The Problem With Health Research: Why Meta-Analyses Sometimes Give Conflicting Results
In 2012, Stanford University unveiled the shocking results of a study looking at organic food, declaring there is "little evidence of health benefits." The study was a meta-analysis, meaning it combed a mountain of research on the nutritional value of organic food and narrowed those studies into a smaller pool based on rigorous criteria. “Some believe that organic food is always healthier and more nutritious,” said lead author Dr. Crystal Smith-Spangler in a news release. “We were a little surprised that we didn’t find that.”
The purpose of systematic reviews, which critique the academic literature on thorny questions of science, and meta-analyses, which crunch vast data sets, are to capitalize on the investigative power of more data. A broader set of information, researchers hope, will expose outliers and average lopsided results into a more reliable portrait.
So how, then, did the British Journal of Nutrition conclude in its June meta-analysis that the health benefits of organic foods were "statistically significant" over non-organic foods? In a video posted on YouTube, the celebrity doctor Aaron Carroll says that the latter meta-analysis was larger and therefore perceived as being more accurate. But, as he explains, larger meta-analyses bring in more baggage than ones with tighter standards. Watch this video; educate yourself: