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Harnessing Poshan Tracker to Detect Composite Index of Anthropometric Failure Among 0-3 Year Olds in Rural Puducherry

Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Evidences suggest that the conventional indicators of malnutrition does not reflect the holistic burden of malnutrition. Hence, the utilization of Composite index of anthropometric failure (CIAF) for reporting malnutrition in Indian context was recommended. Our objective was to determine the proportion of children with CIAF and its association with age and sex in 0-3 years children from selected Anganwadis’ of rural Puducherry. Methods: This cross-sectional study using secondary data of 0-3 years was conducted across the 25 Anganwadis’ of our rural field practice area during July 2024. All children of 0-3 years whose length (<2 years)/height (≥2 years), weight and date of birth information were available in the Poshan Tracker were included in the study. The interpretation of their nutritional status was obtained from the Poshan Tracker. WHO Anthro Survey analyser and R software was used for further analysis. Results: Of the 829 children, proportion of children with CIAF was 281(33.8%). There was a significant difference in proportion of anthropometric failure between girls with 28% and boys with 41% (P <0.001). As per CIAF stages (N=281), stunting was the predominant form of malnutrition in 19% followed by stunting and underweight in 6% and wasting in 3.6%. The prevalence of anthropometric failure was higher in children between 1-2 years and among boys. Interpretation and Conclusions: One in three children of 0-3 years age group had anthropometric failure with more prevalence among children less than two years and boys. Longitudinal follow up of these children along with exploration of their dietary intake might provide insights for targeted interventions. The cross-sectional nature of this study limits causality inference.
DOI: 10.55489/njcm.161220255850
Language: English
Field: Nursing
Open Access status: diamond
OpenAlex ID: W4416841035
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