Advanced analytical methodologies for measuring healthy ageing and its determinants, using factor analysis and machine learning techniques: the ATHLOS project.
Advanced analytical methodologies for measuring healthy ageing and its determinants, using factor analysis and machine learning techniques: the ATHLOS project.
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DOI：
10.1038/srep43955
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发表时间：
2017-03-10
影响因子：
4.6
通讯作者：
Panagiotakos DB
中科院分区：
文献类型：
--
作者：
Caballero FF;Soulis G;Engchuan W;Sánchez-Niubó A;Arndt H;Ayuso-Mateos JL;Haro JM;Chatterji S;Panagiotakos DB
对参与老龄化研究的科学家来说，一项最具挑战性的任务是制定一项衡量标准，以量化不同人群和不同时间的健康状况。在本研究中，贝叶斯多层次的项目反应理论的方法是用来创建一个健康评分，可以在不同的波在纵向研究中进行比较，使用锚项目和项目，在不同的波。同样的方法可以应用于比较不同纵向研究的健康评分，使用不同研究的项目。数据来自英国老龄化纵向研究（艾尔莎）。使用混合效应多水平回归和机器学习方法来确定社会人口统计学与所创建的健康评分之间的关系。健康指标是为参与前六波艾尔莎中至少一波的17，886名受试者（54.6%的女性）创建的，与已知的影响健康的条件相关。未来的努力将在一个协调的数据集，包括几个纵向研究老龄化实施这种方法。这将使临床和社区居住人群之间的有效比较，并有助于产生规范，可能是有用的日常临床实践。
A most challenging task for scientists that are involved in the study of ageing is the development of a measure to quantify health status across populations and over time. In the present study, a Bayesian multilevel Item Response Theory approach is used to create a health score that can be compared across different waves in a longitudinal study, using anchor items and items that vary across waves. The same approach can be applied to compare health scores across different longitudinal studies, using items that vary across studies. Data from the English Longitudinal Study of Ageing (ELSA) are employed. Mixed-effects multilevel regression and Machine Learning methods were used to identify relationships between socio-demographics and the health score created. The metric of health was created for 17,886 subjects (54.6% of women) participating in at least one of the first six ELSA waves and correlated well with already known conditions that affect health. Future efforts will implement this approach in a harmonised data set comprising several longitudinal studies of ageing. This will enable valid comparisons between clinical and community dwelling populations and help to generate norms that could be useful in day-to-day clinical practice.