Related Experiment Video
Updated: Jan 20, 2026
Author Spotlight: Alleviating Nausea and Vomiting in Pregnancy with Safe and Effective Auricular Acupuncture
Published on: August 4, 2023
Gestational Weight Gain Charts by Gestational Age and Body Mass Index for Chinese Women: A Population-Based Follow-up
Aiqun Huang1, Yanhui Xiao2, Huanqing Hu1
1National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention.
Insights
New charts provide unbiased guidance on gestational weight gain (GWG) for Chinese women. These tools, based on early pregnancy BMI, help monitor healthy weight gain during pregnancy.
Area of Science:
- Obstetrics and Gynecology
- Maternal Health
- Public Health Nutrition
Background:
- Establishing unbiased associations between gestational weight gain (GWG) and perinatal health is crucial in China.
- The study addresses the need for localized GWG data, considering China's large population.
Purpose of the Study:
- To create weight-gain-for-gestational-age charts tailored for Chinese women.
- To utilize early pregnancy Body Mass Index (BMI) for presenting selected percentiles of GWG.
Main Methods:
- A population-based follow-up study involving 132,835 pregnant women in China.
- Application of multilevel analyses and restricted cubic splines to model GWG.
- Internal and external validation of the developed models.
Main Results:
- Models developed using 34,288 women, estimating GWG percentiles for each week of gestation.
- Median GWG at 40 weeks varied by pre-pregnancy BMI: 15.0 kg (underweight) to 12.1 kg (obese).
- External validation confirmed model accuracy, with specificities between 90% and 100% for various percentiles.
Conclusions:
- Population-based gestational weight gain Z-score charts demonstrated effectiveness.
- The charts provide valuable guidance for expected GWG in Chinese women.
Background:
Establishment of an unbiased association between gestational weight gain (GWG) and perinatal health is urgently needed in China, which has the largest population in the world. Our study aimed to create weight-gain-for-gestational-age charts using early pregnancy body mass index (BMI) to present selected percentiles of GWG in China.
Methods:
A population-based follow-up study was conducted based on the Maternal and Newborn Health Monitoring System, which recruited 132,835 pregnant women between October 2013 and September 2016 in 12 districts/counties of 6 provinces in China. Multilevel analyses and restricted cubic splines were performed to model the longitudinal repeated maternal weight gain measurements and obtain smoothed curves for GWG. The internal and external validation of each model was also assessed.
Results:
To develop models of GWG, 34,288 women were included. Smoothed percentiles of GWG in the 3rd, 10th, 50th, 90th, and 97th percentiles were estimated for each week of gestation. The median figures for GWG were 15.0 kg, 14.4 kg, 13.5 kg, and 12.1 kg in underweight, normal weight, overweight, and obese women, respectively, at 40 weeks. Of all the weight measurements, more than 70% and 95% fell within the expected 1 to 2 standard deviations, respectively. To accomplish external validation of the models, 20,458 women were included. The specificities of measurements in the 5th, 10th, 15th, 25th, 75th, 85th, 90th, and 95th percentiles in four BMI categories were between 90% and 100%.
Conclusions:
The population-based gestational weight gain Z-score charts performed well in providing guidance regarding expected gestational weight gain in Chinese women.
Related Concept Videos
05:33Ear Plaster Therapy as a Safe and Effective Treatment for Gestational Vomiting
07:13Induction of Maternal Immune Activation in Mice at Mid-gestation Stage with Viral Mimic Poly(I:C)
01:22Diabetes Mellitus: Type 2 and Gestational
01:19Mass and Weight
07:44Evaluation of Changes in Hydration and Body Cell Mass with Bioelectrical Impedance Analysis after Exercise Program for Rheumatoid Arthritis Patients
07:20Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies