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Record W2914143469 · doi:10.1289/isee.2015.2015-862

Long-Term Exposure To Air Pollution And Traffic Noise And Global Cognitive Score – Results From The Heinz Nixdorf-Recall Study

2015· article· en· W2914143469 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueISEE Conference Abstracts · 2015
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsInterquartile rangeConfidence intervalTraffic noisePopulationMedicineMontreal Cognitive AssessmentCognitionEnvironmental healthRecallDemographyPsychologyAudiologyCognitive impairmentInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Introduction: Investigations of adverse effects of air pollution (AP) and ambient noise on cogni-tive function are scarce, and their results are inconsistent. The aim of this study was to analyze the associations of long-term exposure to AP and traffic noise with a global cognitive score (GCS) in single and two-exposure models. Data: Our analysis is based on cross-sectional data from the first follow-up examination (2006-2008) of the population-based Heinz Nixdorf Recall study, located in three adjacent in the highly urbanized German Ruhr Area. Methods: Cognitive performance was completed in 4086 of 4157 participants using five subtests: verbal fluency, labyrinth test, immediate and delayed verbal recall, and clock-drawing tests. The GCS was additively calculated using age- and education-specific z scores of the five subtests. We assessed long-term residential concentrations for size-specific particulate matter (PM) and nitrogen oxides with land use regression and dispersion models, and traffic noise (weighted 24-h (LDEN) and night-time (LNIGHT) means) according to the EU directive 2002/49/EC. Multiple linear regression models adjusted for individual risk factors (age, sex, socio-economic status, alcohol consumption, smoking status, self-reported passive smoking, any regular physical activity, and body mass index) were calculated for the association of environmental exposures with GCS. Results: In the fully adjusted model, AP and noise were negatively associated with GCS. For example, an interquartile range (IQR) increase in PM2.5 (1.43 µg/m3) was associated with a de-crease in GCS of β =-0.05 [95% confidence interval (CI) -0.0.8;-0.03] and for a 10 dB(A) increase in LDEN, β was -0.07 [-0.13; -0.01]). In two-exposure models, the estimates remained stable and significant for AP, but slightly attenuated for noise. Discussion: Long-term exposures to AP and road traffic noise were adversely associated with GCS in one- and two exposure models.

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.

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)0.001
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 score0.566
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.098
GPT teacher head0.382
Teacher spread0.284 · 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