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      Weight Estimation Tool for Children Aged 6 to 59 Months in Limited-Resource Settings

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      1 , * , 2
      PLoS ONE
      Public Library of Science

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          Abstract

          Importance

          A simple, reliable anthropometric tool for rapid estimation of weight in children would be useful in limited-resource settings where current weight estimation tools are not uniformly reliable, nearly all global under-five mortality occurs, severe acute malnutrition is a significant contributor in approximately one-third of under-five mortality, and a weight scale may not be immediately available in emergencies to first-response providers.

          Objective

          To determine the accuracy and precision of mid-upper arm circumference (MUAC) and height as weight estimation tools in children under five years of age in low-to-middle income countries.

          Design

          This was a retrospective observational study. Data were collected in 560 nutritional surveys during 1992–2006 using a modified Expanded Program of Immunization two-stage cluster sample design.

          Setting

          Locations with high prevalence of acute and chronic malnutrition.

          Participants

          A total of 453,990 children met inclusion criteria (age 6–59 months; weight ≤ 25 kg; MUAC 80–200 mm) and exclusion criteria (bilateral pitting edema; biologically implausible weight-for-height z-score (WHZ), weight-for-age z-score (WAZ), and height-for-age z-score (HAZ) values).

          Exposures

          Weight was estimated using Broselow Tape, Hong Kong formula, and database MUAC alone, height alone, and height and MUAC combined.

          Main Outcomes and Measures

          Mean percentage difference between true and estimated weight, proportion of estimates accurate to within ± 25% and ± 10% of true weight, weighted Kappa statistic, and Bland-Altman bias were reported as measures of tool accuracy. Standard deviation of mean percentage difference and Bland-Altman 95% limits of agreement were reported as measures of tool precision.

          Results

          Database height was a more accurate and precise predictor of weight compared to Broselow Tape 2007 [B], Broselow Tape 2011 [A], and MUAC. Mean percentage difference between true and estimated weight was +0.49% (SD = 10.33%); proportion of estimates accurate to within ± 25% of true weight was 97.36% (95% CI 97.40%, 97.46%); and Bland-Altman bias and 95% limits of agreement were 0.05 kg and (-2.15 kg; 2.24 kg). The height model fitted for MUAC classes was accurate and precise. For MUAC < 115 mm, the proportion of estimates accurate to within ± 25% of true weight was 97.15% (95% CI 96.90%, 97.42%) and the Bland-Altman bias and 95% limits of agreement were 0.08 kg and (-1.21 kg; 1.37 kg). For MUAC between 115 and 125 mm, the proportion of estimates accurate to within ± 25% of true weight was 98.93% (95% CI 98.82%, 99.03%) and Bland-Altman bias and 95% limits of agreement were 0.05 kg and (-1.15 kg; 1.24 kg). For MUAC > 125 mm, the proportion of estimates accurate to within ± 25% of true weight was 98.33% (95% CI 98.29%, 98.37%) and Bland-Altman bias and 95% limits of agreement were 0.05 kg and (-2.08 kg; 2.19 kg).

          Conclusions and Relevance

          Models estimating weight from height alone and height with MUAC class in children aged 6–59 months in a database from low-to-middle income countries were more accurate and precise than previous weight estimation tools. A height-based weight estimation tape stratified according to MUAC classes is proposed for children aged 6–59 months in limited-resource settings.

          Related collections

          Most cited references34

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          • Abstract: found
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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            [Standardization of quantitative epidemiological methods in the field].

            J Habicht (1974)
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              • Abstract: found
              • Article: not found

              A rapid method for estimating weight and resuscitation drug dosages from length in the pediatric age group.

              Drug dosages used during pediatric emergencies and resuscitation are often based on estimated body weight. The Broselow Tape, a tape measure that estimates weight and drug dosages for pediatric patients from their length, has been developed to facilitate proper dosing during emergencies. In our study, 937 children of known weight were measured with this tape. Weight estimates generated by the tape were found to be within 15% error for 79% of the children. The tape was found to be extremely accurate for children from 3.5 to 10 kg, and from 10 to 25 kg. Regression lines of estimated compared with actual weight for these children have slopes of 0.98 and 0.96, respectively, not significantly different from the ideal slope of 1.00 (P = 28 and .13). Accuracy was significantly decreased for measured children who weighed more than 25 kg. In a separate group of children (n = 53), the tape was shown to be more accurate than weight estimates made by residents and pediatric nurses (P less than .0001). Use of the Broselow Tape is a simple, accurate method of estimating pediatric weights and drug doses and eliminates the need for memorization and calculation.

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 August 2016
                2016
                : 11
                : 8
                : e0159260
                Affiliations
                [1 ]Department of Pediatrics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America
                [2 ]Brixton Health, Llawryglyn, Powys, Wales, United Kingdom
                TNO, NETHERLANDS
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceived and designed the experiments: MER MAM.

                • Performed the experiments: MAM.

                • Analyzed the data: MAM MER.

                • Contributed reagents/materials/analysis tools: MAM.

                • Wrote the paper: MER MAM.

                Article
                PONE-D-16-01075
                10.1371/journal.pone.0159260
                4987045
                27529816
                b6c7998e-2553-421c-9ee2-1062d9e51db0

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 9 January 2016
                : 23 May 2016
                Page count
                Figures: 4, Tables: 5, Pages: 18
                Funding
                The authors have no support or funding to report.
                Categories
                Research Article
                People and Places
                Population Groupings
                Age Groups
                Children
                People and Places
                Population Groupings
                Families
                Children
                Biology and Life Sciences
                Nutrition
                Malnutrition
                Medicine and Health Sciences
                Nutrition
                Malnutrition
                Social Sciences
                Anthropology
                Physical Anthropology
                Anthropometry
                Biology and Life Sciences
                Physical Anthropology
                Anthropometry
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Edema
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Edema
                Computer and Information Sciences
                Data Management
                Medicine and Health Sciences
                Critical Care and Emergency Medicine
                Resuscitation
                Medicine and Health Sciences
                Pediatrics
                People and places
                Geographical locations
                North America
                United States
                Custom metadata
                The data are available via Figshare at: https://dx.doi.org/10.6084/m9.figshare.3503021.

                Uncategorized
                Uncategorized

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