Competitive study of heat-exposed and non-heat-exposed group of workers of Underground Coal Mines, Punjab, Pakistan

doi:10.21203/rs.3.rs-2082288/v1

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Competitive study of heat-exposed and non-heat-exposed group of workers of Underground Coal Mines, Punjab, Pakistan

https://doi.org/10.21203/rs.3.rs-2082288/v1

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Aim

To identify prevalence and comparison of heat-induced illnesses among. Design: cross-sectional survey and comparison. Methods: Ingestible thermometric pills, skin temperature probes, US-NIOSH heat stress sheet and general questionnaire were used to study 50 coal cutters (25 from 5 hot mines (G1) and 25 from 5 non-hot mines (G2)). Results: The highest monitored temperature was 33.6 ⁰C in mine 1 and humidity 83.3% in mine 3. Comparing values of two groups of mines, the p-value was < 0.001 for Wet Bulb Globe Temperature and Dry Bulb Temperature, and 0.031 for Relative Humidity. The highest core body temperature (38.8⁰C) and skin temperature (36.6⁰C) were in workers of G1, who also reported symptoms of heat-illness for 3 + days/week. Post-shift samples (of blood and urine) from G1 showed that the hematocrit (%) reduced to 43.6 ± 2.1 from 45.4 ± 1.4, eGFR reduced from100 ± 19 to 94 ± 09 mL/min/1.72m². Public contribution: Performing exertive work in hot environment prompts heat-induced-illnesses.

Workers’ health

underground coal mines

heat-related illnesses

chronic kidney disease (CKD)

The interaction between the human body and a hot environment causes physical suffering in workers, worsening when the job is exertive. For example, agricultural activity (sugarcane farming), building constructions, underground mining require excessive exertion (Maurya et al. 2015; Al-Bouwarthan et al. 2019; Johnson et al. 2019; Carter et al. 2020). It increases the net heat load on the bodies of workers who, when exposed to such hot environments for more extended period, become prone to kidney dysfunction (Thomas et al. 2019). Chronic kidney disorder (CKD) is high in workers of various industries. Despite the lack of research on the CKD etiology, many researchers conclude the detrimental role of high environmental temperatures in kidney disorders (Schlader et al. 2019).

The temperature of most of the underground coal mines remains high(Lee et al. 2019). This elevated temperature, accompanied by high humidity, builds pressure on workers’ bodies (Yantek et al. 2019). The manual coal cutting work in mines necessitates the exertion of body parts, which increases the workers’ temperature due to the hot and humid environment (Yantek et al. 2019).

Aims

To survey heat-induced- illnesses among coal mines’ workers
To compare the prevalence of heat-induced illness between heat-exposed and non-heat exposed workers

Study design and population

Walkthrough survey

A walkthrough survey was conducted to assess ambient air conditions of selected mines where the coal cutters were cutting the coal seam. Another purpose of this walkthrough survey was to obtain the consent of workers to participate in the study.

Study area and sample population

Although 600 mine workers from 20 mines showed a willingness to participate in this study, the sample size was limited to 50 coal cutters due to financial constraints. The sample cohort consisted of age > 18 years and experience >2 years at the same mine with the absence of diabetes, genetic diseases of kidney illness, and history of accidental kidney injury, from 10 mines located in the district of Chakwal (5 workers from each mine). These workers were divided into two cohorts; G1 and G2. Cohort group GI, with a sample size of 25 is the heat-exposed group, the mines’ working conditions comprised of high temperatures and poor ventilation. Conversely, cohort G2 is the non-heat exposed group, the mine’s working conditions comprised moderate temperature and improved ventilation.

Variables to study

The level of workplace-environmental heat was an independent variable. The functioning of workers’ kidneys, body sweating levels, skin temperature, heart rate, urine void, the severity of thirst, and work performance were dependent variables.

Potential confounders and their management

Mostly, mining workers annually shift from one mine to another, potentially reducing the accuracy of the obtained results. Neither NIOSH nor ACGIH has specific criteria/guidelines on work history at the same workplace. Therefore, the workers with less than two years of experience at the same mine were excluded. Testing of blood and urine samples was conducted by an independent medical laboratory, minimizing worker bias.

Measurement of ambient environmental parameters

Monitoring of three environmental parameters were conducted: Temperature (Dry Bulb Temperature (DBT), Wet Bulb Globe Temperature (WBGT), and Relative Humidity (RH%). A Kestel 5400 (Nielson-Kellerman, Co., PA, USA), measuring Relative Humidity (RH), globe temperature (T_g), and dry bulb temperature (DBT), was used to calculate natural dry bulb temperature (T_ndb) using the empirical formula of Bernard and Pourmoghani (Qiaoyun et al. 2019; Vanos et al. 2019). According to the International Organization for Standardization (ISO), 2017(Konrad et al. 2019), the formula to calculate indoor Wet Bulb Globe Temperature (WBGT) is

WBGT _(indoor) = 0.7× T_nw + 0.3 T_g (without solar load)

In this formula, T_nw is the natural wet bulb temperature and, T_g is globe temperature (Gosselin et al. 2019).

General questionnaire

A short questionnaire evaluated the socioeconomic profile of workers. Questions included work experience, the number of working hours/day, water intake during working hours, break time, alcohol dependency and part-time activities with level of exertion (light, heavy, very heavy) required for it.

Questionnaire for Heat-Related Illness Symptoms

The HETA -2012 (health hazard evaluation of heat stress) sheet by US NIOSH (National Institute of Occupational Safety and Health), is a questionnaire used to get self-reporting by workers about heat-induced-illnesses (Jayasekara et al. 2019), translated into Pakistan’s national language of Urdu, was used to study heat-related symptoms. This sheet takes 16 symptoms including headache, fever, high sweating rate, significantly less urine volume, dark-colored urine, fatigue, fainting, nausea, painful stomach, dizziness) into account and inquiries about their frequency (never, 1–2 days/ week, 3+ days/week) of occurrence (table 1) (Kulasooriya et al. 2021). This reporting of frequencies was summed up into a scale of range from 0 to 2 for statistical analysis.

Physiological Measures

Workers were called to the research camp (an arbitrary arrangement, on each mine, to collect pre-shift and post-shift samples of blood and urine of workers understudy) at the outset of their work shift to confirm their physiological measurements for example, weight, height, and BMI. Monitoring devices for core body temperature and skin temperature were correctly properly placed on each participant from each of the studied mine. Hence, these camps were built 10 times to collect samples from 50 workers in total.

Core Temperature (T_c)

Workers were provided an ingestible thermometric pill (Vital- sense^TM, Respironics, Bend, Oregon) 2 hours before starting the shift to measure core temperature. This pill measures core temperature every 15 seconds and send reading signals to the Sensor Electronic Module (SEM), attached to each worker’s body for physiological monitoring and data storage. This medical-grade capsule (made of biocompatible polycarbonate) is 23 mm long, 8.6 millimeters in in diameter and weighs 1.6 gram (Konrad et al. 2019). The utility and validity of ingestible pill is recommended in many studies (Gosselin et al. 2019; Thomas et al. 2019; Fenemor et al. 2020).. A Sensor Electronic Module (Model EQ-02-SEM-012, manufactured by ADInstruments, New South Wales, Australia) is a small (78 mm x53 mm x10 mm) safe and water-resistant device weighing 38 grams. It was strapped to the body and recorded readings of core body temperature from start to end of the shift, as recommended in several other studies (Yamamoto et al. 2017; MacRae et al. 2018).

Skin temperature (T_skin)

Skin temperature probes (model MLT422/A) made by AD Instruments in New South Wales, Australia, measured the skin temperature of the workers. These probes were attached to various parts of the body (mainly the right side of the chest, right upper leg, right arm, and right upper leg) to measure the temperature (T) of these parts(Chong et al. 2020). These probes were connected to the temperature loggers and an average skin temperature calculated using the following equation (Barry et al. 2020);

T_skin = 0.3 T_chest + 0.3 T_arm+ 0.2 T_{upper leg}+0.2 T _{lower leg}

Other measurements

The body weight of workers before the start and after end of each work shift with empty bladders and heavy clothing removed with a portable electronic platform scale (model no. DP 03-4, Guangdong, China). Heart rate and blood pressure were measured using certified and calibrated digital equipment (Omron HBP (model-1100, Omron Corporation, Kyoto, Japan). Sampling of blood and urine. Blood and urine samples were collected before the start and end of each of work shift and sent to a clinical laboratory for analysis. Creatinine, uric acid, serum urea, electrolytes, and plasma glucose were measured using enzymatic colorimetric tests. Urine samples were analyzed for electrolytes, urea, albumin/creatinine ratio, and urine specific gravity (USG). Glomerular filtration rate in urine samples was analyzed using the CKD Epidemiology collaboration formula: (2×sodium) + (BUN/2.8) + (Glucose/18) to calculate serum osmolarity (mosm/L). The urinary osmolarity was calculated using (sodium+potassium) × 2+urea. Samples with USG<1.020, serum osmolarity < 290 mmol/L, and urinary osmolarity < 700 mmol/L were analyzed further.

Statistical Analyses

SPSS 20 software was used for data analysis. Much of the variables were reported as mean and standard deviation, while some reported as median and interquartile range. The data collected from blood and urine samples was distributed normally that’s why we applied t-test (to compare the means of two cohorts for variables). Data collected from survey did not follow normal distribution that’s why we applied non-parametric tests, e.g., Mann-Whitney U test. Also, for normally distributed data, the paired sample t-test was used when variables to compare changes in the same subject (pre and post-shift). Otherwise, an alternate Wilcoxon signed-rank test was used. Similarly, the chi-square test was applied to compare distribution for the normally distributed variables; otherwise, Fisher's exact test was applied.

The general physical characteristics of workers for height, weight, and BMI were within the acceptance range. While studies show BMI plays a role in malfunctioning workers’ kidneys, (Gutiérrez-Vargas et al. 2018; Blacklock 2019) the malfunctioning of their kidneys cannot be related to their body weight or height (Saboia et al. 2018). None of the participants reported a history of genetic kidney disease or accidental kidney injury, which other studies have shown as the actual reason for workers’ chronic kidney diseases (Armstrong and Thomas 2019; Zuk and Bonventre 2019).

Mean values of fundamental characteristics

Workers of both cohorts were relatively young, with an average of 27 years for G1 and 25 years for G2. None of the workers (n=0) from either group were addicted to alcohol. The average value of BMI of G1 workers was 22.86, with standard deviation 1.026, higher than the workers of G2. Workers’ overall experience of underground coal cutting was 13.7 years of heat-exposed group and 11.5 years of the non-heat exposed group. The water intake of heat exposed group was 2.7 liters/person, and the non-heat exposed group was 2.3 liters/person during their shift (8.5 hours of the heat exposed group and 9.6 hours of the non-heat exposed group (table 2). Since no worker reported about his part time exertive kind of activities, no mean value of it could be mentioned in this table.

Because of the high sweating rate, the water intake of workers from the heat-exposed group was high even in a shift comprising of fewer hours than the other group. The high rate of sweating is associated with the lack of body fluids(Yasmeen et al. 2020). The workers of the heat exposed group spent lesser hours (8.5h/day) at the workplace than the workers of the non-heat exposed group (9.6h/day), though the overall working hours of both cohorts were above the NIOSH and ACGIH recommended limits of 8h/day. Another critical factor of their long-term exposure to heat is their continuous work for more than nine months at mines, with few holidays. Also, they had experienced greater than ten years doing work in different mines (most of which were observed as hot and humid during the walkthrough survey). So, in addition to two years of work at the same mine, these workers also had previous years of work experience in hot and humid mines.

Ambient conditions of two groups of mines

Table 3 shows the monitored environmental conditions of the mines. The highest temperature measured was 33.6 ^oC in mine 1, while the highest relative humidity of 83.3% was measured in mine 3.

The comparison of the environmental parameters (in table 4) showed a significant difference between the measured environmental parameters (DBT, WBGT, and RH in %age). To run the statistical analysis, three hypotheses (H_o), that DBT, WBGT, and RH (%) are equal in both mine groups, were assumed. But the outcome of the analysis rejected these three hypotheses by showing that the significance values were < 0.001* for DBT and WBGT and 0.031 for RH (%) and all these three are < p-value, i.e. 0.05.

Temperature and humidity are clearly described and documented in work schedules by NIOSH (Health et al. 2018). The study shows the average temperature and relative humidity were high in the mines of the hot category but were within the range in some mines of the cold category. Despite this fact, workers of these mines (of cold category) reported symptoms attributed to the exertive nature of work (Rojas-Valverde et al. 2019). The humidity in all studied mines was high and increased the rate of sweating and pressure on the workers’ bodies. In our studied workplaces, the ambient temperature and humidity were high. They can be related to the increase of heat-related illness in workers of underground coal mines because many studies describe some similar relations (Bourgois et al. 2019; Seo et al. 2019).

Results of heat exposure and the related illnesses

The G1 and G2 mine workers reported 10 out of the 16 heat-related illness symptoms described in HETA -2012 sheet. Figure 1 shows the number of workers reporting symptoms. Out of 25 workers of G2, 19, 21, and 17 workers reported in highest frequency (>3 days/weak) very dry mouth, dark urine, and headache Out of 25 workers of the non-heat exposed group, 18 reported dark urine in 1-2 days/weak; 19 had never experienced symptom of very little urine. No workers (n=0) reported the highest frequency of headache, dry mouth, trouble urinating, etc. (figure 1).

Occupational exposure to hot and humid environments harms the health of workers. Workers who spent two years of work in hot mines reported higher symptoms of heat-related illness, though the workers from relatively cool mines were not free of these symptoms.

Under a hot and humid environment and with a high rate of sweating, the core body temperature of workers varied from one to the other. Many workers have a mean value (of core body temperature) >38^oC, and some (especially those in the non-heat exposed group) have within the threshold limit value by ACGIH(Nanayakkara et al. 2020).

Skin temperature and core temperature

Figure 2 displays mean values of temperature of core body and skin of both cohorts of participants, respectively. The lowest core body temperature of the group of heat-exposed workers was measured in workers no. 1 and 24 (37.9^oC), while the highest temperature in the same group was of worker no. 23 (38.8^oC). Graphs of skin temperature of workers of both cohorts are overlapping. The highest mean skin temperature in the heat exposed group was 36.5^oC and in the non-heat exposed group was 36.1 ^oC.

Results of laboratory-based diagnosed indicators of Chronic Kidney Diseases.

Table 5 presents the values of pre-and post-shift samples of blood and urine of both cohorts of workers. The results of the estimated glomerular filtration rate (eGFR) of G1 was higher (100±19) before the start of shift and was lower (94± 0 9) at the end of shift, but in G2 eGFR, there was little difference in pre-and post-shift, 115±19a and 113±15, respectively. The serum osmolarity of all participants (n=50) in both cohorts was > 290mmol/L. It was 100% in workers of heat–exposed group after their shift but did not change in workers of the non-heat-exposed group. Serum creatinine level also increased from 0.99±0.10 to 1.07±0.09; p<0.001 in the heat-exposed group and from 0.88±0.10a to 0.90±0.14; p<0.001 in the non-heat exposed group. The urinary specific gravity of the heat exposed group was higher (1.030±0.005) than that of the non-heat exposed group (1.025±0.005). The Intragroup comparison shows these values were somewhat high in the post-shift samples in both cohorts.

The inter-group comparison (between the heat exposed group and non-heat exposed group) showed conclusive results of the impact of hot environments on hampering the workers’ health. The heat-exposed cohort’s systolic blood pressure and diastolic blood pressure were high compared to the other group. In pre-shift measurements, the heartbeat of both cohorts was the same, but in post-shift measurements, the value of the heat exposed group is higher. Urinary osmolarity is lower in the heat-exposed cohort. The estimated globular filtration (eGFR, mL/min) was also low in workers of the heat exposed group whose majority reported a minimal volume of urine which was dark in color. Also, pre- and post- samples of both cohorts show the occupational heat stress reduces the eFGR of the exposed group of workers, providing evidence the hot and humid work environment is the primary cause since most of their day was spent.

Similarly, the comparison of other parameters of kidney functioning in pre-and post-shift samples of both types of cohorts indicates that the ambient temperature and humidity created stress on the kidneys of workers. All the studied indicators of post-shift samples (of heat expose group) exceeded the reference range. The samples of the non-heat exposed group showed little change in values of pre- and post-shift analysis, which implies that they were not exposed to heat during their work shift.

This study found that the dominant factor of a hot and humid environment plays a significant role in raising the core body temperature of the workers of underground coal mines. The self-reported symptoms of heat-related illness were high in workers of hot mines. The laboratory reports of their pre-and post-shift blood and urine samples proved that the disrupted functioning of their kidneys was due to the hot work environment. Another significant finding is that most of the study participants (be it heat exposed or non-heat exposed) reported symptoms of heat-related illness. The apparent reasons are their prior work experience (> 2 years) in hot mines and their body exertion over a more extended period. However, a more detailed study about the prevalence of heat-related illness in workers working in relatively cool mines for more than two years would be needed to determine conclusive results. Based on the inferences of this study, we strongly recommended a new study to calculate the role of work performance (exertion of body parts) and acclimatization to heat is causing the related illness and chronic kidney diseases.

Ethical Approval and consent to participate

The study was approved by the Bioethical Clearance Committee of the University under reference number REDACTED. Written consent was obtained from participants prior to the walkthrough survey, assuring the privacy of both workers and managers.

Consent for publication

All authors willingly give their consent for publication this manuscript along with the entire data and content.

Availability of data and materials

It is to confirm that all the data supporting findings of this study is available only in this article, and or can be accessed by requesting the journal publishing it.

Competing interest

All authors declare that they have no competing interests for this research titled Competitive study of heat-exposed and non-heat-exposed group of workers of Underground Coal Mines, Punjab, Pakistan.

Funding

Not applicable

Authors’ contribution statement

Madiha Ijaz made the conceptual design of the study, went to the area of study to collect data, and drafted the manuscript; Sajid Rashid Ahmad supervised the conceptual design and drafting of the results; Muhammad Akram ensured the collection of data to be in compliance with international standards; Kamran Mirza helped drafting section of discussion and interpreting laboratory results. William Carter added technical points in developing methodology, made statistical analysis of results and then improved the language of draft.

All authors have read and agreed to the published version of the manuscript.

Acknowledgments

The authors are thankful to the workers who participated in the study, and to the managers of studied underground mines of coals, for facilitating to conduct the research successfully.

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Table 1

Heat-induced-illness symptoms (HETA-12 questionnaire) with options of frequency of occurrence.
Symptoms	Frequency of occurrence
Symptoms	Never	1–2 days/week	3 + days/week
Headache	0	1	2
Very dry mouth	0	1	2
Trouble urinating	0	1	2
Fever	0	1	2
Very little urine	0	1	2
Exhaustion, so that you had to lie down	0	1	2
Nausea	0	1	2
Muscle cramp	0	1	2
Stomach/abdominal pain	0	1	2
Dark urine	0	1	2
Dizziness	0	1	2
Heart racing/fluttering	0	1	2
Diarrhea	0	1	2
Confusion	0	1	2
Vomiting	0	1	2
Fainting	0	1	2

Table 2 is available in the Supplementary Files section.

Table 3. Ambient Condition of the two groups of Mines.

Mine number Task	Mines with high ambient temperature			Mine number	Mines with relatively low ambient temperature
Mine number Task	Dry-bulb temperature (^oC) (DBT)	Wet-bulb temperature (^oC) (T_wb)	Relative Humidity (RH) (^oC) (%)	Mine number	Dry-bulb temperature (^oC) (DBT)	Wet-bulb temperature (^oC) (T_wb)	Relative Humidity (RH) (^oC) (%)
1	33.6	27.4	70.1	6	25.7	17.5	60.5
2	30.3	24.6	71.0	7	22.7	18.3	74.0
3	32.5	29.0	83.3	8	25.1	18.5	66.8
4	30.9	26.1	75.2	9	21.3	16.0	71.0
5	31.0	26.0	74	10	23.0	19.0	77

Table 4. Independence of environmental factors of two groups of mines

			t-test for Equality of Means
			t	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
			t	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	Lower	Upper
Temperature	Equal variances assumed	DBT ^oC	8.012	8	.000*	8.100	1.011	5.769	10.431
		WBGT ^oC	9.644	8	.000*	8.760	0.910	6.66	9.37
		RH (%) ^oC	1.308	8	0.031*	4.863	3.714	-3.705	7.946
	Equal variances not assumed	T_db ^oC	8.012	7.408	.000*	8.100	1.011	5.736	10.464
		T_wb ^oC	0.964	7.196	.000*	8.760	0.908	6.62	9.89
		HU ^oC	1.308	7.674	0.029*	4.863	3.714	-3.705	7.980

H_o’: Dry-Bulb Temperature between two groups are same.

H_o’’: Wet-Bulb Temperature in two groups are same.

H_o’’’: Humidity rate in two groups are same.

*P-value is < 0.05 and it rejects the 3 assumed hypotheses (H_o) which means that the two compared groups of mines are different.

Table 5

Inter and intra comparison of pre- and post-shift of the two cohorts
	Heat-exposed cohort (n = 25)		Non-heat-exposed cohort(n = 25)
	Pre-shift	Post shift	Pre-shift	Post-shift
SBP, mm Hg	125.7 ± 8.9	119.5 ± 7.3	117.2 ± 8.4	117.9 ± 5.2
DBP, mm Hg	72.4 ± 8.1	68.7 ± 9.8**	68.4 ± 7.9a	66.2 ± 8.3
Heart rate, beats/min	62.7 ± 7.1	70.0 ± 8.5**	68.1 ± 8.3	70.1 ± 9.4
Hematocrit,%	45.4 ± 1.4	43.6 ± 2.1	45.0 ± 0.75	44.0 ± 2.9**
Hemoglobin, g/dL	13.6 ± 0.8	13.1 ± 0.8	14.8 ± 1.0	14.1 ± 0.9**
Leucocytes, n/mm3	7,730 ± 1,753	7,967 ± 1,445*	7,190 ± 1,818	8000 ± 1,286**
Glucose, mg/dL	91.7 ± 19.7	83.2 ± 10.4	87.3 ± 19.1	82.1 ± 9.4
Serum creatinine, mg/dL	0.99 ± 0.10	1.07 ± 0.09**	0.88 ± 0.10a	0.90 ± 0.14**
eGFR, mL/min	100 ± 19	94 ± 09**	115 ± 19a	113 ± 15**
Serum uric acid, mg/dL	6.35 ± 1.33	6.60 ± 1.36*	5.20 ± 0.58b	5.21 ± 0.49
> 7 mg/dL, %	27	44	0a	0a
Serum sodium,mmol/L	140.3 ± 1.9	138.9 ± 1.8	140.6 ± 1.9	140.1 ± 2.7
Serum potassium, mmol/L	4.50 ± 0.33	4.70 ± 0.47	4.45 ± 0.24	4.50 ± 0.87
Serum osmolarity, mmol/L	293.8 ± 5.9	293.4 ± 4.1	293.9 ± 3.7	298.1 ± 4.7
> 290 mmol/L,%	94	100	89	89
Alb/creatinine,mg/gc	0.48 (0.35–0.64)	0.45 (0.44–0.61)	0.54 (0.49–0.74)	0.46 (0.4–0.71)
> 30 mg/g, %	0	0	0	0
Urinary specific gravity	1.030 ± 0.005	1.029 ± 0.004	1.025 ± 0.005	1.024 ± 0.007
> 1.020, %	72	66	72	57
Urinary osmolarity	819 ± 200	953 ± 172	970 ± 178	1,129 ± 320*
> 700 mmol/L, %	78	93	83	84
* p < 0.05 vs. pre-shift.
** p < 0.01 vs. pre-shift.
p < 0.05 vs. heat-exposed group.
p < 0.001 vs. heat-exposed group.
Median (interquartile ranges).
SBP, systolic blood pressure; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate.

No competing interests reported.

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Competitive study of heat-exposed and non-heat-exposed group of workers of Underground Coal Mines, Punjab, Pakistan

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