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LETTER TO EDITOR  
Year : 2018  |  Volume : 43  |  Issue : 4  |  Page : 326
 

Response from the Authors (Kumar P et al)[1]



Date of Web Publication21-Dec-2018

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How to cite this article:
. Response from the Authors (Kumar P et al)[1]. Indian J Community Med 2018;43:326

How to cite this URL:
. Response from the Authors (Kumar P et al)[1]. Indian J Community Med [serial online] 2018 [cited 2019 Jan 21];43:326. Available from: http://www.ijcm.org.in/text.asp?2018/43/4/326/249456




Dear Sir,

Response to the comments on our article:

  1. We quote findings from a study[2] which was conducted in a busy village health and nutrition day of Purnea District, Bihar at a health sub-centre (catering to a population of 7,000 people) where armband MUAC (a bangle, with circumference 23 cm) and MUAC non-stretchable tape measurements were included in addition to weight and height measurements taken by a trained Auxillary Nurse Midwife (ANM), under supervision of a trained post-graduate nutrition researcher. Measurement times for each were recorded. The measurement time for MUAC using non-stretchable tape was 54 seconds and height 59 seconds. This excludes the time taken for other steps like self-introduction, obtaining informed consent, taking out tools for measurements and adjustment of clothes/footwear as the study was a part of a service delivery site where these aspects were already being done.
  2. We reported 84% sensitivity (268 being true positive out of 316) and specificity of 81% (48 being true negative out of 316) in mothers screened with low MUAC (MUAC <23 cm) when compared to BMI <18.5 kg/m2 as gold standard. Positive and negative predictive values were 78% and 87%, respectively. Positive and negative likelihood ratios were 4.5 (95% confidence interval [CI]: 3.67, 5.58) and 0.19 (95% CI: 0.14, 0.24), respectively. Good agreement was also observed between MUAC <21 cm and BMI <16 kg/m2 (k = 0.490 and P =0.00), where MUAC <21 cm was able to detect 79.6% of true positive but 90% true negative. In our study sample, we found women with thinness and severe thinness by BMI was 44% (BMI <18.5 kg/m2) and 8% (BMI <16 kg/m2), respectively. Corresponding percentages with MUAC were 48% thinness (MUAC <23 cm) and 14% severe thinness (MUAC <21cm), respectively. Thus, a higher proportion of women were identified as being thin/severely thin using MUAC compared to BMI. We do agree that if a MUAC cut-off with a high sensitivity is selected at the expense of specificity, health care systems must have the ability to handle large numbers of false positives (women who are falsely identified as "at risk"). Similarly, if a MUAC cut-off with high specificity is selected at the expense of sensitivity, programs may end up spending a large amount of resources screening women and identifying only a small proportion who are truly at risk. In a food-insecure settings, such as where this study was conducted, it would be rather programmatically desirable to include false negatives rather than exclude true positives, basis the type of intervention provided, particularly if only additional nutrition counselling and establishing linkages with social security nets including food entitlements, livelihood programmes is envisaged. This will prevent even the moderately thin women from falling into the severe acute malnutrition trap.
  3. There is limited data available on screening of maternal acute malnutrition using adult MUAC in resource poor settings. Hence, to fill the gap an attempt has been made in this paper to tabulate all studies from grey literature as well for the benefit of the reader. Out of five studies mentioned in Table 1, three studies are under publication in respective journals.
  4. The care packages mentioned in our study cover complete list of interventions relevant for a women with low MUAC as provided in MoHFW (2017) for screening and management of adult thinness and severe thinness, which are used in tuberculosis wards.[3] It includes: Improve dietary intake through nutrition education and counselling, test and treat for underlying diseases- such as diarrhoea, anemia, malaria, HIV and tuberculosis and linkages with various schemes: Integrated Child Development Scheme and public distribution scheme via a special food basket and F-100 supplement to those who are severely thin (MUAC <19 cms) and admited in the facility.
  5. In our study, MUAC cut-offs of <23 cm and <21 cm corresponding to BMI of <18.5 kg/m2 and <16 kg/m2 was used for screening acute and severe acute malnutrition, respectively. BMI <16 kg/m2 was taken as a gold standard to screen women with severe acute malnutrition. Good agreement (κ = 0.490, P = 0.00) was also observed between MUAC <21 cm and BMI <16.0 kg/m2. The prevalence of test was 7%, sensitivity was 79% (43 being true positive), and specificity was 90% (11 being true negative), respectively. An 8.5-fold likelihood of test being positive (95% CI: 6.5, 11.17) and 0.22-fold likelihood of it being negative (95% CI: 0.13, 0.38) were observed.
  6. The cited document also mentioned that MUAC cut-off (or range of cutoffs) based is only a first step toward determining a standardized and global MUAC cut-off for non-pregnant adults. They also reported that validation studies are needed to determine whether the proposed MUAC cut-off of <23 cm can be efficiently and effectively used as a screening tool for adult undernutrition.[4] The Ministry of Health and Family Welfare guidance document on nutritional care and support for patients with Tuberculosis in India recommended MUAC cut-offs of < 19 cm and <23 cm to screen adult women with severe acute malnutrition and acute malnutrition.[3]



   References Top


  1. Kumar P, Sareen N, Agrawal S, Kathuria N, Yadav S, Sethi V. Screening maternal acute malnutrition using adult mid-upper arm circumference in resource-poor settings. Indian Journal of Community Medicine: Official Publication of Indian Association of Preventive and Social Medicine 2018;43: 132-4.
  2. Sethi V, Parhi RN, Dar S, Agrawal S. Feasibility and diagnostic accuracy of using armband mid-upper arm circumference as a simple screening tool for maternal wasting in rural India. Rural Remote Health 2017;17:4221.
  3. Ministry of Health and Family Welfare (MoHFW). Guidance document: Nutritional care and support for patients with Tuberculosis in India. Government of India, New Delhi, India. 2017. Available from: https://tbcindia.gov.in/WriteReadData/Guidance%20Document%20-%20Nutritional%20Care%20%26%20Support%20for%20TB%20patients%20in%20India.pdf. [Last accessed on 2018 Apr 22].
  4. Tang AM, Chung M, Dong K, Wanke C, Bahwere P, Bose K, et al. Determining a global mid-upper arm circumference cut off to assess underweight in adults (men and non-pregnant women). Washington, DC. 2017: FHI 360/FANTA.




 
   References Top

1.
Kumar P, Sareen N, Agrawal S, Kathuria N, Yadav S, Sethi V. Screening maternal acute malnutrition using adult mid-upper arm circumference in resource-poor settings. Indian Journal of Community Medicine: Official Publication of Indian Association of Preventive and Social Medicine 2018;43:132-4.  Back to cited text no. 1
    
2.
Sethi V, Parhi RN, Dar S, Agrawal S. Feasibility and diagnostic accuracy of using armband mid-upper arm circumference as a simple screening tool for maternal wasting in rural India. Rural Remote Health 2017;17:4221.  Back to cited text no. 2
    
3.
Ministry of Health and Family Welfare (MoHFW). Guidance document: Nutritional care and support for patients with Tuberculosis in India. Government of India, New Delhi, India. 2017. Available from: http://tbcindia.gov.in/WriteReadData/Guidance%20Document%20-%20Nutritional%20Care%20%26%20Support%20for%20TB%20 patients%20in%20India.pdf. [Last accessed on 2018 Apr 22].  Back to cited text no. 3
    
4.
Tang AM, Chung M, Dong K, Wanke C, Bahwere P, Bose K, et al. Determining a global mid-upper arm circumference cut off to assess underweight in adults (men and non-pregnant women). Washington, DC. 2017: FHI 360/FANTA.  Back to cited text no. 4
    




 

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