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Original Contribution  |   March 2017
Predictors of Sunburn Risk Among Florida Residents
Author Notes
• From the Nova Southeastern University College of Osteopathic Medicine (NSU-COM) in Fort Lauderdale, Florida (Student Doctor Arutyunyan, Ms Alfonso, Ms Hernandez, and Dr Fernández), and the Department of Dermatology at Broward Health Medical Center in Fort Lauderdale, Florida (Dr Favreau).
• Support: This study was supported by the Research Fellowship Program at NSU-COM.
•  *Address correspondence to M. Isabel Fernández, PhD, 3200 S University Dr, Fort Lauderdale, FL 33328-2018. E-mail: mariafer@nova.edu

Article Information
Medical Education / Graduate Medical Education
Original Contribution   |   March 2017
##### Predictors of Sunburn Risk Among Florida Residents
The Journal of the American Osteopathic Association, March 2017, Vol. 117, 150-157. doi:10.7556/jaoa.2017.029
The Journal of the American Osteopathic Association, March 2017, Vol. 117, 150-157. doi:10.7556/jaoa.2017.029
Abstract

Context: The incidence of skin cancer, the most common type of cancer in the United States, is increasing. Sunburn is a major modifiable risk factor for skin cancer, and its prevalence among the US population is high.

Objectives: To identify predictors of having had a red or painful sunburn in the past 12 months among people living in Florida.

Methods: Florida residents were recruited from public places and online. They were asked to complete an anonymous cross-sectional survey that assessed demographic information, dermatologic history, as well as knowledge, attitude, and behavior factors associated with sunburn.

Results: A total of 437 participants whose data were complete for all variables were included in the multivariate analysis. In multivariate logistic regression, younger age (18-29 years) was the most significant predictor of sunburn (OR, 15.26; 95% CI, 5.97-38.98; P<.001). Other significant predictors included identifying as nonwhite (OR, 0.51; 95% CI, 0.29-0.90; P<.02), having had a full-body skin examination by a physician (OR, 1.8; 95% CI, 1.03-3.14; P<.04), reporting higher levels of skin sensitivity to the sun (OR, 4.63; 95% CI, 2.07-10.34; P<.001), having a less favorable attitude toward sun protection (OR, 0.88; 95% CI, 0.81-0.94; P<.001), having high perceived vulnerability to skin cancer (OR, 1.21; 95% CI, 1.05-1.41; P<.009), and spending less than 1 hour outside between 10 am and 4 pm on weekends (OR, 0.46; 95% CI, 0.22-0.96; P<.04). The model was statistically significant at P<.001 and correctly classified 78% of participants.

Conclusions: Sunburn prevention programs that osteopathic physicians can readily implement in clinical practice are urgently needed, particularly for young adult patients. This study identified 7 predictors of sunburn in Florida residents. With additional research findings, promoting attitude change toward sun protection may be a viable strategy.

Keywords: Florida, skin cancer, SPF, sun protection factor, sunburn

7 Predictors of Sunburn
eVideo. Sunburn is a major modifiable risk factor for skin cancer, the most common type of cancer in the United States. Seven predictors of sunburn were identified in a study of 437 men and women in Florida.
The incidence of skin cancer in the United States increased from 2002 to 2011.1 It is now the most common cancer in the country, with 5 million people receiving treatment each year.2 Even more concerning is the rise in the incidence of melanoma, the type of skin cancer that carries the highest morbidity and mortality.1,3 Skin cancer rates are elevated in states such as Florida, where the level of ultraviolet radiation (UVR) is among the highest in the country.4,5 In the United States, the annual cost of treating patients with skin cancer is estimated at $8.1 billion.1 Although it represents less than 2% of all cases of skin cancer, melanoma causes the majority of skin cancer deaths, and the cost of treating patients with melanoma exceeds$3 billion annually.2 The annual productivity losses are estimated at \$3.8 billion.6 Skin cancer has become such a major public health issue that the US Surgeon General issued the first-ever Call to Action to Prevent Skin Cancer in 2014, urging all levels of society to mount efforts to prevent the disease.7 Osteopathic physicians have historically played an important role in disease prevention and should be able to contribute greatly to the efforts in decreasing the incidence of skin cancer.
A number of well-established risk factors for skin cancer have been reported. These include male sex, fair skin and hair, freckling, history of sunburn, common or atypical nevi, personal or family history of melanoma, and UVR exposure from sunlight or tanning beds.2,8 Among the modifiable (ie, nongenetic) risk factors, sunburn is easily preventable.9 The risk of melanoma nearly doubles for people with a history of sunburn,8-10 and 86% of melanomas can be attributed to exposure to UVR from the sun.11 The risk of sunburn is particularly high among people who live in states such as Florida, which has a high percentage of sunny days and where many have prolonged sun exposure during recreation at beaches.12
Despite the salience of sunburn to skin cancer risk, a limited number of studies have examined the factors associated with sunburn, a necessary first step toward developing preventive interventions. Two of the more important studies are secondary analyses of nationally representative US-based cross-sectional surveys.13,14 Sunburn in the past 12 months was significantly associated with younger age, higher income, higher levels of education, and recent binge drinking.13,14 Its association with white race, more sensitive skin type, family history of melanoma, being physically active, being overweight/obese, tanning indoors, and consuming alcohol was also statistically significant.14 Analyses of national surveys are limited to the variables available in the datasets. These surveys did not measure knowledge and attitudinal factors associated with skin cancer and sun protective behaviors, sun exposure during the key hours of 10 am to 4 pm, or whether respondents had their skin examined by a physician or had done it themselves.
Because sunburn is preventable, it is critical to measure attitudinal and behavioral measures when examining the predictors of sunburn. Not only will this knowledge advance our basic understanding of the barriers to sun protection, but, more importantly, it will also contribute to the development of preventive interventions. This approach has been successfully used to modify other health-related behaviors, such as performing Pap smears and colonoscopies to screen for cervical and colorectal cancer, respectively, and promoting exercise and a healthy diet to potentially reduce cardiovascular disease and prevent cancer.15-17 Although studies have included behavioral measures,13,14 few have measured attitudinal factors. Rather than focusing on modifiable behaviors directly relevant to sunburn, such as use of sunscreen or hours spent in the sun, these studies assessed other less directly related behaviors, such as binge drinking and obesity.
The goal of the current study was to examine a more comprehensive set of factors associated with sunburn in a community sample of Florida residents as an initial step toward the development and implementation of interventions to prevent sunburn. This study extends past research by assessing dermatologically relevant variables, as well as knowledge, attitudes, and behaviors with regard to skin cancer and sun protection.
Methods
From February to April 2015, we recruited people from public places (eg, beaches, coffee shops, libraries, streets, university campuses) and online (e-mails, listservs, and posts on social media) to complete a 20-minute anonymous cross-sectional survey on paper or online after screening for eligibility. Eligible participants were those who resided in Florida, were aged 18 years or older, and spoke and understood English. Nova Southeastern University’s institutional review board approved the protocol as exempt in January 2015.
All eligible participants were informed that by completing the survey they were providing consent. At the end of the survey, participants were invited to provide an unlinked e-mail address to be entered into a raffle of 3 iPod Nano devices (Apple). Participants who completed the paper form wrote their e-mail address on a separate page; online participants were redirected to a different website to submit their e-mail address.
Survey
The researchers compiled 79 questions from the set of core items developed by Glanz et al18 and other questions found in the literature.19,20 The survey was pilot tested for comprehension and readability on 10 participants. The following areas were assessed:
• Demographic characteristics. Participants reported their age, sex, race, education, and employment. The large age range of the respondents was collapsed into 3 age categories (18-29, 30-59, and ≥60 years).
• Dermatologic factors. Participants selected 1 of 6 options to represent their skin’s sensitivity to the sun using responses that ranged from 1 (“always burns, never tans”) to 6 (“never burns, tans very easily”). To facilitate analyses, these responses were collapsed into 3 categories (1, always or usually burns; 2, sometimes mildly or rarely burns; and 3, very rarely or never burns). They also reported the average number of hours spent outside from 10 am to 4 pm on weekdays and weekends, whether they had ever used tanning beds or had a full-body skin examination performed by a physician or themselves, and their personal and family history of skin cancer.
• Knowledge. For each of 18 items, participants responded whether the item was true or false. Sample items included: “You cannot get sunburned on a cloudy day” or “Sunscreen should be reapplied every 2 hours.” The number of correct responses was summed to calculate a knowledge score.
• Attitudinal factors. Using a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree), participants reported how strongly they agreed or disagreed with items related to skin cancer risk and sun protection. Sample items included “I think it is important to protect myself from the sun” and “I worry about getting skin cancer.”
• Sun protective behaviors. Participants reported the frequency with which they engaged in 9 behaviors using a 5-point Likert scale ranging from 1 (never) to 5 (always). Sample items included “How often do you avoid the sun during the hours of 10 am to 4 pm?” and “How often do you wear sunscreen when you are outdoors?” A sum score was calculated for use in the analysis; the higher the score, the greater the engagement in sun-protective behaviors.
• Sunburn history. Participants reported the number of red or painful sunburns they had in the past 12 months. Because few respondents reported more than 2, the data were collapsed into 2 categories: 0 (no sunburns) and 1 (≥1 sunburn). The dichotomous variable was used as the dependent variable in the analyses.
Statistical Analysis
Because the internal consistency (Cronbach α) of the attitudinal items was low, a principal component analysis was conducted. Examining the scree plot and the eigenvalues of the factors led to the selection of a 3-factor solution. This solution placed eigenvalues for each factor above 1.0. These factors were then examined from an internal consistency and theoretical standpoint, and final subscale grouping for ambiguous items loading on multiple factors were made based on the strongest conceptual grouping. Items with poor reliability were trimmed, as well as items deemed redundant with other items. Three subscales were then constructed with associated Cronbach α and named factor 1: awareness of skin cancer risk (α=.70); factor 2: attitudes toward sun protection (α=.70); and factor 3: perceived vulnerability to skin cancer (α=.50). Higher scores were associated with stronger agreement. Variable computations and statistical analyses were performed using SPSS version 23.0 (IBM).
Descriptive statistics and measures of central tendency were used to examine sample characteristics. Prevalence was calculated by dividing the number of participants reporting sunburn by the total sample. Bivariate analyses were then conducted to examine the association between sunburn and the predictor variables (age, sex, race, education, employment, sensitivity of skin to sun, hours spent outside between 10 am and 4 pm on weekdays and weekends, use of tanning beds, full-body skin examination by self or physician, personal or family member skin cancer diagnosis, knowledge score, awareness of skin cancer risk, attitudes toward sun protection, perceived vulnerability to skin cancer, and behavior score). χ2 analyses were used for categorical variables, and correlational analyses were conducted for the continuous variables. All variables significantly associated with the outcome at P<.05 were included in the multivariate logistic regression analysis. As per Hosmer and Lemeshow, theoretically relevant variables that approached significance at P=.10 were also included.21
Results
Of 619 Florida residents who were recruited, 437 (70.6%) whose data were complete for all variables were included in the multivariate analysis. Missing data were random; no patterns for missing data were identified. The characteristics of the sample are presented in Table 1. The mean age of the sample was 40.7 years (range, 18-92 years; median, 34 years). More than 50% of the sample was white, employed, and college educated. The sample comprised 205 men (33.1%) and 412 women (66.6%). Two hundred thirty-one (37%) reported having had a red or painful sunburn that lasted a day or more in the past 12 months, and 265 (43%) reported having had a full-body skin examination by a physician. A previous diagnosis of any type of skin cancer was reported by 79 participants (12.8%), and melanoma was reported by 12 participants (2.75%). Participants had relatively strong knowledge regarding skin cancer and sun protection and awareness of skin cancer risk. Attitudes toward sun protection and perceived vulnerability to skin cancer were not as strong.
Table 1.
Sunburn Risk Among Adult Florida Residents: Sample Characteristics (N=619)
Factor No. (%)a
Age, y
18-29 263 (42.8)
30-59 217 (35.3)
≥60 134 (21.8)
Sex
Male 205 (33.1)
Female 412 (66.6)
Race
White 336 (56.0)
Nonwhite 264 (44.0)
Highest Level of Education
High school diploma/GED 166 (27.0)
Vocational degree 25 (4.1)
Master’s degree 94 (15.3)
Doctorate degree 72 (11.7)
Employment
Employed 404 (65.8)
Unemployed 210 (34.2)
Skin Sensitivity to Sun
Always or usually burns 131 (27.5)
Sometimes or rarely burns 246 (51.7)
Very rarely or never burns 99 (20.8)
Painful Sunburn in Past 12 mob
Yes 231 (37.4)
No 387 (62.6)
Hours Outside, 10 am-4 pm
Weekday
≤1 403 (65.1)
2-3 144 (23.3)
≥4 72 (11.6)
Weekend
≤1 221 (35.7)
2-3 242 (39.1)
≥4 156 (25.2)
Use of Tanning Beds
Yes 135 (21.9)
No 481 (78.1)
Full-Body Skin Examination
By physician
Yes 265 (43.1)
No 350 (56.9)
By self
Yes 192 (31.5)
No 418 (68.5)
History of Skin Cancer
Personal
Yes 79 (12.8)
No 539 (87.2)
Family
Yes 228 (37.1)
No 386 (62.9)
Knowledge/Attitude/Behavior, mean (SD) score
Knowledge (maximum score, 18)c 15.55 (2.16)
Awareness of skin cancer risk (maximum score, 40)d 33.39 (4.11)
Attitudes toward sun protection (maximum score, 25)e 14.41 (3.84)
Perceived vulnerability to skin cancer (maximum score, 10)f 6.13 (1.84)
Sun protective behaviors (maximum score, 45)g 28.77 (6.36)

a The total sample size for each variable may not add up to 619 because of missing data. Data are presented as No. (%) unless otherwise indicated.

b Main outcome measure.

c 18 items, 1 point was awarded for each correct answer and the score was calculated by summing the number of correct responses with maximum knowledge score of 18 points.

d 8 items, each awarded up to 5 points, for a maximum score of 40 points.

e 5 items, each awarded up to 5 points for a maximum of 25 points.

f 2 items, each awarded up to 5 points for a maximum of 10 points.

g 9 items, each awarded up to 5 points for a maximum of 45 points.

Table 1.
Sunburn Risk Among Adult Florida Residents: Sample Characteristics (N=619)
Factor No. (%)a
Age, y
18-29 263 (42.8)
30-59 217 (35.3)
≥60 134 (21.8)
Sex
Male 205 (33.1)
Female 412 (66.6)
Race
White 336 (56.0)
Nonwhite 264 (44.0)
Highest Level of Education
High school diploma/GED 166 (27.0)
Vocational degree 25 (4.1)
Master’s degree 94 (15.3)
Doctorate degree 72 (11.7)
Employment
Employed 404 (65.8)
Unemployed 210 (34.2)
Skin Sensitivity to Sun
Always or usually burns 131 (27.5)
Sometimes or rarely burns 246 (51.7)
Very rarely or never burns 99 (20.8)
Painful Sunburn in Past 12 mob
Yes 231 (37.4)
No 387 (62.6)
Hours Outside, 10 am-4 pm
Weekday
≤1 403 (65.1)
2-3 144 (23.3)
≥4 72 (11.6)
Weekend
≤1 221 (35.7)
2-3 242 (39.1)
≥4 156 (25.2)
Use of Tanning Beds
Yes 135 (21.9)
No 481 (78.1)
Full-Body Skin Examination
By physician
Yes 265 (43.1)
No 350 (56.9)
By self
Yes 192 (31.5)
No 418 (68.5)
History of Skin Cancer
Personal
Yes 79 (12.8)
No 539 (87.2)
Family
Yes 228 (37.1)
No 386 (62.9)
Knowledge/Attitude/Behavior, mean (SD) score
Knowledge (maximum score, 18)c 15.55 (2.16)
Awareness of skin cancer risk (maximum score, 40)d 33.39 (4.11)
Attitudes toward sun protection (maximum score, 25)e 14.41 (3.84)
Perceived vulnerability to skin cancer (maximum score, 10)f 6.13 (1.84)
Sun protective behaviors (maximum score, 45)g 28.77 (6.36)

a The total sample size for each variable may not add up to 619 because of missing data. Data are presented as No. (%) unless otherwise indicated.

b Main outcome measure.

c 18 items, 1 point was awarded for each correct answer and the score was calculated by summing the number of correct responses with maximum knowledge score of 18 points.

d 8 items, each awarded up to 5 points, for a maximum score of 40 points.

e 5 items, each awarded up to 5 points for a maximum of 25 points.

f 2 items, each awarded up to 5 points for a maximum of 10 points.

g 9 items, each awarded up to 5 points for a maximum of 45 points.

×
At the bivariate level, age, race, employment, skin sensitivity to the sun, hours spent outside between 10 am and 4 pm on weekdays and weekends, use of tanning beds, having had a full-body skin examination conducted by a physician, having a personal history of skin cancer, having a family history of skin cancer, attitudes toward sun protection, and perceived vulnerability to skin cancer were statistically significantly associated with sunburn. All were entered into the logistic regression analyses.
The final multivariate logistic regression model is presented in Table 2. The associations of sunburn at the multivariate level with younger age, identifying as nonwhite, having had a full-body skin examination by a clinician, reporting higher levels of skin sensitivity to the sun, having less favorable attitudes toward sun protection, and having high perceived vulnerability to skin cancer were statistically significant. Participants who were aged 18 to 29 years were 15.3 times more likely and those aged 30 to 59 years were 5.82 times more likely to have been sunburned in the past 12 months than those aged 60 years or older. Participants with more favorable attitudes toward sun protection were 0.88 times less likely to have been sunburned than those with less favorable attitudes. Those with higher perceived vulnerability to skin cancer were 1.21 times more likely to have been sunburned than those with lower perceived vulnerability. The model was statistically significant at P<.001 and correctly classified 341 participants (78%).
Table 2.
Multivariate Predictors of Sunburn Among Florida Residents in the Past 12 Months (N=619)
Independent Variable OR (95% CI) P Value
Age, y
18-29 15.26 (5.97-38.98) <.001
30-59 5.82 (2.40-14.13) <.001
≥60 (referent)
Nonwhite Race 0.51 (0.29-0.90) .02
Skin Sensitivity to Sun
Always or usually burns 4.63 (2.07-10.34) <.001
Sometimes or rarely burns 3.08 (1.53-6.20) .002
Very rarely or never burns (referent)
No. of Hours Outside, 10 am-4 pm (weekend)
≤1 0.46 (0.22-0.96) .04
2-3 0.87 (0.47-1.64)
≥4 (referent)
Full-Body Skin Examination (physician) 1.80 (1.03-3.14) .04
Knowledge/Attitude/Behavior
Attitudes toward sun protection 0.88 (0.81-0.94) .001
Perceived vulnerability to skin cancer 1.21 (1.05-1.41) .009
Table 2.
Multivariate Predictors of Sunburn Among Florida Residents in the Past 12 Months (N=619)
Independent Variable OR (95% CI) P Value
Age, y
18-29 15.26 (5.97-38.98) <.001
30-59 5.82 (2.40-14.13) <.001
≥60 (referent)
Nonwhite Race 0.51 (0.29-0.90) .02
Skin Sensitivity to Sun
Always or usually burns 4.63 (2.07-10.34) <.001
Sometimes or rarely burns 3.08 (1.53-6.20) .002
Very rarely or never burns (referent)
No. of Hours Outside, 10 am-4 pm (weekend)
≤1 0.46 (0.22-0.96) .04
2-3 0.87 (0.47-1.64)
≥4 (referent)
Full-Body Skin Examination (physician) 1.80 (1.03-3.14) .04
Knowledge/Attitude/Behavior
Attitudes toward sun protection 0.88 (0.81-0.94) .001
Perceived vulnerability to skin cancer 1.21 (1.05-1.41) .009
×
Discussion
The American Osteopathic Association has identified 5 research focus areas that would have the greatest potential to affect patient care and demonstrate the value osteopathic physicians offer in these areas.22 One focus area encompasses prevention, diagnosis, and management of diseases with high public health impact and for which osteopathic approaches can lead to improvements in patient outcomes and reduction in health care costs.22 As rates of skin cancer continue to increase, it is important to launch directed efforts to prevent its occurrence. A possible approach is to develop tailored interventions that target modifiable risk factors such as sunburns. Identifying factors associated with sunburn, as reported in the current paper, is a critical first step toward the development of interventions.
The 37% prevalence of sunburn in our sample mirrors national prevalence estimates.13,14 Prevalence rates for men (38.7%) and women (36.9%) were comparable in the current study; thus, no statistically significant bivariate differences by sex were found. It was surprising that neither knowledge nor engagement in sun protective behaviors was significantly associated with sunburn at the bivariate level. The association between knowledge and sunburn could have been attenuated, considering that the content of the knowledge items did not exclusively focus on sunburn prevention and other sun protective behaviors but also assessed knowledge of skin cancer. However, this was not the case for behaviors because the items directly assessed behaviors that would protect against sunburn.
Similar to previous reports,13,14 younger age was the most statistically significant predictor of sunburn in the multivariate model. This consistent finding is particularly troubling given that melanoma is the most common type of all cancers for people aged 25 to 29 years and the second most common type of cancer for people aged 15 to 29 years.23 It also suggests that existing sunburn prevention efforts are not reaching those most at risk, which points to the importance of developing prevention messages and programs tailored specifically to young adults. Innovative apps promoting sunburn protection that can be incorporated as part of routine clinical care could be developed. Messages from osteopathic physicians through texts, social media, or websites to disseminate this information to their patients may also be effective.
Interestingly, being nonwhite was a statistically significant predictor of sunburn. It could be that nonwhite participants may think that their darker skin protects them from sunburn and as a result do not practice sun-protective behaviors. Several dermatologically relevant factors, including skin sensitivity to the sun and having had a full-body skin examination by a physician were significantly associated with sunburn. Whereas some might argue that a full-body skin examination might reflect a tendency to engage in preventive behaviors overall and consequently should be inversely related to sunburn, it could also be that having had a severe sunburn might have prompted some participants to ask their clinicians for full-body skin examinations. Because a cross-sectional assessment does not elucidate temporal associations, it is not possible to differentiate whether the sunburn prompted the skin examination or whether negative results made patients overconfident. Neither lifetime history of using tanning beds nor having a personal or a family history of skin cancer diagnosis emerged as statistically significant predictors of sunburn in the final model.
Two attitudinal factors (attitude toward sun protection and perceived vulnerability to skin cancer) remained statistically significant in the final model. Participants with a less favorable attitude toward sun protection may not have strongly believed that sun-protective behavior is an important part of maintaining healthy skin. Participants with high perceived vulnerability to skin cancer may have been sunburned in the past but continue to get sunburned despite the risk of getting skin cancer.
Because it is modifiable, attitude toward sunburn and sun protection may be an effective target to reduce sunburns. This factor has not received widespread attention, possibly because a reliable and valid attitudinal measure related to sunburn and sun protection has yet to be developed. Constructing a reliable and valid attitudinal measure should be a research priority. The attitudinal measure used in the current study can be construed as an initial measurement step. All 3 factors had adequate internal consistency, which could be improved with item refinement and additional psychometric testing.
The cross-sectional design and the use of a convenience sample are 2 limitations of the current study. Despite these limitations, the prevalence rate was comparable to national estimates, suggesting that our sample was sufficiently broad. Although the survey was designed using previously published items, it was not a standardized measure. Thus, the psychometric properties of the attitudinal items might have attenuated the strength of the association.
Conclusion
The current study examined dermatologically relevant factors, as well as sunburn-specific knowledge, attitudes, and behaviors, in a sample that, by virtue of living in Florida, is at increased risk of sunburn. The findings highlight the urgency of developing tailored sunburn prevention programs, particularly aimed at young adults, who are at greatest risk. The link between attitudinal factors and sunburn history suggests that such programs might benefit from promoting changes in attitudes. An important focus of future research would be the development of standardized attitudinal measures that could yield more nuanced understanding of the associations with sunburn risk so that improved prevention methods could be developed and incorporated as a routine part of clinical practice.
References
Guy GP, Machlin SR, Ekwueme DU, Yabroff KR. Prevalence and costs of skin cancer treatment in the U.S., 2002-2006 and 2007-2011. Am J Prev Med. 2015;48(2):183-187. doi:10.1016/j.amepre.2014.08.036
Cancer Facts & Figures. Atlanta, GA: American Cancer Society; 2014.
Purdue MP, Freeman LEB, Anderson WF, Tucker MA. Recent trends in incidence of cutaneous melanoma among US Caucasian young adults. J Invest Dermatol. 2008;128(12):2905-2908. doi:10.1038/jid.2008.159
UVA index. United States Environmental Protection Agency website. https://www.epa.gov/sunsafety/uv-index-1. Accessed January 27, 2017.
Nole G, Johnson AW. An analysis of cumulative lifetime solar ultraviolet radiation exposure and the benefits of daily sun protection. Dermatol Ther. 2004;17(suppl 1):57-62.
Bickers DR, Lim HW, Margolis D, et al The burden of skin diseases 2004: a joint project of the American Academy of Dermatology Association and the Society for Investigative Dermatology. J Am Acad Dermatol. 2006;55(3):490-500.
US Department of Health and Human Services. The Surgeon General’s Call to Action to Prevent Skin Cancer. Washington, DC: US Dept of Health and Human Services, Office of the Surgeon General; 2014.
Gandini S, Sera F, Cattaruzza MS, et al Meta-analysis of risk factors for cutaneous melanoma, II: sun exposure. Eur J Cancer. 2005;41(1):45-60. doi:10.1016/j.ejca.2004.10.016
Armstrong BK, Kricker A. The epidemiology of UV induced skin cancer. J Photochem Photobiol B. 2001;63(1-3):8-18.
Kennedy C, Bajdik CD, Willemze R, De Gruijl FR, Bouwes Bavinck JN; Leiden Skin Cancer Study. The influence of painful sunburns and lifetime sun exposure on the risk of actinic keratoses, seborrheic warts, melanocytic nevi, atypical nevi, and skin cancer. J Invest Dermatol. 2003;120(6):1087-1093. doi:10.1046/j.1523-1747.2003.12246.x
Parkin DM, Mesher D, Sasieni. P 13. Cancers attributable to solar (ultraviolet) radiation exposure in the UK in 2010. Br J Cancer. 2011;105(suppl 2):S66-S69. doi:10.1038/bjc.2011.486
Ranking of cities based on % annual possible sunshine in descending order from most to least average possible sunshine. National Oceanic and Atmospheric Administration website. http://www1.ncdc.noaa.gov/pub/data/ccd-data/pctposrank.txt. Accessed January 18, 2017.
Brown TT, Quain RD, Troxel AB, Gelfand JM. The epidemiology of sunburn in the US population in 2003. J Am Acad Dermatol. 2006;55(4):577-583. doi:10.1016/j.jaad.2006.05.029
Holman DM, Berkowitz Z, Guy GPJr, Hartman AM, Perna FM. The association between demographic and behavioral characteristics and sunburn among U.S. adults - National Health Interview Survey, 2010. Prev Med. 2014;63:6-12. doi:10.1016/j.ypmed.2014.02.018
Demark-Wahnefried W, Rock CL, Patrick K, Byers T. Lifestyle interventions to reduce cancer risk and improve outcomes. Am Fam Physician. 2008;77(11):1573-1578.
Lippman SM, Hawk ET. Cancer prevention: from 1727 to milestones of the past 100 years. Cancer Res. 2009;69(13):5269-5284. doi:10.1158/0008-5472.CAN-09-1750
Greenwald P, Dunn BK. Landmarks in the history of cancer epidemiology. Cancer Res. 2009;69(6):2151-2162. doi:10.1158/0008-5472.CAN-09-0416
Glanz K, Yaroch AL, Dancel M, et al Measures of sun exposure and sun protection practices for behavioral and epidemiologic research. Arch Dermatol. 2008;144(2):217-222. doi:10.1001/archdermatol.2007.46
Patel SS, Nijhawan RI, Stechschulte S, et al Skin cancer awareness, attitude, and sun protection behavior among medical students at the University of Miami Miller School of Medicine. Arch Dermatol. 2010;146(7):797-800. doi:10.1001/archdermatol.2010.140
Rouhani P, Parmet Y, Bessell AG, Peay T, Weiss A, Kirsner RS. Knowledge, attitudes, and behaviors of elementary school students regarding sun exposure and skin cancer. Pediatr Dermatol. 2009;26(5):529-535. doi:10.1111/j.1525-1470.2009.00908.x
Hosmer DW, Lemeshow S. Model-building strategies and methods for logistic regression. In: Applied Logistic Regression. 2nd ed. New York, NY: Wiley; 2000:91-142. Chapter 4.
Focus areas. American Osteopathic Association website. https://www.osteopathic.org/inside-aoa/development/research-and-development/Pages/focus-areas.aspx. Accessed January 18, 2017.
Bleyer A, O’Leary M, Barr R, Ries LAG, eds. Cancer Epidemiology in Older Adolescents and Young Adults 15 to 29 Years of Age, Including SEER Incidence and Survival: 1975-2000. Bethesda, MD: National Cancer Institute; 2006. NIH publication 06-5767.
Table 1.
Sunburn Risk Among Adult Florida Residents: Sample Characteristics (N=619)
Factor No. (%)a
Age, y
18-29 263 (42.8)
30-59 217 (35.3)
≥60 134 (21.8)
Sex
Male 205 (33.1)
Female 412 (66.6)
Race
White 336 (56.0)
Nonwhite 264 (44.0)
Highest Level of Education
High school diploma/GED 166 (27.0)
Vocational degree 25 (4.1)
Master’s degree 94 (15.3)
Doctorate degree 72 (11.7)
Employment
Employed 404 (65.8)
Unemployed 210 (34.2)
Skin Sensitivity to Sun
Always or usually burns 131 (27.5)
Sometimes or rarely burns 246 (51.7)
Very rarely or never burns 99 (20.8)
Painful Sunburn in Past 12 mob
Yes 231 (37.4)
No 387 (62.6)
Hours Outside, 10 am-4 pm
Weekday
≤1 403 (65.1)
2-3 144 (23.3)
≥4 72 (11.6)
Weekend
≤1 221 (35.7)
2-3 242 (39.1)
≥4 156 (25.2)
Use of Tanning Beds
Yes 135 (21.9)
No 481 (78.1)
Full-Body Skin Examination
By physician
Yes 265 (43.1)
No 350 (56.9)
By self
Yes 192 (31.5)
No 418 (68.5)
History of Skin Cancer
Personal
Yes 79 (12.8)
No 539 (87.2)
Family
Yes 228 (37.1)
No 386 (62.9)
Knowledge/Attitude/Behavior, mean (SD) score
Knowledge (maximum score, 18)c 15.55 (2.16)
Awareness of skin cancer risk (maximum score, 40)d 33.39 (4.11)
Attitudes toward sun protection (maximum score, 25)e 14.41 (3.84)
Perceived vulnerability to skin cancer (maximum score, 10)f 6.13 (1.84)
Sun protective behaviors (maximum score, 45)g 28.77 (6.36)

a The total sample size for each variable may not add up to 619 because of missing data. Data are presented as No. (%) unless otherwise indicated.

b Main outcome measure.

c 18 items, 1 point was awarded for each correct answer and the score was calculated by summing the number of correct responses with maximum knowledge score of 18 points.

d 8 items, each awarded up to 5 points, for a maximum score of 40 points.

e 5 items, each awarded up to 5 points for a maximum of 25 points.

f 2 items, each awarded up to 5 points for a maximum of 10 points.

g 9 items, each awarded up to 5 points for a maximum of 45 points.

Table 1.
Sunburn Risk Among Adult Florida Residents: Sample Characteristics (N=619)
Factor No. (%)a
Age, y
18-29 263 (42.8)
30-59 217 (35.3)
≥60 134 (21.8)
Sex
Male 205 (33.1)
Female 412 (66.6)
Race
White 336 (56.0)
Nonwhite 264 (44.0)
Highest Level of Education
High school diploma/GED 166 (27.0)
Vocational degree 25 (4.1)
Master’s degree 94 (15.3)
Doctorate degree 72 (11.7)
Employment
Employed 404 (65.8)
Unemployed 210 (34.2)
Skin Sensitivity to Sun
Always or usually burns 131 (27.5)
Sometimes or rarely burns 246 (51.7)
Very rarely or never burns 99 (20.8)
Painful Sunburn in Past 12 mob
Yes 231 (37.4)
No 387 (62.6)
Hours Outside, 10 am-4 pm
Weekday
≤1 403 (65.1)
2-3 144 (23.3)
≥4 72 (11.6)
Weekend
≤1 221 (35.7)
2-3 242 (39.1)
≥4 156 (25.2)
Use of Tanning Beds
Yes 135 (21.9)
No 481 (78.1)
Full-Body Skin Examination
By physician
Yes 265 (43.1)
No 350 (56.9)
By self
Yes 192 (31.5)
No 418 (68.5)
History of Skin Cancer
Personal
Yes 79 (12.8)
No 539 (87.2)
Family
Yes 228 (37.1)
No 386 (62.9)
Knowledge/Attitude/Behavior, mean (SD) score
Knowledge (maximum score, 18)c 15.55 (2.16)
Awareness of skin cancer risk (maximum score, 40)d 33.39 (4.11)
Attitudes toward sun protection (maximum score, 25)e 14.41 (3.84)
Perceived vulnerability to skin cancer (maximum score, 10)f 6.13 (1.84)
Sun protective behaviors (maximum score, 45)g 28.77 (6.36)

a The total sample size for each variable may not add up to 619 because of missing data. Data are presented as No. (%) unless otherwise indicated.

b Main outcome measure.

c 18 items, 1 point was awarded for each correct answer and the score was calculated by summing the number of correct responses with maximum knowledge score of 18 points.

d 8 items, each awarded up to 5 points, for a maximum score of 40 points.

e 5 items, each awarded up to 5 points for a maximum of 25 points.

f 2 items, each awarded up to 5 points for a maximum of 10 points.

g 9 items, each awarded up to 5 points for a maximum of 45 points.

×
Table 2.
Multivariate Predictors of Sunburn Among Florida Residents in the Past 12 Months (N=619)
Independent Variable OR (95% CI) P Value
Age, y
18-29 15.26 (5.97-38.98) <.001
30-59 5.82 (2.40-14.13) <.001
≥60 (referent)
Nonwhite Race 0.51 (0.29-0.90) .02
Skin Sensitivity to Sun
Always or usually burns 4.63 (2.07-10.34) <.001
Sometimes or rarely burns 3.08 (1.53-6.20) .002
Very rarely or never burns (referent)
No. of Hours Outside, 10 am-4 pm (weekend)
≤1 0.46 (0.22-0.96) .04
2-3 0.87 (0.47-1.64)
≥4 (referent)
Full-Body Skin Examination (physician) 1.80 (1.03-3.14) .04
Knowledge/Attitude/Behavior
Attitudes toward sun protection 0.88 (0.81-0.94) .001
Perceived vulnerability to skin cancer 1.21 (1.05-1.41) .009
Table 2.
Multivariate Predictors of Sunburn Among Florida Residents in the Past 12 Months (N=619)
Independent Variable OR (95% CI) P Value
Age, y
18-29 15.26 (5.97-38.98) <.001
30-59 5.82 (2.40-14.13) <.001
≥60 (referent)
Nonwhite Race 0.51 (0.29-0.90) .02
Skin Sensitivity to Sun
Always or usually burns 4.63 (2.07-10.34) <.001
Sometimes or rarely burns 3.08 (1.53-6.20) .002
Very rarely or never burns (referent)
No. of Hours Outside, 10 am-4 pm (weekend)
≤1 0.46 (0.22-0.96) .04
2-3 0.87 (0.47-1.64)
≥4 (referent)
Full-Body Skin Examination (physician) 1.80 (1.03-3.14) .04
Knowledge/Attitude/Behavior
Attitudes toward sun protection 0.88 (0.81-0.94) .001
Perceived vulnerability to skin cancer 1.21 (1.05-1.41) .009
×

7 Predictors of Sunburn
eVideo. Sunburn is a major modifiable risk factor for skin cancer, the most common type of cancer in the United States. Seven predictors of sunburn were identified in a study of 437 men and women in Florida.