisely investigate the relationship between air pollutants and SGA. We tested the concentration-response relationship according to the odds ratio of the quartile pollutants through their trimester-specific periods. All statistical analyses were conducted by R.

In our study, 2039 single infants were included in our study from January 1, 2018 to December 31, 2020, with the incidence of SGA was 6.93% (142/2039). Baseline characteristics of pregnant women between SGA and AGA infants were performed in Table 1, gravidity and parities were classified into binomial varieties compared one and one more time, respectively. All covariates were transformed into categorized varieties. Not only difference with maternal age and GDM of pregnant women between SGA and AGA had statistical significance in our study that the pregnant women with a history of Gestational Diabetes Mellitus were more likely to deliver SGA infants, but there had crucial discrepancy in the distribution of infants on birth year and birth season. The SGA infants were less likely to be born in winter in our study, and the maternal age tended to be from 30 to 34 in mothers of SGA, while in the population of AGA mothers, maternal age usually in the range of 25 to 29.

Table 1

baseline characteristics between SGA infants and AGA infants
	SGA	AGA	P
Gravidity
1	51	642
> 1	89	1084	0.857
Parity
1	65	879
> 1	75	847	0.306
Maternal Age
≤ 24	15	211
25–29	49	815
30–34	57	537
≥ 35	19	163	0.015*
Drug Allergy
No	133	1678
yes	7	48	0.217
Blood Type
0	39	477
1	50	517
2	35	515
3	13	175
4	3	42	0.63
Gestational Diabetes Mellitus
No	128	1646
yes	12	80	0.039*
Birth year
2018	100	826
2019	25	695
2020	15	205	< 0.001**
Season
Spring	22	435
Summer	40	373
Autumn	21	335
Winter	57	583	0.013
(Chi-square test was used for categorical variables. SGA: small for gestational age. AGA: appropriate for gestational age.)

Figure 1 shows the change trend of pollutant concentration from 2018 to 2020. Women who gave birth in winter had higher exposure levels in the early stages of pregnancy. Table 2 showed the summary statistical characters of specific air pollutant by exposure period. According to the global air quality guidelines by World Health Organization in 2021 [25], the air pollutant concentration in Xuzhou are much higher than the recommended standards of which the average concentration of PM_2.5, PM₁₀, NO₂, O₃ are 15µg/m³, 45µg/m³, 25µg/m³, 60µg/m³. The average concentration of PM_2.5 was 4 times higher compared the standards by WHO during the 1st trimester, the SO₂ and CO basically conforms to international standard.

Table 2

Estimated characters of air pollutants by exposure period
	Mean	SD	Percentile
			min	25th	50th	75th	max
PM_2.5
Trimester 1	60.81	22.58	28.34	39.52	59.42	82.36	96.25
Trimester 2	52.92	19.63	29.20	35.41	46.08	68.26	96.85
Trimester 3	51.19	22.18	22.45	32.09	41.13	70.35	110.13
Entire pregnancy	54.82	8.30	34.57	49.03	55.42	61.97	78.14
PM₁₀
Trimester1	103.61	28.42	47.81	81.13	99.36	130.25	150.74
Trimester2	93.84	25.84	52.22	72.44	87.52	112.47	149.75
Trimester3	90.59	30.56	42.18	62.09	83.50	115.53	155.96
Entire pregnancy	95.89	12.16	68.81	88.28	96.48	105.61	127.34
SO₂
Trimester1	11.66	2.09	7.20	9.94	11.44	13.54	15.66
Trimester2	10.75	2.26	7.51	9.05	10.23	12.86	15.63
Trimester3	9.95	2.22	5.82	8.05	9.60	11.01	16.08
Entire pregnancy	10.79	1.65	8.59	9.47	10.00	12.72	14.20
NO₂
Trimester1	37.42	9.86	20.34	28.71	36.92	45.82	53.61
Trimester2	34.63	9.06	21.61	27.05	32.97	41.97	53.06
Trimester3	34.25	10.88	17.44	24.04	31.75	44.66	55.60
Entire pregnancy	35.39	3.96	26.09	32.46	35.07	38.18	47.16
CO
Trimester1	0.88	0.17	0.55	0.79	0.84	1.04	1.15
Trimester2	0.78	0.16	0.56	0.64	0.74	0.90	1.14
Trimester3	0.78	0.18	0.52	0.64	0.70	0.92	1.24
Entire pregnancy	0.81	0.07	0.63	0.75	0.81	0.85	0.96
O₃
Trimester1	62.71	26.83	24.00	36.72	61.39	87.04	108.42
Trimester2	69.42	21.34	27.60	52.41	74.53	88.11	97.78
Trimester3	67.52	24.38	20.37	44.29	73.93	88.43	113.85
Entire pregnancy	66.78	7.35	42.56	61.57	66.87	73.41	86.14
(PM_2.5: µg/m³; PM₁₀: µg/m³; O₃: µg/m³; NO2: µg/m³; SO₂: µg/m³; CO: mg/m³. Abbreviations: SD, standard deviation; Min, minimum; Max, maximum)

Figure 2 showed the estimated odds ratio associated with SGA of six pollutants by exposure period among our infants. Obviously, prenatal exposure to SO₂ during pregnancy had a strong association with giving birth to a SGA infant during the third trimester, the OR value peaked at 1.382(1.177–1.623, P < 0.001). The significant associations between air pollutants of PM_2.5, PM₁₀ and SGA infants were observed over the total, first and third trimester after adjusting the effect of confounders (PM_2.5:1.094 (1.043–1.147) P < 0.001, 1.049(1.018–1.081) P < 0.001; 1.072(1.034–1.112) P < 0.001; PM₁₀:1.052(1.025–1.079) P < 0.001, 1.025(1.010–1.041) P < 0.001, 1.034(1.012–1.058) P < 0.001). As for the second trimester, no association was observed except the SO₂. There was no relationship with SGA infants for O₃ at any trimesters in our study.

To further explore whether there were threshold effects of exposure-response, we calculated the odds ratio for the unit of quartile for pollutants, the final results were showed in Table 3. We found significant positive associations among most of the air pollutants over the entire pregnancy. During the first and second trimester, a higher concentration of SO₂ will produce a bigger impact on infants, especially at the percent of 50 and 75. A negative association of maternal exposure to NO₂ was observed at the 25 and 50 percent during the first trimester, while at the 50 and 75 percent during the second trimester, we can found the positive relationship of NO₂ with SGA. Although the odds ratio of CO with risks indicated by SGA was performed a large fluctuation, we could still observe a relative higher risk with increased concentration of air pollutant over the entire pregnancy and the first trimester.

Table 3

the estimates of increased OR with 95%CIs for each IQR of each pollutants compared with the concentration of 25th percentage.
pollutant	IQR	Entire pregnancy	Trimester1	Trimester2	Trimester3
		OR ^a(95%CI)	OR ^a(95%CI)	OR ^a(95%CI)	OR ^a(95%CI)
PM_2.5	Q1	-	-	-
	Q2	*1.920 (1.055–3.496)**	0.964 (0.500-1.859)	1.882(0.983–3.603)	0.715(0.401–1.274)
	Q3	5.365 (2.478–11.614)**	0.594 (0.200-1.767)	2.527(0.991–6.440)	0.437(0.155–1.226)
	Q4	9.395 (3.404–25.930)**	1.094 (0.296–4.042)	2.885(0.711–11.702)	0.928(0.205–4.214)
PM₁₀	Q1	-	-	-	-
	Q2	0.808(0.434–1.505)	0.847(0.421–1.706)	1.744(0.911–3.339)	0.561(0.309–1.017)
	Q3	2.617 (1.491–4.591)**	0.912(0.386–2.155)	2.950(1.303–6.681)**	*0.334(0.130–0.856)**
	Q4	3.163 (1.455–6.872)**	1.867(0.629–5.545)	2.860(0.967–8.457)	0.758(0.213–2.692)
SO₂	Q1	-	-	-	-
	Q2	1.458(0.768–2.766)	1.562(0.890–2.741)	1.331(0.659–2.687)	0.832(0.495-1.400)
	Q3	4.260 (2.065–8.788)**	*2.010 (1.163–3.473)**	2.828 (1.445–5.534)**	0.515(0.224–1.186)
	Q4	3.237(1.778–5.892)**	2.388(1.329–4.291)**	3.477(1.901–6.359)**	1.878(0.618–5.709)
NO₂	Q1	-	-	-	-
	Q2	1.301(0.760–2.228)	0.374(0.193–0.723)**	1.802(1.000-3.248)	0.681(0.406–1.143)
	Q3	*1.823(1.021–3.256)**	*0.445(0.205–0.965)**	3.753(2.048–6.878)**	0.499(0.241–1.033)
	Q4	2.757 (1.424–5.337)**	0.656(0.307–1.402)	*2.346(1.060–5.193)**	1.302(0.545–3.109)
CO	Q1	-	-	-	-
	Q2	*1.947(1.171–3.237)**	2.090(1.249–3.497)**	1.110(0.674–1.828)	0.670(0.416–1.081)
	Q3	1.423(0.816–2.48)	1.300(0.746–2.263)	*1.610(1.013–2.558)**	0.462(0.273–0.783)**
	Q4	2.144(1.281–3.590)**	2.339(1.405–3.894)**	0.883(0.521–1.497)	1.035(0.674–1.588)
O₃	Q1	-	-	-
	Q2	1.700(0.969–2.984)	0.890(0.512–1.546)	1.723(0.801–3.707	0.497(0.228–1.084)
	Q3	0.867(0.356–2.109)	0.783(0.267–2.297)	0.887(0.283–2.783)	0.828(0.273–2.513)
	Q4	0.437(0.137–1.388)	1.801(0.446–7.274)	0.667(0.175–2.533)	1.207(0.282–3.739)
(Q1: The first quartile; Q2: The second quartile; Q3: The third quartile; Q4: The fourth quartile. OR ^a: adjusted for gestation, parturition, advanced age, humidity, temperature, gestational diabetes mellitus, drug allergy, gestational hypertension, blood type)

To the best of our knowledge, this is the first study systematically investigating the relationship of prenatal exposure to air pollutants with SGA over the entire and trimester-specific pregnancy in Xuzhou in the northern Jiangsu province in China. In our study, a total of six kinds of air pollutants exposure were examined to test the effects on SGA, of which the SO₂ was the most significant representative air pollutant, to which our calculated odds ratio reached up 1.382(95% confidence interval:1.177–1.623) during the third trimester.

The incidence of SGA varied greatly among different areas, of which the 6.93% in Xuzhou while 15.4% in the southern district of Israel and 5.74% in Beijing of China and 11.1% in a multicenter study in American [26–28]. The reasons for these differences may be diverse selection of research objects, sample size and economic and medical development of the studied regions. For example, Beijing, a political, economic and cultural center in China, has a relatively better medical and health care level and people have a higher health quality. The selected subjects may have different levels of physical activity and education, as well as socioeconomic status, which can affect the health of the new infants. Lee [29]reported that high levels of occupational physical activity were significantly associated with SGA while a completely opposite opinion was performed a study in Brazil [30], the relative physical activity level with adverse birth outcome also needed to be furthered.

All our air pollutants exception NO₂ and O₃ were observed adversely weak or strong association over the entire or trimester-specific pregnancy. Although there were many studies investigating the association between exposure to SO₂ and being born to SGA, the results remained still inconsistent. While adverse effects of exposure to SO₂ during pregnancy with SGA were observed in some studies [31–33], other had the completely different conclusions with null even protective association [16, 34–37]. Similar to the study conducted in a multicenter study in US using Binary Poisson regression and a low urbanization of Italy using multivariate regression analysis [19, 31], we also found the susceptibly sensitive windows periods of gestation of maternal exposure to SO₂ over the total and each trimester of pregnancy. Thus the varied studying population, research design, statistical methods, degree of exposure misclassification among various studies, we finally came to the same conclusion as above studies that exposure to SO₂ during pregnancy will exert adverse effect on pregnant women and their babies in some extent. Especially, when we calculated whether there was exposure-response relationship between the SO₂ and the SGA, we found that the risk of SGA became stronger per IQR increase from the point of Q3 concentration over the entire and during the 1st and 2nd trimester, suggesting that the risk of SGA could increase with a threshold at the range of the second and third quartile. Considering the inconsistent susceptible exposure windows and threshold effect, future studies needed to be conducted to precisely investigate the sensitive exposure windows to provide government prevention advices timely.

Completely inverse results from the study conducted in US investigating the relationship between prenatal exposure to O₃ and SGA [18], we found null association during each trimester while adverse relationship was observed for O₃ for SGA during the third trimester and protective effect was observed for PM_2.5 and SGA over the entire pregnancy and the first and second trimester in their study. We also found that prenatal exposure to particulate matter with aerodynamics diameter less than 10µm and CO decreased the risk of SGA during the second and third trimester, which seems not biologically plausible and inconsistent with previous studies. Embryos sensitive to early air pollution may eventually be stillborn or die in the intrauterine phase, however, our study only included live births, which could be one reason and create selection bias. This discrepancy also may be due to our inconsistent adjustment of model covariates and exposure heterogeneity, our study did not consider factors such as socioeconomic and marital status, maternal education level and history of smoking, which are all significant factors analyzing the causes born to SGA in recent studies[38–40]. Considering the negative impacts of smoking and drinking on human health, it is necessary to adjust the effects of confounders. Furthermore, a large amount of studies have reported a strong correlation between PM_2.5 and PM₁₀ [41–43], we also found the similar effects on SGA between the two air pollutants in our study although only the positive relationship over the entire pregnancy. An OR increase was observed per IQR increase over the entire trimester, suggesting that there was no threshold effect of pollutants as the concentration of PM_2.5 increased. The adverse effects attributed to PM_2.5 exposure not only compromised SGA, but the prevalent low birth weight and preterm birth, which are all far-reaching consequences of air pollutants exposure [44, 45]. The possible biological mechanism of particulate matter on SGA may include immunity impairment and oxidative stress inflammation induced by PM_2.5 [46, 47], which will cause endocrine disorder in pregnant women and hinder the essential nutrition and gases passing through the placenta.

In this cross sectional study in Xuzhou, we found null association of exposure to NO₂ and moderate effect between CO and SGA over the entire pregnancy and the first trimester. Inconsistent with previous study conducted in meta analysis [32, 48], which may be due to that included a large number of black people, a relatively susceptible and understudied population, resulting the heterogeneity of studying population.

This study also has several strengthens. It is the first study on the relationship between air pollution and SGA in Xuzhou, and we found that SO₂ is an independent risk factor for SGA. We included six pollutants to explore the possible relationship between air pollutants and adverse birth outcomes. Meanwhile, our study also have some limitations. The average exposure level of the monitoring site is for the population rather than the individual exposure level, which may cause exposure measurement bias and ultimately affect the determination of the relationship. We did not include indicators of and socioeconomic status and lifestyle factors related to smoking and alcohol consumption among pregnant women, which are all confounders of air pollutants and SGA.

The incidence of SGA in Xuzhou is relatively high, and SO₂ is the most representative among the six pollutants resulting SGA. We found that early pregnancy may be the sensitive exposure window for all pollutants, providing scientific support for the government's work in maternal and child health. The mechanism of air pollutants leading to SGA needs to be further explored in the future.

Author Contributions

Dejia Li and Wei Zhu conceived and designed the study; Shijie Zhu and Xiaowei Zhang collected and cleaned the data; Faxue Zhang performed the data analysis; Gaichan Zhao wrote the manuscript and Xupeng Zhang helped revised the manuscript. All authors read and approved the final manuscript.

Disclosure Statement

The authors declare that they have no competing interests.

Ethical Statements

This study was approved by the Ethics Committee of Wuhan University.

Data Availability Statement

The original contributions presented in the study are included in the article.

Funding

Not applicable.

Conflicts of Interest Statement

The authors declare that they have no conflicts of interest.

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No competing interests reported.

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posted 25 Mar, 2022

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The effect of maternal exposure to air pollutants on small for gestational age among infants in Xuzhou, China from 2018 to 2020: a cross sectional study

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Abstract

Figures

1. Introduction

2. Materials And Methods

2.1 Studying population

2.2 Exposure assessment

2.3 Covariates

2.4 Statistical analysis

3. Results

4. Discussion

5. Conclusions

Declarations

References

Competing Interests

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