MétaCan
Menu
Back to cohort
Record W3005181024 · doi:10.1002/oby.22710

Stress is Associated with Adiposity in Parents of Young Children

2020· article· en· W3005181024 on OpenAlexaffabout
V Hruska, Tory Ambrose, Gerarda Darlington, David W.L., Jess Haines, Andrea C. Buchholz

Bibliographic record

VenueObesity · 2020
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsWaistMedicineDistressDemographyWaist-to-height ratioBody mass indexYoung adultObesityFat massInternal medicineClinical psychology

Abstract

fetched live from OpenAlex

Objective This study investigated associations between stress (general stress, parenting distress, and household chaos) and adiposity among parents of young children. Methods The sample consisted of 49 mothers and 61 fathers from 70 families with young children living in Ontario, Canada. Linear regression using generalized estimating equations was used to investigate associations between stress measures and BMI, waist circumference (WC), waist to height ratio (WHtR), and percent fat mass. Results General stress was significantly associated with BMI ( = 0.54; 95% CI: 0.04‐1.03) and WC ( = 1.44; 95% CI: 0.10‐2.77). Parenting distress was significantly associated with BMI ( = 0.16; 95% CI: 0.02‐0.31), WC ( = 0.39; 95% CI: 0.04‐0.75), and WHtR ( = 0.003; 95% CI: 0.001‐0.005). Household chaos was significantly associated with all adiposity measures (BMI: = 0.20 [95% CI: 0.08‐0.33]; WC: = 0.48 [95% CI: 0.21‐0.75]; WHtR: = 0.003 [95% CI: 0.001‐0.005]; percent fat mass: = 0.29 [95% CI: 0.08‐0.49]). Conclusions General stress, parenting distress, and household chaos are associated with adiposity among parents of young children. Future research should elucidate mechanisms by which this occurs and elucidate how this risk may be mitigated.

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)0.000
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 score0.015
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Citations15
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueObesitySame topicObesity, Physical Activity, DietFrench-language works237,207