详细的三维身体形态特征可预测身体成分、血液代谢物和功能强度：Shape Up! 研究。
Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies.
机构信息
University of Hawaii Cancer Center, Honolulu, HI, USA.
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
出版信息
Am J Clin Nutr. 2019 Dec 1;110(6):1316-1326. doi: 10.1093/ajcn/nqz218.
BACKGROUND
Three-dimensional optical (3DO) body scanning has been proposed for automatic anthropometry. However, conventional measurements fail to capture detailed body shape. More sophisticated shape features could better indicate health status.
OBJECTIVES
The objectives were to predict DXA total and regional body composition, serum lipid and diabetes markers, and functional strength from 3DO body scans using statistical shape modeling.
METHODS
Healthy adults underwent whole-body 3DO and DXA scans, blood tests, and strength assessments in the Shape Up! Adults cross-sectional observational study. Principal component analysis was performed on registered 3DO scans. Stepwise linear regressions were performed to estimate body composition, serum biomarkers, and strength using 3DO principal components (PCs). 3DO model accuracy was compared with simple anthropometric models and precision was compared with DXA.
RESULTS
This analysis included 407 subjects. Eleven PCs for each sex captured 95% of body shape variance. 3DO body composition accuracy to DXA was: fat mass R2 = 0.88 male, 0.93 female; visceral fat mass R2 = 0.67 male, 0.75 female. 3DO body fat test-retest precision was: root mean squared error = 0.81 kg male, 0.66 kg female. 3DO visceral fat was as precise (%CV = 7.4 for males, 6.8 for females) as DXA (%CV = 6.8 for males, 7.4 for females). Multiple 3DO PCs were significantly correlated with serum HDL cholesterol, triglycerides, glucose, insulin, and HOMA-IR, independent of simple anthropometrics. 3DO PCs improved prediction of isometric knee strength (combined model R2 = 0.67 male, 0.59 female; anthropometrics-only model R2 = 0.34 male, 0.24 female).
CONCLUSIONS
3DO body shape PCs predict body composition with good accuracy and precision comparable to existing methods. 3DO PCs improve prediction of serum lipid and diabetes markers, and functional strength measurements. The safety and accessibility of 3DO scanning make it appropriate for monitoring individual body composition, and metabolic health and functional strength in epidemiological settings.This trial was registered at clinicaltrials.gov as NCT03637855.
背景
三维光学（3DO）身体扫描已被提议用于自动人体测量。然而，传统的测量方法无法捕捉到详细的身体形状。更复杂的形状特征可以更好地指示健康状况。
目的
本研究旨在使用统计形状建模，从 3DO 身体扫描中预测 DXA 全身和局部身体成分、血清脂质和糖尿病标志物以及功能强度。
方法
在“Shape Up！成人横断面观察性研究”中，健康成年人接受全身 3DO 和 DXA 扫描、血液测试和力量评估。对已注册的 3DO 扫描进行主成分分析。使用 3DO 主成分（PC）进行逐步线性回归，以估计身体成分、血清生物标志物和强度。将 3DO 模型的准确性与简单的人体测量模型进行比较，并与 DXA 的精度进行比较。
结果
本分析纳入了 407 名受试者。每个性别有 11 个 PC 捕获了 95%的身体形状方差。3DO 身体成分的 DXA 准确性为：男性脂肪质量 R2=0.88，女性 R2=0.93；男性内脏脂肪质量 R2=0.67，女性 R2=0.75。3DO 身体脂肪的测试-重测精度为：均方根误差=男性 0.81kg，女性 0.66kg。男性 3DO 内脏脂肪的精度与 DXA 相当（%CV=7.4，女性 6.8），女性 3DO 内脏脂肪的精度与 DXA 相当（%CV=6.8，女性 7.4）。多个 3DO PC 与血清高密度脂蛋白胆固醇、甘油三酯、葡萄糖、胰岛素和 HOMA-IR 显著相关，独立于简单的人体测量。3DO PC 改善了等长膝关节力量的预测（综合模型 R2=男性 0.67，女性 0.59；仅人体测量模型 R2=男性 0.34，女性 0.24）。
结论
3DO 体型 PC 可以很好地预测身体成分，准确性和精度与现有方法相当。3DO PC 可以改善血清脂质和糖尿病标志物以及功能强度测量的预测。3DO 扫描的安全性和可及性使其适合在流行病学环境中监测个体身体成分和代谢健康及功能强度。本试验在 clinicaltrials.gov 注册为 NCT03637855。
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