The Impact of Demographics and Comorbidities on Fall Incidence and Prevalence in Older Adults

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This study examines the incidence and prevalence of falls among individuals aged 65 and above, focusing on the influence of demographic factors and comorbid conditions such as hypertension, diabetes mellitus, cancer, and obesity. Methods: A retrospective cohort study was conducted using data from the TriNetX network at Virginia Commonwealth University Health System (VCUHS) from 2019 to 2023. The study population included 16,400 individuals aged 65 and above who presented with fall-related trauma. Data on demographics, clinical diagnoses, procedures, and comorbid conditions were analyzed using descriptive statistics to evaluate the incidence and prevalence of falls. Results: The mean age of the study population was 77.3 years, with a higher proportion of females (60.97%) compared to males (39.02%). Despite the larger number of female participants, incidence and prevalence of falls were highest among individuals aged 65-69 years, and fall rates were notably higher among males compared to females. This suggests that while fewer in number, males in our study experienced falls more frequently. Patients with hypertension had the highest incidence proportion (56.67%) and prevalence (75.75%) among comorbid conditions. Conclusions: Falls among older adults are significantly influenced by demographic factors and comorbid conditions. Hypertension, in particular, is associated with the highest fall risk. These findings highlight the need for targeted interventions to manage comorbidities and reduce fall risks among older adult patients. Geriatrics & Gerontology Falls Older adults Incidence Prevalence Comorbidities Background Falls among older adult individuals represent a significant public health concern due to their profound impacts on morbidity, mortality, and quality of life 1 . The World Health Organization reports that falls are the second leading cause of unintentional injury deaths worldwide, particularly affecting adults older than 65 years old 2 . The Centers for Disease Control and Prevention (CDC) identify falls as the leading cause of injury and injury-related deaths in older adults in the United States 3 . Over recent years, the incidence and prevalence of falls have shown a disturbing upward trend 3 . Annually, approximately 36 million older adults experience a fall, leading to over 32,000 fatalities and nearly 3 million emergency department visits 3,4 . This rising trend is influenced by factors including an aging population, prevalent chronic conditions, and inadequate environmental safety 5 . Research consistently demonstrates that the risk of falls increases with age. Specifically, individuals aged 85 and older experience the highest incidence of falls, with 13.5% reporting fall injuries and approximately 40% falling each year 6,7 . Additionally, gender differences are notable, with women more likely to experience falls than men, potentially due to higher rates of osteoporosis and sarcopenia in women, which contribute to frailty and balance issues 8–10 . In addition to age and gender, racial disparities also play a significant role in the risk of falls among older adults. The studies showed that African American and Hispanic older adult populations have higher rates of fall-related injuries compared to their White counterparts 11–13 . This discrepancy can be attributed to factors such as differences in socioeconomic status, access to healthcare, health care complexity and the prevalence of chronic conditions that exacerbate fall risk 7 . Moreover, chronic conditions such as hypertension, diabetes mellitus, obesity and cancer are prevalent in this population and are associated with an increased risk of falls 14–17 . A high proportion (75%) of older adult fall patients suffer from hypertension, which can lead to dizziness and balance problems, especially when antihypertensive medications are involved 18 . Diabetes mellitus, affecting about 38% of older adult fall patients, can cause neuropathy and vision impairments, thereby increasing the risk of falls 15,19 . Cancer also presents unique challenges; approximately 43% of older adults fall patients are affected, and treatments such as chemotherapy can lead to muscle weakness, fatigue, and neuropathy, all of which increase susceptibility to falls 20 . Moreover, corticosteroid use, often prescribed for cancer-related conditions, has been linked to adverse fall outcomes, particularly among hypertensive patients, exacerbating fall risks due to muscle wasting and bone loss 21,22 . Falls among older adults not only pose a significant risk for injury but also underscore a mounting public health challenge indicative of underlying gaps in geriatric health management and preventive care. This retrospective study investigates the incidence and prevalence of falls over the past four years using data extracted from the TriNetX network Virginia Commonwealth University- Health System VCUHS database spanning from 2019 to 2023. With ethical approval secured, the study analyses a cohort of 16,400 individuals aged 65 and above who were presented at hospitals with fall-related trauma. By examining the demographics, including age, gender, ethnicity and racial distribution, alongside comorbidities and risk factors associated with these incidents, this research aims to explore incidence and prevalence of falls related trauma. The findings from this project are critical for developing targeted interventions to reduce the frequency and severity of falls among the older adults. These results will be used to refine fall risk assessments and to shape effective strategies for intervention at both the individual and community levels. Method Study Design A retrospective cohort study utilizes data extracted from the TriNetX network VCU database, encompassing 16,400 participants from January 1st, 2019 to December 31st, 2023. The study aims to evaluate the incidence and prevalence of falls among older adults aged 65 years and above who are presented at hospitals with fall-related trauma. Data Source Data for this retrospective cohort study was obtained from the TriNetX network at Virginia Commonwealth University Health System (VCUHS), which aggregates electronic health records (EHRs) exclusively from within the VCUHS network. This database serves as a comprehensive repository of patient information, including demographics such as age, gender, ethnicity and race. These demographic details are used to characterize the study population of older adults aged 65 years and above who experienced fall-related trauma. Clinical diagnoses documented in the EHRs provide insights into prevalent health conditions and comorbidities among the cohort, including hypertension, obesity, diabetes mellitus, and cancer, all of which influence fall risk and outcomes. Procedures recorded in the database illuminate the medical interventions and treatments administered to patients following fall-related injuries, offering context for understanding healthcare management strategies and utilization patterns. Data Handling and Analysis The richness of data within the TriNetX network 23 facilitated robust statistical analysis. Descriptive statistics were employed to characterize the study population, detailing variables such as age, gender, race, and the prevalence and incidence rate of comorbid conditions. These statistics included means, medians, standard deviations, and frequency distributions. The prevalence and incidence functions on the TriNetX platform were utilized to accurately capture and analyze these metrics, providing a comprehensive overview of the study population's health status and the impact of comorbid conditions on fall risk. Additionally, patients were identified through ICD-10 codes related to fall injuries, ensuring accurate classification and analysis of fall-related trauma cases. Results Demographics The study population consisted of 16,400 individuals aged 65 years and above, with a mean age of 77.3 years (SD ± 8.07), who were presented with fall-related trauma. Gender distribution showed that 60.97% (10,000) of the patients were female, while 39.02% (6,400) were male, with a small fraction (0.06%, or 10 individuals) having an unknown gender. In terms of ethnicity, a vast majority, 96.4% (15,810), were not Hispanic or Latino, 3.04% (500) were Hispanic or Latino, and 0.6% (100) had unknown ethnicity. Regarding race, 62.92% (10,320) of the patients were White, 31.58% (5,180) were Black or African American, 2.92% (480) were Asian, 0.6% (100) were American Indian or Alaska Native, and 0.18% (30) were Native Hawaiian or Other Pacific Islander. Additionally, 1.89% (310) of the patients identified as another race. This demographic distribution provides a comprehensive overview of the study population, highlighting the diversity and prevalent characteristics within the older adult cohort who experienced falls (Tables 1 ). Table 1 Demographic Characteristics of the Study Population Demographic Variable Category N Percentage (%) Age Group Mean ± SD (77.3 ± 8.07) 16,400 100 Gender Female 10,000 60.97 Male 6,400 39.02 Unknown 10 0.06 Ethnicity Not Hispanic or Latino 15,810 96.4 Hispanic or Latino 500 3.04 Unknown Ethnicity 100 0.6 Race White 10,320 62.92 Black or African American 5,180 31.58 Asian 480 2.92 American Indian or Alaska Native 100 0.6 Native Hawaiian or Other Pacific Islander 30 0.18 Incidence and Prevalence by Demographics Our study examined falls among older adults, analyzing data by age, gender, race, and ethnicity. The highest incidence proportion, 26.78%, and a prevalence of 46.18% were recorded among individuals aged 65–69, with an incidence rate of 2.86 per 1,000 person-days. This trend decreased with age; individuals 85 and older showed the lowest rates: an incidence proportion of 18.06% and prevalence of 33.68%. Males demonstrated higher incidence (26.25%) and prevalence (44.54%) compared to females (22.19% incidence and 42.21% prevalence). Racial analysis revealed the highest incidence among American Indian or Alaska Native individuals at 50%, with a prevalence of 33.33%. Black or African American individuals had an incidence proportion of 24.23% and a prevalence of 47.87%. For ethnicity, Hispanic or Latino individuals had an incidence proportion of 22.22% and a prevalence of 30%, but the highest incidence rate of 4.66 per 1,000 person-days, whereas Non-Hispanic or Latino individuals exhibited an incidence proportion of 23.97% and a prevalence of 43.62%. (Table 2 ). Table 2 Incidence and Prevalence of Falls Stratified by Demographics Demographic Variable Category Incidence Proportion Prevalence Incidence Rate (cases/person-day) Age Group 65–69 0.26778242 0.4617737 2.8573073E-4 70–74 0.2614679 0.4651163 2.7698395E-4 75–79 0.24022347 0.43514645 2.7270336E-4 80–84 0.20714286 0.39673913 2.4734615E-4 85 and older 0.18064517 0.33684212 2.4629655E-4 Gender Female 0.22192152 0.42211056 2.3936154E-4 Male 0.2625 0.44541408 3.0896158E-4 Unknown Gender 1.0 1.0 0.011947432 Race American Indian or Alaska Native 0.5 0.33333334 5.108818E-4 Asian 0.2857143 0.4 3.583138E-4 Black or African American 0.24225353 0.47868216 2.4403581E-4 Native Hawaiian or Other Pacific Islander 1.0 1.0 0.01017294 Unknown Race 0.25 0.29032257 3.816898E-4 White 0.23954372 0.4163424 2.7602146E-4 Other Race 0.175 0.33333334 2.3377126E-4 Ethnicity Hispanic or Latino 0.22222222 0.3 4.6598323E-4 Not Hispanic or Latino 0.23972602 0.4361905 2.6624283E-4 Unknown Ethnicity 0.1904762 0.30612245 2.1566889E-4 Incidence and Prevalence of Falls among Patients with Diabetes Mellitus Type II Diabetes Mellitus Type II incidence proportion was 21.21% with a prevalence of 38.33% and an incidence rate of 2.20 cases per 1,000 person-days. Age-specific analysis showed a gradual decrease in incidence proportion from 22.49% in the 65–69 age group to 16.88% in those 85 and older. Similarly, prevalence and incidence rates varied slightly across age groups. Gender analysis revealed that males had a higher incidence proportion (24%) and prevalence (40.44%) compared to females. In terms of racial stratification, American Indian or Alaska Native individuals had the highest rates with an incidence proportion of 50% and prevalence of 66.67%. Ethnicity-wise, Hispanic or Latino individuals exhibited a high incidence rate of 6.56 cases per 1,000 person-days, matching a prevalence of 30%. (Table 3 ). Table 3 Comorbidities Stratified Results by Demographics Diabetes Mellites type DM II Demographic Variable Category Incidence Proportion Prevalence Incidence Rate (cases/person-day) Overall 2019-01-01–2023-12-31 0.21205008 0.38334355 2.2008002E-4 65–69 0.2248996 0.40978593 2.2014206E-4 70–74 0.23043478 0.41196012 2.2894268E-4 75–79 0.22872343 0.39330545 2.4665735E-4 80–84 0.21333334 0.35869566 2.3355192E-4 85 and older 0.16875 0.3 2.1087358E-4 Gender Female 0.19512194 0.36984923 1.9574359E-4 Male 0.24 0.40438873 2.6387515E-4 Unknown Gender 1.0 1.0 0.011947432 Race American Indian or Alaska Native 0.5 0.66666667 7.041573E-4 Asian 0.25 0.3 2.7848172E-4 Black or African American 0.2764706 0.5232558 2.7974666E-4 Native Hawaiian or Other Pacific Islander 1.0 1.0 0.010050251 Unknown Race 0.2413793 0.29032257 3.7190918E-4 White 0.1863426 0.3151751 1.9083255E-4 Other Race 0.24324325 0.41666666 3.7255973E-4 Ethnicity Hispanic or Latino 0.3 0.3 6.556804E-4 Not Hispanic or Latino 0.21026894 0.384127 2.164523E-4 Unknown Ethnicity 0.26190478 0.3877551 3.1567106E-4 Hypertension (HTN) Demographic Variable Category Incidence Proportion Prevalence Incidence Rate (cases/person-day) Overall 0.5667396 0.75750154 9.408766E-4 65–69 0.5277778 0.74006116 7.978435E-4 70–74 0.5903614 0.77408636 9.3713007E-4 75–79 0.6 0.7824268 0.0010945909 80–84 0.64761907 0.79891306 0.0012591217 85 and older 0.6513761 0.8 0.0016007035 Gender Female 0.5332136 0.7386935 8.3775294E-4 Male 0.6201117 0.7868339 0.0011324827 Unknown Gender 1.0 1.0 0.90909094 Race American Indian or Alaska Native 0.5 0.6666667 8.45666E-4 Asian 0.5 0.6 8.378484E-4 Black or African American 0.6492891 0.85658914 0.0011636964 Native Hawaiian or Other Pacific Islander 1.0 1.0 0.029325513 Unknown Race 0.5769231 0.6451613 0.0011215121 White 0.5470219 0.71789885 8.729749E-4 Other Race 0.45454547 0.625 0.0010088985 Ethnicity Hispanic or Latino 0.6 0.6 0.0015579155 Not Hispanic or Latino 0.5650173 0.76 9.361068E-4 Unknown Ethnicity 0.5945946 0.71428573 9.916029E-4 Cancer Demographic Variable Category Incidence Proportion Prevalence Incidence Rate (cases/person-day) Overall 0.23832923 0.4318876 2.634043E-4 Age Group 65–69 0.26666668 0.46341464 2.812224E-4 70–74 0.2614679 0.46357617 2.7299204E-4 75–79 0.24022347 0.43333334 2.704202E-4 80–84 0.20567375 0.39673913 2.451714E-4 85 and older 0.18064517 0.33684212 2.447009E-4 Gender Female 0.22297297 0.4232698 2.38103E-4 Male 0.26403326 0.4453125 3.0847368E-4 Unknown Gender 1.0 1.0 0.011947432 Race White 0.24050634 0.41650486 2.7436882E-4 Black or African American 0.24507043 0.48069498 2.4444156E-4 Asian 0.2857143 0.4 3.5910512E-4 Native Hawaiian or Other Pacific Islander 1.0 1.0 0.01017294 American Indian or Alaska Native 0.5 0.33333334 5.108818E-4 Unknown Race 0.25 0.29032257 3.751199E-4 Other Race 0.175 0.33333334 2.3280564E-4 Ethnicity Hispanic or Latino 0.22222222 0.3 4.4066453E-4 Not Hispanic or Latino 0.24102564 0.43726236 2.6529646E-4 Unknown Ethnicity 0.1904762 0.3 2.1467751E-4 High Weight/ Obesity Demographic Variable Category Incidence Proportion Prevalence Incidence Rate (cases/person-day) Overall 0.16105418 0.2988365 1.6495131E-4 65–69 0.20152092 0.35779816 2.0036096E-4 70–74 0.18032786 0.33554816 1.773495E-4 75–79 0.15686275 0.28033474 1.6027583E-4 80–84 0.09580839 0.18478261 9.729123E-5 85 and older 0.06818182 0.1368421 7.991337E-5 Gender Female 0.17013463 0.31859297 1.722493E-4 Male 0.14754099 0.26802507 1.5379589E-4 Unknown Gender 0.0 0.0 0.0 Race American Indian or Alaska Native 0.5 0.6666667 6.4114894E-4 Asian 0.11111111 0.2 1.1108396E-4 Black or African American 0.18734178 0.37790698 1.8117481E-4 Native Hawaiian or Other Pacific Islander 1.0 1.0 0.021645023 White 0.15410574 0.26750973 1.594208E-4 Unknown Race 0.13333334 0.16129032 1.8771234E-4 Other Race 0.11904762 0.22916667 1.4704412E-4 Ethnicity Hispanic or Latino 0.1 0.1 1.9410692E-4 Not Hispanic or Latino 0.16259542 0.30349207 1.657288E-4 Unknown Ethnicity 0.1521739 0.20408164 1.6150318E-4 Incidence and Prevalence of Falls among Patients with Hypertension (HTN) The incidence and prevalence of falls among hypertensive patients, revealing that 56.67% experienced at least one fall, with a prevalence of 75.75% and a high incidence rate of 9.41 per 1,000 person-days. Older age groups, particularly those aged 85 and older, displayed the highest figures: a 65.14% incidence and 80% prevalence. Males showed a greater incidence (62.01%) and prevalence (78.68%) compared to females. Racially, Native Hawaiian or Other Pacific Islander individuals recorded the highest rates, both at 100%, with a notably high incidence rate of 29.33 per 1,000 person-days. Among ethnic groups, Hispanic or Latino individuals reported a 60% incidence and prevalence, demonstrating significant variations across demographics in the impact of hypertension on fall risk. (Table 3 ) Incidence and Prevalence of Falls among Patients with Cancer The incidence proportion of falls among Patients with Cancer is 23.83% and a prevalence of 43.19%, with an incidence rate of 2.63 per 1,000 person-days. Incidence rates were highest among those aged 65–69 years at 26.67% and gradually decreased with age, with the lowest rates observed in individuals 85 and older. Males displayed higher rates compared to females, with a 26.40% incidence and 44.53% prevalence. Racial disparities were pronounced, with Native Hawaiian or Other Pacific Islander individuals showing an incidence and prevalence of 100%, and the highest incidence rate of 10.17 per 1,000 person-days. Hispanic or Latino patients also showed higher rates compared to non-Hispanic or Latino, emphasizing the variability across different ethnic and racial groups (Table 3 ). Incidence and Prevalence of Falls among Patients with High Weight/Obesity The incidence proportion of high Weight/Obesity is 16.11% with prevalence of 29.88%, with an incidence rate of 1.65 per 1,000 person-days. Incidence proportions were highest in the 65–69 age group at 20.15% and decreased with age, showing the lowest rates in those 85 and older. Females displayed higher incidence proportions (17.01%) and prevalence (31.86%) compared to males. Racial differences were significant, with Native Hawaiian or Other Pacific Islander individuals recording the highest incidence and prevalence at 100%, and an incidence rate of 21.65 per 1,000 person-days. Ethnic variations also showed that Hispanic or Latino individuals had a notably lower incidence proportion and prevalence of 10%, while Non-Hispanic or Latino individuals reported higher figures. These findings underscore the varying impact of obesity on fall risks across different demographic groups (Table 3 ). Summery The study examined the incidence and prevalence of falls among patients with various comorbidities, including cancer, diabetes mellitus, hypertension (HTN), and high weight/obesity. Among the fall patients, those with hypertension had the highest incidence proportion at 56.67% (0.5667396), with a prevalence of 75.75% (0.75750154) and an incidence rate of 0.94 cases per person-day (0.0009408766). Patients with cancer showed an incidence proportion of 23.71% (0.23707958), a prevalence of 43.11% (0.4311084), and an incidence rate of 0.26 cases per person-day (0.000264396). For those with diabetes mellitus, the incidence proportion was 21.21% (0.21205008), with a prevalence of 38.33% (0.38334355) and an incidence rate of 0.22 cases per person-day (0.000220008). Patients with high weight/obesity exhibited an incidence proportion of 16.11% (0.16105418), a prevalence of 29.88% (0.2988365), and an incidence rate of 0.16 cases per person-day (0.00016495131). Discussion The findings of this study underscore the significant impact of falls among the older adult population, highlighting critical demographic disparities and the prevalence of comorbidities. The data obtained from the TriNetX network at Virginia Commonwealth University Health System (VCUHS) provided a comprehensive overview of the incidence and prevalence of falls among individuals aged 65 and older over a five-year period. The demographic analysis reveals that falls are most frequent among those aged 65–69, with an incidence of 26.78% and a prevalence of 46.18%. Rates generally decrease with age. Research consistently shows that the risk of falls escalates with age, especially among individuals aged 85 and older, who are notably prone to falling 6 . Males exhibit higher fall rates (incidence: 26.25%, prevalence: 44.54%) compared to females (incidence: 22.19%, prevalence: 42.21%). Literature indicates that women are more likely to experience falls than men, possibly due to higher rates of osteoporosis and sarcopenia contributing to frailty and balance issues 24(p3) 25,26 . Among ethnic groups, American Indian or Alaska Native individuals show the highest fall incidence (50%) and rate (5.11 per 1,000 person-days), highlighting significant racial disparities. Hispanic or Latino individuals have an incidence of 22.22% and the highest rate (4.66 per 1,000 person-days), underscoring the need for targeted interventions. Studies reveal that African American and Hispanic older adult populations experience higher rates of fall-related injuries compared to their White counterparts, emphasizing significant disparities in fall risks among ethnic groups 27 12 . The incidence and prevalence of falls among patients with various comorbidities, including cancer, diabetes mellitus, hypertension (HTN), and high weight/obesity. Our results indicate that among patients who experienced falls, those with hypertension had the highest incidence proportion (56.67%) and prevalence (75.75%), as well as an elevated incidence rate per person-day. Hypertension, in particular, is associated with the highest incidence and prevalence of falls, potentially due to the effects of antihypertensive medications causing dizziness and balance problems 14,18 . Our study found that cancer patients had an incidence proportion of 23.71%, a prevalence of 43.11%, and an incidence rate of 0.26 fall cases per person-day. These results highlight a significant burden of fall-related incidents among cancer patients. Similar studies support our findings. Stone et al. reported that falls are common among cancer patients, with a prevalence and incidence rate that closely align with our data 28 . They noted that cancer treatments, increased frailty, and decreased mobility contribute significantly to falling risk among these patients 29 . Additionally, Capone et al. found comparable incidence rates, underscoring the widespread nature of this issue in cancer populations 30 . The high prevalence rate observed in our study might be due to factors such as cancer treatment side effects, increased frailty, and decreased mobility among patients. The significant incidence proportion indicates a substantial number of new fall cases, underscoring the need for robust prevention strategies. Our findings, validated by existing literature, emphasize the critical need for ongoing research and effective healthcare policies to reduce fall incidence among cancer patients, ultimately improving their safety and quality of life. In addition to our findings on cancer patients, our study also revealed significant data for patients with diabetes mellitus. Specifically, the incidence proportion for diabetes patients was 21.21%, with a prevalence of 38.33%, and an incidence rate of 0.22 fall cases per person-day. These findings underscore a substantial burden of fall-related incidents within the diabetic patient population. Supporting studies show similar trends. Yang et al., conducted a systematic review and found that older adults with diabetes have a significantly higher risk of falls, with an annual incidence of up to 39% in older adults diabetic individuals. This higher incidence is likely due to complications from diabetes such as neuropathy, poor glycemic control, and increased frailty, which impair balance and increase fall risk 31 . Similarly, Tinetti and Speechley observed that the risk of falls is significantly elevated in diabetic individuals, highlighting the need for targeted prevention strategies 32 . The high prevalence rate in our study may be attributed to the same factors, including poor glycemic control, neuropathy, and other comorbid conditions. These complications can impair balance and mobility, thereby increasing the risk of falls 33 . The significant incidence proportion indicates a substantial number of new fall cases, emphasizing the urgent need for effective fall prevention strategies specifically tailored for diabetic patients. Also, we examined patients with high weight/obesity, finding an incidence proportion of 16.11%, a prevalence of 29.88%, and an incidence rate of 0.16 cases per person-day. Supporting studies align with our findings. Mitchell et al. reported that obesity increases fall risk due to factors such as decreased mobility and joint instability, reinforcing the need for targeted fall prevention strategies in obese populations 34 . These findings highlight the significant impact of comorbid conditions on the risk of falls, emphasizing the need for targeted interventions to manage these comorbidities and reduce fall risk among older adult patients. Strength This study has several notable strengths. Utilizing a large and diverse dataset from the TriNetX network at Virginia Commonwealth University Health System (VCUHS) allows for robust analysis with significant sample size, enhancing statistical power and reliability. The use of standardized ICD-10 codes for data extraction ensures consistency and accuracy in identifying diagnoses and comorbidities, minimizing misclassification risk and improving validity. Covering a five-year period, the study provides a longitudinal perspective on the incidence and prevalence of falls among the older adults, allowing for trend observation over time. Additionally, detailed stratification by age, gender, race, and ethnicity identifies high-risk groups, supporting targeted interventions and policies to reduce fall risk and improve outcomes for older adults’ individuals. Limitation This retrospective study faces multiple limitations that may affect the interpretation of its findings. Firstly, the reliance on electronic health records (EHRs) could introduce biases related to incomplete or inaccurate data entries and variations in documentation practices across different providers. Additionally, the use of ICD-10 codes for data extraction might not fully capture the clinical context, possibly leading to misclassification errors. Due to its retrospective design, the study is unable to establish causal relationships. Another significant limitation is the geographic and institutional restriction of the data to the Virginia Commonwealth University Health System (VCUHS), which may limit the generalizability of the results to other settings. The study also did not account for variables such as the severity of comorbidities and socio-economic factors, which could influence the outcomes, thereby limiting the comprehensiveness of the analysis. Importantly, the time period of data extraction did not explicitly account for the impact of the COVID-19 pandemic. The years 2020 and 2021 saw a notable decrease in reported falls, likely due to increased reluctance to leave home and the presence of more caregivers at home to assist the elderly. This trend might significantly skew the data, representing a critical limitation for this study period. Conclusion The study underscores the critical impact of comorbid conditions such as hypertension, cancer, diabetes mellitus, and obesity on the incidence and prevalence of falls. Hypertension patients were most affected, exhibiting the highest incidence and prevalence rates. The data reveals a clear correlation between these comorbidities and increased fall risks, necessitating targeted preventive strategies and interventions. By addressing these underlying health issues, healthcare providers may have the opportunity to mitigate fall risks, potentially enhancing patient safety and quality of life. However, it is important to note that our study does not conclusively prove this relationship, and further research is needed to establish direct causal links. Declarations Authors' Contributions Asmaa Namoos, MD, MPH, PhD: Conceptualization, methodology, data analysis, writing – original draft preparation, and project administration. Nicholas Thomson, PhD: Supervision, methodology, review, and editing of the manuscript. Sarah Bradley, RN: Data collection, validation, and review of the manuscript. Michel Aboutanos, MPH, MD: Supervision, funding acquisition, and critical review of the manuscript. Acknowledgement and Funding Statemen t We extend our gratitude to the informatics team at Virginia Commonwealth University's (VCU) C. Kenneth and Dianne Wright Center for Clinical and Translational Research, especially Dr. Tamas Gal and his team members, Evan French and Patrick Shi, for their invaluable support in data extraction. This work was supported by the Wright Center under the Clinical and Translational Science Award (CTSA) Grant number UM1TR004360. Data Availability Statement The datasets generated and/or analyzed during the current study were extracted from the TriNetX database and are available upon request from the corresponding author due to privacy and ethical restrictions. Ethics Approval Statement Ethical approval for this study was obtained from the Institutional Review Board (IRB) at Virginia Commonwealth University, classified as a non-human subject submission to ensure adherence to ethical guidelines and patient confidentiality. Access to the TriNetX database was secured through the observational informatics program at Virginia Commonwealth University’s C. Kenneth and Dianne Wright Center for Clinical and Translational Research, following strict data governance protocols to protect patient privacy and comply with regulatory standards. Patient Consent Statement Patient consent was not required for this retrospective study using de-identified data. References Vaishya R, Vaish A. Falls in Older Adults are Serious. Indian J Orthop . 2020;54(1):69-74. doi:10.1007/s43465-019-00037-x Falls. Accessed June 30, 2024. https://www.who.int/news-room/fact-sheets/detail/falls CDC. About Older Adult Fall Prevention. Older Adult Fall Prevention. Published June 13, 2024. Accessed June 30, 2024. https://www.cdc.gov/falls/about/index.html Falls in Older Adults - Geriatrics. Merck Manual Professional Edition. Accessed June 30, 2024. https://www.merckmanuals.com/professional/geriatrics/falls-in-older-adults/falls-in-older-adults Appeadu MK, Bordoni B. Falls and Fall Prevention in Older Adults. In: StatPearls . StatPearls Publishing; 2024. Accessed June 30, 2024. http://www.ncbi.nlm.nih.gov/books/NBK560761/ Prevention I of M (US) D of HP and D, Berg RL, Cassells JS. Falls in Older Persons: Risk Factors and Prevention. In: The Second Fifty Years: Promoting Health and Preventing Disability . National Academies Press (US); 1992. Accessed July 1, 2024. https://www.ncbi.nlm.nih.gov/books/NBK235613/ Qin Z, Baccaglini L. Distribution, Determinants, and Prevention of Falls Among the Elderly in the 2011–2012 California Health Interview Survey. Public Health Rep . 2016;131(2):331-339. Lee DY, Shin S. Association of Sarcopenia with Osteopenia and Osteoporosis in Community-Dwelling Older Korean Adults: A Cross-Sectional Study. J Clin Med . 2021;11(1):129. doi:10.3390/jcm11010129 Stevens J, Sogolow E. Gender differences for non-fatal unintentional fall related injuries among older adults. Inj Prev . 2005;11(2):115-119. doi:10.1136/ip.2004.005835 Risk Factors for Falls Among Seniors: Implications of Gender | Request PDF. ResearchGate . doi:10.1093/aje/kwu268 Bergen G. Falls and Fall Injuries Among Adults Aged ≥65 Years — United States, 2014. MMWR Morb Mortal Wkly Rep . 2016;65. doi:10.15585/mmwr.mm6537a2 Nicklett EJ, Taylor RJ. Racial/ethnic predictors of falls among older adults: The Health and Retirement Study. J Aging Health . 2014;26(6):1060-1075. doi:10.1177/0898264314541698 Falls in African American and White Community-Dwelling Elderly Residents | Request PDF. Accessed June 30, 2024. https://www.researchgate.net/publication/11290209_Falls_in_African_American_and_White_Community-Dwelling_Elderly_Residents Abu Bakar AAZ, Abdul Kadir A, Idris NS, Mohd Nawi SN. Older Adults with Hypertension: Prevalence of Falls and Their Associated Factors. Int J Environ Res Public Health . 2021;18(16):8257. doi:10.3390/ijerph18168257 Risk factors for falls in older adults with diabetes mellitus: systematic review and meta-analysis | BMC Geriatrics | Full Text. Accessed June 30, 2024. https://bmcgeriatr.biomedcentral.com/articles/10.1186/s12877-024-04668-0 G R Neri S, S Oliveira J, B Dario A, M Lima R, Tiedemann A. Does Obesity Increase the Risk and Severity of Falls in People Aged 60 Years and Older? A Systematic Review and Meta-analysis of Observational Studies. J Gerontol A Biol Sci Med Sci . 2020;75(5):952-960. doi:10.1093/gerona/glz272 Balance Problems and Falls | Cancer-related Side Effects | American Cancer Society. Accessed June 30, 2024. https://www.cancer.org/cancer/managing-cancer/side-effects/falls.html Tinetti ME, Han L, Lee DSH, et al. Antihypertensive Medications and Serious Fall Injuries in a Nationally Representative Sample of Older Adults. JAMA Intern Med . 2014;174(4):588-595. doi:10.1001/jamainternmed.2013.14764 Milanesi A, Weinreb JE. Diabetes in the Elderly. In: Feingold KR, Anawalt B, Blackman MR, et al., eds. Endotext . MDText.com, Inc.; 2000. Accessed June 30, 2024. http://www.ncbi.nlm.nih.gov/books/NBK279147/ Morris R, Lewis A. Falls and Cancer. Clin Oncol . 2020;32(9):569-578. doi:10.1016/j.clon.2020.03.011 Jung YS, Suh D, Kim E, Park HD, Suh DC, Jung SY. Medications influencing the risk of fall-related injuries in older adults: case–control and case-crossover design studies. BMC Geriatr . 2023;23(1):452. doi:10.1186/s12877-023-04138-z van Staa TP, Leufkens HGM, Abenhaim L, Zhang B, Cooper C. Oral corticosteroids and fracture risk: relationship to daily and cumulative doses. Rheumatology . 2000;39(12):1383-1389. doi:10.1093/rheumatology/39.12.1383 Real-world data for the life sciences and healthcare | TriNetX. Accessed July 1, 2024. https://trinetx.com/?utm_id=130&utm_campaign=enterprise&utm_source=emagine&utm_medium=paid-display&utm_content=evergreen&gad_source=1&gclid=CjwKCAjwp4m0BhBAEiwAsdc4aAuhCMohbUTSdxCaY02DQr-dYQlT2zUMo-vLvtAwBua2dG1F5XDPyxoC_0cQAvD_BwE Greco EA, Pietschmann P, Migliaccio S. Osteoporosis and Sarcopenia Increase Frailty Syndrome in the Elderly. Front Endocrinol . 2019;10:255. doi:10.3389/fendo.2019.00255 Martin FC, Ranhoff AH. Frailty and Sarcopenia. In: Falaschi P, Marsh D, eds. Orthogeriatrics: The Management of Older Patients with Fragility Fractures . 2nd ed. Springer; 2021. Accessed July 1, 2024. http://www.ncbi.nlm.nih.gov/books/NBK565582/ Asavamongkolkul A, Adulkasem N, Chotiyarnwong P, et al. Prevalence of osteoporosis, sarcopenia, and high falls risk in healthy community-dwelling Thai older adults: a nationwide cross-sectional study. JBMR Plus . 2024;8(2):ziad020. doi:10.1093/jbmrpl/ziad020 Wehner-Hewson N, Watts P, Buscombe R, Bourne N, Hewson D. Racial and Ethnic Differences in Falls Among Older Adults: a Systematic Review and Meta-analysis. J Racial Ethn Health Disparities . 2022;9(6):2427. doi:10.1007/s40615-021-01179-1 Stone CA, Lawlor PG, Savva GM, Bennett K, Kenny RA. Prospective study of falls and risk factors for falls in adults with advanced cancer. J Clin Oncol Off J Am Soc Clin Oncol . 2012;30(17):2128-2133. doi:10.1200/JCO.2011.40.7791 Kenis C, Decoster L, Flamaing J, et al. Incidence of falls and fall-related injuries and their predictive factors in frail older persons with cancer: a multicenter study. BMC Geriatr . 2022;22(1):877. doi:10.1186/s12877-022-03574-7 Campbell G, Wolfe RA, Klem ML. Risk factors for falls in adult cancer survivors: An integrative review. Rehabil Nurs Off J Assoc Rehabil Nurses . 2018;43(4):201-213. doi:10.1097/rnj.0000000000000173 Yang Y, Hu X, Zhang Q, Zou R. Diabetes mellitus and risk of falls in older adults: a systematic review and meta-analysis. Age Ageing . 2016;45(6):761-767. doi:10.1093/ageing/afw140 Tilling LM, Darawil K, Britton M. Falls as a complication of diabetes mellitus in older people. J Diabetes Complications . 2006;20(3):158. Freire LB, Brasil-Neto JP, da Silva ML, et al. Risk factors for falls in older adults with diabetes mellitus: systematic review and meta-analysis. BMC Geriatr . 2024;24(1):201. doi:10.1186/s12877-024-04668-0 Mitchell RJ, Lord SR, Harvey LA, Close JCT. Obesity and falls in older people: mediating effects of disease, sedentary behavior, mood, pain and medication use. Arch Gerontol Geriatr . 2015;60(1):52-58. doi:10.1016/j.archger.2014.09.006 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4762014","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":328663934,"identity":"cc697a0f-d536-40d6-88c6-3fdd7cdf890c","order_by":0,"name":"Asmaa M Namoos","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYNCDD0BswMDAeICxgUgdjDMgWhgOHCRWCzMPMVr4+08nfvjBcEdet7358GfbNrvE7ezNDw5/3MEgZ96/AKsWiRu5myV7GJ4ZbjtzLE06ty05cWfPMYMDB88wGMvceIDdmhu8GyR4GA4zbruRY8acc+ZA4oYbCUAtbQyJMyQOYNUhf/7s5p9/GA7bA7UYf7YAabn//ANeLQYHcrdJA21JBGoxkGaoANnCA7WFH3sYGN7I3WYtY3A4GeQXyZ6KZOMNZ3IKDpxtkzCWkMDuFTmgw26+qThsu+148+EPPwzsZDccP77xQWWbjZwEP3aHQZ2HKQS0QiIBjxbsAK8to2AUjIJRMIIAAIlXcGMmtJqLAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-7720-0500","institution":"Virginia Commonwealth University","correspondingAuthor":true,"prefix":"","firstName":"Asmaa","middleName":"M","lastName":"Namoos","suffix":""},{"id":328663935,"identity":"22342fa4-a590-4466-a61b-a635cb8434e8","order_by":1,"name":"Nicholas Thomson","email":"","orcid":"","institution":"Virginia Commonwealth University","correspondingAuthor":false,"prefix":"","firstName":"Nicholas","middleName":"","lastName":"Thomson","suffix":""},{"id":328663936,"identity":"9cdbb493-9dd1-4074-98be-fd60567c8239","order_by":2,"name":"Sarah Bradley","email":"","orcid":"","institution":"Virginia Commonwealth University","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Bradley","suffix":""},{"id":328663937,"identity":"2b643cb6-60ab-4d99-88c1-c44ac6a55cac","order_by":3,"name":"Michel Aboutanos","email":"","orcid":"","institution":"Virginia Commonwealth University","correspondingAuthor":false,"prefix":"","firstName":"Michel","middleName":"","lastName":"Aboutanos","suffix":""}],"badges":[],"createdAt":"2024-07-18 10:52:54","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-4762014/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4762014/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60650533,"identity":"13e22503-b768-4004-adc5-8e8d925e577e","added_by":"auto","created_at":"2024-07-19 06:22:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":809940,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4762014/v1/713095a6-31cc-492e-82dd-5125e7bc004b.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe Impact of Demographics and Comorbidities on Fall Incidence and Prevalence in Older Adults\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eFalls among older adult individuals represent a significant public health concern due to their profound impacts on morbidity, mortality, and quality of life\u003csup\u003e1\u003c/sup\u003e. The World Health Organization reports that falls are the second leading cause of unintentional injury deaths worldwide, particularly affecting adults older than 65 years old\u003csup\u003e2\u003c/sup\u003e. The Centers for Disease Control and Prevention (CDC) identify falls as the leading cause of injury and injury-related deaths in older adults in the United States\u003csup\u003e3\u003c/sup\u003e. Over recent years, the incidence and prevalence of falls have shown a disturbing upward trend\u003csup\u003e3\u003c/sup\u003e. Annually, approximately 36\u0026nbsp;million older adults experience a fall, leading to over 32,000 fatalities and nearly 3\u0026nbsp;million emergency department visits\u003csup\u003e3,4\u003c/sup\u003e. This rising trend is influenced by factors including an aging population, prevalent chronic conditions, and inadequate environmental safety\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eResearch consistently demonstrates that the risk of falls increases with age. Specifically, individuals aged 85 and older experience the highest incidence of falls, with 13.5% reporting fall injuries and approximately 40% falling each year\u003csup\u003e6,7\u003c/sup\u003e. Additionally, gender differences are notable, with women more likely to experience falls than men, potentially due to higher rates of osteoporosis and sarcopenia in women, which contribute to frailty and balance issues\u003csup\u003e8\u0026ndash;10\u003c/sup\u003e. In addition to age and gender, racial disparities also play a significant role in the risk of falls among older adults. The studies showed that African American and Hispanic older adult populations have higher rates of fall-related injuries compared to their White counterparts\u003csup\u003e11\u0026ndash;13\u003c/sup\u003e. This discrepancy can be attributed to factors such as differences in socioeconomic status, access to healthcare, health care complexity and the prevalence of chronic conditions that exacerbate fall risk\u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMoreover, chronic conditions such as hypertension, diabetes mellitus, obesity and cancer are prevalent in this population and are associated with an increased risk of falls\u003csup\u003e14\u0026ndash;17\u003c/sup\u003e. A high proportion (75%) of older adult fall patients suffer from hypertension, which can lead to dizziness and balance problems, especially when antihypertensive medications are involved\u003csup\u003e18\u003c/sup\u003e. Diabetes mellitus, affecting about 38% of older adult fall patients, can cause neuropathy and vision impairments, thereby increasing the risk of falls \u003csup\u003e15,19\u003c/sup\u003e. Cancer also presents unique challenges; approximately 43% of older adults fall patients are affected, and treatments such as chemotherapy can lead to muscle weakness, fatigue, and neuropathy, all of which increase susceptibility to falls \u003csup\u003e20\u003c/sup\u003e. Moreover, corticosteroid use, often prescribed for cancer-related conditions, has been linked to adverse fall outcomes, particularly among hypertensive patients, exacerbating fall risks due to muscle wasting and bone loss\u003csup\u003e21,22\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFalls among older adults not only pose a significant risk for injury but also underscore a mounting public health challenge indicative of underlying gaps in geriatric health management and preventive care. This retrospective study investigates the incidence and prevalence of falls over the past four years using data extracted from the TriNetX network Virginia Commonwealth University- Health System VCUHS database spanning from 2019 to 2023. With ethical approval secured, the study analyses a cohort of 16,400 individuals aged 65 and above who were presented at hospitals with fall-related trauma. By examining the demographics, including age, gender, ethnicity and racial distribution, alongside comorbidities and risk factors associated with these incidents, this research aims to explore incidence and prevalence of falls related trauma. The findings from this project are critical for developing targeted interventions to reduce the frequency and severity of falls among the older adults. These results will be used to refine fall risk assessments and to shape effective strategies for intervention at both the individual and community levels.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eA retrospective cohort study utilizes data extracted from the TriNetX network VCU database, encompassing 16,400 participants from January 1st, 2019 to December 31st, 2023. The study aims to evaluate the incidence and prevalence of falls among older adults aged 65 years and above who are presented at hospitals with fall-related trauma.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eData for this retrospective cohort study was obtained from the TriNetX network at Virginia Commonwealth University Health System (VCUHS), which aggregates electronic health records (EHRs) exclusively from within the VCUHS network. This database serves as a comprehensive repository of patient information, including demographics such as age, gender, ethnicity and race. These demographic details are used to characterize the study population of older adults aged 65 years and above who experienced fall-related trauma. Clinical diagnoses documented in the EHRs provide insights into prevalent health conditions and comorbidities among the cohort, including hypertension, obesity, diabetes mellitus, and cancer, all of which influence fall risk and outcomes. Procedures recorded in the database illuminate the medical interventions and treatments administered to patients following fall-related injuries, offering context for understanding healthcare management strategies and utilization patterns.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Handling and Analysis\u003c/h2\u003e \u003cp\u003eThe richness of data within the TriNetX network\u003csup\u003e23\u003c/sup\u003e facilitated robust statistical analysis. Descriptive statistics were employed to characterize the study population, detailing variables such as age, gender, race, and the prevalence and incidence rate of comorbid conditions. These statistics included means, medians, standard deviations, and frequency distributions. The prevalence and incidence functions on the TriNetX platform were utilized to accurately capture and analyze these metrics, providing a comprehensive overview of the study population's health status and the impact of comorbid conditions on fall risk. Additionally, patients were identified through ICD-10 codes related to fall injuries, ensuring accurate classification and analysis of fall-related trauma cases.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDemographics\u003c/h2\u003e \u003cp\u003eThe study population consisted of 16,400 individuals aged 65 years and above, with a mean age of 77.3 years (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;8.07), who were presented with fall-related trauma. Gender distribution showed that 60.97% (10,000) of the patients were female, while 39.02% (6,400) were male, with a small fraction (0.06%, or 10 individuals) having an unknown gender. In terms of ethnicity, a vast majority, 96.4% (15,810), were not Hispanic or Latino, 3.04% (500) were Hispanic or Latino, and 0.6% (100) had unknown ethnicity.\u003c/p\u003e \u003cp\u003eRegarding race, 62.92% (10,320) of the patients were White, 31.58% (5,180) were Black or African American, 2.92% (480) were Asian, 0.6% (100) were American Indian or Alaska Native, and 0.18% (30) were Native Hawaiian or Other Pacific Islander. Additionally, 1.89% (310) of the patients identified as another race. This demographic distribution provides a comprehensive overview of the study population, highlighting the diversity and prevalent characteristics within the older adult cohort who experienced falls (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of the Study Population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (77.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16,400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15,810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10,320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmerican Indian or Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIncidence and Prevalence by Demographics\u003c/h2\u003e \u003cp\u003eOur study examined falls among older adults, analyzing data by age, gender, race, and ethnicity. The highest incidence proportion, 26.78%, and a prevalence of 46.18% were recorded among individuals aged 65\u0026ndash;69, with an incidence rate of 2.86 per 1,000 person-days. This trend decreased with age; individuals 85 and older showed the lowest rates: an incidence proportion of 18.06% and prevalence of 33.68%. Males demonstrated higher incidence (26.25%) and prevalence (44.54%) compared to females (22.19% incidence and 42.21% prevalence). Racial analysis revealed the highest incidence among American Indian or Alaska Native individuals at 50%, with a prevalence of 33.33%. Black or African American individuals had an incidence proportion of 24.23% and a prevalence of 47.87%. For ethnicity, Hispanic or Latino individuals had an incidence proportion of 22.22% and a prevalence of 30%, but the highest incidence rate of 4.66 per 1,000 person-days, whereas Non-Hispanic or Latino individuals exhibited an incidence proportion of 23.97% and a prevalence of 43.62%. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIncidence and Prevalence of Falls Stratified by Demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncidence Proportion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIncidence Rate (cases/person-day)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26778242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4617737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.8573073E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2614679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4651163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7698395E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.24022347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.43514645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7270336E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.20714286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39673913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4734615E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 and older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.18064517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.33684212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4629655E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22192152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.42211056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3936154E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.44541408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.0896158E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011947432\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmerican Indian or Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.33333334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.108818E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2857143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.583138E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.24225353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47868216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4403581E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01017294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29032257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.816898E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23954372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4163424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7602146E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.33333334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3377126E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22222222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.6598323E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23972602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4361905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6624283E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1904762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.30612245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1566889E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eIncidence and Prevalence of Falls among Patients with Diabetes Mellitus Type II\u003c/h2\u003e \u003cp\u003eDiabetes Mellitus Type II incidence proportion was 21.21% with a prevalence of 38.33% and an incidence rate of 2.20 cases per 1,000 person-days. Age-specific analysis showed a gradual decrease in incidence proportion from 22.49% in the 65\u0026ndash;69 age group to 16.88% in those 85 and older. Similarly, prevalence and incidence rates varied slightly across age groups. Gender analysis revealed that males had a higher incidence proportion (24%) and prevalence (40.44%) compared to females. In terms of racial stratification, American Indian or Alaska Native individuals had the highest rates with an incidence proportion of 50% and prevalence of 66.67%. Ethnicity-wise, Hispanic or Latino individuals exhibited a high incidence rate of 6.56 cases per 1,000 person-days, matching a prevalence of 30%. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComorbidities Stratified Results by Demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eDiabetes Mellites type DM II\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncidence Proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIncidence Rate (cases/person-day)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019-01-01\u0026ndash;2023-12-31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21205008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38334355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2008002E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2248996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40978593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2014206E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23043478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41196012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2894268E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22872343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39330545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4665735E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21333334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35869566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3355192E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 and older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1087358E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19512194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.36984923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.9574359E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40438873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6387515E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011947432\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmerican Indian or Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66666667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.041573E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7848172E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2764706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5232558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7974666E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010050251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2413793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29032257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.7190918E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1863426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3151751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.9083255E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24324325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41666666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.7255973E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.556804E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21026894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.384127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.164523E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26190478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3877551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.1567106E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eHypertension (HTN)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncidence Proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIncidence Rate (cases/person-day)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5667396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75750154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.408766E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5277778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74006116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.978435E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5903614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77408636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.3713007E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7824268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0010945909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64761907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79891306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0012591217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 and older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6513761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0016007035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5332136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7386935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.3775294E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6201117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7868339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0011324827\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.90909094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmerican Indian or Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6666667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.45666E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.378484E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6492891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85658914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0011636964\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.029325513\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5769231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6451613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0011215121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5470219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71789885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.729749E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45454547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0010088985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0015579155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5650173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.361068E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5945946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71428573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.916029E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncidence Proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIncidence Rate (cases/person-day)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23832923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4318876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.634043E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eAge Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26666668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46341464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.812224E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2614679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46357617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7299204E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24022347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43333334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.704202E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20567375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39673913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.451714E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 and older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18064517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33684212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.447009E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22297297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4232698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.38103E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26403326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4453125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.0847368E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011947432\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24050634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41650486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7436882E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24507043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48069498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4444156E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2857143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.5910512E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01017294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmerican Indian or Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33333334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.108818E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29032257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.751199E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33333334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3280564E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22222222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.4066453E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24102564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43726236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6529646E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1904762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1467751E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eHigh Weight/ Obesity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncidence Proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIncidence Rate (cases/person-day)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16105418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2988365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6495131E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20152092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35779816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0036096E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18032786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33554816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.773495E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15686275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28033474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6027583E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09580839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18478261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.729123E-5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 and older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06818182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1368421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.991337E-5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.17013463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31859297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.722493E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14754099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26802507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5379589E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmerican Indian or Alaska Native\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6666667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4114894E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11111111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1108396E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18734178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37790698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8117481E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021645023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15410574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26750973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.594208E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.13333334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16129032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8771234E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11904762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22916667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.4704412E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.9410692E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Hispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16259542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.30349207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.657288E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1521739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.20408164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6150318E-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eIncidence and Prevalence of Falls among Patients with Hypertension (HTN)\u003c/h2\u003e \u003cp\u003eThe incidence and prevalence of falls among hypertensive patients, revealing that 56.67% experienced at least one fall, with a prevalence of 75.75% and a high incidence rate of 9.41 per 1,000 person-days. Older age groups, particularly those aged 85 and older, displayed the highest figures: a 65.14% incidence and 80% prevalence. Males showed a greater incidence (62.01%) and prevalence (78.68%) compared to females. Racially, Native Hawaiian or Other Pacific Islander individuals recorded the highest rates, both at 100%, with a notably high incidence rate of 29.33 per 1,000 person-days. Among ethnic groups, Hispanic or Latino individuals reported a 60% incidence and prevalence, demonstrating significant variations across demographics in the impact of hypertension on fall risk. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIncidence and Prevalence of Falls among Patients with Cancer\u003c/h2\u003e \u003cp\u003eThe incidence proportion of falls among Patients with Cancer \u003cem\u003eis\u003c/em\u003e 23.83% and a prevalence of 43.19%, with an incidence rate of 2.63 per 1,000 person-days. Incidence rates were highest among those aged 65\u0026ndash;69 years at 26.67% and gradually decreased with age, with the lowest rates observed in individuals 85 and older. Males displayed higher rates compared to females, with a 26.40% incidence and 44.53% prevalence. Racial disparities were pronounced, with Native Hawaiian or Other Pacific Islander individuals showing an incidence and prevalence of 100%, and the highest incidence rate of 10.17 per 1,000 person-days. Hispanic or Latino patients also showed higher rates compared to non-Hispanic or Latino, emphasizing the variability across different ethnic and racial groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eIncidence and Prevalence of Falls among Patients with High Weight/Obesity\u003c/h2\u003e \u003cp\u003eThe incidence proportion of high Weight/Obesity is 16.11% with prevalence of 29.88%, with an incidence rate of 1.65 per 1,000 person-days. Incidence proportions were highest in the 65\u0026ndash;69 age group at 20.15% and decreased with age, showing the lowest rates in those 85 and older. Females displayed higher incidence proportions (17.01%) and prevalence (31.86%) compared to males. Racial differences were significant, with Native Hawaiian or Other Pacific Islander individuals recording the highest incidence and prevalence at 100%, and an incidence rate of 21.65 per 1,000 person-days. Ethnic variations also showed that Hispanic or Latino individuals had a notably lower incidence proportion and prevalence of 10%, while Non-Hispanic or Latino individuals reported higher figures. These findings underscore the varying impact of obesity on fall risks across different demographic groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSummery\u003c/h2\u003e \u003cp\u003eThe study examined the incidence and prevalence of falls among patients with various comorbidities, including cancer, diabetes mellitus, hypertension (HTN), and high weight/obesity. Among the fall patients, those with hypertension had the highest incidence proportion at 56.67% (0.5667396), with a prevalence of 75.75% (0.75750154) and an incidence rate of 0.94 cases per person-day (0.0009408766). Patients with cancer showed an incidence proportion of 23.71% (0.23707958), a prevalence of 43.11% (0.4311084), and an incidence rate of 0.26 cases per person-day (0.000264396). For those with diabetes mellitus, the incidence proportion was 21.21% (0.21205008), with a prevalence of 38.33% (0.38334355) and an incidence rate of 0.22 cases per person-day (0.000220008). Patients with high weight/obesity exhibited an incidence proportion of 16.11% (0.16105418), a prevalence of 29.88% (0.2988365), and an incidence rate of 0.16 cases per person-day (0.00016495131).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this study underscore the significant impact of falls among the older adult population, highlighting critical demographic disparities and the prevalence of comorbidities. The data obtained from the TriNetX network at Virginia Commonwealth University Health System (VCUHS) provided a comprehensive overview of the incidence and prevalence of falls among individuals aged 65 and older over a five-year period.\u003c/p\u003e \u003cp\u003eThe demographic analysis reveals that falls are most frequent among those aged 65\u0026ndash;69, with an incidence of 26.78% and a prevalence of 46.18%. Rates generally decrease with age. Research consistently shows that the risk of falls escalates with age, especially among individuals aged 85 and older, who are notably prone to falling \u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMales exhibit higher fall rates (incidence: 26.25%, prevalence: 44.54%) compared to females (incidence: 22.19%, prevalence: 42.21%). Literature indicates that women are more likely to experience falls than men, possibly due to higher rates of osteoporosis and sarcopenia contributing to frailty and balance issues\u003csup\u003e24(p3) 25,26\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong ethnic groups, American Indian or Alaska Native individuals show the highest fall incidence (50%) and rate (5.11 per 1,000 person-days), highlighting significant racial disparities. Hispanic or Latino individuals have an incidence of 22.22% and the highest rate (4.66 per 1,000 person-days), underscoring the need for targeted interventions. Studies reveal that African American and Hispanic older adult populations experience higher rates of fall-related injuries compared to their White counterparts, emphasizing significant disparities in fall risks among ethnic groups\u003csup\u003e27 12\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe incidence and prevalence of falls among patients with various comorbidities, including cancer, diabetes mellitus, hypertension (HTN), and high weight/obesity. Our results indicate that among patients who experienced falls, those with hypertension had the highest incidence proportion (56.67%) and prevalence (75.75%), as well as an elevated incidence rate per person-day. Hypertension, in particular, is associated with the highest incidence and prevalence of falls, potentially due to the effects of antihypertensive medications causing dizziness and balance problems\u003csup\u003e14,18\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur study found that cancer patients had an incidence proportion of 23.71%, a prevalence of 43.11%, and an incidence rate of 0.26 fall cases per person-day. These results highlight a significant burden of fall-related incidents among cancer patients.\u003c/p\u003e \u003cp\u003eSimilar studies support our findings. Stone et al. reported that falls are common among cancer patients, with a prevalence and incidence rate that closely align with our data\u003csup\u003e28\u003c/sup\u003e. They noted that cancer treatments, increased frailty, and decreased mobility contribute significantly to falling risk among these patients\u003csup\u003e29\u003c/sup\u003e. Additionally, Capone et al. found comparable incidence rates, underscoring the widespread nature of this issue in cancer populations\u003csup\u003e30\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe high prevalence rate observed in our study might be due to factors such as cancer treatment side effects, increased frailty, and decreased mobility among patients. The significant incidence proportion indicates a substantial number of new fall cases, underscoring the need for robust prevention strategies.\u003c/p\u003e \u003cp\u003eOur findings, validated by existing literature, emphasize the critical need for ongoing research and effective healthcare policies to reduce fall incidence among cancer patients, ultimately improving their safety and quality of life.\u003c/p\u003e \u003cp\u003eIn addition to our findings on cancer patients, our study also revealed significant data for patients with diabetes mellitus. Specifically, the incidence proportion for diabetes patients was 21.21%, with a prevalence of 38.33%, and an incidence rate of 0.22 fall cases per person-day. These findings underscore a substantial burden of fall-related incidents within the diabetic patient population.\u003c/p\u003e \u003cp\u003eSupporting studies show similar trends. Yang et al., conducted a systematic review and found that older adults with diabetes have a significantly higher risk of falls, with an annual incidence of up to 39% in older adults diabetic individuals. This higher incidence is likely due to complications from diabetes such as neuropathy, poor glycemic control, and increased frailty, which impair balance and increase fall risk\u003csup\u003e31\u003c/sup\u003e. Similarly, Tinetti and Speechley observed that the risk of falls is significantly elevated in diabetic individuals, highlighting the need for targeted prevention strategies\u003csup\u003e32\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe high prevalence rate in our study may be attributed to the same factors, including poor glycemic control, neuropathy, and other comorbid conditions. These complications can impair balance and mobility, thereby increasing the risk of falls\u003csup\u003e33\u003c/sup\u003e. The significant incidence proportion indicates a substantial number of new fall cases, emphasizing the urgent need for effective fall prevention strategies specifically tailored for diabetic patients.\u003c/p\u003e \u003cp\u003eAlso, we examined patients with high weight/obesity, finding an incidence proportion of 16.11%, a prevalence of 29.88%, and an incidence rate of 0.16 cases per person-day. Supporting studies align with our findings. Mitchell et al. reported that obesity increases fall risk due to factors such as decreased mobility and joint instability, reinforcing the need for targeted fall prevention strategies in obese populations\u003csup\u003e34\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThese findings highlight the significant impact of comorbid conditions on the risk of falls, emphasizing the need for targeted interventions to manage these comorbidities and reduce fall risk among older adult patients.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrength\u003c/h2\u003e \u003cp\u003eThis study has several notable strengths. Utilizing a large and diverse dataset from the TriNetX network at Virginia Commonwealth University Health System (VCUHS) allows for robust analysis with significant sample size, enhancing statistical power and reliability. The use of standardized ICD-10 codes for data extraction ensures consistency and accuracy in identifying diagnoses and comorbidities, minimizing misclassification risk and improving validity. Covering a five-year period, the study provides a longitudinal perspective on the incidence and prevalence of falls among the older adults, allowing for trend observation over time. Additionally, detailed stratification by age, gender, race, and ethnicity identifies high-risk groups, supporting targeted interventions and policies to reduce fall risk and improve outcomes for older adults\u0026rsquo; individuals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitation\u003c/h2\u003e \u003cp\u003eThis retrospective study faces multiple limitations that may affect the interpretation of its findings. Firstly, the reliance on electronic health records (EHRs) could introduce biases related to incomplete or inaccurate data entries and variations in documentation practices across different providers. Additionally, the use of ICD-10 codes for data extraction might not fully capture the clinical context, possibly leading to misclassification errors. Due to its retrospective design, the study is unable to establish causal relationships.\u003c/p\u003e \u003cp\u003eAnother significant limitation is the geographic and institutional restriction of the data to the Virginia Commonwealth University Health System (VCUHS), which may limit the generalizability of the results to other settings. The study also did not account for variables such as the severity of comorbidities and socio-economic factors, which could influence the outcomes, thereby limiting the comprehensiveness of the analysis.\u003c/p\u003e \u003cp\u003eImportantly, the time period of data extraction did not explicitly account for the impact of the COVID-19 pandemic. The years 2020 and 2021 saw a notable decrease in reported falls, likely due to increased reluctance to leave home and the presence of more caregivers at home to assist the elderly. This trend might significantly skew the data, representing a critical limitation for this study period.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study underscores the critical impact of comorbid conditions such as hypertension, cancer, diabetes mellitus, and obesity on the incidence and prevalence of falls. Hypertension patients were most affected, exhibiting the highest incidence and prevalence rates. The data reveals a clear correlation between these comorbidities and increased fall risks, necessitating targeted preventive strategies and interventions. By addressing these underlying health issues, healthcare providers may have the opportunity to mitigate fall risks, potentially enhancing patient safety and quality of life. However, it is important to note that our study does not conclusively prove this relationship, and further research is needed to establish direct causal links.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eAsmaa Namoos, MD, MPH, PhD:\u003c/strong\u003e Conceptualization, methodology, data analysis, writing \u0026ndash; original draft preparation, and project administration.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eNicholas Thomson, PhD:\u003c/strong\u003e Supervision, methodology, review, and editing of the manuscript.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSarah Bradley, RN:\u003c/strong\u003e Data collection, validation, and review of the manuscript.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMichel Aboutanos, MPH, MD:\u003c/strong\u003e Supervision, funding acquisition, and critical review of\u0026nbsp;the manuscript.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement and Funding Statemen\u003c/strong\u003et\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe extend our gratitude to the informatics team at Virginia Commonwealth University\u0026apos;s (VCU) C. Kenneth and Dianne Wright Center for Clinical and Translational Research, especially Dr. Tamas Gal and his team members, Evan French and Patrick Shi, for their invaluable support in data extraction. This work was supported by the Wright Center under the Clinical and Translational Science Award (CTSA) Grant number UM1TR004360.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study were extracted from the TriNetX database and are available upon request from the corresponding author due to privacy and ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Institutional Review Board (IRB) at Virginia Commonwealth University, classified as a non-human subject submission to ensure adherence to ethical guidelines and patient confidentiality. Access to the TriNetX database was secured through the observational informatics program at Virginia Commonwealth University\u0026rsquo;s C. Kenneth and Dianne Wright Center for Clinical and Translational Research, following strict data governance protocols to protect patient privacy and comply with regulatory standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Consent Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient consent was not required for this retrospective study using de-identified data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVaishya R, Vaish A. Falls in Older Adults are Serious. \u003cem\u003eIndian J Orthop\u003c/em\u003e. 2020;54(1):69-74. doi:10.1007/s43465-019-00037-x\u003c/li\u003e\n\u003cli\u003eFalls. Accessed June 30, 2024. https://www.who.int/news-room/fact-sheets/detail/falls\u003c/li\u003e\n\u003cli\u003eCDC. About Older Adult Fall Prevention. Older Adult Fall Prevention. Published June 13, 2024. Accessed June 30, 2024. https://www.cdc.gov/falls/about/index.html\u003c/li\u003e\n\u003cli\u003eFalls in Older Adults - Geriatrics. 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Racial and Ethnic Differences in Falls Among Older Adults: a Systematic Review and Meta-analysis. \u003cem\u003eJ Racial Ethn Health Disparities\u003c/em\u003e. 2022;9(6):2427. doi:10.1007/s40615-021-01179-1\u003c/li\u003e\n\u003cli\u003eStone CA, Lawlor PG, Savva GM, Bennett K, Kenny RA. Prospective study of falls and risk factors for falls in adults with advanced cancer. \u003cem\u003eJ Clin Oncol Off J Am Soc Clin Oncol\u003c/em\u003e. 2012;30(17):2128-2133. doi:10.1200/JCO.2011.40.7791\u003c/li\u003e\n\u003cli\u003eKenis C, Decoster L, Flamaing J, et al. Incidence of falls and fall-related injuries and their predictive factors in frail older persons with cancer: a multicenter study. \u003cem\u003eBMC Geriatr\u003c/em\u003e. 2022;22(1):877. doi:10.1186/s12877-022-03574-7\u003c/li\u003e\n\u003cli\u003eCampbell G, Wolfe RA, Klem ML. Risk factors for falls in adult cancer survivors: An integrative review. \u003cem\u003eRehabil Nurs Off J Assoc Rehabil Nurses\u003c/em\u003e. 2018;43(4):201-213. doi:10.1097/rnj.0000000000000173\u003c/li\u003e\n\u003cli\u003eYang Y, Hu X, Zhang Q, Zou R. Diabetes mellitus and risk of falls in older adults: a systematic review and meta-analysis. \u003cem\u003eAge Ageing\u003c/em\u003e. 2016;45(6):761-767. doi:10.1093/ageing/afw140\u003c/li\u003e\n\u003cli\u003eTilling LM, Darawil K, Britton M. Falls as a complication of diabetes mellitus in older people. \u003cem\u003eJ Diabetes Complications\u003c/em\u003e. 2006;20(3):158.\u003c/li\u003e\n\u003cli\u003eFreire LB, Brasil-Neto JP, da Silva ML, et al. Risk factors for falls in older adults with diabetes mellitus: systematic review and meta-analysis. \u003cem\u003eBMC Geriatr\u003c/em\u003e. 2024;24(1):201. doi:10.1186/s12877-024-04668-0\u003c/li\u003e\n\u003cli\u003eMitchell RJ, Lord SR, Harvey LA, Close JCT. Obesity and falls in older people: mediating effects of disease, sedentary behavior, mood, pain and medication use. \u003cem\u003eArch Gerontol Geriatr\u003c/em\u003e. 2015;60(1):52-58. doi:10.1016/j.archger.2014.09.006\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Virginia Commonwealth University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Falls, Older adults, Incidence, Prevalence, Comorbidities","lastPublishedDoi":"10.21203/rs.3.rs-4762014/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4762014/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cu\u003eIntroduction\u003c/u\u003e: Falls among older adults are more than mere accidents; they are a silent epidemic, profoundly impacting the health and well-being of millions of older adults worldwide. This study examines the incidence and prevalence of falls among individuals aged 65 and above, focusing on the influence of demographic factors and comorbid conditions such as hypertension, diabetes mellitus, cancer, and obesity.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eMethods: \u003c/u\u003eA retrospective cohort study was conducted using data from the TriNetX network at Virginia Commonwealth University Health System (VCUHS) from 2019 to 2023. The study population included 16,400 individuals aged 65 and above who presented with fall-related trauma. Data on demographics, clinical diagnoses, procedures, and comorbid conditions were analyzed using descriptive statistics to evaluate the incidence and prevalence of falls.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eResults: \u003c/u\u003eThe mean age of the study population was 77.3 years, with a higher proportion of females (60.97%) compared to males (39.02%). Despite the larger number of female participants, incidence and prevalence of falls were highest among individuals aged 65-69 years, and fall rates were notably higher among males compared to females. This suggests that while fewer in number, males in our study experienced falls more frequently. Patients with hypertension had the highest incidence proportion (56.67%) and prevalence (75.75%) among comorbid conditions.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConclusions:\u003c/u\u003e Falls among older adults are significantly influenced by demographic factors and comorbid conditions. Hypertension, in particular, is associated with the highest fall risk. These findings highlight the need for targeted interventions to manage comorbidities and reduce fall risks among older adult patients.\u003c/p\u003e","manuscriptTitle":"The Impact of Demographics and Comorbidities on Fall Incidence and Prevalence in Older Adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-19 06:14:19","doi":"10.21203/rs.3.rs-4762014/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"92d1264b-0cda-4c58-a735-e44ff9f6c79b","owner":[],"postedDate":"July 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":34787485,"name":"Geriatrics \u0026 Gerontology"}],"tags":[],"updatedAt":"2024-07-19T06:14:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-19 06:14:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4762014","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4762014","identity":"rs-4762014","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}