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Online ISSN
1305-3124

Established
1993

Editors-in-Chief
​Cihat Şen, ​Nicola Volpe

Editors
Daniel Rolnik, Mar Gil, Murat Yayla, Oluş Api

Statistics Editor
Resul Arısoy

Article info

The effect of body mass index, smoking and anemia on fetal birth weight. Perinatal Journal 2021;29(2):- DOI: 10.2399/prn.21.0292004

Author(s) Information

Ersin Çintesun1,
Feyza Nur İncesu Çintesun2,
Meltem Aydoğdu1,
Emine Taşkın1,
Mete Can Ateş1,
Abdul Hamid Güler1,
Çetin Çelik1

  1. Selçuk Üniversitesi Tıp Fakültesi Kadın Hastalıkları ve Doğum Anabilim Dalı Konya TR
  2. SBÜ.Konya Şehir Hastanesi Kadın Hastalıkları ve Doğum Kliniği Konya TR
Correspondence

Ersin Çintesun, Selçuk Üniversitesi Tıp Fakültesi Kadın Hastalıkları ve Doğum Anabilim Dalı Konya TR, [email protected]

Publication History

Manuscript Received: April 09, 2021

Manuscript Accepted: June 21, 2021

Earlyview Date: June 21, 2021

Conflicts of Interest

No conflicts declared.

Objective
Fetal growth is an important indicator of fetal health. Low birth weight (LBW)  is also associated with increased perinatal morbidity and mortality. Numerous factors that affect fetal weight have been identified. In this study, we aimed to investigate the effect of body mass index, smoking, and anemia on fetal birth weight on term pregnant women who had vaginal delivery in our clinic.
 
Methods
This study is a retrospective cross-sectional study. This study included patients who had a spontaneous vaginal delivery at our hospital between January 1st, 2018, and June 15th, 2020. Measurements of hemoglobin (Hb) and hematocrit (Hct) levels during birth supported the diagnosis of anemia. Hb levels were compared in three categories in this study: (1) Hb <10 g/dL; (2) ≥10 g/dL, <11 g/dL; and (3) Hb ≥11 g/dL. Anemia was defined as having a Hb level <11 mg/dL. Birth weight was categorized as LBW <2500 g; normal birth weight (NBW) as ≥2500-3999 g, and macrosomia as ≥4000 g.
Results
Analysis was performed on 1428 pregnant women. There was a statistically significant difference for the Hct and Hb subgroups between the groups (p<.05). Fetal birth weight was found higher in the non-smoking group than in the smoking group (3302.1 ± 381.5g vs. 2839.7 ± 491.5g; p<.001).  BMI and Hb levels positively predicted fetal birth weight (β=0.134; p<.001 and β=0.051; p=.046), smoking was negatively predicted fetal birth weight (β=-0.245; p<.001).
Conclusion
BMI, Hb levels, and smoking status during mother's birth are effective on fetal weight. Smoking was the strongest predictor of fetal birth weight compared with the other variables.
Keywords

delivery, hematocrit, hemoglobin, pregnancy, smoking

Introduction
Fetal growth is an important indicator of fetal health. Low birth weight (LBW) is also associated with increased perinatal morbidity and mortality (1). Fetal growth is mostly modulated by placental functions. Numerous factors have been identified that affect fetal growth and weight gain (2). These are maternal weight before pregnancy, weight gain during pregnancy, maternal nutrition (anemia), harmful habits of the mother (e.g. smoking, alcohol, caffeine, cocaine, opiates), drugs used by the mother during pregnancy, mother's stress and anxiety, mother's perinatal infections, mother's pregnancy or chronic diseases (e.g. preeclampsia, diabetes, autoimmune diseases), and the mother's condition of exercise (2-4).
Cigarette smoking is one of the most important risk factors associated with adverse maternal, fetal, and neonatal outcomes (5). As a result of increased public health education, smoking rates have tended to decrease compared with previous years (6). However, some women continue to smoke during pregnancy. A study in the United States of America (USA) showed that 8% of pregnant women smoked at any time during pregnancy (7). The rate of smoking during pregnancy in studies in Turkey ranged from 2-17% (8). The true prevalence of smoking during pregnancy is difficult due to incomplete records and self-reported systems. Studies based on biochemical markers such as exhaled carbon monoxide and urinary cotinine have indicated that pregnant women underreport both smoking status and the extent of smoking (9). Secondhand smoke in pregnancy is also one of the important causes of the elevation of cotinine levels in the blood. Many adverse effects of smoking on pregnancy have been reported. In a study conducted in the USA, 5 to 8% of preterm births, 13 to 19% of term infants with intrauterine growth restriction, 5 to 7% of preterm-related deaths, and 23 to 34% of sudden infant death syndrome were found to be related to prenatal smoking (10).
Anemia is a leading global health problem affecting millions of women of reproductive age (11). Anemia during pregnancy is a fundamental indicator of maternal mortality and poor birth outcomes in both developing and developed countries (4). Many studies showed that low maternal hemoglobin (Hb) (<110 g/L) was associated with poor birth outcomes (LBW, preterm birth, small‐for‐gestational‐age (SGA), stillbirth, and perinatal and neonatal mortality) and adverse maternal outcomes (postpartum hemorrhage, preeclampsia, and blood transfusion) (3, 4, 12).

When the literature is reviewed, it will be seen that many factors are affecting fetal birth weight. Obesity, anemia, and smoking are the most important public health factors of our century. However, although these three variables have been shown in the literature to be separately effective on fetal birth weight, it is known that they are also effective on each other (13). It has also been shown that anemic women have higher umbilical cord oxygen levels (14). For this reason, this study aimed to examine the relationships of these variables with each other separately and examine the effects of these variables on fetal birth weight by correcting the confounding effect.
This study aimed to investigate the effect of body mass index, smoking, and anemia on fetal birth weight on term pregnant women who had a vaginal delivery in our clinic.

 
Methods
Study design
This study was a retrospective cross-sectional study. This study included patients who had a spontaneous vaginal delivery at Selcuk University Medical Faculty Hospital between January 1st, 2018, and June 15th, 2020. The Local ethics committee of Selcuk University approved the study.
Inclusion and Exclusion Criteria
The inclusion criteria were as follows: being at 37 weeks of gestation and later and spontaneous vaginal delivery. The exclusion criteria were as follows: induced or spontaneous preterm deliveries, maternal systemic diseases (e.g. preeclampsia, hypertension, diabetes), uterine and fetal anomalies, cesarean deliveries (Figure 1).
Birth outcomes and maternal variables
The gestational week was calculated according to the women's last menstrual period or ultrasound results in the first trimester. The measurement of Hb and hematocrit (Ht) levels during birth supported the diagnosis of anemia. Hb levels were compared in three categories in this study: (1) Hb <10 g/dL, (2) ≥10 g/dL, <11 g/dL, (3) Hb ≥11 g/dL. Anemia was defined as having a Hb level <11 mg/dL. The birth weight was categorized as low birth weight (LBW) as <2500 g, normal birth weight (NBW) as ≥2500-3999 g, and macrosomia as ≥4000 g. Hemogram and hematocrit values of the patients were blood results before birth. Body mass index (BMI) was accepted as the pre-birth measurements.
Statistical analysis
Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 21.0 software (IBM Corp., Armonk, NY, USA). The distribution of variables was tested for normality using histograms and the Shapiro-Wilk test. Outliers were analyzed using boxplot graphics. Parametric continuous data are presented as means ± standard deviation, nonparametric continuous data are presented as medians (min-max), and categorical variables are expressed as numbers (percentages). Data were analyzed using Student’s t-test, the Mann-Whitney U test, one-way analysis of variance (ANOVA), the Kruskal-Wallis test, and Pearson’s Chi-square test, where appropriate. Multivariate linear regression analysis was used to predict fetal birth weight using age, smoking, BMI, and Hb levels. P<.05 was considered statistically significant.
 
Results
There were a total of 4137 total deliveries at our tertiary hospital between January 1st, 2018, and June 15th, 2020. Of these, 2141 women who underwent cesarean delivery were excluded from the study. The delivery records of 1996 patients who had vaginal delivery were analyzed. Of these, 34 patients were excluded from the study because of fetal problems (fetal anomaly, intrauterine fetal death, etc.) and 534 patients because of maternal problems (preeclampsia, gestational diabetes mellitus, fetal growth restriction, etc.). As a result, a total of 1428 patients' records were included in this study (Figure 1).
Analysis was performed on 1428 pregnant women. 72 (5%) of these patients reported smoking, and 1356 (95%) pregnant women reported not smoking. Gravida and Parity were higher in the smoking group than in the non-smoking group (3 (1-6) vs 2(1-8), p0.001 and 1(0-4) vs 1(0-7) p0.009). Ht and Hb were statistically different between groups (p0.026). Fetal birth weight was lower in the smoking group (2839.7 +/- 491.5 vs 3302.1 +/- 381.5, p<0.001). LBW was most common in the smoking group than in the non-smoking group (25% vs 1.2%, p<0.001) (Table 1).
The comparison of variables according to fetal birth weight categories is summarized in Table 2. Patients were divided into three groups, as explained before (LBW, NBW, and macrosomia). When analyzing LBW and NBW + macrosomia, all variables except smoking status and Hb levels were similar between the groups. In the analyses among the three groups, all variables except maternal weight, BMI, and smoking status were similar between the groups. The BMI of the macrosomia group was significantly higher than in the NBW group (mean 29.7 ± 3.6 versus 28.5 ± 3.3 kg/m2; p=.045). The smoking rate in the LBW group was also significantly higher than in the NBW and macrosomia groups ( 52.9% vs 4% and 1.9%, p<0.001). (Table 2.)
Multivariate linear regression analysis was performed to predict fetal birth weight using age, BMI, smoking, and Hb level variables. Age, BMI, smoking, and Hb levels were statistically significant predictors of fetal birth weight (F(4,1423) = 32,212; p<.001). BMI, smoking, and Hb levels separately predict fetal birth weight. While BMI and Hb levels positively predicted fetal birth weight (β=0.134; p<.001 and β=0.051; p=.046), smoking was negatively predicted fetal birth weight (β=-0.245; p<.001). Smoking was the strongest predictor of fetal birth weight compared with the other variables. Equation predicting fetal weight: B= 2707.137 – 2.167*Age + 16.227 * BMI - 444.679 * Smoking (yes=1. no=0) + 15.469 * Hb (Table 3).
Discussion
In this study, maternal BMI, anemia, and smoking history, which affect fetal birth weight, were investigated. It was found that fetal birth weight was lower in smokers. In addition, we found the hematocrit value to be lower in smokers. In the study, multivariate regression analysis was performed to eliminate possible confounding effects of variables on each other. As a result of this analysis, it was found that smoking, hemoglobin, and BMI values had a significant effect on fetal weight. Smoking was found to be the most effective variable.
We found that the anemia rate was significantly lower in the LBW group and patients who smoked. Anemia in pregnancy is a global health problem as the World Health Organization (WHO) has declared (15). Some degree of dilutional anemia may be seen in normal pregnancy physiology, but iron deficiency anemia can have severe adverse health problems for both the mother and child (16). Due to dilutional anemia, the anemia limits of pregnant women and healthy women are different. The classification recommended by the American College of Obstetricians and Gynecologists (ACOG) for anemia is as follows: In the first trimester, Hb (g/dL) and Hct (%) levels below 11 g/dL and 33%, respectively; in the second trimester 10.5 g/dL and 32%, respectively; and in the third trimester 11 g/dL and 33%, respectively (17). There are many large studies on fetal and maternal negative effects of severe anemia during pregnancy (18, 19). A study by Zamora et al. found that severe antenatal or postnatal maternal anaemia (of any type) was associated with an increased risk of maternal death (OR=2.36) (18). Tunkyi et al. found that prematurity, birth weight, and hypertensive disorders of pregnancy were different between the anemic and non-anemic pregnancies (19). In our study, we did not investigate maternal outcomes with anemia. We specifically investigated the effect of anemia and smoking on fetal birth weight. Our study found the mean of Hb lower in the LBW group compared with the non-LBW group (p=.035). Also, the rate of smoking was found high in the LBW group. In the multivariate linear regression analysis including smoking, age, BMI, and Hb levels, Hb was found to be a significant predictor of fetal birth weight (B=15.469; p=.046).
Cigarette smoke contains a large number of toxins that affect the entire body system. Naturally, they also have effects on fetal health during pregnancy (10). In a study by Stephanie et al., it was found that women who smoked had a lower weight by 200 g (20). Women who smoked were 1.5 to 3.5 times more likely to have an LBW infant in other studies (21, 22). In a study by Chuhao et al., it was found that passive smoking resulted in LBW (23). Smoking was associated with low fetal birth weight, miscarriage, stillbirth and neonatal death, preterm premature rupture of membranes, placental abruption/placenta previa, preterm birth, congenital malformations (24). Various mechanisms describing adverse pregnancy outcomes associated with maternal smoking have been observed. These include impaired fetal oxygenation, varying fetal development, and physiologic response, and toxin exposure. Data on mechanisms associated with e-cigarette use are currently mainly available from animal models (25, 26). In our study, lower birth weight was found in patients who smoked, similar to the literature. In addition, in our study, Hb and Hct levels were found lower in patients who smoked. In literatüre, it was reported that smoking caused increasing in Hct and Hb levels (13). Although it was expected that Hb levels should be higher in smoking women than non-smoking women, it was not found higher. The Hb level we detected in smoking women may also be high values ​​related to smoking. New Hb threshold values ​​may be required for pregnant women who smoke. However, studies conducted with pregnant women have shown that smoking does no effect on hematological changes (27). However, it is not possible to explain this effect only with smoking, due to the physiological changes that occur during pregnancy, the unknown frequency of smoking, the unknown blood carbon monoxide levels, and the lack of maternal nutrition and iron support that affect the hemoglobin value. In our study, in regression analysis, smoking, compared with non-smoking, negatively affected fetal birth weight.
Another factor effective in fetal weight is maternal weight status. The relationship between maternal weight status and fetal weight has been shown in many studies (28, 29). In our study, we used maternal pre-birth weight and BMI. In multivariate linear regression analysis, We found that BMI was a significant predictor of fetal birth weight.
The limitations of the study are its design being a retrospective study, the frequency and time of smoking of the patients are unknown, which type of cigarette is unknown, the blood carbon monoxide levels of the patients are unknown, and that all factors affecting weight gain were not included in the study. The strength of the study is that more specifically, smoking status and Hb values are investigated in terms of fetal weight.
Conclusion
Smoking at the end of the pregnancy correlates with lower birth weight. Higher BMI and higher Hb levels at the end of the pregnancy correlate with higher birth weight. However, prospective studies reinforced with blood and urine analysis will provide more precise results with the inclusion of the passive smoking of patients.



 
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File/Dsecription
Figure 1.
Flow diagram
Table 1.
Comparison of variables according to smoking status.
Table 2.
Comparison of variables according to fetal birth weight categories
Table 3.
Linear regression analysis of the factors to predict fetal birth weight.