基于出生登记数据的研究：母亲吸烟对足月单胎新生儿胎盘重量及胎盘重量与出生体重比值的影响

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BACKGROUND

Maternal smoking during pregnancy is one of the most common modifiable risk factors of adverse short- and long-term pregnancy outcomes such as miscarriages [1], preterm deliveries [2, 3], low birthweight (BW) [3], and some birth defects [2–4]. Some complications are related to placenta development and can be partially explained by disfunction of trophoblasts and hormonal disbalance in early pregnancy caused by smoking [1] and vascular effects of nicotine [5]. All women are advised to quit smoking before conception or during the first trimester of pregnancy. It was found that the most benefits were observed in case of smoking cessation before week 15 of pregnancy [6]. It can improve the prognosis and reduce the risk of adverse pregnancy outcomes. However, the prevalence of smoking in pregnant women in many countries, including Russia, is still relatively high. For example, our previous study in the North-West of Russia revealed up to 25% and 18% smoking mothers before and during pregnancy, respectively [7].

Placental weight (PW) and placental-to-birth weight ratio (PW/BW) are well-known indicators of adverse pregnancy outcomes as they reflect prenatal functioning [8]. An unbalanced PW/BW may indicate abnormal placental functioning or placental adaptation to an adverse intrauterine environment. Previous research showed that low PW z-scores were associated with a two-fold increase in fetal death, whereas high z-scores were associated with higher odds of neonatal morbidity [9]. Salavati et al. (2017) determined BW/PW in 3311 deliveries and found that low BW/PW was associated with higher risk of neonatal morbidity [10]. Shehata et al. (2010) [11] found that low BW/PW was associated with higher risks of intensive care unit admission, low Apgar scores, and fetal death. These findings indicate that PW/BW, when interpreted based on defined thresholds and in relation to other clinical parameters, is a useful diagnostic tool for identifying potential intrauterine growth restrictions and placental insufficiency in newborns. Research on the relationship between smoking and placental morphology, especially PW/BW, is scarce. In addition, smoking cessation effects on placenta are still unclear. Some studies showed significant difference in the placental structure and weight between smoking and non-smoking mothers [12] and higher PW/BW in smoking mothers [9, 10]. However, other authors consider that despite lower first-trimester placental vascularization flow indices, a negative smoking effect on PW is not evident yet [15]. Another important issue is how smoking cessation during pregnancy affects placental development. Some studies revealed a positive effect of smoking cessation on anthropometric measurements in newborns compared with offspring of smoking mothers due to improved placental transfer [3, 16].

Currently, most studies in Russia investigate relationships between smoking and placental insufficiency [17, 18], premature maturation of placenta, and histological changes in pregnant smokers [18, 19]. The relationship between smoking before and during pregnancy and high PW and PW/BW have, to our knowledge, not been studied yet.

Two population-based birth registries established in the Murmansk County (MC) in the North-West of Russia two decades ago contain data on maternal smoking behavior before and during pregnancy and morphological examinations of placenta in all deliveries in this region, allowing to investigate changes in placental morphology in pregnancy.

Aim

The study was aimed to explore potential associations between maternal smoking status during pregnancy (including the effect of smoking cessation and daily number of smoked cigarettes) and PW, including PW/BW. Thus, our primary objectives were to: (i) determine PW and BW for gestational age and sex; and (ii) examine a potential association between smoking status during pregnancy (including daily number of smoked cigarettes) and z-scores of PW and PW/BW.

METHODS

Study Setting, Design, and Sample Size

The Murmansk County Birth Registry (MCBR) has registered all births from 22 weeks of gestation in MC from January 1, 2006 to December 31, 2011. The detailed information on its design, implementation, and data collection was presented in our previous study [20].

In this study, we used all cases with singleton pregnancy delivered at > 37 completed weeks of gestation from the registry. Our study focused on two main tobacco-smoking issues related to pregnancy: (i) smoking status before pregnancy and during the first antenatal visit, and (ii) the number of cigarettes smoked daily. Sampling details are summarized in Fig. 1.

 

Fig. 1. Study population selection flow chart.

 

Data Collection

The MCBR contains anonymized maternal data, such as age, parity, weight and height measured at the first antenatal visit, marital status, residence, ethnic origin, education, and self-reported smoking status at the first antenatal visit (including the number of cigarettes per day before and during pregnancy), collected from medical records and personal interviews with pregnant women. Data on the mode of delivery, gestational diabetes, preeclampsia/eclampsia, gestational age, year of delivery, and anemia to be included in the MCBR were taken from individual obstetric records. In addition, the MCBR contains data on the sex of newborns, PW, and BW.

Dependent Variables

PW and BW were measured in grams. PW/BW was calculated by dividing PW by BW in grams. We calculated z-scores in the sample using means and standard deviation of PW and PW/BW for each gestational age. Moreover, z-scores were calculated separately for male and female newborns. PW and PW/BW z-scores were classified as < −1; − 1 to + 1; and > +1.

Independent Variables

Smoking status during pregnancy was defined as smoker (women who smoked before and during pregnancy), quitter (women who quit smoking during pregnancy), and non-smoker (women who smoked neither before nor during pregnancy). For pregnant smokers, the number of cigarettes smoked daily was treated as a categorical variable, i.e. 0; 1–5; 6–10; and ≥ 11.

Data Analysis

Distribution of continuous variables were checked for normality using the Shapiro–Wilk test and presented as a mean and standard deviation. Two-sample t-test was used to compare the mean values (PW and BW) in two groups of data. Simple linear regression was used to determine the relationship between PW, BW, and gestational age for male and female newborns separately. An analysis of covariance (ANCOVA) was conducted with gestational age as a covariate to determine the difference in PW between maternal smoking categories. We used a multinomial logistic regression to assess the correlations between z-scores (low, medium, and high) of PW and PW/BW and smoking status during pregnancy, including the daily number of smoked cigarettes. Medium z-scores were chosen as the base outcome; therefore, it was used as the reference to build the regression models. Unadjusted and adjusted relative risk ratios (RRR) derived from multinominal logistic regression models were calculated with 95% confidence intervals (CI). Maternal age (≤ 19 years, 20–24 years, 25–29 years, 30–34 years, and ≥ 35 years), parity (0, 1, and ≥ 2 deliveries), marital status (married, cohabitation, or single [including divorced or widowed women]), place of residence (urban and rural), ethnic origin (Russian or other), education (university, etc.), year of delivery, body mass index (≤ 18.4, 18.5–24.9, 25.0–29.9, ≥ 30, or unspecified), mode of delivery (vaginal or caesarean section), gestational diabetes, preeclampsia/eclampsia, anemia, and BW were used for mutual adjustment as potential confounders in multinominal logistic regression models. Statistical processing was performed using STATA v. 14 (StataCorp LLC).

Ethical Approval

The MCBR establishment and data collection was approved by the Regional Healthcare Office of the Murmansk County. A special law was adopted by the regional government on mandatory registration of births in the MCBR for all delivering women. The registry database does not contain any personal identifiers.

This study was approved by the Ethical Committee of the Northern State Medical University (Arkhangelsk, Russia) (No. 08/12-14 dated December 10, 2014).

RESULTS

Placental Weight and Birth Weight by Gestational Age and Sex

The mean PW for male newborns was 534.1 g (SD:117.9 g) and 523.7 g (SD: 116.6 g) for female newborns. The mean BW for male newborns was 3500 g (SD: 457.1 g) and 3366 g (SD: 439.0 g) for female newborns (see Table 1).

 

Table 1. Mean placental weight and birth weight by gestational age and sex (g)

Gestational age	Male newborns, Mean (SD)			Female newborns, Mean (SD)			p value1
	n	PW	BW	n	PW	BW	PW	BW
37 weeks	1555	508.9 (123.2)	3148 (467)	1275	498.9 (117.8)	3023 (423)	0.029	< 0.001
38 weeks	3788	524.2 (119.1)	3352 (433)	3236	511.8 (117.9)	3205 (430)	< 0.001	< 0.001
39 weeks	6765	534.9 (118.2)	3493 (432)	6133	523.1 (115.8)	3354 (418)	< 0.001	< 0.001
40 weeks	6854	540.6 (117.2)	3594 (428)	6458	528.8 (115.4)	3440 (408)	< 0.001	< 0.001
41 weeks	2794	541.8 (112.3)	3633 (448)	3024	532.3 (116.2)	3500 (425)	0.002	< 0.001
≥ 42 weeks	1244	539.2 (116.6)	3612 (474)	1285	536.0 (116.7)	3483 (455)	0.497	< 0.001
Total	23,000	534.1 (117.9)	3500 (457)	21,411	523.7 (116.6)	3366 (439)	< 0.001	< 0.001

Note: PW, placental weight; BW, birth weight; ¹ calculated using the two-sample t-test.

 

Moreover, mean PW and BW increased with gestational age. Linear regression: PW_males, B=6.25 (95% CI 5.0–7.5) and PW_females, B=7.05 (95% CI 5.8–8.3); BW _males, B=97.5 (95% CI 92.9–102.1) and BW_females, B=94.3 (95% CI 89.8–98.9). Difference in PW in the groups by smoking status stratified by gestational age and sex is shown in Table 2.

 

Table 2. Mean placental weight by smoking status stratified by age and sex (g)

Gestational age	Placental weight (male newborns), Mean (SD)			Placental weight (female newborns), Mean (SD)
	Non-smoker	Quitter	Smoker	Non-smoker	Quitter	Smoker
37 weeks	507 (122)	520 (134)	513 (122)	501 (121)	505 (122)	491 (106)
38 weeks	524 (120)	531 (110)	522 (118)	511 (115)	516 (128)	514 (125)
39 weeks	532 (117)	546 (117)	542 (124)	521 (116)	529 (115)	528 (116)
40 weeks	538 (115)	544 (124)	551 (122)	526 (114)	535 (111)	540 (121)
41 weeks	540 (112)	543 (112)	547 (113)	531 (114)	536 (125)	536 (120)
≥ 42 weeks	540 (116)	511 (110)	542 (119)	537 (120)	553 (107)	527 (106)
Total	532 (117)	539 (118)	539 (120)	522 (116)	530 (117)	527 (119)
p1	< 0,001			0,002

Note: ¹ calculated using ANCOVA (gestational age as a covariate).

 

Association Relationship between Smoking Status During Pregnancy and Z-Scores of Placental Weight and Placental-to-Birth Weight Ratio

The relationships between smoking status during pregnancy and z-scores of PW and PW/BW are shown in Table 3. Smokers and those who quit smoking during pregnancy were less likely to have low PW z-score only after adjustment for potential confounders compared to non-smokers: adjusted RRR_smoker=0.75 (95% CI 0.70–0.81) and adjusted RRR_quitter=0.86 (95% CI 0.76–0.97). Moreover, smokers and quitters were less likely to have low PW/BW z-score both before and after adjustment for socio-demographic and medical parameters of pregnant women compared to non-smokers. Smokers and quitters were more likely to have high z-scores of PW and PW/BW compared to non-smokers as shown by the unadjusted and adjusted values summarized in Table 3.

 

Table 3. Relationship between smoking status before and during pregnancy and z-scores of PW and PW/BW in the Murmansk Region (n = 44,411)

Z-score		Unadjusted RRR (95% CI)			Adjusted RRR (95% CI)
		Smoking status during pregnancy			Smoking status during pregnancy
		Non-smoker	Quitter	Smoker	Non-smoker	Quitter	Smoker
PW1	Low	1.00	0.91 (0.81–1.02)	0.98 (0.92–1.05)	1.00	0.86 (0.76–0.97)	0.75 (0.70–0.81)
	High	1.00	1.14 (1.03–1.27)	1.16 (1.08–1.24)	1.00	1.21 (1.09–1.36)	1.35 (1.25–1.45)
PW/BW2	Low	1.00	0.85 (0.76–0.96)	0.71 (0.65–0.77)	1.00	0.87 (0.77–0.97)	0.76 (0.70–0.83)
	High	1.00	1.21 (1.09–1.35)	1.73 (1.62–1.84)	1.00	1.18 (1.06–1.31)	1.52 (1.43–1.63)

Note: Z-score (− 1;1) was used as a reference; Z-score of less than − 1 was defined as low; Z-score higher than + 1 was defined as high; PW, placental weight; BW, birth weight; ¹ Relative risk ratio adjusted for the variables (maternal age, parity, marital status, residence, ethnicity, education, year of delivery, body mass index, mode of delivery, gestational diabetes, preeclampsia/eclampsia, anemia, and birth weight); ² Relative risk ratio adjusted for all variables, except birth weight.

 

A negative dose–response relationship was found between the number of cigarettes smoked daily during pregnancy and the odds of low z-scores of both PW and PW/BW. Adjustment for potential confounders did not change this relationship (see Table 4).

 

Table 4. Relationship between the number of cigarettes smoked daily during pregnancy and z-scores of PW and PW/BW in the Murmansk Region (n = 40,464)

Z-score		Unadjusted RRR (95% CI)1			Adjusted RRR (95% CI)2
		Cigarettes smoked daily during pregnancy (0 as a reference)			Cigarettes smoked daily during pregnancy (0 as a reference)
		1–5	6–10	≥ 11	1–5	6–10	≥ 11
PW1	Low	0.62 (0.52–0.73)	0.56 (0.47–0.67)	0.52 (0.38–0.72)	0.47 (0.39–0.56)	0.36 (0.29–0.43)	0.30 (0.21–0.42)
	High	1.55 (1.38–1.74)	1.81 (1.62–2.03)	2.01 (1.66–2.42)	1.87 (1.65–2.13)	2.48 (2.19–2.82)	2.97 (2.41–3.64)
PW/BW2	Low	0.38 (0.31–0.46)	0.31 (0.24–0.39)	0.29 (0.19–0.46)	0.42 (0.34–0.52)	0.34 (0.27–0.43)	0.32 (0.21–0.51)
	High	2.16 (1.93–2.41)	3.10 (2.80–3.44)	4.14 (3.49–4.91)	1.87 (1.67–2.09)	2.69 (2.42–3.00)	3.55 (2.98–4.23)

Note: Z-score (− 1;1) was used as a reference; Z-score of less than − 1 was defined as low; Z-score higher than + 1 was defined as high; PW, placental weight; BW, birth weight; ¹ Relative risk ratio adjusted for the variables (maternal age, parity, marital status, residence, ethnicity, education, year of delivery, body mass index, mode of delivery, gestational diabetes, preeclampsia/eclampsia, anemia, and birth weight); ² Relative risk ratio adjusted for all variables, except birth weight.

 

However, positive dose–response relationship was observed between the high z-scores of PW and PW/BW and the number of cigarettes smoked daily during pregnancy (see Table 4). Moreover, mothers who smoked ≥ 11 cigarettes per day during pregnancy were 2.97 and 3.55 times more likely to have a high z-score of PW and PW/BW, respectively, compared to non-smokers.

DISCUSSION

In our singleton pregnancy study, mean PW at any week of gestation was lower compared with mean PW (SD) of 612 (138) g at term pregnancies (37–42 weeks) reported by Nascente et al. (2020) [21]. We found that mean BW increased with gestational age for both female and male newborns born at 37–41 weeks of pregnancy. Other studies also showed a trend toward a higher BW in infants born at 37–41 weeks, which is consistent with our findings [21–23].

In our study, smokers and quitters were more likely to have high z-scores of PW and PW/BW as opposed to non-smokers. These findings are consistent with previous studies, where it was confirmed that continued smoking during pregnancy caused higher PW [9, 10, 24]. For example, in a birth cohort study conducted in Japan involving 91,951 records, both PW and PW/BW were higher in smokers compared with non-smokers [24]. Heidari et al. (2018) also found higher mean PW in smokers (610 g) as compared with non-smokers (455 g) [8]. A recent meta-analysis showed a 182 g heavier placenta in smoking pregnant women compared with quitters [10]. In contrast to non-smokers, PW demonstrated a higher mean value in quitters [25].

Smoking during pregnancy affects the development and function of placenta. However, the underlying mechanisms remain unclear. In contrast to non-smokers, heavy smokers had 1.5-times lower total volume of placenta blood vessels and 2-times lower volume density of blood vessels. These differences were statistically significant. In smokers, the total volume of intervillous space, syncytiotrophoblast, and fibrin was almost 1.5-times higher compared with the control (non-smoker) group [12]. Previously, it has been suggested that abnormal vascularisation of the placenta and subsequent placental insufficiency in smokers were the leading causes of adverse pregnancy outcomes [26]. In addition, previous studies observed a differential expression of angiogenic factors in placenta in pregnancy with complications [9, 27, 28]. Pfarrer et al. (1999) explained the higher PW in smokers by adaptive angiogenesis in placental villi [29]. Their findings suggested an adaptive response of the capillary bed in fetus within placental villi in smoking pregnant women. It increases the surface area used for gas and nutrients exchange by reducing the negative effect of hypoxia. Gloria-Bottini et al. (2015) [30] confirmed a discordant effect of smoking on BW and PW in Haptoglobin 2 phenotype mothers, but a concordant effect on BW and PW in mothers carrying the Haptoglobin 1 allele. These results further support the hypothesis of a possible relationship between BW and PW and maternal haptoglobin phenotype. In contrast, previous studies did not confirm the expected negative effect of smoking on PW. This inconsistency may be explained by methodological limitations of the study [11].

In this study, both the PW and PW/BW z-scores were related to the number of cigarettes smoked daily during pregnancy. The women who smoked eleven or more cigarettes per day had heavier placentas and higher PW/BW compared with light (1–5 cigarettes) smokers. Consistent with a Mendelian study [10], our study showed that continued smoking during pregnancy causes a higher PW. Furthermore, we found a higher PW/BW in smokers compared with quitters and in quitters compared with non-smokers. In contrast to non-smokers, quitters and smokers were approximately 1.2 and 1.5 times, respectively, more likely to have high PW/BW z-scores.

We observed a positive dose–response relationship between the high z-scores of PW and PW/BW and the number of cigarettes smoked daily. Our study is consistent with earlier findings, which showed that PW/BW in smokers increased with the number of cigarettes smoked, regardless of the smoking status in the third trimester [25].

Our study is the first in Russia to determine the relationship between smoking before and during pregnancy and PW using a large population-based sample, which included all pregnant women in the region. This can mitigate the risk of sampling biases; however, a relatively high number of missing records in registered pregnancies may affect the results. We have not used any imputation technique to deal with the problem of missing data, leading to exclusion of approx. 17%–18% of observations. This may potentially decrease the power of the study, but it is still higher than 80%. Pregnancy cases with missing records can probably be systematically different from those without any omissions. We did not perform sensitivity analysis in this study. However, our previous study based on the MCBR did not show any difference between those with and without missing data on core maternal parameters.

Another limitation of the study affecting its results is a possible data bias as questions on smoking status can be sensitive for pregnant women and the relevant data on this behavior factor collected by doctors may be misclassified. However, consistent results of the previous study allow the self-assessment of smoking to be treated with confidence.

CONCLUSION

The mean PW for male newborns was 534.1 g (SD: 117.9 g) and 523.7 g (SD: 116.6 g) for female newborns and increased with gestational age. The study found a higher PW and PW/BW ratio in smokers and whose who quitted before the first antenatal visit and this relationship has dose–response relationship for smokers. Our findings confirm that both smoking cessation and decrease in the number of cigarettes smoked daily may reduce the risks of adverse pregnancy outcomes for the fetus. It can potentially be used as a motivation tool to promote primary prevention strategies aimed at reducing adverse pregnancy outcomes in smoking women.

ADDITIONAL INFORMATION

Author contribution: O.A. Kharkova: design of the study, statistical analysis, data interpretation, writing—original draft; V.A. Postoev, A.A. Usynina: published data search and analysis, writing—original draft, writing—review & editing. All the authors approved the version of the manuscript to be published and agreed to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Ethical approval: The study was approved by Ethical Committee of the Northern State Medical University (Arkhangelsk, Russia) (Protocol No. 08/12-14 dated December 10, 2014).

Disclosure of interests: The authors have no relationships, activities, or interests for the last three years related to for-profit or not-for-profit third parties whose interests may be affected by the content of the article.

Statement of originality: No previously published material (text, images, or data) was used in this work.

Data availability statement: The editorial policy regarding data sharing does not apply to this work.

Generative AI: No generative artificial intelligence technologies were used to prepare this article.

Provenance and peer review: This paper was submitted unsolicited and reviewed following the standard procedure. The peer review process involved two members of the editorial board and the in-house scientific editor.

作者简介

Olga A. Kharkova

Northern State Medical University

编辑信件的主要联系方式.
Email: harkovaolga@yandex.ru
ORCID iD: 0000-0002-3130-2920
SPIN 代码: 2167-7550
Scopus 作者 ID: 55912362200
Researcher ID: AAO-8495-2020

Cand. Sci. (Psychology), Associate Professor

俄罗斯联邦, Arkhangelsk

Vitaly A. Postoev

Northern State Medical University

Email: v.postoev@nsmu.ru
ORCID iD: 0000-0003-4982-4169
SPIN 代码: 6070-2486

MD, Cand. Sci. (Medicine), Associate Professor

俄罗斯联邦, Arkhangelsk

Anna A. Usynina

Northern State Medical University

Email: perinat@mail.ru
ORCID iD: 0000-0002-5346-3047
SPIN 代码: 3735-1100

MD, Dr. Sci. (Medicine), Associate Professor

俄罗斯联邦, Arkhangelsk

参考

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