Dyslipidemia and its associated factors in Ethiopia: a systematic review and meta-analysis
Notice bibliographique
Résumé
Dyslipidemia is a major risk factor for cardiovascular disease, with its prevalence steadily rising in both developed and developing nations. An unhealthy lifestyle significantly contributes to the development of dyslipidemia, with smoking being a well-known risk factor. A comprehensive search was conducted across several databases, including Google Scholar, Web of Science, African Journals Online (AJOL), HINARI, and PubMed/MEDLINE. Articles published up until June 24, 2024, were considered for inclusion. Data extraction and organization were carried out using Microsoft Excel, while analysis was performed using STATA/MP 17.0. The quality of the included studies was evaluated using the Newcastle–Ottawa Scale (NOS). To analyze the pooled data, a weighted inverse variance random effects model with a 95% confidence interval was applied. Heterogeneity among studies was assessed using Cochrane’s I2 statistics, and Egger’s test was conducted to detect potential publication bias. The association between dyslipidemia and its associated factors was examined using the log odds ratio, with a p-value of less than 0.05 considered statistically significant. A total of 44 articles involving 12,395 participants were included. The overall pooled prevalence of dyslipidemia in Ethiopia was 56.60% (95% CI 50.40–62.80). Dyslipidemia was observed across various population groups, with notable prevalence rates associated with different risk factors. Among individuals with insufficient physical activity, the prevalence was 30.12% (95% CI 22.53–37.70). In those who smoked cigarettes, it was observed in 6.81% (95% CI 4.27–9.34). Among chronic alcohol consumers, the prevalence of dyslipidemia was 15.75% (95% CI 9.65–21.86). Furthermore, 30.12% (95% CI 22.53–37.70) of dyslipidemia was reported among individuals with inadequate physical exercise. The prevalence of dyslipidemia in Ethiopia was 56.60%, indicating a significant public health concern. The condition is particularly prevalent among individuals with insufficient physical activity, smoking habits, and chronic alcohol consumption, suggesting strong associations with these modifiable risk factors. To reduce dyslipidemia, public health initiatives should focus on promoting physical activity, anti-smoking campaigns, and educating on the risks of excessive alcohol use. Health professionals should also prioritize early detection and management in high-risk groups to reduce long-term cardiovascular risks.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,022 | 0,003 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».