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Respiratory symptoms and lung function test among cement industry workers at Dangote and Mugher cement industries in Ethiopia
, Aschalew Worku1, Tewodros H. Gebremariam2,3, Dawit Kebede Huluka1, Eyob Kebede Etissa1, Deborah A. Haisch4, Neil Schluger5
*Corresponding author: Amsalu Bitew Workie, Department of Internal Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia. namsalu@yahoo.com
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Received: ,
Accepted: ,
How to cite this article: Workie AB, Binegdie AB, Ahmed HY, Worku A, Haile T, Huluka DK, et al. Respiratory symptoms and lung function test among cement industry workers at Dangote and Mugher cement industries in Ethiopia. J Pan Afr Thorac Soc. doi: 10.25259/JPATS_3_2026
Abstract
Objectives:
The cement industry in Ethiopia is rapidly growing, with a plan to reach 179 kg/capita consumption by 2025. However, there is limited research on respiratory symptoms and lung function tests in the industry. This study aims to determine the prevalence of respiratory symptoms, lung function status, and associated factors among cement industry workers.
Materials and Methods:
A cross-sectional study was conducted on 458 cement factory workers in Ethiopia using the British Medical Research Council questionnaire and the Medical Research Council questionnaire with certain modifications. The study measured and interpreted forced expiratory volume (FEV1), forced vital capacity (FVC), FEV1/FVC, and peak expiratory flow rate according to the American Thoracic Society/European Respiratory Society recommendations. A simple random sampling method was used to select participants. A multivariable binary logistic regression was used to identify factors associated with respiratory symptoms and abnormal lung function.
Results:
The prevalence of respiratory symptoms was 47.6%. Abnormal spirometry characterized by an FEV1/FVC ratio <0.70 was found in only 5.7% of the study subjects, and FEV1/FVC > 0.70 with FEV1 < 0.80 was found in 8.8% of study subjects. Factors such as body mass index (p = 0.009), personal protective equipment (PPE) use (p = 0.010), and respiratory disease history (p = 0.000) were significantly associated with respiratory symptoms. Place of residence (p = 0.033), employment (p = 0.017), presence of symptoms (p = 0.040), oxygen saturation (p = 0.033), and history of disease (p = 0.023) were also associated with abnormal lung function.
Conclusion:
The study reveals a high prevalence of respiratory symptoms despite most individuals using PPE and a low prevalence of abnormal lung function despite the long duration of exposure.
Keywords
Cement workers
Ethiopia
Lung function
Occupational exposure
Respiratory symptoms
INTRODUCTION
Occupational exposures are significant contributors to the global burden of respiratory diseases, with pneumoconiosis, such as silica, coal workers’ pneumoconiosis, and asbestosis contributing nearly 100% of the occupational burden. Other conditions with an estimated occupational burden of 10% or more include asthma, chronic obstructive pulmonary disease (COPD), chronic bronchitis, idiopathic pulmonary fibrosis, hypersensitivity pneumonitis, other noninfectious granulomatous lung diseases (including sarcoidosis), pulmonary alveolar proteinosis, and community-acquired pneumonia.[1,2]
The Global Burden of Disease study found that COPD, asthma, and pneumoconioses caused 519,000 deaths globally, accounting for almost 34% of all fatalities caused by occupational exposures studied. Lung cancer accounted for 300,000 deaths, and mesothelioma caused 28000 deaths.[2] Cement dust, a common source of crystalline silica, is one of the earliest recognized and most studied occupational inhalational exposures. Inhalation of respirable crystalline silica dust causes silicosis, a chronic fibrotic lung disease, but is also associated with an increased risk of COPD, lung cancer, and tuberculosis (TB). Silicosis is a fibrotic respiratory disease caused by the inhalation and deposition of respirable crystalline silica (SiO2) particles <10 μm in diameter.[3-6]
A systematic review of 594 studies found reduced lung function levels in workers exposed to cement dust. Symptoms ranged from 1.2 to 4.8, and forced expiratory volume (FEV1)/forced vital capacity (FVC) was 1–6% lower in exposed workers.[7] Cohort studies reported a high yearly decline in FEV1/FVC. A dose–response relationship between exposure and lung function decline was only shown in one cohort.[7] A study in Nigeria found that cement factory workers with a mean exposure duration of 10.2 ± 5.6 years to cement dust had significantly lower vital capacity and FEV1 compared to non-exposed subjects.[8] In the United Arab Emirates (UAE), a study found that exposed workers had higher respiratory symptoms and decreased ventilator function compared to unexposed workers.[9] A cross-sectional study in the Democratic Republic of Congo found a higher prevalence of COPD and respiratory symptoms among workers exposed to cement dust, particularly in cleaning, transportation, and production tasks.[10]
A study in Ethiopia found that cleaners and production workers had significantly higher chronic respiratory symptoms than controls. Between 2009 and 2010, these workers experienced a significant reduction in FEV1 and FEV1/FVC.[11] A cross-sectional study in Dejen cement factory revealed 62.9% of workers had chronic respiratory symptoms. Factors affecting these symptoms included male sex, age, education, work experience, lack of occupational safety training, smoking, and chronic respiratory diseases.[12] A study at Dire Dawa cement factory found high dust exposure in the crusher, packing, and guards’ sections, with years of work and current smoking causing a decrease in peak expiratory flow (PEF).[13]
Ethiopia’s cement industry is rapidly growing, with an average per capita cement consumption increasing from 39 kg to 62 kg. The government plans to expand the industry by upgrading existing plants and opening new ones. By the year 2025, per capita cement consumption is expected to increase to 179 kg. The country has become one of Africa’s largest cement markets and a major exporter in the SubSaharan African region. However, the industry heavily relies on imported energy sources and outdated technologies, which have environmental and energy impacts. Due to the expansion and growth of the industry, energy consumption and CO2 emissions are expected to increase. In the year 2010, 1.4Mt of CO2 emission was recorded only from the production of cement in Ethiopia, which also had a health impact.[4] This study aims to assess the impact of cement dust exposure and associated factors on the lung health of cement industry workers at Dangote and Mugher cement industries.
MATERIAL AND METHODS
Study sites and period
Dangote and Mugher Cement Industries (Ethiopia) Plc are located in the Oromia regional government, West Shewa zone, Ada Berga woreda, around 90 km away from Addis Ababa, with 3286 and 2500 employees respectively. The study period was from August 2022 to April 2023.
Study design
A cross-sectional study design was employed for this research. The source population consisted of all employees working in the Dangote and Mugher cement industries. The study population included employees who were randomly selected from the Dangote and Mugher cement plants.
Inclusion and exclusion criteria
Inclusion criteria
Employees who were actively working and willing to provide informed consent were included in the study.
Exclusion criteria
Employees who were not eligible for spirometry were excluded. This included individuals who had undergone a recent surgical procedure involving the head, chest, abdomen, or eyes. Employees with unexplained hemoptysis (coughing up blood) were also excluded. In addition, employees diagnosed with TB and those with a history of pneumothorax or who were at a higher risk of developing pneumothorax were not included in the study.
Sample size determination
The sample size was determined using the single population proportion formula. The calculation assumed a 95% confidence level (CI), 80% power, and a 5% margin of error. The prevalence of chronic respiratory symptoms was taken as 0.62, while the prevalence of lung function decline was 0.36.[12,13] After accounting for a 10% non-response rate, the final sample size was set at 399 participants. Although the calculated minimum sample size was 399, we included 458 participants to improve the precision of prevalence estimates and enhance the statistical power for subgroup analyses. Of these, 326 employees were selected from Dangote and 132 employees from Mugher. This over-enrollment was possible due to greater-than-expected worker availability during the data collection period.
Data Collection tool, procedure, and quality assurance
Using a pre-developed and pre-tested case report form, the employees were interviewed. Respiratory symptoms were assessed through standardized participant self-reports. Under the supervision of the primary investigator and an experienced data collector, the interviews were conducted by a qualified nurse. The British Medical Research Council questionnaire and the Medical Research Council Questionnaire (MRCQ), with certain modifications, were used to collect the data.[14] Using the Easy on-PC spirometer, order no: 2700-3, FEV1, FVC, FEV1/FVC, and PEF rate were measured and interpreted according to the American Thoracic Society/European Respiratory Society recommendations (ATS/ERS) for all selected individuals by an experienced trained nurse during the time of the interview.[15,16]
The spirometer underwent daily calibration using a 3-L syringe, verifying volume accuracy within a ±3% tolerance in order to maintain data integrity, each participant was required to complete a minimum of three acceptable maneuvers to ensure the reliability of the lung function measurements. The 20 participants who underwent post-bronchodilator testing were those who demonstrated an obstructive pattern on prebronchodilator spirometry and were known asthmatic and COPD patients.
Personal dust samples were gathered from workers’ breathing zones using 37 mm Millipore plastic sampling cassettes equipped with 5 μm pore size polyvinyl chloride filters that were connected to Side Kick Casella pumps set to a flow rate of 2 L/min. The average sampling time was 280 min, ranging from 188 to 323 min. The dust samples were analyzed gravimetrically at the Environmental and Occupational Health (EOSH) laboratory of the College of Health Sciences, Addis Ababa University, using an AT261 Mettler Toledo microbalance scale with a detection limit of 0.01 mg/m3. If the flow rate deviated by ±10% from the 2.0 L/min target, the sample was deemed invalid for analysis. In addition, pumps were inspected every 2 h during the sampling period to ensure they were functioning correctly. Field blanks were employed to adjust for any changes in weight during the sampling process.
Sampling process for personal total dust exposure assessment
The sample size for assessing personal total dust exposure was determined following the guidelines proposed by Rappaport et al. (2008).[17] They recommended that 5–10 randomly selected individuals, with 10–20 measurements per similar exposure group (SEG), are sufficient to estimate group exposure levels for cement dust. An SEG is defined as a group of workers performing the same type of job in a comparable work area for the same duration. In this study, four SEGs were identified: the crusher, raw mill, cement mill, and packing sections. Five workers from each SEG were randomly chosen for personal total dust measurements, resulting in a total of 40 samples with repeated measurements. The subjects of the study are 20 in number, but for each one of them, two samples were taken, which makes 40 samples to get a reliable average measurement.
Study variables
Dependent variables
The dependent variables of the study were respiratory symptoms and lung function test results.
Independent variables
The independent variables included sociodemographic characteristics, occupational exposure history and safety practices, smoking history, respiratory symptoms, history of respiratory diseases, other medical illnesses, and spirometry parameters.
Operational definitions
Respiratory symptoms
They are operationally defined according to the definition of MRCQ definition of respiratory symptoms approved Medical Research Council’s Committee on EOSH.
Standardization of spirometry is based on the updated 2019 guideline of ATS/ERS. Interpretative strategies on lung function tests are based on the 2015 series “ATS/ERS task force” for standardization of lung function testing.
Pack years
Number of years a patient has smoked. It is calculated by the number of packs of cigarettes smoked in a day times years of smoking.
Data entry and analysis
The collected data were entered into Epi-Info Version 7, cleaned, and analyzed using SPSS Version. 26. The continuous variables were expressed by computing the mean and standard deviation, whereas the categorical variables were expressed as frequency and percentage. They were presented in the form of tables. We utilized binary logistic regression to examine factors associated with the prevalence of respiratory symptoms and abnormal lung function. All the potential independent variables were included in the multivariable regression model after a fitness test on the model was met (Hosmer and Lemeshow test, p = 0.919 and 0.327, respectively), a 95% CI was used, and a p = 0.05 was considered statistically significant.
The dust samples were analyzed gravimetrically at the EOSH laboratory of the College of Health Sciences, Addis Ababa University, using an AT261 Mettler Toledo microbalance scale with a detection limit of 0.01 mg/m3.
Ethical clearance
The proposal was submitted and approved by the Ethics and Research Committee of the Department of Internal Medicine and the Institutional Review Board of the College of Health Sciences of Addis Ababa University. Study participants were also asked to give their informed consent. The research was done in accordance with the Declaration of Helsinki and in strict confidence in collaboration with the national cement enterprise and the national ethical committee.
RESULTS
Data were collected from 458 cement plant workers: 326 (71.2%) from Dangote and 132 (28.8%) from Muger cement plant. The majority of the participants, 411 (89.7%), were male, and 47 (10.3%) were female. The mean age of the sample was 37 years (standard deviation ± 9). The majority (203, 44.3%) was between the ages of 30 and 39 years. Most of the employees are literate, completing at least elementary school 343 (74.9%), and the majority of the workers 267 (58.3%) live within a 500-m distance around the production area, 36% resides far away from, and only 26 (5.7%) live inside the compound of the cement plant. There is no initial medical checkup documented for the majority of employees at the time of employment, 409 (89.3%), and more than two-thirds 309 (69.7%), have a normal body mass index (BMI).
More than one-third of workers included in the study are working in areas of cement processing and packing, 158 (34.5%). 87.3% of workers are exposed to cement dust for more than 5 years, and 335 (73.1%) have a habit of always using personal protective equipment’s (PPEs). Only 27 (5.9%) of workers were found to be either current or ex-smokers [Table 1].
| Variables | n(%) |
|---|---|
| Age in years: Mean (SD)=37±9 | |
| 18–29 year | 105 (22.9) |
| 30–39 year | 203 (44.3) |
| 40–49 years | 86 (18.8) |
| ≥50 | 64 (14.0) |
| Sex | |
| Male | 411 (89.7) |
| Female | 47 (10.3) |
| Level of education | |
| Illiterate | 15 (3.3) |
| Only read and write | 2 (0.4) |
| Elementary and junior school | 98 (21.4) |
| High school | 109 (23.8) |
| College and above | 234 (51.1) |
| Place of residence | |
| Inside the compound of the factory | 26 (5.7) |
| Within a 500-m distance around the production area | 267 (58.3) |
| Far away from the production area | 165 (36.0) |
| An initial check-up at employment | |
| Yes | 49 (10.7) |
| No | 409 (89.3) |
| Body mass index: mean (SD)=23±3.5 | |
| Underweight | 33 (7.2) |
| Normal | 309 (67.5) |
| Overweight | 98 (21.4) |
| Obese | 18 (3.9) |
| Place of employment | |
| Raw material (Crusher, crane, and raw mill) | 27 (5.9) |
| Cement processor (Kiln, cement mill, and maintenance worker) and packing | 158 (34.5) |
| Guard and cleaners | 60 (13.1) |
| Others (Office, drivers, health, safety, and environmental workers) | 105 (22.9) |
| Year of service: Median (interquartile range), 9 (7–15) | |
| <5 years | 58 (12.7) |
| 5–10 years | 209 (45.6) |
| 10 years | 191 (41.7) |
| Availability of PPE | |
| Yes | 431 (94.1) |
| No | 27 (5.9) |
| Availability of facemask | |
| Yes | 412 (90.0) |
| No | 46 (10.0) |
| Habits of using PPEs | |
| Always | 335 (73.1) |
| Often | 60 (13.1) |
| Occasional | 38 (8.3) |
| None | 25 (5.5) |
| Smoking | |
| Yes | 27 (5.9) |
| No | 431 (94.1) |
PPE: Personal protective equipment, SD: Standard deviation
The prevalence of respiratory symptoms in cement factory workers was 218 (47.6%). Recurrent sneezing 166 (36.2%) and recurrent nasal discharge 143 (31.2%) were the most prevalent, followed by cough 93 (20.3). Sixty-eight (14.8%) have a history of respiratory disease, and the number of workers with bronchial asthma was 23 (5.0%). Comorbidities other than respiratory diseases were prevalent in 47 of the employees (10.3%), with the most prevalent being hypertension (36, 7.9%) [Table 2].
| Variables | Status | n(%) |
|---|---|---|
| Respiratory symptom | Yes | 218 (47.6) |
| No | 240 (52.4) | |
| Cough | Yes | 93 (20.3) |
| Phlegm (sputum) | Yes | 71 (15.5) |
| Shortness of breath | Yes | 83 (18.1) |
| Nocturnal breathlessness | Yes | 55 (12.0) |
| Wheezing | Yes | 62 (13.5) |
| Chest pain/tightness | Yes | 85 (18.6) |
| Difficulty of nasal breathing | Yes | 92 (20.1) |
| Recurrent sneezing | Yes | 166 (36.2) |
| Recurrent nasal discharge | Yes | 143 (31.2) |
| oxygen saturation: Median (interquartile range), 95 (93–96) | <95% | 182 (39.7) |
| ≥95% | 276 (60.3) | |
| History of respiratory disease | Yes | 68 (14.8) |
| No | 390 (85.2) | |
| Chest injury or trauma | Yes | 8 (1.7) |
| Bronchitis | Yes | 10 (2.2) |
| Bronchial Asthma | Yes | 23 (5.0) |
| Pulmonary tuberculosis | Yes | 9 (2.0) |
| Pleurisy | Yes | 2 (0.4) |
| COVID-19 | Yes | 18 (3.9) |
| Comorbidity (medical illness) | Yes | 47 (10.3) |
| No | 411 (89.7) | |
| Diabetes mellitus | Yes | 11 (2.4) |
| Hypertension | Yes | 36 (7.9) |
| Dyslipidemia | Yes | 3 (0.7) |
| Chronic kidney disease | Yes | 10 (2.2) |
| Malignancy | Yes | 0 (0.0) |
BMI, habit of using PPE, and history of respiratory disease were significantly associated with the prevalence of respiratory symptoms. The odds of having respiratory symptoms were 6 times higher in obese workers (adjusted odds ratio [AOR] = 6.12, 95% CI: 1.57, 23.87, p = 0.009). The presence of a history of respiratory disease also increased the odds of having respiratory symptoms (AOR = 3.63, 95% CI: 1.67, 5.52, p= 0.000). Those workers with a habit of occasionally using PPE had 68% lower odds of having respiratory symptoms than those with the habit of always using (AOR = 0.32, 95% CI: 0.13, 0.76, p = 0.010) [Table 3].
| Variables | Unadjusted OR (95% CI) | p-value | Adjusted OR (95% CI) | p-values |
|---|---|---|---|---|
| Age | ||||
| 18–29 | 1 | 1 | ||
| 30–39 | 0.93 (0.58–1.49) | 0.763 | 0.91 (0.51–1.64) | 0.752 |
| 40–49 | 0.83 (0.46–1.47) | 0.526 | 0.60 (0.27–1.32) | 0.208 |
| ≥50 | 1.60 (0.85–3.01) | 0.139 | 1.08 (0.44–2.66) | 0.861 |
| Sex | ||||
| Male | 1.14 (0.62–2.09) | 0.673 | 2.14 (0.96–5.13) | 0.071 |
| Female | 1 | 1 | ||
| Level of education | ||||
| Illiterate | 1 | 1 | ||
| Only read and write | 0.50 (0.26–9.77) | 0.648 | 0.29 (0.01–7.05) | 0.450 |
| Elementary and junior school | 0.61 (0.19–1.92) | 0.403 | 0.67 (0.19–2.47) | 0.577 |
| High school | 0.40 (0.13–1.27) | 0.123 | 0.38 (0.10–1.35) | 0.137 |
| College and above | 0.40 (0.13–1.20) | 0.104 | 0.40 (0.11–1.37) | 0.143 |
| Place of residence | ||||
| Inside the factory | 0.54 (0.22–1.32) | 0.182 | 0.55 (0.20–1.48) | 0.236 |
| Within a 500-m distance of the production area | 1.27 (0.86–1.88) | 0.219 | 1.12 (0.68–1.83) | 0.653 |
| Far away from the production area | 1 | 1 | ||
| Body mass index | ||||
| Underweight | 1.13 (0.55–2.33) | 0.728 | 1.07 (0.49–2.33) | 0.853 |
| Normal | 1 | 1 | ||
| Overweight | 1.11 (0.70–1.75) | 0.646 | 1.29 (0.78–2.12) | 0.317 |
| Obese | 6.03 (1.71–21.27) | 0.005 | 6.12 (1.57–23.87) | 0.009 |
| Place of employment | ||||
| Raw material | 1.48 (0.63–3.49) | 0.360 | 1.43 (0.56–3.63) | 0.455 |
| Cement processor and packing | 0.95 (0.60–1.51) | 0.854 | 0.88 (0.52–1.47) | 0.628 |
| Guard and cleaners | 1.83 (0.96–3.49) | 0.064 | 1.76 (0.75–4.15) | 0.194 |
| Others | 1 | 1 | ||
| Year of service | ||||
| <5 years | 1 | 1 | ||
| 5–10 years | 0.63 (0.35–1.13) | 0.124 | 0.68 (0.34–1.37) | 0.288 |
| >10 years | 0.67 (0.37–1.22) | 0.193 | 0.63 (0.29–1.36) | 0.245 |
| Habits of using personal protective equipment | ||||
| Always | 1 | 1 | ||
| Often | 0.70 (0.40–1.22) | 0.212 | 0.69 (0.37–1.28) | 0.236 |
| Occasional | 0.35 (0.16–0.74) | 0.006 | 0.32 (0.13–0.76) | 0.010 |
| None | 1.25 (0.55–2.83) | 0.593 | 0.82 (0.30–2.23) | 0.705 |
| Smoker (current or former) | ||||
| Yes | 1.64 (0.74–3.63) | 0.215 | 1.28 (0.51–3.18) | 0.591 |
| No | 1 | 1 | ||
| Oxygen saturation | ||||
| <95% | 0.87 (0.60–1.27) | 0.488 | 0.81 (0.53–1.24) | 0.337 |
| ≥95% | 1 | 1 | ||
| Hx of respiratory disease | ||||
| Yes | 2.65 (1.53–4.57) | <0.001 | 3.63 (1.67–5.52) | <0.001 |
| No | 1 | 1 | ||
| Comorbidity (medical illness) | ||||
| Yes | 1.28 (0.70–2.35) | 0.419 | 1.08 (0.49–2.36) | 0.848 |
| No | 1 | 1 |
CI: Confidence interval, OR: Odds ratio
The pre-means values of FVC, FEV1, and FEV1/FVC of the employees were found to be normal 4.00 ± 0.72, 3.31 ± 0.62, and 0.82 ± 0.06, respectively. Similarly, the mean predicted % of FVC, FEV1, and FEV1/FVC ratio were found to be 101.7 ± 16.4, 100.9 ± 16.6, and 99.8 ± 7.9, respectively. Twenty-six employees (5.7%) were found to have an FEV1/FVC ratio of <0.70. In those with FEV1/FVC ratio >0.70, only 38 of them (8.8%) were found to have FEV1 < 80% predicted value [Table 4].
| Variables | Mean |
|---|---|
| Pre-bronchodilator n=458 | |
| Pre FVC | 4.00±0.72 |
| Pre FEV1 | 3.31±0.62 |
| Pre FEV1/FVC | 0.82±0.06 |
| Pre PEFR | 8.95±2.03 |
| Pre FVC %Pred | 101.72±16.45 |
| Pre FEV1Pred | 100.94±16.64 |
| Pre FEV1/FVC Pred | 99.82±7.94 |
| Pre PEFR Pred | 106.14±21.1 |
| Post-bronchodilator n=20 | |
| Post FVC | 4.15±0.85 |
| Post FEV1 | 3.31±0.84 |
| Post FEV1/FVC | 0.73±0.07 |
| Post PEFR | 8.03±1.66 |
| Post FVC % Pred | 101.35±19.69 |
| Post FEV1% Pred | 91.75±19.35 |
| Post FEV1/FVC % Pred | 90.75±8.46 |
| Post PEFR Pred | 92.05±17.66 |
PEFR: Peak expiratory flow rate, FEV: Forced expiratory volume, FVC: Forced vital capacity
After adjusting for covariates, place of residence, place of employment, presence of respiratory symptoms, oxygen saturation (SpO2), and history of respiratory disease were significantly associated with abnormal lung function (FEV1/FVC ratio <70) in the multivariable binary logistic regression. Workers who live within 500-m distance of the cement plant and those working in cement processor and packing had a 76% reduced risk of abnormal lung function than those who live far away from production area and other relatively non exposed workers (AOR = 0.24, 95% CI: 0.06, 0.88, p = 0.033) and (AOR = 0.24, 95% CI: 0.07, 0.77, p = 0.017) respectively. Participants having respiratory symptoms were 3 times (AOR = 3.13, 95% CI: 1.05, 9.29, p = 0.040) more likely to have abnormal lung function. Workers SpO2 < 95% had a 3-times (AOR = 2.97, 95% CI: 1.09, 8.08, p = 0.033) higher risk of abnormal lung function. Patients with a history of respiratory disease had a more than 3-fold higher odds of abnormal lung function compared to those who had not had (AOR = 3.30, 95% CI: 1.18, 9.26, p = 0.023) [Table 5].
| Variables | Unadjusted OR (95% CI) | p-value | Adjusted OR (95% CI) | p-value |
|---|---|---|---|---|
| Age | ||||
| 18–29 | 1 | 1 | ||
| 30–39 | 1.39 (0.36–5.37) | 0.629 | 0.81 (0.15–4.26) | 0.800 |
| 40–49 | 2.55 (6.19–10.51) | 0.195 | 0.51 (0.07–3.50) | 0.496 |
| ≥50 | 5.55 (1.44–21.40) | 0.013 | 1.06 (0.14–8.02) | 0.953 |
| Sex | ||||
| Male | 1090 (0.00–….) | 0.997 | 1078 (0.00–….) | 0.997 |
| Female | 1 | 1 | ||
| Level of education | ||||
| Illiterate | 1 | 1 | ||
| Only read and write | 0.00 (0.00–….) | 0.999 | 0.00 (0.00–….) | 0.999 |
| Elementary and junior school | 1.95 (0.23–16.22) | 0.535 | 2.26 (0.14–35.06) | 0.558 |
| High school | 0.53 (0.56–5.11) | 0.586 | 0.62 (0.03–11.90) | 0.755 |
| College and above | 0.56 (0.66–4.73) | 0.595 | 0.42 (0.02–7.27) | 0.557 |
| Place of residence | ||||
| Inside the factory | 1.06 (0.22–5.04) | 0.939 | 0.39 (0.05–2.72) | 0.345 |
| Within a 500-m distance of the production area | 0.66 (0.26–1.36) | 0.225 | 0.24 (0.06–0.88) | 0.033 |
| Far away from the production area | 1 | 1 | ||
| Body mass index | ||||
| Underweight | 0.50 (0.65–3.91) | 0.513 | 0.78 (0.08–7.60) | 0.832 |
| Normal | 1 | 1 | ||
| Overweight | 0.86 (0.31–2.40) | 0.787 | 0.74 (0.20–2.79) | 0.667 |
| Obese | 2.02 (0.43–9.47) | 0.372 | 0.70 (0.09–5.17) | 0.729 |
| Place of employment | ||||
| Raw material | 0.35 (0.44–2.92) | 0.338 | 0.26 (0.02–2.63) | 0.254 |
| Cement processor and packing | 0.28 (0.11–0.75) | 0.011 | 0.24 (0.07–0.77) | 0.017 |
| Guard and cleaners | 1.20 (0.43–3.35) | 0.720 | 1.44 (0.30–6.91) | 0.645 |
| Others | 1 | 1 | ||
| Year of service | ||||
| <5 years | 1 | 1 | ||
| 5–10 years | 2.56 (0.31–20.67) | 0.376 | 1.75 (0.17–18.27) | 0.638 |
| >10 years | 5.21 (0.67–40.17) | 0.113 | 4.80 (0.42–53.98) | 0.204 |
| Habits of using personal protective equipment | ||||
| Always | 1 | 1 | ||
| Often | 1.81 (0.64–5.14) | 0.264 | 1.54 (0.34–5.51) | 0.502 |
| Occasional | 1.10 (0.24–5.01) | 0.894 | 0.52 (0.08–3.04) | 0.470 |
| None | 2.71 (0.73–10.04) | 0.134 | 0.46 (0.07–3.12) | 0.431 |
| Smoker (current or former) | ||||
| Yes | 3.23 (1.02–10.16) | 0.045 | 1.18 (0.28–4.92) | 0.818 |
| No | 1 | 1 | ||
| Respiratory symptom | ||||
| Yes | 3.93 (1.55–10.0) | 0.004 | 3.13 (1.05–9.29) | 0.040 |
| No | 1 | 1 | ||
| Oxygen saturation | ||||
| <95% | 3.05 (1.33–7.01) | 0.008 | 2.97 (1.09–8.08) | 0.033 |
| ≥95% | 1 | 1 | ||
| Hx of respiratory disease | ||||
| Yes | 4.03 (1.74–9.30) | 0.001 | 3.30 (1.18–9.26) | 0.023 |
| No | 1 | 1 | ||
| Comorbidity (medical illness) | ||||
| Yes | 0.87 (0.25–3.01) | 0.825 | 0.41 (0.07–2.37) | 0.322 |
| No | 1 | 1 |
CI: Confidence interval, OR: Odds ratio
Characteristics of personal total cement dust exposure by job groups
The data were gathered from 20 subjects working in the cement industry, resulting in a total of 40 repeated samples. The average sampling time was 280 min, with a range of 188–323 min. The arithmetic mean (AM) and geometric mean for the overall total dust exposure were 34.0 mg/m3 and 18.3 mg/m3, respectively, with a range of 2.2–94.5 mg/m3 [Table 6]. It is important to note that all the samples (100%) exceeded the Occupational Safety and Health Administration (OSHA) exposure limit of 10 mg/m3.
| Job Groups/Departments | Sampling time (min) AM (range) |
NW | NS | AM (range) (mg/m3) |
GM (mg/m3) | % OEL >10 mg/m3 (OSHA) |
|---|---|---|---|---|---|---|
| Packing | 284 (187–314) | 5 | 10 | 71.7 (42.7–94.5) | 69.2 | 100 |
| Loading | 271 (207–294) | 5 | 10 | 14.1 (2.2–57.0) | 5.7 | 100 |
| Cement Mill | 282 (254–323) | 5 | 10 | 37.0 (16.8–65.8) | 33.3 | 100 |
| Limestone store | 285 (282–287) | 5 | 10 | 13.0 (3.6–34.92) | 8.5 | 100 |
| Grand-total | 280 (188–323) | 20 | 40 | 34.0 (2.2–94.5) P95=93.96 | 18.3 | 100 |
OEL: Occupational exposure limit>10 mg/m3; AM: Arithmetic Mean; NS: Number of samples, NW: Number of workers, GM: Geometric mean, P95: 95th percentile
The packing job group had the highest AM of cement dust exposure at 71.7 mg/m3, with a range from 42.7 mg/m3 to 94.5 mg/m3, followed by the cement mill job group at 37.0 mg/m3, ranging from 16.8 mg/m3 to 65.8 mg/m3. The limestone store had the lowest dust concentration at 13.0 mg/m3 [Table 6].
DISCUSSION
This study found that the overall prevalence of respiratory symptoms among cement factory workers was 47.6%, Among the identified symptoms, recurrent sneezing (36.2%) and recurrent nasal discharge (31.2%) were the most common, followed by cough (20.3%), chest tightness (18.6%), shortness of breath (18.6%), phlegm (15.5%), and wheezing (13.5%). Notably, all workers with morbid obesity (BMI > 30 kg/m2) were symptomatic, suggesting that obesity may be an important risk factor for respiratory symptoms in this population. In addition, 39.7% of participants had peripheral SpO2 below 95% at the time of assessment, although the underlying causes require further investigation.
Regarding lung function, the majority of participants had FVC, FEV1, and FEV1/FVC values within the predicted ranges based on ATS/ERS standards. Only 5.7% had an FEV1/FVC ratio below 0.7, and among those with normal ratios, only 8.8% had FEV1 values below 80% of predicted. These findings suggest relatively preserved lung function despite the presence of respiratory symptoms.
Notably, the packaging department of the factories exhibited significantly elevated dust exposure levels (mean = 71.7 mg/m3), highlighting from the outset that this area represents a key priority for occupational health interventions.
When compared with other studies, the prevalence observed in this study is lower than reports from Dejen cement factory (62.9%) and cement factory workers from North Shoa Administrative Zone (66.2%). Similarly, studies from Shiraz, Iran, reported higher frequencies of symptoms such as cough (31.8%), phlegm (21.6%), and wheezing (28.4%). Furthermore, higher prevalences of chronic respiratory symptoms, including chronic cough (24.5%), chronic phlegm (24.5%), chronic wheezing (36.9%), and chronic shortness of breath (38.6%), were documented in earlier studies from Dejen.[12-14]
The relatively lower prevalence in the present study may be explained by several factors, including the use of improved industrial technology, a high level of PPE utilization (86.25%), and data collection conducted across both dry and rainy seasons, which may have reduced exposure variability. Unlike many previous studies, this study also provided a more detailed characterization of individual symptoms, allowing better clinical interpretation of symptom patterns.
In contrast to studies demonstrating significant reductions in lung function among exposed workers, such as those conducted in Nigeria, the UAE, and longitudinal studies in Ethiopia, the present study did not find substantial impairment in spirometry indices. For example, prior research has shown reduced FEV1 and FEV1/FVC ratios and accelerated decline in lung function among highly exposed workers. However, the absence of a control group and baseline lung function measurements in this study limits direct comparison and causal inference.[8,9,11]
The observed “PPE paradox,” where respiratory symptoms are common despite frequent PPE use, yet occasional users show lower odds of symptoms (AOR = 0.32, p = 0.010), likely stems from reverse causality and the healthy worker effect.[18] Symptomatic workers may adopt consistent PPE use, while healthier workers use it less often yet remain symptom-free.[19] Moreover, self-reported “always” use does not ensure correct or effective use.[20] Thus, these findings should be interpreted cautiously, as they probably reflect behavioral and methodological biases rather than a true protective effect.
This study has several strengths. It provides a comprehensive assessment of respiratory symptoms alongside objective spirometry measurements, and it includes detailed symptom profiling, which enhances clinical relevance. In addition, the inclusion of workers across different seasons improves the representativeness of exposure conditions. A key strength of this study is the environmental assessment, which identified a critically hazardous work environment with all dust concentrations exceeding OSHA limits.
However, the study also has important limitations. The cross-sectional design limits the ability to establish causality between cement dust exposure and respiratory outcomes. The lack of a control group and baseline lung function data further restricts the interpretation of the observed spirometry findings. Moreover, security challenges during data collection resulted in the underrepresentation of workers from key high-exposure units such as grinding, crushing, and raw mill processing sections, as well as the exclusion of workers from the Mugher cement plant. These issues may have introduced selection bias and limited the generalizability of the findings.
CONCLUSION
The comparatively lower prevalence of symptoms observed in this study may reflect improvements in workplace conditions, including better technology and higher utilization of PPE. However, the presence of symptoms alongside largely normal spirometric findings highlights the need for continued surveillance, as early respiratory effects may precede measurable declines in lung function.
Given the limitations of the cross-sectional design and absence of baseline or control comparisons, causal relationships cannot be firmly established. Therefore, further longitudinal studies with appropriate control groups are recommended to better understand the long-term impact of cement dust exposure. Strengthening occupational health measures, promoting consistent use of protective equipment, and addressing modifiable risk factors such as obesity are essential to reduce the burden of respiratory symptoms among cement factory workers. The packing department showed exceptionally high dust exposure levels, highlighting it as a priority area for targeted interventions, including engineering controls, improved ventilation, and stricter dust mitigation strategies.
Acknowledgment:
East African Training Initiative and Addis Ababa University.
Ethical approval:
The research/study was approved by the Institutional Review Board at Addis Ababa University, College of Health Science (IRB), number 016/22/IM, dated April 26, 2022.
Declaration of patient consent:
The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient has given consent for clinical information to be reported in the journal. The patient understands that the patient’s names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Conflict of interest:
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation:
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript, and no images were manipulated using AI.
Financial support and sponsorship: East African Training Initiative (EATI)
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