Association Between Socioeconomic Status and Adherence to Fecal Occult Blood Tests in Colorectal Cancer Screening Programs: Systematic Review and Meta-Analysis of Observational Studies
Bibliographic record
Abstract
BACKGROUND: Screening adherence is important in reducing colorectal cancer (CRC) incidence and mortality. Disparity in CRC screening adherence was observed in populations of different socioeconomic status (SES), but the direction and strength of the association remained unclear. OBJECTIVE: We aimed to systematically review all the observational studies that have analyzed the association between SES and adherence to organized CRC screening based on fecal occult blood tests. METHODS: We systematically reviewed the studies in PubMed, Embase, and Web of Science and reference lists of relevant reviews from the inception of the database up until June 7, 2023. Individual SES, neighborhood SES, and small-area SES were included, while any SES aggregated by geographic areas larger than neighbors were excluded. Studies assessing SES with any index or score combining indicators of income, education, deprivation, poverty, occupation, employment, marital status, cohabitation, and others were included. A random effect model meta-analysis was carried out for pooled odds ratios (ORs) and relative risks for adherence related to SES. RESULTS: Overall, 10 studies, with a total of 3,542,379 participants and an overall adherence rate of 64.9%, were included. Compared with low SES, high SES was associated with higher adherence (unadjusted OR 1.73, 95% CI 1.42-2.10; adjusted OR 1.53, 95% CI 1.28-1.82). In the subgroup of nonindividual-level SES, the adjusted association was significant (OR 1.57, 95% CI 1.26-1.95). However, the adjusted association was insignificant in the subgroup of individual-level SES (OR 1.46, 95% CI 0.98-2.17). As for subgroups of the year of print, not only was the unadjusted association significantly stronger in the subgroup of early studies (OR 1.97, 95% CI 1.59-2.44) than in the subgroup of late studies (OR 1.43, 95% CI 1.31-1.56), but also the adjusted one was significantly stronger in the early group (OR 1.86, 95% CI 1.43-2.42) than in the late group (OR 1.26, 95% CI 1.14-1.39), which was consistent and robust. Despite being statistically insignificant, the strength of the association seemed lower in studies that did not adjust for race and ethnicity (OR 1.31, 95% CI 1.21-1.43) than the overall estimate (OR 1.53, 95% CI 1.28-1.82). CONCLUSIONS: The higher-SES population had higher adherence to fecal occult blood test-based organized CRC screening. Neighborhood SES, or small-area SES, was more competent than individual SES to be used to assess the association between SES and adherence. The disparity in adherence between the high SES and the low SES narrowed along with the development of interventions and the improvement of organized programs. Race and ethnicity were probably important confounding factors for the association.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".