Modern contraceptive utilization and associated factors among married and cohabiting women in Papua New Guinea: a population-based cross-sectional study
Notice bibliographique
Résumé
BACKGROUND: Universal access to family planning has been emphasized by the international development agenda, as evident in the Sustainable Development Goal 3.7. This notwithstanding, the use of modern contraceptives has been minimal in low- and middle-income countries, especially in Papua New Guinea. In view of this, we investigated the factors associated with the use of modern contraceptives and the associated factors among married and cohabiting women in Papua New Guinea. METHODS: The study utilised the Demographic and Health Survey data of 2345 women in sexual unions in Papua New Guinea. We employed a descriptive and binary logistic regression analyses. We presented the results as crude Odds Ratios (COR) and adjusted Odds Ratios (AOR), with 95% confidence intervals (CI) signifying level of precision. Level of statistical significance was set at p < 0.05. RESULTS: We found that 74.4% of the women were using modern contraceptives ranging from injectables (44.5%) to other modern methods (0.23%). Women aged 15-19 [AOR = 7.425, 95% CI = 2.853, 19.32], residents of the Highland region [AOR = 1.521, 95% CI =1.086, 2.131], self-employed women in the agricultural sector [AOR = 1.710, 95% CI = 1.218, 2.400], and women who listened to radio at least once a week [AOR = 1.409, 95% CI = 1.048, 1.895] had higher odds of modern contraceptive usage. However, women in the Islands region [AOR = 0.291, 95% CI = 0.224, 0.377], women whose husbands had higher education [AOR = 0.531,95%CI = 0.318,0.886], women in professional/technical/managerial work [AOR = 0.643, 95% CI = 0.420, 0.986], and those with no child [AOR = 0.213, CI = 0.0498,0.911] had lower odds of modern contraceptive use. CONCLUSION: Out of the 2345 participants, we found that majority of them were using modern contraceptives and the commonly used modern contraceptive was injectables. Age, region of residence, partner's education, employment, partner's desire for children, and frequency of listening to radio are associated with modern contraceptive usage. Tailored reproductive healthcare should be developed for women who are disadvantaged when it comes to the usage of modern contraceptives in order to boost modern contraceptive use among them. Further investigation is needed to unravel the motivation for the high usage of injectables among married and cohabiting women in Papua New Guinea.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,000 | 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 ».