The association between neighborhood socioeconomic status and the risk of incidence and mortality of colorectal cancer: A systematic review and meta-analysis of 1,678,582 participants
Bibliographic record
Abstract
We conducted a systematic review and meta-analysis to evaluate the association between neighborhood socioeconomic status (n-SES) and the risk of incidence and mortality in colorectal cancer (CRC). A comprehensive literature search was performed using PubMed/MEDLINE, ISI Web of Science and Scopus without any limitation until October 11, 2023. Inclusion criteria consisted of observational studies in adult subjects (≥18 years) which provided data on the association between n-SES and CRC-related incidence and mortality. Relative risk (RR) and 95 % confidence interval (CI) were pooled by employing a random-effects model. We employed validated methods to assess study quality and publication bias, utilizing the Newcastle-Ottawa Scale for quality evaluation, subgroup analysis to find possible sources of heterogeneity, Egger's regression asymmetry and Begg's rank correlation tests for bias detection and sensitivity analysis. Finally, 24 studies (21 cohorts and 3 cross-sectional studies) from seven different countries with 1678,582 participants were included. The analysis suggested that a significant association between lower n-SES and an increased incidence of CRC (RR=1.11; 95 % CI: 1.08, 1.14; I 2 =64.4 %; p<0.001; n=46). The analysis also indicated a significant association between lower n-SES and an increased risk of mortality of CRC (RR=1.21; 95 % CI: 1.16, 1.26; I 2 =76.4 %; p<0.001; n=23). Furthermore, subgroup analysis revealed that there was a significant association between lower n-SES and an increased risk of incidence of CRC in colon location (RR=1.06; 95 % CI: 1.02, 1.10; I2=0.0 %; p=0.001; n=8), but not rectal location. In addition, subgroup analysis for covariates adjustment suggested that body mass index, smoking, physical activity, alcohol intake, or sex adjustment may influence the relationship between n-SES and the risk of incidence and mortality in CRC. Lower n-SES was found to be a contributing factor to increased incidence and mortality rates associated with CRC, highlighting the substantial negative impacts of lower n-SES on cancer susceptibility and health outcomes. • A significant association was observed between lower n-SES and an increased incidence of CRC. • A significant association was observed between lower n-SES and an increased mortality of CRC. • There was a significant association between lower n-SES and an increased risk of incidence of CRC in colon location.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".