ArticleCureus2026
Analysis of Factors Affecting Child Nutrition in Nepal Using the Nepal Demographic and Health Survey 2022.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Child malnutrition remains a major public health problem globally, including in Nepal. Previous studies reported that low maternal body mass index, maternal education, wealth status, anemia, low birth weight, etc., are significant predictors of childhood under-nutrition. However, child feeding practices/complementary feeding, in multivariable models specific to each anthropometric outcome, have not been explored. This study, using updated information from the Nepal Demographic and Health Survey (NDHS) 2022, will address child factors such as feeding practices, especially focusing on complementary feeding of younger children, along with other birth factors, parental factors, and socioeconomic factors. Methods This study used nationally representative data from the NDHS 2022, where a total of 629 children aged 6-23 months were selected for analysis. Three anthropometric indicators (stunting, wasting, and underweight) were used to monitor the nutritional status of children. Independent variables were child characteristics, infant and young child feeding practices, parental factors, household wealth, and region. Binomial logistic regression analysis was carried out after adjusting for covariates. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were reported, and p-values <0.05 were considered statistically significant. Results Children with increasing age (12-23 months) had significantly higher odds of stunting. Children from households with better economic status showed lower odds of stunting. Children perceived as very small birth size had significantly higher odds of stunting (OR = 6.06; 95% CI: 2.05-17.91; p = 0.001) and being underweight (OR = 6.28; 95% CI: 2.06-19.17; p = 0.001). Maternal factors showed a strong association with all three outcomes. Children whose fathers underwent secondary and higher education had significantly greater odds of wasting compared with those whose fathers had no education (OR = 3.56; 95% CI: 1.08-11.82; p = 0.038), (OR = 11.40; 95% CI: 2.14-60.58; p = 0.004), respectively. Feeding frequency and minimum dietary diversity score were not significantly associated with any of the three anthropometric outcomes. Conclusion The findings of this study showed that the increasing age of children was significantly associated with stunting. Maternal education, maternal age, and maternal BMI were important protective determinants of child under-nutrition. From the findings of this study, complementary feeding practices, along with maternal and household factors, may prevent child under-nutrition.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.