|Year : 2018 | Volume
| Issue : 1 | Page : 12-19
Study of metabolic syndrome among health professionals in a rural eastern Indian population and its relation with quality of life
Arpan K Ghosh1, Arunima Chaudhuri1, Asha Kahar2, Debasis Adhya1
1 Department of Physiology, Burdwan Medical College and Hospital, Burdwan, West Bengal, India
2 College of Medicine and JNM Hospital, WBUHS, Kalyani, West Bengal, India
|Date of Submission||03-Jan-2018|
|Date of Decision||25-Mar-2018|
|Date of Acceptance||05-Apr-2018|
|Date of Web Publication||13-Mar-2020|
Dr. Arunima Chaudhuri
Krishnasayar South, Borehat, Burdwan 713102, West Bengal
Source of Support: None, Conflict of Interest: None
Background The increasing prevalence of metabolic syndrome (MetS) is a challenging threat for the 21st century.
Aims To assess the prevalence of MetS and find out the relation with the quality of life among health professionals in a population of eastern India.
Materials and Methods This study was conducted in a time span of 1 year among the various categories of 300 health professionals working at Burdwan Medical College and Hospital after taking institutional ethical clearance and informed consent from the participants. The presence of at least three out of five components of MetS was used for diagnosis. Data collection methodology was based on WHO STEP-wise approach using questionnaire, physical, and biochemical measurements.
Results MetS was found among 131 participants (43.7%). Among the participants with MetS, there were 71 (54.2%) doctors, 32 (24.4%) nurses, 16 (12.2%) paramedics, and 12 (9.2%) other health professionals. But there was no significant difference in prevalence among the categories of profession. MetS was diagnosed more among females compared to males (53.8% vs. 34.2%, χ2 = 11.699, P < 0.001). Females were twice as likely to develop MetS compared to males (odds ratio 2.24, confidence interval 1.40–3.57, P < 0.001). Among the various components of MetS within the study population, increased waist circumference (58.7%) had the highest prevalence, followed by low high-density lipoprotein cholesterol (48.3%), high blood pressure (46.3%), increased blood glucose (39.7%), and hypertriglyceridemia (35.3%).
Conclusions The present study highlighted the high prevalence of MetS among health professionals with a female preponderance. MetS was associated with the poor quality of life, especially the domains of physical health, psychological health, and social relationships.
Keywords: Health professionals, metabolic syndrome, quality of life
|How to cite this article:|
Ghosh AK, Chaudhuri A, Kahar A, Adhya D. Study of metabolic syndrome among health professionals in a rural eastern Indian population and its relation with quality of life. Saudi J Obesity 2018;6:12-9
|How to cite this URL:|
Ghosh AK, Chaudhuri A, Kahar A, Adhya D. Study of metabolic syndrome among health professionals in a rural eastern Indian population and its relation with quality of life. Saudi J Obesity [serial online] 2018 [cited 2020 Dec 2];6:12-9. Available from: https://www.saudijobesity.com/text.asp?2018/6/1/12/280265
| Introduction|| |
The rapid rise of noncommunicable diseases (NCDs) is presenting a formidable challenge in the 21st century which is threatening the economic and social development of the world. NCDs currently cause 68% deaths globally, more than all other causes combined. NCD deaths are projected to increase from 38 million in 2012 to 52 million by 2030. Four major NCDs [cardiovascular diseases (CVDs) (46%), cancer, chronic respiratory diseases and diabetes] are responsible for 82% of NCD deaths. In India, NCDs are estimated to account for 60% of total deaths and 26% of premature deaths between age 30 and 70 years.
Asian Indians have long been considered to be a “high-risk population” for both metabolic syndrome (MetS) and CVD. The prevalence of MetS in South Asians varies according to region, extent of urbanization, lifestyle patterns, and socioeconomic/cultural factors. In India, studies have reported prevalence varying from 24.9% in northern India to 41% in southern India using different definitions., Recent data show that about one-third of the urban population in large cities in India have MetS.
A dose-response association exists between exposure to work stress and the MetS. Employees with chronic work stress have more than double the odds of the syndrome than those without work stress, after other risk factors are taken into account. Health professionals are an important population subgroup, because they are committed to health promotion and prevention, or treatment of diseases, which affect not only their own health but also communities, families, and individuals with which they work. The present study was conducted to assess the prevalence of MetS and its components and associated sociodemographic variables among health professionals and to find out the relation of MetS with the quality of life in a rural population of eastern India.
| Materials and methods|| |
The present study was conducted among various categories of three hundred health professionals working at Burdwan Medical College and Hospital during 2015–2017 after taking institutional ethical clearance and informed consent from the participants.
The following formula is used to calculate the sample size:
where, n = sample size; Z═Z statistic for a level of confidence; p = expected prevalence or proportion; and d = precision.
Calculated sample size was 262 considering MetS prevalence of 43.2% in eastern India, taking 6% of absolute precision and Z = 1.96 at level of confidence of 95%. To compensate for the nonresponse of 10%, the sample size was 288. Finally, we approached and included 300 health professionals for the study.
- Health professionals of age 25–65 years;
- Both genders;
- Those who voluntarily consented to participate.
- Women who were pregnant;
- Individuals using long-term steroids or under therapy for cancer;
- Participants who were seriously ill;
- Those who did not give consent.
Procedure of data collection
Data collection methodology was based on WHO STEP-wise approach to surveillance (STEPS) of major NCD risk factors. The generic STEPS Instrument covers three sequential phases or “steps” of risk factor assessment: step 1 (questionnaire-based assessment), step 2 (physical measurements), and step 3 (biochemical measurements).
Each participant was required to fill up a self-report questionnaire and physical measurements were performed after that. Fasting blood samples were collected on scheduled days and sent for analysis.
Prevalidated and pretested self-report structured questionnaire was used for the collection of information on different items. The data collection sheet was divided into nine parts.
It included anthropometric measurements such as height, weight, and waist circumference along with the clinical measurement of blood pressure (BP). Anthropometric measurements were performed according to the techniques recommended by WHO. Blood pressure was measured using mercury sphygmomanometer as per guidelines by WHO and the seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7).
This included collection of blood under fasting condition and analysis to measure fasting plasma glucose, serum high-density lipoprotein cholesterol (HDL), and serum triglycerides levels.
Definition of study outcome
Defining MetS: Diagnostic criteria laid down in “Harmonizing the Metabolic Syndrome” − a joint interim statement of the International Diabetes Federation (IDF), National Heart Lung and Blood Institute (NHLBI), American Heart Association (AHA), World Heart Federation (WHF), International Atherosclerosis Society; and the International Association for the Study of Obesity criteria, with three abnormal findings out of five measures (abdominal obesity, increased blood pressure, hypertriglyceridemia, low HDL cholesterol, and increased blood glucose level) were used for the clinical diagnosis of MetS.
Measurement of quality of life
The WHOQOL-BREF is a 26-item instrument consisting of two items about an individual’s overall perception of Quality of Life and General Health and 24 items of satisfaction divided into four domains: physical health with seven items (domain 1), psychological health with six items (domain 2), social relationships with three items (domain 3), and environmental health with eight items (domain 4).
Scoring of the WHOQOL-BREF
Each individual item of the WHOQOL-BREF is scored from 1 to 5 on a five-point Likert scale. Except for three negatively worded items, a low rating toward 1 suggests a negative evaluation and a high rating toward 5 indicates a more positive perception of QOL. The mean score of items within each domain is used to calculate the domain score. Domain scores are scaled in a positive direction (i.e., higher scores denote the higher quality of life). There are also two items that are examined separately (question 1 asks about the overall perception of QoL and question 2 asks about the overall perception of health). WHOQOL-BREF domain scores are then transformed to a 0–100 scale. These transformed scores should be used when interpreting the data to ease comparisons to other validated instrument tools.
Raw scores for each domain were calculated manually and conversion of raw scores to transformed scores (on a 0–100 scale) was performed. For the transformation of the raw scores of the two global items (Q1 and Q2), the following formula was used:
Data management and statistical analyses: The computer software “Statistical Package for the Social Sciences version 16.0 for Windows (released 2007, SPSS Inc., Chicago)” was used to analyze the data; *P < 0.05 was considered as statistically significant; and **P < 0.01 was considered as statistically highly significant.(SPSS)
| Results|| |
A total of 300 health professionals were included in the present study, among them 146 (48.7%) doctors, 76 (25.3%) nurses, 41 (13.7) paramedical professionals, and 37 (12.3%) other health professionals participated in the study. Out of 300 respondents, 151 (51.7%) were male and 145 (48.3%) were female. Among doctors, 69.9% were male and among nurses all (100%) were female. The mean age of the study population was 44.9 ± 9.5 years. On the basis of marital status, most of them were married (253, 84.3%), 9 (3%) divorced/separated, and 38 (12.7%) were unmarried. On examining their duration of work/job life, 107 (35.7%) were working for <10 years, 108 (36%) for 10–19 years, and remaining 85 (28.3%) were in job for 20 or more years. On examining their working schedule, 62 (20.7%) were working in day shifts, 123 (41%) in rotating shifts, and 115 (38.3%) were working as on call (irregular shift). Most of the doctors (63%) were found working in irregular shifts and most of the nursing professionals (68.4%) were working in rotating shifts.
Out of 300 respondents, 64 (21.3%) were current smokers. Smoking was significantly higher among males (41.3%, P < 0.001). All female participants were nonsmokers. Most of the health professionals had never or occasionally used alcoholic drinks (289, 96.3%). Only 11 (3.7%) used alcoholic drinks regularly, that also was more among males compared to females (P < 0.05). Thirty minutes or more of daily moderate amount of physical activity was performed by 61.3% health professionals compared to 38.7% whose daily physical activity duration did not reach 30 min. But there was no significant difference between males and females. 48.3% of the study population was found to be sitting or reclining for more than 4 h a day and this trend was significantly higher among females (61.4% vs. 36.1%, P < 0.001) [Table 1].
|Table 1 Percentage distribution of participants according to behavioral characteristics to gender|
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MetS was found among 131 participants (43.7%). Among the participants with MetS, there were 71 (54.2) doctors, 32 (24.4%) nurses, 16 (12.2%) paramedics, and 12 (9.2%) other health professionals. There was no significant difference in prevalence among the categories of profession. The prevalence of MetS among doctors, nurses, paramedics, and other health professionals was 48.6, 42.1, 39.0, and 32.4%, respectively. MetS was diagnosed more among females compared to males (53.8% vs. 34.2%, χ2 = 11.699, P < 0.001). Females were twice as likely to develop MetS compared to males [odds ratio (OR) 2.24, confidence interval (CI) 1.40–3.57, P < 0.001]. Married and divorced or widowed had a higher percentage of MetS (47.4 and 44.4%) compared to unmarried (18.4%) and that was statistically significant (χ2 = 11.305, P < 0.05). The prevalence of MetS among participants residing in home, staff quarter, and hostel was 49.8, 45.0, and 28.6%, respectively. Among the various components of MetS within the study population, increased waist circumference (58.7%) had the highest prevalence, followed by low HDL cholesterol (48.3%), high blood pressure (46.3%), increased blood glucose (39.7%), and hypertriglyceridemia (35.3%) [Table 2].
|Table 2 Descriptive statistics showing the distribution of different components of metabolic syndrome in respect of gender|
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The mean waist circumferences for female participants (84.68 ± 5.749 cm) and male participants (90.15 ± 7.318 cm) were above the cut-off values for abdominal obesity. The mean WC among participants with MetS was 91.37 ± 7.152 cm and for those without MetS was 84.51 ± 5.526 cm (t = 9.361, P < 0.001). The value for non-MetS was above the WC cut-off for females. The prevalence of longer waist circumference was higher among women compared to men (60.8% vs. 39.2%, P < 0.01). Similar significantly higher prevalence in women compared to men was also seen with hyperglycemia (59.7% vs. 40.3%) and low HDL level (61.4% vs. 38.6%). The prevalence of MetS increased significantly with increase in duration of work-life (χ2 = 47.801, P < 0.001). MetS was diagnosed in 18.7% of participants working for <10 years, 50% among those working for 10–19 years, and 67.1% among participants with work-life of 20 or more years. The prevalence of MetS was more among those with job life interfering family life with participants opting for always (100%), often (68.1%), and sometimes (42%) compared to those opting for rarely (15.8%) or never. This difference was statistically significant (χ2 = 40.899, P < 0.001). For the question asking how often the participants find their work stressful, 92.3% answering “always” and 72.3% opting “often” were found to have MetS compared to those opting “sometimes” (31.9%) and hardly ever (8%) or never (0%) and this difference was highly significant (P < 0.001). Regarding the level of job satisfaction, health professionals who are “very satisfied” or “somewhat satisfied” had lesser prevalence of MetS (14.3 and 3.8%, respectively) compared to those who are “somewhat dissatisfied” or “not at all satisfied” (85.1 and 94.7%, respectively). MetS was found in 28.7% individuals who are neither satisfied nor dissatisfied with their job. The distribution was found to be significant at χ2 = 148.454 and P < 0.001 [Table 3].
|Table 3 Descriptive statistics showing the distribution of different work-life characteristics in participants with and without metabolic syndrome|
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MetS was found to be more prevalent among smokers compared to nonsmokers (70.3% vs. 36.4%, χ2 = 23.482, P < 0.001). Smokers were four times more susceptible to develop MetS (OR 4.13, CI 2.27–7.51, P < 0.001). Among alcohol users, MetS was found among 63.6% of regular users and 42.9% of occasional or nonusers but the difference was insignificant. MetS was less prevalent among those who consumed 25 g (6 teaspoons) or less added sugar per day compared to those consuming more than 25 g (32.8% vs. 78.9%, χ2 = 46.868, P < 0.001). MetS was found significantly higher among individuals with daily added salt consumption more than 5–6 g (69.1%) compared to those consuming less (17.6%). Low salt consumption reduces the risk by 10-fold (OR 0.10, CI 0.06–0.16, P < 0.001). Persons consuming less fruits and vegetable (<3 cups per day) had a prevalence of MetS at 95.3% compared to those consuming more than three cups (29.7%) and this difference was highly significant at χ2 = 88.215 and P < 0.01. Those consuming three or more meals per week that were not prepared at home had 36.2% prevalence of MetS compared to those consuming less (45.1%) but the difference was not statistically significant (P = 0.259). Health professionals involved in 30 or more minutes of daily physical activity of moderate intensity had less MetS (22.3%) than those doing less physical activity (77.6% MetS). Physical activity <30 min per day increases the risk by 12-fold (OR 12.07, P < 0.001). MetS was also more prevalent among those sitting or reclining more than 4 h (77.2% vs. 22.8%). The longer duration of sitting time increases the risk many times (P < 0.001) [Table 4].
|Table 4 Descriptive statistics showing the distribution of health professionals with and without metabolic syndrome in respect of different behavioral factors|
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The overall quality of life and general health scores are significantly lower among participants with MetS (P < 0.001). Within the domain scores, the physical health, psychological health, and Social relationship scores are also lower among participants with MetS and the difference was highly significant (P < 0.001) [Table 5].
|Table 5 Descriptive statistics showing the comparison of mean scores of domain of WHOQOL-BREF between participants with and without metabolic syndrome|
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| Discussion|| |
The present study described the epidemiological factors of MetS and its relation with the quality of life among health professionals working in a particular medical college in West Bengal. The overall prevalence of MetS was 43.7%. Our study finding was very similar to studies conducted in India by Kanjilal et al. (40.3%), Kaur et al. in Chennai (41.3–51.4%), Prasad et al. in Orissa (43.2%) and others using similar criteria for MetS and lower cut-offs for waist circumference. Studies from Bangladesh, Pakistan, and other South Asian countries reported similar high prevalence of MetS. In the NHANES 1999–2000 study, increase in waist circumference predominate among women, whereas increase in fasting plasma triglyceride levels and hyperglycemia were more likely in men. In a study in Bangladesh, low-plasma HDL level was found to be the most common abnormality and elevated waist circumference was the least frequent component. In a study in South African Indian individuals with MetS, elevated fasting blood glucose was found to be the most frequently occurring criterion.MetS was found more among those whose job life often or always interfered with their family life. The higher prevalence of MetS was also noted among health professionals who felt their work stressful. A large body of literature suggests that psychosocial attributes and stressful events predict occurrence of CVD, T2DM, and MetS.,,
Persons consuming less fruits and vegetable (<3 cups per day) had a higher prevalence of MetS at 95.3% compared to those consuming more (29.7%). The consumption of three or more cups of fruits and vegetables daily was highly protective. In a study in Chennai, the consumption of more than three servings of fruits and vegetables was protective. One of the most important and modifiable risk factors is unhealthy diet. Foods high in fats, sugars, and salt have been associated with earlier onset of MetS and CVDs. MetS was diagnosed more among persons doing <30 min of physical activity per day compared to the other group (77.6% vs. 22.3%). Lower engagement in physical activity increases the risk multiple folds compared to those doing ≥30 min of daily moderate level physical activity. The beneficial association of physical activity with the MetS found in this study is similar to the findings from other population groups in both developed and developing countries. In a study by Ford et al. from NHANES 1999–2000, participants who did not engage in any moderate or vigorous physical activity had almost twice the odds of having MetS as those who reportedly engaged in ≥150 min/week of such activity. Compared to their counterparts doing the least physical activity, the lower odds of the MetS were observed among Omani adults with higher physical activity at work and during transport.
In an Iranian study using WHOQOL-BREF, after adjusting the role of sociodemographic factors as components of QoL score, no association was observed between QoL domains and MetS in men, whereas significant difference was observed between women with and without Mets in regard to physical health and social relations domains. Intervention on MetS resulted in change in the metabolic parameters along with improvement in QOL measures.
The present study highlighted the high prevalence of MetS among health professionals with a female preponderance. MetS was associated with the poor quality of life, especially the domains of physical health, psychological health, and social relationships.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organization. Global Health Estimates: Deaths by Cause, Age, Sex and Country, 2000–2012. Geneva: World Health Organization 2014.
World Health Organization. Noncommunicable Diseases (NCD) Country Profiles, 2014. Geneva: World Health Organization 2014.
Misra A, Misra R, Wijesuriya M, Banerjee D. The metabolic syndrome in South Asians: Continuing escalation and possible solutions. Indian J Med Res 2007;125:345-54.
] [Full text]
Ramachandran A, Snehalatha C, Satyavani K, Sivasankari S, Vijay V. The metabolic syndrome in urban Asian Indian adults − A population study using modified ATP III criteria. Diabetes Res Clin Pract 2003;60:199-204.
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.
Chandola T, Brunner E, Marmot M. Chronic stress at work and the metabolic syndrome: Prospective study. BMJ 2006;332:521-5.
International Standard Classification of Occupations. Structure, Group Definitions and Correspondence Tables: ISCO-08, vol. 1. Geneva: International Labour Office, International Labour Organization; 2012. p. 1-433. Available from: www.ilo.org/public/english/bureau/stat/isco/isco08/index.htm
. [Last accessed on 2016 Jul 21].
WHO Noncommunicable Diseases and Mental Health. STEPS: A Framework for Surveillance. The WHO STEPwise Approach to Surveillance of Noncommunicable Disease. (STEPS). Geneva: World Health Organization 2003.
Prasad DS, Kabir Z, Dash AK, Das BC. Prevalence and risk factors for metabolic syndrome in Asian Indians: A community study from urban eastern India. J Cardiovasc Dis Res 2012;3:204-11. [Full text]
World Health Organization. WHO STEPS Surveillance Manual: The WHO STEPwise Approach to Noncommunicable Disease Risk Factor Surveillance. Geneva: World Health Organization 2017.
National High Blood Pressure Education Program. The Seventh Report of the Joint National Committee (JNC7) on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. United States: National Institutes of Health (NIH), National Heart, Lung, and Blood Institute (NHLBI); 2004.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA et al.
Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120:1640-5.
The WHOQOL Group. Programme on Mental Health. WHOQOL-BREF Introduction, Administration, Scoring and Generic Version of the Assessment. Field Trial Version. Geneva: The World Health Organization 1996.
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.
Kaur P, Radhakrishnan E, Rao SR, Sankarasubbaiyan S, Rao TV, Gupte MD. The metabolic syndrome and associated risk factors in an urban industrial male population in South India. J Assoc Physicians India 2010;58:363-71.
Jesmin S, Islam MR, Islam AM, Mia MS, Sultana SN, Zaedi S et al.
Comprehensive assessment of metabolic syndrome among rural Bangladeshi women. BMC Public Health 2012;12:49.
Ranasinghe P, Mathangasinghe Y, Jayawardena R, Hills AP, Misra A. Prevalence and trends of metabolic syndrome among adults in the Asia-Pacific region: A systematic review. BMC Public Health 2017;17:101.
Mozumdar A, Liguori G. Persistent increase of prevalence of metabolic syndrome among US adults: NHANES III to NHANES 1999–2006. Diabetes Care 2011;34:216-9.
Ranjith N, Pegoraro RJ, Naidoo DP, Shanmugam R, Rom L. Genetic variants associated with insulin resistance and metabolic syndrome in young Asian Indians with myocardial infarction. Metab Syndr Relat Disord 2008;6:209-14.
Wasir JS, Misra A. The metabolic syndrome in Asian Indians: The impact of nutritional and socio-economic transition in India. Metab Syndr Relat Disord 2004;2:14-23.
Vitaliano P, Scanlan JM, Zhang J, Savage MV, Hirsh IB, Siegler IC. A path model of chronic stress, the metabolic syndrome, and coronary heart disease. Psychosom Med 2002;64:418-35.
Pyykkönen AJ, Räikkönen K, Tuomi T, Eriksson JG, Groop L, Isomaa B. Stressful life events and the metabolic syndrome: The prevalence, prediction and prevention of diabetes (PPP) − Botnia Study. Diabetes Care 2010;33:378-84.
Singh PN, Arthur KN, Orlich MJ, James W, Purty A, Job JS et al.
Global epidemiology of obesity, vegetarian dietary patterns, and noncommunicable disease in Asian Indians. Am J Clin Nutr 2014;100:359-64S.
Gopalan C. The changing nutrition scenario. Indian J Med Res 2013;138:392-7.
] [Full text]
Ford ES, Kohl HW 3rd, Mokdad AH, Ajani UA. Sedentary behavior, physical activity, and the metabolic syndrome among U.S. adults. Obes Res 2005;13:608-14.
Mabry RM, Winkler EA, Reeves MM, Eakin EG, Owen N. Associations of physical activity and sitting time with the metabolic syndrome among Omani adults. Obesity 2012;20:2290-5.
Sarrafzadegan N, Gharipour M, Ramezani MA, Rabiei K, Zolfaghar B, Tavassoli A et al.
Metabolic syndrome and health-related quality of life in Iranian population. J Res Med Sci 2011;16:254-61.
Saboya PP, Bodanese LC, Zimmermann PR, Gustavo AS, Macagnan FE, Feoli AP et al.
Lifestyle intervention on metabolic syndrome and its impact on quality of life: A randomized controlled trial. Arq Bras Cardiol 2017;108:60-9.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]