Determinants of adherence to micronutrient powder use among young children in Ethiopia
Bibliographic record
Abstract
In Ethiopia, home fortification of complementary foods with micronutrient powders (MNPs) was introduced in 2015 as a new approach to improve micronutrient intakes. The objective of this study was to assess factors associated with intake adherence and drivers for correct MNP use over time to inform scale-up of MNP interventions. Mixed methods including questionnaires, interviews and focus group discussions were used. Participants, 1,185 children (6-11 months), received bimonthly 30 MNP sachets for 8 months, with instruction to consume 15 sachets/month, that is, a sachet every other day and maximum of one sachet per day. Adherence to distribution (if child receives ≥14 sachets/month) and adherence to instruction (if child receives exactly 15[±1] sachets/month) were assessed monthly by counting used sachets. Factors associated with adherence were examined using generalized estimating equations. Adherence fluctuated over time, an average of 58% adherence to distribution and 28% for adherence to instruction. Average MNP consumption was 79% out of the total sachets provided. Factors positively associated with adherence included ease of use (instruction), child liking MNP and support from community (distribution and instruction) and mother's age >25 years (distribution). Distance to health post, knowledge of correct use (OR = 0.74, 95% CI = 0.66-0.81), perceived negative effects (OR = 0.73, 95% CI = 0.54-0.99) and living in Southern Nations, Nationalities and People Region (OR = 0.59, 95% CI = 0.52-0.67) were inversely associated with adherence to distribution. Free MNP provision, trust in the government and field staff played a role in successful implementation. MNP is promising to be scaled-up, by taking into account factors that positively and negatively determine adherence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".