The prevalence of occupational injury and its associated factors in Ethiopia: a systematic review and meta-analysis
Notice bibliographique
Résumé
Abstract Background Occupation related fatality and mortality rate is becoming the devastating issue globally as reported by the International Labor Organization (ILO). Though there are reports about exposure and burden of occupational injury from the regional states, the studies were fragmented and inconclusive ones at the national level. Hence, the authors’ intention being to come up with the national pooled estimates of occupation related injury and the associated factors in Ethiopia. Methods The international reputable databases (PubMed, Google Scholar, ScienceDirect and Cochrane Library), cross-referencing and manual search strategies were explored rigorously following Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol (PRISMA-P) guideline. Studies that reported the prevalence of occupational injury were included for this systematic review and meta-analysis. The Newcastle-Ottawa quality assessment tool scale for cross-sectional studies was used for the critical appraisal of the studies. The heterogeneity between the studies was checked using Cochran Q statistic with the inverse variance (I2) value. Random effects meta-analysis was considered assess the summative effect size of occupational injury and the factors associated with it. Subgroup analysis and meta-regression were also employed to identify the possible source of heterogeneity and factors associated with occupational injury respectively. Both Egger’s and Begg’s test with the p-value less than 5% were used to declare the presence of publication bias. Results A total of 23 original studies were considered to estimate the pooled effect size of occupational injury in Ethiopia. The pooled prevalence of occupational injury in Ethiopia was 44.66% (95% CI: 43.83, 45.49). Based on the subgroup analysis, the highest prevalence of occupational injury was reported from the construction sites (50.8%) in particular of the Addis Ababa city administration (49.5.Being male workers [OR = 1.46 (95% CI: 1.01, 2.11)], working more than eight hours per day [OR = 2.84 (95% CI: 1.81, 4.46)], absence of supervision for labor workers [OR = 1.60 (95% CI: 1.08, 2.37)], lack of personal protective equipment [OR = 3.01 (95% CI: 1.61, 5.63)] and lack of occupational health and safety training [OR = 1.49 (95% CI: 1.15, 1.92)] had increased odds of occupational injury. Conclusion Based on this systematic review and meta-analysis, it is concluded that nearly half of the labor workers in Ethiopia were experienced occupational injury. This issue was more encountered among the labor workers of construction sites and whose working place were at the Addis Ababa city administration respectively. Being male sex, working more than eight hours per day, lack of personal protective equipment, lack of supervision, and lack of training about occupational health and safety had increased odds of occupational injury in Ethiopia. Hence, the concerned body should give special emphasis for all the explored factors in order to minimize occupation related injury, mortality and morbidity in the country.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,016 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,018 | 0,039 |
| Bibliométrie | 0,012 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».