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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.

Cardiovascular disease (CVD) is a major threat to public health worldwide. The relationship between CVD and temperature has been widely reported in developed countries and regions. However, there are few studies of severe CVD in poor rural areas of developing countries. Therefore, this study aimed to explore the relationship between CVD and apparent temperature (AT) in a rural area of Linxia Hui Autonomous Prefecture, China. Daily CVD admission data and meteorological data were collected from Linxia between 2014 and 2015. The media of AT was used as the reference temperature to estimate the cumulative relative risk (RR) of CVD admission. The distributed lag non-linear models were used to examine the association between AT and cumulative RR of CVD admission at lag 0-21 days. In Linxia, high AT (20 °C) had a persistent adverse effect on cumulative RR of CVD admissions, and the RR increased with increasing lag days. Cold (- 10 °C) had a protective effect on the first and later lag days (lag 0-14 and lag 0-21). Adults (aged < 65 years) and females were more susceptible to the effects of heat than males and the elderly (aged ≥ 65 years). In Linxia, China, extremely high AT is an important risk factor for CVD hospitalizations in suburban and rural populations., (© 2023. Springer Nature Limited.)

The effect of ambient temperature on relative risk (RR) of cardiovascular disease (CVD) is different in China than in other countries due to the different geographical environment, climate the different inter- and intra-individual characteristics of the population within China. It is therefore important to integrate information to evaluate the impact of temperature on RR of CVD in China. We performed a meta-analysis to evaluate the effect of temperature on RR of CVD. The Web of Science, Google Scholar, and China National Knowledge Infrastructure databases were searched back to 2022 and nine studies were included in the study. The Cochran Q test and I 2 statistics were used to assess heterogeneity, while Egger's test was used to assess publication bias. The pooled estimated size of the relationship between ambient temperature and CVD hospitalization in the random effect model was 1.2044 (95%CI: 1.0610-1.3671) for the cold effect and 1.1982 (95%CI: 1.0166-1.4122) for the heat effect. The Egger's test showed a potential publication bias for the cold effect, whereas there was no apparent publication bias for the heat effect. There is a significant effect of ambient temperature on RR of CVD for both the cold effect and heat effect. The effect of socioeconomic factors should be considered more thoroughly in future studies., (© 2023. The Author(s) under exclusive licence to International Society of Biometeorology.)

Cardiovascular diseases (CVDs) are a leading cause of morbidity and mortality around the world. The physiological or pathological processes of CVDs can be well indicated by timely and accurate diagnosis of relevant biomarkers and function parameters. Nanosensors integrating the advantages of nanomaterials and sensing platforms have shown good potential for rapid diagnosis of CVDs, especially for early prediction. In this review, recent advances in nanosensors for the detection of CVDs are summarized, including electrochemical, optical, pressure, and paper-based nanosensors. Design strategies for different nanosensors and the corresponding sensing nanomaterials, mechanisms, and properties are briefly discussed. This review also offered a preliminary analysis of the obstacles and prospects for using nanosensors to diagnose CVDs., (Copyright © 2022 Elsevier Inc. All rights reserved.)

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., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)