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In the United States, some populations suffer from far greater disparities in health than others. Those disparities are caused not only by fundamental differences in health status across segments of the population, but also because of inequities in factors that impact health status, so-called determinants of health. Only part of an individual's health status depends on his or her behavior and choice; community-wide problems like poverty, unemployment, poor education, inadequate housing, poor public transportation, interpersonal violence, and decaying neighborhoods also contribute to health inequities, as well as the historic and ongoing interplay of structures, policies, and norms that shape lives. When these factors are not optimal in a community, it does not mean they are intractable: such inequities can be mitigated by social policies that can shape health in powerful ways. Communities in Action: Pathways to Health Equity seeks to delineate the causes of and the solutions to health inequities in the United States. This report focuses on what communities can do to promote health equity, what actions are needed by the many and varied stakeholders that are part of communities or support them, as well as the root causes and structural barriers that need to be overcome.
To what extent may highway investments shape population growth and land development? To answer this question, three decades of data were examined in the Virginia locations of Fairfax County, Spotsylvania County, and Newport News. In each location, a highway investment (or deliberate decision not to make such an investment) was proposed by some as an instrument for increasing, shaping, or decreasing population or development growth. The case study approach was used, considering Fairfax County's decision not to build Monticello and other freeways proposed in 1960s comprehensive plans, Spotsylvania's efforts to manage Route 3 traffic congestion, and Newport News' desire for the construction of I-664. By comparing what planners intended these transportation decisions to accomplish with what transpired, the adequacy of using highway investments to influence growth may be assessed. The results suggest that in many ways, transportation investments are a blunt policy instrument. They can and do affect short-term travel and longer term location choices, but it is difficult to use investments to manage growth precisely. In fact, in none of the three case studies were all planners' intentions realized: when planned roads were not built in order to stop growth, growth continued, and when roads were built to encourage development or redevelopment in a specific location, growth occurred elsewhere. Yet, the three case studies suggest several findings that, if applied to planning practice, can yield future plans that are more realistic: (1) view transportation improvements in a supply/demand context; (2) quantify expected impacts where possible; (3) give transportation plans a realistic implementation mechanism; and (4) present forecasts as ranges rather than point values. Although these practices may be "common sense," their explicit consideration may facilitate planning efforts in the short run. However, an unintended consequence of reviewing the case study histories is that they strongly suggest Virginia counties have limited options for managing growth. To some extent, counties can influence the specific location of growth and what type is attracted--but the case studies leave the impression that if the market is there to support growth, eventually it will come. Within Virginia's current legal environment, counties have limited options for how they can accommodate this growth.
The focus of this research is Virginia's Secondary Highway Construction System funding allocations and its impact on statewide deficient lane miles reduction. The research question guiding this study is: "Which of the four allocation models -- the current Secondary Highway System allocation model or one of three alternatives of this model based on Brian D. Taylor's geographic equity categories (outcome, opportunity, and market) best maximizes statewide deficient lane miles reductions?" Taylor defines each of these geographic equity categories (independent variables for this study) for all levels of government. While Taylor's research focus has been on equity as it relates to transit and congestion pricing, this study applied his construct to highways. As a result of scanning subjects related to transportation, the need for this study became apparent. Since the 1980's, Virginia's highway allocation formula has not changed (Virginia Department of Transportation, 2005). The Virginia General Assembly has sponsored follow-up studies through a series of resolutions over the years (Auditor of Pubic Accounts, 2004). To date, none of the legislatively sponsored research findings have prompted an update of Virginia's highway allocation formula (Virginia Transportation Research Council, 2008). There is a significant academic and professional literature on federal transportation politics and specific transportation engineering issues. However, there is very limited research on the development of state level highway transportation funding methodologies. This study used the quantitative research approach, which is concerned with determining the relationship between one factor (an independent variable) and another (a dependent or outcome variable) in a population (Walker, 2005, Newman, 1998, and Geddes, 1990). Therefore, this study employed the quantitative research approach to study cause and effect (Mulhall, 2004, Loughborough, 1995, and Collier 1995) relationships of Virginia's Secondary construction allocations to individual counties and statewide deficient lane miles reductions overall. The .20 portion of the formula for area was examined because this data rarely changes due to locality annexations. Conversely, the .80 portion of the formula was excluded from the analysis because of the demographic variability due to population shifts. As such, the Federal Highway Administration and states update population statistics from the decennial census with the apportionment of funds for formula based programs such as Virginia's Secondary Highway Construction program (Federal Register, 2002). This researcher concluded that of the four geographic allocation models, the geographic opportunity equity maximized an additional 4.15 statewide deficient lane miles reductions over the baseline model. This study recommends using the geographic opportunity equity model when allocating Virginia's Secondary Highway Construction funds to maximize the statewide deficient lane miles reductions above the baseline model, the geographic market equity model and the geographic outcome equity model.