.ntal Protection Agency
lice of Research and Development, Gulf Ecology Division
".2561
Report # EPA/600/R-12/02J
March 2012
H
licators and Methods for Constructing a U.S.
Human Well-being Index (HWBI) for Ecosystem
Services Research
United States
Environmental Protection Agency
if fi»
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Photo credits for the cover
Clouds in the sky - Microsoft.com
Family holding hands on beach —M icrosoft.com
Boardwalk —U.S. Fish and Wildlife Service (U.S. FWS)
Rainbow —M icrosoft.com
Kayaker - U.S. EPA
Great Blue Heron - U.S. FWS
Cypress swamp- Heather Smith
Inside Cover
U.S. EPA
Additional photo credit information
Background pictures for well-being domain pages(*and on page 13)
Social Cohesion (holding hands) —M icrosoft.com
Education (apple) —M icrosoft.com
Connection to Nature (boy and butterfly) —U.S. FWS
Health (leapfrog couple) —M icrosoft.com
Living Standards (dollar bills) —Veer Images (Microsoft partner)
Leisure Time (sundial) —M icrosoft.com
Safety and Security (vault) —Photos.com (Microsoft partner)
Cultural Fulfillment (boats) —M icrosoft.com
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Acknowledgements
This Indicators and Methods for Constructing a U.S. Human Well-being Index (HWBI)for Ecosystem Services
Research Report was prepared by the U.S. Environmental Protection Agency (EPA), Office of Research and
Development (ORD), National Health and Environmental Effects Research Laboratory (NHEERL), Gulf Ecology
Division (GED). The following task members provided written materials and technical information throughout
the preparation of the document.
Lisa M. Smith, Office of Research and Development
Heather M. Smith, Student Services Contractor
Jason L. Case, Student Services Contractor
Linda C. Harwell, Office of Research and Development
J. Kevin Summers, Office of Research and Development
Christina Wade, Student Services Contractor
Disclaimer:
This document has been reviewed in accordance with U.S. Environmental Protection Agency policy and ap-
proved for publication.
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ontents
Courtesy of Chuck Felix; freedigitalphotos.net
Acknowledgements i
Abstract iv
Introduction l
Data Sources and Quality Assurance 5
Well-being Domains and Indicators 6
Connection to Nature 7
Biophilia 9
Cultural Fulfillment 10
Activity Participation 12
Education 13
Social, Emotional and Developmental Aspects 15
Basic Knowledge and Skills of the Youth 17
Participation and Attainment 18
Health 21
Personal Well-being 23
Life Expectancy and Mortality 24
Physical and Mental Health Conditions 28
Lifestyle and Behavior 32
Healthcare 34
Leisure Time 36
Time Spent 38
Activity Participation 38
Working Age Adults 39
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Living Standards 41
Wealth 43
Income 44
Work 45
Basic Necessities 46
Safety and Security 48
Actual Safety 50
Risk 52
Perceived Safety 52
Social Cohesion 53
Social Engagement 55
Attitude Towards Others and the Community 56
Family Bonding 59
Democratic Engagement 60
Social Support 63
Summary Table of Data and Available Spatial Scales 64
Constructing the Composite Index of Well-being 66
Current Status and Next Steps 69
References 70
Appendices 75
A Descriptive statistics and histograms used to establish metric distributions 76
B Contribution weights for domains and elements of well-being 100
C Graphical summary of indicator development and index construction methodologies 102
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\
Abstract
Humans are dependent upon the services provided by nature, and unless we effectively account for the
range of values from ecosystems in our efforts to protect the environment, we cannot sustain human
well-being. In light of this dependence, a national measure of well-being is needed which is responsive to
changes in the provisioning of ecosystem services as well as service flows from economic and social
sectors. To conceptualize the eco-human linkages we must identify the measurable components of well-
being that can be related to ecosystem service provisioning. The indicators and metrics used in existing
well-being indices provide a basis for developing a core set of domains to develop such a composite
measure of well-being; however these indices lack the ability to link well-being endpoints specifically to
service flows from different types of capital. This report suggests a core set of well-being domains that
can be linked to ecosystem services via their relationship to economic, environmental and societal well-
being. The development of indicators and metrics used as domain measures are described and the
methodologies for constructing a composite human well-being index (HWBI) are detailed. The HWBI is
intended to be used as a sustainability indicator for evaluating the provisioning of ecosystem, economic
and social services in a predictive modeling framework, allowing decision makers to use alternate
scenarios to assess potential impact on communities.
"Ecosystem services incorporate the language of economics and business,
through their valuation, and the language of development, through their
support for human well-being. Efforts tosupportthe long-term sustainable
supply of those services are as important to human well-being and survival as
they are for nature itself."
Mainka Susan A., Jeffrey A. McNeely and William J. Jackson. 2008 Depending on Nature:
Ecosystem Services for Human Livelihoods. Environment: Science and Policy for Sustainable
Development. 50(2):42-55.
Courtesy of Roxanne Lavelle
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Introduction
One of the primary goals of the United States Environmental Protection Agency's (USEPA) Sustainable and
Healthy Communities Research Program (SHCRP) is to assess, valuate, and provide comparisons of changes in
ecosystem services resulting from local, regional, and national decision making. Valuation is generally thought
of as a conversion of ecological services to their extrinsic value to humans in economic terms. However, many
of the services provided by healthy, resilient ecosystems have intrinsic value (e.g., traditions and customs,
belief systems, values and attitudes, security, disability recovery, happiness) that are difficult to valuate in
traditional ways (Boyd 2008).
The conceptual relationship between the quality of the environment and its services to human well-being is
well established and generally accepted and may have profound implications for policy-making and
sustainability (Daily et al. 2009). While accepted, the determination of the quantitative "value" of the intrinsic
and extrinsic services of ecosystems is more elusive and requires broader thinking than more straightforward
economic approaches. To better understand the contribution of ecosystem services to overall human well-
being we must first describe human well-being and delineate a core set of indicators that represent the state
of society across time, culture and scale. Additionally, the relationship of ecosystem services to these aspects
of well-being must be evaluated in context of service flows from human, built and social capitals (categorized
as economic and social services) (Figure 1).
Industry
(human and built capital)
economic value
is created for society
Society
(human and social capital)
ecological goods
and sen/ices are
utilized in industry
some waste
is recovered
and recycled
labor is utilized in
industry
waste and emissions
mostly return to the
environment
ecological goods
and services are utilized
in society
Most frequently, well-being indices are
designed to address specific policy
objectives and are driven by economic
and social measures. While some
composite indices of well-being
include measures of environmental
quality, ecosystem condition or health
outcomes related to environmental
exposures, the concept of ecosystem
services and the potential impact of
loss of services has not been
addressed for environmental
accountability and decision making.
What is evident from our extensive
literature review of human well-being
research, however, is that holistic
measures of well-being should be
inclusive of the elements of societal
well-being as described in terms of
subjective well-being and meeting
basic human needs, economic well-
being, and environmental well-being (Summers et al. in press). Therefore the objective of human well-being
research within SHCRP is to develop a national human well-being index (HWBI) for the United States that
describes well-being by integrating endpoint measures of these elements and to ultimately show how
changes in service flows from different capitals (economic, social and ecosystem services provisioning) are
reflected in this composite index.
Environment (natural capital)
Figure 1. Capital Flows in a Sustainable Society; adapted from J.
Fiksel, A Framework for Sustainable Materials Management, Journal
of Materials, August 2006
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Describing Well-being
Our approach to linking the provisioning of ecosystem services to human well-being is anchored in the develop-
ment of an index of well-being for the United States based on indicators and metrics derived from existing
measures of well-being. Groups of indicators described by suites of metrics are commonly aggregated to evalu-
ate components of well-being (domains). The domains we have identified for developing a United States index
of well-being are influenced by service flows from different capitals. More specifically, the domains of well-being
described in this document were adapted from the framework for the Canadian Index of Well-being (CIW)
released in April 2011 and closely resemble domains described in the Organisation for Economic Co-operation
and Development (OECD) Better Life Index (http://www.oecdbetterlifeindex.org/). Note that not all indicators
represented in the domains of the CIW and OECD were used, and in some cases we chose additional indicators,
as appropriate for a well-being index for the United States. The proposed index of well-being for the United
States represents the following eight domains of human well-being:
• Social cohesion
• Education
• Connection to nature
• Health
• Living standards
• Leisure time
& m *A
Well-bein Huirian
ill-being
...,,. , Domains Well-being
Cultural fulfillment ^^^^
,\
Photos Courtesy of U.S. EPA (Ecosystem Services), photostock (Well-being Domains), and Microsoft.com (Human Well-being)
The metrics chosen here for index development reflect measures of the human condition as opposed to the
quality and quantity of goods and services supporting society. The metrics describing service flows will be used
to model well-being as an endpoint measure in a predictive modeling framework. Therefore, the HWBI de-
scribed in this document is an "ends" measure separated from the "means". By doing so, we can ultimately de-
velop alternate scenarios for decision support tools for managers and policy makers. Information quantifying the
delivery of social and economic services, and ongoing research within SHCRP seeking to measure ecosystem
functions and quantify goods and services provisioning will provide information for model input (Figure 2). Mod-
eling efforts will involve Relative Importance Values (RIVs) like those described in the section titled "Constructing
the Composite Index of Well-being" on page 67 of this report. RIVs will also be used to link each service
(ecosystem, social and economic) to each well-being domain by establishing their subjective importance. A con-
ceptualized modeling framework highlighting ecosystem goods and services is presented in Figure 3 which de-
lineates the components of the composite index of well-being.
This report provides a short description for each well-being domain chosen for the construction of the HWBI,
how each relates to economic and social drivers, and emphasizes the relationships to ecosystem goods and
services. The domain descriptions are followed by the domain indicators and their corresponding metrics. A
summary of metric data is provided, and metric selection criteria and quality assurance are briefly described.
Finally, the methods used to construct the composite HWBI are described on pages 66-68 and are illustrated in
Appendix C.
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Ecosystem Functions and Processes
Ecosystem Goods and Services
Water Quality Regulation
Nutrient fixed into biomass
Denitrification rates
Advective nutrient removal rates
Dilution rates
Nutrient burial rates
Contaminant burial and removal rates
Freshwater inflow rates
Heat flux rates
Sediment loading rates
Light attenuation rates
Pathogen removal
Surface/groundwater ratios
Net production of dissolved oxygen
Availability of Habitat/Refugia
Area of habitat
Habitat complexity
Temperature
Dissolved oxygen concentrations
Salinity
Depth
Light availability
Soil/sediment characteristics
Contaminant concentrations
Habitat connectivity
Animal and plant abundances
Sediment loading rates
Erosion rates
Water Quantity Regulation
Precipitation rates
Aquifer recharge rates
Surface water reservoir capacity
Salt water infiltration rates
Atmospheric Regulation
CO2 fixed into biomass
Carbon content of biomass
Carbon burial rates
Soil and sediment carbon content
Ozone, CO, NO2 and SO2 removal rates
Particulate removal rates
Temperature
CH4 emissions
Food and Fiber Provisioning
Row crop production
Timber production
Livestock production
Fishery production
Fuel production
Natural Hazard Protection
Water retention capacity of soils
Wetland floodwater receiving capacity
Storm surge attenuation rates
Biodiversity Regulation
Number of species per functional role
Plant and animal diversity indices
Number of charismatic species
Fragmentation statistics
Green Space
Area of recreational space
Travel distance to "natural" areas
Diversity of recreational opportunities
Aesthetic quality
Usable Water
Drinkable, swimmable, and fishable water
Temperature moderation
Salinity moderation
Water clarity maintenance
DO moderation
Habitat/Refugia
Productive terrestrial and
aquatic environments
Maintenance of habitat structure
Habitat characteristics maintained in viable range
Available Water
Fresh water supply
Usable Air
Clean Air
Air pollutants removed
Temperature moderation
Stable Climate
Greenhouse gas reduction
Food, Fiber, and Energy
Flood Protection
Flood and storm surge buffer
Retention/removal of precipitation
Attenuation of peak flows
Attenuation of storm surge
Biodiversity
Functional Stability
Functional redundancy maintained
Indirect existent uses maintained
Habitat heterogeneity supported
Recreation and Aesthetics
Recreational opportunities
Direct use activities
Access to natural areas
Figure 2. Final ecosystem goods and services flowing from ecosystem functions and
processes (identified by EPA ecologists).
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Quality and Quantity
of Capital
( Social ) ( Natural ) ( Human)
( Built )
Demand
Influences the flow of — ( Good Governance J
Goods and Services
Economic
Capital investment
Capital mamienance
Consumption
Empioym&ni
Finance
Income
Innovation
Production
Re-di slri button
Social
Acth/Him
Communication
Community and failn-based initiatives
Education service's
Emergency preparedness
Family services
Financial assistance
Health care
Justice
Labor
Public healh
Public works
Ecosystem
Usable Air
Clean air
Air pollutants removed
Temperature m&dera&on
1
Flood Protection
Flood buffer
Storm surge buffer
Retention/removal of precipitation
Attenuation of peak flows
Attenuation of storm surge
B Eod rvtrslty
Functional stability
Functions! redundancy ma ntainad
Indirect existent uses maintained
Habitat heterogeneity supported
Stable Climate
Greenhouse gas reduction
Aval la bit Water
Fresh water supply
Food, Fiber
and Fuel Supply
Food
Fiber
Energy
Usable Water
Drinkable, swimable and
fi&hable water
Temperature moderation
Salinity moderation
Water clarity maintenance
Recreation ancf Aesthetics
Recreational opportunities
Direct use activities
Access to natural areas
Habitat/Refugta
Productive terrestrial and
aquatic environments
Maintenance of habitat structure
Habitat characteristics maintained in
vnable range
t
Freedom of Choice
and Opportunity
— — influences
1_
Domains of Well-Bemg
f:
Social Cohesion
Bonds that tie peopte together in soctety
(connectedness, identity, participation, trust and obligation,
volunteering and city satisfaction
Education
Outcomes derived from formal and informal transfer of knowledge
and skills (attainment tests results, participation.
local knowledge and tra ning)
Connection to Nature
The Innate emotional affiliation of humans to other
living organisms (Respect and appreciation for nature)
Health
Personal well-being, physical and psycholog
(behavior, perceived health, life satisfaction
Well-Being Elements
Environmental Weil-Being
Desire for clean, health/
and stable natural environments
tcai human health
and happiness)
used tc
Living Standards
Wealth, nccme levels, housing and food security
(household and community debt median home value.
food availability ar>d access, median income, poverty)
Leisure Time
Amount and quaillty of time spent outside of obligations to work
and home (time spent on hobbies, sporting events, relaxing, etc )
Safety and Security
Freedom from harm, both perceived and actual
(crime rates and natural disaster)
Cultural Fulfillment
Opportunity to meet cultural needs
(importance of arts, culture, and heritage)
• evaluate
Societal Welt-Being
Ability to fulfill basic needs
and enhance subjective
well-being
combine to describe
[ Human Well-Befng I
Economic Well -Being
Achieving financial stability
i
i
i
i
i
!*
1 0)
'1
!|
1 0
1°
1
1
1
1
1
1
1
Figure 3. A conceptualized modeling framework showing the components of the
composite index of well-being highlighting ecosystem goods and services inputs,
( Smith etal. 2013).
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Data Sources and Quality Assurance
An extensive review of existing well-being indices was performed to determine the current indicators and
metrics in use. As stated previously, the categories of domains, indicators, and metrics were mainly adapted
from the Canadian Index of Well-being and the OECD Better Life Index because they contained the most
complete set of measurements identified in the review of all potential indices. Data collected by the following
institutions and organizations was used in our index (* most used data sources):
• Centers for Disease Control and Prevention (CDC) *l
• U.S. Census Bureau *2
• General Social Survey (GSS)3
• Gallup, Inc. (Gallup Brain, Gallup Healthways) 4
• Bureau of Labor Statistics (BLS)
• Bureau of Economic Analysis (BEA)
• U.S. Department of Health and Human Services (HHS)
• Federal Bureau of Investigation (FBI)
• American National Election Study (ANES)
• National Center for Education Statistics (NCES)
• Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS)
• National Oceanic and Atmospheric Administration (NOAA)
• Association of Religion Data Archives (ARDA)
• University of South Carolina Hazards and Vulnerability Research Institute (HVRI)
These data sources were chosen based on the following criteria:
1. Availability and access: The data were publicly available and easy to understand, access and extract.
2. Reliability and data credibility: The sources collected data in a manner that was vetted by the
professional community and had metadata available for review.
3. Spatial preference: County-level data were the lowest geospatial level preferred, and could be rolled
into larger scales as needed. In the absence of county-level data, or when it was not feasible to pull
county-level data (i.e., data only available from local governmental sites; lack of compiled data from a
single source), state, regional, and national-level data were used.
4. Coverage: The data were available for a large portion of the United States.
5. Chronological history and the likelihood that the data will continue to be collected: Data had a good
history of collection or consistent collection. The goal was to initially create a time series beginning
with the year 2000 and continuing through 2010; however, if the data were not available from a
single data source for all years, other sources containing similar measurements were used to
complete the time series.
6. Subjective and objective data: Both subjective and objective data were included.
1 CDC Behavioral Risk Factor Surveillance System data is derived from telephone surveys and therefore does not include persons without a home telephone number.
2 U.S. Census Bureau American Community Survey 1-year estimates are only available for geographic areas with populations greater than 65,000 people..
3 Questions asked may or may not be repeated in subsequent survey years and is only available on a biennial basis.
4 Gallup Healthways is proprietary data and only pre-calculated index values are publicly available at the national level.
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Weil-Being Domains and Indicators
Domains are collections of indicators and metrics used to describe different components of human well-being
(see Fig. 3). Although these components are often interrelated, domains are commonly identified for use in
well-being indices in an attempt to separate the main aspects of the human condition to be measured by
serving as the foundation for selecting and developing indicators. Ultimately, these domains correspond with
one or more of the three main elements of well-being: economic, environmental, and societal well-being
(societal includes basic human needs and subjective well-being) that constitute a multidimensional approach
to modeling human well-being.
The following pages contain descriptions of the chosen well-being domains, including how each may relate to
economic and social services, and emphasize the relationships to ecosystem goods and services. The linkages
of ecosystem services to a domain might not be as obvious or as widely known. We have highlighted prior
research that has shown, both directly and indirectly, how ecosystem services can influence each domain of
well-being. Unfortunately there is a lack of metrics depicting direct ecosystem service-domain relationships
that are widespread or have good coverage across the United States. This will likely change with time due to
increasing interest and research in this area of well-being studies.
Details of the domain indicators and corresponding metrics are also included. Each metric description
includes basic information such as the data source(s) and years available, as well as calculations performed to
create the final datasets. We examined the distribution for all metrics using descriptive statistics for pooled
data (2000-2010) to determine the appropriate method for evaluating the data. The graphical results and
statistical summaries for each metric are included in Appendix A.
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Domain: Connection to Nature
Biophilia (2)
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Connection to Nature
Humans' connection with nature is a subjective trait most easily explained by the biophilia hypothesis.
Biophilia is a term coined by prominent evolutionary biologist and entomologist, Edward 0. Wilson, who
defined it as the "innately emotional affiliation of human beings to other living organisms" and hypothesized
that this psychological, and possibly genetic, phenomena arose due to humans' long time interaction with the
natural environment (Wilson 1984, 1993). Biophilia is most evident by the popularity of zoos and outdoor
activities and in people who have non-economic motivations for the protection of natural areas and
biodiversity, such as positive experiences of an area, solastalgia, and having affection or sympathy for non-
human species (Wilson 1993, Serpell 2004, Chawla 2006, Higginbotham et al. 2007, Martin-Lopez et al. 2007,
Nisbetetal. 2011).
Biophilia is also evident in other domains of well-being such as
spiritual and cultural fulfillment, education, health, and leisure
time. Humans, however, are experiencing an increasing
disconnection with nature through urban development and
technology— especially noted in children as the "nature-deficit
disorder" and coincides with rising trends in obesity, attention
deficit disorder, and depression (Wilson 1993, Kellert 2005, Louv
2005). An attempt to correct this growing disconnection and to
incorporate the health of the environment in land use planning is
through "biophilic design", which aims to enhance human physical
health, psychological benefits, and productivity by fostering a
human-nature connection (Baldwin et al. 2011). Although our
detachment with nature will never completely rid us of the desire
to associate with nature, it can weaken our appreciation for nature
and decrease our well-being (Kellert 1997).
Courtesy of Evgeni Dinev; freedigitalphotos.net
Economic and social services have significant direct and indirect effects on the connection to nature domain.
For example, economic programs and funding can increase or decrease natural areas, either by putting aside
more areas or decreasing those areas through capital investment (e.g., new infrastructure, mining/extraction
activities). Additionally, social services such as activism, community and faith-based initiatives, justice (e.g.,
environmental justice), and public works can affect policies that support ecosystems or can possibly be used
as indirect measures of our connection to nature.
• Relationship to Ecosystem Services
Biophilia is largely affected by biodiversity and amplified by access to nature and exposure to diverse, healthy
ecosystems (Wilson 1993). Nature Relatedness (NR), similar to biophilia, has been used to quantify our
connection to nature (Nisbet et al. 2011). Natural areas and green spaces are needed for humans to
experience nature and increase NR, which is most often accomplished through the ecosystem goods of
p recreation and aesthetics. The total area of these spaces directly affects the availability and diversity of
fc^ recreational and aesthetic opportunities and the health of the ecosystem and its ability to provide other
\ services such as water and air quality regulation (EPA 1997, MEA 2005, Pongsiri and Roman 2007).
\ Additionally, due to the interconnectedness of plants and animals occupying these areas, biodiversity is
especially important for the functioning of the ecosystem and of humans psychologically (Kellert 1997, MEA
2005, Chavas 2009, Nisbet et al. 2011).
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Indicator; Biophilia
Spiritual Fulfillment
Metric Variable: BEAUSPRT
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable BEAUSPRT, I am spiritually touched by the beauty of creation
Alternate Source: N/A
Years Available: 1998*, 2004
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered "Many times a day", "Every
day", and "Most days". *1998 values were used for imputation purposes only
Connection to Life
Metric Variable: ALLOFLFE
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable ALLOFLFE, You may experience the following in your daily
life, if so how often? Experience a connection to all of life
Alternate Source: N/A
Years Available: 2004
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered "Many times a day", "Every
day", and "Most days"
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Domain: Cultural Fulfillment
I Activity Participation (2)
10
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Cultural Fulfillment
This domain captures metrics that measure opportunities that afford people and communities access to
fulfilling their cultural needs. Indicators are multi-faceted and may represent cultural interests, cultural
identity, and/or connection to nature (i.e., visits to national parks). Cultural indicators encompass values-
driven metrics that examine the concepts of the "self" that centers around vital interconnections with others
and the environment (Centre for Rural and Remote Mental Health 2009).
While there are many variations of the specific definition, few would
argue the important role of spirituality and culture within populations.
Cultural values are in many ways integral to vital communities ,yet are
rarely considered in most well-being indices. Investment in museums,
cultural centers, and other similar gathering places offer educational
opportunities to help mitigate inequities typical of cultural exclusion.
Faith- and community-based activities, such as festivals, concerts, arts
and crafts shows, etc.,, further strengthen social cohesion by
preserving cultural and spiritual heritage. Moreover, it is the
environmental culture that is often the harmonizing factor that
supports community vitality when obvious economic disparity would
courtesy of istockphoto otherwise cause discord ("A Tale of Two Aspens" 2011).
Relationship to Ecosystem Services
Cultural ecosystem services represent the "non material
benefits people obtain from ecosystems through spiritual
enrichment, cognitive development, reflection, recreation, and
aesthetic experiences" (MEA 2005, p. 40). For many
populations, culture and spirituality are strongly connected
with the environment. Swan and Raphael (1995) noted that
Aboriginal Australians holistically view "health" as harmonized,
inter-relating factors that include spiritual, environmental,
ideological as well as mental and physical aspects that,
collectively, are identified as "cultural well-being". The social,
sacred, and cultural aspects of ecosystems significantly
contribute to Native American well-being but are often
overlooked in qualitative assessments. Native Americans seek
cultural and spiritual fulfillment by communing with nature,
praying and meditating, fishing and hunting, collecting herbs,
and conducting vision quests or other ceremonies (Burger
2011).
The interwoven relationship between humans and the landscape is manifested in cultural diversity and
heritage, educational values and ecological knowledge, social relations and sense of place (MEA 2005, Rossler
2006, Schaich et al. 2010). The tangible and intangible heritage associated with the human nature interface is
tightly coupled with people's involvement in environmental conservation (Philips 1998). Thus it follows that
cultural and spiritual fulfillment is influenced by our connection to natural systems and an opportunity to
identify with our heritage through visits to natural historical sites, national parks, and celebrations revolving
around cultural landscapes and nature's bounty.
Courtesy of Microsoft.com
11
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Indicator; Activity Participation
Performing Arts Attendance
Metric Variable: PERARTS
Source: U.S. Census Bureau & Bureau of Labor Statistics - Current Population Survey
Source Question or Measurement: Census variables PESA1A through PESA9A (Attended jazz, classical music,
opera, musical stage play, non-musical stage play, ballet, or modern, folk, tap performance, or visited an art
museum/gallery or art/craft fair/festival)
Alternate Source: N/A
Years Available: 2002
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of people who responded "yes" to any of the variables
Rate of Congregational Adherence
Metric Variable: TOTRATE
Source: Association of Religion Data Archives, U.S. Church Membership Data, Religious Congregations and
Membership Studies
Source Question or Measurement: ARDA variable TOTRATE, All denominations/groups-Rates of adherence
per 1,000 population
Alternate Source: N/A
Years Available: 2000, 2010
Smallest Geospatial Level Available: County
Calculation Methods: N/A
12
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Domain: Education
Social, Emotional and Developmental Aspects
Basic Knowledge and Skills of the Youth
Paticipation and Attainment
13
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Education
The domain of education is defined as the outcomes derived from the formal and informal transfer of
knowledge and skills and is measured using standardized test scores, literacy rates, educational attainment
and participation, and various social, emotional, and developmental aspects in childhood. Education has been
referred to as a basic capability leading to the expansion of other capabilities and is fundamental to well-being
(Terzi 2004). Educational progress and benefits influence other well-being domains and may be measured at
the individual level by economic returns by subjective feelings of achievement and accomplishment, or at a
societal level by creating a skilled workforce with enhanced worker productivity, lower crime rates, and
greater civic participation (Guhn et al. 2010, Hill et al. 2005).
Economic and social services provide funding and other programs that influence the access to and
opportunities for education. Educational services provide programs are aimed at reaching more students,
especially those with disabilities or other special circumstances, and hiring qualified teachers. Community and
faith-based initiatives may also act in this manner to reach additional children and families. Communication
through public broadcasting and public service announcements helps educate the public about various issues
(e.g., public health issues). Financial assistance in the form of grants, scholarships, and student loans is also
essential to allow opportunities for post-secondary education
Relationship to Ecosystem Services
Ecosystems provide a plethora of learning opportunities at many levels of
education. Some areas may be designated as public learning centers and accessible
to all ages, while post-secondary educational institutions may use natural areas for
teaching and scientific research (EPA 1997). Environment-based education
programs and school grounds greening in elementary and secondary schools have
shown several positive effects on the mental health and brain development in early
and middle childhood. These benefits include improved standardized test scores
and problem-solving skills, decreased symptoms of attention deficit disorder, and
enhanced cooperation and interpersonal skills, all of which lead to a better
educational experience and improved well-being (Lieberman and Hoody 1998,
Louv 2005, Guhn et al. 2010).
Courtesy of U.S. FWS
Ecosystem research is also integral to innovation and the
progression of society. By studying the function and uses of
organisms, we are able to discover untapped sources of
Pharmaceuticals, crops, and other goods and also transfer that
knowledge into art, other scientific fields, and practical affairs
(Wilson 1993). Local environmental knowledge is also important
in providing historical accounts of an area. These accounts
contribute to scientific research and environmental management,
but also contribute to various cultural aspects of the area.
(Huntington 2000). Continual research on ecosystems is crucial for
understanding how ecosystems provide services that effect
human well-being, as well as understanding how our actions
affect the provisioning of these services.
Courtesy of U.S. FWS
14
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!
Indicator; Social. Emotional and Developmental Aspects
Preprimary Education and Care
Metric Variable: CONFACT
Source: Bureau of Labor Statistics- American Time Use Surveys
Source Question or Measurement: Time spent reading to/with household children identified by activity code
030102 (and where the youngest household child was between the ages of 3 and 5 years old).
Alternate Source: N/A
Years Available: 2002-2008
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of parents who have children that reported time spent
Coincidence, not actual time spent) reading to/with their children
Bullying
Metric Variable: BULLY
Source: Centers for Disease Control and Prevention- Youth Risk Behavior Surveillance System
Source Question or Measurement: During the past 30 days, on how many days did you not go to school be-
cause you felt you would be unsafe at school or on your way to or from school?
Alternate Source: N/A
Years Available: 1999*-2009; biennial
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of students in grades 9-12 who responded with 1 or more
days. *1999 values were used for imputation purposes only
15
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Indicator; Social. Emotional and Developmental Aspects (continued)
Child Physical Health
Metric Variable: CHLDHLTH
Source: U.S. Department of Health and Human Services- National Survey of Children's Health
Source Question or Measurement: NSCH Indicator 1.1: In general, how would you describe [child name]'s
health? Would you say [his/her] health is excellent, very good, good, fair, or poor? Percentage of children
(age 0-17 years) in excellent or very good health
Alternate Source: N/A
Years Available: 2003, 2005, 2007
Smallest Geospatial Level Available: State
Calculation Methods: N/A
Social Relationships and Emotional Well-being
Metric Variable: CHLDSOCIAL
Source: U.S. Department of Health and Human Services- National Survey of Children's Health
Source Question or Measurement: NSCH Indicator 2.5: How many children often exhibit caring, respectful be-
haviors when interacting with other children and adults? Percentage of children (age 6-17 years) who often
exhibit positive social skills . "Often exhibit" is defined as answering "usually" or "always" to at least 2 of the 4
questions [S7Q53; S7Q52; S7Q54; S7Q59].
Alternate Source: N/A
Years Available: 2003, 2007
Smallest Geospatial Level Available: State
Calculation Methods: N/A
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Indicator; Basic Educational Knowledge and Skills of the Youth
Mathematics Skills
Metric Variable: MATHTEST
Source: National Center for Education Statistics- National Assessment of Educational Progress
Source Question or Measurement: Percentages at or above each achievement level for mathematics, grade
[4, 8] by year, jurisdiction, and All students [TOTAL].
Alternate Source: N/A
Years Available: 2000, 2003, 2005, 2007, 2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the average of the percentages in grades 4 and 8 at or above achievement
level.
Reading Skills
Metric Variable: READTEST
Source: National Center for Education Statistics- National Assessment of Educational Progress
Source Question or Measurement: Percentages at or above each achievement level for reading, grade [4, 8]
by year, jurisdiction, and All students [TOTAL].
Alternate Source: N/A
Years Available: 2002, 2003, 2005, 2007, 2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the average of the percentages in grades 4 and 8 at or above achievement
level.
17
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Indicator; Basic Educational Knowledge and Skills of the Youth (continued)
^
Science Skills
Metric Variable: SCITEST
Source: National Center for Education Statistics- National Assessment of Educational Progress
Source Question or Measurement: Percentages at or above each achievement level for science, grade [4, 8]
by year, jurisdiction, and All students [TOTAL].
Alternate Source: N/A
Years Available: 2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the average of the percentages in grades 4 and 8 at or above achievement
level.
Indicator; Participation and Attainment
Adult Literacy
Metric Variable: ADULTLIT
Source: National Center for Education Statistics- National Assessment of Adult Literacy (NAAL)
Source Question or Measurement: Indirect estimate of percent lacking Basic prose literacy skills and corre-
sponding credible intervals. Percent [age 16 and older) lacking basic prose literacy skills. Those lacking Basic
prose literacy skills include those who scored Below Basic in prose and those who could not be tested due to
language barriers.
Alternate Source: N/A
Years Available: 1992*, 2003
Smallest Geospatial Level Available: State
Calculation Methods: N/A. *1992 values were used for imputation purposes only.
18
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Indicator; Participation and Attainment (continued)
Participation
Metric Variable: PARTNEDU
Source: U.S. Census Bureau & Bureau of Labor Statistics - Current Population Survey
Source Question or Measurement: CPS variables PETYPE- School enrollment 2 or 4 year college, PRTAGE- sin-
gle year of age
Alternate Source: N/A
Years Available: 2000-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of people aged 18-24 enrolled in post-secondary educa-
tion
High School Completion
Metric Variable: HSGRAD
Source: U.S. Census Bureau-American Community Survey
Source Question or Measurement: ACS variables CO, C12, CIS, C24, C30, C84, C90, C96, C102, C108, C114,
C120, C126. Population totals and percentages who obtained a high school (or equivalent) diploma or higher
for age groups 18-24 and 25 and older
Alternate Source: N/A
Years Available: 2005-2009
Smallest Geospatial Level Available: County
Calculation Methods: Percentages of attainment were summed within each age group and then averaged to-
gether using population totals as weights
19
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Indicator; Participation and Attainment (continued)
Post-Secondary Attainment
Metric Variable: UNIVGRAD
Source: U.S. Census Bureau-American Community Survey
Source Question or Measurement: ACS variables CO, C24, C30, C108, C114, C120, C126. Population totals and
percentages who obtained a bachelor's degree or higher for age groups 18-24 and 25 and older.
Alternate Source: N/A
Years Available: 2005-2009
Smallest Geospatial Level Available: County
Calculation Methods: Percentages of attainment were summed within each age group and then averaged to-
gether using population totals as weights.
20
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Domain: Health
• Personal Well-being
LJ Life Expectancy/Mortality
y Physical and Mental Health
y Lifestyle and Behavior
y Healthcare
21
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Health
The domain of healthy populations includes health outcome measures of personal well-being, life expectancy
and mortality, and physical and mental health conditions. This domain also incorporates lifestyle behavior and
healthcare, all of which influences a population's health status. Food utilization (a part of food security) also
falls into this domain because of its connection to healthy behaviors. Other outside influences such as
environmental quality (e.g., clean air days, clean water, etc.) are captured through indicators of ecosystem
services.
The connections between economic services and human health are so numerous and complex that an entire
sub-discipline of economics, known as health economics, has emerged. Economic assessments of health-
related interventions are critical to decision makers because expenditure on health care in the United States
has outpaced the general rate of inflation (Meltzer 2001). Social services are also strongly tied to human
health. Many large organizations within the U.S. government were formed to protect and enhance the health
of the U.S. population, and several well-known private organizations, such as the American Red Cross, United
Way of America, and Ronald McDonald House Charities, provide health-related services to populations in
need.
Relationship to Ecosystem Services
FISH CONTAMINATED
DO NOT EAT
Courtesy of iStockphoto
The impact of environmental quality and condition on human health
is well known. Yet the connection between ecosystem services and
human health and development is a relatively new field of study.
McMichael et al. (2003) points out that climate change is known to
have an adverse affect on human health and that an estimated 83%
of medicinal goods have yet to be discovered and used for human
benefit from tropical vegetation, much of which could be lost
forever if biodiversity continues to decline. Ecosystem condition also
has direct impacts on human health resulting from bacterial
contamination, air pollution, and toxic algal blooms (Cox et al. 2003).
Access to nature, even if only through a window view, provides
restorative experiences that can improve psychological and
physiological health (Van Den Berg et al. 2007).
Greenspace and connection to nature have been linked to healthy physical, cognitive, and behavioral
development, especially in children and youth. For instance, sensatory stimulation promoted positive healthy-
related behaviors by affecting interpersonal processes among a
group working in a community garden (Hale et al. 2011).
Children and youth living in greener neighborhoods had lower
BMI after 2 years, presumably due to increased physical activity
or time spent outdoors (Bell et al. 2008). Children also see
improvements in motor fitness, balance, and coordination when
provided with a natural landscape for play (Fjortoft 2004).
Lifestyle is responsible for the bulk of the current avoidable
disease burden, making the impact of ecosystem services on
healthy behaviors that much more important (de Hollander and
Staatsen 2003).
Courtesy of Microsoft.com
22
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Indicator; Personal Well-being
Perceived Health
Metric Variable: PRCVDHLTH
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: CDC variable GENHLTH, Would you say that in general your health is
excellent, very good, good, fair, or poor?
Alternate Source: Gallup Healthways variable H36, Would you say your own health in general is excellent,
very good, good, fair, or poor?
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of people who responded that their health was
"Excellent", "Very Good" or "Good"
Life Satisfaction
Metric Variable: LIFESATIS
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: CDC variable LSATISFY, In general how satisfied are you with your life?
Alternate Source: Gallup Healthways variable WP15, In general, are you satisfied or dissatisfied with the way
things are going in your own personal life?
Years Available: 2005-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the proportion of people who are satisfied with their life (Gallup), and
"Very satisfied" or "Satisfied" with their life (BRFSS)
' 23
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Indicator; Personal Well-being (continued)
Happiness
Metric Variable: HAPPY
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable HAPPY, Taken all together, how would you say things are
these days- Would you say that you are very happy, pretty happy, or not too happy?
Alternate Source: Gallup Healthways variable WP6878, Did you experience happiness a lot of the day
yesterday?
Years Available: 2000, 2002, 2004, 2006, 2008, 2009
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Very happy" or "Pretty
happy" (GSS); and the percentage of respondents who answered "Yes" (Gallup)
Indicator; Life Expectancy and Mortality
Life Expectancy at Birth
Metric Variable: LIFEXPCT
Source: CDC- Compressed Mortality Files
Source Question or Measurement: Compressed Mortality Files- all
Alternate Source: N/A
Years Available: 2000-2007
Smallest Geospatial Level Available: County
Calculation Methods: Calculated using CDC's Compressed Mortality Files and Fergany's (1971) methods. Life
expectancy was determined by county-level age group rates; missing or zero age group rates were imputed
from the next higher spatial level (state or national)
24
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Indicator; Life Expectancy and Mortality (continued)
i -.
Cancer Mortality
Metric Variable: CANCMORT
Source: CDC- Compressed Mortality Files
Source Question or Measurement: Number of deaths due to malignant neoplasms and various cancer
diseases, age-adjusted (ICD 113 Group Codes GR113-020 through GR113-044, excluding GR113-037)
Alternate Source: N/A
Years Available: 2000-2007
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of deaths that were cancer-related
Infant Mortality
Metric Variable: INFMORT
Source: CDC-Compressed Mortality Files
Source Question or Measurement: Compressed Mortality, 1999-2007, Age group <1 year, Rates per 10,000*
Alternate Source: N/A
Years Available: 2000-2007
Smallest Geospatial Level Available: County
Calculation Methods: N/A. *Note that the rate is expressed per 10,000 population under 1 year and not as a
percentage of live births
25
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Indicator; Life Expectancy and Mortality (continued)
Suicide Mortality
Metric Variable: SUICDMORT
Source: CDC- Compressed Mortality Files
Source Question or Measurement: Number of deaths due to intentional self-harm, age-adjusted (ICD 113
Group Codes GR113-125 and GR113-126)
Alternate Source: N/A
Years Available: 2000-2007
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of deaths that were suicide-related
Diabetes Mortality
Metric Variable: DIABMORT
Source: CDC- Compressed Mortality Files
Source Question or Measurement: Number of deaths due to Diabetes mellitus, age-adjusted (ICD 113 Group
Code GR113-046)
Alternate Source: N/A
Years Available: 2000-2007
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of deaths that were diabetes-related
26
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Indicator; Life Expectancy and Mortality (continued)
Heart Disease Mortality
Metric Variable: HRTDISMORT
Source: CDC- Compressed Mortality Files
Source Question or Measurement: Number of deaths due to various heart diseases and other conditions
caused by hypertension and/or high cholesterol, age-adjusted (ICD 113 Group Codes GR113-055 through
GR113-074, excluding GR113-058, -061, -064, and -072)
Alternate Source: N/A
Years Available: 2000-2007
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of deaths that were heart disease-related
Asthma Mortality
Metric Variable: ASTHMORT
Source: CDC- Compressed Mortality Files
Source Question or Measurement: Number of deaths due to asthma, age-adjusted (ICD 113 Group Code
GR113-085)
Alternate Source: N/A
Years Available: 2000-2007
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of deaths that were asthma-related
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Indicator; Physical and Mental Health Conditions
Diabetes Prevalence
Metric Variable: DIABETES
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: BRFSS variables DIABETES (2000-2003) and DIABETE2 (2004-2010), Have
you ever been told by a doctor or other health professional that you have diabetes?
Alternate Source: Gallup Healthways variable H4C, Have you ever been told by a physician or nurse that you
have diabetes?
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of people who responded "Yes"
Cancer Prevalence
Metric Variable: CANCER
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: BRFSS variable CNCRHAVE, Have you ever been told by a doctor, nurse, or
other health professional that you have cancer.?
Alternate Source: Gallup Healthways variable H4G, have you ever been told by a physician or nurse that you
have cancer?
Years Available: 2009-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of people who responded "Yes"
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Indicator; Physical and Mental Health Conditions (continued)
Depression Prevalence
Metric Variable: DEPRESSION
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: BRFSS variable ADDEPEV, Has a doctor or other healthcare provider ever
told you that you have a depressive disorder (including depression, major depression, dysthymia, or minor
depression)?
Alternate Source: Gallup Healthways variable H4D, Have you ever been told by a physician or nurse that you
have depression?
Years Available: 2006-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Yes"
Coronary Heart Disease Prevalence
Metric Variable: HRTDISEASE
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: CDC variables CVDCORHD (2000), CVDCRHD2 (2001-2004), CVDCRHD3
(2005-2006), and CVDCRHD4 (2007-2010), Have you ever been told by a doctor or other health professional
that you had angina or coronary heart disease?
Alternate Source: N/A
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Yes"
29
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Indicator; Physical and Mental Health Conditions (continued)
Stroke Prevalence
Metric Variable: STROKE
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: CDC variables CVDSTROK (2000), CVDSTRK2 (2001-2004), CVDSTRK3
(2005-2010), Have you ever been told by a doctor or other health professional that you had a stroke?
Alternate Source: N/A
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Yes"
Heart Attack Prevalence
Metric Variable: HRTATTACK
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: BRFSS variables CVDINFAR (2000), CVDINFR2 (2001-2004), CVDINFR3
(2005-2006), CVDINFR4 (2007-2010), Have you ever been told by a doctor or other health professional that
you had a heart attack (also called myocardial infarction)?
Alternate Source: Gallup Healthways variable H4E, Have you been told by a physician or nurse that you had a
heart attack?
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Yes"
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Indicator; Physical and Mental Health Conditions (continued)
Adult Asthma Prevalence
Metric Variable: ADLTASTHMA
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: BRFSS variables ASTHMA (2000) and ASTHMA2 (2001-2010), Has a doctor
or other health professional ever told you that you had asthma?
Alternate Source: Gallup Healthways variable H4F, Have you ever been told by a physician or nurse that you
have asthma?
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Yes"
Childhood Asthma Prevalence
Metric Variable: CHLDASTHMA
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System (BRFSS)
Source Question or Measurement: BRFSS variables ASTHCHLD (2001), CASTHDX (2002-2004), and CASTHDX2
(2005-2010), Earlier you said there were [fill in number from core Q12.6] children age 17 or younger living in
your household. How many of these children have ever been diagnosed with asthma?
Alternate Source: N/A
Years Available: 2001-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who reported 1 or more child
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Indicator; Physical and Mental Health Conditions (continued)
Obesity Prevalence
Metric Variable: OBESITY
Source: CDC- National Diabetes Surveillance System
Source Question or Measurement: NDSS variable ADJPERCENT, age-adjusted percentage of population aged
18 and older classified as obese (BMI>=30)
Alternate Source: N/A
Years Available: 2004-2008
Smallest Geospatial Level Available: County
Calculation Methods: N/A
Indicator; Lifestyle and Behavior
Teen Smoking Rate
Metric Variable: TEENSMK
Source: CDC- Youth Risk Behavior Surveillance System (YRBSS)
Source Question or Measurement: Percentage of children in grades 9-12 who smoked cigarettes on 20 or
more days in the past 30 days
Alternate Source: N/A
Years Available: 1999*-2009; biennial
Smallest Geospatial Level Available: State
Calculation Methods: N/A. *1999 values were used for imputation purposes only
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Indicator; Lifestyle and Behavior (continued)
Healthy Behaviors Index
Metric Variable: HBI
Source: Gallup Healthways
Source Question or Measurement: The Healthy Behaviors Index (HBI) is a mean of four items receded to
reflect the positive responses only. The four items are Gallup variables Hll (Do you smoke?), M16 (Did you
eat healthy all day yesterday?), H12A (if respondent reported exercising 3-7 times per week), and H12B (if
respondent reported eating 5 fruits and vegetables per day, 4 or more times per week).
Alternate Source: CDC- BRFSS variables RFPAMOD (Risk factor for moderate physical activity defined as 30 or
more minutes per day for 5 or more days per week, or vigorous activity for 20 or more minutes per day on 3
or more days), FRTINDEX (summary index based on the calculated number of daily servings of fruits and
vegetables), and SMOKER2 and SMOKERS (Four level smoker status: Every day smoker, Someday smoker,
Former smoker, Non-smoker).
Years Available: 2001-2010
Smallest Geospatial Level Available: County
Calculation Methods: The average index value was calculated for each county (Gallup). The average of the
variables was computed at the respondent level following the same receding procedure as Gallup (CDC)
Teen Pregnancy
Metric Variable: TEENPREG
Source: CDC-VitalStats Birth Data Files
Source Question or Measurement: CDC variables for year, county of residence, and age of mother
Alternate Source: CDC- WONDER, CDC variables for year, county of residence, and age of mother
Years Available: 2000-2008
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of births to mothers in the age groups "under 15" and
"15-19" as a percentage of all births
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Indicator; Lifestyle and Behavior (continued)
Alcohol Consumption
Metric Variable: ALCOHOL
Source: CDC- BRFSS
Source Question or Measurement: 1) CDC variables DRINKANY, DRNKANY2, DRNKANY3, and DRNKANY4,
During the past month have you had at least one drink of any alcoholic beverage such as beer, wine, wine
coolers, or liquor? 2) CDC variables ALCDAYS, ALCDAY3, ALCDAY4, and ALCOHOL, During the past 30 days,
how many days per week or per month did you have at least one drink of any alcoholic beverage? 3) CDC
variables NALCOCC, AVEDRNK, and AVEDRNK2, On the days when you drank, about how many drinks did you
drink on the average?
Alternate Source: N/A
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of people who drank on average more than one drink per
day using the variables listed above
Indicator: Healthcare
Population with a Regular Family Doctor
Metric Variable: FAMDOC
Source: CDC- BRFSS
Source Question or Measurement: BRFSS variables PERSDOC and PERSDOC2, Do you have one person you
think of as your personal doctor or health care provider?
Alternate Source: Gallup Healthways variable H13, Do you have a personal doctor?
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Yes"
34
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Indicator; Healthcare (continued)
Satisfaction with Healthcare
Metric Variable: SATISHLTHC
Source: Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS)
Source Question or Measurement: NCAHPS variable H_HSP_RATING_9_10, How do patients rate the hospital
overall? Patients who gave a rating of 9 or 10 (high)
Alternate Source: N/A
Years Available: 2008, 2009
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the average percent of patients who gave a rating of 9 or 10
35
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Domain: Leisure Time
• Activity Participation
H Time Spent
U Working Age Adults
36
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Leisure Time
Leisure time is time that individuals have to voluntarily engage in pleasurable activities when they are free
from the demands of work or other responsibilities. It is commonly deemed as necessary for basic survival
and has increasingly been referred to as a domain of the "good life" (Smale et al. 2010). Suggested metrics of
this domain are the amount of time spent on specific leisure activities, types of activities, frequency of
participation, and expenditures on leisure activities. Measures of work hours and continuous sleep time can
be used as surrogate measures indicating the amount of time available for leisure activities. Enjoyable
activities may also act as "restorers" that facilitate the individual's recovery from stress as the result of
positive social interactions or relaxation that lead to increased positive emotions (Pressman et al. 2009).
Participation in leisure time activities has been positively linked to both physical and mental health measures
(Williams and Patterson 2008, Krueger et al. 2009). Leisure time also provides for psychological detachment
from work which in turn promotes well-being and productivity (Sonnentag et al. 2010). Leisure time activities
also provide opportunities for social interactions through group participation (e.g., clubs, sports, religious
organizations) and expand the size of social networks, enhancing social cohesion. Higher income has been
positively associated with increased leisure time as it relates to more disposable income; however, in the U.S.
the cost of the loss of leisure time due to increased work hours has continued to rise since the 1950s (Talberth
etal. 2007).
Relationship to Ecosystem Services
Specific activities individuals engage in can be linked to access and exposure to nature and greenspace.
According to Korpela and Kinnunen (2010), time spent in interaction with nature is significantly correlated to
both life satisfaction and relaxation, contributors
to our subjective well-being and health. Among a
variety of leisure time activities evaluated,
exercise, spending free time outdoors, and
interacting with nature were the most effective
activities for recovery from work stress (Korpela
and Kinnunen 2010). These activities are closely
tied to recreational opportunities and aesthetics,
biodiversity, usable water (swimmable, fishable),
and clean air. The U.S. downward trend in the
amount of free time afforded to individuals places
increased value on the amount of time available
outside work. The potential impact of outdoor
activities and interactions with nature on our well-
being exemplifies the contribution of ecosystem
goods and services that support these leisure
activities. Courtesy of U.S. EPA
37
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Indicator; Time Spent
Leisure Activities
Metric Variable: LEISURE
Source: Bureau of Labor Statistics- American Time Use Survey
Source Question or Measurement: Time spent on socializing, relaxing, leisure and sports identified by activity
codes 12xxxx-13xxxx (where "xx" indicates any numbers to complete the 6-digit activity code from the coding
lexicon).
Alternate Source: N/A
Years Available: 2002-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the average percentage of time involved in these activities
Indicator; Activity Participation
Physical Activity
Metric Variable: PHYSACTIV
Source: Centers for Disease Control and Prevention- Behavioral Risk Factor Surveillance System
Source Question or Measurement: CDC variable EXERANY2, During the past month/30 days, other than your
regular job, did you participate in any physical activities or exercise such as running, calisthenics, golf,
gardening, or walking for exercise?
Alternate Source: N/A
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of people who answered "yes"
38
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Indicator; Activity Participation (continued)
Average Nights on Vacation
Metric Variable: VACATION
Source: Bureau of Labor Statistics (BLS)- American Time Use Survey, Trips Survey Supplement
Source Question or Measurement: BLS variable TUTRV2- Main purpose for the trip, and BLS variable TUTRV5-
Total nights away from home
Alternate Source: N/A
Years Available: 2004-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the average number of nights away from home when the main purpose
was vacation or visiting friends/relatives
Indicator; Working Age Adults
Adults Working Standard Hours
Metric Variable: NORMWRKHRS
Source: Bureau of Labor Statistics- American Time Use Survey
Source Question or Measurement: Work and work-related activities identified by activity codes OSOlxx
(where "xx" indicates any numbers to complete the 6-digit activity code from the coding lexicon)
Alternate Course: N/A
Years Available: 2003-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of work activity duration during daytime hours (9 am to 5
pm) from total work activity duration
39
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Indicator; Working Age Adults (continued)
Adults Working Long Hours
Metric Variable: LONGWRKHRS
Source: U.S. Census Bureau- Current Population Survey
Source Question or Measurement: CPS variable PEHRUSLT, # hours usually worked at all jobs
Alternate Course: N/A
Years Available: 2002-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of employed respondents reporting that they work 50
hours or more per week
Adults who Provide Care to Seniors
Metric Variable: SENIORCARE
Source: Bureau of Labor Statistics- American Time Use Survey
Source Question or Measurement: Adult care activities identified by activity codes 0304xx, 0305xx, 0404xx,
0405xx (where "xx" indicates any numbers to complete the 6-digit activity code from the coding lexicon).
Alternate Course: N/A
Years Available: 2002-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of adult care activities duration from total activities
duration
40
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Domain: Living Standards
I Wealth
ilncome
i Work
(Basic Necessities
41
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Living Standards
In the simplest of terms, living standards may be best described as "the physical circumstances in which
people live, the goods and services they are able to consume and the economic resources to which they have
access" (New Zealand Economic Social Report 2010). Living standard indicators tend to be largely economic in
nature, characterized by demography and geography. Income level is the most dominate class of metrics used
for evaluating standard of living followed by living conditions which includes housing status, household
crowding (rooms per person), and state of housing repair. Home ownership, household assets, and other
measures of material affluence were used to evaluate wealth.
Economic and social services aim to improve the living standards of a
population. Economic services provide a means to accumulate and
distribute wealth ,while many social services help to improve living
conditions among the most impoverished within the community.
Poverty metrics (e.g., income- and housing-related) figure promi-
nently in living standard assessments because there is a close
relationship between standards of living and attainment of basic
human needs. However, wealth disparity alone cannot fully account
for standards of living. Current research suggests that
conceptualizing basic human needs in light of multi-dimensional well-
being may provide a more comprehensive picture relative to living
standards (Sen 1993, Sumner 2004, Wagle 2008). For example,
indices that exclude time use measures may be missing non-market
activities that may enhance standards of living without significantly
contributing to household income (Folbre 2009). Further, the
perception of living standards is often an overlooked influence on a
population's overall well-being.
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Relationship to Ecosystem Services
Ecosystem services may greatly influence living standards both monetarily
and non-monetarily. Coastal and Great Lake ecosystems, for example, create
approximately 100 million jobs nationwide (National Ocean Economics
Program 2009). Ecosystems such as wetlands or grasslands provide
regulating services that may reduce infrastructure cost by using existing
natural capacity for increasing the availability of clean and safe drinking and
recreational water. Urban greenspace helps mitigate environmentally-borne
health-related illness such as asthma thus reducing healthcare-related costs
and stress. Easy access to natural space provides opportunities for culturally-
fulfilling, quality recreational activities for those populations who are most
likely to have the least amount of leisure-time available.
Courtesy of USDA NRCS
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Indicator; Wealth
Median Home Value
Metric Variable: HOMEVAL
Source: U.S. Census Bureau- American Community Survey
Source Question or Measurement: ACS variable B25077, Median value of owner-occupied housing units
Alternate Source: N/A
Years Available: 2004-2009
Smallest Geospatial Level Available: County
Calculation Methods: N/A
.f Mortgage Debt
Metric Variable: MTGDEBT
Source: U.S. Census Bureau- American Community Survey
Source Question or Measurement: ACS variable B25081, Mortgage status of owner-occupied housing units
Alternate Source: N/A
Years Available: 2004-2009
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of owner-occupied housing units with no second mort-
gage or home equity loan
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Indicator; Income
Median Household Income
Vj
s
Metric Variable: MEDINCOME
Source: U.S. Census Bureau-SAIPE
Source Question or Measurement: Median household income, in dollars; number
Alternate Source: N/A
Years Available: 2000-2009
Smallest Geospatial Level Available: County
Calculation Methods: N/A
Incidence of Low Income
Metric Variable: POVERTY
Source: U.S. Census Bureau- SAIPE
Source Question or Measurement: All ages in poverty; Percent
Alternate Source: N/A
Years Available: 2000-2009
Smallest Geospatial Level Available: County
Calculation Methods: N/A
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Indicator; Income (continued)
Persistence of Low Income
Metric Variable: POVPERSIST
Source: General Social Survey (GSS) and U.S. Census Bureau
Source Question or Measurement: 1) U.S. Census Bureau weighted average poverty threshold for the year
1986. 2) GSS variable REALINC: Family income on 1972-2006 surveys in constant dollars (base = 1986). 3) GSS
variable FINALTER: During the last few years, has your financial situation been getting better, worse, or has it
stayed the same? 4) GSS variable HOMPOP Household Size and Composition (see Appendix D: Recedes in the
General Social Surveys, 1972-2008 Cumulative Codebook for more information about the GSS variables)
Alternate Source: N/A
Years Available: 2000-2008; biennial
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered "Stayed the same" for GSS
variable FINALTER, while using the responses to GSS variables REALINC and HOMPOP to determine what re-
spondents were below the U.S. Census poverty thresholds
Indicator: Work
Job Quality
Metric Variable: JOBLOSE
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable JOBLOSE, Thinking about the next 12 months, how likely do
you think it is that you will lose your job or be laid off-very likely, fairly likely, not too likely, or not at all likely?
I Alternate Source: N/A
Years Available: 2000-2008; biennial
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered "Not too likely" or "Not at
all likely"
,
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Indicator; Work (continued)
Job Satisfaction
Metric Variable: JOBSATIS
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable SATJOB1, All in all how satisfied would you say you are with
your job?
Alternate Source: Gallup Healthways variable WP9045, Are you satisfied or dissatisfied with your job or the
work you do?
Years Available: 2002, 2006, 2009
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Very Satisfied" and
"Somewhat Satisfied" (GSS), and the percentage of respondents who answered "Satisfied" (Gallup)
Indicator: Basic Necessities
Housing Affordability
Metric Variable: HOMEAFFORD
Source: U.S. Census Bureau- American Community Survey
Source Question or Measurement: ACS variable B25092, Median selected monthly owner costs as a
percentage of household income, Total
Alternate Source: N/A
Years Available: 2004-2009
Smallest Geospatial Level Available: County
Calculation Methods: N/A
m
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Indicator; Basic Necessities (continued)
Food Security
r f
i
I
Metric Variable: FOODSECURE
Source: U.S. Census Bureau- Current Population Survey
Source Question or Measurement: Census variable HRFS12M1, Food Security Summary Status, 12-month
Alternate Source: N/A
Years Available: 2005-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of households that responded "Food Secure - High or
Marginal Food Security"
15
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Domain: Safety and Security
• Actual Safety
H Perceived Safety
HRisk
48
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Safety and Security
Based on Maslow's hierarchy of basic human needs, once physical needs are relatively satisfied, safety needs
take precedence. Personal security can be linked to unemployment, poverty, education level and social
cohesion, and is most often evaluated using crime rates, number of accident-related injuries and deaths, and
perceived safety. In basic terms, safety and security can be described as freedom from harm (physical
security—personal and national) but is also described by measures related to financial security. Economic
security is evaluated in the event of unemployment, sickness, widowhood, old age and disability. These
measures can be linked to economic services of employment and income and heavily associated with social
nets provided through the provisioning of social services — particularly financial assistance and healthcare.
Our sense of safety and security can be altered in the wake of technological and natural disasters due to
degradation of ecosystems, economic loss, and increased reliance on social safety nets and recovery services.
From the ecosystem services perspective, clean water and air, sufficient food production, and natural hazard
protection significantly contribute to our sense of safety and security through direct relationships to our
health via exposure to pathogens and contaminants, food supply, and prevention of loss of life and property
(MEA 2005). Additionally, there is a comfort derived from knowing that we are not on the brink of
environmental problems and that a natural system will be conserved for future generations (Higginbotham et
al. 2007).
Relationship to Ecosystem Services
The domain of safety and security is frequently evaluated using violent crime and property crime rates
combined with measures of perceived neighborhood safety. Green spaces in urban areas have been linked to
a reduction in neighborhood crime, especially in inner city neighborhoods (Kuo and Sullivan 2001). Urban
green spaces provide opportunities for simultaneous users and
increased throughput which in combination deter criminal behavior;
however, densely vegetated areas often evoke feelings of insecurity
(Kuo and Sullivan 2001, Kuo 2010). In some cases, natural areas
appreciated for aesthetic and therapeutic value and recreational
opportunities may also be perceived by some as "scary" places,
concealing criminal activities or harboring dangerous animals,
poisonous plants, and vector borne disease (Louv 2005, Milligan and
Bingley 2007). In reference to accident-related injuries, more
specifically traffic accidents, there are opposing views on the role of
roadway vegetation. Roadside aesthetic appeal has been reported to
positively affect driver behavior by promoting a calming effect and
reducing speeding and driver fatigue (Cackowski and Nasar 2003). Conversely, traffic engineers and city
planners purport that roadside vegetation introduces collision hazards, reduces traffic visibility, and distracts
drivers (Wilde 2010). Similarly, public perceptions may present conflicting valuations of ecosystems such as
wetlands, which are valued for species diversity, habitat and recreational areas, but also depreciated because
of associated vector borne diseases such as West Nile virus (Barbier et al. 1997).
Because of the multitude of conflicting perceptions, the fear of nature and lack of public knowledge regarding
ecosystem goods and services benefits, the evaluation of the contribution of ecosystems to safety and
security is not as clear cut as the influence of economic and social drivers. However, clarifying these
relationships through education and inclusion of public perception and preferences could help mitigate these
differences towards a better understanding of the linkages between ecosystems and the domains of well-
being. A common understanding of nature's benefits is vital to sustainable well-being.
Courtesy of Microsoft.com
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Indicator; Actual Safety
Property Crime
Metric Variable: PROPCRIME
Source: National Archives of Criminal Justice Data
Source Question or Measurement: NACJD variables BURGLRY, LARCENY, MVTHEFT, ARSON, Number of
burglary, larceny, motor vehicle theft, and arson offenses
Alternate Source: N/A
Years Available: 2000-2005, 2008
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the total (sum) number of property crimes per 100,000 people.
Population estimates were provided by the NACJD (variable CPOPCRIM) and reflect the total population
served by reporting agencies.
Violent Crime
Metric Variable: VIOLCRIME
Source: National Archives of Criminal Justice Data
Source Question or Measurement: NACJD variables MURDER, RAPE, ROBBERY, AGASSLT, Number of murder,
rape, robbery, and aggravated assault offenses
Alternate Source: N/A
Years Available: 2000-2005, 2008
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the total (sum) number of violent crimes per 100,000 people. Population
estimates were provided by the NACJD (variable CPOPCRIM) and reflect the total population served by
reporting agencies.
50
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Indicator; Actual Safety (continued)
Loss of Human Life
Metric Variable: NATMAZH LOSS
Source: University of South Carolina, Hazards and Vulnerability Research Institute
Source Question or Measurement: SHELDUS dataset, Fatalities and injuries from hazardous weather
Alternate Source: N/A
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the number of fatalities and injuries from hazardous weather per 100,000
population
Accidental Morbidity and Mortality
Metric Variable: ACCMM
Source: CDC-Compressed Mortality Files
Source Question or Measurement: Number of deaths due to external causes (ICD-10 Group Codes V01
through Y89), excluding deaths caused by natural hazards and intentional deaths (ICD-10 group codes X30-
X39, X60-X84, Y85-Y89)
Alternate Source: N/A
Years Available: 2000-2010
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the number of deaths per 100,000 population that were accident-related
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Indicator; Risk
Social Vulnerability to Environmental Factors
Metric Variable: SOVI
Source: University of South Carolina, Hazards and Vulnerability Research Institute
Source Question or Measurement: Social Vulnerability Index (SoVI®) for the United States, SoVI Score. This
index estimates a population's ability to prepare for, respond to, and recover from environmental hazards.
Higher scores indicate more vulnerability.
Alternate Source: N/A
Years Available: 2000, 2007, 2008 (*2007 and 2008 data points reflect aggregate 2005-09 and 2006-10
indices, respectively)
Smallest Geospatial Level Available: County
Calculation Methods: N/A
Indicator; Perceived Safety
Community Safety
Metric Variable: PRCVDSAFE
Source: Gallup Healthways
Source Question or Measurement: Gallup variable WP113, Do you feel safe walking alone at night in the city
or area where you live?
Alternate Source: N/A
Years Available: 2009
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of people who responded "Yes"
52
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Domain: Social Cohesion
• Social Support
HSocial Engagement
H Attitude towards Others and the Community
B Family Bonding
M Democratic Engagement
53
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Social Cohesion
The ties that bind humans together in society have a large bearing on our personal well-being and the well-
being of our community (Putnam 2000, Smith 2003). A social network propagates opportunities to enhance
the quality of life to all of its members, and creates a safety net for difficult times. A cohesive community
allows open discussion and resolution of difficult problems, and gives its members a sense of identity
(Jeannotte et al. 2002). Social participation of all concerned
citizens is essential to obtaining environmental well-being
(Mann 1992). Indicators of social cohesion vary greatly, with
the most common indicator being volunteering rates.
Measures of the health of one's social network typically
revolved around qualitative assessments of existing
relationships and quantitative assessments of the size of the
network. Feelings and behaviors associated with trust and
reciprocity are often used as a proxy for community cohesion.
Divorce rates, migration patterns, family demographics, and
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charitable contributions were some of the more objective
,'-'. ^^K m. i^| measures used to measure cohesiveness.
Courtesy ofiStockphoto.com
Social services can establish social norms that promote cohesion, repair and strengthen family cohesion, and
provide safe, equitable working environments which foster healthy coworker relationship development.
Economic services impact social cohesion by creating equitable wages and redistributing wealth, thereby
relieving tensions between different social-economic classes (Rupasingha et al. 2006), and they allow
businesses to generate excess revenue to be given back to the community.
Relationship to Ecosystem Services:
Greenspace and access to nature promote pro-social behavior
and help mitigate some of the negative antisocial behaviors
associated with crowding and urbanization (Kuo and Sullivan
2001, Kuo 2010). Natural spaces within communities afford
people opportunities to interact with others beyond their own
family dynamics through proximate open areas reserved for
recreational and cultural activities, such as festivals and picnics.
A healthy natural environment also helps provide a sense of
community by enhancing feelings of pride and a stronger sense
of kinship among its citizens who share the common goal of
making their community a better place to live (EPA 1997).
^^H
Courtesy of Microsoft.com
54
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Indicator; Social Engagement
Participation in Group Activities
Metric Variable: GRPACTV
Source: General Social Survey
Source Question or Measurement: GSS variable MEMNUM, Could you tell me whether or not you are a
member of any type of organization?
Alternate Source: N/A
Years Available: 2004
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of people who are members of one or more groups
Volunteering
Metric Variable: VOLNTR
Source: Bureau of Labor Statistics and the U.S. Census- Volunteering in America
Source Question or Measurement: Volunteer rate (equals the percentage of Current Population Survey
respondents who reported that they had performed any unpaid volunteer work)
Alternate Source: N/A
Years Available: 2002-2009
Smallest Geospatial Level Available: State
Calculation Methods: N/A
55
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Indicator; Social Engagement (continued)
••
Children Participating in Organized, Extracurricular Activities _
Metric Variable: CHLDACTV
Source: U.S. Department of Health and Human Services- National Survey of Children's Health
Source Question or Measurement: Percentage of children aged 6-17 years old who participate in one or more
organized activities outside of school
Alternate Course: N/A
Years Available: 2003, 2007
Smallest Geospatial Level Available: State
Calculation Methods: N/A
Indicator; Attitude toward Others and the Community
Trust
Metric Variable: CANTRUST
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable CANTRUST, Generally speaking, would you say that people
can be trusted or that you can't be too careful in dealing with people?
Alternate Source: N/A
Years Available: 2004, 2008
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered "people can almost always
be trusted" and "people can usually be trusted."
56
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Indicator; Attitude toward Others and the Community (continued)
City Satisfaction
Metric Variable: CITYSATIS
Source: Gallup Healthways
Source Question or Measurement: Gallup variable WP83, Are you satisfied or dissatisfied with the city or area
where you live?
Alternate Source: N/A
Years Available: 2009
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered "Satisfied"
Belonging to Community
Metric Variable: CLSETOWN
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable CLSETOWN, How close do you feel to your town or city?
Alternate Source: N/A
Years Available: 2004
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered "Very Close" and "Close"
57
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Indicator; Attitude toward Others and the Community (continued)
Discrimination
Metric Variable: DISCRM2
Source: Centers for Disease Control and Prevention (CDC)- Behavioral Risk Factor Surveillance System
Source Question or Measurement: CDC Variable RREMTSM1, Within the past 12 months on average, how
often have you felt emotionally upset, for example angry, sad, or frustrated, as a result of how you were
treated based on your race?
Alternate Source: N/A
Years Available: 2005-2006
Smallest Geospatial Level Available: County
Calculation Methods: Calculated as the percentage of respondents who answered anything except
"Never" (CDC)
Helping Others
Metric Variable: HELPFUL
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable HELPFUL, Would you say that most of the time people try to
be helpful, or that they are mostly just looking out for themselves?
Alternate Source: N/A
Years Available: 2000-2008; biennial
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of people who responded "Try to be helpful"
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Indicator; Family Bonding
Parent-child Reading Activities
Metric Variable: CHLDREAD
Source: Bureau of Labor Statistics- American Time Use Survey
Source Question or Measurement: Adults reading to children identified by activity codes 030102 and 040102.
Alternate Source: N/A
Years Available: 2002-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of parent-child reading activity duration from total
activities duration
Exceeded Screen Time Guidelines
Metric Variable: WATCHTV
Source: Centers for Disease Control and Prevention- Youth Risk Behavior Surveillance System
Source Question or Measurement: Percentage of children in grades 9-12 who watch television 3 or more
hours per day
Alternate Source: N/A
Years Available: 2001-2009; biennial
Smallest Geospatial Level Available: State
Calculation Methods: N/A
59
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Indicator; Family Bonding (continued)
•
Frequency of Meals at Home
Metric Variable: MEALS
Source: Bureau of Labor Statistics- American Time Use Survey
Source Question or Measurement: Time spent by children, aged 15-17 years old, eating at home with their
parents, identified by activity codes llxxxx (where "xx" indicates any numbers to complete the 6-digit activity
code from the coding lexicon).
Alternate Source: N/A
Years Available: 2003-2009
Smallest Geospatial Level Available: State
Calculation Methods: Calculated as the percentage of time spent eating at home with parents by children
(aged 15-17) from the child's total eating time
Indicator; Democratic Engagement
Trust in Government
Metric Variable: TRUSTGOV
Source: American National Election Study (ANES)
Source Question or Measurement: ANES Variable VCF0604, People have different ideas about the
government in Washington. These ideas don't refer to Democrats or Republicans in particular, but just
government in general. We want to see how you feel about these ideas. How much of the time do you think
you can trust the government in Washington to do what is right-just about always, most of the time, only
some of the time?
Alternate Source: General Social Survey (GSS) variable POLEFF17, Most government administrators can be
trusted to do what is best for the country.
Years Available: 2000-2008; biennial
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered "Most of the time" or "Just
about always" for the variable VCF0604 (ANES), and the percentage of respondents who answered "Strongly
agree" or "Agree" for the variable POLEFF17 (GSS).
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Indicator; Democratic Engagement (continued)
VOTE
*****
Voter Turnout
Metric Variable: VOTRTOUT
Source: U.S. Census Bureau- Current Population Survey
Source Question or Measurement: Percentage of U.S. citizens aged 18 and older that voted
Alternate Source: N/A
Years Available: 2000-2008; biennial
Smallest Geospatial Level Available: State
Calculation Methods: N/A
Interest in Politics
Metric Variable: POLINTRST
Source: American National Election Study (ANES)
Source Question or Measurement: ANES variable VCF0310, Some people don't pay much attention to political
campaigns. How about you, would you say that you have been/were very much interested, somewhat
interested, or not much interested in the political campaigns (so far) this year?
Alternate Source: General Social Survey (GSS) variable POLINT and POLINT1, How interested would you say
you personally are in politics?
Years Available: 2000-2008; biennial
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of people who answered "Somewhat interested" or "Very
much interested" for variable VCF0310 (ANES). Calculated as the percentage of people who answered "Very
interested", "Fairly interested", or "Somewhat interested" for variable POLINT, and the percentage of people
who answered "Very interested" or "Fairly interested" for variable POLINT1 (GSS).
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Indicator; Democratic Engagement (continued)
Registered Voters
Metric Variable: REGVOTRS
Source: U.S. Census Bureau- Current Population Survey
Source Question or Measurement: Percentage of U.S. citizens aged 18 and older (eligible voters) that are
registered to vote
Alternate Source: N/A
Years Available: 2000-2008; biennial
Smallest Geospatial Level Available: State
Calculation Methods: N/A
Voice in Government Decisions
Metric Variable: VOICENGOV
Source: American National Election Study (ANES)
Source Question or Measurement: ANES Variable VCF0609, Please tell me how much you agree or disagree
with this statement: Public officials don't care much what people like me think.
Alternate Source: General Social Survey (GSS) variable POLEFF11, People like me don't have any say about
what the government does.
Years Available: 2000-2008; biennial
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered "Disagree" for variable
VCF0609 (ANES), and the percentage of respondents who answered "Disagree" or "Strongly disagree" for the
variable POLEFF11 (GSS).
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Indicator; Democratic Engagement (continued)
Satisfaction with Democracy
Metric Variable: SATDEM
Source: General Social Survey (GSS)
Source Question or Measurement: GSS Variable DEMTODAY, How well does democracy work in America
today? On the whole, on a scale of 0 to 10 where 0 is very poorly and 10 is very well. GSS Variable SATDEMOC,
On the whole, are you very satisfied, fairly satisfied, not very satisfied, or not at all satisfied with the way
democracy works in the United States?
Alternate Source: N/A
Years Available: 2000, 2004
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered 6 through 10 for the
variable DEMTODAY, and "very satisfied" and "fairly satisfied" for the variable SATDEMOC
Indicator; Social Support
Close Family and Friends
Metric Variable: CLSFRNDFAM
Source: General Social Survey (GSS)
Source Question or Measurement: GSS variable NUMPROBS, Of these (NUMCNTCT) friends and relatives,
about how many would you say you feel really close to, that is close enough to discuss personal or important
problems with? (variable NUMCNTCT: Not counting people at work or family at home, about how many other
friends or relatives do you keep in contact with at least once a year?).
Alternate Source: N/A
Years Available: 2002
Smallest Geospatial Level Available: GSS Region
Calculation Methods: Calculated as the percentage of respondents who answered 6 or more friends or
relatives
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Summary Table of Data and Available Spatial Scales
DOMAIN
Connection to Nature
Cultural Fulfillment
Education
Health
INDICATOR
Biophilia
Activity Participation
Basic Educational Knowledge
and Skills of Youth
Participation and Attainment
Social, Emotional and
Developmental Aspects
Healthcare
Life Expectancy and Mortality
Lifestyle and Behavior
Personal Well-being
Physical and Mental Health
Conditions
METRIC
Connection to Life
Spiritual Fulfillment
Performing Arts Attendance
Rate of Congregational Adherence
Mathematics Skills
Reading Skills
Science Skills
Adult Literacy
High School Completion
Participation
Post-Secondary Attainment
Bullying
Child Physical Health
Social Relationships and Emotional Well-being
Preprimary Education and Care
Population with a Regular Family Doctor
Satisfaction with Healthcare
Asthma Mortality
Cancer Mortality
Diabetes Mortality
Heart Disease Mortality
Infant Mortality
Life Expectancy
Suicide Mortality
Alcohol Consumption
Healthy Behaviors Index
Teen Pregnancy
Teen Smoking Rate
Happiness
Life Satisfaction
Perceived Health
Adult Asthma Prevalence
Cancer Prevalence
Childhood Asthma Prevalence
Depression Prevalence
Diabetes Prevalence
Heart Attack Prevalence
Coronary Heart Disease Prevalence
Obesity Prevalence
Stroke Prevalence
METRIC
VARIABLE
ALLOFLFE
BEAUSPRT
PERARTS
TOTRATE
MATHTEST
READTEST
SCITEST
ADULTLIT
HSGRAD
PARTNEDU
UNIVGRAD
BULLY
CHLDHLTH
CHLDSOCIAL
CON FACT
FAMDOC
SATISHLTHC
ASTHMORT
CANCMORT
DIABMORT
HRTDISMORT
INFMORT
LIFEXPCT
SUICDMORT
ALCOHOL
HBI
TEENPREG
TEENSMK
HAPPY
LIFESATIS
PRCVDHLTH
ADLTASTHMA
CANCER
CHLDASTHMA
DEPRESSION
DIABETES
HRTATTACK
HRTDISEASE
OBESITY
STROKE
LOWEST AVAILABLE
SCALE
COUNTY
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
LU
1
X
X
X
X
X
X
X
X
X
X
X
REGION
X
X
64
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Summary Table of Data and Available Spatial Scales
(continued)
DOMAIN
Leisure Time
LivingStandards
Safety and Security
Social Cohesion
INDICATOR
Activity Participation
Time Spent
Working Age Adults
Basic Necessities
Income
Wealth
Work
Actual Safety
Perceived Safety
Risk
Attitude toward Others and
the Community
Democratic Engagement
Family Bonding
Social Engagement
Social Support
METRIC
Physical Activity
Average Nights on Vacation
Leisure Activities
Adults Working Long Hours
Adults Working Standard Hours
Adults who Provide Care to Seniors
Food Security
Housing Affordability
Median Household Income
Incidence of Low Income
Persistence of Low Income
Median Home Value
Mortgage Debt
Job Quality
Job Satisfaction
Accidental Morbidity and Mortality
Loss of Human Life
Property Crime
Violent Crime
Community Safety
Social Vulnerability to Environmental Factors
Trust
City Satisfaction
Belonging to Community
Discrimination
Helping Others
Interest in Politics
Registered Voters
Satisfaction with Democracy
Trust in Government
Voice in Government Decisions
VoterTurnout
Parent-child Reading Activities
Frequency of Meals at Home
Exceeded Screen Time Guidelines
Participation in Organized, Extracurricular Activities
Participation in Group Activities
Volunteering
Close Friends and Family
METRIC
VARIABLE
PHYSACTIV
VACATION
LEISURE
LONGWRKHRS
NORMWRKHRS
SENIORCARE
FOODSECURE
HOMEAFFORD
MEDINCOME
POVERTY
POVPERSIST
HOMEVAL
MTGDEBT
JOBLOSE
J DBS ATI S
ACCMM
NATHAZHLOSS
PROPCRIME
VIOLCRIME
PRCVDSAFE
SOVI
CANTRUST
CITYSATIS
CLSETOWN
DISCRM2
HELPFUL
POLINTRST
REGVOTRS
SATDEM
TRUSTGOV
VOICENGOV
VOTRTOUT
CHLDREAD
MEALS
WATCHTV
CHLDACTV
GRPACTV
VOLNTR
CLSFRNDFAM
LOWEST AVAILABLE
COUNTY
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
LU
1
X
X
X
X
X
X
X
X
X
X
X
X
X
REGION
X
X
X
X
X
X
X
X
X
X
X
65
-------
Constructing the Composite Index of Well-being
Composite score
Well-being Index
Elements
Specific measurements
Domains
Indicators
Normalizing and Imputing Metric Values
Based on the distribution of data for each metric and the variety of metric units, we elected to use the
normalization procedure used by the Organisation for Economic Co-operation and Development (OECD) Better
Life Index (OECD 2011).
Normalization is done using OECD's formula which converts the original values of the metrics into proportions
that range between 0 (for the worst possible outcome) and 1 (for the best possible outcome). The formula is:
(value to convert - minimum value) / (maximum value - minimum value)
When an metric measures a negative component of well-being the formula used is:
1 - (value to convert - minimum value) / (maximum value - minimum value)
Prior to normalization, we identified outlying values falling beyond the far fences of a box-and-whisker plot
(i.e. less/greater than 3 interquartile ranges from the 1st and 3rd quartiles, respectively). We set the minimum
and maximum values to the lowest and highest values within the far fences, and set the identified outliers to
these extremes. Finally, normalized values were linearly rescaled between 0.1 and 0.9 (rescaled
value=.8*'normalized value + .1) to allow for potential improvements and declines beyond what was observed
in the data.
A mean value imputation method was used as a substitute for missing county-level metric data points. County
groupings were created based on a combination of the Rural-Urban Continuum Code (RUCC) classifications
(USDA, 2013) and the Gini Index (GINI) for household income inequality quintile bandings (US Census, 2012).
This RUCC-GINI combination helped to account for the relative spatial relationship of a county to the nearest
large urban center and its measured income dispersion. A mean value was calculated across all years where
metric data were available and within each RUCC-GINI band in an effort to calculate imputed metric values
using data from counties exhibiting similar characteristics. In the few cases where data were not available
within a RUCC or GINI delineation, a county's related state or GSS region data were used to substitute for
missing values, as appropriate.
66
-------
Constructing the Composite Index of Well-being
(continued)
Calculating the Domain Score
The mean of the normalized metric values are used to calculate the individual indicator scores. Domain scores
are then calculated as the sum of the indicator scores divided by the total possible score for all the indicators
in that domain. The domain score is weighted by the contribution of the domain to the elements based on
relative importance values (RIVs) and prioritization weights.
Domain and Element Weights
The approach used to develop and apply domain and element weights for calculating the composite index of
well-being is outlined in Figure 4. Relative importance values (RIVs) for each of the domains were derived
using qualitative data based on professional opinion and public perception. During roundtable discussions,
professionals in relevant fields (e.g., ecology, sociology, etc.) assigned RIVs to relationships between each
domain and element of well-being based on an ordinal rating scale ranging from 0 (no relationship) to 5 (very
strong relationship). The elements of well-being used to develop these relationships are described in Summers
et al. (2012) and are briefly defined below:
• Economic Well-being—Sense of well-being derived from financial stability
• Environmental Well-being—Sense of well-being derived from having opportunities to experience healthy,
natural environments
• Societal Well-being—A combination of well-being derived from having the opportunity to meet the
requirements for healthy human growth and development (Basic Human Needs) and the perception of life
as a whole based on opportunities and achievements (Subjective Well-being)
:
rofessional Opinion Assigned
Domain-Element RIVs and
Element-Well-being RIVs
Contribution to Well-being
(Target Prioritization Weights)
Prioritization
Weights
t
Professional Opinio
Rank Data for
Domains
• I
Weighted
Element Index
Scores
Prioritization
Weights
ublic Perceptio
Rank Data for
Domains and
Elements
J
Human
Well-being Index
(HWBI)
Figure 4. Steps for deriving relative importance values (RIVs) as domain and element weighting factors for
construction of the human well-being index (HWBI)
67
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Constructing the Composite Index of Well-being
(continued)
Individual researchers in the workgroup were also asked to rank randomly selected groups of domains based
on their perceived contribution to overall well-being. Additional rank data were collected for these same
components utilizing a public perception convenience survey (70 respondents). Prioritization weights were
generated for rank data from both populations using techniques borrowed from the analytic hierarchy process
(Saaty 1980). The weights were combined into a target weight for estimating the contribution of domains to
elements and elements to overall well-being. The differences between the RIV-based calculated contribution
of each component and the target weights was used to derive an adjustment factor which was applied to the
original RIV values resulting in adjusted RIV values for all linkages. From the adjusted RIVs, the estimated
contribution of each domain to each element and of each element to overall well-being was calculated.
Appendix B contains the contribution weights for both the domains and the elements. For detailed
methodology regarding the development of RIVs used for domain and element weights in the construction of
the composite index refer to Smith et al. (2013).
Calculating the Element Index scores and the Composite Index of Well-being
Each domain score is multiplied by the corresponding domain contribution weight resulting in an element
sub-index score. Eight sub-index scores are calculated for each element (one for each domain). The product of
the sub-index scores are calculated for each element to produce the element index score. Each of the element
indices are then multiplied by the corresponding element contribution weight yielding the weighted index
score for each element. The composite index of well-being is the sum of the weighed element scores. The
methods are described for the national scale index, but may be applied at smaller scales where data are
available. The detailed methodologies for constructing the composite index of well-being are illustrated in
Appendix C.
68
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Current Status and Next Steps
Courtesy of iStockphoto
Many obstacles exist in developing comparable measures of human
well-being-lack of consistently available data, transparency of
performance of indicators and domains and cultural differences in
the perception of well-being. We are aware that even within
disciplines, the aggregation of indicators to create an index for
evaluating well-being is highly contentious and that many
researchers argue that summary indices have no value as tools in
policy forums (Booysen 2002, Saltelli 2007). Additionally, lack of
scientific robustness has rendered many sustainability indices
inadequate in the policy arena (Bohringer and Jochem 2007).
Perhaps for these reasons, many well-being measures have been
relegated to specific areas of economic and social policy. However,
composite indices represent an aggregate of the most widely
accepted measurements within a particular discipline (i.e.,
sociology, economics, ecology, health) and the individual indicators
used to develop the composite measure are based on quantitative values, generally recognized qualitative
assessments, and sound methodologies. The ultimate goal of this research is to create a balanced index of
well-being for the U.S that will illustrate the importance of ecosystem services in context of social and
economic drivers which also adequately emphasizes the degree to which environmental factors influence
well-being endpoints.
The majority of the selected metrics and indicators developed for this report represent environmental,
economic and social elements at state and regional scales. We can aggregate information to provide a
national scale picture of well-being for the U.S., but data gaps may present challenges for applying the index
at finer resolutions. The index will be tested within the Sustainable and Healthy Communities Research
Program's place-based projects to identify modifications
that may be needed for application at smaller scales.
Validation of the index in place-based projects will be a
transition of the human well-being research into
community-based sustainability projects. Although the
metrics and indicators may vary depending on scale,
preference and data availability, the domains described for
the index should transcend scale, culture and time.
Relative importance values can be developed at the
community level and applied as weighting factors in index
construction; however, the methodologies described for
constructing the index should not be affected by scale.
Future research will focus on testing and modifying the
index for application in various community typologies, as well as for specific populations (e.g., tribes) and
across generations (inter-generational equity). The suite of human well-being indices are intended to be used
in conjunction with other sustainability measures to provide information to assist communities with selecting
appropriate measures for establishing and evaluating community sustainability goals.
Courtesy of sakhornBS; freedigitalphotos.net
69
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Appendices
75
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Appendix A
Descriptive statistics and histograms used to establish
metric distributions
76
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Connection to Nature
Connection to Life
DOMAIN: Connection to Nature INDICATOR: Biophilia
Spiritual Fulfillment
DOMAIN: Connection to Nature INDICATOR: Biophilia
26 -
20
Sis-
Summary Statistics
N 18
Mean 71.75
Median 72.86
Std Dev 6.78
Range 57.97 to 81.33
6B
Curve:
• Lognormal(Theta=38.6 Shape=0.19 Scale=3.1 B)
XM
NOTE: One outlier observation was excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
Curve:
• Lognormal(Theta=33.1 Shape=0.19 Scale=3.64)
77
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Cultural Fulfillment
Performing Arts Attendance
DOMAIN: Cultural Fulfillment INDICATOR: Activity Participation
Rate of Congregational Adherence
DOMAIN: Cultural Fulfillment INDICATOR: Activity Participation
35
12 -\
\
\
\
\
Summary Statistics
N
Mean
Median
Std Dev
6279
522.2
504.7
184
Range 18.16 to 1925
25 125 225 325 425 525 625 725 B25 925 1025 1125 1225 1325
Metric Value
Curve:
• Lognormal(Theta=-475 Shape=0.18 Scale=6.B9)
Curve:
• Lognormal(Theta=-61 Shape=O.OB Scale=4.71)
NOTE: Seven outlier observations vtere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
78
-------
Education
Mathematics Skills Reading Skills
DOMAIN: Education INDICATOR: Basic Educational Knowledge and Skills of Youth DOMAIN: Education INDICATOR: Basic Educational Knowledge and Skills of Youth
30
25 -
20 ~
10 -
Summary Statistics
N 245
Mean 73.01
Median 75.3
Std Dev 9.943
Range 23.47 to 89.08
Curve:
Metric Value
• Lognormal(Theta=-1E3 Shape=0.01 Scale=7.08)
NOTE: Tvfo outlier observations were excluded prior to histogram construction
and lognorma! estimate: summary statistics include all observations
35 -
30 -
20 -
10 -
5
Summary Statistics
N
Mean
Median
Std Dev
Curve:
>0 55 60 65
Metric Value
• Lognormal(Theta=-1 E3 Shape=0.01 Scale=7.04)
75
Science Skills
DOMAIN: Education INDICATOR: Basic Educational Knowledge and Skills of Youth
30 -I
25
Adult Literacy
DOMAIN: Education INDICATOR: Participation and Attainment
Summary Statistics
N 46
Mean 69.24
Median 70.2
Std Dev 8.453
Range 47.56 to 83.14
30 -
25 -
„ 20 -
15 -
Summary Statistics
N 102
Mean 12.81
Median 12.27
Std Dev 4.419
Range 5.816 to 25.22
Curve:
Metric Value
• Lognormal(Theta=-42 Shape=0.08 Scale=4.71)
Curve:
12 15 18 21
Metric Value
• Lognormal(Theta=1.92 Shape=0.42 Scale=2.3)
79
-------
Education
High School Completion
DOMAIN: Education INDICATOR: Participation and Attainment
Participation
DOMAIN: Education INDICATOR: Participation and Attainment
61.5 64.5 67.5 70.5
Curve:
73.5 76.5 79.5 82.5 85.5 88.5 91.5 94.5 97.5
Metric Value
• Lognormal(Theta=-1 E4 Shape=0 Scale=9.3)
20.0 -
15.0 -
£1°.° -
D_
5.0 -
=]
Summary Statistics
N 510
36.98
36.79
6.186
19.5 22.5 25.5 28.5 31.5 34.5 37.5 40.5 43.5 46.5 49.5 52.5 65.5
Metric Value
NOTE: Three outlier observations v/ere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
Curve:
• Lognormal(Theta=-51 Shape=0.07 Scale=4.47)
Post-Secondary Attainment
DOMAIN: Education INDICATOR: Participation and Attainment
Bullying
DOMAIN: Education INDICATOR: Social, Emotional and Developmental Aspects
3.75 8.75 13.75 18.75 23.75 28.75 33.75 38.75 43.75 48.75 53.75 58.75
Metric Value
35 -I
25 -
„ 20 -
Summary Statistics
15 -
10 -
6 7.8 9
Metric Value
M
Mean
Median
Std Dev
Range
193
5.883
5.5
1.951
2.8 to 16.9
10.2 11.4 12.6 13.8
Curve:
• Lognormal(Trieta=0.3 Sliape=0.37 Scale=3.07)
Curve:
• Lognormal(Theta=0.38 Shape=0.32 Scale=1.64)
NOTE: Five outlier obsewations were excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
NOTE: One outlier observation vias excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
80
-------
Education
Physical Health
DOMAIN: Education INDICATOR: Social, Emotional and Developmental Aspects
Social Relationships and Emotional Well-being
DOMAIN: Education INDICATOR: Social, Emotional and Developmental Aspects
35
35
25 -
to
'-
to
D_
15 -
10
Summary Statistics
Curve:
B3 85 87
Metric Value
• Lognormal(Theta=-72 Shape=0.02 Scale=5.06)
Curve:
89.25 90.75 92.25 93.
Metric Value
• Lognormal(Tlieta=-32 Shape=0.02 Scale=4.83)
95.25
81
-------
Health
Population with a Regular Family Doctor
DOMAIN: Health INDICATOR: Healthcare
Satisfaction with Healthcare
DOMAIN: Health INDICATOR: Healthcare
51.6 55.2 58.8
Curve:
69.6 73.2 76.8 80.4
Metric Value
87.6 91.2 94.8 98.4
17.5 -
15.0 -
12.5 -
_ 10.0
5.0 -
Summary Statistics
\
N
Mean
Median
Std Dev
Range
3275
65.98
66
8.424
21 .33 to 96
33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 99
Metric Value
• Lognorrnal(Theta=-5E4 Shape=0 Scale=10.8)
Curve:
• Lognormal(Theta=-2E3 Shape=0 Scale=7.42)
NOTE: 177 outlier observations vtere excluded prior to histogram construction
and lognormal estimate: summar/ statistics include all observations
NOTE: Seven outlier observations vtere excluded prior to histogram construction
and Sognormal estimate; summary statistics include all observations
Asthma Mortality
DOMAIN: Health INDICATOR: Life Expectancy and Mortality
Cancer Mortality
DOMAIN: Health INDICATOR: Life Expectancy and Mortality
25 -
3
0.075 0.1050.135 0.165 0.1950.2250.255 0.285 0.3150.345 0.375 0.4050.435 0.465 0.495
Metric Value
; 5 -
r
Summary Statistics
N
Mean
Median
Std Dev
Range
23542
22.8
22.72
3.486
9.707 to 58.1 9
9.9 11.7 13.5 15.3 17.1 18.9 20.7 22.5 24.3 26.1 27.9 29.7 31.5 33.3 35.1
Metric Value
Curve:
• Lognormal(Theta=0.03 Shape=0.4 Scale=-1.9)
Curve:
• Lognormal(Theta=-52 Shape=0.04 Scale=4.31)
NOTE: 10 outlier observations vtere excluded prior to histogram construction
and lognormal estimate; summar/ statistics include all observations
NOTE: 72 outlier observations were excluded prior to histogram construction
and lognormal estimate; summary statistics include all observations
82
-------
Health
Diabetes Mortality
DOMAIN: Health INDICATOR: Life Expectancy and Mortality
Heart Disease Mortality
DOMAIN: Health INDICATOR: Life Expectancy and Mortality
0.25 0.75 1.25 1.75 2.25 2.75 3.25 3.75 4.25 4.75 5.25 5.75 6.25 6.75 7.25 7.75 8.25
Metric Value
8
L
I
\
s,
Summary Statistics
N 23963
Mean 27.14
Median 26.85
Std Dev 4.933
Range 10.35to64.47
10.5 13.5 16.5 19.5 22.5 25.5 2B.5 31.5 34.5 37.5 40.5 43.5 46.5
Metric Value
Curve:
• Lognormal(Theta=-.oe Shape=0.32 Scale=1.2)
Curve:
• Lognormal(Theta=-16Shape=0.11 Scale=3.76)
NOTE: 102 outlier observations were excluded prior to histogram construction
and lognormal estimate: summary statistics include ail observations
NOTE: 32 outlier observations were excluded prior to histogram construction
and lognormal estimate: summar/ statistics include all observations
Infant Mortality
DOMAIN: Health INDICATOR: Life Expectancy and Mortality
Life Expectancy
DOMAIN: Health INDICATOR: Life Expectancy and Mortality
14 -
12 -
\
\
\
96 112 128
Metric Value
Summary Statistics
N 4775
Mean 82.55
Median 75.56
Std Dev 34.55
Range 21.31 to 649.4
\
rb-^^—
10 -
144 160 176
Summary Statistics
N 24960
Mean 76.6
Median 76.69
Std Dev 2.217
Range 63.39 to 92.31
f
66.25 67.75 69.25 70.75 72.25 73.75 75.25 76.75 78.25 79.75 81.25 82.75 84.25 85.75 87.25
Metric Value
Curve:
• LognQrmai(Theta=6.44 Shape=Q.39 Scale=4.24)
Curve:
- l_ognorma!(Theta=-3E3 Shape=Q Scale=8.17)
NOTE: 40 outlier observations were excluded prior to histogram construction
and lognorma! estimate: summary statistics include all observations
NOTE: Seven outSier observations v/ere excluded prior to histogram construction
and Sognorma! estimate: summary statistics include all observations
83
-------
Health
Suicide Mortality
DOMAIN: Health INDICATOR: Life Expectancy and Mortality
Alcohol Consumption
DOMAIN: Health INDICATOR: Lifestyle and Behavior
12
10 -
6 -
2
J
Jf
1
/
L
Summary Statistics
1
I
n
r
— i
x
(T
N 61 70
^
Mean 1.642
Median 1.484
V| Std Dev 0.746
\
y Range 0,267 to 15.11 |
\
\
\
\
PL
rrttT^^—
0.3 0.6 0.9 1.2 1.5 1.8 2.1 2.4
Metric Value
3.3 3.6 3.9 4.2
8 -
6 -
03
£4
2 -
A \L
T \
r
\
\
M
Summary Statistics
N
Mean
Median
Std Dev
Range
14617
7.565
7.273
4.B07
0 to 100
3.6 5.2 6.8 8.4 10 11.6 13.2 14.8 16.4 18 19.6 21.2 22.8 24.4 26
Metric Value
Cuive:
• Lognormal(Theta=-.02 Shape=0.37 Scale=0.42)
Curve:
• Lognormal(Theta=-17 Shape=0.17 Scale=3.2)
NOTE: 48 outlier observations were excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
NOTE: 50 outlier observations v/ere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
Healthy Behaviors Index
DOMAIN: Health INDICATOR: Lifestyle and Behavior
Teen Pregnancy
DOMAIN: Health INDICATOR: Lifestyle and Behavior
14 -
12 -
10 -
s
\
33 37 41 45 49 53
57 61 65 69
Metric Value
77 81 85 89 93
Curve:
• Lognormal(Theta=-2E4 Shape=0 Scale=9.9)
NOTE: 150 outlier observations were excluded prior to histogram construction
and lognormal estimate: summar/ statistics include all observations
12 -f
10
O)
% 6
4
2 -
Summary Statistics
N 4515
Mean 10.14
Median 10.19
Std Dev 3.761
Range 1.061 to 22.88
0.5 2.5 4.5 6.5 8.5 10.5 12.5 14.5 16.5 18.5 20.5 22.5
Curve:
• Lognormal(Theta=-58 Shape=0.06 Scale=4.22)
84
-------
Health
35 -"
30 -
15 -
5
Teen Smoking Rate
DOMAIN: Health INDICATOR: Lifestyle and Behavior
Summary Statistics
N 195
Mean 10.35
Median 9.35
Std Dev 4.244
Range 2.12 to 24.02
-1.25 1.25 3.75 6.25 8.75 11.25 13.75 16.25 18.75 21.25 23.75
Metric Value
Curve:
• Lognormal(Theta=-2.6 Shape=0.32 Scale=2.51)
Happiness
DOMAIN: Health INDICATOR: Personal Well-being
10
2
Summary Statistics
N
Mean
Median
Std Dev
Range
3153
87.93
89.14
9.924
0 to 100
72 76
Metric Value
88
\
\
Curve:
• Lognormal(Theta=-1 E4 Shape=0 Scale=9.26)
AIOTE: 36 outlier observations were excluded prior to histogram construction
and Iognormal estimate: summary statistics include alt observations
\
100
15.0 1
Life Satisfaction
DOMAIN: Health INDICATOR: Personal Well-being
76 77.6 79.2 80.8 82.4
85.6 87.2 88.8 90.4 92
Metric Value
93.6 95.2 96.8 98.4 100
Curve:
• Lognormal(Theta=-4E4 Shape=0 Scale=10.5)
NOTE: 583 outlier observations were excluded prior to histogram construction
and Iognormal estimate: summary statistics include all observations
Perceived Health
DOMAIN: Health INDICATOR: Personal Well-being
0>
" 4 -
nl ^
Summary Statistics
N
Mean
Median
Std Dev
Range
18652
79.31
81
10.52
0 to 100
I
39.75 44.25 48.75 53.25 57.75 62.25 66.75 71.25 75.75 80.25 84.75 89.25 93.75 98.25
Metric Value
Curve:
- Lognormal(Theta=-6E4 Shape=Q Scale=11)
NOTE: 125 outfier observations were excluded prior to histogram construction
and iognormat estimate: summary statistics include afi observations
85
-------
Health
Adult Asthma Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
Cancer Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
2.4 4.8
Curve:
12 14.4 16.8 19.2 21.6 24 26.4 28.8 31.2
Metric Value
• LognormahTheta=-486 Shape=0.01 Scale=6.21)
8
\
\
\
\
Summary Statistics
N 5998
Mean 11.21
Median 10.26
Std Dev 9.464
Range C to 100
0.75 3.75 6.75 9.7512.7515.7518.7521.7524.7527.7530.7533.7536.7539.7542.75
Metric Value
Curve:
• Lognormal(Theta=-16 Shape=0.27 Scale=3.25)
NOTE: 190 outlier obseivations v/ere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
NOTE: 55 outlier observations were excluded prior to histogram construction
and lognormal estimate: summar/ statistics include all observations
Childhood Asthma Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
Depression Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
15.0 -
12.5
10.0 -
|
I 7.5 -
D-
5.0 -
2.5 -
n -
'
r nary Statistics
8109
Mean 14.44
Median 13.62
Std Dev 11.52
Range 0 to 100
X"
/
/
/
/
jf
-
—
—
•^*
s
-
s
~~
s
s
s
X.
s
V.
FTJT^^^^. n
-1.5 1.5 4.5 7.510.513.516.519.522.525.528.531.534.537.540.543.546.549.5
Metric Value
12 -
10 -
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52
Metric Value
Curve:
• Lognormal(Theta=-25 Shape=0.24 Scale=3.64)
Curve:
• Lognormal(Theta=-76 Shape=0.1 Scale=4.53)
NOTE: 66 outlier observations were excluded prior to histogram construction
and lognormal estimate: summar/ statistics include all observations
NOTE: 53 outlier observations were excluded prior to histogram construction
and lognormal estimate: summar/ statistics include all observations
86
-------
Health
Diabetes Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
Heart Attack Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
-1 1
\i
\
TV
Curve:
11 13 15 17 19 21 23 25 27 29 31 33 35
Metric Value
• Lognorma!(Theta=-16 Shape=0.21 Scale=3.27)
ram construction
t: 178 outlier observations were excluded prior to histogram construc
and lognormal estimate: summary statistics include ail observations
Summary Statistics
N
Mean
Median
Std Dev
Range
15375
6.318
5.556
5.321
0 to 1 00
0 1.2 2.4 3.6 4.8 6 7.2 8.4 9.6 10.8 12 13.214.415.616.8 18 19.220.421.1
Metric Value
Curve:
• Lognormal(Theta=-8.2 Shape=0.27 Scale=2.61)
NOTE: 202 outlier observations v«re excluded prior to histogram construction
and lognormal estimate: summary statistics include ail observations
Coronary Heart Disease Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
Obesity Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
Summary Statistics
H
Mean
Median
Std Dev
Range
12267
6.595
5.963
5.056
0 to 100
Curve:
4.2 5.4 6.6 7.8 9 10.211.412.613.8 15 16.217.418.619.8 21
Metric Value
— Lognormal(Theta=-11 Shape=0.2 Scale=2.9)
12
10 -
4
Summary Statistics
N
Mean
Median
Std Dev
Range
15690
27.17
27.22
3.816
11.5 to 43.9
12.814.4 16 17.6 19.220.S 22.4
M 25.627.228.830.4 32 33.635.236.838.4 40 41.6
Metric Value
Curve:
• l_Dgnormal(Trieta=-8E3 Shape=Q Scale=8.97)
NOTE: 122 outlier observations were excluded prior to histogram construction
and lognorma! estimate: summary statistics include alt observations
NOTE: 22 outlier observations vtere excluded prior to histogram construction
and lognormal estimate: summar/ statistics include ail observations
87
-------
Health
Stroke Prevalence
DOMAIN: Health INDICATOR: Physical and Mental Health Conditions
12 -
10 11 12 13 14 15 16
Curve:
Metric Value
• Lognormal(Theta=-4.1 Shape=0.35 Scale=2.03)
NOTE: 115 outlier observations viere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
88
-------
Leisure Time
Average Nights on Vacation
DOMAIN: Leisure Time INDICATOR: Activity Participation
Leisure Activities
DOMAIN: Leisure Time INDICATOR: Time Spent
30 -f
20 -
5 -
Summary Statistics
305
4.62S
4.363
1.564
2 to 19.25
2.7
Cuive:
33
3.9
4.5 5.1 5.7
Metric Value
6.3
6.9
8.1
• Lognormal(Theta=0.03 Shape=0.22 Scale=1.47)
NOTE: Seven outlier observations vtere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
20 -
15-
10
5
Summary Statistics
210 225 240 255 270 285 300 315 330 345 360 375 390
Metric Value
Curve:
• Lognormal(Theta=-78 Shape=0.06 Scale=5.94)
NOTE: One outlier observation vtas excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
35 -
30 -
25 -
20 -
10 -
Adults Working Long Hours
DOMAIN: Leisure Time INDICATOR: Working Age Adults
Summary Statistics
N
Mean
Median
14.48
14.17
Std Dev 3.454
'***\ Range
\
\
\
\
s
4.1671032.35
"V^
Curve:
10 12 14 16 18 20 2
Metric Value
• Lognormal(Theta=-13 Shape=0.11 Scale=3.3)
Adults Working Standard Hours
DOMAIN: Leisure Time INDICATOR: Working Age Adults
35
25 -
, 20 -
10 -
Summary Statistics
N
Mean
Median
Std Dev
Range
Curve:
60 63
Metric Value
• Lognormal(Theta=-115 Shape=0.02 Scale=5.2)
NOTE: Three outlier observations were excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
NOTE: One outlier observation v/as excluded prior to histogram construction
and lognormal estimate; summary statistics include all observations
89
-------
25 H
Leisure Time
Adults who Provide Care to Seniors
DOMAIN: Leisure Time INDICATOR: Working Age Adults
Curve:
10 12 14 16
Metric Value
• Lognormal(Theta=-7.8 Shape=0.26 Scale=2.66)
NOTE: Five outlier observations vtere excluded prior to histogram construction
and Sognormal estimate: summary statistics include all observations
90
-------
Living Standards
Food Security
DOMAIN: Living Standards INDICATOR: Basic Necessities
22.5 -
17.5 -
t=12.5
7.5 -
79.5 81 82.5 84 85.5 87 88.5 90 91.5 93 94.5
Metric Value
Curve: — Lognornial(Theta=-43 Shape=0.02 Scale=4.87)
7
5
S4
D_
3
2 -
Median Household Income
DOMAIN: Living Standards INDICATOR: Income
Summary Statistics
750 6750 12750 18750 24750 30750 36750 42750 48750 54750 60750 66750 72750 7875C
Metric Value
Curve:
• Lognurmal(Theta=-2E4 Shape=0.17 Scale=10.9)
NOTE: 200 outlier observations were excluded prior to histogram construction
and lognormal estimate' summar/ statistics include all observations
7
6 -
5 -
4
2
0
Incidence of Low Income
DOMAIN: Living Standards INDICATOR: Income
Summary Statistics
H
Mean
Median
Std Dev
Range
31430
14.51
13.5
5.97
Oto62
9.2 11.6 14 16.4 18.8 21.2 23.6
Metric Value
!6 28.4 30.8 33.2 35.6 38
Curve:
• Lognormal(Theta=-5.4 Shape=0.28 Scale=2.95)
NOTE: 80 outlier observations were excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
40 1
35 -
25 -
£ 20 -
15 -
Persistence of Low Income
DOMAIN: Living Standards INDICATOR: Income
8
10
Curve:
Metric Value
• Lognormal(Theta=-1 .4 Shape=0.33 Scale=1 .93)
91
-------
Living Standards
Median Home Value
DOMAIN: Living Standards INDICATOR: Wealth
15.0 -
10.0 -
2.5 -
0 -J-
\
40000
1E5
Curve:
16E4
28E4 34E4
Metric Value
Summary Statistics
4172
194E3
155E3
118E3
53100 to923E3
4E5
46E4
52E4
• Lognormal(Theta=45E3 Shape=0.65 Scale=11.6)
NOTE: 89 outlier observations v/ere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
17.5 -
„ 10.0
2.5 -
Mortgage Debt
DOMAIN: Living Standards INDICATOR: Wealth
30 32 34 36 38 40 42 44
48 50 52 54 56 58 60 62 64
Metric Value
68 70 72 74
Curve:
• Lognormal(Trieta=-42 Shape=0.06 Scale=4.53)
NOTE: Six outlier observations v/ere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
Job Quality
DOMAIN: Living Standards INDICATOR: Work
40
35 -
Curve:
Metric Value
• Lognormal(Tlieta=-18 Shape=0.05 Scale=4.67)
Job Satisfaction
DOMAIN: Living Standards INDICATOR: Work
35 -
30 -
25 -
20 -
10 -
Summary Statistics
N 3087
Mean 91.58
Median 92.31
StdDev 9.454
Range 0 to 100
Curve:
• Lognormal(Theta=-1 E4 Shape=0 Scaie=9.48)
NOTE: 29 outlier observations v/ere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
92
-------
Safety and Security
Loss of Human Life
DOMAIN: Safety and Security INDICATOR: Actual Safety
Property Crime
DOMAIN: Safety and Security INDICATOR: Actual Safety
100 -
80 -
60 -
0>
oi
D_
40 -
20 -
n -
Summary Statistics
N 25272
Mean 3.876
Median 0
Std Dev 100.3
Range 0 to 14493
9 -
g -
7 -
6 -
c 5
a)
n
^4 -
3 -
2 J
Hy
1
1
7
i
Summary Statistics
_ IN 20040
/
/
/
/
/
/
/
1
' —
/•
"I
Mean 2563
t Median 2266
\
Std Dev 1 588
\
Range 1.978to39405
1
\
\
1
N,
V
N.
\n
*^t
rh^K-i-.
-125 625 1375 2125 2875 3625 4375 5125 5875 6625 7375 8125 8875
-0.03 0.05 0.125 0.2 0.275 0.35 0.425 0.5 0.575 0.65 0.725 0.8 0.875 0.95 1.025
Metric Value
NOTE: 4597 outlier observations were excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
Curve:
• Lognormal(Theta=-1 E3 Shape=0.39 Scale=8.16)
NOTE: 46 outlier observations viere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
Violent Crime
DOMAIN: Safety and Security INDICATOR: Actual Safety
Community Safety
DOMAIN: Safety and Security INDICATOR: Perceived Safety
10 -
N 19550
Mean 305
Median 229.2
Std Dev 284.7
Range 2.472 to 7726
90 180 270 360 450 540 630 720 810 900 990 1080 1170
Metric Value
14 H
12 -
Summary Statistics
N 3096
Mean 76.45
Median 77.44
Std Dev 14.15
Range 0 to 100
/
/
/
7
r
\
\
LI
4
7\
32 36 40 44
52 56 60 64 68 72 76
Metric Value
Curve:
• Lognormal(Theta=-31 Shape=0.7 Scale=5.53)
Curve:
• Lognormal(Theta=-9E3 Shape=0 Scale=9.12)
NOTE: 232 outlier observations were excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
NOTE: 10 outlier observations were excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
93
-------
Safety and Security
Accidental Morbidity and Mortality
DOMAIN: Safety and Security INDICATOR: Actual Safety
Summary Statistics
N
Mean
Median
Std Dev
Range
34518
BO. 93
57.64
1 90.3
0 to 11111
Curve:
60 72 84 96 108 120 132 144 156 168 180 192
Metric Value
• Lognormal(Theta=-4.3 Shape=0.43 Scale=4.11)
NOTE: 1532 outlier observations ivere excluded prior to histogram construction
and lognormal estimate; summary statistics include all observations
94
-------
Social Cohesion
Trust City Satisfaction
DOMAIN: Social Cohesion INDICATOR: Attitude toward Others and the Community DOMAIN: Social Cohesion INDICATOR: Attitude toward Others and the Community
36 -f
30 -
20 -
15 -
Summary Statistics
/
/*•
/
N 18
Mean 48.11
"~-N^ Median 47.94
>v Std Dev 6.863
\
Range 35.37 to 58.1 4
\
\
V
37.5
57.5
Curve:
• LognornialfTheta=22.1 Shape=0.28 Scale=3.22)
14
10 -
Summary Statistics
N
Mean
Median
Std Dev
Range
3097
88.21
89.47
9.187
0 to 100
52 56
60
'2 76 80 84
Metric Value
Curve: — Lognonnal(Trieta=-9E3 Shape=0 Scale=9.06)
NOTE: 28 outlier observations were excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
Belonging to Community Discrimination
DOMAIN: Social Cohesion INDICATOR: Attitude toward Others and the Community DOMAIN: Social Cohesion INDICATOR: Attitude toward Others and the Community
50 T
40 -
30
20 -
76
Curve:
• Lognormal(Theta=48.1 Shape=0.35 Scale=2.96)
35 -|
30 -
25 -
„ 20 -
t:
01
CL
10 -
Summary Statistics
N
Mean
Median
Std Dev
Range
Curve:
B 12 16 20 24
Metric Value
• Lognormal(Theta=-2.6 Shape=0.56 Scale=2.35)
117
11.45
7.874
13.92
0 to 100
NOTE: Three outlier observations vtere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
95
-------
Social Cohesion
Helping Others
DOMAIN: Social Cohesion INDICATOR: Attitude toward Others and the Community
35 -
0
57
Interest in Politics
DOMAIN: Social Cohesion INDICATOR: Democratic Engagement
30 -
25 -
Summary Statistics
N
Mean
34
75.94
Median 76.09
Std Dev 6.39
Range 65.22 to 88.65
10
5
Curve:
• Lognormal(Theta=-75 Shape=0.06 Scale=4.8)
Curve:
72 76 80 84
Metric Value
• Lognormal(Theta=53 4 Shape=0.3 Scale=3.07)
Registered Voters
DOMAIN: Social Cohesion INDICATOR: Democratic Engagement
35 -
30 -
25 -
20 -
10
Satisfaction with Democracy
DOMAIN: Social Cohesion INDICATOR: Democratic Engagement
35 -
30 -
, 20 -
10 -
Summary Statistics
N 18
Mean 74.73
Median 73.74
Std Dev 6.335
Range 62.82 to 84.54
62.5
82.5
Curve:
• Lognormal(Tlieta=-82 Shape=0.04 Scale=5.03)
Curve:
• Lognormal(Theta=49.7 Shape=0.27 Scale=3.19)
96
-------
Social Cohesion
Trust in Government
DOMAIN: Social Cohesion INDICATOR: Democratic Engagement
30 -
25 -
-------
Social Cohesion
Frequency of Meals at Home
DOMAIN: Social Cohesion INDICATOR: Family Bonding
25 H
10 -
Summary Statistics
N 345
Mean 31.77
Median 31.57
StdDev 17.29
Range 0 to 100
32 40 48
Metric Value
64 72
80
Curve:
• Lognormal(Theta=-12e Shape=0.1 Scale=5.07)
NOTE: Three outlier observations v/ere excluded prior to histogram construction
and lognormal estimate: summary statistics include all observations
30 -f
25 -
OJ
CL
10 -
5 -
Exceeded Screen Time Guidelines
DOMAIN: Social Cohesion INDICATOR: Family Bonding
Summary Statistics
17.5 22.5
Curve:
32.5 37.5 42.5
Metric Value
47.5 52.5 57.5
• Lognormal(Theta=-6.2 Shape=0.2 Scale=3.64)
Participation in Organized, Extracurricular Activities
DOMAIN: Social Cohesion INDICATOR: Social Engagement
Participation in Group Activities
DOMAIN: Social Cohesion INDICATOR: Social Engagement
30 -
73.6
Curve:
79.5 82.5
Metric Valu
• Lognormal(Trieta=-24 Shape=0.04 Scale=4.67)
75
Curve:
• Lognormal(Theta=13.4 Shape=0.18 Scale=3.89)
98
-------
Social Cohesion
Volunteering
DOMAIN: Social Cohesion INDICATOR: Social Engagement
Close Friends and Family
DOMAIN: Social Cohesion INDICATOR: Social Support
22.5 -T
20.0
17.5 -
15.0
: 12.5 -
' 10.0 -
7.5 -
5.0 -
2.5 -
Summary Statistics
50 -
40
20 -
10
13.5 16.5 19.5 22.5 25.5 28.5 31.5 34.5 37.5 40.5 43.5 46.5 49.5
Metric Value
56
Cuive:
• Lognormal(Theta=-3.4 Shape=0.18 Scale=3.49)
Curve:
• Lognormal(Theta=25.4 Shape=0.55 Scale=2.62)
99
-------
Appendix B
Contribution weights for domains and elements of
well-being
100
-------
The contribution weights for the domains and elements of well-being were derived using rank data from
professional opinion and public perception and calculated using many steps (see Figure 4, page 67). These
weights were necessary to estimate the final contribution of each domain to each element and of each
element to overall well-being in constructing the composite index, and to ultimately model human well-being
in the United States.
Weighting factors applied to domain scores in the calcuation of element sub-index scores
Domain
Connection to Nature
Cultural Fulfillment
Education
Health
Leisure Time
Living Standards
Safety and Security
Social Cohesion
Economic Well-Being Environmental Well-Being Societal Well-Being
0.087
0.118
0.106
0.190
0.071
0.153
0.166
0.109
0.148
0.030
0.179
0.128
0.143
0.093
0.169
0.110
0.097
0.148
0.088
0.212
0.118
0.103
0.111
0.121
Weighting factors applied to Element scores in the
calculation of the Human Well-being Index (HWBI)
Element Overall Well-being
Economic Well-Being 0.328
Environmental Well-Being 0.313
Societal Well-Being 0.359
101
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Appendix C
Graphical summary of indicator development and
index construction methodologies
102
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Connection to Nature Domain Score and
Element Sub-Index Scores
Biophilia (2)
Environmental
Well-beingScore
(EnWB,)
Connection to
Nature
CON Nat
CON NAT
Biophilia
Spiritual Fulfillment:
Percentageof people \
whoarespiritually
touched bythe beauty
of creation (GSS)
Connection to Life:
Percentageof people
who experience a
connectiontoallof life
(GSS)
103
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Cultural Fulfillment Domain Score and
Element Sub-Index Scores
Activity Participation (2)
Environmental
Well-beingScore
(EnWB8)
CU [_y^1'cu|-T-EnWB
Societal
Well-being Score
(SoWB
Economic
Well-beingScore
(EcWB8)
Performing Arts
Attendance:
Percentage of people
who attended any
performing arts or art
museum/fair/festival
(Surveys of Public
Participation in the
Arts/Census)
•
Adherence: Capture
congregational
membership. (The
Association of Religion
Data Achieves)
104
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Education Domain Score and
Element Sub-Index Scores
Environmental
Well-being Score
(EnWBj)
Societal
Well-beingScore
(SoWBj
EDU
Education
Score
EDU
Economic
Well-being Score
(CCWB2)
lathematics Skills: Average
standardized
m athem atics test scores of
students in grades 4 and 8
(NCES)
Science Skills: Averageof
standardized science test
scores of students in grades
4 and 8(NCES)
Reading Skills: Averageof
standardized reading test
scores of students in grades
4 and 8 (NCES)
Participation and
Attainment
Social, Emotion.
and Developmental
Aspects
High School Completion:
Percentage of population who
obtained a high school diploma or
equivalent (Census)
Participation: Enrollmentrates in
post-secondary education of adults
aged 18-24 years old (Census)
Post-Secondary Attainment:
Percentage of adult population who
obtained a Bachelor's degree or
higher (Census)
Adult Literacy: Percentage of adult
population (aged 16 and older)
lacking basic prose literacy skills
(NCES)
Contextual Factors:
Percentage of children or
parents involved in parent-
child reading activities
(Federal Inter agency Forum
on Children and
Physical Health: Percentage
of children in excellent or
verygood health (HHS)
Social Relationships:
Percentage of children aged
4-7 and 11-14 that have
emotional, social, or
behavioral issues/or that
exhibit positive social
behaviorsfCDC/HHS)
Bullying: Percentage of
children in gr ades 9-12 who
didn'tgo to school because
they felt unsafe (CDC)
105
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Health Domain Score and
Element Sub-Index Scores
• Personal Well-being
y Life Expectancy/Mortality
HPhysical and Mental Health
HLifestyle and Behavior
Healthcare
Environmental
Well-be ingScore
(EnWB4)
Societal
Well-being Score
(SoWB4)
Health
Score
HLTH
Economic
Well-beingScore
(EcWB4)
Perceived Health: Percentage
of people who reported good
health (GSS/Gallup)
Life Satisfaction: Percentage
of people who are satisfied
withtheirlife(Gallup)
Happiness: Percentage of
people who are happy (World
Database of Happiness/GSS)
Disease Prevalence:
Percentage of people with
cancer, diabetes, coronary
heart disease, stroke, heart
attack, adult/childhood
asthma (CDC)
Depression Prevalence:
Percentage of people with
depression (SAMHSA)
Overweight and Obesity
Prevalence: Age-adjusted
prevalence of overweight
and obese adults (CDC)
Life Expectancy:
Average numbers of
life years at birth (CDC)
Infant Mortality:
Infant deaths per 1,000
live births (CDC)
Disease Mortality:
Percentage of deaths
from suicide, cancer,
diabetes, heart
disease, and asthma
(CDC)
106
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Health Domain Score and
Element Sub-Index Scores (continued)
• Personal Well-being
M Life Expectancy/Mortality
H Physical and Mental Health
LJ Lifestyle and Behavior
U Healthcare
Environmental
Well-beingScore
(EnWB4)
HLTH
wt
HLT_POP-EnWB
Societal
Well-beingScore
(SoWB4)
Economic
Well-beingScore
(EcWB4)
H LTH wtHLT-pop-EcWB
Teen smoking: Percentage
of teens who smoke daily
(NIH)
Teen pregnancy:
Percentage of births to
mothers under 18 years
old (CDC)
Healthy Behavior: Index
of healthy behaviors
(Gallup)
Alcohol Consumption:
Percentage of adults who
consume more than one
alcoholic beverages per
day (CDC)
Satisfaction: Percentage
of people satisfied with
hospital stay(HCAHPS)
Family Doctor:
Percentage of people with
a regularfamilydoctor
(Gallup)
107
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Leisure Time Domain Score and
Element Sub-Index Scores
• Activity Participation
_iTime Spent
U Working Age Adults
Environmental
Well-beingScore
(EnWE6)
Societal
Well-being Score
(SoWB6)
LEI
LEI
Leisure Time
Score
LEI TIM
Economic
Well-being Score
(EcWB6)
LEI TIM
Vacation: Aver age numbei of
days on vacation (BLS)
Physical Activity: Parentage of
adults who engaged in regular
leisure time activity (CDC)
Leisure Activities: Percentage-
time spent time on socializing,
relaxing, leisure, and sports
(BLS)
Adults Working Standard
Hours: Percentage ot time that
work and work-related activities
are perform ed between the
hours of 9a.m. and 5 p.m. (BLS)
Adults Working Long Hours:
Percentage of people who work
more than 50 hours per week
(Census)
Adults who Provide Care to
Seniors; Percentage of time
spent in adult care (BLS)
108
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Living Standards Domain Score and
Element Sub-Index Scores
• Wealth
• Income
HWork
_j Basic Necessities
Env ronmental
Well-be ng Score
(EnWB5)
Societal
Well-being Score
|SoW%)
LIV
LIV
Economic
Wei-being Score
Living Standards
Score
LIV STD
LIV STDWW-
Median Household
Income: Household
income at the 50th
percentile (Census)
PersisteiceoHow
Income: Percentage of
the population who
remained below poverty
level [Census and GSS)
lence of Low Income:
Percentageof the
population below poverty
level [Census)
Job Quality: An index
comprised of full-time
employment rate, job
compensation, and job
stability (BLS, Census, and
GSS)
Job Satisfaction:
Percentage of population
satisfied with their job
(GSS and Gallup)
Housing Affordability:
Percentageof homes sold
that were affordable to
families earning median
income 01 median
selected ov«nei costs as a
percentage of household
income I National
Association of Home
Builders/Census)
Food Security: Percentage
of households that were
food secure
(USDA/Census)
Median Home Value:
Median value of owner
occupied housing units
(Census)
Mortgage Debt: Housing
units with no second
mortgage or home equity
loan (Census)
109
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Safety and Security Domain Score and
Element Sub-Index Scores
Actual Safety
Perceived Safety
Risk
Societal
Well-beingScore
(SoWB
Environmental
Well-beingScore
(EnWB7)
Economic
Well-beingScore
(EcWB
Property Crime: Number of
property crimes known to law
enforremenr per 100.000
population (FBI)
Violent Crime: Numberof
violent crimes known to law
enforcement pel 100,000
population (FBI)
Loss from Natural Hazards:
Fatalities and injuries from
hazardousweathet (NOAAt
Social
Vulnerability
Index: Estimates
a population's
ability to
prepare for,
respond tor and
recover from
environmental
hazards(SOVl)
Perceived Safety:
Percentage of people
who feel safe walking
alone at night in the
city or area where
they live {Gallup
Healthways)
110
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Social Cohesion Domain Score and
Element Sub-Index Scores
• Social Support
• Social Engagement
W Attitude towards Others and the Community
y Family Bonding
Democratic Engagement
Environmental
Well-beingScore
(EnWBj)
Societal
Well-being Score
(SoWBjJ
SOC
SOC
1
Economic
Well-being Score
(EcWBJ
SOC
Social Cohesion
Score
SOC COM
Participation in Group
Activities: Percentage of
people who belong and/or
Pa
Ac
people1.
acti vely pa i ti cipate in grou p
activities (GSS)
Volunteering: Percentage of
people who volunteer
(BLS/Census)
Participation in Organized,
Extracurricular Activities:
percentage of children aged
6-17 years old who
participate in activities
outside of school (HHS)
Close Friends and Family:
Percentage of population
with 6 or more close friends
and relatives (Gallup
Poll/CSS)
Attitudes
Towards Others
Trust: Percentage of people
v/ho felt that people can be
trusted (6SS)
City Satisfaction:
Percentage of people
satisfied with their city or
area (Gallup)
L
Helping Others: Percentage
of people who think people
try to be helpful (GSS)
Belonging: Percentageof
people who feel close to
their town (GSS)
Discrimination: Hate crimes
per 100,000 people and
percentage of people upset
as a result of how they were
treated based on their race
(FBI/CDC)
111
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Social Cohesion Domain Score and
Element Sub-Index Scores (continued)
• Social Support
• Social Engagement
w Attitude towards Others and the Community
El Family Bonding
_ Democratic Engagement
Environmental
Well-being Score
Societal
Well-being Score
(SoWBj)
SOC
SOC
1
Economic
Well-being Score
(ECWBJ
SOC
Social Cohesion
Score
SOC_COH
(Continued)
Democratic
Engagement
Family Bonding
Interest in Politics: Percentage
of people who are interested in
political campaigns/affairs
(ANES)
Voice in Government Decisions:
Percentage of people who agree
that they have a voice in
governin ent (AN E S/GSS}
I
VoterTurnout: Percentage of
U.S. citizens that voted (Census)
Trust in Government:
Percentage of people who trust
the government to do what is
right (ANES/GSS)
Registered Voters: R
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Weighted Element Index Scores and the Composite
Index of Well-being
Economic Well-being Element Sub-Index Scores
Environmental Well-being ElementSub-lndexScores
EcWB4=HLTHwt"LTHEcWB
EcWB5=LIV_STDwtuv-STDEcWB
EcWB6=LEI_TIMwtLE'-™E=WB
EcWB7=SAF_SECwtsAF-SECEcWB
EcWBs=CULTwtQJLTEcWB
EnWB2=EDUwtEDUEnWB
EnWB3=CON_NATwtcoN-NA
EnWB=HLTH
wt"LTH
STDwtuv-STDEnWB
EnWB6=LEI_TIMwtLEI-™E"WB
EnWB7=SAF_SECwtsAF-SEC EnWB
EnWBs=CULTwtcuLTEnWB
EcWBinde)f=EcWB1*EcWB2*EcWB3*EcWB4*EcWB5*EcWB6*EcWB7*EcWB8 | | EnWBinde)f=EnWB1*EnWB2*EnWB3*EnWB4*EnWB5*EnWB6*EnWB7*EnWB
HWBI=(EcWBindex*WtEcWB)+(SoWBindex*WtSoWB)+(EnWBindex*WtEnWB)
SoWB,.ndex=SoWB1*SoWB2*SoWB3*SoWB4*SoWB5*SoWB6*SoWB7*SoWB8
Societal Well-being Element Sub-lndexScores
SoWB3=CON_NATwtmN-NATS°WB
SoWB^HLTH™'"1™5"1"8
SoWB7=SAF_SECwtsAF-SEC S°
SoWB^CULT
•WtCULT-SoWB
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