Cohort study on clustering of lifestyle risk factors and understanding its association with stress on health and wellbeing among school teachers in Malaysia (CLUSTer) – a study protocol

BMC Public Health

Awang M Bulgiba¹  HB(as) Bueno-de-Mesquita⁵  David Koh⁶  Petra A Wark²  Brian Buckley³  Noran Naqiah Hairi¹  Victor Chee Wai Hoe⁴  Foong Ming Moy¹ 

[1] Julius Centre University of Malaya, Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia;Global eHealth Unit, Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom;Department of Surgery, University of Manila, Manila, Philipines;Centre for Occupational and Environmental Health-UM, Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia;Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands;Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore

关键词: Clustering of lifestyle risk factors;    Work related stress;    Cohort study;    Teachers;   

Others  :  1129301
DOI  :  10.1186/1471-2458-14-611

 received in 2014-06-10, accepted in 2014-06-13,  发布年份 2014

【 摘 要 】

Background

The study on Clustering of Lifestyle risk factors and Understanding its association with Stress on health and wellbeing among school Teachers in Malaysia (CLUSTer) is a prospective cohort study which aims to extensively study teachers in Malaysia with respect to clustering of lifestyle risk factors and stress, and subsequently, to follow-up the population for important health outcomes.

Method/design

This study is being conducted in six states within Peninsular Malaysia. From each state, schools from each district are randomly selected and invited to participate in the study. Once the schools agree to participate, all teachers who fulfilled the inclusion criteria are invited to participate. Data collection includes a questionnaire survey and health assessment. Information collected in the questionnaire includes socio-demographic characteristics, participants’ medical history and family history of chronic diseases, teaching characteristics and burden, questions on smoking, alcohol consumption and physical activities (IPAQ); a food frequency questionnaire, the job content questionnaire (JCQ); depression, anxiety and stress scale (DASS21); health related quality of life (SF12-V2); Voice Handicap Index 10 on voice disorder, questions on chronic pain, sleep duration and obstetric history for female participants. Following blood drawn for predefined clinical tests, additional blood and urine specimens are collected and stored for future analysis. Active follow up of exposure and health outcomes will be carried out every two years via telephone or face to face contact. Data collection started in March 2013 and as of the end of March 2014 has been completed for four states: Kuala Lumpur, Selangor, Melaka and Penang. Approximately 6580 participants have been recruited. The first round of data collection and blood sampling is expected to be completed by the end of 2014 with an expected 10,000 participants recruited.

Discussion

Our study will provide a good basis for exploring the clustering of lifestyle risk factors and stress and its association with major chronic medical conditions such as obesity, hypertension, impaired glucose tolerance, diabetes mellitus, coronary heart diseases, kidney failure and cancers among teachers.

【 授权许可】

   
2014 Moy et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

【 参考文献 】

• [1]Ministry of Education: Malaysia Educational Statistics, 2013. In Malaysia. Kuala Lumpur: Ministry of Education; 2013.
• [2]Austin V, Shah S, Muncer S: Teacher stress and coping strategies used to reduce stress. Occup Ther Int 2005, 12(2):63-80.
• [3]Jepson E, Forrest S: Individual contributory factors in teacher stress: the role of achievement striving and occupational commitment. Br J Educ Psychol 2006, 76(Pt 1):183-197.
• [4]Retneswari M, Azlan D, Ting SA, Roslinah A, Awang Bulgiba AM, Koh D: Salivary biomarkers of stress among teachers in an urban setting. Asia Pac J Publ Health 2012, 24(2):278-287.
• [5]Stampfer MJ, Hu FB, Manson JE, Rimm EB, Willett WC: Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med 2000, 343(1):16-22.
• [6]World Cancer Research Fund / American Institute for Cancer Research: Food, Nutrition, Physical Activity, and the Prevention of Cancer: a Global Perspective. 1st edition. Washington DC: AIRC; 2007.
• [7]Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L: Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004, 364(9438):937-952.
• [8]Poortinga W: The prevalence and clustering of four major lifestyle risk factors in an English adult population. Prev Med 2007, 44(2):124-128.
• [9]Chou KL: The prevalence and clustering of four major lifestyle risk factors in Hong Kong Chinese older adults. J Aging Health 2008, 20(7):788-803.
• [10]Chandola T, Brunner E, Marmot M: Chronic stress at work and the metabolic syndrome: prospective study. BMJ 2006, 332(7540):521-525.
• [11]Bergmann N, Gyntelberg F, Faber J: The appraisal of chronic stress and the development of the metabolic syndrome: a systematic review of prospective cohort studies. Endocr Connections 2014, 3(2):R55-R80.
• [12]Eller NH, Netterstrom B, Gyntelberg F, Kristensen TS, Nielsen F, Steptoe A, Theorell T: Work-related psychosocial factors and the development of ischemic heart disease: a systematic review. Cardiol Rev 2009, 17(2):83-97.
• [13]Kivimaki M, Virtanen M, Elovainio M, Kouvonen A, Vaananen A, Vahtera J: Work stress in the etiology of coronary heart disease–a meta-analysis. Scand J Work Environ Health 2006, 32(6):431-442.
• [14]Rosengren A, Hawken S, Ounpuu S, Sliwa K, Zubaid M, Almahmeed WA, Blackett KN, Sitthi-amorn C, Sato H, Yusuf S: Association of psychosocial risk factors with risk of acute myocardial infarction in 11119 cases and 13648 controls from 52 countries (the INTERHEART study): case-control study. Lancet 2004, 364(9438):953-962.
• [15]Cosgrove MP, Sargeant LA, Caleyachetty R, Griffin SJ: Work-related stress and Type 2 diabetes: systematic review and meta-analysis. Occup Med (Lond) 2012, 62(3):167-173.
• [16]Heraclides A, Chandola T, Witte DR, Brunner EJ: Psychosocial stress at work doubles the risk of type 2 diabetes in middle-aged women: evidence from the Whitehall II study. Diabetes Care 2009, 32(12):2230-2235.
• [17]Tsurugano S, Nakao M, Takeuchi T, Nomura K, Yano E: Job stress strengthens the link between metabolic risk factors and renal dysfunction in adult men. Tohoku J Exp Med 2012, 226(2):101-108.
• [18]Nielsen NR, Stahlberg C, Strandberg-Larsen K, Kristensen TS, Zhang ZF, Hundrup YA, Gronbaek M: Are work-related stressors associated with diagnosis of more advanced stages of incident breast cancers? Canc Causes Contr 2008, 19(3):297-303.
• [19]Schernhammer ES, Hankinson SE, Rosner B, Kroenke CH, Willett WC, Colditz GA, Kawachi I: Job stress and breast cancer risk: the nurses' health study. Am J Epidemiol 2004, 160(11):1079-1086.
• [20]Siegrist J, Rodel A: Work stress and health risk behavior. Scand J Work Environ Health 2006, 32(6):473-481.
• [21]Lallukka T, Lahelma E, Rahkonen O, Roos E, Laaksonen E, Martikainen P, Head J, Brunner E, Mosdol A, Marmot M, Sekine M, Nasermoaddeli A, Kagamimori S: Associations of job strain and working overtime with adverse health behaviors and obesity: evidence from the Whitehall II Study, Helsinki Health Study, and the Japanese Civil Servants Study. Soc Sci Med 2008, 66(8):1681-1698.
• [22]Kang K, Sung J, Kim CY: High risk groups in health behavior defined by clustering of smoking, alcohol, and exercise habits: National Heath and Nutrition Examination Survey. J Prev Med Publ Health 2010, 43(1):73-83.
• [23]Disease Control Division: Malaysia NCD Surveillance 2006: Non communicable disease risk factors in Malaysia. Kuala Lumpur: Ministry of Health Malaysia; 2006.
• [24]Lwanga SK, Lemeshow S, World Health Organization: Sample size determination in health studies: a practical manual. Geneva: World Health Organization; 1991. http://www.tbrieder.org/publications/books_english/lemeshow_samplesize.pdf webcite
• [25]Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P: International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003, 35(8):1381-1395.
• [26]Hadi AA, Naing NN, Daud A, Nordin R: Reliability and construct validity of the Malay version of the Job Content Questionnaire (JCQ) among secondary school teachers in Kota Bharu, Kelantan, Malaysia. Southeast Asian J Trop Med Publ Health 2006, 37(6):1254-1259.
• [27]Musa R, Fadzil MA, Zain Z: Translation, validation and psychometric properties of Bahasa Malaysia version of the Depression Anxiety and Stress Scales (DASS). ASEAN J Psychiatr 2007, 8(2):82-89.
• [28]Gandek B, Ware JE, Aaronson NK, Apolone G, Bjorner JB, Brazier JE, Bullinger M, Kaasa S, Leplege A, Prieto L, Sullivan M: Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol 1998, 51(11):1171-1178.
• [29]Ware J Jr, Kosinski M, Keller SD: A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care 1996, 34(3):220-233.
• [30]Rosen CA, Lee AS, Osborne J, Zullo T, Murry T: Development and validation of the voice handicap index-10. Laryngoscope 2004, 114(9):1549-1556.
• [31]Zimmet P, Alberti G, Shaw J: A new IDF worldwide definition of the metabolic syndrome:the rationale and the results. Diabetes Voice 2005, 50:31-33.
• [32]El Assaad MA, Topouchian JA, Darne BM, Asmar RG: Validation of the Omron HEM-907 device for blood pressure measurement. Blood Press Monit 2002, 7(4):237-241.
• [33]Friedewald WT, Levy RI, Fredrickson DS: Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972, 18(6):499-502.
• [34]Mirnalini K, Zalilah MS, Safiah MY, Tahir A, Siti Haslinda MD, Siti Rohana D: Energy and Nutrient Intakes: Findings from the Malaysian Adult Nutrition Survey (MANS). Mal J Nutr 2008, 14(1):1-24.
• [35]Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L: A data-based approach to diet questionnaire design and testing. Am J Epidemiol 1986, 124:453-469.
• [36]Frank L, Engelke P, Schmid T: Health and Community Design: The Impact of the Built Environment on Physical Activity. Washington, DC: Island Press; 2003.
• [37]Leslie E, Coffee N, Frank L, Owen N, Bauman A, Hugo G: Walkability of local communities: using geographic information systems to objectively assess relevant environmental attributes. Health Place 2007, 13:111-122.
• [38]HP TeleFormhttp://www.hpteleform.com/ webcite
• [39]Michels KB, Schulze MB: Can dietary patterns help us detect diet-disease associations? Nutr Res Rev 2005, 18(2):241-248.
• [40]Jamal R, Syed Zakaria SZ, Kamaruddin MA, Abd Jalal N, Ismail N, Mohd Kamil N, Abdullah N, Baharudin N, Hussin NH, Othman H, Mahadi NM: Cohort profile: The Malaysian Cohort (TMC) project: a prospective study of non-communicable diseases in a multi-ethnic population. Int J Epidemiol 2014. Advance Access published April 11, 2014
• [41]Rolland B, Smith BR, Potter JD: Coordinating centers in cancer-epidemiology research: the Asia cohort consortium coordinating center. Canc Epidemiol Biomarkers Prev 2011, 20:2115-2119.