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一种使用偏最小二乘回归的年龄-时期-队列分析新方法:格拉斯哥校友队列中血压的趋势。

A new approach to age-period-cohort analysis using partial least squares regression: the trend in blood pressure in the Glasgow Alumni cohort.

机构信息

Division of Biostatistics, Centre for Epidemiology & Biostatistics, University of Leeds, Leeds, United Kingdom.

出版信息

PLoS One. 2011 Apr 27;6(4):e19401. doi: 10.1371/journal.pone.0019401.

Abstract

Due to a problem of identification, how to estimate the distinct effects of age, time period and cohort has been a controversial issue in the analysis of trends in health outcomes in epidemiology. In this study, we propose a novel approach, partial least squares (PLS) analysis, to separate the effects of age, period, and cohort. Our example for illustration is taken from the Glasgow Alumni cohort. A total of 15,322 students (11,755 men and 3,567 women) received medical screening at the Glasgow University between 1948 and 1968. The aim is to investigate the secular trends in blood pressure over 1925 and 1950 while taking into account the year of examination and age at examination. We excluded students born before 1925 or aged over 25 years at examination and those with missing values in confounders from the analyses, resulting in 12,546 and 12,516 students for analysis of systolic and diastolic blood pressure, respectively. PLS analysis shows that both systolic and diastolic blood pressure increased with students' age, and students born later had on average lower blood pressure (SBP: -0.17 mmHg/per year [95% confidence intervals: -0.19 to -0.15] for men and -0.25 [-0.28 to -0.22] for women; DBP: -0.14 [-0.15 to -0.13] for men; -0.09 [-0.11 to -0.07] for women). PLS also shows a decreasing trend in blood pressure over the examination period. As identification is not a problem for PLS, it provides a flexible modelling strategy for age-period-cohort analysis. More emphasis is then required to clarify the substantive and conceptual issues surrounding the definitions and interpretations of age, period and cohort effects.

摘要

由于识别问题,如何估计年龄、时期和队列的独特影响一直是流行病学中健康结果趋势分析中的一个有争议的问题。在这项研究中,我们提出了一种新的方法,偏最小二乘法(PLS)分析,以分离年龄、时期和队列的影响。我们的示例取自格拉斯哥校友队列。共有 15322 名学生(11755 名男性和 3567 名女性)在 1948 年至 1968 年间在格拉斯哥大学接受了医学筛查。目的是研究血压在 1925 年和 1950 年的长期趋势,同时考虑到检查年份和检查时的年龄。我们从分析中排除了出生于 1925 年之前或检查时年龄超过 25 岁的学生以及混杂因素中存在缺失值的学生,因此分别有 12546 名和 12516 名学生用于分析收缩压和舒张压。PLS 分析表明,收缩压和舒张压均随学生年龄的增长而升高,而出生较晚的学生平均血压较低(男性 SBP:每增加 1 岁收缩压降低 0.17mmHg[95%置信区间:0.19 至 0.15];女性 SBP:每增加 1 岁收缩压降低 0.25[-0.28 至 -0.22];男性 DBP:每增加 1 岁舒张压降低 0.14[-0.15 至 -0.13];女性 DBP:每增加 1 岁舒张压降低 0.09[-0.11 至 -0.07])。PLS 还显示血压在检查期间呈下降趋势。由于 PLS 不存在识别问题,因此它为年龄-时期-队列分析提供了一种灵活的建模策略。因此,需要更加重视澄清围绕年龄、时期和队列效应的定义和解释的实质性和概念性问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d01/3083444/a6a0612db326/pone.0019401.g001.jpg

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