Enhancing impacts of mesoscale eddies on Southern Ocean temperature variability and extremes.

As a major sink of anthropogenic heat and carbon, the Southern Ocean experienced pronounced warming with increasing extreme temperature events over the past decades. Mesoscale eddies that strongly influence the uptake, redistribution, and storage of heat in the ocean are expected to play important roles in these changes, yet observational evidence remains limited. Here, we employ a comprehensive analysis of over 500,000 historical hydrographic profile measurements combined with satellite-based eddy observations to show enhanced thermal eddy imprints in the Southern Ocean. Our observations reveal that anticyclonic (cyclonic) eddies are responsible for nearly half of the subsurface high (low)-temperature extremes detected, although only 10% of the profiles are located in eddy interiors. Over the past decade (2006 to 2019), both mean and extreme temperature anomalies within eddies in the Antarctic Circumpolar Current increased significantly, promoting the rise in subsurface ocean temperature variability. This enhanced role of eddies is likely a result of enhanced eddy pumping due to the increase in eddy intensity and ocean stratification caused by ocean warming. Our analysis underscores the crucial role of eddies in amplifying ocean temperature variability and extremes, with their effects expected to be even more pronounced as global warming persists.

Effects of ambient temperature on pediatric incident seizure: A case-crossover analysis using distributed lag non-linear models.

OBJECTIVE: Emerging evidence supports that brain dysfunction may be attributable to environmental factors. This study aims to examine associations of ambient temperature and temperature variability (TV) with seizure incidence in children, which has not been explored. MATERIAL AND METHODS: Data on 2718 outpatient visits due to seizure were collected in Shanghai, China, from 2018 to 2023. Exposure to ambient temperature was estimated at children's residential addresses using spatial-temporal models. A time-stratified case-crossover design with a distributed lag non-linear model (DLNM) was conducted to assess the association between seizure incidence and daily average of ambient temperature over a period of 21 days prior to a case date of disease onset. For a given case date, we selected all dates falling on the same day of the week within the same month as control dates. We calculated a composite index of intra-day and inter-day TV, which was the standard deviation of the daily minimum and maximum temperatures, respectively, over 7 days preceding a case date. We then assessed the association between TV and seizure incidence. Stratified analyses were conducted by age (73.51% < 5 years old and 26.49 % ≥ 5 years old), sex (41.83% female), presence of fever (69.72%), and diagnosis of epilepsy (27.63%). RESULTS: We observed inversed J-shaped temperature-response curves. Lower temperatures had a significant and prolonged effect than higher temperatures. Using 20 °C (with the minimum effect) as the reference, the cumulative odds ratios (ORs) for over 0-21 days preceding the onset at the 5th percentile of the temperature (3 °C) and at the 95th percentile (29 °C) were 3.17 (95% CI: 1.77, 5.68) and 1.54 (95% CI: 0.97, 2.44), respectively. In addition, per 1 °C increases in TV0-7 was associated with OR of 1.08 (95% CI: 1.01, 1.15). Older children and those experiencing seizure with fever exhibited a higher risk of seizure onset at both lower and higher ambient temperatures. CONCLUSION: Both low and high temperatures can contribute to the morbidity related to pediatric seizure. Lower temperatures, however, exerted a longer period of effect prior to seizure onset than higher temperatures. An increased risk for incident seizure was significantly associated with temperature variability during preceding 7 days.

Time-series analysis of temperature variability and cardiovascular emergency department visits in Atlanta over a 27-year period.

BACKGROUND: Short-term temperature variability, defined as the temperature range occurring within a short time span at a given location, appears to be increasing with climate change. Such variation in temperature may influence acute health outcomes, especially cardiovascular diseases (CVD). Most research on temperature variability has focused on the impact of within-day diurnal temperature range, but temperature variability over a period of a few days may also be health-relevant through its impact on thermoregulation and autonomic cardiac functioning. To address this research gap, this study utilized a database of emergency department (ED) visits for a variety of cardiovascular health outcomes over a 27-year period to investigate the influence of three-day temperature variability on CVD. METHODS: For the period of 1993-2019, we analyzed over 12 million CVD ED visits in Atlanta using a Poisson log-linear model with overdispersion. Temperature variability was defined as the standard deviation of the minimum and maximum temperatures during the current day and the previous two days. We controlled for mean temperature, dew point temperature, long-term time trends, federal holidays, and day of week. We stratified the analysis by age group, season, and decade. RESULTS: All cardiovascular outcomes assessed, except for hypertension, were positively associated with increasing temperature variability, with the strongest effects observed for stroke and peripheral vascular disease. In stratified analyses, adverse associations with temperature variability were consistently highest in the moderate-temperature season (October and March-May) and in the 65 + age group for all outcomes. CONCLUSIONS: Our results suggest that CVD morbidity is impacted by short-term temperature variability, and that patients aged 65 and older are at increased risk. These effects were more pronounced in the moderate-temperature season and are likely driven by the Spring season in Atlanta. Public health practitioners and patient care providers can use this knowledge to better prepare patients during seasons with high temperature variability or ahead of large shifts in temperature.

Effects of meteorological factors on influenza transmissibility by virus type/subtype.

BACKGROUND: Quantitative evidence on the impact of meteorological factors on influenza transmissibility across different virus types/subtypes is scarce, and no previous studies have reported the effect of hourly temperature variability (HTV) on influenza transmissibility. Herein, we explored the associations between meteorological factors and influenza transmissibility according to the influenza type and subtype in Guangzhou, a subtropical city in China. METHODS: We collected influenza surveillance and meteorological data of Guangzhou between October 2010 and December 2019. Influenza transmissibility was measured using the instantaneous effective reproductive number (Rt). A gamma regression with a log link combined with a distributed lag non-linear model was used to assess the associations of daily meteorological factors with Rt by influenza types/subtypes. RESULTS: The exposure-response relationship between ambient temperature and Rt was non-linear, with elevated transmissibility at low and high temperatures. Influenza transmissibility increased as HTV increased when HTV < around 4.5 °C. A non-linear association was observed between absolute humidity and Rt, with increased transmissibility at low absolute humidity and at around 19 g/m3. Relative humidity had a U-shaped association with influenza transmissibility. The associations between meteorological factors and influenza transmissibility varied according to the influenza type and subtype: elevated transmissibility was observed at high ambient temperatures for influenza A(H3N2), but not for influenza A(H1N1)pdm09; transmissibility of influenza A(H1N1)pdm09 increased as HTV increased when HTV < around 4.5 °C, but the transmissibility decreased with HTV when HTV < 2.5 °C and 3.0 °C for influenza A(H3N2) and B, respectively; positive association of Rt with absolute humidity was witnessed for influenza A(H3N2) even when absolute humidity was larger than 19 g/m3, which was different from that for influenza A(H1N1)pdm09 and influenza B. CONCLUSIONS: Temperature variability has an impact on influenza transmissibility. Ambient temperature, temperature variability, and humidity influence the transmissibility of different influenza types/subtypes discrepantly. Our findings have important implications for improving preparedness for influenza epidemics, especially under climate change conditions.

Footprint of greenhouse forcing in daily temperature variability.

Changes in mean climatic conditions will affect natural and societal systems profoundly under continued anthropogenic global warming. Changes in the high-frequency variability of temperature exert additional pressures, yet the effect of greenhouse forcing thereon has not been fully assessed or identified in observational data. Here, we show that the intramonthly variability of daily surface temperature changes with distinct global patterns as greenhouse gas concentrations rise. In both reanalyses of historical observations and state-of-the-art projections, variability increases at low to mid latitudes and decreases at northern mid to high latitudes with enhanced greenhouse forcing. These latitudinally polarized daily variability changes are identified from internal climate variability using a recently developed signal-to-noise-maximizing pattern-filtering technique. Analysis of a multimodel ensemble from the Coupled Model Intercomparison Project Phase 6 shows that these changes are attributable to enhanced greenhouse forcing. By the end of the century under a business-as-usual emissions scenario, daily temperature variability would continue to increase by up to a further 100% at low latitudes and decrease by 40% at northern high latitudes. Alternative scenarios demonstrate that these changes would be limited by mitigation of greenhouse gases. Moreover, global changes in daily variability exhibit strong covariation with warming across climate models, suggesting that the equilibrium climate sensitivity will also play a role in determining the extent of future variability changes. This global response of the high-frequency climate system to enhanced greenhouse forcing is likely to have strong and unequal effects on societies, economies, and ecosystems if mitigation and protection measures are not taken.

Phytoplankton biodiversity is more important for ecosystem functioning in highly variable thermal environments.

The 21st century has seen an acceleration of anthropogenic climate change and biodiversity loss, with both stressors deemed to affect ecosystem functioning. However, we know little about the interactive effects of both stressors and in particular about the interaction of increased climatic variability and biodiversity loss on ecosystem functioning. This should be remedied because larger climatic variability is one of the main features of climate change. Here, we demonstrated that temperature fluctuations led to changes in the importance of biodiversity for ecosystem functioning. We used microcosm communities of different phytoplankton species richness and exposed them to a constant, mild, and severe temperature-fluctuating environment. Wider temperature fluctuations led to steeper biodiversity-ecosystem functioning slopes, meaning that species loss had a stronger negative effect on ecosystem functioning in more fluctuating environments. For severe temperature fluctuations, the slope increased through time due to a decrease of the productivity of species-poor communities over time. We developed a theoretical competition model to better understand our experimental results and showed that larger differences in thermal tolerances across species led to steeper biodiversity-ecosystem functioning slopes. Species-rich communities maintained their ecosystem functioning with increased fluctuation as they contained species able to resist the thermally fluctuating environments, while this was on average not the case in species-poor communities. Our results highlight the importance of biodiversity for maintaining ecosystem functions and services in the context of increased climatic variability under climate change.

The role of vegetation structural diversity in regulating the microclimate of human-modified tropical ecosystems.

Vegetation regulates microclimate stability through biophysical mechanisms such as evaporation, transpiration and shading. Therefore, thermal conditions in tree-dominated habitats will frequently differ significantly from standardized free-air temperature measurements. The ability of forests to buffer temperatures nominates them as potential sanctuaries for tree species intolerant to the increasingly challenging thermal conditions established by climate change. Although many factors influencing thermal conditions beneath the vegetation cover have been ascertained, the role of three-dimensional vegetation structure in regulating the understory microclimate remains understudied. Recent advances in remote sensing technologies, such as terrestrial laser scanning, have allowed scientists to capture the three-dimensional structural heterogeneity of vegetation with a high level of accuracy. Here, we examined the relationships between vegetation structure parametrized from voxelized laser scanning point clouds, air and soil temperature ranges, as well as offsets between field-measured temperatures and gridded free-air temperature estimates in 17 sites in a tropical mountain ecosystem in Southeast Kenya. Structural diversity generally exerted a cooling effect on understory temperatures, but vertical diversity and stratification explained more variation in the understory air and soil temperature ranges (30%-40%) than canopy cover (27%), plant area index (24%) and average stand height (23%). We also observed that the combined effects of stratification, canopy cover and elevation explained more than half of the variation (53%) in understory air temperature ranges. Stratification's attenuating effect was consistent across different levels of elevation. Temperature offsets between field measurements and free-air estimates were predominantly controlled by elevation, but stratification and structural diversity were influential predictors of maximum and median temperature offsets. Moreover, stable understory temperatures were strongly associated with a large offset in daytime maximum temperatures, suggesting that structural diversity primarily contributes to thermal stability by cooling daytime maximum temperatures. Our findings shed light on the thermal influence of vertical vegetation structure and, in the context of tropical land-use change, suggest that decision-makers aiming to mitigate the thermal impacts of land conversion should prioritize management practices that preserve structural diversity by retaining uneven-aged trees and mixing plant species of varying sizes, e.g., silvopastoral, or agroforestry systems.

A new method to separate the impacts of interday and intraday temperature variability on mortality.

BACKGROUND: Temperature variability (TV) is associated with increased mortality risks. However, the independent impacts of interday and intraday are still unknown. METHODS: We proposed a new method to decompose TV into interday TV and intraday TV through algebra derivation. Intraday TV was defined as the weighted average standard deviation (SD) of minimum temperature and maximum temperature on each day. Interday TV was defined as the weighted SD of daily mean temperatures during the exposure period. We then performed an illustrative analysis using data on daily mortality and temperature in France in 2019-2021. RESULTS: The novel interday and intraday TV indices were good proxies for existing indicators, inlcluding diurnal temperature range (DTR) and temperature change between neighbouring days (TCN). In the illustrative analyses, interday and intraday TVs showed differentiated mortality risks. Mortality burden related to TV was mainly explained by the intraday component, accounting for an attributable fraction (AF) of 1.81% (95% CI: 0.64%, 2.97%) of total mortality, more than twice the AF of interday TV (0.86%, 95% CI: 0.47%, 1.24%). CONCLUSIONS: This study proposed a novel method for identifying and isolating the different components of temperature variability and offered a comprehensive way to investigate their health impacts.

Temperature variability and common diseases of the elderly in China: a national cross-sectional study.

BACKGROUND: In the context of climate change, it has been well observed that short-term temperature variability (TV) could increase the overall and cause-specific mortality and morbidity. However, the association between long-term TV and a broader spectrum of diseases is not yet well understood, especially in the elderly. METHODS: Our study used data from the fourth Urban and Rural Elderly Population (UREP) study. Long-term TV was calculated from the standard deviation (SD) of daily minimum and maximum temperatures within the study periods (2010-2014, 2011-2014, 2012-2014, 2013-2014, and 2014). Ten self-reported diseases and conditions were collected by questionnaire, including cataract, hypertension, diabetes, cardio-cerebrovascular diseases, stomach diseases, arthritis, chronic lung disease, asthma, cancer, and reproductive diseases. The province-stratified logistic regression model was used to quantify the association between long-term TV and the prevalence of each disease. RESULTS: A total of 184,047 participants were included in our study. In general, there were significant associations between TV and the prevalence of most diseases at the national level. Cardio-cerebrovascular disease (OR: 1.16, 95% CI: 1.13, 1.20) generated the highest estimates, followed by stomach diseases (OR: 1.15, 95% CI: 1.10, 1.19), asthma (OR: 1.14, 95% CI: 1.06, 1.22), chronic lung diseases (OR: 1.08, 95% CI: 1.03, 1.13), arthritis (OR: 1.08, 95% CI: 1.05, 1.11), and cataract (OR: 1.06, 95% CI: 1.02, 1.10). Moreover, the associations varied by geographical regions and across subgroups stratified by sex, household income, physical activity, and education. CONCLUSIONS: Our study showed that long-term exposure to TV was associated with the prevalence of main diseases in the elderly. More attention should be paid to the elderly and targeted strategies should be implemented, such as an early warning system.

A study of temperature variability on admissions and deaths for cardiovascular diseases in Northwestern China.

OBJECTIVE: To explore the effect of temperature variability (TV) on admissions and deaths for cardiovascular diseases (CVDs). METHOD: The admissions data of CVDs were collected in 4 general hospitals in Jinchang City, Gansu Province from 2013 to 2016. The monitoring data of death for CVDs from 2013 to 2017 were collected through the Jinchang City Center for Disease Control and Prevention. Distributed lag nonlinear model (DLNM) was combined to analyze the effects of TV (daily temperature variability (DTV) and hourly temperature variability (HTV)) on the admissions and deaths for CVDs after adjusting confounding effects. Stratified analysis was conducted by age and gender. Then the attribution risk of TV was evaluated. RESULTS: There was a broadly linear correlation between TV and the admissions and deaths for CVDs, but only the association between TV and outpatient and emergency room (O&ER) visits for CVDs have statistically significant. DTV and HTV have similar lag effect. Every 1 ℃ increase in DTV and HTV was associated with a 3.61% (95% CI: 1.19% ~ 6.08%), 3.03% (95% CI: 0.27% ~ 5.86%) increase in O&ER visits for CVDs, respectively. There were 22.75% and 14.15% O&ER visits for CVDs can attribute to DTV and HTV exposure during 2013-2016. Males and the elderly may be more sensitive to the changes of TV. Greater effect of TV was observed in non-heating season than in heating season. CONCLUSION: TV was an independent risk factor for the increase of O&ER visits for CVDs, suggesting effective guidance such as strengthening the timely prevention for vulnerable groups before or after exposure, which has important implications for risk management of CVDs.

Temperature variability associated with respiratory disease hospitalisations, hospital stays and hospital expenses the warm temperate sub-humid monsoon climate.

OBJECTIVES: The abrupt change of climate has led to an increasing trend of hospitalised patients in recent years. This study aimed to analyse the temperature variability (TV) associated with respiratory disease (RD) hospitalisations, hospital stays and hospital expenses. STUDY DESIGN: The generalized linear model combined with distributed lag non-linear model was used to investigate the association between TV and RD hospitalisations. METHODS: TV was determined by measuring the standard deviation of maximum and minimum temperatures for the current day and the previous 7 days. RD hospitalisations data were obtained from three major tertiary hospitals in Huaibei City, namely, the Huaibei People's Hospital, the Huaibei Hospital Of Traditional Chinese Medicine and the Huaibei Maternal and Child Health Care Hospital. First, using a time series decomposition model, the seasonality and long-term trend of hospitalisations, hospital stays and hospital expenses for RD were explored in this warm temperate sub-humid monsoon climate. Second, robust models were used to analyse the association between TV and RD hospitalisations, hospital stays and hospital expenses. In addition, this study stratified results by sex, age and season. Third, using the attributable fraction (AF) and attributable number (AN), hospitalisations, hospital stays and hospital expenses for RD attributed to TV were quantified. RESULTS: Overall, 0.013% of hospitalisations were attributed to TV0-1 (i.e. TV at the current day and previous 1 day), corresponding to 220 cases, 1603 days of hospital stays and 1,308,000 RMB of hospital expenses. Females were more susceptible to TV than males, and the risk increased with longer exposure (the highest risk was seen at TV0-7 [i.e. TV at the current day and previous 7 days] exposure). Higher AF and AN were observed at ages 0-5 years and ≥65 years. In addition, it was also found that TV was more strongly linked to RD in the cool season. The hot season was positively associated with hospital stays and hospital expenses at TV0-3 to TV0-7 exposure. CONCLUSIONS: Exposure to TV increased the risk of hospitalisations, longer hospital stays and higher hospital expenses for RD. The findings suggested that more attention should be paid to unstable weather conditions in the future to protect the health of vulnerable populations.

Temperature variability and metabolic adaptation in terrestrial and aquatic ectotherms.

Thermodynamics is a major factor determining rates of energy expenditure, rates of biochemical dynamics, and ultimately the biological and ecological processes linked with resilience to global warming in ectothermic organisms. Nonetheless, whether ectothermic organisms exhibit general adaptive metabolic responses to cope with worldwide variation in thermal conditions has remained as an open question. Here we combine a model comparison approach with a global dataset of standard metabolic rates (SMR), including 1,160 measurements across 788 species of aquatic invertebrates, insects, fishes, amphibians and reptiles, to investigate the association between metabolic rates and environmental temperatures in their respective habitats. Our analyses suggest that variation in SMR after removing allometric and thermodynamic effects is best explained by the temperature range encountered across seasons, which always provided a better fit than the average temperature for the hottest and coldest month and mean annual temperatures. This pattern was consistent across taxonomic groups and robust to sensitivity analyses. Nonetheless, aquatic and terrestrial lineages responded differently to seasonality, with SMR declining - 6.8% °C-1 of thermal range across seasons in aquatic organisms and increasing 2.8% °C-1 in terrestrial organisms. These responses may reflect alternative strategies to mitigate the impact of increments in warmer temperatures on energy expenditure, either by means of metabolic reduction in thermally homogeneous water bodies or effective behavioral thermoregulation to exploit temperature heterogeneity on land.

Interactions of urbanisation, climate variability, and infectious disease dynamics: insights from the Coimbatore district of Tamil Nadu.

Climate change and shifts in land use/land cover (LULC) are critical factors affecting the environmental, societal, and health landscapes, notably influencing the spread of infectious diseases. This study delves into the intricate relationships between climate change, LULC alterations, and the prevalence of vector-borne and waterborne diseases in Coimbatore district, Tamil Nadu, India, between 1985 and 2015. The research utilised Landsat-4, Landsat-5, and Landsat-8 data to generate LULC maps, applying the maximum likelihood algorithm to highlight significant transitions over the years. This study revealed that built-up areas have increased by 67%, primarily at the expense of agricultural land, which was reduced by 51%. Temperature and rainfall data were obtained from APHRODITE Water Resources, and with a statistical analysis of the time series data revealed an annual average temperature increase of 1.8 °C and a minor but statistically significant rainfall increase during the study period. Disease data was obtained from multiple national health programmes, revealing an increasing trend in dengue and diarrhoeal diseases over the study period. In particular, dengue cases surged, correlating strongly with the increase in built-up areas and temperature. This research is instrumental for policy decisions in public health, urban planning, and climate change mitigation. Amidst limited research on the interconnections among infectious diseases, climate change, and LULC changes in India, our study serves as a significant precursor for future management strategies in Coimbatore and analogous regions.

Physiological responses and adjustments of corals to strong seasonal temperature variations (20-28°C).

Temperature is a key driver of metabolic rates. So far, we know little about potential physiological adjustments of subtropical corals to seasonal temperature changes (>8°C) that substantially exceed temperature fluctuation experienced by their counterparts in the tropics. This study investigated the effect of temperature reductions on Montastraea cavernosa and Porites astreoides in Bermuda (32°N; sea surface temperature ∼19-29°C) over 5 weeks, applying the following treatments: (i) constant control temperature at 28°C, and (ii) temperature reduction (0.5°C day-1) followed by constant temperature (20 days; acclimatization period) at 24°C and (iii) at 20°C. Both species decreased photosynthesis and respiration during temperature reduction as expected, which continued to decrease during the acclimatization period, indicating adjustment to a low energy turnover rather than thermal compensation. Trajectories of physiological adjustments and level of thermal compensation, however, differed between species. Montastraea cavernosa zooxanthellae metrics showed a strong initial response to temperature reduction, followed by a return to close to control values during the acclimatization period, reflecting a high physiological flexibility and low thermal compensation. Porites astreoides zooxanthellae, in contrast, showed no initial response, but an increase in pigment concentration per zooxanthellae and similar photosynthesis rates at 24°C and 20°C at the end of the experiment, indicating low acute thermal sensitivity and the ability for thermal compensation at the lowest temperature. Respiration decreased more strongly than photosynthesis, leading to significant build-up of biomass in both species (energy reserves). Results are important in the light of potential poleward migration of corals and of potential latitudinal and species-specific differences in coral thermal tolerance.

Association of childhood asthma with intra-day and inter-day temperature variability in Shanghai, China.

OBJECTIVES: Short-term temperature variability (TV) is associated with the exacerbation of asthma, but little is known about the relative effects of intra- and inter-day TV. We aimed to assess the relative impacts of intra- and inter-day TV on childhood asthma and to explore the modification effects by season. METHODS: A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was adopted to evaluate the nonlinear and lagged effects of TV on childhood asthma in Shanghai from 2009 to 2017. Intra- and inter-day TV was measured with diurnal temperature range (DTR) and temperature changes between neighboring days (TCN), respectively. RESULTS: Increased DTR was associated with the elevated relative risk (RR) of daily outpatient visits for childhood asthma (DOVCA) in both the whole year (RRlag0-14 for the 99th percentile: 1.264, 95% confidence interval (CI): 1.052, 1.518) and cold season (RRlag0-12 for the 99th percentile: 1.411, 95% CI: 1.053, 1.889). Higher TCN in the warm season was associated with the increased RR of DOVCA (RRlag0-14 for the 99th percentile: 2.964, 95% CI: 1.636, 5.373). The number and fraction of DOVCA attributed to an interquartile range (IQR) increase of TCN were higher than those attributed to DTR in both the whole year period and warm season. However, the number and fraction of DOVCA attributed to an IQR increase of DTR were greater than those attributed to TCN in the cold season. CONCLUSIONS: Our results provide novel evidence that both intra- and inter-day TV might be a trigger of childhood asthma. Higher DTR appeared to have greater impacts on childhood asthma in the cold season while an increase in TCN seemed to have bigger effects in the warm season.

Seasonal characteristics of temperature variability impacts on childhood asthma hospitalization in Hefei, China: Does PM2.5 modify the association?

OBJECTIVES: Evidence of childhood asthma hospitalizations associated with temperature variability (TV) and the attributable risk are limited in China. We aim to use a comprehensive index that reflected both intra- and inter-day TV to assess the TV-childhood asthma relationship and disease burden, further to identify seasonality vulnerable populations, and to explore the effect modification of PM2.5. METHODS: A quasi-distributed lagged nonlinear model (DLNM) combined with a linear threshold function was applied to estimate the association between TV and childhood asthma hospitalizations during 2013-2016 in Hefei, China. Subgroup analysis was conducted by age and sex. Disease burden is reflected by the attributable fraction and attributable number. Besides, modifications of PM2.5 were tested by introducing the cross-basis of TV and binary PM2.5 as an interaction term. RESULTS: The risk estimates peaked at TV0-3 and TV0-4 in the cool and the warm season separately, with RR of 1.051 (95%CI: 1.021-1.081) and 1.072 (95%CI: 1.008-1.125), and the effects lasted longer in the cool season. The school-age children in the warm season and all subgroups except pre-school children in the cool season were vulnerable to TV. It is estimated that the disease burden related to TV account for 6.2% (95% CI: 2.7%-9.4%) and 4% (95% CI: 0.6%-7.1%) during the cool and warm seasons in TV0-3. In addition, the risks of TV were higher under the high PM2.5 level compared with the low PM2.5 level in the cool season, although no significant differences between them. CONCLUSIONS: TV exposure significantly increases the risk and disease burden of childhood asthma hospitalizations, especially in the cool season. More medical resources should be allocated to school-age children. Giving priority to pay attention to TV in the cool season in practice could obtain the greatest public health benefits and those days with high TV and high PM2.5 need more attention.

The association between ambient temperature variability and myocardial infarction in a New York-State-based case-crossover study: An examination of different variability metrics.

BACKGROUND: Short-term temperature variability has been consistently associated with mortality, with limited evidence for cardiovascular outcomes. Previous studies have used multiple metrics to measure temperature variability; however, those metrics do not capture hour-to-hour changes in temperature. OBJECTIVES: We assessed the correlation between sub-daily temperature-change-over-time metrics and previously-used metrics, and estimated associations with myocardial infarction (MI) hospitalizations. METHODS: Hour-to-hour change-over-time was measured via three metrics: 24-hr mean absolute hourly first difference, 24-hr maximum absolute hourly first difference, and 24-hr mean hourly first difference. We first assessed the Spearman correlations between these metrics and four previously-used metrics (24-hr standard deviation of hourly temperature, 24-hr diurnal temperature range, 48-hr standard deviation of daily minimal and maximal temperatures, and 48-hr difference of daily mean temperature), using hourly data from the North America Land Data Assimilation System-2 Model. Subsequently, we estimated the association between these metrics and primary MI hospitalization in adult residents of New York State for 2000-2015 using a time-stratified case-crossover design. RESULTS: The hour-to-hour change-over-time metrics were correlated, but not synonymous, with previously-used metrics. We observed 809,259 MI, 45% of which were among females and the mean (standard deviation) age was 70 (15). An increase from mean to 90th percentile in mean absolute first difference of temperature was associated with a 2.04% (95% Confidence Interval [CI]: 1.30-2.78%) increase in MI rate. An increase from mean to 90th percentile in mean first difference also yielded a positive association (1.86%; 95%CI: 1.09-2.64%). We observed smaller- or similar-in-magnitude positive associations for previously-used metrics. DISCUSSION: First, short-term hour-to-hour temperature change was positively associated with MI risk. Second, all other variability metrics yielded positive associations with MI, with varying magnitude. In future research on temperature variability, researchers should define their research question, including which aspects of variability they intend to measure, and apply the appropriate metric. ALTERNATIVE: All metrics of temperature variability, including short-term hour-to-hour temperature changes, were positively associated with MI risk, though the magnitude of effect estimates varied by metric.

Disparities of weather type and geographical location in the impacts of temperature variability on cancer mortality: A multicity case-crossover study in Jiangsu Province, China.

BACKGROUND: Considering the serious health burden caused by adverse weather events, increasing researches focused on the relationship between temperature variability (TV) and cause-specific mortality, but its association with cancer was not well explored. We aimed to investigate the impacts of TV on cancer mortality and examine the modifying effects of weather type and geographical location as well as other characteristics. MATERIALS AND METHODS: Daily city-specific data of cancer deaths, mean temperature (Tmean), maximum and minimum temperatures (Tmax and Tmin), relative humidity (RH), rainfall, and air pollutants were collected during 2016-2017 in 13 cities in Jiangsu Province, China. TV0-t was defined as the standard deviation of the daily Tmax and Tmin on the exposure 0-t days. A two-stage analysis was applied. First, a time-stratified case-crossover design was used to examine the odds ratio (OR) and attributable fraction of cancer mortality per 1 °C increase in TV by adjusting for potential confounders. Random effect meta-analysis was used to summarize the pooled ORs. Second, stratified analysis was performed for weather type, geographical location, demographics, and other city-level characteristics. The weather was defined as four types according to days during warm or cold season combined with high or low RH. RESULTS: A total of 303670 cases were included in our study. Meta-analysis showed that the ORs of cancer mortality per 1 °C increase in TV0-t significantly increased and peaked in TV0-2 (OR=1.0098, 95% CI: 1.0039-1.0157). The attributable fraction of TV0-2 on cancer mortality was 4.74%, accounting for 14395 deaths in the study period. Significant ORs of TV-related cancer mortality were found during the warm season combined with high RH and in the northern region of Jiangsu. Susceptible groups of TV-related cancer mortality were identified as female patients, patients aged 45-65 years, and those living in cities with lower per capita green area. CONCLUSIONS: TV can significantly increase the risk of cancer mortality, especially during warm and humid days and in the northern region of Jiangsu. Findings are of great significance to formulate urban planning, resource allocation, and health intervention to prolong the life of cancer patients.

The acute effects of temperature variability on heart rate variability: A repeated-measure study.

BACKGROUND: The impacts of temperature variability on cardiac autonomic function remain unclear. OBJECTIVE: To explore the short-term associations between daily temperature variability and parameters of heart rate variability (HRV). METHODS: This is a repeated-measure study among 78 eligible participants in Shanghai, China. We defined temperature variability as diurnal temperature range (DTR), the standard-deviation of temperature (SDT) and temperature variability (TV). We evaluated 3 frequency-domain HRV parameters (VLF, LF and HF) and 4 time-domain parameters (SDNN, SDANN, rMSSD and pNN50). We used linear mixed-effect models to analyze the data after controlling for environmental and individual confounders. RESULTS: Temperature variability was significantly associated with decreased HRV, especially on the concurrent day. The exposure-response relationships were almost inversely linear for most parameters. Every one interquartile range (IQR) increase of DTR was associated with a decrease of 3.92% for VLF, 6.99% for LF, 5.88% for HF, 3.94% for rMSSD and 1.30% for pNN50. Each IQR increase of SDT was associated with a decline of 6.48% for LF, 5.91% for HF, 4.26% for rMSSD and 1.87% for pNN50. Every IQR increase of SDT was associated with a decrease of 4.39% for VLF, 7.67% for LF, 6.52% for HF, 3.22% for SDNN, 2.98% for SDANN, 4.05% for rMSSD, and 1.41% for pNN50. The decrements in HRV associated with temperature variability were more prominent in females. CONCLUSION: Temperature variability on the concurrent day could significantly decrease cardiac autonomic function, especially in females.

Effects of high-frequency temperature variabilities on the morbidity of chronic obstructive pulmonary disease: Evidence in 21 cities of Guangdong, South China.

BACKGROUND: While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported. OBJECTIVES: To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization. METHODS: We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities. RESULTS: A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12-38%) increase in COPD admissions. An IQR increase in IITV0-1 was associated with 18% (95% CI: 7-27%) increase in COPD admissions. Males and people aged 0-64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality. CONCLUSIONS: The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.