Grilling the data: application of specification curve analysis to red meat and all-cause mortality
Wang Y, Pitre T, Wallach JD, de Souza RJ, Jassal T, Bier D, Patel CJ, Zeraatkar D
Journal of clinical epidemiology · 5 citations
Review labels
Neutral facts our review recorded about how this study was done. They describe method, never whether we like the result.
How it was studied
- Design
- Systematic review (indexed by PubMed)
- Studied in
- People
- Main outcome
- Clinical events such as disease or death
- Intake measured by
- Not stated
Who paid for it
- Funding
- Possibly industry funded
- University or hospital
- Yale University
- Company
- Arnold Ventures
- Government
- National Institutes of Health
- Government
- U.S. Food and Drug Administration
- Government
- National Institute on Alcohol Abuse and Alcoholism
- Government
- National Institute of Environmental Health Sciences
- Government
- NIAAA NIH HHS
- Government
- NIEHS NIH HHS
- Authors
- At least one author declares a financial tie to industry
- Grants
- National Institute of Environmental Health Sciences (R01 ES032470); National Institute on Alcohol Abuse and Alcoholism (K01 AA028258); National Institutes of Health (1K01AA028258)
Based on 8 listed funder(s) and full-text disclosure statement.
Publication
- Published
- 2024-02-12 · J Clin Epidemiol · vol. 168 · p. 111278
- Publisher
- Elsevier BV
- Cited
- 12 citations · more than 95% of similar papers · 4.6× the field average
- Impact
- Top 10% most cited in its field
- References
- 52 works
- Access
- Open access (hybrid journal) · CC-BY-NC-ND
- Research areas
- Nutritional Studies and Diet · Agriculture Sustainability and Environmental Impact · Meat and Animal Product Quality
- Keywords
- Covariate, Statistics, Hazard ratio, Hazard, Observational study, Quantile, Medicine, Red meat, Specification, Epidemiology, Hazard analysis, Econometrics, Computer science, Mathematics, Internal medicine, Pathology, Engineering, Confidence interval, Reliability engineering, Biology
- MeSH
- humans, nutrition surveys, mortality, cause of death, data interpretation, statistical, female, male, observational studies as topic, red meat
8 authors
From US, CA
- Yumin WangHarvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Tyler PitreHarvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Joshua David WallachHarvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Russell J. de SouzaHarvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Tanvir JassalHarvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Dennis M. BierHarvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
Abstract
Objectives
To present an application of specification curve analysis-a novel analytic method that involves defining and implementing all plausible and valid analytic approaches for addressing a research question-to nutritional epidemiology.
Study design and setting
We reviewed all observational studies addressing the effect of red meat on all-cause mortality, sourced from a published systematic review, and documented variations in analytic methods (eg, choice of model, covariates, etc.). We enumerated all defensible combinations of analytic choices to produce a comprehensive list of all the ways in which the data may reasonably be analyzed. We applied specification curve analysis to data from National Health and Nutrition Examination Survey 2007 to 2014 to investigate the effect of unprocessed red meat on all-cause mortality. The specification curve analysis used a random sample of all reasonable analytic specifications we sourced from primary studies.
Results
Among 15 publications reporting on 24 cohorts included in the systematic review on red meat and all-cause mortality, we identified 70 unique analytic methods, each including different analytic models, covariates, and operationalizations of red meat (eg, continuous vs quantiles). We applied specification curve analysis to National Health and Nutrition Examination Survey, including 10,661 participants. Our specification curve analysis included 1208 unique analytic specifications, of which 435 (36.0%) yielded a hazard ratio equal to or more than 1 for the effect of red meat on all-cause mortality and 773 (64.0%) less than 1. The specification curve analysis yielded a median hazard ratio of 0.94 (interquartile range: 0.83-1.05). Forty-eight specifications (3.97%) were statistically significant, 40 of which indicated unprocessed red meat to reduce all-cause mortality and eight of which indicated red meat to increase mortality.
Conclusion
We show that the application of specification curve analysis to nutritional epidemiology is feasible and presents an innovative solution to analytic flexibility.
Abstract via Europe PMC. Copyright remains with the authors or publisher (CC BY-NC-ND).
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