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 language | English |
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Pages (from-to) | 1077-1086 |
Number of pages | 10 |
Journal | American Journal of Epidemiology |
Volume | 159 |
Issue number | 11 |
DOIs | |
Publication status | Published - Jun 1 2004 |
Keywords
- Alcohol drinking
- Dose-response
- Meta-analysis
- Mortality
- Polynomial regression
- Regression analysis
- Spline smoothing
ASJC Scopus subject areas
- Epidemiology