Aging is a universal phenomenon associated with deteriorating health status. With time, certain changes take place in organs leading to morbidities, disabilities, and even death.¹ In recent years, advancements in the medical field are made possible by rescuing many lives and helped in increasing life expectancy. As a result, the geriatric population has increased. The boundary of old age cannot be defined exactly as it has different meanings in various societies.² National Programme for Health Care of the Elderly (NPHCE), the persons aged 60 years and above are considered as geriatric population.³ Now-a-days due to disintegration of joint family system and an increased nuclear family, elderly people are forced to reside in old age homes (OAH).⁴

The growth and development of OAH had begun in India in 1901.⁵ According to the population census of 2011, there are nearly 104 million elderly people in India and is expected to grow to 173 million by 2026.⁶ It has been observed that the prevalence of diseases rises with increasing age from 39% in 60-64 years of age group to 55% in more than 70 years of age group.⁷ Chronic diseases cause medical, social, and psychological problems that limit the activities of elderly people in the community. Current challenges, health needs, and management of geriatric people differ from others. A thorough examination of geriatric people for morbidity and related risk factors is required to improve the delivery of health care to the elderly. The current study aims to describe the morbidity profile and the associated risk factors among elderly people living in OAHs.

A cross-sectional study was conducted over a period of three months during May to July 2019, following approval from both the Institutional Scientific Committee and the Institutional Ethical Committee. After obtaining necessary permissions, the study was done at six old age homes located within the Tirupati urban area. The study population comprised elderly individuals aged 60 years or above residing in these facilities. Elderly individuals who exhibited hostile behaviour or declined to provide consent to participate in the study were excluded. Applying the formula n=Zα²p(1-p)/d² for a cross-sectional study with qualitative outcome at 95% confidence limits, with a relative marginal error 5% of the estimate and considering most prevalent morbidity condition of musculoskeletal disorders recorded as 77.2%⁸, minimum sample size was estimated as 114. From the available six OAHs, a total of 120 subjects were recruited. Before collecting data, all subjects were briefed about the purpose of the study and informed written consent was obtained. Subjects were given the right to withdraw consent at any stage. Data on socio-demographic and cultural factors including age, gender, religion, caste, type of family, education, socioeconomic status, and tobacco and alcohol usage were collected using a pre-tested questionnaire. Anthropometric measurements such as height and weight were recorded, and the nutritional status of participants was assessed by calculating their Body Mass Index (BMI). In the context of addiction (Tobacco usage and alcohol), an ever user is an individual who has used a substance at least once in their life. In contrast, a current user is defined as someone who has used the substance within the past 30 days. Subjects who engaged in activities such as walking, yoga, or gardening for at least 30 minutes per day were considered to have physical activity. Furthermore, a comprehensive head-to-toe physical examination was conducted alongside a verification of previous health records to identify a wide range of existing disease conditions within the elderly population. These conditions encompassed various physical health problems such as hypertension, diabetes mellitus, visual and hearing problems, musculoskeletal issues, respiratory illnesses, cardiovascular diseases, cancer, accidents and injuries, diseases of the locomotor and genitourinary systems, as well as psychological and neurological disorders. The collected data was entered in MS Excel spread sheet and analysed by using EPI INFO software version 7.2.0. Categorical variables were expressed in percentages and Continuous variables in mean and standard deviation. The difference between proportions were analysed by using chi-square test. Tables and bar diagrams were used to represent data.

Figure 1: Distribution of morbidity profile of the subjects

Table 1: Sociodemographic and lifestyle details of subjects (n=120)

Majority of the study participants were belonged to the age group of 60-70 years (50.0%) followed by age group of 71-80 years (25.8%) and mean age was found to be 72.15±10.77 years. Slightly higher proportion were females (63.3%) than males (36.7%). About 94.2% of study subjects belong to Hindu religion. Most of the study subjects were illiterates (53.3%), married (58.3%) and unemployed/ housewives (43.4%). In past, around 60.0% of study participants were lived in a nuclear family and Majority of the study subjects were staying in old age homes for more than or equal to 3 years (43.3%). Regarding lifestyle practices, high prevalence of physical inactivity (72.5%), a normal BMI (65.8% <25), and low rates of substance addictions, with smoking being the most common (14.2%) was recorded [Table:1].

The most prevalent morbidity among elderly residents was musculoskeletal problems (50.0%), followed by hypertension (35.0%) and visual impairments (33.3%). A notable portion of subjects had psychological disorders (22.5%) and respiratory issues (21.7%)[Figure:1].

Figure 2: Distribution of drug intake among the subjects

The treatment adherence for various morbidities shows a mixed pattern; while conditions like hypertension (88.1% regular treatment) and diabetes mellitus (100% regular treatment) demonstrate excellent management, other prevalent issues like musculoskeletal problems (61.7% regular), psychological disorders (59.3% regular), and respiratory problems (46.2% regular) suffer from significant rates of irregular or not starting any treatment [Figure:2].

Table 2: Association of most prevalent morbidity conditions with socio demographic & lifestyle factors

*Significant

The analysis revealed that while advanced age (>75 years) consistently showed a higher raw prevalence across most morbidities, these associations were not statistically significant (e.g., Hypertension p=0.62, Musculoskeletal p=0.58). The most significant predictors were related to psychological health, with illiteracy (p=0.004), unemployment (p=0.005), and living in a non-nuclear family (p=0.02) all showing strong positive correlations. For physical health, significant associations were found between illiteracy and hypertension (p=0.03), alcohol use and respiratory illness (p=0.02), and a lower BMI (<25) was unexpectedly associated with psychological morbidities (p=0.01). The vast majority of tested variables, including gender, physical activity, and tobacco use, demonstrated no statistically significant relationship (p>0.05) with the assessed health conditions [Table:2

This study explores the socio-demographic and morbidity profile of an elderly population residing in old age homes and the association of these morbidities with various factors. The majority of participants were aged 60-70 years (50%), with a mean age of 72.15 years, aligning with findings from studies in Uttarakhand⁹ and South India¹⁰. Females constituted a higher proportion (63.3%) than males, a trend consistent with studies from Kolkata¹¹. Religiously, the cohort was predominantly Hindu (94.2%), similar to study in Assam¹².

A significant portion of the population was illiterate (53.3%), a finding supported by a study done by Mao L etal¹¹, though contrasting studies from Assam¹² and South India¹⁰ reported higher literacy rates. Occupational status prior to joining the home was predominantly unemployed / housewives (43.4%) or unskilled workers (29.2%), mirroring findings from Assam¹². A majority (60%) previously lived in a nuclear family; a pattern also observed in studies from Assam¹² and Manipur¹³. Regarding their stay in the old age home, 43.3% had been residents for three or more years, while a study in Gujarat¹⁴ found a higher proportion of shorter stays.

Musculoskeletal problems were the most prevalent morbidity (50%), followed by hypertension (35%), visual problems (33.3%), and respiratory issues (22.5%). Diabetes mellitus was present in 19.2% of subjects. This pattern of musculoskeletal and visual issues being predominant is consistent with findings from studies in Gujarat⁶ and Mangalore¹⁵. However, other studies^14,16,17 reported hypertension and visual problems as the most common ailments.

Overweight and obesity were found in 34.1% of subjects, a rate comparable to a study in Chennai¹⁸. Substance use was relatively low, with 15.2% using any form of tobacco and 8.3% alcoholics, figures similar to a study in Aurangabad¹⁹ but lower than one from Pune²⁰. A large majority (72.5%) did not engage in regular physical activity, contrasting with the high activity rate (73.3%) found in Chennai¹⁸. Reduced appetite was reported by 27.5% of participants while it was only 7.5% in a study conducted by Ramaswamy etal²¹. Disturbed sleep pattern was observed in 34.2%, similar to a study at Tamilnadu²².

The analysis revealed several trends, though many associations were not statistically significant. The prevalence of hypertension was higher in those over 75 years (37.8%), females (36.8%), and literates (44.6%). A study in Tamil Nadu²³ also found high hypertension rates among literates but reported higher rates in males and the 60-70 ages group. Musculoskeletal morbidities were more common in subjects aged over 75 years (53.3%) and males (52.3%), a finding supported by a Lucknow study²⁴. Visual problems were also higher in the older age group (44.5%) and males (36.4%), though other studies^15,16 found a higher prevalence in females. A significant association was found for psychological morbidities, which were higher among illiterates (32.9%). Respiratory morbidities were significantly higher in subjects aged 75 years and above (35.5%) compared to those aged 60-75 years (13.4%). A Gujarat study¹⁴ found a slightly higher prevalence in males.

This study's key strengths include calculated and justified sample size, use of a comprehensive, systematic data collection method with a pre-tested questionnaire. Precise operational definitions for critical variables enhance clarity, and the combination of physical examinations with health record verification improves the accuracy of morbidity data. The study's main limitations are its cross-sectional design, which prevents causal inference, and its limited generalizability due to the specific sample from old-age homes in a single urban area. Findings are also susceptible to information bias from self-reported data. 

It can be concluded that the elderly population residing in old age homes is predominantly female, Hindu, and in their seventh decade, with a high prevalence of illiteracy. The most common health issues are musculoskeletal problems, hypertension, and visual impairments, while psychological morbidities are significantly associated with being illiterate, married, unemployed, and having a lower BMI. Furthermore, advanced age (>75 years) and alcoholism are significant risk factors for a higher prevalence of respiratory diseases. The findings underscore the need for integrated geriatric healthcare programs focused on regular screening, management of chronic conditions, and addressing modifiable risk factors like lifestyle choices to improve the quality of life in this vulnerable population.

Source of support: Under Graduate Student Research Scholarship-2022 by Dr. NTR University of health sciences, Vijayawada, Andhra Pradesh

Conflicts of interest: None declared

1. Surekha Kishore, Ruchi Juyal, Jayanti semwal, Ramesh Chandra. Morbidity profile of elderly persons. JK Science 2007; 9(2):87-9.
2. Jeyalakshmi S, Chakrabarti S, Gupta N. Situation analysis of the elderly in India. Central Statistics Office Ministry of Statistics & Programme Implementation, Government of India, New Delhi; June 2011. Available from: https://www.researchgate.net/publication/274093346. [Last accessed on 9^th Sep 2022].
3. National Program for the Health Care of the Elderly (NPHCE)-An approach towards Active and Healthy Ageing-Operational Guidelines. Directorate General of Health Services, Ministry of Health and Family Welfare, Government of India. Available at https://www.mohfw.gov.in/?q=en/major-programmes/Non-Communicable-Diseases/Non-Communicable-Diseases-1. [Last accessed on 4^th Sep 2022].
4. Beevi JS. Morbidity Status of The Elderly Women in Institutions and Non-institutions. Help age India-Research and Development Journal. 2008 Oct;14(3):248-58.
5. Help age India. Available from: https://www.helpage.org. [Last accessed on 15^th Sep 2022].
6. Zalavadiya DD, Banerjee A, Joshi NB, Bhola CN, Sheth AM. A Comparative Study of Morbidity Profile of Elderly Residing in Old Age Homes and in the Community of a Tier-II City in India. Natl J Community Med 2018;9(07):480- 5.
7. Srinivasan K, Vaz M, Thomas T. Prevalence of Health-related disability among community- dwelling urban elderly from middle socioeconomic strata in Bengaluru, India. Indian J Med Res.2010 Apr;131(4):515-21.
8. Usha P, Kishore S, Singh M, Jain B, Kumar D, Kumar Reddy NK, Rehan A, Ranjan SK. A study of morbidity profile among geriatric population in Uttarakhand: A community based cross-sectional study. J Family Med Prim Care. 2020 Jul 30;9(7):3677-3681.
9. Usha P, Kishore S, Ranjan SK. A study of morbidity profile among geriatric population in Uttarakhand: A community based cross-sectional study. J of family medicine and primary care 2020;9(7):3677-81.
10. Joseph N, Nelliyanil M, Nayak S, Agarwal V, Kumar A, Yadav H, et al. Assessment of morbidity pattern, quality of life and awareness of government facilities among elderly population in South India. J Family Med Prim Care. 2015;4(3):405.
11. Mao L, Mondal K, Manna M. A comparative study on quality of life of older adults. Indian Cont Nsg Edn. 2019;20(1):73.
12. Pathak G, Kalita D, Deka B. Study on morbidity pattern among elderly in urban area of Barpeta, Assam, India. J Family Med Prim Care. 2022;11(2):553-8
13. Rajkumari G. A Study of Elderly Living in Old Age Homes in Manipur, India 2021. J Gerontol Geriatr Res;10(4):1-5.
14. Rana A, Likhar S. K, Narkhede V, Choudhary S. K, Likhar K. S, Mishra M. K. Morbidity Pattern and Social Interaction Amongst Elderly Living in Old Age Homes. Biomed Pharmacol J 2009;2(2).
15. Padmanabha U, Udayakiran N, Nagarajaiah P, Kempaller V. Morbidity profile of inmates in old age homes in Mangalore, South India. Int J Med Sci Public Health. 2016;5(11):2230-3.
16. Asadullah Md, Kuvalekar K, Katarki B, Malamardi S, Khadka S, et al. A study on morbidity profile and quality of life of inmates in old age homes in Udupi district, Karnataka 2012;2(3):91-7.
17. Patel P, Patel U, Thakor N. Profile of elderly inmates of old age homes of Patan district, Gujarat, India: a cross sectional study. Int J Res Med Sci. 2015;2725–8.
18. R, Seralathan M, S. J. Prevalence and factors associated with overweight and obesity among elderly people in a semi-urban area of Chennai. Int J Community Med Public Health. 2018;5(9):3887-91.
19. Mundada V, Gaikwad A, Jadhav V. Study of addiction problems and morbidity among geriatric population in rural area of Aurangabad district. J Mid-life Health. 2013;4(3):172-5.
20. Pandve HT, Manohar Chavan V, A Giri P. Study of Health Problems and Addiction Pattern among Elderly Population in Rural Areas of Pune, India. Epidemiology (Sunnyvale) 2017;7(2):303.
21. Ramaswamy S, Joshi SM, Velankar DH. An epidemiological study of health and morbidity profile among geriatric population in field practice area of a Medical College in Navi Mumbai. Indian J Community Health. 2021 Jun 30;33(2):266–75.
22. Reddy NB, Pallavi M, Reddy NN, Reddy CS, Singh RK, and Pirabu RA. Psychological morbidity status among the rural geriatric population of Tamil Nadu, India: A cross- sectional study. Indian J Psychol Med. 2012; 34(3): 227– 31.
23. Vidyalakshmi M, Raja Sakkarapani TC. A study of morbidity profile in south Indian geriatric population in a rural community at Thiruverkadu Thiruvallur district. AGEMS. 2021 Feb 28;7(2):73–7.
24. Kumar S, Majumdar S, Paul A, Bhattacharyya N. Morbidity pattern among geriatric population in a rural area of West Bengal: A cross-sectional study. Journal of Clinical and Diagnostic Research. 2021;15(10):28-31