Kulvir Singh1,2, Swinderpal Singh1, Ginjinder Kaur1, Kaushik Bose3
1. Department of Human Genetics, Punjabi University, Patiala- 147002, Punjab, India.
2. Department of Physiology, Desh Bhagat Dental College and Hospital, Desh Bhagat University,
Mandi Gobindgarh- 147303,Punjab, India.
3. Department of Anthropology, Vidyasagar University, Midnapore – 721102, West Bengal, India.
Corresponding to: Kaushik Bose, Department of Anthropology, Vidyasagar University, Midnapore – 721 102, West Bengal,India, e-mail: email@example.com
Care Weekly 2019;
Published online September 1 6, 2019, http://dx.doi.org/10.14283/cw.2019.5
Objective: To use mid upper arm circumference (MUAC) as a proxy measure of undernutrition in elderly males of Punjab, India.
Design and measurements: Male participants in old age homes (n=215) and community based (n=239) were measured for standing height, weight and mid upper arm circumference (MUAC) during … from different areas of Punjab. Chronic energy deficiency (CED) was determined using the WHO international guidelines as BMI<18.5 kg/m2 and normal as BMI≥18.5 kg/m2. Descriptive statistics and percentiles were calculated and multiple linear regression analysis was undertaken to assess the associations between age, MUAC and BMI. Receiver-operating characteristic curve (ROC) analysis was performed to determine the best MUAC cut-off values to identify CED status. The χ2 test was used to assess significance of the difference in CED prevalence across MUAC categories.
Setting: Old age homes and selected community based elderly of Punjab State, India.
Participants: Elderly males in old age homes (n=215) and community based (n=239) were chosen after obtaining the informed consent. Results: MUAC cut-off value of 22.9 cm among the elderly in old age home and 23.4 cm among the community based elderly were the best cut-off points to differentiate between CED and non-CED individuals.
Conclusions: The present study proposes the MUAC of 23.5 cm to differentiate between CED and non-CED male elderly individuals. There is a greater need to establish statistically appropriate MUAC cutoff values to predict undernutrition and morbidity in elderly across different ethnic groups.
Keywords: Mid upper arm circumference, body mass index, chronic energy deficiency, elderly, old age home.
The proportion of the elderly section is rising in India (1, 2) who are more prone to poor health conditions. Undernutrition is one of the major conditions in elderly, associated with the increased risk of mortality, morbidity, frailty, declining in physical functions and mental health problems (3-8). The opposite could also be true, that physical and mental health illness leads to loss of appetite and undernutrition (9). The intake of energy equals the output of energy in living organisms in stable body weight situations (10).There seems to be an extremely efficient regulatory system that helps maintaining the stability of the amount of fat in the body (stored energy) and is usually termed as ‘energy homeostasis’ (10). Insulin and leptin are two major hormones, which help in regulating the fat storage in body (11-13). Optimal nutrition is essential for good physical and mental health. However, the consumption of food varies from individual to individual. Overnutrition results in greater fat storage and manifested as increased weight and size of the body. On the other hand, undernutrition causes the loss of fat storage, which results in thinness among the adults and, stunting and wasting among the children. In elderly, undernutrition is of greater concern, as it has greater association with morbidity and mortality as compared to obesity(14-16).
The use of anthropometry to assess the body size and composition is well established. Anthropometric measurements are the reliable indicators of nutrition and health status of the individual(17). The WHO recommended the use of BMI (≤18.5 kg/m2) calculated from height and weight as an indicator of under nutrition and adiposity at all ages(17,18). Among the elderly individuals BMI predicted under nutrition is associated with quality of life, mortality, cognitive and self rated health(19-20). Incidence of spinal deformities(21),physical dysfunction and frailty(22) was higher in the elderly individuals as compared to the younger peer. Given these practical issues, recording height and weight measurements on elderly individuals is not always possible. Hence, the use of BMI for screening under nutrition among elderly is limited(23). There is a greater possibility that those older individuals, which could not be measured properly, would be left out or are incorrectly measured(24-26).
The MUAC is another simpler anthropometric measurement that can be used as an indicator of nutritionand health status among the adults and elderly individuals(15,27,28).It is highly associated with morbidity and mortality among the elderly residing in old age care facilities(26,29,30) as well as among community dwelling elderly population (31-33).Use of MUAC as an indicator of nutritional status among adolescents and adults is well documented (34) and is also used in establishing an optimal MUAC cut-off (35). To conduct MUAC measurement, the circumference of the upper arm at the mid point of the tip of olecranon and the tip of acromion processes is measured using a standardized tape. The MUAC measurement can be easily obtained on the individuals who cannot sit or stand properly. Bed ridden and older participants not able to stand erect for height measurements can’t be studied for BMI but can conveniently be measured for MUAC to assess the nutritional status. The correlation between BMI and MUAC has been well established by different studies conducted among different ethnic groups (27, 36, 37).
Regular screening of undernutriton among elderly is desirable to reverse the effect of undernutrition and consequent weight loss among older individuals (38-40). To offset the negative energy balance caused by lower intake of energy in the past by an increased intake of energy later on seems unlikely among elderly (41). Due to sarcopenia in older ages, after the weight loss it is difficult to regain proportional skeletal muscle mass during weight gain (42-44). Among the older individuals, decline in physical mobility and cognitive skills (45) make them dependent on others (family members or health care providers) for their health care. Therefore, we need a tool that is inexpensive, quick, has least instrumentation, require least technical skills and can be applied in field setting. The family members can use such a tool with ease and health care providers in old age care facilities can apply such tool quickly, on large number of individuals.
The present study attempts to use mid upper arm circumference (MUAC) as a proxy measure of undernutrition in elderly males of Punjab, India.
Method and materials
Participants and setting
In the present cross-sectional study, Anthropometric data of 454 male participants aged 60 years and above (215 old age home based and 239community based) were collected cross-sectionally from six districts of Punjab, India, includingAmritsar, Barnala, Ferozpur, Jalandhar, Patiala and Sangrur during year 2012 to 2014. The management and caretaking authorities of the old age homes visited were informed about the objective of the research and written informed consent was obtained from them and from each subject. In total 21 old age homes were visited during sample collection. All the old age homes were maintained by non-governmental organizations or single private individuals. The elderly who were able to stand erect for height measurements and not suffering from any visible disability were included in the study. No statistical sampling technique could be applied given the limited number of elderly in old age homes and also by obtaining the informed consent(46). All the elderly residing in old age homes from at least 5 years were included in the study. As the old age homes draw their inmates from their adjoining areas, therefore the samples for community based elderly were obtained by visiting home to home, from adjoining areas to the old age homes to maintain homogeneity between both the study groups. Each subject along with family members were informed about the objective of the study and written informed consent was obtained from them. Ethical clearance had been obtained from Institution Clinical Ethical Committee, Punjabi University, Patiala, Punjab, India (Letter number: 427/DIS; Dated: 27/11/2012; ICED clearance number: ICEC 57).
Socio economic status
The information regarding the education level, personal source of income, marital status and number of children was obtained for both the groups of elderly to elucidate social and economic conditions. For the community based elderly, the information about whether they were living with son/sons, daughter or only with their spouse was recorded. The duration of the total stay in old age home was recorded (in years) for the old age home based elderly participants. Educational level was recorded as the standard of class for which examination is passed by the individual. The following educational categories were made: uneducated (not able to read and write, including below the third standard), up to matric (from the third up to the tenth standard), and higher education(eleventh standard and above).The income from personal sources included incomes received directly by the elderly, but not from any of their family members and children. The pensions obtained from government’s old age pension schemes being very paltry was not considered as an income source. The marital status was categorized as: married, unmarried (never married) and widowed or separated (lost their spouse by death or divorce). The information about number of living children was stratified into three categories: none (no child), up to three children and more than three children.
Anthropometry and nutritional status
The anthropometric measurements were obtained following the standard methodology(47).Height was recordedup to the nearest millimeter. Only those participants who were able to stand erect were included in the study. Participants were asked to stretch as much as possible. The head was held so that Frankfort plane becomes horizontal. Height and MUAC were recorded to the nearest millimeter and weight to the nearest 100 g. BMI was computed as weight in kilograms divided by the square of height in meters. Nutritional status was determined using the WHO international guidelines (WHO, 1995) (17) as: CED (BMI < 18.5kg/m2), normal (BMI = 18.5–24.9 kg/m2), overweight(BMI = 25.0–29.9 kg/m2) and obese (BMI ≥ 30.0 kg/m2); as well as with the Asia Pacific guidelines (WHO, 200018) as: CED(BMI < 18.5 kg/m2), normal (BMI = 18.5–22.9 kg/m2),overweight (BMI = 23.0–24.9 kg/m2) and obese (BMI ≥25.0 kg/m2).
Descriptive statistics of mean, SD and 25th, 50th and 75thpercentile values were calculated to describe the characteristics of the sample. Association between age, MUAC and BMI was analyzed by multiple linear regression analysis. Receiver-operating characteristic (ROC) curve analysis was performed to determine the optimal MUAC cut-off point to differentiate between CED (BMI< 18.5)and non-CED (BMI≥ 18.5). Sensitivity (SENS), specificity (SPEC), positive predictive value (PPV) and negative predictive value (NPV) were computed to identify these cut-off points in both the groups of elderly males elderly, respectively. Among old age home based and community-based elderly, three groups for each were created based on the ROC curve results: MUAC < 23.0 cm, MUAC= 23.0–24.9 cm andMUAC ≥ 25.0 cm for old age home based elderly; and MUAC<23.5 cm, MUAC = 23.5–25.49 cm and MUAC≥ 25.50 cm for community based elderly. Contingency χ2 tests were used to study the relationships between these MUAC groups and CED categories. All statistical analyses were performed using the SPSS version16 and MedCalc statistical software packages.
Table 1 shows the distribution of male elderly in both the study groups according to socio-economic variables. Among the community based elderly, 89.5 % of the elderly were residing with their sons, 10.0 % were residing only with spouse and only 0.4 % were residing with their daughters. Literacy rate was 45.5 percent in old age home based elderly and 29.2% in community based elderly. Among both the study groups, 7.9 % elderly had secondary or higher education status, while elderly educated up to metric standard were 37.6% and 21.3 % among old age home and community based elderly, respectively. Regarding marital status, 90.2% of the old age home based and 94.9 % of the community-based elderly were married. Of the married elderly 22.3 % of the old age home based and 10.0 % of the community based elderly lost their spouse by death or divorce. The elderly that had personal source of earning were 12.5 and 59.8 percent in old age home based and community-based elderly, respectively. For the old age home based elderly, the average duration of the stay in the old age home was 8.83 years (SD=1.75), with 72.5 % of the elderly staying in old age home from last 5 to 10 years and 27.4 % staying in old age home from more than last 10 years.
Descriptive statistics including mean, standard deviation, minimum, maximum, and 25th, 50th and 75th percentile are presented in Table 2.BMI and MUAC were highly correlated among old age home based (r=0.70) and community based elderly (r=0.68) (Figure 1). Among the elderly residing in old age homes, weight (F=9.19, p<0.001), BMI (F=6.16,p=0.003) and MUAC (F=24.509,p<0.001) decreased significantly with advancing age from 60 to greater than 80 years, while among community based elderly changes were non-significant. The mean weight (t=11.13,p<0.001), BMI (t=11.48,p<0.001) and MUAC (t=8.20,p<0.001) were significantly higher among the elderly living in home as compared to community based elderly.
*significantly higher among the community based elderly as compared to those living in old age homes; †Decreased significantly with advancing age from 60 to >80 years.
Table 3 presents the distribution of old age home based and community based elderly according to BMI with respect to WHO Asia Pacific guidelines and WHO international guidelines. According to the WHO’s Asia Pacific (χ2=89.14,p<0.001) and international guidelines (χ2=70.22,p<0.001) of BMI classification, there was significant difference in distribution between the old age home based and community based elderly. The percentage of the elderly in CED (BMI<18.5 kg/m2) category was 28.5 % in old age home based elderly and 10.5 % in community based elderly. According to WHO Asia Pacific guidelines for BMI classification, percentage of overweight and obese elderly was 8% among old age home based elderly and 48.5 % among community based elderly. On the other hand, according to WHO international guidelines for BMI classification, percentage of overweight and obese elderly was 1.5% among old age home based elderly and 29.5 % among community based elderly.
Analysis of receiver operating curve of MUAC vs. CED status (CED= BMI <18.5 kg/m2 and non-CED= BMI≥ 18.5 kg/m2) among old age home based elderly and community based elderly is presented in Table 4.For the ROC among old age home based elderly, the area under curve was 0.83 (SE 0.03, 95% CI 0.77-0.87). The Youden Index (YI)was estimated to be 0.54. The MUAC of 22.9 cm was observed to be the optimal cut-off value to differentiate between CED and non-CED elderly. The sensitivity, specificity, positive predictive value and negative predictive value were 76.22%, 75.44%, 88.6 %and 55.8 %, respectively. The ROC for old age home based elderly is presented in Figure2. For the ROC among community based elderly, the area under curve was 0.85 (SE 0.04, 95% CI 0.79-0.90). The YI was estimated to be 0.67. The MUAC of 23.4 cm was observed to be the optimal cut-off value to differentiate between CED and non-CED elderly. The sensitivity, specificity, positive predictive value and negative predictive value were 86.03%, 80.95%, 97.5 and 40.5 percent, respectively. The ROC for community-based elderly is presented in Figure 3.
(bleu) plot of sensitivity v. (1 – specificity; (red) line of no discrimination.
The prevalence of CED (chronic energy deficiency) and mean BMI according to MUAC category are shown in Table 5. Among both the groups of elderly, lowest MUAC category (MUAC ≤23 cm in old age home based and ≤23.50 cm in community based elderly had highest prevalence of CED (old age home based CED 51.2%; community based CED 37.8%). The old age home based elderly with MUAC ≤23 cm had 57.51 times higher odds of CED as compared to those with MUAC ≥25 cm. In the case of community based elderly, those with MUAC ≤23.5 cm had 40.14 times higher odds of CED as compared to those with MUAC ≥25.5 cm. The prevalence of CED decreased significantly with increasing MUAC category (old age home based χ2= 39.93, p<0.001; community based χ2= 48.91, p<0.001) and the mean BMI increased significantly with increasing MUAC category (old age home based F=31.27, p<0.001; community based F= 46.28, p<0.001) among both the groups of male elderly.
*Adjusted for age; †Mean BMI increased (F=31.27, p<0.001) and prevalence of chronic energy deficiency decreased(chi square = 39.93, p<0.001) with increasing MUAC category.
‡ Mean BMI increased (F=48.91, p<0.001) and prevalence of chronic energy deficiency decreased (chi square = 46.28, p<0.001) with increasing MUAC category
(bleu) plot of sensitivity v. (1 – specificity; (red) line of no discrimination.
Government of India envisaged a new program intended to build new architecture for elderly care (48-50), however, at present the incidence of the public provision for the old age care is very dismal, (such as nursing homes and health insurances) (51).There is lack of organizational structure to take care of elderly in India. Some local bodies, regional institutes, national and international NGOs are maintaining old age homes in the country. Older adults in the developing countries are at higher risk of undernutrition (27, 52). In such resource limited setting with lack of professional and trained staff, MUAC may prove a better tool to assess under nutrition.The use of BMI to identify the under nutrition is well documented. However, due to the practical limitation, BMI may not be the suitable measurement for this purpose among elderly (23, 53). Recent studies conducted in older adults have recommended the use of MUAC for nutritional and health status screening (28, 54). The MUAC is well correlated with BMI to identify undernutrition among adult population(46,55-61). However, there is paucity of studies showing association between BMI and MUAC among elderly population.
In the present study, BMI was highly correlatedwith MUAC among both the groups of elderly. Findings of the present study suggested that MUAC serves as the predictor of low BMI (< 18.5 kg/m2) for screening CED elderly. Among the old age home based elderly, MUAC of <22.9 cm was observed to be the most optimal cut-off for differentiating between CED and non-CED elderly. Similarly, among the community based elderly, MUAC of <23.4 cm was observed to be the most optimal cut-off for differentiating between CED and non-CED elderly. The same cut-off was suggested by Tsai et al., (62), whoobserved that among community dwelling elderly males of Taiwan, the MUAC of <23.5 was significantly associated with the MNA (Mini Nutrition Assessment) predicted proportion of elderly at malnutrition risk. A major study conducted among adult population of five African countries, India, China and Papua New Guinea suggested MUAC of 23 cm as cut-off for screening nutritional status (63). Various studies conducted among the different ethnic (tribal) groups from India used MUAC of <23 cm as cut-off to define undernourishment among adult male (including elderly) population (57, 64).
On the other hand, Goswami et al. (53) proposed the MUAC of <25.7 cm for community based elderly men of urban region of Delhi, India. However, instead of using height to calculate BMI, they had used arm span.Chakraborty et al. (58) and Chakraborty et al. (61) proposed the MUAC of <24 cm as an optimal cut-off point for screening clinical undernourishment among themale slum dwellers of Kolkata and Oraon males of Jharkhand, India. Among Bangladeshi adults the MUAC of <25.1 cm was suggested as the optimal cut-off to detect undernutrition (65). Studies among elderly of rural Puducherry, India(53) and Haryana, India (27), concluded that MUAC (AUC=0.88, r=0.74and AUC= 0.93, r=0.88, respectively) can be used as the proxy measure to predict CED (BMI<18.5 kg/m2). However, they did not suggest MUAC cut-off value to differentiate between CED and non-CED elderly. The fact that height declines with ageing is well established (66-68). The age related loss in height was higher among institutionalized elderly as compared to community based elderly (69). The height loss with normal ageing may contribute to the increased relative weight (BMI), without similar change in upper arm composition. Therefore, in the case of elderly, a higher MUAC cut-off value than observed can be considered, particularly for old age home based elderly.In the view of these findings, it is proposed that the MUAC of 23.5 cm could be utilized as cut-off value to differentiate between CED and non-CED elderly individuals. Our study observed higher odds ratio for MUAC predicted under nutrition among old age home based elderly (OR=58.82) as compared to community based elderly (OR=40.14). Gibson (2005) (70)suggested that among individuals with lower subcutaneous fat, the MUAC predicts the body composition with greater accuracy. It has greater inverse association with all-cause mortality in non-obese individuals (71). As the older adults residing in old age homes had lower subcutaneous fat, the MUAC predicted under nutrition could be particularly more reliable among old age homes based elderly.
MUAC is a simple measure as compared to BMI. According to WHO guidelines, for children aged 6–59 months, severe acute malnutrition is defined as mid upper arm circumference <115 mm (72).These recommendations are also included in WHO program of Integrated Management of Childhood Illness (IMCI): caring for newborns and children in the community (72). However, no such recommendations to implement MUAC cut-off value for monitoring adults are included in guidelines of Integrated Management of Adolescent and Adult Illness (IMAI), which also include elderly individuals (73).This may be ascribed to non-availability of an appropriate universal MUAC cut-off for adults, and a complete dearth of data and evidence for elderly. For elderly individuals, MUAC could achieve higher rate of inclusion with greater sensitivity to identify appropriate beneficiaries having an increased health risk due to acute under nutrition. In a resource-constrained situation of developing countries, it could also facilitate the proper utilization of limited financial resources. The elderly found under nourished by MUAC can be considered for more comprehensive nutrition assessment (by an accredited practicing dietician) to identify those with complex nutritional needs (74). The automation in measurement of MUAC, to reduce manual errors could be achieved bystandardisation of photogrammetric anthropometry softwares (75).
The present study proposed that among community and old age home based elderly the MUAC cut-off value of 23.5 cm could be used to differentiate between CED (BMI value of <18·5 kg/m2)and non-CED individuals. Given the fact that height decline with ageing contributes to the increase in relative weight (BMI), without similar change in upper arm composition. A higher MUAC cut-off than observed can be considered, particularly for old age home based elderly. However, to conduct studies focusing on this particular problem is imperative. For elderly individuals, MUAC could achieve higher rate of inclusion with greater sensitivity to identify appropriate beneficiaries having an increased health risk due to acute under nutrition. In a resource-constrained situation of developing countries, it could also facilitate the proper utilization of limited financial resources.
The experiments performed in this research comply with the current laws in India.
Conflicts of Interest
Authors have no conflict of interest.
The ethical clearance had been obtained from Institution Clinical Ethical Committee, Punjabi University, Patiala, Punjab, India (Letter number: 427/DIS; Dated: 27/11/2012; ICED clearance number: ICEC 57).
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