Nicola Orsini, Susanna C. Larsson, Georgia Salanti
Characterizing the change in the risk of a health-related outcome according to the levels of an exposure is increasingly popular in systematic reviews. We provide an introduction to the statistical methods currently used to perform linear and nonlinear dose–response analysis based on aggregated data from multiple studies. We explain how dose–response associations are estimated within a study and summarized across studies. A re-analysis of observational studies about coffee consumption and mortality is used to illustrate how to move beyond a linear dose–response trend, and the complexity of making inference on risk ratios when using restricted cubic splines.
There are currently no corrections for this chapter.
See practicals below.
R script and Stata do file for the analysis presented in Chapter 14
Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
Susanna C. Larsson
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
How to cite this chapter?
For the printed version of the book
Orsini, N., Larsson, S.C. and Salanti, G. (2022). Chapter 14. Dose–response meta-analysis. In: Systematic Reviews in Health Research: Meta-analysis in Context (eds M. Egger, J.P.T. Higgins and G. Davey Smith), pp 258-269. Hoboken, NJ : Wiley.
For the electronic version of the book
Orsini, N., Larsson, S.C. and Salanti, G. (2022). Chapter 14. Dose–response meta-analysis. In: Systematic Reviews in Health Research: Meta-analysis in Context (eds M. Egger, J.P.T. Higgins and G. Davey Smith). https://doi.org/10.1002/9781119099369.ch14