Prevalence and determinants of non-communicable diseases risk factors among reproductive-aged women: Findings from a nationwide survey in Bangladesh
Notice bibliographique
Résumé
INTRODUCTION: Knowing the risk factors like smoking status, overweight/obesity, and hypertension among women of reproductive age could allow the development of an effective strategy for reducing the burden of non-noncommunicable diseases. We sought to determine the prevalence and determinants of smoking status, overweight/obesity, hypertension, and cluster of these non-noncommunicable diseases risk factors among Bangladeshi women of reproductive age. METHODS: This study utilized the Bangladesh Demographic and Health Survey (BDHS) data from 2017-2018 and analyzed 5,624 women of reproductive age (age 18-49 years). This nationally representative cross-sectional survey utilized a stratified, two-stage sample of households. Poisson regression models with robust error variance were fitted to find the adjusted prevalence ratio (APR) for smoking, overweight/obesity, hypertension, and for the clustering of non-noncommunicable diseases risk factors across demographic variables. RESULTS: The average age of 5,624 participants was 31 years (SD = 9.1). The prevalence of smoking, overweight/obesity, and hypertension was 9.6%, 31.6%, and 20.3%, respectively. More than one-third of the participants (34.6%) had one non-noncommunicable diseases risk factor, and 12.5% of participants had two non-noncommunicable diseases risk factors. Age, education, wealth index, and geographic location were significantly associated with smoking status, overweight/obesity, and hypertension. Women between 40-49 years had more non-noncommunicable diseases risk factors than 18-29 years aged women (APR: 2.44; 95% CI: 2.22-2.68). Women with no education (APR: 1.15; 95% CI: 1.00-1.33), married (APR: 2.32; 95% CI: 1.78-3.04), and widowed/divorced (APR: 2.14; 95% CI: 1.59-2.89) were more likely to experience multiple non-noncommunicable diseases risk factors. Individuals in the Barishal division, a coastal region (APR: 1.44; 95% CI: 1.28-1.63) were living with a higher number of risk factors for non-noncommunicable diseases than those in the Dhaka division, the capital of the country. Women who belonged to the richest wealth quintile (APR: 1.82; 95% CI: 1.60-2.07) were more likely to have the risk factors of non-noncommunicable diseases. CONCLUSIONS: The study showed that non-noncommunicable diseases risk factors are more prevalent among women from older age group, currently married and widowed/divorced group, and the wealthiest socio-economic group. Women with higher levels of education were more likely to engage in healthy behaviors and found to have less non-noncommunicable diseases risk factors. Overall, the prevalence and determinants of non-noncommunicable diseases risk factors among reproductive women in Bangladesh highlight the need for targeted public health interventions to increase opportunities for physical activity and reduce the use of tobacco, especially the need for immediate interventions in the coastal region.
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 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».