Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-26T14:49:53.589Z Has data issue: false hasContentIssue false
  • English
  • Français

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

Published online by Cambridge University Press:  28 June 2021

Aparna Roy Open the ORCID record for Aparna Roy [Opens in a new window]  and
T. V. Sekher
Aparna Roy*
Affiliation:
International Institute for Population Sciences, Mumbai, India
T. V. Sekher
Affiliation:
Department of Population Policies and Programmes, International Institute for Population Sciences, Mumbai, India
*
*Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

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. (2017) 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.

Keywords

Adolescent nutritionMid upper arm circumferenceBody mass index
Type
Research Article
Information
Journal of Biosocial Science , Volume 54 , Issue 4 , July 2022 , pp. 617 - 628
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abdel-Rahman, SM, Bi, C and Thaete, K (2017) Construction of lambda, mu, sigma values for determining mid-upper arm circumference z scores in US children aged 2 months through 18 years. Nutrition in Clinical Practice 32(1), 68–76.CrossRefGoogle Scholar
Bhattacharya, A, Pal, B, Mukherjee, S and Roy, SK (2019) Assessment of nutritional status using anthropometric variables by multivariate analysis. BMC Public Health 19(1), 1045.CrossRefGoogle ScholarPubMed
Blackwell, N, Myatt, M, Allafort-Duverger, T, Balogoun, A, Ibrahim, A and Briend, A (2015) Mothers Understand And Can do it (MUAC): a comparison of mothers and community health workers determining mid-upper arm circumference in 103 children aged from 6 months to 5 years. Archives of Public Health 73(1), 26.CrossRefGoogle Scholar
Briend, A, Maire, B, Fontaine, O and Garenne, M (2012) Mid-upper arm circumference and weight-for-height to identify high-risk malnourished under-five children. Maternal & Child Nutrition 8(1), 130–133.CrossRefGoogle ScholarPubMed
Cashin, K and Oot, L (2018) Guide to Anthropometry: A Practical Tool for Program Planners, Managers, and Implementers. Food and Nutrition Technical Assistance III Project (FANTA), FHI 360.Google Scholar
Christian, P and Smith, ER (2018) Adolescent undernutrition: Global burden, physiology, and nutritional risks. Annals of Nutrition and Metabolism 72(4), 316–328.CrossRefGoogle ScholarPubMed
Cogill, B (2003) Guide to Anthropometry: A Practical Tool for Program Planners, Managers, and Implementers. Food and Nutrition Technical Assistance (FANTA), Academy for Educational Development, Washington, DC.Google Scholar
Cole, TJ (1990) The LMS method for constructing normalized growth standards. European Journal of Clinical Nutrition 44(1), 45–60.Google ScholarPubMed
Cusick, SE and Kuch, AE (2012) Determinants of undernutrition and overnutrition among adolescents in developing countries. Adolescent Medicine: State of the Art Reviews 23(3), 440.Google ScholarPubMed
Das, A, Saimala, G, Reddy, N, Mishra, P, Giri, R, Kumar, A et al. (2020) Mid-upper arm circumference as a substitute of the body mass index for assessment of nutritional status among adult and adolescent females: learning from an impoverished Indian state. Public Health 179, 68–75.CrossRefGoogle ScholarPubMed
Dasgupta, A, Butt, A, Saha, TK, Basu, G, Chattopadhyay, A and Mukherjee, A (2010) Assessment of malnutrition among adolescents: can BMI be replaced by MUAC. Indian Journal of Community Medicine 35(2), 276.CrossRefGoogle ScholarPubMed
Garenne, M, Maire, B, Fontaine, O and Briend, A (2013) Adequacy of child anthropometric indicators for measuring nutritional stress at population level: a study from Niakhar, Senegal. Public Health Nutrition 16(9), 1533–1539.CrossRefGoogle ScholarPubMed
Gorstein, J and Akré, J (1988) The use of anthropometry to assess nutritional status. World Health Statistics Quarterly 41 (2), 48–58.Google ScholarPubMed
IIPS and ICF (2017) National Family Health Survey 4, 2015–16. International Institute for Population Sciences, Mumbai.Google Scholar
Jeyakumar, A, Ghugre, P and Gadhave, S (2013) Mid-Upper-Arm Circumference (MUAC) as a simple measure to assess the nutritional status of adolescent girls as compared with BMI. ICAN: Infant, Child, & Adolescent Nutrition 5(1), 22–25.Google Scholar
Lillie, M, Lema, I, Kaaya, S, Steinberg, D and Baumgartner, JN (2019) Nutritional status among young adolescents attending primary school in Tanzania: contributions of mid-upper arm circumference (MUAC) for adolescent assessment. BMC Public Health 19(1), 1582.CrossRefGoogle ScholarPubMed
Mramba, L, Ngari, M, Mwangome, M, Muchai, L, Bauni, E, Walker, AS et al. (2017) A growth reference for mid upper arm circumference for age among school age children and adolescents, and validation for mortality: growth curve construction and longitudinal cohort study. British Medical Journal 358, j3423.CrossRefGoogle ScholarPubMed
Myatt, M, Khara, T and Collins, S (2006) A review of methods to detect cases of severely malnourished children in the community for their admission into community-based therapeutic care programs. Food and Nutrition Bulletin 27(Supplement 3), S7–S23.CrossRefGoogle ScholarPubMed
Sadler, K, Puett, C, Mothabbir, G and Myatt, M (2011) Community Case Management of Severe Acute Malnutrition in Southern Bangladesh. Tufts University, Boston. URL: SAM-Bangladesh-Feinstein-Save-2011.pdf (researchgate.net)Google Scholar
Sethi, V, Lahiri, A, Bhanot, A, Kumar, A, Chopra, M, Mishra, R et al. (2019) Adolescents, Diets and Nutrition: Growing well in a Changing World. The Comprehensive National Nutrition Survey, Thematic Reports, Issue 1. URL: CNNS-Thematic-Report-Adolescents-Diets-and-Nutrition.pdf (unicef.org)Google Scholar
Tang, AC, Dong, K, Deitchler, M, Chung, M, Maalouf-Manasseh, Z, Tumilowicz, A and Wanke, C (2013) Use of Cutoffs for Mid-Upper Arms Circumference (MUAC) as an Indicator or Predictor of Nutritional and Health-Related Outcomes in Adolscents and Adults: A Systematic Review. FHI 360/FANTA, Washington, DC.Google Scholar
Teferi, DY, Atomssa, GE and Mekonnen, TC (2018) Overweight and undernutrition in the cases of school-going adolescents in Wolaita Sodo Town, Southern Ethiopia: cross-sectional study. Journal of Nutrition and Metabolism 2018, ID 8678561. URL: https://doi.org/10.1155/2018/8678561 CrossRefGoogle Scholar
Thurnham, DI (2013) Nutrition of adolescent girls in low-and middle-income countries. Sight Life 27(3), 26–37.Google Scholar
United Nations (2019) World Population Prospects 2019. Department of Economic and Social Affairs, Population Division. URL: https://population.un.org/wpp/DataQuery/ (accessed February 2020).Google Scholar
Walters, T, Sibson, V and McGrath, M (2012) Mid Upper Arm Circumference and Weight-for-Height Z-Score as Indicators of Severe Acute Malnutrition. ENN, SCUK, ACF, UNHCR. URL: https://www.ennonline.net/attachments/1398/muac-wfh-reportweb.pdf Google Scholar
WHO (2006) Adolescent Nutrition: A Review of the Situation in Selected South-East Asian Countries. No. SEA-NUT-163. WHO Regional Office for South-East Asia.Google Scholar
WHO (2007) BMI-for-Age (5–19 Years). World Health Organization, Geneva. URL: http://www.who.int/growthref/who2007_bmi_for_age/en/ (accessed December 2019).Google Scholar
WHO (2014) Health for the World’s Adolescents. A Second Chance in the Second Decade. World Health Organization, Geneva. URL: http://apps.who.int/adolescent/second-decade/section2. (accessed February 2020).Google Scholar
WHO (2018) Implementing Effective Actions for Improving Adolescent Nutrition. World Health Organization, Geneva.Google Scholar
Young, MF, Nguyen, P, Tran, LM, Avula, R and Menon, P (2020) A double-edged sword? Improvements in economic conditions over a decade in India led to declines in undernutrition as well as increases in overweight among adolescents and women. Journal of Nutrition 150(2), 364–372.Google Scholar