Distributed Lag Non-linear Model Research Articles

Effect of short-term exposure to air pollution on hospital admission for cardiovascular disease: A time-series study in Xiangyang, China

BackgroundData on the relationship between short-term exposure to air pollution and cardiovascular diseases (CVDs) and the potential modifying factors are limited and inconsistent. ObjectiveTo explore the relationship between short-term exposure to air pollution and CVD risk, and potential modification effect factors. MethodA time series study was conducted on 52,991 hospital admissions for CVD from 2015 to 2019 in Xiangyang City, China. Air pollution data from four national fixed monitoring stations were collected to estimate exposure level in Xiangyang City. A quasi-Poisson generalized additive model incorporating a distributed lag nonlinear model was applied to evaluate the association between air pollution and CVD risk. The potential modification effect of sex, age, and season on the above associations was also evaluated. ResultsCVD risk was positively associated with air pollution. Peak associations in single lag day structures were observed for particulate matter ≤10 μm in aerodynamic (PM10; RR: 1.040, 95 % CI: 0.996–1.087), PM2.5 (1.025, 1.004–1.045), nitrogen dioxide (NO2; 1.074, 1.039–1.111), and sulfur dioxide (SO2; 1.079, 1.019–1.141) at Lag 0 and ozone (O3; 1.018, 1.004–1.031) at Lag 4. In cumulative lag day structures, the highest RRs were 1.225 (1.079,1.392) for PM10 at Lag 06, 1.054 (1.013, 1.098) for PM2.5 at Lag 03, 1.200 (1.119, 1.287) for NO2 at Lag 04, and 1.135 (1.025, 1.257) for SO2 at Lag 02. Moreover, the association between air pollution and CVD risk was modified by sex and age (P < 0.05). Females and individuals aged ≤65 years were more vulnerable to NO2 and had a higher CVD risk. ConclusionShort-term exposure to air pollution was positively associated with CVD risk. Moreover, sex and age could modify the effect of air pollution on CVD risk. Females and individuals aged ≤65 years had a higher NO2 exposure-induced CVD risk.

Short-term exposure to extreme temperature and outpatient visits for respiratory diseases among children in the northern city of China: a time-series study.

Although studies have indicated that extreme temperature is strongly associated with respiratory diseases, there is a dearth of studies focused on children, especially in China. We aimed to explore the association between extreme temperature and children's outpatient visits for respiratory diseases and seasonal modification effects in Harbin, China. A distributed lag nonlinear model (DLNM) was used to explore the effect of extreme temperature on daily outpatient visits for respiratory diseases among children, as well as lag effects and seasonal modification effects. Extremely low temperatures were defined as the 1st percentile and 2.5th percentile of temperature. Extremely high temperatures were defined as the 97.5th percentile and 99th percentile of temperature. At extremely high temperatures, both 26°C (97.5th) and 27°C (99th) showed adverse effects at lag 0-6 days, with relative risks (RRs) of 1.34 [95% confidence interval (CI): 1.21-1.48] and 1.38 (95% CI: 1.24-1.53), respectively. However, at extremely low temperatures, both - 26°C (1st) and - 23°C (2.5th) showed protective effects on children's outpatient visits for respiratory diseases at lag 0-10 days, with RRs of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.95), respectively. We also found seasonal modification effects, with the association being stronger in the warm season than in the cold season at extremely high temperatures. Our study indicated that extremely hot temperatures increase the risk of children's outpatient visits for respiratory diseases. Efforts to reduce the exposure of children to extremely high temperatures could potentially alleviate the burden of pediatric respiratory diseases, especially during the warm season.

Associations between short-term exposure to ambient temperature and renal disease mortality in Japan during 1979-2019: A time-stratified case-crossover analysis.

Previous studies have indicated that renal disease mortality is sensitive to ambient temperatures. However, most have been limited to the summer season with inconclusive evidence for changes in population vulnerability over time. This study aims to examine the association between short-term exposure to ambient temperatures and mortality due to renal diseases in Japan, and how this association varied over time. We conducted a two-stage, time-stratified case-crossover study from 1979 to 2019 across 47 prefectures of Japan. We obtained the data of daily mortality counts for all renal diseases, acute renal failure, and chronic renal disease. We fitted a conditional quasi-Poisson regression model with a distributed lag nonlinear model. A random-effects meta-analysis was applied to calculate national averages. We performed additional analyses by four subperiods, sex, and age groups. We analyzed 997,590 renal mortality cases and observed a reversed J-shaped association. Lower temperatures were associated with increased mortality in all renal disease categories. The cumulative relative risks at 2.5th percentile compared to the minimum mortality temperature percentile were 1.34 (95% confidence interval [CI] = 1.29, 1.40), 1.51 (95% CI = 1.33, 1.71), and 1.33 (95% CI = 1.24, 1.43) for all renal, acute renal failure, and chronic renal disease mortality, respectively. The associations were observed in individuals of both sexes and aged 65 years and above. The associations of kidney mortality with low temperature remained consistent, while the associations with high temperature were pronounced in the past, but not in recent periods. Protection for individuals with impaired renal function from exposure to low temperatures during cold seasons is warranted.

Impact of urban outdoor thermal conditions on selected hospital admissions in Novi Sad, Serbia

Climate change has been recognized as an important issue in public health, with particular concerns being raised about the effects of heat and cold extremes on health, and about seasonal changes over the year and their associations with increased mortality and hospitalizations. This paper explored the relationship between physiological equivalent temperature (PET) and cardiovascular and respiratory hospital admissions in Novi Sad (Serbia) with the aim of assessing the impact of urban outdoor thermal conditions on health. Analysis was performed using daily data on cardiovascular and respiratory hospital admissions by gender covering the period from January 1, 2016 to December 31, 2017. For the same period, PET was calculated using data from two urban meteorological network stations. The association between PET and hospital admissions was examined using a generalized additive model (GAM) combined with a distributed lag non-linearmodel (DLNM). The study found a non-linear relationship between PET and cardiovascular and respiratory hospital admissions, with a larger impact during the cold period of the year. The findings also indicated that under conditions of high PET, the cumulative RR increased for cardiovascular admissions (for males) and respiratory admissions (for females). People with pre-existing respiratory diseases were found to be more vulnerable under conditions of extremely low and moderately low PET, with a greater effect at lag 0–14 days. By contrast, for people with cardiovascular diseases, low PET was linked to a decrease in hospital admissions, with the risk being lowest at lag 0 and 0–3 days.

The association between ambient temperature and semen quality in a Northern Peninsular Province, China.

Extreme ambient temperature has been linked to decline in males' semen quality. Although the temperature-semen quality association has been examined in certain cities of South China, how the effect size of the extreme temperature may lag over critical windows in spermatogenesis and whether the strength of association may vary in North China have yet been adequately explored. To quantify the association between air temperature and semen quality, and identify critical exposure windows in a Northern Peninsular Province, China. Data on semen quality in 2014-2019 were collected from the Human Sperm Bank of Institute of Women, Children and Reproductive Health, Shandong University, China. Daily meteorological data (0.01°×0.01°) were assigned to each subject's residential address. The linear mixed-effect model combined with the distributed lag nonlinear model was used to estimate the effect of ambient temperature over critical spermatogenesis windows. The temperature-semen quality association was inverted V-shaped, with the maximum lag being 0-45 days before ejaculation and the threshold being 9.2°C. Progressively and total motile sperm number, and total sperm number declined more substantially than other semen quality parameters. Semen quality was more sensitive to cold exposure during the epididymal storage period than the sperm motility development period. By contrast, semen quality was insensitive to heat exposure during both critical spermatogenesis windows. Impairment of certain semen quality parameters was more obvious for males with higher educational attainment and those aged over 35 years. Exposure to non-optimal temperature is associated with decreased semen quality in North China, with the epididymal storage and sperm motility development periods more sensitive to cold exposure than heat. Older males and those with higher educations may need particular awareness.

An investigation of the effects of meteorological factors on the incidence of tuberculosis

To explore the influence of meteorological factors on the incidence of tuberculosis (TB) in Yingjisha County, Kashgar Region, Xinjiang, and to provide a scientific basis for the prevention and control of TB. The Spearman correlation analysis and distribution lag nonlinear model analysis were conducted on the number of daily reported cases of TB from 2016 to 2023 to study the association effect of various meteorological factors and the daily incidence number of TB in Yingjisha County. A total of 13,288 TB cases were reported from January 2016 to June 2023, and June to October is the peak period of annual TB incidence. Spearman correlation analysis revealed that average daily temperature (AT) and average daily wind speed (WS) were positively correlated with TB incidence (rAT = 0.110, rWS = 0.090); and average daily relative humidity (RH) and TB incidence was negatively correlated (rRH = − 0.093). When AT was − 15 °C, the RR reached a maximum of 2.20 (95% CI: 0.77–6.29) at a lag of 21 days. When RH was 92%, the RR reached a maximum of 1.05 (95% CI: 0.92–1.19) at a lag of 6 days. When WS was 5.2 m/s, the RR reached a maximum of 1.30 (95% CI: 0.78–2.16) at a lag of 16 days. There is a non-linearity and a certain lag between meteorological factors and the occurrence and prevalence of TB in the population, which is mainly manifested in the fact that the risk of incidence of TB decreases with the increase of the daily AT, has a hazardous effect within a certain range of humidity as the average daily RH rises, and gradually increases with the increase of the average daily WS. Local residents are advised to pay attention to climate change so as to take appropriate preventive measures, especially women and middle and old age group should pay close attention to climate change and add more clothes in time, minimise travelling in hazy weather and windy and sandy weather, maintain good nutrition, adequate sleep and moderate exercise in daily life to enhance their immunity, wash hands frequently and ventilate the air, and try to avoid staying in humid and confined spaces in order to reduce the risk of latent TB patients developing the disease.

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

IntroductionNeighborhood 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. MethodsThis 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). ResultsOur 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. ConclusionsNeighborhood 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.

How multiple air pollutants affect hand, foot, and mouth disease incidence in children: assessing effect modification by geographical context in multicity of Sichuan, southwest China

BackgroundSeveral studies have suggested a significant association of hand, foot, and mouth disease (HFMD) with ambient air pollutants. Existing studies have characterized the role of air pollutants on HFMD using only risk ratio measures while ignoring the attributable burden. And whether the geographical context (i.e., diverse topographic features) could modulate the relationships is unclear.MethodsDaily reported childhood HFMD counts, ambient air pollution, and meteorological data during 2015–2017 were collected for each of 21 cities in Sichuan Province. A multistage analysis was carried out in different populations based on geographical context to assess effect modification by topographic conditions. We first constructed a distributed lag nonlinear model (DLNM) for each city to describe the relationships with risk ratio measures. Then, we applied a multivariate meta-regression to estimate the pooled effects of multiple air pollutants on HFMD from the exposure and lagged dimensions. Finally, attributable risks measures were calculated to quantify HFMD burden by air pollution.ResultsBased on 207554 HFMD cases in Sichuan Province, significant associations of HFMD with ambient air pollutants were observed mainly at relatively high exposure ranges. The effects of ambient air pollutants on HFMD are most pronounced on lag0 or around lag7, with relative risks gradually approaching the reference line thereafter. The attributable risks of O3 were much greater than those of other air pollutants, particularly in basin and mountain regions.ConclusionsThis study revealed significant pooled relationships between multiple air pollutants and HFMD incidence from both exposure and lag dimensions. However, the specific effects, including RRs and ARs, differ depending on the air pollution variable and geographical context. These findings provide local authorities with more evidence to determine key air pollutants and regions for devising and implementing targeted interventions.

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

IntroductionSome 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. Objectives1) 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. MethodsA 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. ResultsThe 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. ConclusionsThe 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.

Effects of extreme temperature events on deaths and its interaction with air pollution

BackgroundBoth extreme temperature events (ETEs) and air pollution affected human health, and their effects were often not independent. Previous studies have provided limited information on the interactions between ETEs and air pollution. MethodsWe collected data on deaths (non-accidental, cardiovascular, and respiratory) in Zibo City along with daily air pollution and meteorological data from January 2015 to December 2019. Distributed lag non-linear model was used to explore the health effects of ETEs on deaths. Non-parametric binary response model, hierarchical model and joint effect model were used to further explore the interaction between ETEs and air pollution in different seasons. Meanwhile, subgroup analysis by gender and age (≥ 65 years old and < 65 years old) was conducted to identify the vulnerable population. ResultsETEs increased death risk, especially for cardiovascular and respiratory deaths. Heat waves had a stronger impact than cold spells. Cold spells had a longer lag and fluctuating trend. Heat waves had a short-term impact, followed by a decrease. Females and those aged ≥ 65 were more affected, but subgroup differences were not significant. During ETEs and non-ETEs, there were different effects on deaths with per IQR increase in air pollutant concentrations. Joint effect models revealed that there was a significant interaction between ETEs and air pollution on non-accidental deaths. The interaction between PM2.5 and cold spells was antagonistic in the cold season. In the warm season, the health effects of heat waves and high O3 concentration were enhanced. The relative excess risk due to interaction (RERI) of cold spells and PM2.5 in total population was −0.09 (95 % CI: −0.17, −0.01), and 9 % (95 % CI: 1 %, 17 %) of the total effect was attributable to interaction. Subgroup analysis confirmed the interactions in females and those aged ≥ 65. ConclusionsSignificant association observed between ETEs and deaths. Females and ≥ 65 age groups were vulnerable. There were interactions between ETEs and air pollution. The effect of PM2.5 on deaths decreased during cold spells, while the effect of O3 increased during heat waves. In addition to improving air quality, it is necessary to further strengthen the prevention and control of ETEs.

Enabling countries to manage outbreaks: statistical, operational, and contextual analysis of the early warning and response system (EWARS-csd) for dengue outbreaks.

Dengue is currently the fastest-spreading mosquito-borne viral illness in the world, with over half of the world's population living in areas at risk of dengue. As dengue continues to spread and become more of a health burden, it is essential to have tools that can predict when and where outbreaks might occur to better prepare vector control operations and communities' responses. One such predictive tool, the Early Warning and Response System for climate-sensitive diseases (EWARS-csd), primarily uses climatic data to alert health systems of outbreaks weeks before they occur. EWARS-csd uses the robust Distribution Lag Non-linear Model in combination with the INLA Bayesian regression framework to predict outbreaks, utilizing historical data. This study seeks to validate the tool's performance in two states of Colombia, evaluating how well the tool performed in 11 municipalities of varying dengue endemicity levels. The validation study used retrospective data with alarm indicators (mean temperature and rain sum) and an outbreak indicator (weekly hospitalizations) from 11 municipalities spanning two states in Colombia from 2015 to 2020. Calibrations of different variables were performed to find the optimal sensitivity and positive predictive value for each municipality. The study demonstrated that the tool produced overall reliable early outbreak alarms. The median of the most optimal calibration for each municipality was very high: sensitivity (97%), specificity (94%), positive predictive value (75%), and negative predictive value (99%; 95% CI). The tool worked well across all population sizes and all endemicity levels but had slightly poorer results in the highly endemic municipality at predicting non-outbreak weeks. Migration and/or socioeconomic status are factors that might impact predictive performance and should be further evaluated. Overall EWARS-csd performed very well, providing evidence that it should continue to be implemented in Colombia and other countries for outbreak prediction.

Impact of cash transfers on the association between prenatal exposures to high temperatures and low birthweight: Retrospective analysis from the LEAP 1000 study.

To explore the associations between prenatal temperature exposures and low birthweight (LBW) and modification by cash transfer (CT) receipt. Retrospective cohort study. Five rural districts in Northern Ghana. A total of 3016 infants born to women interviewed as part of the Livelihood Empowerment Against Poverty (LEAP 1000) impact evaluation between 2015 and 2017. Birthweight was collected using household surveys administered to LEAP 1000 eligible women. We used a UNICEF-developed multiple imputation approach to address missingness of birthweight and applied an empirical heaping correction to the multiply imputed birthweight data. Survey data were linked to the European Centre for Medium-Range Weather Forecasts Reanalysis 5-hourly temperature averaged to weeks for 2011-2017 using community centroids. Using distributed-lag nonlinear models, we explored the lag-specific associations between weekly average temperatures greater than 30°C and LBW, and stratified by LEAP 1000 treatment. Low birthweight (<2.5 kg). Twelve percent (n = 365) of infants were LBW; the mean ± SD birthweight was 3.02 ± 0.37 kg. Overall, increasing temperatures were associated with increased odds of LBW, with the greatest odds observed in the 3 weeks before birth (odds ratio 1.005-1.025). These positive associations were even larger among comparison infants and null among treatment infants. Our study found increased odds of LBW with high weekly average temperatures throughout pregnancy and the preconception period and demonstrate mitigated effects by the LEAP 1000 CT program. More evidence on the potential of CTs to serve as adaptation interventions in low- and middle-income countries is needed to protect pregnant persons and their infantsfrom the impacts of climate change.

Ambient Temperature Effects on Hospitalization Risk Among Farmers: A Time-Series Study on Multiple Diseases in Vietnam.

The aim of the study is to assess the effect of high temperatures on hospitalization for all causes and heat-sensitive diseases among Vietnamese farmers. The Poisson generalized linear model and distributed lag nonlinear model were used to investigate the temperature-hospitalization association for all causes and seven cause-specific disease groups. Every 1°C increase in daily mean temperature above the threshold increased the estimated relative risk (95% CI) of all-cause hospitalization by 1.022 (0.998-1.047) at the country level, 1.047 (1.007-1.089) in the south, and 0.982 (0.958-1.006) in the north. Infectious disease hospitalization was most affected by high temperatures (1.098 [1.057-1.140]). High temperatures significantly increased the risk of all-cause hospitalization for farmers 60 years and younger in three of the six provinces. The findings emphasized the need for health promotion programs to prevent heat-related health issues.

Short-term high temperature may increase the incidence risk of collective conflicts: A case-crossover study in the Greater Middle East

BackgroundViolent conflict is a formidable global challenge, with long-lasting impacts on individual health and society security. There has been compelling evidence that heat can increase aggression intention on the individual level. However, little is known about the short-term relationship between ambient temperature and collective violent conflicts, especially in less developed regions. MethodWe conducted a time-stratified case-crossover study combined with the distributed lag nonlinear model (DLNM) among 247,773 violent conflicts from 29 countries or regions in the Greater Middle East, between 1997 and 2021. Potential modification effects of economic status and climate conditions were explored by stratified analyses. Negative control and sensitivity analyses were also performed to test the robustness of our model. ResultsWe observed significant associations between higher temperature and the onset of five categories of violent conflicts. The effects generally occurred within the first several days after exposure. The incidence risks of battles, violence against civilians, explosions/remote violence, protests and riots were 1.60 [95 % confidence interval (CI): 1.31–1.95], 1.82 (95 % CI: 1.37–2.42), 1.24 (95 % CI: 1.08–1.41), 1.16 (95 % CI: 1.09–1.24) and 1.54 (95 % CI: 1.22–1.95) when comparing extreme high temperatures to minimum-risk temperatures. The associations were generally more prominent in areas with lower economic levels and associations in regions of the continental climate are also stronger. ConclusionsOur finding reveals novel and concrete evidence that short-term high temperature could increase the risk of multiple forms of violent conflict in the Greater Middle East and provides new insights into the potential short-term mechanisms under the heat-collective violence association.

Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China

Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1–2.5, and coarse particles (PM2.5–10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015–2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 μg/m3 for PM1, PM1–2.5, PM2.5, PM10 and PM2.5–10. An inter-quartile range increase for PM1, PM1–2.5, PM2.5, PM10 and PM2.5–10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3–51.9%), 53.7% (22.4–93.1%), 32.6% (15.0–53.0%), 35.1% (17.7–55.0%) and 25.9% (13.0–40.3%) in MD-related deaths at lag 0–3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75–84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1–2.5, PM2.5, PM10 and PM2.5–10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.

The role of meteorological factors on influenza incidence among children in Guangzhou China, 2019-2022.

Analyzing the epidemiological characteristics of influenza cases among children aged 0-17 years in Guangzhou from 2019 to 2022. Assessing the relationships between multiple meteorological factors and influenza, improving the early warning systems for influenza, and providing a scientific basis for influenza prevention and control measures. The influenza data were obtained from the Chinese Center for Disease Control and Prevention. Meteorological data were provided by Guangdong Meteorological Service. Spearman correlation analysis was conducted to examine the relevance between meteorological factors and the number of influenza cases. Distributed lag non-linear models (DLNM) were used to explore the effects of meteorological factors on influenza incidence. The relationship between mean temperature, rainfall, sunshine hours, and influenza cases presented a wavy pattern. The correlation between relative humidity and influenza cases was illustrated by a U-shaped curve. When the temperature dropped below 13°C, Relative risk (RR) increased sharply with decreasing temperature, peaking at 5.7°C with an RR of 83.78 (95% CI: 25.52, 275.09). The RR was increased when the relative humidity was below 66% or above 79%, and the highest RR was 7.50 (95% CI: 22.92, 19.25) at 99%. The RR was increased exponentially when the rainfall exceeded 1,625 mm, reaching a maximum value of 2566.29 (95% CI: 21.85, 3558574.07) at the highest rainfall levels. Both low and high sunshine hours were associated with reduced incidence of influenza, and the lowest RR was 0.20 (95% CI: 20.08, 0.49) at 9.4 h. No significant difference of the meteorological factors on influenza was observed between males and females. The impacts of cumulative extreme low temperature and low relative humidity on influenza among children aged 0-3 presented protective effects and the 0-3 years group had the lowest RRs of cumulative extreme high relative humidity and rainfall. The highest RRs of cumulative extreme effect of all meteorological factors (expect sunshine hours) were observed in the 7-12 years group. Temperature, relative humidity, rainfall, and sunshine hours can be used as important predictors of influenza in children to improve the early warning system of influenza. Extreme weather reduces the risk of influenza in the age group of 0-3 years, but significantly increases the risk for those aged 7-12 years.

Association of air pollution and weather conditions during infection course with COVID-19 case fatality rate in the United Kingdom

Although the relationship between the environmental factors, such as weather conditions and air pollution, and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed. We developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone, N{O}_{2}, S{O}_{2}, CO, P{M}_{10} and P{M}_{2.5}) using data between March 26, 2020 and September 15, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria and the closeness between the predicted and observed values of CFR. The risk of death reached its maximum level when the low temperature (6 °C) occurred 1 day before (OR 1.59; 95% CI 1.52–1.63), prolonged sunlight duration (11–14 h) 3 days after (OR 1.24; 95% CI 1.18–1.30) and increased P{M}_{2.5} (19 μg/m3) 1 day after the onset of symptom (OR 1.12; 95% CI 1.09–1.16). After reopening, many COVID-19 cases will be identified after their symptoms appear. The findings highlight the importance of designing different preventive measures against severe illness or death considering the time before and after symptom onset.

Socio-environmental modifiers of heat-related mortality in eight Swiss cities: A case time series analysis

In the light of growing urbanization and projected temperature increases due to climate change, heat-related mortality in urban areas is a pressing public health concern. Heat exposure and vulnerability to heat may vary within cities depending on structural features and socioeconomic factors. This study examined the effect modification of the temperature-mortality association of three socio-environmental factors in eight Swiss cities and population subgroups (<75 and ≥ 75 years, males, females): urban heat islands (UHI) based on within-city temperature contrasts, residential greenness measured as normalized difference vegetation index (NDVI) and neighborhood socioeconomic position (SEP). We used individual death records from the Swiss National Cohort occurring during the warm season (May to September) in the years 2003–2016. We performed a case time series analysis using conditional quasi-Poisson and distributed lag non-linear models with a lag of 0–3 days. As exposure variables, we used daily maximum temperatures (Tmax) and a binary indicator for warm nights (Tmin ≥20 °C).In total, 53,593 deaths occurred during the study period. Overall across the eight cities, the mortality risk increased by 31% (1.31 relative risk (95% confidence interval: 1.20–1.42)) between 22.5 °C (the minimum mortality temperature) and 35 °C (the 99th percentile) for warm-season Tmax. Stratified analysis suggested that the heat-related risk at 35 °C is 26% (95%CI: −4%, 67%) higher in UHI compared to non-UHI areas. Indications of smaller risk differences were observed between the low vs. high greenness strata (Relative risk difference = 13% (95%CI: −11%; 44%)). Living in low SEP neighborhoods was associated with an increased heat related risk in the non-elderly population (<75 years). Our results indicate that UHI are associated with increased heat-related mortality risk within Swiss cities, and that features beyond greenness are responsible for such spatial risk differences.

The short-term effect of ambient particulate matter on suicide death

BackgroundAir pollution can cause various respiratory and neurological diseases and continuous exposure can lead to death. Previous studies have reported that particulate matter (PM) exposure increases the risk of depression, suicidal thoughts, and suicidal death; however, the results are inconsistent and limited. This study aimed to examine the relationship between short-term PM exposure and suicide deaths, as well as investigate the short-term effects of PM on suicide death within vulnerable groups based on factors such as sex, age group, suicide-related information (note, method, and cause), psychiatric disorders, and physical diseases.MethodsData on a total of 28,670 suicide deaths from 2013 to 2017, provided by the Korea Foundation for Suicide Prevention, were analyzed. The study design employed a time-series analysis with a two-stage approach. In the first step, a generalized additive model combined with a distributed lag nonlinear model was used to estimate the short-term effect of PM exposure on suicide risk specific to each city. In the second step, the estimated results from each city were pooled through a meta-analysis to derive the overall effect. We determined the effects of single lag, cumulative lag, and moving average PM concentrations from days 0–7 before suicide.ResultsWe confirmed an association between exposure to PM10 (≤ 10 μm in diameter) and deaths due to suicide. In particular, among individuals with psychiatric disorders and those who employed non-violent suicide methods, increased exposure to PM10 was associated with a higher risk of death by suicide, with percentage changes of 5.92 (95% confidence interval [CI]: 3.95–7.92) and 11.47 (95% CI: 7.95–15.11), respectively. Furthermore, in the group with psychiatric disorders, there was an observed tendency of increasing suicide risk as PM10 levels increased up to 120 µg/m3, whereas in the group with non-violent suicide deaths, there was a pronounced trend of rapid increase in suicide risk with an increase in PM10 up to 100 µg/m3.ConclusionsThese results show an association between short-term exposure to PM and suicide. Our study adds evidence for the benefits of reducing PM in preventing diseases and improving mental health.

Relation of prenatal and postnatal PM2.5 exposure with cognitive and motor function among preschool-aged children

The literature informing susceptible periods of exposure on children's neurodevelopment is limited. We evaluated the impacts of pre- and postnatal fine particulate matter (PM2.5) exposure on children's cognitive and motor function among 1303 mother-child pairs in the Spanish INMA (Environment and Childhood) Study. Random forest models with temporal back extrapolation were used to estimate daily residential PM2.5 exposures that we averaged across 1-week lags during the prenatal period and 4-week lags during the postnatal period. The McCarthy Scales of Children's Abilities (MSCA) were administered around 5 years to assess general cognitive index (GCI) and several subscales (verbal, perceptual-performance, memory, fine motor, gross motor). We applied distributed lag nonlinear models within the Bayesian hierarchical framework to explore periods of susceptibility to PM2.5 on each MSCA outcome. Effect estimates were calculated per 5 μg/m3 increase in PM2.5 and aggregated across adjacent statistically significant lags using cumulative β (βcum) and 95% Credible Intervals (95%CrI). We evaluated interactions between PM2.5 with fetal growth and child sex. We did not observe associations of PM2.5 exposure with lower GCI scores. We found a period of susceptibility to PM2.5 on fine motor scores in gestational weeks 1–9 (βcum = −2.55, 95%CrI = −3.53,-1.56) and on gross motor scores in weeks 7–17 (βcum = −2.27,95%CrI = −3.43,-1.11) though the individual lags for the latter were only borderline statistically significant. Exposure in gestational week 17 was weakly associated with verbal scores (βcum = −0.17, 95%CrI = −0.26,-0.09). In the postnatal period (from age 0.5–1.2 years), we observed a window of susceptibility to PM2.5 on lower perceptual-performance (β = −2.42, 95%CrI = −3.37,-1.46). Unexpected protective associations were observed for several outcomes with exposures in the later postnatal period. We observed no evidence of differences in susceptible periods by fetal growth or child sex. Preschool-aged children's motor function may be particularly susceptible to PM2.5 exposures experienced in utero whereas the first year of life was identified as a period of susceptibility to PM2.5 for children's perceptual-performance.