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Record W4404085622 · doi:10.1080/09637486.2024.2420279

The influence of Mediterranean diet and physical activity-related energy expenditure on weight status and cardiometabolic risk. What “weights” more? The HERMEX study

2024· article· en· W4404085622 on OpenAlexaff
L. Morán, Virginia A. Aparicio, Marta Flor‐Alemany, Daniel Fernández‐Bergés, Teresa Nestares, Elena Nebot-Valenzuela, Francisco Javier Félix-Redondo

Bibliographic record

VenueInternational Journal of Food Sciences and Nutrition · 2024
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsCentre for Movement Disorders
Fundersnot available
KeywordsEnergy expenditureMediterranean dietEnvironmental healthPhysical activityMedicineEndocrinologyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

In this cross-sectional study, we explored the influence of Mediterranean Diet (MD) adherence and physical activity-related energy expenditure on weight status and cardiometabolic risk in a large sample of 2.833 young, middle-aged and older adults. A food frequency questionnaire was employed, and MD Score to assess MD adherence. Physical activity-related energy expenditure was reported through the Minnesota Leisure Time Physical Activity Questionnaire. Anthropometry, blood pressure, lipid and glycaemic markers were measured. Most of the participants were overweight or obese and had a medium-high MD adherence. The obesity group showed lower energy expenditure and a greater clustered cardiometabolic risk. Overweight and obese had a greater clustered cardiometabolic risk compared to the high MD adherence and normo-weight. Obese showed the greatest clustered cardiometabolic risk with independence of MD adherence. Increasing energy expenditure through physical activity better than restrictive diets might be one of the key components for reducing cardiometabolic risk among obese people.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.305
Teacher spread0.290 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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