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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Comparison of anthropometric indicators to predict mortality in a population-based prospective study of children
Kieran S O'Brien1,2, Abdou Amza3, Boubacar Kadri3
1Francis I. Proctor Foundation, University of California San Francisco, 513 Parnassus Avenue, S334, San Francisco, CA 94143, USA.
Insights
Mid-upper arm circumference (MUAC) is a better predictor of child mortality than other anthropometric measures in Niger. This finding is crucial for identifying at-risk children in high-malnutrition settings.
Area of Science:
- Pediatrics
- Public Health
- Nutrition Science
Background:
- Child malnutrition is a significant global health issue, particularly in low-resource settings.
- Accurate anthropometric indicators are vital for assessing malnutrition and predicting mortality risk.
- Existing indicators may have varying effectiveness in different epidemiological contexts.
Purpose of the Study:
- To compare the efficacy of various anthropometric indicators in predicting child mortality.
- To identify the most effective anthropometric measure for risk stratification in a high-malnutrition community.
- To inform public health interventions for child survival in Niger.
Main Methods:
- A longitudinal, population-based study nested within a cluster-randomized trial was conducted in Niger.
- Weight, height, and mid-upper arm circumference (MUAC) were measured in children aged 6-60 months.
- Mortality was assessed over a 2-year period using census and monitoring data.
Main Results:
- Malnutrition was prevalent, with 76.0% of children exhibiting moderate to severe stunting.
- Over 2 years, 5.7% of the children studied died.
- Mid-upper arm circumference (MUAC) demonstrated the highest predictive accuracy (AUC=0.68) and strongest association with mortality (HR=2.21).
Conclusions:
- Mid-upper arm circumference (MUAC) is a superior predictor of mortality compared to height-for-age, weight-for-age, and weight-for-height Z-scores in this setting.
- MUAC's effectiveness highlights its utility in resource-limited areas with high malnutrition rates.
- The findings support the use of MUAC for early identification and intervention to reduce child mortality in Niger.
Objective:
In the present study, we aimed to compare anthropometric indicators as predictors of mortality in a community-based setting.
Design:
We conducted a population-based longitudinal study nested in a cluster-randomized trial. We assessed weight, height and mid-upper arm circumference (MUAC) on children 12 months after the trial began and used the trial's annual census and monitoring visits to assess mortality over 2 years.
Setting:
Niger.
Participants:
Children aged 6-60 months during the study.
Results:
Of 1023 children included in the study at baseline, height-for-age Z-score, weight-for-age Z-score, weight-for-height Z-score and MUAC classified 777 (76·0 %), 630 (61·6 %), 131 (12·9 %) and eighty (7·8 %) children as moderately to severely malnourished, respectively. Over the 2-year study period, fifty-eight children (5·7 %) died. MUAC had the greatest AUC (0·68, 95 % CI 0·61, 0·75) and had the strongest association with mortality in this sample (hazard ratio = 2·21, 95 % CI 1·26, 3·89, P = 0·006).
Conclusions:
MUAC appears to be a better predictor of mortality than other anthropometric indicators in this community-based, high-malnutrition setting in Niger.
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