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Record W2330427017 · doi:10.1016/j.jenvman.2016.03.051

The modifying effect of socioeconomic status on the relationship between traffic, air pollution and respiratory health in elementary schoolchildren

2016· article· en· W2330427017 on OpenAlexafffundabout
Sabit Cakmak, Chris Hebbern, Jasmine D. Cakmak, Jennifer Vanos

Bibliographic record

VenueJournal of Environmental Management · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of OttawaHealth Canada
FundersClean Air Regulatory AgendaGovernment of CanadaUniversity of WindsorMinistry of EnvironmentU.S. Environmental Protection Agency
KeywordsInterquartile rangeSocioeconomic statusEnvironmental healthAir pollutionOdds ratioOddsMedicineDemographyLogistic regressionPopulationChemistryInternal medicine

Abstract

fetched live from OpenAlex

The volume and type of traffic and exposure to air pollution have been found to be associated with respiratory health, but few studies have considered the interaction with socioeconomic status at the household level. We investigated the relationships of respiratory health related to traffic type, traffic volume, and air pollution, stratifying by socioeconomic status, based on household income and education, in 3591 schoolchildren in Windsor, Canada. Interquartile range changes in traffic exposure and pollutant levels were linked to respiratory symptoms and objective measures of lung function using generalised linear models for three levels of income and education. In 95% of the relationships among all cases, the odds ratios for reported respiratory symptoms (a decrease in measured lung function), based on an interquartile range change in traffic exposure or pollutant, were greater in the lower income/education groups than the higher, although the odds ratios were in most cases not significant. However, in up to 62% of the cases, the differences between high and low socioeconomic groups were statistically significant, thus indicating socioeconomic status (SES) as a significant effect modifier. Our findings indicate that children from lower socioeconomic households have a higher risk of specific respiratory health problems (chest congestion, wheezing) due to traffic volume and air pollution exposure.

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)0.003
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 score0.155
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.030
GPT teacher head0.289
Teacher spread0.260 · 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

Citations93
Published2016
Admission routes3
Has abstractyes

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