Introduction

Radiation, fast-moving energy that is emitted as particles or waves, is in two forms non-ionizing radiation (NIR) and ionizing radiation (IR) (Williams and Fletcher 2010). NIR is low-frequency radiation that disperses energy through heat and increased molecular movement such as ultraviolet rays (part of it), visible light, infrared rays, and radio waves. IR, which includes alpha and beta particles and some electromagnetic radiations (e.g., gamma and X-rays), can, directly and indirectly, alter the normal structure of a living cell (Nassef and Kinsara 2017). Nowadays, IR and radioactive materials have expanded significantly and have found useful applications in various fields, including medicine, industry, agriculture, and research (Nassef and Kinsara 2017). Medical applications of IR, such as imaging techniques, play an essential role in the early diagnosis of diseases (e.g., cancers), planning and staging of treatment, and patient monitoring (Baker 1990).

The United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) has named X-rays as the most widely used radiation in medicine (UNSCEAR-Annex 2008). In 2008 alone, more than 3,600 million X-ray examinations, 37 million nuclear medicine procedures, and 7.5 million radiotherapy treatments have reported worldwide (Buls 2016), which raised concerns about the potential risk of IR to radiation workers in the related departments (Ahmad et al. 2019). As one of the most widely used radiations in medical science, X-rays can penetrate living tissues and lead to abnormal cell function or death (Baskar et al. 2014; Shi and Tashiro 2018). Therefore, due to its medical side effects, the United States National Cancer Institute (USNCI) has classified these rays as human carcinogens (Zahm and Devesa 1995; Zargan et al. 2016). Exposure to IR can be defined and surveyed as internal and external exposures (Misra et al. 2015). Internal exposure is the entry of radiation into the body caused by inhalation, ingestion, or entry of a radionuclide into the bloodstream (by injection, through open wounds, etc.). Internal radiation can be stopped by spontaneously removing radionuclides from the body or under various treatments’ influence (Ionizing radiation 2016). In external exposure, radioactive material does not enter the body. In other words, the radiation source is out of the body, and depending on the type of radiation, different protection methods can be used (Salvato et al. 2003). Studies have shown that exposure to high doses of IR can cause various cancers. However, exposure to low doses also can have adverse health effects (Piotrowski et al. 2017; Suzuki and Yamashita 2012). Therefore, different dose limits have been defined for exposure to radiation, which varies depending on different conditions such as exposure type (public or occupational) and exposed body organ. The dose limits for radiation exposures are presented in Table 1 (Oztas et al. 2012).

Table 1 Dose limits for occupationally exposed workers and the public (Oztas et al. 2012)
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Immune cells, including lymphocytes, are the most sensitive cells to moderate and high levels of radiation (Schaue and McBride 2012), with the potential risk of mutagenicity and carcinogenicity from exposure to IR has been reported (Hayata 2005; Hei et al. 2005) and discussed in many studies (Mavragani et al. 2017). The radiation workers in various diagnostic and therapeutic settings (e.g., hospitals and clinics) are exposed to low-dose radiation for a long time despite the use of personal protective equipment and employing the instructions (Cheon et al. 2018; Gaskin et al. 2014). The use of IR is common in various wards of a hospital, including radiography and nuclear medicine (Dorfman et al. 2011). Hence, clinicians, nurses, technicians in radiology departments, and paramedics are people who can be exposed to IR in hospitals (Szarmach et al. 2015). Evidence shows that the frequency of chromosomal damage in these individuals, even those exposed to less radiation than dose limits, was higher than normal individuals (Jha and Sharma 1991; Kasuba et al. 2005; Kim et al. 2017; Linet et al. 2012), putting workers at risk of cancers, especially brain cancer (Rajaraman et al. 2016). The mechanism of this health effect is yet to be explored. At the same time, elevated levels of reactive oxygen species (ROS), oxidative DNA damage, and Immunosuppression triggered by exposure to IR are mentioned as possible reasons (Ahmad et al. 2019). Previous studies have shown that exposure to IR in radiation workers, even under the dose limits recommended by International Commission on Radiological Protection, changes the redox of the environment by increasing the amount of ROS, especially superoxide (Ahmad et al. 2016, 2019). In addition, evidence shows that chronic oxidative stress is involved in many pathological conditions such as inflammation, fibrosis, necrosis (Citrin et al. 2012; Shi and Tashiro 2018), DNA damage, and cancers (Jacob et al. 2009; Zakeri and Hirobe 2010; Zielinski et al. 2009). Understanding the potential health effects of exposure to IR, especially among radiation workers, is crucial to better tailor targeted preventive interviews to reduce harmful exposure to IR. Therefore, in this study, we aimed to investigate the relationship between exposure to IR and changes in interleukin-6 (IL-6) and complete blood count (CBCs) (i.e., white blood cells (WBC), neutrophils, lymphocyte, monocyte, eosinophil, basophil, red blood cells (RBC), hemoglobin (HGB), hematocrit (HCT), mean cell volume (MCV), mean corpuscular hemoglobin (MCH), mean cell hemoglobin concentration (MCHC), cellular hemoglobin concentration mean (CHCM), red blood cell distribution width (RDW), platelet (PLT), mean platelet volume (MPV)) in radiation workers of different related hospital wards (diagnostic and therapeutic) in Tabriz, northwest of Iran. The reference ranges of the studied biomarkers are shown in Table 2 (43).

Table 2 Reference dose of the studied biomarkers (Samadi et al. 2019, 2020)
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Methods

Study design

A cross-sectional study was conducted to explore the effects of long-term exposure to IR in radiation workers in Tabriz megacity hospitals from May 1, 2016 to May 1, 2021. Two study groups were selected as exposed (radiation workers) and unexposed (control) to IR. Despite previous studies that have shown no significant effects of work experience on the level of biomarkers (Tavakkoli et al. 2012; Zargan et al. 2016), radiation workers with work experience of more than 10 years were selected as the exposed group. All study sections took place in a private room in each hospital to ensure the confidentiality of information. A de-identified code also was assigned for each study participant.

Study population

To calculate the sample size for this study, we considered the mean (SD) concentration of the IL-6 as 0.44 pg/mL (0.08) in control and 0.83 pg/mL (0.21) in the exposed group based on previous literature (Ahmad et al. 2019). Power analysis with α = 0.05 and β = 0.80 yielded a sample of 30 participants for each group. To increase the study power, 10% of the sample size was added to the original sample, resulting in 67 participants; n = 33 radiation workers and n = 34 control group. Stratified random sampling was applied to select the final sample for each group. To reduce selection bias, participants in the control group were selected from the staff of the same hospitals who were not exposed to IR. Work experience of less than 10 years for radiologists, age less than 20 years and more than 60 years, presence of chronic and acute disease for all participants, and pregnancy for females were the exclusion criteria of the present study.

Covariates

The literature review showed that factors such as FBS (Kitsios et al. 2012; Mohammadi et al. 2017; Pradhan et al. 2001; Sarbijani et al. 2016), BMI (Kitsios et al. 2012; Pradhan et al. 2001; Roytblat et al. 2000), smoking (Aldaham et al. 2015; de Maat and Kluft 2002), age (Aldaham et al. 2015), medical supplements and physical activity (Eder et al. 2009) can affect the levels of studied biomarkers. Hence, self-reported demographic characteristics and medical history were assessed including sex (male/female), age (years), body height (cm), body weight (kg), body mass index (BMI; body weight divided by the square of the body height; normal ≤ 24.9, overweight = 25 to 29.9, and obese ≥ 30 kg/m2), diabetes mellitus (DM), physical activity, consumption of alcohol and dietary supplements, smoking status, history of diseases such as thalassemia, hemophilia, and infections and history of taking certain medications. Glucose oxidase kits (PARS AZMUN) were used to assess the FBS and DM (FBS ≥ 126 mg/dL) (Samadi et al. 2019, 2020). Participants who were taking diabetes-related medications were considered diabetic patients. Bodyweight and height were measured using a standard scale and stadiometer (Body Scale BS769), respectively, (Pietrobelli et al. 1998). Participants who presently smoked cigarettes, participants who have smoked 100 cigarettes in life but currently not smoking, and participants who had smoked less than 100 cigarettes in life were defined as current, former, and never status, respectively (Samadi et al. 2019). Physical activity was assessed using the Godin Leisure Exercise Questionnaire (Ahmad et al. 2019).

Absorbed radiation dose estimation

The absorbed dose in radiation workers was measured by a personal film badge (FUMA, Japan). The dosimetry was performed every 2 months and estimated by PARSIAN and SANJESH PARTO MEHR ARSHID companies.

Blood markers

We evaluated selected biomarkers (e.g., IL-6 and CBCs) considering the normal range based on the previous studies (Samadi et al. 2019, 2020). We obtained venous blood samples (by trained nurses) in each study site (i.e., hospital). The separated serum was shipped to a laboratory in a cold box at about 4 °C and was kept at − 80 °C immediately (El-Mikkawy et al. 2020). IL-6 was measured using ELISA (Karmania Pars Gene ELISA kits, Karmania Pars Gene Co, Kerman, Iran) and an automatic analyzer (AWARENESS STAT FAX 2100). CBC was measured by an automatic hematology analyzer (Siemens ADVIA360).

Statistical analyses

Spearman rank correlation was used to examine the correlation between quantitative parameters (age, FBS, BMI, etc.) with dependent variables (CBCs and IL-6). The difference between average exposure dose in various working wards (angiography, radiotherapy, nuclear medicine, radiology, and CT scan) was evaluated by one-way analysis of variance (ANOVA). Independent Student’s t-test was used to examine the association between dependent variables and demographic characteristics (e.g., age, sex, BMI) and medical history (e.g., DM). The effect of working ward and smoking status on dependent variables was evaluated by ANOVA followed by post hoc Tukey’s method. Multiple linear regression models were used to assess the association between exposure to IR and biomarkers after adjusting for confounders. All statistical analyses were performed in the Stata software, version 14 (StataCorp), at a significance level of 0.05.

Results

The mean age of participants was 39.9 (± 1.1) years, with 52% female, and the mean BMI of 26.32 kg/m2. Of all participants, 91% were non-smokers, 57% had insufficient physical activity, and 96% had lower FBS (< 126 mg/dL). None of the participants consumed alcohol, and 19% of participants reported a history of taking dietary supplements or chronic medical conditions (Table 3).

Table 3 Descriptive statistics of the study population (n = 67)
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The average absorbed dose (5 years’ periods) of the radiation workers is shown in Table 4. The absorbed dose for all of the radiation workers was lower than the defined dose limits (Table 1). The reference range and descriptive statistics of the studied biomarkers are shown in Table 2 (Samadi et al. 2019) and Table 5, respectively. After adjusting for potential confounders, our regression models show the significant difference in the mean concentration of IL-6 in radiation workers compared to the control group (49.78 vs. 36.17, p = 0.02) (Table 6). In the case of CBC, only the significant difference in the mean concentration of eosinophils was observed between the radiation workers compared to their counterparts (0.17 vs. 0.14, p = 0.049) (Table 7).

Table 4 Average exposure dose (5 years’ periods) of radiation workers depending on working place
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Table 5 Descriptive statistics of the studied biomarkers
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Table 6 The association between IL-6 levels and selected covariates in radiation workers using multiple linear regressions
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Table 7 The association between eosinophil levels and selected covariates in radiation workers using multiple linear regressions
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As shown in Table 4, maximum and minimum absorbed radiation dose was related to the radiology, and radiotherapy wards, respectively. The highest mean absorbed dose was related to CT scan and then nuclear medicine wards.

Two-sample t-test (results not shown) demonstrated that the level of MCV in radiation workers who had a cold in the past month was lower than the other radiation workers (p = 0.016). In the case of medical supplement consumption, in the control group, the level of RBC (p = 0.008), HGB (p = 0.036), HCT (p = 0.02), CHCM (p = 0.038), and lymphocytes (p = 0.044) in individuals who taking medical supplements is significantly lower than the individuals who do not take medical supplements. However, the opposite of this result is true in the case of neutrophils level (p = 0.022). In radiation workers, the MPV level is significantly lower in individuals who do not take medical supplements (p = 0.01). Regarding the special drug consumption, RDW, MPV, and neutrophil levels are significantly higher in radiation workers who take special drugs (p = 0.001, 0.02, and 0.023, respectively). In the control group, the lymphocyte level is significantly higher in individuals with a history of a specific disease (p = 0.044).

According to the results of Spearman rank correlation (results not shown), no significant relationship was observed between FBS and studied biomarkers. Physical activity had a significant negative relationship with MCH only in radiation workers (r =  − 0.368, p = 0.039). However, there was a significant negative relationship between BMI and RBC (r =  − 0.401, p = 0.019), HCT (r =  − 0.403, p = 0.018) and CHCM (r =  − 0.412, p = 0.015) in control group and a significant positive relationship with eosinophils (r = 0.389, p = 0.028) in radiation workers. Doing any regular activity long enough to work up a sweat at work during a typical 7-Day period has a significant negative correlation with CHCM (r =  − 0.569, p = 0.001) and MCHC (r =  − 0.399, p = 0.019) in control group and a significant positive correlation with MCH (r = 0.403, p = 0.022) in radiation workers. In control group, age had a significant negative relationship with MCHC (r =  − 0.341, p = 0.048) and a significant positive relationship with Neutrophil (r = 0.395, p = 0.02) and leukocytes (r = 0.345, p = 0.045).

ANOVA followed by Tukey’s method demonstrated that, the level of RBC (p = 0.027), HGB (p = 0.019), HCT (p = 0.018), and CHCM (p = 0.037) in former smokers is significantly higher than non-smokers. In addition, the results showed that the level of HCT (p = 0.026) and MPV (p = 0.045) in current smokers was significantly higher than in non-smokers. However, the level of MPV (p = 0.025) is higher in current smokers than in former smokers.

Discussion

In this study, the mean serum levels of IL-6 and eosinophils in radiation workers were higher than the control group. We also found that the absorbed radiation dose for all of the radiation workers was lower than the defined dose limits, and the mean concentrations of all studied biomarkers fell within the standard ranges. Our findings, in general, show that the long-term exposure to IR, even lower than defined threshold limitations, can alter some of the biomarkers, namely IL-6 and eosinophils.

The normal range of IL-6 serum levels varies depending on the community. Therefore, it is preferable to use the control group’s mean as a reference range. This range in our control group was (~ 36) but was markedly higher in radiation workers (~ 48). Although IL-6 has been identified as one of the protein biomarkers associated with radiation injuries in total and partial-body exposure (Blakely et al. 2014; Ossetrova et al. 2014a, b; Redon et al. 2011), elevated levels of IL-6 have been identified in animal and human studies as a major mediator of potential health outcomes (Kulkarni et al. 2013; Singh et al. 2010, 2011, 2012a, b, c, 2014). For example, Citrin et al. (2012) reported a dose–response association between the neck and head radiotherapy and expression of IL-6 and some of the other cytokines. This is worrisome especially in the current global crisis. For example, higher levels of IL-6 are associated with increased risk of mortality from several diseases such as COVID-19. In COVID-19 patients (especially healthcare providers who are at greater risk), higher IL-6 levels increase the chance of mechanical ventilation requirements and can lead to severe SARS-CoV-2 induced pneumonia (Guirao et al. 2020).

Exposure to IR can change the numbers and functions of immune system cells and cause an inflammatory response, which activates various pro-survival pathways and factors such as nuclear factor kappa B (NF-kB) and members of signal transducers and activators of transcription (STATs) (Criswell et al. 2003; Dent et al. 2003; Meeren et al. 1997; Najafi et al. 2017a). By regulating the expression of pro-inflammatory cytokines such as IL-6, NF-kB plays an important role in inflammatory and immune responses (Calò et al. 2003; Yu et al. 2009). Moreover, exposure to IR can cause the expression of many other growth factors and cytokines such as GM-CSF, interferon-gamma (IFN-γ), tumor necrosis factor (TNF-α), transforming growth factor-beta (TGF-β), IL-1β, IL-1α, IL-33, IL-18, IL-12, IL-10, IL-4, and IL-5 (Di Maggio et al. 2015; Najafi et al. 2017b). IL-6, along with other extracellular ligands such as PDGF and EGF, can activate STATs, which can stop or develop the tumor (Calò et al. 2003; Yu et al. 2009). This pathway’s protective or adverse outcome depends on the pro-inflammatory and anti-inflammatory cytokines balances (Sun et al. 2013). For example, STAT3 as an oncogene can promote cell proliferation (tumor developer), while STAT1 stimulates and enhances anti-proliferative, inflammation, and immunity responses (tumor stopper) (Calò et al. 2003; Shen et al. 2001). The radiation resistance in increased levels of IL-6 and radiation sensitivity in decreased levels of IL-6 have been reported previously in prostate cancer cells (Wu et al. 2013). Hence, it is crucial to consistently monitor the levels of IL-6 among radiation workers to avoid dire health consequences.

Although our findings yielded significant results only for one CBC parameter, namely eosinophils in radiation workers compared to the control group. However, contrary to this result, some previous studies found that radiation exposure does not significantly affect the number of neutrophils (Buescher and Gallin 1984; Rees et al. 2004; Schubauer-Berigan and Wenzl 2001). They attributed this result to the relative resistance of phagocytes to irradiation. In line with our findings, other studies have reported no association between exposure to low dose radiation and WBC (Forslund et al. 1985; Heydarheydari et al. 2012; Meo 2004; Salek Moghaddam et al. 2004; Shafiee et al. 2016a; Zargan et al. 2016), PLT (Heydarheydari et al. 2012, 2016; Sayed et al. 2011; Shafiee et al. 2016a; Tavakkoli et al. 2012; Zargan et al. 2016), RBC (DavudianTalab et al. 2018; Meo 2004; Mezhoud et al. 2014; Shafiee et al. 2016a), MCH (Mezhoud et al. 2014; Shafiee et al. 2016a), MCHC (Shafiee et al. 2016a), HCT (Hauck et al. 2011; Mezhoud et al. 2014; Shafiee et al. 2016a), HGB (Hauck et al. 2011; Mezhoud et al. 2014), and MCV levels (Mezhoud et al. 2014). Nevertheless, statistically significant decreases in WBC (Davoudi et al. 2012; Mezhoud et al. 2014; Shahid et al. 2015a; Tavakkoli et al. 2012), neutrophil (Shahid et al. 2015a; Taqi et al. 2018), monocytes (Taqi et al. 2018), basophile (Taqi et al. 2018) lymphocytes (Sabagh and Chaparian 2019), PLT (Dainiak 2002; Davoudi et al. 2012; Faraj and Mohammed 2018; Meo 2004; Mezhoud et al. 2014; Sabagh and Chaparian 2019; Shafiee et al. 2016b; Shahid et al. 2015a; Taqi et al. 2018), RBC (Abdolmaleki et al. 2012; Heydarheydari et al. 2016), HGB (Abdolmaleki et al. 2012; Heydarheydari et al. 2016; Shahid et al. 2015a), MCV (Abdolmaleki et al. 2012; Heydarheydari et al. 2016; Taqi et al. 2018), RDW (Taqi et al. 2018), HCT (Shahid et al. 2015a), MCH (Shahid et al. 2015a, 2014), and MCHC levels (Sabagh and Chaparian 2019; Shahid et al. 2015a) were reported in radiation workers compared with the control group. Also, the result of some studies yielded a significantly increased level of WBC (Nureddin and Alatta 2016), lymphocytes (Shahid et al. 2015a; Taqi et al. 2018), PLT (Nureddin and Alatta 2016; Sayed et al. 2011), RBC (Shahid et al. 2015a; Taqi et al. 2018), MCV (Abdolmaleki et al. 2012), HGB (Shahid et al. 2015a; Taqi et al. 2018), and HCT (Sabagh and Chaparian 2019; Shahid et al. 2015a; Taqi et al. 2018) in response to low-dose radiation. Several factors could explain these discrepancies and commonalities between previous literature and our findings, including study design, study sites, sample of study, characteristics of the participants (whether the radiation workers or control group), time of blood sampling, and other covariates (e.g., time and duration of exposure), and more importantly we cannot preclude the reporting bias that may cause some differences between findings. Future large multicenter longitudinal studies are warranted to investigate these differences in various populations deeply.

As a result of exposure to various hospital infections, hospital staff has a stronger immune system than normal individuals (Faraj 2021). However, studies that have reported a positive association between CBC counts and radiation exposure identified the hematopoietic acute radiation syndrome, an acute toxic syndrome that was reported as a result of total body exposure to IR dose between 0.7 and 10 Gy, as a possible reason (Billings et al. 2014; Ma et al. 2010; Shahid et al. 2014, 2015b). In contrast, other studies explain the adaptive response as a reason why exposure to a low dose of IR does not affect CBC counts. In this phenomenon, body organs that are exposed long-term to low dose radiations have sufficient time to restore the damaged cells and increase the levels of cell cytoprotective genes. Thus, in subsequent exposures, the body becomes resistant to IR (Feinendegen et al. 2004; Kadhim et al. 2004; Liu et al. 2006; Salek Moghaddam et al. 2004; Schimmöller et al. 2014; Tucker 2008).

Our adjusted regression model showed that WBC, PLT, and monocytes in individuals with higher levels of FBS (≥ 126 mg/dL) were significantly lower than the individuals with lower FBS (i.e., < 126 mg/dL). CHCM and HDW significantly decrease with increasing weight, but this difference is only statistically significant in participants with overweight (BMI = 25 to 29.9 kg/m2) compared to participants with BMI within normal range (BMI ≤ 24.9 kg/m2). MPV in middle-aged participants (30–49 years) was significantly higher than the younger counterparts (20–29 years old). Neutrophils increase with increasing age, and this difference was statistically significant among participants aged 30–59 years compared to 20–29 years. This was expected since associations between age and CBC parameters were reported in the literature (Burton et al. 1983; Fujiwara et al. 1986; Tuschl et al. 1990). For instance, decreased number of WBC has been reported with increasing age (DavudianTalab et al. 2018). Prevention programs should consider demographic characteristics to achieve effective outcomes in the targeted population, especially radiation workers.

Two-sample t-test (results not shown) demonstrated that the level of RBC (p = 0.0 for both radiation workers and control groups), HGB (p = 0.0 for both radiation workers and control groups), HCT (p = 0.0 for both radiation workers and control groups), and CHCM (p = 0.003 for radiation workers and p = 0.006 for control group) were higher in males than females. However, the PLT level in female radiation workers was higher than the male radiation workers (p = 0.002). (DavudianTalab et al. 2018) reported no significant difference for CBC between the radiation worker and control group by gender. However, similar to the results of the current study, the level of RBC, HGB, HCT, MCHC, and lymphocytes was reported significantly higher in males, and PLT was reported significantly higher in female radiation workers by (Sabagh and Chaparian 2019).

Our findings were in line with previous research showing that the increased levels of RBC (Anandha Lakshmi et al. 2014), HGB (Anandha Lakshmi et al. 2014; Malenica et al. 2017; Whitehead et al. 1995), HCT (Anandha Lakshmi et al. 2014; Whitehead et al. 1995), and CHCM (Malenica et al. 2017) were higher in current smokers than non-smokers. To minimize radiation exposure, it is recommended that radiation workers be trained in the use of personal protection instructions. In addition, using dietary supplements (including antioxidants such as vitamins E, C, B6) potentially can protect the risks on immune systems of radiation workers (Guan et al. 2006). The SARS-CoV-2 pandemic, lack of access to all hospitals, and poor cooperation of radiologists were the limitations of the present study. In addition, it is recommended that under normal conditions, the number of participants in the control or non-exposed group should be twice the number of the exposed group, and the environmental exposure to radiation (including; external radiation exposures such as sunlight and climate-related radiations, and internal radiation exposures such as contaminated water, foods, and respirable air) should also be measured.

Conclusion

This study revealed that hazardous exposure to IR after adjusting for significant covariates was significantly associated with increased IL-6 and eosinophils in radiation workers compared to the non-exposed control group in several hospitals in Iran. We found that the absorbed dose in all radiation workers was lower than the dose limits. Hence, it should be noted that long-term exposure to ionizing radiations, even under defined dose limits, can have adverse health effects. This highlights the crucial role of monitoring radiation workers as at-risk populations who are key workers at the time of health crises such as the current COVID-19 pandemic. Regarding the studied biomarkers, it should be noted that CBCs may not be considered a specific biomarker of radiation exposure. In essence, it is practical to use them to follow up on the overall health of radiation workers. Although the levels of IL-6 are associated with radiation exposure, in order to monitor the health effect of radiation exposure, it is recommended that other cytokines also be measured. Since the balances between pro-inflammatory (or inflammatory) cytokines (for example, IL-1, IL-6, and IL-8) and anti-inflammatory cytokines (for example, IL-4, IL-10, and IL-13) will determine the final health effect.