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Community-Based Prevention: More Than the Sum of Its Parts

This chapter discusses how the methods of systems science can help increase understanding about the complexity of community-based prevention intervention by disentangling important features and associated variables, clarifying whether and how each of the variables changes over time, identifying causal relationships among the variables, quantifying the variables and the causal relationships, and simulating how changes to the system affect the variables and causal relationships in the system. Domains of value (health, community well-being, and community process) and illustrative elements within each domain are discussed, as are issues in valuing resources and costs of community-based prevention.

As discussed in Chapter 2, community-based prevention interventions cover a broad spectrum of types, from those directed at a specific health condition (e.g., high blood pressure or diabetes) to those aimed at a much broader and more complex array of conditions, including the prevalence of chronic and infectious diseases; the social, economic, and environmental determinants of population health; and health disparities and inequities experienced by lower income, lower educational status, and racial and ethnic minority populations. Chapter 2 also discussed the ecological model and pointed out the existence of multiple determinants of health at multiple levels that interact and link with each other. However, prevailing approaches to funding, research, and practice associated with community-based prevention interventions often fail to recognize their inherent complexity. For instance, categorical funding programs promote a one-disease-at-a-time



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3 Community-Based Prevention: More Than the Sum of Its Parts This chapter discusses how the methods of systems science can help increase understanding about the complexity of community- based prevention intervention by disentangling important features and associated variables, clarifying whether and how each of the variables changes over time, identifying causal relationships among the variables, quantifying the variables and the causal relationships, and simulating how changes to the system affect the variables and causal relationships in the system. Domains of value (health, community well-being, and community process) and illustrative elements within each domain are discussed, as are issues in valuing resources and costs of community-based prevention. As discussed in Chapter 2, community-based prevention interventions cover a broad spectrum of types, from those directed at a specific health condition (e.g., high blood pressure or diabetes) to those aimed at a much broader and more complex array of conditions, including the prevalence of chronic and infectious diseases; the social, economic, and environmental determinants of population health; and health disparities and inequities ex- perienced by lower income, lower educational status, and racial and ethnic minority populations. Chapter 2 also discussed the ecological model and pointed out the existence of multiple determinants of health at multiple lev- els that interact and link with each other. However, prevailing approaches to funding, research, and practice associated with community-based pre- vention interventions often fail to recognize their inherent complexity. For instance, categorical funding programs promote a one-disease-at-a-time 61

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62 ASSESSING THE VALUE OF COMMUNITY-BASED PREVENTION vision (with an accompanying set of interventions) for improving popula- tion health behaviors and health outcomes. Similarly, many research and evaluation questions seek to identify the best intervention or to examine interventions in the context of a single behavioral or health outcome. And, in the field, approaches to policy and practice change often reflect the inter- ests of the institutions or organizations leading the efforts (e.g., government agencies, community-based organizations, or advocacy groups). Current approaches tend to focus on individual rather than compre- hensive interventions, to attribute changes in health behaviors and health outcomes to specific interventions instead of multiple or synergistic efforts, to not assess effectiveness and costs in terms of the collective value of multi- component intervention approaches, and to guide decisions about priorities and allocate resources intervention by intervention in line with these types of evidence. As such, prevailing approaches fall short in depicting the col- lective impact of community-based prevention efforts (Hanleybrown et al., 2012; Kania and Kramer, 2011). However, there has been a growing amount of attention paid to new approaches to address these dynamic and complex systems (Homer and Hirsch, 2006; Luke and Stamatakis, 2012; Mabry et al., 2008; Madon et al., 2007). Examples include the community transformation grants from the Centers for Disease Control and Prevention (CDC); intervention and ap- plied research efforts such as community-based participatory research; the dissemination and implementation research supported by the NIH National Heart, Lung, and Blood Institute and the Office of Behavioral and Social Sciences Research; and cross-sector and multidisciplinary interventions, such as the CDC Communities Putting Prevention to Work program and the Healthy Kids Healthy Communities program (BSSR/NIH, 2012; CDC, 2012a,b; Horowitz et al., 2009; NHLBI/NIH, 2012; RWJF, 2012). Systems science methods have the potential for overcoming some of the problems with current approaches. Systems science is the study of ­ dynamic “ interrelationships of variables at multiple levels of analysis (e.g., from cells to society) simultaneously (often through causal feedback processes), while also studying the impact on the behavior of the system as a whole over time.”1 For purposes of this report, a system will refer to the inter­ relationships of relevant elements, resources, and processes that characterize community-based prevention. Systems science approaches excel at identi- fying nonlinear relationships, bidirectional feedback loops, time-delayed effects, emergent properties of systems, and oscillating system behavior (Mabry et al., 2010). 1   s defined by the Office of Behavioral and Social Sciences Research at the National Insti- A tutes of Health: http://obssr.od.nih.gov/scientific_areas/methodology/systems_science/index. aspx (accessed July 5, 2012).

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COMMUNITY-BASED PREVENTION: MORE THAN THE SUM 63 Systems thinking is increasingly associated with community-based pre- vention, notably in obesity control. Of major importance from a systems science perspective is the context in which those interventions take place, that is, the social systems that are imbedded in and interacting with other social systems. Second, there is a growing literature that uses the system metaphor to describe the structure and functioning of the intervention itself (IOM, 2010; Livingood et al., 2011; Trickett, 2009). Because of the complexity, comprehensiveness, and intersectoral, and context-responsive nature of the broader community-based prevention efforts, a systems per- spective is well equipped to provide needed analytical descriptions and evaluations of the multiple transformations targeted by such programs, policies, and strategies. Using a systems science approach to think about community-based prevention can help people think through all the links that may be involved in and affected by a change in the community, whether that change comes from a deliberate intervention or a trend, (such as more smoking or less exercise) caused by forces that may lie outside the community. Furthermore, systems science can help further elucidate • the pathways through which policy, system, and environmental changes operate to affect population health. • important ingredients that are needed to implement effective c ­ommunity-based prevention interventions as well as the imple- mentation fidelity and “dose” of these activities (Carroll et al., 2007; Glasgow et al., 1999; Linnan and Steckler, 2002). • methods needed to capture multi-component and dynamic com- munity trends and to triangulate different qualitative and quanti- tative data sources (Patton, 2002; Rossi et al., 2004; Teddlie and T ­ ashakkori, 2009; Ulin et al., 2005). • the extent to which scale-up and spread of evidence-based inter- ventions may be limited by the need to customize these strategies to local political or environmental circumstances, resource con- ­ straints, populations (e.g., race and ethnicity, poverty, urban versus rural, youth versus adult), and settings (e.g., home, child care, school, work, community). • the challenges posed by political, social, and economic forces to the structures (e.g., partners, resources) and processes (e.g., participa- tion, decision making) associated with collaborative community approaches to planning, implementing, enforcing, evaluating, and sustaining these prevention interventions. Systems science methods are designed to deal with complexity and could prove particularly useful in analyzing community-based prevention

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64 ASSESSING THE VALUE OF COMMUNITY-BASED PREVENTION interventions and their impacts (Hammond, 2009; Huang et al., 2009). Results of the application of systems science methods could prove useful in valuing community-based prevention because they can provide information about not only the intervention programs, policies, and associated out- comes but also the contextual conditions, the multi-cause nature of change, and the dynamic interactions among all of the factors. APPLYING SYSTEMS SCIENCE TO COMMUNITY-BASED PREVENTION Systems science methods can be used to explore the various pathways leading from community-based prevention interventions to improvements in population behavioral and health outcomes, such as the influence of a sugar-sweetened beverage tax on the purchase and consumption of foods and beverages. Such methods can also capture the variation in these path- ways associated with contextual factors (such as population characteristics, concentration of fast food restaurants, employment opportunities, and liv- ing wages) and detect changes in the overall system as new interventions surface. Systems science methods can address both detail and dynamic complex- ity. With respect to detail complexity, these methods can clarify assump- tions about public health problems, local community context, and change strategies and processes by identifying the variables and the underlying causal relationships among the variables. At the same time these methods are designed to examine how causal structures change over time, including the effect of changes in the type or number of interventions implemented, changes in social norms and community practices, changes in leadership or staff, and so on. Examining these causal structures can help identify the sys- tem leverage points that have the greatest potential for affecting behavioral and health outcomes, can increase understanding about intended effects and unintended consequences of the interventions implemented, and can identify facilitating factors and challenges influencing community change processes (Meadows, 1999; Sterman, 2000; Ulrich, 2000). For examples of systems science approaches to valuing community- based prevention interventions, see Appendix B. VALUING COMMUNITY-BASED PREVENTION: DOMAINS AND ELEMENTS Policy makers, funders, and relevant stakeholders make decisions about the value of community-based interventions. Traditional approaches to assess value tend to focus solely on health impacts, to value interventions in isolation, to overlook community processes, and to fail to monitor

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COMMUNITY-BASED PREVENTION: MORE THAN THE SUM 65 pathways toward progress. The committee was asked to develop a frame- work for assessing the value of community-based prevention. Because of the way in which community-based prevention is designed and developed (e.g., often to address the social and environmental determinants of health), the committee concluded that impacts of these interventions go beyond health effects. Therefore, a framework for valuing community-based prevention needs to take into account not only the outcomes in the domain of health, but also the outcomes in areas other than health. A framework that does not take into account and value non-health outcomes would be counting all the costs but not all the benefits, thereby providing an inaccurate and inadequate picture of the value of community-based prevention. To assess the true value of community-based prevention, therefore, decision makers, funders, and stakeholders would benefit from an approach that looks not just at health impacts, but at other impacts as well. A major task facing the committee, then, was determining what do- mains should be included in a framework to value community-based pre- vention interventions. As a first step, each committee member was asked to list the outcomes he or she thought could result from community-based prevention interventions. The list generated included more than 100 items and all acknowledged that not everything that could be valued appeared on the list. As a next step, the committee decided to group the items into major categories. Clearly, a major outcome of community-based prevention is its impact on health. Therefore, health was identified as a major domain of interest. However, there were a number of other items on the list that did not fall neatly into a health domain, for example, education, income, green space, crime, social support, and workplace safety. Initially, the commit- tee identified six major categories under which these other items could be grouped: social environment, physical environment, economics, equity, em- ployment, and education. Yet, as the committee discussed these items and reviewed the literature, it became clear that these elements were all elements related to well-being. Therefore, the committee identified a second major domain as the domain of community well-being. There were a number of items that did not fit readily into either the health category or the well-being category but which the committee identi- fied as important items of value, including such things as leadership, skill building, and civic participation. An examination of the history of com- munity health efforts demonstrates that various process elements (such as skill building, leadership, and participation) are features that account for the relative success of community-based programs. Early efforts in the first half of the 20th century involved engaging stakeholder organizations and affected populations in first, the support of planned programs, then

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66 ASSESSING THE VALUE OF COMMUNITY-BASED PREVENTION in actually planning programs, then in evaluating programs, and finally in community-based participatory research (CBPR) (Green, 1986). Based on the literature of CBPR (e.g., Minkler and Wallerstein, 2008) the committee deliberately decided to identify community process as a spe- cific area of valued outcomes for community-based prevention. Elements in the community process domain inherently affect outcomes upstream (e.g., civic participation) that, in turn, affect outcomes down- stream (e.g., policy adoption and implementation), further downstream (e.g., equitable access to environments or resources to support health), fur- ther downstream (e.g., healthy behaviors of citizens in these environments or use of these resources), further downstream (e.g., healthy lifestyle choices of citizens), and, ultimately, health (although health feeds back to greater capacity for civic participation). Therefore, the committee concludes com- munity process should be identified as a separate domain because in many cases, community empowerment and community capacity have been shown to be valued by communities in their own right (Sandoval et al., 2011). Also, because process elements are intermediary outcomes that increase well-being and health interventions (Minkler et al., 2008; Viswanathan et al., 2004), failing to recognize the increase of such potential as a valued outcome will further disadvantage those communities whose structural and population characteristics put them at increased risk of health and well- being deficit. It is important to note that without a solid grounding in sci- ence, community process, as is the case with any democratic process, could lead to worse outcomes with respect to health and well-being. This section of Chapter 3 describes in more detail the wide array of ef- fects that community-based prevention can have, grouping them under the three distinct but interrelated categories of outcomes, or domains of value: health, community well-being, and community process. The committee is aware that health is a component of well-being but for purposes of this re- port the health component is separated from other elements of community well-being because health is a particular outcome of interest. The goal in valuing these domains is to account for all of the potential harms and ben- efits of community-based interventions as well as the possible savings and costs associated with the interventions. This section introduces the domains of value as well as associated elements. It is important to note that the list of elements included in each domain below is meant to be illustrative. The actual elements selected for valuing will depend on the particular intervention and its implementation. It is un- likely that any given intervention will have value in all elements listed, and there may well be other elements not listed here that should be included. The committee has identified one element, equity, that crosses all domains.

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COMMUNITY-BASED PREVENTION: MORE THAN THE SUM 67 Health Physical health includes mortality, morbidity, and functional capability. Mental health includes cognition, individual resilience or emotional re- serves, mortality due to such causes as suicide, morbidity (e.g., depression), and socio-emotional health-related quality of life (e.g., stress, behaviors, injuries, and perceptions of health). The promotion of mental and physical health includes several elements, in particular, reductions in the incidence and prevalence of disease, declines in mortality, and increases in health- related quality of life. Equity is another important element in the health domain. It is well documented that significant health disparities exist by race, ethnicity, and socioeconomic status (SES) (AHRQ, 2012; APHA, no date; IOM, 2003). Health inequalities across demographic groups (e.g., by race, ethnicity, gender, and SES) may be caused by inequalities in ac- cess to health care, by the unequal effect of public measures aimed at risk reduction, or by the unequal distribution of various social determinants of health (e.g., education, income and wealth, opportunity and liberty) (AHRQ, 2012; IOM, 2003, 2009). It may be, however, that the two goals of health policy—improving population health in the aggregate and distrib- uting health fairly—are in tension. For example, some efforts that improve population health in the aggregate may increase health inequalities between groups, for example, a campaign to improve prenatal care that primarily reaches middle to higher income women and is not effective among lower income women may well increase health disparities. Reasonable people may disagree about when to give priority to one goal over the other. However, when assessing value, health inequalities are one element to consider. The charge to the committee specified a focus on the prevention of long-term chronic diseases. As noted throughout the report, long-term chronic illnesses are often the result of a complex, extended interaction between genetics, individual behaviors, and environments. This complex- ity can make the task of valuing more difficult. For example, behaviors, such as eating foods with minimal nutritional value and participating in sedentary activities that can lead to obesity and related chronic diseases, are generally the result of lifestyles shaped in part by an individual’s environ- ment. Lifestyle interventions aimed at preventing certain diseases, such as cardiovascular disease (CVD) and diabetes, have been shown to be effective (Saha et al., 2010). However, lowering the prevalence of CVD and diabetes is an outcome that takes a long time to realize. Interventions aimed at such outcomes can produce intermediate markers, such as decreased insulin resistance or lower blood pressure. For long-term outcomes such as the pre- vention of chronic disease, it will be important to identify intermediate or proximal outcomes as part of the valuation and determination of progress.

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68 ASSESSING THE VALUE OF COMMUNITY-BASED PREVENTION Community Well-Being Community well-being is a valued outcome in and of itself. Independent of the health of individuals in a community, the concept of community well- being has been used to account for elements associated with community context, or the social, economic, and physical environments characterizing the community (IOM, 2009). Elements of community well-being include wealth and income, education, employment, safety, transportation, hous- ing, worksites, food, health care, and recreational spaces, among others. These elements are produced, reproduced, and transformed by the practice of individuals in the community. Their benefits accrue to both individuals and the community as a whole. Physical Environment Frumkin (2003) writes of the “atmosphere of a place, the quality of its environment” and the effect that it can have on both health and well-being. He identified four aspects of the built environment that may have an impact on human health and community well-being: nature contact, buildings, public spaces, and urban form. The built environment includes how land is used, the quality of housing and other buildings, transportation, and other design features “that together provide opportunities for travel and physical activity” and, more broadly, an environment that “is designed and constructed by humans” (IOM, 2001; TRB/IOM, 2005). Land use, urban form, and green space  The composition of the built envi- ronment, Frumkin’s “urban form,” has been associated with a number of health effects. For example, physical characteristics of neighborhoods have been found to be associated with lower levels of physical exercise and an increased risk of obesity (Ewing et al., 2006; Lopez, 2004; Nelson et al., 2006). The presence or absence of amenities, particularly the opportunities to buy healthy affordable food, can also have an effect on health (Bodor et al., 2010; Leung et al., 2011; Michimi and Wimberly, 2010; Morland et al., 2006; Powell et al., 2007). Access to—or even the presence of—green space is associated with increased physical activity, better perceived general health, mitigation of the effects of stressful life events, and lower prevalence of some illnesses (Ellaway, 2005; Maas et al., 2006, 2009; Ulrich, 1984; Van Den Berg et al., 2010). Urban form also has effects beyond those on health. For example, areas with a high degree of “walkability” are perceived to be more aesthetically pleasing and are associated with more unplanned interactions with others and a greater sense of community (Wood et al., 2010). Trees in cities allow

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COMMUNITY-BASED PREVENTION: MORE THAN THE SUM 69 for greater energy conservation and lower heating and cooling costs for buildings (McPherson et al., 1997). Transportation  Numerous studies have found that using public transit increases physical activity (Besser and Dannenberg, 2005; Lachapelle and Frank, 2009; Weinstein and Schimek, 2005; Wener and Evans, 2007). MacDonald and colleagues (2010) found that commuting to work by light rail was associated with a reduction in body mass index and reduced odds of becoming obese. Active travel, such as walking and cycling, along with increasing physical activity can also lead to a decrease in vehicle emissions, thereby improving air quality (de Nazelle, 2011). Investment in public transportation has other benefits as well—for example, bringing jobs and economic activity to communities (Weisbrod and Reno, 2009). Building quality (indoor air)  Housing is another area that has effects on both health and community well-being. People spend most of their time indoors, making buildings a component of the built environment that can have a significant impact on an individual’s health. Indoor air can contain radon, environmental tobacco smoke, and thousands of other chemicals and biological contaminants that pose serious risks to health (EPA, 2001). Children, in particular, are at risk of harm from indoor and outdoor air pollution, and the impact can be lifelong (Barakat-Haddad et al., 2012; EPA, 2001). A 2011 IOM committee found that “poor indoor environ- mental quality is creating health problems today and impairs the ability of occupants to work and learn” (IOM, 2011a, p. 7). In addition to its health benefits, providing quality housing also brings benefits to the community in the form of such things as improved educational outcomes and reduced crime (Carlson et al., 2011). Social and Economic Environments Education  Extensive research has demonstrated the link between education and health outcomes throughout the life course (IOM, 2006a; Lleras-Muney, 2005). Researchers have also documented the relationship of education and well-being (i.e., higher earnings, higher percentages of home ownership and second-car ownership, reduced crime, reduced welfare, reduced unemploy- ment and reduced poverty (Barnett, 1985, 1996; Gorey, 2001; Schweinhart et al., 1993). Employment/unemployment  Unemployment is positively associated with mortality from all causes, with both physical and mental illness, and with the increased use of health care services (Haan and Myck, 2009; Jin et al.,

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70 ASSESSING THE VALUE OF COMMUNITY-BASED PREVENTION 1995; Rueda et al., 2012; Strully, 2009; Wilkinson and Marmot, 2003). Employment also has numerous non-health effects. For example, it is as- sociated with more marriage, less divorce, more marital happiness, and greater child well-being (White and Rogers, 2000). Decreases in the un- employment rate have been found to be associated with declines in prop- erty crime rates (Raphael and Winter-Ebmer, 2001). Rising unemployment increases the incidence of foster home placement (Catalano et al., 1999). Crime/safety  Research has associated increased physical activity with in- creased feelings of neighborhood safety (Harrison et al., 2007). Conversely, those living in high crime areas were more likely to smoke and to report poorer health, poor sleep habits, and less exercise (Johnson et al., 2009; Shareck and Ellaway, 2011). In terms of non-health effects, crime and the fear of violence can interfere with social interaction and trust among com- munity members. For example, crime or the fear of crime has been found to limit women’s movement around their environment and to increase levels of mistrust and fear, (Keane, 1998; Ross and Jang, 2000). Milam and colleagues (2010) found that math and reading achievement in schools decreased significantly with increasing neighborhood violence. Social support and social networks  Social networks are defined as webs of person-centered ties (Berkman and Glass, 2000). Numerous research studies have shown the relationship of social support and social networks to both physical and mental health (Berkman and Glass, 2000; Berkman and Kawachi, 2000; Cohen et al., 2000; Cornwell and Waite, 2009; Kawachi and Berkman, 2003; Marmot and Wilkinson, 1999; Maulik et al., 2009; Stansfeld et al., 1999). However, in addition to their relation- ship to health, social networks and social support are important in and of themselves. For example, Skogan (1989) found that neighborhoods in which residents have organizations and social support resources upon which to draw have more opportunity for action in “defense of their community.” Research has also shown that positive academic outcomes are promoted by social support (Garnefski and Diekstra, 1996; Malecki and Demaray, 2007). Social cohesion Social cohesion has been characterized by Marmot and Wilkinson (1999) as including “mutual trust and respect between different sections of society.” Social cohesion has been shown to be positively associ- ated with health and levels of physical activity (Cradock et al., 2009; Kim et al., 2008; Lindén-Boström et al., 2010; Marmot and Wilkinson, 1999). But social cohesion also has important effects beyond those on health. For example, areas with higher levels of social cohesion are associated with lower levels of crime, with increasing contributions to group goals, and

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COMMUNITY-BASED PREVENTION: MORE THAN THE SUM 71 with economic prosperity (Hirschfield and Bowers, 1997; Shimizu, 2011; Stanley, 2003). Equity  As mentioned previously, equity is an important element that crosses all three domains. Elements of community well-being are often not equitably distributed in a community. For example, both education and wealth, which are elements of the social environment, are often distributed unequally by race, and considerable attention has been given in recent lit- erature to growing inequalities in income and wealth. The same point may be made for social trust: Levels may vary across various groups in a society, and some practices may weaken trust across groups. The built environment in a society may also be inequitable in its impact on different groups— neighborhoods may vary in the quality of housing, green space, transpor- tation, or even access to fresh food. It is important in valuing community well-being to focus not only on aggregate measures, but also on how com- munity well-being is distributed. Inequity in the distribution of these aspects of community well-being may lead to inequities in the distribution of health and may also contribute to inequities in community processes. Community Processes Community-based prevention involves decisions among groups of peo- ple about how to live in society, how cities are built, what food is served in schools, and so on. Therefore, it is important that the process by which an intervention is adopted and undertaken be treated as a valued outcome. With a vaccination, effectiveness does not depend on whether the patient trusts the doctor. In contrast, the success of a healthful eating campaign may hinge on the level of trust in the process. Community processes refer to several elements that have a distinc- tive influence on community participation in the decision making as well as in the design and implementation associated with community-based interventions. These elements include civic engagement, local leadership development, community participation, trust, skill building, transparency, and inclusiveness. Community processes typically have a sequence of ac- tivities that incorporate learning about various options available for health improvement, deliberations associated with the selection of one or more options, consideration of the appropriate methods to implement the health improvement initiatives, and critical reflection on the entire process. The way that decisions are made and carried out not only can be important to the success of a strategy or policy—and thus to community well-being—but also can have a direct impact on well-being through benefits of broad partic- ipation and buy-in to decisions (Minkler and Wallerstein, 2008; Wallerstein and Duran, 2010). Community processes also support local adaptation and

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78 ASSESSING THE VALUE OF COMMUNITY-BASED PREVENTION Various governmental and nongovernmental groups recommend—or require—specific discount rates, but there is no general agreement among them on what the discount rate should be (Jawad and Ozbay, 2006). For example, the Office of Management and Budget recommends a real (ad- justed for inflation) discount rate of 7 percent per year, with 3 percent as an alternative to test the sensitivity of an evaluation’s results to the discount rate (OMB, 2003). The Panel on Cost-Effectiveness in Health and Medicine recommends a real rate of 3 percent for cost-effectiveness analyses and the National Institute of Health and Clinical Excellence in the United Kingdom requires a real rate of 3.5 percent. DATA SOURCES AND INDICATORS FOR VALUING COMMUNITY-BASED PREVENTION There are a variety of sources of data on health, including surveys (e.g., the National Health Interview Survey and the Behavioral Risk Factor Surveillance System), cohort studies (e.g., the Framingham Heart Study), registries, health services data, vital statistics, and data collected by state public health agencies. Unfortunately, there are several limitations on using these data for local, community-based measurement (IOM, 2011b). For example, national surveys are unable to provide the detailed data needed for local estimates without specifically designing local data collection. Reg- istries and health services data provide information only about those who seek and receive health services, cohort studies are resource intensive, and vital statistics are subject to coding errors (IOM, 2011b). To collect information to measure baseline health and changes in health at the local level may require developing and implementing local surveys aimed at the specific health issues of interest. Identifying measures and sources of information for community well- being and community process elements is even more challenging than collecting such information about health. Table 3-2 lists elements and indicators that could be used in the three domains of interest: health, com- munity well-being, and community process. As stated before, these are examples only. The actual elements and indicators chosen will depend on the community-based prevention intervention being considered. Applying methods from systems science to community-based preven- tion efforts can help increase our understanding of the complex interre- lationships among factors important to building healthy populations and healthy communities. The following chapter discusses how a framework for valuing resides within a decision-making context, reviews eight frameworks currently used to assess community-based prevention, and discusses the strengths and limitations of each for addressing the special characteristics of community-based prevention.

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COMMUNITY-BASED PREVENTION: MORE THAN THE SUM 79 TABLE 3-2  Domains and Examples of Elements and Indicators for Valuing Community-Based Prevention Interventions Value Component Elements (examples) Possible Measures (data sources) Health Overall Overall 1. Quality of life 1. Quality-adjusted life year (QALY) or health-adjusted life expectancy (HALE) 2. Perceived health 2. Self-reported health status Physical Physical 1. Mortality (overall and per cause) 1. Deaths 2. Morbidity 2. Rates of conditions or diseases of interest, unhealthy days 3. Functional capability 3. Level of activities of daily living, exercise 4. Injuries 4. Rates of injuries Mental Mental—Change in rates 1. Cognition 1. Cognitive Abilities Screening Instrument (Adult), Dementia Rating Scale (Adult), Differential Abilities Scale (Children) 2. Morbidity 2. Self-reported unhealthy days mental 3. Depression 3. Self-reported healthy days mental Anxiety Stress Perceived well-being 4. Suicide rates 4. Rates of suicides Community Built environment Built environment Well-Being 1. Land use 1. Number and quality of facilities— schools, libraries, housing 2. Transportation 2. Number of sidewalks for walking, bike paths, buses, metro/trains, automobiles. 3. Building quality (indoor air) 3. Levels of pollutants (e.g., radon, tobacco smoke, chemicals) 4. Food systems 4. Grocery stores with healthy choices, farmer’s markets continued

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80 ASSESSING THE VALUE OF COMMUNITY-BASED PREVENTION TABLE 3-2  Continued Value Component Elements (examples) Possible Measures (data sources) Natural physical environment Natural physical environment Green space Parks, preserved open spaces, beauty Social and economic environments Social and economic environments 1. Social support and social 1. Number, type, frequency of networks contact 2. Social cohesion 2. Trust, respect 3. Education 3. Number and quality of schools a. Resources a. Books, computers, play equipment, class size b. Achievement b. 3rd-grade reading level, high school and college graduation rates c. Health literacy c. Change in level of health literacy 4. Employment 4. Employment/unemployment rate a. Safe work places a. Physical environment and job effort b. Stress b. Job demand versus control, job effort versus rewards c. Income c. Wages, food stamp use 5. Crime/safety 5. Rates for various crimes 6. Access to health care and health 6. Number and type of health care insurance facilities, rate of uninsured Community 1. Local leadership development 1. Elected leaders reflect community Process diversity, number and type of community activists 2. Skill building 2. Number and type of peer counselors and community organizers 3. Civic engagement or participation 3. Voting rates, volunteering, participation in clubs or other local organizations 4. Community mobilization 4. Involvement in civic activities (e.g., town hall meetings)

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