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Record W2951203363 · doi:10.1093/cdn/nzz052.p14-001-19

Caffeine Intake and Demographic Characteristics of Shift Workers: A Cross-sectional Analysis Using NHANES 2005–2010 Data (P14-001-19)

2019· article· en· W2951203363 on OpenAlex
Sanjiv Agarwal, Victor L. Fulgoni, John A. Caldwell, Harris R. Lieberman

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Developments in Nutrition · 2019
Typearticle
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsImpact
Fundersnot available
KeywordsEveningCaffeineShift workMorningMedicineNational Health and Nutrition Examination SurveyCross-sectional studyDemographyWork shiftEnvironmental healthInternal medicinePopulationPsychiatry

Abstract

fetched live from OpenAlex

Caffeine is the most widely consumed stimulant in the world and sociodemographic factors including occupation are associated with its intake. Non-standard work schedules are required in various occupations, and it is difficult to adapt to them. Shift work is associated with poor sleep, inadequate diet and numerous adverse health effects. We assessed whether caffeine intake differs in individuals working various shifts since it is assumed shift workers use more caffeine to cope with fatigue and disrupted circadian rhythms. The 24-h dietary recall data collected in NHANES 2005–2010 datasets (employed adults age 19–70 years, n = 8500) were used to estimate individual usual caffeine intake from caffeine-containing foods and beverages. Daily patterns of work were self-reported as: regular daytime shift; evening shift; night shift; rotating shift; or “other”. Regression analyses assessed associations of shift work with caffeine intake after adjustment for age, gender, ethnicity, smoking status, work hours, energy intake, and alcohol intake, all known to be associated with caffeine intake. Approximately 73.5% of employed adults were day shift workers and 26.5% were non-day shift workers. Day shift workers were more likely to be non-Hispanic white and of higher economic status compared to other shift workers. Mean 24-hour caffeine intake of day shift workers (204 ± 5 mg) was similar (P > 0.2) to that of evening, night, and rotating shift workers (209 ± 23, 184 ± 18, and 199 ± 15 mg, respectively). Regardless of work schedule, individuals consumed the most caffeine during morning hours. Evening and night shift workers consumed less caffeine during their work hours (76.8 ± 8.8 and 98.4 ± 18.5 mg, respectively) and more during non-work hours (131 ± 24 and 84.9 ± 9.5 mg, respectively) compared to day shift workers (157 ± 4 and 49.7 ± 3.4 mg during work hours and non-work hours, respectively; P < 0.01 for both). Unexpectedly, daily caffeine intake was similar across different types of shift workers after adjustment for age, gender, ethnicity, smoking, economic status and other factors. Opinions or assertions contained herein are private views of the authors and not to be construed as official or reflecting views of the Army or DoD. DMRP/MRMC.

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)0.000
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 score0.005
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.102
GPT teacher head0.391
Teacher spread0.290 · 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