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Record W7161802239 · doi:10.82308/42201

The retail food environment and the cardiometabolic health of Canadians

2023· dissertation· en· W7161802239 on OpenAlexaboutno aff
Andrew Stevenson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNeighbourhood (mathematics)OverweightObesityBody mass indexWaistPopulation healthPopulationUnhealthy food

Abstract

fetched live from OpenAlex

Diet is among the most important modifiable risk factors for morbidity and mortality worldwide, primarily through the development of cardiometabolic disease. Most Canadians have a suboptimal diet, which poses a considerable health burden on the population, given the importance of dietary quality to disease prevention and management. Poor diet at the population-level likely reflects responses to the food environment that individuals are exposed to. The retail food environment is a component of the built environment that can be modified to contribute to improvements in the health of Canadians at the population level. The overarching hypothesis of the thesis is that less favourable neighbourhood retail food environments will be associated higher prevalence of overweight and obesity (as measured by Body Mass Index or BMI higher body weight), larger waist circumferences (WC) and higher rates of hypertension in the Canadian adult population. Less favourable neighbourhood food environments are characterized by an overabundance of less healthy food stores or a scarcity of healthier food stores. Work to address the overarching hypothesis unfolded over five thesis objectives:1)To systematically review the Canadian literature on associations between neighbourhood food environments, diet and BMI;2)To develop and validate the first pan-Canadian dataset (Can-FED) of neighbourhood food environment measures that are publicly shareable and made using the Statistics Canada Business Register;3)To investigate population-level associations between Can-FED measures, measured BMI and WC of adult participants from the Canadian Health Measures Survey (CHMS);4)To investigate population-level associations between Can-FED measures and hypertension of adult participants from the Canadian Health Measures Survey (CHMS);5)To systematically observe and describe how local food environments have changed in Montreal over the course of the thesis The systematic review (chapter 4) found little evidence of a food environment–diet quality relationship and modest evidence of a food environment–BMI relationship. Chapter 5 was devoted to the development and validation of two versions of Can-FED using a gold standard database of businesses – the Statistics Canada Business Register. These datasets are the first publicly shareable pan-Canadian measures of neighbourhood food environments. Agreement between Can-FED food environment measures and those derived from a proprietary dataset and a municipal health inspection list ranged from rs=0.28 for convenience store density and rs=0.53 for restaurant density. Using the Can-FED measures, I demonstrated that a one standard deviation (SD) increase in the percentage of restaurants that are fast-food was positively associated with BMI and WC for men (BMI: β= 1.49%, 95% CI, 0.37% to 2.61%; WC: β =0.85%, 95% CI, 0.14% to 1.56%) in fully adjusted models, but associations did not reach statistical significance for women. I also demonstrated that a one SD increase in the proportion of fast-food outlets relative to the sum of fast-food outlets and restaurants was associated with higher odds of measured hypertension in the full sample (OR=1.17, 95% CI 1.05 to 1.31) and in sex-specific models (women: OR=1.14, 95% CI 1.01 to 1.29; and men: OR=1.21, 95% CI 1.03 to 1.43). In Montreal, there was wide variation in the characteristics of the retail food environments across five neighbourhoods; however, there was no clear patterning in the characteristics of the food environment by neighbourhood marginalization. I also showed that measures of the food environment are relatively stable over a three-year year period

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.930

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 studies0.0010.000
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 head0.026
GPT teacher head0.234
Teacher spread0.208 · 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 designOther design
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

Citations0
Published2023
Admission routes1
Has abstractyes

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