Mortality risks during extreme temperature events (ETEs) using a distributed lag non-linear model

Site characteristics determine the prevalence of extreme weather events affecting freshwater macroinvertebrate communities

Understanding the impacts of extreme weather events on freshwater ecosystems is imperative during a time when a multitude of challenges compromises these environments' health. Exploring how such events affect macroinvertebrate communities in rivers sheds light on the resilience of freshwater ecosystems, which is essential for human well-being and biodiversity conservation. In this study, long-term time series of benthic macroinvertebrate communities from four sites along three freshwater streams within the Rhine-Main-Observatory Long-Term Ecological Research site in Germany were analyzed. Each of them was sampled annually over a span of ~20 years to assess the impacts of extreme weather events (floods, droughts, and extreme heat) on macroinvertebrate communities. The findings reveal that the effects of extreme events are site-specific, suggesting that the impacts of an extreme event can vary based on several potential factors, including the life history traits of the organisms within the community and, among others, the hydrography of the site. Moreover, the analysis highlights that the cumulative impact of these events over time is more significant than the impact of a single event's magnitude, while following distinct temporal dynamics. This underscores the importance of considering both the temporal dynamics and the biological characteristics of communities when evaluating the consequences of extreme weather events on biodiversity, illustrating that the resilience of freshwater ecosystems and their biodiversity under such conditions depends on a complex interplay of factors rather than the severity of individual events.

Cold exposure, gut microbiota and health implications: A narrative review

Temperature has been recognized as an important environmental factor affecting the composition and function of gut microbiota (GM). Although research on high-temperature impacts has been well studied, knowledge about the effect of cold exposure on GM remains limited. This narrative review aims to synthesize the latest scientific findings on the impact of cold exposure on mammalian GM, and its potential health implications. Chronic cold exposure could disrupt the α-diversity and the composition of GM in both experimental animals and wild-living hosts. Meanwhile, cold exposure could impact gut microbial metabolites, such as short-chain fatty acids. We also discussed plausible biological pathways and mechanisms by which cold-induced changes may impact host health, including metabolic homeostasis, fitness and thermogenesis, through the microbiota-gut-brain axis. Intriguingly, alterations in GM may provide a tool for favorably modulating the host response to the cold temperature. Finally, current challenges and future perspectives are discussed, emphasizing the need for translational research in humans. GM could be manipulated by utilizing nutritional strategies, such as probiotics and prebiotics, to deal with cold-related health issues and enhance well-being in populations living or working in cold environments.

Assessment of mortality risks due to a strong cold spell in 2022 in China

Background

With the intensification of global climate warming, extreme low temperature events such as cold spells have become an increasingly significant threat to public health. Few studies have examined the relationship between cold spells and mortality in multiple Chinese provinces.

Methods

We employed health impact functions for temperature and mortality to quantify the health risks of the first winter cold spell in China on November 26th, 2022, and analyzed the reasons for the stronger development of the cold spell in terms of the circulation field.

Results

This cold spell was a result of the continuous reinforcement of the blocking high-pressure system in the Ural Mountains, leading to the deepening of the cold vortex in front of it. Temperature changes associated with the movement of cold fronts produced additional mortality risks and mortality burdens. In general, the average excess risk (ER) of death during the cold spell in China was 2.75%, with a total cumulative excess of 369,056 deaths. The health risks associated with temperatures were unevenly distributed spatially in China, with the ER values ranging from a minimum of 0.14% to a maximum of 5.72%, and temperature drops disproportionately affect southern regions of China more than northern regions. The cumulative excess deaths exibited the highest in eastern and central China, with 87,655 and 80,230 respectively, and the lowest in northwest China with 27,474 deaths. Among the provinces, excess deaths pronounced the highest in Shandong with 29,492 and the lowest in Tibet with only 196.

Conclusion

The study can provide some insight into the mortality burden of cold spells in China, while emphasising the importance of understanding the complex relationship between extreme low temperature events and human health. The outcomes could provide valuable revelations for informing pertinent public health policies.

Summer heat waves and their mortality risk over a 14-year period in a western region of Iran

Compared to previous decade, impact of heat waves (HWs) on mortality in recent years needs to be discussed in Iran. We investigated temporal change in added impact of summer HWs on mortality in eight cities of Iran. The pooled length of HWs was compared between 2015-2022 and 2008-2014 using random and fixed-effects of meta-analysis regression model. The temporal change in impact of HWs was evaluated through interaction effect between crossbasis function of HW and year in a two-stage time varying model. In order to pool the reduced coefficients of each period, multivariate meta-regression model, including city-specific temperature and temperature range as heterogenicity factors, was used. In addition to relative risk (RR), attributable fraction (AF) of HW in the two periods was also estimated in each city. In the last years, the frequency of all HWs was higher and the weak HWs were significantly longer. The only significant RR was related to the lowest and low severe HWs which was observed in the second period. In terms of AF, compared to the strong HWs, all weak HWs caused a considerable excess mortality in all cities and second period. The subgroup analysis revealed that the significant impact in the second period was mainly related to females and elderlies. The increased risk and AF due to more frequent and longer HWs (weak HWs) in the last years highlights the need for mitigation strategies in the region. Because of uncertainty in the results of severe HWs, further elaborately investigation of the HWs is need.

Association Between Air Pollution and Coronary Heart Disease Hospitalizations in Lanzhou City, 2013-2020: a Time Series Analysis

Coronary heart disease (CHD) is one of the most serious public health problems. However, few studies have focused on the effects of exposure to particulate matter and gaseous air pollutants on CHD. This study aimed to explore the relationship between air pollutants and the number of hospitalized patients with CHD in Lanzhou, and we collected daily data on the number of hospitalized patients with CHD, daily air pollutants, and meteorological factors from 2013 to 2020. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson regression model was applied to evaluate the relationship between air pollutants and the number of hospitalized patients with CHD. The results indicated that the hysteresis effect of all pollutants except O38h reached its maximum at lag3, and the relative risk of coronary heart disease admission was 1.0014 (95%CI: 1.0004, 1.0023), 1.0003 (95%CI: 1.0000, 1.0006), 1.0020 (95%CI: 1.0004, 1.0035), and 1.0053 (95%CI: 1.0026, 1.0080) when PM2.5, PM10, NO2, and SO2 concentrations were increased by 10 μg/m3, respectively. Each 1 mg/m3 increase in CO concentration was associated with a relative risk of coronary heart disease; hospitalization risk was 1.1076 (95%CI: 1.0530, 1.1650). We observed a relative risk of 0.9991 (95%CI: 0.9986, 0.9999) for each 10 μg/m3 increase in O38h for coronary heart disease admission at lag1. Women and elderly were more susceptible to the impact of air pollution, and the impact was greater during cold seasons. Our results indicate that air pollution increased the risk of hospitalization for CHD in a short term. The research findings can provide strategic insights into the impact of current and future air pollution on CHD.

Spatio-temporal interpolation and delineation of extreme heat events in California between 2017 and 2021

Robust spatio-temporal delineation of extreme climate events and accurate identification of areas that are impacted by an event is a prerequisite for identifying population-level and health-related risks. In prior research, attributes such as temperature and humidity have often been linearly assigned to the population of the study unit from the closest weather station. This could result in inaccurate event delineation and biased assessment of extreme heat exposure. We have developed a spatio-temporal model to dynamically delineate boundaries for Extreme Heat Events (EHE) across space and over time, using a relative measure of Apparent Temperature (AT). Our surface interpolation approach offers a higher spatio-temporal resolution compared to the standard nearest-station (NS) assignment method. We show that the proposed approach can provide at least 80.8 percent improvement in identification of areas and populations impacted by EHEs. This improvement in average adjusts the misclassification of about one million Californians per day of an extreme event, who would be either unidentified or misidentified under EHEs between 2017 and 2021.

Associations between congenital heart disease and air pollutants at different gestational weeks: a time-series analysis

Exposure to air pollution during pregnancy has been linked to birth defects. But the directions of studies on the associations between air pollutants exposure and effect on the incidence of congenital heart disease (CHDs) were inconsistent. To date, few studies were concentrated on the effects of both particulate matter and gaseous air pollutant exposure on CHDs across the full gestational week simultaneously. Our study aimed to investigate the critical exposure windows for each air pollutant throughout 40 gestational weeks. Data on CHDs, air pollution, and meteorological factors from 2013 to 2019 were collected in Lanzhou, China. A distributed lag nonlinear model combined with a quasi-Poisson regression model was applied to evaluate the weekly exposure-lag-response association between air pollutants levels and CHDs, and the subgroup analyses were conducted by gender (baby boy and baby girl). The study included 1607 mother-infant pairs. The results demonstrated that exposure of pregnant women to particulate matter ≤ 5 μm (PM_2.5) at lag 1-4 weeks was significantly associated with the risk of CHDs, and the strongest effects were observed in the lag 1 week (1.150, 95%CI 1.059-1.248). For exposure to particulate matter ≤ 10 μm (PM₁₀) at lag 1-3 weeks, the strongest effects were observed in the lag 1 week (1.075, 95% CI 1.026-1.128). For exposure to sulfur dioxide (SO₂) at lag 1-4 weeks, the strongest effects were observed in the lag 1 week (1.154, 95% CI 1.025-1.299). For exposure to carbon monoxide (CO) at lag 1-3 weeks, the strongest effects were observed in the lag 1 week (1.089, 95% CI 1.002-1.183). For exposure to ozone (O₃) concentration at lag 9-15 weeks, the strongest effects were observed in the lag 15 weeks (1.628, 95% CI 1.001-2.649). The cumulative effects of PM_2.5, PM₁₀, SO₂, and CO along weeks with a maximum of 1.609 (95%CI 1.000-2.589), 1.286 (95%CI 1.007-1.641), 1.648 (95%CI 1.018-2.668), and 1.368 (95%CI 1.003, 1.865), respectively. The effects were obvious in the initial gestational weeks too. Through the gender stratification analysis, the air pollutants with significant effects were PM_2.5 for baby boys and PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃ for baby girl. For the relationship between CHDs and air pollution in Lanzhou, PM_2.5, PM₁₀, SO₂, CO, and O₃ played an important role in the initial gestational weeks, especially for baby girl.

High ambient temperature increases the number of emergency visits for upper urolithiasis in Hefei City, China

Background

Few studies have examined the effect of ambient temperature on upper urolithiasis in developing countries, with even fewer considering individual factors.

Methods

The present study analyzed data on emergency department visits for upper urolithiasis from three hospital sites of a large hospital in Hefei, China, during 2016-2020. Data on environmental factors during the same period were also analyzed. A time series analysis employing a generalized Poisson regression model (GPRM) combined with a distributed lag non-linear model (DLNM) was conducted to evaluate the effect of ambient temperature on the number of emergency department visits for upper urolithiasis.

Results

We found that ambient temperatures above 9 °C were positively associated with the frequency of upper urolithiasis visits, with the relationship being most significant on the current day and with a one-day lag. In the single-day lag effect, the most significant relative risk (RR) for mild heat (75th percentile) and high heat (95th percentile) was 1.229 (95% CI: 1.100-1.373) and 1.337 (95% CI: 1.134-1.577), respectively. The cumulative lag effect was significantly higher than the single-day lag effect, with maximum relative risks (RRs) of 1.779 (95% CI: 1.356-2.335) and 2.498 (95% CI: 1.688-3.697), respectively. The maximum lag time was 7 days. RRs were also higher among women and individuals aged 30-44 years.

Conclusions

Increased ambient temperature is a risk factor for upper urolithiasis, and there is a hysteresis effect. Women and individuals aged 30-44 years are the most susceptible.

Analysis of the effect of temperature on tuberculosis incidence by distributed lag non-linear model in Kashgar city, China

The aim of this study was to explore the effect of temperature on tuberculosis (TB) incidence using the distributed lag non-linear model (DLNM) from 2017 to 2021 in Kashgar city, the region with higher TB incidence than national levels, and assist public health prevention and control measures. From January 2017 to December 2021, a total of 8730 cases of TB were reported, with the higher incidence of male than that of female. When temperature was below 1 °C, it was significantly correlated with TB incidence compared to the median observed temperature (15 °C) at lag 7, 14, and 21, and lower temperatures showed larger RR (relative risk) values. High temperature produced a protective effect on TB transmission, and higher temperature from 16 to 31 °C has lower RR. In discussion stratified by gender, the maximum RRs were achieved for both male group and female group at - 15 °C with lag 21, reporting 4.28 and 2.02, respectively. At high temperature (higher than 20 °C), the RR value of developing TB for female group was significantly larger than 1. In discussion stratified by age, the maximum RRs were achieved for all age groups (≤ 35, 36-64, ≥ 65) at - 15 °C with lag 21, reporting 3.20, 2.07, and 3.45, respectively. When the temperature was higher than 20 °C, the RR of the 36-64-year-old group and the ≥ 65-year-old group was significantly larger than 1 at lag 21, while significantly smaller than 1 for cumulative RR at lag 21, reporting 0.11, 95% confidence interval (CI) (0.01, 0.83) and 0.06, 95% CI (0.01, 0.44), respectively. In conclusion, low temperature, especially in extreme level, acts as a high-risk factor inducing TB transmission in Kashgar city. Males exhibit a significantly higher RR of developing TB at low temperature than female, as well as the elderly group in contrast to the young or middle-aged groups. High temperature has a protective effect on TB transmission in the total population, but female and middle-aged and elderly groups are also required to be alert to the delayed RR induced by it.

The Impact of Ambient Temperature on Cardiorespiratory Mortality in Northern Greece

It is well-established that exposure to non-optimum temperatures adversely affects public health, with the negative impact varying with latitude, as well as various climatic and population characteristics. This work aims to assess the relationship between ambient temperature and mortality from cardiorespiratory diseases in Eastern Macedonia and Thrace, in Northern Greece. For this, a standard time-series over-dispersed Poisson regression was fit, along with a distributed lag nonlinear model (DLNM), using a maximum lag of 21 days, to capture the non-linear and delayed temperature-related effects. A U-shaped relationship was found between temperature and cardiorespiratory mortality for the overall population and various subgroups and the minimum mortality temperature was observed around the 65th percentile of the temperature distribution. Exposure to extremely high temperatures was found to put the highest risk of cardiorespiratory mortality in all cases, except for females which were found to be more sensitive to extreme cold. It is remarkable that the highest burden of temperature-related mortality was attributed to moderate temperatures and primarily to moderate cold. The elderly were found to be particularly susceptible to both cold and hot thermal stress. These results provide new evidence on the health response of the population to low and high temperatures and could be useful to local authorities and policy-makers for developing interventions and prevention strategies for reducing the adverse impact of ambient temperature.

Population vulnerability to extreme cold days in rural and urban municipalities in ten provinces in Spain

BACKGROUND

The objective was to analyze whether there are differences in vulnerability to Extreme Cold Days (ECD) between rural and urban populations in Spain.

METHODOLOGY

Time series analysis carried out from January 1, 2000, through December 31, 2013. Municipalities with over 10,000 inhabitants were included from 10 Spanish provinces, classified into 42 groups by isoclimate and urban/rural character as defined by Eurostat criteria. The statistical strategy was carried out in two phases. First: It was analyzed the relationship between minimum daily temperature (Tmin) (source: AEMET) and the rate of daily winter mortality due to natural causes -CIE-10: A00 - R99- (source: National Statistics Institute). Then, It was determinated the threshold of Tmin that defines the ECD and its percentile in the series of winter Tmin (Pthreshold), which is a measure of vulnerability to ECD so that the higher the percentile, the higher the vulnerability. Second: possible explanatory variables of vulnerability were explored using Mixed Generalized Models, using 13 independent variables related to meteorology, environment, socioeconomics, demographics and housing quality.

RESULTS

The average Pthreshold was 18 %. The final model indicated that for each percentage point increase in unemployment, the vulnerability to ECD increased by 0.4 (0.2, 0.6) points. Also, with each point increase in rurality index, this vulnerability decreased by -6.1 (-2.1, -10.0) points. Although less determinant, other factors that could contribute to explaining vulnerability at the province level included minimum winter daily temperatures and the percentage of housing with poor insulation.

CONCLUSIONS

The vulnerability to ECD was greater in urban zones than in rural zones. Socioeconomic status is a key to understanding how this vulnerability is distributed. These results suggest the need to implement public health prevention plans to address ECD at the state level. These plans should be based on threshold temperatures determined at the smallest scale possible.

The influence of heat and cold waves on mortality in Russian subarctic cities with varying climates

Publications on ambient temperature-related mortality among Arctic or subarctic populations are extremely rare. While circumpolar areas cover large portions of several European countries, Canada, and the USA, the population of these territories is relatively small, and the data needed for statistical analysis of the health impacts of extreme temperature events are frequently insufficient. This study utilizes standard time series regression techniques to estimate relative increases in cause- and age-specific daily mortality rates during heat waves and cold spells in four Russian cities with a subarctic climate. The statistical significance of the obtained effect estimates tends to be greater in the continental climate than in the marine climate. A small meta-analysis was built around the obtained site-specific health effects. The effects were homogeneous and calculated for the selected weather-dependent health outcomes. The relative risks of mortality due to ischemic heart disease, all diseases of the circulatory system, and all non-accidental causes during cold spells in the age group ≥ 65 years were 1.20 (95% CI: 1.11-1.29), 1.14 (1.08-1.20), and 1.12 (1.07-1.17), respectively. Cold spells were more harmful to the health of the residents of Murmansk, Archangelsk, and Magadan than heat waves, and only in Yakutsk, heat waves were more dangerous. The results of this study can help the public health authorities develop specific measures for the prevention of excess deaths during cold spells and heat waves in the exposed subarctic populations.

Analysis of vulnerability to heat in rural and urban areas in Spain: What factors explain Heat's geographic behavior?

INTRODUCTION

There is currently little knowledge and few published works on the subject of vulnerability to heat in rural environments at the country level. Therefore, the objective of this study was to determine whether rural areas are more vulnerable to extreme heat than urban areas in Spain. This study aimed to analyze whether a pattern of vulnerability depends on contextual, environmental, demographic, economic and housing variables.

METHODS

An ecological, longitudinal and retrospective study was carried out based on time series data between January 01, 2000 and December 31, 2013 in 42 geographic areas in 10 provinces in Spain. We first analyzed the functional relationship between the mortality rate per million inhabitants and maximum daily temperature (Tmax). We then determined the summer temperature threshold (Pthreshold) (June-September) at which increases in mortality are produced that are attributable to heat. In a second phase, based on Pthreshold, a vulnerability variable was calculated, and its distribution was analyzed using mixed linear models from the Poisson family (link = log). In these models, the dependent variable was vulnerability, and the independent variables were exposure to high temperatures, aridity of the climate, deprivation index, percentage of people over age 65, rurality index, percentage of housing built prior to 1980 and condition of dwellings.

RESULTS

Rurality was a protective factor, and vulnerability in urban areas was six times greater. In contrast, risk factors included aridity (RR = 5.89 (2.26 15.36)), living in cool summer zones (2.69 (1.23, 5.91)), poverty (4.05 (1.91 8.59)) and the percentage of dysfunctional housing (1.13 (1.04 1.24)).

CONCLUSIONS

Rural areas are less vulnerable to extreme heat than the urban areas analyzed. Also, population groups with worse working conditions and higher percentages of dwellings in poor conditions are more vulnerable.

Trends in Excess Winter Mortality (EWM) from 1900/01 to 2019/20-Evidence for a Complex System of Multiple Long-Term Trends

Trends in excess winter mortality (EWM) were investigated from the winter of 1900/01 to 2019/20. During the 1918-1919 Spanish flu epidemic a maximum EWM of 100% was observed in both Denmark and the USA, and 131% in Sweden. During the Spanish flu epidemic in the USA 70% of excess winter deaths were coded to influenza. EWM steadily declined from the Spanish flu peak to a minimum around the 1960s to 1980s. This decline was accompanied by a shift in deaths away from the winter and spring, and the EWM calculation shifted from a maximum around April to June in the early 1900s to around March since the late 1960s. EWM has a good correlation with the number of estimated influenza deaths, but in this context influenza pandemics after the Spanish flu only had an EWM equivalent to that for seasonal influenza. This was confirmed for a large sample of world countries for the three pandemics occurring after 1960. Using data from 1980 onward the effect of influenza vaccination on EWM were examined using a large international dataset. No effect of increasing influenza vaccination could be discerned; however, there are multiple competing forces influencing EWM which will obscure any underlying trend, e.g., increasing age at death, multimorbidity, dementia, polypharmacy, diabetes, and obesity-all of which either interfere with vaccine effectiveness or are risk factors for influenza death. After adjusting the trend in EWM in the USA influenza vaccination can be seen to be masking higher winter deaths among a high morbidity US population. Adjusting for the effect of increasing obesity counteracted some of the observed increase in EWM seen in the USA. Winter deaths are clearly the outcome of a complex system of competing long-term trends.

The effects of maximum ambient temperature and heatwaves on dengue infections in the tropical city-state of Singapore - A time series analysis

BACKGROUND

Global incidence of dengue has surged rapidly over the past decade. Each year, an estimated 390 million infections occur worldwide, with Asia-Pacific countries bearing about three-quarters of the global dengue disease burden. Global warming may influence the pattern of dengue transmission. While previous studies have shown that extremely high temperatures can impede the development of the Aedes mosquito, the effect of such extreme heat over a sustained period, also known as heatwaves, has not been investigated in a tropical climate setting.

AIM

We examined the short-term relationships between maximum ambient temperature and heatwaves and reported dengue infections in Singapore, via ecological time series analysis, using data from 2009 to 2018.

METHODS

We studied the effect of two measures of extreme heat - (i) heatwaves and (ii) maximum ambient temperature. We used a negative binomial regression, coupled with a distributed lag nonlinear model, to examine the immediate and lagged associations of extreme temperature on dengue infections, on a weekly timescale. We adjusted for long-term trend, seasonality, rainfall and absolute humidity, public holidays and autocorrelation.

RESULTS

We observed an overall inhibitive effect of heatwaves on the risk of dengue infections, and a parabolic relationship between maximum temperature and dengue infections. A 1 °C increase in maximum temperature from 31 °C was associated with a 13.1% (Relative Risk (RR): 0.868, 95% CI: 0.798, 0.946) reduction in the cumulative risk of dengue infections over six weeks. Weeks with 3 heatwave days were associated with a 28.3% (RR: 0.717, 95% CI: 0.608, 0.845) overall reduction compared to weeks with no heatwave days. Adopting different heatwaves specifications did not substantially alter our estimates.

CONCLUSION

Extreme heat was associated with decreased dengue incidence. Findings from this study highlight the importance of understanding the temperature dependency of vector-borne diseases in resource planning for an anticipated climate change scenario.

Short-term effects of ambient temperature and pollutants on the mortality of respiratory diseases: A time-series analysis in Hefei, China

BACKGROUND

The air pollution has become an important environmental health problem due to its adverse health effect. The objective of this study was to investigate the effects of ambient temperature and pollutants on mortality of respiratory diseases (RD) in Hefei, China, a typical inland city.

METHODS

Nonlinear exposure-response dependencies and delayed effects of urban daily mean temperature (DMT) and pollutants were evaluated by distributed lag non-linear models (DLNM). To further explore this effect, different genders and ages were also examined by stratified analysis.

RESULTS

A total of 12876 deaths from RD were collected from January 1, 2014 to December 31, 2018 in Hefei, China. There was a U-shaped correlation between DMT and RD mortality, and the RD mortality rised by 11.6% (95% CI: 2.2-22.0%) when the DMT was 35.8 °C (reference temperature is 20 °C). The results show that risk of death with short-term exposure to elevated concentrations of PM₁₀ and SO₂ was not significant. The maximum hysteresis and cumulative relative risk (RR) of RD mortality were 1.012 (95% CI: 1.003 ~ 1.021, lag 0 day) and 1.072 (95% CI: 1.014 ~1.133, lag 10 days) for each 10 μg/m³ augment in NO₂; 1.005 (95% CI: 1.001-1.009, lag 0 day) and 1.027 (95% CI: 1.004-1.051, lag 10 days) for each 10 μg/m³ augment in O_3; a negative association between CO exposure and the cumulative risk of death was observed (RR = 0.964, 95% CI: 0.935-0.993, lag 07 days). Subgroup analysis showed the effect of high temperatures, NO_2, O₃ and CO exposure was still statistically significant for the elderly and male.

CONCLUSION

The present study found that short-term exposure to high temperature, NO_2, O₃ and CO were significantly associated with the risk of RD mortality and male as well as elderly are more susceptible to these factors.

Systematic review of ambient temperature exposure during pregnancy and stillbirth: Methods and evidence

BACKGROUND

Associations between ambient temperature exposure during pregnancy and stillbirth have been reviewed and described in the literature. However, there is no existing review of environmental and epidemiologic methods applied to measure stillbirths resulting from exposure to ambient temperatures during pregnancy. The objective of this study is to systematically review published methods, data sources, and data linkage practices to characterize associations between ambient temperature and stillbirth to inform stillbirth prevention and risk management strategies.

METHODS

A systematic review of published studies that assess the association between ambient temperature exposure during pregnancy using any measures or approach and stillbirth was undertaken in Cochrane Library, PubMed, Medline, Scopus, Embase, and Web of Science of studies (2000-2020, inclusive). Selection of studies were assessed by pre-specified eligibility criteria and documented using PRISMA. Citations were managed using EndNote X8 whilst selection, reviewing, and data extraction were performed using Covidence. The screening, selection, and data extraction process consisted of two blind, independent reviews followed by a tertiary independent review. An adapted Critical Appraisal Skills Program (CASP) checklist was used to assess quality and bias. The main findings and characteristics of all studies was extracted and summarized. Where appropriate, a meta-analysis will be performed for measures of association.

RESULTS

Among 538 original records, 12 eligible articles were identified that analysed associations between ambient temperature exposure and stillbirth for 42,848 stillbirths among 3.4 million births across seven countries. Varied definitions of stillbirth were reported based on gestational age, birthweight, both, or neither. The overall rate of stillbirth ranged from 1.9 to 38.4 per 1000 among six high-income countries and one low-middle-income country. All study designs were retrospective and included ten cohort studies, three case-crossover studies, and two additional case-control subgroup analysis. Exposure data for ambient temperature was mostly derived from standard municipal or country-level monitors based on weather stations (66.6%) or a forecasting model (16.7%); otherwise, not reported (16.7%). Results were not statistically pooled for a meta-analysis due to heterogeneity of methods and models among included studies. All studies reported associations of increased risk of stillbirth with ambient temperature exposures throughout pregnancy, particularly in late pregnancy. One study estimates 17-19% (PAR) of stillbirths are potentially attributable to chronic exposure to hot and cold ambient temperatures during pregnancy. Overall, risk of stillbirth was observed to increase below 15 °C and above 23.4 °C, where highest risk is above 29.4 °C.

CONCLUSION

Exposure to hot and cold temperatures during pregnancy may increase the risk of stillbirth, although a clear causative mechanism remains unknown. Despite lack of causal evidence, existing evidence across diverse settings observed similar effects of increased risk of stillbirth using a variety of statistical and methodological approaches for exposure assessments, exposure windows, and data linkage. Managing exposure to ambient temperatures during pregnancy could potentially decrease risk of stillbirth, particularly among women in low-resource settings where access to safe antenatal and obstetric care is challenging. To fully understand the effects or dose-response relationship of maternal exposure to ambient temperatures and stillbirth, future studies should focus on biological mechanisms and contributing factors in addition to improving measurement of ambient temperature exposure.

An Exploratory Study of the Association between Housing Price Trends and Antidepressant Use in Taiwan: A 10-Year Population-Based Study

This study examined the relationship between various economic indexes and incidences of antidepressant prescriptions during 2001-2011 using the National Health Insurance Research Database (NHIRD). As of 2007, approximately 98.4% of Taiwanese people were enrolled in the NHIRD. In total, 531,281 records identified as antidepressant prescriptions were collected. Furthermore, 2556 quarterly observations from the Taiwan Housing Index (THI) and Executive Yuan were retrieved. We examined the association between the housing index and antidepressant prescription incidence. During the 10-year follow-up period, a higher incidence of antidepressant prescriptions was associated with the local maximum housing index. The relative risk of being prescribed antidepressant increased by 13.3% (95% confidence interval (CI): 1.01~1.27) when the THI reached a peak. For the low-income subgroup, the relative risk of being prescribed antidepressants increased by 28% during the high season of the THI. We also stratified the study sample on the basis of their sex, age, and urbanization levels. Both sexes followed similar patterns. During 2001-2011, although rising economic indexes may have increased incomes and stimulated the housing market, the compromise of public mental health could be a cost people have to pay additional attention to.

Analysis of the impact of heat waves on daily mortality in urban and rural areas in Madrid

The objective of this study was to analyze and compare the effect of high temperatures on daily mortality in the urban and rural populations in Madrid. Data were analyzed from municipalities in Madrid with a population of over 10,000 inhabitants during the period from January 1, 2000 to December 31, 2020. Four groups were generated: Urban Metropolitan Center, Rural Northern Mountains, Rural Center, and Southern Rural. The dependent variable used was the rate of daily mortality due to natural causes per million inhabitants (CIE-X: A00-R99) between the months of June and September for the period. The primary independent variable was maximum daily temperature. Social and demographic "context variables" were included: population >64 years of age (%), deprivation index and housing indicators. The analysis was carried out in three phases: 1) determination of the threshold definition temperature of a heat wave (Tumbral) for each study group; 2) determination of relative risks (RR) attributable to heat for each group using Poisson linear regression (GLM), and 3) calculation of odds ratios (OR) using binomial family GLM for the frequency of the appearance of heat waves associated with context variables. The resulting percentiles (for the series of maximum daily temperatures for the summer months) corresponding to Tthreshold were: 74th percentile for Urban Metropolitan Center, 76th percentile for Southern Rural, 83rd for Rural Northern Mountains and 98th percentile for Center Rural (98). Greater vulnerability was found for the first two. In terms of context variables that explained the appearance of heat waves, deprivation index level, population >64 years of age and living in the metropolitan area were found to be risk factors. Rural and urban areas behaved differently, and socioeconomic inequality and the composition of the population over age 64 were found to best explain the vulnerability of the Rural Center and Southern Rural zones.

The effect of cold waves on daily mortality in districts in Madrid considering sociodemographic variables

While there is much research that focuses on the association between cold waves and their impacts on daily mortality at the city level, few analyze the impact related to social context and demographic variables at levels lower than the municipal. The objective of this study was to determine the role of the percentage of people over age 65, income level and percentage of homes without heating in the analysis of the impact of cold waves on daily mortality between January 1, 2010 and December 31, 2013 in different districts of the municipality of Madrid. We calculated Relative Risks (RR) and Attributable Risks (RA) for each of 17 districts to determine correlations between the effect of cold waves and daily mortality due to natural causes (CIEX: A00-R99) using Generalized Linear Models (GLM) of the Poisson family (link log). The pattern of risks obtained by district was analyzed using binomial family models (link logit), considering socioeconomic and demographic variables. In terms of results, an impact of cold on mortality was detected in 9 of the 17 districts analyzed. The analysis of risk patterns revealed that the probability of detecting an impact in a district increases in a statistically significant way (p-value <0.05) with a higher percentage of homes without heating systems and a higher percentage of population over age 65. The results obtained identify the factors that should be considered in public health policies that target the district level to reduce the impact of cold waves.

The evolution of minimum mortality temperatures as an indicator of heat adaptation: The cases of Madrid and Seville (Spain)

The increase in the frequency and intensity of heat waves is one of the most unquestionable effects of climate change. Therefore, the progressive increase in maximum temperatures will have a clear incidence on the increase in mortality, especially in countries that are vulnerable due to geographical location or their socioeconomic characteristics. Different research studies show that the mortality attributable to heat is decreasing globally, and research is centred on future scenarios. One way of detecting the existence of a lesser impact of heat is through the increase in the so-called temperature of minimum mortality (TMM). The objective of this study is to determine the temporal evolution of TMM in two Spanish provinces (Seville and Madrid) during the 1983-2018 period and to evaluate whether the rate of adaptation to heat is appropriate. We used the gross rate of daily mortality due to natural causes (CIEX: A00-R99) and the maximum daily temperature (°C) to determine the quinquennial TMM using dispersion diagrams and realizing fit using quadratic and cubic curvilinear estimation. The same analysis was carried out at the annual level, by fitting an equation to the line of TMM for each province, whose slope, if significant (p < 0.05) represents the annual rate of variation in TMM. The results observed in this quinquennial analysis showed that the TMM is higher in Seville than in Madrid and that it is higher among men than women in the two provinces. Furthermore, there was an increase in TMM in all of the quinquennium and a clear decrease in the final period. At the annual level, the linear fit was significant for Madrid for the whole population and corresponds to an increase in the TMM of 0.58 °C per decade. For Seville the linear fits were significant and the slopes of the fitted lines was 1.1 °C/decade. Both Madrid and Seville are adapting to the increase in temperatures observed over the past 36 years, and women are the group that is more susceptible to heat, compared to men. The implementation of improvements and evaluation of prevention plans to address the impact of heat waves should continue in order to ensure adequate adaptation in the future.

Association between extreme heat and hospital admissions for cataract patients in Hefei, China

Cataract is the first cause of blindness and the major cause of visual impairment worldwide. Under conditions of global warming, researchers have begun to give attention to the influence of increasing temperature on cataract patients. Our paper aimed to investigate the association between extreme heat and hospital admissions for cataract in Hefei, China. Based on data from the New Rural Cooperative Medical System and National Meteorological Information Center, we used a generalized additive model and a distributed lag nonlinear model to examine the relationship between extreme heat and hospitalizations for cataract, with consideration of cumulative and lagged effects. When current mean temperature was above 28 °C, each 1 °C rise was associated with a 4% decrease in the number of cataract admissions (RR = 0.96, 95% CI = 0.94-0.98). The cumulative relative risk over 11 days of lag was the lowest, which indicated that every 1 °C increase in mean temperature above 28 °C was associated with a 19% decrease in the number of hospital admissions for cataract (RR = 0.81, 95% CI = 0.75-0.88). In subgroup analyses, the negative association between extreme heat and hospital admissions for cataract was stronger among patients who were not admitted to provincial-level hospitals. In conclusion, this paper found that extreme heat was negatively associated with cataract hospitalizations in Hefei, providing useful information for hospitals and policymakers.

Monitoring Large-Scale Inland Water Dynamics by Fusing Sentinel-1 SAR and Sentinel-3 Altimetry Data and by Analyzing Causal Effects of Snowmelt

The warming climate is threatening to alter inland water resources on a global scale. Within all waterbody types, lake and river systems are vital not only for natural ecosystems but, also, for human society. Snowmelt phenology is also altered by global warming, and snowmelt is the primary water supply source for many river and lake systems around the globe. Hence, (1) monitoring snowmelt conditions, (2) tracking the dynamics of snowmelt-influenced river and lake systems, and (3) quantifying the causal effect of snowmelt conditions on these waterbodies are critical to understand the cryo-hydrosphere interactions under climate change. Previous studies utilized in-situ or multispectral sensors to track either the surface areas or water levels of waterbodies, which are constrained to small-scale regions and limited by cloud cover, respectively. On the contrary, in the present study, we employed the latest Sentinel-1 synthetic aperture radar (SAR) and Sentinel-3 altimetry data to grant a high-resolution, cloud-free, and illumination-independent comprehensive inland water dynamics monitoring strategy. Moreover, in contrast to previous studies utilizing in-house algorithms, we employed freely available cloud-based services to ensure a broad applicability with high efficiency. Based on altimetry and SAR data, the water level and the water-covered extent (WCE) (surface area of lakes and the flooded area of rivers) can be successfully measured. Furthermore, by fusing the water level and surface area information, for Lake Urmia, we can estimate the hypsometry and derive the water volume change. Additionally, for the Brahmaputra River, the variations of both the water level and the flooded area can be tracked. Last, but not least, together with the wet snow cover extent (WSCE) mapped with SAR imagery, we can analyze the influence of snowmelt conditions on water resource variations. The distributed lag model (DLM) initially developed in the econometrics discipline was employed, and the lagged causal effect of snowmelt conditions on inland water resources was eventually assessed.

Intensity-duration-frequency relationship of WBGT extremes using regional frequency analysis in South Korea

The risk levels of heat-related extreme events need to be estimated for prediction and real-time monitoring to mitigate their impacts on air quality, public health, the ecosystem, and critical infrastructure. Many countries have adopted meteorological variable base thresholds for assessing the risk level of heat-related extreme events. These thresholds provide an approximate risk level for a specific event but do not consider its intensity and duration in the risk assessment. The current study provides a statistical tool to assess the risk of heat-related extreme events while concurrently considering their intensities and durations based on the wet-bulb globe temperature (WBGT). To this end, the intensity-duration-frequency (IDF) relationship of the extreme WBGT in South Korea was derived. Regional frequency analysis was employed to understand the IDF relationship. Return levels of heat-related extreme events in South Korea were calculated and their characteristics were investigated based on the annual maximum WBGT observations. The results showed that the IDF relationship could provide the risks of heat-related extreme events while concurrently considering their intensities and durations. The extreme WBGT in South Korea was used to categorize two regions such as coastal and inland based on their statistical characteristics. The return levels of the annual maximum WBGT events were found to vary largely by location. The return levels corresponding to 32 °C with 3-h duration for stations in the coastal and inland regions ranged from 1- to 100-years and 3- to 1000-years, respectively. Mean values of return levels for heatwave events in Seoul, Incheon, Daejon, Gwangju, Daegu, and Busan were 2.8-, 8.4-, 15.3-, 2.8-, 1.6-, and 2.2-years, respectively. The return levels of heatwaves for the warmer cities are smaller than those for cooler cities. The return levels of the heatwave events in South Korea showed a significant increasing trend in several cities, supporting the notion that the impact of heatwave events on South Korea might become more severe in the future.

Impact of Foehn Wind and Related Environmental Variables on the Incidence of Cardiac Events

In Poland there is no data related to the impact of halny wind and the related environmental variables on the incidence of cardiac events. We decided to investigate the relationship between this weather phenomenon, as well as the related environmental variables, and the incidence of cardiac events in the population of southern Poland, a region affected by this type of wind. We also decided to determine whether the environmental changes coincide with or predate the event examined. We analysed data related to 465 patients admitted to the cardiology ward in a large regional hospital during twelve months of 2011 due to acute myocardial infarction. All the patients in the study group lived in areas affected by halny wind and at the time of the event were staying in those areas. The frequency of admissions on halny days did not differ significantly from the admissions on the remaining days of the year (p = 0.496). No statistically significant differences were found between the number of admissions on halny days and on the remaining days during halny months (p = 0.084). We have identified a difference in the number of admissions between days with no halny and days immediately preceding onset of halny (p = 0.001). However, no effects of the related environmental variables have been observed in the incidence of cardiac events (p = 0.866, F = 0.37). On the days with halny wind, incidence of cardiac events is similar to that on the remaining days of the year.

Impacts of climate change on the public health of the Mediterranean Basin population - Current situation, projections, preparedness and adaptation

The Mediterranean Basin is undergoing a warming trend with longer and warmer summers, an increase in the frequency and the severity of heat waves, changes in precipitation patterns and a reduction in rainfall amounts. In this unique populated region, which is characterized by significant gaps in the socio-economic levels particularly between the North (Europe) and South (Africa), parallel with population growth and migration, increased water demand and forest fires risk - the vulnerability of the Mediterranean population to human health risks increases significantly. Indeed, climatic changes impact the health of the Mediterranean population directly through extreme heat, drought or storms, or indirectly by changes in water availability, food provision and quality, air pollution and other stressors. The main health effects are related to extreme weather events (including extreme temperatures and floods), changes in the distribution of climate-sensitive diseases and changes in environmental and social conditions. The poorer countries, particularly in North Africa and the Levant, are at highest risk. Climate change affects the vulnerable sectors of the region, including an increasingly older population, with a larger percentage of those with chronic diseases, as well as poor people, which are therefore more susceptible to the effects of extreme temperatures. For those populations, a better surveillance and control systems are especially needed. In view of the climatic projections and the vulnerability of Mediterranean countries, climate change mitigation and adaptation become ever more imperative. It is important that prevention Health Action Plans will be implemented, particularly in those countries that currently have no prevention plans. Most adaptation measures are "win-win situation" from a health perspective, including reducing air pollution or providing shading solutions. Additionally, Mediterranean countries need to enhance cross-border collaboration, as adaptation to many of the health risks requires collaboration across borders and also across the different parts of the basin.

Ambient temperature and non-accidental mortality: a time series study

Under the background of global climate change, the present study aimed to evaluate the effects of daily mean temperature and diurnal temperature range (DTR) on the non-accidental mortality. Poisson generalized linear model (PGLM) combined with distributed lag non-linear model (DLNM) was used to evaluate these effects after adjusting the relative humidity and major air pollutants. All effects were presented as relative risk (RR), with 75th percentiles of daily mean temperature and DTR compare with their lowest RRs corresponding values. Daily mean temperature was associated with the non-accidental mortality with a U-shaped curve, and the non-accidental mortality increased by 1.8% (95% CI: 0.7~3.0%) when the temperature was 24.4 °C (20 °C as the reference). Additionally, the non-accidental mortality increased by 1.4% (95% CI: 0.1~2.7%) on lag6 day when DTR was 11.3 °C (7 °C as the reference). The elderly (≥ 65 years) were more susceptible to daily mean temperature and DTR, and females were more susceptible to high DTR effect than males. Our study provides evidence that daily mean temperature and DTR are significantly associated with non-accidental mortality and have delayed effects. Both females and elderly people are vulnerable to the potential adverse effects.

Heatwave Events and Mortality Outcomes in Memphis, Tennessee: Testing Effect Modification by Socioeconomic Status and Urbanicity

Heatwave studies typically estimate heat-related mortality and morbidity risks at the city level; few have addressed the heterogeneous risks by socioeconomic status (SES) and location within a city. This study aimed to examine the impacts of heatwaves on mortality outcomes in Memphis, Tennessee, a Mid-South metropolitan area top-ranked in morbidity and poverty rates, and to investigate the effects of SES and urbanicity. Mortality data were retrieved from the death records in 2008-2017, and temperature data from the Applied Climate Information System. Heatwave days were defined based on four temperature metrics. Heatwave effects on daily total-cause, cardiovascular, and respiratory mortality were evaluated using Poisson regression, accounting for temporal trends, sociodemographic factors, urbanicity, and air pollution. We found higher cardiovascular mortality risk (cumulative RR (relative risk) = 1.25, 95% CI (confidence interval): 1.01-1.55) in heatwave days defined as those with maximum daily temperature >95th percentile for more than two consecutive days. The effects of heatwaves on mortality did not differ by SES, race, or urbanicity. The findings of this study provided evidence to support future heatwave planning and studies of heatwave and health impacts at a coarser geographic resolution.

Estimating personal ambient temperature in moderately cold environments for occupationally exposed populations

Despite high mortality and morbidity rates in the winter season, few studies have investigated the health effects from working in moderately cold environments, especially among vulnerable outdoor worker populations in the southeastern US. Yet recent research has shown that the mortality risk from cold events is greatest in southern cities compared to other US locations. We performed repeated personal cold exposure measurements in outdoor grounds management workers in the southeastern US using consumer-based sensors. We recruited outdoor workers from two locations (Raleigh, NC and Boone, NC) each characterized by climatological differences in cold temperature to participate in a 3-week data collection period at the peak of the winter (Jan/Feb 2018). Lower personal ambient temperatures were observed among participants who worked in a warmer climate (Raleigh, NC). The relative risk for cold symptomatology was higher in moderately cold personal ambient temperatures (0 °C to 20 °C) than extremely cold personal ambient temperatures (less than 0 °C). A weak significant relationship was observed between personal ambient temperatures and weather station measurements highlighting that epidemiological researchers should be cautious when investigating the health effects of ambient temperatures based on fixed site measurements. As mobile technology progresses, real-time temperature health monitoring and analysis of environmental conditions at the individual level across multiple occupational-settings will become more feasible and ultimately, we believe, a digitally enhanced workforce will become standard practice in the field.

The Mortality Response to Absolute and Relative Temperature Extremes

While the impact of absolute extreme temperatures on human health has been amply studied, far less attention has been given to relative temperature extremes, that is, events that are highly unusual for the time of year but not necessarily extreme relative to a location's overall climate. In this research, we use a recently defined extreme temperature event metric to define absolute extreme heat events (EHE) and extreme cold events (ECE) using absolute thresholds, and relative extreme heat events (REHE) and relative extreme cold events (RECE) using relative thresholds. All-cause mortality outcomes using a distributed lag nonlinear model are evaluated for the largest 51 metropolitan areas in the US for the period 1975-2010. Both the immediate impacts and the cumulative 20-day impacts are assessed for each of the extreme temperature event types. The 51 metropolitan areas were then grouped into 8 regions for meta-analysis. For heat events, the greatest mortality increases occur with a 0-day lag, with the subsequent days showing below-expected mortality (harvesting) that decreases the overall cumulative impact. For EHE, increases in mortality are still statistically significant when examined over 20 days. For REHE, it appears as though the day-0 increase in mortality is short-term displacement. For cold events, both relative and absolute, there is little mortality increase on day 0, but the impacts increase on subsequent days. Cumulative impacts are statistically significant at more than half of the stations for both ECE and RECE. The response to absolute ECE is strongest, but is also significant when using RECE across several southern locations, suggesting that there may be a lack of acclimatization, increasing mortality in relative cold events both early and late in winter.

Ambient temperature and solar insolation are associated with decreased prevalence of SSRI-treated psychiatric disorders

Serotonergic function is known to fluctuate in association with light and temperature. Serotonin-related behaviors and disorders similarly vary with climatic exposure, but the associations are complex. This complexity may reflect the importance of dose and timing of exposure, as well as acclimation. This cross-sectional study tests how average climate exposures (ambient temperature and solar insolation) vary with the prevalence of a group of SSRI-treated disorders. For comparison, we similarly studied a group of disorders not treated by SSRIs (i.e substance use disorders). Psychiatric prevalence data were obtained from the Collaborative Psychiatric Epidemiology Surveys (CPES). Average yearly solar insolation was obtained from NASA's NLDAS-2 Forcing Dataset Information. Average yearly temperature was obtained from NOAA's US Climate Normals. Logistic regression models were generated to assess the relationship between these two climatic factors and the prevalence of SSRI-treated and substance use disorders. Age, gender, race, income, and education were included in the models to control for possible confounding. Temperature and insolation were significantly associated with the SSRI-responsive group. For an average 1 GJ/m²/year increase, OR was 0.90 (95% CI 0.85-0.96, p = 0.001), and for an average 10 °F increase, OR was 0.93 (95% CI 0.88-0.97, p = 0.001). This relationship was not seen with substance use disorders (insolation OR: 0.97, p = 0.682; temperature OR: 0.96, p = 0.481). These results warrant further investigation, but they support the hypothesis that chronic exposure to increased temperature and light positively impact serotonin function, and are associated with reduced prevalence of some psychiatric disorders. They also support further investigation of light and hyperthermia treatments.

The influence of extreme cold events on mortality in the United States

Many studies have analyzed the effects of extreme heat on human mortality, however fewer studies have focused on the effects of cold related mortality due to the complicated nature of the lagged response. This study utilized a Distributed Lag Non-Linear Model with a 30-day lag to determine the cumulative effects of extreme cold events (ECEs) on mortality across 32 cities in the United States for the period of 1975-2010. ECEs were divided into specific categories based on duration, magnitude, and timing of occurrence. Mortality was divided into all-age mortality as well as mortality of individuals >64 years old. The findings suggest a strong relationship between a city's latitude as well as the timing of an ECE with mortality. Early season ECEs result in a much higher relative risk of increased mortality, particularly in cities with higher mean winter temperatures, while the RR of mortality of individuals >64 was consistently higher for each city. This study suggests early season ECEs should receive enhanced preparedness efforts as individuals may be particularly vulnerable when not acclimatized to extreme cold.

Extreme temperature and mortality: evidence from China

The frequency, intensity, and duration of extreme temperature events are expected to rise in the future and increase the related health risks of human beings. Using a novel, nationwide dataset that links extreme temperature and mortality, we estimated the short-term and long-term effects of extreme temperature on mortality in China during 2002-2013. Both extreme hot and extreme cold had immediate and long-term effects on all-cause mortality. Annual deaths per 100,000 people due to extreme hot and cold in the long term were considerably larger compared to the short term. The change in cold spell duration indicator exhibited the greatest effects on annual deaths per 100,000 people among a set of extreme weather indicators. Furthermore, cities with low economic development levels were more vulnerable to extreme temperature, compared to cities with high economic development levels. Our results offer important policy implications for developing a regional-specific extreme weather plan to handle extreme temperature events in China.

The effect of ambient temperature on the activity of influenza and influenza like illness in Jiangsu Province, China

OBJECTIVE

We aimed to evaluate and quantify the association between ambient temperature and activity of influenza like illness (ILI) and influenza in Jiangsu Province, China.

METHOD

Daily data of meteorology, influenza-like illness and detected influenza virus from 1 April 2013 to 27 March 2016 were collected. Distributed lag non-linear model (DLNM) was used to quantify the exposure-lag-response of ILI and influenza activity to daily average temperature.

RESULT

Influenza A virus (Flu-A) circulated throughout the year with two peaks at -4 °C and 28 °C respectively, while influenza B (Flu-B) viruses were usually tested positive in winter or early spring and peaked at 5 °C. The lag-response curves revealed that the RR of ILI increased with time and peaked 1 day later at low temperature (3 °C), however, the maximum RR of ILI caused by high temperature (26 °C) appeared immediately on day 0, the similar phenomena of immediate effect to ILI at high temperature were also observed in the lag-response curve for Flu-A or Flu-B.

CONCLUSION

ILI and Flu-A experienced two peaks of circulates at both low and high temperature in Jiangsu. The influenza viruses activity did drive up the rising of ILI%, particularly the activity of Flu-A which circulated throughout the year played a crucial role. Regional homogeneity was the relatively mainstream in aspects of cumulative association between influenza activity and temperature in Jiangsu Province.

Where are weather-suicide associations valid? An examination of nine US counties with varying seasonality

There has been much research on the associations between weather variables and suicide rates. However, the state of understanding has remained rather stagnant due to many contradictory findings. The purpose of this project is to examine a larger database of suicides that includes a longer and more recent period of record (1975-2010) across numerous locations in the USA. In all, we examine nine total counties (and the primary city associated with them) with a special effort made to compare locations with varying degrees of temperature seasonality: Cook (Chicago), Fulton (Atlanta), King (Seattle), Los Angeles (Los Angeles), Maricopa (Phoenix), Miami-Dade (Miami), Philadelphia (Philadelphia), Salt Lake (Salt Lake City), and St. Louis (St. Louis). We first examine the unique seasonal cycle in suicides evident in each locale and then use distributed lag nonlinear modeling (DLNM) to relate the suicide data to daily surface temperatures. Results suggest that a late spring/summer peak generally exists in suicide rates, and above average temperatures are associated with increased suicide risk in almost all study counties. Further, it appears that these associations can be found in both mid-latitude and sub-tropical climate types.

The effects of hot nights on mortality in Barcelona, Spain

Heat-related effects on mortality have been widely analyzed using maximum and minimum temperatures as exposure variables. Nevertheless, the main focus is usually on the former with the minimum temperature being limited in use as far as human health effects are concerned. Therefore, new thermal indices were used in this research to describe the duration of night hours with air temperatures higher than the 95% percentile of the minimum temperature (hot night hours) and intensity as the summation of these air temperatures in degrees (hot night degrees). An exposure-response relationship between mortality due to natural, respiratory, and cardiovascular causes and summer night temperatures was assessed using data from the Barcelona region between 2003 and 2013. The non-linear relationship between the exposure and response variables was modeled using a distributed lag non-linear model. The estimated associations for both exposure variables and mortality shows a relationship with high and medium values that persist significantly up to a lag of 1-2 days. In mortality due to natural causes, an increase of 1.1% per 10% (CI95% 0.6-1.5) for hot night hours and 5.8% per each 10° (CI95% 3.5-8.2%) for hot night degrees is observed. The effects of hot night hours reach their maximum with 100% and lead to an increase by 9.2% (CI95% 5.3-13.1%). The hourly description of night heat effects reduced to a single indicator in duration and intensity is a new approach and shows a different perspective and significant heat-related effects on human health.