Cargando…
Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model
We developed a model to compare the impacts of different lifestyle interventions among prediabetes individuals and to identify the optimal age groups for such interventions. A stochastic simulation was developed to replicate the prediabetes and diabetes trends (1997–2010) in the U.S. adult populatio...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695408/ https://www.ncbi.nlm.nih.gov/pubmed/31417128 http://dx.doi.org/10.1038/s41598-019-48312-z |
_version_ | 1783444032779714560 |
---|---|
author | Khademi, Amin Shi, Lu Nasrollahzadeh, Amir Ali Narayanan, Hariharaprabhu Chen, Liwei |
author_facet | Khademi, Amin Shi, Lu Nasrollahzadeh, Amir Ali Narayanan, Hariharaprabhu Chen, Liwei |
author_sort | Khademi, Amin |
collection | PubMed |
description | We developed a model to compare the impacts of different lifestyle interventions among prediabetes individuals and to identify the optimal age groups for such interventions. A stochastic simulation was developed to replicate the prediabetes and diabetes trends (1997–2010) in the U.S. adult population. We then simulated the population-wide impacts of three lifestyle diabetes prevention programs, i.e., the Diabetes Prevention Program (DPP), DPP-YMCA, and the Healthy Living Partnerships to Prevent Diabetes (HELP-PD), over a course of 10, 15 and 30 years. Our model replicated the temporal trends of diabetes in the U.S. adult population. Compared to no intervention, the diabetes incidence declined 0.3 per 1,000 by DPP, 0.2 by DPP-YMCA, and 0.4 by HELP-PD over the 15-year period. Our simulations identified HELP-PD as the most cost-effective intervention, which achieved the highest 10-year savings of $38 billion for those aged 25–65, assuming all eligible individuals participate in the intervention and considering intervention achievement rates. Our model simulates the diabetes trends in the U.S. population based on individual-level longitudinal data. However, it may be used to identify the optimal intervention for different subgroups in defined populations. |
format | Online Article Text |
id | pubmed-6695408 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66954082019-08-19 Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model Khademi, Amin Shi, Lu Nasrollahzadeh, Amir Ali Narayanan, Hariharaprabhu Chen, Liwei Sci Rep Article We developed a model to compare the impacts of different lifestyle interventions among prediabetes individuals and to identify the optimal age groups for such interventions. A stochastic simulation was developed to replicate the prediabetes and diabetes trends (1997–2010) in the U.S. adult population. We then simulated the population-wide impacts of three lifestyle diabetes prevention programs, i.e., the Diabetes Prevention Program (DPP), DPP-YMCA, and the Healthy Living Partnerships to Prevent Diabetes (HELP-PD), over a course of 10, 15 and 30 years. Our model replicated the temporal trends of diabetes in the U.S. adult population. Compared to no intervention, the diabetes incidence declined 0.3 per 1,000 by DPP, 0.2 by DPP-YMCA, and 0.4 by HELP-PD over the 15-year period. Our simulations identified HELP-PD as the most cost-effective intervention, which achieved the highest 10-year savings of $38 billion for those aged 25–65, assuming all eligible individuals participate in the intervention and considering intervention achievement rates. Our model simulates the diabetes trends in the U.S. population based on individual-level longitudinal data. However, it may be used to identify the optimal intervention for different subgroups in defined populations. Nature Publishing Group UK 2019-08-15 /pmc/articles/PMC6695408/ /pubmed/31417128 http://dx.doi.org/10.1038/s41598-019-48312-z Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Khademi, Amin Shi, Lu Nasrollahzadeh, Amir Ali Narayanan, Hariharaprabhu Chen, Liwei Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model |
title | Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model |
title_full | Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model |
title_fullStr | Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model |
title_full_unstemmed | Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model |
title_short | Comparing the Lifestyle Interventions for Prediabetes: An Integrated Microsimulation and Population Simulation Model |
title_sort | comparing the lifestyle interventions for prediabetes: an integrated microsimulation and population simulation model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695408/ https://www.ncbi.nlm.nih.gov/pubmed/31417128 http://dx.doi.org/10.1038/s41598-019-48312-z |
work_keys_str_mv | AT khademiamin comparingthelifestyleinterventionsforprediabetesanintegratedmicrosimulationandpopulationsimulationmodel AT shilu comparingthelifestyleinterventionsforprediabetesanintegratedmicrosimulationandpopulationsimulationmodel AT nasrollahzadehamirali comparingthelifestyleinterventionsforprediabetesanintegratedmicrosimulationandpopulationsimulationmodel AT narayananhariharaprabhu comparingthelifestyleinterventionsforprediabetesanintegratedmicrosimulationandpopulationsimulationmodel AT chenliwei comparingthelifestyleinterventionsforprediabetesanintegratedmicrosimulationandpopulationsimulationmodel |