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The early care and education (ECE) workforce plays a pivotal role in shaping early childhood developmental trajectories and simultaneously experiences significant mental health disparities. The purpose of this study is to investigate how social determinants of health and external stressors are associated with the mental health of ECE staff, which represent a low-resourced segment of the workforce; how psychological capital (psycap) can mitigate these associations.

The authors administered an 89-item survey to 332 ECE staff employed in 42 Head Start centers in the USA. The authors ran three hierarchical linear regression models to analyze associations between social determinants of health, external sources of stress, psycap and potential moderation effects and mental health outcomes.

Individuals experiencing greater finance-related stress reported 0.15 higher scores on the depression scale and 0.20 higher scores on the anxiety scale than those experiencing less finance-related stress (p < 0.05). Individuals experiencing greater work-related stress reported 1.26 more days of poorer mental health in the past month than those experiencing less work-related stress (p < 0.01). After controlling for all sociodemographic variables and sources of stress, psycap was significantly and negatively associated with depressive symptomology (b-weight = −0.02, p < 0.01) and the number of poor mental health days reported in the past month (b-weight = −0.13, p < 0.05). Moderation models suggest that higher levels of psycap may mitigate the association between work-related stress and the number of poor mental health days reported in the past month (b-weight = −0.06, p = 0.02).

The implications of these findings suggest a need for policy change to mitigate social determinants of health and promote pay equity and multi-level interventio ns that target workplace-related stressors and psycap to combat poor mental health of the ECE workforce.

This chapter re-examines the determinants of health care expenditure (HCE), using a panel of 32 Organization for Economic Cooperation and Development (OECD) countries from 1990 to 2012. In particular, a panel semiparametric technique (i.e., a partially linear model) is employed, with cross-sectional dependence allowed. Beside the study of coefficients, this chapter investigates the trending functions of HCE. After the common and individual trends of HCE are estimated via semiparametric methods, the authors calibrate them with polynomial specifications, leading to out-of-sample forecasting. The validities of the calibration are tested as well. Contrary to those studies that do not take into account time series properties, our finding suggests that medical care is not a luxury commodity. Other determinants, such as public financing, and the supply of doctors, are all positively related to HCE. Moreover, the calibrated trending models perform well in out-of-sample forecasting.

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.

This chapter attempts to study the long-term determinants of public and private healthcare expenditure in Hong Kong, by employing time series data over the period from 1990 to 2017. We find that income is not a determinant of either public or private spending per capita on healthcare services. Rather, a higher proportion of elderly will raise public expenditure on health and private spending even more. The share of children within the population will conversely decrease both public and private spending. Results also show that the rising density of doctors decreases both public and private per capita healthcare spending, showing that the supplier-induced demand problem is not an issue in Hong Kong.

Many in Generation Z are concerned about health, nutrition, and lifestyle. They are sensitive to the social determinants of health, represented through concerns about access to health care, viable and affordable housing, poverty, and unemployment. They are also concerned about food choices, their environmental footprint, and the way food is produced. There is similarly high awareness about the importance of nutrition for health. Despite engaging in physical exercise, Generation Z is also exposed to the risks associated with obesity and sedentary lifestyle.

Unequal social conditions that provide people with unequal opportunities to live healthy lives are considered unjust and associated with “health inequity”. Governing power is impacting people's lives through laws, policies and professional decisions, and can be used intentionally to combat health inequity by addressing and changing people's living- and working conditions. Little attention is paid to how these ways of exercising governing power unintentionally can structure further conditions for health inequity. In this paper, the authors coin the term “governance determinants of health” (GDHs). The authors' discussion of GDHs potential impact on health inequity can help avoid the implementation of governing strategies with an adverse impact on health equality. This paper aims to discuss the aforementioned objective.

The authors identify Governance Determinants of Health, the GDHs. GDHs refer to governance strategies that structurally impact healthcare systems and health equality. The authors focus on the unintended, blind sides of GDHs that maintain or reinforce the effects of socioeconomic inequality on health.

The power to organize healthcare is manifested in distinct structural approaches such as juridification, politicalization, bureaucratization and medical standardization. The authors explore the links between different forms of governance and health inequalities.

The authors' discussion in this article is innovative as it seeks to develop a framework that targets power dynamics inherent in GHDs to help identify and avoid GDHs that may promote unequal access to healthcare and prompt health inequity. However, this framework has limitations as the real-world, blurred and intertwined aspects of governing instruments are simplified for analytical purposes. As such, it risks overestimating the boundaries between the separate instruments and reducing the complexity of how the GDHs work in practice. Consequently, this kind of theory-driven framework does not do justice to the myriad of peoples' complex empirical practices where GDHs may overlap and intertwine with each other. Nevertheless, this framework can still help assist governing authorities in imagining a direction for the impacts of GDHs on health equity, so they can take precautionary steps to avoid adverse impacts.

The authors develop and explore – and demonstrate – the relevance of a framework that can assist governing authorities in anticipating the impacts of GDHs on health inequity.

This article analyses the new venture creation by patient innovators in 40 countries examining the effects of the four macro-level factors on entrepreneurship, adding a fifth sector-specific (healthcare) factor.

By applying the statistical tool of principal component analysis, we find a clustering behavior of health user entrepreneurs across countries, indicating that common macro-level conditions affect this phenomenon in a nonlinear way.

Healthy user innovators are more likely to become entrepreneurs in those countries where creativity, economic opportunities and business environment are increasing from the lower level until a certain threshold. After that level, user entrepreneurship seems to be not relevant.

We contribute to the extant literature about macro-level determinants of entrepreneurship by exploring how much such conditions impact on the decision to create new firm by user innovators.

This paper discusses the role played by social determinants of health in the incidence and management of type 2 diabetes mellitus (diabetes) among vulnerable populations. This issue is especially important in light of recent data from Statistics Canada indicating that mortality rates from diabetes have been increasing among Canadians since the mid‐1980s, with increases being especially great among those living in low‐income communities. Diabetes therefore appears – like cardiovascular disease – to be an affliction more common among the poor and excluded. It also appears to be especially likely to afflict poor women. Yet we know little about how these social determinants of health influence diabetes incidence and management. What evidence is available is provided and the case is made that the crisis in diabetes requires new ways of thinking about this disease, its causes, and its management.

Canada’s visible minority population is increasing rapidly, yet despite the demographic significance of this population, there is a surprising dearth of nationally representative health data on visible minorities. This is a major challenge to undertaking research on the health of this group, particularly in the context of investigating racial/ethnic disparities and health disadvantages that are rooted in racialization. The purpose of this paper is to summarize: mortality and morbidity patterns for visible minorities; determinants of visible minority health; health status and determinants of the health of visible minority older adults (VMOA); and promising data sources that may be used to examine visible minority health in future research.

A scoping review of 99 studies or publications published between 1978 and 2014 (abstracts of 72 and full articles of 27) was conducted to summarize data and research findings on visible minority health to answer four specific questions: what is known about the morbidity and mortality patterns of visible minorities relative to white Canadians? What is known about the determinants of visible minority health? What is known about the health status of VMOA, a growing segment of Canada’s aging population, and how does this compare with white older adults? And finally, what data sources have been used to study visible minority health?

There is indeed a major gap in health data and research on visible minorities in Canada. Further, many studies failed to distinguish between immigrants and Canadian-born visible minorities, thus conflating effects of racial status with those of immigrant status on health. The VMOA population is even more invisible in health data and research. The most promising data set appears to be the Canadian Community Health Survey (CCHS).

This paper makes an important contribution by providing a comprehensive overview of the nature, extent, and range of data and research available on the health of visible minorities in Canada. The authors make two key recommendations: first, over-sampling visible minorities in standard health surveys such as the CCHS, or conducting targeted health surveys of visible minorities. Surveys should collect information on key socio-demographic characteristics such as nativity, ethnic origin, socioeconomic status, and age-at-arrival for immigrants. Second, researchers should consider an intersectionality approach that takes into account the multiple factors that may affect a visible minority person’s health, including the role of discrimination based on racial status, immigrant characteristics for foreign-born visible minorities, age and the role of ageism for older adults, socioeconomic status, gender (for visible minority women), and geographic place or residence in their analyses.

Developments at all levels between project and policy have a potential impact on human health. Health‐impact assessment (HIA) is a discipline that seeks to assess these impacts to safeguard and enhance human health. There is a growing consensus about the scope, methodology and context for HIA but there are also many unresolved issues. This paper reviews the main trends as they vary between the healthy public policy, environmental assessment and environmental epidemiology communities; and between retrospective and prospective, developed and developing economies and urban/industrial versus rural settings. There are unresolved issues associated with the nature of evidence, the link with economic appraisal, and with the core biophysical and social health determinants. The nature of the evidence used is examined and some resolutions are proposed. The growing number of guidelines testify to a demand by development agencies for HIA, but increased consensus is required to ensure that quality assessments are delivered.