Skip to main content

Workplace Health and Workplace Wellness: Synergistic or Disconnected?

  • Chapter
  • First Online:
Case Studies in Applied Bayesian Data Science

Part of the book series: Lecture Notes in Mathematics ((LNM,volume 2259))

  • 2124 Accesses

Abstract

Workplace health and wellness is paramount in many businesses and industries, for economic and social reasons. Workplace wellness programs have emerged to meet this need. This paper pursues a deeper understanding of the relationship between workplace health and workplace wellness initiatives in Australia. Based on a survey of published literature, Bayesian networks are developed to describe and quantify factors that contribute to each of these components of workplace efficiency. Workplace health was found to be a complex system of acute and chronic occupational medical conditions, as well as lifestyle factors. Successful wellness programs were found to be those that have a high level of participation and positive financial impacts, and are integrated into business strategy and company culture. It was observed that many workplace wellness programs tend to target non-occupational health risks and that there is an opportunity to address other critical components of worker health risk factors. The outputs of the Bayesian networks can provide an interrogative monitor of workplace health and the potential impact of corresponding wellness initiatives, facilitating the development of more targeted and cost-effective programs.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. I. Ajunwa, Workplace wellness programs could be putting your health data at risk. Harv. Bus. Rev. (19 January 2017)

    Google Scholar 

  2. B.B. Alexy, Factors associated with participation or nonparticipation in a workplace wellness center. Res. Nurs. Health 14, 33–40 (1991)

    Article  Google Scholar 

  3. O. Atilola, O. Akinyemi, B. Atilola, Taking the first step towards entrenching mental health in the workplace: insights from a pilot study among HR personnel in Nigeria. J. Natl. Assoc. Resid. Doct. Niger. 23(1), 70–76 (2014)

    Google Scholar 

  4. Australian Bureau of Statistics (ABS), Australian Health Survey: First Results, 2011-12 (Heart Stroke and Vascular Disease, Canberra, 2012a)

    Google Scholar 

  5. Australian Bureau of Statistics (ABS), Australian Health Survey: First Results, 2011-12 (Key Findings, Canberra, 2012b)

    Google Scholar 

  6. Australian Bureau of Statistics (ABS), Labour Fource, Australia, Dec 2012. (Canberra, 2013)

    Google Scholar 

  7. Australian Institute of Health and Welfare (AIHW), Chronic Disease and Participation in Work. Report DOI: 9781740248785, 2009

    Google Scholar 

  8. Australian Institute of Health and Welfare (AIHW), Australia’s Health 2014. (Canberra, 2014)

    Google Scholar 

  9. V.V. Baba, B.L. Galperin, T.R. Lituchy, Occupational mental health: a study of work-related depression among nurses in the Caribbean. Int. J. Nurs. Stud. 36(2), 163–169 (1999)

    Article  Google Scholar 

  10. D.A. Beaudequin, F.A. Harden, A. Roiko, H. Stratton, C. Lemckert, K.L. Mengersen, Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks. Environ. Int. 80, 8–18 (2015)

    Article  Google Scholar 

  11. W.S. Beckett, Occupational respiratory diseases. N. Engl. J. Med. 342(6), 406–413 (2000)

    Article  Google Scholar 

  12. L. Berry, A.M. Mirabito, W.B. Baun, What’s the hard return on employee wellness programs? Harv. Bus. Rev. 88(12), 104–112 (2010)

    Google Scholar 

  13. R. Brook, B. Franklin, W. Cascio, Y. Hong, G. Howard, M. Lipsett, R. Luepker, M. Mittleman, J. Samet, S. Smith Jr., I. Tager, Air pollution and cardiovascular disease: a statement for healthcare professionals from the expert panel on population and prevention science of the American Heart Association. Circulation 109, 2655–2671 (2004)

    Article  Google Scholar 

  14. A. Burdorf, Economic evaluation in occupational health--its goals, challenges, and opportunities. Scand. J. Work Environ. Health 33(3), 161–164 (2007)

    Article  Google Scholar 

  15. Business in the Community, Mental Health at Work Report. (National Employee Mental Wellbeing Survey Findings 2017, 2017), https://wellbeing.bitc.org.uk/system/files/research/bitcmental_health_at_work_report-2017.pdf. Accessed 8 Dec 2017

  16. B.L. Callen, L.C. Lindley, V.P. Niederhauser, Health risk factors associated with presenteeism in the workplace. J. Occup. Environ. Med. 55(11), 1312–1317 (2013)

    Article  Google Scholar 

  17. W.H. Charles, E.T. Holly, C.M. Stephen, B. Nicole, The occupational burden of mental disorders in the U.S. military: psychiatric hospitalizations, involuntary separations, and disability. Am. J. Psychiatry 162(3), 585–591 (2005)

    Article  Google Scholar 

  18. L.C. Coffey, J.J.K. Skipper, F.D. Jung, Nurses and shift work: effects on job performance and job-related stress. J. Adv. Nurs. 13(2), 245–254 (1988)

    Article  Google Scholar 

  19. Comcare, Benefits to Business: The Evidence for Investing in Worker Health and Wellbeing (Australian Government, Canberra, 2011)

    Google Scholar 

  20. C.E. Crump, J.L. Earp, C.M. Kozma, I. Hert-Picciotto, Effect of organizational-level variables on differential employee participation in 10 Federal worksite health promotion programs. Health Educ. Q. 23(2), 204–223 (1996)

    Article  Google Scholar 

  21. M.R. Cullen, M.G. Cherniack, L. Rosenstock, Occupational medicine (1). N. Engl. J. Med. 322(9), 594–601 (1990)

    Article  Google Scholar 

  22. Department of Health and Ageing (DOHA), Promoting Healthy Weight (Australian Government Report, Canberra, 2009)

    Google Scholar 

  23. J.-P. Després, N. Alméras, L. Gauvin, Worksite health and wellness programs: Canadian achievements and prospects. Prog. Cardiovasc. Dis. 56(5), 484–492 (2014)

    Article  Google Scholar 

  24. M.J. Eckardt, T.C. Harford, C.T. Kaelber, E.S. Parker, L.S. Rosenthal, R.S. Ryback, G.C. Salmoiraghi, E. Vanderveen, K.R. Warren, Health hazards associated with alcohol consumption. J. Am. Med. Assoc. 246(6), 648–666 (1981)

    Article  Google Scholar 

  25. G. Edwards, S. Guthrie, A controlled trial of in-patient and outpatient treatment of alcohol dependency. Lancet 1, 555–559 (1967)

    Article  Google Scholar 

  26. ERS Research and Consultancy (Health at Work: Economic Evidence Report. U.K., 2016), https://www.bhf.org.uk/health-at-work. Accessed 6 Dec 2017

  27. M. Estryn-Behar, M. Kaminski, E. Peigne, N. Bonnet, E. Vaichere, C. Gozlan, S. Azoulay, M. Giorgi, Stress at work and mental health status among female hospital workers. Br. J. Ind. Med. 47(1), 20–28 (1990)

    Google Scholar 

  28. D.M. Gates, P. Succop, B.J. Brehm, G.L. Gillespie, B.D. Sommers, Obesity and presenteeism: the impact of body mass index on workplace productivity. J. Occup. Environ. Med. 50(1), 39–45 (2008)

    Article  Google Scholar 

  29. D.L. Gebhardt, C.E. Crump, Employee fitness and wellness programs in the workplace. Am. Psychol. 45(2), 262–272 (1990)

    Article  Google Scholar 

  30. M.M. Glatt, D.R. Hills, Occupational behaviour patterns in samples of English alcoholic employees. Br. J. Addict. 61, 71–78 (1965)

    Article  Google Scholar 

  31. F.M.S. Golbabaei, A. Ghahri, H. Shirkhanloo, M. Khadem, H. Hassani, N. Sadeghi, B. Dinari, Assessment of welders exposure to carcinogen metals from manual metal arc welding in gas transmission pipelines, Iran. Iran. J. Public Health 41(8), 61–70 (2012)

    Google Scholar 

  32. I.F. Groeneveld, K.I. Proper, A.J. van der Beek, V.H. Hildebrandt, W. van Mechelen, Lifestyle-focused interventions at the workplace to reduce the risk of cardiovascular disease--a systematic review. Scand. J. Work Environ. Health 36(3), 202–215 (2010)

    Article  Google Scholar 

  33. S.F.M. Haynes, Women, work and coronary heart disease: prospective findings from the Framingham Heart Study. Am. J. Public Health 70, 133–141 (1980)

    Article  Google Scholar 

  34. J. He, S. Vupputuri, K. Allen, M.R. Prerost, J. Hughes, P. Whelton, Passive smoking and the risk of coronary heart disease: a meta-analysis of epidemiologic studies. N. Engl. J. Med. 340, 920–926 (1999)

    Article  Google Scholar 

  35. A. Henschel, Obesity as an occupational hazard. Can. J. Public Health 58, 491–493 (1967)

    Google Scholar 

  36. A.B. Hill, The environment and disease: association or causation? Proc. R. Soc. Med. 58(5), 295–300 (1965)

    Google Scholar 

  37. M.F. Hilton, H.A. Whiteford, J.S. Sheridan, C.M. Cleary, D.C. Chant, P.S. Wang, R.C. Kessler, The prevalence of psychological distress in employees and associated occupational risk factors. J. Occup. Environ. Med. 50(7), 746–757 (2008)

    Article  Google Scholar 

  38. D. Hoffmann, E.L. Wynder, Smoking and occupational cancers. Prev. Med. 5(2), 245–261 (1976)

    Article  Google Scholar 

  39. K. Husgafvel-Pursiainen, P.W. Brandt-Rauf, A. Kannio, P. Oksa, T. Suitiala, H. Koskinen, R. Partanen, K. Hemminki, S. Smith, R. Rosenstock-Leibu, Mutations, tissue accumulations, and serum levels of p53 in patients with occupational cancers from asbestos and silica exposure. Environ. Mol. Mutagen. 30(2), 224–230 (1997)

    Article  Google Scholar 

  40. R. Jenkins, S. Harvey, T. Butler, R.L. Thomas, A six year longitudinal study of the occupational consequences of drinking over “safe limits” of alcohol. Br. J. Ind. Med. 49(5), 369–374 (1992)

    Google Scholar 

  41. J. Johnson, E.M. Hall, Job strain, work place social support, and cardiovascular disease: a cross-sectional study of a random sample of the Swedish working population. Am. J. Public Health 78(10), 1336–1342 (1988)

    Article  Google Scholar 

  42. S. Johnson, K. Mengersen, Integrated Bayesian network framework for modeling complex ecological issues. Integr. Environ. Assess. Manag. Online, 1–11 (2011)

    Google Scholar 

  43. R.C. Kessler, R.G. Frank, The impact of psychiatric disorders on work loss days. Psychol. Med. 27(4), 861–873 (1997)

    Article  Google Scholar 

  44. H.K. Laschinger, D.S. Havens, The effect of workplace empowerment on staff nurses’ occupational mental health and work effectiveness. J. Nurs. Adm. 27(6), 42–50 (1997)

    Article  Google Scholar 

  45. C. Lee, M. Chen, C. Chu, The health promoting hospital movement in Taiwan: recent development and gaps in workplace. Int. J. Public Health 58(2), 313–317 (2013)

    Article  Google Scholar 

  46. D. Lin, K. Sanderson, A. Gavin, Lost productivity among full-time workers with mental disorders. J. Mental Health Policy Econ. 3(3), 139–146 (2000)

    Article  Google Scholar 

  47. J.L.Y. Liu, N. Maniadakis, A. Gray, M. Rayner, The economic burden of coronary heart disease in the UK. Heart Br. Cardiac Soc. 88(6), 597–603 (2002)

    Article  Google Scholar 

  48. D.M. Lloyd-Jones, M.G. Larson, A. Beiser, D. Levy, Lifetime risk of developing coronary heart disease. Lancet 353, 89–92 (1999)

    Article  Google Scholar 

  49. W. Macdonald, O. Evans, Research on the Prevention of Work-related Musculoskeletal Disorders Stage 1 - Literature Review (Safe Work Australia, 2006)

    Google Scholar 

  50. T.W. Mangione, J. Howland, B. Amick, J. Cote, M. Lee, N. Bell, S. Levine, Employee drinking practices and work performance. J. Stud. Alcohol 60(2), 261–270 (1999)

    Article  Google Scholar 

  51. T.H. Marc, G.H. Deborah, W.Z. Theodore, Role of low energy expenditure and sitting in obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease. Diabetes 56(11), 2655–2667 (2007)

    Article  Google Scholar 

  52. S. Mattke, H. Liu, J.P. Caloyeras, C.Y. Huang, K.R. van Busum, D. Khodyakov, V. Shier, Workplace Wellness Programs Study Final Report (RAND Health, 2013). https://www.rand.org/content/dam/rand/pubs/research_reports/RR200/RR254/RAND_RR254.sum.pdf. Accessed 8 Feb 2017

  53. S. Mattke, K.A. Kapinos, J. Caloyeras, E.A. Taylor, B.S. Batorsky, H.H. Liu, K.R. van Busum, S. Newberry, Workplace wellness programs. Services offered, participation and incentives. Rand Health Q. 5(2), 7 (2015)

    Google Scholar 

  54. D.I. McBride, Noise-induced hearing loss and hearing conservation in mining. Occup. Med. 54(5), 290–296 (2004)

    Article  Google Scholar 

  55. J.H. Medalie, H.A. Kahn, H.N. Neufeld, E. Rise, U. Goldbourt, Five year myocardial infarction incidence: 2. Association of single variables to age and birthplace. J. Chronic Dis. 26, 329–349 (1973)

    Article  Google Scholar 

  56. C.N. Michaels, A.M. Greene, Worksite wellness: increasing adoption of workplace health promotion programs. Health Promot. Pract. 14, 473 (2013)

    Article  Google Scholar 

  57. B. Moe, P.J. Mork, A. Holtermann, T.I. Nilsen, Occupational physical activity, metabolic syndrome and risk of death from all causes and cardiovascular disease in the HUNT 2 cohort study. Occup. Environ. Med. 70(2), 86 (2013)

    Article  Google Scholar 

  58. M. Moreau, F. Valente, R. Mak, E. Pelfrene, P. de Smet, G. De Backer, M. Kornitzer, Obesity, body fat distribution and incidence of sick leave in the Belgian workforce: the Belstress study. Int. J. Obes. Relat. Metab. Disord. 28, 574–582 (2004)

    Article  Google Scholar 

  59. S.J. Motowidlo, J.S. Packard, M.R. Manning, Occupational stress: its causes and consequences for job performance. J. Appl. Psychol. 71(4), 618–629 (1986)

    Article  Google Scholar 

  60. J.E. Myers, T.J. Sweeney, Five Factor Wellness Inventory (Mind Garden Inc., 2005)

    Google Scholar 

  61. J.E. Myers, K. Williard, Integrating spirituality into counseling and counselor training: a development, wellness approach. Couns. Values 47(2), 142–155 (2003)

    Article  Google Scholar 

  62. A. Mykletun, S.B. Harvey, Prevention of mental disorders: a new era for workplace mental health. Occup. Environ. Med. 69(12), 868 (2012)

    Article  Google Scholar 

  63. National Institute for Occupational Safety and Health (NIOSH), Work Related Hearing Loss. (Centers for Disease Control and Prevention, 2001)

    Google Scholar 

  64. National Institute for Occupational Safety and Health (NIOSH), The Work-related Lung Disease Surveillance Report, 2002. (Cincinnati, 2003)

    Google Scholar 

  65. National Institute for Occupational Safety and Health (NIOSH), Promising and Best Practices in Total Worker Health. Joint Report on workshop convened by NIOSH and the Institute of Medicine (2014). https://www.cdc.gov/niosh/twh/practices.html. Accessed 4 Dec 2017

  66. D.I. Nelson, R.I. Nelson, M. Concha-Barrientos, M. Fingerhut, The global burden of occupational noise-induced hearing loss. Am. J. Ind. Med. 48(6), 446–458 (2005)

    Article  Google Scholar 

  67. L. Punnett, J. Gold, J. Katz, R. Gore, D. Wegman, Ergonomic stressors and upper extremity musculoskeletal disorders in automobile manufacturing: a one year follow up study. J. Occup. Environ. Med. 61, 668–674 (2004)

    Article  Google Scholar 

  68. A. Rongen, S.J.W. Robroek, F.J. van Lenthe, A. Burdorf, Workplace health promotion: a meta-analysis of effectiveness. Am. J. Prev. Med. 44(4), 406–415 (2013)

    Article  Google Scholar 

  69. M.H. Ross, J. Murray, Occupational respiratory disease in mining. Occup. Med. 54(5), 304–310 (2004)

    Article  Google Scholar 

  70. Safe Work Australia, National OHS Strategy 2002–2012. (Canberra, 2002)

    Google Scholar 

  71. Safe Work Australia, Occupational Disease Indicators. (Canberra, 2010)

    Google Scholar 

  72. Safe Work Australia, Occupational Disease Indicators. (Canberra, 2012)

    Google Scholar 

  73. R.T. Sataloff, J. Sataloff, Occupational Hearing Loss (CRC Press Taylor & Francis Group, Boca Raton, 2006)

    Book  Google Scholar 

  74. J.K. Schmier, M.L. Jones, M.T. Halpern, Cost of obesity in the workplace. Scand. J. Work Environ. Health 32(1), 5–11 (2006)

    Article  Google Scholar 

  75. P.L. Schnall, P.A. Landsbergis, D. Baker, Job strain and cardiovascular disease. Annu. Rev. Public Health 15(1), 381–411 (1994)

    Article  Google Scholar 

  76. P. Schulte, Work, obesity, and occupational safety and health. Am. J. Public Health 97(3), 428–436 (2007)

    Article  Google Scholar 

  77. J. Siemiatycki, L. Richardson, K. Straif, B. Latreille, R. Lakhani, S. Campbell, M.-C. Rousseau, P. Boffetta, Listing occupational carcinogens. Environ. Health Perspect. 112(15), 1447–1459 (2004)

    Article  Google Scholar 

  78. R.P. Sloan, J.C. Gruman, Participation in workplace health promotion programs: the contribution of health and organizational factors. Health Educ. Q. 15(3), 269–288 (1988)

    Article  Google Scholar 

  79. F. Smit, P. Cuijpers, J. Oostenbrink, N. Batelaan, R. de Graaf, A. Beekman, Costs of nine common mental disorders: implications for curative and preventive psychiatry. J. Ment. Health Policy Econ. 6(4), 193–200 (2006)

    Google Scholar 

  80. A. Smith, The Fifteenth Most Serious Health Problem in the WHO Perspective (IFHOH World Congress, Helsinki, 2004)

    Google Scholar 

  81. J. Sowers, Obesity and cardiovascular disease. Clin. Chem. 44(8), 1821–1825 (1998)

    Article  Google Scholar 

  82. M. Stanisławska, B. Janasik, M. Trzcinka-Ochocka, Assessment of occupational exposure of welders based on determination of fumes and their components produced during stainless steel welding. Med. Pr. 62(4), 359–368 (2011)

    Google Scholar 

  83. G.B. Stewart, K. Mengersen, N. Meader, Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions. Res. Synth. Methods 5(1), 1–12 (2014)

    Article  Google Scholar 

  84. R. Sturm, The effects of obesity, smoking, and drinking on medical problems and costs. Health Aff. 21, 245–253 (2002)

    Article  Google Scholar 

  85. R. Sturm, K.B. Wells, Does obesity contribute as much to morbidity as poverty and smoking? J. Public Health 115, 229–235 (2001)

    Article  Google Scholar 

  86. M.S. Taitel, V. Haufle, D. Heck, R. Loeppke, D. Fetterolf, Incentives and other factors associated with employee participation in health risk assessments. J. Occup. Environ. Med. 50(8), 863–872 (2008)

    Article  Google Scholar 

  87. C. Tennant, Work-related stress and depressive disorders. J. Psychosom. Res. 51(5), 697–704 (2001)

    Article  Google Scholar 

  88. M. Thun, J. Henley, L. Apicella, Epidemiologic studies of fatal and nonfatal cardiovascular disease and ETS from spousal smoking. Environ. Health Perspect. 107, 841–846 (1999)

    Google Scholar 

  89. F.E. Thurston, The worker’s ear: a history of noise-induced hearing loss. Am. J. Ind. Med. 56(3), 367–377 (2012)

    Article  Google Scholar 

  90. S. Torp, H. Vinje, Is workplace health promotion research in the Nordic countries really on the right track? Scand. J. Public Health 42, 74–81 (2014)

    Article  Google Scholar 

  91. L.A. Tucker, G.M. Friedman, Obesity and absenteeism: an epidemiologic study of 10,825 employed adults. Am. J. Health Promot. 12, 202–207 (1998)

    Article  Google Scholar 

  92. W. Watson, J. Gauthier, The viability of organizational wellness programs: an examination of promotion and results. J. Appl. Soc. Psychol. 33(6), 1297–1312 (2003)

    Article  Google Scholar 

  93. World Health Organisation, Constitution Principles (WHO, Geneva, 1946)

    Google Scholar 

  94. World Health Organisation (WHO), Occupational and community noise. Fact sheet Number 258 (WHO, Geneva, 2001)

    Google Scholar 

  95. World Health Organisation (WHO), The World Health Report: Reducing Risks, Promoting Healthy Life (WHO, Geneva, 2002)

    Google Scholar 

  96. P.P. Wu, J. Pitchforth, K. Mengersen, A hybrid queue-based Bayesian network framework for passenger facilitation modelling. Transp. Res. Part C: Emerg. Technol. 46, 247–260 (2014)

    Article  Google Scholar 

  97. Y. Yamada, M. Ishizaki, I. Tsuritani, Prevention of weight gain and obesity in occupational populations: a new target of health promotion services at worksites. J. Occup. Health 44, 373–384 (2002)

    Article  Google Scholar 

  98. S. Yamato, Y. Nakamura, Happy workplace program: workplace health promotion program driven by Thai Health Promotion Foundation. J. Occup. Health 56(3), 87–89 (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kerrie L. Mengersen .

Editor information

Editors and Affiliations

Appendices

Appendix 1

1.1 Healthy Worker Literature Survey

The following table summarises selected literature that identifies occupational associations with health outcomes among workers.

Health outcome

Occupational associations

Obesity

• Around 2/3 of Australians are overweight or obese, and the proportion is growing [5].

• The economic costs of being overweight in the workplace have been shown to be higher than those of smoking, drinking, and poverty [26, 67, 68].

• Increases risk of hypertension, cardiovascular diseases, asthma, musculoskeletal disorders, some cancers [21, 62].

• Modifies response to occupational stress, immune response to chemical exposures, and risk of disease from occupational neurotoxins [62].

• Modifies intensity of response to various occupational hazards including heat exhaustion, pesticide exposure, accidents with equipment operators, and respiratory and physiological strain during hard physical work [31].

• Reduces effectiveness of personal respirator tests, protective equipment and clothing, particularly in hot and humid conditions [62].

• Increases absenteeism [49, 62, 73].

• Increases incidence of sick leave [13, 61]

• Increases presenteeism [26].

• Occupational stress and fatigue increases behaviours associated with weight gain [77].

• Augments endocrine factors related to weight gain caused by psychological strain [77].

Musculoskeletal Disorders

• Encompasses a variety of inflammatory and degenerative conditions involving muscles, tendons, ligaments, joints, peripheral nerves and supporting blood vessels

• Can be caused by one acute traumatic event, or by chronic stress over a period of time due to repetitive use [58].

• Muscular stress due to lifting, carrying, lowering, and handling of objects as well as from other strenuous physical movements [58].

• Repetitive movements, excessive loading, muscle overuse and vibration are specific activities often associated with a heightened risk of musculoskeletal diseases [62].

• Exacerbated by jobs that demand excessive workloads and high responsibilities, time pressures, insufficient rest breaks, and inadequate resources and workplace support and resulting in increased injury risk from fatigue, poor posture, and stress [42].

Health outcome

Occupational associations

Cardiovascular Disease

• Encompasses a range of disorders including heart disease and circulatory conditions.

• A major cause of death globally [65].

• Air pollution, including short and long term exposure to gases, chemicals and particulate matter, can potentially increase the risk of heart disease. This is exacerbated by the well-established relationship between smoking, both active and passive, and heart disease and stroke [12, 30, 71].

• Occupational stress can increase the risk of cardiovascular disease [29, 35, 47].

• Impact of occupational cardiovascular disease on absenteeism and presenteeism, but this is not trivial [41]. Altering risk factors such as diet, exercise and smoking can aid in preventing the onset of various cardiovascular diseases [4, 28, 43].

Noise-induced hearing loss

• Noise exposure has a range of undesirable effects including elevated blood pressure, reduced performance, sleeping difficulties, annoyance and stress, temporary shift in the hearing threshold, tinnitus and noise-induced hearing loss (NIHL) [55].

• Exposure to excessive noise at the workplace can cause NIHL, also known as industrial deafness [58].

• The extent of hearing loss can be affected by the level of noise and the length of exposure [52, 55] and by the type of exposure [46].

• NIHL impedes spoken communication and can cause social isolation and stress [55, 60].

• Hearing loss is the second most self reported occupational disease [52].

Respiratory Diseases

• Various respiratory diseases have been associated with workplaces, including bronchitis, asthma, upper and lower respiratory illness, chronic obstructive pulmonary disease, lung cancer, pneumoconiosis [10, 20].

• Agents in the workplace that can exacerbate or cause several respiratory diseases include pesticides, herbicides, dust, lead, fumes, chemicals, gases, faulty air conditioners, particulates and gases emitted from fire and other activities, emissions from furnishings, and so on [10, 20].

• Occupational dust is a significant contributor to the development of bronchitis, asthma and other respiratory illnesses [20, 53].

• Exposure to dust in the workplace is also associated with chronic obstructive pulmonary disease with potential for continued development of the disease many years after exposure [10].

• There are also numerous respiratory carcinogens including asbestos, arsenic, radon, silica, chromium, cadmium, nickel and beryllium [10].

• Asbestos-related disorders and industrial bronchitis and asthma are respiratory diseases that have been amongst the most common occupational diseases, and silicosis and pneumoconiosis have been reported in US coal workers [20].

Health outcome

Occupational associations

Cancers

• A variety of cancers are reportedly associated with occupational carcinogens, including lung, bone, liver, thyroid, bladder, skin and leukaemia [33].

• Well recognised carcinogenic agents include asbestos, silica, nickel, chromium, arsenicals, vinyl chloride, and halo ethers as well as ionising and solar radiation [33].

Mental Health Disorders

• Poor mental health among workers is pervasive [14].

• It can lead to work impairment [37, 40], reduced job commitment and satisfaction [38].

• Anxiety disorders can be more costly than alcohol-related disorders due to their higher frequency rate [64].

• Occupational factors that can lead to poor mental health include long hours [32, 70], shift work [17, 25], low job control and high work demand [70].

• Traumatic events associated with work related incidents, harassment, bullying and exposure to violence have also been linked to mental disorders [58].

• Occupational stress can lead to absenteeism, loss of productivity, unemployment, social impairment and a high use rate of health care [16].

Alcohol-related Disorders

• Alcohol affects hepatic and pancreatic systems [23, 34] and is also related to increased blood pressure, an increased risk of developing certain cancers, and cerebral dysfunction [23].

• Excessive alcohol consumption is related to poor health, resulting in absenteeism and presenteeism. It has also been linked with late arrival at work and reduced promotion success [34].

Appendix 2

1.1 Workplace Wellness Literature Survey

1.1.1 Definition of Wellness

Wellness is a balance of positive mental, physical and social health. It is variously defined, for example by the World Health organization as a “state of complete physical, mental and social-wellbeing and not merely the absence of disease or infirmity” [75], or “the process and state of a quest for maximum human functioning that involves the body, mind, and spirit” [51]. Models for wellness also exist, such as the Indivisible Self Model [50] which comprises five components, namely The Essential Self, The Creative Self, The Coping Self, The Social Self and The Physical Self.

1.1.2 Wellness Programs: Case Studies

The following table provides a summary of the wellness programs surveyed for the purposes of developing the Workplace Wellness BN. Numbers in brackets refer to number of programs.

Country

Aims

Methods

Outcomes

Australia:

No. programs surveyed (9).

No. programs that detailed:

 - purpose (7)

 - methods (9)

 - outcomes (7)

• Improved physical health and wellbeing of employees (5)

• Reduced risk of lifestyle disease (3)

• Save money, improve productivity, improve staff relationships, reduce stress, reduce absenteeism, provide information to employees on benefit of a healthy lifestyle, improve quality of life, ensure employees are fit to work (≥ 2)

• Comprehensive health assessment of each employee (7)

• Needs assessment and information sessions on healthy lifestyle (5)

• Exercise programs, financial support to participate in community events (3)

• Marketing of events outside the program, workplace audit, meditation classes, health challenges (2).

• Reduced sedentary category (4)

• Improved blood pressure, energy, eating habits and staff morale, decreased stress levels (3)

• Increase in employees in healthy weight range, increase in employees in ideal category for total cardiac risk, increased health knowledge, improved physical health, enhanced motivation, improved mental health, better staff relationships, increased job satisfaction (2)

USA:

No. programs surveyed (8).

No. programs that detailed:

 - purpose (5)

 - methods (6)

 - outcomes (7)

• Reduction of tobacco intake (4)

• Reduction of stress (3)

• Improve exercise, improve diet, manage employee weight, improve employee fitness, reduce business costs (2)

• Tobacco cessation program (6)

• Nutrition classes (4)

• On-site exercise facilities, weight control programs, health services, free health screenings (3)

• Educational material on health, stress management programs, fitness and activity programs, vaccinations, wellness magazines or newsletters, incentive programs, fitness classes (2)

• Saved money (7)

• Reduced absenteeism (4)

• Reduced weight, cholesterol, smoking and blood pressure (2)

• Increased productivity, improvements in nutrition and emotional health, increased exercise, decreased alcohol use (≥ 1)

UK:

No. programs surveyed (7).

No. programs that detailed:

 - purpose (0)

 - methods (7)

 - outcomes (7)

N/A

• Smoking cessation classes and stress interventions (4)

• Massage sessions, healthy eating options at work, fitness classes, weight management courses, discounts at local gyms, blood pressure testing, counselling services (3)

• Pedometer use (2)

• Decrease in staff absence (5)

• Decrease in staff turnover, increase in corporate image, decrease in risky behaviour including smoking cessation, increased physical activity (3)

• Increased employee engagement (2)

1.1.3 Types of Wellness Initiatives

Wellness initiatives have been categorised in many ways over many years. For example, Gebhardt and Crump [27] separated workplace wellness programs into three functional levels. Level one involves awareness programs such as newsletters, health fairs, screening sessions, posters, flyers and educational classes. These are not solely aimed at improving participants’ health or instantiating long term behavioural change, but are aimed at raising awareness of the consequences of unhealthy behaviours. Level two programs aim for behaviour and lifestyle modification and include self-administered fitness programs, memberships at local fitness facilities, classes related to proper performance of physically demanding work tasks, etc. Level three programs aim to create an environment that supports the sustainability of new healthy behaviours, for example via the provision of equipment, space or locker facilities at the worksite, availability of healthy foods and the removal of unhealthy temptations.

This historic categorisation generally conforms to more recent classifications of wellness initiatives. For example, Mattke et al. [45] performed a cluster analysis of a large dataset and identified five common configurations of workplace wellness programs that offered different levels of service for health risk screening, lifestyle management to reduce health risks and encourage healthy lifestyles, and chronic disease management.

Of the Australian case studies examined, a large proportion were level one programs, with the most popular being health and needs assessments. Information sessions on healthy lifestyle were also very popular, followed by marketing of the program audits of the workplace, health risk screening and marketing of events outside the program. Level two programs in Australia most commonly included: exercise programs; financial support to participate in community events; challenges and meditation sessions. None of the Australian case studies examined included any level three wellness programs.

In the United States wellness programs run were evenly distributed between level one and two programs, with the most popular level one programs: nutrition classes, free health screenings, educational materials on health and wellness newsletters or magazines. Level two programs included tobacco cessation programs; weight control programs, fitness classes and fitness and activity programs. The only level three program was the provision of onsite exercise facilities.

In the United Kingdom studies there was a greater proportion of level two programs, with only one level one and level three program offered by more than one company. The level one program was blood pressure testing. The most common level two programs included smoking cessation classes, fitness classes, discounted bicycle purchase, weight management courses, discounts at local gym, counselling services and the provision of pedometers. The level three option included was healthy eating options at work.

1.1.4 Characteristics of Successful Wellness Initiatives

In order to evaluate the success of a work-based wellness programme, it is necessary to establish what is used to define a program as either a success or a failure. Success can be defined in terms of financial, health and social benefits, and within different timeframes. For example, results from the 2004 National Worksite Health Promotion (NWHP) Survey revealed that the most commonly used definition of success was employee feedback, followed by employee participation, workers’ compensation costs, health care claims costs and reduced absenteeism, whereas the most common barriers to success were lack of employee interest, lack of staff resources and funding, lack of participation of high-risk employees and lack of support from upper level management.

These findings have been echoed in later surveys, for example, in the comprehensive studies of U.S. employers [45] and in U.K businesses [24]. The latter study reported reduced sickness absence (in 82% of programs surveyed), reduced staff turnover (33%), reduced accidents and injuries (29%), increased employee satisfaction (25%), reduced resource allocation (16%), increased company profile (15%), increased productivity (15%), and increased health and welfare (15%). Each of these was linked to positive economic contributions.

Similar benefits were observed among the successful wellness programs surveyed in the present paper. These included integration of the program into business strategy and company culture, the inclusion of a full time or part time program co-ordinator, support from upper level management, social support, the use of incentives to increase participation in the program and the convenience and accessibility of the program.

The following table provides a selection of references to literature supporting these findings.

Factors that increase the likelihood of success of a workplace wellness initiative:

• The program is woven into the business strategy and culture of the company; a program is more vulnerable if it is considered to be a luxury rather than a necessity [11]

• Strong management support for the program; the more an individual perceives support from their supervisor, the higher their participation [63].

• Employee involvement in the program design and implementation [69]

• A full time or part time coordinator with the ability to motivate participation [27]

• Use of incentives to increase employee participation [69]. Incentives work positively because employees prefer to feel that they are acting of their own volition rather than being forced to act by management policies [11].

• Accessibility and convenience of a program. In order to ensure maximum accessibility making a program either free or low cost to participants must be a priority [11].

• Onsite integration of wellness programs, making participation more straightforward and convenient for employees [11].

Factors that have contentious influence:

• Co-worker support is reported in some studies to be an important influential factor on participation in health-related and fitness activities for all employee subgroups [19] but not in other studies [2, 63].

• Mattke et al. [45] found little evidence of the benefit of employee participation in the management aspects of wellness programs.

 

A final method of determining success is to examine the purpose of the program as set out by the company and then examining the achievements that were reported by the company. To be considered successful the company must as a minimum achieve the majority of the points set out in its “purpose of program statement”. For the Australian case studies, five of the nine companies detailed their purpose of program as well as the achievements. Based upon the criteria of a successful program, two of the five Australian programs that listed both their purpose of program as well as the achievements of their program can be labelled as successful. Four of the eight case studies examined from the United States detailed both their purpose of program and achievements. Three of these four programs can be classed as successful programs based on the criteria of a successful program. Three companies reportedly achieved everything they set out to achieve, saved money and improved productivity, although only one of these provided data on specific outcomes to support their claims. Success of the United Kingdom programs could not be evaluated due to the lack of recorded information on their purpose of program.

Appendix 3

1.1 Quantification of the Bayesian Networks

The Healthy Worker and Workplace Wellness BNs were quantified as follows. The quantification is intended for exposition purposes only. The resultant probabilities should not be interpreted medically, socially or economically, nor with respect to particular workplaces or wellness programs. However, the structure of the Healthy Worker network and its quantification could be targeted to a particular workplace cohort if data about the associated personal and lifestyle factors, health outcomes and workplace risks were made available. Similarly, the Workplace Wellness network could be structured and quantified using program-specific information, resulting in interpretable probabilities of success.

For the Healthy Worker model, each node was categorised as ‘yes’ or ‘no’. All exposures and factors at the top of the network were set to equal probabilities for each category and each health outcome was assigned equal weight. Thus the probability of a health outcome was determined by the number of detrimental factors affecting the node (depicted as directed arrows to the node) divided by the total number of factors affecting the node. Exceptions to this rule were made for respiratory diseases and acute & chronic diseases. Since the survey indicated that exercise heightens the inhalation of unwanted air pollution, exercise was included as a factor when combined with poor quality air, but was ignored for good quality air. However, since exercise was reportedly not as influential a risk factor as smoking, a weight of 0.2 of developing a respiratory disease was assigned to exercise alone, 0.4 to both smoking and poor air quality, 0.6 to performing strenuous activity and poor air quality, and 1.0 if the worker also smoked. For the node representing acute & chronic diseases, it was determined that if a worker had three or more diseases then they were deemed to have a higher chronic disease rate. Having two diseases was given a 2/3 weighting; having 1 disease was given a 1/3 weighting and no disease was given a 0 weighting. While this approach simplified the quantification of the network, the many nodes linking to the chronic and acute nodes meant that it was relatively easy to obtain a poor score on the chronic, acute, and overall worker health nodes.

The systems model for the workplace wellness programs was quantified in a similar manner. Probabilities were then assigned to each node, based on these information sources and on the other nodes in the model. For each of the nodes such as participation in program, physical, behavioural, and return on investment, the probability of a positive outcome was directly proportional to the number of positive outcomes in the parent nodes, with the maximum value set to 0.95 if all parent nodes were positive and the minimum value set to 0.05 if all parent nodes were ‘negative’. For those with two parent nodes, such as increase in wellness and accessibility of program, the probability of a positive outcome was set to 0.80 if both parent nodes were positive and to 0.2 if both parent nodes were negative.

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Davis, G., Moloney, E., da Palma, M., Mengersen, K.L., Harden, F. (2020). Workplace Health and Workplace Wellness: Synergistic or Disconnected?. In: Mengersen, K., Pudlo, P., Robert, C. (eds) Case Studies in Applied Bayesian Data Science. Lecture Notes in Mathematics, vol 2259. Springer, Cham. https://doi.org/10.1007/978-3-030-42553-1_12

Download citation

Publish with us

Policies and ethics