Distributed Lag Non-linear Model Research Articles

Excess mortality related to high air temperature: Comparison of the periods including 1994 and 2018, the worst heat waves in the history of South Korea.

Climate change has caused extreme weather events, including frequent summer heat waves. We examined how the effects of high air temperatures on mortality have changed between the two study periods (1991-1995 and 2015-2019), including 1994 and 2018, the worst heat wave years in the meteorological history of South Korea. Temperature data from the Korea Meteorological Administration and mortality data from Statistics Korea were used in this study. We used distributed lag nonlinear models to estimate the cumulative relative risks (CRRs) to determine the association between daily maximum temperature in summer (June to September) and mortality. CRRs were estimated for each province and pooled using a random-effects meta-analysis for all provinces. Maximum temperature and annual average days in heat wave were 37.7°C and 11.8 in 1991-1995 and 38.3°C and 18.8 in 2015-2019. The slope of the CRR for mortality increases with increasing temperature and has been steeper in the past than in recent years and steeper in those over 65 than in those under 65. Excess mortality has recently declined compared with that in the past. The impact of high summer temperatures on mortality changed between the two periods, suggesting improved population resilience.

A study of the correlation between meteorological factors and hospitalization for acute lower respiratory infections in children.

The study focuses on the effect of temperature and relative humidity on hospitalization for acute lower respiratory tract infections (LRTI) in children, respectively. In this study, the Distributed Lag Nonlinear Model (DLNM) based on quasi-Poisson distribution was used to investigate the effect of temperature and relative humidity on LRTI hospitalization in children, and subgroup analyses were conducted to identify sensitive populations by gender and age. A total of 43,951 children were hospitalized for LRTI from 1 January 2014 to 31 December 2019 in Lanzhou. The mean temperature during the study period was 11.34°C and the mean relative humidity was 51.03%. With reference to the median temperature of 12.7°C during the study period, both low (-4.1°C) and high (25.43°C) temperature had a detrimental effect on LRTI hospitalization, and the maximum effect was reached at lag0-10 and lag0-9, respectively, with RR values of 1.645 (95%CI: 1.533, 1.764) and 1.098 (95%CI: 1.018, 1.184). With a reference to the median relative humidity of 51.17% during the study period, both low relative humidity (26.71%) and high relative humidity (76.70%, P95) had a detrimental effect on LRTI hospitalization, and the maximum effect was reached at lag0-21 and lag21, respectively, with RR values of 1.235 (95% CI: 1.163, 1.311) and 1.044 (95% CI: 1.036, 1.051). The results of subgroup analyses showed that changes in meteorological factors had a stronger effect on Female and children aged 5-14years. The meteorological factors all have different degrees of influence on LRTI hospitalization in children. Girls and the children aged 5-14years are more sensitive. Attention to these meteorological risks can inform targeted interventions.

Impact of Heat on Respiratory Hospitalizations among Older Adults in 120 Large US Urban Areas.

Extreme heat exposure is a well-known cause of mortality among older adults. However, the impacts of exposure on respiratory morbidity across US cities and population subgroups is not well understood. A nationwide study to determine the impact of high heat on respiratory disease hospitalizations among older adults (65+) living in the 120 largest US cities between 2000-2017. Daily rates of inpatient respiratory hospitalizations were examined with respect to variations in ZIP-code-level daily mean temperature and heat index. For each city, we estimated cumulative associations (lag-days 0-6) between warm-season heat (June-September) and cause-specific respiratory hospitalizations using time-stratified conditional quasi-Poisson regression with distributed lag non-linear models. We estimated nationwide associations using multivariate meta-regression and updated city-specific associations via best linear unbiased prediction. With stratified models, we explored effect modification by age, sex, and race (Black/white). Results were reported as percent change in hospitalizations at high temperatures (95th percentile) compared to median temperatures for each outcome, demographic group, and metropolitan area. We identified 3,275,033 respiratory hospitalizations among Medicare beneficiaries across 120 large US cites between 2000 and 2017. Nationwide, 7-day cumulative associations at high temperatures, resulted in a 1.2% (0.4%, 2.0%) increase in hospitalizations for primary diagnoses of all-cause respiratory disease, primarily driven by increases in respiratory tract infections [1.8% (0.6%, 3.0%)], and chronic respiratory diseases/respiratory failure [1.2% (0.0%, 2.4%)]. Stronger associations were observed when exposure was defined using the heat index instead of temperature. Across the 120 cities, we observed considerable geographic variation in the relative risk of heat-related respiratory hospitalizations, and we observed disproportionate burdens of heat-related respiratory hospitalizations among the oldest beneficiaries (85+ years), and among Black beneficiaries living in South Atlantic cities. During the 18-year study period, there were an estimated 11,710 excess respiratory hospitalizations due to heat exposure. Results suggest that high temperature and humidity contribute to exacerbation of respiratory tract infections and chronic lung diseases among older adults. Geographic variation in heat-related hospitalization rates suggests that contextual factors largely account for disproportionate burdens, and area-level influences should be further investigated in multi-city studies.

Windows of susceptibility and joint effects of prenatal and postnatal ambient air pollution and temperature exposure on asthma and wheeze in Mexican children

IntroductionPrenatal and early-life exposure to air pollution and extreme temperatures are associated with childhood asthma and wheeze. However, potential windows of susceptibility and their sex-specific and interactive effects have not been fully elucidated. We aimed to identify critical windows of susceptibility and evaluate sex-specific effects in these associations, and evaluate exposure interactions. MethodsWe analyzed data from 468 mother–child pairs enrolled in the PROGRESS birth cohort in Mexico City. Daily residential levels of PM2.5, NO2, and temperature were generated from our validated spatiotemporally resolved models from conception to age 4 years. Childhood asthma and wheeze outcomes were collected at 4–6 and 7–8 years. Distributed lag nonlinear models (DLNMs) were used to identify susceptible windows for prenatal weekly-specific and postnatal monthly-specific associations of air pollution and temperature with respiratory outcomes adjusting for covariates. To evaluate sex-specific effects, DLNMs were stratified. Joint effects were assessed using relative excess risk due to interaction and attributable proportion. ResultsMid-gestation was a critical window for both PM2.5 (weeks 20–28, cumulative OR: 1.18 [95% CI: 1.01, 1.37]; weeks 19–26, cumulative OR: 1.18 [95% CI: 1.02, 1.36]) and NO2 (weeks 18–25, cumulative OR: 1.16 [95% CI: 1.02, 1.31]) exposure, associated with higher odds of wheeze. Postnatal exposure to PM2.5 and NO2 during the first year of life was also linked to higher odds of wheeze. The warmer and colder temperatures showed mixed effects on respiratory outcomes. We observed a synergistic interaction between high PM2.5 and high temperature exposure during the first year of life, associated with higher odds of current wheeze. The associations of prenatal air pollution and temperature exposure with respiratory outcomes were more pronounced in males. ConclusionsEarly-life air pollution exposure contributes to the development of childhood asthma and wheeze, while exposure to temperature showed mixed associations with respiratory outcomes.

Effect of heatwaves on mortality of Alzheimer's disease and other dementias among elderly aged 60 years and above in China, 2013–2020: a population-based study

BackgroundChina has the largest number of dementia patients in the world, posing a significant health and economic burden. Alzheimer's disease (AD) and other dementia patients face a higher risk of mortality during heatwaves, but relevant studies on this topic have been limited so far. MethodsThe study extracted data from the China Cause of Death Reporting System (CDRS) on deaths of AD and other dementia patients aged 60 years and above between 2013-2020. Using an individual-level, time-stratified, and case-crossover study design, the effects of heatwaves across nine scenarios on dementia mortality were quantified by conditional logistic regression combined with distributed lag non-linear model (DLNM). Additionally, the attributable fractions (AFs) of deaths due to heatwaves were calculated. FindingsA total of 399,036 death cases were reported caused by AD and other dementias during the study period. It was found that heatwaves significantly increased the risk of death among people with AD and other dementias. As the intensities and durations of the heatwaves increased, the lag0-7 cumulative odds ratios (CORs) of mortality increased progressively from 1·140 (95% CI: 1·118, 1·163) under the mildest heatwave to 1·459 (95% CI: 1·403, 1·518) under the most severe one, across nine heatwave scenarios examined. Additionally, under specific heatwave scenarios, sex and regions modified the mortality risk, but no significant age differences were observed. The AFs of AD and other dementia mortality due to milder heatwaves were lower compared to more severe heatwaves, ranging from 12·281% (95% CI: 10·555%, 14·015%) to 31·460% (95% CI: 28·724%, 34·124%). InterpretationThe study provided critical insights into the substantial increase in heatwave-related mortality among AD and other dementia patients during and after heatwave events. The results from our quantitative analyses will provide needed scientific evidence for policymakers and practitioners to develop relevant policies and guidelines to protect the health and well-beings of vulnerable populations in future in the context of both seasonal changes and long-term climate change. FundingThis work was supported by the Project of Prevention and Intervention on Major Diseases for Elderly in China, NCNCD [00240201307], the National Key Research and Development Program of China [2022YFC2602301, 2023YFC2308703] and the Science and Technology Fundamental Resources Investigation Program of China [2017FY101201].

Projecting future minimum mortality temperature in China

Minimum mortality temperature (MMT) increases with global warming due to climate adaptation, which is crucial for the precise assessment of mortality burden attributed to climate change. Nevertheless, forecasting future MMT poses a challenge given the unavailability of future mortality data. Here, we attempted to develop a novel approach to project future MMT. First, we estimated the MMT of 334 locations in China using a distributed lag nonlinear model. Then, meta regression models were applied to investigate the associations between MMT and several temperature variables(Most Frequent Temperature(MFT), average daily mean temperature, average daily minimum temperature, average daily maximum temperature and percentiles of temperature from 1st to 100th). A generalized linear regression model was employed to investigate whether significant differences existed in the relationships between MMT and temperature from the 1st to the 100th percentile. Finally, an optional indicator of MMT for projecting future values was identified. Our results indicated that temperatures in the 85th to 89th percentiles were closely associated with MMT, with the 88th percentile temperature serving as the most effective indicator, as confirmed by meta-regression models. Using the 88th percentile of temperature as alternative indicator of MMT, compared with the period of 2006-2015, the projected MMT in most districts and counties in China tended to rise under three representative concentration pathways (RCPs) in the 2030s (2030-2039), 2060s (2060-2069), and 2090s (2090-2099). Our findings provide some insight to project future MMT for assessing mortality burden related to temperature change driven by global warming.

Association Between Short-Term Exposure to Air Pollutants and Emergency Attendance for Upper Gastrointestinal Bleeding in Hong Kong: A Time-Series Study.

The relationship between exposure to ambient air pollutants and emergency attendance for upper gastrointestinal bleeding (UGIB) remains inconclusive. This study examines the association between short-term exposure to various ambient pollutants and the risk of UGIB emergency attendance. Data on daily UGIB emergency attendance, ambient pollutants, and meteorological conditions in Hong Kong were collected from 2017 to 2022. A time-series study using a distributed lag non-linear model to analyze the data, considering lag days. Stratified analysis was performed based on sex, seasons, and the COVID-19 pandemic period. The burden was quantified using attributable fraction (AF) and number (AN). The study included 31,577 UGIB emergency records. Exposure to high levels of PM2.5 significantly increased the risk of UGIB emergency attendance from lag day 3 (RR: 1.012) to day 6 (RR: 1.008). High NO2 exposure also posed a significant risk from lag day 0 (RR: 1.026) to day 2 (RR: 1.014), and from lag day 5 (RR: 1.013) to day 7 (RR: 1.024). However, there was no association between UGIB and high O3 levels. The attributable burden of high-concentration NO2 exposure was higher compared to those of PM2.5. Males and elderly individuals (≥65years) faced a higher risk of UGIB emergencies, particularly during cold seasons. Our study suggests that both PM2.5 and NO2 exposure are associated with an increased risk of emergency attendance for UGIB. Ambient pollutant exposure has a stronger effect on UGIB in males and the elderly, particularly during cold seasons.

Case-Time Series Study on the Short-term Impact of Meteorological Factors on West Nile Virus Incidence in Italy at the Local Administrative Unit Level, 2012 to 2021.

IntroductionWest Nile Virus (WNV) is a significant public health concern in southern Europe, with meteorological, climatic, and environmental factors playing a critical role in its transmission dynamics. This study aims to assess the short-term effects of meteorological variables on the incidence of WNV in five Italian regions in Northern Italy from 2012 to 2021. MethodsLinking epidemiological data from the national surveillance system and local meteorological data, we conducted a Case-Time Series analysis to examine the association between WNV incident cases and temperature, humidity, and precipitation recorded up to ten weeks before case occurrence at the local administrative unit level. We employed conditional quasi-Poisson regression and distributed lag non-linear models to explore delayed effects. ResultsOur study analyzed 1,110 autochthonous human cases of WNV. We found a positive association between WNV incidence and weekly mean temperature recorded between one to nine weeks before the diagnosis, with the highest effect at one week lag (IRR: 1.16; 95% CI 1.11-1.21). An increase in weekly precipitations between the sixth and ninth weeks before diagnosis was also positively associated with WNV incidence. Variations in minimum weekly humidity did not show a consistent impact. ConclusionsOur findings underscore the influence of temperature and, to a lesser extent, precipitation on WNV incidence in Northern Italy, highlighting the potential of climatic data in developing early warning systems for WNV surveillance and public health interventions.

Heat and cause-specific cardiopulmonary mortality in Germany: a case-crossover study using small-area assessment

High temperatures have been associated with increased mortality, with evidence reported predominately in large cities and for total cardiovascular or respiratory deaths. This case-crossover study examined heat-related cause-specific cardiopulmonary mortality and vulnerability factors using small-area data from Germany. We analyzed daily counts of cause-specific cardiopulmonary deaths from 380 German districts (2000-2016) and daily mean temperatures estimated by spatial-temporal models. We applied conditional quasi-Poisson regression using distributed lag nonlinear models to examine heat effects during May-September in each district and random-effects meta-analysis to pool the district-specific estimates. Potential individual- and district-level vulnerability factors were examined by subgroup analyses and meta-regressions, respectively. Heat was associated with increased mortality risks for all cardiopulmonary sub-causes. The relative risk (RR) of total cardiovascular and respiratory mortality for a temperature increment from the 75th to the 99th percentile was 1.24 (95% confidence interval: 1.23, 1.26) and 1.34 (1.30, 1.38), respectively. The RRs of cardiovascular sub-causes ranged from 1.16 (1.13, 1.19) for myocardial infarction to 1.32 (1.29, 1.36) for heart failure. For respiratory sub-causes, the RR was 1.27 (1.22, 1.31) for COPD and 1.49 (1.42, 1.57) for pneumonia. We observed greater susceptibility related to several individual- and district-level characteristics, e.g., among females or in highly urbanized districts. Heat vulnerability factors remained consistent between urban and rural areas. Our study highlights heat-related increases in cause-specific cardiopulmonary mortality across Germany and identifies key vulnerability factors, offering insights for improving public health practices to mitigate heat-related health impacts. European Union's Horizon 2020 research and innovation program; Helmholtz Associations Initiative and Networking Fund.

Association between temperature and air pollutants with atrial fibrillation presentations to emergency departments.

Understanding the impact of environmental exposures on disease incidence is important for environmental guidelines, health services management, and advising patients. We aimed to assess the relationship between daily mean temperature and common pollutants with atrial fibrillation (AF) presentations to emergency departments (EDs). The study included consecutive adult patients presenting with AF to EDs from 1/1/2014 to 31/12/2020 with linkage to hospital and emergency discharge diagnosis data. A time series quasi-Poisson regression with a distributed lag nonlinear model was fitted to assess the association between AF with mean air temperature and five common pollutants, overall and according to sex and region, with adjustment for season, day of the week, long-term trend, and co-pollutants. In 82 575 AF presentations to EDs during the study period, mean (standard deviations [SD]) (SD) age was 69.6 (SD 14.7) years and 50.7% were female. AF presentations were associated with elevated levels of Particulate Matter (PM) 2.5 (≥57.7 µg/m3) and nitrous dioxide (NO2) (≥16.5 parts per billion), but not mean air temperature or other pollutants (carbon monoxide, sulphur dioxide, or ozone). The attributable fraction of AF presentations relating to above optimal NO2 and PM 2.5 levels was 7.24% and 3.81% resulting in 854 and 450 annual excess AF presentations, respectively. High levels of NO2 and PM 2.5 are associated with increased risk of AF presentations to EDs. These findings have important implications for environmental policies and advice to patients susceptible to AF presentations to EDs, especially in regions with higher baseline levels of PM 2.5 or NO2.

Suitable temperature indicator for adverse health impacts in sub-tropical cities: a case study in Hong Kong from 2010-2019.

Heat-health warning systems and services are important preventive actions for extreme heat, however, global evidence differs on which temperature indicator is more informative for heat-health outcomes. We comprehensively assessed temperature predictors on their summer associations with adverse health impacts in a high-density subtropical city. Maximum, mean, and minimum temperatures were examined on their associations with non-cancer mortality and hospital admissions in Hong Kong during summer seasons 2010-2019 using Generalized Additive Models and Distributed Lag Non-linear Models. In summary, mean and minimum temperatures were identified as strong indicators for mortality, with a relative risk(RR) and 95% confidence interval(CI) of 1.037 (1.006-1.069) and 1.055 (1.019-1.092), respectively, at 95th percentile vs. optimal temperature. Additionally, minimum temperatures captured the effects of hospital admissions, RR1.009 (95%CI: 1.000- 1.018). In stratified analyses, significant associations were found for older adults, female sex, and respiratory-related outcomes. For comparison, there was no association between maximum temperature and health outcomes. With climate change and projected increase of night-time warming, the findings from this comprehensive assessment method are useful to strengthen heat prevention strategies and enhance heat-health warning systems. Other locations could refer to this comprehensive method to evaluate their heat risk, especially in highly urbanized environments and subtropical cities.

High sodium intake increases interstitial lung disease and pulmonary sarcoidosis based on the Global Burden of Disease study 1999–2019

This study investigated the relationships between dietary sodium intake and the incidence and prevalence of interstitial lung disease (ILD) and pulmonary sarcoidosis using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. This study assessed the strength of the abovementioned relationships via LASSO analysis and a generalized additive model with Poisson regression and determined the nonlinear and lagged effects via a distributed lag nonlinear model (DLNM). In the past three decades, global dietary sodium intake has decreased gradually. Two LASSO and generalized additive analyses both suggested that dietary sodium intake is obviously correlated with the incidence and prevalence of ILD and pulmonary sarcoidosis. The overall exposure‒response curve revealed a dose‒effect relationship between dietary sodium intake and the incidence and prevalence of ILD and pulmonary sarcoidosis. The maximum lag-specific RR of extremely high dietary sodium intake was 1.75 (95% CI: 1.61–1.91, lag 0 year) for incidence and 3.19 (95% CI: 2.24–4.53, lag 0 year) for prevalence relative to the reference. Our study suggests that dietary sodium intake is positively associated with the incidence and prevalence of ILD and pulmonary sarcoidosis. These findings may have important policy implications for dietary sodium intake-reduction strategies to decrease the burden of respiratory diseases and promote public health.

Risks of high temperature exposure on infectious diseases in Portuguese hospitals

Abstract Background The convergence of climate change and infectious diseases presents a growing public health challenge. As global temperatures continue to climb, the geographical spread of climate-sensitive diseases is shifting, underscoring the necessity for comprehensive early warning systems grounded in a One Health framework. Methods This retrospective observational study analyzed daily maximum temperature from May to September, between 2000 and 2018, in mainland Portugal, at a county level, obtained from a European-level gridded observations dataset. Hospital admissions with a primary diagnosis of infectious and parasitic diseases were sourced from the Hospital Morbidity Database. A distributed lag non-linear model was developed to estimate the immediate and lagged relative risks (RR) of temperature exposure on admissions, focused on a lag of 10 days. Results Our research reveals a 16% (95% CI: 9% - 23%) rise in the RR of hospital admissions due to infectious and parasitic diseases after exposure to extremely high temperatures (39 °C). This elevated risk persists for up to 2 days following exposure, with the second day exhibiting the largest increase at 53% (31% - 80%). Furthermore, our findings indicate a subsequent resurgence in RR, reaching 6% (2% - 11%) 9 days after exposure. Conclusions Our results highlight a short-term effect of extreme temperature exposure on infectious and parasitic disease admissions. This data provides valuable insights to guide policymakers in identifying critical periods of vulnerability and implementing this knowledge into heat early warning systems, contributing to developing effective public health strategies against climate change. Acknowledgments The authors thank Fundação para a Ciência e a Tecnologia (FCT, Portugal) for research grant UIDP/04923/2020 and NOVA National School of Public Health for access to the Hospital Morbidity Database made available for research purposes by Administração Central do Sistema de Saúde, IP (ACSS). Key messages • Exposure to extremely high temperatures increases the risk of admission due to infectious and parasitic diseases by 16%, with a peak occurring two days after exposure. • This data is essential for policymakers to identify and integrate vulnerable periods into early heat warning systems, enhancing effective public health strategies against climate change.

Development of a heat mortality surveillance approach for England

Abstract Background England’s unprecedented temperatures in 2022 and 2023 highlighted the severe risks of rising global temperatures on public health. This study considers the impact of heatwave events on mortality rates, supporting the development of improved health surveillance and intervention strategies. Methods Firstly, heat-associated mortality for each heat episode was estimated by comparing observed daily mortality values with the expected baseline of daily deaths. Secondly, the historic temperature-mortality relationship was established at national and regional levels using a distributed lag non-linear model with temperature and mortality data from the previous 5 years. Finally, modelled estimates of heat-associated excess mortality were generated based on the historic temperature-mortality relationships, to assess any difference between observed and modelled estimates. Results In 2022 which saw record-breaking maximum temperatures in the UK, an estimated 2,985 (2,258-3,712) heat-associated deaths were recorded across five heat episodes, the highest annual count to date. Despite relatively cool temperatures, 2023 saw the third-highest heat-associated mortality since reporting began in 2016 of 2,295 (1,681-2,910). Comparisons between modelled and observed mortality were generally similar, but showed statistically significant discrepancies for certain heat episodes across the two summers. Conclusions Heatwaves have a rapid and clear impact on health, emphasising the need for effective early warning systems and interventions. The comparison of observed mortality with predictions from historic temperature-mortality relationships at regional level demonstrates the need for a nuanced approach to surveillance and health protection for adverse heat, with factors other than temperature also playing a critical role in health impacts. This will inform continuous improvements in England’s impact-based Heat Health Alerting system. Key messages • Heatwaves pose a significant risk to public health, as evidenced by the unprecedented excess deaths during the record-breaking temperatures in England in Summer 2022. • Comparison of observed mortality with predictions from historic data can provide insight into contextual factors modulating the health impacts of heat, and inform future surveillance and response.

Low ambient temperature and incident myocardial infarction with or without obstructive coronary arteries: a Chinese nationwide study.

Although non-optimum ambient temperature is a major non-traditional risk factor for acute myocardial infarction, there is no prior knowledge on whether non-optimum ambient temperature could differentially affect myocardial infarction with obstructive coronary artery disease (MI-CAD) and myocardial infarction with non-obstructive coronary arteries (MINOCA). Using the Chinese Cardiovascular Association database-Chest Pain Center Registry, a nationwide, time-stratified, case-crossover investigation was conducted from 2015 to 2021. Meteorological data were obtained from an established satellite-based model, and daily exposures were assigned according to the onset of myocardial infarction in each patient. A conditional logistic regression model combined with distributed lag non-linear models (10 days) was used to estimate the exposure-response relationships. A total of 83 784 MINOCA patients and 918 730 MI-CAD patients were included. The risk of MINOCA and MI-CAD associated with low temperature occurred at lag 2 day and lasted to 1 week. Extremely low temperature was associated with a substantially greater odds ratio (OR) of MINOCA [OR 1.58, 95% confidence interval (CI) 1.31-1.90] than MI-CAD (unmatched: OR 1.32, 95% CI 1.23-1.43; equally matched by age and sex: OR 1.25, 95% CI 1.04-1.50), compared with the corresponding reference temperatures (30°C, 35°C, and 30°C). Stronger associations were observed for patients who were aged ≥65 years, female, or resided in the south. There was no significant difference for the impacts of high temperature on MINOCA and MI-CAD. This nationwide study highlights the particular susceptibility of MINOCA patients to ambient low temperature compared with that of MI-CAD patients.

Impact of temperature and humidity on airway obstruction in a cohort of elderly women

Abstract Background Temperature and relative humidity (RH) impact human health. However, little is known about the combined association between temperature and RH on respiratory health in the elderly. In this study, we evaluated the interactive associations of temperature and RH on airway obstruction in elderly German women. Methods Using data from the second follow-up (2007-2010) of the German SALIA cohort study, we assessed the short-term (Lag0-8) combined association between maximum and minimum temperature (Tmax, Tmin) and RH on airway obstruction. Airway obstruction was defined as the ratio of first second of forced expiration (FEV1) / forced vital capacity (FVC) < 0.70. Multivariable logistic regression with a distributed lag non-linear model (DLNM) was constructed for the interaction between temperature and RH and adjusted for a single pollutant, location, socioeconomic status and smoking status. Results 735 elderly women with an average (±SD) age of 73.46 (±3.09) years were included. Around 16.73% of them had airway obstruction. For non-linear antagonistic Tmax and RH interaction models, we found a U-shaped relationship from Lag 0-8, with an immediate adverse association from Lag0-1 and a significant delayed adverse association from Lag7-8. For non-linear antagonistic Tmin and RH interaction models, the relationship was U-shaped and showed an immediate adverse association from Lag0-1, while there was also a significant delayed association from Lag6-8. Conclusions Climate change increases the likelihood of exposure to adverse temperatures and weather conditions. Vulnerable populations like the elderly are more susceptible to the adverse associations of climate change. In this epidemiological study, we found that exposure to Tmax/Tmin and RH had immediate and delayed adverse associations by increasing respiratory obstruction in elderly women. Increasing public awareness of the danger of interactions between non-optimum temperature and RH on respiratory health is crucial. Key messages • Elderly women’s respiratory health is impacted by temperature and humidity interactions, requiring awareness and proactive measures. • Climate change heightens risk for vulnerable groups, emphasising the need to address environmental impacts on health.

A data-driven framework for the definition of heat in CV research for better comprehension of climate changes on human health

Abstract Background Recent literature has identified numerous combinations of meteorological indicators, methods and comparison thresholds to define heat in order to analyse its impact on adverse cardiovascular (CV) events. In fact, despite increasing attention to the issue due to ongoing climate change, there is no standardised definition of heat nor guidelines for its establishment, and in studies often little attention is given to the selected definition, despite its impact on the results. Purpose To fill this gap, our aim was to propose a data-driven framework for selecting the temperature threshold for defining heat in the context of studies on adverse CV outcomes, combining the most common approaches identified in the literature. Methods The following five-step framework is proposed: 1) Selection of temperature lags based on the contour plot obtained by the distributed lag non-linear model (DLNM); 2) Estimation of the relative risk (RR) of having a CV emergency in heat versus non-heat days by Poisson regression considering the 90th-99th percentile (%ile) of the temperature distribution for each lag; 3) Selection of the final lag based on the curvatures of the 10 included %iles; 4) Calculation of the % change in RR from %ile i to %ile i+1; 5) Selection of the heat threshold, defined as the %ile from which all the next %iles are associated with a higher % change, or, if not existing, the %ile preceding the one with the highest % change. We tested this framework, for each year, on retrospective CV emergencies in May-September 2017-2022 in Milan, Italy, using the apparent temperature data, accounting for air temperature, relative humidity and wind speed. Results The contour plot of the DLNM, controlled for air pollution, seasonality and long-term trend, showed that lags 0 and 1 were characterised by an increased RR for a CV emergency. The RR estimated for each %ile for each considered lag (i.e., heat on day i, heat on day i or on day i-1, and heat on day i and on day i-1), produced a similar curvature, so first lag option was arbitrarily selected. For Milan, the 95th %ile was the point from which all the subsequent %iles were associated to progressively higher % changes, resulting in a RR of having a CV emergency compared to non-heat days equal to 1.113 (95% CI: 1.087-1.139). The mean daily apparent temperature values associated to such %ile, varying from 27.7 °C to 29.9 °C depending on the year, should then be considered as the heat threshold in the examined context. Conclusion We proposed a flexible data-driven framework for the definition of heat that could easily be extended to similar scenarios. Although the framework still requires some arbitrary choices to be made, and the need of validation on other real-world data, it could provide a valuable guideline for relevant research, and could contribute to the standardization of heat definition for CV health research aiming at a better comprehension of climate changes on human health.

Effects of short-term exposures to lower air temperature and cold spells on myocardial infarction hospital admissions: a nationwide study in Sweden

Abstract Background Exposures to lower air temperature and cold spells have been associated with an increased risk of various diseases. However, the short-term effect of lower air temperature and cold spells on myocardial infarction (MI) remains incompletely understood. Purpose We aimed to evaluate the short-term effects of lower air temperature and cold spells on MI hospital admissions within the nationwide SWEDEHEART registry. Methods This population-based nationwide study included 120,380 MI cases admitted to hospitals in Sweden during the cold season (October to March) from 2005 to 2019. Daily mean air temperature was estimated at 1 km2 spatial resolution across Sweden using a three-stage machine learning approach and percentiles of daily temperatures experienced by individuals in the same municipality were employed as individual exposure indicators to account for potential geographic adaptation. Cold spells were defined as periods of at least two consecutive days with a daily mean temperature below the 10th percentile of the temperature distribution for each municipality. A time-stratified case-crossover design incorporating a conditional logistic regression model with distributed lag non-linear model using lag 0-1 and lag 2-6 days was employed to evaluate the short-term effects of lower air temperature and cold spells on total MI, non-ST-segment elevation MI (NSTEMI) and ST-segment elevation MI (STEMI). Results We found significant increases in risk for total MI, NSTEMI, and STEMI in association with a decrease of one percentile in temperature at a lag of 2-6 days, indicated by ORs (95% CI) of 1.099 (1.057-1.142), 1.110 (1.06-1.164), and 1.076 (1.004-1.153), respectively. Additionally, we found that cold spells were significantly associated with increased risks for total MI, NSTEMI, and STEMI at a lag of 2-6 days, with ORs (95% CI) of 1.077 (1.037-1.12), 1.069 (1.02-1.119), and 1.095 (1.023-1.172), respectively. Moreover, independent effects of lower air temperature and cold spells on MI occurrence were found after adjusting for each other. Conversely, we observed that lower air temperature and cold spells were associated with decreased risks for MI at a lag of 0-1 days. Conclusions This nationwide case-crossover study demonstrated a novel biphasic pattern in MI risk following exposure to lower air temperatures and cold spells, characterized by an initial transient reduction in risk at lags 0-1 day, followed by a significant increase in risk at lags 2-6 days. As climate change continues to induce complex shifts in regional weather patterns, enhancing protections to reduce future cold-related cardiac hospitalizations is crucial.

Short-term effects of ambient temperature variability on myocardial infarction hospitalizations in Sweden: A nationwide case-crossover study

Abstract Background Climate change threatens human health and general welfare via multiple dimensions. However, the short-term effect of temperature variability, a crucial aspect of climate change, on myocardial infarction (MI) remains largely unexplored. Purpose We aimed to assess the short-term effects of temperature variability on MI hospitalizations within the nationwide SWEDEHEART registry. Methods This population-based nationwide study involved 228,897 MI patients from the SWEDEHEART registry in Sweden from 2005 to 2019. High-resolution (1 km × 1 km) daily mean ambient temperature was estimated using a spatiotemporal machine learning methodology and assigned to patients’ home addresses. Temperature variability was calculated as the difference between the same-day (as the MI event) ambient temperature and the average temperature recorded over the preceding seven days. Specifically, an upward temperature shift represents a rise in the current day’s temperature relative to the seven-day average, while a downward temperature shift indicates a corresponding decrease. A time-stratified case-crossover design incorporating a conditional logistic regression model with distributed lag non-linear model was applied to estimate the association between ambient temperature variability and total MI, ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI). Moreover, we assessed potential effect modification by sex and medication intake. The results were expressed as odds ratio (OR, with their 95% confidence intervals [CIs]) per 1°C increase in temperature variability. Results Our study found that a 1°C increase in upward temperature shift was significantly associated with increased risks for total MI, STEMI, and NSTEMI (OR [95% CI]: 1.010 [1.006-1.015], 1.014 [1.006-1.022], and 1.009 [1.004-1.014], respectively). Furthermore, a 1°C greater in downward temperature shift was significantly associated with decreased risks for total MI and NSTEMI (OR [95% CI]: 0.995 [0.991-0.999], and 0.993 [0.988-0.998], respectively). Moreover, we found that males and patients who were on any heart medication, particularly digitalis, were at a higher risk of MI associated with exposure to higher upward temperature shifts compared to females and their counterparts not taking these medications. Conclusions This nationwide case-crossover study provides novel evidence that short-term exposure to increasing upward temperature shift is associated with an increased risk of MI hospitalization. Our finding highlights the cardiovascular health threats posed by upward temperature shifts, which are anticipated to increase in frequency and intensity due to climate change.

Effects of meteorological factors on tuberculosis and potential modifiers in Zhejiang Province, China

Although some studies have explored the role of meteorological factors in the development of tuberculosis (TB), the majority have been confined to single regions, leading to inconsistent findings. Consequently, we conducted a multi-city study not only to determine whether meteorological factors significantly influence the risk of developing TB but also to assess the magnitude of these effects and explore potential modifying factors. Data on daily reported TB cases and meteorological factors were collected from January 1, 2013, to December 31, 2022, across 11 cities in Zhejiang Province. A distributed lag non-linear model using a quasi-Poisson distribution was employed. Multivariate meta-regression was used to obtain overall pooled estimates and assess heterogeneity. From 2013 to 2022, 267,932 TB cases were reported in Zhejiang Province. Notably, a nonlinear relationship was observed between temperature and TB, with the relative risk (RR) peaking at 1.0 °C (RR = 1.882, 95% CI 1.173–3.020). The effect of low temperature was immediate and significant for a 13-day lag period, with the maximum effect at lag0 (RR = 1.014, 95% CI 1.008–1.021). The exposure-response curve between relative humidity (RH) and TB exhibited an M-shape, with the RR peaking at 47.7% (RR = 1.642, 95% CI 1.044–2.582). The lag effect of low RH was significant at lag 25–59, with the highest RR observed at lag 32 (RR = 1.011, 95% CI 1.001–1.022). Gross domestic product (GDP) per person, population density, and latitude demonstrated significant modification effects. Our study showed that low temperature and RH were associated with an increased risk of TB. Additionally, GDP per person, population density, and latitude may play important roles in explaining the association between RH and TB. These findings provide scientific evidence for the development of geographically specific public health policies.