Journal Article

Flexible Meta-Regression Functions for Modeling Aggregate Dose-Response Data, with an Application to Alcohol and Mortality

Vincenzo Bagnardi, Antonella Zambon, Piero Quatto and Giovanni Corrao

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 159, issue 11, pages 1077-1086
Published in print June 2004 | ISSN: 0002-9262
Published online June 2004 | e-ISSN: 1476-6256 | DOI: http://dx.doi.org/10.1093/aje/kwh142
Flexible Meta-Regression Functions for Modeling Aggregate Dose-Response Data, with an Application to Alcohol and Mortality

More Like This

Show all results sharing this subject:

  • Public Health and Epidemiology

GO

Show Summary Details

Preview

In this paper, the authors describe fractional polynomials and cubic splines with which to represent smooth dose-response relations in summarizing meta-analytical aggregate data. Use of these two curve-fitting families can help prevent the problems arising from inappropriate linearity assumptions. These methods are illustrated in the problem of estimating the shape of the dose-response curve between alcohol consumption and all-cause mortality risk. The authors considered aggregate data from 29 cohort studies investigating this issue (1966–2000). J-shaped curves with a nadir at approximately 5–7 g/day of alcohol consumption and a last protective dose of 47–60 g/day were consistently obtained from fractional polynomials and cubic splines. The authors conclude that both of the curve-fitting families are useful tools with which to explore dose-response epidemiologic questions by means of meta-analytical approaches, especially when important nonlinearity is anticipated.

Keywords: alcohol drinking; dose-response; meta-analysis; mortality; polynomial regression; regression analysis; spline smoothing; Abbreviations: AIC, Akaike’s Information Criterion; CI, confidence interval; RR, relative risk.

Journal Article.  7256 words.  Illustrated.

Subjects: Public Health and Epidemiology

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.