Health statistics quarterly最新文献

{"title":"Inequalities in healthy life expectancy by social class and area type: England, 2001-03.","authors":"Chris White,&nbsp;Grace Edgar","doi":"10.1057/hsq.2010.3","DOIUrl":"https://doi.org/10.1057/hsq.2010.3","url":null,"abstract":"<p><strong>Background: </strong>Healthy life expectancy (HLE) is an important indicator which combines longevity with health status. This article examines inequalities in HLE by socio-economic position in England, and between Local Authorities (LAs) in the deprived 'Spearhead group' and other LAs.</p><p><strong>Methods: </strong>Census and vital event data available from the ONS Longitudinal Study were used to calculate estimates of HLE based on general health status for each Registrar General's Social Class (RGSC) in 2001-03, in England as a whole and within the 'Spearhead group' and non-Spearhead LAs.</p><p><strong>Results: </strong>A predominantly linear relationship was present with HLE increasing with rising social class. The differences observed in HLE at birth and at age 65 between people assigned to the professional and unskilled manual social classes were statistically significant and substantial, demonstrating a clear social inequality in the amount of life, the quality of those years lived, the absolute number of healthy life years, and thus the relative proportion of life spent in 'Good' or 'Fairly Good' health.HLEs at birth were statistically significantly higher for women than for men in the non-Spearhead LAs for all social classes; however, in the 'Spearhead group' of areas higher HLEs in women were only present among the skilled non-manual, skilled manual and partly skilled social classes. This suggests that an interaction effect between sex and area in the level of HLE may be operating.The magnitude of inequality in HLE between professionals and the unskilled manual class in the proportion of life spent in 'Good' or 'Fairly Good' health also varied between the 'Spearhead group' and non-Spearhead LAs: among men, a difference of 6.6 per cent was present in non-Spearhead LAs, compared with 10.6 per cent in the 'Spearhead group'; among women, the equivalent differences were 5.3 per cent and 7.6 per cent.</p><p><strong>Conclusions: </strong>The within-class HLEs for men and women were lower in the 'Spearhead group' compared with the non-Spearhead LAs, and statistically significantly lower among the intervening social classes for men; among women they are significant for all social classes other than the professional class. The scale of inequalities shown is important for policy responses and understanding of differences in service needs.</p>","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":" 45","pages":"28-56"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28913929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Update to the methodology used to calculate health expectancies for the UK and constituent countries.","authors":"Michael P Smith,&nbsp;Olugbenga Olatunde,&nbsp;Chris White","doi":"10.1057/hsq.2010.5","DOIUrl":"https://doi.org/10.1057/hsq.2010.5","url":null,"abstract":"<p><strong>Background: </strong>Changes to the design of the General Household Survey (GHS) risk a discontinuity in the ONS Health Expectancy (HE) series. This report compares methodological approaches to ensure consistency of this important National Statistic and reports improvements to the methodology surrounding standard error (SE) estimation.</p><p><strong>Methods: </strong>A comparison of the use of cross-sectional and longitudinal GHS data in estimating health state prevalence and HE in the UK, GB and constituent countries for the period 2005-07. Incorporation of the GHS sampling design effect into the calculation of standard errors surrounding estimates of HE backdated to 2000-02.</p><p><strong>Results: </strong>The prevalence of favourable health states was significantly higher in the longitudinal compared to the cross-sectional sample of the GHS. Compared to established trends, the inclusion of longitudinal data in estimates of healthy life expectancy (HLE) led to implausible increases in this metric. However, the prevalence of limiting long-standing illness and estimates of disability-free life expectancy (DFLE) using longitudinal data were broadly comparable and in line with recent trends.Inclusion of the design effect had only a minor impact on the estimation of current and historic HE standard errors. On three occasions, increases in HLE over time were no longer significant using this enhanced method of SE estimation and in a single instance differences in DFLE between countries were no longer significant.</p><p><strong>Conclusions: </strong>Attrition in the GHS longitudinal dataset introduces significant bias into estimates of health state prevalence and a discontinuity in the established trend of HLE. Utilising the cross-sectional GHS sample alone in 2005-07 represents the most reliable approach to maintain the consistency of this important series. Incorporation of the design effect enhances the precision of estimates of HE.</p>","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":" 45","pages":"81-99"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28913931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in social inequalities in male mortality, 2001-08. Intercensal estimates for England and Wales.","authors":"Ann Langford,&nbsp;Brian Johnson","doi":"10.1057/hsq.2010.14","DOIUrl":"https://doi.org/10.1057/hsq.2010.14","url":null,"abstract":"<p><strong>Background: </strong>This article presents estimates of mortality rates for men of working age by the National Statistics Socio-economic Classification (NS-SEC). Previously it has been possible to produce such mortality rates only at the time of a census, when populations are enumerated by occupation and NS-SEC. This is the first time that annual intercensal estimates have been produced, enabling the measurement of health inequalities by NS-SEC for the period 2001-08.</p><p><strong>Methods: </strong>The Labour Force Survey (LFS) was used to provide population denominators by age and NS-SEC for men aged 25-64 for each year between 2001 and 2008. Numbers of deaths for the corresponding period were obtained from death registrations, and age-standardised mortality rates were derived. A number of measures of the inequality in mortality rates across socio-economic classes were compared.</p><p><strong>Results: </strong>There has been a steady decrease in mortality rates for all NS-SEC classes over the period, 2001-08. Mortality rates for the 'Routine' class declined on average by around 11 deaths per 100,000 population per year, almost double that of the 'Higher managerial and professional' class. Absolute differences between the mortality of the least and most advantaged classes showed a small decline based on three different measures. Relative differences, however, increased over this period. In 2001 the mortality rate of those in routine and manual occupations was 2.0 times that of those in managerial and professional occupations. In 2008 that ratio had risen to 2.3. This pattern of declining absolute but rising relative inequalities is a well known phenomenon in the context of declining overall mortality rates.</p><p><strong>Conclusions: </strong>The results presented suggest that annual trends in inequalities in mortality at the national level can be effectively monitored using LFS-based measures. This would complement the current measures that are based on area of residence rather than the socio-economic position of the individual.</p>","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":" 47","pages":"5-32"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.14","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29292003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In brief","authors":"","doi":"10.1057/hsq.2010.1","DOIUrl":"https://doi.org/10.1057/hsq.2010.1","url":null,"abstract":"","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":"45 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58663148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring inequalities in health expectancies in England - small area analyses from the Census 2001 and General Household Survey 2001-05.","authors":"Michael P Smith,&nbsp;Olugbenga Olatunde,&nbsp;Chris White","doi":"10.1057/hsq.2010.11","DOIUrl":"https://doi.org/10.1057/hsq.2010.11","url":null,"abstract":"<p><strong>Background: </strong>Deprivation and ill health are intimately linked. Monitoring this relationship in detail and with sufficient frequency is key in attempts to reduce health inequalities through more efficient targeting of healthcare resources. This study explores the potential of the General Household Survey (GHS) to provide an inter-censal measure of health expectancies in small areas experiencing differing degrees of deprivation.</p><p><strong>Methods: </strong>The prevalence of health status and the health expectancy of males and females at birth and at age 65 by quintiles of small area deprivation are estimated. Comparisons are made between census 2001 and GHS 2001-05 to inform the suitability of the latter as an inter-censal measure of health expectancy across small areas. Comparisons are also made between the health expectancies of people living in more and less deprived areas.</p><p><strong>Results: </strong>Reports of 'good' and 'fairly good' health fell and health expectancies declined as deprivation increased. Consistency between census and GHS data indicates that the latter is a suitable source for the inter-censal measurement of health expectancies across quintiles of deprivation. At birth, people living in the least deprived areas can expect more than 12 additional years of life in good or fairly good health than those in the most deprived areas, at age 65 the difference was more than four years. In terms of the proportion of life spent in favourable health states; at birth, those living in the least deprived areas could expect to spend around 91 per cent or more of their lives in good or fairly good health compared to 82 per cent for those in the most deprived areas. At age 65, people in the least deprived areas could expect to spend around 82 per cent of their remaining life in good or fairly good health compared to 69 per cent or less for those in the most deprived areas.</p><p><strong>Conclusions: </strong>This study represents the first use of the Index of Multiple Deprivation (IMD) 2004 in the measurement of health expectancy across small areas. Both the census and GHS highlighted substantial differences in the health status and health expectancies of people experiencing differing degrees of ecological deprivation. These findings serve as a useful measure and benchmark in the targeting and assessment of interventions designed to ameliorate health inequalities.</p>","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":" 46","pages":"51-68"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.11","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29039006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inequalities in disability-free life expectancy by area deprivation: England, 2001-04 and 2005-08.","authors":"Michael P Smith,&nbsp;Olugbenga Olatunde,&nbsp;Chris White","doi":"10.1057/hsq.2010.20","DOIUrl":"https://doi.org/10.1057/hsq.2010.20","url":null,"abstract":"<p><strong>Background: </strong>The reduction of health inequalities is a long-standing public health priority. Accurate and timely measurement of the magnitude of health inequalities over time is complex, often relying on data available from a decennial census to conduct detailed analyses of social and geographical inequalities. While inequalities in mortality rates and life expectancy are well-established, the scale of inequality in health expectancies has been reported to be even greater. This study examines changes in inequality in disability-free life expectancy (DFLE) over time between Lower Super Output Areas (LSOAs) in England, grouped into quintiles of an area-based measure of relative deprivation.</p><p><strong>Methods: </strong>Life expectancy (LE) and DFLE for males and females at birth and at age 65 were estimated using a combination of survey, mortality and population data; survey data provided an estimate of the prevalence of limiting long-standing illness or disability (LLSI) used in the DFLE metric. An estimate of the inequality in DFLE between area-based quintiles of relative deprivation (using the Index of Multiple Deprivation 2007) in the periods 2001-04 and 2005-08 enabled the measurement of change in equality over time between advantaged and disadvantaged areas.</p><p><strong>Results: </strong>The prevalence of LLSI among males and females rose incrementally with increasing levels of deprivation in both periods. Males and females in the most deprived areas were more than 1.5 times more likely to report LLSI compared to those in the least deprived areas. There were also large inequalities in LE and DFLE in a similar pattern to LLSI. The extent of inequality in DFLE between the most and least deprived quintiles was approximately twice that of LE. Although LE and DFLE generally increased over time, this improvement varied across quintiles, causing the gap between the most and least deprived quintiles to increase. In comparison with more advantaged areas, people experiencing the greatest deprivation spent the greatest proportion of their lives with a limiting illness or disability, and this proportion increased over time.</p><p><strong>Conclusions: </strong>Males and females at birth and at age 65 in the less deprived areas could expect longer, healthier lives than their counterparts in more deprived areas in both 2001-04 and 2005-08. This analysis suggests that the inequality in DFLE between deprived and affluent area clusters has increased during the first decade of the 21st century.</p>","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":" 48","pages":"36-57"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.20","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29513138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploratory analysis of seasonal mortality in England and Wales, 1998 to 2007.","authors":"Gary Brown,&nbsp;Vanessa Fearn,&nbsp;Claudia Wells","doi":"10.1057/hsq.2010.21","DOIUrl":"https://doi.org/10.1057/hsq.2010.21","url":null,"abstract":"<p><strong>Background: </strong>This article reports research carried out to inform possible methods of describing seasonal mortality in relation to extremes of temperature. In particular, since different methods are currently used to assess excess winter mortality and heatwave related mortality, we aimed to find out whether a single method could be used to measure all seasonal mortality in relation to temperature. In order to do this the project investigated whether there are temperatures above or below which excess deaths occur, and explored whether it is possible to predict reliably how many deaths would occur at extreme temperatures.</p><p><strong>Methods: </strong>Daily and monthly Central England Temperatures for 1998 to 2007 were supplied by the Met Office Hadley Centre and daily death occurrence data between 1993 and 2007 was extracted from the death registrations database held by the Office for National Statistics (ONS). Least squares regression, based on the previous five years of data, was used to predict expected mortality, and excess mortality was calculated as the difference between the expected mortality and the observed mortality on any given day. Statistically significant increases in both daily deaths and temperatures were investigated with the probability of excess mortality assessed on those days. Two regression models were calculated, one for deaths and temperature and one for excess deaths and temperature.</p><p><strong>Results: </strong>Five days with statistically significant excess mortality were identified over the period 1 January 1998 to 31 December 2007, the largest being on 31 December 1999. Three of the five days identified coincided with extremely hot weather occurring in August 2003 and July 2006. However, more extreme temperatures were seen on some days with no excess mortality, so predicting mortality using extreme temperatures alone would cause frequent false positive results. Regression models based on daily death and temperature explained only 8 per cent of the variance in summer mortality and 7 per cent of the variance in winter mortality. The models based on excess deaths and temperature explained 20 per cent of the variance in excess mortality in summer, but only 1 per cent of the variance in excess mortality in winter.</p><p><strong>Conclusion: </strong>There is a weak but significant relationship between temperature and mortality in both the summer and winter months. While in winter mortality does increase as it gets colder, winter mortality is variable and high mortality can occur on relatively mild days. Similarly, in the summer high temperatures are often associated with relatively increased mortality, but a single hot day does not always lead to excess deaths. Daily mortality cannot be predicted from temperature alone: the prevalence of influenza in winter and factors such as air pollution in summer should also be considered.</p>","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":" 48","pages":"58-80"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.21","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29513139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In brief","authors":"","doi":"10.1057/hsq.2010.13","DOIUrl":"https://doi.org/10.1057/hsq.2010.13","url":null,"abstract":"","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":"79 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.13","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58663241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Life expectancy and disability-free life expectancy estimates for Middle Super Output Areas; England, 1999-2003.","authors":"Olugbenga Olatunde,&nbsp;Chris White,&nbsp;Michael P Smith","doi":"10.1057/hsq.2010.15","DOIUrl":"https://doi.org/10.1057/hsq.2010.15","url":null,"abstract":"<p><strong>Background: </strong>In recent years, there has been increasing demand for health indicators at small area level to support monitoring and planning. This study investigates the use of a small area geography, Middle Layer Super Output Areas (MSOAs) for the estimation and comparison of disability-free life expectancy (DFLE) in England.</p><p><strong>Methods: </strong>Using death registrations from 1999 to 2003 and data on limiting long-term illness from the Census 2001, life expectancy and DFLE are estimated for English MSOAs and Government Office Regions. Figures are presented for quintiles based on MSOA DFLE values, and quintiles of relative deprivation using the Index of Multiple Deprivation 2004. Health inequalities are assessed at regional level and between quintile extremes for both measures.</p><p><strong>Results: </strong>The distribution of DFLE across MSOAs was characterised by a north-south geographical divide: the highest DFLE at birth for males was in Kensington and Chelsea 016 (73.9 years) and lowest was in Manchester 013 (44.1 years). For females the highest value was in Kensington and Chelsea 012 (74.4 years) and the lowest in Liverpool 039 (48.2 years). Over 40 per cent of MSOAs in the South East, but only about 3 per cent of those in the North East, were in the quintile with the highest DFLE values at birth. Conversely, the equivalent proportions in the quintile with the lowest values were approximately 4 per cent and 50 per cent respectively.At birth, males in the most affluent areas could expect to spend an additional 12.6 years without a disability compared to those in the most deprived areas. For females this inequality was 10.9 years. At age 65 inequalities persisted but the differences were narrower.</p><p><strong>Conclusions: </strong>This is the first use of MSOAs in estimating DFLE, and the results highlight the substantial inequalities between quintile groupings based on DFLE values as well as between the least and most deprived MSOAs in England. These findings provide useful health outcomes information to planners at the local level, for benchmarking purposes and to assist in resource allocation through the identification of differences in relative need between local populations.</p>","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":" 47","pages":"33-65"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.15","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29292004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intercensal denominators - feasibility of using the Labour Force Survey to estimate mortality rates by NS-SEC.","authors":"Brian Johnson,&nbsp;Ann Langford","doi":"10.1057/hsq.2010.2","DOIUrl":"https://doi.org/10.1057/hsq.2010.2","url":null,"abstract":"<p><strong>Background: </strong>The purpose of this analysis is to investigate the feasibility of using the Labour Force Survey (LFS) to provide population denominators for the estimation of mortality rates by the National Statistics Socio-economic Classification (NS-SEC). This is in order to contribute to the monitoring of health inequalities over time. Currently it is possible to produce mortality rates only at the time of a census when populations are enumerated by occupation and NS-SEC.</p><p><strong>Methods: </strong>The Labour Force Survey (LFS) was used to provide population denominators by age, sex and NS-SEC for various time periods. Numerators for mortality rates were derived by obtaining aggregate deaths by age group and NS-SEC analytic class for men aged 25-64. Standardised mortality rates were then derived. Results for 2001-03 were compared with published estimates which used 2001 Census-based denominators.</p><p><strong>Results: </strong>Significant differences were detected for most NS-SEC classes between mortality rate estimates, based on the 2001 Census, and those based on the contemporary LFS dataset. However the results for different years, based on LFS denominators, suggest that a series of mortality rates using LFS-based denominators appeared to have internal consistency. The LFS-based estimates showed a statistically significant decrease in mortality rates between the periods 2001-03 and 2005-07, across all but one NS-SEC classes. The precision of LFS-based estimates at different levels of geography was also assessed in order to determine the feasibility of using these estimates to monitor inequalities at sub-national level.</p><p><strong>Conclusions: </strong>The LFS can be used to produce regular population denominators for the estimation of mortality rates, to assess health inequalities by NS-SEC for men at the level of England & Wales, both on an annual basis and over three-year time periods. It is recommended that, in order for the LFS-based estimates to be effective over time, they would have to be related to each other rather than to the census-based ones. At the level of Government Office Region (GOR), it would also be possible to do this, but on a three-year period basis only. Below this level of geography, estimates would be insufficiently precise. Information exists on the LFS to produce a similar analysis for women.</p>","PeriodicalId":87183,"journal":{"name":"Health statistics quarterly","volume":" 45","pages":"3-27"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1057/hsq.2010.2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28913928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}