Socioeconomic Inequalities in Physical Activity and Sedentary Behaviour among the Chilean Population: A Systematic Review of Observational Studies
Bibliographic record
Abstract
Socioeconomic inequalities in physical (in)activity and sedentary behaviours are key mediators in obesity and health socioeconomic inequalities. Considering the high and uneven obesity rates in Chile, this review aims to systematically assess the socioeconomic inequalities in physical activity (PA) and sedentary behaviour (SB) among the Chilean population from different age groups. Peer-reviewed and grey literature were searched from inception until 31st December 2019 in PubMed, Scopus, PsycINFO, Web of Sciences and LILACS. Publications in English and Spanish, from observational studies that reported the comparison of at least one indicator of PA or SB between at least two groups of different socioeconomic positions (SEP), from the general Chilean population, were included. Data searches, screening, extraction, and quality assessment, using the Newcastle Ottawa Quality Assessment Scale for observational studies, were conducted by two independent researchers. Seventeen articles (from 16 studies) met the inclusion criteria (14 cross-sectional; two cohort). Across these, quality was considered low, medium and high for 19%, 69% and 13%, respectively. Results showed consistent evidence for a lower leisure-time PA and sitting time, and higher physical inactivity among adults from the lower, compared to the highest, SEP groups. Associations between SEP and total PA, moderate-to-vigorous PA, low PA, and transport and work-related PA were inconsistent. These findings provide insights to public health and physical activity researchers and policymakers aiming to reduce socioeconomic inequalities in PA and SB in Chile and other countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".