Earlier routine induction of labor-Consequences on mother and child morbidity.

A growing number of birth interventions had led to a concern for potential health consequences. This study investigates the consequences of earlier routine labor induction. It exploits a natural experiment caused by the introduction of new Danish obstetric guidelines in 2011. Consequently, routine labor induction was moved forward from 14 to 10-13 days past the expected due date (EDD) and extended antenatal surveillance was introduced from 7 days past the EDD. Using administrative data, I find that affected mothers on average had a 9-11 percentage points (32%-38%) higher risk of being induced the following years. Yet, mother and child short- and medium-term morbidity were largely unaffected.

The vacated space of volume/price of the drugs centralized procurement with quantity in secondary and above public hospitals of China.

BACKGROUND: In 2018, the National Centralized Drug Procurement (NCDP) policy has been implemented in 11 provinces, and promoted across the country in 2019. The main feature of the policy is "volume for price", therefore, it is necessary to measure the price relationship, not only to reduce the price of drugs, reduce the burden of patients' medical costs, but also facilitate pharmaceutical companies to access enough innovation incentives. The aim of this study was to assess the vacated space effect of the drug centralized procurement by national organizations in exchange of price for quantity. METHODS: A difference-in-differences (DID) model was employed to analyze the effect of the 4 + 7 pilot drugs centralized purchasing policy on drug sales volume and selected versus clinically substitutable unselected varieties, using observational data from 2018 to 2019. We compared drug procurement data between secondary and above public hospitals in pilot and non-pilot cities throughout China. RESULTS: The study showed that the average treatment effect (ATE) of sales in the in-hospital market for the selected supply varieties in centralized purchasing is -0.42, and with a sales volume of 0.49. This indicates a volume-price vacated space of 1.16 ~ 1.17 DDD (defined daily dose)/Yuan, implying that for every 1 defined daily dose (DDD) increase in reported volume, the standardized price decreased by 1.16-1.17 Yuan. The ATE of in-hospital market sales for drugs not selected in centralized procurement shows a decrease of 0.13. This finding highlights the presence of the price linkage effect. The ATE of sales volume is 0.57, indicating a volume-price space of 4.38 ~ 4.39 DDD/Yuan for unselected drugs, approximately 3.75 higher relative to that of the selected ones. CONCLUSIONS: The ratio of the volume-price space of clinically substitutable unselected and selected drugs may serve as direct evidence for evaluating the shift from centralized purchasing of drug varieties to clinically substitutable other ones. To strengthen the volume-based negotiation approach and maximize the effectiveness of centralized purchasing policies, we recommend the strategic implementation of a three-tiered centralized purchasing system, the expansion of drug coverage, and the introduction of relevant constraints and incentives.

Impact of urban and rural residents medical insurance on self-rated health of residents in China: a panel study from the China family panel studies national baseline survey.

Objective: This study aimed to investigate the health performance of the Urban and Rural Residents Medical Insurance (URRMI) scheme in China and to make practical recommendations and scientific references for its full implementation in China. Methods: This is a panel study that uses data from the China Family Panel Studies from 2018 to 2020, which is separated into treated and control groups each year, utilizing the key approach of propensity score matching and difference-in-difference (PSM-DID). Using 1-to-1 k-nearest neighbor matching, we proportionate the baseline data. Using difference-in-difference model, we examine the mean treatment impact of the outcome variables. Using a 500-time random sample regression model, we validate the robustness of the model estimation. Results: The result was credible after matching, minimizing discrepancies. Good overall performance of self-rated health with an average Hukou status of, respectively, 0.8 and 0.4 in the treated and control group, primarily in rural and urban regions separately. The participation of URRMI significantly impacted self-rated health of residents, with a 0.456-unit improvement probabilities observed (p < 0.1). Additionally, the individuals are categorized into urban and rural, and those with urban hukou had a 0.311 expansion in the probability of having better health status compared to rural hukou (p < 0.05). Other factors, such as age, highest education, annual income, medical expenditure, hospital scale, clinic satisfaction, and napping, also impacted self-rated health. Moreover, elder individuals, higher education levels, and higher medical expenditure having a higher probability of improvement. The study utilized a placebo test to verify the robustness of the URRMI regression. The estimated coefficients showed that basic medical insurance did not significantly improve the health of insured residents under the URRMI scheme. Conclusion: The study demonstrates the crucial role of PSM-DID in determining the influence of URRMI on self-rated health status. It indicates that purchasing in URRMI has a favorable influence on the health of residents, advancing enhanced self-rated health effectiveness. It does, however, reveal geographical disparities in health, with urban dwellers faring far better than those who live in the suburb. Study suggests expanding URRMI coverage, narrowing urban-rural divide, increasing insurance subsidies, reforming laws, and developing effective advertising strategies.

The impact and mechanism analysis of Clean Development Mechanism on the synergistic effects of pollution mitigation and carbon reduction.

The establishment of the Clean Development Mechanism (CDM) has greatly improved China's carbon emission trading system. However, due to the unbalanced development of CDM in China, the effects and mechanism of CDM on reducing pollution and carbon are still unclear. In order to explore the effects and mechanism of CDM on the synergistic effects of pollution mitigation and carbon reduction, we first set up a theoretical analysis framework. Utilizing panel data from 254 prefecture-level cities across China spanning from 2004 to 2021, we employ a synergy degree model of composite system to evaluate the synergistic effects of pollution mitigation and carbon reduction. By treating CDM as a quasi-natural experimental research subject, we construct a multi-period difference-in-difference model to assess the CDM projects' effects. Our findings indicate a positive association between CDM projects and the synergistic effects of pollution mitigation and carbon reduction. Heterogeneity analysis reveals that CDM projects located in the western region, areas with lower levels of economic development, non-resource cities, non-old industrial bases, and projects with Certified Emission Reductions issued exhibit the most pronounced synergistic effects. Specially, dynamic policy effect analysis shows that only non-resource cities and non-old industrial bases exhibit enhanced policy implementation regarding CDM. Mechanism analysis demonstrates that CDM primarily enhances synergistic effects through improved energy efficiency, technological innovation and energy transition. These findings enrich empirical investigations concerning market-driven emission reduction policy in China, shedding light on pivotal pathways for synergistic control of pollution mitigation and carbon reduction and offering valuable policy insights for comprehensive economic and social green transformation in China.

Impact of the targeted poverty alleviation policy on older adults' healthcare utilization: A quasi-experimental analysis from China.

China implemented the Targeted Poverty Alleviation (TPA) policy in 2015 to fight against poverty. In order to assess the health performance of the TPA policy, this study aims to evaluate the impact of the TPA policy on healthcare utilization among older adults who normally have higher vulnerability to poverty and diseases. Drawing on data from four waves of the China Health and Retirement Longitudinal Study (CHARLS), we investigated the impact of the TPA policy on older individuals' outpatient and inpatient utilization using the difference-in-differences (DID) approach. In total, 5285 older respondents were incorporated into a final sample. The results indicated that the implementation of the TPA policy had a significantly positive impact on increasing inpatient care utilization for poor older adults. However, its impact on outpatient service utilization was not significant. To ensure that the increased level of inpatient care utilization was not caused by deteriorating health status, we further analyzed the impact of the TPA policy on poor older adults' health outcomes. Results indicated that the TPA policy improved self-rated health and reduced the number of ADL limitations among older adults in registered poor households. The positive impact of the TPA policy on inpatient care utilization was found to be most beneficial for older adults in poor households who were female, coupled, and aged 70 years and above. The TPA policy in China improved healthcare access for economically disadvantaged older adults and contributed to the enhancement of their health outcomes. This evidence may have broad implications for other low- and middle-income countries aiming to reduce poverty and achieve health equity.

Estimating the effectiveness of marked sidewalks: An application of the spatial causality approach.

Various safety enhancements and policies have been proposed to enhance pedestrian safety and minimize vehicle-pedestrian accidents. A relatively recent approach involves marked sidewalks delineated by painted pathways, particularly in Asia's crowded urban centers, offering a cost-effective and space-efficient alternative to traditional paved sidewalks. While this measure has garnered interest, few studies have rigorously evaluated its effectiveness. Current before-after studies often use correlation-based approaches like regression, lacking effective consideration of causal relationships and confounding variables. Moreover, spatial heterogeneity in crash data is frequently overlooked during causal inference analyses, potentially leading to inaccurate estimations. This study introduces a geographically weighted difference-in-difference (GWDID) method to address these gaps and estimate the safety impact of marked sidewalks. This approach considers spatial heterogeneity within the dataset in the spatial causal inference framework, providing a more nuanced understanding of the intervention's effects. The simplicity of the modeling process makes it applicable to various study designs relying solely on pre- and post-exposure outcome measurements. Conventional DIDs and Spatial Lag-DID models were used for comparison. The dataset we utilized included a total of 13,641 pedestrian crashes across Taipei City, Taiwan. Then the crash point data was transformed into continuous probability values to determine the crash risk on each road segment using network kernel density estimation (NKDE). The treatment group comprised 1,407 road segments with marked sidewalks, while the control group comprised 3,097 segments with similar road widths. The pre-development program period was in 2017, and the post-development period was in 2020. Results showed that the GWDID model outperformed the spatial lag DID and traditional DID models. As a local causality model, it illustrated spatial heterogeneity in installing marked sidewalks. The program significantly reduced pedestrian crash risk in 43% of the total road segments in the treatment group. The coefficient distribution map revealed a range from -22.327 to 2.600, with over 95% of the area yielding negative values, indicating reduced crash risk after installing marked sidewalks. Notably, the impact of crash risk reduction increased from rural to urban areas, emphasizing the importance of considering spatial heterogeneity in transportation safety policy assessments.

Impact of National Centralized Drug Procurement policy on chemical pharmaceutical enterprises' R&D investment: a difference-in-differences analysis in China.

Objective: This study aimed to evaluate the impact of the National Centralized Drug Procurement (NCDP) policy on chemical pharmaceutical enterprises' R&D investment and provide references for improving NCDP policy design and encouraging innovation in the pharmaceutical industry. Methods: Using the panel data of 102 Shanghai and Shenzhen A-share listed enterprises from 2016 to 2022 under the chemical pharmaceutical classification of Shenwan in Wind database as the research sample, this study developed difference-in-differences (DID) models on bid-winning and bid-non-winning enterprises, respectively, to evaluate the impact of NCDP policy on their R&D investment. In addition, this study tested the heterogeneity of bid-winning enterprises based on the bid success rate, the decline of drug price, and enterprise size. Results: The NCDP policy could encourage chemical pharmaceutical companies to increase R&D investment, but the low bid success rate and excessive drug price reduction would reduce their R&D enthusiasm, especially for small- and medium-sized enterprises. Discussion: It is suggested that the NCDP policy should be further improved: first, revise the bidding rule of the NCDP policy and increase the bid success rate so that more enterprises can win bids, and second, to solve the problem of excessive drug price reduction, evaluate the rationality of bid-winning prices, and introduce a two-way selection mechanism between medical institutions and supply enterprises. Integrate pharmacoeconomic evaluation into the NCDP rules to form a benign competition among enterprises. Third, attention should be paid to supporting policies for small- and medium-sized enterprises. By increasing procurement volume, shortening payment time limits, and increasing the proportion of advance payments, enterprises' cash flow shortages can be alleviated, thus achieving fairness and inclusiveness in the implementation of the NCDP policy.

Medicaid expansion in California and breast cancer incidence across neighborhoods with varying social vulnerabilities.

PURPOSE: To investigate changes in breast cancer incidence rates associated with Medicaid expansion in California. METHODS: We extracted yearly census tract-level population counts and cases of breast cancer diagnosed among women aged between 20 and 64 years in California during years 2010-2017. Census tracts were classified into low, medium and high groups according to their social vulnerability index (SVI). Using a difference-in-difference (DID) approach with Poisson regression models, we estimated the incidence rate, incidence rate ratio (IRR) during the pre- (2010-2013) and post-expansion periods (2014-2017), and the relative IRR (DID estimates) across three groups of neighborhoods. RESULTS: Prior to the Medicaid expansion, the overall incidence rate was 93.61, 122.03, and 151.12 cases per 100,000 persons among tracts with high, medium, and low-SVI, respectively; and was 96.49, 122.07, and 151.66 cases per 100,000 persons during the post-expansion period, respectively. The IRR between high and low vulnerability neighborhoods was 0.62 and 0.64 in the pre- and post-expansion period, respectively, and the relative IRR was 1.03 (95% CI 1.00 to 1.06, p = 0.026). In addition, significant DID estimate was only found for localized breast cancer (relative IRR = 1.05; 95% CI, 1.01 to 1.09, p = 0.049) between high and low-SVI neighborhoods, not for regional and distant cancer stage. CONCLUSIONS: The Medicaid expansion had differential impact on breast cancer incidence across neighborhoods in California, with the most pronounced increase found for localized cancer stage in high-SVI neighborhoods. Significant pre-post change was only found for localized breast cancer between high and low-SVI neighborhoods.

Impact of a Pilot Project for Integrated Care on Hospitalization Rate among Older Adults in South Korea.

Introduction: Since 2019, the Korean government has implemented a pilot project for integrated care to encourage healthy aging of older adults. This study investigated the changes in hospitalization rates among older adults who participated in the integrated care pilot project. Methods: Administrative survey data collected from 13 local governments and the National Health Insurance Database were used in present study. The participants comprised 17,801 older adults who participated in the pilot project between August 01, 2019 and April 30, 2022 and 68,145 matched controls. A propensity score matching method was employed to select the control group, and this study employed difference-in-differences (DID) approach to examine variations in the hospitalization rate. Results: The DID analysis revealed that the odds ratio for rates of hospitalization among older adults who participated in the pilot project was 0.88 (95% confidence interval [CI] 0.84, 0.91) in comparison to control group. In specifically, as compared to the control group, the odds ratio for hospitalization rates among the pilot project's discharged patients was 0.17 (95% CI 0.15, 0.20). Although not statistically significant, the odds ratio of older adults who utilized LTCI services was 0.93 (95% CI 0.83, 1.05), and the odds ratio of older adults who applied for LTCI but were rejected or were intensive social care was 1.09 (95% CI 0.95, 1.26) compared to the comparison group. Discussion: The findings imply that the discharged patient group had greater medical demands than the other types, and it can be claimed that this is the group that may anticipate greater efficacy while using health services. In addition, the integrated care services provided by the pilot project have the effect of reducing unnecessary hospitalization such as social hospitalization. Conclusion: Participants in the integrated care pilot project showed a lower hospitalization rate than the older adults who did not participate in the project but had similar characteristics. In particular, the admission rate of discharged patients showed a sharp decline.

No change in substance use disorders or overdose after implementation of state Earned Income Tax Credit (EITC).

BACKGROUND: Inadequate income is associated with higher likelihood of experiencing a substance use disorder (SUD). This study tests whether the earned income tax credit (EITC), which issues supplemental income for workers with children in the U.S., is associated with lower rates of SUD and fatal overdose. METHODS: We examined the effects of state-level refundable EITC presence and generosity (i.e., state EITC rate as a % of federal rate) on SUD-related outcomes (SUD prevalence and intentional and unintentional fatal overdose) using a difference-in-difference methodology, with both two-way fixed-effects models and event study plots. Several sensitivity analyses were conducted to assess the robustness of findings. Five data sources were used to create a combined state-level longitudinal dataset. RESULTS: We did not find significant effects of refundable EITC presence or generosity on unintentional or intentional fatal overdose or SUD prevalence in two-way models. Event study models detected a very slight upward shift in SUD prevalence following refundable EITC implementation (not seen in sensitivity analyses) and no significant effects of EITC implementation on any of the fatal overdose outcomes. CONCLUSIONS: Evidence regarding income support programs is being highly sought by policy makers as income support programs have become increasingly popular policy levers since the start of the COVID-19 pandemic. Our study indicates EITC policies likely have no impact on SUD or overdose, however, other income support programs without family restrictions are important to investigate further.

Information consumption city and carbon emission efficiency: Evidence from China's quasi-natural experiment.

The transformation of public consumption patterns has become a burning question, but there are few studies on public consumption patterns. Therefore, evaluating the impact of Information consumption city (ICC) policy on carbon emission efficiency holds significant implications. This study settles on 104 pilot cities in China from 2006 to 2020 to assess the impact and the response mechanism of ICC policy on carbon emission efficiency through the time-vary Difference-in-Difference (DID) model. The result shows that: (1) ICC policy significantly promotes the local carbon emission efficiency, which remains robust after a battery of sensitivity tests. (2) It improves carbon emission efficiency through production factors agglomeration effect, industrial structural changing effect, innovation promotion effect, and environmental attention effect; (3) The direct impact of ICC policy on carbon emission efficiency varies across regions with different information consumption and carbon emission base. (4) ICC can improve carbon emission efficiency through the joint implementation of smart city (SC), new urbanization (NU), ecological civilization city construction (EC), Belt and Road Initiative (BR), Broadband China (BC), low-carbon city pilot policy (LCC), and air quality standards (AQS) policy.

Evaluating Population-Level Interventions and Exposures for Suicide Prevention.

Evaluations of interventions targeting the population level are an essential component of the policy development cycle. Pre-post designs are widespread in suicide prevention research but have several significant limitations. To inform future evaluations, our aim is to explore the three most frequently used approaches for assessing the association between population-level interventions or exposures and suicide - the pre-post design, the difference-in-difference design, and Poisson regression approaches. The pre-post design and the difference-in-difference design will only produce unbiased estimates of an association if there are no underlying time trends in the data and there is no additional confounding from other sources. Poisson regression approaches with covariates for time can control for underlying time trends as well as the effects of other confounding factors. Our recommendation is that the default position should be to model the effects of population-level interventions or exposures using regression methods that account for time effects. The other designs should be seen as fall-back positions when insufficient data are available to use methods that control for time effects.

Uneven primary healthcare supply of rural doctors and medical equipment in remote China: community impact and the moderating effect of policy intervention.

BACKGROUND: Unequal access to primary healthcare (PHC) has become a critical issue in global health inequalities, requiring governments to implement policies tailored to communities' needs and abilities. However, the place-based facility dimension of PHCs is oversimplified in current healthcare literature, and formulating the equity-oriented PHC spatial planning remains challenging without understanding the multiple impacts of community socio-spatial dynamics, particularly in remote areas. This study aims to push the boundary of PHC studies one step further by presenting a nuanced and dynamic understanding of the impact of community environments on the uneven primary healthcare supply. METHODS: Focusing on Shuicheng, a remote rural area in southwestern China, multiple data are included in this village-based study, i.e., the facility-level healthcare statistics data (2016-2019), the statistical yearbooks, WorldPop, and Chinese GDP's spatial distribution data. We evaluate villages' PHC service capacity using the number of doctors and essential equipment per capita, which are the major components of China's PHC delivery. The indicators describing community environments are selected based on extant literature and China's planning paradigms, including town- and village-level factors. Gini coefficients and local spatial autocorrelation analysis are used to present the divergences of PHC capacity, and multilevel regression model and (heterogeneous) difference in difference model are used to examine the driving role of community environments and the dynamics under the policy intervention. RESULTS: Despite the general improvement, PHC inequalities remain significant in remote rural areas. The village's location, aging, topography, ethnic autonomy, and economic conditions significantly influence village-level PHC capacity, while demographic characteristics and healthcare delivery at the town level are also important. Although it may improve the hardware setting in village clinics (coef. = 0.350), the recent equity-oriented policy attempts may accelerate the loss of rural doctors (coef. = - 0.517). Notably, the associations between PHC and community environments are affected inconsistently by this round of policy intervention. The town healthcare centers with higher inpatient service capacity (coef. = - 0.514) and more licensed doctors (coef. = - 0.587) and nurses (coef. = - 0.344) may indicate more detrimental policy effects that reduced the number of rural doctors, while the centers with more professional equipment (coef. = 0.504) and nurses (coef. = 0.184) are beneficial for the improvement of hardware setting in clinics. CONCLUSIONS: The findings suggest that the PHC inequalities are increasingly a result of joint social, economic, and institutional forces in recent years, underlining the increased complexity of the PHC resource allocation mechanism. Therefore, we claim the necessity to incorporate a broader understanding of community orientation in PHC delivery, particularly the interdisciplinary knowledge of the spatial lens of community, to support its sustainable development. Our findings also provide timely policy insights for ongoing primary healthcare reform in China.

Impact of Medical-Pharmaceutical Separation Reform on Hospitalization Expenditure in Tertiary Public Hospitals: Difference-in-Difference Analysis Based on Panel Data from Beijing.

Purpose: The medical-pharmaceutical separation (MPS) reform is a healthcare reform that focuses on reducing the proportion of drug expenditure. This study aims to analyze the impact of the MPS reform on hospitalization expenditure and its structure in tertiary public hospitals. Methods: Using propensity score matching and multi-period difference-in-difference methods to analyze the impact of the MPS reform on hospitalization expenditure and its structure, a difference-in-difference-in-difference model was established to analyze the heterogeneity of whether the tertiary public hospital was a diagnosis-related-group (DRG) payment hospital. Of 22 municipal public hospitals offering tertiary care in Beijing, monthly panel data of 18 hospitals from July 2011 to March 2017, totaling 1242 items, were included in this study. Results: After the MPS reform, the average drug expenditure, average Western drug expenditure, and average Chinese drug expenditures per hospitalization decreased by 24.5%, 24.6%, and 24.1%, respectively (P < 0.001). The proportions of drug expenditure decreased by 4.5% (P < 0.001), and the proportion of medical consumables expenditure increased significantly by 2.7% (P < 0.001). Conclusion: The MPS reform may significantly optimize the hospitalization expenditure structure and control irrational increases in expenditure. DRG payment can control the tendency to increase the proportions of medical consumables expenditure after the reform and optimize the effect of the reform. There is a need to strengthen the management of medical consumables in the future, promote the MPS reform and DRG payment linkage, and improve supporting measures to ensure the long-term effect of the reform.

How can open public data promote efficient and equitable green production? Evidence from eco-efficiency in China.

Nowadays, concurrent attention to economic development and ecological issues is becoming an important trend. In this paper, we measure the eco-efficiency of 285 Chinese cities from 2003 to 2019 using a non-radial directional distance function and the data envelopment analysis method, based on which we analyze the club convergence of cities' eco-efficiency using the logt test; we estimate the impact of open public data platforms on eco-efficiency and its convergence using a multi-period difference in difference model and panel-ordered logit model, respectively. We find that, first, open public data platforms improve cities' eco-efficiency by about 6.5%, and the impact mechanisms include scale efficiency, technical efficiency, and total factor productivity, or, at the micro level, increasing the economic agglomeration degree, boosting the amount of foreign investment used, and increasing green innovation level. Second, there are three convergence clubs of eco-efficiency in China's cities, whose average eco-efficiency trends are above, close to, and below average, respectively. Third, public data platforms significantly increase the probability of cities belonging to the convergence clubs of high and medium eco-efficiency (Clubs 1 and 2) and decrease the probability of belonging to the low one (Club 3). However, the mechanisms only include technical efficiency and total factor productivity, or the amount of foreign investment used and the green innovation level at the micro level.

Hidden danger: The long-term effect of ultrafine particles on mortality and its sociodemographic disparities in New York State.

Although previous studies have shown increased health risks of particulate matters, few have evaluated the long-term health impacts of ultrafine particles (UFPs or PM0.1, ≤ 0.1 µm in diameter). This study assessed the association between long-term exposure to UFPs and mortality in New York State (NYS), including total non-accidental and cause-specific mortalities, sociodemographic disparities and seasonal trends. Collecting data from a comprehensive chemical transport model and NYS Vital Records, we used the interquartile range (IQR) and high-level UFPs (≥75 % percentile) as indicators to link with mortalities. Our modified difference-in-difference model controlled for other pollutants, meteorological factors, spatial and temporal confounders. The findings indicate that long-term UFPs exposure significantly increases the risk of non-accidental mortality (RR=1.10, 95 % CI: 1.05, 1.17), cardiovascular mortality (RR=1.11, 95 % CI: 1.05, 1.18) particularly for cerebrovascular (RR=1.21, 95 % CI: 1.10, 1.35) and pulmonary heart diseases (RR=1.33, 95 % CI: 1.13, 1.57), and respiratory mortality (borderline significance, RR=1.09, 95 % CI: 1.00, 1.18). Hispanics (RR=1.13, 95 % CI: 1.00, 1.29) and non-Hispanic Blacks (RR=1.40, 95 % CI: 1.16, 1.68) experienced significantly higher mortality risk after exposure to UFPs, compared to non-Hispanic Whites. Children under five, older adults, non-NYC residents, and winter seasons are more susceptible to UFPs' effects.

Transportation infrastructure upgrading and green development efficiency: Empirical analysis with double machine learning method.

In order to deal with the environmental problems such as pollution emissions and climate change, sustainable development in the field of transportation has gradually become a hot topic to all sectors of society. In addition, promoting the green and low-carbon transformation of China's transportation is also an important issue in the new era. Thus, it is particularly important to correctly identify the green effect of high-speed rail. However, the traditional causal reasoning model faces several challenges such as 'dimensional curse' and multicollinearity. Based on the panel data of 283 prefecture-level cities in China from 2003 to 2019, this study uses the double machine learning model to explore the impact of transportation infrastructure upgrading on the efficiency of urban green development in China. The research shows that the upgrading of transportation infrastructure can effectively improve the efficiency of urban green development by 4%. Service industry agglomeration and green innovation are verified as two mediating channels. Moreover, the synthetic difference in difference model is employed to evaluate the regional impact of high-speed rail, and finds that the regional impact of transportation policies often exceeds the impact of individual cities. We further apply the conclusions of this paper to the research at the micro enterprise level. Goodman-Bacon decomposition and a variety of robustness tests confirm the validity of our conclusions. The study's comprehensive empirical analysis not only validates the positive effects of transportation upgrades on green development, but also offers novel insights into the underlying mechanisms and policy implications of transportation upgrading.

Medicaid expansion and palliative care for advanced-stage liver cancer.

BACKGROUND: Medicaid expansion (ME) has contributed to transforming the United States healthcare system. However, its effect on palliative care of primary liver cancers remains unknown. This study aimed to evaluate the association between ME and the receipt of palliative treatment in advanced-stage liver cancer. METHODS: Patients diagnosed with stage IV hepatocellular carcinoma or intrahepatic cholangiocarcinoma were identified from the National Cancer Database and divided into pre-expansion (2010-2013) and postexpansion (2015-2019) cohorts. Logistic regression identified predictors of palliative treatment. Difference-in-difference (DID) analysis assessed changes in palliative care use between patients living in ME states and patients living in non-ME states. RESULTS: Among 12,516 patients, 4582 (36.6%) were diagnosed before expansion, and 7934 (63.6%) were diagnosed after expansion. Overall, rates of palliative treatment increased after ME (18.1% [pre-expansion] vs 22.3% [postexpansion]; P < .001) and are more pronounced among ME states. Before expansion, only cancer type and education attainment were associated with the receipt of palliative treatment. Conversely, after expansion, race, insurance, location, cancer type, and ME status (odds ratio [OR], 1.23; 95% CI, 1.06-1.44; P = .018) were all associated with palliative care. Interestingly, the odds were higher if treatment involved receipt of pain management (OR, 2.05; 95% CI, 1.23-2.43; P = .006). Adjusted DID analysis confirmed increased rates of palliative treatment among patients living in ME states relative to non-ME states (DID, 4.4%; 95% CI, 1.2-7.7; P = .008); however, racial disparities persist (White, 5.6; 95% CI, 1.4-9.8; P = .009; minority, 2.6; 95% CI, -2.5 to 7.6; P = .333). CONCLUSION: The implementation of ME contributed to increased rates of palliative treatment for patients residing in ME states after expansion. However, racial disparities persist even after ME, resulting in inequitable access to palliative care.

Temporal dynamics of public transportation ridership in Seoul before, during, and after COVID-19 from urban resilience perspective.

We delve into the temporal dynamics of public transportation (PT) ridership in Seoul, South Korea, navigating the periods before, during, and after the COVID-19 pandemic through a spatial difference-in-difference model (SDID). Rooted in urban resilience theory, the study employs micro-level public transportation card data spanning January 2019 to December 2023. Major findings indicate a substantial ridership decline during the severe COVID impact phase, followed by a period in the stable and post-COVID phases. Specifically, compared to the pre-COVID phase, PT ridership experienced a 32.1% decrease in Severe, followed by a reduced magnitude of 21.8% in Stable and 13.5% in post-COVID phase. Interestingly, the observed decrease implies a certain level of adaptability, preventing a complete collapse. Also, contrasting with findings in previous literature, our study reveals a less severe impact, with reductions ranging from 27.0 to 34.9%. Moreover, while the ridership in the post-COVID phase exhibits recovery, the ratio (Post/Pre) staying below 1.0 suggests that the system has not fully returned to its pre-pandemic state. This study contributes to the urban resilience discourse, illustrating how PT system adjusts to COVID, offering insights for transportation planning.

The impact of the free trade zones construction on green technological innovation efficiency --evidence from 288 cities in Chinese.

We measure the green technology innovation efficiency of 288 cities in China from static and dynamic dimensions using the super-SBM model and Malmquist-Luenberger index, and employ "Difference in Difference" (DID) model to evaluate the impact of FTZs construction on green technology innovation efficiency using panel data from 288 prefecture-level cities from 2008 to 2020. The findings show: (1) The FTZs significantly improve green technology innovation efficiency. The decomposition indexes promote the green technology innovation efficiency more from the dynamic productivity dimension (GTFP) functioning on technological advancement. (2) The FTZs can boost the efficiency of green technology innovation through industrial agglomeration, digital economy, and government financial support; (3) The effect of FTZs on the efficiency of green technology innovation differs based on the size and location of the city. Green technology innovation will reach maximum potential when promoting FTZ policy in less developed central, western, and interior regions. This study addresses whether FTZ policies can genuinely support regional green innovation and policy insights to expand opening up and enhance high-quality economic growth.