I only wish I had the time and focus to do this myself. Instead, hats off to Nicholas Chartres, Alice Fabbri, and Lisa A. Bero. From JAMA Internal Medicine, “Association of Industry Sponsorship With Outcomes of Nutrition Studies“:
Importance Food industry sponsorship of nutrition research may bias research reports, systematic reviews, and dietary guidelines.
Objective To determine whether food industry sponsorship is associated with effect sizes, statistical significance of results, and conclusions of nutrition studies with findings that are favorable to the sponsor and, secondarily, to determine whether nutrition studies differ in their methodological quality depending on whether they are industry sponsored.
Data Sources OVID MEDLINE, PubMed, Web of Science, and Scopus from inception until October 2015; the reference lists of included reports.
Study Selection Reports that evaluated primary research studies or reviews and that quantitatively compared food industry–sponsored studies with those that had no or other sources of sponsorship.
Data Extraction Two reviewers independently extracted data from each report and rated its quality using the ratings of the Oxford Centre for Evidence-Based Medicine, ranging from a highest quality rating of 1 to a lowest of 5.
Main Outcomes and Measures Results (statistical significance and effect size) favorable to the sponsor and conclusions favorable to the sponsor. If data were appropriate for meta-analysis, we used an inverse variance DerSimonian-Laird random-effects model.
Every time I write about a nutrition study, someone screams “BIAS!” at me. At least, they do when they don’t like the results. It is assumed, and not totally without merit, that when industry sponsors studies, they get the results they prefer. These intrepid researchers searched the medical literature for research studies and reviews that explored whether food industry sponsorship was related to whether the results were favorable to that company. They extracted data from all of the studies and also graded them on their quality.
So awesome.
They reviewed 775 reports, and 12 of them met criteria for inclusion.
- Two of them looked at food industry sponsorship and the statistical significance of results; neither found any.
- One looked at food industry sponsorship and effect size, and found that when industry sponsored studies looking at the harm of soft drinks with weight and energy intake, the harmful effects were smaller than when the studies were not sponsored by industry.
- Eight reports, analyzing 340 studies, tested associations between industry sponsorship and authors’ conclusions. The differences found were not statistically significant overall.
- Five reports looked at whether industry sponsorship was associated with methodological quality, and did not find an association.
- There was insufficient evidence to assess the quantitative effect of industry sponsorship on nutrition research results and quality.
This is where things get fascinating. If I were to summarize this, I would say:
A meta-analysis of eight reports that tested whether industry sponsorship affected author’s conclusions did not find a statistically significant relationship. Reports could also not find a relationship between industry sponsorship and the quality of studies or whether the results were statistically significant. One report found that food industry sponsored studies were more likely to find fewer harmful effects from soft drink consumption.
This is how the researchers themselves concluded, though:
Although industry-sponsored studies were more likely to have conclusions favorable to industry than non–industry-sponsored studies, the difference was not significant. There was also insufficient evidence to assess the quantitative effect of industry sponsorship on the results and quality of nutrition research. These findings suggest but do not establish that industry sponsorship of nutrition studies is associated with conclusions that favor the sponsors, and further investigation of differences in study results and quality is needed.
Who’s right? I don’t know. All kinds of biases can influence the conclusions of papers.
