The effects of bushfire smoke exposure on oxidative stress and inflammatory biomarkers: a systematic review

Bushfire smoke as a global health challenge

Bushfire smoke (BFS) has emerged as a significant public health concern, particularly as climate change intensifies the frequency and severity of bushfires worldwide [1], [2], [3], [4]. These fires release a complex mixture of gases and particles, including particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NOx), volatile organic compounds (VOCs), water vapor, organic debris, and minerals from incomplete combustion [5], 6].

The public health burden of BFS is substantial. During the 2019–2020 Black Summer bushfires in Australia, BFS has been estimated to be responsible for more than 417 excess deaths, over 2000 hospitalizations for respiratory and cardiovascular diseases, and more than 1,300 emergency departments visits for asthma [4]. Similar patterns have been observed worldwide. In the western United States (U.S), BFS events caused spikes in respiratory morbidity, cardiovascular admissions, and premature deaths [7], [8], [9]. Transboundary event further worsened the problem. For example, the 2023 Canadian wildfires caused significantly elevated levels of PM2.5 in the U.S, exposing 354 million population in North America and Europe to hazardous air quality [10].

The burden is particularly severe in low-and middle-income countries (LMICs), where povert and poor health infrastructure exacerbate vulnerability [11]. Long-term exposure to PM and NO2 has been associated with reduced lung function and higher prevalence of chronic obstructive pulmonary disease (COPD) [12]. Emergency visits for respiratory infections are more common in low-income populations [11], and climate-driven increases in bushfires are projected to further raise PM2.5-related mortality in LMICs [13].

Known health effects of bushfire smoke exposure

BFS contribute a substantial proportion of ambient PM2.5, which is considered more toxic than PM2.5 from other sources [13]. Global average exposure to PM2.5 from BFS increased by 65 % between year 2000 and 2021, exposing a greater proportion of the world’s population to elevated health risks [13]. Acute exposure has been linked asthma exacerbations, and COPD flare-ups, reduced attention in adults, and higher risk of hospitalizations and mortality [1], 3], [6], [7], [8], [9, [12], [13], [14], [15], [16], [17], [18].

Long-term exposure to BFS is also increasingly recognized. Prolonged BFS exposure has been associated with cognitive decline, increased risk of stroke, and cardio-respiratory diseases, cancer, and neurodegenerative diseases such as dementia and Parkinson’s diseases [15], [18], [19], [20], [21]. Pregnant women exposed to BFS have higher risks of low birth weight and preterm birth [22], [23], [24], [25]. Elderly, people with pre-existing conditions, and socioeconomically disadvantaged groups are particularly vulnerable [12], 15], 26], 27]. Outdoor workers, especially firefighters, are likely to be exposed to higher levels which increases the risks of adverse health effects [3], 6], 28], 29]. Children and adolescents are also vulnerable, with respiratory-related morbidities being a major concern in this population [13], 30], 31].

These findings demonstrate that BFS exposure either in short-term or long-term cause significant health effects to human, especially among vulnerable populations. This broad spectrum of health effects underscores the importance of investigating the biological pathways, particularly oxidative stress and inflammation that may explain these outcomes.

Biological mechanism: oxidative stress and inflammation

While BFS has drawn attention due to its substantial risks to the human health, research is increasingly focusing on the biological mechanisms underlying the health effects caused by exposure to BFS, particularly oxidative stress and inflammation [32], [33], [34], [35], [36], [37]. Oxidative stress and inflammatory responses occurs when there is an imbalance between the production and buildup of reactive oxygen species (ROS) in cells and tissues and the capacity to detoxify or neutralize these reactive molecules [14], 38]. These processes are fundamental to the pathophysiology of many health conditions linked to air pollution exposure, including respiratory, cardiovascular, cerebrovascular damage, and neurological diseases [17], 21], 37], 39].

Particulate matter from BFS has been found to be more toxic to lung cells than PM from vehicle emissions, inducing greater oxidative stress, triggering systemic inflammation, alterations to the immune system, and increased susceptibility to various diseases and infections [1], 6], 14], 15], 37], 39]. BFS also contains immune-toxic components including VOCs, and polyaromatic hydrocarbons (PAHs) which deplete antioxidants like ascorbate and glutathione and elevates levels of inflammatory cytokines [37], 40], 41]. These processes generate airway and systemic inflammation, reinforcing oxidative stress as a key driver of health impacts.

Importance of biomarkers in environmental health research

Biomarkers of oxidative stress and inflammation provide measurable indicators of early physiological disruption and offer mechanistic evidence linking BFS exposure to health outcomes [14], 19], 37], 42]. They allow comparisons across populations and exposure settings, and help identify vulnerable groups. For example, studies on biomass smoke exposure have reported elevated levels of inflammatory cytokines such as interleukin-6 (IL-6), interleukin-8 (IL-8), and tumor necrosis factor-alpha (TNF-α), as well as lipid peroxidation markers such as 8-isoprostane and malondialdehyde (MDA), and DNA damage markers such as 8-hydroxy-2′-deoxyguanosine (8-OHdG) [37], 41], 43], 44]. These biomarkers provide insight into distinct pathways of oxidative injury, which are implicated in the onset of respiratory and cardiovascular diseases [30], 38], 45], 46].

Understanding the effects of BFS on the biomarkers could help to protect the health and safety of population at risks to the acute or chronic health effects of to BFS exposure. These biomarkers provide mechanistic evidence linking BFS exposure to disease outcomes and highlight the biological plausibility of observed epidemiological associations. Although studies have demonstrated the effects of BFS on health, the existing literature mediated through oxidative stress and inflammatory biomarkers are limited. Many studies specifically address other than BFS such as biomass smoke and fuel, making it unclear if the findings can be generalized to BFS contexts. To our knowledge, there is no comprehensive review to examine the impact of BFS on biomarkers of oxidative stress and inflammation across diverse populations. Thus, this review aims to address this gap by synthesizing current knowledge on this topic. By integrating epidemiological and mechanistic evidence, this review provides a novel and timely synthesis that advances understanding of the biological effects of BFS exposure and offers a roadmap for future studies and health interventions.

Search strategy and selection criteria

A total of 734 documents were identified from the search, in which 373 duplicates were removed by Covidence or manually. We screened 361 titles and abstracts for inclusion and retrieved 45 documents for full-text review. Fourteen studies met the inclusion criteria and were reviewed. This process is shown in Figure 1.

Figure 1:

Identification of studies via databases using PRISMA flow diagram.

This systematic review adopted Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement that includes new reporting guidance in methods to identify, select, appraise, and synthesize studies [47]. A review protocol was developed and registered with PROSPERO (ID: CRD42024554409). Population, exposure, comparator, and outcomes (PECO) elements were followed for the inclusion criteria: (i) population: studies conducted in humans including children, adults, firefighters, and pregnant women. (ii) exposure: studies that evaluated the effects of BFS. (iii) comparator: a comparison population exposed to lower level, high level or pre and post exposures. (iv) outcome: oxidative stress or inflammatory biomarkers. The review only selected documents conducted in human subjects, without limitation to year of publication, with no limit on publication language. Reviews, commentary, letter, responses and editorials, duplicated publications, and conference abstract were excluded from the review.

Online database search was performed from five databases including PubMed, Embase, Web of Science, Scopus and Cochrane Library on 7th July 2024. Terms for BFS and biomarkers of interest were searched in title and abstracts. Example of search strategy performed in PubMed is below with full search available in Supplementary Table 1.

(“bushfire smoke(”[tiab] OR “bush fire smoke”[tiab] OR “wildfire smoke”[tiab] OR “forest fire smoke”[tiab] OR “vegetation fire smoke”[tiab]) AND (“oxidative stress”[tiab] OR “Reactive oxygen species”[tiab] OR “Oxidative damage”[tiab] OR “Oxidative injury”[tiab] OR “Oxidative markers”[tiab] OR “Inflammatory Biomarkers”[tiab] OR “Inflammation markers”[tiab] OR “inflammatory factors”[tiab] OR “inflammatory response”[tiab] OR “inflammatory mediators”[tiab]).

Study selection and data extraction

Document selection was managed using Covidence. Title and abstract screening were independently conducted by four reviewers (LR, IA, DR, SNN). Full-text review was conducted by three reviewers (GL, LR, SNN). Five reviewers (SNN, GL, LR, IA, DR) independently extracted data using extraction template provided in the Covidence. Any conflicts or disagreements throughout the three processes were solved through discussion and involvement of the expert (DV).

Risk of bias

A quality assessment tool for observational cohort and cross-sectional studies from National Heart, Lung, and Blood Institute (NIH) was used to assess the risk of bias in this review. The domain-based tool consists of 14 criteria that address research question clarity, study population selection, exposure and outcome assessments, timeframe sufficiency, control of confounding, and bias sources like selection, measurement, and attrition which evaluate the internal validity and risk of bias. The criteria were assessed as “Yes”, “No”, “Cannot Determine”, “Not Applicable”, and “Not Reported”. After considering each criterion, the overall quality of the study was reported as “good”, “fair” or “poor” based on fulfillment of ≥ 10, 7–9, or ≤6 criteria rating (Supplementary Table 2). We rated 10 studies as good quality, one fair, and three were poor quality.

Data analysis

A full meta-analysis was not feasible in this review due to substantial heterogeneity in study designs, exposure assessment metrics (e.g., PM2.5, CO, shift duration), biological matrices (e.g., blood, urine, EBC), and timing of biomarker sampling (e.g., pre-shift, post-shift, seasonal follow-up). These factors precluded direct comparability and risked introducing bias if pooled indiscriminately. Therefore, findings were synthesized narratively. However, to strengthen interpretation, we conducted a focused quantitative synthesis for the most consistent biomarker, IL-8, where sufficient homogeneity existed. Three studies examining IL-8 levels in firefighter blood samples were included in a forest plot analysis. Two studies used cross-shift comparisons (defined as pre- vs. post-shift biomarker levels), while one study assessed seasonal differences between baseline and post exposure periods. Effect sizes and 95 % confidence intervals were extracted or calculated, and a random-effects model was used to pool estimates. Two studies were excluded due to methodological differences but are discuss narratively. Analysis was conducted using R (version 2024.04.1) using the metafor package.

Study characteristics

The systematic review included 14 studies that examined the effects of BFS exposure on oxidative stress and inflammatory biomarkers. Table 1 shows the detailed characteristics of the included studies. Most were conducted in the United States (n=8), with others from Australia (n=2), Canada (n=2), Thailand (n=1), and Greece (n=1). The study populations varied, encompassing firefighters (11/14), adults (2/14), and elderly (1/14). Firefighters were the most frequently studied population, reflecting their high-risk exposure to BFS.

Eleven studies employed an observational cohort design, one study was cross-sectional, and two studies were randomized cross-over design. The biological matrices varied across studies included urine, blood, sputum, and exhaled breath condensate (EBC) to measure various oxidative stress and inflammatory biomarkers. Exposure durations ranged from short-term exposures lasting a few hours during firefighting shifts to longer durations extending over several days during bushfire events. Exposure from different time points within a work shift was observed in some studies. This exposure, usually referred to as “cross-shift”, specifically involved measuring biomarkers levels at pre-shift, post-shift, the next morning after burn days, and during regular non-burn shifts. Across the studies, exposure to BFS was commonly assessed using PM2.5_, CO, and black carbon either through personal monitoring or ambient measurements. However, the specific exposure assessment methods varied, with some studies using proxies such as work duration, fire event timing, or location-specific pollution data to estimate exposure.

Outcomes of oxidative stress and inflammatory biomarkers in associated studies

Inflammatory biomarkers

Cytokines and chemokines

Pro-inflammatory IL-8 showed the most consistent acute response to BFS in firefighters. Two studies reported significant post-shift increases in blood IL-8, while a seasonal follow-up study found IL-8 levels returned to baseline after three months, suggesting potential adaptation or changes in immune response over time [53]. To further synthesize evidence, three firefighter studies that measured IL-8 in blood samples with comparable pre- and post-shift [16], 33] or seasonal designs [53] were included in a forest plot analysis (Figure 2). The pooled estimate indicated an overall elevation in IL-8 levels following BFS exposure (mean difference 9.76 pg/mL, 95 % CI –8.26, 27.79), although heterogeneity across studies was substantial. By contrast, a study that assessed EBC reported null findings [32], while another study observed increases in sputum and serum IL-8 [54]. Together, these findings suggest that blood-based measures more consistently capture IL-8 changes in firefighters, whereas results vary across matrices and exposure durations.

Figure 2:

Forest plot of mean differences in IL-8 (pg/mL) pre- vs. post-exposure among firefighters. Three blood-based studies were included (Swiston [16]; Main et al. [33]; Cherry [53]). Effect sizes are shown as mean differences with 95% confidence intervals. A random-effects model was applied to account for between-study heterogeneity. Swiston and Main reported significant post-shift increases in IL-8, whereas Cherry’s seasonal comparison showed no significant change.

The same findings were observed with IL-6 [16], 33], 53]. A study did not include IL-6 analysis due to limited detection in EBC (only three of 142 samples detectable), possibly due to lower exposure intensity and use of a less sensitive matrix [32]. IL-10 consistently decreased across work-shift and seasonal analysis [33], 53]. These variations suggest that both the timing of biomarker measurement and magnitude and duration of exposure may influence these markers detectability and direction of response. Besides that, factors such as strenuous physical activities, and thermal strain may play important role in modulating the inflammatory response [33].

Other interleukins showed various associations with BFS exposure. These include IL-13, IL-1β, IP-12P70, and GM-CSF which increased during cross-shift [33], 54] and decreased during seasonal follow-up [53]. Conversely, there were significant decrease in IL-15, IL-17A, IL-12P40, IL-1RA, IL-1a, IL-3, IFN-γ, IFN-α2, and TGF- β in some studies [53], 54]. These findings highlight the critical influence of sample timing and biological matrices on cytokine interpretation but require more studies to confirm the associations.

Other inflammatory biomarkers

Other markers of respiratory inflammation such as MPO and ECP were also examined in sputum, nasal lavage fluid, and blood samples, with mixed findings. Significant associations were reported for MPO levels and ECP in sputum and nasal lavage fluid [55] as well as blood [35], whereas others observed no significant changes [34], 54]. PTX3 and SP-D demonstrated significant increases in plasma and EBC following controlled BFS exposure [34]. However, post-exposure effects were observed in blood samples, suggesting that systemic markers may be more sensitive to PM exposure than EBC markers. Fractional exhaled nitric oxide (FeNO) showed positive associations with BFS across all lag periods and coal mine fire smoke at 4hr lag [27], suggesting its utility as a short-term exposure indicator. By contrast, CRP showed no significant associations in most studies [27], 32], 49].

IL-8 as a consistent inflammatory biomarker

Our review, supported by a forest plot analysis of three firefighter studies [16], 33], 53], identifies IL-8 as the most consistent inflammatory biomarker associated of BFS exposure. Blood-based measures showed reproducible post-shift increases, while results from EBC, sputum and seasonal assessments were more variable. IL-8 is a pro-inflammatory chemokine involved in the recruitment and activation of neutrophils, airway inflammation and immune responses [56]. The findings indicate that IL-8 levels typically rose within 6–12 h post-exposure [16], 33], but declined after 24 h or over months [53], 54]. These findings suggest that while acute inflammation occurs shortly after exposure, IL-8 gradually return to baseline over time as supported by several studies that found inverse associations between IL-8 and long-term exposure to air pollution [57], 58].

Our findings also suggest that IL-8 responses could depends on the biological matrix used. However, more studies are needed especially among firefighters who are at risk to smoke inhalation, heat exposure and strenuous physical activities. Biological matrix from blood shows promising result. While a study observed a significant increase of IL-8 in nasal lavage fluid from PM2.5 exposure in ambient air pollution [59], we could not find other literature to support this finding. This highlights the robustness of IL-8 across different biological matrices. Experimental evidence in animal models further supports the role of IL-8 in the initiation and progression of lung inflammation after smoke inhalation, indicating it‘s importance as a mechanistic mediator of airway injury [60].

Although the subsequent decline over time suggests inflammatory resolution, repeated exposures could contribute to cumulative immune activation, which may have long-term health implications particularly for firefighters. However, there is limited evidence to support this hypothesis, highlighting the need for further research on the long-term effects of repeated BFS exposure among this group.

Other inflammatory cytokines (TNF-α, IL-6, GM-CSF, IFN-γ)

Other inflammatory biomarkers, like IL-6 [16], 33], 53], TNF-α [33], 53], 54], GM-CSF [33], 53], and IFN-γ [33], 53] were also reported, suggesting that BFS exposure triggers an acute immune response. While these findings indicate their potential as informative biomarkers, interpretation of their levels requires an understanding of their role and kinetics in the inflammatory cascade. For example, Main et al. [33] and Swiston [16] reported acute increases in IL-6 within hours of exposure, while Cherry [53] found IL-6 increases between off season and post exposure periods. These findings are biologically plausible, as IL-6 plays a key role in the acute phase reaction [61] and has been implicated as a predictor of COPD exacerbations [62]. Evidence from experimental study also demonstrate that prolonged smoke exposure (six months) can elevate IL-6 alongside TNF-α and GM-CSF [63], supporting observations from BFS studies.

Evidence shown that stimulation of IL-6 produced CRP [64]. Our reviewed identified only two studies measured CRP together with IL-6 [16], 32], with only one observed significant association with BFS exposure. While CRP typically peaks 36–50 h after an inflammatory trigger [64], short hours exposure might explain why CRP result in another study is null. This likely explains why cytokines such as IL-8, which respond rapidly within hours, consistently demonstrated acute changes, whereas slower-responding systemic markers like C-reactive protein (CRP) showed null results. These observations indicate that BFS exposure may similarly trigger a cascade of cytokine production in the respiratory system [36], although comparisons are limited by the scarcity of BFS specific studies.

The timing of cytokine release is critical for interpretation. TNF-α, for example, is rapidly released by epithelial cells in response to irritants and serves to stimulate IL-8 production from both epithelial cells and macrophages, leading to neutrophil recruitment. Most BFS studies measured outcomes within short exposure (1–5 h), which aligns with these early cytokine responses [16], 32], 33], 53], 54].

Studies among firefighters also explored other inflammatory biomarkers such as ICAM-1, VCAM-1, IL-1β, IL-13, ECP, serum amyloid A (SAA), immunoglobulin G, and leukocyte count [19]. However, the evidence base remains relatively small. These findings emphasize the importance of investigating not only which biomarkers change, but also when they change and why, to better understand the immune response to BFS exposure.

Oxidative stress biomarkers (8-isoprostane, MDA, 8-OHdG)

In BFS exposure studies, 8-isoprostane, MDA and 8-OHdG were commonly assessed oxidative stress biomarkers. 8-isoprostane and MDA reflect damage to lipids in cell membranes while 8-OHdG signifies damage to DNA [65], [66], [67]. These biomarkers provide complementary insight into different pathways of oxidative injury. However, there were mixed results that complicates these biomarkers interpretation as reliable indicators of oxidative damage from BFS exposure.

8-isoprostane was the most frequently examined biomarker, but findings were inconsistent. Few studies among firefighters reported no significant cross-shift changes in urinary or EBC concentrations [32], 50], 51], while a longer exposure study found only a modest associations with levoglucosan [48]. Urinary levoglucosan however is not suitable to be used as a biomarker to assess BFS exposure due to influence from demographic, dietary intake, and behavioral factors [68], 69]. Controlled exposure experiments further demonstrated significant increases of 8-isoprostane after short-term duration of woodsmoke at varying PM2.5 concentrations (0, 250, 500 μg/m³) [34], 35]. This contrast suggests that systemic biomarkers measured under standardized exposure conditions may be more sensitive to short-term oxidative stress than in field-based assays. Variability in findings may be due to differences in sampling matrices, timing of measurements, and exposure intensities [45], 70], 71], reinforcing the need for harmonized biomarker protocol. Despite its limitations, 8-isoprostane remains the most commonly used biomarker for oxidative stress assessment in human [45], but studies are needed specifically in occupational BFS contexts.

Our review also indicates inconsistent results for MDA as biomarker of oxidative stress due to BFS exposure. Most studies observed no significant associations between MDA and BFS exposure, with only one study reporting increased of urinary MDA with black carbon concentrations [50], 51]. These inconsistencies were likely due to small sample sizes (12–19 subjects) and dietary influences from high-lipid content food [50], 51] which reinforce the need for bigger sample size and the use of diverse biological matrix, and refined methods to validate MDA as a biomarker of BFS induced outcome [72]. Although urine is the most commonly used matrix due to convenience and non-invasive nature [73], other matrices like EBC, serum, and nasal fluid may offer greater sensitivity [74], 75]. Supporting this, studies on traffic-related air pollution (TRAP) also consistently show stronger associations with MDA levels when assessed in EBC, serum or plasma in traffic-exposed populations including residence, urban workers, and taxi drivers [76], [77], [78], [79]. This suggests that BFS studies may benefit from adopting similar approaches to improve reproducibility across populations.

While 8-OHdG provided valuable insights into the effects of BFS exposure on oxidative damage biomarkers among firefighters, it still remains limited and scarce. In broader literature, 8-OHdG has been widely used a biomarker of oxidative DNA damage from PM2.5 exposure, with levels shown to increase in proportion to the PM concentration [72], 80]. However, its application in BFS studies is still underdeveloped. Existing studies are constrained by small sample size, reliance on convenience sampling, and confounders such as dietary factors that weakened the reliability of 8-OHdG as a robust biomarker of BFS exposure [48], 51], 52].

Taken together, evidence of oxidative stress biomarkers in BFS exposure remains inconsistent. While chamber experiments demonstrate clear oxidative responses, field studies often show null or variable results, highlighting the influence of methodological heterogeneity. Standardized protocols, use of multiple biological matrices, and adequately powered longitudinal cohorts are critical to clarify the role of 8-isoprostane, MDA, and 8-OHdG in capturing oxidative stress responses to BFS.

Impact of study populations and exposure settings

Most included studies were observational cohort designs comparing the levels of biomarker levels across firefighting work-shifts (pre-and post-shift) during bushfire events and two randomized controlled trials mimicking firefighter exposure. This reflects their occupational exposure risk, including repeated deployments over consecutive weeks, prolonged work shifts up to 16 h, and exposure to extreme levels of smoke increase susceptibility to acute cardiovascular effects and long-term risks such as lung cancer mortality [6], 28], 29]. Fire-related exposures are known to alter inflammatory cytokines as well as of vascular damage and tissue injury in firefighters [19].

Importantly, physiological adaptation may also influence biomarker outcomes. Newer firefighters (≤2 years of service) showed higher oxidative DNA damage, while those with longer service may develop adaptation to the upregulation of antioxidant enzymes [52]. One possible explanation for these findings is that newer firefighters may not yet have developed adaptive physiological responses to repeated smoke exposure. Occupational adaptation could involve the upregulation of endogenous antioxidant defense systems such as superoxide dismutase, glutathione peroxidase, and catalase, which help mitigate reactive oxygen species generated during intense exposure [81], [82], [83]. Gianniou et al. [54] reported higher oxidative DNA damage in newer firefighters, possibly reflecting an underdeveloped antioxidant response to repeated exposures. Broader literature supports that repeated exposures may strengthen antioxidant defense systems [84], 85], partly explaining lower biomarker levels among experienced firefighters.

Another plausible mechanism is epigenetic modification. Prolonged occupational exposure to PM and combustion products has been linked to DNA methylation changes in genes regulating oxidative stress and inflammatory pathways [86], [87], [88]. These modifications may alter individual susceptibility over time, suggesting that the differences between newer and experienced firefighters reflects not only years of service but also complex biological interactions. However, this pattern may be confounded by the healthy worker effect, a form of selection bias wherein individuals who remain employed in high-stress occupations like firefighting tend to be healthier and more resilient that those who leave early [89]. Thus, lower biomarker levels in long-serving firefighters may reflect selective retention rather than true physiological resilience. Despite potential adaptation, long-serving firefighters remain at risk of chronic inflammation and cardiovascular disease [19], suggesting adaptation may reduce acute effects but not prevent cumulative damage.

These observations highlight the importance of occupational health surveillance. Early-career firefighters may benefit from biomarker-based monitoring, antioxidant or nutrition support, and physiological screening to identify those at greatest risk, while longitudinal monitoring of experienced workers is needed to assess whether adaptation offers protection or masks cumulative long-term risks [19], 90].

While valuable for characterizing acute and high-level exposures, the included studies may not reflect the effects of BFS on the general population. Only one study examined elderly people [27], reporting increased FeNO after short-term exposure to PM2.5 at levels as low as 10 μg/m³. This aligns with epidemiological evidence showing that BFS PM2.5 exposure>80 μg/m³ increases respiratory hospitalizations, while even lower levels (>25 μg/m³) can elevate cardiovascular mortality in adults above 65 years old [9], 91]. This is because aging renders the cardiovascular system more susceptible to the damaging effects of BFS [29].

Other vulnerable groups remain underrepresented. Studies observed significant health effects from air pollution on lung function and COPD among individuals from lower-income households [12], and maternal BFS exposure has been associated with pre-term birth during the second trimester and decreased birth weight during the first trimester [92]. Despite this findings, few biomarker-based studies have targeted pregnant women, children, or disadvantaged groups, limiting mechanistic understanding in these populations.

Overall, current evidence is dominated by firefighter cohorts, limiting generalizability. While epidemiological research consistently demonstrates that PM2.5 from BFS contributes to respiratory disease [13], biomarker studies among broader vulnerable populations remain limited. Expanding biomarker research to elderly individuals, pregnant women, children, and socioeconomically disadvantaged communities is critical to improve health risk assessments and guide protective interventions across diverse populations. This underscores the importance to improve the reliability of health assessments of PM2.5 from bushfire through assessment of oxidative stress and inflammation biomarkers accross diverse populations.

Methodological heterogeneity and challenges

A key limitation of the existing literature on BFS biomarkers is the substantial heterogeneity in study design, exposure assessment, and outcome measurement. Most included studies were observational cohort studies that compared biomarker levels pre- and post-shift in firefighters. While such designs are valuable for capturing acute occupational exposures, they lack the standardization needed to facilitate comparisons across populations and settings. Only two studies employed controlled exposure experiments simulating firefighter conditions [34], 35], which allowed for tighter control over exposure levels but may not accurately reflect real-world variability.

We found that exposure assessment methods varied widely across studies. Most studies conducted direct measurement of pollutants such as PM2.5, black carbon, and CO or surrogate markers like levoglucosan, while some studies conducted controlled exposure experiments. These approaches can introduce misclassification and make it difficult to directly compare the results, particularly when individual-level exposures are not measured. In our opinion, there is potential recall bias when some studies supplemented self-reported information on work tasks, firefighting years, or shift activities. Similarly, biological matrix assessment in the studies is differed across studies. The use of blood, urine, EBC, or nasal lavage fluid could influence both sensitivity and specificity of biomarker detection. For example, measurement of 8-isoprostane in blood showed stronger responses than EBC and urine [32], 34], 35], 48], 50], 51]. Thus, it is important to select appropriate biological matrix for analysis which requires more studies.

Finally, many cohort studies were limited by small sample sizes, with some had less than 20 participants [32], [50], [51], [52]. Such underpowered designs reduce the ability to detect meaningful associations and increase susceptibility to random error. Potential confounders such as diet, concurrent air pollution exposures, or individual differences in antioxidant capacity were often unmeasured or insufficiently controlled, weakening the reliability of findings.

Together, these methodological limitations highlight the challenges of synthesizing evidence across studies and underscore the need for standardized protocols in biomarker research on BFS. Harmonizing exposure metrics, expanding sampling windows, and adopting multi-matrix biomarker approaches could significantly enhance comparability and strengthen causal inference in future studies. These sources of heterogeneity also explain why only IL-8 across three firefighter studies was pooled quantitatively using a forest plot, while all other biomarkers were narratively synthesized. The differences in biomarker matrices, exposure characterization, and timing of outcome assessment would have made quantitative pooling misleading, reinforcing the importance of cautious interpretation.

Implications for public health and occupational safety

The findings of this review carry important implications for both public health and occupational safety. The consistent observation of acute inflammatory responses, particularly IL-8 shows that BFS exposure can trigger immediate immune activation. For firefighters, who often experience repeated and prolonged exposures, these short-term responses may accumulate into long-term health risks, including chronic respiratory disease, cardiovascular dysfunction, and even cancer risk. This highlights the need for strengthened occupational health surveillance and protective measures, such as optimized respiratory protection, rotational deployment schedules, and regular biomarker-based health monitoring.

From a broader public health perspective, the limited evidence among elderly individuals, pregnant women, and lower-income populations points to significant gaps in current preparedness strategies. Vulnerable groups are more likely to experience adverse outcomes, such as pre-term birth, impaired lung function, and cardiovascular events, even at relatively modest levels of PM2.5 exposure. Developing targeted public health interventions during bushfire events, including real-time air quality warnings, accessible indoor clean-air shelters, and community-level education campaigns on exposure mitigation are essential.

Moreover, the inconsistent results for oxidative stress and inflammatory biomarkers highlight methodological gaps that impede translation into practice. Standardized biomarker protocols across diverse populations would improve the reliability of health assessments and provide stronger evidence for risk communication and policymaking. Integrating biomarker data with epidemiological outcomes could also support the development of exposure thresholds that are specific to BFS rather than generalized from urban or traffic-related air pollution studies.

These findings emphasize that protecting both firefighters and the general population from BFS exposure requires a dual approach. This includes targeted occupational safeguards for high-risk workers and inclusive public health strategies for vulnerable groups. Strengthening biomarker research and surveillance will be critical to mitigating the long-term health burden of increasingly frequent and severe bushfire events.

Limitations and potential biases

This review has several limitations that should be considered when interpreting the findings. First, most studies had small sample sizes, often fewer than 50 participants which increases the risk of random error, limits statistical power, and may reduce the representativeness of the study population. No study provided sample size justifications or power calculations, further constraining confidence in the robustness of their results. As emphasized by Sadiq [93], adequate sample sizes are essential to ensure robust and applicable observed associations to broader populations [93].

Second, substantial heterogeneity in study design, exposure measurement methods, and biomarker matrices complicates direct comparisons or meta-analytic synthesis. For example, exposure metrics ranged from PM2.5 and black carbon to gaseous pollutants, while biomarkers were measured in diverse matrices such as urine, blood, exhaled breath condensate, and nasal lavage fluid. Inconsistent timing of sample collection from pre-shift to post-shift or days or months later likely contributing to inconsistent results.

Third, most studies did not adequately adjust for confounding variables such as diet, physical exertion, and baseline health status, all of which can influence oxidative and inflammatory biomarkers. The absence of proper adjustment might introduce potential bias in estimating the effects of BFS.

Fourth, most studies were derived from firefighter cohorts, reflecting occupational risk but limiting generalizability of findings to other vulnerable groups such as children, older adults, pregnant individuals, and those with pre-existing conditions.

Lastly, few studies examined long-term outcomes, with most investigations restricted to short-term or cross-shift exposures. This prevents firm conclusions about the cumulative effects of repeated BFS exposure or potential progression to chronic diseases such as COPD, cardiovascular disease, or adverse birth outcomes. Taken together, these limitations constrain the interpretability and generalizability of current findings.

Research gaps and future directions

Building on the limitations above, several research gaps warrant urgent attention. First, while IL-8 emerged as the most consistent short-term inflammatory biomarker, the variability in its measurements across biological matrices other than blood as well as inconsistencies in other biomarkers including IL-6, TNF-α, GM-CSF, IFN-γ, 8-isoprostane, MDA, and 8-OHdG, requires standardized biomarker protocols and harmonized sampling strategies. These would improve reproducibility and allow meta-analysis across studies.

Second, future studies should prioritize community-based populations, particularly pregnant women, the elderly, children, and socioeconomically disadvantaged populations who seems to be neglected. Longitudinal studies on the effects of BFS exposure are needed to better capture chronic and population-level health impacts.

Third, the phenomenon of physiological adaptation in firefighters, whereby oxidative stress responses may decline with years of service, requires deeper investigation. It remains unclear whether adaptation lowers long-term disease risk or simply delays the onset of chronic conditions. Longitudinal biomarker monitoring alongside clinical outcomes could help clarify these effects.

Finally, integration of biomarker data with epidemiological and exposure modeling studies is needed to establish exposure-response relationships specific to BFS, rather than extrapolating from urban or traffic-related air pollution. Such evidence would support the development of health-protective air quality guidelines tailored to BFS events.

To our knowledge, this is the first systematic review to comprehensively synthesize evidence on oxidative stress and inflammatory biomarkers associated with bushfire smoke (BFS) exposure across occupational and community populations. The study was conducted with methodological rigor, following the PRISMA 2020 guidelines, registered in PROSPERO, and supported by a formal risk-of-bias assessment to ensure transparency and reproducibility. By integrating findings from multiple biomarkers, biological matrices, and exposure contexts, this review provides a broad and mechanistic understanding of BFS-related health effects. Importantly, the synthesis identifies key research gaps and proposes a structured roadmap for future studies, offering practical value for both scientific inquiry and public health policy development. Future research should expand beyond occupational cohorts, adopt standardized biomarker protocols, and employ longitudinal and multidisciplinary approaches. Addressing these gaps will strengthen the evidence base, improve public health preparedness, and inform occupational safety standards in the face of increasingly frequent and severe bushfires.