CEBP Meeting Calendar Targets
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online
Cancer Epidemiology Biomarkers & Prevention 17, 428, February 1, 2008. Published Online First February 4, 2008;
doi: 10.1158/1055-9965.EPI-07-0369
© 2008 American Association for Cancer Research
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
1055-9965.EPI-07-0369v1
17/2/428    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Dixon, H. G.
Right arrow Articles by Wakefield, M. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Dixon, H. G.
Right arrow Articles by Wakefield, M. A.
Related Collections
Right arrow Behavioral Science
Right arrow Behavioral Science: Interventions: Behavioral, Pharmacologic, Pharmacogenetic

Use of Sun-Protective Clothing at Outdoor Leisure Settings from 1992 to 2002: Serial Cross-sectional Observation Survey

Helen G. Dixon1, Magdalena Lagerlund2, Matthew J. Spittal1, David J. Hill3, Suzanne J. Dobbinson1 and Melanie A. Wakefield1

1 Centre for Behavioural Research in Cancer, The Cancer Council Victoria, Carlton, Victoria, Australia; 2 Department of Epidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada; and 3 Director, The Cancer Council Victoria, Carlton, Victoria, Australia

Requests for reprints: Melanie Wakefield, Centre for Behavioural Research in Cancer, The Cancer Council Victoria, 1 Rathdowne Street, Carlton, Victoria 3053, Australia. Phone: 61-3-9635-5046; Fax: 61-3-9635-5380. E-mail: melanie.wakefield{at}cancervic.org.au


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: Previous population-based surveys to monitor sun protection behavior over time have relied on self-report, which can be subject to recall and misclassification bias and social desirability bias. The present study aimed to describe the prevalence and determinants of teenagers' and adults' observed sun protection behavior while engaged in outdoor leisure activities on summer weekends, over a decade of the SunSmart skin cancer prevention program, which involved public education and advocacy.

Method: Serial cross-sectional observational field surveys of teenagers and adults at leisure were undertaken during summer weekends between 11 a.m. and 3 p.m., from 1992 to 2002 (N = 46,810). The four types of setting for observation were parks and gardens, golf courses, tennis courts, and pools and beaches, located within a 25-km radius of Melbourne city center, Australia. The main outcome measure was a binary clothes cover index representing persons above or below the median level of body cover for each type of leisure setting. The index was based on the proportion of body surface covered by the type of hat, shirt, and leg cover garments worn.

Results: Body cover varied by environmental factors and the activity demands and demographic characteristics of individuals. After adjusting for covariates, significant improvements in the extent of body cover occurred over the decade, such that the odds of the proportion of people wearing clothes cover above the median level increased by 3% per year (95% confidence interval, 2-4%).

Conclusion: Results suggest that significant gains in sun-protective behavior have occurred, coincident with the conduct of an ongoing comprehensive skin cancer prevention program. (Cancer Epidemiol Biomarkers Prev 2008;17(2):428–34)


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Australia has the highest skin cancer rates in the world and treatment costs to the health system are higher than for other cancers (1, 2). Despite an overall increase in nonmelanoma skin cancer rates, in younger people this has begun to plateau after decades of increase (3). Melanoma mortality in Australia peaked in about 1985 and has now plateaued (4). Stabilization in skin cancer rates may be due to extensive public health programs. However, data documenting improvements in people's skin cancer prevention practices in association with prevention efforts are needed to lend support to this hypothesis.

The present study of sun protection behavior was conducted in Victoria, Australia, where the SunSmart (initially Slip! Slop! Slap!) skin cancer prevention program has been running for more than 20 years (5). The long-term aim of the program is to reduce the incidence of, and morbidity and mortality from, skin cancer in Victoria. SunSmart seeks to promote environmental changes supportive of sun protection, such as provision of shade in outdoor settings, and to promote individual behaviors that decrease solar exposure. These include wearing a hat, covering up with clothes, and staying in the shade during peak periods of solar UV radiation intensity.

The campaign's main routes of influence have been public education and advocacy. Televised public education campaigns have been used to promote pro-sun protection knowledge, attitudes, and intentions in individuals and to promote social and cultural norms supportive of sun protection. Advocacy has been used to support environmental and policy changes that have led to improvements in the quality of available sun protection (e.g., a standard for sunglasses safety) (6), as well as change in school (7) and workplace (8) sun protection policies. For example, a SunSmart accreditation program that has been operating in Victorian primary schools since 1993 has led to accredited schools having more sun-protective policies and practices than nonaccredited schools (7). SunSmart sponsorship of Victorian lifesavers resulted in improved sun protection behavior and less sunburn among these important role models (9). SunSmart collaboration with local governments who employ many outdoor workers and are responsible for a significant proportion of outdoor space resulted in a substantial increase over time in the proportion of local authorities with sun protection policies for outdoor workers as well as policies applying to children's programs, and improvement in shade cover over children's wading pools (5). Additional detail about the elements of the program can be found in Montague et al. (5).

The aims of this study are to (a) describe change in the prevalence of teenagers' and adults' use of sun-protective clothing during outdoor leisure activities on sunny weekends from 1992 to 2002, and (b) examine the extent to which environmental factors (temperature, wind, cloud cover, shade, and leisure setting) and individual factors (sex, age, activity, and social group) were associated with people's use of sun-protective clothing.

Previous population-based surveys used to monitor people's sun protection behavior over time have relied on self-report through telephone surveys (10-12), questionnaire surveys (13-15), or a mixture of face-to-face and telephone interviews (16). The validity of self-report data can be threatened by potential biases, such as recall and misclassification bias and social desirability bias (17, 18). Some studies have used the prevalence method in which data relate to the previous weekend (10, 11) and some have assessed usual behavior (13-16), which is even more prone to recall bias.

This study is novel in that it is a survey of observed sun protection behavior among ~4,000 teenagers and adults per year over a decade. To our knowledge, this is the largest and longest-running observational survey on sun protection, enabling examination of determinants and trends in sun protection behavior using objective measures.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Participants and Setting
An observational field survey of sun protection behavior was conducted as an annual serial cross-sectional survey from 1992 to 2002. It targeted people who seemed to be 14 years or older, at leisure at parks, gardens, golf courses, tennis courts, pools, or beaches located within a 25-km radius of Melbourne city center, Australia. People swimming, working, or in uniforms were excluded. This study reports on 46,810 observations with complete data on all covariates. Table 1 provides descriptive data on the sample, which ranged from 3,337 observations in 1994 to 5,195 observations in 1999.


View this table:
[in this window]
[in a new window]

  		Table 1. Distribution of body cover index, adjusted ORs, 95% CI, P values, and Wald tests of observed characteristics by clothes cover index for the three-level random intercept logistic regression models

 
Materials and Procedures
Each year, a complete set of maps for the suburbs located within a 25-km radius of Melbourne was divided up among trained field workers, specifying their regions for data collection. Field workers were required to identify the public parks/gardens, beaches/outdoor public pools, golf courses, and tennis courts within their maps, and record observations at these sites. Sites were visited once per year. At each site, field workers were instructed to collect data until they reached a recommended number of observations, had been at the site for 30 min, or had observed all eligible people present at the site, whichever occurred first. The recommended number of observations per venue was 50 people at each golf course, pool, or beach; for each tennis club, the recommended number was 75 people on Saturdays or 25 people on Sundays (as more people play tennis on Saturdays); and for each park, 25 people on Saturdays and 75 people on Sundays. At crowded venues, field workers were required to follow a systematic protocol for sampling people to observe, to avoid selection bias. For example, at a crowded beach they were required to observe each adult they encountered when walking at a 45-degree angle from the top of the beach to the water's edge (and in the shallows) and, if necessary, walking back up the beach at the same angle along another path.

A precoded record sheet was used to document observations for each site (suburb, site address, type of leisure setting, temperature in the sun, observed cloud and wind, date, and time) and the people within it (age, sex, type of hat, shirt and leg cover garments worn, shade use, and activity). If a person was a member of a social group, this was noted, and the number in the group was recorded. Field workers followed strict rules of observation to minimize selection bias attributable to individual observer decisions.

Further to the local observations, each observation was assigned the official weather data (temperature, cloud cover, and wind) from the Bureau of Meteorology corresponding as closely as possible with the time and place of observation. A proxy indicator of socioeconomic status was assigned based on the postcode of the suburb of observation. The Australian Bureau of Statistics' 1996 urban index of relative socioeconomic advantage was used (19). For the data collection sites in the study, the range of scores on this index represented the range for the whole of Victoria, suggesting the survey achieved good breadth of sampling in this regard.

Observations were conducted when solar UV levels peak between 11 a.m. and 3 p.m. on mainly sunny and warm weekends in February and March.

Analysis
The primary outcome of interest was an index of participant's clothes cover, computed on the basis of the type of hat, shirt, and leg cover garments worn (20). For each garment, the approximate surface area of the body covered was calculated based on the cover estimated to be provided to each of 21 separate sections of the body. However, the main proportions relate to 9% cover each by the head including the neck, the left and right arms, the front and back upper chest, the front and back lower torso, upper and lower left leg, and upper and lower right leg. Using these proportions, a composite index of the proportion of the body surface covered by clothes was calculated by summing the cover provided to each individual body section. This method for estimating the body surface area covered by different garments was adapted from the body clothing coverage index used in a previous study (21) with revisions to provide more detailed calculation of head cover as afforded by different styles of hats and to account for the absence of assessment of footwear and sunscreen use. Use of sunglasses was not included in the index because it was not recorded in all years. This index was then dichotomized to represent those less than or equal to the median level of body cover for each type of setting (parks and gardens, golf courses, tennis courts, and pools and beaches) and those greater than the median with the data pooled across all years. The rationale for varying the cutoff point by setting type was that certain activity settings predicate certain clothing norms (e.g., people tend to wear trousers and shirts at golf courses, whereas at pools or beaches briefer clothing like swimsuits may be worn).

Multilevel logistic regression analysis was done to determine the effects of contextual and demographic variables on the odds of individuals achieving above the median level of clothes cover for their setting type, accounting for the high similarity in body cover within social groups and settings. Random intercepts were allowed for social groups and sites for each year. All analyses were done using GLLAMM in Stata 8.2 (22). Model 1 included time and other covariates, whereas model 2 also included variables that were found to interact with time: these were time by sex and time by activity interactions. The interactions to be tested were chosen on the basis of their educational implications for targeting of messages (age, sex, activity, wind speed, and cloud cover). Both models treated predictor variables as categorical, except for socioeconomic status, temperature, wind, and time, which were treated as continuous variables.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
During the observation period, the mean temperature was 24.8°C (SD, 1.3°C); the mean wind speed was 10.7 knots (SD, 1.7 knots). The median level of clothing cover for each setting type was 74.1% for parks and gardens, 83.0% for golf courses, 64.9% for tennis courts, and 50.9% for pools and beaches. Figure 1 shows the unadjusted trend over time for each venue in the proportion of people wearing more than the median clothing cover. Over the years, the odds of having clothes cover above the median increased for people at parks and gardens [odds ratio (OR), 1.04; 95% confidence interval (95% CI), 1.02-1.04], tennis courts (OR, 1.12; 95% CI, 1.11-1.14), and pools and beaches (OR, 1.03; 95% CI, 1.03-1.05), but decreased by 5% per year for people at golf courses (OR, 0.95; 95% CI, 0.93-0.96).


Figure 1
View larger version (11K):
[in this window]
[in a new window]
[Download PPT slide]
  		Figure 1. Unadjusted trends over time.

 
Table 1 shows the characteristics of the study population and unadjusted prevalence of wearing more than the median clothing cover for all categorical covariates. In multivariate analysis (Table 1), model 1 shows that there was a significant increase per year in the proportion of people wearing clothes above the median, with the odds increasing by 3% per year. Model 2 shows that there were significant differences in the rate of change among males and females and among those undertaking different activities. Having adjusted for all other covariates, the odds of males wearing above the median clothing cover increased by 4% per year, whereas females increased by 8% per year (Fig. 2 ). There were increases over time in clothing cover for those who were sitting and exercising (sitting OR, 1.05; exercising OR, 1.04), but no change for those who were lying, walking, or standing (lying OR, 1.00; walking OR, 0.99; standing OR, 1.00; Fig. 3 ). We undertook further analysis to assist interpretation of this pattern of findings. Table 2 shows that 6.4% of the sample was lying and nearly all of these (87.4%) were located at the pools and beaches. Overall, 27.1% of the sample was walking, and 72.2% of these were located in parks and gardens and golf courses. Over time, Table 2 also shows that the proportion of the sample that was engaged in sitting or standing did not vary. However, there were fewer people who were lying or walking as time progressed and an increase in the proportion of people who were exercising.


Figure 2
View larger version (9K):
[in this window]
[in a new window]
[Download PPT slide]
  		Figure 2. Percentage with clothing above the median by sex and time (fixed effects only).

 

Figure 3
View larger version (11K):
[in this window]
[in a new window]
[Download PPT slide]
  		Figure 3. Percentage with clothing above the median by activity and time (fixed effects only).

 

View this table:
[in this window]
[in a new window]

  		Table 2. Sample size for each activity, percent at each venue type, and change in the composition of people undertaking each activity over time (ORs and 95% CIs)

 
Environmental factors, activities undertaken, and demographic attributes were associated with body cover greater than the median in each setting. In terms of environment, compared with days of "sunshine," the odds of above the median body cover was higher on days when the observed cloud cover was "mixed thin" (13% increase), "overcast thin" (22% increase), and especially "mixed thick" (66% increase). People in partial and total shade were more likely to have above the median body cover (35% and 102% increase) compared with people in settings where shade was not available; people not using available shade were less likely to have body cover above the median (8% decrease). The odds of clothes cover decreased with higher temperatures, with a 1-unit increase in temperature associated with a decrease of 11% in the odds of having above the median body cover. A 1-unit increase in wind speed was associated with a 1% increase in the odds of having above the median body cover. Socioeconomic status of the site had no relationship with clothing cover. No significant effects were found for group size. The odds of above median body cover was lower for those who seemed to be of ages 14 to 20 years (63% decrease) and 20 to 50 years (50% decrease) compared with those of ages ≥50 years.

The random effects indicate that the body cover of both the social group and the site contribute to the odds of an individual having body cover above the median. Social groups accounted for more variance in predicting clothes cover than sites.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Results indicate that improvement in people's use of sun-protective clothing occurred during the SunSmart campaign from 1992 to 2002. This change may reflect cumulative behavioral change in association with the SunSmart campaign or other sociocultural trends. It is not possible to attribute causality with this data set. Nonetheless, the improvement over time is notable because it corroborates findings from self-report surveys that also suggest improvements in clothes cover over time and attitudes consistent with greater sun protection (11, 12). Whereas increases in self-reported sun-protective behavior could reflect a response bias due to increased awareness of the sun protection message, observational data such as these would not be compromised by such. Further, the behavioral improvements found in the respective surveys are consistent with epidemiologic evidence of a stabilization in common skin cancers in Australia (3, 4).

Strengths of this study compared with self-report surveys were that there were no dropouts, refusals, or nonresponses; the measure of sun-protective behavior was not subject to response bias; and objective weather data were obtained. Inter-rater reliability analyses indicate that the behavioral measures were not influenced by individual observer bias (20). This observational method has not previously been used to comprehensively assess clothing cover across different venues or over time in Australia or elsewhere. There are a total of just five published studies of adolescents or adults that have incorporated an observational component, but all of these have been conducted at beaches and all have supplemented the observations with interview data (17, 23-26). This means that assessment of the level of sun protection in these few studies has been a combination of observed clothing cover and reported sunscreen use. Therefore, these studies at beaches are not directly comparable with observations made in the pools and beach venues of our study.

Caution is needed in generalizing from this sample to the general population because people staying indoors to avoid the sun and those in private settings were not observed. The study did not follow a cohort over time, so the direction of causality for observed associations cannot be confirmed. Other limitations were that it was not feasible to monitor detail such as the UV-protective properties of the textiles, people's skin type, the amount of time spent outdoors, or feet and hand cover.

The study found that people on golf courses and in parks and gardens tended to have around three quarters of their skin surface covered by protective clothing. However, people at tennis courts and pools and beaches wore less protective clothing, leaving around one third to half of their skin exposed, rendering them especially vulnerable to excessive sun exposure. Previous studies have found that people are more likely to suffer excessive sun exposure when playing water sports or other sports, which tend to occur in unshaded locations and are of some duration (21, 27). This study found improvements over time in the proportion of people covering up with clothes for all the leisure settings monitored except golf courses. The apparent decline in clothes cover among golfers could reflect changes in fashion, a shift toward greater reliance on sunscreen as a method of protection, or a failure of the SunSmart campaigns to reach golfers. We also found that vigorous activity (exercising) was associated with lower odds of clothes cover than moderate activity. These results could reflect comfort concerns about heat or ease of movement, social norms, or fashion concerns. Those lying down were least likely to wear clothes cover, which could reflect deliberate sunbathing. Taken together, the results on settings, activity levels, and time suggest that there may be a persistent, albeit increasingly smaller, group of people who intentionally seek a tan by lying down in the sun at beaches and pools. In a more positive direction, we found that more people over time were exercising and increasingly greater proportions of this group covered up when outdoors. We found no change in the number of people who were sitting, but the median clothing cover of this group improved.

Options for protection other than clothes cover are available (e.g., shade and sunscreens). Yet, the results indicate that shade did not tend to be used as an alternative to clothes cover, but rather these two protective behaviors often co-occurred. The tendency of those not using available shade to also wear fewer clothes may reflect deliberate sunbathing or perceptions of warmth—it feels hotter in the sun so people disrobe more. People could have been using sunscreen (which could not be monitored in this observational study). Sunscreen is not recommended as a sole method of sun protection but to be used in conjunction with other more reliable methods of sun avoidance, such as using shade and protective clothing and hats (28).

Young people may be especially vulnerable to skin damage from solar UV in outdoor leisure settings because they are markedly less likely to wear protective clothing (especially young females). Epidemiologic research indicates that sun exposure of susceptible individuals during childhood and adolescence is an important cause of skin cancer (29, 30). Promoting increased use of sun-protective clothes among young people may compete with some social and fashion trends. Nonetheless, these data suggest that all age groups improved their sun protection at a similar rate over the years, albeit from different baselines. The data also suggest that women may have been especially responsive to the sun protection message. People's level of clothes cover also related to their social groupings within settings. This could reflect people's deliberate or inadvertent use of clothing as a signifier of social group affiliation. Among certain social subgroups, fashion norms may enable or inhibit individual's use of sun-protective clothing. Identifying and effectively reaching vulnerable groups is a continuing challenge for skin cancer prevention programs.

Clothing selection is clearly a complex behavior associated with a range of contextual and social factors. It seems that thermal concerns drove people's clothes cover more than need for sun protection because higher temperatures and less cloud cover (which are both associated with higher UV levels) were associated with lower odds of protective clothes cover. People presumably perceive that wearing more clothes when the sun is stronger is uncomfortable, or wearing less on warmer, sunnier days may reflect social norms or fashion. However, it is also possible that some people had lower clothing cover to intentionally get a tan during warmer temperatures. That this study found improvements in use of sun-protective clothing occurred over time, after controlling for various demographic characteristics and competing activity and environmental demands, provides support for the hypothesis that sustained primary skin cancer prevention campaigns have succeeded in facilitating improvements in the public's sun protection behavior.


   Acknowledgments
 
We thank Cathy Segan, who assisted in the design and implementation of the survey, and the team of field workers, who helped collect and enter the data.


   Footnotes
 
Grant support: The Cancer Council Victoria, The Victorian Health Promotion Foundation, and the Swedish Council for Working Life and Social Research (M. Lagerlund).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: D.J. Hill is the director of The Cancer Council Victoria.

Conflict of interest: Helen Dixon, Matthew Spittal, David Hill, Suzanne Dobbinson, and Melanie Wakefield are employees of The Cancer Council Victoria, which runs the SunSmart skin cancer prevention program.

Received 4/23/07; revised 11/ 2/07; accepted 11/15/07.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Carter R, Marks R, Hill D. Could a national skin cancer primary prevention campaign in Australia be worthwhile? An economic perspective. Health Promot Int 1999;14:73–82.[Abstract/Free Full Text]
  2. Mathers C, Penm R, Carter R, Stevenson C. Health system costs of diseases and injury in Australia 1993-94: an analysis of costs, service use and mortality for major disease and injury groups. Canberra: Australian Institute of Health and Welfare; the National Cancer Control Initiative; 1998.
  3. Staples MP, Marks R, Giles GG. Trends in the incidence of non-melanocytic skin cancer (NMSC) treated in Australia 1985-1995: are primary prevention programs starting to have an effect? Int J Cancer 1998;78:144–8.[CrossRef][Medline]
  4. Giles GG, Armstrong BK, Burton RC, Staples MP, Thursfield VJ. Has mortality from melanoma stopped rising in Australia? Analysis of trends between 1931 and 1994. Br Med J 1996;312:1121–5.[Abstract/Free Full Text]
  5. Montague M, Borland R, Sinclair C. Slip! Slop! Slap! and SunSmart, 1980-2000: skin cancer control and 20 years of population-based campaigning. Health Educ Behav 2001;28:290–305.[Abstract/Free Full Text]
  6. Standards Australia. AS 1067.1-1990: sunglasses and fashion spectacles. Part I: safety requirements. Sydney: Standards Australia; 1990.
  7. Dobbinson SJ, Peipers AM, Borland R, Nolan KM. Are Victorian primary schools SunSmart? The ongoing development of the SunSmart Schools Program. Health Promot J Aust 2000;10:43–50.
  8. Dobbinson S, Knight K. Protecting workers from ultraviolet radiation in sunlight. J Occup Health Safety 2001;17:587–9.
  9. Dobbinson S, Borland R, Anderson M. Sponsorship and sun protection practices in lifesavers. Health Promot Int 1999;14:167–76.[Abstract/Free Full Text]
  10. Baade PD, Balanda KP, Lowe JB. Changes in skin protection behaviours, attitudes and sunburn: in a population with the highest incidence of skin cancer in the world. Cancer Detect Prev 1996;20:566–75.[Medline]
  11. Dobbinson S, Wakefield M, Jamsen K, et al. Weekend sun protection and sunburn in Australia: trends (1987-2002) and association with SunSmart television advertising. Am J Prev Med. In press 2008.
  12. Hill D, White V, Marks R, Borland R. Changes in sun-related attitudes and behaviours, and reduced sunburn prevalence in a population at high risk of melanoma. Eur J Cancer Prev 1993;2:447–56.[Medline]
  13. Coogan PF, Geller A, Adams M, Benjes LS, Koh HK. Sun protection practices in preadolescents and adolescents: a school-based survey of almost 25,000 Connecticut schoolchildren. J Am Acad Dermatol 2001;44:512–9.[CrossRef][Medline]
  14. Livingston PM, White V, Hayman J, Dobbinson S. Sun exposure and sun protection behaviour among Australian adolescents: trends over time. Prev Med 2003;37:577–84.[CrossRef][Medline]
  15. Schofield PE, Freeman JL, Dixon HG, Borland R, Hill DJ. Trends in sun protection behaviour among Australian young adults. Aust N Z J Public Health 2001;25:62–5.[Medline]
  16. Tamir D, Tamir J, Dayan I, Josef H, Orenstein A, Shafir R. Positive changes in sun-related behavior in Israel (1994-1998). Prev Med 2002;35:369–75.[Medline]
  17. Bennetts K, Borland R, Swerissen H. Sun protection behaviour of children and their parents at the beach. Psychol Health 1991;5:279–87.
  18. Sudman S, Bradburn N. Asking questions: a practical guide to questionnaire design. New York: Jossey-Bass; 1982.
  19. Australian Bureau of Statistics. 2039.0 Information paper: census of population and housing—Socio-Economic Indexes For Areas, Australia, 2001. Canberra: Australian Bureau of Statistics; 2003.
  20. Lagerlund M, Dixon HG, Simpson JA, Spittal M, Taylor HR, Dobbinson SJ. Observed use of sunglasses in public outdoor settings around Melbourne, Australia: 1993 to 2002. Prev Med 2006;42:291–6.[Medline]
  21. Hill D, White V, Marks R, Theobald T, Borland R, Roy C. Melanoma prevention: behavioural and nonbehavioural factors in sunburn among an Australian urban population. Prev Med 1992;21:654–69.[CrossRef][Medline]
  22. StataCorp. Stata statistical software: release 8.2. College Station (TX): Stata Corporation; 2003.
  23. Pratt K, Borland R. Predictors of sun protection among adolescents at the beach. Aust Psychol 1994;29:135–9.
  24. Foot G, Girgis A, Boyle CA, Sanson-Fisher RW. Solar protection behaviours: a study of beachgoers. Aust J Public Health 1993;17:209–14.[Medline]
  25. Robinson JK, Rademaker AW. Sun protection by families at the beach. Arch Pediatr Adolesc Med 1998;152:466–70.[Abstract/Free Full Text]
  26. O'Riordan DL, Lunde KB, Steffen AD, Maddock JE. Validity of beachgoers' self-report of their sun habits. Arch Dermatol 2006;142:1348–50.[Free Full Text]
  27. Herlihy E, Gies P, Roy C, Jones M. Personal dosimetry of solar UV radiation for different outdoor activities. Photochem Photobiol 1994;60:288–94.[Medline]
  28. International Agency for Research on Cancer. Do sunscreens prevent skin cancer? Press release no. 132, 5 June 2000. Lyon (France): WHO; 2000.
  29. Armstrong B. Melanoma: childhood or lifelong exposure? In: Grob JJ, Stern RS, MacKie RM, Weinstock WA, editors. Epidemiology, causes and prevention of skin diseases. Oxford: Blackwell Science; 1997. p. 63–6.
  30. Whiteman DC, Whiteman CA, Green AC. Childhood sun exposure as a risk factor for melanoma: a systematic review of epidemiologic studies. Cancer Causes Control 2001;12:69–82.[CrossRef][Medline]



This article has been cited by other articles:


Home page
 Journal Watch DermatologyHome page
"I've Told You a Hundred Times" Works for Sun Protection
Journal Watch Dermatology, March 14, 2008; 2008(314): 5 - 5.
[Full Text]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
1055-9965.EPI-07-0369v1
17/2/428    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Dixon, H. G.
Right arrow Articles by Wakefield, M. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Dixon, H. G.
Right arrow Articles by Wakefield, M. A.
Related Collections
Right arrow Behavioral Science
Right arrow Behavioral Science: Interventions: Behavioral, Pharmacologic, Pharmacogenetic

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online