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晚年多系统生物风险建模:洛锡安出生队列研究 1936 年的应激负荷。

Modeling multisystem biological risk in later life: allostatic load in the Lothian birth cohort study 1936.

机构信息

Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, EH8 9JZ, UK.

出版信息

Am J Hum Biol. 2013 Jul-Aug;25(4):538-43. doi: 10.1002/ajhb.22406. Epub 2013 Jun 10.

DOI:10.1002/ajhb.22406
PMID:23754497
Abstract

OBJECTIVES

To investigate and replicate a multisystem model of biological risk, or allostatic load, in a sample of generally healthy older adults.

METHODS

Multigroup confirmatory factor analysis (MG-CFA) was applied to data from the Lothian Birth Cohort 1936 (n = 726). Blood samples were taken at a physical examination. Three markers of inflammation (fibrinogen, interleukin-6, and C-reactive protein), five metabolic markers (high- and low-density lipoprotein, body mass index, glycated hemoglobin, and triglyceride), and blood pressure (mean sitting systolic and diastolic blood pressure) were used to estimate a second-order CFA model of allostatic load. Our sample was split into those taking antihypertensive, anti-inflammatory, lipid-lowering, and diabetes medications (n = 470), and those who were not (n = 256), in order to test the stability of the CFA model across groups.

RESULTS

In the nonmedicated sample, a second-order allostatic load model showed good fit to the data. However, the second-order model failed to estimate in the medicated group. The factor correlations between blood pressure and inflammation and metabolism were smaller in magnitude in the medicated group. Invariance analysis on the first-order measurement model suggested significant differences across groups in the associations of low-density lipoprotein and HbA1c with metabolism.

CONCLUSIONS

Reliable measurement of allostatic load is possible in ageing samples free of medications but is complicated in the presence of medications. MG-CFA represents a highly versatile method for the analysis of allostatic load.

摘要

目的

在一般健康的老年人群体样本中,研究并复制生物风险(即压力负荷)的多系统模型。

方法

多群组验证性因子分析(MG-CFA)应用于洛锡安出生队列 1936 年(n = 726)的数据。在体检时采集血液样本。使用三种炎症标志物(纤维蛋白原、白细胞介素 6 和 C 反应蛋白)、五种代谢标志物(高低密度脂蛋白、体重指数、糖化血红蛋白和甘油三酯)和血压(平均坐位收缩压和舒张压)来估计压力负荷的二阶 CFA 模型。我们的样本分为服用抗高血压、抗炎、降脂和糖尿病药物的组(n = 470)和未服用药物的组(n = 256),以测试 CFA 模型在组间的稳定性。

结果

在未服用药物的样本中,二阶压力负荷模型与数据拟合良好。然而,二阶模型在服用药物的组中无法估计。在服用药物的组中,血压与炎症和代谢之间的因子相关性较小。一阶测量模型的不变性分析表明,在与代谢相关的低密度脂蛋白和 HbA1c 方面,各组之间存在显著差异。

结论

在没有药物的老年人群体样本中,压力负荷的可靠测量是可能的,但在存在药物的情况下会变得复杂。MG-CFA 是分析压力负荷的一种非常灵活的方法。

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