Home The impact of abnormal maternal body mass index during pregnancy on perinatal outcomes: a registry-based study from Qatar
Article Open Access

The impact of abnormal maternal body mass index during pregnancy on perinatal outcomes: a registry-based study from Qatar

  • Ghinwa Lawand , Fathima Minisha ORCID logo EMAIL logo , Salwa Abu Yaqoub , Nader Al Dewik ORCID logo , Hilal Al Rifai and Thomas Farrell
Published/Copyright: August 24, 2023
Download Article (PDF)
Journal of Perinatal Medicine
From the journal Journal of Perinatal Medicine Volume 51 Issue 9

Abstract

Objectives

Abnormal body mass index (BMI) during pregnancy, a growing public health concern, increases maternal and neonatal complications. This study aimed to investigate the impact of abnormal BMI on perinatal outcomes compared to normal BMI.

Methods

A total of 14,624 women having singleton births were categorized as underweight (BMI<18.5 kg/m2), overweight (25.0–29.9 kg/m2), obesity class I (30.0–34.9 kg/m2), obesity class II (35.0–39.9 kg/m2), and obesity class III (≥40.0 kg/m2) and compared to those with normal BMI (18.5–24.9 kg/m2). Outcomes included gestational diabetes (GDM), gestational hypertension (GHT), postpartum haemorrhage (PPH), cesarean delivery (CD), preterm birth (PTB), low birth weight (LBW), congenital anomalies and neonatal intensive care unit admission.

Results

Women with increasing BMI had increasingly higher odds of developing specific adverse outcomes, the highest being in the class III obesity group (GDM-aOR 2.71, 95 % CI 2.25–3.27, p<0.001, GHT-aOR 5.32 95 % CI 3.49–8.11, p<0.001, CD-aOR 2.33 95 % CI 1.85–2.94, p<0.001, PPH-aOR 1.77 95 % CI 1.35–2.33, p<0.001). On the other hand, being underweight during pregnancy was associated with increased odds of PTB (aOR 2.09, 95 % CI 1.37–3.20, p=0.001), LBW (OR 1.88, 95 % CI 1.27–2.79, p=0.002) and congenital anomalies (aOR 2.52 95 % CI 1.12–5.64, p=0.025). Majority in the underweight category gained less than expected gestational weight gain during the pregnancy.

Conclusions

The findings of this study have important implications for the clinical management of pregnant women with abnormal BMI. Interventions to improve maternal and neonatal outcomes must focus on enhancing pre-pregnancy BMI and maintaining adequate gestational weight gain.

Keywords: adverse perinatal outcomes; gestational weight gain; maternal BMI; obesity

Introduction

The World Health Organization (WHO) states that obesity, described as harmful excessive body fat, is one of the most significant global health issues of the twenty-first century due to the alarming rise in prevalence, which has tripled since 1975. By 2030, it is estimated that 1 in 5 women and 1 in 7 men will be living with obesity, which equates to more than 1 billion people worldwide [1], [2], [3]. The most widely used biomarker of obesity is body mass index (BMI), obtained by the weight in kilos divided by the square of the height in meters. The WHO categorizes BMI into four groups based on the increasing risks for conditions such as diabetes, heart disease, and cancer leading to premature death [4]. Along with the rise in obesity rates in the general population, obesity during pregnancy has increased, making it a common high-risk condition in obstetrics today [5]. Approximately 38.9 million pregnant women worldwide were overweight or obese in 2021 [6].

Maternal weight has emerged as a key indicator of adverse maternal and fetal outcomes [7]. Significant maternal morbidities, ranging from gestational diabetes mellitus (GDM), hypertension (GHT), protracted labour, shoulder dystocia, instrumental deliveries, caesarean delivery (CD), anaesthesia complications, postpartum haemorrhage (PPH), infection, thromboembolism, extended hospital stay, and postpartum depression have been linked to maternal obesity. Miscarriages, birth abnormalities, macrosomia, unexplained stillbirths, neonatal intensive care unit (NICU) care, and neonatal death are also associated with obesity [8].

Following the global alert for overweight and obesity, attention has been directed to the other extreme of nutritional status in developing and developed countries [9]. Less research has been targeted at the effect of maternal underweight, that is associated with adverse neonatal outcomes [10]. Although GHT, preeclampsia, and GDM are less likely to occur in women with low BMI, these women have higher risks of preterm delivery, fetal intrauterine growth restriction (IUGR), and small for gestational age (SGA) [11, 12].

Due to recent changes in social and cultural factors, diet and nutrition, lack of physical activity, and rapid urbanization, there is an expanding concern with quickly growing obesity and its linked medical problems in the Middle East [13]. In Qatar, adult obesity was 40.0 % in men and 49.7 % in women in 2014. However, there is a lack of research in Qatar that quantifies the adverse effects of abnormal BMI on pregnancy, which would help develop targeted management strategies. This study aimed to evaluate the association between abnormal maternal BMI (underweight, overweight, and obesity) and adverse maternal and neonatal outcomes among singleton pregnancies compared to normal maternal BMI.

Materials and methods

Study design and setting

This registry-based study included women delivering at the largest tertiary maternity hospital in Qatar (averaging 16–18,000 deliveries per year) between January 2017 and December 2017. The data used in this study was extracted from the PEARL Peristat registry (Perinatal Neonatal Outcomes Research Study in the Arabian Gulf), a population-based registry funded by the Qatar National Research Fund (Grant number NPRP 6-238-3-059), including maternal and fetal outcomes of all hospital deliveries during the registry period. Additional ethical approval specific for this study was not required, as only secondary analysis of registry data was done.

Participants

We extracted data from women with a reported live birth after singleton pregnancies, gestational age (GA)≥24 completed weeks at birth, and a BMI documented at the first antenatal visit. The women were categorized into five exposure groups based on WHO BMI classification: underweight (BMI<18.5 kg/m2), overweight (BMI 25.0–29.9 kg/m2), obesity class-I (BMI 30.0–34.9 kg/m2), obesity class-II (BMI 35.0–39.9 kg/m2), and obesity class-III (BMI≥40.0 kg/m2). Women with a normal BMI (18.5–24.9 kg/m2) formed the comparison group (unexposed). Those with a booking BMI in the first trimester were analyzed separately to explore the antenatal weight gain in the different BMI groups.

Data source and variables

The maternal demographic variables included:

  1. Maternal age: in years-continuous variable; and categorized into two groups, median age used as the cutoff.

  2. Nationality as documented in official hospital records: classified into Qatari and non-Qatari.

  3. Parity-defined as previous births at ≥24 weeks gestation. This variable was classified into three groups-nulliparous (no previous births), multiparous (1–3), grand multiparous (≥4).

  4. Number of previous CDs-classified into two groups (0 previous CD and ≥1 previous CD).

  5. Pre-existing medical illnesses such as diabetes, chronic hypertension and anaemia (yes/no).

Maternal age and parity were considered apriori confounders and were adjusted for in the analysis of all outcomes. Other known confounders were also adjusted for, provided they did not fall in the causal pathway between maternal BMI and the outcome variables.

The primary maternal and fetal outcome variables included:

  1. Gestational diabetes (GDM)-defined as an abnormal 75 g glucose tolerance test performed between 16 and 32 weeks gestation according to the prior risk of the patient.

  2. Gestational hypertension (GHT) – first onset of hypertension occurring after 20 weeks of gestation [14] (including preeclampsia and eclampsia) in women not known to have chronic hypertension.

  3. Mode of delivery-vaginal delivery (spontaneous and instrumental) vs. CD (elective and emergency).

  4. Postpartum haemorrhage (PPH) – abnormal bleeding after birth (>500 mL during vaginal delivery and >1000 mL during CD [15].

  5. Preterm birth (PTB)-defined as delivery before 37 completed weeks of gestation [16].

  6. Low birth weight (LBW)-birthweight<2,500 g, regardless of gestational age at birth [17].

  7. Macrosomia – birthweight>4,000 g, regardless of gestational age at birth [18].

  8. Admission to NICU-baby requiring admission to intensive care unit after birth for any reason.

  9. APGAR score of <7 at 1 min of life-as evaluated by the delivery midwife or the attending neonatologist.

  10. Congenital anomalies-any internal or external physical anomalies at birth diagnosed by the attending neonatologist after clinical examination and/or imaging.

Additionally, for women who had their first antenatal visit in the first trimester (≤13 completed weeks), the maternal gestational weight gain (GWG) was calculated as the difference between the documented maternal weight in kilograms at booking and delivery. This variable was classified into three categories depending on if the weight gain observed during pregnancy was less than the lower limit, within or more than the upper limit of the expected range of weight gain in pregnancy for each BMI group, as sourced from the Institute of Medicine international guidelines for weight gain in pregnancy [19].

Statistical methods

Continuous variables were reported as mean ± standard deviation (SD) or median ± interquartile range (IQR) according to the distribution of the variable (assessed by histograms and Shapiro Wilk test for normality) and compared using one-way ANOVA or Kruskal–Wallis test as appropriate. Categorical variables were described using frequencies and percentages and compared using Chi-Square or Fisher’s exact test as appropriate.

The frequencies of each outcome variable were calculated, and the percentages of the total in each group were depicted as bar graphs to visualize the differences between the groups. Adjusted odds ratios (aOR) and 95 % confidence intervals (CI) were calculated using multivariable logistic regression models, adjusting for confounders. The normal BMI group formed the baseline group for calculating the ORs. The weight gain during the antenatal period was reported as mean ± SD.

All statistical analysis was performed in STATA statistical software, Release 16 [20]. The null hypothesis for the models stated that there is no difference in the odds of outcomes in each abnormal BMI group compared to the normal BMI group. A p-value <0.05 provided evidence against this null hypothesis and was considered statistically significant.

Results

A total of 14,624 women were included in the study: 203 (1 %) women were underweight, 3,525 (24 %) had normal BMI, 5,033 (35 %) formed the overweight category, 3,665 (25 %), 1,561 (11 %) and 637 (4 %) belonged to obesity class-I, class-II and class-III respectively.

The maternal demographics in the different exposure groups are shown in Table 1. As the BMI increased, a higher proportion of women were older (≥30 years age group). Nearly 70 % in the obesity-III group belonged to the older age group compared to only 16 % in the underweight category. A higher proportion of women in the class-II and class-III groups were Qatari. Grand multiparity was more prevalent as the BMI increased, with around 20 % and more multiparous women in the three obesity groups. In addition, 50 % of mothers in the underweight group were nulliparous.

Table 1:

Distribution of maternal demographic variables among the exposure groups.

Demographic variables n=14,624 Normal BMI (n=3,525) Underweight (n=203) Overweight (n=5,033) Obesity I (n=3,665) Obesity II (n=1,561) Obesity III (n=637) p-Value
n %n n %n n %n n %n N %n n %n
BMI at booking, kg/m2 22.6 ± 1.7 17.4 ± 0.86 27.5 ± 1.4 32.2 ± 1.4 37.1 ± 1.4 43.7 ± 3.8 <0.001a
Age, years 27.7 ± 5.1 25.2 ± 4.6 29.6 ± 5.4 30.7 ± 5.5 31.8 ± 5.4 32.3 ± 5.4 <0.001a
Age <30 years 2,284 64.8 171 84.2 2,551 50.7 1,586 43.3 530 34.0 199 31.2 <0.001
≥30 year 1,241 35.2 32 15.8 2,482 49.3 2,079 56.7 1,031 66.1 438 68.8
Nationality Qatari 889 25.2 53 26.1 1,495 29.7 1,257 34.3 634 40.6 277 43.5 <0.001
Non-Qatari 2,636 74.8 150 73.9 3,538 70.3 2,408 65.7 927 59.4 360 56.5
Parity Nulliparous 1,374 39.0 102 50.3 1,434 28.5 754 20.6 228 14.6 74 11.6 <0.001
Multiparous 1,935 54.9 96 47.3 2,968 59.0 2,209 60.3 908 58.2 378 59.3
Grand multi 216 6.1 5 2.5 631 12.5 702 19.2 425 27.2 185 29.0
Previous caesarean 0 3,012 85.4 189 93.1 3,970 78.9 2,582 70.5 1,061 68.0 395 62.0 <0.001
≥1 513 14.6 14 6.9 1,063 21.1 1,083 29.6 500 32.0 242 38.0
Pre-existing diabetes 40 1.1 3 1.5 95 1.9 111 3.03 75 4.8 45 7.1 <0.001
Chronic hypertension 41 1.2 1 0.5 60 1.2 73 2.0 29 1.9 20 3.1 <0.001
Anaemia 439 12.5 32 15.8 496 9.9 342 9.3 157 10.1 63 9.9 <0.001
Assisted reproduction 79 2.2 3 1.5 136 2.7 102 2.8 42 2.7 20 3.1 0.514

  1. a Compared using ANOVA, Continuous variables represented as mean ± standard deviation. Categorical variables analysed using Chi-Square test; p<0.05 considered evidence again null hypothesis of no difference. The bold values were used to highlight all the percentages as it is a crowded table and we intended the focus to be on the percentages, however this is not necessary to be done.

More than 30 % of women in the obesity groups had a previous CD (38 % in obesity-III) compared to only 7 % in the underweight group. Women in the overweight and obesity groups had a higher prevalence of pre-existing diabetes and chronic hypertension compared to other groups, with an increasing trend noted as the BMI increased. Nearly 16 % of women in the underweight category suffered from anaemia, compared to nearly 10 % in the overweight and obesity groups.

Maternal outcomes

An increasing trend was noted in the incidence of the various maternal outcomes as the BMI groups moved from underweight to class-III (Figure 1). The risk of GDM in this cohort was 30 % (4,212 out of 14,255 women without pre-existing diabetes). Nearly 44 % of women in the highest BMI group developed GDM compared to 20 % in the underweight and normal BMI groups. Similarly, 8 % of women in the class-III group developed GHT compared to 1–1.5 % in the lowest BMI groups, the overall risk in our study sample being 3 %. The risk of CD in the normal BMI group was 22 %. While this risk decreased in the underweight group, the risk steadily increased as the BMI increased and more than doubled (47 %) in the class-III group. In addition, with a 10 % risk of PPH in the entire cohort, there was a steady increase in the incidence from 8 % in the normal BMI group to a maximum of 13 % in the highest BMI group.

Figure 1: Percentages of women in each group with maternal pregnancy outcomes.
Figure 1:

Percentages of women in each group with maternal pregnancy outcomes.

Women in the overweight group had 40 % higher odds of developing GDM (aOR=1.40, 95 % CI=0.26–1.55, p<0.001), as shown in Table 2. Furthermore, the OR increased steadily with BMI and class-III group had 2.71 times higher odds of developing GDM (aOR=2.71, 95 % CI=2.25–3.27, p<0.001).

Table 2:

Adjusted odds ratios for the association between BMI categories and maternal outcomes.

Maternal outcomes Normal BMI Underweight Overweight Obesity I Obesity II Obesity III
Gestational diabetes (n=14,255) aOR (95 % CI) 1 0.99 (0.68–1.42) 1.40 (1.26–1.55) 1.90 (1.70–2.12) 2.35 (2.05–2.70) 2.71 (2.25–3.27)
p-Value – 0.937 <0.001a <0.001a <0.001a <0.001a
Gestational hypertension (n=14,624) aOR (95 % CI) 1 0.79 (0.19–3.29) 1.60 (1.14–2.24) 2.38 (1.69–3.34) 3.89 (2.69–5.62) 5.32 (3.49–8.11)
p-Value – 0.747 0.007a <0.001a <0.001a <0.001a
Caesarean delivery (n=14,624) aOR (95 % CI) 1 0.93 (0.61–1.42) 1.31 (1.16–1.48) 1.55 (1.36–1.77) 1.96 (1.66–2.31) 2.33 (1.85–2.94)
p-Value – 0.746 <0.001a <0.001a <0.001a <0.001a
Postpartum haemorrhage (n=14,517) aOR (95 % CI) 1 0.62 (0.33–1.15) 1.25 (1.07–1.46) 1.29 (1.09–1.52) 1.48 (1.20–1.82) 1.77 (1.35–2.33)
p-Value – 0.131 0.004a 0.003a <0.001a <0.001a

  1. Gestational diabetes adjusted for age and parity categories, nationality, and chronic hypertension (excluded 369 women with pre-existing diabetes). Gestational hypertension adjusted for age and parity categories, nationality and pre-existing diabetes. Caesarean delivery adjusted for age and parity categories, previous caesarean, pre-existing diabetes and chronic hypertension. Postpartum haemorrhage adjusted for age and parity categories, nationality, chronic hypertension, pre-existing diabetes (missing data n=107–0.7 %). a=p<0.05 strong evidence against null hypothesis of no difference. The bold values represent all the statistically significant results at the cut off of p<0.05.

Similarly, the odds of developing GHT increased steadily from an aOR of 1.60 (95 % CI=1.14–2.24, p<0.001) in the overweight group to an aOR of 5.32 (95 % CI=3.49–8.1, p<0.001) in class-III group. In the last two groups, the odds of CD delivery were nearly twice that of the control group (aOR=1.96, 95 % CI=1.66–2.31 and aOR=2.33, 95 % CI=11.85–2.94 respectively, p<0.00). The odds of PPH were 25–30 % higher in the overweight and class-I groups, which increased to 77 % higher odds in class-III (aOR 1.77, 95 % CI 1.35–2.33). The model for PPH excluded the women with missing data for blood loss at the time of delivery (n=107, 0.7 %).

The underweight category had similar chances of GDM and CD compared to the control. For GHT, a 21 % reduction in odds was seen (aOR=0.79 95 % CI=0.19–3.29), and a 38 % reduction for PPH (aOR=0.62, 95 % CI=0.33–1.15) were noted in this group. However, none of these associations reached statistical significance (p>0.05).

Neonatal outcomes

There was an 8 % incidence of PTB and LBW babies in our sample, which increased sharply to 14 % PTB and 16 % LBW in the underweight group while remaining roughly similar in all other groups (Figure 2). Similarly, in the cohort with a 1.5 % risk of congenital anomalies, the underweight group had more than double the risk (3.5 %). The incidence pattern of macrosomia had the familiar upward slant with the increase in BMI, with the highest risk (9 %) noted in the highest BMI group. Nearly 11 % of the babies were admitted to the NICU, which rose to 14–15 % in the extreme BMI groups (underweight and class-III). More than 2 % of the babies had a low APGAR at 1 min of life, roughly the same in all exposure groups.

Figure 2: Percentages of women in each group with adverse neonatal outcomes.
Figure 2:

Percentages of women in each group with adverse neonatal outcomes.

Women underweight had 2.09 times higher odds of having a PTB (95 % CI=1.37–3.20, p=0.001), as shown in Table 3. No other BMI group had a statistically significant association with PTB. Similarly, the underweight group was at increased risk of LBW (aOR=1.88, 95 % CI=1.27–2.79, p=0.002). However, the odds decreased as BMI increased, with the highest BMI group having a 47 % reduced chance of LBW (aOR=0.53 95 % CI=0.37–0.76, p<0.001). The underweight group had an 80 % reduction in the odds of fetal macrosomia (aOR=0.20, 95 % CI=0.03–1.46, p=0.114), whereas class-III had a 3.88 times higher odds of having fetal macrosomia (aOR=3.88, 95 % CI=2.73–5.53 p<0.001) compared to the unexposed, with the OR increasing with each BMI group.

Table 3:

Adjusted odds ratios for the association between BMI categories and neonatal outcomes.

Neonatal outcomes Normal BMI Underweight Overweight Obesity I Obesity II Obesity III
Preterm birth n=14,624 aOR (95 % CI) 1 2.09 (1.37–3.20) 0.90 (0.76–1.06) 0.94 (0.79–1.13) 0.94 (0.75–1.18) 0.84 (0.61–1.15)
p-Value – 0.001a 0.213 0.519 0.572 0.273
Low birth weight n=14,618 aOR (95 % CI) 1 1.88 (1.27–2.79) 0.77 (0.66–0.91) 0.70 (0.58–0.83) 0.61 (0.48–0.78) 0.53 (0.37–0.76)
p-Value – 0.002a 0.001a <0.001a <0.001a 0.001a
Macrosomia n=14,618 aOR (95 % CI) 1 0.20 (0.03–1.46) 1.44 (1.68–2.83) 2.18 (1.68–2.83) 2.62 (1.94–3.55) 3.88 (2.73–5.53)
p-Value – 0.114 0.006a <0.001a <0.001a <0.001a
Admission to NICU n=14,624 aOR (95 % CI) 1 1.49 (0.99–2.24) 1.04 (0.91–1.21) 1.22 (1.05–1.42) 1.30 (1.07–1.58) 1.36 (1.04–1.77)
p-Value – 0.055 0.519 0.011a 0.007a 0.022a
APGAR score <7 at 1 min of life n=14,624 aOR (95 % CI) 1 0.71 (0.26–1.97) 0.79 (0.59–1.05) 0.75 (0.54–1.05) 0.99 (0.67–1.49) 0.95 (0.54–1.68)
p-Value – 0.515 0.109 0.092 0.982 0.854
Congenital anomalies n=14,624 aOR (95 % CI) 1 2.52 (1.12–5.64) 1.01 (0.70–1.46) 1.21 (0.82–1.78) 1.08 (0.66–1.79) 0.92 (0.44–1.90)
p-Value – 0.025a 0.970 0.337 0.757 0.814

  1. Preterm birth adjusted for age and parity categories, nationality, pre-existing diabetes, and chronic hypertension. Low birth weight adjusted for age and parity categories, nationality, pre-existing diabetes, and chronic hypertension (6 missing data). Macrosomia adjusted for age and parity categories, nationality, pre-existing diabetes, and chronic hypertension (6 missing data). Admission to NICU and APGAR score <7 adjusted for age and parity categories, chronic hypertension, and pre-existing diabetes. Congenital anomalies adjusted for age and parity categories, nationality, chronic hypertension and pre-existing diabetes. a=p<0.05 strong evidence against null hypothesis of no difference. The bold values represent all the statistically significant results at the cut off of p<0.05.

Women in the underweight group had 2.52 times higher odds of an infant with congenital anomalies (95 % CI=1.12–5.64, p=0.025). The other BMI groups had similar odds to the control group. Additionally, there were higher odds of admission to NICU in the extreme BMI groups– 50 % higher odds (aOR=1.49, 95 % CI=0.99–2.24) and 36 % higher odds (aOR=1.36, 95 % CI=1.04–1.77) in the underweight and class-III groups respectively. There were 20–30 % lesser odds of low APGAR score at birth in the underweight, overweight and class-I groups; however, these associations did not reach statistical significance.

Gestational weight gain

There were 4,796 women with a booking BMI recorded in the first trimester. The mean GWG was 11.1 ± 4.7 kg in the underweight group, 10.7 ± 5.4 kg for women with normal BMI, 9.3 ± 5.9 kg for overweight women, and 7.9 ± 6.4 kg, 6.2 ± 5.8 kg, and 5.2 ± 6.3 kg for classes I, II and III respectively (Table 4). These values were compared to the expected GWG. Only 30 % of our cohort had a GWG within the expected range for each BMI group. Nearly 67 % in the underweight group had less than average expected weight gain, compared to the 56 % in the normal BMI group and 45–46 % in the class II and III groups. In class-I, 42 % of women gained more than expected (highest among all groups).

Table 4:

Gestational weight gain in women with first-trimester booking.

Total n=4,796 Normal BMI (n=1,527) Underweight (n=117) Overweight (n=1,616) Obesity I (n=1,093) Obesity II (n=445) Obesity III (n=178)
Expected weight gain, kg (IOM guidelines) 11.5–16 12.5–18 7–11.5 5–9 5–9 5–9
Weight at booking, kga 57.1 ± 6.1 43.7 ± 4.4 69.0 ± 6.6 81.2 ± 7.4 93.6 ± 7.9 110.1 ± 13.4
Weight at delivery, kga 67.8 ± 8.5 54.8 ± 6.8 78.3 ± 9.0 89.2 ± 10.2 99.7 ± 9.8 115.3 ± 14.3
Weight gain, kga 10.7 ± 5.4 11.1 ± 4.7 9.3 ± 5.9 7.9 ± 6.4 6.2 ± 5.8 5.2 ± 6.3
Number of women with observed weight gain, n (%)
Less than expected 857 (56.1) 78 (66.7) 555 (34.3) 336 (30.7) 205 (46.1) 79 (44.4)
Within expected 452 (29.6) 31 (26.5) 498 (30.8) 301 (27.5) 101 (22.7) 60 (33.7)
More than expected 218 (14.3) 8 (6.8) 563 (34.8) 456 (41.7) 139 (31.2) 39 (21.9)

  1. kg, kilograms; n, number of women with first trimester booking BMI; IOM, Institute of Medicine; Av, average; a=continuous variables represented as mean ± standard deviation.

Discussion

The study results unequivocally show that belonging to the underweight, overweight or obesity categories increases the probability of unfavourable maternal and neonatal outcomes. The odds of developing maternal outcomes such as GDM, GHT, PPH, and delivery by CD and neonatal outcomes such as macrosomia were higher with increasing BMI categories compared to the normal BMI group, with no difference detected between the underweight and normal BMI group. On the other hand, women in the underweight group had a higher chance of PTB, LBW, and congenital anomalies. Both extremes of BMI categories had higher odds of NICU admission.

By classifying women according to their BMI, this study specifically demonstrates a link between increasing BMI (from overweight to obesity class-III) and increased risk of adverse outcomes. Our results are consistent with previous studies showing an association between abnormal BMI and poor maternal and neonatal outcomes [21]. Similar findings from a case-control study conducted in Tehran revealed that obese mothers had a 4.5-fold higher risk of developing hypertensive diseases in pregnancy [22]. In the US, as the mother’s BMI increased compared to normal, the prevalence of cesarean deliveries increased by 28.3 % [23].

In our study, maternal BMI was found to significantly affect birthweight, with women with obesity more likely to have macrosomic babies and women in the underweight category more likely to deliver babies with LBW. This conclusion is reinforced by a meta-analysis reporting that obese women had a 2-fold higher risk of giving birth to a macrosomic baby [24]. In a study conducted in India, mothers underweight during pregnancy had a 17.2 % risk of LBW babies, similar to our study [25]. This high rate of LBW infants is concerning due to the increased risk of infant mortality and morbidity [26].

Our study shows a 2.5 times higher odds of congenital anomalies in babies born to underweight women, supported by Mezzasalma et al. [27], who reported a higher incidence of anomalies like the nervous system, orofacial and urogenital anomalies [27]. Meta-analyses report that maternal obesity, not maternal underweight, is significantly linked to an increased risk of congenital heart disease in their offspring. Metabolic changes such as elevated estrogen levels, hyperinsulinemia, high blood pressure, high blood sugar, and nutritional deficiencies may make women with obesity more vulnerable to having babies with congenital anomalies [28].

Another study investigating the association of maternal pre-pregnancy BMI with infant mortality showed that newborns with spina bifida born to underweight or obese mothers had poorer chances of survival than newborns of mothers with normal weight [29]. However, our study does not demonstrate a statistically significant association between obese women and congenital anomalies in their babies. This could be because this study looks at congenital anomalies as a whole and not any specific anomaly leading to a lack of power in detecting this association.

Based on results from observational studies looking at associations between GWG and preterm birth, small and large for gestational age at birth, CD, postpartum weight retention, and childhood obesity, the US Institute of Medicine (IOM) published revised recommended gestational weight gain ranges in 2009. These ranges are 12.5–18 kg, 11.5–16 kg, 7–11.5 kg, and 5–9 kg for underweight, normal weight and obese women, respectively [30].

Our results show that a significant proportion (nearly 70 %) of women in the underweight category did not achieve the expected weight gain. A 2021 study conducted in India showed a 44 % higher risk for LBW in women gaining below the expected GWG [31]. This could explain the higher incidence of LBW noted in our study in the underweight group. Only 22 % of class-III women gained more than expected GWG in our cohort; however, this group still had the highest incidence of GDM, GHT, and CD. In addition, studies investigating the influence of GWG on the health of newborns among class-III women report a higher incidence of admission to NICU [32], which is similar to the results in our study regardless of the GWG in that group. This emphasizes the importance of adequate preconception weight and nutrition management, as the BMI at conception appears to have a more considerable impact on the outcomes than the GWG alone.

According to Vesco et al., gaining below IOM recommendations protected against large for gestational age babies but increased the risk for SGA [33]. Similarly, the study by Bloomberg in 2011 found that class-III women faced a higher likelihood of SGA when losing weight while having more favourable maternal outcomes [34]. However, more than half of the class-III in our study gained more than the recommended weight during their pregnancy; hence the outcomes in this group contrast with the studies mentioned.

The overall findings of our study highlight the importance of addressing abnormal BMI in pregnant women, as it can have significant implications for maternal and neonatal health. Additionally, these results suggest that interventions to prevent and manage abnormal BMI in women of reproductive age may positively impact maternal and neonatal outcomes. The findings of this study can help change clinical practice, such as improving preconception counselling starting from an early age and setting up dedicated antenatal abnormal BMI clinics to manage pregnancies with abnormally high or low maternal BMI. This is particularly important given the increasing rates of obesity in Qatar and globally. Further interventional studies can prove the impact of these interventions on perinatal outcomes.

Strengths and limitations

To our knowledge, this is the first study in Qatar and the Middle East region to examine each distinct category of BMI, including the underweight group and pregnancy outcomes. One of the study’s key strengths is standardized classifications which makes it possible to make valid comparisons with other studies and include these results in meta-analyses. In addition, the women in the study represent the pregnant population in Qatar, as more than 80 % of deliveries in the country occurs at the study site. Qatar has a heterogenous population consisting of women from nearly 100 different nationalities, which differs from more homogenous populations in other countries. Therefore, results from this local study will be much more relevant to inform changes in clinical practice in Qatar.

This study has the advantage of using registry data extracted meticulously by trained data collectors. Missing data, if present, were<1 % of the total number and therefore did not affect the analysis or interpretation. The large numbers make the study well-powered to detect important differences in the chosen outcomes. There was an apriori consideration of possible confounders, and adjusted models were used to determine associations, excluding variables in the causal pathway. This gives more strength and credibility to the associations noted.

However, some limitations must be considered while interpreting the results. The study results apply to only women satisfying the inclusion criteria. Pregnancies less than 24 weeks, with multiple pregnancies and those complicated by intrauterine fetal death, were excluded, leading to a small underestimation of the prevalence of outcomes such as GDM, GHT, and CDs. Misclassification of the exposure groups is possible due to human error in entering the height and weight in the medical records-however, this is unlikely to vary according to any outcome. Many women choose not to perform a glucose tolerance test and hence might not be diagnosed-this is more likely in women in the underweight or normal BMI groups leading to an underestimation of the incidence of GDM in these groups. Finally, residual confounding is still a concern as there is significant heterogeneity in the pregnant population of Qatar and various socioeconomic factors impacting pregnancy outcomes that are difficult to adjust for.

Conclusions

In conclusion, this study highlights the need for healthcare providers to be aware of potential risks associated with abnormal BMI. Belonging to the overweight or obesity categories during pregnancy negatively influenced maternal and neonatal outcomes with a rising risk as BMI increases. Since obesity is becoming more common among women of reproductive age, it is expected that the burden of maternal obesity will increase further in the future. Therefore, it is crucial to utilize resources wisely when planning antenatal care for women with abnormal BMI to minimize perinatal complications and undue burden on healthcare.

Corresponding author: Dr. Fathima Minisha, MBBS, MRCOG, MSc, Department of Obstetrics and Gynecology, Women’s Wellness and Research Centre, Hamad Medical Corporation, P.O. Box 3050, Doha, Qatar, E-mail:

Acknowledgments

We would like to acknowledge the members of the PEARL Peristat registry group (Dr. Tawa Oluwade, Dr. Mai AlQubaisi, Dr. Sawsan Al Obaidly, Dr. Husam Salam, and the data collection team) for providing us with a high-quality dataset for this study.

  1. Research ethics: The local Institutional Review Board deemed the study exempt from review.

  2. Informed consent: Not applicable.

  3. Author contributions: Authors TF, SAQ, NAD, and HAR conceptualized the study. FM, TW, and GL were involved in data accrual and processing. FM, TF, and NAD were involved in data analysis and presentation; GL and FM prepared the initial draft of the manuscript. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Competing interests: The authors state no competing interest.

  5. Research funding: None declared.

References

1. Sirimi, N, Goulis, DG. Obesity in pregnancy. Hormones 2010;4:299–306. https://doi.org/10.14310/horm.2002.1280.Search in Google Scholar PubMed

2. World Health organization. Obesity and overweight [Internet]. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight [Accessed 22 Nov 2022].Search in Google Scholar

3. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet 2017;390:2627–42. https://doi.org/10.1016/S0140-6736(17)32129-3.Search in Google Scholar PubMed PubMed Central

4. Nimptsch, K, Konigorski, S, Pischon, T. Diagnosis of obesity and use of obesity biomarkers in science and clinical medicine. Metabolism 2019;92:61–70. https://doi.org/10.1016/j.metabol.2018.12.006.Search in Google Scholar PubMed

5. Chu, SY. The epidemiology of obesity in pregnancy. In: Pregnancy in the obese woman: clinical management. New Jersey, USA: Wiley- Blackwell Publishing Ltd.; 2011:1–14 pp.10.1002/9781444391183.ch1Search in Google Scholar

6. Shahrir, NF, Abdul Jalil, RR, Jeganathan, JR, Devi Karalasingam, S, Mohd Nordin, N, Abdullah, MF, et al.. Maternal obesity and its associated factors and outcomes in klang valley, Malaysia: findings from national obstetric registry. Malays Fam Physician 2021;16:56. https://doi.org/10.51866/OA1138.Search in Google Scholar PubMed PubMed Central

7. Ayensu, J, Annan, RA, Edusei, A, Badu, E. Impact of maternal weight on pregnancy outcomes: a systematic review. Nutr Food Sci 2016;46:542–56. https://doi.org/10.1108/nfs-11-2015-0146.Search in Google Scholar

8. Sunder, A, Varghese, B, Darwish, B, Shaikho, NM, AlSada, A, Albuainain, H, et al.. Maternal obesity: an obstetric risk. Cureus 2022;14:e29345. https://doi.org/10.7759/CUREUS.29345.Search in Google Scholar

9. Triunfo, S, Lanzon, A. Impact of maternal under nutrition on obstetric outcomes. J Endocrinol Invest 2015;38:31–8. https://doi.org/10.1007/s40618-014-0168-4.Search in Google Scholar PubMed

10. Domanski, G, Lange, AE, Ittermann, T, Fallenberg, J, Allenberg, H, Zygmunt, M, et al.. Maternal pre-pregnancy underweight as a risk factor for the offspring: survey of Neonates in Pomerania. Acta Paediatr 2021;110:1452–60. https://doi.org/10.1111/APA.15701.Search in Google Scholar PubMed

11. Salihu, HM, Garcia, BY, Dongarwar, D, Maiyegun, SO, Yusuf, KK, Agili, DEA. Maternal pre-pregnancy underweight and the risk of small-for-gestational-age in Asian-American ethnic groups. Obstet Gynecol Sci 2021;64:496–505. https://doi.org/10.5468/OGS.21243.Search in Google Scholar PubMed PubMed Central

12. Burnie, R, Golob, E, Clarke, S. Pregnancy in underweight women: implications, management and outcomes. Obstet Gynaecol 2022;24:50–7. https://doi.org/10.1111/tog.12792.Search in Google Scholar

13. Bashir, T, Abdul Hasseb, M, Sharif, M. Obesity epidemic in the middle east, an overview of how Qatar is dealing with it. Jordan: Multi-Knowledge Electronic Comprehensive Journal for Education and Science Publications; 2020.Search in Google Scholar

14. Brown, MA, Lindheimer, MD, de Swiet, M, van Assche, A, Moutquin, JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the international society for the study of hypertension in pregnancy (ISSHP). Hypertens Pregnancy;20:ix–xiv. https://doi.org/10.3109/10641950109152635.Search in Google Scholar

15. Saleh, HA, Shurbak, ZS, Maducolil, MK, Selmy, OI, Bakri, S, Abdalla, H, et al.. Incidence and determinants of massive post partum haemorrhage: a two year retrospective review from a multiethnic population. EC Gynaecol 2019;8:205–14.Search in Google Scholar

16. Frey, HA, Klebanoff, MA. The epidemiology, etiology, and costs of preterm birth. Semin Fetal Neonatal Med 2016;21:68–73. https://doi.org/10.1016/j.siny.2015.12.011.Search in Google Scholar PubMed

17. Xi, C, Luo, M, Wang, T, Wang, Y, Wang, S, Guo, L, et al.. Association between maternal lifestyle factors and low birth weight in preterm and term births: a case-control study. Reprod Health 2020;17:1–9. https://doi.org/10.1186/S12978-020-00932-9/TABLES/4.Search in Google Scholar

18. Akanmode, AM, Macrosomia, MH. StatPearls. Treasure Island, FL: StatPearls Publishing [Internet]. 2023. https://www.ncbi.nlm.nih.gov/books/NBK557577/ [Accessed 6 Sep 2022].Search in Google Scholar

19. Institute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines, Rasmussen, KM, Yaktine, AL, editors. Weight gain during pregnancy: reexamining the guidelines. US: National Academies Press; 2009.Search in Google Scholar

20. StataCorp. Stata statistical software: release. College Station, TX: StataCorp LLC; 2019, vol 16.Search in Google Scholar

21. Scott-Pillai, R, Spence, D, Cardwell, CR, Hunter, A, Holmes, VA. The impact of body mass index on maternal and neonatal outcomes: a retrospective study in a UK obstetric population, 2004–2011. BJOG 2013;120:932–9. https://doi.org/10.1111/1471-0528.12193.Search in Google Scholar PubMed

22. Kazemian, E, Sotoudeh, G, Dorosty-Motlagh, AR, Eshraghian, MR, Bagheri, M. Maternal obesity and energy intake as risk factors of pregnancy-induced hypertension among Iranian women. J Health Popul Nutr 2014;32:486. https://doi.org/10.4172/2167-0420.1000116.Search in Google Scholar

23. Dietz, PM, Callaghan, WM, Morrow, B, Cogswell, ME. Population-based assessment of the risk of primary cesarean delivery due to excess pre-pregnancy weight among nulliparous women delivering term infants. Matern Child Health J 2005;9:237–44. https://doi.org/10.1007/S10995-005-0003-9/METRICS.Search in Google Scholar

24. Gaudet, L, Ferraro, ZM, Wen, SW, Walker, M. Maternal obesity and occurrence of fetal macrosomia: a systematic review and meta-analysis. BioMed Res Int 2014;2014:640291. https://doi.org/10.1155/2014/640291.Search in Google Scholar PubMed PubMed Central

25. Verma, A, Shrimali, L. Maternal body mass index and pregnancy outcome. J Clin Diagn Res: J Clin Diagn Res 2012;6:1531–3. https://doi.org/10.7860/JCDR/2012/4508.2551.Search in Google Scholar PubMed PubMed Central

26. Group on Behalf of the KS, Han, Z, Mulla, S, Liao, G, McDonald, SD. Maternal underweight and the risk of preterm birth and low birth weight: a systematic review and meta-analyses. Int J Epidemiol 2011;40:65–101. https://doi.org/10.1093/IJE/DYQ195.Search in Google Scholar PubMed

27. Mezzasalma, L, Santoro, M, Coi, A, Pierini, A. Association between maternal body mass index and congenital anomalies: a case-control study in Tuscany (Italy). Birth Defects Res 2022;114:116–23. https://doi.org/10.1002/bdr2.1970.Search in Google Scholar PubMed

28. Wu, L, Li, N, Liu, Y. Association between maternal factors and risk of congenital heart disease in offspring: a systematic review and meta-analysis. Matern Child Health J 2022;27:29–48. https://doi.org/10.1007/s10995-022-03538-8.Search in Google Scholar PubMed PubMed Central

29. Pace, ND, Siega‐Riz, AM, Olshan, AF, Chescheir, NC, Cole, SR, Desrosiers, TA, et al.. Survival of infants with spina bifida and the role of maternal pre-pregnancy body mass index. Birth Defects Res 2019;111:1205–16. https://doi.org/10.1002/bdr2.1552.Search in Google Scholar PubMed PubMed Central

30. Santos, S, Eekhout, I, Voerman, E, Gaillard, R, Barros, H, Charles, MA, et al.. Gestational weight gain charts for different body mass index groups for women in Europe, North America, and Oceania. BMC Med 2018;16:201. https://doi.org/10.1186/s12916-018-1189-1.Search in Google Scholar PubMed PubMed Central

31. Chowdhury, RN, Choudhary, TS, Dhabhai, N, Mittal, P, Dewan, R, Kaur, et al.. Gestational weight gain and pregnancy outcomes: findings from North Indian pregnancy cohort. Matern Child Nutr 2021;18:e13238. https://doi.org/10.1111/mcn.13238.Search in Google Scholar

32. Njagu, R, Adkins, LM, Tucker, A, Gatta, L, Brown, HL, Reiff, E, et al.. Maternal weight gain and neonatal outcomes in women with class III obesity. J Matern Fetal Neonatal Med 2020;35:546–50. https://doi.org/10.1080/14767058.2020.1729116.Search in Google Scholar PubMed

33. Vesco, KK, Sharma, AJ, Dietz, PM, Rizzo, JH, Callaghan, WM, England, L, et al.. Newborn size among obese women with weight gain outside the 2009 Institute of Medicine Recommendation. Obstet Gynecol 2011;117:812–18. https://doi.org/10.1097/aog.0b013e3182113ae4.Search in Google Scholar

34. Blomberg, M. Maternal and neonatal outcomes among obese women with weight gain below the new Institute of Medicine Recommendations. Obstet Gynecol 2011;117:1065–70. https://doi.org/10.1097/aog.0b013e318214f1d1.Search in Google Scholar
Received: 2023-05-09
Accepted: 2023-07-21
Published Online: 2023-08-24
Published in Print: 2023-11-27

© 2023 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Obituary
  3. A tribute to Professor Moshe Mazor, M.D.
  4. Mini Review
  5. Systematic review of the long-term effects of postnatal corticosteroids
  6. Opinion Paper
  7. The proposal of the novel fetal shoulder dystocia graduation: a clinical-based opinion
  8. Corner of Academy
  9. Prenatal diagnosis of bilobate placenta: incidence, risk factors and impact on pregnancy outcomes
  10. Original Articles – Obstetrics
  11. High mobility group box 1 in women with unexplained recurrent pregnancy loss
  12. Velamentous cord insertion in monochorionic twin pregnancies: a step forward in screening for twin to twin transfusion syndrome and birthweight discordance?
  13. Advanced maternal age (AMA) and 75 g oGTT glucose levels are pedictors for insulin therapy in women with gestational diabetes (GDM)
  14. Perinatal, obstetric and parental risk factors for asthma in the offspring throughout childhood: a longitudinal cohort study
  15. Increased risk of severe COVID-19 in pregnancy in a multicenter propensity score-matched study
  16. Comparative clinical and placental pathologic characteristics in pregnancies with and without SARS-CoV-2 infection
  17. An analysis of factors affecting survival in prenatally diagnosed omphalocele
  18. The impact of abnormal maternal body mass index during pregnancy on perinatal outcomes: a registry-based study from Qatar
  19. Original Articles – Fetus
  20. Embryonic and fetal tiny pericardial fluid collections at less than 12 weeks of gestation
  21. Modeling fetal cortical development by quantile regression for gestational age and head circumference: a prospective cross sectional study
  22. The effect of 50 GR oral glucose tolerance test on fetal celiac artery and superior mesenteric artery Doppler parameters in healthy pregnancies
  23. Original Articles – Neonates
  24. Carboxyhaemoglobin levels in infants with hypoxic ischaemic encephalopathy
  25. Exploring professionals’ views regarding prenatal counselling in congenital diaphragmatic hernia
  26. Letter to the Editor
  27. Cutting of the strangulated double nuchal umbilical cord in a release of the severe shoulder dystocia: forensically justified or controversial procedure
  28. Retraction
  29. Retraction of: Pre-operative tranexemic acid vs. etamsylate in reducing blood loss during elective cesarean section: randomized controlled trial
  30. Retraction of: Lidocaine vs. tramadol vs. placebo wound infiltration for post-cesarean section pain relief: a randomized controlled trial
https://doi.org/10.1515/jpm-2023-0198
Keywords for this article
adverse perinatal outcomes; gestational weight gain; maternal BMI; obesity
Creative Commons
BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Obituary
  3. A tribute to Professor Moshe Mazor, M.D.
  4. Mini Review
  5. Systematic review of the long-term effects of postnatal corticosteroids
  6. Opinion Paper
  7. The proposal of the novel fetal shoulder dystocia graduation: a clinical-based opinion
  8. Corner of Academy
  9. Prenatal diagnosis of bilobate placenta: incidence, risk factors and impact on pregnancy outcomes
  10. Original Articles – Obstetrics
  11. High mobility group box 1 in women with unexplained recurrent pregnancy loss
  12. Velamentous cord insertion in monochorionic twin pregnancies: a step forward in screening for twin to twin transfusion syndrome and birthweight discordance?
  13. Advanced maternal age (AMA) and 75 g oGTT glucose levels are pedictors for insulin therapy in women with gestational diabetes (GDM)
  14. Perinatal, obstetric and parental risk factors for asthma in the offspring throughout childhood: a longitudinal cohort study
  15. Increased risk of severe COVID-19 in pregnancy in a multicenter propensity score-matched study
  16. Comparative clinical and placental pathologic characteristics in pregnancies with and without SARS-CoV-2 infection
  17. An analysis of factors affecting survival in prenatally diagnosed omphalocele
  18. The impact of abnormal maternal body mass index during pregnancy on perinatal outcomes: a registry-based study from Qatar
  19. Original Articles – Fetus
  20. Embryonic and fetal tiny pericardial fluid collections at less than 12 weeks of gestation
  21. Modeling fetal cortical development by quantile regression for gestational age and head circumference: a prospective cross sectional study
  22. The effect of 50 GR oral glucose tolerance test on fetal celiac artery and superior mesenteric artery Doppler parameters in healthy pregnancies
  23. Original Articles – Neonates
  24. Carboxyhaemoglobin levels in infants with hypoxic ischaemic encephalopathy
  25. Exploring professionals’ views regarding prenatal counselling in congenital diaphragmatic hernia
  26. Letter to the Editor
  27. Cutting of the strangulated double nuchal umbilical cord in a release of the severe shoulder dystocia: forensically justified or controversial procedure
  28. Retraction
  29. Retraction of: Pre-operative tranexemic acid vs. etamsylate in reducing blood loss during elective cesarean section: randomized controlled trial
  30. Retraction of: Lidocaine vs. tramadol vs. placebo wound infiltration for post-cesarean section pain relief: a randomized controlled trial
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 25.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/jpm-2023-0198/html
Scroll to top button