Modeling exposure-lag-response associations with distributed lag non-linear models

Private vs. public emergency visits for mental health due to heat: An indirect socioeconomic assessment of heat vulnerability and healthcare access, in Curitiba, Brazil

Few studies have explored the influence of socioeconomic status (SES) on the heat vulnerability of mental health (MH) patients. As individual socioeconomic data was unavailable, we aimed to fill this gap by using the healthcare system type as a proxy for SES. Brazilian national statistics indicate that public patients have lower SES than private. Therefore, we compared the risk of emergency department visits (EDVs) for MH between patients from both healthcare types. EDVs for MH disorders from all nine public (101,452 visits) and one large private facility (154,954) in Curitiba were assessed (2017-2021). Daily mean temperature was gathered and weighed from 3 stations. Distributed-lag non-linear model with quasi-Poisson (maximum 10-lags) was used to assess the risk. We stratified by private and public, age, and gender under moderate and extreme heat. Additionally, we calculated the attributable fraction (AF), which translates individual risks into population-representative burdens - especially useful for public policies. Random-effects meta-regression pooled the risk estimates between healthcare systems. Public patients showed significant risks immediately as temperatures started to increase. Their cumulative relative risk (RR) of MH-EDV was 7.5 % higher than the private patients (Q-Test 26.2 %) under moderate heat, suggesting their particular heat vulnerability. Differently, private patients showed significant risks only under extreme heat, when their RR became 4.3 % higher than public (Q-Test 6.2 %). These findings suggest that private patients have a relatively greater adaptation capacity to heat. However, when faced with extreme heat, their current adaptation means were potentially insufficient, so they needed and could access healthcare freely, unlike their public counterparts. MH patients would benefit from measures to reduce heat vulnerability and access barriers, increasing equity between the healthcare systems in Brazil. AF of EDVs due to extreme heat was 0.33 % (95%CI 0.16;0.50) for the total sample (859 EDVs). This corroborates that such broad population-level policies are urgently needed as climate change progresses.

Maternal PM2.5 exposure and hypospadias risk in Chinese offspring: Insights from a nationwide surveillance-based study

Research on the association between maternal PM2.5 exposure and hypospadias risk in male offspring, particularly in highly polluted areas, has been limited and inconsistent. This study leveraged data from China's National Population-based Birth Defects Surveillance System spanning the years 2013 to 2019, and employed sophisticated machine learning models to estimate daily PM2.5 levels and other pollutants for mothers at a 1-km resolution and a 6-km buffer surrounding maternal residences. Multivariate logistic regression analyses were performed to evaluate the relationship between PM2.5 exposure and hypospadias risk. For sensitivity analyses, stratification analysis was conducted, and models for one-pollutant and two-pollutants, as well as distributed lag nonlinear models, were constructed. Of the 1194,431 boys studied, 1153 cases of hypospadias were identified. A 10 μg/m3 increase in maternal PM2.5 exposure during preconception and the first trimester was associated with an elevated risk of isolated hypospadias, with Odds Ratios (ORs) of 1.102 (95% CI: 1.023-1.188) and 1.089 (95% CI: 1.007-1.177) at the 1-km grid, and 1.122 (95% CI: 1.034-1.218) and 1.143 (95% CI: 1.048-1.246) within the 6-km buffer. Higher quartiles of PM2.5 exposure were associated with increased odds ratios compared to the lowest quartile. These findings highlight a significant association between PM2.5 exposure during the critical conception period and an elevated risk of isolated hypospadias in children, emphasizing the need for targeted interventions to reduce PM2.5 exposure among expectant mothers.

Scaling features in high-concentrations PM2.5 evolution: the Ignored factor affecting scarlet fever incidence

As an acute respiratory disease, scarlet fever has great harm to public health. Some evidence indicates that the time distribution pattern of heavy PM2.5 pollution occurrence may have an impact on health risks. This study aims to reveal the relation between scaling features in high-concentrations PM2.5 (HC-PM2.5) evolution and scarlet fever incidence (SFI). Based on the data of Hong Kong from 2012 to 2019, fractal box-counting dimension (D) is introduced to capture the scaling features of HC-PM2.5. It has been found that index D can quantify the time distribution of HC-PM2.5, and lower D values indicate more cluster distribution of HC-PM2.5. Moreover, scale-invariance in HC-PM2.5 at different time scales has been discovered, which indicates that HC-PM2.5 occurrence is not random but follows a typical power-law distribution. Next, the exposure-response relationship between SFI and scale-invariance in HC-PM2.5 is explored by Distributed lag non-linear model, in conjunction with meteorological factors. It has been discovered that scale-invariance in HC-PM2.5 has a nonlinear effect on SFI. Low and moderate D values of HC-PM2.5 are identified as risk factors for SFI at small time-scale. Moreover, relative risk shows a decreasing trend with the increase of exposure time. These results suggest that exposure to short-term clustered HC-PM2.5 makes individual more prone to SFI than exposure to long-term uniform HC-PM2.5. This means that individuals in slightly-polluted regions may face a greater risk of SFI, once the PM2.5 concentration keeps rising. In the future, it is expected that the relative risk of scarlet fever for a specific region can be estimated based on the quantitative analysis of scaling features in high-concentrations PM2.5 evolution.

Determining critical periods for thermal acclimatisation using a distributed lag non-linear modelling approach

Rapid changes in thermal environments are threatening many species worldwide. Thermal acclimatisation may partially buffer species from the impacts of these changes, but currently, the knowledge about the temporal dynamics of acclimatisation remains limited. Moreover, acclimatisation phenotypes are typically determined in laboratory conditions that lack the variability and stochasticity that characterise the natural environment. Through a distributed lag non-linear model (DLNM), we use field data to assess how the timing and magnitude of past thermal exposures influence thermal tolerance. We apply the model to two Scottish freshwater Ephemeroptera species living in natural thermal conditions. Model results provide evidence that rapid heat hardening effects are dramatic and reflect high rates of change in temperatures experienced over recent hours to days. In contrast, temperature change magnitude impacted acclimatisation over the course of weeks but had no impact on short-term responses. Our results also indicate that individuals may de-acclimatise their heat tolerance in response to cooler environments. Based on the novel insights provided by this powerful modelling approach, we recommend its wider uptake among thermal physiologists to facilitate more nuanced insights in natural contexts, with the additional benefit of providing evidence needed to improve the design of laboratory experiments.

Delayed effects of air pollution on public bike-sharing system use in Seoul, South Korea: A time series analysis

BACKGROUND

As a complementary means to urban public transit systems, public bike-sharing provides a green and active mode of sustainable mobility, while reducing carbon-dioxide emissions and promoting health. There has been increasing interest in factors affecting bike-sharing usage, but little is known about the effect of ambient air pollution.

METHOD

To assess the short-term impact of daily exposure to multiple air pollutants (PM2.5, PM10, NO2, and O3) on the public bike-sharing system (PBS) usage in Seoul, South Korea (2018-2021), we applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM). The model was adjusted for day of the week, holiday, temperature, relative humidity, and long-term trend. We also conducted stratification analyses to examine the potential effect modification by age group, seasonality, and COVID-19.

RESULTS

We found that there was a negative association between daily ambient air pollution and the PBS usage level at a single lag day 1 (i.e., air quality a day before the event) across all four pollutants. Our results suggest that days with high levels of air pollutants (at 95th percentile) are associated with a 0.91% (0.86% to 0.96%) for PM2.5, 0.89% (0.85% to 0.94%) for PM10, 0.87% (0.82% to 0.91%) for O3, and 0.92% (0.87% to 0.98%) for NO2, reduction in cycling behavior in the next day compared to days with low levels of pollutants (at 25th percentile). No evidence of effect modification was found by seasonality, age nor the COVID-19 pandemic for any of the four pollutants.

CONCLUSIONS

Our findings suggest that high concentrations of ambient air pollution are associated with decreased rates of PBS usage on the subsequent day regardless of the type of air pollutant measured.

Short-term effects of temperature-related indices on emergency ambulance dispatches due to mental and behavioral disorders in Shenzhen, China

Introduction

The precise associations between temperature-related indices and mental and behavioral disorders (MBDs) have yet to be fully elucidated. Our study aims to ascertain the most effective temperature-related index and assess its immediate impact on emergency ambulance dispatches (EADs) due to MBDs in Shenzhen, China.

Methods

EADs data and meteorological data from January 1, 2013, to December 31, 2020, in Shenzhen were collected. Distributed lag non-linear models (DLNMs) were utilized to examine the non-linear and lagged effects of temperature-related indices on EADs due to MBDs. The Quasi Akaike Information criterion (QAIC) was used to determine the optimal index after standardizing temperature-related indices. After adjusting for confounding factors in the model, we estimated the immediate and cumulative effects of temperature on EADs due to MBDs.

Results

The analysis of short-term temperature effects on EADs due to MBDs revealed Humidex as the most suitable index. Referring to the optimal Humidex (3.2th percentile, 12.00°C), we observed a significant effect of Humidex over the threshold (34.6th percentile, 26.80°C) on EADs due to MBDs at lag 0-5. The cumulative relative risks for high temperature (90th percentile, 41.90°C) and extreme high temperature (99th percentile, 44.20°C) at lag 0-5 were 1.318 (95% CI: 1.159-1.499) and 1.338 (95% CI: 1.153-1.553), respectively. No significant cold effect was observed on EADs due to MBDs.

Conclusion

High Humidex was associated with more EADs due to MBDs in subtropical regions. Health authorities should implement effective measures to raise public awareness of risks related to high temperature and protect vulnerable populations.

Spatiotemporal distribution and lag effect of extreme temperature exposure on mortality of residents in Jiangsu, China

Background

With the ever-increasing occurrence of extreme weather events as a result of global climate change, the impact of extreme temperatures on human health has become a critical area of concern. Specifically, it is imperative to investigate the impact of extreme weather conditions on the health of residents.

Methods

In this study, we analyze the daily death data from 13 prefecture-level cities in Jiangsu Province from January 2014 to September 2022, using the distributed lag nonlinear model (DLNM) to comprehensively account for factors such as relative humidity, atmospheric pressure, air pollutants, and other factors to evaluate the lag and cumulative effects of extreme low temperature and high temperature on the death of residents across different age groups. Additionally, we utilize the Geographical Detector to analyze the effects of various meteorological and environmental factors on the distribution of resident death in Jiangsu Province. This provides valuable insights that can guide health authorities in decision-making and in the protection of residents.

Results

The experimental results indicate that both extreme low and high temperatures increase the mortality of residents. We observe that the impact of extreme low temperatures has a delayed effect, peaking after 3-5 days and lasting up to 11-21 days. In contrast, the impact of extreme high temperature is greatest on the first day, and lasts only 2-4 days.

Conclusion

Both extreme high and low temperatures increase the mortality of residents, with the former being more transient and stronger and the latter being more persistent and slower. Furthermore, residents over 75 years of age are more vulnerable to the effects of extreme temperatures. Finally, we note that the spatial distribution of resident deaths is most closely associated consistent with the spatial distribution of daily mean temperature, and there is significant spatial heterogeneity in deaths among residents in Jiangsu Province.

Floods and cause-specific mortality in the UK: a nested case-control study

BACKGROUND

Floods are the most frequent weather-related disaster, causing significant health impacts worldwide. Limited studies have examined the long-term consequences of flooding exposure.

METHODS

Flood data were retrieved from the Dartmouth Flood Observatory and linked with health data from 499,487 UK Biobank participants. To calculate the annual cumulative flooding exposure, we multiplied the duration and severity of each flood event and then summed these values for each year. We conducted a nested case-control analysis to evaluate the long-term effect of flooding exposure on all-cause and cause-specific mortality. Each case was matched with eight controls. Flooding exposure was modelled using a distributed lag non-linear model to capture its nonlinear and lagged effects.

RESULTS

The risk of all-cause mortality increased by 6.7% (odds ratio (OR): 1.067, 95% confidence interval (CI): 1.063-1.071) for every unit increase in flood index after confounders had been controlled for. The mortality risk from neurological and mental diseases was negligible in the current year, but strongest in the lag years 3 and 4. By contrast, the risk of mortality from suicide was the strongest in the current year (OR: 1.018, 95% CI: 1.008-1.028), and attenuated to lag year 5. Participants with higher levels of education and household income had a higher estimated risk of death from most causes whereas the risk of suicide-related mortality was higher among participants who were obese, had lower household income, engaged in less physical activity, were non-moderate alcohol consumers, and those living in more deprived areas.

CONCLUSIONS

Long-term exposure to floods is associated with an increased risk of mortality. The health consequences of flooding exposure would vary across different periods after the event, with different profiles of vulnerable populations identified for different causes of death. These findings contribute to a better understanding of the long-term impacts of flooding exposure.

Temporal changes in temperature-related mortality in relation to the establishment of the heat-health alert system in Victoria, Australia

Extreme heat alerts are the most common form of weather forecasting services used in Australia, yet very limited studies have documented their effectiveness in improving health outcomes. This study aimed to examine the temporal changes in temperature-related mortality in relation to the activation of the heat-health alert and response system (HARS) in the State of Victoria, Australia. We examined the relationship between temperatures and mortality using quasi-Poisson regression and the distributed lag non-linear model (dlnm) and compared the temperature-mortality association between the two periods: period 1- prior-HARS (1992-2009) and period 2- post-HARS (2010-2019). Since the HARS heavily weights heatwave effects, we also compared the main effects of heatwave events between the two periods. The heatwaves were defined for three levels, including 3 consecutive days at 97th, 98th, and 99th percentiles. We also controlled the potential confounding effect of seasonality by including a natural cubic B-spline of the day of the year with equally spaced knots and 8 degrees of freedom per year. The exposure-response curve reveals the temperature mortality was reduced in period 2 in comparison with period 1. The relative risk ratios (RRR) of Period 2 over Period 1 were all less than one and gradually decreased from 0.86 (95% CI, 0.72-1.03) to 0.64 (95% CI, 0.33-1.22), and the differences in attributable risk percent increased from 13.2 to 25.3%. The reduction in the risk of heatwave-related deaths decreased by 3.4% (RRp1 1.068, 95% CI, 1.024-1.112 versus RRp2 1.034, 95% CI, 0.986-1.082) and 10% (RRp1 1.16, 95% CI, 1.10-1.22 versus RRp2 1.06, 95% CI, 1.002-1.119) for all groups of people. The study indicated a decrease in heat-related mortality following the operation of HARS in Victoria under extreme heat and high-intensity heatwaves conditions. Further studies could investigate the extent of changes in mortality among populations of differing socio-economic groups during the operation of the heat-health alert system.

Windows of sensitivity for risk of adverse birth outcomes related to gestational PM2.5 exposure: Evidence from a natural experiment

While numerous studies have associated maternal exposure to PM2.5 with adverse birth outcomes, findings remain inconsistent and difficult to generalize. We aimed to investigate the causal relationship and window of sensitivity between gestational exposure to PM2.5 and birth outcomes. We leveraged high-resolution satellite data to quantify gestational PM2.5 exposure at the individual level, along with a combined model to determine daily relative risks (RRs) of birth outcomes in COVID-19 prelockdown and lockdown groups. RRs between the two groups were further compared using a longitudinal pre-post non-experimental design to identify sensitivity windows of adverse birth outcomes. A total of 73,781 pregnant women from the COVID-19 prelockdown group and 6267 pregnant women from the lockdown group were included for analysis. The daily mean PM2.5 concentrations in the lockdown group decreased by 21.7% compared to the prelockdown group. During the first trimester, every 10 μg/m3 increase in PM2.5 significantly increased the risk of congenital abnormalities of major organs such as the cardiovascular system, gastrointestinal tract, nervous system, urinary system, and respiratory system. Moreover, gestational exposure to PM2.5 during the first trimester was associated with higher risks of premature delivery and term low birth weight. While PM2.5 exposure during the second trimester was positively correlated with macrosomia. Gestational exposure to PM2.5 is associated with increased risks of various adverse birth outcomes with specific sensitive windows. We demonstrated that gestational exposure to PM2.5 increased risks of various adverse birth outcomes with specific window of sensitivity through the natural experiment design. Our findings underscore the urgent need for policies and initiatives targeting PM2.5 reduction, especially during critical periods of pregnancy.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States

BACKGROUND

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important.

METHODS

We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season.

RESULTS

For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods.

CONCLUSIONS

Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

Cardiovascular admission risk attributable to hot apparent temperature: a study in a rural area of northwest China

Cardiovascular disease (CVD) is the leading cause of mortality worldwide, posing a significant threat to public health. Research on the relationship between CVD and temperature has primarily focused on developed urban settings, with limited studies conducted in rural regions with lower levels of development. Additionally, compared to relative risks, attributable risks can provide more information when assessing the risk of CVD hospitalizations associated with exposure to apparent temperature (AT). Apparent temperature is a composite temperature index that takes into account both meteorological factors and temperature, providing an objective reflection of human thermal sensation. Therefore, this study investigates the impact of AT on CVD hospitalization and quantifies the burden of CVD admission in the rural areas of China. We employed the distributed lag non-linear model (DLNM) to estimate the relationship between AT and the relative risk (RR) of CVD hospitalization. Finally, we used attributable risk methods to quantify this relationship further.

Association between PM10 pollution and the hospitalization of chronic obstructive pulmonary disease with comorbidity: evidence in 17 cities of Henan, Central China

Particulate matter (PM10) changes have been confirmed as one of the contributory factors affecting human health, the association between PM10 pollution and the hospitalization of chronic obstructive pulmonary disease (COPD) with comorbidity diseases was rarely reported. The same inpatient more than twice times admissions with COPD illness from January 1, 2016 to December 31, 2021 were identified from hospitals in the 17 cities of Henan, Central China. City-specific associations were firstly estimated using the case time series (CTS) model and then combined to obtain the regional average association. The multivariate meta-analytic model produces pooled estimates of the set of coefficients representing the PM10-COPD hospitalizations association across the 17 cities. Cause-specific hospitalization analyses were performed by COPD patients with different comorbidity combinations. A total of 34,348 elderly (age ≥ 65) subjects were analyzed and with a total of 35,122.35 person-years. These coefficients can be used to compute the linear exposure-response curve expressed as relative risk (RR) in per 10 µg/m3 increase in PM10 at lag03, which was 1.0091 (95% CI 1.0070-1.0112) for COPD with comorbidity, 1.0089 (95% CI 1.0067-1.0110) for COPD with circulatory system diseases, 1.0079 (95% CI 1.0052-1.0105) for COPD with respiratory system diseases, 1.0076 (95% CI 1.0032-1.0121) for COPD with endocrine system diseases, and 1.0087 (95% CI 1.0013-1.0162) for COPD with genitourinary system diseases, respectively. Some heterogeneity was found across cities, with estimates ranging from 1.0227 in the Puyang and Jiaozuo to 1.0053 in Henan Provance, China. The effect of higher PM10, on average, was higher in studies for northern cities, with a steeper raise in risk: per 10 µg/m3 increase in PM10, the RR from 1.0062 (95% CI 1.0030-1.0093) for the 10th percentile of latitude to 1.0124 (95% CI 1.0089-1.0160) for the 90th percentile. Our findings indicated that PM10 exposure may increase the risk of hospitalizations for COPD with comorbidity. Moreover, there might be a higher morbidity risk associated with PM10 in northern latitudes, indicating that stricter air quality standards could potentially reduce PM10-related morbidity among individuals with COPD. These findings have implications for the implementation of effective clean air interventions aligned with national climate policies.

Ambient air temperature exposure and foetal size and growth in three European birth cohorts

INTRODUCTION

Ambient air temperature may affect birth outcomes adversely, but little is known about their impact on foetal growth throughout pregnancy. We evaluated the association between temperature exposure during pregnancy and foetal size and growth in three European birth cohorts.

METHODS

We studied 23,408 pregnant women from the English Born in Bradford cohort, Dutch Generation R Study, and Spanish INMA Project. Using the UrbClimTM model, weekly ambient air temperature exposure at 100x100m resolution at the mothers' residences during pregnancy was calculated. Estimated foetal weight, head circumference, and femur length at mid and late pregnancy and weight, head circumference, and length at birth were converted into standard deviation scores (SDS). Foetal growth from mid to late pregnancy was calculated (grams or centimetres/week). Cohort/region-specific distributed lag non-linear models were combined using a random-effects meta-analysis and results presented in reference to the median percentile of temperature (14 °C).

RESULTS

Weekly temperatures ranged from -5.6 (Bradford) to 30.3 °C (INMA-Sabadell). Cold and heat exposure during weeks 1-28 were associated with a smaller and larger head circumference in late pregnancy, respectively (e.g., for 9.5 °C: -1.6 SDS [95 %CI -2.0; -0.4] and for 20.0 °C: 1.8 SDS [0.7; 2.9]). A susceptibility period from weeks 1-7 was identified for cold exposure and a smaller head circumference at late pregnancy. Cold exposure was associated with a slower head circumference growth from mid to late pregnancy (for 5.5 °C: -0.1 cm/week [-0.2; -0.04]), with a susceptibility period from weeks 4-12. No associations that survived multiple testing correction were found for other foetal or any birth outcomes.

CONCLUSIONS

Cumulative exposure to cold and heat during pregnancy was associated with changes in foetal head circumference throughout gestation, with susceptibility periods for cold during the first pregnancy trimester. No associations were found at birth, suggesting potential recovery. Future research should replicate this study across different climatic regions including varying temperature profiles.

The relationship between hot temperatures and hospital admissions for psychosis in adults diagnosed with schizophrenia: A case-crossover study in Quebec, Canada

INTRODUCTION

Some studies have found hot temperatures to be associated with exacerbations of schizophrenia, namely psychoses. As climate changes faster in Northern countries, our understanding of the association between temperature and hospital admissions (HA) for psychosis needs to be deepened.

OBJECTIVES

1) Among adults diagnosed with schizophrenia, measure the relationship between mean temperatures and HAs for psychosis during summer. 2) Determine the influence of individual and ecological characteristics on this relationship.

METHODS

A cohort of adults diagnosed with schizophrenia (n = 30,649) was assembled using Quebec's Integrated Chronic Disease Surveillance System (QICDSS). The follow-up spanned summers from 2001 to 2019, using hospital data from the QICDSS and meteorological data from the National Aeronautics and Space Administration's (NASA) Daymet database. In four geographic regions of the province of Quebec, a conditional logistic regression was used for the case-crossover analysis of the relationship between mean temperatures (at lags up to 6 days) and HAs for psychosis using a distributed lag non-linear model (DLNM). The analyses were adjusted for relative humidity, stratified according to individual (age, sex, and comorbidities) and ecological (material and social deprivation index and exposure to green space) factors, and then pooled through a meta-regression.

RESULTS

The statistical analyses revealed a statistically significant increase in HAs three days (lag 3) after elevated mean temperatures corresponding to the 90th percentile relative to a minimum morbidity temperature (MMT) (OR 1.040; 95% CI 1.008-1.074), while the cumulative effect over six days was not statistically significant (OR 1.052; 95% IC 0.993-1.114). Stratified analyses revealed non statistically significant gradients of increasing HAs relative to increasing material deprivation and decreasing green space levels.

CONCLUSIONS

The statistical analyses conducted in this project showed the pattern of admissions for psychosis after hot days. This finding could be useful to better plan health services in a rapidly changing climate.

Short-Term Effects of Extreme Meteorological Factors on Hand, Foot, and Mouth Disease Infection During 2010-2017 in Jiangsu, China: A Distributed Lag Non-Linear Analysis

Hand, Foot, and Mouth Disease (HFMD) is an infectious disease that primarily affects young children. In densely populated Jiangsu Province in China, the impact of extreme meteorological factors on HFMD is a concern. We aimed to examine the association between extreme meteorological variables and HFMD infection risk using daily HFMD infections and meteorological data from 2010 to 2017 in Jiangsu Province. We used distributed lag non-linear model (DLNM) to analyze the data, which can effectively capture the nuanced non-linear dynamics and lag effects in the relationship between HFMD and extreme meteorological factors. Comparing the 10th and 90th percentiles of meteorological variables with their respective median values, our results showed that extremely low temperatures and high humidity were significantly associated with increased HFMD infection risk. The greatest effect of extremely low temperatures was observed at a lag of 1-2 days, elevating the risk by 18 ∼ 33% (RR = 1.18 ∼ 1.33). Extremely high humidity was found to increase the risk of infection, starting at a lag of 4 days. In contrast, extremely high temperatures, low humidity, and high wind speed were associated with reduced risk of infection at lag of 0-12 days, with the range of RR values being 0.60-0.98 for extremely high temperatures, 0.69-0.89 for extremely low humidity, and 0.84-0.98 for extremely high wind speed respectively. Our findings suggest that extreme meteorological factors can significantly impact the incidence of HFMD in Jiangsu Province, and highlight the need for effective public health protection measures during the periods of extreme meteorological condition, particularly for vulnerable populations.

Association between ambient temperature and genitourinary emergency ambulance dispatches in Japan: A nationwide case-crossover study

Background

Although the effects of temperature on genitourinary morbidity and mortality have been investigated in several countries, it remains largely unexplored in Japan. We investigated the association between ambient temperature and genitourinary emergency ambulance dispatches (EADs) in Japan and the modifying roles of sex, age, and illness severity.

Methods

We conducted a time-stratified case-crossover study with conditional quasi-Poisson regression to estimate the association between mean temperature and genitourinary EADs in all prefectures of Japan between 2015 and 2019. A mixed-effects meta-analysis was used to pool the association at the country level. Subgroup analyses were performed to explore differences in associations stratified by sex, age, and illness severity.

Results

We found an increased risk of genitourinary EAD associated with higher temperatures. The cumulative relative risk (RR) at the 99th temperature percentile compared with that at the 1st percentile was 1.74 (95% confidence interval (CI) = [1.60, 1.89]). We observed higher heat-related RRs in males (RR = 1.89; 95% CI = [1.73, 2.07]) than females (RR = 1.56; 95% CI = [1.37, 1.76]), and in the younger (RR = 2.13; 95% CI = [1.86, 2.45]) than elderly (RR = 1.39; 95% CI = [1.22, 1.58]). We found a significant association for those with mild or moderate cases (RR = 1.77; 95% CI = [1.62, 1.93]), but not for severe or life-threatening cases (RR = 1.20; 95% CI = [0.80, 1.82]).

Conclusion

Our study revealed heat effects on genitourinary EADs in Japan. Men, youth, and mild-moderate illnesses were particularly vulnerable subgroups. These findings underscore the need for preventative measures aimed at mitigating the impact of temperature on genitourinary emergencies.

Nitrogen dioxide exposure, attentional function, and working memory in children from 4 to 8 years: Periods of susceptibility from pregnancy to childhood

BACKGROUND

Air pollution exposure during pregnancy and childhood has been linked to executive function impairment in children, however, very few studies have assessed these two exposure periods jointly to identify susceptible periods of exposure. We sought to identify potential periods of susceptibility of nitrogen dioxide (NO2) exposure from conception to childhood on attentional function and working memory in school-aged children.

METHODS

Within the Spanish INMA Project, we estimated residential daily NO2 exposures during pregnancy and up to 6 years of childhood using land use regression models (n = 1,703). We assessed attentional function at 4-6 years and 6-8 years, using the Conners Kiddie Continuous Performance Test and the Attention Network Test, respectively, and working memory at 6-8 years, using the N-back task. We used distributed lag non-linear models to assess the periods of susceptibility of each outcome, adjusting for potential confounders and correcting for multiple testing. We also stratified all models by sex.

RESULTS

Higher exposure to NO2 between 1.3 and 1.6 years of age was associated with higher hit reaction time standard error (HRT-SE) (0.14 ms (95 % CI 0.05; 0.22) per 10 μg/m3 increase in NO2) and between 1.5 and 2.2 years of age with more omission errors (1.02 (95 % CI 1.01; 1.03) of the attentional function test at 4-6 years. Higher exposure to NO2 between 0.3 and 2.2 years was associated with higher HRT-SE (10.61 ms (95 % CI 3.46; 17.75) at 6-8 years only in boys. We found no associations between exposure to NO2 and working memory at 6-8 years.

CONCLUSION

Our findings suggest that NO2 exposure during the first two years of life is associated with poorer attentional function in children from 4 to 8 years of age, especially in boys. These findings highlight the importance of exploring long-term effects of traffic-related air pollution exposure in older age groups.

Assessing the impact of climatic variability on acute respiratory diseases across diverse climatic zones in South Africa

Acute respiratory diseases are a significant public health concern in South Africa, with climatic variables such as temperature and rainfall being key influencers. This study investigates the associations between these variables and the prevalence of acute respiratory diseases in Johannesburg, Cape Town, and Gqeberha (Port Elizabeth), representing distinct climatic zones. Spearman's correlation analyses showed negative correlations in Johannesburg for respiratory disease claims with maximum temperature (r = -0.12, p < 0.0001) and mean temperature (r = -0.13, p < 0.0001), and a negative correlation with daily rainfall (r = -0.12, p < 0.0001). Cape Town demonstrated a negative correlation with maximum temperature (r = -0.18, p < 0.0001) and a positive correlation with rainfall (r = 0.08, p < 0.0001). Utilizing Distributed Lag Non-linear Models (DLNM), the study revealed that in Johannesburg, the relative risk (RR) of respiratory claims increases notably at temperatures below 12 °C, and again at a Tmax between 16 and 23 °C. The risk escalates further at >30 °C, although with a considerable error margin. For Cape Town, a stable level of moderate RR is seen from Tmax 15-24 °C, with a significant increase in RR and error margin above 30 °C. In Gqeberha, the DLNM results are less definitive, reflecting the city's moderate climate and year-round rainfall. The RR of acute respiratory diseases did not show clear patterns with temperature changes, with increasing error margins outside the 22 °C threshold. These findings emphasize the imperative for region-specific public health strategies that account for the complex, non-linear influences of climate on respiratory health. This detailed understanding of the climate-health nexus provides a robust basis for enhancing public health interventions and future research directed at reducing the impacts of climate factors.

Maternal exposure to ambient air temperature and adverse birth outcomes: An umbrella review of systematic reviews and meta-analyses

BACKGROUND

Multiple systematic reviews on prenatal ambient temperature and adverse birth outcomes exist, but the overall epidemiological evidence and the appropriate metric for thermal stress remain unclear. An umbrella review was performed to summarise and appraise the evidence with recommendations.

METHODS

Systematic reviews and meta-analyses on the associations between ambient temperature and adverse birth outcomes (preterm birth, stillbirth, birth weight, low birth weight, and small for gestational age) up to December 20, 2023, were synthesised according to a published protocol. Databases PubMed, CINAHL, Scopus, MEDLINE/Ovid, EMBASE/Ovid, Web of Science Core Collection, systematic reviews repositories, electronic grey literature, and references were searched. Risk of bias was assessed using Joanna Briggs Institute's critical appraisal tool.

RESULTS

Eleven systematic reviews, including two meta-analyses, were included. This comprised 90 distinct observational studies that employed multiple temperature assessment metrics with a very high overlap of primary studies. Primary studies were mostly from the United States while both Africa and South Asia contributed only three studies. A majority (7 out of 11) of the systematic reviews were rated as moderate risk of bias. All systematic reviews indicated that maternal exposures to both extremely high and low temperatures, particularly during late gestation are associated with increased risks of preterm birth, stillbirth, and reduced fetal growth. However, due to great differences in the exposure assessments, high heterogeneity, imprecision, and methodological limitations of the included systematic reviews, the overall epidemiological evidence was classified as probable evidence of causation. No study assessed biothermal metrics for thermal stress.

CONCLUSIONS

Despite the notable methodological differences, prenatal exposure to extreme ambient temperatures, particularly during late pregnancy, was associated with adverse birth outcomes. Adhering to the appropriate systematic review guidelines for environmental health research, incorporating biothermal metrics into exposure assessment, evidence from broader geodemographic settings, and interventions are recommended in future studies.

Associations of meteorological factors and dynamics of scrub typhus incidence in South Korea: A nationwide time-series study

Scrub typhus, also known as Tsutsugamushi disease, is a climate-sensitive vector-borne disease that poses a growing public health threat. However, studies on the association between scrub typhus epidemics and meteorological factors in South Korea need to be complemented. Therefore, we aimed to analyze the association among ambient temperature, precipitation, and the incidence of scrub typhus in South Korea. First, we obtained data on the weekly number of scrub typhus cases and concurrent meteorological variables at the city-county level (Si-Gun) in South Korea between 2001 and 2019. Subsequently, a two-stage meta-regression analysis was conducted. In the first stage, we conducted time-series regression analyses using a distributed lag nonlinear model (DLNM) to investigate the association between temperature, precipitation, and scrub typhus incidence at each location. In the second stage, we employed a multivariate meta-regression model to combine the association estimates from all municipalities, considering regional indicators, such as mite species distribution, Normalized Difference Vegetation Index (NDVI), and urban-rural classification. Weekly mean temperature and weekly total precipitation exhibited a reversed U-shaped nonlinear association with the incidence of scrub typhus. The overall cumulative association with scrub typhus incidence peaked at 18.7 C° (with RRs of 9.73, 95% CI: 5.54-17.10) of ambient temperature (reference 9.7 C°) and 162.0 mm (with RRs of 1.87, 95% CI: 1.02-3.83) of precipitation (reference 2.8 mm), respectively. These findings suggest that meteorological factors contribute to scrub typhus epidemics by interacting with vectors, reservoir hosts, and human behaviors. This information serves as a reference for future public health policies and epidemiological research aimed at controlling scrub typhus infections.

Heat exposure and chronic kidney disease: a temporal link in a Taiwanese agricultural county

Heat stress-related kidney injury has drawn public health attention. This study explored the temporal relationships between impaired kidney function and preceding outdoor heat exposure Taiwan. Data of participants collected through a health screening program was used to assess the association between chronic kidney disease (CKD) and average ambient temperature with various time lag structures. A total of 1,243 CKD cases and 38,831 non-CKD participants were included in the study. After adjusting for demographic, socioeconomic, lifestyle factors, and comorbidities, CKD was positively associated with the ambient temperature within 1-9 months. The 9-month average ambient temperature yielded the highest odds ratio of CKD (OR = 1.22; 95% CI = 1.09-1.37). Furthermore, females and farmers were found to be more vulnerable to CKD risk after outdoor heat exposure. These findings suggest that the prevention of heat stress-related kidney injury should consider relevant time frames and focus on vulnerable populations.

Association of prenatal exposure to PM2.5 and NO2 with gestational diabetes in Western New York

BACKGROUND

Although many studies have examined the association between prenatal air pollution exposure and gestational diabetes (GDM), the relevant exposure windows remain inconclusive. We aim to examine the association between preconception and trimester-specific exposure to PM2.5 and NO2 and GDM risk and explore modifying effects of maternal age, pre-pregnancy body mass index (BMI), smoking, exercise during pregnancy, race and ethnicity, and neighborhood disadvantage.

METHODS

Analyses included 192,508 birth records of singletons born to women without pre-existing diabetes in Western New York, 2004-2016. Daily PM2.5 and NO2 at 1-km2 grids were estimated from ensemble-based models. We assigned each birth with exposures averaged in preconception and each trimester based on residential zip-codes. We used logistic regression to examine the associations and distributed lag models (DLMs) to explore the sensitive windows by month. Relative excess risk due to interaction (RERI) and multiplicative interaction terms were calculated.

RESULTS

GDM was associated with PM2.5 averaged in the first two trimesters (per 2.5 μg/m3: OR = 1.08, 95% CI: 1.01, 1.14) or from preconception to the second trimester (per 2.5 μg/m3: OR = 1.10, 95% CI: 1.03, 1.18). NO2 exposure during each averaging period was associated with GDM risk (per 10 ppb, preconception: OR = 1.10, 95% CI: 1.06, 1.14; first trimester: OR = 1.12, 95% CI: 1.08, 1.16; second trimester: OR = 1.10, 95% CI: 1.06, 1.14). In DLMs, sensitive windows were identified in the 5th and 6th gestational months for PM2.5 and one month before and three months after conception for NO2. Evidence of interaction was identified for pre-pregnancy BMI with PM2.5 (P-for-interaction = 0.023; RERI = 0.21, 95% CI: 0.10, 0.33) and with NO2 (P-for-interaction = 0.164; RERI = 0.16, 95% CI: 0.04, 0.27).

CONCLUSION

PM2.5 and NO2 exposure may increase GDM risk, and sensitive windows may be the late second trimester for PM2.5 and periconception for NO2. Women with higher pre-pregnancy BMI may be more susceptible to exposure effects.

Susceptible windows of prenatal and postnatal fine particulate matter exposures and attention-deficit hyperactivity disorder symptoms in early childhood

Few prior studies have explored windows of susceptibility to fine particulate matter (PM2.5) in both the prenatal and postnatal periods and children's attention-deficit/hyperactivity disorder (ADHD) symptoms. We analyzed data from 1416 mother-child pairs from the Spanish INMA (INfancia y Medio Ambiente) Study (2003-2008). Around 5 years of age, teachers reported the number of ADHD symptoms (i.e., inattention, hyperactivity/impulsivity) using the ADHD Diagnostic and Statistical Manual of Mental Disorders. Around 7 years of age, parents completed the Conners' Parent Rating Scales, from which we evaluated the ADHD index, cognitive problems/inattention, hyperactivity, and oppositional subscales, reported as age- and sex-standardized T-scores. Daily residential PM2.5 exposures were estimated using a two-stage random forest model with temporal back-extrapolation and averaged over 1-week periods in the prenatal period and 4-week periods in the postnatal period. We applied distributed lag non-linear models within the Bayesian hierarchical model framework to identify susceptible windows of prenatal or postnatal exposure to PM2.5 (per 5-μg/m3) for ADHD symptoms. Models were adjusted for relevant covariates, and cumulative effects were reported by aggregating risk ratios (RRcum) or effect estimates (βcum) across adjacent susceptible windows. A similar susceptible period of exposure to PM2.5 (1.2-2.9 and 0.9-2.7 years of age, respectively) was identified for hyperactivity/impulsivity symptoms assessed ~5 years (RRcum = 2.72, 95% credible interval [CrI] = 1.98, 3.74) and increased hyperactivity subscale ~7 years (βcum = 3.70, 95% CrI = 2.36, 5.03). We observed a susceptibility period to PM2.5 on risk of hyperactivity/impulsivity symptoms ~5 years in gestational weeks 16-22 (RRcum = 1.36, 95% CrI = 1.22, 1.52). No associations between PM2.5 exposure and other ADHD symptoms were observed. We report consistent evidence of toddlerhood as a susceptible window of PM2.5 exposure for hyperactivity in young children. Although mid-pregnancy was identified as a susceptible period of exposure on hyperactivity symptoms in preschool-aged children, this association was not observed at the time children were school-aged.

Warm season ambient ozone and children's health in the USA

BACKGROUND

Over 120 million people in the USA live in areas with unsafe ozone (O3) levels. Studies among adults have linked exposure to worse lung function and higher risk of asthma and chronic obstructive pulmonary disease (COPD). However, few studies have examined the effects of O3 in children, and existing studies are limited in terms of their geographic scope or outcomes considered.

METHODS

We leveraged a dataset of encounters at 42 US children's hospitals from 2004-2015. We used a one-stage case-crossover design to quantify the association between daily maximum 8-hour O3 in the county in which the hospital is located and risk of emergency department (ED) visits for any cause and for respiratory disorders, asthma, respiratory infections, allergies and ear disorders.

RESULTS

Approximately 28 million visits were available during this period. Per 10 ppb increase, warm-season (May through September) O3 levels over the past three days were associated with higher risk of ED visits for all causes (risk ratio [RR]: 0.3% [95% confidence interval (CI): 0.2%, 0.4%]), allergies (4.1% [2.5%, 5.7%]), ear disorders (0.8% [0.3%, 1.3%]) and asthma (1.3% [0.8%, 1.9%]). When restricting to levels below the current regulatory standard (70 ppb), O3 was still associated with risk of ED visits for all-cause, allergies, ear disorders and asthma. Stratified analyses suggest that the risk of O3-related all-cause ED visits may be higher in older children.

CONCLUSIONS

Results from this national study extend prior research on the impacts of daily O3 on children's health and reinforce the presence of important adverse health impacts even at levels below the current regulatory standard in the USA.

Short-term exposure to air pollution and hospital admission after COVID-19 in Catalonia: the COVAIR-CAT study

BACKGROUND

A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19.

METHODS

The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days.

RESULTS

Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0_7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant.

CONCLUSIONS

Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization.

Extreme temperature events and dementia mortality in Chinese adults: a population-based, case-crossover study

BACKGROUND

The effect of exposure to extreme temperature events (ETEs) on dementia mortality remains largely unknown. We aimed to quantify the association of ETE exposure with dementia mortality.

METHODS

We conducted a population-based, case-crossover study among 57 791 dementia deaths in Jiangsu province, China, during 2015-20. Daily mean temperatures were extracted from a validated grid dataset at each subject's residential address, and grid-specific exposures to heat wave and cold spell were assessed with a combination of their intensity and duration. We applied conditional logistic regression models to investigate cumulative and lag effects for ETE exposures.

RESULTS

Exposure to ETE with each of all 24 definitions was associated with an increased odds of dementia mortality, which was higher when exposed to heat wave. Exposure to heat wave (daily mean temperature ≥95th percentile, duration ≥3 days (d); P95_3d) and cold spell (≤5th percentile, duration ≥3 d; P5_3d) was associated with a 75% (95% CI: 61%, 90%) and 30% (19%, 43%) increase in odds of dementia mortality, respectively. Definitions with higher intensity were generally associated with a higher odds of dementia mortality. We estimated that 6.14% of dementia deaths were attributable to exposure to heat wave (P90_2d) and cold spell (P10_2d). No effect modifications were observed by sex or age, except that the association for heat wave was stronger among women.

CONCLUSIONS

Exposure to both heat wave and cold spell was associated with an increased odds of dementia mortality. Our findings highlight that reducing individual ETE exposures may be helpful in preventing deaths from dementia, especially among women in summer.

Global, regional, and national burden of mortality associated with cold spells during 2000-19: a three-stage modelling study

BACKGROUND

Exposure to cold spells is associated with mortality. However, little is known about the global mortality burden of cold spells.

METHODS

A three-stage meta-analytical method was used to estimate the global mortality burden associated with cold spells by means of a time series dataset of 1960 locations across 59 countries (or regions). First, we fitted the location-specific, cold spell-related mortality associations using a quasi-Poisson regression with a distributed lag non-linear model with a lag period of up to 21 days. Second, we built a multivariate meta-regression model between location-specific associations and seven predictors. Finally, we predicted the global grid-specific cold spell-related mortality associations during 2000-19 using the fitted meta-regression model and the yearly grid-specific meta-predictors. We calculated the annual excess deaths, excess death ratio (excess deaths per 1000 deaths), and excess death rate (excess deaths per 100 000 population) due to cold spells for each grid across the world.

FINDINGS

Globally, 205 932 (95% empirical CI [eCI] 162 692-250 337) excess deaths, representing 3·81 (95% eCI 2·93-4·71) excess deaths per 1000 deaths (excess death ratio), and 3·03 (2·33-3·75) excess deaths per 100 000 population (excess death rate) were associated with cold spells per year between 2000 and 2019. The annual average global excess death ratio in 2016-19 increased by 0·12 percentage points and the excess death rate in 2016-19 increased by 0·18 percentage points, compared with those in 2000-03. The mortality burden varied geographically. The excess death ratio and rate were highest in Europe, whereas these indicators were lowest in Africa. Temperate climates had higher excess death ratio and rate associated with cold spells than other climate zones.

INTERPRETATION

Cold spells are associated with substantial mortality burden around the world with geographically varying patterns. Although the number of cold spells has on average been decreasing since year 2000, the public health threat of cold spells remains substantial. The findings indicate an urgency of taking local and regional measures to protect the public from the mortality burdens of cold spells.

FUNDING

Australian Research Council, Australian National Health and Medical Research Council, EU's Horizon 2020 Project Exhaustion.

Effects of socioeconomic status and greenspace on respiratory emergency department visits under short-term temperature variations: An age-stratified case time-series study

INTRODUCTION

Neighborhood socioeconomic status (SES) and greenspace can affect respiratory health. However, it is unclear whether effects of neighborhood SES and greenspace on respiratory health still exist regardless of temperature variations.

METHODS

This paper conducted a two-stage, age-stratified case time-series study. The first goal is to examine the associations between two temperature metrics (daily mean temperature [DMT] and diurnal temperature range [DTR]) and respiratory emergency department (ED) visits among four age groups in New York City. The second goal is to evaluate whether neighborhood SES and greenspace would be determinants of respiratory ED visits independent from temperature varying factors. A distributed lag nonlinear model was applied on ED data from 135 zip codes (October 2016 - February 2020).

RESULTS

Our first-stage analysis indicated that older adults aged 65+ had higher risk of ED visits (RR=2.78, 95% eCI: 2.41, 3.22; with 7 days of lag) on days with low DMT (-10°C), followed by adults aged 18-64 (RR=2.48, 95% eCI: 2.32, 2.65), children and youth aged 5-17 (RR=1.38, 95% eCI: 1.24, 1.53), and young children aged 0-4 (RR=1.04, 95% eCI: 0.96, 1.13). However, no excess respiratory ED visits were observed on days with high DMT (30°C). Higher DTR was associated with higher risk, with children and youth more susceptible when DTR was high (DTR 20°C; RR=5.70, 95% eCI: 3.42, 9.49; with 7 days of lag). The second-stage analysis indicated neighborhood SES and greenspace had significant associations with respiratory ED visits regardless of temperature variations. Specifically, Higher income and greenspace exposure were negatively associated with ED visits among all age groups.

CONCLUSIONS

Neighborhood SES and greenspace could affect respiratory morbidity regardless of weather conditions. Daily temperature variations accelerated the short-term risk among population subgroups under different weather conditions (e.g., higher risk of days with low DMT among older adults, higher risk of days with high DTR among children and youth aged 5-17), which could create co-effects with neighborhood SES and greenspace on respiratory health.

The added effects of cold spells on stroke admissions: Differential effects on ischemic and hemorrhagic stroke

BACKGROUND

Epidemiological evidence suggests an association between low ambient temperature and stroke risk, but available data are limited particularly on associations with different stroke subtypes.

AIMS

The aim of this study is to estimate the relationship between cold spells and stroke admissions, including the effect of cold spells on different stroke subtypes (ischemic stroke and intracerebral hemorrhage (ICH)).

METHODS

A total of 144,405 stroke admissions from the Tianjin Centre for Health and Meteorology Multidisciplinary Innovation in China, covering the period from January 2016 to December 2020, were studied, as well as meteorological and air pollutant data. A generalized additive model with a distributed lag nonlinear model was employed to assess the relationship, considering 12 different definitions of a cold spell based on various temperature thresholds and durations. The analysis controlled for lagged and nonlinear effects of temperature. Analyses were performed on all strokes as well as ischemic stroke and ICH.

RESULTS

There was a significant increase in stroke admissions during cold spells. Generally, the increased risk during cold spells increased as the temperature threshold decreased, but was not significantly affected by the duration. The optimal model was obtained using the cold-spell definition based on an average daily temperature below the 10th percentile (0.11°C) for 2 or more consecutive days. According to this model, the effect of cold spells on ischemic stroke admissions had a significant lag effect and was long-lasting, with a single-day effect occurring on lag 7d, peaking on lag 13d (relative risk (RR) = 1.05; 95% confidence interval (CI) = 1.02 to 1.09), and lasting until lag 20d. In contrast, the effect on ICH was immediate and short-lived, with the most significant single-day effect occurring on the current day (RR = 1.17; 95% CI = 1.06 to 1.29) and limited within 3 days. 14.15% of stroke cases could be attributed to cold spells, with ICH exhibiting a higher burden than ischemic stroke except for strict temperature threshold definitions.

CONCLUSION

Cold spells are associated with an increased stroke risk. Different patterns of association were seen for different stroke subtypes. The effect on ischemic stroke had a lag effect and a longer duration, whereas the effect on ICH had an immediate effect and a shorter duration. These findings support the development and improvement of stroke cold-spell early warning systems and highlight the importance of public health interventions to mitigate the adverse health impacts of cold spells.

Modeling the lagged impacts of hourly weather and speed variation factors on the segment crash risk of rural interstate freeways: Applying a space-time-stratified case-crossover design

In the realm of traditional roadway crash studies, cross-sectional modeling methods have been commonly employed to investigate the intricate relationship between the crash risk of roadway segments and variables including roadway geometrics, weather conditions, and speed distribution. However, these methodologies assume that the explanatory variables and target variable are only associated within the same time period. Although this assumption is well-founded for static factors like roadway geometrics, it proves inadequate when dealing with highly time-varying variables related to weather conditions and speed variation. Recent investigations have unveiled that these time-varying variables may exhibit lagged impacts on segment crash risk, necessitating the adoption of more comprehensive time-series modeling methods. This study employs two interpretable statistical methods, namely the distributed lag model (DLM) and the distributed lag nonlinear model (DLNM), to elucidate meaningful and interpretable patterns of the lagged impacts of weather and speed variation factors on segment crash risk. Empirical evidence based on crash data collected from rural interstate freeways in the state of Texas demonstrates coherent and interpretable lagged impact patterns of these variables. This study's results serve as strong support for the existence of lagged impacts on roadway segment-level crash risk, emphasizing the need for considering time-series effects in future crash modeling research. Furthermore, these findings could offer practical implications for the design of real-time crash warning systems and the effective implementation of variable speed limits to enhance road safety.

Association between prenatal and childhood PM2.5 exposure and preadolescent anxiety and depressive symptoms

Background

Fine particulate matter (PM2.5) exposure has been linked to anxiety and depression in adults; however, there is limited research in the younger populations, in which symptoms often first arise.

Methods

We examined the association between early-life PM2.5 exposure and symptoms of anxiety and depression in a cohort of 8-11-year-olds in Mexico City. Anxiety and depressive symptoms were assessed using the Spanish versions of the Revised Children's Manifest Anxiety Scale and Children's Depression Inventory. Daily PM2.5 was estimated using a satellite-based exposure model and averaged over several early and recent exposure windows. Linear and logistic regression models were used to estimate the change in symptoms with each 5-µg/m3 increase in PM2.5. Models were adjusted for child's age, child's sex, maternal age, maternal socioeconomic status, season of conception, and temperature.

Results

Average anxiety and depressive symptom T-scores were 51.0 (range 33-73) and 53.4 (range 44-90), respectively. We observed consistent findings for exposures around the fourth year of life, as this was present for both continuous and dichotomized anxiety symptoms, in both independent exposure models and distributed lag modeling approaches. This window was also observed for elevated depressive symptoms. An additional consistent finding was for PM2.5 exposure during early pregnancy in relation to both clinically elevated anxiety and depressive symptoms, this was seen in both traditional and distributed lag modeling approaches.

Conclusion

Both early life and recent PM2.5 exposure were associated with higher mental health symptoms in the child highlighting the role of PM2.5 in the etiology of these conditions.

Exposure to mixtures of PM2.5 components and term premature rupture of membranes: a case-crossover study in Shijiazhuang, China

This study aims to explore the acute effects of short-term exposure to PM2.5 components and their mixture on PROM. Counts of hospital admissions due to PROM were collected at the Fourth Hospital of Shijiazhuang. The associations between the PROM and PM2.5 components was examined using a time-stratified case-crossover approach. The overall effects of components on TPROM were examined using the BKMR. During the study period 30,709 cases of PROMwere identified. The relative risks and the 95% CI of TPROM were 1.013 (1.002, 1.028) and 1.015 (1.003, 1.028) associated with per interquartile range increase in nitrate and ammonium ion on the current day and they were 1.007 (1.001, 1.013) and 1.003 (1.000, 1.005) on the previous day. The results from the BKMR models showed a higher risk of TPROM was associated with exposure to mixtures, in which, nitrate and organic matter were the main contributors to the overall effect.

Impact of short-term exposure to air pollution on natural mortality and vulnerable populations: a multi-city case-crossover analysis in Belgium

BACKGROUND

The adverse effect of air pollution on mortality is well documented worldwide but the identification of more vulnerable populations at higher risk of death is still limited. The aim of this study was to evaluate the association between natural mortality (overall and cause-specific) and short-term exposure to five air pollutants (PM2.5, PM10, NO2, O3 and black carbon) and identify potential vulnerable populations in Belgium.

METHODS

We used a time-stratified case-crossover design with conditional logistic regressions to assess the relationship between mortality and air pollution in the nine largest Belgian agglomerations. Then, we performed a random-effect meta-analysis of the pooled results and described the global air pollution-mortality association. We carried out stratified analyses by individual characteristics (sex, age, employment, hospitalization days and chronic preexisting health conditions), living environment (levels of population density, built-up areas) and season of death to identify effect modifiers of the association.

RESULTS

The study included 304,754 natural deaths registered between 2010 and 2015. We found percentage increases for overall natural mortality associated with 10 μg/m3 increases of air pollution levels of 0.6% (95% CI: 0.2%, 1.0%) for PM2.5, 0.4% (0.1%, 0.8%) for PM10, 0.5% (-0.2%, 1.1%) for O3, 1.0% (0.3%, 1.7%) for NO2 and 7.1% (-0.1%, 14.8%) for black carbon. There was also evidence for increases of cardiovascular and respiratory mortality. We did not find effect modification by individual characteristics (sex, age, employment, hospitalization days). However, this study suggested differences in risk of death for people with preexisting conditions (thrombosis, cardiovascular diseases, asthma, diabetes and thyroid affections), season of death (May-September vs October-April) and levels of built-up area in the neighborhood (for NO2).

CONCLUSIONS

This work provided evidence for the adverse health effects of air pollution and contributed to the identification of specific population groups. These findings can help to better define public-health interventions and prevention strategies.

Short-Term Increases in NO2 and O3 Concentrations during Pregnancy and Stillbirth Risk in the U.S.: A Time-Stratified Case-Crossover Study

Associations between gaseous pollutant exposure and stillbirth have focused on exposures averaged over trimesters or gestation. We investigated the association between short-term increases in nitrogen dioxide (NO2) and ozone (O3) concentrations and stillbirth risk among a national sample of 116 788 Medicaid enrollees from 2000 to 2014. A time-stratified case-crossover design was used to estimate distributed (lag 0-lag 6) and cumulative lag effects, which were adjusted for PM2.5 concentration and temperature. Effect modification by race/ethnicity and proximity to hydraulic fracturing (fracking) wells was assessed. Short-term increases in the NO2 and O3 concentrations were not associated with stillbirth in the overall sample. Among American Indian individuals (n = 1694), a 10 ppb increase in NO2 concentrations was associated with increased stillbirth odds at lag 0 (5.66%, 95%CI: [0.57%, 11.01%], p = 0.03) and lag 1 (4.08%, 95%CI: [0.22%, 8.09%], p = 0.04) but not lag 0-6 (7.12%, 95%CI: [-9.83%, 27.27%], p = 0.43). Among participants living in zip codes within 15 km of active fracking wells (n = 9486), a 10 ppb increase in NO2 concentration was associated with increased stillbirth odds in single-day lags (2.42%, 95%CI: [0.37%, 4.52%], p = 0.02 for lag 0 and 1.83%, 95%CI: [0.25%, 3.43%], p = 0.03 for lag 1) but not the cumulative lag (lag 0-6) (4.62%, 95%CI: [-2.75%, 12.55%], p = 0.22). Odds ratios were close to the null in zip codes distant from fracking wells. Future studies should investigate the role of air pollutants emitted from fracking and potential racial disparities in the relationship between short-term increases in NO2 concentrations and stillbirth.

Reconstructing individual-level exposures in cohort analyses of environmental risks: an example with the UK Biobank

Recent developments in linkage procedures and exposure modelling offer great prospects for cohort analyses on the health risks of environmental factors. However, assigning individual-level exposures to large population-based cohorts poses methodological and practical problems. In this contribution, we illustrate a linkage framework to reconstruct environmental exposures for individual-level epidemiological analyses, discussing methodological and practical issues such as residential mobility and privacy concerns. The framework outlined here requires the availability of individual residential histories with related time periods, as well as high-resolution spatio-temporal maps of environmental exposures. The linkage process is carried out in three steps: (1) spatial alignment of the exposure maps and residential locations to extract address-specific exposure series; (2) reconstruction of individual-level exposure histories accounting for residential changes during the follow-up; (3) flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. The procedure is exemplified by the linkage and processing of daily averages of air pollution for the UK Biobank cohort using gridded spatio-temporal maps across Great Britain. This results in the extraction of exposure summaries suitable for epidemiological analyses of both short and long-term risk associations and, in general, for the investigation of temporal dependencies. The linkage framework presented here is generally applicable to multiple environmental stressors and can be extended beyond the reconstruction of residential exposures. IMPACT: This contribution describes a linkage framework to assign individual-level environmental exposures to population-based cohorts using high-resolution spatio-temporal exposure. The framework can be used to address current limitations of exposure assessment for the analysis of health risks associated with environmental stressors. The linkage of detailed exposure information at the individual level offers the opportunity to define flexible exposure summaries tailored to specific study designs and research questions. The application of the framework is exemplified by the linkage of fine particulate matter (PM2.5) exposures to the UK Biobank cohort.

The influence of humid heat on morbidity of megacity Shanghai in China

BACKGROUND

Increased attention has been paid to humid-heat extremes as they are projected to increase in both frequency and intensity. However, it remains unclear how compound extremes of heat and humidity affects morbidity when the climate is projected to continue warming in the future, in particular for a megacity with a large population.

METHODS

We chose the Wet-Bulb Globe Temperature (WBGT) index as the metric to characterize the humid-heat exposure. The historical associations between daily outpatient visits and daily mean WBGT was established using a Distributed Lag Non-linear Model (DLNM) during the warm season (June to September) from 2013 to 2015 in Shanghai, a prominent megacity of China. Future morbidity burden related to the combined effect of high temperature and humidity were projected under four greenhouse gases (GHGs) emission scenarios (SSP126, SSP245, SSP370 and SSP585).

RESULTS

The humid-heat weather was significantly associated with a higher risk of outpatient visits in Shanghai than the high-temperature conditions. Relative to the baseline period (2010-2019), the morbidity burden due to humid-heat weather was projected to increase 4.4 % (95 % confidence interval (CI): 1.1 %-10.1 %) even under the strict emission control scenario (SSP126) by 2100. Under the high-GHGs emission scenario (SSP585), this burden was projected to be 25.4 % (95 % CI: 15.8 %-38.4 %), which is 10.1 % (95 % CI: 6.5 %-15.8 %) more than that due to high-temperature weather. Our results also indicate that humid-hot nights could cause large morbidity risks under high-GHGs emission scenarios particularly in heat-sensible diseases such as the respiratory and cardiovascular disease by the end of this century.

CONCLUSIONS

Humid heat exposures significantly increased the all-cause morbidity risk in the megacity Shanghai, especially in humid-hot nights. Our findings suggest that the combined effect of elevated temperature and humidity is projected to have more substantial impact on health compared to high temperature alone in a warming climate.

Using a novel strategy to identify the clustered regions of associations between short-term exposure to temperature and mortality and evaluate the inequality of heat- and cold-attributable burdens: A case study in the Sichuan Basin, China

BACKGROUND

Few studies have focused on the spatially clustered regions in the association between short-term exposure to temperature and mortality, which is important for identifying high-susceptibility population and enhancing the prevention of high/low temperatures. Previous studies have explored the association inequality, but no study has evaluated the inequalities of temperature-attributable burdens, which may be more meaningful for reducing temperature-related regional inequality.

METHODS

Taking the Sichuan Basin (SCB), an economically imbalanced area with high humidity and four distinctive seasons, as an example, we used a novel multi-stage strategy to investigate the two issues. First, distributed lag nonlinear models were independently constructed to obtain the county-level associations between daily temperature and cardiorespiratory mortality. Then, an estimation-error-based spatial scan statistic was used to detect the association-clustered regions. Third, multivariate meta-regression incorporating the identified clustered regions and socioeconomic and natural factors was used to obtain stable county-specific associations, based on which the heat- and cold-attributable deaths were mapped and their inequalities were evaluated using concentration indices and Lorenz curves.

RESULTS

On average, a U-shaped temperature-mortality association was examined. A significantly association-clustered region was detected (P = 0.017), in which heat and cold temperatures presented significantly stronger associations than those in the non-clustered region, particularly for heat temperatures. The cold-attributable deaths (3.5%) were substantially more than the heat-attributable deaths (0.5%). Both presented severe inequalities over counties. Significant temperature-attributable inequalities were also found over per-capital public budget, urbanization rate, employment rate and per-capital GDP. The directions of inequalities over GDP and urbanization rate were opposite between heat and cold temperatures.

CONCLUSIONS

Our analysis provided the first evidence about the clustering of temperature-mortality associations and the inequality of cold- and heat-attributable burdens. Significantly association-clustered regions and heavy temperature-attributable inequalities were found in the SCB. Rural people bore heavier cold-attributable but less heat-attributable mortality risk than urban people, suggesting that different policies should be designed to reduce the temperature-attributable inequalities for heat and cold temperatures and different regions. This novel strategy can provide an interesting new perspective in the association between environmental exposure and human health.

Weekly prenatal PM2.5 and NO2 exposures in preterm, early term, and full term infants: Decrements in birth weight and critical windows of susceptibility

BACKGROUND

Previous studies have observed associations between birth weight and prenatal air pollution exposure, but there is not consensus on timing of critical windows of susceptibility.

OBJECTIVE

We estimated the difference in birth weight among preterm, early term and full term births associated with weekly exposure to PM2.5 and NO2 throughout gestation.

METHODS

We included all singleton live births in the Lower Peninsula of Michigan (United States) between 2007 and 2012 occurring at or after 32 weeks gestational age (n = 497,897). Weekly ambient PM2.5 and NO2 concentrations were estimated at maternal residences using 1-km gridded data from ensemble-based models. We utilized a distributed lag nonlinear model to estimate the difference in birth weight associated with weekly exposures from the last menstrual period (week 0) through 31 weeks gestation for preterm births; through 36 weeks gestation for early term births; and through 38 weeks gestation for full term births.

RESULTS

In single-pollutant models, a 5 μg/m3 increase in PM2.5 exposure was associated with a reduction in birth weight among preterm births (-37.1 g [95% confidence interval [CI]: 60.8 g, -13.5 g]); early term births (-13.5 g [95% CI: 26.2 g, -0.67 g]); and full term births (-8.23 g [95% CI: 15.8 g, -0.68 g])]. In single-pollutant models, a 10 ppb increase in NO2 exposure was associated with a -11.7 g (95% CI: 14.46 g, -8.92 g) decrement in birth weight among full term births only. In models co-adjusted for PM2.5 and NO2, PM2.5 exposure was associated with reduced birth weight among preterm births (-36.9 g [95% CI: 61.9 g, -11.8 g]) and NO2 exposure was associated with reduced birth weight among full term births (-11.8 g [95% CI: 14.7 g, -8.94 g]). The largest decrements in birth weight were associated with PM2.5 exposure between approximately 10 and 26 weeks of pregnancy; for NO2 exposure, the largest decrements in birth weight in full term births were associated with exposure between weeks 6-18.

CONCLUSION

We observed the largest and most persistent adverse associations between PM2.5 exposure and birth weight in preterm infants, and between NO2 exposure and birth weight in full term infants. Exposure during the first half of pregnancy had a greater impact on birthweight.

Short-term effects of heatwaves on clinical and subclinical cardiovascular indicators in Chinese adults: A distributed lag analysis

AIMS

Previous studies have related heat waves to morbidity and mortality of cardiovascular diseases; however, potential mechanisms remained limited. Our aims were to investigate the short-term effects of heat waves on a series of clinical/subclinical indicators associated with cardiovascular health.

METHODS

Our study used 80,574 health examination records from the Health Management Center of Nanjing Zhongda Hospital during the warm seasons of 2019-2021, including 62,128 participants. A total of 11 recognized indicators of cardiovascular risk or injury were assessed. Air pollution and meteorological data were obtained from the Nanjing Ecological Environment Bureau and the China Meteorological Data Network, respectively. Heat waves were defined as a daily average temperature over the 95th percentile for three or more consecutive days from May to September. We used a combination of linear mixed effects models and distributed lag nonlinear models to assess the lagged effects of heat waves on clinical and subclinical cardiovascular indicators. Stratified analyses based on individuals' characteristics, including gender, age, body mass index (BMI), diabetes, and hypertension, were also performed.

RESULTS

Heat waves were related to significant changes in most indicators, with the magnitude of effects generally peaking at a lag of 0 to 3 days. Moreover, the cumulative percentage changes over lag 0-7 days were -0.82 % to -2.55 % in blood pressure, 1.32 % in heart rate, 0.20 % to 2.66 % in systemic inflammation markers, 0.36 % in a blood viscosity parameter, 9.36 % in homocysteine, and 1.35 % to 3.25 % in injuring myocardial enzymes. Interestingly, females and males showed distinct susceptibilities in different indicators. Stronger effects were also found in participants aged 50 years or over, individuals with abnormal BMI status, and patients with diabetes.

CONCLUSION

Short-term exposure to heat waves could significantly alter clinical/subclinical cardiovascular indicator profiles, including blood pressure changes, increased heart rate, acute systemic inflammation, elevated blood viscosity, and myocardial injury.

Association of drought conditions and heavy rainfalls with the quality of drinking water in Barcelona (2010-2022)

BACKGROUND

Climate change influences the incidence and scope of climate extreme events that affect communities and the environment around the world. In an urban context such as Barcelona, these climate extremes can have a negative impact on drinking water quality. The worsening of drinking water quality can have important repercussions on human health, leading to the appearance of different diseases.

OBJECTIVE

Investigate the association between climate extremes, in particular heavy rainfall events and drought conditions, and the drinking water quality in the city of Barcelona from 2010 to 2022.

METHODS

We conducted a daily retrospective time-series study using data covering 13 years of daily monitoring of conductivity, nickel, turbidity and trihalomethanes parameters of raw water in the Llobregat River catchment area and treated water in the Drinking Water Treatment Plant (DWTP) Sant Joan Despí. We used river flow as a proxy for drought conditions and heavy rainfall events. We analyzed short-term associations between river flow rate and quality parameters in raw and treated water using generalized linear regression with distributed lag-non-linear models (DLNM).

RESULTS

A low flow, as an indicator of drought condition or low rainfall, was significantly associated with an increase in conductivity in raw water and nickel in both raw and treated water. A high flow, as an indicator of heavy rainfall events, was significantly associated with an increase of turbidity in raw water, and a decrease in all other quality parameters.

IMPACT STATEMENT

This study provides novel evidence that climate extremes have an impact on the quality of drinking water in urban areas with a Mediterranean climate. The findings of this study are significant because they suggest that as the frequency and intensity of climate extremes increase due to climate change, there will be further challenges in managing and treating drinking water, which could have a detrimental effect on public health. This study serves as an important reminder of the need to strengthen and accelerate adaptation actions in water management to ensure an adequate supply of drinking water that protects the people's health.

Impact of heat on mental health emergency visits: a time series study from all public emergency centres, in Curitiba, Brazil

OBJECTIVES

Quantify the risk of mental health (MH)-related emergency department visits (EDVs) due to heat, in the city of Curitiba, Brazil.

DESIGN

Daily time series analysis, using quasi-Poisson combined with distributed lag non-linear model on EDV for MH disorders, from 2017 to 2021.

SETTING

All nine emergency centres from the public health system, in Curitiba.

PARTICIPANTS

101 452 EDVs for MH disorders and suicide attempts over 5 years, from patients residing inside the territory of Curitiba.

MAIN OUTCOME MEASURE

Relative risk of EDV (RREDV) due to extreme mean temperature (24.5°C, 99th percentile) relative to the median (18.02°C), controlling for long-term trends, air pollution and humidity, and measuring effects delayed up to 10 days.

RESULTS

Extreme heat was associated with higher single-lag EDV risk of RREDV 1.03(95% CI 1.01 to 1.05-single-lag 2), and cumulatively of RREDV 1.15 (95% CI 1.05 to 1.26-lag-cumulative 0-6). Strong risk was observed for patients with suicide attempts (RREDV 1.85, 95% CI 1.08 to 3.16) and neurotic disorders (RREDV 1.18, 95% CI 1.06 to 1.31). As to demographic subgroups, females (RREDV 1.20, 95% CI 1.08 to 1.34) and patients aged 18-64 (RREDV 1.18, 95% CI 1.07 to 1.30) were significantly endangered. Extreme heat resulted in lower risks of EDV for patients with organic disorders (RREDV 0.60, 95% CI 0.40 to 0.89), personality disorders (RREDV 0.48, 95% CI 0.26 to 0.91) and MH in general in the elderly ≥65 (RREDV 0.77, 95% CI 0.60 to 0.98). We found no significant RREDV among males and patients aged 0-17.

CONCLUSION

The risk of MH-related EDV due to heat is elevated for the entire study population, but very differentiated by subgroups. This opens avenue for adaptation policies in healthcare: such as monitoring populations at risk and establishing an early warning systems to prevent exacerbation of MH episodes and to reduce suicide attempts. Further studies are welcome, why the reported risk differences occur and what, if any, role healthcare seeking barriers might play.

Projection of extreme heat- and cold-related mortality in Sweden based on the spatial synoptic classification

BACKGROUND

Climate change is projected to result in increased heat events and decreased cold events. This will substantially impact human health, particularly when compounded with demographic change. This study employed the Spatial Synoptic Classification (SSC) to categorize daily weather into one of seven types. Here we estimated future mortality due to extremely hot and cold weather types under different climate change scenarios for one southern (Stockholm) and one northern (Jämtland) Swedish region.

METHODS

Time-series Poisson regression with distributed lags was used to assess the relationship between extremely hot and cold weather events and daily deaths in the population above 65 years, with cumulative effects (6 days in summer, 28 days in winter), 1991 to 2014. A global climate model (MPI-M-MPI-ESM-LR) and two climate change scenarios (RCP 4.5 and 8.5) were used to project the occurrence of hot and cold days from 2031 to 2070. Place-specific projected mortality was calculated to derive attributable numbers and attributable fractions (AF) of heat- and cold-related deaths.

RESULTS

In Stockholm, for the RCP 4.5 scenario, the mean number of annual deaths attributed to heat increased from 48.7 (CI 32.2-64.2; AF = 0.68%) in 2031-2040 to 90.2 (56.7-120.5; AF = 0.97%) in 2061-2070, respectively. For RCP 8.5, heat-related deaths increased more drastically from 52.1 (33.6-69.7; AF = 0.72%) to 126.4 (68.7-175.8; AF = 1.36%) between the first and the last decade. Cold-related deaths slightly increased over the projected period in both scenarios. In Jämtland, projections showed a small decrease in cold-related deaths but no change in heat-related mortality.

CONCLUSIONS

In rural northern region of Sweden, a decrease of cold-related deaths represents the dominant trend. In urban southern locations, on the other hand, an increase of heat-related mortality is to be expected. With an increasing elderly population, heat-related mortality will outweigh cold-related mortality at least under the RCP 8.5 scenario, requiring societal adaptation measures.

Multiple exposure distributed lag models with variable selection

Distributed lag models are useful in environmental epidemiology as they allow the user to investigate critical windows of exposure, defined as the time periods during which exposure to a pollutant adversely affects health outcomes. Recent studies have focused on estimating the health effects of a large number of environmental exposures, or an environmental mixture, on health outcomes. In such settings, it is important to understand which environmental exposures affect a particular outcome, while acknowledging the possibility that different exposures have different critical windows. Further, in studies of environmental mixtures, it is important to identify interactions among exposures and to account for the fact that this interaction may occur between two exposures having different critical windows. Exposure to one exposure early in time could cause an individual to be more or less susceptible to another exposure later in time. We propose a Bayesian model to estimate the temporal effects of a large number of exposures on an outcome. We use spike-and-slab priors and semiparametric distributed lag curves to identify important exposures and exposure interactions and discuss extensions with improved power to detect harmful exposures. We then apply these methods to estimate the effects of exposure to multiple air pollutants during pregnancy on birthweight from vital records in Colorado.

Effect of Ambient Temperature on Hospital Admissions for Respiratory Disease in Suburban Rural Villages of a Semi-Arid Region in Northwest China

OBJECTIVE

This study evaluated the effects of extreme temperatures on hospital admissions for respiratory diseases (RDs) in a semi-arid region in the Northwest of China.

METHODS

Distributed lag nonlinear model was constructed, and stratified analysis by gender and age was performed.

RESULTS

The exposure-response curve between temperature and RD hospital admissions was almost W-shaped. Either extremely cold temperatures or moderately cold temperatures presented a short-term acute harmful effect, and the relative risks were higher among males (1.976, 95% confidence interval [CI]: 1.773-2.203; 1.242, 95% CI: 1.203-1.282) and the elderly (2.363, 95% CI: 1.724-3.240; 1.267, 95% CI: 1.154-1.390). Both extreme and moderately hot temperatures had higher risks among females (2.040, 95% CI: 1.815-2.292; 1.328, 95% CI: 1.276-1.381).

CONCLUSIONS

The relationship between air temperature and RD hospital admissions was nonlinear. Vulnerable populations varied according to extreme temperature conditions.

Ambient temperature and preeclampsia: A historical cohort study

Previous studies found inconsistent associations between ambient temperature during pregnancy and the risk of preeclampsia. If such associations are causal, they may impact the future burden of preeclampsia in the context of climate change. We used a historical cohort of 129,009 pregnancies (5074 preeclampsia cases) from southern Israel that was merged with temperature assessments from a hybrid satellite-based exposure model. Distributed-lag and cause-specific hazard models were employed to study time to all preeclampsia cases, followed by stratification according to early (≤34 weeks) and late (>34 weeks) onset disease and identify critical exposure periods. We found a positive association between temperature and preeclampsia during gestation, which was stronger in the 3rd trimester. For example, during week 33, compared to the reference temperature of 22.4 °C, the cause-specific hazard ratio (HRCS) of preeclampsia was 1.01 (95% confidence interval (CI): 1.01-1.02) when exposed to 30 °C, 1.05 (95%CI: 1.03-1.08) at 35 °C, and 1.07 (95%CI: 1.04-1.10) at 37 °C. The associations existed with both early- and late-onset preeclampsia; however, the associations with the early-onset disease were somewhat stronger, limited to the first weeks of pregnancy and the third trimester, and with larger confidence intervals. The HRCS for early preeclampsia onset, when exposed to 37 °C compared to 22.4 °C during week 33, was 1.12 (95%CI: 0.96-1.30), and for late-onset preeclampsia, the HRCS was 1.09 (95%CI: 1.05-1.13). To conclude, exposure to high temperatures at the beginning and, particularly, the end of gestation is associated with an increased risk of preeclampsia in southern Israel.

Association between thermal stress and cardiovascular mortality in the subtropics

Hazardous thermal conditions resulting from climate change may play a role in cardiovascular disease development. We chose the Universal Thermal Climate Index (UTCI) as the exposure metric to evaluate the relationship between thermal conditions and cardiovascular mortality in Shenzhen, China. We applied quasi-Poisson regression non-linear distributed lag models to evaluate the exposure-response associations. The findings suggest that cardiovascular mortality risks were significantly increased under heat and cold stress, and the adverse effects of cold stress were stronger than heat stress. Referencing the 50th percentile of UTCI (25.4°C), the cumulative risk of cardiovascular mortality was 75% (RRlag0-21 =1.75, 95%CI: 1.32, 2.32) higher in the 1st percentile (3.5°C), and 40% (RRlag0-21=1.40, 95%CI: 1.09, 1.80) higher in the 99th percentile (34.1°C). We observed that individuals older than 65 years were more vulnerable to both cold and heat stress, and females were identified as more susceptible to heat stress than males. Moreover, increased mortality risks of hypertensive disease and cerebrovascular disease were observed under cold stress, while heat stress was related to higher risks of mortality for hypertensive disease and ischemic heart disease. We also observed a stronger relationship between cold stress and ischemic heart disease mortality during the cold season, as well as a significant impact of heat stress on cerebrovascular disease mortality in the warm season when compared to the analysis of the entire year. These results confirm the significant relationship between thermal stress and cardiovascular mortality, with age and sex as potential effect modifiers of this association. Providing affordable air conditioning equipment, increasing the amount of vegetation, and establishing comprehensive early warning systems that take human thermoregulation into account could all help to safeguard the well-being of the public, particularly vulnerable populations, in the event of future extreme weather.

Detecting the spatial clustering of exposure-response relationships with estimation error: a novel spatial scan statistic

Detecting the spatial clustering of the exposure-response relationship (ERR) between environmental risk factors and health-related outcomes plays important roles in disease control and prevention, such as identifying highly sensitive regions, exploring the causes of heterogeneous ERRs, and designing region-specific health intervention measures. However, few studies have focused on this issue. A possible reason is that the commonly used cluster-detecting tool, spatial scan statistics, cannot be used for multivariate spatial datasets with estimation error, such as the ERR, which is often defined by a vector with its covariance estimated by a regression model. Such spatial datasets have been produced in abundance in the last decade, which suggests the importance of developing a novel cluster-detecting tool applicable for multivariate datasets with estimation error. In this work, by extending the classic scan statistic, we developed a novel spatial scan statistic called the estimation-error-based scan statistic (EESS), which is applicable for both univariate and multivariate datasets with estimation error. Then, a two-stage analytic process was proposed to detect the spatial clustering of ERRs in practical studies. A published motivating example and a simulation study were used to validate the performance of EESS. The results show that the clusters detected by EESS can efficiently reflect the clustering heterogeneity and yield more accurate ERR estimates by adjusting for such heterogeneity.

Differentiating the impacts of ambient temperature on pneumonia mortality of various infectious causes: a nationwide, individual-level, case-crossover study

BACKGROUND

It remains unknown how ambient temperature impact pneumonia of various infectious causes.

METHODS

Based on the national death registry covering all counties in Chinese mainland, we conducted an individual-level case-crossover study in China from 2013 to 2019. Exposures were assigned at residential addresses for each decedent. Conditional logistic regression model combined with distributed lag non-linear models were used to estimate the exposure-response associations. The attributable fractions due to non-optimum temperature were calculated after accounting for spatial and temporal patterns for the excess risks.

FINDINGS

The exposure-response curves were inversely J-shaped with both low and high temperature increasing the risks, and the effect of low temperature was stronger. Extremely low temperature was associated with higher magnitude of influenza-related pneumonia [relative risk (RR): 2.46, 95% confidence interval (CI): 1.62-3.74], than viral pneumonia (RR: 1.89, 95% CI: 1.55-2.30) and bacterial pneumonia (RR: 1.81, 95% CI: 1.56-2.09). The magnitudes of RRs associated with extremely high temperature were similar among the three categories of pneumonia. The mortality attributable fraction for influenza-related pneumonia (29.78%) was the highest. The effects were stronger in people of low education level or residence in the north.

INTERPRETATION

This nationwide study presents findings on the varied risk and burden of pneumonia mortality of various infectious causes, and highlights the susceptibility of influenza-related pneumonia to ambient low temperature.

FUNDING

This study is supported by the National Key Research and Development Program (2022YFC3702701), the Shanghai Municipal Science and Technology Commission (21TQ015) and Shanghai International Science and Technology Partnership Project (21230780200).

Critical Windows of Maternal Exposure to Biothermal Stress and Birth Weight for Gestational Age in Western Australia

BACKGROUND

There is limited and inconsistent evidence on the risk of ambient temperature on small for gestational age (SGA) and there are no known related studies for large for gestational age (LGA). In addition, previous studies used temperature rather than a biothermal metric.

OBJECTIVES

Our aim was to examine the associations and critical susceptible windows of maternal exposure to a biothermal metric [Universal Thermal Climate Index (UTCI)] and the hazards of SGA and LGA.

METHODS

We linked 385,337 singleton term births between 1 January 2000 and 31 December 2015 in Western Australia to daily spatiotemporal UTCI. Distributed lag nonlinear models with Cox regression and multiple models were used to investigate maternal exposure to UTCI from 12 weeks preconception to birth and the adjusted hazard ratios (HRs) of SGA and LGA.

RESULTS

Relative to the median exposure, weekly and monthly specific exposures showed potential critical windows of susceptibility for SGA and LGA at extreme exposures, especially during late gestational periods. Monthly exposure showed strong positive associations from the 6th to the 10th gestational months with the highest hazard of 13% for SGA (HR = 1.13 ; 95% CI: 1.10, 1.14) and 7% for LGA (HR = 1.07 ; 95% CI: 1.03, 1.11) at the 10th month for the 1st UTCI centile. Entire pregnancy exposures showed the strongest hazards of 11% for SGA (HR = 1.11 ; 95% CI: 1.04, 1.18) and 3% for LGA (HR = 1.03 ; 95% CI: 0.95, 1.11) at the 99th UTCI centile. By trimesters, the highest hazards were found during the second and first trimesters for SGA and LGA, respectively, at the 99th UTCI centile. Based on estimated interaction effects, male births, mothers who were non-Caucasian, smokers, ≥ 35 years of age, and rural residents were most vulnerable.

CONCLUSIONS

Both weekly and monthly specific extreme biothermal stress exposures showed potential critical susceptible windows of SGA and LGA during late gestational periods with disproportionate sociodemographic vulnerabilities. https://doi.org/10.1289/EHP12660.