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Record W3148526522 · doi:10.1289/ehp7944

Ambient Fine Particulate Matter Air Pollution and Risk of Weight Gain and Obesity in United States Veterans: An Observational Cohort Study

2021· article· en· W3148526522 on OpenAlexaff
Benjamin Bowe, Andrew K. Gibson, Yan Xie, Yan Yan, Aaron van Donkelaar, Randall V. Martin, Ziyad Al‐Aly

Bibliographic record

VenueEnvironmental Health Perspectives · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBody mass indexInterquartile rangeObesityHazard ratioMedicineWeight gainParticulatesAerodynamic diameterProportional hazards modelCohort studyEnvironmental healthCohortDemographyConfidence intervalInternal medicineBody weightChemistry

Abstract

fetched live from OpenAlex

Background: Experimental evidence and studies of children and adolescents suggest that ambient fine particulate matter [particulate matter ≤2.5μm in aerodynamic diameter (PM2.5)] air pollution may be obesogenic, but the relationship between PM2.5 and the risk of body weight gain and obesity in adults is uncertain. Objectives: Our goal was to characterize the association between PM2.5 and the risks of weight gain and obesity. Methods: We followed 3,902,440 U.S. Veterans from 2010 to 2018 (median 8.1 y, interquartile range: 7.3–8.4) and assigned time-updated PM2.5 exposures by linking geocoded residential street addresses with satellite-based estimates of surface-level PM2.5 mass (at ∼1-km2 resolution). Associations with PM2.5 were estimated using Cox proportional hazards models for incident obesity [body mass index (BMI)≥30 kg/m2] and a 10-lb increase in weight relative to baseline and linear mixed models for associations with intra-individual changes in BMI and weight. Results: A 10-μg/m3 higher average annual PM2.5 concentration was associated with risk of incident obesity [n=2,325,769; hazard ratio (HR)=1.08 (95% CI: 1.06, 1.11)] and the risk of a 10-lb (4.54 kg) increase in weight [HR=1.07 (95% CI: 1.06, 1.08)] and with higher intra-individual changes in BMI [0.140 kg/m2 per year (95% CI: 0.139, 0.142)] and weight [0.968 lb/y (95% CI: 0.955, 0.981)]. Nonlinear exposure–response models indicated associations at PM2.5 concentrations below the national standard of 12 μg/m3. As expected, a negative exposure control (ambient air sodium) was not associated with obesity or weight gain. Associations were consistent in direction and magnitude across sensitivity analyses that included alternative outcomes and exposures assigned at different spatial resolutions. Discussion: PM2.5 air pollution was associated with the risk of obesity and weight gain in a large predominantly male cohort of U.S. Veterans. Discussions about health effects of PM2.5 should include its association with obesity, and deliberations about the epidemiology of obesity should consider its association with PM2.5. Investigation in other cohorts will deepen our understanding of the relationship between PM2.5 and weight gain and obesity. https://doi.org/10.1289/EHP7944

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)0.001
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 score0.009
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.033
GPT teacher head0.311
Teacher spread0.278 · 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

Citations57
Published2021
Admission routes1
Has abstractyes

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