Flexible meta-regression functions for modeling aggregate dose-response data, with an application to alcohol and mortality

Vincenzo Bagnardi, Antonella Zambon, Piero Quatto, Giovanni Corrao

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)1077-1086
Number of pages10
JournalAmerican Journal of Epidemiology
Volume159
Issue number11
DOIs
Publication statusPublished - Jun 1 2004

Keywords

  • Alcohol drinking
  • Dose-response
  • Meta-analysis
  • Mortality
  • Polynomial regression
  • Regression analysis
  • Spline smoothing

ASJC Scopus subject areas

  • Epidemiology

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