Double burden of malnutrition and its association with infant and young child feeding practices among children under-five in Thailand
Bibliographic record
Abstract
OBJECTIVE: This study examined the prevalence of stunting-overweight and socio-demographic determinants among children under-five years of age, as well as associations with infant and young child feeding (IYCF) among children aged 6-23 months. DESIGN: Secondary data analysis based on the Thailand Multiple Indicator Cluster Survey 2015-2016. SETTING: Cross-national study. PARTICIPANTS: Nationally representative sample of children under-five years of age (n 12 313). RESULTS: The prevalence of wasting, stunting, overweight and stunting-overweight was 5·3, 10·5, 10·1 and 1·6 %, respectively. In multivariate analyses, children under 6 months, children from low and middle wealth tertiles, and children living in rural areas were prone to being wasted. Male children, low wealth tertile and a non-Thai speaking household head were positively and children aged 48-59 months and a one-child household were inversely associated with stunting. Children from a low wealth tertile were less likely to be overweight, while older age, male children and children from a one-child household were more likely to be overweight. Stunting-overweight was associated with children aged 24-47 months, male children, mothers having secondary education, a one-child household, a non-Thai speaking household head and an urban area. In terms of IYCF indicators, despite no association with stunting and stunted-overweight children, current breast-feeding and inadequate meal frequency were associated with being wasting, while current breast-feeding and dietary diversity were inversely associated with being overweight. CONCLUSIONS: This study revealed the double burden of malnutrition at the individual and population levels among Thai children under-five, which calls for concrete integrated interventions to tackle all forms of malnutrition.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".