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Record W3135947538 · doi:10.3390/obesities1010003

Effects of Nine-Month Lifestyle Intervention on Cardiometabolic Risk Factors: Sex Differences in Obese Individuals

2021· article· en· W3135947538 on OpenAlexaff
Florent Besnier, Anil Nigam, Martin Juneau, Valérie Guilbeault, Élise Latour, Mathieu Gayda

Bibliographic record

VenueObesities · 2021
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsMedicineCardiorespiratory fitnessConfoundingWaistBody mass indexObesityBlood pressureDemographyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Limited data is available on the sex differences and individual responses of cardiometabolic parameters adjusted with potential confounders (i.e. sex, age, baseline values) after a longer term Mediterranean diet (MedD) and high intensity interval training (HIIT) in obese subjects. The objective of this study was to compare the effects of nine-month MedD counseling and supervised HIIT on cardiometabolic risk factors and individual responses in obese women (n = 99) and obese men (n = 35). Body composition (body mass, fat mass, lean body mass, waist circumference), cardiorespiratory fitness (METs), and cardiometabolic risk factors (blood pressure, blood sample variables) were measured at baseline and after nine months of a program combining MedD and HIIT two to three times a week. When adjusted with sex, age, and baseline values, obese women similarly improved their body composition, METs, and cardiometabolic risk factors vs. obese men. The proportion of responders according to clinical cutoff levels were the same in obese women and men. A longer MedD and HIIT intervention similarly improves body composition, cardiometabolic risk factors, and individual responses in obese women and men, even after adjustment of confounders (sex, age, baseline value).

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.261
Teacher spread0.248 · 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 designNon-randomized trial
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

Citations0
Published2021
Admission routes1
Has abstractyes

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