Health Related Quality Of Life Of Chinese Population

BackgroundSince the beginning of the 21th century, China has made magnificent economic achievement. The gross domestic product of China ranks the second globally, and almost every corner of the world is full of "MADE IN CHINA". Meanwhile, the process of urbanization and industrialization in China is underway with unprecedented speed and unparaelled scale. This situation, on one hand, has changed the poverty-stricken status of China and improved the living standard of its citizens. Besides, the medical technologies and facilities have been enhanced and the life expectancy of the residents has been prolonged. Nevertheless, the balance between resources, environment and population has been destroyed to some degree. New features of health risk factors have emerged and more attention have been paid to quality of life.Besides the existing differentiation in terms of natural resources among areas, the national strategy made at the beginning of economic reform and opening up policy deteriorated the unbalanced situation of socioeconomic development. The side effects of family planning policy, which aimed to control the population size and enhance its quality, became a new challenge of the society, and the health status and quality of life of the aging population have to be put on the agenda of the government.The above situation made comprehensive and in-depth research on the health-realated quality of life of Chinese residents very necessary. However, currently lage scale investigation targeting health-related quality of life in China is still rare, and no national representative research can be retrieved in published literature.ObjectivesThe overall objective is to evaluate the health-related quality of life of Chinese population aged 15 and above and provide some evidence and illumination for improving health-related quality of life along with the socioeconomic development. Specific objectives include:a) to describe and compare the health-related quality of life of residents in different areas or with different sociodemographic characters; b) to evaluate the health inequity associated with socioeconomic status and explore the feasibility of using self-rated health as the health indicator in health inequality analysis; c) to discuss the application of self-rated health in evaluating the health-related quality of life of those who suffered from chronic diseases; d) to assess the importance of the social network to health of the elderly in urban areas and explore the key aspects of social network which has strongest influence.Material and MethodsThe study is based on the data from the 4th national household health interview survey conducted in 2008. The households for survey were slected with multiple-stage stratified random sampling procedure. Ninety-four county-level adminstraion regions were selected from 31 provinces, ethnic autonomous regions and central municipalities. The county-level adminstraion regions were classified into large, medium-sized and small cities and type 1, type 2, type 3 and type 4 rural areas according to their population and socioeconomic development, respectively. In all, 177501 individuals from 56456 households were interviewed with a structured questionnaire. For those who aged 15 and above, born before June 1993, a sub-questinnare of Euro quality of life five-dimension (EQ-5D) were also applied.The indicators used in this paper cover socio-demographic characters, geographic areas, illnesses and injuries, health-related behavior and life style of individuals, disability, social support and social participation of city dwelling individuals aged 60 and above, together with the reponses to Euro quality of life five-dimension questionnaire (EQ-5D).146231 records were included in the research at the beginning.SAS 9.1.3, SPSS 16.0 and Microsoft Excel 2007 software were used to analyze the data. EQ-5D index and Visual Analogue Scale score were compared among subgroups in various geographic and administration areas or with different sociodemographic characters. T test, variance analysis or t'test, nonparameter methods were used according to the precondition of the data. Chi-square test was used to compare the rates or proportions among different subgroups. Mutiple linear regression and multiple logistic regression were used to identify the factors affecting health-related quality of life. The whole population was divided into several subgroups according to their socioeconomic status and age standardization was performed to calculate the value of different health indicators. RR and concentration index were calculated based on different health indicators. Multiple linear regression was performed when exploring the relatoship between quality of life and chronic diseases. Optimal scaling regression was used to assess the association between the quality of life and social networks of city dwelling old adults.ResultsThe proportion of respondents who reported any problem in mobility, self-care, usual activities, pain/discomfort, anxiety/depression and any dimension was 5.47%, 3.75%,5.33%,9.02%,6.50% and 13.07%, respectively. The average value of EQ-5D index and VAS score was 0.954 and 80.35, respectively.The proportion of respondents who reported any problem in any dimension in eastern, middle and western areas was 11.52%,11.99%and 15.33%, respectively. The proportion of respondents who reported any problem in mobility, self-care, usual activities, pain/discomfort, and anxiety/depression was especilly high in type 3 and type 4 rural areas, up to 6.53%,4.56%,6.51%,11.39%and 9.79%.The average value of VAS score of the respondents was 81.90,80.23 and 79.00 in eastern, middle and western areas, respectively. For respondents in large, medium-sized and small cities, the average value was 78.15,80.81 and 80.37, respectively. For respondents in type 1, type 2, type 3 and type 4 rural areas, the average value was 81.53,81.13,80.01 and 79.34. The average value of VAS score of the respondents in eastern small cities was highest, up to 85.09, while western large cities got the lowest, only 76.97. As the socioeconomic development improved, the distribution of VAS score in different areas was like a reversed "V" shape.The difference among proportions of respondents who reported any problem in specific dimension was very siginificant among subgroups with different education background. Lower education level was associated with higher proportion of ill health. As for occupation, the situation was totally different. Respondents fell in subgroups with relatively lower and higher occupation levels reported higher proportion of any problem and the distribution was like a "V" shape.The average value of VAS score of respondents whose education level were illiterate, primary school, junior middle school, senior middle school or its equivalents, and college and above was 71.50,77.92,83.59,83.97 and 84.56. When it came to subgroups divided by occupation, the average value of VAS score of small business holders was highest, and those who were unemployed got the lowest. Besides the physiological aspects, sociodemographic characters, geographic and administration areas, health related behavior and life style factors were associated with VAS score independently. On the assumption that all of the other conditions were the same, compared with respondents aged 15 to 24, the value of VAS score of respondents aged 25 to 34,35 to 44,45 to 54,55 to 64 and 65 and above suffered a decrease of 2.14,4.36,6.88,8.84 and 12.39 on average, repectively; compared with those who were illiterate, respondents whose education level was primary school, junior middle school, senior middle school or its equivalents, and college and above got higher value of VAS score on average, the gap was 1.92,3.16,3.14 and 3.12, respectively; compared with the subgroup of lowest level of annual household income per capita, the subgroups of lower, modest, higher and highest levels got an increase of 1.54,2.09,2.36 and 3.64, respectively; compared with respondents in eastern areas, the value of VAS score of those in middle and western areas suffered a decrease of 1.95 and 2.79, respectively; compared with those in large cities, respondents in medium-sized cities, small cities, type 1, type 2, type 3 and type 4 rural areas got an increase of 1.95,3.67,2.57,1.92,2.25 and 2.40 on average, respectively.No matter which socioeconomic status indicator was used, the absolute value of the concentration index calculated based on proportion of bad self-rated health was greater than that based on physical discomfort in the past two weeks or chronic diseases within half a year.On the assumption that age and gender were fixed, compared with subgroups without any chronic diseases, respondents who suffered from one, two, three and more categories of chronic diseases at the same time reported lower value of VAS score, the gap was 9.39,13.58 and 17.52, respectively; respondents who suffered from gastroenteritis, hypertension, intervertebral disc diseases, diabetes, rheumatoid arthritis and cerebrovascular diseases lost 9.25,8.30,11.46,10.82,11.56 and 16.74, respectively.Ranked by the relative importance, the influence factors of the VAS score of city dwelling old adults were chronic diseases, disability, physical discomfort in the past two weeks, physical exercises, age, meeting relatives and friends, affiliate with neighbours, education level, social meetings and modest work, etc. Social participation was significantly associated with the value of VAS score.Conclusions and RecommendationsHealth-related quality of life had not been improved paralelly with regional socioeconomic development in China. Socioeconomic development is essential but not the only precondition for the improvement of health-related quality of life, thus the government should attach importance to the development of poverty-striken areas. Nevertheless, citizens'health-related quality of life cannot be ignored when we pursue economic achievement. The scientific outlook on development ought to be accepted and implemented as a guideline of local governments when they make plans or strategies for socioeconomic development, ecological enviroment protection and public social services must be paid to the same attention as the economic growth. The central government should support and help the local governments to coordinate the socioeconomic development across the country. County-level economy is the key to ease the heavy burden of population, resources and environment in large cities. The government should spare no effort to enchance the economic development and infrastructure instruction in minority dwelling areas and outlying areas, to improve public services such as education and health, to promote the equalization and integration of public services in urban and rural areas, and by doing so provide necessary conditions for the improvement of health-related quality of life in underdevelopment areas.Self-rated health can be more appropriate for evaluating the health inequities associated with socioeconomic status than physical discomfort in the past two weeks or chronic diseases within half a year, only if the measure instrument and statistical analysis methods were proper. VAS score can be viewed as "net health" after the damage to individuals'physiological and mental health by chronic diseases was taken into consideration. Thus, the application of self-rated health in health inequities evaluation and health-related qualiy of life research of patients suffered from various chronic diseases should be advocated.Social network is significantly connected with the health-related quality of life of the elderly in urban areas. Compared with the support from relatives and descendants, social involvement of the city-dwelling old adults seems more important to their health. Community-based facilities and services for old adults should be improved in order to make a convienient platform for them to communicate with each other and provide wonderful cultural life, and finally make the idea of "healthy aging" into a reality.