Journal of Preventive Medicine And Care

Journal of Preventive Medicine And Care

Journal of Preventive Medicine and Care

Current Issue Volume No: 3 Issue No: 2

Research Article Open Access Available online freely Peer Reviewed Citation

Prevalence and Risk Factors of Metabolic Syndrome Among Teaching Staff of Engineering Colleges in Central India

Sanjay Agrawal 1,   Sanjeev M. Chaudhary 2,   Sanjay S. Kubde 3,   Manjusha Dhoble 4,   Moin Shaikh 5  

1Assistant Professor cum Statistician, Department of Community Medicine, Indira Gandhi Government Medical College, Nagpur

2Associate Professor, Department of Community Medicine, Government Medical College, Akola.

3Professsor, Department of Community Medicine, Government Medical College, Nagpur

4Assistant Professor, Department of Community Medicine, Indira Gandhi Government Medical College, Nagpur

5Medical Officer, Maharashtra Medical and Health Services

Abstract

Background

Prevalence of Metabolic syndrome is high among Asians including Indians, and is high among those having sedentary occupations. Teaching is one of the important occupations, which demands no strenuous physical activity. However, there is little information available about the prevalence of metabolic syndrome among teaching staff of engineering college. Hence, the present study was conducted to study its prevalence, certain risk factors and co-morbidities among teaching staff of engineering institutes.

Methods

Teachers from engineering colleges of Nagpur city were the study subjects. Data was collected by interview technique. Clinical examination and laboratory investigations like Fasting blood glucose, High Density Lipoproteins and Serum Triglycerides were done. National Cholesterol Evaluation Programme (NCEP) Adult Treatment Panel Three (ATPIII) criteria were used to study Metabolic syndrome. Blood pressure and anthropometric measurements like height, weight and waist circumference were obtained by standard methods.

Results

The prevalence of metabolic syndrome was found to be 20.5%. It was 25.32% in females and 19.31% in males. It was more common in subjects of higher age group, muslim religion, and among widows and separated. Alcohol consumption, smoking and sedentary life style was found to be significantly associated with presence of metabolic syndrome. Frozen shoulder, fungal infection and stroke were common co morbidities found among subjects having metabolic syndrome.

Author Contributions
Received 21 Dec 2020; Accepted 23 Dec 2020; Published 25 Dec 2020;

Academic Editor: Khuram SHAHZAD, Department of Polymer Engineering and Technology, University of the Punjab, Lahore, 54590 Pakistan.

Checked for plagiarism: Yes

Review by: Single-blind

Copyright ©  2020 Sanjay Agrawal, et al.

License
Creative Commons License     This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Competing interests

The authors have declared that no competing interests exist.

Citation:

Sanjay Agrawal, Sanjeev M. Chaudhary, Sanjay S. Kubde, Manjusha Dhoble, Moin Shaikh (2020) Prevalence and Risk Factors of Metabolic Syndrome Among Teaching Staff of Engineering Colleges in Central India. Journal of Preventive Medicine And Care - 3(2):8-16. https://doi.org/10.14302/issn.2474-3585.jpmc-20-3672

Download as RIS, BibTeX, Text (Include abstract )

DOI 10.14302/issn.2474-3585.jpmc-20-3672

Introduction

The rapid rise of non communicable diseases (NCDs) is presenting a challenge in twenty-first century which is threatening economic and social development of the world as well as the lives and health of millions across the globe. As many countries are struggling to control infectious diseases, they are facing an explosion in chronic diseases- a situation for which they have neither the resources and personnel, nor the health service infrastructure required to respond effectively. Of the 57 million deaths that occurred globally in 2008, 36 million – almost two thirds – were due to NCDs, comprising mainly cardiovascular diseases, cancers, diabetes and chronic lung diseases. Especially in developing countries, the burden of chronic diseases is increasing rapidly and will have significant social, economic, and health consequences in the coming years.

India is also undergoing rapid urbanization with increased industrialization, rising incomes, expanded education and improved health care. There is increase in smoking habits, an unhealthy diet, physical inactivity and adoption of other unhealthy lifestyles leading to rise in prevalence of non communicable diseases. On the other hand, modern medical care is now enabling many with chronic diseases to survive. The impact of chronic diseases on the lives of people is serious when measured in terms of years of loss of life, disablement, family hardship, poverty and economic loss to the country.

Metabolic syndrome , which is also known as “Syndrome X,” was first described by Reaven in his 1988 Bantin Lecture1. It is characterized by clustering of cardiovascular risk factors, namely central obesity, elevated blood pressure, elevated plasma glucose, and dyslipidemia.It is increasingly attracting the attention of international research institutions and scientific societies, as a major modifiable determinant of cardiovascular disease and type 2 diabetes. There are various definitions proposed for the metabolic syndrome. National Cholesterol Education Program – Adult Treatment Panel III (NCEP-ATP III)2 and the American Heart Association (AHA)/ National Heart Lung and Blood Institute (NHLBI)3 defined the Metabolic syndrome as presence of any three out of the five components namely central obesity, raised triglycerides, low HDL, raised plasma glucose and raised blood pressure. On the other hand, the International Diabetes Federation (IDF)4 definition includes central obesity as an essential component of the Metabolic syndrome in addition to any two of the four above-mentioned components.

Prevalence of Metabolic syndrome is high among Asians including Indians and is rising particularly with the adoption of modernized lifestyle. Many studies in India have reported high prevalence of Metabolic syndrome in a range of 9–48%.5 But there are limited data on comparison of the Metabolic syndrome criteria in the same study population to assess the strengths and limitations of the proposed criteria in the context of South Asian ethnicity. Teaching is one of the important occupations, which demands no strenuous physical activity. Teaching staff is usually sedentary. It was observed in many studies that the metabolic syndrome and cardiovascular diseases are rising in sedentary population. However, there is little information available about the prevalence of metabolic syndrome among teaching staff of engineering college. Hence, the present study was conducted to study its prevalence, certain risk factors and co-morbidities among teaching staff of engineering institutes.

Material and Methods

The present cross sectional study was carried out among teaching staff of engineering colleges in central part of Nagpur city. Four engineering colleges were selected randomly from the list of engineering colleges of Nagpur. Institutional ethics committee’s clearance was sought before the start of study. The necessary permission was obtained from the Principal of each engineering college for conducting the present study. Study subjects were explained regarding objective and nature of study, and their consent was sought before data collection. Members of the physical education department of engineering college co-operated in conducting the study. They made necessary arrangements to carry out the physical examination and facilitated the interviewing of study subjects.

The list of teaching staff was obtained from college authority. A time schedule was prepared for study subjects so that they could participate in the study conveniently. All individuals who participated in this project received a verbal explanation of the procedures involved and the benefits expected from the study. All respondents were asked to sign an informed consent form prior to the commencement of the study. Anonymity of the study subjects and confidentiality of all the data was assured during the process of data collection and it was explained that all results would be reported as a group data so that no individual could be identified.

Those study subjects who could not be examined due to absence on the day of data collection were called at Urban Health Training Centre for examination and laboratory investigations. The pilot study was done on 100 participants. The pilot study was carried out to check the feasibility and to test the proforma. Necessary changes were made in the proforma after pilot study. The pretested structured questionnaire was used for collection of data. Data was collected by interview technique. Clinical examination and necessary laboratory investigations were done. National Cholesterol Evaluation Programme (NCEP) Adult Treatment Panel Three (ATPIII) criteria were used to study Metabolic syndrome. Physical activity assessed by usingjoint FAO/WHO expert consultation, Rome, Oct.2001. Blood pressure and anthropometric measurements like height, weight and waist circumference were obtained by standard methods. After an overnight fasting, blood samples for High Density Lipoproteins and Serum Triglycerides were taken. Five milliliters of venous blood was taken from the ante- cubital fossa with all aseptic precautions and placed in empty sterile tubes. The samples were transported to the Biochemistry laboratory of the Medical College, for analysis within a day, using an automated ARCHITECT c8000 machine. Fasting blood sugar was measured by using Accu-check glucometer.

Data Analysis

Epi info version 7, open Epi info and Statcal were used to analyze the data. Chi square tests were used to examine differences in responses among the demographic variables, risk factors and knowledge on a number of variables.

Sample Size

Assuming prevalence of 0.5, confidence level of 90% and relative error of 10%, sample size (n) was estimated as n =Z2(1-α) 2×p× (1-p)/ d2=3.84×0.5×0.5/(0.05) 2=384

A total of 152, 128, 77 and 43 teachers of the four engineering institutes were included in our study, which made the total sample of 400.

Results

Out of a total of 400 teachers, 321(80.25%) were males and 79 (19.75%) were females. As seen in Table 1, majority of the subjects were of over 40 years of age, maximum study subjects belonged to Hindu religion, were from nuclear family, were married and consumed a mixed diet. Around 7% subjects had diabetes mellitus, and similar number of subjects had hypertension. Maximum subjects were doing moderate physical activity. BMI of around half of the study subjects was found to be in normal range.

Table 1. Demographic characteristics of study subjects
  Male (n=321) Female(n=79)
  No. Percent No. Percent
Age group (years)        
<30 6 1.87 2 2.53
31—40 99 30.84 24 30.38
41-50 143 44.55 31 39.24
51-60 73 22.74 22 27.85
Religion        
Hindu 199 62.00 39 49.37
Muslim 62 19.31 16 20.25
Buddha 29 9.03 17 21.52
Others 31 9.66 7 8.86
Marital status        
Married 287 89.40 70 88.60
Unmarried 12 3.74 1 1.27
Widowed 10 3.12 8 10.13
Divorced 12 3.74 0 0
Type of family        
Nuclear 238 74.14 59 74.68
Joint 71 21.12 14 17.72
Three Generation 12 3.74 6 7.59
Type of diet        
Vegetarian 60 18.69 31 39.24
Mixed 261 81.31 48 60.76
History of past illness        
DM 23 7.17 6 7.59
HT 24 7.48 8 10.1
MI 13 4.05 3 3.8
Family history        
DM 35 10.9 9 11.4
HT 32 9.97 10 12.7
Obesity 18 5.61 4 5.06
MI 13 4.05 1 1.27
Stroke 4 1.25 0 0
Physical Activity        
Sedentary 63 19.6 24 30.4
Moderate 222 69.2 53 67.1
Vigorous 36 11.2 2 2.53
BMI        
<18.5 (underwt.) 1 0.31 0 0
18.5-22.9 (normal) 169 52.6 45 57
23-27.49 (overwt.) 117 36.4 21 26.6
≥27.5 (obese) 34 10.6 13 16.5

(Table 2) shows mean and standard deviation of different components of metabolic syndrome among the subjects. Except triglycerides, mean of all the parameters was more among males as compared to females, though the difference was statistically not significant. In contrast, prevalence of individual component of metabolic syndrome was higher in females, for all components except high density lipoprotein (Table 3).

Table 2. Mean and standard deviation of individual component of metabolic syndrome
Component of Metabolic syndrome Malen=321 Femalen =79 Total(n=400)
Waist circumference (cm) 85.50±5.07 81.02±5.72 84.61±5.49
Systolic BP (mmHg) 124.06±10.96 123.99±11.73 124.05±10.50
Diastolic BP(mmHg) 83.21±50.66 80.30±5.62 82.63±45.45
Blood glucose (mg/dl) 92.92±30.77 91.57±37.26 92.64±30.83
Triglycerides≥150mg/dl 140.03±11.98 141.94±14.34 140.4±12.4
High Density Lipoproteins(mg/dl) 51.43±9.20 44.81±8.16 51.12±9.3

• Mean + SD
Table 3. Prevalence of individual component of metabolic syndrome
Component of Metabolic syndrome Malen=321 No.(%) Femalen=79 No.(%) Totaln=400 No.(%)
Waist circumference ≥cut off 45(14.01) 44(55.70) 89(22.25)
Elevated blood pressure+ Known cases 71(22.11) 23(29.11) 94(23.25)
Elevated blood glucose level + known cases 78(24.30) 25(31.64) 103(25.75)
Triglycerides≥150 mg/dl 40(12.46) 17(21.51) 57(14.25)
HDL≤ Cut off 76(23.67) 18(22.78) 94(23.5)

Majority of the study subjects i.e. 41 (10.25%) were having 3 components of Metabolic Syndrome at a time, followed by 30 (7.5%) subjects who were having 4 components. Eleven subjects (2.75%) were having 5 components of Metabolic Syndrome at a time (Table 4).

Table 4. Number of components of metabolic syndrome
No. of componentsof Metabolic Syndrome* Male Female Total
No. % No. % No. %
None 226 70.40 50 63.29 276 69.00
1 24 7.47 2 2.54 26 6.50
2 10 3.12 6 7.59 16 4.00
3 30 9.35 11 13.92 41 10.25
4 23 7.17 7 8.86 30 7.50
5 8 2.49 3 3.80 11 2.75
Total 321 100 79 100 400 100

Study subjects having 3 and more than 3 components of Metabolic syndrome constituted 82 (20.5%). So the prevalence of metabolic syndrome was found to be 20.5%. In present study, as seen in Table 5, metabolic syndrome was found to be significantly associated with advanced age, married status, alcohol abuse, smoking and physical inactivity.

Table 5. Factors associated with metabolic syndrome
Factors Metabolic syndrome Chi square value
  Present (n=82) Absent (n=318)  
Age>40 years 69 (84.15) 200 (62.89) 13.3*
Sex- male 61 (74.39) 260 (81.76) 2.34**
Religion- Hindu 50 (60.98) 188 (59.12) 0.09**
Marital status- married 66 (80.49) 291 (91.51) 8.25*
Alcohol abuse 13 (15.85) 22 (6.92) 6.51*
Smoking 26 (31.71) 43 (13.5) 15.1*
Mixed Diet 67 (81.71) 242 (72.6) 1.16**
No Physical activity 44 (53.66) 231 (72.6) 10.9*

* df=1, p<0.05, significant
** df=1, p≥0.05, non significant

Metabolic syndrome is a condition which causes biochemical changes in body making person prone to different kinds of diseases. These include life threatening diseases like myocardial infarction, stroke, etc., and lifelong diseases like diabetes mellitus, obesity, hypertension and their related complications. In the present study, common co-morbidities associated with Metabolic syndrome found were fungal infection, frozen shoulder, stroke, cataract and myocardial infarction (Table 6).

Table 6. Co-morbidities associated with metabolic syndrome
Co-Morbidity Metabolic Syndrome
Yes No Total
No (%) No (%) No (%)
Fungal infection 21 (75.00) 7 (25.00) 28(100)
Frozen Shoulder 16 (76.19) 5 (23.81) 21(100)
Cataract 12 (63.16) 7 (36.84) 19(100)
Myocardial Infarction 10 (62.5) 6 (37.50) 16(100)
Stroke 3 (75.00) 1 (25.00) 4 (100)

Discussion

The prevalence found in our study was lower than that reported by Mishra et al (30%)6 and Sarkar S et al (30%)7, while it was higher than that reported by Gang Hu et al (15%)8, Gupta et al9 (13%) and Kamble P et al (17.3%)10. The finding that prevalence of Metabolic syndrome was higher in females as compared to males, is similar to many other previous studies.10, 11, 12, 13, 14 However some authors found contradictory results, reporting a higher prevalence among men.15, 16, 17

In present study, Metabolic syndrome was found to be associated with advanced age. These findings were similar to Ford et al12 who reported prevalence of 42.0% for participants aged 60-69 years and 43.5% in 70 years and above.Similarly Bjorn Hildrum et al18concluded that the prevalence of Metabolic syndrome increased with age affecting less than 10% people in their 20s and 40% of people in their 60s. Other researchers19, 20, 21 have reported similar findings.

In the present study maximum 50% widow and separated had metabolic syndrome. 66 (18.49%) married study subjects were having metabolic syndrome and 1 (7.69%) unmarried subjects have metabolic syndrome. These findings were similar to Troxel WM et al22who reported divorced (OR= 2.47; 95% CI=1.02-5.97), and widowed (OR=5.82; 95% CI=1.88-18.03) women were significantly more likely to have the Metabolic syndrome, but contradictory toBhanushali et al23 who reported single women had significantly lower prevalence of Metabolic syndrome compare with married women (OR= 0.43, 95% CI=0.43-0.99). HoweverPark et al24 reported that prevalence of Metabolic syndrome was not statistically significant in divorced or widowed men and women compared with married men and women (OR= 0.82, 95% CI= 0.57-1.17 and OR=1.03, 95% CI=0.84-1.26, respectively).

The present study shows that,37.14 % subjects with Metabolic syndrome used to consume alcohol, and the association was statistically significant. This finding was similar to some studies25,26 while contradictory to others27, 28, 29.

Present study found that 37.68 % study subjects with Metabolic syndrome were smokers and 16.92% were non-smoker. Smokers were more prone to develop Metabolic syndrome. This finding was similar to previous studies. 30, 31, 32, 33, 34, 35HoweverBhanushali et al23found no association between smoking and prevalence of Metabolic syndrome in African-American men and women.

We found that vigorous physical activity was protective against metabolic syndrome. Similar finding has been reported in earlier studies. 36, 37, 38, 39, 40, 41, 42.

In the presentmost common co-morbidity associated with Metabolic syndrome was frozen shoulder followed by stroke, cataract and myocardial infarction.

Isomma et al43 in a Botnia Studyreported, in patient with Metabolic syndrome relative risk of CAD was 2.96 (CI 95% 2.36 to 3.72; P<0.0001) and cardiovascular mortality was significantly increased to 12% compared to 2% in subjects without Metabolic syndrome.Lakka et al44 in another Finnish study, found that all cause mortality associated with the Metabolic syndrome increased 1.9 fold and CVD mortality 2.6 fold.Sattar N et al45 reported Metabolic syndrome was associated with a 3.7 fold increase in coronary artery disease risk and 24.5 fold increase in incident diabetes compared to men without Metabolic syndrome,The Framingham Offspring Study46 reported the risk of CHD increased 2.4 fold for men and 5.9 for women, whileBonora et al47in the Verona Diabetes Complication Study found 92.3% of the population with CVDs to have Metabolic syndrome according to World Health Organization criteria.

References

  1. 1.Reaven G M.Banting lecture 1988. Role of insulin resistance in human disease. Diabetes 37(12), 1595-607.
  1. 2.NCEP.Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on. 01-3670.
  1. 3.Grundy S M, Cleeman J I, Daniels S R, K a Donato, Eckel R H et al. (2005) Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute scientific statement. , Circulation 112(17), 2735-52.
  1. 4. (2006) International Diabetes Federation. The IDF consensus worldwide definition of the metabolic syndrome. , IDF Consens Worldw Defin Metab Syndr 28, 1-7.
  1. 5.Misra A, Vikram N K, Gupta R, Pandey R M, Wasir J S et al. (2006) Waist circumference cutoff points and action levels for Asian Indians for identification of abdominal obesity. , Int J Obes (Lond) 30(1), 106-11.
  1. 6.Misra A, Pandey R M, Devi J R, Sharma R, Vikram N K et al. (2001) High prevalence of diabetes, obesity and dyslipidaemia in urban slum population in northern India. , Int J Obes Relat Metab Disord 25(11), 1722-9.
  1. 7.Sarkar S, Das M, Mukhopadhyay B, Chakrabarti C S, Majumder P P. (2006) High prevalence of metabolic syndrome & its correlates in two tribal populations of India & the impact of urbanization. , Indian J Med Res 123(5), 679-86.
  1. 8.Hu G, Qiao Q, Tuomilehto J, Eliasson M, EJM Feskens et al. (2004) Plasma insulin and cardiovascular mortality in non-diabetic European men and women: a meta-analysis of data from eleven prospective studies. , Diabetologia 47(7), 1245-56.
  1. 9.Gupta A, Gupta R, Sarna M, Rastogi S, Gupta V P et al. (2003) Prevalence of diabetes, impaired fasting glucose and insulin resistance syndrome in an urban Indian population. Diabetes Res Clin Pr. 61(1), 69-76.
  1. 10.Kamble P, Deshmukh P R, Garg N. (2010) Metabolic syndrome in adult population of rural Wardha, central India. , Indian J Med Res 132(6), 701-5.
  1. 11.Surana S P, Shah D B, Gala K, Susheja S, Hoskote S S et al. (2008) Prevalence of metabolic syndrome in an urban Indian diabetic population using the NCEP ATP III guidelines. , J Assoc Physicians India.;56: 865-8.
  1. 12.Ford E S, Giles W H, Dietz W H. (2002) Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. , JAMA 287(3), 356-9.
  1. 13.Gu D, Reynolds K, Wu X, Chen J, Duan X et al. (2005) Prevalence of the metabolic syndrome and overweight among adults in China. , Lancet 365(9468), 1398-405.
  1. 14.Pathania D, Bunger R, Mishra P, Pathak R, Arora A. (2013) . Community Medicine & Health Education A Study to Assess Prevalence of Metabolic Syndrome and its Socio Demographic Risk Factors in Rural Area of District Ambala , Haryana 3(5), 3-6.
  1. 15.Nilsson S. (2001) Research contributions of Eskil Kylin. , Sven Med Tidskr 5(1), 15-28.
  1. 16.Lim H, Nguyen T, Choue R, Wang Y. (2012) Sociodemographic disparities in the composition of metabolic syndrome components among adults in South Korea. Diabetes Care.35(10):. 2028-35.
  1. 17.Sawant A, Mankeshwar R, Shah S, Raghavan R, Dhongde G et al. (2011) Prevalence of metabolic syndrome in Urban India. , Cholesterol 1.
  1. 18.Hildrum B, Mykletun A, Hole T, Midthjell K, Dahl A A. (2007) Age-specific prevalence of the metabolic syndrome defined by. the International Diabetes Federation and the National Cholesterol Education Program: the Norwegian HUNT 2 study. BMC Public Health.;7: 220.
  1. 19.Arai H, Yamamoto A, Matsuzawa Y, Saito Y, Yamada N et al. (2010) Prevalence of metabolic syndrome in the general Japanese population in. , J Atheroscler Thromb 13(4), 202-208.
  1. 20.Riediger N D, Clara I. (2011) Prevalence of metabolic syndrome in the Canadian adult population. , CMAJ 183(15), 1127-34.
  1. 21.Dhatrak V S, SubrotoNS DhumneUL. (2015) Metabolic syndrome in different sub occupations among mine workers.Indian JOccupEnviron Med. 19(2), 76-9.
  1. 22.Troxel W M, Buysse D J, K a Matthews, Kip K E, Strollo P J et al. (2010) Sleep symptoms predict the development of the metabolic syndrome. 33(12), 1633-40.
  1. 23.Bhanushali C J, Kumar K, Wutoh A K, Karavatas S, Habib M J et al.Association between Lifestyle Factors and Metabolic Syndrome among African Americans in the United States. , J Nutr Metab 2013, 516475.
  1. 24.Park M J, Yun K E, Lee G E, Cho H J, Park H S. (2007) A cross-sectional study of socioeconomic status and the metabolic syndrome in Korean adults. , Ann Epidemiol 17(4), 320-6.
  1. 25.Baik I, Shin C.Prospective study of alcohol consumption and metabolic syndrome. , Am J Clin Nutr 87(5), 1455-63.
  1. 26.Stoutenberg M, Lee D, Sui X, Hooker S, Horigian V et al. (2013) Prospective study of alcohol consumption and the incidence of the metabolic syndrome in US men. , Br J Nutr 110(5), 901-10.
  1. 27.Imamura F, Lichtenstein A H, Dallal G E, Meigs J B, Jacques P F. (2009) Confounding by dietary patterns of the inverse association between alcohol consumption and type 2 diabetes risk. , Am J Epidemiol 170(1), 37-45.
  1. 28.Buja A, Scafato E, Sergi G, Maggi S, Suhad M A et al. (2010) Alcohol consumption and metabolic syndrome in the elderly: Results from the Italian longitudinal study on aging. , Eur J Clin Nutr 64(3), 297-307.
  1. 29.Aneja J, Basu D, Mattoo S K, Kohli K K. (2013) Metabolic syndrome in alcohol-dependent men: A cross-sectional study. , Indian J Psychol Med; 35, 190.
  1. 30.Zhu S, St-Onge M P, Heshka S, Heymsfield S B. (2004) Lifestyle behaviors associated with lower risk of having the metabolic syndrome. , Metabolism 53(11), 1503-11.
  1. 31.Chen C C, Li T C, Chang P C, Liu C S, Lin W Y et al. (2008) Association among cigarette smoking, metabolic syndrome, and its individual components: the metabolic syndrome study in Taiwan. , Metabolism 57, 544-8.
  1. 32.Matsushita Y, Nakagawa T, Yamamoto S, Takahashi Y, Noda M et al. (2011) Associations of smoking cessation with visceral fat area and prevalence of metabolic syndrome in men: the Hitachi health study. Obesity (Silver Spring). 19(3), 647-51.
  1. 33.Cena H, Fonte M L, Turconi G. (2011) Relationship between smoking and metabolic syndrome. , Nutr Rev 69(12), 745-53.
  1. 34.Bradshaw P T, Monda K L, Stevens J. (2013) Metabolic syndrome in healthy obese, overweight, and normal weight individuals: the Atherosclerosis Risk in Communities Study. Obesity (Silver Spring). 21(1), 203-209.
  1. 35.Calo W A, Ortiz A P, Suárez E, Guzmán M, Pérez C M. (2013) Association of cigarette smoking and metabolic syndrome in a puerto rican adult population. , International Journal of Preventive Medicine 849-56.
  1. 36.Misra A, Vikram N K, Gupta R, Pandey R M, Wasir J S et al. (2006) Waist circumference cutoff points and action levels for Asian Indians for identification of abdominal obesity. , Int J Obes (Lond) 30(1), 106-11.
  1. 37.V Sarang Dhatrak. (2015) Article On Metabolic syndrome in different sub occupations among mine workers. 19(2), 76-9.
  1. 38.Wannamethee S G, Shaper A G, Whincup P H. (2006) Modifiable lifestyle factors and the metabolic syndrome in older men: Effects of lifestyle changes. , J Am Geriatr Soc 54(12), 1909-14.
  1. 39.Galassi A, Reynolds K, He J. (2006) Metabolic Syndrome and Risk of Cardiovascular Disease: A Meta-Analysis. , Am J 119(10), 812-9.
  1. 40.Katzmarzyk P T, Leon A S, Wilmore J H, Skinner J S, Rao D C et al. (2003) Targeting the metabolic syndrome with exercise: Evidence from the HERITAGE Family Study. Med Sci Sports Exerc.35(10):. 1703-9.
  1. 41.Wagner a, Dallongeville J, Haas B, Ruidavets J B, Amouyel P et al. (2012) Sedentary behaviour, physical activity and dietary patterns are independently associated with the metabolic syndrome. , Diabetes Metab 38(5), 428-35.
  1. 42.Laursen A H, Kristiansen O P, Marott J L, Schnohr P, Prescott E. (2012) Intensity versus duration of physical activity: implications for the metabolic syndrome. A prospective cohort study. , BMJ Open Respir Res 2(5).
  1. 43.Pattyn N, SRT Eshghi, Vanhees L. (2013) The Effect of Exercise on the Cardiovascular Risk Factors Constituting the Metabolic Syndrome. Sports Med. 43, 121-33.
  1. 44.Choi M, Yeom H A, Jung D. (2013) Association between physical activity and metabolic syndrome in older adults in Korea: analysis of data from the Korean National Health and Nutrition Examination Survey IV. Nurs Heal Sci. 15(3), 379-86.
  1. 45.Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K et al. (2001) Cardiovascular Morbidity and Mortality Associated With the Metabolic Syndrome. Diabetes Care. 24(4), 683-9.
  1. 46.Lakka H M, Laaksonen D E, Lakka T A, Niskanen L K, Kumpusalo E et al. (2002) The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. , JAMA 288(21), 2709-16.
  1. 47.Sattar N, McConnachie A, a G Sh, Blauw G J, Buckley B M et al. (2008) Can metabolic syndrome usefully predict cardiovascular disease and diabetes? Outcome data from two prospective studies. , Lancet 371(9628), 1927-35.
  1. 48.Meigs J B, Cupples L A, PWF Wilson. (2000) The Framingham Offspring Study. World Health.57(23):. 2201-7.
  1. 49.Bonora E, Targher G, Formentini G, Calcaterra F, Lombardi S et al. (2003) The Metabolic Syndrome is an independent predictor of cardiovascular disease in Type 2 diabetic subjects. Prospective data from the Verona Diabetes Complications Study. Diabet Med. 21(1), 52-8.

Cited by (1)

  1. 1.Ali Nurshad, Samadder Mitu, Shourove Jahid Hasan, Taher Abu, Islam Farjana, 2023, Prevalence and factors associated with metabolic syndrome in university students and academic staff in Bangladesh, Scientific Reports, 13(1), 10.1038/s41598-023-46943-x