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Anthropometry and moderate malnutrition in preschool children
Mary E Lloyd1, Sally A Lederman
1Istituto Maestre Pie Filippini, Rome, Italy. mel@linet.it
Insights
Identifying moderate malnutrition (MM) in children is crucial. This study statistically determined optimal anthropometric measures and cut-off points, like mid-upper arm circumference (MUAC), for diagnosing MM in preschool children globally.
Area of Science:
- Pediatric Nutrition
- Public Health
- Anthropometry
Background:
- Moderate malnutrition (MM) causes more child deaths than severe malnutrition.
- Identifying children with MM remains a challenge.
- Few studies focus on specific diagnostic indicators for MM.
Purpose of the Study:
- To statistically determine appropriate anthropometric measures for diagnosing moderate malnutrition in preschool children.
- To identify optimal cut-off points for these measures.
- To provide evidence-based tools for early MM detection.
Main Methods:
- Collected anthropometric data from 609 preschool children in Ethiopia, India, and Brazil.
- Calculated sensitivity, specificity, PPV, and LR for various anthropometric indices.
- Used the McNemar Test and Kappa coefficient to determine statistically significant cut-off points.
Main Results:
- Weight-for-height (WFH) showed high PPV and LR but lacked statistical significance.
- Mid-upper arm circumference (MUAC) demonstrated significant results across all sites.
- Optimal MUAC cut-off points varied by location: <15.5 cm in India/Brazil, <15 cm in Ethiopia.
Conclusions:
- WFH and MUAC, alongside WFA, can effectively identify children with moderate malnutrition.
- Location-specific cut-off points for MUAC are necessary.
- Statistically validated indicators, particularly MUAC, can significantly improve child survival rates through early MM detection.
Objective:
For years it has been shown that more children die from moderate malnutrition (MM) than severe. Till yet few studies deal specifically with identifying these children. This study attempts to statistically determine the appropriate anthropometric measures and cut-off points for diagnosing moderate malnutrition in preschool children.
Methods:
Anthropometric measurements were obtained from 609 preschool children from the cities of Adigrat, Ethiopia; Janampet, India; San Paulo, Brazil. The values were used to determine the sensitivity, specificity, positive predictive value (PPV) and likelihood ratio (LR) of each index studied. The optimum cutoff point for each index was considered to be the cutoff point with the maximum Kappa coefficient for efficiency. The McNemar Test for the significance of changes was used to determine if these findings were in agreement when applied to this data.
Results:
Weight for height (WFH) at each site had the highest PPV and LR of 4 but was not signficant by the McNemar Test. Mid-upper arm circumference (MUAC) in India had the same PPV (77%) as WFH but a LR of 2. MUAC in India, Brazil and Ethiopia tested significantly for the McNemar Test. The cut-off point for MUAC in India and Brazil was determined to be <15.5 cm in India and Brazil but was <15 cm in Ethiopia. Waist circumference in India tested a significantly PPV of 64%, and a LR of 2.
Conclusion:
These results show that WFH and MUAC could be used with WFA to identify the MM child. The cut-off points for MUAC may vary per location. WC positive data suggests further study is warranted. The McNemar findings yielded significant evidence that statistically determined indicators can be established to identify MM. With further study these methods may prove to be an important component in the efforts to improve child survival.