The association between human perceived heat and early-stage syphilis and its variance: Results from a case-report system

Independent and interaction effects of prenatal exposure to high AQI and extreme Humidex on the risk of preterm birth: A large sample population study in northern China

The combined effects of air pollution and extreme temperature on PTB remain unclear. To evaluate the independent effect and interaction effect of prenatal extreme exposure to air quality index (AQI) and Humidex, on PTB. Based on the National Health Care Data Platform of Shandong University, women who gave birth in 2019-2020 were selected for the study. First, the independent effects of AQI and Humidex on PTB were assessed by logistic regression model. Subsequently, the interaction effects of AQI and Humidex on PTB were estimated separately by calculation of the relative excess risk of interaction (RERI). A total of 34365 pregnant women were included and 1975 subjects were diagnosed with PTB. We observed a significant increase in the odds of PTB associated with maternal high AQI exposure, with an OR of 1.70 (95% CI: 1.59, 1.81). Similarly, extreme exposure to Humidex also demonstrated an elevated PTB odds, with a low Humidex OR of 2.48 (95% CI: 2.23, 2.76) and a high Humidex OR of 1.48 (95% CI: 1.31, 1.67). Finally, we observed an interaction between high AQI and extreme Humidex during the 1st trimester. Interaction effects were noted between high AQI and low Humidex throughout the entire trimester and the 2nd trimester. This study suggests that prenatal exposure to high AQI and extreme Humidex could increase the odds of PTB, with effects exhibiting the sensitivity window and a cumulative trend. Additionally, there is an interaction between AQI and Humidex.

The role of extreme high humidex in depression in chongqing, China: A time series-analysis

As global climate change intensifies, people are paying increasing attention to the impact of temperature changes on adverse mental health outcomes, especially depression. While increasing attention has been paid to the effect of temperature, there is little research on the effect of humidity. We aimed to investigate the association between humidex, an index combining temperature and humidity to reflect perceived temperature, and outpatient visits for depression from 2014 to 2019 in Chongqing, the largest and one of the most hot and humid cities of China. We also aimed to further identify susceptible subgroups. A distributed lag non-linear model (DLNM) was used to explore the concentration-response relationship between humidex and depression outpatient visits. Hierarchical analysis was carried out by age and gender. A total of 155,436 visits for depression were collected from 2014 to 2019 (2191 days). We found that depression outpatient visits were significantly associated with extremely high humidex (≥40). The significant positive single-lag day effect existed at lag 0 (RR = 1.029, 95%CI: 1.000-1.059) to lag 2 (RR = 1.01, 95%CI: 1.004-1.028), and lag 12 (RR = 1.013, 95%CI: 1.002-1.024). The significant cumulative adverse effects lasted from lag 01 to lag 014. Hierarchical analyses showed that females and the elderly (≥60 years) appeared to be more susceptible to extremely high humidex. The attributable numbers (AN) and fraction (AF) of extremely high humidex on depression outpatients were 1709 and 1.10%, respectively. Extremely high humidex can potentially increase the risk of depression, especially in females and the elderly. More protective measures should be taken in vulnerable populations.

Spatio-temporal variation on syphilis from 2005 to 2018 in Zhejiang Province, China

Background

Syphilis has spread throughout China, especially in Zhejiang Province which endangers the health and lives of people. However, the spatial and temporal epidemiological studies of syphilis in Zhejiang are not thorough enough. The temporal and spatial variation and the relevant factors of syphilis incidence should be analyzed for more effective prevention and control in Zhejiang, China.

Methods

Data on confirmed cases of syphilis in Zhejiang Province from 2005 to 2018 was used and the spatio-temporal distributions were described. The spatial autocorrelation analysis and SaTScan analysis were performed to identify spatio-temporal clusters. A Bayesian spatial Conditional Autoregression (CAR) model was constructed to explore the relationships between syphilis incidence and common social and natural indicators.

Results

474,980 confirmed cases of syphilis were reported between 2005 and 2018 with a large peak in 2010. Farmers and unemployed people accounted for the largest proportion of confirmed cases. And the significant spatial clusters of syphilis were concentrated in the north of Zhejiang Province, especially in more economically developed regions. Seven spatio-temporal clusters were identified and the main three high-risk areas were located in Hangzhou (RR = 1.62, P < 0.05), Zhoushan and Ningbo (RR = 1.99, P < 0.05), and Lishui (RR = 1.68, P < 0.05). The findings showed that the morbidity of syphilis was positively correlated with the Gross Domestic Product (GDP) per capita, the number of health technicians per 10,000 people, the proportion of the elderly and air temperature were negatively correlated with the proportion of the urban population, the proportion of men and precipitation.

Conclusions

The spatio-temporal analysis revealed that the prevalence of syphilis was still serious in Zhejiang Province. Syphilis high-risk areas were mainly located in the more developed coastal regions where more targeted intervention measures were required to be implemented. The study highlighted the need to strengthen Sexually Transmitted Diseases (STD) screening and health education for high-risk groups and improve the coverage of syphilis testing to reduce hidden syphilis cases.

Spatial Heterogeneity and Its Influencing Factors of Syphilis in Ningxia, Northwest China, from 2004 to 2017: A Spatial Analysis

Syphilis remains a growing and resurging infectious disease in China. However, exploring the influence of environmental factors on the spatiotemporal distribution of syphilis remains under explore. This study aims to analyze the spatiotemporal distribution characteristics of syphilis in Ningxia, Northwest China, and its potential environmental influencing factors. Based on the standardized incidence ratio of syphilis for 22 administrative areas in Ningxia from 2004 to 2017, spatiotemporal autocorrelation and scan analyses were employed to analyze the spatial and temporal distribution characteristics of syphilis incidence, while a fixed-effect spatial panel regression model identified the potential factors affecting syphilis incidence. Syphilis incidence increased from 3.78/100,000 in 2004 to 54.69/100,000 in 2017 with significant spatial clustering in 2007 and 2009-2013. The "high-high" and "low-low" clusters were mainly distributed in northern and southern Ningxia, respectively. The spatial error panel model demonstrated that the syphilis incidence may be positively correlated with the per capita GDP and tertiary industry GDP and negatively correlated with the number of health facilities and healthcare personnel. Sex ratio and meteorological factors were not significantly associated with syphilis incidence. These results show that the syphilis incidence in Ningxia is still increasing and has significant spatial distribution differences and clustering. Socio-economic and health-resource factors could affect the incidence; therefore, strengthening syphilis surveillance of migrants in the economically developed region and allocating health resources to economically underdeveloped areas may effectively help prevent and control syphilis outbreaks in high-risk cluster areas of Ningxia.

Prevalence and spatial heterogeneity of Trichomonas vaginalis infection among the female population and association with climate in Guangxi Zhuang autonomous region, Southern China

BACKGROUND

Two cervical cancer screening (CCS) projects have been ongoing for years in Guangxi Zhuang autonomous region (Guangxi), and some Trichomonas vaginalis infection (TVI) cases have been found as an opportunistic finding. This study aimed to identify the high-risk population and expound the spatial epidemiological features of TVI in Guangxi.

METHODS

This study was based on CCS from 2012 to 2019. Adjusted odds ratio (AOR), and spatial analyses were used to identify the high-risk subgroups, as well as to depict the spatial epidemiological feature and its relationship with meteorological factors.

RESULTS

The infection rate of TVI was 0.38% in 873,880 samples. Significant association with a high risk of TVI was found in the following: females aged 40-49 years (aOR=4.464; 95% CI, 3.359-5.932; p<0.001), aged 50-59 years (aOR=3.169; 95% CI, 2.370-4.237; p<0.001), from urban (aOR=1.577; 95% CI, 1.471-1.691; p<0.001), from minority areas (aOR=1.183; 95% CI, 1.060-1.320; p=0.003), areas with GPD <41,500 CNY (aOR=1.191; 95% CI, 1.106-1.282; p<0.001), and inland areas (aOR=1.520; 95% CI, 1.339-1.726; p<0.001). Counties with higher infection rate were concentrated in northwest Guangxi's mountainous area (Z-score=3.9656, p<0.001), in the upper reaches of the Hongshui River and Yu River, and with a significant spatial autocorrelation (Moran's I=0.581, p=0.002). Spatial error model showed significantly negative regressions among temperature (B=-0.295, p=0.002), annual temperature range (B=-0.295, p=0.002), and TVI spatial distribution.

CONCLUSION

The spatial clustering and disparity of TVI in northwest Guangxi warrant further study, and meteorological conditions may play an important role in TVI in northwest Guangxi.

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.

Spatiotemporal distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005-2017

Background

Previous studies exploring the factors associated with the incidence of syphilis have mostly focused on individual-level factors. However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. Studies on the sociodemographic and socioeconomic factors associated with syphilis incidence are scarce, and they have rarely controlled for spatial effects, even though syphilis shows spatial autocorrelation.

Methodology/Principal findings

Syphilis data from 21 cities in Guangdong province between 2005 and 2017 were provided by the National Notifiable Infectious Disease Reporting Information System. The incidence time series, incidence map, and space-time scanning data were used to visualize the spatiotemporal distribution. The spatial panel data model was then applied to explore the relationship between sociodemographic factors (population density, net migration rate, male:female ratio, and the number of health institutions per 1,000 residents), socioeconomic factors (gross domestic product per capita, the proportion of secondary/tertiary industry), and the incidence of primary and secondary syphilis after controlling for spatial effects. The incidence of syphilis increased slowly from 2005 (11.91 per 100,000) to 2011 (13.42 per 100,000) and then began to decrease, reaching 6.55 per 100,000 in 2017. High-risk clusters of syphilis tended to shift from developed areas to underdeveloped areas. An inverted U-shaped relationship was found between syphilis incidence and gross domestic product per capita. Moreover, syphilis incidence was significantly associated with population density (β = 2.844, P = 0.006), the number of health institutions per 1,000 residents (β = -0.095, P = 0.007), and the net migration rate (β = -0.219, P = 0.002).

Conclusions/Significance

Our findings suggest that the incidence of primary and secondary syphilis first increase before decreasing as economic development increases further. These results emphasize the necessity to prevent syphilis in regions at the early stages of economic growth.

Syphilis is a sexually transmitted infection that continues to cause morbidity and mortality worldwide. The primary and secondary stages of syphilis are the most transmissive stages in the entire process of the disease. We analyzed primary and secondary (P&S) syphilis data from 2005 to 2017 in Guangzhou, China, provided by the National Notifiable Infectious Disease Reporting Information System. The results showed that the annual incidence rates of P&S syphilis slightly increased from 2005 to 2011 and then began to decrease in 2017. Cases of P&S syphilis were spatially clustered. The high-risk syphilis clusters tended to shift from developed areas to underdeveloped areas. There may be an inverted U-shaped relationship between the level of economic development and the incidence of P&S syphilis, suggesting that the incidence of P&S syphilis first increased before decreasing as the level of economic development increased further. These results emphasize the necessity of preventing syphilis at locations in the early stage of economic growth. Investments in syphilis prevention education for people in regions at early development stages may mitigate the increasing cost of syphilis to future healthcare systems.

Projecting life-cycle environmental impacts of corn production in the U.S. Midwest under future climate scenarios using a machine learning approach

Climate change is exacerbating environmental pollution from crop production. Spatially and temporally explicit estimates of life-cycle environmental impacts are therefore needed for suggesting location and time relevant environmental mitigations strategies. Emission factors and process-based mechanism models are popular approaches used to estimate life-cycle environmental impacts. However, emission factors are often incapable of describing spatial and temporal heterogeneity of agricultural emissions, whereas process-based mechanistic models, capable of capturing the heterogeneity, tend to be very complicated and time-consuming. Efficient prediction of life-cycle environmental impacts from agricultural production is lacking. This study develops a rapid predictive model to quantify life-cycle global warming (GW) and eutrophication (EU) impacts of corn production using a novel machine learning approach. We used the boosted regression tree (BRT) model to estimate future life-cycle environmental impacts of corn production in U.S. Midwest counties under four emissions scenarios for years 2022-2100. Results from BRT models indicate that the cross-validation (R²) for predicting life cycle GW and EU impacts ranged from 0.78 to 0.82, respectively. Furthermore, results show that future life-cycle GW and EU impacts of corn production will increase in magnitude under all four emissions scenarios, with the highest environmental impacts shown under the high-emissions scenario. Moreover, this study found that changes in precipitation and temperature played a significant role in influencing the spatial heterogeneity in all life-cycle impacts across Midwest counties. The BRT model results indicate that machine learning can be a useful tool for predicting spatially and temporally explicit future life-cycle environmental impacts associated with corn production under different climate scenarios.

Impact of heat on mortality and morbidity in low and middle income countries: A review of the epidemiological evidence and considerations for future research

Heat waves and high air temperature are associated with increased morbidity and mortality. However, the majority of research conducted on this topic is focused on high income areas of the world. Although heat waves have the most severe impacts on vulnerable populations, relatively few studies have studied their impacts in low and middle income countries (LMICs). The aim of this paper is to review the existing evidence in the literature on the impact of heat on human health in LMICs. We identified peer-reviewed epidemiologic studies published in English between January 1980 and August 2018 investigating potential associations between high ambient temperature or heat waves and mortality or morbidity. We selected studies according to the following criteria: quantitative studies that used primary and/or secondary data and report effect estimates where ambient temperature or heat waves are the main exposure of interest in relation to human morbidity or mortality within LMICs. Of the total 146 studies selected, eighty-two were conducted in China, nine in other countries of East Asia and the Pacific, twelve in South Asia, ten in Sub-Saharan Africa, eight in the Middle East and North Africa, and seven in each of Latin America and Europe. The majority of studies (92.9%) found positive associations between heat and human morbidity/mortality. Additionally, while outcome variables and study design differed greatly, most utilized a time-series study design and examined overall heath related morbidity/mortality impacts in an entire population, although it is notable that the selected studies generally found that the elderly, women, and individuals within the low socioeconomic brackets were the most vulnerable to the effects of high temperature. By highlighting the existing evidence on the impact of extreme heat on health in LMICs, we hope to determine data needs and help direct future studies in addressing this knowledge gap. The focus on LMICs is justified by the lack of studies and data studying the health burden of higher temperatures in these regions even though LMICs have a lower capacity to adapt to high temperatures and thus an increased risk.