India ranks second among the most populated countries in the world with over 1.4 billion people. According to the 2011 census of India, the elderly population (aged above 60 years) constitutes 8.6% of the total population, which is projected to increase to 198 million by the year 2030. India is currently undergoing a demographic transition that led to a rise in the elderly population, thereby increasing the health care needs of older adults to improve their quality of life. ^[1-3] Increasing life expectancy, decreased fertility rates, socio-economic progress, and reduced mortality and birth rates have contributed to the rise in the geriatric population. ^[4]

Falls among the elderly have become a major public health concern globally, with the rapid increase in the ageing population. The prevalence of falls in India, above the age of 60 years, reported to range 14%–53%. ^[5,6] Injuries resulting from falls cause discomfort and disabilities in the elderly and also create stress for their caregivers. ^[7] Unintentional injuries have been reported as the fifth leading cause of death worldwide among the elderly, and falls account for about two out of every three deaths in this segment of the population. ^[6] Falls causes physical health consequences such as injuries, fractures and reduced activities of daily living. They also have psychological effects, where the person may become depressed, fear of falling again, lack of self-confidence leading to decreased mobility. ^[8]

Activities of Daily Living (ADL) denotes the basic skills which are necessary for persons to perform independently to care for themselves, viz., eating, bathing and mobility, and the terminology ADL was first coined by Sidney Katz in the year 1950. ^[9,10] Disability is defined as a difficulty in performing everyday activities necessary for independent living, such as Basic Activities of Daily Living (BADL) and Instrumental Activities of Daily Living (IADL). ^[11] Ageing is a natural phenomenon which causes a decline in the functional status of the individuals and also, a common reason for gradual loss of ADL. ^[12] Many conditions among the elderly involving the musculoskeletal, neurological, circulatory and sensory systems can cause decreased physical function and impairment in ADL. ^[13]

Falls among the elderly also affects their caregivers, as most of them develop increased concern about their care recipients falling again. ^[14,15] As a result, the caregivers experience heightened psychological distress, social restriction, and care giving burden. ^[15-18] Additionally, the caregivers begin adopting various strategies for the elderly to prevent further fall such as increasing vigilance and avoiding leaving the elderly alone at home. However, these strategies have drawbacks for caregivers, including a lack of personal time, difficulty in carrying out routine activities, and neglect of other responsibilities. ^[19-22] With this background, the present study was conducted to assess fall risk status of the elderly people, their activities of daily living and functional dependence, and to understand the impact of falls on both the elderly and their caregivers.

Study Setting: The study was conducted in the field practice area of Rural Health Training Centre (RHTC), Venmalagaram, Tamil Nadu which comprises 32 villages with a population of 33418, located 23 kilometres from our tertiary care institute.

Study design: A community based cross-sectional study, Mixed Method approach was used. Dependence on daily activities, fall risk assessment and risk factors for elderly fall were assessed by quantitative method. Qualitative method was used to better explore the effects of fall among the elderly (causes of fall and their health seeking behaviour, life of elderly before and after fall and the effect on fall on the life of the caregivers).

Study period: The study was conducted from March 2025 to June 2025.

Study Participants: People aged more than 65 years and who were permanent residents of RHTC field practice area were included in the study for collecting quantitative data. The victims of fall and their care takers were randomly selected and interviewed regarding the effects of fall.

Inclusion Criteria:

• Participants of both the genders aged more than 65 years and permanent residents of RHTC field practice area.

Exclusion Criteria:

• People who were bedridden, unable to participate in the
• People who are unable to answer due to mental and cognitive

Sample size: Sample size was calculated based on single proportion formula as given below.

n = (z1-α/2) 2 x p q / d ²

Where, z1- α/2 = 1.96

p = 36.6% (prevalence of elderly fall in earlier study), q = 1- p = 63.4%

d = Absolute precision = 7.5%

design effect = 2

Sample size (n) = 317

Sampling technique: Two-stage cluster sampling method was used to select the sample for the study.  In the first stage, 20 clusters were selected from the available 32 villages of the Rural Health Training Centre (RHTC) Venmalagaram of Chengalpattu district. In the second stage, a minimum of 17-18 elderly were selected from each cluster.

Study Procedure: Data collection was done by house-to-house survey. After obtaining an informed written consent, a pre-tested structured questionnaire was used for collecting the quantitative data. The questionnaire had four sections viz., i) questions on socio-demographic details of the elderly participants, ii) assessment of Independence in Activities of daily living, iii) Fall risk assessment questions and iv) questions to assess the risk factors for fall. The questionnaire was prepared from the available literature and were translated into Tamil language. The questionnaire was pilot tested with 55 participants (15% of the sample size) of similar study setting and the results were used for modifying the questions for easy comprehension of the participants. Also, the content validity was ensured by expert opinion and pilot testing of the questionnaire.

Data were collected in the field by the field staffs and Interns posted in Rural Health Training Centre (RHTC). The interns and field staffs were sensitized and explained about the study and also about the questionnaire prior to the commencement of data collection. The investigators cross-checked data collection to ensure the quality of the collected data.

Then, the effects of fall on the elderly and their care-givers were explored by conducting in-depth interview. The victims (elderly) of fall were randomly selected and interviewed regarding the causes of fall and their health seeking behaviour, life of elderly before and after fall. The care-givers of the victims of the fall were also interviewed about the effect of fall on the life of the caregivers

Study tools for data collection: The first part of the questionnaire had questions related to the socio-demographic details of the elderly participants. For assessment of Independence in Activities of daily living,

Katz Index was used which ranks adequacy of performance in the six functions of Bathing, Dressing, Toileting, Transferring, Continence and Feeding. Participants were scored 0 for dependence and 1 for independence for each of the 6 functions. A total score of 6 indicates patient being highly independent and 0 indicates patient being highly dependent.

Fall Risk assessment tool (FRAT) is a screening tool that can identify individuals who are at high risk of fall and the factors resulting in fall. It has four components:

1. Recent fall
2. Medications
3. Psychological
4. Cognitive status

Recent fall component summarizes the fall in the last one year and the scores were evaluated based on the same. Medications scores were given based on the number of medications the participants were taking. Psychological component was assessed by PHQ-9 (Patient Health Questionnaire- 9). Cognitive status component was assessed by AMTS (Abbreviated Mental Test Score) which is a screening tool that assess the patient cognitive function using 10 questions, with each question given a score of 1 for correct answer and 0 for wrong answer. Based on the Abbreviated Mental Test Score, the risk score for the elderly fall was finally assessed.

The Fall risk status total score was calculated based on four components and the risk was classified based on the score as follows:

Low risk: 5-11

Medium risk: 12-15

High risk: 16-20

Operational definition of recent fall: An unintended event in which an older adult  comes to rest inadvertently on the ground or floor or other lower level, occurring within the past 12 months, and excluding episodes due to major trauma, seizures, or loss of consciousness.^[23]

Method of Statistical Analysis and test applied: The collected data were entered in the Epicollect 5 which is a mobile and web application for free and easy data collection which is developed and maintained by Oxford Big Data Institute and it is available in public domain for free use. Data were analysed using Statistical Package for Social Sciences (SPSS) version 29 (IBM Corp. SPSS Statistics for Windows, Version 29. Armonk, NY: IBM Corp; 2022). Mean, median, proportions, chi-square test and logistic regression were used to analyse quantitative data considering p < 0.05 statistically significant. The data collected by in-depth interview were analysed by thematic content analysis where the audio recorded qualitative data were transcribed into local language (Tamil), translated into English language and then the translated data were coded by key words and categorized into various themes and subthemes.

Characteristics of the participants: According to the WHO classification, the majority of study participants belonged to the young-old category (86.9%), followed by the middle-old (11.1%) and the oldest-old (2%), as presented in (Table 1). Most of the elderly participants were female (60%) and identified as Hindu by religion (96.9%). Approximately two- thirds of the participants were illiterate. About 36.3% of the participants were unemployed, 72% were currently married, and 26.9% were widowed. Nearly half of the participants reported financial dependence on family members. Based on the Modified BG Prasad classification, two-thirds of the participants were categorized under the lower-middle and lower socio-economic classes.

Table: 1 - Socio-Demographic characteristics of the study participants (n=350)

Functional dependence and fall risk status: With respect to Activities of Daily Living (ADL), 97.1% of the participants were fully independent in performing routine activities based on the Katz Index of Independence. In contrast, 1.1% were moderately dependent, and 1.8% were fully dependent, as illustrated in (Figure 1). The Fall Risk Assessment Tool was utilized to evaluate the fall risk status among the elderly participants. It was observed that 76% had a low risk, 19.1% had a medium risk, and 4.9% had a high risk of falls as shown in (Figure 2).

Figure 1: Distribution on the dependency of study participants based on KATZ index reference (n=350).

Figure 1 shows the functional dependence of the elderly individuals which was assessed by their activities of daily living using KATZ index. Majority of them were fully independent on their daily activities, where a few were fully dependent on others for

their daily activities.

Figure 2: Distribution of the study participants based on the fall risk status (n=350).

Figure 2 shows the risk of fall among the elderly participants assessed by Fall Risk Assessment Tool (FRAT). Three-fourth of the participants had low risk of fall, while one-fifth had medium risk and less than five percent had high risk of fall Association between co-morbidities and fall risk status: The Chi-square test was employed to examine the association between fall risk and co-morbidities among the elderly participants. Significant associations were observed between fall risk and factors such as vision problems, mobility difficulties, behavioural issues, undernutrition, living alone, type 2 diabetes mellitus, hypertension, osteoarthritis, and spinal problems (p < 0.05), as presented in (Table 2). The Chi-square test was also applied to assess the association between selected socio-demographic factors and fall risk, revealing significant associations with age and sleep pattern (p < 0.05), (Table 3).

Table 2: Association between Fall Risk Status and associated co-morbidities of the elderly participants (n=350)

*Chi-square test, p<0.05 - statistically significant

Table 3: Association between Socio-Demographic Variables and Fall Risk Status (n=350)

*Chi-square test, p<0.05 - statistically significant, SES- Socio-economic class

Multivariate Analysis:

The prevalence of falls among the study participants was found to be 58.8%. Binary logistic regression analysis was performed to identify predictors of falls among the elderly, as detailed in (Table 4). Participants in the middle-old and oldest-old age groups exhibited higher odds of falling compared to the young-old, also these predictions were statistically significant. Elderly individuals with substance use (AOR: 1.161; 95% CI: 0.734–1.836; p > 0.05) showed increased odds of falls compared to those without substance use, but it was statistically insignificant. Other significant predictive factors associated with fall included living alone (AOR: 3.447; 95% CI: 1.947–12.54; p < 0.05), diabetes mellitus (AOR: 1.915; 95% CI: 1.069–3.431; p

< 0.05), hypertension (AOR: 6.29; 95% CI: 2.039–19.459; p < 0.05) and visual problems (AOR: 1.335; 95% CI: 1.034–2.462;

p < 0.05). Factors such as abnormal sleep pattern, osteoarthritis, spine problems and behavioural disorders were found to be predictors of fall, however they were not statistically significant (p > 0.05).

Table 4: Predictors of fall among the elderly participants - Binary Logistic Regression (n=350)

*(p < 0.05) statistically significant

Effects of fall on elderly and their caregivers: By thematic content analysis, five themes emerged from the qualitative component (in-depth interviews): common causes of fall among the elderly, health-seeking behaviour after sustaining a fall, life of the elderly before the fall, life of the elderly after the fall and life of their caregivers after the fall, as shown in (Table 5). Non-communicable diseases, environmental causes, socio-cultural factors and the use of medications were identified as the common causes of falls among the elderly. Fall victims preferred public hospitals over private ones for treatment due to financial constraints, and most of them opted for allopathy treatment rather than traditional or native remedies. Before the fall, elderly individuals were able to carry out their routine activities independently and participate in social events which became difficult or impossible after the fall. Caregivers reported several challenges, assisting the elderly with daily activities, lack of support from elderly in household responsibilities, and restriction on their own activities.

Table 5: Effects of fall in the elderly and their care-givers obtained from In-depth interviews (IDI)

In the present study, 97.1% of elderly participants were found to be fully independent in performing activities of daily living, as assessed by Katz Index of Independence in Activities of Daily Living. Only 1.8% were fully dependent on family members for their daily needs, while 1.1% of them were moderately dependent. These findings were consistent with previous studies conducted in India.^[24,25] Fall risk status was assessed using the Fall Risk Assessment Tool (FRAT). The results indicated that 4.9% of participants were at high risk of falls, 19.1% were at medium risk and 76% were at low risk. Similar findings were reported in a study from Andhra Pradesh by Lotheti SK et al., where 2% of participants were at high risk, 16% at medium risk and 82% at low risk. ^[26] A study conducted in Thrissur, Kerala also reported comparable results regarding fall risk among the elderly.^[27]

Risk factors for falls in the elderly were explored in the present study by finding association between fall risk and co-morbidities as well as selected demographic and lifestyle characteristics. Significant risk factors identified in the present study included visual impairment, reduced mobility, behavioural disturbances, undernutrition, hypertension, diabetes, osteoarthritis, spine problems and elderly living alone. Advancing age was associated with visual decline and increased fear of falling, both of which elevate the risk of falls. Furthermore, medications used to treat non-communicable diseases such as diabetes, hypertension may lead to hypoglycaemia and hypotension thereby increasing the fall risk.  Considerable risk factors were identified in a study conducted in Bangalore by Jyoti SV et al., which highlighted similar associations between co-morbidities and fall risk in the elderly population. ^[28] Similarly, Rekha et al. in a study from Kerala reported findings consistent with our observations.^[29] In addition, basic characteristics such as increasing age and abnormal sleep patterns were significantly associated with fall risk in this study, in agreement with the existing literature. ^[30,31]

Many studies in India have aimed to identify the predictors of falls among the and have reported several contributing factors. Some of these include fear of falling, lack of formal education^[32], depression, sleep problems ^[33], self-rated poor health ^[34] and anxiety ^[35]. The present study identified various significant predictors of elderly fall, such as age, living alone, diabetes, hypertension and visual problems.

There is a paucity of studies examining the impact of falls on elderly individuals and their caregivers in the Indian context, as most existing research has been conducted in Western countries. Non-communicable diseases, urinary incontinence, degenerative bone conditions, medications, environmental factors and socio-cultural factors were found to play a significant role in the causation of falls among the elderly. Most participants sought immediate treatment from public hospitals, preferring allopathy treatment over native or traditional remedies. The consequences of falls included activity restriction, social withdrawal and reduced mobility which led to diminished self-confidence among the victims. Caregivers faced challenges such as assisting the elderly with daily activities, restricted mobility, and being overburdened with additional responsibilities. These findings align with those of a previous study conducted in Kerala. ^[36]

Strengths of the study: One of the strengths of this study is that the effects of falls on caregivers were explored—an area that has not been extensively studied in the Indian context. Validated tools were used to ensure the validity and reliability of the findings. A pilot study was conducted, and necessary modifications were made based on the feedback received.

Limitations: Our study had a limited sample size, which reduces the generalizability of the findings. Moreover, as it was a cross-sectional study, conclusions regarding causality could not be drawn. There is a possibility of recall bias, as elderly participants were required to recall fall events from the past one year.

This mixed-method study underscores the complex and multifactorial nature of fall risk among the elderly population in rural Tamil Nadu. Although the majority of participants were functionally independent, a considerable proportion exhibited medium to high fall risk. Bivariate analysis revealed significant associations between fall risk and co-morbidities such as vision impairment, mobility limitations, undernutrition, and chronic illnesses including diabetes and osteoarthritis. However, multivariate analysis did not identify any statistically significant predictors. Qualitative findings highlighted the profound impact of falls on the daily functioning and social engagement of elderly individuals, as well as the considerable physical and emotional strain experienced by caregivers. These insights emphasize the importance of comprehensive fall prevention strategies, early identification of high-risk individuals, and strengthened caregiver support within primary healthcare and community-based interventions.

Ethical considerations: Ethical approval was obtained from the Institutional Ethics Committee. (IEC no. MAPIMS/IEC/521/03/2025)

Source of funding: Nil

Acknowledgment: I would like to acknowledge the village people, field staffs of my institute, department faculties and my colleagues who helped and contributed for my study.

Conflict of interest: Nil

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