Longitudinal Analysis of Long-Term Air Pollution Levels and Blood Pressure: A Cautionary Tale from the Multi-Ethnic Study of Atherosclerosis

Abstract

Background: Air pollution exposures are hypothesized to impact blood pressure, yet few longitudinal studies exist, their findings are inconsistent, and different adjustments have been made for potentially distinct confounding by calendar time and age.

Objective: We aimed to investigate the associations of long- and short-term [Formula: see text] and [Formula: see text] concentrations with systolic and diastolic blood pressures and incident hypertension while also accounting for potential confounding by age and time.

Methods: Between 2000 and 2012, Multi-Ethnic Study of Atherosclerosis participants were measured for systolic and diastolic blood pressure at five exams. We estimated annual average and daily [Formula: see text] and [Formula: see text] concentrations for 6,569 participants using spatiotemporal models and measurements, respectively. Associations of exposures with blood pressure corrected for medication were studied using mixed-effects models. Incident hypertension was examined with Cox regression. We adjusted all models for sex, race/ethnicity, socioeconomic status, smoking, physical activity, diet, season, and site. We compared associations from models adjusting for time-varying age with those that adjusted for both time-varying age and calendar time.

Results: We observed decreases in pollution and blood pressures (adjusted for age and medication) over time. Strong, positive associations of long- and short-term exposures with blood pressure were found only in models with adjustment for time-varying age but not adjustment for both time-varying age and calendar time. For example, [Formula: see text] higher annual average [Formula: see text] concentrations were associated with 2.7 (95% CI: 1.5, 4.0) and [Formula: see text] (95% CI: [Formula: see text] 1.0) mmHg in systolic blood pressure with and without additional adjustment for time, respectively. Associations with incident hypertension were similarly weakened by additional adjustment for time. Sensitivity analyses indicated that air pollution did not likely cause the temporal trends in blood pressure.

Conclusions: In contrast to experimental evidence, we found no associations between long- or short-term exposures to air pollution and blood pressure after accounting for both time-varying age and calendar time. This research suggests that careful consideration of both age and time is needed in longitudinal studies with trending exposures. https://doi.org/10.1289/EHP2966.

Figure 1.

Trends in adjusted systolic and diastolic blood pressures due to both time-varying age and calendar time. Residuals of adjusted blood pressures outputted from a model of medication adjusted blood pressures after control for either calendar time or age and covariates (sex, race/ethnicity, education, study site, neighborhood socioeconomic status and its interaction with study site, season and its interaction with study site, body-mass index, waist-to-hip ratio, tobacco smoke exposure, and physical activity as well as random slopes and intercepts for subject). Gray bands are 95 confidence intervals.

Figure 2.

Associations (95% CI) of systolic blood pressures with ${\mathrm{PM}}_{2.5}$ and ${\text{NO}}_2$ concentrations with and without additional adjustment for calendar time. Models adjusted for age at exam, sex, race/ethnicity, education, study site, neighborhood socioeconomic status and its interaction with study site, season and its interaction with study site, body-mass index, waist-to-hip ratio, tobacco smoke exposure, physical activity, and calendar time (as noted) as well as random slopes and intercepts for subject. Note: CI, confidence interval; IQR, interquartile range; ${\mathrm{PM}}_{2.5}$, particulate matter less than $2.5\mathrm{\mu }\mathrm{m}$ in aerodynamic diameter; SBP, systolic blood pressure.

Figure 3.

Associations (95% CI) of diastolic blood pressures with ${\mathrm{PM}}_{2.5}$ and ${\text{NO}}_2$ concentrations with and without additional adjustment for calendar time. Models adjusted for age at exam, sex, race/ethnicity, education, study site, neighborhood socioeconomic status and its interaction with study site, season and its interaction with study site, body-mass index, waist-to-hip ratio, tobacco smoke exposure, physical activity, and calendar time (as noted) as well as random slopes and intercepts for subject. Note: CI, confidence interval; DBP, diastolic blood pressure; IQR, interquartile range; ${\mathrm{PM}}_{2.5}$, particulate matter less than $2.5\mathrm{\mu }\mathrm{m}$ in aerodynamic diameter.

Figure 4.

Trends in annual average ${\mathrm{PM}}_{2.5}$ and adjusted blood pressure stratified by extent of air pollution reductions. Models adjusted for age at exam, sex, race/ethnicity, education, study site, neighborhood socioeconomic status and its interaction with study site, body-mass index, waist-to-hip ratio, tobacco smoke exposure, and physical activity as well as random slopes and intercepts for subject. Solid lines indicate an assumption of nonlinear trend using B-splines in calendar time. Note: DBP, diastolic blood pressure; ${\mathrm{PM}}_{2.5}$, particulate matter less than $2.5\mathrm{\mu }\mathrm{m}$ in aerodynamic diameter; SBP, systolic blood pressure. Dotted lines indicate an assumption of linear trend in calendar time.