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Children and adolescents can engage in an active lifestyle by walking to school; however, several barriers may limit this behavior. This study estimates the prevalence of walking to school and related barriers as reported by U.S. parents. Data from the 2017 SummerStyles, a Web-based survey conducted on a nationwide sample of U.S. adults, were analyzed in 2017. Parents of children aged 5–18 years (n = 1137) were asked whether their youngest child walked to or from school during a usual school week and what barriers make this difficult. Frequencies are presented overall and by parent characteristics. About 1 in 6 parents (16.5%) reported their youngest child walks to or from school at least once during a usual week. Prevalence differed by parental race/ethnicity, marital status, region, and distance from school. The most common barrier was living too far away (51.3%), followed by traffic-related danger (46.2%), weather (16.6%), “other” barrier (14.7%), crime (11.3%), and school policy (4.7%). The frequency at which parents reported certain barriers varied by their child's walking status, distance to school, age of youngest child, race/ethnicity, education level, household income, and metropolitan statistical area status. However, the relative ranking of barriers did not differ by these characteristics. Prevalence of walking to school is low in the U.S., and living too far away and traffic-related danger are common barriers reported by parents. Implementing Safe Routes to School programs and other initiatives that utilize strategies to overcome locally-relevant barriers could help increase the prevalence of children walking to school.

Objective: Studies addressing effective contraceptive use by population density are lacking. We hypothesize that contraception counseling and effective contraception use vary by population density. Study Design: This is a cross-sectional study using the 2006-2010 National Survey of Family Growth data, including female subjects ages 15 to 19. The primary exposure was population density, defined as Principal city of a Metropolitan Statistical Area (MSA) or “city”, Other MSA or “non-city urban”, and Not MSA or “rural.” The primary outcome was effective contraception use and the secondary outcome was contraceptive counseling exposure. Multivariate analysis using logistic regression was performed to estimate the association between population density and effective contraception use, as well as the likelihood of receiving contraceptive counseling. Results: 2284 subjects were studied. Compared to non-city urban dwellers, city adolescents had similar effective contraception use (aOR: 0.99, [0.79, 1.24]), whereas rural adolescents had significantly higher use (aOR: 1.79, [1.35, 2.36]). Among sexually active respondents who were not using contraception, the rate of contraception counseling in non-city urban adolescents was 66.7%. In comparison, the city dwellers had higher rate of counseling (79.1%, aOR: 1.87; 95% CI: [1.09, 3.22]). Similarly, rural adolescents also had higher rate of counseling (81.5%, aOR: 2.37; 95% CI: [1.08, 5.19]). Conclusions: Rural residents were more likely to use effective contraception methods than their city and non-city urban counterparts. However, higher rates of contraception counseling among sexually active adolescents not using contraception in city and rural densities could suggest ineffective counseling in these groups.

Auditing standards require auditors to evaluate the reasonableness of reported fair value estimates, but audit regulators frequently cite auditors for deficiencies in these estimates. Specific to goodwill, auditors must evaluate the probability that recorded goodwill is impaired. Based on small sample frames and availability theories, we predict that experiencing a recorded impairment at an unrelated client increases auditors’ internal perceived probability of downside risk. As a result, we expect more impairments at subsequent clients with economic indicators of impairment. Using a sample of 7,500 client-years from 2004-2014 with potential goodwill impairments, we find evidence consistent with our expectation at the audit office level. We also find evidence at the metropolitan statistical area and non-Big 4 audit firm levels; however, consistent with our expectation that the closer the auditor is to the prior impairment the stronger the effect, the audit office level effect is stronger than the other two levels and is especially strong in audit offices below the median size. Our study suggests that enhancing knowledge sharing around experienced goodwill impairments could help improve auditor difficulties in auditing uncertain fair value estimates and increase recognition of goodwill impairments.

If house prices in one metropolitan statistical area (MSA) are increasing much faster than in another MSA, should one infer that overall inflation is also much faster in the former?

Author(s): Godoy, Mariela | Abstract: Innovation has increased dramatically since the advent of the 1765 steam machine. Today, we possess technology that can process millions of instructions in a matter of seconds. Endogenous growth theory has stressed the importance of technological change and education as a source of economic growth. Thanks to technological innovation and the related economic growth, many people are better off today than before. However, computers cannot mimic human capacity in creativity and the ability to envision new solutions to existing problems. The rate at which workers use these unique capabilities is industry related. Therefore, in this study I relate the proportion of workers in each industry to known industry level innovation rates to predict economic growth rates at the local level. This study is especially important, as it guides policy makers as to what incentives they might use to attract new industries to bolster their future economic well being. Specifically, this study analyzes how innovation and other factors impact growth in the United States through the years 2005-2015 at the Metropolitan Statistical Area (MSA) using a lagged first-difference quantitative statistical model. This model is well matched to the structure of the data in revealing causality between the independent variables and the dependent. Results indicate no significant relationship between innovation, as measured by localized Multifactor Productivity (MFP), and growth. However, results do indicate a strong relationship between educational attainment and economic growth. Quantitative analysis reveals that a 1% increase in average years of education within an MSA will, on average, cause an increase in localized GDP the following year by 2.33%. Future research is encouraged to better understand the matter and to determine policies that can aid educational attainment and thus, boost economic growth.

To address urban problems and for planning and zoning purposes, city planners need to understand urban growth. This chapter reviews the classic internal structure models and urban system modeling. Urban models have a relatively short history. Early city structure and growth analysis dates back to the 1920s University of Chicago sociologists. De-densification and horizontal urban expansion lead to a polycentric urban form. Urban form and transport are interrelated. Changes in activity distribution impact travel including journey to work. Studying urban form changes helps understand changes in travel patterns including commuting. The impact of spatial structure (employment locations) upon commuting is investigated in the Baton Rouge Metropolitan Statistical Area. Commuting is studied under monocentric and polycentric assumptions. Comparison of two spatial separation measures including commute time and length supports “co-location theory” with polycentric structure contributing to commuting reduction.

Rising economic segregation suggests a need to examine constraints to job access by race/ethnicity and economic inequality simultaneously. This often requires detailed socio-spatial interaction data to make progress on theoretical and modeling development, empirical studies and policy insights. Commuting data are commonly used because of its wide availability. Despite excellent work trip datasets from the U.S. Census such as the Census Transportation Planning Package and the Longitudinal Employer-Household Dynamics (LEHD) data, there are often gaps between the data that are available and ideal detailed commuting data suited to models and data analysis. This is because commuting data are available for a limited set of socio-economic dimensions and this coarseness limits researchers in their ability to uncover nuances of place-based generalizations about commuting, either socially or spatially. In one promising approach, an information minimizing technique was proposed as a workable practical method to synthesize disaggregated work trip flows. Because the strength of fit between predicted and observed trips is unknown, this paper validates this method using real commutes disaggregated by income and then synthesizes race–income work trips using LEHD data for the Wichita, Kansas metropolitan statistical area. We find that low-income Whites travel longer distances and have more dispersed travel patterns than all African-American and Asian income groups and that both low- and middle-income groups of all race groups have spatially constrained flows.

Volunteering has often been cited as a potential pathway for economic opportunity for the out of work to increase their job prospects, but little empirical research has been conducted on the topic. Using a nationally representative data set of 70,535 unemployed persons across a 10-year period (2002-2012) from the U.S. Current Population Survey, we found that when out of work in Year 1, those who volunteered had a 27% higher likelihood of being employed in Year 2, compared with those who did not volunteer. The relationship between volunteering and employment was strongest for individuals without a high school diploma and persons living in rural areas, where the increased likelihood of being employed in Year 2 for volunteers was 51% and 55%, respectively. We found that the relationship between volunteering and employment is stable across gender, race and ethnic categories, age, time, metropolitan statistical area (MSA), and unemployment rate.

Determining the spatial distribution of gay and lesbian households is relevant to understanding gay and lesbian identity and empowerment, and it has been a goal for geographers over the past half century. Our paper answers to calls for investigations of gay and lesbian geography beyond traditional enclaves. We use 9210 street addresses of advertised rental and for-sale properties posted between 1986 and 2012 in the gay and lesbian-oriented Dallas Voice to map historical changes in the spatial distribution of the Dallas-Fort Worth Metropolitan Statistical Area’s gay and lesbian population. We show how gay and lesbian markets contrast with those of all Dallas-Fort Worth Metropolitan Statistical Area renters and homeowners, and consider our data in light of Dallas Voice coverage of how the location of the gay and lesbian population has shifted. Among other things, we find that advertisements have come to feature properties further from gay bars, and in census tracts of higher income, education levels, and rents, but that these advertisements also have consistently featured properties in census tracts with older construction and a higher proportion of same-sex coupled households. Our findings provide evidence of dispersion from old enclaves and reclustering in new areas, suggesting both lesser attachment to traditional enclaves, and the continuing importance of proximity to each other for gay and lesbian households.

Purpose. To develop a reliable observational data collection instrument to measure characteristics of the fast-food restaurant environment likely to influence consumer behaviors, including product availability, pricing, and promotion. Design. The study used observational data collection. Setting. Restaurants were in the Chicago Metropolitan Statistical Area. Subjects. A total of 131 chain fast-food restaurant outlets were included. Measures. Interrater reliability was measured for product availability, pricing, and promotion measures on a fast-food restaurant observational data collection instrument. Analysis. Analysis was done with Cohen's κ coefficient and proportion of overall agreement for categorical variables and intraclass correlation coefficient (ICC) for continuous variables. Results. Interrater reliability, as measured by average κ coefficient, was .79 for menu characteristics, .84 for kids' menu characteristics, .92 for food availability and sizes, .85 for beverage availability and sizes, .78 for measures on the availability of nutrition information, .75 for characteristics of exterior advertisements, and .62 and .90 for exterior and interior characteristics measures, respectively. For continuous measures, average ICC was .88 for food pricing measures, .83 for beverage prices, and .65 for counts of exterior advertisements. Conclusion. Over 85% of measures demonstrated substantial or almost perfect agreement. Although some measures required revision or protocol clarification, results from this study suggest that the instrument may be used to reliably measure the fast-food restaurant environment.

Location-based social media provide an enormous stream of data about humans' life and behavior. With geospatial methods, those data can offer rich insights into public health. In this research, we study the effect of climate and seasonality on the prevalence of depression in Twitter users in the U.S. Text mining and geospatial methods are used to detect tweets related to depression and their spatiotemporal patterns at the scale of Metropolitan Statistical Area. We find the relationship between depression rates, climate risk factors and seasonality are varied and geographically localized. The same climate measure may have opposite association with depression rates at different places. Relative humidity, temperature, sea level pressure, precipitation, snowfall, weed speed, globe solar radiation, and length of day all contribute to the geographic variations of depression rates. A conceptual compact map is designed to visualize scattered geographic phenomena in a large area. We also propose a three-stage framework that semi-automatically detects and analyzes geographically distributed health issues using location-based social media data.

The scope of empirical environmental justice (EJ) research has expanded beyond hazards exposure to scrutinize social inequities in access to amenities, but no prior study has examined the EJ implications of public beach access. Furthermore, quantitative research on white privilege is very scarce. To address these knowledge gaps, our study examines racial/ethnic and socioeconomic inequities in access to public beaches in the Miami metropolitan statistical area, Florida. Public beach accessibility is modeled with an innovative geospatial approach that involves population weighted distances to beach access sites. To assess EJ implications of public beach access for various racial/ethnic and socioeconomically vulnerable groups, spatial regression models are estimated using census tract-level data. Results indicate that beaches are more accessible to neighborhoods with a higher proportion of non-Hispanic Whites, while neighborhoods with higher percentages of Hispanics and socioeconomically disadvantaged residents have limited access. This study demonstrates the importance of assessing white privilege and access to environmental amenities in EJ research to better understand social inequities.

This paper demonstrates the application of the local geographically weighted regression (GWR) method to mortgage studies, using the Philadelphia metropolitan statistical area (MSA) as a case study. Previous related studies widely employed the global, ordinary least square (OLS) method to examine the spatial distribution of subprime/higher priced mortgages. The OLS method, however, masks the spatial variations in mortgage distributions. The innovative GWR method not only provides a significant improvement in model fitness but also reveals that the statistical relationships between neighborhood characteristics and the prevalence of higher priced mortgage shares are spatially varied. In addition, the GWR method can bring forward potential implications for place-based policy making. Improving upon previous methodologies in mortgage studies, this paper shows that the GWR method can advance our understanding of how neighborhood environments are associated with mortgage lending patterns.

This paper applies the dynamic panel data generalized method of moments estimator to the data on commercial passenger air traffic at all primary airports in the United States to evaluate the impact of traffic volume and number of destinations served with non-stop flights on the key indicators of regional economic development. We find that number of destinations served with non-stop flights has a much clearer and more robust impact on level of employment, number of business establishments, and average wage in the region. Passenger traffic volume affects employment and average wage, but not number of establishments. At the sample median, connecting a metropolitan statistical area with an extra destination, keeping everything else constant, creates 98 jobs and facilitates the opening of four new business establishments that employ people. The corresponding numbers for the sample mean are 223 jobs and 15 businesses. The impact of air travel on regional economic development is influenced by competition on the respective airline markets.

In this study, we explored the spatial and temporal patterns of land cover and land use (LCLU) and population change dynamics in the St. Louis Metropolitan Statistical Area. The goal of this paper was to quantify the drivers of LCLU using long-term Landsat data from 1972 to 2010. First, we produced LCLU maps by using Landsat images from 1972, 1982, 1990, 2000, and 2010. Next, tract level population data of 1970, 1980, 1990, 2000, and 2010 were converted to 1-km square grid cells. Then, the LCLU maps were integrated with basic grid cell data to represent the proportion of each land cover category within a grid cell area. Finally, the proportional land cover maps and population census data were combined to investigate the relationship between land cover and population change based on grid cells using Pearson's correlation coefficient, ordinary least square (OLS), and local level geographically weighted regression (GWR). Land cover changes in terms of the percentage of area affected and rates of change were compared with population census data with a focus on the analysis of the spatial-temporal dynamics of urban growth patterns. The correlation coefficients of land cover categories and population changes were calculated for two decadal intervals between 1970 and 2010. Our results showed a causal relationship between LCLU changes and population dynamics over the last 40 years. Urban sprawl was positively correlated with population change. However, the relationship was not linear over space and time. Spatial heterogeneity and variations in the relationship demonstrate that urban sprawl was positively correlated with population changes in suburban area and negatively correlated in urban core and inner suburban area of the St. Louis Metropolitan Statistical Area. These results suggest that the imagery reflects processes of urban growth, inner-city decline, population migration, and social spatial inequality. The implications provide guidance for sustainable urban planning and development. We also demonstrate that grid cells allow robust synthesis of remote sensing and socioeconomic data to advance our knowledge of urban growth dynamics from both spatial and temporal scales and its association with population change.

BACKGROUND The authors investigated whether residential segregation (the degree to which racial/ethnic groups live separately from one another in a geographic area) 1) was associated with mortality among urban women with breast cancer, 2) explained racial/ethnic disparities in mortality, and 3) whether its association with mortality varied by race/ethnicity. METHODS Using Texas Cancer Registry data, all-cause mortality and breast-cancer mortality were examined among 109,749 urban black, Hispanic, and white women aged ≥50 years who were diagnosed with breast cancer from 1995 to 2009. Racial (black) segregation and ethnic (Hispanic) segregation of patient's neighborhoods were measured and were compared with the larger metropolitan statistical area using the location quotient measure. Shared frailty Cox proportional hazard models were used to nest patients within residential neighborhoods (census tract) and were controlled for race/ethnicity, age, diagnosis year, tumor stage, grade, histology, neighborhood poverty, and county-level mammography availability. RESULTS Greater black segregation and Hispanic segregation were adversely associated with cause-specific mortality and all-cause mortality. For example, in adjusted models, Hispanic segregation was associated with cause-specific mortality (adjusted hazard ratio, 1.24; 95% confidence interval, 1.05-1.46). Compared with whites, blacks had higher mortality for both outcomes, whereas Hispanics demonstrated equivalent (cause-specific) or lower (all-cause) mortality. Segregation did not explain racial/ethnic disparities in mortality. Within each race/ethnicity strata, segregation was either adversely associated with mortality or was not significant. CONCLUSIONS Among urban women with breast cancer in Texas, segregation has an independent, adverse association with mortality, and the effect of segregation varies by patient race/ethnicity. The novel application of a small-area measure of relative racial segregation should be examined in other cancer types with documented racial/ethnic disparities across varied geographic areas. Cancer 2015;121:1845–1855. © 2015 American Cancer Society.

Over the past decade, both the housing market and the subprime mortgage market in the United States experienced a rise and fall. To explore whether subprime lending has increased or decreased social inequality between subprime neighborhoods and nonsubprime neighborhoods, this article examines the relationship between subprime mortgages and housing price variations within the Philadelphia Metropolitan Statistical Area (MSA), using a global, ordinary least squares (OLS) method and a local, geographically weighted regression (GWR) method. The results show that neighborhoods obtaining disproportionate numbers of subprime mortgages enjoyed lower housing price appreciation rates than other neighborhoods during the housing boom era but suffered higher housing price depreciation rates during the housing bust era, after controlling for other variables. The results also show that the association between housing price variations and explanatory variables differs across geographic submarkets. The empirical evidence d...

The study highlights the critical purchasing power disparity (gap) and its applicable solutions in the Albany Metropolitan Statistical Area (Albany MSA). This disparity explains a high level of poverty among African Americans in the MSA. With an improved education, the article encourages minority businesses partnerships and entrepreneurship, and microfinancing to enhance minority capital formation. These have been proven to have a spread effect in reducing poverty and purchasing power disparity.

Using Consumer Expenditure Survey data this paper shows that more educated workers demand more high-skill-intensive services and, to a lesser extent, more very low-skill-intensive services (such as personal services). Additional evidence at the Metropolitan Statistical Area (MSA) level shows that this “education elasticity of demand” mechanism can explain part of the correlation between the share of college-educated workers in a city and the employment share of service industries. The parametrization of a simple model suggests that this induced demand shift can explain around 6.5 percent of the relative demand shift in the United States between 1984 and 2002. Similar results are provided for the United Kingdom. (JEL D12, J24, J31, L84)

The HIV care continuum has gained significant traction as a useful framework among both public health practitioners and academic researchers. The continuum estimates the proportion of HIV-infected persons who are HIV diagnosed, linked to and retained in care, initiated on antiretroviral therapy, and virally suppressed. Public health practitioners are increasingly being called upon (and required) to estimate and improve the HIV care continuum in their jurisdiction (e.g., state, dependent area, and metropolitan statistical area). Public health estimates of the HIV care continuum typically rely on CD4 counts and viral loads reported to HIV surveillance. In this issue of Sexually Transmitted Diseases, Toren et al. use surveillance data to show that the time between HIV diagnosis and viral suppression for persons diagnosed as having HIV in Seattle & King County decreased dramatically from 2007 to 2013. We welcome the contribution by Toren et al. as a valuable and timely contribution to the literature on the effects of rapidly changing treatment paradigms on improvements in the HIV care continuum. Being population-based, public health surveillance data offer a unique opportunity to obtain unbiased estimates of the HIV care continuum. Estimation of the HIV care continuum is inherently limited in clinical cohorts. Namely, clinical cohorts represent a nonrandom subset of all HIV-diagnosed persons who (1) ever entered care and (2) remained in care at the clinic where the cohort is based. Because surveillance data are population-based, the recent work by Toren et al. has the advantage of being able to include all persons diagnosed as having HIV in Seattle & King County, including persons who never enter care and never achieve viral suppression. The inclusion of persons diagnosed as having HIV avoids bias inherent in clinic-based analyses: (1) of absolute time toviral suppression if personswho never enter care and thus never suppress are excluded from the risk set, (2) of characteristics associated with prompt viral suppression if HIV-infected persons who enter care differ from those who do not enter care, and (3) of changing time to viral suppression over calendar time if the characteristics of HIV-infected persons who entered care varied over time. Most clinics do not have the resources for extensive patient tracing if patients fail to return for follow-up. Patients may leave a clinic because they move out of the area, switch clinical providers within the same area, or fall out of clinical care; this information is not generally recorded. In one clinical cohort, loss to clinic was substantial (5-year risk, 46%), yet mortality among persons lost to clinic was similar to mortality among persons retained in care, suggesting that some of those who were lost to clinic likely entered care elsewhere and loss to clinic may overestimate loss to care. Because public health surveillance data are not clinic based, they (hypothetically) capture laboratory measures for HIV-infected patients, regardless of the provider who ordered the laboratories, and therefore follow patients if they change clinics within the same area. (Rules for laboratory reporting and levels of compliance with reporting rules vary across jurisdictions.) However, public health surveillance data still cannot typically distinguish between persons who move out of jurisdiction and persons who are lost to care. Seattle & King County is one of very few public health agencies that have gathered additional information to distinguish out-migration from loss to care so that emigrants can be censored. Indeed, Seattle & King County is also one of a minority of public health jurisdictions that have been collecting laboratory surveillance data consistently enough to be able to estimate changes in time to viral suppression. Name-based reporting of HIV diagnoses was not implemented in all 50 states until 2008, a full year after follow-up in the analysis by Toren et al. began. From 2011 to 2013, of 50 states and 6 dependent areas, only 19, 18, and 28 jurisdictions (respectively) had laboratory data that were estimated to be at least 95% complete. These observations serve to illustrate both how quickly HIV

The Atlanta metropolitan area encompasses 20 northern Georgia counties and includes development patterns that range from very urban to very rural. The Atlanta metropolitan area was the ninth-largest metropolitan statistical area (MSA) in the United States in 2010. In 1994, responding to the attention that would be on the city of Atlanta in 1996, and that would reveal the poor physical and social conditions in Atlanta's large housing projects, Atlanta Housing Authority (AHA) embarked on an ambitious program to redevelop more than a dozen large sites. Without a large body of water or mountain range nearby, the Atlanta metropolitan area has no physical barriers to growth. This chapter gives a general picture of Atlanta and the Atlanta metropolitan area covering key demographic indicators, primarily for the years 2000 and 2010. It discusses that the increase in the percentage of Hispanics was especially significant in Gwinnett County.

The Memphis Metropolitan Statistical Area evidences social problems common to large urban areas, including crime, infant mortality, bankruptcy, and housing stock decay. Responding to these public issues and needs, the nonprofit sector in the Mid-South is a diverse and vibrant part of the local environment. This chapter illustrates the instrumental role of a champion in selling the initial need for the collaborative effort, bringing key players and funding to the table, and allowing quick movement through the early stages of the collaboration life cycle. At the same time, the champion’s role had to be tempered with demands for greater levels of involvement from all participants. Developing policies and procedures that spell out tenure of office and responsibilities for key roles enabled the collaboration to move beyond “founder’s syndrome.” The history of collaboration among many of the participants allowed significant changes in leadership to occur without inhibiting the effort’s progress.

Portland Metro's actions embody many elements of the smart growth strategy. Although a few Southern California cities, especially in Ventura County, have passed smart growth ballot initiatives, most jurisdictions remain predisposed to development. The chapter focuses on aggregate population and employment data in the metropolitan regions. The Los Angeles Consolidated Metropolitan Statistical Area consists of five counties: Los Angeles, Orange, Riverside, San Bernardino, and Ventura. The comparison that many observers find hard to believe is that Portland, despite decades of density-promoting planning, has such a low density compared to Los Angeles. The rationale for the focuses on Portland is justified by its reputation as a paradigm for urban sustainability efforts. The chapter suggests that smart growth ballot initiatives are more window-dressing than a recipe for change. It argues by drawing some parallels with Los Angeles, widely regarded as the epitome of unsustainability.

Objectives: We examined the survival rates after diagnosis of HIV infection stage 3 (AIDS) in the United States by population density area of residence at diagnosis. Methods: We used data from the National HIV Surveillance System to calculate survival rates among people aged ≥13 with HIV infection stage 3 (AIDS) diagnosed from 2005 through 2010. We determined survival rates for more than 12, 24, and 36 months after diagnosis; overall and by demographic characteristics; and across 3 population density area categories (large metropolitan statistical areas [MSAs, ≥500 000 people], small-to-medium MSAs [50 000 to 499 999 people], and nonmetropolitan areas [Results: The survival rates for more than 12, 24, and 36 months after diagnosis were highest among people residing in large MSAs (90.2%, 87.2%, and 84.9%, respectively) and lowest among people residing in nonmetropolitan areas (87.3%, 84.1%, and 81.4%, respectively). With a few exceptions, survival rates were lower in those residing in nonmetropolitan areas than those residing in large MSAs and small-to-medium MSAs across most subgroups by age at diagnosis, race/ethnicity, sex, transmission category, region of residence, and year of diagnosis. Between 2005 and 2010, significant year-to-year increases occurred in the proportion of people surviving more than 36 months after diagnosis across all 3 population density area categories (estimated annual percentage change: large MSAs [0.88; 95% confidence interval (CI), 0.56-1.20]; small-to-medium MSAs [0.94; 95% CI, 0.06-1.83]; and nonmetropolitan areas [1.26; 95% CI, 0.07-2.46]). Conclusions: Although survival rates for those with HIV infection stage 3 (AIDS) improved in all 3 population density area categories, efforts to remove barriers to care and promote treatment adherence in nonmetropolitan areas will be necessary to eliminate survival disparities.

In the US, the non-Hispanic Black infant mortality rate exceeds the rate among non-Hispanic Whites by more than two-fold. To explore factors underlying this persistent disparity, we employed a mixed methods approach with concurrent quantitative and qualitative data collection and analysis. Eighteen women participated in interviews about their experience of infant loss. Several common themes emerged across interviews, grouped by domain: individual experiences (trauma, grieving and counseling; criminalization); negative interactions with healthcare providers and the healthcare system; and broader contextual factors. Concurrently, we estimated the Black infant mortality rate (deaths per 1000 live births) using linked live birth-infant death records from 2010 to 2013 in every metropolitan statistical area in the US. Poisson regression examined how contextual indicators of population health, socioeconomic conditions of the Black population, and features of the communities in which they live were associated with Black infant mortality and inequity in Black–White infant mortality rates across 100 metropolitan statistical areas with the highest Black infant mortality rates. We used principal components analysis to create a Birth Equity Index in order to examine the collective impact of contextual indicators on Black infant mortality and racial inequity in mortality rates. The association between the Index and Black infant mortality was stronger than any single indicator alone: in metropolitan areas with the worst social, economic, and environmental conditions, Black infant mortality rates were on average 1.24 times higher than rates in areas where conditions were better (95% CI = 1.16, 1.32). The experiences of Black women in their homes, neighborhoods, and health care centers and the contexts in which they live may individually and collectively contribute to persistent racial inequity in infant mortality.

Objective To determine the impact of community participation on nonprofit hospital priorities as outlined in a Community Health Needs Assessment. Design Using 3 completed Community Health Needs Assessments, we compare key stakeholder survey responses with community survey responses and determine their contribution to the finalized priorities. Setting Three communities in West Virginia served by nonprofit hospitals (1 metropolitan statistical area, 1 micropolitan statistical area, and 1 rural community). Participants Key stakeholders and the general population of communities served by the hospital. Main outcome measure Finalized priorities as outlined in the Community Health Needs Assessment. Results Community participation had an impact on finalized priorities. Conclusion Community participation is key in identifying unique health needs and should be incorporated into the assessment process by nonprofit hospitals, local health departments, and other public health practitioners. As reforms are considered to the Patient Protection and Affordable Care Act, it will be important to emphasize the importance of community input in identifying ways nonprofit hospitals contribute community benefit. CHNAs without adequate public input may not translate into implementation plans that accurately address pressing health concerns.

Renewable energy development and entrepreneurship in the Coachella Valley, which are at fairly early stages, are compared to benchmark mature metropolitan areas for renewable energy in Texas and Maryland. The purpose is to achieve broader perspective from states outside the U.S. Southwest, and to gain insights into possible opportunities and challenges for the Valley in the future. A literature review examines the history of policy formulation for wind energy in Texas and of barriers to residential adoption of solar. The main chapter focus is on the metropolitanarea benchmarks of Houston-The Woodlands-Sugar Land for wind energy; and Baltimore-Columbia-Towson for solar energy. For each metropolitan area and its state, the history and background of renewable energy are examined, as well as the geographic distributions of renewable manufacturing facilities relative to socio-economic features. Case examples are presented of wind and solar innovation. The findings on the benchmark areas are compared to those from Chap. 4 for the Coachella Valley, and the implications are discussed.

I estimate the effects of U.S. Metropolitan Statistical Area (MSA) housing prices on a variety of health outcomes and risky health behaviors separately for homeowners and tenants. The constructed dataset consists of information on individuals from the 2002-2012 Behavioral Risk Factor Surveillance System (BRFSS) combined with homeownership data from the March Current Population Survey (CPS) and housing prices from Freddie Mac. I estimate positive results for homeowners in terms of their health and negative results for tenants. I also find increases in risky behaviors among tenants associated with increases in housing prices, which may be driving the reduction in their health status. Those estimated effects are concentrated on low income homeowners and tenants. The estimated contemporaneous effects do not persist in the long run while the effects of an increase in housing prices on being obese become more pronounced for homeowners, resulting in worse self-reported health.

This paper examines how the Securities and Exchange Commission’s (SEC) enforcement actions and whom they target deter future financial misconduct. An enforcement action reduces the incidence of misconduct in other firms in the same industry and metropolitan statistical area (MSA) in the future. Furthermore, an enforcement that punishes a guilty company has a larger deterrence effect on future misconduct than punishing an officer, auditor, attorney, or other entity. In addition, the results are robust to using alternative measures of financial misconduct such as restatements and Fscore. These results have several policy implications on how regulatory agencies can maximize the value of their enforcements.

Socioeconomic status (SES) is often considered a risk factor for health outcomes. SES is typically measured using individual variables of educational attainment, income, housing, and employment variables or a composite of these variables. Approaches to building the composite variable include using equal weights for each variable or estimating the weights with principal components analysis or factor analysis. However, these methods do not consider the relationship between the outcome and the SES variables when constructing the index. In this project, we used weighted quantile sum (WQS) regression to estimate an area-level SES index and its effect in a model of colonoscopy screening adherence in the Minnesota-Wisconsin Metropolitan Statistical Area. We considered several specifications of the SES index including using different spatial scales (e.g., census block group-level, tract-level) for the SES variables. We found a significant positive association (odds ratio = 1.17, 95% CI: 1.15-1.19) between the SES index and colonoscopy adherence in the best fitting model. The model with the best goodness-of-fit included a multi-scale SES index with 10 variables at the block group-level and one at the tract-level, with home ownership, race, and income among the most important variables. Contrary to previous index construction, our results were not consistent with an assumption of equal importance of variables in the SES index when explaining colonoscopy screening adherence. Our approach is applicable in any study where an SES index is considered as a variable in a regression model and the weights for the SES variables are not known in advance.

We study whether foreign banks increased or decreased lending in the United States during the 1990-1991, 2001, and 2007-2009 recessions. Using a matched sample of foreign banks paired with domestic banks, univariate tests show that commercial and industrial loans by foreign banks increased in the 1990-1991 recession, decreased in the 2001 recession, and marginally increased in the 2007-2009 recession. Since recessions have differential impacts in an economy, we tested the lending behavior using granular data at the local metropolitan statistical area (MSA) level. Multivariate test results show that foreign branches engaged in countercyclical lending in the 1990 and 2001 recessions and foreign subsidiaries in the 2008 recession by lending in MSAs where GDP was falling or unemployment increasing. We conclude foreign banks continue to play a positive role in the American economy.

Within the social sciences, there is a long and storied history of the effect of economic conditions on vote choice. The traditional arguments are that voters have personal (egotropic) and/or other-regarding (sociotropic) preferences and that they reward and punish politicians electorally based on economic conditions at these levels. However, there is a third option. As industries, employment, and economic conditions are not uniformly distributed across the country, preferences may be locally based. This project combines unique survey data with Metropolitan Statistical Area unemployment numbers and finds evidence of distinct preferences at a third “communotropic” level.

The American Heart Association/American Stroke Association guidelines recommend all patients presenting to emergency departments (EDs) with a potential stroke be seen within 10 minutes of arrival, although this may not be achieved in all patients. We sought to identify factors associated with delayed evaluation of ED patients with potential stroke.Using the National Hospital Ambulatory Medical Care Survey, we identified all patient ED visits from 2003 to 2010 and further identified those patients with strokes or stroke-like symptoms using International Classification of Disease, Ninth Revision codes. Visits were classified as those evaluated within 10 minutes of ED arrival or those where evaluation by the treating provider was 10 minutes or greater (delayed evaluation). We stratified visits, compared proportions, and calculated the unadjusted and adjusted odds ratios (ORs) in a multivariable model.We identified 743 cases in the database representing an estimated 2.3 million ED visits for patients with strokes. Of these, 600000 were seen within 10 minutes and 1.7 million visits with delayed evaluation. Visits at nonmetropolitan statistical area hospitals were associated with decreased odds of delayed evaluation (OR, 0.41 [95% confidence interval, 0.26-0.64]; P.001). Being triaged to a less urgent emergency severity index category was associated with increased odds of delayed evaluation (OR 3.08 (95% CI 1.94-4.89) p0.001). Other factors were not associated with delayed evaluation.In this national sample of patients presenting with strokes to US EDs, patient visits to metropolitan statistical area hospitals and those triaged to less urgent categories were associated with delayed evaluation.

This study explores factors affecting changes in tax revenue diversification in Florida counties using socioeconomic, taxpayer, and institutional characteristics. The data cover 30 years and are analyzed using panel data analysis. The findings show that taxable consumption value, the number of interstate highways, the charter, and the form of government are associated with a greater degree of revenue diversification. Taxable property value, the presence of a metropolitan statistical area, the proportion of homeownership, the proportion of Democrat voters, income, and property tax millage rate are negatively associated with revenue diversification.

This paper estimates the conditional wage gaps between black and white full-time male workers at the metropolitan statistical area (MSA) level using data from the 1990 and 2000 U.S. Censuses. The magnitudes of the wage gaps are found to vary substantially across location. As predicted in Becker's (The economics of discrimination, University of Chicago Press, Chicago, 1957) seminal theory on wage discrimination, we find that the wage gaps are greater in MSAs that have a larger proportion of black workers in the labor force. This is the most consistent result across all specifications and years. We also find the gaps to be greater where there is an overrepresented black population in jail and a more segregated population if the MSA is in the South. The proportion of workers covered by a collective bargaining agreement in the private sector is associated with greater relative black earnings. We find that although the relationship between race and wages has diminished over time as famously suggested in Wilson (The declining significance of race: Blacks and changing American institutions, University of Chicago Press, Chicago, 1978), the significance of race remains.

Background and Aims Heroin-related overdose is linked to polydrug use, changes in physiological tolerance and social factors. Individual risk can also be influenced by the structural risk environment including the illicit drug market. We hypothesized that components of the US illicit drug market, specifically heroin source/type, price and purity, will have independent effects on the number of heroin-related overdose hospital admissions. Methods Yearly, from 1992 to 2008, Metropolitan Statistical Area (MSA) price and purity series were estimated from the US Drug Enforcement Administration data. Yearly heroin overdose hospitalizations were constructed from the Nationwide Inpatient Sample. Socio-demographic variables were constructed using several databases. Negative binomial models were used to estimate the effect of price, purity and source region of heroin on yearly hospital counts of heroin overdoses controlling for poverty, unemployment, crime, MSA socio-demographic characteristics and population size. Results Purity was not associated with heroin overdose, but each $100 decrease in the price per pure gram of heroin resulted in a 2.9% [95% confidence interval (CI) = 4.8%, 1.0%] increase in the number of heroin overdose hospitalizations (P = 0.003). Each 10% increase in the market share of Colombian-sourced heroin was associated with a 4.1% (95% CI = 1.7%, 6.6%) increase in number of overdoses reported in hospitals (P = 0.001) independent of heroin quality. Conclusions Decreases in the price of pure heroin in the United States are associated with increased heroin-related overdose hospital admissions. Increases in market concentration of Colombian-source/type heroin is also associated with an increase in heroin-related overdose hospital admissions. Increases in US heroin-related overdose admissions appear to be related to structural changes in the US heroin market.

Personal travel time in U.S. urban areas has been stable, clashing with the assertion that urban sprawl greatly lengthens travel. Average commute time rises by 7.7 percent with each cross- sectional doubling of Metropolitan Statistical Area (MSA) jobs. Using the RELU-TRAN structural computable general equilibrium model of the Chicago MSA, we simulate the equilibrium effects of a 24 percent population increase projected from 2000 to 2030 by the Chicago Metropolitan Agency for Planning. If no new road capacity is added, then congestion per mile increases. Although the urbanized land area increases by 19 percent, indicating sprawl, the vehicle miles traveled (VMT) per car-trip decreases by 1.31 percent and the VMT per car-trip to work decreases by 2.78 percent. Car travel time increases by only 6.25 percent and commuting time by only 4.54 percent, from 30.3 minutes in 2000 to 31.7 in 2030 or 3.4 seconds per year. We further explore the effects of new road capacity, gasoline prices, public transit speed, fuel economy gains, limits on suburban construction, and importantly, the cross-elasticity of public transit use with respect to car times. The availability of public transportation, economizing on nonwork travel, and land use adjustments that increase job-residence proximity keep times stable.

In this study, we use a Geographic Information System-based index to measure spatial accessibility of public high schools. The index is applied to the Baton Rouge Metropolitan Statistical Area in 1990, 2000, and 2010. Overall, urban areas had consistently worse accessibility scores compared with suburban and rural areas. High schools with more African American students tended to have poorer accessibility levels. Schools with lower accessibility tended to be associated with poorer average student performance, and the effect strengthened between 2000 and 2010. In developing a better understanding of the accessibility of public high schools, this paper reaffirms the significance of space, place, and race, and challenges the notion of declining relevance of accessibility in Louisiana public education policymaking.

Background National estimates of all-terrain vehicle (ATV) riding patterns among youth in the USA are lacking. Methods We analysed the 2011 YouthStyles survey to estimate the proportion of 12–17 year olds in the USA who had ridden an ATV at least once during the past 12 months and summarise their patterns of helmet use. Results Of the 831 youth respondents, an estimated 25% reported riding an ATV at least once during the past year. The proportion of youth living outside of a Metropolitan Statistical Area who reported riding an ATV was twice that of those living inside of a Metropolitan Statistical Area. Males and females reported similar proportions of riding at least once during the past year, but among riders, the proportion of males who rode ≥6 times was triple that of females. Only 45% of riders reported always wearing a helmet, and 25% reported never wearing a helmet. The most frequent riders had the lowest consistent helmet use, with 8 of 10 youth who rode ≥6 times during the past year not always wearing a helmet. Conclusions ATV riding appears to remain popular among youth in the USA, particularly in rural areas, and consistent helmet use while riding is low. A more thorough understanding of gender differences in ATV riding patterns among youth and perceived risks and benefits of both safe and unsafe riding practices might help inform future ATV injury prevention efforts.

While environmental justice (EJ) research in the United States has focused primarily on the social distribution of chronic pollution risks, previous empirical studies have not analyzed disparities in exposure to both chronic (long-term) and acute (short-term) pollution in the same study area. Our article addresses this limitation though a case study that compares social inequities in exposure to chronic and acute pollution risks in the Greater Houston Metropolitan Statistical Area, Texas. The study integrates estimates of chronic cancer risk associated with ambient exposure to hazardous air pollutants from the Environmental Protection Agency's National-Scale Air Toxics Assessment (2005), hazardous chemical accidents from the National Response Center's Emergency Response Notification System (2007-2011), and sociodemographic characteristics from the American Community Survey (2007-2011). Statistical analyses are based on descriptive comparisons, bivariate correlations, and locally derived spatial regression models that account for spatial dependence in the data. Results indicate that neighborhoods with a higher percentage of Hispanic residents, lower percentage of homeowners, and higher income inequality are facing significantly greater exposure to both chronic and acute pollution risks. The non-Hispanic black percentage is significantly higher in neighborhoods with greater chronic cancer risk, but lower in areas exposed to acute pollution events. Households isolated by language--those highly likely to face evacuation problems during an actual chemical disaster--tend to reside in areas facing significantly greater exposure to high-impact acute events. Our findings emphasize the growing need to examine social inequities in exposure to both chronic and acute pollution risks in future EJ research and policy.

This article examines the dynamics between mortgage broker competition, origination fees and price transparency. A reverse first-price sealed-bid auction model is used to motivate broker pricing behavior. Confirming the model predictions, our empirical analysis shows that increased mortgage brokerage competition at the Metropolitan Statistical Area level leads to lower fees. The findings are robust to different measures of fees as well as different measures of competition. We also provide evidence that broker competition reduces mortgage origination fees on retail (nonbrokered) loans as well. In addition, our results indicate that pricing complexity is an important determinant of fees, and increased broker competition is associated with a higher probability of a loan being priced with transparency. Our results suggest that mortgage brokers increase competition and lower fees in the mortgage market.

Objective To examine preventive care visit patterns among commercially insured adolescents during 2003-2010. In 2005-2007, the Advisory Committee on Immunization Practices (ACIP) recommended 3 vaccines targeted at adolescents. We also investigate the relationship between preventive care visits and immunization. Study design Data were drawn from the MarketScan database. Adolescents aged 11-21 continuously enrolled in the same insurance plan during the calendar year were included. We calculated the annual proportion of adolescents with at least 1 preventive and 1 vaccination-related visit. Longitudinal analyses were conducted by following the 1992 birth cohort for 8 consecutive years. Results The proportion of adolescents making at least 1 preventive visit increased from 24.6%-41.1% during 2003-2010. The rate of vaccination-related visits increased from 12.9%-26.3%. The magnitude of the increase in preventive and vaccination-related visits was greater during the years in which ACIP issued recommendations. The rates of preventive and vaccination-related visits were considerably higher among female and early adolescents and adolescents in managed care plans. Longitudinal analyses indicated that only 2.4% of adolescents had an annual preventive visit during the 8 years. Conclusions Yearly improvements in preventive care visits by adolescents were substantial. ACIP recommendations may be associated with this improvement. However, ongoing efforts are needed to improve the use and delivery of preventive care services.

A long stream of academic literature has established that public funding towards research and development matters for economic growth because it relates to increases in innovation, productivity and the like. The impact of public funding on the creation of new firms has received less attention in this literature despite theoretical constructs that support such association. In the present paper we study whether indeed there is a relationship between public research funds and local firm births in the context of the U.S. biotechnology industry. In doing so, we introduce a number of changes that strengthen the robustness of our findings when compared with existing literature. These changes include a direct measure of research expenditures and a considerably lengthier longitudinal dataset which allows us to capture a structural relationship and not a chance event. We empirically demonstrate that increases in the level of research funding from the National Institutes of Health towards biotechnology associate with increases in the number of biotechnology firm births at the Metropolitan Statistical Area level. Further, we reveal that public funds towards established firms associate with local firm births considerably more strongly when compared with funds towards universities and research institutes/hospitals. We conclude the paper with academic and policy implications of the present work that highlight the complexity of factors that underlie the creation of local firms in high technology industries.\ud \ud

Web 2.0 has yielded a wealth of publicly available data, largely through the popularization of social media and the proliferation of user-generated content (UGC). Thus, the data void in social science research is diminishing as these new data sources are exploited. The discipline of geography, in particular, stands to benefit considerably from geotagged UGC or volunteered geographic information (VGI). In this article, we utilize a form of UGC—restaurant reviews—to evaluate the geography of Web 2.0 in Franklin County, Ohio. We find that restaurant reviews are largely concentrated in relatively few areas of the city, indicating that the impacts of Web 2.0 have not touched down evenly within the central county of the Columbus metropolitan statistical area. We argue that an intraurban digital divide is still apparent and might even be exacerbated by Web 2.0.

Intuitively, increasing the available land, which is an economic resource, should improve social welfare. However, traditional economic models of urban economy show that an urban growth boundary (UGB) policy, which restricts land availability, actually improves social welfare by reducing the negative externalities imposed by congestion. Nevertheless, recent studies have found that a UGB policy is not always welfare improving. This paper examines both expansive and restrictive UGB regimes using the Chicago metropolitan statistical area as an example. The simulation results presented herein show that an expansive UGB positively affects social welfare, while a restrictive UGB improves social welfare if open spaces are considered and vacant land outside the UGB registers a moderate fall in value. Further, the proportion of absentee landlords is an important determinant of welfare gains, since their gain (or loss) from a UGB policy in the real estate market is a drain from the urban economy. Moreover, a restrictive UGB leads to centralized land use, while an expansive UGB results in moderate suburbanization. Finally, gasoline consumption decreases under a restrictive UGB but increases under an expansive UGB because vehicle miles travelled increase as the city expands outward.

This study examined the association between ozone and fine particulate (PM2.5) exposure and asthma risk by place of residence. We linked 412,832 adult respondents from the 2009 U.S. Behavioral Risk Factor Surveillance System to their residence counties. Observed and interpolated ozone and PM2.5 concentration data from 2006 to 2009 were used as exposures. We linked self-reported current asthma status and other individual risk factors to county-level risk factors in multilevel logistic regressions. Results indicated spatially varied asthma risks and spatially varied associations between ambient air pollution and asthma risk. Residents in counties not located within a metropolitan statistical area (MSA) and in inner ring suburbs had a relatively higher asthma risk. Positive ozone-asthma associations were detected across all spatial settings, while positive PM2.5-asthma associations were detected only in central cities of an MSA and in outer ring suburbs, indicating that residence location modified the relationship between ambient air pollution and asthma risk.

Some cancer survivors report spending 20% of their annual income on medical care. Undue financial burden that patients face related to the cost of care is referred to as financial hardship, which may be more prevalent among rural cancer survivors. This study examined contrasts in financial hardship among 1419 rural and urban cancer survivors using the 2011 Medical Expenditure Panel Survey supplement - The Effects of Cancer and Its Treatment on Finances. We combined four questions, creating a measure of material financial hardship, and examined one question on financial worry. We conducted multivariable logistic regression analyses, which produced odds ratios (OR) for factors associated with financial hardship and worry, and then generated average adjusted predicted probabilities. We focused on rural and urban differences classified by metropolitan statistical area (MSA) designation, controlling for age, education, race, marital status, health insurance, family income, and time since last cancer treatment. More rural cancer survivors reported financial hardship than urban survivors (23.9% versus 17.1%). However, our adjusted models revealed no significant impact of survivors' MSA designation on financial hardship or worry. Average adjusted predicted probabilities of financial hardship were 18.6% for urban survivors (Confidence Interval [CI]: 11.9%-27.5%) and 24.2% for rural survivors (CI: 15.0%-36.2%). For financial worry, average adjusted predicted probabilities were 19.9% for urban survivors (CI: 12.0%-31.0%) and 18.8% for rural survivors (CI: 12.1%-28.0%). Improving patient-provider communication through decision aids and/or patient navigators may be helpful to reduce financial hardship and worry regardless of rural-urban status.

The Miami-Fort Lauderdale-West Palm Beach metropolitan statistical area (MSA) is the eighth most populous in the U.S. but ranks sixteenth in land area. Confined within the twenty-miles between the Atlantic Ocean and the Everglades, most of the land area the MSA envelops cannot expand as its population grows. As a result, continued development has increased the proximity of urban population centers to less-populated “rural” areas. The results of long-term sound level measurements conducted at over 50 locations throughout the MSA are assessed in conjunction with land uses, population densities, and other statistical data to determine conformance with ASA, ANSI, and WHO guidelines and the U.S. EPA prediction model. Initial analyses revealed noise levels at most measurement locations to be inconsistent with these criteria, even in less-populated areas farther from urban centers. The datasets are compared to establish relationships at the local level and are combined based on their land use designations and respective location within municipal and county boundaries, the MSA, and smaller statistical areas for further correlation with standardized guidelines.The Miami-Fort Lauderdale-West Palm Beach metropolitan statistical area (MSA) is the eighth most populous in the U.S. but ranks sixteenth in land area. Confined within the twenty-miles between the Atlantic Ocean and the Everglades, most of the land area the MSA envelops cannot expand as its population grows. As a result, continued development has increased the proximity of urban population centers to less-populated “rural” areas. The results of long-term sound level measurements conducted at over 50 locations throughout the MSA are assessed in conjunction with land uses, population densities, and other statistical data to determine conformance with ASA, ANSI, and WHO guidelines and the U.S. EPA prediction model. Initial analyses revealed noise levels at most measurement locations to be inconsistent with these criteria, even in less-populated areas farther from urban centers. The datasets are compared to establish relationships at the local level and are combined based on their land use designations and re...

The first author acknowledges the support from the National Natural Science Foundation of China under Grant No. 71774152, 91546109; and the Youth Innovation Promotion Association of the Chinese Academy of Sciences (Grant No. Y7x0231505).