Obstetricians and gynecologists (OB-GYNs) provide essential health care to women across their lifespan. Yet nearly half of US counties have no OB-GYNs, with nonmetropolitan communities disproportionately affected. Targeted Regulation of Abortion Providers (TRAP) laws, spurred by the 1992 US Supreme Court decision in Planned Parenthood v. Casey, impose regulatory burdens on abortion providers and may have influenced whether and where OB-GYNs choose to practice, which has not yet been comprehensively studied. Using a staggered difference-in-differences design and county-level data, we found that TRAP laws were associated with an average reduction of 4.67percent in the density of OB-GYNs per 100,000 women ages 15-44 during the period 1993-2021, between Casey and the Dobbs v. Jackson Women's Health Organization decision in 2022. TRAP laws affected both general and fellowship-trained OB-GYNs, as well as counties without abortion facilities. Concerningly, TRAP laws led to lower physician density in nonmetropolitan counties-a difference that persisted for a decade. As OB-GYN shortages are projected to worsen and TRAP laws are still in effect in twenty-four states, policy makers should consider the long-run effects of TRAP laws on women's access to health care and their potential to exacerbate geographic disparities in access to care.

ABSTRACT This paper employs county-level panel data from 2012 to 2020 and a staggered difference-in-differences (DID) approach to examine the impact of China’s National New-Type Urbanization Plan (NNUP) on firm entry. The findings indicate that the NNUP significantly discourages firm entry through two main channels: first, by increasing enterprise costs due to enhanced worker welfare policies; and second, by intensifying fiscal pressure on local governments because of increased investments in public services. This negative effect exhibits regional heterogeneity depending on strategic orientations and administrative levels. However, the NNUP also fosters positive structural changes by promoting the growth of public service sectors such as education, healthcare, and transportation. The study further reveals that although the NNUP enhances social welfare and sustainability, achieving inclusive economic growth requires striking a balance between urbanization objectives and a business-friendly environment. Specifically, local governments should adopt fiscal diversification strategies and formulate adaptive policies tailored to regional characteristics to ensure sustainable development during the process of urbanization reform and resident welfare enhancement. This research contributes to a deeper understanding of the microeconomic impacts of urbanization, providing valuable insights into urban policy design in developing economies.

Abstract The growing number of extreme weather events has contributed to an increasing number and severity of power outages. However, the complex interplay of extreme weather events and their compounding effects on power outage characteristics (e.g. event duration) has not been comprehensively explored. Power outage data is often not publicly available, especially at high spatial resolution. Identifying outages related to weather events can also be challenging, as various weather variables can trigger or modulate power outages when they occur, in isolation or combined. Here, we use county-level power outage data from EAGLE-I for the state of Florida from 2015 to 2022 to identify moderate and major weather-related outages and analyze their characteristics. We show that total outage counts were higher in metro areas than in non-metro areas. However, the percentage of weather-related power outages was higher in non-metro areas than in metro areas. The spatial variation of grid reliability indicators derived from all weather-related events follows similar patterns as derived when just focusing on tropical cyclone events, highlighting the importance of these types of extremes in creating prolonged outages. Considering six relevant weather variables, we identify univariate and compound events (i.e. when more than one weather variable was extreme at the time of the outage). Univariate events have a relatively homogenous pattern across the state of Florida, while compound events have more localized hotspots. The average duration of the outages also increases when moving from univariate to multivariate events. Our results shed light on the relative importance of different weather variables (in isolation or combination) in creating power outages with different characteristics across Florida. Identifying such relationships is an important step toward understanding how power outage frequency and/or severity may change when certain extreme weather events become more frequent and/or intense.

Background: Cardiovascular disease (CVD) is the leading cause of morbidity, hospitalization and mortality among adults in the United States (US): every 33 seconds, one person dies from a CVD. Social Vulnerability Index (SVI) is used to identify and prioritize communities that need more support during disasters .Previous studies have shown a significant association between SVI and the prevalence and risk factors of CVD, However, little is known about the collective impact of SVI and CVD-related hospitalization rate (CVDHR) in the US. Objectives: To examine the association between county-level SVI and CVDHR among adults aged 35 years and older in terms of gender, race and state in the top 5 populated US states between 2019 to 2021. Methods: This was a retrospective cross-sectional study of county-level SVI data from the top 5 populated states in the US (California, Texas, Florida, New York,Pennsylvania).The data were obtained from the Centers for Disease Control and Prevention Interactive Atlas of Heart Disease and Stroke database. This data was linked to county-level SVI data obtained from the Agency for Toxic Substances and Disease Registry. The linked data was divided into quartiles based on SVI percentile scores with SVI-Q1(0-0.25, least vulnerable)to SVI-Q4(0.75-1, most vulnerable). The CVDHR(per 100,000) persons and the 95% confidence interval (CI) were computed for the overall population and then stratified by gender, race, state of residence, and SVI quartile. The outcome was the rate difference between SVI-Q4&SVI-Q1 and a negative impact by SVI was characterized by a higher CVDHR within SVI-Q4 compared with SVI-Q1 and nonoverlapping CIs. Results: The overall mean CVDHR for SVI-Q4 (41.3; CI: 39.8-42.7) was higher than that for SVI-Q1 (38.4: CI: 37.1-39.7) with an excess of 2.9 .For Females SVI-Q4 vs SVI-Q1 [(36.8; CI:35.4-38.3 vs 33.1: CI:32.0-34.3); excess of 3.7];Hispanics, [(33.9; CI:30.5-37.3 vs 32.0; CI:30.4-33.5); excess of 4.3] and in Whites [(41.4; CI:39.3-42.9 vs 40.1; CI:39.4-40.8);excess of 2.9]. In California, SVI-Q4 vs SVI-Q1 [34.4; CI: 31.3-37.5 vs 28.2; CI:25.8-30.5); excess of 6.2]. There was no significant difference between SVI-Q4 &-Q1 for males, Black people, and the other states. Conclusion: Higher county-level social vulnerability was associated with increased CVDRH, and in specific demographic groups. More attention should be focused on vulnerable communities ie. increasing preventive care measures and awareness on healthy lifestyles.

Improving regional economic resilience is a key goal for governments around the world to address global economic instability. This paper employs a quasi-natural experiment of “Province-Managing-County” (PMC) reform in China, uses a time-varying DID method to investigate the mechanism and the impact of the flattening government on county-level economic resilience (CER) in China. Through empirical analysis of county-level data in China from 2000 to 2020, we found that government flattening significantly improved CER. The heterogeneity test results indicate that cities located in eastern China, regions with higher levels of economic development, and industries with higher levels of industrial upgrading are more affected by PMC reform. A reliable mechanism indicates that PMC policies effectively affect CER by promoting fiscal self-sufficiency, narrowing the urban-rural gap, and improving local innovation levels. Therefore, government should promote and improve PMC reform to address regional disparities and enhance local fiscal capacity, which is an important measure to enhance regional economic development.

Hearing loss is a significant public health issue, affecting 23% of individuals 12 years and older in the US. While hearing loss can be efficaciously treated in many cases, shortages in the supply of hearing health care (HHC) professionals may limit uptake. To quantify the US HHC professional workforce from 2012 to 2022 and identify areas experiencing HHC professional shortages in 2019. In this quality improvement study, raw data from the National Plan and Provider Enumeration System were transformed to create a state- and county-level database of HHC professionals, including audiologists and hearing instrument specialists from 2012 to 2022, to assess HHC workforce supply. To assess HHC workforce demand, 2019 state- and county-level hearing loss prevalence data from Sound Check and US Census population data were used. Shortage areas were determined by comparing these measures of supply and demand in 2019. The audiologists and hearing instrument specialists included possessed National Provider Identifiers, allowing them to bill public and private insurance in the US. The data were analyzed between August 2022 and December 2024. Potential-shortage areas were defined using a threshold of 1 or fewer audiologists per 3500 individuals with hearing loss, and shortage areas were defined using a threshold of 1 or fewer HHC professionals per 3500 individuals with hearing loss. From 2012 to 2022, the number of HHC professionals in the US increased from 16 770 to 30 704, or more than 83%. By the end of 2022, 72.4% of the HHC workforce were audiologists, and 27.6% were hearing instrument specialists, compared to 82.6% and 17.4%, respectively, in 2012. In June 2019, 75.0% of US counties were identified as shortage counties, and these counties were disproportionately rural. Ten states, primarily in the South Census region, are identified as shortage states. This quality improvement study showed that despite workforce growth, many areas of the US continue to experience shortages of HHC professionals, disproportionately affecting rural populations. Addressing these shortages may improve access to care for individuals with hearing loss.

Head and neck (H&N) cancers, a diverse group of epithelial malignancies, significantly impact patients' quality of life and require complex, multidisciplinary care. Despite the need for specialized care, access to H&N cancer specialists is uneven across the United States, leading to disparities in patient outcomes and health equity. To assess geographic disparities in access to H&N cancer specialists in the U.S. and to identify factors contributing to these disparities, with the goal of informing targeted interventions and policies that promote equitable healthcare access. This geospatial analysis utilized data from various public databases, including the National Provider Identifier Registry, American Society of Clinical Oncology, and U.S. News and World Report, to examine the distribution of H&N cancer specialists relative to incident cancer cases. The study analyzed county-level data across the United States, incorporating demographic factors such as race/ethnicity, age, education, and socioeconomic status. Travel time to the nearest H&N specialist was estimated using the Travel Time API. The analysis included 1,112 H&N specialists (453 surgical oncologists, 346 medical oncologists, and 308 radiation oncologists) identified through self-reported data and relevant fellowships. The primary outcome was the estimated travel time to the nearest H&N specialist, with secondary measures including a disparity index that combined cancer incidence, social vulnerability, and travel time to highlight regions with the greatest access disparities. Significant regional disparities in access to H&N specialists were identified, with non-metropolitan areas and regions outside the Northeast showing notably longer travel times. Socioeconomic and demographics factors, including lower household income, lower insurance coverage, and higher median age, were associated with increased travel times. Disparity Index scores highlighted counties in the South and Western regions as having the highest access disparities. Geographic and socioeconomic disparities in access to H&N cancer specialists contribute to health inequities in the U.S. The disparity index developed in this study provides a valuable tool for identifying high-need areas and guiding policy interventions. Addressing these disparities through targeted resource allocation, mobile clinics, and provider incentives is essential for improving access to specialized care and promoting health equity.

How do people in authoritarian regimes adapt to external economic pressure? We examine how economic sanctions affect informal economic activity in North Korea. Using county-level data from 167 regions for the years 2016, 2018, and 2022, we find that informal economic activity significantly expanded in areas most affected by sanctions, particularly those reliant on heavy industry such as primary metals, machinery, and transportation. These bottom-up adaptations illustrate how citizens, rather than the state, absorb the shocks of international pressure. By tracing micro-level adjustments over time, our study sheds light on the uneven and indirect effects of sanctions in targeted countries. The findings highlight the need for more strategic, sector-sensitive sanction design and contribute to broader debates on the effectiveness of economic sanctions, authoritarian resilience, and economic coping mechanisms under constraint.

ABSTRACT Accurate crop yield mapping is critical for ensuring food security and optimizing agricultural management amid increasing climate variability. However, conventional light use efficiency (LUE) models primarily address water deficit impacts while neglecting excessive moisture effects, a critical limitation in humid regions like China’s Middle and Lower Yangtze River Basin (MLYR), where waterlogging reduces winter wheat yields by up to 30%. To address this gap, we propose a novel water stress factor (named w s _ mod ) based on soil moisture (SM) and Land Surface Water Index (LSWI) to accurately characterize the influence of excessive water on winter wheat yield. County-level winter wheat yield of three provinces (Jiangsu, Anhui, Hubei) from 2000, 2002, 2004, 2006, 2008, 2010, 2012, and 2014 were used as the training dataset, with the other seven years of county-level data and independent city-level data (2015–2021) for validation. The results show that considering the impact of excess water in humid and semi-humid regions can improve the accuracy of crop yield estimation. The combined LUE model, which considered water excess and water deficit, achieved superior performance (RMSE = 69.34 g C m−2 year−1, MAE = 52.23 g C m−2 year−1, R = 0.60), reducing 3.86 g C m−2 year−1, 3.13 g C m−2 year−1 compared with LSWI-based water stress ( w s _ lswi ) alone. Spatial validation using city-level data (2015–2021) confirmed robustness, with northern MLYR regions (e.g. Huang-Huai-Hai Plain) showing stable high yields ( >200 g C m− 2 year−1) and southern areas exhibiting waterlogging-induced reductions (e.g. 2002, Figure S3). This study could provide reference for estimating crop yields in humid to semi-humid regions at a national or even global scale.

Abstract No-till management is often recognized for its environmental and economic benefits, but its potential to reduce climate warming is still uncertain. Beyond ongoing debate over its effects on soil carbon storage, no-till also leaves plant residue on the surface, which can reflect more sunlight. This increase in surface reflectivity, called albedo, may help mitigate climate change by reducing the energy absorbed by the land. Here, we assessed this climate benefit of no-till across the U.S. Corn Belt using conservation survey records, county-level tillage data, and satellite observations. We found that no-till increased land surface brightness during the dormant season, reducing absorbed solar energy by an estimated 50 grams of CO2 equivalent per square meter per year. Regionally, this could add up to 24 teragrams of CO2 equivalent per year in potential climate benefits. Areas with low adoption, especially those with dark, carbon-rich soils, offer the greatest opportunity for further mitigation.

Abstract We consider the effect of labor market volatility on employment and wages in the meat processing sector. The period of study includes the COVID-19 pandemic, which resulted in significant labor market shocks in the sector. We examine the relationship between historical volatility of employment and wages and current employment and wages, focusing on the animal slaughtering and processing sector (NAICS 3116). We utilize county-level data to estimate dynamic panel data models of employment and wages. We find that historical volatility in both employment and wages had a significant negative impact on employment in the sector. In the case of wage volatility, we find that wages are higher following periods of significant wage volatility, suggesting that workers demand higher wages under conditions of market volatility. During COVID, smaller meat processors had lower levels of employment, but a small number of large processors had significantly higher levels of employment. In contrast, wages were higher after COVID-19 for almost all counties included in the analysis. In an aggregate sense, COVID tended to largely reduce employment but increase wages in the meat processing sector.

Cattle markets, where livestock producers may buy and sell cattle and calves, act as major hubs in the shipment network that connect cattle populations across the United States (U.S.). Cattle markets can then provide insight into the integration of the U.S. cattle industry, thus informing how regional price fluctuations may influence cattle prices nationally. Despite biosecurity measures and regulatory compliance from livestock markets, commingling and re-distribution of animals from multiple sources may elevate the risk of disease spread and make tracing animal movements more complex, which could pose significant challenges if a transboundary animal disease (TAD) were introduced into the U.S. Therefore, knowing the size and location of cattle markets in the U.S. is critical to understanding cattle industry market dynamics and enhancing pandemic scenario modeling efforts. In this article, we present a list of cattle markets, their locations, and estimated quarterly cattle sales. We compiled a list of 1619 known cattle markets with and without market sales data from 1131 counties across the U.S. from 2012–2016. To estimate unknown market sales data, we fit a spatial autoregressive lag model to annual county-level market sales data and used the fit to predict annual sales in counties that lacked sales information. County-level sales data provide important insight into the structure of the U.S. cattle industry. The dataset can be used to improve national-scale cattle movement models, livestock disease models, and inform TAD surveillance efforts.

The Internet provides many populations access to virtual health services, social resources, and health education. It is not understood how lack of household Internet adoption impacts the risk of negative health outcomes. Our study aimed to examine the relationship between Internet adoption and self-reported diabetes prevalence in US counties, while controlling for social determinants of health. This cross-sectional, retrospective study used US national county-level data obtained from the 2021 American Communities Survey and the 2021 Behavioral Risk Factors Surveillance System. Analysis included descriptive statistics, two-stage linear regression, and machine learning. A total of 3076 counties were analyzed. The results show that, in 2021, Internet adoption had a significant inverse relationship ( β = -.20, P < .001) with diabetes prevalence in US counties while controlling for other social determinants of health. The results suggest that as household Internet adoption rates increase, diabetes prevalence decreases, at the county level. The relationships between social characteristics, Internet adoption, and health behaviors on diabetes prevalence in US counties warrant future research including individual-level validation and integration of health behaviors related to diabetes risk. These findings provide evidence of Internet adoption as a social determinant of health.

Social capital, the strength of people’s friendship networks and community ties, has been hypothesized as an important determinant of survey participation. Investigating this hypothesis has been difficult given data constraints. In this paper, we provide insights by investigating how response rates and nonresponse bias in the American Community Survey are correlated with county-level social network data from Facebook. We find some evidence that areas of the United States where people have more exclusive and homogenous social networks have higher nonresponse bias and lower response rates. These results provide further evidence that the effects of social capital may not be simply a matter of whether or not people are socially isolated, but also what types of social connections people have and the sociodemographic heterogeneity of their social networks.

ABSTRACT This study examines the economic and structural determinants of premature mortality, measured in years of potential life lost. Using county-level panel data from 2014–2020, covering 2,880 U.S. counties and over 20,000 county-year observations, this study employed an instrumental variables approach to address endogeneity and estimate causal effects. A ten-day increase in mentally unhealthy days per month was associated with a 1.29-year reduction in life expectancy, driven by increased mortality from suicide, drug overdoses, and alcohol-related diseases. A five-percentage-point rise in child poverty led to a 0.72-year decline in life expectancy through food insecurity, adverse childhood experiences, and long-term chronic health conditions. Increasing primary care providers by one per 10,000 residents extended life expectancy by 0.91 years, with larger effects in economically distressed and racially segregated counties. The analysis explored underlying mechanisms linking these determinants to mortality outcomes, including subgroup analyses across counties stratified by racial composition, poverty levels, rural – urban classification, and U.S. census regions. Mental health distress amplified the negative effects of economic deprivation on mortality. Limited healthcare access constrained preventive interventions. These findings highlight the need for integrated policy solutions to expand mental health services, reduce child poverty, and improve healthcare accessibility in vulnerable communities.

Abstract Aim HIV and sexually transmitted infections (STIs) are increasing in prevalence, and individuals with a positive status may turn to online dating due to stigma or discrimination. The purpose of this study is to examine the relationship of online dating and cell phone app dating with the prevalence of STIs/HIV using census data on demographic factors, consumer dating data, and HIV/STI surveillance data. Subject and methods The study looks at demographic factors (race, age, urban living, and gender) to determine what factors are associated with online dating/cell phone app dating and HIV/ STIs. The US Census 2023 Dating Services–2023 Consumer Expenditure Surveys (CEX), and Centers for Disease Control and Prevention (CDC) HIV and STI data were analyzed using multiple regressions (N = 2617). A Pearson correlation and multiple regression were used to determine correlations. Results Pearson correlation showed a positive correlation for HIV and STIs with online dating and cell phone app dating. The regressions showed that online dating and cell phone app dating were positively correlated with HIV and not with STIs. Also, age group 25–44, male, non-Hispanic Black, and urban living were demographics associated with online dating, cell phone app dating, and HIV. No STIs were significantly associated with online or cell phone app dating. Conclusion This study can help professionals develop interventions using online and cell phone app dating services. Implementing interventions using online dating to target demographics that may be at greater risk of HIV can reduce the prevalence of HIV.

ABSTRACT While road infrastructure plays a pivotal role in rural development, the effects on rural residents’ income and the underlying mechanisms remain less explored. Combining micro-level survey data from the Chinese Household Income Project (CHIP) and county-level road data, this paper empirically investigates the impact of road infrastructure on the income of rural residents. Our findings confirm that both inter-county highways and intra-county roads contribute significantly to rural residents’ income, and the results remain robust to the endogeneity problem using an instrumental variables approach. Roads increase rural residents’ income mainly by stimulating their non-agricultural behaviour. County roads encourage rural residents to participate in local non-agricultural activities, while highways facilitate rural residents’ participation in both local and external non-agricultural activities. We also find that highways benefit rural residents at all income levels, while county roads predominantly benefit middle and upper-income groups. Our estimates provide evidence for the construction of roads in developing countries and regions intending to increase rural incomes and reduce poverty.

Factors Influencing the Use of the Text2Quit Feature in the Virginia Quitline Program.

Assessing the impacts of climate anomalies on plague risk in China during 1754-1949.

Amid the global drive to enhance public sector performance in the digital economy era, improving government spending efficiency has become a critical governance objective. This study investigates the impact of digital inclusive finance on government spending efficiency from a digital finance systems perspective using county-level panel data in China’s Yangtze River Delta for the period 2014–2022 and constructing the fixed-effects model and instrumental variable method to estimate the effect of digital inclusive finance and explore its underlying mechanisms. Heterogeneity across regions with varying economic development levels is analyzed, and fiscal pressure is examined as a potential mediating factor. The results indicate that (1) digital inclusive finance significantly enhances government spending efficiency, primarily through broad service coverage and deep usage of digital financial services such as mobile payments, digital credit, and insurance; (2) the positive effect is more pronounced in counties with lower government spending efficiency and economic development; and (3) fiscal pressure acts as a key transmission channel, with broader digital inclusive finance coverage helping to alleviate fiscal stress and improve government spending efficiency. These findings offer empirical insights into the role of digital finance in promoting effective and adaptive public financial governance.