Associations Between Systemic Inflammation, Lung Function, and Respiratory Symptoms in Wildland Firefighters in Northern Thailand

Singkaew PANNAWADEE; Pudpong PUNYISA; Tonchoy PRAKASIT; Kantow SUPAKAN; Kloypan CHIRAPHAT

doi:10.7888/juoeh.47.191

Abstract

Wildland firefighters are at risk of respiratory impairment and systemic inflammation. However, integrated assessments of inflammatory biomarkers, lung function, and symptoms are limited, especially among Thai firefighters. This study aimed to examine the associations between inflammatory biomarkers, lung function, respiratory symptoms, and related health factors in wildland firefighters in Northern Thailand. This cross-sectional study surveyed 146 wildland firefighters from eight Phayao stations using interviewer-administered questionnaires, including a Thai-adapted ATS-DLD-78-A questionnaire to assess demographics, lifestyle, health, work factors, and respiratory symptoms. High-sensitivity C-Reactive Protein (hs-CRP) levels, fractional exhaled nitric oxide (FeNO), and Pulmonary function (FVC%-predicted, FEV₁%-predicted, FEV₁/FVC%, FEF_25–75%-predicted) were measured. Data were analyzed using Mann–Whitney U, Kruskal–Wallis, and Spearman’s correlation tests. Median hs-CRP was 1.44 µg/l, and median FeNO was 11.83 ppb. Significant positive associations were identified between hs-CRP levels and BMI (P=0.003) and FeNO (P<0.001). Lung function parameters (FVC%-predicted, FEV₁%-predicted, FEF_25–75%-predicted) were negatively correlated with hs-CRP levels (P<0.05). Elevated hs-CRP and reduced lung function were significantly associated with increased respiratory symptoms (P<0.05). Lifestyle factors, such as smoking and alcohol, were not significantly associated with hs-CRP. This study highlights associations between systemic inflammation, lung function decline, and respiratory symptoms in wildland firefighters, emphasizing the need for integrated biomarker and lung function monitoring for early detection in occupational health surveillance.

Introduction

Wildland firefighters in Northern Thailand face significant health risks because of their exposure to hazardous pollutants such as particulate matter (PM), specifically PM2.5 and PM10, during wildfire suppression activities [1]. Prolonged exposure to PM2.5 has been associated with a higher risk of lung cancer and heart-related mortality [2], while short-term exposure may worsen disorders such as asthma and chronic obstructive pulmonary disease (COPD) [3]. Furthermore, acute exposure to wildfire smoke increases the likelihood of hospitalization for respiratory and cardiovascular disorders [4].

PM2.5 can enter the bloodstream, causing lung inflammation and vascular dysfunction via oxidative stress [5]. The mechanism of oxidative stress is induced by the generation of reactive oxygen species (ROS) from cellular sources such as the mitochondria and nicotinamide adenine dinucleotide phosphate (NADPH) oxidases, while antioxidant depletion exacerbates damage, leading to inflammation and lung toxicity [6]. Systemic inflammatory markers such as fibrinogen and C-reactive protein (CRP) become elevated, increasing the risk of chronic systemic inflammation and cardiovascular disease [7].

High-sensitivity C-Reactive Protein (Hs-CRP) is a key marker for assessing chronic health risks from repeated environmental exposure [8]. Another relevant biomarker, fractional exhaled nitric oxide (FeNO), serves as a biomarker of airway inflammation. Elevated FeNO levels have been linked to increased inflammatory responses after short-term exposures to PM2.5 and nitrogen dioxide (NO2) [9, 10]. Combined hs-CRP and FeNO measurements are critical for assessing systemic and airway responses to wildfire smoke in wildland firefighters.

The lung function indices Forced vital capacity (FVC)%-predicted and Forced expiratory volume in the first second (FEV1)%-predicted serve as essential gauges of respiratory health. A decline in the cross-shift FEV1 in firefighters exposed to high PM levels has indicated the acute effects of smoke [11]. Repeated PM exposures exacerbate airway inflammation and lead to decreased lung function [12, 13] and elevated respiratory symptoms such as coughing, wheezing, and dyspnea, coupled with small airway dysfunction [1].

Lifestyle factors such as smoking, alcohol use, and the role of exercise in a person’s life may also affect hs-CRP levels, but they remain understudied in wildland firefighters. Most existing studies emphasize pollution’s direct effects but overlook interactions with individual behaviors and occupational stressors [14–16]. These gaps highlight the need for more extensive research focused on how lifestyle, health, and work-related variables correlate with hs-CRP levels and broader health outcomes in wildland firefighters. This study addresses these gaps by examining the associations among hs-CRP levels, lifestyle factors (i.e., smoking, alcohol consumption, and exercise habits), health and work-related factors, and environmental exposures, as well as the relationships between hs-CRP levels, FeNO levels, lung function parameters, PM measurements, and respiratory symptoms in Northern Thai wildland firefighters.

Material and Methods

Study participants

This cross-sectional study was conducted from April to mid-May 2021 and included regular and seasonal male wildland firefighters from eight forest fire control stations (FFCSs) across all nine districts in Phayao province, Thailand. It was based on a population of 340 firefighters and an estimated 21% prevalence of elevated hs-CRP (>3 mg/l) reported in a previous study [17]. The required sample size was calculated as 146 by Krejcie and Morgan’s formula [18], with a 5% margin of error and 95% confidence level.

Participants were selected through proportional stratified random sampling, ensuring representation from each FFCS. The sample was proportionally allocated based on station size, followed by simple random sampling within each station to ensure equal selection probability. The inclusion criteria were: age more than 20 years, at least one year of employment, participation in at least one firefighting operation during data collection, and provision of informed consent. Exclusion criteria included physician-diagnosed asthma, recurrent wheezing before the age of ten, a family history of asthma, or an inability to perform valid spirometry. Ethical approval was obtained from the University of Phayao Human Research Ethics Committee (project no. 1.3/008/63), and written informed consent was secured from all participants.

Instruments and measurements

Data were collected by the research team at each FFCS using an interviewer-administered questionnaire with the following sections: (a) demographic, health, and work characteristics, including age, weight, height, underlying diseases, smoking status, alcohol consumption, exercise habits, work experience, and wildfire suppression duration; (b) respiratory symptoms were assessed using the Thai version of the ATS-DLD-78-A questionnaire [19], which includes structured yes/no items across six domains: cough, phlegm, cough with phlegm, wheezing, shortness of breath, and chest tightness. Participants were classified as symptomatic in a given domain if they answered “yes” to at least one key item. Cough and phlegm were identified based on frequent or persistent symptoms, including those occurring in the morning or at night. Cough with phlegm was recorded if both symptoms persisted for at least three consecutive weeks. Wheezing was noted when reported during colds, cold weather, or throughout the day or night. Shortness of breath was determined from breathlessness while walking, climbing, or dressing. Chest pain or tightness was recorded if associated with respiratory infections or exertion. All questionnaires were administered by trained interviewers, and ambiguous responses were conservatively coded as “no.”

Measurements of particulate matter (PM2.5 and PM10)

PM2.5 and PM10 were measured using the Aerocet 531S (Met One Instruments, Inc. OR). The Aerocet 531S is an advanced handheld mass meter and particle counter that can simultaneously measure the mass concentration ranges. Air leaks or contaminants in the particle sensor might lead to faulty counts, particularly in low-particle environments. A zero-count test was conducted to verify correct functionality before each measurement.

Pulmonary function test

Spirometry was performed on all subjects using a spirometer (FIM Model Q13, FIM Medical, Lyon, France). The parameters measured included FVC, FEV1, mid-forced expiratory flow (FEF25–75%), and the FEV1/FVC ratio, with predicted values calculated using the Thai Siriraj equation [20]. Participants practiced the spirometry procedure without equipment before the actual test to ensure comfort and accurate data collection.

High-sensitivity C-Reactive Protein (hs-CRP)

Blood samples were collected aseptically by a licensed technologist via venipuncture into 6 ml sterile tubes, mixed with stabilizer, and frozen at –20°C until analysis. The hs-CRP levels were measured using immunonephelometric assays, a sensitive method for detecting low-grade systemic inflammation.

Fractional exhaled nitric oxide (FeNO) measurement

FeNO levels were assessed in all participants following the ATS/ERS guidelines, utilizing the Quark NO breath analyzer (COSMED Srl, Italy) [21]. Participants inhaled fully and exhaled steadily at 50 ml/s for 12 seconds while maintaining flow within the target range. The analyzer was calibrated automatically by the system software before each test. To ensure the accuracy of the FeNO measurements, participants were advised to avoid eating, drinking, or engaging in vigorous physical activity for at least two hours prior to the test.

Data analysis

Statistical analyses were performed using SPSS version 28 (IBM Corp. NY). Continuous variables were represented as medians with 10th–90th percentiles, and categorical variables as frequencies and percentages. Mann–Whitney U and Kruskal–Wallis tests were used to compare hs-CRP across groups. Spearman’s rank correlation was used to assess associations between hs-CRP and the continuous variables. A two-sided P-value < 0.05 was considered statistically significant.

Results

The wildfire fighters in the study had a median age of 38.50 years, with a body mass index (BMI) of 24.07 kg/m² and a median weight of 67.55 kg. The median oxygen saturation was 98.00%, while the median diastolic and systolic blood pressures were 89.00 mm Hg and 136.00 mm Hg, respectively. Among the participants, 54.80% were smokers, 80.10% consumed alcohol, and 77.40% engaged in regular exercise. A history of cardiovascular disease was reported by 18.50%, and 9.60% had current hypertension.

In terms of occupational experience, the median years of work experience was 8, and the median time spent on wildfire suppression was 4 hours. The median FeNO level was 11.83 ppb. Lung function values for FVC%-predicted, FEV1%-predicted, FEV1/FVC%, and FEF25–75%-predicted were 97.86%, 100.42%, 82.26%, and 89.88%, respectively. The median hs-CRP level was 1.44 µg/l, while the median PM2.5 and PM10 concentrations were 48.49 µg/m³ and 95.00 µg/m³, respectively, as shown in Table 1.

Table 1. Baseline Characteristics of Study Participants (n = 146)

Variable	n = 146
Age (years)	38.50 (24.00, 54.00)^a
Body mass index (kg/m²)	24.07 (19.91, 29.76)^a
Weight (kg)	67.55 (55.35, 84.44)^a
Oxygen saturation (%)	98.00 (97.00, 99.00)^a
Diastolic blood pressure (mm Hg)	89.00 (74.00, 105.00)^a
Systolic blood pressure (mm Hg)	136.00 (116.00, 157.00)^a
Current smoker, n (%)	80 (54.80)
Current alcohol consumption, n (%)	117 (80.10)
Regular exercise, n (%)	113 (77.40)
History of cardiovascular disease, n (%)	27 (18.50)
Current hypertension, n (%)	14 (9.60)
Work experience (years)	8 (1.00, 23.00)^a
Duration of wildfire suppression (Hr)	4 (2.50, 6.50)^a
FeNO (ppb)	11.83 (4.00, 32.00)^a
FVC%-Predicted	97.86 (80.25, 113.82)^a
FEV1%-Predicted	100.42 (81.84, 116.94)^a
FEV1/FVC%	82.26 (79.32, 85.08)^a
FEF25–75%-Predicted	89.88 (61.91, 123.47)^a
High-sensitivity C-reactive protein (µg/l)	1.44 (0.28, 9.16)^a
PM2.5 concentration (ug/m³)	48.49 (36.91, 96.79)^a
PM10 concentration (ug/m³)	95.00 (81.95, 156.59)^a

^aMedian and 10th, 90th percentiles.

The hs-CRP levels were significantly positively correlated with BMI (rs = 0.247, P = 0.003), FeNO (rs = 0.298, P < 0.001), PM2.5 (rs = 0.315, P = 0.008), and PM10 (rs = 0.265, P = 0.027). Additionally, lung function variables such as FVC%-predicted, FEV1%-predicted, and FEF25–75%-predicted were negatively associated with hs-CRP (Table 2).

Table 2. Associations between hs-CRP Concentration and Selected Physiological and Environmental Variables age and selected environmental and function parameters

Variables	rs*	P Value
Age (years)	0.117	0.161
BMI	0.247	0.003
Oxygen saturation (%)	–0.075	0.366
FeNO (PPB)	0.298	<0.001
FVC%-Predicted	–0.228	0.006
FEV1%-Predicted	–0.248	0.003
FEV1/FVC%	–0.106	0.202
FEF25–75%-Predicted	–0.188	0.023
PM2.5 concentration	0.315	0.008
PM10 concentration	0.265	0.027

*Spearman’s rank correlation coefficient. hs-CRP: High-sensitivity C-Reactive Protein, FeNO: Fractional exhaled nitric oxide, FVC: Forced vital capacity, FEV1: Forced expiratory volume in the first second, FEF25-75%: mid-forced expiratory flow.

Significant associations were found between hs-CRP levels and variables such as age (P = 0.020), BMI (P = 0.015), FeNO (P = 0.005), and lung function parameters, including FVC%-predicted, FEV1%-predicted, and FEF25–75%-predicted (P < 0.050). Additionally, higher concentrations of PM2.5 and PM10 were associated with increased hs-CRP (P = 0.003 and P = 0.004, respectively), as demonstrated in Table 3.

Table 3. Associations between hs-CRP Concentration and Demographic, Physiological, Lung Function, and Environmental Variables

Variables		hsCRP (µg/l)					P Value
Variables		N	Median	Min.	Max.	IQR	P Value
Age	≤30 years	47	0.940	0.100	15.01	2.240	0.020*
Age	>30 years	99	1.780	0.110	18.710	3.270	0.020*
BMI	Underweight and Normal (<18.5, 18.5-22.9)	59	0.910	0.110	18.820	2.240	0.015*
	Overweight (23.0-24.9)	26	1.705	0.170	15.010	5.820
	Obesity (≥25.0)	61	1.770	0.100	18.440	3.280
Oxygen saturation	≤95%	8	1.720	0.180	5.610	4.460	0.770
Oxygen saturation	96-100%	138	1.435	0.100	18.820	3.080	0.770
FeNO	<25	119	1.180	0.100	15.010	2.210	0.005*
FeNO	≥25	27	2.370	0.320	18.820	12.730	0.005*
FVC%-Predicted	≤95.0	59	2.030	0.110	18.440	4.250	0.009
FVC%-Predicted	>95.0	87	1.070	0.100	18.820	1.980	0.009
FEV1%-Predicted	≤95.0	52	1.855	0.110	16.120	3.620	0.039*
FEV1%-Predicted	>95.0	94	1.135	0.100	18.820	2.130	0.039*
FEV1/FVC%	≤80.0	21	1.210	0.170	18.820	3.760	0.834
FEV1/FVC%	>80.0	125	1.630	0.100	18.440	3.170	0.834
FEF25–75%-Predicted	≤80.0	54	2.310	0.110	16.120	3.800	0.047*
FEF25–75%-Predicted	>80.0	92	1.155	0.100	18.820	1.970	0.047*
PM2.5 concentration	≤37.5	15	0.590	0.100	4.630	1.400	0.003*
PM2.5 concentration	>37.5	131	1.650	0.110	18.820	3.470	0.003*
PM10 concentration	≤120.0	122	1.195	0.100	15.010	2.150	0.004*
PM10 concentration	>120.0	24	3.345	0.170	18.820	8.170	0.004*

* Mann–Whitney U test; ** Kruskal–Wallis one-way analysis of variance. hs-CRP: High-sensitivity C-Reactive Protein, FeNO: Fractional exhaled nitric oxide, FVC: Forced vital capacity, FEV1: Forced expiratory volume in the first second, FEF25-75%: mid-forced expiratory flow.

Significant differences were identified between individuals with and without respiratory symptoms. Participants with respiratory symptoms exhibited elevated hs-CRP levels (P = 0.015) and reduced lung function, as indicated by lower FVC%-predicted (P = 0.035), FEV1%-predicted (P = 0.008), FEV1/FVC% (P = 0.003), and FEF25–75%-predicted (P = 0.022), as shown in Table 4.

Table 4. Associations between Respiratory Symptoms and hs-CRP Concentration, FeNO, and Lung Function Variables

Variables	Present (98)				Absent (48)				P Value
Variables	Median	Min.	Max.	IQR	Median	Min.	Max.	IQR	P Value
hsCRP (µg/l)	1.790	0.140	18.440	4.350	1.135	0.100	18.820	1.060	0.015
FeNO (PPB)	12.000	1.330	51.670	16.580	11.333	1.330	48.330	11.000	0.579
FVC%-Predicted	96.330	60.180	131.430	16.450	101.840	35.980	160.660	22.05	0.035
FEV1%-Predicted	97.950	58.760	129.27	16.31	103.785	25.100	194.940	21.36	0.008
FEV1/FVC%	82.956	78.450	86.600	3.480	81.543	74.880	85.220	2.840	0.003
FEF25–75%-Predicted	83.843	33.860	142.210	34.73	97.355	39.340	192.560	24.580	0.022

* Mann–Whitney U test. hs-CRP: High-sensitivity C-Reactive Protein, FeNO: Fractional exhaled nitric oxide, FVC: Forced vital capacity, FEV1: Forced expiratory volume in the first second, FEF25-75%: mid-forced expiratory flow.

The box plots in Figure 1 demonstrate an association between an increasing number of respiratory symptoms and elevated inflammatory markers (hs-CRP and FeNO), along with declines in lung function parameters (FVC%-predicted, FEV1%-predicted, and FEF25–75%-predicted). Participants reporting no symptoms consistently exhibited better lung function and lower levels of inflammation. In contrast, participants in the “4 or more” group showed significantly lower lung function and higher inflammatory markers.

Figure 1. Distributions of hs-CRP (μg/l), FeNO (ppb), and lung function parameters (% predicted) across categories of self-reported respiratory symptoms (0 = Absent, 1-3, and ≥4 symptoms). Brackets indicate group comparisons between asymptomatic and sympomatic participants using Mann-Whitney U tests.

Discussion

This study found a significant association between hs-CRP levels and certain key factors, including BMI, airway inflammation (FeNO levels), air pollution (PM2.5 and PM10 measurements), and lung function parameters (FVC%, FEV1%, and FEF25–75%). These findings suggest that systemic inflammation may be associated with poorer respiratory health.

A significantly positive correlation was observed between BMI and hs-CRP test levels. This finding supports the hypothesis that obesity drives systemic inflammation by releasing pro-inflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor (TNF-α) from adipose tissue; these cytokines stimulate the hepatic production of CRP [22]. Similar results have been reported in Thailand [23], especially in those with central obesity or metabolic syndrome, who have shown elevated hs-CRP levels.

Our results showed that the FeNO level was positively correlated with the hs-CRP values (rs = 0.298, P < 0.001). PM rapidly irritates the respiratory system, inducing oxidative stress and airway inflammation. FeNO levels may increase within hours of PM exposure [9]. Furthermore, PM can elevate hs-CRP levels by inducing systemic immune responses and oxidative stress [24]. Wildland firefighters who had FeNO levels of 25 ppb or higher had higher hs-CRP levels than the group who had FeNO levels of less than 25 ppb, with a P-value of 0.005. This was especially the case with exposure to high concentrations of PM2.5, PM10, CO, and CO2 in forest firefighters [25, 26].

However, this study also found that hs-CRP levels were higher in participants with respiratory symptoms, and that this increase was significant (P = 0.015), while the FeNO levels were different but the difference was not significant (P = 0.579). These results suggested that symptoms were likely caused by non-specific airway inflammation or PM irritation rather than eosinophilic inflammation. This was consistent with ATS guidelines, which indicate that FeNO levels below 25 ppb do not reflect eosinophilic airway inflammation [27].

Our analysis identified a significant inverse association between hs-CRP levels and pulmonary function parameters (FVC, FEV1, and FEF25-75%). Elevated hs-CRP levels were associated with reduced FVC%-predicted and FEV1%-predicted values, particularly with levels of 95% or lower, and this highlighted a possible association between systemic inflammation and reduced lung function. These findings align with prior research [11], which revealed that structural firefighters with hs-CRP levels in the highest quartile (Q4 > 2.48 mg/l) had significantly reduced lung function compared with those in the lowest quartile (Q1 ≤ 0.57 mg/l). The mean FVC%-predicted declined from 104% to 94.8% and the FEV1%-predicted from 99.4% to 93.3% in these firefighters [1]. Elevated hs-CRP levels were associated with a lower level and greater decline in lung function over time in the general population [28]. Additionally, our study revealed a significant inverse correlation between hs-CRP levels and the FEF25–75%-predicted, suggesting that elevated hs-CRP levels may indicate occupational- or environmental-related small airway impairment.

This study showed a significant dose–response relationship between PM2.5 and PM10 exposure and elevated hs-CRP levels, indicating systemic inflammation without clinical symptoms. The findings align with previous studies showing that small increases in the PM2.5 (3.70 µg/m³) were linked to a 3.68% rise in hs-CRP levels and a higher risk of hs-CRP levels exceeding 3 mg/l (OR = 1.08) [29].

In contrast to urban populations with prolonged exposure to low PM levels, wildland firefighters face exposure to high PM levels over the short-term during wildfire suppression. Although area sampling was used to estimate PM2.5 and PM10 concentrations, actual personal exposure during wildfire suppression likely exceeded these ambient levels, averaging 1,430 µg/m³ during prescribed burns [30]. This discrepancy, which can vary depending on task, location, and duration of activity, may have resulted in exposure misclassification and influenced the observed association with hs-CRP levels [25]. Future studies should incorporate personal monitoring techniques to better capture individual-level exposure and improve the accuracy of exposure–response analysis.

Although age was not directly correlated with hs-CRP levels, participants over 30 years of age had higher levels, suggesting that their early inflammation was possibly due to age-related cellular decline. Prior studies reported higher hs-CRP levels among individuals over 45 years of age compared with younger adults (1.31 [0.69–2.75] mg/l vs. 1.05 [0.53–2.16] mg/l, P < 0.001), suggesting a progressive increase in inflammation with age [31, 32]. Our findings imply that this process may start in young adulthood, especially in persons with high-risk jobs. Older wildland firefighters consistently had higher hs-CRP levels than younger ones, likely because they had experienced heat many times, and its effects had been cumulative, and because of long-term PM exposure [33].

The findings of this study suggest a notable link between elevated hs-CRP levels and respiratory symptoms in wildland firefighters, with symptomatic individuals having higher median hs-CRP levels (1.790 µg/l vs 1.135 µg/l). PM can activate epithelial cells and alveolar macrophages, inducing the secretion of pro-inflammatory cytokines such as IL-6 and TNF-α, which in turn promote the synthesis of hs-CRP in the liver [34]. An increase in hs-CRP levels may be linked to signs of airway injury such as epithelial damage, mucus overproduction, and bronchoconstriction, and this contributes to respiratory symptoms and lung function decline [35].

Symptomatic participants exhibited significantly lower FVC%-predicted and FEV1%-predicted values, indicating reductions in both lung volume and expiratory flow; this was likely due to inflammation-related airway remodeling, mucus retention, and reduced compliance. These findings align with those of an Indonesian study in which prolonged smoke exposure in firefighters led to increases in productive cough, dyspnea, wheezing, and restrictive patterns (FVC < 80%-predicted) [36]. Our study found that the FEV1/FVC% ratio was within normal limits but was significantly higher in symptomatic individuals (82.96% vs. 81.54%). This unexpected increase may have resulted from a disproportionately greater decline in FVC, potentially concealing early restrictive or mixed patterns associated with airway inflammation. Supporting this, a prior study showed that a twofold increase in lower respiratory symptom scores was associated with a reduction in the FEV1/FVC% ratio, indicating subtle ventilatory changes [37].

The most marked difference was observed in the FEF25–75%-predicted, a key indicator of small airway function; it was significantly reduced in the symptomatic participants (83.8% vs 97.4%). Small airways, which lack cartilage and are thinly lined, are susceptible to the effects of smoke; prolonged PM exposure causes epithelial loss, mucus buildup, and thickening, which narrow the airways and reduce airflow. Even when normal spirometry testing shows no obvious obstruction, a lower FEF25-75% may indicate early small airway dysfunction. Our findings are consistent with those of a previous study [38], which reported short-term declines in the FEV1 and FEF25–75% in firefighters with no existing respiratory conditions who were exposed to house fire smoke.

This study had several strengths that enhanced its credibility and comprehensiveness. First, it focused on wildland firefighters in northern Thailand, who are a high-risk group directly exposed to wildfire smoke, which makes the findings highly relevant for occupational health policies. We integrated findings on lung function, airway inflammation, and systemic inflammation to provide a comprehensive view of the impact of wildfire smoke on health. Another strength was the study’s multifaceted assessment of firefighter health, integrating pulmonary function (FVC, FEV1), FeNO levels, hs-CRP levels, and respiratory symptoms. Lastly, the use of standardized instruments and The American Thoracic Society/European Respiratory Society (ATS/ERS) guidelines ensured accurate, reliable data and minimized measurement bias, enhancing the findings’ relevance for occupational and firefighter health research.

Although this study provided valuable findings, several limitations should be noted. First, its cross-sectional design limited the ability to infer causality between exposure and health effects. Second, the relatively small sample size may have limited the generalizability of the findings beyond Northern Thailand and reduced their statistical power. Replication in more diverse or larger populations is recommended to validate these findings. Finally, multivariable analyses adjusting for potential confounders (e.g., age, BMI, smoking) were not performed, limiting the interpretation of independent associations.

Conclusion

This study demonstrated that systemic inflammation, as indicated by elevated hs-CRP levels, was associated with age, BMI, FeNO levels, and reduced lung function, which may suggest a relationship with wildfire smoke exposure. However, due to the cross-sectional design of this study, causal inferences could not be drawn. Further longitudinal studies are warranted to clarify the temporal and causal links among these variables. Common respiratory symptoms further support the presence of airway involvement. These findings emphasize the need for integrating biomarkers and lung function tests into routine health monitoring of firefighters to support early detection and prevention of lung damage.

Acknowledgments

We sincerely thank all participants for their time and involvement. This study was funded by the School of Public Health, University of Phayao, under Grant Number PHUP 03/2565.

Conflict of Interest

All authors declare they have no potential competing interest.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Author Contributions

Conceptualization: Pannawadee Singkaew, Punyisa Pudpong

Methodology: Pannawadee Singkaew, Punyisa Pudpong

Investigation: Pannawadee Singkaew, Supakan Kantow, Punyisa Pudpong, Chiraphat Kloypan

Data curation: Pannawadee Singkaew, Prakasit Tonchoy

Formal analysis: Prakasit Tonchoy, Pannawadee Singkaew

Writing – original draft: Pannawadee Singkaew, Punyisa Pudpong

Writing – review & editing: Prakasit Tonchoy, Supakan Kantow, Chiraphat Kloypan

Funding acquisition: Pannawadee Singkaew

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