Senior Research Fellow, Centre for Social Science Research, Kumasi Technical University, Kumasi 854, Ghana.
Biomedical Scientist, Department of Laboratory Technology, Kumasi Technical University, Kumasi 854, Ghana.
Int J Environ Res Public Health. 2021 Apr 5;18(7):3792. doi: 10.3390/ijerph18073792.
The issue of malnutrition is perhaps the most important public health determinant of global wellbeing. It is one of the main causes of improper mental and physical development as well as death of many children. The Mid Upper Arm Circumference (MUAC) rapid text setup is able to diagnose malnutrition due to the fact that the human arm contains subcutaneous fat and muscle mass. When proportional food intake increases or reduces, the corresponding increase or reduction in the subcutaneous fat and muscle mass leads to an increase or decrease in the MUAC. In this study, the researchers attempt to develop a model for determining the performance of MUAC in predicting Child malnutrition in Ghana. It focuses on the Joint Generalized Linear Model (Joint-GLM) instead of the traditional Generalized Linear Model (GLM). The analysis is based on primary data measured on children under six years, who were undergoing nutritional treatment at the Princess Marie Louise (PML) Children's Hospital in the Ashiedu Keteke sub-metro area of Accra Metropolis. The study found that a precisely measured weight of a child, height, and albumen levels were positive determinants of the predicted MUAC value. The study also reveals that, of all the variables used in determining the MUAC outcome, the hemoglobin and total protein levels of a child would be the main causes of any variation between the exact nutritional status of a child and that suggested by the MUAC value. The final Joint-GLM suggests that, if there are occasions where the MUAC gave false results, it could be a result of an imbalance in the child's hemoglobin and protein levels. If these two are within acceptable levels in a child, the MUAC is most likely to be consistent in predicting the child's nutritional status accurately. This study therefore recommends the continued use of MUAC in diagnosis of child malnutrition but urges Ghana and countries in Sub-Saharan Africa to roll out an effective nutrition intervention plan targeting the poor and vulnerable suburbs so that the nutritional status of children under five years of age, who were the focus of the current study, may be improved.
营养不良问题或许是全球福祉最重要的公共卫生决定因素。它是造成许多儿童发育不良、身体和精神受损乃至死亡的主要原因之一。中臂围（MUAC）快速检测法能够诊断营养不良，因为人类手臂含有皮下脂肪和肌肉。当食物摄入相应增加或减少时，皮下脂肪和肌肉量的增减会导致 MUAC 的增减。在这项研究中，研究人员试图建立一个模型，用于确定 MUAC 在预测加纳儿童营养不良方面的表现。它侧重于联合广义线性模型（Joint-GLM）而不是传统的广义线性模型（GLM）。该分析基于在阿希耶杜·凯泰克（Ashiedu Keteke）阿克拉都会区的玛丽·路易丝公主（Princess Marie Louise）儿童医院接受营养治疗的 6 岁以下儿童的原始数据进行。研究发现，儿童的精确体重、身高和白蛋白水平是预测 MUAC 值的正决定因素。该研究还表明，在用于确定 MUAC 结果的所有变量中，儿童的血红蛋白和总蛋白水平将是儿童实际营养状况与 MUAC 值建议之间差异的主要原因。最终的联合广义线性模型表明，如果 MUAC 出现错误结果，可能是由于儿童的血红蛋白和蛋白水平失衡所致。如果这两个水平在儿童体内处于可接受的范围内，那么 MUAC 就很可能在准确预测儿童营养状况方面保持一致。因此，该研究建议继续使用 MUAC 诊断儿童营养不良，但敦促加纳和撒哈拉以南非洲国家推出一项针对贫困和弱势郊区的有效营养干预计划，以便改善当前研究重点关注的 5 岁以下儿童的营养状况。
