Abstract
Flood is an annual phenomenon in Assam. This study aims to understand the after flood effects on children in the worst flood-hit districts of Assam during the last decades most devastating flood where more than 1,00,000 people were affected. A cross sectional population-based study was done covering 7512 children of 0–12 years of age in 35 worse flood-affected villages in three districts of lower Assam for nutritional risk profiling, low birth weight and morbidity pattern. Anthropometric measurements of the children were compared with standard WHO definitions for nutritional risk profiling. ANOVA was conducted to see any relationship of nutritional status between the age groups and BMI for the districts. Two-factor ANOVA to analyse the effect of ARI on the morbidity status of different districts was done. District-wise and village-wise heat maps were generated to understand different nutritional parameters for analysing which areas within each district are more affected and why. The moderate (< 2SD) and severely underweight (< 3SD) children under 5 years of age were highest in the Barpeta district (45.5% and 24.2% respectively). The moderate and severe stunting was highest in Morigaon (47.6%) and Barpeta (24.3%) respectively. The moderate and severe wasting was highest in the Morigaon district (46.1% and 20.6% respectively). All the nutritional indicators were less than the WHO standard. The age-wise and district-wise distribution of nutritional status shows variations in all three districts. Severe underweight was observed highest among 24–35 months’ children (50.9%) in Barpeta. The moderate and severe undernutrition status was found to be higher among the age group of 10–12 years of age compared to 5 to 10 years. This survey has provided a comprehensive picture of the nutritional status of the targeted children in the worst flood-affected areas. However, attention to its impact on health particularly among those exposed at very early stages in life is still lacking. This kind of rapid assessment helps to understand the health and nutritional status of the vulnerable groups in a deeper way and to plan robust region-specific interventions.
Published Version
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