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Evaluating community-driven cardiovascular health policy changes in the United States using agent-based modeling.
Garney, Whitney R; Panjwani, Sonya; Garcia, Kristen; Szucs, Leigh E; Primm, Kristin; McLeroy, Kenneth; Li, Yan.
Afiliação
  • Garney WR; Department of Health and Kinesiology, Texas A&M University, 2929 Research Parkway, College Station, TX, 77843, USA. wrgarney@tamu.edu.
  • Panjwani S; Department of Health and Kinesiology, Texas A&M University, 2929 Research Parkway, College Station, TX, 77843, USA.
  • Garcia K; Department of Health and Kinesiology, Texas A&M University, 2929 Research Parkway, College Station, TX, 77843, USA.
  • Szucs LE; Department of Health and Kinesiology, Texas A&M University, 2929 Research Parkway, College Station, TX, 77843, USA.
  • Primm K; Department of Health and Kinesiology, Texas A&M University, 2929 Research Parkway, College Station, TX, 77843, USA.
  • McLeroy K; Center for Community Health Development, Texas A&M University, 1266 TAMU, College Station, TX, 77843, USA.
  • Li Y; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, 1770 Madison Avenue, New York, NY, 10035, USA.
J Public Health Policy ; 43(1): 40-53, 2022 Mar.
Article em En | MEDLINE | ID: mdl-35145216
ABSTRACT
Comprehensive smoke-free policy is a strategy to prevent cardiovascular disease (CVD) at a population-level; however, evaluating their long-term outcomes is difficult. This study used an agent-based model to estimate long-term impacts of a comprehensive smoke-free policy, as it was implemented in two communities, Arlington and Mesquite, Texas. The model predicted the percentage of myocardial infarction (MI), stroke, and diabetes in the population 10 and 20 years following policy adoption. In Arlington, the percentage of the population with these conditions each decreased by approximately 0.5% over 20 years; in Mesquite, the percentage of the population with diabetes, myocardial infarction (MI), and stroke decreased by 1.1%, 0.6%, and 0.3%, respectively, after 20 years. The results were statistically significant (p < 0.001). As an evaluation strategy, agent-based modeling can help researchers and practitioners estimate the potential long-term effects of policies and garner intervention support for implementation.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Política Antifumo País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Política Antifumo País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos