The role of weather conditions and normal level of air pollution in appearance of stroke in the region of Southeast Europe

Health risk assessment for particulate matter: application of AirQ+ model in the northern Caribbean region of Colombia

Air pollution is considered the world's most important environmental and public health risk. The annual exposure for particulate matter (PM) in the northern Caribbean region of Colombia between 2011 and 2019 was determined using PM records from 25 monitoring stations located within the area. The impact of exposure to particulate matter was assessed through the updated Global Burden of Disease health risk functions using the AirQ+ model for mortality attributable to acute lower respiratory disease (in children ≤ 4 years); mortality in adults aged > 18 years old attributable to chronic obstructive pulmonary disease, ischaemic heart disease, lung cancer, and stroke; and all-cause post-neonatal infant mortality. The proportions of the prevalence of bronchitis in children and the incidence of chronic bronchitis in adults attributable to PM exposure were also estimated for the population at risk. Weather Research and Forecasting-California PUFF (WRF-CALPUFF) modeling systems were used to estimate the spatiotemporal trends and calculate mortality relative risk due to prolonged PM_2.5 exposure. Proportions of mortality attributable to long-term exposure to PM_2.5 were estimated to be around 11.6% of ALRI deaths in children ≤ 4 years of age, 16.1% for COPD, and 26.6% for IHD in adults. For LC and stroke, annual proportions attributable to PM exposure were estimated to be 9.1% and 18.9%, respectively. An estimated 738 deaths per year are directly attributed to particulate matter pollution. The highest number of deaths per year is recorded in the adult population over 18 years old with a mean of 401 events. The mean risk in terms of the prevalence of bronchitis attributable to air pollution in children was determined to be 109 per 100,000 inhabitants per year. The maximum RR values for mortality (up 1.95%) from long-term PM_2.5 exposure were predicted to correspond to regions downwind to the industrial zone.

Supplementary information

The online version contains supplementary material available at 10.1007/s11869-023-01304-5.

The Influence of Selected Meteorological Factors on the Prevalence and Course of Stroke

Background: The objective of this study was to evaluate the impact of weather factors on stroke parameters. Methods: This retrospective study analyzed the records of stroke patients concerning the influence of meteorological conditions and moon phases on stroke parameters. Results: The study group consisted of 402 patients aged between 20 and 102; women constituted 49.8% of the subjects. Ischaemic stroke was diagnosed in 90.5% of patients and hemorrhagic stroke was diagnosed in 9.5% of patients. The highest number of hospitalizations due to stroke was observed in January (48 events); the lowest number was observed in July (23 events). There was no statistically significant correlation between the meteorological parameters on the day of onset and the preceding day of stroke and the neurological status (NIHSS) of patients. Mean air temperature on the day of stroke and the day preceding stroke was significantly lower in the group of patients discharged with a very good functional status (≤2 points in modified Rankin scale (mRS)) compared to the patients with a bad functional status (>2 points in mRS); respectively: 7.98 ± 8.01 vs. 9.63 ± 7.78; p = 0.041 and 8.13 ± 7.72 vs. 9.70 ± 7.50; p = 0.048). Humidity above 75% on the day of stroke was found to be a factor for excellent functional state (RR 1.61; p = 0.016). The total anterior circulation infarcts (in comparison with stroke in the other localization) were more frequent (70%) during a third quarter moon (p = 0.011). The following parameters had a significant influence on the number of stroke cases in relation to autumn having the lowest number of onsets: mean temperature (OR 1.019 95% CI 1.014–1.024, p < 0.000), humidity (OR 1.028, CI 1.023–1.034, p < 0.0001), wind speed (OR 0.923, 95% CI 0.909–0.937, p < 0.0001), insolation (OR 0.885, 95% CI 0.869–0.902, p < 0.0001), precipitation (OR 0.914, 95% CI 0.884–0.946, p < 0.0001). Conclusion: Air humidity and air temperature on the day of stroke onset as well as air temperature on the day preceding stroke are important for the functional status of patients in the acute disease period. A combination of the following meteorological parameters: lowered mean temperature and low sunshine, high humidity and high wind speed all increase the risk of stroke during the winter period. High humidity combined with high precipitation, low wind speed and low sunshine in the autumn period are associated with the lowest stroke incidence risk. A possible relationship between phases of the moon and the incidence requires further investigation.

Forecasting PM2.5 concentration using artificial neural network and its health effects in Ahvaz, Iran

The main objective of the present study was to predict the associated health endpoint of PM_2.5 using an artificial neural network (ANN). The neural network used in this work contains a hidden layer with 27 neurons, an input layer with 8 parameters, and an output layer. First, the artificial neural network was implemented with 80% of data for training then with 90% of data for training. The value of R for the data validation of these two networks was 0.80 and 0.83 respectively. The World Health Organization AirQ ⁺ software was utilized for assessing Health effects of PM_2.5 levels. The mean PM_2.5 over the 9-year study period was 63.27(μg/m³), about six times higher than the WHO guideline. However, the PM_2.5 concentration in the last year decreased by about 25% compared to the first year, which is statistically significant (P-value = 0.0048). This reduced pollutant concentration led to a decrease in the number of deaths from 1785 in 2008 to 1059 in 2016. Moreover, a positive correlation was found between PM_2.5 concentration and temperature and wind speed. Considering the importance of predicting PM_2.5 concentration for accurate and timely decisions as well as the accuracy of the artificial neural network used in this study, the artificial neural network can be utilized as an effective instrument to reduce health and economic effects.

Dependence of seasonal dynamics of hemorrhagic and ischemic strokes on the climate of a region: A meta-analysis

BACKGROUND

Cardiovascular events occur more often in winter than in summer; however, the dependence of strokes on various meteorological factors remains unclear.

AIMS

The purpose of this meta-analysis was to determine the dependence of the circannual dynamics of hospitalizations for hemorrhagic stroke and ischemic stroke on seasonal fluctuations in meteorological factors.

SUMMARY OF REVIEW AND CONCLUSIONS

For our meta-analysis, we selected 20 and 26 publications examining the seasonal dynamics of hemorrhagic stroke and ischemic stroke, respectively . The meta-analysis showed that hemorrhagic stroke is less likely to occur in summer than in other seasons and does not depend on a region's climate. The seasonal dynamics of ischemic stroke are not clearly expressed and are determined by the characteristics of a region's climate. In a climate without pronounced seasonal dynamics of atmospheric pressure and in wet winters, the vector of ischemic stroke incidents will not be expressed or slightly shifted toward winter. Low atmospheric pressure in summer is associated with an increased likelihood of ischemic stroke during this season compared to winter. There was also a relation between ischemic stroke risk with high relative humidity and a significant decrease in ρO₂ in summer, but there is not enough evidence regarding this association. We did not reveal dependence of the seasonal dynamics of strokes on the amplitude of annual fluctuations in air temperature.

Meteorological correlates and AirQ+ health risk assessment of ambient fine particulate matter in Tehran, Iran

There are few studies in the world that have been evaluated the mortality due to exposure to particulate matter smaller than 2.5 µm by AirQ+ software. Therefore, the study aimed to correlate between fine particulate matter (PM2.5) and meteorological variables and estimate all-cause annual mortality and mortality from cerebrovascular disease (stroke), ischemic heart disease (IHD), acute lower respiratory infection (ALRI), lung cancer (LC), chronic obstructive pulmonary disease (COPD) attributed to long-term exposure to ambient PM2.5 in Tehran from March 2017 to March 2018 using the WHO AirQ+ software. Data related to air quality, meteorological condition, population and the baseline incidence rates of health endpoints in Tehran were gathered from government agencies. The association between the PM2.5 concentrations and meteorological variables in the period of study were assessed by correlation analysis. The results of correlation analysis showed a weak positive correlation between PM2.5 concentrations and average monthly temperature (r = 0.42, P < 0.05) and average monthly humidity (r = 0.37, P < 0.05) in Tehran. The quantitative risk assessment related to all-cause annual mortality, the mortality of IHD, stroke, COPD, LC and ALRI were estimated 6710, 3797, 1145, 172, 135 and 27 cases, respectively. The results of regression association analysis between PM_2.5 and the number of recorded deaths was showed that with an increase of one microgram per cubic meter of PM_2.5, it is expected that about 27 cases will be added to air pollution mortality in Tehran.