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Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling

INTRODUCTION: Healthy People 2010 (HP 2010) objectives call for a 38% reduction in the prevalence of diagnosed diabetes mellitus, type 1 and type 2, by the year 2010. The process for setting this objective, however, did not focus on the achievability or the compatibility of this objective with other...

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Autores principales: Milstein, Bobby, Jones, Andrew, Homer, Jack B, Murphy, Dara, Essien, Joyce, Seville, Don
Formato: Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1955415/
https://www.ncbi.nlm.nih.gov/pubmed/17572956
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author Milstein, Bobby
Jones, Andrew
Homer, Jack B
Murphy, Dara
Essien, Joyce
Seville, Don
author_facet Milstein, Bobby
Jones, Andrew
Homer, Jack B
Murphy, Dara
Essien, Joyce
Seville, Don
author_sort Milstein, Bobby
collection PubMed
description INTRODUCTION: Healthy People 2010 (HP 2010) objectives call for a 38% reduction in the prevalence of diagnosed diabetes mellitus, type 1 and type 2, by the year 2010. The process for setting this objective, however, did not focus on the achievability or the compatibility of this objective with other national public health objectives. We used a dynamic simulation model to explore plausible trajectories for diabetes prevalence in the wake of rising levels of obesity in the U.S. population. The model helps to interpret historic trends in diabetes prevalence in the United States and to anticipate plausible future trends through 2010. METHODS: We conducted simulation experiments using a computer model of diabetes population dynamics to 1) track the rates at which people develop diabetes, are diagnosed with the disease, and die, and 2) assess the effects of various preventive-care interventions. System dynamics modeling methodology based on data from multiple sources guided the analyses. RESULTS: With the number of new cases of diabetes being much greater than the number of deaths among those with the disease, the prevalence of diagnosed diabetes in the United States is likely to continue to increase. Even a 29% reduction in the number of new cases (the HP 2010 objective) would only slow the growth, not reverse it. Increased diabetes detection rates or decreased mortality rates — also HP 2010 objectives — would further increase diagnosed prevalence. CONCLUSION: The HP 2010 objective for reducing diabetes prevalence is unattainable given the historical processes that are affecting incidence, diagnosis, and mortality, and even a zero-growth future is unlikely. System dynamics modeling shows why interventions to protect against chronic diseases have only gradual effects on their diagnosed prevalence.
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spelling pubmed-19554152007-09-17 Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling Milstein, Bobby Jones, Andrew Homer, Jack B Murphy, Dara Essien, Joyce Seville, Don Prev Chronic Dis Original Research INTRODUCTION: Healthy People 2010 (HP 2010) objectives call for a 38% reduction in the prevalence of diagnosed diabetes mellitus, type 1 and type 2, by the year 2010. The process for setting this objective, however, did not focus on the achievability or the compatibility of this objective with other national public health objectives. We used a dynamic simulation model to explore plausible trajectories for diabetes prevalence in the wake of rising levels of obesity in the U.S. population. The model helps to interpret historic trends in diabetes prevalence in the United States and to anticipate plausible future trends through 2010. METHODS: We conducted simulation experiments using a computer model of diabetes population dynamics to 1) track the rates at which people develop diabetes, are diagnosed with the disease, and die, and 2) assess the effects of various preventive-care interventions. System dynamics modeling methodology based on data from multiple sources guided the analyses. RESULTS: With the number of new cases of diabetes being much greater than the number of deaths among those with the disease, the prevalence of diagnosed diabetes in the United States is likely to continue to increase. Even a 29% reduction in the number of new cases (the HP 2010 objective) would only slow the growth, not reverse it. Increased diabetes detection rates or decreased mortality rates — also HP 2010 objectives — would further increase diagnosed prevalence. CONCLUSION: The HP 2010 objective for reducing diabetes prevalence is unattainable given the historical processes that are affecting incidence, diagnosis, and mortality, and even a zero-growth future is unlikely. System dynamics modeling shows why interventions to protect against chronic diseases have only gradual effects on their diagnosed prevalence. Centers for Disease Control and Prevention 2007-06-15 /pmc/articles/PMC1955415/ /pubmed/17572956 Text en
spellingShingle Original Research
Milstein, Bobby
Jones, Andrew
Homer, Jack B
Murphy, Dara
Essien, Joyce
Seville, Don
Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling
title Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling
title_full Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling
title_fullStr Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling
title_full_unstemmed Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling
title_short Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling
title_sort charting plausible futures for diabetes prevalence in the united states: a role for system dynamics simulation modeling
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1955415/
https://www.ncbi.nlm.nih.gov/pubmed/17572956
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