NTH YEAR
JUNE 2014
Health Disparities in the Midwest:
A Framework for Action
Committee on Institutional Cooperation (CIC)
Julie C. Jacobson Vann, Ph.D., M.S., R.N.
American Institutes for Research
Brandy Farrar, Ph.D.
American Institutes for Research
June 2014
American Institutes for Research
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Washington, DC 20007-3835
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Copyright © 2014 American Institutes for Research. All rights reserved.
Contents
Summary .........................................................................................................................................4
Statement of the Problem and Background ...............................................................................5
Goal of Health for All .........................................................................................................5
Health Disparities ................................................................................................................6
Determinants of Health .......................................................................................................6
CSDH Framework and Determinants of Health: ..........................................................7
Element 1: Socio-economic and political context ........................................................7
Element 2: Structural determinants and socioeconomic position .................................7
Element 3: Intermediary determinants ..........................................................................7
Pathways and Root Causes of Health and Health Disparities .......................................8
Historical Perspectives and Evidence on Determinants of Health ..............................10
Social Determinants of Health—Contemporary Evidence .........................................11
Inequitable Allocation of Resources to Public Health and Non-medical
Approaches to Improving Population Health ....................................................................11
Focus on Health and Health Disparities through Health in All Policies Approach ..........12
CIC Objectives
....................................................................................................................13
Developing Data around Disparities .................................................................................14
Identifying Appropriate Interventions ..............................................................................14
Implementing Relevant Interventions to Eliminate or Reduce Disparities and
Advance Health Equity ......................................................................................................15
Statement of Benefits—Value Proposition ...............................................................................15
Operational Plans and Logistics ................................................................................................16
Roles, Responsibilities and Steps in Developing and Coordinating the
Partnerships . ......................................................................................................................16
Steps and Decision Points to Facilitate a Successful Collaboration .................................16
Establishing Priorities in Addressing Health Disparities ..................................................19
Strategies for Addressing Health Disparities ....................................................................19
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Budgets and Resources ................................................................................................................21
Expected Results and Evaluation Plan .....................................................................................21
References ....................................................................................................................................23
Appendix A. Examples of Health Disparities ............................................................................31
Appendix B. Three Elements of the Commission on Social Determinants of
Health Framework ...................................................................................................................36
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Health Disparities in the Midwest: A Framework for Action
Summary
Academic and public health agency partnerships are key to addressing the health
disparities that exist today. Fifteen world-class research universities that are members of the
Committee on Institutional Cooperation (CIC) are poised and well-positioned to collaborate with
their respective state departments of public health – launching an initiative to address health
disparities with the ultimate goal of achieving greater health equity in the region.
The overarching objective of this project is to plan for multi-state and multi-institutional
interventions that enable health equity to be understood, tracked, as well as implementation
begun. The initiative recognizes the context for such health disparities within a broader
framework of the social determinants of health. The project will launch with a major research
summit, drawing on scholars and practitioners within the CIC universities and state departments
of health to identify priority health disparity targets. The summit will likewise support the launch
of a second area of collaboration – the establishment of a large, coordinated data repository on
public health. The repository will safely store large data sets across multiple states and
universities; thus enabling wider scale and comparative studies. The repository will also support
free scholarly access to these data sets while protecting sensitive data. A third objective of the
two-year planning grant is the launch of significant yet broad interventions that support health
equity. Through a regional campaign that highlights overarching health and wellness themes,
such as child wellness, state-level and focused interventions can advance and articulate more
targeted messages that play upon particular dimensions of this them – vaccinations, for example.
Through this three-pronged approach, the initiative will lend itself to exploring the possibility of
a successful longer-term implementation project.
The CIC universities are well-placed to carry out this health disparities project, and the
CIC, itself, is well-suited to facilitate the project. The institutions include fifteen leading research
universities that stretch across eleven US states, located largely in the Midwest. Organizationally, the CIC was founded over 55 years ago, and it fosters multiple strategic collaborations
across its member institutions, which include research, teaching, leadership development, and
technology alliances. Among these activities are: 1) the Traumatic Brain Injury Project, which
leverages the research strengths of both the CIC and Ivy League universities; 2) OmniPoP, a very
high-speed fiber optic network that enables the sharing of research with research hubs
worldwide; and 3) a data storage working group that supports inter-institutional research groups,
advising them of opportunities and considerations for storing big data sets.
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Health Disparities in the Midwest: A Framework for Action
Committee on Institutional Cooperation (CIC)
Statement of the Problem and Background
Collaboration is important to the future of the health of the U.S. and to the efforts by
public health departments and academic researchers to solve the complex, multifactorial
problems the U.S. faces today. Partnerships between public health agencies and academic
institutions have historically been focused on single specific issues or services. What is missing
is a systemic approach or view of academic-public health agency partnerships (Committee on
Institutional Cooperation [CIC], 2014).
As a way of fostering that collaboration, a partnership is being developed between CIC
universities and the state health departments in their respective states to address some of the
social determinants of health. This comes about because of the discovery that some of the
greatest health disparities exist in the states where CIC schools are located (CIC, 2014).
Health is determined by much more than just the medical care and public health systems.
The social determinants of health play a much bigger role than medical care. The social
determinants could be influenced by research within a wide array academic disciplines. That is
why the link between state health departments and CIC institutions has such great potential (CIC,
2014).
Goal of Health for All
The vision of Healthy People 2020 is “a society in which all people live long, healthy lives” (Healthy People 2020, n.d.). Two key concepts in this vision statement are “healthy” and “all people”. A well-accepted definition of health was published in the Constitution of the World
Health Organization (WHO) in 1946, which states: “health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” (WHO, 1946). This definition is embraced by health professionals in public health, nursing, medicine, and other
disciplines because of its comprehensive nature, focus on the whole person, and an
understanding that health is determined by a wide range of factors that lie outside of traditional
health services systems. The concept of “all persons” in the Healthy People vision statement emphasizes the need to develop and implement policies, systems, programs, and services that
support the full population and not just those in the majority or those with sufficient resources,
support systems, political influence, or environmental characteristics to achieve health. This
concept is further supported by the Healthy People Overarching Goal to “achieve health equity, eliminate disparities, and improve the health of all groups” (Healthy People 2020, n.d.). To achieve this vision requires knowledge and understanding of the health status of populations,
including existing health disparities, the determinants of health, and strategies that are known to
effectively improve the health of populations.
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Health Disparities
The Healthy People 2020 goal to achieve health equity and eliminate disparities in the
U.S. has not been met. In fact, in recent years, health disparities have persisted or increased for
most of the Healthy People 2010 objectives (Meyer et al., 2013). Health status, health outcomes,
and life expectancy often vary by a number of factors, including race and/or ethnicity,
socioeconomic status, and geographic area (Frieden, 2013). Examples of specific health
disparities are summarized in Appendix B.
Determinants of Health
The health of individuals and populations is influenced by a number of factors or
determinants that are described in frameworks developed and described by various individuals,
groups, committees, and commissions. The World Health Organization has categorized the
determinants of health into three major categories: social and economic environment, physical
environment, and individual characteristics and behaviors (WHO, 2014b). Additional health
determinants outlined by WHO include income and social status, education, social support
networks, genetics, health services, and gender (WHO, 2014b). The WHO’s Commission on Social Determinants of Health framed the social determinants of health into three major
elements: (1) the socio-political context; (2) structural determinants and socioeconomic position;
and (3) intermediary determinants (CSDH, 2007; CSDH 2010). (Exhibit 1.)
Exhibit 1. Three Major Elements of the Social Determinants of Health
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This framework will be used in this paper to organize key concepts, such as evidence to
support the relationships between social determinants and health (Appendix B). Healthy People
2020 framed the determinants of health similarly into five key areas: economic stability;
education; social and community context; health and health care; and neighborhood and built
community (Healthy People 2020, 2014). These and other frameworks emphasize the importance
of factors external to health service delivery systems in promoting population health. The
conditions and circumstances in which people live and work help to explain why some people
are healthier than others (Healthy People 2020, 2014).
CSDH Framework and Determinants of Health:
The World Health Organization created the Commission on Social Determinants of
Health as part of a plan to promote health equity on a global level (CSDH, 2007). The intention
to create this Commission was announced at the 2004 World Health Assembly (page 6). The
Commission developed a framework to provide guidance in identifying where to promote
changes in policies and practices aimed at reducing health disparities (CSDH, 2007). This CSDH
framework is intended to be action-oriented, and incorporates the work of a number of
previously developed models focused on health determinants and health disparities.
There are three major components or elements within the CSDH Framework:
socioeconomic and political context; structural determinants and socioeconomic position; and
intermediary determinants (Exhibit 2).
Element 1: Socio-economic and political context
Element 1 of the CSDH Framework, the socio-economic and political context, “refers to the spectrum of factors in society that cannot be directly measured at the individual level” (CSDH, 2007, page 21). Context refers to structural, cultural and functional aspects of society.
Element 2: Structural determinants and socioeconomic position
Element 2 of the CSDH Framework, the structural determinants and socioeconomic
position, refers to social factors that promote or undermine health and social processes that are
associated with the unequal distribution of social factors.
Element 3: Intermediary determinants
Element 3 of the CSDH Framework, the intermediary determinants, are the downstream
factors that influence health and health disparities.
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Exhibit 2. Elements in the Commission on Social Determinants of Health Framework
Pathways and Root Causes of Health and Health Disparities
The factors that determine health and health inequities are complex and
multidimensional. From a simplistic standpoint, it is relatively easy to see and understand the
relationships between health behaviors and health status and outcomes, diseases, injuries and
death. In addition, there are observable relationships between access to and receipt of medical
and health services and some health outcomes. Yet, in order to improve the health of populations
and decrease health disparities it will take a much broader view of health determinants than a
focus on individual-level health behaviors and health services. This broader view must
encompass the social determinants of health and health inequities and the socioeconomic and
political contexts that exert influence over the environment in which people live, work and play.
This will involve addressing not just the proximal causes of health problems and disparities but
the causes of the causes or the root causes as well (Braveman & Gottlieb, 2014). It is important
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to answer the following questions when developing strategies for addressing health disparities:
“What creates health?” as well as “Where do the health differences among social groups originate, if we trace them back to their deepest roots?” (CSDH, 2007, page 4).
Teasing out the sources of health inequities is complex and challenging. The consensus is
that structural inequalities in populations’ social position are the root cause of these inequities.
Various social, cultural, and institutional processes – such as economic policies and racist and
sexist ideologies – result in inequitable distributions of power, prestige, and income among
demographic groups. Specifically, women, racial and ethnic minorities, the poor and the less
educated are systematically marginalized and thus occupy the lowest positions in the social
hierarchy. These low status positions, in turn, contribute to material, psychological, and
behavioral circumstances that make getting healthy and staying healthy difficult.
In short, material circumstances reflect access to healthy places to live, work, play, and
learn as well as to goods and services that may prevent and treat illness. Psychological
circumstances reflect pathways to mental and emotional well-being. Behavioral circumstances
reflect pathways to healthy lifestyles. Consistent with this conceptualization of health
determinants as spanning many aspects of social life – not just health care – a variety of
individuals and organizations are identified as potential stakeholders in population health,
including those involved in education, labor, housing, community planning and development,
and transportation.
Many who work in public health frame health as a human right and as such view these
inequitable distributions as a social injustice that must be remedied by government agencies and
collective action of the people affected. This framing, along with the identification of the root
causes and intermediary determinants of health inequities and key stakeholders discussed above,
is reflected in the strategies offered for addressing health inequities. Core strategies include:
Addressing the root causes of health inequities alongside the intermediary determinants;
Collaborations across sectors;
Community participation and empowerment; and
Population-based approaches.
A population perspective is important to addressing health disparities because it focuses
on addressing the health of full populations that are located in the community/target area not just
those who seek services. The concept of population health extends beyond providing sick care
services. It seeks to identify needs, meet needs, and especially identify and meet the needs of
vulnerable and underserved populations that may not seek services, may have undetected and
unmet needs, and may not even be known to the health, social services, and other agencies in the
area. It also recognizes the impact of policy decisions on the social determinants of health that
impact communities and the opportunities for health available to community members. The
blending of a population-based approach with a focus on root causes of health disparities can
lead to widespread improvements in health for all segments of society.
Exhibit 3 displays an oversimplification of the concept of root causes using examples of
health disparities that are briefly described in Appendix B. In many U.S. states, school districts
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in high poverty areas receive less funding per student than school districts in wealthier areas
(Iton, n.d.). Evidence has shown that inequitable school funding is associated with lower
performance of low-income students and students of color (Iton, n.d.). Lower levels of
educational attainment are then associated with a number of adverse health outcomes that are
mediated by other factors. For example, between 1988 and 2007, the infant mortality rate among
U.S. mothers who were at least 20 years of age was almost two times higher for those who did
not graduate from high school (7.8%) when compared to mothers who graduated from college
(4.2; Braveman, 2010);
Exhibit 3. Relationship between State Educational Policy and Infant Mortality Rates
Historical Perspectives and Evidence on Determinants of Health
The current understanding of social determinants of health and relatively limited
influence of medical interventions on health has been supported by several landmark studies. The
Whitehall I study, which began in 1967 and was published in 1984, followed a cohort of more
than 17,000 British male civil servants over time to examine the association between mortality
and social class, as measured by employment grade (Marmot, Shipley & Rose, 1984). An inverse
relationship was identified between social class and deaths from coronary heart disease with
higher 10-year mortality rates being observed for persons with lower employment grades, such
as manual labor (Marmot, Shipley & Rose, 1984). When comparing the two lowest employment
grades with the two highest grades, age-adjusted mortality was greater among persons in the
lowest grades compared with the highest grades for almost all causes of death, with the exception
of genitourinary diseases (Marmot, Shipley & Rose, 1984). Overall, the 10-year mortality rate
among males 40 to 64 years of age was more than three times higher among those in the clerical
and manual labor grades than senior administrative grades(Marmot, Shipley & Rose, 1984;
Evans, Barer & Marmor, 1994). The Whitehall II study examined social class differences and the
relationship to morbidity in a cohort of more than 10,000 men and women in London, England,
aged 35 to 55 years (Marmot et al., 1991). The adverse relationship between social class, as
observed in the Whitehall I study, continued to be observed in Whitehall II. Persons in the lower
employment grades, such as clerical roles, were found to have a higher prevalence of angina,
evidence of ischemia on electrocardiograms, chronic bronchitis, and current smoking status than
among those with higher employment grades, such as administrators (Marmot et al., 1991). The
pattern of association between job grade and health status was typically a stepped gradient.
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Dr. Thomas McKeown, the late Professor Emeritus of Social Medicine at the University
of Birmingham, England, published well-known and at times controversial studies on the
determinants of health. He examined and provided an explanation for the decline in infant
mortality and increase in life expectancy at birth that occurred during the late 1800s and early
1900s (McKeown, 2001). Dr. McKeown deduced that the increase in life expectancy, especially
for young children in England and Wales, could be linked to a reduction in deaths from
infectious diseases. Because deaths from prevalent infectious diseases of that time period, such
as tuberculosis, bronchitis, pneumonia, influenza, pertussis, measles, and scarlet fever, started to
decline before effective medical treatments and vaccinations were available, Dr. McKeown
searched for other explanations for the decline in deaths. He concluded that the death rate from
infectious diseases could primarily be attributed to an increase in food production and improved
nutrition (McKeown, 2001). Other contributing factors were improvements in hygiene and safer
food and water supplies.
The Report of the Working Group on Inequalities in Health, also known as the Black
Report, provides additional historical evidence on the contributions of social determinants of
health (Gray, 1982). This report was published by the United Kingdom Department of Health
and Social Security in 1980. It describes the unequal distribution of morbidity and mortality
among the British population. As in the Whitehall studies, morbidity and mortality rates were
found to be higher among those in the lower social classes. These inequalities continued to be
observed after the National Health Service was established in 1948, providing indirect evidence
that health status is determined by factors that extend beyond access to medical care
(Gray,1982). The Black Report concluded that inequalities in health could be attributed to
inequalities in the factors that influence health, such as income, education, housing, nutrition,
employment, and work conditions.
Social Determinants of Health—Contemporary Evidence
Evidence to support the relationships between health status and social determinants of
health has grown considerably since publication of the Whitehall studies, The Black Report and
other landmark reports. Inequalities in health status have been found to be associated with:
income, education, social position or social class, employment, gender, sex, race and ethnicity,
physical environment such as housing, neighborhood conditions, and working conditions, and
political and social contexts. Many of these factors are associated with intermediary
determinants, such as health behaviors, that directly influence health status. Examples of
relationships between social determinants of health and health outcomes are described in
Appendix B. The scope of evidence on relationships between social determinants of health and
health status extends far beyond what is presented here. However, Appendix B highlights a
sample of the relationships that are described in the CSDH Framework.
Inequitable Allocation of Resources to Public Health and Non-medical
Approaches to Improving Population Health
In the U.S. the distribution of resources intended to improve the health of individuals and
populations is highly skewed, with the majority of funds and other resources for services,
policies, and research being directed at the medical care system. On the other hand, public health
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programs and other initiatives aimed at preventing health problems receive a small percent of the
resources. For example, during 2012 only $75 billion of the $2,793.4 billion spent on health, or
2.68% of the total health expenditures in the U.S., was spent on government public health
activities (CMS, n.d.), which tend to focus on health promotion and disease prevention. In
contrast, $565 billion were spent on physician services and $263.3 billion on prescription drugs
that same year (CMS, n.d.). On a per capita basis, $8,915 was spent per person on health services
overall during 2012. Of this per capita amount, $7,533 was spent on personal health care
services, including $2,816 for hospital services, $1,803 for physician services, and $840 for
prescription drugs. Only $239 was spent per capita for government public health services (CMS,
n.d.).
Health-related resource allocation in the U.S. is not paying off in terms of improved
health status. Despite the U.S. spending more than twice what most other industrialized countries
spend on health services, the U.S falls behind on many key health measures. In the 2011
National Scorecard on U.S. Health System Performance, the U.S. achieved an overall score of 64
out of 100 on 42 indicators when compared against benchmarks of the highest performing
countries or areas (The Commonwealth Fund, 2011). In the Scorecard’s “Healthy Lives” dimension, the U.S. scored relatively poorly on infant mortality, adults with activity limitations,
children who missed 11 or more days of school because of illness or injury, adults who smoke,
and children aged 10 to 17 who are overweight or obese (The Commonwealth Fund, 2011). In
addition, the U.S. ranks 24th out of 30 nations on life expectancy (Forsberg & Fichtenberg, 2012).
It has been estimated that approximately 75 percent of our health care costs are related to
preventable conditions (Forsberg & Fichtenberg, 2012). To improve our health systems
performance scores and the health status of populations a new approach is needed, one that
focuses on population-based strategies that are aimed at preventing health problems and reducing
health disparities through greater emphasis on the root causes of health problems and disparities.
Focus on Health and Health Disparities through Health in All Policies
Approach
The Health in All Policies (HiAP) approach aims to improve population health through
strategies that complement health care and public health programs (Ståhl, Wismar, Ollila,
Lahtinen & Leppo, 2006). This approach addresses the broader health determinants by
influencing policies and practices across disciplines that are not traditionally health-focused but
affect health, such as education, agriculture, environment, fiscal, housing, and transportation
policies, to name a few (Exhibit 4; Ståhl, Wismar, Ollila, Lahtinen & Leppo, 2006). A major
strength of this approach is that the risk factors for major diseases or determinants of health can
be modified by policies and strategies that are managed by government sectors and other entities
in society that are external to the health sector. The CIC has the opportunity to assume leadership
of the HiAP approach by engaging the CIC Universities and State Departments of Health or
Public Health in planning, implementing and evaluating regional strategies that have the
potential to improve health through innovative approaches.
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Exhibit 4. Health in All Policies—Sectors to Address Health Disparities and Improve
Population Health
(Sectors: Minnesota Department of Health, 2014)
CIC Objectives
The CIC Health Disparities Project will create an infrastructure to develop and foster
collaborations at the systems level with the goal of:
Developing data around disparities
Identifying appropriate interventions
Implementing relevant interventions to eliminate or reduce disparities and advance health
equity (CIC, 2014).
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Of note, at the regional scale, this project will foster unique and important understandings of the
data and the interventions. The collaboration will support interregional, state-level comparisons
as interventions are implemented.
Developing Data around Disparities
The collection, identification, sharing and use of data are critical components of the CIC
Health Disparities Project plan. The major components of this objective are:
Defining the potential data that are available and their sources;
Defining the data that may be needed;
Identifying whether additional data need to be collected;
Implementing a repository for this data; and
Defining how the data may be used.
The categories of data that are likely to be needed include:
Identification, quantification, description, and comparison of health disparities among
partner states;
Identification, quantification, description, and comparison of disparities in factors that
influence health, such as social and economic indicators, and data on employment,
housing, environmental exposures, minimum wage, and other factors;
Identification, quantification, description, and comparison of intermediary determinants
of health, such as health behaviors among target populations; and
Descriptions of existing federal, state, and local policies that may influence health.
These data will be used to prioritize health disparities to be addressed with appropriate
interventions.
Identifying Appropriate Interventions
A second objective of the CIC Health Disparities Project is to identify interventions that
help to address the selected health disparities. This process may involve conducting systematic
reviews of the literature and/or reviews of existing reviews to identify interventions that are
informed by evidence to the degree feasible. Additionally, the partnership of CIC universities
and state departments of public health provides the CIC project with access to a wide range of
experts who are likely to bring broad experiences and knowledge to the table in identifying and
prioritizing interventions. The data to be obtained may also be analyzed, when appropriate, to
identify the influence of existing interventions or policies on health and health disparities. The
regional scale of this project and these interventions will prove informative in understanding
both health and wellness outcomes within the region and between the CIC states, as well as in
reference to non-CIC states. Several specific components of this objective are:
Identification of the health disparities issues;
Identification of the evidence-based interventions to address the health disparities; and
Summarizing and synthesizing the findings from key scientific resources to establish
priority health disparities issues and interventions.
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Implementing Relevant Interventions to Eliminate or Reduce Disparities and
Advance Health Equity
The third CIC objective is to implement interventions aimed at eliminating or reducing
disparities and advancing health equity. This objective will involve leveraging the partnerships in
collaboratively planning interventions that may be implemented on a regional basis in at least
one CIC state and potentially in all CIC states. The specific components of this objective to be
achieved are:
Developing specific plans to implement and evaluate interventions aimed at reducing
targeted disparities;
Identifying potential funding sources for the target interventions and seeking funding;
Developing a partnership plan with specific roles and responsibilities of partner
organizations, leaders, experts, and scientists;
Developing a plan for evaluation that includes plans to leverage existing data;
Implementing interventions in the selected demonstration states;
Evaluating the interventions; and
Disseminating effective strategies in other CIC states that did not participate in the
demonstration.
Statement of Benefits—Value Proposition
“The CIC Health Disparities Project provides potential benefit to the participating state
health departments, academic institutions, and the populations that are served throughout the
states. The benefits for public health agencies are aligned with access to the intellectual capital
embedded in academic institutions. For the universities, the formalized relationship would
provide access to public health data as well as evidence to validate, support or otherwise inform
academic institutions. Finally, more formalized interaction would be an important component in
the staff development of both institutions (CIC, 2014).”
The case for the CIC Health Disparities Project extends beyond the benefits to be accrued
by the universities and state health departments to the benefits that will be accrued by the
participating states, businesses, and health care organizations. Health equity is not only a social
justice issue, it is an economic issue (Association of State and Territorial Health Officials
[ASTHO], n.d.). Health disparities lead to both direct health services costs and indirect costs to
businesses and other organizations in terms of lost productivity through decreased absenteeism
and presenteeism. The costs of health inequalities and premature death in the U.S. during 2003 to
2003 were estimated at $1.24 trillion (ASTHO, n.d.). Addressing health equity also has the
benefit of improving efficiency within health care organizations (Massachusetts General Hospital
[MGH], 2006). By addressing the root causes of health disparities it is expected that reductions
can be achieved in medical errors, inappropriate test ordering, length of hospital stays,
readmissions, and ambulatory care sensitive avoidable admissions (MGH, 2006). Health
organizations are then expected to operate more efficiently.
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Operational Plans and Logistics
Roles, Responsibilities and Steps in Developing and Coordinating the
Partnerships
The growing interest in using collaboration to deal with problems that affect population
health stems from the fact that many of these problems are complex; consequently, they go
beyond the capacity, resources, or jurisdiction of any single person, program, organization, or
sector to change or control (Israel et al., 1998; Mitchell & Shorter, 2000). Collaborations have
been successful in addressing social issues, including health inequity (Zakocs & Edwards, 2006;
Rousoss & Fawcett, 2000). However, the success of collaborations depends on a variety of
factors, including the availability and use of resources, partner characteristics, partnership
characteristics, partner relationships, and the external environment (Lasker, Weiss & Miller,
2001; Travis, Hart, Hardin & Harwell, 2013; Brown, White & Leibrandt, 2006; Weiss, Anderson
& Lasker, 2002). The collaborative process needs to be designed and run by its diverse
participants rather than by any single stakeholder, and together, the participants need to
determine how their collective work gets done (Lasker & Weiss, 2003).
Steps and Decision Points to Facilitate a Successful Collaboration
Here, the key steps and decision points are outlined that are expected to facilitate a
successful collaboration to address health inequities in the CIC region, recognizing that the
specific content of these choices and their operationalization will depend upon the needs, desires,
and capacities of the interested collaborators.
1. Identify Partners
When identifying good candidates for collaborating partners, there are several criteria to
consider. One consideration is whether potential partners have the resources to contribute
helpfully to the efforts of the collaboration. Resources can include knowledge, funds, staffing,
and time (Emerson, Nabatchi & Balogh, 2012; Ansell & Gash, 2008; Weiss, Anderson &
Lasker,2002).
Another organizational characteristic to consider is whether or not the organization is one
that has a history of collaborating with the partners. Prior experience with positive collaboration
often helps to facilitate the success of the current collaboration by expediting the trust-building
process and familiarity with the specific policies, practices and culture of the collaborating
organizations (Ansell & Gash, 2008).
Last, it is important to partner broadly. As Chrislip and Larson (1994) note, ‘‘The first condition of successful collaboration is that it must be broadly inclusive of all stakeholders who
are affected by or care about the issue.’’ Inclusiveness is important because it facilitates a comprehensive understanding of a problem as well as the potential strategies that might be
employed to address the problem. Inclusiveness also encourages buy-in and facilitates the
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dissemination of the collaborative’s actions to the right people (Emerson, Nabatchi & Balogh,
2012).
2. Establish Infrastructure
The CIC along with the state departments of health within the eleven states that host CIC
institutions will be key and synergistic partners advancing the Health Disparities Project.
Importantly, the both the leadership of the CIC, the fifteen universities’ provosts and the state
health officials expressed enthusiasm for this major planning initiative.
The CIC is in a unique position to facilitate this planning initiative. For more than half a
century, the CIC has supported world-class research institutions’ academic missions, created unique opportunities for students and faculty, and served the common good by sharing expertise,
leveraging campus resources, and collaborating on innovative programs. The CIC leads many
collaborative initiatives, exemplified by the following: 1) a major research collaboration on
traumatic brain injury between the CIC schools and the Ivy League; 2) several projects that
support the professional training and leadership development of underrepresented students, postdoctoral fellows, and faculty; 3) a fiber optic network with very high-speed connectivity that
connects research “hubs” worldwide;; and 4) a data storage working group that advises interinstitutional research groups on platforms for sharing large data sets, securely between scholars.
By combining their networks and institutional strengths the state departments of health and the
CIC will enable successful objectives and outcomes highlighted above.
Formalizing governance structures, including roles, communication processes, and
decision-making processes, such that there is transparency and accountability, are better than
informal structures (Ansell & Gash 2008). One example of how to formalize the governance
structure is to use written agreements (Bryson, Crosby & Stone, 2006; Crosby & Bryson, 2010).
Three types of governing structures are common: (1) self-governing structures in which decision
making occurs through regular meetings of members or through informal, frequent interactions;
(2) a lead organization that provides major decision-making and coordinating activities; and (3) a
network administrative organization, which is a separate organization formed to oversee network
affairs (Crosby & Bryson, 2010). Little evidence has tested the efficacy of different approaches,
but some research suggests that the first governance structure is most effective (Lasker & Weiss,
2003).
Next, identification of strong leaders is vital (Weiss, Anderson & Lasker, 2002). Good
leaders: take responsibility for the partnership, inspire, motivate and empower the partners, work
to develop a common language within the partnership, create an environment where opinions are
discussed openly and respectfully, work to resolve conflict among partners, combine
perspectives, resources and skills of partners, and help the collective group develop creative
strategies to be successful (Weiss, Anderson & Lasker, 2002; Bryson, Crosby & Stone, 2006;
Lasker & Weiss 2003).
Regarding communication and decision-making processes, experts suggest that the use of
facilitators and face-to-face dialogue are most effective because these strategies encourage active
17
participation by all parties in a way that is respectful and transparent (Ansell & Gash 2008;
Bryson, Crosby & Stone, 2006; Crosby & Bryson 2010).
The CIC Health Disparities Project will need to be supported by several key positions and
structures, such as:
Planning group that is represented by the participating CIC universities, state health departments,
and a central coordinator;
Advisory committee to provide additional expertise to the planning group, and to review and
provide feedback on plans;
Central coordinator to manage the initiatives, collaborative processes and communication, and
support the partners by assisting with identifying funding opportunities, identifying potential data
sources, developing and maintaining a tracking system to manage plans, deadlines, and
achievements, and addressing additional needs of the project;
Designated lead at each CIC institution to represent the participating organizations on planning
and decision-making and to manage the internal communication within their respective
organizations;
Lead at each state health department to represent the participating state health
departments on planning and decision-making and to manage the internal communication
within their respective organizations;
Data or evaluation coordinator or analyst, to assist with obtaining datasets, conduct data
analysis to identify disparities in health and determinants of health, summarize findings, and
support efforts to write funding proposals and evaluate CIC projects; and
Fiscal agent to assist the project team(s) with identifying potential sources of funding,
assisting with budget preparation for CIC activities, managing funds, and maintaining financial
documentation;
Independent research firm to assist the CIC and SDH teams with activities to be
determined by the project leaders. For example, the firm may provide expertise and capacity to
support:
o Writing research proposals, manuscripts and white papers
o Planning, leading, and/or conducting systematic reviews of the literature to assess the
relative effectiveness of previously studied interventions to reduce health disparities
o Conducting quantitative data analysis
o Conducting formative research, including qualitative data collection, coding, analysis
and reporting
o Evaluating interventions
o Providing technical assistance
o Developing and validating health measures
3. Collaboratively Set Agenda, including Priorities, Objectives, and Action Plans
All collaborating partners must have a shared stake in and understanding of the mission
of the collaborative for it to be successful (Ansell & Gash 2008; Bryson, Crosby & Stone, 2006;
Crosby & Bryson, 2010; Emerson, Nabatchi & Balogh, 2012; Lasker & Weiss, 2003). Thus, a
series of activities designed to seek input on and reach consensus regarding the priorities,
objectives, and actions of the collaborative are vital. Examples of these activities include
listening sessions, forums, focus groups, and deliberations (Crosby & Bryson, 2010).
18
4. Monitor Progress toward Success
It is important to develop a system of accountability that tracks the inputs, processes, and
outcomes of the collaborative so that adjustments can be made in “real-time” to overcome challenges and continue to progress towards desired outcomes (Crosby & Bryson, 2010).
Establishing Priorities in Addressing Health Disparities
The second objective of the CIC Health Disparities Project is to identify interventions
that help to address the selected health disparities and opportunities for creating health in the
states. In selecting priority areas for health disparities, several factors may be considered: the
scope and distribution of the health disparity problems among CIC states; the availability of
evidence regarding interventions aimed at reducing the health disparity evidence by focusing on
social determinants of health; the availability of potential funding sources; and the preferences
of the CIC planning and advisory groups.
Through a rapid review of health disparities reports, several health disparities among all
or most of the CIC states have been identified. These may be important for the CIC members to
consider when establishing priorities for action. Exhibit 4 displays the identified health
disparities topics from a disease and health behavior focus for the eleven CIC states. Infant
mortality stands out as one major health issue that has shown some improvements over time;
however, the disparity between blacks and whites remains relatively high in all states hosting a
CIC university (Mathews & MacDorman, 2013). During 2007 to 2009, the ratio of non-Hispanic
black to non- Hispanic white infant mortality rates among CIC states was 2.0 or higher for each
state with one state having a ratio of greater than 3.0 (Mathews & MacDorman, 2013). Other
disease-or condition-focused disparities are: hypertension, cardiovascular disease, diabetes, and
cancer. High-disparity health behaviors include physical inactivity and tobacco use (Office on
Women’s Health, 2013).
Strategies for Addressing Health Disparities
Addressing health disparities at the level of social determinants of health is a complex
process that may involve a range of interventions and policy changes. Given that the social
determinants are the most powerful influences on health, policy analysis in the areas of
economics, agriculture, education, transportation, housing, etc. (areas that are in the purvue of
CIC schools) will be crucial. This review process exceeds the scope of this paper. However, in
considering the problem of higher rates of obesity and physical inactivity among racial/ethnic
minorities, the problem can be addresses through several avenues. For example, several
interventions that have been recommended for increasing physical activity include:
Changes to communities to enhance safety and the perception of safety to provide
children and families with a safe place to recreate
Informational approaches intended to motivate people
Points-of-decision prompts, such as motivational signs near elevators and escalators; this
has been recommended based on evidence (Task Force on Community Preventive
Services, 2002);
19
Community-wide campaigns, for example, use of television and other types of
advertisements that promote physical activity in a highly visible way; the campaigns may
aso have targeted activities such as creation of walking trails, support and self-help
groups, and community health fairs;
Mass media campaigns: insufficient evidence
Classroom-based health education focused on information provision: insufficient
evidence
Behavioral and social approaches to increasing physical activity
School-based physical education: strongly recommended
College-based health education and physical education: insufficient evidence
Social support interventions in community settings: strongly recommended
Family-based social support: insufficient evidence
Creation of or enhanced places for physical activity combined with informational
outreach activities: strongly recommended (Task Force on Community Preventive
Services, 2002)
The selection of specific interventions to address each health disparity requires additional review
of evidence.
Exhibit 4.a. Major Health Disparities Identified by Each State Health Department
20
Exhibit 4.b. Major Health Disparities Identified by Each State Health Department
State Major Health Priorities or Health Disparities Issues
21
Budgets and Resources
The financial and other resources that are needed to launch the CIC Health Disparities
Project include a combination of infrastructure and external research funding. Over time, some
of the infrastructure to support the initiative may be absorbed by grant or contract funding.
However, until outside funding is obtained, these expenditures will likely need internal support
from the CIC partnering universities and state departments of public health. In the description of
Operational Plans and Logistics several key positions and collaborators are listed that may
require internal support in the short term, including: central coordinator; data or evaluation
coordinator or analyst; fiscal agent; and contractor(s). In addition, the state departments of public
health and universities should anticipate providing leadership support to the project, as well as
representatives on the planning committee and advisory group. The external funding sources will
be critical for investing in research and evaluations.
Expected Results and Evaluation Plan
An evaluation plan will focus on monitoring the activities of the CIC initiative and
progress toward meeting process-related goals as well as the specific outcomes that are achieved
through the health disparities-related interventions. The evaluation should be supported with a
tracking system to document and monitor progress. In addition, each initiative must describe
specific plans to evaluate the outcomes that include: data sources, data elements to be collected,
processes for data collection and analysis, and reporting. The Planning Group and Advisory
Committee should actively develop a guiding set of evaluation goals and objectives. In addition,
a set of metrics will need to be developed to evaluate the effort. Several broad metrics to
potentially measure over time may include:
Reductions in selected disparities, on a university and regional level
Changes in characteristics of enrolled students and graduates at the universities if
interventions focus on changing the profile of students
Focus of research projects and publications
Student experiences related to social determinants of health in the classroom and
experiential learning
Policy changes within states
Relationships with federal agencies on priorities
A major expected outcome of this initiative is an increase in collaboration among state
departments of public health and universities, with a sharing of information and ideas.
Collaborations are desirable strategies to achieving health equity goals for three core reasons:
1. People have a right to be involved in designing and implementing policies and practices
that affect them.
2. Health inequity is a complex issue involving processes at the local, state and federal
levels, within both public and private institutions and across multiple aspects of our
society such as labor, education, housing, and health care.
3. Synergy can occur through the pooling of knowledge, skill, and financial resources across
multiple individuals and organizations (Solar & Irwin 2007; Solar & Irwin, 2010;
Wilkinson & Marmott, 2003; Lasker & Weiss, 2003; Roussos & Fawcett, 2000; Weiss,
Anderson & Lasker, 2002).
22
References
Alma-Ata Conference. (1978). Declaration of Alma-Ata. International conference on primary
health care, Alma-Ata, USSR, 6-12 September 1978 Retrieved from
http://www.who.int/publications/almaata_declaration_en.pdf
American Lung Association. (2013). Disparities and the impact of air pollution. Retrieved from
http://www.stateoftheair.org/2013/health-risks/health-risks-disparities.html
American Psychological Association. (2014). Health disparities and stress. Retrieved from
https://www.apa.org/topics/health-disparities/stress.pdf
Ansell, C., & Gash, A. (2008). Collaborative Governance in Theory and Practice. Journal of
Public Administration Research and Theory, 18(4), 543–571. doi:10.1093/jopart/mum032
Association of State and Territorial Health Officials. (n.d.). The economic case for health equity.
Retrieved from http://www.astho.org/Programs/Health-Equity/Economic-Case-Issue-Brief/
Baron, S. L., Steege, A. L., Marsh, S. M., Chaumont Menéndez, C., & Myers, J. R. (2013).
Nonfatal work-related injuries and illnesses – United States, 2010. CDC health disparities and
inequities report – United States, 2013. MMWR, Supplement 62(3), 35-40. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Beckles, G. L. & Chou, C. (2013). Diabetes – United States, 2006 and 2010. CDC health
disparities and inequities report – United States, 2013. MMWR, Supplement 62(3), 99-104.
Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Boehmer, T. K., Foster, S. L., Henry, J. R., Woghiren. Akinnifesi, E. L. & Yip, F. Y. (2013).
Residential proximity to major highways – United States, 2010. CDC health disparities and
inequities report – United States, 2013. MMWR, Supplement 62(3), 46-50. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Braveman, P. & Gottlieb, L. (2014). The social determinants of health: it’s time to consider the causes of the causes. Public Health Reports. Supplement 2(129), 19-31.
Braveman, P. A., Cubbin, C., Egerter, S., Williams, D. R., & Pamuk, E. (2010). Socioeconomic
disparities in health in the United States: what the patterns tell us. American Journal of Public
Health, 100(Suppl 1), S186-S196. Doi. 10.2105/AJPH.2009.166082
Brown, D., White, J., & Leibbrandt, L. (2006). Collaborative partnerships for nursing faculties
and health service providers: what can nursing learn from business literature? Journal of Nursing
Management, 14(3), 170–179. doi:10.1111/j.1365-2934.2006.00598.x
Bryson, J. M., Crosby, B. C., & Stone, M. M. (2006). The Design and Implementation of CrossSector Collaborations: Propositions from the Literature. Public Administration Review, 66, 44–
55. doi:10.1111/j.1540-6210.2006.00665.x
23
Centers for Disease Control and Prevention. (2013). CDC health disparities and inequities report
– United States, 2013. MMWR, Supplement, 62(3). Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Centers for Medicare and Medicaid Services (n.d.). Table 1. National health expenditures;
aggregate and per capita amounts, annual percent change and percent distribution: selected
calendar years 1960-2012. Retrieved from http://www.cms.gov/Research-Statistics-Data-andSystems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/tables.pdf
Chrislip, D. D., & Larson, C. E. (1994). Collaborative leadership: How citizens and civic leaders
can make a difference. Jossey-Bass San Francisco. Retrieved from
http://www.getcited.org/pub/103177164
Commission on Social Determinants of Health. (2007). Geneva: World Health Organization
Commission on Social Determinants of Health. (2010). A conceptual framework for action on the social determinants of health. Geneva: World Health Organization.
Committee on Institutional Cooperation. (n.d.). CIC health disparities project proposal – “Straw model”. Minnesota Department of Health. Conn, B. M. & Marks, A. K. (2014). Ethnic/racial differences in peer and parent influence
onadolescent prescription drug misuse. Journal of Developmental & Behavioral
Pediatrics,35(4), 257-265. Doi: 10.1097/DBP.0000000000000058
Crosby, B. C., & Bryson, J. M. (2010). Integrative leadership and the creation and maintenance
of cross-sector collaborations. The Leadership Quarterly, 21(2), 211–230.
doi:10.1016/j.leaqua.2010.01.003
Crosby, A. E., Ortega, L. & Stevens, M. R. (2013). Suicides – United States, 2005 - 2009. CDC
health disparities and inequities report – United States, 2013. MMWR,Supplement 62(3), 179183. Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Emerson, K., Nabatchi, T., & Balogh, S. (2012). An Integrative Framework for Collaborative
Governance. Journal of Public Administration Research and Theory, 22(1), 1–29.
doi:10.1093/jopart/mur011
Evans, R. G., Barer, M. L. & Marmor, T. R. (1994). Why are some people healthy and others
not? Aldine De Gruyter, New York.
Forsberg, V. & Fichtenberg, C. (2012). The prevention and public health fund: A critical
investment in our nation’s physical and fiscal health. American Public Health Association.
Retrieved from http://www.apha.org/NR/rdonlyres/8FA13774-AA47-43F2-838B1B0757D111C6/0/APHA_PrevFundBrief_June2012.pdf
24
Frieden, T. R. (2013). Foreword. CDC health disparities and inequities report – United States,
2013. MMWR, Supplement, 62(3), 1-2x; retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Garrett, B. E., Dube, S. R., Winder, C. & Caraballo, R. S. (2013). Cigarette smoking – United
States, 2006 – 2008 and 2009 - 2010. CDC health disparities and inequities report – United
States, 2013. MMWR, Supplement 62(3), 80 - 84. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Gillespie, C. D. & Hurvitz, K. A. (2013). Prevalence of hypertension and controlled hypertension
– United States, 2007 - 2010. CDC health disparities and inequities report – United States, 2013.
MMWR, Supplement, 62(3), 144-148. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Gillespie, C. D., Wigington, C. & Hong, Y. (2013). Coronary heart disease and stroke – United
States, 2009. CDC health disparities and inequities report – United States, 2013. MMWR,
Supplement, 62(3), 157-160. Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Gray, A. M. (1982). Inequalities in health. The Black Report: a summary and comment.
International Journal of Health Services, 12(3), 349-380.
Grimm, K. A., Moore, L. V. & Scanlon, K. S. (2013). Access to healthier food retailers – United
States, 2011. CDC health disparities and inequities report – United States, 2013. MMWR,
Supplement, 62(3), 20-26. Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Health Policy Institute of Ohio. (2009). Policy brief. Unhealthy differences. Health disparities
between men and women in Ohio. Retrieved from
http://a5e8c023c8899218225edfa4b02e4d9734e01a28.gripelements.com/pdf/policybrief_disparitiesgende
r.pdf
Healthy People 2020. (n.d.). Framework. The vision, mission and goals of Healthy People 2020.
Retrieved from http://www.healthypeople.gov/2020/Consortium/HP2020Framework.pdf
Healthy People 2020. (2014). Social determinants of health. 2020 topics and objectives.
Retrieved from http://www.healthypeople.gov/2020/topicsobjectives2020/overview.aspx?topicid=39
HighScope. (n.d.). Long-term benefits. Head Start study finds long term impact. Retrieved from
http://www.highscope.org/Content.asp?ContentId=260
Hood, E. (2005). Dwelling disparities. How poor housing leads to poor health. Environmental
Health Perspectives, 113(5), A310-A317. Retrieved from
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1257572/
Israel, B. A., Schulz, A. J., Parker, E. A., & Becker, A. B. (1998). Review of Community Based
Research: Assessing Partnership Approaches to Improve Public Health. Annual Review of Public
Health, 19(1), 173–202. doi:10.1146/annurev.publhealth.19.1.173
25
Iton, A. (n.d.). Tackling the root causes of health disparities through community capacity
building. Chapter 7. Tackling health inequities through public health practice: A
handbook for action. Retrieved from http://chc.ucsf.edu/pdf/ItonTackling%20The%20Root%20Causes%20of%20Health%20Disparities.pdf
Johnson, A. S., Beer, L., Sionean, C., Hu, X., Furlow-Parmley, C., Le, B., … Dean, H. D. (2013). HIV infection -- United States, 2006 – 2008 and 2009 - 2010. CDC health
disparities and inequities report – United States, 2013. MMWR, Supplement 62(3), 112 119. Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Kanny, D., Lui, Y., Brewer, R. D. Lu, H (2013). Binge drinking -- United States, 2011. CDC
health disparities and inequities report – United States, 2013. MMWR, Supplement 62(3), 77-80.
Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Krehely, J. (2009). How to close the LGBT health disparities gap. Center for American Progress.
Retrieved from http://www.americanprogress.org/issues/2009/12/pdf/lgbt_health_disparities.pdf
Landsbergis, P. A., Grzywacz, J. G. & LaMontagne, A. D., (2011). Work organization, job
insecurity, and occupational health disparities. An issue paper for discussion at the
Eliminating Health and Safety Disparities at Work Conference, Chicago, Illinois.
Retrieved from
http://www.aoecdata.org/conferences/healthdisparities/whitepapers/workorganization.pdf
Lasker, R. D., & Weiss, E. S. (2003). Broadening participation in community problem solving: A
multidisciplinary model to support collaborative practice and research. Journal of Urban Health:
Bulletin of the New York Academy of Medicine, 80(1), 14–47. doi:10.1093/jurban/jtg014
Lasker, R. D., Weiss, E. S., & Miller, R. (2001). Partnership Synergy: A Practical Framework for
Studying and Strengthening the Collaborative Advantage. Milbank Quarterly, 79(2), 179–205.
doi:10.1111/1468-0009.00203
Logan, J. E., Hall, J., McDaniel, D. & Stevens, M. R. (2013). Homicides – United States, 2007
and 2009. CDC health disparities and inequities report – United States, 2013.
MMWR, Supplement 62(3), 164-170. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
MacDorman, M. F. & Mathews, T. J. (2013). Infant deaths -- United States, 2005 -- 2008. CDC
health disparities and inequities report – United States, 2013. MMWR, Supplement 62(3), 171175. Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Markowitz, L. E., Sternberg, M., Dunne, E. F., McQuillan, G., & Unger, E.R. (2009).
Seroprevalence of human papillomavirus types 6, 11, 16, and 18 in the United States:
National Health and Nutrition Examination Survey 2003–2004. Journal of Infectious
Diseases, 200(7), 1059-1067.
Marmot, M. G., Kogevinas, M. & Elston, M. A. (1987). Social/economic status and disease.
Annual Review of Public Health, 8, 111-135. DOI: 10.1146/annurev.pu.08.050187.000551
26
Marmot, M. G., Shipley, M. J., & Rose, G. (1984). Inequalities in death – specific explanations
of a general pattern? The Lancet, 8384, 1003-1006.
Marmot, M. G., Smith, G.D., Stansfeld, S., Patel, C., North, F., Head, J., … Feeney, A. (1991). Health inequalities among British civil servants: the Whitehall II study. The Lancet, 337(8754),
1387-1393.
Marsh, S. M., Chaumont Menéndez, C., Baron, S. L., Steege, A. L., & Myers, J. R. (2013). Fatal
work-related injuries – United States, 2005-2009. CDC health disparities and inequities report –
United States, 2013. MMWR,Supplement 62(3), 41-45. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Martin, J. A. & Osterman, M, J. K. (2013). Preterm births – United States, 2006 and 2010. CDC
health disparities and inequities report – United States, 2013. MMWR,Supplement 62(3), 136138. Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Mason, D.J., Leavitt, J.K., & Chafee, M.W. (2007). Policy & politics in nursing and health care.
Saunders Elsevier, St. Louis, MO., 5th edition.
Massachusetts General Hospital. (2006). Improving quality and achieving equity: a guide for
hospital leaders. Chapter 2: Why should you care? The business case: disparities, efficiency, and
the bottom line. Retrieved from http://www2.massgeneral.org/disparitiessolutions/guide2.b.html
Mathews, T. J. & MacDorman, M. F. (2013). Infant mortality statistics from the 2009 period
linked birth/infant death data set. National Vital Statistics Reports. 61(8). Retrieved from
http://www.cdc.gov/nchs/data/nvsr/nvsr61/nvsr61_08.pdf
May, A. L., Freedman, D., Sherry, B. & Blanck, H. M. (2013). Obesity -- United States, 1999 -2010. CDC health disparities and inequities report – United States, 2013.
MMWR,Supplement 62(3), 120-128. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
McKeown, T. (2001). , Determinants of Health. The Nation’s Health. Sixth Edition, Jones and
Bartlett Publishers, Boston, Massachusetts.
Meyer, P. A., Yoon, P. W. & Kaufmann, R. (2013). Introduction: CDC health disparities and
inequities report – United States, 2013. MMWR, Supplement, 62(3), 3-5; retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Michigan Department of Community Health. (2011). Michigan health equity tables and related
technical documents 2000-2009. Michigan health equity data project. Health Disparities
Reduction and Minority Section, Division of Health, Wellness, and Disease Control and Division
of Genomics, Perinatal Health, and Chronic Disease Epidemiology. Retrieved from:
http://michigan.gov/documents/mdch/MI_Health_Equity_Data_Tables_-_May_2011_361868_7.pdf
Minnesota Department of Health. (2014). Advancing health equity in Minnesota. Report to the
legislature. Commissioner’s Office. Retrieved from
27
http://www.health.state.mn.us/divs/chs/healthequity/ahe_leg_report_020414.pdf
Mitchell, S. M., & Shortell, S. M. (2000). The Governance and Management of Effective
Community Health Partnerships: A Typology for Research, Policy, and Practice. Milbank
Quarterly, 78(2), 241–289. doi:10.1111/1468-0009.00170
Molla, M. T. (2013). Expected years of life free of chronic condition – induced activity
limitations – United States, 1999-2008. MMWR, Supplement, 62(3), 87-92; retrieved
from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Moonesinghe, R., Chang, M. & Truman, B. I. (2013). Health insurance coverage – United States,
2008 and 2010. CDC health disparities and inequities report – United States, 2013. MMWR,
Supplement 62(3), 61-64. Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Moorman, J. E, Person, C. J. & Zahran, H. S. (2013). Asthma attacks among persons with
current asthma – United States, 2001-2010. MMWR, Supplement, 62(3), 93-98; retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
National Cancer Institute. (n.d.). Agricultural health study. National Cancer Institute Fact Sheet.
Retrieved from http://www.cancer.gov/cancertopics/factsheet/Risk/ahs
Nuru-Jeter, A., Dominguez, T. P., Hammond, W. P., Leu, J., Skaff, M., Egerter, S., …Braveman, P. (2009). ‘‘It’s the skin you’re in’’: African-American women talk about their experiences of
racism. An exploratory study to develop measures of racism for birth outcome studies. Maternal
and Child Health. 13, 29-39. DOI: 10.1007/s10955-008-0357-x.
Office on Women’s Health. (2013). State profiles. Health disparities profiles. Retrieved from http://www.healthstatus2020.com/disparities/ChartBookData_list.asp
Roussos, S. T., & Fawcett, S. B. (2000). A Review of Collaborative Partnerships as a Strategy
for Improving Community Health. Annual Review of Public Health, 21(1), 369–402.
doi:10.1146/annurev.publhealth.21.1.369
Schoen, C., Davis, K., How, S. Schoenbaum, S. (2006). U.S. health system performance: a
national scorecard. Health Affairs, web exclusive; w457 – w475.
Seith, D. & Isakson, E. (2011). Who are America’s poor children? Examining health disparities among children in the United States. National Center for Children in Poverty. Mailman School of
Public Health. Columbia University. Retrieved from
http://www.nccp.org/publications/pdf/text_995.pdf
Solar, O. & Irwin, A. (2007) A conceptual framework for action on the social determinants of
health. Social Determinants of Health Discussion Paper 1 (Policy and Practice).
Solar, O. & Irwin, A. (2010) A conceptual framework for action on the social determinants of
health. Social Determinants of Health Discussion Paper 2 (Policy and Practice). Stable url:
http://www.who.int/sdhconference/resources/ConceptualframeworkforactiononSDH_eng.pdf
28
Steele, C. B., Rim, S. H., Joseph, D. A., King, J. B. & Seeff, L. C. (2013). Colorectal cancer
incidence and screening – United States, 2008 and 2010. CDC health disparities and inequities
report – United States, 2013. MMWR,Supplement 62(3), 53-60. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Ståhl, T., Wismar, M., Ollila, E., Lahtinen, E., & Leppo, K. (2006). Health in all policies.
Prospects and potentials. Ministry of Social Affairs and Health, Finland, and European
Observatory on Health Systems and Policies. Retrieved from
http://ec.europa.eu/health/archive/ph_information/documents/health_in_all_policies.pdf
Tarlov, A. R. (1999). Public policy frameworks for improving population health. Annals New
York Academy of Sciences. 896, 281-293.
Travis, L., Hart, A., Hardin, S. R., & Hardwell, K. (2012). Academic-service partnerships: Seven
dimensions of successful collaboration. Journal of Nursing Education and Practice, 3(1), p1.
doi:10.5430/jnep.v3n1p1
The Commonwealth Fund. (2011). Why not the best? Results from a national scorecard on U.S.
health system performance. 2011. The Commonwealth Fund Commission on a High
Performance Health System. Retrieved from
http://www.commonwealthfund.org/~/media/files/publications/fundreport/2011/oct/1500_wntb_
natl_scorecard_2011_web_v2.pdf
Ventura, S. J., Hamilton, B. E. & Mathews, T. J. (2013). Pregnancy and childbirth among
females aged 10-19 years -- United States, 2007 - 2010. CDC health disparities and inequities
report – United States, 2013. MMWR,Supplement 62(3), 71-76. Retrieved from
http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Volkers, A. C., Westert, G. P. & Schellevis, G. (2007). Health disparities by occupation,
modified by education: a cross-sectional population study. BMC Public Health. 7, 196.
Watson M., Saraiya, M., Benard, V., Coughlin, S. S., Flowers, L., Cokkinides, V., Guiliano, A.
(2008). Burden of cervical cancer in the United States, 1998–2003. Cancer, 113(S10), 28552864. Doi: 10.1002/cncr.23756.
Weiss, E. S., Anderson, R. M., & Lasker, R. D. (2002). Making the Most of
Collaboration:Exploring the Relationship Between Partnership Synergy and Partnership
Functioning. Health Education & Behavior, 29(6), 683–698. doi:10.1177/109019802237938
Wilkinson, R. G., & Marmot, M. G. (2003). Social Determinants of Health: The Solid Facts.
World Health Organization.
World Health Organization. (2007). A conceptual framework for action on the social
determinants of health. Commission of Social Determinants of Health. Retrieved from
http://www.who.int/social_determinants/resources/csdh_framework_action_05_07.pdf
29
World Health Organization (1946). The Constitution of the World Health Organization.
Retrieved from http://whqlibdoc.who.int/hist/official_records/constitution.pdf
World Health Organization. (2014a). History of the World Health Organization. Retrieved from
http://www.who.int/about/history/en/
World Health Organization. (2014b). Health impact assessment (HIA). The determinants of
health. Retrieved from http://www.who.int/hia/evidence/doh/en/
World Health Organization. (2014c). Social determinants of health. Key concepts. Retrieved
from http://www.who.int/social_determinants/final_report/key_concepts_en.pdf?ua=1
Zack, M. M. (2013). Health-related quality of life -- United States, 2006 and 2010. CDC health
disparities and inequities report – United States, 2013. MMWR ,Supplement 62(3), 105- 111.
Retrieved from http://www.cdc.gov/mmwr/pdf/other/su6203.pdf
Zakocs, R. C., & Edwards, E. M. (2006). What Explains Community Coalition Effectiveness?: A
Review of the Literature. American Journal of Preventive Medicine, 30(4), 351–361.
doi:10.1016/j.amepre.2005.12.004
30
Appendix A. Examples of Health Disparities
Pregnancy and childbirth
Non-Hispanic blacks have more than double the infant mortality rate of non-Hispanic
whites (Frieden, 2013);
Infant mortality rates vary by geographic area, with higher rates in the south and Midwest
than other areas in the U.S. (Frieden, 2013);
Overall, in the U.S. from 2006 to 2009, infant mortality rates during the first year of life
were approximately 2.3 times higher among non-Hispanic blacks (13.1 per 1,000 live
births) than non-Hispanic whites (5.58 per 1,000) or Hispanics (5.5 per 1,000;
MacDorman & Mathews, 2013).
Several CIC states were among those with the highest infant mortality rates for nonHispanic blacks, including Indiana (15.36 per 1,000), Wisconsin (15.14 per 1,000), and
Ohio (15.03 per 1,000; MacDorman & Mathews, 2013).
Birth rates for 15 to 19 year old females during 2010 were highest among Hispanics (55.7
births per 1,000 females), followed by non-Hispanic blacks (51.5 per 1,000), American
Indian or Alaskan Natives (38.7 per 1,000), non-Hispanic whites (23.5 per 1,000), and
Asian or Pacific Islanders (10.0 per 1,000; Ventura, Hamilton,& Mathews, 2013).
Preterm births in the U.S. during 2010 were highest among Black, non-Hispanic women
(17.1%) followed by American Indian and Alaskan Native women (13.6%); rates were
lowest among Asian or Pacific Islanders (10.7%) and non-Hispanic whites (10.8%;
Martin & Osterman, 2013).
Life expectancy and health life expectancy
In 2008, total life expectancy for U.S. blacks (74.0 years) was less than for whites (78.5
years; Molla, 2013);
In 2008, the years of life free of activity limitation (YFAL) was lower for U.S. blacks
(61.1 years) compared with whites (67.0 years; Molla, 2013).
Health status or quality of life
During 2010, the proportion of U.S. adults who rated their health as poor or fair in the
Behavioral Risk Factor Surveillance System telephone survey varied by age group, race
or ethnicity, educational attainment, primary language spoken at home and disability
status (Zack, 2013).
American Indians and Alaskan Natives had the highest age-adjusted percentage of
persons who rated their health as poor or fair (30.8%), followed by Hispanics (28.1%),
Black, non-Hispanics (23.3%), white, non-Hispanics (13.3%), and Asians or Pacific
Islanders (11.9%; Zack, 2013).
Adults with less than a high school education were more likely to report poor or fair
health status (38.4%) than college graduates (7.3%; Zack, 2013).
Persons who spoke Spanish or another language at home were more likely to report poor
or fair health status (37.6% and 40.7% respectively) than persons who spoke English
(15.0%) during 2010 (Zack, 2013).
31
Heart disease, heart attack or stroke, and hypertension
Non-Hispanic blacks are approximately 50% more likely to die from a heart attack or
stroke before 75 years of age than non-Hispanic whites (Frieden, 2013).
Age-adjusted mortality rates for persons with coronary heart disease were highest among
black, non-Hispanics (141.3 per 100,000), compared with Asian/Pacific Islanders (67.3
per 100,000), Hispanics (86.5 per 100,000), and non-Hispanic whites (117.7 per 100,000;
Gillespie, Wigington & Hong, 2013) during 2009.
Among U.S. adults, aged 18 years and older during 2007 to 2010, hypertension rates
were highest among Black, non-Hispanics (41.3%), with little variation between Mexican
Americans (27.5%), Hispanics (27.7%), and non- Hispanic whites (28.6%; Gillespie &
Hurvitz 2013).
Diabetes
Adult Hispanics, non-Hispanic blacks, and persons with other or mixed races have a
higher prevalence of diabetes than non-Hispanic whites and Asians (Frieden, 2013);
Prevalence of diabetes among adults is higher for those without college degrees
compared to those with college degrees and for perhaps with lower household incomes
(Frieden, 2013);
During 2010, the age standardized incidence of medically diagnosed diabetes among U.S.
adults ages 18 to 79 years was highest among Hispanics (12.2 per 1,000 population),
followed by black non-Hispanics (9.2 per 1,000), and lowest among white non-Hispanics
(6.0 per 1,000; Beckles & Chou, 2013).
Diabetes incidence was highest among U.S. persons with less than a high school
education (13.7 per 1,000) and lowest among those with a college degree or higher (4.3
per 1,000; Beckles & Chou, 2013).
In the U.S during 2010, the poor, defined as persons with an income less than the FPL,
were found to have a higher incidence of diabetes (11.5 per 1,000) than those with a high
income (6.2 per 1,000), defined as an income at least four times the FPL (Beckles &
Chou, 2013).
Cancer
In 2008, men had higher colorectal cancer (CRC) incidence (51.6 per 100,000
population) than women (38.7 per 100,000 population); deaths rates from CRC were also
higher among men (19.7 per 100,000) than women (13.8 per 100,000) that same year;
non-Hispanic blacks had higher death rates from CRC (23.5 per 100,000) than white nonHispanics (16.1 per 100,000), Asian or Pacific islanders (15.9 per 100,000) and American
Indian or Alaskan Natives (11.5 per 100,000; Steele, Rim, Joseph, King & Seeff, 2013);
In 2010, the percentage of respondents, aged 50 to 75 years who reported being up-todate with CRC screening was lower among persons who: are Hispanic (51.0%) when
compared with non-Hispanics (65.7%); have less than a high school education (34.6%)
when compared with persons with a college degree (68.3%); have an annual income less
than $15,000 (42.3%) when compared with those having an income of at least $75,000
(69.9%); and did not have health insurance (31.6%) when compared with those who had
health insurance (63.3%; Steele, Rim, Joseph, King & Seeff, 2013).
Black women have an increased incidence of cervical cancer (12.6 per 100,000)
compared with whites (8.4 per 100,000, p<0.05) and increased mortality (5.2 vs. 2.6 per
32
100,000), with the highest incidence and mortality rates in the South (Watson et al.,
2008).
In the Agricultural Health Study, conducted in Iowa and North Carolina, agricultural
workers had higher rates of leukemia, non-Hodgkin lymphoma, multiple myeloma, soft
tissue sarcoma, and cancers of the skin, lip, stomach, brain, and prostate (National Cancer
Institute, n.d.).
Asthma
During 2006 to 2010, the frequency of asthma attacks was not significantly different for
U.S. children based on family income levels; however, among U.S. adults asthma attacks
were somewhat higher among those with incomes less than 100% of the federal poverty
level (FPL; 53.9%) than those with incomes at least 450% FPL (48.9%; Moorman,
Person & Zahran, 2013).
Sexually-transmitted infections
Rates of human immunodeficiency virus (HIV) infection were approximately twenty
times higher among black women (51.8 per 100,000 population), ages 18 and older in
2010, than white women (2.6 per 100,000; Johnson et al., 2013).
High-risk occupations, work-related injuries and illnesses
In 2010, almost 17 million U.S. workers were employed in high-risk occupations in the
private sector. Males (21.1%) were more likely to be employed in high-risk occupations
than females (8.9%). Hispanics (24.4%), Black non-Hispanics (20.8%), and American
Indians or Alaskan Natives (20.2%) were more likely to be employed in high-risk
occupations than Asians (9.2%) and non-Hispanic whites (13.0%). Foreign-born workers
(22.1%) were more likely to be employed in high-risk occupations than persons born in
the U.S. (13.9%). And, persons with no more than a high school education (25.6%) were
more likely to be employed in high-risk occupations than those persons with an education
beyond high school (8.6%; Baron, Steege, Marsh, Chaumont Menéndez & Meyers,
2013).
During 2011, approximately 4,700 workers died from occupational injuries in the U.S.;
the rate of injury-related deaths at work during 2005 to 2009 was 3.7 per 100,000
workers; the highest rates were among Hispanics (4.4 per 100,000) and foreign-born
workers (4.0 per 100,000; (Marsh, Chaumon Menéndez, Baron, Steege & Myers, 2013).
Obesity, nutrition, & access to healthier food
In 2011, approximately 83.6 million people in the U.S. lived in a census tract that did not
have at least one food retailer that was classified as “healthier”. The relationships between access to healthier food retailers and demographic characteristics was not
consistent in all geographic areas; yet, access to healthier food retailers was four times
higher for persons in urban areas than in rural areas (Grimm, Moore & Scanlon, 2013);
From 2007 to 2010, the prevalence of obesity among females 18 years and older was
highest among Black, non-Hispanics (53%), followed by Mexican-Americans (44%), and
lowest among white non-Hispanics (32%; May, Freedman, Sherry & Blanck, 2013);
33
Among children and adolescents aged 2 to 17 years, obesity rates for males were highest
among Mexican- Americans (25%) and lowest among white, non-Hispanics (16%) from
2007 to 2010; for females, Black, non- Hispanics had the highest obesity rates (23%),
followed by Mexican-Americans (18%) and non-Hispanic whites (13%; May et al.,
2013).
Alcohol and other drug abuse
Based on more than 18,000 responses to the 2010 National Survey of Drug Use and
Health by 12 to 17 year olds, white adolescents were found to misuse stimulants (2.4%)
more frequently than African Americans (1.3%) or Hispanics (2.6%); white adolescents
also were more likely to misuse tranquilizers (3.4%) than African Americans (0.9%) and
Hispanics (2.9%; Conn & Marks, 2014);
In 2011, self-reported binge drinking was lower for persons who did not graduate from
high school (16.8%) when compared with high school graduates (18.7%), and persons
with some college (20.1%) or college graduates (20.4%). However, the highest frequency
(4.7 episodes) and average intensity (7.4 drinks) in the past 30 days was highest among
persons who have not completed high school and report binge drinking (Kanny, Liu,
Brewer & Lu, 2013).
Tobacco use
Rates of cigarette smoking in the U.S. vary by educational level and socioeconomic
status as measured by percent of the FPL; during 2009 to 2010, youth who were of 12th
grade age yet had dropped out of high school had a 46.4% prevalence of smoking,
compared with 21.9% among 12th graders who were still in school; smoking prevalence
was 34.6% among adults who did not graduate from high school, compared with 13.2%
among persons with a college degree (13.2%; Garrett, Dube, Winder & Caraballo, 2013)
Exposure to environmental pollutants
An estimated 11.3 million persons in the U.S. live in close proximity to a major highway;
this measure was used as a proxy for exposure to traffic-related air pollution; Hispanics
(5.0%) and Asians or Pacific Islanders (5.4%) were more likely to live within 150 meters
of a major highway than American Indians or Alaskan Natives (2.6%) and non-Hispanic
whites (3.1%); relatively high rates of living within 150 meters of a major highway were
also observed for foreign-born persons (5.1%), persons who speak Spanish at home
(5.1%), and those who speak another non-English language at home (4.9%; Boehmer,
Foster, Henry, Woghiren-Akinnifesi & Yip, 2013).
Poor children are more likely to be exposed to environmental toxins than non-poor
children. Mothers of poor children were more likely to have smoked during pregnancy
(24.3%) than mothers of non-poor children (15.4%). Children ages 0 to 17 years were
more likely to live with someone who smokes in the home (31.5%) than nonpoorchildren (12.3%) during 2007—2008 (Seith & Isakson, 2011).
Vaccinations and Vaccination-preventable illnesses
In one recent U.S. study, an estimated 12.2% of males tested positive for at least one of
the four human papillomavirus (HPV) strains in the quadrivalent HPV (HPV4) vaccine;
34
black males (18.7%) were significantly more likely to test positive than white males
(11.8%, p=0.05; Markowitz, Sternberg, Dunne, McQuillan, & Unger, 2009).
Intentional and nonintentional injuries or deaths
Suicide rates are approximately 4 times higher among men than women (Frieden, 2013).
For example, among non-Hispanic whites, the suicide rate for men during 2009 was 24.4
per 100,000 population compared with 6.4 per 100,000 females (Crosby, Ortega &
Stevens, 2013). Similar male-female disparities and rates were observed among
American Indians and Alaskan Natives (23.2 versus 8.2). Rates among non-Hispanic
blacks and Hispanics were much lower, with male-female disparities remaining. Black,
non-Hispanic males had suicide rates of 8.9 per 100,000 during 2009 compared with 1.9
for females. Rates among Hispanics were lowest with 8.5 for males and 1.9 for females
(Crosby, Ortega & Stevens, 2013).
During 2009, homicide rates among Black, non-Hispanics (19.9 per 100,000 population)
were approximately 9 times higher than among Asian/Pacific Islanders (2.2 per 100,000)
and almost 8 times higher than among white,non-Hispanics (2.6 per 100,000; Logan,
Hall, McDaniel & Stevens, 2013).
Health Insurance Coverage
During 2011, approximately 25% of adults aged 19 to 64 years did not have health
insurance at some point that year; during 2010, Hispanics were most likely to be
uninsured (41.0%), followed by American Indian or Alaskan Natives (33.5%) and black,
non-Hispanics (26.2%); in contrast, 16.1% of white, non-Hispanics and 17.3% of Asian
or Pacific Islanders lacked health insurance during 2010 (Moonesinghe, R., Chang, M, &
Truman, B. I., 2013).
35
Appendix B. Three Elements of the Commission on Social
Determinants of Health Framework
Element 1. Socio-economic and Political Context—Examples of Health Disparities
Sub-e
Sub-Element
Examples(s) of Evidence
Governance or governance
patterns, including civil
society participation,
accountability and
transparency
Macroeconomic policies
Social policies: labor, social
welfare, land and housing
distribution
Public policy in other areas,
such as education, health and
medical care, water and
sanitation; social protection
policies
Income segregation, the practice of housing the poor in discrete areas of a city,
has been linked with obesity and adverse mental health outcomes (Hood 2005).
Lack of sidewalks, bike paths, and recreational areas in some communities
discourages physical activity and contributes to obesity (Hood 2005).
Culture and societal values
Epidemiologic conditions
Element 2. Structural Determinants and Socioeconomic Position—Examples of Health
Disparities
Sub-element Example(s) of Evidence
Sub-element
Example(s) of Evidence
Structural determinants:
“components of people’s socioeconomic position”
Socioeconomic position:
position in the social
stratification system;
36
Sub-element
Income
Education
Occupation
Example(s) of Evidence
Using U.S. data from 1988—2007, respondent-assessed health status was
lower, on average, for persons 0 to 17 years whose family income was less than
100% of the federal poverty level (FPL) when compared with persons whose
family income is at least 400% the FPL; this trend showed incremental
increases in health status as income increased (Braveman, Cubbin, Egerter,
Williams & Pamuk, 2010);
Sedentary behavior among 12 to 19 year olds in the U.S., as measured by the
percentage of persons who did not engage in moderate or vigorous leisure-time
physical activity for at least 10 minutes in the past 30 days, was highest among
youth with family incomes less than 100% FPL (18.3%); this rate dropped to
6.3% for youth in households with family incomes at or above 400% FPL
(Braveman et al., 2010);
The prevalence of diabetes among U.S. persons age 20 to 64 years with family
incomes less than 100% FPL is higher among blacks (17.0%) and Mexican
Americans (15.3%) than among whites (8.8%); the rates of diabetes for all
races combined is more than double for people in families less than 100% FPL
(11.3%) than for those with family incomes of at least 400% FPL (4.5%;
Braveman et al., 2010);
The percent of the U.S. population with family income less than 100% of the
FPL is higher among blacks (24.5%) and Hispanics (21.5%) than among whites
(8.2%; Braveman et al., 2010);
In Michigan, African American children were 3.3 times more likely to be
living in households below poverty (41.7%) than whites (12.6%; Michigan
Department of Community Health, 2011).
Using U.S. data from 1988—2007, respondent-assessed health status was
lower, on average, for persons who did not graduate from high school than
persons with higher educational levels; 32.1% of persons who had not
graduated from high school reported not having an excellent or very good
health status compared with 8.1% of college graduates; this trend showed
incremental increases in self-perceived health status as educational levels
increased (Braveman, Cubbin, Egerter, Williams & Pamuk, 2010);
Between 1988 and 2007, infant mortality for U.S. mothers who were at least 20
years of age was almost twice as high for those who did not graduate from high
school (7.8%) compared to mothers who graduated from college (4.2%;
Braveman, 2010);
The percent of U.S. persons who had not graduated from high school was
higher among Hispanics (40.1%) and blacks (20.7%) than among whites
(11.1%); the rate of college graduation was lower among Hispanics (12.3%)
and blacks (16.8%) than among whites (30.0%; Braveman et al., 2010);
Between 1988 and 2007, U.S. persons 20 to 64 years of age who have not
completed high school have higher rates of diabetes (10.1%) than those who
have graduated from college (4.1%; Braveman, 2010);
In a Dutch study of > 385,000 persons, the risk of poor health decreased in
higher occupational positions. The lowest occupational position was adversely
associated with poor health among men (OR = 1.6) and women (OR = 1.3).
Higher levels of depression, diabetes, heart disease, arthritis, muscle pain, neck
and back pain and tension headache were reported among persons in the lower
occupational groups when compared with people with the highest occupational
positions (OR 1.2 to 1.6). Lower educational levels for persons in the lower
positions increased the risk (Volkers, Westert & Schellevis, 2007).
37
Sub-element
Social Class: defined by
relations of ownership or
control over productive
resources (i.e. physical,
financial, and
organizational)
Gender: characteristics of
women and men which are
socially constructed;
masculine or feminine
Race/Ethnicity
Example(s) of Evidence
Features of work organization and feelings of job insecurities can create work
hazards that increase the risk of occupational illnesses, injuries and poorer
health status. Differential job insecurity, with persons in lower socioeconomic
levels and women experiencing higher levels of job insecurity, puts them at
higher risk of health problems (Landsbergis, Grzywacz & LaMontagne,
2011).
Women were more likely to live at or below 200% of FPL than men (Health
Policy Institute of Ohio, 2009).
Higher levels of self-reported excellent or very good health have been
reported among heterosexual adults (83%) than those who are lesbian, gay or
bisexual (LGB, 77%), or transgender (67%; Krehely, 2009).
Overall, in the U.S. from 2006 to 2009, infant mortality rates during the first
year of life were approximately 2.3 times higher among non-Hispanic blacks
(13.1 per 1,000 live births) than non-Hispanic whites (5.58 per 1,000) or
Hispanics (5.5 per 1,000; MacDorman & Mathews, 2013).
In Michigan, the infant mortality rate among blacks was 2.7 times higher
(15.3 per 1,000 live births) than whites (5.6) during 2007 to 2009; the rate was
1.8 times higher for American Indians and Alaskan Natives (9.9 per 1,000)
and 1.7 times higher for Hispanics/Latinos (9.7 per 1,000) than whites
(Michigan Department of Community Health, 2011)
In Michigan, during 2007 to 2009, the percent of American Indians and
Alaskan Natives who reported poor or fair health (31.1%) was 2.5 times
higher than for whites (12.5%; Michigan Department of Community Health,
2011).
In Michigan, during 2007 to 2009, the incidence of gonorrhea was 27.3 times
higher among blacks (545.0 per 100,000 population) than whites (20.0 per
100,000); the incidence was 3.3 times higher (66.0 per 100,000) among
American Indians and Alaskan Natives and 2.5 times higher among Hispanics
or Latinos (49.0 per 100,000) than among whites (Michigan Department. of
Community Health, 2011);
The HIV infection rate among blacks in Michigan from 2007 to 2009 was 9.3
times higher (574 per 100,000) than among whites (62.0 per 100,000;
Michigan Dept. of Community Health, 2011); the rate among
Hispanics/Latinos was 2.2 times higher (139.0 per 100,000) than among
whites.
Element 3. Intermediary Determinants—Examples of Health Disparities
Sub-element Example(s) of Evidence
Sub-element
Example(s) of Evidence
Material circumstances:
“linked to the physical
environment, such as
housing, consumption
potential, physical working
and neighborhood
environments;
Housing: structure of
dwelling; internal
conditions, such as
temperature, moisture, and
contaminants; crowding;
A higher percentage of people of color live within 150 meters of a highway.
Among non-Hispanic whites, 3.1% lived near a highway compared to 5.4% of
Asian/Pacific Islanders and 4.5% of African Americans (Boehmer et al.,
2013)
Census tracts in the United States with at least 36% of people being of race
and ethnicity other than non-Hispanic whites were about half as likely than
census tracts with a higher proportion of non-Hispanics whites to not have
access to a healthier food retailer (Grimm, Moore & Scanlon, 2013).
Dilapidated housing is associated with exposures to lead, asthma triggers
(such as mold, moisture, dust mites, and rodents) and mental health stressors
such as violence and social isolation (Hood 2005).
38
Sub-element
Example(s) of Evidence
Psychosocial
circumstances or socialenvironmental:
psychosocial stressors,
stressful living conditions,
social support, coping
styles
Perceptions of discrimination, based on race/ethnicity, sex, sexual-orientation,
or other factors, has been linked with chronic stress-related health disparities
(American Psychological Association, 2014).
American women have expressed, in focus groups, feeling of experiencing
racism throughout life; the responses to racism was manifested in behaviors,
emotions, and somatically; these feelings of racism and the associated stress
among child-bearing women are suspected of contributing to adverse birth
outcomes (Nuru-Jeter et al., 2009).
Not a direct focus of this paper; social determinants of health often influence health
behaviors
Behavioral and/or
biological factors:
smoking, diet, alcohol
consumption, lack of
physical activity
Health system as a social
determinant of health:
Example: access
Not a focus of this paper
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