Comparison of three gestational weight gain guidelines for adverse pregnancy outcomes in Chinese women with gestational diabetes: A cohort study

ABSTRACT

Background

This study aimed to assess the associations between post‐diagnostic gestational weight gain (GWG) and adverse pregnancy outcomes among women with gestational diabetes mellitus (GDM) and to systematically compare the predictive performance of three mainstream GWG guidelines (IOM‐2009, CNS‐2021, NHCC‐2023), so as to provide real‐world evidence for precise GWG management in clinical GDM care.

Methods

This retrospective population‐based study was conducted utilizing the standardized prenatal surveillance system in Tianjin, China. Women with GDM were stratified into insufficient, appropriate, and excessive GWG groups according to the IOM‐2009, CNS‐2021, and NHCC‐2023 criteria. Independent associations of abnormal GWG with adverse perinatal outcomes were analyzed using independent t‐tests, chi‐squared tests, and multivariable logistic regression models in SPSS 26.0.

Results

A total of 69,859 pregnant women were enrolled in the present study, including 7,198 women diagnosed with GDM. The NHCC‐2023 guideline identified the highest proportion of excessive GWG (56.6%), compared with CNS‐2021 (52.7%) and IOM‐2009 (53.3%). Notably, only NHCC‐2023 revealed a significant bidirectional association between GWG and PE risk: insufficient GWG (OR = 1.512, 95% CI: 1.057–2.162) and excessive GWG (OR = 2.449, 95% CI: 1.844–3.253) were both independently correlated with higher PE susceptibility. Excessive postdiagnostic GWG was associated with elevated risks of cesarean section and large for gestational age (LGA) infants across all three guideline frameworks, while associations for preterm birth and small‐for‐gestational‐age (SGA) varied by guideline criteria.

Conclusions

The GDM‐specific NHCC‐2023 guideline supports precise, population‐tailored GWG management for Chinese women with GDM and holds promising clinical applicability for Asian GDM populations.

Abbreviations

AGA

appropriate for gestational age

CHSC

Community Health Service Center

CNS

Chinese Nutrition Society

eMHR

electronic maternal health record

GCT

glucose challenge test

GDM

Gestational diabetes mellitus

GWG

gestational weight gain

IADPSG

International Association of Diabetes and Pregnancy Study Groups

IOM

Institute of Medicine

LGA

large for gestational age

NHCC

National Health Commission of the People's Republic of China

OGTT

oral glucose tolerance test

PE

preeclampsia

SGA

small for gestational age

BACKGROUND

Gestational diabetes mellitus (GDM), a prevalent metabolic disorder unique to pregnancy, affects 14.0% of pregnancies worldwide ¹ and substantially increases the risks of adverse maternal and neonatal outcomes, including preeclampsia (PE), preterm birth, cesarean section, and large for gestational age (LGA) or small for gestational age (SGA) infants ² , ³ . Gestational weight gain (GWG)—a modifiable component of GDM management ⁴ , ⁵ —is a critical determinant of perinatal prognosis: excessive GWG aggravates insulin resistance and placental dysfunction, whereas insufficient GWG may indicate fetal nutrient deprivation, with both scenarios contributing to adverse perinatal outcomes ⁶ , ⁷ .

However, a notable clinical gap persists: standardized GWG assessment frameworks specifically designed for GDM populations, particularly Asian individuals, remain lacking. The globally adopted 2009 Institute of Medicine (IOM) GWG guidelines—Weight Gain During Pregnancy: Reexamining the Guidelines (IOM‐2009) ⁸ —were formulated based on Western cohorts and may not fully account for ethnic disparities in body composition, dietary habits, and gestational metabolic characteristics among Chinese and other Asian women ⁹ . Such ethnic inconsistencies partially explain the heterogeneous associations between IOM‐recommended GWG ranges and GDM‐related adverse outcomes observed in Asian populations ¹⁰ . Although the 2021 Chinese Nutrition Society (CNS) guidelines—Weight Monitoring and Evaluation During Pregnancy Period of Chinese Women (CNS‐2021), the first domestic GWG criterion for healthy pregnant Chinese women ¹¹ —have mitigated the regional limitations of Western criteria, they do not address the unique pathophysiological features of GDM, including disrupted glucose homeostasis and elevated inflammatory status. In 2023, the National Health Commission of China (NHCC) issued the first nationwide GWG standard exclusively tailored for women with GDM—Standard of Recommended Gestational Weight Gain for Women with Gestational Diabetes Mellitus (NHCC‐2023) ¹² —to compensate for this deficiency. Nevertheless, its predictive performance for adverse pregnancy outcomes remains unvalidated in large population‐based cohorts.

Against this backdrop, this retrospective study was conducted based on data from a population‐based mother–child cohort established in Tianjin in 2015 (n = 69,859). By comparing the performance of the IOM‐2009, CNS‐2021, and NHCC‐2023 guidelines in evaluating postdiagnostic GWG and its association with adverse pregnancy outcomes (PE, preterm birth, cesarean section, LGA, and SGA), this study aimed to (1) validate the efficacy of the NHCC‐2023 guidelines for screening high‐risk women with GDM, (2) clarify inter‐guideline discrepancies in the associations between inappropriate GWG and adverse perinatal outcomes, and (3) provide real‐world evidence to support precise GWG management for Chinese and Asian populations with GDM.

The present findings carry important clinical implications. Validation of this China‐specific, GDM‐tailored GWG standard enables clinicians to implement targeted interventions, reduce preventable perinatal complications, and improve maternal and child health equity in GDM‐endemic Asian regions.

MATERIALS AND METHODS

Study population and data collection

This study enrolled 69,859 pregnant women who received prenatal care across all 16 districts of Tianjin throughout 2015 (Figure S1). Eligible participants were aged 18–45 years with singleton pregnancies, initiated prenatal screening before 14 weeks of gestation, and completed follow‐up until delivery. Women with prepregnancy diabetes or hypertension, severe hepatic or renal dysfunction, other digestive system diseases, or untreated thyroid diseases were excluded. All participant data were fully anonymized and labeled with unique identification codes for confidentiality. This study was approved by the Ethics Committee of Tianjin Women and Children's Health Center.

Data were retrieved from the standardized Tianjin Three‐Level Maternal and Child Health Network, officially defined as the Tianjin Women and Children Health Care System (TJWCHCS). Established in accordance with China's national maternal health service model, this public health surveillance system comprises a three‐tier perinatal care framework:

• Primary tier: Community Health Service Centers (CHSCs) undertake initial maternal registration and basic antenatal surveillance;

• Secondary tier: District‐level maternal and child health institutions and obstetric facilities provide specialized antenatal care and routine perinatal interventions;

• Tertiary tier: Tianjin Women and Children's Health Center and regional maternal emergency centers manage high‐risk pregnancies and complicated deliveries.

Web‐based data integration across the three‐tier network via the Tianjin Women and Children's Health Information Platform enables full coverage of pregnant women residing in all 16 administrative districts of Tianjin. For local reproductive‐age women, pregnancy confirmation through urine/serum human chorionic gonadotropin testing and ultrasonography allows the establishment of a standardized electronic maternal health record (eMHR) at local CHSCs. eMHR enrollment incorporates participants into the municipal unified maternal health management system, supporting continuous, standardized perinatal care, including serial maternal surveillance, real‐time fetal and neonatal well‐being monitoring, evidence‐based antenatal health education and lifestyle guidance, and coordinated intrapartum care and delivery management.

All personnel responsible for participant assessment, biological sample collection, and data extraction received unified centralized training and passed standardized competency validation, in strict accordance with the 2015 Tianjin Municipal Guidelines for Maternal Health Data Collection and Quality Assurance. Standardized operating procedures, uniformly calibrated instruments (e.g., automated biochemical analyzers and fetal Doppler ultrasound devices), and consistent reagent batches were adopted across all participating institutions to guarantee cross‐site data integrity. Furthermore, annual internal quality control audits were performed to ensure intra‐site measurement precision, and external quality assessment programs organized by the Tianjin Center for Clinical Laboratory Quality Control were implemented to verify the inter‐site accuracy of all detected biomarkers and clinical indicators.

Collection of perinatal information

Perinatal information was systematically collected covering maternal baseline characteristics, prenatal examination results, follow‐up events, and delivery and neonatal outcomes. Maternal baseline information included demographic and socioeconomic characteristics (birth date, ethnicity, educational level), medical and obstetric history (chronic disease history, family history of hereditary diseases or adverse perinatal outcomes, smoking status, gravidity, parity, and prior adverse pregnancy events), and basic gestational information (last menstrual period). Routine prenatal data consisted of physical measurements (height, prepregnancy weight, serial gestational weight, and trimester‐specific blood pressure) and laboratory biomarkers (complete blood count, fasting plasma glucose, hepatic and renal function, and thyroid function). Serial prenatal follow‐up data included dynamic monitoring of gestational weight and blood pressure, as well as recorded pregnancy complications (GDM, PE) and other obstetric high‐risk conditions. Delivery‐related variables comprised delivery date, first‐trimester ultrasound‐confirmed gestational age, predelivery weight, and mode of delivery. Neonatal outcomes included infant sex, birth weight and length, Apgar scores, and congenital malformations.

Screening and diagnosis of gestational diabetes mellitus

GDM screening was conducted at CHSCs between 24 and 28 weeks of gestation using a 50‐g oral glucose challenge test (GCT), in accordance with local Tianjin GDM screening and management guidelines ¹³ . Pregnant women with a 1‐h postload glucose level ≥7.8 mmol/L were referred to Tianjin Women and Children's Health Center for confirmatory testing via a 75‐g oral glucose tolerance test (OGTT) ¹⁴ . GDM was diagnosed based on the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria: fasting plasma glucose ≥5.1 mmol/L, 1‐h postload glucose ≥10.0 mmol/L, or 2‐h postload glucose ≥8.5 mmol/L, exceeding any single threshold confirmed a GDM diagnosis ¹⁵ .

Measurement and assessment of gestational weight gain

In this study, GWG was specifically defined as weight gain occurring after GDM diagnosis. The weekly GWG rate (kg/week) was calculated as the weight difference between predelivery weight and weight at GDM diagnosis, divided by the interval of gestational weeks between the two measurements. Prepregnancy body mass index (BMI) was calculated as weight (kg) divided by the square of height (m²). According to Chinese national guidelines ¹¹ , prepregnancy BMI was stratified into four categories: underweight (BMI < 18.5 kg/m²), normal weight (18.5 ≤ BMI < 23.9 kg/m²), overweight (24.0 ≤ BMI < 27.9 kg/m²), and obese (BMI ≥ 28.0 kg/m²).

Classification of gestational weight gain in women with GDM

Women with GDM were stratified into insufficient, appropriate, and excessive GWG groups according to postdiagnosis GWG ranges defined by three authoritative guidelines (Table 1).

Table 1.

Recommended ranges for weight gain in the second and third trimesters of pregnancy in three pregnancy weight management guidelines

Prepregnancy BMI	IOM‐2009	CNS‐2021	NHCC‐2023 †
	(kg/week)	(kg/week)	(kg/week)
Underweight	0.51 (0.44 ~ 0.58)	0.46 (0.37 ~ 0.56)	0.46 (0.37 ~ 0.56)
Normal weight	0.42 (0.35 ~ 0.50)	0.37 (0.26 ~ 0.48)	0.37 (0.26 ~ 0.48)
Overweight	0.28 (0.23 ~ 0.33)	0.30 (0.22 ~ 0.37)	0.26 (0.19 ~ 0.32)
Obese	0.22 (0.17 ~ 0.27)	0.22 (0.15 ~ 0.30)	0.18 (0.12 ~ 0.23)

BMI, body Mass Index; CNS, Chinese Nutrition Society; GDM, gestational diabetes mellitus; IOM, Institute of Medicine; NHCC, National Health Commission of the People's Republic of China.

^† Weight gain in the second and third trimesters of pregnancy after the diagnosis of GDM.

IOM‐2009 ⁸ , CNS‐2021 ¹¹ , and NHCC‐2023 ¹² . Briefly, IOM‐2009 represents the most globally prevalent GWG standard. Launched in October 2021, CNS‐2021 constitutes China's first domestic GWG specification for healthy pregnant women. Implemented in June 2024, NHCC‐2023 is the first Chinese GWG criterion specifically tailored for GDM populations. For each guideline, GWG was categorized as insufficient (below the recommended lower limit), appropriate (within the recommended range), or excessive (above the recommended upper limit).

Adverse pregnancy outcomes

Preterm birth was defined as delivery occurring at a gestational age <37 weeks ¹⁶ . PE was diagnosed in pregnant women after 20 weeks of gestation presenting with systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg, accompanied by any one of the following proteinuria abnormalities: 24‐h urine protein ≥0.3 g, urine protein/creatinine ratio ≥0.3, or positive random urine protein ¹⁷ . Based on the 2015 Chinese neonatal birth weight criteria ¹⁸ , neonatal birth weight was classified as appropriate for gestational age (AGA, P10–P90), LGA (>P90), or SGA (<P10) according to sex‐ and gestational age‐specific birth weight percentiles.

Statistical analysis

All statistical analyses were performed using SPSS 26.0 (IBM Corp., Armonk, NY, USA). Continuous variables with normal or approximately normal distributions were described as mean ± standard deviation (SD), and between‐group differences were compared using the independent samples t‐test. Categorical variables were presented as frequencies and percentages, with intergroup comparisons conducted via the chi‐squared test. Multivariate logistic regression models were applied to explore factors associated with adverse pregnancy outcomes, with adjustments for maternal age, educational attainment (≤12 vs. >12 years), parity (nulliparous vs. multiparous), smoking status, and fetal sex. A two‐tailed P‐value of <0.05 was considered statistically significant for all analyses.

RESULTS

Population characteristics

A total of 69,859 pregnant women were enrolled in the present study (Figure S1), including 7,198 women with GDM and 62,661 non‐GDM controls (Table 2). Compared with controls, women in the GDM group had significantly higher maternal age, prepregnancy BMI, systolic and diastolic blood pressure, and first‐trimester fasting plasma glucose (all P < 0.01). The GDM group also presented higher proportions of multiparity, educational attainment >12 years, smoking status, and a family history of diabetes or hypertension (all P < 0.01). Additionally, women with GDM initiated prenatal care at a later gestational age and delivered at an earlier gestational age (both P < 0.01). In terms of perinatal outcomes, the GDM group exhibited significantly higher rates of cesarean section, preterm birth, PE, and LGA, alongside a lower incidence of SGA (all P < 0.01).

Table 2.

Comparison of characteristics of pregnant women in the GDM and control group

Characteristics	GDM	Control	χ 2/t	p
	(n = 7,198)	(n = 62,661)
Age (years)	29.81 ± 4.20	27.98 ± 4.09	−35.099	<0.001
Han ethnicity (n, %)	6,903 (95.9%)	59,980 (95.7%)	0.514	0.473
Multiparity (n, %)	2,287 (31.8%)	18,571 (29.6%)	14.058	<0.001
Education >12 years (n, %)	4,728 (65.7%)	39,014 (62.3%)	32.315	<0.001
Smoker (n, %)	51 (0.7%)	227 (0.4%)	19.53	<0.001
Family history of diabetes (n, %)	302 (4.2%)	1,244 (2.0%)	14.757	<0.001
Family history of hypertension (n, %)	414 (5.8%)	2,685 (4.3%)	32.76	<0.001
Prepregnancy BMI (kg/m2)	24.54 ± 4.35	22.45 ± 3.67	−39.108	<0.001
Gestational age at initial prenatal examination (week)	10.87 ± 1.60	10.79 ± 1.62	−3.623	<0.001
Systolic blood pressure in the first trimester (mmHg)	110.28 ± 21.01	106.72 ± 16.57	−16.73	<0.001
Diastolic blood pressure in the first trimester (mmHg)	71.49 ± 8.73	69.10 ± 7.97	−22.213	<0.001
Fasting blood glucose in the first trimester (mmol/L)	5.11 ± 0.95	4.75 ± 0.50	−31.894	<0.001
Gestational age was diagnosed with GDM (week)	25.97 ± 0.91	25.95 ± 0.95	−1.564	0.118
Gestational age at delivery (week)	39.06 ± 1.56	39.38 ± 1.46	16.24	<0.001
Sex of fetus (male)	3,781 (52.5%)	32,209 (51.4%)	4.162	0.125
Stillbirth (n, %)	27 (0.4%)	263 (0.4%)	0.311	0.577
Cesarean section (n, %)	4,311 (59.9%)	31,386 (50.1%)	248.302	<0.001
Preterm birth (n, %)	481 (6.7%)	2,597 (4.1%)	98.731	<0.001
Preeclampsia (n, %)	447 (6.2%)	1,635 (2.6%)	289.509	<0.001
Large for gestational age (n, %)	1,366 (19.0%)	7,408 (11.8%)	300.979	<0.001
Small for gestational age (n, %)	302 (4.2%)	3,328 (5.3%)	16.309	<0.001

Data are mean ± SD or n (%).

BMI, body mass index; GDM, gestational diabetes mellitus.

Gestational weight gain and incidence of adverse pregnancy outcomes

Women with GDM were stratified into insufficient, appropriate, and excessive GWG groups based on the IOM‐2009, CNS‐2021, and NHCC‐2023 guidelines, respectively (Table 3). All three guideline frameworks yielded consistent associative trends: GDM women with excessive postdiagnosis GWG exhibited significantly higher incidences of cesarean section, preterm birth, PE, and LGA (all P < 0.01). In contrast, women with insufficient GWG had the highest SGA incidence (P < 0.01). Notably, the proportion of excessive GWG identified by NHCC‐2023 standard (56.6%) was higher than those determined by the CNS‐2021 (52.7%) and IOM‐2009 guidelines (53.3%).

Table 3.

Adverse pregnancy outcomes of GDM women with different weight gain

Guideline	Outcome	Postdiagnosis weight gain						χ 2	P
		Insufficient		Appropriate		Excessive
		n	%	n	%	n	%
IOM‐2009		1952	27.1	1,408	19.6	3,838	53.3
	Cesarean section	1,058	54.2	834	59.3	2,419	63.0	42.255	<0.01
	Preterm birth	73	3.7	39	2.8	368	9.6	113.786	<0.01
	PE	75	3.8	53	3.8	319	8.3	62.305	<0.01
	LGA	252	12.9	255	18.1	859	22.4	76.320	<0.01
	SGA	107	5.5	59	4.2	136	3.5	12.089	<0.01
CNS‐2021		1,436	19.9	1969	27.4	3,793	52.7
	Cesarean section	804	56.0	1,133	57.6	2,374	62.6	25.007	<0.01
	Preterm birth	61	4.2	55	2.8	364	9.6	113.207	<0.01
	PE	67	3.9	76	4.7	304	8.0	45.717	<0.01
	LGA	193	13.4	329	16.7	844	22.3	61.610	<0.01
	SGA	81	5.6	88	4.5	133	3.5	12.313	<0.01
NHCC‐2023		1,332	18.5	1790	24.9	4,076	56.6
	Cesarean section	737	55.3	1,005	56.1	2,569	63.0	38.466	<0.01
	Preterm birth	57	4.3	46	2.6	377	9.2	104.095	<0.01
	PE	61	4.6	54	3.0	332	8.1	63.587	<0.01
	LGA	174	13.1	274	15.3	918	22.5	79.159	<0.01
	SGA	76	5.7	86	4.8	140	3.4	15.113	<0.01

CNS, Chinese Nutrition Society; GDM, gestational diabetes mellitus; IOM, Institute of Medicine; LGA, large for gestational age; NHCC, National Health Commission of the People's Republic of China; PE, Preeclampsia; SGA, small for gestational age.

Multivariate analysis for gestational weight gain and adverse pregnancy outcomes

Logistic regression models were constructed to further explore the independent associations between postdiagnostic GWG status (insufficient/excessive vs. appropriate) and adverse pregnancy outcomes among women with GDM (Table 4). Adverse outcomes, including cesarean section, preterm birth, PE, LGA, and SGA, were defined as binary variables (0 = absent, 1 = present). Two analytical models were applied: an unadjusted crude model (Model 1), with GWG category (0 = appropriate, 1 = insufficient, 2 = excessive) as the independent variable, and a fully adjusted model (Model 2), controlling for maternal age, educational attainment, parity, smoking status, and fetal sex.

Table 4.

Odd ratios of Insufficient/excessive GWG for the risk of adverse pregnancy outcomes

Outcome	Model 1				Model 2
	Insufficient	Appropriate	Excessive		Insufficient	Appropriate	Excessive
	OR(95% CI)			P‐trend	OR (95% CI)			P‐trend
IOM‐2009
Cesarean section	0.813 (0.708 ~ 0.934) *	1	1.171 (1.034 ~ 1.327) *	<0.01	0.784 (0.680 ~ 0.904) *	1	1.155 (1.016 ~ 1.313) *	<0.01
Preterm birth	1.363 (0.918 ~ 2.023)	1	3.720 (2.659 ~ 5.205) *	<0.01	1.327 (0.983 ~ 1.971)	1	3.674 (2.674 ~ 5.244) *	<0.01
PE	1.005 (0.718 ~ 1.406)	1	2.042 (1.543 ~ 2.703) *	<0.01	1.007 (0.716 ~ 1.414)	1	1.942 (1.461 ~ 2.583) *	<0.01
LGA	0.670 (0.554 ~ 0.809) *	1	1.303 (1.115 ~ 1.522) *	<0.01	0.675 (0.558 ~ 0.816) *	1	1.281 (1.096 ~ 1.497) *	<0.01
SGA	1.325 (0.957 ~ 1.835)	1	0.839 (0.614 ~ 1.146)	0.061	1.311 (0.946 ~ 1.818)	1	0.842 (0.615 ~ 1.151)	0.073
CNS‐2021
Cesarean section	0.938 (0.817 ~ 1.076)	1	1.233 (1.103 ~ 1.378) *	<0.01	0.911 (0.791 ~ 1.049)	1	1.247 (1.112 ~ 1.398) *	<0.01
Preterm birth	1.543 (1.065 ~ 2.236) *	1	3.692 (2.765 ~ 4.929) *	<0.01	1.501 (1.035 ~ 2.177) *	1	3.754 (2.809 ~ 5.016) *	<0.01
PE	1.210 (0.883 ~ 1.657)	1	1.871 (1.465 ~ 2.390) *	<0.01	1.219 (0.886 ~ 1.677)	1	1.815 (1.414 ~ 2.328) *	<0.01
LGA	0.774 (0.638 ~ 0.938) *	1	1.426 (1.238 ~ 1.642) *	<0.01	0.782 (0.644 ~ 0.948) *	1	1.411 (1.225 ~ 1.626) *	<0.01
SGA	1.277 (0.937 ~ 1.741)	1	0.776 (0.590 ~ 1.022)	<0.05	1.262 (0.925 ~ 1.723)	1	0.777 (0.589 ~ 1.024)	<0.05
NHCC‐2023
Cesarean section	0.969 (0.840 ~ 1.118)	1	1.332 (1.189 ~ 1.491) *	<0.01	0.937 (0.809 ~ 1.085)	1	1.318 (1.173 ~ 1.480) *	<0.01
Preterm birth	1.205 (0.889 ~ 1.633)	1	1.557 (1.228 ~ 1.974) *	<0.01	1.652 (1.112 ~ 2.454) *	1	3.881 (2.840 ~ 5.303) *	<0.01
PE	1.544 (1.084 ~ 2.200) *	1	2.604 (1.969 ~ 3.444) *	<0.01	1.512 (1.057 ~ 2.162) *	1	2.449 (1.844 ~ 3.253) *	<0.01
LGA	0.832 (0.678 ~ 1.021)	1	1.608 (1.387 ~ 1.865) *	<0.01	0.838 (0.682 ~ 1.029)	1	1.580 (1.361 ~ 1.833) *	<0.01
SGA	1.200 (0.874 ~ 1.648)	1	0.705 (0.536 ~ 0.927) *	<0.01	1.186 (0.862 ~ 1.630)	1	0.704 (0.534 ~ 0.928) *	<0.01

Model 1 (univariate analysis): GWG category (coded as 0 = appropriate, 1 = insufficient, 2 = excessive) served as the independent variable. Model 2 (multivariate analysis): Adjusted for confounding variables including maternal age, educational attainment, parity (multiparous vs. nulliparous), smoking status (smoker vs. nonsmoker), and fetal sex (male vs. female).

Abbreviations: CNS, Chinese Nutrition Society; GWG, gestational weight gain; IOM, Institute of Medicine; LGA, large for gestational age; NHCC, National Health Commission of the People's Republic of China; PE, Preeclampsia; SGA, small for gestational age.

^* The difference is statistically significant (P < 0.05).

Multivariate regression revealed a significant dose–response relationship between GWG and PE risk across all three guideline systems (all P for trend <0.01). Based on the GDM‐specific NHCC‐2023 criteria, both insufficient GWG (OR = 1.512, 95% CI: 1.057–2.162, P < 0.05) and excessive GWG (OR = 2.449, 95% CI: 1.844–3.253, P < 0.01) were independently associated with elevated PE risk relative to appropriate GWG. In contrast, no significant association between insufficient GWG and PE was observed using the general pregnancy CNS‐2021 criteria (AOR = 1.219, 95% CI: 0.886–1.677, P > 0.05) or the IOM‐2009 guidelines (OR = 1.007, 95% CI: 0.716–1.414, P > 0.05).

A consistent dose–response association between GWG and preterm birth risk was also identified across all three guidelines (all P for trend <0.01). Insufficient GWG was correlated with higher preterm birth risk when classified by NHCC‐2023 (OR = 1.652, 95% CI: 1.112–2.454, P < 0.05) and CNS‐2021 (OR = 1.501, 95% CI: 1.035–2.177, P < 0.05), while no significant association was found under the IOM‐2009 framework (OR = 1.327, 95% CI: 0.983–1.971, P > 0.05). Furthermore, all three guideline systems demonstrated significant dose–response relationships between GWG and the risks of cesarean section and LGA (all P for trend <0.01), with excessive GWG independently increasing the likelihood of these two adverse events (all P < 0.05).

For SGA outcomes, a significant dose–response association with GWG was only detected in the two Chinese guideline systems (NHCC‐2023 and CNS‐2021; both P for trend <0.05). Specifically, excessive GWG defined by NHCC‐2023 was protective against SGA (OR = 0.704, 95% CI: 0.534–0.928, P < 0.05). Conversely, IOM‐2009 showed no significant linear association between GWG and SGA risk (P for trend >0.05), with neither insufficient GWG (OR = 1.311, 95% CI: 0.946–1.818, P > 0.05) nor excessive GWG (OR = 0.842, 95% CI: 0.615–1.151, P > 0.05) correlated with SGA occurrence.

DISCUSSION

GDM remains a major contributor to global maternal and neonatal morbidity. GWG, a modifiable determinant of perinatal prognosis, is currently hampered by inconsistent and population‐mismatched assessment frameworks for GDM populations. This study addressed these critical clinical gaps by systematically evaluating three mainstream GWG guidelines based on a large real‐world cohort of Chinese women with GDM. The findings validate the clinical applicability of the recently released GDM‐tailored NHCC‐2023 standard and further clarify the relationships between altered GWG and adverse perinatal outcomes in Asian populations.

IOM‐2009, though widely adopted globally, was established primarily on Western populations and fails to account for ethnic disparities in body composition, dietary habits, and gestational metabolic characteristics among Chinese and Asian women. The present findings confirm such population mismatch: IOM‐2009 identified a lower proportion of excessive GWG (53.3%) relative to NHCC‐2023 (56.6%) and failed to detect the association between insufficient GWG and PE. Similarly, CNS‐2021, while optimized for general Chinese pregnant women, does not incorporate the unique pathophysiological features of GDM (e.g., insulin resistance‐mediated placental dysfunction), which explains its limited capacity to capture the link between insufficient GWG and elevated PE risk ¹⁹ . In contrast, NHCC‐2023 standard, the first nationwide GWG criterion specifically tailored for Chinese women with GDM, integrates disease‐specific metabolic and epidemiological characteristics, thereby enabling superior identification of clinically meaningful GWG‐outcome associations.

A key strength of this study is the novel finding of a bidirectional dose–response relationship between postdiagnostic GWG and PE risk exclusively captured by the NHCC‐2023 framework. Specifically, insufficient GWG increased PE risk by approximately 1.5‐fold (OR = 1.512, 95% CI: 1.057–2.162), whereas excessive GWG conferred a 2.5‐fold higher PE risk (OR = 2.449, 95% CI: 1.844–3.253). This bidirectional association is biologically reasonable. Insufficient GWG may indicate suboptimal maternal nutrient supply, leading to impaired placental angiogenesis, ischemic injury, and subsequent PE development; conversely, excessive GWG exacerbates systemic inflammation and endothelial dysfunction, which are core pathological mechanisms of PE ²⁰ , ²¹ . The inability of IOM‐2009 and CNS‐2021 to identify this association is likely attributable to their neglect of GDM‐specific placental metabolic vulnerability to fluctuating gestational weight ²² . For instance, GDM patients with insufficient GWG may have latent nutrient deficiencies that aggravate defective spiral artery remodeling, further elevating hypertensive disorder risks in pregnancy ²³ , ²⁴ . Moreover, NHCC‐2023 comprehensively predicted the associations between abnormal GWG and multiple adverse outcomes, including preterm birth, cesarean section, LGA, and SGA. Such comprehensive predictive performance supports the implementation of individualized and precise weight management for GDM pregnancies, rather than universal, generalized weight gain guidance.

This study provides robust real‐world evidence to promote targeted GWG intervention strategies in high‐burden GDM regions, including China and other Asian countries. Benefiting from the standardized three‐tier maternal and child healthcare system in Tianjin, with high prenatal coverage and standardized GDM screening procedures, NHCC‐2023 can be seamlessly integrated into routine prenatal care to stratify GDM patients by GWG risk and deliver individualized nutritional and weight management counseling. Furthermore, given the shared ethnic characteristics, dietary patterns, and metabolic profiles across Asian populations, the localized and GDM‐adapted GWG grading principle of NHCC‐2023 can be referenced and generalized to optimize regional GDM management, improve maternal and child health equity, and reduce the long‐term risk of offspring metabolic diseases such as childhood obesity.

Strengths and limitations

The primary strength of this study lies in its large, geographically representative cohort (n = 69,859) derived from Tianjin's standardized population‐based maternal and child health surveillance system. The comprehensive citywide sampling framework minimized selection bias and enhanced the generalizability of the findings to other Chinese and Asian regions with similar socioeconomic and ethnic backgrounds. Nevertheless, several inherent limitations should be acknowledged. First, the retrospective study design precludes the establishment of causal relationships between aberrant GWG and adverse perinatal outcomes. Future prospective cohort studies are warranted to validate whether adherence to the NHCC‐2023 GWG recommendations can effectively reduce GDM‐related perinatal complications and improve pregnancy prognosis. Second, GDM screening in this cohort adopted a two‐step 50‐g GCT followed by a 75‐g OGTT protocol, rather than the unified one‐step IADPSG criteria. This diagnostic approach may underestimate the prevalence of mild GDM cases, potentially introducing selection bias and constraining population generalizability. Third, although all exposure and outcome data were collected in strict accordance with the 2015 Tianjin Municipal Guidelines for Maternal Health Data Collection and Quality Assurance, with standardized operational protocols, regular equipment calibration, systematic internal and external quality control, and professional staff training to guarantee data reliability, formal external validation of the municipal surveillance system is currently unavailable. Future research should expand sampling to diverse geographical and socioeconomic settings to further refine and validate the regional applicability of NHCC‐2023, thereby facilitating its nationwide promotion and precise clinical application.

CONCLUSIONS

This study strengthens the evidence base for individualized GWG management among Chinese women with GDM. Compared with the Western IOM‐2009 and domestic general pregnancy CNS‐2021 guidelines, the newly released NHCC‐2023 GDM‐specific standard exhibits superior performance in identifying clinically meaningful associations between aberrant postdiagnostic GWG and multiple adverse perinatal outcomes, particularly the bidirectional relationship between insufficient/excessive GWG and elevated preeclampsia risk. Based on large‐scale real‐world cohort data, the present findings highlight the critical limitations of generalized, nondisease‐tailored GWG criteria and support a paradigm shift toward precise, population‐specific weight management for GDM pregnancies. NHCC‐2023 has promising applicability for routine prenatal care in Chinese and other Asian GDM populations, with substantial potential to reduce preventable perinatal complications and optimize long‐term maternal and child health outcomes in high‐prevalence Asian regions. These findings should be interpreted with caution, considering the inherent limitations of the two‐step GDM screening protocol and the lack of external validation for the municipal maternal health surveillance system.

ETHICAL STATEMENTS

The study protocol was approved by the Human Subjects Committee of the Tianjin Women and Children's Health Center. All methods were carried out in accordance with relevant guidelines and regulations. Since this was a retrospective analysis of data routinely collected from participants, the consent for participation was not applicable. The need for informed consent was waived by the Ethics Committee of Tianjin Women and Children's Health Center.

CONSENT

Not applicable.

DISCLOSURE

The authors declare no conflict of interest.

Approval of the research protocol: The study protocol was approved by the Human Subjects Committee of the Tianjin Women and Children's Health Center. All methods were carried out in accordance with relevant guidelines and regulations. Since this was a retrospective analysis of data routinely collected from participants, the consent for participation was not applicable. The need for informed consent was waived by the Ethics Committee of Tianjin Women and Children's Health Center.

Informed consent: N/A.

Registry and the registration no. of the study/trial: N/A.

Animal studies: N/A.

FUNDING

This research received no specific grant from funding agencies in the public, commercial, or not‐for‐profit sectors.

AUTHOR CONTRIBUTIONS

S. Z.: Writing – Original draft, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. W.L.: Methodology, Formal analysis, Data curation. N.L., J.G., and L.T.: Methodology, Investigation, Data curation. H.L.: Supervision, Resources. All authors have approved the final version of the manuscript.

Supporting information

Figure S1. Study flow chart.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available upon request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.