Suppr超能文献

使用同时自我报告或先前测量的身高和体重预测体重指数

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

作者信息

Cui Zhaohui, Stevens June, Truesdale Kimberly P, Zeng Donglin, French Simone, Gordon-Larsen Penny

机构信息

Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.

Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.

出版信息

PLoS One. 2016 Nov 29;11(11):e0167288. doi: 10.1371/journal.pone.0167288. eCollection 2016.

Abstract

OBJECTIVE

To compare alternative models for the imputation of BMIM (measured weight in kilograms/measured height in meters squared) in a longitudinal study.

METHODS

We used data from 11,008 adults examined at wave III (2001-2002) and wave IV (2007-2008) in the National Longitudinal Study of Adolescent to Adult Health. Participants were asked their height and weight before being measured. Equations to predict wave IV BMIM were developed in an 80% random subsample and evaluated in the remaining participants. The validity of models that included BMI constructed from previously measured height and weight (BMIPM) was compared to the validity of models that used BMI calculated from concurrently self-reported height and weight (BMISR). The usefulness of including demographics and perceived weight category in those models was also examined.

RESULTS

The model that used BMISR, compared to BMIPM, as the only variable produced a larger R2 (0.913 vs. 0.693), a smaller root mean square error (2.07 vs. 3.90 kg/m2) and a lower bias between normal-weight participants and those with obesity (0.98 vs. 4.24 kg/m2). The performance of the model containing BMISR alone was not substantially improved by the addition of demographics, perceived weight category or BMIPM.

CONCLUSIONS

Our work is the first to show that concurrent self-reports of height and weight may be more useful than previously measured height and weight for imputation of missing BMIM when the time interval between measures is relatively long. Other time frames and alternatives to in-person collection of self-reported data need to be examined.

摘要

目的

在一项纵向研究中比较估算体重指数(体重以千克为单位/身高以米的平方为单位)的替代模型。

方法

我们使用了来自全国青少年至成人健康纵向研究中第三波(2001 - 2002年)和第四波(2007 - 2008年)检查的11008名成年人的数据。参与者在测量前被询问了他们的身高和体重。在80%的随机子样本中开发预测第四波体重指数的方程,并在其余参与者中进行评估。将包含根据先前测量的身高和体重构建的体重指数(BMIPM)的模型的有效性与使用根据同时自我报告的身高和体重计算的体重指数(BMISR)的模型的有效性进行比较。还检查了在这些模型中纳入人口统计学和感知体重类别是否有用。

结果

与BMIPM相比,将BMISR作为唯一变量的模型产生了更大的R²(0.913对0.693)、更小的均方根误差(2.07对3.90千克/平方米)以及正常体重参与者与肥胖参与者之间更低的偏差(0.98对4.24千克/平方米)。单独包含BMISR的模型的性能并未因添加人口统计学、感知体重类别或BMIPM而得到实质性改善。

结论

我们的研究首次表明,当测量间隔时间相对较长时,对于估算缺失的体重指数,同时自我报告的身高和体重可能比先前测量的身高和体重更有用。需要研究其他时间框架以及亲自收集自我报告数据的替代方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8791/5127553/b0a259ec25e0/pone.0167288.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验