Precision of Measurements Performed by a Cadre of Anthropometrists Trained for a Large Household Nutrition Survey in Ethiopia

Abstract

Background Well-trained anthropometrists are essential for the delivery of high-quality anthropometric data used to evaluate public health nutrition interventions. Scant data are currently available on the precision of data collected by large teams of anthropometrists employed for nutrition surveys in low-income country settings. Objective The purpose of this study was to assess the precision of child mid-upper arm circumference (MUAC) and length/height measurements taken by fieldworkers training for nutrition survey deployment. Methods Following three days of training, an anthropometry standardization exercise was conducted in small teams of trainees at seven sites in Amhara region, Ethiopia. In groups of two to four, trainee anthropometrists (n = 79) each measured sixteen children aged 6–47 months (n = 336) twice for MUAC and length/height. Intra-observer and inter-observer precision were analyzed using technical error of measurement (TEM), relative TEM, coefficient of reliability (R), and repeatability metrics. Bland-Altman limits of agreement were calculated for intra-observer measurements. Results Intra-observer technical error of measurement (TEM) was between 0.00 and 0.57 cm for MUAC (Bland-Altman 95% limits of agreement: −0.50 to 0.54 cm) and between 0.04 and 2.58 cm for length/height measurements (Bland-Altman 95% limits of agreement: -1.43 to 1.41 cm). Inter-observer TEM was between 0.09 and 0.43 cm for MUAC and between 0.06 and 2.98 cm for length/height measurements. A high proportion of trainees achieved intra-observer R > 0.95 (MUAC 95%; length/height 97%). Most teams also achieved inter-observer R > 0.95 (MUAC 90%; length/height 95%). Conclusions Large numbers of anthropometrists (over 75) in low-income settings can attain satisfactory precision in anthropometry following training and standardization. These protocols permit researchers to assess trainees, identify individuals who have not achieved the desired level of precision, and retrain or adjust roles prior to survey deployment.

Training and Assessing Model for the Ability of Community Health Volunteers in Anthropometric Measurement Using the Rasch Stacking and Racking Analyses

“…The findings that CHVs could perform appropriate measurements after being trained, although the training was short, are in line with those of the studies conducted by Mwangome et al [ 20 ] and Moss et al [ 31 ]. Nevertheless, there were differences between this study and that of Mwangome et al, Moss et al, and Ayele et al, [ 20 , 31 , 32 ]. Mwangome et al only observed MUAC measurement with Bland–Altman and Pitman's analysis [ 20 ].…”

“…Mwangome et al only observed MUAC measurement with Bland–Altman and Pitman's analysis [ 20 ]. Moss et al observed MUAC and length/height measurements using technical error of measurements (TEMs) with Bland–Altman analysis [ 31 ]. The good thing about racking and stacking analysis compared to the abovementioned methods is that the raw data transforms into equal-interval scale (logit) providing precise and accurate measurement regarding CHVs' skills (as shown in Tables 2 and 3 ).…”

The Sanitation Hygiene Infant Nutrition Efficacy (SHINE) Trial: Protocol for school-age follow-up

“…Additional training was provided for any DCs below a set threshold in anthropometry or cognitive measurement, derived from the intra- and inter-observer technical error of measurement for continuous measurements ( e.g. , anthropometry) 14 and intraclass correlation coefficient (ICC) for discrete measurements ( e.g. , cognitive test scores).…”

The influence of fasting on energy and nutrient intake and their corresponding food sources among 6-23 months old children in rural communities with high burden of stunting from Northern Ethiopia

“…Data were collected by health professionals who were well trained and skilled in child anthropometric measurements. Duplicate measurements (length and weight) were taken following standard procedures [ 23 ]. Height-for-age, weight-for-age, and weight-for-height were calculated according to the WHO Standard Reference [ 24 ] using the software ENA 2015.…”