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Record W1488679952 · doi:10.1111/nhs.12218

Lifestyle habits and obesity progression in overweight and obese American young adults: Lessons for promoting cardiometabolic health

2015· article· en· W1488679952 on OpenAlexaboutno aff
EunSeok Cha, Margeaux K. Akazawa, Kevin H. Kim, Colleen R. Dawkins, Hannah M. Lerner, Guillermo E. Umpierrez, Sandra B. Dunbar

Bibliographic record

VenueNursing and Health Sciences · 2015
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Institutes of HealthAtlanta Clinical and Translational Science InstituteNational Institute of Nursing ResearchUniversity of PittsburghEmory University
KeywordsOverweightObesityMedicineDyslipidemiaGerontologyDiabetes mellitusEnvironmental healthPhysical therapyDemographyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Obesity among young adults is a growing problem in the United States and is related to unhealthy lifestyle habits, such as high caloric intake and inadequate exercise. Accurate assessment of lifestyle habits across obesity stages is important for informing age-specific intervention strategies to prevent and reduce obesity progression. Using a modified version of the Edmonton Obesity Staging System (mEOSS), a new scale for defining obesity risk and predicting obesity morbidity and mortality, this cross-sectional study assessed the prevalence of overweight/obese conditions in 105 young adults and compared their lifestyle habits across the mEOSS stages. Descriptive statistics, chi-square tests, and one-way analyses of variance were performed. Eighty percent of participants (n = 83) fell into the mEOSS-2 group and had obesity-related chronic disorders, such as diabetes, hypertension, and/or dyslipidemia. There were significant differences in dietary quality and patterns across the mEOSS stages. Findings highlighted the significance of prevention and early treatment for overweight and obese young adults to prevent and cease obesity progression.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.166
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.407
Teacher spread0.356 · 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 teacher head, 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

Citations38
Published2015
Admission routes1
Has abstractyes

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