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[This corrects the article DOI: 10.1371/journal.pone.0278919.].
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BACKGROUND: Lifestyle choices, metformin, and dietary supplements may prevent GDM, but the effect of intervention characteristics has not been identified. This review evaluated intervention characteristics to inform the implementation of GDM prevention interventions. METHODS: Ovid, MEDLINE/PubMed, and EMBASE databases were searched. The Template for Intervention Description and Replication (TIDieR) framework was used to examine intervention characteristics (who, what, when, where, and how). Subgroup analysis was performed by intervention characteristics. RESULTS: 116 studies involving 40,940 participants are included. Group-based physical activity interventions (RR 0.66; 95% CI 0.46, 0.95) reduce the incidence of GDM compared with individual or mixed (individual and group) delivery format (subgroup p-value = 0.04). Physical activity interventions delivered at healthcare facilities reduce the risk of GDM (RR 0.59; 95% CI 0.49, 0.72) compared with home-based interventions (subgroup p-value = 0.03). No other intervention characteristics impact the effectiveness of all other interventions. CONCLUSIONS: Dietary, physical activity, diet plus physical activity, metformin, and myoinositol interventions reduce the incidence of GDM compared with control interventions. Group and healthcare facility-based physical activity interventions show better effectiveness in preventing GDM than individual and community-based interventions. Other intervention characteristics (e.g. utilization of e-health) don't impact the effectiveness of lifestyle interventions, and thus, interventions may require consideration of the local context.
The effect of any given intervention to prevent gestational diabetes (high blood sugar levels that arise during pregnancy) may depend on the way it is delivered (how, when, what, etc). This study reviewed published literature to investigate if the effects of interventions (diet, exercise, metformin, probiotics, myoinositol) to prevent gestational diabetes differ according to the way it is being delivered (e.g., online vs in-person, by health professionals or others, etc.). Exercise delivered to group settings, or those delivered at a healthcare facility worked better to prevent gestational diabetes. Although we did not observe any differences with other delivery characteristics (e.g., online vs in-person), it does not mean they are always equally effective, it is important to consider individual situations when prescribing or developing interventions.
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BACKGROUND: 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 responses to interventions in gestational diabetes mellitus (GDM) prevention. METHODS: 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. RESULTS: From 10347 studies, 116 studies (n = 40940 women) are included. Physical activity results 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]). Combined diet and physical activity interventions result 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 GDM history (0.62 [0.47, 0.81] vs 0.85 [0.76, 0.95]). Metformin interventions are 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 (0.21 [0.11, 0.40] vs 1.15 [0.86-1.55]). Parity, history of having a large-for-gestational-age infant or family history of diabetes have no effect on intervention responses. CONCLUSIONS: GDM prevention through metformin or lifestyle differs according to some individual characteristics. Future research should include trials commencing preconception and provide results disaggregated by a priori defined participant characteristics including social and environmental factors, clinical traits, and other novel risk factors to predict GDM prevention through interventions.
An individual's characteristics, such as medical, biochemical, social, and behavioural may affect their response to interventions aimed at preventing gestational diabetes, which occurs during pregnancy. Here, we evaluated the published literature on interventions such as diet, lifestyle, drug treatment and nutritional supplement and looked at which individual participant characteristics were associated with response to these interventions. Certain participant characteristics were associated with greater prevention of gestational diabetes through particular treatments. Some interventions were more effective when started prior to conception. Future studies should consider individual characteristics when assessing the effects of preventative measures.
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BACKGROUND: The burden of Gestational Diabetes Mellitus (GDM) is very high in south Asia (SA) and southeast Asia (SEA). Thus, there is a need to understand the prevalence and risk factors for developing prediabetes and type 2 diabetes mellitus (T2DM) postpartum, in this high-risk population. AIM: To conduct a systematic review and meta-analysis to estimate the prevalence of prediabetes and T2DM among the women with history of GDM in SA and SEA. METHODS: A comprehensive literature search was performed in the following databases: Medline, EMBASE, Web of Knowledge and CINHAL till December 2021. Studies that had reported greater than six weeks of postpartum follow-up were included. The pooled prevalence of diabetes and prediabetes were estimated by random effects meta-analysis model and I2 statistic was used to assess heterogeneity. RESULTS: Meta-analysis of 13 studies revealed that the prevalence of prediabetes and T2DM in post-GDM women were 25.9% (95%CI 18.94 to 33.51) and 29.9% (95%CI 17.02 to 44.57) respectively. Women with history of GDM from SA and SEA seem to have higher risk of developing T2DM than women without GDM (RR 13.2, 95%CI 9.52 to 18.29, p<0.001). The subgroup analysis showed a rise in the prevalence of T2DM with increasing duration of follow-up. CONCLUSION: The conversion to T2DM and prediabetes is very high among women with history of GDM in SA and SEA. This highlights the need for follow-up of GDM women for early identification of dysglycemia and to plan interventions to prevent/delay the progression to T2DM.
Subject(s)
Diabetes Mellitus, Type 2 , Diabetes, Gestational , Prediabetic State , Pregnancy , Female , Humans , Diabetes, Gestational/epidemiology , Diabetes, Gestational/etiology , Diabetes Mellitus, Type 2/epidemiology , Diabetes Mellitus, Type 2/complications , Southeast Asian People , Prediabetic State/epidemiology , Prediabetic State/complications , Risk FactorsABSTRACT
AIMS: Gestational diabetes mellitus (GDM) diagnosed during the first trimester of pregnancy is called 'early pregnancy Gestational Diabetes Mellitus' (eGDM). The burden of eGDM has only been studied sporadically. This review aims to understand the global burden of eGDM in terms of prevalence, risk factors, pregnancy outcomes, treatment and postpartum dysglycemia. METHODS: A review of epidemiologic studies reporting on early GDM screening as per Joanna Briggs Institute (JBI) methodology for prevalence reviews was conducted. A customized search strategy was used to search electronic databases namely, PubMed, CINAHL, EMBASE, Cochrane Library, Scopus, MEDLINE, Ovid, ScienceDirect, and Google Scholar. Three independent reviewers reviewed studies using Covidence software. Observational studies irrespective of study design and regardless of diagnostic criteria were included. Quality of evidence was appraised, and findings were synthesized. RESULTS: Of 58 included studies, 41 reported a prevalence of eGDM, ranging from 0.7 to 36.8%. Body mass index (BMI), previous history of GDM, family history of diabetes and multiparity were reported as eGDM risk factors. Adverse pregnancy outcomes associated with eGDM were macrosomia, caesarean delivery, induction of labour, hypertension, preterm delivery, and shoulder dystocia. The incidence of postpartum dysglycemia and the need for insulin was higher in women with eGDM. The risk of bias was moderate. Heterogeneity of studies is a limitation. Meta-analysis was not performed. CONCLUSIONS: There is heterogeneity in the prevalence of eGDM and intrapartum and postpartum ill effects for the mother and the offspring. There is a need to develop a universal screening protocol for eGDM.
