Non-communicable disease mortality in young people with a history of contact with the youth justice system in Queensland, Australia: a retrospective, population-based cohort study
Notice bibliographique
Résumé
BACKGROUND: Young people who have had contact with the criminal justice system are at increased risk of early death, especially from injuries. However, deaths due to non-communicable diseases (NCDs) in this population remain poorly described. We aimed to estimate mortality due to NCDs in people with a history of involvement with the youth justice system, compare NCD mortality rates in this population with those in the general population, and characterise demographic and justice-related factors associated with deaths caused by NCDs in people with a history of contact with the youth justice system. METHODS: In this retrospective, population-based cohort study (the Youth Justice Mortality [YJ-Mort] study), we included all people aged 10-18 years (at baseline) charged with a criminal offence in Queensland, Australia, between June 30, 1993, and July 1, 2014. We probabilistically linked youth justice records with adult correctional records and national death records up to Jan 31, 2017. Indigenous status was ascertained from youth justice and adult correctional records, with individuals identified as Indigenous in either source classified as Indigenous in the final dataset. We estimated crude mortality rates and standardised mortality ratios (SMRs) for comparisons with data from the Australian general population. We identified risk factors for NCD deaths using competing-risks regression. FINDINGS: Of 48 670 individuals aged 10-18 years (at baseline) charged with a criminal offence in Queensland, Australia, between June 30, 1993, and July 1, 2014, 11 897 (24·4%) individuals were female, 36 773 (75·6%) were male, and 13 250 (27·2%) were identified as identified as Indigenous. The median age at first contact with the youth justice system was 15 years (IQR 14-16), the median follow-up time was 13·4 years (8·4-18·4), and the median age at the end of the study was 28·6 years (23·6-33·6). Of 1431 deaths, 932 (65·1%) had a known and attributed cause, and 121 (13·0%) of these were caused by an NCD. The crude mortality rate from NCDs was 18·5 (95% CI 15·5-22·1) per 100 000 person-years among individuals with a history of involvement with the youth justice system, which was higher than among the age-matched and sex-matched Australian general population (SMR 1·67 [1·39-1·99]). Two or more admissions to adult custody (compared with none; adjusted sub-distribution hazard ratio 2·09 [1·36-3·22]), and up to 52 weeks in adult custody (compared with none; 1·98 [1·18-3·32]) was associated with NCD death. INTERPRETATION: Young people with a history of contact with the justice system are at increased risk of death from NCDs compared with age-matched and sex-matched peers in the general Australian population. Reducing youth incarceration and providing young people's rights to access clinical, preventive, and restorative services should be a priority. FUNDING: National Health and Medical Research Council.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».