P-333 Health related economic burden among unorganized sector workers: a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Unorganized sector constitutes around 87% working population in India (Periodic Labor Force Survey, 2017 – 18) and 60% working population around the world (ILO Report 2018). Aim of the current study is to find the proportion of the income spent on Health among unorganized sector workers around the world. Materials and Methods A systematic search was conducted for published studies in English till December 2022. Independent two electroic searches were carried out in PubMed, EMBASE and Web of Science using key words ‘economic burden/financial burden/monetary/cost of illness/Health care cost’ AND ‘unorganized sector/informal sector/blue-collar job/agricultural laborer/construction workers/migrant workers/leather workers/artisans/beedi workers/fishermen/barbers/newspaper vendors/vegetable vendors/fruit vendors/casual laborer/mill workers.’ We have included articles reporting total income of the worker, health related cost. References of the selected articles were also traced. Meta-analysis was performed to calculate pooled estimate using random effects model. Quality of studies was assessed using Newcastle Ottawa Scale adapted for cross-sectional studies. Results We have got 321 records from all searched data bases. Of which, 16 records were included for full text review after screening abstract and removing duplicates. Finally, five records were included for meta-analysis. All the variables were first converted from the local currency to USD of that particular year and then to USD of 2022 after adjusting for inflation. Proportion of income was spent on Health was 15.9% (95% CI: 10.9 – 21.7) of the total income earned among the workers belonging to unorganized sector. Significant amount of heterogeneity (I2 = 92.34%) existed among studies. Conclusion A significant proportion of total income of unorganized sector workers is being utilized for Health. There is thus an urgent need for devising means of publicly funded healthcare services for the unorganized sector workers.
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 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 | 0.011 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.021 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".