Individual-level determinants of depressive symptoms and associated diseases history in Turkish persons aged 15 years and older: A population-based study
Notice bibliographique
Résumé
Background: Depressive symptoms are associated with both long-lasting and short-term repetitive mood disorders and affect a person's ability to function and lead a rewarding life. In addition to predisposing genetic causes, other factors such as socioeconomic and demographic factors, and chronic diseases have also been reported to associate with depression. In this study, we analyzed the association between history of chronic diseases and presentation of depressive symptoms amongst Turkish individuals. Methods: We employed the 2019 Turkey health survey to analyze data of 11,993 individuals aged 15+ years. Depressive symptoms were assessed using the eight-item Patient Health Questionnaire (PHQ-8) coded with a binary measure, a score of <10 as less depressed and >10 as moderate-severely depressed. A number of sociodemographic characteristics were adjusted for in the analyses. Logistic regression models were used to test the association between chronic diseases and depressive symptoms in the study sample. Results: Our analysis revealed that 6.24% of the 11,993 participants had reported an episode of depressive symptoms. The prevalence of depressive symptoms in men was 1.85% and in women, it was 2.34 times higher. Participants who had previously reported experiencing coronary heart diseases (AOR = 7.79, 95% CI [4.96-12.23]), urinary incontinences (AOR = 7.90, 95% CI [4.93-12.66]), and liver cirrhosis (AOR = 7.50, 95% CI [4.90-10.42]) were approximately eight times likely to have depressive symptoms. Similarly, participants with Alzheimer's disease (AOR = 6.83, 95% CI [5.11-8.42]), kidney problems (AOR = 6.63, 95% CI [4.05-10.85]), and history of allergies (AOR = 6.35, 95% CI [4.28-9.23]) had approximately seven-fold odds of reporting episodes of depressive symptoms. The odds of presenting with depressive symptoms amongst participants aged ≥ 50 were higher than in individuals aged ≤ 49 years. Conclusion: At individual level, gender and general health status were associated with increased odds of depression. Furthermore, a history of any of the chronic diseases, irrespective of age, was a positive predictor of depression in our study population. Our findings could help to serve as a reference for monitoring depression amongst individuals with chronic conditions, planning health resources and developing preventive and screening strategies targeting those exposed to predisposing factors.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| 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 ».