Modeling the impacts of ambient temperatures on cardiovascular mortality in Yinchuan: evidence from a northwestern city of China

Zhang, Huiling; Wang, Qingan; Zhang, Yajuan; Yang, Yi; Zhao, Yi; Sang, Jianren; Yin-e, Zhang; Xie, Fan; Li, Shanshan; Zhang, Yuhong; Lee, Hyewon

doi:10.1007/s11356-017-0920-3

Cited by 10 publications

(5 citation statements)

References 26 publications

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“…High temperature increases the CVDs mortality by affecting the cardiopulmonary functions, including blood pressure, blood viscosity, serum cholesterol, and heart rate ( 25 – 26 ). First, elevated air temperatures increase the heart rate and myocardial oxygen consumption in the human body, meanwhile blood travels faster from organs to the skin surface, creating higher pressure on the heart and lungs ( 27 ), further increasing CVD incidence.…”

Section: Resultsmentioning

confidence: 99%

Spatio-Temporal Mechanism Underlying the Effect of Urban Heat Island on Cardiovascular Diseases

Huang¹,

Deng²,

Yang³

et al. 2020

ijph

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Background: We explored the spatio-temporal characteristics of urban heat island (UHI) effect on cardiovascular diseases (CVDs). Methods: The land surface temperatures (LST) were retrieved from four Landsat remote-sensing images’ data, the temperature data from 95 meteorological stations, and analysis data on CVDs mortality. Based on these data, landscape pattern indexes were used to analyze the pattern-process-function and the mechanism. Results: During 1984–2017, the effects of UHI on CVDs increased, thereby increased the mortality by 28.8%. The affected areas gradually expand from the central area of the city and undergo three evolution stages; the highly affected areas are mainly distributed in central and southern regions, and patches increase in number. The areas and ratio of high-level patches also show an upward tendency, increasing dominance in the overall landscape. Patches of the overall landscape become more complicated in shape, whereas those of high-level ones become less complicated. Concentration degree of the overall landscape decreases gradually with the types of landscapes patches increasing, reaching a rather even space distribution. Conclusion: Increased temperatures exacerbated by UHI lead to increased CVD mortality. As cities expand, the effects of UHI on CVDs increase in terms of both intensity and areas, with the overall landscape in uneven distribution, high-level affected areas in point distribution, and low-level ones in large-area concentration.

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Section: Resultsmentioning

confidence: 99%

Spatio-Temporal Mechanism Underlying the Effect of Urban Heat Island on Cardiovascular Diseases

Huang¹,

Deng²,

Yang³

et al. 2020

ijph

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“…Many studies have illustrated some evidences for the association between particulate air pollution and human illness (especially cardiovascular and respiratory diseases) [28,41,42,43]. In China, the main research attention focused on the impact of PM 2.5 on the respiratory diseases for the developed provinces in southern China.…”

Section: Resultsmentioning

confidence: 99%

“…Ningxia Hui Ethnic Autonomous Region is located in the northwest inland plateau of China, with a typical continental semi-humid semi-arid climate, where have approximately 650 million populations [28]. Existing surveillance result has shown that influenza was one kind of major category C infectious diseases (accounted for about 2.85% of infectious diseases) in Ningxia, Northwest China [29].…”

Section: Introductionmentioning

confidence: 99%

Identifying the Dynamic Pattern and Influencing Factors of Influenza in Northwest China from 2013 to 2020, Based on Dynamic Regression Model and Wavelet Analysis

Wang

et al. 2020

Preprint

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Background: Influenza remains a serious global public health problem and a substantial economic burden. The dynamic pattern of influenza differs considerably among geographic and climatological areas, however, the factors underlying these differences are still uncertain. The aim of this paper is to characterize the dynamic pattern of influenza and its potential influencing factors in Northwest China. Methods: Influenza cases in Ningxia China from Nov. 2013 to Jun. 2020 were served as influenza proxy. Firstly, the baseline seasonal ARIMA model of influenza cases and seasonal pattern were analyzed. Then, the dynamic regression model was used to identifying the potential influencing factors of influenza. In addition, the wavelet analysis was further used to explore the coherence between influenza cases and these significant influencing factors.Results: The high risk periods of influenza in Ningxia presented a winter cycle outbreaks pattern and the fastigium came in January. The seasonal ARIMA(0,0,1)(1,1,0)12 was the optimal baseline forecast model. The dynamic regression models and wavelet analysis indicated that PM2.5 and public awareness are significantly positively associated with influenza, as well as minimum temperature is negatively associated. Conclusion: Meteorological (minimum temperature), pollution (PM2.5) and social (public awareness) factors may significantly associated with influenza in Northwest China. Decreasing PM2.5 concentration or increasing the public awareness prior to the fastigium of influenza may be the serviceable methods to reduce the disease risk of influenza, which have an important implication for policy-makers to choose an optimal time for influenza prevention campaign.

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“…Specifically, the first two site regions, Yinchuan and Otogqianqi are situated in the northwest region of China, while the other two, Tongliao and Zhangwu are located in the northeast (Figure S1). The long distances between the northwestern sampling sites and the northeastern ones (1,300 to 1,500 kilometers) and the remarkable difference in altitudes (northwestern sites: 1,100 to 1,300 meters; northeastern sites: 85 to 180 meters) lead to the significantly differentiated climatic characteristics for these two sampling site groups (northwestern sites: semi-humid and semiarid continental climate; northeastern sites: semi-arid continental monsoon climate) (Li et al, 2016;Li et al, 2018;Zhang et al, 2018;Guo, 2022) (Supplementary Table 1). Then, leaf samples of yellowhorn were collected in July 2019 from the above four sites, which were subjected to genomic DNA extraction in laboratory and subsequent 16S rRNA gene amplicon sequencing analysis.…”

Section: Composition Of the Phyllosphere Bacterial Community Of Yello...mentioning

confidence: 99%

Differentiated responses of the phyllosphere bacterial community of the yellowhorn tree to precipitation and temperature regimes across Northern China

Wang,

Hu,

Chang

et al. 2023

Front. Plant Sci.

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IntroductionAs an ephemeral and oligotrophic environment, the phyllosphere harbors many highly diverse microorganisms. Importantly, it is known that their colonization of plant leaf surfaces is considerably influenced by a few abiotic factors related to climatic conditions. Yet how the dynamics of phyllosphere bacterial community assembly are shaped by detailed climatological elements, such as various bioclimatic variables, remains poorly understood.MethodsUsing high-throughput 16S rRNA gene amplicon sequencing technology, we analyzed the bacterial communities inhabiting the leaf surfaces of an oilseed tree, yellowhorn (Xanthoceras sorbifolium), grown at four sites (Yinchuan, Otogqianqi, Tongliao, and Zhangwu) whose climatic status differs in northern China.Results and DiscussionWe found that the yellowhorn phyllosphere’s bacterial community was generally dominated by four phyla: Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes. Nevertheless, bacterial community composition differed significantly among the four sampled site regions, indicating the possible impact of climatological factors upon the phyllosphere microbiome. Interestingly, we also noted that the α-diversities of phyllosphere microbiota showed strong positive or negative correlation with 13 bioclimatic factors (including 7 precipitation factors and 6 temperature factors). Furthermore, the relative abundances of 55 amplicon sequence variants (ASVs), including three ASVs representing two keystone taxa (the genera Curtobacterium and Streptomyces), exhibited significant yet contrary responses to the precipitation and temperature climatic variables. That pattern was consistent with all ASVs’ trends of possessing opposite correlations to those two parameter classes. In addition, the total number of links and nodes, which conveys community network complexity, increased with rising values of most temperature variables. Besides that, remarkably positive relevance was found between average clustering coefficient and most precipitation variables. Altogether, these results suggest the yellowhorn phyllosphere bacterial community is capable of responding to variation in rainfall and temperature regimes in distinctive ways.

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Modeling the impacts of ambient temperatures on cardiovascular mortality in Yinchuan: evidence from a northwestern city of China

Cited by 10 publications

References 26 publications

Spatio-Temporal Mechanism Underlying the Effect of Urban Heat Island on Cardiovascular Diseases

Spatio-Temporal Mechanism Underlying the Effect of Urban Heat Island on Cardiovascular Diseases

Identifying the Dynamic Pattern and Influencing Factors of Influenza in Northwest China from 2013 to 2020, Based on Dynamic Regression Model and Wavelet Analysis

Differentiated responses of the phyllosphere bacterial community of the yellowhorn tree to precipitation and temperature regimes across Northern China

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