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

Anil Kumar Goswami; Ramadass Sathiyamoorthy; Kalaivani Mani; Shashi Kant; Sanjeev Kumar Gupta

doi:10.4103/ijcfm.ijcfm_23_22

ORIGINAL ARTICLE

Year : 2022 | Volume : 8 | Issue : 2 | Page : 143-147

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

Anil Kumar Goswami¹, Ramadass Sathiyamoorthy¹, Kalaivani Mani², Shashi Kant¹, Sanjeev Kumar Gupta¹
¹ Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
² Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India

Date of Submission	06-Mar-2022
Date of Decision	07-Dec-2022
Date of Acceptance	09-Dec-2022
Date of Web Publication	31-Dec-2022

Correspondence Address:
Prof. Sanjeev Kumar Gupta
Centre for Community Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi - 110 029
India

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijcfm.ijcfm_23_22

Abstract

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 < 0.001) and 0.76 (P < 0.001) among men and women, respectively. The MUAC cutoff for underweight was <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.

Keywords: Body mass index, elderly persons, mid-upper arm circumference, nutritional assessment

How to cite this article:
Goswami AK, Sathiyamoorthy R, Mani K, Kant S, Gupta SK. Could mid-upper arm circumference be a valid proxy to the body mass index for elderly persons?. Indian J Community Fam Med 2022;8:143-7

How to cite this URL:
Goswami AK, Sathiyamoorthy R, Mani K, Kant S, Gupta SK. Could mid-upper arm circumference be a valid proxy to the body mass index for elderly persons?. Indian J Community Fam Med [serial online] 2022 [cited 2023 May 28];8:143-7. Available from: https://www.ijcfm.org/text.asp?2022/8/2/143/366546

Introduction

The nutritional status of the adult population is commonly determined by Body Mass Index (BMI).^[1] The standards for BMI measurement and the categories of nutritional status were established by the World Health Organization (WHO) through various studies.^[2],[3] Body composition of elderly persons differ significantly from the adult population aged <60 years.^[4] As age increases, there is a decrease in fat-free mass and increase in the percentage of body fat.^[5] Elderly persons suffer from loss of muscle mass, increased spinal curvature, and loss of inter-vertebral space. There is also difficulty in the measurement of weight and height in bedridden elderly persons. These changes may result in erroneous assessments of height and weight. Due to these factors, BMI may not be the best indicator for the measurement of body composition in elderly persons.

Malnutrition is common among the elderly population in India as well as the world.^[6],[7],[8] Early detection of malnutrition among the elderly can help in correcting it through various simple measures such as oral supplementation and dietary advice.^[9],[10] In community settings, the assessment of nutrition requires an easy and valid method. Studies from Canada and Mexico reported that the mid-upper arm circumference (MUAC) is a valid tool to assess the nutritional status of the elderly.^[11],[12] In India, there was limited published data that assessed the correlation between MUAC and BMI. This study aimed to fill this gap, and to suggest appropriate cutoff values to identify malnutrition.

Material and Methods

The study was carried out from December 2019 to March 2020 in a resettlement colony located in the southern part of Delhi. The record of all residents of the area was stored in an electronic Health Management Information System that was accessible to the researchers. All residents of this colony that were aged 60 years or older were eligible to participate in the study. The exclusion criteria were otherwise eligible participants who could not either/or communicate or comprehend. Using the standard formula,^[13] the required sample size was 1308. This was based on the assumption that the power of the study to be 90%, the alpha error of 5%, the correlation coefficient of 0.5,^[14] and to also make allowance for migration (15%) and death (20%). The sampling technique was simple random sampling.

House-to-house visits were made by trained nonspecialist graduate data collectors. The data collectors were trained in the measurement of the anthropometry of the elderly persons, namely, weight, arm span, and MUAC. If the selected participant was not available at home during three separate house visits, then she was categorized as noncontactable. Written informed consent was sought before the start of the data collection. The WHO-approved methods were used for anthropometric measurements.^[3] The final recording was the average of two measurements. The arm span was recorded to the nearest 0.1 cm using a nonelastic measuring tape. Digital weighing machine was used to measure the weight to the nearest 100 g. Height was substituted by arm span in the formula used to calculate BMI.^[15],[16] The categorization of BMI was as per the cutoff values suggested by the WHO. The participants were categorized with a BMI of <18.5 kg/m² as underweight, and ≥25 kg/m² as overweight/obesity. The MUAC was measured, using standard technique, to the nearest 0.1 cm, and the average of two measurements was recorded.

The data were entered in Epi Info Version 7.2. (CDC, Atlanta, Georgia, USA) MUAC and BMI were expressed as mean standard deviation (SD). Their relationship was evaluated through scatter diagrams and regression lines. The receiver operating characteristic (ROC) and area under the curve (AUC) were reported. ROC curves were used to assess the ability of MUAC in detecting malnutrition. ROC was used to identify the MUAC cutoff where the sensitivity and specificity were maximum and closest to each other for both categories separately.

All the regulations of Helsinki declaration were followed.^[17] The institutional Ethics Committee of All India Institute of Medical Sciences (AIIMS), New Delhi had approved the study. The AIIMS provided a research grant for this study.

Results

Out of the selected sample of 1308 elderly persons, 87 were dead, and 169 had migrated. Of the remaining 1,052 persons, 75 refused to participate, and 18 were noncontactable. Weight and/or arms-span could not be measured in seven participants, as they were bedridden due to sickness (three), handicapped (two), paralyzed (one), or had an arm in a plaster cast (one). In twelve participants, arm span and weight were not measured for six participants, and MUAC was not measured for the remaining six participants. Hence, data were collected from 946 elderly persons out of the selected sample of 1052 (89.9%).

Of all participants, 568 (60%) were women. The overall mean MUAC was 25.9 ± 3.3 cm and BMI was 23.2 ± 4.8 kg/m². Women had mean MUAC and BMI of 26.1 ± 3.6 cm and 26.1 ± 3.6 kg/m². Men had mean MUAC and BMI of 25.7 ± 3 cm and 21.5 ± 4 kg/m², respectively [Table 1].

Table 1: Distribution of mean mid-upper arm circumference and mean body mass index by gender and age group of elderly persons (N=952)

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There was a positive correlation (correlation coefficient of 0.72 (P < 0.001)) between MUAC and BMI [Figure 1]. The positive correlation was strongly maintained across all age groups and gender [Table 2].

Table 2: Distribution of correlation between mid-upper arm circumference and body mass index by age group among elderly persons

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Figure 1: Correlation of MUAC and BMI among elderly persons. MUAC: Mid-upper arm circumference, BMI: Body mass index

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The cutoff value of MUAC for the identification of underweight was <25.5 cm for men and <24.0 cm for women. The sensitivity and specificity in men were 61.9% and 90.4%, respectively. In women, the sensitivity and specificity were 72.0% and 82.5%, respectively. Overall, the cutoff value for MUAC was <25.0 cm with 68.8% sensitivity and 84.9% specificity [Table 3].

Table 3: Mid-upper arm circumference cutoff value in detecting undernutrition and overweight/obesity among elderly persons

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ROC cutoff of MUAC for correctly identifying overweight and obesity were combined. The cutoff for MUAC in men was ≥27.0 cm, with a sensitivity of 83.9% and specificity of 64.9%. In women, the cutoff was ≥26.0 cm with a sensitivity of 85.5% and specificity of 59.5%. Overall, in both gender, the cutoff was ≥27.0 cm with a sensitivity of 71.7% and specificity of 70.0%.

When the MUAC cutoff was <25.0 cm, the AUC was 0.84 (0.80–0.88) for correctly identifying underweight in both men and women. The corresponding MUAC figure to correctly identify overweight/obesity was ≥27.0 with the AUC as 0.78 (0.75–0.82). These were depicted in [Figure 2] and [Figure 3], respectively.

Figure 2: ROC curve of MUAC in correctly identifying underweight among elderly persons. MUAC: Mid-upper arm circumference, ROC: Receiver operating characteristic

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Figure 3: ROC curve of MUAC in correctly identifying overweight or obesity among elderly persons. MUAC: Mid-upper arm circumference, ROC: Receiver operating characteristic

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Discussion

This study found a significant positive correlation of 0.72 (P < 0.001) between MUAC and BMI among elderly persons (both genders included). A study by Benítez Brito et al. among inpatients of a nutrition clinic in Spain reported a similar correlation (Pearson r = 0.78, P < 0.001).^[18] A positive correlation of 0.743 (P < 0.001) was reported between MUAC and BMI where the participants were adult attendants of patients admitted to a hospital in Bangladesh.^[19] A Pearson's correlation coefficient of 0.872 (P < 0.001) was reported for adult patients from two government hospitals in Nepal.^[20] The correlation was high separately for both women (r = 0.889) as well as men (r = 0.846). In the present study, men had a correlation coefficient of 0.67 (P < 0.001) and women had 0.76 (P < 0.001). The slight decrease in the correlation coefficient in the present study could be due to the community-based study design.

Another study conducted in northern India (rural) had reported a strong positive correlation of 0.88 (P < 0.001) between MUAC and BMI.^[21] The correlation remained high separately for men (r = 0.88) as well as women (r = 0.90). The slightly lower correlation in the present study could be due to the study setting, i.e., rural versus urban.

The cutoff for MUAC in correctly identifying underweight and overweight/obesity was <25.0 cm and ≥27.0 cm, respectively. For men, the cutoff for MUAC in detecting underweight and overweight/obesity was <25.5 cm and ≥27.0 cm, respectively. For women, the cutoff for MUAC in detecting underweight and overweight/obesity was <24.0 cm and ≥26.0 cm, respectively. The sensitivity and specificity in the present study were 68.8% and 84.9%, respectively, when the AUC was 0.84 (0.80–0.88). Selvaraj et al. conducted a study in a rural area of Puducherry among elderly persons and found that the MUAC cutoff for correctly identifying underweight was 24.0 cm. At this cut-off, they reported a sensitivity of 82% and specificity of 76% with an AUC of 0.88 (0.84–0.92).^[22] Another study from an urban slum in West Bengal found that the appropriate cutoff of MUAC was 22·7 cm. They found a sensitivity of 85.7%, and a specificity of 74.8%.^[23] A study by Chakraborty et al., conducted among the adult population in Jharkhand, found that the cutoff of MUAC in correctly identifying chronic energy deficiency/underweight was 24.0 cm.^[24] In their study, the sensitivity was 80.2%, and the specificity was 67.6%. Thus, the findings of the present study generally concur with those published earlier.

The strengths of this study were its community-based sample and good response rate. The limitation is that the MUAC cutoff determined for underweight and overweight/obesity was generalizable only to the elderly population residing in urban colonies. Further studies in different geographical locations are necessary to establish a standard cutoff for MUAC in assessing malnutrition among elderly persons in India.

Conclusion

The MUAC was positively correlated with BMI. The cutoff value of MUAC in identifying underweight was <25.0 cm, and overweight was ≥27.0 cm. This study corroborates that MUAC as a measurable parameter correlates well with BMI; its use may be considered as a complement or a substitute for BMI in community-based settings among elderly persons. The MUAC cutoffs may be used as an alternative for BMI, acknowledging its sensitivity and specificity depending on the context and its usefulness.

Financial support and sponsorship

Funded from Intramural Research Grant of All India Institute of Medical Sciences, New Delhi.

Conflicts of interest

There are no conflicts of interest.

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