Abstract
Purpose
This study aimed to identify risk factors for falls and fall-related injuries among community-dwelling older adults in Korea.
Methods
This longitudinal study analyzed 3,186 adults aged 65 or older using nationally representative data from the Korean Longitudinal Study of Aging across three waves (2018, 2020, and 2022). We conducted multiple logistic regression analyses to identify risk factors for falls and fall-related injuries.
Results
Over the 4-year follow-up, 148 participants (4.6%) experienced a fall, and 118 of these (79.7% of fallers) sustained a fall-related injury. The risk of falls increased with advanced age (odds ratio [OR]=2.01, 95% confidence interval [CI]=1.37~2.96), female sex (OR=1.64, 95% CI=1.07~2.52), lower self-rated health (OR=1.94, 95% CI=1.01~3.77), and being underweight (OR=2.71, 95% CI=1.36~5.42) or obese (OR=1.69, 95% CI=1.11~2.55). For fall-related injuries, significant risk factors included advanced age (OR=1.74, 95% CI=1.14~2.65), female sex (OR=1.71, 95% CI=1.06~2.75), lower self-rated health (OR=2.61, 95% CI=1.22~5.59), and being underweight (OR=3.01, 95% CI=1.46~6.20).
Conclusion
These findings indicate that falls and fall-related injuries among older adults are complex health issues that extend beyond simple physical problems. Further research should continue to identify risk factors through repeated studies and support the development and implementation of comprehensive education and intervention programs that address the risk factors identified in this study.
Keywords: Accidental falls, Wounds and injuries, Risk factors, Aged
INTRODUCTION
The rapid increase in the older population has made health issues among older adults a significant societal concern. Falls are a common and serious problem among older adults and pose significant threats to their health, safety, and independence [1]. Approximately one-third of community-dwelling older adults experience at least one fall each year in high-income countries, including the United States and European countries, and a substantial proportion of these falls result in fall-related injuries [2,3]. In Korea, the prevalence of falls among community-dwelling older adults ranges from 7.1% to 16.6% [4,5]. Falls directly cause injuries and also lead to fear of falling and reduced physical activity, which can increase functional dependence and negatively affect quality of life [6,7]. Falls also raise the likelihood of admission to long-term care facilities and increase healthcare costs due to complications such as fractures and intracranial hemorrhage [8].
Falls are a major risk factor for reduced quality of life in older adults and create significant economic burdens for individuals and society because of increased long-term care needs and healthcare expenses [8]. Although falls can occur at any age, they are most common among adults aged 65 and older [2]. As the older population grows, the socioeconomic burden from falls, including healthcare costs, is expected to rise. Identifying risk factors for falls and developing strategies to reduce these risks are key priorities for clinicians and policymakers in an aging society.
Because most falls are predictable and preventable [4], identifying modifiable risk factors is essential for effective prevention. Previous studies have found several predictors of falls among community-dwelling older adults, including sociodemographic factors (e.g., age, sex, living arrangement, and residential area) [2,9-13]; health status and behaviors (e.g., self-rated health, chronic conditions, medication use, visual impairment, obesity, and regular exercise) [1,4,10-17]; and mental health factors (e.g., depression, cognitive function, and fear of falling) [9,12,13].
Despite a growing body of evidence, several limitations remain, particularly in studies of Korean older adults. Many studies have examined factors associated with falls in Korea, but most rely on cross-sectional designs, limiting the ability to establish temporal relationships between risk factors and falls. Few studies have comprehensively examined multiple risk factors simultaneously using longitudinal data, and earlier studies [10,13] are now outdated. Research on fall-related injuries, which may have more severe consequences than falls alone, remains insufficient. Although recent fall prediction models for Korean older adults exist [4,5,16], most focus exclusively on falls, underscoring the need for updated analyses that consider a broader range of outcomes, including fall-related injuries.
This study aimed to identify risk factors for falls and fall-related injuries among older adults using a nationally representative longitudinal dataset. The findings are intended to provide evidence for developing strategies to prevent falls in Korea’s rapidly aging population.
METHODS
Ethic statement: This study used anonymized secondary data from KLoSA. All participants provided informed consent at the time of data collection. The Institutional Review Board of Chungbuk National University approved the study (IRB No. CBNU-2025-0368).
1. Study Design and Population
This study was conducted in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines (https://www.strobe-statement.org). A prospective cohort (longitudinal) study design was employed using secondary data from the 2018, 2020, and 2022 waves of the Korean Longitudinal Study of Aging (KLoSA), conducted by the Korea Employment Information Service. KLoSA is a nationally representative survey of community-dwelling adults aged 45 years and older in South Korea, designed to provide foundational information for developing socio-economic policies in an aging society. The survey covers seven domains: demographics, family, health, employment, income, assets, subjective expectations and satisfaction. Conducted every 2 years, KLoSA uses a multistage stratified sampling design based on geographic regions and housing types. Participants were randomly selected to form a nationally representative sample. Raw data were obtained from the KLoSA website (https://survey.keis.or.kr/) following required application procedures.
For this study, we included participants aged 65 years or older at baseline (2018) who participated in both the 2020 and 2022 waves. Of the 4,352 older adults aged 65 years or older in 2018, we excluded 915 who dropped out, 61 with missing fall-related outcomes, and 190 with missing covariate data, resulting in a final analytic sample of 3,186 participants (Figure 1). This study was designed as a longitudinal analysis to prospectively assess falls and fall-related injuries over a 4-year period. To assess potential selection bias, baseline characteristics were compared between participants included in the final analysis and those excluded due to missing data or loss to follow-up.
Fig. 1.
Flow diagram of study sample selection
2. Measures
In this study, variables were selected based on previously identified risk factors for falls and fall-related injuries among older adults. Independent variables, including sociodemographic characteristics, health status, health behaviors, and mental health factors, were measured at baseline (2018) to establish temporal precedence relative to fall outcomes. Dependent variables were fall occurrence and fall-related injuries over the subsequent 4-year period.
1) Falls and Fall-Related Injuries
Falls were defined as unexpected events in which an individual came to rest on the ground or a lower level, excluding incidents caused by external forces, loss of consciousness, or sudden paralysis [18]. Fall-related injury was operationally defined as any injury resulting from a fall that required medical care [14]. In KLoSA, falls were assessed by asking participants, “Since the previous baseline survey, have you experienced a fall?” Participants who responded “yes” were classified as having experienced a fall during the corresponding follow-up period. Among participants who reported a fall, fall-related injury was assessed by asking, “Was the injury from your most recent fall severe enough to require treatment?” Participants who responded “yes” were classified as having experienced a fall-related injury. In this study, fall occurrence and fall-related injuries were assessed during the subsequent 4-year follow-up using self-reported data from the 2020 and 2022 survey waves, with the 2018 survey serving as the baseline.
2) Sociodemographic Characteristics
Variables included age (65~74 years vs. ≥75 years), sex, educational level (elementary school or less, middle school graduate, high school graduate or higher), and living arrangement (living alone vs. with family).
3) Health Status and Behaviors
Health-related variables included self-rated health, number of chronic diseases, number of medications, visual impairment, body mass index (BMI), and regular exercise. Self-rated health was measured by asking, “How would you evaluate your health?” Responses of “very good” or “good” were coded as “good,” “fair” as “fair,” and “poor” or “very poor” as “poor.” Chronic diseases included arthritis, cancer, cerebrovascular disease, chronic pulmonary disease, diabetes, heart disease, hypertension, and liver disease. The number of chronic diseases and medications was categorized as 0, 1, 2, 3 or more. Visual impairment was assessed with the question, “How is your vision (including corrected vision)?” Responses of “very good,” “good,” or “fair” were coded as no visual impairment, while “poor” or “very poor” were coded as visual impairment. BMI was calculated as weight (kg) divided by height squared (m²), and obesity was classified according to the Korean Society for the Study of Obesity guidelines [19]: underweight (<18.5 kg/m2), normal weight (18.5~22.9 kg/m2), overweight (23.0~24.9 kg/m2), and obese (≥25.0 kg/m2). Regular exercise was defined as physical activity at least once per week, based on the survey question, with responses coded as “yes” or “no.”
4) Mental Health Variables
Mental health variables included depressive symptoms, cognitive function, and fear of falling. Depressive symptoms were measured using the Korean version of the Center for Epidemiological Studies-Depression Scale (CES-D-10) [20]. The CES-D-10 consists of 10 items, each rated on a 4-point Likert scale (0~3), with total scores ranging from 0 to 30, where higher scores indicate more severe depressive symptoms. A cutoff score of ≥7 was used to indicate the presence of depressive symptoms. In this study, the internal consistency of the CES-D-10 was acceptable (Cronbach’s α=.777). Cognitive function was assessed using the Korean version of the Mini-Mental State Examination (MMSE-K), which is standardized and validated for older adults [21]. The MMSE-K consists of 30 items, with total scores ranging from 0 to 30, where higher scores indicate better cognitive function. Participants were classified as having normal cognitive function or cognitive impairment based on MMSE-K cutoff scores adjusted for age, sex, and education, according to established Korean normative data. In this study, the internal consistency of the MMSE-K was acceptable (Cronbach’s α=.803). MMSE-K variables provided in the KLoSA dataset were used for this secondary data analysis; however, the MMSE is a copyrighted instrument and the present study did not directly administer the instrument but utilized pre-collected survey data. The authors acknowledge responsibility for compliance with applicable copyright and licensing regulations. Fear of falling was assessed with the question, “Are you afraid of falling?” and responses were coded as “not at all,” “somewhat,” or “very much.”
3. Statistical Analysis
Data were analyzed using IBM SPSS/WIN version 26.0 (IBM Corp.). Descriptive statistics were performed for each variable using the frequency (%) for categorical variables, and mean and standard deviation for numerical variables. The chi-square test and t-test were used to examine differences in falls and fall-related injuries by participant characteristics. Multiple logistic regression analyses were conducted to identify risk factors for falls and fall-related injuries, with results reported as odds ratios (ORs) and 95% confidence intervals (CIs). Multicollinearity among independent variables was assessed using variance inflation factors (VIFs) and tolerance values. The VIFs ranged from 1.04 to 3.09, and tolerance values ranged from 0.324 to 0.955, indicating no evidence of significant multicollinearity. Statistical significance was defined as p<.05.
RESULTS
1. Participant Characteristics
Table 1 presents the baseline sociodemographic characteristics, health status and behaviors, and mental health variables of the study participants. The mean age of the participants was 74.3 years, 41.2% were male and 58.8% were female. In terms of education, 51.8% had completed elementary school or less. Most participants (80.9%) lived with family. The most frequently reported self-rated health status was “fair” (48.1%). On average participants had 1.53 chronic diseases and used 1.13 medications. Visual impairment was reported by 24.3% of participants. Based on BMI classification, 3.2% were underweight, 40.7% normal weight, 29.8% overweight, and 26.3% obese. Regular exercise was reported by 34.9% of participants. Depressive symptoms were present in 3.1% of participants, 34.2% had cognitive impairment, and the most common response to fear of falling was “somewhat” (61.3%).
Table 1.
Baseline Characteristics of Study Participants (N=3,186)
| Variable | n (%) or mean±SD |
|---|---|
| Age (year) | 74.3±6.4 |
| 65~74 | 1,724 (54.1) |
| ≥75 | 1,462 (45.9) |
| Sex | |
| Male | 1,314 (41.2) |
| Female | 1,872 (58.8) |
| Educational level | |
| ≤Elementary school | 1,650 (51.8) |
| Middle school | 579 (18.2) |
| ≥High school | 957 (30.0) |
| Living arrangement | |
| Living alone | 609 (19.1) |
| With family | 2,577 (80.9) |
| Self-rated health | |
| Good | 650 (20.4) |
| Fair | 1,534 (48.1) |
| Poor | 1,002 (31.5) |
| Number of chronic diseases* | 1.53±1.20 |
| 0 | 698 (21.9) |
| 1 | 1,010 (31.7) |
| 2 | 817 (25.6) |
| ≥3 | 661 (20.7) |
| Number of medications | 1.13±1.08 |
| 0 | 1,087 (34.1) |
| 1 | 1,057 (33.2) |
| 2 | 681 (21.4) |
| ≥3 | 361 (11.3) |
| Visual impairment | |
| Yes | 775 (24.3) |
| No | 2,411 (75.7) |
| Body mass index (kg/m2) | |
| Underweight (<18.5) | 102 (3.2) |
| Normal (18.5~22.9) | 1,296 (40.7) |
| Overweight (23.0~24.9) | 951 (29.8) |
| Obese (≥25.0) | 837 (26.3) |
| Regular exercise | |
| Yes | 1,112 (34.9) |
| No | 2,074 (65.1) |
| Depressive symptoms | |
| Yes | 100 (3.1) |
| No | 3,086 (96.9) |
| Cognitive function | |
| Normal | 2,097 (65.8) |
| Impairment | 1,089 (34.2) |
| Fear of falling | |
| Not at all | 533 (16.7) |
| Somewhat | 1,952 (61.3) |
| Very much | 701 (22.0) |
Chronic diseases include hypertension, diabetes, cancer, chronic pulmonary disease, liver disease, heart disease, cerebrovascular disease, and arthritis. SD=Standard deviation.
Baseline characteristics were compared between participants included in the final analysis and those excluded due to missing data or loss to follow-up (Supplementary Table 1). There were no significant differences in age, sex, self-rated health, number of chronic conditions, number of medications, visual impairment, BMI, or depressive symptoms between the two groups. However, significant differences were observed in educational level, living arrangement, regular exercise, cognitive function, and fear of falling.
2. Differences in Falls and Fall-Related Injuries by Participant Characteristics
During the 4-year follow-up, 148 participants (4.6%) experienced falls, and 118 participants (3.7% of the total sample; 79.7% of those who experienced falls) reported fall-related injuries. The occurrence of falls differed significantly by age (p<.001), sex (p<.001), education level (p<.001), self-rated health (p<.001), number of chronic diseases (p<.001), number of medications (p<.001), visual impairment (p<.001), BMI (p<.001), cognitive function (p=.004), and fear of falling (p<.001). There were no significant differences by living arrangement (p=.099), regular exercise (p=.176), and depressive symptoms (p=.105).
The occurrence of fall-related injuries was also significantly associated with age (p<.001), sex (p<.001), education level (p<.001), self-rated health (p<.001), number of chronic diseases (p<.001), number of medications (p=.006), visual impairment (p=.024), BMI (p<.001), cognitive function (p=.021), and fear of falling (p=.001). No significant associations were found for living arrangement (p=.076), regular exercise (p=.307), or depressive symptoms (p=.486) (Table 2).
Table 2.
Incidence of Falls and Fall-Related Injuries During 4 Years by Participant Characteristics (N=3,186)
| Variable | Category | Falls during 4 years (%) |
Fall-related injuries during 4 years (%) |
||||
|---|---|---|---|---|---|---|---|
| Yes (n=148) | No (n=3,038) | p-value | Yes (n=118) | No (n=3,068) | p-value | ||
| Age (year) | 65~74 | 33.1 | 55.1 | <.001 | 35.6 | 54.8 | <.001 |
| ≥75 | 66.9 | 44.9 | 64.4 | 45.2 | |||
| Sex | Male | 25.7 | 42.0 | <.001 | 26.3 | 41.8 | <.001 |
| Female | 74.3 | 58.0 | 73.7 | 58.2 | |||
| Educational level | ≤Elementary school | 70.3 | 50.9 | <.001 | 68.6 | 51.1 | <.001 |
| Middle school | 11.5 | 18.5 | 9.3 | 18.5 | |||
| ≥High school | 18.2 | 30.6 | 22.0 | 30.3 | |||
| Living arrangement | Living alone | 24.3 | 18.9 | .099 | 25.4 | 18.9 | .076 |
| With family | 75.7 | 81.1 | 74.6 | 81.1 | |||
| Self-rated health | Good | 9.5 | 20.9 | <.001 | 8.5 | 20.9 | <.001 |
| Fair | 39.2 | 48.6 | 41.5 | 48.4 | |||
| Poor | 51.4 | 30.5 | 50.0 | 30.7 | |||
| Number of chronic diseases* | 0 | 13.5 | 22.3 | <.001 | 14.4 | 22.2 | <.001 |
| 1 | 27.0 | 31.9 | 27.1 | 31.9 | |||
| 2 | 23.0 | 25.8 | 22.9 | 25.7 | |||
| ≥3 | 36.5 | 20.0 | 35.6 | 20.2 | |||
| Number of medications | 0 | 20.9 | 34.8 | <.001 | 22.9 | 34.6 | .006 |
| 1 | 31.1 | 33.3 | 33.1 | 33.2 | |||
| 2 | 25.0 | 21.2 | 24.6 | 21.3 | |||
| ≥3 | 23.0 | 10.8 | 19.5 | 11.0 | |||
| Visual impairment | Yes | 35.8 | 23.8 | <.001 | 33.1 | 24.0 | .024 |
| No | 64.2 | 76.2 | 66.9 | 76.0 | |||
| Body mass index (kg/m2) | Underweight (<18.5) | 8.1 | 3.0 | <.001 | 9.3 | 3.0 | <.001 |
| Normal (18.5~22.9) | 33.8 | 41.0 | 36.4 | 40.8 | |||
| Overweight (23.0~24.9) | 22.3 | 30.2 | 22.0 | 30.1 | |||
| Obese (≥25.0) | 35.8 | 25.8 | 32.2 | 26.0 | |||
| Regular exercise | Yes | 29.7 | 35.2 | .176 | 30.5 | 35.1 | .307 |
| No | 70.3 | 64.8 | 69.5 | 64.9 | |||
| Depressive symptoms | Yes | 5.4 | 3.0 | .105 | 4.2 | 3.1 | .486 |
| No | 94.6 | 97.0 | 95.8 | 96.9 | |||
| Cognitive function | Normal | 54.7 | 66.4 | .004 | 55.9 | 66.2 | .021 |
| Impairment | 45.3 | 33.6 | 44.1 | 33.8 | |||
| Fear of falling | Not at all | 12.2 | 17.0 | <.001 | 12.7 | 16.9 | .001 |
| Somewhat | 48.6 | 61.9 | 51.7 | 61.6 | |||
| Very much | 39.2 | 21.2 | 35.6 | 21.5 | |||
Chronic diseases include hypertension, diabetes, cancer, chronic pulmonary disease, liver disease, heart disease, cerebrovascular disease, and arthritis.
3. Multivariate Analysis of Risk Factors for Falls and Fall-Related Injuries
Multivariate logistic regression analysis showed that age, sex, self-rated health, and BMI were significant risk factors for falls among older adults. Old-old adults had 2.01 times higher odds of falling compared to young-old adults (OR=2.01, 95% CI=1.37~2.96). Females had higher odds of falls than males (OR=1.64, 95% CI=1.07~2.52). Participants with poor self-rated health had 1.94 times higher odds of falling than those with good health (OR=1.94, 95% CI=1.01~3.77). Underweight participants had 2.71 times higher odds (OR=2.71, 95% CI=1.36~5.42), and obese participants had 1.69 times higher odds (OR=1.69, 95% CI=1.11~2.55) compared to those with normal BMI (Table 3).
Table 3.
Multivariate Logistic Regression Analysis of Risk Factors for Falls and Fall-Related Injuries During 4 Years
| Variable | Category | Falls during 4 years |
Fall-related injuries during 4 years |
|---|---|---|---|
| OR* (95% CI) | OR* (95% CI) | ||
| Age (year) | 65~74 | 1 | 1 |
| ≥75 | 2.01 (1.37~2.96) | 1.74 (1.14~2.65) | |
| Sex | Male | 1 | 1 |
| Female | 1.64 (1.07~2.52) | 1.71 (1.06~2.75) | |
| Educational level | ≥High school | 1 | 1 |
| Middle school | 0.90 (0.48~1.70) | 0.58 (0.28~1.21) | |
| ≤Elementary school | 1.31 (0.80~2.16) | 1.04 (0.61~1.76) | |
| Living arrangement | With family | 1 | 1 |
| Living alone | 0.80 (0.53~1.22) | 0.90 (0.57~1.43) | |
| Self-rated health | Good | 1 | 1 |
| Fair | 1.43 (0.78~2.61) | 1.80 (0.90~3.64) | |
| Poor | 1.94 (1.01~3.77) | 2.61 (1.22~5.59) | |
| Number of chronic diseases† | 0 | 1 | 1 |
| 1 | 0.82 (0.38~1.78) | 0.84 (0.37~1.93) | |
| 2 | 0.67 (0.27~1.63) | 0.82 (0.32~2.08) | |
| ≥3 | 0.99 (0.39~2.54) | 1.49 (0.57~3.90) | |
| Number of medications | 0 | 1 | 1 |
| 1 | 1.41 (0.71~2.78) | 1.34 (0.65~2.74) | |
| 2 | 1.37 (0.61~3.11) | 1.05 (0.45~2.47) | |
| ≥3 | 1.69 (0.68~4.21) | 0.97 (0.37~2.53) | |
| Visual impairment | No | 1 | 1 |
| Yes | 1.23 (0.84~1.81) | 1.09 (0.71~1.68) | |
| Body mass index (kg/m2) | Normal (18.5~22.9) | 1 | 1 |
| Underweight (<18.5) | 2.71 (1.36~5.42) | 3.01 (1.46~6.20) | |
| Overweight (23.0~24.9) | 1.02 (0.65~1.61) | 0.92 (0.55~1.51) | |
| Obese (≥25.0) | 1.69 (1.11~2.55) | 1.34 (0.84~2.14) | |
| Regular exercise | Yes | 1 | 1 |
| No | 0.97 (0.66~1.43) | 0.99 (0.64~1.51) | |
| Depressive symptoms | No | 1 | 1 |
| Yes | 1.16 (0.53~2.54) | 0.86 (0.33~2.27) | |
| Cognitive function | Normal | 1 | 1 |
| Impairment | 0.90 (0.61~1.32) | 0.91 (0.59~1.40) | |
| Fear of falling | Not at all | 1 | 1 |
| Somewhat | 0.75 (0.44~1.30) | 0.77 (0.43~1.39) | |
| Very much | 1.00 (0.54~1.86) | 0.88 (0.45~1.75) |
All models are adjusted for age, sex, education, living arrangement, self-rated health, number of chronic diseases, number of medications, visual impairment, body mass index, regular exercise, depressive symptoms, cognitive function, and fear of falling.
Chronic diseases include hypertension, diabetes, cancer, chronic pulmonary disease, liver disease, heart disease, cerebrovascular disease, and arthritis. CI=Confidence interval; OR=Odds ratio.
For fall-related injuries, age, sex, self-rated health, and BMI were also significant risk factors. Old-old adults had 1.74 times higher odds of experiencing fall-related injuries compared to young-old adults (OR=1.74, 95% CI=1.14~2.65). Females were at 1.71 times higher odds than males (OR=1.71, 95% CI=1.06~2.75). Participants with poor self-rated health had 2.61 times higher odds compared to those with good health (OR=2.61, 95% CI=1.22~5.59). Underweight participants had 3.01 times higher odds of fall-related injuries compared to those with normal BMI (OR=3.01, 95% CI=1.46~6.20) (Table 3).
DISCUSSION
This study aimed to identify the incidence and risk factors for falls and fall-related injuries among older adults in Korea, which has the fastest aging population worldwide. The results showed that age, sex, self-rated health, and BMI were significant risk factors for falls and fall-related injuries among community-dwelling older adults. Using nationally representative longitudinal data and tracking fall events over 4 years, this study builds on previous research on falls among Korean older adults.
The 4-year incidence of falls in this study was 4.6%, which is lower than rates reported in previous international studies. For example, Ooi et al. [12] reported a fall incidence of 17.5% over 18 months among 1,763 adults aged 60 and older in Malaysia. In China, Huang et al. [11] found a 17.4% 2-year incidence among 3,685 adults aged 60 and older. Studies in Australian and Hong Kong reported 1-year fall incidences of 24% [22] and 26.4% [23], respectively. In domestic studies of older adults aged 65 and above, fall incidences ranged from 4.2% to 6.3% [10,13].
The relatively lower incidence observed in this study may result from two main factors. First, differences in measurement, such as the definition of falls and recall periods, may have influenced the results. Unlike studies that included minor slips [22] or used repeated 2-month surveys [23], the KLoSA relied on participants’ recall over a 2-year period, which may have led to underreporting of falls that did not require medical attention. Second, the KLoSA panel data exclude participants who died, were institutionalized, or hospitalized between surveys, which may have contributed to the lower observed incidence. Among those who experienced falls, 79.7% reported fall-related injuries, a rate higher than previously reported rates of 10.2%~69.2% [2,10,22]. This higher proportion may be explained by the survey’s focus on older adults with relatively lower cognitive function and its capture of only medically treated falls, as participants were asked to recall serious incidents over a 2-year period. These differences highlight the importance of considering study population, fall definition, measurement method, survey frequency, and follow-up duration when interpreting and comparing findings across studies [10]. Therefore, when interpreting findings from studies on falls among older adults and comparing them with other research, these factors should be considered.
Consistent with previous research [2,9], this study found that older age is associated with higher risks of falls and fall-related injuries. For example, Gale et al. [9] reported an increased risk of falls with age in a 4-year follow-up of 3,298 adults aged 60 and older in the United Kingdom, and Moreland et al. [2] found that rates of falls and fall-related injuries increased with age, with adults aged 85 and older showing higher rates than those aged 65~74. In this study, old-old adults had 2.01 times higher odds of falls and 1.74 times higher odds of fall-related injuries compared to young-old adults. Many risk factors for falls, such as chronic health conditions, increased medication use, and functional decline, also rise with age [24]. Future research should examine differences in risk factor profiles for falls and fall-related injuries between young-old and old-old adults, and develop targeted interventions based on the combinations of modifiable risk factors identified within each subgroup.
This study found that females had higher risks of falls and fall-related injuries than males, consistent with previous studies [2,10-13]. Possible explanations include lower muscle mass and leg strength in females, which reduce balance and postural recovery, slower gait speed, and greater susceptibility to falls [25]. Although older females in this study were more likely to have multiple chronic conditions and potentially take medications known to increase fall risk [26], the number of medications was not identified as a significant risk factor for falls or fall-related injuries. This may reflect differences in medication types, doses, or the overall health profile of participants, suggesting that factors such as physical function, frailty, or comorbidities may play a more important role in fall risk among older females. Females who have experienced a fall are at higher risk for recurrent falls [27]. Higher rates of fall-related injuries in females may also result from postmenopausal estrogen loss, which decreases bone mineral density and increases osteoporosis prevalence, as well as faster age-related declines in muscle mass and balance, leading to greater injury risk during falls [28]. These findings indicate the need for targeted fall prevention education and interventions for older females and their caregivers.
Poor self-rated health was also a significant risk factor for falls and fall-related injuries, consistent with previous research [4,16,17]. Wang et al. [17] found that self-rated health was linked to a higher risk of falls among 2,968 adults aged 65 and older in Beijing, regardless of age, sex, or urban or rural residence. Suh et al. [16] developed a fall prediction model using machine learning for community-dwelling older adults in Korea and identified satisfaction with one’s own health as the most important predictive factor. Older adults with lower subjective health may have greater fear of falling, reduced activity, and resulting muscle weakness, which contribute to increased fall risk [29]. Self-rated health reflects multiple underlying factors, including physical function, comorbidities, and psychological status, and may serve as a useful indicator for identifying individuals at high risk. Therefore, fall prevention strategies should incorporate a multifactorial approach that considers these underlying factors.
In this study, obesity was linked to a higher risk of falls but not to fall-related injuries, which is partially consistent with previous studies [1,14]. Cho et al. [1] found that among community-dwelling older adults in the United States, those with obesity did not have a significantly greater risk of falls compared to individuals with normal weight, and their likelihood of fall-related injuries was even lower. The association between obesity and falls may be due to reduced lower limb strength and postural instability from excessive fat accumulation, which increases fall risk.
Underweight older adults had a higher risk of both falls and fall-related injuries compared to those with normal weight, partially supporting previous studies that suggest a U-shaped relationship between BMI and falls [15]. However, Huang et al. [11] found that low BMI was independently associated with a lower risk of falls, which does not align with the present study’s findings. The increased risk of falls and fall-related injuries in underweight older adults may be explained by a higher likelihood of frailty and sarcopenia, which are associated with reduced muscle strength, impaired balance, and increased vulnerability to external stressors. In addition, lower bone mineral density in this population may increase susceptibility to injuries when falls occur. Research on this topic is still limited, and further studies are needed. Additionally, because obesity classification criteria differ across studies [13], and some studies have reported that abdominal obesity, as measured by waist circumference, is positively associated with an increased risk of falls and may predict falls more accurately than BMI in older adults [1,30], future studies should examine alternative obesity measures, such as waist circumference, for predicting falls in this population.
In contrast to previous studies, several variables that have been consistently identified as significant risk factors for falls, such as living arrangement [10,13], depression [4,9,12,13], and comorbidities [5,10,13], were not statistically significant in this study. This discrepancy may be explained by differences in study populations, measurement approaches, and analytical methods. For example, variations in the characteristics of the study population, including age distribution and health status, may have influenced the observed associations. In addition, the use of different instruments or categorizations for measuring cognitive and physical function may have affected the results. Furthermore, differences in statistical modeling strategies, including the selection and adjustment of covariates, may also contribute to the inconsistency. Therefore, further studies are needed to clarify these relationships using standardized measurements and longitudinal analytical approaches.
This study has several limitations. First, although this study was based on a prospective cohort design using longitudinal data, the analyses did not account for time-varying changes in risk factors. Therefore, the findings may not fully capture the temporal dynamics of these associations, and future studies applying longitudinal analytical methods that incorporate changes over time are warranted. Second, as a secondary data analysis, some potential risk factors for falls and fall-related injuries could not be included. In addition, cognitive function was assessed using MMSE-K variables from a national survey dataset, and the use of pre-collected standardized data may limit control over measurement procedures, which could affect the accessibility and reproducibility of cognitive assessments in future studies. Third, differences were observed in several baseline characteristics between participants included in the final analysis and those excluded due to missing data or loss to follow-up. In addition, older adults who died or were institutionalized during the follow-up period were not included in the analysis. These exclusions may introduce selection bias and limit the generalizability of the findings. As a result, the associations observed in this study may have been under- or overestimated. Future studies should aim to include these populations to provide more comprehensive estimates of the risk of falls and fall-related injuries.
Despite these limitations, this study is one of the few studies in Korea to examine both the incidence and risk factors of falls and fall-related injuries among community-dwelling older adults using a prospective cohort design, providing important evidence for the development of fall prevention and health promotion strategies.
CONCLUSION
This study examined the incidence of falls and fall-related injuries and their associated risk factors among community-dwelling older adults using nationwide longitudinal data. The results showed that the risk of falls increased with older age, female sex, lower self-rated health, and being underweight or obese. For fall-related injuries, older age, female sex, lower self-rated health, and being underweight were identified as risk factors, whereas obesity was associated with falls but not significantly with fall-related injuries.
These findings suggest that falls and fall-related injuries in older adults are complex health issues influenced by multiple dimensions of health. In particular, self-rated health, which reflects an individual’s overall physical, psychological, and functional status, was associated with an increased risk of falls. Therefore, fall prevention strategies should incorporate comprehensive assessments that consider both objective health conditions and individuals’ perceived health status. Future research should further identify risk factors for falls and fall-related injuries and develop and implement education and intervention programs based on these findings.
Footnotes
Authors' contribution
Study conception and design - BH and SK; Data collection - BH and SK; Analysis and interpretation - BH and SK; Writing–original draft & review & editing - BH and SK; Final approval - BH and SK
Conflict of interest
No existing or potential conflict of interest relevant to this article was reported.
Funding
None.
Data availability
Please contact the corresponding author for data availability.
Acknowledgements
None.
Supplementary materials
Comparison of Baseline Characteristics Between Included and Excluded Participants
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Comparison of Baseline Characteristics Between Included and Excluded Participants