Design a protocol to investigate the effects of climate change in vivo

Nasiri, Rasul; Zarandi, Saeed Motesaddi; Bayat, Mohammad; Amini, Abdollah

doi:10.1016/j.envres.2022.113482

Cited by 4 publications

(3 citation statements)

References 91 publications

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“…However, our current work still has some limitations: (1) The study utilized retrospective observational data, which limits the ability to investigate the direct impact of air pollution on influenza, as well as the ability to obtain specific exposure information from the population regarding air pollution, such as exposure duration. (2) In order to have a more comprehensive understanding of the mechanisms underlying the influenza outbreak in Fuzhou, it is also necessary to consider meteorological factors such as temperature, humidity, and diurnal variations, as well as the economic development level of the region 36 . (3) The current STWR model cannot support multiple scales, which will reduce the reliability of the analysis to a certain extent.…”

Section: Discussionmentioning

confidence: 99%

Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model

Chen,

Zheng,

et al. 2024

Sci Rep

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Air pollution has become a significant concern for human health, and its impact on influenza, has been increasingly recognized. This study aims to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza and to confirm a better method for infectious disease surveillance. Spearman correlation coefficient was used to evaluate the correlation between air pollution and the influenza case counts. VIF was used to test for collinearity among selected air pollutants. OLS regression, GWR, and STWR models were fitted to explore the potential spatiotemporal relationship between air pollution and influenza. The R2, the RSS and the AICc were used to evaluate and compare the models. In addition, the DTW and K-medoids algorithms were applied to cluster the county-level time-series coefficients. Compared with the OLS regression and GWR models, STWR model exhibits superior fit especially when the influenza outbreak changes rapidly and is able to more accurately capture the changes in different regions and time periods. We discovered that identical air pollutant factors may yield contrasting impacts on influenza within the same period in different areas of Fuzhou. NO2 and PM10 showed opposite impacts on influenza in the eastern and western areas of Fuzhou during all periods. Additionally, our investigation revealed that the relationship between air pollutant factors and influenza may exhibit temporal variations in certain regions. From 2013 to 2019, the influence coefficient of O3 on influenza epidemic intensity changed from negative to positive in the western region and from positive to negative in the eastern region. STWR model could be a useful method to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza in geospatial processes. The research findings emphasize the importance of considering spatiotemporal heterogeneity when studying the relationship between air pollution and influenza.

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Section: Discussionmentioning

confidence: 99%

Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model

Chen,

Zheng,

et al. 2024

Sci Rep

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“…Shifts in global food systems (with increasing exposure to high-energy processed food and drinks) and low physical activity have resulted in substantial rises in the obesity rate ( 101 ). Some scholars have observed that the “trend for shorter sleep duration has developed over the same time period as the dramatic increase in the prevalence of obesity” ( 102 ).…”

Section: Compounding and Cascading Effects Of Global And Planetary Sl...mentioning

confidence: 99%

“…Some scholars have observed that the “trend for shorter sleep duration has developed over the same time period as the dramatic increase in the prevalence of obesity” ( 102 ). There is a close relationship between the “obesity pandemic” and sleep disturbances, with overweight and obese individuals being at higher risk for sleep issues and individuals with sleep disturbances being at higher risk for developing metabolic impairments, as well ( 101 , 102 ). Overweight and obese subjects can present defective diet-induced heat regulation and thermogenesis ( 103 ), and they may be, as such, more susceptible to deviations in normal temperature values caused by climate change and other planetary emergencies.…”

Section: Compounding and Cascading Effects Of Global And Planetary Sl...mentioning

confidence: 99%

Planetary sleep medicine: Studying sleep at the individual, population, and planetary level

Bragazzi

Garbarino

Puce

et al. 2022

Front. Public Health

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Circadian rhythms are a series of endogenous autonomous oscillators that are generated by the molecular circadian clock which coordinates and synchronizes internal time with the external environment in a 24-h daily cycle (that can also be shorter or longer than 24 h). Besides daily rhythms, there exist as well other biological rhythms that have different time scales, including seasonal and annual rhythms. Circadian and other biological rhythms deeply permeate human life, at any level, spanning from the molecular, subcellular, cellular, tissue, and organismal level to environmental exposures, and behavioral lifestyles. Humans are immersed in what has been called the “circadian landscape,“ with circadian rhythms being highly pervasive and ubiquitous, and affecting every ecosystem on the planet, from plants to insects, fishes, birds, mammals, and other animals. Anthropogenic behaviors have been producing a cascading and compounding series of effects, including detrimental impacts on human health. However, the effects of climate change on sleep have been relatively overlooked. In the present narrative review paper, we wanted to offer a way to re-read/re-think sleep medicine from a planetary health perspective. Climate change, through a complex series of either direct or indirect mechanisms, including (i) pollution- and poor air quality-induced oxygen saturation variability/hypoxia, (ii) changes in light conditions and increases in the nighttime, (iii) fluctuating temperatures, warmer values, and heat due to extreme weather, and (iv) psychological distress imposed by disasters (like floods, wildfires, droughts, hurricanes, and infectious outbreaks by emerging and reemerging pathogens) may contribute to inducing mismatches between internal time and external environment, and disrupting sleep, causing poor sleep quantity and quality and sleep disorders, such as insomnia, and sleep-related breathing issues, among others. Climate change will generate relevant costs and impact more vulnerable populations in underserved areas, thus widening already existing global geographic, age-, sex-, and gender-related inequalities.

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Machine learning insights into PM2.5 changes during COVID-19 lockdown: LSTM and RF analysis in Mashhad

Moezzi,

Mohammadi,

Mohammadi

et al. 2024

Environ Monit Assess

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Design a protocol to investigate the effects of climate change in vivo

Cited by 4 publications

References 91 publications

Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model

Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model

Planetary sleep medicine: Studying sleep at the individual, population, and planetary level

Machine learning insights into PM2.5 changes during COVID-19 lockdown: LSTM and RF analysis in Mashhad

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