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Study On Sub-health Status And Its Relationship With Sleep Quality Of Urban And Rural Residents In Hubei Province

Posted on:2010-04-24Degree:MasterType:Thesis
Country:ChinaCandidate:L LiuFull Text:PDF
GTID:2194330338987963Subject:Epidemiology and Health Statistics
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Objective:To evaluate the Sub-health Assessment Scale and use the scale to investigate the sub-health status of urban and rural residents in Hubei Province in large sample.To determine the epidemiological condition of the sub-health status and the sleep quality in urban and rural areas of Hubei Province, and to explore the relationship between them. These provide objective and scientific references for establishing preventive strategies and therapeutic regimen.Methods:The purposive-cluster sampling methods were carried out to select 1683 urban residents and 1673 rural residents into this survey. Personal Health Status Questionnaire made by Peking Union Medical College was used to investigate the people's healthy conditions. The reliability and validity of the Sub-health Assessment Scale were tested by Spearman correlation analysis, principal component factor analysis, and the epidemiological condition of the sub-health status and the sleep quality in urban and rural areas of Hubei Province were analyzed by analysis of variance (ANOVA) and chi-square test. Canonical correlation analysis and structural equation model were conducted to analyze the relationship between the sub-health status and the sleep quality. Results:(1) Three dimensionalities of the Sub-health Assessment Scale, including physical sub-health, mental and social well being, and personal satisfaction indicated a good fit by reliability and validity test. The eigenvalue of each factor was larger than 1, and cumulative variance contribution rate was 64.21%. The chronbach'sαcoefficient of the scale was 0.905 and spearman-brown split-half reliability of the scale was 0.862.(2) Different demographic characteristics of the sub-health status have statistically significant (P <0.01 of all). Females were more serious than males. People aged more than 30 were more likely to experience sub-health than those of from 15 to 30 years old. The condition of the sub-health in the people with a low level of education (primary school or illiteracy) was the worst compared to other people with a higher education level. The prevalence of sub-health among divorced, separated and widowed people was the highest.The farmers and workers'condition was the worst and the student was the best among the occupation.(3) All with different demographic characteristics were different in the sleep quality (P <0.01 of all), but the sex. The older of the people, the worse of the sleep quality was. The sleep quality in the people with a low level of education (primary school or illiteracy) was the worst compared to other people with a higher education level. The sleep quality among divorced, separated and widowed people was the worst. In different occupations, The farmers and workers'condition was the worst and the student was the best(4) According to the Canonical correlation analysis, we found the canonical correlation coefficient between the sub-health and the sleep quality was 0.44, mainly represented by the physical sub-health, mental and social well-being and subjective sleep quality. 11% of the variance of the sub-health related to the sleep quality and 6% of the variance of the sleep quality related to the sub-health. According to the structural equation model,we could get to the totall effect of the sleep quality to the sub-health is 44%.Conclusion:The new established scale of sub-health has good reliability and validity, and could be used to assess the epidemiological condition of the sub-health objectively. The condition of the sub-health and the sleep problems exist to a great extent in people with different demographic characteristics. Relevant departments should pay great attention to these issues.
Keywords/Search Tags:Sub-health, Urban and rural residents, The Sub-health Assessment Scale, Canonical correlation analysis, Structural equation model
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