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Coastal wetlands play a vital role in the migration and transformation of heavy metal pollutants in watersheds. There were 30 surface sediment samples that were analysed to investigate the distribution and ecological risks of heavy metals in the coastal wetlands around the Bohai Sea. Our results showed that the average concentrations of Pb, Cr, Ni, Cu, Zn, and Cd in these wetlands were 17.92 ± 5.81, 50.29 ± 20.50, 31.53 ± 9.71, 25.37 ± 4.29, 80.13 ± 15.11, and 0.92 ± 0.54 mg/kg, respectively. Relative to other wetlands, Pb (25.43 ± 2.68 mg/kg) and Cd (1.67 ± 0.06 mg/kg) contents were higher in the Liaohe Delta wetland (LHDW). Cu (28.44 ± 3.71 mg/kg), Cr (83.11 ± 5.80 mg/kg), and Ni (45.91 ± 3.02 mg/kg) contents were higher in the Yellow River Delta wetland (YRDW). The Zn (120.86 ± 7.41 mg/kg) content was higher in the Qilihai wetland. Heavy metal concentrations in coastal wetland sediments are shown to be positively correlated with organic matter content. Our results showed that the concentration of heavy metals decreases with increasing sediment particle size. In this study, Cd showed the highest pollution index and, therefore, more attention should be paid to the potential ecological risks of Cd in coastal wetlands around the Bohai Sea, especially in the LHDW and YRDW.

Abstract Background Breast cancer is the most common malignant tumor in the world. Intraoperative frozen section of sentinel lymph nodes is an important basis for determining whether axillary lymph node dissection is required for breast cancer surgery. We propose an RRCART model based on a deep-learning network to identify metastases in 2362 frozen sections and count the wrongly identified sections and the associated reasons. The purpose is to summarize the factors that affect the accuracy of the artificial intelligence model and propose corresponding solutions. Methods We took the pathological diagnosis of senior pathologists as the gold standard and identified errors. The pathologists and artificial intelligence engineers jointly read the images and heatmaps to determine the locations of the identified errors on sections, and the pathologists found the reasons (false reasons) for the errors. Through NVivo 12 Plus, qualitative analysis of word frequency analysis and nodal analysis was performed on the error reasons, and the top-down error reason framework of “artificial intelligence RRCART model to identify frozen sections of breast cancer lymph nodes” was constructed based on the importance of false reasons. Results There were 101 incorrectly identified sections in 2362 slides, including 42 false negatives and 59 false positives. Through NVivo 12 Plus software, the error causes were node-coded, and finally, 2 parent nodes (high-frequency error, low-frequency error) and 5 child nodes (section quality, normal lymph node structure, secondary reaction of lymph nodes, micrometastasis, and special growth pattern of tumor) were obtained; among them, the error of highest frequency was that caused by normal lymph node structure, with a total of 45 cases (44.55%), followed by micrometastasis, which occurred in 30 cases (29.70%). Conclusions The causes of identification errors in examination of sentinel lymph node frozen sections by artificial intelligence are, in descending order of influence, normal lymph node structure, micrometastases, section quality, special tumor growth patterns and secondary lymph node reactions. In this study, by constructing an artificial intelligence model to identify the error causes of frozen sections of lymph nodes in breast cancer and by analyzing the model in detail, we found that poor quality of slices was the preproblem of many identification errors, which can lead to other errors, such as unclear recognition of lymph node structure by computer. Therefore, we believe that the process of artificial intelligence pathological diagnosis should be optimized, and the quality control of the pathological sections included in the artificial intelligence reading should be carried out first to exclude the influence of poor section quality on the computer model. For cases of micrometastasis, we suggest that by differentiating slices into high- and low-confidence groups, low-confidence micrometastatic slices can be separated for manual identification. The normal lymph node structure can be improved by adding samples and training the model in a targeted manner.

Abstract Background Air pollution has been identified as related to the diseases of susceptible population, but the spatial heterogeneity of its economic burden and its determinants are rarely investigated. The issue is of great policy significance, especially after the epidemic of COVID-19, when human are facing the joint crisis of health and environment, and some areas is prone to falling into poverty. Methods The geographical detector was adopted to study the spatial distribution characteristics of the incidence of catastrophic health expenditure (ICHE) for older adults in 100 rural areas in China at the prefecture-city level. The health factors, sociological factors, policy factors and environmental factors and their interactions are identified. Results First, most health service factors had strong explanatory power for ICHE whether it interacts with air pollution. Second, 50 single-factor high-risk areas of ICHE were found in the study, but at the same time, there were 21 areas dominated by multiple factors. Conclusion The different contributions and synergy among the factors constitute the complex mechanism of factors and catastrophic health expenditure. Moreover, during this process, air pollution aggravates the contribution of health service factors toward ICHE. In addition, the leading factors of ICHE are different among regions. At the end, this paper also puts forward some policy suggestions from the perspective of health and environment crisis in the post-COVID-19 world: environmental protection policies should be combined with the prevention of infectious diseases; advanced health investment is the most cost-effective policy for the inverse health sequences of air pollution and infectious diseases such as coronavirus disease 2019 (COVID-19); integrating environmental protection policy into healthy development policy, different regions take targeted measures to cope with the intertwined crisis.

Abstract Background China’s medical insurance schemes and poverty alleviation policy at this stage have achieved population-wide coverage and the system's universal function. At the late stage of the elimination of absolute poverty task, how to further exert the poverty alleviation function of the medical insurance schemes has become an important agenda for targeted poverty alleviation. To analyse the risk of catastrophic health expenditure (CHE) occurrence in middle-aged and older adults with vulnerability characteristics from the perspectives of social, regional, disease, health service utilization and medical insurance schemes. Methods We used data from the 2018 China Health and Retirement Longitudinal Study (CHARLS) database and came up with 9190 samples. The method for calculating the CHE was adopted from WHO. Logistic regression was used to determine the different characteristics of middle-aged and older adults with a high probability of incurring CHE. Results The overall regional poverty rate and incidence of CHE were similar in the east, central and west, but with significant differences among provinces. The population insured by the urban and rural integrated medical insurance (URRMI) had the highest incidence of CHE (21.17%) and health expenditure burden (22.77%) among the insured population. Integration of Medicare as a medical insurance scheme with broader benefit coverage did not have a significant effect on the incidence of CHE in middle-aged and older people with vulnerability characteristics. Conclusions Based on the perspective of Medicare improvement, we conducted an in-depth exploration of the synergistic effect of medical insurance and the poverty alleviation system in reducing poverty, and we hope that through comprehensive strategic adjustments and multidimensional system cooperation, we can lift the vulnerable middle-aged and older adults out of poverty.

Abstract Background The high incidence of catastrophic health expenditure (ICHE) among middle-aged and elderly population is a major deterrent for reducing the financial risk of disease. Current research is predominantly based on the assumption of spatial homogeneity of nationwide population characteristics, ignoring the differences in regional characteristics. Thus, our study aimed to explore the impact of various influencing factors on the ICHE from a spatiotemporal perspective. Methods We used data from the China Health and Retirement Longitudinal Study (waves 1 to 4), to conduct a retrospective cohort study across 28 provinces, from 2011 to 2018. We measured regional incidences of catastrophic health expenditure using methods recommended by the World Health Organization. Ordinary least squares (OLS) and geographical and temporal weighted regression (GTWR) were used as the global and local estimation models, respectively. The Fortheringham method was used to test the spatiotemporal non-stationarity. Results National ICHE showed a gradual increase from 2011 to 2015, but suddenly decreased from 2015 to 2018, also showing the spatial heterogeneity. And the southwest area and Hebei showed persistently high ICHE (Qinghai even reached the highest value of 27.5% in 2015). Out-of-pocket payment, gross domestic product, PM2.5, ageing, incidence of non-communicable diseases and disabilities, number of nurses, and health insurance coverage in the global estimation passed the significance test, and the GTWR model showed a better model fit (0.769) than the OLS model (0.388). Furthermore, except for health insurance coverage, all seven variables had spatiotemporal non-stationarity among their impacts on ICHE. Conclusion In this longitudinal study, we found spatiotemporal non-stationarity among the variable relationships, supporting regional governments’ adoption of regional-target policies. First, after the completion of universal health insurance coverage, the spatiotemporal non-stationarity of the prevalence of non-communicable diseases and disability and ageing should be the focus of the next phase of health insurance design, where improvements to compensation coverage and benefit packages are possible policy instruments. Second, the governance and causes of catastrophic health expenditure need to be laid out from a macro perspective rather than only from the individual/household perspective, especially for the potential impact of economic development, air pollution and nursing resources.

Abstract Background As the fifth-largest global mortality risk factor, air pollution has caused nearly one-tenth of the world’s deaths, with a death toll of 5 million. 21% of China’s disease burden was related to environmental pollution, which is 8% higher than the US. Air pollution will increase the demand and utilisation of Chinese residents’ health services, thereby placing a greater economic burden on the government. This study reveals the spatial impact of socioeconomic, health, policy and population factors combined with environmental factors on government health expenditure. Methods Spearman’s correlation coefficient and GeoDetector were used to identify the determinants of government health expenditure. The GeoDetector consist of four detectors: factor detection, interaction detection, risk detection, and ecological detection. One hundred sixty-nine prefecture-level cities in China are studied. The data sources are the 2017 data from China’s Economic and Social Big Data Research Platform and WorldPOP gridded population datasets. Results It is found that industrial sulfur dioxide attributed to government health expenditure, whose q value (explanatory power of X to Y) is 0.5283. The interaction between air pollution factors and other factors will increase the impact on government health expenditure, the interaction value (explanatory power of × 1∩× 2 to Y) of GDP and industrial sulfur dioxide the largest, whose values is 0.9593. There are 96 simple high-risk areas in these 169 areas, but there are still high-risk areas affected by multiple factors. Conclusion First, multiple factors influence the spatial heterogeneity of government health expenditure. Second, health and socio-economic factors are still the dominant factors leading to increased government health expenditure. Third, air pollution does have an important impact on government health expenditure. As a catalytic factor, combining with other factors, it will strengthen their impact on government health expenditure. Finally, an integrated approach should be adopted to synergisticly governance the high-risk areas with multi-risk factors.

Abstract Objective Middle-aged and older adults are more likely to suffer from chronic diseases because of their particular health characteristics, which lead to a high incidence of catastrophic health expenditure (CHE). This study plans to analyse the different factors affecting CHE in middle-aged and older adults with chronic diseases, target the vulnerable characteristics, and suggest groups that medical insurance policies should pay more attention to. Methods The data used in this study came from the 2018 China Health and Retirement Longitudinal Study (CHARLS) database. The method of calculating the CHE was adopted from the World Health Organization (WHO). The logistic regression was used to determine the family characteristics of chronic disease in middle-aged and older adults with a high probability of incurring CHE. Results The incidence of CHE in middle-aged and older adults with chronic disease was highest in sub-poverty level families (26.20%) was lowest in wealthier level families (20.07%). Households with malignant tumours had the highest CHE incidence under any circumstances, especially if the householder had been using inpatient service in the past year. Among the comparison of CHE incidence in different types of medical insurance, the Urban and Rural Residents’ Basic Medical Insurance (URRBMI) was the highest (27.46%). The incidence of CHE was 2.73 times (95% CI 2.30–3.24) and 2.16 times (95% CI 1.81–2.57) higher among people who had used inpatient services in the past year or outpatient services in the past month than those who had not used them. Conclusions Relatively wealthy economic conditions cannot significantly reduce the financial burden of chronic diseases in middle-aged and older adults. For this particular group with multiple vulnerabilities, such as physical and social vulnerability, the high demand and utilization of health services are the main reasons for the high incidence of CHE. After achieving the goal of lowering the threshold of universal access to health services, the medical insurance system in the next stage should focus on multiple vulnerable groups and strengthen the financial protection for middle-aged and older adults with chronic diseases, especially for patients with malignant tumours.

Abstract Background The vulnerability of cardiovascular disease (CVD) patients’ health abilities, combined with the severity of the disease and the overlapping risk factors, leads such people to bear the economic burden of the disease due to the medical services. We estimated the economic burden of CVD and identified the weak link in the design of the medical insurance. Methods Data from 5610 middle-aged and elderly with CVD were drawn from the 2015 wave of “China Health and Retirement Longitudinal Study” (CHARLS). The recommended method of the “World Health Organization” (WHO) was adopted to calculate “catastrophic health expenditure” (CHE), “impoverishment by medical expenses” (IME), and applied the treatment-effect model to analyze the determinants of CHE. Results The incidence of CHE was 19.9% for the elderly families with CVD members, which was 3.6% higher than for uninsured families (16.3%). Families with CVD combined with > 3 other chronic diseases (38.88%) were the riskiest factor for the high CHE in the new rural cooperative medical system (NCMS). Moreover, families with members > 75 years old (33.33%), having two chronic disease (30.74%), and families having disabled members (33.33%), hospitalization members (32.41%) were identified as the high risky determinants for the high CHE in NCMS. Conclusions Elderly with physical vulnerabilities were more prone to CHE. The medical insurance only reduced barriers to accessing health resources for elderly with CVD; however it lacked the policy inclination for high-utilization populations, and had poorly accurate identification of the vulnerable characteristics of CVD, which in turn affects the economic protection ability of the medical insurance. The dispersion between the multiple medical security schemes leads to the existence of blind spots in the economic risk protection of individuals and families.

Abstract Background In light of the health poverty alleviation policy, we explore whether the New Rural Cooperative Medical System (NRCMS) has effectively reduced the economic burden of medical expenses on rural middle-aged and elderly people and other impoverished vulnerable groups. The study aims to provide evidence that can be used to improve the medical insurance system. Methods Data were obtained from the 2015 China Health and Retirement Longitudinal Study (CHARLS). The method of calculating the catastrophic health expenditure (CHE) and impoverishment by medical expense (IME) was adopted from the World Health Organization (WHO). The treatment effect model was used to identify the determinants of CHE for rural middle-aged and elderly people. Results The incidence of CHE in rural China for middle-aged and elderly people is 21.8%, and the IME is 8.0%. The households that had enrolled in the NRCMS suffered higher CHE (21.9%) and IME (8.0%), than those that had not enrolled (CHE: 20.6% and IME: 7.7%). The NRCMS did not provide sufficient economic protection from CHE for households with three or more chronic diseases, inpatients, or households with members aged over 65 years. Key risk factors for the CHE included education levels, households with inpatients, households with members aged over 65 years, and households with disabilities. Conclusions Although the NRCMS has reduced barriers to the usage of household health services by reducing people’s out-of-pocket payments, it has not effectively reduced the risk of these households falling into poverty. Our research identifies the characteristics of vulnerable groups that the NRCMS does not provide enough support for, and which puts them at a greater risk of falling into poverty due to health impoverishment.

Abstract Background We examined the physiological, household, and spatial agglomeration characteristics of the health poverty population in China. We identified weak links that affect the implementation of the medical insurance and further improve its effectiveness for health poverty alleviation. Methods A national representative sample from the China Health and Retirement Longitudinal Study (CHARLS) was analyzed. The WHO recommended method was adopted to calculate catastrophic health expenditure (CHE) and impoverishment by medical expenses (IME). We created a binary indicator for IME as the outcome variable and applied the treatment-effect model to analyze the determinants of IME. Results The incidence of IME was 7.2% of the overall population, compared to 20.3% of the sample households trapped in CHE. The incidence of IME enrolled in insurance schemes was 7.4% higher than that of uninsured families (4.8%). Economic level, living area, family size, age of household head, having hospitalized members, and participating in insurance were statistically significant for the occurrence of IME. Conclusions The original poverty-promoting policies has not reached the maximum point of convergence with China’s current demand for health. The overlapped health vulnerabilities exacerbated the risk of poverty among the elderly and households with high health needs and utilization. In addition, the medical insurance schemes have proven to be insufficient for protection against economic burden of poor households. So, special health needs, age, and household capacity to pay should be comprehensively considered while strengthening the connection between the disease insurance scheme with supplementary insurance.

Aims: Non-communicable diseases (NCD) drag the NCD patients' families to the abyss of poverty. Medical insurance due to weak control over medical expenses and low benefits levels, may have actually contributed to a higher burden of out-of-pocket payments. By making a multi-dimensional calculation on catastrophic health expenditure (CHE) in Heilongjiang Province over 10 years, it is significant to find the weak links in the implementation of medical insurance to achieve poverty alleviation.Methods: A logistic regression was undertaken to predict the determinants of catastrophic health expenditure.Results: The average CHE of households dropped from 18.9% in 2003 to 14.9% in 2013. 33.2% of the households with three or more NCD members suffered CHE in 2013, which was 7.2 times higher than the households without it (4.6%). The uninsured households with cardiovascular disease had CHE of 12.0%, which were nearly 10% points lower than insured households (20.4–22.4%). For Medical Insurance for Urban Employees Scheme enrolled households, the increasing number of NCD members raised the risk of impoverishment from 3.4 to 20.0% in 2003, and from 0.3 to 3.1% in 2008. Households with hospital in-patient members were at higher risk of CHE (OR: 3.10–3.56).Conclusions: Healthcare needs and utilization are one of the most significant determinants of CHE. Households with NCD and in-patient members are most vulnerable groups of falling into a poverty trap. The targeting of the NCD groups, the poorest groups, uninsured groups need to be primary considerations in prioritizing services that are contained in medical insurance and poverty alleviation.