Skip to main content
NCBI home page
Frontiers in Endocrinology logoLink to Frontiers in Endocrinology
. 2024 Jun 4;15:1280692. doi: 10.3389/fendo.2024.1280692

Influence of maternal body mass index on pregnancy complications and outcomes: a systematic review and meta-analysis

Yi Zhang 1,2,†, Mei Lu 1,2,†, Ying Yi 3,†, Luming Xia 4, Renjun Zhang 5, Chao Li 6,*, Ping Liu 6,*
PMCID: PMC11183281  PMID: 38894748

Abstract

Background

The prevalence of obesity among women of reproductive age is increasing worldwide, with implications for serious pregnancy complications.

Methods

Following PRISMA guidelines, a systematic search was conducted in both Chinese and English databases up to December 30, 2020. Pregnancy complications and outcomes including gestational diabetes mellitus (GDM), gestational hypertension (GHTN), pre-eclampsia, cesarean section (CS), induction of labor (IOL), and postpartum hemorrhage (PPH) were analyzed. Random-effects or fixed-effects models were utilized to calculate the odds ratio (OR) with 95% confidence intervals (CIs).

Results

Women with overweight and obesity issues exhibited significantly higher risks of GDM (OR, 2.92, 95%CI, 2.18-2.40 and 3.46, 95%CI, 3.05-3.94, respectively) and GHTN (OR, 2.08, 95%CI, 1.72-2.53 and 3.36, 95%CI, 2.81-4.00, respectively) compared to women of normal weight. Pre-eclampsia was also significantly higher in women with overweight or obesity, with ORs of 1.70 (95%CI, 1.44-2.01) and 2.82 (95%CI, 2.66-3.00), respectively. Additionally, mothers with overweight or obesity issues had significantly higher risks of CS (OR, 1.44, 95%CI, 1.41-1.47, and 2.23, 95%CI, 2.08-2.40), IOL (OR, 1.33, 95%CI, 1.30-1.35 and 1.96, 95%CI, 1.85-2.07), and PPH (OR, 1.67, 95%CI, 1.42-1.96 and 1.88, 95%CI, 1.55-2.29).

Conclusion

Women with overweight or obesity issues face increased risks of pregnancy complications and adverse outcomes, indicating dose-dependent effects.

Keywords: maternal, body mass index, obesity, pregnancy outcomes, complications

Introduction

The prevalence of obesity is skyrocketing across the globe. According to a study on the Global Burden of Disease, the proportion of adults with a body mass index (BMI) of 25 or greater surged from approximately 29% to 37% in men and from around 30% to 38% in women between 1980 and 2013. Additionally, in 2013, 22.6% of girls in developed countries and 13.4% of girls in developing countries were classified as overweight or obesity (1).

Nowadays, the prevalence of obesity among women of reproductive age is on the rise globally (2). In most developed countries, over half of women of reproductive age are classified as overweight (BMI 25-29.9 kg/m2) or obesity (≧30 kg/m2) (3). It has been estimated that 23.9% of any pregnancy complication was attributable to maternal overweight/obesity (4). M Maternal obesity is associated with a myriad of adverse perinatal outcomes (5), including large for gestational age, macrosomia, preterm birth, and stillbirth (6), Additionally, it can impact delivery outcomes (7), such as cesarean section (CS), induction of labor (IOL), and shoulder dystocia (8), as well as contribute to various pregnancy complications (9), like miscarriage, gestational diabetes mellitus (GDM) (10), etc.

Numerous original studies have extensively examined the impacts of pre-pregnancy BMI on maternal health outcomes (11, 12), Numerous original studies have extensively examined the impacts of pre-pregnancy BMI on maternal health outcomes (13–16). However, these reviews primarily focused on English and French publications and used a limited number of studies to analyze various complications, including maternal, fetal, and neonatal adverse outcomes. Notably, many studies on Chinese women have been published in reputable domestic journals in Chinese (17–19). These studies and their findings may contribute to differences in the relationship between maternal BMI and pregnancy outcomes compared to previous studies. Given the existing literature landscape and the desire for a more focused analysis, this article exclusively examines the relationship between BMI and maternal outcomes. This approach is taken because our previous research has already summarized the relationship between BMI and neonatal or fetal outcomes (5), concentrating solely on maternal outcomes aims to ensure the analysis and discussion are more comprehensive in this paper. Therefore, we conducted a systematic review and meta-analysis to investigate the relationship between maternal pre-pregnancy BMI and the risk of pregnancy complications and outcomes. The pregnancy complications and outcomes evaluated in this meta-analysis include GDM, GHTN, pre-eclampsia, CS, IOL, and PPH.

Materials and methods

Search strategy

The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed for conducting the systematic search. The search encompassed various databases from their earliest available dates up to December 30, 2020. Chinese databases, including China National Knowledge Infrastructure (CNKI), Wiper database (VIP), China Biomedical Literature Database (CBM), and Wanfang database (WF), were searched, along with English databases such as PubMed, Embase, and ISI. The search strategy involved identifying relevant literature using the following terms: (“BMI” or “Body Mass Index” or “obesity” or “overweight” or “underweight” or “Quetelet index”) AND (“pregnancy complications” or “outcomes”). Additionally, efforts were made to include unpublished studies to mitigate publication bias.

Study eligibility

Studies were considered eligible for inclusion in this meta-analysis if they met the following criteria: (1) The study type was observational, including cross-sectional, case-control, or cohort designs. (2) Participants were women, with a measured BMI in the first trimester of pregnancy or at their first antenatal visit. (3) Complete baseline maternal clinical information and pertinent outcome data were available. (4) Participants were singleton pregnant with no pre-existing medical disorders before conception. (5) Studies provided the number of women in each BMI category and reported the occurrence of related adverse outcomes. (6) Exposure groups consisted of women classified as underweight, overweight, or obesity, while the control group comprised women of normal weight. (7) The outcomes of interest were adverse pregnancy complications, which encompassed gestational diabetes mellitus [GDM, defined based on a 75g 2-hour oral glucose tolerance test conducted in the second trimester of pregnancy], gestational hypertension [GHTN, also known as pregnancy-induced hypertension, PIH, defined as diastolic blood pressure ≥90 mm Hg or systolic blood pressure ≥140 mm Hg in the second or third trimester among mothers who had normal blood pressure before pregnancy], and pre-eclampsia [defined as blood pressure ≥140/90 mmHg accompanied by proteinuria], as well as delivery complications, including cesarean section [CS, encompassing both elective and emergency deliveries], induction of labor[IOL, involving the administration of inducing drugs such as prostaglandins or oxytocin to expedite delivery], and post-partum hemorrhage [PPH, defined as blood loss exceeding 500mL within 24 hours after delivery].

Studies were excluded if they involved women with incomplete information on height or weight, or if they did not report any outcomes relevant to the scope of this meta-analysis.

Data extraction and quality assessment

The following information was extracted from each study: author name, country of population, year of publication, study design, the number of women categorized into different BMI levels, pregnancy outcomes, and their occurrence. Data extraction was performed independently by two authors to ensure accuracy, and any inconsistencies were resolved through consensus or consultation with other authors.

The quality assessment of case-control or cohort studies was conducted using the 9-star Newcastle-Ottawa Scale, while the quality of cross-sectional studies was evaluated using the 11-point scale from the Agency for Healthcare Research and Quality (AHRQ). Each study is based on predefined standards, with a score of ≥7 out of 9 or 9 out of 11 indicating high quality. Studies scoring 5-6 out of 9 or 7-8 out of 11 were classified as medium quality, while those with scores <5 out of 9 or <7 out of 11 were considered low quality. Only studies rated as medium or high quality were included in the analysis. The quality assessment was conducted independently by two authors, with any disagreements resolved through consensus.

Statistical analysis

BMI, also known as the Quetelet index, is defined as (weight in kilograms)/(height in meters)2 (20). It has become a universally accepted measure of the degree of overweight or obesity. The World Health Organization (WHO) and the National Institute of Health (NIH) have defined three cutoff points (18.5 kg/m2, 25.0 kg/m2, 30.0 kg/m2), which classify individuals into four groups: underweight, normal weight, overweight and obesity (21).

For this meta-analysis, BMI levels were categorized into these four groups, with normal weight serving as the reference group. The risk of pregnancy complications for individuals in other BMI categories was assessed using odds ratios (OR) with 95% confidence intervals (CIs).

Heterogeneity among studies was assessed using standard chi-square tests and I2 values, with tests carried out in Stata. A random-effects model (REM) was employed in the presence of heterogeneity (I2 >50%), while the fixed-effect model (FEM) was utilized otherwise. Sensitivity analysis was conducted to examine potential sources of heterogeneity. Additionally, meta-regression was conducted to identify the sources of the heterogeneity. The funnel plot and Egger’s regression asymmetry test were used to assess the potential publication bias.

Data analysis was conducted using Stata version 11.0 (Stata Corporation, College Station, TX, USA) software. All p-values were two-tailed, and p-value < 0.05 was considered statistically significant.

Results

Search results

Initially, 865 articles were identified regarding the association between maternal BMI and pregnancy complications. Of these, 441 were found in Chinese databases and 424 in English databases. After excluding 260 duplicated articles, 605 records remained. Subsequently, 285 articles were selected for full-text review after removing 320 pieces based on screening of titles and abstracts. Eventually, 83 studies met all general criteria and were included in the quantitative analysis. A flow diagram illustrating the selection process is provided in Figure 1 .

Figure 1.

Figure 1

Open in a new tab

Flow diagram of selecting articles for inclusion.

Characteristics of included studies

These 83 studies, encompassing 1,966,026 women, were published between 1998 and 2019, with sample sizes ranging from 100 to 621,221. The majority of studies were carried out in Asia (n = 53) [China (n = 42), India (n = 5), Korea (n = 2), United Arab Emirates (n = 2), Iran (n = 1), Israel (n = 1)]. Additionally, 16 studies were conducted in Europe [UK (n=6), Denmark (n = 3), Turkey (n=2), Finland (n = 1), Ireland (n = 1), Italy (n = 1), Spain (n = 1), Sweden (n = 1)]. Eight studies were conducted in North America [USA (n=8)], three in Africa [Cameroon (n=1), Nigeria (n=1), Sudan (n=1)], and three in Oceania [Australia (n=3)]. The primary information regarding these studies is summarized in Table 1 .

Table 1.

Information of articles included in analysis of association between maternal BMI and pregnancy complications.

Study Country Study Design* Underweight Normal Overweight Obese Quality Score
Ogunyemi D 1998 (20) USA C 78 223 78 203 8
Kumari AS 2000 (21) United Arab Emirates RC – 300 – 188 8
Michlin R 2000 (22) Israel CC – 167 – 167 7
Sebire NJ 2001 (23) UK RC – 176923 79014 31276 8
Kaufman H 2001 (24) USA RC 6135 11886 4189 2221 9
Baeten JM 2001 (25) USA RC 18988 50425 17571 9817 9
Yajun Yuan 2003 (26) China RC 545 549 – 544 6
Cedergren MI 2004 (27) Sweden PC – 535900 – 85321 9
Li Ping 2004 (28) China PC 158 152 23 – 7
Liu Xuejun 2004 (29) China C 28 159 76 17 7
Kristensen J 2005 (30) Denmark PC 1812 19169 2573 951 8
Caihong Luo 2005 (31) China RC 271 541 – 308 6
Raatikainen K 2006 (32) Finland PC – 20333 3388 1880 8
Roman H 2007 (33) USA PC – 2081 – 2081 9
Smith GC 2007 (34) UK C 17968 95516 50214 23592 9
Fu B 2007 (35) China RC 63 256 97 34 6
Han Aihong 2007 (36) China PC 61 654 262 105 7
Bhattacharya S 2007 (37) UK RC 2842 14076 5308 2015 8
Driul L 2008 (38) Italy RC 230 533 102 51 8
Zheng Min 2008 (39) China RC 97 482 181 79 8
Leung TY 2008 (40) China RC 2629 22041 3956 677 7
Joy S 2009 (41) USA RC – 9171 – 3744 9
Khashan AS 2009 (42) Ireland C 2581 45463 25476 16203 9
Schrauwers C 2009 (43) Australia RC – 100 100 170 9
Hoff GL 2009 (44) USA RC – 125 568 342 6
Knight M 2010 (45) UK C – 634 – 659 9
Mantakas A 2010 (46) UK RC 737 3102 1727 1048 8
Aydin C 2010 (47) Turkey RC – 5685 2214 1213 8
Athukorala C 2010 (48) Australia RC – 943 446 272 7
Xuemei Li 2010 (49) China PC 258 1245 394 – 6
Park JH 2011 (50) Korea RC 385 1387 539 – 9
Juanhua Tang 2011 (51) China PC 52 682 – 66 7
Qiaoying Liu 2011 (52) China RC – 340 – 40 6
Bailing Jiang 2011 (53) China RC 67 258 85 – 8
Xuemin Liu 2011 (54) China RC 579 3200 926 342 7
Joshi S 2011 (55) India C – 838 251 111 8
Rayis DA 2011 (56) Sudan CS – 654 597 323 7
Han YS 2011 (57) Korea C 111 363 67 67 9
Green C 2011 (58) Australia RC – 179 – 45 9
Ezeanochie MC 2011 (59) Nigeria CC – 201 – 201 8
Mandal D 2011 (60) India PC – 422 – 422 8
Ovesen P 2011 (61) Denmark RC 15776 233160 77250 43161 9
Situ Wenbei 2011 (62) China C – 140 100 40 8
Meenakshi 2012 (63) India PC – 45 87 83 8
Verma A 2012 (64) India PC 116 406 165 97 9
Halloran DR 2012 (65) USA RC – 11308 2388 1425 7
Sebastian 2012 (66) Spain RC 168 2597 – 251 8
Jing Xu 2012 (67) China RC 247 1452 202 63 7
Jie Chen 2012 (68) China RC 64 352 121 78 6
Guohua Meng 2012 (69) China RC 157 541 – 60 6
Zhenyu Cai 2012 (70) China PC 309 1319 259 70 7
Yazdani S 2012 (71) Iran RC 128 412 356 104 7
Jain D 2012 (72) India CS 10 188 102 – 7
Xiaofeng Xu 2012 (73) China C 66 364 116 54 8
Magann EF 2013 (74) USA PC 276 1965 1072 1177 9
Oteng-Ntim E 2013 (75) UK C 967 10101 4349 2227 8
Yundi Liu 2013 (76) China RC 31 189 – 76 6
Vaswani PR 2013 (77) United Arab Emirates RC – 420 635 930 8
Qingping Zhao 2013 (78) China RC – 50 – 50 6
Jin Tong 2013 (79) China RC 445 1685 – 279 7
Nan Li 2013 (80) China PC 3809 21942 6185 2037 9
Kai Shi 2013 (81) China RC – 35 31 60 6
Lulu Chen 2014 (82) China PC 56 170 – 24 6
Jian Jin 2014 (17) China RC 56 157 – 43 6
Gesche J 2015 (83) Denmark RC – 455 – 231 9
Ding XX 2015 (84) China PC 2365 7240 – 646 9
Fouelifack FY 2015 (12) Cameroon RC 17 228 152 65 8
Lu Liu 2015 (18) China RC 250 1370 388 116 8
Rezi Wanguli 2016 (85) China RC 132 606 – 112 7
Haiyan Liu 2016 (86) China RC 188 509 – 58 7
Aiying Song 2017 (87) China RC 150 150 150 150 7
Jianling Tang 2017 (88) China RC 40 290 – 50 6
Aozheng Chen 2017 (89) China RC 42 795 135 28 7
Jingyuan Lv 2017 (90) China RC 108 521 113 38 8
Kansu-Celik H 2017 (11) Turkey PC – 261 – 80 8
Xiuhui Qu 2018 (91) China RC 49 526 211 84 7
Yinchun Liu 2018 (92) China RC 49 391 – 75 6
Chenxiang Du 2018 (93) China RC 75 254 69 30 7
Yuqiao Yang 2019 (94) China RC 210 628 – 362 7
Huying Zhao 2019 (95) China RC 174 – 196 79 6
Lili Wang 2019 (96) China RC 395 901 – 773 7
Jinghua Li 2019 (19) China PC 1119 1128 120 27 8
Zhao RF 2019 (97) China RC 1687 8123 1149 177 9
Open in a new tab

*PC, Prospective cohort; RC, Retrospective cohort; C, Cohort; CC, Case-Control; CS, Cross-sectional.

Among the 83 studies, 63 involved CS, 58 involved GDM, 34 involved GHTN, 38 involved PPH, 27 involved pre-eclampsia, and 19 involved IOL. These studies were utilized to assess the risk of pregnancy complications at different BMI levels. The number of studies and individuals involved is presented in Table 2 .

Table 2.

The number of articles and individuals of each complication involved in this meta-analysis.

Complication No. Under VS Normal Over VS Normal Obesity VS Normal
No. Under +/- Normal +/- No. Over +/- Normal +/- No. Obesity +/- Normal +/-
GDM 58 36 942/30669 7339/298064 29 3644/98773 4873/231082 37 2193/13475 4360/59583
GHTN 34 19 542/8973 3644/36594 15 2204/9342 4572/35850 23 1640/6836 4982/47253
Pre-eclampsia 27 15 744/41155 10235/363066 15 929/22923 1658/62375 15 2025/29799 3477/152086
CS 63 40 9899/37362 44509/117059 31 17029/51141 33096/138224 50 15659/30012 52265/147678
IOL 19 6 961/3437 5710/17894 12 18788/72728 35420/175808 19 22997/104899 78225/683427
PPH 38 24 680/8417 5370/40500 21 1661/11550 4271/38161 30 9669/75427 39104/425626
Open in a new tab

No, number of studies; GD, gestational diabetes mellitus; GHTN, gestational hypertension; PPH, post-partum haemorrhage; CS, cesarean section including emergent CS and selective CS; IOL, Induction of labor.

Methodological quality

Eighty-one cohort or case-control studies were assessed using the NOS scale and obtained an average score of 7.58 ± 1.05 ( Table 1 ). Among these, 65 were classified as high-quality studies, while 16 were categorized as medium-quality studies. Additionally, two cross-sectional studies were assessed using the AHRQ scale and were deemed of medium quality, each receiving 7 points.

Maternal pre-pregnancy BMI and the risk of pregnancy complications

Women with overweight and obesity exhibited a significantly higher risk of GDM (OR, 2.92, 95%CI, 218-2.40 and 3.46, 95%CI, 3.05-3.94, respectively, as shown in Figures 2 , 3 ) and GHTN (OR, 2.08, 95%CI, 1.72-2.53 and 3.36, 95%CI, 2.81-4.00, respectively) compared to women of normal weight. Conversely, when women were underweight, these risks were lower (GDM: OR, 0.63, 95%CI, 0.54-0.73, as depicted in Figure 4 ; GHTN: OR, 0.64, 95%CI, 0.58-0.71). Pre-eclampsia, a complication of GHTN, was significantly more prevalent in women with overweight and obesity, with ORs of 1.70 (95%CI, 1.44-2.01) and 2.82 (95%CI, 2.66-3.00). On the other hand, pre-eclampsia was significantly lower in women classified as underweight, with an OR of 0.69 (95%CI, 0.64-0.75).

Figure 2.

Figure 2

Open in a new tab

Gestational diabetes mellitus forest plot for overweight compared with normal weight.

Figure 3.

Figure 3

Open in a new tab

Gestational diabetes mellitus forest plot for obesity compared with normal weight.

Figure 4.

Figure 4

Open in a new tab

Gestational diabetes mellitus forest plot for under weight compared with normal weight.

Analyzing the mode of delivery in mothers with overweight and obesity revealed a significantly higher risk of CS (OR, 1.44, 95%CI, 1.41-1.47, as depicted in Figure 5 , and 2.23, 95%CI, 2.08-2.40) and IOL (OR, 1.33, 95%CI, 1.30-1.35 and 1.96, 95%CI, 1.85-2.07), respectively. In contrast, mothers classified as underweight had a significantly lower risk of CS (OR, 0.75, 95%CI, 0.73-0.77). Women with overweight and obesity had higher odds of PPH (OR, 1.67, 95%CI, 1.42-1.96 and 1.88, 95%CI, 1.55-2.29) while being underweight was associated with lower odds (0.67, 95%CI, 0.62-0.73). The ORs, heterogeneity, and selected pooling models are presented in Table 3 .

Figure 5.

Figure 5

Open in a new tab

Cesarean section forest plot for overweight compared with normal weight.

Table 3.

The associations between maternal pre-pregnancy BMI and pregnancy complications and outcomes.

Outcome Under VS Normal Over VS Normal Obesity VS Normal
I2 (%) Models OR (95%CI) I2 (%) Models OR (95%CI) I2 (%) Models OR (95%CI)
GDM 55.5 REM 0.63(0.54-0.73) 30.6 FEM 2.92(2.18-2.40) 56.2 REM 3.46(3.05-3.94)
GHTN 39.9 FEM 0.64(0.58-0.71) 77.7 REM 2.08(1.71-2.53) 71.0 REM 3.36(2.81-4.00)
Pre-eclampsia 30.8 FEM 0.69(0.64-0.75) 56.6 REM 1.70(1.44-2.01) 39.4 FEM 2.82(2.66-3.00)
CS 29.4 FEM 0.75(0.73-0.77) 28.9 FEM 1.44(1.41-1.47) 72.5 REM 2.23(2.08-2.40)
IOL 54.3 REM 0.94(0.79-1.11) 1.9 FEM 1.33(1.30-1.35) 66.0 REM 1.96(1.85-2.07)
PPH 31.5 FEM 0.67(0.62-0.73) 56.9 REM 1.67(1.42-1.96) 95.2 REM 1.88(1.55-2.29)
Open in a new tab

The bold values represent the confidence intervals, which exclude 1, indicating statistical significance.

Sensitivity analysis

Sensitivity analyses were performed following the summary effect of each of the six outcomes, particularly when significant heterogeneities (I2 > 50%) were observed. In such cases, influential studies were identified and excluded to reassess the combined effect. For example, in the analysis comparing women who were overweight versus those with normal weight in the CS variable, the original I2 value was greater than 76.4%. After removing three articles, the value dropped to 28.9%. The results of sensitivity analyses are shown in Figure 6A . As indicated in Table 3 , the majority of results exhibited low or moderate heterogeneity, except for the comparison of obesity versus normal in PPH. For this outcome, sensitivity analyses were illustrated in Figure 6B .

Figure 6.

Figure 6

Open in a new tab

Sensitivity analyses: (A) overweight versus normal weight of cesarean section, (B) obesity versus normal weight of postpartum haemorrhage.

Sub-group analysis and meta-regression

Due to the high heterogeneity observed in PPH among mothers with obesity, we conducted subgroup and meta-regression analyses to explore the source of this heterogeneity. Among the 30 studies included in the analysis, 16 were conducted in China, and 22 were conducted in Asia. Therefore, we performed subgroup analyses and meta-regression using the country and continent of study to assess their potential contributions to the observed heterogeneity in the studies.

The subgroup analysis revealed that the risk of PPH was lower among mothers with obesity in China (OR, 1.77, 95% CI, 1.32-2.36, with I2 = 44.4%) compared to other countries (OR, 1.97, 95% CI, 1.51-2.56, with I2 = 97.8%) ( Figure 7 ). When stratified by continent of study, mothers with obesity had a higher risk of PPH in Asia (OR, 1.92, 95% CI, 1.40-2.62, with I2 = 63.8%) compared to non-Asia regions (OR, 1.86, 95% CI, 1.38-2.50, with I2 = 98.7%) ( Figure 8 ). Although the heterogeneity was lower in the China or Asia subgroup analyses by countries or continent, respectively, the OR value of the Asian group was greater than that of China. This difference may be attributed to one study conducted in India among the six articles in Asia but not in China, with a reported OR value of 7.06 (55), thereby elevating the overall OR value in Asia. Meta-regression analysis indicated that neither the country nor the continent of study was the source of heterogeneity, with p-values of 0.502 and 0.416, respectively. It is plausible that other factors such as the age and parity of pregnant women, sample size, season of pregnancy, or environmental factors may contribute to the observed significant heterogeneity.

Figure 7.

Figure 7

Open in a new tab

Sub-group analysis (China VS non-China) of Postpartum haemorrhage for overweight compared with normal weight.

Figure 8.

Figure 8

Open in a new tab

Sub-group analysis (Asia VS non-Asia) of Postpartum haemorrhage for overweight compared with normal weight.

Despite all studies being observational, among them there are two case-control studies and two cross-sectional studies, we attempted to perform subgroup analysis based on the study design. Results indicate that for the CS outcome, the OR values of case-control or cross-sectional studies have slightly decreased compared to the previous total results, yet the 95% confidence interval has significantly widened. Conversely, for cohort studies, there is minimal difference between the results and the total results. Due to the limited number of articles by case-control and cross-sectional study designs for other outcomes, subgroup analysis was not conducted.

Publication bias evaluation

The funnel plots and Egger’s test results indicated no significant publication bias (P > 0.05) across the 18 results of the six pregnancy outcomes. A funnel plot for CS, which encompassed the largest number of studies, is provided in Figure 9 .

Figure 9.

Figure 9

Open in a new tab

The funnel plots for cesarean section: (A) underweight versus normal weight, (B) overweight versus normal weight, and (C) obese versus normal weight.

Discussion

Main findings

This study provided a quantitative estimation of the risk of adverse pregnancy complications among mothers with varying BMI levels. It was found that mothers who were diagnosed as overweight or obesity faced a significantly higher risk of pregnancy complications, including GDM, GHTN, and pre-eclampsia. Additionally, they were at a heightened risk of adverse pregnancy outcomes such as CS, IOL, and PPH. Moreover, a dose-dependent relationship was observed, indicating an increased risk as the BMI levels rose.

Strengths and limitations

While previous systematic reviews and meta-analyses have explored the association between maternal body mass index and maternal health outcomes (13–16), each has its unique approach and findings. Three reviews among them only included 49 (13), 22 (14) and 13 (15) studies, respectively, a limited number in the quantitative synthesis. Furthermore, they all focused on the impact of maternal pre-pregnancy body mass index on maternal, fetal, and neonatal adverse outcomes, which results in less relevant literature on maternal outcomes. For example, the meta-analysis published in 2008 (13), which included 49 articles, only focused on hemorrhage and infection outcomes of pregnant women, with 3-4 studies. In another meta-analysis published in 2019 (15), only five and seven articles were used to analyze the relationship between gestational diabetes, gestational hypertension, and maternal pre-pregnancy BMI. The most extensive review to date, published in 2021 (16), included 86 studies and evaluated the relationship between maternal, fetal, and neonatal adverse outcomes and maternal pre-pregnancy body mass index, a broader range of outcomes. However, while examining almost the same number of studies, our review offers a distinct perspective by including a more diverse range of studies. Particularly, we included more articles from Asia, Africa, Europe, and North America providing a more comprehensive understanding of the global landscape of maternal health outcomes related to BMI. Thus, our findings complement existing literature and offer valuable insights into the worldwide situation.

Our study employed rigorous methodology, conducting comprehensive literature searches and applying stringent inclusion criteria, resulting in the inclusion of 83 articles for quantitative synthesis. The quality of included studies was assessed using the NOS tool for 81 cohort or case-control studies and ARHQ for cross-sectional studies, ensuring methodological robustness. Notably, our analysis revealed medium to low levels of heterogeneity between studies, and the relatively narrow confidence intervals further strengthened the reliability of our findings. These methodological strengths enabled us to draw firm conclusions from our meta-analysis.

There are several limitations to acknowledge in this meta-analysis. Firstly, the majority of included studies relied on pre-pregnancy BMI, with only a small portion using first-trimester BMI. While this discrepancy could potentially impact our meta-analysis results, previous stratified analyses have suggested that the difference may not be statistically significant (14). Secondly, our analysis focused solely on the association between maternal pre-pregnancy BMI and pregnancy outcomes, overlooking the effect of gestational weight gain (GWG). Given that approximately half of reproductive-age women have overweight or obesity issues and are at higher risk of substantial weight gain during pregnancy, the omission of GWG could be a limitation. Indeed, studies have shown that excessive GWG is associated with an increased risk of GHTN, PPH, and CS compared to women with normal weight gain (98). Several recently published meta-analyses (99) have focused on the association between GWG and maternal and infant outcomes. Combining these findings with our results could provide a more comprehensive understanding of the factors influencing pregnancy outcomes. Thirdly, the lack of detailed parity or age data across BMI groups in most studies may introduce bias into the pooled risk estimates. However, many included studies accounted for parity or age imbalances among BMI groups through adjustments during data analysis, mitigating potential biases to some extent. Fourthly, the outcome of CS encompassed both emergent and selective CS, with unclear distinctions provided in many included articles. Considering previous studies indicating that pregnant women with obesity or overweight have a higher likelihood of choosing selective CS over emergent CS (15), this ambiguity could affect our findings. Lastly, despite we have conducted subgroup analyses on certain factors regarding the outcomes of PPH or CS, the absence of subgroup analyses based on regions, study design types, or relevant environmental factors related to other outcomes of interest may constrain the generalizability of our results.

Interpretation

In our paper, pregnant women with overweight and obesity faced an increased risk of developing GDM, with ORs 2.20 (95% CI, 2.02-2.39) and 3.46 (95% CI, 3.05-3.94), respectively. These findings presented narrower confidence intervals compared to a previous meta-analysis based on the PubMed database and 20 articles conducted in 2007 (10), where the ORs were reported as 2.14 (95% CI, 1.82-2.53) and 3.56 (95% CI, 3.05-4.21). Markedly, our meta-analysis, including 58 studies on GDM, demonstrated low to medium between-study heterogeneities (I 2 = 54.3%, 33.4%, 56.2%), contributing to the narrowed 95% CI of the ORs. Additionally, research has indicated (100) that the cumulative incidence of type 2 diabetes increased significantly in the first 5 years postpartum due to elevated fasting glucose levels during pregnancy. Therefore, targeting pregnant mothers with elevated glucose levels may represent a more effective approach to diabetes prevention.

In our analysis of 34 studies, it was evident that mothers with overweight and obesity faced an elevated risk of GHTN. While an earlier study suggested that obesity might not independently contribute to pregnancy-induced hypertensive disorders (101), our findings underscored the disparities in GHTN risks across various BMI levels, potentially attributed to higher booking blood pressure among women with obesity (102). Controlling appropriate pre-pregnancy weight could be a preventive measure for GHTN, highlighting the importance of further research to elucidate its underlying mechanisms.

An evident dose-dependent effect was observed concerning maternal pre-pregnancy BMI and the likelihood of delivery by CS. Women with overweight and obesity have a higher propensity to opt for CS (containing emergent CS and selective CS) or IOL, a finding consistent with several previous meta-analyses (16, 103). The heightened risk of CS in women with higher BMI may be attributed to various factors. Firstly, increased BMI could contribute to labor induction failure (104), a potentially leading to CS instead of IOL (103). Moreover, factors such as fetal macrosomia, labor dystocia due to increased pelvic soft tissue, and other complications might further predispose women with higher BMI to CS (61). Furthermore, considering other adverse pregnancy complications like gestational hypertension, gestational diabetes, and fetal complications such as stillbirth or admission to the neonatal intensive care unit (6), these factors could contribute to the increased CS rate observed in women with obesity.

In contrast to women with overweight and obesity, those classified as underweight exhibited a protective effect against GDM, GHTN, pre-eclampsia, CS, and PPH. However, it’s important to note that being underweight during pregnancy may carry its own set of risks, such as an increased likelihood of preterm birth and delivering an SGA or LBW baby (5). Therefore, it is imperative to establish appropriate clinical guidelines and implement public health interventions aimed at managing the weight of pregnant women, whether they are classified as obesity or underweight, in order to safeguard the health of both mothers and their babies.

Conclusion

Our analysis provides a quantitative estimation of the detrimental effects of pre-pregnancy overweight and obesity on maternal complications and delivery outcomes. Future studies should strive to explore more effective strategies to mitigate the growing threat of overweight and obesity among pregnant women.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.

Author contributions

YZ: Writing – original draft, Funding acquisition, Conceptualization, Resources. ML: Writing – original draft, Data curation, Software, Visualization. YY: Writing – original draft, Software, Formal analysis. LX: Writing – review & editing. RZ: Writing – review & editing. CL: Writing – review & editing, Supervision. PL: Writing – original draft, Conceptualization.

Funding Statement

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was funded by Guizhou Science and Technology Plan Project (QKHJC-ZK[2023]-Key057, QKHZC[2021]-Normal163, and QKHZC[2020]-1Y037), Special project of new academic seedling cultivation and innovation exploration of Zunyi Medical University (Guizhou science cooperation platform talents [2018]5772–070), Scientific Research Program of Guizhou Provincial Department of Education (QJJ [2023] 019) and Science & Technology Program of Guizhou Province (QKHPTRC-CXTD[2022]014).

Abbreviations

BMI, body mass index; GDM, gestational diabetes mellitus; GHTN, gestational hypertension; CS, cesarean section; IOL, induction of labor; PPH, postpartum hemorrhage.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fendo.2024.1280692/full#supplementary-material

Table_1.docx (31.1KB, docx)

References

  • 1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. (2014) 384:766–81. doi:  10.1016/s0140-6736(14)60460-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Poston L, Caleyachetty R, Cnattingius S, Corvalán C, Uauy R, Herring S, et al. Preconceptional and maternal obesity: epidemiology and health consequences. Lancet Diabetes Endocrinol. (2016) 4:1025–36. doi:  10.1016/s2213-8587(16)30217-0 [DOI] [PubMed] [Google Scholar]
  • 3. Kaplan SA. Re: National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. J Urol. (2011) 186:1982–3. doi:  10.1016/j.juro.2011.07.061 [DOI] [PubMed] [Google Scholar]
  • 4. Santos S, Voerman E, Amiano P, Barros H, Beilin LJ, Bergström A, et al. Impact of maternal body mass index and gestational weight gain on pregnancy complications: an individual participant data meta-analysis of European, North American and Australian cohorts. Bjog. (2019) 126:984–95. doi:  10.1111/1471-0528.15661 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Liu P, Xu L, Wang Y, Zhang Y, Du Y, Sun Y, et al. Association between perinatal outcomes and maternal pre-pregnancy body mass index. Obes Rev. (2016) 17:1091–102. doi:  10.1111/obr.12455 [DOI] [PubMed] [Google Scholar]
  • 6. Aune D, Saugstad OD, Henriksen T, Tonstad S. Maternal body mass index and the risk of fetal death, stillbirth, and infant death: a systematic review and meta-analysis. Jama. (2014) 311:1536–46. doi:  10.1001/jama.2014.2269 [DOI] [PubMed] [Google Scholar]
  • 7. Ellis JA, Brown CM, Barger B, Carlson NS. Influence of maternal obesity on labor induction: A systematic review and meta-analysis. J Midwifery Womens Health. (2019) 64:55–67. doi:  10.1111/jmwh.12935 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Ramachenderan J, Bradford J, McLean M. Maternal obesity and pregnancy complications: a review. Aust N Z J Obstet Gynaecol. (2008) 48:228–35. doi:  10.1111/j.1479-828X.2008.00860.x [DOI] [PubMed] [Google Scholar]
  • 9. Lim CC, Mahmood T. Obesity in pregnancy. Best Pract Res Clin Obstet Gynaecol. (2015) 29:309–19. doi:  10.1016/j.bpobgyn.2014.10.008 [DOI] [PubMed] [Google Scholar]
  • 10. Chu SY, Callaghan WM, Kim SY, Schmid CH, Lau J, England LJ, et al. Maternal obesity and risk of gestational diabetes mellitus. Diabetes Care. (2007) 30:2070–6. doi:  10.2337/dc06-2559a [DOI] [PubMed] [Google Scholar]
  • 11. Kansu-Celik H, Kisa Karakaya B, Guzel AI, Tasci Y, Erkaya S. To evaluate the effect of pre-pregnancy body mass index on maternal and perinatal outcomes among adolescent pregnant women. J Matern Fetal Neonatal Med. (2017) 30:1574–8. doi:  10.1080/14767058.2016.1214122 [DOI] [PubMed] [Google Scholar]
  • 12. Fouelifack FY, Fouedjio JH, Fouogue JT, Sando Z, Fouelifa LD, Mbu RE. Associations of body mass index and gestational weight gain with term pregnancy outcomes in urban Cameroon: a retrospective cohort study in a tertiary hospital. BMC Res Notes. (2015) 8:806. doi:  10.1186/s13104-015-1765-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Heslehurst N, Simpson H, Ells LJ, Rankin J, Wilkinson J, Lang R, et al. The impact of maternal BMI status on pregnancy outcomes with immediate short-term obstetric resource implications: a meta-analysis. Obes Rev. (2008) 9:635–83. doi:  10.1111/j.1467-789X.2008.00511.x [DOI] [PubMed] [Google Scholar]
  • 14. Rahman MM, Abe SK, Kanda M, Narita S, Rahman MS, Bilano V, et al. Maternal body mass index and risk of birth and maternal health outcomes in low- and middle-income countries: a systematic review and meta-analysis. Obes Rev. (2015) 16:758–70. doi:  10.1111/obr.12293 [DOI] [PubMed] [Google Scholar]
  • 15. D'Souza R, Horyn I, Pavalagantharajah S, Zaffar N, Jacob CE. Maternal body mass index and pregnancy outcomes: a systematic review and metaanalysis. Am J Obstet Gynecol MFM. (2019) 1:100041. doi:  10.1016/j.ajogmf.2019.100041 [DOI] [PubMed] [Google Scholar]
  • 16. Vats H, Saxena R, Sachdeva MP, Walia GK, Gupta V. Impact of maternal pre-pregnancy body mass index on maternal, fetal and neonatal adverse outcomes in the worldwide populations: A systematic review and meta-analysis. Obes Res Clin Pract. (2021) 15:536–45. doi:  10.1016/j.orcp.2021.10.005 [DOI] [PubMed] [Google Scholar]
  • 17. Jin J. The relationship between preconceptional body mass index and gestational growth and maternal and infant outcomes (in Chinese). Chin J Women Children Health. (2014) 5:69–70. doi:  10.19757/j.cnki.issn1674-7763.2014.06.021 [DOI] [Google Scholar]
  • 18. Liu L, Hong ZX, Wang J, Ding BJ, Bi YX. Effects of pre-pregnancy BMI and peri-gestational weight gain on pregnancy outcomes (in Chinese). Chin J Woman Child Health Res. (2015) 26:1139–42. doi:  10.3969/j.issn.1673-5293.2015.06.011 [DOI] [Google Scholar]
  • 19. Li JH, Yang L, Chen Q, Liu J, He Y. A prospective cohort study on the effects of prepregnancy body mass index and gestational weight gain on pregnancy complications and pregnancy outcomes(in Chinese). Chin J Obstetrics Gynecol. (2019) 54:184–8. doi:  10.3760/cma.j.issn.0529-567x.2019.03.008 [DOI] [Google Scholar]
  • 20. Ogunyemi D, Hullett S, Leeper J, Risk A. Prepregnancy body mass index, weight gain during pregnancy, and perinatal outcome in a rural black population. J Matern Fetal Med. (1998) 7:190–3. doi:  10.1002/(sici)1520-6661(199807/08)7:4<190::Aid-mfm5>3.0.Co;2-d [DOI] [PubMed] [Google Scholar]
  • 21. Kumari AS. Pregnancy outcome in women with morbid obesity. Int J Gynaecol Obstet. (2001) 73:101–7. doi:  10.1016/s0020-7292(00)00391-x [DOI] [PubMed] [Google Scholar]
  • 22. Michlin R, Oettinger M, Odeh M, Khoury S, Ophir E, Barak M, et al. Maternal obesity and pregnancy outcome. Isr Med Assoc J. (2000) 2:10–3. [PubMed] [Google Scholar]
  • 23. Sebire NJ, Jolly M, Harris JP, Wadsworth J, Joffe M, Beard RW, et al. Maternal obesity and pregnancy outcome: a study of 287,213 pregnancies in London. Int J Obes Relat Metab Disord. (2001) 25:1175–82. doi:  10.1038/sj.ijo.0801670 [DOI] [PubMed] [Google Scholar]
  • 24. Kaufman HK, Jacques DL, Coleman SK. Ganzeier G Prepregnancy body mass index and pregnancy outcome. Obstetrics Gynecol. (2001) 97:S71. [Google Scholar]
  • 25. Baeten JM, Bukusi EA, Lambe M. Pregnancy complications and outcomes among overweight and obese nulliparous women. Am J Public Health. (2001) 91:436–40. doi:  10.2105/ajph.91.3.436 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Yuan YJ, Cao WQ, Wang JP, Yang XF, Huang M. Effects of body mass index on high-risk pregnancy and pregnancy outcome(in Chinese). Maternal Child Health Care China. (2003) 10):26–7. [Google Scholar]
  • 27. Cedergren MI. Maternal morbid obesity and the risk of adverse pregnancy outcome. Obstet Gynecol. (2004) 103:219–24. doi:  10.1097/01.Aog.0000107291.46159.00 [DOI] [PubMed] [Google Scholar]
  • 28. Li P, Luo LM, Wu QK. Relevance of body mass index with complication and outcome of pregnancy(in Chinese). Shanghai Med J. (2004) 11):840–2. doi:  10.3969/j.issn.0253-9934.2004.11.016 [DOI] [Google Scholar]
  • 29. Liu XJ, Zhang CX. The relationshops between the pregestational weight and the abnormal pregnancy result(in Chinese). J Shandong First Med Univ Shandong Acad Med Sci. (2004) 05):403–5. doi:  10.3969/j.issn.1004-7115.2004.05.009 [DOI] [Google Scholar]
  • 30. Kristensen J, Vestergaard M, Wisborg K, Kesmodel U, Secher NJ. Pre-pregnancy weight and the risk of stillbirth and neonatal death. Bjog. (2005) 112:403–8. doi:  10.1111/j.1471-0528.2005.00437.x [DOI] [PubMed] [Google Scholar]
  • 31. Luo CH. A probe into the relationship between abnormal boby mass index and outcome of pregnancy(in Chinese). Guangxi Med J. (2005) 09):1343–5. doi:  10.3969/j.issn.0253-4304.2005.09.018 [DOI] [Google Scholar]
  • 32. Raatikainen K, Heiskanen N, Heinonen S. Transition from overweight to obesity worsens pregnancy outcome in a BMI-dependent manner. Obes (Silver Spring). (2006) 14:165–71. doi:  10.1038/oby.2006.20 [DOI] [PubMed] [Google Scholar]
  • 33. Roman H, Robillard PY, Hulsey TC, Laffitte A, Kouteich K, Marpeau L, et al. Obstetrical and neonatal outcomes in obese women. West Indian Med J. (2007) 56:421–6. [PubMed] [Google Scholar]
  • 34. Smith GC, Shah I, Pell JP, Crossley JA, Dobbie R. Maternal obesity in early pregnancy and risk of spontaneous and elective preterm deliveries: a retrospective cohort study. Am J Public Health. (2007) 97:157–62. doi:  10.2105/ajph.2005.074294 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Fu B. A clinical research of effect of pre-pregnancy body mass index and maternal weight gain on pregnancy outcome(in Chinese). Maternal Child Health Care China. (2007) 08):1024–6. doi:  10.3969/j.issn.1001-4411.2007.08.017 [DOI] [Google Scholar]
  • 36. Han AH. The effect of prepregnancy body mass index and pregnancy weight gain on pregnancy outcome(in Chinese). Maternal Child Health Care China. (2007) 32):4534–5. doi:  10.3969/j.issn.1001-4411.2007.32.017 [DOI] [Google Scholar]
  • 37. Bhattacharya S, Campbell DM, Liston WA, Bhattacharya S. Effect of Body Mass Index on pregnancy outcomes in nulliparous women delivering singleton babies. BMC Public Health. (2007) 7:168. doi:  10.1186/1471-2458-7-168 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Driul L, Cacciaguerra G, Citossi A, Martina MD, Peressini L, Marchesoni D. Prepregnancy body mass index and adverse pregnancy outcomes. Arch Gynecol Obstet. (2008) 278:23–6. doi:  10.1007/s00404-007-0524-0 [DOI] [PubMed] [Google Scholar]
  • 39. Zheng M, Yao MY, Tan FM. The effect to before pregnancy body mass index on pregnancy outcome in nulliparous women(in Chinese). J Mudanjiang Med Univ. (2008) 29:27–30. doi:  10.13799/j.cnki.mdjyxyxb.2008.06.034 [DOI] [Google Scholar]
  • 40. Leung TY, Leung TN, Sahota DS, Chan OK, Chan LW, Fung TY, et al. Trends in maternal obesity and associated risks of adverse pregnancy outcomes in a population of Chinese women. Bjog. (2008) 115:1529–37. doi:  10.1111/j.1471-0528.2008.01931.x [DOI] [PubMed] [Google Scholar]
  • 41. Joy S, Istwan N, Rhea D, Desch C, Stanziano G. The impact of maternal obesity on the incidence of adverse pregnancy outcomes in high-risk term pregnancies. Am J Perinatol. (2009) 26:345–9. doi:  10.1055/s-0028-1110084 [DOI] [PubMed] [Google Scholar]
  • 42. Khashan AS, Kenny LC. The effects of maternal body mass index on pregnancy outcome. Eur J Epidemiol. (2009) 24:697–705. doi:  10.1007/s10654-009-9375-2 [DOI] [PubMed] [Google Scholar]
  • 43. Schrauwers C, Dekker G. Maternal and perinatal outcome in obese pregnant patients. J Matern Fetal Neonatal Med. (2009) 22:218–26. doi:  10.1080/14767050902801652 [DOI] [PubMed] [Google Scholar]
  • 44. Hoff GL, Cai J, Okah FA, Dew PC. Pre-pregnancy overweight status between successive pregnancies and pregnancy outcomes. J Womens Health (Larchmt). (2009) 18:1413–7. doi:  10.1089/jwh.2008.1290 [DOI] [PubMed] [Google Scholar]
  • 45. Knight M, Kurinczuk JJ, Spark P, Brocklehurst P. Extreme obesity in pregnancy in the United Kingdom. Obstet Gynecol. (2010) 115:989–97. doi:  10.1097/AOG.0b013e3181da8f09 [DOI] [PubMed] [Google Scholar]
  • 46. Mantakas A, Farrell T. The influence of increasing BMI in nulliparous women on pregnancy outcome. Eur J Obstet Gynecol Reprod Biol. (2010) 153:43–6. doi:  10.1016/j.ejogrb.2010.06.021 [DOI] [PubMed] [Google Scholar]
  • 47. Aydin C, Baloglu A, Yavuzcan A, Inci A. The effect of body mass index value during labor on pregnancy outcomes in Turkish population (obesity and pregnancy outcomes). Arch Gynecol Obstet. (2010) 281:49–54. doi:  10.1007/s00404-009-1060-x [DOI] [PubMed] [Google Scholar]
  • 48. Athukorala C, Rumbold AR, Willson KJ, Crowther CA. The risk of adverse pregnancy outcomes in women who are overweight or obese. BMC Pregnancy Childbirth. (2010) 10:56. doi:  10.1186/1471-2393-10-56 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Li XM. The effect of maternal body mass index and pregnancy weight gain on pregnancy outcome(in Chinese). Chin J Woman Child Health Res. (2010) 21:596–597,600. doi:  10.3969/j.issn.1673-5293.2010.05.0010 [DOI] [Google Scholar]
  • 50. Park JH, Lee BE, Park HS, Ha EH, Lee SW, Kim YJ. Association between pre-pregnancy body mass index and socioeconomic status and impact on pregnancy outcomes in Korea. J Obstet Gynaecol Res. (2011) 37:138–45. doi:  10.1111/j.1447-0756.2010.01332.x [DOI] [PubMed] [Google Scholar]
  • 51. Tang JH. The effect of body mass index on the pregnancy outcome of primiparas(in Chinese). Compr Clin Pract China. (2011) 27:1219–21. doi:  10.3760/cma.j.issn.1008-6315.2011.11.035 [DOI] [Google Scholar]
  • 52. Liu QY, Gan XH, Jiang H. The effect of pre-pregnancy body mass index (BMI) and pregnancy weight gain on pregnancy outcome(in Chinese). J Qiqihar Med Univ. (2011) 32:2094–5. doi:  10.3969/j.issn.1002-1256.2011.13.023 [DOI] [Google Scholar]
  • 53. Jiang BL. Study on the correlation between prepregnancy body mass index and pregnancy weight gain and pregnancy outcome. J Military Surgeon Southwest China. (2011) 13:668–9. doi:  10.3969/j.issn.1672-7193.2011.04.047 [DOI] [Google Scholar]
  • 54. Liu XM, Chen ZY, Wang GX, Wang W, Xi Q, Du J. Effects of pre-pregnancy BMI and increasing range of BMI during pregnancy on pregnancy outcome(in Chinese). Maternal Child Health Care China. (2010) 25:3084–7. [Google Scholar]
  • 55. Joshi S, Unni J, Vijay S, Khanijo V, Gupte N, Divate U. Obesity and pregnancy outcome in a private tertiary hospital in India. Int J Gynaecol Obstet. (2011) 114:82–3. doi:  10.1016/j.ijgo.2011.01.020 [DOI] [PubMed] [Google Scholar]
  • 56. Rayis DA, Abbaker AO, Salih Y, Adam I. Obesity and pregnancy outcome in Khartoum, Sudan. Int J Gynaecol Obstet. (2011) 113:160–1. doi:  10.1016/j.ijgo.2010.12.008 [DOI] [PubMed] [Google Scholar]
  • 57. Han YS, Ha EH, Park HS, Kim YJ, Lee SS. Relationships between pregnancy outcomes, biochemical markers and pre-pregnancy body mass index. Int J Obes (Lond). (2011) 35:570–7. doi:  10.1038/ijo.2010.162 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Green C, Shaker D. Impact of morbid obesity on the mode of delivery and obstetric outcome in nulliparous singleton pregnancy and the implications for rural maternity services. Aust N Z J Obstet Gynaecol. (2011) 51:172–4. doi:  10.1111/j.1479-828X.2010.01271.x [DOI] [PubMed] [Google Scholar]
  • 59. Ezeanochie MC, Ande AB, Olagbuji BN. Maternal obesity in early pregnancy and subsequent pregnancy outcome in a Nigerian population. Afr J Reprod Health. (2011) 15:55–9. [PubMed] [Google Scholar]
  • 60. Mandal D, Manda S, Rakshi A, Dey RP, Biswas SC, Banerjee A. Maternal obesity and pregnancy outcome: a prospective analysis. J Assoc Physicians India. (2011) 59:486–9. [PubMed] [Google Scholar]
  • 61. Ovesen P, Rasmussen S, Kesmodel U. Effect of prepregnancy maternal overweight and obesity on pregnancy outcome. Obstet Gynecol. (2011) 118:305–12. doi:  10.1097/AOG.0b013e3182245d49 [DOI] [PubMed] [Google Scholar]
  • 62. C. SW, Zhang YX, Wu YY, Xu YH. Clinical study of pregnancy and pregnancy outcome in women with simple obesity(in Chinese). J Med Inf. (2011) 24:5397–8. [Google Scholar]
  • 63. Meenakshi, Srivastava R, Sharma NR, Kushwaha KP, Aditya V. Obstetric behavior and pregnancy outcome in overweight and obese women: maternal and fetal complications and risks in relation to maternal overweight and obesity. J Obstet Gynaecol India. (2012) 62:276–80. doi:  10.1007/s13224-012-0215-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64. Verma A, Shrimali L. Maternal body mass index and pregnancy outcome. J Clin Diagn Res. (2012) 6:1531–3. doi:  10.7860/jcdr/2012/4508.2551 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65. Halloran DR, Marshall NE, Kunovich RM, Caughey AB. Obesity trends and perinatal outcomes in black and white teenagers. Am J Obstet Gynecol. (2012) 207:492.e1–7. doi:  10.1016/j.ajog.2012.09.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Sebastián Manzanares G, Angel Santalla H, Irene Vico Z, López Criado MS, Alicia Pineda L, José Luis Gallo V. Abnormal maternal body mass index and obstetric and neonatal outcome. J Matern Fetal Neonatal Med. (2012) 25:308–12. doi:  10.3109/14767058.2011.575905 [DOI] [PubMed] [Google Scholar]
  • 67. Xu J, Chen X, Wang Y. Influence of body mass index index increase in nulliparous women pregnancy outcome(in Chinese). Clin Focus. (2012) 27:1393–5. [Google Scholar]
  • 68. Chen J. Study on the relationship between maternal body mass index and adverse pregnancy outcome(in Chinese). J Hebei Med Univ. (2012) 33:948–9. doi:  10.3969/j.issn.1007-3205.2012.08.029 [DOI] [Google Scholar]
  • 69. Meng GH, Zhou L. Pre-pregnancy weight and weight gain during pregnancy have an influence on pregnancy outcome(in Chinese). Anhui Med Pharm J. (2012) 16:778–80. doi:  10.3969/j.issn.1009-6469.2012.06.025 [DOI] [Google Scholar]
  • 70. Cai ZY, Jia Z, Liang XJ. Relationship between prepregnancy body mass index, pregnancy weight gain and pregnancy outcome(in Chinese). J Aerospace Med. (2012) 23:952–4. doi:  10.3969/j.issn.2095-1434.2012.08.034 [DOI] [Google Scholar]
  • 71. Yazdani S, Yosofniyapasha Y, Nasab BH, Mojaveri MH, Bouzari Z. Effect of maternal body mass index on pregnancy outcome and newborn weight. BMC Res Notes. (2012) 5:34. doi:  10.1186/1756-0500-5-34 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72. Jain D, Khuteta R, Chaturvedi V, Khuteta S. Effect of body mass index on pregnancy outcomes in nulliparous women delivering singleton babies: observational study. J Obstet Gynaecol India. (2012) 62:429–31. doi:  10.1007/s13224-012-0225-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73. Wu XF. Relationship between weight before pregnancy, weight gain during pregnancy and pregnancy outcome(in Chinese). China Pract Med. (2012) 7:270–1. doi:  10.14163/j.cnki.11-5547/r.2012.15.183 [DOI] [Google Scholar]
  • 74. Magann EF, Doherty DA, Sandlin AT, Chauhan SP, Morrison JC. The effects of an increasing gradient of maternal obesity on pregnancy outcomes. Aust N Z J Obstet Gynaecol. (2013) 53:250–7. doi:  10.1111/ajo.12047 [DOI] [PubMed] [Google Scholar]
  • 75. Oteng-Ntim E, Kopeika J, Seed P, Wandiembe S, Doyle P. Impact of obesity on pregnancy outcome in different ethnic groups: calculating population attributable fractions. PloS One. (2013) 8:e53749. doi:  10.1371/journal.pone.0053749 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76. Liu YD. Relationship between BMI increase and pregnancy outcome in early pregnancy (in Chinese). J Qiqihar Med Coll. (2013) 34:49–50. doi:  10.3969/j.issn.1002-1256.2013.01.031 [DOI] [Google Scholar]
  • 77. Vaswani PR, Balachandran L. Pregnancy outcomes in a population with high prevalence of obesity: How bad is it? Clin Epidemiol Global Health. (2013) 1:5–11. doi:  10.1016/j.cegh.2012.11.006 [DOI] [Google Scholar]
  • 78. Zhao QP. Analysis of the influence of prepregnancy obesity and pregnancy weight gain on pregnancy outcome (in Chinese). China Health Industry. (2013) 10:171–2. doi:  10.16659/j.cnki.1672-5654.2013.19.094 [DOI] [Google Scholar]
  • 79. Tong J, Gu N, Li J, Xu CC, Yang L, Zhu ZH, et al. Effects of prepregnancy body mass index and pregnancy weight gain on pregnancy outcome(in Chinese). Chin J Perinatal Med. (2013) 16:561–5. doi:  10.3760/cma.j.issn.1007-9408.2013.09.014 [DOI] [Google Scholar]
  • 80. Li N, Liu E, Guo J, Pan L, Li B, Wang P, et al. Maternal prepregnancy body mass index and gestational weight gain on pregnancy outcomes. PloS One. (2013) 8:e82310. doi:  10.1371/journal.pone.0082310 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81. Shi K, Gu AW, Qiang JP. Effect of pre-pregnancy body mass index on pregnancy outcome(in Chinese). J Ningxia Med Univ. (2013) 35:1173–4. doi:  10.16050/j.cnki.issn1674-6309.2013.10.042 [DOI] [Google Scholar]
  • 82. Chen LL, Liu J, Kang Y, Liu J, He SF. Relationship between prepregnancy body mass index and pregnancy growth and maternal and neonatal outcome(in Chinese). Chongqing Med. (2014) 43:1178–80. doi:  10.3969/j.issn.1671-8348.2014.10.008 [DOI] [Google Scholar]
  • 83. Gesche J, Nilas L. Pregnancy outcome according to pre-pregnancy body mass index and gestational weight gain. Int J Gynaecol Obstet. (2015) 129:240–3. doi:  10.1016/j.ijgo.2014.12.013 [DOI] [PubMed] [Google Scholar]
  • 84. Ding XX, Xu SJ, Hao JH, Huang K, Su PY, Tao FB. Maternal pre-pregnancy BMI and adverse pregnancy outcomes among Chinese women: Results from the C-ABCS. J Obstet Gynaecol. (2016) 36:328–32. doi:  10.3109/01443615.2015.1050652 [DOI] [PubMed] [Google Scholar]
  • 85. Rezi Wanguli ADL, Rezia ABLT, Chen PP, Zhang SY, Li LX. Prepregnancy weight, pregnancy weight gain and the relationship between age and pregnancy outcome(in Chinese). Maternal Child Health Care China. (2016) 31:78–80. doi:  10.7620/zgfybj.j.issn.1001-4411.2016.01.32 [DOI] [Google Scholar]
  • 86. Liu HY, Cai YY, Xu K, Xu YJ, Zhou JM, Long FM, et al. Effect of pre-pregnancy BMI and gestational weight gain of primiparas on delivery way and pregnancy outcomes(in Chinese). J Guizhou Med Univ. (2016) 41:37–40+44. doi:  10.19367/j.cnki.1000-2707.2016.01.011 [DOI] [Google Scholar]
  • 87. Song AY. Maternal weight before and during pregnancy and its relationship with obstetric complications and pregnancy outcomes(in Chinese). Clin Res Pract. (2017) 2:124–5. doi:  10.19347/j.cnki.2096-1413.201723061 [DOI] [Google Scholar]
  • 88. Tang JL. Correlation analysis of pregnancy BMI and BMI increased during pregnancy and pregnancy outcome (in chinese). Electronic J Pract Gynecological Endocrinol (2017) 4(25):47–9. doi:  10.3969/j.issn.2095-8803.2017.25.027 [DOI] [Google Scholar]
  • 89. Chen AZ, Qin JL, Li Y, Zhao PY, Wang L, Cheng JJ. Impact of pre-pregnancy BMI on obstetric complications and pregnancy outcomes (in chinese). J Tongji University(Medical Science) (2017) 38(02):114–9. doi:  10.16118/j.1008-0392.2017.02.024 [DOI] [Google Scholar]
  • 90. Lv JY, Guan YQ. The clinical analysis for pre-pregnancy overweight, gestational hypertension and the outcome of maternal and child after pregnancy (in chinese). Heilongjiang Med Pharm (2017) 40(04):139–41. doi:  10.3969/j.issn.1008-0104.2017.04.065 [DOI] [Google Scholar]
  • 91. Qu XH. Study on the correlation between prepregnancy body mass index and pregnancy weight gain and pregnancy outcome (in Chinese). World Latest Med Inf (2018) 18(81):54–5. doi:  10.19613/j.cnki.1671-3141.2018.81.035 [DOI] [Google Scholar]
  • 92. Liu YC, Zhu LY, Huang YC, Ouyang LZ, Huang XL, Zhang Q. Effects of different pre pregnancy body mass index and maternal body mass changes on pregnancy outcomes (in chinese). Jilin Med J (2018) 39(03):423–5. doi:  10.3969/j.issn.1004-0412.2018.03.009 [DOI] [Google Scholar]
  • 93. Du CX, Liu H, Li QY, Zhang Y, Cchen M, Ru XC, et al. Impact of pre-pregnancy BMI and gestational weight gain on obstetric complications and pregnancy outcomes of hami uygur women (in Chinese). Int Med Health Guidance News (2018) 24(19):2948–51. doi:  10.3760/cma.j.issn.1007-1245.2018.19.0187- [DOI] [Google Scholar]
  • 94. Yang YQ, Dong XF. Effect of BMI and weight gain on complications and outcomes before pregnancy (in chinese). Xinjiang Med J (2019) 49(11):1101–4. [Google Scholar]
  • 95. Zhao HY, Pan SL, Liu YL, Zheng WT, Li DJ. Effects of pre-pregnancy overweight/obesity on obstetric outcomes and labor duration (in chinese). Prog Obstetrics Gynecology (2019) 28(06):416–9. doi:  10.13283/j.cnki.xdfckjz.2019.06.003 [DOI] [Google Scholar]
  • 96. Wang LL, Tian Y, Lu LP. Effects of pre-pregnancy body mass index and pregnancy weight gain on the incidence and pregnancy outcome of gestational diabetes mellitus (in chinese). Maternal Child Health Care China (2019) 34(01):62–4. doi:  10.7620/ZGFYBJ.J.ISSN.1001-4411.2019.01.21 [DOI] [Google Scholar]
  • 97. Zhao RF, Zhou L, Zhang WY. Identifying appropriate pre-pregnancy body mass index classification to improve pregnancy outcomes in women of childbearing age in beijing, china: a retrospective cohort study. Asia Pac J Clin Nutr (2019) 28(3):567–76. doi:  10.6133/apjcn.201909_28(3).0016 [DOI] [PubMed] [Google Scholar]
  • 98. Kominiarek MA, Saade G, Mele L, Bailit J, Reddy UM, Wapner RJ, et al. Association between gestational weight gain and perinatal outcomes. Obstet Gynecol (2018) 132(4):875–81. doi:  10.1097/aog.0000000000002854 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 99. Goldstein RF, Abell SK, Ranasinha S, Misso ML, Boyle JA, Harrison CL, et al. Gestational weight gain across continents and ethnicity: systematic review and meta-analysis of maternal and infant outcomes in more than one million women. BMC Med (2018) 16(1):153. doi:  10.1186/s12916-018-1128-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100. Kim C, Newton KM, Knopp RH. Gestational diabetes and the incidence of type 2 diabetes: a systematic review. Diabetes Care (2002) 25(10):1862–8. doi:  10.2337/diacare.25.10.1862 [DOI] [PubMed] [Google Scholar]
  • 101. van Hoorn J, Dekker G, Jeffries B. Gestational diabetes versus obesity as risk factors for pregnancy-induced hypertensive disorders and fetal macrosomia. Aust N Z J Obstet Gynaecol (2002) 42(1):29–34. doi:  10.1111/j.0004-8666.2002.00035.x [DOI] [PubMed] [Google Scholar]
  • 102. Ohkuchi A, Iwasaki R, Suzuki H, Hirashima C, Takahashi K, Usui R, et al. Normal and high-normal blood pressures, but not body mass index, are risk factors for the subsequent occurrence of both preeclampsia and gestational hypertension: a retrospective cohort study. Hypertens Res (2006) 29(3):161–7. doi:  10.1291/hypres.29.161 [DOI] [PubMed] [Google Scholar]
  • 103. Ray JG, Vermeulen MJ, Shapiro JL, Kenshole AB. Maternal and neonatal outcomes in pregestational and gestational diabetes mellitus, and the influence of maternal obesity and weight gain: the DEPOSIT study. Diabetes Endocrine Pregnancy Outcome Study Toronto. Qjm (2001) 94(7):347–56. doi:  10.1093/qjmed/94.7.347 [DOI] [PubMed] [Google Scholar]
  • 104. Wolfe KB, Rossi RA, Warshak CR. The effect of maternal obesity on the rate of failed induction of labor. Am J Obstet Gynecol (2011) 205(2):128.e1–7. doi:  10.1016/j.ajog.2011.03.051 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table_1.docx (31.1KB, docx)

Data Availability Statement

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.

Articles from Frontiers in Endocrinology are provided here courtesy of Frontiers Media SA

RESOURCES