Impact of temperature changes between neighboring days on COPD in a city in Northeast China

Comparison for the effects of different components of temperature variability on mortality: A multi-country time-series study

BACKGROUND

Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects.

OBJECTIVES

We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality.

METHODS

We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates.

RESULTS

Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0-7 (0.9 °C). An IQR increase in inter-day TV0-7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0-7 and inter-day TV0-7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type.

CONCLUSIONS

Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.

Hospital admission tendencies caused by day-to-day temperature changes during summer: a case study for the city of Novi Sad (Serbia)

Increased temperature risk in cities threatens the health and well-being of urban population and is fueled by climate change and intensive urbanization. Consequently, further steps must be taken for assessing temperature conditions in cities and their association with public health, in order to improve public health prevention at local or regional level. This study contributes to solving the problems by analyzing the connection between extreme temperatures and the tendencies of all-cause hospital admissions. The analyses used (a) 1-h air temperature data, and (b) daily data of all-cause hospital admissions. The datasets include the summer period (June, July, August) for the years 2016 and 2017. We tested the effects of two temperature indices, day-to-day change in maximum temperature - T_max,c and daily temperature range - T_r, with all-cause hospital admission subgroups, such as all-cause cases - H_a, hospital admissions in the population below 65 - H_a<65, and hospital admissions in the population aged 65 and over - H_a≥65. The results show the highest values of H_a when T_max,c is between 6 and 10 °C. Therefore, more intensive hospital admissions can be expected when T_max increases from day-to-day (positive values of T_max,c), and it is more visible for H_a and H_a<65 (1 °C = 1% increase in hospital admissions). Also, T_r values between 10 °C and 14 °C cause an increase in the number of hospital admissions, and it is more noticeable for H_a≥65.

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

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

Short-term effect of ambient temperature and ambient temperature changes on the risk of warts outpatient visits in Hefei, China: a retrospective time-series study

Concerns are growing about the adverse health effects of ambient temperature and ambient temperature changes. However, the association between ambient temperature and ambient temperature changes on the risk of warts outpatient visits is poorly understood. Our study used the distributed lag non-linear model (DLNM) aimed to evaluate the association between ambient temperature, ambient temperature changes (including temperature change between neighboring days (TCN) and diurnal temperature range (DTR)), and warts outpatient visits. We also performed subgroup analyses in order to find susceptible populations by gender and age groups. The maximum relative risk (RR) of low ambient temperature (0 °C) for warts outpatient visits was 1.117 (95% CI: 1.041-1.198, lag 04 days), and the maximum RR of high ambient temperature (32 °C) for warts outpatient visits was 1.318 (95% CI: 1.083-1.605, lag 07 days). The large temperature drop (TCN =  - 3 °C) decreased the risk of warts visits, with the lowest RR value at the cumulative exposure of lag 7 days (RR = 0.888, 95% CI: 0.822-0.959), and the large temperature rise (TCN = 2 °C) increased the risk of warts visits, with the highest RR value at the cumulative exposure of lag 7 days (RR = 1.080, 95% CI: 1.022-1.142). Overall, both low and high ambient temperatures and large temperature rise can increase the risk of warts visits, while large temperature drop is a protective factor for warts visits. However, we did not find any association between DTR and warts visits. Furthermore, subgroup analyses showed that males and the young (0-17 years old) were more sensitive to low and high ambient temperatures, and the elderly (≥ 65 years old) were more susceptible to TCN. The results may provide valuable evidence for reducing the disease burden of warts in the future.

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.

Global disease burden of COPD from 1990 to 2019 and prediction of future disease burden trend in China

OBJECTIVES

This study aimed to assess and predict the disease burden attributable to chronic obstructive pulmonary disease (COPD) in a timely, comprehensive, and reliable manner, thereby mitigating the health hazards of COPD.

STUDY DESIGN AND METHODS

Data on the disease burden owing to COPD from 1990 to 2019 were extracted from the Global Burden of Disease (GBD) Study 2019. Linear regression analysis was used to calculate the estimated annual percentage change (EAPC) in the age-standardized rates. Non-parametric tests were used for subgroup analysis. The Bayesian age-period-cohot (BAPC) model integrated nested Laplace approximations to predict the disease burden over the next 25 years. Sensitivity analysis was performed using the Norpred APC model.

RESULTS

Globally, the COPD-related age-standardized incidence rate decreased from 216.48/100,000 in 1990 to 200.49/100,000 in 2019, with an EAPC of -0.33. But the number of new cases increased from 8,722,966 in 1990 to 16, 214, 828 in 2019. Trends in prevalence, deaths, and disability-adjusted life years (DALYs) were the same as incidence. There were significant differences in disease burden between the genders and all age groups (P < 0.05) in China. The projections suggested that the COPD-related number of new cases and deaths in China would increase by approximately 1.5 times over the next 25 years.

CONCLUSIONS

The number of incidence, prevalence, deaths, and DALYs had all increased in China in the past and would continue to grow over the next 25 years. Therefore, measures should be taken to target risk factors and high-risk groups.

Temperature Change between Neighboring Days Contributes to Years of Life Lost per Death from Respiratory Disease: A Multicounty Analysis in Central China

BACKGROUND

Many epidemiological studies have recently assessed respiratory mortality attributable to ambient temperatures. However, the associations between temperature change between neighboring days and years of life lost are insufficiently studied. Therefore, we assessed the attributable risk of temperature change between neighboring days on life loss due to respiratory disease.

METHODS

We obtained daily mortality and weather data and calculated crude rates of years of life lost for 70 counties in Hunan Province, Central China, from 2013 to 2017. A time-series design with distributed lag nonlinear model and multivariate meta-regression was used to pool the relationships between temperature change between neighboring days and rates of years of life lost. Then, we calculated the temperature change between neighboring days related to average life loss per death from respiratory disease.

RESULTS

The total respiratory disease death was 173,252 during the study period. The association between temperature change and years of life lost rates showed a w-shape. The life loss per death attributable to temperature change between neighboring days was 2.29 (95% CI: 0.46-4.11) years, out of which 1.16 (95% CI: 0.31-2.01) years were attributable to moderately high-temperature change between neighboring days, and 0.99 (95% CI: 0.19-1.79) years were attributable to moderately low-temperature change between neighboring days. The temperature change between neighboring days related to life loss per respiratory disease death for females (2.58 years, 95% CI: 0.22-4.93) and the younger group (2.97 years, 95% CI: -1.51-7.44) was higher than that for males (2.21 years, 95% CI: 0.26-4.16) and the elderly group (1.96 years, 95% CI: 0.85-3.08). An average of 1.79 (95% CI: 0.18-3.41) life loss per respiratory disease death was related to non-optimal ambient temperature.

CONCLUSIONS

The results indicated that more attention should be given to temperature change, and more public health policies should be implemented to protect public health.

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

BACKGROUND

While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported.

OBJECTIVES

To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization.

METHODS

We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities.

RESULTS

A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12-38%) increase in COPD admissions. An IQR increase in IITV_0-1 was associated with 18% (95% CI: 7-27%) increase in COPD admissions. Males and people aged 0-64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality.

CONCLUSIONS

The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.

Effect of diurnal temperature change on cardiovascular risks differed under opposite temperature trends

Temperature change between neighboring days (TCN) is an important trigger for cardiovascular diseases, but the modulated effects by seasonal temperature trends have been barely taken into account. A quantified comparison between impacts of positive TCNs (temperature rise) and negative situations (temperature drop) is also needed. We evaluated the associations of TCNs with emergency room (ER) visits for coronary heart disease (CHD) and cerebral infarction (CI) in Beijing, China, from 2008 to 2012. A year was divided into two segments dominated by opposite temperature trends, quasi-Poisson regression with distributed lag nonlinear models estimating TCN-morbidity relations were employed, separately for each period. High morbidities of CHD and CI both occurred in transitional seasons accompanied by large TCNs. Under warming backgrounds, positive TCNs increased CHD risk in patients younger than 65 years, and old people showed limited sensitivity. In the cooling periods, negative TCNs induced CHD risk in females and the elderly; the highest RR showed on lag 6 d. In particular, a same diurnal temperature decrease (e.g., - 2°C) induced greater RR (RR = 1.113, 95% CIs: 1.033-1.198) on old people during warming periods than cooling counterparts (RR = 1.055, 95% CIs: 1.011-1.100). Moreover, positive TCNs elevated CI risk regardless of background temperatures, and males were particularly vulnerable. Seasonal temperature trends modify TCN-cardiovascular morbidity associations significantly, which may provide new insights into the health impact of unstable weathers.

The relationship between ambient temperature and acute respiratory and cardiovascular diseases in Shenyang, China

The purpose of this study was to analyze the acute effect of ambient temperature on hospitalization due to acute exacerbation of chronic obstructive pulmonary disease (AECOPD), stroke, and myocardial infarction (MI) in Shenyang, China. We used the distributed delayed nonlinear model to evaluate the impact of ambient temperature on respiratory and cardiovascular diseases. The study population was divided into four groups: < 65 group and ≥ 65 age groups, female and male groups. The < 65 age group of AECOPD patients was more likely to be affected by high ambient temperature, while the ≥ 65 age group of AECOPD patients was more sensitive to low ambient temperature. The hospitalization risk of MI admission increased in the ≥ 65 age group at 1-8 days delay under low ambient temperature conditions.

Temporal cross-correlations between air pollutants and outpatient visits for respiratory and circulatory system diseases in Fuzhou, China

BACKGROUND

Previous studies have suggested that there is an association between air pollutants and circulatory and respiratory diseases; however, relatively few have analyzed the association between air pollutants and outpatient visits based on the mortality, hospitalization rates, etc., especially in areas with relatively good air quality. Therefore, we conducted this study to research the association between air pollutants and outpatient visits in Fuzhou, China.

METHODS

We used a generalized linear Poisson model to study the association between air pollution and outpatient visits for respiratory and circulatory diseases from 2016 to 2018 in Fuzhou, China.

RESULTS

In the single pollutant model, nitrogen dioxide (NO2) had a significant effect. For lag day 0 to lag day 5, the effect decreased with every 10 μg/L increase in NO2. The daily maximum 8-h mean ozone (O3-8h) and upper respiratory outpatient visits were positively associated during the cold period [lag2, excess risk (ER) (95% confidence interval (CI)): 1.68% (0.44-2.94%)], while O3-8h and respiratory disease were positively associated during the warm period [lag5, ER (95% CI): 1.10% (0.11-2.10%) and lag4, ER (95% CI): 1.02% (0.032-2.02%)]. Similarly, particulate matter (PM) with an average aerodynamic diameter of less than 10 μm (PM10) and lower respiratory diseases were positively associated during the warm period [lag0, ER (95% CI): 1.68% (0.44-2.94%)]. When the concentration of O3-8h was higher than 100 μg/L, there was a positive effect on circulatory [lag5, ER (95% CI): 2.83% (0.65-5.06%)], respiratory [lag5, ER (95% CI): 2.47% (0.85-4.11%)] and upper respiratory [lag5, ER (95% CI): 3.06% (1.38-4.77%)] outpatient visits. The variation in O3-8h changed slightly when we adjusted for other air pollutants, and after adjusting for O3-8h, the ERs of the other air pollutants changed slightly. After adjusting for PM with an average aerodynamic diameter of less than 2.5 μm (PM2.5), the ERs of the other air pollutants increased, and after adjusting for NO2, the ER of PM decreased.

CONCLUSION

Exposure to ambient NO2, O3, PM2.5 and PM10 was associated with an increase in respiratory and circulatory system-related outpatient visits in Fuzhou, China.