|Year : 2016 | Volume
| Issue : 1 | Page : 32-36
Occurrence of metabolic syndrome with relation to job profile among mine employees
Subroto Shambhu Nandi, Sarang Vilas Dhatrak, Umesh Laxman Dhumne
Occupational Health Department, National Institute of Miners' Health, JNARDDC Campus, Nagpur, Maharashtra, India
|Date of Submission||15-Jul-2015|
|Date of Decision||15-Dec-2015|
|Date of Acceptance||05-Apr-2016|
|Date of Web Publication||16-Jun-2016|
Sarang Vilas Dhatrak
National Institute of Miners' Health, JNARDDC Campus, Wadi, Nagpur - 440 023, Maharashtra
Source of Support: None, Conflict of Interest: None
Background: Metabolic syndrome (MS) is an emerging concern of modern times and has an increasing trend in developing countries because of the westernization of diet and lifestyle. The significance of diagnosis of this MS is to identify individuals at a high risk of type 2 diabetes and cardiovascular disease. Objective: To study the occurrence of MS among different categories of mine employees. Materials and Methods: Health surveillance data of 1116 mine employees were analyzed and classified according to their job profile as office workers, maintenance workers, machine operators, and helpers. The WHO criteria were used for the diagnosis of MS. Results: MS was present in 14.7% of the mine employees with highest among machine operators (19.6%) and least among helper group (10.4%). It was also observed that occurrence of MS was directly proportional to age. The occurrence of MS increased by 9%, 11.5%, 38.7%, and 40.6% in the age group of 18-30, 31-40, 41-50, and 51-60 years, respectively. Conclusion: MS is becoming a major health concern among mine employees. There is a need to establish regular educational programs and effective intervention strategies to promote healthy lifestyle for mine employees.
Keywords: Job profile, metabolic syndrome, mine employees, WHO criteria
|How to cite this article:|
Nandi SS, Dhatrak SV, Dhumne UL. Occurrence of metabolic syndrome with relation to job profile among mine employees. J Obes Metab Res 2016;3:32-6
|How to cite this URL:|
Nandi SS, Dhatrak SV, Dhumne UL. Occurrence of metabolic syndrome with relation to job profile among mine employees. J Obes Metab Res [serial online] 2016 [cited 2021 Jan 19];3:32-6. Available from: https://www.jomrjournal.org/text.asp?2016/3/1/32/184139
| Introduction|| |
Metabolic syndrome (MS) is an emerging concern of modern times; it is a condition defined as a cluster of features, associated with obesity that raise the risk of cardiovascular disease (CVD) and type 2 diabetes (T2DM). These syndromic features are increased waist circumference, high blood pressure (BP), high level of triglycerides (TGs), low level of high-density lipoprotein cholesterol (HDL-C), and high fasting blood glucose levels.  MS is a condition in which at least three of these features are present simultaneously.  Data suggest that this syndrome has an increasing trend in developing countries because of the westernization of diet and lifestyle.  The significance of diagnosis of the MS is to identify individuals at a high risk of T2DM and CVD.  Studies have shown that this syndrome is relatively common in societies that have undergone alterations in lifestyle habits due to economic and technological changes. It has been estimated that 44% of the American population above 50 years of age are affected with this syndrome.  Worldwide, prevalence ranges from 10% to about 84%, depending on the region, sex, age, race, and ethnicity of the studied population.  Prevalence of MS is high among Asians, including Indians, and is rising particularly with the adoption of modernized lifestyle. Prevalence in India ranges from 10% to 50% depending on age and sex. ,,, Many studies have been carried out in general population. However, there is scarce information available about the prevalence of MS in different occupational settings. This article deals with the magnitude of this syndrome among mine employees of Gujarat state in India.
| Materials and methods|| |
Health surveillance data of 1116 male mine employees, from Gujarat state, were analyzed. Based on their occupational profile, the mine employees were categorized into four major groups, namely office workers - those involved in administrative work, maintenance workers - those involved in the maintenance of mines machinery, machine operators - those involved in the operation of mine machineries, and helpers - those involved in labor and assistant work in mines [Table 1]. Body weight and height were measured and body mass index (BMI) was calculated as weight in kilograms divided by squared height in meter (kg/m 2 ). Arterial BP (systolic and diastolic) was measured. The Joint National Committee recommendation was followed for the measurement of arterial hypertension.  Fasting blood sample (5 ml) was collected from each subject and serum was obtained by centrifugation. The blood samples were assayed for biochemical tests by standard methods for glucose, total cholesterol, TG, and HDL-C, using a semi-automated analyzer. The fasting blood glucose was analyzed by glucose oxidase peroxidase (GOP-PAP) method,  total cholesterol and HDL-C were analyzed by CHOD-PAP method,  and TGs was analyzed by GPO-PAP Trinder method.  The LDL-C concentrations were calculated by applying the Friedewald equation.  Very low-density lipoprotein cholesterol (VLDL-C) was calculated by indirect method as VLDL-C is one-fifth of TG level. The WHO criteria were used for the diagnosis of MS.  As per the criteria, MS is diagnosed when an individual with diabetes mellitus or impaired glucose tolerance has any of the two or more of the following conditions such as increased central obesity (waist/hip ratio >0.90 in males or BMI >30 kg/m 2 ), elevated TG (≥150 mg/dl), low HDL-C (<35 mg/dl for males), and systolic arterial BP ≥ 140 mmHg and diastolic arterial BP ≥ 90 mmHg. Data were analyzed using the Epi-Info version 3.3.2 software (Centers for Disease Control and Prevention Atlanta, Georgia, USA). All continuous variables were reported as mean and standard deviation, and Chi-squared test and P value were used to analyze the data.
| Results|| |
Occupation and age-wise distribution of mine employees is summarized in [Table 1]. Majority (67.1%) of the mine employees were in the age group of 41-60 years while 32.9% were in the age group of 18-40 years. The mean values of BMI, BP, and clinical biochemistry of the study population are shown in [Table 2]. Presence of MS and its components in various occupational groups is shown in [Table 3]. MS was present in 14.7% of the mine employees with the highest prevalence among machine operators (19.6%) and the least among helper group (10.4%). Occurrence of MS with respect to age group among different occupational groups is shown in [Table 4].
|Table 2: Mean values of body mass index, blood pressure, and clinical biochemistry |
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|Table 3: Presence of metabolic syndrome and its components in various occupational groups |
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|Table 4: Group-wise occurrence of metabolic syndrome in different age groups |
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| Discussion|| |
Prevalence of MS is on rise globally, including in India. Many studies have reported this rising trend in general population. However, there are very few studies conducted in occupational settings. Mining being one of the important occupations, engaging millions of persons globally, studies related to occurrence of MS among them are desirable.
Few studies conducted among different occupational groups have depicted the prevalence of MS in different occupational groups. ,, In one study conducted among Spanish workers, MS was present in about 15.1% among machine installers, operators, and assemblers, with an overall prevalence of 11.6% in male workers.  In a study among the U.S. workers, the overall prevalence of MS was 20.6% with highest among transportation and material occupation workers - 33.1%.  In another study among Korean workers, MS was present in 31.7% among manager group and 35.4% among machine operators' group. 
A study conducted among Indian workers by Nair reported the prevalence of MS among managers (30.7%), clerical support workers (24%), and elementary occupations (15.7%). 
The present study assessed the occurrence of MS and its components among mine employees engaged in different occupational groups. MS was present in 14.7% mine employees with highest among machine operators (19.6%) followed by maintenance (18.7%), office workers (14.4%), and least among helper group (10.4%). The difference among the groups was found to be statistically significant (P = 0.003). An occupation-wise prevalence of MS in the present study suggests that it is a major health problem even in those who are engaged in physically active occupation, but with a sedentary demand. As the helper group is involved in more physical work, the occurrence of MS might be least as compared to other groups.
Among the individual MS components, diabetes/impaired glucose tolerance (45.9%) was most common component followed by hypertriglyceridemia (43.6%), elevated BP (26.5%), low HDL-C (14.1%), and obesity (11.0%). Chi-square test analysis showed that diabetes and obesity were statistically significant in all occupation groups while other components were not statistically significant.
In this study, out of 1116 mine employees, 43.6% employees had TG level ≥ 150 mg/dl. Many prospective epidemiological studies have reported a positive relationship between serum TG levels and incidence of coronary heart disease. Thus, elevated serum TGs help to identify persons who are at risk. , Obesity (BMI >30) was seen in 11% of the study population. It is known that obesity increases the risk of dyslipidemia, T2DM, and hypertension, and it is a strong predictor of coronary heart disease. 
The prevalence of obesity, hypertension, dyslipidemia, and hyperglycemia increases with age, and hence the prevalence of MS is also expected to increase by age. In an European study, ,, among 11 population-based cohorts, the prevalence increased noticeably from the age of 30, and similar observations have been made in the U.S. and China. , In the present study too, it was observed that occurrence of MS was directly proportional to age in all the groups. The prevalence increased by 9%, 11.5%, 38.7%, and 40.6% in the age group of 18-30, 31-40, 41-50, and 51-60 years, respectively [Table 4].
This is probably the first study to report the prevalence of MS among mine employees in Gujarat state. Data from this study may be helpful to formulate interventional strategies to prevent avoidable complications of MS such as CVD, T2DM, and thereby preventing morbidity among mine employees. In addition to regular health examinations, there is a need of inclusion of behavior modification programs regarding mental stress at work, importance of regular exercise, healthy diet, etc., among mine employees.
| Conclusion|| |
The present study showed that MS is becoming a major health concern among mine employees. Diabetes and hypertriglyceridemia are the major contributors of MS. There is a need to establish regular educational programs and effective intervention strategies to promote healthy lifestyle for mine employees.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Grundy SM, Brewer HB Jr., Cleeman JI, Smith SC Jr., Lenfant C; American Heart Association; National Heart, Lung, et al. Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation 2004;109:433-8.
Akinci G, Coskun S, Akinci B, Hekimsoy Z, Bayindir P, Onur E, et al. Atherosclerosis risk factors in children of parents with the metabolic syndrome. Atherosclerosis 2007;194:e165-71.
Alberti G, Zimmet P, Shaw J. The metabolic syndrome new worldwide definition. J Diabetes 2005;366:1059-62. Available from: http://www.thelancet.com
. [Last accessed on 2005 Sep 24].
Alexander CM, Landsman PB, Teutsch SM, Haffner SM; Third National Health and Nutrition Examination Survey (NHANES III); National Cholesterol Education Program (NCEP). NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. Diabetes 2003;52:1210-4.
Cameron AJ, Shaw JE, Zimmet PZ. The metabolic syndrome: Prevalence in worldwide populations. Endocrinol Metab Clin North Am 2004;33:351-75.
Deepa M, Farooq S, Datta M, Deepa R, Mohan V. Prevalence of metabolic syndrome using WHO, ATPIII and IDF definitions in Asian Indians: The Chennai urban rural epidemiology study (CURES-34). Diabetes Metab Res Rev 2007;23:127-34.
Kanjilal S, Shanker J, Rao VS, Khadrinarasimhaih NB, Mukherjee M, Iyengar SS, et al. Prevalence and component analysis of metabolic syndrome: An Indian atherosclerosis research study perspective. Vasc Health Risk Manag 2008;4:189-97.
Gupta R, Deedwania PC, Gupta A, Rastogi S, Panwar RB, Kothari K. Prevalence of metabolic syndrome in an Indian urban population. Int J Cardiol 2004;97:257-61.
Kamble P, Deshmukh PR, Garg N. Metabolic syndrome in adult population of rural Wardha, central India. Indian J Med Res 2010;132:701-5.
The sixth report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Arch Intern Med 1997;157:2413-46.
Trinder P. Quantitative determination of glucose using GOP-PAP method. Clin Biochem 1969;6:24-7.
Allain CC, Poon LS, Chan CS, Richmond W, Fu PC. Enzymatic determination of total serum cholesterol. Clin Chem 1974;20:470-5.
Trinder P. Triglyceride estimation by GPD-PAP method. Ann Clin Biochem 1969;6:24-7.
Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499-502.
Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998;15:539-53.
Davila EP, Florez H, Fleming LE, Lee DJ, Goodman E, LeBlanc WG, et al. Prevalence of the metabolic syndrome among U.S. workers. Diabetes Care 2010;33:2390-5.
Sánchez-Chaparro MA, Calvo-Bonacho E, González-Quintela A, Fernández-Labandera C, Cabrera M, Sáinz JC, et al. Occupation-related differences in the prevalence of metabolic syndrome. Diabetes Care 2008;31:1884-5.
Ryu JY, Hong S, Kim CH, Lee S, Kim JH, Lee JT, et al. Prevalence of the Metabolic Syndrome among Korean Workers by Occupational Group: Fifth Korean National Health and Nutrition Examination Survey (KNHANES) 2010. Ann Occup Environ Med 2013;25:13.
Nair CV. Metabolic syndrome: An occupational perspective. Indian J Community Med 2010;35:122-4.
Assmann G, Schulte H, Funke H, von Eckardstein A. The emergence of triglycerides as a significant independent risk factor in coronary artery disease. Eur Heart J 1998;19 Suppl M: M8-14.
Austin MA, Hokanson JE, Edwards KL. Hypertriglyceridemia as a cardiovascular risk factor. Am J Cardiol 1998;81:7B-12B.
Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults - The evidence report. National Institutes of Health. Obes Res 1998;6 Suppl 2:51S-209S.
Qiao Q, Tuomilehto J, Balkau B, Borch-Johnsen K, Heine R, Wareham NJ; DECODE Study Group. Are insulin resistance, impaired fasting glucose and impaired glucose tolerance all equally strongly related to age? Diabet Med 2005;22:1476-81.
Hu G, Qiao Q, Tuomilehto J, Balkau B, Borch-Johnsen K, Pyorala K; DECODE Study Group. Prevalence of the metabolic syndrome and its relation to all-cause and cardiovascular mortality in nondiabetic European men and women. Arch Intern Med 2004;164:1066-76.
Hu G, Qiao Q, Tuomilehto J, Eliasson M, Feskens EJ, Pyörälä K; DECODE Insulin Study Group. Plasma insulin and cardiovascular mortality in non-diabetic European men and women: A meta-analysis of data from eleven prospective studies. Diabetologia 2004;47:1245-56.
Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: Findings from the third National Health and Nutrition Examination Survey. JAMA 2002;287:356-9.
Gu D, Reynolds K, Wu X, Chen J, Duan X, Reynolds RF, et al. Prevalence of the metabolic syndrome and overweight among adults in China. Lancet 2005;365:1398-405.
[Table 1], [Table 2], [Table 3], [Table 4]