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.

Did COVID-19 enlarge spatial disparities in population dynamics? A comparative, multivariate approach for Italy

A short-term issue that has been occasionally investigated in the current literature is if (and, eventually, how) population dynamics (directly or indirectly) driven by COVID-19 pandemic have contributed to enlarge regional divides in specific demographic processes and dimensions. To verify this assumption, our study run an exploratory multivariate analysis of ten indicators representative of different demographic phenomena (fertility, mortality, nuptiality, internal and international migration) and the related population outcomes (natural balance, migration balance, total growth). We developed a descriptive analysis of the statistical distribution of the ten demographic indicators using eight metrics that assess formation (and consolidation) of spatial divides, controlling for shifts over time in both central tendency, dispersion, and distributional shape regimes. All indicators were made available over 20 years (2002-2021) at a relatively detailed spatial scale (107 NUTS-3 provinces) in Italy. COVID-19 pandemic exerted an impact on Italian population because of intrinsic (e.g. a particularly older population age structure compared with other advanced economies) and extrinsic (e.g. the early start of the pandemic spread compared with the neighboring European countries) factors. For such reasons, Italy may represent a sort of 'worst' demographic scenario for other countries affected by COVID-19 and the results of this empirical study can be informative when delineating policy measures (with both economic and social impact) able to mitigate the effect of pandemics on demographic balance and improve the adaptation capacity of local societies to future pandemic's crises.

Estimating long-term and short-term impact of COVID-19 activity restriction on regional highway traffic demand: A case study in Zhejiang Province, China

Since the outbreak of COVID-19 in China in late 2019, government administrators have implemented traffic restriction policies to prevent the spread of COVID-19. However, highway traffic volumes obtained from ETC data in some provinces did not return to the levels of previous years after the end of the traffic restriction policy, suggesting that traffic restriction policy may have long-term effects. This paper proposed a method that analyzes traffic restriction policies' long-term and short-term impact on highway traffic volume under COVID-19. This method first analyzes the long-term and short-term impacts of traffic restriction policies on the highway traffic volume using the Prophet model combined with the concept of traffic volume loss. It further investigates the relationship between COVID-19 cases and the long-term and short-term impacts of the traffic restriction policy using Granger causality and the impulse response function of the Bayesian vector autoregressive (BVAR) model. The results showed that during the COVID-19 pandemic, highway traffic in Zhejiang Province decreased by about 95.5%, and the short-term impact of COVID-19 cases was most pronounced on the second day. However, the long-term effects were relatively small when the traffic restriction policy ended and was verified by data from other provinces. These results will provide decision support for traffic management and provide recommendations for future traffic impact assessments in the event of similar epidemics.

Pristine and sulfidized ZnO nanoparticles alter microbial community structure and nitrogen cycling in freshwater lakes

Zinc oxide nanoparticles (ZnO NPs) and its sulfidized form (ZnS NPs) are increasingly entering into freshwater systems through multiple pathways. However, their impacts on the composition and function of sedimentary microbial communities are still largely unknown. Here, two kinds of lake-derived microcosms were constructed and incubated with ZnO NPs, or ZnS NPs to investigate the short-term (7 days) and long-term (50 days) impacts on sedimentary microbial communities and nitrogen cycling. After 7 days, both ZnO NPs and ZnS NPs dosed microbial communities experienced distinct alterations as compared to the undosed controls. By day 50, the structural shifts of microbial communities caused by ZnO NPs were significantly enlarged, while the microbial shifts induced by ZnS NPs were largely resolved. Additionally, ZnO NPs and ZnS NPs could significantly alter nitrogen species and nitrogen cycling genes in sediments, revealing their non-negligible impacts on nitrogen cycling processes. Furthermore, our data clearly indicated that the impacts of ZnO NPs and ZnS NPs on nitrogen cycling differed distinctly in different lake-derived microcosms, and the impacts were significantly correlated with microbial community structure. Overall, this research suggests that the entrance of pristine or sulfidized ZnO NPs into freshwater systems may significantly impact the sedimentary microbial community structure and nitrogen cycling.