Toward more rigorous and informative nutritional epidemiology: The rational space between dismissal and defense of the status quo

Brown, Andrew W.; Aslibekyan, Stella; Bier, Dennis M.; Silva, Rafael Ferreira da; Hoover, Adam; Klurfeld, David M.; Loken, Eric; Mayo‐Wilson, Evan; Menachemi, Nir; Pavela, Gregory; Patrick, Donald W.; Quinn, Patrick D.; Schoeller, Dale; Carmen,; Tekwe,; Danny,; Valdez,; Vorland, Colby J.; Whigham, Leah D.; Allison, David B.

doi:10.1080/10408398.2021.1985427

Cited by 33 publications

(26 citation statements)

References 153 publications

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“…Beyond the specific criticism of the NOVA classification system and of its theoretical background, it is important to remember that the use of such a classification in observational (or cohort) epidemiological studies must be interpreted with caution and in the context of the general limitations typical of this type of study design (69) . These include the relative inability of the dietary intake assessment methods used in such studies to determine accurately and precisely the intake of individual foods (and, therefore, nutrients), the relationships among these individual constituents and the health outcomes resulting from their consumption (70,71) No matter how well such epidemiological studies are carried out and how few residual confounders remain in the analyses (72) , they can never prove causality (73) ; intervention trials are required to provide this type of evidence alongside supporting information from mechanistic studies (69) .…”

Section: Nova Classification and Poor Prognosis In Epidemiological St...mentioning

confidence: 99%

The ultra-processed foods hypothesis: a product processed well beyond the basic ingredients in the package

Visioli

Marangoni²,

Fogliano

et al. 2022

Nutr. Res. Rev.

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The NOVA classification of food items has become increasingly popular and is being used in several observational studies as well as in nutritional guidelines and recommendations. We propose that there is a need for this classification and its use in the formulation of public health policies to be critically discussed and re-appraised. The terms “processing” and “ultra-processing,” which are crucial to the NOVA classification, are ill-defined, as no scientific, measurable, or precise reference parameters exist for them. Likewise, the theoretical grounds of the NOVA classification are unclear and inaccurate. Overall, the NOVA classification conflicts with the classic, evidence-based evaluation of foods based on composition and portion size because NOVA postulates that the food itself (or how much of it is eaten) are unimportant, but rather that dietary effects are due to how the food is produced. We contend that the NOVA system suffers from a lack of biological plausibility so the assertion that ultra-processed foods are intrinsically unhealthful is largely unproven, and needs further examination and elaboration.

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Section: Nova Classification and Poor Prognosis In Epidemiological St...mentioning

confidence: 99%

The ultra-processed foods hypothesis: a product processed well beyond the basic ingredients in the package

Visioli

Marangoni²,

Fogliano

et al. 2022

Nutr. Res. Rev.

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“…Correlation or regression coefficients estimating associations between self-reported nutrition intakes and health outcomes can be subject to substantial error (52, 53). To address such reporting bias issues, there has been increased interest in the use of statistical models in conjunction with biomarker data (54, 55).…”

Section: Discussionmentioning

confidence: 99%

Bias in nutrition-health associations is not eliminated by excluding extreme reporters in empirical or simulation studies

Yamamoto

Ejima

Zoh

et al. 2022

Preprint

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Self-reported nutrition intake (NI) data are prone to reporting bias that may induce bias in estimands in nutrition studies; however, they are used anyway due to high feasibility. We examined whether applying Goldberg cutoffs to remove “implausible” self-reported NI could reliably reduce bias compared to biomarkers for energy, sodium, potassium, and protein. Using IDATA data, significant bias in mean NI was removed with Goldberg cutoffs (120 among 303 participants excluded). Associations between NI and outcomes (weight, waist circumference, heart rate, systolic/diastolic blood pressure, and VO2 max) were estimated, but sample size was insufficient to evaluate bias reductions. We therefore simulated data based on IDATA. Significant bias in simulated associations using self-reported NI was reduced but not eliminated by Goldberg cutoffs in 14 of 24 nutrition-outcome pairs; bias was not reduced for remaining cases. 95% coverage probabilities were improved by applying Goldberg cutoffs in most cases but underperformed compared with biomarker data. Although Goldberg cutoffs may achieve bias elimination in estimating mean NI, bias in estimates of associations between NI and outcomes will not necessarily be reduced or eliminated after application of Goldberg cutoffs. Whether one uses Goldberg cutoffs should therefore be decided based on research purposes and not general rules.Impact StatementElimination of extreme reporters using Goldberg cutoffs does not always produce unbiased estimates of associations between nutrition intakes and health outcomes.

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“…It is mainly the associations observed in some observational studies that, with their repeatedly articulated limitations [ 27 , 28 , 29 , 30 ], lend credence to the search for mechanistic explanations for supposed adverse effects of LES, since the support is not clearly coming from the controlled trials. The result is an absurd situation in which mechanistic and observational research continually reinforce each other in generating hypotheses that consistently fail to be supported by direct empirical testing.…”

Section: Perspectivementioning

confidence: 99%

“…Observational studies (and the reviews citing them) lean toward finding adverse associations of LES with metabolic health outcomes, whereas RCTs lean toward neutral or beneficial effects, often for the same outcomes, such as body weight [ 40 , 41 ]. Large, well-designed observational studies with appropriate analyses can highlight legitimate areas of concern, although there is considerable debate around the use and limitations of observational data in nutrition [ 30 ]. For observational research on LES specifically, the validity of certain associations must however be questioned when they are repeatedly disconfirmed by evidence from intervention trials, combined with a susceptibility to confounding that undermines the assignment of a causal interpretation [ 27 , 29 , 42 , 43 ].…”

Section: Perspectivementioning

confidence: 99%

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Is There an Academic Bias against Low-Energy Sweeteners?

Mela¹

2022

Nutrients

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This perspective considers evidence of a common academic bias against low-energy sweeteners (LES). The core proposition is that this bias is manifested in research and reporting focused on generating and placing a negative spin on LESs, largely through selective citation, interpretation and reporting. The evidence centres on three inter-related points, which together may generate a misleading impression of the balance of evidence: (1) basic and mechanistic research on LES perpetuates “explanations” for unsubstantiated adverse effects of LES; (2) the literature on LES—particularly narrative reviews and commentaries—continually reprises hypotheses of adverse effects without acknowledging where these hypotheses have been rigorously tested and rejected; and (3) negative interpretations of the effects of LES largely rely upon selectively emphasising lower-quality research whilst ignoring or dismissing higher-quality evidence. The expert community should consider these issues in assuring scientific integrity and balance in the academic discourse on LES, and how this is translated into messages for public health and consumers.

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Toward more rigorous and informative nutritional epidemiology: The rational space between dismissal and defense of the status quo

Cited by 33 publications

References 153 publications

The ultra-processed foods hypothesis: a product processed well beyond the basic ingredients in the package

The ultra-processed foods hypothesis: a product processed well beyond the basic ingredients in the package

Bias in nutrition-health associations is not eliminated by excluding extreme reporters in empirical or simulation studies

Is There an Academic Bias against Low-Energy Sweeteners?

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