Spatial distribution and determinants of health care access barriers among female Pakistan youths: spatial and multilevel regression analysis
Notice bibliographique
Résumé
INTRODUCTION: Ensuring universal access to high-quality healthcare services including services free from financial barriers, is a global priority. However, accessing healthcare services remains challenging for youth in low- and middle-income countries (LMICs), including Pakistan. This study investigates the spatial distribution and determinants of healthcare access barriers among female youths in Pakistan. METHODS: We used the 2017/18 Pakistan Demographic and Health Survey (PDHS) dataset, including 2,924 female youth aged 15-24, to examine healthcare access barriers. These barriers were considered as an outcome variable and were regarded where a respondent reported encountering any of the following impediments to accessing healthcare services during illness: (i) difficulty obtaining permission to visit a health facility; (ii) financial constraints in meeting healthcare expenses or treatment costs; (iii) significant travel distance to access a health facility; and (iv) reluctance to visit health facilities alone. To analyse multi-level determinants and geographical disparities in healthcare access barriers among youths, we employed multilevel logistic regression and spatial analysis techniques, respectively. The analysis accounted for sample weights to ensure the robustness and representativeness of the findings. RESULTS: Almost four-fifths (79.4%) of female youth in Pakistan (95% CI: 77.9 to 80.9) have reported having perceived barriers to accessing healthcare services. Barriers to accessing healthcare among female youth were associated with not having employment (AOR = 1.96; 95% CI; 1.39, 2.76), living in a household where the head was a male (AOR = 1.97; 95% CI; 1.40, 2.77), having low and middle household wealth status (low: AOR = 3.22; 95% CI; 2.18, 4.75; middle: AOR = 1.89; 95% CI; 1.36, 2.63), being unempowered (AOR = 2.08; 95% CI; 1.55, 2.80), and residing in areas with low community female youth literacy rates (AOR = 1.48; 95% CI: 1.02, 2.15) and living in federally administered tribal areas (FATA), Balochistan, and Azad Jammu and Kashmir (AJK) regions. CONCLUSION: A substantial proportion of female youth in Pakistan have major perceived barriers to accessing healthcare services. Several individual- and community-level factors were associated with perceived barriers to accessing healthcare services among female youth. Significant geographic variation was observed in the perceived barriers to healthcare services among Pakistan's female youth. Policymakers had better take measures to improve access to healthcare services through the formulation of youth-responsive policies and strategies.
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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 | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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) | 0,000 | 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 ».