Mid-upper Arm Circumference Cut-offs Research Articles

Improving case-detection of severe wasting among under-five-year-old children in Timor Leste: A secondary analysis of data from the 2020 national cross-sectional food and nutrition survey.

The World Health Organization recommends using weight-for-height Z-score (WHZ) <-3 or Mid-Upper Arm Circumference (MUAC) <115 mm as independent criteria for diagnosing severe wasting. However, there are several challenges in using the WHZ criterion. As a result, the MUAC (and edema)-only approach for identifying children needing treatment for severe wasting has been developed and is being rapidly scaled-up globally, including in Timor-Leste. But previous studies reported that MUAC<115 mm has poor diagnostic accuracy for detecting children with WHZ<-3. The two options being explored globally for improving the identification of these children in MUAC (and edema)-only programming contexts include expanding MUAC cut-off and the combination of the indicators MUAC and Weight-for-Age Z-score (WAZ). This study explored the accuracy for diagnosing severe wasting (WHZ<-3) of these two options in Timor-Leste. We conducted a secondary analysis of data from the 2020 national Timor-Leste Food and Nutrition Survey. We tested the accuracy of various MUAC cut-offs, and predefined case definitions in five age groups (0-5 months, 6-23 months, 24-59 months, 6-59 months, and 0-59 months). We calculated the standard diagnostic test parameters (sensitivity, specificity, Youden Index, and others) and used the Youden Index as the principal criterion for rating the overall level of accuracy. The sample analyzed comprised 11,056 children with complete information on our key variables (anthropometric data, age, and sex), of whom 52.2% were boys. The age groups 0 to 5 months, 6 to 23 months, and 24 to 59 months represented 9.0%, 33.7%, and 57.3% of the sample, respectively. We found that the optimal diagnostic MUAC cut-off varied across the age groups between 117 mm and 142 mm, with the Youden Index remaining < 55% in all the age groups considered. The use of case definitions combing MUAC and WAZ optimized the identification of children with WHZ<-3. The case definition MUAC<130 mm or WAZ<-3 Z-score had the best diagnostic accuracy in all the age groups except for the 0 to 5 months age group for which the case definition MUAC<110 mm or WAZ<-2 Z-score had the highest Youden Index. Our findings show that it is challenging to significantly improve diagnostic accuracy for identifying children with WHZ<-3 by only expanding the MUAC cut-off in under five Timorese children. However, In settings facing challenges in using WHZ, the combination of MUAC and WAZ indicators offers a promising approach. Further research is needed to confirm the effectiveness of the proposed combination of MUAC and WAZ indicators case definitions in a programmatic context in Timor-Leste, and other similar contexts.

Inadequacy of a 12.5 cm MUAC as a cutoff for malnutrition for children aged three to five years

Introduction: MUAC (mid-upper arm circumference) is a simple and easily taught screening tool for identifying malnutrition in children. South Sudan use a MUAC of 12.5 cm for children aged between six months and five years as a cut-off for moderate acute malnutrition. Currently, in South Sudan, children from six months to five years have the same MUAC cutoff for malnutrition. Method: This study evaluated the sensitivity of using a MUAC of 12.5 cm as a screening tool for children between 6 and 60 months applied to data obtained from children enrolled in urban and rural primary schools in Maridi County, South Sudan. We used the 12.5 cm cutoff which was 2 standard deviations from the median for boys at nine months and for girls at 20 months. We also used 14.0 cm as the cutoff and compared the number of children identified, and also the false positive rate, assuming -2 SD from the median to be the accepted norm for malnutrition. Finally, we considered two different standards, using 14.0 cm for children aged 3-5 years and 12.5 cm for children under three years. Results: Comparing the results obtained using the two different MUAC standards (12.5 cm versus 14.0 cm) against a single MUAC standard there is a dramatic difference in outcome. Using the current standard (12.5 cm), only 7.3% of the children were found to be malnourished. Using 14.0 cm, 33.8 % were found to be malnourished (Table 4). If we accept the norm of 2 SD below the median for age as an adequate definition of malnutrition, the false positive rate using 14.0 cm is 9.6 %, an acceptable figure for a screening device, but the false negative rate for 12.5 cm is 17.4 %, a clearly unacceptable rate for a screening device. If, however, instead of using one cut-off for children from six months to five years, a period characterized normally by rapid growth and changes in body composition, we used two different standards—12.5 cm for those under three years and 14 cm for those aged 3-5 years, the number of false positives drops down to 2.7% and false negatives to 0.9 % Conclusion: We suggest that the use of 12.5 cm for malnourished children is inappropriate above two years, that 14 cm would be a more appropriate screening measurement from 3-5 years of age.

Comparing Mid-Upper Arm Circumference With Body Mass Index for Assessing Nutritional Status in Indian Adults: Evidence From the National Family Health Survey 2015-16 (NFHS-4).

Background The surge in the twin burden of malnutrition - undernutrition and overweight/obesity - poses a severe threat worldwide including India. The adult group, primarily considered as an economic pillar of the society, suffered significant health problems, yet their nutritional issues are often neglected. Screening of nutritional status through anthropometric measurements is widely accepted. Body mass index (BMI) is commonly used but has certain limitations. Mid-upper arm circumference (MUAC), another simpler tool, is universally accepted in children, but its use in adults is debatable. The current research aims to determine the MUAC cutoffs and their predictive accuracies corresponding to BMI cutoffs for adult men and nonpregnant women. Subject and methods A cross-sectional analysis was conducted of the anthropometric data of Indian adult men and nonpregnant women collected in 2015-16 via the National Family Health Survey (NFHS-4). The receiver operating characteristic (ROC) curve analysis was performed to derive the MUAC cutoffs against BMI cutoffs. Results A significant moderate correlation for both men (r=0.56) and women (r=0.68) was observed. In relation to ROC analysis, the MUAC cutoffs against the BMI cutoffs of 18.5, 23, 25, and 30 kg/m2 were approximated to be 25, 26, 28, and 30 cm for men and 23, 25, 27, and 28 cm for women, respectively. These MUAC cutoffs showed good predictive accuracy with a high range of sensitivity and specificity for both men and women. Conclusions The non-invasive MUAC method correlates very well with BMI and offers several advantages, including accuracy, ease of measurement, and minimal logistical support and training, and can assess the nutritional status even in geographically remote areas. Therefore, it can be an important tool in public health, especially in resource-limited settings, for identifying populations at risk of malnutrition.

How Useful are Mid-Arm and Calf Circumferences to Indicate Reduced Muscle Mass in Order to Recognize GLIM-Defined Malnutrition in Elderly Individuals?

The aim of this study was to estimate cutoff values of mid-upper arm circumference (MUAC) and calf circumference (CC) for reduced muscle mass and analyze their accuracy in identifying malnutrition among individuals of 65 years of age or older in Bosnia and Herzegovina. The study is a secondary analysis dataset assessing nutritional risk and malnutrition among 446 community-dwellers and nursing home residents in Bosnia and Herzegovina. Malnutrition assessment included phenotypic criterions (weight loss, low body mass index, and reduced muscle mass) and etiologic criterions (inadequate food intake, disease-related inflammation, or albumin levels) according to recommendations of the Global Leadership Initiative on Malnutrition (GLIM). Receiver operating curves were used to calculate MUAC and CC's cutoff values as compared to the Mini Nutritional Assessment (MNA). The optimal cutoff value for MUAC in men was 24 cm (AUC = 0.910, sensitivity 100%, specificity 77%), and in women 23 cm (AUC = 0.792, sensitivity 64%, specificity 83%). Optimal cutoff value of CC in men was 31 cm (AUC = 0.818, sensitivity 100%, specificity 67%) and in women 29 cm (AUC = 0.882, sensitivity 86%, specificity 74%). Two hundred fifty nine elderly individuals were categorized as malnourished/at risk for malnutrition per MNA. The prevalence of malnutrition based on GLIM criteria ranged from 19% to 30%. The study suggested that MUAC and CC may be used as the alternative indicators of muscle mass when other assessment methods are unavailable. Future validation and reliability studies for GLIM using anthropometric parameters as a proxy of reduced muscle mass are needed.

Mid-upper arm circumference (MUAC) measurement usage among children with disabilities: A systematic review.

Background: Anthropometric measurements, including mid-upper arm circumference (MUAC), are used for monitoring and evaluating children's nutritional status. Evidence is limited on optimal nutritional assessment for children with disabilities, who are at high risk for malnutrition. Aim: This study describes MUAC use among children with disabilities. Methods: Four databases (Embase, Global Health, Medline, and CINHAL) were searched from January 1990 through September 2021 using a predefined search strategy. Of the 305 publications screened, 32 papers were included. Data included children 6 months to 18 years old with disabilities. Data including general study characteristics, methods for MUAC measurement, terminology, and measurement references were extracted into Excel. Due to heterogeneity of the data, a narrative synthesis was used. Results: Studies from 24 countries indicate that MUAC is being used as part of nutritional assessment, but MUAC measurement methods, references, and cutoffs were inconsistent. Sixteen (50%) reported MUAC as a mean ± standard deviation (SD), 11 (34%) reported ranges or percentiles, 6 (19%) reported z-scores, and 4 (13%) used other methods. Fourteen (45%) studies included both MUAC and weight-for-height but nonstandard reporting limited comparability of the indicators for identifying those at risk of malnutrition. Conclusion: Although its speed, simplicity, and ease of use afford MUAC great potential for assessing children with disabilities, more research is needed to understand its appropriateness, and how it performs at identifying nutritionally high-risk children in comparison to other measures. Without validated inclusive measures to identify malnutrition and monitor growth and health, millions of children could have severe consequences for their development.

Accuracy of Mid-Upper Arm Circumference for Detecting Acute Malnutrition in Children Aged 6-59 Months in an Urban Slum in Bangladesh: A Cross-Sectional Analysis.

Background The weight-for-height z-score (WHZ) is considered the gold standard for detecting acute malnutrition in children. However, an accurate assessment of WHZ can often be challenging, especially in community settings. Mid-upper arm circumference (MUAC) is a simple and easy-to-perform method to identify children with acute malnutrition. The objective of the study was to evaluate the accuracy of MUAC in detecting acute malnutrition compared to WHZ among children aged 6-59 months in Bangladesh. Methods We used anthropometric data for 239 children aged 6-59 months from a cross-sectional study conducted in 2013 in an urban slum in Dhaka, Bangladesh. The sensitivity and specificity of MUAC to detect acute malnutrition were calculated, considering WHZ as the gold standard. Results The mean age of the children was 29.4 ± 12.7 months, with a male-to-female ratio of 1:1.2. The prevalence of acute malnutrition was 17.1% and 22.5% based on WHZ and MUAC, respectively. The total area under the receiver operating characteristic curve was 0.816. For detecting acute malnutrition, the sensitivity of MUAC was 61.0% and the specificity was 85.4% for the World Health Organization (WHO) recommended cutoff of <125 mm. Using the Youden index, the best MUAC cutoff point to detect acute malnutrition was <128 mm with a sensitivity of 75.6% and a specificity of 74.7%. Conclusions Our study demonstrated a low sensitivity of MUAC to identify acute malnutrition at the WHO cutoff of <125 mm. The cutoff could be increased to <128 mm to capture more children with acute malnutrition.

Mid-upper arm circumference and neck circumference to screen for overweight-obesity in young adults in South India

IntroductionThere are many anthropometric techniques to screen for overweight-obesity like the body mass index (BMI), waist circumference (WC), and waist-hip ratio (WHR). These may be difficult or less acceptable in community and outpatient settings. We determine the cut-offs of mid-upper arm circumference (MUAC) and neck-circumference (NC) to screen overweight (BMI ≥25 kg/m2), abdominal obesity by waist circumference (WC; men: ≥90 cm; women: ≥80 cm) and high percent body fat (PBF) (men: ≥20%; women: ≥30%) and explore participant preference for various anthropometric methods. Methodology: We enrolled 282 medical students in South India and performed anthropometry (height, weight, WC, MUAC and NC), bio-impedance analysis (BIA, Inbody 770) to detect PBF. Receiver operator curves were generated and best cut-offs derived using highest Youden Index (sensitivity + specificity-1). ResultsOf the 282 participants, 83 (29.4%) were overweight, 113 (38.7%) had abdominal obesity and 186 (66%) had higher PBF. The MUAC cut-off was 31.3cm for men (sensitivity: 86%; specificity: 74%) to detect overweight and 31.2 cm (sensitivity: 85%; specificity: 73%) to detect abdominal obesity. The corresponding cut-offs in women were 28.5 cm (sensitivity:88%; specificity: 83%) to detect overweight and 28.3 cm (sensitivity: 74%; specificity: 92%) for abdominal obesity. For NC, the proposed cut-off in men was 36.6 cm (sensitivity: 81%; specificity: 82%) for overweight and 37.1 cm (sensitivity:78%; specificity:82%) for abdominal obesity. In women, this was 31.4 cm for both overweight as per BMI (sensitivity: 88%; specificity: 71%) and for abdominal obesity (sensitivity: 75%; specificity: 81%). Neck circumference was preferred by 225 (79.8%) participants. ConclusionBoth MUAC and NC can be considered for screening overweight and abdominal obesity with good sensitivity and specificity but their sensitivity and specificity for screening high PFB were not very good. Neck circumference was the most preferred anthropometric method.

Mid-upper arm circumference as a substitute for body mass index in the assessment of nutritional status among adults in eastern Sudan

BackgroundBody mass index (BMI) remains the most used indicator of nutritional status despite the presence of a potentially credible alternative. Mid-upper arm circumference (MUAC) is an anthropometric measure that requires simple equipment and minimal training. The aim of this study was to compare MUAC with BMI and propose a MUAC cut-off point corresponding to a BMI of < 18.5 kg/m2 (underweight) and ≥ 30.0 kg/m2 (obesity) among Sudanese adults.MethodsA cross-sectional study using multistage cluster sampling was conducted in New-Halfa, eastern Sudan. Participants’ age and sex were recorded and their MUAC, weight and height were measured using the standard procedures. The MUAC (cm) cut-offs corresponding to < 18.5 kg/m2 and ≥ 30.0 kg/m2 were calculated and determined using receiver operating characteristic (ROC) curve analysisResultsFive hundreds and fifty-two adults were enrolled in the study. The median (interquartile range, IQR) of the participants age was 31.0 (24.0 ̶ 40.0) years and 331 (60.0%) of them were females. The medians (IQR) of BMI and MUAC were 22.4 (19.1 ̶ 26.3) kg/m2 and 25.0 (23.0 ̶ 28.0) cm, respectively.There was a significant positive correlation between MUAC and BMI (r = 0.673, p < 0.001).Of the 552 enrolled participants, 104 (18.8%), 282 (51.1%), 89 (16.1%) and 77 (13.9%) were normal weight, underweight, overweight and obese, respectively. Best statistically derived MUAC cut-off corresponding to a BMI < 18.5 kg/m2 (underweight) was ≤ 25.5 cm in both males and females (Youden’s Index, YI = 0.51; sensitivity = 96.0%; specificity = 54.0%), with a good predictive value (AUROCC = 0.82). Best statistically derived MUAC cut-off corresponding to a BMI ≥ 30.0 kg/m2 (obesity) was ≥ 29.5 cm in both males and females (YI = 0.62, sensitivity = 70.3%, specificity = 92.0%), with a good predictive value (AUROCC = 0.86, 95.0% CI = 0.76 – 0.95).ConclusionThe results suggest that the cut-offs based on MUAC can be used for community-based screening of underweight and obesity

Mid upper arm circumference as screening tool of overweight or obesity among adult employees of Mizan Tepi University, Southwest Ethiopia

BackgroundOverweight or obesity is an excessive fat accumulation that impairs the health and wellbeing of the adult population throughout the world. Recently Mid upper arm circumference (MUAC) was suggested as a screening index for overweight or obesity among adolescents, but its utilization for the assessment of overweight or obesity in the adult population is not clear yet. In addition, little is known about the screening ability of MUAC for overweight or obesity in the adult population of Ethiopia. Therefore, this study aimed to evaluate the utility of MUAC for screening overweight or obesity among adult employees of Mizan Tepi University, Southwest Ethiopia. MethodA Facility -based cross-sectional study was carried out from February 21 to March 20, 2020, at Mizan Tepi University. About 585 study participants were selected by gender-based stratified sampling technique. Anthropometric data like weight, height, and MUAC were collected. Pearson's correlation between MUAC, body mass index (BMI), and age was calculated to see a relationship between them. The Receiver operating characteristics (ROC) curve was calculated to identify the screening ability of MUAC for overweight or obesity. The appropriate MUAC cutoff point for both men and women established using the Youden index. Additionally, sensitivity, specificity, positive, and negative predictive values were calculated. ResultThe prevalence of overweight and obesity among the study participants was 18.1% and 4.8%, respectively. MUAC had a strong positive correlation with BMI, r = 0.65 (95% CI; 0.56–0.69). According to ROC analysis, MUAC is an excellent screening tool for male and female employees with excellent accuracy (AUC = 0.9 with 91.4% sensitivity and 76.4% specificity) and good accuracy (AUC = 0.83 with 67.2% sensitivity and 83.5% specificity), respectively. Based on the youden index, the cutoff point of MUAC to screen overweight or obesity among male and female employees was 26.91cm. ConclusionMid-upper arm circumference (MUAC) has an equal ability with BMI to screen overweight or obesity among adults. Therefore, MUAC can be utilized as an alternative index to screen overweight and obesity in resource-limited setups.

Relationship Between Mid-upper Arm Circumference (MUAC) and Body Mass Index (BMI) in Children Aged 6 - 12 Years: A Cross-sectional Study

Background: Obesity has become one of the most important health problems worldwide. Body mass index (BMI) is a clinical assessment of overweight and obesity in children, although mid-upper arm circumference (MUAC) assessment is more straightforward, especially for parents. Objectives: This study aimed to investigate the relationship between MUAC and BMI in children aged 6 - 12 years. Methods: This cross-sectional study was performed on 455 elementary school children aged 6 - 12, including 278 girls and 177 boys with a mean age of 8.8 ± 1.8 years selected using the census method. Our researcher was trained for anthropometric data collection. Data were analyzed by SPSS version 25 software using Mann-Whitney, Kolmogorov-Smirnov, and Kruskal-Wallis tests. Results: The mean age was 9.19 ± 1.8 years, the mean height was 135 ± 12 cm, the mean weight was 31.85 ± 11 kg, the mean MUAC was 21 ± 3.1 cm, and the mean BMI was 17 ± 3.6 kg/m2. There was a significant correlation between MUAC and BMI in both sexes, but it was stronger in girls than in boys (P-value &lt; 0.05). The MUAC cutoff point was 23.75 cm (77% sensitivity and 80% specificity) and 24.75 cm (93% sensitivity and 88% specificity) for overweigh and obesity in girls, respectively. Also, it was 23.25 cm (88% sensitivity and 83% specificity) and 25.25 cm (87% sensitivity and 90% specificity) for overweigh and obesity in boys, respectively. Conclusions: We recommend MUAC as a predictor of early diagnosis of overweight and obesity.

Could mid-upper arm circumference be a valid proxy to the body mass index for elderly persons?

Introduction: In elderly persons, due to physiological, anatomical, and functional changes, body mass index (BMI) may not be suitable for the assessment of nutritional status. Mid-upper arm circumference (MUAC) can be a proxy indicator to identify underweight and overweight/obesity among elderly persons. This study aimed to estimate the correlation between MUAC and BMI, and the cutoffs for MUAC using receiver operating characteristic (ROC) analysis. Material and Methods: This survey was carried out in a resettlement colony of Delhi. The participants were residents of the area who were aged 60 years or older, and selected by a simple random sampling technique. The arm span, weight, and MUAC of the participants were measured. The correlation between MUAC and BMI for gender and age group was calculated. The ROC curve was also constructed. Results: A total of 946 eligible participants were enrolled. The correlation between MUAC and BMI was 0.67 (P &lt; 0.001) and 0.76 (P &lt; 0.001) among men and women, respectively. The MUAC cutoff for underweight was &lt;25 cm with a sensitivity of 68.8% and specificity of 84.9%. The area under the curve (AUC) was 0.84 (0.80–0.88). The MUAC cutoff for overweight/obesity was ≥27 cm with a sensitivity of 83.9% and specificity of 64.9%, and AUC was 0.78 (0.75–0.82). Conclusion: The MUAC of the participants increased as the BMI of the participants increased. MUAC cutoff was determined using the ROC curve for underweight and overweight/obesity among elderly persons.

Validation of MUAC Cut-Offs of WHO for Diagnosis of Acute Malnutrition among Children under 5 Years in Karachi, Pakistan

Objective: To validate the WHO recommended Mid-Upper Arm Circumference (MUAC) cut-offs for acute malnutrition screening in children younger than five in Karachi, Pakistan.&#x0D; Methods: A cross-sectional study was conducted, including an anthropometric examination following WHO guidelines. Height was measured using Stadiometer and Infantometer. The link between MUAC and Weight-for-Height-Z score (WHZ) for different cut-offs of MUAC for Moderate Acute Malnutrition (MAM) and Severe Acute Malnutrition (SAM) was shown using Receiver Operator Characteristics (ROC) curves and the Youden index. Sensitivity and specificity of MUAC &lt;11.5 cm and ≥11.5 to &lt;12.5cm were determined using WHZ scores of -3 Standard Deviation (SD) and ≥-3 to &lt;-2 SD for SAM and MAM, respectively.&#x0D; Results: Among 499 children, as per WHZ score, 9.6% and 27.1% had SAM and MAM, respectively, whereas according to MUAC, 6.4% and 3.6% had MAM and SAM, respectively. At the maximum value of the Youden index of 55.6%, an optimum cut-off of 12.7cm for screening of SAM with MUAC was found compared to the recommended cut-off of 11.5cm. Similarly, at the maximum value of the Youden index of 57.7%, an optimum cut-off of 13.9cm for screening of MAM with MUAC was found compared to the recommended cut-off of 12.5cm.&#x0D; Conclusion: The current MUAC cut-off of WHO for screening SAM and MAM cases captures only a small percentage of children under five. This needs to be revised to capture children with acute malnutrition for timely treatment in Pakistan.

Accuracy of Using Mid-Upper Arm Circumference to Detect Wasting Among Children Aged 6-59 Months in Nepal.

In countries with a high prevalence of undernutrition, timely, accurate screening at the community level is essential to identify children with wasting. The World Health Organization recommends using either weight-for-height z-scores (WHZ) and mid-upper arm circumference (MUAC) or both measures and signs of edema to be used to identify children with severe acute malnutrition for treatment. We compared WHZ and MUAC cutoffs to identify wasting among children aged 6-59 months in Nepal, using WHZ as the reference standard. We used cross-sectional anthropometric data for 3,169 children aged 6-59 months from a 2017 cross-sectional dataset, representative of 42 of Nepal's 77 districts. We used descriptive statistics, receiver operating characteristic (ROC) curves, and kappa statistics to compare the use of MUAC and WHZ to identify wasting. The Youden index was calculated to determine the optimum MUAC cutoffs. The prevalence of wasting was 3.1% and 10.5% using MUAC and WHZ, respectively. We found 13.6% sensitivity for severe acute malnutrition (SAM) (MUAC <115 mm) and 21.0% sensitivity for moderate acute malnutrition (MAM) (MUAC ≥115 to <125 mm), with specificity of 99.7% and 91.2%, respectively. The sensitivity of MUAC for children aged 6-23 months was higher than for children aged 24-59 months. The total area of the ROC curve was 0.53 for the MUAC cutoff for SAM and 0.56 for MAM. The optimum MUAC cutoffs for SAM and MAM were 125 mm and 132 mm, respectively. Although MUAC can be used as a rapid screening tool to detect wasting in children aged 6-59 months, using the recommended MUAC cutoffs captures only a small proportion of the total number of wasted children. The poor sensitivity and specificity of MUAC compared to WHZ suggests a need to refine admission and discharge criteria for acute malnutrition management programs to ensure that wasting among infants and children in Nepal is consistently and accurately diagnosed and treated.

Validating mid-upper arm circumference (MUAC) cut off points as an indicator of nutritional status among nine tribal populations of India

Mid-upper arm circumference (MUAC) is an alternative anthropometric measurement to assess undernutrition but a universally accepted cut-off is yet to be established. The objectives of the present study are to determine whether the proposed sex-specific global cut-offs are suitable across several tribes in India. This cross-sectional study was conducted among nine tribal populations in India (1046 males, 1087 females). Weight, height and MUAC values were obtained, and body mass index (BMI) was calculated. The BMI cut-off (&lt;18.5 kg/m2) was used to determine chronic energy deficiency (CED). The ROC Curve analyses of binomial logistic regression for MUAC versus CED revealed optimal cut-off point of MUAC as 23.8 cm (in males) and 21.8 cm (in females). MUAC cut-offs were similar in females, relative to males, in all tribes. Males with MUAC&lt;24cm and females with MUAC&lt;22 encompassed significantly higher numbers of CED than those with MUAC≥24 and ≥22 cm, respectively (χ2-value males: 254.9, p&lt;0.001; females: 493.60, p&lt;0.01). A single cut off point of MUAC may not be universally applicable for diverse populations and both sexes as well. It seemed that there is no alternative than to undertake further validation studies in various populations before using the MUAC cut off to identify undernourished or CED condition.

High Prevalence of Overweight and Its Association with Mid-Upper Arm Circumference among Female and Male Farmers in Tanzania and Mozambique.

The increasing prevalence of overweight/obesity may already have reached the farmers in Tanzania and Mozambique. Here, the measurement of the mid-upper-arm-circumference (MUAC) could become a simple and sensitive tool for early detection of at-risk groups of overweight as well as underweight. Body Mass Index (BMI) and MUAC of female and male farmers (n = 2106) from different regions of Tanzania and the Zambézia province, Mozambique, were analyzed by region, sex, age, and correlates. MUAC cut-offs, calculated via BMI cut-offs (<18.5, ≥25, and ≥30 kg/m2), and multiple linear regression (MLR), compared to those selected by highest Youden’s index (YI) value, were assessed. The study showed an overall higher prevalence of overweight (19%) than underweight (10%) due to the high number of overweight female farmers (up to 35%) in southern Tanzania. BMI, which was mainly and positively predicted by MUAC, was higher in Tanzania and among female farmers, and decreased significantly from the age of ≥65 years. MUAC cut-offs of <24 cm and ≥30.5 cm, calculated by MLR, detected 55% of farmers being underweight and 74% being overweight, with a specificity of 96%; the higher cut-off <25 cm and lower cut-off ≥29 cm, each selected according to YI, consequently detected more underweight (80%) and overweight farmers (91%), but on the basis of a lower specificity (87–88%). Overweight was evident among female farmers in East Africa. MUAC cut-offs, whether defined via linear regression or Youden’s Index, could prove to be easy-to-use tools for large-scale screenings of both underweight and overweight.

Use of mid-upper arm circumference to screen for thinness among sub-Saharan African male detainees.

BMI is a time-intensive measurement to assess nutritional status. Mid-upper arm circumference (MUAC) has been studied as a proxy for BMI in adults, but there is no consensus on its optimal use. We calculated sensitivity, specificity and area under receiver operating characteristic curve (AUROCC) of MUAC for BMI < 18·5, <17 and <16 kg/m2. We designed a system using two MUAC cut-offs, with a healthy (non-thin) 'green' group, a 'yellow' group requiring BMI measurement and a 'red' group who could proceed directly to treatment for thinness. We retrospectively analysed monitoring data collected by the International Committee of the Red Cross in places of detention. 11 917 male detainees in eight African countries. MUAC had excellent discriminatory ability with AUROCC: 0·87, 0·90 and 0·92 for BMI < 18·5, BMI < 17 and BMI < 16 kg/m2, respectively. An upper cut-off of MUAC 25·5 cm to exclude healthy detainees would result in 64 % fewer detainees requiring BMI screening and had sensitivity 77 % (95 % CI 69·4, 84·7) and specificity 79·6 % (95 % CI 72·6, 86·5) for BMI < 18·5 kg/m2. A lower cut-off of MUAC < 21·0 cm had sensitivity 25·4 % (95 % CI 11·7, 39·1) and specificity 99·0 % (95 % CI 97·9, 100·0) for BMI < 16 kg/m2. An additional 50 kg weight requirement improved specificity to 99·6 % (95 % CI 99·0, 100·0) with similar sensitivity. A MUAC cut-off of 25·5 cm, above which detainees are classified as healthy and below receive further screening, would result in significant time savings. A cut-off of <21·0 cm and weight <50 kg can identify some detainees with BMI < 16 kg/m2 who require immediate treatment.

Mid upper arm circumference as an alternative measure to assess the nutritional status of adolescents: a study in India based on NFHS-4 data.

Use of body mass index (BMI) to assess the nutritional status of adolescents requires many resources, especially for country-level assessment. This study aimed to determine the relationship between BMI and mid upper arm circumference (MUAC) among adolescent males and females in India and to examine whether MUAC effectively represents the nutritional status of adolescents. The study utilized anthropometric measurement data collected by India's National Family Health Survey-4 (2015-16). The weighted sample for analysis included 91,315 female and 14,893 male adolescents. The BMI and MUAC measurements showed a positive correlation in both female and male adolescents. Using BMI-for-age Z-score classifications, 12.7% of the adolescents were undernourished. Using MUAC (in cm) as per NACS (Nutrition Assessment, Counselling, and Support) guidelines and Mramba et al. () classified 22.9% and 3.7% of the adolescents as undernourished respectively. Finally, using the MUAC-for-age Z-score classification, 98.4% of adolescents were determined to be normal and 1.7% undernourished. Sensitivity and specificity tests of the MUAC cut-offs, in comparison with BMI cut-offs, showed that all three MUAC cut-off classifications had high specificity (NACS cut-off: 81.3%; Mramba et al. cut-off (cm): 97.7%; Mramba et al. cut-off (Z-score): 99.1%). The NACS cut-off had moderately high sensitivity (52.2%) but the Mramba et al. cut-offs had low sensitivity (13.3% for the centimetre cut-off and 6.6% for the Z-score cut-off). Sensitivity and specificity tests proved the relationship between BMI and MUAC, and that MUAC represents adolescent nutritional status with considerable efficiency. With further research, it may be established that MUAC is a better and promising measure of adolescent nutrition, having the advantage of needing fewer resources for data collection. The MUAC has the potential to offer a simple and low-resource alternative to BMI to assess nutritional status among adolescents in poor countries.

Mid-Upper Arm Circumference as an Alternative Screening Instrument to Appendicular Skeletal Muscle Mass Index for Diagnosing Sarcopenia.

PurposeMid-upper arm circumference (MUAC) is a simple, noninvasive anthropometric indicator. This study evaluated the applicability of MUAC as an alternative screening instrument to appendicular skeletal muscle mass index (ASMI) for detecting sarcopenia, and determined the optimal MUAC cutoff values.Patients and MethodsA total of 4509 subjects ≥50 years of age from the West China Health and Aging Trend study were included in the present study. ASM was measured by bioelectrical impedance analysis. MUAC, calf circumference (CC), and grip strength were evaluated and the Short Physical Performance Battery and 3-m timed up-and-go test were administered. Low muscle mass was diagnosed based on Asian Working Group for Sarcopenia 2019 (AWGS2019) and updated European Working Group on Sarcopenia in Older People 2 (EWGSOP2) criteria.ResultsASMI was positively correlated with MUAC in both men (r=0.726, P<0.001) and women (r=0.698, P<0.001). The area under the receiver operating characteristic curve (AUC) for MUAC as an indicator of low muscle mass in men and women was 0.86 (95% confidence interval [CI]: 0.85–0.88) and 0.85 (95% CI: 0.84–0.86), respectively, according to AWGS2019 criteria; and 0.86 (95% CI: 0.85–0.88) and 0.86 (95% CI: 0.85–0.88), respectively, according to EWGSOP2 criteria. Optimal MUAC cutoff values for predicting low muscle mass were ≤28.6 cm for men and ≤27.5 cm for women. There was no significant difference between the AUCs of MUAC and CC in men according to the 2 reference standards (P=0.809), whereas the AUC of CC was superior to that of MUAC in women according to AWGS2019 (P<0.001) and EWGSOP2 (P=0.008) criteria.ConclusionMUAC is strongly correlated with ASMI among community-dwelling middle-aged and older adults in China. MUAC can be used as a simple screening instrument to ASMI for diagnosing sarcopenia, especially in men.

Discriminatory ability of mid-upper arm circumference in identifying overweight and obese adolescents: Findings from the comprehensive national nutrition survey, India.

Overweight and obesity during adolescence is an important public health problem. However, little is known about the age-and sex-specific mid-upper arm circumference (MUAC) cut-offs for identifying overweight and obese adolescents. The present study was planned to assess diagnostic performance of MUAC in identifying overweight and obese adolescents and estimating age specific MUAC cut-offs, separately for males and females, taking body mass index for age Z-score (BAZ) as the gold standard. The present study is secondary data analysis using Comprehensive National Nutrition Survey, India, on 31,471 adolescents. The, area under curve receiver operating characteristic curve (AUC), and Youden Index were used to estimate MUAC cut-offs for overweight (BAZ > +1) and obesity (BAZ > +2). The MUAC cut-offs to identify overweight were: For 10-14 years- 22.9/23.4 cm, for 15-19 years - 27.0/25.6 cm for males and females, respectively; and for obesity were: For 10-14 years - 24.5/25.1, for 15-19 years - 28.5/28.0 cm for males and females, respectively. For overweight, among males, the age-specific cut-off ranged between 21.2 cm (10 years) and 29.8 (19 years), and for females ranged between 21.2 cm (10 years) and 26.7 cm (19 years). For obesity, it ranged between 22.4 cm (10 years) and 31.1 cm (18 years) for males, and 23.9 cm (10 years) to 26.9 cm (19 years) for females. For obesity, AUC ranged between 0.81 and 0.92, indicating good to excellent diagnostic accuracy. Age- and sex-specific MUAC cut-offs could be considered as a screening tool for identifying overweight and obese adolescents.

Anthropometric Criteria for Identifying Infants Under 6 Months of Age at Risk of Morbidity and Mortality: A Systematic Review.

Background:There is increasing global focus on small and nutritionally at-risk infants aged <6 months (<6 m). Current WHO guidelines recommend weight-for-length z-score (WLZ) for enrolment to malnutrition treatment programmes but acknowledge a weak evidence-base. This review aims to inform future guidelines by examining which anthropometric criteria best identify infants <6 m at high risk of mortality/morbidity.Methods:We searched Medline, EMBASE, CINAHL, Global Health, Cochrane Library and POPLINE for studies conducted in low- and middle-income countries and published between 1990 and October 2020. We included studies reporting anthropometric assessment of nutritional status in infants <6 m and assessed the association with subsequent morbidity or mortality.Results:A total of 19 studies were included in the final review, covering 20 countries, predominantly in sub-Saharan Africa. WLZ had poor reliability and poor prognostic ability to identify infants at risk of death. Mid-upper arm circumference (MUAC) and weight-for-age z-score (WAZ) were better at identifying infants at risk of mortality/morbidity. MUAC-for-age z-score did not perform better than using a single MUAC cut-off. Suggested MUAC cut-offs for this age group varied by context, ranging from 10.5 to 11.5 cm. The assessment for reliability showed that length was difficult to measure, making WLZ the least reliable indicator overall.Conclusion:Evidence from our review suggests that a change in current practice is necessary. To better identify small and nutritionally at-risk infants <6 m WAZ and/or MUAC rather than WLZ should be used. Future research should explore possible benefits for programme coverage, impact and cost-effectiveness. Research should also examine if context-specific MUAC thresholds are needed.