A new way to measure mid-upper-arm circumference in African villages - Gregor Pollach; Eleanore Bradley; Abigail Cole; Kai Jung (MDPI AG, 2014)
In 2011 we published a study on how to detect the threshold for malnutrition in children, simply using their own hands and without any technical tool. The fight against malnutrition can only be reached when its measurements involve every single child, almost continuously, in the affected villages. In this paper we try to show that, thanks to our method, it is possible to use mid-upper-arm-circumference as a measurement for malnutrition in children, discriminating between severe and moderate malnutrition and providing the basis for the decision on whether to admit a child to a nutritional rehabilitation unit or not. We trained 63 participants in four groups (Group 1: doctors and clinical officers; Group 2: nurses and students; as Group 3 we defined the 20 best participants and Group 4 consisted of 10 more intensely trained participants) to measure the circumference of 9 different artificial arms (between 9 and 13 cm) using their own fingers and hands. The training was short and consisted of an introduction of 5 min, a first training phase of 10-15 min, a test, the critical discussion of the results, a second training phase of 5 min and a final test. We found that 95.3% of participants in the general group and 97.9% in the intensely trained group have identified the severely malnourished child; 87.3% in the general group and 91.9% in the intensely trained group have additionally identified the moderately malnourished child. Both groups haven't admitted the well nourished child to a therapeutic feeding program retaining their resources. The third group reached without any additional training the results in the above categories. A subsequent discussion with the participants on the influence of procurement, maintenance and pricing of our tool, found our method much less vulnerable than others. We conclude that this method should be considered as a future training in the villages to detect the trend towards malnutrition early enough.