Respiratory Inflammation and Short-Term Ambient Air Pollution Exposures in Adult Beijing Residents with and without Prediabetes: A Panel Study

Abstract

Background: Accumulating evidence suggests that individuals with glucose metabolism disorders are susceptible to mortality associated with fine particles. However, the mechanisms remain largely unknown.

Objectives: We examined whether particle-associated respiratory inflammation differed between individuals with prediabetes and healthy control participants.

Methods: Based on a panel study [A prospective Study COmparing the cardiometabolic and respiratory effects of air Pollution Exposure on healthy and prediabetic individuals (SCOPE)] conducted in Beijing between August 2013 and February 2015, fractional exhaled nitric oxide (FeNO) was measured from 112 participants at two to seven visits to indicate respiratory inflammation. Particulate pollutants-including particulate matter with an aerodynamic diameter of $\le 2.5\mu m$ (${\mathrm{PM}}_{2.5}$), black carbon (BC), ultrafine particles (UFPs), and accumulated-mode particles-were monitored continuously at a single central monitoring site. Linear mixed-effects models were used to estimate associations between ln-FeNO with pollutant concentrations at individual 1-h lags (up to 24 h) and with average concentrations at 8 and 24 h before the clinical visit. We evaluated glucose metabolism disorders as a potential modifier by comparing associations between participants with high vs. low average fasting blood glucose (FBG) and homeostasis model assessment insulin resistance (HOMA-IR) levels.

Results: FeNO was positively associated with all pollutants, with the strongest associations for an interquartile range increase in 1-h lagged exposures (ranging from 21.3% for ${\mathrm{PM}}_{2.5}$ to 74.7% for BC). Associations differed significantly according to average HOMA-IR values when lagged 6-18 h for ${\mathrm{PM}}_{2.5}$, 15-19 h for BC, and 6-15 h for UFPs, with positive associations among those with $\text{HOMA-IR}\ge 1.6$ while associations were closer to the null or inverse among those with $\text{HOMA-IR}<1.6$. Associations between ${\mathrm{PM}}_{2.5}$ and FeNO were consistently higher among individuals with average $\text{FBG}\ge 6.1\text{mmol}/L$ vs. low FBG, with significant differences for multiple hourly lags.

Discussion: Glucose metabolism disorders may aggravate respiratory inflammation following exposure to ambient particulate matter. https://doi.org/10.1289/EHP4906.

Figure 1.

Estimated percent difference in FeNO (95% CI) per IQR increase in 1- to 24-h lagged (A) ${\mathrm{PM}}_{2.5}$, (B) BC, (C) UFPs, and (D) Acc concentrations. All models were single-pollutant linear mixed-effects models of ln-FeNO with random participant-specific intercepts, adjusted for ambient temperature on the previous day, average relative humidity during the 7 d before the visit, day of the week, age (continuous), sex, and smoking history (nonsmoker vs. former smoker). See Table S4 for corresponding numeric data. Note: Acc, accumulated-mode particles; BC, black carbon; CI, confidence interval; FeNO, fractional exhaled nitric oxide; IQR, interquartile range; ${\mathrm{PM}}_{2.5}$, particulate matter with an aerodynamic diameter of $\le 2.5\mathrm{\mu }\mathrm{m}$; UFPs, ultrafine particles.

Figure 2.

Estimated percent difference in FeNO (95% CI) per IQR increases in 1–24 h lagged particle concentrations according to high and low FBG (A) ${\mathrm{PM}}_{2.5}$, (C) BC, (E) UFPs, and (G) Acc and HOMA-IR (B) ${\mathrm{PM}}_{2.5}$, (D) BC, (F) UFPs, and (H) Acc based on average values over all study visits. All models were single-pollutant linear mixed-effects models of ln-FeNO with random participant-specific intercepts, adjusted for ambient temperature on the previous day, average relative humidity during the 7 d before the visit, day of the week, age (continuous), sex, and smoking history (nonsmoker vs. former smoker). Low-FBG, high-FBG, low-IR, and high-IR groups referred to participants with average level of FBG $<6.1\text{\hspace{0.17em}mmol}/\mathrm{L}$, $\text{FBG}\ge 6.1\text{\hspace{0.17em}mmol}/\mathrm{L}$, $\text{HOMA-IR}<1.6$ and $\text{HOMA-IR}\ge 1.6$, respectively. See Tables S6 and S8 for corresponding numeric data and interaction p-values for all pairs of estimates according to FBG and HOMA-IR. The IQRs for each pollutant and lag period are provided in Table S4. Note: Acc, accumulated-mode particles; BC, black carbon; CI, confidence interval; FBG, fasting blood glucose; FeNO, fractional exhaled nitric oxide; HOMA-IR, homeostasis model assessment insulin resistance; IQR, interquartile range; IR, insulin resistance; UFPs, ultrafine particles.

Figure 3.

Estimated percent difference in FeNO per IQR increase in 1 h lagged particle concentrations based on two-pollutant models for (A) all participants, (B) low-FBG group, (C) high-FBG group, (D) low HOMA-IR group, and (E) high HOMA-IR group. All models were linear mixed-effects models of ln-FeNO with random participant-specific intercepts. The models were adjusted for other pollutants as indicated, plus ambient temperature on the previous day, average relative humidity during the 7 d before the visit, day of the week, age (continuous), sex, and smoking history (nonsmoker vs. former smoker). Low-FBG, high-FBG, low-IR, high-IR groups referred to participants with average level of $\text{FBG}<6.1\text{\hspace{0.17em}mmol}/\mathrm{L}$, $\text{FBG}\ge 6.1\text{\hspace{0.17em}mmol}/\mathrm{L}$, $\text{HOMA-IR}<1.6$ and $\text{HOMA-IR}\ge 1.6$, respectively. See Table S9 for corresponding numeric data and interaction p-values for all pairs of estimates according to FBG and HOMA-IR. The IQRs for each pollutant and lag period are provided in Table S4. Note: Acc, accumulated-mode particles; BC, black carbon; FBG, fasting blood glucose; FeNO, fractional exhaled nitric oxide; HOMA-IR, homeostasis model assessment insulin resistance; IQR, interquartile range; IR, insulin resistance; UFPs, ultrafine particles.