A prospective cohort study on the prevalence and influencing factors of falls among community-dwelling older adults in Guangzhou City

SUN Siyu; YANG Wenhao; HUANG Tingyuan; YUAN Lexin; CHEN Jiamin; LIU Hui; LIN Weiquan; ZHU Wei

doi:10.16462/j.cnki.zhjbkz.2024.10.008

Volume 28 Issue 10

Oct. 2024

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SUN Siyu, YANG Wenhao, HUANG Tingyuan, YUAN Lexin, CHEN Jiamin, LIU Hui, LIN Weiquan, ZHU Wei. A prospective cohort study on the prevalence and influencing factors of falls among community-dwelling older adults in Guangzhou City[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(10): 1164-1169. doi: 10.16462/j.cnki.zhjbkz.2024.10.008

Citation:

SUN Siyu, YANG Wenhao, HUANG Tingyuan, YUAN Lexin, CHEN Jiamin, LIU Hui, LIN Weiquan, ZHU Wei. A prospective cohort study on the prevalence and influencing factors of falls among community-dwelling older adults in Guangzhou City[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(10): 1164-1169. doi: 10.16462/j.cnki.zhjbkz.2024.10.008

Citation:

SUN Siyu, YANG Wenhao, HUANG Tingyuan, YUAN Lexin, CHEN Jiamin, LIU Hui, LIN Weiquan, ZHU Wei. A prospective cohort study on the prevalence and influencing factors of falls among community-dwelling older adults in Guangzhou City[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(10): 1164-1169. doi: 10.16462/j.cnki.zhjbkz.2024.10.008

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A prospective cohort study on the prevalence and influencing factors of falls among community-dwelling older adults in Guangzhou City

doi: 10.16462/j.cnki.zhjbkz.2024.10.008

SUN Siyu¹,
YANG Wenhao¹,
HUANG Tingyuan²,
YUAN Lexin³,
CHEN Jiamin⁴,
LIU Hui⁴,
LIN Weiquan^{4
,
,},
ZHU Wei^{1, 5
,
,}

1.
Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China
2.
Department of Chronic Non-Communicable Disease Prevention and Control, Center for Disease Control and Prevention of Guangzhou, Guangzhou 510440, China
3.
Department of Nursing, Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
4.
Department of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou 510440, China
5.
Department of Science and Education, Center for Disease Control and Prevention of Guangzhou, Guangzhou 510440, China

SUN Siyu, YANG Wenhao and HUANG Tingyuan contributed equally to this work

Funds:

National Natural Science Foundation of China 72104061

Guangzhou Municipal Health Science and Technology Project 20241A011055

Key Medical Discipline Construction Project of Guangzhou 2021-2023-12

Guangzhou Key Laboratory for Chronic and Major Disease Monitoring and Control 2024A03J0558

More Information

Corresponding author: LIN Weiquan, E-mail: linweiquan0503@163.com; ZHU Wei, E-mail: gzcdc_zhuw@gz.gov.cn
Received Date: 2024-06-04
Rev Recd Date: 2024-09-19

Available Online: 2024-12-11

Publish Date: 2024-10-10

Abstract

Abstract

Objective To understand the prevalence and influencing factors of falls among community-dwelling older adults in Guangzhou City, and to explore the synergistic patterns and influencing pathways among different factors. Methods The prospective cohort study method was used for a baseline survey of 4 950 community-dwelling older adults aged 65 years and above in Guangzhou City in 2021; the occurrence of falls and other health conditions among baseline older adults was followed up in 2022. Cox proportional hazards model was used to analyze the influencing factors of falls. Association rules and Bayesian network modeling were used to analyze the synergistic patterns and influence pathways of the influencing factors. Results A final valid sample of 3 393 older adults was included with a median follow-up of 1.53 years. The prevalence of falls was 25.49% (95% CI: 24.02%-26.96%). Cox proportional hazards model results showed that females (HR=1.246, 95% CI: 1.088-1.426), ≥75 years (HR=1.343, 95% CI: 1.133-1.592), insured (HR=1.440, 95% CI: 1.038-1.997), diabetes (HR=1.309, 95% CI: 1.143-1.498) and stroke (HR=1.914, 95% CI: 1.309-2.799) increased the risk of falls occurring in older adults; high school and above (HR=0.861, 95% CI: 0.750-0.987), daily exercise (HR=0.684, 95% CI: 0.580-0.807), and satisfaction with self-assessment of health status (HR=0.484, 95% CI: 0.278-0.841) reduced the risk of falls among older adults. The results of association rules showed that the most common collaboration mode was diabetes, females, and falls (support: 19.07%, confidence: 32.77%, lift: 1.29). The result of Bayesian Network model showed that exercise frequency, age, education, self-assessment of health status, gender, diabetes, and stroke were the important influencing factors of falls, and the area under the curve of the model was 0.612. Conclusions The prevalence of falls among community-dwelling older adults in Guangzhou City was high, and the influencing factors are complex. It is recommended to develop and implement comprehensive intervention measures for high-risk groups, including those who are physically inactive, elderly, female, and those with chronic diseases.
- Falls,
- Prevalence,
- Cox proportional hazards model,
- Association rule,
- Bayesian network

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References(23)

References

[1]	国家统计局. 人口老龄化及其衡量标准是什么[EB/OL]. (2023-01-01)[2024-05-26]. https://www.stats.gov.cn/zs/tjws/tjbz/202301/t20230101_1903949.html#:~:text.
[2]	Peng K, Tian MY, Andersen M, et al. Incidence, risk factors and economic burden of fall-related injuries in older Chinese people: a systematic review[J]. Inj Prev, 2019, 25(1): 4-12. DOI: 10.1136/injuryprev-2018-042982.
[3]	WHO. Step safely: strategies for preventing and managing falls across the life-course[R/OL]. (2021-04-27)[2024-05-27]. https://www.who.int/publications/i/item/978924002191-4.
[4]	Mirelman A, Rochester L, Maidan I, et al. Addition of a non-immersive virtual reality component to treadmill training to reduce fall risk in older adults (V-TIME): a randomised controlled trial[J]. Lancet, 2016, 388(10050): 1170-1182. DOI: 10.1016/S0140-6736(16)31325-3.
[5]	林伟权, 黄婷苑, 秦发举, 等. 2016―2017年广州市60岁及以上老年人跌倒/坠落伤害监测病例特征分析[J]. 疾病监测, 2018, 33(12): 1037-1041. DOI: 10.3784/j.issn.1003-9961.2018.12.016. Lin WQ, Huang TY, Qin FJ, et al. Characteristics of injury caused by fall in the elderly aged ≥60 years in Guangzhou, 2016-2017[J]. Dis Surveill, 2018, 33(12): 1037-1041. DOI: 10.3784/j.issn.1003-9961.2018.12.016.
[6]	董航, 刘华章, 林国桢, 等. 2012―2013年广州市60岁及以上老年人伤害死亡原因分析[J]. 实用预防医学, 2016, 23(4): 483-486. DOI: 10.3969/j.issn.1006-3110.2016.04.032. Dong H, Liu HZ, Lin GZ, et al. Causes of injury-related deaths among the elderly aged 60 years and above in Guangzhou City, 2012-2013[J]. Pract Prev Med, 2016, 23(4): 483-486. DOI: 10.3969/j.issn.1006-3110.2016.04.032.
[7]	Sibley KM, Voth J, Munce SE, et al. Chronic disease and falls in community-dwelling Canadians over 65 years old: a population-based study exploring associations with number and pattern of chronic conditions[J]. BMC Geriatr, 2014, 14: 22. DOI: 10.1186/1471-2318-14-22.
[8]	石婧, 姚慧卿, 陶永康, 等. 北京市社区老年人跌倒的发生率及相关因素的随访研究[J]. 中华老年医学杂志, 2016, 35(5): 551-555. DOI: 10.3760/cma.j.issn.0254-9026.2016.05.023. Shi J, Yao HQ, Tao YK, et al. The incidence of the fall and its risk factors in community-dwelling elderly people in Beijing: a follow-up study[J]. Chin J Geriatr, 2016, 35(5): 551-555. DOI: 10.3760/cma.j.issn.0254-9026.2016.05.023.
[9]	周德定, 徐乃婷, 高宁, 等. 应用结构方程模型分析上海市中心城区老年人跌倒的影响因素[J]. 环境与职业医学, 2019, 36(8): 703-709. DOI: 10.13213/j.cnki.jeom.2019.19223. Zhou DD, Xu NT, Gao N, et al. A structural equation model of fall-related risk factors among the elderly in urban areas of Shanghai[J]. J Environ Occup Med, 2019, 36(8): 703-709. DOI: 10.13213/j.cnki.jeom.2019.19223.
[10]	谢娜, 杨悦, 魏全. 成都市社区60岁及以上老年人跌倒现状及影响因素分析[J]. 实用预防医学, 2019, 26(1): 42-45, 58. DOI: 10.3969/j.issn.1006-3110.2019.01.011. Xie N, Yang Y, Wei Q. Current status of falls and its influencing factors among the community elderly aged 60 years and above in Chengdu City[J]. Pract Prev Med, 2019, 26(1): 42-45, 58. DOI: 10.3969/j.issn.1006-3110.2019.01.011.
[11]	周健, 刘博, 秦明照. 老年人跌倒风险评估及干预研究进展[J]. 中华老年医学杂志, 2021, 40(3): 388-392. DOI: 10.3760/cma.j.issn.0254-9026.2021.03.025. Zhou J, Liu B, Qin MZ. Fall risk assessment and relative interventions in the elderly: a latest advances[J]. Chin J Geriatr, 2021, 40(3): 388-392. DOI: 10.3760/cma.j.issn.0254-9026.2021.03.025.
[12]	Lin WQ, Lin L, Sun SY, et al. Prevalence of falls, injury from falls and associations with chronic diseases among community-dwelling older adults in Guangzhou, China: a cross-sectional study[J]. Front Public Health, 2023, 11: 1251858. DOI: 10.3389/fpubh.2023.1251858.
[13]	Salari N, Darvishi N, Ahmadipanah M, et al. Global prevalence of falls in the older adults: a comprehensive systematic review and meta-analysis[J]. J Orthop Surg Res, 2022, 17(1): 334. DOI: 10.1186/s13018-022-03222-1.
[14]	Moreland B, Kakara R, Henry A. Trends in nonfatal falls and fall-related injuries among adults aged ≥65 years - United States, 2012-2018[J]. MMWR Morb Mortal Wkly Rep, 2020, 69(27): 875-881. DOI: 10.15585/mmwr.mm6927a5.
[15]	Almada M, Brochado P, Portela D, et al. Prevalence of falls and associated factors among community-dwelling older adults: a cross-sectional study[J]. J Frailty Aging, 2021, 10(1): 10-16. DOI: 10.14283/jfa.2020.44.
[16]	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[J]. BMC Geriatr, 2024, 24(1): 201. DOI: 10.1186/s12877-024-04668-0.
[17]	Xu QM, Ou XM, Li JF. The risk of falls among the aging population: a systematic review and Meta-analysis[J]. Front Public Health, 2022, 10: 902599. DOI: 10.3389/fpubh.2022.902599.
[18]	连红强, 赵常红, 张丽蓉, 等. 老年2型糖尿病患者跌倒诱因及运动康复预防研究进展[J]. 中华老年多器官疾病杂志, 2023, 22(4): 308-311. DOI: 10.11915/j.issn.1671-5403.2023.04.064. Lian HQ, Zhao CH, Zhang LR, et al. Research progress in triggering factor of falls and exercise rehabilitation prevention in elderly patients with type 2 diabetes mellitus[J]. Chin J Mult Organ Dis Elder, 2023, 22(4): 308-311. DOI: 10.11915/j.issn.1671-5403.2023.04.064.
[19]	Samuelsson CM, Hansson PO, Persson CU. Early prediction of falls after stroke: a 12-month follow-up of 490 patients in the fall study of Gothenburg (FallsGOT)[J]. Clin Rehabil, 2019, 33(4): 773-783. DOI: 10.1177/0269215518819701.
[20]	Persson CU, Kjellberg S, Lernfelt B, et al. Risk of falling in a stroke unit after acute stroke: the fall study of Gothenburg (FallsGOT)[J]. Clin Rehabil, 2018, 32(3): 398-409. DOI: 10.1177/0269215517728325.
[21]	Ahmad Kiadaliri A, Turkiewicz A, Englund M. Educational inequalities in falls mortality among older adults: population-based multiple cause of death data from Sweden[J]. J Epidemiol Community Health, 2018, 72(1): 68-70. DOI: 10.1136/jech-2017-209616.
[22]	康宁, 于海军, 陆晓敏, 等. 中国老年人跌倒发生率的Meta分析[J]. 中国循证医学杂志, 2022, 22(10): 1142-1148. Kang N, Yu HJ, Lu XM, et al. The rate of falls in Chinese elderly: a Meta-analysis[J]. Chin J Evid-Based Med, 2022, 22(10): 1142-1148.
[23]	Malini FM, Lourenço RA, Lopes CS. Prevalence of fear of falling in older adults, and its associations with clinical, functional and psychosocial factors: the frailty in brazilian older people-rio de Janeiro study[J]. Geriatr Gerontol Int, 2016, 16(3): 336-344. DOI: 10.1111/ggi.12477.