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As of 2021, China has entered a phase of moderate aging, with a significant projected increase in the elderly population over the next decade due to a second baby boom starting in 1962. This demographic shift poses significant challenges for national finances, social healthcare services, and home assistance. Falls are the primary cause of fatal injuries and illnesses among Chinese individuals over 65 years old (1). Research indicates that about 1/3 of 65-year-olds and half of 80-year-olds have experienced a fall, with a high likelihood of recurrence for those with a history of falls. Prompt prevention and diagnosis of falls using clear criteria can yield visible results quickly (2). Preventing and managing falls among the elderly is a key priority for facilitating healthy and active aging in China. Domestic researchers have successfully implemented the “5E” strategy — Education, Environmental modifications, Engineering improvements, Enforcement measures, and Evaluation — to mitigate fall risks among elderly inpatients (3-4). Nonetheless, there is a scarcity of studies evaluating the efficacy of group-based fall prevention interventions for rural older adults.
This study aims the effectiveness of a group-based comprehensive intervention strategy to prevent falls in older adults through a prospective cohort study conducted from October 2022 to September 2023. Using random cluster sampling, six project townships were chosen from Yunnan Province and Chongqing Municipality, with one project village selected from each township. The survey involved 1,536 rural elderly individuals aged 60 and above across 6 project villages. Baseline data from 1,276 rural elderly individuals aged 60 and over from the same villages collected from November to December 2018 was used for self-control. The research was part of the “Community Participation to Promote Rural Elderly Health – Phase II” project by the National Health Commission (NHC). Inclusion criteria included individuals aged 60 and above residing in the project area for at least six months, while exclusion criteria involved severe mental illness, paralysis, and epilepsy.
The research team implemented a detailed, household-level investigation by deploying a specifically designed questionnaire. This questionnaire encompassed a wide array of topics, capturing essential resident demographics, lifestyle choices, daily activity capabilities, overall physical health, and impressions of the intervention project. The multifaceted “5E” strategy for injury prevention was employed, focusing on the following dimensions: 1) Provision of targeted health education, which addressed themes such as fall prevention and awareness, handling falls, the significance of physical activity, and safety measures associated with exercise. 2) Modification of the living environment in an age-sensitive manner, entailing upgrades such as smoothing out uneven surfaces, enhancing lighting in communal areas, bathroom repairs, handrail installations, and setting up fitness equipment. 3) Dispensation of age-friendly assistive devices that included items like reading glasses for presbyopia, portable commodes, walking sticks, and crutches aimed at reducing the fall risk for the elderly. 4) Oversight of the entire intervention process, from the development and procurement of necessary resources to the actual execution and subsequent assessment of the interventions. 5) Conducting risk evaluations for potential recurrent falls. Evaluation metrics involved measuring the frequency of falls, defined as the percentage of participants who reported experiencing a fall in the preceding year, as well as quantifying re-fall risk. For assessing re-fall risk, we employed the endorsed scoring systems of the Fall Risk For Older People-Community Setting (FROP-Com) (5) and the Falls Risk Assessment Tool (FRAT) (6), resulting in a comprehensive 37-point score with 13 primary factors, comprising: fall history, medications influencing fall risk, medical conditions affecting balance and flexibility, paresthesia occurrences, sleep quality, health literacy, urinary incontinence, nutritional health, environmental safety assessment, level of physical activity, proficiency in everyday activities, engagement in physical exercise, and emotional well-being.
Data analysis was performed using SPSS statistical software (version 27.0, SPSS Inc., Chicago, IL, USA). This study was approved by the Ethics Review Committee of the National Center for Women and Children’s Health, China CDC, under the protocol (Ethics Review Number: FY2018-07). Before the intervention, participants were well-informed about the study procedures and provided their informed consent.
The initial data indicated that 159 individuals suffered falls; however, in the subsequent survey, only 33 reported falls. The prevalence of falls decreased from 12.46% to 2.15% following the intervention (Table 1). The mean scores for the reassessment of fall risk decreased from 9.64±2.99 to 7.79±2.44. Analysis using a regression model revealed that regular physical activity [odds ratio (OR): 0.34, 95% confidence interval (CI): 0.16, 0.72] and a positive attitude (OR: 0.22, 95% CI: 0.07, 0.64) were protective factors, while sleep disturbances (OR: 2.86, 95% CI: 1.21, 6.77) and hearing impairment (Wald χ2=8.46, P=0.037) were identified as risk factors for falls. Visual impairments such as blurred vision can be corrected with the use of presbyopia glasses (Table 2). The ratio of falls attributed to intrinsic factors versus environmental factors was approximately 1∶1. Slippery surfaces or obstacles in the surroundings (33.33%) were identified as the primary causes of falls (Table 3).
Item Post-intervention χ2 P Pre-intervention χ2 P Number Number of falls (%) Number Number of falls (%) Sex 2.899 0.089 0.489 0.484 Male 737 11 (1.49) 635 75 (11.81) Female 799 22 (2.75) 641 84 (13.10) Ethnicity 5.729 0.126 4.903 0.179 Han 426 15 (3.52) 316 46 (14.56) Tujia 423 7 (1.65) 453 61 (13.47) Lahu 469 6 (1.28) 317 29 (9.15) Other 218 5 (2.29) 190 23 (12.11) Age (years) 2.981 0.225 6.353 0.042 60– 773 12 (1.55) 698 73 (10.46) 70– 551 14 (2.54) 417 65 (15.59) ≥80 212 7 (3.30) 161 21 (13.04) Educational level 10.750 0.005 4.871 0.088 Illiterate 969 28 (2.89) 827 112 (13.54) Primary school 506 3 (0.59) 327 39 (11.93) Junior high school and above 61 2 (3.28) 122 8 (6.56) Occupation 7.821 0.020 0.485 0.785 Housework 416 14 (3.37) 513 67 (13.06) Farming 1,075 16 (1.49) 721 86 (11.93) Other 45 3 (6.67) 42 6 (14.29) Alcohol consumption 0.329 0.566 1.456 0.228 Yes 441 8 (1.81) 456 50 (10.96) No 1095 25 (2.28) 820 109 (13.29) Having sleeping problems 7.498 0.006 3.757 0.053 Yes 169 9 (5.33) 389 59(15.17) No 1,367 24 (1.76) 887 100(11.27) Physical exercise 10.054 0.002 4.661 0.031 Yes 964 12 (1.24) 541 80 (14.79) No 572 21 (3.67) 735 79 (10.75) Having chronic disease 0.001 0.971 1.322 0.250 Yes 554 12 (2.17) 368 52 (14.13) No 982 21 (2.14) 908 107 (11.78) Vision 7.845 0.049 14.512 0.002 Normal 504 8 (1.59) 338 29 (8.58) Slightly blurred 835 17 (2.04) 609 79 (12.97) Often unable to see clearly 176 5 (2.84) 192 22 (11.46) Blurred 21 3 (14.29) 137 29 (21.17) Hearing 7.894 0.048 11.647 0.009 Normal 672 8 (1.19) 694 68 (9.80) Sometimes cannot hear 689 20 (2.90) 367 62 (16.89) Often cannot hear 139 5 (3.60) 131 19 (14.50) Severe hearing loss 36 0 84 10 (11.90) Mentality 6.793 0.009 8.881 0.003 Positive 1,025 4 (0.39) 971 106 (10.92) Loneliness, anxiety or depression 511 29 (5.68) 305 53 (17.38) Table 1. Univariate analysis of the impact factors of falls among rural elderly pre- and post-intervention in six pilot villages, Yunnan and Chongqing, China, 2018–2023.
Impact factors (Reference groups) β S.E. Wald χ2 P OR 95% CI Pre-intervention With exercise (No) −0.392 0.174 5.100 0.024 0.68 0.48, 0.95 Vision (Blurred vision) 8.417 0.038 Normal vision −0.259 0.241 1.159 0.282 0.77 0.48, 1.24 Slightly blurred −0.829 0.313 7.028 0.008 0.44 0.24, 0.81 Often unable to see clearly −0.110 0.324 0.116 0.733 0.90 0.48, 1.69 Mentality (Loneliness, anxiety or depression) −0.466 0.188 6.173 0.013 0.63 0.43, 0.91 Post-intervention Having sleeping problems (No) 1.050 0.440 5.686 0.017 2.86 1.21, 6.77 With exercise (No) −1.089 0.387 7.897 0.005 0.34 0.16, 0.72 Hearing (Normal) 8.464 0.037 Sometimes cannot hear 1.161 0.750 2.393 0.122 0.31 0.07, 1.36 Often cannot hear 0.527 0.622 0.718 0.397 1.69 0.50, 5.73 Severe hearing loss 18.903 6041.682 − 0.998 − − Mentality (Loneliness, anxiety or depression) −1.534 0.557 7.571 0.006 0.22 0.07, 0.64 Note: “−”:The number of falls due to severe hearing loss is zero.
Abbreviation: S.E.=standard error; OR=odds ratio; CI=confidence interval.Table 2. Multivariate logistic regression analysis of the impact factors of falls among rural elderly pre- and post-intervention in six pilot villages in Yunnan and Chongqing, China, 2018–2023.
Cause of fall Post-intervention Pre-intervention N % N % Elderly themselves Leg weakness 14 16.67 30 8.33 Poor body balance ability 11 13.10 64 17.78 Distraction 11 13.10 30 8.33 Vision problems 6 7.14 25 6.94 Unwell episodes 3 3.57 45 12.50 Surroundings Slippery grounds and obstacles 28 33.33 118 32.78 Insufficient or blinding light 8 9.52 26 7.22 Steps with large height difference 2 2.38 13 3.61 Furniture too high or too low 1 1.19 7 1.94 No handrails in bathroom 0 0 2 0.56 Table 3. The comparison of the leading cause of falls among rural elderly, pre- and post-intervention in six pilot villages, Yunnan and Chongqing, China, 2018–2023.
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