Factors Associated with Falls in Older Adults: A Retrospective Hospital-Based Study Using Comprehensive Geriatric Assessment in Thailand (2020–2023)

Abstract

Background:

Falls are a leading cause of injury and disability in older adults, significantly impacting their quality of life. Identifying fall-related factors through comprehensive geriatric assessment (CGA) offers valuable insights into fall prevention strategies. This study aimed to explore factors associated with falls from CGA among older adults in Thailand.

Methods:

A retrospective cross-sectional study was conducted among older adults aged 60 years and older attending a geriatric clinic, Thailand between October 2020 and October 2023. Data were collected from electronic medical records, including personal information and CGA data (physical, psychological, and functional). The fall assessment was conducted on the same day by simply asking, “Have you ever fallen in the past year?”. The answer yes indicates a faller. Univariable and multivariable logistic regression analyses were performed to identify factors associated with falls.

Results:

Out of the 338 older adults, 96 (28.4%) reported a history of falls, 223 (65.98%) were older females, with a mean age of 69.76 ± 6.70 years. Significant factors of falls included advancing age (mOR 2.49, 95% CI 1.08-5.76, P-value = .033), female (mOR 1.92, 95% CI 1.02-3.61, P-value = .043), body mass index (BMI; mOR 0.92, 95% CI 0.85-0.99, P-value = .031), knee osteoarthritis (mOR 1.76, 95% CI 1.01-3.08, P-value = .045), and positive 2Q (mOR 0.33, 95% CI 0.11-0.99, P-value = .048).

Conclusion:

This study identified several CGA-derived factors—such as advanced age, female sex, lower BMI, knee osteoarthritis, and depression— that were associated with falls in older adults. These findings highlight the importance of integrating CGA into routine geriatric care to identify high-risk individuals and to inform targeted fall-prevention strategies in hospital settings.

Introduction

Many countries around the world, including Thailand, are transitioning into aging societies. ¹ As individuals age, they experience physiological changes that increase their susceptibility to chronic diseases and geriatric syndromes. ² Falls, one of the most common geriatric syndromes, are a prevalent concern among older adults and lead to a wide range of injuries, from minor to severe, such as hip fractures and head injuries. ³ These injuries often result in extended hospitalizations, a diminished ability to perform daily activities, and an elevated risk of disability and mortality. ⁴

In recent years, several studies have expanded the focus on fall risk factors to include additional elements such as activities of daily living (ADLs), nutrition, cognition, depression, the number of prescription medications, and the number of clinical diagnoses.^{5 -9} Other factors influencing fall risk identified in previous studies include chronic diseases, ¹⁰ history of hospital admissions, ¹¹ regular medication use, ¹² vision and hearing problems, ¹³ and body mass index (BMI).^12,14 Some studies have found that factors like alcohol consumption, smoking, energy drinks, and coffee do not significantly impact fall risk. ¹² Previous studies in Thailand have reported a high prevalence of falls among older adults, ¹⁵ with risk factors spanning physical, social, and environmental domains. ¹⁵ Most Thai older adults live with family members in multi-generational households, where traditional housing designs, such as elevated wooden houses with uneven flooring or steep stairways, may further increase fall risk. ¹⁵ These contexts highlight the need for tailored strategies to address fall risk in Thai older adults.

However, most previous studies gathered these factors through patient self-assessment or other indirect means, rather than being directly evaluated through a thorough assessment of the patient’s health status. Therefore, there is a need to identify fall-related factors using a more thorough approach, such as the Comprehensive Geriatric Assessment (CGA), a structured assessment that combines real performance measures and standardized questionnaires, providing a more comprehensive and multidimensional evaluation of older adults, including physical, psychological, functional, social, and environmental domains, as well as a medication review. ¹⁶ Assessing fall-related factors in this way is crucial for identifying individuals at risk and implementing timely interventions to reduce these risks. ¹⁷ Conventional fall risk assessments mainly focus on mobility or a limited set of risk factors. In contrast, CGA integrates multiple domains to capture the complexity of aging. ¹⁶ When applied in primary care settings, CGA provides real-world insights that are often overlooked in research or screening-based approaches. This holistic evaluation enables healthcare providers to identify potential fall risk, to develop tailored prevention and management strategies that address each individual’s multidimensional needs. ¹⁶ In Thailand, health screening for older adults is supported by a national program that incorporates periodic assessments as well as a structured system of CGA.^18,19 This system has been implemented across all hospital levels, from primary to tertiary care, and is designed to cover multiple health domains. ¹⁹ While the overall framework is consistent, the specific tools and methods used for screening vary according to the capacity of healthcare providers at each level. The recommended tools and algorithms are outlined in the Thai national guidelines, which were most recently updated in 2021, ¹⁹ and can be adapted to local resources and the specific needs of patients.

Despite the importance of CGA in identifying fall-related factors, few studies have comprehensively examined fall-associated factors using CGA data collected in routine clinical practice. As a result, there is limited evidence on fall-related factors directly measured through multidimensional assessments that accurately reflect patients’ actual physical and functional performance. Such data can enhance fall prevention efforts by reflecting patients’ actual health status and identifying cumulative risks across domains. This study aims to explore factors associated with falls in older adults based on CGA data, to inform more effective prevention strategies for this population.

Methods

Study Design

A retrospective observational cross-sectional study was conducted to investigate factors associated with falls in older patients who visited the geriatric at Maharaj Nakorn Chiang Mai Hospital, Thailand, between October 2020 and October 2023. The study received approval from the Research Ethics Committee of the institution (Approval No.0117/2567, Study Code: FAM-2567-0117) and was conducted in accordance with the Declaration of Helsinki. This retrospective study used secondary data without identifiable personal information. Therefore, the requirement for informed consent was waived by the Research Ethics Committee of the institution.

Participant and Setting

We included patients aged 60 years and older who visited the Geriatric Clinic in Thailand at Maharaj Nakorn Chiang Mai Hospital, between October 2020 and October 2023. All patients with CGA data recorded in our hospital’s electronic medical records (EMRs) during this period were included, while those without CGA data were excluded.

The sample size was calculated using a 2-sample comparison of means in STATA, based on estimates of the mean and standard deviation (SD) from a previous study. ²⁰ In that study, the mean age was 79.2 ± 6.2 years in the group with a history of falls and 76.6 ± 6.2 years in the group without a history of falls. The calculation was performed to achieve a statistical power of 0.80 and an alpha of 0.05 for detecting differences, resulting in a required sample size of at least 240 participants. However, in this study, we collected data from all cases between October 2020 and October 2023.

Data Collection

Data were collected using a standardized form to extract relevant information from EMRs. Personal information, including gender, age, weight, height, body mass index (BMI), and smoking status, was recorded. In this study, a fall was defined as an unexpected event in which an individual comes to rest on the ground, floor, or a lower level. ²¹ The fall assessment was conducted on the same day by simply asking, “Have you ever fallen in the past year?” The answer yes indicates a faller.

Additionally, CGA data were collected to comprehensively assess factors across physical, psychological, and functional domains, using standardized tools as described below. These assessments were completed comprehensively by the physician on the same day, without a fixed sequence. Each assessment typically required approximately 45 to 60 minutes per patient to complete. Following the assessment, the results were used by the clinical team to guide patient management, including health promotion, fall prevention advice, tailored interventions, and referrals to specialists as indicated. These results were further used to develop a coordinated and integrated treatment and follow-up plan. ¹⁶ The CGA toolkit is extensively utilized both in Thailand and globally. The version used in this study was developed by the department of Family Medicine at Chiang Mai University, adapted from the Thai version originally designed by the Institute of Geriatric Medicine, Department of Medical Services, Ministry of Public Health. ²² The CGA assessment and data recording in EMRs were conducted by the physician on the same day. Fall risk was evaluated using the Timed Up and Go (TUG) test. ²³ Patients were instructed to rise from a chair, walk 3 m forward, turn, and return to their original seated position at a normal gait speed. A completion time of more than 12 seconds indicated a high risk of falls. ²³ The toolkit includes the following assessments:

1. Osteoarthritis of the knee (OA knee): OA knee was screened using a 2-step approach. First, participants were asked 2 primary questions: (1) “Do you have knee osteoarthritis?” and (2) “Do you experience knee pain?” If they reported knee pain, a further evaluation was conducted to identify key symptoms associated with osteoarthritis, including crepitus, tenderness, morning stiffness lasting less than 30 minutes, knee swelling, and warmth. The presence of at least 2 of these symptoms suggested a high likelihood of OA of the knee. ²⁴

2. Cardiovascular risk: Cardiovascular risk was assessed using the Thai CV Risk Score, which calculates the ten-year cardiovascular risk based on smoking history, diabetes status, fasting blood sugar, blood pressure, total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL). A result of more than 20% indicated a high-risk group. ²⁵

3. Vision: Vision was evaluated using a Snellen chart to assess visual acuity (VA). ²⁶ Participants wore their usual corrective lenses, if applicable, during the test. A VA of 20/60 or worse was classified as impaired vision in this study. ²⁶

4. Hearing: Hearing ability was evaluated using self-reported concerns and the Finger Rub Test. ²⁷ Participants who exhibited abnormal results on the test were suspected of having hearing impairment and underwent further assessment.

5. Nutritional status: Nutritional status was assessed using the Mini Nutritional Assessment short form (MNA-SF), ²⁸ a 6-item tool that evaluates eating behaviors over the past 3 months. Scores were used to classify individuals, with a cutoff score of ≤11 indicating those at risk of malnutrition. ²⁸

6. Sleep: Sleep was assessed using 2 primary questions: (1) “Do you have trouble sleeping?” and (2) “Do you feel drowsy or fatigued during the day?” A positive response to either question was considered indicative of a sleep problem. Those who reported sleep difficulties underwent further evaluation to identify the specific nature and extent of their issues. ²⁹

7. Depression: Depression screening was performed using the 2Q Tool, ³⁰ which includes 2 questions assessing feelings of hopelessness and loss of interest in activities over the past 2 weeks. A positive result was defined as answering “yes” to one or both questions, indicating the need for further evaluation or intervention.

8. Cognition: Cognitive function was assessed using the Thai Mental State Examination (TMSE), ³¹ with copyright permission from the Faculty of Medicine, Siriraj Hospital, Mahidol University, a screening tool designed to differentiate dementia from normal cognition in the general population. The TMSE evaluates 6 key cognitive domains: orientation (awareness of time and place), registration (memory acquisition), attention (concentration), calculation (arithmetic skills), language (comprehension and expression), and recall (short-term memory). A score of ≤23 out of 30 indicates cognitive impairment. ³¹

9. Medication adherence: Medication adherence was assessed using the 4-item Morisky Green Levine Medication Adherence Scale (MGL-4). ³² Each question was scored with 1 point for a “No” answer, resulting in a maximum possible score of 4. A score of 4 indicates good medication adherence, while scores of 2-3 and 0-1 suggest moderate and low levels of adherence, respectively.

10. The ability to perform daily activities: The ability to perform daily activities was evaluated using the Barthel Activities of Daily Living (ADL) scale. This scale assesses ten basic daily tasks, with a total score of 20 points. A higher score indicates better functional capacity. ³³

Statistics Analysis

Statistical analyses were performed using Stata 16 (StataCorp, College Station, TX, USA), with a P-value of less than .05, considered statistically significant. Continuous data that were normally distributed were summarized using the mean and SD, while non-normally distributed continuous data were described using the median and interquartile range (IQR). Comparisons of these variables were made using the 2-sample t-test and Wilcoxon rank-sum test as appropriate. Categorical data were presented as frequency and percentage, and group comparisons were conducted using the chi-square test. If the expected frequency in one or more cells was less than 5, Fisher’s exact test was applied.

The association between factors related to falls from CGA was analyzed using univariable logistic regression to evaluate the individual effect size and statistical significance of each variable. To explore the factors associated with the history of falls, we employed a full model approach by including all pre-defined predictors in the multivariable logistic regression without stepwise elimination, using complete case analysis. The pre-defined predictors, selected based on prior evidence of fall risk, included: age ≥80 years, female gender, BMI, OA knee, impaired vision (VA worse than 20/60), impaired hearing (abnormal Finger Rub Test), risk of malnutrition (MNA-SF ≤11), positive 2Q test, sleep problems, cognitive impairment (TMSE ≤23), and Barthel ADL score <20. The influence of each factor on fall risk was expressed as odds ratios (OR) with corresponding 95% confidence intervals (95% CI).

Results

A total of 346 records were initially retrieved from the geriatric clinic database. Eight records were excluded due to duplication, as these patients had undergone repeated assessments in different years during the study period, resulting in 338 records (97.7%) included in the final analysis (Figure 1). Among the 338 participants included in the study, 96 individuals (28.4%) had a history of falls. The majority were female (223 individuals, 65.98%), with a mean age of 69.76 ± 6.70 years and a mean BMI of 24.95 ± 3.73 kg/m². Significant differences were observed between participants with and without a history of falls in mean age (P < .001), age ≥80 years (P = .005), female (P = .001), weight (P < .001), height (P = .001), and BMI (P = .027). Regarding CGA findings, participants with a history of falls had significantly higher TUG test scores compared to those without a history of falls (12.10 ± 4.03 vs 11.00 ± 3.62, P = .016). The prevalence of OA knees was also significantly higher among those with a history of falls (43.75% vs 28.51%, P = .007). Additionally, a greater proportion of individuals in the fall group had TMSE scores ≤23 (9.47% vs 3.75%, P = .036), indicating potential cognitive impairment. Functional independence, assessed using Barthel ADL scores, was significantly lower in the fall group (19.72 ± 0.87 vs 19.86 ± 0.43, P = .048) (Table 1). Other baseline characteristics are provided in Supplementary Table S1 .

Figure 1.

Flow of study.

Table 1.

Baseline Characteristics of Older Patients Stratified by Fall History (N = 338).

Variables	Total (N = 338)	Previous fall (N = 96)	Never fall (N = 242)	P-value
Personal information
Age	69.76 ± 6.70	71.90 ± 6.79	68.91 ± 6.49	<.001
Age < 80 years	303 (89.64)	79 (82.29)	224 (92.56)	.005
Age ≥ 80 years	35 (10.36)	17 (17.71)	18 (7.44)
Gender				.001
Male	115 (34.02)	19 (19.79)	96 (39.67)
Female	223 (65.98)	77 (80.21)	146 (60.33)
Weight (kg)	60.58 ± 11.75	57.12 ± 11.23	61.96 ± 11.69	<.001
Height (cm)	155.45 ± 7.98	153.27 ± 7.42	156.32 ± 8.05	.001
Body mass index (kg/m2)	24.95 ± 3.73	24.24 ± 3.86	25.23 ± 3.65	.027
CGA information
Timed up and go test (sec)	11.31 ± 3.77	12.10 ± 4.03	11.00 ± 3.62	.016
Knee osteoarthritis	111 (32.84)	42 (43.75)	69 (28.51)	.007
Thai CV risk	17.21 ± 7.23	17.53 ± 7.65	17.08 ± 7.06	.609
Thai CV risk < 20%	235 (69.53)	66 (68.75)	169 (69.83)	.845
Thai CV risk ≥ 20%	103 (30.47)	30 (31.25%)	73 (30.17%)
VAa				.732
Normal to 20/60	265 (79.10)	74 (77.89)	191 (79.58)
Worse than 20/60	70 (20.90)	21 (22.11)	49 (20.42)
Finger rub test				.659
Normal	255 (75.44)	74 (77.08)	181 (74.79)
Abnormal	83 (24.56)	22 (22.92)	61 (25.21)
MNA-SF total	13.00 ± 1.43	12.91 ± 1.50	13.04 ± 1.40	.433
Score ≤ 11	24 (7.10)	6 (6.25)	18 (7.44)	.701
Score 12-14	314 (92.90)	90 (93.75)	224 (92.56)
Sleep problem				.110
No	199 (58.88)	50 (52.08)	149 (61.57)
Yes	139 (41.12)	46 (47.92)	93 (38.43)
2Q				.280
Negative	312 (92.31)	91 (94.79)	221 (91.32)
Positive	26 (7.69)	5 (5.21)	21 (8.68)
TMSE scorea	27.70 ± 2.47	27.32 ± 2.89	27.85 ± 2.27	.072
Score ≤ 23a	18 (5.37)	9 (9.47)	9 (3.75)	.036
Score 24-30a	317 (94.63)	86 (90.53)	231 (96.25)
MGL-4 score	3.26 ± 0.95	3.34 ± 0.87	3.22 ± 0.99	.295
Score 1-3	167 (49.41)	45 (46.88)	122 (50.41)	.557
Score = 4	171 (50.59)	51 (53.13)	120 (49.59)
Barthel ADL	19.82 ± 0.59	19.72 ± 0.87	19.86 ± 0.43	.048
Score < 20	45 (13.31)	16 (16.67)	29 (11.98)	.253
Score = 20	293 (86.69)	80 (83.33)	213 (88.02)

Abbreviations: ADL, Activities of Daily Living; MGL-4, 4-item Morisky Green Levine Medication Adherence Scale; MNA-SF, Mini Nutritional Assessment short form; Thai CV risk, Thai Cardiovascular Risk; TMSE, Thai Mental State Examination; VA, visual acuity.

aMissing data for each variable was minimal, with missing participants 3 (0.01% of the total participants).

In univariable logistic regression, significant predictors include age ≥80 years, female, BMI, OA knee, and TMSE score ≤23. In the full model with 333 participants, significant predictors included advanced age (≥80 years) (mOR 2.49, 95% CI 1.08-5.76, P-value = .033), female (mOR 1.92, 95% CI 1.02-3.61, P-value = .043), BMI (mOR 0.92, 95% CI 0.85-0.99, P-value = .031), OA knee (mOR 1.76, 95% CI 1.01-3.08, P-value = .045), and positive 2Q (mOR 0.33, 95% CI 0.11-0.99, P-value = 0.048) (Table 2).

Table 2.

Logistic Regression Analysis of Factors Related to Falls from CGA (N=333).

History of falls	Univariable			Multivariable
	uOR	95% CI	P-value	mOR	95% CI	P-value
Age
Age < 80 years	Reference			Reference
Age ≥ 80 years	2.68	1.32 to 5.45	.007	2.49	1.08 to 5.76	.033
Gender
Male	Reference			Reference
Female	2.66	1.52 to 4.69	.001	1.92	1.02 to 3.61	.043
Body mass index (kg/m2)	0.93	0.86 to 0.99	.028	0.92	0.85 to 0.99	.031
Osteoarthritis of the knee	1.95	1.20 to 3.18	.008	1.76	1.01 to 3.08	.045
Thai CV risk
Thai CV risk < 20%	Reference			Reference
Thai CV risk ≥ 20%	1.05	0.63 to 1.75	.845	1.30	0.74 to 2.30	.361
VA
Normal to 20/60	Reference			Reference
Worse than 20/60	1.11	0.62 to 1.97	.732	0.87	0.45 to 1.66	.667
Finger Rub test
Normal	Reference			Reference
Abnormal	0.88	0.51 to 1.54	.659	0.87	0.47 to 1.61	.664
MNA-SF
Score ≤ 11	0.83	0.32 to 2.16	.702	0.55	0.18 to 1.67	.294
Score 12-14	Reference			Reference
Sleep problem
No	Reference			Reference
Yes	1.47	0.91 to 2.37	.111	1.57	0.92 to 2.70	.097
2Q
Negative	Reference			Reference
Positive	0.58	0.21 to 1.58	.286	0.33	0.11 to 0.99	.048
TMSE
Score ≤ 23	2.69	1.03 to 6.99	.043	1.79	0.63 to 5.12	.276
Score 24-30	Reference			Reference
MGL-4
Score 1-3	Reference			Reference
Score = 4	1.15	0.72 to 1.85	.558	1.02	0.60 to 1.71	.953
Barthel ADL
Score < 20	1.47	0.76 to 2.85	.255	1.17	0.55 to 2.50	.677
Score = 20	Reference			Reference

Abbreviations: ADL, activities of daily living; MGL-4, 4-item Morisky Green Levine Medication Adherence Scale; MNA-SF, Mini Nutritional Assessment short form; Thai CV risk, Thai Cardiovascular Risk; TMSE, Thai Mental State Examination; VA, visual acuity.

Discussion

The results of this study revealed that the prevalence of a history of falls among individuals aged 60 years and older was 28.4%. Several factors were found to be significantly associated with the history of falls, as identified through CGA. These factors included advanced age (≥80 years), female, lower BMI, a diagnosis of knee osteoarthritis, and a positive 2Q screening for depression. Understanding these factors is crucial for developing targeted interventions and preventive strategies aimed at reducing the risk of falls in this vulnerable population.

The prevalence of falls observed in this study, at 28.4%, is consistent with global findings, where approximately one-third of older adults experience falls. For example, in the United States, 28.7% of older adults reported falling at least once in the preceding 12 months in 2014. ³⁴ This is similar to the prevalence observed in other regions, such as Japan, where 20% to 30% of individuals aged 60 years and older experience falls annually, ³⁵ in Europe, where approximately 25% to 30% of community-dwelling older adults report falls each year, ³⁶ and in Oceania, which reports the highest fall prevalence at 34.4% among older adults. ³⁷ These findings highlight the widespread nature of falls in older populations, underscoring the importance of identifying risk factors to develop effective prevention strategies.

The factors associated with the history of falls in this study, particularly those identified through CGA, are consistent with previous studies. A study in the Middle East involving a population of 64,273 individuals also reported that age, sex, and knee osteoarthritis were significant risk factors for falls in older adults. ³⁸ Several studies have found that females are significantly associated with an increased risk of falls and consistently report higher fall rates among women.^{39 -41} This elevated risk is often attributed to gender-specific health conditions, particularly osteoporosis. ⁴² Postmenopausal women experience a marked reduction in bone mineral density, making them more susceptible to falls and fractures. ⁴² Additionally, osteoporosis has been shown to impair postural control, negatively affecting balance and increasing the risk of falls. ⁴³ These findings emphasize the importance of addressing gender-specific factors in fall prevention strategies.

Advancing age was also found to be a significant risk factor for falls in our study, consistent with previous research.^44,45 The risk of falling tends to increase with age, due to various factors such as declines in mobility, as well as physical and cognitive functions. ⁴⁶ Age-related sarcopenia, characterized by the loss of muscle mass and strength, results in reduced physical stability and increased frailty. ⁴⁷ Vision impairments, such as cataracts and macular degeneration, reduce depth perception and visual acuity, making it more difficult to detect hazards. ⁴⁸ Additionally, cognitive decline, including reduced attention and executive function, impairs the ability to anticipate and respond to environmental challenges. ⁴⁹ These age-related changes contribute to the increased risk of falls.

OA of the knee is a common issue among older adults, and our study found an association between OA of the knee and falls, which aligns with prior research. A systematic review of 21 studies also identified knee osteoarthritis as a prominent risk factor for falls. ⁵⁰ The European Project on Osteoarthritis identified an association between clinical OA of the hip and knee and impaired physical function. ⁵¹ OA has also been associated with reduced physical activity, ⁵² primarily due to pain, stiffness, and joint instability, which can lead to muscle weakness and decreased balance control, further increasing fall risk. ⁵³ Additionally, concerns about falls or pain, or injury may lead individuals with OA to avoid movement, resulting in physical deconditioning and increased susceptibility to falls. ⁵⁴

Lower BMI has been associated with an increased risk of falls, as it contributes to the decline in muscle strength and physical function. ⁵⁵ Sarcopenia, often linked to low BMI, further increases the risk of recurrent falls. ⁵⁶ Several studies have examined the association between low BMI and fall risk. For instance, a study of over 50,000 participants found that individuals with low BMI were at higher risk of falls compared to those with a normal BMI. ⁵⁷ However, some studies have reported that underweight BMI may not necessarily increase fall risks in certain populations and may even provide some protection in specific contexts, such as among females in community settings. ⁵⁸

Our study found that a positive 2Q test was associated with a lower risk of falling, which is contrary to most previous research. ⁵⁹ Meta-analyses have identified depression as a major risk factor for falls, suggesting that individuals with depressive symptoms are more likely to experience falls. ⁵⁹ This discrepancy may be explained by several factors, including limitations of the 2Q screening tool, which may not fully capture the severity of depression and has lower specificity compared to the 9Q or PHQ-9, ⁶⁰ and characteristics of our study population, who were older adults attending a geriatric clinic during the COVID-19 pandemic and may have been more health-conscious or received interventions that reduced fall risk. ⁶¹ These findings highlight the need for further studies to clarify the true relationship between depression and falls in older adults.

Several factors identified through the CGA are associated with falls. While other factors may not yet be found to be significantly associated with a history of falls, older adults with a history of falls should still undergo a thorough CGA and receive holistic care. This approach is crucial for identifying both intrinsic and extrinsic risk factors specific to everyone, as fall risk differs among older adults. Such evaluations will help guide the development of personalized fall prevention strategies in the future.

Strength and Limitation

This study has several strengths. First, it considers a broad range of factors across physical, psychological, and functional domains, offering a holistic approach to evaluating fall risk. Second, we utilized factors from the CGA, which not only reflect the physical performance of older adults but are also practical and easily applicable in primary care settings. Third, this study analyzed CGA data collected during routine clinical practice in a geriatric outpatient setting, which provides real-world insights into the health status of older adults. This study has some limitations. First, it was conducted at a single center with a relatively small sample size, which may limit generalizability and statistical power. Future multicenter studies with larger, more diverse populations and prospective fall monitoring could improve accuracy. Second, fall history was assessed retrospectively by asking participants about any previous falls within the past year. While this approach allows for a comprehensive capture of fall events and helps identify individuals at higher risk, ⁶² it may introduce recall bias. Future studies should consider a prospective design. Developing predictive models and targeted interventions based on CGA factors may further enhance fall prevention and care for older adults.

Conclusions

This study suggests that factors derived from the CGA, including advanced age, female sex, lower BMI, and knee osteoarthritis, are associated with an increased risk of falls, while depression was associated with a lower risk. CGA can be used in routine practice to assess fall risk, identify high-risk individuals, and guide tailored interventions at both hospital and community levels. In situations where a full CGA cannot be performed, the presence of key factors should prompt careful attention to fall risk, with the option to conduct a comprehensive CGA at a later stage. Further research is needed to confirm these findings and optimize strategies for fall prevention.