Pianarosa Emilie, O'Neill Meghan, Kornas Kathy, Diemert Lori M, Tait Christopher, Rosella Laura C
Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada.
Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada; ICES, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada; Institute for Better Health, Trillium Health Partners, 100 Queensway West, Mississauga, ON L5B 1B8, Canada; Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, Simcoe Hall, 1 King's College Cir, Toronto, ON M5S 1A8, Canada.
Prev Med. 2023 Oct;175:107673. doi: 10.1016/j.ypmed.2023.107673. Epub 2023 Aug 18.
Obesity is a known risk factor for major chronic diseases. Prevention of chronic disease is a top global priority. The study aimed to model scenarios of population-level and targeted weight loss interventions on 10-year projected risk of chronic disease in Canada using a population-level risk prediction algorithm. The validated Chronic Disease Population Risk Tool (CDPoRT) forecasts 10-year risk of chronic disease in the adult population. We applied CDPoRT to the 2013/14 Canadian Community Health Survey to generate prospective chronic disease estimates for adults 20 years and older in Canada (n = 83,220). CDPoRT was used to model the following scenarios: British Columbia's (BC) and Quebec's (QC) provincial population-level weight reduction targets, a population-level intervention that could achieve weight loss, targeted weight loss interventions for overweight and obese groups, and the combination of a population-level and targeted weight loss intervention. We estimated chronic disease risk reductions and number of cases prevented in each scenario compared with the baseline. At baseline, we predicted an 18.4% risk and 4,151,929 new cases of chronic disease in Canada over the 10-year period. Provincial weight loss targets applied to the Canadian population estimated chronic disease reductions of 0.6% (BC) and 0.1% (QC). The population-level intervention estimated a greater reduction in risk (0.2%), compared to the targeted interventions (0.1%). The combined approach estimated a 0.3% reduction in chronic disease risk. Our modelling predicted that population-level approaches that achieve weight loss in combination with targeted weight loss interventions can substantially decrease the chronic disease burden in Canada.
肥胖是已知的主要慢性病风险因素。预防慢性病是全球首要任务。本研究旨在使用人群水平风险预测算法，模拟加拿大人群水平和针对性减肥干预对慢性病10年预测风险的影响情况。经过验证的慢性病人群风险工具（CDPoRT）可预测成年人群慢性病的10年风险。我们将CDPoRT应用于2013/14年加拿大社区健康调查，以生成加拿大20岁及以上成年人（n = 83,220）的前瞻性慢性病估计值。CDPoRT用于模拟以下情况：不列颠哥伦比亚省（BC）和魁北克省（QC）的省级人群水平减重目标、一项可实现体重减轻的人群水平干预、针对超重和肥胖群体的针对性减肥干预，以及人群水平和针对性减肥干预的组合。我们估计了每种情况下与基线相比慢性病风险降低情况及预防病例数。在基线时，我们预测加拿大在10年期间慢性病风险为18.4%，新发病例为4,151,929例。应用于加拿大人群的省级减肥目标估计慢性病风险降低0.6%（BC）和0.1%（QC）。与针对性干预（0.1%）相比，人群水平干预估计风险降低幅度更大（0.2%）。联合方法估计慢性病风险降低0.3%。我们的模型预测，实现体重减轻的人群水平方法与针对性减肥干预相结合，可大幅降低加拿大的慢性病负担。
