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Record W4404373972 · doi:10.1371/journal.pgph.0003719

Did socioeconomic inequalities in overweight and obesity in South African women of childbearing age improve between 1998 and 2016? A decomposition analysis

2024· article· en· W4404373972 on OpenAlexaff
Mweete D Nglazi, John E. Ataguba

Bibliographic record

VenuePLOS Global Public Health · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of Manitoba
FundersMedical Research CouncilDivision of Research Capacity DevelopmentSouth African Medical Research Council
KeywordsOverweightSocioeconomic statusObesityInequalityBody mass indexMedicineResidenceDemographyEnvironmental healthGerontologyPopulationSociologyMathematicsEndocrinology

Abstract

fetched live from OpenAlex

Overweight and obesity in adult women contribute to deaths and disability from non-communicable diseases (NCDs) and obesity-related health problems in their offspring. Globally, overweight and obesity prevalence among women of childbearing age (WCBA) has increased, but associated socioeconomic inequality remains unclear. This study, therefore, assesses the changing patterns in the socioeconomic inequality in overweight and obesity among South African non-pregnant WCBA between 1998 and 2016. It uses data from the 1998 and 2016 Demographic and Health Surveys. Socioeconomic inequality in overweight and obesity was assessed using the concentration index (C). The index was decomposed to identify contributing factors to obesity and overweight inequalities. Factors contributing to changes in inequalities between 1998 and 2016 were assessed using the Oaxaca-type decomposition approach. Socioeconomic inequalities in overweight and obesity among WCBA in South Africa increased between 1998 (C of 0.02 and 0.06, respectively) and 2016 (C of 0.04 and 0.08, respectively). Socioeconomic status was the biggest contributor to overweight and obesity inequalities for both years. The Oaxaca-type decomposition showed that race and urban residence are major contributors to changes in overweight and obesity inequalities. Policies such as the current tax on sugar-sweetened beverages and subsidising fruits and vegetables, among others, are needed to prioritise WCBA, especially for those from disadvantaged socioeconomic backgrounds, in addressing inequalities in overweight and obesity in South Africa.

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)0.003
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 score0.047
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.035
GPT teacher head0.299
Teacher spread0.265 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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