Diabetes in Pregnancy: Worldwide Perspective

Lee, I-Lynn; Maple-Brown, Louise

doi:10.1007/978-3-319-90988-2_20

Cited by 1 publication

(2 citation statements)

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“…Hyperglycemia in pregnancy (HIP), inclusive of gestational diabetes and type 1 and type 2 diabetes diagnosed before or during pregnancy, is increasing both in Australia and internationally,1–4 challenging the capacity of healthcare services. The increase in HIP is directly associated with the increasing prevalence of risk factors including overweight, obesity, older maternal age and shifts in population demographics and ethnicities 2 3 5. With increasing prevalence of risk factors, service providers report that women are more frequently presenting with more complex diabetes and obstetric care needs 6.…”

Section: Introductionmentioning

confidence: 99%

“…With increasing prevalence of risk factors, service providers report that women are more frequently presenting with more complex diabetes and obstetric care needs 6. Additionally, diabetes during pregnancy increases the risk for later cardiometabolic disease for the woman3 and early onset of overweight, obesity and type 2 diabetes for her children 2 7…”

Section: Introductionmentioning

confidence: 99%

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‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling

Freebairn

Atkinson

Yang

et al. 2020

BMJ Open Diab Res Care

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IntroductionHyperglycemia in pregnancy (HIP, including gestational diabetes and pre-existing type 1 and type 2 diabetes) is increasing, with associated risks to the health of women and their babies. Strategies to manage and prevent this condition are contested. Dynamic simulation models (DSM) can test policy and program scenarios before implementation in the real world. This paper reports the development and use of an advanced DSM exploring the impact of maternal weight status interventions on incidence of HIP.MethodsA consortium of experts collaboratively developed a hybrid DSM of HIP, comprising system dynamics, agent-based and discrete event model components. The structure and parameterization drew on a range of evidence and data sources. Scenarios comparing population-level and targeted prevention interventions were simulated from 2018 to identify the intervention combination that would deliver the greatest impact.ResultsPopulation interventions promoting weight loss in early adulthood were found to be effective, reducing the population incidence of HIP by 17.3% by 2030 (baseline (‘business as usual’ scenario)=16.1%, 95% CI 15.8 to 16.4; population intervention=13.3%, 95% CI 13.0 to 13.6), more than targeted prepregnancy (5.2% reduction; incidence=15.3%, 95% CI 15.0 to 15.6) and interpregnancy (4.2% reduction; incidence=15.5%, 95% CI 15.2 to 15.8) interventions. Combining targeted interventions for high-risk groups with population interventions promoting healthy weight was most effective in reducing HIP incidence (28.8% reduction by 2030; incidence=11.5, 95% CI 11.2 to 11.8). Scenarios exploring the effect of childhood weight status on entry to adulthood demonstrated significant impact in the selected outcome measure for glycemic regulation, insulin sensitivity in the short term and HIP in the long term.DiscussionPopulation-level weight reduction interventions will be necessary to ‘turn the tide’ on HIP. Weight reduction interventions targeting high-risk individuals, while beneficial for those individuals, did not significantly impact forecasted HIP incidence rates. The importance of maintaining interventions promoting healthy weight in childhood was demonstrated.

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Section: Introductionmentioning

confidence: 99%