Metropolitan Statistical Areas Level Research Articles

Urban landscape affects scaling of transportation carbon emissions across geographic scales

Understanding the carbon dynamics of the transportation sector is necessary to mitigate global climate change. While urban scaling laws have been used to understand the impact of urban population size on carbon efficiency, the instability of these scaling relationships raises additional questions. Here, we examined the scaling of on-road transportation carbon emissions across 378 US metropolitan statistical areas (MSAs) using diverse urban landscape patterns and spatial units, from the MSA level down to 1 km grid cells. Beginning with a baseline scaling model that uses only population size, we expanded the model to include landscape metrics at each spatial scale based on correlation results. We found that: (1) urban landscape characteristics provide insights into carbon mechanisms not fully captured by population size alone, (2) the impact of population size on on-road carbon emissions transitions from linear to sub-linear scaling relationships as the geographic scale of analysis decreases, and (3) clustered urban developments can form carbon-efficient landscapes, while fragmented urban areas tend to be carbon-inefficient. Based on empirical evidence, this research advocates for hierarchical spatial planning and supports the implementation of policy measures aligned with smart growth principles to mitigate carbon pollution.

Cervical cancer geographical burden analyzer: An interactive, open-access tool for understanding geographical disease burden in patients with recurrent or metastatic cervical cancer.

5523 Background: Examining geographic distributions of high and low proportions of recurrent or metastatic cervical cancer (r/mCC) can identify regions with high need of intervention and advance our understanding of r/mCC community-specific risk factors. Previous studies of epidemiologic or geographic clusters in late-stage cervical cancer were conducted prior to the availability of modern treatments for r/mCC. Due to the rapidly evolving treatment landscape for r/mCC use of commercial claims is an important way to follow dynamic practice changes. Our study objective was to understand recent geographical disparities among r/mCC patients in the US. Methods: We developed a web-based tool, Cervical Cancer Geographical Disease Burden Analyzer, that allows users to quantify r/mCC disease burden across metropolitan statistical areas (MSA) over multiple years. The inputs to the web-based tool were extracted through a retrospective analysis of the 2015-2020 MarketScan commercial claims database using a previously validated methodology. We then calculated the r/mCC rate as the ratio of r/mCC cases over cervical cancer (CC) cases for each of the >400 MSA considered. The calculated MSA-specific r/mCC rate was visualized in an interactive US map,. The online interactive tool allowed the users to filter the results by year, age group, and minimum number of diagnoses at the MSA level. Results: Our findings showed that there is large variation with respect to r/mCC disease burden across MSA in the US, with a range of 0-45%. The top five MSA with the highest r/mCC rates from 2018-2020 are presented in the table. In particular, r/mCC rates in Sacremento-Roseville-Arden-Arcade (SRAA), CA and Boston-Cambridge-Newton (BCN), MA were on an increasing trajectory (33% in 2018 to 50% in 2020 in SRAA, CA; and from 41% in 2018 to 50% in 2020 in BCN, MA). On the other hand, while disease burden remained high, we observed decreasing r/mCC rates in Grand Rapids, MI (55% in 2018 and 31% in 2020, resulting in an average r/mCC rate of 42%). Finally, in Cape Coral-Fort Myers, FL and Baltimore-Columbia-Towson, MD the r/mCC rates have fluctuated across time but were consistently >30%. Conclusions: Our web-based online interactive tool can help with identifying areas with high need of intervention, and inform how access, prevention and new or emerging therapies may potentially change the distribution of r/mCC disease burden. To better understand underlying drivers of geographic disparities observed, further efforts should be targeted towards identifying local-level factors. [Table: see text]

The heterogeneous effects of interactions between parent's education and MSA level college share on children's school enrollment

This study finds that location matters more for children of parents with low educational attainment than for children of more educated parents. Specifically, children of parents without a high school diploma are statistically more likely to be enrolled in high schools or colleges in metropolitan statistical areas (MSAs) where the college graduate share is higher. The statistical relationship between a child's school enrollment and the MSA's college graduate share becomes weaker as their parents’ educational attainment increases. We also find that the least educated households are significantly less likely to be homeowners and are more likely to pay greater housing costs as a share of income in cities with higher college graduate shares, indicating that these households are paying a high price to live in high-skilled cities. Our results imply that the increasing lack of housing affordability in high-skilled cities makes it more difficult for households with less educational attainment to stay in or move to these places, contributing to intergenerational education inequality.

Evidence for HIV transmission across key populations: a longitudinal analysis of HIV and AIDS rates among Black people who inject drugs and Black heterosexuals in 84 large U.S. metropolitan areas, 2008–2016

PurposeTo assess cross-population linkages in HIV/AIDS epidemics, we tested the hypothesis that the number of newly diagnosed AIDS cases among Black people who inject drugs (PWID) was positively related to the natural log of the rate of newly diagnosed HIV infections among Black non-PWID heterosexuals in 84 large U.S. metropolitan statistical areas (MSAs) in 2008–2016. MethodsWe estimated a multilevel model centering the time-varying continuous exposures at baseline between the independent (Black PWID AIDS rates) and dependent (HIV diagnoses rate among Black heterosexuals) variables. ResultsAt MSA level, baseline (standardized β = 0.12) Black PWID AIDS rates and change in these rates over time (standardized β = 0.11) were positively associated with the log of new HIV diagnoses rates among Black heterosexuals. Thus, MSAs with Black PWID AIDS rates that were 1 standard deviation= higher at baseline also had rates of newly diagnosed HIV infections among Black non-PWID heterosexuals that were 10.3% higher. A 1 standard deviation increase in independent variable over time corresponded to a 7.8% increase in dependent variable. ConclusionsBlack PWID AIDS rates may predict HIV rates among non-PWID Black heterosexuals. Effective HIV programming may be predicated, in part, on addressing intertwining of HIV epidemics across populations.

Revisiting the relationship between traffic congestion and the economy: a longitudinal examination of U.S. metropolitan areas

Conventional transportation practices typically focus on alleviating traffic congestion affecting motorists during peak travel periods. One of the underlying assumptions is that traffic congestion, particularly during these peak periods, is harmful to a region’s economy. This paper seeks to answer a seemingly straightforward question: is the fear of the negative economic effects of traffic congestion justified, or is congestion merely a nuisance with little economic impact? This research analyzed 30 years of data for 89 US metropolitan statistical areas (MSAs) to evaluate the economic impacts of traffic congestion at the regional level. Employing a two-stage, least squares panel regression model, we controlled for endogeneity using instrumental variables and assessed the association between traffic congestion and per capita gross domestic product (GDP) as well as between traffic congestion and job growth for an 11-year time period. We then investigated the relationship between traffic congestion and per capita income for those same 11 years as well as for the thirty-year time period (1982–2011) when traffic congestion data were available. Controlling for the key variables found to be significant in the existing literature, our results suggest that the potential negative impact of traffic congestion on the economy does not deserve the attention it receives. Economic productivity is not significantly negatively impacted by high levels of traffic congestion. In fact, the results suggest a positive association between traffic congestion and per capita GDP as well as between traffic congestion and job growth at the MSA level. There was a statistically insignificant effect on per capita income. There may be valid reasons to continue the fight against congestion, but the idea that congestion will stifle the economy does not appear to be one of them.

Income Inequality and US Children's Secondhand Smoke Exposure: Distinct Associations by Race-Ethnicity.

Prior studies have found considerable racial and ethnic disparities in secondhand smoke (SHS) exposure. Although a number of individual-level determinants of this disparity have been identified, contextual determinants of racial and ethnic disparities in SHS exposure remain unexamined. The objective of this study was to examine disparities in serum cotinine in relation to area-level income inequality among 14 649 children from the National Health and Nutrition Examination Survey. We fit log-normal regression models to examine disparities in serum cotinine in relation to Metropolitan Statistical Areas level income inequality among 14 649 nonsmoking children aged 3-15 from the National Health and Nutrition Examination Survey (1999-2012). Non-Hispanic black children had significantly lower serum cotinine than non-Hispanic white children (-0.26; 95% CI: -0.38, -0.15) in low income inequality areas, but this difference was attenuated in areas with high income inequality (0.01; 95% CI: -0.16, 0.18). Serum cotinine declined for non-Hispanic white and Mexican American children with increasing income inequality. Serum cotinine did not change as a function of the level of income inequality among non-Hispanic black children. We have found evidence of differential associations between SHS exposure and income inequality by race and ethnicity. Further examination of environments which engender SHS exposure among children across various racial/ethnic subgroups can foster a better understanding of how area-level income inequality relates to health outcomes such as levels of SHS exposure and how those associations differ by race/ethnicity. In the United States, the association between children's risk of SHS exposure and income inequality is modified by race/ethnicity in a manner that is inconsistent with theories of income inequality. In overall analysis this association appears to be as predicted by theory. However, race-specific analyses reveal that higher levels of income inequality are associated with lower levels of SHS exposure among white children, while levels of SHS exposure among non-Hispanic black children are largely invariant to area-level income inequality. Future examination of the link between income inequality and smoking-related health outcomes should consider differential associations across racial and ethnic subpopulations.

Industry Clusters and Regional Economic Performance: A Study Across U.S. Metropolitan Statistical Areas

Cluster theory provides a framework for categorizing and analyzing industry dynamics at a variety of spatial and temporal scales. However, definitions and categorizations of clusters vary widely in the literature, which to date has hindered the development of rigorous econometric models for cluster analysis. Based on a review of the literature on industry clusters and regional economic development, we categorize cluster types using The Cluster Mapping Project (CMP) aggregations of North American Industry Classification System (NAICS) six-digit industry codes. We then present empirical measures for cluster growth, cluster diversity, and cluster strength. These measures are calculated using employment data for 366 U.S. metropolitan statistical areas (MSAs) for the years 2002-2003 and 2011-2012. Additionally, we estimate the relationship of our cluster performance measures to several traditional economic development indicators at the MSA level using multivariate linear regression. We assess potential applications of the new cluster performance measures and conclude that our measures for local and traded cluster growth can explain much of the variation in regional economic performance.

Racialized risk environments in a large sample of people who inject drugs in the United States

BackgroundSubstantial racial/ethnic disparities exist in HIV infection among people who inject drugs (PWID) in many countries. To strengthen efforts to understand the causes of disparities in HIV-related outcomes and eliminate them, we expand the “Risk Environment Model” to encompass the construct “racialized risk environments,” and investigate whether PWID risk environments in the United States are racialized. Specifically, we investigate whether black and Latino PWID are more likely than white PWID to live in places that create vulnerability to adverse HIV-related outcomes. MethodsAs part of the Centers for Disease Control and Prevention's National HIV Behavioral Surveillance, 9170 PWID were sampled from 19 metropolitan statistical areas (MSAs) in 2009. Self-reported data were used to ascertain PWID race/ethnicity. Using Census data and other administrative sources, we characterized features of PWID risk environments at four geographic scales (i.e., ZIP codes, counties, MSAs, and states). Means for each feature of the risk environment were computed for each racial/ethnic group of PWID, and were compared across racial/ethnic groups. ResultsAlmost universally across measures, black PWID were more likely than white PWID to live in environments associated with vulnerability to adverse HIV-related outcomes. Compared to white PWID, black PWID lived in ZIP codes with higher poverty rates and worse spatial access to substance abuse treatment and in counties with higher violent crime rates. Black PWID were less likely to live in states with laws facilitating sterile syringe access (e.g., laws permitting over-the-counter syringe sales). Latino/white differences in risk environments emerged at the MSA level (e.g., Latino PWID lived in MSAs with higher drug-related arrest rates). ConclusionPWID risk environments in the US are racialized. Future research should explore the implications of this racialization for racial/ethnic disparities in HIV-related outcomes, using appropriate methods.

Sa1020 Association of Use of Anesthesia Services During Colonoscopies and Colorectal Cancer Screening Rates

Background: Current guidelines recommend that the gastroenterologist-nurse team deliver sedation to low-risk patients undergoing colonoscopy screening. Yet a 2012 study demonstrated that professional anesthesia service (PAS) use increased from 14% in 2003 to over 30% in 2009, and more than two-thirds of PAS was delivered to low-risk patients. Recently, the Centers for Medicare and Medicaid Services stated PAS use was becoming the standard of care and proposed waiving the copayments for Medicare patients undergoing screening. The cost and benefits of this policy change are unknown. Objective: To estimate the association between PAS use in screening colonoscopies and colorectal cancer screening rates (benefit), and the PAS cost associated with each additional colorectal cancer prevented by increasing PAS use. Data: We used 2008-2012 Medicare claims data to derive the rate of PAS use for fee-for-service beneficiaries during colonoscopy, and 2008-2012 Behavioral Risk Factor Surveillance System Survey (BRFSS) data to estimate colorectal cancer screening rates. Methods: Rates for PAS, colonoscopy and overall cancer screening rates (including fecal occult blood test) were constructed for the 150 metropolitan statistical areas (MSA) that had both BRFSS and LDS data during 2008-2012. Colonoscopies and PAS use were identified based on CPT-4 codes, which were linked based on service date and location. The PAS rate was defined as the proportion of colonoscopies with PAS. The colonoscopy screening and colorectal cancer screening rates were defined as proportion of eligible individuals in compliance with the CDC's guideline on screenings. Sampling weights were used to generate MSA level estimates. Combining our estimates with those from the published literature, we approximated the increase in PAS cost associated with the detection of one additional case colorectal cancer. Results: From 2008 to 2012, colonoscopy screening rates increased from 63% to 70%, overall colorectal cancer screening rates from 71% to 75%, and PAS use from 32% to 42%. PAS use was positively correlated with colonoscopy screening rates (rho=0.180, p 0.050). PAS cost associated with each additional colorectal cancer prevented was estimated to be $16.6 million (95% CI: $11.0 million, $33.2 million) in 2014 U.S. dollars. Conclusions: PAS use in colonoscopies was modestly associated with colonoscopy screening rates but not with overall colorectal cancer screening rates. Improving coverage of PAS during screening colonoscopies is unlikely to increase screening in a cost-effective fashion.

Female and male differences in AIDS diagnosis rates among people who inject drugs in large U.S. metro areas from 1993 to 2007

PurposeWe estimated female and male incident AIDS diagnosis rates (IARs) among people who inject drugs (PWID) in U.S. metropolitan statistical areas (MSAs) over time to assess whether declines in IARs varied by sex after combination antiretroviral therapy (cART) dissemination. MethodsWe compared IARs and 95% confidence intervals for female and male PWID in 95 of the most populous MSAs. To stabilize estimates, we aggregated data across three-year periods, selecting a period immediately preceding cART (1993–1995) and the most recent after the introduction of cART for which data were available (2005–2007). We assessed disparities by comparing IAR 95% confidence intervals for overlap, female-to-male risk ratios, and disparity change scores. ResultsIARs declined an average of 58% for female PWID and 67% for male PWID between the pre-cART and cART periods. Among female PWID, IARs were significantly lower in the later period relative to the pre-cART period in 48% of MSAs. Among male PWID, IARs were significantly lower over time in 86% of MSAs. ConclusionsIARs among female PWID in large U.S. MSAs have declined more slowly than among male PWID. This suggests a need for increased targeting of prevention and treatment programs and for research on MSA level conditions that may drive differences in declining AIDS rates among female and male PWID.

Okun’s law, asymmetries and regional spillovers: evidence from Virginia metropolitan statistical areas and the District of Columbia

The purpose of this paper was to examine the strength of the relationship between unemployment and GDP, to determine the extent to which this relationship has been stable in Virginia metropolitan statistical areas (MSA) during the Great Recession and to examine the importance of regional spillovers in Okun’s law. Our results suggest that regional spillovers are very important in local labor markets and in defining the relationship observed at the national level. The MSA level data further supports asymmetries in Okun’s law. The weaker direct relationship between GDP and unemployment at the local level suggests that while federal fiscal and monetary policies to stimulate aggregate demand during periods of economic recovery may be effective, over time, in reducing the unemployment rate, local economic development policies are not effective in achieving the substantial short-term reduction in unemployment needed during recovery. The strong business cycle effects observed in the state MSA, relative to the U.S., suggests that countercyclical policies are fundamentally important and should be targeted more generally to exploit regional spillovers.

Banks' Liability Structure and Mortgage Lending During the Financial Crisis

We examine the impact of banks’ exposure to market liquidity shocks through wholesale funding on their supply of credit during the financial crisis in the United States. We focus on mortgage lending to minimize the impact of confounding demand factors that could potentially be large when comparing banks’ overall lending across heterogeneous categories of credit. The disaggregated data on mortgage applications that we use allows us to study the time variations in banks’ decisions to grant mortgage loans, while controlling for bank, borrower, and regional characteristics. The wealth of data also allows us to carry out matching exercises that eliminate imbalances in observable applicant characteristics between wholesale and retail banks, as well as various other robustness tests. We find that banks that were more reliant on wholesale funding curtailed their credit significantly more than retail-funded banks during the crisis. The demand for mortgage credit, on the other hand, declined evenly across wholesale and retail banks. To understand the aggregate implications of our findings, we exploit the heterogeneity in mortgage funding across U.S. Metropolitan Statistical Areas (MSAs) and find that wholesale funding was a strong and significant predictor of a sharper decline in overall mortgage credit at the MSA level.

Banks' Liability Structure and Mortgage Lending During the Financial Crisis

We examine the impact of banks’ exposure to market liquidity shocks through wholesale funding on their supply of credit during the financial crisis in the United States. We focus on mortgage lending to minimize the impact of confounding demand factors that could potentially be large when comparing banks’ overall lending across heterogeneous categories of credit. The disaggregated data on mortgage applications that we use allows us to study the time variations in banks’ decisions to grant mortgage loans, while controlling for bank, borrower, and regional characteristics. The wealth of data also allows us to carry out matching exercises that eliminate imbalances in observable applicant characteristics between wholesale and retail banks, as well as various other robustness tests. We find that banks that were more reliant on wholesale funding curtailed their credit significantly more than retail-funded banks during the crisis. The demand for mortgage credit, on the other hand, declined evenly across wholesale and retail banks. To understand the aggregate implications of our findings, we exploit the heterogeneity in mortgage funding across U.S. Metropolitan Statistical Areas (MSAs) and find that wholesale funding was a strong and significant predictor of a sharper decline in overall mortgage credit at the MSA level.

Sectoral Shocks and Metropolitan Employment Growth

In this paper, we study the sources of industry employment growth in each of five metropolitan statistical areas (MSAs). The objective is to understand the relative importance of aggregate disturbances versus local sectoral shocks in generating observed employment fluctuations at the MSA level. The empirical evidence presented in this paper derives from structural vector autoregressions (SVARs), estimated for each of the five MSAs. Estimations use monthly employment data covering nine one-digit industrial categories for the period 1951:1–1999:8, as well as two variables that capture the influences of aggregate (i.e., national) shocks on MSAs. We find that within-MSA industry shocks explain considerably more of the forecast error variance in industry employment growth than do aggregate shocks. Sectoral shocks account for between 87 and 94% of the 36-month-ahead forecast error variance. Among individual local sectors, shocks to MSA-specific government, manufacturing, and service sector employment growth are the predominate sources of variability.

Local Geographic Spillovers between University Research and High Technology Innovations

This paper re-examines the empirical evidence on the degree of spatial spillover between university research and high technology innovations. The familiar Griliches–Jaffe knowledge production function is estimated at both the state and the metropolitan statistical areas (MSA) level and extended with more precise measures of spatial spillover. Alternatives based on the gravity potential and covering indices are formulated for Jaffe's “geographical coincidence index” and found to provide strong evidence of local spillovers at the state level. At the MSA level, a distinction is made between research and development activities and university research in the MSA and in the surrounding counties. Evidence is found of local spatial externalities between university research and high technology innovative activity, both directly and indirectly via private research and development.

The Relationship between Selected Causes of Postneonatal Infant Mortality and Particulate Air Pollution in the United States

Recent studies have found associations between particulate air pollution and total and adult mortality. The relationship between particulate air pollution and mortality among infants has not been examined in the United States. This study evaluates the relationship between postneonatal infant mortality and particulate matter in the United States. Our study involved analysis of cohorts consisting of approximately 4 million infants born between 1989 and 1991 in states that report relevant covariates; this included 86 metropolitan statistical areas (MSAs) in the United States. Data from the National Center for Health Statistics-linked birth/infant death records were combined at the MSA level with measurements of particulate matter 10 microns or less (PM10) from the EPA's Aerometric Database. Infants were categorized as having high, medium, or low exposures based on tertiles of PM10. Total and cause-specific postneonatal mortality rates were examined using logistic regression to control for demographic and environmental factors. Overall postneonatal mortality rates were 3.1 among infants with low PM10 exposures, 3.5 among infants with medium PM10 exposures, and 3.7 among highly exposed infants. After adjustment for other covariates, the odds ratio (OR) and 95% confidence intervals (CI) for total postneonatal mortality for the high exposure versus the low exposure group was 1.10 (1.04, 1.16). In normal birth weight infants, high PM10 exposure was associated with respiratory causes [OR = 1.40, (1.05, 1.85)] and sudden infant death syndrome [OR = 1.26, (1.14, 1.39)]. For low birth weight babies, high PM10 exposure was associated, but not significantly, with mortality from respiratory causes [OR = 1.18, (0.86, 1.61)]. This study suggests that particulate matter is associated with risk of postneonatal mortality. Continued attention should be paid to air quality to ensure optimal health of infants in the United States.

The relationship between selected causes of postneonatal infant mortality and particulate air pollution in the United States.

Recent studies have found associations between particulate air pollution and total and adult mortality. The relationship between particulate air pollution and mortality among infants has not been examined in the United States. This study evaluates the relationship between postneonatal infant mortality and particulate matter in the United States. Our study involved analysis of cohorts consisting of approximately 4 million infants born between 1989 and 1991 in states that report relevant covariates; this included 86 metropolitan statistical areas (MSAs) in the United States. Data from the National Center for Health Statistics-linked birth/infant death records were combined at the MSA level with measurements of particulate matter 10 microns or less (PM10) from the EPA's Aerometric Database. Infants were categorized as having high, medium, or low exposures based on tertiles of PM10. Total and cause-specific postneonatal mortality rates were examined using logistic regression to control for demographic and environmental factors. Overall postneonatal mortality rates were 3.1 among infants with low PM10 exposures, 3.5 among infants with medium PM10 exposures, and 3.7 among highly exposed infants. After adjustment for other covariates, the odds ratio (OR) and 95% confidence intervals (CI) for total postneonatal mortality for the high exposure versus the low exposure group was 1.10 (1.04, 1.16). In normal birth weight infants, high PM10 exposure was associated with respiratory causes [OR = 1.40, (1.05, 1.85)] and sudden infant death syndrome [OR = 1.26, (1.14, 1.39)]. For low birth weight babies, high PM10 exposure was associated, but not significantly, with mortality from respiratory causes [OR = 1.18, (0.86, 1.61)]. This study suggests that particulate matter is associated with risk of postneonatal mortality. Continued attention should be paid to air quality to ensure optimal health of infants in the United States.