Impacts of ambient temperature on the burden of bacillary dysentery in urban and rural Hefei, China

Using a Leroux-prior-based conditional autoregression-based strategy to map the short-term association between temperature and bacillary dysentery and its attributable burden in China

Background

In China, bacillary dysentery (BD) is the third most frequently reported infectious disease, with the greatest annual incidence rate of 38.03 cases per 10,000 person-years. It is well acknowledged that temperature is associated with BD and the previous studies of temperature-BD association in different provinces of China present a considerable heterogeneity, which may lead to an inaccurate estimation for a region-specific association and incorrect attributable burdens. Meanwhile, the common methods for multi-city studies, such as stratified strategy and meta-analysis, have their own limitations in handling the heterogeneity. Therefore, it is necessary to adopt an appropriate method considering the spatial autocorrelation to accurately characterize the spatial distribution of temperature-BD association and obtain its attributable burden in 31 provinces of China.

Methods

A novel three-stage strategy was adopted. In the first stage, we used the generalized additive model (GAM) model to independently estimate the province-specific association between monthly average temperature (MAT) and BD. In the second stage, the Leroux-prior-based conditional autoregression (LCAR) was used to spatially smooth the association and characterize its spatial distribution. In the third stage, we calculate the attribute BD cases based on a more accurate estimation of association.

Results

The smoothed association curves generally show a higher relative risk with a higher MAT, but some of them have an inverted "V" shape. Meanwhile, the spatial distribution of association indicates that western provinces have a higher relative risk of MAT than eastern provinces with 0.695 and 0.645 on average, respectively. The maximum and minimum total attributable number of cases are 224,257 in Beijing and 88,906 in Hainan, respectively. The average values of each province in the eastern, western, and central areas are approximately 40,991, 42,025, and 26,947, respectively.

Conclusion

Based on the LCAR-based three-stage strategy, we can obtain a more accurate spatial distribution of temperature-BD association and attributable BD cases. Furthermore, the results can help relevant institutions to prevent and control the epidemic of BD efficiently.

Effects of temperature on incidence of bacillary dysentery in a temperate continental arid climate city in northwest China

The effect of ambient temperature on health continues to draw more and more attention with the global warming. Bacillary dysentery (BD) is a major global environmental health issue and affected by temperature and other environmental variables. In the current study, we evaluated the effect of temperature on the incidence of BD from January 1st, 2008 to December 31st, 2011 in Jiayuguan, a temperate continental arid climate city in the Hexi Corridor of northwest China. A distributed lag non-linear model (DLNM) was performed to evaluate the lag effect of temperature on BD up to 30 days. Results showed the risk of BD increased with temperature significantly, especially after 8 °C. The maximum risk of BD was observed at extreme high temperature (29 °C). The effect of temperature on BD risk was significantly divided into short-term effect at lag 5 days and long-term effect at lag 30 days. Age ≤ 15 years were most affected by high temperature. The maximum cumulative risk for lag 30 days (25.8, 95% CIs: 11.8-50.1) was observed at 29 °C. Age ≤ 15 years and females showed short-term effect at lag 5 days and long-term effect at lag 30 days, while age > 15 years and males showed acute short-term effect at lag 0 and light long-term effect at lag 16 days.

Effect and attributable burden of hot extremes on bacillary dysentery in 31 Chinese provincial capital cities

BACKGROUND

High atmospheric temperature has been associated with the occurrence of bacillary dysentery (BD). Recent studies have suggested that hot extremes may influence health outcomes, however, none have examined the association between hot extremes and BD risk, especially at the national level.

OBJECTIVES

To assess the effect and attributable burden of hot extremes on BD cases and to identify populations at high risk of BD.

METHODS

Daily incident BD data of 31 provincial capital cities from 2010 to 2018 were collected from the Chinese Center for Disease Control and Prevention, weather data was obtained from the fifth generation of the European Re-Analysis Dataset. Three types of hot extremes, including hot day, hot night, and hot day and night, were defined according to single or sequential occurrence of daytime hot and nighttime hot within 24 h. A two-stage analytical strategy combined with distributed lag non-linear models (DLNM) was used to evaluate city-specific associations and national pooled estimates.

RESULTS

Hot extremes were significantly associated with the risk of BD on lagged 1-6 days. The overall cumulative relative risk (RR) was 1.136 [95% confidence interval (CI): 1.022, 1.263] for hot day, 1.181 (95% CI: 1.019, 1.369) for hot night, and 1.154 (95% CI: 1.038, 1.283) for hot day and night. Northern residents, females, and children younger than or equal to 14 years old were vulnerable under hot night, southern residents were vulnerable under hot day, and males were vulnerable under hot day and night. 1.854% (95% CI: 1.294%, 2.205%) of BD cases can be attributable to hot extremes, among which, hot night accounted for a large proportion.

CONCLUSIONS

Hot extremes may significantly increase the incidence risk and disease burden of BD. Type-specific protective measures should be taken to reduce the risk of BD, especially in those we found to be particularly vulnerable.

The effect and attributable risk of daily temperature on category C infectious diarrhea in Guangdong Province, China

Previous studies have explored the effect between ambient temperature and infectious diarrhea (ID) mostly using relative risk, which provides limited information in practical applications. Few studies have focused on the disease burden of ID caused by temperature, especially for different subgroups and cities in a multi-city setting. This study aims to estimate the effects and attributable risks of temperature on category C ID and explore potential modifiers among various cities in Guangdong. First, distributed lag non-linear models (DLNMs) were used to explore city-specific associations between daily mean temperature and category C ID from 2014 to 2016 in Guangdong and pooled by applying multivariate meta-analysis. Then, multivariate meta-regression was implemented to analyze the potential heterogeneity among various cities. Finally, we assessed the attributable burden of category C ID due to temperature, low (below the 5th percentile of temperature) and high temperature (above the 95th percentile of temperature) for each city and subgroup population. Compared with the 50th percentile of daily mean temperature, adverse effects on category C ID were found when the temperature was lower than 12.27 ℃ in Guangdong Province. Some city-specific factors (longitude, urbanization rate, population density, disposable income per capita, and the number of medical technicians and beds per thousand persons) could modify the relationship of temperature-category C ID. During the study period, there were 60,505 category C ID cases (17.14% of total cases) attributable to the exposure of temperature, with the attributable fraction (AF) of low temperature (4.23%, 95% empirical confidence interval (eCI): 1.79-5.71%) higher than high temperature (1.34%, 95% eCI: 0.86-1.64%). Males, people under 5 years, and workers appeared to be more vulnerable to temperature, with AFs of 29.40%, 19.25%, and 21.49%, respectively. The AF varied substantially at the city level, with the largest AF of low temperature occurring in Shaoguan (9.58%, 95% eCI: 8.36-10.09%), and that of high temperature occurring in Shenzhen (3.16%, 95% eCI: 2.70-3.51%). Low temperature was an important risk factor for category C ID in Guangdong Province, China. The exposure-response relationship could be modified by city-specific characteristics. Considering the whole population, the attributable risk of low temperature was much higher than that of high temperature, and males, people under 5 years, and workers were vulnerable populations.

Socioeconomic factors and bacillary dysentery risk in Jiangsu Province, China: a spatial investigation using Bayesian hierarchical models

Bacillary dysentery (BD) is an acute diarrheal disease prevalent in areas affected by socioeconomic disparities. We investigated BD risk and its associations with socioeconomic factors at the county-level in Jiangsu province, China using epidemiological and socioeconomic data from 2011-2014. We fitted four Bayesian hierarchical models with various prior specifications for random effects. As all model comparison criteria values were similar, we presented results from a reparameterized Besag-York-Mollié model, which addressed issues with the identifiability of variance captured by spatial and independent effects. Our model adjusted for year and socioeconomic status showed 18-65% decreased BD risk compared to 2011. We found a high relative risk in the northwestern and southwestern counties. Increasing the percentage of rural households, rural income per capita, health institutions per capita, or hospital beds per capita decreases the relative risk of BD, respectively. Our findings can be used to improve infectious diarrhea surveillance and enhance existing public health interventions.

Temperature and risk of infectious diarrhea: a systematic review and meta-analysis

Infectious diarrhea (ID) is an intestinal infectious disease including cholera, typhoid and paratyphoid fever, bacterial and amebic dysentery, and other infectious diarrhea. There are many studies that have explored the relationship between ambient temperature and the spread of infectious diarrhea, but the results are inconsistent. It is necessary to systematically evaluate the impact of temperature on the incidence of ID. This study was based on the PRISMA statement to report this systematic review. We conducted literature searches from CNKI, VIP databases, CBM, PubMed, Web of Science, Cochrane Library, and other databases. The number registered in PROSPERO is CRD42021225472. After searching a total of 4915 articles in the database and references, 27 studies were included. The number of people involved exceeded 7.07 million. The overall result demonstrated when the temperature rises, the risk of infectious diarrhea increases significantly (RR_cumulative=1.42, 95%CI: 1.07-1.88, RR_single-day=1.08, 95%CI: 1.03-1.14). Subgroup analysis found the effect of temperature on the bacillary dysentery group (RR_cumulative=1.85, 95%CI: 1.48-2.30) and unclassified diarrhea groups (RR_cumulative=1.18, 95%CI: 0.59-2.34). The result of the single-day effect subgroup analysis was similar to the result of the cumulative effect. And the sensitivity analysis proved that the results were robust. This systematic review and meta-analysis support that temperature will increase the risk of ID, which is helpful for ID prediction and early warning in the future.

The exposure-response association between humidex and bacillary dysentery: A two-stage time series analysis of 316 cities in mainland China

BACKGROUND

Many studies have reported the interactive effects between relative humidity and temperature on infectious diseases. However, evidence regarding the combined effects of relative humidity and temperature on bacillary dysentery (BD) is limited, especially for large-scale studies. To address this research need, humidex was utilized as a comprehensive index of relative humidity and temperature. We aimed to estimate the effect of humidex on BD across mainland China, evaluate its heterogeneity, and identify potential effect modifiers.

METHODS

Daily meteorological and BD surveillance data from 2014 to 2016 were obtained for 316 prefecture-level cities in mainland China. Humidex was calculated on the basis of relative humidity and temperature. A multicity, two-stage time series analysis was then performed. In the first stage, a common distributed lag non-linear model (DLNM) was established to obtain city-specific estimates. In the second stage, a multivariate meta-analysis was conducted to pool these estimates, assess the significance of heterogeneity, and explore potential effect modifiers.

RESULTS

The pooled cumulative estimates showed that humidex could promote the transmission of BD. The exposure-response relationship was nearly linear, with a maximum cumulative relative risk (RR) of 1.45 [95% confidence interval (CI): 1.29-1.63] at a humidex value of 40.94. High humidex had an acute adverse effect on BD. The humidex-BD relationship could be modified by latitude, urbanization rate, the natural growth rate of population, and the number of primary school students per thousand persons.

CONCLUSIONS

High humidex could increase the risk of BD incidence. Thus, it is suitable to incorporate humidex as a predictor into the early warning system of BD and to inform the general public in advance to be cautious when humidex is high. This is especially true for regions with higher latitude, higher urbanization rates, lower natural growth rates of population, and lower numbers of primary school students per thousand persons.

Spatial heterogeneity of bacillary dysentery and the impact of temperature in the Beijing-Tianjin-Hebei region of China

Previous studies indicate that the incidence of bacillary dysentery is closely related to meteorological factors. However, the impact of temperature and the spatial heterogeneity of the disease in regions of unbalanced socioeconomic development remains unclear. Therefore, this research collected data for 29,639 daily bacillary dysentery cases in children under 5 years of age, as well as the meteorological variables from China's Beijing-Tianjin-Hebei region, to analyze the spatial pattern of bacillary dysentery and reveal its nonlinear association with temperature. The SatScan method was employed first, to detect the spatial heterogeneity of the disease risk, and then the distributed lag nonlinear model (DLNM) was used to analyze the relationships between the daily minimum, mean, and maximum temperatures and bacillary dysentery in the stratified heterogeneous regions. The results indicated that bacillary dysentery incidence presented statistically significant spatial heterogeneity. The area of highest risk was found to be Beijing and its neighboring regions, which have high population densities. There was also a positive association between bacillary dysentery and temperature. Hotter temperatures were accompanied by higher relative risks. In the most likely spatial cluster region, the excess risk (ER) values for a 1°C rise in minimum, mean, and maximum temperatures above the median were 4.65%, 11.30%, and 19.21%, respectively. The effect of temperature on bacillary dysentery peaked at a lag of 3 to 4 days. The findings of this study will aid risk assessments and early warning systems for bacillary dysentery.

Effect of temperature and its interaction with other meteorological factors on bacillary dysentery in Jilin Province, China

Bacterial dysentery (BD) brings a major disease burden to developing countries. Exploring the influence of temperature and its interaction with other meteorological factors on BD is significant for the prevention and early warning of BD in the context of climate change. Daily BD cases and meteorological data from 2008 to 2018 were collected in all nine prefecture-level cities in Jilin Province. A one-stage province-level model and a two-stage city-specific multivariate meta-pooled level distributed lag non-linear model were established to explore the correlation between temperature and BD, then the weather-stratified generalised additive model was used to test the interaction. During the study period, a total of 26 971 cases of BD were developed. The one-stage and two-stage cumulative dose-response ‘J’ curves overlapped, and results showed a positive correlation between temperature and BD with a 1–6 days lag effect. Age group ⩾5 years was found to be more sensitive to the effects. Moreover, there was a significant interaction between temperature, humidity and precipitation (P = 0.004, 0.002, respectively) on BD under high temperature (>0 °C), reminding residents and policymakers to pay attention to the prevention of BD in situations with both high temperature and humidity, high temperature and precipitation during the temperate monsoon climate.

Associations between floods and bacillary dysentery cases in main urban areas of Chongqing, China, 2005-2016: a retrospective study

Background

Understanding the association between floods and bacillary dysentery (BD) incidence is necessary for us to assess the health risk of extreme weather events. This study aims at exploring the association between floods and daily bacillary dysentery cases in main urban areas of Chongqing between 2005 and 2016 as well as evaluating the attributable risk from floods.

Methods

The association between floods and daily bacillary dysentery cases was evaluated by using distributed lag non-linear model, controlling for meteorological factors, long-term trend, seasonality, and day of week. The fraction and number of bacillary dysentery cases attributable to floods was calculated. Subgroup analyses were conducted to explore the association across age, gender, and occupation.

Results

After controlling the impact of temperature, precipitation, relative humidity, long-term trend, and seasonality, a significant lag effect of floods on bacillary dysentery cases was found at 0-day, 3-day, and 4-day lag, and the cumulative relative risk (CRR) over a 7-lag day period was 1.393 (95%CI 1.216–1.596). Male had higher risk than female. People under 5 years old and people aged 15–64 years old had significantly higher risk. Students, workers, and children had significantly higher risk. During the study period, based on 7-lag days, the attributable fraction of bacillary dysentery cases due to floods was 1.10% and the attributable number was 497 persons.

Conclusions

This study confirms that floods can increase the risk of bacillary dysentery incidence in main urban areas of Chongqing within an accurate time scale, the risk of bacillary dysentery caused by floods is still serious. The key population includes male, people under 5 years old, students, workers, and children. Considering the lag effect of floods on bacillary dysentery, the government and public health emergency departments should advance to the emergency health response in order to minimize the potential risk of floods on public.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12199-021-00971-z.

Real-time forecasting and early warning of bacillary dysentery activity in four meteorological and geographic divisions in China

BACKGROUND

Accurate and timely forecasts of bacillary dysentery (BD) incidence can be used to inform public health decision-making and response preparedness. However, our ability to detect BD dynamics and outbreaks remains limited in China.

OBJECTIVES

This study aims to explore the impacts of meteorological factors on BD transmission in four representative regions in China and to forecast weekly number of BD cases and outbreaks.

METHODS

Weekly BD and meteorological data from 2014 to 2016 were collected for Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China). A boosted regression tree (BRT) model was conducted to assess the impacts of meteorological factors on BD transmission. Then a real-time forecast and early warning model based on BRT was developed to track the dynamics of BD and detect the outbreaks. The forecasting methodology was compared with generalized additive model (GAM) and seasonal autoregressive integrated moving average model (SARIMA) that have been used to model the BD case data previously.

RESULTS

Ambient temperature was the most important meteorological factor contributing to the transmission of BD (80.81%-92.60%). A positive effect of temperature was observed when weekly mean temperature exceeded 4 °C, -3 °C, 9 °C and 16 °C in Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China), respectively. BD incidence (Beijing and Shenyang) in temperate cities was more sensitive to high temperature than that in subtropical cities (Chongqing and Shenzhen). The dynamics and outbreaks of BD can be accurately forecasted and detected by the BRT model. Compared to GAM and SARIMA, BRT model showed more accurate forecasting for 1-, 2-, 3-weeks ahead forecasts in Beijing, Shenyang and Shenzhen.

CONCLUSIONS

Temperature plays the most important role in weather-attributable BD transmission. The BRT model achieved a better performance in comparison with GAM and SARIMA in most study cities, which could be used as a more accurate tool for forecasting and outbreak alert of BD in China.

A review of the impact of outdoor and indoor environmental factors on human health in China

The Intergovernmental Panel on Climate Change (IPCC) reported that global climate change has led to the increased occurrence of extreme weather events. In the context of global climate change, more evidence indicates that abnormal meteorological conditions could increase the risk of epidemiological mortality and morbidity. In this study, using a systematic review, we evaluated a total of 175 studies (including 158 studies on outdoor environment and 17 studies on indoor environment) to summarize the impact of outdoor and indoor environment on human health in China using the database of PubMed, Web of Science, the Cochrane Library, and Embase. In particular, we focused on studies about cardiovascular and respiratory mortality and morbidity, the prevalence of digestive system diseases, infectious diseases, and preterm birth. Most of the studies we reviewed were conducted in three of the metropolises of China, including Beijing, Guangzhou, and Shanghai. For the outdoor environment, we summarized the effects of climate change-related phenomena on health, including ambient air temperature, diurnal temperature range (DTR), temperature extremes, and so on. Studies on the associations between temperature and human health accounted for 79.7% of the total studies reviewed. We also screened out 19 articles to explore the effect of air temperature on cardiovascular diseases in different cities in the final meta-analysis. Besides, modern lifestyle involves a large amount of time spent indoors; therefore, indoor environment also plays an important role in human health. Nevertheless, studies on the impact of indoor environment on human health are rarely reported in China. According to the limited reports, adverse indoor environment could impose a high health risk on children.

Daily Temperature and Bacillary Dysentery: Estimated Effects, Attributable Risks, and Future Disease Burden in 316 Chinese Cities

BACKGROUND

Bacillary dysentery (BD) remains a significant public health issue, especially in developing countries. Evidence assessing the risk of BD from temperature is limited, particularly from national studies including multiple locations with different climatic characteristics.

OBJECTIVES

We estimated the effect of temperature on BD across China, assessed heterogeneity and attributable risks across cities and regions, and projected the future risk of BD under climate change.

METHODS

Daily BD surveillance and meteorological data over 2014-2016 were collected from the Chinese Center for Disease Control and Prevention and the China Meteorology Administration, respectively. A two-stage statistical model was used to estimate city-specific temperature-BD relationships that were pooled to derive regional and national estimates. The risk of BD attributable to temperature was estimated, and the future burden of BD attributable to temperature was projected under different climate change scenarios.

RESULTS

A positive linear relationship for the pooled effect was estimated at the national level. Subgroup analyses indicate that the estimated effect of temperature on BD was similar by age (≤5y or >5y) and gender. At baseline, estimated attributable risks for BD due to average daily mean temperatures above the 50th percentile were highest for the Inner Mongolia (16%), Northeast China (14%), and Northern China (13%). Most of the individual cities in the same regions and most of the cities in the Northwest, Southern, and Southwest regions, had high attributable risks (≥5%). The Northern, Northeast, Inner Mongolia, Northwest, and Southern China regions were identified as high risk for future BD, with estimated increases by the 2090s compared with baseline of 20% (95% confidence interval: 11%, 27%), 15% (6%, 20%), 15% (-1%, 22%), 12% (1%, 19%), and 11% (5%, 15%), respectively, under Representative Concentration Pathway 8.5.

CONCLUSIONS

The positive association between temperature and BD in different climatic regions of China, and the projection for increased risk due to climate change, support efforts to mitigate future risks. https://doi.org/10.1289/EHP5779.

Impact of climate change on dysentery: Scientific evidences, uncertainty, modeling and projections

Dysentery is water-borne and food-borne infectious disease and its incidence is sensitive to climate change. Although the impact of climate change on dysentery is being studied in specific areas, a systematic review is lacking. We searched the worldwide literature using three sets of keywords and six databases. We identified and selected 98 studies during 1866-2019 and reviewed the relevant findings. Climate change, including long-term variations in factors, such as temperature, precipitation, and humidity, and short-term variations in extreme weather events, such as floods and drought, mostly had a harmful impact on dysentery incidence. However, some uncertainty over the exact effects of climate factors exists, specifically in the different indexes for the same climate factor, various determinant indexes for different dysentery burdens, and divergent effects for different population groups. These complicate the accurate quantification of such impacts. We generalized two types of methods: sensitivity analysis, used to detect the sensitivity of dysentery to climate change, including Pearson's and Spearman's correlations; and mathematical models, which quantify the impact of climate on dysentery, and include models that examine the associations (including negative binomial regression models) and quantify correlations (including single generalized additive models and mixed models). Projection studies mostly predict disease risks, and some predict disease incidence based on climate models under RCP 4.5. Since some geographic heterogeneity exists in the climate-dysentery relationship, modeling and projection of dysentery incidence on a national or global scale remain challenging. The reviewed results have implications for the present and future. Current research should be extended to select appropriate and robust climate-dysentery models, reasonable disease burden measure, and appropriate climate models and scenarios. We recommend future studies focus on qualitative investigation of the mechanism involved in the impact of climate on dysentery, and accurate projection of dysentery incidence, aided by advancing accuracy of extreme weather forecasting.

Epidemiological characteristics of bacillary dysentery from 2009 to 2016 and its incidence prediction model based on meteorological factors

Background

This study aimed to analyse the epidemiological characteristics of bacillary dysentery (BD) caused by Shigella in Chongqing, China, and to establish incidence prediction models based on the correlation between meteorological factors and BD, thus providing a scientific basis for the prevention and control of BD.

Methods

In this study, descriptive methods were employed to investigate the epidemiological distribution of BD. The Boruta algorithm was used to estimate the correlation between meteorological factors and BD incidence. The genetic algorithm (GA) combined with support vector regression (SVR) was used to establish the prediction models for BD incidence.

Results

In total, 68,855 cases of BD were included. The incidence declined from 36.312/100,000 to 23.613/100,000, with an obvious seasonal peak from May to October. Males were more predisposed to the infection than females (the ratio was 1.118:1). Children < 5 years old comprised the highest incidence (295.892/100,000) among all age categories, and pre-education children comprised the highest proportion (34,658 cases, 50.335%) among all occupational categories. Eight important meteorological factors, including the highest temperature, average temperature, average air pressure, precipitation and sunshine, were correlated with the monthly incidence of BD. The obtained mean absolute percent error (MAPE), mean squared error (MSE) and squared correlation coefficient (R²) of GA_SVR_MONTH values were 0.087, 0.101 and 0.922, respectively.

Conclusion

From 2009 to 2016, BD incidence in Chongqing was still high, especially in the main urban areas and among the male and pre-education children populations. Eight meteorological factors, including temperature, air pressure, precipitation and sunshine, were the most important correlative feature sets of BD incidence. Moreover, BD incidence prediction models based on meteorological factors had better prediction accuracies. The findings in this study could provide a panorama of BD in Chongqing and offer a useful approach for predicting the incidence of infectious disease. Furthermore, this information could be used to improve current interventions and public health planning.

Brain diseases in changing climate

Climate change is one of the biggest and most urgent challenges for the 21st century. Rising average temperatures and ocean levels, altered precipitation patterns and increased occurrence of extreme weather events affect not only the global landscape and ecosystem, but also human health. Multiple environmental factors influence the onset and severity of human diseases and changing climate may have a great impact on these factors. Climate shifts disrupt the quantity and quality of water, increase environmental pollution, change the distribution of pathogens and severely impacts food production - all of which are important regarding public health. This paper focuses on brain health and provides an overview of climate change impacts on risk factors specific to brain diseases and disorders. We also discuss emerging hazards in brain health due to mitigation and adaptation strategies in response to climate changes.

Impacts of exposure to ambient temperature on burden of disease: a systematic review of epidemiological evidence

Ambient temperature is an important determinant of mortality and morbidity, making it necessary to assess temperature-related burden of disease (BD) for the planning of public health policies and adaptive responses. To systematically review existing epidemiological evidence on temperature-related BD, we searched three databases (PubMed, Web of Science, and Scopus) on 1 September 2018. We identified 97 studies from 56 counties for this review, of which 75 reported the fraction or number of health outcomes (include deaths and diseases) attributable to temperature, and 22 reported disability-adjusted life years (include years of life lost and years lost due to disability) related to temperature. Non-optimum temperatures (i.e., heat and cold) were responsible for > 2.5% of mortality in all included high-income countries/regions, and > 3.0% of mortality in all included middle-income countries. Cold was mostly reported to be the primary source of mortality burden from non-optimum temperatures, but the relative role of three different temperature exposures (i.e., heat, cold, and temperature variability) in affecting morbidity and mortality remains unclear so far. Under the warming climate scenario, almost all projections assuming no population adaptation suggested future increase in heat-related but decrease in cold-related BD. However, some studies emphasized the great uncertainty in future pattern of temperature-related BD, largely depending on the scenarios of climate, population adaptation, and demography. We also identified important discrepancies and limitations in current research methodologies employed to measure temperature exposures and model temperature-health relationship, and calculate the past and project future temperature-related BD. Overall, exposure to non-optimum ambient temperatures has become and will continue to be a considerable contributor to the global and national BD, but future research is still needed to develop a stronger methodological framework for assessing and comparing temperature-related BD across different settings.

Exploring the Relevance of Green Space and Epidemic Diseases Based on Panel Data in China from 2007 to 2016

Urban green space has been proven effective in improving public health in the contemporary background of planetary urbanization. There is a growing body of literature investigating the relationship between non-communicable diseases (NCDs) and green space, whereas seldom has the correlation been explored between green space and epidemics, such as dysentery, tuberculosis, and malaria, which still threaten the worldwide situation of public health. Meanwhile, most studies explored healthy issues with the general green space, public green space, and green space coverage, respectively, among which the different relevance has been rarely explored. This study aimed to examine and compare the relevance between these three kinds of green space and incidences of the three types of epidemic diseases based on the Panel Data Model (PDM) with the time series data of 31 Chinese provinces from 2007 to 2016. The results indicated that there exists different, or even opposite, relevance between various kinds of green space and epidemic diseases, which might be associated with the process of urban sprawl in rapid urbanization in China. This paper provides a reference for re-thinking the indices of green space in building healthier and greener cities.

Effects of ambient temperature on bacillary dysentery: A multi-city analysis in Anhui Province, China

BACKGROUND

Rising ambient temperature is expected to increase incidence of bacillary dysentery (BD), but few studies have compared the temperature-BD effects of different age groups and cities in China, especially in a multi-city setting.

OBJECTIVES

We used city-specific data including BD cases and meteorological variables to determine the relationship between BD incidence and temperature at provincial level.

METHODS

Weekly BD disease surveillance data and meteorological variables were collected in all 16 prefecture-level cities in Anhui Province of China. Firstly, city-specific weekly mean temperature-BD incidence associations were estimated with Distributed Lag Nonlinear Model (DLNM). Secondly, city-specific estimates were pooled at province-level through multivariate meta-analysis. Also, we conducted subgroup analyses for ages (children <5 years old and population of other ages) and urbanization of cities (high and low level), respectively.

RESULTS

In Anhui, BD morbidity risk increased with increasing weekly mean temperature. Relative risks (RR) at the 90th percentile (27.5 °C) versus the 50th percentile (17 °C) of weekly mean temperature were 1.42 (95% confidence interval (CI): 1.16, 1.75) and 2.02 (95% CI: 1.76, 2.32) for children <5 and population of other ages, respectively. The relative risk of high temperature on other ages group was higher than that of children under five years old (p = 0.006). Children under 5 in high urbanized cities appeared to be more vulnerable to the effects of ambient high temperature (RR: 1.56, 95% CI: 1.20, 1.92) than in low urbanized cities (RR: 1.01, 95% CI: 0.70, 1.46), the difference between two intervals was statistically significant (p = 0.044).

CONCLUSIONS

This study suggests that high temperatures may be an important trigger of BD incidence, and especially lead to a substantial burden of BD for high urbanized cities in Anhui Province of China.

Health impact of climate change in cities of middle-income countries: the case of China

BACKGROUND

This review examines the human health impact of climate change in China. Through reviewing available research findings under four major climate change phenomena, namely extreme temperature, altered rainfall pattern, rise of sea level and extreme weather events, relevant implications for other middle-income population with similar contexts will be synthesized.

SOURCES OF DATA

Sources of data included bilingual peer-reviewed articles published between 2000 and 2018 in PubMed, Google Scholar and China Academic Journals Full-text Database.

AREAS OF AGREEMENT

The impact of temperature on mortality outcomes was the most extensively studied, with the strongest cause-specific mortality risks between temperature and cardiovascular and respiratory mortality. The geographical focuses of the studies indicated variations in health risks and impacts of different climate change phenomena across the country.

AREAS OF CONTROVERSY

While rainfall-related studies predominantly focus on its impact on infectious and vector-borne diseases, consistent associations were not often found.

GROWING POINTS

Mental health outcomes of climate change had been gaining increasing attention, particularly in the context of extreme weather events. The number of projection studies on the long-term impact had been growing.

AREAS TIMELY FOR DEVELOPING RESEARCH

The lack of studies on the health implications of rising sea levels and on comorbidity and injury outcomes warrants immediate attention. Evidence is needed to understand health impacts on vulnerable populations living in growing urbanized cities and urban enclaves, in particular migrant workers. Location-specific climate-health outcome thresholds (such as temperature-mortality threshold) will be needed to support evidence-based clinical management plans and health impact mitigation strategies to protect vulnerable communities.

Effect of ambient temperature and its effect modifiers on bacillary dysentery in Jinan, China

BACKGROUND

Studies about the modified effect among various meteorological factors on bacillary dysentery (BD) are limited. This study aimed to investigate the effect of ambient temperature and its effect modifiers on BD in Jinan.

METHODS

Daily data of BD cases and meteorological factors from 2005 to 2013 were collected. A generalized additive model (GAM) was conducted to explore the relationship between meteorological factors and BD. Then a distributed lag non-linear model (DLNM) was developed to assess the lag and cumulative effect. Finally, the modified effect between temperature and other meteorological factors on BD was explored by the GAM and a weather-stratified model.

RESULTS

A total of 11,738 cases of BD were notified over the study period. The exposure-response relationship between temperature and BD was liner with a single threshold value of 0 °C. Results of DLNM showed that after temperature exceeds the threshold, each 5 °C rise in temperature caused a 19% (RR = 1.19, 95% CI: 1.14-1.24) increase in the number of cases of BD at lag 0. The analysis of cumulative effects showed that each 5 °C rise in temperature can increase the number of cases by 61% (RR = 1.61, 95% CI: 1.58-1.63) at lag 0-lag 7 days. The effect modification of the association between temperature and BD by humidity was observed in our study, while the modification by precipitation and wind speed were not statistically significant. The risk of BD was highest when temperature and humidity were both high.

CONCLUSIONS

Our study indicates that temperature is significantly associated with the risk of BD in the study area, and the effect can be modified by humidity. Public health professionals and medical service providers should pay more attention BD prevention and control when the weather condition of both high temperature and high humidity would occur.