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Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents.体重指数与全因死亡率:四大洲239项前瞻性研究的个体参与者数据荟萃分析
Lancet. 2016 Aug 20;388(10046):776-86. doi: 10.1016/S0140-6736(16)30175-1. Epub 2016 Jul 13.
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BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants.体重指数与全因死亡率:对230项队列研究的系统评价和非线性剂量反应荟萃分析,3030万参与者中有374万人死亡。
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Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants.1975年至2014年200个国家成人身体质量指数的趋势:对1698项基于人群测量研究的汇总分析,涉及1920万参与者。
Lancet. 2016 Apr 2;387(10026):1377-1396. doi: 10.1016/S0140-6736(16)30054-X.
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Revealing the burden of obesity using weight histories.利用体重史揭示肥胖负担。
Proc Natl Acad Sci U S A. 2016 Jan 19;113(3):572-7. doi: 10.1073/pnas.1515472113. Epub 2016 Jan 4.
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Sex-age-specific association of body mass index with all-cause mortality among 12.8 million Korean adults: a prospective cohort study.1280万韩国成年人中体重指数与全因死亡率的性别年龄特异性关联:一项前瞻性队列研究
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Long-Term BMI Trajectories and Health in Older Adults: Hierarchical Clustering of Functional Curves.老年人的长期体重指数轨迹与健康:功能曲线的层次聚类
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Using maximum weight to redefine body mass index categories in studies of the mortality risks of obesity.使用最大体重重新定义肥胖死亡率研究中的体重指数类别。
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Obesity and mortality risk: new findings from body mass index trajectories.肥胖与死亡率风险:体重指数轨迹的新发现。
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验证一种体重史汇总指标以对肥胖的健康后果进行建模。

Validating a summary measure of weight history for modeling the health consequences of obesity.

作者信息

Stokes Andrew, Ni Yu

机构信息

Department of Global Health and Center for Global Health and Development, Boston University School of Public Health, Boston, MA.

Department of Epidemiology, University of Washington, Seattle.

出版信息

Ann Epidemiol. 2016 Dec;26(12):821-826.e2. doi: 10.1016/j.annepidem.2016.10.005. Epub 2016 Oct 26.

DOI:10.1016/j.annepidem.2016.10.005
PMID:27894565
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5142761/
Abstract

PURPOSE

Data on weight history may enhance the predictive validity of epidemiologic models of the health risks of obesity, but collecting such data is often not feasible. In this study, we investigate the validity of a summary measure of weight history.

METHODS

We evaluated the quality of reporting of maximum weight in a sample of adults aged 50-84 years using data from the Health and Retirement Study. Recalled max body mass index (BMI, measured in kilogram per square meter) based on recalled weight in 2004 was compared with calculated max BMI based on self-reported weight collected biennially between 1992 and 2004. Logistic regression was used to assess similarity between the measures in predicting prevalent conditions.

RESULTS

The correlation coefficient between recalled and calculated max weight in the overall sample was 0.95. Recalled max BMI value was within three BMI units of the calculated value 91.4% of the time. The proportions of individuals with obese I (BMI: 30.0-34.9), obese II (BMI: 35.0-39.9), and obese III (BMI: 40.0 and above) were 28.8%, 12.7%, and 6.6% using recalled values compared with 27.1%, 10.5%, and 4.9% using calculated values. In multivariate analyses, the two BMI measures similarly predicted disease prevalence across a number of chronic conditions.

CONCLUSIONS

Recalled max BMI was strongly correlated with max BMI calculated over the 12-year period before recall, suggesting that this measure can serve as a reliable summary measure of recent weight status.

摘要

目的

体重历史数据可能会提高肥胖健康风险流行病学模型的预测效度,但收集此类数据往往不可行。在本研究中,我们调查了一种体重历史简易测量方法的效度。

方法

我们使用健康与退休研究的数据,评估了50 - 84岁成年人样本中最大体重的报告质量。将基于2004年回忆体重得出的回忆最大体重指数(BMI,单位为千克每平方米)与基于1992年至2004年每两年收集一次的自我报告体重计算得出的最大BMI进行比较。使用逻辑回归评估这些测量方法在预测流行疾病方面的相似性。

结果

总体样本中回忆的和计算出的最大体重之间的相关系数为0.95。回忆的最大BMI值在91.4%的时间内与计算值相差三个BMI单位以内。使用回忆值时,I度肥胖(BMI:30.0 - 34.9)、II度肥胖(BMI:35.0 - 39.9)和III度肥胖(BMI:40.0及以上)个体的比例分别为28.8%、12.7%和6.6%,而使用计算值时分别为27.1%、10.5%和4.9%。在多变量分析中,两种BMI测量方法对多种慢性病患病率的预测相似。

结论

回忆的最大BMI与回忆前12年计算得出的最大BMI高度相关,表明该测量方法可作为近期体重状况的可靠简易测量方法。