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Record W2152655853 · doi:10.1183/09031936.03.00055702

Nutrition and respiratory health in adults: findings from the Health Survey for Scotland

2003· article· en· W2152655853 on OpenAlexaff
Yvonne Kelly, Amanda Sacker, Michael Marmot

Bibliographic record

VenueEuropean Respiratory Journal · 2003
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsCanadian Society for International Health
FundersMedical Research Council
KeywordsMedicineConfoundingPhlegmVitamin EVitaminEnvironmental healthVitamin CPulmonary function testingPopulationRespiratory systemPhysiologyFood scienceAntioxidantInternal medicineBiology

Abstract

fetched live from OpenAlex

There is a growing body of evidence to support the hypothesised links between consumption of antioxidant rich foods and the occurrence of obstructive airway disease. The main research question was to examine the relationships between two types of dietary exposure and two indicators of respiratory morbidity in Scottish adults. The relationships between dietary consumption of fruit, vegetables and fish, and plasma levels of vitamins A, C, E and beta-carotene, and pulmonary function (forced expiratory volume in one second (FEV1)) and symptoms (phlegm production and shortness of breath with wheezing), were examined in a random population sample of adults. A dose/response relationship was found between fruit consumption and pulmonary function. In comparison with eating fruit rarely or never, eating fruit at least once per day, 1-6 times per week, and 1-3 times per month were associated with differences of 132, 100 and 63 mL in FEV1, after adjustment for known confounders and dietary intake of vegetables and fish (n=6186). An SD score change in plasma vitamin C was associated with a 49 mL difference in FEV1 (n=930). Fruit and vitamin E were associated with a reduced prevalence of phlegm production for 3 months or more per year. The most beneficial combination of dietary components may be found in natural foodstuffs, particularly fresh fruit.

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)0.007
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 score0.039
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.056
GPT teacher head0.337
Teacher spread0.281 · 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

Citations85
Published2003
Admission routes1
Has abstractyes

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