Using 3D Imaging Technology to Accurately Collect Postmortem Anthropometric Measurements in Children Under 5 Years of Age. (29th May 2020) - Gupta, Priya; Akelo, Victor; Addo, O Yaw; Sivalogan, Kasthuri; Oliech, Richard; Gethi, Dickson; Barr, Beth Tippett; Blau, Dianna; Suchdev, Parminder
Abstract: Objectives: The Child Health and Mortality Prevention Surveillance Network (CHAMPS) aims to identify causes of under-5 mortality in sub-Saharan African and South Asian surveillance sites. To address challenges in postmortem nutritional assessment, we evaluated anthropometry training and 3D imaging in the CHAMPS Kenya site. Methods: Staff were trained using World Health Organization (WHO) recommended standard anthropometry equipment as well as 3D imaging to collect postmortem measurements. Following the training, 76 cases were measured in duplicate using standard anthropometry and 3D imaging and were compared to 75 pre-intervention cases. Outcomes included data quality metrics [standard deviations (SD), digit preference, % biologically implausible values (BIV, Length-for-age z-score (LAZ) BIV = ± 6 SD), measurement reliability (technical errors of measurement, TEM), and accuracy (correlation coefficients and Bland Altman plots of standard vs. 3D scan measurements). We used both WHO growth standard and internal standardization to produce sex and age-specific LAZ. Results: Standard anthropometry data quality improved as indicated by digit preference (all measures rounded to 0.0 or 0.5 pre-intervention vs. no preference post-intervention). When using the WHO growth standards, we observed increases between pre- and post-training LAZ SD (2.55 vs. 2.92) and % BIV (5.33 vs. 15.13). Internal standardization eliminated the % BIV, with pre-intervention LAZ ranging from-1.78 to 2.27, and post intervention LAZ: −2.27 to 2.04, falling within the WHO ranges for biologically plausible values (−6 SD < LAZ < 6 SD). Reliability of length measurements post-intervention was high as indicated by low relative TEM of 0.53%. Accuracy of 3D imaging was high (R = 0.99) comparing post-training vs. 3D imaging for length; however, examination of Bland Altman plots revealed that on average 3D scans overestimated length by 3.87 centimeters. Conclusions: Training on standard anthropometry improved data quality. 3D imaging may be an accurate alternative to standard anthropometry, but adjustment of the technology is needed to avoid overestimation of length. Future research on the appropriate use of reference standards to define malnutrition in this severely ill population is needed. Funding Sources: Bill & Melinda Gates Foundation.