Ultra-processed Food = Greater Cancer Risk

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Discussion Overview

The discussion centers on the potential link between ultra-processed food consumption and increased cancer risk, referencing a study published in the British Medical Journal. Participants explore the implications of the findings, the definitions of processed foods, and the validity of the research methodology.

Discussion Character

  • Debate/contested
  • Technical explanation
  • Exploratory

Main Points Raised

  • Some participants highlight that a 10% increase in ultra-processed food consumption correlates with a 10% increase in cancer risk over a 7.5-year study period.
  • Others argue that correlation does not imply causation, pointing out that socioeconomic status may be a confounding factor not controlled for in the study.
  • One participant notes that the study's cohort may not represent the general population due to its health-conscious and higher socioeconomic demographic.
  • Concerns are raised about the low signal-to-noise ratio of a 10% increase, suggesting that the findings may not be robust.
  • Participants express uncertainty regarding the definition of "processed" foods, indicating that it is often poorly defined and encompasses a broad range of actions.
  • One participant references a separate article discussing the reliability of published research findings, suggesting that many claims in scientific literature may be false due to various biases and methodological issues.

Areas of Agreement / Disagreement

Participants generally do not reach consensus, as there are multiple competing views regarding the interpretation of the study's findings, the definitions of processed foods, and the validity of the research methodology.

Contextual Notes

Limitations mentioned include the potential influence of socioeconomic status on the study's outcomes, the ambiguous definition of processed foods, and the implications of study design on the reliability of research findings.

Tom.G
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Correlation is not causation. One obvious confounding factor which it appears from the abstract that the authors did not control for is socioeconomic status.
 
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Ygggdrasil said:
Correlation is not causation. One obvious confounding factor which it appears from the abstract that the authors did not control for is socioeconomic status.
Agreed.
See about 60% of the way thru the report under "Strengths and limitations of study":
"Firstly, as is generally the case in volunteer based cohorts, participants in the NutriNet-Santé cohort were more often women, with health conscious behaviours and higher socio-professional and educational levels than the general French population.56"[/color] (emphasis added)[/color]

Also article footnotes 31, 32, 56.[/color]
 
A couple other things (without first reading the articles...)
10% is a really low signal to noise ratio
"Processed" is typically pretty poorly defined and a broad set of actions
 
russ_watters said:
"Processed"
My first reaction? "Dirty" stainless steel. "Dirty" meaning poorly refined/manufactured; lots of heavy metal impurities, As, Sb, and the like.
 
russ_watters said:
10% is a really low signal to noise ratio
Sure is! (About 0.4dB Signal-to-Noise Ratio. :wink:)
russ_watters said:
"Processed" is typically pretty poorly defined and a broad set of actions
Yes, again. That's why the second link is there, it points to the internationally recognized definitions.
 
Think this is an example of:

http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020124

Abstract
Summary
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research
 

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