Association between prepregnancy body mass index or gestational weight gain and adverse pregnancy outcomes among Chinese women with gestational diabetes mellitus: a systematic review and meta-analysis

Abstract

Objective

The association between prepregnancy body mass index (BMI) or gestational weight gain (GWG) and adverse pregnancy outcomes among Chinese women with gestational diabetes mellitus (GDM) is unknown. This study aims to evaluate such association by synthesising the evidence.

Design

Systematic review and meta-analysis.

Data sources

PubMed, Web of Science, Scopus, EMBASE, China Biology Medicine disc, China National Knowledge Infrastructure, Wangfang, and China Science and Technology Journal Database searched from inception to 11 August 2023.

Eligibility criteria

Prospective cohort studies, retrospective cohort studies and case–control studies estimating the relationship of abnormal prepregnancy BMI (including underweight, overweight or obesity) or inappropriate GWG (including excess GWG or insufficient GWG) with adverse pregnancy outcomes of interest were included. Outcomes included macrosomia, caesarean section, preterm birth, gestational hypertension, large for gestational age (LGA) and small for gestational age (SGA).

Data extraction and synthesis

Two reviewers independently selected studies, extracted the data and assessed the risk of bias. OR estimate and its 95% CI were pooled using Stata software fixed-effect model. Subgroup analysis, meta-regression and sensitivity analysis were performed to ensure credibility of the results.

Results

Twenty-three studies (eighteen retrospective cohort studies, three prospective cohort studies and two case control studies) involving 57 013 Chinese women with GDM were identified. Meta-analysis results showed that compared with GDM women with normal weight, GDM women with underweight were at a higher risk of SGA (OR=1.79 (1.54 to 2.07), five studies involving 31 967 women); women with overweight had higher risks of macrosomia (OR=1.65 (1.49 to 1.82), eleven studies involving 41 683 women), caesarean section (OR=1.48 (1.38 to 1.59), ten studies involving 34 935 women), preterm birth (OR=1.27 (1.13 to 1.43), eight studies involving 38 295 women) and LGA (OR=1.73 (1.54 to 1.95), seven studies involving 31 342 women) and women with obesity had higher risks of macrosomia (OR=2.37 (2.04 to 2.76), eleven studies involving 41 683 women), caesarean section (OR=2.07 (1.84 to 2.32), nine studies involving 34 829 women), preterm birth (OR=1.31 (1.09 to 1.57), eight studies involving 38 295 women) and LGA (OR=2.63 (2.15 to 3.21), six studies involving 31 236 women). Regard to GWG, compared with Chinese GDM women with sufficient GWG, GDM women with excessive GWG had higher risks of macrosomia (OR=1.74 (1.58 to 1.92), twelve studies involving 40 966 women), caesarean section (OR=1.44 (1.36 to 1.53), nine studies involving 36 205 women) and LGA (OR=2.12 (1.96 to 2.29), twelve studies involving 42 342 women); women with insufficient GWG conversely had higher risks of preterm birth (OR=1.59 (1.45 to 1.74), nine studies involving 37 461 women) and SGA (OR=1.38 (1.27 to 1.51), ten studies involving 41 080 women).

Conclusions

For Chinese women with GDM, abnormal prepregnancy BMI or inappropriate GWG were related to higher risks of many adverse pregnancy outcomes. Therefore, medical staff should pay more attention to the weight management of GDM women during pregnancy.

YZ and QZ are joint first authors.

Strengths and limitations of this study

• This systematic review and meta analysis comprehensively evaluated the association between prepregnancy body mass index (BMI) or gestational weight gain (GWG) and adverse pregnancy outcomes among Chinese women with gestational diabetes mellitus. And we found abnormal prepregnancy BMI or inappropriate GWG were related to higher risks of many adverse pregnancy outcomes.

• Limitation of this systematic review may be that subgroup analysis unable to determine some confounding factors that affect the validity of pool results. However, we preferred to pool the adjusted ORs to reduce bias.

Introduction

Gestational diabetes mellitus (GDM) is a common obstetric complication manifesting as any degree of hyperglycaemia that is first detected during pregnancy.¹ The prevalence of GDM varies at 13.97% to 14.04% in several countries² and is 14.8% in China.³ GDM is associated with increased risks of short-term adverse health outcomes including for macrosomia, hyperglycaemia, hyperbilirubinemia, caesarean section, gestational hypertension and preterm birth.^{4 5} Moreover, GDM are at higher risks of long-term health consequences, such as maternal type 2 diabetes in postpartum and childhood obesity.⁶ Therefore, a management strategy for GDM is needed.

Gestational weight gain (GWG) represents the amount of bodyweight change during pregnancy and is usually calculated by maternal weight before delivery minus prepregnancy weight.⁷ Weight management is an important aspect of modulating GDM.⁸ A systematic review showed that based on the National Academy of Medicine (NAM) recommendations, compared with GDM women with sufficient GWG, GDM women with excessive GWG was related to higher risks of macrosomia, large for gestational age (LGA), caesarean section and pharmacological treatment; however, GDM women with insufficient GWG had not higher risks of small for gestational age (SGA).⁹ NAM also recommended GWG guidelines which was according to the prepregnancy BMI classification method of WHO: underweight (BMI<18.5 kg/m²), normal weight (18.5 kg/m²≤BMI<25.0 kg/m²), overweight (25.0 kg/m²≤BMI<30.0 kg/m²) and obesity (BMI≥30.0 kg/m²).¹⁰ The WHO also developed BMI classification criteria for Asians: underweight (BMI<18.5 kg/m²), normal weight (18.5 kg/m²≤BMI<23.0 kg/m²), overweight (23.0 kg/m²≤BMI<27.5 kg/m²) and obesity (BMI≥27.5 kg/m²).¹⁰ However, the Working Group on Obesity in China (WGOC) has developed tailored BMI classification criteria for Chinese: underweight (BMI<18.5 kg/m²), normal weight (18.5 kg/m²≤BMI<24.0 kg/m²), overweight (24.0 kg/m²≤BMI<28.0 kg/m²) and obesity (BMI≥28.0 kg/m²).¹¹ For Chinese pregnant women, the chosen BMI classification methods would influence the contribution of prepregnancy BMI groups and consequently the selection of GWG range.

Previous systematic reviews verified the association between prepregnancy BMI and adverse pregnancy outcomes among Chinese women¹² and the relationship between GWG and perinatal outcomes among GDM women.⁹ To date, no comprehensive appraisals of the association between prepregnancy BMI or GWG and adverse pregnancy outcomes among Chinese women with GDM have been conducted. In this systematic review and meta-analysis, we aim to explore the relationship between prepregnancy BMI or GWG and adverse pregnancy outcomes among Chinese women with GDM. The findings of this study would provide the evidence for Chinese women with GDM to adopt positive weight management strategies.

Method

Eligibility criteria

The inclusion criteria were as following: (a) Population included Chinese women with GDM and a single pregnancy. (b) Exposure variables included at least one of the following: abnormal prepregnancy BMI (included underweight, overweight and obesity) and inappropriate GWG (excessive and insufficient GWG). Three BMI classification methods^{10 11} widely used in China were applied, namely, WHO general criteria, WHO criteria for Asians and WGOC criteria (see online supplemental table S1). For prepregnancy BMI, normal weight was set as the reference category in the original study. Meanwhile, GWG was classified into three groups: insufficient, sufficient and excessive GWG according to NAM recommendations (see online supplemental table S1). Sufficient GWG was set as the reference category in the original study. (c) Outcome variables included at least one of the following: primary outcomes included macrosomia (defined as a birthweight>4000 g), caesarean section (defined as the use of surgery for delivery by obstetricians) and preterm birth (defined as 28–37 gestational week).¹³ And secondary outcomes included gestational hypertension (defined as new-onset hypertension after the 20th gestational week in the absence of proteinuria or other findings suggestive of pre-eclampsia, with blood pressure≥140 mm Hg or diastolic blood pressure≥90 mm Hg at least two occasions),¹⁴ LGA (defined as weight greater than the 90th percentile for gestational age)¹⁵ and SGA (defined as weight less than the 10th percentile for gestational age).¹⁵ (d) Study design included cohort studies (prospective and retrospective cohort studies) and case–control studies. Locate relevant studies that focusing on Chinese women with GDM were included. The exclusion criteria were as following: (a) the related data cannot be accessed even after contacting with the original author and (b) the quality was rated as low when Newcastle-Ottawa Scale (NOS) scores of less than six points.

Information sources

Eight databases including PubMed, the core collection of Web of Science, Scopus, EMBASE, China Biology Medicine disc, China National Knowledge Infrastructure (CNKI), Wangfang and China Science and Technology Journal Database (VIP), were searched from inception to 11 August 2023 (searching time interval of each database, please see in online supplemental table S2). For PubMed, Embase and China Biology Medicine disc databases, a search strategy of Mesh-term combined with text-word was applied. Different combinations of the following terms were utilised: ‘body mass index’, ‘gestational weight gain’, ‘GWG’, ‘gestational diabetes mellitus’ and ‘pregnancy complications’ (detailed search strategies are reported in online supplemental table S2).

Study selection

All identified studies were imported to EndNote X9 (Thomson Scientific), and the duplicated studies were removed automatically and manually. Irrelevant studies were initially excluded by reading the title and abstract. A full-text review then performed for screening. Two researchers (YZ and YP) independently accessed citations for eligibility independently. Discrepancies were resolved through consensus or consulting with a third researcher (XJ) whenever necessary. The included studies were identified by naming ‘first author, publication year’ as study identity (study ID).

Data extraction

Multiple researchers (YZ, YP and QZ) jointly designed an Excel data extraction form. Two researchers (Y Z and YP) extracted the following information from the original studies: study ID, study design, study period, sample size, number of GWG above/within/below the NAM recommendations, BMI classification method, diagnostic criteria for GDM, involved outcomes, abnormal BMI or inappropriate GWG and their OR with 95% CI and NOS scores. In case of crude/adjusted ORs and fourfold table data coexisted, crude/adjusted ORs was extracted preferentially. For studies without ORs, fourfold table data were extracted and transferred to crude ORs (normal weight group was considered as a reference, then underweight group, overweight group and obesity group were estimated, respectively).

Assessment of risk of bias

Two researchers (YZ and YP) independently rated the quality of included studies independently using the NOS (https://www.ohri.ca/programs/clinical_epidemiology/nos_manual.pdf). For NOS, scores of 8–9 points, 6–7 points and <6 points indicated high, medium and low quality, respectively. Any disagreement regarding scores was resolved through discussion with a third researcher (XJ).

Synthesis of result

Statistical analysis was performed using Stata software (V.14.0; STATA, College Station, TX, USA), and data were plotted with GraphPad Prism (V.8.0). For studies without OR, fourfold table data were first transferred to crude OR and its 95% CI. All OR and 95% CI values were then transformed to pooled estimates using a fixed-effects model.^{16 17} The weight of each study was obtained based on its reliability (CI) in overall estimate. I² statistic was used to assess heterogeneity, in which >50% and ≤50% indicated high and low level heterogeneities, respectively. Subgroup analysis, meta-regression and sensitivity analysis were carried out to explore the source of heterogeneity when I²>50%. Subgroup analysis and meta-regression were performed using the following possible variables: study design (prospective cohort study, retrospective cohort study and case-control study), BMI classification method (WHO, WHO for Asian and WGOC) and diagnostic criteria for GDM (WHO, International Association of Diabetes and American Diabetes Association). Sensitivity analysis was performed by removing potential studies that may be the source of high heterogeneity. Additionally, potential publication bias was analysed by Egger’s test and Begg’s test.

Patient and public involvement

None

Result

Study selection and characteristics

Figure 1 showed the complete selection process. A total of 15 242 studies were retrieved. After title, abstract and full text reading, 23 studies were identified finally.^18–40 Among them, there were eighteen retrospective cohort studies, three prospective cohort studies and two case-control studies. Totally, 57 013 Chinese women with GDM were involved in this study. Thirteen studies were classified as high quality and ten studies were classified as moderate quality. All the studies were published from 2009 to 2022. The characteristics of the included studies are reported in table 1.

Figure 1. PRISMA flow chart of study selection. CNKI, China National Knowledge Infrastructure; PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses.

Table 1

The characteristics of included studies for the systematic review and meta-analysis

Study ID	Study design	Study period	Sample size	BMI classification method/diagnostic criteria for GDM	Number of GWG above/within/below the NAM recommendations*	Involved outcomes†	NOS score
Chen et al18 2015	Retrospective cohort study	2010–2012	1049	WHO BMI classification for Asian/IADPSG criteria	293/755/NA (there was one woman with missing data in the weight gain category)	(5)	8
Chen Xu and Coelho19 2022	Retrospective cohort study	2014–2018	13 467	WHO BMI classification criteria/IADPSG criteria	3850/4372/5245	(2) (3) (4) (5) (6)	8
Gou et al20 2019	Retrospective cohort study	2013–2016	1523	WHO BMI classification criteria/IADPSG criteria	484/588/451	(2) (3) (5) (6)	8
Huang et al21 2023	Case control study	2014–2022	1651	WHO BMI classification criteria/IADPSG criteria	346/632/673	(6)	8
Ke et al22 2023	Retrospective cohort study	2016	764	WGOC BMI classification criteria/IADPSG criteria	197/329/238	(2) (3) (5) (6)	8
Leng et al23 2015	Retrospective cohort study	2009–2011	1263	WGOC BMI classification criteria/WHO criteria	713/394/156	(5)	8
Miao et al24 2017	Retrospective cohort study	2013–2014	832	WGOC BMI classification criteria/IADPSG criteria	293/352//187	(2) (3) (5) (6)	7
Nie et al25 2016	Retrospective cohort study	2011	5010	WGOC BMI classification criteria/IADPSG criteria	NA	(3)	7
Shi et al26 2021	Retrospective cohort study	2010–2020	1606	WHO BMI classification criteria/IADPSG criteria	501/545/560	(2) (3) (4) (5) (6)	8
Sun et al27 2014	Retrospective cohort study	2010–2012	1418	WGOC BMI classification criteria/IADPSG criteria	NA	(2) (4)	6
Wang et al28 2018	Prospective cohort study	2014	601	WGOC BMI classification criteria/IADPSG criteria	222/267/112	(2) (5)	7
Wei et al29 2016	Prospective cohort study	2013	2868	WGOC BMI classification criteria/IADPSG criteria	NA	(2) (3)	6
Xu et al30 2021	Retrospective cohort study	2018–2019	2381	WHO BMI classification criteria/IADPSG criteria	610/1185/586	(3) (5) (6)	7
Yang et al31 2016	Prospective cohort study	2011–2012	106	WHO BMI classification criteria/ADA criteria	NA	(5) (6)	7
Zheng et al32 2022	Retrospective cohort study	2013–2018	14 578	WHO BMI classification criteria/IADPSG criteria	2495/6001/5082	(2) (3) (5) (6)	8
Chen et al33 2021	Case control study	2014–2018	1135	WGOC BMI classification criteria/IADPSG criteria	NA	(1)	7
Chen et al34 2021	Retrospective cohort study	2017–2018	2611	WHO BMI classification criteria/IADPSG criteria	462/1152/997	(3) (5) (6)	7
Dong35 2017	Retrospective cohort study	2015–2016	124	WHO BMI classification criteria/IADPSG criteria	NA	(2)	6
Lin et al36 2021	Retrospective cohort study	2018–2019	709	WGOC BMI classification criteria/IADPSG criteria	NA	(3) (5) (6)	8
Shen et al37 2023	Retrospective cohort study	2019–2021	1667	WHO BMI classification criteria/IADPSG criteria	219/566/882	(3) (5) (6)	8
Wang and Zhou38 2020	Retrospective cohort study	2014–2017	1641	WHO BMI classification criteria/IADPSG criteria	640/626/375	(2)	7
Xu et al39 2021	Retrospective cohort study	2017–2019	1237	WGOC BMI classification criteria/IADPSG criteria	NA	(2)	7
Yang et al40 2018	Retrospective cohort study	2015–2017	413	WGOC BMI classification criteria/IADPSG criteria	80/256/77	(2) (3)	7

*Above/within/below the NAM recommendations: IOM recommended that women who are underweight, overweight and obese should gain body weight 12.5–18, 11.5–16.0, 7.0–1.5 and 5.0–9.0 kg during pregnancy, respectively. Actual gestational weight gain above, within and below the recommendations were defined as ‘excessive weight gain’, ‘sufficient weight gain’ and ‘insufficient weight gain’, respectively.

†Included outcomes: (1) macrosomia; (2) caesarean section; (3) preterm birth; (4) gestational hypertension; (5) large for gestational age; (6) small for gestational age.

ADA, American Diabetes Association; BMI, body mass index; GDM, gestational diabetes mellitus; GWG, gestational weight gain; IADPSG, International Association of Diabetes and Pregnancy Study; NA, not available; NAM, National Academy of Medicine; NOS, Newcastle-Ottawa Scale; OGTT, oral glucose tolerance test; WGOC, Working Group on Obesity in China.

Association between maternal prepregnancy BMI and adverse pregnancy outcomes

Figure 2 shows that compared with Chinese GDM women with normal weight, GDM women with underweight had higher risk of SGA (OR=1.79 (1.54 to 2.07), p<0.001, I²=0%, 5 studies involving 31 967 women) and lower risks of macrosomia (OR=0.43 (0.34 to 0.54), p<0.001, I²=15.1%, 11 studies involving 25 611 women), caesarean section (OR=0.62 (0.57 to 0.67), p<0.001, I²=35.7%, 12 studies involving 39 615 women) and LGA (OR=0.40 (0.33 to 0.48), p<0.001, I²=13.0%, 7 studies involving 20 914 women). By contrary, compared with GDM women with normal weight, GDM women with overweight had higher risks of macrosomia (OR=1.65 (1.49 to 1.82), p<0.001, I²=39.4%, 11 studies involving 41 683 women), caesarean section (OR=1.48 (1.38 to 1.59), p<0.001, I²=64.4%, 10 studies involving 34 935 women), preterm birth (OR=1.27 (1.13 to 1.43), p<0.001, I²=0%, 8 studies involving 38 295 women), gestational hypertension (OR=1.81 (1.29 to 2.54), p=0.001, I²=50.7%, 2 studies involving 14 885 women) and LGA (OR=1.73 (1.54 to 1.95), p<0.001, I²=0%, 7 studies involving 31 342 women) and lower risk of SGA (OR=0.75 (0.64 to 0.88), p=0.001, I²=0%, 5 studies involving 29 692 women). Besides, GDM women with obesity also had similar results with the overweight one when they compared with GDM women with normal weight. Similarly, GDM women with obesity had higher risks of macrosomia (OR=2.37 (2.04 to 2.76), p<0.001, I²=27.7%, 11 studies involving 41 683 women), caesarean section (OR=2.07 (1.84 to 2.32), p<0.001, I²=8.3%, 9 studies involving 34 829 women), preterm birth (OR=1.31 (1.09 to 1.57), p=0.004, I²=29.3%, 8 studies involving 38 295 women), gestational hypertension (OR=3.32 (2.41 to 4.57), p<0.001, I²=73.6%, 2 studies involving 14 885 women) LGA (OR=2.63 (2.15 to 3.21), p<0.001, I²=0%, 6 studies involving 31 236 women) and lower risk of SGA (OR=0.64 (0.50 to 0.82), p<0.001, I²=0%, 4 studies involving 29 586 women).

Figure 2. Meta-analysis summary results forest plot for the association between prepregnancy BMI and adverse pregnancy outcomes. *Statistically significant. BMI, body mass index.

Association between maternal gestational weight gain and adverse pregnancy outcomes

Figure 3 shows that compared with Chinese GDM women with sufficient GWG, GDM women with excessive GWG had higher risks of macrosomia (OR=1.74 (1.58 to 1.92), p<0.001, I²=92.6%, 12 studies involving 40 966 women), caesarean section (OR=1.44 (1.36 to 1.53), p<0.001, I²=75.1%, 9 studies involving 36 205 women), gestational hypertension (OR=1.68 (1.31 to 2.15), p<0.001, I²=0%, 3 studies involving 15 837 women) and LGA (OR=2.12 (1.96 to 2.29), p<0.001, I²=60.0%, 12 studies involving 42 342 women) and a lower risk of SGA (OR=0.82 (0.73 to 0.92), p=0.001, I²=33.5%, 9 studies involving 39 429 women). However, the results were contrary with above when GDM women with insufficient GWG compared with GDM women with sufficient GWG. In fact, GDM women with insufficient GWG had lower risks of macrosomia (OR=0.51 (0.45 to 0.58), p<0.001, I²=13.1%, 12 studies involving 40 966 women), caesarean section (OR=0.88 (0.83 to 0.93), p<0.001, I²=35.1%, 9 studies involving 36 205 women), gestational hypertension (OR=0.64 (0.48 to 0.85), p=0.002, I²=24.4%, 3 studies involving 15 837 women) and LGA (OR=0.58 (0.53 to 0.64), p<0.001, I²=74.4%, 11 studies involving 41 293 women) and higher risks of preterm birth (OR=1.59 (1.45 to 1.74), p<0.001, I²=56.0%, 9 studies involving 37 461 women) and SGA (OR=1.38 (1.27 to 1.51), p<0.001, I²=0%, 10 studies involving 41 080 women).

Figure 3. Meta-analysis summary results forest plot for the association between gestational weight gain and pregnancy outcomes. *Statistically significant. GWG, gestational weight gain.

Subgroup analysis, meta-regression and sensitivity analysis

High-level heterogeneity (I²>50%) was observed in nine analysis groups as follows: the relationship between GDM women with excessive GWG and macrosomia; the relationship between GDM women with overweight or excessive GWG and caesarean section; the relationship between GDM women with insufficient GWG or excessive GWG and preterm birth; the relationship between GDM women with overweight or obesity and gestational hypertension; the relationship between GDM women with insufficient GWG or excessive GWG and LGA. Thus, we conducted subgroup analysis (see online supplemental table S3) and meta-regression (see online supplemental table S4) based on study design, BMI classification method and diagnostic criteria for GDM. Additionally, sensitivity analysis (see table 2) was also performed by excluding dubious studies which are a potential source of high heterogeneity. The results revealed a decrease in the high-level heterogeneity across studies. However, we were unable to identify their specific features affecting the heterogeneity because of blurred information. Among the nine analysis groups above, subgroup analysis, meta-regression and sensitivity analysis were not performed in the group explaining the relationship between GDM women with overweight/obesity and gestational hypertension due to the limitations that there were only two included studies. Overall, online supplemental file 1 showed the overall results after sensitivity analysis of high-level heterogeneity analysis groups, which indicated that the overall estimates of this study were still comparatively stable.

Table 2

Sensitivity analysis of the association between prepregnancy BMI or gestational weight gain and adverse pregnancy outcomes

The relationship of BMI/GWG and adverse pregnancy outcomes	Before sensitivity analysis		Removed study	After sensitivity analysis
	OR (95% CI)	I2 (%)		OR (95% CI)	I2 (%)
The relationship between excessive GWG and macrosomia (vs sufficient GWG)	1.74 (1.58 to 1.92)	92.6	Chen et al33 2021	2.07 (1.87 to 2.29)	23.9
The relationship between overweight and caesarean section (vs normal weight)	1.48 (1.38 to 1.59)	64.4	Yang et al31 2016	1.50 (1.40 to 1.61)	30.3
The relationship between excessive GWG and caesarean section (vs sufficient GWG)	1.44 (1.36 to 1.53)	75.1	Zheng et al32 2022, Wang and Zhou38 2020, Yang et al40 2018, Xu et al39 2021	1.30 (1.16 to 1.46)	2.9
The relationship between insufficient GWG and preterm birth (vs sufficient GWG)	1.59 (1.45 to 1.74)	56.0	Gou et al20 2019	1.56 (1.43 to 1.71)	42.5
The relationship between excessive GWG and preterm birth (vs sufficient GWG)	0.95 (0.84 to 1.07)	85.2	Shi et al26 2021	1.11 (0.98 to 1.27)	43.0
The relationship between insufficient GWG and large for gestational age (vs sufficient GWG)	0.58 (0.53 to 0.64)	74.2	Chen et al34 2021	0.51 (0.46 to 0.57)	25.8
The relationship between excessive GWG and large for gestational age (vs sufficient GWG)	2.12 (1.96 to 2.29)	60.0	Miao et al24 2017	2.17 (2.00 to 2.35)	49.7

BMI, body mass index; GWG, gestational weight gain.

Publication biases

Egger’s test and Begg’s test results showed all p-values greater than 0.05, implying that no publication biases existed in the included studies (see online supplemental table S5).

Discussion

Main findings

In this systematic review and meta-analysis, 23 studies with over 57 013 Chinese women with GDM were identified. We explored the association between prepregnancy BMI or GWG and adverse pregnancy outcomes among Chinese women with GDM. In summary, compared with GDM women with normal weight or sufficient GWG, GDM women with pregestational overweight/obesity or excessive GWG were both associated with higher risks of macrosomia, caesarean section, gestational hypertension and LGA; by contrast, GDM women with pregestational underweight or insufficient GWG were also both related to higher risk of SGA. Regards to preterm birth, GDM women with overweight or obesity or insufficient GWG were positively associated with high risk of preterm birth.

Interpretation

Maternal obesity is a major public health concern worldwide.⁴¹ The prevalence of obesity is up to 30% among women.⁴² Consistent with this study, a published systematic review¹² focusing on Chinese women found that a high prepregnancy BMI was related to increased risks of macrosomia, LGA and preterm birth and a decreased risk of SGA. Another meta-analysis⁴³ comprised on European, American and Australian cohorts also demonstrated that maternal obesity was associated with higher risks of gestational hypertension, preterm birth and LGA. Moreover, a systematic review⁴⁴ of Gulf Cooperation Council cohort studies showed that obese women were at higher risks of macrosomia and caesarean section. Overall, maternal obesity was closely associated with increased risks of developing adverse pregnancy outcomes. Obese women are at a higher risk of developing GDM,⁴⁵ and GDM itself is a risk factor of developing adverse pregnancy outcomes.^{5 46} Some researchers explored the effect of ‘diabesity’—the combination of GDM and pregravid maternal obesity on perinatal outcomes,^{47 48} and found that the joint impact of obesity and GDM on perinatal outcomes may be stronger than their individual effects. In our study, the observed relationship between maternal overweight/obesity and adverse pregnancy outcomes among GDM women may indicate their strong correlations.

Next to prepregnancy BMI, inappropriate GWG is also related to the adverse pregnancy outcomes.⁴⁹ Consistent with previous systematic reviews among non-GDM women,^{50 51} our research found that excessive GWG was related to increased risks of gestational hypertension and caesarean section and insufficient GWG was associated with high risks of SGA and preterm delivery.⁵² A meta-analysis involving 88 500 women with GDM showed that GDM women with GWG below NAM recommendations had low risks of macrosomia and LGA but it seemed that they were not associated with high risk of SGA.⁹ However, our study found that GDM women with insufficient GWG were associated with low risks of macrosomia, LGA, caesarean section and gestational hypertension and with a high risk of SGA. This finding may be related to the applicability of NAM guidelines among Chinese population.⁵³ The National Health Commission of the People’s Republic of China has recently released a standard of recommendation for GWG during pregnancy period:⁵⁴ 11.0–16.0 kg total GWG for underweight (BMI<18.5 kg/m²), 8.0–14.0 kg for normal weight (BMI: 18.5–23.9 kg/m²), 7.0–11.0 kg for overweight (BMI: 24.0–27.9 kg/m²), 5.0–9.0 kg for overweight (BMI≥28.0 kg/m²), respectively. Compared with NAM guidelines, these ranges were stricter and shifted to the left, indicating that the NAM guidelines were excessive for Chinese.⁵⁵ To date, no consensus on recommendations for Chinese women with GDM has been achieved. Cheng et al⁵⁶ explored the suggested GWG ranges for Chinese women with GDM, that is, 9.5–14.0 kg for normal-weight and 3.0–7.5 kg for overweight women. Inconsistent with the above conclusion, another study suggested the following optimal GWG ranges for Chinese women with GDM: 11.0–17.5 kg for underweight women, 3.7–9.7 kg for normal-weight women, −0.6 to 4.8 kg for overweight women and −9.8 to 4.2 kg for obese women.⁵⁷ In the future, additional studies with large sample size are needed to explore the optimal GWG ranges for Chinese women with GDM belonging to each weight groups.

Owning to social factors, Chinese women prefer caesarean section during delivery. However, a recent survey showed that the prevalence of caesarean section among Chinese women with GDM was only 36%,³² which was lower than the rate in China in 2010 at 46.2%.⁵⁸ In this study, we revealed that GDM women with overweight or obesity or excessive GWG were related to an increased risk of caesarean section. This relationship could be explained by several mechanisms. First, women who are obese and gaining excess GWG are predisposed to adverse pregnancy outcomes including macrosomia, foetal distress and poor myometrium contraction, which resulted in difficulty during vaginal delivery. Obese women also have a longer first stage of labour than normal weight women.⁵⁹ Second, over nutrition caused by overweight and excessive GWG leads to the accumulation of fatty tissue, which in turn increased the soft tissue deposits in the pelvis, reduce the pelvic area and increased the difficult of vaginal delivery.⁶⁰ Although the present study did not differentiate between elective and emergency caesarean section, all caesarean section deliveries were executed with surgical indications.

We found that GDM women with overweight or obesity had higher risk of preterm birth compared with GDM women with normal weight. Surprisingly, GDM women with insufficient GWG also had higher risk of preterm birth compared with women with sufficient GWG, which was consistent with results of non-GDM women.⁵⁰ A prior meta-analysis⁶¹ also observed that the relationship between maternal prepregnancy BMI or GWG and the risk of preterm birth showed a U-shaped trend, which indicated that the risk of preterm birth was increased at abnormal prepregnancy BMI or inappropriate GWG. Therefore, Chinese women with GDM should avoid excessive pregestational bodyweight and inappropriate GWG during pregnancy.

Significance of prepregnancy BMI and GWG for Chinese women with GDM

In China, women are usually screened for GDM in the second trimester. However, the interventions for prepregnancy BMI during this time that appears to be too late. In accordance with the findings of this study, we suggested to consider maternal prepregnancy BMI as an indicator of the direction of pregnancy outcomes.^{62 63} According to the GWG recommendations of NAM, our meta-analysis revealed that GDM women with excessive or insufficient GWG had increased risks of multiple adverse pregnancy outcomes, when they compared with women with sufficient GWG. This finding demonstrated that the importance of gaining appropriate GWG for GDM women. Zheng et al⁶⁴ suggested that oral glucose tolerance test (OGTT) divides pregnancy into two periods. For Chinese women with GDM, GDM women with excessive GWG after OGTT was positively associated with the risk for adverse pregnancy outcomes, such as macrosomia, LGA and caesarean section. Women with GDM should restrict their GWG depending on their weight prior to their diagnosis.⁶⁴ Therefore, more studies that explored the GWG guidelines after OGTT for Chinese women with GDM are needed in the future.

Strength and limitation

To the best of our knowledge, this study is the first systematic review to comprehensively confirm the association between prepregnancy BMI or GWG and adverse pregnancy outcomes among Chinese women with GDM. The conclusions provide information on the guidance of weight gain before and during pregnancy in GDM women to achieve positive pregnancy outcomes. Moreover, we adopted a complete and rigorous study design and included moderate to high quality studies to ensure the credibility of the conclusions.

However, several limitations should be considered. First, not all included studies reported the adjusted ORs, and unmeasured multiple aspects of lifestyle, such as diet and exercise, may be act as residual confounders. We were unable to adequately account for various confounding factors. In the presence of multiple data types (adjusted OR, crude OR and raw data), while we preferred to pool the adjusted ORs to reduce bias. Second, a moderate-to-high heterogeneity between some studies was observed for the following adverse outcomes: macrosomia, LGA, caesarean section, gestational hypertension and preterm birth. We performed analyses by comparing various study characteristics and exploring their effect on heterogeneity. After sensitivity analysis of high-level heterogeneity analysis groups, which indicated that the overall estimates of this study were still comparatively stable.

Conclusion

For Chinese women with GDM, abnormal prepregnancy BMI and inappropriate GWG were related to higher risks of many adverse pregnancy outcomes. Therefore, medical staff should pay more attention to the weight management of women with GDM during pregnancy. Future studies exploring the optimal GWG for Chinese women with GDM are needed.

Data availability statement

No data are available. Data were extracted from the included studies. Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Ethics statements

Patient consent for publication

Not required.

Ethics approval

Not required.

Footnote

YZ and QZ contributed equally.

Contributors All authors contributed to the study conception and design. YZ and QZ contributed equally to this paper and are joint first author. YZ was responsible for manuscript drafting and revision, data collection, data extraction and data analysis; QZ contributed to study design, data collection, data extraction, data interpretation and manuscript drafting revision; YP contributed to study design, data collection, data extraction, data analysis and data interpretation; XJ was responsible for study design, data interpretation and manuscript revision; JL, RL and LH were responsible for manuscript revision. XJ is responsible for the overall content as guarantor and XJ accepts full responsibility for the finished work and/or the conduct of the study, had access to the data, and controlled the decision to publish.

Funding This work was supported by the Fujian Maternity and Child Health Hospital (grant number (YCXH 22-02)) and Joint Funds for the Innovation of Science and Technology, Fujian Province (grant number (2020Y9133)).

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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