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Record W2111972479 · doi:10.1093/ije/dyp349

Author's Response * Dietary patterns and the risk of mortality: impact of cardiorespiratory fitness

2009· article· en· W2111972479 on OpenAlexaff
Martin E. Héroux, Ian Janssen

Bibliographic record

VenueInternational Journal of Epidemiology · 2009
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsQueen's University
Fundersnot available
KeywordsCardiorespiratory fitnessEnvironmental healthMedicineGerontologyDemographyPhysical therapySociology

Abstract

fetched live from OpenAlex

We would like to thank Drs Ding, Hu and Pischon for their insights and commentaries on our paper ‘Dietary patterns and the risk of mortality: impact of cardiorespiratory fitness’.1 In the spirit of a healthy debate, there are a few issues that we would like to address in our response. We would first like to highlight that the purpose of our paper was not to argue against the role of an unhealthy diet as a risk factor for morbidity and mortality. We are in full agreement that a healthy diet is important and that there is an abundance of evidence to support this position. Rather, our goal was to highlight that previous studies examining the relation between dietary patterns and health have not properly controlled for the confounding effects of physical activity, which, without exception, have been measured by self-report. Validation studies have consistently found that self-reported physical activity measures are biased (e.g. most people overestimate their activity) and only modestly associated with objective measures of physical activity.2–4 The imprecision of these estimates would result in an underestimated effect of physical activity on the morbidity and mortality outcomes, and in studies of unhealthy dietary patterns and poor health, would result in residual confounding for physical activity. Our study attempted to overcome this limitation by including an objective marker of physical activity as a covariate in the analyses. Indeed, the risk estimates for dietary patterns were substantively smaller when cardiorespiratory fitness was the covariate compared with when self-reported physical activity was the covariate. Next, we would like to address the concern regarding the use of cardiorespiratory fitness as a marker of physical activity participation. We appreciate that fitness is not a direct measure of physical activity and that other factors such as genetics, age and sex play a role in determining one’s fitness. However, by using age- and sex-specific cut-points to define the different fitness groups, our analyses accounted for some of the most meaningful non-activity determinants of fitness. Furthermore, several studies have shown that fitness is highly related to physical activity participation in recent months2,5,6 and that fitness is responsive to changes in physical activity.7–9 Thus, while we recognize that there is not a perfect relation between physical activity and fitness, it is clear that physical activity is a major driver of fitness. We, therefore, are confident that cardiorespiratory fitness can be used as a proxy and objective measure of physical activity. Both commentaries argued that diet is an important determinant of cardiorespiratory fitness. We do not support this position. Randomized controlled trials have clearly demonstrated that diet-induced weight loss is not associated with improvements in fitness, whereas exercise with or without weight loss is.6,8 Dr Pischon is correct in that dietary factors affect lipid and glucose metabolism. However, while these changes in metabolism would alter long-distance endurance performance (e.g. distance run in 1 h), they would not have a meaningful impact on performance in a relatively short (e.g. 15 min) cardiorespiratory fitness test, such as that performed in our study, as the utilization of fats relative to carbohydrates is not a determinant of success in a test of this duration. Thus, we do not feel the comments that diet is a determinant of cardiorespiratory fitness are supported by research findings or biological plausibility. Subsequently, we do not agree that dietary associations are mediated rather than confounded by fitness, or that fitness is an intermediary variable in the association of an unhealthy dietary pattern and mortality risk. Another important point that was raised in the commentaries was about the choice of biomarker response variables for the reduced rank regression (RRR) analysis. While the biomarkers chosen for this study are primarily considered as risk factors related to cardiovascular disease, we would like to point out that they are also related to numerous other chronic diseases such as type 2 diabetes and some cancers. Nonetheless, we agree that the number of risk factors considered was limited and does not represent a complete global index of all dietary effects on cardiovascular or all-cause mortality. In summary, while no study or analysis is perfect, we strongly believe that the results of this article are important and provide strong evidence for the need to use objective measures of physical activity in studies examining the relation between diet and health. We agree that it would be interesting to examine the confounding effects of objectively measured physical activity using accelerometers in comparison with cardiorespiratory fitness. However, at the present time we are unaware of any large, prospective studies in adults that have obtained such measures. Conflict of interest: None declared.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.114
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.061
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.114
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0150.019
Insufficient payload (model declined to judge)0.0610.024

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.126
GPT teacher head0.465
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2009
Admission routes1
Has abstractyes

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