What mathematical model should be used to study the relationship between stroke incidence and temper

According to epidemiological investigations, the incidence of stroke varies from season to season. The incidence of stroke begins to decline in the cold winter months, warms up in the spring, and the incidence of stroke begins to decline, with the lowest incidence in the summer and rising again in the fall.

Stroke is also prone to occur in autumn and early spring. Because this season is most susceptible to cold snaps, the temperature plummets, and the difference between the maximum and minimum temperatures of the day is too great. For those who have just experienced a hot summer or are just feeling the warmth of spring, the sudden onset of climate change can be devastating for the elderly and those at high risk of stroke.

Many doctors have experienced that the temperature plummets, and the streets and shopping malls will look deserted, but the hospital is the opposite, when the number of patients in the emergency room has increased significantly, and the number of patients with cerebral hemorrhage and cerebral thrombosis has increased significantly compared to usual.

Why does climate change affect the occurrence of stroke? In the cold environment, the peripheral blood vessels constrict, the peripheral resistance increases, the blood pressure increases, and the cold can also increase the fibrin in the snow, increase the blood viscosity, and easily make thrombosis. Especially during sleep, blood flow is slow, and cerebral thrombosis is more likely to occur if the room temperature is low.

When the temperature changes suddenly, these physiological reactions are more violent, and the blood pressure fluctuates significantly, which is easy to cause stroke in some elderly people and people with risk factors for stroke.

In addition to temperature changes, stroke is also related to air pressure and relative humidity. In winter, high air pressure, low humidity, and low temperature are often associated with cerebral hemorrhage; In summer, low air pressure, high humidity, and high temperature make cerebral thrombosis prone to occur. Agree.

[Result] The average error rate of the BP artificial neural network model was 17 12. The nonlinear correlation coefficient is 0 76. The average error rate of the multiple linear regression model was 10:74; The nonlinear correlation coefficient is 0 88.

The multiple linear regression model showed that the important meteorological factors affecting the incidence of dysentery were mean air pressure, mean minimum temperature, mean maximum temperature and mean relative humidity. The results of the BP artificial neural network model are basically consistent with the results, and the average pressure, mean relative humidity, average maximum temperature, and average temperature are the top four meteorological factors in the order of importance. [Conclusion] The incidence of dysentery in a certain area of China can be carried out by using a multiple linear regression model with meteorological factors as the independent variable, and the main meteorological functions affecting the incidence of dysentery are mean air pressure, mean minimum temperature, mean maximum temperature and mean relative humidity.

Objective: The effect of meteorological factors on the incidence of acute stroke.

Methods: By collecting the data of acute stroke hospitalization cases in the Department of Neurology of the First Hospital of Shanxi Medical University in Taiyuan City from 1996 to 2005, the characteristics of stroke onset time of inpatients with cerebral infarction and cerebral hemorrhage were analyzed (the number of cases of subarachnoid hemorrhage was too small to be analyzed), the monthly and bimonthly incidence patterns were identified, the differences of incidence in different seasons were observed, and the concentrated trend of annual incidence and the concentration trend of total incidence in ten years were analyzed by circular distribution. Univariate correlation and multivariate stepwise regression were used to analyze the effects of 8 major monthly meteorological indicators, namely, monthly mean temperature ta( ), monthly average maximum temperature hh( ), minimum temperature t1 ( ), monthly mean pressure PA (HPA), monthly average maximum pressure pH (HPA), minimum pressure PL (HPA), monthly average relative humidity HA (%), minimum humidity hl (%) and maximum humidity of 100%, usually not recorded) on the incidence of cerebral hemorrhage and cerebral infarction in the same period in the past 5 years (01-05).

Results: 1) The incidence of intracerebral hemorrhage was obviously seasonal, with a high incidence in winter and a low incidence in autumn. The incidence of cerebral infarction is relatively high in winter, but it is not as obvious as that of cerebral hemorrhage.

2) There was a concentrated trend in the incidence of cerebral hemorrhage only in 01, the average angle was December 12, and the total incidence in 10 years also had a concentrated trend, and the average angle was November 21 (p, cerebral infarction had a concentrated trend in three out of 10 years, which were November and October and November, respectively, (p, the average angle of the total of 10 years was not statistically significant (p.

3) The results of univariate correlation analysis showed that cerebral infarction was positively correlated with the monthly average maximum temperature and monthly average maximum pressure (r=, p r=, p, and negatively correlated with the monthly average relative humidity (r=, p; Intracerebral hemorrhage was positively correlated with monthly mean air pressure and monthly mean maximum air pressure (r=, p r=, p, negatively correlated with monthly mean temperature, monthly average maximum temperature, and monthly average minimum temperature (r=, p r=, p r=, p r=, p .

4) The results of multivariate stepwise regression showed that cerebral infarction was related to the monthly average maximum pressure and monthly average relative humidity, while intracerebral hemorrhage was related to the monthly average air pressure, monthly average maximum pressure and monthly average maximum temperature.

Conclusion: The incidence of intracerebral hemorrhage is seasonal, with a common incidence in winter, and the annual incidence is concentrated in four months of winter (November to February of the following year). The seasonality of cerebral infarction is not obvious, and the incidence trend tends to be from December to January. The incidence of intracerebral hemorrhage is related to high air pressure and cold air mass activity, while the incidence of cerebral infarction is related to high temperature, high pressure and low temperature conditions.

A variety of meteorological factors synergize or antagonize each other to jointly affect the incidence of cerebral infarction and cerebral hemorrhage, and the abnormal fluctuation of meteorological factors and the imbalance of temperature and pressure configuration are easy to induce the occurrence of acute stroke.