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 citas
Etiquetas de revisión
Vínculos de autores con la industriaDatos neutrales que nuestra revisión registró sobre cómo se hizo este estudio. Describen el método, nunca si nos gusta el resultado.
Cómo se estudió
- Diseño
- Revisión sistemática (indexado por PubMed)
- Estudiado en
- Personas
- Resultado principal
- Eventos clínicos como enfermedad o muerte
- Consumo medido con
- No se indica
Quién lo pagó
- Financiación
- Posiblemente financiado por la industria
- Universidad u hospital
- Yale University
- Empresa
- Arnold Ventures
- Gobierno
- National Institutes of Health
- Gobierno
- U.S. Food and Drug Administration
- Gobierno
- National Institute on Alcohol Abuse and Alcoholism
- Gobierno
- National Institute of Environmental Health Sciences
- Gobierno
- NIAAA NIH HHS
- Gobierno
- NIEHS NIH HHS
- Autores
- Al menos un autor declara un vínculo económico con la industria
- Subvenciones
- National Institute of Environmental Health Sciences (R01 ES032470); National Institute on Alcohol Abuse and Alcoholism (K01 AA028258); National Institutes of Health (1K01AA028258)
Según 8 financiadores declarados y la declaración de financiación del texto completo.
Publicación
- Publicado
- 2024-02-12 · J Clin Epidemiol · vol. 168 · pág. 111278
- Editorial
- Elsevier BV
- Citado
- 12 citas · más que el 95% de estudios similares · 4.6× el promedio de su campo
- Impacto
- Entre el 10 % más citado de su campo
- Referencias
- 52 trabajos
- Acceso
- Acceso abierto (revista híbrida) · CC-BY-NC-ND
- Áreas de investigación
- Nutritional Studies and Diet · Agriculture Sustainability and Environmental Impact · Meat and Animal Product Quality
- Palabras clave
- 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 autores
- Yumin Wang🇺🇸🇨🇦Harvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Tyler Pitre🇺🇸🇨🇦Harvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Joshua David Wallach🇺🇸🇨🇦Harvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Russell J. de Souza🇺🇸🇨🇦Harvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Tanvir Jassal🇺🇸🇨🇦Harvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Dennis M. Bier🇺🇸🇨🇦Harvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Chirag J. Patel🇺🇸🇨🇦Harvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
- Dena Zeraatkar🇺🇸🇨🇦Harvard University; Emory University; Baylor College of Medicine; Impact; McMaster University
Resumen
El texto original del estudio, en el idioma en que se publicó.
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.
Resumen vía Europe PMC. Los derechos de autor siguen siendo de los autores o la editorial (CC BY-NC-ND).
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