|Year : 2018 | Volume
| Issue : 2 | Page : 150-154
Assessment of nutritional status, psychological depression, and functional ability of elderly population in South India
Vamsi Krishna Boyanagari1, Paramjot Panda1, Manaswitha Boyanagari1, Suchismita Panda2
1 Department of Public Health, Manipal University, Manipal, Karnataka, India
2 Department of Clinical Psychology, Government College, Bhawanipatna, Odisha, India
|Date of Web Publication||31-Dec-2018|
Mr. Paramjot Panda
Department of Public Health, Manipal University, Manipal, Karnataka
Source of Support: None, Conflict of Interest: None
Background: Nutrition and depression among elderly have emerged as a major public-health problem, and depression is one of the leading causes of disease burden worldwide. The evidence shows that more than 50% of the elderly population is underweight and more than 90% has an energy intake below the recommended intake.
Objective: The objective of this study is to determine the prevalence and correlates of malnutrition and the relationship with disability and psychological well-being, and to assess the pattern of morbidity, co-morbidity, among the elderly in Udupi taluk of Karnataka.
Methodology: This cross-sectional study conducted during January–June 2017 included 570 participants of ≥60 years of age. The data were analyzed for percentages, mean, and standard deviation. The tests of significance such as analysis of variance and Independent t-test were used; P < 0.05 was considered statistically significant.
Results: It was observed during the study that the majority belonged to the young old age group (63.2%), were financially dependent (55.8%) and most of them are from rural (61. 1%). The prevalence of malnutrition based on the malnutrition indicator score was found to be (11.22%) and (44.73%) are at risk of malnutrition. The mid-upper arm circumference and calf circumference measurements were (8.24%) and (11. 75%), respectively. The prevalence of depression in the elderly was found to be 6.6%.
Conclusion: The care of the elderly should also include the nutrition and mental healthcare components for better addressal of the health needs of elderly which requires to be brought on the national health care agenda.
Keywords: Depression, elderly, morbidity, nutrition
|How to cite this article:|
Boyanagari VK, Panda P, Boyanagari M, Panda S. Assessment of nutritional status, psychological depression, and functional ability of elderly population in South India. Arch Ment Health 2018;19:150-4
|How to cite this URL:|
Boyanagari VK, Panda P, Boyanagari M, Panda S. Assessment of nutritional status, psychological depression, and functional ability of elderly population in South India. Arch Ment Health [serial online] 2018 [cited 2020 Feb 26];19:150-4. Available from: http://www.amhonline.org/text.asp?2018/19/2/150/248876
| Introduction|| |
The World Health Organization (WHO) has projected that populations aged 60 and above will present new challenges to healthcare. The health of the elderly will play an important role in defining the health status of a population. As the number of elderly increases, so too will their health needs. Multimorbidity associated with increasing age is common and is found to be more frequent in resource-poor countries. In India, the elderly (aged 60 and above) constitute 8.2% of the total population of 1.2 billion and this number is increasing. The majority of the elderly population lives in rural India and the National Health Policy 2017 focusing on maternal health, child health and communicable diseases, the health status of the elderly have not been given due consideration. Since nutrition of the elderly affects immunity and functional ability, it is a vital component of elderly care that warrants further consideration. The magnitude of undernourishment among the elderly in India is underreported. The studies show that >50% of the elderly population is underweight and more than 90% has an energy intake below the recommended intake. However, few studies were carried out in India using screening tools to assess malnutrition. The use of malnutrition screening tools for community-dwelling elderly has helped to accurately identify those with low nutritional status. There is no gold standard for estimating undernourishment among the elderly. Body mass index (BMI; weight [kg]/height [m2]) predicts disease risk both in those termed underweight and in those who are obese. The international classification of BMI for adults given by WHO categorizes BMI <18.5 as underweight, 18.5–24.9 as normal weight, 25–29.9 as overweight, 30–34.99 as Class I obesity, 35–39.9 as Class II obesity, and Class III obesity >40. Nevertheless, BMI may be unreliable in the presence of confounding factors such as edema or ascites and may not identify significant unintentional weight loss if used as a single assessment.,, Furthermore, reliable measurement of height can be difficult in the elderly because of vertebral compression, loss of muscle tone, and postural changes., Mini nutrition assessment is a widely used international questionnaire to evaluate the nutritional state of elderly with high sensitivity (98.9%), specificity (94.3%), and diagnostic accuracy (97.2%). It closely correlates with biochemical (albumin, prealbumin, transferrin levels, and lymphocyte numbers) and anthropometrical markers (measuring of subcuticular fat and arms circumference) that were verified by a number of clinical studies on wide sets of geriatric patients., At this point, there is a need to evaluate the morbidity profile of elderly, and the impact of morbidities on functional disability and psychological well-being for better understanding of the relation between perceived health and chronic and disabling conditions of elderly. Nutritional status, functional ability, and psychological status among the elderly, especially from poorer sections of the developing countries, has to be assessed to determine the relationship of comorbid conditions with disability and psychological well-being of the elderly.
Therefore, the aims of the study are as follows: (1) to determine the prevalence and correlates of malnutrition and the relationship with disability and psychological well-being (2) To assess the pattern of morbidity, comorbidity, among the elderly population over 60-years-old in Udupi taluk of Karnataka.
| Methodology|| |
Study design, settings, and eligibility criteria for selecting participants
A community-based cross-sectional study was conducted among urban and rural adult dwellers of Udupi Taluk in Udupi district of Karnataka, India. Participants who are aged 60 and above were included from January 2017 to June 2017.
The sample size was calculated using the formula n = z2 pq/d2, where n is the sample size, pis the prevalence of malnutrition, q is 1-p, and d is the absolute precision. A total of 570 elderly person participated in the study.
The following tools were used: Mini Nutritional Assessment Questionnaire, Katz Index of Independence in Activities of daily living, and geriatric depression scale (GDS).
Sampling technique and data collection methods
Study was conducted from January 2017 to June 2017. A list of all the 86 villages and 36 wards under the Udupi Taluk was obtained from Census India 2011. The number of elderly to be interviewed and examined in each village was calculated using population proportional to size. Systematic random sampling method was used to select the houses by calculating sampling interval for each village, starting from the center, a direction was chosen randomly. In the event of a household having more than one elderly, only one elderly was chosen randomly irrespective of gender. In the event of a house being locked, an elderly from the adjacent house was interviewed. A written informed consent was obtained from the participant before the interview, after explaining about the study, in a language understood by the participant. Data were collected using initial interview schedule for socio-demographic details, history of comorbidities, and habits. The nutritional status was assessed using the Mini nutritional assessment questionnaire. The anthropometric measurements i.e., height, weight, calf circumference, and mid-upper arm circumference (MUAC) were taken. The activities of daily living were assessed using the Katz index of activities of daily living. A psychiatric assessment to look for the prevalence of depression in the elderly was carried out using the GDS.
The data were entered and analyzed using Statistical Package for Social Sciences (SPSS) Version 16.0 (IBM, Chicago, SPSS Inc.). The data were analyzed for percentages, mean, and standard deviation. The tests of significance such as analysis of variance and independent t-test were used where ever applicable. P < 0.05 was considered statistically significant.
| Results|| |
A total of 570 elderly persons were interviewed and assessed. The study group comprised of (38%) females and (62%) males with a age range between 60 and 100 years [Table 1].
The prevalence of overweight (61.76%) was found to be more than underweight (18.77%). Based on the malnutrition indicator score (MIS), (11.22%) of the elderly were found to be malnourished with (44.73%) at risk of malnutrition. The MUAC and calf circumference measurements indicated (8.24%) and (11.75%) to be undernourished, respectively, depicted in [Table 2].
The functional ability [Table 3] in the elderly was assessed using the Katz index of activities of daily living, and GDS, according to Katz index, 98% of the elderly were found to be dependent for activities of daily living. The prevalence of depression in the elderly was found to be 6.6%.
The results of the functional ability assessment in the study population are depicted in [Table 3].
The nutritional status in the elderly was found to be significantly influenced by age [Table 3]. There was a significant difference in BMI for young old and oldest old (P = 0.001) The MUAC and the calf circumference also significantly vary with age. The prevalence of chronic comorbidities such as diabetes and hypertension was also found to have an impact on the nutritional status. It was noted that the calf circumference and MUAC measurements are good anthropometric measurements to detect undernourishment in the elderly based on the strong significant associations with nutritional indicators such as BMI and MIS. The study also tried to correlate nutritional status with the functional ability and it was interesting to note that there is no significant association between the Katz activities of daily living index and BMI (P = 0.44). In case of MIS, there was a significant difference in MIS and Katz activities of daily living index (P = 0.001). In addition, depression gauged by the GDS (P = 0.02) found to be significantly contributing toward the nutritional status in the elderly.
| Discussion|| |
The previous studies done by Vedantam et al. (2010) in South India found the prevalence of malnutrition among elderly to be nearly 33%. Physical frailty is defined as dependence in at least one activity of daily living (ADL) or cognitive deterioration or decreased outside mobility. The prevalence of frailty is 98% in person with age 65 and more than 33% of those over 85, needs assistance with at least one basic ADL. Moreover, balance and gait disorders affect 10%–15% of elderly patients who thus suffer an increased risk of falling. The lack of functional autonomy to look after oneself and to prepare and eat food is a factor that can result in malnutrition and deserves the attention of professionals and family since functional capacity assessment can be an indicator of nutritional risk which is particularly associated with food intake. Depression is also a common disorder among elderly which is highly underestimated by health professionals. It is one of the profound factors which influence functional ability in the geriatric population. In a similar cross-sectional study done by Agarwalla et al., among 360 elderly in Boko-Bongaon Block, Assam, India, 15% were found to be malnourished and 55% were at risk of malnutrition. The association between nutritional status and older age group, female gender, dependent functional status, dependent financial status, and inadequate calorie intake was found to be significant as in this study. The functional status of the elderly determines their ability to perform basic self-care tasks and live independently, which also includes food intake. The association between functional and nutritional status was found to be significant in our study which was similar with Shahar et al., Oliveira et al. and Olayiwola and Ketiku et al.,, There was a significant association between calorie intake and nutritional status in our study similar observations were also revealed by Vedantam et al. in their study in South India; the most common reasons cited for inadequate calorie intake were difficulty in chewing and swallowing (59.5%), and loss of appetite (54.2%). The inability of elderly to take decisions about food intake (47.8%), lack of funds (48.4%) lack of awareness (38.4%) was other reasons cited. Physical and financial dependency thus definitely influenced nutritional status. In a similar cross-sectional study conducted by Ohri et al. in Dehradun among elderly, it was seen that were independent in their ADLs, with more dependence in the very old elderly with maximum inability in bathing and dressing female elderly being more dependent than male (P < 0.05). Education and socioeconomic status had a positive effect on independence in instrument ADL.
| Conclusion|| |
This study showed that there is a high prevalence of poor nutritional status (11.22%) and psychological depression (6.66%) among the study population. With increasing longevity and proportion of the elderly population in India, and the trend toward urbanization and emergence of nuclear families, dependency leading to depression among the elderly is likely to become a disease challenging “public health problem” status in the near future. The care of the elderly should also include the nutrition and mental healthcare components for better addressal of the health needs of elderly which requires to be brought on the national health care agenda.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]