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Epidemiological Characteristics Of Falls And Its Prevention Strategies Among Elderly People Of Urban Community Dwellers In Beijing

Posted on:2011-12-10Degree:DoctorType:Dissertation
Country:ChinaCandidate:P L YuFull Text:PDF
GTID:1114330335989007Subject:Epidemiology and Health Statistics
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Background:With increasing of age, a series of changes in the structure and physical functions of human bodies result in the prevalence of falls in the elderly. Falls has been the first death cause of injury, which influences physical and psychological health and quality of life of aged persons, brings much burden for the elderly themselves, their families and.the society as a whole, and becomes an important public health issue. Nowadays, not so much systematic and comprehensive studies on falls in the elderly can be retrieved on scientific literatures, and not enough attention has been paid to the consequences caused by falls. Therefore, more studies on it should be conducted further, particularly in the urban community where more aged people live, and prevention of falls should be strengthened urgently.Objective:1. To understand the epidemiological characteristics of falls in the community-dwelling elderly persons:the distributions, consequence of falls are investigated by questionnaire.2. To investigate the major risk factors and protective factors for falls in the community-dwelling elderly persons:data of the questionnaire are analyzed, the risk factors and protective factors of falls, frequency of falls, subsequent falls, frequency of subsequent falls are revealed.3. To evaluate the preventing effectiveness of health education on falls in the community-dwelling elderly persons:to improve the living quality, increase the independent ability, and provide a low-cost and high-efficient intervention model of the falls suitalble for the community-dwelling elderly.Methods:A cross-sectional study was conducted in Long-tan community of Chongwen District in Beijing in 2005. A total of 1512 persons aged 60 years and over from 4 residents committees were selected with stratified cluster sampling. All information about demography, physical health, activities of daily life, mental health, family and social relation, economic status, utilization of health care service, home environment, falls information during the past one year and the consequences of falls were collected with a standardized structured questionnaire by face-to-face interview. Free popular science books on preventing falls were distributed to the interviewees, and health education on falls prevention was carried out two times in one year.A follow-up survey was led in 2009, and a total of 472 aged persons were selected including 5/8 of the population with falls history in 2005 and 1/4 of the population without falls history in 2005. All the information about falls was collected with the same questionnaire as in 2005.All the data were analyzed by SPSS 13.0 and SAS 9.1.3 software, and X2 test, binary logistic regression analysis, ordinal logistic regression analysis and multilevel model analysis were used to explore related factors for falls in the elderly.Results:1. Distribution of the fallsIn 2005, falls incidence was 18.0%(272 aged persons) during the past one year among 1512 interviewees with the average frequency of falls (1.39±0.97) times. The incidence rate was higher among women than that among men (20.1% vs.14.9%, X2=7.45, P<0.01). Recurrent falls incidence was 4.0% among the elderly. Falls mostly occurred in summer and daytime, and the place was mostly the dwelling place.In 2009, falls incidence was 17.8%(84 aged persons) during the past one year among 472 interviewees with the average frequency of falls (1.44±0.67) times. The incidence rate of subsequent falls was 28.8%(49 aged persons) among 170 aged persons with falls history in 2005 with the average frequency of falls (1.27±0.64) times. And among 302 aged persons without falls history in 2005, the incidence rate of falls and average frequency of falls were 11.6% and (1.46±0.75) times, respectively.2. Consequences of fallsIn 2005, among 1512 interviewees,8.7%(131 aged persons) of older people suffered from injuries of falls. Among the elderly with falls, 35.7%(97 aged persons) of them decreased daily activities,58.8%(160 aged persons) of them feared subsequent falls and 30.1%(82 aged persons) of them had negative emotion such as depression, impatience, obduracy and self-confidence decreasing due to falls.3. Risk factors for fallsThe risk factors of falls included intrinsic factors and extrinsic factors. Forty-one variables were statistically significant in univariate analysis. The associations between variables of demography, health status, balance function, diseases, drugs, behavior, psychology, social economy, environment and falls were analyzed by binary logistic regression model, respectively. Results showed that female, older age, gait, balance function, living alone, suffering from chronic diseases, taking two or more than two kinds of medications, fear of falls and unsafe home environment were all associated with falls.4. Risk factors for frequency of fallsOrdinal logistic regression model was performed to analyze the relationship between variables of demography, home safety, health status, social economy, environment and frequency of falls, and female, advanced age, living alone and hypopsia were the risk factors for frequency of falls.5. Risk factors for subsequent fallsIn considering that subsequent falls may be resulted from varied factors, univariate analysis and binary logistic regression model were performed to evaluate the relationship between variables of demography, home safety, social economy, health services, health status, balance function and subsequent falls. Results showed that family monthly income, living alone, bad health condition, fear of subsequent fall were the risk factors for subsequent fall; the suitable width of the staircase footboard, believing fall was preventable, enough light in passageway or stairs, dunnage handled easily were the protection factors for subsequent fall.6. Risk factors for frequency of subsequent fallsThe relationship between variables of demography, home safety, health status, social economy, environment and frequency of subsequent falls were analyzed by ordinal logistic regression model. Family monthly income, bad health status, living alone, fear about falls were all associated with frequency of subsequent falls, and the suitable height of the staircase footboard was the protection factors for frequency of subsequent falls.7. Results from multilevel model analysisFor self-reasons, the main influence factor was the location of falls (in the dwelling place), the other self-reason was the location of falls (out of the dwelling place). But for external reasons, the main influence factors were season of falls (summer) and time of falls (midnight).8. The effect of interventionThe standardized incidence rate of falls was decreased in follow-up elderly population in 2009(18.4% to 13.1%), and their knowledge, attitudes and practice about falls were improved after intervention.Conclusions:1. The incidence rate of falls among elderly urban community-dweller in Beijing was high, which had caused serious consequences and become a heavy burden to both family and society. It also had become a major issue in public health seriously influencing older people's health and quality of life.2. In the elderly, falls resulted from both intrinsic and extrinsic factors including biological factors, behavioral and psychological factors, social factors and environmental factors.3. Incidence rate of falls could be decreased by developing health education of falls prevention among the elderly in communities.4. The elderly people themselves, their families, community health-care providers and the whole society should all be involved in the prevention for falls in the elderly. Intervention strategy should be targeted at varied factors related to it and focused on primary prevention. The core provider of intervention should be general practitioners and community nurses.
Keywords/Search Tags:The elderly, Falls, Risk factors, Prevention, Intervention, Multilevel model analysis
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