Abstract:
Background Falls occur as a result of a complex interaction of risk factors. The World Health Organization categorizes the risk factors into four dimensions:biological, behavioral, environmental, and socioeconomic factors.
Objectve This study is designed to analyze the factors affectng the falls of the elderly in urban areas and provide evidence for targeted interventon programs.
Methods A total of 3 480 elderly partcipants from 7 urban areas of Shanghai were surveyed by questonnaires, tested for gait and balance functon, and evaluated for home environment. A structural equaton model was developed to examine the relatonships between independent variables (biological, socioeconomic, behavioral, and home environmental factors) and dependent variable (falls). The latent variables of falls were indicated by manifest variables including number of falls, number of injuries, days of hospitalizaton, and days of rest; the latent variables of biological factors were indicated by manifest variables including osteoporosis risk score, timed up and go test (TUG) time, physical risk assessment score, age, and gender; the latent variables of socioeconomic factors were indicated by manifest variables including whether living alone and educaton.
Results Of the 3 385 subjects who completed the questonnaire survey, 13.06% fell in the past year. The rates of falls were signifcantly higher in women (χ2=25.83, P < 0.05), the 70- years and 80- years age groups (χ2=52.27, P < 0.05), those with elementary school or less educaton (χ2=10.05, P < 0.05), and those with no cohabitant (χ2=3.98, P < 0.05). The elderly partcipants who fell had higher physical risk score (Z=12.51, P < 0.05), TUG time (Z=9.29, P < 0.05), osteoporosis risk score (Z=8.46, P < 0.05), behavioral factor score (Z=4.91, P < 0.05), and home environmental factors score (Z=4.66, P < 0.05) than those who did not fall. The structural equaton model showed that the standardized regression coefcients (β) of the biological factors, behavioral factors, and home environmental factors were 0.564 (P < 0.01), 0.070 (P < 0.01), and 0.083 (P < 0.01), respectvely, and the regression coefcient (β) of socioeconomic factors was not statstcally signifcant. Among the biological factors, the regression coefcients (β) for physical risk and TUG time were 0.658 (P < 0.01) and 0.477 (P < 0.01) respectvely, higher than the coefcients of other manifest variables. Women were more likely to fall than men. The regression coefcient (β) of home environmental factors of falls in female elderly people was 0.111 (P < 0.01), and the coefcient (β) of male elderly people was not signifcant.
Conclusion Biological, behavioral, and home environmental factors may affect the falls of the elderly. Among them, biological factors are dominant and are most closely associated with physical risk score and TUG time. The risk of falls is higher for women than for men. Home environment as a risk factor is unique to women.
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