Association of ambient temperature and diurnal temperature range with the outcome of in vitro fertilization in women from Hubei, China: A retrospective cohort study.

OBJECTIVES: To examine the relationship between ambient temperature and DTR and pregnancy outcomes in vitro fertilization/intracytoplasmic monosperm injection and embryo transfer (IVF/ICSI-ET) women. METHODS: The study included 5264 women who were treated with IVF/ICSI-ET at two centers in Hubei province from 2017 to 2022. The daily mean, daily maximum, and daily minimum temperatures at the subjects' home addresses were extracted, and DTR values were calculated based on latter two. The associations between ambient temperature and DTR with clinical pregnancy and live birth rates were assessed using multivariate logistic regression models adjusted for covariates. Subgroup analyses were also conducted to explore potential modifiers. RESULT: High/low temperatures as well as a larger DTR had a significant effect on pregnancy outcomes in fresh cycles, but not in FET cycles. Specifically, hot weather exposure to high temperatures was associated with reduced clinical pregnancy rates: Period 4 (embryo transfer to serum HCG testing) (aOR = 0.873, 95%CI: 0.763-0.999). Ambient temperature in cold weather was positively associated with live birth rate: Period 2 (Gn initiation to oocyte retrieval) (aOR = 1.082, 95% CI: 1.01-1.170), Period 3 (oocyte retrieval to embryo transfer) (aOR = 1.111, 95% CI: 1.019-1.212), Period 4 (aOR = 1.134, 95% CI: 1.028-1.252), and Period 7 (85 days prior to oocyte retrieval to serum hCG testing) (aOR = 1.105, 95% CI: 1.007-1.212). For DTR, exposure to larger DTR (Q3) at Period 2, Period 3, and Period 6 (Gn initiation to embryo transfer) reduces clinical pregnancy and live birth rates compared with Q1. Subgroup analyses revealed susceptibility profiles across age groups and residential address populations in different sensitivity windows. CONCLUSION: Our study shows that exposure to hot and cold weather and higher DTR reduces clinical pregnancy rates and live birth rates in women undergoing fresh embryo transfer, but has no significant effect on FET cycles.

Diurnal temperature range and hypertension: cross-sectional and longitudinal findings from the China Health and Retirement Longitudinal Study (CHARLS).

BACKGROUND: Research indicates a positive association between short-term diurnal temperature range (DTR) exposure and hypertension. However, the impact of long-term DTR exposure has not been thoroughly studied in population-based cohort research. METHODS: This study conducted cross-sectional (including 16,690 participants) and longitudinal analyses (including 9,650 participants) based on the China Health and Retirement Longitudinal Study (CHARLS). Daily temperature data was sourced from the National Scientific Data of the Qinghai-Tibet Plateau. We calculated the moving average of DTR exposure of all the participants in CHARLS with exposure windows of 30-day, 60-day, 180-day, 1-year, and 2-year before the interview month of CHARLS Wave1 (2011). Logistic regression and age-stratified Cox proportional hazards models were employed in our analysis. RESULTS: In the cross-sectional study, 6,572 (39.4%) participants had hypertension. We found higher DTR is associated with a higher prevalence of hypertension across different exposure windows. The effect was strongest when the exposure window of DTR was 180-day, with an adjusted odds ratio (OR) of 1.261 (95% confidence interval (CI): 1.124-1.416 [highest tertile DTR vs. lowest tertile DTR]). In the cohort study, 3,020 (31.3%) participants developed hypertension during 83 months of follow-up. A higher level of DTR (hazard ratio (HR): 1.224, 95% CI: 1.077-1.391) was associated with a higher risk of incident hypertension. We found significant interactions between DTR and age (P interaction: <0.001) and residence (P interaction: 0.045). CONCLUSION: We found significant positive associations between DTR and prevalent and incident hypertension. Individuals younger than 65 and those living in rural areas are at an elevated risk of developing hypertension due to DTR.

The correlation between daily temperature, diurnal temperature range, and asthma hospital admissions in Lanzhou city, 2013-2020.

BACKGROUND: With the backdrop of global climate change, the impact of climate change on respiratory diseases like asthma is receiving increasing attention. However, the effects of temperature and diurnal temperature range (DTR) on asthma are complex, and understanding these effects across different seasons, age groups, and sex is of utmost importance. METHODS: This study utilized asthma hospitalization data from Lanzhou, China, and implemented a distributed lag nonlinear model (DLNM) to investigate the relationship between temperature and DTR and asthma hospitalizations. It considered differences in the effects across various seasons and population subgroups. RESULTS: The study revealed that low temperatures immediately increase the risk of asthma hospitalization (RR = 1.2010, 95% CI: 1.1464, 1.2580), and this risk persists for a period of time. Meanwhile, both high and low DTR were associated with an increased risk of asthma hospitalization. Lower temperatures (RR = 2.9798, 95% CI: 1.1154, 7.9606) were associated with higher asthma risk in the warm season, while in the cold season, the risk significantly rose for the general population (RR = 3.6867, 95% CI: 1.7494, 7.7696), females (RR = 7.2417, 95% CI: 2.7171, 19.3003), and older individuals (RR = 18.5425, 95% CI: 5.1436, 66.8458). In the warm season, low DTR conditions exhibited a significant association with asthma hospitalization risk in males (RR = 7.2547, 95% CI: 1.2612, 41.7295) and adults aged 15-64 (RR = 9.9494, 95% CI: 2.2723, 43.5643). Children also exhibited noticeable risk within specific DTR ranges. In the cold season, lower DTR increases the risk of asthma hospitalization for the general population (RR = 3.1257, 95% CI: 1.4004, 6.9767). High DTR significantly increases the risk of asthma hospitalization in adults (RR = 5.2563, 95% CI: 2.4131, 11.4498). CONCLUSION: This study provides crucial insights into the complex relationship between temperature, DTR, and asthma hospitalization, highlighting the variations in asthma risk across different seasons and population subgroups.

Association between diurnal temperature range and outpatient visits for urticaria disease in Lanzhou, China: a distributed lag nonlinear analysis.

BACKGROUND: A growing number of epidemiological studies have shown that daily temperatures are associated with urticaria. However, the relationship between daily changes in temperature and urticaria is unclear. OBJECTIVES: To assess the diurnal temperature difference (DTR) effects on urticaria outpatient visits in Lanzhou, China. METHODS: Urticaria outpatient visits data during 2011-2019 were collected from three major tertiary hospitals in Lanzhou. Daily temperature data from the official website of China Meteorological Administration. Assessment of the relationship between urticaria outpatient volume and DTR in Lanzhou City using a distributed lag nonlinear model. RESULTS: A total of 83,022 urticaria visits were enrolled. There was a nonlinear relationship between DTR and urticaria outpatient visits and a lagged effect of DTR impact. The effects of high DTR on urticaria visits were not seen in all populations but in the male population and in the 15-59 age group. High DTR (P95: 18.2 °C) was associated with a 27% (95% CI: 0.01, 60.53%) and 31% (95% CI: 1.60, 68.99%) increase in the number of urticaria visits in the 21-day lag effect for the male cohort and the 15-59 year old cohort, respectively, compared with 11.5 °C, respectively. CONCLUSIONS: Our study suggests that DTR is a potential risk factor for urticaria. The results of this study may provide a scientific basis for local governments to improve preventive measures in the health care system.

The impact of short-term exposure to meteorological factors on the risk of death from hypertension and its major complications: a time series analysis based on Hefei, China.

OBJECTIVES: This study aimed to reveal the short-term impact of meteorological factors on the mortality risk in hypertensive patients, providing a scientific foundation for formulating pertinent prevention and control policies. METHODS: In this research, meteorological factor data and daily death data of hypertensive patients in Hefei City from 2015 to 2018 were integrated. Time series analysis was performed using distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Furthermore, we conducted stratified analysis based on gender and age. Relative risk (RR) combined with 95% confidence interval (95% CI) was used to represent the mortality risk of single day and cumulative day in hypertensive patients. RESULTS: Single-day lag results indicated that high daily mean temperature (T mean) (75th percentile, 24.9 °C) and low diurnal temperature range (DTR) (25th percentile, 4.20 °C) levels were identified as risk factors for death in hypertensive patients (maximum effective RR values were 1.144 and 1.122, respectively). Extremely high levels of relative humidity (RH) (95th percentile, 94.29%) reduced the risk of death (RR value was 0.893). The stratified results showed that the elderly and female populations are more susceptible to low DTR levels, whereas extremely high levels of RH have a more significant protective effect on both populations. CONCLUSION: Overall, we found that exposure to low DTR and high T mean environments increases the risk of death for hypertensive patients, while exposure to extremely high RH environments significantly reduces the risk of death for hypertensive patients. These findings contribute valuable insights for shaping targeted prevention and control strategies.

Effects of short-term and long-term exposure to ambient air pollution and temperature on long recovery duration in COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) has spread rapidly around the world since December 8, 2019. However, the key factors affecting the duration of recovery from COVID-19 remain unclear. OBJECTIVE: To investigate the associations of long recovery duration of COVID-19 patients with ambient air pollution, temperature, and diurnal temperature range (DTR) exposure. METHODS: A total of 427 confirmed cases in Changsha during the first wave of the epidemic in January 2020 were selected. We used inverse distance weighting (IDW) method to estimate personal exposure to seven ambient air pollutants (PM2.5, PM2.5-10, PM10, SO2, NO2, CO, and O3) at each subject's home address. Meteorological conditions included temperature and DTR. Multiple logistic regression model was used to investigate the relationship of air pollution exposure during short-term (past week and past month) and long-term (past three months) with recovery duration among COVID-19 patients. RESULTS: We found that long recovery duration among COVID-19 patients was positively associated with short-term exposure to CO during past week with OR (95% CI) = 1.42 (1.01-2.00) and PM2.5, NO2, and CO during past month with ORs (95% CI) = 2.00 (1.30-3.07) and 1.95 (1.30-2.93), and was negatively related with short-term exposure to O3 during past week and past month with ORs (95% CI) = 0.68 (0.46-0.99) and 0.41 (0.27-0.62), respectively. No association was observed for long-term exposure to air pollution during past three months. Furthermore, increased temperature during past three months elevated risk of long recovery duration in VOCID-19 patients, while DTR exposure during past week and past month decreased the risk. Male and younger patients were more susceptible to the effect of air pollution on long recovery duration, while female and older patients were more affected by exposure to temperature and DTR. CONCLUSION: Our findings suggest that both TRAP exposure and temperature indicators play important roles in prolonged recovery among COVID-19 patients, especially for the sensitive populations, which provide potential strategies for effective reduction and early prevention of long recovery duration of COVID-19.

Diurnal temperature range impacts on outpatients department visits for allergic rhinitis in Lanzhou, China.

OBJECTIVE: This study aims to investigate the association between the diurnal temperature range (DTR) and allergic rhinitis (AR) outpatient visits in Lanzhou, China, utilizing more than 7 years of participant surveys. METHODS: Our study used the distributed lag non-linear model (DLNM) aimed to evaluate the association between DTR and AR outpatient visits. We also performed subgroup analyses in order to find susceptible populations by gender and age groups. RESULTS: In 2013-2019, DTR in Lanzhou demonstrates a non-linear correlation with outpatient visits for AR, which is S-shaped. In addition, when DTR was located in the 0.9-5.3 °C and 12-20 °C compared with 12 °C, the risk of outpatient visits for AR increased. Moreover, males appeared to be more vulnerable to the DTR effect than females, the risk of children visits exceeded both the adult and the elderly groups at the higher DTR. CONCLUSION: Our study adds to the evidence that DTR is a possible risk factor for outpatient visits for AR; therefore, the public health sector and medical staff should take DTR into account when it comes to preventing AR onset.

Characterization of the Difference between Day and Night Temperatures on the Growth, Photosynthesis, and Metabolite Accumulation of Tea Seedlings.

Currently, the effects of the differences between day and night temperatures (DIFs) on tea plant are poorly understood. In order to investigate the influence of DIFs on the growth, photosynthesis, and metabolite accumulation of tea plants, the plants were cultivated under 5 °C (25/20 °C, light/dark), 10 °C (25/15 °C, light/dark), and 15 °C (25/10 °C, light/dark). The results showed that the growth rate of the new shoots decreased with an increase in the DIFs. There was a downward trend in the photosynthesis among the treatments, as evidenced by the lowest net photosynthetic rate and total chlorophyll at a DIF of 15 °C. In addition, the DIFs significantly affected the primary and secondary metabolites. In particular, the 10 °C DIF treatment contained the lowest levels of soluble sugars, tea polyphenols, and catechins but was abundant in caffeine and amino acids, along with high expression levels of theanine synthetase (TS3) and glutamate synthase (GOGAT). Furthermore, the transcriptome data revealed that the differentially expressed genes were enriched in valine, leucine, and isoleucine degradation, flavone/flavonol biosyntheses, flavonoid biosynthesis, etc. Therefore, we concluded that a DIF of 10 °C was suitable for the protected cultivation of tea plants in terms of the growth and the quality of a favorable flavor of tea, which provided a scientific basis for the protected cultivation of tea seedlings.

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 (Lag0-21, P ≤ 0.05). In addition, in extreme high DTRs, the cumulative effects of cardiovascular significantly decreased in total (Lag0-13 and Lag0-21, P ≤ 0.05), and in warm (Lag0-21, P ≤ 0.05) and cold seasons (Lag0-21, P ≤ 0.05). Moreover, respiratory admissions significantly decreased in total (Lag0-21, P ≤ 0.05) and in warm season (Lag0-21, 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.

Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities.

In this article, the maximum and minimum daily temperature data for Indian cities were tested, together with the predicted diurnal temperature range (DTR) for monthly time horizons. RClimDex, a user interface for extreme computing indices, was used to advance the estimation because it allowed for statistical analysis and comparison of climatological elements such time series, means, extremes, and trends. During these 69 years, a more erratic DTR trend was seen in the research area. This study investigates the suitability of three deep neural networks for one-step-ahead DTR time series (DTRTS) forecasting, including recurrent neural network (RNN), long short-term memory (LSTM), gated recurrent unit (GRU), and auto-regressive integrated moving average exogenous (ARIMAX). To evaluate the effectiveness of models in the testing set, six statistical error indicators, including root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (R), percent bias (PBIAS), modified index of agreement (md), and relative index of agreement (rd), were chosen. The Wilson score approach was used to do a quantitative uncertainty analysis on the prediction error to forecast the outcome DTR. The findings show that the LSTM outperforms the other models in terms of its capacity to forget, remember, and update information. It is more accurate on datasets with longer sequences and displays noticeably more volatility throughout its gradient descent. The results of a sensitivity analysis on the LSTM model, which used RMSE values as an output and took into account different look-back periods, showed that the amount of history used to fit a time series forecast model had a direct impact on the model's performance. As a result, this model can be applied as a fresh, trustworthy deep learning method for DTRTS forecasting.

[Effect of Diurnal Temperature Range on the Number of Residents Hospitalized Due to Stroke in Lanzhou].

Objective To analyze the relationship between diurnal temperature range (DTR) and the hospitalization of stroke in Lanzhou,so as to provide a scientific basis for probing into the mechanism of temperature changes in inducing stroke and formulating comprehensive prevention and control measures for stroke by relevant departments.Methods The information of the patients hospitalized due to stroke in Lanzhou during January 2014 to December 2019 and the air pollutants (PM10,SO2,and NO2) and meteorological data in the same period were collected for statistical analysis.Spearman rank correlation analysis was performed to analyze the correlations between air pollutants and meteorological factors.The distributed lag nonlinear model was adopted to fit the relationship between DTR and the number of stroke inpatients,and three-dimensional diagrams and the correlation diagrams of DTR against stroke risk were established.The stratified analysis was performed according to gender and age (< 65 years and ≥65 years).Results From 2014 to 2019,a total of 92 812 stroke patients were hospitalized in Lanzhou,with a male-to-female ratio of 1.35:1.There was a nonlinear relationship between DTR and the number of stroke inpatients in Lanzhou,which presented a lag effect.The low DTR at 4.5 ℃ had the largest RR value of 1.25 (95%CI=1.16-1.35) for stroke inpatients at a cumulative lag of 18 d.The effect of high DTR (18.5 ℃) on the hospitalization of stroke patients peaked at a cumulative lag of 21 d,with an RR value of 1.09 (95%CI=1.01-1.18).The stratified analysis results suggested that low levels of DTR had greater effects on the hospitalization of male stroke patients and stroke patients <65 years.Conclusions Short-term exposure to different levels of DTR had an impact on the number of stroke inpatients,and low levels of DTR had a slightly greater impact on stroke inpatients than high levels of DTR.Importance should be attached to the protection of males and people aged <65 years at low levels of DTR.

Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range.

Phenotypic plasticity is observed widely in plants and often studied with reaction norms for adult plant or end-of-season traits. Uncovering genetic, environmental and developmental patterns behind the observed phenotypic variation under natural field conditions is needed. Using a sorghum (Sorghum bicolor) genetic population evaluated for plant height in seven natural field conditions, we investigated the major pattern that differentiated these environments. We then examined the physiological relevance of the identified environmental index by investigating the developmental trajectory of the population with multistage height measurements in four additional environments and conducting crop growth modelling. We found that diurnal temperature range (DTR) during the rapid growth period of sorghum development was an effective environmental index. Three genetic loci (Dw1, Dw3 and qHT7.1) were consistently detected for individual environments, reaction-norm parameters across environments and growth-curve parameters through the season. Their genetic effects changed dynamically along the environmental gradient and the developmental stage. A conceptual model with three-dimensional reaction norms was proposed to showcase the interconnecting components: genotype, environment and development. Beyond genomic and environmental analyses, further integration of development and physiology at the whole-plant and molecular levels into complex trait dissection would enhance our understanding of mechanisms underlying phenotypic variation.

Short-term effect of meteorological factors on the risk of rheumatoid arthritis hospital admissions: A distributed lag non-linear analysis in Hefei, China.

Rheumatoid arthritis (RA) is an autoimmune disease, mainly characterized by erosional arthritis. The proportion of adults suffering from RA is about 0.5%-1%. There have been reports on the association of rainfall and traffic-related air pollutants with RA hospitalization rates. However, there have been no studies on the association of diurnal temperature range (DTR) and relative humidity (RH) with RA hospitalization rates. This study aimed to examine the short-term association of DTR, RH and other meteorological factors with the hospital admission rate of RA patients, while excluding the interference of PM2.5, SO2, NO2, CO and O3 atmospheric pollutants. We collected daily RA occupancy rate and meteorological factor data in Hefei city from 2015 to 2018 and used the generalized additive model (GAM) combined with the distributed lag nonlinear model (DLNM) for time series analysis, and further stratified analysis by gender and age. Single-day and cumulative-day risk estimates of RA admissions were expressed as relative risk (RR) and its 95% confidence interval (95% CI). For the cumulative-day lag model, high RH was statistically significant after cumulative lag 0-8 days, and the effect gradually increases. Stratified analysis shows that females seem to be more susceptible to high or extremely high DTR and RH exposure, and extremely high DTR exposure may increase the risk of RA admission in all populations. In conclusion, this study found that high DTR and high RH exposure increased the risk of hospitalization in RA patients and provided clues to the potential association between other meteorological factors and RA.

Seasonal variation in association between temperature change and emergency department visits: A multi-site study in China.

BACKGROUND: There is limited evidence of effects and seasonal variation of temperature change on emergency department visits (EDVs). OBJECTIVE: To investigate the association between diurnal temperature range (DTR), temperature change between neighboring days (TCN) and a comprehensive collection of cause-specific EDVs in China. METHODS: We collected EDVs, weather, and air pollution data in 20 sites in China from 2014 to 2018. We applied a quasi-Poisson regression with distributed lag nonlinear model to evaluate DTR- and TCN-EDVs association. We used meta-analysis to pool site-specific estimates. We also conducted seasonal analysis and assess effects of modifiers. RESULTS: A 1 °C increase of DTR and TCN was associated with 0.29% [95% confidence interval (CI): 0.07%, 0.51%)] and 1.44% (95% CI: 0.93%, 1.96%) increase of total EDVs, respectively. People aged 18-44 were sensitive to DTR and TCN, while the elderly population was sensitive to TCN only in spring and autumn. In seasonal analysis, effects of temperature change on total EDVs were lower in summer. TCN increased risks of genitourinary diseases in summer, respiratory diseases in winter, injury in autumn, and mental diseases in spring. DTR increased the risk of respiratory diseases in autumn. CONCLUSION: Exposure to DTR and TCN was associated with elevated risk of EDVs but with great seasonal variations. Our results provided potential time and target populations for adaptive strategies and preventive measures.

An analysis of past and future heatwaves based on a heat-associated mortality threshold: towards a heat health warning system.

Heatwaves can have severe impacts on human health extending from illness to mortality. These health effects are related to not only the physical phenomenon of heat itself but other characteristics such as frequency, intensity, and duration of heatwaves. Therefore, understanding heatwave characteristics is a crucial step in the development of heat-health warning systems (HHWS) that could prevent or reduce negative heat-related health outcomes. However, there are no South African studies that have quantified heatwaves with a threshold that incorporated a temperature metric based on a health outcome. To fill this gap, this study aimed to assess the spatial and temporal distribution and frequency of past (2014 - 2019) and future (period 2020 - 2039) heatwaves across South Africa. Heatwaves were defined using a threshold for diurnal temperature range (DTR) that was found to have measurable impacts on mortality. In the current climate, inland provinces experienced fewer heatwaves of longer duration and greater intensity compared to coastal provinces that experienced heatwaves of lower intensity. The highest frequency of heatwaves occurred during the austral summer accounting for a total of 150 events out of 270 from 2014 to 2019. The heatwave definition applied in this study also identified severe heatwaves across the country during late 2015 to early 2016 which was during the strongest El Niño event ever recorded to date. Record-breaking global temperatures were reported during this period; the North West province in South Africa was the worst affected experiencing heatwaves ranging from 12 to 77 days. Future climate analysis showed increasing trends in heatwave events with the greatest increases (80%-87%) expected to occur during summer months. The number of heatwaves occurring in cooler seasons is expected to increase with more events projected from the winter months of July and August, onwards. The findings of this study show that the identification of provinces and towns that experience intense, long-lasting heatwaves is crucial to inform development and implementation of targeted heat-health adaptation strategies. These findings could also guide authorities to prioritise vulnerable population groups such as the elderly and children living in high-risk areas likely to be affected by heatwaves.

An Observational Constraint on Aviation-Induced Cirrus From the COVID-19-Induced Flight Disruption.

Global aviation dropped precipitously during the covid-19 pandemic, providing an unprecedented opportunity to study aviation-induced cirrus (AIC). AIC is believed to be responsible for over half of aviation-related radiative forcing, but until now, its radiative impact has only been estimated from simulations. Here, we show that satellite observations of cirrus cloud do not exhibit a detectable global response to the dramatic aviation reductions of spring 2020. These results indicate that previous model-based estimates may overestimate AIC. In addition, we find no significant response of diurnal surface air temperature range to the 2020 aviation changes, reinforcing the findings of previous studies. Though aviation influences the climate through multiple pathways, our analysis suggests that its warming effect from cirrus changes may be smaller than previously estimated.

Impact of diurnal temperature range on cardiovascular disease hospital admissions among Chinese farmers in Dingxi (the Northwest China).

BACKGROUND: Diurnal temperature range (DTR) has been widely applied in exploring its effect on cardiovascular disease (CVD). However, few studies have investigated the correlations between DTR and CVD in poor rural areas in China. This study aimed to examine the association between DTR and CVD in rural China. METHODS: A distributed lag nonlinear model was used to evaluate the relationship between DTR and CVD risk among farmers living in the city of Dingxi (Northwest China) in the period from January 1, 2016 to December 31, 2019. RESULTS: We observed nonlinear M-patterns between the relative risk (RR) of DTR (reference: median DTR, 12 °C) and CVD hospitalizations in all subgroups. The peak RR of CVD was noticed at DTR of 6 °C (total: 1.418; men: 1.546; women: 1.403; young: 1.778; old: 2.549) and 17 °C (total: 1.781; men: 1.937; women: 1.712; young: 2.233; old: 1.798). The adverse effect of DTR on CVD risk was more pronounced in females (RR 1.438) and elderly (RR 2.034) than males (RR 1.141) and younger adults (RR 1.852) at the extremely low (5th, 4 °C) DTR. The reverse was observed at the extremely high DTR (95th, 19 °C) (male: 1.267; females: 0.993; young: 1.586; old: 1.212). CONCLUSIONS: DTR is associated with CVD morbidity. This association was more pronounced in women and elderly, but men and younger peoples at extremely high DTR (19 °C). Future measures should take DTR into account to prevent CVD among susceptible populations.

Temperature variation and preterm birth among live singleton deliveries in Shenzhen, China: A time-to-event analysis.

OBJECTIVE: Ambient temperature extremes due to heat exposure was an established risk factor for preterm birth (<37 gestational weeks). However, there is insufficient epidemiological evidence on the effects of temperature variation(TV), although TV is also associated with heat exposure and can influence human health risk. This study aimed to investigate the relationship between inter- and intraday TV and preterm birth (PTB). METHOD: A total of 1,388,994 live singleton births were collected from January 2003 to December 2012, from the Shenzhen Birth registry system. Daily temperature range (DTR) was defined as the difference between the highest and lowest recorded daily temperature. Intraday TV was defined as the maximum daily diurnal temperature range in a given week (Max-DTR). Inter-day TV was defined as the maximum increase or decrease in daily mean temperature between days t and t-1in a given week; either an increase (Temp-inc) or a decrease (Temp-dec). We used Cox proportional hazards models to estimate TV-related PTB risks during the first trimester, the second trimester, and in late pregnancy. RESULTS: The maximum values for DTR, Temp-inc, and Temp-dec were 17 °C, 8 °C and 11 °C, respectively. The greatest TV-related PTB risk occurred in the second trimester, with 5.8% (95%CI: 3.3%, 8.3%), 23.7% (95%CI: 19.6%, 27.9%), and 4.4% (95%CI: 1.8%, 7.1%) differences per 1 °C increase in Max-DTR, Temp-inc, and Temp-dec, respectively. Greater TV was associated with elevated PTB risk during the warm season. The association between TV and PTB was modified by seasons, maternal education and chronic conditions. CONCLUSIONS: Sharp TV is a likely risk factor for PTB. Policy makers and clinicians should recognize the potential role of TV in the etiology of PTB so that interventions can be designed to protect pregnant women and their fetuses against extreme temperatures.

The effect and prediction of diurnal temperature range in high altitude area on outpatient and emergency room admissions for cardiovascular diseases.

PURPOSE: Diurnal temperature range (DTR) is a meteorological indicator closely associated with global climate change. Thus, we aim to explore the effects of DTR on the outpatient and emergency room (O&ER) admissions for cardiovascular diseases (CVDs), and related predictive research. METHODS: The O&ER admissions data for CVDs from three general hospitals in Jinchang of Gansu Province were collected from 2013 to 2016. A generalized additive model (GAM) with Poisson regression was employed to analyze the effect of DTR on the O&ER admissions for all cardiovascular diseases, hypertension, ischemic heart disease (IHD) and stoke. GAM was also used to preform predictive research of the effect of DTR on the O&ER admissions for CVDs. RESULTS: There were similar positive linear relationships between DTR and the O&ER visits with the four cardiovascular diseases. And the cumulative lag effects were higher than the single lag effects. A 1 °C increase in DTR corresponded to a 1.30% (0.99-1.62%) increase in O&ER admissions for all cardiovascular diseases. Males and elderly were more sensitivity to DTR. The estimates in non-heating season were higher than in heating season. The trial prediction accuracy rate of CVDs based on DTR was between 59.32 and 74.40%. CONCLUSIONS: DTR has significantly positive association with O&ER admissions for CVDs, which can be used as a prediction index of the admissions of O&ER with CVDs.

Effect modification of the association between diurnal temperature range and hospitalisations for ischaemic stroke by temperature in Hefei, China.

OBJECTIVES: Diurnal temperature range (DTR) is an important indicator of global climate change. Many epidemiological studies have reported the associations between high DTR and human health. This study investigated the association between DTR and hospitalisations for ischaemic stroke in Hefei, China. STUDY DESIGN: This is an ecological study. METHODS: Data of daily hospital admissions for ischaemic stroke and meteorological variables from 1 January 2009 to 31 December 2017 were collected in Hefei, China. A generalised additive model combined with distributed lag non-linear model was used to quantify the effects of DTR on ischaemic stroke. The interactive effect between DTR and temperature was explored with a non-parametric bivariate response surface model. RESULTS: High DTR was associated with hospitalisations for ischaemic stroke. The adverse effect of extremely high DTR (99th percentile [17.1 °C]) occurred after 8 days (relative risk [RR] = 1.021, 95% confidence interval [CI] = 1.002, 1.041) and the maximum effect appeared after 12 days (RR = 1.029, 95% CI = 1.011, 1.046). The overall trend of the effect of DTR on ischaemic stroke was decreasing. In addition, there was a significant interactive effect of high DTR and low temperature on ischaemic stroke. CONCLUSIONS: This study suggests that the impact of high DTR should be considered when formulating targeted measures to prevent ischaemic stroke, especially for those days with high DTR and low mean temperature.