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Record W2755321138 · doi:10.3390/nu9091020

Baseline and Estimated Trends of Sodium Availability and Food Sources in the Costa Rican Population during 2004–2005 and 2012–2013

2017· article· en· W2755321138 on OpenAlexafffund
Adriana Blanco‐Metzler, Rafael Moreira Claro, Katrina Heredia-Blonval, Ivannia Caravaca Rodríguez, María de los Ángeles Montero-Campos, Branka Legetić, Mary R. L’Abbé

Bibliographic record

VenueNutrients · 2017
Typearticle
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsUniversity of Toronto
FundersInternational Development Research Centre
KeywordsSodiumConsumption (sociology)PopulationEnvironmental healthFood processingMedicineFood scienceChemistry

Abstract

fetched live from OpenAlex

In 2012, Costa Rica launched a program to reduce salt and sodium consumption to prevent cardiovascular disease and associated risk factors, but little was known about the level of sodium consumption or its sources. Our aim was to estimate the magnitude and time trends of sodium consumption (based on food and beverage acquisitions) in Costa Rica. Data from the National Household Income and Expenditure Surveys carried out in 2004–2005 (n = 4231) and 2012–2013 (n = 5705) were used. Records of food purchases for household consumption were converted into sodium and energy using food composition tables. Mean sodium availability (per person/per day and adjusted for a 2000-kcal energy intake) and the contribution of food groups to this availability were estimated for each year. Sodium availability increased in the period from 3.9 to 4.6 g/person/day (p < 0.001). The income level was inversely related to sodium availability. The main sources of sodium in the diet were domestic salt (60%) in addition to processed foods and condiments (with added sodium) (27.4%). Dietary sources of sodium varied within surveys (p < 0.05). Sodium available for consumption in Costa Rican households largely exceeds the World Health Organization-recommended intake levels (<2 g sodium/person/day). These results are essential for the design and implementation of effective policies and interventions.

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)0.000
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 score0.005
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.034
GPT teacher head0.310
Teacher spread0.277 · 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 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

Citations25
Published2017
Admission routes2
Has abstractyes

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