|Year : 2012 | Volume
| Issue : 3 | Page : 137-141
Noncommunicable disease risk profile of factory workers in Delhi
Jugal Kishore, Charu Kohli, Pramod Kumar Sharma, Ekta Sharma
Department of Community Medicine, Maulana Azad Medical College, New Delhi, India
|Date of Web Publication||13-May-2013|
Department of Community Medicine, Maulana Azad Medical College, New Delhi - 110 002
Source of Support: Indian Council of Medical Research, New Delhi, India funded the project for rural area,, Conflict of Interest: None
Background: Noncommunicable diseases (NCDs) are becoming more prevalent in India. The data for presence of NCDs and its risk factors among factory workers is deficient in India. Materials and Methods: A cross-sectional comparative study was carried out among 37 factory workers and equal number of comparable subjects from general population. Screening for presence of diabetes along with its risk factors was made in both the groups using pretested predesigned World Health Organization STEPwise approach to surveillance (WHO STEPS) questionnaire in rural area of Delhi. Data was analyzed using SPSS version 16 software. The estimation of risk in two groups was done with calculation of odds ratio (OR). P values less than 0.05 were considered significant. Results: A total of 74 participants were included in the present study. Hypertension and diabetes was present in 13.5 and 5.4% of factory workers and four (10.8%) and three (8.8%) subjects in comparative group, respectively. Seven (18.9%) factory and eight (21.6%) non-factory subjects fell in the category of current smoker or smokeless tobacco users. High density lipoprotein levels were found abnormal among one (2.7%) factory worker and nine (24.3%) subjects in comparative group (P-value = 0.01). Behavioral risk factors, alcohol consumption, and fruits and vegetable intake were significantly different among two groups. Conclusion: Factory workers were having better profile than non-factory subjects except for risk factors such as alcohol intake and inadequate fruits and vegetable intake. However, healthy worker effect phenomenon cannot be ruled out.
Keywords: Factory, healthy worker effect phenomenon, noncommunicable diseases
|How to cite this article:|
Kishore J, Kohli C, Sharma PK, Sharma E. Noncommunicable disease risk profile of factory workers in Delhi. Indian J Occup Environ Med 2012;16:137-41
|How to cite this URL:|
Kishore J, Kohli C, Sharma PK, Sharma E. Noncommunicable disease risk profile of factory workers in Delhi. Indian J Occup Environ Med [serial online] 2012 [cited 2019 Apr 19];16:137-41. Available from: http://www.ijoem.com/text.asp?2012/16/3/137/111761
| Introduction|| |
Noncommunicable diseases (NCDs) are the leading causes of death globally, killing more people each year than all other causes combined. Available data demonstrate that nearly 80% of NCD deaths occur in low- and middle-income countries.  According to the World Health Organization (WHO), 36 million of 57 million deaths in 2008 were due to NCDs, 29% of NCD deaths in low- and middle-income countries in 2008 occurred before the age of 60 i.e., premature deaths. It was also found that 80% of premature heart disease, stroke, and diabetes can be prevented.  NCDs; especially cardiovascular disease, cancer, and type 2 diabetes mellitus; account for 53 and 44% of all deaths and disability adjusted life years (DALYs), respectively in India. 
According to WHO statistics for 2010 in India, NCDs are estimated to account for 53% of all deaths. Of these deaths, cardiovascular diseases and diabetes are the most common causes of deaths due to NCDs in India. 
The modifiable behavioral risk factors such as dietary habits, physical activity levels, tobacco, and alcohol abuse and high stress levels precipitate the development of physiological risk factors like obesity, raised blood pressure, deranged blood glucose, and dyslipidemia, leading to the ultimate progression to disease outcomes like coronary heart disease, stroke, diabetes, etc. 
As per WHO, in India, prevalence of behavioral risk factors like current daily tobacco smoking and physical inactivity are 13.9 and 14%, respectively; while prevalence of metabolic risk factors like raised blood pressure, raised blood glucose, overweight, obesity, and raised cholesterol are 32.5, 10.0, 11.0, 1.9, and 27.1%, respectively.  An important factor which is gaining increasing curiosity among researchers is occupation, work environment, and stress associated with it and to what extent it contributes to the development of NCDs. Studies have shown that hypertension and diabetes are more prevalent among the working population as compared to general population. ,
The present article is an attempt to identify NCDs and their risk factors among factory workers and compare it with the comparable sample from general population.
| Materials and Methods|| |
It was a cross-sectional comparative study.
The factory establishment where this study was carried out is situated in a rural area of Delhi. The factory is having processing unit for metal plating of sanitary materials.
The study was conducted over a period from November 2011 to April 2012.
Selection of cases
Thirty-seven subjects working in the factory and residing in the rural area were included as cases.
Selection of comparative group
Residents of same area where the factory was situated who were not working in that factory were taken as comparative group. This rural area (Pooth Khurd and Barwala) consists of a population of 18,800 in 2011. Equal number of matched age and sex subjects was taken from the rural area to prevent selection bias and to nullify the effect of confounding factors. Comparative group belonged to similar age group of 5 years as factory workers.
Screening for presence of diabetes along with its risk factors was made in both factory and comparative subjects. Both groups were subjected to fasting and postprandial blood sugar examination by glucose oxidase method and were also tested for presence of hyperlipidemia using semi auto analyzer. Their behavioral problems like tobacco and alcohol intake, physical activity and dietary habits, and anthropometric measurements were also recorded using standard techniques. Reports of all investigations were conveyed to the study subjects and were referred to nearest health facility if needed.
Predesigned, pretested, semistructured questionnaire containing items to assess identification data and socioeconomic status besides risks factors of diabetes was used.
The WHO STEPwise approach to surveillance (STEPS) approach was employed to study the profile of the risk factors for the NCDs in the population. STEPS approach includes three sequential phases: Collection of information on sociodemographic variables, behavioral risk factors, that is, tobacco use, alcohol use, physical inactivity, diet, and related factors using a questionnaire (STEP 1); obtaining clinical measurements such as weight, height, waist circumference, and blood pressure using standardized protocols and instruments (STEP 2); acquiring biochemical measurements, that is, blood glucose using fasting blood samples and postprandial after ensuring to give 75 g of glucose (STEP 3).  The standard WHO STEPS questionnaire was adapted by including local terms and translated into local (Hindi) language and was pretested before the study.
Self-reported history of use of tobacco as beedi/cigarette or any other form of tobacco, alcohol consumption, physical activity, and dietary habits including consumption of fruits and vegetables as well as history of hypertension and diabetes mellitus were obtained from both the groups.
Definitions of variables
Working definitions of variables are adopted from the WHO STEPS questionnaire. Current smoker/smokeless tobacco user was defined as someone who at the time of the survey, smokes/uses tobacco in any form either daily or occasionally. Current daily smoker/smokeless tobacco user was defined as someone who smokes/uses tobacco everyday with rare exceptions such as not on days of religious fasting or during acute illnesses. Past tobacco smokers/user were defined as the current smokers or current daily smokers without any history of smoking/tobacco use for past one year. Current alcohol consumption was defined as one or more than one drink of alcohol consumed daily, one or more times in 1 week, one or more than one in 30 days, and one or more than one in 1 year. Former alcohol user is one who has not taken any drink for last 1 year but was taking before. Adequate fruit intake and vegetable intake was defined as one or more than one serving any seasonal fruit and cooked or raw vegetables, respectively consumed in a day for most days in a week. Physical activity is adequate when person is exercising regularly (daily or 3-4 times a week) in which his/her heart rate or respiratory rate increased for at least 10 min.
Physical body measurements including blood pressure, height, weight, waist, and hip circumference were taken. Blood pressure was recorded three times in sitting position on the right arm using a standard digital sphygmomanometer. The standard protocol was followed and the average of the last two readings was used in the analyses. Hypertension was defined as blood pressure more than or equal to 140 mmHg systolic and/or 90 mmHg diastolic according to the seventh report of the Joint National Committee.  Measuring tape made of nonstretchable steel which measures height to nearest centimeter with an accuracy of 0.5 cm was used.
Portable weighing machine with capacity up to 150 kg and measures weight to the nearest 500 g was taken. Waist circumference was measured using a tape measure in centimeters, and the measurement was made in the midaxillary line midway between the last rib and highest point of the iliac crest. Hip circumference was measured horizontally at the point of maximum circumference over the buttocks. Height was measured with the participant standing barefoot, upright against a wall with head in the Frankfort position, heels and knees together and looking straight ahead. After being appropriately positioned, the participant was asked to exhale and height was marked on the wall. The height of that marked point on wall was measured by nonstretchable steel tape to the nearest centimeter. Weight was recorded in kilograms using a standard weighing scale with the participant in light clothing, standing still with face forward and arms by the sides of the body. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Obesity was defined as BMI ≥ 25 kg/m 2 .  Waist circumference > 90 cm for males and > 80 cm for females was considered an indicator of abdominal obesity.  Lipid disorders were defined according to National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) final report as total cholesterol ≥ 200 mg%, triglycerides ≥ 150 mg%, low density lipoprotein cholesterol ≥ 130 mg%, and high density lipoprotein (HDL) cholesterol < 40 mg%. 
The participants were asked to fast overnight (at least 8 h) for sample collection next morning. A fasting venous blood sample was obtained for metabolic profile. Postprandial samples were taken after 2 h of 75 g of glucose intake. Estimations for fasting blood glucose and postprandial were performed using commercial kits. Raised fasting glucose was taken as the fasting plasma glucose level of > 126 mg/dL, according to the diagnostic criteria of the WHO.
Inclusion and exclusion criteria
All workers working in the factory for at least past 1 year and residing in same locality were included in the study; known cases of diabetes mellitus were also included in the study. Workers who were seriously ill due to physical or mental component of health were excluded from the study.
The estimation of risk in two groups with respect to diabetes, hypertension, hyperlipidemia, etc., was done with calculation of odds ratio (OR) with 95% confidence interval (CI). P values less than 0.05 were considered to be significant.
All the participants were explained procedure and purpose of the study before taking data. Confidentiality was maintained throughout the study. Written informed consent was taken from the study subjects. Option to withdraw from the study at any time was kept open. The ethical clearance for the study was obtained from the institutional ethics committee.
| Results|| |
A total of 74 participants were included in the present study; 37 factory workers and 37 comparative group (non factory workers). In both the groups, there were 21 males and 16 females. Among factory workers, 20 (54.1%) were illiterate and 17 (45.9%) were literate while in comparative group all of them were literate. Among factory workers 30 were Hindus and seven were Muslims but in comparative group all of them were Hindus. Majority of participants in both the groups were married; 32 (86.5%) and 31 (83.8%) in factory workers and comparative group, respectively. Detail of demographic profile is given in [Table 1].
Non communicable diseases
Hypertension was found to be present in five (13.5%) factory workers and four (10.8%) subjects in comparative group, however it was not significant (OR = 0.77, CI = 0.19-3.15, P value = 0.72). Diabetes was present in two (5.4%) factory workers and three (8.1%) subjects in comapartive group, but this was also not significant (OR = 0.64, CI = 0.10-4.12, P value = 0.64). Total cholesterol levels were high among five (13.5%) factory workers and nine (24.3%) subjects in comparative group, but this difference was not significant (OR = 2.05, CI = 0.61-6.86, P value = 0.23). Triglycerides levels were also checked in which it was found that they were raised among six (16.2%) factory workers and five (13.5%) in the comparative group, but again this was not significant (OR = 0.80, CI = 0.22-2.92, P value = 0.74). HDL levels were found abnormal among one (2.7%) factory worker and nine (24.3%) subjects in comparative group and this difference was significant (OR = 11.57, CI = 1.38-96.80, P value = 0.01. Details are given in [Table 2].
Behavioral risk factors
Seven (18.9%) factory workers and eight (21.6%) in comparative group fell in category of current smoker or smokeless tobacco users but this was not statistically significant (OR = 1.18, CI = 0.38-3.68, P value = 0.77). There were no past tobacco users/smokers in any group. Current alcohol consumption was present in six (16.2%) factory workers and two (5.4%) in comparative group, while former alcohol use was present in four (10.8%) factory workers and zero (0%) subjects in comparative group. This was statistically significant with (χ2 = 7.03, P value = 0.03). BMI was also calculated in which it was found to be raised among seven (18.9%) factory workers and 13 (35.1%) subjects in comparative group, but it was not statistically significant (OR = 2.32, CI = 0.80-6.72, P value = 0.11). Adequate physical activity was practiced by one (2.7%) in factory worker group and three (8.1%) in comparative group, but this was not significant with (OR = 3.17, CI = 0.31-32.03, P value=0.30). Adequate fruits and vegetable intake was found in zero factory worker and six (16.2%) in comparative group which was statistically significant with χ2 = 6.52, P value = 0.01 as shown in [Table 3].
| Discussion|| |
The present study showed that occurrence of NCDs like hypertension and diabetes mellitus type 2 in factory workers are not much different from the non-factory subjects. Hypertension was present in 13.5% of the factory workers. Diabetes was diagnosed in 5.4% of factory workers. For both the diseases among two groups, results were not statistically significant. In another study by Martinez et al.,  among metallurgic and siderurgic company's workers in 2006 showed prevalence of 24.7% of hypertension and 11.4% for diabetes.  Blood investigation for total cholesterol levels and triglyceride levels were also not different among the two groups. The results for the above parameters were not statistically significant. But significantly higher percentage (24.3%) of comparative group had abnormal HDL levels as compared to factory workers (2.7%) with odds ratio of 11.57. A study by Amidu et al.,  among automobile garage workers in 2012 found that raised triglycerides was present in 31.5% of workers and reduced HDL levels were found in 38.5% of the workers. 
When modifiable behavioral risk factors like tobacco use, alcohol intake, physical activity, and dietary habits were assessed, it was found that 18.9% of factory workers fell in the category of current smoker/smokeless tobacco user. This goes in line with another study by Mou et al.,  among migrant factory workers in China in 2012 where overall smoking prevalence (including occasional, daily, and heavy daily smoking) was 19.1% among factory workers which was less than the rates obtained for national population.  However, alcohol usage was more statistically significantly among the factory workers than other group. The obesity was present in 18.9% of factory workers although the results were not statistically significant. A study by Al-Zurba et al.,  among non-Bahraini workers (labor force) in Bahrain in 2003 found that 30.6% of workers had BMI > 25.
For physical activity, it was found that inadequate physical activity was present in 97.3% of the population. This is in contrast to another study by Mehan et al.,  in 2006 where about 17.3% of the subjects were categorized as physically inactive. In this study the tobacco and alcohol usage habit was prevalent in 31.4 and 5% of the study subjects, respectively. Inadequate fruit and vegetable intake was present in 100% of the workers as compared to 83% of the non-factory group. This is in accordance with another study by Mehan et al.,  among chemical industry workers in Baroda in 2007 in which majority (93.2%) of the workers had low intake of fruits and vegetables. In another study by Kishore and Joshi  in 2001 among male workers in Delhi showed that prevalence of chronic illnesses like asthma, heart disease, and diabetes in businessmen and professionals was higher than other categories of workers. Current tobacco, alcohol use and non-vegetarian diet was more prevalent in unskilled (41.61, 36.02, and 61.09%), semiskilled (42.57, 37.62, and 64.34%), and skilled (44.75, 36.96, and 61.09%) workers.
The present study shows that factory workers are not at a greater risk of developing NCDs as compared to non-factory worker with some exceptions like HDL levels, alcohol use, and fruits and vegetable intake. Other possible explanations for the results could be small sample size and healthy worker phenomenon. Healthy worker effect (HWE) is a phenomenon initially observed in studies of occupational diseases. It means that occupationally active people have a more favorable mortality experience than the population at large.  HWE phenomenon has also been shown in some other studies.  The results could also be influenced by statistically significant difference in educational status and monthly income.
The study has not taken attempts to control the HWE phenomenon. The two groups were not comparable in all aspects as shown by the significant difference in education and income category.
| Conclusion|| |
NCDs risk factors of alcohol intake and inadequate fruits and vegetable intake are present in factory workers. HWE phenomenon might have influenced the results. Further studies are required to assess the relationship of NCD risk factors with occupation after control of confounding factors and HWE phenomenon with an adequate sample size.
| Acknowledgment|| |
The authors are highly grateful to factory workers and inhabitants of village who participated in the study.
| References|| |
|1.||Global status report on noncommunicable diseases 2010. Available from: http://whqlibdoc.who.int/publications/2011/9789240686458_eng.pdf. [Last accessed on 2012 Jun 10]. |
|2.||Global Health Observatory. Noncommunicable diseases (NCD). Available from: http://www.who.int/gho/ncd/en/index.html [Last accessed on 2012 July 15]. |
|3.||World Health Organization. Report on preventing chronic diseases: A vital investment. WHO: 2005. Available from: http://www.who.int/chp/chronic_disease_report/en/ [Last accessed on 2012 Aug 2]. |
|4.||NCDs country profile. 2010. Available from: http://www.who.int/nmh/countries/ind_en.pdf [Last accessed on 2012 Oct 14]. |
|5.||World Health Organization. Quantifying selected major risks to health. In: The World health reports 2002 reducing risks, promoting health life. Geneva: World Health Organization. Available from: http://www.who.int/whr/2002/en/whr02_en.pdf [Last accessed on 2012 Oct 2]. |
|6.||Undhad A, Bharodiya PJ, Sonani RP. Correlates of hypertension among the bank employees of Surat city of Gujarat. Nat J Commun Med 2011;2:123 5. |
|7.||Golmohammadi R, Abdulrahman B. Relationship between occupational stress and non insulin dependent diabetes in different occupation in Hamadan (West of Iran). J Med Sci 2006;6:241 4. |
|8.||WHO STEPS Instrument (Core and Expanded). WHO Geneva. Available from: http://www.who.int/chp/steps/Part 5.pdf [Last accessed on 2012 Oct 12]. |
|9.||Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, et al. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension 2003;42:1206 52. |
|10.||Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al. Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India 2009;57:163 70. |
|11.||Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 2001;285:2486 97. |
|12.||Martinez MC, Latorre Mdo R. Risk factors for hypertension and diabetes mellitus in metallurgic and siderurgic company′s workers. Arq Bras Cardiol 2006;87:471 9. |
|13.||Amidu N, Owiredu WK, Mireku EK, Agyemang C. Metabolic syndrome among garage workers in the automobile industry in Kumasi, Ghana. J Med Biomed Sci 2012;1:29 36. |
|14.||Mou J, Fellmeth G, Griffiths S, Dawes M, Cheng J. Tobacco smoking among migrant factory workers in Shenzhen, China. Nicotine Tob Res 2013;15:69 76. |
|15.||Al Zurba FI, Al Mansour AA. Prevalence of diabetes mellitus among non Bahraini workers registered in primary health care in Bahrain. Bahrain Med Bull 2003;25:12 7. |
|16.||Mehan MB, Srivastava N, Pandya H. Profile of non communicable disease risk factors in an industrial setting. J Postgrad Med 2006;52:167 71. |
|17.||Mehan M, Kantharia N, Surabhi S. Risk factor profile of noncommunicable disease in industrial productive (25 59 years) population in Baroda. Int J Diabetes Dev Ctries 2007;27:116 21. |
|18.||Kishore J, Joshi TK. Health status and health seeking behaviour of male workers in Delhi. Ind J Commn Med 2001;26:192 7. |
|19.||Kishore J. A dictionary of public health. 2nd ed. New Delhi: Century Publications; 2007, p. 407. |
|20.||Iwatsubo Y, Matrat M, Brochard P, Ameille J, Choudat D, Conso F, et al. Healthy worker effect and changes in respiratory symptoms and lung function in hairdressing apprentices. Occup Environ Med 2003;60:831 40. |
[Table 1], [Table 2], [Table 3]
|This article has been cited by|
||Noncommunicable disease risk profile of factory workers in Delhi: An occupational tinge!
| ||Chaudhary, S. |
| ||Indian Journal of Occupational and Environmental Medicine. 2013; 17(2): 80-81 |