Effects of diurnal temperature range on first-ever strokes in different seasons: a time-series study in Shenzhen, China

The impact of diurnal temperature range on the risk of hospitalizations in a low-income setting: the case of the Central Coast of Vietnam

The study aims to evaluate the effects of diurnal temperature range (DTR) on all causes, cardiovascular and respiratory conditions in the Central Coast of Vietnam, a tropical, low-income region with high DTR exposure but limited research. Daily hospital admission data from the largest hospitals in three provinces were analyzed alongside meteorological data. A time-series analysis using a generalized linear distributed lag model was conducted to examine the non-linear DTR-hospitalization association. A random-effect meta-analysis using restricted maximum likelihood was performed to calculate the pooled effects across three provinces. Stratified analyses by gender, age, season and natural disaster occurrence were conducted to identify vulnerable subpopulations. The multi-province pooled effects indicated that a 1 °C increase in DTR raised the risk of hospitalizations for all causes and respiratory diseases by 1.5% [1.2-1.8%] and 0.5% [0.0-1.0%], at lag 0-6 days. The effects of DTR on cardiovascular diseases, as well as those stratified by subgroups, were not statistically significant. Additionally, DTR had a greater adverse effect during the dry season and in the presence of natural disaster. Females and the elderly were slightly more susceptible to respiratory admissions, while males and younger individuals had a higher risk of all-cause admissions due to greater DTR effects. DTR was an independent risk factor for the exacerbation of all and specific causes, particularly among the susceptible subgroups. The findings suggested that it is necessary to take preventive measures to protect these at-risk populations from the adverse effects of extreme DTR exposure.

Daily temperature variability and mental health-related hospital visits in New York State

BACKGROUND

Despite plausible behavioral and physiological pathways, limited evidence exists on how daily temperature variability is associated with acute mental health-related episodes.

OBJECTIVES

We aimed to explore associations between daily temperature range (DTR) and mental health-related hospital visits using data of all hospital records in New York State during 1995-2014. We further examined factors that may modify these associations, including age, sex, hospital visit type and season.

METHODS

Using a case-crossover design with distributed lag non-linear DTR terms (0-6 days), we estimated associations between ZIP Code-level DTR and hospital visits for mood (4.6 million hospital visits), anxiety (2.4 million), adjustment (∼368,000), and schizophrenia disorders (∼211,000), controlling for daily mean temperature, via conditional logistic regression models. We assessed potential heterogeneity by age, sex, hospital visit type (in-patient vs. out-patient), and season (summer, winter, and transition seasons).

RESULTS

For all included outcomes, we observed positive associations from period minimum DTR (0.1 °C) until 25th percentile (5.2 °C) and between mean DTR (7.7 °C) and 90th percentile (12.2 °C), beyond which we observed negative associations. For mood disorders, an increase in DTR from 0.1 °C to 12.2 °C was associated with a cumulative 16.0% increase (95% confidence interval [CI]: 12.8, 19.2%) in hospital visit rates. This increase was highest during transition seasons (32.5%; 95%CI: 26.4, 39.0%) compared with summer (10.7%; 95%CI: 4.8, 16.8%) and winter (-1.6%; 95%CI: -7.6, 4.7%). For adjustment and schizophrenia disorders, the strongest associations were seen among the youngest group (0-24 years) with almost no association in the oldest group (65+ years). We observed no evidence for modification by sex and hospital visit type.

DISCUSSION

Daily temperature variability was positively associated with mental health-related hospital visits within specific DTR ranges in New York State, after controlling for daily mean temperature. Given uncertainty on how climate change modifies temperature variability, additional research is crucial to comprehend the implications of these findings, particularly under different scenarios of future temperature variability.

Effects of intra- and inter-day temperature change on acute upper respiratory infections among college students, assessments of three temperature change indicators

Background

Acute upper respiratory infection (AURI) is a significant disease affecting all age groups worldwide. The differences in the impacts of different temperature change indicators, such as diurnal temperature range (DTR), temperature variation (TV), and temperature change between neighboring days (TCN), on AURI morbidity, are not clear.

Methods

We collected data on 87,186 AURI patients during 2014-2019 in Zhengzhou. Distributed lag non-linear model was adopted to examine the effects of different temperature change indicators on AURI. We calculated and compared the attributable fractions (AF) of AURI morbidity caused by various indicators. We used stratified analysis to investigate the modification effects of season and gender.

Results

With the increase in DTR and TV, the risk of AURI tended to increase; the corresponding AF values (95% eCI) higher than the references (5% position of the DTR or TV distribution) were 24.26% (15.46%, 32.05%), 23.10% (15.59%, 29.20%), and 19.24% (13.90%, 24.63%) for DTR, TV0 - 1, and TV0 - 7, respectively. The harmful effects of TCN on AURI mainly occurred when the temperature dropped (TCN < 0), and the AF value of TCN below the reference (0°C) was 3.42% (1.60%, 5.14%). The harm of DTR and TV were statistically significant in spring, autumn and winter, but not in summer, while the harm of TCN mainly occurred in winter. Three indicators have statistically significant effects on both males and females.

Conclusions

High DTR and TV may induce AURI morbidity, while the harm of TCN occurs when the temperature drops. The impacts of DTR and TV on AURI are higher than that of TCN, and the impact of few-day TV is higher than that of multi-day TV. The adverse effects of DTR and TV are significant except in summer, while the hazards of TCN mainly occur in winter.

Seasonal impact of diurnal temperature range on intracerebral hemorrhage in middle-aged and elderly people in central China

OBJECTIVES

This study investigated the seasonal impact of diurnal temperature range (DTR) on hospitalization rates for intracerebral hemorrhage (ICH) in middle-aged and elderly adults.

METHODS

We collected data on the DTR and hospitalization records of ≥45-year-old patients with ICH in 2019 in Hunan Province, central China. Time-series analyses were performed using a distributed lag non-linear model.

RESULTS

Overall, 54,690 hospitalizations for ICH were recorded. DTR showed a non-linear relationship with ICH hospitalization in both middle-aged and elderly populations (45-59 and ≥60 years, respectively). During spring, a low DTR coupled with persistently low temperatures increased ICH risk in both age groups, while a high DTR was associated with an increased risk in the middle-aged group only (relative risk [RR], 1.24; 95% confidence interval [CI], 1.21 to 1.27). In the summer, a low DTR combined with persistently high temperatures was linked to a higher risk exclusively in the middle-aged group. A high DTR in the autumn was correlated with increased risk in both age groups. In winter, either a low DTR with a continuously low temperature or a high DTR elevated the risk solely in the elderly population (RR, 1.37; 95% CI, 1.00 to 1.69). In the elderly group, the impact of DTR on hospitalization risk manifested within a 5-day period.

CONCLUSIONS

The impact of DTR on ICH hospitalization risk differed significantly across seasons and between age groups. Elderly individuals demonstrated greater sensitivity to the impact of DTR. Weather forecasting services should emphasize DTR values, and interventions targeting sensitive populations are needed.

Climate change and disorders of the nervous system

Anthropogenic climate change is affecting people's health, including those with neurological and psychiatric diseases. Currently, making inferences about the effect of climate change on neurological and psychiatric diseases is challenging because of an overall sparsity of data, differing study methods, paucity of detail regarding disease subtypes, little consideration of the effect of individual and population genetics, and widely differing geographical locations with the potential for regional influences. However, evidence suggests that the incidence, prevalence, and severity of many nervous system conditions (eg, stroke, neurological infections, and some mental health disorders) can be affected by climate change. The data show broad and complex adverse effects, especially of temperature extremes to which people are unaccustomed and wide diurnal temperature fluctuations. Protective measures might be possible through local forecasting. Few studies project the future effects of climate change on brain health, hindering policy developments. Robust studies on the threats from changing climate for people who have, or are at risk of developing, disorders of the nervous system are urgently needed.

Hourly Heat Exposure and Acute Ischemic Stroke

Importance

Previous studies have demonstrated the associations of daily high temperature with hospitalizations and mortality from ischemic stroke, but the hourly association of ambient heat and acute ischemic stroke (AIS) onset has been rarely examined.

Objectives

To evaluate the association between hourly high ambient temperature and the onset of AIS.

Design, Setting, and Participants

This time-stratified case-crossover study was conducted using a nationwide registry that collects data from more than 200 stroke centers in China. Participants were adult patients with AIS who were hospitalized in the warm seasons between January 1, 2019, and December 31, 2021.

Exposures

Hourly temperature and single-hour temperature exposure lag up to 24 hours before the AIS onset (lag 0 hours to lag 24 hours).

Main Outcomes and Measures

The main outcome was onset of AIS. Associations between hourly mean temperatures and AIS onset were analyzed using conditional logistic regression integrated with the distributed lag nonlinear model. Stratification analyses were applied to examine potential association modifiers. Several sensitivity analyses were conducted to examine the robustness of the results.

Results

A total of 82 455 patients with AIS (mean [SD] age, 65.8 [11.9] years; 52 267 males [63.4%]) were included in the final analysis. A monotonically increasing risk of AIS onset was associated with higher temperatures. The excess AIS risk occurred immediately at lag 0 hours and persisted for 10 hours. Compared with the reference temperature (12.1 °C), the cumulative odds ratio (OR) over lag 0 to 10 hours of AIS onset associated with extremely high temperature (33.3 °C) was 1.88 (95% CI, 1.65-2.13) nationwide. The exposure-response curve was steeper in the north than in the south (OR, 1.80 [95% CI, 1.53-2.11] vs 1.57 [95% CI, 1.31-1.87]). The ORs were greater for males and patients with a history of dyslipidemia or atrial fibrillation, but the differences were not significant.

Conclusions and Relevance

Results of this study suggest that hourly heat exposure is associated with increased risk of AIS onset. This finding may benefit the formulation of public health strategies to reduce cerebrovascular risk associated with high ambient temperature under global warming.

Impact of diurnal temperature range on other infectious diarrhea in Tongcheng, China, 2010-2019: a distributed lag non-linear analysis

Our study aimed to quantify the exposure-lag-response effects of the diurnal temperature range (DTR) on other infectious diarrhea (OID) in Tongcheng city and examine the vulnerable populations. Distributed lag non-linear model (DLNM) and generalized additive model (GAM) were applied jointly to quantify the association between DTR and the daily number of OID cases compared with the median DTR. Stratified analysis was performed by gender, age, and seasons of onset. There are a total of 8231 cases during this decade. We observed a j-shaped relationship between DTR and OID, with a peak point at the maximum DTR (RR: 2.651, 95% CI: 1.320-5.323) compared to the median DTR. As DTR increased from 8.2 to 10.9 °C, we found the RRs started to decrease and then rise from day 0, and the minimum value occurred on day 7 (RR:1.003, 95% CI: 0.996-1.010). From stratified analysis, we observed that females and adults are more likely to be affected by high DTR significantly. In addition, the influence of DTR was different in cold and warm seasons. High DTR in warm seasons affects the number of OID daily cases, but no statistical significance was identified in cold seasons. This study suggests a significant relationship between high DTR and the incidence risk of OID.

Diurnal temperature range and hospital admission due to cardiovascular and respiratory diseases in Dezful, a city with hot climate and high DTR fluctuation in Iran: an ecological time-series study

The results of previous studies have indicated the effects of temperature changes on health status. The present study was conducted to investigate the effects of diurnal temperature range (DTR) and hospital admission on cardiovascular and respiratory diseases in Dezful, in Iran. In this ecological time-series study, data related to hospital admissions based on ICD-10, meteorological, and climatological data were gathered over a period of six years from 2014 to 2019. A distributed lag nonlinear model combined with a quasi-Poisson regression was then used to assess the impact of DTR on cardiovascular and respiratory hospital admissions. Potential confounders, including wind speed, air pollution, seasonality, time trend, weekends and holidays, days of week, and humidity were controlled. In extreme low DTRs, the cumulative effects of cardiovascular admissions significantly increased in total, and in warm and cold seasons (Lag_0-21, P ≤ 0.05). In addition, in extreme high DTRs, the cumulative effects of cardiovascular significantly decreased in total (Lag_0-13 and Lag_0-21, P ≤ 0.05), and in warm (Lag_0-21, P ≤ 0.05) and cold seasons (Lag_0-21, P ≤ 0.05). Moreover, respiratory admissions significantly decreased in total (Lag_0-21, P ≤ 0.05) and in warm season (Lag_0-21, P ≤ 0.05).Our result indicates that extreme low DTRs could increase the risk of daily cardiovascular admissions, and extreme high DTRs may cause a protective effect on daily respiratory and cardiovascular admissions in some regions with high fluctuations in DTR.

Impacts of Climate Change and Air Pollution on Neurologic Health, Disease, and Practice: A Scoping Review

BACKGROUND AND OBJECTIVES

Although the international community collectively seeks to reduce global temperature rise to less than 1.5°C before 2100, irreversible environmental changes have already occurred, and as the planet warms, these changes will continue to occur. As we witness the effects of a warming planet on human health, it is imperative that neurologists anticipate how the epidemiology and incidence of neurologic disease may change. In this review, we organized our analysis around 3 key themes related to climate change and neurologic health: extreme weather events and temperature fluctuations, emerging neuroinfectious diseases, and pollutant impacts. Across each of these themes, we appraised and reviewed recent literature relevant to neurologic disease and practice.

METHODS

Studies were identified using search terms relating to climate change, pollutants, and neurologic disease in PubMed, OVID MEDLINE, EMBASE, PsycInfo, and gray literature. Studies published between 1990 and 2022 were included if they pertained to human incidence or prevalence of disease, were in English, and were relevant to neurologic disease.

RESULTS

We identified a total of 364 articles, grouped into the 3 key themes of our study: extreme weather events and temperature fluctuations (38 studies), emerging neuroinfectious diseases (37 studies), and pollutant impacts (289 studies). The included studies highlighted the relationships between neurologic symptom exacerbation and temperature variability, tick-borne infections and warming climates, and airborne pollutants and cerebrovascular disease incidence and severity.

DISCUSSION

Temperature extremes and variability both associated with stroke incidence and severity, migraine headaches, hospitalization in patients with dementia, and multiple sclerosis exacerbations. Exposure to airborne pollutants, especially PM2.5 and nitrates, associated with stroke incidence and severity, headaches, dementia risk, Parkinson disease, and MS exacerbation. Climate change has demonstrably expanded favorable conditions for zoonotic diseases beyond traditional borders and poses the risk of disease in new, susceptible populations. Articles were biased toward resource-rich regions, suggesting a discordance between where research occurs and where changes are most acute. As such, 3 key priorities emerged for further study: neuroinfectious disease risk mitigation, understanding the pathophysiology of airborne pollutants on the nervous system, and methods to improve delivery of neurologic care in the face of climate-related disruptions.

Relationship between diurnal temperature range and emergency ambulance dispatches due to stroke in Guangzhou, China

BACKGROUND

The evidence between diurnal temperature range (DTR) and stroke remains controversial and sparse. We aimed to assess the relationship between DTR and emergency ambulance dispatches (EADs) due to stroke, and to explore whether there were effect modifications to the relationship.

METHODS

A Quasi-Poisson generalized linear regression combined with a distributed lag non-linear model was used to examine the relationship between DTR and EADs for stroke between January 1st 2011 and June 30th 2018 in Guangzhou, China. We estimated the effects of the low DTR and high DTR (defined as DTR below and above 10 °C respectively) on EADs. The effects of minimum, maximum, 5th, 25th, 50th, 75th, and 95th percentiles of DTR compared with the DTR of 10 °C were also analyzed.

RESULTS

A total of 20,275 EADs for stroke were included for analyses, among which 17,556 EADs were used in the model further adjusted for age and sex. A quasi-U-shaped relationship between DTR and EADs over lag0-2 days was observed. For the low DTR, per 1 °C decrease in DTR was significantly associated with an increase of 2.64% (RR = 1.03, 95% CI: 1.01-1.04) for EADs, while per 1 °C increase for the high DTR was non-significantly related with an increased risk of EADs (RR = 1.01, 95% CI: 0.90-1.13). Significant effects of the 5th and 25th percentiles of DTR on EADs were found when compared with the DTR of 10 °C. No significant effect modifications by age, sex or season were found to the association between DTR and EADs.

CONCLUSIONS

We found a quasi-U-shaped relationship between DTR and EADs due to stroke in this study, while age, sex or season did not significantly modify the association between DTR and EADs. More high-quality evidence is needed to further explore and validate the relationship between DTR and stroke.

The Influence of Selected Meteorological Factors on the Prevalence and Course of Stroke

Background: The objective of this study was to evaluate the impact of weather factors on stroke parameters. Methods: This retrospective study analyzed the records of stroke patients concerning the influence of meteorological conditions and moon phases on stroke parameters. Results: The study group consisted of 402 patients aged between 20 and 102; women constituted 49.8% of the subjects. Ischaemic stroke was diagnosed in 90.5% of patients and hemorrhagic stroke was diagnosed in 9.5% of patients. The highest number of hospitalizations due to stroke was observed in January (48 events); the lowest number was observed in July (23 events). There was no statistically significant correlation between the meteorological parameters on the day of onset and the preceding day of stroke and the neurological status (NIHSS) of patients. Mean air temperature on the day of stroke and the day preceding stroke was significantly lower in the group of patients discharged with a very good functional status (≤2 points in modified Rankin scale (mRS)) compared to the patients with a bad functional status (>2 points in mRS); respectively: 7.98 ± 8.01 vs. 9.63 ± 7.78; p = 0.041 and 8.13 ± 7.72 vs. 9.70 ± 7.50; p = 0.048). Humidity above 75% on the day of stroke was found to be a factor for excellent functional state (RR 1.61; p = 0.016). The total anterior circulation infarcts (in comparison with stroke in the other localization) were more frequent (70%) during a third quarter moon (p = 0.011). The following parameters had a significant influence on the number of stroke cases in relation to autumn having the lowest number of onsets: mean temperature (OR 1.019 95% CI 1.014–1.024, p < 0.000), humidity (OR 1.028, CI 1.023–1.034, p < 0.0001), wind speed (OR 0.923, 95% CI 0.909–0.937, p < 0.0001), insolation (OR 0.885, 95% CI 0.869–0.902, p < 0.0001), precipitation (OR 0.914, 95% CI 0.884–0.946, p < 0.0001). Conclusion: Air humidity and air temperature on the day of stroke onset as well as air temperature on the day preceding stroke are important for the functional status of patients in the acute disease period. A combination of the following meteorological parameters: lowered mean temperature and low sunshine, high humidity and high wind speed all increase the risk of stroke during the winter period. High humidity combined with high precipitation, low wind speed and low sunshine in the autumn period are associated with the lowest stroke incidence risk. A possible relationship between phases of the moon and the incidence requires further investigation.

Neural Network-Based Models for Estimating Weighted Mean Temperature in China and Adjacent Areas

The weighted mean temperature (Tm) is a key parameter when converting the zenith wet delay (ZWD) to precipitation water vapor (PWV) in ground-based Global Navigation Satellite System (GNSS) meteorology. Tm can be calculated via numerical integration with the atmospheric profile data measured along the zenith direction, but this method is not practical in most cases because it is not easy for general users to get real-time atmospheric profile data. An alternative method to obtain an accurate Tm value is to establish regional or global models on the basis of its relations with surface meteorological elements as well as the spatiotemporal variation characteristics of Tm. In this study, the complex relations between Tm and some of its essentially associated factors including the geographic position and terrain, surface temperature and surface water vapor pressure were considered to develop Tm models, and then a non-meteorological-factor Tm model (NMFTm), a single-meteorological-factor Tm model (SMFTm) and a multi-meteorological-factor Tm model (MMFTm) applicable to China and adjacent areas were established by adopting the artificial neural network technique. The generalization performance of new models was strengthened with the help of an ensemble learning method, and the model accuracies were compared with several representative published Tm models from different perspectives. The results show that the new models all exhibit consistently better performance than the competing models under the same application conditions tested by the data within the study area. The NMFTm model is superior to the latest non-meteorological model and has the advantages of simplicity and utility. Both the SMFTm model and MMFTm model show higher accuracy than all the published Tm models listed in this study; in particular, the MMFTm model is about 14.5% superior to the first-generation neural network-based Tm (NN-I) model, with the best accuracy so far in terms of the root-mean-square error.

Optimal Antihypertensive Medication Adherence Reduces the Effect of Ambient Temperature on Intracerebral Hemorrhage Occurrence: A Case-Crossover Study

BACKGROUND AND PURPOSE

The role of antihypertensive medication adherence in reducing the effect of ambient temperature (TEM) on intracerebral hemorrhage (ICH) pathogenesis is unclear. We aimed to study the influence of ambient TEM on the ICH occurrence in hypertensive patients with different medication adherence.

METHODS

We enrolled consecutive ICH patients with a definite history of hypertension in a teaching hospital over a period of six years. Medication adherence was calculated using the proportion of prescription days covered (PDC) to antihypertensive mediation in the last month before the ICH attack. Optimal medication adherence (OMA) was the PDC > 80%, and non-optimal medication adherence (non-OMA) was ≤80%. Daily ambient TEM and its variation were collected as the explanatory variables, and dominant air pollutants were gathered as covariates. We adopted a time-stratified case-crossover approach to minimize individual confounders. Conditional logistic regression was conducted to calculate the odds ratio (OR) of daily ambient TEM on ICH occurrence.

RESULTS

We recruited a total of 474 patients in this study. The number of participants with OMA and non-OMA was 249 and 225. Daily mean and max TEM in lag0 to lag2, as well as daily min TEM in lag0 to lag1, were significantly related to ICH onset in all enrolled patients and non-OMA cases. However, only daily TEM in lag0 was meaningfully associated with ICH onset in the OMA cases. The risk of ICH in OMA patients, respectively, changed by 7.9% (OR = 0.921, [0.861, 0.985]) or 6.3% (OR = 0.937, [0.882, 0.995]) when daily mean or max TEM was altered by 1°C in lag0, but the change raised by 10.4% (OR = 0.896, [0.836, 0.960]) or 7.5% (OR = 0.925, [0.868, 0.986]) in non-OMA patients. And the risk varied (OR = 0.933, [0.882, 0.988]) only in non-OMA patients when daily min TEM was altered by 1°C in lag1.

CONCLUSION

Our results indicate that OMA to antihypertensive drugs reduces the influence of ambient TEM on ICH occurrence in hypertensive patients.