Determinants of metabolic syndrome in obese workers: gender differences in perceived job-related stress and in psychological characteristics identified using artificial neural networks
- 79 Downloads
The metabolic syndrome (MS) is a multifactorial disorder associated with a higher risk of developing cardiovascular diseases and type 2 diabetes. However, its pathophysiology and risk factors are still poorly understood. In this study, we investigated the associations among gender, psychosocial variables, job-related stress and the presence of MS in a cohort of obese Caucasian workers.
A total of 210 outpatients (142 women, 68 men) from an occupational medicine service was enrolled in the study. Age, BMI, waist circumference, fasting glucose, blood pressure, triglycerides and HDL cholesterol were collected to define MS. In addition, we evaluated eating behaviors, depressive symptoms, and work-related stress. Data analyses were performed with an artificial neural network algorithm called Auto Semantic Connectivity Map (AutoCM), using all available variables.
MS was diagnosed in 54.4 and 33.1% of the men and women, respectively. AutoCM evidenced gender-specific clusters associated with the presence or absence of MS. Men with a moderate occupational physical activity, obesity, older age and higher levels of decision-making freedom at work were more likely to have a diagnosis of MS than women. Women with lower levels of decision-making freedom, and higher levels of psychological demands and social support at work had a lower incidence of MS but showed higher levels of binge eating and depressive symptomatology.
We found a complex gender-related association between MS, psychosocial risk factors and occupational determinants. The use of these information in surveillance workplace programs might prevent the onset of MS and decrease the chance of negative long-term outcomes.
Level of evidence
Level V, observational study.
KeywordsObesity Metabolic syndrome Gender Eating disorders Depression Occupational determinants ANN Occupational physical activity
The authors did not receive any form of funding.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Human and animal participants rights
This article does not contain any studies with human participants performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
- 8.Strine TW, Mokdad AH, Dube SR, Balluz LS, Gonzalez O, Berry JT, Manderscheid R, Kroenke K (2008) The association of depression and anxiety with obesity and unhealthy behaviours among community-dwelling US adults. Gen Hosp Psychiatry 30:127–137. https://doi.org/10.1016/j.genhosppsych.2007.12.008 CrossRefGoogle Scholar
- 13.Ateco 2007 (2009) Classificazione delle attività economiche. https://www4.istat.it/it/strumenti/definizioni-e-classificazioni/ateco-2007. Accessed 5 Jan 2018
- 15.World Health Organization (2000) Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser, 894. WHO, Geneva, pp 1–253Google Scholar
- 16.Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, Spertus JA, Costa F, American Heart Association; National Heart, Lung, and Blood Institute (2005) Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 112:2735–2752. https://doi.org/10.1161/CIRCULATIONAHA.105.169404 CrossRefGoogle Scholar
- 18.Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J (1961) An inventory for measuring depression. Arch Gen Psychiatry 4:561–571. https://doi.org/10.1001/archpsyc.1961.01710120031004 CrossRefGoogle Scholar
- 20.Baldasseroni A, Camerino D, Cenni P, Cesana GC, Fattorini E, Ferrario M, Tartaglia R (2001) La valutazione dei fattori psicosociali. Proposta della versione italiana del Job Content Questionnaire di R. A. Karasek. Fogli d’Informazione ISPESL 3:20–32Google Scholar
- 21.Ulivieri FM, Piodi LP, Grossi E, Rinaudo L, Messina C, Tassi AP, Filopanti M, Tirelli A, Sardanelli F (2018) The role of carboxy-terminal cross-linking telopeptide of type I collagen, dual X-ray absorptiometry bone strain and Romberg test in a new osteoporotic fracture risk evaluation: a proposal from an observational study. PLoS One. https://doi.org/10.1371/journal.pone.0190477 (Accessed 05 Jan 2018) Google Scholar
- 22.Eller-Vainicher C, Zhukouskaya VV, Tolkachev YV, Koritko SS, Cairoli E, Grossi E, Beck-Peccoz P, Chiodini I, Shepelkevich AP (2011) Low bone mineral density and its predictors in type 1 diabetic patients evaluated by the classic statistics and artificial neural network analysis. Diabetes Care 34:2186–2191. https://doi.org/10.2337/dc11-0764 CrossRefGoogle Scholar
- 23.Hirose H, Takayama T, Hozawa S, Hibi T, Saito I (2011) Prediction of metabolic syndrome using artificial neural network system based on clinical data including insulin resistance index and serum adiponectin. Comput Biol Med 41:1051–1056. https://doi.org/10.1016/j.compbiomed.2011.09.005 CrossRefGoogle Scholar
- 27.Hudson JI, Lalonde JK, Coit CE, Tsuang MT, McElroy SL, Crow SJ, Bulik CM, Hudson MS, Yanovski JA, Rosenthal NR, Pope HG Jr (2010) Longitudinal study of the diagnosis of components of the metabolic syndrome in individuals with binge-eating disorder. Am J Clin Nutr 91(6):1568–1573. https://doi.org/10.3945/ajcn.2010.29203 CrossRefGoogle Scholar
- 28.Lasserre AM, Strippoli MF, Glaus J, Gholam-Rezaee M, Vandeleur CL, Castelao E, Marques-Vidal P, Waeber G, Vollenweider P, Preisig M (2017) Prospective associations of depression subtypes with cardio-metabolic risk factors in the general population. Mol Psychiatry 22(7):1026–1034. https://doi.org/10.1038/mp.2016.178 CrossRefGoogle Scholar
- 31.Gostynski M, Gutzwiller F, Kuulasmaa K, Döring A, Ferrario M, Grafnetter D, Pajak A, WHO MONICA Project (2004) Analysis of the relationship between total cholesterol, age, body mass index among males and females in the WHO MONICA Project. Int J Obes Relat Metab Disord 28:1082–1090CrossRefGoogle Scholar
- 32.Wietlisbach V, Marques-Vidal P, Kuulasmaa K, Karvanen J, Paccaud F, WHO MONICA Project (2013) The relation of body mass index and abdominal adiposity with dyslipidemia in 27 general populations of the WHO MONICA Project. Nutr Metab Cardiovasc Dis 23:432–442. https://doi.org/10.1016/j.numecd.2011.09.002 CrossRefGoogle Scholar
- 34.Kivimäki M, Nyberg ST, Fransson EI, Heikkilä K, Alfredsson L, Casini A, Clays E, De Bacquer D, Dragano N, Ferrie JE, Goldberg M, Hamer M, Jokela M, Karasek R, Kittel F, Knutsson A, Koskenvuo M, Nordin M, Oksanen T, Pentti J, Rugulies R, Salo P, Siegrist J, Suominen SB, Theorell T, Vahtera J, Virtanen M, Westerholm PJ, Westerlund H, Zins M, Steptoe A, Singh-Manoux A, Batty GD, IPD-Work Consortium (2013) Associations of job strain and lifestyle risk factors with risk of coronary artery disease: a meta-analysis of individual participant data. CMAJ 185:763–769. https://doi.org/10.1503/cmaj.121735 CrossRefGoogle Scholar
- 39.Kessler RC, Berglund PA, Chiu WT, Deitz AC, Hudson JI, Shahly V, Aguilar-Gaxiola S, Alonso J, Angermeyer MC, Benjet C, Bruffaerts R, de Girolamo G, de Graaf R, Maria Haro J, Kovess-Masfety V, O’Neill S, Posada-Villa J, Sasu C, Scott K, Viana MC, Xavier M (2013) The prevalence and correlates of binge eating disorder in the World Health Organization World Mental Health Surveys. Biol Psychiatry 73:904–914. https://doi.org/10.1016/j.biopsych.2012.11.020 CrossRefGoogle Scholar
- 41.Raikkonen K, Matthews KA, Kuller LH (2007) Depressive symptoms and stressful life events predict metabolic syndrome among middle-aged women: a comparison of World Health Organization, Adult Treatment Panel III, and International Diabetes Foundation definitions. Diabetes Care 30:872–877. https://doi.org/10.2337/dc06-1857 CrossRefGoogle Scholar
- 43.Imayama I, Alfano CM, Kong A, Foster-Schubert KE, Bain CE, Xiao L, Duggan C, Wang CY, Campbell KL, Blackburn GL, McTiernan A (2011) Dietary weight loss and exercise interventions effects on quality of life in overweight/obese postmenopausal women: a randomized controlled trial. Int J Behav Nutr Phys Act 8:118. https://doi.org/10.1186/1479-5868-8-118 CrossRefGoogle Scholar