workers’ uv exposure and the subsequent impact on skin · workers’ uv exposure and the...
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Workers’ UV Exposure and the
Subsequent
Impact on Skin
Keqin (George) Jia
BMed (CHINA), GradDipEH (QUT)
(04773195)
Principal Supervisor: Professor Michael Kimlin
Associate Supervisor: Dr Thomas Tenkate
Queensland University of Technology
Faculty of Health
School of Public Health
Thesis submitted for the degree of Master of Applied Science
(HL84)
2010
KEYWORDS
Ultraviolet Radiation (UVR), UVA-sensitive dosimeter and erythemal UV-sensitive
dosimeter, erythemal, skin pigmentation, photoaging.
2
Abstract
Introduction: Excessive exposure to ultraviolet (UV) radiation from sunlight is a
causative factor in the development of skin damage and skin cancer. Little research
has been undertaken into assessing the sun exposure linking to skin damage inside
buildings or behind window glass. This project directly addressed this issue by
aiming to assess the role that UV exposure has on skin damage for indoor workers
and drivers.
Methods: Measurements of personal UV exposure using UV sensitive polymer
dosimeters were undertaken of 41 indoor workers and 3 professional drivers.
Physical measurements of skin characteristics including skin pigmentation and UV
induced skin photoaging were also determined. In addition, demographic information
along with phenotypic characteristics, sun exposure and sun protection practice
history, and history of skin damage were assessed through a questionnaire.
Results: Indoor workers typically received low doses of UV radiation. However, one
driver received a high dose (13J/cm2 UVA and 4.99 MED UVB on the arm). Age
and years residing in Australia had a positive correlation with UV induced skin
pigmentation.
The number of major sunburns before 18 years was a risk factor for skin damage in
adults. Those participants with fair skin, non-black hair and blue/green /blue-grey
eye were more likely to have skin damage related to sun exposure.
Conclusions: A person’s age, years residing in Australia, numbers of major sunburn,
skin colour, hair colour and eye colour are important factors associated with the
development of sun-related skin damage in workers.
‘Real World’ implications: 1. The number of major sunburns before 18 years was a
risk factor for skin damage in adults. This clearly confirms the importance of early
prevention. To protect the skin from extensive sun exposure for your generation
should have significance for further prevention of skin damage. 2. It is unsurprising
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that age and years residing in Australia were associated with skin damage related UV
radiation. Therefore, the general public should reinforce their sun protective
measures and check skin regularly. 3. Drivers should take sun protective measures
during their working hours between sunrise and sunset.
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Table of Contents
1 CHAPTER 1. INTRODUCTION .............................................................................................................. 12
1.1 PROJECT AIMS AND HYPOTHESES ......................................................................................................... 13
1.2 OVERVIEW OF THESIS ........................................................................................................................... 14
2 CHAPTER 2. LITERATURE REVIEW ................................................................................................. 15
2.1. SOLAR ULTRAVIOLET RADIATION ................................................................................................... 15
2.1.1 The Sun and ultraviolet radiation (UVR) ............................................................................................. 15
2.1.2 Units of UV radiation ........................................................................................................................... 16
2.1.3 The UV index ........................................................................................................................................ 19
2.1.4 Factors influencing UV irradiance ...................................................................................................... 20 2.1.4.1 Latitude and altitude ............................................................................................................................. 20 2.1.4.2 Season, the time of day and clouds ....................................................................................................... 21 2.1.4.3 Aerosols ................................................................................................................................................ 21 2.1.4.4 Ozone levels .......................................................................................................................................... 21
2.2 HEALTH IMPACTS OF UV EXPOSURE ..................................................................................................... 22
2.2.1 Effects of acute and chronic UV irradiation on the skin ...................................................................... 22 2.2.1.1 Erythema ............................................................................................................................................... 23 2.2.1.2 Tanning or melanin pigmentation ........................................................................................................ 25 2.2.1.3 Freckling, Actinic lentigines, and cutaneous melanoma risk ............................................................... 26 2.2.1.4 Melanocytic Naevi ............................................................................................................................... 26 2.2.1.5 Melanocytic skin cancer ....................................................................................................................... 27 2.2.1.6 Basal cell carcinoma (BCC) ................................................................................................................. 27 2.2.1.7 Squamous cell carcinoma (SCC) .......................................................................................................... 28
2.3 UVA RADIATION ................................................................................................................................. 28
2.3.1 UVA HEALTH IMPACTS ..................................................................................................................... 29
2.3.1.1 UVA and photoaging: ........................................................................................................................ 29
2.3.1.2 UVA and skin cancer ......................................................................................................................... 30
2.4 SUMMARY ............................................................................................................................................ 32
3 CHAPTER 3. ASSESSMENT OF UV EXPOSURE ................................................................................ 34
3.1 DOSIMETRY FOR PERSONAL UV EXPOSURE MEASURMENT ................................................................... 34 3.1.1 Polysulphone dosimeter ........................................................................................................................... 34 3.1.2 Phenothiazine/Mylar film dosimeter ........................................................................................................ 35
4 CHAPTER 4. RESEARCH METHODS ................................................................................................... 38
4.1 OVERVIEW OF RESEARCH DESIGN ......................................................................................................... 38
4.2 HUMAN RESEARCH ETHICS ................................................................................................................... 38
4.3 RECRUITMENT ...................................................................................................................................... 39
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4.4 DATA COLLECTION ............................................................................................................................... 39
4.4.1 Participant demographics .................................................................................................................... 39
4.4.2 Skin colour testing ............................................................................................................................... 41
4.4.3 Assessment of UV-induced skin damage .............................................................................................. 42 4.4.3.1 Skin pigmentation ................................................................................................................................. 42 4.4.3.2 skin photoaging ..................................................................................................................................... 43
4.4.4 Personal UV exposure measurement.................................................................................................... 44 4.4.4.1 Personal UVA dosimeter and calibration .............................................................................................. 44 4.4.4.2 Study protocol of UV exposure measurement ...................................................................................... 44
4.5 DATA MEASUREMENT AND DATA ANALYSIS ................................................................................. 45
4.5.1 Data measurement................................................................................................................................ 46 4.5.1.1 Data storage .......................................................................................................................................... 46 4.5.1.2 Data coding ........................................................................................................................................... 46 4.5.1.3 Data entry .............................................................................................................................................. 46 4.5.1.4 Data cleaning ........................................................................................................................................ 46
4.5.2 Data analysis ........................................................................................................................................ 47 4.5.2.1 Descriptive data analysis ....................................................................................................................... 47 4.5.2.2 Bivariate analyses ................................................................................................................................. 47 4.5.2.3 Multiple regressions analysis ................................................................................................................ 48
5 CHAPTER 5. RESULTS ............................................................................................................................ 49
5.1 DESCRIPTION OF THE STUDY DATA ....................................................................................................... 49
5.1.1 Participants demographics .................................................................................................................. 49
5.1.2 Characteristics of skin colour, hair colour and eye colour. ................................................................ 50
5.1.3 Sun exposure time ............................................................................................................................... 50
5.1.4 Self reported sunburn and freckling ................................................................................................... 52
5.1.5 Results from skin spectrophotometer.................................................................................................... 52
5.1.6 Sun protection measures ...................................................................................................................... 53
5.1.7 One-day sun exposure measurement and sun exposure time ............................................................... 54
5.1.8 Results from the photo damage assessment tool .................................................................................. 55 5.1.8.1 Skin pigmentation on the faces ............................................................................................................. 55 5.1.8.2 Wrinkles on the face ............................................................................................................................. 56 5.1.8.3 Red areas on the face ............................................................................................................................ 57 5.1.8.4 Texture on the workers’ face ................................................................................................................. 58
5.2 BIVARIATE ANALYSIS ........................................................................................................................... 59
5.2.1 Correlations between age and outcome variables ............................................................................... 59 5.2.1.1 Skin pigmentation ................................................................................................................................. 59 5.2.1.2 Wrinkles, red areas and texture on the face ........................................................................................... 60
5.2.2 Correlations between years residing in Australia and outcome variables ........................................... 62 5.2.2.1 Skin pigmentation ................................................................................................................................ 62 5.2.2.2 Wrinkles, red areas and texture on the face ........................................................................................... 63
5.2.3 One day UV exposure and skin damage ............................................................................................... 65
5.2.4 Comparisons of outcome variables by major sunburn groups ............................................................. 65
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5.2.4.1 SPI and SPII .......................................................................................................................................... 65 5.2.4.2 Wrinkles, red areas and texture. ............................................................................................................ 67
5.2.5 Comparisons of outcome variables by skin colour, hair colour, and eye colour groups ..................... 67 5.2.5.1 SPI and SPII .......................................................................................................................................... 67 5.2.5.2 Comparisons of wrinkles, red areas and texture by skin colour groups, hair colour groups and
eye colours groups ............................................................................................................................................ 69 5.2.6 Comparisons of outcome variables by gender ..................................................................................... 69
5.2.7 Correlations between the density of freckling and outcome variables ................................................. 70
5.2.8 Comparisons of outcome variables by the place where was born. ....................................................... 71
5.3 MULTIVARIABLE REGRESSION ................................................................................................... 73
5.3.1 Rationale for variables included in multivariable regression analysis ................................................ 73
5.3.2 Results of Multivariable regression analysis for determinants of SPI on the face ............................... 74
5.3.3 Results of Multivariable regression analysis for determinants of SPII on the face .............................. 75
5.3.4 Results of Multivariable regression analysis for determinants of wrinkles on the face ....................... 76
5.3.5 Results of Multivariable regression analysis for determinants of red areas on the face ...................... 77
5.3.6 Results of Multivariable regression analysis for determinants of red texture on the face ................... 77
CHAPTER 6. DISCUSSION AND CONCLUSION ................................................................................... 79
6.1 ONE DAY SUN EXPOSURE AND SKIN DAMAGE ................................................................................. 79
6.2 AGE, YEARS RESIDING IN AUSTRALIA AND THE PLACE WHERE WAS BORN VERSUS OUTCOME
VARIABLE ................................................................................................................................................... 81
6.2.1 Age, years residing in Australia and the place where was born Versus SPI and SPII ......................... 81
6.2.2 Age, years residing in Australia and the place where was born versus photoaging ............................ 82
6.3 SUNBURNS RELATED TO SPI, SPII. ...................................................................................................... 82
6.4 DIFFERENCE BETWEEN GROUPS OF SKIN COLOUR, HAIR COLOUR AND EYE COLOUR ............................. 83
6.5 STUDY LIMITATIONS & STUDY STRENGTHS .......................................................................................... 84
6.5.1 Study Limitations .................................................................................................................................. 84
6.5.2 Study strengths .................................................................................................................................... 85
6.6 THE STUDY IMPLICATIONS .................................................................................................................... 86
6.7 RECOMMENDATIONS FOR FUTURE RESEARCH ....................................................................................... 87
6.8 CONCLUSION ........................................................................................................................................ 87
6 APPENDICES ............................................................................................................................................. 90
APPENDIX 1. THE LETTER TO INDOOR WORKERS FROM QUT ..................................................................... 90
APPENDIX 2. INFORMATION FOR PROFESSIONAL DRIVERS ................................................................... 91
APPENDIX 3. PARTICIPANT INFORMATION SHEET .......................................................................... 92
APPENDIX 4. CONSENT FORM ................................................................................................................ 96
APPENDIX 5. QUESTIONNAIRE FOR INDOOR WORKERS ............................................................................... 98
APPENDIX 6. QUESTIONNAIRE FOR PROFESSIONAL DRIVERS .................................................................... 111
APPENDIX 7. PERSONAL CHARACTERISTICS ............................................................................................. 124
APPENDIX 8. HOW TO MEASURE SUN EXPOSURE TIME .............................................................................. 126
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APPENDIX 9. UV EXPOSURE DOSIMETRY AND CALIBATION ...................................................................... 127
APPENDIX 10. CHECKLIST FORM .............................................................................................................. 130
APPENDIX 11. CODEBOOK ....................................................................................................................... 131
TABLES
TABLE 1. THE FITZPATRIK CLASSIFICATION OF SKIN TYPE (FITZPATRICK, 1975) ....................................... 17
TABLE 2. UV RADIATION EXPOSURE CATEGORIES (WHO, 2002) ............................................................... 19
TABLE 3. PARTICIPANTS DEMOGRAPHICS ................................................................................................... 50
TABLE 4. SELF REPORTED SKIN, HAIR AND EYE COLOUR ........................................................................... 50
TABLE 5. SUNBURNS BEFORE 18 YEARS AND SUNBURNS AFTER 18 YEARS ................................................. 52
TABLE 6. DENSITY OF FRECKLING ON THE FACE, FOREARMS AND SHOULDER DURING ADOLESCENCE ....... 52
TABLE 7. RESULTS OF SKIN SPECTROPHOTOMETER (“L*” = LIGHTNESS: RANGE 0-100) ............................. 53
TABLE 8. SUN PROTECTION MEASURES ...................................................................................................... 53
TABLE 9. UVA (J/M2) EXPOSURE ON THE LEFT, RIGHT ARMS AND ON THE HEAD ....................................... 54
TABLE 10. UVB (MED) EXPOSURE ON THE LEFT, RIGHT ARMS AND ON THE FACE ..................................... 54
TABLE 11. SPI ON THE FACE....................................................................................................................... 55
TABLE 12. SPII ON THE FACE ..................................................................................................................... 55
TABLE 13. WRINKLES ON THE FACE ........................................................................................................... 57
TABLE 14. RED AREAS ON THE FACE .......................................................................................................... 58
TABLE 15. TEXTURE ON THE FACE ............................................................................................................. 59
TABLE 16. CORRELATIONS BETWEEN YEARS RESIDING IN AUSTRALIA AND WRINKLES, RED AREAS
AND TEXTURE ............................................................................................................................................. 65
TABLE 17. COMPARISONS SPI AND SPII BY MAJOR SUNBURN GROUPS ...................................................... 65
TABLE 18. COMPARISONS OF SPI AND SPII BY SKIN COLOUR GROUPS ....................................................... 67
TABLE 19. COMPARISIONS OF SPI AND SPII BY HAIR COLOUR GROUPS ..................................................... 68
TABLE 20. COMPARISIONS OF SPI AND SPII BY EYE COLOUR GROUPS ....................................................... 68
TABLE 21. COMPARISONS OF SPI AND SPII BY GENDER ............................................................................. 69
TABLE 22. COMPARISONS OF RED AREAS BY GENDER ................................................................................ 69
TABLE 23. COMPARISONS OF SPI AND SPII BY THE PLACE WHERE WAS BORN ........................................... 73
TABLE 24. REGRESSION RESULT FOR POSSIBLE DETERMINANTS OF SPI ON THE FACE ................................ 75
TABLE 25. REGRESSION RESULT FOR POSSIBLE DETERMINANTS OF SPII ON THE FACE .............................. 76
TABLE 26. REGRESSION RESULT FOR POSSIBLE DETERMINANTS OF WRINKLES ON THE FACE ..................... 76
TABLE 27. REGRESSION RESULT FOR POSSIBLE DETERMINANTS OF RED AREAS ON THE FACE .................... 77
TABLE 28. REGRESSION RESULT FOR POSSIBLE DETERMINANTS OF TEXTURE ON THE FACE ....................... 78
TABLE 29. EXAMPLE FOR ONE DAY SUN EXPOSURE IN QUESTIONNAIRE ................................................... 126
FIGURES
FIGURE 1. THE ELECTROMAGNETIC SPECTRUM (LUCAS, 2002) .................................................................. 16
FIGURE 2. FITZPATRICK SKIN TYPE (FITZPATRICK, 1988) .......................................................................... 18
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FIGURE 3. ACUTE UV AND CHRONIC UV EFFECTS ON SKIN (MATSUMURA, 2004) ..................................... 23
FIGURE 4. A REFERENCE ACTION SPECTRUM FOR ULTRAVIOLET INDUCED ERYTHEMA IN HUMAN SKIN
(CIE, 1987) ................................................................................................................................................ 24
FIGURE 5. THE STRUCTURAL UNIT OF POLYSULPHONE ............................................................................... 34
FIGURE 6. PHENOTHIAZINE/MYLAR DOSIMETER MADE FROM AUSSUN RESEARCH LAB. ........................... 36
FIGURE 7. PHENOTHIAZINE DOSIMETERS SUMMER CALIBRATION CURVE .................................................. 36
FIGURE 8. A STANDARD FRECKLING CHART (HARRISON, 1994) ................................................................. 41
FIGURE 9. SKIN SPECTROPHOTOMETER: KONICA MINOLTA CM-2500D .................................................... 42
FIGURE 10. PHOTO DAMAGE ASSESSMENT TOOL (CANFIELD, 2007) .......................................................... 43
FIGURE 11. UVA DOSIMETER AND ERYTHEMAL UV DOSIMETER IN ONE HOLDER ...................................... 44
FIGURE 12. UVA DOSIMETERS AND ERYTHEMAL UV DOSIMETERS ............................................................ 45
FIGURE 13. AGE DISTRIBUTION OF ALL PARTICIPANTS ............................................................................... 49
FIGURE 14. TIME OUTSIDE DURING WEEKDAYS .......................................................................................... 51
FIGURE 15. TIME OUTSIDE DURING WEEKENDS .......................................................................................... 51
FIGURE 16. SPI ON THE FACE ..................................................................................................................... 55
FIGURE 17. SPII ON THE FACE .................................................................................................................... 56
FIGURE 18. WRINKLES ON THE FACE ......................................................................................................... 57
FIGURE 19. RED AREAS ON THE FACE ........................................................................................................ 58
FIGURE 20. TEXTURE ON THE FACE ............................................................................................................ 59
FIGURE 21. THE SCATTERPLOT OF AGE AND SPI ........................................................................................ 60
FIGURE 22. THE SCATTERPLOT OF AGE AND SPII ....................................................................................... 60
FIGURE 23. THE SCATTERPLOT OF AGE AND WRINKLES .............................................................................. 61
FIGURE 24. THE SCATTERPLOT OF AGE AND RED AREAS ............................................................................. 61
FIGURE 25. THE SCATTERPLOT OF AGE AND TEXTURE ................................................................................ 61
FIGURE 26. THE SCATTERPLOT OF YEARS RESIDING IN AUSTRALIA AND SPI ............................................. 62
FIGURE 27. THE SCATTERPLOT OF THE YEARS RESIDING IN AUSTRALIA AND SPII ..................................... 63
FIGURE 28. THE SCATTERPLOT OF THE YEARS RESIDING IN AUSTRALIA AND WRINKLES ............................ 64
FIGURE 29. THE SCATTERPLOT OF THE YEARS RESIDING IN AUSTRALIA AND RED AREAS ........................... 64
FIGURE 30. THE SCATTERPLOT OF THE YEARS RESIDING IN AUSTRALIA AND TEXTURE .............................. 64
FIGURE 32. THE SCATTERPLOT OF THE FRECKLING AND SPI ON THE FACE ................................................. 70
FIGURE 33. THE SCATTERPLOT OF THE FRECKLES AND SPII ON THE FACE .................................................. 71
FIGURE 34. THE BOXPLOT OF THE PLACE WHERE WAS ............................................................................... 72
FIGURE 35. THE BOXPLOT OF THE PLACE WHERE WAS ............................................................................... 72
FIGURE 36. UV-1700 SPECTROPHOTOMETER ........................................................................................... 128
FIGURE 37. PS DOSIMETERS (ABOVE) AND PHENOTHIAZINE/MYLAR DOSIMETERS (BELOW) .................... 129
LIST OF REFERENCES ............................................................................................................................. 140
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Glossary of abbreviations
UVR Ultraviolet Radiation
UVA Ultraviolet A (wavelength 315 - 400nm)
UVB Ultraviolet B (wavelength 280 - 315nm)
UVC Ultraviolet C (wavelength 100 - 280nm)
MED Minimal erythemal dose
SZA Solar Zenith Angle
ARPANZA The Australian Radiation Protection and Nuclear Safety
Agency
WHO The World Health Organization
ICNIRP International Commission on Nonionizing Radiation
Protection
DU Dobson Units
IPD Immediate pigment darkening
DT Delayed tanning
MN Melanocytic naevi
MSC Melanocytic skin cancer
BCC Basal cell carcinoma
SCC Squamous cell carcinoma
DTH Delayed type hypersensitivity
PUVA Psoralen and ultraviolet A radiation
SP Skin pigmentation
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Statement of original authorship
The work contained in this thesis has not been previously submitted for a degree or
diploma at any other higher institution. To the best of my knowledge and belief, this
thesis contains no material previously published or written by another person except
where due reference is made.
Signature _____________________________
Date_______________________________
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Acknowledgements
There are many people to whom due acknowledgement must be made. It would be
impossible to name everyone, but all the help I have received has been greatly
appreciated.
First of all, I would like to express my gratitude to my primary supervisor, Prof.
Michael Kimlin. His insight, direction and experience have helped inspire me
towards further research and a career based on research. Without his encouragement,
interest and enthusiasm, I could not have completed this thesis.
Sincere thanks are also due to my Associate Supervisor, Dr Thomas Tenkate, for his
support and for the guidance he has provided throughout my research, as well as for
sharing his expertise in the Environmental health and Risk assessment and
management. He has always been encouraging and positive in his response to my
research. Again, I could not have completed this thesis without his assistance.
To the members of the AusSun Research LAB who also generously give their time to
assist with my data collection, English checking and have provided support
throughout my study.
I would also like to express my gratitude to all of the staff from the School of Public
Health, QUT, especially Dr Diana Battistutta, for her statistical advice and Mr Martin
Reese, for his advice on thesis writing.
To my friend Juanita Anderson who gives her time to assist with my thesis writing
and encourages me on my study all the time.
And last, but not least, to my wife Jenny, my son Jack, my home stay daughter Milki
and family who have provided support throughout my Masters by Research degree.
Without their help, I could not have completed this thesis.
12
1Chapter 1. Introduction
Excessive exposure to ultraviolet radiation (UV) from sunlight is a causative factor
in the development of skin damage and skin cancer (Matsumura, 2002). There have
been a number of studies, which were examining the sun exposure and the impact on
skin for people working outside or doing activities in the sun (Holman, 1983; Diffey,
1998). Little research has been undertaken into assessing sun exposure for workers
inside buildings or behind window glass and the linking of their exposure to skin
damage. This project directly addressed this issue by aiming to assess the role that
UV exposure to plays on skin damage.
Australia has the highest skin cancer rates in the world due to its proximity to the
equator, high levels of environmental Ultraviolet Radiation (UVR), a predominantly
fair skinned population and an outdoor lifestyle (Armstrong, 2001; Mccarthy, 2004;
Souhami, 1995b).
UVR is classified as the most prominent and common physical carcinogen for the
skin in the natural environment (Gruijl, 1999). All cities in Australia receive an
annual total UVR of more than 10000 SED each year which were higher than the
almost Europe cities. (Gies, 2004). As a public health issue, overexposure to solar
irradiation can cause acute skin effects and chronic effects such as photoaging,
sunburn, immunosuppression and skin cancer (Matsumura, 2002). There are
approximately 380,000 new cases of skin cancer diagnosed in Australia each year
(Armstrong, 2001; Arpnsa, 2006). It is estimated that 95% of cutaneous melanomas,
and 99% of squamous and basal cell carcinomas, are caused by solar UV radiation
(Armstrong, 2004).
Recent research regarding UV exposure behind window glass and indoors has
confirmed there are considerable doses of UVR for those working indoors and inside
motor vehicles (Gies, 1992; Kimlin, 1999; Moehrle, 2003; Parisi, 2000; Parisi, 1998).
This project was undertaken to measure workers’ UV exposures under conditions
inside an office building and a motor vehicle. UVA (315 -400nm) and UVB (280-
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315nm) exposures were measured by using erythemal UV- sensitive dosimeters
(Diffey, 1977b) and UVA-sensitive dosimeters (Diffey, 1997; Kimlin, 2003; Parisi,
2005). Additionally, specific outcomes of long-term UV exposure on the skin were
assessed for participants and they included skin pigmentation (I) skin pigmentation
(II), wrinkles, red areas and texture.
1.1 PROJECT AIMS AND HYPOTHESES
The aims of this study were to:
1. Measure and compare the occupational UVB and UVA exposure for indoor
workers and drivers.
Hypothesis:
H0: There is no difference on the measured UVB and UVA exposure between
that of indoor workers and drivers.
2. Measure and compare sun-related skin damage for indoor workers and drivers.
Hypothesis:
H0: There is no difference in skin damage between that of indoor workers and
drivers.
3. Investigate the relationship between sun exposure and skin damage such as age,
gender, skin type, years residing in Australia, freckling, history of skin damage and
sun exposure.
Hypothesis:
3(a). H0: There is no relationship between age, years residing in Australia and
skin damage for indoor workers and drivers.
3(b). H0: There is no difference between gender and skin damage for indoor
workers and drivers.
3(c). H0: There is no difference between personal characteristics (skin colour,
hair colour and eye colour) and skin damage for indoor workers and drivers.
3(d). H0: There is no relationship between freckling on the face and skin damage
for indoor workers and drivers.
3(e). H0: There is no relationship between one day UV exposure and skin
damage for indoor workers and drivers.
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3(f). H0: There is no difference between the number of major sunburn and skin
damage for indoor workers and drivers.
1.2 OVERVIEW OF THESIS
Chapter 1—Introduction: This chapter provides background information on sun
exposure and health, and an overview of the aims and hypotheses of this present
research.
Chapter 2— Literature reviews: This chapter presents a review of the literature on
solar UV exposure and health impacts.
Chapter 3—: Assessment of UV exposure: This chapter described the use UV
personal dosimetry approaches to measure UVR.
Chapter 4—: Research methods: This chapter discusses the study design, sampling,
participant recruitment, data collection and statistical approaches for data analysis
for this project.
Chapter 5—: Results: This chapter reports the results of sun exposure, skin damage
and the data from the questionnaire. The relationships between skin damage and sun
exposure are discussed in this chapter.
Chapter 6—: Discussion and conclusion: This chapter overviews the study’s
findings, strengths and limitations, and the study’s implications. Finally, this chapter
elaborates the significance of all the findings, and make suggests recommendations
for future research
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Chapter 2. Literature review
2.1 SOLAR ULTRAVIOLET RADIATION
2.1.1 The Sun and ultraviolet radiation (UVR)
The sun is the largest source of ultraviolet radiation (UVR) in the natural
environment on the earth (Diffey, 1998). Sun exposure has both beneficial effects
and harmful effects for human beings (Diffey, 1991).
Solar Radiation from the sun that reaches the earth’s surface is divided into infrared
radiation, visible light, and ultraviolet radiation (Diffey, 2002). All of the different
forms of energy coming from the sun are referred to as the electromagnetic spectrum
(Haire, 1999). Ultraviolet radiation, which is part of the sun spectrum, is divided into
three bands according to wavelength and biological effects; they are UVA (320-
400nm), UVB (280- 320nm) and UVC (200-280nmm) (CIE, 1987).Howevere, the
exact boundaries of these bands are decribed differently by different organizations,
with the WHO defing the wavelength regions as UVA (400-315nm); UVB (315-
280nm) and UVC (280-100nm) (WHO, 2008). According to environmental and
dermatological photobiologists, the wavelength regions are normally defined as
UVA (400-320nm), UVB (320-290nm) and UVC (290-200nm) (Diffey, 2002). The
reason to choose 290nm as the division between UVB and UVC is that there is less
UVR at shorter wavelengths in terrestrial sunlight. Diffey stated that ‘the choice of
320nm as the division between UVB and UVA is perhaps more arbitrary’ (Diffey,
2002). Figure 1 shows range of three bands of UVR and the incident intensity when
UVR passing through the atmosphere. UVC has the strongest energy and potential
for biological damage. Fortunately, for human beings the ozone layer absorbs almost
all UVC on the surface of the earth through absorption in the atmosphere (Tuchinda,
2006). The biological significance of solar UVR therefore is only related to UVB
and UVA. It is estimated that 96.5% of UVA and 3.5% of UVB reach the earth’s
surface during a summer day (Diffey, 2002).
16
Figure 1. The electromagnetic spectrum (Lucas, 2002)
(Adapted from Office of Public Outreach, Space telescope Science Institute.
http://amazing-space.stsce.edu/light/ems-frames.htm>)
The UV radiation reaching the Earth’s surface is mainly composed of UVA with a
small UVB component. One interesting aspect of solar UV exposure is that small
amounts of UV are essential for the production of vitamin D in human beings, yet
overexposure may result in acute skin conditions and in chronic skin cancer (WHO,
2008).
2.1.2 Units of UV radiation
The units of measurement relating to UV radiation are expressed using radiometric
terminology. For example, the terms radiant energy and radiant flux are used to
describe a beam of radiation passing through space. The terms radiation intensity or
radiance, however, relate to a source of radiation. The most commonly used term in
photobiology is irradiance and this relates to the object (eg. A person) struck by the
radiation. Often the term dose is used, however, this is a common term that is more
17
correctly referred to as radiant exposure or exposure dose. The time integral of the
irradiance is correctly described as radiant exposure (Diffey, 2002).
MED: the term minimal erythemal dose (MED) as a “measure” of erythemal
radiation has been used for many years. The term erythemal radiation refers to those
wavelengths of UV which are able to produce adverse effects on the skin,
particularly erythema. One MED has been defined as the lowest amount of UV
exposure that is sufficient to produce erythema in people of Fitzpatrick skin type I
within 8-24 hours after exposure (Mckinlay, 1987). One MED corresponds to 200 to
250J/m2 in people with skin type I (Diffey, 1992; Moehrle, 2003). Fitzpatrick firstly
proposed the classification of skin type in 1975 (Table 1) and developed a score
system to assess skin type through responses to sun exposure as the action of burning
and tanning (Figure 2) (Fitzpatrick, 1975, 1988).
Table 1. The Fitzpatrik classification of skin type (Fitzpatrick, 1975)
Skin type Typical Features Tanning ability
I
II
III
IV
V
VI
Pale white skin, Blue/hazel eyes, Blond/red hair
Fair skin, blue eyes
Darker white skin
Light brown skin
Brown skin
Dark brown or black skin
Always burns, does not tan
Burns easily, tans poorly
Tans after initial burn
Burns minimally, tans easily
Rarely burns, tans darkly easily
Never burns, always tans darkly
Skin colour is an essential factor in determining the result of sun exposure. People
with fair skin could get an erythemal reaction in 15 to 30 minutes of midday summer
sunshine, while; people with moderately pigmented skin may need 1-2 hours of
exposure. Whereas, people with darkly pigmented skin will not got normally sunburn
(Diffey, 1998).
In AusSun Research Laboratory, one MED corresponds to 250J/m2 for routine
monitoring and research.
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Figure 2. Fitzpatrick Skin Type (Fitzpatrick, 1988)
19
2.1.3 The UV index
The UV index (UVI) is an international standard measurement of the intensity of the
ultraviolet (UV) radiation from the sun at the Earth’s surface (WHO, WMO, 2002).
The UV index is a scale that is primarily used in daily forecasts for the general
public. It has been designed to help people to effectively protect them from UVR.
Public-health organizations recommend that people protect themselves when the UV
index is 3 or higher (WHO, 2002).
Canada was the first country in the world to use the UV index (WHO. 2002). In
1992, Environment Canada developed the UV index to broadcast forecasts of the
predicted daily UV levels for the next day (Kinney, 2000). The World Health
Organization (WHO) has replaced the inconsistent regional methods by using a
worldwide standardized UV index in 2002 (WHO, 2002). Nowadays several
international organizations and standards agree on the UV Index (International
Commission on Nonionizing Radiation Protection, World Health Organization,
World Meteorological Organization or European Commission) and it is proposed to
be used in public information (ICNIRP, 1995; WHO, 2002; CIE, 2003; Eropean
Commission, 2006). The UV Index is not only a base for sun protection
recommendations, but also used in risk assessment and health care (Table 2).
Table 2. UV radiation exposure categories (WHO, 2002)
UV Index
Description Media Graphic Color
Recommended Protection
0–2 Low danger to the average person
Green Wear sunglasses use sunscreen if there is snow on the ground, which reflects UV radiation, or if you have particularly fair skin.
3–5 Moderate risk of harm from unprotected sun exposure
Yellow Wear sunglasses and use sunscreen, cover the body with clothing and a hat, and seek shade around midday when the sun is most intense.
6–7 High risk of harm from unprotected sun exposure
Orange Wear sunglasses and use sunscreen having SPF 15 or higher, cover the body with sun protective clothing and a wide-brim hat, and reduce time in the sun from two hours before to three hours after solar noon (roughly 11:00 AM to 4:00 PM during summer in zones that observe daylight saving time).
8–10 Very high risk of harm from unprotected sun exposure
Reddish-purple
Same precautions as above, but take extra care — unprotected skin can burn quickly.
20
11+ Extreme risk of harm from unprotected sun exposure
Violet
Take all precautions, including: wear sunglasses and use sunscreen, cover the body with a long-sleeve shirt and pants, wear a broad hat, and avoid the sun from two hours before to three hours after solar noon.
The UV index varies with levels of UV radiation during the day. The UV index
reaches a maximum at solar noon. According to records, the UV index can reach up
to 20 in countries close to the equator (WHO, 2002).
The UVI is a unitless quantity defined by the formula:
Where Eλ is the solar spectral irradiance expressed in W/(m2.nm) at wavelength λ and dλ
is the wavelength interval used in the summation. Ser( λ) is the erythema reference action
spectrum, and Ker is a constant equal to 40 m2/W (WHO, 2002).
2.1.4 Factors influencing UV irradiance
Solar UVR intensity on the earth’s surface is substantially affected by the following
factors.
2.1.4.1 Latitude and altitude
UV radiation levels gradually decrease with increasing latitude. Equatorial regions have
higher UV radiation levels than temperate latitudes (WHO, 2002), with the ambient
annual UV radiation in temperate latitudes being about 2/3 that of the tropics (Mckenzie,
1997).
The UV radiation levels increase with increasing altitude due to the reduction in the
amount of aerosols, air molecules and ozone in the atmosphere (Mckenzie, 1997). It is
assessed that UV radiation levels increase by 10% to 12% with every 1000 metre
increase in altitude (WHO, 2002).
21
2.1.4.2 Season, the time of day and clouds
Both the quality and quantity of UV radiation on the earth’s surface change with the
season, the time of day, and the day of the year (Diffey, 2002). UVR changes because
the solar zenith angle changes. Solar Zenith Angle (SZA), which is ‘the angle of an
object between the zenith or local vertical and the direction of the sun’ (Parisi, 2004).
The SZA changes with the geographical location, with time of day and day of the year.
The reason is that there is less absorption and scattering of the UV before reaching the
ground due to its shorter path through the atmosphere. The minimum SZA for a certain
location occurs at local solar noon (Parisi, 1997). For instance, the surface receives about
20% of total daily radiation from 11:00am to 1:00pm, and about 75% between 9:00am to
3:00pm (Anthony, 1998).
Clouds composed of either liquid or ice droplets in the sky usually attenuate UV
intensity by scattering (Diffey, 2002). Complete light cloud cover can reduce by about
one half terrestrial UV intensity from a clear sky. Heavy cloud cover may reduce UV
radiation seldom to less than 10% of that under clear sky. However, very heavy storm
clouds can eliminate almost all terrestrial UV radiation, even in summertime (Diffey,
1998b). Thick cloud can reduce up to 99% surface UVB radiation. Even scattered
clouds on the horizon can also significantly lower the UV radiation (Ola, 2005). Diffey
roughly estimated that clouds reduced about 1/3 annual UV radiation in temperate
latitudes and about 1/4 for the tropics (Diffey, 2002).
2.1.4.3 Aerosols
Aerosols are small solid or liquid particles suspended in the air, for example sulphate
haze, soot, dust and sea-salt aerosols (Madronich, 1998). Dickerson divided aerosols into
two kinds of aerosol particles; UV-scattering particles and UV-absorbing aerosols such
as mineral dust and soot, which reduce the levels of ultraviolet radiation by up to 20%
(Dickerson, 1997).
2.1.4.4 Ozone levels
Ozone is produced in the stratosphere (above about 20 km) as a result of photochemical
reactions in the atmosphere. UV light splits O2 to produce free oxygen atoms; these
oxygen atoms then react with O2 and a mediator molecule to produce O3 (Sanna, 2008).
The standard way to express total ozone levels (the volume of ozone in a vertical
22
column) in the atmosphere is expressed in Dobson Units (DU) after the British physicist
George Dobson. Concentrations at a point are measured in parts per billion (ppb) or in
μg/m³. Dobson developed a means of estimating the concentration of ozone in a
column of air of given dimensions based on the amount of UV light absorbed by the
atmosphere. The global distribution of ozone shows a general increase from the tropics
(250 DU) to the poles (>300DU) (Metcalfe, 2005).
About 90 percent of all the ozone in the atmosphere is found in the stratosphere, which is
mainly between 8km to 18km above the surface. This is known as the ozone layer and it
effectively blocks a large quantity of incoming UVB radiation. The troposphere contains
about 10% of atmospheric ozone (Metcalfe, 2005). The effect of O3 depletion would be
to increase the amount of UV reaching the earth’s surface. A 1% decrease in column O3
would be expected to increase the surface flux of UVB by 2% (Godish, 1997). In Health
and Environmental Effects of Ultraviolet Radiation (WHO, 1994), it stated that ‘A 10%
reduction in ozone could lead to as much as a 15-20% increase in UV exposure
depending on the biological process being considered’. High concentrations of
tropospheric ozone have been associated with a range of environmental impacts
including damage to vegetation and building materials, and health effects including
respiratory diseases (Friis, 2005; Metcalfe, 2005).
2.2 HEALTH IMPACTS OF UV EXPOSURE
Ultraviolet irradiation has both beneficial and harmful effects on normal human skin.
The beneficial effects include killing pathogens on the skin, inducing Vitamin D
synthesis and treating certain skin diseases such as psoriasis vulgaris.(Matsumura, 2002)
The harmful effects of UV irradiation are sunburn, photoaging, immune suppression and
skin cancer (Diffey, 1998a).
2.2.1 Effects of acute and chronic UV irradiation on the skin
The responses of skin to UV radiation can be described as acuate effects and chronic
effects. Acute effects of ultraviolet irradiation include sunburn inflammation (erythema),
and tanning, histological changes such as thickening of the epidermis, and local or
systemic immunosuppression. Chronic UV irradiation leads to photoaging, sustained
immunosuppression and photocarcinogenesis (Figure 3) (Matsumura, 2004).
23
Figure 3. Acute UV and Chronic UV effects on skin (Matsumura, 2004)
2.2.1.1 Erythema
Erythema, or sunburn, is ‘an acute injury following excessive exposure to solar UV
radiation’ and its redness is easy distinguished by the border around the skin (Diffey,
1998a; Harrison, 2002). Symptoms of sunburn include erythema, pain, tenderness,
swelling, inching, and blistering of the skin (Silverstone, 1997). The redness of the skin
is caused by dilatation of the blood vessels in the dermis. Erythema is also wide used in
clinical diagnosis for sun exposure and skin damage. UVB are known as “the burning
rays” and they are able to be absorbed in the upper layers of the skin. UVB can cause not
only sunburn, but also freckles, thickening of the skin, and skin cancer. The lowest dose
to induce erythema is defined as One MED (Harrison, 2002). ‘High doses may result in
enythema, pain, blistering, and after a few days, peeling’ (Diffey, 1998).
Skin colour influences the skin response for UV radiation. For example, it takes 15-30
minutes of midday summer sunshine to induce an erythemal reaction for fair-skinned
people, while it needs 1-2 hours for moderately pigmented skin people. However, people
with darkly pigmented skin will not normally have erythema (Diffey, 1998). Other risk
24
factors include light-coloured hair colour, blue and green colour eyes, and freckles
(Andraessi, 1987; Azizi, 1988).
Erythema resulting from UV irradiation can be seen quickly within seconds or a delayed
erythema can peak a few hours later. In individuals with skin type 1 or II, the immediate
reaction is usually seen after sun exposure. However, the delayed response may reach a
peak by 6-24 hours depending on dose (Pathak, 1983; Farr, 1985). The symptoms may
occur later than erythema and commonly the symptoms begin to manifest as soon as 3 to
5 hours after UVB exposure, peak at 12 to 24 hours, and subside at 72 hours following
sunburn (Driscoll, 2000). In 1960s, Olson already found that erythemal sensitivity varied
with different anatomic location and UV radiation dose. The erythemal sensitivity of the
face, neck and trunk are two to four times higher than those of the limbs (Olson, 1966).
Erythemal sensitivity may vary with age; however, there is no difference between sexes
(Diffey, 1998). Children get sunburn much easier than adult because children are more
susceptible to skin damage and their skin is more sensitive than the skin of adults.
Figure 4 shows the action spectrum for erythema in human in human skin (CIE, 1987).
UV below 320nm makes up the majority of the action spectra and erythema is still
produced by up to 400nm (Diffey, 1998a) .
Figure 4. A reference action spectrum for ultraviolet induced erythema in
human skin (CIE, 1987)
25
2.2.1.2 Tanning or melanin pigmentation
Melanocytes are ‘phenotypically prominent but histologically inconspicuous skin
cells. They are responsible for the pigmentation of skin and hair, and thereby
contribute to the appearance of skin and provide protection from damage by
ultraviolet radiation’(Lin, 2007). Melanocytes are cells located in the bottom layer
(the stratum basale) of the skin’s epidermis (Halaban, 2003). Melanocytes comprise
from 5% to 10% of the cells in the basal layer of epidermis and there are between
1000 and 2000 melanocytes per square millimetre of skin (Halaban, 2003). The
difference in skin colour between fair people and dark people depends on the degree
of pigment production (Lin, 2007).
The main contributor to pigmentation is melanin, which formed in organelles called
melanosomes within melanocytes (Lin, 2007). Melanosome is a special container,
which can be transferred from the melanocyte into neighbouring keratinocytes
(Hoogduijn, 2004). ‘The melanin pigment forms a “cap” protecting the nucleus of
keratinocyte or appearing in the path of incoming UV photons. Thus, keratinocytes
accept transferred melanin from melanocytes and the pigment is distributed more
widely within the epidermis, increasing its photoprotective capacity’ (Kobayashi,
1998); Barbare, 1996; Gidanian, 2008; Susan 2002).
There are two distinct phases of a tanning response: one is immediate pigment
darkening (IPD) and the other is delayed tanning (DT). In the IPD phase, there is no
new pigment synthesis in this phase, and the colour change appears to result from
redistribution of melanosomes. In the DT phase, following solar UV exposure, both
the activity and number of melanocytes increase. This status leads to increased new
melanin and the number of melanin granules (Gilhrest, 1996). Accelerated melanin
transfer to keratinocytes then results in a large increase in melanin granules in the
epidermis (Matsumura, 2002). Tanning is typically a response to UVB; however,
Rosen reported that significant doses of the lower energy UVA and visible light
could induce a tanning response, specially in IPD (Rosen, 1990).
Whatever the melanin pigmentation is its response for ultraviolet radiation or
protection from damage by ultraviolet radiation can be used to provide an assessment
of skin damage related to ultraviolet radiation as well as information to prevent and
26
treat skin diseases (Lin, 2007). In this project, participant’s complexion pigmentation
was measured by using the photo damage assessment tool, which can analyse the
skin pigmentation and wrinkles result in sun exposure.
2.2.1.3 Freckling, Actinic lentigines, and cutaneous melanoma risk
Freckles are clusters of accumulated melanin and also called “ephelis”. Both the
degree and the history of freckling have been found to be associated with a
significantly high risk for cutaneous melanoma (Grulich, 1996; Tucker, 1997;
Whiteman, 1997; Youl, 2002). Freckling has been reported to be a risk factor
independent of common melanin naevi (MN) counts (Green, 1985; Mackie, 1989).
The independence of freckling and MN counts indicates that these measures
represent separate host characteristics, both of which are also related to sun exposure.
Actinic lentigines have been found as a risk factor for the development of cutaneous
melanoma independently of the number of common melanocytic naevi. Both
markers, freckling and actinic lentigines were found to be highly significant related
to each other and to the risk for cutaneous melanoma. (Garbe, 1994; Naldi, 2000).
2.2.1.4 Melanocytic Naevi
A few epidemiological studies show that an increasing number of melanocytic naevi,
both counts and densities, is the strongest risk factor for melanoma (Bauer, 2005;
Bauer, 2003). Moreover, melanocytic nevi were considered to be precursor lesions of
a substantial proportion of cutaneous melanoma (Kruger, 1995). According to the
histologic studies, 18-57% of cases have an association of malignant melanoma with
melanocytic naevi (Kamino, 2008). ‘Melanocytic naevi represent proliferations of
melanocytes that are in contact with each other, forming small collections of cells
known as “nests” that are located either in the epidermis (functional nevus), dermis
(dermal nevus), or both (compound nevus)’ (Kincannon, 1999).
Sun exposure is one of the major determinants of melanin naevi development.
Studies comparing different populations have clearly shown that melanocytic nevi is
more common in the fair-skinned populations than in the dark-skinned populations
(Green, 1989). Sun exposure habit plays the predominant role for the development of
27
melanocytic nevi, especially during holidays in tropical countries (Harrison, 1999;
Kelly, 1994). Children living at lower latitudes have higher melanocytic nevi counts
than those living at higher latitudes (Maclennan, 2003). The most common skin sites
for melanocytic nevi in faired-skin people are the head and neck, trunk and limbs
(Souhami, 1995a). Increased instances of both acute and chronic exposure to sun are
associated with melanocytic nevi development (Harrison, Sun exposure and
melanocytic naevi in young Australian children, 1994).
In this project, melanocytic nevi were monitored under both skin pigmentation I and
skin pigmentation II indicators by using the photo damage assessment tool.
2.2.1.5 Melanocytic skin cancer
‘The predominant melanocytic skin cancer (MSC), melanoma, is a tumour of
melanocytes. MSCs usually arise from, or in conjunction with, melanocytic nevi’
(Harrison, 1999). It is also called malignant melanoma (MM), and is most the lethal
skin cancer because it grows rapidly and quickly invades other tissues. Sun exposure
is the strongest environmental risk factor for the development of these cancers. Other
factors include an individuals’s family history (Gruber, 2006; Paraskevas, 2005).
This cancer in more frequent in faired-skin males and around 160,000 new cases of
melanoma are diagnosed worldwide each year (Ries, 2003). There are about 48,000
melanoma related deaths that occur worldwide per annum according to the WHO
report (WHO, 2008). The disease is almost ten times as common in Australia and
New Zealand as it is in Europe (Souhami, 1995a). Faired skin people have a much
higher incidence of melanoma than Africans or Asians (Dwyer, 1998). In Australia,
up to 95% of cutaneous melanomas are caused by solar UV radiation (Armstrong,
2004) .
2.2.1.6 Basal cell carcinoma (BCC)
Basal cell carcinoma is the most common cancer in the white population and the
incidence is 762 per 100,000 in Australia (Marks, 1993). Exposure to sun ultraviolet
radiation is the main risk factor leading BCC (Wong, 2003). In Australia, it is
estimated that 99% of squamous and basal cell carcinomas are caused by solar UV
radiation (Armstrong, 2004). Other risk factors include skin type I, red or blonde hair,
and blue and green eyes (Lear, 1997). High density of freckling in childhood and
28
severe sunburn in childhood are reported to contribute more to the development of
basal cell carcinoma (Cornona, 2002). Basal cell carcinomas are most commonly
seen around the nose, forehead, cheeks and lower eyelid and upper trunk. They
appear as a lump or scaly area and are pale, pearly or red in colour. They may have
blood vessels on the surface (Wong, 2003). In one American prospective study of
1000 patients with a basal cell carcinoma, 36% developed a second within a 5-year
period. About 9% of Australian cases have multiple primary lesions at presentation
(Souhami, 1995a).
2.2.1.7 Squamous cell carcinoma (SCC)
Squamous cell carcinoma is ‘a malignant tumour that may arise from the
keratinizing cells of the epidermis or its appendages. It is locally invasive and has
the potential to metastasize to other organs of the body’ (Motley, 2002). SCC
frequently occurs on the sun-exposed skin of middle-aged and elderly fair-skinned
people. Exposure to the sun is the main cause to develop SCC. In addition, direct
exposure to X-rays, arsenic ingestion, and occupational carcinogens are all known to
be important. These cancers usually develop quickly over a period of weeks to
months. These cancers may spread to other parts of body if not treated promptly.
Most SCC are readily identified and treated easily with a surgical procedure (Sahni,
2009). Tumours may have scaling, red areas, which may bleed easily and ulcerate,
looking like an unhealing sore. The commonest sites include the exposed areas of the
head and neck, particularly the nose, temples, rim of the ear and lip, as well as the
side and back of the neck, and the dorsal surfaces of the hand and forearm (Souhami,
1995a). In Australia, it is estimate that 99% of squamous and basal cell carcinomas
are caused by solar UV radiation (Armstrong, 2004).
2.3 UVA RADIATION
It is generally agreed that the shorter UVB wavelengths (290-320nm) predominantly
causes erythema, sunburns and non-melanoma skin cancer (De Gruijl, 1999; Larsson,
2005). However, the health effects of UVA have been increasingly investigated due
to: its much greater intensity in sunlight as well as in many artificial sources, and the
greater period of the day in which sunlight UVA remains at high intensities, UVA
can have significant biological effects (Wang, 2001). During a summer day, the UV
29
spectrum that reaches the earth’s surface consists of 5-10% UVB and 90-95%
UVA(Miller, 1998). UVA radiation comprises more than 90 percent of incident
midday solar ultraviolet radiation and is present for more hours of each day and
throughout the year than UVB radiation (Parrish, 2005). Also UVA radiation
penetrates more deeply into human living tissue through the skin than does UVB.
Whereas 9-14% of incident UVB reachs melanocytes, up to 50% of UVA reaches the
dermis (Bruls, 1984; Wang, 2001). In recent years, the harmfulness of UVA was
more precisely demonstrated at cellular and molecular levels, and there have been
more studies and evidence of UVA involvement in photoaging, DNA damage, cancer
and tumour development and immunosuppression (Jing, 2009; Stern, 2001;
Fourtanier, 2006).
When solar ultraviolet radiation transmits through glass, the glass filters almost all
UVB while UVA are only slightly affected (Gies & Kimlin, 1992). There is up to
70% UVA transmission through glass (Moehrle & Kimlin, 2003). In this project,
UVA exposure for indoor workers and drivers were monitored by a UVA-sensitive
dosimeter.
2.3.1 UVA HEALTH IMPACTS
2.3.1.1 UVA and photoaging:
Skin aging is divided into two types according to clinical and biological features; one
is innate or intrinsic aging and other is extrinsic aging or photoaging (Uitto, 1997).
Intrinsic aging is a natural aging due to a variety of internal organs irreversible
degeneration of tissue. Photoaging is the result of exposure to the sun exposure in
environment. ‘Photoaging is the superposition of chronic ultraviolet (UV)-induced
damage on intrinsic aging and accounts for most age-associated changes in skin
appearance’ (Yaar, 2007).
UVA plays a major role in photoaging because of three reasons. First, UVA has 10
times greater abundance than UVB in terrestrial sunlight. Second, UVA has higher
irradiance on the Earth’s surface than UVB. Third, UVA can penetrate into the
dermis more deeper than UV (Lavker, Cumulative effects from repeated exposures to
suberythemal doses of UVB anad UVA in human skin, 1995).
30
The changes in photoaging appearance include wrinkling, wilting, laxity, sagging,
shrivelled face, shallowness, patchy/mottled pigmentation, telangiectasia, dryness,
roughness, etc(Uitto, 1997). Those phenomenons are also called solar elastosis,
which is the massive accumulation of elastotic material in the upper and middle
dermis. Kligman (1986) summarized photoaging characteristics as ‘loss of skin tone
and resilience, increased roughness and dryness, irregular pigmentation, and deep
wrinkles. The main places of photoaging appear in the sun-exposed areas, such as
the face, neck, ears, dorsal aspects of the hands, the exterior surface of forearms and
the lower legs (Anthony, 1998).
In this project, each participant’s wrinkles were monitored by photo damage
assessment tool as well as their UVA exposure was monitored by using a UVA-
sensitive dosimeter.
2.3.1.2 UVA and skin cancer
UVR from the sun has harmful effects on human skin and the spectral range
responsible for cancer induction has become clearer in recent studies. UVB can cause
erythema and sunburns when skin is exposed to solar UVR (Diffey, 1998a; Harrison,
2002). It is commonly confirmed that UVB can induce non-melanoma skin cancer
(Wong, 2003; (Armstrong, 2004). UVA has been proven not only to cause
pigmentation and photoaging, but also to induce skin cancer in animal models and
clinical evidences (Larsson, 2005; Wang, 2001).
Three skin cancer models have confirmed that UVA induces tumours in animal
experiments. In those models, melanoma can be induced after UVA radiation on
hairless mice (Kelfkens, 1992), the hybrid fish Xiphophorus (Setlow, 1993) and
opossums (Ley, 1997).
Clinical evidence has also showed an increase in melanomas in patients exposed to
PUVA. In a key report, 1380 patients were treated with oral methoxsalen (psoralen)
and UVA radiation (PUVA) for psoriasis and many other skin conditions in 1975 to
1997. The patients treated with PUVA therapy had more than 5-fold increased
relative risk for the development of melanoma (Stern, 1997). Another 5.7 year
31
prospective study showed that multiple aggressive squamous cell carcinomas
developed in UVA-exposed sites in patients with psoriasis treated with high-dose
UVA (Stern, 1984). In 1990s, two publications (Anders, 1995; Lavker, 1995) have
reported the damaging effects of UVA radiation on humans and the induction of
tumours. However, in another study in Sweden, 944 patients who were treated with
PUVA and 4799 patients treated with systemic PUVA showed no increased risk
between UVA radiation and the development of melanoma during 15 and 16 years
following up. Therefore, as Wang wrote in a clinical review: ‘There are clinical data
suggesting an association between PUVA therapy and development of melanoma, but
the evidence is not conclusive. Furthermore, it has been argued that psoralens are
DNA adducts and that the carcinogenic effects of PUVA may result from the
mutagenic effects of psoralens after UVA radiation, not a direct effect of UVA’
(Wang, 2001).
2.3.1.3 UVA and DNA damage
UVR from sunlight is the major environmental risk factor for skin cancer and a
complete carcinogen by damaging DNA and by suppressive immune responses.
UVB was thought to be the principal carcinogen in sunlight; the reason is that UVB
is efficiently absorbed by DNA. However, UVA may also be carcinogenic in the skin.
UVA is weakly absorbed by DNA, but is can generate reactive species that damage
DNA. This was confirmed in the early 1990s that UVA can cause DNA damage via
photosensitised reactions that result in oxygen radical species (e.g. hydrogen
peroxide, single oxygen, superoxide anion) (Ananhaswamy & Pierceall, 1990). UVA
can induce gene expression in human cells (Grether-Beck, Buteener, & Krutmann,
1997). It was confirmed that solar UVA radiation induced gene express was involved
in photocarcinogenesis, in the pathogenesis of the most frequent photodermatosis,
and photoaging according to analysis of the underlying photobiological and
molecular mechanism (Grether-Beck, Bonizzi, & Schmitt-Breden, 2000). Moreover,
UVA can penetrate more deeply into skin where melanocytes reside than UVB
(Lund & Timmins, 2007).
Recently, Jing found that UVA produces a significant amount of a basic sites and
cyclobutane pyrimidine dimmers (CPDs) by exploiting atomic force microscopy
(AFM) imaging of individual DNA ;molecules, alone and in complexes. This
32
founding strongly suggest that CPDs are produced by UVA directly (Jing, Rabbi, &
Kim, 2009).
2.3.1.4 UVA and the immune system
Ullrich recently showed that solar-simulated UV radiation (UVA+UVB: 295-
400nm), applied after immunization, suppressed immunological memory and the
elicitation of delay type hypersensitivity (DTH) to the common opportunistic
pathogen, Candida albicans. Further, it was found that wavelengths in the only UVA
region of solar spectrum (320-400nm) were equally effective in activating immune
suppression as UVA+UVB radiation (Ullricn, Kripke, & Ananhaswamy, 2002). This
is one experimental evidence of UVA can induce immunosuppression.
In recently years, the harmfulness of UVA was more precisely demonstrated at
cellular and molecular levels, more studies and evidence of UVA involvement in
tumour development and depression of immune function (Fourtanier et al., 2006).
2.4 SUMMARY
The ultraviolet radiation present in sunlight has both beneficial and harmful effects
on human health. Overexposure to solar UVR may lead to skin damage such as
sunburn, photoaging, and skin cancer (Silverstone, 1997; Driscoll, 2000; Uitto, 1997;
Armstrong, 2004). UVB contributes to almost all acute effects such as sunburn, and
tanning. UV radiation also causes DNA damage, skin aging, immunosuppression and
skin carcinogenesis. Recently studies have shown that UVA not only contributes to
photoaging, but also induces skin carcinogenesis.
It is difficult to set up a dose-response relationship for UVR and disease.
Additionally, there is not a simple linear relationship between UVR exposure and
disease (Lucas, 2002). In sun exposure and skin cancer studies, one study in
Australia reported that risk of BCC was positively associated with lifetime exposure
on non-working days (Kricker, 1995). However, the real relationship needs further
study. Animal skin cancer models and epidemiological studies have reported that UV
exposure induces skin cancer. In addition, skin pigmentation, freckling and
melanocytic nevi have been found to be risk factors and associated with cutaneous
melanoma (Matsumura, 2002; Youl, 2002; Tucker, 1997; Kriger, 1995). It is not
33
possible to directly equate the dose-response relationships for UVR exposure and
melanoma. On the other hand, skin pigmentation, freckling and melanocytic nevi can
be used as indictors or predictors for skin damage.
In this project, sun exposure for people working inside office buildings as well as people
driving behind windscreens was monitored. In addition, using a skin spectrophotometer
and photo damage assessment tool monitored the skin damage as a result of sun
exposure.
34
2Chapter 3. Assessment of UV exposure
3.1 DOSIMETRY FOR PERSONAL UV EXPOSURE MEASURMENT
3.1.1 Polysulphone dosimeter
Polysulphone dosimeters have been used in UV research for more than three
decades(Parisi, 2006). Polysulphone dosimeters were first introduced to monitor
ultraviolet radiation in 1976 (Diffey, 1977a) and are the most commonly used
dosimeters in human research related to sun exposure and health impacts (Green, 2006).
The polysulphone undergoes UV-induced photodegradation when exposed to solar
irradiation. Importantly the polysulphone film has an action spectrum which is very
close to the erythemal response of human skin when it is cast as a film 30-40um thick
(Davis, 1976) The structure of polysulphone contains many aromatic rings (Fig 5) which
are responsible for the strong absorption in the UV region (Kollias, 2003).
Figure 5. The structural unit of polysulphone
The degree of degradation is detected by use of a spectrophotometer to measure the
change in optical absorbance (A) at 330nm (Parisi, 2006). The polysulphone has a high
response in the UVB waveband and drops rapidly for wavelengths greater than
approximately 300nm. This corresponds to an erythemal exposure of about 10 to 20
MED (Parisi, 2006). The polysulphone film does not respond to wavelengths longer than
330 to 340nm (Parisi, 2004).
Measurements of solar UVB using polysulphone film has been found to be strongly
correlated (R2 >0.95) with measurements using a spectroradiometer (Kollias, 2003).
‘Polysulphone film as a personal environmental UV monitor has the advantage of good
35
stability to thermal radiation, humidity and high-energy radiation’ (Davis, 1982;
Kollias, 1988).
Polysulphone dosimeters have been widely used in the quantification of erythemal UV
in many different environments and during different human activities. For instance, they
have been used to investigate the UV exposures for outdoor workers, indoor workers and
school children (Kimlin, 1998); athletes (Kimlin, 2006); gardeners, roofers and
bricklayers (Holman, 1983); as well as exposures underwater, in aircraft, in a welding
environment, during outdoor activities (Parisi, 2007). They are easily portable and have
been used to estimate the annual solar UV exposure dose for infants and small children
in tropical Queensland (Moise, 1999).
Being economical, stable and easy to apply, polysulphone dosimeters are widely used in
field studies (Diffey, 1987). In this project, participants were asked to wear dosimeters on
a hat and upper arms to measure UV exposure.
3.1.2 Phenothiazine/Mylar film dosimeter
The UVA dosimeter is a combination of Phenothiazine with Mylar film, which is a
novel technique for the development of a prototype UVA dosimeter. Phenothiazine
(Diffey, 1997) is known to have a response in the UVA and UVB part of the UV
spectrum. Mylar film (Cadillac Plastics, Australia) was found to filter almost all UVB
(Parisi, 2005). Phenothiazine is first cast directly on to the Mylar film to create a
combination film. The film of Phenothiazine on Mylar film will be mounted together
into 3 x 3 cm rigid plastic holders, each with a 1.5 cm diameter central aperture to
produce dosimeters (Figure 6). When doing UVA exposure monitoring, the side with
the Mylar film of the dosimeter should face the direction of the UV source. Therefore,
the Malar film transmits almost UVA and filter almost UVB. The phenothiazine film
only responds to the UVA wavelengths, which transmits through the Maylar film. The
pre- and post- exposure absorbances at 370 nm were measured for each UVA dosimeter
in order to measure the change of absorbance.
36
Figure 6. Phenothiazine/Mylar dosimeter made from AusSun Research Lab.
According to the calibration of the dosimeters, the dose that each dosimeter received can
be calculated. The calibration of the UVA dosimeters was undertaken by exposing a
series of dosimeters to the sun on a horizontal plane while concurrent data on UVA was
obtained from AusSun Research Lab’s UV detector on the Kelvin Grove campus, QUT.
According to the formulation of calibration (Figure 7), the dose of UVA exposure for
each individual UVA dosimeter can be calculated.
Figure 7. Phenothiazine dosimeters Summer Calibration Curve
and formulation( AusSun Research Lab)
In summary, the Phenothiazine/Mylar dosimeter is a convenient detector for
monitoring personal solar UVA exposure in different circumstances. In addition, it is
valid and reliable for monitoring solar UVA exposure and allows quantification of
37
the UVA exposures for various field science studies. In this project, indoor workers
and drivers wore UVA dosimeters on their hats and upper arms to measure the UVA
doses they received.
38
3Chapter 4. Research methods
4.1 OVERVIEW OF RESEARCH DESIGN
This research was an observational design with no follow-up.
The main aim of this study was to assess UV exposure and skin damage for indoor
workers and drivers. Regarding UV exposure, both a sun exposure history and one
day’s UV exposure in real life was collected. Information of skin damage related to
sun exposure was collected by relevant questions and also analysed by a novel photo
damage assessment tool. Each participant’s demographics including age, years
residing in Australia, country of birth, gender were analysed with indicators of skin
damage in order to find out influence factors. An ethics application had been
approval prior to commencing the study. Finally, the relationships between UV
exposure and skin damage were analysed using the Statistical Package for Social
Sciences version 16.0 (SPSS).
4.2 HUMAN RESEARCH ETHICS
Ethical approval was obtained from the University Human Research Ethics
Committee, Queensland University of Technology on 30/07/2008. The Committee
confirmed that all ethical implications of the proposed research have been considered
and all relevant local, state and national guidelines, regulations and legislation have
been considered and the investigators conducted the research involving humans
under the National Statement on Ethical Conduct in Research and the university’s
research ethics arrangements.
This research was a level-2 low risk research and conducted under the Declaration of
Helsinki. The Research Safety of the project has been considered and the measures
taken are appropriate. Investigators were trained and were appropriate to the study.
All participants were required to read and sign a consent form (Appendix 4).
Participant’s personal data was treated with strict confidentially.
Approval No: 0800000436
39
4.3 RECRUITMENT AND BIASES
A convenience sample of 44 participants was recruited between January and
March 2009. Among them, there were 41indoor workers and three taxi drivers. The
main investigator sent an email (Appendix 1) the indoor workers and displayed an
information sheet (Appendix 2) at the driver’s company office or presented them with in
a face-to-face setting at taxi ranks in Brisbane city and Fortitude Valley. When
participants showed their interest in this study, the investigator provided further
information and organized a suitable time for them to attend. Once participants agreed to
participate in this study, they were asked to visit the AusSun Research Lab’s clinic,
which is located at 44 Musk Ave, at Kelvin Grove campus, QUT. Eligibility criteria for
this study included Age >18 years and the requirement that participants worked
inside office buildings or they drove a car during their work time as a professional
driver.
There may be potential biases appearing in this study, such as confounding, selection
bias and information bias. Age might be a confounding according to process of
freckles and skin photoaging. The partial correlation could be used to solve this issue.
Selection bias could occur because the participants were from a convenience
sampling frame and may not represent the target population. Information bias may
occur due to systematic measurement error participants’ recall bias.
4.4 DATA COLLECTION
This study was conducted during January and March 2009. This time period
included two months in summer and one month in fall. In those seasons, the solar
UV radiation was at its highest irradiation periods.
4.4.1 Participant demographics
Information on demographics such as age, gender, country of birth and how long they
had been resident in Australia was collected in the questionnaires (Appendix 5, 6).
Participant’s sun exposure and their history of skin diseases related to sun exposure were
also collected. Self-assessment of skin/hair/eye/freckling phenotype at age 18 years was
recorded according to each participant’s subjective judgment (Appendix 7). The
following section explains some variables’ meanings and definitions.
40
Date of birth was required in the questionnaire and was translated into age in year. The
country where a participant was born and how long they were residing in Australia were
being asked. The country where was born was divided into two categories: one was in
Australia and another was outside Australia. The years residing in Australia were also
accounted in years.
In order to get accurate sun exposure time, participants were required to record the
time they spent outside everyday total in one week period (please see detail in
Appendix 8).
A history of sunburn may affect skin damage later in life. Participants were asked to
answer a question about how many major sunburns they had prior to 18 years of age and
after 18 years. Major sunburn included painful and/or blistering after sun exposure and
they were the two typical symptoms of sunburn. Sunburn also includes erythema, pain,
tenderness, swelling, itching, and blistering of the skin (Silverstone, 1997). There were
six selections for choice according to number of sunburns (None, 1, 2-5, 6-10, over 10
and don’t know).
Self-assessment of skin/hair/eye and freckling phenotype was required to recall at
age of 18 year. The question “what is your natural skin colour?” with tip (This is
generally considered to be the colour of the skin at the inside area of your upper arm).
Skin colour was recorded to “fair”, “medium”, “Olive”, “dark/black” and “other” for
choose. Hair colour was recorded as “black”, “brown” and “fair/blonde/red”. Eye
colour was recorded as “brown” “hazel”, and “blue/green/blue-grey”. Freckling
phenotype was assessed according to Harrison’s standard freckling chart (Figure 8)
(Harrison, 1994). The range of the freckling density was from 00 (no freckling) to
100 (very heavy freckling). Participants were asked to recall the degree of freckling
at their face, arms and shoulders at age 18 years by comprising the chart.
41
Figure 8. A standard freckling chart (Harrison, 1994)
4.4.2 Skin colour testing
Skin colour was assessed with a portable spectrophotometer (Konica Minolta CM-
2500D) (Figure 9). The spectrophotometer provided 3 continuous axes: “L*” (Black to
white), “a*” (red to green) and “b*” (yellow to blue). In this study, “L*” score was used
to express the skin colour. The scores of the ‘L*” from 0 to 100 represent skin lightness
on a continuous black/white axes, with 100 being perfectly white and 0 being perfectly
black (Armas, 2007).
42
Figure 9. Skin spectrophotometer: Konica Minolta CM-2500D
Five sites of the body was been measured, they were upper inner aspect of arm, both
hands of the dorsum between thumb and index finger, both side of the face. It was
predicted that skin colour might be different for drivers on each side of the body due to
receiving different sun exposure.
4.4.3 Assessment of UV-induced skin damage
Participants’ skin damage related to UV exposure was measured using a photo damage
assessment tool, which is currently being introduced by Canfield (Figure 10). The novel
technique called RBX was used to monitor skin pigmentation and photoaging. This tool
provides two series of important variables that indicate sun damage: skin pigmentation
and skin photoaging.
4.4.3.1 Skin pigmentation
Skin pigmentation includes skin pigmentation (I) (SPI) and skin pigmentation (II) (SPII).
SPI “occurs when melanin coagulates below the skin surface as a result of sun damage.
SPI are generally invisible under normal lighting conditions. The selective absorption of
the UV light by the epidermal melanin enhances its display and detection by RBX
(Canfield, 2007).
43
SPII “occur as a result of sun exposure” and SPII are “associated with a decrease in skin
elasticity.” SP II are lesions on the skin such as hyperpigmentation, freckles, lentigines,
and melasma. SPII produce an uneven appearance to the skin and are detected by RBX
(Canfield, 2007).
The photo damage assessment tool provides the scores of SPI and SPII in selected areas.
The scores recorded describe and absolute measure for the selected areas’ pigmentation
and is unitless. Absolute scores can be used to analysis the skin damage related UV
exposure, and also can be used to track treatment progress for skin damage.
SPI and SPII are both the important indictors related to skin damage as a result of sun
exposure and both of them to measure the density of pigmentation in absolute value.
There is a minor significance difference between them is that SPI describes deeper
pigmentation on or in skin than SPII. This difference can be confirmed by its technique
RBX or the measurement results.
4.4.3.2 Skin photoaging
The other series of measurements described skin photoaging using scores for the number
of wrinkles, red areas and texture on the face by the photo damage assessment tool.
Wrinkles are “furrows, folds or creases in the skin, which increase in occurrence as a
result of sun exposure, and are associated with decreasing skin elasticity” (Canfield,
2007). Red areas occur when blood vessels and haemoglobin contained in variety of
conditions such as telangiectasis (one photoaging appearance). Texture is a description
of skin smoothness using the photo damage assessment tool.
Figure 10. Photo damage assessment tool (Canfield, 2007)
44
Prior to taking photographs, participants were asked if their skin had been recently
cleaned and whether make-up or skin conditioners had been applied. If make-up or other
products had been recently applied to the face, participants were asked to clean their face
with non-irritant facial wipes. The participants with oily skin were also asked to clean
their skin prior to taking the photographs. If skin was not cleaned, the scores would be
influenced by make-up, oily skin, sunscreen, etc. A hair band was provided to
participants who had long hair in case their hair dropped in the area of imaging. A black
collar drape cloth was draped around each participant’s neck to minimize any reflections
from clothing, which may affect their results. There were three positions for each
participant to be photographed: right-facing, left-facing and front-facing.
Each participant’s ID number, personal details (Date of birth, name, skin colour and skin
condition, gender) was entered into the system.
4.4.4 Personal UV exposure measurement
4.4.4.1 Personal UV dosimetry and calibration
Personal UVA dosimeter and erythemal UV dosimeter were employed to measure
each participant’s one day UV exposure. How to make those dosimeters; how those
dosimeters work and how to do calibration can be seen in Appendix 10.
4.4.4.2 Study protocol of UV exposure measurement
Each participant was given a hat, UVA dosimeters and erythemal UV dosimeters
during the day when they visited AusSun Research Laboratory clinic. In this study,
the UVA dosimeter and erythemal UV dosimeter were in one holder to make them
easy to wear (Figure 11).
Figure 11. UVA dosimeter and erythemal UV dosimeter in one holder
45
The investigator showed participants how to wear the dosimeters on their hats and
clothing. Participants were required to wear the dosimeters on the following sites:
left hat, right hat, left arm and right arm during their working hours on one day, the
day chosen was to be a sunny day (Figure 12). After the questionnaire and skin
assessment was undertaken.
Figure 12. UVA dosimeters and erythemal UV dosimeters
were fixed the hat and upper arm on the clothing
A sun exposure diary was also to be completed during that day. After testing,
participants were asked to put all dosimeters and sun exposure diaries in a QUT pre-
paid return envelope and send it back to AusSun Research Lab. UVA and erythemal
UV exposure and sun exposure time period could then be calculated for each
participant.
4.5 PIOLET STUDY.
A pilot study was conducted in October, 2008 and 15 indoor workers were recruited.
The aim of this study was to test whether or not the feasibility, equipment and
methods were ready for full study. The self-administered questionnaire was
conducted and got useful feedback to revise questionnaire to the final vision.
46
4.6 DATA MEASUREMENT AND DATA ANALYSIS
4.6.1 Data measurement
4.6.1.1 Data storage
All the original materials including questionnaire, results from skin
spectrophotometer and photo damage assessment tool from each participant were
kept in a storage box, which was safely stored in a secure cabinet in the researcher’s
office. Only the Masters’ candidate and his supervisors were allowed to access this
data.
4.6.1.2 Data coding
The coding frame was set up prior to the data collection. The basic rules for the
development of the coding frame were that the codes were mutually exclusive,
coding formats for each item were comprehensive and the codes were applied
consistently (Bowling, 2002). For example, the skin colour was named as Skin
colour for SPSS and was divided into five categories: 1 = Fair skin, 2 = Medium
skin, 3 = Olive, 4 = Dark/Black and 5 = Other. In this research, all missing data was
coded as -1 (See Appendix 9).
4.6.1.3 Data entry
The data from each participant was entered into the SPSS according to each ID
number. Each participant’s data were entered twice to maintain precision of data.
The data was entered twice into two separate SPSS data sets and compared each
variable’s number and sum. If there were any different existing, the candidate looked
back the raw data and found out where the error came from and fixed it. Double data
entry, this method was insuring that two data sets were 100% similar and this method
was a data entry quality control method.
4.6.1.4 Data cleaning
47
Data cleaning was conducted once the data entry was completed and this process
eliminated the errors that occurred during the data collection, coding and input
stages. There were two standard procedures to check data cleaning. The first was a
check for outliers and wild codes by inspecting frequency distributions. The second
data-cleaning procedure involved consistency checks, which focused on internal data
consistency. For example, when checking the range of ages (23-61), the original
records were checked if the value was less than 23 or more than 61. Another
example: gender was coded into two categories: 1 = Male and 2= Female, -1 means
missing data. As such, if a 3 appeared in the database, the raw data record was
checked to conduct data cleaning.
4.6.2 Data analysis
In this research, independent variables were, skin colour, sun exposure time, sun
protective manners, UVA dose and erythemal UV dose. Outcome variables were the
data from photo damage assessment tool.
SPSS was used for all statistical analyses. The data analysis included using statistical
description techniques, bivariate analyses and multivariable analysis. Assumptions
for bivariate analyses such as t-test and ANOVA should meet the requirements for
those tests. The significance level was set at 0.05 (p < 0.05). This means that the
probability of making a Type I error is 0.05. If the sample proportion falls within the
region of acceptance, accept the null hypothesise; otherwise, reject the mull
hypothesis.
4.6.2.1 Descriptive data analysis
The characteristics of all independent variables were examined and described by using frequency
distribution, mean or median and standard deviation.
4.6.2.2 Bivariate analyses
Correlation coefficients between each independent variable (continual variables) and
each outcome variable analyses were analysed. Independent-samples t-test and one-
way analysis of variance (ANOVA) were used to compare the outcome variables
between two or more than two categorical groups. Those test was selected to do
bivariate analyses, the reasons were that: the data in this study were independent of
48
one another; the distribution of scores were normality or could be transfer into
normally distribution (e.g. wrinkles on the face). Scatterplots and bar charts were
also used to analyse the relationship between an independent variable and an
outcome variable. Boxplots were used to compare outcome variables between
different categorical groups.
4.6.2.4 Multiple regressions analysis
Standard multiple regressions were used to examine the relationship between
selected independent variables and the outcome variables. Conducting the regression
was based on correlation. In standard multiple regression, all the independent
variables are entered into the equation simultaneously. Each independent variable
was evaluated in the model and which independent variable was the best predictor of
an outcome. The model also was used to address how well a set of variables was able
to predict a particular outcome.
49
Chapter 5. Results
5.1 DESCRIPTION OF THE STUDY DATA
5.1.1 Participants demographics
There were 41 indoors workers and 3 drivers recruited for this study. The median age
was 34 years (range 23 - 61) for all the participants. A histogram of age distribution
(Figure 13) shows that 79.5% of participants were between 23 to 45 years.
Figure 13. Age distribution of all participants
There were 30 females (68.2%) and 14 males (31.8%) in this study (Table 3). There
were no female participants in the driver’s group. 27 participants (65.9%) were born
in Australia and 17 participants (38.6%) were born outside Australia. The three
drivers all came from overseas.
Indoor workers had been residing in Australia for an average of 31 years (median,
range from 1 to 60 years). Three drivers had been residing in Australia for 8, 10, and
53 years respectively (Table 3).
50
Table 3. Participants demographics
Age Median (range)
Gender
Where was born
Years residing in Australia Median (Range)
Male N (%)
Female N (%)
In Australia N (%)
Elsewhere Australia N (%)
Indoor workers (n = 31)
34 (23-60)
11 (26.8%)
30 (73.2%)
27 (65.9%)
14 (34.1%)
41 (1-60)
Drivers (n = 3)
28 29 61
3 0 0 3 10 (8-53)
Total (N = 44)
34 (23-61)
14(31.8%) 30(68.2%) 27(61.4%) 17(38.6%) 30.5 (1-60) 44(100%) 44(100%)
5.1.2 Characteristics of skin colour, hair colour and eye colour.
Skin colour, eye and hair colour at 18 years are presented in Table 4. Most
participants were either fair (59.1%) or medium/olive skin colour (40.9 %). The
most common hair colour was brown /black (77.3%), followed by fair/blond/red
(22.7%). Eye colour was divided half and half, consisting of a brown/hazel group
and a group with blue/green/blue-grey eyes.
Table 4. Self reported skin, hair and eye colour
Skin colour Hair colour Eye colour
Fair N (%)
Medium /Olive N (%)
Brown/ Black N (%)
Fair/Blond/Red N (%)
Brown/Hazel N (%)
Blue/Green /Blue-grey) N (%)
Total
26 (59.1%)
18(40.9%)
34(77.3%)
10(22.7%)
23 (52.3%) 21 (47.7%)
44(100%) 44(100%) 44(100%)
5.1.3 Sun exposure time
Each participant was asked to report on time they spent outside (all activities,
including: exercise, gardening, driving, walking, recreation) between sunrise and
sunset for seven days. The average time they spent outside was 2.42 hours/per day
(range 0.65 to 12.00 hours) during weekdays and 3.0 hours/per day (0.15 to
10.25hours) between Saturday and Sunday.
51
Figure 14 and Figure 15 show time outside distribution for all participants during
weekdays and weekend. Drivers spent more time outside on both weekdays and
weekends. For example, drivers spent up to 12 hours every day during weekdays and
10.25 hours per day during weekend.
Figure 14. Time outside during weekdays
Figure 15. Time outside during weekends
52
5.1.4 Self reported sunburn and freckling
Each participant reported the number of major sunburns prior to 18 years of age and after
18. A major sunburn was defined as painful and/or blistering as soon as 3 to 5 hours
after UVB exposure, peak at 12 to 24 hours, and subside at 72 hours following sunburn
(Driscoll, 2000). Table 5 provides a description of all participants regarding major
sunburns before and after 18. The number of sunburns (6 and more times) reduced after
18 years comparing with before 18 years from 11(25.0%) to 6 (13.6%). In addition, the
number of participants who had no sunburn after 18 years increased compared with
those before 18 years.
Table 5. Sunburns before 18 years and sunburns after 18 years
Number sunburn
Major sunburns before 18 years Major sunburns after 18 years N (%) N (%)
None 1-5 6 and more Don’ t know
9 (20.5%) 22 (50.0%) 11 (25.0%) 2 (4.5%)
15 (34.1%) 23 (52.3%) 6 (13.6%)
0 Total 44 (100%) 44 (100%)
Table 6 shows the density of freckling on the face, forearms and shoulders during
adolescence. Among all the participants, the density on the forearms (20) was higher
than those on the face (10) and on the shoulder (10) during adolescence. The three
drivers had no freckling on their faces, forearms or shoulders during adolescence during
their adolescence.
Table 6. Density of freckling on the face, forearms and shoulder during
adolescence
Density of Freckling on face
Density of Freckling on forearms
Density of Freckling on shoulder
Median (range)
10 (0-80)
20 (0-80)
10 (0-80)
5.1.5 Results from skin spectrophotometer
An objective measure of each participant’s skin colour was measured by skin
spectrophotometer. The range of the skin spectrophotometer measured was from
“L*” score 0 to 100(total black = 0 and total white = 100). Table 7 presents the
median and range of objective skin “L*” score at sites on the right side of inner
upper arm, both side of hands and both sides of the face. It can be seen that the
53
median of the skin colour on the inner upper arm was higher than other exposure
areas. The reason was that lower sun exposure areas have higher reflectance than the
areas that receive more solar UV radiation. The “L*” scores on both side of hands
and faces were very close for all participants.
Table 7. Results of skin spectrophotometer (“L*” = lightness: range 0-100)
Inner upper arm
Right hand Left hand Right face Left face
Median (range)
69.1 (54.6-74.2)
63.5 (43.3-71.2)
62.8 (43.9-73.8)
63.7 (47.9-69.8)
63.7 (48.5-68.9)
5.1.6 Sun protection measures
About 66% of the participants always or usually wore sunglasses and over half
(54.5%) of them always or usually applied sunscreen, while only about 30% of the
participants always or usually wore a hat when they went outside (Table 8). There
were 72.7% of the workers who preferred to wear short-sleeved shirts. It was noticed
that the minority of the participants in the “Never” category of using any of sun
protection measures, for example, the rate of never wearing a hat was 13.6%, 6.9%
never applying sunscreen and 9.2% never wearing sunglass.
Table 8. Sun protection measures
Measures Frequency of time to using sun projection measures
N (%)
Hat
Always Usually Sometimes Rarely Never
4 (9.1%) 9 (20.5%) 10 (22.7%) 13 (29.5%) 8 (18.2%)
Total 44 (100%) Sunscreen
Always Usually Sometimes Rarely Never
9 (20.5%) 15 (34.1%) 11 (25.0%) 5 (11.4%) 4 (9.1%)
Total 44 (100%) Sunglass
Always Usually Sometimes Rarely Never
17 (38.6%) 12 (27.3%) 7 (15.9%) 4 (9.2%) 4 (9.2%)
Total 44 (100%) Clothing
Short –sleeved Long-sleeved
32 (72.7%) 12 (27.3%)
Total 44 (100%)
54
5.1.7 One-day sun exposure measurement and sun exposure time
Each participant was asked to wear UVA and erythemal UV dosimeters during a typical
workday. Each participant was asked to write a sun exposure diary in order to calculate
his or her sun exposure time period. Table 9 and 10 show the worker’s UVA and UVB
received from sun exposure. 40 indoor workers’ one-day sun exposure was been
measured. On the face, the maximum of received UVA was 0.14 J/m2 and UVB was
0.81 MED. Unfortunately, there was only one driver who did sun exposure testing in
this study. However, the driver received an extremely high dose of both UVA 13.14 J/m2
and UVB 4.99 MED on his right arm.
Indoor workers received 1.8% of the UVA and 1.4% UVB from environmental UV
radiation with the driver mentioned above receiving 16.9% for UVA and 10.3% for
UVB from environmental UV radiation. Indoor workers spent little time outside; it
related to about 6.61% of all of their working time. The drivers spent 97.9% of their
working time in the car.
Table 9. UVA (J/m2) exposure on the left, right arms and on the head
Left upper arm
Right upper arm
Left side of head (a)
Right side of head (b)
Indoor Workers
N = Median Min Max
40 0.0 0.00 0.55
40 0.0 0.00 0.14
40 0.0 0.00 0.14
40 0.0 0.00 0.14
Driver UVA 0.10 13.14 0.01 0.01
Table 10. UVB (MED) exposure on the left, right arms and on the face
Left upper arm
Right upper arm
Left side of head (a)
Right side of head (b)
Indoor Worker
N = Median Min Max
40 0.09 0 0.82
40 0.09 0 1.08
40 0.17 0.00 0.76
40 0.16 0.00 0.81
Driver UVB 0.61 4.99 0.38 0.88
55
5.1.8 Results from the photo damage assessment tool
5.1.8.1 Skin pigmentation on the faces
Skin pigmentation was important outcome variables relating to skin damage due to sun
exposure. The photo damage assessment tool provided data for three sites on the face:
right side, left side and front of face. The values from the three sites together form a
value for the whole face. Tables 11, 12 and Figures 18 and 19, provide a description of
SPI, SPII and their distribution.
Table 11. SPI on the face
Left side of face (a)
Front face (b)
Right side of face (c)
On the whole face (a+b+c)
N Median Min Max
44 12.94 1.14 23.27
44 10.23 0.10 20.27
44 12.84 0.80 23.67
44 35.88 2.03 62.60
Figure 16. SPI on the face
Table 12. SPII on the face
Left side of face (a)
Front face (b)
Right side of face (c)
On the whole face (a+b+c)
N Median Min Max
44 9.67 1.15 13.57
44 8.27 0.03 14.81
44 9.57 0.00 14.15
44 27.70 1.18 41.27
56
Figure 17. SPII on the face
Both SPI and SPII occur when melanin cumulated below the skin surface as a result of
sun damage (Canfield, 2007). As mentioned in introduction of the photo damage
assessment tool, SPI and SPII the results related to UV exposure. They are lesions on the
skin such as hyperpigmentation, freckles, lentigines, and melasma. The difference
between SPI and SPII is that SPI may cover deeper of pigmentation in skin than SPII
does due to using different detective UV wavelengths in RBX. For instance, the average
scores of SPI on the whole face is 35.88, while the score of SPII is 27.70.
5.1.8.2 Wrinkles on the face
Wrinkles on three sites (right-facing, front-facing, left-facing) of each worker’s face
were analysed using the photo damage assessment tool (Table 13). Wrinkles on the
face are a unitless variable, which occurs as a result of sun exposure and are
associated with a decrease in skin elasticity. The score of wrinkles on the whole face
came from the summing up of three sites’ scores (Figure 18).
57
Table 13. Wrinkles on the face
Left side of Face (a)
Front face (b)
Right side of face (c)
On the whole face (a+b+c)
N Median Min Max
44 1.63 0.0 33.16
44 1.42 0.0 18.48
44 1.39 0.10 39.08
44 4.43 0.50 77.4
Figure 18. Wrinkles on the face
5.1.8.3 Red areas on the face
The photo damage assessment tool provides scores for red areas on three sites of
workers. Red areas are also unitless variables, which describe the various conditions
of blood vessels and hemoglobin contained in the skin. The participants had a 9.93
58
(median) score of red areas on their whole face. The range was from 1.8 to 21.6
(Table 14).
Table 14. Red areas on the face
Left side of face (a)
Front face (b)
Right side of face (c)
On the whole face (a+b+c)
N Median Min Max
44 3.30 0.30 8.13
44 3.14 0.45 8.43
44 3.49 0.35 8.95
44 9.93 1.84 21.55
A histogram of red areas on whole face distribution is shown in Figure 19. This
histogram shows a large proportion of participants in this sample with their scores for
red areas from 2.5 to 15, with peaks at score 10.
Figure 19. Red areas on the face
5.1.8.4 Texture on the workers’ face
The photo damage assessment tool provides scores for texture on three sites of
participants. Textures are also unitless variables, which describes skin smoothness in
the selected area of the face. The participants had 11.5 (median) score of texture on
their whole face. The range was from 3.9 to 30.2 (Table 15).
59
Table 15. Texture on the face
Left side of face (a)
Front face (b)
Right side of face (c)
On the whole face (a+b+c)
N Median Min Max
44 2.61 0.41 13.73
44 5.31 0.34 21.94
44 2.73 0.70 15.11
44 11.50 3.93 30.23
A histogram of texture on whole face distribution is shown in Figure 20. This
histogram shows a large proportion of workers in this sample where their score for
texture range from 2.5 to 25, with peaks at around score 2.5 to 15.
Figure 20. Texture on the face
5.2 BIVARIATE ANALYSIS
5.2.1 Correlations between age and outcome variables
5.2.1.1 Skin pigmentation
From the figure 21, there appears to be a moderate, positive correlation between age
and SPI.
60
Figure 21. The scatterplot of age and SPI
From figure 22, it can be seen that there appears to be a moderate, positive
correlation between age and SPII.
Figure 22. The scatterplot of age and SPII
The relationships between age and skin pigmentation was investigated using Pearson
product-moment correlation coefficient. There were medium and positive correlation
between age and skin pigmentation (SPI: r = 0.48, n = 44, p < 0.001; SPII: r = 0.52, n
= 44, p < 0.001) (Table 17).
5.2.1.2 Wrinkles, red areas and texture on the face
Three scatterplots (Figure 23 to 25) show that age and photoaging indicators
(wrinkles, red areas and texture) are related in a linear way, separately. They are all
positively related.
61
Figure 23. The scatterplot of age and wrinkles
Figure 24. The scatterplot of age and red areas
Figure 25. The scatterplot of age and texture
62
The relationship between age and wrinkles, red areas and texture was investigated
using Pearson product-moment correlation coefficient. Correlation analyses show
that age and photoaging indicators have positive linear relationships. Age and
wrinkles have a strong, positive correlation (r = 0.70, n = 44, p < 0.05). Age and red
areas have a positive correlation (r = 0.48, n = 44, p < 0.05). In addition, age and
texture has a positive correlation (r = 0.45, n = 44, p < 0.05).
5.2.2 Correlations between years residing in Australia and outcome variables
5.2.2.1 Skin pigmentation
From the Figure 26 and 27, there appears to be positive correlation between years
residing in Australia and skin pigmentation.
Figure 26. The scatterplot of years residing in Australia and SPI
63
Figure 27. The scatterplot of the years residing in Australia and SPII
The relationships between the years in Australia and SPI, SPII were investigated
using Pearson product-moment correlation coefficient. There was a positive
correlation between the years in Australia and the two outcome variables (SPI: r =
0.77, n = 44, p < 0.001; SPII: r = 0.62, n = 44, p < 0.001).
5.2.2.2 Wrinkles, red areas and texture on the face
Three scatterplots (Figure 28 to 30) show that years residing in Australia and
photoaging indicators (wrinkles, red areas and texture) are related in a linear
direction, separately. With increasing of years residing in Australia, the three
indicators of photoaging are increasing gradually.
64
Figure 28. The scatterplot of the years residing in Australia and wrinkles
Figure 29. The scatterplot of the years residing in Australia and red areas
Figure 30. The scatterplot of the years residing in Australia and texture
65
The relationship between the years residing in Australia and three photoaging
indicators were investigated using the Pearson product-moment correlation
coefficient (Table 16). There was a positive correlation between the years residing in
Australia and wrinkles (r > 0.5).
Table 16. Correlations between years residing in Australia and wrinkles, red
areas and texture
Variables between N r Pearson’s p - value Wrinkles on the face Years residing in Australia
44 0.65 p < 0.05
Red areas on the face Years residing in Australia
44 0.44 P < 0.05
Texture on the face Years residing in Australia
44 0.45 p < 0.05
5.2.3 One day UV exposure and skin damage
There was no linear relationship found between one-day exposure (UVA and UVB
exposure) and skin damage (SPI, SPII, wrinkles, red areas and texture).
5.2.4 Comparisons of outcome variables by major sunburn groups
5.2.4.1 SPI and SPII
A one-way between-groups analysis of variance was conducted to explore the
difference of SPI and SPII between the two groups (Table 17). According to the
times of sunburns, the workers were divided into three groups:
Group1: Never had sunburn;
Group 2: 1-5 major sunburns;
Group 3: 6 and more major sunburns.
Table 17. Comparisons SPI and SPII by major sunburn groups
Groups F/G-G p - value SPI
Between groups F = 6.917 p < 0.05 Within groups
Group 1 – Group 2 Group 1 – Group 3
p < 0.05 p < 0.05
SPII
Between groups F = 7.728 p < 0.05 Within groups
Group 1 – Group 2 Group 1 – Group 3
p < 0.05 p < 0.05
SPI and SPII were statistically significantly different between Group 1 and other
groups before 18 years.
66
For SPI, p < 0.05 level for three groups (F = 6.917, p < 0.05). Post-hoc comparisons
using the Tukey HSD test indicated that the mean score for the Group 1 (mean =
19.29) was significantly different from that for Group 2 (mean = 36.6, p < 0.05) and
also different from Group 3 (mean = 44.5, p < 0.05). Figure 31 shows the mean of
SPI the three groups before 18 years old.
There was not any significant difference between other two groups (Group 2 and
Group 3) before 18 years old.
After 18 years old, there was not any significant difference within any two groups.
Figure 31. SPI (above)/SPII (below) in three groups according to number
of major sunburn before 18 years old
67
For SPII, there were significant differences between groups before 18 years at p <
0.05 levels for the three groups (F = 7.728, p < 0.05). Post-hoc comparisons using the
Tukey HSD test indicated that Group 1 (mean = 15.5) was significantly different
from Group 2 (mean = 26.9, p < 0.05) and also different from Group 3 (mean = 32.1,
p < 0.05). Figure 38 shows that the mean of SPII in the three groups before 18 years
old.
There was not any significant difference between the other two groups (Group 2 and
group 3) before 18 years. After 18 years, there was not any significant difference for
SPII within any two groups.
5.2.4.2 Wrinkles, red areas and texture.
There were no significant differences between groups, which were divided according
to the number of major sunburns, and outcome variables (wrinkles, red areas and
texture) before and after 18 years of age.
5.2.5 Comparisons of outcome variables by skin colour, hair colour, and eye colour
groups
5.2.5.1 SPI and SPII
The two groups were divided according to worker’s skin colour: one was with fair
skin colour and another was with medium/olive skin colour. SPI and SPII were
compared in two skin colour groups by using independent-samples t-tests. There
were significant differences in both SPI and SPII for the two groups (Table 18). For
SPI, mean difference = 14.6, 95% CI: 6.46 to 22.8, t = 3.612, df (42), p < 0.05. For
SPII, mean difference = 7.69, 95% CI: 2.27-13.11, df (42), p < 0.05).
Table 18. Comparisons of SPI and SPII by skin colour groups
outcome Variables
Group
N (percent)
Mean
Mean difference 95% CI
Std, Error difference
t
p -value
SPI Fair (Medium /Olive)
26 (59.1%) 18 (40.9%)
41.0 26.4
14.6 (6.46-22.8)
4.01
3.612
p < 0.05
SPII
Fair (Medium / Olive)
26 (59.1%) 18 (40.9%)
29.0 21.0
7.69 (2.27-13.11)
2.69
2.863
p < 0.05
68
The two groups were also divided according to worker’s hair colour: one was with
black/brown hair colour and another was with fair/blond/red hair colour. SPI and
SPII were compared in the two hair colour groups by using independent-sample t-
tests (Table 19. There were significant differences in SPI between the two groups.
For SPI, mean difference = 13.6, 95% CI: 3.46-23.73, t = 2.708, df (42), p < 0.05.
There was no significant difference in SPII for the two groups.
Table 19. Comparisions of SPI and SPII by hair colour groups
Outcome Variables
Group
N (percent)
Mean
Mean difference 95% CI
Std, Error difference
t
p-value
SPI Black/Brown Fair/Blond/Red)
34 (77%) 10(23%)
31.9 45.5
13.6 (3.46-23.73) 5.02 2.708 p < 0.05
SPII
Black/Brown Fair/Blond/Red)
34 (77%) 10(23%)
24.5 30.3
5.74 (0.98-12.46) 2.93 1.742 p < 0.05
Two independent-sample t-tests were conducted to compare SPI and SPII for the two
eye colour groups. One group had brown/hazel eyes and the other group had
blue/green/blue-grey eyes. There were significant differences in scores of both SPI
and SPII for the two eye colour groups (Table 20). The score of SPI in the
brown/hazel group (mean = 27.9) was lower than the scores in the blue/green/blue-
grey eyes group (mean = 42.8), the mean difference = 14.9, 95% CI: 6.96 to 22.88, t
= 3.94, df(42), p < 0.05. The scores of SPII in the brown/hazel eyes group (mean=
23.1) are lower than the scores in the blue/green/blue-grey eyes group (mean = 28.8),
the mean difference = 5.78, 95% CI: 0.22-11.33, t = 2.1, df (42), p < 0.05.
Table 20. Comparisions of SPI and SPII by eye colour groups
outcome Variables
Group
N (percent)
Mean
Mean difference 95% CI
Std, Error difference
t
p-value
SPI Brown/Hazel (Blue/Green Blue-grey)
23 (52.3%) 21 (47.7%)
27.9 42.8
14.9 (6.96-22.88)
3.94 3.785 p < 0.05
SPII
Brown/Hazel (Blue/Green Blue-grey)
23 (52.3%) 21 (47.7%)
23.1 28.8
5.78 (0.22-11.33)
2.75 2.1 p < 0.05
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5.2.5.2 Comparisons of wrinkles, red areas and texture by skin colour groups,
hair colour groups and eye colours groups
There were not any significant differences for wrinkles, red areas and texture in the
pairs of groups divided according to skin colour, hair colour and eye colour. In other
words, skin colour, hair colour and hair colour do not affect the score for wrinkles,
red areas and texture on the skin.
5.2.6 Comparisons of outcome variables by gender
An independent-sample t-test was conducted to compare the outcome variables for
male and female workers (Table 21).
Table 21. Comparisons of SPI and SPII by gender
Outcome Variables
N
Mean
Mean Difference (95% CI)
Standard Error Difference
t
P -value
SPI for Male SPI for Female
14 30
28.7 37.8
9.2 (0.2-18.7) 4.7 1.975 0.055
SPII for Male SPII for Female
14 30
23.1 27.1
3.9 (2.2-10.1) 3.0 1.289 0.258
There was no significant difference in SPI for males (mean = 28.7,) and females
(mean = 37.8, t = 1.975, df (42), p > 0.05).
There was also no significant difference in SPII for males (mean = 23.1,) and
females (mean = 27.1, t = -0.59, df (42), p > 0.05).
There were no significant differences in wrinkles and texture for males and females.
However, there was a significant difference in red areas between males and females.
The score of red areas for males (mean = 14.1) was higher than the scores in females
(mean = 8.9), the mean difference = 5.19, 95% CI: 2.00 to 8.37, t = 3.291, df(42), p <
0.05 (Table 22).
Table 22. Comparisons of red areas by gender
Outcome Variables
N
Mean
Mean Difference (95% CI)
Standard Error Difference
t
p -value
Red areas for Male Red areas for Female
14 30
14.1 8.9
5.19 (2.00 -8.37) 1.58 3.291 p < 0.05
70
5.2.7 Correlations between the density of freckling and outcome variables
The relationship between freckling with SPI and SPII were investigated using the
Pearson product-moment correlation coefficient. There is a positive relationship
between the density of freckling on the face during adolescence and SPI (Figure 32).
There were positive correlations between the density of the freckling and SPI on the
face (r = 0.582, N = 44, p < 0.05).
Figure 31. The scatterplot of the freckling and SPI on the face
There is a positive relationship between the density of the freckling and SPII on the
face (Figure 33). However, this relationship did not have any statistically significant
correlation (r = 0.261, N = 44, p > 0.05).
71
Figure 32. The scatterplot of the freckles and SPII on the face
There were no significant correlations between freckles and photoaging indicator
variables: wrinkles, red areas and texture.
5.2.8 Comparisons of outcome variables by the place where was born.
The boxplots of Figure 34 and Figure 35 show that SPI and SPII on the whole face at
different levels for the groups born in Australia and outside Australia. Both SPI and
SPII are higher in the group born in Australia than in the group born outside
Australia.
72
Figure 33. The boxplot of the place where was
born and SPI on the face
Figure 34. The boxplot of the place where was
born and SPII on the face
73
From Table 23, an independent-samples t-test shows that there were significant
differences for SPI and SPII between the workers who were born in Australia and
outside Australia. For SPI, the group who were born in Australia (mean = 43) was
higher than the group from outside Australia (mean = 23.2, t = 6.126, p < 0.05). For
SPII, the group who were born in Australia (mean = 29.5,) is also higher than the
group from outside Australia (mean = 21, t = 0.3.561, p < 0.05).
Table 23. Comparisons of SPI and SPII by the place where was born
Outcoome Variables
N (percent)
Mean
Mean difference (95%CI)
Std. Error Difference
t
p-value
SPI Australia Outside Australia
27 (65.9%) 14 (34.1%)
43.0 (10.1) 23.2 (9.3)
19.9 (13.3, 26.4)
3.24
6.126
p < 0.05
SPII Australia Outside Australia
27 (65.9%) 14 (34.1%)
29.5 (6.9) 21.0 (7.9)
8.5 (3.7, 26.3)
3.70
3.561
p < 0.05
There were no significant differences on wrinkles, red areas and texture for the
participants who came from Australia or outside Australia.
5.3 MULTIVARIABLE REGRESSION BETWEEN INDEPENDENT
VARIABLES AND OUTCOME VARIABLE
5.3.1 Rationale for variables included in multivariable regression analysis
The sample in this study was a convenient sample and the size was small. However,
the observations that made up my data were independent of one another. Scores on
each variable were normality distributed. Therefore, multiple regressions were used
to address: 1. whether the set off variables should be able to predict each outcome, 2.
which variable in a set of variables was the best predictor of an outcome. 3.
Confounding bias would be solved by the multiple models. All the variables were put
into the model had linear relationship.
The following variables were included in the multivariable regression analysis for
possible determinants of SPI, SPII, wrinkles, red areas and texture on the whole face:
74
age, years residing in Australia, time spent outside during weekdays, time outside
during weekends, freckling on the face at 18 years, skin reflectance on the face.
Almost all variables used in the multivariable regression showed significant
correlation with outcome variable at the bivariate level except skin reflectance on the
face. Skin reflectance was hypothesized to be a determinants of both of SPI and SPII
on the whole face. Thus, variable was then added to the model.
In this model, the variables of one-day sun exposure were omitted due to all the
values being too small to do this analysis. In addition, this was a one-day sun
exposure for the workers; there has not any statistically significant correlation
relationship with the outcome variables. Thus, then was not added in to the model of
multiple regressions.
Regarding the premise for standard multiple regression, all the independent variables
should be entered into the equation simultaneously. In order to minimize the effect
on the predictive power, the only one variable- skin colour was been entered into the
model instead of all variables to describe personal characteristics.
5.3.2 Confounding and effect modification
Partial correlation was used to explore the relationship between outcome variables and freckles,
while controlling for scores on age. Preliminary analyses were performed to ensure no violation
of the assumptions of normality, linearity and homoscedasticity. There was a medium, positive,
partial correlation between age and SPI, r = 0.42, n = 41, p < 0.05. However, there was no
correlation relationship between age and freckles. Therefore, age should be a factor between SPI
and freckles in this study instead of as a confounding.
There was no difference for SPI and SPII according to gender. Therefore, gender was not put into
the multivariable regression analysis.
Results of Multivariable regression analysis for determinants of SPI on the face
Table 24 presents the results of the multivariable regression analysis for possible
determinants of SPI on the whole face. Years residing in Australia and freckles on
the face at 18 years were the variables to reach statistical significance as a
determinant of the SPI on the face (B = 0.57, p < 0.05). The density of freckling on
75
the face as adolescent showed an increased trend with SPI on the whole face (B =
0.382, p < 0.05). The other variables included in the model: age, time outside during
weekdays, time outside during the weekend, skin colour (reflectance ratio) on the
face did not show any independent determinants of SPI on the face.
As a group, the 6 variables explained a significant proportion in the variability of SPI
on the face of the workers (Adjusted R2=0.714; F=12.737, p < 0.05). Adjusted R2
was reported due to the relatively small sample size used (N=44) to provide a more
accurate estimate of the true population value. The adjusted R2 value can be
interpreted as the model explaining 71.4% of the variance in SPI on the face.
Table 24. Regression Result for possible determinants of SPI on the face
Determinants B t p-value Age in years 0.103 0.802 0.428
Years residing in Australia 0.57 4.319 p < 0.05 Time outside weekdays 0.022 0.186 0.853 Time outside weekend 0.123 1.087 0.285
Freckling on the face during adolescence
0.382 3.706 p < 0.05
Skin colour (L) -0.018 -0.137 0.892
Model summary
R2: 0.754 Adjusted R2: 0.714
F(df): 18.906 p < 0.05
5.3.3 Results of Multivariable regression analysis for determinants of SPII on the
face
Table 25 shows the results of the multivariable regression analysis for possible
determinants of SPII on the face. Years residing in Australia were the only variable
to reach statistical significance as a determinant of SPII on the whole face (B = 0.484,
p < 0.05). The other variables in the model were not independent determinants of
SPII on the face.
76
Table 25. Regression Result for possible determinants of SPII on the face
Determinants B t p-value Age in years 0.276 1.644 0.109
Years residing in Australia 0.484 2.687 p < 0.05 Time outside weekdays -0.297 -1.517 0.138 Time outside weekend 0.270 1.719 0.094
Freckling on the face during adolescence
0.092 0.668 0.508
Skin colour (L) -0.038
-0.231
0.819
Model summary
R2: 0.476 Adjusted R2: 0.391
F(df): 5.593 p < 0.05
As a group, the 6 variables explained a significant proportion in the variability of
SPII on the face (Adjusted R2=0.461; F=4.028, p < 0.05). Adjusted R2 was reported
due to the relatively small sample size used (N=44) to provide a more accurate
estimate of the true population value. The adjusted R2 value can be interpreted as the
model explaining 39.1% of the variance in SPII on the face.
5.3.4 Results of Multivariable regression analysis for determinants of wrinkles on
the face
Table 26 shows the results of the multivariable regression analysis for possible
determinants of wrinkles on the face. Age was the only variable to reach statistical
significance as a determinant of wrinkles on the whole face (B = 0.590, p < 0.05).
The other variables were not any independent determinants of wrinkles on the face.
Table 26. Regression Result for possible determinants of wrinkles on the face
Determinants B t p-value Age in years 0.590 3.786 p < 0.05
Years residing in Australia 0.197 1.147 0.259 Time outside weekdays 0.053 0.365 0.718 Time outside weekend 0.163 1.133 0.265
Freckling on the face during adolescence
0.003
0.024 0.981
Skin colour (L) 0.104 0.845 0.404 Model summary
R2: 0.548
Adjusted R2: 0.474 F(df): 7.464 p < 0.05
77
As a group, the 6 variables explained a significant proportion in the variability of
wrinkles on the face (Adjusted R2=0.474; F=7.464, p < 0.05). Adjusted R2 was
reported due to the relatively small sample size used (N=44) to provide a more
accurate estimate of the true population value. The adjusted R2 value can be
interpreted as the model explaining 47.4% of the variance in wrinkles on the face.
5.3.5 Results of Multivariable regression analysis for determinants of red areas on
the face
Table 27 shows the results of the multivariable regression analysis for possible
determinants of red areas on the face. There is no best variable to reach statistical
significance as a determinant of red areas on the whole face.
Table 27. Regression Result for possible determinants of red areas on the face
Determinants B t p-value Age in years 0.305 0.669 0.104
Years residing in Australia 0.256 1.271 0.212 Time outside weekdays 0.238 1.401 0.169 Time outside weekend 0.134 0.795 0.432
Freckling on the face during adolescence
-0.020 -0.133 0.895
Skin colour (L) 0.034 0.234 0.817 Model summary
R2: 0.38
Adjusted R2: 0.279 F(df): 3.78 p < 0.05
As a group, the 6 variables explained a significant proportion in the variability of red
areas on the face (Adjusted R2=0.279; F=3.781, p < 0.05). Adjusted R2 was reported
due to the relatively small sample size used (N=44) to provide a more accurate
estimate of the true population value. The adjusted R2 value can be interpreted as the
model explaining 27.9% of the variance in red areas on the face.
5.3.6 Results of Multivariable regression analysis for determinants of red texture
on the face
Table 28shows the results of the multivariable regression analysis for possible
determinants of texture on the face. There is no best variable to reach statistical
significance as a determinant of texture on the whole face.
78
Table 28. Regression Result for possible determinants of texture on the face
Determinants B t p-value Age in years 0.333 1.772 0.085
Years residing in Australia 0.189 0.910 0.369 Time outside weekdays 0.256 1.468 0.151 Time outside weekend 0.030 0.176 0.861
Freckling on the face during adolescence
0.034 0.213 0.832
Skin colour (L) -0.026 -0.176 0.861 Model summary
R2: 0.344
Adjusted R2: 0.277 F(df): 3.228 p < 0.05
As a group, the 6 variables explained a significant proportion in the variability of
texture on the face (Adjusted R2=0.277; F=3.228, p < 0.05). Adjusted R2 was
reported due to the relatively small sample size used (N=44) to provide a more
accurate estimate of the true population value. The adjusted R2 value can be
interpreted as the model explaining 27.7% of the variance in texture on the face.
79
Chapter 6. Discussion and Conclusion
6.1 ONE DAY SUN EXPOSURE AND SKIN DAMAGE
The One-day UV exposure measurements showed that indoor workers received a
relatively low UV exposure during one day’s work. The median of UVB that indoor
workers received on the face was 0.1 MED (Median = 0.01, range 0.01- 1.51MED) and
the dose of UVA they received was zero UVA (Median = 0, range: 0 - 0.14 J/cm2) on the
face. According to a study by Mccurdy (2003), office workers spend an average 80 % of
their days indoors. It has been estimated that individuals who work indoors receive of
the equivalent of 2.8 to 4 MED per day in spring and 0.8 MED in winter or on cloudy
summer days (Parisi, 2000). The dose of UVB in this study was lower than Parisi’s
finding. Indoor workers also received a lower amount of UVA exposure during the one-
day of sun exposure testing compared to the previous study (Parisi, 2000). As sunlight
passes through the atmosphere, the UV radiation reaching the earth’s surface is mainly
composed of UVA with a small UVB component (WHO, 2008). UVA transmission
through glass was estimated between 2.1% to 70% of outside environment UV radiation
(Gies, 1992). Many reasons would lead to low UVA exposure inside office buildings,
such as window conditions (tanned, with awnings), direction of the sun, distance to the
windows and furniture in the room.
The research was the first time using photo damage assessment tool to analysis skin
damage in Australian population. Then, the background information of skin damage for
the workers can be seen in this study. The average of SPI on the face was 35.9 (median,
range 2 - 62.6) and the average of SPII on the face was 27.7 (median, range 1.2 - 41.3)
among indoor workers and drivers. Neither SPI nor SPII on the face were associated
with one-day UVA and UVB exposure (UVA-SPI R: -0.237, UVA-SPII: R:-0. 082;
UVB-SPI R; -0.224; UVB-SPII R: -0.059). The possible reason is that the dose of one-
day UV exposure was not high enough to result in any effects on the skin. Another
reason is that the one-day exposure might not represent annual UV exposure for each
participant.
80
One driver received a high UV exposure on the right side of his arm during the one day
sun exposure testing. The driver received 13.14J/cm2 UVA (16.9% from environmental
UV radiation) and 4.99 MED UVB (10.3% from environmental UV radiation) on the
right side of his arm. He received 0.01 J/cm2 UVA and 0.88 MED UVB on his face.
Parisi’s study (2000) showed that the range of the annual UVA exposures in a vehicle
was 489 to 2969 J/cm2 or 1% to 8% of the ambient UVA. A professional driver in a car
with windows closed has been estimated to receive 35 MED each year (220 working
days), which was about 0.15 MED in each working day (Moehrle, 2003). In this
research, three drivers were recruited and only one driver did UV exposure testing. The
driver received 13.14 J/cm2 UVA, which was similar to the result found by Parisi (489 to
2969J/cm2 annual is about 2.2 to 13.5J/cm2 per day). However, the driver received
extremely high UVB (4.99MED) on the right side of his arm during the one-day sun
exposure testing in a car. This result is more than 33 times higher than Moehrle’s
estimation for a driver in a car. This level of UVB may seriously damage skin for year-
long exposure.
Although there was only one driver who had UV exposure in this study, the driver’s UV
exposure was extremely high and the results were found significant. This highlights the
need for further UV exposure monitoring and to explore the relationship between UV
exposure and skin damage for professional drivers. Dr Fosko’s finding indicated that
UVR exposure has harmful effects on drivers and skin cancer is linked to frequent
driving (Hitti, 2007). Sun exposure could be a potential occupational risk factor for
drivers relating to skin damage.
One-day UV exposure was found to have no linear relationship with wrinkles, red areas
and texture on the face. The possible reasons are the same as those described that of the
relationship between UV exposure and SPI and SPII. One is that the dose of one-day UV
exposure was not high enough to result in any effects on the skin. Another reason is that
the one-day exposure might not represent annual UV exposure for each participant.
81
6.2 AGE, YEARS RESIDING IN AUSTRALIA AND THE PLACE WHERE
WAS BORN VERSUS OUTCOME VARIABLE
6.2.1 Age, years residing in Australia and the place where was born Versus SPI and
SPII
The present study suggested that skin damage was associated with age and years residing
in Australia. The median age for participants was 34 (range 23-60) and years residing in
Australia was 31 years (median, range 1-60). The relationship between skin damage and
age and years residing in Australia were analysed. The results showed that both SPI and
SPII had a medium to strong, positive correlation with age (SPI r = 0.48, p < 0.05; SPII, r
= 0.52, p < 0.05) and years residing in Australia (SPI r = 0.77, p < 0.05; SPII, r = 0.62, p <
0.05).
Australia has high levels of UV radiation from the sun due to its geographical position,
and the shorter sun-earth separation of 3% in summer in Australia compared with the
summer in the northern hemisphere. Australia has 7% additional intensity of solar UV
radiation in summer than the other side of the earth. This fact, together with clear
atmospheric conditions and the ozone layer destruction over Antarctica results in
Australia getting 12-15% more than similar locations in the Northern Hemisphere. Most
cities in Australia get more than 4000 MED annually (Gies, 2004). People who live in
this environment have more chance to receive a higher dose of UV radiation and skin
damage. The medium to strong correlation between age, years residing in Australia and
SPI and SPII on the face confirmed again that UV radiation has a harmful effect on skin.
The results from multivariable regression analysis suggested that years residing in
Australia had a significant impact on SPI and SPII. In other words, the more time people
live in Australia, the more pigmentation could appear on the skin. This statement was
also confirmed by an independent-samples t-test between the group who were born in
Australia and the group who were born outside Australia. The t-test shows that there was
a significant difference in SPI and SPII between the two groups. For SPI, the group
who was in Australia (M = 43) was higher than for those who were born outside
Australia (M = 23.2, t = 6.126, p < 0.05). For SPII, the group from Australia (M = 29.5,)
was also higher than the group from outside Australia (M = 21, t = 0.3.561, P = 0.001). It
was reported by the Cancer Council Australia that Australia has one of the highest
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incidences of skin cancer in the world, nearly four times the rates in Canada, the US and
the UK (Cancer Council Australia, 2009). Therefore, people who come from other
countries to Australia should protect their skin while residing in such a high UV
exposure environment.
6.2.2 Age, years residing in Australia and the place where was born versus
photoaging
Our results displayed increasingly strong correlations between age and wrinkles, which
show a strong, positive correlation (r = 0.7, n = 44, p < 0.05). Moderate, positive trends
can be seen for age and red areas (r = 0.49, n = 44, p < 0.05) and age and texture (r =
0.45, n = 44, p < 0.05). Years residing in Australia have the same trend as age on
photoaging (wrinkles r = 0.65, n = 44, p < 0.05; red areas r = 0.44, n = 44, p < 0.05;
texture r = 0.45, n = 44, p < 0.05). There were no significant differences for the
participants who were born in Australia or outside Australia on their photoaging.
Photoaging of the skin is a complex biological process, which includes intrinsic and
extrinsic aging (Wlaschek, 2001). Extrinsic photoaging is the result of exposure to the
sun exposure in environment. ‘Photoaging is the superposition of chronic ultraviolet
(UV)-induced damage on intrinsic aging and accounts for most age-associated changes
in skin appearance’ (Yaar, 2007). Photoaging is a chronic process. Our results show that
as age and years residing in Australia increase, photoaging indicators, including
wrinkles, red areas and textures, also increase.
6.3 SUNBURNS RELATED TO SPI, SPII.
Sunburn is the result of overexposure to solar UV radiation. In this study, the numbers of
major sunburns before and after 18 years were recalled in the questionnaire. Before 18
years, 75% of the participants had one major sunburn at least. The School of Medicine
of the St. Louisa University, USA, also found similar results. Before 18 years old was
the time to get sunburn much more easily than adults because younger people were more
susceptive to skin damage and their skin was more sensitive than the skin of adults. It
reported that more than half of one’s lifetime sun exposure occurs before 20 years of
age, and this is correlated with the risk of developing skin cancer as an adult. It is a result
of damage that has occurred during childhood and /or adolescence (Lucas, 2002). Our
results confirmed this statement again by comparing SPI and SPII in different sunburn
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groups. After 18 years, the percentage of sunburn decreased to 65.9% for the participants
in this study. A one-way between-groups analysis of variance was conducted to explore
the difference of major sunburns before and after 18 years with the SPI and SPII. There
was a statistically significant difference for SPI and SPII before 18 years at the p <
0.05levels for the four groups (SPI: F = 6.92, p = 0.001; and SPII: F = 7.77, p < 0.05).
Post-hoc comparisons using the Tukey HSD test indicated that the SPI and SPII for the
Group 1 (Never Sunburn) were significantly lower than other Groups with one or more
sunburns. After 18 years, there was no any significant difference between any two
groups related to SPI or SPII. This result shows that the number of major sunburns
before 18 years was a risk factor for skin damage in adults. The other study by Simone
(1994) also confirmed that children skin damage were significantly associated with sun
exposure of more than 4 hours perday and with a history of bunburn. Therefore, it is
important to protect skin from sun exposure in early stage of lifetime, in particular before
18 years during childhood and adolescence.
6.4 DIFFERENCE BETWEEN GROUPS OF SKIN COLOUR, HAIR
COLOUR AND EYE COLOUR
People with different skin types, hair colour and eye colour are known to have different
responses to UV radiation. In order to compare the results of skin damage for the
participants with different skin colour, all the workers were divided into two skin colour
groups. One group had a fair skin colour and the other group included people with a
medium/olive skin colour. The two groups t-test showed that the group with the fair skin
colour had higher SPI (Mean = 41) than the group with medium/olive skin colour (Mean
= 26.4, t = 3.612, p < 0.05). SPII were also different between the fair skin colour group
(Mean = 29) and the medium/olive skin colour group (Mean = 21, t = 2.863, p < 0.05).
All the participants were also divided into two hair colour groups: the black/brown hair
colour and the fair/blond/red colour group. SPI on the face were significantly different
for the participants with fair/blond/red hair (Mean = 40.1) and black/brown hair (M =
19.9, t = 4.77, p < 0.05) as well as SPII for participants with fair/blond/red hair (Mean =
33) and black / brown hair (M = 18.1, t = 3.493, p < 0.05).
The participants were divided into two groups according to their eye colours; one group
with blue/green/blue-grey eye colour and the other had brown/hazel eye colour. The SPI
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on the face for the participants with blue/green/blue-grey eyes (Mean = 42.8) were
significantly different from the participants with brown /hazel eyes (Mean = 28.8, t =
2.1, p < 0.05).
All results above show that fair skinned participants with either fair/blond/red hair or
blue/green/blue-grey eyes had higher SPI and SPII than other participants.
6.5 STUDY LIMITATIONS & STUDY STRENGTHS
6.5.1 Study Limitations
This study was conducted with the aim to assess UV exposure and skin damage for
both indoor workers and professional drivers. However, of the three drivers recruited
only one of them had UV exposure data. The reasons for unsuccessful recruitment
for drivers might be because: firstly, the rate of drivers’ participation was over-
estimated; secondly, there were no incentives for drivers’ participation and no
rewards to compensate their time for participation. A hat was given as a small gift
and also used as a tool for the study (asked each participant to wear the hat with
attached badges).
In this study, a convenience sample was used rather than a random sample for indoor
workers and professional drivers. The small sample size (N = 41 for the indoor
workers and N = 3 for the professional drivers) reduced the generalisibility of the
results to the general indoor workers and professional driver population. Therefore, a
statistical comparison analysis could not be done between these two groups due to
small sample size in the driver’s group. In addition, even for the indoor workers, the
relatively small sample size (N = 41) was still not large enough especially when it
was divided into subgroups. The ideal sampling method would be simple random
sampling for both indoor workers and professional drivers.
One-day sun exposure was measured for each participant and a sun exposure diary
was requested. However, we did not use this data to estimate the annual sun
exposure. The reason was that one-day sun exposure did not represent the general
average daily sun exposure through a year. Sun exposure during weekdays and
weekends might be totally different. Seasons change; weather conditions and workers’
85
activities can impact on sun exposure (Gies, 2004; Diffey, 1998a; Ola, 2005). Therefore,
further studies should monitor UV exposure in different seasons and weather conditions
as well as considering participants’ activities. For instance, to measure sun exposure for
a few days in different seasons during weekdays and at weekends in order to get more
accurate data about annual UV exposure. The relationship between sun exposure and
skin damage needs further study.
The photo damage assessment tool was used in this study to explore the damage on
complexion. However, skin damage on other exposure sites were not assessed such as
hands and forearms. To address this need, whole body skin scanning is to be installed in
the AusSun Research Lab in coming months. The correlation between sun exposure and
skin damage on all exposure sites of the body can be soon analysed.
6.5.2 Study strengths
The study used the photo damage assessment tool for the first time to analyse skin
damage among indoor workers and professional drivers in Australia. This tool can
provide a series of data related to sun exposure such as SPI, SPII and three variables
related to photoaging. In a past study to measure the density of melanocytic naevi, a UV
camera was used, but the density of melanocytic naevi had to be counted by hand. It was
time-consuming and might not be suitable for a large-scale sample study. Compared
with using a UV camera, this tool can provide a highly effective, accurate set of data for
analysis of complexion damage related to sun exposure over time.
The study also used dosimeters to measure UVB and UVA at the same time for the
participants. Polysulphone dosimeters have been used in UV research for more than
three decades and they have a high response in the UVB waveband. UVA dosimeters
have been recently introduced and their use has been refined by the AusSun Research
Lab in recent years. This produce development testing for the UVA dosimeter has
indicated its validity, reliability and convenience as a detector to monitor personal solar
UVA exposure.
The study has endeavoured to collect comprehensive information in order to analyse the
relationship between sun exposure and skin damage. In the questionnaire, data on age,
gender, years residing in Australia, skin, hair, and eye colour, history of skin disease, sun
86
exposure history and sun protective measures were collected. In addition, freckling as an
adolescent was recalled and skin reflections were measured by skin spectrophotometer.
Finally, appropriate statistical methods were used to describe and analyse each variable’s
characteristics and the relationships between them.
6.6 THE STUDY IMPLICATIONS
One finding from the present study was that the participants who experienced one or
more major sunburns before 18 years had higher SPI and SPII than those without any
sunburns. This suggests that sunburns in the early stage of life could influence the level
of skin damage in later life. A reason for this is that people under 18 years of age are
highly sensitive to sunlight and can easily receive skin damage. Therefore, protecting the
skin from extensive sun exposure for the younger generation should be a significant
priority in future prevention initiatives.
The present study also found that age and years residing in Australia were moderately to
strongly related to skin damage. A reason for this is that Australia has high levels of
environmental UV radiation. Therefore, people born or residing in Australia should
enhance their sun protective measures.
The present study shows that one driver received a high UV exposure on the right side of
his arm during the one-day sun exposure testing. According to previous reports, there
are moderate to hight UV exposure behind glass, and skin cancer is linked to frequent
driving (Moehrle, 2003; Parisi, 2000; Lucas, 2002). Therefore, it is strong remind that
professional drivers should take sun protective measures during sunrise and sunset
period when they are driving in a vehicle in order to reduce skin damage related to UV
exposure.
Finally, this study found that people with fair skin, either fair/blond/red hair or
blue/green/blue-grey eyes had higher SPI and SPII than people with medium/olive skin.
Therefore, people with fair skin and higher levels of SPI and SPII should reinforce their
sun protective measures and have regular shin checks.
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6.7 RECOMMENDATIONS FOR FUTURE RESEARCH
In order to analyse the correlation between UV exposure and skin
damage, improved data on annual UV exposures needed. It is suggested
that UV exposure measurements should be conducted over a few days
during weekdays and weekends and in different seasons.
Skin damage (SPI, SPII and indicators of photoaging) should be
measured on all exposure sites (such as hands, forearms and neck) in
order to obtain more detailed data on skin impacts of UV exposure.
To improve recruitment, participants could receive incentives and
rewards for their time and participation, especially for studies involving
professional drivers.
6.8 CONCLUSION
The aim of this study focused on indoor workers’ and professional drivers’ UV exposure
and the subsequent impact on skin.
The findings show that indoor workers received relatively low levels of UV exposure
(both UVA and UVB) during one working day. One driver received a high level of UV
exposure (UVA and UVB) during his working time (day time), especially on the right
side of his body. Therefore, drivers should take sun protective measures all the time
during their working hours between sunrise and sunset. In addition, further research
needs to explore professional drivers’ UVA and UVB exposure on different sites of their
body during their working hours and further studies on annual UV exposure are needed.
The photo damage assessment tool was used for the first time to measure skin damage
for the workers in Australia. The score of SPI on their face was 35 and score of SPII was
25.8. Correlation analysis showed no relationship between one-day UV exposure (UVA
and UVB) and skin damage (SPI, SPII and photoaging). A reason for this is that one
day’s UV exposure was extremely low and is difficult to draw direct relationship from
such limited exposure data to skin damage. Another reason might be that one day’s UV
exposure did not represent annual UV exposure, with the participants also potentially
receiving more UV exposure during the weekend or their recreation time. Therefore,
88
further studied are needed to monitor and establish data on the annual UV exposure of
workers.
This study showed that skin damage had significant correlations with age and years in
Australia. Multivariable regression analysis also provided evidence that years in
Australia were a significant determinant of skin damage. A reason for this is Australia’s
geographical position and the high intensity of solar UVR. Almost all cites in Australia
get more than 4000 MED annually. Australia has the highest skin cancer rates in the
world due to people’s lifestyle combined with high environmental UVR. As we are
unable to decrease the UVR from sunlight, it is possible to avoid extensive sun exposure
and to use effective sun protective measures. Therefore, this study emphasises the deed
to reinforce the importance of basic sun protection for workers and the general public.
It is very different to measure the UV exposure a human receives due to the complex
surfaces on the body. In addition, the measurement of UV exposure could vary with
individual personal sun exposure hobbies and personal sun protection measures.
Therefore, to estimate the relationship between sun exposure and skin damage for human
being become even more complicated than to assess the dose-response for animals in
laboratories. In this study, a history of sunburn was correlated with skin damage. The
number of major sunburns before 18 years and the density of freckling as an adolescent
had a significant correlation with two skin damage indicators: SPI and SPII. The skin
damage that happens during childhood and before 18 therefore may influence the
development of skin cancer in adults. As a result, it is important to raise the general
public’s awareness of commencing sun protective measures as early as possible.
This study also found that skin colour, hair colour and eye colour were important impact
factors for skin damage. The participants with fair skin, fair/blond/red hair and
blue/green/ blue-grey eyes had higher SPI and SPII than people with medium/olive skin,
black/brown hair and brown/hazel eyes. This result is similar to that shown in the
literature review that skin damage and skin cancer is common in light-skinned people.
As such, people with fair skin need to avoid excessive UVR exposure and ensure that
they implement sun protective measures. It is also suggested that people with high SPI
and SPII should have their skin chucked regularly by their GP or Dermatologist.
89
90
4Appendices
Appendix 1. The letter to indoor workers from QUT
Indoor Sun Exposure Project
Research is being conducted by AusSun Research Lab to investigate the links
between sun exposure and skin damage for people over 18 years who work and study
in office buildings.
In this project, participants will be asked to complete a questionnaire that will assess
sun exposure and general health information. Measurements of skin colour along
with skin damage (to the facial region) will also be conducted; these images will be
given to participant to keep. Finally, participants will be asked to wear UV-sensitive
badges for one day in order to assess their sun exposure.
The QUT Human Research Ethics Committee has approved this project.
Approval number: 0800000436.
All information collected from participants will be treated confidentially and
personal information and photographs will not be published.
For more information please contact:
George Jia
AusSun Research Lab
Queensland University of Technology
(07) 313 88664
91
Appendix 2. INFORMATION FOR professional drivers
92
Appendix 3. PARTICIPANT INFORMATION SHEET
PARTICIPANT INFORMATION SHEET
Workers’ UV exposure in vehicles and the subsequent
impact on skin”
Principal Supervisor: Professor Michael Kimlin on 3138 5802 or
Associate Supervisor: Dr Thomas Tenkate on 31385790 or
Masters student: Keqin George Jia on 3138 8664, or
Description
Queensland has the highest rates of skin cancer in Australia. With the publicity and
educational campaigns on decreasing sun exposure, the general public is aware of the
dangers of ultraviolet (UV) radiation in outside conditions such as at beaches,
playgrounds and gardens. However, they may disregard the ultraviolet radiation
exposure indoors. UV radiation exposure behind glass has been studied over 15 years,
since 1992. The main research finding from those work suggested that there are still
considerable amounts of sun exposure behind glass. Therefore, further studies need
to explore the relationship between sun exposure and skin damage.
In this project, participants will be invited to the AusSun Research Laboratory where
we will introduce the project and give a participant information sheet. If participants
agree to participate, they should sign their name on the consent form. After that, we
will take a few photographs of the participant’s face by using the VISIA complexion
analysis system. This system includes VISIA booth, VISIA software that provide
valuable data of skin damage related sun exposure.
93
We will measure the pigmentation of participant’s inner upper arm and the skin on
their left and right side of their face; back of the left and right hands with a skin
colour reader (spectrophotometer). The skin from the inside of the upper arm is a
typically unexposed site where there has been little to no UV exposure. This can be
compared to skin in other highly exposed areas (typically chronic exposure sites)
such as the back of the hands and face.
A questionnaire will be used to collect data from participants about their health, sun
exposure history, and sun protection measure.
We will measure each participant’s UV exposure under his or her working conditions
for two days. Participants will be asked to wear UV badges on hat (provided by
AusSun Research Lab) and on clothing (on the bottom of outside of upper arm)
during their working time between sunrise and sunset.
This research will survey how well UV image data correlates with participant UV
exposure. Finally, the association between sun exposure and skin damage will be
explored. This project is undertaken as part of the research at AusSun Research Lab,
Queensland University of Technology (QUT) in Brisbane.
What to expect as a study participant:
Once you have agreed to participate in this study, you will be asked to visit AusSun
Research Lab, Room 1.48, 44 Musk Ave, at Kelvin Grove campus, QUT, where we
will:
Introduce the project and give you a participant information sheet
If you agree to participate, you should sign you name on the consent form
Ask you to complete a questionnaire.
Take normal colour photos and UV photos of the right, left side and centre of
your face.
Take readings of skin colour and reflectance using a spectrophotometer. We
will measure five sites on your skin; inner-upper arm, your hands and face
(left and right side).
94
Give you UV badges in an envelope for measure UV exposure, after exposure,
please post the envelope (pre-payed) to us.
The whole process should take about 30 minutes of your time.
Expected benefits
1. Your participation in this project may not benefit you directly. However
during the process of recruiting participants, the awareness may increase in
the
general public with regard to knowledge of solar UV radiation and health
effects
on skin through posters, or letters from AusSun Research Laboratory.
2. This project will research UV exposure for people working inside motor
vehicle comparing in office building and try to find the relationship between
sun exposure and skin damage. In this research, the density of pigment and
the spots of UV will be as indictors for skin damage.
Risks
There are no health and safety risks associated with participation in this project.
1. Photos will be taken by using VISIA complexion analysis system. This
system uses filtered light and has less energy than normal camera light.
2. A skin spectrophotometer is used to measure melanin density and will not
have any damaging effects on the participants’ skin.
3. There will not be any sensitive questions, confidential questions or questions
that will make participants feel upset in the questionnaire.
4. The ethics approval number of this research is 0800000436.
If you feel you require Medical advice after participating in this project, QUT
offers the following services:
Medical Services
a) Gardens Point campus: (8:30 am – 5 pm). Level 1, Y Block (opposite the
gym). Phone: 07 38642321
95
b) Kelvin Grove campus: 8:30 am – 4:pm. Level 4, C Block. Phone: 07
38643136
Confidentiality
All comments and responses are and will be treated confidentially. The names of
individual persons are not required in any of the responses. All questionnaires
and data will be stored in a secure cabinet, in a restricted access room. Participant
images will be de-identified and stored in a secure password protected network.
Voluntary participation
Your participation in this project is voluntary. If you do not agree to participate,
you can withdraw from participation at any time during the study without
comment or penalty. The decision to participate will in no way impact upon your
current or future relationship with QUT.
Questions/further information
If you have any other questions please contact:
Principal Supervisor Associate Supervisor
Prof. Michael Kimlin Dr Thomas Tenkate
Institute of Health & Biomedical Innovation Institute of Health & Biomedical
Innovation QUT KG, E201 QUT, O BLOCK- D725
KG
Phone (07) 3864 5802 Phone (07) 3138 8664
Email address: [email protected] Email address:
Masters student: Keqin (George) Jia on 07 31388664 or email: [email protected]
Concerns/complaints
Please contact the Research Ethics Officer on 3138 2340 or Ethicscontact @qut.edu.au
if you have any concerns or complaints about the ethical conduct of the project.
Thank you for participating in this research. Your contribution is greatly appreciated.
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Appendix 4. CONSENT FORM
CONSENT FORM
Workers UV Exposure and The Subsequent
Impact On Skin
Principal Supervisor: Associate
Supervisor:
Prof. Michael G. Kimlin Dr Thomas
Tenkate
Queensland University of Technology Queensland University
of Technology
Phone 07 31385802 Phone 07
31385790
Email: [email protected] Email:
Masters student: Keqin Jia, 07 31388664 Email:
Statement of consent
By signing below, you are indicating that:
1. I have read and understood the information brochure describing this study and I
voluntarily consent to take part in this study. All my questions have been answered to
my satisfaction and if I have any further questions. I know I can contact the research
team.
2. I understand that any personal information collected as part of this study will be treated
confidentially.
97
3. I understand that I do not have to take part in this study, or can withdraw at any time,
and my decision will not affect my future relationship with QUT in any way.
4. I understand that if I wish to withdraw from this study, I will notify the research team
and complete a “withdrawal of consent” form.
5. I understand that I will not personally be identified in any reports or publications arising
from this study – including my photographs.
6. I understand that I have agreed to have normal photos and UV photos taken of the right
side & left side and centre of the face in the AusSun lab.
7. I understand that I have agreed to take a skin colour measurement in the AusSunlab.
8. I understand that I have agreed to wear UV badges on hat and attached on my clothing
in one working day for this study.
9. I understand that this research will comply with the National Health and Medical
Research Council’s (NHMRC) National Statement on Ethical Conduct in Research
Involving Humans.
10. I understand that if I have any concerns about the ethical conduct of this study, I can
contact the QUT Research Ethics Officer on (07) 3138 2340.
Name ______________________________
Signature _____________________________
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Appendix 5. Questionnaire for indoor workers
Queensland University of Technology
Brisbane Australia
School of Public Health
Workers’ UV Exposure In Motor Vehicles and
The Subsequent Impact On Skin
Your Name:________________ (Once your dosimeter results and the questionnaires have
been matched, your name will be removed from the records)
Date: _________/_________/2009
QUESTIONNAIRE
Thank you for agreeing to take part in this study.
If you have any problems or queries please do not hesitate to contact:
George Jia on 3138 8664, or [email protected]
Professor Michael Kimlin on 3138 5802 [email protected]
Dr Thomas Tenkate on 31385790 or [email protected]
All of the information that you provide will remain strictly
confidential
99
SECTION 1: PERSONAL DETAILS
1. Your gender is (Please tick the appropriate box)
Male
Female
2. What is your date of birth? _____/_____/______ (dd/mm/yyyy)
3. You were born in (name of the country)__________________________
4. If you were not born in Australia, in which year did you come to live in Australia?
5. What is your natural skin colour? (This is generally considered to be the colour of
the
skin at the inside area of your upper arm) (Please tick the appropriate box below)
Fair skin
Medium skin
Olive
Dark/Black
Other
6. What is your natural hair colour? (Please tick the appropriate box below)
Black
Brown
Fair/blond
Red
Other
7. What is your natural eye colour? (Please tick the appropriate box below)
Brown
Hazel
Blue
Green
Blue-grey
Other
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SECTION 2: SUN EXPOSURE AND YOUR SKIN
8. Thinking about the PAST MONTH, we would like to know the TIMES OF DAY as
well as
the USUAL LENGTH OF TIME that you spend OUTSIDE (all outdoor activities
including:
exercise, gardening, driving, walking, recreation) between sunrise and sunset on:
8a. A typical MONDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
101
8b. A typical TUESDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
8c. A typical WEDNESDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
102
8d. A typical THURSDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
8e. A typical FRIDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
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8f. A typical SATURDAY (Tick one response for EACH time period)
Length of time spent outside
Never <15 minutes
15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
8g. A typical SUNDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes 15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
9. Is the PATTERN of sun exposure described above FOR THE PAST MONTH similar to
your pattern of exposure over the previous months?
Yes
No
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10a. Do you drive a motor vehicle?
Yes (Please tick the appropriate box below)
Bus
Truck
Taxi
Max taxi
Car (small car, wagon)
Motor bike, scooter
Other (Please describe)___________________
No (Please go to Question 12)
10b. If Yes, on average, how much time did you usually spend each day inside/on
the
vehicle during weekdays (Monday to Friday) between sunrise & sunset on:
(Please tick appropriate boxes below)
Occupational driving Travelling to and from work Recreational driving Motor vehicle Public transport
0 hour 0 hour 0 hour 0 hour 15 minutes 15 minutes 15 minutes 15 minutes 30 minutes 30 minutes 30 minutes 30 minutes 45 minutes 45 minutes 45 minutes 45 minutes 1 hour 1 hour 1 hour 1 hour 1 – 2 hours 1 – 2 hours 1 – 2 hours 1 – 2 hours 2 – 3 hours 2 – 3 hours 2 – 3 hours 2 – 3 hours 3 – 4 hours 3 – 4 hours 3 – 4 hours 3 – 4 hours 4 – 5 hours 4 – 5 hours 4 – 5 hours 4 – 5 hours 5 – 6 hours 5 – 6 hours 5 – 6 hours 5 – 6 hours 6 – 7 hours 6 – 7 hours 6 – 7 hours 6 – 7 hours 7 – 8 hours 7 – 8 hours 7 – 8 hours 7 – 8 hours 8 or more hours 8 or more hours 8 or more hours 8 or more hours
105
10c. On average, how much time did you usually spent each day inside/on the
vehicle during weekend (Saturday and Sunday) between sunrise & sunset?
(Please tick one appropriate box below)
Occupational driving Travelling to and from work Recreational driving Motor vehicle Public transport
0 hour 0 hour 0 hour 0 hour 15 minutes 15 minutes 15 minutes 15 minutes 30 minutes 30 minutes 30 minutes 30 minutes 45 minutes 45 minutes 45 minutes 45 minutes 1 hour 1 hour 1 hour 1 hour 1 – 2 hours 1 – 2 hours 1 – 2 hours 1 – 2 hours 2 – 3 hours 2 – 3 hours 2 – 3 hours 2 – 3 hours 3 – 4 hours 3 – 4 hours 3 – 4 hours 3 – 4 hours 4 – 5 hours 4 – 5 hours 4 – 5 hours 4 – 5 hours 5 – 6 hours 5 – 6 hours 5 – 6 hours 5 – 6 hours 6 – 7 hours 6 – 7 hours 6 – 7 hours 6 – 7 hours 7 – 8 hours 7 – 8 hours 7 – 8 hours 7 – 8 hours 8 or more hours 8 or more hours 8 or more hours 8 or more hours
11. At what age, did you start driving?
12. How many major sunburns (painful and/or blistering) have you had
a. Prior to 18 years of age? (Please tick the appropriate box below)
None
1
2-5
6-10
Over 10
Don’t know
b. After 18 years of age? (Please tick the appropriate box below)
None
1
2-5
6-10
Over 10
Don’t know
106
13. Have you ever suffered from a skin disease related to solar UV exposure?
No
Yes (if yes, what kind of skin disease, please select one of the
following)
a) Melanoma
b) Basal cell carcinoma
c) Squamous cell carcinoma
d) others
14. We are interested in whether your skin burns.
Suppose your skin is exposed to strong sunlight for the first time in summer,
with no
protection such as sunscreen or shade. If you stayed in the sun for 30 minutes
would your skin (Please tick the appropriate box below)
Never burn
Rarely burn
Sometimes burn
Mostly burn
Always burn
15. We are also interested in whether your skin tans.
Imagine you spend several weeks at the beach and have a lot of sun exposure,
without any protection such as sunscreen or clothing. What would your skin be
like? (Please tick the appropriate box below)
Very brown & deeply tanned
Moderately tanned
Slightly tanned
Not tanned at all
16. Have you ever used a solarium? (Please tick the appropriate box below)
No (Please go to Question 17)
Yes
107
16a. If yes, how often do you use a solarium (occasional user).
Once a year
Twice a year
3 times or more
16b. If you use a solarium regularly, what frequency do you use a solarium?
Once/a week
Once/a fortnight
Once/a month
Other __________________ (Please explain)
SECTION 3: SUN AND YOUR WORKING PLACE
17. On average, how many hours per day do you spend indoors in your office
between
sunrise and sunset? (Please tick the appropriate box below)
0.5 - 1 hour
1 - 2 hours
2 - 4 hours
4 - 6 hours
6 - 8 hours
Over 8 hours
18a. On average, how many days each week do you work at your office indoors
between sunrise and sunset from Monday to Friday? (Please tick one
appropriate box below).
0 day
1 day
2 days
3 days
4 days
5 days
108
18b. How many days each week do you work at your office indoors between sunrise
and
sunset during the weekend (Saturday and Sunday)? (Please tick one
appropriate box below)
0 day
1 day
2 days
19. How far approximately (metres) is your seat to the closest window in the office?
(Please tick the appropriate box below)
0.1-1.0m
1.0-2.0m
2.0-3.0m
3.0-4.0m
4+m
Not sure
20. Are the windows of your office tinted? (Please tick the appropriate box below)
Yes
No
Unsure
SECTION 4: SUN PROTECTION
21a. Do you wear any hat/cap when you go outside?
Always (all the time 100% when you go outside)
Usually (about 75%)
Sometimes (half the time 50%)
Rarely (about 25%)
Never (No time 0%, never wear hat outside)
109
21b. If Yes, which one is the closest to the style that you wear? (Please tick the
appropriate box below)
Baseball cap
Short brim hat
Wide brim hat
22. What kind of clothing do you wear when you go outside in the sunshine?
(Please
tick the appropriate box below)
Short-sleeved (shirt)
Long-sleeved (shirt)
Singlet
23a. Do you use sunscreen when you go outside?
Always (all the time 100% when you go outside)
Usually (about 75%)
Sometimes (half the time 50%)
Rarely (about 25%)
Never (No time 0%, never use sunscreen outside)
23b. If you answer is Yes, what is the sun-protection factor (SPF) of the sunscreen
that
you typically use? (Please tick the appropriate box below)
15+ SPF
15–30 SPF
30+SPF
24. Do you wear sunglasses when you go outside between sunrise and sunset?
(Please
tick the appropriate box below)
Always (all the time 100% when you go outside)
Usually (about 75%)
Sometimes (half the time 50%)
Rarely (about 25%)
Never (No time 0%, never wear sunglass outside
110
THANK YOU VERY MUCH FOR TAKING THE TIME TO PARTICIPATE
IN THIS STUDY
111
Appendix 6. Questionnaire for professional drivers
Queensland University of Technology
Brisbane Australia
School of Public Health
Workers’ UV Exposure In Motor Vehicles and
The Subsequent Impact On Skin
Your Name:_______________ (Once your dosimeter results and the questionnaires have
been matched, your name will be removed from the records)
Date: _________/_________/2009
QUESTIONNAIRE Thank you for agreeing to take part in this study. It is very important that you answer
all the questions.
If you have any problems or queries please do not hesitate to contact:
George Jia on 3138 8664, or [email protected]
Professor Michael Kimlin on 3138 5802 [email protected]
Dr Thomas Tenkate on 31385790 or [email protected]
All of the information that you provide will remain strictly
confidential
112
SECTION 1: PERSONAL DETAILS
1. Your gender is (Please tick the appropriate box below)
Male
Female
2. What is your date of birth? _____/_____/______ (dd/mm/yyyy)
3. Your occupation is: (Please tick the appropriate box below)
Bus driver
Truck driver
Taxi driver
Maxi taxi driver
Car (small car, wagon) driver (other than taxi driver)
Other___________
4. How long have you been a driver? _____ Years
(if less than one year, please write how many month: __________).
5. You were born in (name of the country)__________________________
6. If you were not born in Australia, in which year did you come to live in Australia?
7. What is your natural skin colour? (This is generally considered to be the colour of
the
skin at the inside area of your upper arm) (Please tick the appropriate box
below)
Fair skin
Medium skin
Olive
Dark/Black
Other
113
8. What is your natural hair colour? (Please tick the appropriate box below)
Black
Brown
Fair/blond
Red
Other
9. What is your natural eye colour? (Please tick the appropriate box below)
Brown
Hazel
Blue
Green
Blue-grey
Other
SECTION 2: SUN EXPOSURE AND SKIN DAMAGE
10. Have you worked a night shift at least once in the past month? (Please tick the
appropriate box below)
Yes
No (please go to Question 11)
If Yes, please tell us approximately how many night shifts you have worked in the
past month? (Please tick the appropriate box below)
1 night shift 8-10 night shifts
2 night shifts 11-13 night shifts
3 night shifts 14-16 night shifts
4 night shifts 17-19 night shifts
5-7 night shifts 20 or more night shifts in the past month
11.Thinking about the PAST MONTH, we would like to know the TIMES OF DAY as
well as the USUAL LENGTH OF TIME that you spend OUTSIDE (all outdoor activities
114
including: exercise, gardening, driving, walking, recreation) between sunrise and
sunset on:
11a. A typical MONDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
1b. A typical TUESDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes 15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
115
11c. A typical WEDNESDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
11d. A typical THURSDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes 15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
116
11e. A typical FRIDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes 15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
11f. A typical SATURDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes 15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
117
11g. A typical SUNDAY (Tick one response for EACH time period)
Length of time spent outside Never <15
minutes 15-30 minutes
30-45 minutes
45-60 minutes
Morning (am) 5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
12. Is the PATTERN of sun exposure described above FOR THE PAST MONTH similar to
your pattern of exposure over the previous months?
Yes
No
13. How many major sunburns (painful and/or blistering) have you had:
a. Prior to 18 years of age? (Please tick the appropriate box below)
None
1
2-5
6-10
Over 10
Don’t know
b. After 18 years of age? (Please tick the appropriate box below)
None
1
2-5
118
6-10
Over 10
Don’t know
14. Have you ever suffered from a skin disease related to solar UV exposure?
No
Yes (if yes, what kind of skin disease, please select one of the following)
a) Melanoma
b) Basal cell carcinoma
c) Squamous cell carcinoma
d) others
15. We are interested in whether your skin burns.
Suppose your skin is exposed to strong sunlight for the first time in summer,
with no
protection, such as sunscreen or shade. If you stayed in the sun for 30 minutes;
would your skin: (Please tick the appropriate box below)
Never burn
Rarely burn
Sometimes burn
Mostly burn
Always burn
16. We are also interested in whether your skin tans.
Imagine you spend several weeks at the beach in strong sunlight and have a lot
of
sun exposure, without any protection such as sunscreen or clothing. What would
your skin be like? (Please tick the appropriate box below)
Very brown & deeply tanned
Moderately tanned
Slightly tanned
Not tanned at all
17. Have you ever used a solarium? (Please tick the appropriate box below)
No (please go to Question 18)
Yes
119
17a. If yes, how often do you use a solarium (occasional user).
Once a year
Twice a year
3 times or more
17b. If you use a solarium regularly, what frequency do you use a solarium?
Once/a week
Once/a fortnight
Once/a month
Other __________________ (Please explain)
SECTION 3: SUN EXPOSURE AND YOUR VEHICLE
18. On average, how much time each day do you usually spend inside a vehicle
during
weekdays (Monday to Friday) between sunrise and sunset: (Please tick
appropriate boxes below
Occupational driving
Travelling to and from work Recreational driving Motor vehicle Public transport
0 hour 0 hour 0 hour 0 hour 15 minutes 15 minutes 15 minutes 15 minutes 30 minutes 30 minutes 30 minutes 30 minutes 45 minutes 45 minutes 45 minutes 45 minutes 1 hour 1 hour 1 hour 1 hour 1 – 2 hours 1 – 2 hours 1 – 2 hours 1 – 2 hours 2 – 3 hours 2 – 3 hours 2 – 3 hours 2 – 3 hours 3 – 4 hours 3 – 4 hours 3 – 4 hours 3 – 4 hours 4 – 5 hours 4 – 5 hours 4 – 5 hours 4 – 5 hours 5 – 6 hours 5 – 6 hours 5 – 6 hours 5 – 6 hours 6 – 7 hours 6 – 7 hours 6 – 7 hours 6 – 7 hours 7 – 8 hours 7 – 8 hours 7 – 8 hours 7 – 8 hours 8 or more hours 8 or more hours 8 or more hours 8 or more hours
120
19. If you work on weekends (Saturday and Sunday), on average, how much
time do you usually spend inside a vehicle between sunrise and sunset:
(Please tick appropriate boxes below).
Occupational driving Travelling to and from work Recreational driving Motor vehicle Public transport
0 hour 0 hour 0 hour 0 hour 15 minutes 15 minutes 15 minutes 15 minutes 30 minutes 30 minutes 30 minutes 30 minutes 45 minutes 45 minutes 45 minutes 45 minutes 1 hour 1 hour 1 hour 1 hour 1 – 2 hours 1 – 2 hours 1 – 2 hours 1 – 2 hours 2 – 3 hours 2 – 3 hours 2 – 3 hours 2 – 3 hours 3 – 4 hours 3 – 4 hours 3 – 4 hours 3 – 4 hours 4 – 5 hours 4 – 5 hours 4 – 5 hours 4 – 5 hours 5 – 6 hours 5 – 6 hours 5 – 6 hours 5 – 6 hours 6 – 7 hours 6 – 7 hours 6 – 7 hours 6 – 7 hours 7 – 8 hours 7 – 8 hours 7 – 8 hours 7 – 8 hours 8 or more hours 8 or more hours 8 or more hours 8 or more hours
20a. On average, how many days each week do you work as a driver from
Monday to
Friday? (Please tick one appropriate box below).
0 day
1 day
2 days
3 days
4 days
5 days
20b. How many days each week do you work as a driver during the weekend
(Saturday and Sunday)? (Please tick one appropriate box below)
0 day
1 day
2 days
21. What is your preference for the window position on driver side of the vehicle
when
you are driving?
121
a. During summer time (Please tick the appropriate box below)
Window up
Window half down
Window down
b. During winter time (Please tick the appropriate box below)
Window up
Window half down
Window down
22. Which type of vehicle do you drive for work? (Please tick the appropriate box
below)
Bus
Truck
Taxi
Max taxi
Car (small car, wagon)
Motor bike, scooter
Other (Please describe)___________________
23. Are the windows of your vehicle tinted? (Please tick the appropriate box below)
Yes
No
Unsure
24. Does your vehicle have air conditioning?
Yes
No
SECTION 4: SUN PROTECTION
25a. Do you wear any hat/cap when you are driving between sunrise and sunset?
Always (all the time 100% when you drive)
Usually (about 75%)
Sometimes (half the time 50%)
Rarely (about 25%)
122
Never (No time 0%, never wear hat/cap. Please go to Question 26)
25b. If Yes, which one is the closest to the style that you wear? (Please tick the
appropriate box below)
Baseball cap
Short brim hat
Wide brim hat
26a. What kind of clothing do you generally wear inside your vehicle when you
drive between sunrise and sunset? (Please tick the appropriate box below)
Short sleeved (shirt)
Long-sleeved (shirt)
Singlet
26b. If you wear a long-sleeved shirt, do you roll the sleeves up often?
Yes
No
27a. Do you use sunscreen when you drive?
Always (all the time 100% when you drive)
Usually (about 75%)
Sometimes (half the time 50%)
Rarely (about 25%)
Never (No time 0%, never use sunscreen)
27b. If you answer is Yes, what is the sun-protection factor (SPF) of the sunscreen
that
you typically use? (Please tick the appropriate box below)
15+ SPF
15 – 30 SPF
30+SPF
28. Do you wear sunglasses when you drive inside a vehicle between sunrise and
sunset? (Please tick the appropriate box below)
Always (all the time 100% when you drive)
Usually (about 75%)
Sometimes (half the time 50%)
Rarely (about 25%)
123
Never (No time 0%, never wear sunglass)
THANK YOU VERY MUCH FOR TAKING THE TIME
TO PARTICIPATE IN THIS STUDY
124
Appendix 7. Personal characteristics
PERSONAL CHARACTERISTICS
Freckling as an adolescent: (please refer to Freckling Chart provided)
Face: Forearms: Shoulders:
Natural Hair colour at age of 18 years:
Black Brown Fair/Blond Red other
Eye colour:
Brown Hazel Blue Green other
Subjective Skin Colour
Fair Medium Olive Dark/Black other
Skin Colour – Skin Reflectance
Inner Upper Arm
No. ______ L A
B
Right Hand
No. ______ L A
B
Left Hand
No. ______ L A
B
Right Face
No. ______ L A
B
Left Face
No. ______ L A
B
Are you interested in being contacted in the future to participate in this or other UV-
related research project?
Yes
No
125
If Yes, your contact details are: Phone: ___________________
Email address: __________________
Mailing address:__________________________
126
Appendix 8. How to measure sun exposure time
In order to get accurate sun exposure time, participants were required to record the time
they spent outside everyday total in one week. The time started from 5 am to 7 pm each
day and each hour was divided into four quarters. Participants were asked to record the
times that they went outside (Table 29). Therefore, the total sun exposure time could be
calculated by adding all the times together. This question was based on questions from
AusSun Research Lab’s AusD study to assess participant’s sun exposure.
Table 29. Example for one day sun exposure in questionnaire
Length of time spent outside Never <15
minutes15-30 minutes
30-45 minutes
45-60 minutes
Morning (am)
5-6 6-7 7-8 8-9 9-10 10-11 11-12 Afternoon (pm)
12-1 1-2 2-3 3-4 4-5 5-6 6-7
127
Appendix 9. UV exposure dosimetry and calibation
1. The UVA-sensitive dosimeter
As described in Chapter 3, the Phenothiazine/Mylar dosimeter is a detector for
monitoring personal solar UVA exposure. In addition, it is valid and reliable for
monitoring solar UVA exposure and allows quantification of the UVA exposures (Diffey,
1997). In this project, participants wore UVA dosimeters on their hats and upper arms to
measure the UVA doses they received during working hours. AusSun Research Lab
provided UVA dosimeters for this study.
2. The erythemal UV-sensitive dosimeter:
Polysulphone dosimeters were also used in this study to measure the eryhemal UV
radiation exposure for participants in a vehicle and in an office building. The
polysulphone dosimeter, as described in Chapter 3, has been used in UV research (Parisi,
2006) for more than three decades (Diffey, 1977). The dosimeter has an action spectrum
closely approximating the erythemal response of human skin (Davis, 1976). These
dosimeters are widely useful in field studies due to their being inexpensive, stable and
easy to apply (Diffey, 1987). The polysulphone film was cut into suitable size and
mounted into 3 x 3 cm rigid plastic holders, each with a 1.5 cm central aperture to
produce a dosimeter. The dosimeters for this study were made from AusSun Research
Lab.
3. Equipment: spectrophotometer UV-1700
Each dosimeter’s absorbance of pre-exposure and post-exposure was measured by
the spectrophotometer UV 1700 (Figure 36). For the UVA dosimeter, its absorbance
was measured at 370nm (Parisi, 2005) wavelength while the erythemal UV
dosimeter was at 330nm (Davis, 1976). According to the changes of absorbance, the
dose each dosimeter received can be calculated against a calibration curve, which
was provided by AusSun Research Lab.
128
Figure 35. UV-1700 spectrophotometer
4. PS and Phenothiazine/Mylar dosimeter calibration
In order to get the stable response of the PS dosimeters and Phenothiazine/Mylar
dosimeters on action spectrum in different seasons, AusSun Research Lab conducts
seasonal calibration for both of dosimeters. A calibration technique for the
measurement of UVB / UVA is to expose a series of dosimeters to different periods
of solar UV exposure on a horizontal plane. According to the change of absorbance
of each dosimeter and the UVB/UBA dose at each set intervals, the calibration curve
can be achieved. Data of UVB /UVA come from AusSun Research Lab UV detect
station which is located at Kelvin Grove Campus (latitude: 270 30 0 S; longitude:
1530 1 0 E), QUT, Brisbane. Data of erythemal UV and UVA are recorded at five
minute intervals over 24 hours by a Solar Light Co. 501A Biometer. The calibration
of the polysulphone film dosimeter and phenothiazine film dosimeter was being
made according to the data from the Solar Light Co. 501 Biometer. Figure 37 shows
two examples for PS and Phenothiazime/Mylar dosimeters’ summer calibration in
2009.
129
Figure 36. PS dosimeters (above) and Phenothiazine/Mylar dosimeters (below)
calibration
A general formula has been employed to calculate UV exposure from the calibration
results (Diffy, 1987):
UV = K[A + (A)2 + 9(A)3 ]
Where K is a calibration constant to be determined in the calibration of the
dosimeters.
According to this formulation, the dose of UV exposure can be made out.
130
Appendix 10. Checklist form
Workers’ UV Exposure and The Subsequent Impact
On Skin
Checklist
Consent form completed
yes No
Date of birth written on the first page of Questionnaire
yes No
Skin colour/phenotype measured
yes No
UV photographs taken
yes No
Questionnaires completed
yes No
Initialled:________________________
Date:____________________________
131
Appendix 11. Codebook
Workers’ UV Exposure And The Subsequent
Impact On Skin
Codebook
132
Variable SPSS variable name Coding instructions Identification number ID Number assigned to each
questionnaire Group Group 1 = QUT staff and students
2 = Drivers -1 = missing
Gender Gender 1 = Male 2 = Female -1 = missing
Age Age Age in years Where born Whereborn 1 = Australia
other for waiting to divide into different groups -1 = missing
Years in Australia YinAus years in Australia -1 = missing
Skin colour Skincolour 1 = Fair skin 2 = Medium skin 3 = Olive 4 = Dark/Black -1 = missing
Hair colour Haircolour 1 = Black 2 = Brown 3 = Fair/blond 4 = Red -1 = missing
Eye colour Eyecolour 1 = Brown 2 = Hazel 3 = Blue 4 = Green 5 = Blue-grey -1 = missing
Monday sun exposure in total
Monday In minutes -1 = missing
Tuesday sun exposure in total
Tuesday In minutes -1 = missing
Wednesday sun exposure in total
Wednesday In minutes -1 = missing
Thursday sun exposure in total
Thursday In minutes -1 = missing
Friday sun exposure in total Friday In minutes -1 = missing
Time outside weekdays Timeoutweekdays In miuntes -1 = missing
Saturday sun exposure in total
Saturday In minutes -1 = missing
Sunday sun exposure in total Saturday In minutes
133
-1 = missing Time outside weekend Tmeoutend In minutes
-1 = missing Similar to last month Pattern 1 = Yes
2 = No -1 = missing
Type of vehicle you drive YDMvehic 1 = Bus 2 = Truck 3 = Taxi 4 = Max taxi 5 = Car (small car, wagon) 6 = Motor bike, scooter 7 = Other 8 = No 9 = 5+6 -1 = missing
Occupational driving from Mon to Fri
Ocupdri 1 = 0 hour 2 = 15 minutes 3 = 30 minutes 4 = 45 minutes 5 = 1 hour 6 = 1-2hours 7 = 2-3hours 8 = 3-4hours 9 = 4-5hours 10 = 5-6hours 11 = 6-7hours 12 = 7-8hours 13 = 8 or mores -1 = missing
Travelling by motor vehicle to and from work from Mon to Fri
Tramotor 1 = 0 hour 2 = 15 minutes 3 = 30 minutes 4 = 45 minutes 5 = 1 hour 6 = 1-2hours 7 = 2-3hours 8 = 3-4hours 9 = 4-5hours 10 = 5-6hours 11 = 6-7hours 12 = 7-8hours 13 = 8 or mores -1 = missing
Travelling by public transport from Mon to Fri
Tradpublc 1 = 0 hour 2 = 15 minutes 3 = 30 minuties 4 = 45 minutes 5 = 1 hour 6 = 1-2hours 7 = 2-3hours 8 = 3-4hours 9 = 4-5hours 10 = 5-6hours 11 = 6-7hours
134
12 = 7-8hours 13 = 8 or mores -1 = missing
Recreational driving from Mon to Fri
Recratfon 1 = 0 hour 2 = 15 minutes 3 = 30 minutes 4 = 45 minutes 5 = 1 hour 6 = 1-2hours 7 = 2-3hours 8 = 3-4hours 9 = 4-5hours 10 = 5-6hours 11 = 6-7hours 12 = 7-8hours 13 = 8 or mores -1 = missing
Occupational driving on weekend
EOcupdri 1 = 0 hour 2 = 15 minutes 3 = 30 minutes 4 = 45 minutes 5 = 1 hour 6 = 1-2hours 7 = 2-3hours 8 = 3-4hours 9 = 4-5hours 10 = 5-6hours 11 = 6-7hours 12 = 7-8hours 13 = 8 or mores -1 = missing
Travelling by motor vehicle to and form work on weekend
ETramotor 1 = 0 hour 2 = 15 minutes 3 = 30 minutes 4 = 45 minutes 5 = 1 hour 6 = 1-2hours 7 = 2-3hours 8 = 3-4hours 9 = 4-5hours 10 = 5-6hours 11 = 6-7hours 12 = 7-8hours 13 = 8 or mores -1 = missing
Travelling by public transport on weekend
ETradpublc 1 = 0 hour 2 = 15 minutes 3 = 30 minutes 4 = 45 minutes 5 = 1 hour 6 = 1-2hours 7 = 2-3hours 8 = 3-4hours 9 = 4-5hours 10 = 5-6hours
135
11 = 6-7hours 12 = 7-8hours 13 = 8 or mores -1 = missing
Recreational driving on weekend
ERecratfon 1 = 0 hour 2 = 15 minutes 3 = 30 minutes 4 = 45 minutes 5 = 1 hour 6 = 1-2hours 7 = 2-3hours 8 = 3-4hours 9 = 4-5hours 10 = 5-6hours 11 = 6-7hours 12 = 7-8hours 13 = 8 or mores -1 = missing
How long you drive HowlongD How long driving in years -1 = missing
Major sunburns before 18 MajsunbB 1 = None 2 = 1 3 = 2-5 4 = 6-10 5 = Over 10 6 = Don’t know -1 = missing
Major sunburns after 18 MajsunbA 1 = None 2 = 1 3 = 2-5 4 = 6-10 5 = Over 10 6 = Don’t know -1 = missing
Skin diseases related to UV exposure
Skindise 1 = No 2 = Melanoma 3 = Basal cell carcinoma 4 = Squamous cell carcinoma 5 = other 6 = 2+3+4 -1 = missing
Exposure to strong sunlight for 30 minutes skin burns
Skinburns 1 = Never burn 2 = Rarely burn 3 = Sometimes burn 4 = Mostly burn 5 = Always burn -1 = missing
Several weeks at the beach skin tans
Skintans 1=Very brown & deeply tanned 2=Moderately tanned 3=Slightly tanned 4=Not tanned at all -1=missing
Use a solarium Solarum 1 = No 2 = Yes
136
-1 = missing
How often use solarium Nosolair 1 = Once a year 2 = Twice a year 3 = 3 times or more a year 4 = 0 -1 = missing
Frequency using solarium Frequenc 1 = Once/a week 2 = Once/a fortnight 3 = Once/a month 4 = Other 5 = 0 -1=missing
Hours indoors per day ( driver inside vehicle)
InHHD 1 = 0.5 - 1 hour 2 = 1 - 2 hours 3 = 2 - 4 hours 4 = 4 - 6 hours 5 = 6 - 8 hours 6 = Over 8 hours -1 = missing
Days inside office for Mon to Fri
OMonFri 1 = 0 day 2 = 1 day 3 = 2 days 4 = 3 days 5 = 4 days 6 = 5 days -1 = missing
Days inside office on weekend
OSatSun 1 = 0 day 2 = 1 day 3 = 2 days -1 = missing
Meters form seat to the closest window
WindowMS 1 = 0.1-1.0m 2 = 1.0-2.0m 3 = 2.0-3.0m 4 = 3.0-4.0m 5 = 4+m 6 = Not sure -1 = missing
Windows tinted Widtited 1 = Yes 2 = No 3 = Unsure -1 = missing
Hat cap outside Hatcap 1 = Always 2 = Usually 3 = Sometimes 4 = Rarely 5 = Never -1 = missing
Hat style Hatstyle 1 = Baseball cap 2 = Short brim hat 3 = Wide brim hat 4 = no hat -1 = missing
137
Clothing Clothing 1 = Short-sleeved (shirt) 2 = Long-sleeved (shirt) 3 = Singlet -1 = missing
Sunscreen Sunscreen 1 = Always 2 = Usually 3 = Sometimes 4 = Rarely 5 = Never -1 = missing
SPF SPF 1 = 15+ SPF 2 = 15–30 SPF 3 = 30+SPF 4 = never -1=missing
Sunglass Sunglass 1 = Always 2 = Usually 3 = Sometimes 4 = Rarely 5 = Never -1 = missing
Freckling on face 18 FreckFc Continuous variable, -1 = missing Freckling on forearms 18 FreckArm Continuous variable, -1 = missing Freckling on shoulders 18 FreckShl Continuous variable, -1 = missing self report hair colour SelRHair 1 = Black
2 = Brown 3 = Fair/blond 4 = Red 5 = other -1 = missing
self-report eye colour SeREye 1 = Brown 2 = Hazel 3 = Blue 4 = Green 5 = Blue-grey 6 = other -1 = missing
Self-report skin colour SeRSkin 1 = Fair skin 2 = Medium skin 3 = Olive 4 = Dark/Black 5 = other -1 = missing
Skin Reflectance inner upper arm
SRinarm Continuous variable, -1 = missing
Skin Reflectance right hand SRrightH Continuous variable, -1 = missing Skin Reflectance left hand SRleftH Continuous variable, -1 = missing Skin Reflectance right face SRrightF Continuous variable, -1 = missing Skin Reflectance left face SRleftF Continuous variable, -1 = missing UVA left head first day ALhead1 Continuous variable, -1 = missing UVA Right head first day ARhead1 Continuous variable, -1 = missing
138
UVA Left arm first day ALarm1 Continuous variable, -1 = missing UVA Right arm first day ARarm1 Continuous variable, -1 = missing UVB Light head first day BLhead1 Continuous variable, -1 = missing UVB Right head first day BRhead1 Continuous variable, -1 = missing UVB Left arm first day BLarm1 Continuous variable, -1 = missing UVB Right arm first day BRarm1 Continuous variable, -1 = missing Surface spots on right side of face
RSpots Continuous variable, -1 = missing
Pores on right side of face RPores Continuous variable, -1 = missing Wrinkles on right side of face
RWrinkles Continuous variable, -1 = missing
Texture on right side of face RTexture Continuous variable, -1 = missing Porphyrin on right side of face
RPorphyrins Continuous variable, -1 = missing
UV spots on right side of face
RUVspots Continuous variable, -1 = missing
Red areas on right side of face
RRedareas Continuous variable, -1 = missing
Brown spots on right side of face
RBrspots Continuous variable, -1 = missing
Surface spots on Centre of forehead
Fspots Continuous variable, -1 = missing
Pores on centre of forehead FPores Continuous variable, -1 = missing Wrinkles on centre of forehead
FWrinkles Continuous variable, -1 = missing
Texture on centre of forehead
FTexture Continuous variable, -1 = missing
Porphyrins on centre of forehead
FPorphyrins Continuous variable, -1 = missing
UV spots on centre of forehead
FUVspots Continuous variable, -1 = missing
Red areas on centre of forehead
FRedareas Continuous variable, -1 = missing
Brown spots on centre of forehead
FBrspots Continuous variable, -1 = missing
Surface spots on left side of face
LSspots Continuous variable, -1 = missing
Pores on left side of face LPores Continuous variable, -1 = missing
Wrinkles on left side of face LWrinkles Continuous variable, -1 = missing Texture on left side of face LTexture Continuous variable, -1 = missing Porphyrin on left side of face LPorphyrins Continuous variable, -1 = missing UVspots on left side of face LUVspots Continuous variable, -1 = missing Red areas on left side of face LRedareas Continuous variable, -1 = missing Brown spots on left side of face
LBrspots Continuous variable, -1 = missing
Whole face spots Spots Contiunous variable, -1= missing Whole face pores Pores Continuous variable, -1 = missing Whole face wrinkles Wrinkles Continuous variable, -1 = missing Whole texture Texture Continuous variable, -1 = missing Whole face porphyrin Porphyrins Continuous variable, -1 = missing Whole face UVspots UVspots Continuous variable, -1 = missing Whole face red areas Redareas Continuous variable, -1 = missing
139
Whole face brown spots Brspots Continuous variable, -1 = missing Work and study time WandStime Continuous variable (hours), -1 =
missing Time outside Timeoutside Continuous variable (minutes), -1 =
missing Environmental UVB simultaneous
EnUVBsimultaneous Continuous variable (MED), -1 = missing
Environmental UVA simultaneous
EnUVAsimultaneous Continuous variable (J/cm2), -1 = missing
QUTUVBP Percentage of outsice UVB
Continuous variable (%), -1 = missing
QUTUVAP Percentage of outsice UVA
Continuous variable (%), -1 = missing
Timeoutviaall Percentage of time out via all work hours
Continuous variable (h), -1 = missing
Timeinhour Time outside in hour Continuous variable (h), -1 = missing AverageUVAR Average each
participant received UVA
Continuous variable (J/cm2), -1 = missing
AverageUVBR Average each participant received UVB
Continuous variable (MED), -1 = missing
SkincolourInTwo Skin colour in two groups
1 = Fair skin 2 = Medium/Olive skin -1 = missing
HaircolourInTwo Hair colour in two groups
1 = Black 2 = Brown/Fair/Blond/Red -1 = missing
EeycolourInTwo Eye colour in two groups
-1 = missing
AReflctanceleonhands Reflectance on two hands
Continuous variable, -1 = missing
ReflectonComplexion
Reflectance on whole complexion
Continuous variable, -1 = missing
UVAdoseonface UVA exposure on face (total both sides )
Continuous variable, -1 = missing
UVBdoseonface UVB exposure on face (total both sides)
Continuous variable, -1 = missing
UVAONFACE UVA (left + right)/2 Continuous variable, -1 = missing UVBONFACE UVB (left + right)/2 Continuous variable, -1 = missing
140
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