Introduction
The aging population presents significant challenges to healthcare systems worldwide. The World Health Organization (WHO) defines individuals aged 60 years or older as part of the aging population [
1]. The aging population poses significant challenges to healthcare systems globally, including in Pakistan, and the quality of life among older adults is not satisfactory [
1]. Falls are a major cause of disability and prolonged hospitalization [
2]. According to the Centers for Disease Control (CDC) report, worldwide, 36 million elders report falling each year, which accounts for nearly 33% of the prevalence of falls in community-based older adults [
3]. Females over 70 are more likely to experience falls [
4,
5]. The frequency of falls varies across countries. China reported a prevalence of 31 to 34%, Japan at 21%, and Latin America reported 16%, in Pakistan, approximately 44% of falls were documented in a survey study. Out of these falls, 8% resulted in injuries, placing individuals at a high risk for hospitalization or even premature death [
2]. Therefore, older individuals in the Pakistani community should undergo regular fall risk assessments to develop a fall prevention strategy. With a projected increase in the number of individuals over 60 years old, it is crucial to understand the risk factors associated with falls in order to develop a healthy community. Therefore, this study aims to explore the prevalence of falls and associated factors in community-based older adults of Khyber Pakhtunkhwa, Pakistan, where the majority of the population belongs to the Muslim community. It is evident that Muslim communities have their own unique values and traditional systems. In these communities, females are often encouraged to stay at home while males are responsible for outdoor chores. However, this division of roles may increase the risk of falling for both genders.
Aging is characterized by a gradual deterioration in physiological and functional capacities. This includes the musculoskeletal and neurological systems, cognitive well-being, and sensory functions, as well as the onset of non-communicable diseases such as diabetes, cardiovascular diseases, and respiratory conditions. These factors collectively influence the activity levels of older adults and increase the likelihood of experiencing falls and disability [
6,
7]. However, it is important to note that certain environmental factors also contribute to falls, such as slippery floors, inadequate lighting, and infrastructure that is not conducive to safe movement [
8]. A comprehensive review study has also suggested that the risk of falls increases in advanced age due to a progressive decline in neurological and functional status [
9].
The occurrence of falls in older adults is multifactorial. One out of four older adults aged 65 or older falls at least once a year. These falls are mostly contextual and individualized in nature. They occur when physical, psychological, social, and environmental factors work together to contribute to their prevalence [
5,
10,
11].
Several studies have investigated the risk factors for falls, mostly reported from developed countries [
7,
12]. he risk factors of falling can be divided into intrinsic factors, such as low energy levels, cardiovascular diseases, disability, and poor vision, and extrinsic factors such as housing conditions, economic status, and weather conditions etc. [
6,
13]. Functional declines are increasing due to a lack of exercise, and physical activities, which increases the risk of falling, as reported in previous studies [
4]. Exercise has emerged as a promising and evidence-based intervention to reduce the risk of falls among older adults. The body of evidence addressing how exercise helps prevent falls in older individuals is extensive and consistently supports the idea that exercise programs can significantly reduce the risk of falls. Together, strength training, balance and gait training, flexibility exercises, and aerobic activities, when combined, improve physical function, reduce the risk of fall-related injuries, and enhance overall quality of life. Customized exercise regimens that are tailored to individuals' abilities, skills, and preferences can assist older individuals in maintaining their independence, mobility, and overall well-being. This, in turn, can lead to a healthier and safer aging process, regardless of any existing health condition [
14‐
16]. Physical activity level is primarily assessed by habitual walking speed [
11,
15]. The Time Up and Go (TUG) is commonly used to assess functional health-related fall risk in older adults, whether they have physical mobility problems or not [
17].
Several body movements, such as bowing and prostration, are therapeutic exercises that are similar to range of motion exercises [
18]. These movements can improve visual and cognitive health by increasing blood circulation and sugar levels. Mild to moderate level of therapeutic exercises are essential to maintain cardiovascular fitness such as orthostatic hypotension, high blood pressure, and improving muscular strength, coordination, [
7,
14,
19], prevent lumbar spondylosis, diabetes, and urinary incontinence (UI), highly correlated with falling history of older adults in previous studies [
5,
15,
16,
20], and cause premature deaths [
3,
4]. Falling does not solely depend on personal factors; there are also multiple external factors. Commonly identified home hazards that increase the risk of falls in older adults include difficulties with home access, such as navigating around the house, slippery floors, and falls specifically related to the bathroom. Previous studies have shown that these factors significantly contribute to the occurrence of falls [
6,
11,
12]. Fear of falling, even without any fall history, is another factor in falls in older adults. This fear may restrict their activities, and ultimately, they may adopt a sedentary lifestyle [
21]. According to Cameron and others, contain central nervous system depressant drugs, such as antihypertensive, can lower blood pressure and impair cognitive function, leading to blurred vision and postural hypotension [
6,
22]. Oshiro et al. conducted a study to predict the risk of falling by considering a combination of psychological and medical characteristics, medication usage, and sensory factors [
23]. The study found a significant 98% positive correlation between adjusted variables and fall risk, as well as an 8% negative correlation. A cross-sectional study reported that falls were higher among sedentary older adults compared to those who engaged in daily basis [
2]. Another study mentioned that prescribing appropriate body movements during Muslim prayers holds substantial promise in preventing falls in older adults. Regular performance of these movements can improve musculoskeletal strength, balance in gait, cardiovascular and respiratory system health, and metabolism [
24]. Older adults in developing countries face a higher risk of sustaining fall-related injuries [
25]. This can be attributed to several factors, including non-conducive environmental conditions, limited access to health facilities and screening opportunities, lack of awareness regarding healthy aging, lack of exercise, and lack of social support [
12,
26]. Identifying and addressing fall-related risk factors enables healthcare professionals to establish safer home environments and manage the modifiable risk factors associated with falls in older adults.
Identifying older adults who are at higher risk of falling and require interventions is challenging for clinicians and public health professionals. However, various fall predictors and scales have been developed and tested in various settings to assess fall risk among older adults. The Time Up and Go test (TUG) is the most frequently used tool to assess fall risk in older adults. It is assessed by having the participant rise from a chair, walk three meters, turn around, walk back, and sit down on the chair within an assigned time. The systematic review study mentioned that the TUGT score varies for different age groups and depends on the individual's health condition. Another review study claimed that the threshold time demarcating individuals classified as non-fallers and fallers exhibited variation, ranging from 10 s to 32.6 s [
27]. Furthermore, an average time of less than 19 s for a 3m walk can be considered normal functional mobility for a healthy older adult [
28]. Lusardi et al. included the Mini-Mental State Examination (MMSE) in their predictive model [
29]. Another study mentioned a comprehensive list of risk indicators, emphasizing the high predictive value of variables such as TUG, visual acuity, and cognitive scores [
17]. Moreover, a 12-point checklist consisting of medical history, medication use, balance, gait, muscle strength, and environmental hazards is frequently used in clinical settings to assess fall risk among older adults [
7]. Due to its multi-factorial nature, the researchers focus on formulating predictive models to assess fall related risk factors based on the individualized and environmental determinants that can be different from context to context. Therefore, regular fall risk assessment is crucial to preventing fall-related injuries in older adults living in developing countries [
30], where they are more susceptible to fall-related disabilities [
6,
29].
Within the scope of fall risk assessment and its multifactorial nature, the current challenge lies in the inability to directly apply risk factor assessment checklists to a specific demographic and environmental context. The debate in the literature revolves around the possibility of predicting falls through various models available to assess fall risk in older adults without any neurological decline and includes interventions that contribute to fall prevention [
31]. A systematic study was conducted to examine all prognostic predictive models for fall risk assessment, which included 30 papers on fall risk predictions. The results supported that a history of falls, age over 75, being female, having TUG scores > 19, poor vision, and a level of disability cutoff point > 5 were predictors of fall occurrence in older adults [
6]. The collective accuracy of these predictions were ranged from 0.62 to 0.69 in the previous study [
23], indicating inconsistency in the predictive factors of falls.
There are several predictive models and fall assessment checklists available, but they may not be effective in preventing falls in a population with different geographic and demographic characteristics. Although estimating gait quality scores with TUGT cut-off points, cognitive function status, past incidence of falls, and visual health may be common factors among individuals above 60 years of age group [
31]. Mishra and colleagues conducted a study in the United States of America (USA) and developed a predictive model. The cutoff point for "time-up and go" test scores was determined to be > 12 s for a 3 m walk. Additionally, they used a cognitive screening (10-CS) scale with a cutoff point of < 7 and considered individuals with a history of at least one fall in the last six months. The model was highly sensitive with an Area Under Curve (AUC) of 0.80 (95% CI 0.76–0.85), and a sensitivity of 0.82 (95% CI 0.74–0.89) [
32]. These parameters have been utilized in multiple falls risk assessment studies as a standard checklist for community-based older adults without any neurological health declines.
Diverse methods have been used in the literature to develop fall risk assessment models, including decision tree analysis [
27], fall prediction algorithms [
28], logistic regression [
31], and receiver operator characteristic (ROC) analysis for fall risk screening in older adults [
28]. In the field of predictive models, the six key predictors have shown the ability to accurately predict fall events, with probabilities ranging from 30.4% to 71.9%. A comparative review of predictive models measured parameters, such as area under the curve of any predictive factors (0.70 vs. 0.64), accuracy (0.65 vs. 0.62), sensitivity (0.62 vs. 0.50), positive predictive value (0.66 vs. 0.65), and negative predictive value (0.66 vs. 0.65). These parameters can be used as standard measures for fall risk assessment.
It is important to develop contextual and individualized intervention strategies to prevent falls in older adults from different populations. To achieve this, an updated assessment checklist is needed to evaluate the risk of falls in Muslim older adults living worldwide.
There is a noticeable gap in the research, as many studies have mentioned the beneficial effects of exercise and physical activities in preventing falls in older adults. However, Muslim people claim to perform five-time prayers with seven distinct body movements [
29], they argue that these scientifically based therapeutic exercises help keep joints, bones, and muscles healthy, improve cognition, enhance sleep quality, promote blood circulation at the capillary level, and reduce pain [
24,
33]. According to my knowledge, no study has been conducted to evaluate the beneficial effect of the seven steps of prayers in preventing falls among older Muslim adults, except for a few studies carried out to assess the actual level of performance in different Muslim countries such as Malaysia and Iran [
24,
34]. Older adults in the Muslim community primarily prioritize prayers. However, the quality of life and fall prevalence do not differ significantly from other communities. Therefore, an objective assessment is needed to evaluate fall risk. This assessment will involve assigning scores to seven steps, ranging from 1 to 7. A cutoff point of 5 scores will be used to determine the validity of the checklist in relation to fall risk. Incorporating statistical techniques, such as binary regression models, holds the potential to reveal predictive capacities and identify threshold values. This can help determine if non-compliance with the seven stages correlates with a higher risk of falls [
35]. Therefore, the purpose of our study was to identify potential contextual risk factors associated with falls in Muslim adults who were at risk for falling. Our goal was not only to identify risk factors for falls but also to develop a predictive model that highlights the intricate relationship between the lack of body movement during Muslim prayers and the risk of falls in older adults.