Abstract

Background-aim:

Landfill workers face a range of occupational exposures that can adversely affect their health and overall quality of life. The aim of this study was to assess cadmium and lead concentrations in the blood of workers employed at sanitary landfill sites, while documenting additional health indicators. Another objective was to explore potential associations between exposure levels and demographic factors, occupational history, working conditions.

Methods:

A cross-sectional study was conducted among employees working at four landfill sites in Northern Greece. Participants completed a questionnaire and underwent clinical examination. Blood samples were collected for hematological, biochemical analyses, and the determination of lead and cadmium concentrations. Statistical analyses were performed to identify differences in the examined parameters across occupational exposure groups and to identify predictors of lead and cadmium levels.

Results:

A total of 147 employees were recruited (76.9% males, n = 113), with a mean age of 48 ± 7.6 years. Blood lead levels were significantly higher in males compared to females (2.26 μg/dL vs. 1.40 μg/dL, p = 0.001), while no sex differences were observed for cadmium (p = 0.438). Increasing age was associated with higher lead levels (p = 0.001), but not with cadmium (p = 0.382). Cadmium levels increased with higher BMI, whereas lead levels decreased (normal weight: 2.24 ± 1.67 μg/dL and 1.25 ± 1.33 μg/L; overweight: 2.05 ± 1.33 μg/dL and 1.41 ± 1.97 μg/L; obese: 1.88 ± 1.15 μg/dL and 1.45 ± 1.89 μg/L, respectively). Smoking was a significant determinant of both metals, with higher levels observed among smokers (lead: 1.61 ± 0.98 μg/dL; cadmium: 0.50 ± 0.71 μg/L). Significant predictors of cadmium and lead levels included smoking, duration of employment, work position, occupational site and use of personal protective equipment (PPE). Highly exposed workers had significantly higher cadmium (2.12 ± 2.38 μg/L) and lead levels (2.69 ± 1.61 μg/dL) compared to moderate and low exposure groups (p ≤ 0.016).

Conclusion:

Blood cadmium and lead levels among landfill workers were associated with occupational exposure intensity and individual factors such as age, BMI, and smoking. Although overall concentrations were relatively low, cumulative exposure influenced by both workplace conditions and lifestyle factors is evident. These findings underscore the need for ongoing occupational health monitoring and targeted preventive measures to reduce exposure and protect worker health.

1 Introduction

Sanitary landfills are engineered facilities composed of sealed underground cells designed for waste disposal. At the base of these disposal areas, leachate is generated as water percolates through waste. This leachate is collected and treated through processes such as recycling, evaporation, spraying, and controlled discharge. It contains a wide range of chemical compounds, including heavy metals such as lead (Pb) and cadmium (Cd), which pose significant risks to human health (1–6).

Previous studies have demonstrated that workers involved in waste management activities may experience increased exposure to heavy metals. For example, workers engaged in precipitate cleaning have been shown to exhibit elevated blood lead levels (1), while recycling workers are also at increased risk due to direct contact with waste materials (2, 7, 8). The use of personal protective equipment (PPE) has been associated with reduced exposure levels (1), highlighting the importance of preventive measures. However, available evidence remains heterogeneous, and findings are often context-specific. Studies conducted in Thailand have examined blood lead and cadmium levels in relation to PPE use and hygiene practices (9), while environmental studies in Greece have documented heavy metal contamination in landfill soils (5). Nevertheless, data on internal exposure levels among landfill workers, particularly in European settings, remain limited.

A substantial body of evidence indicates that heavy metal contamination of ecosystems is largely attributable to human activities (1, 10–12). Once released into the environment, these metals can disrupt normal biological functions, cause irreversible damage to critical organs, and, in severe cases, result in mortality (7, 13–15). Exposure to heavy metals has been associated with chronic diseases such as type II diabetes, Alzheimer’s disease, and hypertension (16–18). Human exposure to soil-derived heavy metals occurs primarily through ingestion, inhalation, and dermal contact (4–6). Therefore, the implementation of appropriate protective measures—such as the use of masks, gloves, and protective work clothing—is essential for workers at risk of occupational exposure.

Despite these concerns, there is limited evidence on biomonitoring of heavy metal exposure among landfill workers, particularly in Southern Europe, where occupational conditions and waste management practices may differ from those reported elsewhere. Furthermore, few studies have simultaneously examined the combined influence of occupational exposure, workplace conditions, and individual lifestyle factors on internal metal burden.

The objective of the present study was to assess blood levels of Pb and Cd among landfill workers in Northern Greece and to investigate their association with demographic characteristics, occupational history, working conditions, and lifestyle factors. Pb and Cd were selected as target pollutants due to their widespread presence in municipal solid waste, persistence in the environment, bioaccumulative properties, and well-documented toxic effects on multiple organ systems. Additionally, both metals are widely used as biomarkers in occupational biomonitoring, enabling comparison with existing literature. A secondary aim was to evaluate general health indicators, including hematological and biochemical parameters, as to explore potential correlations with the concentrations of Pb and Cd.

2 Materials and methods

The study had a cross-sectional design and included employees from various job positions across four sanitary landfill sites in the area surrounding the city of Thessaloniki, in Northern Greece.

Inclusion criteria were the following: being employed for at least 1 year and consent to participate. No exclusion criteria were applied, except for refusal to participate.

Participants were recruited over an 18-month period. All eligible workers were invited to participate and were scheduled for evaluation at the Occupational Medicine Department. Upon attendance, participants were informed about the study procedures and provided written informed consent prior to enrollment.

Face-to-face interviews were conducted, followed by clinical examination at the Occupational Medicine Department. A structured questionnaire was administered to collect information from the participating workers, covering anthropometric characteristics, family status, educational level, lifestyle habits (e.g., smoking and alcohol consumption), individual medical history, occupational history, family medical history, and use of personal protective equipment. The questionnaire was developed based on commonly used items in occupational health research to capture demographic, occupational, and lifestyle information; however, formal validation and reliability testing were not performed.

Moreover, venous blood samples were collected from each participant, and three 5 mL aliquots were prepared and stored in acid-cleaned plastic tubes. These samples were used for hematological and biochemical analyses, as well as for the determination of lead (Pb) and cadmium (Cd) concentrations. Metal analysis was performed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) (Analytik Jena, PlasmaQuant MS, Aspect MS software v3.3.4.7), a highly sensitive technique for trace element detection.

For trace metal analysis, blood samples were collected in metal-free tubes to prevent contamination and subsequently diluted (1:10 or 1:20) with a solution containing NH₄OH, Triton X-100, and EDTA to ensure hemolysis and stabilization of metals. Internal standards (rhodium and iridium) were applied to correct for instrumental variability, and analyses were conducted using a helium collision gas system. Calibration was performed on a daily basis, including calibration blanks prepared with the same diluent as the samples. Quality control was ensured using certified reference materials (Recipe Clin Chek) at three concentration levels.

The limits of detection (LOD) ranged from 0.0001 to 0.0005 μg/L for Pb and from 0.0001 to 0.0008 μg/L for Cd, while the limits of quantification (LOQ) were 0.38 μg/L for Pb and 0.30 μg/L for Cd.

Participants were categorized into four groups according to their worksite and corresponding exposure level: (1) workers employed at an active landfill site (direct exposure); (2) workers at a recycling material management facility (direct exposure); (3) workers at an inactive landfill site (former waste disposal areas) (indirect exposure); and (4) workers at a rehabilitated/ environmental park site, i.e., a former landfill area that has been inactive for more than 35 years (indirect exposure).

Exposure groups were formed based on job title, specific work tasks, and worksite characteristics, as defined in the Written Occupational Risk Assessments conducted in accordance with national legislation (Law 3850/2010), which systematically evaluate occupational hazards and exposure levels. This classification, derived from standardized occupational risk assessment procedures, was used as a proxy for relative exposure intensity and is consistent with established occupational health risk management practices, supporting its validity for exposure stratification in the present study.

Table 1 provides an overview of employees’ job tasks and duties, along with the corresponding levels of exposure across the four groups.

SitesWork positionsSettingRelated duties/task descriptionLevel of exposure1. Active landfill area

Machine operators

Drivers

Signalmen

Waste unloading process, burial operations, waste disposal, waste coverall, leachate management systemLandfilling, spreading, compacting and covering the waste, according to the program and the instructions of supervisor. Driving vehicles to the area, Various other tasks (e.g., Water spraying on the roads, good maintenance of the vehicles)Direct/HighWatering, assisting operators in cleaning machinery, assisting in guiding vehicles to disposal sites, transportation of materials and tools. The maintainers are responsible for the maintenance and repair (painting, etc.) of the landfill administration building and its other facilities.Direct/Moderate

Supervisors

Administrative personnel

Monitors, controls and intervenes in the waste disposal process in accordance with the site development plan. Specifically: Personal supervision of the operation of the unit’s services.Direct/Low2. Recycling management centerRecycling material management centerSorting and separate itemsDirect/High3. Inactive landfill areaInactive landfill area, tree planting, and the general care on of the areaOperations manager, Tree planting, gardening and cleaningIndirect/low4. Environmental/rehabilitated parks (former landfill areas)Environmental Parks (Former Landfill Areas) Stopped operating 35 years ago.
Planted with trees- parks in urban tissue, open to the public.The area Operations Manager, Cleaning, tree planting, watering, mowing, gardeningIndirect/Low

Characteristics of the work positions and settings in the four examined sites.

2.1 Ethical considerations and approvals

Permission to conduct the study was granted by the Regional Association of Solid Waste Management Bodies of Central Macedonia, Greece (protocol no. 8443/24-08-2016; meeting no. 27/2016; decision no. 633). Ethical approval was subsequently obtained from the Ethics Committee of the Democritus University of Thrace (protocol no. 44844/75; approval date: 24 May, 2017). The study was conducted in accordance with applicable ethical standards and regulations. Informed consent was obtained from all participants prior to their participation in the study.

2.2 Statistical analysis

Data were entered and managed using Microsoft Excel and statistical analyses were performed with IBM SPSS Statistics for Windows (Version 22.0). Continuous variables are presented as mean ± standard deviation and categorical variables as frequencies and percentages. Normality and homogeneity of variances were assessed using the Kolmogorov–Smirnov and Levene tests, respectively. Group comparisons were performed using independent samples t-tests or one-way ANOVA. Welch’s ANOVA with Games-Howell post hoc tests was applied when homogeneity of variance was violated. Nonparametric tests were used, where appropriate. Correlations between categorical variables were examined using the chi-squared test. Bivariate analyses were performed to examine associations between blood lead and cadmium concentrations and demographic characteristics, behavioral risk factors (smoking status and alcohol consumption), and occupational parameters (workplace, job category, and tenure). Variables that showed statistical significance were included in hierarchical linear regression models to identify independent predictors of metal concentrations. Predictors were entered in sequential blocks (demographic, behavioral, and occupational factors) to assess their contribution to the explained variance. Model assumptions (linearity, normality, homoscedasticity, and multicollinearity) were assessed using standard diagnostic criteria. Statistical significance was set at 0.05.

3 Results3.1 General characteristics of the participants

The total sample included 147 workers. (76.9% males, n = 113), with a mean age of 48 ± 7.6 years. Of them, 44.2% (n = 65) were overweight, and 26.5% (n = 39) obese. The majority (54.4%) were active smokers, 25.2% were former smokers, and 20.4% were non-smokers. More detailed information is presented in Table 2.

CharacteristicCategoryn (%)Age≤ 4337 (25.2%)44–5378 (53.1%)≥ 5432 (21.8%)BMI statusNormal weight43 (29.3%)Overweight65 (44.2%)Obese39 (26.5%)SmokingNon-smokers30 (20.4%)Ex-smokers37 (25.2%)Smokers80 (54.4%)Age of smoking onset (†)≤ 18 years45 (56.3%)> 18 years35 (43.7%)Cigarettes/day (†)< 2030 (37.5%)≥ 2050 (62.5%)Pack-years (††)Non-smokers67 (45.6%)Light26 (17.7%)Moderate41 (27.9%)Heavy13 (8.8%)Alcohol useNo134 (91.2%)Yes13 (8.8%)Work positionHigh exposure51 (34.7%)Moderate exposure69 (46.9%)Low exposure27 (18.4%)Occupational siteActive landfill76 (51.7%)Recycling center19 (12.9%)Inactive landfill33 (22.4%)Environmental park19 (12.9%)Years of employment< 10 years58 (39.5%)10–19 years53 (36.1%)≥ 20 years36 (24.5%)

General characteristics (demographic, anthropometric), behavioral risk factors (smoking habits and alcohol use), occupational characteristics and working conditions of participants.

(†) Data refer to self-reported smokers only.

(††) Pack-years = (Number of cigarettes smoked per day/20) × Years of smoking.

Non-smokers = 0 pack years, Light smokers = 1–20 pack years, Moderate smokers = 20–40 pack years, Heavy smokers ≥ 40 pack years.

3.2 Working environment and exposures

As seen in Table 2, participants were employed in four different waste management areas. More specifically, over half of employees (51.7%, n = 76) were employed in an active landfill (Site 1), 19 participants (12.9%) worked in recycling facilities (Recyclable Materials Management Center- Site 2). Moreover, 22.4% (n = 33) were employed in an inactive landfill (Site 3) and 19 (12.9%) in site 4, a rehabilitated/ environmental park (that stopped operating >35 years ago).

Based on exposure levels, 51 employees (34.7%) were classified as highly exposed, including machine operators, drivers, and flagmen; all individuals in this group were male. Sixty-nine employees (46.9%) were moderately exposed, comprising general labor and maintenance personnel. The remaining 27 employees (18.4%) were categorized as having low exposure and included supervisors and administrative staff.

Among the participants, 39.5% (n = 58) had less than 10 years of experience in their current position or specialty, 36.1% (n = 53) had between 10 and 19 years of experience, and 24.5% (n = 36) had more than 20 years of work experience.

3.3 Laboratory exams

To assess the overall health status of the participating workers, a set of hematological and biochemical laboratory tests was conducted. The detailed results of the hematological analyses in the total sample and comparison of differences between sites is displayed in Table 3.

Work positionParameter (normal range)Total sampleMachine operators–drivers–Flagmen (n = 51)General labor and maintenance personnel (n = 69)Supervisory and administrative personnel (n = 27)Test statisticp-valueMean (SD)Mean (SD)Mean (SD)Mean (SD)F*Serum glucose (70–110 mg/dL)97.39 (16.87)98.08 (19.66)97.06 (15.19)96.92 (15.82)F(2.144) = 0.06p = 0.937Creatinine (0.6–1.4 mg/dL)0.91 (0.17)0.97 (0.14)0.88 (0.18)0.88 (0.16)F(2.144) = 4.04p = 0.020Aspartate aminotransferase (AST) (11–38 iu/l)19.88 (8.41)20.78 (6.88)19.97 (10.12)17.96 (5.69)F(2.144) = 1.00p = 0.370Alanine aminotransferase (ALT) (11–43 iu/l)25.39 (14.24)27.29 (10.75)24.90 (16.78)23.07 (12.88)F(2.144) = 0.85p = 0.429White blood cells (4,000-10,000/ mm3)7254.35 (2021.14)7436.47 (1659.23)7193.62 (2126.66)7065.55 (2388.32)F(2.144) = 0.35p = 0.703Hemoglobin (12–16 g/100 mL)14.37 (1.42)15.04 (1.17)14.13 (1.40)13.73 (1.46)F(2.144) = 10.60p < 0.001Hematocrit (36–46%)42.60 (3.69)44.56 (3.13)41.76 (3.47)41.02 (3.79)F(2.144) = 13.35p < 0.001Platelets (140,000-440,000 /mm3)241299.32 (53951.71)231019.61 (45146.65)243130.43 (57690.33)256037.04 (57265.56)F(2.144) = 2.00p = 0.139Neutrophils (40–75%)56.62 (6.92)56.43 (6.96)56.38 (7.06)57.59 (6.60)F(2.144) = 0.33p = 0.723Lymphocytes (20–45%)32.98 (6.29)32.88 (6.27)33.48 (6.41)31.89 (6.12)F(2.144) = 0.62p = 0.537Monocytes (2–10%)7.21 (1.84)7.45 (1.86)7.15 (1.98)6.92 (1.36)F(2.144) = 0.80p = 0.450Eosinophils (1–6%)2.58 (1.70)2.69 (1.67)2.43 (1.59)2.74 (2.03)F(2.144) = 0.47p = 0.627

Hematological-biochemical parameters and blood pressure of the participants (in total and by work position).

Bold Values indicate statistical significance.

3.4 Bivariate analyses of laboratory blood tests and cardiovascular parameters, based on participants’ work position

Bivariate analyses were performed to assess differences in laboratory blood parameters across exposure-level groups. As seen in Table 3, significant differences were observed among employees in the three different work positions in creatinine, hemoglobin, and hematocrit levels. Specifically, in the high-exposure group (i.e., operators, drivers, and flagmen) significantly higher hemoglobin and hematocrit values were found compared with general labor and maintenance personnel, as well as supervisory and administrative staff.

It should be also noted, that no statistically significant differences were identified between occupational groups in heart rate, systolic blood pressure, or diastolic blood pressure (all p > 0.05), with only minimal variation observed across specialties.

3.5 Blood cadmium and lead levels

The analysis showed a statistically significant difference in blood lead levels between males and females, with higher concentrations observed in males (mean 2.26 ± 1.49 μg/dL) compared to females (mean 1.40 ± 0.69 μg/dL), p = 0.001. In contrast, no significant sex difference was found for cadmium levels p = 0.438.

Increasing age was significantly associated with increased blood lead concentrations (p = 0.001), but not with cadmium levels (p = 0.382).

Behavioral factors, particularly smoking and alcohol use, were associated with increased blood concentrations of both lead and cadmium. Smokers had significantly higher mean levels of lead and cadmium compared to ex-smokers and non-smokers. When smoking exposure was further classified by pack-years, moderate (20–40 pack-years) and heavy (≥40 pack-years) smokers showed progressively higher blood concentrations of both metals, indicating a clear dose–response relationship [lead: p = 0.001; cadmium: p < 0.001]. Similarly, participants who smoked at least 20 cigarettes per day had significantly higher lead and cadmium levels than those who smoked fewer cigarettes per day [lead: p = 0.011; cadmium, p = 0.006].

Alcohol consumption was also associated with increased heavy metal levels. Participants who reported alcohol use had significantly higher blood concentrations of both lead (3.45 vs. 1.93 μg/dL) and cadmium (2.88 vs. 1.23 μg/L) compared with those who did not report alcohol consumption (lead: p < 0.001; cadmium: p = 0.001). A comprehensive summary of the bivariate analyses examining associations between heavy metal levels and general and behavioral characteristics is presented in Table 4.

Characteristic–parameterTotal (Ν = 147)Blood lead level (μg/dL)Test statistic*–p-valueBlood cadmium level (μg/L)Test statistic*–p-valuen (%)Mean (SD)Mean (SD)SexMale113 (76.9%)2.26 (1.49)t(145) = 3.251.44 (1.85)t(145) = 0.78Female34 (23.1%)1.40 (0.69)p = 0.0011.17 (1.52)p = 0.438Age≤ 4337 (25.2%)1.50 (0.83)FW(3.56.74) = 7.991.02 (0.99)F(2.144) = 0.9744–5378 (53.1%)2.08 (1.40)p = 0.0011.49 (2.02)p = 0.382≥ 5432 (21.8%)2.66 (1.66)1.51 (1.84)Educational levelPrimary/secondary school36 (24.5%)2.34 (1.51)F(2.144) = 1.291.40 (1.75)F(2.144) = 1.23High school/vocational school90 (61.2%)2.02 (1.41)p = 0.2781.49 (1.93)p = 0.297University21 (14.3%)1.74 (1.05)0.82 (0.82)BMI statusNormal weight43 (29.3%)2.24 (1.67)F(2.144) = 0.661.25 (1.33)F(2.144) = 0.15Overweight65 (44.2%)2.05 (1.33)p = 0.5181.41 (1.97)p = 0.860Obesity39 (26.5%)1.88 (1.15)1.45 (1.89)Alcohol useNo134 (91.2%)1.93 (1.26)t(145) = −3.951.23 (1.53)t(145) = −3.30Yes13 (8.8%)3.45 (1.96)p < 0.0012.88 (3.10)p = 0.001SmokingNon smokers30 (20.4%)1.43 (0.83)FW(2.82.91) = 9.440.34 (0.28)FW(2.76.35) = 28.79Ex-smokers37 (25.2%)1.76 (1.07)p < 0.0010.63 (0.91)p = 0.001Smokers80 (54.4%)2.44 (1.58)2.11 (2.05)Age of smoking onset (†)≤ 18 years old45 (56.3%)2.57 (1.76)t(78) = 0.832.08 (2.14)t(78) = −0.16> 18 years old35 (43.7%)2.27 (1.32)p = 0.4102.15 (1.96)p = 0.876Number of cigarettes smoked per day (†)< 20 cigarettes/day30 (37.5%)1.87 (1.01)t(78) = −2.601.31 (1.22)t(78) = −2.81≥ 20 cigarettes/day50 (62.5%)2.78 (1.76)p = 0.0112.58 (2.30)p = 0.006Pack-year categories (††)Non smokers67 (45.6%)1.61 (0.98)FW(3.41.19) = 7.190.50 (0.71)FW(3.38.14) = 17.53Light smokers26 (17.7%)1.67 (0.80)p = 0.0011.10 (0.87)p < 0.001Moderate smokers41 (27.9%)2.67 (1.46)2.36 (1.74)Heavy smokers13 (8.8%)3.25 (2.39)3.32 (3.46)

Blood lead and cadmium levels according to general characteristics and behavioral risk factors of the participants (smoking habits and alcohol use).

Mean, average number of participants; SD, Standard deviation; df, degrees of freedom.

(*) Independent samples t-test, One way Analysis of Variance–ANOVA (F), Welch’s ANOVA–(FW).

(†)

Data refer to self-reported smokers only.