Age and Gender Differences in Fall-Related Factors Affecting Community-Dwelling Older Adults : Journal of Nursing Research

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Age and Gender Differences in Fall-Related Factors Affecting Community-Dwelling Older Adults

SUH, Minhee1; KIM, Da Hye2; CHO, Insook3; HAM, Ok Kyung3,*

Author Information
Journal of Nursing Research ():10.1097/jnr.0000000000000545, March 4, 2023. | DOI: 10.1097/jnr.0000000000000545
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Falls, one of the major adverse events affecting older adults, lead to serious injuries. Hospitalizations because of fall-related injuries have been increasing (Moreland et al., 2021), and deaths because of falls have risen 30% between 2007 and 2016 (Burns & Kakara, 2018). The older adult population in South Korea is projected to roughly double from 16.5% in 2021 to 32.3% in 2038 (Statistics Korea, 2019). Moreover, falls are expected to become a more prominent issue, as they are considered a significant cause of mortality in older adults (Burns & Kakara, 2018). Research results point to a high risk of fall events during acute episodes of disease and accidental falls coupled with comorbidities leading to life-threatening consequences in older adults (K. Zhang et al., 2022). These authors also noted that older adults may become increasingly frail as they age, increasing the risk of falls and reducing their ability to survive the resultant injuries.

Falls may be prevented by timely screening for fall risk factors and implementing related interventions. Although several multifactorial interventions and tailored fall-prevention programs have been tested, a recent meta-analysis revealed that some of these interventions do not produce sufficient changes and that challenges because of barriers such as attrition and adherence remain (Oluwaseyi et al., 2018). Another meta-analysis suggested that local community characteristics must be considered to develop truly effective fall interventions (Hill et al., 2018).

The occurrence of falls among older adults differs by age and gender. Older adults in the oldest age group (over 75 years) and older women have been reported to face the highest risk of falls (Wu & Ouyang, 2017) and fall-related mortality (Alamgir et al., 2012). The causes of falls may differ in these groups from those in other groups and may reflect age- and gender-related changes in physical and mental functions. Specifically, decreasing limb-muscle strength and physical performance has been identified as a major risk factor for falls (Kawabata et al., 2021) and may play a crucial role in the fall risk faced by women and by individuals in the oldest age group, as these groups are most vulnerable to these factors (Nakano et al., 2014; Winger et al., 2021). Although regular exercise is currently encouraged for community-dwelling older adults to increase their motor skills and physical performance, it is unclear how much exercise is required to effectively prevent falls. Nevertheless, few studies have examined the physical condition and exercise habits of older adults, and even fewer have analyzed the effects of age and gender on fall risk factors in large older adult study samples.

In addition to physical status, other complex factors are also known to contribute to falls in older adults (Chen et al., 2021). Factors previously suggested include impaired physical condition, neuropsychological deficits, visual acuity, multimorbidity, number of medications, and dependency in activities of daily living (ADLs; Bloch et al., 2010). However, few researchers have analyzed fall risk factors considering multiple dimensions of health based on the biopsychosocial model targeting Korean older adults. The biopsychosocial model posits that health issues result from interactions among biological, psychological, and social factors (Wade & Halligan, 2017). As this model adds the social, psychological, and behavioral dimensions of health to the classic biomedical model (Engel, 1981), it may offer a favorable framework for conducting a systemic analysis of complex and multifaceted fall risk factors. In applying the biopsychosocial model, studies involving multifactorial analyses are needed to address the independent influence of each factor on falls stratified by age and gender to help researchers develop effective strategies tailored to the needs of different age and gender groups.

The aim of this study was to use a biopsychosocial model to investigate the prevalence of falls among older adults living in the community; to assess their exercise habits, lower-limb muscle strength, and physical performance; and to elucidate the significant fall-contributing factors by age and gender.


Study Population

This cross-sectional study was based on data from the 2017 National Survey of Older Koreans. This nationwide, 3-year interval survey is regularly conducted by the Ministry of Health and Welfare in Korea. The 2017 survey covered 17 metropolitan areas and provinces in Korea using a proportional two-stage stratified cluster sampling method. First, the data were stratified by Korea's seven constituent metropolitan areas, nine constituent provinces, and Sejong (a self-governing city), with the nine provinces and Sejong city further stratified by urban (neighborhood) and rural (town and township) areas (Ministry of Health and Welfare [MOHW] & Korea Institute of Health and Social Affairs [KIHASA], 2017). The data were obtained via face-to-face interviews conducted by well-trained interviewers from June 12 to August 28, 2017. The 2017 National Survey of Older Koreans included 10,299 individuals aged ≥ 65 years living in standard housing. The raw data used in this study were obtained on December 5, 2020, from the Health and Welfare Data Portal ( Of the 10,299 responses, 226 proxy responses were excluded to increase data accuracy. Overall, the data from 10,073 older adults (response rate: 97.8%) were included in the final analysis. The study was approved by the institutional review board with which all of the authors were affiliated (200825-2A).


The biopsychosocial model proposed by Engel (1981) was used in this study to highlight the contributions of biological, psychological, and social factors to determining an individual's health concerns. After the use of meta-analysis and the application of the International Classification of Functioning on fall predictors in previous studies (Bloch et al., 2010; Soh et al., 2020), the selected fall-related factors were integrated into the biopsychosocial model. In this study, the fall-related biological factors were chronic diseases, number of medications, visual difficulties, ADL dependence, lower-limb muscle strength, and physical performance; the fall-related psychological factors were depression, cognitive ability, regular smoking, alcohol consumption in the last year, nutritional status, and exercise; and the fall-related social factors were educational level, annual income, living conditions, and instrumental ADL (IADL) dependence.

Demographic and health-related characteristics

The demographic characteristics considered in this study included age, gender, years of education, marital status, living conditions, and household income. The participants were divided into two age categories: young–old (< 75 years) and old–old (≥ 75 years; Yoshimura et al., 2013).

The health-related characteristics considered in this study included number of chronic diseases, number of medications currently taken, nutritional status, ADL and IADL dependence, level of depression, cognitive status, smoking status, and alcohol consumption in the past year. Nutritional status was evaluated using the Nutritional Screening Initiative checklist (Posner et al., 1993), which includes 10 items and a total checklist score range of 0–21. Each participant was asked to circle the item corresponding to their situation, and each item was assigned a weighted score ranging from 1 to 4. Circling no items resulted in a total checklist score of 0, whereas circling all 10 items resulted in a total checklist score of 21 (Posner et al., 1993), with 0–2 indicating adequate nutritional status, 3–5 indicating at-risk nutritional status, and ≥ 6 indicating malnourishment. ADL and IADL dependence statuses were assessed using the Korean version of the ADL scale (Won, Rho, Kim et al., 2002) and the Korean version of the IADL scale (Won, Rho, SunWoo et al., 2002). The Korean version of the ADL scale comprises seven questions on basic self-care abilities such as hygiene, bathing, dressing, eating, toileting, control of urination and defecation, and indoor activities. The Korean version of the IADL scale contains 10 questions on abilities related to grooming, going out, shopping, food preparation, housekeeping, laundry, transportation, using the telephone, self-medication, and handling finances. Each item is scored from 1 (completely independent) to 3 or 4 (completely dependent). Depression level was measured using the Geriatric Depression Scale-Short Form (GDS-SF), Korean Version (Kee, 1996). The GDS-SF Korean Version consists of 15 items in a binary response format (yes/no) with a total score ranging from 0 to 15 and higher scores indicating a more severe level of depression. The Cronbach's alpha of the GDS-SF has been calculated as .80 (Park et al., 2017) and was calculated as .89 in this study. Cognitive status was assessed using the Mini-Mental Status Examination for Dementia Screening (MMSE-DS; Seoul National University Bundang Hospital, 2009). The MMSE-DS consists of 19 items. Each item is weighted from 1 to 5 for a maximum score of 30, with higher scores indicating better cognitive status.


The participants were asked whether they had fallen (or slipped) within the past 12 months for any reason and regardless of whether the incident had resulted in injury. The respondents were considered to have experienced a fall if they answered “yes” to the question. Number of falls, reasons for falls, and related medical treatments were also recorded.

Lower-limb muscle strength

A five-times sit-to-stand test (FSTST) was performed to assess lower-limb muscle strength (F. Zhang et al., 2013). Older adults were instructed to stand up and sit down 5 times from a 45-cm-high chair or bed, with a score assigned between 1 and 4 (1 representing “unable to perform,” 2 representing “very difficult to perform,” 3 representing “slightly difficult to perform,” and 4 representing “able to perform without difficulties”) and higher scores indicating stronger lower-limb muscle strength.

Physical performance

Physical performance was evaluated using five items related to mobility from the Physical Functioning Scale developed by Lee et al. (2002). These items respectively assess ability to run 400 meters, climb 10 steps without a break, kneel or squat, reach out to an object overhead, and lift an object ≥ 8 kg. Each item is scored from 1 to 4 (1 representing “unable to perform,” 2 representing “very difficult to perform,” 3 representing “slightly difficult to perform,” 4 representing “able to perform without difficulties”), with higher score indicating better physical performance. The Cronbach's alpha of the physical functioning scale was previously calculated as .81 (H. Kim & Park, 2014).


The question “Do you exercise regularly?” was asked to determine whether the participants exercised regularly. Exercise frequency and duration were respectively determined using the questions “How often do you exercise?” and “How long do you exercise in a single workout?” The answer to the exercise frequency question was scored from 0 to 2 (0 = none, 1 = 1–2 times per week, and 2 = ≥ 3 times per week). The answer to the exercise duration question was scored from 0 to 3 (0 = none, 1 = < 30 minutes, 2 = 30–59 minutes, and 3 = ≥ 60 minutes).


On the basis of the 2014 National Survey of Older Koreans questionnaire, a panel of experts (25 professors and researchers in the fields of public health and gerontology) reviewed and provided comments for further refinement of the study instruments. The instruments were revised by the research team members based on recommendations from the panel of experts. The revised instruments were pretested with 45 older adults in Korea. After the pretest, some items were deleted, the order of some items was adjusted, and answer choices for the multiple-choice questions were added (MOHW & KIHASA, 2017).

Sixty trained interviewers and 15 supervisors were involved in collecting data. The interviewers were divided into 15 teams, with four in each group, and each team was supervised by one supervisor. The survey was conducted in a presampled survey area. All of the households in the survey area were visited by trained interviewers, and all residents aged ≥ 65 years living in those households were interviewed for data collection purposes. Data collection was continued until the requisite number of older adults in the survey area had completed the questionnaire (i.e., 10 older adults in urban areas and 20 older adults in rural areas; MOHW & KIHASA, 2017).

Data Analysis

IBM SPSS Statistics Version 25 for Windows (IBM Inc., Armonk, NY, USA) was used for the analysis. Descriptive statistics (means, standard deviations, frequencies, and percentages) were used to describe general and health-related characteristics. Chi-square tests were performed to analyze age- and gender-related differences in the participants' physical performance. Finally, logistic regression analyses were performed to identify the significant age- and gender-related factors associated with falls among the participants. Our logistic regression analysis included the fac­tors significant for fall in univariate analysis.


Demographic and Health-Related Characteristics of the Participants

The general characteristics of the study population are summarized in Table 1. The mean age was 73.9 years (SD = 6.54, range: 65–106 years), and 4,224 (41.9%) participants were in the old–old group (≥ 75 years old). Of the 10,073 participants, 5,787 (57.5%) were women. The average educational level was 7.18 years (SD = 4.59). Most participants were married, and 3,138 (31.2%) were widowed. Twenty-four percent (n = 2,416) lived alone. The mean annual income per household was 25,710,000 (equivalent to 24,000 USD). The average number of chronic diseases diagnosed by physicians and the total medications currently taken were 2.7 (SD = 1.84) and 4.1 (SD = 3.41), respectively. Thirty-four percent (n = 3,409) of the participants had visual difficulties. Of the sample, 9,369 (93.0%) and 7,766 (77.1%) participants were completely independent in terms of ADLs and IADLs, respectively. The average depression score was 4.1 (SD = 4.08), and the average MMSE-DS score was 25.2 (SD = 3.84). One thousand twenty-nine (10.2%) older adults were regular smokers, and the average number of times they consumed alcohol during the last year was 1.1 (SD = 2.09). The nutritional status was “adequate” for 4,102 (40.7%) of the participants.

Table 1 - Participant Demographic and Health-Related Characteristics (N = 10,073)
Variable n % Median IQR
Age (years; M and SD) 73.9 6.54 73.00 10
 Young–old adults < 75 years 5,849 58.1
 Old–old adults ≥ 75 years 4,224 41.9
 Male 4,286 42.5
 Female 5,787 57.5
Education (years; M and SD) 7.18 4.59 6.00 6
Marital status
 Married 6,416 63.7
 Widowed 3,138 31.2
 Divorced 365 3.6
 Other 154 1.5
Living alone
 Yes 2,416 24.0
 No 7,657 76.0
Household income (10k, KRW; M and SD) 2,571.9 2,244.32 1,888.62 2,202
Number of chronic diseases (M and SD) 2.7 1.84 3.00 3
Diseases diagnosed
 Hypertension 5,945 59.0
 Anemia 215 2.1
 Benign prostrate  hypertrophy 893 8.9
 Thyroid disease 328 3.3
Total number of medications (M and SD) 4.1 3.41 3.00 5
Visual difficulty
 Yes 3,409 33.8
 No 6,664 66.2
 Completely independent 9,369 93.0
 Help needed 704 7.0
 Completely independent 7,766 77.1
 Help needed ≤ 4 domains 1,549 15.4
 Help needed ≥ 5 domains 758 7.5
Depression (M and SD) 4.1 4.08 3.00 15
MMSE (M and SD) 25.2 3.84 26.00 5
Regular smoking
 Yes 1,029 10.2
 No 9,044 89.8
Number of drinks during the last 1 year (M and SD) 1.1 2.09 0.00 1
Nutritional status
 Adequate 4,102 40.7
 At risk 3,646 39.2
 Malnutrition 2,025 20.1
Fall experience during the last 1 year
 Yes 1,585 15.7
 No 8,488 84.3
Number of falls (n = 1,585)
 1 time 1,035 65.3
 ≥ 2 times 550 34.7
Treatment because of fall injury (n = 1,585)
 Yes 1,032 65.1
 No 553 34.9
Fall reason (n = 1,585)
 Slippery surface 427 26.9
 Wobbly leg 306 19.3
 Tripping over something 266 16.8
 Losing one's footing 224 14.2
 Sudden dizziness 184 11.6
 Steep slope 59 3.7
 Others 119 7.5
Note. IQR = interquartile range; ADL = activity of daily living; IADL = instrumental activity of daily living; MMSE = Mini-Mental Status Examination.

Of the 10,073 participants, 1,585 (15.7%) had experienced falls during the last year, 550 (34.7%) of whom had fallen more than twice. The major causes of falls were slippery surfaces and wobbly legs. One thousand thirty-two (65.1%) of those who fell received treatment because of their fall-related injury during the previous year.

Lower-Limb Muscle Strength, Physical Performance, and Exercise by Age and Gender

In terms of lower-limb muscle strength, 8,055 (80.0%) of the participants were able to sit and stand 5 times without difficulty (Table 2). Significantly fewer older adults in the old–old group (p < .001 for both men and women) and female group (p < .001 for both young and old age groups) were able to finish the test. In terms of physical performance, 1,589 (15.8%) and 5,741 (57.0%) participants were able to run 400 m and climb 10 stairs without difficulty, respectively. Furthermore, 8,743 (86.8%) participants were able to reach out and touch objects overhead, and 7,226 (71.7%) were able to lift or move objects weighing ≥ 8 kg. Significantly fewer older adults in the old–old group (p < .001 in both men and women) and female participants (p < .001 in both young–old and old–old age groups) were able to perform either activity. Of the entire sample, 6,854 (68.0%) exercised regularly, 6,096 (60.5%) exercised more than 3 times a week, and 3,352 (33.3%) exercised more than 60 minutes per session. The young–old group reported significantly more regular exercise (p = .005 in men, p < .001 in women), more frequent exercise sessions (p < .001 in both men and women), and longer exercise periods (p < .001 in both men and women) than the old–old group. Older women exercised significantly less than their male counterparts in the old–old group in terms of regularity (p < .001), frequency (p < .001), and duration (p < .001).

Table 2 - Descriptive Statistics of Lower Limb Muscle Strength, Physical Performance, and Exercise, by Age and Gender (N = 10,073)
Variable Total Young–Old Group
(< 75 Years Old)
Old–Old Group
(≥ 75 Years)
n % Male Female Male Female
n % n % n % n %
Five-times sit-to-stand test
 Unable to stand 80 0.8 12 0.5*** 12 0.4***,††† 18 1.0 38 1.5†††
 Having slight difficulties 1,938 19.2 142 5.6 468 14.1 344 19.6 984 39.8
 Able to stand 8,055 80.0 2,382 93.9 2,833 85.5 1,389 79.3 1,451 58.7
Physical performance
 Run 400 m (n = 10,057)
  Unable to perform 1,888 18.8 196 7.7*** 568 17.2***,††† 328 18.8 796 32.2†††
  Very difficult to perform 3,425 34.1 524 20.7 1,112 33.6 643 36.8 1,146 46.4
  Having slight difficulties 3,155 31.4 938 37.0 1,161 35.1 577 33.0 479 19.4
  Able to perform 1,589 15.8 877 34.6 465 14.1 199 11.4 48 1.9
 Climb 10 stairs without rest
  Unable to perform 334 3.3 29 1.1*** 69 70.4***,††† 63 3.6 173 7.0†††
  Very difficult to perform 1,212 12.0 108 4.3 332 10.0 192 11.0 580 23.5
  Having slight difficulties 2,786 27.7 315 12.5 913 27.5 508 29.0 1,050 42.4
  Able to perform 5,741 57.0 2,083 82.1 2,000 60.3 988 56.4 670 27.1
 Kneeling or squatting
  Unable to perform 423 4.2 29 1.1*** 159 4.8***,††† 58 3.3 177 7.2†††
  Very difficult to perform 1,141 11.3 114 4.5 375 11.3 159 9.1 493 19.9
  Having slight difficulties 2,621 26.0 309 12.2 829 25.0 451 25.7 1,032 41.7
  Able to perform 5,888 58.5 2,084 82.2 1,950 58.9 1,083 61.9 771 31.2
 Reach out and touch object over the head (n = 10,072)
  Unable to perform 33 0.3 1 0.0*** 10 0.3***,††† 7 0.4 15 0.6†††
  Very difficult to perform 249 2.5 23 0.9 57 1.7 28 1.6 140 5.7
  Having slight difficulties 1,047 10.4 85 3.4 254 7.7 167 9.5 542 21.9
  Able to perform 8,743 86.8 2,426 95.7 2,991 90.3 1,548 88.5 1,777 71.8
 Lift or move objects of 8 kg
  Unable to perform 265 2.6 24 0.9*** 54 1.6***,††† 40 2.3 147 5.9†††
  Very difficult to perform 797 7.9 47 1.9 231 7.0 101 5.8 419 16.9
  Having slight difficulties 1,785 17.7 141 5.6 558 79.8 275 15.7 811 32.8
  Able to perform 7,226 71.7 2,323 91.6 2,472 74.6 1,333 76.2 1,098 44.4
Regular exercise
 Yes 6,854 68.0 1,843 72.7** 2,387 72.0*** 1,207 69.0 1,417 57.3†††
Exercise frequency
 No exercise 3,220 32.0 693 27.3*** 927 28.0*** 543 31.0 1,057 42.7†††
 1–2 times/week 757 7.5 215 8.5 272 8.2 86 31.9 184 7.4
 ≥ 3 times/week 6,096 60.5 1,628 64.2 2,114 63.8 1,121 64.1 1,233 49.8
Exercise duration
 No exercise 3,220 32.0 693 27.3*** 927 28.0*** 543 31.0 1,057 42.7†††
 < 30 minutes 876 8.7 145 5.7 261 7.9 151 8.6 318 12.9
 30–59 minutes 2,625 26.1 563 22.2 987 29.8 443 25.3 632 25.6
 ≥ 60 minutes 3,352 33.3 1,135 44.8 1,138 34.4 613 35.0 466 18.8
*p < .05, **p < .01, ***p < .001: for difference between age groups; p < .05, ††p < .01, †††p < .001: for difference between men and women.

Factors Associated With Falls in Older Adults

A logistic regression analysis for fall-contributing factors among the older men showed that falls were independently associated with taking more medications in both the young–old (OR = 1.069, p = .015) and old–old (OR = 1.051, p = .038) groups (Table 3). Moreover, falls were negatively associated with physical performance in terms of ability to run 400 m (OR = 0.662, p < .001) and ability to kneel or squat (OR = 0.672, p < .001) in the young–old group. Falls were also independently associated with higher levels of depression (OR = 1.051, p = .016). In the old–old group, falls were independently related to having higher numbers of chronic diseases (OR = 1.125, p = .026), dependency in ADLs (OR = 1.844, p = .045), and ability to climb 10 stairs (OR = 1.502, p = .006; Table 3).

Table 3 - Factors Associated With Falls in Male Participants (N = 4,286)
Variable Young–Old Group (< 75 Years Old) Old–Old Group (≥ 75 Years)
β Exp(β) 95% CI β Exp(β) 95% CI
Biological factors
 No. of chronic diseases .086 1.089 [0.974,1.218] .118 1.125* [1.014, 1.248]
 No. of total medication .067 1.069* [1.013, 1.128] .050 1.051* [1.003, 1.102]
 Visual difficulty: yes .131 1.140 [0.836, 1.556] .073 1.076 [0.804, 1.440]
 ADL dependent −.481 0.618 [0.245, 1.559] .612 1.844* [1.014, 3.353]
 Lower limb muscle strength .124 1.132 [0.674, 1.904] −.159 0.853 [0.578, 1.259]
 Physical performance
  Run 400 m −.412 0.662*** [0.545, 0.805] −133 0.876 [0.710, 1.080]
  Climbing steps .254 1.289 [0.946, 1.756] .407 1.502** [1.125, 2.006]
  Kneeling or squatting −.397 0.672*** [0.520, 0.869] −.211 0.810 [0.631, 1.039]
  Reaching out −.012 0.988 [0.631, 1.547] −.159 0.853 [0.593, 1.227]
  Lifting −.129 0.879 [0.836, 1.556] −.064 0.938 [0.709, 1.241]
Psychological factors
Depression .049 1.051* [1.009, 1.094] .034 1.035 [0.995, 1.076]
 MMSE −.008 0.992 [0.942, 1.045]
 Nutritional status: adequate (ref.)
  At risk −.005 0.978 [0.699, 1.417] .047 1.049 [0.738, 1.489]
  Malnutrition .085 1.088 [0.692, 1.712] .011 1.011 [0.646, 1.580]
 Exercise frequency .063 1.065 [0.784, 1.448] −.086 0.918 [0.678, 0.242]
 Exercise duration −.059 0.943 [0.754, 1.180] .012 1.012 [0.800, 1.280]
Social factors
 Education years .011 1.011 [0.970, 1.053]
 IADL dependent .262 1.299 [0.873, 1.935] −.084 0.920 [0.691, 1.223]
Note. Variables that were found to be significantly associated with falls in bivariate analyses were included in the logistic model for each age group. CI = confidence interval; ADL = activity of daily living; MMSE = Mini-Mental Status Examination; ref. = reference; IADL = Instrumental activity of daily living.
*p < .05. **p < .01. ***p < .001.

For the older women, falls were found to be negatively associated with physical performance related to kneeling or squatting in both the young–old (OR = 0.776, p = .001) and old–old (OR = 0.827, p = .017) groups (Table 4). Greater depression was also independently related to falls in both the young–old (OR = 1.080, p < .001) and old–old (OR = 1.053, p < .001) groups. In the young–old group, falls were independently associated with dependency in terms of ADLs (OR = 1.775, p = .013) and poor nutritional status (OR = 1.304, p = .025). In the old–old group, falls were independently related to having higher numbers of chronic diseases (OR = 1.080, p = .028), dependency in IADLs (OR = 1.246, p = .010), and malnutrition status (OR = 1.642, p = .003).

Table 4 - Factors Associated With Falls in Female Participants (N = 5,787)
Variable Young–Old Group (< 75 Years Old) Old–Old Group (≥ 75 Years)
β Exp(β) 95% CI β Exp(β) 95% CI
Biological factors
 No. of chronic diseases .015 1.015 [0.948, 1.086] .077 1.080* [1.008, 1.158]
 No. of total medication .013 1.013 [0.977, 1.051] −.020 0.981 [0.944, 1.019]
 Visual difficulty: yes −.016 0.984 [0.802, 1.209] .077 1.080 [0.879, 1.327]
 ADL dependent .574 1.775* [1.128, 2.792] .064 1.066 [0.789, 1.441]
 Lower limb muscle strength −.018 0.982 [0.742, 1.301] .003 1.003 [0.796, 1.263]
 Physical performance
  Run 400 m −.098 0.906 [0.790, 1.040] −.125 0.883 [0.743, 1.049]
  Climbing steps .083 1.087 [0.904, 1.307] .026 1.027 [0.855, 1.232]
  Kneeling or squatting −.254 0.776** [0.670, 0.898] −.189 0.827* [0.708, 0.967]
  Reaching out −.226 0.798 [0.635, 1.003] .009 1.010 [0.839, 1.215]
  Lifting .010 1.010 [0.857, 1.191] −.024 0.976 [0.841, 1.133]
Psychological factors
Depression .077 1.080*** [1.053, 1.108] .051 1.053*** [1.026, 1.080]
 MMSE .024 1.024 [0.993, 1.056] .019 1.019 [0.995, 1.044]
 No. of drinking for the last 1 year .070 1.072 [0.994, 1.157]
 Nutritional status: adequate (ref.)
  At risk .266 1.304* [1.034, 1.644] .272 1.312 [0.979, 1.759]
  Malnutrition .265 1.303 [0.961, 1.768] .496 1.642** [1.182, 2.281]
 Exercise frequency .077 1.080 [0.894, 1.305] .143 1.154 [0.956, 1.392]
 Exercise duration −.037 0.964 [0.834, 1.114] −.078 0.925 [0.787, 1.087]
Social factors
 Household income .000 1.000 [1.000, 1.000]
 Living alone .182 1.199 [0.968, 1.486] .180 1.197 [0.953, 1.504]
 IADL dependent −.027 0.973 [0.773, 2.225] .220 1.246* [1.053, 1.474]
Note. Variables that were found to be significantly associated with falls in bivariate analyses were included in the logistic model for each age group. CI = confidence interval; ADL = activity of daily living; MMSE = Mini-Mental Status Examination; ref. = reference; IADL = Instrumental activity of daily living.
*p < .05. **p < .01. ***p < .001.


This was the first comprehensive study to investigate the characteristics of falls and related biological, psychological, and social factors in older adults. Using a biopsychosocial model, a multivariate analysis was conducted to determine the most prominent factors contributing to falls by age group and gender in a large population of older adults.

Prevalence of Falls and Related Characteristics

In this study, the prevalence of falls and multiple falls among the participants was 15.7% and 5.5%, respectively. These numbers are significantly lower than the respective 32.3% and 11.7% found among older German adults in a previous study (Just et al., 2021). The difference may be because of variations in the physical status of the study populations. Only 0.8% of our study population was unable to perform the FSTST, whereas 4.2% were unable to perform the FSTST in Just et al. (2021). The frailer status of the community-dwelling older adults in that previous study may have led to the higher observed fall prevalence (Chittrakul et al., 2020). Racial differences may also contribute to differences in fall prevalence. In a previous study, older Asian adults were reported to be less likely to fall than older adults in other ethnic groups (Wehner-Hewson et al., 2022). Similar to the findings in this study, the prevalence of multiple falls was found to be 6.7% among Chinese older adults in another study, with multiple falls further found to be associated with physical frailty (OR = 6.79; Ma et al., 2021). However, the findings of this study showed that most of the participants who fell were not physically frail. Nevertheless, the 65.1% of participants who received treatment because of fall-related injuries in this study was much higher than the average 36.9% of Korean adults overall who receive fall-related treatments (M.-S. Kim et al., 2021). Thus, more attention should be paid to preventing falls in older adults.

Factors Associated With Falls in Older Men and Women

When analyzing the factors associated with falls according by age group and gender, inability to kneel or squat (and not exercise habits) was shown to significantly relate to falls in all older adult groups with the exception of men in the old–old (≥ 75) group. This is in line with a previous study that addressed the importance of strength in the knee extensor/flexor and ankle plantarflexor/dorsiflexor muscles during falls (Sohng & Choi, 2007). Moreover, contrary to expectations, this factor's influence on falls was greater in the men than the women, although physical conditions, such as lower-limb muscle strength and physical performance, were better among the men. In addition, the findings of this study highlighted that inability to kneel or squat outweighed overall lower-limb muscle strength in terms of impact on fall-related experiences, making kneel/squat ability an important fall-related factor (Ahmadiahangar et al., 2018). Thus, improving this ability should be encouraged along with enhancing lower-limb muscle strength. In particular, for fall prevention in older adult men, assessing ongoing ability to kneel or squat may be more beneficial than assessing FSTST. Interestingly, men in the old–old group who performed better on climbing 10 steps were 1.5 times more likely to experience falls. Stairway falls are prevalent in older adults (Jacobs, 2016). This may be that, although those who use stairs more often in their daily lives performed better on the stair climbing test, they are at a higher risk of stairway falls in daily life. Furthermore, older adult men have reported less fear of falling (Chamroonkiadtikun et al., 2021) and lower fall risk perception (Welk et al., 2015) than older adult women. This subjective perception may increase fall-related accidents when using stairs, especially when accompanied by attenuated physical ability among men in the old–old adult population. Thus, safety-focused education on the use of stairs to prevent falls should be reinforced for fall prevention in adults older than 75 years.

Number of medications taken was found to be independently associated with falls in the male participants but not in the female participants in this study, although the men reported taking fewer medications. This may imply that older adult men are more likely to take medications that increase fall risk. Prostate-selective α-antagonists and thyroid therapy medications have recently been associated with increased fall risk (Kvelde et al., 2013). In this study, 20.8% of the older adult men were receiving benign prostate enlargement treatment, and significantly more men than women were receiving thyroid therapy. These factors may have contributed to the identified association between medication and falls among the male participants. A careful review of medications is necessary to prevent falls, especially in older adult men.

Among the psychological factors studied, depression was found to be significantly associated with falls in all older adult groups with the exception of men in the old–old group. However, it was a secondary factor with low ORs, followed by the influence of physical performance. This result is consistent with that of a previous meta-analysis that addressed the relationship between depression and falls (Kamińska et al., 2015). However, another study reported no association between depression and falls when depression was included in a multivariate analysis alongside physical functioning (Jo et al., 2020). Regarding the low ORs of depression and its nonsignificant association in the male old–old group in the multivariate analysis, the influence of depression on falls may have been more attenuated by age and gender in the study population. Nevertheless, as depression was still shown to be independently associated with falls, especially in older adult women, it should be considered in fall prevention programs along with physical performance.

For older adult women, poor nutritional status and issues with ADL/IADL dependence were found to be independently associated with falls, which echoes the findings of Chien and Guo (2014). The findings of this study suggest that biological, psychological, and social factors may act in complex ways that, in combination, have a greater influence on falls in older adult women than physical performance. Poor nutrition in older adults has been shown to exacerbate anemia symptoms, such as dizziness or fatigue (Bianchi, 2016) and physical frailty (Kiuchi et al., 2021), and may significantly impact fall risk. Because older women are traditionally in charge of shopping and cooking for the family, restrictions in ADLs/IADLs and nutritional deficiencies caused by decreased muscle strength or physical performance may have a greater impact on their fall-related accidents than physical ability. Therefore, strategies should be developed to improve the nutritional status and ADL/IADL performance of older women to reduce fall risk.


This study was affected by several limitations. First, the use of cross-sectional secondary data leaves the cause-and-effect relationships among variables unclear. Therefore, the findings should be verified using prospective studies. Second, fall-related experiences were assessed using self-reported data, which may be affected by recall bias. Third, data collection was performed in a community setting in Korea. Thus, caution should be taken when generalizing the results to other settings or countries. Finally, as this study utilized secondary data, environmental factors that may have influenced fall risk could not be assessed.


The findings of this study indicate that the prominent factors contributing to falls differ between men and women. The major factors contributing to falls in the older men in this study were biological, including physical performance (kneeling or squatting) and number of medications taken. Among the older women in this study, the major fall-related factors were nutritional status, IADL dependence, and presence of chronic diseases. ADL dependence, physical performance (kneeling or squatting), and depression were associated with falls in both gender groups, implying that the three dimensions of the biopsychosocial model interact in a complex manner in terms of fall risk. On the basis of these findings, an effective fall-prevention strategy for older adults, especially men, should include continuing to practice kneeling and squatting as well as reviewing medication lists. Safety education on using stairs to prevent falls should be reinforced in men ≥ 75 years old. Moreover, fall prevention strategies for older women should include improving nutritional status and ADL/IADL dependence. Depression, rather than cognitive impairment, should be considered for fall prevention along with physical performance.


This study was supported by the Incheon Public Health Policy Institute.

Author Contributions

Study conception and design: All authors

Data collection: MS, DHK

Data analysis and interpretation: MS, DHK

Drafting of the article: MS, DHK

Critical revision of the article: MS, OKH


Ahmadiahangar A., Javadian Y., Babaei M., Heidari B., Hosseini S., Aminzadeh M. (2018). The role of quadriceps muscle strength in the development of falls in the elderly people, a cross-sectional study. Chiropractic & Manual Therapies, 26(1), Article No. 31.
Alamgir H., Muazzam S., Nasrullah M. (2012). Unintentional falls mortality among elderly in the United States: Time for action. Injury, 43(12), 2065–2071.
Bianchi V. E. (2016). Role of nutrition on anemia in elderly. Clinical Nutrition ESPEN, 11, e1–e11.
Bloch F., Thibaud M., Dugué B., Brèque C., Rigaud A. S., Kemoun G. (2010). Episodes of falling among elderly people: A systematic review and meta-analysis of social and demographic pre-disposing characteristics. Clinics (Sao Paulo, Brazil), 65(9), 895–903.
Burns E., Kakara R. (2018). Deaths from falls among persons aged ≥ 65 years—United States, 2007–2016. Morbidity and Mortality Weekly Report, 67(18), 509–514.
Chamroonkiadtikun P., Ananchaisarp T., Wajancomkul P. (2021). The prevalence and associated factors of the fear of falling in elderly patients at the primary care clinic of Songklanagarind hospital. Topics in Geriatric Rehabilitation, 37(1), 44–49.
Chen X., Lin Z., Gao R., Yang Y., Li L. (2021). Prevalence and associated factors of falls among older adults between urban and rural areas of Shantou City, China. International Journal of Environmental Research and Public Health, 18(13), Article 7050.
Chien M.-H., Guo H.-R. (2014). Nutritional status and falls in community-dwelling older people: A longitudinal study of a population-based random sample. PLOS ONE, 9(3), Article e91044.
Chittrakul J., Siviroj P., Sungkarat S., Sapbamrer R., Sapbamrer R. (2020). Physical frailty and fall risk in community-dwelling older adults: A cross-sectional study. Journal of Aging Research, 2020, Article ID 3964973.
Engel G. L. (1981). The clinical application of the biopsychosocial model. The Journal of Medicine and Philosophy, 6(2), 101–124.
Hill K. D., Suttanon P., Lin S. I., Tsang W. W. N., Ashari A., Hamid T. A. A., Farrier K., Burton E. (2018). What works in falls prevention in Asia: A systematic review and meta-analysis of randomized controlled trials. BMC Geriatrics, 18(1), Article No. 3.
Jacobs J. V. (2016). A review of stairway falls and stair negotiation: Lessons learned and future needs to reduce injury. Gait & Posture, 49, 159–167.
Jo A. R., Park M. J., Lee B. G., Seo Y. G., Song H. J., Paek Y. J., Park K. H., Noh H. M. (2020). Association between falls and nutritional status of community-dwelling elderly people in Korea. Korean Journal of Family Medicine, 41(2), 111–118. (Original work published in Korean)
Just K. S., Dallmeier D., Böhme M., Steffens M., Braisch U., Denkinger M. D., Rothenbacher D., Stingl J. C. (2021). Fall-associated drugs in community-dwelling older adults: Results from the ActiFE Ulm atudy. The Society of Post-Acute and Long-Term Care Medicine, 22(10), 2177–2183.E10.
Kamińska M. S., Brodowski J., Karakiewicz B. (2015). Fall risk factors in community-dwelling elderly depending on their physical function, cognitive status and symptoms of depression. International Journal of Environmental Research and Public Health, 12(4), 3406–3416.
Kawabata K., Matsumoto T., Kasai T., Chang S. H., Hirose J., Tanaka S. (2021). Association between fall history and performance-based physical function and postural sway in patients with rheumatoid arthritis. Modern Rheumatology, 31(2), 373–379.
Kee B. S. (1996). A preliminary study for the standardization of Geriatric Depression Scale Short Form-Korea version. Journal of Korean Neuropsychiatric Association, 35(2), 298–307. (Original work published in Korean)
Kim H., Park M. (2014). Physical function and ego-integrity in frail and non-frail elders in a local community. Journal of Korean Gerontological Nursing, 16(1), 27–37. (Original work published in Korean)
Kim M.-S., Jung H.-M., Lee H.-Y., Kim J. (2021). Risk factors for fall-related serious injury among Korean adults: A cross-sectional retrospective analysis. International Journal of Environmental Research and Public Health, 18(3), Article 1239.
Kiuchi Y., Makizako H., Nakai Y., Tomioka K., Taniguchi Y., Kimura M., Kanouchi H., Takenaka T., Kubozono T., Ohishi M. (2021). The association between dietary variety and physical frailty in community-dwelling older adults. Healthcare, 9(1), Article 32.
Kvelde T., McVeigh C., Toson B., Greenaway M., Lord S. R., Delbaere K., Close J. C. T. (2013). Depressive symptomatology as a risk factor for falls in older people: Systematic review and meta-analysis. Journal of the American Geriatrics Society, 61(5), 694–706.
Lee Y., Lee K. J., Han G. S., Yoon S. J., Lee Y. K., Kim C. H., Kim J. L. (2002). The development of physical functioning scale for community-dwelling older persons. Journal of Preventive Medicine and Public Health, 35(4), 359–374. (Original work published in Korean)
Ma Y., Li X., Pan Y., Zhao R., Wang X., Jiang X., Li S. (2021). Cognitive frailty and falls in Chinese elderly people: A population-based longitudinal study. European Journal of Neurology, 28(2), 381–388.
Ministry of Health and Welfare & Korea Institute of Health and Social Affairs. (2017). 2017 National survey of older Koreans. (Original work published in Korean)
Moreland B. L., Burns E. R., Haddad Y. K. (2021). National rates of non-fatal emergency department visits and hospitalisations due to fall-related injuries in older adults 2010–2014 and 2016: Transitioning from ICD-9-CM to ICD-10-CM. Injury Prevention, 27(S1), i75–i78.
Nakano M. M., Otonari T. S., Takara K. S., Carmo C. M., Tanaka C. (2014). Physical performance, balance, mobility, and muscle strength decline at different rates in elderly people. Journal of Physical Therapy Science, 26(4), 583–586.
Oluwaseyi O., Oluwatoyosi O., Susan A. O. (2018). Adherence and attrition in fall prevention exercise programs for community-dwelling older adults: A systematic review and meta-analysis. Journal of Aging and Physical Activity, 26(2), 304–326.
Park Y.-H., Choi-Kwon S., Park K. A., Suh M., Jung Y. S. (2017). Nutrient deficiencies and depression in older adults according to sex: A cross sectional study. Nursing & Health Sciences, 19(1), 88–94.
Posner B. M., Jette A. M., Smith K. W., Miller D. R. (1993). Nutrition and health risks in the elderly: The nutrition screening initiative. American Journal of Public Health, 83(7), 972–978.
Seoul National University Bundang Hospital. (2009). Standardization of Korean version of MMSE for dementia screening. (Original work published in Korean)
Soh S., Barkder A. L., Morello R. T., Ackerman I. N. (2020). Applying the international classification of functioning, disability and health framework to determine the predictors of falls and fractures in people with osteoarthritis or at high risk of developing osteoarthritis: Data from the osteoarthritis initiative. BMC Musculoskeletal Disorders, 21, Article No. 138.
Sohng K. Y., Choi D. W. (2007). Instrumental activities of daily living, leg muscle strength, cognitive and visual function according to demographic variables and the experience of falling in community resident elderly Koreans. Journal of Korean Academy of Fundamentals of Nursing, 14(2), 221–229. (Original work published in Korean)
Statistics Korea. (2019). Population projections for Korea. Korean. Statistical Information Service. Retrieved June 25, 2021, from (Original work published in Korean)
Wade D. T., Halligan P. W. (2017). The biopsychosocial model of illness: A model whose time has come. Clinical Rehabilitation, 31(8), 995–1004.
Wehner-Hewson N., Watts P., Buscombe R., Bourne N., Hewson D. (2022). Racial and ethnic differences in falls among older adults: A systematic review and meta-analysis. Journal of Racial and Ethnic Health Disparities, 9, 2427–2440.
Welk B., McArthur E., Fraser L.-A., Hayward J., Dixon S., Hwang Y. J., Ordon M. (2015). The risk of fall and fracture with the initiation of a prostate-selective α antagonist: A population based cohort study. BMJ, 351, Article h5398.
Winger M. E., Caserotti P., Ward R. E., Boudreau R. M., Hvid L. G., Cauley J. A., Piva S. R., Harris T. B., Glynn N. W., Strotmeyer E. S. (2021). Jump power, leg press power, leg strength and grip strength differentially associated with physical performance: The developmental epidemiologic cohort study (DECOS). Experimental Gerontology, 145, Article 111172.
Won C. W., Rho Y. G., Kim S. Y., Cho B. R., Lee Y. S. (2002). The validity and reliability of Korean activities of daily living (K-ADL) scale. Journal of Korean Geriatrics Society, 6(2), 98–106. (Original work published in Korean)
Won C. W., Rho Y. G., SunWoo D., Lee Y. S. (2002). The validity and reliability of Korean instrumental activities of daily living (K-IADL) scale. Annals Geriatric Medicine Research, 6(4), 273–280. (Original work published in Korean)
Wu H., Ouyang P. (2017). Fall prevalence, time trend and its related risk factors among elderly people in China. Archives of Gerontology and Geriatrics, 73, 294–299.
Yoshimura K., Yamada M., Kajiwara Y., Nishiguchi S., Aoyama T. (2013). Relationship between depression and risk of malnutrition among community-dwelling young–old and old–old elderly people. Aging and Mental Health, 17(4), 456–460.
Zhang F., Ferrucci L., Culham E., Metter E. J., Guralnik J., Deshpande N. (2013). Performance on five times sit-to-stand task as a predictor of subsequent falls and disability in older persons. Journal of Aging and Health, 25(3), 478–492.
Zhang K., Qi J., Zuo P., Yin P., Liu Y., Liu J., Wang L., Lia L. (2022). The mortality trends of falls among the elderly adults in the mainland of China, 2013–2020: A population-based study through the National Disease Surveillance Points system. The Lancet Regional Health—Western Pacific, 19, Article 100336.

falls; older adults; age; gender; depression

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