Objective Based on meteorological factors, the prediction of the risk of cardiovascular and cerebrovascular diseases(CVD) and the analysis of its correlation with the incidence rate. Methods The research utilizes six years of data on CVD incidence from Xingyi, from 2017 to 2022, as the subject of study. The incidence risk levels are categorized based on the 25%, 50%, 75%, and 95% quantiles of the cumulative probability of the number of cases. The study is conducted based on the relationship between meteorological factors and the risk of incidence of CVD. Results The incidence of CVD shows a significant correlation with temperature, vapor pressure, atmospheric pressure, and relative humidity. It is negatively correlated with temperature and vapor pressure, among which the correlation with the daily minimum temperature is the highest at -0.504 (P < 0.05), and positively correlated with atmospheric pressure and relative humidity. Meteorological factors that have a significant correlation with the incidence rate are selected as input factors for the machine prediction model. It was found that the random forest model performs best in predicting the risk of incidence of CVD, with a comprehensive score of 0.851. Analysis of Relative Risk (RR) values found that there is a lagged association between exposure levels to meteorological factors and the incidence of cardiovascular and cerebrovascular diseases. A temperature drop of more than 11°C and an increase in atmospheric pressure of more than 8 hPa can significantly increase the risk of incidence. Conclusion The study revealed significant correlations between the incidence of CVD and meteorological parameters including temperature, water vapor pressure, atmospheric pressure, and relative humidity. Utilizing machine learning models, the research effectively predicted the risk of these diseases, uncovering that extreme weather conditions significantly elevate the risk of incidence. These findings provide a basis for meteorological risk assessment in public health interventions, emphasizing the importance of taking preventative measures in the context of extreme climate changes.

Objective To explore the effects of air pressure, humidity, wind, and sunshine on the incidence of cardiovascular and cerebrovascular diseases (CVD) in Guiyang, and to provide reference for the prevention of CVD. Methods Using CVD incidence data from September 2021 to August 2022 in Guiyang City and meteorological data including average air pressure, average humidity, wind, and sunshine during the same period, the effects of meteorological factors on CVD incidence were explored and the importance of each factor was analyzed. Results When air pressure was below 868 hPa, above 887 hPa, or between 877 and 883 hPa, and when air pressure dropped less than 5.3 hPa within 24 hours, there was a higher risk of CVD. When the humidity was above 81%, the wind speed was small (<1.2 m/s) or high (>4m/s), and there was less sunlight (less than 3 hours), the risk of CVD was higher. Low humidity (<60%) was not conducive to the onset of CVD. There were highest risks at lag 5~10 days and 4-25 days for high pressure and low sunlight, respectively. When the relative humidity was saturated, there was an immediate effect. When the wind speed was low and high, the immediate effect and hysteresis effects were significant. Among the above meteorological factors, the impact of 24-hour variation of pressure and high or low atmospheric pressure on the incidence of CVD was the most significant, while the impact of sunlight and humidity was the weakest. The impact of diurnal variations in wind and atmospheric pressure was not clear. Conclusion The impact of air pressure on the incidence of CVD does not exhibit a simple linear relationship. The risk of CVD is high in high humidity, low light, and moderate or strong winds. It is necessary to fully consider changes in meteorological factors for CVD prevention and control.

Objective To assess the effects of temperature and rainfall on the incidence of cardiovascular and cerebrovascular diseases (CVD) in Guiyang. Methods Using daily CVD incidence data and temperature and rainfall data in Guiyang City from September 2021 to August 2022, a distributed lag non-linear model was used to explore the nonlinear relationship between meteorological and environmental factors and CVD incidence. Results The risk of CVD was higher under cold (average, minimum, and maximum temperatures <2.1 ℃, 1.6 ℃, and 4.2 ℃, respectively) and hot (maximum temperature>32.5 ℃) effects, and the cumulative lag effect reached its maximum at 10 and 17 days, respectively. The risk of CVD increased sharply when there was a small diurnal temperature (<6.9 ℃), sudden drop in temperature (over 6.1 ℃), and heating (over 2.4 ℃ in 24 hours). The incidence risk of CVD was high when the daily rainfall exceeded 21.5 mm and the continuous rainy days exceed 5.7 days. The risk in rainstorm was 0.81 higher than that in heavy rain. Continuous absence of rain helped to prevent CVD patients from developing symptoms. Conclusion Meteorological environments such as hot and cold weather, dramatic change in temperature, significant rainfall and continuous rainfall have an impact on the incidence of CVD. It is necessary to consider the changes of the meteorological environment during the prevention and control of CVD.