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Kidney Disease and Population Health

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Stratification for Confounding – Part 1: The Mantel-Haenszel Formula

Tripepi G.a · Jager K.J.b · Dekker F.W.b, c · Zoccali C.a

Author affiliations

aCNR-IBIM, Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension of Reggio Calabria, ReggioCalabria, Italy; bERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, and cDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands

Corresponding Author

Dr. Giovanni Tripepi, MSc

CNR-IBIM, Istituto di Biomedicina, Epidemiologia Clinica e Fisiopatologia

delle Malattie Renali e dell’Ipertensione Arteriosa, c/o Euroline di Ascrizzi Vincenzo

Via Vallone Petrara No. 55/57, IT–89124 Reggio Calabria (Italy)

Tel. +39 0965 397 010, Fax +39 0965 26879, E-Mail gtripepi@ibim.cnr.it

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Abstract

Stratification allows to control for confounding by creating two or more categories or subgroups in which the confounding variable either does not vary or does not vary very much. The Mantel-Haenszel formula is applied in cohort and in case-control studies to calculate an overall, unconfounded, effect estimate of a given exposure for a specific outcome by combining stratum-specific relative risks (RR) or odds ratios (OR). Stratum-specific RRs or ORs are calculated within each stratum of the confounding variable and compared with the corresponding effect estimates in the whole group (that is, with the unstratified RR or OR). The use of the Mantel-Haenszel formula presents some limitations: (1) if there is more than a single confounder, the application of this formula is laborious and demands a relatively large sample size, and (2) this method requires continuous confounders to be constrained into a limited number of categories thus potentially generating residual confounding (a phenomenon particularly relevant when the variable is categorized into few strata). In the stratified analysis, residual confounding can be minimized by increasing the number of strata, a possibility strictly dependent on sample size.

© 2010 S. Karger AG, Basel


References

  1. Jager KJ, Zoccali C, Macleod A, Dekker FW: Confounding: what it is and how to deal with it. Kidney Int 2008;73:256–260.
  2. Mantel N, Haenszel W: Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 1959;22:719–748.
  3. Szklo M, Nieto FJ: Epidemiology. Beyond the Basics. Boston, Jones & Bartlett, 2004, pp 265–273.
  4. Rothman KJ: Epidemiology. An Introduction. New York, Oxford University Press, 2002, pp 101–105, 144–158.
  5. Maldonado G, Greenland S: Simulation study of confounder-selection strategies. Am J Epidemiol 1993;138:923–936.
  6. Zoccali C, Mallamaci F, Tripepi G, Parlongo S, Cutrupi S, Benedetto FA, Bonanno G, Seminara G, Fatuzzo P, Rapisarda F, Malatino LS: Chlamydia pneumoniae, overall and cardiovascular mortality in end-stage renal disease. Kidney Int 2003;64:579–584.

Article / Publication Details

First-Page Preview
Abstract of Kidney Disease and Population Health

Published online: July 28, 2010
Issue release date: November 2010

Number of Print Pages: 1
Number of Figures: 1
Number of Tables: 4


eISSN: 1660-2110 (Online)

For additional information: https://www.karger.com/NEC

References

  1. Jager KJ, Zoccali C, Macleod A, Dekker FW: Confounding: what it is and how to deal with it. Kidney Int 2008;73:256–260.
  2. Mantel N, Haenszel W: Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 1959;22:719–748.
  3. Szklo M, Nieto FJ: Epidemiology. Beyond the Basics. Boston, Jones & Bartlett, 2004, pp 265–273.
  4. Rothman KJ: Epidemiology. An Introduction. New York, Oxford University Press, 2002, pp 101–105, 144–158.
  5. Maldonado G, Greenland S: Simulation study of confounder-selection strategies. Am J Epidemiol 1993;138:923–936.
  6. Zoccali C, Mallamaci F, Tripepi G, Parlongo S, Cutrupi S, Benedetto FA, Bonanno G, Seminara G, Fatuzzo P, Rapisarda F, Malatino LS: Chlamydia pneumoniae, overall and cardiovascular mortality in end-stage renal disease. Kidney Int 2003;64:579–584.
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