Air pollution exposure can raise high blood pressure risk

Air pollution exposure can raise high blood pressure risk
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Exposure to air pollutants arising from coal burning, vehicle exhaust, airborne dust and dirt can increase the risk of developing high blood pressure, warns a new study. 

Exposure to air pollutants arising from coal burning, vehicle exhaust, airborne dust and dirt can increase the risk of developing high blood pressure, warns a new study. High blood pressure can be defined as systolic blood pressure more than 140 mm Hg and/or diastolic blood pressure over 90 mm Hg or by anti-hypertensive drug use.

The findings showed that both short and long-term exposure to air borne pollutants such as sulfur dioxide (SO2) from the burning of fossil fuel, nitrogen oxide (NOx) from power plants and vehicle exhaust, as well as particulate matter (PM) particles found in the air, including dust, dirt, smoke and liquid droplets can significantly elevate the levels of blood pressure.

"In the study, we discovered a significant risk of developing high blood pressure due to exposure to air pollution," said lead author Tao Liu, epidemiologist at Guangdong Provincial Institute of Public Health in China. Also, air pollution can lead to inflammation and oxidative stress causing changes in the arteries.

High blood pressure has been identified as a major risk factor for cardiovascular disease and stroke, the researchers said. "People should limit their exposure on days with higher air pollution levels, especially for those with high blood pressure, even very short-term exposure can aggravate their conditions," Liu suggested.

For the study, published in the journal Hypertension, the team performed a meta-analysis of 17 studies, which involved over 108,000 hypertension patients and 220,000 non-hypertensive controls, assessing the health effects of all air pollution on hypertension risk. Air pollution exposure was assessed by taking average of data from the nearest air pollution monitoring stations or using complex dispersion models or land use regression models.

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