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Social determinants of stressful events (SE) play an important role in justifying the cause of inequality in the experience of SE. The purpose of this study is to investigate the determinants that impact on inequality in the experience of SE.

The statistical population of this study includes all residents of Tehran. The statistical sample was 5,895 people who were selected by multistage cluster method and were proportional to the population size. The research tool is a researcher-made questionnaire designed to measure SE in Tehran, which includes 11 psychological stressors. The Oaxaca–Blinder decomposing method was used to analyze data.

In a total of 11 psychological SE, in 6 of those events, there was significant inequality in the experience of SE. Concentration Index (CI) of political SE is (CI = −0.27, 95% CI: −0.47, −0.07) and in favor of the rich (pro-rich). Education (OR = 1.60) in poor group and region development in poor and rich (respectively in all of the following) (OR = 0.42–0.73) are the main determinants of inequality in this stressor. CI of neighborhood underdevelopment SE is (CI = −0.47, 95% CI: 0.66, −0.28) and pro-rich. Education (OR = 1.26–1.27) and region development (OR = 1.18–2.24) are the main determinants of inequality in this stressor. CI of livelihood problems SE is (CI = −0.58, 95% CI: 0.68, −0.32) and pro-rich. Education (OR = 1.40) and health status (OR = 1.63) in poor group are the main determinants of inequality in this stressor. CI of future uncertainty SE is (CI = −0.12, 95% CI: 0.34, −0.08) and pro-rich. Gender (OR = 1.22) in poor group and region development (OR = 0.24–0.58) are the main determinants of inequality in this stressor. CI of education problems (CI = 0.19, 95% CI: 0.05, 0.32) and pro-poor. Age (OR = 0.32–0.34) and education (OR = 3.65–3.30) are the main determinants of inequality in this stressor. CI of housing problems is (CI = −0.29, 95% CI: −0.49, −0.08) and pro-rich. Education (OR = 1.31) and region development (OR = 1.64) in poor group are the main determinants of inequality in this stressor.

The first limitation is related to the level of data analysis, and the second limitation is the lack of comprehensive data on social determinants.

Social determinants affecting the formation of inequality in the experience of SE. Some social determinants, such as the level of education and development of the region, play a more prominent role in justifying inequality in the experience of stress between rich and poor groups.

Inequality in the experience of SE is a serious threat to mental and social health. One of the ways to reduce the experience of psychological and social stress is to pay attention to social determinants that play a role in the formation of stress.

This original paper was conducted by examining the effect of social determinants on the formation of inequality in the experience of stress, which draws the serious attention of policymakers.

This chapter provides both an introduction to the volume and a review of literature on health disparities and social determinants.

Literature Review.

The chapter argues for the importance of greater consideration of social determinants of health disparities. This includes a consideration of race/ethnicity and socioeconomic status factors, geographic and place factors, and disparities especially linked to particular diseases.

Reviews the topic of health disparities and social determinants and previews this book.

Epidemiology is often described as “the basic science of public health” (Savitz, Poole & Miller, 1999; Syme & Yen, 2000). This description suggests both a close association with public health practice, and the separation of “pure” scientific knowledge from its application in the messy social world. Although the attainability of absolute objectivity is rarely claimed, epidemiologists are routinely encouraged to “persist in their efforts to substitute evidence for faith in scientific reasoning” (Stolley, 1985, p. 38) and reminded that “public health decision makers gain little from impassioned scholars who go beyond advancing and explaining the science to promoting a specific public health agenda” (Savitz et al., 1999, p. 1160). Epidemiology produces authoritative data that are transformed into evidence which informs public health. Those data are authoritative because epidemiology is regarded as a neutral scientific enterprise. Because its claims are grounded in science, epidemiological knowledge is deemed to have “a special technical status and hence is not contestable in the same way as are say, religion or ethics” (Lock, 1988, p. 6). Despite the veneer of universality afforded by its scientific pedigree, epidemiology is not a static or monolithic discipline. Epidemiological truth claims are embodied in several shifting paradigms that span the life of the discipline. Public health knowledges and practices, competing claims internal and external to epidemiology, and structural conditions (such as current political economies, material technologies, and institutions) provide important contexts in which certain kinds of epidemiological knowledge are more likely to emerge.

A crucial contemporary public health issue is the construction and contestation of the relevance of the natural world to human health.

Taking a critical approach, this chapter examines how the natural environment as a health determinant is positioned in relation to the ‘social’ within social theory generally and social epidemiological studies of health, illness and disease specifically.

– This study shows how current constructions of social and natural environmental health drivers contour social approaches to the study of health and proposes an integrated social-ecological approach for generating new contributions of social epidemiology to research on environmentally driven health injuries.

– The research breaks ground for further social scientific studies of health and the environment and in particular substantiates the call for an extended notion of the ‘environment’ using ecological principles. Methodologically, the interdisciplinary reach of this research draws attention to the tensions that arise when working across the medical, natural and social sciences.

Late nephrology referral, a problem currently identified across many high income countries, has been associated with reduced opportunities for delaying or halting the progression of chronic kidney disease (CKD), delayed dialysis initiation, reduced choice in treatment modality, increased morbidity and hospitalization, and premature death. Despite a recent finding that the progression of CKD nearly always presents warning signs, and despite the fact that all Canadians are entitled to receive medically necessary health care free at the point of patient entry, each year in the province of British Columbia (BC) a substantial number of people with CKD experience late or no referral to nephrology care prior to requiring renal replacement therapy. A subset of these CKD patients experience no referral and “crash” onto dialysis (experience an acute or emergent start). Existing research has not fully explored the range of potential health determinants that may affect the timing of nephrology referral. This paper adopts a “determinants of health” framework and assesses the impact of a variety of indicators on patients’ physical health, demographics, socioeconomic status, social support, geographic and health system characteristics. Using a late referral definition of <3 months and data on BC patients who began dialysis between April 2000 and March 2003, multiple regression analysis indicates that the following determinants have an independent effect on the timing of referral: cause of end-stage renal disease (p=<0.0001); age (p=<0.0001); race/ethnicity (p=0.0019); English ability (p=0.0158); marital status (p=0.0202); proximity to care (p=0.0118); and, “age by first language” (p=0.0244).

This paper is an account of the discussions and recommendations by the exper t advisory panel on potential metrics and ‘sentinel indicators’ for improved outcomes in housing and mental health, as par t of an inter‐agency seminar called to advise on the development of metrics and measures for community mental health, for Fair Society, Healthy Lives: The Marmot Review (Marmot, 2010). The seminar covered all aspects of mental health in both its broadest and narrower senses.Much of the background material for these discussions, therefore, cuts across familiar knowledge silos between the fields of health and housing. Where it is necessary to elucidate the text, references are included to relevant research and policy frameworks that may be unfamiliar to the general reader. This paper is not, however, intended as a general literature review nor is it an evaluation of the available research. A paper on this subject will feature in a future issue of the Journal.1The conclusions from the panel discussion are presented in four main areas, reflecting the need to specify metrics across the wide‐ranging interface between housing and mental health, while still keeping the task manageable. Five current or potential health service metrics were proposed as having par ticular value as signal indicators. Two of these (relating to primary care prevention and public health) have no precision as yet, par tly as new services and approaches are still evolving. Among existing health datasets, the Mental Health Minimum Dataset (MHMDS) (NHS Information Centre, 2009a), SITuation REPor ts (SITREPS) (Department of Health, 2003), and the Summary Care Record data were singled out, though each is thought to need more work to improve the current data categories as well as data collection.One rather more fundamental point made was that the identifying, assessing and encouraging of effective inter‐sector par tnership work will be the key to tackling health inequalities. The use of other, non‐health services data therefore holds great potential for a better recognition both of needs and of outcomes in successful par tnership work, especially where this can be interpreted at local level. These wider comments are elaborated in the context of housing, but may be applicable to all effor ts to evidence and work with the social determinants and the social outcomes of mental health. For the future, a combination of well‐crafted nationally sanctioned metrics and the ‘soft intelligence’ of locally identified meaning may be most effective.Subsequent developments confirm the potential in cross‐sector development work, and indicate the potential for fur ther collaboration via the local performance framework. As policy frameworks continue to evolve rapidly, the ar ticle ends with a Codex, updating the relevant policy frameworks context since the seminar (in Spring 2009) and especially in the context of a new coalition government with aspirations to ar ticulate and promote public health in the context of the local performance framework and the ‘new localism’ agenda. This final section and comments therein are therefore entirely the responsibility of the author.

This paper aims to report findings from the first year of the Vanguard Laundry evaluation study, which explores the impacts of a work integration social enterprise (WISE) on health.

Drawing on social determinants of health (SDH) conceptual framework, a mixed-methods longitudinal case study is used to evaluate the health impacts of a WISE employing people with lived experience of mental illness. In stage one of this study, 31 participants including staff and managers completed semi-structured interviews, validated health and well-being measures and a questionnaire based on the organisation’s theory of change. Quantitative data were analysed descriptively, and qualitative data are analysed thematically.

Data provided further evidence of the conceptualised WISE pathways for impact on SDH through employment, social integration, increased income, improved social position and living conditions. While social enterprise (SE) beneficiary staff had lower well-being scores than other staff members and management, the majority reported improved health, increased social supports and enhanced well-being through improved material conditions and increased sense of purpose, confidence and social connection.

Stage one of this study relied on self-reported data. Future stages will incorporate income support and health data extracted from government agencies with participant consent.

This paper responds to calls for longitudinal studies that include a range of participants and use health outcome measures to further explore how a WISE impacts health through acting on SDH.

A public health approach for promoting mental health has become a major health policy agenda of many governments. Despite this worldwide attention on research addressing population mental health and general wellbeing, very little is heard on positive mental health from the low-and middle-income countries. This paper aims to present an attempt to develop a model of positive mental health among young people. This could be used for integrating the concept of positive mental health (PMH) into public health interventions.

The study was conducted in the state of Kerala, India. The paper administered the “Achutha Menon Centre Positive Mental health Scale” to a sample of 453 (230 men and 223 women) in the age group 18-24, along with an interview schedule exploring the relationship of PMH with many explanatory variables such as sex, beliefs, religion, education, employment and social capital. The paper developed an input path model through a series of multiple regressions explaining the levels of PMH in the community, which was then tested statistically (using AMOS version 7.0). The input model was created by identifying the determinants and correlates of PMH based on their predictive power on the outcome variable, the PMH score. The input diagram was used to test the model fit of the data.

The path model (Figure 1) clearly specified the determinants of PMH. Among them, the variables that have a direct determinant effect on PMH are: quality of home learning environment, employment status, education status, marital status, self-perception on possession of skills, happiness with life, membership in social organizations and socializing capability.

In this study, path model is used to confirm relationships among observed and latent variables. The path diagram assesses the comparative strength of the correlations between the variables and does not test the directionality. Or, the model itself cannot prove causation.

Determinants of PMH those are amenable to interventions as well as those which help in recognizing characteristic groups for intervention could help to plan future intervention programs.

Original paper based on primary data collected through a cross-sectional survey.

An expanding conceptual and research literature identifies cardiovascular disease (CVD) as the disease whose incidence varies most, according to income level. To date however, there has been virtually no public consideration in Canada of the role that societal factors play in its incidence. In an attempt to redress this gap, a community coalition brought together the latest research on the societal determinants of CVD. Barriers to public awareness and public policy action to address these societal determinants of health included the unwillingness of health care associations to consider societal determinants of health as relevant to their activities; general resistance by the media; and active attempts by governments of the day to shift focus away from societal determinants of health. Considering these barriers, university personnel involvement appears essential to any attempt to identify and address the societal determinants of CVD and other diseases.