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Record W2139685444 · doi:10.1186/1475-2891-12-4

Differences in perceptions and fast food eating behaviours between Indians living in high- and low-income neighbourhoods of Chandigarh, India

2013· article· en· W2139685444 on OpenAlexafffund
Christopher R. Aloia, Danijela Gašević, Salim Yusuf, Koon Teo, Arun Chockalingam, Binod Kumar Patro, Rajesh Kumar, Scott A. Lear

Bibliographic record

VenueNutrition Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicDietary Effects on Health
Canadian institutionsProvidence Health CareMcMaster UniversitySimon Fraser University
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of CanadaPfizer
KeywordsNeighbourhood (mathematics)MedicineEnvironmental healthPerceptionSocioeconomicsUrbanizationGeographyGerontologyPsychologyEconomic growthEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Increased density of fast food restaurants is associated with increased prevalence of obesity in developed countries. However, less is known about this relationship in developing countries undergoing rapid urbanization and how differences in neighbourhood income affect the patronage of fast food outlets. The purpose of the study is to explore the differences in fast food preferences, perceptions, and patronage between Indians living in high- and low-income neighbourhoods. METHODS: This cross-sectional study recruited 204 men and women (35 to 65 years in age) from high- and low-income neighbourhoods who completed a questionnaire on fast food consumption. The questionnaire asked participants to define fast food and to provide reasons for and frequency of visits to fast food restaurants. The differences were analyzed using Chi square and t-tests for categorical and continuous variables, respectively. RESULTS: Participants from a high-income neighbourhood were more likely to perceive Western -style fast food as fast food, while people from the low-income neighbourhood were more likely to identify food sold by street vendors as fast food (p <0.001). Furthermore, compared to participants from the high-income neighbourhood, people from the low-income neighbourhood were more likely to report buying food from street vendors while less likely to dine out at both fast food and non-fast food restaurants (p<0.001). Although the high-income neighbourhood group was more likely to report enjoying eating at fast food restaurants than their low-income neighbourhood counterparts, there were no significant differences in the reasons for visiting fast food restaurants (convenience, price, social enjoyment, and quality of meals) between the two groups. Both groups preferred home cooked over restaurant meals, and they recognized that home cooked food was healthier. CONCLUSIONS: Overall, consumption of fast food was low. People from a high-income neighbourhood dined out more frequently and were more likely to perceive Western-style food as fast food compared to their counterparts from the low-income neighbourhood.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.264
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2013
Admission routes2
Has abstractyes

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