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Record W2758175275 · doi:10.1177/0260106017732719

Special diets in modern America: Analysis of the 2012 National Health Interview Survey data

2017· article· en· W2758175275 on OpenAlex
Brenda Leung, Romy Lauche, Matthew Leach, Yan Zhang, Holger Cramer, David Sibbritt

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

VenueNutrition and Health · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsNational Health Interview SurveyMedicineGerontologyEnvironmental healthPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Special diets are frequently used by the public but reasons for use and characteristics of users remain unclear. AIM: To determine prevalence of the use of special diets, the individual characteristics associated with their use and reasons for use. METHODS: The secondary analysis used data from the 2012 National Health Interview Survey (NHIS), a cross-sectional household interview survey of a nationally representative sample of non-hospitalized US adult populations ( n = 34,525). The dependent variables in this secondary analysis were the use of a special diet (vegetarian, macrobiotic, Atkins, Pritikin, and Ornish) ever and during the past 12 months. Independent variables included sociodemographic, clinical and behavioral variables. Prevalence of special diet use and reasons for use were analyzed descriptively. Associations between independent and dependent variables were analyzed using Chi-square tests and logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. RESULTS: Lifetime and 12-month prevalence of using special diets were 7.5% (weighted n = 17.7 million) and 2.9% (weighted n = 6.9 million), respectively. Individuals using special diets in the past 12 months were more likely female (OR = 1.45; 95% CI = 1.21-1.74), not married (OR = 0.76; 95% CI = 0.63-0.91), college-educated (OR = 1.98; 95% CI = 1.25-3.11) and depressed (OR = 1.50; 95% CI = 1.14-1.98). They more likely also used herbal products (OR = 2.35; 95%CI = 1.84-2.99), non-vitamin (OR = 1.82; 95% CI = 1.45-2.27) and vitamin supplements (OR = 1.57; 95% CI = 1.24-1.99). Diets were mainly used to improve overall health (76.7%) or for general wellness/prevention (70.4%). CONCLUSIONS: Special diets are mainly used for unspecific health reasons by those who are females, have a college degree or with depression, and commonly used in conjunction with herbs and dietary supplements.

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 score0.133
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.145
GPT teacher head0.384
Teacher spread0.238 · 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