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Estimating population attributable fractions to quantify the health burden of obesity

机译:估计人群可归因的比例以量化肥胖的健康负担

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Purpose: Obesity is a highly prevalent condition in the United States and elsewhere and is associated with increased mortality and morbidity. Here, we discuss some issues involved in quantifying the health burden of obesity using population attributable fraction (PAF) estimates and provide examples. Methods: We searched PubMed for articles reporting attributable fraction estimates for obesity. We reviewed eligible articles to identify methodological concerns and tabulated illustrative examples of PAF estimates for obesity relative to cancer, diabetes, cardiovascular disease, and all-cause mortality. Results: There is considerable variability among studies regarding the methods used for PAF calculation and the selection of appropriate counterfactuals. The reported estimates ranged from 5% to 15% for all-cause mortality,-0.2% to 8% for all-cancer incidence, 7% to 44% for cardiovascular disease incidence, and 3% to 83% for diabetes incidence. Conclusions: To evaluate a given estimate, it is important to consider whether the exposure and outcome were defined similarly for the PAF and for the relative risks, whether the relative risks were suitable for the population at hand, and whether PAF was calculated using correct methods. Strong causal assumptions are not necessarily warranted. In general, PAFs for obesity may be best considered as indicators of association.
机译:目的:肥胖症在美国和其他地区非常普遍,与死亡率和发病率增加有关。在这里,我们讨论使用人口归因分数(PAF)估算来量化肥胖的健康负担所涉及的一些问题,并提供示例。方法:我们在PubMed中搜索了报告可归因于肥胖的比例估计的文章。我们审查了符合条件的文章,以确定方法论上的关注点,并列出了PAF估计的相对于癌症,糖尿病,心血管疾病和全因死亡率的肥胖症示例。结果:在研究PAF计算方法和选择合适的反事实方面,研究之间存在很大差异。据报道,估计的全因死亡率为5%至15%,全癌发病率为-0.2%至8%,心血管疾病发病率为7%至44%,糖尿病发病率为3%至83%。结论:要评估给定的估计值,重要的是要考虑PAF和相对风险的暴露和结局是否类似地定义,相对风险是否适合手头人群以及PAF是否使用正确的方法计算。不一定要有强有力的因果假设。一般而言,肥胖的PAFs最好被视为关联的指标。

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