When does brain aging accelerate? Dangers of quadratic fits in cross-sectional studies
When does brain aging accelerate? Dangers of quadratic fits in cross-sectional studies
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DOI：
10.1016/j.neuroimage.2010.01.061
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发表时间：
2010-05-01
期刊：
影响因子：
5.7
通讯作者：
Dale, Anders M.
中科院分区：
文献类型：
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作者：
Fjell, Anders M.;Walhovd, Kristine B.;Dale, Anders M.
许多大脑结构显示出复杂的、非线性的成熟模式和与年龄相关的变化。通常，二次模型（beta（0）+ beta（1）年龄+ beta（2）年龄（2）+ β）被用来描述这种关系。在这里，我们证明了二次模型的拟合在很大程度上受到看似不相关的因素的影响，例如采样的年龄范围。测量了434名8至85岁的健康参与者的海马体积，并将二次模型拟合到不同年龄范围的样本子集。结果发现，随着年龄范围的底部增加，出现峰值的年龄向上移动，估计在年龄跨度的最后一部分下降变得更大。因此，儿童是否包括在内影响到60至85岁之间的估计下降。我们的结论是，应谨慎推断年龄轨迹的全球拟合模型，如二次模型。非参数局部平滑技术（平滑样条）被认为是更强大的不同的起始年龄的影响。结果在309名参与者的独立样本中重复。(C)2010年爱思唯尔公司All rights reserved.
Many brain structures show a complex, non-linear pattern of maturation and age-related change. Often, quadratic models (beta(0) + beta(1)age + beta(2)age(2) + epsilon) are used to describe such relationships. Here, we demonstrate that the fitting of quadratic models is substantially affected by seemingly irrelevant factors, such as the age-range sampled. Hippocampal volume was measured in 434 healthy participants between 8 and 85 years of age, and quadratic models were fit to subsets of the sample with different age-ranges. It was found that as the bottom of the age-range increased, the age at which volumes appeared to peak was moved upwards and the estimated decline in the last part of the age-span became larger. Thus, whether children were included or not affected the estimated decline between 60 and 85 years. We conclude that caution should be exerted in inferring age-trajectories from global fit models, e.g. the quadratic model. A nonparametric local smoothing technique (the smoothing spline) was found to be more robust to the effects of different starting ages. The results were replicated in an independent sample of 309 participants. (C) 2010 Elsevier Inc. All rights reserved.