Predictors of pulmonary dysfunction vis-à-vis the hypertension status of mine workers in Gujarat,western India: A cross-sectional study on the need to further investigate the role of anti-hypertensive drugs

Abstract

BACKGROUND:

Mine workers face various health risks from occupational hazards, notably dust-related pulmonary dysfunction. This dysfunction is also attributed to diverse risk factors and health conditions. Despite the variety of underlying mechanisms, conflicting evidence persists regarding hypertension as a potential risk factor for such dysfunction.

OBJECTIVE:

To determine the predictors of pulmonary dysfunction vis-à-vis the hypertension status of mine workers.

METHODS:

We conducted a cross-sectional study among 444 mine workers from ten open-cast mines in Gujarat state (western part of India) from November 2020 to February 2022. We collected data on demographics, occupation, addiction, and comorbidities, including measurements like anthropometry, blood pressure, blood sugar, haemoglobin, and lipid levels. Hypertension was confirmed based on self-reported history and/or onsite blood pressure measurement, while pulmonary functions were assessed using a spirometer (expressed as forced expiratory volume in the first second FEV1 and forced vital capacity FVC). Multiple linear regression analysis was performed to determine the significant predictor of FEV1 or FVC vis-à-vis the hypertension status after adjusting for confounding variables. In addition, we assessed the effect of anti-hypertensive medications on pulmonary dysfunction.

RESULTS:

A total of 41% (95% CI: 36-45%) of mine workers were suffering from hypertension. On multiple linear regression, only being a male and work experience duration were the significant predictors of FEV1 [0.900 (0.475-1.092), p=<0.001; -0.029 (-0.034 - -0.021, p=<0.001] and FVC [1.088 (0.771-1.404), p=<0.001; -0.031 (-0.038 - -0.024, p = 0.001] respectively. While unadjusted analysis indicated hypertension led to FEV1 and FVC reduction, this effect lost significance after adjusting for confounders. Nevertheless, subgroup analysis revealed those on antihypertensive medications had reductions in FEV1 and FVC by -0.263 (95% CI: -0.449 - -0.078, p = 0.006) L and -0.271 (95% CI: -0.476 - -0.067, p = 0.009) L respectively.

CONCLUSION:

In our study among mine workers, alterations in lung function (FEV1 and FVC) on spirometry were predicted by gender and duration of work experience, while hypertension did not serve as a predictor. It is noteworthy that antihypertensive drugs were found to reduce lung functions on spirometry, highlighting the need for further research.

Keywords

Blood pressure spirometry antihypertensive agents cross-sectional studies miners India

1 Introduction

The mining industry in India is a crucial financial pillar, employing around 20 million people, with the majority working in the unorganized sector [1 –3]. Although mining provides raw materials for most industries, it has been a necessary evil of the modern world since ancient times due to its arduous work environment [4]. It is considered a dangerous occupation because of traumatic injuries and various morbidities associated with exposure to dust, noise, heat, vibration, radiation, and other hazards [5, 6]. Among the various morbidities, silicosis and coal workers’ pneumoconiosis are the most common pulmonary hazards faced by mine workers due to regular exposure to airborne respirable dust [7 –9]. Moreover, due to numerous risk factors linked to mining activities, environment, and lifestyle, mine workers are also susceptible to developing non-communicable diseases such as cancer, type 2 diabetes, and cardiovascular disease [10, 11]. Among these, hypertension has emerged as a significant concern, affecting up to 28% of mine workers in India and 40% in other countries [10 , 12–14]. Apart from being a powerful independent risk factor for cardiovascular mortality and overall death, hypertension is also a major contributor to clinical and pre-clinical damage to various organs, including the lungs [15, 16].

While prolonged exposure to airborne respirable dust is the primary cause of pulmonary dysfunction in mine workers, hypertension has also been suggested as a possible cause of such dysfunction [16, 17]. Decreased pulmonary function in hypertensive individuals is hypothesized to be caused by left ventricular failure brought on by high sustained blood pressure, which causes interstitial oedema and reduced elasticity of the pulmonary parenchyma [16]. However, studies investigating the impact of hypertension on pulmonary dysfunction in hypertensive individuals have reported conflicting findings [16 , 18–20]. Some studies have reported a reduction of spirometry parameters in patients with hypertension [16 , 19], while few others have mentioned no such difference [20].

There is a renewed interest in documenting the prevalence of non-communicable diseases among mine workers [10, 11]. Despite the high prevalence of hypertension and pulmonary dysfunction among mine workers, there is no evidence from the literature that mine workers’ hypertension status may also contribute to pulmonary dysfunction. Also, prior studies on the general population did not account for important occupational confounding variables such as dust exposure while working and years of work experience. To address this gap in knowledge, we conducted a cross-sectional study to determine the predictors of pulmonary dysfunction vis-à-vis the hypertension status of mine workers in Gujarat, western India. We hypothesized that hypertension may also predict pulmonary dysfunction among the mine workers, independent of their occupational exposure to dust and years of work experience. We also predicted that mine workers with hypertension who are taking anti-hypertensive drugs would have better pulmonary function than those who are not taking these medications.

The findings from our study provided important insights into the predictors of pulmonary dysfunction vis-à-vis hypertension status of mine workers. Additionally, it highlighted the possible influence of anti-hypertensive drugs on the risk of pulmonary dysfunction in this group. These findings may guide future research and interventions targeting the reduction of pulmonary dysfunctions among mine workers in India and other countries with comparable mining industries.

2 Methods

2.1 Study design and setting

We conducted a cross-sectional study among mine workers of ten open-cast lignite mines in Gujarat state (western part of India). Gujarat is an Indian state that ranks high in lignite production and has sizeable lignite reserves in its Kutch, Saurashtra, and South Gujarat regions [21, 22]. According to the Ministry of Coal, Government of India, the state of Gujarat was the second-highest lignite-producing state in India during the financial year 2020-21, with a production of around 10 million tones, accounting for approximately 26% of India’s total lignite production [23].

2.2 Study duration

The study was conducted from November 2020 to February 2022 but was significantly impacted by the COVID-19 pandemic in India. Specifically, the first wave from March to October 2020 and the second wave from March to May 2021 caused significant disruptions, resulting in the suspension of the field study [24]. However, during the periods without waves, the study team implemented necessary safety measures to ensure the well-being of both participants and researchers, which included the use of personal protective equipment, maintaining social distancing, and following disinfection protocols.

2.3 Sampling

At the inception of the research project, the investigator had a meeting with the managers at the mines to discuss the study’s objectives, the necessary facilities required, and the cooperation needed from the management and workers. The managers of the mines showed their readiness to support the research and suggested three mining sites with nearby healthcare centres. The investigator visited these sites to ensure that all arrangements were in place for the study to run smoothly and to establish a positive connection with the officials of the healthcare centre and mine workers. Following this, the investigators randomly selected 25% of the workers from the total workforce and gave the information to the mine managers. On the day of the field study, the chosen workers were informed of their participation and transported to the healthcare facility. A participant information sheet was given to each participant in the local language, and only those who met the eligibility criteria were enrolled.

2.4 Study population

The study included adult mine workers, aged 18 to 64, who were present during visits to ten mines and provided written informed consent to participate. Mine workers who had contraindications for performing spirometry, such as those with gross abnormalities of the vertebral column or thoracic cage, neuromuscular disease, malignancy, cardiopulmonary disease, who had undergone major abdominal and chest surgeries, or, those who were unable to perform spirometry properly were excluded from the study.

2.5 Data collection procedures

2.5.1 Detailed history and general examination

Participants’ data on personal demography, work, addiction, self-reported hypertension and other co-morbidities and drug history (yes/no) were recorded in the data collection form. A physical examination including a general medical check-up and measurements of height (in centimetres), and body weight (in kilograms) was conducted and recorded.

2.5.2 Blood pressure measurement

Both systolic and diastolic blood pressures were measured using a pre-calibrated mercury sphygmomanometer in adherence to the American Heart Association (AHA) guidelines [25]. Before the measurement, the participants were seated and allowed to relax for five minutes. The cuff of appropriate size was wrapped around the right arm, which was extended at heart level. The participant’s blood pressure was measured once, and it was noted if it fell within the normal range. However, if the results revealed abnormally high or low blood pressure, the measurement was repeated five minutes later to check for consistency, and the average of the measurements was noted. The number of measurements did not follow the AHA guidelines but was instead based on a protocol used in reliable surveys in developed countries [12 , 26]. Furthermore, research suggests that it is unlikely for individuals with normal initial blood pressure readings to be reclassified as having hypertension [27]. The participants were classified as hypertensive if their systolic blood pressure was≥140 mm Hg and/or diastolic blood pressure was≥90 mm Hg [28].

2.5.3 Spirometry

Spirometry was performed by using a Schiller (Spirovit SP-1) spirometer, a computerized validated instrument in wide use for performing pulmonary function tests. The spirometer was operated at room temperature and calibrated daily before beginning the assessments. All tests were carried out at a fixed time of the day (10 AM to 3 PM) to minimize diurnal variations. The procedure was explained by trained technicians to each participant individually and was performed in a seated position with a fitted nose clip according to the standard recommendations of American Thoracic Society (ATS) guidelines [29]. Participants were asked to blow forcefully as long as possible into the transducer (mouthpiece) after a full deep inhalation. Three acceptable forced maximal expirations with acceptability and reproducibility criteria were recorded. The highest measurements of forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) manoeuvre were used for further analysis. Apart from this, the spirometer also provided values for the FEV1/FVC ratio (expressed as a percentage).

2.5.4 Biochemical investigation

A 5 ml venous blood sample was collected from each participant in the study which was assessed on the same day of collection using standard techniques. Haemoglobin levels were determined using a spectrophotometer through the cyanmethemoglobin method and the diagnosis of anaemia was done according to the cutoffs recommended by the World Health Organization (WHO) [30]. Random blood sugar (RBS), total cholesterol, triglycerides (TG), and high-density lipoprotein (HDL) levels were analyzed using a semi-automated analyzer. RBS was assessed via the glucose oxidase peroxidase (GOD-POD) method [31], while total cholesterol and HDL were measured using the CHOD-PAP method [32]. TGs were examined through the glycerol-3-phosphate oxidase-(GPO)-PAP Trinder method [33], and LDL-C concentration was calculated using the Friedewald equation [34]. Due to logistical constraints, diabetes diagnosis relied on participants’ self-reported medical history (i.e., if they have ever been diagnosed with diabetes mellitus as told by a doctor or health professional) instead of the recommended dual RBS measurements [35, 36]. Meanwhile, dyslipidemia was defined following the National Cholesterol Education Program (NCEP)-Adult Treatment Panel III (NCEP-ATP III) guidelines [37].

2.6 Variables

The primary outcome variables were FEV1 and FVC in litres, measured as continuous variables. The exposure variable was a history of hypertension (self-reported as well as newly diagnosed) (dichotomous variable). The confounding variables were age in years, male gender, body mass index (BMI), and dust exposure during work (based on occupational history - individuals working in mining operations were regarded to be exposed to dust, whereas those involved in office work were not), work experience in years, tobacco smoking (self-reported) and suffering from diabetes (self-reported). For sub-group analysis, the exposure variable of history of hypertension (yes/no) was categorized into three categorical variables: mine workers who were on anti-hypertensive drugs (self-reported), those newly diagnosed with hypertension, and those without hypertension.

Table 1
Characteristics of mine workers in ten mines of Gujarat state from November 2020 to February 2022 (n = 444)

Characteristics Non-hypertensive Hypertensive P-value

(n = 264) (n = 180)

Number (%) or Number (%) or

Mean (±SD) Mean (±SD)

Socio-demographic, occupational and anthropometric characteristics

Male 250 (95) 174 (97) 0.326

Age (years) 48 (±11) 55 (±5) <0.001

Job Type

Office 86 (33) 59 (33) 0.402

Maintenance 82 (31) 51 (28)

Operator 26 (10) 27 (15)

Labour 70 (26) 43 (24)

Dust exposure during work 179 (68) 120 (67) 0.802

Work experience (years) 24 (±12) 30 (±7) <0.001

BMI (kg/m²) 25 (±6) 27 (±7) 0.009

Addiction

Smoking 30 (11) 27 (15) 0.261

Tobacco chewing 21 (8) 32 (18) 0.002

Alcohol drinking 6(2) 7(4) 0.321

Biochemical parameters

Random blood sugar (mg/dl) 112 (±60) 130 (±71) 0.008

Haemoglobin level (gm/dl) 13.5 (±1) 13.5 (±1) 0.851

Cholesterol level (mg/dl) 191(±27) 196 (±32) 0.155

Triglyceride level (mg/dl) 150 (±26) 154 (±30) 0.130

LDL level (mg/dl) 118 (±24) 121 (±29) 0.173

HDL level (mg/dl) 44 (±4) 43 (±4) 0.424

Comorbidities

Diabetes 39 (15) 54 (30) <0.001

Anaemia 43 (16) 25 (14) 0.491

Dyslipidemia 112 (42) 79 (44) 0.760

Spirometry results

% Predicted FEV1 (L) 120 (±22) 122 (±26) 0.507

% Predicted FVC (L) 106 (±19) 106 (±22) 0.730

Measured FEV1 (L) 2.92 (±0.75) 2.77 (±0.68) 0.031

Measured FVC (L) 3.46 (±0.83) 3.31 (±0.77) 0.046

Measured FEV1/FVC (%) 84 (9) 84 (8) 0.472

Characteristics	Non-hypertensive	Hypertensive	P-value
Socio-demographic, occupational and anthropometric characteristics
Male	250 (95)	174 (97)	0.326
Age (years)	48 (±11)	55 (±5)	<0.001
Job Type
Office	86 (33)	59 (33)	0.402
Maintenance	82 (31)	51 (28)
Operator	26 (10)	27 (15)
Labour	70 (26)	43 (24)
Dust exposure during work	179 (68)	120 (67)	0.802
Work experience (years)	24 (±12)	30 (±7)	<0.001
BMI (kg/m²)	25 (±6)	27 (±7)	0.009
Addiction
Smoking	30 (11)	27 (15)	0.261
Tobacco chewing	21 (8)	32 (18)	0.002
Alcohol drinking	6(2)	7(4)	0.321
Biochemical parameters
Random blood sugar (mg/dl)	112 (±60)	130 (±71)	0.008
Haemoglobin level (gm/dl)	13.5 (±1)	13.5 (±1)	0.851
Cholesterol level (mg/dl)	191(±27)	196 (±32)	0.155
Triglyceride level (mg/dl)	150 (±26)	154 (±30)	0.130
LDL level (mg/dl)	118 (±24)	121 (±29)	0.173
HDL level (mg/dl)	44 (±4)	43 (±4)	0.424
Comorbidities
Diabetes	39 (15)	54 (30)	<0.001
Anaemia	43 (16)	25 (14)	0.491
Dyslipidemia	112 (42)	79 (44)	0.760
Spirometry results
% Predicted FEV1 (L)	120 (±22)	122 (±26)	0.507
% Predicted FVC (L)	106 (±19)	106 (±22)	0.730
Measured FEV1 (L)	2.92 (±0.75)	2.77 (±0.68)	0.031
Measured FVC (L)	3.46 (±0.83)	3.31 (±0.77)	0.046
Measured FEV1/FVC (%)	84 (9)	84 (8)	0.472

2.7 Statistical analysis

The present study employed both descriptive and inferential statistics to analyze the data. Descriptive statistics were used to summarize categorical and continuous variables within the non-hypertensive and hypertensive groups. Categorical variables were presented as percentages, while continuous variables were expressed as mean (±SD). For basic inferential analysis, a t-test was employed to determine the presence of significant differences for continuous variables and a chi-square test for categorical variables between non-hypertensive and hypertensive mine workers. Advanced analysis used regression analysis to determine the predictors of pulmonary function test parameters (FEV1 and FVC) vis-à-vis the hypertension status of the mine workers. Initially, univariable linear regression analysis was used to identify the potential predictors for subsequent multivariable analysis. Predictors with a p-value≤0.2 on univariable linear regression were included in the multivariable analysis. Then, tolerance and VIF statistics were employed to identify any multi-co-linearity that might exist among the predictors. To avoid the impact of co-linearity on the results, predictors that had a tolerance value of < 0.25 or a VIF > 4 were deemed to have co-linearity issues and were removed from the final analysis. Finally, a multivariable linear regression analysis was applied using the “Enter” method to determine the predictors that significantly affect FEV1 and FVC while adjusting for confounding variables.

In addition, a subgroup analysis was conducted to investigate the effect of anti-hypertensive drugs and newly diagnosed hypertension (without drug treatment) on pulmonary function among mine workers. Pulmonary function parameters were individually compared through separate univariable linear regression analyses: first between mine workers on anti-hypertensive drugs and those without hypertension, and then between individuals with newly diagnosed hypertension and those without hypertension. The difference was said to be statistically significant when p-values were < 0.05. Statistical Package for Social Sciences (SPSS) version 23 was used for all statistical analysis.

3 Results

3.1 Selection and characteristics of mine workers

We analyzed the data of 444 mine workers from the ten mines in our study setting (Figure 1). Among these, a total of 180 mine workers (41% with a 95% confidence interval of 36-45%) were identified as suffering from hypertension. Upon comparing various socio-demographic, occupational, and anthropometric characteristics between workers with and without hypertension, it was observed that the mean (±SD) age in years (55±5 vs. 48±11, p=<0.001), mean (±SD) duration of work experience in years (30±7 vs. 24±12, p=<0.001) and mean (±SD) body mass index (27±7 vs. 25±6, p = 0.009) were higher in workers with hypertension (Table 2). An evaluation of addictive behaviours revealed that worker classified as hypertensive had a greater history of tobacco chewing (18% vs. 8%, p = 0.002). Furthermore, workers with hypertension exhibited a greater prevalence of type 2 diabetes mellitus (30% vs. 15%, p=<0.001) along with elevated mean (±SD) random blood sugar levels (130±71 vs. 112±60, p = 0.008). The assessment of pulmonary function tests indicated that the mean values (±SD) of FEV1 in litres were lower in the hypertensive group compared to the non-hypertensive group (2.77±0.68 vs. 2.92±0.75, p = 0.031). Similarly, the mean values of FVC in litres were also lower in the hypertensive group compared to the non-hypertensive group (3.31±0.77 vs. 3.46±0.83, p = 0.046).

Fig. 1

Selection of mine workers in ten mines in Gujarat between November 2020 and February 2022.

Table 2

Univariable and multivariable linear regression analysis for variables predicting FEV1 among mine workers of Gujarat state from November 2020 to February 2022 (n = 444)

Variables	Univariable linear regression		Multivariable linear regression
	Beta-coefficients (95% CI)	P-value	Beta-coefficients (95% CI)	P-value
Age (years)	–0.034 (–0.041 ––0.028)	<0.001	–	–
Male	1.035 (0.724 –1.346)	<0.001	0.900 (0.475 –1.092)	<0.001
BMI (kg/m²)	0.003 (–0.008 –0.014)	0.629	–	–
Dust exposure during work	–0.173 (–0.316 ––0.030)	0.018	–0.016 (–0.129 –0.127)	0.807
Work experience (years)	–0.031 (–0.037 ––0.025)	<0.001	–0.029 (–0.034 ––0.021)	<0.001
History of tobacco smoking	–0.090 (–0.291 –0.112)	0.383	–	–
Diabetes status	–0.251 (–0.416 ––0.087)	0.003	-0.135 (–0.296 ––0.001)	0.073
Hypertension status	–0.150 (–0.287 ––0.013)	0.031	0.038 (–0.095 –0.157)	0.552

3.2 Predictors of FEV1

Age in years, male gender, dust exposure during work, work experience in years, history of diabetes and history of hypertension were the confounding variables for FEV1 having a p-value≤0.2 on univariable linear regression analysis (Table 2). However, age and work experience demonstrated co-linearity while examining the tolerance and VIF statistics for the model predicting FEV1 (see Supplementary Table 1). Hence, while performing multivariable linear regression to determine the predictors of FEV1, the variable age was excluded. On performing multivariable linear regression, being a male and work experience duration significantly predicted FEV1. Males had a higher FEV1 of 900 ml (95% CI: 0.475 - 1.092, p-value<0.001), and it declined by 29 ml (95% CI: -0.034 - -0.021, p-value<0.001) with every year of work.

3.3 Predictors of FVC

On univariable linear regression analysis, all confounding variables with a p-value of≤0.2 for FVC were similar to those for FEV1 (Table 3). However, age and work experience displayed co-linearity for the model predicting FVC (see Supplementary Table 2) and the variable age was removed while performing multivariable regression analysis. Being a male and duration of work experience were significant predictors of FVC, the same as that for FEV1, on multivariable linear regression. Males had a higher FVC of 1088 ml (95% CI: 0.771 - 1.404, p-value<0.001) and it was decreased by 31 ml (95% CI: -0.038 - -0.024, p-value<0.001) with every year of work.

Table 3
Univariable and Multivariable linear regression analysis for variables predicting FVC among mine workers of Gujarat state from November 2020 to February 2022 (n = 444)

Variables Univariable linear regression Multivariable linear regression

Beta-coefficients (95% CI) P-value Beta-coefficients (95% CI) P-value

Age (years) –0.038 (–0.045 ––0.030) <0.001 – –

Male 1.224 (0.880 –1.569) <0.001 1.088 (0.771 –1.404) <0.001

BMI (kg/m²) 0.001 (–0.012 –0.013) 0.905 – –

Dust exposure during work –0.159 (–0.318 –0.001) 0.052 0.015 (–0.127 –0.158) 0.833

Work experience (years) –0.033 (–0.040 ––0.027) <0.001 –0.031 (–0.038 ––0.024) <0.001

History of tobacco smoking 0.043 (–0.182 –0.268) 0.705 – –

Diabetes status –0.277 (–0.460 ––0.094) 0.003 –0.154 (–0.318 –0.011) 0.067

Hypertension status –0.155 (–0.308 ––0.003) 0.046 0.046 (–0.095 –0.187) 0.522

Variables	Univariable linear regression	Multivariable linear regression
Age (years)	–0.038 (–0.045 ––0.030)	<0.001	–	–
Male	1.224 (0.880 –1.569)	<0.001	1.088 (0.771 –1.404)	<0.001
BMI (kg/m²)	0.001 (–0.012 –0.013)	0.905	–	–
Dust exposure during work	–0.159 (–0.318 –0.001)	0.052	0.015 (–0.127 –0.158)	0.833
Work experience (years)	–0.033 (–0.040 ––0.027)	<0.001	–0.031 (–0.038 ––0.024)	<0.001
History of tobacco smoking	0.043 (–0.182 –0.268)	0.705	–	–
Diabetes status	–0.277 (–0.460 ––0.094)	0.003	–0.154 (–0.318 –0.011)	0.067
Hypertension status	–0.155 (–0.308 ––0.003)	0.046	0.046 (–0.095 –0.187)	0.522

3.4 Subgroup analysis

For the purpose of subgroup analysis, a total of 180 mine workers diagnosed with hypertension were further stratified into two groups. The first group consisted of 79 individuals (44%) who had a documented history of hypertension and were actively undergoing treatment using antihypertensive medications. The average duration of their history of hypertension and its treatment was 6 years, with a standard deviation of 5 years. Through univariable linear regression analysis, it was observed that these mine workers had significant reductions in FEV1 and FVC. The observed reductions were quantified at 263 ml (95% CI: -0.449 to -0.078, p-value=0.006) for FEV1 and 271 ml (95% CI: -0.476 to -0.067, p-value=0.009) for FVC (Table 4). The second group comprised 101 individuals (56%) who were previously unaware of their hypertension condition. However, upon undergoing measurements, these mine workers were newly diagnosed with hypertension. In this subset, univariable linear regression analysis showed no significant reduction in FEV1 and FVC (Table 4).

Table 4
Univariable linear regression analysis predicting FEV1 and FVC among hypertensive mine workers, categorized by history of hypertension and anti-hypertensive drug use (n = 343), and by newly diagnosed hypertension (n = 365)

Having a history of hypertension and on anti-hypertensive drugs (n = 343)

Variables FEV1 FVC

Beta coefficient (95% CI) P-value Beta coefficient (95% CI) P-value

Constant 2.918 (2.828 –3.007) <0.001 3.462 (3.363-3.560) <0.001

History of hypertension and drug treatment –0.263 (–0.449 ––0.078) 0.006 –0.271 (–0.476 ––0.067) 0.009

Newly diagnosed hypertension (n = 365)

Variables FEV1 FVC

Beta coefficient (95% CI) P-value Beta coefficient (95% CI) P-value

Constant 2.918 (2.830 –3.005) <0.001 3.462 (3.365-3.560) <0.001

Newly diagnosed hypertension –0.062 (–0.229 –0.105) 0.467 –0.065 (–0.252 –0.122) 0.496

Having a history of hypertension and on anti-hypertensive drugs (n = 343)
Constant	2.918 (2.828 –3.007)	<0.001	3.462 (3.363-3.560)	<0.001
History of hypertension and drug treatment	–0.263 (–0.449 ––0.078)	0.006	–0.271 (–0.476 ––0.067)	0.009
	Newly diagnosed hypertension (n = 365)
Variables	FEV1	FVC
	Beta coefficient (95% CI)	P-value	Beta coefficient (95% CI)	P-value
Constant	2.918 (2.830 –3.005)	<0.001	3.462 (3.365-3.560)	<0.001
Newly diagnosed hypertension	–0.062 (–0.229 –0.105)	0.467	–0.065 (–0.252 –0.122)	0.496

4 Discussion

4.1 Summary of findings

In our study, we found that changes in lung function (FEV1 and FVC) as measured by spirometry among mine workers were only predicted by gender and the duration of work experience. FEV1 and FVC increased in male participants while they decreased as work experience increased. We could not determine the hypertension status as a predictor with lung function parameters. Nevertheless, mine workers who were on antihypertensive drugs had decreased FEV1 and FVC.

4.2 Comparison with existing literature

In our study, we observed that hypertensive mine workers show a reduction in spirometry results in comparison to non-hypertensive individuals. This finding aligned with the results of the majority of research conducted either in general or in hospital populations [16 , 38–40]. However, we were not able to determine hypertension status as a significant predictor of pulmonary dysfunction among mine workers. A similar outcome was observed in a study conducted by Schnabel et al. involving the general adult population [20]. However, contrasting results were seen in studies by Margretardottir et al. and Schnabel et al. in the general adult population, where they concluded that hypertension status could be a predictor of pulmonary dysfunction [18, 40]. We compared our findings to those of studies conducted in either a hospital or a general community setting because we were unable to find studies for comparison among mine workers despite our best efforts. Apart from spirometry results, mine workers in hypertensive groups were older and had a higher BMI as compared to nonhypertensives which showed a similar trend with previous studies [20, 40]. Additionally, the nearly doubled prevalence of diabetes and elevated levels of random blood sugar among those with hypertension, compared to their non-hypertensive counterparts, can be attributed to the established bidirectional connection between diabetes and hypertension [41]. Studies examining the relationships between pulmonary function tests and various predictors among mine workers frequently overlook comorbidities such as diabetes and hypertension, which, in our opinion, should now be the focus of attention given their rising prevalence among mine workers [10, 11].

4.3 Antihypertensive drugs and their complex interactions with lung functions

In a subgroup analysis of our study, mine workers who had a history of antihypertensive drug intake exhibited a reduction in spirometry results. This was similar to a study done by Schnabel et al., which concluded that high blood pressure may decrease lung function when accompanied by antihypertensive medication rather than high blood pressure alone [20]. Another study found that the use of beta-blockers was associated with decreased lung function in the general adult population [18]. To support this finding, there is evidence that antihypertensive beta-blockers, even those that are relatively cardioselective, cause bronchoconstriction and hence reduce respiratory flow. It may also cause a slight reduction in expiratory muscle strength, resulting in a proportional reduction in FEV1 and FVC [18, 20]. However, contradicting results were found in a study done by Margretardottir et al. in which there was no significant difference in FEV1 or FVC between hypertensive participants who used beta-blockers and those who did not [40]. Another study demonstrated that the use of beta blockers, but not the use of other antihypertensive drugs, was associated with decreased lung function in the general adult population[18]. While literature suggests that apart from beta blockers, other antihypertensive drug classes, such as diuretics, calcium channel blockers, or ACE inhibitors, may also have an impact on pulmonary function [20]. To answer these complex interactions, in our opinion, future research with comprehensive pharmacological data of the drugs/dosages/duration used will be required to understand the interplay between pulmonary functions and various therapeutic classes of antihypertensive medications.

4.4 Secondary findings

In this study, work experience in years was the only predictor that showed a reduction of spirometry results similar to the previous study among mine workers [42, 43]. It is a very well-known occupational predictor for pneumoconiosis as well as mortality from respirable disease [42, 44]. Being male was the only predictor that exhibited the higher pulmonary function test parameters, similar to another study conducted by Birhan and Abebe and Yadav et al. [16, 19]. Possible explanations for the gender differences include changes in lung geometry; females are expected to have smaller airways and lung capacity than males [16, 45].

The proportion of mineworkers detected with hypertension in our study was 41% (95% CI: 36–45%), which was much higher than studies done by Kalyani et al. in Goa (5%), Oliveira et al. in Goa (8%) and Neelakanti and Sriramula in South India (19%) [46 –48]. Studies conducted outside of India found an almost similar prevalence of hypertension, such as 31% in US coal mine workers and 40% in South African gold mine workers [12, 13]. We were unable to determine the exact cause of these discrepancies, but it might be because studies conducted outside of India primarily focused on hypertension prevalence, whereas it was a secondary finding in Indian studies. Therefore, we suggest that future studies on mine workers should be rigorous in their methodology and strict in their criteria, with a primary focus on detailed clinical history/examination related to hypertension.

4.5 Hypertension and its complex interactions with lung functions

The interplay between hypertension and pulmonary functions is bi-directional. Due to interstitial edema of the lung and decreased elasticity of its parenchyma, hypertension might be associated with lung impairment, however, lung impairment might also increase the risk of hypertension through chronic hypoxia, inflammatory mediators, and oxidative stress [49 –52]. Subjects who have a high risk of developing hypertension have decreased spirometry parameters many years before diagnosis, which further progressively deteriorate after the development of hypertension [53]. Moreover, on one side, pulmonary dysfunction due to hypertension has been under-recognized clinically because of the large microvascular bed, its substantial loss can be tolerated without developing dyspnea [16]. On the other side, it has been reported that altered lung functions have an association with increased morbidity and mortality among patients with hypertension even in the absence of overt respiratory symptoms or disease [53 –55]. All these findings and suggested hypotheses make the relationship between hypertension and lung function very complex and difficult to understand. Hence, future research should focus on finding answers to this complex relationship through prospective studies.

4.6 Strengths and limitations

Our study is one of the initial studies among mine workers, adjusting for important confounding variables, for determining the predictors of pulmonary dysfunction vis-à-vis the hypertension status. The usage of standardized spirometry methods and the high response rate among the participants give strength to this study. Additionally, the authors followed the STROBE guidelines for cross-sectional study reporting [56].

However, when interpreting the results of our study, it is important to consider its limitations. Firstly, we may not have included all the possible confounders that could affect pulmonary functions, such as a specific class of anti-hypertensive drugs and types of mines. Secondly, our study’s cross-sectional design and use of linear regression statistical methods do not allow us to establish causal relationships. Thirdly, we measured each participant’s blood pressure only once and re-checked it only if the initial reading was abnormal, which deviates from standard guidelines. This deviation could have affected the accuracy of our blood pressure measurements, and measuring blood pressure at multiple points could have resulted in more precise readings. Finally, our study’s results may have constrained generalizability to a wider population of mine workers, as they could exclusively pertain to mine workers in Gujarat.

5 Conclusions

We conclude that among mine workers, alterations in lung function parameters (FEV1 and FVC) on spirometry were primarily predicted by gender and duration of work experience, whereas hypertension status did not demonstrate a role as a predictor. Nevertheless, due to the rising prevalence of hypertension among mine workers and their susceptibility to pulmonary dysfunction, it is crucial to measure and record blood pressure levels and screen for hypertension during every clinic visit, in addition to periodic medical examinations. It is noteworthy that antihypertensive drugs were found to reduce lung function, highlighting the need for further research. We suggest conducting prospective cohort studies or designing retrospective cohorts based on existing data from periodic medical examinations to either confirm or refute hypertension as a risk factor for pulmonary dysfunction. Additionally, future research should obtain detailed information on drug class, dosage, and duration of antihypertensive drug use among mine workers to determine their precise impact on pulmonary function.

Ethics statement

The study was approved by the Institutional Human Ethics Committee of ICMR - National Institute of Occupational Health (Ahmedabad) [approval number: ICMR-NIOH/EC/2020/01, date: August 04, 2020]. The study was performed following the Declaration of Helsinki.

Informed consent

Written informed consent was obtained from all study participants before their enrolment in the study.

Conflict of interest

None to report.

Footnotes

Acknowledgments

The authors thank Mr Umesh Dhumane, Technical officer and Mr Moinuddin Mansuri, Technician –‘A’ at ICMR-National Institute of Occupational Health (Ahmedabad, Gujarat) for their assistance in field studies.

Funding

This is non-funded research.

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