Effect modification of greenness on PM2.5 associated all-cause mortality in a multidrug-resistant tuberculosis cohort.

RATIONALE: Evidence for the association between fine particulate matter (PM2.5) and mortality among patients with tuberculosis (TB) is limited. Whether greenness protects air pollution-related mortality among patients with multidrug-resistant tuberculosis (MDR-TB) is completely unknown. METHODS: 2305 patients reported in Zhejiang and Ningxia were followed up from MDR-TB diagnosis until death, loss to follow-up or end of the study (31 December 2019), with an average follow-up of 1724 days per patient. 16-day averages of contemporaneous Normalised Difference Vegetation Index (NDVI) in the 500 m buffer of patient's residence, annual average PM2.5 and estimated oxidant capacity Ox were assigned to patients regarding their geocoded home addresses. Cox proportional hazards regression models were used to estimate HRs per 10 µg/m3 exposure to PM2.5 and all-cause mortality among the cohort and individuals across the three tertiles, adjusting for potential covariates. RESULTS: HRs of 1.702 (95% CI 1.680 to 1.725) and 1.169 (1.162 to 1.175) were observed for PM2.5 associated with mortality for the full cohort and individuals with the greatest tertile of NDVI. Exposures to PM2.5 were stronger in association with mortality for younger patients (HR 2.434 (2.432 to 2.435)), female (2.209 (1.874 to 2.845)), patients in rural (1.780 (1.731 to 1.829)) and from Ningxia (1.221 (1.078 to 1.385)). Cumulative exposures increased the HRs of PM2.5-related mortality, while greater greenness flattened the risk with HRs reduced in 0.188-0.194 on average. CONCLUSIONS: Individuals with MDR-TB could benefit from greenness by having attenuated associations between PM2.5 and mortality. Improving greener space and air quality may contribute to lower the risk of mortality from TB/MDR-TB and other diseases.

Coupling analysis of population aging and economic growth with spatial-temporal variation: a case study in China.

BACKGROUND: China now faces an increasingly aging society which may exert economic pressure in the long run. This study illustrates the spatial pattern and evolution of population aging and economic development in China. The coupling coordination degree of population aging and economic development at the national and provincial levels are calculated and demonstrated, and the spatial patterns and characteristics are investigated. METHODS: This paper presents a coupling analysis of the elderly population rate (EPR) and per capita Gross Regional Product (GRPpc) in China by using the coupling and coordination model. Further, the spatial pattern and evolution of population aging and economic development are investigated based on the standard deviational ellipse. The collected data is at the level of provincial administrative units in mainland China covering the period 2002 to 2020. RESULTS: The results reveal the spatial difference in the coupling and coordination degree between EPR and GRPpc across provinces. The eastern coastal areas are higher than the central and western regions of China. The orientation and directions of EPR are more than GRPpc, indicating that the polarization in population aging is more severe than economic development. Significant positive correlations between coupling coordination degree and sustainable competitiveness are detected. CONCLUSIONS: Policymakers should fully consider regional differences and sustainable development in policy formulation of China. The western and northeastern provinces should be given priority in the regional sustainable development plan. At the same time, the coordination between population aging and economic development also requires to be examined especially.

Gestational PM2.5 exposure may increase the risk of small for gestational age through maternal blood pressure and hemoglobin: A mediation analysis based on a prospective cohort in China, 2014-2018.

BACKGROUND: Maternal gestational PM2.5 exposure was associated with small for gestational age (SGA). Identifying potential mediating factors may help design preventive strategies to reduce this risk. OBJECTIVE: This study aimed to explore the roles of maternal blood pressure and hemoglobin may play in the PM2.5 exposure and SGA relationship among 117,162 births in 16 counties across China during 2014-2018. METHODS: Daily PM2.5 concentration was collected from China National Environmental Monitoring Center. According to maternal residency during pregnancy, the PM2.5 exposure for each trimester and the whole pregnancy was assessed using an inverse-distance weighting approach. Repeated measurements of maternal blood pressure and hemoglobin during pregnancy were collected for each woman. We estimated the total effect of gestational PM2.5 exposure on SGA, and further tested the mediation effects of maternal blood pressure and hemoglobin concentration during pregnancy. RESULTS: Of 117,162 included mother-infant pairs, 11,361 (9.7 %) were SGA. The odds ratios of SGA associated with PM2.5 exposure (per 10 µg/m3 increase) in the second trimester and the whole pregnancy were 1.023 (95 % CI: 1.009, 1.037) and 1.024 (1.001, 1.048), respectively. We identified the independent mediating effect of blood pressure and hemoglobin in the second and third trimesters, with the proportion of mediation ranging from 1.64 % to 5.78 % and 2.40 % to 8.70 %, respectively. When considering the mediators jointly, we found a stronger mediating effect with a proportion of mediation ranging from 3.93 % to 13.69 %. DISCUSSION: Increases in maternal blood pressure and hemoglobin in the second and third trimesters can independently and jointly mediate the effects of gestational PM2.5 exposure on SGA. Monitoring and managing maternal blood pressure and hemoglobin during prenatal care may constitute a promising avenue to reducing SGA risk associated with gestational PM2.5 exposure.

Effect of different resumption strategies to flatten the potential COVID-19 outbreaks amid society reopens: a modeling study in China.

BACKGROUND: The effect of the COVID-19 outbreak has led policymakers around the world to attempt transmission control. However, lockdown and shutdown interventions have caused new social problems and designating policy resumption for infection control when reopening society remains a crucial issue. We investigated the effects of different resumption strategies on COVID-19 transmission using a modeling study setting. METHODS: We employed a susceptible-exposed-infectious-removed model to simulate COVID-19 outbreaks under five reopening strategies based on China's business resumption progress. The effect of each strategy was evaluated using the peak values of the epidemic curves vis-à-vis confirmed active cases and cumulative cases. Two-sample t-test was performed in order to affirm that the pick values in different scenarios are different. RESULTS: We found that a hierarchy-based reopen strategy performed best when current epidemic prevention measures were maintained save for lockdown, reducing the peak number of active cases and cumulative cases by 50 and 44%, respectively. However, the modeled effect of each strategy decreased when the current intervention was lifted somewhat. Additional attention should be given to regions with significant numbers of migrants, as the potential risk of COVID-19 outbreaks amid society reopening is intrinsically high. CONCLUSIONS: Business resumption strategies have the potential to eliminate COVID-19 outbreaks amid society reopening without special control measures. The proposed resumption strategies focused mainly on decreasing the number of imported exposure cases, guaranteeing medical support for epidemic control, or decreasing active cases.

Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis.

BACKGROUND: As one of its Millennium Development Goals (MDGs), China has achieved a dramatic reduction in the maternal mortality ratio (MMR), although a distinct spatial heterogeneity still persists. Evidence of the quantitative effects of determinants on MMR in China is limited. A better understanding of the spatiotemporal heterogeneity and quantifying determinants of the MMR would support evidence-based policymaking to sustainably reduce the MMR in China and other developing areas worldwide. METHODS AND FINDINGS: We used data on MMR collected by the National Maternal and Child Health Surveillance System (NMCHSS) at the county level in China from 2010 to 2013. We employed a Bayesian space-time model to investigate the spatiotemporal trends in the MMR from 2010 to 2013. We used Bayesian multivariable regression and GeoDetector models to address 3 main ecological determinants of the MMR, including per capita income (PCI), the proportion of pregnant women who delivered in hospitals (PPWDH), and the proportion of pregnant women who had at least 5 check-ups (PPWFC). Among the 2,205 counties, there were 925 (42.0%) hotspot counties, located mostly in China's western and southwestern regions, with a higher MMR, and 764 (34.6%) coldspot counties with a lower MMR than the national level. China's westernmost regions, including Tibet and western Xinjiang, experienced a weak downward trend over the study period. Nationwide, medical intervention was the major determinant of the change in MMR. The MMR decreased by 1.787 (95% confidence interval [CI]: 1.424-2.142, p < 0.001) per 100,000 live births when PPWDH increased by 1% and decreased by 0.623 (95% CI 0.436-0.798, p < 0.001) per 100,000 live births when PPWFC increased by 1%. The major determinants for the MMR in China's western and southwestern regions were PCI and PPWFC, while that in China's eastern and southern coastlands was PCI. The MMR in western and southwestern regions decreased nonsignificantly by 1.111 (95% CI -1.485-3.655, p = 0.20) per 100,000 live births when PCI in these regions increased by 1,000 Chinese Yuan and decreased by 1.686 (95% CI 1.275-2.090, p < 0.001) when PPWFC increased by 1%. Additionally, the western and southwestern regions showed the strongest interactive effects between different factors, in which the corresponding explanatory power of any 2 interacting factors reached up to greater than 80.0% (p < 0.001) for the MMR. Limitations of this study include a relatively short study period and lack of full coverage of eastern coastlands with especially low MMR. CONCLUSIONS: Although China has accomplished a 75% reduction in the MMR, spatial heterogeneity still exists. In this study, we have identified 925 (hotspot) high-risk counties, mostly located in western and southwestern regions, and among which 332 counties are experiencing a slower pace of decrease than the national downward trend. Nationally, medical intervention is the major determinant. The major determinants for the MMR in western and southwestern regions, which are developing areas, are PCI and PPWFC, while that in China's developed areas is PCI. The interactive influence of any two of the three factors, PCI, PPWDH, and PPWFC, in western and southwestern regions was up to and in excess of 80% (p < 0.001).

Climate factors and the East Asian summer monsoon may drive large outbreaks of dengue in China.

OBJECTIVE: To investigate the relationship between climate variables, East Asian summer monsoon (EASM) and large outbreaks of dengue in China. METHODS: We constructed ecological niche models (ENMs) to analyse the influence of climate factors on dengue occurrence and predict dengue outbreak areas in China. Furthermore, we formulated a generalised additive model (GAM) to quantify the impact of the EASM on dengue occurrence in mainland China from 1980 to 2016. RESULTS: Mean Temperature of Coldest Quarter had a 62.6% contribution to dengue outbreaks. Southern China including Guangdong, Guangxi, Fujian and Yunnan provinces are more vulnerable to dengue emergence and resurgence. In addition, we found population density had a 68.7% contribution to dengue widely distribution in China using ENMs. Statistical analysis indicated a dome-shaped association between EASM and dengue outbreak using GAM, with the greatest impact in the South-East of China. Besides, there was a positive nonlinear association between monthly average temperature and dengue occurrence. CONCLUSION: We demonstrated the influence of climate factors and East Asian summer monsoon on dengue outbreaks, providing a framework for future studies on the association between climate change and vector-borne diseases.

Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050.

BACKGROUND: Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well constructed in previous research. This study aims to estimate these nonlinear relationships and predict future malaria scenarios in northern China. METHODS: Nonlinear relationships between malaria incidence and predictor variables were constructed using a genetic programming (GP) method, to predict the spatial distributions of malaria under climate change scenarios. For this, the examples of monthly average malaria incidence were used in each county of northern China from 2004 to 2010. Among the five variables at county level, precipitation rate and temperature are used for projections, while elevation, water density index, and gross domestic product are held at their present-day values. RESULTS: Average malaria incidence was 0.107 ‰ per annum in northern China, with incidence characteristics in significant spatial clustering. A GP-based model fit the relationships with average relative error (ARE) = 8.127 % for training data (R(2) = 0.825) and 17.102 % for test data (R(2) = 0.532). The fitness of GP results are significantly improved compared with those by generalized additive models (GAM) and linear regressions. With the future precipitation rate and temperature conditions in Special Report on Emission Scenarios (SRES) family B1, A1B and A2 scenarios, spatial distributions and changes in malaria incidences in 2020, 2030, 2040 and 2050 were predicted and mapped. CONCLUSIONS: The GP method increases the precision of predicting the spatial distribution of malaria incidence. With the assumption of varied precipitation rate and temperature, and other variables controlled, the relationships between incidence and the varied variables appear sophisticated nonlinearity and spatially differentiation. Using the future fluctuated precipitation and the increased temperature, median malaria incidence in 2020, 2030, 2040 and 2050 would significantly increase that it might increase 19 to 29 % in 2020, but currently China is in the malaria elimination phase, indicating that the effective strategies and actions had been taken. While the mean incidences will not increase even reduce due to the incidence reduction in high-risk regions but the simultaneous expansion of the high-risk areas.

Niche modeling predictions of the potential distribution of Marmota himalayana, the host animal of plague in Yushu County of Qinghai.

BACKGROUND: After the earthquake on 14, April 2010 at Yushu in China, a plague epidemic hosted by Himalayan marmot (Marmota himalayana) became a major public health concern during the reconstruction period. A rapid assessment of the distribution of Himalayan marmot in the area was urgent. The aims of this study were to analyze the relationship between environmental factors and the distribution of burrow systems of the marmot and to predict the distribution of marmots. METHODS: Two types of marmot burrows (hibernation and temporary) in Yushu County were investigated from June to September in 2011. The location of every burrow was recorded with a global positioning system receiver. An ecological niche model was used to determine the relationship between the burrow occurrence data and environmental variables, such as land surface temperature (LST) in winter and summer, normalized difference vegetation index (NDVI) in winter and summer, elevation, and soil type. The predictive accuracies of the models were assessed by the area under the curve of the receiving operator curve. RESULTS: The models for hibernation and temporary burrows both performed well. The contribution orders of the variables were LST in winter and soil type, NDVI in winter and elevation for the hibernation burrow model, and LST in summer, NDVI in summer, soil type and elevation in the temporary burrow model. There were non-linear relationships between the probability of burrow presence and LST, NDVI and elevation. LST of 14 and 23 °C, NDVI of 0.22 and 0.60, and 4100 m were inflection points. A substantially higher probability of burrow presence was observed in swamp soil and dark felty soil than in other soil types. The potential area for hibernation burrows was 5696 km(2) (37.7% of Yushu County), and the area for temporary burrows was 7711 km(2) (51.0% of Yushu County). CONCLUSIONS: The results suggested that marmots preferred warm areas with relatively low altitudes and good vegetation conditions in Yushu County. Based on these results, the present research is useful in understanding the niche selection and distribution pattern of marmots in this region.

Spatial patterns of the congenital heart disease prevalence among 0- to 14-year-old children in Sichuan Basin, P. R China, from 2004 to 2009.

BACKGROUND: Congenital heart disease (CHD) is the most common type of major birth defects in Sichuan, the most populous province in China. The detailed etiology of CHD is unknown but some environmental factors are suspected as the cause of this disease. However, the geographical variations in CHD prevalence would be highly valuable in providing a clue on the role of the environment in CHD etiology. Here, we investigate the spatial patterns and geographic differences in CHD prevalence among 0- to 14-year-old children, discuss the possible environmental risk factors that might be associated with CHD prevalence in Sichuan Basin from 2004 to 2009. METHODS: The hierarchical Bayesian model was used to estimate CHD prevalence at the township level. Spatial autocorrelation statistics were performed, and a hot-spot analysis with different distance thresholds was used to identify the spatial pattern of CHD prevalence. Distribution and clustering maps were drawn using geographic information system tools. RESULTS: CHD prevalence was significantly clustered in Sichuan Basin in different spatial scale. Typical hot/cold clusters were identified, and possible CHD causes were discussed. The association between selected hypothetical environmental factors of maternal exposure and CHD prevalence was evaluated. CONCLUSIONS: The largest hot-spot clustering phenomena and the CHD prevalence clustering trend among 0- to 14-year-old children in the study area showed a plausibly close similarity with those observed in the Tuojiang River Basin. The high ecological risk of heavy metal(Cd, As, and Pb)sediments in the middle and lower streams of the Tuojiang River watershed and ammonia-nitrogen pollution may have contribution to the high prevalence of CHD in this area.

Spatiotemporal trends in neonatal, infant, and child mortality (1990-2019) based on Bayesian spatiotemporal modeling.

Background: Neonatal mortality rate (NMR), infant mortality rate (IMR), and child mortality rate (CMR) show a huge difference across countries, which has been posing challenges for public health policies and medical resource allocation. Methods: Bayesian spatiotemporal model is applied to assess the detailed spatiotemporal evolution of NMR, IMR, and CMR from a global perspective. Panel data from 185 countries from 1990 to 2019 are collected. Results: The continuously decreasing trend of NMR, IMR, and CMR indicated a great improvement in neonatal, infant, and child mortality worldwide. Further, huge differences in the NMR, IMR, and CMR still exist across countries. In addition, the gap of NMR, IMR, and CMR across the countries presented a widening trend from the perspective of dispersion degree and kernel densities. The spatiotemporal heterogeneities demonstrated that the decline degree among these three indicators could be observed as CMR > IMR > NMR. Countries such as Brazil, Sweden, Libya, Myanmar, Thailand, Uzbekistan, Greece, and Zimbabwe showed the highest values of b1i , indicating a weaker downward trend compared to the overall downward trend in the world. Conclusions: This study revealed the spatiotemporal patterns and trends in the levels and improvement of NMR, IMR, and CMR across countries. Further, NMR, IMR, and CMR show a continuously decreasing trend, but the differences in improvement degree present a widening trend across countries. This study provides further implications for policy in newborns, infants, and children's health to reduce health inequality worldwide.

Knowledge mapping and research trends of the social determinants of health (SDoH): a scientometric analysis.

Social determinants of health (SDoH) play an essential role in the risk of developing diseases or medical disorders. Conducting a comprehensive retrospective analysis is necessary to better understand the development status, research hotspots, and development trends of SDoH research. The bibliometric analysis method is applied based on CiteSpace and VOS viewer to quantitatively analyze and visually review the articles published in the field of SDoH from Web of Science core databases from 2000 to 2021. We quantitatively analyzed the author, institution, and other basic information to probe the development of SDoH and then visually investigated the high-frequency keywords, burst keywords, and keyword clusters to understand better the evolution of hotspots and development directions of SDoH during the study period. Health inequality is the main keyword of the SDoH field, and disease burden is expected to maintain a hotspot in recent years. Further, research methodologies could be improved to explain how upstream SDoH influences human lived experience. Additionally, the SDoH field needs to utilize the horizons of the multidisciplinary approach to consider and discuss sustainable development issues to offer implications for health improvement policy and interventions.

Associations Between Gender Gaps in Life Expectancy, Air Pollution, and Urbanization: A Global Assessment With Bayesian Spatiotemporal Modeling.

Objectives: It's evident that women have a longer life expectancy than men. This study investigates the spatiotemporal trends of gender gaps in life expectancy (GGLE). It demonstrates the spatiotemporal difference of the influence factors of population-weighted air pollution (pwPM2.5) and urbanization on GGLE. Methods: Panel data on GGLE and influencing factors from 134 countries from 1960 to 2018 are collected. The Bayesian spatiotemporal model is performed. Results: The results show an obvious spatial heterogeneity worldwide with a continuously increasing trend of GGLE. Bayesian spatiotemporal regression reveals a significant positive relationship between pwPM2.5, urbanization, and GGLE with the spatial random effects. Further, the regression coefficients present obvious geographic disparities across space worldwide. Conclusion: In sum, social-economic development and air quality improvement should be considered comprehensively in global policy to make a fair chance for both genders to maximize their health gains.

Effects of gestational ambient extreme temperature exposures on the risk of preterm birth in China: A sibling-matched study based on a multi-center prospective cohort.

BACKGROUND: Previous epidemiological findings on extreme temperature and preterm birth (PTB) were heterogeneous, especially for extreme cold exposure. Measured and unmeasured individual-level factors such as genetic factors or lifecourse exposures may constitute important contributors but have not been addressed. OBJECTIVES: We aimed to examine the association of gestational heat and cold exposure with PTB using a novel sibling-matched study. METHODS: Based on a multi-center population-based birth cohort across 16 counties in China, we included 10,826 sibling pairs born from March 2013 to December 2018. Conditional logistic and Cox Proportional Hazard regression models were used to estimate the effects of heat and cold exposure on PTB in each trimester, one and four weeks before delivery and the entire pregnancy. We also tested the heterogeneity in the association of temperature with PTB between siblings. FINDINGS: Exposure to heat during the third trimester and the entire pregnancy increased the risk of PTB. For heat (> 90th) defined with mean temperature, the odds ratios were 2.32 (1.63, 3.30) and 3.19 (2.22, 4.58), respectively. Cold exposure (< 10th) during the first, the third, and the entire pregnancy was associated with a higher PTB risk, with ORs (95%CIs) of 2.04 (1.43, 2.90), 3.13 (2.14, 4.58), and 4.26 (2.94, 6.19), respectively. We found slightly stronger associations of heat exposure during the entire pregnancy with the firstborn PTB, and stronger associations of cold exposure during one week and four weeks before delivery with secondborn PTB. CONCLUSIONS: Using a sibling-matched study, we took into account some mother-level unobserved confounding. Our research strengthens the evidence that gestational exposure to heat and cold increases the risk of PTB. Our findings may have important implications for improving the health of newborns in the context of climate change.

Effects of public-health measures for zeroing out different SARS-CoV-2 variants.

Targeted public health interventions for an emerging epidemic are essential for preventing pandemics. During 2020-2022, China invested significant efforts in strict zero-COVID measures to contain outbreaks of varying scales caused by different SARS-CoV-2 variants. Based on a multi-year empirical dataset containing 131 outbreaks observed in China from April 2020 to May 2022 and simulated scenarios, we ranked the relative intervention effectiveness by their reduction in instantaneous reproduction number. We found that, overall, social distancing measures (38% reduction, 95% prediction interval 31-45%), face masks (30%, 17-42%) and close contact tracing (28%, 24-31%) were most effective. Contact tracing was crucial in containing outbreaks during the initial phases, while social distancing measures became increasingly prominent as the spread persisted. In addition, infections with higher transmissibility and a shorter latent period posed more challenges for these measures. Our findings provide quantitative evidence on the effects of public-health measures for zeroing out emerging contagions in different contexts.

Temperature-related mortality in China from specific injury.

Injury poses heavy burden on public health, accounting for nearly 8% of all deaths globally, but little evidence on the role of climate change on injury exists. We collect data during 2013-2019 in six provinces of China to examine the effects of temperature on injury mortality, and to project future mortality burden attributable to temperature change driven by climate change based on the assumption of constant injury mortality and population scenario. The results show that a 0.50% (95% confident interval (CI): 0.13%-0.88%) increase of injury mortality risk for each 1 °C rise in daily temperature, with higher risk for intentional injury (1.13%, 0.55%-1.71%) than that for unintentional injury (0.40%, 0.04%-0.77%). Compared to the 2010s, total injury deaths attributable to temperature change in China would increase 156,586 (37,654-272,316) in the 2090 s under representative concentration pathways 8.5 scenario with the highest for transport injury (64,764, 8,517-115,743). Populations living in Western China, people aged 15-69 years, and male may suffer more injury mortality burden from increased temperature caused by climate change. Our findings may be informative for public health policy development to effectively adapt to climate change.

Spatiotemporal characteristics and drivers of Chinese urban total noise pollution from 2007 to 2019.

Noise pollution as a result of urbanization and socioeconomic development threatens human health and has become a major environmental problem worldwide, particularly for urban residents. Based on observed equivalent noise data of 113 major Chinese cities, a Bayesian spatiotemporal hierarchy model (BSTHM) was employed to investigate the spatiotemporal characteristics of urban noise pollution in China from 2007 to 2019. Meanwhile, the BART model was adopted to explore the drivers of urban noise pollution. The mean and medium of the equivalent noise of the 113 major cities decreased from 2007 to 2011 but increased from 2011 to 2019; the corresponding annual growth is 0.0793 dB and 0.0947 dB per year. The overall spatial pattern has a certain geographical feature. The cities located in the eastern and north-eastern coastal regions generally have a higher level of noise pollution, and the western and southwestern cities have a lower level. One hundred cities not only have greater noise pollution but also an increasing trend. Although the 52 cities located in Western China have less noise pollution, they have increasing local trends. The results indicate that economic and social factors are the main drivers of noise pollution of China; the explanatory power is 46.2%. Traffic factors are also relatively important drivers, of which bus ridership is the leading one. In terms of the natural environment, climatic factors, including temperature and relative humidity, and presence of green areas containing parkland and general green land are the main determinants.

Spatiotemporal trends in life expectancy and impacts of economic growth and air pollution in 134 countries: A Bayesian modeling study.

Life expectancy (LE) varies across countries in space and time, and economic growth and air pollution are two important influence factors to LE. This study mainly aims to investigate spatiotemporal trends in LE in 134 countries from 1960 to 2016 by using Bayesian spatiotemporal modeling. Further, the relations between per capita gross domestic product (GDPpc) and population-weighted fine particulate matter (pwPM2.5) and LE are investigated from a global perspective from 1998 to 2016 by using the Bayesian regression model. The results illustrated the heterogeneity of spatiotemporal trends in LE globally. Specifically, Africa and South-East Asia show much lower LE levels, and the Americas, European, and Western Pacific exhibit a relatively higher LE level compared to the overall level. The countries with low overall levels of LE show a relatively stronger upward trend than the overall upward trend and vice versa. In addition, this study demonstrates that the spatial differences in effects of influence factors on LE in the six WHO regions in the 134 countries. Africa shows the highest positive regression coefficient of GDPpc and lowest negative regression coefficient of pwPM2.5 on LE than other regions in the world. Furthermore, it shows the complexity of the interaction between economic growth and air pollution on LE across six WHO regions. Our findings suggest the public policies to reduce the health damage caused by air pollution, especially in Africa, Eastern Mediterranean, and Europe where the pwPM2.5 negatively affect the LE benefits from economic growth.

Effects of extreme temperature on the risk of preterm birth in China: A population-based multi-center cohort study.

Background: Extreme temperatures are associated with the risk of preterm birth (PTB), but evidence on the effects of different clinical subtypes and across different regions is limited. We aimed to evaluate the effects of maternal exposure to extreme temperature on PTB and its clinical subtypes in China, and to identify effect modification of regional factors in dimensions of population, economy, medical resources and environmental factors. Methods: This was a prospective population-based cohort of 210,798 singleton live births from 16 counties in eight provinces across China during 2014-2018. We used an extended Cox regression with time-varying variables to evaluate the effects of extreme heat and cold on PTB and its subtypes in the entire pregnancy, each trimester, the last gestational month and week. Meta-analysis and meta-regression were conducted to estimate the pooled effects of each city and effect modification by regional characteristics. Findings: Exposure to heat and cold during the entire pregnancy significantly increased the risk of PTB. The effects varied with subtypes, for medically indicated and spontaneous PTB, hazard ratios were 1·84 (95% CI: 1·29, 2·61) and 1·50 (95% CI: 1·11, 2·02) for heat, 2·18 (95% CI: 1·83, 2·60) and 2·15 (95% CI: 1·92, 2·41) for cold. The associations were stronger for PTB less than 35 weeks than those during weeks 35-36. The effects varied across locations, and GDP per capita (ß=-0·16) and hospital beds per 1000 persons (ß=-0·25) were protective factors for the effects. Interpretation: Extreme temperature can increase the risk of medically indicated and spontaneous PTB, and higher regional socio-economic status may moderate such effects. In the context of climate change, such findings may have important implications for protecting the health of vulnerable groups, especially newborns. Funding: National Key R&D Program of China (2018YFA0606200), National Natural Science Foundation of China (42175183), Strategic Priority Research Program of the Chinese Academy of Sciences (XDA20030302), National Natural Science Foundation of China (42071377).

Climate and socio-economic factors drive the spatio-temporal dynamics of HFRS in Northeastern China.

Background: Hemorrhagic fever with renal syndrome (HFRS) occurs widely in Northeastern China, but the mechanism and interactions of meteorological and socio-economic factors on the transmission of HFRS are still largely unknown. Objective: We explored the effects of socioeconomic-environmental factors on the spatio-temporal variation of HFRS incidence from 2001 to 2019 in Northeastern China. Specifically, the relative importance and contribution rates (CR) of determinants of HFRS were identified by boosted regression tree and variance partitioning analysis, respectively. Structural equation models (SEMs) were used to explain the roles of climatic and socio-economic factors in the transmission of HFRS. And a negative binomial regression was used to identify the risk effect between monthly meteorological variables and HFRS with 0-6 months lags in Northeastern China. Results: Over the past decades, the high-risk areas of HFRS were mainly concentrated in the northern and eastern areas of Northeastern China. Additionally, HFRS mainly presented a decreasing trend from 2001 to 2019 in most areas of Northeastern China, but slightly increased in the cities of Daqing, Songyuan, Baicheng, and Tonghua. The temporal dynamics of the incidence of HFRS were primarily explained by the variations in population density (CR = 27.30%), climate (CR = 13.30%), and economic condition(CR = 1.90%). The spatial variations of HFRS were medicated by the climate (CR = 16.95%) and population density (CR = 9.45%) and medical health care (CR = 2.25%). The SEM models indicated that humid and warm climates were conducive to the incidence and increase of HFRS, but the improvement in education and an increase in population density reduced the transmission of HFRS. Conclusion: Climate and population density appeared to mediate the spatio-temporal variation of HFRS in Northeastern China. These findings may provide valuable empirical evidence for the management of HFRS in endemic areas.

Future injury mortality burden attributable to compound hot extremes will significantly increase in China.

BACKGROUND: As climate change, compound hot extremes (CHEs), daytime and nighttime persistent hot extremes, are projected to become much more frequent and intense, which may pose a serious threat to human health. However, evidence on the impact of CHEs on injury is rare. METHODS: We collected injury death data and daily meteorological data from six Chinese provinces during 2013-2018. A time-stratified case-crossover design with two-stage analytic approach was applied to assess the associations of CHEs with injury mortality by intention, mechanism, age and gender. Using the projected daily temperatures of five General Circulation Models (GCMs), we projected the frequency of CHEs and CHEs-attributable mortality burden of injury under three Representative Concentration Pathway (RCP) scenarios. RESULTS: CHEs were significantly associated with increased injury mortality risk (RR = 1.14, 95%CI: 1.09-1.19), with strong effects on unintentional injuries (RR = 1.16, 95%CI:1.11,1.22) and intentional injuries (RR = 1.11, 95%CI:0.99,1.25). Female (RR = 1.21,95%CI: 1.13-1.29) and the elderly (RR = 1.30, 95%CI: 1.22-1.39) were more susceptible to CHEs. Both the frequency and injury mortality burden of CHEs showed a steep rising trend under RCP8.5 scenario, with a 7.37-fold and 8.22-fold increase respectively, by the end of the century, especially in southern, eastern, central and northwestern China. CONCLUSION: CHEs were associated with increased injury mortality risk, and the CHEs-attributable injury mortality burden was projected to aggravate substantially in the future as global warming. It is urgent to develop targeted adaptation policies to alleviate the health burden of CHEs.