Timely treatment of acute malnutrition in children 500,000 deaths annually. Screening at community level is essential to identify children with malnutrition. Current WHO guidelines for community screening for malnutrition recommend a Mid Upper Arm Circumference (MUAC) of 11,000 Cambodian children, obtained by different surveys between 2010 and 2012, was used to calculate sensitivity and ROC curves for MUAC and WHZ. The secondary analysis showed that using the current WHO cut-off of 115 mm for screening for severe acute malnutrition over 90% of children with a weight-for-height z-score (WHZ) <−3 would have been missed. Reversely, WHZ<−3 missed 80% of the children with a MUAC65% of children with a WHZ<−3. Importantly, MUAC and WHZ identified different sub-groups of children with acute malnutrition, therefore these 2 indicators should be regarded as independent from each other. We suggest a 2-step model with MUAC used a screening at community level, followed by MUAC and WHZ measured at a primary health care unit, with both indicators used independently to diagnose severe acute malnutrition. Current guidelines should be changed to reflect this, with treatment initiated when either MUAC <115 mm or WHZ<−3.

We assessed prevalence of concurrently wasted and stunted (WaSt) and explored the overlaps between wasted, stunted, underweight and low mid‐upper arm circumference (MUAC) among children aged 6–59 months in Karamoja, Uganda. We also determined optimal weight‐for‐age (WAZ) and MUAC thresholds for detecting WaSt. We conducted secondary data analysis with 2015–2018 Food Security and Nutrition Assessment (FSNA) cross‐sectional survey datasets from Karamoja. Wasting, stunting and underweight were defined as <−2.0 z‐scores using WHO growth standards. Low MUAC was defined as <12.5 cm. We defined WaSt as concurrent wasting and stunting. Prevalence of WaSt was 4.96% (95% CI [4.64, 5.29]). WaSt was more prevalent in lean than harvest season (5.21% vs. 4.53%; p = .018). About half (53.92%) of WaSt children had low MUAC, and all were underweight. Younger children aged <36 months had more WaSt, particularly males. Males with WaSt had higher median MUAC than females (12.50 vs. 12.10 cm; p < .001). A WAZ <−2.60 threshold detected WaSt with excellent sensitivity (99.02%) and high specificity (90.71%). MUAC threshold <13.20 cm had good sensitivity (81.58%) and moderate specificity (76.15%) to detect WaSt. WaSt prevalence of 5% is a public health concern, given its high mortality risk. All children with WaSt were underweight and half had low MUAC. WAZ and MUAC could be useful tools for detecting WaSt. Prevalence monitoring and prospective studies on WAZ and MUAC cut‐offs for WaSt detection are recommended. Future consideration to integrate WAZ into therapeutic feeding programmes is recommended to detect and treat WaSt children.

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.

A cross-sectional analysis of the Cambodia Demographic Health Surveys from 2000, 2005 and 2010 was conducted to observe the national trends in infant and young child feeding practices. The results showed that rates of exclusive breastfeeding among infants aged 0–5.9 months have increased substantially since 2000, concurrent with an increase in the rates of early initiation of breastfeeding and a reduction in the giving of pre-lacteal feeds. However, the proportion of infants being fed with breast-milk substitutes (BMS) during 0–5.9 months doubled in 5 years (3.4% to 7.0%) from 2000 to 2005, but then did not increase from 2005, likely due to extensive public health campaigns on exclusive breastfeeding. BMS use increased among children aged 6–23.9 months from 2000 to 2010 (4.8% to 9.3%). 26.1% of women delivering in a private clinic provided their child with breast-milk substitute at 0–5.9 months, which is five times more than women delivering in the public sector (5.1%), and the greatest increase in bottle use happened among the urban poor (5.8% to 21.7%). These findings are discussed with reference to the increased supply and marketing of BMS that is occurring in Cambodia.

Anthropometric data collected in clinics and surveys are often inaccurate and unreliable due to measurement error. The Body Imaging for Nutritional Assessment Study (BINA) evaluated the ability of 3D imaging to correctly measure stature, head circumference (HC) and arm circumference (MUAC) for children under five years of age. This paper describes the protocol for and the quality of manual anthropometric measurements in BINA, a study conducted in 2016–17 in Atlanta, USA. Quality was evaluated by examining digit preference, biological plausibility of z-scores, z-score standard deviations, and reliability. We calculated z-scores and analyzed plausibility based on the 2006 WHO Child Growth Standards (CGS). For reliability, we calculated intra- and inter-observer Technical Error of Measurement (TEM) and Intraclass Correlation Coefficient (ICC). We found low digit preference; 99.6% of z-scores were biologically plausible, with z-score standard deviations ranging from 0.92 to 1.07. Total TEM was 0.40 for stature, 0.28 for HC, and 0.25 for MUAC in centimeters. ICC ranged from 0.99 to 1.00. The quality of manual measurements in BINA was high and similar to that of the anthropometric data used to develop the WHO CGS. We attributed high quality to vigorous training, motivated and competent field staff, reduction of non-measurement error through the use of technology, and reduction of measurement error through adequate monitoring and supervision. Our anthropometry measurement protocol, which builds on and improves upon the protocol used for the WHO CGS, can be used to improve anthropometric data quality. The discussion illustrates the need to standardize anthropometric data quality assessment, and we conclude that BINA can provide a valuable evaluation of 3D imaging for child anthropometry because there is comparison to gold-standard, manual measurements.

3D imaging for body measurements is regularly used for design of garments and ergonomic products. The development of low‐cost 3D scanners provided an opportunity to extend the use of 3D imaging to the health sector. We developed and tested the AutoAnthro System, the first mobile, low‐cost, full‐body, 3D imaging system designed specifically for child anthropometry. This study evaluated the efficiency, invasiveness, and user experience of the AutoAnthro System. We used a mixed‐methods, collaborative approach that included a quantitative time‐motion study and qualitative interviews of anthropometrists. For cooperative children, anthropometrists considered the use of 3D imaging an easy, “streamlined experience,” but with uncooperative children, anthropometrists reported that capturing a good quality scan was out of their control. The mean time to complete a full set of scans was 68 s (standard deviation [SD] 29), compared with 135 s (SD 22) for a set of manual measurements (stature, head circumference, and arm circumference). We observed that crying was more common during manual measurement, and anthropometrist interviews confirmed that 3D imaging was less stressful for children than manual measurement. In a previous publication, we showed the potential of 3D imaging to produce reliable and accurate measurements. In this study, we found that anthropometrists were not ready to abandon manual equipment for 3D scanners because of difficulty in measuring uncooperative children. Revising the AutoAnthro System to address anthropometrists' concerns on capturing good quality scans of uncooperative children should help to facilitate widespread use of 3D imaging for child anthropometry.