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Record W3177645494 · doi:10.3390/nu13072404

Socioeconomic Status Impact on Diet Quality and Body Mass Index in Eight Latin American Countries: ELANS Study Results

2021· article· en· W3177645494 on OpenAlexaff
Georgina Gómez, Irina Kovalskys, Ana Carolina Barco Leme, Dayana Quesada, Attilio Rigotti, Lilia Yadira Cortés, Martha Cecilia Yépez García, Maria Reyna Liria-Domínguez, Marianella Herrera‐Cuenca, Regina Mara Fisberg, Ágatha Nogueira Previdelli, Viviana Guajardo, Gérson Ferrari, Mauro Fisberg, Juan C. Brenes

Bibliographic record

VenueNutrients · 2021
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBody mass indexSocioeconomic statusLatin AmericansEnvironmental healthIndex (typography)DemographyMedicineGeographyGerontologyPolitical scienceInternal medicineSociologyPopulation

Abstract

fetched live from OpenAlex

Poor health and diet quality are associated with living within a low socioeconomic status (SES). This study aimed to investigate the impact of SES on diet quality and body mass index in Latin America. Data from the "Latin American Health and Nutrition Study (ELANS)", a multi-country, population-based study of 9218 participants, were used. Dietary intake was collected through two 24 h recalls from participants of Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Peru and Venezuela. Diet quality was assessed using the dietary quality score (DQS), the dietary diversity score (DDS) and the nutrients adequacy ratio (NAR). Chi-squared and multivariate-variance analyses were used to estimate possible associations. We found that participants from the low SES consumed less fruits, vegetables, whole grains, fiber and fish and seafood and more legumes than those in the high SES. Also, the diet quality level, assessed by DQS, DDS and NAR mean, increased with SES. Women in the low SES also showed a larger prevalence of abdominal obesity and excess weight than those in the middle and high SES. Health policies and behavioral-change strategies should be addressed to reduce the impact of socioeconomic factors on diet quality and body weight, with gender as an additional level of vulnerability.

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 score0.012
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.348
Teacher spread0.324 · 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

Citations86
Published2021
Admission routes1
Has abstractyes

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