Contraceptive Use Measured in a National Population–Based Approach: Cross-Sectional Study of Administrative Versus Survey Data
Notice bibliographique
Résumé
BACKGROUND: Prescribed contraception is used worldwide by over 400 million women of reproductive age. Monitoring contraceptive use is a major public health issue that usually relies on population-based surveys. However, these surveys are conducted on average every 6 years and do not allow close follow-up of contraceptive use. Moreover, their sample size is often too limited for the study of specific population subgroups such as people with low income. Health administrative data could be an innovative and less costly source to study contraceptive use. OBJECTIVE: We aimed to explore the potential of health administrative data to study prescribed contraceptive use and compare these data with observations based on survey data. METHODS: We selected all women aged 15-49 years, covered by French health insurance and living in France, in the health administrative database, which covers 98% of the resident population (n=14,788,124), and in the last French population-based representative survey, the Health Barometer Survey, conducted in 2016 (n=4285). In health administrative data, contraceptive use was recorded with detailed information on the product delivered, whereas in the survey, it was self-declared by the women. In both sources, the prevalence of contraceptive use was estimated globally for all prescribed contraceptives and by type of contraceptive: oral contraceptives, intrauterine devices (IUDs), and implants. Prevalences were analyzed by age. RESULTS: There were more low-income women in health administrative data than in the population-based survey (1,576,066/14,770,256, 11% vs 188/4285, 7%, respectively; P<.001). In health administrative data, 47.6% (7034,710/14,770,256; 95% CI 47.6%-47.7%) of women aged 15-49 years used a prescribed contraceptive versus 50.5% (2297/4285; 95% CI 49.1%-52.0%) in the population-based survey. Considering prevalences by the type of contraceptive in health administrative data versus survey data, they were 26.9% (95% CI 26.9%-26.9%) versus 27.7% (95% CI 26.4%-29.0%) for oral contraceptives, 17.7% (95% CI 17.7%-17.8%) versus 19.6% (95% CI 18.5%-20.8%) for IUDs, and 3% (95% CI 3.0%-3.0%) versus 3.2% (95% CI 2.7%-3.7%) for implants. In both sources, the same overall tendency in prevalence was observed for these 3 contraceptives. Implants remained little used at all ages, oral contraceptives were highly used among young women, whereas IUD use was low among young women. CONCLUSIONS: Compared with survey data, health administrative data exhibited the same overall tendencies for oral contraceptives, IUDs, and implants. One of the main strengths of health administrative data is the high quality of information on contraceptive use and the large number of observations, allowing studies of subgroups of population. Health administrative data therefore appear as a promising new source to monitor contraception in a population-based approach. They could open new perspectives for research and be a valuable new asset to guide public policies on reproductive and sexual health.
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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 | 0,007 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 ».