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Socio-economic and demographic factors affecting the Composite Index of Anthropometric Failure (CIAF)
1Department of Anthropology, University of North Bengal, India. jaydipsen@rediffmail.com
Insights
The Composite Index of Anthropometric Failure (CIAF) more accurately identifies undernourished children than traditional methods. This index highlights how socio-economic factors impact multiple nutritional failures in children.
Area of Science:
- Nutritional epidemiology
- Public health
Background:
- Conventional nutritional indices may underestimate the prevalence of under-nutrition.
- Assessing the impact of socio-economic and demographic factors is crucial for targeted interventions.
Purpose of the Study:
- To evaluate the Composite Index of Anthropometric Failure (CIAF) against conventional indices for nutritional assessment.
- To determine the influence of socio-economic and demographic variables on CIAF in children.
Main Methods:
- Cross-sectional study of 3444 children (aged 1-12 years) in Darjeeling district, West Bengal, India.
- Collected anthropometric, socio-economic, and demographic data.
- Used multinomial logistic regression to analyze factors affecting CIAF.
Main Results:
- Under-nutrition prevalence was 21.5% (wasting), 43.3% (stunting), and 52.0% (underweight).
- CIAF revealed a higher prevalence of 63.6%.
- Socio-economic and demographic variables significantly correlated with double and multiple anthropometric failures.
Conclusions:
- CIAF offers superior precision in identifying nutritionally vulnerable populations.
- Disaggregating CIAF data can enhance nutritional intervention efficacy by pinpointing children with multiple failures.
Background:
The present cross-sectional study evaluates the utility of the Composite Index of Anthropometric Failure (CIAF) over conventional nutritional indices for nutritional assessment. It also assesses the impact of various socio-economic and demographic factors on the CIAF.
Subjects And Methods:
Height, weight, age, socio-economic and demographic data were recorded from 3444 children (1682 boys; 1762 girls) aged 1-12 years and residing in Darjeeling district, West Bengal, India. The conventional anthropometric indices and CIAF were compared with the NCHS reference data to assess prevalence of under-nutrition. A multinomial logistic regression was used to assess the impact of different socio-economic and demographic variables on the CIAF.
Results:
Prevalence of under-nutrition was observed to be 21.5% (wasting), 43.3% (stunting) and 52.0% (underweight). This increased to 63.6% using the CIAF. The multinomial logistic regression odds showed that children suffering from double and multiple failures were significantly associated with the socio-economic and demographic variables.
Conclusion:
The CIAF provides more precision in identifying the nutritionally vulnerable segment of the population. The disaggregation of CIAF has an adequate potential to enhance the efficacy of a nutritional intervention programme by identifying double or multiple failures.
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