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      Relationship between Mid-Upper Arm Circumference and Body Mass Index in Inpatients

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          Abstract

          Introduction

          Nutritional screening is a fundamental aspect of the initial evaluation of the hospitalised patient. Body Mass Index (BMI) in association with other parameters is a good marker of malnutrition (<18.5 kg/m 2), but it presents the handicap that the great majority of patients cannot be weighed and measured. For this reason it is necessary to find other indicators that can be measured in these patients.

          Objectives

          1) Analyse the relationship between BMI and Mid-Upper Arm Circumference (MUAC); 2) establish a cut-off point of MUAC equivalent to BMI <18.5 kg/m 2.

          Materials and Methods

          The anthropometric data of patients hospitalised over the period 2004–2013 were retrospectively revised. The following variables were collected: weight, height, BMI, MUAC, sex and age.

          Results

          1373 patients were evaluated, who presented a mean weight of: 65.04±15.51 kg; height: 1.66±0.09 m; BMI: 23.48±5.03 kg/m 2; MUAC: 26.95±4.50 cm; age: 56.24±16.77. MUAC correlates suitably to BMI by means of the following equation (simple linear regression): BMI = − 0.042 + 0.873 x MUAC (cm) (R 2 = 0.609), with a Pearson r value of 0.78 (p<0.001). The area under the curve of MUAC for the diagnosis of malnutrition was 0.92 (95% CI: 0.90–0.94; p<0.001). The MUAC value ≤22.5 cm presented a sensitivity of 67.7%, specificity of 94.5%, and a correct classification of 90%. No significant statistical differences were found in the cut-off point of MUAC for the diagnosis of malnutrition based on sex (p = 0.115) and age (p = 0.694).

          Conclusions

          1) MUAC correlates positively and significantly with BMI. 2) MUAC ≤ 22.5 cm correlates properly with a BMI of <18.5 kg/m 2, independent of the age or sex of the patient, although there are other alternatives. MUAC constitutes a useful tool as a marker of malnutrition, fundamentally in patients for whom weight and height cannot be determined.

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          Most cited references16

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          Malnutrition in hospital outpatients and inpatients: prevalence, concurrent validity and ease of use of the 'malnutrition universal screening tool' ('MUST') for adults.

          The 'malnutrition universal screening tool' ('MUST') for adults has been developed for all health care settings and patient groups, but ease of use and agreement with other published tools when screening to identify malnutrition requires investigation. The present study assessed the agreement and the prevalence of malnutrition risk between 'MUST' and a variety of other tools in the same patients and compared the ease of using these tools. Groups of patients were consecutively screened using 'MUST' and: (1) MEREC Bulletin (MEREC) and Hickson and Hill (HH) tools (fifty gastroenterology outpatients); (2) nutrition risk score (NRS) and malnutrition screening tool (MST; seventy-five medical inpatients); (3) short-form mini nutritional assessment (MNA-tool; eighty-six elderly and eighty-five surgical inpatients); (4) subjective global assessment (SGA; fifty medical inpatients); (5) Doyle undernutrition risk score (URS; fifty-two surgical inpatients). Using 'MUST', the prevalence of malnutrition risk ranged from 19-60% in inpatients and 30% in outpatients. 'MUST' had 'excellent' agreement (kappa 0.775-0.893) with MEREC, NRS and SGA tools, 'fair-good' agreement (kappa 0.551-0.711) with HH, MST and MNA-tool tools and 'poor' agreement with the URS tool (kappa 0.255). When categorisation of malnutrition risk differed between tools, it did not do so systematically, except between 'MUST' and MNA-tool (P=0.0005) and URS (P=0.039). 'MUST' and MST were the easiest, quickest tools to complete (3-5 min). The present investigation suggested a high prevalence of malnutrition in hospital inpatients and outpatients (19-60% with 'MUST') and 'fair-good' to 'excellent' agreement beyond chance between 'MUST' and most other tools studied. 'MUST' was quick and easy to use in these patient groups.
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            The Mini Nutritional Assessment (MNA) and its use in grading the nutritional state of elderly patients.

            The Mini Nutritional Assessment (MNA) has recently been designed and validated to provide a single, rapid assessment of nutritional status in elderly patients in outpatient clinics, hospitals, and nursing homes. It has been translated into several languages and validated in many clinics around the world. The MNA test is composed of simple measurements and brief questions that can be completed in about 10 min. Discriminant analysis was used to compare the findings of the MNA with the nutritional status determined by physicians, using the standard extensive nutritional assessment including complete anthropometric, clinical biochemistry, and dietary parameters. The sum of the MNA score distinguishes between elderly patients with: 1) adequate nutritional status, MNA > or = 24; 2) protein-calorie malnutrition, MNA < 17; 3) at risk of malnutrition, MNA between 17 and 23.5. With this scoring, sensitivity was found to be 96%, specificity 98%, and predictive value 97%. The MNA scale was also found to be predictive of mortality and hospital cost. Most important it is possible to identify people at risk for malnutrition, scores between 17 and 23.5, before severe changes in weight or albumin levels occur. These individuals are more likely to have a decrease in caloric intake that can be easily corrected by nutritional intervention.
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              Assessment of Under Nutrition of Bangladeshi Adults Using Anthropometry: Can Body Mass Index Be Replaced by Mid-Upper-Arm-Circumference?

              Background and Objective Body-mass-index (BMI) is widely accepted as an indicator of nutritional status in adults. Mid-upper-arm-circumference (MUAC) is another anthropometric-measure used primarily among children. The present study attempted to evaluate the use of MUAC as a simpler alternative to BMI cut-off <18.5 to detect adult undernutrition, and thus to suggest a suitable cut-off value. Methods A cross-sectional study in 650 adult attendants of the patients of Dhaka-Hospital, of the International Centre for Diarrheal Disease Research, Bangladesh (icddr,b) was conducted during 2012. Height, weight and MUAC of 260 male and 390 female aged 19–60 years were measured. Curve estimation was done to assess the linearity and correlation of BMI and MUAC. Sensitivity and specificity of MUAC against BMI<18.5 was determined. Separate Receiver-operating-characteristic (ROC) analyses were performed for male and female. Area under ROC curve and Youden's index were generated to aid selection of the most suitable cut-off value of MUAC for undernutrition. A value with highest Youden's index was chosen for cut-off. Results Our data shows strong significant positive correlation (linear) between MUAC and BMI, for males r = 0.81, (p<0.001) and for females r = 0.828, (p<0.001). MUAC cut-off <25.1 cm in males (AUC 0.930) and <23.9 cm in females (AUC 0.930) were chosen separately based on highest corresponding Youden's index. These values best correspond with BMI cut-off for under nutrition (BMI <18.5) in either gender. Conclusion MUAC correlates closely with BMI. For the simplicity and easy to remember MUAC <25 cm for male and <24 cm for female may be considered as a simpler alternative to BMI cut-off <18.5 to detect adult undernutrition.
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                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
                5 August 2016
                2016
                : 11
                : 8
                : e0160480
                Affiliations
                [1 ]Endocrinology and Nutrition Department of Hospital Universitario Nuestra Señora de Candelaria, Ctra. Del Rosario n°145, 38010, Santa Cruz de Tenerife, Spain
                [2 ]Preventitive Medicine Department of Hospital Clínico San Carlos, Calle Profesor Martín Lagos, S/N, 28040, Madrid, Spain
                Hospital Universitario de la Princesa, SPAIN
                Author notes

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

                • Conceived and designed the experiments: NBB JPSL.

                • Performed the experiments: NBB JPSL MFF JGOG IDB FPGC NCC CXAR.

                • Analyzed the data: NBB MFF.

                • Contributed reagents/materials/analysis tools: NBB JPSL MFF JGOG IDB FPGC NCC CXAR EPA.

                • Wrote the paper: NBB JPSL MFF.

                Article
                PONE-D-15-56237
                10.1371/journal.pone.0160480
                4975446
                27494612
                6334ee31-9e9d-447b-8f3c-48849aded301
                © 2016 Benítez Brito et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 January 2016
                : 20 July 2016
                Page count
                Figures: 3, Tables: 2, Pages: 10
                Funding
                No current funding sources for this study. The authors only received funding to publish the article in open access (Fresenius Kabi España, S. A. U.) ( www.fresenius-kabi.es). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Nutrition
                Malnutrition
                Medicine and Health Sciences
                Nutrition
                Malnutrition
                Medicine and Health Sciences
                Health Care
                Patients
                Inpatients
                Social Sciences
                Anthropology
                Physical Anthropology
                Anthropometry
                Biology and Life Sciences
                Physical Anthropology
                Anthropometry
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Body Mass Index
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Body Mass Index
                Research and Analysis Methods
                Research Design
                Retrospective Studies
                Biology and Life Sciences
                Nutrition
                Medicine and Health Sciences
                Nutrition
                Medicine and Health Sciences
                Geriatrics
                People and Places
                Population Groupings
                Age Groups
                Elderly
                Custom metadata
                All relevant data are within the paper.

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                Uncategorized

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