Impact of Community Health Clubs on Diarrhea and Anthropometry in Western Rwanda: Cluster‐Randomized Controlled Trial
Notice bibliographique
Résumé
Objective Community health clubs (CHCs)—multi‐session village‐level gatherings led by trained facilitators, designed to promote healthful behaviors—have been implemented in several African and Asian countries but have never been rigorously evaluated. We aimed to evaluate the impact of CHCs on child health and nutrition outcomes. Methods We conducted a cluster‐randomized controlled trial to evaluate the health impact of two versions of the CHC model in Rusizi district, western Rwanda. We enrolled 8734 households with children under five years of age in a baseline survey in 2013. A total of 150 villages were randomized to three groups: no intervention (control, n=50), eight sessions (Lite, n=50), or 20 sessions (Classic, n=50). We re‐enrolled 7934 (91%) of the households in an endline survey in 2015. The primary outcomes were caregiver‐reported diarrhea in children <5 years within the previous seven days and nutritional status of children <2 years, measured through length‐for‐age (LAZ) and weight‐for‐length (WLZ) z‐scores. We measured intermediate outcomes related to water, sanitation, hygiene, infant and young child feeding, and food security. To analyze impact on dichotomous variables at the individual level, we used log‐binomial regression with a log link function and generalized estimating equations (GEE) to account for community level clustering, then exponentiated the coefficients to obtain prevalence ratios (PRs). For dichotomous outcomes at the household level, we used binomial regression with an identity link function and GEE, to obtain risk differences (RDs). For continuous variables, we used linear regression with GEE. All analyses accounted for clustering at the village level. Analysis was by intention to treat and per‐protocol. Results We observed no impact on caregiver‐reported diarrhea in the Lite (PR=0.97, 95% CI: 0.81–1.16) or the Classic group (PR=0.99, CI: 0·85–1·15). We observed no impact on LAZ in the Lite (β=−0·04, 95% CI: −0·18–0·11) or the Classic (β=−0·08, 95% CI: −0·23–0·08) group, nor on WLZ in the Lite (β=−0·01, 95% CI: −0·12–0·10) or the Classic (β=−0·07, 95% CI: −0·18–0·05) group. The Classic intervention had a positive impact on reported household water treatment (RD=0·086, 95% CI: 0·029–0·14), use of improved sanitation facilities (RD=0·085, 95% CI: 0·015–0·16), and presence of structurally complete sanitation facility (RD=0·065, 95% CI: 0·0013–0·13). There was no impact on the remaining intermediate outcomes, including improved microbiological water quality; drinking water source; presence of a hand washing station with soap; exclusive breastfeeding for children <6 months; dietary diversity for children 6–23 months; or household food security. In the Lite intervention, there was no impact on any intermediate outcomes. Per‐protocol analysis of households in the Classic arm who reported attending all 20 sessions suggested positive impacts on reported household water treatment (RD=0·20, 95% CI: 0·12–0·28), use of improved sanitation facility (RD=0·14, 95% CI: 0·053–0·22), and presence of structurally complete sanitation facility (RD=0·075, 95% CI: 0·0014–0·15). No other differences were noted. Conclusions The CHC approach, as implemented in this setting in western Rwanda, had no impact on any main outcomes, but it had a positive impact on household water treatment and type and structure of sanitation facility. Our results raise questions about the value of implementing this intervention at scale. Support or Funding Information Bill & Melinda Gates Foundation
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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 | 0,005 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».