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A Grandmother‐Inclusive Approach to Community Nutrition Positively Impacted Maternal Nutrition and Health Seeking Practices in Southern Sierra Leone

2017· article· en· W3027521016 on OpenAlexaffabout
Amy Girard, Rebecca Wee, Joseph Simba, Christina Gruenewald, Judi Aubel, Carolyn MacDonald, Allieu S. Bangura, Bridget Aidam

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsWorld Wildlife Fund Canada
Fundersnot available
KeywordsSierra leoneNutrition EducationBehavior change communicationEnvironmental healthMedicinePsychologySocioeconomicsGerontologySociologyPopulation

Abstract

fetched live from OpenAlex

Poor nutrition and health seeking practices of pregnant and lactating women contribute to maternal morbidity, poor birth outcomes and undernutrition of children in Sierra Leone. We examined how a grandmother (GM) inclusive approach to nutrition‐related social and behavior change affected maternal diet and health seeking practices in southern Sierra Leone. The GM‐inclusive approach is grounded in formative ethnographic research and builds on GMs' culturally‐designated role as advisors and caregivers and aims to strengthen their knowledge and confidence to promote positive change for maternal and child health. Following mixed methods formative research, World Vision implemented a quasi‐experimental proof of concept study in two sections in the Bum Chiefdom, Bonthe Sierra Leone. The villages of one section received the grandmother‐inclusive approach consisting of monthly participatory nutrition education sessions with GMs, quarterly community praise sessions focused on the attributes of and supportive roles of GMs, the identification and support of GM leaders as change agents for maternal and child health and intergenerational forums. Villages in the control section received the standard of care for nutrition education provided by the Ministry of Health. The endline survey utilized a census based sampling strategy and surveyed all women in the study communities who were pregnant (PW, N=101) or had a child less than 2 years of age (MU2, N=291). Data were collected on household sociodemographics, maternal diet and IYCF knowledge, attitudes, and intentions/practices. Preliminary analyses examined differences in proportions between intervention and comparison participants with chi‐square. The proportions of MU2 (94.6% vs. 67.3%, P <0.001) and PW (96.3% vs 61.7%, P <0.001) achieving minimum dietary diversity in the previous 24 hours were significantly higher in the intervention compared to the comparison group. As well, a significantly greater proportion of PW in the intervention group intended to consume more food (88.9% vs 48.9%, P <0.0001) and work less (94.4% and 88.1%, P =0.002) during their current pregnancy. Similarly, a significantly greater proportion of MU2 in the intervention group reported increased meal frequency (94.6% vs 63.6%, P <0.001) and decreased work (91.3% vs 75.7%, P <0.001) during their most recent pregnancy. A greater proportion of MU2 in the intervention communities also reported attending ANC at least 4 times (97.1% vs. 80.8%, P <0.001) and delivering in a health facility (96.7% vs 90.7%, P =0.03). Few studies have shown improved nutrition practices during pregnancy, and particularly during crisis (e.g., Ebola). Preliminary analyses suggest that a grandmother‐inclusive approach that recognizes GMs' role in nutrition and health and strengthens their knowledge can contribute to improved nutrition and health practices during pregnancy improved nutrition and health practices in pregnancy. Support or Funding Information Funding provided by World Vision Canada, World Vision Germany, World Vision Sierra Leone and the Emory University Global Field Experiences Program

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.060
GPT teacher head0.352
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations2
Published2017
Admission routes2
Has abstractyes

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