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开发和验证儿童和青少年体脂预测模型:使用个体参与者数据的荟萃分析。

Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data.

机构信息

Population Health Research Institute, St George's, University of London, London SW17 0RE, UK.

Population, Policy and Practice Programme, UCL Great Ormond Street Institute of Child Health, London, UK.

出版信息

BMJ. 2019 Jul 24;366:l4293. doi: 10.1136/bmj.l4293.

Abstract

OBJECTIVES

To develop and validate a prediction model for fat mass in children aged 4-15 years using routinely available risk factors of height, weight, and demographic information without the need for more complex forms of assessment.

DESIGN

Individual participant data meta-analysis.

SETTING

Four population based cross sectional studies and a fifth study for external validation, United Kingdom.

PARTICIPANTS

A pooled derivation dataset (four studies) of 2375 children and an external validation dataset of 176 children with complete data on anthropometric measurements and deuterium dilution assessments of fat mass.

MAIN OUTCOME MEASURE

Multivariable linear regression analysis, using backwards selection for inclusion of predictor variables and allowing non-linear relations, was used to develop a prediction model for fat-free mass (and subsequently fat mass by subtracting resulting estimates from weight) based on the four studies. Internal validation and then internal-external cross validation were used to examine overfitting and generalisability of the model's predictive performance within the four development studies; external validation followed using the fifth dataset.

RESULTS

Model derivation was based on a multi-ethnic population of 2375 children (47.8% boys, n=1136) aged 4-15 years. The final model containing predictor variables of height, weight, age, sex, and ethnicity had extremely high predictive ability (optimism adjusted R: 94.8%, 95% confidence interval 94.4% to 95.2%) with excellent calibration of observed and predicted values. The internal validation showed minimal overfitting and good model generalisability, with excellent calibration and predictive performance. External validation in 176 children aged 11-12 years showed promising generalisability of the model (R: 90.0%, 95% confidence interval 87.2% to 92.8%) with good calibration of observed and predicted fat mass (slope: 1.02, 95% confidence interval 0.97 to 1.07). The mean difference between observed and predicted fat mass was -1.29 kg (95% confidence interval -1.62 to -0.96 kg).

CONCLUSION

The developed model accurately predicted levels of fat mass in children aged 4-15 years. The prediction model is based on simple anthropometric measures without the need for more complex forms of assessment and could improve the accuracy of assessments for body fatness in children (compared with those provided by body mass index) for effective surveillance, prevention, and management of clinical and public health obesity.

摘要

目的

开发并验证一种适用于 4-15 岁儿童的体脂预测模型,该模型使用身高、体重和人口统计学信息等常规风险因素,无需更复杂的评估形式。

设计

个体参与者数据的荟萃分析。

设置

英国的四项基于人群的横断面研究和第五项外部验证研究。

参与者

一个汇集的推导数据集(四项研究)包括 2375 名儿童和一个外部验证数据集包括 176 名儿童,他们的人体测量值和体脂的氘稀释评估数据完整。

主要观察指标

使用向后选择纳入预测变量并允许非线性关系的多变量线性回归分析,基于四项研究开发一种预测模型,用于预测无脂肪量(随后通过从体重中减去预测值来预测脂肪量)。使用内部验证,然后进行内部-外部交叉验证,以检查模型在四个开发研究中的预测性能是否存在过度拟合和普遍性;然后使用第五个数据集进行外部验证。

结果

模型推导基于一个由 2375 名 4-15 岁的多民族儿童(47.8%为男孩,n=1136)组成的人群。包含身高、体重、年龄、性别和种族等预测变量的最终模型具有极高的预测能力(乐观调整 R:94.8%,95%置信区间 94.4%至 95.2%),且观察值和预测值的校准效果极好。内部验证表明模型具有最小的过度拟合和良好的通用性,且校准和预测性能都很好。在 11-12 岁的 176 名儿童中进行的外部验证表明,该模型具有很好的通用性(R:90.0%,95%置信区间 87.2%至 92.8%),观察到的和预测到的脂肪量的校准效果也很好(斜率:1.02,95%置信区间 0.97 至 1.07)。观察到的脂肪量与预测脂肪量之间的平均差值为-1.29 千克(95%置信区间-1.62 至-0.96 千克)。

结论

该模型能够准确预测 4-15 岁儿童的体脂水平。该预测模型基于简单的人体测量指标,无需更复杂的评估形式,可提高儿童体脂评估的准确性(与体重指数相比),从而有效监测、预防和管理临床和公共卫生肥胖。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ffc/6650932/b70c23f65126/hudm049262.f1.jpg

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