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      Population health status in China: EQ-5D results, by age, sex and socio-economic status, from the National Health Services Survey 2008


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          To measure and analyse national EQ-5D data and to provide norms for the Chinese general population by age, sex, educational level, income and employment status.


          The EQ-5D instrument was included in the National Health Services Survey 2008 ( n = 120,703) to measure health-related quality of life (HRQoL). All descriptive analyses by socio-economic status (educational level, income and employment status) and by clinical characteristics (discomfort during the past 2 weeks, diagnosed with chronic diseases during the past 6 months and hospitalised during the past 12 months) were stratified by sex and age group.


          Health status declines with advancing age, and women reported worse health status than men, which is in line with EQ-5D population health studies in other countries and previous population health studies in China. The EQ-5D instrument distinguished well for the known groups: positive association between socio-economic status and HRQoL was observed among the Chinese population. Persons with clinical characteristics had worse HRQoL than those without.


          This study provides Chinese population HRQoL data measured by the EQ-5D instrument, based on a national representative sample. The main findings for different subgroups are consistent with results from EQ-5D population studies in other countries, and discriminative validity was supported.

          Electronic supplementary material

          The online version of this article (doi:10.1007/s11136-010-9762-x) contains supplementary material, which is available to authorized users.

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          Most cited references36

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          Estimating an EQ-5D population value set: the case of Japan.

          Quality adjustment weights for quality-adjusted life years (QALYs) are available with the EQ-5D Instrument, which are based on a survey that quantified the preferences of the British public. However, the extent to which this British value set is applicable to other, especially non-European, countries is yet unclear. The objectives of this study are (a) to compare the valuations obtained in Japan and Britain, and (b) to explore a local Japanese value set. A diminished study design is employed, where 17 hypothetical EQ-5D health states are evaluated as opposed to 42 in the British study. The official Japanese version of the instrument and the Time Trade-Off method are used to interview 543 members of the public. The results are: firstly, the evaluations obtained in Japan and those from Britain differ by 0.24 on average on a [-1, +1] scale, and mean absolute error (MAE) in predicting the Japanese preferences with the British value set is 0.23. Secondly, comparable regressions suggest that the two peoples have systematically different preference structures (p<0.001 for 8 of 12 coefficients; F-test). Thirdly, using alternative models, the predictions are improved so that the local Japanese value set achieves MAE in the order of 0.01. Copyright 2002 John Wiley & Sons, Ltd.
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            Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from Europe.

            In this paper we review the available summary measures for the magnitude of socio-economic inequalities in health. Measures which have been used differ in a number of important respects, including (1) the measurement of "relative" or "absolute" differences; (2) the measurement of an "effect" of lower socio-economic status, or of the "total impact" of socio-economic inequalities in health upon the health status of the population; (3) simple versus sophisticated measurement techniques. Based on this analysis of summary measures which have previously been applied, eight different classes of summary measures can be distinguished. Because measures of "total impact" can be further subdivided on the basis of their underlying assumptions, we finally arrive at 12 types of summary measure. Each of these has its merits, and choice of a particular type of summary measure will depend partly on technical considerations, partly on one's perspective on socio-economic inequalities in health. In practice, it will often be useful to compare the results of several summary measures. These principles are illustrated with two examples: one on trends in the magnitude of inequalities in mortality by occupational class in Finland, and one on trends in the magnitude of inequalities in self-reported morbidity by level of education in the Netherlands.
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              Swedish population health-related quality of life results using the EQ-5D.

              Health-related quality of life (HRQoL) measured on population level may be useful to guide policies for health. This study aims to describe the HRQoL; in EQ-5D dimensions, mean rating scale (RS) scores and mean EQ-5D index values, in the general population, by certain disease and socio-economic groups, in Stockholm County 1998. The EQ-5D self-classifier and a RS were included in the 1998 cross-sectional postal Stockholm County public health survey to a representative sample (n = 4950, 20-88 years), 63% response rate. Mean RS score ranged from 0.90 (20-29 years) to 0.69 (80-88 years), mean EQ-5D index value ranged from 0.89 (20-29 years) to 0.74 (80-88 years). For different diseases mean RS scores ranged from 0.80 (asthma) to 0.69 (angina pectoris), mean EQ-5D index values ranged from 0.79 (asthma) to 0.66 (low back pain). The mean health state scores (RS and EQ-5D index) were 0.06 lower in the unskilled manual group than in the higher non-manual group after controlling for age and sex (p < 0.0001). This difference was 0.03 after controlling also for different diseases (p < 0.0001). In conclusion, our results show that the HRQoL varies greatly between socio-economic and disease groups. Furthermore, after controlling for age, sex and disease, HRQoL is lower in manual than in non-manual groups.

                Author and article information

                +46-8-52484779 , sun.sun@ki.se
                +86-25-86862950 , jychen@njmu.edu.cn
                Qual Life Res
                Quality of Life Research
                Springer Netherlands (Dordrecht )
                2 November 2010
                2 November 2010
                April 2011
                : 20
                : 3
                : 309-320
                [1 ]Department of Learning, Informatics, Management and Ethics, Medical Management Centre, Karolinska Institutet, Nobels väg 15a, 171 77 Stockholm, Sweden
                [2 ]Department of Public Health Sciences, Division of Social Medicine, Karolinska Institutet, Nobels väg 15a, 171 77 Stockholm, Sweden
                [3 ]School of Health Policy and Management, Nanjing Medical University, Hanzhong Rd 140, 210 029 Nanjing, P. R. China
                [4 ]Department of Economics, Stockholm School of Economics, Box 6501, 113 83 Stockholm, Sweden
                [5 ]Centre for Health Economics, University of York, York, YO10 5DD UK
                [6 ]Centre for Health Statistics and Information, Ministry of Health, Xizhimenwainanlu 1, 100 044 Beijing, P. R. China
                © The Author(s) 2010
                : 27 September 2010
                Custom metadata
                © Springer Science+Business Media B.V. 2011

                Public health
                socio-economic status,general population,health surveys,china,eq-5d,inequalities
                Public health
                socio-economic status, general population, health surveys, china, eq-5d, inequalities


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