BackgroundIn order to improve the health of the most vulnerable groups in society, the WHO Commission on Social Determinants of Health (CSDH) called for multi-sectoral action, which requires research and policy on the multiple and inter-linking factors shaping health outcomes. Most conceptual tools available to researchers tend to focus on singular and specific social determinants of health (SDH) (e.g. social capital, empowerment, social inclusion). However, a new and innovative conceptual framework, known as social quality theory, facilitates a more complex and complete understanding of the SDH, with its focus on four domains: social cohesion, social inclusion, social empowerment and socioeconomic security, all within the same conceptual framework. This paper provides both an overview of social quality theory in addition to findings from a national survey of social quality in Australia, as a means of demonstrating the operationalisation of the theory.MethodsData were collected using a national random postal survey of 1044 respondents in September, 2009. Multivariate logistic regression analysis was conducted.ResultsStatistical analysis revealed that people on lower incomes (less than $45000) experience worse social quality across all of the four domains: lower socio-economic security, lower levels of membership of organisations (lower social cohesion), higher levels of discrimination and less political action (lower social inclusion) and lower social empowerment. The findings were mixed in terms of age, with people over 65 years experiencing lower socio-economic security, but having higher levels of social cohesion, experiencing lower levels of discrimination (higher social inclusion) and engaging in more political action (higher social empowerment). In terms of gender, women had higher social cohesion than men, although also experienced more discrimination (lower social inclusion).ConclusionsApplying social quality theory allows researchers and policy makers to measure and respond to the multiple sources of oppression and advantage experienced by certain population groups, and to monitor the effectiveness of interventions over time.

BackgroundEvidence suggests that there is a link between inequitable access to healthcare and inequitable distribution of illness. A recent World Health Organization report stated that there is a need for research and policy to address the critical role of health services in reducing inequities and preventing future inequities. The aim of this manuscript is to highlight disparities and differences in terms of the factors that distinguish between poor and good access to healthcare across six Asia-Pacific countries: Australia, Hong Kong, Japan, South Korea, Taiwan, and Thailand.MethodsA population survey was undertaken in each country. This paper is a secondary analysis of these existing data. Data were collected in each country between 2009 and 2010. Four variables related to difficulties in access to healthcare (distance, appointment, waiting time, and cost) were analysed using binomial logistic regression to identify socio- and demographic predictors of inequity.ResultsConsistent across the findings, poor health and low income were identified as difficulties in access. Country specific indicators were also identified. For Thailand, the poorest level of access appears to be for respondents who work within the household whereas in Taiwan, part-time work is associated with difficulties in access. Within Hong Kong, results suggest that older (above 60) and retired individuals have the poorest access and within Australia, females and married individuals are the worst off.ConclusionRecognition of these inequities, from a policy perspective, is essential for health sector policy decision-making. Despite the differences in political and economic climate in the countries under analysis, our findings highlight patterns of inequity which require policy responses. Our data should be used as a means of deciding the most appropriate policy response for each country which includes, rather than excludes, socially marginalised population groups. These findings should be of interest to those involved in health policy, but also in policy more generally because as we have identified, access to health care is influenced by determinants outside of the health system.

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