Environmental Science and Pollution Research

, Volume 22, Issue 10, pp 7612–7621 | Cite as

A study on the risk perception of light pollution and the process of social amplification of risk in Korea

  • Kyung Hee Kim
  • Jae Wook ChoiEmail author
  • Eunil Lee
  • Yong Min Cho
  • Hyung Rae Ahn
Research Article


In this study, the risk perception level of each light pollution type was analyzed, and the effects of the variables (e.g., psychometric paradigm factor, trust in the government, etc.) on the process of the increase in the risk perception were analyzed. For the sample population (1096 persons) in Korea, the risk perception levels of each light pollution type and other environmental and health risk factors were compared, and the relative magnitude was examined. In addition, to test which variables affect the group with high-risk perception of each light pollution type, a logistic regression analysis was performed. For the group with highest risk perception of light pollution, the odds ratios (OR) of all psychometric paradigms (excluding controllability) increased compared to those of the group with low-risk perception. Additionally, the level showing the acquisition of information from the media and the recollection level of media criticism on each light pollution type showed a statistically significant increase. Especially, the risk perception of light trespass increased as trust in the government decreased. The significance of this study includes the finding that the public’s risk perception of light pollution was significantly affected by the psychometric paradigm factors. Moreover, this study analyzed the differences of the variables that affect the increase in the risk perception of each light pollution type and provided a theoretical framework that can practically reflect the strategy for the risk communication of light pollution.


Light pollution Risk perception Light trespass Over-illumination Glare Light clutter 



This work was supported by a future environmental R&D grant funded by the Korean Environmental Industry and Technology Institute (RE201206020).

Conflict of interest

The authors declare that they have no conflicts of interest.


  1. Agha S (2003) The impact of a mass media campaign on personal risk perception, perceived self-efficacy and on other behavioural predictors. AIDS Care 15(6):749-762.Google Scholar
  2. Anisimov VN, Vinogradova IA, Panchenko AV, Popovich IG, Zabezhinski MA (2012) Light-at-night-induced circadian disruption, cancer and aging. Curr Aging Sci 5(3):170–177CrossRefGoogle Scholar
  3. Baird BN (1986) Tolerance for environmental health risks: the influence of knowledge, benefits, voluntariness, and environmental attitudes. Risk Anal 6(4):425–435CrossRefGoogle Scholar
  4. Chepesiuk R (2009) Missing the dark health effects of light pollution. Environmental Health Perspectives 117(1):A20-27 (last accessed 10 April 2014)
  5. Cohen L, Manion L, Morrison K (2007) Research methods in education 6th edition. Routledge, USA and CanadaGoogle Scholar
  6. Crittenden KS (1983) Sociological aspects of attribution. Annu Rev Sociol 9:425–446CrossRefGoogle Scholar
  7. Di Giuseppe G, Abbate R, Albano L, Marinelli P, Angelillo IF (2008) A survey of knowledge, attitudes and practices towards avian influenza in an adult population of Italy. BMC Infect Dis 8:36CrossRefGoogle Scholar
  8. European Commission (2005) Eurobarometer survey, social values, science and technology. Special Eurobarometer Report 225. (last accessed 10 April 2014)
  9. European Commission (2011) Scientific committee on emerging and newly identified health risks, health effects of artificial light. (last accessed 10 April 2014)
  10. Evans G, Durant J (1995) The relationship between knowledge and attitudes in the public understanding of science in Britain. Public Underst Sci 4:57–74CrossRefGoogle Scholar
  11. Falchi F, Cinzano P, Elvidge CD, Keith DK, Haim A (2011) Limiting the impact of light pollution on human health, environment and stellar visibility. J Environ Manag 92(10):2714–2722CrossRefGoogle Scholar
  12. Fischhoff B, Slovic P, Lichtenstein S (1978) How safe is safe enough? A psychometric study of attitudes towards technological risks and benefits. Policy Sci 9:127–152CrossRefGoogle Scholar
  13. Frewer L, Salter B (2002) Public attitudes, scientific advice and the politics of regulatory policy (The case of BSE). Sci Public Policy 29(2):137–145CrossRefGoogle Scholar
  14. Gooley JJ, Chamberlain K, Smith KA, Khalsa SBS, Rajaratnam SMW, Reen EV, Zeitzer JM, Czeisler CA, Lockley SW (2011) Exposure to room light before bedtime suppresses melatonin onset and shortens melatonin duration in humans. J Clin Endocrinol Metab 96(3):E463–E472CrossRefGoogle Scholar
  15. Harris CR, Jenkins M, Glaser D (2006) Gender differences in risk assessment: why do women take fewer risks than men? Judge Decis Making 1:48–63Google Scholar
  16. International Agency for Research on Cancer (IARC) (2010) Monographs on the evaluation of carcinogenic risks to humans 98 Shiftwork, 563–754. (last accessed 10 April 2014)
  17. Jensen KK (2004) BSE in the UK: why the risk communication strategy failed. J Agric Environ Ethics 17:405–423CrossRefGoogle Scholar
  18. Kantermann T, Roenneberg T (2009) Is light-at-night a health risk factor or a health risk predictor? Chronobiol Int 26(6):1069–1074CrossRefGoogle Scholar
  19. Kasperson RE, Renn O, Slovic P, Brown HS, Emel J, Goble R, Kasperson JX, Ratick S (1988) The social amplification of risk: a conceptual framework. Risk Anal 8(2):177–187CrossRefGoogle Scholar
  20. Kim KH, Kim HJ, Song DJ, Cho YM, Choi JW (2014) Risk perception and public concerns of electromagnetic waves from cellular phones in Korea. Bioelectromagnetics 35(4):235–244CrossRefGoogle Scholar
  21. Kloog I, Haim A, Stevens RG, Barchana M, Portnov BA (2008) Light at night co-distributes with incident breast but not lung cancer in the female population of Israel. Chronobiol Int 25(1):65–81CrossRefGoogle Scholar
  22. Kretschmer V, Schmidt KH, Griefahn B (2013) Bright-light effects on cognitive performance in elderly persons working simulated night shifts: psychological well-being as a mediator? Int Arch Occup Environ Health 86(8):901–914CrossRefGoogle Scholar
  23. Kronfeld-Schor N, Einat H (2012) Circadian rhythms and depression: human psychopathology and animal models. Neuropharmacol 62(1):101–114CrossRefGoogle Scholar
  24. Lang JT, Hallman WK (2005) Who does the public trust? The case of genetically modified food in the United States. Risk Anal 25(5):1241–1252CrossRefGoogle Scholar
  25. Leikas S, Lindeman M, Roininen K, Lähteenmäki L (2007) Food risk perceptions, gender, and individual differences in avoidance and approach motivation, intuitive and analytic thinking styles, and anxiety. Appetite 48(2):232–240CrossRefGoogle Scholar
  26. Lyytimaki J, Tapio P, Assmuth T (2012) Unawareness in environmental protection: the case of light pollution from traffic. Land Use Policy 29:598–604CrossRefGoogle Scholar
  27. Miller MW (2006) Apparent effects of light pollution on singing behavior of American Robins. Condor 108(1):130–139CrossRefGoogle Scholar
  28. Millstone E, Zwanenberg PV (2002) The evolution of food safety policy-making institutions in the UK, EU and codex alimentarius. Soc Policy Adm 36:593–609CrossRefGoogle Scholar
  29. Morgan MG, Slovic P, Nair I, Geisler D, MacGregor D, Fischhoff B, Lincoln D, Florig K (1985) Powerline frequency electric and magnetic fields: a pilot study of risk perception. Risk Anal 5(2):139–149CrossRefGoogle Scholar
  30. Munch M, Kobialka S, Steiner R, Oelhafen P, Wirz-Justice A, Cajochen C (2006) Wavelength-dependent effects of evening light exposure on sleep architecture and sleep EEG power density in men. Am J Physiol Regul Integr Comp Physiol 290:R1421–R1428CrossRefGoogle Scholar
  31. Munn T, Timmerman P, Whyte A (1999) Emerging environmental issues: a global perspective of SCOPE. Ambio 28:464–471Google Scholar
  32. Petty RE. Cacioppo JT (1986) Communication and persuasion: central and peripheral routes to attitude change. New YorkGoogle Scholar
  33. Schernhammer ES, Laden F, Speizer F, Willett EC, Hunter DJ, Kawachi I, Fuchs CS, Colditz GA (2003) Night-shift work and risk of colorectal cancer in the nurses’ health study. J Natl Cancer Inst 4:95(11):825–828CrossRefGoogle Scholar
  34. Shepherd R, Barker G, French S, Hart A, Maule J, Cassidy A (2006) Managing food chain risks: integrating technical and stakeholder perspectives on uncertainty. J Agric Econ 57(2):313–327CrossRefGoogle Scholar
  35. Siegrist M (2000) The influence of trust and perceptions of risks and benefits on the acceptance of gene Technology. Risk Anal 20(2):195–204CrossRefGoogle Scholar
  36. Sjöberg L, Drottz-Sjöberg BM (1991) Knowledge and risk perception among nuclear power plant employees. Risk Anal 11(4):607–618CrossRefGoogle Scholar
  37. Slovic P (1987) Perceptions of risk. Science 236:280–285CrossRefGoogle Scholar
  38. Snyder LB, Rouse RA (1995) The media can have more than an impersonal impact: the case of AIDS risk perceptions and behavior. Health Commun 7(2):125–145CrossRefGoogle Scholar
  39. Vandewalle G, Schmidt C, Albouy G, Sterpenich V, Darsaud A, Rauchs G, Berken PV, Balteau E, Degueldre C, Luxen A, Maquet P, Dijk DJ (2007) Brain responses to violet, blue, and green monochromatic light exposures in humans: Prominent Role of Blue Light and the Brainstem. PLoS ONE 2(11):e1247CrossRefGoogle Scholar
  40. Wahlberg AAF, Sjoberg L (2000) Risk perception and the media. J Risk Res 3:31–50CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Kyung Hee Kim
    • 1
  • Jae Wook Choi
    • 1
    • 2
    Email author
  • Eunil Lee
    • 2
    • 3
  • Yong Min Cho
    • 1
  • Hyung Rae Ahn
    • 1
  1. 1.Institute for Occupational and Environmental HealthKorea UniversitySeoulRepublic of Korea
  2. 2.Department of Preventive Medicine, College of MedicineKorea UniversitySeoulRepublic of Korea
  3. 3.Department of Environmental Health Science, Graduate School of Public HealthKorea UniversitySeoulRepublic of Korea

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