Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, GA, United States of America.
Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States of America.
PLoS One. 2018 Oct 24;13(10):e0205320. doi: 10.1371/journal.pone.0205320. eCollection 2018.
The usefulness of anthropometry to define childhood malnutrition is undermined by poor measurement quality, which led to calls for new measurement approaches. We evaluated the ability of a 3D imaging system to correctly measure child stature (length or height), head circumference and arm circumference. In 2016-7 we recruited and measured children at 20 facilities in and around metro Atlanta, Georgia, USA; including at daycare, higher education, religious, and medical facilities. We selected recruitment sites to reflect a generally representative population of Atlanta and to oversample newborns and children under two years of age. Using convenience sampling, a total of 474 children 0-5 years of age who were apparently healthy and who were present at the time of data collection were included in the analysis. Two anthropometrists each took repeated manual measures and repeated 3D scans of each child. We evaluated the reliability and accuracy of 3D scan-derived measurements against manual measurements. The mean child age was 26 months, and 48% of children were female. Based on reported race and ethnicity, the sample was 42% Black, 28% White, 8% Asian, 21% multiple races, other or race not reported; and 16% Hispanic. Measurement reliability of repeated 3D scans was within 1 mm of manual measurement reliability for stature, head circumference and arm circumference. We found systematic bias when analyzing accuracy-on average 3D imaging overestimated stature and head circumference by 6 mm and 3 mm respectively, and underestimated arm circumference by 2 mm. The 3D imaging system used in this study is reliable, low-cost, portable, and can handle movement; making it ideal for use in routine nutritional assessment. However, additional research, particularly on accuracy, and further development of the scanning and processing software is needed before making policy and clinical practice recommendations on the routine use of 3D imaging for child anthropometry.
人体测量学在定义儿童营养不良方面的作用因测量质量差而受到削弱，这导致人们呼吁采用新的测量方法。我们评估了一种 3D 成像系统正确测量儿童身高（长度或高度）、头围和臂围的能力。2016-7 年，我们在美国佐治亚州亚特兰大及周边地区的 20 个设施中招募并测量了儿童；包括日托、高等教育、宗教和医疗设施。我们选择招募地点是为了反映亚特兰大的一般代表性人群，并对新生儿和两岁以下的儿童进行了抽样。使用便利抽样，共纳入了 474 名 0-5 岁的、明显健康且在数据收集时在场的儿童进行分析。两名人体测量员分别对每个儿童进行了多次手动测量和 3D 扫描。我们评估了 3D 扫描测量值与手动测量值的可靠性和准确性。儿童的平均年龄为 26 个月，48%的儿童为女性。根据报告的种族和族裔，样本中 42%为黑人，28%为白人，8%为亚洲人，21%为多种族，其他或未报告种族；16%为西班牙裔。重复 3D 扫描的测量可靠性与手动测量可靠性相差在 1 毫米以内，适用于身高、头围和臂围的测量。我们发现，在分析准确性时存在系统偏差-平均而言，3D 成像高估了身高和头围，分别高出 6 毫米和 3 毫米，而低估了臂围，低估了 2 毫米。本研究中使用的 3D 成像系统可靠、成本低、便携，且可以处理运动；非常适合用于常规营养评估。然而，在就 3D 成像在儿童人体测量中的常规使用提出政策和临床实践建议之前，还需要进行更多的研究，特别是在准确性方面，以及对扫描和处理软件的进一步开发。
