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Record W4414290427 · doi:10.2196/76666

Effects of Maternal Use of the Continuum of Care on Complementary Feeding Practices in Bangladesh: Cross-Sectional Study

2025· article· en· W4414290427 on OpenAlexvenueno aff
M. A. Rifat, Rokibul Islam, Rinath Bintey Didar, Joya Bhowmick, Plabon Sarkar, Md Ruhul Amin, Sanjib Saha

Bibliographic record

VenueJMIR Public Health and Surveillance · 2025
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthMaternal healthHealth careContinuum of carePopulationMEDLINE

Abstract

fetched live from OpenAlex

Background: The continuum of care (CoC) for maternal health, which includes ≥4 antenatal care (ANC) visits, delivery assisted by skilled birth attendants, and a postnatal care (PNC) visit within 48 hours of delivery, is a crucial health care package associated with survival and improved health outcomes for children and mothers. In addition, the CoC serves as a platform for delivering messages and counseling on child feeding practices. However, the effect of maternal use of the CoC on complementary feeding practices in Bangladesh remains unexamined. Objective: This study aimed to estimate the effect of maternal use of CoC on complementary feeding practices among children aged 6 to 23 months in Bangladesh. Methods: Data from 2 consecutive nationally representative surveys-the Bangladesh Demographic and Health Survey 2017-2018 and 2022-were analyzed. Observations corresponding to the CoC for maternal health and complementary feeding indicators, including (1) timely introduction of solid, semisolid, and soft food (ISSSF); (2) minimum meal frequency (MMF); (3) minimum dietary diversity (MDD); and (4) minimum acceptable diet (MAD), were merged to prepare the analyzed samples. The differences in complementary feeding practice indicators by maternal use of the CoC were observed using chi-square tests. Multivariable logistic regression models were used to observe the associations. Results: The analysis included 887, 4967, 4967, and 4967 mother-child pairs for the timely ISSSF, MMF, MDD, and MAD indicators, respectively. The status of complementary feeding indicators was significantly different (P<.05) by maternal use of the full CoC, ≥4 ANC visits, status of receiving PNC within 48 hours of birth, maternal educational level, husband's educational level, maternal occupation, wealth index of families, maternal perceived problems with accessing health care, and division of residence. Mothers who received the full CoC were 29% and 32% more likely to meet the MDD (adjusted odds ratio [AOR] 1.29, 95% CI 1.10-1.51; P=.002) and MAD (AOR 1.32, 95% CI 1.13-1.55; P=.001) than those who did not receive the full CoC, respectively. Among the individual components of the CoC, mothers who received ≥4 ANC visits were 23%, 31%, and 34% more likely to meet the MMF (AOR 1.23, 95% CI 1.05-1.45; P=.01), MDD (AOR 1.31, 95% CI 1.13-1.51; P<.001), and MAD (AOR 1.34, 95% CI 1.15-1.56; P<.001) than those with fewer ANC visits, respectively. Furthermore, the effects of delivery assisted by skilled birth attendants and receiving PNC within 48 hours of delivery on complementary feeding indicators were also statistically insignificant (P≥.05). Conclusions: Maternal use of the CoC appears to be effective in improving MDD and MAD among children aged 6 to 23 months in Bangladesh. The findings highlight the pivotal role of recommended ANC visits in promoting complementary feeding practices and further suggest opportunities to amplify the impact of CoC on timely ISSSF and MMF.

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)0.004
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 score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.044
GPT teacher head0.373
Teacher spread0.329 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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