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Record W2115456075 · doi:10.1183/09031936.00012112

General and abdominal obesity and incident asthma in adults: the HUNT study

2012· article· en· W2115456075 on OpenAlexaff
Ben Brumpton, Arnulf Langhammer, Pål Romundstad, Yue Chen, Xiao‐Mei Mai

Bibliographic record

VenueEuropean Respiratory Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Ottawa
FundersNorwegian Institute of Public HealthNorges Teknisk-Naturvitenskapelige Universitet
KeywordsMedicineAsthmaAbdominal obesityObesityPediatricsInternal medicineMetabolic syndrome

Abstract

fetched live from OpenAlex

Measures of body mass index (BMI) and waist circumference define general obesity and abdominal obesity respectively. While high BMI has been established as a risk factor for asthma in adults, waist circumference has seldom been investigated. To determine the association between BMI, waist circumference and incident asthma in adults, we conducted a prospective study (n=23,245) in a population living in Nord-Trøndelag, Norway in 1995-2008. Baseline BMI and waist circumference were measured and categorised as general obesity (BMI ≥30.0 kg·m(2)) and abdominal obesity (waist circumference ≥88 cm in females and ≥102 cm in males). Incident asthma was self-reported new-onset cases during an 11-yr follow-up period. Odds ratios for asthma associated with obesity were calculated using multivariable logistic regression. General obesity was a risk factor for asthma in females (OR 1.96, 95% CI 1.52-2.52) and males (OR 1.84, 95% CI 1.30-2.59). In females, after additional adjustment for BMI, abdominal obesity remained a risk factor for asthma development (OR 1.46, 95% CI 1.04-2.05). Abdominal obesity seems to increase the risk of incident asthma in females in addition to BMI, indicating that using both measures of BMI and waist circumference in females may be a superior clinical assessment for asthma risk than any measure alone.

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 score0.030
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.016
GPT teacher head0.271
Teacher spread0.255 · 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

Citations122
Published2012
Admission routes1
Has abstractyes

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