Bruyère Research Institute, 43 Bruyère Street, Ottawa, ON, K1N 5C8, Canada.
Ottawa Hospital Research Institute, Ottawa Hospital - Civic Campus, 1053 Carling Ave Box 693, 2-005 Admin Services Building, Ottawa, ON, K1Y 4E9, Canada.
Can J Public Health. 2019 Feb;110(1):52-57. doi: 10.17269/s41997-018-0109-7. Epub 2018 Jul 23.
Population Health Intervention Research (PHIR) is an expanding field that explores the health effects of population-level interventions conducted within and outside of the health sector. Simulation modeling-the use of mathematical models to predict health outcomes in populations given a set of specified inputs-is a useful, yet underutilized tool for PHIR. It can be employed at several phases of the research process: (1) planning and designing PHIR studies; (2) implementation; and (3) knowledge translation of findings across settings and populations. Using the example of community-wide, built environment interventions for the prevention of type 2 diabetes, we demonstrate how simulation models can be a powerful technique for chronic disease prevention research within PHIR. With increasingly available data on chronic disease risk factors and outcomes, the use of simulation modeling in PHIR for chronic disease prevention is anticipated to grow. There is a continued need to ensure models are appropriately validated and researchers should be cautious in their interpretation of model outputs given the uncertainties that are inherent with simulation modeling approaches. However, given the complexity of disease pathways and methodological challenges of PHIR studies, simulation models can be a valuable tool for researchers studying population interventions that hold the potential to improve health and reduce health inequities.
人群健康干预研究（PHIR）是一个不断发展的领域，它探讨了在卫生部门内外实施的人群层面干预措施对健康的影响。模拟建模——使用数学模型根据一组特定的输入预测人群中的健康结果——是 PHIR 的一种有用但未充分利用的工具。它可以在研究过程的几个阶段使用：（1）规划和设计 PHIR 研究；（2）实施；（3）在不同环境和人群中对研究结果进行知识转化。我们以预防 2 型糖尿病的全社区建筑环境干预为例，展示了模拟模型如何成为 PHIR 中慢性病预防研究的有力技术。随着慢性病危险因素和结果数据的日益丰富，预计在 PHIR 中使用模拟建模进行慢性病预防的情况将会增加。需要不断确保模型得到适当验证，并且鉴于模拟建模方法固有的不确定性，研究人员在解释模型输出时应谨慎。然而，考虑到疾病途径的复杂性和 PHIR 研究的方法学挑战，模拟模型可以为研究人群干预措施的研究人员提供有价值的工具，这些干预措施有可能改善健康状况并减少健康不平等。
