Impact of Community Health Clubs on Diarrhea and Anthropometry in Western Rwanda: Cluster‐Randomized Controlled Trial
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".