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Record W1987663545 · doi:10.1210/jc.2008-1356

Epidemiology of Obesity in the Western Hemisphere

2008· review· en· W1987663545 on OpenAlexaboutno aff
Earl S. Ford, Ali H. Mokdad

Bibliographic record

VenueThe Journal of Clinical Endocrinology & Metabolism · 2008
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersCenters for Disease Control and Prevention
KeywordsObesityPublic healthSocioeconomic statusEpidemiological transitionEpidemiologyGeographyNutrition transitionEnvironmental healthPopulationMedicineDemographyDeveloping countryGerontologySocioeconomicsEconomic growthOverweightEconomics

Abstract

fetched live from OpenAlex

CONTEXT: Obesity has emerged as a global public health challenge. The objective of this review was to examine epidemiological aspects of obesity in the Western Hemisphere. EVIDENCE ACQUISITION: Using PubMed, we searched for publications about obesity (prevalence, trends, correlates, economic costs) in countries in North America, Central America, South America, and the Caribbean. To the extent possible, we focused on studies that were primarily population based in design and on four countries in the Western Hemisphere: Brazil, Canada, Mexico, and the United States. EVIDENCE SYNTHESIS: Data compiled by the International Obesity Task Force show a substantial level of obesity in all of or selected areas of the Bahamas, Barbados, Canada, Chile, Guyana, Mexico, Panama, Paraguay, Peru, St. Lucia, Trinidad and Tobago, the United States, and Venezuela. Furthermore, countries such as Brazil, Canada, Mexico, and the United States have experienced increases in the prevalence of obesity. In many countries, the prevalence of obesity is higher among women than men and in urban areas than in rural areas. The relationship between socioeconomic status and obesity depends on the stage of economic transition. Early in the transition, the prevalence of obesity is positively related to income whereas at some point during the transition the prevalence becomes inversely related to income. CONCLUSIONS: Like other countries in the Western Hemisphere, the four countries that we focused on have experienced a rising tide of obesity. The high and increasing prevalence of obesity and its attendant comorbidities are likely to pose a serious challenge to the public health and medical care systems in these countries.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.807
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0110.003
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.006
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 head0.180
GPT teacher head0.466
Teacher spread0.287 · 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 designOther design
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

Citations246
Published2008
Admission routes1
Has abstractyes

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