Algorithms for Converting Child Malnutrition Estimates
Author Information
Author(s): Yang Hong, de Onis Mercedes
Primary Institution: World Health Organization
Hypothesis
Can algorithms be developed to convert child malnutrition estimates from the NCHS reference to the WHO standards?
Conclusion
The algorithms provide a highly accurate tool for converting existing NCHS estimates into WHO estimates for child malnutrition.
Supporting Evidence
- The algorithms were validated using a different set of surveys.
- The average difference between predicted and observed values was less than 0.5% for most indicators.
- The correlation coefficients for the algorithms were all greater than 0.90.
Takeaway
This study created a way to change old child health data into a new format that helps us understand how many kids are healthy or not.
Methodology
The study analyzed 68 surveys using WHO standards and developed algorithms through linear regression.
Limitations
The algorithms may not be applicable to surveys with age ranges outside of 0-60 months.
Participant Demographics
Surveys included children aged 0 to 60 months.
Statistical Information
P-Value
p<0.05
Confidence Interval
95% CI
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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