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Record W3161466986 · doi:10.1590/0102-311x00237020

Excess weight and obesity prevalence in the RPS Brazilian Birth Cohort Consortium (Ribeirão Preto, Pelotas and São Luís)

2021· article· en· W3161466986 on OpenAlexfundno aff
Carolina Abreu de Carvalho, Elma Izze da Silva Magalhães, Heloísa Bettiol, Marco Antônio Barbieri, Viviane Cunha Cardoso, Alícia Matijasevich, Ana Maria Baptista Menezes, Bernardo Lessa Horta, Fernando C. Wehrmeister, Helen Gonçalves, Iná S. Santos, Natália Peixoto Lima, Ana Karina Teixeira da Cunha França, Antônio Augusto Moura da Sílva

Bibliographic record

VenueCadernos de Saúde Pública · 2021
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersEuropean CommissionAssociação Brasileira de Saúde ColetivaInternational Development Research CentreWorld Health Organization
KeywordsObesityMedicineExcess weightOverweightCohortBody mass indexDemographyCohort studyPediatricsGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Our objective was to estimate the prevalence of excess weight and obesity, according to sex and income in the RPS Brazilian Birth Cohort Consortium (Ribeirão Preto, Pelotas, and São Luís). Participants in the Ribeirão Preto (1978/1979 and 1994), Pelotas (1982, 1993 and 2004) and São Luís (1997/1998) birth cohorts were included in different follow-ups from 7 years old onwards. Excess weight (overweight and obesity) were assessed by body mass index. The highest prevalences were observed in Ribeirão Preto (excess weight: 27.7% at 9-11 and 47.1% at 22-23 years; obesity: 8.6% at 9-11 and 19.8% at 22-23 years) while the smallest was in São Luís (excess weight: 5.4 to 7-9 and 17.2% at 18-19 years; obesity: 1.8% at 7-9 and 3.6% at 18-19 years). The younger the cohort, the greater the prevalence of excess weight and obesity when comparing similar age groups. Increases in obesity prevalence were greater than in excess weight prevalence. Women had lower excess weight prevalence in older cohorts and higher obesity prevalence in younger cohorts. Higher excess weight and obesity prevalence were observed in higher income children and adolescents, and in poorer adults. Differences in the prevalence of excess weight and obesity evidenced that individuals from younger cohorts are more exposed to this morbidity, as well as those who were born in the most developed city, low-income adults as well as children and adolescents belonging to families of the highest income tertile. Therefore, the results of this study indicate the need to prioritize actions aimed at younger individuals.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.012
GPT teacher head0.265
Teacher spread0.252 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

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