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Body mass estimation from dimensions of the fourth lumbar vertebra in middle-aged Finns

机译:中年芬兰紫杉角椎体尺寸的体重估计

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Although body mass is not a stable trait over the lifespan, information regarding body size assists the forensic identification of unknown individuals. In this study, we aimed to study the potential of using the fourth lumbar vertebra (L4) for body mass estimation among contemporary Finns. Our sample comprised 1158 individuals from the Northern Finland Birth Cohort 1966 who had undergone measurements of body mass at age 31 and 46 and lumbar magnetic resonance imaging (MRI) at age 46. MRI scans were used to measure the maximum and minimum widths, depths, and heights of the L4 body. Their means and sum were calculated together with vertebral cross-sectional area (CSA) and volume. Ordinary least squares (OLS) and reduced major axis (RMA) regression was used to produce equations for body mass among the full sample (n = 1158) and among normal weight individuals (n = 420). In our data, body mass was associated with all the L4 size parameters (R = 0.093-0.582, p <= 0.019 among the full sample; R = 0.243-0.696, p <= 0.002 among the normal-weight sample). RMA regression models seemed to fit the data better than OLS, with vertebral CSA having the highest predictive value in body mass estimation. In the full sample, the lowest standard errors were 6.1% (95% prediction interval +/- 9.6 kg) and 7.1% (+/- 9.1 kg) among men and women, respectively. In the normal-weight sample, the lowest errors were 4.9% (+/- 6.9 kg) and 4.7% (+/- 5.7 kg) among men and women, respectively. Our results indicate that L4 dimensions are potentially useful in body mass estimation, especially in cases with only the axial skeleton available.
机译:虽然体重不是稳定的特质,但是关于体型的信息有助于法医鉴定未知的个体。在这项研究中,我们旨在研究使用第四腰椎(L4)在当代芬兰人之间进行体重估计的潜力。我们的样本包括来自芬兰北部的1158人,1966年,在46岁及46岁时经历了体重的体重测量,46岁的腰部磁共振成像(MRI)。MRI扫描用于测量最大和最小宽度,深度,深度,和L4体的高度。它们的方法和总和与椎体横截面积(CSA)和体积一起计算。普通的最小二乘(OLS)和减小的长轴(RMA)回归用于在完整样品(n = 1158)和正常重量个体中产生体重的方程(n = 420)。在我们的数据中,体重与所有L4尺寸参数有关(r = 0.093-0.582,完全样品中的p <= 0.019; r = 0.243-0.696,p <= 0.002,在正常重量样品中)。 RMA回归模型似乎比OLS更好地符合OLS,椎体CSA具有最高的体重估计预测值。在完整的样本中,最低标准误差分别为6.1%(95%预测间隔+/- 9.6千克),男女和女性分别为7.1%(+/- 9.1千克)。在正常重量样品中,最低误差分别为4.9%(+/- 6.9千克),分别为男性和女性4.7%(+/- 5.7千克)。我们的结果表明,L4尺寸可能在体重估计中有用,特别是在仅可用轴向骨架的情况下。

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