{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:50:01Z","timestamp":1783039801978,"version":"3.54.6"},"posted":{"date-parts":[[2023,4,17]]},"group-title":"Endocrinology (including Diabetes Mellitus and Metabolic Disease)","reference-count":41,"publisher":"openRxiv","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2023,4,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background and aims<\/jats:title>\n                  <jats:p>Precision prevention involves using the unique characteristics of a particular group to determine their responses to preventive interventions. This study aimed to systematically evaluate the participant characteristics associated with interventions in gestational diabetes mellitus (GDM) prevention.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We searched MEDLINE, EMBASE, and Pubmed to identify lifestyle (diet, physical activity, or both), metformin, myoinositol\/inositol and probiotics interventions of GDM prevention published up to May 24, 2022.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>From 10347 studies, 116 studies (n=40940 women) were included. Physical activity resulted in greater GDM reduction in participants with a normal body mass index (BMI) at baseline compared to obese BMI (risk ratio, 95% confidence interval: 0.06 [0.03, 0.14] vs 0.68 [0.26, 1.60]). Diet and physical activity interventions resulted in greater GDM reduction in participants without polycystic ovary syndrome (PCOS) than those with PCOS (0.62 [0.47, 0.82] vs 1.12 [0.78-1.61]) and in those without a history of GDM than those with unspecified history (0.62 [0.47, 0.81] vs 0.85 [0.76, 0.95]). Metformin interventions were more effective in participants with PCOS than those with unspecified status (0.38 [0.19, 0.74] vs 0.59 [0.25, 1.43]), or when commenced preconception than during pregnancy (0.22 [0.11, 0.45] vs 1.15 [0.86-1.55]). Parity, history of having a large-for-gestational-age infant or family history of diabetes had no effect.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>GDM prevention through metformin or lifestyle differs according to some individual characteristics. Future research should include trials commencing preconception and provide results stratified by participant characteristics including social and environmental factors, clinical traits, and other novel risk factors to predict GDM prevention through interventions.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Plain language summary<\/jats:title>\n                  <jats:p>Precision prevention involves using a group\u2019s unique context to determine their responses to preventive interventions. This study aimed to evaluate the participant characteristics associated with interventions in GDM prevention. We searched medical literature databases to identify lifestyle (diet, physical activity), metformin, myoinositol\/inositol and probiotics interventions. A total of 116 studies (n=40903 women) were included. Diet and physical activity interventions resulted in greater GDM reduction in participants without polycystic ovary syndrome (PCOS) and those without a history of GDM. Metformin interventions resulted in greater GDM reduction in participants with PCOS or when started during the preconception period. Future research should include trials starting in the preconception period, and provide results stratified by participant characteristics to predict GDM prevention through interventions.<\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2023.04.16.23288650","type":"posted-content","created":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T02:30:18Z","timestamp":1681785018000},"source":"Crossref","is-referenced-by-count":5,"title":["A systematic review and meta-analysis of participant characteristics in the prevention of gestational diabetes: a summary of evidence for precision medicine"],"prefix":"10.64898","author":[{"given":"Siew","family":"Lim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wubet Worku","family":"Takele","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kimberly K","family":"Vesco","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leanne","family":"Redman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"ADA PMDI GDM prevention working group","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jami","family":"Josefson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2023042106050836000_2023.04.16.23288650v1.1","doi-asserted-by":"publisher","DOI":"10.2337\/diab.29.12.1023"},{"key":"2023042106050836000_2023.04.16.23288650v1.2","doi-asserted-by":"crossref","unstructured":"Zhang Y , Xiao CM , Zhang Y , Chen Q , Zhang XQ , Li XF , et al. Factors Associated with Gestational Diabetes Mellitus: A Meta-Analysis. 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