Prevalence and Risk Factors of Falls Among Older Adults in the United States: A Cross- sectional Study

Prevalence and Risk Factors of Falls Among Older Adults in the United States: A Cross- sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence and Risk Factors of Falls Among Older Adults in the United States: A Cross- sectional Study Philip Obiri Ankomah, Isaac Obeng-Gyasi, Susan Onumanyiwa Nyanteh, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9224503/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Several studies have examined fall risk among older adults in the United States; however, studies using recent nationally representative data to evaluate fall prevalence and associated factors in this population are limited. We investigated the current prevalence of falls among adults aged ≥ 60 years in the United States and examined the demographic and health-related factors associated with falls. Method Using data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS) dataset, we estimated the prevalence and associated factors of falls among older adults aged ≥ 60 years in the United States. We investigated the weighted prevalence of falls and conducted bivariate and multivariate analyses to determine the factors associated with falls using “at least one fall in the last 12 months” as the dependent variable. Results Of 197,432 participants recruited from the 2023 BRFSS, 27.0% (n = 53,306) reported “at least one fall in the past 12 months.” Participants aged ≥ 80 years had higher odds of falling than those aged 60–69 years (aOR = 1.13, 95% CI: 1.07–1.18). Female sex (aOR = 1.09, 95% CI: 1.05–1.13), lower income (aOR = 1.06, 95% CI: 1.01–1.11), lower educational level (aOR = 0.75, 95% CI: 0.69–0.81), and “not working” (aOR = 1.21, 95% CI: 1.15–1.26) were independent factors associated with increased fall risk. Poor general health (aOR = 1.46, 95% CI: 1.40–1.53), visual difficulty (aOR = 1.27, 95% CI: 1.19–1.36), hearing loss (aOR = 1.26, 95% CI: 1.19–1.32), arthritis (aOR = 1.43, 95% CI: 1.38–1.49, p < 0.001), difficulty concentrating/deciding (aOR = 2.09, 95% CI: 1.98–2.21, p < 0.001), and difficulty climbing stairs/moving (aOR = 2.36, 95% CI: 2.26–2.47, p < 0.001) were strongly associated with falls. Conclusion These findings highlight the need for comprehensive fall-prevention strategies that address modifiable risk factors such as sensory impairments, chronic disease management, and mobility limitations to reduce the burden of falls in aging populations. BRFSS Falls Older adults United States 1. BACKGROUND Older adults (≥ 60 years) now account for 12.3% of the global population [ 1 ]. Notably, there are more older adults than children < 5 years, causing significant economic, healthcare, and social shifts [ 2 ]. With older age comes complex health states commonly called geriatric syndromes, including falls, which are often the consequence of multiple underlying factors [ 2 ]. Falls remain a major public health burden and the second leading cause of injury-related mortality among older adults [ 3 ]. Globally, 26.5–35% of adults aged ≥ 60 experience at least one fall each year, with the prevalence increasing to 32–42% for those aged > 70 years [ 4 ]. In the United States, 1 in 4 older adults (14 million) report at least one every year [ 5 ]. Falls can result in a variety of complications ranging from fractures to long-term hospitalizations and mental health problems. The consequences of falls can be physical (fractures, pain or discomfort, medical conditions/health problems due to prolonged immobility, difficulty or inability to move independently, and unsteady walking patterns), social (loss of independence, changes to daily routine, financial costs of hospitalization, loss of social contacts due to long-term hospitalization, and decreased quality of life), and psychological (frustration due to loss of independence, fear of falling again, uncertainty and anxiety, embarrassment from injury and/or usage of walking aids, loss of self-esteem) [ 6 ]. According to Ying et al, the most common risk factors for falls among older adults in the community are fear of falling, age, female gender, balance disorder, dementia, depression, previous falls, and unclear vision [ 2 ]. In older adults, falls are a leading cause of injury, disability, reduced quality of life (QoL), and mortality [ 7 ]. Despite the elaborate research on the prevalence and risk factors of falls among older adults, most research in the United States based on hospital records, emergency department data, nursing home populations, and regional cohorts. These studies only capture severe falls, missing non-injurious falls, underestimating the true prevalence of falls in older adults. Therefore, recent nationally representative data on fall prevalence and risk factors among older adults in the United States is required. Therefore, we used data from the Behavioral Risk Factor Surveillance System (BRFSS) database to investigate the prevalence and risk factors of falls in community-dwelling older adults aged ≥ 60 years. 2. METHODS 2.1 Design We conducted a cross-sectional analytical study using data from the 2023 BRFSS database. 2.2 Participants The BRFSS is a system of health-related telephone surveys that collects state data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. It collects data in all 50 states as well as the District of Columbia and three United States territories. BRFSS completes > 400,000 adult interviews each year, making it the largest continuous health survey system in the world [ 8 ]. We included and analyzed the data of adults aged ≥ 60 years in the 2023 BRFSS dataset who recorded at least one fall in 2023. We excluded older adults with missing information on the number of falls reported in 2023. 2.3 Variables The dependent variable was “falls in past 12 months” (Yes/No). The independent variables included age group, sex, marital status, educational level, employment status, income level, smoking status, alcohol status, body mass index (BMI), general health (defined as self-perceived mental, physical, and social wellbeing), hearing loss, visual difficulty, difficulty concentrating and deciding, difficulty moving/climbing the stairs, high blood pressure, and diagnosed arthritis. 2.4 Data collection and ethical considerations With technical and methodological assistance from the Centre for Disease Control (CDC), state health departments use in-house interviewers or contract with telephone call centers or universities to administer the BRFSS surveys continuously through the year. The states use a standardized core questionnaire, optional modules, and state-added questions. The survey is conducted using Random Digit Dialing techniques on both landlines and cell phones. Participation in the BRFSS is entirely voluntary, and anonymity and privacy of the responders are maintained [ 8 ]. 2.5 Data analysis The data were extracted from the CDC BRFSS database, imported, and analyzed using IBM SPSS Statistics for Windows, Version 28.0 (IBM Corp., Armonk, NY, USA). Participants’ general characteristics are summarized using descriptive statistics, including frequencies, percentages, means, and standard deviations. We calculated the weighted prevalence of falls. We conducted a bivariate analysis using the weighted chi-square tests to source out potential risk factors of falls in this population. Multiple regression analysis was conducted to identify the risk factors of falls in this population. To adjust for confounders, variables with p values > 0.25 were excluded from the multiple logistic regression analysis. We reported adjusted odds ratios (aOR), 95% confidence intervals (CIs), and p-values, with P < 0.05 considered statistically significant. 3. RESULTS Prevalence of Falls A total of 197,432 older adults aged ≥ 60 years were included in the study. The mean age of the participants was 71.12 ± 6.52 years. Most participants were aged 60–69 years (42.8%), followed by 70–79 years (38.6%), and ≥ 80 years (18.7%). Of these, 53,306 (27%) experienced “at least one fall in the last 12 months,” while 144125 (73%) reported no falls. Therefore, the overall prevalence of falls in this population was 27.0% (95% CI: 26.5–27.4). Characteristics of the Study Population Of the 197,432 participants, 52.6% (n = 103,849) were female, 47.4% (n = 93,582) were male, 55.9% were unmarried, and 43.2% were married (Table 1 ). Most participants had an educational level of high school or higher (93.7%) and 49.1% of participants were working, while 49.1% were not. Overall, 44% of the respondents reported a high income (> 25,000 USD annually). Most respondents were physically active (88.0%). Regarding lifestyle behaviors, 83.9% were non-smokers, whereas 10.4% were current smokers. Additionally, 49.3% reported no alcohol consumption, while 44.3% reported alcohol use. Body mass index (BMI) distribution indicated that 32.2% were overweight, 29.5% were obese, 27.1% had normal weight, and 1.6% were underweight (Table 1 ). Table 1 Characteristics of the Study Population (N = 197,432) Variable Category Frequency (n) Percentage (%) Age group 60–69 years 84,430 42.8 70–79 years 76,135 38.6 ≥ 80 years 36,867 18.7 Sex Male 93,643 47.4 Female 103,789 52.6 Marital status Married 85,223 43.2 Not married 110,275 55.9 Missing 1,934 1.0 Educational level High school or more 184,955 93.7 Less than high school 11,421 5.8 Missing 1,056 0.5 Income level > $ 25,000 annually 86,823 44.0 < $ 25,000 annually 22,303 11.3 Missing 88,306 44.7 Smoking status Not current smoker 165,669 83.9 Current smoker 20,454 10.4 Missing 11,309 5.7 Employment status Working 96,867 49.1 Not working 96,984 49.1 Missing 3,581 1.8 Body Mass Index Underweight 3,116 1.6 Normal 53,492 27.1 Overweight 63,576 32.2 Obese 58,296 29.5 Missing 18,952 9.6 Alcohol use Alcohol use 97,270 49.3 No alcohol use 85,430 43.3 Missing 14,732 7.4 [Insert Table 1 here] Factors associated with falls in adults In the bivariate analysis, falls were more common among older age groups. Participants aged ≥ 80 years reported the highest prevalence of falls (29.8%), followed by those aged 60–69 years (26.9%) and 70–79 years (25.1%). Falls were also more common among females (28.5%) compared with males (24.8%). Higher fall prevalence was observed among individuals with poor self-rated health (44.0%), visual difficulty (46.4%), hearing loss (38.6%), and mobility limitations such as difficulty climbing stairs (50.3%). Functional limitations, particularly difficulty climbing stairs or moving and difficulty concentrating or making decisions, showed some of the strongest associations (p < 0.001). These findings highlight the multifactorial nature of falls in older adults, encompassing demographic, socioeconomic, lifestyle, sensory, cognitive, and functional domains. In the multivariable logistic regression analysis, we identified several factors that were independently associated with falls among adults aged ≥ 60 years. Participants aged ≥ 80 years had significantly higher odds of experiencing a fall compared with those aged 60–69 years (aOR = 1.13, 95% CI: 1.07–1.18). However, the association for adults aged 70–79 years was not statistically significant (aOR = 0.97, 95% CI: 0.93–1.02). Female sex was associated with a modestly higher likelihood of falling compared with males (aOR = 1.09, 95% CI: 1.05–1.13). Socioeconomic factors were also associated with fall risk. Participants with annual income below $ 25,000 had increased odds of falls (aOR = 1.06, 95% CI: 1.01–1.11). Similarly, those not currently working had higher odds of falls (aOR = 1.21, 95% CI: 1.15–1.26). Interestingly, individuals with lower education levels had lower odds of falls compared with those with higher educational attainment (aOR = 0.75, 95% CI: 0.69–0.81). Several health-related factors demonstrated strong associations with falls. Participants reporting poor general health had significantly higher odds of falling (aOR = 1.46, 95% CI: 1.40–1.53). Sensory impairments were also associated with falls. Individuals with hearing loss had increased odds of falls (aOR = 1.26, 95% CI: 1.19–1.32), and those reporting visual difficulty had higher odds as well (aOR = 1.27, 95% CI: 1.19–1.36). Further, arthritis (aOR = 1.43, 95% CI: 1.38–1.49, p < 0.001), difficulty concentrating/deciding (aOR = 2.09, 95% CI: 1.98–2.21, p < 0.001), and difficulty climbing stairs/moving (aOR = 2.36, 95% CI: 2.26–2.47, p < 0.001) were strongly associated with falls (Table 2 ). Table 2 Multivariable Logistic Regression Analysis of Factors Associated with Falls Among Adults Aged ≥ 60 Years Variable Category Adjusted Odds Ratio (aOR) 95% CI p-value Age group 60–69 years 1.00 Reference — 70–79 years 0.97 0.93–1.02 0.197 ≥ 80 years 1.13 1.07–1.18 < 0.001 Sex Male 1.00 Reference — Female 1.09 1.05–1.13 < 0.001 Marital status Not married 1.00 Reference — Married 1.03 0.99–1.07 0.134 Educational level High school or more 1.00 Reference — Less than high school 0.75 0.69–0.81 $ 25,000 1.00 Reference — < $ 25,000 1.06 1.01–1.11 0.026 Smoking status Not current smoker 1.00 Reference — Current smoker 1.03 0.97–1.09 0.304 Alcohol use No alcohol use 1.00 Reference — Alcohol use 1.15 1.11–1.19 < 0.001 General health Good health 1.00 Reference — Poor health 1.46 1.40–1.53 < 0.001 Employment status Working 1.00 Reference — Not working 1.21 1.15–1.26 < 0.001 Hearing loss No 1.00 Reference — Yes 1.26 1.19–1.32 < 0.001 Visual difficulty No 1.00 — Yes 1.27 1.19–1.36 < 0.001 Difficulty concentrating No 1.00 — Yes 2.09 1.98–2.21 < 0.001 Difficulty climbing stairs No 1.00 — Yes 2.36 2.26–2.47 < 0.001 Diagnosed arthritis No 1.00 — Yes 1.43 1.38–1.49 < 0.001 High blood pressure No 1.00 — Yes 0.99 0.96–1.03 0.736 Body Mass Index Underweight 1.00 — Normal 0.93 0.81–1.08 0.343 Overweight 0.92 0.79–1.06 0.230 Obese 0.94 0.81–1.08 0.388 [Insert Table 2 here] 4. DISCUSSION Principal Findings The prevalence of falls in adults ≥ 60 years in the 2023 BRFSS cohort was 27%. The factors associated with fall risk included advanced age, female sex, marital status, lower socioeconomic status, sensory impairments, chronic health conditions, and functional limitations. Difficulty concentrating or making decisions, difficulty climbing stairs, poor general health, high blood pressure, and visual impairment showed the strongest associations with fall risk. Comparison With Previous Studies The prevalence of falls reported in this study was similar to the global report by the world health organization stating that 28–35% of people aged ≥ 65 fall each year increasing to 32–42% for those aged > 70 years [ 9 , 10 ]. Further, a study by Ying Li et al reported that the prevalence of falls among community-dwelling older adults was approximately 30% each year [ 1 ]. Contrary to our results, a study conducted in Europe reported that the prevalence of falls among community-dwelling older adults was 8.2% [ 11 ]. However, in this European study, “falls in the last six months” was the dependent variable, contrary to “falls in the last 12 months” used in our study. This could explain the disparity in the prevalence of falls. More importantly, while global aging is a universal trend, the U.S. faces a unique combination of health, environmental, and systemic factors, such as higher rates of chronic diseases and obesity, that contribute to this disparity [ 12 ]. Nonetheless, these prevalences highlight that falls are a major public health issue and a major cause of injury, mortality, and morbidity among older adults [ 13 ]. Thus, it should be given more attention considering the rapid and continuous increase in the aging population [ 14 ]. Socio-demographic risk factors In our study, the prevalence of falls increased with age, with individuals aged ≥ 80 years having higher odds of falling than younger participants. Similarly, in a study from the Baltimore Longitudinal Study on Aging, the prevalence of falls increased from 18.5% in young adults (ages 20–45) to 21% in middle-aged adults, and 35% in those aged ≥ 65 years [ 15 ]. Interestingly, in another study conducted in the U.S., while the prevalence of falls generally increased with age, the risk disappeared for older healthy adults: Among adults aged ≥ 85 years who reported "excellent" overall health status, there was no greater risk of falling compared to those aged 65–84 years [ 16 ]. This suggests that the increase in falls is driven by the deterioration of health status (comorbidities, muscle loss, etc.) rather than “aging” itself. Falls are more common among older adults as a result of interactions between extrinsic (environmental hazards), intrinsic (age-related decline in function, disorders, and adverse drug effects), and situational factors (related to the activity done, e.g., rushing to the bathroom) [ 17 ]. In this study, female sex was associated with increased fall risk. This is similar to previous studies reporting similar trends [ 18 ]. A study rvealed that among 70-year-old women, approximately 50% had greater risks of falls than men and showed significantly higher gait variability (instability) during dual-task activities than men, which directly contributes to their higher fall risk [ 19 ]. Women experience higher fall rates partly due to lower muscle mass, greater prevalence of osteoporosis, and longer life expectancy, which increases exposure to fall risk factors [ 11 ]. In our study, socioeconomic factors were also significantly associated with risk of falls. Lower income, lower educational attainment, unemployment, and being unmarried were associated with increased risk of falls. Similarly, a study by Agnieszka et al reported that educational background and financial constraints contributed to fall risk, emphasizing the need for targeted fall prevention programs among vulnerable populations [ 20 ]. Socioeconomic disadvantage may influence falls through limited access to healthcare, poorer living environments, and reduced participation in preventive health programs [ 21 ]. Lifestyle-related risk factors In this study, alcohol consumption was significantly associated with a higher risk of falls. Similarly, a previous study found that the risk of falling is almost linearly associated with alcohol intake of up to 40 grams of ethanol per day [ 22 ]. Alcohol consumption is a modifiable risk factor for falls in older adults, primarily due to its dose-dependent relationship with injury severity and its interaction with aging physiology [ 22 ] [ 23 ]. Notably, in our study, “not common smokers” had higher odds of falling than current smokers. This finding is contrary to most previous findings which highlight that current smokers have higher odds of falling, primarily due to increased frailty, dizziness, and reduced physical function [ 24 ]. However, recent research has found that those who recently quit smoking may show higher odds of falling than current smokers [ 25 ]. Further, some studies have noted that non-smokers may spend more time outdoors or engaged in vigorous physical activity. Since they are more physically mobile than sedentary smokers, they are more exposured to risks, leading to more frequent falls despite being in good general health [ 26 ]. Regarding BMI, in this study, being underweight was association with an increased risk of falls. This is simlar with previous reports stating that the association of underweight and obesity with increased falls risk was consistent in participants aged ≥ 65 years [ 27 ]. The relationship between BMI and falls is described as U-shaped, where both underweight and obese individuals face higher risks of falling [ 27 , 28 ]. Underweight individuals are at high risk, often associated with lower bone mineral density, weakness, and sarcopenia (loss of muscle mass) [ 28 ]. Health-Related Risk Factors In this study, several health-related conditions were strongly associated with falls. Participants reporting poor health had significantly higher odds of falling. In a previous study, health status played a significant mediating role in the relationship between the number of chronic diseases and sleeptime and falls in older adults [ 29 ]. Self-perceived health status is reliable indicator of overall health and may reflect the cumulative burden of chronic disease, disability, and functional decline [ 13 ]. Sensory impairments also emerged as important predictors of falls. Both visual difficulty and hearing loss were independently associated with fall risk. Similarly, in a study by Zhang et al, older adults with vision or hearing problem had a 20% higher risk of falling and a 37% higher risk of developing a fall-related injury. Interestingly, when individuals recovered their sensory function, their risk of falling reduced [ 30 ]. Vision plays a critical role in maintaining balance and detecting environmental hazards, and visual impairment has consistently been linked with increased fall risk among older adults. Similarly, hearing loss may contribute to falls by impairing spatial awareness and balance control. Chronic conditions such as hypertension and arthritis were also associated with increased fall risk. In a study carried out among Chinese middle-aged and older adults, the risk of falls increased linearly with the number of chronic diseases [ 31 ]. Adults with rheumatoid arthritis have an increased risk of falls. Arthritis may increase falls through joint pain, stiffness, and reduced mobility, which can impair gait and balance [ 32 ]. In a study by Wang et al, 22.60% of older adults with hypertension experienced falls. Hypertension and related treatments may also contribute to fall risk through dizziness, orthostatic hypotension, or medication side effects [ 33 ]. Cognitive and Functional Limitations Notably, in this study, there was a strong association between falls and cognitive and functional limitations. Difficulty concentrating or making decisions was significantly associated with a higher risk of falling. Interestingly. falls are not just a consequence of cognitive impairment but are also a potential clinical marker for undiagnosed dementia. Older adults who experience an injurious fall have a 10.6% of patients who experienced a fall were subsequently diagnoed with dementia within 1 year [ 34 ]. Cognitive impairment increases fall risk by affecting attention, executive function, and hazard perception, which are important for safe mobility [ 34 ]. Further, difficulty climbing stairs or moving was one of the strongest predictors of falls in this study. Previous research has consistently identified mobility impairment as one of the strongest predictors of falls among older adults. One such study reported that participants with difficulty climbing down stairs eperienced more falls [ 35 ]. Functional mobility limitations often reflect underlying problems such as muscle weakness, balance deficits, frailty, and neurological impairment [ 36 ]. Public Health Implications The findings of this study have important implications for fall prevention strategies. Falls are recognized globally as a leading cause of injury, disability, and mortality among older adults [ 9 ]. Given the multifactorial nature of falls, prevention strategies should adopt multidisciplinary approaches that address physical, cognitive, and environmental risk factors. Interventions focusing on strength and balance training, management of chronic diseases, vision screening, and mobility improvement may substantially reduce fall risk. In addition, community-based programs and routine fall risk assessments in primary healthcare settings could help identify high-risk individuals and implement targeted preventive measures. Strengths and Limitations This study has several strengths. First, the analysis was conducted using a very large sample of more than 200,000 participants, which enhances the statistical power and generalizability of the findings. Second, the study examined a wide range of sociodemographic, behavioral, and health-related variables, allowing for a comprehensive evaluation of fall risk factors. However, some limitations should be acknowledged. The study relied on self-reported data, which may be subject to recall bias. Additionally, the cross-sectional design limits the ability to establish causal relationships between risk factors and falls. Finally, some potentially relevant factors, such as medication use, environmental hazards, or objective balance assessments, were not available in the dataset. Conclusion Falls remain a significant health concern among older adults, with more than one-quarter of participants reporting “at least one fall in the past 12 months”. The results indicate that falls are influenced by a variety of demographic, socioeconomic, health-related, cognitive, and functional factors. Preventive strategies targeting these factors may play an important role in reducing falls among older adults. List of Abbreviations AOR, adjusted odds ratios; BRFSS, Behavioral Risk Factor Surveillance System; BMI, body mass index; CDC, Centre for Disease Control; CI, Confidence Intervals; QoL, Quality of life Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing interests The authors declare that they have no competing interests Funding None Author Contribution POA, IO-G, SON, and BFA conceptualized and designed the study; CNE acquired and analyzed data, drafted the manuscript; IO-G, POA, SON, and BFA critically reviewed and revised the manuscript. All authors contributed to data interpretation and approved the final manuscript. Acknowledgements Not Applicable Data Availability The datasets used and analyzed in the current study are available from the CDC BRFSS website available at [https://www.cdc.gov/brfss/index.html] References Li Y, Hou L, Zhao H, Xie R, Yi Y, Ding X. 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BMC Geriatr. 2022;22:374. 10.1186/s12877-022-03055-x . Nie J, Liao B, Wang X, Ferrari G, Rezende LFM, Qiu Y, et al. Longitudinal changes in sensory impairments and subsequent falls and fall-related injuries among middle-aged and older adults: a pooled analysis of four prospective cohorts. BMC Public Health. 2025;26:130. 10.1186/s12889-025-25679-5 . Huang D, Fu Y, Yang W, Xu B, Yang Z. Longitudinal association between chronic diseases and fall risk among middle-aged and older adults in China: the mediating role of activity limitations. J Glob Health 16:04106. 10.7189/jogh.16.04106 Stanmore EK, Oldham J, Skelton DA, O’Neill T, Pilling M, et al. Risk Factors for Falls in Adults With Rheumatoid Arthritis: A Prospective Study. Arthritis Care Res. 2013;65:1251–8. 10.1002/acr.21987 . Wang Y, Zhang Y, Cao S, Chen X, Xian X, Niu T. Associated factors and gender differences of falls in older adults with hypertension: a national cross-sectional survey. Front Public Health. 2025;13. 10.3389/fpubh.2025.1537587 . Ordoobadi AJ, Dhanani H, Tulebaev SR, Salim A, Cooper Z, Jarman MP. Risk of Dementia Diagnosis After Injurious Falls in Older Adults. JAMA Netw Open. 2024;7:e2436606. 10.1001/jamanetworkopen.2024.36606 . Verghese J, Wang C, Xue X, Holtzer R. Self-Reported Difficulty in Climbing Up or Down Stairs in Nondisabled Elderly. Arch Phys Med Rehabil. 2008;89:100–4. 10.1016/j.apmr.2007.08.129 . Biswal S, Kiruthika S, George SM, Chakrawarty A, Wig N, Rao AR. A multidimensional analysis of fall risk among older adults in India: evidence from the longitudinal ageing study in India (LASI). Eur Geriatr Med. 2026. 10.1007/s41999-026-01408-y . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 18 May, 2026 Reviewers agreed at journal 17 May, 2026 Reviews received at journal 07 May, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers invited by journal 22 Apr, 2026 Editor assigned by journal 03 Apr, 2026 Editor invited by journal 02 Apr, 2026 Submission checks completed at journal 01 Apr, 2026 First submitted to journal 01 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9224503","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":631760737,"identity":"0c2fcf5a-46af-492f-84c8-ee8452e11165","order_by":0,"name":"Philip Obiri Ankomah","email":"","orcid":"","institution":"University of South Carolina","correspondingAuthor":false,"prefix":"","firstName":"Philip","middleName":"Obiri","lastName":"Ankomah","suffix":""},{"id":631760738,"identity":"66e2666f-dfad-47df-88bc-fbfa509f152b","order_by":1,"name":"Isaac Obeng-Gyasi","email":"","orcid":"","institution":"University of California","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Obeng-Gyasi","suffix":""},{"id":631760739,"identity":"f55d8447-1a6a-4eda-a7de-e7a4b48063f2","order_by":2,"name":"Susan Onumanyiwa Nyanteh","email":"","orcid":"","institution":"Korle Bu Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Susan","middleName":"Onumanyiwa","lastName":"Nyanteh","suffix":""},{"id":631760740,"identity":"ee5548e1-ca0d-4790-82a9-5b796db264e5","order_by":3,"name":"Bibiana Frans-Asmah","email":"","orcid":"","institution":"Ashtead Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bibiana","middleName":"","lastName":"Frans-Asmah","suffix":""},{"id":631760741,"identity":"68b055ea-cb1e-43a3-b7ff-88e967d66927","order_by":4,"name":"Claudia Noumbissie Evenge","email":"data:image/png;base64,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","orcid":"","institution":"Editspur","correspondingAuthor":true,"prefix":"","firstName":"Claudia","middleName":"Noumbissie","lastName":"Evenge","suffix":""}],"badges":[],"createdAt":"2026-03-25 14:39:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9224503/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9224503/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109067484,"identity":"8ec4404f-7a57-41a3-a773-492ae853b1ae","added_by":"auto","created_at":"2026-05-12 09:54:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":384180,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9224503/v1/cc1e154e-5c22-4e06-9989-109e8bf879a3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence and Risk Factors of Falls Among Older Adults in the United States: A Cross- sectional Study","fulltext":[{"header":"1. BACKGROUND","content":"\u003cp\u003eOlder adults (\u0026ge;\u0026thinsp;60 years) now account for 12.3% of the global population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Notably, there are more older adults than children\u0026thinsp;\u0026lt;\u0026thinsp;5 years, causing significant economic, healthcare, and social shifts [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. With older age comes complex health states commonly called geriatric syndromes, including falls, which are often the consequence of multiple underlying factors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFalls remain a major public health burden and the second leading cause of injury-related mortality among older adults [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Globally, 26.5\u0026ndash;35% of adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 experience at least one fall each year, with the prevalence increasing to 32\u0026ndash;42% for those aged\u0026thinsp;\u0026gt;\u0026thinsp;70 years [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In the United States, 1 in 4 older adults (14\u0026nbsp;million) report at least one every year [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFalls can result in a variety of complications ranging from fractures to long-term hospitalizations and mental health problems. The consequences of falls can be physical (fractures, pain or discomfort, medical conditions/health problems due to prolonged immobility, difficulty or inability to move independently, and unsteady walking patterns), social (loss of independence, changes to daily routine, financial costs of hospitalization, loss of social contacts due to long-term hospitalization, and decreased quality of life), and psychological (frustration due to loss of independence, fear of falling again, uncertainty and anxiety, embarrassment from injury and/or usage of walking aids, loss of self-esteem) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. According to Ying et al, the most common risk factors for falls among older adults in the community are fear of falling, age, female gender, balance disorder, dementia, depression, previous falls, and unclear vision [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In older adults, falls are a leading cause of injury, disability, reduced quality of life (QoL), and mortality [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the elaborate research on the prevalence and risk factors of falls among older adults, most research in the United States based on hospital records, emergency department data, nursing home populations, and regional cohorts. These studies only capture severe falls, missing non-injurious falls, underestimating the true prevalence of falls in older adults. Therefore, recent nationally representative data on fall prevalence and risk factors among older adults in the United States is required.\u003c/p\u003e \u003cp\u003eTherefore, we used data from the Behavioral Risk Factor Surveillance System (BRFSS) database to investigate the prevalence and risk factors of falls in community-dwelling older adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Design\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional analytical study using data from the 2023 BRFSS database.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Participants\u003c/h2\u003e \u003cp\u003eThe BRFSS is a system of health-related telephone surveys that collects state data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. It collects data in all 50 states as well as the District of Columbia and three United States territories. BRFSS completes\u0026thinsp;\u0026gt;\u0026thinsp;400,000 adult interviews each year, making it the largest continuous health survey system in the world [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe included and analyzed the data of adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years in the 2023 BRFSS dataset who recorded at least one fall in 2023. We excluded older adults with missing information on the number of falls reported in 2023.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Variables\u003c/h2\u003e \u003cp\u003eThe dependent variable was \u0026ldquo;falls in past 12 months\u0026rdquo; (Yes/No). The independent variables included age group, sex, marital status, educational level, employment status, income level, smoking status, alcohol status, body mass index (BMI), general health (defined as self-perceived mental, physical, and social wellbeing), hearing loss, visual difficulty, difficulty concentrating and deciding, difficulty moving/climbing the stairs, high blood pressure, and diagnosed arthritis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data collection and ethical considerations\u003c/h2\u003e \u003cp\u003eWith technical and methodological assistance from the Centre for Disease Control (CDC), state health departments use in-house interviewers or contract with telephone call centers or universities to administer the BRFSS surveys continuously through the year. The states use a standardized core questionnaire, optional modules, and state-added questions. The survey is conducted using Random Digit Dialing techniques on both landlines and cell phones. Participation in the BRFSS is entirely voluntary, and anonymity and privacy of the responders are maintained [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data analysis\u003c/h2\u003e \u003cp\u003eThe data were extracted from the CDC BRFSS database, imported, and analyzed using IBM SPSS Statistics for Windows, Version 28.0 (IBM Corp., Armonk, NY, USA). Participants\u0026rsquo; general characteristics are summarized using descriptive statistics, including frequencies, percentages, means, and standard deviations. We calculated the weighted prevalence of falls. We conducted a bivariate analysis using the weighted chi-square tests to source out potential risk factors of falls in this population. Multiple regression analysis was conducted to identify the risk factors of falls in this population. To adjust for confounders, variables with p values\u0026thinsp;\u0026gt;\u0026thinsp;0.25 were excluded from the multiple logistic regression analysis. We reported adjusted odds ratios (aOR), 95% confidence intervals (CIs), and p-values, with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e\u003cstrong\u003ePrevalence of Falls\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 197,432 older adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years were included in the study. The mean age of the participants was 71.12\u0026thinsp;\u0026plusmn;\u0026thinsp;6.52 years. Most participants were aged 60\u0026ndash;69 years (42.8%), followed by 70\u0026ndash;79 years (38.6%), and \u0026ge;\u0026thinsp;80 years (18.7%). Of these, 53,306 (27%) experienced \u0026ldquo;at least one fall in the last 12 months,\u0026rdquo; while 144125 (73%) reported no falls. Therefore, the overall prevalence of falls in this population was 27.0% (95% CI: 26.5\u0026ndash;27.4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristics of the Study Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the 197,432 participants, 52.6% (n\u0026thinsp;=\u0026thinsp;103,849) were female, 47.4% (n\u0026thinsp;=\u0026thinsp;93,582) were male, 55.9% were unmarried, and 43.2% were married (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Most participants had an educational level of high school or higher (93.7%) and 49.1% of participants were working, while 49.1% were not. Overall, 44% of the respondents reported a high income (\u0026gt;\u0026thinsp;25,000 USD annually). Most respondents were physically active (88.0%). Regarding lifestyle behaviors, 83.9% were non-smokers, whereas 10.4% were current smokers. Additionally, 49.3% reported no alcohol consumption, while 44.3% reported alcohol use. Body mass index (BMI) distribution indicated that 32.2% were overweight, 29.5% were obese, 27.1% had normal weight, and 1.6% were underweight (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of the Study Population (N\u0026thinsp;=\u0026thinsp;197,432)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eFrequency (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e60\u0026ndash;69 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e84,430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e42.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e70\u0026ndash;79 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e76,135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e38.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;80 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e36,867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e18.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e93,643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e103,789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e52.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e85,223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e43.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNot married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e110,275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e55.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1,934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHigh school or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e184,955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e93.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLess than high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e11,421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1,056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026gt; \u003cspan\u003e$\u003c/span\u003e25,000 annually\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e86,823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e44.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026lt; \u003cspan\u003e$\u003c/span\u003e25,000 annually\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e22,303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e88,306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e44.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNot current smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e165,669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e83.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e20,454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e11,309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eWorking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e96,867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNot working\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e96,984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody Mass Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e53,492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e27.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e63,576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eObese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e58,296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e29.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e18,952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAlcohol use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e97,270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e49.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo alcohol use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e85,430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e43.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e14,732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e[Insert Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with falls in adults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the bivariate analysis, falls were more common among older age groups. Participants aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years reported the highest prevalence of falls (29.8%), followed by those aged 60\u0026ndash;69 years (26.9%) and 70\u0026ndash;79 years (25.1%). Falls were also more common among females (28.5%) compared with males (24.8%). Higher fall prevalence was observed among individuals with poor self-rated health (44.0%), visual difficulty (46.4%), hearing loss (38.6%), and mobility limitations such as difficulty climbing stairs (50.3%). Functional limitations, particularly difficulty climbing stairs or moving and difficulty concentrating or making decisions, showed some of the strongest associations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings highlight the multifactorial nature of falls in older adults, encompassing demographic, socioeconomic, lifestyle, sensory, cognitive, and functional domains.\u003c/p\u003e\n\u003cp\u003eIn the multivariable logistic regression analysis, we identified several factors that were independently associated with falls among adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years. Participants aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years had significantly higher odds of experiencing a fall compared with those aged 60\u0026ndash;69 years (aOR\u0026thinsp;=\u0026thinsp;1.13, 95% CI: 1.07\u0026ndash;1.18). However, the association for adults aged 70\u0026ndash;79 years was not statistically significant (aOR\u0026thinsp;=\u0026thinsp;0.97, 95% CI: 0.93\u0026ndash;1.02). Female sex was associated with a modestly higher likelihood of falling compared with males (aOR\u0026thinsp;=\u0026thinsp;1.09, 95% CI: 1.05\u0026ndash;1.13). Socioeconomic factors were also associated with fall risk. Participants with annual income below \u003cspan\u003e$\u003c/span\u003e25,000 had increased odds of falls (aOR\u0026thinsp;=\u0026thinsp;1.06, 95% CI: 1.01\u0026ndash;1.11). Similarly, those not currently working had higher odds of falls (aOR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 1.15\u0026ndash;1.26). Interestingly, individuals with lower education levels had lower odds of falls compared with those with higher educational attainment (aOR\u0026thinsp;=\u0026thinsp;0.75, 95% CI: 0.69\u0026ndash;0.81). Several health-related factors demonstrated strong associations with falls. Participants reporting poor general health had significantly higher odds of falling (aOR\u0026thinsp;=\u0026thinsp;1.46, 95% CI: 1.40\u0026ndash;1.53). Sensory impairments were also associated with falls. Individuals with hearing loss had increased odds of falls (aOR\u0026thinsp;=\u0026thinsp;1.26, 95% CI: 1.19\u0026ndash;1.32), and those reporting visual difficulty had higher odds as well (aOR\u0026thinsp;=\u0026thinsp;1.27, 95% CI: 1.19\u0026ndash;1.36). Further, arthritis (aOR\u0026thinsp;=\u0026thinsp;1.43, 95% CI: 1.38\u0026ndash;1.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), difficulty concentrating/deciding (aOR\u0026thinsp;=\u0026thinsp;2.09, 95% CI: 1.98\u0026ndash;2.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and difficulty climbing stairs/moving (aOR\u0026thinsp;=\u0026thinsp;2.36, 95% CI: 2.26\u0026ndash;2.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were strongly associated with falls (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariable Logistic Regression Analysis of Factors Associated with Falls Among Adults Aged\u0026thinsp;\u0026ge;\u0026thinsp;60 Years\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eAdjusted Odds Ratio (aOR)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e60\u0026ndash;69 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e70\u0026ndash;79 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.93\u0026ndash;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;80 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.07\u0026ndash;1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.05\u0026ndash;1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNot married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.99\u0026ndash;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHigh school or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLess than high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.69\u0026ndash;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026gt; \u003cspan\u003e$\u003c/span\u003e25,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026lt; \u003cspan\u003e$\u003c/span\u003e25,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.01\u0026ndash;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNot current smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.97\u0026ndash;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo alcohol use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAlcohol use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.11\u0026ndash;1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral health\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGood health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePoor health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.40\u0026ndash;1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eWorking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNot working\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.15\u0026ndash;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHearing loss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.19\u0026ndash;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisual difficulty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.19\u0026ndash;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eDifficulty concentrating\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.98\u0026ndash;2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eDifficulty climbing stairs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e2.26\u0026ndash;2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosed arthritis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.38\u0026ndash;1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh blood pressure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.96\u0026ndash;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.736\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody Mass Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.81\u0026ndash;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.79\u0026ndash;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eObese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.81\u0026ndash;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e[Insert Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here]\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003ePrincipal Findings\u003c/p\u003e \u003cp\u003eThe prevalence of falls in adults\u0026thinsp;\u0026ge;\u0026thinsp;60 years in the 2023 BRFSS cohort was 27%. The factors associated with fall risk included advanced age, female sex, marital status, lower socioeconomic status, sensory impairments, chronic health conditions, and functional limitations. Difficulty concentrating or making decisions, difficulty climbing stairs, poor general health, high blood pressure, and visual impairment showed the strongest associations with fall risk.\u003c/p\u003e \u003cp\u003eComparison With Previous Studies\u003c/p\u003e \u003cp\u003eThe prevalence of falls reported in this study was similar to the global report by the world health organization stating that 28\u0026ndash;35% of people aged\u0026thinsp;\u0026ge;\u0026thinsp;65 fall each year increasing to 32\u0026ndash;42% for those aged\u0026thinsp;\u0026gt;\u0026thinsp;70 years [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Further, a study by Ying Li et al reported that the prevalence of falls among community-dwelling older adults was approximately 30% each year [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Contrary to our results, a study conducted in Europe reported that the prevalence of falls among community-dwelling older adults was 8.2% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, in this European study, \u0026ldquo;falls in the last six months\u0026rdquo; was the dependent variable, contrary to \u0026ldquo;falls in the last 12 months\u0026rdquo; used in our study. This could explain the disparity in the prevalence of falls. More importantly, while global aging is a universal trend, the U.S. faces a unique combination of health, environmental, and systemic factors, such as higher rates of chronic diseases and obesity, that contribute to this disparity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Nonetheless, these prevalences highlight that falls are a major public health issue and a major cause of injury, mortality, and morbidity among older adults [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Thus, it should be given more attention considering the rapid and continuous increase in the aging population [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSocio-demographic risk factors\u003c/p\u003e \u003cp\u003eIn our study, the prevalence of falls increased with age, with individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years having higher odds of falling than younger participants. Similarly, in a study from the Baltimore Longitudinal Study on Aging, the prevalence of falls increased from 18.5% in young adults (ages 20\u0026ndash;45) to 21% in middle-aged adults, and 35% in those aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Interestingly, in another study conducted in the U.S., while the prevalence of falls generally increased with age, the risk disappeared for older healthy adults: Among adults aged\u0026thinsp;\u0026ge;\u0026thinsp;85 years who reported \"excellent\" overall health status, there was no greater risk of falling compared to those aged 65\u0026ndash;84 years [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This suggests that the increase in falls is driven by the deterioration of health status (comorbidities, muscle loss, etc.) rather than \u0026ldquo;aging\u0026rdquo; itself. Falls are more common among older adults as a result of interactions between extrinsic (environmental hazards), intrinsic (age-related decline in function, disorders, and adverse drug effects), and situational factors (related to the activity done, e.g., rushing to the bathroom) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, female sex was associated with increased fall risk. This is similar to previous studies reporting similar trends [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. A study rvealed that among 70-year-old women, approximately 50% had greater risks of falls than men and showed significantly higher gait variability (instability) during dual-task activities than men, which directly contributes to their higher fall risk [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Women experience higher fall rates partly due to lower muscle mass, greater prevalence of osteoporosis, and longer life expectancy, which increases exposure to fall risk factors [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, socioeconomic factors were also significantly associated with risk of falls. Lower income, lower educational attainment, unemployment, and being unmarried were associated with increased risk of falls. Similarly, a study by Agnieszka et al reported that educational background and financial constraints contributed to fall risk, emphasizing the need for targeted fall prevention programs among vulnerable populations [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Socioeconomic disadvantage may influence falls through limited access to healthcare, poorer living environments, and reduced participation in preventive health programs [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLifestyle-related risk factors\u003c/p\u003e \u003cp\u003eIn this study, alcohol consumption was significantly associated with a higher risk of falls. Similarly, a previous study found that the risk of falling is almost linearly associated with alcohol intake of up to 40 grams of ethanol per day [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Alcohol consumption is a modifiable risk factor for falls in older adults, primarily due to its dose-dependent relationship with injury severity and its interaction with aging physiology [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNotably, in our study, \u0026ldquo;not common smokers\u0026rdquo; had higher odds of falling than current smokers. This finding is contrary to most previous findings which highlight that current smokers have higher odds of falling, primarily due to increased frailty, dizziness, and reduced physical function [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, recent research has found that those who recently quit smoking may show higher odds of falling than current smokers [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Further, some studies have noted that non-smokers may spend more time outdoors or engaged in vigorous physical activity. Since they are more physically mobile than sedentary smokers, they are more exposured to risks, leading to more frequent falls despite being in good general health [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegarding BMI, in this study, being underweight was association with an increased risk of falls. This is simlar with previous reports stating that the association of underweight and obesity with increased falls risk was consistent in participants aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The relationship between BMI and falls is described as U-shaped, where both underweight and obese individuals face higher risks of falling [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Underweight individuals are at high risk, often associated with lower bone mineral density, weakness, and sarcopenia (loss of muscle mass) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHealth-Related Risk Factors\u003c/p\u003e \u003cp\u003eIn this study, several health-related conditions were strongly associated with falls. Participants reporting poor health had significantly higher odds of falling. In a previous study, health status played a significant mediating role in the relationship between the number of chronic diseases and sleeptime and falls in older adults [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Self-perceived health status is reliable indicator of overall health and may reflect the cumulative burden of chronic disease, disability, and functional decline [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSensory impairments also emerged as important predictors of falls. Both visual difficulty and hearing loss were independently associated with fall risk. Similarly, in a study by Zhang et al, older adults with vision or hearing problem had a 20% higher risk of falling and a 37% higher risk of developing a fall-related injury. Interestingly, when individuals recovered their sensory function, their risk of falling reduced [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Vision plays a critical role in maintaining balance and detecting environmental hazards, and visual impairment has consistently been linked with increased fall risk among older adults. Similarly, hearing loss may contribute to falls by impairing spatial awareness and balance control.\u003c/p\u003e \u003cp\u003eChronic conditions such as hypertension and arthritis were also associated with increased fall risk. In a study carried out among Chinese middle-aged and older adults, the risk of falls increased linearly with the number of chronic diseases [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Adults with rheumatoid arthritis have an increased risk of falls. Arthritis may increase falls through joint pain, stiffness, and reduced mobility, which can impair gait and balance [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In a study by Wang et al, 22.60% of older adults with hypertension experienced falls. Hypertension and related treatments may also contribute to fall risk through dizziness, orthostatic hypotension, or medication side effects [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCognitive and Functional Limitations\u003c/p\u003e \u003cp\u003eNotably, in this study, there was a strong association between falls and cognitive and functional limitations. Difficulty concentrating or making decisions was significantly associated with a higher risk of falling. Interestingly. falls are not just a consequence of cognitive impairment but are also a potential \u003cb\u003eclinical marker\u003c/b\u003e for undiagnosed dementia. Older adults who experience an injurious fall have a 10.6% of patients who experienced a fall were subsequently diagnoed with dementia within 1 year [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCognitive impairment increases fall risk by affecting attention, executive function, and hazard perception, which are important for safe mobility [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurther, difficulty climbing stairs or moving was one of the strongest predictors of falls in this study. Previous research has consistently identified mobility impairment as one of the strongest predictors of falls among older adults. One such study reported that participants with difficulty climbing down stairs eperienced more falls [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Functional mobility limitations often reflect underlying problems such as muscle weakness, balance deficits, frailty, and neurological impairment [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePublic Health Implications\u003c/p\u003e \u003cp\u003eThe findings of this study have important implications for fall prevention strategies. Falls are recognized globally as a leading cause of injury, disability, and mortality among older adults [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Given the multifactorial nature of falls, prevention strategies should adopt multidisciplinary approaches that address physical, cognitive, and environmental risk factors.\u003c/p\u003e \u003cp\u003eInterventions focusing on strength and balance training, management of chronic diseases, vision screening, and mobility improvement may substantially reduce fall risk. In addition, community-based programs and routine fall risk assessments in primary healthcare settings could help identify high-risk individuals and implement targeted preventive measures.\u003c/p\u003e \u003cp\u003eStrengths and Limitations\u003c/p\u003e \u003cp\u003eThis study has several strengths. First, the analysis was conducted using a very large sample of more than 200,000 participants, which enhances the statistical power and generalizability of the findings. Second, the study examined a wide range of sociodemographic, behavioral, and health-related variables, allowing for a comprehensive evaluation of fall risk factors.\u003c/p\u003e \u003cp\u003eHowever, some limitations should be acknowledged. The study relied on self-reported data, which may be subject to recall bias. Additionally, the cross-sectional design limits the ability to establish causal relationships between risk factors and falls. Finally, some potentially relevant factors, such as medication use, environmental hazards, or objective balance assessments, were not available in the dataset.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eFalls remain a significant health concern among older adults, with more than one-quarter of participants reporting \u0026ldquo;at least one fall in the past 12 months\u0026rdquo;. The results indicate that falls are influenced by a variety of demographic, socioeconomic, health-related, cognitive, and functional factors. Preventive strategies targeting these factors may play an important role in reducing falls among older adults.\u003c/p\u003e"},{"header":"List of Abbreviations","content":"\u003cp\u003eAOR, adjusted odds ratios; BRFSS, Behavioral Risk Factor Surveillance System; BMI, body mass index; CDC, Centre for Disease Control; CI, Confidence Intervals; QoL, Quality of life\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNone\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePOA, IO-G, SON, and BFA conceptualized and designed the study; CNE acquired and analyzed data, drafted the manuscript; IO-G, POA, SON, and BFA critically reviewed and revised the manuscript. All authors contributed to data interpretation and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot Applicable\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and analyzed in the current study are available from the CDC BRFSS website available at [https://www.cdc.gov/brfss/index.html]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi Y, Hou L, Zhao H, Xie R, Yi Y, Ding X. Risk factors for falls among community-dwelling older adults: A systematic review and meta-analysis. Front Med. 2023;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmed.2022.1019094\u003c/span\u003e\u003cspan address=\"10.3389/fmed.2022.1019094\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgeing. and health. 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Eur Geriatr Med. 2026. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s41999-026-01408-y\u003c/span\u003e\u003cspan address=\"10.1007/s41999-026-01408-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"BRFSS, Falls, Older adults, United States","lastPublishedDoi":"10.21203/rs.3.rs-9224503/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9224503/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSeveral studies have examined fall risk among older adults in the United States; however, studies using recent nationally representative data to evaluate fall prevalence and associated factors in this population are limited. We investigated the current prevalence of falls among adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years in the United States and examined the demographic and health-related factors associated with falls.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eUsing data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS) dataset, we estimated the prevalence and associated factors of falls among older adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years in the United States. We investigated the weighted prevalence of falls and conducted bivariate and multivariate analyses to determine the factors associated with falls using \u0026ldquo;at least one fall in the last 12 months\u0026rdquo; as the dependent variable.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 197,432 participants recruited from the 2023 BRFSS, 27.0% (n\u0026thinsp;=\u0026thinsp;53,306) reported \u0026ldquo;at least one fall in the past 12 months.\u0026rdquo; Participants aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years had higher odds of falling than those aged 60\u0026ndash;69 years (aOR\u0026thinsp;=\u0026thinsp;1.13, 95% CI: 1.07\u0026ndash;1.18). Female sex (aOR\u0026thinsp;=\u0026thinsp;1.09, 95% CI: 1.05\u0026ndash;1.13), lower income (aOR\u0026thinsp;=\u0026thinsp;1.06, 95% CI: 1.01\u0026ndash;1.11), lower educational level (aOR\u0026thinsp;=\u0026thinsp;0.75, 95% CI: 0.69\u0026ndash;0.81), and \u0026ldquo;not working\u0026rdquo; (aOR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 1.15\u0026ndash;1.26) were independent factors associated with increased fall risk. Poor general health (aOR\u0026thinsp;=\u0026thinsp;1.46, 95% CI: 1.40\u0026ndash;1.53), visual difficulty (aOR\u0026thinsp;=\u0026thinsp;1.27, 95% CI: 1.19\u0026ndash;1.36), hearing loss (aOR\u0026thinsp;=\u0026thinsp;1.26, 95% CI: 1.19\u0026ndash;1.32), arthritis (aOR\u0026thinsp;=\u0026thinsp;1.43, 95% CI: 1.38\u0026ndash;1.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), difficulty concentrating/deciding (aOR\u0026thinsp;=\u0026thinsp;2.09, 95% CI: 1.98\u0026ndash;2.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and difficulty climbing stairs/moving (aOR\u0026thinsp;=\u0026thinsp;2.36, 95% CI: 2.26\u0026ndash;2.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were strongly associated with falls.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese findings highlight the need for comprehensive fall-prevention strategies that address modifiable risk factors such as sensory impairments, chronic disease management, and mobility limitations to reduce the burden of falls in aging populations.\u003c/p\u003e","manuscriptTitle":"Prevalence and Risk Factors of Falls Among Older Adults in the United States: A Cross- sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-30 13:27:42","doi":"10.21203/rs.3.rs-9224503/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"201899061692700690705937552211198193324","date":"2026-05-18T16:01:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"277202078356789245297946249750727235130","date":"2026-05-17T04:23:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T19:51:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294560476931424376955740346796418230875","date":"2026-04-22T11:02:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-22T07:37:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-03T10:48:57+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-02T06:38:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-01T16:00:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2026-04-01T14:13:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"536941d7-83c2-44a3-b499-db3bd929f47b","owner":[],"postedDate":"April 30th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"201899061692700690705937552211198193324","date":"2026-05-18T16:01:32+00:00","index":54,"fulltext":""},{"type":"reviewerAgreed","content":"277202078356789245297946249750727235130","date":"2026-05-17T04:23:57+00:00","index":53,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T19:51:44+00:00","index":40,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-30T13:27:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-30 13:27:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9224503","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9224503","identity":"rs-9224503","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}