Trends in poverty risks among people with and without limiting-longstanding illness by employment status in Sweden, Denmark, and the United Kingdom during the current economic recession – a comparative study

BACKGROUND: Previous studies have found higher employment rates and lower risk of relative poverty among people with chronic illness in the Nordic countries than in the rest of Europe. However, Nordic countries have not been immune to the general rise in poverty in many welfare states in recent decades. This study analysed the trends in poverty risks among a particularly vulnerable group in the labour market: people with limiting-longstanding illness (LLSI), examining the experience of those with and without employment, and compared to healthy people in employment in Sweden, Denmark and the United Kingdom. METHODS: Cross-sectional survey data from EU-SILC (European Union Statistics on Income and Living Conditions) on people aged 25–64 years in Sweden, Denmark and the United Kingdom (UK) were analysed between 2005 and 2010. Age-standardised rates of poverty risks (<60% of national median equalised disposable income) were calculated. Odds ratios (ORs) of poverty risks were estimated using logistic regression. RESULTS: In all three countries, non-employed people with LLSI had considerably higher prevalence of poverty risk than employed people with or without LLSI. Rates of poverty risk in the UK for non-employed people with LLSI were higher than in Sweden and Denmark. Over time, the rates of poverty risk for Swedish non-employed people with LLSI in 2005 (13.8% CI=9.7-17.8) had almost doubled by 2010 (26.5% CI=19.9-33.1). For both sexes, the inequalities in poverty risks between non-employed people with LLSI and healthy employed people were much higher in the UK than in Sweden and Denmark. Over time, however, the odds of poverty risk among British non-employed men and women with LLSI compared with their healthy employed counterparts declined. The opposite trend was seen for Swedish men: the odds of poverty risk for non-employed men with LLSI compared with healthy employed men increased from OR 2.8 (CIs=1.6-4.7) in 2005 to OR 5.3 (CIs=3.2-8.9) in 2010. CONCLUSIONS: The increasing poverty risks among the non-employed people with LLSI in Sweden over time are of concern from a health equity perspective. The role of recent Swedish social policy changes should be further investigated

Is occupation a good predictor of self-rated health in China?

China's rapidly changing economic landscape has led to widening social inequalities. Occupational status in terms of occupational type and prestige may reflect these socio-structural shifts of social position and be more predictive of self-rated health status than income and education, which may only reflect more gradual acquisitions of social status over time. The goals of this study were to understand the role of occupational status in predicting self-rated health, which is well known to be associated with long-term mortality, as well as compare the occupational status to the other major socioeconomic indicators of income and education.Data from the 2010 baseline surveys of the China Family Panel Studies, which utilized multi-stage probability sampling with implicit stratification was used. Logistic regression was used to examine the relationship of various socioeconomic indicators (i.e. occupational status, income, and education) with self-rated health as the primary outcome of interest. A series of models considered the associations of occupational category or occupational prestige with self-rated health.The final sample consisted of 14,367 employed adults aged 18-60, which was nationally representative of working adults in China. We found that occupation was not a major predictor of self-rated health in China when age, ethnicity, location, marital status, physical and mental health status were controlled for, with the exception of women working in lower grade management and professional jobs (OR = 1.82, 95% CI: 1.03-3.22). In comparison, income followed by education exhibited greater association with self-rated health. The highest income group had the least probability to report poor health (In men: OR = 0.30, 95% CI: 0.21-0.43. In women: OR = 0.44, 95% CI: 0.26-0.73). People educated with junior high school had better self-rated health than those with primary and below education level (In men: OR = 0.62, 95% CI: 0.50-0.75. In women: OR = 0.53, 95% CI: 0.42-0.68). Income, education and occupation were correlated with each other.Within the context of rapid societal changes in China, income and its implications for greater healthcare access and benefits had the greatest association with self-rated health followed by education. Occupational status was not associated. Occupational categories and prestige should be better adapted to reflect China's unique sociopolitical and historical context

The Forms and Determinants of Social Exclusion in the European Union: The Case of Luxemburg

Social exclusion, Deprivation, Economic and social disadvantages, D60, 050,

Democracy and human development: issues of conceptualization and measurement

This study attempts to reconcile competing positions in an important debate about the relationship between regime type and human development. We contend that this empirical relationship is contingent upon issues of conceptualization and measurement in democracy. First, the relationship is more likely to be perceived when democracy is measured in a nuanced fashion, taking account of gradations of democracy and autocracy. Second, some aspects of democracy – those associated with competitive elections – are more strongly associated with human development than others. Third, the components of electoral democracy interact in a reinforcing manner. Finally, the impact of democracy on human development is a distal relationship that depends upon a country’s entire regime history. Our approach draws on several new datasets that interrogate change across a century, enhancing empirical leverage on this important question. To measure human development, we employ the Gapminder project, covering most sovereign countries from 1900 to 2012. To measure democracy, we draw on Varieties of Democracy data, which measure democracy in a highly differentiated fashion for most sovereign countries from 1900 to the present. An extensive set of analyses offer strong corroboration for the argument