title: A new approach to age-period-cohort analysis using partial least squares regression: the trend in blood pressure in the Glasgow Alumni cohort.
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.
authors.affiliation: Division of Biostatistics, Centre for Epidemiology & Biostatistics, University of Leeds, Leeds, United Kingdom. y.k.tu@leeds.ac.uk
authors.forename: Yu-Kang
authors.initials: YK
authors.lastname: Tu
authors.forename: George
authors.initials: G
authors.lastname: Davey Smith
authors.forename: Mark S
authors.initials: MS
authors.lastname: Gilthorpe
mesh_terms: D001794:Blood Pressure; D015331:Cohort Studies; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D008297:Male; D012606:Scotland