Socioeconomic status and oral health‐related quality of life: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVES: To systematically review observational studies assessing the association between socioeconomic status (SES) and oral health-related quality of life (OHRQoL) in children, adolescents and adults. METHODS: Electronic searches were performed in the PubMed, Embase, Web of Science, LILACS and Scopus databases for articles published up to September 2020. Two independent reviewers performed the search and critical appraisal of the studies. The inclusion criteria were observational studies that evaluated the effect of SES on the OHRQoL in all age groups using validated methods. Quality assessment was conducted using the Newcastle-Ottawa Scale. Data were extracted for meta-analysis followed by a meta-regression analysis. A random-effects model was used to estimate the pooled calculate prevalence ratio (PR) and respective 95% confidence intervals (CI) for each study. RESULTS: The search strategy retrieved 6114 publications. Some 139 articles met the eligibility criteria and were included in the systematic review. Of those, 75 were included in the general meta-analysis they represented a total sample of 109 269 individuals. People of lower SES had worse OHRQoL (PR 1.30; 95% CI 1.26-1.35). In the meta-analyses of different subgroups, an association was found between low SES and worse OHRQoL in countries of all economic classifications, in all age groups and irrespective of the socioeconomic indicator used. A socioeconomic gradient in OHRQoL was also observed, in which the lower the individuals' socioeconomic position, the poorer their OHRQoL. CONCLUSIONS: Individuals of low SES had poorer OHRQoL, regardless of the country's economic classification, SES indicator and age group. Public policies aiming to reduce social inequalities are necessary for better OHRQoL throughout life.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| grok | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
| opus | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | medium |
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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.029 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".