Long-Term Exposure to Traffic-Related Air Pollution Associated with Blood Pressure and Self-Reported Hypertension in a Danish Cohort

Abstract

Background: Short-term exposure to air pollution has been associated with changes in blood pressure (BP) and emergency department visits for hypertension, but little is known about the effects of long-term exposure to traffic-related air pollution on BP and hypertension.Objectives: We studied whether long-term exposure to air pollution is associated with BP and hypertension.Methods: In 1993–1997, 57,053 participants 50–64 years of age were enrolled in a population-based cohort study. Systolic and diastolic BP (SBP and DBP, respectively) were measured at enrollment. Self-reported incident hypertension during a mean follow-up of 5.3 years was assessed by questionnaire. We used a validated dispersion model to estimate residential long-term nitrogen oxides (NOx), a marker of traffic-related air pollution, for the 1- and 5-year periods prior to enrollment and before a diagnosis of hypertension. We conducted a cross-sectional analysis of associations between air pollution and BP at enrollment with linear regression, adjusting for traffic noise, measured short-term NOx, temperature, relative humidity, and potential lifestyle confounders (n = 44,436). We analyzed incident hypertension with Cox regression, adjusting for traffic noise and potential confounders.Results: A doubling of NOx exposure during 1- and 5-year periods preceding enrollment was associated with 0.53-mmHg decreases [95% confidence interval (CI): –0.88, –0.19 mmHg] and 0.50-mmHg decreases (95% CI: –0.84, –0.16 mmHg) in SBP, respectively. Long-term exposure also was associated with a lower prevalence of baseline self-reported hypertension (per doubling of 5-year mean NOx: odds ratio = 0.96; 95% CI: 0.91, 1.00), whereas long-term NOx exposure was not associated with incident self-reported hypertension during follow-up.Conclusions: Long-term exposure to traffic-related air pollution was associated with a slightly lower prevalence of BP at baseline, but was not associated with incident hypertension.

A rapid assessment of the impact of hazard reduction burning around Sydney, May 2016

“…Those who have done so found that excess risks of air pollution in the proximity of roads generally remained after adjustment for noise for cardiovascular mortality (Beelen et al, 2008a;Gan et al, 2012), hypertension and diabetes mellitus (Coogan et al, 2012), hypertension (Fuks et al, 2011;Sørensen et al, 2012), and cognitive performance of primary schoolchildren (van Kempen et al, 2012). Therefore, these studies show effects of air pollution that cannot be explained by noise.…”

Associations of Short-Term and Long-Term Exposure to Ambient Air Pollutants With Hypertension

“…4,5,10,12,[23][24][25][26][27][28][29] We used a standardized table to extract the following information from all of the included articles: authors, publication year, study setting, study population, study duration, study design, short-term or long-term effect, exposure measurement method, data source, number of controls and cases, type of air pollution, exposure mean and range, adjusted odds ratio (OR) and their 95% confidence intervals (CIs), adjusted covariates, and the number of lag days for short-effect if applicable. Eligibility assessments and all of the data extraction were checked and verified by consensus of the 2 investigators.…”

“…Of the 17 included studies, 3 studies defined hypertension as systolic blood pressure ≥140 mm Hg and diastolic blood pressure ≥90 mm Hg 4,24,25 ; 5 studies defined hypertension according to the ICD9 or ICD10 code [6][7][8][9]21 ; 2 studies used self-reported doctor-diagnosed hypertension 5,27 ; and 7 studies used >1 methods to define the hypertension cases 10,12,21,23,26,28,29 ( Tables 1 and 2). …”

“…Four studies assessed the air pollution exposure using complex dispersion models or land use regression models that included various databases, including traffic, meteorology, roadway geometry, vehicle emission, air quality monitoring data, and land use. 5,23,28,29 These models could estimate each subject's exposure level with high accuracy. One study used both data from central air pollution monitoring stations and self-monitoring data 8 ( Tables 1 and 2).…”

“…4,5,10,12,[23][24][25][26][27][28][29] Of these studies, the most common epidemiological designs were cross-sectional (n=5) and cohort studies (n=4). Two other studies were casecontrol designs.…”