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Record W4399678294 · doi:10.1093/eurjpc/zwae175.099

Air pollution in relation to brain health indicators and global cognitive functioning in patients with cardiovascular disorders along the heart-brain axis

2024· article· en· W4399678294 on OpenAlexaboutno aff
Erik J. Timmermans, Émeric Bron, Michiel L. Bots, Annebet Leeuwis, Justine Moonen, Frank J. Wolters, Geert Jan Biessels, Ilonca Vaartjes

Bibliographic record

VenueEuropean Journal of Preventive Cardiology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
FundersDutch Cardiovascular Alliance
KeywordsMedicineBrain sizeCognitionHyperintensityCross-sectional studyEffects of sleep deprivation on cognitive performanceNeuropsychologyMontreal Cognitive AssessmentCognitive skillCardiologyInternal medicineEnvironmental healthMagnetic resonance imagingCognitive impairmentPsychiatryPathology

Abstract

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Abstract Background/Introduction Exploring, understanding, and preventing the effects of exposure to air pollutants on the brain, and possible links to cognitive functioning, have been indicated as major global health challenges that urgently need to be addressed. Yet, relatively little work has been conducted to examine the associations of air pollution with indicators of brain health that are potentially related to cognitive functioning in patients who are at increased risk to develop cognitive impairments. Purpose This study aimed to examine cross-sectional and longitudinal associations of air pollution with global cognitive functioning, white matter hyperintensities (WMH), total brain volume (TBV), and cerebral blood flow (CBF) in individuals without or with heart failure, carotid occlusive disease, or vascular cognitive impairment. Additionally, this study examined whether the cross-sectional associations of air pollution with global cognitive functioning were mediated by WMH, TBV, and CBF. Methods For the cross-sectional and longitudinal analyses, we used data from 341 and 180 participants of the Dutch multi-center Heart-Brain Study, respectively. Cognitive functioning was measured using neuropsychological tests at baseline and two-year follow-up. Brain Magnetic Resonance Imaging provided WMH and TBV in mL, and CBF in mL/100g/min. WMH and TBV were divided by total intracranial volume. Annual average outdoor concentrations of particulate matter with diameters <2.5µm (PM2.5) and <10.0µm (PM10), and nitrogen dioxide (NO2) in µg/m3 in residential six-digit postal code areas were linked to participants at baseline. Adjusted multi-level regression analyses were applied to assess the associations of interest. Results No significant cross-sectional (βPM2.5=0.014, 95% CI=-0.076-0.104; βPM10=0.034, 95% CI=-0.043-0.111; βNO2=0.020, 95% CI=-0.004-0.045) and longitudinal associations (βPM2.5=0.041, 95% CI=-0.029-0.110; βPM10=0.016, 95% CI=-0.045-0.078; βNO2=-0.001, 95% CI=-0.022-0.022) of air pollution with global cognitive functioning were observed. No significant associations of air pollution with WMH, TBV, and CBF were found. The associations of PM2.5, PM10 and NO2 with global cognitive functioning were not significantly mediated by WMH, TBV, and CBF. Conclusions No supportive evidence was found for associations of air pollution with global cognitive functioning, WMH, TBV and CBF in healthy and vascularly compromised individuals.

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)0.005
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 score0.121
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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