Transfusion Technology Assessment, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands.
Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands.
Transfus Med. 2023 Apr;33(2):113-122. doi: 10.1111/tme.12902. Epub 2022 Aug 9.
Serum ferritin levels are increasingly being used to assess iron stores. Considerable variation in ferritin levels within and between individuals has been observed, but our current understanding of factors that explain this variation is far from complete. We aim to combine multiple potential determinants in an integrative model, and investigate their relative importance and potential interactions.
We use ferritin measurements collected by Sanquin Blood Bank on both prospective (N = 59 596) and active blood donors (N = 78 318) to fit a structural equation model with three latent constructs (individual characteristics, donation history, and environmental factors). Parameters were estimated separately by sex and donor status.
The model explained 25% of ferritin variance in prospective donors, and 40% in active donors. Individual characteristics and donation history were the most important determinants of ferritin levels in active donors. The association between environmental factors and ferritin was smaller but still substantial; higher exposure to air pollution was associated with higher ferritin levels, and this association was considerably stronger for active blood donors than for prospective donors.
In active donors, individual characteristics explain 20% (17%) of ferritin variation, donation history explains 14% (25%) and environmental factors explain 5% (4%) for women (men). Our model presents known ferritin determinants in a broader perspective, allowing for comparison with other determinants as well as between new and active donors, or between men and women.
血清铁蛋白水平越来越多地被用于评估铁储存量。个体内和个体间的铁蛋白水平存在很大差异,但我们对解释这种差异的因素的理解还远远不够。我们旨在将多个潜在的决定因素纳入一个综合模型,并研究它们的相对重要性和潜在的相互作用。
我们使用 Sanquin 血液银行在前瞻性(N=59596)和活跃献血者(N=78318)中收集的铁蛋白测量值来拟合一个具有三个潜在结构的结构方程模型(个体特征、献血史和环境因素)。参数按性别和献血者状态分别估计。
该模型解释了前瞻性献血者铁蛋白变异的 25%,在活跃献血者中解释了 40%。个体特征和献血史是活跃献血者铁蛋白水平的最重要决定因素。环境因素与铁蛋白的关联虽然较小,但仍然相当大;更高的空气污染暴露与更高的铁蛋白水平相关,而且这种关联在活跃献血者中比在前瞻性献血者中要强得多。
在活跃献血者中,个体特征解释了铁蛋白变异的 20%(17%),献血史解释了 14%(25%),环境因素解释了 5%(4%),女性(男性)。我们的模型从更广泛的角度呈现了已知的铁蛋白决定因素,允许与其他决定因素以及新献血者和活跃献血者之间、男性和女性之间进行比较。