Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies
Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies
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DOI：
10.1093/ajcn/nqz218
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发表时间：
2019-12-01
影响因子：
7.1
通讯作者：
Shepherd, John A.
中科院分区：
文献类型：
--
作者：
Ng, Bennett K.;Sommer, Markus J.;Shepherd, John A.
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，传统的测量无法捕捉详细的身体形状。更复杂的形状特征可以更好地指示健康状况。目标：目标是使用统计形状模型通过 3DO 身体扫描预测 DXA 总体和局部身体成分、血脂和糖尿病标志物以及功能强度。方法：健康成年人在 Shape Up! 中接受全身 3DO 和 DXA 扫描、血液测试和力量评估！成人横断面观察研究。对配准的 3DO 扫描进行主成分分析。使用 3DO 主成分 (PC) 进行逐步线性回归来估计身体成分、血清生物标志物和强度。 3DO 模型的准确性与简单的人体测量模型进行比较，精确度与 DXA 进行比较。结果：该分析包括 407 名受试者。每个性别的 11 个 PC 捕获了 95% 的体型差异。 DXA 的 3DO 身体成分准确度为：脂肪量 R-2 = 0.88 男性，0.93 女性；内脏脂肪量 R-2 = 0.67 男性，0.75 女性。 3DO体脂重测精度为：均方根误差=男性0.81公斤，女性0.66公斤。 3DO 内脏脂肪与 DXA（男性%CV = 7.4，女性 6.8）一样精确（男性%CV = 7.4，女性 7.4）。多个 3DO PC 与血清 HDL 胆固醇、甘油三酯、葡萄糖、胰岛素和 HOMAIR 显着相关，独立于简单的人体测量学。 3DO PC 改进了对等长膝关节力量的预测（组合模型 R-2 = 0.67 男性，0.59 女性；纯人体测量模型 R-2 = 0.34 男性，0.24 女性）。结论：3DO 体型 PC 预测身体成分的准确度和精密度与现有方法相当。 3DO PC 改进了血脂和糖尿病标记物的预测以及功能强度测量。 3DO 扫描的安全性和可访问性使其适合在流行病学环境中监测个人身体成分、代谢健康和功能强度。
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 R-2 = 0.88 male, 0.93 female; visceral fat mass R-2 = 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 HOMAIR, independent of simple anthropometrics. 3DO PCs improved prediction of isometric knee strength (combined model R-2 = 0.67 male, 0.59 female; anthropometrics-only model R-2 = 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.