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Age–period–cohort analysis of chronic disease rates. I: modelling approach

✍ Scribed by Chris Robertson; Peter Boyle

Publisher: John Wiley and Sons
Year: 1998
Tongue: English
Weight: 163 KB
Volume: 17
Category: Article
ISSN: 0277-6715
DOI: 10.1002/(sici)1097-0258(19980630)17:12<1305::aid-sim853>3.0.co;2-w

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✦ Synopsis

Age-Period-cohort models are widely used by epidemiologists to analyse trends in disease incidence and mortality. The interpretation of such models is fraught with difficulty in view of the exact linear dependency between the three variables. It is the purpose of this paper to review, compare and contrast some of the more common approaches to this problem based on Poisson regression and a linear model for the log rates. Also the results of using the different approaches on a single series of data on breast cancer incidence among females in Scotland from 1960-1989 are presented for comparison. Recommendations as to the merits and drawbacks of the approaches are also given in the conclusions. Models which are based upon the estimable contrasts such as local curvatures and deviations from linearity are most suitable.

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✍ Niels Keiding 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 43 KB

In the above paper the authors give a well-balanced set of recommendations concerning graphical analysis of age}period}cohort variation of disease (or other) rates. For the historical record it may be pointed out that the usefulness of graphical approaches to age}period}cohort variations of mortalit