The effect of diurnal temperature range on blood pressure among 46,609 people in Northwestern China

Ambient air pollution contributed to pulmonary tuberculosis in China

Published studies on outdoor air pollution and tuberculosis risk have shown heterogeneous results. Discrepancies in prior studies may be partially explained by the limited geographic scope, diverse exposure times, and heterogeneous statistical methods. Thus, we conducted a multi-province, multi-city time-series study to comprehensively investigate this issue. We selected 67 districts or counties from all geographic regions of China as study sites. We extracted data on newly diagnosed pulmonary tuberculosis (PTB) cases, outdoor air pollutant concentrations, and meteorological factors in 67 sites from January 1, 2014 to December 31, 2019. We utilized a generalized additive model to evaluate the relationship between ambient air pollutants and PTB risk. Between 2014 and 2019, there were 172,160 newly diagnosed PTB cases reported in 67 sites. With every 10-μg/m3 increase in SO2, NO2, PM10, PM2.5, and 1-mg/m3 in CO, the PTB risk increased by 1.97% [lag 0 week, 95% confidence interval (CI): 1.26, 2.68], 1.30% (lag 0 week, 95% CI: 0.43, 2.19), 0.55% (lag 8 weeks, 95% CI: 0.24, 0.85), 0.59% (lag 10 weeks, 95% CI: 0.16, 1.03), and 5.80% (lag 15 weeks, 95% CI: 2.96, 8.72), respectively. Our results indicated that ambient air pollutants were positively correlated with PTB risk, suggesting that decreasing outdoor air pollutant concentrations may help to reduce the burden of tuberculosis in countries with a high burden of tuberculosis and air pollution.

Potential mechanisms of ischemic stroke induced by heat exposure

Recent decades of epidemiological and clinical research have suggested that heat exposure could be a potential risk factor for ischemic stroke. Despite climate factors having a minor impact on individuals compared with established risk factors such as smoking, their widespread and persistent effects significantly affect public health. The mechanisms by which heat exposure triggers ischemic stroke are currently unclear. However, several potential mechanisms, such as the impact of temperature variability on stroke risk factors, inflammation, oxidative stress, and coagulation system changes, have been proposed. This article details the potential mechanisms by which heat exposure may induce ischemic stroke, aiming to guide the prevention and treatment of high-risk groups in hot climates and support public health policy development.

The effect of ambient temperature on lipid metabolism in children: From a prospective cohort study

BACKGROUND

Dyslipidemia is increasingly recognized as an essential risk factor for cardiovascular diseases. However, few studies illustrated the effects of ambient temperature exposure (TE) on lipid levels in children. The study aimed to examine the association between ambient TE and lipid levels in children.

METHODS

Based on a prospective cohort, a total of 2423 children (with 4466 lipids measure person-time) were collected from 2014 to 2019. The meteorological observation data and adjusted variables were collected. Mixed-effect models and generalized additive mixed model (GAMM) were applied to investigate the association between ambient TE and lipid levels.

RESULTS

A significant negative association was observed between TE and low-density lipoprotein cholesterol (LDL-C) or total cholesterol (TC) levels both in all children [LDL-C, β(95%CI) = -0.350(-0.434,-0.265), P < 0.001; TC, β(95%CI) = -0.274(-0.389,-0.160), P < 0.001] and by different sex group. However, no significant association was found in low-density lipoprotein cholesterol (HDL-C) or triglycerides (TG) levels. The estimated optimal ambient TEs for LDL-C were 18.273 °C and 18.024 °C for girls and boys, respectively. For TC, the optimal ambient TEs were 17.949 °C and 18.024 °C, respectively. With ambient TE decreased, the risk of dyslipidemia increased for both boys [OR = 0.032(0.006,0.179), P < 0.001] and girls [OR = 0.582(0.576,0.587), P < 0.001].

CONCLUSION

This study provided a comprehensive illustration about the associations between ambient TE and lipid levels in different sex and ages from a prospective cohort study. The findings will provide evidence for the government to prevent dyslipidemia in vulnerable children through regulating TE.

A longitudinal study on the effect of PM2.5 components on blood pressure in the hypertensive patients from 2011 to 2019

Extensive research has established the link between PM2.5 exposure and blood pressure (BP) levels among normal individuals. However, the association between PM2.5 components and BP levels in hypertensive patients has not been fully explored. In this study, 12 971 hypertensive cases from Jinchang cohort (in Jinchang City, China) with nearly 9 years of follow-up were enrolled. Based on the linear mixed-effect model, the effects of fine particulate matter (PM2.5) and five major components [sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), black carbon (BC) and organic matter (OM)]on BP [systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP)]were evaluated by single-component model, component-joint model and component-residual model, respectively. A positive correlation was found between PM2.5 as well as its components (SO42-, NO3-, NH4+, BC and OM) exposure and BP levels. The effects of SO42-, BC and OM on BP were observed to be the most robust among the three models. Based on the results of interaction effects and stratified analysis, the effect of BC exposure on SBP, and the effect of PM2.5 and its five components on PP were greater in female than in males. Compared with elderly hypertensive patients, OM had more significant effects on SBP, DBP and MAP in young and (or) middle-aged hypertensive patients. During the heating season, the effect of PM2.5 and its components on BP was grater compared to the non-heating season. Meanwhile, PM2.5 and its components have a greater influence on BP in patients with hypertension combined with diabetes. Therefore, the findings suggested that both PM2.5 exposure and its components had a significant effect on BP in patients with hypertension. Women and young and middle-aged hypertensive patient were the sensitive population. The implementation of source control and reduction of PM2.5 emission (mainly for SO42-, BC and OM) may be of great significance to control BP level and could reduce the risk of cardiovascular disease in patients with hypertension.

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.

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.

Public health impacts of air pollution from the spatiotemporal heterogeneity perspective: 31 provinces and municipalities in China from 2013 to 2020

Air pollution has long been a significant environmental health issue. Previous studies have employed diverse methodologies to investigate the impacts of air pollution on public health, yet few have thoroughly examined its spatiotemporal heterogeneity. Based on this, this study investigated the spatiotemporal heterogeneity of the impacts of air pollution on public health in 31 provinces in China from 2013 to 2020 based on the theoretical framework of multifactorial health decision-making and combined with the spatial durbin model and the geographically and temporally weighted regression model. The findings indicate that: (1) Air pollution and public health as measured by the incidence of respiratory diseases (IRD) in China exhibit significant spatial positive correlation and local spatial aggregation. (2) Air pollution demonstrates noteworthy spatial spillover effects. After controlling for economic development and living environment factors, including disposable income, population density, and urbanization rate, the direct and indirect spatial impacts of air pollution on IRD are measured at 3.552 and 2.848, correspondingly. (3) China's IRD is primarily influenced by various factors such as air pollution, economic development, living conditions, and healthcare, and the degree of its influence demonstrates an uneven spatiotemporal distribution trend. The findings of this study hold considerable practical significance for mitigating air pollution and safeguarding public health.

Association between short-term daily temperature variability and blood pressure in the Chinese population: From the China hypertension survey

BACKGROUND

We aimed to evaluate the impacts of short-term daily temperature variability (DTV) on blood pressure (BP) among participants with normotension, prehypertension, and hypertension, respectively, and explore the effects in different climate zones and seasons.

METHODS

A representative population sample (n = 397,173) covering the subtropical, temperate continental, and temperate monsoon zones was obtained from the China Hypertension Survey. DTV was calculated as the standard deviation of daily minimum and maximum temperatures during the exposure days. The linear mixed effect regression model was used to estimate the associations between DTV exposure and BP among normotension, prehypertension, and hypertension, respectively, and further stratified analysis was performed by climate zones and seasons.

RESULTS

After adjustment for confounders, per interquartile range (IQR) increase in DTV (2.28 °C) at 0-6 days of exposure was associated with an increase of 0.41 mmHg (95 % confidence interval [CI]: 0.07, 0.75) in systolic BP (SBP) and 0.41 mmHg (95 % CI: 0.09, 0.72) in pulse pressure (PP) among hypertensive participants in the subtropical zone. Similarly, DTV exposure was associated with an increase of 0.31 mmHg (95 % CI: 0.06, 0.55) in SBP and 0.59 mmHg (95 % CI: 0.24, 0.94) in PP among prehypertensive participants in the temperate continental zone. Additionally, during the warm season, DTV was positively associated with SBP among populations with prehypertension and hypertension, and with PP among all three populations.

CONCLUSION

Short-term DTV exposure was associated with an increase in SBP and PP among hypertensive and prehypertensive participants in the subtropical zone and the temperate continental zone. In addition, positive associations of DTV with SBP and PP were observed among participants with prehypertension and hypertension in the warm season. Comprehensive health education and effective intervention strategies should be implemented to mitigate the effects of temperature variations on BP, particularly among prehypertensive and hypertensive populations.

Effects of large temperature change lasting for several days on cardiovascular disease hospital admissions among farmers in China's Western villages

Global climate change has resulted in an increase in the frequency, intensity, and duration of extreme events. However, we know very little about the associations between large temperature changes lasting for several days (LTCD) and CVD, particularly in less-developed, rural areas. We collected daily data on cardiovascular-related diseases and weather conditions from 119 villages in seven counties between 2010 and 2016. A distributed lag non-linear model was used to investigate the association between LTCD and relative risk (RR) of hospital admissions for CVD. Analyses were stratified by the duration and intensity of LTCD, age, and sex. The RR of CVD increases with the intensity and duration of LTCD. Men and young people were more vulnerable to LTCD of longer duration and higher intensity than women and old. Our findings may help local public health authorities develop adaptive preventive strategies targeting inhabitants of villages.

The modification of meteorological factors on the relationship between air pollution and periodontal diseases: an exploration based on different interaction strategies

We aimed to characterize the association between air pollutants exposure and periodontal diseases outpatient visits and to explore the interactions between ambient air pollutants and meteorological factors. The outpatient visits data of several large stomatological and general hospitals in Hefei during 2015-2020 were collected to explore the relationship between daily air pollutants exposure and periodontal diseases by combining Poisson's generalized linear model (GLMs) and distributed lag nonlinear model (DLNMs). Subgroup analysis was performed to identify the vulnerability of different populations to air pollutants exposure. The interaction between air pollutants and meteorological factors was verified in both multiplicative and additive interaction models. An interquartile range (IQR) increased in nitrogen dioxide (NO2) concentration was associated with the greatest lag-specific relative risk (RR) of gingivitis at lag 3 days (RR = 1.087, 95% CI 1.008-1.173). Fine particulate matter (PM2.5) exposure also increased the risk of periodontitis at the day of exposure (RR = 1.049, 95% CI 1.004-1.096). Elderly patients with gingivitis and periodontitis were both vulnerable to PM2.5 exposure. The interaction analyses showed that exposure to high levels of NO2 at low temperatures was related to an increased risk of gingivitis, while exposure to high levels of NO2 and PM2.5 may also increase the risk of gingivitis and periodontitis in the high-humidity environment, respectively. This study supported that NO2 and PM2.5 exposure increased the risk of gingivitis and periodontitis outpatient visits, respectively. Besides, the adverse effects of air pollutants exposure on periodontal diseases may vary depending on ambient temperature and humidity.

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.

Short-term impact of diurnal temperature range on cardiovascular diseases mortality in residents in northeast China

It has been reported that cardiovascular disease (CVD) has become one of the major threats to global public health and is associated with climate change. Several previous studies have shown the influence of ambient temperature on CVD, but lack some evidence for the short-term effect of diurnal temperature range (DTR) on CVD mortality in northeast China. This is the first study to assess the correlation between DTR and CVD mortality in Hulunbuir located in northeast China. Daily CVD mortality data and meteorological data were collected from 2014 to 2020. A quasi-Poisson generalized linear regression with a distributed lag non-linear model (DLNM) was applied to exploring the short-term impact of DTR on CVD mortality. Stratified analyses by gender, age, and season were conducted and the short-term impacts of extremely high DTR on CVD mortality were investigated. In this study, a total of 21,067 CVD mortality cases were recorded in Hulunbuir, China from 2014 to 2020. Compared to the reference value (11.20 [Formula: see text]C, 50[Formula: see text] percentile), a "U-shaped" non-linear relationship between DTR and CVD mortality was observed, and extremely high DTR increased the risk of CVD mortality. The short-term effect of extremely high DTR occurred immediately and lasted up to 6 days. In addition, the male and the age [Formula: see text] 65 groups were more likely to be affected by extremely high DTR compared with the female and the age < 65 groups, respectively. The results also showed that extremely high DTR in cold season had a more adverse effect on CVD mortality than warm season. This study suggests that extremely high DTR for cold season should be paid enough attention to for residents in northeast China. The male and the age [Formula: see text] 65 groups were more vulnerable to the impacts of DTR. The study results may provide some suggestions for decision-making by local public health authorities to avoid the adverse impacts of high DTR, and improve the health of residents, especially vulnerable groups in cold season.

Effects of indoor temperature and its fluctuation on blood pressure and its variability

Cardiovascular diseases (CVDs) are the number one health threat globally. Adverse indoor thermal environments are associated with excess mortality caused by CVDs in the cold season. While many studies have focused on the impact of indoor temperature on CVDs, none has considered the fluctuation of indoor temperature. To quantify the effect of indoor temperature on blood pressure and the effect of indoor temperature fluctuation on blood pressure variability (BPV), 172 middle-aged and elderly people in areas that experience both hot summers and cold winters in China completed a household survey regarding their characteristics and living habits. A hierarchical linear model (HLM) was used to analyze the impact of indoor temperature on home blood pressure. A multiple linear model was used to analyze the effect of indoor temperature fluctuation on day-to-day home blood pressure variability. The results showed that there was a significant negative correlation between morning temperature below 18 °C and blood pressure, especially systolic blood pressure (SBP). At the same time, morning temperature fluctuations have an independent influence on BPV, and a deviation of morning temperature fluctuation greater than 1.1 °C significantly increased BPV. Morning temperature and its fluctuation threshold for the rise of SBP and its variability of middle-aged and elderly people were clarified, which can provide a basis for the design, operation, and evaluation of residential thermal environmental health performance for the middle-aged and elderly population in this area, thereby reducing the cardiovascular health risk of the corresponding population.

Augmented temperature fluctuation aggravates muscular atrophy through the gut microbiota

Large temperature difference is reported to be a risk factor for human health. However, little evidence has reported the effects of temperature fluctuation on sarcopenia, a senile disease characterized by loss of muscle mass and function. Here, we demonstrate that higher diurnal temperature range in humans has a positive correlation with the prevalence of sarcopenia. Fluctuated temperature exposure (10-25 °C) accelerates muscle atrophy and dampens exercise performance in mid-aged male mice. Interestingly, fluctuated temperature alters the microbiota composition with increased levels of Parabacteroides_distasonis, Duncaniella_dubosii and decreased levels of Candidatus_Amulumruptor, Roseburia, Eubacterium. Transplantation of fluctuated temperature-shaped microbiota replays the adverse effects on muscle function. Mechanically, we find that altered microbiota increases circulating aminoadipic acid, a lysine degradation product. Aminoadipic acid damages mitochondrial function through inhibiting mitophagy in vitro. And Eubacterium supplementation alleviates muscle atrophy and dysfunction induced by fluctuated temperature. Our results uncover the detrimental impact of fluctuated temperature on muscle function and provide a new clue for gut-muscle axis.

Effects of short-term PM2.5 exposure on blood lipids among 197,957 people in eastern China

Globally, air pollution is amongst the most significant causes of premature death. Nevertheless, studies on the relationship between fine particulate matter (PM_2.5) exposure and blood lipids have typically not been population-based. In a large, community-based sample of residents in Yixing city, we assessed the relationship between short-term outdoor PM_2.5 exposure and blood lipid concentrations. Participants who attended the physical examination were enrolled from Yixing People's hospital from 2015 to 2020. We collected general characteristics of participants, including gender and age, as well as test results of indicators of blood lipids. Data on daily meteorological factors were collected from the National Meteorological Data Sharing Center ( http://data.cma.cn/ ) and air pollutant concentrations were collected from the China Air Quality Online Monitoring and Analysis Platform ( https://www.aqistudy.cn/ ) during this period. We applied generalized additive models to estimate short-term effects of ambient PM_2.5 exposure on each measured blood lipid-related indicators and converted these indicators into dichotomous variables (non- hyperlipidemia and hyperlipidemia) to calculate risks of hyperlipidemia associated with PM_2.5 exposure. A total of 197,957 participants were included in the analysis with mean age 47.90 years (± SD, 14.28). The increase in PM_2.5 was significantly associated with hyperlipidemia (odds ratio (OR) 1.003, 95% CI 1.001-1.004), and it was still significant in subgroups of males and age < 60 years. For every 10 μg/m³ increase in PM_2.5, triglyceride levels decreased by 0.5447% (95% CI - 0.7873, - 0.3015), the low-density lipoprotein cholesterol concentration increased by 0.0127 mmol/L (95% CI 0.0099, 0.0156), the total cholesterol concentration increased by 0.0095 mmol/L (95% CI 0.0053, 0.0136), and no significant association was observed between PM_2.5 and the high-density lipoprotein cholesterol concentration. After excluding people with abnormal blood lipid concentrations, the associations remained significant except for the high-density lipoprotein cholesterol concentration. PM_2.5 was positively correlated with low-density lipoprotein cholesterol and total cholesterol, and negatively correlated with triglyceride, indicating PM_2.5 can potentially affect health through blood lipid levels.

The association of ambient temperature variability with blood pressure in southern China

OBJECTIVES

Numerous studies have shown a positive relationship between temperature variability and mortality, but few studies have investigated the effect of temperature variability on blood pressure (BP). We aimed to estimate the effect of temperature variability on BP in Guangdong Province, southern China.

METHODS

Data on meteorological factors were obtained from the Guangdong Meteorological Center, and BP was collected from a series of cross-sectional surveys conducted in Guangdong Province, China, from 2004 to 2015. There were 38 088 participants aged 18 years and over. A generalized additive model was used to estimate the association between temperature variability and BP after adjusting for confounding variables.

RESULTS

Our study found a significant positive association between temperature variability and SBP, and this effect increased with the increment of exposure days in total population. The highest estimate was for temperature variability at 7 days lag (TV 0-7 ) with a 0.497 (95% confidence interval, 0.335-0.660) mmHg rise of SBP for each 1°C increase of TV 0-7 . The effects of TV 0-1 and TV 0-2 on SBP were higher for hypertensives than that for normotensives, and in warm season higher than that in cold season. However, we did not observe statistical significance between temperature variability and DBP.

CONCLUSIONS

There was a positive association between temperature variability and SBP in Guangdong Province, which should be considered in clinical management and epidemiological survey of hypertension.

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.

Health effect of temperature change on respiratory diseases in opposite phase in semi-arid region

The impact of temperature variation on health has attracted increasing attention under global climate change. A distributed lag non-linear model (DLNM) was performed to estimate the risk of two indicators of temperature change (diurnal temperature range (DTR) and temperature change between neighboring days (TCN)) on respiratory hospital visits in Lanzhou, a semi-arid climate city in western China from 2012 to 2018. The whole year is divided into two different temperature change periods according to the TCN of each solar term. The results showed that extreme high DTR can apparently enlarge respiratory risk, and it indicated strong cumulative relative risk (RR) in the temperature drop period. Extreme low TCN had strong adverse effects on respiratory diseases especially in temperature rise period, with the greatest RR of 1.068 (95% CI 1.004, 1.136). The effect of extreme high TCN was more obvious in temperature drop period, with a RR of 1.082 (95% CI 1.021, 1.148) at lag 7. Females were more affected by extreme temperature changes. Young people were more vulnerable to DTR, while TCN has a greater impact on the elderly.

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.

Sources of automatic office blood pressure measurement error: a systematic review

OBJECTIVE

Accurate and reliable blood pressure (BP) measurement is important for the prevention and treatment of hypertension. The oscillometric-based automatic office blood pressure measurement (AOBPM) is widely used in hospitals and clinics, but measurement errors are common in BP measurements. There is a lack of systematic review of the sources of measurement errors.

APPROACH

A systematic review of all existing research on sources of AOBPM errors. A search strategy was designed in six online databases, and all the literature published before October 2021 was selected. Those studies that used the AOBPM device to measure BP from the upper arm of subjects were included.

MAIN RESULTS

A total of 1365 studies were screened, and 224 studies were included in this final review. They investigated 22 common error sources with clinical AOBPM. Regarding the causes of BP errors, this review divided them into the following categories: the activities before measurement, patient's factors, measurement environment, measurement procedure, and device settings. 13 sources caused increased systolic and diastolic BP (SBP and DBP), 2 sources caused the decrease in SBP and DBP, only 1 source had no significant effect on BPs, and the other errors had a non-uniform effect (either increase or decrease in BPs). The error ranges for SBP and DBP were -14 to 33 mmHg and -6 to 19 mmHg, respectively.

SIGNIFICANCE

The measurement accuracy of AOBPM is susceptible to the influence of measurement factors. Interpreting BP readings need to be treated with caution in clinical measurements. This review made comprehensive evidence for the need for standardized BP measurements and provided guidance for clinical practitioners when measuring BP with AOBPM devices.

High-normal blood pressure (prehypertension) is associated with PM2.5 exposure in young adults

We aimed to examine PM_2.5 exposure, blood pressure (SBP and DBP) measurement, and hypertension risk factors and to assess the association between PM_2.5 exposure and hypertension among young adults. The mean SBP was 117.78 mmHg, with 11.22% high-normal blood pressure (prehypertension) and 2.51% hypertension (≥ 140 mmHg). DBP was 75.48 mmHg with 26.37% prehypertension and 4.53% hypertension (≥ 90 mmHg). The median PM_2.5 in the past year was 31.79 μg/m³, with highest in winter (49.33 μg/m³), followed by spring (37.34 μg/m³), autumn (29.64 μg/m³), and summer (24.33 μg/m³). Blood pressure was positively correlated with age, height, weight, BMI, daily smoking, alcohol consumption, mental stress, and staying up in the past 1 year, and negatively with season-specific temperature. After adjustment for the covariates, each 10 μg/m³ increase in PM_2.5 was associated with SBP (day 1 = 1.07 mmHg, day 3 = 1.25 mmHg, day 5 = 1.01 mmHg) and DBP (day 1 = 1.06 mmHg, day 3 = 1.28 mmHg, day 5 = 1.29 mmHg, day 15 = 0.87 mmHg, day 30 = 0.56 mmHg). Exposure in winter and the past year was associated with 1.21 mmHg and 0.95 increase mmHg in SBP, respectively. Logistic models showed for every 1 μg/m³ increase of PM_2.5, SBP in day 1 and day 5 was increased by 6% and 4%, and DPB by 3% and 16%, respectively. SBP was increased by 8% in spring and 19% in winter, and DBP was increased by 7% in winter. Our data suggest a certain prevalence of pre- or hypertension among young population, which is associated with short-term fluctuation and season-specific exposure of PM_2.5.

Effects of short-term ambient particulate matter exposure on the risk of severe COVID-19

OBJECTIVES

Previous studies have suggested a relationship between outdoor air pollution and the risk of coronavirus disease 2019 (COVID-19). However, there is a lack of data related to the severity of disease, especially in China. This study aimed to explore the association between short-term exposure to outdoor particulate matter (PM) and the risk of severe COVID-19.

METHODS

We recruited patients diagnosed with COVID-19 during a recent large-scale outbreak in eastern China caused by the Delta variant. We collected data on meteorological factors and ambient air pollution during the same time period and in the same region where the cases occurred and applied a generalized additive model (GAM) to analyze the effects of short-term ambient PM exposure on the risk of severe COVID-19.

RESULTS

A total of 476 adult patients with confirmed COVID-19 were recruited, of which 42 (8.82%) had severe disease. With a unit increase in PM10, the risk of severe COVID-19 increased by 81.70% (95% confidence interval [CI]: 35.45, 143.76) at a lag of 0-7 days, 86.04% (95% CI: 38.71, 149.53) at a lag of 0-14 days, 76.26% (95% CI: 33.68, 132.42) at a lag of 0-21 days, and 72.15% (95% CI: 21.02, 144.88) at a lag of 0-28 days. The associations remained significant at lags of 0-7 days, 0-14 days, and 0-28 days in the multipollutant models. With a unit increase in PM2.5, the risk of severe COVID-19 increased by 299.08% (95% CI: 92.94, 725.46) at a lag of 0-7 days, 289.23% (95% CI: 85.62, 716.20) at a lag of 0-14 days, 234.34% (95% CI: 63.81, 582.40) at a lag of 0-21 days, and 204.04% (95% CI: 39.28, 563.71) at a lag of 0-28 days. The associations were still significant at lags of 0-7 days, 0-14 days, and 0-28 days in the multipollutant models.

CONCLUSIONS

Our results indicated that short-term exposure to outdoor PM was positively related to the risk of severe COVID-19, and that reducing air pollution may contribute to the control of COVID-19.

A comparison of the effect of diurnal temperature range and apparent temperature on cardiovascular disease among farmers in Qingyang, Northwest China

Climate change is increasing the incidence of extreme weather events which have a significant impact on public health. Cardiovascular diseases (CVDs) are the number one cause of death globally (40%). Apparent temperature (AT) and diurnal temperature range (DTR) have been extensively used to evaluate the effects of temperature on cardiovascular disease (CVD). However, the relevant information is quite limited from analysis and comparison of effects and differing pathogenesis of DTR and AT on CVD especially in less-developed, rural areas of China. This is the first attempt to analyze different effects between AT and DTR on CVD using distributed lag nonlinear modeling (DLNM) in rural area. Data on CVD hospital admission in Qingyang (Northwest China) in 2014-2017 originated from the New Rural Cooperative Medical System (NRCMS) of Gansu Province, and meteorological variables were provided by the Meteorological Science Data Sharing Service. Both AT and DTR had significant nonlinear and delayed impacts on hospital admissions for CVD. DTR had a stronger and more persistent effect on CVD incidence than AT. Females were more affected by high AT and low DTR than were males, while males were more vulnerable to low AT and high DTR. Temperature effects were not significantly different between people above and below 65 years of age. These findings provide local public health authorities with reference concerning sensitive temperature indices for susceptible populations with a view to improve CVD preventive strategies in rural areas.

Temporal trends of the association between temperature variation and hospitalizations for schizophrenia in Hefei, China from 2005 to 2019: a time-varying distribution lag nonlinear model

Along with climate change, unstable weather patterns are becoming more frequent. However, the temporal trend associated with the effect of temperature variation on schizophrenia (SCZ) is not clear. Daily time-series data on SCZ and meteorological factors for 15-year between January 1, 2005 and December 31, 2019 were collected. And we used the Poisson regression model combined with the time-varying distribution lag nonlinear model (DLNM) to explore the temporal trend of the association between three temperature variation indicators (diurnal temperature range, DTR; temperature variability, TV; temperature change between neighboring days, TCN) and SCZ hospitalizations, respectively. Meanwhile, we also explore the temporal trend of the interaction between temperature and temperature variation. Stratified analyses were performed in different gender, age, and season. Across the whole population, we found a decreasing trend in the risk of SCZ hospitalizations associated with high DTR (from 1.721 to 1.029), TCN (from 1.642 to 1.066), and TV (TV0-1, from 1.034 to 0.994; TV0-2, from 1.041 to 0.994, TV0-3, from 1.044 to 0.992, TV0-4, from 1.049 to 0.992, TV0-5, from 1.055 to 0.993, TV0-6, from 1.059 to 0.991, TV0-7, from 1.059 to 0.990), but an increasing trend in low DTR (from 0.589 to 0.752). Subgroup analysis results further revealed different susceptible groups. Besides, the interactive effect suggests that temperature variation may cause greater harm under low-temperature conditions. There was a synergy between TCN and temperature on the addition and multiplication scales, which were 1.068 (1.007, 1.133) and 0.067 (0.009, 0.122), respectively. Our findings highlight public health interventions to mitigate temperature variation effects needed to focus not only on high temperature variations but also moderately low temperature variations. Future hospitalizations for SCZ associated with temperature variation may be more severely affected by temperature variability from low temperature environments. The temporal trend is associated with the effect of temperature variation on schizophrenia (SCZ).

Effects of diurnal temperature range on cardiovascular disease hospital admissions in farmers in China's Western suburbs

Cardiovascular disease (CVD), reported to relate with climate change, is the leading cause of global mortality and morbidity. Since the relevant information is quite limited from suburbs and countryside in developing and underdeveloped countries, there are no studies that focused on morbidity through diurnal temperature range (DTR) for these regions. This is the first study to evaluate the short-term effect of DTR on CVD hospital admission in suburban farmers, as well as to identify vulnerable subpopulations. Daily time series data of CVD hospital admissions on suburban farmers of Qingyang, China, and meteorological data from 2011 to 2015 were collected, and a distributed lag non-linear model (DLNM) combined with a quasi-Poisson generalized additive regression model (GAM) was used to examine the exposure-response relationship and delayed effect between DTR and CVD hospital admissions. Stratified analyses by age and gender were performed and extreme DTR effects were examined. Non-linear relation between DTR and CVD hospital admissions was observed, and whether DTR lower or higher than the reference (13 °C, 50^th percentile) had adverse effect while lower DTR have slightly higher impact. Also, both extreme low and extreme high DTR had adverse effect. Besides, adults (age < 65) and males were more vulnerable to the effects of DTR compared with the old (age ≥ 65) and females, respectively. This study provides evidence that not only high DTR but also low DTR had adverse effects on CVD which should be paid attention to. Adults and males were more vulnerable among suburban farmers. The results are inconsistent with the studies from urban and indicate differences between urban and suburban residents. Multiple factors such as occupations, risk awareness, and lifestyles could have a significant influence on CVD morbidity, and further study is needed to explore more evidence.

Effect of short-term ambient PM2.5 exposure on fasting blood glucose levels: A longitudinal study among 47,471 people in eastern China

As a common health indicator in physical examinations, fasting blood glucose (FBG) level measurements are widely applied as a diagnostic method for diabetes mellitus. Uncertain conclusions remained regarding the relationship between PM_2.5 exposure and FBG levels. We enrolled 47,471 subjects who participated in annual physical examinations between 2017 and 2019. We collected their general characteristics and FBG levels, and environmental factors simultaneously. We applied the generalized additive model to evaluate the impact of short-term outdoor PM_2.5 exposure on FBG levels. Among the entire population, the single-pollutant models showed that a 10 μg/m³ increase in PM_2.5 significantly contributed to 0.0030, 0.0233, and 0.0325 mmol/L increases in FBG at lag 0-7 days, lag 0-21 days, and lag 0-28 days, respectively. Accordingly, in multipollutant models, when PM_2.5 increased by 10 μg/m³, there was an elevation of 0.0361, 0.0315, 0.0357, and 0.0387 mmol/L in FBG for 8-day, 15-day, 22-day, and 29-day moving averages, respectively. Similarly, we observed a significant positive association between them in the normal population. Moreover, the effects could be modified by age in both the entire and normal populations. Decreasing the ambient PM_2.5 concentrations can alleviate the elevation of FBG, which may significantly impact the burden of diabetes mellitus.

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.

Diurnal Temperature Ranges in Relation to Lower Limb Amputation Rate of Diabetic Foot in South Korea: A Population Based Nationwide Study

The evidence for the association between diurnal temperature range (DTR) and diabetic foot amputations is limited. We aimed to investigate the region-specific association between DTR and the amputation rate of diabetic foot in Korean national-wide data. Daily data on DTR and the rate of diabetic foot amputations from 16 provincial capital cities in Korea were obtained (2011-2018). In this study, the latitude ranged from 33°11' N to 38°61' N, and we classified each region according to latitude. Region 1, which was located at a relatively high latitude, included Seoul, Incheon, Gyeonggi-do, and Gangwon-do. Region 2, which was located at a relatively low latitude, included Busan, Ulsan, Gyeonsannam-do, Gwangju, Jeollanam-do, Jeollabuk-do, and Jeju-do. The region-specific DTR effects on the amputation rate were estimated based on a quasi-Poisson generalized linear model, combined with a distributed lag non-linear model based on the self-controlled case series design. The DTR impacts were generally limited to a period of nine days, while significant effects during lag days 7-14 were only found in the cities of Seoul, Incheon, and Gyeonggi-do (10th lag day: RR [95% CI]; Seoul: 1.015, [1.001-1.029]; Incheon: 1.052 [1.006-1.101]; Gyeonggi-do: 1.018 [1.002-1.034]). In the subgroup analysis (according to the latitude), an increase of 1 °C in DTR was associated with the risk of diabetic foot in relatively high latitude regions. DTR has considerable effects on the risk of diabetic foot amputation in various provinces in Korea, and it was particularly affected by latitude. The results can inform the decisions on developing programs to protect vulnerable subpopulations from adverse impacts.

Short-Term Effect of Temperature Change on Non-Accidental Mortality in Shenzhen, China

Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02065-8.

Determining the effects of socioeconomic and environmental determinants on chronic obstructive pulmonary disease (COPD) mortality using geographically and temporally weighted regression model across Xi'an during 2014-2016

Numerous methods have been implemented to evaluate the relationship between environmental factors and respiratory mortality. However, the previous epidemiological studies seldom considered the spatial and temporal variation of the independent variables. The present study aims to detect the relations between respiratory mortality and related affecting factors across Xi'an during 2014-2016 based on a novel geographically and temporally weighted regression model (GTWR). Meanwhile, the ordinary least square (OLS) and the geographically weighted regression (GWR) models were developed for cross-comparison. Additionally, the spatial autocorrelation and Hot Spot analysis methods were conducted to detect the spatiotemporal dynamic of respiratory mortality. Some important outcomes were obtained. Socioeconomic and environmental determinants represented significant effects on respiratory diseases. The respiratory mortality exhibited an obvious spatial correlation feature, and the respiratory diseases tend to occur in winter and rural areas of the study area. The GTWR model outperformed OLS and GWR for determining the relations between respiratory mortality and socioeconomic as well as environmental determinants. The influence degree of anthropic factors on COPD mortality was higher than natural factors, and the effects of independent variables on COPD varied timely and locally. The results can supply a scientific basis for respiratory disease controlling and health facilities planning.

Short-term effect of ambient temperature change on the risk of tuberculosis admissions: Assessments of two exposure metrics

BACKGROUND

Although the effects of seasonal variations and ambient temperature on the incidence of tuberculosis (TB) have been well documented, it is still unknown whether ambient temperature change is an independent risk factor for TB. The aim of this study was to assess the association between ambient temperature change and the risk of TB admissions.

METHOD

A distributed lag non-linear model (DLNM) combined with Poisson generalized linear regression model was performed to assess the association between ambient temperature change and the risk of TB admissions from 2014 to 2018 in Hefei, China. Two temperature change metrics including temperature change between neighboring days (TCN) and diurnal temperature range (DTR) were used to assess the effects of temperature change exposure. Subgroup analyses were performed by gender, age and season. Besides, the attributable risk was calculated to evaluated the public health significance.

RESULTS

The overall exposure-response curves suggested that there were statistically significant associations between two temperature change metrics and the risk of TB admissions. The maximum lag-specific relative risk (RR) of TB admissions was 1.088 (95%CI: 1.012-1.171, lag 4 day) for exposing to large temperature drop (TCN= -4 °C) in winter. Besides, the overall cumulative risk of TB admissions increased continuously and peaked at a lag of 7 days (RR=1.350, 95%CI: 1.120-1.628). Subgroup analysis suggested that exposure to large temperature drop had an adverse effect on TB admissions among males, females and adults. Similarly, large level of DTR exposure (DTR=15 °C) in spring also increased the risk of TB admissions on lag 0 day (RR=1.039, 95%CI: 1.016-1.063), and the cumulative RRs peaked at a lag of 1 days (RR=1.029, 95%CI: 1.012-1.047). We also found that females and elderly people were more vulnerable to the large level of DTR exposure. Additionally, the assessment of attributable risk suggested that taking target measures for the upcoming large temperature drop (b-AF = 4.17%, 95% eCI: 1.24%, 7.22%, b-AN = 1195) may achieve great public health benefits for TB prevention.

CONCLUSION

This study suggests that ambient temperature change is associated with the risk of TB admissions. Besides, TCN may be a better predictor for the TB prevention and public health.