Dataset Information

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. Objectives:The purpose of this study was to assess the precision of child midupper arm circumference (MUAC) and length/height measurements taken by fieldworkers training for nutrition survey deployment. Methods:Following 3 d of training, an anthropometry standardization exercise was conducted in small teams of trainees at 7 sites in the Amhara region of Ethiopia. In groups of 2-4, trainee anthropometrists (n = 79) each measured 16 children aged 6-47 mo (n = 336) twice for MUAC and length/height. Both intraobserver and interobserver 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 intraobserver measurements. Results:Intraobserver 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). Interobserver 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 intraobserver R >0.95 (MUAC: 95%; length/height: 97%). Most teams also achieved interobserver R >0.95 (MUAC: 90%; length/height: 95%). Conclusions:Large numbers of anthropometrists (>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.

SUBMITTER: Moss C

PROVIDER: S-EPMC7475006 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Moss Cami C Kuche Desalegn D Bekele Tesfaye Hailu TH Salasibew Mihretab M Ayana Girmay G Abera Andinet A Eshetu Solomon S Dangour Alan D AD Allen Elizabeth E

Current developments in nutrition 20200821 9

<h4>Background</h4>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.<h4>Objectives</h4>The purpose of this study was to assess the precision of child midupper arm circumference (MUAC) and length/height measurements taken by field ...[more]

PMID: 32923923

Similar Datasets

Project description:BACKGROUND:Undernutrition is an important risk factor for childhood mortality, and remains a major problem facing many developing countries. Millennium Development Goal 1 calls for a reduction in underweight children, implemented through a variety of interventions. To adequately judge the impact of these interventions, it is important to know the reproducibility of the main indicators for undernutrition. In this study, we trained individuals from rural communities in Ethiopia in anthropometry techniques and measured intra- and inter-observer reliability. METHODS AND FINDINGS:We trained 6 individuals without prior anthropometry experience to perform weight, height, and middle upper arm circumference (MUAC) measurements. Two anthropometry teams were dispatched to 18 communities in rural Ethiopia and measurements performed on all consenting pre-school children. Anthropometry teams performed a second independent measurement on a convenience sample of children in order to assess intra-anthropometrist reliability. Both teams measured the same children in 2 villages to assess inter-anthropometrist reliability. We calculated several metrics of measurement reproducibility, including the technical error of measurement (TEM) and relative TEM. In total, anthropometry teams performed measurements on 606 pre-school children, 84 of which had repeat measurements performed by the same team, and 89 of which had measurements performed by both teams. Intra-anthropometrist TEM (and relative TEM) were 0.35 cm (0.35%) for height, 0.05 kg (0.39%) for weight, and 0.18 cm (1.27%) for MUAC. Corresponding values for inter-anthropometrist reliability were 0.67 cm (0.75%) for height, 0.09 kg (0.79%) for weight, and 0.22 kg (1.53%) for MUAC. Inter-anthropometrist measurement error was greater for smaller children than for larger children. CONCLUSION:Measurements of height and weight were more reproducible than measurements of MUAC and measurements of larger children were more reliable than those for smaller children. Community-drawn anthropometrists can provide reliable measurements that could be used to assess the impact of interventions for childhood undernutrition.

Project description:BackgroundHousehold food and nutrition insecurity continued to be a development and policy agenda in Ethiopia. Assessing the patterns and determinants of household dietary diversity is an important area of research given its importance for policy uptake in the country. This study is, therefore, initiated to identify the dominant food groups consumed by households and to investigate the determinants of household dietary diversity in the country.MethodWe used data from the 4th wave of the Ethiopian socioeconomic survey. The survey data for this study included 3,115 households living in rural areas (hereafter called 'rural households'). Household Dietary Diversity Score (HDDS) was calculated and categorized as per the FAO's recommendation: low HDDS category for those who consume three or less food groups, medium HDDS for those who consume four to six, and high HDDS for those who consume seven and more food groups during the past seven days. Ordinal logistic regression model was employed to estimate the determinants of rural household's dietary diversity.ResultsCereals were the most dominant food group consumed by 96.4% of the households followed by pulses, which was consumed by 82% of the households Nutrition-dense food commodities such as lean meat, vegetables and fruits were the least consumed food groups by households in Ethiopia. In terms of determinants of dietary diversity, female headed households have 38% more chance of consuming diverse foods compared to their male-headed counterparts (AOR = 1.38, 95% CI: 1.10, 1.73). Household heads who completed secondary education and above have 62% more chance of consuming diverse foods compared to uneducated household heads (AOR = 1.62, 95% CI: 1.2, 2.30). Household heads who are single have 37% less chance of consuming diverse foods compared to those household heads who are married (AOR = 0.63, 95% CI: 0.50, 0.80). Those households located in Harari regional state and in the rural surroundings of Diredawa town have 6.56 times more chance of consuming diverse foods compared to those households living in Tigray and Amhara regional states (AOR = 6.56, 95% CI: 4.60, 9.37). The results also highlighted that households who are in the upper wealth category have 9 times more chance of consuming diverse foods compared to those households who are the lower wealth category (AOR = 8.54, 95% CI: 6.79, 11.98).

Project description:To target food security interventions for smallholder households, decision makers need large-scale information, such as maps on poverty, food security and key livelihood activities. Such information is often based on expert knowledge or aggregated data, despite the fact that food security and poverty are driven largely by processes at the household level. At present, it is unclear if and how household level information can contribute to the spatial prediction of such welfare indicators or to what extent local variability is ignored by current mapping efforts. A combination of geo-referenced household level information with spatially continuous information is an underused approach to quantify local and large-scale variation, while it can provide a direct estimate of the variability of welfare indicators at the most relevant scale. We applied a stepwise regression kriging procedure to translate point information to spatially explicit patterns and create country-wide predictions with associated uncertainty estimates for indicators on food availability and related livelihood activities using household survey data from Uganda. With few exceptions, predictions of the indicators were weak, highlighting the difficulty in capturing variability at larger scale. Household explanatory variables identified little additional variation compared to environmental explanatory variables alone. Spatial predictability was strongest for indicators whose distribution was determined by environmental gradients. In contrast, indicators of crops that were more ubiquitously present across agroecological zones showed large local variation, which often overruled large-scale patterns. Our procedure adds to existing approaches that often only show large-scale patterns by revealing that local variation in welfare is large. Interventions that aim to target the poor must recognise that diversity in livelihood activities for income generation within any given area often overrides the variability of livelihood activities between distant regions in the country.

Project description:BackgroundAnaemia continues to be a major public health challenge globally, including in Ethiopia. Previous studies have suggested that improved household environmental conditions may reduce anaemia prevalence; however, population-level evidence of this link is lacking in low-income countries. Therefore, this study aimed to examine the association between environmental factors and childhood anaemia in Ethiopia.MethodsIn this study, we conducted an analysis of the data from the Ethiopian Demographic and Health Survey (EDHS), a nationally representative population-based survey conducted in Ethiopia between 2005 and 2016. The study included a total of 21,918 children aged 6-59 months. Children were considered anemic if their hemoglobin (Hb) concentration was less than 11.0 g/dl. To examine the association between environmental factors and anemia, we used multilevel mixed-effect models. These models allowed us to control for various confounding factors including: child, maternal, household and community-level variables. The study findings have been reported as adjusted odds ratios (AORs) along with 95% confidence intervals (CIs) at a significance level of p < 0.05.ResultsThe study found the overall prevalence of childhood anaemia to be 49.3% (95%CI: 48.7-49.9) between 2005 and 2016 in Ethiopia. The prevalence was 47.6% (95%CI: 46.1-49.1) in 2005, 42.8% (95%CI: 41.8-43.8) in 2011, and increased to 57.4% (95%CI: 56.3-58.4) in 2016. The pooled data showed that children from households practising open defecation were more likely to be anaemic (AOR: 1.19, 95% CI: 1.05-1.36). In our survey specify analysis, the odds of anaemia were higher among children from households practising open defecation (AOR: 1.33, 95% CI: 1.12-1.58) in the EDHS-2011 and EDHS-2016 (AOR: 1.49, 95% CI: 1.13-1.90). In contrast, neither household water sources nor the time to obtain water was associated with anaemia after controlling for potential confounders. The other variables significantly associated with childhood anaemia include: the child's age (6-35 months), not fully vaccinated (AOR: 1.14, 95%CI: 1.05-1.24), children not dewormed in the last 6 months (AOR: 1.11, 95%CI: 1.01-1.24), children born to mothers not working (AOR: 1.10, 95%CI: 1.02-1.19), children from poor households (AOR: 1.18: 95%CI: 1.06-1.31), and rural residence (AOR: 1.23, 95%CI: 1.06-1.42).ConclusionIn Ethiopia, about fifty percent of children suffer from childhood anemia, making it a serious public health issue. Open defecation is a major contributing factor to this scourge. To address this issue effectively, it is recommended to strengthen initiatives aimed at eliminating open defecation that involve various approaches, including sanitation infrastructure development, behavior change campaigns, and policy interventions. In addition, to reduce the burden of anemia in children, a multi-faceted approach is necessary, involving both prevention and treatment strategies.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets