Lung function benefits of traditional Chinese medicine Qiju granules against fine particulate air pollution exposure: a randomized controlled trial

1 Introduction

Ambient air pollution is an important global public health challenge. Epidemiological studies have demonstrated that exposure to particulate matter (PM_2.5) increases mortality and morbidity in respiratory diseases (1, 2). The global burden of disease study estimated that 1.4 million deaths were due to respiratory diseases caused by ambient particulate matter alone (3), with PM_2.5 identified as the most common detrimental factor among ambient particulate matter pollutants (3). The most effective way to minimize health hazards is by improving air quality by reducing pollutant release. Although more countries have been taking increased actions, over 90% of the people worldwide continue to breathe polluted air (4). Thus, personalized behavioral and preventive interventions may offer an alternative way to mitigate health hazards due to air pollution.

Previous studies have proved that both personal protective equipment and dietary supplementation could mitigate the adverse effects of PM_2.5 air pollution (5–7). Health benefits have been demonstrated by using air purifiers and particulate-filtering respirators (5, 7). However, on many occasions, these interventions are not portable or readily available (e.g., outdoors and social interactions). Omega-3 fatty acid supplementation has been shown to alleviate some adverse effects in cardiovascular, metabolic, and neurological systems from air pollution (6). Given the role of the lung as the entrance of PM_2.5 inhalational exposure, attenuating respiratory damage from air pollution should help prevent subsequential systemic injuries in our bodies. The exact pathophysiological mechanisms of lung injury are yet to be fully understood. Multiple targets including airway inflammation, oxidative stress, and pulmonary fibrosis are regarded as potential mechanisms that are involved in PM_2.5-induced lung dysfunction (8). Therefore, it is reasonable to speculate that multi-target intervention of these biological pathways may offer more effective and preventive benefits against pulmonary injury from PM_2.5 air pollution.

The traditional Chinese medicine (TCM) formula known as Qi-Ju-Di-Huang-Wan (Lycium, Chrysanthemum, and Rehmannia Formula, QJDHW) originates from “Yi Ji Juan Ba” of Dong Xiyuan of the Qing Dynasty (9). Qiju granules are derived from QJDHW, which has been traditionally used to treat symptoms such as cough with phlegm, dry mouth and throat, and liver heat (10, 11). In TCM's Five Phases Theory, Qiju granules are considered to have the properties of nourishing Yin and clearing heat with wood and fire attributes. Qiju granules contain five edible herbs, including Rhodiola rosea L. (Crassulaceae), Portulaca oleracea L. (Portulacaceae), Lycium barbarum L. (Solanaceae), Chrysanthemum × morifolium (Ramat.) Hemsl. (Asteraceae), and Siraitia grosvenorii (Swingle) C.Jeffrey ex A.M.Lu & Zhi Y.Zhang (Cucurbitaceae). These herbs are often used as a part of the regimen to treat lung disorders, which show attenuation in inflammation, oxidative stress, and fibrosis response (12–16). Our preliminary study has demonstrated the potential lung benefits of using Qiju granules against exposure to PM_2.5 air pollution in an animal model (17). An oral administration of Qiju decoction decreases the concentration of tumor necrosis factor-α (TNF-α) and malondialdehyde (MDA), improving the expression of glutathione-peroxidase (GSH-PX) in serum (17). Qiju granules may act as a better alternative to attenuate lung injury from PM_2.5. However, it remains unknown whether Qiju granules have protective effects against PM_2.5-induced lung damage in humans.

In order to verify the effects of Qiju granules on humans, we conducted a randomized, double-blinded, and placebo-controlled trial to assess whether Qiju granules offered lung benefits against the adverse effects of PM_2.5 exposure among healthy young adults.

2 Methods

2.1 Study participants and design

This trial was conducted from December 2018 to April 2019. We initially recruited 60 healthy college students at Zhejiang Chinese Medical University, Hangzhou, China, with the exclusion of students who are primary tobacco smokers or whose roommates are smokers, who are clinically diagnosed with cardiovascular or lung diseases, who had recent infection, who took antibiotics within the past month, or who had a history of allergies or family allergies. A total of 47 eligible participants were randomly assigned to two different treatment groups: the Qiju group and the placebo group. The randomization process was conducted using computer-generated random numbers. Gender was considered during randomization to ensure baseline comparability between the two groups. The random assignment procedure was carried out by independent researchers who were not involved in participant recruitment or diagnostic assessments, thus minimizing potential biases. All participants were intervened and monitored in a double-blinded manner throughout the study period. Two rounds of follow-up, with an interval of 2 weeks, were scheduled during a total intervention of 4 weeks. Data on individual characteristics (i.e., age, sex, height, and weight) and vital signs (i.e., heart rate (HR), blood pressure (BP), and respiration rate) were recorded, and lung function at the baseline and during the follow-ups was measured. Peripheral blood and the first-morning urine (midstream) samples were collected at the baseline and the end of the trial. Real-time PM_2.5 exposure concentrations of those participants were also measured daily during the study time periods.

The study was registered in the Chinese Clinical Trial Registry (ChiCTR1900021235) on 13 February 2019 and was approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang Chinese Medical University. All participants gave written informed consent at enrollment.

2.2 Ultra Performance Liquid Chromatography-Quadrupole-Time of Flight/Mass Spectrometry analysis of Qiju granules

The Ultra Performance Liquid Chromatography-Quadrupole-Time of Flight/Mass Spectrometry (UPLC-Q-TOF/MS) instrument was set to a capillary voltage of 2.5 kV (negative ion mode), sample cone voltage of 40 V, source temperature of 120°C, desolvation temperature of 500°C, and desolvation gas flow of 1000 L/h. Collision energy was set at 6 eV, and the full scan spectra were recorded from 50 to 1200 Da. Qiju granules were dissolved in purified water at a concentration of 100 mg/ml, and the solution was centrifuged to obtain the supernatant. The supernatant was analyzed by UPLC using reversed-phase C18 analytical columns (2.1 × 100 mm) packed with silica beads of 1.6 μm diameter (Cortecs^® UPLC^® T3, Waters, SYNAPT G2-Si, USA). The mobile phase consisted of 10% of solvent A (0.1% of formic acid) and 90% of solvent B (acetonitrile). The elution of Qiju granules was achieved over a period of 35 min with an injection volume of 2 μl and flow rates of 0.3 ml/min. The gradient elution program was set as follows: 0–2 min, 5% B; 2–32 min, 5–100% B; 32–33 min, 100% B; and 33–35 min, 5% B. The MS spectra of Qiju granules were acquired in negative-ion mode (Supplementary Figure S1).

2.3 Interventions

Qiju granules and placebo granules were provided by Huadong Medicine Co., LTD (Hangzhou, Zhejiang Province, China). Qiju granules were extracted and purified from Rhodiola rosea L. [Crassulaceae], Portulaca oleracea L. [Portulacaceae], Lycium barbarum L. [Solanaceae], Chrysanthemum × morifolium (Ramat.) Hemsl. [Asteraceae], and Siraitia grosvenorii (Swingle) C.Jeffrey ex A.M.Lu & Zhi Y.Zhang [Cucurbitaceae]. Placebo granules were purified from dextrin and caramel, with their appearance being identical and taste being similar to Qiju granules. The granules were stored at room temperature. Participants in the Qiju and control groups were instructed to dissolve 1 package of granules (15 g) in warm drinking water and take them orally every morning throughout the study period. The participants and researchers were blinded to either intervention.

2.4 Exposure assessment

To obtain real-time measurements of ambient PM_2.5 concentrations, a portable environmental dust monitor (AirCasting Air Monitor Casing, New York Hall of Science, NY, USA) was provided to every two or three participants with similar activities who lived in the same dorm room. Enrolled participants were asked to wear the portable monitors from 8 am to 8 pm. The portable monitor was able to record ambient PM_2.5 concentrations every second, and the data were collected to calculate daily average PM_2.5 concentrations. To ensure the accuracy of the monitor, each portable monitor was calibrated through an aerosol monitoring meter (pDR-1500, Thermo Scientific, China) beforehand, and PM_2.5 concentrations were calculated using the following formula:

$\begin{array}{l}Formula1:Y=\frac{B_{max}^{*}X}{K_d+X},\end{array}$

Y represents the concentrations of the portable monitor; X represents ambient PM_2.5 concentrations; B_max represents the maximum specific binding in the same units as Y; and K_d represents the equilibrium dissociation constant, in the same units as X. The fitting degree of R² was found to be between 0.90 and 0.98 in this formula (Supplementary Table S1, Supplementary Figure S2).

2.5 Health examination

At each round of health examinations, we measured the key characteristics of the participants, including height, body weight, blood pressure (BP), heart rate (HR), and lung function between 8:00 and 9:00 AM to minimize potential influences from circadian rhythms. Height and weight were measured by electronic scale without shoes and heavy coats, and then body mass index (BMI) was calculated. After the participant sat for at least 5 min, BP and HR were measured by an electronic sphygmomanometer (Omron J710, Japan). BP was measured using the left upper arm for at least three times at 1-min intervals. The mean values of the second and third HR, systolic BP (SBP), and diastolic BP (DBP) measurements were obtained. If the differences between the second and third readings of BP were >5 mmHg, additional measurements were obtained until satisfaction was achieved. Fasting peripheral blood and the first-morning midstream urine samples were collected between 8:00 and 9:00 AM. Routine blood and urine tests and hepatic and renal function examinations were conducted at the beginning and the end of the trial. A lung function detector (HI-101, Chestgraph, Tokyo, Japan) was utilized to measure the major parameters of lung function, including forced vital capacity (FVC), forced expiratory volume in one second (FEV₁), peak expiratory flow (PEF), maximal mid-expiratory flow (MMEF), forced expiratory flow at 75% of FVC (FEF₇₅), forced expiratory flow at 50% of FVC (FEF₅₀), and forced expiratory flow at 25% of FVC (FEF₂₅). Then, the ratio of the measured value to the predicted value was calculated as the lung function parameter.

2.6 Statistical analyses

PM_2.5 concentrations and health data were associated with the time of lung function measured. Health data including lung function, BP, and HR were directly used as those were normally distributed. Linear mixed-effects models were applied to evaluate PM_2.5 exposure concentrations in relation to each of the lung function parameters within each group. In the basic model, PM_2.5 was included as a fixed-effect independent term, and a random-effect intercept was added for each subject to account for correlations among repeated measurements per person, assuming a compound symmetry covariance structure, which was further adjusted for sex and BMI. In order to explore the lag patterns regarding the impact of PM_2.5 exposure on individual lung function, multiple averaging periods preceding the measurement of lung function were applied, i.e., lag 0 week (7 days before the examination day), lag 1 week (from 8 to 14 days before the examination day), and lag 0–1 week (14 days before the examination day). All linear mixed-effects models were conducted using the “lme4” package of R software version 3.3.1. In different group analyses, the difference in the lung function parameters and 95% CIs between the two groups were presented.

3 Results

3.1 Demographic characteristics

A total of 60 participants were screened, and 47 were enrolled and underwent randomization (24 were assigned to the Qiju group and 23 were assigned to the placebo group). Among those, 40 participants completed the scheduled follow-ups; of which 20 were in the Qiju group and 20 were in the control group (Figure 1). The participants in this study are aged between 19 and 22 years old, with 47.50% being male participants. There were no statistically significant differences in age or gender between the two groups. The other characteristics of these two groups were no significant differences at enrollment in the distributions of BMI, HR, SBP, DBP, respiratory rate (RPR), FVC, FEV1, PEF, MMEF, FEF75, FEF25, and FEF50 (Table 1). There was no statistically significant difference in biomarkers of the routine blood test, routine urine test, hepatic function, or renal function between these two groups at either baseline or at the end of the trial (Supplementary Table S2).

Figure 1

Figure 1. Flow diagram of enrollment and randomization. The intervention lasted for consecutive 4 weeks for both randomized arms. Of the 20 participants in the Qiju group who were included in the primary analysis, 3 participants discontinued intervention and 1 participant refused clinical follow-up. Of the 20 participants in the control group who were included in the primary analysis, 2 discontinued intervention and 1 refused clinical follow-up.

Table 1

Table 1. Characteristics of the participants at baseline.

3.2 Monitoring of PM_2.5 concentration

The average concentrations of individual PM_2.5 exposure among participants were 64.72 ± 34.98 μg/m³ during the study period, which is slightly higher than that from the average level of Hangzhou city. At the individual level, daily and weekly averages of PM_2.5 concentrations aligned well between the two groups during the study period (Figures 2A, B). The exposure of PM_2.5 concentrations during different time periods before the conduction of the health examination was also calculated. The average concentrations at lag 0 week (7 days before the examination day), lag 1 week (from 8 to 14 days before the examination day), and lag 0–1 week (14 days before the examination day) were 57.58 ± 6.26 μg/m³, 80.12 ± 6.53 μg/m³, and 68.85 ± 4.63 μg/m³, respectively (Supplementary Table S3).

Figure 2

Figure 2. PM_2.5 concentrations during the study period. (A) average daily PM_2.5 concentrations; (B) average weekly PM_2.5 concentrations. Values are expressed as mean ± SEM.

3.3 Correlation of lung function with PM_2.5 concentrations

Lung function was primarily measured by FVC, FEV₁, MMEF, PEF, FEF₂₅, FEF₅₀, and FEF₇₅. The majority of these parameters were significantly negatively correlated with PM_2.5 exposure concentrations at lag 1 week except FVC. None of these parameters was significantly correlated with PM_2.5 exposure concentrations at lag 0 week. The majority of these parameters of lung function was not significantly correlated with PM_2.5, and only PEF and PEF₂₅ were significantly correlated with PM_2.5 exposure concentrations at lag 0–1 week (Table 2).

Table 2

Table 2. Correlation between lung function and PM_2.5 exposure concentrations at different periods before health examination^#.

3.4 Percentage changes in lung function

Overall, the majority of the parameters related to lung function was significantly decreased in response to PM_2.5 exposure concentration at lag 1 week in the control group. However, weaker associations with no statistical significance were observed in the Qiju group. Lung function did not vary significantly at lag 0 week and 0–1 week in response to PM_2.5 exposures in either group (Figures 3, 4).

Figure 3

Figure 3. Percentage changes in airway function when adjusted sex and BMI. Percentage changes (mean and 95% confidence intervals) in airway function per 10 μg/m³ increase in PM_2.5 exposure concentrations in the Qiju group and the control group at different lag times were shown. (A) FVC percentage of the predicted value change. (B) FEV₁ percentage of the predicted value change. (C) PEF percentage of the predicted value change. Values are expressed as mean ± SEM. FVC, forced vital capacity; FEV₁, forced expiratory volume in 1 s; PEF, peak expiratory flow.

Figure 4

Figure 4. Percentage changes in small airway function when adjusted sex and BMI. Percentage changes (mean and 95% confidence intervals) in small airway function per 10 μg/m³ increase in PM_2.5 exposure concentrations in the Qiju and the control groups at different lag times were shown. (A) MMEF percentage of the predicted value change. (B) FEF₇₅ percentage of the predicted value change. (C) FEF₅₀ percentage of the predicted value change. (D) FEF₂₅ percentage of the predicted value change. Values are expressed as mean ± SEM. MMEF, maximal mid-expiratory flow; FEF₇₅, forced expiratory flow at 75% of FVC; FEF₅₀, forced expiratory flow at 50% of FVC; FEF₂₅, forced expiratory flow at 25% of FVC.

3.5 Percentage changes in large airway function

As shown in Figure 3, FEV₁ and PEF, which are the major parameters of large airway function, were negatively correlated with PM_2.5 exposure concentrations in the control group at lag 1 week, but not statistically significant in the Qiju group. In the control group, there was an 8.80% (95% CI: 3.54% to 13.74%) decrease in the percentage of estimate FEV₁ and a 7.07% (95% CI: 1.00% to 13.21%) decrease in the percentage of estimate PEF per 10 μg/m³ increase in PM_2.5 at lag 1 week. However, the changes in FEV₁ and FEF were not significant in the Qiju group with only 2.86% (95% CI: −3.45% to 9.77%) and 4.98% (95% CI: −5.82% to 13.21%) decrease in the percentage of estimate FEV₁ and FEF, respectively, at lag 1 week. The association between FVC and PM_2.5 exposure concentrations was not significant at each time point in both groups (Figure 3).

3.6 Percentage changes in small airway function

As shown in Figure 4, MMEF, FEF₇₅, FEF₅₀, and FEF₂₅, which are the major parameters of small airway function, were negatively correlated with PM_2.5 exposure concentrations in the control group at lag 1 week, but not statistically significant in the Qiju group. In the control group, there was 13.07% (95% CI: 7.12% to 19.03%) decrease in the percentage of estimate MMEF, 13.38% (95% CI: 6.12% to 20.30%) decrease in the percentage of estimate FEF₇₅, 12.53% (95% CI: 6.31% to 19.08%) decrease in the percentage of estimate FEF₅₀, and 9.67% (95% CI: 2.95% to 16.26%) decrease in the percentage of estimate FEF₂₅ per 10 μg/m³ increase in PM_2.5 at lag 1 week. However, the changes in these parameters were not significant in the Qiju group with only 3.71% (95% CI: −4.98% to 14.63%), 4.98% (95% CI: −9.06% to 13.47%), 6.81% (95% CI: −1.36% to 17.68%), and 8.84% (95% CI: −1.46% to 19.92%) decrease in the percentage of estimate MMEF, FEF₇₅, FEF₅₀, and FEF₂₅, respectively, at lag 1 week (Figure 4).

3.7 The difference in airway function between groups when PM_2.5 was adjusted

As shown in Figure 5, no parameters of lung function were statistically significant between the Qiju group and the control group at baseline. The difference in lung function parameters between these two groups became greater, and the trend to provide lung health benefits tended to increase in the Qiju group in the 2nd and 4th weeks. However, there were no statistical differences in all time periods (Figure 5).

Figure 5

Figure 5. The difference in airway function between groups when adjusted PM_2.5 concentrations. Different percentages (mean and 95% confidence intervals) in airway function between the Qiju group and the control group in different intervention times (baseline, the 2nd week, and the 4th week). PM_2.5 exposure concentrations were adjusted in the 2nd and 4th weeks. Values are expressed as mean ± SEM. FVC, forced vital capacity; FEV₁, forced expiratory volume in 1 s; PEF, peak expiratory flow; MMEF, maximal mid-expiratory flow; FEF₇₅, forced expiratory flow at 75% of FVC; FEF₅₀, forced expiratory flow at 50% of FVC; FEF₂₅, forced expiratory flow at 25% of FVC.

4 Discussion

In this randomized trial among healthy young adults in Hangzhou, China, we examine lung function benefits of Qiju granules against PM_2.5 exposure at different time periods occurring at lag intervals of 0, 1, or 0–1 week before health examination, which include large airways function (FVC, FEV₁, and PEF) and small airways function (MMEF, FEF₇₅, FEF₅₀, and FEF₂₅). Our major findings include the following: (1) PM_2.5 exposure concentration is associated with reduced lung function parameters, including FEV₁, PEF, MMEF, FEF₇₅, FEF₅₀, and FEF₂₅ in healthy adults. High-level PM_2.5 exposure has a stronger correlation with a decrease in lung function. PM_2.5 may impair small airway function more seriously than large airway function (2). The impact of PM_2.5 on lung function depends on the time lag (3). Qiju granules may alleviate the decrease in lung function after PM_2.5 exposure.

Some studies have reported significantly different sensitivity to air pollution between male and female subjects (18–20), and others have found significant differences in the association between lung function and air pollution according to BMI (6, 21). Guo et al. (6) reported that the association between FEV₁ and air pollution was stronger for the participants with low and normal BMI (BMI < 23 kg/m²). Siddique et al. (21) reported that the association between lung function and air pollution was stronger for both low normal BMI and obese participants compared with normal weight participants. Those studies suggest that sex and BMI may have an impact on the association between lung function and air pollution exposure. Therefore, we used linear mixed-effects models, adjusted sex and BMI to evaluate the association between PM_2.5 exposure concentrations and lung function outcomes within each group at different time periods.

The association between PM_2.5 exposure concentrations and lung health has been investigated in detail. Numerous epidemiology studies provided evidence that PM_2.5 exposure damages lung function (6, 22, 23). A longitudinal cohort study indicates that each 10 μg/m³ increase in PM_2.5 exposure concentrations is associated with decreases in FVC and FEV₁ (6). A cross-sectional study of adults from Shanghai, China has shown that higher PM_2.5 exposure concentrations are significantly associated with lower FVC, IC, and VC (12). PM_2.5 is a main pollutant of ambient air pollution. The adverse effect on lung health is mostly attributed to its smaller particle size, larger surface area, physical characteristics of the particles, and stronger activity. In addition, PM_2.5 may be composed of sulfur dioxide, sulfates, metals, nitrates, acids, and carbon particles with various chemicals adsorbed onto their surfaces (24). A recent study in an animal model demonstrated that PM_2.5 led to easier deposition into lung tissues compared with other pollutants (25). The deposition of PM_2.5 increases the expression of inflammatory cytokine by activating inflammatory-associated cells and triggers oxida-tive stress by impairing the immune balance (25). Some studies indicate that PM_2.5 is a critical factor for overall lung function impairment progression by the regulation of oxidative stress in the lungs and inflammation in mice (26, 27). Hence, anti-oxidation and anti-inflammatory supplementation may protect people from the adverse effects of PM_2.5 on lung function.

Qiju granules are extracted from traditional Chinese herbs, including Rhodiola rosea L. [Crassulaceae], Portulaca oleracea L. [Portulacaceae], Lycium barbarum L. [Solanaceae], Chrysanthemum × morifolium (Ramat.) Hemsl. [Asteraceae] and Siraitia grosvenorii (Swingle) C.Jeffrey ex A.M.Lu & Zhi Y.Zhang [Cucurbitaceae]. Rhodiola rosea L. [Crassulaceae] is often used as a part of the regimen to treat lung disorders. The main constituent of Rhodiola rosea L. [Crassulaceae] is salidroside, which shows attenuation in inflammation and oxidative stress response (12, 13). Portulaca oleracea L. [Portulacaceae] is a nutritious vegetable, which is useful for the prevention of diseases caused by oxidative stress. Lycium barbarum L. [Solanaceae] exhibits anti-oxidative and anti-inflammatory effects by modulating mRNA expression in many diseases (14). Chrysanthemum × morifolium (Ramat.) Hemsl. [Asteraceae] has been widely consumed as tea for centuries. The combinations of Chrysanthemum × morifolium (Ramat.) Hemsl. [Asteraceae] and Lycium barbarum L. [Solanaceae] also possess anti-oxidation and anti-inflammation properties by inhibiting MAPKs and NF-kB pathways (15). Siraitia grosvenorii (Swingle) C.Jeffrey ex A.M.Lu & Zhi Y.Zhang [Cucurbitaceae] has been used as a natural sweetener and as a traditional medicine for the treatment of pharyngitis and tussis. Its active constituents also show anti-oxidative, hypoglycemic, immunologic, anti-tussive, and sputum-reducing efficacy (16). These traditional Chinese herbs are widely used to treat and prevent lung disorders.

Our study demonstrates that exposure to PM_2.5 concentration induced lung function impairment. However, the results indicate that only some lung function parameters are consistent with previous studies. In our study, we find an 8.80% decrease in the percentage of estimate of FEV₁, and a 7.07% decrease in the percentage of estimate of PEF per 10 μg/m³ increase in PM_2.5 exposure concentrations. These results are stronger than those reported in other studies (6, 28). This discrepancy may be attributable to the higher PM_2.5 concentrations in our study time periods. We also measured small airway function parameters, including MMEF, FEF₇₅, FEF₅₀, and FEF₂₅. Only a few previous studies have examined MMEF, FEF₇₅, FEF₅₀, and FEF₂₅. We suggest that those are important parameters of small airway function that are critical in small airway disease development, such as asthma and chronic obstructive pulmonary disease (COPD) (29). In our study, we demonstrated that PM_2.5 exposure concentrations generally had a stronger association with MMEF, FEF₇₅, FEF₅₀, and FEF₂₅ than FEV₁ and PEF. There is a 13.07% decrease in the percentage of the estimate of MMEF, a 13.38% decrease in FEF₇₅, a 12.53% decrease in FEF₅₀, a 9.67% decrease in FEF₂₅ per 10 μg/m³ of increase in PM_2.5 exposure concentration. However, there is only an 8.80% decrease in FEV₁, a 7.07% decrease in PEF, and no significant decrease in FVC. It seems that our findings are consistent with several previous studies (6, 20, 22), which suggest that PM_2.5 may have more serious impacts on small airway function than on large airway function.

Previous studies indicated that PM_2.5 induced a significant delayed effect on population health (6, 23, 30, 31). In our study, we show that most lung function parameters are significantly correlated with weekly average PM_2.5 exposure concentrations of lag 1 week, although other periods of average PM_2.5 concentrations (lag 0 and 0–1 week) are not significantly correlated with most parameters of lung function, which seems different when compared with some previous studies. We assume it may be primarily due to the fact that weekly average PM_2.5 concentrations were applied instead of daily average concentrations in those analyses while lag 1 week average concentrations were much higher than those in other time periods. It suggests that high-level PM_2.5 exposure may have a stronger correlation with lung function, and the impact of PM_2.5 on lung health does have time lags, which could be acute or even lifetime.

Our study also demonstrates that Qiju granules protect against PM_2.5 induced lung function impairment, especially in small airway functions. In the control group, FEV₁, PEF, MMEF, FEF₇₅, FEF₅₀, and FEF₂₅ were significantly decreased when PM_2.5 exposure concentrations were increased. However, this did not happen in the Qiju group when PM_2.5 exposure concentrations were increased, which suggests that Qiju may have a preventive effect on small airway functions against PM_2.5 exposure-related injury. This reason may be due to the active constituents of Qiju granules being able to attenuate inflammation, oxidative stress, and fibrosis response, protecting people from the adverse effects of PM2.5 on lung function. We also compare the change in parameters of lung function between the Qiju group and the control group when adjusting the PM_2.5 exposure concentrations. Our data demonstrate that the majority of lung function parameters are slightly higher in the Qiju group than in the control group in the 2nd week and 4th week. Unfortunately, there is no significant difference between the two groups in all lung function parameters during these time periods. This could be attributed to our limited enrollment size (40) along with the brief duration of the study (4 weeks), which might not provide sufficient power to demonstrate any further potential lung function benefits.

5 Strengths

This study has several strengths. The first strength of the study is reducing the effects of psychological and other confounding factors on outcomes by double-blinded and placebo control. The second strength of the study is monitoring PM_2.5 exposure concentrations with personal and portable devices, rather than estimating exposures based on outdoor monitors, are precise real-time personal exposures and variation range of exposures for regression analysis. The third strength of the study is that it is conducted among healthy college students on campus, rather than in an exposure-controlled environment, which is closer to real-world situations where local residents live. The fourth strength of the study is that the participants are healthy college students, who are a vulnerable population to PM_2.5 exposure (32). In addition, the season of the study period has relatively high PM_2.5 concentrations, which occur frequently in major cities in China and in other developing countries. It has enabled us to obtain stable and precise estimates. Finally, we analyze numerous lung function parameters, including large and small airway function parameters, and use mixed-effects models, adjusting sex and BMI to evaluate PM_2.5 exposure in relation to lung functions. It provides more stable and reliable results.

6 Limitations

This study also has several limitations. The first limitation is the study sample, comprising only 20 participants per group, which consisted of healthy individuals within a relatively ideal experimental setting. Thus, caution should be exercised when generalizing these findings to the broader population and real-world contexts. The second limitation is that healthy adults may be less susceptible to the adverse effects of PM_2.5 exposure on lung dysfunction and respiratory disorders compared with vulnerable populations, such as children and seniors. The lung function benefits from Qiju granules await further verification with more susceptible and diverse populational studies. The third limitation is that other air pollutants, such as SO₂, NO₂, and Ozone, and meteorological parameters, including temperature and humidity, are not collected and analyzed. Therefore, we cannot distinguish the association between PM_2.5 and lung dysfunction due to PM_2.5 specifically or in conjunction with other air pollutants and meteorological factors. Finally, although we adjust sex and BMI for the association between PM_2.5 and lung function, more confounding factors, such as behavior, diet, and living environment, should be considered in future studies.

7 Conclusion

In summary, PM_2.5 exposure is associated with reduced lung function parameters. Qiju granules significantly alleviate the decrease in lung function after PM_2.5 exposure, which may be effective in protecting lung health against adverse effects of PM_2.5 exposure.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

The studies involving humans were registered in Chinese Clinical Trial Registry (ChiCTR1900021235) on 13 February 2019 and was approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang Chinese Medical University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

RC: Writing – original draft. LuZ: Writing – original draft. WG: Writing – original draft. RL: Writing – original draft. HH: Writing – original draft. LiZ: Writing – original draft. JZ: Writing – original draft. YW: Writing – original draft. PN: Writing – original draft. SX: Writing – original draft. ZW: Writing – review & editing. QS: Writing – review & editing. CL: Writing – review & editing. JY: Writing – review & editing.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Natural Science Foundation of China (grant number 82004143), Education Project of Zhejiang Province (grant number Y202045128), Key R&D International Cooperation Projects (grant number 2019YFE0114500), Medical Health Science and Technology Project of Zhejiang Province (grant numbers 2019KY471 and 2018KY545), and Foundation of Zhejiang Chinese Medical University (grant number 2019ZZ04).

Acknowledgments

The authors gratefully acknowledge all volunteers who participated in this study.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmed.2024.1370657/full#supplementary-material

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