Assessment of Nutritional Status of Community-Dwelling Older Adults in Rural North India using Mini Nutritional Assessment-Short Form : Medical Journal of Dr. D.Y. Patil University

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Assessment of Nutritional Status of Community-Dwelling Older Adults in Rural North India using Mini Nutritional Assessment-Short Form

Sahni, Bhavna; Mir, Lubna; Langeh, Sahil; Kalotra, Anuradha; Bala, Kiran

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Medical Journal of Dr. D.Y. Patil Vidyapeeth 16(2):p 213-219, Mar–Apr 2023. | DOI: 10.4103/mjdrdypu.mjdrdypu_114_21
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The challenges of geriatric populace are plentiful and vexing, malnutrition being a critical issue. We studied the burden of malnutrition and determined its association with socio-demographic factors, depression, and other health variables.


A cross-sectional study was conducted among 162 community-dwelling older adults to screen for malnutrition using mini nutritional assessment short-form (MNA-SF). Pearson’s Chi-square test, one-way analysis of variance, correlation, and Multinominal logistic regression were used for data analysis.


Four-point nine percent older adults were malnourished and 42.6% were at risk of malnutrition. Malnutrition was higher in 60–69 years of age group (5.95%) and females (6.9%), while risk of malnutrition was high among >80 years (59.1%) and widowed (66.7%). Weight loss, decrease in food intake, dementia, stress, decreased mobility, and depression were significantly associated with malnutrition. Geriatric Depression and MNA-SF scores showed a significant negative correlation (r = −0.434). Comparison of means of MNA-SF and geriatric depression scale scores among well-nourished, at risk, and malnourished subjects showed significant difference (P < 0.001). Multinominal regression revealed that it is highly likely (P < 0.01) that the subjects were malnourished if they had body mass index <19 kg/m2, reported weight loss >3 kg or suffered from acute disease or stress in the past 3 months while the likelihood of being “at risk” increased significantly only if subjects had acute disease or stress in preceding 3 months.


Screening with MNA-SF can help identify at low cost a sizable proportion of elderly who are malnourished and “at risk.” Timely intervention can be instrumental in preventing the progression of infirmity and reducing its catastrophic consequences.


Our planet is home to nearly 900 million people over the age of 60 years as the life expectancy globally has risen from 48 years in early 1950s to 68 years in the 21st century.[1] The challenges of geriatric age group are plentiful and vexing. However, with thoughtful planning and appropriate investment in the health and well-being of older population, we can envision communities where the older people are hale, hearty, productive, and economically secure.

According to the World Health Organization, it is estimated that there will be approximately 1.2 billion older adults people in 2025, and this figure will reach 2 billion by 2050, about 80% of them living in developing countries.[2] Geriatric population in India rose from 5.63% in 1961 to 6.58% in 1991 and to 7.5% in 2001 and is estimated to comprise 12% of total population in 2030.[3] As per Global Nutrition Report, currently 1 in 3 people are malnourished worldwide and 31%–46% of geriatric population are at risk for malnutrition, making it a growing public health challenge.[4] World Health Organization has named nutritional disorders as one of the most common causes of death in the older adults.[5] It defines Malnutrition, through an etiology-based approach and includes individuals who are both overweight or underweight.

Age on one hand makes one more vulnerable to malnutrition as both lean body mass and basal metabolic rate decline with age. Age also initiates a vicious cycle of degenerative diseases such as cardiovascular and cerebrovascular diseases, diabetes, osteoporosis, and cancer, which are among the most common diseases which are also diet-related. Keeping the incommodious circumstances of older adults in mind it is pertinent to do nutritional screening followed by a thorough and comprehensive clinical assessment of the nutritional status of the aged, but for a developing country like India, at community level, this time-consuming, expensive, and often least prioritized. Therefore, brief nutritional screening tools that provide an effective and inexpensive way to detect malnutrition are preferred. The mini nutrition assessment tool (MNA) is one such tool specifically developed for assessing the nutritional status of older persons.[6] It comprises 18 items presenting an anthropometric assessment, general assessment, dietary assessment, and subjective assessment, and the first six items have been used for screening people with undernutrition as the MNA-short form (SF).[7] This MNA-SF was revised in 2009 and proposed as a stand-alone nutritional screening tool by adapting three categories of nutritional classification: Well-nourished, at risk of malnutrition, and malnutrition.[8]

With this background, the present study was conceptualized to assess the burden of malnutrition among older adults and to determine the association of malnutrition with sociodemographic factors, depression, and other health variables included in MNA-SF.


The present study was cross-sectional in nature and was conducted in July–August 2018 after obtaining ethical clearance from institutional ethical committee vide communication no. IEC/GMC/CatC/2020/196. Line listing of all older adults in village Kirpind of block R S Pura in Jammu was done by village-level health workers. A total of 183 older persons, aged 60 years or more were identified by house-to-house visits. The present study was conducted in the same older adult population which was sampled for assessment of geriatric depression using geriatric depression scale-15 (GDS-15), the results of which have been published elsewhere.[9] Hence, the same sample size of 158 was used in the present study, using a prevalence of 11.6%, absolute precision of 5%, at 95% confidence limits, and a design effect of 1.[9] Individuals aged 60 years and above, who were permanent residents and living in the study area for at least 1 year, and those who gave consent to participate in the study were included. However, individuals from locked houses and those who could not be contacted even after two visits, individuals having aphasia, disorders of speech and hearing, hospitalized older adults, or those residing in old age homes, etc., were excluded. After applying inclusion and exclusion criteria, 162 out of 183 subjects were found eligible and all were screened, as there were no refusals.

Many advanced nations have accepted the chronological age of 65 years as a definition of “elderly.” As there is no standard criterion, the United nations’ cut-off of >60 years to refer to the older population was adopted in the present study.[10]

Verbal consent was taken from eligible individuals after explaining the purpose of the study. Individuals were guaranteed that the assessment report will be kept confidential. The screening for malnutrition was done by trained interns, undergraduate and postgraduate students under the supervision of faculty. The screening team underwent training in the department of community medicine. Malnutrition was assessed using the MNA-SF questionnaire, which is a self-reported, basic screening measure of malnutrition in the older adults. A valid Hindi as well as English language version of MNA-SF was made available and used where ever needed. For older persons who were uneducated, not interested or unable to fill the questionnaire due to any reason, the questions were read out, explained, and responses recorded. The questionnaire used in the study included information on sociodemographic variables including age, gender, religion, literacy, marital status and family type; and health variables such as decrease in food intake, weight loss, mobility, and body mass index (BMI). Malnutrition was assessed on a score of 15. Scores of 0–7 were considered severe malnutrition, 8–11 indicated mild malnutrition; and 12 or more implied normal nutrition. Any score ≤7 on the MNA-SF is an indication for an in-depth clinical evaluation and these subjects were referred to the nearest Primary Health Centre and Community Health Centre. These respondents along with those who were found to be at risk of malnutrition were counseled about a balanced diet, healthy dietary habits and encouraged to include locally available seasonal fruits, vegetables, whole grains, etc., in their regular diet by the faculty and the health care workers.

Statistical analysis

The data were analyzed using IBM SPSS Statistics for Windows, Version 23.0 (IBM Corp. Armonk, NY, USA). The Kolmogorov–Smirnov test was used to assess normal distribution of study variables. Categorical variables were presented as counts and percentages (%) and quantitative data were presented as mean (± standard deviation [SD]). Pearson’s Chi-square test was used for univariate analysis of categorical variables. One-way analysis of variance (ANOVA) was used to test significance between group means. Relationship between MNA-SF scores and GDS-15 scores was studied using Pearsons correlation. Multinominal logistic regression was used to find out which independent variables affect malnutrition. All the tests were performed at the significance level of 5%, i.e., an association was significant if the “P” value was < 0.05.


As shown in Table 1, 162 older adults, 72 females and 90 males, were screened for malnutrition. The mean age for the participants was 69.19 ± 7.43 years of age. More than half of the subjects were well-nourished, 42.6% were at risk of malnutrition and 4.9% were malnourished. More than half of the participants were Hindus (55%), followed by Sikhs (44%) and only one participant was a Muslim. Ninety-one percent of the participants were married, 78% of the participants lived in joint/three-generation families and almost two-thirds of the participants were literate.

Table 1:
Nutritional status of older adults according to demographic variables

Malnutrition was highest in the age group of 60–69 years, while among older adults >80 years of age almost 60% were at risk. The majority of males (61%) were found to be well-nourished but in case of females, at least half were at risk of malnutrition and a higher percentage were malnourished (7%) in comparison to their male counterparts (3%), the difference being statistically significant. Malnutrition was found to be in a similar range (5%) in all religions. Education did not show significant association, two-thirds of widowed/separated participants were at risk of malnutrition and 5% married participants were malnourished; while subjects living in joint/3G families showed marginally higher percentage of malnutrition.

As shown in Table 2 the response rate for each health-related variable in MNA-SF questionnaire was 100%. Two-thirds of subjects with weight loss >3 kg in the last 3 months were “at risk” while one-third were malnourished. Among subjects who reported moderate decrease in food intake during the last 3 months, 12.5% and 72% were malnourished and at risk of malnutrition respectively and the association was statistically significant. Half and two-thirds of the old adults with mild and severe dementia respectively were at risk of malnutrition while a much lower percentage of 7.8% and 9.09% of participants with mild and severe dementia respectively were actually malnourished. Seventy two percent of those with psychological stress were at risk while 13.7% were actually malnourished. Among the bed/chair bound/partially mobile, almost half were at the risk of malnutrition and one-fifth were malnourished. Among subjects with BMI <19 kg/m2, two-thirds were at risk and one-third were malnourished while a little less than half of the elders with calf circumference <31 cm were malnourished. All heath-related variables showed statistical significance with regard to nutritional status.

Table 2:
Nutritional status of older adults according to health/physical variables

Screening for geriatric depression was done using GDS-15 and it was observed as depicted in Table 3, that two-thirds of subjects with no depression (GDS score 0–4) were well nourished as opposed to more than half of elders with depression (GDS score 5–15) who were at risk of malnutrition, the association between depression and nutritional status being statistically significant.

Table 3:
Association of nutritional status of older adults with depression

Table 4 shows a negative and moderate correlation between the MNA-SF scores and GDS scores which is statistically significant.

Table 4:
Correlation between mini nutritional assessment short form score and geriatric depression score-15 score

When the mean (±SD) of the MNA-SF and GDS scores were compared between the three groups using one-way ANOVA as shown in Table 5, it was observed that the difference between means was statistically significant for both the scores. However, mean BMI and mean ages did not differ significantly among the three nutritional categories.

Table 5:
Differences between means of mini nutritional assessment short form scores, geriatric depression score scores, body mass index and age according to nutritional status

Parameter estimates of multinominal logistic regression as shown in Table 6, implied that it is highly likely that the subjects were malnourished rather than well-nourished if they had BMI <19 (P = 0.00009), reported weight loss >3 kg in the last 3 months (P = 0.00014) or suffered from acute disease or stress (P = 0.014) in the last 3 months. Furthermore, the likelihood of being at risk of malnutrition increased slightly if subjects had weight loss between 1 and 3 kg in the last 3 months (P = 0.048) and significantly if they suffered from acute disease or stress in the last 3 months (P = 0.0002) in comparison to well-nourished reference category.

Table 6:
Results of multinominal logistic regression


This study used MNA-SF tool to screen 162 older adults, 72 females and 90 males for malnutrition in Kirpind village of RS PURA block of Jammu in North India. The mean age for the participants was 69.19 ± 7.43 years of age. The majority of the screened participants were Hindus followed by Sikhs. A large proportion of the participants were literate, married, and lived in joint/three-generation families.

We found that 4.9% of the screened subjects were actually malnourished. Other studies of malnutrition prevalence among older people have found almost similar rates of malnutrition to the tune of 5.8% in community settings, 8.4% among nursing home residents in Turkey, 6.6% in a study by Kalan et al., 3.5% in Italy, and 12.5% in Sri Lanka,[11–15] while malnutrition prevalence was 24% in a study done in Nepal and 38.2% in Turkey.[16,17] Forty two point six percent elders in the present study were found to be “at risk” of malnutrition which is consistent with other studies which reported 37% and 31.6% in Turkey,[12,13] 46.2% in a multinational study,[11] 52.4% in Sri Lanka,[15] 49.2% in Manipur,[18] 60.4% in West Bengal, India.[19] These numbers indicate the dire need to cater to the nutrition of older adults for which early detection using screening tools such as MNA-SF and timely intervention plays a vital role. As has been seen in the current pandemic of COVID 19, it is the older adult population that bore the major brunt, owing to their poor nutritional status, psychological needs, low immunity, and associated co-morbidities which are spokes of the same wheel leading to poor outcomes for the geriatric population.

The current study showed that malnutrition (7%) and risk of malnutrition (52%) were significantly more in females, which is in agreement with studies done in Turkey in 2019, Italy in 2018, Manipur in 2018, Saudi Arabia in 2017, Rural Nepal in 2017, West Bengal India in 2015[12,14,16,18–20] Psychological mindset of females, family environment, amount of food intake, education, socioeconomic and many other cultural factors influence the nutrition of women. Hence, it becomes important to focus on women health in a holistic way, if we intend to improve the health of the society as a whole as female nutrition and education is the bed-rock of a healthy Nation.

In primary health care, BMI is one of the most commonly used crude screening tools. In our study, among older persons with BMI <19 kg/m2, two-thirds were at risk and one-third were malnourished which is in coherence with a study done in Sri Lanka while a little less than half of the elders with calf circumference <31 cm were malnourished.[15] Hundred out of 138 older adults whose height and weight were recorded had BMI more than 23 kg/m², putting them in over-weight or obese category which is similar to a study done in Turkey in 2019 where it was found that 35% of study population showed BMI more than 23 kg/m².[12] The malnutrition group and the other groups were significantly different with respect to mean GDS score in our study which is similar to findings of Gündüz et al. in Turkey.[21]

The likelihood of malnutrition was higher if subjects had BMI <19, reported weight loss >3 kg in the last 3 months, or suffered from acute disease or stress in the last 3 months which corroborates with another study done in nursing homes in Turkey.[12]

In the present study, we reported a significant association between depression and nutritional status which is in agreement with other studies done in rural Punjab and old age homes in Kolkata.[22,23] Geriatric Depression and MNA-SF scores showed a significant negative correlation (r = −0.434) which is in corroboration with other studies in Kolkata and Delhi which reported Spearman’s rho of − 0.436 (P < 0.05) and 0.608 (P < 0.01) respectively.[23,24] Our observations support the scientific evidence that depression and malnutrition have common risk factors such as lonesomeness, lack of social and financial security, physical and functional impairment. Therefore, it is imperative that clinicians should take into account the social epidemiology and pay heed to both psychological and physical domains during managing older adults with depression and/or malnutrition.


To the best of our knowledge, this is the only study which has investigated the nutritional status and psychological well-being of community-dwelling older adults in Jammu region. In addition, no such screening tool has ever been validated in our area of research. MNA-SF which is easy to use by undergraduates, postgraduates, and even field health workers or people with no clinical background. Also because of the limited laboratory facilities available in rural areas like Kirpind, MNA-SF is a good way to access the nutritional status as there is no need for biochemical testing in this method.


The assessment of malnutrition was based on self-reported data may be subject to recall bias. The MNA-SF tool used in the present study is intended only for screening and is not a replacement of clinical diagnosis. The study being cross-sectional in nature does not establish causation, it only observes associations. The sample size could have been increased by including adjacent villages but we had a short time available for participant recruitment and data collection. A lack of religious diversity and small sample size affects generalizability. There could be potential confounders among the studied variables and the results may not be relevant to urban India, as sociocultural nutritional factors vary widely in urban and rural areas.


In tune with similar studies done in various setups, our study also revealed that MNA-SF can be successfully used, especially in less developed parts of the world like our rural field practice area to screen the geriatric population for nutrition-related issues and aid timely prevention and treatment of malnutrition, thereby preventing major loss of life and finances. Effective measures for dietary education and redressal of gender-related discrimination and dietary issues and care for our older adults is the need of hour. This study has provided preliminary data on the prevalence of malnutrition and its association with socio-demographic factors, depression, and other health variables of interest.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.


The authors would like to acknowledge the contribution of second professional MBBS students, postgraduates, and interns who were involved in the process of data collection.


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Depression; Geriatric assessment; Geriatrics; Malnutrition; Nutrition assessment

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