Percent Of Counties Research Articles

Spatial Big Data Analytics of Inequity in Access to Live Music Among Disadvantaged Populations

In recent years, music cities around the world have developed various supportive policy frameworks ensuring live music is accessible to large populations. The question of whether live music is equitably distributed by socioeconomic status remains unanswered, however. This study investigated the accessibility of music events in socially and economically disadvantaged communities. The level of accessible concerts varies substantially across U.S. counties, revealing significant inequity in access to concerts. Almost 80 percent of concerts are located in 5 percent of counties. Ordinary least squares (OLS) regression, geographically weighted regression (GWR), and multiscale geographically weighted regression (MGWR) methods were then employed to explore associations between accessible concerts and the socioeconomic characteristics of communities where these concerts are located. The regression models revealed that areas with a higher proportion of residents without a high school degree, higher unemployment rate, and higher poverty rate were less likely to have access to concerts, yet positive associations were found between accessible concerts and mean household income. Local R 2 values further confirmed the robustness of regression results of both GWR and MGWR and showed significant spatial nonstationarity of model performance. GWR and MGWR methods improved model performance significantly over the OLS method and proved how local conditions influence the OLS regression. The results from this study can guide decision makers and stakeholders in making appropriate policies to achieve equitable access to music events, especially for disadvantaged communities.

The U.S. COVID-19 County Policy Database: a novel resource to support pandemic-related research

BackgroundIt is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. There has been limited systematic evaluation of variation in U.S. local COVID-19-related policies. This study introduces the U.S. COVID-19 County Policy (UCCP) Database, whose objective is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies.MethodsIn January-March 2021, we collected an initial wave of cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health. We characterized the presence and comprehensiveness of policies using univariate analyses. We also examined the correlation of policies with one another using bivariate Spearman’s correlations. Finally, we examined geographical variation in policies across and within states.ResultsThere was substantial variation in the presence and comprehensiveness of county policies during January-March 2021. For containment and closure policies, the percent of counties with no restrictions ranged from 0% (for public events) to more than half for public transportation (67.8%), hair salons (52.6%), and religious gatherings (52.0%). For economic policies, 76.6% of counties had housing support, while 64.9% had utility relief. For public health policies, most were comprehensive, with 70.8% of counties having coordinated public information campaigns, and 66.7% requiring masks outside the home at all times. Correlations between containment and closure policies tended to be positive and moderate (i.e., coefficients 0.4–0.59). There was variation within and across states in the number and comprehensiveness of policies.ConclusionsThis study introduces the UCCP Database, presenting granular data on local governments’ responses to the COVID-19 pandemic. We documented substantial variation within and across states on a wide range of policies at a single point in time. By making these data publicly available, this study supports future research that can leverage this database to examine how policies contributed to and continue to influence pandemic-related health and socioeconomic outcomes and disparities. The UCCP database is available online and will include additional time points for 2020–2021 and additional counties nationwide.

Race and ethnic minority, local pollution, and COVID-19 deaths in Texas

The costs of COVID-19 are extensive, and, like the fallout of most health and environmental crises in the US, there is growing evidence that these costs weigh disproportionately on communities of color. We investigated whether county-level racial composition and fine particulate pollution (PM2.5) are indicators for COVID-19 incidence and death rates in the state of Texas. Using county-level data, we ran linear regressions of percent minority as well as historic 2000–2016 PM2.5 levels against COVID-19 cases and deaths per capita. We found that a county's percent minority racial composition, defined as the percentage of population that identifies as Black or Hispanic, highly correlates with COVID-19 case and death rates. Using Value-of-Statistical-Life calculations, we found that economic costs from COVID-19 deaths fall more heavily on Black and Hispanic residents in Harris County, the most populous county in Texas. We found no consistent evidence or significant correlations between historic county-average PM2.5 concentration and COVID-19 incidence or death. Our findings suggest that public health and economic aid policy should consider the racially-segregated burden of disease to better mitigate costs and support equity for the duration and aftermath of health crises.

Structural Racism as an Environmental Justice Issue: A Multilevel Analysis of the State Racism Index and Environmental Health Risk from Air Toxics

Communities of color and poor neighborhoods are disproportionately exposed to more air pollution—a pattern known as environmental injustices. Environmental injustices increase susceptibility to negative health outcomes among residents in affected communities. The structural mechanisms distributing environmental injustices in the USA are understudied. Bridging the literatures on the social determinants of health and environmental justice highlights the importance of the environmental conditions for health inequalities and sheds light on the institutional mechanisms driving environmental health inequalities. Employing a critical quantitative methods approach, we use data from an innovative state racism index to argue that systematic racialized inequalities in areas from housing to employment increase outdoor airborne environmental health risks in neighborhoods. Results of a multilevel analysis in over 65,000 census tracts demonstrate that tracts in states with higher levels of state-level Black–white gaps report greater environmental health risk exposure to outdoor air pollution. The state racism index explains four-to-ten percent of county- and state-level variation in carcinogenic risk and noncarcinogenic respiratory system risks from outdoor air toxics. The findings suggest that the disproportional exposure across communities is tied to systematic inequalities in environmental regulation and other structural elements such as housing and incarceration. Structural racism is an environmental justice issue.

Radon in child care centers: An examination of state laws and regulations in the United States

Radon is the second leading cause of lung cancer after smoking in the United States (US); however, there is a lack of state policies and regulations to address radon gas exposure. This study aimed to explain if state radon legislation for child care centers is associated with the percent of counties within the state in radon zone 1(above 4 pCi/L). The research method was secondary analysis. Data were obtained from EPA radon website, journal resources, state laws and regulations, and official state government websites. The existing radon laws were assessed based on the EPA radon zones. Then, independent T-Test with a significant level of P<0.05 was used. The finding of this study indicated 39 US states have at least one county or more in radon zone 1, and 11 states have no counties in radon zone 1. Eleven states have legislation associated with child care centers, and 39 states have no such regulation in place. Twenty eight percent (28%) (n=39) of states with at least one county or more in radon zone 1 have radon regulations for child care facilities. The findings reveal that states located in EPA radon zone 1, partially or completely, were Eighty eight percent (88%) likely to not have different regulations requiring the radon testing in child care centers than states that are not in zone 1. In other words, the association between state radon legislation for child care centers and the percent of counties in radon zone 1 is remarkable but not significant (p-value = 0.12).

Historic and recent trends in county-level coronary heart disease death rates by race, gender, and age group, United States, 1979-2017.

Given recent slowing of declines in national all-cause, heart disease, and stroke mortality, examining spatiotemporal distributions of coronary heart disease (CHD) death rates and trends can provide data critical to improving the cardiovascular health of populations. This paper documents county-level CHD death rates and trends by age group, race, and gender from 1979 through 2017. Using data from the National Vital Statistics System and a Bayesian multivariate space-time conditional autoregressive model, we estimated county-level age-standardized annual CHD death rates for 1979 through 2017 by age group (35-64 years, 65 years and older), race (white, black, other), and gender (men, women). We then estimated county-level total percent change in CHD death rates during four intervals (1979-1990, 1990-2000, 2000-2010, 2010-2017) using log-linear regression models. For all intervals, national CHD death rates declined for all groups. Prior to 2010, although most counties across age, race, and gender experienced declines, pockets of increasing CHD death rates were observed in the Mississippi Delta, Oklahoma, East Texas, and New Mexico across age groups and gender, and were more prominent among non-white populations than whites. Since 2010, across age, race, and gender, county-level declines in CHD death rates have slowed, with a marked increase in the percent of counties with increasing CHD death rates (e.g. 4.4% and 19.9% for ages 35 and older during 1979-1990 and 2010-2017, respectively). Recent increases were especially prevalent and geographically widespread among ages 35-64 years, with 40.5% of counties (95% CI: 38.4, 43.1) experiencing increases. Spatiotemporal differences in these long term, county-level results can inform responses by the public health community, medical providers, researchers, and communities to address troubling recent trends.

1235-P: Effects of Medicaid Expansion on Uninsured Rates: Diabetes Belt vs. Non-Belt Counties

Objective: To examine trends in insurance rates in 2012-2016 among low-income adults aged <65 and determine whether Medicaid expansion helped reduce the gap in uninsured rates between Diabetes Belt (DB) and non-DB counties. The Diabetes Belt is a region with elevated rates of diabetes that includes 644 counties across 15 southeastern states. Methods: Data for 1,180 county-level data from the Small Area Health Insurance Estimates and Area Health Resources File were used to analyze the trends in uninsured rates in populations with household income ≤138% federal poverty line (FPL). Multivariable analysis adjusted for county percent population aged 50-64 years, females, married, distress county index, and rurality. Results: Crude uninsured rates were 5% higher in DB compared to non-DB counties (39% vs. 34%, p < 0.001) in 2012. Uninsured rates declined rapidly in both DB and non-DB counties to 13% and 15% in 2016. Adjusted changes in uninsured rates between 2012 and 2016 were 31% in DB (p < 0.001) and 21% in non-DB counties (p < 0.001) with the adjusted uninsured rates being 16% in both areas in 2016. Figure below shows the trends. Discussion: Medicaid expansion had the intended effects on reducing uninsured rates in both DB and non-DB counties. Initial disparities in uninsured rates between the two areas were completely eradicated by 2016. Medicaid expansion may have helped improve uptake of preventive care in the Diabetes Belt. Disclosure J.M. Lobo: None. S. Kim: None. G.M. Ocker: None. H. Kang: None. T.L. McMurry: None. M. Sohn: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK113295)

Perioperative Mortality in Nonelderly Adult Patients With Cancer: A Population-based Study Evaluating Health Care Disparities in the United States According to Insurance Status.

The purpose of this study was to evaluate whether insurance status predicts for perioperative mortality (death within 30 d of cancer-directed surgery) for the 20 most common surgically treated cancers. The SEER database was examined for the 20 most common surgically resected cancers and included nonelderly adults, aged 18 to 64 years. The database was queried from 2007 to 2011, with a total of 506,722 patients included in the analysis. Insurance status for all patients were the following: non-Medicaid insurance (83%), any Medicaid (10%), uninsured (4%), and unknown (3%). In univariate analyses, predictors for perioperative mortality included insurance status (P<0.001), age (P=0.015), race (P<0.001), marital status (P<0.001), residence (P=0.002), percent of county below the federal poverty level (P<0.001), and median county-level income (P<0.001). Perioperative mortality was also associated with advanced disease (P<0.001). Under multivariate analysis, patients with either Medicaid (Cochran-Mantel-Haenszel odds ratio [CMH OR], 1.21; 95% confidence interval [CI], 1.14-1.29; P<0.001) or uninsured status (CMH OR, 1.56; 95% CI, 1.44-1.70; P<0.001) were more likely to die within 30 days of surgery compared with patients with non-Medicaid insurance. When comparing Medicaid with the uninsured, Medicaid patients had significantly lower rates of perioperative mortality when compared with the uninsured (CMH OR, 0.80; 95% CI, 0.73-0.89, P<0.001). In the largest reported analysis of perioperative mortality evaluating the 20 most common surgically treated malignancies, patients with Medicaid coverage or without health insurance were more likely to die within 30 days of surgery, with the uninsured having the worst outcomes.

Whither the 100th Meridian? The Once and Future Physical and Human Geography of America’s Arid–Humid Divide. Part II: The Meridian Moves East

Abstract The 100th meridian bisects the Great Plains of the United States and effectively divides the continent into more arid western and less arid eastern halves and is well expressed in terms of vegetation, land hydrology, crops, and the farm economy. Here, it is considered how this arid–humid divide will change in intensity and location during the current century under rising greenhouse gases. It is first shown that state-of-the-art climate models from phase 5 of the Coupled Model Intercomparison Project generally underestimate the degree of aridity of the United States and simulate an arid–humid divide that is too diffuse. These biases are traced to excessive precipitation and evapotranspiration and inadequate blocking of eastward moisture flux by the Pacific coastal ranges and Rockies. Bias-corrected future projections are developed that modify observationally based measures of aridity by the model-projected fractional changes in aridity. Aridity increases across the United States, and the aridity gradient weakens. The main contributor to the changes is rising potential evapotranspiration, while changes in precipitation working alone increase aridity across the southern and decrease across the northern United States. The “effective 100th meridian” moves to the east as the century progresses. In the current farm economy, farm size and percent of county under rangelands increase and percent of cropland under corn decreases as aridity increases. Statistical relations between these quantities and the bias-corrected aridity projections suggest that, all else being equal (which it will not be), adjustment to changing environmental conditions would cause farm size and rangeland area to increase across the plains and percent of cropland under corn to decrease in the northern plains as the century advances.

Reproductive justice & preventable deaths: State funding, family planning, abortion, and infant mortality, US 1980–2010

IntroductionLittle current research examines associations between infant mortality and US states’ funding for family planning services and for abortion, despite growing efforts to restrict reproductive rights and services and documented associations between unintended pregnancy and infant mortality. Material and methodsWe obtained publicly available data on state-only public funding for family planning and abortion services (years available: 1980, 1987, 1994, 2001, 2006, and 2010) and corresponding annual data on US county infant death rates. We modeled the funding as both fraction of state expenditures and per capita spending (per woman, age 15–44). State-level covariates comprised: Title X and Medicaid per capita funding, fertility rate, and percent of counties with no abortion services; county-level covariates were: median family income, and percent: black infants, adults without a high school education, urban, and female labor force participation. We used Possion log-linear models for: (1) repeat cross-sectional analyses, with random state and county effects; and (2) panel analysis, with fixed state effects. ResultsFour findings were robust to analytic approach. First, since 2000, the rate ratio for infant death comparing states in the top funding quartile vs. no funding for abortion services ranged (in models including all covariates) between 0.94 and 0.98 (95% confidence intervals excluding 1, except for the 2001 cross-sectional analysis, whose upper bound equaled 1), yielding an average 15% reduction in risk (range: 8–22%). Second, a similar risk reduction for state per capita funding for family planning services occurred in 1994. Third, the excess risk associated with lower county income increased over time, and fourth, remained persistently high for counties with a high percent of black infants. ConclusionsInsofar as reducing infant mortality is a government priority, our data underscore the need, despite heightened contention, for adequate public funding for abortion services and for redressing health inequities.

SAS Macro for Causal Mediation Analysis with Survival Data

SAS Macro for Causal Mediation Analysis with Survival Data

Disparities in stage at diagnosis, treatment, and survival in nonelderly adult patients with cancer according to insurance status.

The purpose of this study was to determine the association of insurance status with disease stage at presentation, treatment, and survival among the top 10 most deadly cancers using the SEER database. A total of 473,722 patients age 18 to 64 years who were diagnosed with one of the 10 most deadly cancers in the SEER database from 2007 to 2010 were analyzed. A Cox proportional hazards model was used for multivariable analyses to assess the effect of patient and tumor characteristics on cause-specific death. Overall, patients with non-Medicaid insurance were less likely to present with distant disease (16.9%) than those with Medicaid coverage (29.1%) or without insurance coverage (34.7%; P < .001). Patients with non-Medicaid insurance were more likely to receive cancer-directed surgery and/or radiation therapy (79.6%) compared with those with Medicaid coverage (67.9%) or without insurance coverage (62.1%; P < .001). In a Cox regression that adjusted for age, race, sex, marital status, residence, percent of county below federal poverty level, site, stage, and receipt of cancer-directed surgery and/or radiation therapy, patients were more likely to die as a result of their disease if they had Medicaid coverage (hazard ratio [HR], 1.44; 95% CI, 1.41 to 1.47; P < .001) or no insurance (HR, 1.47; 95% CI, 1.42 to 1.51; P < .001) compared with non-Medicaid insurance. Among patients with the 10 most deadly cancers, those with Medicaid coverage or without insurance were more likely to present with advanced disease, were less likely to receive cancer-directed surgery and/or radiation therapy, and experienced worse survival.

Recessions, Growth and Banking Crises

We examine the relationship of banking crises with economic growth and recessions. Our data cover 21 economies from around the world, most from 1870 to 2009 with the rest starting in 1901 or earlier. The data include capital investment and human capital formation. We have two major findings. First, there is very large heterogeneity in growth of Gross Domestic Product (GDP) and capital investment after banking crises. Most strikingly, twenty-five percent of counties experience no decrease in real GDP per capita in the year of the crisis or the following two years. Some countries see an increase in long run growth after a crisis while others see a fall, with no clear overall pattern. Second, we find clear evidence consistent with Zarnowitz’s Law. If there is a contraction in economic activity after a banking crisis, larger decreases in real GDP per capita are followed by faster subsequent growth.

Even As Mortality Fell In Most US Counties, Female Mortality Nonetheless Rose In 42.8 Percent Of Counties From 1992 To 2006

Researchers increasingly track variations in health outcomes across counties in the United States, but current ranking methods do not reflect changes in health outcomes over time. We examined trends in male and female mortality rates from 1992-96 to 2002-06 in 3,140 US counties. We found that female mortality rates increased in 42.8percent of counties, while male mortality rates increased in only 3.4percent. Several factors, including higher education levels, not being in the South or West, and low smoking rates, were associated with lower mortality rates. Medical care variables, such as proportions of primary care providers, were not associated with lower rates. These findings suggest that improving health outcomes across the United States will require increased public and private investment in the social and environmental determinants of health-beyond an exclusive focus on access to care or individual health behavior.

Utilization, Measurement, and Funding of Recovery Supports and Services

An environmental survey was conducted regarding substance abuse recovery supports and services (RSS) delivered across California, where these services are offered, and by whom. Inquiries were made regarding RSS measurement efforts, funding mechanisms, and technical assistance needs. A survey was disseminated to all 57 administrators of county alcohol and other drug or behavioral departments. Results indicate that 62% (23 of 37) of responding counties offer RSS. Overall, certified addiction counselors (CACs) were the staff most utilized to provide RSS, followed by peers, clinicians, and volunteers. Among recovery-community organizations (RCOs), peers, volunteers, and CACs were the most utilized staff. Sober living homes were the most prevalent type of RCO, followed by recovery centers, faith-based/recovery ministries, and recovery schools. Forty-five percent of counties reported funding RSS; 37.8% collect data. RSS may provide valuable support services for individuals recovering from alcohol/drug use; however, the field must further define RSS and develop measurement strategies to justify RSS funding.

The Internet and Local Wages: A Puzzle

How did the diffusion of the internet affect regional wage inequality? We examine the relationship between business investment in advanced internet technology and local variation in US wage growth between 1995 and 2000. We identify a puzzle. The internet is widespread, but the economic payoffs are not. Advanced internet technology is only associated with substantial wage growth in the 6 percent of counties that were already highly wealthy, educated, and populated and had IT-intensive industry. Advanced internet and wage growth appear unrelated elsewhere. Overall, advanced internet explains over half the difference in wage growth between already well-off counties and all others. JEL: J31, L86, O33, R11, R23

CMS Payments Necessary to Support HMO Participation in Medicare Managed Care

In recent years, many health maintenance organizations (HMOs)have exited the market for Medicare managed care; since 1998, the number of participating plans has fallen from 346 to 174. As a result of this reduced participation by HMOs, hundreds of thousands of Medicare beneficiaries have been involuntarily disenrolled from the program at the end of each year from 1998 to 2001.This paper estimates the Centers for Medicare and Medicaid Services (CMS) capitation payments that are necessary to support the participation of various numbers of HMOs in Medicare managed care per county market. This paper does not make a normative statement about how many HMOs should be supported in this program; rather, it makes a positive statement about the levels of payment necessary to support various numbers of HMOs.The identification strategy is to observe how the number of participating HMOs varies over counties and time in response to CMS payment, while controlling for estimated costs. This paper studies the period 1993-2001 and focuses in particular on the variation in payment, independent of costs, that occurred as a result of the Balanced Budget Act of 1997, which dramatically changed the way that HMOs are paid in this program. In light of the fact that it may not be cost-effective for CMS to support HMO participation in relatively rural or unpopulated counties, the sample used in this paper is limited to the 60 percent of U.S. counties with the largest populations of Medicare beneficiaries.The ordered probit results presented in this paper indicate that, to support one Medicare HMO in 2001 in half of the counties in the sample, CMS would have to pay $682.08 per average enrollee per month in the marginal county. To support one Medicare HMO in 2001 in every county in the sample, CMS would need to pay $1,008.25 per enrollee per month in the maximum-payment county. For comparison, the maximum monthly payment paid by CMS to any county in 2001 was $833.55.This paper finds that 79.3 percent of counties in the sample received a CMS payment in 2001 that was less than what was necessary to support a single HMO in Medicare managed care. Compared to those counties that received a payment exceeding the estimated threshold for HMO participation, these counties are, on average, more rural and less populated, with citizens who are less wealthy and less educated. The relative disadvantage of rural and unpopulated counties persists three years after the Balanced Budget Act of 1997, designed in part to eliminate such disparities, took effect.

CMS Payments Necessary to Support HMO Participation in Medicare Managed Care

In recent years, many health maintenance organizations (HMOs)have exited the market for Medicare managed care; since 1998, the number of participating plans has fallen from 346 to 174. As a result of this reduced participation by HMOs, hundreds of thousands of Medicare beneficiaries have been involuntarily disenrolled from the program at the end of each year from 1998 to 2001.This paper estimates the Centers for Medicare and Medicaid Services (CMS) capitation payments that are necessary to support the participation of various numbers of HMOs in Medicare managed care per county market. This paper does not make a normative statement about how many HMOs should be supported in this program; rather, it makes a positive statement about the levels of payment necessary to support various numbers of HMOs.The identification strategy is to observe how the number of participating HMOs varies over counties and time in response to CMS payment, while controlling for estimated costs. This paper studies the period 1993-2001 and focuses in particular on the variation in payment, independent of costs, that occurred as a result of the Balanced Budget Act of 1997, which dramatically changed the way that HMOs are paid in this program. In light of the fact that it may not be cost-effective for CMS to support HMO participation in relatively rural or unpopulated counties, the sample used in this paper is limited to the 60 percent of U.S. counties with the largest populations of Medicare beneficiaries.The ordered probit results presented in this paper indicate that, to support one Medicare HMO in 2001 in half of the counties in the sample, CMS would have to pay $682.08 per average enrollee per month in the marginal county. To support one Medicare HMO in 2001 in every county in the sample, CMS would need to pay $1,008.25 per enrollee per month in the maximum-payment county. For comparison, the maximum monthly payment paid by CMS to any county in 2001 was $833.55.This paper finds that 79.3 percent of counties in the sample received a CMS payment in 2001 that was less than what was necessary to support a single HMO in Medicare managed care. Compared to those counties that received a payment exceeding the estimated threshold for HMO participation, these counties are, on average, more rural and less populated, with citizens who are less wealthy and less educated. The relative disadvantage of rural and unpopulated counties persists three years after the Balanced Budget Act of 1997, designed in part to eliminate such disparities, took effect.

The Roepke Lecture in Economic Geography Catastrophic Earthquake Insurance: Patterns of Adoption

In California, earthquake insurance is not mandatory and is relatively expensive. Investment in earthquake insurance is one indicator of individual/ household response to hazards in the urban environment. This paper reports on a series of three surveys of California homeowners undertaken in 1989, 1990, and 1993 in Contra Costa, Santa Clara, Los Angeles, and San Bernardino counties. The surveys addressed six hypotheses: rates of insurance subscription have increased; socioeconomc and demographic characteristics distinguish the insured from the uninsured; insurance purchase is systematically related to geophysical risk at the home site; perceived risk is a predictor of insurance purchase; experience with an earthquake increases perceived risk and motivates insurance purchase; and mandatory noncatastrophic insurance increases the propensity to buy nonmandatory catastrophic insurance. The surveys yielded three primary findings. First, the proportion of households subscribing to earthquake insurance increased steadily, from about 5 percent in 1973 to approximately 40 percent in Santa Clara and Los Angeles counties in 1989 and 50 percent in those counties in 1993. Second, the geographic pattern of insurance subscription has consistently been unrelated to relative geophysical risk: those in areas susceptible to high degrees of ground shaking are no more likely to purchase insurance than those in less risky areas. Third, the strongest and most consistent predictor of earthquake insurance purchase is perceived vulnerability: those who perceive that their homes or communities are likely to experience earthquake damage are more likely to purchase earthquake insurance. Future research should involve cross-cultural studies, specifically addressed at questions of the universality of the empirical relationships between personality, demographic-economic status, and insurance purchase, or, more broadly, earthquake-mitigation behavior.