利用基于人口的预测模型:慢性病人口风险工具(CDPoRT),建立跨公平因素的慢性病风险模型

Kitty Chen, Kathy Kornas, Laura C Rosella
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摘要

背景预测人口层面的慢性病发病率有助于了解未来慢性病的总体负担和预防机会。本研究旨在利用人口层面的风险预测算法估算加拿大安大略省未来的慢性病负担,并为因不利条件和歧视而在获得服务和资源方面遇到障碍的需要公平的群体建立干预模型。方法 经过验证的慢性病人口风险工具(CDPoRT)可估算主要慢性病的 10 年风险和发病率。将 CDPoRT 应用于 2017/2018 年加拿大社区健康调查的数据,以预测加拿大安大略省成年人口中到 2027/2028 年的 10 年慢性病基线估计值,以及需要公平的群体中的慢性病估计值。CDPoRT 被用于模拟在 10 年内降低 2% 和 5% 风险的预防方案,目标群体是高风险的应享公平待遇群体。结果 中学以下教育程度(37.5%)、严重食物无保障(19.5%)、低收入(21.2%)和极端工作压力(15.0%)人群的基线慢性病风险最高。CDPoRT预测,从2017/2018年到2027/2028年,安大略省将新增142万慢性病病例。将慢性病风险降低 5%,可预防中学以下教育程度人群中的 1500 例病例,预防家庭收入低人群中的 14 900 例病例,预防食品无保障人群中的 2800 例病例。在工作压力较大的人群中,将风险降低 5%,可大幅减少 57 100 例病例。结论 预计在公平定义的各种情况下,慢性病病例会大幅减少,这表明需要制定考虑到影响慢性病风险的上游决定因素的预防战略。数据可在公开、开放的资料库中查阅。加拿大社区健康调查公共使用微数据文件可在开放存取资料库()中公开获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling chronic disease risk across equity factors using a population-based prediction model: the Chronic Disease Population Risk Tool (CDPoRT)
Background Predicting chronic disease incidence at a population level can help inform overall future chronic disease burden and opportunities for prevention. This study aimed to estimate the future burden of chronic disease in Ontario, Canada, using a population-level risk prediction algorithm and model interventions for equity-deserving groups who experience barriers to services and resources due to disadvantages and discrimination. Methods The validated Chronic Disease Population Risk Tool (CDPoRT) estimates the 10-year risk and incidence of major chronic diseases. CDPoRT was applied to data from the 2017/2018 Canadian Community Health Survey to predict baseline 10-year chronic disease estimates to 2027/2028 in the adult population of Ontario, Canada, and among equity-deserving groups. CDPoRT was used to model prevention scenarios of 2% and 5% risk reductions over 10 years targeting high-risk equity-deserving groups. Results Baseline chronic disease risk was highest among those with less than secondary school education (37.5%), severe food insecurity (19.5%), low income (21.2%) and extreme workplace stress (15.0%). CDPoRT predicted 1.42 million new chronic disease cases in Ontario from 2017/2018 to 2027/2028. Reducing chronic disease risk by 5% prevented 1500 cases among those with less than secondary school education, prevented 14 900 cases among those with low household income and prevented 2800 cases among food-insecure populations. Large reductions of 57 100 cases were found by applying a 5% risk reduction in individuals with quite a bit workplace stress. Conclusion Considerable reduction in chronic disease cases was predicted across equity-defined scenarios, suggesting the need for prevention strategies that consider upstream determinants affecting chronic disease risk. Data are available in a public, open access repository. Canadian Community Health Survey Public Use Microdata File is publicly available in an open-access repository ().
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