Research Synthesis Methods

Empirical evaluation of meta‐analytic approaches for nutrient and health outcome dose‐response data

Journal Article

  • Author(s): Winifred W. Yu, Christopher H. Schmid, Alice H. Lichtenstein, Joseph Lau, Thomas A. Trikalinos
  • Article first published online: 21 Jun 2013
  • DOI: 10.1002/jrsm.1084
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The objective of this study is to empirically compare alternative meta‐analytic methods for combining dose‐response data from epidemiological studies. We identified meta‐analyses of epidemiological studies that analyzed the association between a single nutrient and a dichotomous outcome. For each topic, we performed meta‐analyses of odds ratios with five approaches: using extreme exposure categories only, two‐step approach (first calculated study‐specific effects then combined across studies) using unadjusted data, two‐step approach using adjusted data, one‐step approach (analyzed all data in one regression model) using unadjusted data, and one‐step approach using adjusted data. Meta‐analyses including only extreme exposure categories gave consistently bigger effects and wider confidence intervals than meta‐analyses using all data. Confidence intervals of effect sizes were generally wider in meta‐analyses with the two‐step approach, compared with the one‐step approach. Meta‐analyses using unadjusted data and adjusted data differed, with no consistent pattern of discordance in direction, statistical significance, or magnitude of effect. We discourage using meta‐analysis approaches that only use data from extreme exposure categories. The one‐step approach generally has higher precision than the two‐step approach. Sensitivity analysis comparing results between meta‐analyses of adjusted and unadjusted data may be useful in indicating the presence of confounding. Copyright © 2013 John Wiley & Sons, Ltd.

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