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Poverty and the extent of child obesity in Canada, Norway and the United States

2006· review· en· W2080426764 on OpenAlexaffabout
Shelley Phipps, Peter Burton, Lars Osberg, Lynn Lethbridge

Bibliographic record

VenueObesity Reviews · 2006
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPovertyObesityNorwegianMicrodata (statistics)Child povertyChild obesityChildhood obesityDemographyMedicineOverweightEnvironmental healthEconomic growthPopulationEconomicsSociology

Abstract

fetched live from OpenAlex

The goal of this paper is to compare the extent of child obesity in Canada, Norway and the United States. As child poverty is an important correlate of child obesity, we wish to examine the potential role of international differences in child poverty in explaining international differences in the extent of child obesity. We use three representative microdata surveys containing parental reports of child height and weight collected in the mid-1990s in Canada, Norway and the US. We calculate both the prevalence and proportional severity of child obesity for 6-11-year-old children in each country, and represent the 'extent' of obesity diagrammatically. Differences in patterns of child poverty are similarly depicted. Obesity extent is also compared for poor and non-poor children in Canada and the US. Finally, child obesity in the three countries is compared using only non-poor children where we find that the extent of child obesity is much lower in Norway than in Canada or the US. The pattern apparent for obesity is remarkably similar to that found for child poverty. In Canada and especially in the US, we find a much greater extent of obesity for poor than non-poor children. However, when we compare only non-poor children in the three countries, although the magnitude of difference is smaller, it remains clear that Norwegian children are much less likely to be obese. Policy and research directed towards reducing the extent of child obesity in both Canada and the US should pay particular attention to issues of child poverty.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.275
Teacher spread0.253 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations75
Published2006
Admission routes2
Has abstractyes

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