Distributed Lag Linear Models Research Articles

Impacts of climate change on diarrhoeal disease hospitalisations: How does the global warming targets of 1.5-2°C affect Dhaka, Bangladesh?

Dhaka is one of the world's densely populated cities and faces significant public health challenges including high burden of diarrhoeal diseases. Climate change is intensifying existing environmental problems including urban heat island effect and poor water quality. While numerous epidemiological studies have linked meteorological factors to diarrhoeal diseases in Bangladesh, assessment of the impacts of future climate change on diarrhoeal diseases is scarce. We provide the assessment of climate change impacts on diarrhoeal disease in Dhaka and project future health risks under climate change scenarios. About 3 million acute diarrhoea cases presenting to the Dhaka Hospital of the International Centre for Diarrhoeal Disease Research Bangladesh (icddr,b) during 1981-2010 were linked to daily temperature, rainfall and humidity and association investigated using time series adapted negative binomial regression models employing constrained distributed lag linear models. The findings were applied to climate projections to estimate future risks of diarrhoea under various global warming scenarios. There was a significantly raised risk of diarrhoea hospitalisation in all ages with daily mean temperature (RR: 3.4, 95% CI: 3.0-3.7) after controlling for the confounding effects of heavy rainfall, humidity, autocorrelations, day of the week effect, long-term time, and seasonal trends. Using the incidence rate ratio (IRR) of 1.034, temperature increases based on the global warming targets of 1.5-2°C could result in an increase of diarrhoea hospitalisations by 4.5-7.4% in all age groups by the 2100s. These effects were more pronounced among <5 children where the predicted temperature increases could raise diarrhoea hospitalisation by 5.7% - 9.4%. Diarrhoea hospitalisation will increase significantly in Dhaka even if the global warming targets adopted by the Paris Agreement is reached. This underscores the importance of preparing the city for management and prevention of diarrhoeal diseases.

Increased Risk of Influenza Infection During Cold Spells in China: National Time Series Study.

Studies have reported the adverse effects of cold events on influenza. However, the role of critical factors, such as characteristics of cold spells, and regional variations remain unresolved. We aimed to systematically evaluate the association between cold spells and influenza incidence in mainland China. This time series analysis used surveillance data of daily influenza from 325 sites in China in the 2014-2019 period. A total of 15 definitions of cold spells were adopted based on combinations of temperature thresholds and days of duration. A distributed lag linear model was used to estimate the short-term effects of cold spells on influenza incidence during the cool seasons (November to March), and we further explored the potential impact of cold spell characteristics (ie, intensity, duration, and timing during the season) on the estimated associations. Meta-regressions were used to evaluate the modification effect of city-level socioeconomic indicators. The overall effect of cold spells on influenza incidence increased with the temperature threshold used to define cold spells, whereas the added effects were generally small and not statistically significant. The relative risk of influenza-associated with cold spells was 3.35 (95% CI 2.89-3.88), and the estimated effects were stronger during the middle period of cool seasons. The health effects of cold spells varied geographically and residents in Jiangnan region were vulnerable groups (relative risk 7.36, 95% CI 5.44-9.95). The overall effects of cold spells were positively correlated with the urban population density, population size, gross domestic product per capita, and urbanization rate, indicating a sterner response to cold spells in metropolises. Cold spells create a substantial health burden on seasonal influenza in China. Findings on regional and socioeconomic differences in the health effects of cold spells on seasonal influenza may be useful in formulating region-specific public health policies to address the hazardous effects of cold spells.

The Influence of Climatic Factors on the Provocation of Epileptic Seizures.

Background/Objectives: Recent studies provide the first indications of the impact of climate factors on human health, especially with individuals already grappling with internal and neurological conditions being particularly vulnerable. In the face of escalating climate change, our research delves into the specific influence of a spectrum of climatic factors and seasonal variations on the hospital admissions of patients receiving treatment for epileptic seizures at our clinic in Kaiserslautern. Methods: Our study encompassed data from 9366 epilepsy patients who were admitted to hospital due to epileptic seizures. We considered seven climate parameters that Germany's National Meteorological Service made available. We employed the Kruskal-Wallis test to examine the correlation between the frequency of admittance to our hospital in the mentioned patient group and seasons. Furthermore, we used conditional Poisson regression and distributed lag linear models (DLMs) to scrutinize the coherence of the frequency of patient admittance and the investigated climate parameters. The mentioned parameters were also analyzed in a subgroup analysis regarding the gender and age of patients and the classification of seizures according to ILAE 2017. Results: Our results demonstrate that climatic factors, such as precipitation and air pressure, can increase the frequency of hospital admissions for seizures in patients with general-onset epilepsy. In contrast, patients with focal seizures are less prone to climatic changes. Consequently, admittance to the hospital for seizures is less affected by climatic factors in the latter patient group. Conclusions: The present study demonstrated that climatic factors are possible trigger factors for the provocation of seizures, particularly in patients with generalized seizures. This was determined indirectly by analyzing the frequency of seizure-related emergency admissions and their relation to prevailing climate factors. Our study is consistent with other studies showing that climate factors, such as cerebral infarcts or cerebral hemorrhages, influence patients' health.

Exploring the Modifying Role of GDP and Greenness on the Short Effect of Air Pollutants on Respiratory Hospitalization in Beijing.

It is unclear whether Gross Domestic Product (GDP) and greenness have additional modifying effects on the association between air pollution and respiratory system disease. Utilizing a time-stratified case-crossover design with a distributed lag linear model, we analyzed the association between six pollutants (PM2.5, PM10, NO2, SO2, O3, and CO) and 555,498 respiratory hospital admissions in Beijing from 1st January 2016 to 31st December 2019. We employed conditional logistic regression, adjusting for meteorological conditions, holidays and influenza, to calculate percent change of hospitalization risk. Subsequently, we performed subgroup analysis to investigate potential effect modifications using a two-sample z test. Every 10μg/m3 increase in PM2.5, PM10, NO2, SO2, and O3 led to increases of 0.26% (95%CI: 0.17%, 0.35%), 0.15% (95%CI: 0.09%, 0.22%), 0.61% (95%CI: 0.44%, 0.77%), 1.72% (95%CI: 1.24%, 2.21%), and 0.32% (95%CI: 0.20%, 0.43%) in admissions, respectively. Also, a 1mg/m3 increase in CO levels resulted in a 2.50% (95%CI: 1.96%, 3.04%) rise in admissions. The links with NO2 (p<0.001), SO2 (p<0.001), O3 (during the warm season, p<0.001), and CO (p<0.001) were significantly weaker among patients residing in areas with higher levels of greenness. No significant modifying role of GDP was observed. Greenness can help mitigate the effects of air pollutants, while the role of GDP needs further investigation.

A protective role of urban greenspace on the association between night-time heat and suicide in Seoul, South Korea

Suicide, a leading cause of death among the youth, has shown a positive association with high temperatures. However, few studies have explored the association between tropical nights and suicide and the potential role of greenness on this association. We investigated the association between suicide and two hot night indices: hot night duration (HNd) and hot night excess (HNe), representing heat duration and excess heat during night-time. We also explored whether the association was modified by urban greenspace, measured by satellite-derived normalized difference vegetation index (NDVI), across 25 districts in Seoul, South Korea from 2000 to 2020. Based on the multi-district daily time-series data, we performed a space-time-stratified case-crossover analysis with a distributed lag linear model with lags of up to 7 d for HNd and HNe, adjusting for daily mean temperature and relative humidity. We added an interaction term between the hot night index and NDVI to assess the effect modification of greenness. In total, 14 693 suicides were included in this study. The relative risk (RR) of suicide per a 10% increase in HNd was 1.059 (95% CI: 1.017–1.103) in low NDVI areas and 1.031 (95% CI: 0.988–1.075) in high NDVI areas. The RR per a 1 °C increase in HNe was 1.011 (95% CI: 0.998–1.024) and 1.005 (95% CI: 0.992–1.018) in low and high NDVI areas, respectively. Greenspaces have expanded over time in all districts of Seoul, and the risk of suicide for night-time heat decreased over time in both low and high NDVI areas. Our findings suggest that exposure to night-time heat is associated with an increased risk of suicide, but this risk may be mitigated by greater greenspaces in urban areas. Prioritizing development and maintenance of urban greenspaces will be a critical co-benefit strategy for promoting public mental health in changing climates.

Exposure to hourly ambient air pollutants and risk of emergency department visits for asthma: A multicenter time-stratified case-crossover analysis

BackgroundExposure to daily ambient air pollutants has been linked with increased risk of asthma morbidity and mortality. However, the association between exposure to air pollution and risk of emergency department (ED) visits for asthma on an hourly level remains unclear. MethodsWe conducted a time-stratified case-crossover design and included a total of 121,112 asthma ED visits from 11 hospitals in three cities located in Zhejiang province, China, between January 1, 2016 and September 30, 2021. We used conditional logistic regressions combined with a distributed lag linear model to estimate the association between risk of asthma ED visits and hourly exposure to fine particulate matter (PM2.5), respirable particulate matter (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO) after adjusted for meteorological factors and public holiday. ResultsHourly exposure to PM2.5, PM10, NO2, SO2, and CO was associated with an increased risk of asthma ED visits. This association was most pronounced in the concurrent hour of exposure (lag 0 h), rapidly attenuated over a period of 3–12 h, and diminished thereafter. Each interquartile range increase in air pollutant over 0–72 h was associated with increased risk of asthma ED visits by 7.0% (95% confidence interval [CI]: 5.4%, 8.6%) for PM2.5, 6.7% (95% CI: 5.1%, 8.2%) for PM10, 18.1% (95% CI: 15.4%, 21.0%) for NO2, 6.5% (95% CI: 4.8%, 8.2%) for SO2, and 7.4% (95% CI: 5.6%, 9.1%) for CO. ConclusionOur findings suggest that hourly exposure to PM2.5, PM10, NO2, SO2, and CO, but not O3, is associated with increased risk of ED visits for asthma shortly after exposure.

Comparison of short-term effects of particulate matter with different particle sizes on first-ever stroke: A national case-crossover study in China

ObjectivesTo compare the effects of short-term exposure to particulate matter (PM) with different particle sizes on first-ever stroke risk in the middle-aged and elderly Chinese population. MethodsHealth information was collected from the China National Stroke Screening Survey (CNSSS) from March 1, 2013, to April 10, 2015. Ambient exposures to PM1, PM2.5, and PM10 were obtained from ChinaHighAirPollutants (CHAP) Grid data. Case-crossover design was used to estimate the increase of first-ever stroke risk per 10 μg/m3 increase in ambient exposures to different size particles. We used distributed lag linear model (DLM) to estimate the hysteresis effects of particle exposures. In addition, in order to assess the effect modification of long-term exposure, we did a stratified analysis using median exposure as the dividing line. ResultsWe included 1326 first-ever stroke events from 242 communities in the present study. We found that effects on first-ever stroke risk increased with the decrease in particle size. The percent increases of first-ever stroke risk increased by 6.6% (95% CI: 1.4, 12.0), 3.3% (95% CI: 0.5, 6.1), and 0.6% (95% CI: -1.2, 2.6) per 10 g/m3 increases in PM1, PM2.5, and PM10 exposures in lag 0–2 days, respectively. Furthermore, the cumulative effect of PM on first-ever stroke reached its peak at distinct time points under different layers of long-term PM exposure. In areas with low PM exposure, the cumulative effects of the three kinds of particles on stroke reached their peak in lag1 day, while the cumulative effect peaked in lag3 day in areas with high PM exposure. ConclusionsThis study found that smaller particles had a stronger short-term effect on first-ever stroke. We also found that people in areas with long-term exposures to lower levels were more sensitive to short-term exposures. These results have public health significance for stroke prevention and air pollution reduction.

Lag-time effects of vaccination on SARS-CoV-2 dynamics in German hospitals and intensive-care units.

The Efficacy and effectiveness of vaccination against SARS-CoV-2 have clearly been shown by randomized trials and observational studies. Despite these successes on the individual level, vaccination of the population is essential to relieving hospitals and intensive care units. In this context, understanding the effects of vaccination and its lag-time on the population-level dynamics becomes necessary to adapt the vaccination campaigns and prepare for future pandemics. This work applied a quasi-Poisson regression with a distributed lag linear model on German data from a scientific data platform to quantify the effects of vaccination and its lag times on the number of hospital and intensive care patients, adjusting for the influences of non-pharmaceutical interventions and their time trends. We separately evaluated the effects of the first, second and third doses administered in Germany. The results revealed a decrease in the number of hospital and intensive care patients for high vaccine coverage. The vaccination provides a significant protective effect when at least approximately 40% of people are vaccinated, whatever the dose considered. We also found a time-delayed effect of the vaccination. Indeed, the effect on the number of hospital patients is immediate for the first and second doses while for the third dose about 15 days are necessary to have a strong protective effect. Concerning the effect on the number of intensive care patients, a significant protective response was obtained after a lag time of about 15-20 days for the three doses. However, complex time trends, e.g. due to new variants, which are independent of vaccination make the detection of these findings challenging. Our results provide additional information about the protective effects of vaccines against SARS-CoV-2; they are in line with previous findings and complement the individual-level evidence of clinical trials. Findings from this work could help public health authorities efficiently direct their actions against SARS-CoV-2 and be well-prepared for future pandemics.

Intensity and lag-time of non-pharmaceutical interventions on COVID-19 dynamics in German hospitals.

Evaluating the potential effects of non-pharmaceutical interventions on COVID-19 dynamics is challenging and controversially discussed in the literature. The reasons are manifold, and some of them are as follows. First, interventions are strongly correlated, making a specific contribution difficult to disentangle; second, time trends (including SARS-CoV-2 variants, vaccination coverage and seasonality) influence the potential effects; third, interventions influence the different populations and dynamics with a time delay. In this article, we apply a distributed lag linear model on COVID-19 data from Germany from January 2020 to June 2022 to study intensity and lag time effects on the number of hospital patients and the number of prevalent intensive care patients diagnosed with polymerase chain reaction tests. We further discuss how the findings depend on the complexity of accounting for the seasonal trends. Our findings show that the first reducing effect of non-pharmaceutical interventions on the number of prevalent intensive care patients before vaccination can be expected not before a time lag of 5 days; the main effect is after a time lag of 10-15 days. In general, we denote that the number of hospital and prevalent intensive care patients decrease with an increase in the overall non-pharmaceutical interventions intensity with a time lag of 9 and 10 days. Finally, we emphasize a clear interpretation of the findings noting that a causal conclusion is challenging due to the lack of a suitable experimental study design.

Prenatal exposure to ambient air pollution is associated with neurodevelopmental outcomes at 2 years of age

BackgroundHigher prenatal ambient air pollution exposure has been associated with impaired neurodevelopment in preschoolers and school-aged children. The purpose of this study was to explore the relationships between prenatal ambient air pollution exposure and neurodevelopment during infancy.MethodsThis study examined 161 Latino mother-infant pairs from the Southern California Mother’s Milk Study. Exposure assessments included prenatal nitrogen dioxide (NO2) and particulate matter smaller than 2.5 and 10 microns in diameter (PM2.5 and PM10, respectively). The pregnancy period was also examined as three windows, early, mid, and late, which describe the first, middle, and last three months of pregnancy. Infant neurodevelopmental outcomes at 2 years of age were measured using the Bayley-III Scales of Infant and Toddler Development. Multivariable linear models and distributed lag linear models (DLM) were used to examine relationships between prenatal exposures and neurodevelopmental scores, adjusting for socioeconomic status, breastfeeding frequency, time of delivery, pre-pregnancy body mass index, and infant birthweight and sex.ResultsHigher prenatal exposure to PM10 and PM2.5 was negatively associated with composite cognitive score (β = -2.01 [-3.89, -0.13] and β = -1.97 [-3.83, -0.10], respectively). In addition, higher average prenatal exposure to PM10 was negatively associated with composite motor (β = -2.35 [-3.95, -0.74]), scaled motor (β = -0.77 [-1.30, -0.24]), gross motor (β = -0.37 [-0.70, -0.04]), fine motor (β = -0.40 [-0.71, -0.09]), composite language (β = -1.87 [-3.52, -0.22]), scaled language (β = -0.61 [-1.18, -0.05]) and expressive communication scaled scores (β = -0.36 [-0.66, -0.05]). DLMs showed that higher prenatal air pollution exposure during mid and late pregnancy was inversely associated with motor, cognitive, and communication language scores.ConclusionsHigher exposure to air pollutants during pregnancy, particularly in the mid and late prenatal periods, was inversely associated with scaled and composite motor, cognitive, and language scores at 2 years. These results indicate that prenatal ambient air pollution may negatively impact neurodevelopment in early life.

In Utero Exposure to Air Pollutants and Mitochondrial Heteroplasmy in Neonates.

Mitochondria are sensitive to oxidative stress, which can be caused by traffic-related air pollution. Placental mitochondrial DNA (mtDNA) mutations have been previously linked with air pollution. However, the relationship between prenatal air pollution and cord-blood mtDNA mutations has been poorly understood. Therefore, we hypothesized that prenatal particulate matter (PM2.5) and NO2 exposures are associated with cord-blood mtDNA heteroplasmy. As part of the ENVIRONAGE cohort, 200 mother-newborn pairs were recruited. Cord-blood mitochondrial single-nucleotide polymorphisms were identified by whole mitochondrial genome sequencing, and heteroplasmy levels were evaluated based on the variant allele frequency (VAF). Outdoor PM2.5 and NO2 concentrations were determined by a high-resolution spatial-temporal interpolation method based on the maternal residential address. Distributed lag linear models were used to determine sensitive time windows for the association between NO2 exposure and cord-blood mtDNA heteroplasmy. A 5 μg/m3 increment in NO2 was linked with MT-D-Loop16311T>C heteroplasmy from gestational weeks 17-25. MT-CYTB14766C>T was negatively associated with NO2 exposure in mid pregnancy, from weeks 14-17, and positively associated in late pregnancy, from weeks 31-36. No significant associations were observed with prenatal PM2.5 exposure. This is the first study to show that prenatal NO2 exposure is associated with cord-blood mitochondrial mutations and suggests two critical windows of exposure in mid-to-late pregnancy.

Cumulative effects of temperature on blood pressure during pregnancy: A cohort study of differing effects in three trimesters

BackgroundLittle is known about the non-linear cumulative effects of temperature on blood pressure (BP) during pregnancy. We investigated the differing effects of daily ambient temperature on BP for up to 30 days in three trimesters. MethodsThe first, second, and third trimester analyses included 2547, 2299, and 2011 pregnant women, respectively, from a prospective cohort in Nanjing from January 2017 to January 2020. BP was measured at each follow-up visit. The individual daily temperature exposures were calculated for 30 days prior to the follow-up date. The Distributed Lag Non-linear Model was used to investigate the relationship between temperature and BP in each trimester. ResultsTemperatures under 15 °C elevate systolic, diastolic BP, and mean arterial pressure (SBP, DBP, and MAP) in the first trimester, while temperatures above 15 °C reduce SBP in the second and third trimesters. By using Distributed Lag Linear Models, we estimated that with a 1 °C decrease in daily temperature, the SBP and DBP increased by 0.32 (95 % CI: 0.12, 0.52) and 0.23 (95 % CI: 0.07, 0.39) mmHg, respectively, in the first trimester with a 20-day cumulative lag, while with a 1 °C increase in daily temperature, the SBP decreased by 0.23 (0.35, 0.10) mmHg in the third trimester with a 30-day cumulative lag. The significant effects of temperature mainly manifested between 2 and 4 weeks of exposure. ConclusionsTemperature has different effects on BP over three trimesters. Protective measures to reduce cold-related BP rise will help reduce the risk of hypertensive disorders of pregnancy.

Low temperature, cold spells, and cardiorespiratory hospital admissions in Helsinki, Finland

There is only limited scientific evidence with varying results on the association between hospital admissions and low ambient temperatures. Furthermore, there has been no research in Northern Europe on cold-associated morbidity. Therefore, this study investigated the associations of daily wintertime temperature and cold spells with cardiorespiratory hospital admissions in the Helsinki metropolitan area, Finland. Daily number of non-elective hospital admissions for 2001–2017 was obtained from the national hospital discharge register and meteorological data from the Finnish Meteorological Institute. Quasi-Poisson regression models were fitted, controlling for potential confounders such as time trend, weekday, holidays, air pollution, barometric pressure, and influenza. The associations of cold season daily mean ambient temperature and cold spells with hospital admissions were estimated using a penalized distributed lag linear models with 21 lag days. Decreased wintertime ambient temperature was associated with an increased risk of hospitalization for myocardial infarction in the whole population (relative risk [RR] per 1 °C decrease in temperature: 1.017, 95% confidence interval [CI]: 1.002–1.032). An increased risk of hospital admission for respiratory diseases (RR: 1.012, 95% CI: 1.002, 1.022) and chronic obstructive pulmonary disease (RR: 1.031, 95% CI: 1.006, 1.056) was observed only in the ≥ 75 years age group. There was an independent effect of cold spell days only for asthma admissions (RR: 2.348, 95% CI: 1.026, 5.372) in the all-ages group. Cold temperature increases the need for acute hospital care due to myocardial infarction and respiratory causes during winter in a northern climate.

The North-South difference of the relationship between cold spells and mortality risk of cardiovascular diseases in China

Objective: To analyze the North-South difference of the relationship between cold spells and mortality risk of cardiovascular diseases in China. Methods: The time series analysis method was used to collect the daily counts of cardiovascular mortality data, meteorological data and PM2.5 concentration in the cold season (November to March of the following year) from January 1, 2013 to December 31, 2018 in 280 districts and counties in China. The non-constrained distributed lag linear model was used to analyze the relationship between cold spells and mortality risk of cardiovascular diseases and its North-South difference in China. Results: From 2013 to 2018, the mean of daily average temperature of the cold season in 280 districts and counties was 5.4 ℃. The mean of daily average relative humidity was 64.4%, and the mean of daily average PM2.5 concentration was 73.7 μg/m3. The average cold spell days in each county was 11.7 days per year,the mean of daily average temperature on cold spell days was (-2.4±6.7) ℃, and M (Q1, Q3) was -1.5 (-5.1, 1.1) ℃. The average of daily number of cardiovascular disease deaths in each county/district was (6±5) cases, and M (Q1, Q3) was 5 (2, 8) cases. The percentage change (95%CI) in the South was 4.94% (3.69%, 6.20%) (lag 0 d), higher than that in the North [the percentage change (95%CI) was 1.49% (1.14%-1.84%) (lag 0-7 d)]. In the North, the mortality risk of ≥75 years old was relatively low among three age groups, with a percentage change (95%CI) about 1.63% (1.33%-1.93%) (lag 0-21 d). In the South, the mortality risk of ≥ 75 years old was relatively high among three age groups, with a percentage change (95%CI) about 5.18% (3.78%-6.59%) (lag 0 d). Conclusion: The mortality risk of cardiovascular diseases caused by cold spells in the South is higher than that in the North of China, and the risk peak occurs earlier in the South.

In utero particulate matter exposure in association with newborn mitochondrial ND4L10550A>G heteroplasmy and its role in overweight during early childhood

BackgroundMitochondria play an important role in the energy metabolism and are susceptible to environmental pollution. Prenatal air pollution exposure has been linked with childhood obesity. Placental mtDNA mutations have been associated with prenatal particulate matter exposure and MT-ND4L10550A>G heteroplasmy has been associated with BMI in adults. Therefore, we hypothesized that in utero PM2.5 exposure is associated with cord blood MT-ND4L10550A>G heteroplasmy and early life growth. In addition, the role of cord blood MT-ND4L10550A>G heteroplasmy in overweight during early childhood is investigated.MethodsThis study included 386 mother-newborn pairs. Outdoor PM2.5 concentrations were determined at the maternal residential address. Cord blood MT-ND4L10550A>G heteroplasmy was determined using Droplet Digital PCR. Associations were explored using logistic regression models and distributed lag linear models. Mediation analysis was performed to quantify the effects of prenatal PM2.5 exposure on childhood overweight mediated by cord blood MT-ND4L10550A>G heteroplasmy.ResultsPrenatal PM2.5 exposure was positively associated with childhood overweight during the whole pregnancy (OR = 2.33; 95% CI: 1.20 to 4.51; p = 0.01), which was mainly driven by the second trimester. In addition, prenatal PM2.5 exposure was associated with cord blood MT-ND4L10550A>G heteroplasmy from gestational week 9 – 13. The largest effect was observed in week 10, where a 5 µg/m3 increment in PM2.5 was linked with cord blood MT-ND4L10550A>G heteroplasmy (OR = 0.93; 95% CI: 0.87 to 0.99). Cord blood MT-ND4L10550A>G heteroplasmy was also linked with childhood overweight (OR = 3.04; 95% CI: 1.15 to 7.50; p = 0.02). The effect of prenatal PM2.5 exposure on childhood overweight was mainly direct (total effect OR = 1.18; 95% CI: 0.99 to 1.36; natural direct effect OR = 1.20; 95% CI: 1.01 to 1.36)) and was not mediated by cord blood MT-ND4L10550A>G heteroplasmy.ConclusionsCord blood MT-ND4L10550A>G heteroplasmy was linked with childhood overweight. In addition, in utero exposure to PM2.5 during the first trimester of pregnancy was associated with cord blood MT-ND4L10550A>G heteroplasmy in newborns. Our analysis did not reveal any mediation of cord blood MT-ND4L10550A>G heteroplasmy in the association between PM2.5 exposure and childhood overweight.

Main and added effects of heatwaves on hospitalizations for Mental and Behavioral Disorders in a tropical megacity of Vietnam

BACKGROUND AND AIM: Vietnam is highly vulnerable to climate change-related extreme weather events such as heatwaves. This study assesses the association between heatwaves and hospitalizations due to mental and behavioral disorders (MBDs) in Ho Chi Minh City (HCMC). METHODS: We collected daily MBD hospital admissions data at the HCMC Mental Health Hospital from 2017 to 2019. Heatwaves effects were characterized into the main effect (i.e., the intensity of temperature during heatwaves) and the added effect (i.e, the duration of heatwaves). Time series Poisson regression coupled with a distributed lag linear model (DLM) was used to quantify the 14-day lags effect of heatwaves. Confounders including long-term trend, seasonality, days of the week, holidays, relative humidity were included in the model. RESULTS: Heatwaves increased all-cause MBD hospitalization by 62% (95%Cl, 36%–93%) for the main effect, and by 8% (95% Cl, -3%–19%) for the added effect. Noticeably, the group aged 18 to 60 years old was affected by the main effect of the heatwave, while the group aged 61 years and older was affected by the added effect of the heatwave. The effects of heatwaves differed among groups of MBD hospitalizations. The mental and behavioral disorder group due to psychoactive substance use was significantly affected by the main effect of heatwaves (RR:2.21; 95%Cl:1.55–3.15). The group of schizophrenia, schizotypal and delusional disorders were highly vulnerable towards both the main and the added effect of heatwaves with RR=1.50 (95%CI, 1.20–1.86) and RR = 1.14 (95%CI, 1.01–1.30), respectively. CONCLUSIONS: These results aroused the need for adequate heat warning and adaptation programs when temperatures are not too high but prolonged, particularly with the elderly

Air Pollution and Respiratory Hospital Admissions in Kuwait: The Epidemiological Applicability of Predicted PM2.5 in Arid Regions.

Dust is a major component of fine particulate matter (PM2.5) in arid regions; therefore, concentrations of this pollutant in countries such as Kuwait exceed air quality standards. There is limited understanding on the impact and burden of high PM2.5 concentrations on morbidity in these countries. In this study, we explore the association of PM2.5 and the risk of respiratory hospital admissions in Kuwait. A time-series regression model was used to investigate daily variations in respiratory admissions and PM2.5 concentrations from 2010 to 2018. Due to the lack of historical air quality sampling in Kuwait, we used estimated daily PM2.5 levels from a hybrid PM2.5 prediction model. Individual and cumulative lag effects of PM2.5 over a 5-day period were estimated using distributed lag linear models. Associations were stratified by sex, age, and nationality. There were 218,749 total respiratory admissions in Kuwait during the study period. Results indicate that for every 10 μg/m3 increase in PM2.5, a 1.61% (95% CI = 0.87, 2.35%) increase in respiratory admissions followed over a 5-day cumulative lag. Our estimates show that a 10 μg/m3 reduction in average exposure will potentially avert 391 yearly respiratory admissions (95% CI = 211,571), with 265 fewer admissions among Kuwaitis (95% CI = 139,393) and 262 fewer admissions among children under 15 years of age (95% CI = 125,351). Different strata of the Kuwaiti population are vulnerable to respiratory hospitalization with short-term exposure to PM2.5, especially those under 15 years of age. The findings are informative for public health authorities in Kuwait and other dust-prone countries.

The acute effect and lag effect analysis between exposures to ambient air pollutants and spontaneous abortion: a case-crossover study in China, 2017–2019

IntroductionRecent studies demonstrated that living in areas with high ambient air pollution may have adverse effects on pregnancy outcomes, but few studies have investigated its association with spontaneous abortion. Further investigation is needed to explore the acute effect and lag effect of air pollutants exposure on spontaneous abortion.ObjectiveTo investigate the acute effect and lag effect between exposure to ambient air pollutants and spontaneous abortion.MethodsResearch data of spontaneous abortion were collected from the Chongqing Health Center for Women and Children (CQHCWC) in China. The daily ambient air pollution exposure measurements were estimated for each woman using inverse distance weighting from monitoring stations. A time-stratified, case-crossover design combined with distributed lag linear models was applied to assess the associations between spontaneous pregnancy loss and exposure to each of the air pollutants over lags 0–7 days, adjusted for temperature and relative humidity.ResultsA total of 1399 women who experienced spontaneous pregnancy loss events from November 1, 2016, to September 30, 2019, were selected for this study. Maternal exposure to particulate matter 2.5 (PM2.5), particle matter 10 (PM10) nitrogen dioxide (NO2), and sulfur dioxide (SO2) exhibited a significant association with spontaneous abortion. For every 20 μg/m3 increase in PM2.5, PM10, NO2, and SO2, the RRs were 1.18 (95% CI: 1.06, 1.34), 1.12 (95% CI, 1.04–1.20), 1.15 (95% CI: 1.02, 1.30), and 1.92 (95% CI: 1.18, 3.11) on lag day 3, lag day 3, lag day 0, and lag day 3, respectively. In two-pollutant model combined with PM2.5 and PM10, a statistically significant increase in spontaneous abortion incidence of 18.0% (RR = 1.18, 95% CI: 1.06, 1.32) was found for a 20 μg/m3 increase in PM2.5 exposure, and 11.2% (RR = 1.11, 95% CI: 1.03, 1.20) for a 20 μg/m3 increase in PM10 exposure on lag day 3, similar to single-pollutant model analysis.ConclusionMaternal exposure to high levels of PM2.5, PM10, NO2, and SO2 during pregnancy may increase the risk of spontaneous abortion for acute effects and lag effects. Further research to explore sensitive exposure time windows is needed.

Main and added effects of heatwaves on hospitalizations for mental and behavioral disorders in a tropical megacity of Vietnam.

Vietnam is highly vulnerable to climate change-related extreme weather events such as heatwaves. This study assesses the association between heatwaves and hospitalizations due to mental and behavioral disorders (MBDs) in Ho Chi Minh City (HCMC). We collected daily MBD hospital admissions data at the HCMC Mental Health Hospital from 2017 to 2019. Heatwaves effects were characterized into the main effect (i.e., the intensity of temperature during heatwaves) and the added effect (i.e., the duration of heatwaves). Time series Poisson regression coupled with a distributed lag linear model (DLM) was used to quantify the 14-day lags effect of heatwaves. Confounders including long-term trend, seasonality, days of the week, holidays, and relative humidity were included in the model. Heatwaves increased all-cause MBD hospitalization by 62% (95%Cl, 36-93%) for the main effect and by 8% (95% Cl, - 3% to 19%) for the added effect. Noticeably, the group aged 18-60years old was affected by the main effect of the heatwave, while the group aged 61years and older was affected by the added effect of the heatwave. The effects of heatwaves differed among groups of MBD hospitalizations. The mental and behavioral disorder group due to psychoactive substance use was significantly affected by the main effect of heatwaves (RR:2.21; 95%Cl:1.55-3.15). The group of schizophrenia, schizotypal and delusional disorders were highly vulnerable towards both the main and the added effect of heatwaves with RR = 1.50 (95%CI, 1.20-1.86) and RR = 1.14 (95%CI, 1.01-1.30), respectively.

Age-specific effects of ozone on pneumonia in Korean children and adolescents: a nationwide time-series study.

OBJECTIVESThe aim of this study was to estimate the age-specific effects of 8-hour maximum ozone levels on pneumonia in children and adolescents.METHODSWe performed quasi-Poisson regression analyses for individuals of 0-4 years, 5-9 years, 10-14 years, and 15-19 years of age using nationwide time-series data from the Korea (2011-2015). We constructed distributed lag linear models employing a generalized difference-in-differences method and controlling for other air pollutants.RESULTSA 10.0-parts per billion increase in 8-hour maximum ozone levels was associated with a higher risk of hospital admissions due to pneumonia at 0-4 (relative risk [RR], 1.02; 95% confidence interval [CI], 1.01 to 1.03) and 5-9 years of age (RR, 1.06; 95% CI, 1.04 to 1.08), but not at 10-14 (RR, 1.01; 95% CI, 0.98 to 1.04) or 15-19 years of age (RR, 1.01; 95% CI, 0.97 to 1.06). The association between ozone and hospital admissions due to pneumonia was stronger in cool seasons (from November to April) than in warm seasons (from May to October), but was similar between boys and girls.CONCLUSIONSShort-term exposure to ozone was associated with a higher risk of pneumonia at 0-4 years and 5-9 years of age, but not at 10-14 years or 15-19 years of age. Our findings can help identify vulnerable periods, determine the target populations for public health interventions, and establish air pollution standards.