A Community Based Cross-Sectional Study on Morbidity Profile and Nutritional Status of Elderly in a Rural Taluk of Karnataka

The proportion of elderly individuals in the population is increasing worldwide, making population ageing an important demographic trend, especially in developing countries like India. Globally, the life expectancy at birth had reached 73.3 years in 2024 and the proportion of elderly aged 60 and above, is projected to increase from 1.1 in 2023 to 1.4 billion by 2030.[1] In India, the elderly population constitutes 8.1% of the total population.[2] This steady rise in elderly population has been attributed to advances in social and economic development, improvements in health care and better control of infectious diseases.[1]

 Ageing is associated with physiological, psychological and social changes that increase vulnerability to various health problems.[3,4] The elderly population are susceptible to many chronic diseases like hypertension, diabetes mellitus, stroke, musculoskeletal disorders, visual impairment and respiratory illnesses.[5-7] These morbidities are known to significantly influence their functional ability, quality of life and independence.[8] This disease burden in the elderly is often compounded by limited access to health care services, poverty, social isolation, and inadequate care giving especially in rural areas where health care infrastructure may be limited.[9-11]

 Another critical determinant of health in the elderly population is their nutritional status.[12,13] Reduced appetite, impaired digestion, chronic illnesses, medication use and socioeconomic constraints can adversely affect dietary intake and nutritional status.[14-17] Because of malnutrition, these elderly may become susceptible to infections, delayed recovery from illnesses, functional decline and higher mortality.[18] Studies conducted in different parts of India have reported the prevalence of malnutrition among the elderly to vary between 7 and 19% when assessed using MNA tool.[2] A metanalysis of studies in India report that the prevalence of malnutrion among the elderly was 18.29% and almost 48.17% were at the risk of malnutrition.[19] Similarly, a community based cross sectional study conducted in Puducherry estimated the prevalence of malnutrition among the elderly to be 17.9% and another 58.8% were estimated to be at risk of malnutrition.[20]

 The coexistence of morbidity and malnutrition among the elderly is a significant public health problem as they form a vicious cycle. Chronic diseases can worsen the nutritional status by increasing the metabolic demands and decreasing the dietary intake, while malnutrition itself can worsen the already existing longstanding illness and increase the vulnerability to new health conditions.[21]

 In rural areas, these problems are aggravated by various factors like poor socio economic status, poor health seeking behavior, limited awareness about nutrition and inadequate access to healthcare services. These elderly population in rural areas are also vulnerable because they may face additional challenges like dependence on family members, social neglect and food insecurity.

 Understanding the morbidity profile and nutritional status of the elderly population is essential for planning appropriate health interventions and policies aimed at improving their quality of life. Thus the present study aims to assess the morbidity pattern and nutritional status of the elderly population residing in rural areas of Sullia taluk, Karnataka, which will help generate evidence for strengthening geriatric health care services and nutritional interventions at community level.

The present study was conducted as a community based cross sectional study in Sullia, a rural taluk in Dakshina Kannada district of Karnataka over a period of 18 months from October 2023 to April 2025. The study population comprised elderly individuals aged 60 years and above residing in the study area.

 The sample size was calculated based on the results of a pilot study conducted among elderly individuals in the study area to estimate the proportion of morbidity among people aged 60 years and above. The prevalence of morbidity was found to be 77%, which was taken as the value of p for sample size calculation. Using the formula n = Z²p(1−p)/d², where Z = 1.96 at 95% confidence level and the allowable error (d) was 5%, the minimum sample size was calculated to be 272. This value was rounded off to 280 participants.

 A cluster sampling method was used to select the study participants. Sullia taluk consists of 40 villages, and seven elderly individuals from each village were selected to achieve the required sample size of 280 participants. In each village, the Village Panchayat was considered as the central point for data collection. From this point, houses along the road to the right were approached to identify eligible elderly individuals and collect data. In situations where fewer houses or eligible participants were available on the right side, the investigator proceeded to the left side. If there were still insufficient houses with elderly individuals or if a dead end was encountered, the investigator continued forward and then approached houses in the opposite direction. Only one elderly individual aged 60 years or above from each household was randomly selected for participation in the study.

 The inclusion criteria for the study included all individuals aged 60 years and above residing in the study area, with the condition that only one elderly individual per household would be randomly selected. The exclusion criteria included individuals who had lived in the study area for less than five years, houses that remained locked during three visit attempts, and elderly individuals who displayed hostile behaviour or declined to sign the informed consent form.

 Data were collected using a predesigned semi-structured proforma, which was validated by at least three experts prior to data collection. The questionnaire included information on sociodemographic characteristics, existing morbidities, and dietary practices of the participants. Nutritional status of the elderly was assessed using the Mini Nutritional Assessment (MNA) tool. Morbidities were assessed based on self reported history and available medical records.

 Prior to data collection, the selected participants were informed about the purpose and importance of the study, and written informed consent was obtained. The participants were seated in a comfortable and private environment to ensure confidentiality and to allow them to respond freely without external influence. A brief preliminary conversation was initiated to establish rapport, following which the interview was conducted using the predesigned proforma to obtain the required information.

 Prior to commencement of the study, approval was obtained from the Institutional Ethics Committee. All participants were informed about the study, and written informed consent was obtained before their inclusion in the study.

The collected data were entered into Microsoft Office Excel 2007, and statistical analysis was performed using IBM SPSS version 21. Categorical variables were analysed using the Chi-square test, while continuous variables, if any, were analysed using the Student’s t-test. A p-value of less than 0.05 was considered statistically significant.

A total of 280 elderly individuals aged ≥60 years participated in the study. The sociodemographic characteristics of the study population are shown in Table 1. The majority of participants belonged to the 60–69 years age group (52.85%), and females (52.14%) slightly outnumbered males (47.85%). Most participants were married (62.85%), while 34.28% were widowed. Nearly 44.64% had primary level education, and 42.85% were unemployed or homemakers. According to the Modified B.G. Prasad classification, the largest proportion of participants belonged to the middle socioeconomic class (33.57%). About 37.14% were fully financially dependent, while 29.28% were financially independent.

 The health characteristics of the participants are summarized in Table 2. A majority were non-smokers (70%) and non-drinkers (74.29%). Nearly 43.57% of participants had two or more comorbidities, and 31.43% were taking three or more medications per day.

 The morbidity profile of the study population is presented in Table 3. Musculoskeletal disorders (49.29%) were the most commonly reported morbidity, followed by hypertension (36.43%) and eye disorders (34.29%). Other commonly reported conditions included diabetes mellitus (24.29%) and respiratory diseases (20.71%).

 The nutritional status assessed using the Mini Nutritional Assessment (Table 4) showed that 55% of participants had normal nutritional status, while 32.9% were at risk of malnutrition and 12.1% were malnourished. The mean MNA score was 22.8 ± 3.9, and the mean BMI was 23.4 ± 4.1 kg/m².

 The association between selected variables and malnutrition is shown in Table 5. Malnutrition was significantly associated with education, marital status, financial dependency, smoking, alcohol use, presence of multiple comorbidities, and polypharmacy (p < 0.05). However, age group and gender were not significantly associated with malnutrition.

 

 

 

 

 

 

 

The present cross-sectional study assessed the morbidity pattern and nutritional status among elderly individuals residing in Sullia taluk of Karnataka. The findings indicate a considerable burden of morbidity and a notable proportion of elderly individuals who were either malnourished or at risk of malnutrition.

 In the present study, the majority of participants belonged to the 60–69 years age group. Similar age distribution has been reported in several community-based studies conducted among elderly populations in India. Krishnamoorthy et al[20] also observed that most participants belonged to the younger elderly age group in a study conducted in rural Puducherry. This pattern is commonly observed in community studies because mortality increases with advancing age, resulting in fewer individuals surviving into the oldest age groups.

 A slight female predominance was observed in the present study. Similar findings have been reported in other Indian studies including those by Krishnamoorthy et al[20] and Simon et al[21]. The higher proportion of females among elderly populations may be attributed to the longer life expectancy of women and the greater likelihood of women being present at home during household surveys.

 Musculoskeletal disorders were the most common morbidity observed in the present study, followed by hypertension and eye disorders. Similar findings have been reported in other studies among elderly populations in India. Jeyasuriya[5] also reported musculoskeletal conditions as one of the most frequently observed morbidities among elderly individuals. Age-related degenerative changes in bones and joints and prolonged physical labour in rural settings may explain the higher prevalence of musculoskeletal disorders. In addition, the increasing burden of non-communicable diseases such as hypertension and diabetes among the elderly has been widely documented in global studies.[6]

 In the present study, 55% of participants had normal nutritional status, while 32.9% were at risk of malnutrition and 12.1% were malnourished. These findings are comparable with those reported by Konda et al[2] and Krishnamoorthy et al.[20] A systematic review by Kushwaha et al[19] also reported that a substantial proportion of elderly individuals in India are either malnourished or at risk of malnutrition, highlighting the importance of early identification and preventive measures.

 Educational status showed a significant association with malnutrition in the present study, with a higher prevalence observed among illiterate individuals. Similar findings have been reported in previous studies where lower educational status was associated with poorer nutritional outcomes among elderly individuals.[20] Limited awareness regarding balanced diet and health-seeking behaviour may contribute to poorer nutritional status among individuals with lower educational attainment.

 Marital status was also significantly associated with malnutrition, with a higher prevalence observed among elderly individuals living alone. Similar findings have been reported in studies where social isolation and lack of family support were identified as important risk factors for malnutrition among older adults.[10] Financial dependency was another factor significantly associated with malnutrition. Elderly individuals who are financially dependent may have limited access to nutritious food and healthcare, which may contribute to poorer nutritional outcomes.[11] Lifestyle factors such as smoking and alcohol consumption were also significantly associated with malnutrition in the present study. Tobacco and alcohol use may adversely affect appetite, nutrient absorption and dietary intake, thereby increasing the risk of malnutrition.[22]

The presence of multiple comorbidities and polypharmacy also showed significant association with malnutrition. Similar associations have been reported in previous studies where chronic illnesses and multiple medications negatively influenced nutritional intake and overall nutritional status.[13,14] Chronic diseases may increase metabolic demands, reduce appetite or require dietary restrictions, thereby increasing the risk of malnutrition among elderly individuals.

 Overall, the findings of the present study indicate that although a majority of elderly individuals had normal nutritional status, a considerable proportion were either malnourished or at risk of malnutrition. These findings emphasize the need for early nutritional screening and appropriate community-based interventions to improve the health and quality of life of the elderly population.

The present study demonstrates that a considerable proportion of elderly individuals in the rural study area were either malnourished or at risk of malnutrition, and several sociodemographic, lifestyle, and health-related factors were found to be significantly associated with nutritional status. The findings emphasize the need for routine nutritional screening among the elderly at the community level, particularly among those who are socially or financially vulnerable and those with multiple comorbidities. Strengthening geriatric health services and promoting awareness regarding adequate nutrition may help in improving the overall health and quality of life of the ageing population.

 

1.       World Health Organization. Ageing: global population [Internet]. Geneva: World Health Organization; 2025 Feb 21. Available from: https://www.who.int/news-room/questions-and-answers/item/population-ageing..

2.       Konda S, Ravi Kumar BP, Giri PA. Prevalence of malnutrition and its determinants in an elderly people in South India. Int J Community Med Public Health 2018;5(8):3570-6.

3.       Asejeje FO, Ogunro OB. Deciphering the mechanisms, biochemistry, physiology, and social habits in the process of aging. Arch Gerontol Geriatr Plus 2024;1(1):100003.

4.       Charles ST, Carstensen LL. Social and emotional aging. Annu Rev Psychol 2010;61:383-409.

5.       Jeyasuriya A. Cross sectional study among elderly population to assess morbidity patterns in tertiary care hospital in Tamilnadu. Int J Curr Pharm Rev Res 2021;13(4):48-52.

6.       Prince MJ, Wu F, Guo Y,. The burden of disease in older people and implications for health policy and practice. Lancet 2015;385(9967):549-62.

7.       Marengoni A, Angleman S, Melis R, Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011;10(4):430-9.

8.       Martín-García S, Rodríguez-Blázquez C, Martínez-López I,. Comorbidity, health status, and quality of life in institutionalized older people with and without dementia. Int Psychogeriatr 2013;25(7):1077-84.

9.       Zaidi I, Sharma T, Chaudhary S, Barriers to access healthcare among the elderly population in rural regions of India. Int J Community Med Public Health 2023;10(11):4480-4.

10.    Donovan NJ, Blazer D. Social isolation and loneliness in older adults: review and commentary of a National Academies report. Am J Geriatr Psychiatry 2020;28(12):1233-44.

11.    McMaughan DJ,. Poverty in older adulthood: a health and social crisis. Online J Issues Nurs 2024;29(1).

12.    World Health Organization. Keep fit for life: meeting the nutritional needs of older persons [Internet]. Geneva: WHO; 2002. Available from: https://apps.who.int/iris/handle/10665/42515.

13.    Morley JE. Undernutrition in older adults. Fam Pract 2012;29(Suppl 1):i89-93.

14.    Ahmed T, Haboubi N. Assessment and management of nutrition in older people and its importance to health. Clin Interv Aging 2010;5:207-16.

15.    Morley JE. Anorexia of aging: physiologic and pathologic. Am J Clin Nutr 1997;66(4):760-73.

16.    World Health Organization. Keep fit for life: meeting the nutritional needs of older persons [Internet]. Geneva: World Health Organization 2002. Available from: https://apps.who.int/iris/handle/10665/42515.

17.    Donini LM, Poggiogalle E, Piredda M, et al. Anorexia and eating patterns in the elderly. PLoS One 2013;8(5):e63539.

18.    Ahmed T, Haboubi N. Assessment and management of nutrition in older people and its importance to health. Clin Interv Aging 2010;5:207-16.

19.    Kushwaha S, Khanna P, Srivastava R, et al. Estimates of malnutrition and risk of malnutrition among the elderly (≥60 years) in India: a systematic review and meta-analysis. Ageing Res Rev 2020;63:101137.

20.    Krishnamoorthy Y, Vijayageetha M, Kumar SG, et al. Prevalence of malnutrition and its associated factors among elderly population in rural Puducherry using mini-nutritional assessment questionnaire. J Family Med Prim Care 2018;7(6):1429-33.

21.    Simon S, Bhavani R, Balabaskaran S. A community-based cross-sectional study on nutritional status among elderly in rural Telangana. Healthline 2024;15(4):299-304.

22.    Johansson Y, Bachrach-Lindström M, Carstensen J, et al. Malnutrition in a home-living older population: prevalence, incidence and risk factors. A prospective study. J Clin Nurs 2009;18(9):1354-64.

23.    Amarya S, Singh K, Sabharwal M. Health consequences of obesity in the elderly. J Clin Gerontol Geriatr 2014;5(3):63-7.