A serious flaw in nutrition epidemiology: A meta-analysis study

Karl E. Peace, Jingjing Yin, Haresh Rochani, Sarbesh Pandeya, Stanley Young

Research output: Contribution to journalSystematic reviewpeer-review

5 Scopus citations

Abstract

Background: Many researchers have studied the relationship between diet and health. Specifically, there are papers showing an association between the consumption of sugar sweetened beverages and Type 2 diabetes. Many meta-analyses use individual studies that do not attempt to adjust for multiple testing or multiple modeling. Hence the claims reported in a meta-analysis paper may be unreliable as the base papers do not ensure unbiased statistics. Objective: Determine (i) the statistical reliability of 10 papers and (ii) indirectly the reliability of the metaanalysis study. Method: We obtained copies of each of the 10 papers used in a metaanalysis paper and counted the numbers of outcomes, predictors, and covariates. We estimate the size of the potential analysis search space available to the authors of these papers; i. e. the number of comparisons and models available. The potential analysis search space is the number of outcomes times the number of predictors times 2c, where c is the number of covariates. This formula was applied to information found in the abstracts (Space A) as well as the text (Space T) of each base paper. Results: The median and range of the number of comparisons possible across the base papers are 6.5 and (2 12,288), respectively for Space A, and 196,608 and (3072-117,117,952), respectively for Space T. It is noted that the median of 6.5 for Space A may be misleading as each study has 60-165 foods that could be predictors. Conclusion: Given that testing is at the 5% level and the number of comparisons is very large, nominal statistical significance is very weak support for a claim. The claims in these papers are not statistically supported and hence are unreliable so the meta-analysis paper is also unreliable.

Original languageEnglish
Article number20180079
JournalInternational Journal of Biostatistics
Volume14
Issue number2
DOIs
StatePublished - 2018

Keywords

  • Meta-analysis
  • Multiple modeling
  • Multiple testing
  • Nutritional epidemiology
  • Observational studies
  • Reliability of claims

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