INTRODUCTION
Saudi Arabia has undergone a rapid demographic shift, with the proportion of its aging population rising steadily [1]. Like many countries worldwide, Saudi Arabia faces the challenge of managing its aging population’s health needs. According to recent estimates, the percentage of people aged 65 years and above in Saudi Arabia is rapidly increasing. By 2035, over 20% of the population is projected to fall into the category of older adults [2]. This demographic shift highlights the need for research into the health and wellness of this population, including the issues of frailty and falls.
Falls present a substantial and multifaceted challenge in older adults, leading to both physical injury and profound psychological distress. The prevalence of falls increases with advancing age, and this susceptibility is notably pronounced in individuals experiencing frailty [3]. Frailty, characterized by vulnerability to physiological stressors due to the cumulative deterioration of multiple organ systems, results in muscle weakness, diminished energy levels, and a decrease in physical activity [4]. Furthermore, research has consistently identified frailty as a key contributor to falls among older adults. Diminished physiological reserves in frail individuals cause issues such as gait instability, postural imbalance, and muscle weakness, which collectively increase the risk of falls. Therefore, frailty and falls stand out as pivotal health concerns with substantial implications for the overall well-being and health of older adults.
In Saudi Arabia, the prevalence of falls among older adults surpasses that of many other countries, accounting for approximately 46% of the older adult population [5]. Frailty is a significant concern, with recent estimates placing its prevalence at approximately 21% among older Saudi adults [6, 7]. However, the intricate relationship between falls and frailty in this demographic remains unelucidated.
Despite the high prevalence of falls and frailty in Saudi Arabia, research exploring the relationship between these conditions is limited. Previous studies have mostly focused on individual factors related to falls or frailty [8, 9], rather than considering shared risk factors. This gap in the literature highlights the importance of further research on the relationship between frailty and falls among older adults in Saudi Arabia. Globally, this study will contribute to a better knowledge of frailty and falls by adding fresh data from the Middle East. The convergence of aging, healthcare, and culture in Saudi Arabia will provide a new viewpoint on frailty and fall prevention measures, emphasizing the importance of personalized treatments in similar socio-cultural settings.
This study aimed to investigate the association between frailty and the risk of falls among older adults in Saudi Arabia. The findings could guide clinical practice, providing valuable information for healthcare professionals and policymakers working to develop interventions to mitigate the risk of falls and frailty among older adults in Saudi Arabia and ultimately enhance the overall health and well-being of older adults in Saudi Arabia. By understanding the association between frailty and the risk of falls in this population, we can identify vulnerable individuals and implement targeted preventive care measures.
METHODS
Study design and participants
In this cross-sectional study, convenient sampling was used. A total of 395 older adults, both male and female, were enrolled as participants. The inclusion criteria were that participants must be 60 years of age or older, be able to read and write in Arabic, and be Saudi citizens. Exclusion criteria included individuals with acute illness. Recruiting was largely done through media and public advertising, as well as engagement with local residential communities (e.g., social centers and residential district committees). All participants provided informed consent to participate in the study, prior to their involvement in the study. The study was conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee at Prince Sattam bin Abdulaziz University (approval no. RHPT/022/010).
Demographics and clinical variables
Independently trained physical therapy researchers meticulously collected data. The process commenced by gathering demographic and clinical data, including age, sex, body mass index (BMI), and chronic diseases. Age was recorded in years and categorized into three categories: 60-69, 70-79, and ≥80 years. BMI was calculated by dividing weight in kilograms by height in meters squared.
Outcome measures
Data on major chronic diseases, including hypertension, diabetes, cardiovascular disease, lung disease, neurological diseases, cancer, and arthritis, were collected via self-reported diagnoses. In this study, the total number of chronic diseases was considered the variable of interest.
To assess frailty among older adults in Saudi Arabia, we used the Arabic version of the fatigue, resistance, ambulation, illness, loss of weigh (FRAIL) scale (AR-FRAIL scale). The AR-FRAIL scale comprises five domains, each of which contributes to the overall frailty assessment and has been validated for use in older adults in Saudi Arabia [10]. These domains include the following:
Resistance: difficulty walking 10 steps without resting or using aids (1 point).
Fatigue: feeling exhausted “all of the time” or “most of the time” in the past 4 weeks (1 point).
Illness: reporting five or more chronic conditions out of 11 total illnesses (1 point).
Ambulation: difficulty walking several hundred meters without resting or using aids (1 point).
Loss of weight: losing 5% or more body weight in the past year (1 point).
The total score on the AR-FRAIL scale was calculated by summing the scores for each domain. A score of 3-5 indicated frailty, a score of 1-2 indicated pre-frailty, and a score of 0 indicated robustness or no frailty. The AR-FRAIL scale is a reliable and valid measure of physical frailty in older adults. This is a simple and easy-to-use scale that can be used in clinical settings and research studies [10, 11].
Falls were measured in terms of the occurrence of falls and the number of falls in the past 12 months. Recurrent falls were defined as two falls or more in the past 12 months.
Data analysis
Descriptive statistics were used to summarize participants’ characteristics. Continuous variables are presented as mean ± standard deviation (SD), and categorical variables are presented as frequencies (percentages). The normality of the included variables was assessed using Kolmogorov–Smirnov test, and the data were normally distributed. Chi-squared tests and one-way analysis of variance (ANOVA) were used to compare the characteristics of participants with and without falls. Multivariable logistic regression analysis was conducted to examine the association between frailty and falls or recurrent falls, adjusting for potential confounding variables such as age, sex, and number of chronic conditions. Model goodness of fit was checked by using the Hosmer–Lemeshow test. Adjusted and unadjusted odds ratio (OR) with 95% confidence intervals (CIs) were reported. All analyses were performed using Stata version 15.1 (Stata Corp., College Station, TX, USA). A P value of less than 0.05 was considered statistically significant.
RESULTS
A total of 395 participants were included in the study. The demographics and clinical factors of the participants are shown in Table 1, stratified by fall status. The mean age of the participants was 66.4 years (SD = 7.1). Approximately 60% (238/395) of the participants were female. A total of 35.1% of the participants were classified as having had one or more falls in the last 12 months. The fall group had a higher number of comorbidities (mean 2.1) than the non-fall group (mean 1.3). The fall group also had a higher BMI (mean 29.7 kg/m2) than the non-fall group (mean 28.1 kg/m2).
Demographics and clinical factors according to fall status groups.
| Variable | Total sample, N = 395 (%) | Non-fall, n = 256 (64.8%) | Fall, n = 139 (35.1%) | P |
|---|---|---|---|---|
| Age group (years), mean (SD)a | ||||
| 60-69 | 295 (74.6) | 204 (69.1) | 91 (30.8) | 0.001 |
| 70-79 | 69 (17.4) | 41 (59.4) | 28 (40.5) | |
| >80 | 31 (8) | 11 (35.4) | 20 (64.5) | |
| Gendera | ||||
| Male | 157 (40) | 113 (72) | 44 (28) | 0.015 |
| Female | 238 (60) | 143 (60) | 95 (40) | |
| Marital statusa | ||||
| Married | 281 (72) | 203 (72.3) | 78 (27.7) | <0.001 |
| Single/widowed/divorced | 114 (28.9) | 53 (46.5) | 61 (53.5) | |
| Educationa | ||||
| No formal education | 201 (50.8) | 117 (58.2) | 64 (41.7) | <0.001 |
| Primary school | 134 (33.9) | 83 (61.9) | 51 (38.1) | |
| Middle school or higher | 60 (15.1) | 56 (93.3) | 24 (6.7) | |
| Number of comorbiditiesb | 1.58 (1.26) | 1.34 (1.14) | 2.1 (1.35) | <0.001 |
| BMI (kg/m2), mean (SD)b | 28.7 (5.7) | 28.1 (5.1) | 29.7 (6.5) | 0.001 |
Abbreviations: ANOVA, analysis of variance; BMI, body mass index; SD, standard deviation.
aChi-squared test.
bOne-way ANOVA.
The results of the multivariate binary logistic regression analysis of the association between falls as a risk factor and frailty status are shown in Table 2. Falls (falls in the last 12 months) were associated with the risk of being pre-frail and frail compared with non-frail individuals [OR 2.33 (95% CI 1.44-3.79); P < 0.001 and OR 5.37 (95% CI 2.85-10.01); P < 0.001, respectively]. This association was significant even after adjusting for age, sex, and number of chronic conditions. Similarly, the risk of recurrent falls was significantly higher in frail older adults than in non-frail older adults. The odds of having a recurrent fall are 2.9 times higher in pre-frail older adults and 4.9 times higher in frail older adults compared to non-frail older adults after adjustments for age, sex, and number of chronic conditions (Table 2).
Multivariable logistic regression estimates of fall and recurrent falls by physical frailty.
| FRAIL scale | Model 1a (N = 395) | Model 2b (N = 395) | ||||
|---|---|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | |||||
| Non-frail | Pre-frail | Frail | Non-frail | Pre-frail | Frail | |
| Fallsc | Reference | 2.33 (1.44-3.79) | 5.37 (2.85-10.01) | Reference | 1.77 (1.06-2.96) | 3.12 (1.53-6.38) |
| Recurrent fallsd | Reference | 3.56 (1.92-6.58) | 8.01 (3.91-16.4) | Reference | 2.99 (1.57-5.70) | 4.95 (2.22-11.06) |
Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio.
aModel 1: unadjusted model.
bModel 2: adjusted for age, sex, BMI, and number of chronic conditions.
cFalls in the last 12 months.
dTwo or more falls in the last 12 months.
DISCUSSION
The findings of this study contribute to a deeper understanding of the associations between falls, recurrent falls, and physical frailty among community-dwelling adults in Saudi Arabia. The results of the current study showed that frail older adults had a significantly higher risk of falls than non-frail older adults. In addition, older adults in the pre-frail or frail groups were more likely to experience recurrent falls than those in the robust group. This finding suggests that frailty is a progressive condition that increases the risk of falling over time.
The results of this study are consistent with those of previous studies showing an association between physical frailty and falls among older adults in different countries. A previous study that used the FRAIL scale to assess frailty found that frailty was independently associated with falls [12]. Kojima et al. reported that both frailty and pre-frailty significantly elevated the risk of falls among older adults [3]. In another review, older adults with frailty face a twofold higher risk of falling than the robust group [13]. Prospective population-based studies also showed a similar association between falls and frailty [14, 15].
One possible explanation for the relationship between frailty and falls is the physical manifestations of frailty. Individuals with frailty often experience muscle weakness, decreased balance, and reduced gait speed, which are well-established risk factors for falls. These factors increase the likelihood of falls, which can result in physical injury, hospitalization, and a poor quality of life. Older Saudi adults may also face specific challenges such as comorbidities [16, 17], musculoskeletal issues [18], and polypharmacy [19], which can exacerbate poor outcomes. Moreover, cognitive impairment reduces an individual’s capacity to adapt to environmental changes and respond rapidly to possible fall hazards, increasing fall risk [20]. In addition to musculoskeletal and neurological issues, metabolic alterations play a significant role in frailty. Oxidative stress and mitochondrial dysfunction, commonly observed in older persons, might worsen muscular weakness by decreasing energy production and increasing cellular damage [21]. Muscle loss, neuromuscular degeneration, metabolic dysfunction, and cognitive impairment all combine to increase frailty and fall risk; thus, when creating fall prevention programs, it is crucial to address each of these mechanisms since they work together to increase frailty and fall risk.
Our findings suggest that frailty is an important risk factor for falls and recurrent falls in older adults. Therefore, frailty assessments must be incorporated into standard geriatric care to assess older persons who are at risk of being frail and to avoid adverse effects on health, such as hospitalization and falls. Early frailty detection will help healthcare professionals develop tailored interventions to reduce the risk of falls in the geriatric population. Traditional fall prevention programs may need to be modified to address the unique challenges faced by frail older adults in Saudi Arabia, such as comorbidities and polypharmacy. These interventions may include exercise programs, physical therapy, and fall prevention education. Policymakers should also develop programs and policies to promote healthy aging and reduce the risk of falls in older adults. In addition to exercise interventions, community-level approaches to lower the risk of falls in public areas should concentrate on incorporating cutting-edge technologies and altering urban design. Improving walkways by ensuring they are level, with good lighting, and free of road hazards like potholes or damaged pavements is one of the main urban design interventions. To improve accessibility for senior citizens, public areas should be furnished with benches, ramps, and visible signage. Additionally, fall hazards can be considerably decreased by creating safer public transportation spaces with features like elevators and spacious doorways. Real-time monitoring of environmental dangers, such as identifying wet floors or inadequate illumination, can be provided by integrating smart infrastructure, such as Internet of Things sensors, which can notify maintenance staff for prompt action. In addition, wearable technology with fall detection capabilities is an area of future research that can help to assess and lower the risk of falls among older adults.
The findings of this study provide strong evidence that physical frailty is a significant risk factor for recurrent falls in older adults. However, the current results should be interpreted in light of the following limitations: the cross-sectional design might limit the causality of the factors associated with frailty and falls. Future research should examine these associations longitudinally. Moreover, we used a self-reported fall assessment in the current study. Thus, the data are prone to recall bias, which may have affected the study’s findings. Additionally, other potential confounders such as medication use, cognitive function, or environmental hazards have not been accounted for in the current analysis; future research might benefit from taking these variables into account to give a more thorough knowledge of the factors that influence fall risk. Finally, using a convenient sample in the current study limits the generalizability of our findings. Therefore, future studies should include larger sample sizes to conduct large-scale studies at the national level and obtain generalizability.
CONCLUSION
In conclusion, our research sheds light on the association between frailty and falls, as well as recurrent falls, in community-dwelling older adults in Saudi Arabia. This emphasizes the importance of specific fall prevention strategies that are tailored to the unique characteristics and challenges of frail older individuals in Saudi Arabia. Integrating frailty tests into standard geriatric care is critical for early detection and minimizing fall-related injuries. These findings are not just pertinent to Saudi Arabia but also have worldwide ramifications, as many other nations confront comparable aging issues. We urge lawmakers and healthcare practitioners to emphasize fall prevention and frailty management to improve the well-being, quality of life, and safety of the geriatric population.