CoChat
Sign Up
Cited by 33Gestational Diabetes Research and ManagementMobile Health and mHealth ApplicationsMaternal and Neonatal Healthcare

Effects of mHealth-Based Lifestyle Interventions on Gestational Diabetes Mellitus in Pregnant Women With Overweight and Obesity: Systematic Review and Meta-Analysis

Open access
He, Yirong, Huang, Chuanya, He, Qiuyang, Liao, Shujuan, Luo, Biru·2024·JMIR mHealth and uHealth
DOI 10.2196/49373PMC PMC10831670

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND The increasing incidence of gestational diabetes mellitus (GDM) is a global health problem that is more likely to occur in pregnant women with overweight or obesity. Adhering to a healthy lifestyle is associated with a reduced risk of GDM. With the development of IT, mobile health (mHealth) interventions have become widely available in health care. However, there are no definitive conclusions on the effectiveness of mHealth-based lifestyle interventions in preventing GDM. OBJECTIVE This study aims to evaluate the impact of mHealth-based lifestyle interventions on GDM and other pregnancy outcomes in pregnant women with overweight or obesity. METHODS A systematic literature search was conducted in 5 English databases (MEDLINE, Embase, Web of Science, CENTRAL, and CINAHL) and 4 Chinese databases (CBM, CNKI, Vip, and Wanfang) to identify randomized controlled trials (RCTs) on the effectiveness of mHealth-based interventions for GDM from inception to January 10, 2023. In total, 2 authors independently screened the studies and extracted the data. The quality of the included studies was examined using the Cochrane risk-of-bias tool. Data synthesis was conducted using Review Manager (version 5.4; The Cochrane Collaboration). RESULTS A total of 16 RCTs with 7351 participants were included in this study. The included studies were published between 2014 and 2021 and were conducted in China, the United States, Australia, New Zealand, the United Kingdom, Ireland, and Norway. The sample sizes of the studies ranged from 75 to 2202, and the duration of the mHealth-based lifestyle interventions ranged from 4 to 28 weeks. Compared with usual care, mHealth-based lifestyle interventions significantly reduced the incidence of GDM (odds ratio [OR] 0.74, 95% CI 0.56-0.96; P=.03; I2=65%), preterm birth (OR 0.65, 95% CI 0.48-0.87; P=.004; I2=25%), macrosomia (OR 0.59, 95% CI 0.40-0.87; P=.008; I2=59%), and gestational weight gain (mean difference=−1.12 kg, 95% CI −1.44 to −0.80; P<.001; I2=43%). The subgroup analysis showed that interventions delivered via apps (OR 0.55, 95% CI 0.37-0.83; P=.004; I2=44%), provided by obstetricians (OR 0.69, 95% CI 0.51-0.93; P=.02; I2=60%), and targeted at Asian populations (OR 0.44, 95% CI 0.34-0.58; P<.001; I2=0%) and that used the International Association of Diabetes and Pregnancy Study Groups diagnostic criteria (OR 0.58, 95% CI 0.39-0.86; P=.007; I2=69%) showed a statistically significant reduction in the risk of GDM. CONCLUSIONS mHealth-based lifestyle interventions had a favorable impact on the prevention of GDM in pregnant women with overweight and obesity. Future studies need to further explore the potential of mHealth-based interventions for GDM through better design and more rigorous large-scale RCTs. CLINICALTRIAL PROSPERO International Prospective Register of Systematic Reviews CRD42021286995; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=286995

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/49373

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Health programs integrating nutrition counseling and structured exercise support showed significant gestational diabetes mellitus risk reductions in overweight and obese pregnant women compared to standard care.

    “Health programs integrating nutrition counseling and structured exercise support showed significant GDM risk reductions in overweight and obese pregnant women, compared to standard care [33].”

    From Pre-Conception Physical Activity and the Risk of Gestational Diabetes Mellitus: Findings from the BORN 2020 Study (2025) · cites this paper as [33]

    The Results (Meta-Analysis Results) report a significant GDM reduction for mHealth interventions overall, but explicitly state that the subgroup combining diet and exercise was not statistically significantly associated with reduced GDM risk (OR 0.71; P=.05). The claim attributes a significant reduction specifically to programs integrating nutrition and exercise, which the subgroup result does not support. (LLM, conf=0.88)

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 43

  1. [3]Johns EC Denison FC Norman JE Reynolds RM Gestational diabetes mellitus: mechanisms, treatment, and complications Trends Endocrinol Metab 2018 11 29 11 743 54 10.1016/j.tem.2018.09.004 30297319 S1043-2760(18)30165-6 30297319 · DOI · Paper page
  2. [5]Feghali MN Catov JM Zantow E Mission J Caritis SN Scifres CM Timing of gestational weight gain and adverse perinatal outcomes in overweight and obese women Obstet Gynecol 2019 05 133 5 962 70 10.1097/AOG.0000000000003234 30969214 00006250-201905000-00016 30969214 · DOI
  3. [6]Mengesha Kassie A Beletew Abate B Wudu Kassaw M Education and prevalence of overweight and obesity among reproductive age group women in Ethiopia: analysis of the 2016 Ethiopian demographic and health survey data BMC Public Health 2020 07 31 20 1 1189 10.1186/s12889-020-08941-w 32736617 10.1186/s12889-020-08941-w 32736617 PMC7393704 · DOI
  4. [7]Poston L Caleyachetty R Cnattingius S Corvalán C Uauy R Herring S Gillman MW Preconceptional and maternal obesity: epidemiology and health consequences Lancet Diabetes Endocrinol 2016 12 4 12 1025 36 10.1016/S2213-8587(16)30217-0 27743975 S2213-8587(16)30217-0 27743975 · DOI · Paper page
  5. [8]West S Ollila MM Franks S Piltonen T Jokelainen J Nevalainen J Puukka K Ruokonen A Järvelin MR Auvinen J Tapanainen JS Morin-Papunen L Overweight, obesity and hyperandrogenemia are associated with gestational diabetes mellitus: a follow-up cohort study Acta Obstet Gynecol Scand 2020 10 99 10 1311 9 10.1111/aogs.13883 32333801 32333801 · DOI
  6. [9]Maas VY Poels M Lamain-de Ruiter M Kwee A Bekker MN Franx A Koster MP Associations between periconceptional lifestyle behaviours and adverse pregnancy outcomes BMC Pregnancy Childbirth 2021 07 07 21 1 492 10.1186/s12884-021-03935-x 34233654 10.1186/s12884-021-03935-x 34233654 PMC8265143 · DOI · Paper page
  7. [11]Davenport MH Ruchat SM Poitras VJ Jaramillo Garcia A Gray CE Barrowman N Skow RJ Meah VL Riske L Sobierajski F James M Kathol AJ Nuspl M Marchand A Nagpal TS Slater LG Weeks A Adamo KB Davies GA Barakat R Mottola MF Prenatal exercise for the prevention of gestational diabetes mellitus and hypertensive disorders of pregnancy: a systematic review and meta-analysis Br J Sports Med 2018 11 52 21 1367 75 10.1136/bjsports-2018-099355 30337463 52/21/1367 30337463 · DOI · Paper page
  8. [13]Sherifali D Nerenberg KA Wilson S Semeniuk K Ali MU Redman LM Adamo KB The effectiveness of eHealth technologies on weight management in pregnant and postpartum women: systematic review and meta-analysis J Med Internet Res 2017 10 13 19 10 e337 10.2196/jmir.8006 29030327 v19i10e337 29030327 PMC5660296 · DOI · Paper page
  9. [14]Gu D Li T Wang X Yang X Yu Z Visualizing the intellectual structure and evolution of electronic health and telemedicine research Int J Med Inform 2019 10 130 103947 10.1016/j.ijmedinf.2019.08.007 31450080 S1386-5056(18)30677-4 31450080 · DOI
  10. [16]Reynolds RM Telehealth in pregnancy Lancet Diabetes Endocrinol 2020 06 8 6 459 61 10.1016/S2213-8587(20)30158-3 32445730 S2213-8587(20)30158-3 32445730 PMC7239612 · DOI
  11. [17]Cotie LM Prince SA Elliott CG Ziss MC McDonnell LA Mullen KA Hiremath S Pipe AL Reid RD Reed JL The effectiveness of eHealth interventions on physical activity and measures of obesity among working-age women: a systematic review and meta-analysis Obes Rev 2018 10 19 10 1340 58 10.1111/obr.12700 30156044 30156044 · DOI
  12. [18]Hutchesson MJ Rollo ME Krukowski R Ells L Harvey J Morgan PJ Callister R Plotnikoff R Collins CE eHealth interventions for the prevention and treatment of overweight and obesity in adults: a systematic review with meta-analysis Obes Rev 2015 05 16 5 376 92 10.1111/obr.12268 25753009 25753009 · DOI · Paper page
  13. [19]Frid G Bogaert K Chen KT Mobile health apps for pregnant women: systematic search, evaluation, and analysis of features J Med Internet Res 2021 10 18 23 10 e25667 10.2196/25667 34524100 v23i10e25667 34524100 PMC8561408 · DOI
  14. [20]Hayman M Alfrey KL Cannon S Alley S Rebar AL Williams S Short CE Altazan A Comardelle N Currie S Denton C Harrison CL Lamerton T Mena GP Moran L Mottola M Nagpal TS Vincze L Schoeppe S Quality, features, and presence of behavior change techniques in mobile apps designed to improve physical activity in pregnant women: systematic search and content analysis JMIR Mhealth Uhealth 2021 04 07 9 4 e23649 10.2196/23649 33825693 v9i4e23649 33825693 PMC8060865 · DOI
  15. [22]Chen H Clinical effectiveness analysis of comprehensive nursing measures for preventing gestational diabetes mellitus of women with overweight or obesity before pregnancy Chin J Fam Plan 2017 25 04 250 3 10.3969/j.issn.1004-8189.2017.04.008 · DOI
  16. [24]Tang L Jian C Yaping W Application of dietary evaluation WeChat platform in obese pregnant women's nutrition intervention Mod Med J 2019 47 05 517 21 10.3969/j.issn.1671-7562.2019.05.006 · DOI
  17. [25]Cao L Analysis of clinical effect of comprehensive nursing measures on prevention of gestational diabetes mellitus in overweight and obese pregnant women before pregnancy Guide Chin Med 2020 18 10 12 4 10.15912/j.cnki.gocm.2020.10.005 · DOI
  18. [26]Wu X Guang H Effect of individualized weight management during pregnancy based on Wechat platform on weight gain and pregnancy outcome of obese pregnant women Clin Med Res Pract 2020 5 35 65 4 10.19347/j.cnki.2096-1413.202035012 · DOI
  19. [27]Zhou H Chenru Wangqin Z Huimei D Xiaocong S Application of pre-pregnancy eugenic guidance combined with pregnancy diet plan in prevention of gestational diabetes mellitus in overweight and obese pregnant women before pregnancy Matern Child Health Care Chin 2021 36 08 1717 20 10.19829/j.zgfybj.issn.1001-4411.2021.08.004 · DOI
  20. [28]Kang L Sung A Effects of wechat dietary education management on the incidence of gestational diabetes in obese pregnant women Clin Med 2021 41 07 66 8 10.19528/j.issn.1003-3548.2021.07.024 · DOI
  21. [29]Ding B Gou B Guan H Wang J Bi Y Hong Z WeChat-assisted dietary and exercise intervention for prevention of gestational diabetes mellitus in overweight/obese pregnant women: a two-arm randomized clinical trial Arch Gynecol Obstet 2021 09 304 3 609 18 10.1007/s00404-021-05984-1 33570656 10.1007/s00404-021-05984-1 33570656 · DOI
  22. [30]Ferrara A Hedderson MM Brown SD Ehrlich SF Tsai A Feng J Galarce M Marcovina S Catalano P Quesenberry CP A telehealth lifestyle intervention to reduce excess gestational weight gain in pregnant women with overweight or obesity (GLOW): a randomised, parallel-group, controlled trial Lancet Diabetes Endocrinol 2020 06 8 6 490 500 10.1016/S2213-8587(20)30107-8 32445736 S2213-8587(20)30107-8 32445736 PMC8886506 · DOI
  23. [31]Liu J Wilcox S Wingard E Turner-McGrievy G Hutto B Burgis J A behavioral lifestyle intervention to limit gestational weight gain in pregnant women with overweight and obesity Obesity (Silver Spring) 2021 04 29 4 672 80 10.1002/oby.23119 33619910 33619910 PMC9206885 · DOI · Paper page
  24. [32]Dodd JM Turnbull D McPhee AJ Deussen AR Grivell RM Yelland LN Crowther CA Wittert G Owens JA Robinson JS LIMIT Randomised Trial Group Antenatal lifestyle advice for women who are overweight or obese: LIMIT randomised trial BMJ 2014 02 10 348 g1285 10.1136/bmj.g1285 24513442 bmj.g1285 24513442 PMC3919179 · DOI · Paper page
  25. [34]Seneviratne S Jiang Y Derraik J McCowan L Parry G Biggs J Craigie S Gusso S Peres G Rodrigues R Ekeroma A Cutfield W Hofman P Effects of antenatal exercise in overweight and obese pregnant women on maternal and perinatal outcomes: a randomised controlled trial BJOG 2016 03 06 123 4 588 97 10.1111/1471-0528.13738 26542419 26542419 · DOI · Paper page
  26. [35]Poston L Bell R Croker H Flynn AC Godfrey KM Goff L Hayes L Khazaezadeh N Nelson SM Oteng-Ntim E Pasupathy D Patel N Robson SC Sandall J Sanders TA Sattar N Seed PT Wardle J Whitworth MK Briley AL UPBEAT Trial Consortium Effect of a behavioural intervention in obese pregnant women (the UPBEAT study): a multicentre, randomised controlled trial Lancet Diabetes Endocrinol 2015 10 3 10 767 77 10.1016/S2213-8587(15)00227-2 26165396 S2213-8587(15)00227-2 26165396 · DOI · Paper page
  27. [36]Kennelly MA Ainscough K Lindsay KL O'Sullivan E Gibney ER McCarthy M Segurado R DeVito G Maguire O Smith T Hatunic M McAuliffe FM Pregnancy exercise and nutrition with smartphone application support: a randomized controlled trial Obstet Gynecol 2018 05 131 5 818 26 10.1097/AOG.0000000000002582 29630009 00006250-201805000-00010 29630009 · DOI · Paper page
  28. [37]Sagedal L Øverby NC Bere E Torstveit M Lohne-Seiler H Småstuen M Hillesund E Henriksen T Vistad I Lifestyle intervention to limit gestational weight gain: the Norwegian Fit for Delivery randomised controlled trial BJOG 2017 01 14 124 1 97 109 10.1111/1471-0528.13862 26768233 26768233 · DOI
  29. [38]Oteng-Ntim E Varma R Croker H Poston L Doyle P Lifestyle interventions for overweight and obese pregnant women to improve pregnancy outcome: systematic review and meta-analysis BMC Med 2012 05 10 10 47 10.1186/1741-7015-10-47 22574949 1741-7015-10-47 22574949 PMC3355057 · DOI · Paper page
  30. [39]Juan J Yang H Prevalence, prevention, and lifestyle intervention of gestational diabetes mellitus in China Int J Environ Res Public Health 2020 12 18 17 24 9517 10.3390/ijerph17249517 33353136 ijerph17249517 33353136 PMC7766930 · DOI
  31. [41]Farahani B Firouzi F Chakrabarty K Firouzi F Chakrabarty K Nassif S Healthcare IoT Intelligent Internet of Things: From Device to Fog and Cloud 2020 Cham, Switzerland Springer 515 45
  32. [42]Vashist SK Schneider EM Luong JH Commercial smartphone-based devices and smart applications for personalized healthcare monitoring and management Diagnostics (Basel) 2014 08 18 4 3 104 28 10.3390/diagnostics4030104 26852680 diagnostics4030104 26852680 PMC4665560 · DOI
  33. [43]Swayamsiddha S Mohanty C Application of cognitive internet of medical things for COVID-19 pandemic Diabetes Metab Syndr 2020 09 14 5 911 5 10.1016/j.dsx.2020.06.014 32570016 S1871-4021(20)30183-1 32570016 PMC7287427 · DOI
  34. [44]Super S Beulen YH Koelen MA Wagemakers A Opportunities for dietitians to promote a healthy dietary intake in pregnant women with a low socio-economic status within antenatal care practices in the Netherlands: a qualitative study J Health Popul Nutr 2021 07 31 40 1 35 10.1186/s41043-021-00260-z 34332642 10.1186/s41043-021-00260-z 34332642 PMC8325401 · DOI
  35. [45]Lim S Liang X Hill B Teede H Moran LJ O'Reilly S A systematic review and meta-analysis of intervention characteristics in postpartum weight management using the TIDieR framework: a summary of evidence to inform implementation Obes Rev 2019 07 03 20 7 1045 56 10.1111/obr.12846 30942550 30942550 · DOI
  36. [46]Escañuela Sánchez T Meaney S O'Connor C Linehan L O'Donoghue K Byrne M Matvienko-Sikar K Facilitators and barriers influencing weight management behaviours during pregnancy: a meta-synthesis of qualitative research BMC Pregnancy Childbirth 2022 09 05 22 1 682 10.1186/s12884-022-04929-z 36064379 10.1186/s12884-022-04929-z 36064379 PMC9443069 · DOI
  37. [47]Shepherd E Gomersall JC Tieu J Han S Crowther CA Middleton P Combined diet and exercise interventions for preventing gestational diabetes mellitus Cochrane Database Syst Rev 2017 11 13 11 11 CD010443 10.1002/14651858.CD010443.pub3 29129039 29129039 PMC6485974 · DOI
  38. [48]Magkos F Hjorth MF Astrup A Diet and exercise in the prevention and treatment of type 2 diabetes mellitus Nat Rev Endocrinol 2020 10 20 16 10 545 55 10.1038/s41574-020-0381-5 32690918 10.1038/s41574-020-0381-5 32690918 · DOI
  39. [49]Pu J Zhao B Wang EJ Nimbal V Osmundson S Kunz L Popat RA Chung S Palaniappan LP Racial/ethnic differences in gestational diabetes prevalence and contribution of common risk factors Paediatr Perinat Epidemiol 2015 09 29 5 436 43 10.1111/ppe.12209 26201385 26201385 PMC6519933 · DOI
  40. [50]Behboudi-Gandevani S Amiri M Bidhendi Yarandi R Ramezani Tehrani F The impact of diagnostic criteria for gestational diabetes on its prevalence: a systematic review and meta-analysis Diabetol Metab Syndr 2019 11 11 10.1186/s13098-019-0406-1 30733833 406 30733833 PMC6359830 · DOI · Paper page
  41. [51]Gete DG Waller M Mishra GD Effects of maternal diets on preterm birth and low birth weight: a systematic review Br J Nutr 2020 02 28 123 4 446 61 10.1017/S0007114519002897 31711550 S0007114519002897 31711550 · DOI
  42. [52]Fair F Soltani H A meta-review of systematic reviews of lifestyle interventions for reducing gestational weight gain in women with overweight or obesity Obes Rev 2021 05 22 5 e13199 10.1111/obr.13199 33459493 33459493 PMC8047893 · DOI
  43. [53]Lau Y Klainin-Yobas P Htun TP Wong SN Tan KL Ho-Lim ST Chi C Tsai C Ong KW Shorey S Tam WS Electronic-based lifestyle interventions in overweight or obese perinatal women: a systematic review and meta-analysis Obes Rev 2017 09 18 9 1071 87 10.1111/obr.12557 28544551 28544551 · DOI

Cited by

Sorted by citations

Authors
He, Y., Huang, C., He, Q., Liao, S., & Luo, B.
Affiliations
Sichuan University (CN)
Corresponding author
Luo, Biru
ORCID
Venue
JMIR mHealth and uHealth
Publisher
JMIR Publications Inc.
Published
2024-01-17
Volume
12
Pages
e49373
ISSN
2291-5222 (ISSN-L)
DOI
10.2196/49373
PMC
PMC10831670
OpenAlex
W4390942280
Cited by
33
References
8
Citations by year
2026: 18 · 2025: 13 · 2024: 2
FWCI
3.08
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Obstetrics and Gynecology › Gestational Diabetes Research and Management
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Health Professions › General Health Professions › Maternal and Neonatal Healthcare
Keywords
gestational diabetes mellitus, mobile health, lifestyle intervention, maternal obesity, maternal overweight, preterm birth, macrosomia, gestational weight gain, pregnancy outcomes, GDM prevention, pregnant women, mobile health apps, wearable devices, telemedicine, digital health interventions, maternal morbidity, maternal mental health, maternal nutrition, maternal physical activity, maternal sleep
MeSH terms
Female, Humans, Infant, Newborn, Life Style, Obesity, Pregnancy, Diabetes, Gestational, Telemedicine, Pregnant People, Pregnant Women, Overweight

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review