Epidemic transition of environmental health risk during China's urbanization

Study on the purification mechanism for ammonia nitrogen in micro-polluted rivers by herbaceous plant - Rumex japonicus Houtt

Water eutrophication caused by nitrogen pollution is an urgent global issue that requires attention. The Qingyi River is a typical micro-polluted river in China. In this study, we took this river as the research object to investigate the nitrogen pollution purification capacity of a herbaceous plant, Rumex japonicus Houtt. (RJH). Compared to nitrate nitrogen (NO3--N) and nitrite nitrogen (NO2--N), RJH showed better purification performance on total nitrogen (TN), total phosphorus (TP) and ammonia nitrogen (NH4+-N), with a highest removal rate of 37.22%, 52.13%, and 100%, respectively. RJH could completely remove ammonia nitrogen and exhibit excellent resistance to pollutant interference when the initial concentration of ammonia nitrogen in the cultivation devices increased from 1 mg/L to 10 mg/L or in the actual river. This indicated the great application potential of RJH in ammonia nitrogen removal from natural micro-polluted rivers. In addition, combined effects of nitrification of roots, absorption of self-growth, stripping, and others contributed to nitrogen removal by RJH. Particularly, the nitrification of roots played a dominant role, accounting for 73.85% ± 8.79%. High-throughput sequencing results indicate that nitrifying bacteria accounted for over 75% of all bacterial species in RJH. Furthermore, RJH showed good growth status and strong adaptability. The correlation coefficients of its relative growth rate with chlorophyll A and the degradation rate of absorption were 0.9677 and 0.9594, respectively. Our research demonstrates that RJH is one of the excellent varieties for ammonia removal. This provides a very promising and sustainable method for purifying micro-polluted rivers.

Impact of climate change on SARS-CoV-2 epidemic in China

The outbreak and prevalence of SARS-CoV-2 have severely affected social security. Physical isolation is an effective control that affects the short-term human-to-human transmission of the epidemic, although weather presents a long-term effect. Understanding the effect of weather on the outbreak allow it to be contained at the earliest possible. China is selected as the study area, and six weather factors that receive the most attention from January 20, 2020 to April 30, 2020 are selected to investigate the correlation between weather and SARS-CoV-2 to provide a theoretical basis for long-term epidemic prevention and control. The results show that (1) the average growth rate (GR) of SARS-CoV-2 in each province is logarithmically distributed with a mean value of 5.15%. The GR of the southeastern region is higher than that of the northwestern region, which is consistent with the Hu Line. (2) The specific humidity, 2-m temperature (T), ultraviolet (UV) radiation, and wind speed (WS) adversely affect the GR. By contrast, the total precipitation (TP) and surface pressure (SP) promote the GR. (3) For every 1 unit increase in UV radiation, the GR decreases by 0.30% in 11 days, and the UV radiation in China is higher than that worldwide (0.92% higher per day). Higher population aggregation and urbanization directly affect the epidemic, and weather is an indirect factor.

Impact of urbanization on morbidity of hepatitis A: a national panel study in China during 2005-2018

BACKGROUND

The effect of urbanization on the morbidity of hepatitis A remains unclear. We aimed to estimate the association between various urbanization-related indices and hepatitis A morbidity in China.

METHODS

Data on the annual morbidity of hepatitis A, urbanization-related measures (i.e., gross domestic product per capita, the number of hospitalization beds per 1000 persons, illiteracy rate, tap water coverage, motor vehicles per 100 persons, population density, and the proportion of arable land), and meteorological factors in 31 provincial-level administrative divisions of Chinese mainland during 2005-2018 were collected from the National Population and Health Science Data Sharing Platform, China Statistical Yearbooks, and the China Meteorological Data Sharing Service System, respectively. Generalized linear mixed models were applied to quantify the impacts of different urbanization-related indices on the morbidity of hepatitis A in China after adjusting for covariates.

RESULTS

A total of 537,466 hepatitis A cases were reported in China during 2005-2018. The annual morbidity had a decline of 79.4% from 5.64 cases to 1.16 cases per 100,000 people. There were obvious spatial variations with higher morbidity in western China. Nationally, gross domestic product per capita and the number of hospitalization beds per 1000 persons increased from 14,040 to 64,644 CNY and from 2.45 to 6.03 during 2005-2018, respectively. The illiteracy rate decreased from 11.0 to 4.9%. Gross domestic product per capita [relative risk (RR) = 0.96, 95% confidence interval (CI): 0.92-0.99], and the number of hospitalization beds per 1000 persons (RR = 0.79, 95% CI: 0.75-0.83) were associated with the declined morbidity of hepatitis A. By contrast, the increased morbidity of hepatitis A was linked to the illiteracy rate (RR = 1.04, 95% CI: 1.02-1.06). Similar influential factors were detected for children and adults, with greater effects witnessed for children.

CONCLUSIONS

People in the western region suffered the heaviest burden of hepatitis A in Chinese mainland. Nationally, there was a sharp decline in the morbidity of hepatitis A. The urbanization process was associated with the reduction of hepatitis A morbidity in China during 2005-2018.

How urbanization affects residents' health risks: evidence from China

Continued urbanization requires a deep understanding of how urbanization affects residents' health risks. This study used regression analysis of Chinese provincial-level panel data from 2004 to 2019 and empirically analyzed the nonlinear effects of urbanization on health risks and regional differences using STIRPAT model. Health risks were assessed by the average number of residents' visits to medical facilities and population mortality. We also examined the moderating effect of income and environmental factors. The results show that (1) urbanization increases the average number of residents' visits and reduces population mortality. The positive effect of urbanization in increasing the average number of visits is reinforced by an increase in income level and environmental pollution, whereas the negative effect of urbanization in reducing population mortality is weakened by environmental pollution. (2) Regarding long-term trends, urbanization has an N-shaped relationship with the average number of residents' visits, and a U-shaped relationship with population mortality; (3) Urbanization has an N-shaped relationship with the average number of residents' visits in the eastern, central, and western regions and an inverted N-shaped relationship with population mortality in the eastern region. Urbanization has significant effects on residents' health risks in areas with high levels of infrastructure. According to the results, suggestions are proposed, such as developing new-type urbanization, improving infrastructure, focusing on green urbanization, and promoting national fitness programs.

Gaps and Directions in Addressing Non-Communicable and Chronic Diseases in China: A Policy Analysis

OBJECTIVE

Non-communicable and chronic diseases (NCDs) have become a public health problem that seriously threatens the population's health, especially in rapidly industrialized countries. Given the complexity of managing NCDs, there is growing evidence that interventions embedding or incorporating health promotion strategies can help reduce the disease burden of NCDs. This review aims to identify and map existing control and prevention policies for NCDs in China and identify gaps or opportunities for policy modifications and development, to transfer evidence-based guidelines into empirical public health intervention practices and research.

DESIGN

A review was conducted to evaluate the policy documents to manage NCDs in China. Keywords "chronic disease", "health", and "policy" were used to search documents published on the Chinese official national websites. Nvivo 12.0 was used to conduct a content analysis of the policy documents.

RESULTS

Fifty-six NCD prevention policies were retrieved from the search, and ten documents that incorporated the health promotion component were analyzed. The Healthy China 2030 Plan and Recommendations on Implementing the Healthy China Action are the core health policies of China's Central Government. These, coupled with three nationwide community-based projects, have provided a foundational transformation platform for health promotion implementation.

CONCLUSION

This review revealed the Chinese Government's determination and commitment toward the prevention and control of NCDs and the promotion public health. Additional efforts and a focus on accelerating policy transformation and strengthening policy evaluation are required to achieve this commitment.

The influence of rainfall and catchment characteristics on runoff generation in urban catchments-a case study in Hebi City of China

An in-depth understanding of the rainfall-runoff process is essential for effective stormwater management. However, the understanding of the hierarchy of rainfall characteristics in terms of their importance in influencing runoff generation is limited. This paper investigates the influence of rainfall characteristics and catchment characteristics on runoff generation in urban catchments. The outcomes showed that there are 4 dominant factors affecting runoff generation: total precipitation TP and maximum 60-min rainfall intensity MAX60 are the two top-ranked factors while average rainfall intensity RI and maximum 5-min rainfall intensity MAX5 are ranked second. Additionally, compared to the moderate rainfall regime (MR), the heavy rainfall regime (HR) tends to produce higher peak flow rates, higher total inflow per unit area, and lower runoff control effect. Note that the antecedent precipitation has a more significant effect on runoff generation and is even the dominant factor when rainstorm events with daily rainfall larger than 50 mm are not considered. The results of analyzing the influence of catchment characteristics suggest that only under HR regime conditions do the catchment characteristics have an impact on runoff generation and behave as smaller catchment areas, and higher proportions of green landscapes always lead lower peak flow rates, lower total inflows per unit area, and higher runoff control effects.

Does China's increasing coupling of 'urban population' and 'urban area' growth indicators reflect a growing social and economic sustainability?

Over the last four decades, China has experienced rapid parallel economic development and urbanization, leading to internal mass -migrations of its people from increasingly marginalized rural areas to urban centers where job opportunities and wealth are now concentrated. We compare the relative temporal growth trends in population-related and land-(i.e., area-) related urbanization systems to evaluate China's urbanization in the context of the 'New-Type' Urbanization Program (2014-2020). Based on coupling coordination models, we observed that the two systems were overall slightly decoupled since spatial urban expansion commonly outgrew urban population growth, but the degree of coordination between the two parameters was increasing. Employing exploratory spatial data analysis, we revealed that a high degree of coupling coordination has spread from Eastern to Western provinces. Urban planning and land policies have contributed to an increasing urban vegetation cover and the control of excessive urban land expansions. While China's urbanization appears to have become increasingly sustainable due to the increasing degree of coupling coordination between its subsystems, ongoing urban expansions require strong oversight to limit the environmental impacts of the country's sprawling mega-cities.

Assessing emission reduction effects from shifts of urban passenger transport modes by implementing targeted emission tax considering the whole fuel cycle

Controlling the emission of urban passenger transport modes has become one of the most important tasks of governing urban air pollution. Most strategies only focused on carbon emission, whereas neglecting the influences of other pollutants (CO, HC, NOx, PM_2.5), especially for upstream emissions from electricity generation caused by the electricity consumed during the operation of electrified transport modes. Based on the multinomial logit model (MNL), this study firstly calculated and evaluated the emission reduction effects brought about by the implementation of targeted emission taxes on different transport modes from the perspective of whole fuel cycle. Taking Jiangning District as an example, our research found that the policy implementing targeted emission tax for different transport modes can not only bring reduce 13.104 tons of CO, 0.327 tons of HC, 0.568 tons of NOx, and 0.140 tons of PM_2.5, but also 26,726.82 (euro) of eco-environmental benefits for the treatment of air pollution. Our study can provide useful insights for shifting the structure of urban passenger transport modes, especially promoting the transfer of private cars to the urban green transport systems, to alleviate urban air pollution by formulating effective emission reduction strategies.

Multi-source sensor based urban habitat and resident health sensing: A case study of Wuhan, China

The COVID-19 pandemic undoubtedly has a great impact on the world economy, especially the urban economy. It is urgent to study the environmental pathogenic factors and transmission route of it. We want to discuss the relationship between the urban living environment and the number of confirmed cases at the community scale, and examine the driving forces of community infection (e.g., environment, ecology, convenience, livability, and population density). Besides, we hope that our research will help make our cities more inclusive, safe, resilient, and sustainable. 650 communities with confirmed COVID-19 cases in Wuhan were selected as the research objects. We utilize deep learning semantic segmentation technology to calculate the Visible Green Index (VGI) and Sky View Factor (SVF) of street view and use Partial Least Squares Structural Equation Modeling (PLS-SEM) to study the driving forces of pandemic situation. Temperature and humidity information recorded by sensors was also used for urban sensing. We find that the more SVF has a certain inhibitory effect on the virus transmission, but contrary to our intuitive perception, higher VGI has a certain promotion effect. Also, the structural equation model constructed in this paper can explain the variance of 28.9% of the number of confirmed cases, and results (path coef.) demonstrate that residential density of community (0.517) is a major influencing factor for pandemic cases, whereas convenience of community living (0.234) strongly influence it. Communities with good suitability of community human settlement (e.g., construction time, price) are safer in the face of pandemic events. Does the influence of SVF and VGI on the results of the pandemic situation mean that sunlight can effectively block the spread of the virus? This spatial heterogeneity in different communities is helpful for us to explore the environmental transmission route of COVID-19.

The Effect of Urbanization on Population Health: Evidence From China

This paper explores the relationship between urbanization rate and death incidence by applying panel threshold regression model to the inland provinces of China. The empirical results highlight that there is a nonlinear single threshold effect between urbanization and population health indicators. In China's inland provinces, the negative impact of urbanization on death rate is reduced when per capita GDP exceeds the threshold, that is, the positive impact of urbanization on population health is significantly weakened. Similarly, this result can also be applied to the north provinces, while there is a no threshold effect in south. These asymmetric effects are strongly related to geographical location, historical background, economic development conditions, and health policies. Therefore, in the urbanization process, while promoting the steady development of population urbanization, the government should also increase health investment to improve the system and mechanism, formulate policies to raise health awareness, protect residents' health and reduce the waste of health resources.

Prediction of the COVID-19 spread in African countries and implications for prevention and control: A case study in South Africa, Egypt, Algeria, Nigeria, Senegal and Kenya

COVID-19 (Corona Virus Disease 2019) is globally spreading and the international cooperation is urgently required in joint prevention and control of the epidemic. Using the Maximum-Hasting (MH) parameter estimation method and the modified Susceptible Exposed Infectious Recovered (SEIR) model, the spread of the epidemic under three intervention scenarios (suppression, mitigation, mildness) is simulated and predicted in South Africa, Egypt, and Algeria, where the epidemic situations are severe. The studies are also conducted in Nigeria, Senegal and Kenya, where the epidemic situations are growing rapidly and the socio-economic are relatively under-developed, resulting in more difficulties in preventing the epidemic. Results indicated that the epidemic can be basically controlled in late April with strict control of scenario one, manifested by the circumstance in the South Africa and Senegal. Under moderate control of scenario two, the number of infected people will increase by 1.43-1.55 times of that in scenario one, the date of the epidemic being controlled will be delayed by about 10 days, and Algeria, Nigeria, and Kenya are in accordance with this situation. In the third scenario of weak control, the epidemic will be controlled by late May, the total number of infected cases will double that in scenario two, and Egypt is in line with this prediction. In the end, a series of epidemic controlling methods are proposed, including patient quarantine, close contact tracing, population movement control, government intervention, city and county epidemic risk level classification, and medical cooperation and the Chinese assistance.

High-resolution urban land-cover mapping and landscape analysis of the 42 major cities in China using ZY-3 satellite images

Detailed and precise urban land-cover maps are crucial for urban-related studies. However, there are limited ways of mapping high-resolution urban land cover over large areas. In this paper, we propose an operational framework to map urban land cover on the basis of Ziyuan-3 satellite images. Based on this framework, we produced the first high-resolution (2 m) urban land-cover map (Hi-ULCM) covering the 42 major cities of China. The overall accuracy of the Hi-ULCM dataset is 88.55%, of which 14 cities have an overall accuracy of over 90%. Most of the producer's accuracies and user's accuracies of the land-cover classes exceed 85%. We further conducted a landscape pattern analysis in the 42 cities based on Hi-ULCM. In terms of the comparison between the 42 cities in China, we found that the difference in the land-cover composition of urban areas is related to the climatic characteristics and urbanization levels, e.g., cities with warm climates generally have higher proportions of green spaces. It is also interesting to find that cities with higher urbanization levels are more habitable, in general. From the landscape viewpoint, the geometric complexity of the landscape increases with the urbanization level. Compared with the existing medium-resolution land-cover/use datasets (at a 30-m resolution), Hi-ULCM represents a significant advance in accurately depicting the detailed land-cover footprint within the urban areas of China, and will be of great use for studies of urban ecosystems.

Spatial Statistics and Influencing Factors of the COVID-19 Epidemic at Both Prefecture and County Levels in Hubei Province, China

The coronavirus disease 2019 (COVID-19) epidemic has had a crucial influence on people's lives and socio-economic development throughout China and across the globe since December 2019. An understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic on multiple scales could benefit the control of the outbreak. Therefore, we used spatial autocorrelation and Spearman's rank correlation methods to investigate these two topics, respectively. The COVID-19 epidemic data reported publicly and relevant open data in Hubei province were analyzed. The results showed that (1) at both prefecture and county levels, the global spatial autocorrelation was extremely significant for the cumulative confirmed COVID-19 cases (CCC) in Hubei province from 30 January to 18 February 2020. Further, (2) at both levels, the significant hotspot and cluster/outlier area was observed solely in Wuhan city and most of its districts/sub-cities from 30 January to 18 February 2020. (3) At the prefecture level in Hubei province, the number of CCC had a positive and extremely significant correlation (p < 0.01) with the registered population (RGP), resident population (RSP), Baidu migration index (BMI), regional gross domestic production (GDP), and total retail sales of consumer goods (TRS), respectively, from 29 January to 18 February 2020 and had a negative and significant correlation (p < 0.05) with minimum elevation (MINE) from 2 February to 18 February 2020, but no association with the land area (LA), population density (PD), maximum elevation (MAXE), mean elevation (MNE), and range of elevation (RAE) from 23 January to 18 February 2020. (4) At the county level, the number of CCC in Hubei province had a positive and extremely significant correlation (p < 0.01) with PD, RGP, RSP, GDP, and TRS, respectively, from 27 January to 18 February 2020, and was negatively associated with MINE, MAXE, MNE, and RAE, respectively, from 26 January to 18 February 2020, and negatively associated with LA from 30 January to 18 February 2020. It suggested that (1) the COVID-19 epidemic at both levels in Hubei province had evident characteristics of significant global spatial autocorrelations and significant centralized high-risk outbreaks, and had an extremely significant association with social and economic factors. (2) The COVID-19 epidemics were significantly associated with the natural factors, such as LA, MAXE, MNE, and RAE, -only at the county level, not at the prefecture level, from 2 February to 18 February 2020. (3) The COVID-19 epidemics were significantly related to the socioeconomic factors, such as RGP, RSP, TRS, and GDP, at both levels from 26 January to 18 February 2020. It is desired that this study enrich our understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic and benefit classified prevention and control of the COVID-19 epidemic for policymakers.

Urban-rural-specific trend in prevalence of general and central obesity, and association with hypertension in Chinese adults, aged 18-65 years

BACKGROUND

China has the largest obese population in the world, and the prevalence of central obesity is increasing dramatically in China. Moreover, the rapid economic growth of China in recent decades has led to rapid urbanization in rural China. However, studies comparing the prevalence trends of different types of obesity and the association of obesity with hypertension between urban and rural areas in China are very scarce, and most studies have focused only on the difference in the prevalence of overweight and general obesity or hypertension among rural and urban populations. Therefore, the focus of this study was to examine the shifts in the overall distribution of the prevalence of different types of obesity and to estimate the risk of hypertension in different types of obesity among urban and rural adults aged 18-65 years.

METHODS

Seven iterations of the China Health and Nutrition Survey (CHNS), conducted in 1993, 1997, 2000, 2004, 2006, 2009 and 2011, were used in this study. A total of 53,636 participants aged 18-65 years were included. Obesity was classified into three types based on body mass index (BMI) and waist circumference (WC). A log-binomial model was constructed to estimate the prevalence ratio (PR) of hypertension with three types of obesity.

RESULTS

The age-standardized prevalence of central obesity only, general obesity only, and both central and general obesity increased from 15.8, 0.2 and 2.9% in 1993 to 30.3, 0.9 and 10.3% in 2011, respectively. The prevalence of central obesity only (urban vs. rural: 20.8% vs. 13.4% in 1993, 29.6% vs. 30.6% in 2011) and both central and general obesity (urban vs. rural: 3.5% vs. 2.5% in 1993, 10.0% vs. 10.6% in 2011) in rural adults exceeded that in urban adults in 2011. Participants with both central and general obesity had the highest risk for incident hypertension compared with those with normal body measurements (adjusted PR, urban: 2.30 (95% CI, 2.01-2.63), rural: 2.50 (95% CI, 2.25-2.77)).

CONCLUSIONS

Both WC and BMI should be considered measures of obesity and targeted in hypertension prevention. More attention should be paid to the incidence of central obesity in adults in rural China.

Spatiotemporal Pattern of Fine Particulate Matter and Impact of Urban Socioeconomic Factors in China

Frequent hazy weather has been one of the most obvious air problems accompanying China's rapid urbanization. As one of the main components of haze pollution, fine particulate matter (PM2.5), which severely affects environmental quality and people's health, has attracted wide attention. This study investigated the PM2.5 distribution, changing trends and impact of urban factors based on remote-sensing PM2.5 concentration data from 2000 to 2015, combining land-use data and socioeconomic data, and using the least-squares method and structural equation model (SEM). The results showed that the high concentration of PM2.5 in China was mainly concentrated in the eastern part of China and Sichuan Province. The trends of the PM2.5 concentration in eastern part and Northeast China, Sichuan, and Guangxi Provinces were positive. Meanwhile, the ratios of increasing trends were strongest in built-up land and agricultural land, and the decreasing trends were strongest in forest and grassland, but the overall trends were still growing. The SEM results indicated that economic factors contributed most to PM2.5 pollution, followed by demographic factors and spatial factors. Among all observed variables, the secondary industrial GDP had the highest impact on PM2.5 pollution. Based on the above results, PM2.5 pollution remains an important environmental issue in China at present and even in the future. It is necessary for decision-makers to make actions and policies from macroscopic and microscopic, long-term and short-term aspects to reduce pollution.