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Currently submitted to: Journal of Medical Internet Research

Date Submitted: Jul 15, 2026
Open Peer Review Period: Jul 16, 2026 - Sep 10, 2026
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Effects of digital health interventions on gestational weight gain: a systematic review and meta-analysis of randomized controlled trials with subgroup analyses

  • Qin Deng; 
  • Xinye Shi; 
  • Zhilin Jiang; 
  • Yuhong Zeng; 
  • Dan Liu; 
  • Peijing Yan; 
  • Min Zhang

ABSTRACT

Background:

Excessive gestational weight gain (GWG) is associated with a range of adverse maternal and neonatal outcomes. Digital health interventions (DHIs) are increasingly used in prenatal care, but their effectiveness for GWG management remains uncertain, and the factors that may influence intervention effects have not been fully clarified.

Objective:

This systematic review and meta-analysis aimed to examine the effectiveness of DHIs on GWG outcomes during pregnancy.

Methods:

We conducted a systematic review and meta-analysis of randomized controlled trials evaluating DHIs for GWG management during pregnancy. PubMed, Embase, Medline, Cochrane CENTRAL, and ClinicalTrials.gov were searched from inception to January 16, 2026. Primary outcomes included total GWG, weekly GWG, and excessive GWG according to Institute of Medicine recommendations. Random-effects models were used to pool mean differences (MDs) and risk ratios (RRs) with 95% confidence intervals (CIs). Prespecified subgroup analyses explored potential effect modifiers, including pre-pregnancy body mass index (BMI), gestational age at intervention initiation, geographic region, and gestational diabetes mellitus (GDM) status.

Results:

Forty randomized controlled trials involving 8,178 pregnant women were included. Compared with usual care, DHIs significantly reduced total GWG (MD = −0.68 kg, 95%CI = −1.11 to −0.25) and weekly GWG (MD = −0.05 kg/week, 95%CI = −0.09 to −0.02). DHIs also reduced the risk of excessive GWG (RR = 0.85, 95%CI = 0.77 to 0.94). Subgroup analyses showed that DHIs reduced total GWG by −1.34 kg (95%CI = −1.69 to −1.02) among women with pre-pregnancy overweight or obesity, whereas no significant reduction was observed among mixed BMI women. Regarding intervention timing, HDIs initiated at or before 20 weeks’ gestation yielded significant reductions in weekly GWG and risk of excessive GWG. Conversely, initiating DHIs after 20 weeks showed greater reductions in total GWG. Geographically, DHIs significantly lowered total GWG in Europe and Asia, but no such effect was observed in North America. Meta-regression analyses did not identify significant linear associations between pre-pregnancy BMI and GWG outcomes. Sensitivity analyses supported the robustness of the findings, although publication bias was detected.

Conclusions:

DHIs can achieve modest but significant improvements in GWG management during pregnancy and may help reduce the likelihood of excessive GWG. The benefits appear more evident among women with pre-pregnancy overweight or obesity and in interventions initiated earlier in pregnancy. Given their accessibility and scalability, DHIs may represent a useful complement to routine prenatal care, although further high-quality large-scale trials are still needed to refine intervention strategies and determine the most effective implementation approaches.


 Citation

Please cite as:

Deng Q, Shi X, Jiang Z, Zeng Y, Liu D, Yan P, Zhang M

Effects of digital health interventions on gestational weight gain: a systematic review and meta-analysis of randomized controlled trials with subgroup analyses

JMIR Preprints. 15/07/2026:107184

DOI: 10.2196/preprints.107184

URL: https://preprints.jmir.org/preprint/107184

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