|Year : 2022 | Volume
| Issue : 1 | Page : 9-15
Incidence and risk for hypertension among regular medical examination attendee cohort in an automobile industry. A cox- regression analysis model
Gautham Melur Sukumar1, Vaishali Dagar1, Kowshik Kupatira2, Pradeep S Banandur1, Gururaj Gopalkrishna1
1 Department of Epidemiology, Centre for Public Health, NIMHANS, Bengaluru, Karnataka, India
2 Chief Medical Officer, Occupational Health Unit, Autombile Industry Pvt Limited, Industry, Bidadi, Karnataka, India
|Date of Submission||18-Oct-2021|
|Date of Acceptance||06-Dec-2021|
|Date of Web Publication||7-Apr-2022|
Dr. Gautham Melur Sukumar
Department of Epidemiology, Centre for Public Health, NIMHANS, Bengaluru - 560 029, Karnataka
Source of Support: None, Conflict of Interest: None
Introduction: With nearly 1,612,505 industrial workers in Karnataka, controlling hypertension among them is necessary to reduce subsequent non-communicable diseases (NCDs). However, information on prevalence, incidence, and risk for hypertension among industrial workers is limited. Objectives: To estimate the prevalence, incidence proportion, incidence rate, and risk for hypertension among annual medical examination [AME] attendee cohort between 2010 and 2014 in an automobile industry in India. Materials and Methods: Longitudinal record analysis (cohort approach) of 640 regular AME attendees between 2010 and 2014 was performed to estimate incidence and incidence rates. Cox regression was conducted to estimate the risk for hypertension in the study period. Necessary permission and ethics clearance was obtained. Results and Conclusion: The prevalence of hypertension significantly increased from 8.8% in 2010 to 26.6% in 2014. The small increase in mean blood pressure (BP) resulted in large increases in the prevalence of hypertension. The incidence rate increased from 6.5 per 1000 person-months of observation in 2012 to 14.5 in 2014. No significant risk for hypertension was observed for the work department and type of plant. Results indicate a rising burden of hypertension with no specific risks associated with different work departments or types of plants. AME data is a utility value to monitor hypertension trends among employees and evaluate the effectiveness of worksite health programs to reduce hypertension.
Keywords: Employees, hypertension, industry, non-communicable diseases, risk
|How to cite this article:|
Sukumar GM, Dagar V, Kupatira K, Banandur PS, Gopalkrishna G. Incidence and risk for hypertension among regular medical examination attendee cohort in an automobile industry. A cox- regression analysis model. Indian J Occup Environ Med 2022;26:9-15
|How to cite this URL:|
Sukumar GM, Dagar V, Kupatira K, Banandur PS, Gopalkrishna G. Incidence and risk for hypertension among regular medical examination attendee cohort in an automobile industry. A cox- regression analysis model. Indian J Occup Environ Med [serial online] 2022 [cited 2022 May 26];26:9-15. Available from: https://www.ijoem.com/text.asp?2022/26/1/9/342673
| Introduction|| |
An estimated 6.1 million people died due to non-communicable diseases (NCDs) in 2019 in India, of which one-fourth were premature deaths. Apart from deaths, NCDs accounted for 57.92% (55.19%–60.35%) of total disability-adjusted life years (DALYs) in the same year. Common modifiable risk factors such as raised blood pressure (hypertension), raised blood sugars (diabetes), abnormal blood lipids (dyslipidemia), obesity, tobacco, alcohol use, and physical inactivity underlie most of these NCDs. With the increase in socio-environmental determinants, the burden of NCDs is only expected to rise in the future, unless intervened. Of the various modifiable risk factors, hypertension is a leading risk factor for cardiovascular diseases and stroke.
The prevalence of hypertension in the Indian general population is estimated at 29.8% (95% confidence interval [CI]: 26.7–33.0). In Karnataka, the prevalence of hypertension among adults (aged 15 + years) is 26.9% among males and 25.0% among females. Workers, being a major sub-set of the general population (39% of the population), are likely to be affected by the prevalence of hypertension in the general population, implying that workplace interventions to reduce hypertension are very important, to achieve control in the general population.
Data from census 2011 indicate that nearly 39% of the 1.34 billion population (around 537 million persons) in India reported themselves as workers, which is around 2,78,73,690 (2.8 crores) in the state of Karnataka (45.62% of the population of the state). Most of these workers are aged between 18 and 59 years, the most prevalent age for onset and progression of hypertension. Identifying and managing hypertension at early stages among these workers would help reduce hypertension and resultant NCDs. Yet, information on prevalence and risk for hypertension among workers is limited in the state.
Industrial workers are a sub-set of workers who work in the factories, and statistics from the department of factories, Karnataka, reveal there are nearly 1,612,505 industrial workers in Karnataka. They are generally subjected to periodical medical examination wherein their blood pressure is often recorded. This serves as a useful date for screening, monitoring, and evaluating hypertension among workers. Understanding prevalence, incidence, and risk for hypertension from medical examination data would facilitate the implementation of evidence-based and risk-appropriate strategies to reduce hypertension. However, evidence from industrial workplaces is also limited in the state.
The Center for Public Health, National Institute of Mental Health and Neuro-Sciences (NIMHANS), is working with a leading automobile industry in Karnataka to strengthen functional integration of NCD care into industrial health systems. As a part of this larger health and productivity-related project, we estimated the prevalence, incidence, incidence rate, and risk for hypertension among regular periodical (annual) examination attendee cohort between 2010 and 2014.
| Objectives|| |
- To estimate the prevalence, incidence, incidence proportion, and incidence rate for hypertension among annual medical examination [AME] attendee cohort between 2010 and 2014 in an automobile industry.
- To estimate the risk for hypertension by age, plant, and work location among AME attendee cohort between 2010 and 2014 in an automobile industry.
| Methods|| |
This longitudinal record analysis was conducted on a regular AME attendee cohort of industrial employees in a leading automobile industry in the southern part of India. Of the total 6,544 “employees on-roll” (as on February 1, 2015), 640 employees attended AME every year between 2010 to 2014 and were defined as “eligible records” for this study.
These employees work in different departments (also referred to as work locations) in the industry, which we broadly categorized as production-related and non–production-related departments. Production-related departments are departments of paint, assembly, internal logistics control department (ILCD), maintenance, press, weld, and quality that are involved directly in the production of automobiles, and employees are engaged in physical activity-based jobs. Non–production-related departments are employees working in the office, providing back-end support and their work involves limited physical activity.
Data of study participants were sourced from occupational health software used by the occupational health unit in the industry to capture and maintain the health data of employees. From this software, AME data for 2010 to 2014 was provided to the project team in an MS Excel format. In addition, data regarding work location (department of work), type of plant (Plant1 and Plant 2), date of birth, and date of joining were sourced from the human resources (HR) department. The HR department and AME data were merged using the VLOOK UP function in MS Excel, matched by employee ID.
Data of employees who had quit/terminated/dismissed from service between 2010 and 2014 were not maintained in the “on-roll” database available with the HR department and hence were not included in the study. Data were checked for consistency in entries, outliers, and coding. Inconsistencies were corrected in consultation with officers from the occupational health unit. After data cleaning, data were rendered into a time-series format to conduct time-to-event analysis.
The duration of work experience for each employee till the end of 2014 was computed by subtracting the date of joining from December 31, 2014. The age of each employee as on December 31, 2014, was computed by subtracting the date of birth with December 3. 2014. The age was further categorized into 18–24 years, 25–29 years, and 30+ years. We clubbed 30+ years as one category as they comprised all non-youth workers (persons aged less than 30 years are youth in India as per the National Youth Policy).
In this study, we have used terms elevated blood pressure and hypertension synonymously and interchangeably as investigators are not aware if the average of three readings were taken for all AME attendees, though health staff revealed an average of three were taken for employees recording higher values in the first reading.,
Date of event identification (diagnosis of hypertension) were considered as the date of attending AME and time-to-event was operationally defined as duration (days/months/years) between the date of joining and date of this AME where abnormal BP was recorded. It reflects the duration of work exposure before the onset of the event. In this particular industry, every employee underwent AME in their birth month.
Employees identified as having elevated BP/hypertension in the first AME (2010) were not included for follow-up and were censored. These employees were prevalent cases and were not included for estimation of incidence rate in 2010. Cases without elevated blood pressure were followed in records and included for assessment of incidence, incidence proportion, and incidence rate from 2011 onward. Any employee with systolic blood pressure (SBP) ≥140 mm of Hg or diastolic blood pressure (DBP) ≥90 mm of Hg was categorized as elevated blood pressure (hypertension), needing management., Workers recording either systolic and diastolic higher than normal, were categorized as employees with elevated blood pressure (hypertension).
Data analysis was done using STATA version 17. Age (in years), blood pressure (in mm of Hg), and work experience (in months) in each year (2010–14) are summarized as mean, standard deviation, and median. Normality was tested using the Shapiro–Wilk test following, which a one-way analysis of variance was applied to assess the significant differences in mean BP between 2010 and 2014.
The service duration (person-months of employment) is a proxy to person-months of exposure and is used as the denominator to calculate incidence rates. The total person-months of exposure of all employees, year-wise and between 2010 and 2014 was calculated by summing up person-months of each employee.
Incidence (number of new cases), incidence proportion (new cases identified/employees at risk), and incidence rates (number of new cases/person-months of employment) for elevated BP were calculated from 2011 onward. Specific incidence rates by year, age groups, and work department were also calculated. Point and period prevalence were also calculated.
Time-to-event is defined as the time from the date of joining till the date of event detection (date of AME on which event was detected). Cox proportional hazard regression modeling was performed to assess the risk/association for hypertension among employees from different categories of age, plant, and work location. The outcome (event) was binary categorical variable, that is, elevated BP (present/absent) and the independent variables were age categories (18–24 years, 25–29 years, ≥30 years), plant type (Plant 1 and Plant 2), work location (assembly production, ILCD production, maintenance, office employee, paint production, press production, quality, and weld production), and service duration categories (≤ 1 year, 2 years, 3 years, 4 years, ≥5 years). Hazard ratios (HR) were calculated with 95% confidence limits to provide a risk estimate for developing elevated BP in the study period. Service duration was later not included for regression as there was significant multi-collinearity with age. Ethical clearance was obtained from the Institutional Ethics committee, NIMHANS vide NIMH/DO/94th IEC/2014.
| Results|| |
The socio-demographic characteristics of the employees attending AME every year (2010–2014) are shown in [Table 1]. Among the 640 employees, 65% were youth (18–29 years), and 35% were aged 30+ years in 2010, which changed to 35% youth and 65% 30+ years by 2014 due to natural age progression. The median years of service are 8.08 years in 2010.
[Table 2] depicts the blood pressure status of AME attendees. The average SBP and DBP values increased by 2.17 mm of Hg and 2.77 mm of Hg, respectively, between 2010 and 2014. A statistically significant increase in mean SBP (F value 15.8574 and P value < 0.00001) and DBP (F value 18.728 and P value < 0.00001) between 2010 and 2014 was observed.
The prevalence of hypertension significantly increased from 8.8% in 2010 to 26.6% in 2014, an increase of 17.8 percent points by 2014 (nearly three times increase in the prevalence) (Chi-square for trend = 49, P < 0.001). There were 96 new cases in 2011, an additional 38, 54, and 69 cases were added in 2012, 2013, and 2014, respectively. The incidence proportion increased from 16.4% in 2011 to 17.4% in 2014. The incidence rate (per 1000 person-months of employment) was 13.7 in 2011 and increased to 14.5 in 2014, with a dip to 6.5 in 2012 as compared to 2011. An increase in the prevalence of pre-hypertensive was also observed. From 2012 onward, the prevalence of hypertension was more among employees aged >30 years.
During the 5-year period, 313 (48.9%) employees were identified to have hypertension. No significant risk for hypertension was observed for the work department and type of plant. Risk for hypertension was significantly lesser among workers aged between 25 and 29 years (HR = 0.15 [0.10,0.22]) and those aged 30 and 34 years (HR = 0.09 [0.06,0.14]), as against employees aged between 18 and 24 years [See [Table 3] and [Figure 1]]. The overall mean time for event occurrence was 11.3 years. (11.09,11.66).
| Discussion|| |
This study is unique as it attempts to communicate the utility of AME data to generate evidence regarding prevalence, incidence rates, and risk for hypertension among employees in an automobile industry in India, for which evidence is limited. A large amount of longitudinal NCD-related data of employees is collected; however, is seldom used for surveillance or NCD programming, either by industrial doctors, factory medical officers, or NCD policymakers. Epidemiologists and public health specialists believe the current epidemic of NCDs in general population is reflected in workplaces. Our discussion examines the results from this perspective.
We estimated a 5- ear hypertension prevalence of 49% and the yearly highest prevalence of 26% in our study. Published literature regarding hypertension among industrial workers, even from different time periods is scarce from Indian settings to attempt comparisons. Studies from IT industries indicate a prevalence as high as 30%. Studies from different parts of India showed a wide prevalence of hypertension ranging 20–44% among other professions such as teachers, police, and bank employees.[15–18] According to National family health survey [NFHS-5] overall prevalence of hypertension in India was 24% among males, which is similar to the prevalence rates in our study which is similar to the prevalence rates in our study. Our results are also consistent with several population-based studies in India showing the prevalence of hypertension between 26.5% and 29.8%., In a crude manner, we could opine that the prevalence observed in our study is nearly similar to the prevalence of hypertension among the adult general population. As we observed no significant association with work location, it is quite possible that hypertension prevalence among workers is a reflection of prevalence in the general population.
The incidence rate per unit exposure time is a better indication of the risk of hypertension among employees. Estimations of incidence rates provide health managers to estimate expected new cases according to dynamic changes in employee population in the industry and hence plan interventions accordingly. Our study estimated the incidence rate at 14.5 cases per 1,000 person-months of observation time in 2014. Information regarding hypertension incidence rates among workers is limited from an Indian context. A 2-year follow-up of industrial workers aged 18–50 years from the southern part of India (Kerala) estimated the incidence of hypertension at 9.0%.
Despite the higher prevalence of hypertension among employees aged 30+ years, we observed an increased risk (hazard ratios) for hypertension among employees aged 18–24 years. This is contrary to known the relationship between age and hypertension. The probable reasons could be due to the fact >95% of workers in age group 18–24 years are from production-elated departments and it is not clear if they were adequately rested before measurement. Job stress can also be a plausible risk factor for elevated BP, which is expected to be more in younger age and early years of service.,, As this is secondary data analysis, information on concomitant hypertension risks such as smoking, alcohol use, family history, physical inactivity, and salt consumption was not available in this AME database. Analyzing the role of these variables adjusted for age may provide results suggesting increased risk for hypertension in higher age groups. Nevertheless, our observations indicate a need for collecting other risk factors information in AME as well as conducting sporadic primary data-based studies to understand risks for hypertension.
A mean increase by 2 mm of Hg of SBP between 2010 and 2014 showed a prevalence increase by nearly 3.3 times in the same period. The small increase in mean blood pressure is associated with a large increase in prevalence. Hence, interventions to focus on achieving small reductions in mean blood pressure among employees, that is, attempt to shift the risk curve to the left.
Data from the Directorate of Factories in India (DGFASLI) indicate that the total employment in factories has gone up from 130 million in 2009 to 164 million in 2017. In the state of Karnataka, official statistics (on March 2021) reveal there are 21,162 registered industries employing around 16, 12, 505 workers., Assuming similar prevalence rates as in our study (26%), we expect around 403,127 industrial workers to be hypertensive in the state. If not intervened in a timely and appropriate manner, it could result in progression to other NCDs, hereby affecting health, productivity, and quality of life. The pre-hypertensive percentage increased more than double at the end of the study period as compared to baseline year and this is specifically important as studies indicate that pre-hypertension significantly increases the risk for coronary heart disease (Relative Risk (RR): 1.12, 95% CI: 1.02–1.23) and stroke mortality (RR: 1.41, 95% CI: 1.28–1.56), respectively.,,, Surveillance of AME data can identify these employees at the earliest.
Evidence from published literature, reviews, and data from periodical medical examinations indicate that in the burden of NCDs and NCD risk factors such as overweight and hypertension, is similar in proportion, if not higher than exposure-related occupational diseases such as pneumoconiosis. A review of legislative provisions for strengthening NCD care in workplaces in India was conducted by the World Health Organization (WHO) and NIMHANS in 2019. The ensuing report estimated that the prevalence of NCDs and NCD risk factors in workplaces is nearly similar to the prevalence in the general population. However, unfortunately, NCDs are not covered by existing legislation in occupational health.
In developing countries such as India, NCDs will contribute to both ill health and financial consequences, directly and indirectly. The annual income loss due to NCDs among working adults in India is estimated at 251 billion rupees with hypertension accounting for 43 billion rupees (nearly 17% of income loss due to NCDs is due to hypertension). The average monthly direct cost of care for hypertension is estimated at INR 223.2 (198.0–329.4) per person. With a 26% prevalence in a 10,000 employee industry, we expect around 2,600 hypertension cases, which would cost the industry 580,230 rupees every month and around 70,00,000 rupees every year. This direct recurring cost is avoidable and is specifically important as data suggest that India stands to lose $4.58 trillion before 2030 due to NCDs and mental health conditions. The cost of treating hypertension is expected to take a huge and rising share of healthcare resources and it is time that industries recognize hypertension as a health priority, use AME data to screen, monitor hypertension of employees, and implement healthy workplace interventions to reduce hypertension and offset the associated costs to the maximum extent possible.
This study has a few limitations. Information regarding the employees who died or quit the job due to inability to work as a result of NCDs was not maintained. This could have influenced the estimations; however, we believe this number would be negligible. Secondly, as it is a secondary data-based study, information on other risk factors for hypertension is not available.
| Conclusions and Recommendations|| |
The study observes hypertension is a key health priority among industrial workers, and a significant increase is observed in mean blood pressure levels between 2010 and 2014. Prevalence and incidence rates are on the rise. The small increase in mean blood pressure levels has resulted in large increase in prevalence and incidence rates. No significant work-location-related risks are associated with hypertension. Results provide a rational basis for implementing specific workplace programs based on AME data to reduce hypertension in the industry. AME data to be used to monitor hypertension trends among employees. We recommend building capacities of industrial medical officers to analyze, interpret, and use AME data to integrate and implement worksite health programs to reduce hypertension in industries.
The Director, Registrar - NIMHANS, Project Section, NIMHANS, Staff of Occupational health unit of the automobile industry.
List of abbreviations
NCDs: Non-communicable diseases, HTN: hypertension, HR: hazard ratio, AME: annual medical examination, BP: blood pressure, SBP: systolic blood pressure, DBP: diastolic blood pressure, CVD: cardiovascular disease, NFHS: national family health survey, ILCD: internal logistics control department.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Anchala R, Kannuri NK, Pant H, Khan H, Franco OH, Di Angelantonio E, et al
. Hypertension in India: A systematic review and meta-analysis of prevalence, awareness, and control of hypertension. J Hypertens 2014;32:1170-7.
International Institute for Population Sciences. National Family Health Survey – 5 2019-20 State Fact Sheet Karnataka.
Gautham MS, Arvind BA, Pradeep BS, Gururaj G, Deepika V, Joshi P. Strengthening Policy and Regulatory Framework for Control of Non-Communicable Diseases (NCDs) in Workplaces in India. Banglore: WHO; 2019.
Nadar SK. Spotlight on hypertension in the Indian subcontinent. J Hum Hypertens 2019;33:559-61.
Gautham MS, Arvind BA. Strengthening Policy and Regulatory Framework for Control of Non-Communicable Diseases (NCDs) in Workplaces in India. Delhi: Submitted to WHO; 2019.
Armstrong C. JNC8 guidelines for the management of hypertension in adults. Am Fam Physician 2014;90:503-4.
James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, et al
. 2014 evidence-based guideline for the management of high blood pressure in adults: Report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA 2014;311:507-20.
Babu GR, Mahapatra T, Detels R. Job stress and hypertension in younger software professionals in India. Indian J Occup Environ Med 2013;17:101-7.
] [Full text]
Ganesh Kumar S, Deivanai Sundaram N. Prevalence and risk factors of hypertension among bank employees in urban Puducherry, India. Int J Occup Environ Med 2014;5:94-100.
Ismail I, Kulkarni A, Kamble S, Rekha R, Amruth M, Borker S. Prevalence of hypertension and its risk factors among bank employees of Sullia Taluk, Karnataka. Sahel Med J 2013;16:139. [Full text]
Brahmankar TR, Prabhu PM. Prevalence and risk factors of hypertension among the bank employees of Western Maharashtra – A cross sectional study. Int J Community Med Public Health 2017;4:1267-77.
Chetia D, Gogoi G, Baruah R. Hypertension and occupational stress among high school teachers of Dibrugarh district. Int J Community Med Public Health 2017;5:206-9.
International Institute for Population Sciences (IIPS) and ICF. National Family Health Survey (NFHS-5): India. Mumbai: IIPS. 2021. p. 2019-21.
Geldsetzer P, Manne-Goehler J, Theilmann M, Davies JI, Awasthi A, Vollmer S, et al
. Diabetes and hypertension in India: A Nationally representative study of 1.3 million adults. JAMA Intern Med 2018;178:363-72.
Mini G, Sarma P, Thankappan K. Risk of progression to hypertension from prehypertension and normal blood pressure: Results from a prospective cohort study among industrial workers in Kerala, India. Heart Mind 2018;2:106-10. [Full text]
Rengganis AD, Rakhimullah AB, Garna H. The correlation between work stress and hypertension among industrial workers: A cross-sectional study. IOP Conf Ser Earth Environ Sci 2020;441:012159.
Gaur J. Occupational stress in Indians working in India and abroad. Indian J Health Well Being 2013;2:1227-9.
Rose G. Sick Individuals and sick populations. Int J Epidemiol 1985;14:32-8.
Huang Y, Su L, Cai X, Mai W, Wang S, Hu Y, et al
. Association of all-cause and cardiovascular mortality with prehypertension: A meta-analysis. Am Heart J 2014;167:160-8.e1.
Prabhakaran D, Jeemon P, Roy A. Cardiovascular diseases in India. Circulation 2016;133:1605-20.
Lawes CMM, Vander Hoorn S, Rodgers A, International Society of Hypertension. Global burden of blood-pressure-related disease, 2001. Lancet Lond Engl 2008;371:1513-8.
Gautham MS Ningappa K, Gururaj G. Screening for Mental Health and Non-Communicable Disease Risk Among Employees in Dalmia Cement (Bharat) Limited, Belagavi, 2016.
Mohan S, Campbell N, Chockalingam A. Time to effectively address hypertension in India. Indian J Med Res 2013;137:627-31.
] [Full text]
Kar SS, Kalidoss VK, Vasudevan U, Goenka S. Cost of care for hypertension in a selected health center of urban Puducherry: An exploratory cost-of-illness study. Int J Non-Commun Dis 2018;3:98-103. [Full text]
[Table 1], [Table 2], [Table 3]