Quantifying Contraceptive Side-Effects: A Prospective Cohort Study of Symptom Burden, Risk Factors, and Daily Life Disruption in South-Central Ethiopia
Notice bibliographique
Résumé
Abstract Unwanted side-effects are the leading cause of dissatisfaction and discontinuation of hormonal contraceptives worldwide. Yet contraceptive side-effects are commonly dismissed as minor and/or misconceptions within global health, in part due to the paucity of quantitative data on side-effects symptoms. This research aimed to (1) compare changes in symptom number and severity among hormonal contraceptive users and a control group over a 3-months period, (2) identify risk factors for such changes, and (3) evaluate their impact on women’s daily lives. We conducted an observational baseline-controlled prospective cohort study among injectable and implant users and a control group of non-users in Central Oromia, Ethiopia. Sociodemographic, diet, activity data and monthly side-effect symptoms were collected from pre-initiation to three months. Multilevel models adjusted for temporal autocorrelation were used to evaluate change in the number and severity of symptoms. Minimally adjusted models were used to identify risk factors for increased negative symptoms among contraceptive users and evaluate the impact of experiencing symptoms on women’s daily activities. A total of 278 participants (106 injectable, 72 implant, 100 non-users) were included for analysis. Compared to pre-initiation, injectable users experienced 28% more symptoms at month 3 (adjusted incident rate ratio (IRR): 1.28, 95% CI: 1.05 – 1.57 p = 0.015), implant users experienced a peak of 41% more symptoms at month 2 (adjusted IRR 1.41, 95% CI: 1.15 – 1.73, p = 0.002), and non-users experienced no changes over a similar time period. Contraceptive users with physically demanding occupations, food insecurity, and a history of recent infection experienced the greatest symptom severity, also associated with negative impacts on women’s activities, including work, chores, and relationships. These findings indicate that reducing the burden of contraceptive side effects requires addressing underlying health stressors and considering the significant impact of side-effects on women’s daily lives, rather than relying solely on dispelling misconceptions. Key messages What is already know on this topic Existing research lacks the data necessary to both identify risk factors for contraceptive side effects and assess the extent of daily disruptions caused by these symptoms. What this study adds The design of this study enables us to demonstrate that side-effects are: (1) significant: users report an increase in symptoms after initiating contraception, unlike non-users who do not exhibit such changes; (2) predictable: women experiencing health stressors (nutritional, physical and infectious) prior to initiation report the greatest number and severity of side-effects when using hormonal contraception; (3) disruptive: higher symptom severity is associated with a decreased ability to carry out key daily activities pertaining to work, relationships, and house chores. How this study might affect research, practice and/or policy Contraceptive counselling should be sensitive to variation in risk of side-effects and support women with high symptom burdens with management options or method switching, rather than dismissing concerns as misconceptions. Our findings highlight the need for further research confirming predictive drivers of side-effect experiences to guide counselling and to move towards personalised contraceptive technology development.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 ».