Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 23
2 Why We Need Health-Informed Policies and Decision-Making On the basis of the most recent data from the World Health Organization, the United States ranks 32nd in the world in life expectancy—behind such coun- tries as Japan, Australia, Italy, Greece, Iceland, Malta, and Luxembourg— despite ranking third in total expenditures on health care as a percentage of gross domestic product (GDP) (WHO 2010). Clearly, the United States still faces im- portant challenges to promoting health and enhancing quality of life. For exam- ple, chronic diseases, many of which are preventable, account for more than 50% of all deaths each year (King et al. 2008). Almost half of all adults have at least one chronic illness (Wu and Green 2000). Obesity, a major risk factor for numerous health conditions, has grown to epidemic proportions in the United States (Ogden et al. 2007, 2008): one-third of all adults and almost one-fifth of people 6-19 years old are obese. Improvement in health has been inconsistent, and major disparities in health associated with socioeconomic circumstances, race, and ethnicity persist (Williams et al. 2010). Despite major medical advances and large health expenditures, many Americans are unable to achieve their full health potential; this affects not only the quality and duration of their lives but their ability to be engaged and produc- tive members of society. Poor health also has important economic implica- tions—for lost productivity and for the costs of diagnosing and treating chronic conditions. Those costs affect individuals, communities, and society at large (WHO 2001; Hammitt 2007; Mackenbach et al. 2007). For example, costs for medical care have mushroomed both in amount and as a portion of the U.S. GDP because of the increases in medical care itself, the increases in use of the health-care system, the aging of the population, and the higher rates of chronic diseases. Health-care spending accounted for 7% of the U.S. GDP in 1970 and 16% of it in 2008 (CMS 2011); it is projected to be close to 20% by 2019 (CMS 2010), and this projection does not take into account the substantial increases in morbidity and mortality that will result from the obesity and diabetes epidemics. 23
OCR for page 24
24 Improving Health in the U.S.: The Role of Health Impact Assessment Diabetes alone accounted for $174 billion in health-care costs in the United States in 2007; diabetes incidence is expected to increase from 7 per 1,000 to 15 per 1,000 by 2050 and diabetes prevalence from 14% to 21% by 2050 and in some scenarios up to 33% (Boyle et al 2010). Thus, the consequences of not preventing chronic health conditions are large, not only in years of healthy life lost but in monetary costs. There is growing recognition among scientists, communities, and policy- makers that health is affected by an array of factors that operate on multiple lev- els and throughout a person’s lifetime (Adler and Stewart 2010). Although the importance of access to and quality of health care is well recognized, prevention is key. Disease prevention and health promotion require addressing a much broader set of factors and policies that shape health-related behaviors in addition to trying to modify biologic processes specifically related to diseases. Efforts to improve early detection and treatment of diseases through improved access to high-quality medical care must be complemented by approaches that address the underlying or root causes of disease. The underlying causes include the factors that shape the conditions in which people are born, grow, live, work, and age, and the policies that affect them. Those factors and their implications for health have been highlighted in a number of recent reports (see, for example, WHO 2002; CSDH 2008; RWJF 2009). The root causes that have been identified indicate that many policies or programs thought to be unrelated to health may have important health conse- quences. Indeed, it has been argued that major health problems, such as the obe- sity epidemic and its associated health and monetary costs, are essentially unin- tended consequences of various social and policy factors related, for example, to the mass production and distribution of energy-dense foods (Ledikwe et al. 2006; Mendoza et al. 2007; Wang et al. 2008) and the engineering of physical activity out of daily life through changes in how transportation is organized and how neighborhoods are designed and built (Gordon-Larsen et al. 2005; Li et al. 2008; Frank and Kavage 2009; Fitzhugh et al. 2010). Such policy and planning decisions have powerful implications for individual behaviors and public health. The prevention of today’s major health problems requires understanding and intervention to affect the root causes of ill health and the policies that shape and affect the root causes. To address them effectively, a better understanding of the possible health consequences of proposed policies and planning decisions as they are being developed is needed so that adverse health effects can be antici- pated and minimized and health benefits maximized. In summary, the health implications of decisions need to be considered explicitly not only to prevent harm but to promote health. Indeed, it can be ar- gued that major improvements in the health of the U.S. public cannot be achieved without attention to the root causes of ill health and to the policies and programs that affect them. Furthermore, many root causes of ill health are com- mon to the entire U.S. population, so interventions that address them can have broad-based impacts that benefit both high-risk groups and the general public.
OCR for page 25
25 Why We Need Health-Informed Policies and Decision-Making KNOWLEDGE OF ROOT CAUSES OF HEALTH CONSEQUENCES Research has identified measurable health consequences that have a wide variety of fundamental or root causes. The causes investigated have included broadly defined socioeconomic circumstances (Lynch et al. 1996; Marmot et al. 2001; Adler et al. 2007), education (Backlund et al. 1999; Din-Dzietham et al. 2000; Fleishman 2005; Lleras-Muney 2005; Kawachi et al. 2010), work and work environments (Marmot and Theorell 1988; Ferrie et al. 1998; Frank and Cullen 2006; Gillen et al. 2007; Cummings and Kreiss 2008; Ferrie et al. 2008; Clougherty et al. 2010), and physical and social features of communities or neighborhoods (Roberts 1997; Clougherty et al. 2007; Diez-Roux and Mair 2010). For example, a large literature has shown that economic resources are strongly associated with many health outcomes. The relationship between eco- nomic resources and health is not limited to those living in poverty; rather, there is abundant evidence of a graded inverse relationship between income and mor- tality or morbidity from chronic diseases that extends well above the poverty level (Adler and Stewart 2010). Higher educational attainment is related to better health, possibly through the consequences of education for income, occupational achievement, residential location, and such other factors as self-efficacy and sense of control (Kawachi et al. 2010). For example, research shows that a 30-year-old white male high- school graduate can expect to live an average of 10 years longer than a 30-year- old white male who has less than 9 years of education. In black men, the educa- tion-based difference in life expectancy is greater than 16 years (Crimmins and Saito 2001). Work environments are also important predictors of health. The adverse health consequences of physical and chemical exposures at work—such as ex- posure to toxicants, noise, and heat—are well established (Rosenstock et al. 2005). Recent work has shown that psychosocial features of the work environ- ment, such as control of the work process, are important risk factors for chronic diseases (Siegrist 1996; Belkic et al. 2004; Ostry et al. 2006; Schulte et al. 2007; Clougherty et al. 2010; Krieger 2010; Meyer et al. 2010). It has also been sug- gested that trends in occupation-related physical activity may contribute to the obesity epidemic (Church et al. 2011). There is abundant evidence of the impact of environmental factors, such as air pollution, on the causation and acceleration of respiratory and cardiovascular diseases (Brook et al. 2004; Dominici et al. 2006; Pope and Dockery 2006). In recent years, a broad and growing scientific literature has documented associa- tions of various aspects of the physical and social environments of neighbor- hoods with health-related behaviors, such as diet and physical activity; these findings highlight important implications for the prevention of obesity, diabetes, and other chronic diseases (Brisbon et al. 2005; Hannon et al. 2006; Sturm 2008; Franzini et al. 2009; Larson et al. 2009; Chen and Florax 2010; Truong et al. 2010). Transportation systems and the location of industrial land uses are related
OCR for page 26
26 Improving Health in the U.S.: The Role of Health Impact Assessment to health; for example, childhood asthma (Gauderman et al. 2005; Jerrett et al. 2008; Mann et al. 2010; Mar et al. 2010), birth outcomes (Salam et al. 2005; Ritz et al. 2007; Slama et al. 2007; Woodruff et al. 2008), and cardiovascular risk (Brook et al. 2010; Park et al. 2010) have all been shown to be associated with transportation and planning decisions that shape exposure to air pollution, including airborne particulate matter and toxic gases generated by traffic and other sources. Health can be affected by planning decisions that result in urban sprawl (Pohanka and Fitzgerald 2004); for example, social isolation created by living in suburban areas may have health consequences (Pohanka and Fitzgerald 2004), and increased use of cars for commuting can result in increases in air- borne particulate matter and in sedentary behavior associated with greater time spent in cars (Friedman et al. 2001). A broad array of social and economic policies—although less frequently investigated in empirical studies—is likely to have measurable health impacts. For example, policies related to taxation, income supplementation, or access to education clearly determine a person’s economic resources and educational at- tainment, which have been shown to affect health. Policies that affect job vari- ety, quality, and environments will affect health, and policies that affect the physical and social environments of communities may also have important health consequences (Dow et al. 2010). Examples include housing policies that affect the quality and location of housing developments; transportation policies that affect the quality and availability of public transportation; urban-planning policies and decisions that affect land use and street connectivity or the creation of new housing developments; policies related to the location of food stores, farmers markets, and other food services; policies that promote safety and social interactions between neighbors, such as those related to community policing, lighting, organization, and design of attractive public spaces; and economic- development and zoning policies that affect the location of businesses and in- dustries. The factors that affect health are also root causes of health disparities as- sociated with socioeconomic status, race, or ethnicity. Those health disparities are pronounced and persistent and do not appear to be declining despite medical advances. It is apparent that reducing the disparities will require addressing the more fundamental causes. Moreover, socioeconomically disadvantaged groups and racial or ethnic minorities are already at a health disadvantage and are the ones most likely to be affected by unintended adverse health consequences of policies or planning decisions because of where they live, their lack of resources to buffer or compensate adverse effects, and their lack of political power to ad- vocate for their health. Indeed, even if a policy or decision improves public health overall, disparities in health related to socioeconomic position, race, or ethnicity may persist (Schulz and Northridge 2004; Frohlich and Potvin 2008).
OCR for page 27
27 Why We Need Health-Informed Policies and Decision-Making WHY ASSESS THE HEALTH CONSEQUENCES OF POLICIES, PROGRAMS, PROJECTS, AND PLANNING DECISIONS? Systematic assessment of the health consequences of policy, program, pro- ject, and planning decisions is of major importance for protecting and promoting public health because it allows the people who are involved in the decision- making process to consider the health impacts with other factors. Decisions can then be modified to minimize adverse health consequences or to maximize health benefits. Failure to consider health consequences can result in unintended harm or in lost opportunities for health improvement and disease prevention. Below are examples that illustrate the implications of failure to consider health consequences of policies, programs, projects, or plans. U.S. agricultural-assistance programs provide subsidies for commodity crops—such as corn, soybeans, wheat, and rice—to help to ensure that U.S. families have an affordable source of food, that crop prices are stable, and that farmers continue to farm. Fruits, vegetables, and nonwheat grains are not subsi- dized, so farmers may be less likely to grow them. Although the assistance pro- grams are considered successful, some researchers argue that an unintended consequence of the subsidies is their contribution to the current obesity epidemic and other nutrition problems (Fields 2004; Tillotson 2004; Hawkes 2007; Drewnowski 2010). For example, products made from the few subsidized crops—including high-fructose corn syrup sweeteners, hydrogenated fats made from soybeans, and feed for cattle and pigs—may saturate the market; this in turn may lower the prices of fattening, nutrient-poor, and energy-dense foods, such as prepackaged snacks, ready-to-eat meals, and fast food. The cheaper foods can easily compete with higher-priced healthier foods, such as fruits and vegetables, and this can affect calorie intake and other dietary factors that have implications for various chronic conditions, such as obesity, diabetes, and meta- bolic syndrome (Ledikwe et al. 2006; Mendoza et al. 2007; Wang et al. 2008). Lower-income groups may also be disproportionately affected by the less ex- pensive, less nutritious foods because a larger portion of their diets may consist of these foods. The health consequences of policies promoting the production of inexpensive, calorie-dense foods could thus be far-ranging but remain unknown in the absence of a systematic assessment. A second example of a failure to anticipate the health effects of policy and planning decisions is apparent in examining the health effects of transportation infrastructure. The Interstate Highway Act of 1956 introduced the development of a transportation infrastructure that has had multiple implications for health, both favorable and unfavorable. Over the last several decades, the transportation infrastructure has focused on road-building, private automobiles, and transporta- tion of goods and has resulted in “an unprecedented level of individual mobility and facilitated economic growth” (APHA 2010, p. 2). It has shaped land-use
OCR for page 28
28 Improving Health in the U.S.: The Role of Health Impact Assessment patterns throughout the United States and has had implications for air quality, toxic exposures, noise, traffic collisions, pedestrian injuries, and neighborhood physical and social features potentially linked to health (Frank et al. 2006). Transportation accounts for 30% of U.S. energy demand, and in 2008, tailpipe emissions from motor vehicles and impacts from fuel production con- tributed an estimated $56 billion in health and related damages (NRC 2010).1 The costs partly reflect transportation-investment decisions that are focused on maximizing the safety and efficiency of automobile use and have resulted in important efficiencies in motor-vehicle transportation. The decisions have also led to transportation systems that discourage pedestrian and bicycle travel be- cause of sheer distances between destinations, lack of adequate infrastructure for pedestrian travel, and increased hazards associated with pedestrian traffic—for example, unsafe pedestrian crossings and absence of pedestrian routes that are separate and safe from motor vehicles (APHA 2010). Personal and societal costs of the transportation decisions include nearly 34,000 deaths in 2009 due to mo- tor-vehicle collisions; more than 12% of the deaths were of pedestrians (NHTSA 2010). The emphasis on motorized transport has been associated with more driv- ing (Ewing and Cervero 2001; Frank et al. 2007), less physical activity (Saelens et al. 2003; Frank et al. 2005, 2006; TRB 2005), higher rates of obesity (Ewing et al. 2003; Frank et al. 2004; Lopez 2004), and higher rates of air pollution (Frank et al. 2000; Frank and Engelke 2005; Frank et al. 2006). A partial ac- counting of costs associated with the health effects, shown in Table 2-1, totals about $400 billion in 2008. There is evidence that adverse health effects associated with transportation disproportionately affect members of racial and ethnic minorities and those in lower socioeconomic strata and thus contribute to persistent racial, ethnic, and socioeconomic disparities in health (Houston et al. 2004; Apelberg et al. 2005; Ponce et al. 2005; Wu and Batterman. 2006; Chakraborty and Zandbergen 2007). In the absence of systematic assessment of health effects and their asso- ciated costs, the implications of transportation decisions for health and health inequities cannot be factored into the process of making decisions about trans- portation infrastructure. As a result, the health-related effects and their costs to individuals and society are hidden or invisible products of transportation-related decisions. Both adverse and beneficial health effects of specific decisions may some- times be manifested rapidly. A study of the health consequences of changes in transit systems during the 1996 Olympic Games in Atlanta documented benefi- cial health effects of decisions made primarily to reduce downtown traffic con- gestion. Efforts to reduce congestion included daily 24-hour public transporta- tion, the addition of 1,000 buses to support park-and-ride transit in the city, local 1 The estimate excludes costs associated with climate change and non-fuel impacts, such as accidents and health effects resulting from reduced exercise.
OCR for page 29
29 Why We Need Health-Informed Policies and Decision-Making TABLE 2-1 Costs of Transportation-Related Health Outcomes, 2008 U.S. dollars, billionsa Outcome Factors Included in Estimate Obesityb Health-care costs $142 Lost wages due to illness and disability Lost future earnings due to premature death Health-care costs Air pollution $50-80 from traffic Premature death Health-care costs Traffic crashes $180 Lost wages Property damage Travel delay Legal and administrative costs Pain and suffering Lost quality of life a All cost estimates are adjusted to 2008 U.S. dollars. b “A portion of these costs are attributable to auto-oriented transportation and land use development that inadvertently limit opportunities for physical activity and access to healthy food” (APHA 2010, p. 2). Source: Adapted from APHA 2010, page 4. Reprinted with permission; copyright 2010, American Public Health Association. business use of alternative work hours and telecommuting, closure of the down- town sector to private automobile travel, alteration of downtown delivery sched- ules, and public announcements of potential traffic and air-quality problems. Those actions resulted in substantial decreases in acute childhood asthma events that were reversed after the end of the Olympic Games and the resumption of usual traffic patterns (Friedman et al. 2001). Similarly, the introduction of electronic toll collection (E-ZPass), which reduced idling and queuing by allowing cars to move more quickly through toll booths, had important favorable effects on birth outcomes. Currie and Walker (2011) compared birth outcomes among women who lived near toll booths where E-ZPass was introduced with birth outcomes among women who lived near busy roadways that were not close to E-ZPass tollbooths. The introduction of E-ZPass greatly reduced traffic congestion and motor-vehicle emissions in the vicinity of highway toll plazas. The reductions in motor vehicle emissions were associated with a 10.8% reduction in prematurity and an 11.8% reduction in low birth weight of infants born to women living within 2 km of E-ZPass toll booths (Currie and Walker 2011). Moreover, there is substantial evidence that the prob- ability of living near highways is unequally distributed by race, ethnicity, and socioeconomic status; this suggests that the changes may not only improve birth outcomes but reduce racial and socioeconomic disparities in those outcomes
OCR for page 30
30 Improving Health in the U.S.: The Role of Health Impact Assessment (Gunier et al. 2003; Green et al. 2004; Houston et al. 2004; Jacobsen et al. 2004; Ponce et al. 2005). In the examples above, health was not the primary force driving the deci- sion to implement a policy or program, but important health consequences were observed. Moreover, the actions had consequences not only for public health generally but for disparities in health given that many of the conditions are more common among specific racial, ethnic, and socioeconomic groups. Integrating health considerations in a systematic way into the planning of programs, poli- cies, and projects is key to preventing poor health and improving and protecting public health. The failure to consider consequences has led and will lead to many unanticipated adverse health consequences that have human and economic implications. The examples also demonstrate the potential of identifying unex- pected health-enhancing policy and program interventions that can contribute substantially in addressing major health problems. In summary, growing scientific evidence of the links between health and many economic, social, and planning factors makes it imperative to evaluate the health implications of policies, programs, projects, and plans that affect the root causes. Health-informed decision-making is sorely needed. The systematic as- sessment of the health consequences of policies and planning decisions is of special importance for protecting the health of vulnerable groups and those al- ready at a health disadvantage because of adverse social or economic circum- stances. In addition, it is fundamental to eliminating health disparities by race, ethnicity, and socioeconomic circumstances. WHY ASSESSMENTS ARE NOT BEING CONDUCTED Scientific information on the importance of root causes is abundant and growing, but it is not being fully used in a practical sense—that is, by applying it to the daily decisions made at the local, state, tribal, or federal level to enhance health and reduce health disparities. There are a number of reasons why health effects may not be systematically incorporated into decisions regarding policies, programs, projects, or plans, including the following: The absence of a mandate or funding to address root causes of ill health or health disparities or to assess the health impacts of planned policies and deci- sions. The presence of structural and administrative barriers to collaboration among public-health, planning, and environmental-health professionals (Epstein et al. 2006). The mismatch and lack of coherence among governance structures— for example, planning decisions about land use are made under the jurisdictions of local townships, and public-health decisions are made at the level of a city, county, or state.
OCR for page 31
31 Why We Need Health-Informed Policies and Decision-Making The perception that health and health disparities are attributable only to individual characteristics and choices (Link and Phelan 1995). The absence of inclusive and participatory mechanisms and processes for systematically integrating planning, public health, and environmental-health promotion in decision-making. The failure to enforce existing regulations to assess health implications of policies, programs, projects, and plans—for example, the failure to capture health impacts adequately in the context of environmental impact assessments. Given the potential to reduce harm and enhance health, it is imperative to overcome the barriers that have prevented the consideration of health in deci- sion-making. Factoring health and health-related costs into decision-making is essential in confronting the nation’s pressing health problems and enhancing public health. WHAT ARE THE OPTIONS FOR ASSESSMENT? Assessing the health consequence of policies, programs, projects, and plans is a challenge that will require an interdisciplinary approach—involving such disciplines as health, social sciences, economics, and policy—and the col- laboration of scientists, policy-makers, and communities. Systematic processes for rigorously assessing health consequences are needed. Although numerous analytic and deliberative tools are being used to incorporate aspects of health into decisions, none fully provides all the necessary attributes. Human health risk assessment has been used for decades to incorporate understanding of the health implications of exposures (often environmental) into the regulatory decision-making process. However, risk assessment as conven- tionally practiced generally focuses on individual chemicals or limited mul- tichemical exposure scenarios and does not capture the array of factors de- scribed earlier in this chapter. Although it could be argued that risk assessment can be applied in a manner that addresses all dimensions of policy influences on health and that the recent move toward cumulative risk assessment recognizes the need to consider a wide array of chemical and nonchemical exposures (NRC 2009), risk assessment without a substantial redefinition of the field is unlikely to be applicable to the great variety of policies, programs, projects, and plans that could have health implications.2 Moreover, traditional risk assessment tends to focus on adverse health effects rather than on beneficial and adverse effects. It also emphasizes quantitative outputs as the primary end points in most appli- 2 The committee notes that cumulative impact assessment as defined in NRC (2009) is somewhat broader than cumulative risk assessment in that it captures a wider array of end points and includes more qualitative components than cumulative risk assessment. How- ever, it is generally oriented more toward characterizing impacts and less toward inform- ing specific interventions or decisions.
OCR for page 32
32 Improving Health in the U.S.: The Role of Health Impact Assessment cations. Although risk assessments include qualitative elements—such as hazard identification—and involve qualitative descriptions in risk characterization, they are generally secondary to the quantitative elements, and outcomes that cannot be quantified are rarely decision-relevant. Even in the context of cumulative risk assessment, NRC (2009) emphasized the importance of retaining the key attrib- utes of quantitative risk assessment. Finally, it rarely engages stakeholders and communities in a deliberative process. Thus, in spite of the well-established regulatory mechanisms for health risk assessment and its potential to be modi- fied in the long term, it is unlikely that all the health consequences of policy and planning decisions could be appropriately captured by conventional risk assess- ment (and in some situations, a narrow application of risk assessment could lead to policy and planning decisions that are injurious to health). Other tools used to incorporate health into decision-making include cost- benefit or cost-effectiveness analysis, which often uses outputs from health risk assessment and the costs of implementing control strategies or other interven- tions. Those analytic tools commonly use a decision-theory framework in which various interventions are considered and an optimal choice is made on the basis of the outputs of the analysis. However, they have limitations similar to those surrounding traditional risk assessment, including a focus on more analytic than deliberative aspects of decision-making and a lack of an obvious mechanism to include qualitative information and participation of stakeholders. The existing tool that may be most closely aligned with the consideration of multilevel and root causes is life-cycle assessment (LCA) (Curran 1996; EPA 2006). LCA examines a process or product and characterizes the full array of its upstream and downstream implications, including effects on human health, eco- systems, and other end points of interest to decision-makers. LCA typically re- lies on a combination of quantitative and qualitative evidence to compare vari- ous approaches to achieve a goal. However, LCA is generally more focused on such applications as manufacturing or fuel-cycle analysis and consists of more generic characterizations rather than site-specific characterizations. Thus, LCA attempts to characterize typical situations often from a national or global per- spective, whereas the types of policies and planning decisions in which health dimensions need to be considered are often local and have unique site-specific attributes that should be considered. Because of the limitations of existing tools in their ability to evaluate the health consequences of an array of policies, programs, projects, and plans sys- tematically, health impact assessment (HIA) is a tool that holds promise for sci- entists, communities, and policy-makers. By its very nature, HIA lies at the in- tersection of science, policy, and stakeholder and community engagement. It includes attributes of health risk assessment, cost-benefit analysis, and LCA but differs from them in important ways, including its applicability to a variety of policies, projects, programs, and plans; its consideration of beneficial and ad- verse health consequences; its ability to consider and incorporate different types of evidence; and its engagement of communities and stakeholders in a delibera- tive process. HIA offers a way to engage agencies and individuals that do not
OCR for page 33
33 Why We Need Health-Informed Policies and Decision-Making normally work together, may not share a common expertise and knowledge, and often have differing priorities, authority, and objectives. It seeks to correct the fundamental problem of failing to consider health at all in decision-making. The committee concludes that HIA is valuable even with a lack of perfect forecasting data and tools because it is better to consider potential health risks and benefits than to ignore them routinely. The committee acknowledges that other assessment approaches may share some features with HIA, but they do not meet the definition and description of HIA that the committee provides in the present report. Those defining features are discussed in detail in the chapters that follow. OTHER BENEFITS OF SYSTEMATIC ASSESSMENT OF HEALTH IMPACTS The committee concluded that HIA has at least three important benefits in addition to the obvious implications for improved policy-making and promotion and protection of health that would result from the systematic assessment of the health consequences of policies, programs, projects, and plans: Improving the evidence. The conduct of systematic assessments of health impacts will explicitly identify data gaps and evidence needed to improve future assessments. It will stimulate policy-relevant scientific research more directly, whether to develop new empirical studies or to improve systematic evaluation and synthesis of existing evidence. In addition, systematic monitoring of the health consequences of policies or actions after they are implemented should provide valuable new data directly relevant to answering policy-relevant causal questions that often cannot be addressed with observational studies or randomized trials. For example, in the Oak-to-Ninth Development Project HIA, the University of California, Berkeley, Health Impact Group conducted an analysis to estimate the effect of project-generated traffic on the frequency of pedestrian-automobile collisions in Chinatown in Oakland, California (UCBHIG 2007). Critiques and discussion of the results of the HIA led to the development and validation of a predictive model for pedestrian collisions (Wier et al. 2009) that was used in a later HIA (Bhatia and Wernham 2008). The process of sys- tematic assessment, critique, and refinements in the development of scientific evidence to inform decision-making is critical for the development of health assessments that inform decision-making effectively. Raising awareness among policy-makers and the public. The system- atic assessment of the health consequences of policies and planning decisions will raise awareness among policy-makers and the public at large about the wide variety of factors that affect health. It can contribute to a more comprehensive understanding of the causes of illness and of the role of policies, programs, pro- jects, and plans in shaping health outcomes, including strategies that are likely to make the most difference in improving health and in reducing health disparities.
OCR for page 34
34 Improving Health in the U.S.: The Role of Health Impact Assessment The recognition that health is affected by much more than lifestyle choices, ge- netic predispositions, and medical care is fundamental in the development and implementation of the types of strategies that are needed to improve public health. For example, the development of systematic evidence has resulted in a growing evidence base that links food policies and food access to the obesity epidemic and associated chronic diseases; the knowledge of these associations has in turn begun to generate attention and action among policy-makers (NAGC 2010). A new paradigm for productive collaborations. The assessment of the health consequences of policy and planning decisions will provide opportunities for a new paradigm for productive collaborations. For example, the collabora- tions offer opportunities (1) for scientists to be more directly involved in the application of the science that they conduct to improve public health and to be made more aware of the type of evidence needed for policy decisions, (2) for identification of new data sources and designs needed to answer important sci- entific and policy-relevant questions, (3) for improved ability of policy-makers to consider health implications in making decisions and improved understanding of the links between policies and health, (4) for active participation of commu- nity members in decision-making and increased access to information on health consequences available through the assessment process, which can enhance their ability to advocate for health, and (5) for improved insights into the potential pathways through which proposed decisions are likely to affect the health of residents (see, for example, Arquette et al. 2002; Corburn 2005). The collaborations hold great potential for enhancing society’s ability to prevent disease and promote public health. Furthermore, the active engagement of representatives of communities whose health stands to be affected by pro- posed policies, programs, projects, and plans is an essential component of de- mocratic decision-making. Public engagement may also enhance understanding of the pathways through which policies, programs, projects, and plans may af- fect health and could promote actions that contribute to the reduction of health disparities. For example, the engagement of community members in HIA may lead to greater awareness of the impact of community resources on health and result in actions to improve community environments. Finally, systematic as- sessment of health consequences will give community groups a practical mechanism for increasing accountability of policy-makers and developers in the public and private sectors. CONCLUSIONS As a society, we routinely make decisions and implement a variety of policies, programs, and strategies without knowledge of their health implica- tions. But those actions could substantially affect the health of the population and health disparities. The health consequences can have economic and social
OCR for page 35
35 Why We Need Health-Informed Policies and Decision-Making costs, which can have multiplying and cumulative effects. Identifying the poten- tial effects in advance is fundamental for disease prevention and could have im- portant consequences for trends in diseases and for social inequalities in a wide variety of health outcomes. By tackling issues that other policy-analysis tools do not systematically incorporate or address, HIA has both a more expansive vision and a number of barriers to overcome to be accepted as a decision-making tool. Thus, it holds great potential but also presents a number of challenges. The following chapters discuss the key elements of HIA, review the status of HIA, and propose ways to improve the quality and utility of HIA in the future. REFERENCES Adler, N., and J. Stewart. 2010. Health disparities across the lifespan: Meaning, methods, and mechanisms. Ann. NY Acad. Sci. 1186:5-23. Adler, N., J. Stewart, S. Cohen, M. Cullen, A.D. Roux, W. Dow, G. Evans, I. Kawachi, M. Marmot, K. Matthews, B. McEwen, J. Schwartz, T. Seeman, and D. Williams. 2007. Reaching for a Healthier Life: Facts on Socioeconomic Status and Health in the U.S. The John D. and Catherine T. MacArthur Foundation Research Network on Socioeconomic Status and Health [online]. Available: http://www.macses.ucsf. edu/downloads/Reaching_for_a_Healthier_Life.pdf [accessed Jan. 10, 2011]. Apelberg, B.J., T.J. Buckley, and R.H. White. 2005. Socioeconomic and racial disparities in cancer risk from air toxics in Maryland. Environ. Health Perspect. 113(6):693- 699. APHA (American Public Health Association). 2010. Backgrounder: The Hidden Health Costs of Transportation. Prepared by Urban Design 4 Health, Inc. and the Ameri- can Public Health Association, Washington, DC. March 2010 [online]. Available: http://www.apha.org/NR/rdonlyres/8CB9D85D-3592-4C0B-8557-C22E925F75A7 /0/FINALHiddenHealthCostsLongNewBackCover.pdf [accessed Jan. 10, 2011]. Arquette, M., M. Cole, K. Cook, B. LaFrance, M. Peters, J. Ransom, E. Sargent, V. Smoke, and A. Stairs. 2002. Holistic risk-based environmental decision-making: A native perspective. Environ. Health Perspect. 110(suppl. 2):259-264. Backlund, E., P.D. Sorlie, and N.J. Johnson. 1999. A comparison of the relationships of education and income with mortality: The National Longitudinal Mortality Study. Soc. Sci. Med. 49(10):1373-1384. Belkic, K.L., P.A. Landsbergis, P.L. Schnall, and D. Baker. 2004. Is job strain a major source of cardiovascular disease risk? Scand. J. Work Environ. Health 30(2):85- 128. Bhatia, R., and A. Wernham. 2008. Integrating human health into environmental impact assessment: An unrealized opportunity for environmental health and justice. Envi- ron. Health Perspect. 116(8): 991-1000. Boyle, J.P., T.J. Thompson, E.W. Gregg, L.E. Barker, and D.F. Williams. 2010. Projec- tion of the year 2050 burden of diabetes in the U.S. adult population: Dynamic modeling of incidence, mortality, and prediabetes prevalence. Popul. Health Metr. 8:29. Brisbon, N., J. Plumb, R. Brawer, and D. Paxman. 2005. The asthma and obesity epidem- ics: The role played by the built environment—a public health perspective. J. Al- lergy Clin. Immunol. 115(5):1024-1028.
OCR for page 36
36 Improving Health in the U.S.: The Role of Health Impact Assessment Brook, R.D., B. Franklin, W. Cascio, Y. Hong, G. Howard, M. Lipsett, R. Luepker, M. Mittleman, J. Samet, S.C. Smith, Jr., and I. Tager. 2004. Air pollution and cardio- vascular disease: A statement for healthcare professionals from the Expert Panel on Population and Prevention Science of the American Heart Association. Circula- tion 109(21):2655-2671. Brook, R.D., S. Rajagopalan, C.A. Pope III, J.R. Brook, A. Bhatnagar, A.V. Diez-Roux, F. Holguin, Y. Hong, R.V. Luepker, M.A. Mittleman, A. Peters, D. Siscovick, S.C. Smith, Jr., L. Whitsel, and J.D. Kaufman. 2010. Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association. Circulation 121(21):2331-2378. Chakraborty, J., and P.A. Zandbergen. 2007. Children at risk: Measuring racial/ethnic disparities in potential exposure to air pollution at school and home. J. Epidemiol. Community Health 61(12):1074-1079. Chen, S.E., and R.J. Florax. 2010. Zoning for health: The obesity epidemic and opportu- nities for local policy intervention. J. Nutr. 140(6):1181-1184. Church, T.S., D.M. Thomas, C. Tudor-Locke, P.T. Katzmarzyk, C.P. Earnest, R.Q. Ro- darte, C.K. Martin, S.N. Blair, and C. Bouchard. 2011. Trends over 5 decades in U.S. occupation-related physical activity and their associations with obesity. PLoS One. 6(5): e19657. Clougherty, J.E., J.I. Levy, L.D. Kubzansky, P.B. Ryan, S.F. Suglia, M.J. Canner, and R.J. Wright. 2007. Synergistic effects of traffic-related air pollution and exposure to violence on urban asthma etiology. Environ. Health Perspect. 115(8):1140- 1146. Clougherty, J.E., K. Souza, and M.R. Cullen. 2010. Work and its role in shaping the so- cial gradient in health. Ann. NY Acad. Sci. 1186:102-124. Corburn, J. 2005. Street Science: Community Knowledge and Environmental Health Practice. Cambridge, MA: MIT Press. Crimmins, E.M., and Y. Saito. 2001. Trends in healthy life expectancy in the United States 1970-1990: Gender, racial, and educational differences. Soc. Sci Med. 52(11):1629-1641. CSDH (Commission on Social Determinants of Health). 2008. Closing the Gap in a Gen- eration: Health Equity through Action on the Social Determinants of Health. Ge- neva: World Health Organization [online]. Available: http://www.who.int/social_ determinants/thecommission/finalreport/en/index.html [accessed May 11, 2011]. CMS (Centers for Medicare & Medicaid Services). 2010. National Health Expenditure Projections 2009-2019. Centers for Medicare & Medicaid Services, Baltimore, MD [online]. Available: https://www.cms.gov/NationalHealthExpendData/down loads/proj2009.pdf [accessed July 11, 2011]. CMS (Centers for Medicare & Medicaid Services). 2011. National Health Expenditure Web Tables. Centers for Medicare & Medicaid Services, Baltimore, MD [online]. Available: http://www.cms.gov/NationalHealthExpendData/downloads/tables.pdf [accessed June 27, 2011]. Cummings, K.J., and K. Kreiss. 2008. Contingent workers and contingent health: Risks of a modern economy. JAMA 299(4):448-450. Curran, M.A. 1996. Environmental Life Cycle Assessment. New York, NY: McGraw- Hill. Currie, J. and R. Walker. 2011. Traffic congestion and infant health: evidence from E- ZPass. American Econ. J. Appl. Econ. 3(1):65-90. Diez Roux, A.V., and C. Mair. 2010. Neighborhoods and health. Ann. NY Acad. Sci. 186:125-145.
OCR for page 37
37 Why We Need Health-Informed Policies and Decision-Making Din-Dzietham, R., D. Liao, A. Diez-Roux, F.J. Nieto, C. Paton, G. Howard, A. Brown, M. Carnethon, and H.A. Tyroler. 2000. Association of educational achievement with pulsatile arterial diameter change of the common carotid artery: The Athero- sclerosis Risk in Communities (ARIC) Study, 1987-1992. Am. J. Epidemiol. 152(7):617-627. Dominici, F., R.D. Peng, M.L. Bell, L. Pham, A. McDermott, S.L. Zeger, and J.M. Samet. 2006. Fine particulate air pollution and hospital admission for cardiovascu- lar and respiratory diseases. JAMA 295(10):1127-1134. Dow, W.H., R.F. Schoeni, N.E. Adler, and J. Stewart. 2010. Evaluating the evidence base: Policies and interventions to address socioeconomic status gradients in health. Ann. NY Acad. Sci. 1186:240-251. Drewnowski, A. 2010. The cost of U.S. foods as related to their nutritive value. Am. J. Clin. Nutr. 92(5):1181-1188. EPA (U.S. Environmental Protection Agency). 2006. Life Cycle Assessment: Principles and Practice. U.S. Environmental Protection Agency [online]. Available: www. epa.gov/nrmrl/lcaccess/pdfs/600r06060.pdf [accessed June 23, 2011]. Epstein, L.H., S. Raja, S.S. Gold, R.A. Paluch, Y. Pak, and J.N. Roemmich. 2006. Reduc- ing sedentary behavior: The relationship between park area and the physical activ- ity of youth. Psychol. Sci. 17(8):654-659. Ewing, R., and R. Cervero. 2001. Travel and the built environment: A synthesis. Trans- portation Research Record 1780:87-114. Ewing, R., T. Schmid, R. Killingsworth, A. Zlot, and S. Raudenbush. 2003. Relationship between urban sprawl and physical activity, obesity, and morbidity. Am. J. Health Promot. 18(1):47-57. Ferrie, J.E., M.J. Shipley, M.G. Marmot, S. Stansfeld, and G.D. Smith. 1998. The health effects of major organizational change and job insecurity. Soc. Sci. Med. 46(2):243-254. Ferrie, J.E., H. Westerlund, M. Virtanen, J. Vahtera, and M. Kivimäki. 2008. Flexible labor markets and employee health. Scand. J. Work Environ. Health 34(6):98-110. Fields, S. 2004. The fat of the land: Do agricultural subsidies foster poor health? Environ. Health Perspect. 112(14):A820-A823. Fitzhugh, E.C., D.R. Bassett, Jr., and M.F. Evans. 2010. Urban trails and physical activ- ity: A natural experiment. Am. J. Prev. Med. 39(3):259-262. Fleishman, J.A. 2005. Demographic and Clinical Variations in Health Status. MEPS Methodology Report No. 15. Agency for Healthcare Research and Quality, Rock- ville, MD [online]. Available: http://www.meps.ahrq.gov/mepsweb/data_files/pub lications/mr15/mr15.pdf [accessed May 11, 2011]. Frank, J. and K. Cullen. 2006. Preventing injury, illness and disability at work. Scand. J. Work Environ. Health. 32(2):160-167. Frank, L.D., and P. Engelke. 2005. Multiple impacts of the built environment on public health: Walkable places and the exposure to air pollution. Int. Reg. Sci. Rev. 28(2):193-216. Frank, L., and S. Kavage. 2009. A national plan for physical activity: The enabling role of the built environment. J. Phys. Act Health. 6(suppl. 2):S186-S195. Frank, L.D., B. Stone, and W. Bachman. 2000. Linking land use with household vehicle emissions in the central Puget sound: Methodological framework and findings. Transport. Res. D-Tr. E. 5(3):173-196. Frank, L.D., M.A. Andresen, and T.L. Schmid. 2004. Obesity relationships with commu- nity design, physical activity, and time spent in cars. Am. J. Prev. Med. 27(2):87- 96.
OCR for page 38
38 Improving Health in the U.S.: The Role of Health Impact Assessment Frank, L.D., T. Schmid, J.F. Sallis, J. Chapman, and B. Saelens. 2005. Linking objec- tively measured physical activity data with objectively measured urban form: Find- ings from SMARTRAQ. Am. J. Prev. Med. 28(suppl. 2):117-125. Frank, L.D., J.F. Sallis, T. Conway, J. Chapman, B. Saelens, and W. Bachman. 2006. Multiple pathways from land use to health: Association between neighborhood walkability and active transportation, body mass index, and air quality. J. Am. Plann. Assoc. 72(1):75-87. Frank, L.D., M. Bradley, S. Kavage, J. Chapman, and T.K. Lawton. 2007. Urban form, travel time, and cost relationships with tour complexity and mode choice. Trans- portation 35(1):37-54. Franzini, L., M.N. Elliott, P. Cuccaro, M. Schuster, M.J. Gilliland, J.A. Grunbaum, F. Franklin, and S.R. Tortolero. 2009. Influences of physical and social neighborhood environments on child physical activity and obesity. Am. J. Public Health 99(2):271-278. Friedman, M.S., K.E. Powell, L. Hutwagner, L.M. Graham, G. Teague. 2001. Impact of changes in transportation and commuting behaviors during the 1996 Summer Olympic Games in Atlanta on air quality and childhood asthma. JAMA 285(7):897-905. Frohlich, K.L., and L. Potvin. 2008. The inequality paradox: The population approach and vulnerable populations. Am. J. Public Health 98(2):216-221. Gauderman, W.J., E. Avol, F. Lurmann, N. Kuenzli, F. Gilliland, J. Peters, and R. McConnell. 2005. Childhood asthma and exposure to traffic and nitrogen dioxide. Epidemiology 16(6):737-743. Gillen, M., I.H. Yen, L. Trupin, L. Swig, R. Rugulies, K. Mullen, A. Font, D. Burian, G. Ryan, I. Janowitz, P.A. Quinlan, J. Frank, and P. Blanc. 2007. The association of socioeconomic status and psychosocial and physical workplace factors with mus- culoskeletal injury in hospital workers. Am. J. Ind. Med. 50(4):245-260. Gordon-Larsen, P., M.C. Nelson, and K. Beam. 2005. Associations among active trans- portation, physical activity, and weight status in young adults. Obes. Res. 13(5):868-875. Green, R.S., S. Smorodinsky, J.J. Kim, R. McLaughlin, and B. Ostro. 2004. Proximity of California public schools to busy roads. Environ Health Perspect. 112(1):61-66. Gunier, R.B., A. Hertz, J. Von Behren, and P. Reynolds. 2003. Traffic density in Califor- nia: Socioeconomic and ethnic differences among potentially exposed children. J. Expo. Anal. Environ. Epidemiol. 13(3):240-246. Hammitt, J.K. 2007. Valuing changes in mortality risk: Lives saved vs. life years saved. Rev. Environ. Econ. Policy 1(2):228-240. Hannon, C., A. Cradock, S.L. Gortmaker, J. Wiecha, A. El Ayadi, L. Keefe, and A. Har- ris. 2006. Play across Boston: A community initiative to reduce disparities in ac- cess to after-school physical activity programs for inner-city youths. Prev. Chronic Dis. 3(3):A100. Hawkes, C. 2007. Promoting healthy diets and tackling obesity and diet-related chronic diseases: What are the agricultural policy levers? Food Nutr. Bull. 28(suppl. 2):S312-S322. Houston, D., J. Wu, P. Ong, and A. Winer. 2004. Structural disparities of urban traffic in southern California: Implications for vehicle-related air pollution exposure in mi- nority and high-poverty neighborhoods. J. Urban Aff. 26(5):565-592. Jacobsen, J.O., N.W. Hengartner, and T.A. Louis. 2004. Inequity Measures for Evalua- tion of Environmental Justice: A Case Study of Close Proximity to Highways in NYC. Paper 29. Johns Hopkins University, Department of Biostatics Working Pa-
OCR for page 39
39 Why We Need Health-Informed Policies and Decision-Making pers [online]. Available: http://www.bepress.com/cgi/viewcontent.cgi?article=102 9&context=jhubiostat [accessed May 11, 2011]. Jerrett, M., K. Shankardass, K. Berhane, W.J. Gauderman, N. Künzli, E. Avol, F. Gilliland, F. Lurmann, J.N. Molitor, J.T. Molitor, D.C. Thomas, J. Peters, and R. McConnell. 2008. Traffic-related air pollution and asthma onset in children: A prospective cohort study with individual exposure measurement. Environ. Health Perspect. 116(10):1433-1438. Kawachi, I., N.E. Adler, and W.H. Dow. 2010. Money, schooling, and health: Mecha- nisms and causal evidence. Ann. NY Acad. Sci. 1186:56-68. King, H.C., D.L. Hoyert, J.Q. Xu, and S.L. Murphy. 2008. Deaths: Final Data for 2005. National Vital Statistics Reports 56(10). Hyattsville, MD: National Center for Health Statistics. Krieger, N. 2010. Workers are people too: Societal aspects of occupational disparities— an ecosocial perspective. Am. J. Ind. Med. 53(2):104-115. Larson, N.I., M.T. Story, and M.C. Nelson. 2009. Neighborhood environments: Dispari- ties in access to healthy foods in the U.S. Am. J. Prev. Med. 36(1):74-81. Ledikwe, J.H., H.M. Blanck, L. Kettel Khan, M.K. Serdula, J.D. Seymour, B.C. Tohill, and B.J. Rolls. 2006. Dietary energy density is associated with energy intake and weight status in US adults. Am. J. Clin. Nutr. 83(6):1362-1368. Li, F., P.A. Harmer, B.J. Cardinal, M. Bosworth, A. Acock, D. Johnson-Shelton, and J.M. Moore. 2008. Built environment, adiposity, and physical activity in adults aged 50- 75. Am. J. Prev. Med. 35(1):38-46. Link, B.G., and J. Phelan. 1995. Social conditions as fundamental causes of disease. J. Health Soc. Behav. (Spec No):80-94. Lleras-Muney, A. 2005. The relationship between education and adult mortality in the United States. Rev. Econ. Stud. 72(1):189-221. Lopez, R. 2004. Urban sprawl and risk for being overweight or obese. Am. J. Public Health 94(9):1574-1579. Lynch, J.W., G.A. Kaplan, R.D. Cohen, J. Tuomilehto, and J.T. Salonen. 1996. Do car- diovascular risk factors explain the relation between socioeconomic status, risk of all-cause mortality, cardiovascular mortality, and acute myocardial infarction? Am. J. Epidemiol. 144(10):934-942. Mackenbach, J.P., W.J. Meerding, and A.E. Kunst. 2007. Economic Implications of Socioeconomic Inequalities in Health in the European Union. Erasmus MC, De- partment of Public Health, Rotterdam, The Netherlands [online]. Available: http:// survey.erasmusmc.nl/intern/pwp/upload/24/Final%20report%20Macroeconomics% 20July%202007-1.pdf [accessed Aug. 9, 2011]. Mann, J.K., J.R. Balmes, T.A. Bruckner, K.M. Mortimer, H.G. Margolis, B. Pratt, S.K. Hammond, F.W. Lurmann, and I.B. Tager. 2010. Short-term effects of air pollu- tion on wheeze in asthmatic children in Fresno, California. Environ. Health Per- spect. 118(10):1497-1502. Mar, T.F., J.Q. Koenig, and J. Primomo. 2010. Associations between asthma emergency visits and particulate matter sources, including diesel emissions from stationary generators in Tacoma, Washington. Inhal. Toxicol. 22(6):445-448. Marmot, M., and T. Theorell. 1988. Social class and cardiovascular disease: The contri- bution of work. Int. J. Health Serv. 18(4):659-674. Marmot, M., M. Shipley, E. Brunner, and H. Hemingway. 2001. Relative contribution of early life and adult socioeconomic factors to adult morbidity in the Whitehall II study. J. Epidemiol. Community Health 55(5):301-307.
OCR for page 40
40 Improving Health in the U.S.: The Role of Health Impact Assessment Mendoza, J.A., A. Drewnowski, and D.A. Christakis. 2007. Dietary energy density is associated with obesity and the metabolic syndrome in U.S. adults. Diabetes Care 30(4):974-979. Meyer, J.D., N. Warren, and S. Reisine. 2010. Racial and ethnic disparities in low birth weight delivery associated with maternal occupational characteristics. Am. J. Ind. Med. 53(2):153-162. NAGC (National Sustainable Agriculture Coalition). 2010. Healthy Food Financing Ini- tiative Introduced in House, Senate, December 1, 2010. National Sustainable Agri- culture Coalition [online]. Available: http://sustainableagriculture.net/blog/hffi- bill-introduced/ [accessed Jan. 11, 2011]. NHTSA (National Highway Traffic Safety Administration). 2010. Fatality Analysis Re- porting System Encyclopedia. U.S. Department of Transportation, National High- way Traffic Safety Administration [online]. Available: http://www-fars.nhtsa.dot. gov/Main/index.aspx [accessed Jan. 11, 2011]. NRC (National Research Council). 2009. Science and Decisions: Advancing Risk As- sessment. Washington, DC: National Academies Press. NRC (National Research Council). 2010. Hidden Costs of Energy: Unpriced Conse- quences of Energy Production and Use. Washington, DC: National Academies Press. Ogden, C.L., M.D. Carroll, M.A. McDowell, and K.M. Flegal. 2007. Obesity Among Adults in the United States—No Statistically Significant Change Since 2003-2004. NCHS Data Brief no 1. Hyattsville, MD: National Center for Health Statistics [online]. Available: http://www.cdc.gov/nchs/data/databriefs/db01.pdf [accessed May 12, 2011]. Ogden, C.L., M.D. Carroll, and K.M. Flegal. 2008. High body mass index for age among U.S. children and adolescents, 2003-2006. JAMA 299(20):2401-2405. Ostry, A.S., S. Radi, A.M. Louie, and A.D. LaMontagne. 2006. Psychosocial and other working conditions in relation to body mass index in a representative sample of Australian workers. BMC Public Health 6:53-60. Park, S.K., A.H. Auchincloss, M.S. O’Neill, R. Prineas, J.C. Correa, J. Keeler, R.G. Barr, J.D. Kaufman, and A.V. Diez-Roux. 2010. Particulate air pollution, metabolic syndrome and heart rate variability: The multi-ethnic study of atherosclerosis (MESA). Environ. Health Perspect. 118(10):1406-1411. Pohanka, M., and S. Fitzgerald. 2004. Urban sprawl and you: How sprawl adversely af- fects worker health. AAOHN J. 52(6):242-246. Ponce, N.A., K.J. Hoggatt, M. Wilhelm, and B. Ritz. 2005. Preterm birth: The interaction of traffic-related air pollution with economic hardship in Los Angeles neighbor- hoods. Am. J. Epidemiol. 162(2):140-148. Pope III, C.A., and D.W. Dockery. 2006. Health effects of fine particulate air pollution: Lines that connect. J. Air Waste Manage. Assoc. 56(6):709-742. Ritz, B., M. Wilhelm, K.J. Hoggatt, and J.K. Ghosh. 2007. Ambient air pollution and preterm birth in the Environment and Pregnancy Outcomes Study at the University of California, Los Angeles. Am. J. Epidemiol. 166(9):1045-1052. Roberts, E.M. 1997. Neighborhood social environments and the distribution of low birthweight in Chicago. Am. J. Public Health 87(4):597–603. Rosenstock, L., M.R. Cullen, C.A. Brodkin, and C.A. Redlich, eds. 2005. Textbook of Clinical Occupational and Environmental Medicine. Philadelphia: W.B. Saunders. RWJF (Robert Wood Johnson Foundation). 2009. Beyond Health Care: New Directions to a Healthier America. Robert Wood Johnson Foundation Commission to Build a
OCR for page 41
41 Why We Need Health-Informed Policies and Decision-Making Healthier America [online]. Available: http://www.rwjf.org/pr/product.jsp?id=410 08 [accessed Jan. 10, 2011]. Saelens, B.E., J.F. Sallis, J.B. Black, and D. Chen. 2003. Neighborhood-based differences in physical activity: An environment scale evaluation. Am. J. Public Health 93(9):1552-1558. Salam, M.T., J. Millstein, Y.F. Li, F.W. Lurmann, H.G. Margolis, and F.D. Gilliland. 2005. Birth outcomes and prenatal exposure to ozone, carbon monoxide, and par- ticulate matter: Results from the Children’s Health Study. Environ. Health Per- spect. 113(11):1638-1644. Schulte, P.A., G.R. Wagner, A. Ostry, L.A. Blanciforti, R.G. Cutlip, K.M. Krajnak, M. Luster, A.E. Munson, J.P. O’Callaghan, C.G. Parks, P.P. Simeonova, and D.B. Miller. 2007. Work, obesity, and occupational safety and health. Am. J. Public Health 97(3):428-436. Schulz, A., and M. Northridge. 2004. Social determinants of health: Implications for environmental health promotion. Health Educ. Behav. 31(4):455-471. Siegrist, J. 1996. Adverse health effects of high-effort/low-reward conditions. J. Occup. Health Psychol. 1(1):27-41. Slama, R., V. Morgenstern, J. Cyrys, A. Zutavern, O. Herbarth, H.E. Wichmann, J. Heinrich, and LISA Study Group. 2007. Traffic-related atmospheric pollutant lev- els during pregnancy and offspring’s term birth weight: A study relying on a land- use regression exposure model. Environ. Health Perspect. 115(9):1283-1292. Sturm, R. 2008. Disparities in the food environment surrounding U.S. middle and high schools. Public Health 122(7):681-690. Tillotson, J.E. 2004. America’s obesity: Conflicting public policies, industrial economic development, and unintended human consequences. Ann. Rev. Nutr. 24:617-643. TRB (Transportation Research Board). 2005. Does the Built Environment Influence Physical Activity? Examining the Evidence. Transportation Research Board Spe- cial Report 282. Washington, DC: Transportation Research Board. Truong, K., M. Fernandes, R. An, V. Shier, and R. Sturm. 2010. Measuring the physical food environment and its relationship with obesity: Evidence from California. Pub- lic Health 124(2):115-118. UCBHIG (University of California Berkeley Health Impact Group). 2007. Oak to Ninth Avenue HIA. University of California Berkeley Health Impact Group, June 2007 [online]. Available: http://sites.google.com/site/ucbhia/projects-and-research [ac- cessed June 2, 2010]. Wang, J., R. Luben, K.T. Khaw, S. Bingham, N.J. Wareham, and N.G. Forouhi. 2008. Dietary energy density predicts the risk of incident type 2 diabetes: The EPIC- Norfolk study. Diabetes Care 31(11):2120-2125. WHO (World Health Organization). 2001. Macroeconomics and Health: Investing in Health for Economic Development. Report of the Commission on Microeconomics and Health. Geneva: World Health Organization [online]. Available: http://www. paho.org/english/hdp/hdd/sachs.pdf [accessed May 13, 2011]. WHO (World Health Organization). 2002. The World Health Report 2002: Reducing Risks, Promoting Healthy Life. Geneva: World Health Organization [online]. Available: http://www.who.int/whr/2002/en/index.html [accessed Jan. 10, 2011]. WHO (World Health Organization). 2010. World Health Statistics: 2010. Geneva: World Health Organization [online]. Available: http://www.who.int/whosis/whostat/en/ [accessed Jan. 10, 2011].
OCR for page 42
42 Improving Health in the U.S.: The Role of Health Impact Assessment Wier, M., J. Weintraub, E.H. Humphreys, E. Seto, and R. Bhatia. 2009. An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning. Accid. Anal. Prev. 41(1):137-145. Williams, D.R., S.A. Mohammed, J. Leavell, and C. Collins. 2010. Race, socioeconomic status, and health: Complexities, ongoing challenges, and research opportunities. Ann. NY Acad. Sci. 1186:69-101. Woodruff, T.J., L.A. Darrow, and J.D. Parker. 2008. Air pollution and postneonatal in- fant mortality in the United States, 1999-2002. Environ. Health Perspect. 116(1):110-115. Wu, S.Y., and A. Green. 2000. Projection of Chronic Illness Prevalence and Cost Infla- tion. Santa Monica, CA: RAND. Wu, Y.C., and S.A. Batterman. 2006. Proximity of schools in Detroit, Michigan to auto- mobile and truck traffic. J. Expo. Sci. Environ. Epidemiol. 16(5):457-470.