According to the World Health Organization burden of disease from ambient air pollution reports, air pollution, especially that caused by particulate matter (PM), is a risk factor associated with acute lower respiratory infections, chronic obstructive pulmonary disease, lung cancer, ischemic heart disease (IHD), and stroke [1,2]. Ambient fine PM (PM_2.5) air pollution caused 7.6% of total mortality and contributed to 17.1% of IHD mortality in 2015 [1]. Several mechanisms assessing the association between PM and cardiovascular disease have been proposed, but the association between PM and pulse wave velocity (PWV), which is an independent predictor of cardiovascular outcome, has not been fully investigated in the healthy population. One possible mechanism is that PM could be associated with endothelial dysfunction, accelerate acute arterial vasoconstriction in healthy adults, and eventually disrupt systolic function and increase heart rate variability [3].

Aortic PWV is an independent predictor of cardiovascular morbidity and mortality in patients with end-stage renal disease and essential hypertension as well as in the general population [4]. In addition, brachial-ankle PWV (baPWV) is an accurate and noninvasive indicator of aortic PWV and has been proven suitable for screening vascular damage in a large cohort [5]. Among several studies evaluating the effects of PM on arterial stiffness, three studies focused on the effect of PM₁₀. Adamopoulos et al. [6] analyzed atmospheric pollution variables, including atmospheric PM concentrations, and their effects on arterial stiffness. They showed that 24-hour mean PM₁₀ levels were associated with an increased amplitude of the aortic-wave reflection magnitude (augmentation pressure) in patients with hypertension but not with PWV. In a cross-sectional study of 127 patients undergoing hemodialysis with a mean baPWV of 1,767 cm/s, Weng et al. [3] reported that the 12-month average PM₁₀ concentration (57.9±5.7 μg/m³) was associated with elevated baPWV. Ljungman et al. [7] showed that living near a major road was associated with higher arterial stiffness. However, satellite measurements of PM levels were not associated with arterial stiffness in the healthy Framingham Heart Study population, and no associations were observed with short-term exposure to air pollutants such as PM_2.5, black carbon, sulfate, nitrogen oxides, and ozone.

Therefore, this study aimed to determine whether the correlation between long- and short-term exposure to PM₁₀ and baPWV exists in apparently healthy cancer-free adults aged 40 years and older and to identify susceptible subgroups.

A total of 1,628 patients were eligible for the study, as shown in Figure 1. Table 1 shows the baseline characteristics of the study population stratified according to a baPWV cutoff of 1,534 cm/s. The mean±standard deviation baPWV and age of the total study population were 1,419±244 cm/s and 56.0±8.4 years, respectively.

In the study population, age, hypertensive medication, diabetes mellitus medication status, blood pressure (both systolic and diastolic), and glucose levels were statistically different between the high (≥1,534) and low (<1,534) baPWV groups. More specifically, patients with high baPWV were mostly older, were more likely to take hypertensive medication, had higher blood pressure, used more diabetes medication, and had higher glucose levels. There were no statistically significant differences between PM₁₀ levels at Lag 0 to Lag 3 days and in moving averages (Table 1).

Table 2 also shows the statistically significant associations between age, systolic and diastolic blood pressure, triglyceride levels, glucose levels, and high baPWV on unadjusted logistic regression analysis. However, we did not observe a significant relationship between short- and long-term exposure to PM₁₀ and high baPWV in the total study population. Although there were no significant associations between long-term exposure to PM₁₀ and high baPWV in the subgroups (Table 3), the associations between short-term exposure to PM₁₀ and high baPWV were marginally significant in non-obese subjects (Figure 2). A 10-μg increase in the 24-hour moving average at Lag 0–1 PM₁₀ exposure was associated with a 6% increased risk of high baPWV in non-obese subjects (OR, 1.059; P=0.058). The elderly, non-obese, and hypertensive individuals showed statistically non-significantly higher ORs than that did their counterparts (the young, obese and non-hypertensive individuals) during short-term exposure to PM₁₀ in Lag 0–1. When we conducted stratified analysis to determine the differential effects of short-term exposure to PM₁₀ exposure of Lag 0 to Lag 0–3 on high PWV, an unfavorable effect was more prominent in the non-obese group than in the obese group (P-value for interaction PM₁₀ Lag 0, 0.041; PM₁₀ Lag 0–1, 0.038) (Supplementary Table 1, Figure 2).

When we assessed the short-term PM₁₀ exposure through the 24-hour moving average of Lag 0 to Lag 3 days prior to medical examination, we found no statistically significant associations in the total study population and subgroups. When we investigated the subgroups according to age, sex, BMI, anti-hypertensive and anti-diabetes medication status, and metabolic syndrome with short-term exposure to PM₁₀ from Lag 0 to Lag 3, participants with a lower BMI (<25.0 kg/m²) presented a slightly greater risk of high PWV compared to their counterparts with a moving average of Lag 0–1. In particular, a 10-μg increase in the 24-hour moving average of PM₁₀ exposure of Lag 0–1 was marginally associated with a 6% elevated risk of high baPWV in non-obese subjects. Long-term exposure assessed through a 365-day moving average of PM₁₀ (PM₁₀ Lag 0–365) was not associated with an increased risk of high baPWV among all subjects and subgroups.

Previous studies on the association between PM₁₀ and baPWV showed inconsistent results due to differences in study populations and small sample sizes. In a systematic review, based on the published literature until January 2017, Zanoli et al. [14] suggested that short- and long-term exposure to gaseous and PM pollutants, including nitric oxide, sulfur dioxide, PM₁₀, and PM_2.5, may be associated with increased arterial stiffness and wave reflection. As a potential marker of arterial stiffness, parameters such as carotid-femoral PWV, baPWV, and augmentation index were assessed in 11 published studies from 2010 to 2016. Various subgroups such as older adults, urban population, patients with hypertension, and patients undergoing hemodialysis were more sensitive to air pollution variables, as manifested by arterial stiffness [3,6,15,16]. Among them, only one study conducted by Weng et al. [3] observed that the 12-month average concentration of PM₁₀ was associated with elevated baPWV in patients undergoing hemodialysis (β=0.13, P=0.04).

In 2018, in a well-characterized large community-based cohort of the Framingham Heart study [7], a positive association between living near a major road and higher arterial stiffness was observed. However, no associations were observed with short- and long-term exposure to air pollutants such as the satellite-measured levels of PM_2.5, black carbon, sulfate, nitrogen oxides, and ozone, with arterial stiffness. Recently, an interquartile increase in PM₁₀ and PM_2.5 did not significantly increase the PWV in 40 healthy volunteers aged 60 years and older in a randomized, crossover study [17]. Our study also showed no significant associations between short-term and long-term exposure to PM₁₀ and baPWV in apparently healthy cancer-free subjects. We observed a marginally elevated risk of high PWV associated with short-term exposure to a 24-hour moving average of PM₁₀ exposure of Lag 0–1 in non-obese subjects. This association in non-obese subjects was significantly different from that in obese subjects.

Several mechanisms underlying the association between PM and PWV have been postulated. Mild and transitory inflammatory stimuli have been proposed as possible links between arterial stiffening [14], functional arterial stiffening, and short-term exposure to air pollutants. Additionally, exposure to PM pollutants is associated with acute arterial vasoconstriction [18] and endothelial dysfunction [19]. Long-term exposure to PM for months to years has been associated with atherosclerosis, vascular dysfunction, and eventually subclinical diseases such as high blood pressure, increased carotid intima media thickness, and increased calcification of arteries [7].

The possible mechanism underlying the differential effect of short-term exposure to PM₁₀ on high PWV in non-obese subjects may be as follows. Previously, Tang et al. [20] suggested that obese individuals have greater nutritional reserves and can therefore cope better with acute stressful events and increased metabolic demands due to the beneficial effect of adipose tissue induced by beneficial hormones and cytokines. In our study, relatively healthy, non-obese individuals showed significantly lower body fat percentage based on our data (body fat % of obese versus non-obese=30.4% versus 25.9%), which may be a possible mechanism by which non-obese individuals have difficulty coping with short-term exposure to PM₁₀, resulting in high PWV. Further research is required to validate our findings.

This study used various laboratory data and clinical measurements to determine specific vulnerable subgroups and explain the potential links underlying the relationship between PM and inflammation, fitness, level of adiposity, and PWV. However, our study had some limitations. Although we analyzed the association between PM₁₀ and baPWV in short- and long-term exposures, we did not analyze PM_2.5, because PM_2.5 data were only available for the city of Seoul between 2006 and 2009, whereas PM₁₀ was available for the entire nation. The study population we used underwent private health screening tests in a single university hospital; thus, this group may not be representative of the general population. Furthermore, we used both short- and long-term PM exposure assessments with fixed monitoring data, which may cause non-differential misclassification at the individual level of exposure and underestimate the association in long-term exposure-related adverse health effects. Finally, because we did not have information regarding the timing of the activities of each patient, we could not ascertain the exact location and timing of exposure to PM₁₀, which could lead to a bias if the PM₁₀ levels between the patient’s workplace and residence differ. Nevertheless, because exposure misclassification could lead to a null hypothesis, we can presume that our results could underestimate the effects of PM₁₀ compared to those that could be obtained by measuring PM₁₀ exposure levels with more precision. In other words, because we did not install 24-hour air pollution monitoring devices for each patient, we could not consider the air pollution levels when commuting to and from work; thus, a more sophisticated modeling approach is required in future studies.

In conclusion, we showed the probable adverse effect of short-term exposure to PM₁₀ on high baPWV in non-obese subjects compared to their obese counterparts. Further large and prospective studies are necessary to validate and elucidate the mechanism underlying of the influence of PM on baPWV, especially in healthy, non-obese subjects.