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How do you determine the healthiest foods to eat? Addressing issues with peer-reviewed nutrition research

By Casey Thaler, B.A., NASM-CPT, FNS
September 24, 2020
Alexander Raths/ Shutterstock.com Alexander Raths/ Shutterstock.com

All too often, popular media hits its audience with the news of another study they deem a scientific breakthrough. [1] [2] [3] While “A new study shows that…” might be one of the most oft-repeated headlines, the truth is far different.[4] [5] [6] [7] [8]

Those in the scientific community know that even the most perfectly designed study rarely results in flawless conclusions.[9] [10] There are many variables that go into each new study, including the number of participants, how long the study lasts, the statistical analysis, to name just a few.[11] [12] [13] Each one of these individual variables can have a significant impact on the overall viability of the study, and even a slight error can discount the entire research project.[14] [15] [16] [17]

While this precise attention to detail can mar even the most well-intentioned study, research in the world of nutrition is even murkier, as it’s nearly impossible to design a flawless nutritional study.[18] [19] The human body is so complex, with internal factors ranging from neuroscience, metabolism, digestion, and genetics influencing what we consume. Therefore, it is extremely difficult to design a study that will control for every possible confounding variable.[20] [21] [22] [23] There’s also the fact that getting subjects to follow a prescribed diet is a challenge.

Of these numerous factors, one of the best ways to create reliable data is to create a large sample size.[24] [25] [26] [27] [28] For example, a study that looks at 30,000 people will almost always provide better data than a project that looks at three people. Of course, if you opt for a large sample size, then you run into different issues—for example, being able to reliably track 30,000 people.[29] [30] Add the complexity and cost presented by controlled studies where subjects are fed and monitored, and the number of possible subjects becomes much smaller.

This also brings up the issue of research funding, which is often very influential, even for seemingly innocuous studies.[31] [32] [33] [34] [35] The general public would be shocked if they realized how the funding for many research projects greatly impacts the conclusions. (The most well-known examples relate to the tobacco industry, as well as the soda industry—coincidentally, this is where several tobacco executives moved on to—as they routinely funded studies that would only provide them with favorable outcomes.[36])

This clear conflict of interest results in the numerous (dubious) studies that declare, “excess sugar consumption shows no side effects.” In fact, Coca-Cola got caught funding scientists who would helpfully state that “obesity had nothing to do with bad diets.” In fact, as has been proven by numerous (legitimate) studies, the single biggest factor in the obesity rate reaching almost 50 percent is, indeed, sugar.[37] [38] [39] [40]

As the New York Times has covered, it is quite difficult to design a perfect nutrition study, which partially explains why Americans have such a difficult time figuring out what to eat. Of course, at The Paleo Diet® we know that the simple answer is to choose the most nutrient-dense foods, and skip the processed food products. Sticking to the basics—things like grass-fed beef, nutrient-dense vegetables, and healthy fats—always leads to the best health outcomes.

One other element that is especially prevalent in peer-reviewed nutrition research is confirmation bias. If you submit your research to a journal in order to get it published, chances are many of your peers will share your same nutritional bias. For example, a plant-based journal will likely not point out any flaws with research putting a positive spin on plant-based diets. Unfortunately, this makes it much more difficult to understand what information is true, and what is closer to propaganda.

And, of course, we live in a very noisy world: most food advertisements do not attempt to be completely honest about the science. The best foods are never advertised—choices like broccoli, chicken, and pasture-raised eggs. This makes nutritional education vitally important, as children are highly influenced by both television and other types of marketing.

In closing, the next time you see a headline touting a “new breakthrough,” look to the details, like the sample size of the study, the methodology of the study, whether it was well-controlled, and whether there were any conflicts of interest. Even if these boxes are all ticked, it still behooves you to take every new study with a grain of salt. Always keep in mind the basics of proper nutrition.

References

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[2] Rippe JM, Marcos A. Controversies about sugars consumption: state of the science. Eur J Nutr. 2016;55(Suppl 2):11-16.

[3] Hall KD. Challenges of human nutrition research. Science. 2020;367(6484):1298-1300.

[4] Lucas M. Conflicts of interest in nutritional sciences: The forgotten bias in meta-analysis. World J Methodol. 2015;5(4):175-8.

[5] Kipnis V, Midthune D, Freedman L, et al. Bias in dietary-report instruments and its implications for nutritional epidemiology. Public Health Nutr. 2002;5(6A):915-23.

[6] Ventura AK, Loken E, Mitchell DC, Smiciklas-wright H, Birch LL. Understanding reporting bias in the dietary recall data of 11-year-old girls. Obesity (Silver Spring). 2006;14(6):1073-84.

[7] Litman EA, Gortmaker SL, Ebbeling CB, Ludwig DS. Source of bias in sugar-sweetened beverage research: a systematic review. Public Health Nutr. 2018;21(12):2345-2350.

[8] Brown AW, Ioannidis JP, Cope MB, Bier DM, Allison DB. Unscientific beliefs about scientific topics in nutrition. Adv Nutr. 2014;5(5):563-5.

[9] Fabbri A, Lai A, Grundy Q, Bero LA. The Influence of Industry Sponsorship on the Research Agenda: A Scoping Review. Am J Public Health. 2018;108(11):e9-e16.

[10] Miles S, Scaife V. Optimistic bias and food. Nutr Res Rev. 2003;16(1):3-19.

[11] Weaver CM, Miller JW. Challenges in conducting clinical nutrition research. Nutr Rev. 2017;75(7):491-499.

[12] Freudenheim JL. A review of study designs and methods of dietary assessment in nutritional epidemiology of chronic disease. J Nutr. 1993;123(2 Suppl):401-5.

[13] Monsen ER, Cheney CL. Research methods in nutrition and dietetics: design, data analysis, and presentation. J Am Diet Assoc. 1988;88(9):1047-65.

[14] Smith R. Peer review: a flawed process at the heart of science and journals. J R Soc Med. 2006;99(4):178-82.

[15] Ioannidis JP. Why Most Clinical Research Is Not Useful. PLoS Med. 2016;13(6):e1002049.

[16] Ioannidis JP. Why most published research findings are false. PLoS Med. 2005;2(8):e124.

[17] Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plast Reconstr Surg. 2010;126(2):619-25.

[18] Confused by nutrition research? Sloppy science may be to blame. (2018, October 29). The New York Times - Breaking News, World News & Multimedia. https://www.nytimes.com/2018/10/29/well/live/confused-by-nutrition-research-sloppy-science-may-be-to-blame.html

[19] Molteni, M. (2018, June 18). The struggles of a $40 million nutrition science crusade. Wired. [20] Skelly" class="redactor-autoparser-object">https://www.wired.com/story/ho... AC, Dettori JR, Brodt ED. Assessing bias: the importance of considering confounding. Evid Based Spine Care J. 2012;3(1):9-12.

[21] Jepsen P, Johnsen SP, Gillman MW, Sørensen HT. Interpretation of observational studies. Heart. 2004;90(8):956-60.

[22] Parab S, Bhalerao S. Study designs. Int J Ayurveda Res. 2010;1(2):128-31.

[23] Kapoor MC. Types of studies and research design. Indian J Anaesth. 2016;60(9):626-630.

[24] Charan J, Biswas T. How to calculate sample size for different study designs in medical research?. Indian J Psychol Med. 2013;35(2):121-6.

[25] Faber J, Fonseca LM. How sample size influences research outcomes. Dental Press J Orthod. 2014;19(4):27-9.

[26] Nayak BK. Understanding the relevance of sample size calculation. Indian J Ophthalmol. 2010;58(6):469-70.

[27] Gupta KK, Attri JP, Singh A, Kaur H, Kaur G. Basic concepts for sample size calculation: Critical step for any clinical trials!. Saudi J Anaesth. 2016;10(3):328-31.

[28] Hickey GL, Grant SW, Dunning J, Siepe M. Statistical primer: sample size and power calculations-why, when and how?. Eur J Cardiothorac Surg. 2018;54(1):4-9.

[29] Ahn E, Kang H. Introduction to systematic review and meta-analysis. Korean J Anesthesiol. 2018;71(2):103-112.

[30] Jahan N, Naveed S, Zeshan M, Tahir MA. How to Conduct a Systematic Review: A Narrative Literature Review. Cureus. 2016;8(11):e864.

[31] Sax JK. Financial conflicts of interest in science. Ann Health Law. 2012;21(2):291-327, 6 p preceding i.

[32] Klitzman R, Chin LJ, Rifai-bishjawish H, Kleinert K, Leu CS. Disclosures of funding sources and conflicts of interest in published HIV/AIDS research conducted in developing countries. J Med Ethics. 2010;36(8):505-10.

[33] Julia, B. E. (2017, April 19). Too many studies have hidden conflicts of interest. A new tool makes it easier to see them. Vox. [34] 50" class="redactor-autoparser-object">https://www.vox.com/2017/4/19/... years ago, sugar industry quietly paid scientists to point blame at fat. (2016, September 13). NPR.org. [35] How" class="redactor-autoparser-object">https://www.npr.org/sections/t... the sugar industry shifted blame to fat. (2016, September 13). The New York Times - Breaking News, World News & Multimedia. [36] Brandt" class="redactor-autoparser-object">https://www.nytimes.com/2016/0... AM. Inventing conflicts of interest: a history of tobacco industry tactics. Am J Public Health. 2012;102(1):63-71.

[37] Harvard Health Publishing. (2019, November 14). The sweet danger of sugar. Harvard Health. [38] Rippe" class="redactor-autoparser-object">https://www.health.harvard.edu... JM, Angelopoulos TJ. Relationship between Added Sugars Consumption and Chronic Disease Risk Factors: Current Understanding. Nutrients. 2016;8(11)

[39] Della corte KW, Perrar I, Penczynski KJ, Schwingshackl L, Herder C, Buyken AE. Effect of Dietary Sugar Intake on Biomarkers of Subclinical Inflammation: A Systematic Review and Meta-Analysis of Intervention Studies. Nutrients. 2018;10(5)

[40] Rippe JM, Angelopoulos TJ. Sugars, obesity, and cardiovascular disease: results from recent randomized control trials. Eur J Nutr. 2016;55(Suppl 2):45-53.

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