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‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling
INTRODUCTION: Hyperglycemia 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...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7265040/ https://www.ncbi.nlm.nih.gov/pubmed/32475837 http://dx.doi.org/10.1136/bmjdrc-2019-000975 |
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author | Freebairn, Louise Atkinson, Jo-an Qin, Yang Nolan, Christopher J Kent, Alison L Kelly, Paul M Penza, Luke Prodan, Ante Safarishahrbijari, Anahita Qian, Weicheng Maple-Brown, Louise Dyck, Roland McLean, Allen McDonnell, Geoff Osgood, Nathaniel D |
author_facet | Freebairn, Louise Atkinson, Jo-an Qin, Yang Nolan, Christopher J Kent, Alison L Kelly, Paul M Penza, Luke Prodan, Ante Safarishahrbijari, Anahita Qian, Weicheng Maple-Brown, Louise Dyck, Roland McLean, Allen McDonnell, Geoff Osgood, Nathaniel D |
author_sort | Freebairn, Louise |
collection | PubMed |
description | INTRODUCTION: Hyperglycemia 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. METHODS: A 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. RESULTS: Population 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. DISCUSSION: Population-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. |
format | Online Article Text |
id | pubmed-7265040 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-72650402020-06-12 ‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling Freebairn, Louise Atkinson, Jo-an Qin, Yang Nolan, Christopher J Kent, Alison L Kelly, Paul M Penza, Luke Prodan, Ante Safarishahrbijari, Anahita Qian, Weicheng Maple-Brown, Louise Dyck, Roland McLean, Allen McDonnell, Geoff Osgood, Nathaniel D BMJ Open Diabetes Res Care Epidemiology/Health Services Research INTRODUCTION: Hyperglycemia 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. METHODS: A 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. RESULTS: Population 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. DISCUSSION: Population-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. BMJ Publishing Group 2020-05-31 /pmc/articles/PMC7265040/ /pubmed/32475837 http://dx.doi.org/10.1136/bmjdrc-2019-000975 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Epidemiology/Health Services Research Freebairn, Louise Atkinson, Jo-an Qin, Yang Nolan, Christopher J Kent, Alison L Kelly, Paul M Penza, Luke Prodan, Ante Safarishahrbijari, Anahita Qian, Weicheng Maple-Brown, Louise Dyck, Roland McLean, Allen McDonnell, Geoff Osgood, Nathaniel D ‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling |
title | ‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling |
title_full | ‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling |
title_fullStr | ‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling |
title_full_unstemmed | ‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling |
title_short | ‘Turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling |
title_sort | ‘turning the tide’ on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling |
topic | Epidemiology/Health Services Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7265040/ https://www.ncbi.nlm.nih.gov/pubmed/32475837 http://dx.doi.org/10.1136/bmjdrc-2019-000975 |
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