Longitudinal associations of long-term exposure to ultrafine particles with blood pressure and systemic inflammation in Puerto Rican adults

Abstract

Background: Few longitudinal studies have examined the association between ultrafine particulate matter (UFP, particles < 0.1 μm aerodynamic diameter) exposure and cardiovascular disease (CVD) risk factors. We used data from 791 adults participating in the longitudinal Boston Puerto Rican Health Study (Massachusetts, USA) between 2004 and 2015 to assess whether UFP exposure was associated with blood pressure and high sensitivity C-reactive protein (hsCRP, a biomarker of systemic inflammation).

Methods: Residential annual average UFP exposure (measured as particle number concentration, PNC) was assigned using a model accounting for spatial and temporal trends. We also adjusted PNC values for participants' inhalation rate to obtain the particle inhalation rate (PIR) as a secondary exposure measure. Multilevel linear models with a random intercept for each participant were used to examine the association of UFP with blood pressure and hsCRP.

Results: Overall, in adjusted models, an inter-quartile range increase in PNC was associated with increased hsCRP (β = 6.8; 95% CI = - 0.3, 14.0%) but not with increased systolic blood pressure (β = 0.96; 95% CI = - 0.33, 2.25 mmHg), pulse pressure (β = 0.70; 95% CI = - 0.27, 1.67 mmHg), or diastolic blood pressure (β = 0.55; 95% CI = - 0.20, 1.30 mmHg). There were generally stronger positive associations among women and never smokers. Among men, there were inverse associations of PNC with systolic blood pressure and pulse pressure. In contrast to the primary findings, an inter-quartile range increase in the PIR was positively associated with systolic blood pressure (β = 1.03; 95% CI = 0.00, 2.06 mmHg) and diastolic blood pressure (β = 1.01; 95% CI = 0.36, 1.66 mmHg), but not with pulse pressure or hsCRP.

Conclusions: We observed that exposure to PNC was associated with increases in measures of CVD risk markers, especially among certain sub-populations. The exploratory PIR exposure metric should be further developed.

Keywords: Blood pressure; C-reactive protein; Exposure assessment; Hispanic; Susceptible populations; Ultrafine particulate matter.

Fig. 1

Spatial distribution of modeled annual average PNC and PIR. a) particle number concentration (PNC) and b) particle inhalation rate (PIR; by quintiles) at participant residences at baseline (n = 754). Data from mobile monitoring, a central monitor at a U.S. Environmental Protection Agency Speciation Trends Network (EPA-STN) site, and residential monitors were used to build and validate the PNC model

Fig. 2

Associations between PNC and PIR with blood pressure and high sensitivity C-reactive protein. a) Change in blood pressure (mmHg) and b) percent change in C-reactive protein (mg/L) with an inter-quartile increase in PNC or PIR. All models control for age. Models additionally adjusted for: * Systolic blood pressure (SBP): education, sex, BMI, high-density lipoprotein (HDL) cholesterol, ln(triglycerides), hypertension medication, anxiety medication, marital status, and year of baseline visit; Diastolic blood pressure (DBP): sex, BMI, low-density lipoprotein (LDL) cholesterol, HDL cholesterol, ln(triglycerides), diabetes, marital status, and year of baseline visit; Pulse pressure (PP): education, LDL cholesterol, hypertension medication, diabetes, marital status, and smoking; High sensitivity C-reactive protein (hsCRP): education, sex, BMI, LDL cholesterol, HDL cholesterol, diabetes, anxiety medication, and smoking. ** SBP: education, BMI, LDL cholesterol, HDL cholesterol, ln(triglycerides), hypertension medication, anxiety medication, marital status, and year of baseline visit; DBP: BMI, LDL cholesterol, HDL cholesterol, ln(triglycerides), marital status, smoking, and year of baseline visit; PP: education, LDL cholesterol, hypertension medication, diabetes, marital status, and smoking; hsCRP: education, BMI, LDL cholesterol, HDL cholesterol, ln(triglycerides), diabetes, and anxiety medication. *** The same covariates are used as in the main models with PNC but only outcome data from the second and third study visits are included