Citation
Prevalence and Correlates of Skin Cancer Risk Behaviors among College Students

Material Information

Title:
Prevalence and Correlates of Skin Cancer Risk Behaviors among College Students
Creator:
Merten, Julie Williams
Place of Publication:
[Gainesville, Fla.]
Florida
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (104 p.)

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Public Health
Behavioral Science and Community Health
Committee Chair:
POMERANZ,JAMIE L
Committee Co-Chair:
MOORHOUSE,MICHAEL D
Committee Members:
XU,XIAOHUI
WALSH-CHILDERS,KIM B
Graduation Date:
8/9/2014

Subjects

Subjects / Keywords:
Adolescents ( jstor )
College students ( jstor )
Disease risks ( jstor )
Exercise ( jstor )
Melanoma ( jstor )
Skin cancers ( jstor )
Sun tanning ( jstor )
Sunburn ( jstor )
Sunscreening agents ( jstor )
Tanning lotions ( jstor )
Behavioral Science and Community Health -- Dissertations, Academic -- UF
cancer -- college -- health -- skin -- sunscreen
Genre:
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Public Health thesis, Ph.D.

Notes

Abstract:
Skin cancer is the most common, yet highly preventable, form of cancer in the United States with melanoma rates steadily increasing. Melanoma rates in the past 40 years have increased 800% in women and 400% in men under the age of 39. Ultraviolet radiation (UVR) from the sun or from indoor tanning machines is directly linked with the development of skin cancer. Young adults ages 18 to 29, specifically college students, comprise the most active age group engaging in risky UV exposure. The purpose of this cross-sectional study is to extend scientific understanding of skin cancer prevention behaviors and explore the relationship between sunscreen use and the health risk behaviors associated with mortality and morbidity among college students. A convenience sample of 747 college students at a mid-sized southeastern university was surveyed about skin cancer prevention behavior and other health risk behaviors. Data were analyzed using SAS 9.2 and SPSS 19. Results showed that overall skin cancer prevention behaviors were inadequate with only 33% of students sufficiently reporting sunscreen use, 72% of students reporting sunburn in the previous year, 58% reporting more than two hours outside during peak hours (10 to 4pm) in the past year, and nearly 80% have never had a skin cancer check by a healthcare provider. White, female, students over the age of 21 were more likely to use sunscreen. Seat belt use, texting while driving, low life satisfaction, and binge drinking predicted inadequate sunscreen use. Findings suggest that despite widespread educational efforts to reduce skin cancer, college students receive large amounts of intentional and unintentional exposure to UV radiation either from the sun or indoor tanning. Further, the identification of associations between sunscreen use and other high-risk behaviors among college students provide the framework to develop multiple risk factor interventions. Programs aimed at multiple behavioral health risks including sun protection, have shown great promise for health promotion and reduced healthcare costs. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2014.
Local:
Adviser: POMERANZ,JAMIE L.
Local:
Co-adviser: MOORHOUSE,MICHAEL D.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2015-08-31
Statement of Responsibility:
by Julie Williams Merten.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Embargo Date:
8/31/2015
Classification:
LD1780 2014 ( lcc )

Downloads

This item has the following downloads:


Full Text

PAGE 1

PREVALENCE AND CORRELATES OF SKIN CANCER RISK BEHAVIORS AMONG COLLEGE STUDENTS By JULIE WILLIAMS MERTEN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREME NTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2014

PAGE 2

2014 Julie Williams Merten

PAGE 3

To my parents, Sharon and Stuart Williams, for giving me a happy, wonderful life filled with opportunity and love. And for my husband, SteveO, for providing entertainment along the way.

PAGE 4

ACKNOWLEDGMENTS I express my deepest appreciation to all of my wonderful colleagues and friends at the University of North Florida who have endured my endless woes over the past three years. My journey at the University of Florida would not be possible without the support from my University of North Florida crew: Pam Chally, Cathy Christie, Michele Moore, Aaron Spaulding, Richmond Wynn, Elissa Barr, Tammie Johnson, Kerr y Clark, Mei Zhao, Natalie Indelicato, JC Churilla, Michelle Boling, Juliana Leding, Jeff Harrison, Joel Beam, Emma Apatu, Colleen Kalynych, Karen Coleman, Julie Schafer, JoAnn Nolin, Li Loriz, Miwa Nguyen, Fred Dale, Judy Perkin, Pam Niemcyzk, Bernie Buck ley, Hugh Cornell, Rachel Martin, and Sam Mathias. You all will never know how much your words of encouragement, advice, and patience have meant over the past three years . I also must acknowledge Bay Bay for getting me started on this adventure and Sweet Baby Ray for helping to finish the job. And, a few dear friends at the University of Florida offered treasured support: Melissa Vilaro, Evelyn King Marshall, Jenn Nguyen, and Jessie King. I also thank my committee members, Drs. Jamie Pomeranz, Kim WalshChilders, Mike Moorhouse, and Xiaohui Xu for their time and guidance during this journey. Specifically, Dr. Walsh Childers for providing solace and friendship during the loss of my fur child. 4

PAGE 5

TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 7 LIST OF FIGURES .......................................................................................................... 8 ABSTRACT ..................................................................................................................... 9 CHAPTER 1 INTRODUCTION .................................................................................................... 11 Skin Cancer Etiology ............................................................................................... 11 Skin Cancer Risk Factors ....................................................................................... 13 College S tudents and UVR ..................................................................................... 16 Problem Behavior Theory and Multiple Health Behavior Risk Research ................ 17 Leading Causes of Morbidity and Mortali ty Among College Students .................... 19 Physical Activity ................................................................................................ 20 Smoking ........................................................................................................... 20 Sub stance Abuse ............................................................................................. 21 Sexual Behavior ............................................................................................... 22 Unintentional Injury ........................................................................................... 23 Mental Health ................................................................................................... 24 Significance ............................................................................................................ 24 Research Aims ....................................................................................................... 25 2 SKIN CANCER RISK AND OTHER HEALTH RISK BEHAVIOR: A SCOPING REVIEW .................................................................................................................. 26 Skin Cancer Causes ............................................................................................... 26 Skin Cancer Prevention .......................................................................................... 28 Problem Behavior Theory and Multiple Health Behavior Research ........................ 28 Methods .................................................................................................................. 30 Research Question ........................................................................................... 31 Identification of Relevant Studies ..................................................................... 31 Selection of Studies .......................................................................................... 31 Results .................................................................................................................... 32 Physical Activity and Exercise .......................................................................... 33 Body Mass Index .............................................................................................. 35 Smoking and Tobacco Use .............................................................................. 36 Alcohol Abuse, Binge Drinking and Driving Under the Influence ...................... 37 Fruit and Vegetable Consumption and Unhealthy Weight loss practices ......... 39 Drug Use .......................................................................................................... 39 Mental Health ................................................................................................... 40 5

PAGE 6

Sunscreen ........................................................................................................ 40 Discussion .............................................................................................................. 41 Study Limitations .................................................................................................... 46 3 SKIN CANCER P REVENTION BEHAVIORS AMONG COLLEGE STUDENTS ..... 56 Methods .................................................................................................................. 58 Results .................................................................................................................... 59 Discussion .............................................................................................................. 61 Conclusion .............................................................................................................. 63 4 THE ASSOCIATION OF MULTIPLE HEALTH RISK FACTORS WITH SUNSCREEN USE AMONG COLLEGE STUDENTS ............................................ 68 Background ............................................................................................................. 68 Methods .................................................................................................................. 71 Study Population and Sample .......................................................................... 71 Study Measures ............................................................................................... 73 Analysis ............................................................................................................ 73 Results .................................................................................................................... 74 Discussion .............................................................................................................. 76 5 SUMMARY AND IMPLICATIONS ........................................................................... 85 Summary ................................................................................................................ 85 Implications ............................................................................................................. 87 REFERENCES .............................................................................................................. 89 BIOGRAPHICAL SKETCH .......................................................................................... 104 6

PAGE 7

LIST OF TABLES Table page 2 1 Skin cancer prev ention key findings. .................................................................. 49 3 1 Demographic characteristics of the study sample (n=747). ................................ 65 3 2 Sun protection, sun exposure, and indoor tanning (n=747). ............................... 66 4 1 Demographic characteristics of the study sample (n=747). ................................ 81 4 2 S unscreen prevalence rates by race, gender and age (n=747). ......................... 82 4 3 Bivariate analysis of sunscreen use by health risk behav iors (n=747). .............. 83 4 4 Relationship between inadequate sunscreen use and selected health risk behaviors ............................................................................................................ 84 7

PAGE 8

LIST OF FIGURES Figure page 2 1 The screening process for the scoping review of skin cancer prevention behavioral correlates yielded 36 studies. ............................................................ 48 3 1 Sunscreen use across the college age span ...................................................... 67 8

PAGE 9

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy PREVALENCE AND CORRELATES OF SKIN CANCER RISK BEHAVIORS AMONG COLLEGE STUDENTS By Julie Williams Merten August 2014 Chair: Jamie Pomeranz Major: Public Health Skin cancer is the most common, yet highly preventable, form of cancer in t he United States with melanoma rates steadily increasing. Melanoma rates in the past 40 years have increased 800% in women and 400% in men under the age of 40. Ultraviolet (UV) radiati on from the sun or from indoor tanning machines is directly linked wit h the development of skin cancer. Young adults ages 18 to 29, specifically college students, comprise the most active age group engaging in risky UV exposure. The purpose of this cross sectional study is to extend scientific understanding of skin cancer prevention behaviors and explore the relationship between sunscreen use and the health risk behaviors associated with mortality and morbidity among college students. A convenience sample of 747 college students at a midsized southeastern comprehensive university was surveyed about skin cancer prevention behavior and other health risk behaviors. Data were analyzed using SAS 9.2 and SPSS 19. Results showed that overall skin cancer prevention behaviors were inadequate with only 33% of students sufficiently reporting sunscreen use, 72% of students reporting sunburn in the previous year, 58% reporting more than two hours outside during peak hours (10 – 4pm) in the past year, and nearly 80% have never had a skin cancer check by a 9

PAGE 10

healthcare provider. W hite, f emale, students over the age of 21 were more likely to use sunscreen. Texting while driving, low life satisfaction, and binge drinking predicted inadequate sunscreen use. Findings suggest that despite widespread educational efforts to reduce skin cancer, college students receive large amounts of intentional and unintentional exposure to UV radiation either from the sun or indoor tanning. Further, t he identification of associations between sunscreen use and other highrisk behaviors among college students provide the framework to develop multiple risk factor interventions. Programs aimed at multiple behavioral health risks in other settings including sun protection, have shown great promise for health promotion and reduced healthcare costs. 10

PAGE 11

CHAPTER 1 I NTRODUCTION Sk in cancer is the most common cancer in the United States and is showing an incidence greater than all of the other cancers combined (Buller et al., 2011; Heckman, CohenFilipoc, Darlow, Kloss, Manne, & Munshi , 2014; Mahler, Kulik, Gerrard, & Gibbons, 2006; Nahar, 2013; Watson et al., 2013; Weir et al., 2011). It is estimated that one in five Americans will be diagnosed with skin cancer with national costs an estimated 1.7 billion dollars in treatment and loss of 3.8 billion dollars in lost pr oductivity every year (Watson et al., 2013). Skin Cancer Etiology The three most common types of skin cancer include squamous cell carcinoma, basal cell carcinoma, and melanoma. Squamous and basal cell carcinomas are the most common forms of skin cancer and are often successfully treated when diagnosed early (C enters for D isease C ontrol [CDC] , 2014). However, though not the most common form of skin cancer , melanoma is the most lethal because it spreads quickly when undetected (Ahmedin, Siegel, Xu, & Ward, 2010). In the US, an estimated 3.5 million cases of skin cancer diagnosed annually with basal cell carcinoma making up 2.8 million of those case, squamous accounting for nearly 700,000 and roughly 100,000 cases of melanoma. Most skin cancers are direct ly related to long term Ultra Violet (UV) r adiation exposure from the sun or indoor tanning (Bul ler et al., 2011; Heckman, Darlow, CohenFilipc, Kloss, Manne, Munshi, & Perlis, 2012; Nahar, 2013; Watson et al., 2013). There are three types of UV radiation: Ultra Violet A (UVA), Ultra Violet B (UVB), and Ultra Violet C (UVC). Ultra Violet A radiation reach th e earth’s surface and penetrate the top 11

PAGE 12

layer of skin and is responsible for connective tissue damage and increased skin cancer risk (CDC, 2014). Ult ra Violet B radiation is partially blocked by the ozone layer and does not penetrate human skin as much as UVA however, UVB can cause skin damage. U ltra V iolet C rays are extremely powerful but do not reach the earth’s surface (CDC, 2014). The skin is th e largest body organ and has many functions including covering and protecting internal organs from injury and bacteria, regulating water and fluid loss, body temperature control, the production of Vitamin D, and protection from UVR (American Cancer Society [ACS], 2012). Normally, without UVR exposure, skin cells grow and divide in a regular order in a process known as the cell cycle. However, any mutation or dysfunction in the cell cycle may result in the formation of noncancerous (benign) or cancerous t umor (malignant) (Nahar, 2013). The skin has three layers , which each later is affected differently by UV radiation. The outer layer, known as the epidermis, is where skin cancer typically develops. The outer layer , or epidermis, consists of epidermal c ells including keratinocytes which are also know as basal cells and squamous cells, melanocytes, Langerhans dendrite cells, Merkel cells and infiltrating cells like lymphocytes and neutrophils (Nahar, 2013). The two main types of skin cancer, melanoma and non melanoma (NMSC) including basal and squamous cell carcinomas are named for the cells within the skin they affect (Agbai et al., 2014; Nahar, 2013) . Squamous cells are continually shed as the body produces new cells, the basal cells are continually di viding to replace cells that shed off the surface of the skin. As noted, basal cell carcinomas are the most common types of skin cancer and roughly 80% of skin cancers are basal cell carcinomas (ACS, 2012). Basal cell cancers grow 12

PAGE 13

slowly, rarely spread, and may come back in the same place after treatment. These cancers usually manifest in sunexposed areas. Squamous cell carcinoma make up roughly 20% of cancer diagnosis, appear on sun exposed arrears, grow deeper in the skin and are more likely to spread to other areas of the body (ACS, 2012). The melanocytes within the epidermis produce melanin which produces a tan. The development of a tan is in fact the result of the body producing melanin as a shield to protect the inner levels of the skin from the harmful effects of UVR . Melanoma starts in the melanocytes within the epidermis, and are not necessarily located in areas that are exposed to the sun. For instance, melanomas are often found on the chest and back of men and legs of women (ACS, 2012). M elanoma is more deadly than basal and squamous cell skin cancers and can spread quickly throughout the body. Skin Cancer Risk Factors Exposure to UV R is the single most modifiable risk factor for skin cancers and is mostly preventable by avoiding the sun a nd indoor tanning machines (National Cancer Institute [NCI], 2010). The American Cancer Society (2012) recommend avoiding the sun during the peak hours between 10am to 4pm , seeking shade when outdoors, wearing sun protective clothing including sunglasses and a widebrimmed hat, and frequently applying broadband sunscreen protection with an sun protection factor (SPF) greater than 15. Proper sunscreen use has been linked to a reduction in squamous cell and melanoma development 40% and 50% respectively (Green, Williams & Neale, 1999; Green, Williams, Logan & Strutton, 2011). Skin cancer risk factors include a family history of skin cancer, a history of severe sunburns, a tendency to develop freckles when exposed to UVR, light hair color, immunosuppression, sunbathing and tanning behaviors, and atypical mole genetic 13

PAGE 14

defects (Nahar, 2013; Watson et al., 2013; Weir et al., 2011) . People with a first deg ree relative with skin cancer are 50% more likely to develop skin cancer than people without a family histor y of cancer (NCI, 2010). Those who have a severe sunburn in childhood or adolescence also increase their risk of adulthood skin cancer which is concerning considering nearly 69% of 11 to 18 year olds reported to having a severe sunburn in the past year (D avis, Cokkinides, Weinstock, O’Connell, & Wingo, 2002) . Only 33% of adults reported sunburn in the past year, with the highest majority (58%) of sunburns occurring in those between the ages of 18 to 29 years of age (Buller et al., 2011; Heckman et al., 20 12). Young adults engage in risky sun behaviors and are the most active users of indoor tanning machines. In fact, one third of nonHispanic white women between the ages of 18 to 21 use indoor tanning machines and those who begin tanning before age 30 i ncrease their melanoma risk by 75% (CDC, 2010). The use of a tanning device, such as a tanning bed or sun lamp, before the age of 35, increases melanoma risk by 60% to 80% depending on the length of exposure (Watson et al., 2013). Young females under the age of 40 have a higher melanoma rates than males, specifically, white nonHispanic females (Buller et al., 2011; Heckman et al., 2012; Weir et al., 2011). While females engage in more indoor tanni ng behaviors, males demonstrate poor sun protection behaviors. For example, in a national population study examining 18 to 29 year olds, 37.1% of women reported using sunscreen always or most of the time while only 15.6% of men reported using sunscreen always or most of the time (CDC, 2012). In fact, only 48% of adult men use one or more sun protective behaviors, whereas 68% of adult women use one or more sun protective behavior (NCI, 2010). 14

PAGE 15

There is speculation the differences between gender may be attributed to a greater concern about skin aging among women and use of sunscreen through makeup and facial cream (Abroms, Jorgensen, Southwell, Geller, & Emmons, 2003). In the nonHispanic white population, skin cancers account for 40% of cancer related deaths across the United States. In populations of color, incidence rates are significantly lower: 5% of Hispanics, 4% of Asians, and 2% of blacks (Agbai et al., 2014; Nahar, 2013). White non Hispanics are considerably more likely to devel op skin cancer than other races; however, other ethnic groups suffer from more advanced skin cancer and have lower survival rates (Cockburn, Zadnick, & Deapen, 2006; Gloster & Neal, 2006). For instance, the overall fiveyear melanoma survival rate among AfricanAmericans is 77% in comparison to 91% among white nonHispanics (Ah medin et al., 2010). Further, 52% of AfricanAmerican patients and 26% of Hispanic patients receive late stage melanoma diagnoses compared with 16% latestage diagnoses among white nonHispanic patients ( Hu, SozaVento, Parker, & Kirsner, 2006). However, perceived risk for skin cancer is low among minorities, so subsequently protection strategies such as sunscreen use among minorities are very low, even among minorities that report frequent sunburn (Briley , Lynfield, & Chavda, 2007; McMichael & Jackson, 2000; Kim, Boone, West, Rademaker, Liu, & Kundu, 2009). For example, 21.7% of AfricanAmerican adolescents reported sunburn after one hour of sun exposure (Davis et al., 2002) yet AfricanAmericans are seven times less likely that whites to use sunscreen ( Hall & Rogers, 1999; Briley et al., 2007). Furthermore, among college students, there is an increase in sunscreen use among students with paler, more sunburn prone skin (Cottrell , McClamroch, & Bernard, 2005) . Although darker complexions have less skin 15

PAGE 16

cancer risk due to higher amounts of melanin, a natural sun protection, skin color alone is not the only individual risk factor that should be considered. Nonwhite ethnicities may have other skin cancer risk factors including skin that burns or freckles or a family history of skin cancer ( W orld H ealth O rganization [WHO] , 1995; Jemal, Devesa, Fears, & Hartge, 2000). College Students and UVR Melanoma is the most common form of cancer for people aged 25 to 29 years old and the second most common cancer for t hose aged 15 to 24 (Bleyer, O’Leary, Barr, & Ries, 2006). Unfortunately, there has been a trend in increasing melanoma rates for this population. In fact, over the past 40 years, melanoma rates among those under the age of 40 have increased 800% in women and 400% in men (Reed, Brewer, Lohse, Bringe, Pruit, & Gibson, 2012). This increase is not unexpected given young adults ages 18 to 29 comprise the most active age group engaging in risky UV exposure (Choi, Lazovich, Southwell, Forster, Rolnick, & Jackso n, 2010). Childhood, adolescent and young adult UV exposure is damaging because it accumulates toward later skin cancer risk (Parkin, Mesher, & Sasieni, 2011). Although this group is spending significant time in the sun, only about 5% of college student s properly use sunscre en (Spradlin, Bass, Hyman, & Keathley, 2010). Further evidence of poor sun protection behaviors was illustrated in a national telephone survey of young adults with 72% reported having at least one prior summer sunburn, 30% reported at least three sunburns and 12% reported more than five sunburns (Davis et al. , 2002). Sun protection attitudes, beliefs, knowledge, motivations and behaviors among college students have been extensively studied, though, there is limited research 16

PAGE 17

exploring other health risk behaviors associated with sunscreen use among college students. Limited investigation has found inconsistent associations between risky sun exposure, primarily indoor tanning, and behavioral risk factors such smoking, substance abuse, diet and physical activity in adolescents and adults (O’Riordan, Field, Geller, 2006; H all, Everett & Saraiya, 2001; Coups, Manne, & Heckman 2008). A study of slightly younger population of high school students, found associations between poor sunscreen use and drinking and driving, smoking, risky sexual activity, and inadequate physical activity (Hall et al., 2001). This study has implications for the college age population because, as adolescents age, they are less likely to use sun protection and clust ered risk behaviors increase (Eaton et al., 2012). Problem Behavior Theory and Multiple Health Behavior Risk Research Problem Behavior Theory provides a theoretical framework for multiple health behavior research. Problem Behavior Theory (PBT) is a social psychological framework specific to adolescents and young adults that use the interaction between three major systems to explain risk behavior: personality, environment, and behavior (Jessor, 1991; Jessor, Donovan, & Costa, 1991). First, the personality s ystem includes individual beliefs, values and attitudes related to social and psychological development such as self esteem, self efficacy and perceived vulnerability. Then, the environmental system includes peer and parental influence to create social norms including influence, control, modeling, expectations and support. Finally, the behavioral system is built on the idea that people who engage in risky behavior are also going to engage in less health prevention, and this system includes actions such as smoking, sunscreen application, drug and alcohol use. 17

PAGE 18

PBT asserts that the three major systems are interrelated and to provide a social context to explain problem behavior. The theory suggests that the social life of young people presents constant opport unities to learn new behaviors and then social expectations reinforce them (DuRant, Smith, Kreister, & Krowchuk, 1999). Further, the risk and problem behaviors cluster because they become part of an individual’s internal validation system similar to affir mation from parents or acceptance from peers (DuRant et al., 1999). PBT posits that many problem healthcompromising behaviors such as alcohol use, marijuana use, unprotected sexual interco urse, driving after drinking cluster because they are influenced by social norms because they are the result of underlying individual factors which tie in neatly with many health behavior theories with similar foundation constructs such a self efficacy, attitudes, social norms, etc. Jessor (1991) further asserted that h ealth risk behavior can develop into “risk behavior syndrome” as a result of the underlying latent variables and individuals who develop health risk behaviors as young adults will continue to develop more health risk behaviors throughout their life. Multip le health behavior risk research based in Problem Behavior Theory is showing great promise to improve public health in a cost effective manner by providing a framework to address many clustered health risk behaviors within a single intervention (Prochaska, 2008). In fact, the National Institutes of Health and the Robert Wood Johnson Foundation have allocated special funding to study multiple health behavior change for disease prevention and management. One study funded by this initiative found significant effects when examining multiple risky behaviors among ninth graders. The authors targeted smoking, diet and sun exposure by employing a homebased 18

PAGE 19

technological intervention with parents of high school students (Prochaska et al., 2004). Also, a similar m ultiple health behavior intervention aimed at lowering cancer risk in the primary care setting focused on smoking, diet, skin cancer and mammography resulted in significant positive outcomes (Prochaska, Velicer, Redding, Rossi, Goldstein, & DePue, 2005). Changing multiple health behaviors offers the opportunity to offer more significant quality of life outcomes, reduce healthcare utilization, and save money by using a bundled healthcare approach. This is becoming more essential given, the likelihood of having multiple health risk factors increases with age (Driskell, Dyment, Mauriello, Castle, & Sherman, 2008). Furthermore, targeting several risk behaviors aligns with the Affordable Care Act’s emphasis on efficient preventative care “bundled” in a clinical setting (Whitlock, Orleans, Pender & Allan, 2002; Ickovics, 2008). Leading Causes of Morbidity and Mortality Among College Students Healthy Campus 2020 is based on the US Surgeon General’s Healthy People 2020 framework and identifies health improvement priorities specific to college students (U.S. Department of Health and Human Services, 2011 ; American College Health Association [ACHA] , 2012). Healthy Campus provides a roadmap for researchers to efficiently study college health risks by categorizing the health indicators that represent the most pressing issues facing college students. As noted, the developmental ages between high school and college are significant in the development of health behaviors that will have a long lasting effect into adulthood. This is, in fact, an excellent time to intervene with young people to establish and maintain healthy behaviors (Cullen, Koehly, & Anderson, 1999; Baronowski , Cullen, & BassenEnguist, 1997). The leading causes of morbidity and mortality among the coll ege community include inadequate 19

PAGE 20

physical activity, smoking, substance abuse, highrisk sexual behavior, and unintentional injury. Additionally, the America College Health Association (2012) recommends the consideration of mental health given there is considerable research showing underlying mental health issues associated with risky health behavior among college students. Additionally, attending college itself is recognized as a period of high levels of perceived stress with negative mental health outcom es (N ational A lliance on M ental I llness [NAMI] , 2012; National Institute on Mental Health [NIMH] , 2005; Substance Abuse and Mental Health Services Administration [SAMHSA], 2010b). Physical Activity Regular physical exercise is associated with reductions in overweight and obesity high blood pressure, diabetes, heart attack, stroke, cancer, arthritis, and symptoms of depression and anxiety (Shaw, Gennat, O’Rourke, & Del Mar, 2006; Powell, 1998; Brown, 1991 ; Crews & Landers, 1987; Pertruzello, Landers, Hatfi eld, Kubitz, & Salazar, 1991; Coyle, 2009). The CDC recommends 150 minutes of moderate aerobic activity each week and muscle strengthening activities at least two days per week. However, half of college students do not meet the minimum guidelines for weekly physical activity (Douglas et al., 1997). In fact, there has been a steady decline in physical activity among college students over the past ten years (ACHA, 2006; ACHA, 2008; Sacheck, Kuder, & Economos, 2010). Smoking Smoking is the leading preventable cause of death and disease (CDC, 2004) and is responsible for 90% of lung cancers and more than 80% of Chronic Obstructive Pulmonary Disease (COPD) deaths in the US (U . S . Cancer Statistics Working Group, 2006). While smoking rates have dropped nationally, the rate of smoking is highest 20

PAGE 21

among young adults ages 18– 25 with approximately 22% of college students using cigarettes. (Ro ck et al. , 2007; SAMSHA, 2010 a ). Substance Abuse Motor vehicle crashes, assault, sexual abuse and academic problems are associated with alcohol use among college students (Hingson, Zha, & Weitzman, 2009). Unfortunately, alcohol consumption among college students is pervasive with roughly 80% reporting drinking alcohol with more than half participating in binge drinking (N ational I nstitute on A lcohol A buse and A lcoholism [NIAAA] , 2013). Binge drinking is classified as consuming more than four drinks in a twohour period for women, and more than five drinks in a twohour period. Binge drinking spikes blood alcohol concentration (BAC) levels that increase risk of mental impairment leading to poor judgment and long term organ damage (NIAAA, 2013). College students aged 18 to 24 are more likely to binge drink than their noncollege enrolled peers (SAMHSA, 2010a ). Substance abuse also encompasses illicit drug use including marijuana, cocaine, amphetamines, and prescription drug abuse. Marijuana use has been increasing among college students with approximately 25% of students using in the past year (Bell, Wechsler, & Johnston, 1997) . In fact, marijuana is the most commonly used illegal drug among college students and is frequently used with tobacco, other illicit drugs, and alcohol (N ational I nstitute on D rug A buse [NIDA] , 2011). Furthermore, habitual marijuana use can lead to ment al health issues, affect work and academic performance, cause respiratory problems, and lead to long term addiction (NIDA, 2011). In addition to marijuana, cocaine has been shown to be a problem among college students. Cocaine is highly addictive, affec ts brain function, and can lead to a host of physiological, emotional, and mental problems (NIDA, 2011). Unfortunately, despite the 21

PAGE 22

grim results, routine cocaine use among the young adult population is fairl y steady at around 1.5% (Arria et al., 2008). I n fact, the majority of cocaine initiates happened over the age of 18 with the average age of first use at 20 years old. Alarmingly, 12.5% of college students have tried cocaine while with prevalence rates higher among male students (Arria et al., 2008). Amphetamine, a common drug abused by college students, increases blood pressure and is especially risky for anyone with a preexisting heart condition and can lead to long term cardiovascular damage (NIDA, 2011). Alas, amphetamine use is experiencing a rise in popularity among college students who favor the stimulant effect to aid enhance study focus and improve party longevity (McCabe, Knight, Teter, & Wechsler, 2005). Usage rates among college students are around 6.9% nationally with some evidence th at the rate is higher at more academically competitive schools (McCabe et al., 2005). Finally, prescription drug use without a doctor’s prescription is another growing trend in on college campuses and is now second to marijuana as a commonly abused drug. In 2012, usage rates among 18 to 25 year olds were around 26% for lifetime use, 14% during the past year, and 5% during the last month (NIDA, 2013). Some of the more frequently used prescription drugs include stimulants, sedatives, and opioid analgesics (NIDA, 2011) and long term prescription drug use without a doctor’s supervision can lead to dependence, respiratory problems, organ complications, and death (SAMSHA, 2010a ) . Sexual Behavior Unintended pregnancies and sexually transmitted diseases (STD) rates remain high among young adults indicating a lack of sexual responsibility. High risk sexual behavior is any sexual behavior that increases negative consequences loosely 22

PAGE 23

categorized as “indiscriminate behaviors” such as having multiple sexual partners or not using protection against pregnancy and STDs (Patrick, Covin, Fulop, Calfas, & Lovato, 1997). In fact, more than half of the currently diagnosed STDs are among young people ages 15 to 24 (U.S. Department of Health and Human Services, 2011) with STD diagnoses rates ranging between 12 % to 25% among sexually active college students (Patrick et al., 1997; Reinsch, Hill, Sanders, & Davis, 1995). Further, more than 15% of female college students report having an unintended pregnancy (Douglas et al., 1997) and 31% of college men report that a female partner has taken the morning after pill (Merten & Bosco, 2013). Unintentional Injury More than 1,800 college students die annually from alcohol related injuries and nearly 600,000 students suffer from al cohol related injuries (Hingson et al., 2009). Drinking and driving rates among college students remain unacceptably high around 35.5%, and 25% of students report riding with someone they consider impaired (SAMSHA, 2010 a ). This behavior is not only a health r isk for the driver and passenger but the general population. Another concern for college unintentional injury is seatbelt use. Seatbelt use reduces the risk of death and serious injury when in a motor vehicle accident. Seatbelt use hovers around 50% among college students (Clayton & Myers, 2009) yet more than half of the people killed in automobile accidents were not wearing their seat belts ( U.S. Department of Transportation, 2010). Finally, while many states have banned texting while operating a motor vehicle, a recent study found that 80% of college students text while driving (Lantz & Loeb, 2013). As a result, more than 1000 people are injured in distracted driving accident s every day in the US (CDC, 2011). 23

PAGE 24

Mental Health Mental health issues are particularly important for college students because it is believed that the majority of mental health issues will manifest by age 24 (N IMH, 2012 ). In fact, depression and anxiety are the most commonly reported mental health issues am ong college students (AC HA, 2008). Further, more than 10% have been clinically diagnosed with depression and more than 11% have been clinically diagnosed with anxiety. Consequently, depression and anxiety are significant predictors of college dropout and suicide (NAMI, 2012). Life satisfaction is a cognitive evaluation of subjective wellbeing (Strine, Chapman, Balluz, Moriarty, & Mokdad, 2008). Life satisfaction is associated with improved grades, social support, and health behavior among college students (Renshaw & Cohen, 201 4). Significance Skin cancer is highly preventable, however, sun safe practices rates remain low among college students. This study would be the first to examine sunscreen use and other correlated health risk behaviors among college students through a co mprehensive health behavior data instrument. The study will yield results that will help identify other health risk behaviors that are associated with poor sunscreen use , thus, leading to a targeted intervention addressing a host of related behaviors detr imental to the health and well being of college students. The findings have long term implications to improve existing sun protection education programs that have been minimally effective at improving sunscreen adherence rates by aiming resources at the i ndividuals at most risk. Specifically, the U . S . Community Preventive Services Taskforce (2013) has noted there are insufficient skin cancer prevention programs designed for a college audience and it is a significant area of need . The early identification of clustered health risk 24

PAGE 25

behaviors offers public health professionals the opportunity to focus resources and programs on specific individuals at greater risk for a host of health behaviors, rather than a general audience. This will lead to more precise, c ost effective interventions with better quality of life outcomes. Research Aims The overall goal of this study is to explore the prevalence and correlates of sunscreen use with other risky behaviors among college students. The following aims will be inv estigated: Aim 1: Investigate prevalence of sunscreen use and other skin cancer prevention behaviors among college students. Aim 2: Explore the association between sunscreen use and the health risk factors responsible for the majority of mortality and morbidity among college students including physical activity, smoking, substance abuse, risky sexual activity, and unintentional injury. Aim 3 : Explore the association between sunscreen use and mental health indicators. Aim 4: Determine the predictive relationship between select variables with sunscreen use among college students. 25

PAGE 26

CHAPTER 2 SKIN CANCER RISK AND OTHER HEALTH RISK BEHAVIOR: A SCOPING REVIEW Skin cancer is the most common form of cancer in the United States (US), with more than 3.5 million cases of basal and squamous cell skin cancer diagnosed in the U.S. every year (ACS, 2012) . Melanoma, the deadliest skin cancer, will account for more than 76,000 cases of skin cancer in 2014. Furthermore, one out of every five people in the United States will develop skin cancer during their lifetime (Robinson, 2005). The economic consequence of this cancer has resulted in a direct annual treatment cost of more than four billion dollars (NCI, 2010). The three most common types of skin cancer include squamous cell carcinoma, basal cell carcinoma, and melanoma. Nonmelanoma skin cancers (NMSC) , including squamous and basal cell carcinomas , are the most common forms of skin cancer and are rarely fatal (CDC, 2014). However, though not the most common form, mel anoma is the most lethal (Ahmedin et al., 2010). An estimated 12,190 deaths (9,180 from melanoma and 3,010 from other non epithelial skin cancers) occurred in 2012 in the U.S. (ACS, 2012). Skin Cancer Causes Ultraviolet (UV) radiation from the sun or indoor tanning machines has been d irectly linked with the development of skin cancer and has been declared a carcinogen by the US Department of Health and Human Services (Diepgen & Mahler, 2002; I nternational A gency for R esearch on C ancer W orking Group [IA RCWG] , 2007. Exposure to UV light is the single most modifiable risk factor for skin cancers and is mostly preventable by avoiding the sun and indoor tanning machines (NCI, 2010). The American Cancer Society (2012) recommends avoiding the sun during peak hours (10am – 4pm), seeking shade when outdoors, wearing sun protective clothing , including 26

PAGE 27

sunglasses and a widebrimmed hat, and frequently applying broadband sunscreen (SPF>15) with both UVA and UVB protection. There is evidence to support the rel ationship between i nadequate sun protection and cancer because melanoma is now the most common form of cancer for people aged 25 to 29 years old (Bleyer et al., 2006). Unfortunately, melanoma rates are increasing for this population. In fact, over the past 40 years, melanoma rates among those under the age of 40 have increased 800% in women and 400% in men (Reed et al. , 2012). This is not surprising given young adults ages 18 to 29 comprise the most active age group engaging in risky UV exposure (Choi et al. , 2010). Childhood, adolescent and young adult UV exposure is damaging because it accumulates toward later skin cancer risk (Parkin et al., 2011). Furthermore, young adults, specifically college students, obtain a majority of their lifetime UV radiation exposure before and during this time of life (Greene, Campo, & Banerjee, 2010). Although this group is spending significant time in the sun, only about 5% of college students properly use sunscreen (Spradlin et al., 2010). Further evidence of poor s un protection behaviors was illustrated in a national telephone survey of young adults which revealed that 72% reported having had at least one summer sunburn, 30% reported at least three sunburns and 12% reported more than five sunburns (Davis et al., 200 2). Sunburns are the short term effect of excessive UV exposure. F actors associated with increased odds of sunburn include greater sun sensitivity, lighter skin tones, younger ages, hours spent outdoors, sunbathing and desirability of a tan (Davis et al. , 2002). Indoor tanning is another avenue for UV exposure, with an estimated 40% to 60% of college students having used indoor tanning machines (Hillhouse, Stapleton, & 27

PAGE 28

Turrisi, 2005). Indoor tanning, also referred to as sunlamps, tanning booths/beds and artificial tanning, has been positively associated with skin cancer (Whitmore, Morison, Potten, & Chadwick, 2001; Karagas, 2002). Skin Cancer Prevention According to Healthy People 2020, the US Department of Health and Human Service’s framework for national health, skin cancer has been recognized as a pressing national public health issue. As a result, a set of objectives have been developed for adolescents and adults to reduce highrisk behaviors. The 2020 objectives for adolescents include: 1. Reduce sunburn and indoor tanning use by 10% among ninth to 12th grade students; 2. Increase proportion of ninth to 12th grade students that use sun protection by 10% (from 9.3% to 11%). The objectives for adults over the age of 18 are similar and include: 1. Reduce sunburn rates by 10% from 37.5% adults reporting one sunburn in the past year to 33.8%; and reduce melanoma deaths by 10% to 2.4 per 100,000 (currently at 2.7 per 100,000); 2. Increase the proportion of people who use at least one sun protection strategy to 73.7% of the US adult population (currently at 67%) and reduce indoor tanning rates by 10% from 5.6% to 3.6% (U . S . Department of Health and Human Services, 2011). As evidenced by the Healthy People 2020 objectives, national skin cancer rates are at unacceptably high levels and are continuing to increase, particularly among young adults. Existing skin cancer prevention programs have fallen short, and public health professional s should consider other approaches to reduce risky UV exposure. Problem Behavior Theory and Multiple Health Behavior Research Problem Behavior Theory (PBT), a social psychological framework specific to adolescents and young adults, offers a theoretical foundation that uses the interaction 28

PAGE 29

between three major systems to explain risk behavior: personality, environment, and behavior (Jessor et al. , 1991). PBT asserts that the three major systems are interrelated and provide a social context to describe problem behavior. The theory posits that the social life of young people pres ent s constant opportunities to learn new behaviors and then social expectations reinforce those learned behaviors (DuRant et al., 1999). Additionally, the risk and problem behaviors cluster because they become part of an individual’s internal validation s ystem , similar to affirmation from parents or acceptance from peers (DuRant et al., 1999). Jessor (1991) further asserted that health risk behavior can develop into “risk behavior syndrome” as a result of the underlying latent variables , and individuals w ho develop health risk behaviors as young adults will continue to develop more health risk behaviors throughout their lives . Multiple health behavior risk research based in Problem Behavior Theory is showing great promise to improve public health in a cost effective manner by providing a framework to address many clustered health risk behaviors within a single intervention (Prochaska, 2008). In fact, the National Institutes of Health and the Robert Wood Johnson Foundation have allocated special funding to study multiple health behavior change for disease prevention and management. One study funded by this initiative found significant improvement when intervening on multiple risky behaviors among ninth graders. The intervention targeted smoking, diet , and sun exposure by employing a homebased technological intervention with parents of high school students (Prochaska, Velicer, Rossi, Redding, Greene, & Rossi, 2004). Also, a similar multiple health behavior intervention aimed at lowering cancer risk in the primary care setting focused 29

PAGE 30

on smoking, diet, skin cancer and mammography resulted in significant positive outcomes (Prochaska et al., 2005). Changing multiple health behaviors offers the opportunity to improve quality of life outcomes, reduce healthcare utilization, and save resources by using a bundled healthcare approach. This is becoming more essential given the likelihood that having multiple health risk factors increases with age (Driskell et al., 2008). Furthermore, targeting several risk behaviors aligns with the Affordable Care Act’s emphasis on efficient preventative care “bundled” in a clinical setting (Whitlock et al., 2002; Ickovics, 2008). Research has shown that prevalence of health risk behaviors increases with age. One study found that only 8.3% of adolescents aged 12 to 13 engage in multiple health risk behaviors, while nearly 33% of 14 to 17 year olds and more than half of college student engage in multiple health risk behaviors , showing a clear increase in clustered risk behavior (Br ener & Collins, 1998). The purpose of this article is to present the results of a scoping review of studies that have examined skin cancer prevention and other correlated health risk behaviors. Methods This investigator conducted a scoping review of skin c ancer risk behaviors and other correlated health risk behaviors. A scoping review methodology was selected to examine the amount of existing research rather than a systematic review that includes a formal quality assessment (Levac, Colquhoum, & O’Brien, 2010). Scoping reviews require five key steps: (i) a clear research question; (ii) identification of relevant studies; (iii) selection of studies; (iv) creation of a data chart; (v) organization and reporting of the results (Arksey & O’Malley, 2005) 30

PAGE 31

Research Q uestion This scoping review aimed to answer the following research question: (1) What health risk behaviors are correlated with skin cancer risk behaviors? Identification of Relevant S tudies This researcher searched online databases in PubMed, PsychI NFO, and Science Direct. Search terms included “sunscreen”, “sun protection”, “tanning”, “sun safety”, “skin cancer prevention”, “skin cancer”, “college student”, “young adult”, “health risk behaviors”, “multiple health risk behaviors”, and “correlates”. To yield additional results, specific health risk behaviors salient to college students , including “alcohol”, “sexual behavior”, “smoking”, “texting”, “physical activity”, “exercise”, “drugs”, “substance abuse” and “mental health” were searched individual ly with a combination of the previously noted key words. Titles and abstracts were reviewed for relevance, and then pertinent articles were categorized by sun category (skin cancer risk, sun protection, sun exposure, or indoor tanning) and health risk dom ain. Reference lists of the relevant articles were cross referenced, and related sources were examined for inclusion. Selection of S tudies Final articles for inclusion were selected bas ed on scoping review guidelines; inclusion and exclusion criteria may be based on pertinence rather than study rigor (Levac et al., 2010). To be included, studies must have met the following criteria: (i) addressed some form of skin cancer risk , including sunscreen use, sun protection, sun exposure or indoor tanning; and (ii) involved correlations with other health risk behaviors. Articles examining attitudinal, cognitive and other latent constructs were excluded. Th e researcher scored the article’s relevance to the research question. Fifty five studies were identified for in depth consideration. Systematic review articles (n=4) 31

PAGE 32

that included broader tanning correlates or skin cancer interventions but did not specifically address skin cancer prevention and other correlated health risk behaviors were included in the first screen. Their reference lists were reviewed and then crosschecked with the other articles meeting inclusion criteria, and prospective publications were pulled for consideration (n=3). After further examination, thirty seven articles were deemed to address some form of skin cancer risk behavior and other behavioral correlates. Only studies written in English and published in peer reviewed publications between 1994 and 2014 were considered. Figure 2 1 notes the article screening process. Results The sear ch and screening process yielded 37 peer reviewed articles examining skin cancer risk and other behavioral correlates. Author information, year of publication, country, study design, participants, sample size, skin cancer risk behavior, and significant findings are documented in Table 1. The studies were primarily quantitative using mostly crosssectional approaches with some case control designs. There was a wide range of number of participants in the studies , ranging from 168 individuals to more than 1 02,000 participants. Ages ranged from nine to 93 years old, with the majority of studies examining adults over the age of 18 (n=26), adolescents (n=10), college students (n=6) and combined adolescents and adults (n=3). A majority of the 36 studies that met inclusion criteria were conducted in the USA (n=26). The remaining studies came from Denmark (n=3), Australia (n=2), and Canada (n=2), Sweden (n=1), the United Kingdom (n=1), Norway (n=1), and France (n=1). The majority of articles included both genders with a greater proportion of female participants and two studies focused exclusively on men. Most of the studies 32

PAGE 33

addressed skin cancer risk including nonmelanoma skin cancer (NMSC) and melanoma (n=8), indoor tanning (n=8), and both indoor and outdoor tanning (n=8), and sunburn (n=6). The other studies covered sunscreen use (n=5), overall sun protection (n=4), and tanning dependence (n=1). Many of the articles addressed multiple correlates of skin cancer prevention behaviors including: physical activ ity (n=15), body mass index (BMI) (n=13), smoking (n=13), alcohol abuse (n=12), fruit and vegetable consumption (n=6), drug use (n=5), sunscreen use – as a correlate of indoor tanning (n=4), depression (n=3), unhealthy weight loss (n=3), seatbelt use (n=2) , suicide (n=1), steroid use (n=1), obsessive compulsive disorder (n=1), drinking and driving (n=1), riding with someone who has been drinking (n=1), sexual risk taking (n=1), and indoor tanning – as a correlate of sunscreen use (n=1). Although the findings are mixed and warrant further investigation, current research suggests there is an association between skin cancer prevention behaviors and other health risk behaviors. However, the scoping review revealed that existing studies on skin cancer prevention behaviors and other r elated health risk behaviors are limited. Specifically, it is notable that the college population has not been studied beyond indoor tanning and tanning dependence. Physical Activity and Exercise The relationship between sunburn, n onmelanoma skin cancer (NMSC), melanoma, sunscreen use, tanning, and physical activity was broadly studied with mixed findings. Sunburn is a useful metric to gauge skin cancer prevention because sunburn indicates UV overexposure with poor protection and is associated with increased melanoma risk. In fact, those with more than five lifetime sunburns double their chance of melanoma ( Pfahlberg, Kolmel, & Gefeller, 2001). Three large scale 33

PAGE 34

cross sectional studies (Holman, Berkowitz, Zahava, Guy, Hartman, & Perna, 2014; Hall, Saraiya, Thompson, Hartman, Glanz, & Rimer, 2003; Coups et al. , 2008) revealed that increased levels of physical activity among adults were associated with higher levels of sunburn than those who did not exercise. In Australia, Jardine et al. (2012) found that adults that engaged in more than seven hours per week of exercise were significantly more likely to report sunburn while adults who exercised were more likely to use sunscreen than their sedentary counterparts (Lawler, Sugiyama, & Owen, 2007) . Additionally, adults between the ages of 18 to 29 and 40 to 49 who engaged in more exercise were more likely to tan indoors ( Heckman, Coups, & Manne, 2011). Findings were more complex among adolescents , with lower sunscreen use among sedent ary adolescents when compared to their physically active peers (Hall et al., 2001). Additionally, physically active girls were less likely to tan indoors than girls that did not exercise (Demko, Borawski, Debanne, Cooper & Stange, 2003) yet high school males that played sports were more likely to tan indoors (Miyamoto, Berkowitz, Jones, & Saraiya, 2012). Studies examining the relationship between physical activity and skin cancer risk revealed provocative findings. Significantly greater NMSC risk w as apparent in physically active men and those who worked outdoors yet not among women (Schnohr, Gronbaek, Petersen, Hein, & Sorensen, 2005; Lee, MacArthur, Gallagher, & Elwood, 2009; Parent, Rosseau, El Zein, Benoit, & Siemiatycki, 2011). Interestingly, in adults with a previous history of skin cancer, physical activity rates were higher , yet those with skin cancer had lower sun exposure rates than those with no history of skin cancer (Falk & Anderson, 2013). Higher levels of exercise ( more than five day s per week) 34

PAGE 35

worked as a protective factor in a case control examination of melanoma patients with higher levels of exercise (Shors, Solomon, McTiernan, & White, 2001). Although these studies did not directly examine coexisting health behaviors, they warrant inclusion because they strengthen the case for additional long term follow up studies of the relationship between exercise and skin cancer. However, it will be difficult to establish causality given the lapse of time between UV exposure and the long te rm outcome of developing skin cancer. Body Mass Index As with physical activity, the relationship between Body Mass Index (BMI) and skin cancer prevention behaviors is complicated but bears compelling findings. Although unhealthy BMI is not a health behavior, rather the result of poor health behaviors, there is strong evidence to suggest a relationship between obesity and a multitude of chronic diseases , including high blood pressure, high cholesterol, diabetes, heart disease, stroke, and some cancers (Must, Spadano, Coakley, Field, Colditz, & Dietz, 1999). Specific to skin cancer risk, a higher BMI was not positively associated with melanoma and was inversely associated with NMSC (Tang et al., 2013; Pothiawala, Qureshi, Li, & Han, 2012). Given that NMSC is associated with cumulative sun exposure rather than sunburn, the findings suggest less cumulative exposure among overweig ht and obese participants (Tang et al ., 2013). However, Shors, Solomon, McTiernan, and White (2001) found an increased risk o f melanoma in overweight men, but not the same effects for overweight women when compared to people of normal weight yet Kirkpatrick, White, and Lee (1994) found a great melanoma incidence among overweight women than overweight men. Among farmers in Iowa and North Carolina, a higher BMI was associated with more melanoma risk (Dennis, Lowe, 35

PAGE 36

Lynch, & Alavanja, 2008) and among operating engineers, a higher BMI was associated with more sunburn (Duffy, Choi, Hollern, & Ronis, 2012). In a largescale national ret rospective study, Holman, Berkowitz, Guy, Hartman, and Perna (2014) found overweight and obese participants were more likely to sunburn that those of normal weight. Furthermore, among high school students, sunscreen use was better among normal weight s tudents than overweight students (H all et al . , 2001). The dynamics of BMI and indoor tanning are far more complex because of the underlying appearance motivations and intentionality of indoor tanning. Heckman, Egleston, Wilson, and Ingersoll (2008) coined the term “tanning dependence” to describe the addictive nature of indoor and outdoor tanning and found that obese adults were less likely to be tanning dependent than their healthy and overweight peers. One study found adolescents with low BMI wer e more likely to indoor tan, (Demko et al . , 2003) while another study found that underweight and normal weight girls were more likely to tan outdoors when compared with their overweight and obese peers (Yoo & Kim, 2012). However, there were curious age dif ferences in the 2005 US National Health Interview Survey that found normal weight people between the ages of 30 and 39 tanned indoors more than their overweight and obese peers, yet these findings were not apparent in any other age groups; 18 to 29, 40 to 49, or over age 50 (Heckman et al ., 2011 ). Smoking and Tobacco Use Among several years of a largescale national cross sectional study, adult smokers were far less likely than nonsmokers to use sunscreen (Santmyire, Feldman, & Fleischer, 2001; Coups et al . , 2008) and more likely to sunburn (Saraiya, Hall, & Uhler, 2002) . Similar eff ects were found internationally: Swedish adult smokers engaged in 36

PAGE 37

sunbathing more often than nonsmokers (Falk & Anderson, 2013); women smokers in the United Kingdom were less likely to use sunscreen ( Allgwer, Wardle, & Steptoe, 2001); and French adult indoor tanners were more likely to be smokers (Ezzedine et al., 2008). Among adolescents, those who smoke were more likely to tan indoors (O’Riordan et al. , 2006; Lazovich et a l. , 2004; Boldeman, Jansson, Nilsson & Ullen, 1997), sunbathe (Wichstrm, 1994), not use sunscreen, or engage in any sun protection (Coogan, Geller, Adams, Benjes, & Koh, 2001; Hall et al . , 2001). Heckman et al. (2008) found current smokers to exhibit mor e signs of tanning dependence than nonsmokers. Indoor tanners between the ages of 18 and 65 (Heckman et al . , 2011) and college women (Mosher & Danoff Burg, 2010b) were more likely to smoke than those who had never tanned indoors. Alcohol Abuse, Binge Dr inking and Driving Under the Influence Alcohol use and abuse across the lifespan is positively correlated with high risk UV exposure. Among adolescents in Connecticut, those who did not use sun protection were mor e likely to use alcohol (Coogan et al . , 2001), and high school students that reported never using sunscreen were more likely to consume alcohol (Hall et al . , 2001). In addition, Hall et al . (2001) found that high school students that did not use sunscreen were also more likely to drink and dri ve as well as ride with someone who had consumed alcohol. In a US study of more than 28,000 adults, men who consumed more than 15 drinks a week, and women who consumed more than 8 drinks a week used less sun protection than those considered low risk drink ers (Coups et al., 2008). Studies on sunburn and alcohol use showed increased sunburn rates among those with higher alcohol consumption (Holman et al., 2014; Saraiya et al., 2002) and adults classified as “problem drinkers” (Duffy et al., 2012). Alcohol consumption was 37

PAGE 38

also a variable when comparing individuals with a previous history of skin cancer. Those who reported significantly higher levels of alcohol consumption were more likely to have skin cancer (Falk & Anderson, 2013). Indoor tanning b ehaviors across the lifespan also showed a pattern associated with alcohol consumption and abuse among minors ( Coogan et al., 2001; Miyamoto et al., 2011; O’Riordan et al., 2006; Demko et al., 2003), binge drinking among college students (Mosher & Danoff B urg, 2010a; Poorsattar & Hornung, 2007; Bagdasarov, Banerjee, Greene, & Campo, 2008), and problem drinking among adults (Heckman et al. , 2011). Among 12 to 18 year old females, those who had used an indoor tanning device more than ten times were more likely to consume alcohol (O’Riordan et al., 2006). Demko et al . (2003) found that white adolescents between the ages of 13 to 19 that used alcohol were also more likely to visit a tanning bed more than three times (visiting a tanning bed less than three times is considered experimental usage). Patterns were consistent among college age indoor tanners with those reporting indoor tanning also reporting higher alcohol use (Mosher & Danoff Burg, 2010a) and strong associations between college women, indoor tanning , and binge drinking behavior (Mosher & Danoff Burg , 2010 a ; Poorsatter & Hornung , 2007). Past tanning bed experience was also found to be associated with binge drinking, yet les s sun risk behavior (Bagdasarov et al., 2008). And the behaviors were consis tent among US adults between the ages of 18 to 65 with a higher prevalence of indoor tanning among those who engaged in high levels of alcohol use (men who consumed more than 15 drinks a week, and women who consumed more than 8 drinks a week) ( Heckman et a l. , 2011). 38

PAGE 39

Fruit and Vegetable Consumption and Unhealthy Weight loss practices Fruit and vegetable consumption was low among most respondents in all of the studies given the Dietary Guidelines for Americans set by the Department of Agriculture who recommended a minimum of five servings of fruits and vegetables per day as part of a balanced diet ( U.S. Department of Agriculture, 2010). Few studies included fruit and vegetable consumption so unhealthy weight loss practices are included in this section given the paucity of research. Among male high school students, indoor tanning was associated with unhealthy weight control practices such as fad dieting yet the same students were more likely to eat five or more fruits and vegetables per day than those who did not tan indoors (Miyamoto et al., 2012). The association between indoor tanning and unhealthy weight loss methods (laxative use or vomiting) and dieting was also found among adolescent girls (O’Riordan et al., 2006; Demk o et al., 2003). Girls who did not use sun protection were more likely to be on a diet (Coogan et al., 2001). Among adults, inadequate daily fruit and vegetable consumption was associated with indoor tanning in the previous year (Heckman et al., 2011) and better fruit consumption was as sociated with better sunscreen use (Duffy et al., 2012). Drug Use Few studies examined illicit drug use in relation to risky sun behavior. The only study to examine sun protection and drug use found that white adolescents that did not use sun protectio n were more likely to use marijuana than their peers that used some form of sun protection (Coogan et al., 2001). Adolescent females that frequently used tanning beds were also more lik ely to use marijuana (O’Riordan et al., 2006 ; Demko et al., 2003). Fi nally, college students who met indoor tanning addiction metrics were also more likely to use marijuana (Mosher & Danoff Burg, 2010b). 39

PAGE 40

Mental Health Among adolescents, both boys and girls who never used sun protection were more likely to be depressed than those who used sun protection (Coogan et al., 2001). Among university students in London, depressive symptoms were associated with poor sunscreen use among women but not among men ( Allgwer et al., 2001) . In one study of adult engineers, sunburn and sy mptoms of depression had a positive relationship in bivariate analysis (Duffy et al., 2012). With regard to indoor tanning, high school boys that used indoor tanning were more likely to attempt suicide (Miyamoto et al., 2012). Indoor tanning use am ong college students was associ ated with anxiety and obsessivecompulsive disorders in men but not among women (Mosher & Danoff Burg, 2010b). College students that were classified as having an addiction to indoor tanning were more likely to report anxious ness, but there were no effects for depression (Mosher & Danoff Burg, 2010b Poorsattar et al., 2007). Sunscreen Sunscreen use, sunburn, sunbathing, overall sun protection, and indoor tanning were examined as independent variables in a few studies with cou nterintuitive findings. In a large study of Danish adults ages 15 to 59, those who sunbathed with the intention of tanning were more likely to use sunscreen than “unintentional” tanners , (Koster, Thorgaard, Philip, & Clemmensen, 2010) while adult indoor t anners were more likely to use sunscreen than those who did not tan indoors (Ezzedine et al., 2008). These findings were consistent among college students in the U . S ., with those who had past indoor tanning experience engaged in less risky sun behaviors ( Bagdasarov et al ., 2008). When considering tanning dependence, indoor tanning, sunburn, and poor 40

PAGE 41

sunscreen use were all associated among university students (Heckman et al., 2008). However, in a population of beachgoers in Rhode Island, Weinstock, Rossi, Redding, Maddock, and Cottrill (2000) found those who did not use indoor tanning demonstrated better sun protection behaviors. Discussion This review uncovered a limited range of existing studies that suggest there is a relationship between skin cancer prevention behaviors and other health risks across the lifespan. The dearth of studies examining skin cancer prevention behaviors other than indoor tanning among college students represents a gap because as adolescents age, they are less likely to use sun protection and clustered risk behaviors increase making the college age span a critical time for intervention (Eaton et al. , 2012). Problem Behavior Theory (PBT) offers insight to the clustered nature of highrisk behaviors among adolescents by suggesting that latent personality variables enable these behaviors and then environments reinforce them. For instance, sunbathing has been associated with risk taking (Keesling & Friedman, 1987) and those who sunbathe and do not use sun protection could have late nt issues such as low self esteem and engage in self destructive behaviors (Coogan et al., 2001). Additionally, adolescence is a period of rebellion for some and being healthy might be an unappealing social construct for a defiant teen , particularly if a parent is encouraging healthy behaviors. Substantial research has found clustered problem behavior such as alcohol and drug use, sexual risk taking, and injury risk, occur in late adolescence. PBT predicts that these risk high behaviors are developed to help adolescents “look cool and fit in” with peers (Bagdasarov et al., 2008). Unfortunately, these habits established in adolescents and 41

PAGE 42

young adults might grow into lifestyle behaviors, hence the importance of examining multiple health risk behaviors dur ing the college age span . Among adults who may have established unhealthy behaviors in their youth such as smoking, drinking, and drug use but have moved past the social norms to fit in, poor health behaviors may have already become an addiction or habit. Specifically, recent studies have examined the addictive nature of tanning and people might become tanning dependent just as those who are nicotine dependent (Heckman et al., 2008). Tanning addiction shares some characteristics with nicotine addiction i n that those with a tanning addiction have a fear of quitting tanning and experience withdrawal symptoms when they are unable to regularly tanning (Heckman et al., 2008). Smoking is often associated with a myriad of other health risk behaviors including alcohol abuse (Chiolero, Wietlisbach, Ruffieux, Paccaud, & Cornuz, 2006), low rates of exercise (Kvaavik, Meyer, & Tverdal, 2004), and poor diet (Schuit, van Loon, Tijhuis, & Ocke, 2002). Smoking is widely known as the leading preventable cause of death and disease (CDC, 2004) and is responsible for 90% of lung cancers and more than 80% of Chronic Obstructive Pulmonary Disease (COPD) deaths in the US (US Cancer Statistics Working Group, 2006). From the public health perspective, smoking shares some paral lels with UV exposure because there is clear evidence of the casual relationship between smoking and lung cancer similar to the link between UV exposure and skin cancer. Despite the widespread public awareness of the relationship, people continue to engag e in these highrisk behaviors. This paradox suggests that smokers are not 42

PAGE 43

concerned about long term health outcomes nor are those who deliberately engage in high risk skin cancer behaviors. Consistent with PBT’s premise that underlying personality iss ues drive clustered health risk behaviors, the self presentation (appearance) concerns related to physical activity, BMI, dieting, and substance abuse help explain the relationship with skin cancer prevention behaviors. Personal appearance motivations and the belief that being tan enhances appearance are among the strongest latent predictors of engaging in risky tanning behaviors (Leary & Jones, 1993). Other research has found correlates between self presentation concerns and risky healthy behaviors , acro ss a spectrum of behaviors including condom use, drug and alcohol use, and physical activity (LargoWight, 2005). When people are most concerned about what others think of them, rather than their own self view, they are more likely to engage in risky heal th behaviors (Leary & Jones, 1993). People with high self presentation concerns tend to be high social monitors, publicly self aware, and hyper conscious about their physical appearance. The relationship between indoor tanning, weight, and dieting is sup ported by the literature, suggesting the link between indoor tanning and appearance concerns. In line with self impression concerns, many health risk behaviors including smoking, marijuana use, and alcohol also cluster with indoor tanning . The clustered relationship is speculated to be a result of peer and mass media influences that promote a thin, tanned person engaging in “fun” activities such as social drinking, smoking, and glamourized drug use. The findings between physical activity and skin cancer present a potential conflict that public health practitioners must carefully navigate. Regular exercise is a known 43

PAGE 44

protective factor against a host of chronic diseases including high blood pressure, diabetes, heart attack (Powell, 1998), stroke, cancer ( Coyle, 2009) arthritis, and symptoms of depression and anxiety (Brown, 1991; Crews & Landers, 1987; Pertruzello et al., 1991). However, as evidenced by the findings and simple logic, sun protection and outdoor physical activity are at odds with each other because to be outside jogging or playing sports, one is likely exposed to the sun, with only sunscreen as a defense strategy. People who exercise outdoors would be at higher risk for NMSC which is due to cumulative sun exposure rather than acute. More p hysical ly active people might be outdoors and exposed to more UV radiation than sedentary people, therefore, sun safety campaigns should be careful to not discourage outdoor physical activity but rather encourage good sun protection strategies such as avoi ding peak sun hours and the use of sun protective clothing, and proper sunscreen application. For instance, a study of college athletes found that nearly 80% of NCAA track athletes did not wear sunscreen in the week prior to the study (Hamant & Adams, 2005). However, more precise studies are needed because most of the existing studies do not differentiate between indoor and outdoor exercise so that is complicating the exact relationship between physical activity and skin cancer. Although BMI is not a l iteral health behavior, it is frequently used as a behavioral correlate in health behavior research to illustrate physical activity and diet constructs given the causal impact on weight. Overweight and obesity rates have been steadily increasing over the past 20 years ( Shaw et al., 2006) and the relationship with skin cancer risk is seemingly inconsistent but there is an underlying logic to the findings. People who are overweight or obese may not be in the sun as consistently as those 44

PAGE 45

with a normal BMI but when they do go in the sun, they are more likely to burn because they haven’t been in the sun and they have larger surface areas to protect (Holman et al., 2014). These findings follow the logic that overweight and obese people might not want to exposure their bodies publicly during outdoor activities such as exercise or sunbathing ; therefore, they have less sun exposure. Appearance concerns are particularly salient among adolescents with underweight and normal weight teens engaging in more sun exposur e than their overweight counterparts. However, indoor tanning bed use was the same between groups , suggesting overweight teens might not want to be seen sun bathing. Body dissatisfaction emerged as an important theme and is often linked to other risky behaviors including disordered eating (Leon, Fulkerson, Perry, & Cudeck, 1993). There is a significant gap in the scientific literature examining multiple health risk factors related to risky UV exposure during the pivotal college experience. National ski n cancer rates are at unacceptably high levels and are continuing to increase particularly among young adults. As discussed, the harmful effects of skin cancer could mostly be avoided with simple sun protection strategies and the avoidance of indoor tanni ng. Unfortunately, college students are not taking the advice of their parents and public health campaigns to use sunscreen and avoid tanning beds. It should be noted that the indoor tanning industry spends millions of dollars every year to promote the i dea that indoor tanning is a safer alternative to natural sun exposure, which undoubtedly furthers confusion (Obayan, Geller, Resnick, & Demierre, 2010). Mass media public health campaigns have made great strides in increasing awareness of the link between UV exposure and skin cancer , yet these efforts have not improved behaviors. There are 45

PAGE 46

limited theoretically based skin cancer prevention interventions for the college population. In fact, many of the existing UV education interventions focus on indoor t anning and the constructs are salient to appearance motivations rather than broader sun safety behaviors. Indoor tanning is an important area of inquiry ; however, overall sun safety education, specifically sunscreen use, affects a greater proportion of college students and the general population. Thus, given the prevalence of inadequate sun protection and increasing skin cancer rates, the early identification of college students at risk for engaging in multiple health risk behaviors is important for publ ic health practitioners in several ways. First, existing interventions can be improved by targeting the clustered health behaviors rather than delivering a variety of disjointed health programs. Secondly, helping college students establish a constellatio n of healthy behavioral habits at a young age can have lifelong health benefits. Finally, the improved quality of life gains by establishing healthy behaviors at a young age can reduce overall healthcare system expenditures. Study L imitations There are expected limitations given the depth and breadth of studies included. These limitations should be considered when evaluating the findings. Many of the studies relied on cross sectional data to analyze multiple health risk correlates. Beyond self selecti on and self report bias intrinsic in cross sectional studies (Olsen, 2008), the approach is limited in the ability to provide insight on the specific reasons for engaging in these behaviors. Specifically, the latent variables that drive health behavior and this area of study would benefit from more qualitative studies to illuminate the underlying characteristics associated with poor skin cancer prevention behavioral correlates. Although risky tanning and appearance motivations have been extensively studied, the 46

PAGE 47

inclusion of multiple health behaviors is relatively novel and would benefit from the richness of context that observational, focus groups, and openended interview studies provide. Also, largescale datasets often lag behind emerging health trends . For instance, texting while driving became a serious public health threat several years before questions were added to national instruments. Additionally, some of the retrospective designs didn’t use standardized skin cancer prevention questions, which limits comparison of findings with other studies. There was also a noticeable absence of longitudinal studies to better understand health behavior trends. Further, many of the studies used different terminology , referring to skin cancer prevention behav iors including sun exposure, sun protection and indoor tanning which further complicates the ability to generalize and compare findings. Future studies would benefit from using a validated instrument such as the standard National Cancer Institute’s core s kin cancer prevention questionnaire (Glanz et al., 2008). Even when using gold standard measurements, it should be noted that precise measurement of proper use of sun protective behaviors is difficult to assess because there are nuances to sunscreen appl ication including amount of sunscreen used per application and frequency of reapplication. 47

PAGE 48

Figure 21. The screening process for the scoping review of skin cancer prevention behavioral correlates yielded 36 studies. Electronic databases were searched for relevant article titles and abstr acts (n=55) Additional articles were gleaned from reference lists of review articles (n=3) Total=54 Other review articles were excluded (n=4) Total=51 Articles not meeting inclusion criteria were excluded (n=17) Total=37 Articles meeting review criteria (n=37) 48

PAGE 49

Table 21. Skin cancer prevention key findings. Author, Year Country Skin Cancer Risk Behavior Sample Study Design Behavioral Correlates Pothiawala et al. (2012) USA Skin cancer risk n=102,748 ages 30 75 females Pooled data from National Nurses' Health Study and the Health Professional Follow up Study Overweight and obesity associated with lower rates of non melanoma skin cancer (NMSC) but not melanoma Hall et al. (2003) USA Sunburn n=32, 374 ages 18 65+ male and female Cross sectional analysis of the 2000 National Health Interview Survey Sunburn in the past year was associated with more exercise, higher BMI, and excessive alcohol use. Former smokers had more sunburns than those who don't smoke or current smokers. A history of alcohol use was associated with greater sunburn. Kirkpatrick et al. (1994) USA Skin cancer risk n=234 cases n=248 controls ages 35 74 male and female Case control study of melanoma patients and controls through the Seattle Puget Sound cancer registry Positive relationship i n men and women between melanoma risk and high BMI. Santmyire et al. (2001) USA Sunscreen use n=32,440 ages 18 65 male and female Cross sectional analysis of 1998 National Health Interview Survey Nonsmokers and those who frequently used seatbelts appli ed sunscreen more often. Schnohr et al. (2005) Denmark Skin cancer risk n=28,000 ages 20 93 male and female 14 year follow up health examination and questionnaire of general population Significantly higher NMSC risk in males who exercised than those who did not exercise. The effects were not apparent for females. Lawler et al. (2007) Australia Overall sun protection n=1,992 ages 20 65 male and female Observational epidemiological study of urban residents in Adelaide Physically active people were more likely than sedentary people to use sunscreen when outdoors. 49

PAGE 50

Table 2 1. Continued Author, Year Country Skin Cancer Risk Behavior Sample Study Design Behavioral Correlates Coups et al. (2008) USA Overall sun protection n=28,235 ages 18 65 male and female Cross sectional analysis of the 2005 National Health Interview Survey. Those with obese or overweight BMI, smokers, and risky drinkers were more likely to engage in poor skin cancer prevention. Lee et al. (2009) Canada Skin cancer risk n=595 ages 20 79 males Case control study of Occupational physical activity and risk of malignant melanoma: The Western Canada Melanoma Study Greater levels of exercise were associated with increased melanoma incidence. Falk et al. (2013) Sweden Sun exposure habits Skin cancer risk n=489 treatment n=664 control ages 55 69 male and female Case control study of skin cancer patients through the Health Care Register Smoking and greater levels of physical activity were associated with sun bathers. Shors et al. (2001) USA Skin cancer risk n=488 case n=727 control ages 35 74 male and female Case control study of melanoma patients through the SeattlePuget Sound Surveillance, Epidemiology, and End Results (SEER) registry Lower chance of melanoma with greater levels of exercise. BMI, fruit and vegetable consumption were not significant. Dennis et al. (2008) USA Skin cancer risk n=168 cases n=89,658 cohort ages 12 93 male and female Analysis of the prospective, cohort Agricultural Health Stu dy of Iowa and North Carolina farmers Higher BMI was associated with greater melanoma risk 50

PAGE 51

Table 2 1. Continued Author, Year Country Skin Cancer Risk Behavior Sample Study Design Behavioral Correlates Duffy et al. (2012) USA Sunburn Sunscreen n=498 ages 18 70 male and female Cross sectional study of operating engineers Higher BMI and more exercise were associat ed with sunburn. Greater fruit consumption and alcohol abuse were associated with sunblock use. Depression was significant in sunburns in bivariate analysis but not in multivariate. Smoking was not significant. Parent et al. (2011) Canada Skin cancer r isk n=103 ages 18 65 males Case control study in Montreal Men with high occupational physical activity levels had decreased melanoma risk. Men engaging in outdoor activities had slightly increased risk of melanoma Tang et al. (2013) USA Skin cancer ris k n=61,657 ages 50 79 females Analysis of the longitudinal, prospective Women's Health Initiative Observational Study Lower skin cancer risk in women with higher BMI. Jardine et al. (2012) Australia Sunburn n=7,802 ages 18 74 male and female Cross sectional analysis of the Queensland Self Reported Health Survey Participants who exercised were more likely to report sunburn in the past year and previous weekend. Particularly high among those who did 7 hours of exercise in a week. Each hour of exercise w as associated with an increase risk of sunburn. Holman et al. (2014) USA Sunburn n=24,970 ages 18 65+ men and women Cross sectional analysis of the 2012 National Health Interview Survey Physical activity, alcohol consumption, and being overweight or obese were all associated with sunburn. 51

PAGE 52

Table 2 1. Continued Author, Year Country Skin Cancer Risk Behavior Sample Study Design Behavioral Correlates Saraiya et al. (2002) USA Sunburn n=156,354 ages 18 65+ men and women Cross sectional analysis of the 1999 Behavioral Risk Factor Survey Sunburn was associated with smoking and risky drinking. Weinstock et al. (200 0) USA Overall sun protection n=2,324 ages 16 65 male and female Convenience sample of beach goers in Rhode Island Those who did not use indoor tanning were more likely to demonstrate sun protection behaviors. Ezzedine et al. (2008) France Indoor and ou tdoor tanning n=7,200 ages 35 60 male and female Cross sectional analysis of middle age French volunteers Indoor tanners were smokers, less active, and used sunscreen Heckman et al. (2008) USA Indoor tanning n=29,394 ages 18 65+ male and female Cross sectional analysis of the 2005 National Health Interview Survey Normal weight people between 30 and 39 year olds indoor tanned more. Those 18 to 29 and 40 to 49, those who exercised tanned indoor more. Those 18 to 49 that consumed less fruit and vegetables indoor tanned more. Indoor tanners 18 to 29 engaged in smoking and risky drinking. Koster et al. (2010) Denmark Sun burn indoor and outdoor tanning n=3,499 ages 1559 male and female Data from a larger cross sectional sun survey No significant differenc e between indoor tanners and nonindoor tanners on sunscreen use. 52

PAGE 53

Table 2 1. Continued Author, Year Country Skin Cancer Risk Behavior Sample Study Design Behavioral Correlates Heckman et al. (2008) USA Tanning dependence n=400 ages 18 65 male and female Convenience sample of a Southeastern university and community volunteers Current smokers were more likely to be tanning dependent (TD). Those who were obese were less likely to be TD than normal and overweight. Physical activity did not predict TD. Tanning dependence was associated with sunburn and poor sunscreen use. Mosher & Danoff Burg. (2010) USA Indoor tann ing n=421 ages 18 25 male and female Convenience sample of in the Northeast university students using CAGE (Cut down, Annoyed, Guilty, Eye opener) questionnaire Indoor tanning was associated with alcohol use, tobacco use, and other substances among women. Obsessive Compulsive Disorder symptoms effects among men. Mosher & Danoff Burg. (2010) USA Indoor tanning n=421 ages 18 25 male and female Convenience sample of in the Northeast university students using CAGE (Cut down, Annoyed, Guilty, Eye opener) qu estionnaire Those addicted to indoor tanning reported more anxiety and higher levels of alcohol, marijuana, and other drug use. Depression status was not affected by indoor tanning status. Allgower et al. (2001) United Kingdom Sunscreen use n=5,529 ages 18 30 male and female Cross sectional analysis of European Health and Behavior Survey of university students in 21 countries Depression was associated with poor sunscreen use among women. Poorsatter et al. (2007) USA Indoor and outdoor tanning n=385 ages 17 30 male and female Convenience sample of university students using CAGE (Cut down, Annoyed, Guilty, Eye opener) questionnaire Substance abuse symptoms and indoor tanning coexist. 53

PAGE 54

Table 2 1. Continued Author, Year Country Skin Cancer Risk Behavior Sample Study Design Behavioral Correlates Bagdasarov et al. (2008) USA Indoor and outdoor tanning n=725 ages 18 25 men and women Data used from a larger study of tanning attitudes of undergraduate students at a large Northeastern university Past tanning bed use was associated with drinking but not lower sun risk behavior. Indoor tanning was associated with smokin g and drinking. Coogan et al. (2001) USA Overall sun protection n=24,645 ages 9 18 men and women Cross sectional analysis of 1988 1995 Connecticut Health Check Adolescents who did not use sun protection were more likely to smoke, use marijuana, use alcohol, and not wear a seatbelt. Girls and boys who never used sun protection were more likely to report signs of depression. Yoo & Kim (2012) USA Indoor and outdoor tanning n=347 ages 11 18 male and female Cross sectional analysis of adolescent middle and high school students BMI only affected indoor tanning not outdoor tanning. Overweight girls engaged in more indoor tanning. Overweight and obese girls did not engage in outdoor tanning as much as underweight and normal weight girls. Hall et al. (2001 ) USA Sunscreen use n=15,349 ages 14 18 male and female Cross sectional analysis of 1999 Youth Risk Behavior Survey Poor sunscreen use was associated with driving after drinking, riding with someone who has been drinking, smoking cigarettes, being sexual ly active and being physically inactive. Normal weight students used sunscreen more often than overweight students. Lazovich et al. (2004) USA Indoor tanning n=1,273 ages 14 17 male and female Telephone interview of Minneapolis St.Paul, MN and Boston, M A youth Indoor tanning was positively associated with a history of smoking and poor sun protection. 54

PAGE 55

Table 2 1. Continued Author, Year Country Skin Cancer Risk Behavior Sample Study Design Behavioral Correlates Boldeman et al. (1997) Denmark Indoor and outdoor tanning n=1,502 ages 14 19 males and females Cross sectional study of 60 Swedish classrooms Indoor tann ing was positively associated with smoking onset at age 14/15. Indoor tanning was also associated with high levels of outdoor tanning. Cokkinides et al. (2002) USA Indoor tanning n=1,192 ages 11 18 males and females Cross sectional study of parent teen pairs Indoor tanners were less likely to use sun protection. Miyamoto et al. (2011) USA Indoor tanning n=7,219 ages 14 18 males Cross sectional analysis of males students responding to the 2009 Youth Risk Behavior Survey Among males, steroid use, unhealthy weight loss methods, sufficient fruit and vegetable consumption, binge drinking and attempted suicide were associated with indoor tanning. O'Riordan et al. (2006) USA Indoor tanning n=6,373 ages 12 18 females Retrospective analysis of the prospecti ve cohort Growing Up Today Study (GUTS) Among girls, binge drinking, cigarette smoking, recreational drug use, laxative use, vomiting to lose weight and dieting were associated with indoor tanning. Demko et al. (2003) USA Indoor tanning n=6,903 ages 13 19 male and female Analysis of white nonHispanic respondents to the National Longitudinal Study of Adolescent Health Indoor tanners had lower BMI, exercised less, were on a diet, engaged in substance abuse (at least two of these: tobacco, alcohol, marijua na). Wichstrom (1994) Norway Outdoor tanning Sunscreen n=15,169 ages 13 19 male and female Cross sectional analysis of national sample of high school students Smoking predicted highrisk sunbathing. 55

PAGE 56

CHAPTER 3 SKIN CANCER PREVENTION BEHAVIORS AMONG COLLEGE STUDENTS Skin cancer is the most common form of cancer in the United States, with more than three million people diagnosed annually (ACS, 2012). Furthermore, one out of every five people in the United States will develop skin cancer during t heir l ifetime (Robinson, 2005). The economic consequence of this cancer has resulted in a direct annual treatment cost of more than four billion dollars (NCI, 2010). The three most common types of skin cancer include squamous cell carcinoma, basal cell carcino ma, and melanoma. Squamous and basal cell carcinomas are the most common forms of skin cancer and are rarely fatal (CDC, 2014). However, though not the most common form, melanoma is the most lethal skin cancer ( Ahmedin et al., 2010) . An estimated 12,190 deaths (9,180 from melanoma and 3,010 from other nonepithelial skin cancers) occurred in 2012 (ACS, 2012). Melanoma is the most common form of cancer for people aged 25 to 29 years old and the second most common cancer for people aged 15 to 29 years ol d – an ever increasing trend affecting young people. ( Bleyer et al. , 2006) . In fact, over the past 40 years, melanoma rates among those under the age of 40 have increased 800% in women and 400% in men ( Reed et al., 2012). This increase is not surprising given young adults ages 18 to 29 comprise the most active age group engaging in risky UV exposure (Choi et al. , 2010). Exposure to UV light is the single most modifiable risk factor for skin cancers and is mostly preventable by avoiding the sun and indoor tanning machines (NCI, 2010). The A merican C ancer S ociety (2012) recommends avoiding t he sun during peak hours (10am to 4pm), seeking shade when outdoors, wearing sun protective clothing , 56

PAGE 57

including sunglasses and a widebrimmed hat, and frequently applying broadband sunscreen protection (SPF>15). Proper sunscreen use has been linked to a reduction in squamous cell and malignant melanoma skin cancer development by 40% and 50% respectively (Green et al. , 1999; Green et al. , 2011). Childhood, adolescent , and young adult UV exposure is damaging because it accumulates toward later skin cancer risk (Parkin et al. , 2011). Furthermore, young adults, specifically college students, obtain a majority of their lifetime UV radiation exposure before and during this tim e of their life (Greene et al. , 2010). Although this group is spending significant time in the sun, only about 5% of college students properly use sun screen (Spradlin et al., 2010). Further evidence of poor sun protection behavior was illustrated in a na tional telephone survey of young adults with 72% reported having at least one prior summer sunburn, 30% reported at least three sunburns and 12% reported more than five sunburns (Davis et al. , 2002). Sunburns are the short term effect of excessive UV exposure and factors associated with increased odds of sunburn include greater sun sensitivity, lighter skin tones, younger ages, hours spent outdoors, sunbathing , and desirability of a tan (Davis et al., 2002). Indoor tanning is another avenue for UV exposure, with an estimated 40% to 60% of college students having used indoor tanning machines (Hillhouse et al. , 2005). Indoor tanning, also referred to as sunlamps, tanning booths/beds and artificial tanning, has been positively associated with skin cancer and has been classified as a carcinogen (Whitmore et al. , 2001; Karagas, 2002). Such machines can be uniquely tied to the rising rates in melanoma through epidemiological trend data and historical examination. Tanning beds were introduced in the United Sta tes in 1978 and became 57

PAGE 58

popular in the 1980s, coinciding with the increases of m elanoma over the past 30 years. Indoor tanning is used to speed the skin tanning process regardless of climate. Tanning machines are particularly problematic given they expose people to even more concentrated doses of UVA and UVB radiation than the sun (Whitmore et al., 2001). About 10% of the US population (30 million people) regularly use indoor tanning , with the highest rates among nonHispanic white women living in the Mi dwest and South ( Choi et al. , 2010). Teenagers (13%) and young adults ages 18 to 29 (20.4%) makeup the largest block of indoor tanners (Choi et al., 2010). In fact, Healthy People 2020 has identified two national objectives for reducing indoor tanning us age among adolescents in grades 9 to 12 and adults 18 years and older (US Department of Health and Human Services, 2012). Young women are more active indoor tanners with 18.1% tanning indoors compared to 6.3% of men (Eaton et al. , 2012). In summary, four out of five cases of skin cancer could be prevented by reducing UV exposure, avoiding indoor tanning, and practicing simple protective measures such as applying sunscreen. The purpose of this study is to examine the skin cancer prevention behaviors amon g college students in the southeast US. Methods The data for this study came from a larger college health assessment survey, Our Campus , Our Health (OCOH) , delivered at a large comprehensive university in the southeast. The survey also included the core skin cancer prevention questionnaire developed by the National Cancer Institute workgroup (Glanz et al. , 2008). All 16,343 undergraduate and graduate students at the institution received an email invitation to participate over a four week period during t he Fall 2013 semester. The survey was delivered through Qualtrics Survey Software (Qualtrics, Provo, UT) by the Institutional 58

PAGE 59

Research office as directed by the IRB to protect participant privacy. Following completion of the survey, participants had the option of clicking on a hyperlink to enter their name and email address to enter a raffle to win a variety of incentives to increase survey participation. All responses were deidentified prior to being shared with the PI. The extensive 121item survey y ielded an 11% response rate with 1,774 participants. To be included in the study sample, participants were required to be between the ages of 18 to 25 and have responded to all demographic and skin cancer prevention variables, which reduced the sample siz e to 747 (4.5% overall response rate) . Data was analyzed using SPSS (SPSS Inc, Chicago, Illinois) and included descriptive statistics and ch i square analysi s. Results The 747 students averaged 21 years of age (M = 21.14, SD= 1.98), were mostly female (73.6%), and white (74.8%), were in their third year of school (32.6%), insured (77.5%), and not working while in school (32.1%). Table 31 illustrates demographic characteristics of the study sample. The sample was reflective of the overall population a t the university with a largely female (56.5%) and white (70.9%) student body. Overall sun protection behaviors were inadequate among respondents. The majority did not regularly use sunscreen (66.3%) with only 12.4% reporting always using sunscreen when outside on a warm sunny day. Sunscreen use did improve with age as depicted in Figure 31. An overwhelming majority (97.1%) did not regularly protect their neck, ears, face and shoulders with a widebrimmed hat, seek shade (82.5%), or use an umbrella (98.7%) when outside on a warm sunny day. Despite these poor sun protection behaviors, participants did not avoid the sun during peak hours (10am to 4pm) with 46.2% never attempting to avoid peak hours and less than 2% always 59

PAGE 60

avoiding peak hours. When asked how many hours they spent outside in the previous summer during peak hours, an alarming majority (58%) reported more than two hours of daily sun exposure. Nearly 60% of respondents reported not regularly wearing a shirt that covered their shoulders while outside on a warm sunny day, yet 53.2% reported often or always wearing sunglasses. Highrisk skin cancer behaviors were further confirmed by the reported sunburn rates with 71.8% of participants reporting at least one sunburn in the previous year and 10% of participants reporting more than five sunburns in the previous year – more than five lifetime sunburns is a risk factor that doubles the chance of developing melanoma. There were significant gender differences in sunscreen rates, sunglasses use, and wearing a shirt that covered the shoulders while outside. Women demonstrated better sunscreen X2 (4, N = 747) = 41.418, p < 0.000 and sunglasses use X2 (4, N = 747) = 10.538, p < 0.001, while men were more likely to wear a shirt covering their shoulders X2 (4, N = 747) = 31.355, p < 0.000. Nearly half (48.8%) of the respondents reported “always” or “usually” spending time in the sun for the purpose of getting a tan and 44.6% reported using sunless tanning creams at home or spray tanning at a salon (12.6% ). The majority of respondents reported never using a tanning bed (73.4% ); however, women were more likely to indoor tan (p<0.000). Of those who reported indoor tanning, the average age of the first tanning bed visit was age 17 (M = 17.15, SD= 1.89), wi th only 21% reporting using a tanning bed more than three times (less than three visits is considered experimental use), and the average usage at eight (M = 8.10, SD= 30.65) lifetime tanning bed visits. In the previous year, 8.6% of the respondents report ed using a 60

PAGE 61

tanning bed more than three times, with average usage at two visits. There were significant gender and age differences in tanning behaviors, with females more likely to spend time in the sun for the purpose of tanning X2 (4, N = 747) = 15.390, p < .005, use tanning creams X2 (1, N = 747) = 43.445 , p < .000 or sprays X2 (1, N = 747) = 18.717 , p < .000, and tan indoors X2 (1, N = 747) = 25.229, p < .000 . Table 3 2 depicts sun protection, sun exposure, and indoor tanning behaviors. Despite poor overall skin cancer prevention behaviors, 79.4% of the respondents have never had their skin checked for skin cancer from head to toe by a health professional. Discussion Insufficient skin cancer prevention behaviors , including sun exposure, sun protection, and indoor tanning were apparent among the college students in this study. Unfortunately, the results are consistent with other studies of college students and help explain the rising melanoma rates among young people ( Cottrell et al., 2005; Spradlin et al., 2010) . One of the more interesting and promising findings from the study is the shift in sunscreen use around the age of 21 as depicted in Figure 31. There was a dramatic increase in sunscreen use that started at age 21 continued to increase through age 25. This is an important finding because most studies examining sunscreen use collectively examine the 18 to 25 age group, or study 20 to 29 year olds together (Heckman et al., 2008) , whereas this study teased out an important agerelated shift in behavior. This finding highlights the need to target sun safety interventions at the freshman level. Also, this study revealed important gender difference in skin cancer prevention risks that will aid in targeting behaviors salient to the respective g enders ( Cottrell et al., 2005; Spradlin et al., 2010) . For instance, males engage in less sunscreen use than females, while females were more likely than males to sunbathe for the purposes of 61

PAGE 62

tanning and use tanning products. University health promotion centers could use this information to design interventions to promote better sunscreen use among fraternities, male dominated disciplines such a science, technology, and building construction. For females, the findings support previous studies that appear ance motivations drive UV exposure so interventions directed toward young women would be different than programs for males ( Leary & Jones, 1993; Hillhouse & Turrisi, 2002) . A promising study promoted appearance improving alternatives to tanning such as the use of tanning creams, makeup with bronzers, and wearing clothing to flatter and enhance one’s natural skin tone (Hillhouse & Turrisi, 2002). Additionally, although the better sunscreen behaviors among women seemingly contradict their tan seeking and indoor tanning behaviors, there is an underlying logic. Women who are concerned about their appearance might use sunscreen to prevent wrinkles, sun spots, and skin aging, while incorrectly believing that indoor tanning is a safer alternative. Also, the sh ort term perceived benefits of an attractive tan may outweigh long term costs such as cancer and skin damage. Sororities and disciplines with high female concentrations such as public relations, psychology, and sociology would be good environments to rein force the message that any UV light causes skin damage, promote a “pale is pretty” message, and encourage appearance enhancement through other methods. Additionally, universities should seek to correct the misconception that indoor tanning is a safer alte rnative to natural sun exposure. This misconception has been promoted by the indoor tanning industry as tanning devices primarily emit UVB radiation associated with sunburn while the sun emits UVA and UVB. UVA is associated with more skin damage, yet bot h UVA and UVB rays are associated with skin cancer. 62

PAGE 63

This study has a number of p otential limitations that should be considered. Although the sample size is robust, the response rate was low (roughly 4.5% after applying the inclusion criteria) given the lengthy survey was sent to all 16,343 students enrolled at the university. Although the response rate is low, the sample is remarkably reflective of the overall demographics of the university as reported by the University Institutional Research Office . The convenience sampling methodology used limits generalizability although, as stated, the demographic characteristics of the sample were remarkably representative of the overall university profile. Male participation (26.4%) was lower than university mal e enrollment (43.5%) and that is consistent with survey response research findings that males are less likely than females to respond to online surveys ( Curtin, Presser, & Singer, 2002; Moore & Tarnai, 2002; Singer, van Hoewyk, & Maher, 2000) . Also, studi es using self report surveys are subject to self report, self selection bias , and recall error (Olsen, 2008). Additionally, proper use of sun protective behaviors cannot adequately be assessed because there are nuances to sun protection, including amount of sun screen used per application, frequency of reapplication, and environmental variables such as reflection from water when seeking shade. Also, the survey did not include questions about complexion, sun sensitivity , or family history of skin cancer – a ll of which contribute to skin cancer risk. Conclusion Despite widespread educational and mass media efforts to reduce skin cancer, college students continue to receive large amounts of intentional and unintentional exposure to UV radiation either from the sun or indoor tanning. Beyond the lack of skin cancer prevention behaviors revealed in this study, the most alarming finding was the majority of students (79.4%) have never had a full body skin check by a healthcare 63

PAGE 64

professional. This finding exposes an oversi ght in our healthcare system given that melanoma is the most common form of cancer among adults ages 25 to 29 and the second most common cancer among 15 to 29 year olds (Bleyer et al., 2006). Primary care providers and pediatricians have a tremendous opportunity to introduce skin health to their young patients by encouraging sun safety, assessing skin cancer risk by using the Fitzpatrick skin type test, taking family skin cancer history, and referring those at risk for skin cancer to a dermatologis t for an annual skin cancer examination. In addition to skin cancer checks performed by a healthcare professional, all patients should be enc ouraged to conduct regular self skin checks and keep a mole map such as the American Academy of Dermatology (2013) DETECT Skin Cancer: Body Mole Map that tracks mole size, shape, color, location, and border. This study , along with the fact that melanoma rates continue to rise, supports the notion that traditional skin cancer prevention programs must evolve to includ e multiple delivery routes including primary care, mass media, and formal education programs. 64

PAGE 65

Table 31. Demographic characteristics of the study sample (n=747). Characteristic N Percent Sex Male Female 197 550 26.4 73.6 Age 18 19 20 21 22 23 24 25 74 103 123 140 110 88 66 43 9.9 13.8 16.5 18.7 14.7 11.8 8.8 5.8 Race/Ethnicity White Hispanic Black Bi/Multirace Other races 559 63 48 26 51 74.8 8.4 6.4 3.5 6.8 Classification Freshman Sophomore Junior Senior Graduate 131 114 244 195 63 17.6 15.3 32.6 26.1 8.4 Insurance Insured Uninsured Unsure 579 134 34 77.5 18.0 4.4 Hours worked per week I do not work 1 – 10 hours 11 – 20 hours 21 – 30 hours 31 – 40 hours Over 40 hours 238 84 152 144 98 31 31.9 11.2 20.4 19.3 13.1 4.2 Relationship status Single In a committed relationship Married Divorced/widowed/separated 269 418 54 6 36.0 56.0 7.2 .8 65

PAGE 66

Table 32. Sun protection, sun exposure, and indoor tanni ng (n=747). Females (n=550) Males (n=197) N Percent N Percent p value Sun protection * Sunscreen use Always or often Sometimes, rarely, or never Wide brimmed hat Always or often Sometimes, rarely, or never Seek shade Always or often Sometimes, rarely, or never Avoid peak hours (10am – 4pm) Always or often Sometimes, rarely, or never Wear a shirt that covers the shoulders Always or often Sometimes, rarely, or never Sunglasses Always or often Sometimes, rarely, or never 210 340 16 528 90 456 51 491 174 376 332 218 38.19 61.81 4.00 96.00 17.10 82.90 10.30 89.27 31.58 68.42 60.32 39.68 42 155 8 189 34 163 28 168 120 77 79 118 21.32 78.68 4.06 95.94 17.26 82.74 14.72 85.28 60.86 39.13 40.21 59.78 0. 000 0.447 0.802 0.058 0.000 0.001 Sun exposure Time spent in the sun to get a tan Always or often Sometimes, rarely, or never Hours spent per day outside in previous summer during peak hours Less than an hour 1 – 2 hours 3 – 4 hours More than 5 hours Sunburn in the past year None 1 – 2 3 – 4 More than five 332 112 227 131 16033 2 154 285 73 38 53.99 46.01 41.30 23.89 29.15 5.66 27.94 51.82 13.36 6.88 70 127 92 49 49 7 58 94 26 19 35.52 64.48 46.74 25.00 25.00 3.26 29.35 47.83 13.04 9.78 0.001 0.640 0.802 Indoor tanning Have ever used indoor tanning Yes No Lifetime indoor tanning usage 2 or less visits More than 3 visits 203 347 526 24 36.84 63.16 95.65 4.35 17 180 138 59 8.70 91.30 70.00 30.00 0.000 0.000 Notes: *The question asks when the participant is outside on a warm, sunny day and answers are on a 5 point Likkert scale ranging from Never to Always. Always or Often is considered adequate use; Sometimes, Rarely, N ever is considered inadequate use. 66

PAGE 67

Figure 31. Sunscreen use across the college age span 77% 78% 78% 65% 62% 64% 61% 53% 23% 22% 22% 35% 38% 36% 39% 47% 18 19 20 21 22 23 24 25 Age High Risk Lower Risk 67

PAGE 68

CHAPTER 4 THE ASSOCIATION OF MULTIPLE HEALTH RISK FACTORS WITH SUNSCREEN USE AMONG COLLEGE STUDENTS Background Skin cancer is the most common form of cancer i n the United States, especially for adolescents and young adults (Greene et al., 2010; Heckman et al., 2011). Of the cancers caused by sun exposure, melanoma is the most serious , with roug hly 100,000 new cases per year ( IARCWG , 2007). Melanoma is only 4% of d iagnosed skin cancer but is attributed to 77% of deaths from skin cancer ( Zhang et al. , 2012 ). The American Dermatology Association found that women under the age of 40 are eight times more likely to get melanoma than they were in 1970 ( Lazovich et al., 2004) . Excessive UV radiation exposure is of particular concern for those who are 18 to 29 years of age, Caucasian, and from Western societies because people with these demographics spend more time outdoors in the sun, perform fewer sun protective behaviors, and are more likely to use tanning beds (Greene et al. , 2010; Isaacowitz & Choi, 2012; Sansone & Sansone, 2010; White et al., 2008). Ultraviolet (UV) radiation is emitted from the sun and from artificial tanning devices, such as tanning beds. Ex posure to UV radiation is associated with adverse health effects , including skin cancer, premature aging, cataracts, and immune suppression ( Dodd & Forshaw, 2010) . The World Health Organization and the United Nations Env ironment Program (UNEP) report global incidence of more than two million non melanoma skin cancers, 200,000 malignant melanomas, and 60,000 melanomarelated deaths each year (WHO, 1995) . The incidence of malignant melanoma continues to rise globally, in strong correlation with the frequency of recreational sun exposure, history of sunburns, and exposure to UV radiation from tanning beds (Kourosh, Harrington, & Adinoff, 2010). Unprotected 68

PAGE 69

exposure to the sun, in addition to five or more severe sunburns in childhood, increases the risk for melanoma in adult s between the ages of 18 and 39 years old (Murphy, 2013). A study by Yoo and Kim (2012) reports the alarming statistic that pe ople who sunbathe on a regular basis before the age of 30 have a 75% or higher risk of developing skin cancer. Despite the fac t that most Americans are knowledgeable about the dangers of UV radiation, skin cancer, and ways to protect themselves from excessive exposure, American adolescents and young adults have the lowest skin protection rates of all age groups and receive large amounts of intentional and unintentional exposure to UV radiation either from the sun or indoor tanning (Heckman & Coups, 2011; Hoffner & Ye, 2009). Healthy People 2020 recognized skin cancer as a pressing national public health issue and set objectives f or adolescents and adults to reduce highrisk behaviors ( U.S. Department of Health and Human Services, 2011) . The 2020 objectives for adolescents include 1. reduce sunburn and indoor tanning use by 10% among 9th to 12th grade students; 2. increase proport ion of 9th to 12th grade students that use sun protection by 10% (from 9.3% to 11%). The objectives for adults are similar and include 1. reduce sunburn rates by 10% from 37.5 adults reporting one sunburn in the past year to 33.8%; and reduce melanoma dea ths by 10% to 2.4 per 100,000 (currently at 2.7 per 100,000); 2. increase the proportion of people who use at least one sun protection strategy to 73.7% of the US adult population (currently at 67%); reduce indoor tanning rates by 10% to 3.6 from 5.6%). 69

PAGE 70

H ealthy Campus 2020 is based on the US Surgeon General’s Healthy People 2020 framework and identifies health improvement priorities specific to college students ( U.S. Department of Health and Human Services , 2012; ACHA , 2012). Healthy Campus provides a roadmap for researchers to efficiently study college health risks by categorizing the health indicators that represent the most pressing issues facing college students. The developmental ages between high school and college are significant in the fostering o f health behaviors that will have a long lasting effect into adulthood. This is, in fact, an excellent time to intervene with young people to establish and maintain healthy behaviors (Cullen et al., 1999; Baronowski et al., 1997). The leading causes of m orbidity and mortality among the college population include inadequate physical activity, smoking, substance abuse, highrisk sexual behavior, and unintentional injury. Additionally, the America College Health Association recommends the consideration of m ental health given there is considerable research showing underlying mental health issues associated with risky health behavior among college students. Additionally, attending college itself is recognized as a period of high levels of perceived stress and negative mental health outcomes (NAMI, 2012; NIMH , 2005; SAMSHA, 2010). Problem Behavior Theory (PBT) is a social psychological framework specific to adolescents and young adults that use the interaction between three major systems to explain risk behav ior: personality, environment, and behavior (Jessor et al. , 1968). Problem Behavior Theory asserts that the three major systems are interrelated and to provide a social context to explain problem behavior. The theory suggests that the social life of young people presents constant opportunities to learn new behaviors and then social expectations reinforce them (DuRant et al. , 1999). Further, the risk and 70

PAGE 71

problem behaviors cluster because they become part of an individual’s internal validation system simil ar to affirmation from parents or acceptance from peers (DuRant et al . , 1999). Multiple health behavior risk research based in Problem Behavior Theory is showing great promise to improve public health in a cost effective manner by providing a framework to address many clustered health risk behaviors within a single intervention (Prochaska, 2008). In summary, four out of five cases of skin cancer could be prevented by reducing UV radiation exposure and practicing simple protective measures such as applying sunscreen. However, less than 50% of people engage in adequate levels of sun protection based on government guidelines, according to an article by Craciun, Schuz, Lippke, & Schwarzer (2010). Among college students, proper sunscreen usage rates hover around 5% (Spradlin et al., 2010). Given these numbers, it is crucial to determine what motivates people to engage in sunscreen use so that effective interventions can be implemented. It is the aim of this study to identify the health risk behaviors that pre dict poor sunscreen usage among college students. Methods Study Population and Sample Data was used from an annual comprehensive health behavior survey, Our Campus, Our Health (OCOH) delivered at a large comprehensive university in the Southeast. OCOH is an instrument modified for the college population from the CDC’s Youth Risk Behavioral Surveillance System (YRBSS). In addition to the health behaviors items, t here are several measures included within the instrument imperative to this study , including t he National Cancer Institute core skin cancer prevention questionnaire (Glanz et al., 2008). Given the change in population from high school 71

PAGE 72

students to college students, efforts were made to ensure validity and reliability by conducting cognitive intervi ews with college students, pilot testing the instrument, and having a panel of content experts annually review the respective health sections. In line with Healthy Campus 2020 recommendations, OCOH addresses the leading health indicators for college stu dents including: physical activity, overweight and obesity, tobacco use, substance abuse, responsible sexual behavior, mental health, injury and violence, environment, immunization and access to health care. And, there are additional questions covering ot her health behaviors spanning the six dimensions of wellness , including intellectual, emotional, spiritual and interpersonal health. When possible, question wording is used directly from CDC’s YRBSS for the purpose of national comparison research. All 16 ,343 undergraduate and graduate students enrolled at the university received an email invitation to participate over a four week period during the Fall 2013 semester. The survey was delivered through Qualtrics Survey Software (Qualtrics, Provo, UT) by the Institutional Research office ( as directed by the IRB ) to protect participant privacy. Following completion of the survey, participants had the option of clicking on a hyperlink to submit their name and email address to enter a raffle to win a variety of incentives to increase survey participation. All responses were deidentified prior to being shared with the PI. The extensive 121item survey yielded an 11% response rate with 1,774 participants. To be included in the study sample, participants must have been between the ages of 18 to 25 and responded to all demographic and variables of interest, which reduced the sample size to 747 (4.5% response rate) . 72

PAGE 73

After application of the sample inclusion criteria, the students were 21 years of age (M = 21.14, SD= 1.98), mostly female (73.6%), white (74.8%), in their third year of school (32.6%), and not working while in school (32.1%). See Table 4 1 for demographic characteristics. The sample was reflective of the overall population at the university with a l argely female (56.5%) and white (70.9%) student body. Nationally, public university undergraduates are 56.4% female, 63% white, and 59% did not work while in school ( U.S. Department of Education Institute of Education Sciences, 2014) Study Measures To operationalize the dependent variable, sunscreen use, the question “How often do you use sunscreen with an SPF of 15 or higher when you are outside on a warm sunny day?” was used. Responses were “never”, “rarely”, “sometimes”, “often”, or “always”. Consist ent with CDC guidelines (CDC, 2012) , adequate sunscreen use is considered answering ‘ often or ‘always’ to indicate regular use of sunscreen when outside on a sunny day. ‘Sometimes”, ‘rarely’, or ‘never’ are considered inadequate use. Responses were dichotomized into those answering “usually” and “always” wearing sunscreen when outside to be considered low risk and those answering “ never ” , “ rarely ” or “ sometimes ” considered high risk. The independent predictor variables included physical activity, smoking , alcohol and drug use, safety , and mental health. Independent variable dichotomization followed CDC methodology and is depicted in Table 4 3. Analysis Sunscreen prevalence rates prior to dichotomization into high and low risk by race, gender and age wer e calculated and reported in Table 4 2 . In bivariate analysis, Spearman Rho correlation examined the relationship between independent variable 73

PAGE 74

scale data to determine potential i ntercorrelations and no associations between variables were found that exceeded 0.54. Then , Pearson’s c hi square analysis was conducted between the dependent variable sunscreen use (low risk/high risk) and all dichotomized independent variables. Table 43 illustrates the results of chi square analysis of sunscreen use by health behavior risk. A multiple logistic regression analysis using backwards stepwise elimination was conducted in SPSS 19.1 on the statistically (p< 0. 05) and marginally significant (p< 0.08) variables identified in the chi square analysis . The Wald Statistic, standard error, corresponding p value, odds ratio , and confidence intervals of the final model are presented in Table 4 4. Results Overall sunscreen use was inadequate among respondents , with 66.3% reporting using sunscreen less than half the time when t hey were outside on a sunny day. Only 12.4% of students reported always using sunscreen. Gender (p = 0.000), age (p = 0.009) and ethnicity (p = 0.006) were significantly associated with sunscreen use. Males were significantly less likely to use sunscreen than females. Inadequate sunscreen use peaked among 18 to 20 year olds compared to those aged 21 to 25 (p = 0 . 009 ). White students were five times more likely to use sunscreen than Blacks and Hispanics demonstrated better sunscreen use than Blacks (p = 0.0 01 ). In bivariate analysis, binge drinking X2 (1, N = 747) = 12.254, p = .000, life satisfaction X2 (1, N = 747) = 12.240, p = .000, texting while driving X2 (1, N = 747) = 6.431, p < .011, depression X2 (1, N = 747) = 6.556, p = .010, and seatbelt us e X2 (1, N = 747) = 4.485, p = .034 were found to be significant. Marginally significant variables included driving after drinking X2 (1, N = 747) = 2.890, p = .089 and sadness during the past 30 days X2 (1, N = 747) = 2.972, p = .085. A backward stepwis e elimination 74

PAGE 75

logistic regression analysis was conducted to predict inadequate sunscreen use using binge drinking, life satisfaction, texting while driving, depression, seatbelt use, driving after drinking, past 30 day sadness, age, gender, and ethnicity as predictors. A test of the full model against a constant only model was statistically significant, indicating that the predictors as a set reliability distinguished between high risk and low risk sunscreen users (chi square = 71.452, p <.000 with df = 8) . Nagelkerke’s R2 of 0.126 indicates a slight relationship between prediction and grouping ; however , the pseudo R2 is not a good indicator for logistic regression. The Hosmer and Lemeshow statistic has a significance of 0.861, indicating it is not statis tically significant and our model is a good fit. Prediction success overall was 66.8% (31.7% low risk, 84.6% high risk). The Wald criterion demonstrated that gender (p = 0.000), ethnicity (p = 0.006), age (p = 0.009), texting while driving (p = 0.030), l ow life satisfaction (p = 0.001), and binge drinking (p = 0.005) significantly predicted inadequate sunscreen use. Past 30 day sadness, driving after drinking, depression, and seat belt use were not significant predictors. Past 30 day sadness was eliminated on step two, driving after drinking was eliminated on step three, depression was eliminated on step four, and seatbelt use was eliminated in step five. Males are more than two times more likely to not us e sunscreen than females; blacks are more than five times more likely than whites to not use sunscreen; and students between the ages of 18 and 20 are nearly two times more likely to not use sunscreen than students age 21 to 25. S tudents that text while driving are nearly two times more likely to not use sunscreen than those who don’t text while driving. T hose who binge drink are more than two times more likely to also not use sunscreen than those who do not regularly binge drink. Students reporting low life satisfaction are more 75

PAGE 76

than two times mor e likely to not use sunscreen than students reporting being satisfied with their life. Table 44 presents the odds ratios for all demographic and independent variables. Discussion The purpose of this study was to identify the other health risk behaviors associated with inadequate sunscreen use to provide a foundation for future interventions to target a variety of health risk behaviors. Consistent with other studies, this study found that sunscreen usage rates remain unacceptably low among college students. Further, b inge drinking, low life satisfaction, and texting while driving predicted poor sunscreen use. Males, blacks, and those under age 21 were also significantly more likely to engage in poor sunscreen behaviors. The demographic trends are cons istent with other findings. Similar trends in alcohol use correlates were found in studies examining other age groups. Adolescents that did not use sun protection were more likely to use alcohol (Coogan et al., 2001), and high school students that report ed never using sunscreen were m ore likely to consume alcohol (Hall et al., 2003). In a US study of more than 28,000 adults, men who consumed more than 15 drinks a week, and women who consumed more tha n eight drinks a week used less sunscreen than those considered low risk drinkers (Coups et al., 2008). To date, no other studies have included texting while driving or life satisfaction as correlates to sunscreen use so this represents two new findings that warrant further investiga tion. As behavioral correlates among college students, binge drinking and texting while driving share several important characteristics; both are widely recognized as high risk, both are socially acceptable despite the risks and texting while driving 76

PAGE 77

being illegal in most states , both are impulsive in nature, and both involve social interaction. While binge drinking is widespread across college campuses, the potential hazards are well documented and include unprotected sexual intercourse, being unable to recall having sex, missing classes and exams, driving drunk, serious bodily injury, rape, and assault ( H ingson et al., 2009) . Texting while driving does not have the long research history of binge drink ing given it did not become a health problem of concern until recently when smart phones became prolific and telephone communication dwindled in favor of text communication. Yet, many states have banned texting while operating a motor vehicle, a recent study found that 80% of college students text while driving (Lantz & Loeb, 2013). As a result, more than 1 , 000 people are injured in distracted driving accident s every day in the US (CDC, 2011), which has surpassed alcohol related crashes. Despite the warnings, college student’s desire to remain connected to their social life outweig h the risk. Problem Behavior Theory offers insight into the reciprocal relationship between binge drinking and texting while driving because the theory posits that the social life of young adults present the opportunities to learn behaviors and then social expectations reinforce them (DuRant et al., 1999) . There is a disconnect between perceived susceptibility of a negative outcome given the very clear social message that texting while driving and binge drinking is dangerous . The deliberate dismissal of these behaviors indicates a high risk individual more interested in social acceptance than their health. When examining life satisfaction’s role in predicting poor sunscreen use, it important to consider that life satisfaction is a subjective measure of happiness rather 77

PAGE 78

than a behavior and widely considered a cornerstone of mental health. Life satisfaction actually makes a lot of sense as a correlate of sunscreen use with binge drinking and texting while driving because of impression management, a social psychology construct. Within the realm of impression management, se lf presentation efforts are goal oriented to shape other ’s impressions of self during social occasions (Leary & Jones, 1993). Those with higher self presentation concerns will be more c oncerned about how they are perceived and alter their behavior to positively improve their social identity. People with high self presentation concerns tend to be high social monitors, publicly self aware, and hyper conscious . When people are more concer ned about what others think of them, rather than their own self view, they are more likely to experience lower life satisfaction (Leary & Jones, 1993). While it helpful to be aware of social image and public perception to adapt to new environments, constant vigilance about social judgment can negatively affect life satisfaction. Social influence appears to play a significant underlying role in the behavioral predictors (binge drinking, texting while driving, and low life satisfaction) of inadequate sunscr een use. This finding is important because t he results of this study can guide targeted interventions that focus on the latent psychological constructs of life satisfaction to address binge drinking, texting while driving , and sunscreen that are detriment al to the health and well being of college students. The results have long term implications to improve existing sun protection education programs that have been minimally effective at improving sunscreen adherence rates by aiming resources at the individ uals at most risk. Specifically, the US Community Preventive Services Taskforce (2013) has noted there are insufficient skin cancer prevention programs designed for a 78

PAGE 79

college audience and it is a significant area of need. The early identification of clus tered health risk behaviors offers public health professionals the opportunity to focus resources and programs on specific individuals at greater risk for a host of health behaviors, rather than a general audience. This will lead to more precise, cost effective interventions with better quality of life outcomes. Changing multiple health behaviors offers the opportunity to offer more significant quality of life outcomes, reduce healthcare utilization, and save money by using a bundled healthcare approach. This is becoming more essential given, the likelihood of having multiple health risk factors increases with age (Driskell et al. , 2008). Furthermore, targeting several risk behaviors aligns with the Affordable Care Act’s emphasis on efficient preventative care “bundled” in a clinical setting (Whitlock et al. , 2002; Ickovics, 2008). This study has a number of p otential limitations that should be considered. Although the sample size is robust, the response rate was low (roughly 4.5% after applying the incl usion criteria) given the lengthy survey was sent to all 16,343 students enrolled at the university. Although the response rate is low, the sample is remarkably reflective of the overall demographics of the university as reported by the University Institu tional Research Office. The convenience sampling methodology used limits generalizability although, as stated, the demographic characteristics of the sample were remarkably representative of the overall university profile. Male participation (26.4%) was lower than university male enrollment (43.5%) and that is consistent with survey response research findings that males are less likely than females to respond to online surveys (Curtin et al., 2002; Moore & Tarnai, 2002; Singer et al., 2000). Also, studies 79

PAGE 80

using self report surveys are subject to self report, self selection bias , and recall error (Olsen, 2008). Additionally, proper use of sun protective behaviors cannot adequately be assessed because there are nuances to sun protection, including amount o f sun screen used per application, frequency of reapplication, and environmental variables such as reflection from water when seeking shade. Also, the survey did not include questions about complexion, sun sensitivity , or family history of skin cancer – al l of which contribute to skin cancer risk. 80

PAGE 81

Table 41. Demographic characteristics of the study sample (n=747). Characteristic N Percent Sex Male Female 197 550 26.4 73.6 Age 18 19 20 21 22 23 24 25 74 103 123 140 110 88 66 43 9.9 13.8 16.5 18.7 14.7 11.8 8.8 5.8 Race/Ethnicity White Hispanic Black Bi/Multirace Other races 559 63 48 26 51 74.8 8.4 6.4 3.5 6.8 Classification Freshman Sophomore Junior Senior Graduate 131 114 244 195 63 17.6 15.3 32.6 26.1 8.4 Insurance Insured Uninsured Unsure 579 134 34 77.5 18.0 4.4 Hours worked per week I do not work 1 – 10 hours 11 – 20 hours 21 – 30 hours 31 – 40 hours More than 40 hours 238 84 152 144 98 31 31.9 11.2 20.4 19.3 13.1 4.2 Relationship status Single In a committed relationship Married Divorced/widowed/separated 269 418 54 6 36.0 56.0 7.2 .8 81

PAGE 82

Table 42. Sunscreen prevalence rates by race, gender and age (n=747). Sunscreen use while outsid e on a warm sunny day Always Often Sometimes Rarely Never Age 18 7 (7.5%) 10 (6.3%) 16 (9.6%) 21 (10.9%) 20 (14.7%) 19 6 (6.5%) 17 (10.7%) 22 (13.2%) 32 (16.7%) 26 (19.1%) 20 17 (18.3%) 26 (16.4%) 28 (16.8%) 34 (17.7%) 18 (13.2%) 21 17 (18.3%) 32 (20.1%) 30 (18.0%) 42 (21.9%) 19 (14.0%) 22 14 (15.1%) 28 (17.6%) 30 (18.0%) 18 (9.4%) 20 (14.7%) 23 12 (12.9%) 20 (12.6%) 21 (12.6%) 22 (11.5%) 13 (9.6%) 24 11 (11.8%) 15 (9.4%) 14 (8.4%) 16 (8.3%) 10 (7.4%) 25 9 (9.7%) 11 (6.9%) 6 (3.6%) 7 (3.6%) 10 (7.4%) Gender Female 83 (89.2%) 127 (79.9%) 130 (77.8%) 135 (70.3%) 75 (55.1%) Male 10 (10.8%) 32 (20.1%) 37 (22.2%) 57 (29.7%) 61 (44.9%) Ethnicity White 68 (73.1%) 135 (84.9%) 139 (83.2%) 138 (71.9%) 79 (58.1% ) Hispanic 10 (10.8%) 8 (5.0%) 11 (6.6%) 20 (10.4%) 14 (10.3%) Black 4 (4.3%) 1 (0.6%) 4 (2.4%) 12 (6.3%) 27 (19.9%) Multi race 2 (2.2%) 9 (5.7%) 5 (3.0%) 8 (4.2%) 2 (1.5%) Other 9 (9.7%) 6 (3.8%) 8 (4.8%) 14 (7.3%) 14 (10.3%) 82

PAGE 83

Table 43. Biv ariate analysis of sunscreen use by health risk behaviors (n=747). Health Risk Behavior Sunscreen Use* Adequate Inadequate p value Met Weekly Physical Activity Requirement 0.146 Met 148 (58.7%) 263 (53.1%) Not met 104 (41.3%) 232 (46.9%) Cig arette use during past 30 days 0.977 No 182 (72.2%) 357 (72.1%) Yes 70 (27.8%) 138 (27.9%) Frequency of binge drinking 0.000 Sometimes, rarely, or never 227 (90.1%) 396 (80.0%) Always or often 25 (9.9%) 99 (20.0%) Marijuana use during past three months 0.584 No 170 (67.5%) 324 (65.5%) Yes 82 (32.5%) 171 (34.5%) Cocaine use during past three months 0.534 No 240 (95.2%) 466 (94.1%) Yes 12 (4.8% 29 (5.9%) Methamphetamine use during past three months 0.375 No 251 (99.6%) 490 (99.0%) Yes 1 (0.4%) 5 (1.0%) Rx drug (w/o Rx) during past three months 0.358 No 229 (90.9% 439 (88.7%) Yes 23 (9.1%) 56 (11.3%) Lifetime sexual partners 0.506 Less than four 153 (60.7%) 288 (58.2%) More than four 99 (39.3%) 207 (41.8%) Condom use during last intercourse 0.861 Yes 122 (48.4%) 243 (49.1%) No 130 (51.6%) 252 (50.9%) Intercourse under the influence in past three months 0.370 No 139 (55.2%) 290 (58.6%) Yes 113 (44.8%) 205 (41.4%) Dr iving after Drinking Alcohol 0.089 No 230 (91.3% 431 (87.1%) Yes 22 (8.7%) 64 (12.9%) Use seatbelt Always or often 247 (98.0%) 469 (94.7%) 0.034 Sometimes, rarely, or never 5 (2.0%) 26 (5.3%) Text while Driving 0.011 Sometimes, rarely, or never 213 (84.5%) 379 (76.6%) Always or often 39 (15.5%) 116 (23.4%) Depression symptoms 0.010 No 168 (66.7%) 282 (57.0%) Yes 84 (33.3%) 213 (43.0%) Felt sad in the past 30 days 0.085 No 120 (47.6%) 203 (41.0%) Yes 132 (52.4%) 292 ( 59.0%) General life satisfaction 0.000 Very satisfied or satisfied 225 (89.3%) 391 (79.0%) Neither, dissatisfied, or very dissatisfied 27 (10.7%) 104 (21.0%) Anti depressant prescription or currently taking 0.700 No 215 (85 .3%) 417 (84.2%) Yes 37 (14.7%) 78 (15.8%) 83

PAGE 84

Table 44. Relationship between inadequate sunscreen use and selected health risk behaviors Wald S.E. p value OR 95% CI Health Risk Behavior Binge Drinking 7.986 0.248 0.005 2.017 1. 240 – 3.280 Texting while Driving 4.717 0.212 0.030 1.586 1.046 – 2.405 Low Life Satisfaction 10.443 0.239 0.001 2.167 1.356 – 3.464 Gender Female Ref* Ref* Ref* Ref* Male 14.963 0.202 0.000 2.187 1.471 – 3.252 Age 18 to 20 Ref* Ref* Ref* Ref* 21 to 25 6.756 0.169 0.009 1.553 1.114 – 2.164 Ethnicity White Ref* Ref* Ref* Ref* Black 11.380 0.488 0.001 5.181 1.992 – 13.475 Hispanic 0.222 0.266 0.637 1.134 0.673 – 1.909 Other 1.292 0.301 0.256 1.408 0.780 – 2.540 84

PAGE 85

CHAPTER 5 SUMMARY AND IMPLICATIONS Summary National skin cancer rates are at historically high levels and are continuing to increase particularly among young adults. T he overall goal of this study was to explore the prevalence and corr elates of sunscreen use with other risky behaviors among college students. The review of literature revealed there a relationship between skin cancer prevention behaviors and other health risks across the lifespan. The search also revealed a significant gap in studies examining the relationship between multiple health risk factors and UV exposure among college students. The limited studies conducted among college students focused on indoor tanning correlates; however, overall skin cancer prevention such as sunscreen use affects a greater proportion of college students and the general population. The dearth of studies examining skin cancer prevention behaviors other than indoor tanning among college students represents a glaring gap because as adolescents age, they are less likely to use sun protection and clustered risk behaviors increase making the college age span a critical time for intervention (Eaton et al. , 2012). The first aim i nvestigated the prevalence of sunscreen use and other skin cancer prev ention behaviors among college students. The study supported previous findings that college students are engaging in a variety of high risk skin cancer behaviors including excessive sun exposure, inadequate sun protection, and using indoor tanning. The m ajority did not regularly use sunscreen (66.3%) with only 12.4% reporting always using sunscreen when outside on a warm sunny day. Females were more lik ely to use sunscreen than males; however , females spent more time in the sun for tanning 85

PAGE 86

purposes (p<.05). More than half of the participants (53%) spent more than two hours outside during the previous summer , and 65% of participants reported at least one sunburn in the previous year. The findings help explain the rising melanoma rates among young people and revealed an important shift in sunscreen use. There was a dramatic increase in sunscreen use that started at age 21 continued to increase through age 25. Additionally, the study found the majority of students (79.4%) have never had a full body skin c heck by a healthcare professional. This finding exposes a disturbing oversight in our healthcare system given that melanoma is the most common form of cancer among adults ages 25 to 29 and the second most common cancer among 15 to 29 year olds (Bleyer et al., 2006). The second study explored the association between sunscreen use and the health risk factors responsible for the majority of mortality and morbidity among college students including physical activity, smoking, substanc e abuse, risky sexual ac tivity, unintentional injury, and mental health. White, female, students over the age of 21 were more likely to use sunscreen. In bivariate analysis, binge drinking , life satisfaction , texting while driving , depression, and seatbelt use were found to be significant. Marginally significant variables included driving after drinking and sadness during the past 30 days . The third study d etermined the predictive relationship between select variables with sunscreen use among college students . A backward st epwise elimination logistic regression analysis was conducted to predict inadequate sunscreen and past 30 day sadness, driving after drinking, depression, and seat belt use were not significant predictors. Past 30 day sadness was eliminated on step two, driving after drinking was 86

PAGE 87

eliminated on step three, depression was eliminated on step four, and seatbelt use was eliminated in step five. Males are more than two times more likely to not us e sunscreen than females; blacks are more than five times more l ikely than whites to not use sunscreen; and students between the ages of 18 and 20 are nearly two times more likely to not use sunscreen than students age 21 to 25. S tudents that text while driving are nearly two times more likely to not use sunscreen tha n those who don’t text while driving. T hose who binge drink are more than two times more likely to also not use sunscreen than those who do not regularly binge drink. Student reporting low life satisfaction are more than two times more likely to not use sunscreen than students reporting being satisfied with their life. Implications This study was the first to examine sunscreen use and other correlated health risk behaviors among college students through a comprehensive health behavior data instrument. The results identified the other health risk behaviors (texting while driving, binge drinking, and low life satisfaction) associated with poor sunscreen, thus, leading to a targeted intervention addresses a host of related behaviors detrimental to the heal th and well being of college students. There are limited theoretically based skin cancer prevention interventions for the college population. In fact, many of the existing UV education intervention focus on indoor tanning and the constructs are salient to appearance motivations rather than sun safety. This study is grounded in theory and takes a novel look at sunscreen use by examining the constellation of other health risk behaviors associated. By identifying these related health risk behaviors, targ eted interventions can be designed to improve a variety of behaviors among college students at highest risk. Approaching multiple 87

PAGE 88

health risk behaviors with one intervention is showing great promise in early studies with significant behavior change. Th e findings have long term implications to improve existing sun protection education programs that have been minimally effective at improving sunscreen adherence rates by aiming resources at the individuals at most risk. Specifically, the US Community Prev entive Services Taskforce has noted there are insufficient skin cancer prevention programs designed for a college audience and it is a significant area of need (2013). The early identification of clustered health risk behaviors offers public health profess ionals the opportunity to focus resources and programs on specific individuals at greater risk for a host of health behaviors, rather than a general audience. This will lead to more precise, cost effective interventions with better quality of life outcomes . 88

PAGE 89

REFERENCES Abroms, L., Jorgensen, C. M., Southwell, B. G., Geller, A. C., & Emmons, K. M. (2003). Gender differences in young adults' beliefs about sunscreen use. Health Education and Behavior, 30, 29 43. Agbai, O., Buster, K., Sanchez, M., Hernandez, C., Kundu, R., Chiu, M., & ... Lim, H. (2014). Skin cancer and photoprotection in people of color: a review and recommendations for physicians and the public. Journal of the American Academy of Dermatology, 70 (4), 748 762. doi:10.1016/j.jaad.2013.11.038. Aghassian, F. (2009). The tribulations of paleness. 100,000 Years of Beauty: Modernity/Globalisation. Paris: Gallimard , 215 217. Ahmedin, J., Siegel, R., Xu, J., & Ward, E. (2010). Cancer Statistics, 2010. Cancer Journal for Clinicians, 60, 288296 . AlexandreBidon, D. (2009). Beauty in his own image. 100,000 Years of Beauty: Classical Age/Confrontations. Paris: Gallimard , 48 53. Allgwer, A., Wardle, J., & Steptoe, A. (2001). Depressive symptoms, social support, and personal health behaviors in young men and women. Health Psychology, 20(3), 223 227. doi:10.1037/02786133.20.3.223 American Academy of Dermatology. (2013). DETECT skin cancer: Body mole map. Retrieved from http://www.aad.org/File%20Library/Global%20navigation /For%20the%20public/aad body mole map.pdf American Cancer Society. (2012). Cancer facts and figures. Retrieved from http://www.cancer.org/acs/groups/content/@epidemiologysurveilance/documents /document/acspc 031941.pdf American College Health Association. (2012). Healthy Ca mpus 2020. Retrieved from http://www.acha.org/HealthyCampus/about.cfm American College Health Association. (2006). American College Health AssociationNational College Health Assessment spring 2005 reference group data report. Journal of American College Health, 55 , 5 16. American College Health Association. (2008). National College Health Assessment Reference Group Executive Summary Fall 2008. Retrieved from http://www.acha ncha.org/docs/ACHANCHA_Reference_Group ExecutiveSummary_Fall2008.pdf. Ark sey, H. & O’Malley, L. (2005). Scoping studies: towards a methodological framework. International Journal of Social Research Methodology, 8(1), 19 32. 89

PAGE 90

Arria, A. M., Caldeira, K. M., O’Grady, K. E., Vincent, K. B., Fitzelle, D. B., Johnson, E. P., & Wis h, E. D. (2008). Drug exposure opportunities and use patterns among college students: Results of a longitudinal prospective cohort study. Substance Abuse, 29(4), 1938. Bagdasarov, Z., Banerjee, S., Greene, K., & Campo, S. (2008). Indoor tanning and pro blem behavior. Journal of American College Health, 56(5), 555 561. doi: 10.3200/jach.56.5.555562 Baronowski, T., Cullen, K. W., & Bassen Enguist, K. (1997). Transition out of high school: a time of increased cancer risk. Preventive Medicine, 6, 694 703. Bell, R., Wechsler, H., & Johnston, L. (1997). Correlates of college student marijuana use: results of an U.S. National Survey. Health and Social Behavior, 92(5), 571581. Bleyer, A., O’Leary, M., Barr, R., & Ries, L. A. G. (2006, May). Cancer epidemi ology in older adolescents and young adults 15 to 29 years of age, including SEER incidence and survival: 19752000. Bethesda, MD: National Cancer Institute. Boldeman, C., Jansson, B., Nilsson, B., & Ullen, H. (1997). Sun bed use in Swedish urban adolescents related to behavioral characteristics. Preventative Medicine, 26, 114119. Brener, N. D., & Collins, J. L. (1998). Cooccurrence of healthrisk behaviors among adolescents in the United States. Journal of Adolescent Health, 22(3), 209 213. Brile y, J. J., Lynfield, Y. L. & Chavda, K. (2007). Sunscreen use and usefulness in African Americans. Journal of Drugs in Dermatology, 6(1), 19 22. Brown, J. D. (1991). Staying fit and staying well: physical fitness as moderator of life stress. Journal of P ersonality and Social Psychology, 60 , 555 561. Buller, D. B., Reynolds, K. D., Ashley, J. L., Buller, M. K., Kane, I. L., Stabell, C. L., . . . Cutter, G. R. (2011). Motivating public school districts to adopt sun protection policies: a randomized control led trial. American Journal of Preventive Medicine, 41(3), 309 316. doi: 10.1016/j.amepre.2011.04.019 Centers for Disease Control and Prevention, Skin Cancer Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and H ealth Promotion. (2014). What is skin cancer? Retrieved from http://www.cdc.gov/cancer/skin/basic_info/what is skin cancer.htm. 90

PAGE 91

Centers for Disease Control and Prevention. (2012). Sunburn and sun protective behaviors among adults aged 18– 29 years, United States, 2000– 2010, MMWR. Morbidity and weekly reports. Retrieved from http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6118a1.htm Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion. (2004). Tobacco information and prevention source, tobacco use in the United States. Retrieved from http://www.cdc.gov/tobacco/data_statistics/fact_sheets/fast_facts/ Centers for Disease Control and Prevention. (2011). Mobile device use while driving — United States and seven European countries, MMWR . Retrieved from http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6210a1.htm?s_cid=mm6210a1 _w Chiolero, A., Wietlisbach, V., Ruffieux, C., Paccaud, F., & Cornuz, J. (2006). Clustering of risk behaviors with cigarett e consumption: A populationbased survey. Prevention Medicine, 42, 348 – 353. Choi, K., Lazovich, D., Southwell, B., Forster, J., Rolnick, S. J., & Jackson, J. (2010). Prevalence and characteristics of indoor tanning use among men and women in the United States. Archives of Dermatology, 146, 1356– 1361. Clayton, M. C., & Myers, E. (2009). Increasing seat belt use on a college campus: An evaluation of two prompting procedures. Journal of Applied Behavior Analysis, 42 (1), 161164. Cockburn, M. G., Zadnic k, J., & Deapen, D. (2006). Developing epidemic of melanoma in the Hispanic population of California. Cancer, 106, 1162 1168. Cokkinides, V. E., O’Connell, M. C., Thun, M. J., & Weinstock, M. A. (2002). Use of indoor tanning sunlamps by US youth, ages 11 18 years, and by their parent or guardian caregivers: Prevalence and correlates. Pediatrics, 109, 11241131. Coogan, P. F., Geller, A., Adams, M., Benjes, L. S., & Koh, H. K. (2001). Sun protection practices in preadolescents and adolescents: a school based survey of almost 25,000 Connecticut schoolchildren. Journal of American Acadamey of Dermatology, 44(3), 512 519. doi: 10.1067/mjd.2001.111621 Cottrell, R., McClamroch, L., & Bernard, A. (2005). Melanoma knowledge and sun protection attitudes and be haviors among college students by gender and skin type. American Journal of Health Education, 36(5), 274 279. Coups, E. J., Manne, S. L., & Heckman, C. J. (2008) Multiple skin cancer risk behaviors in the U.S. population. American Journal of Prevention Medicine, 34(2), 8793. 91

PAGE 92

Coyle, Y. M. (2009). Lifestyle, genes, and cancer. Methods Molecular Biology. 472 , 25 56. Craciun, C., Schz, N., Lippke, S., & Schwarzer, R. (2010). Risk perception moderates how intentions are translated into sunscreen use. J ournal of Behavioral Medicine, 33(5), 392 398. doi:10.1007/s1086501092695 Crews, D. J. & Landers, D. M. (1987). A metaanalytic review of aerobic fitness and reactivity to psychological stressors. Medicine and Science of Sports Exercise, 19, S114 S1 20. Cullen, K. W., Koehly, L. M., & Anderson, C. (1999). Gender differences in chronic disease behaviors through the transition out of high school. American Journal of Preventive Medicine, 17, 1 8. Curtin, R., Presser, S., & Singer, E. (2000). The effects of response rate changes on the index of consumer sentiment. Public Opinion Quarterly, 64, 413428. Davis, K. J., Cokkinides, V. E., Weinstock, M. A., O'Connell, M. C., & Wingo, P. A. (2002). Summer sunburn and sun exposure among US youths ages 11 t o 18: national prevalence and associated factors. Pediatrics, 110, 27 35. Demko, C. A., Borawski, E. A., Debanne, S. M., Cooper, K. D., & Stange, K. C. (2003). Use of indoor tanning facilities by white adolescents in the united states. Archives of Pediat ric Adolescent Medicine, 157(9), 854 860. doi: 10.1001/archpedi.157.9.854 Dennis, L. K., Lowe, J. B., Lynch, C. F., & Alavanja, C. R. (2008). Cutaneous melanoma and obesity in the Agricultural Health Study. Annals of Epidemiologoy, 18(3), 214221. doi: ht tp://dx.doi.org/10.1016/j.annepidem.2007.09.003 Diepgen, T. L., Mahler, V. (2002). The epidemiology of skin cancer. British Journal of Dermatology, 146(suppl 61),16. Dodd, L. J., & Forshaw, M. J. (2010). Assessing the efficacy of appearancefocused in terventions to prevent skin cancer: a systematic review of the literature. Health Psychology Review, 4 (2), 93 111. doi:10.1080/17437199.2010.485393 Douglas, K. A., Collin, J. L., Warren, C., Kann, L., Gold, R., Clayton, S., Kolbe, L. J. (1997). Resul ts from the 1995 national health risk behaviour survey. Journal of American College Health, 46 , 55 66. Driskell, M. M., Dyment S. J., Mauriello, L. M., Castle, P. H., & Sherman, K. J. (2008). Relationships among multiple behaviors for childhood and adolescent obesity prevention. Preventive Medicine, 46, 209 315. 92

PAGE 93

Duffy, S. A., Choi, S. H., Hollern, R., & Ronis, D. L. (2012). Factors associated with risky sun exposure behaviors among operating engineers. American Journal of Industrial Medicine, 55 (9), 78 6 792. doi: 10.1002/ajim.22079 DuRant, R. H., Smith, J. A., Kreiter, S. R., & Krowchuk, D. P. (1999). The relationship between early age of onset of initial substance use and engaging in multiple health risk behaviors among young adolescents. Archives of Pediatric Adolescenct Medicine, 153(3), 286 291. Eaton, D. K., Kann, L., Kinchen, S., Shanklin, S., Flint, K. H., Hawkins, J., Wechsler, H. (2012). Youth risk behavior surveillance—U nited States, 2011. MMWR Surveillance Summaries , 61(4), 1 162. Ezzedine, K., Malvy, D., Mauger, E., Nageotte, O., Galan, P., Hercberg, S., & Guinot, C. (2008). Artificial and natural ultraviolet radiation exposure: beliefs and behaviour of 7200 French a dults. Journal of European Academy Dermatology and Venereology, 22(2), 186 194. doi: 10.1111/j.14683083.2007.02367.x Falk, M., & Anderson, C. D. (2013). Influence of age, gender, educational level and self estimation of skin type on sun exposure habits and readiness to increase sun protection. Cancer Epidemiology, 37(2), 127 132. doi: 10.1016/j.canep.2012.12.006 Glanz, K., Yaroch, A. L., Dancel, M., Saraiya, M., Crane, L. A., & Buller, D. B. (2008). Measures of sun exposure and sun protection practices for behavioral and epidemiologic research. Archives of Dermatology, 144, 217 222. Gloster, H. M. & Neal, K. (2006). Skin cancer in skin of color. Journal of American Academy of Dermatology, 55, 741 760. Green, A., Williams, G., & Neale, R. (1999). Dai ly sunscreen application and betacarotene supplementation in prevention of basal cell and squamous cell carcinoma of the skin: a randomized controlled trial. Lancet, 354 (9180), 723 729. Green, A., Williams, G., Logan, V., & Strutton, G. (2011). Reduced melanoma after regular sunscreen use: randomized trial follow up. Journal of Clinical Oncology, 29(3), 257 263. Greene, K., Campo, S., & Banerjee, S. (2010). Comparing normative, anecdotal, and statistical risk evidence to discourage tanning bed us e. Communication Quarterly , 58(2), 111132. Hall, H. I. & Rogers, J. D. (1999). Sun protection behaviors among African Americans. Ethnicity and Disease, 9 (1), 126 131. 93

PAGE 94

Hall, H. I., Everett, J. S, & Saraiya, M. (2001). Prevalence and correlates of sunsc reen use among US high school students. Journal of School Health, 71(9), 453457. Hall, H. I., Saraiya, M., Thompson, T., Hartman, A., Glanz, K., & Rimer, B. (2003). Correlates of sunburn experiences among U.S. adults: results of the 2000 National Health Interview Survey. Public Health Report, 118(6), 540 549. Hamant, E. S., & Adams, B. B. (2005). Sunscreen use among collegiate athletes. Journal of American Academy of Dermatology, 53(2), 237 241. doi: http://dx.doi.org/10.1016/j.jaad.2005.04.056 Heckma n, C. J., Cohen Filipic, J., Darlow, S., Kloss, J. D., Manne, S. L., & Munshi, T. (2014). Psychiatric and Addictive Symptoms of Young Adult Female Indoor Tanners. American Journal Of Health Promotion, 28(3), 168174. Heckman, C. J., Coups, E. J., & Manne, S. L. (2011). Prevalence and correlates of indoor tanning among US adults. Journal of the American Academy of Dermatology, 58(5), 7697800. doi:10.1016/j.jaad.2008.01.020 Heckman, C.J, Darlow, S., CohenFilipic, J., Kloss, J., Manne, S., Munshi, T., & P erlis, C. (2012). Psychosocial correlates of sunburn among young adult women. International Journal of Environmental Research and Public Health, 9 (6), 22412251. doi:10.3390/ijerph9062241. Heckman, C. J., Manne, S. L., Kloss, J. D., Bass, S., Collins, B., & Lessin, S. R. (2011). Beliefs and intentions for skin protection and UV exposure in young adults. American Journal of Health Behavior, 35(6), 699711. Heckman, C., Egleston, B., Wilson, D., & Ingersoll, K. (2008). A preliminary investigation of the predictors of tanning dependence. American Journal of Health Behavior, 32(5), 451 464. Hillhouse, J. J., & Turrisi, R. (2002). Examination of the efficacy of an appearancefocused intervention to reduce UV exposure. Journal of Behavioral Medicine, 25( 4), 395409. Hillhouse, J., Stapleton, J., & Turrisi, R. (2005). Association of frequent indoor UV tanning with seasonal affective disorder. Archives of Dermatology, 141, 14651472. Hingson, R. W. Zha, W. & Weitzman, E. R. (2009). Magnitude of and tren ds in alcohol related mortality and morbidity among U.S. college students ages 18 to 24, 19982005. Journal of Studies on Alcohol and Drugs Supplement, 16 , 12 20. 94

PAGE 95

Hoffner, C., & Ye, J. (2009). Young adults' responses to news about sunscreen and skin ca ncer: the role of framing and social comparison. Health Communication, 24(3), 189198. doi:10.1080/10410230902804067 Holman, D. M., Berkowitz, Z., Guy, G. P., Hartman, A. M., & Perna, F. M. (2014). The association between demographic and behavioral characteristics and sunburn among U.S. adults — National Health Interview Survey, 2010. Preventive Medicine, 63(0), 6 12. doi: http://dx.doi.org/10.1016/j.ypmed.2014.02.018 Holt, R. (2009). The Victorian ideal. In: Azoulay E, Demain A, Frioux D., eds, 100, 000 Years of Beauty: Modernity/Globalisation. Paris: Gallimard Hu, S., Soza Vento, R. M., Parker, D. F., Kirsner, R. S. (2006). Comparison of stage at diagnosis of melanoma among Hispanic, black, and white patients in Miami Dade County, Florida. Archi ves of Dermatology, 142(6), 704 708. Ickovics, J. R. (2008). Bundling HIV prevention: integrating services to promote synergistic gain. Preventive Medicine, 46(3), 222225. International Agency for Research on Cancer Working Group on Artificial Ultraviolet (UV) Light and Skin Cancer. (2007). The association of use of sunbeds with cutaneous malignant melanoma and other skin cancers: A systematic review. International Journal of Cancer , 120(5), 11161122. Isaacowitz, D. M., & Choi, Y. (2012). Looking, feeling, and doing: are there age differences in attention, mood, and behavioral responses to skin cancer information? Health Psychology, 31(5), 650659. doi:10.1037/a0026666 Jardine, A., Brig ht, M., Knight, L., Perina, H., Vardon, P., & Harper, C. (2012). Does physical activity increase the risk of unsafe sun exposure? Health Promotion Journal of Australia, 23 (1), 52 57. Jemal, A., Devesa, S. S., Fears, T. R., & Hartge, P. (2000). Cancer s urveillance series: changing patterns of cutaneous malignant melanoma mortality rates among whites in the United States. Journal National Cancer Institute, 92, 811 818. Jessor, R. (1991). Risk behavior in adolescence: A psychosocial framework for under standing and action. Journal of Adolescent Health, 12 , 597 605. Jessor, R., Donovan, J. E., & Costa, F. M. (1991). Beyond adolescence: Problem behavior and young adult development. New York: Cambridge University Press. Karagas, M. (2002). Use of tanning devices and risk of basal cell and squamous cell skin cancers. Journal of the National Cancer Institute, 94(3), 224 226. 95

PAGE 96

Keesling, B., & Friedman, H. S. (1987). Psychosocial factors in sunbathing and sunscreen use. Health Psychology, 6(5), 477 493. Ki m, M., Boone, S. L., West, D. P., Rademaker, A. W., Liu, D., & Kundu, R. V. (2009). Perception of skin cancer risk by those with ethnic skin. Archives of Dermatological Research, 145(2), 207208. Kirkpatrick, C. S., White, E., & Lee, J. A. (1994). Case control study of malignant melanoma in Washington State. II. Diet, alcohol, and obesity. American Journal of Epidemiology, 139(9), 869 880. Koster, B., Thorgaard, C., Philip, A., & Clemmensen, I. H. (2010). Prevalence of sunburn and sunrelated behaviour in the Danish population: a cross sectional study. Scand Journal of Public Health, 38(5), 548552. doi: 10.1177/1403494810371250 Kourosh, A. S., Harrington, C. R., & Adinoff, B. (2010). Tanning as a behavioral addiction. American Journal of Drug & Alcohol Abuse, 36 (5), 284 290. Kvaavik, E., Meyer, H. E., & Tverdal, A. (2004). Food habits, physical activity and body mass index in relation to smoking status in 40 – 42 year old Norwegian women and men. Prevention Medicine, 38, 1 5. Lano, C. (2009). The colour of rank. 100,000 Years of Beauty: Classical Age/Confrontations. Paris: Gallimard , 245246 Lantz, G. & Loeb, S. (2013). An exploratory study of psychological tendencies related to texting while driving . International Journal of Sustainable Strategic Management , 4 (1), 39 49. LargoWight, E. (2005). Self presentation and health behavior. The Health Education Monograph Series, 22(2), 6 12. Lawler, S., Sugiyama, T., & Owen, N. (2007). Sun exposure concern, sun protection behaviors and physical acti vity among Australian adults. Cancer Causes Control, 18(9), 10091014. doi: 10.1007/s1055200790415 Lazovich, D., Forster, J., Sorensen, G., Emmons, K., Stryker, J., Demierre, M. F., . . . Remba, N. (2004). Characteristics associated with use or intenti on to use indoor tanning among adolescents. Archives of Pediatric Adolescent Medicine, 158(9), 918924. doi: 10.1001/archpedi.158.9.918 Leary, M. R., and Jones, J. L. (1993). The social psychology of tanning and sunscreen use: Self presentational motives as a predictor of health risk. Journal of Applied Social Psychology , 23, 13901406. 96

PAGE 97

Lee, T. K., MacArthur, A. C., Gallagher, R. P., & Elwood, M. J. (2009). Occupational physical activity and risk of malignant melanoma: the Western Canada Melanoma Study. Melanoma Research, 19(4), 260266. doi: 10.1097/CMR.0b013e32832e0bae Leiter, U. & Garbe, C. (2008). Epidemiology of melanoma and nonmelanoma skin cancer: The role of sunlight. Advances in Experimental Medicine and Biology , 624, 89103. Leon, G. R., Fulkerson, J. A., Perry, C. L., & Cudeck, R. (1993). Personality and behavioral vulnerabilities associated with risk status for eating disorders in adolescent girls. Journal of Abnormal Psychology, 102(3), 438 444. Levac, D., Colquhoum, H., & O’B rien, K. K. (2010). Scoping studies: advancing the methodology. Implementation Science, 5, 69 73. Mahler, H.I., Kulik, J.A., Gerrard, M., & Gibbons, F.X. (2006) Effects of two appearancebased interventions on the sun protection behaviors of Southern California each patrons. Basic and Applied Social Psychology , 28(3), 263 272. McCabe, S. E., Knight, C.J., Teter, H., & Wechsler, H. (2005). Non medical use of prescription stimulants among US college students: Prevalence and c orrelates from a national survey. Addiction, 100(96), 96106. McMichael, A. J. & Jackson, S. (2000). Issues in dermatologic health care delivery in minority populations. Dermatology Clinic, 18(2), 229 233. Merten, J. W. & Bosco, E. (2013). University of North Florida student heal th behavior survey executive summary. Jacksonville, FL: Author. Miyamoto, J., Berkowitz, Z., Jones, S. E., & Saraiya, M. (2012). Indoor tanning device use among male high school students in the United States. Journal of Adolescent Health, 50(3), 308310. doi: 10.1016/j.jadohealth.2011.08.007 Moore, D. L., & Tarnai, J. (2002). Evaluating nonresponse error in mail surveys. In: R. Groves, D. Dillman, J. Eltinge , & R. Little (E ds.), Survey n onresponse (pp. 197211) . New York, NY: John Wiley & Sons, Mosher , C. E., & Danoff Burg, S. (2010a). Addiction to indoor tanning: relation to anxiety, depression, and substance use. Archives of Dermatology, 146(4), 412417. doi: 10.1001/archdermatol.2009.385 Mosher, C. E., & Danoff Burg, S. (2010b). Indoor tanning, men tal health, and substance use among college students: the significance of gender. Journal of Health Psychology, 15 (6), 819 827. doi: 10.1177/1359105309357091 97

PAGE 98

Murphy, M. H. (2013). Health promotion in adolescent and young adult cancer survivors: mobilizin g compliance in a multifaceted risk profile. Journal of Pediatric Oncology Nursing, 30(3), 139145. doi:10.1177/1043454213486194 Must, A. M., Spadano, J., Coakley, E. H., Field, J. E., Colditz, G., & Dietz, W. H. (1999). The disease burden associated wi th overweight and obesity. Journal of the American Medical Association, 282(6), 1523 1529. Nahar, V. K. (2013). Skin cancer prevention among school children: A brief review. Central European Journal of Public Health, 21(4), 227 232. National Alliance on Mental Illness. (2012). College students speak: Survey report on mental health. Retrieved from www.nami.org/collegereport National Cancer Institute, National Institutes of Health, U.S. Department of Healt h and Human Services. (2010). Cancer trends progress report 2009/2010 update: Sun protection. Retrieved from http://progressreport.cancer.gov /doc_detail.asp ?pid=1&did=2009&chid=91&coid=911 National Institute on Alcohol Abuse and Alcoholism. (2013). College drinking. Retrieved from http://www.niaaa.nih.gov/alcohol health/special populations co occurring disorders /college drinking National Institute on Drug Abuse, National Institutes of Health, U.S. Department of Health and Human Services. (2011). Commonly abused drugs . Retrieved from http://www.hhs.gov/ash/oah/adolescent healthtopics/substance abuse/home.html National Institute on Mental Health. (2005). Mental illness exacts heavy toll, beginning in youth . Retrieved from http://www.nimh.nih.gov/sciencenews/2005/mental illness exacts heavy tollbeginning in youth.shtml. Obayan, B., Geller, A. C., Resnick, E. A, & Demeirre, M. F. (2010). Enacting legislation to restrict youth access to tanning beds: A survey of advocates and sponsoring legislators. Journal of the American Academy of Dermatology, 63(1), 63 70. O’Riordan, D. L., Field, A. E., Geller, A. C. (2006). Frequent tanning bed use, weight concerns, and other health risk behaviors in adolescent females in the US. Cancer Causes Control, 17(5), 679686. Olsen, R. (2008). Self selection bias. In P. Lavrakas (Ed.), Encyclopedia of survey research metho ds (pp. 809811). Thousand Oaks, CA: SAGE Publications, Inc. 98

PAGE 99

Parent, M. E., Rousseau, M. C., El Zein, M. L., Benoit, M. D., & Siemiatycki, J. (2011). Occupational and recreational physical activity during adult life and the risk of cancer among men. C ancer Epidemiology, 35(2), 151 159. doi:10.1016/j.canep.2010.09.004 Parkin, D. M., Mesher, D., & Sasieni, P. (2011). Cancers attributable to solar (ultraviolet) radiation exposure in the UK in 2010. British Journal of Cancer, 105 , 66 69. Patrick, K., C ovin, J. R., Fulop, M., Calfas, K., & Lovato, C. (1997). Health risk behaviors among California college students. Journal of American College Health, 45, 265 273. Pertruzello, S. J., Landers, D. M., Hatfield, B. D., Kubitz, K. A., & Salazar, W. (1991). A meta analysis on the anxiety reducing effects of acute and chronic exercise. American Journal of Sports Medicine, 11, 143 182. Pfahlberg, A., Kolmel, K. F., & Gefeller, O. (2001). Timing of excessive ultraviolet radiation and melanoma: epidemiology does not support the existence of a critical period of high susceptibility to solar ultraviolet radiationinduced melanoma. British Journal of Dermatology, 144(3), 471 480. Poorsattar, S. P., & Hornung, R. L. (2007). UV light abuse and highrisk tanning behavior among undergraduate college students. Journal of American Academy of Dermatology, 56(3), 375379. doi: http://dx.doi.org/10.1016/j.jaad.2006.08.064 Pothiawala, S., Qureshi, A. A., Li, Y., & Han, J. (2012). Obesity and the incidence of skin canc er in US Caucasians. Cancer Causes Control, 23(5), 717 726. doi: 10.1007/s105520129941x Powell, K. E. (1998). Habitual exercise and public health: An epidemiological view. Human Kinetics , 23, 15 40. Prochaska, J. O. (2008). Multiple health behavior research represents the future of preventive medicine. Preventive Medicine, 46 , 281 285. Prochaska, J. O., Velicer, W. F., Redding, C., Rossi, J. S., Goldstein, M., & DePue, J. (2005). Stagebased expert systems to guide a population of primary care pati ents to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms. Preventive Medicine, 41, 406 416. Prochaska, J. O., Velicer, W. F., Rossi, J. S., Redding, C. A., Greene, G. W., Rossi, S. R. (2004). Multiple risk expert systems Interventions: Impact of simultaneous stage matched expert system interventions for smoking, highfat diet, and sun exposure in a population of parents. Health Psychology, 23 , 503 516. 99

PAGE 100

Reed, K. B., Brewer, J. D., Lohse, C. M., Bringe, K. E., Pruit, C. N ., & Gibson, L.E. (2012). Increasing incidence of melanoma among young adults: an epidemiological study in Olmsted County, Minnesota. Mayo Clinic Proceedings , 87(4), 328 334. Reinsch, J. M., Hill, C. A., Sanders, S. A. & Davis, M. (1995). High risk sex ual behavior at a midwestern university: A confirmatory survey. Family Planning Perspective, 27, 7982. Renshaw, T. L, & Cohen, A. S. (2014). Life Satisfaction as a distinguishing indicator of college student functioning: Further validation of the twocontinua model of mental health. Social Indicators Research, 117(1), 319 334. doi: 10.1007/s1120501303427 Robinson, J. K. (2005). Sun exposure, sun protection, and Vitamin D. Journal of the American Medical Association, 294, 15411543. Rock, V. J., Ma larcer, A., Kahende, J. W., Asman, K., Husten,C., & Caraballo, R. (2007). Cigarette smoking among adults United States, 2006 . Morbidity & Mortality Weekly Report, 56, 11571161. Sacheck, J. M., Kuder, J. F., & Economos, C. D. (2010). Physical fitness , adiposity, and metabolic risk factors in young college students. Medical and Science of Sports Exercise, 42, 10391044. Sansone, R., & Sansone, L. (2010). Excessive tanning: some psychopathological explanations. Psychiatry, 7 (6), 13 16. Santmyire, B . R., Feldman, S. R., & Fleischer, A. B. (2001). Lifestyle highrisk behaviors and demographics may predict the level of participation in sunprotection behaviors and skin cancer primary prevention in the united states. Cancer, 92(5), 1315 1324. doi: 10 .1002/1097 0142(20010901)92:5<1315::AID CNCR1453>3.0.CO;2I Saraiya, M., Hall, H. I., & Uhler, R. J. (2002). Sunburn prevalence among adults in the United States, 1999. American Journal of Preventive Medicine, 23(2), 91 97. Schnohr, P., Gronbaek, M., Pe tersen, L., Hein, H. O., & Sorensen, T. I. (2005). Physical activity in leisure time and risk of cancer: 14year follow up of 28,000 Danish men and women. Scandanavian Journal of Public Health, 33(4), 244 249. doi: 10.1080/14034940510005752 Schuit, A. J., van Loon, A. J. M., Tijhuis, M., & Ocke, M. C. (2002) Clustering of lifestyle risk factors in a general adult population. Prevention Medicine, 35, 219 224. 100

PAGE 101

Shaw, K., Genat, H., O’Rourke, P., & Del Mar, C. (2006). Exercise for overweight or obesity. Coch rane Database System Review, 4, CD003817. Shors, A. R., Solomon, C., McTiernan, A., & White, E. (2001). Melanoma risk in relation to height, weight, and exercise in US. Cancer Causes Control, 12(7), 599606. Singer, E., van Hoewyk, J., & Maher, M. P. (2 000). Experiments with incentives in telephone surveys. Public Opinion Quarterly, 64, 171188. Spradlin, K., Bass, M., Hyman, W., & Keathley, R. (2010). Skin cancer: Knowledge, behaviors, and attitudes of college students. Southern Medical Journal, 103(1 0), 9991003. Strine, T. W., Chapman, D. P., Balluz, L. S., Moriarty, D. G., & Mokdad, A. H. (2008). The associations between life satisfaction and healthrelated quality of life, chronic illness, and health behaviors among U.S. community dwelling adults. Journal of Community Health, 33(1), 40 50. doi: 10.1007/s10900007 90664 Substance Abuse and Mental Health Services Administration. (2010a). Results from the 2009 national survey on drug use and health: Volume I. Summary of national findings . Retrieve d from http://www.samhsa.gov/data/2k9/2k9Resultsweb/ web/2k9results.pdf Substance Abuse and Mental Health Services Administration. (2010b). Mental health: What a difference student awareness makes. Retrieved from http://www.stopstigma.samhsa.gov/public ations/collegelife.aspx?printid=1&. Tang, J. Y., Henderson, M. T., Hernandez Boussard, T., Kubo, J., Desai, M., Sims, S. T., . . . Stefanick, M. L. (2013). Lower skin cancer risk in women with higher body mass index: the women's health initiative observat ional study. Cancer Epidemiology Biomarkers Prevention, 22(12), 24122415. doi: 10.1158/10559965.epi 13 0647 U.S. Cancer Statistics Working Group, US Department of Health and Human Services, CDC, National Cancer Institute. (2006). United States cancer s tatistics: 1999 2003 incidence and mortality web based report. Retrieved from http://www.cdc.gov/uscs. U.S. Community Preventive Services Task Force. (2013). Guide to community preventive services. Preventing skin cancer: high school and college based interventions . Retrieved from http:// www.thecommunityguide.org /cancer/skin/education policy/secondaryschools.html. U.S. Department of Agriculture and U.S. Department of Health and Human Services. (2010). Dietary guidelines for Americans . Retrieved f rom http://www.health.gov/ dietaryguidelines/dga2010/dietaryguidelines2010.pdf 101

PAGE 102

U.S. Department of Education Institute of Education Sciences National Center for Education Statistics. (2014). Characteristics of postsecondary students. Retrieved from http://nces.ed.gov/programs/coe/indicator_csb.asp U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. (2011). Healthy People 2020. Retrieved from http://www.healthypeo ple.gov . U.S. Department of Transportation, National Highway Traffic Safety Administration. (2010). Traffic safety facts: Highlights of 2009 motor vehicle crashes . Retrieved fromhttp://www nrd.nhtsa.dot.gov/Pubs/811363.PDF Watson, M., Holman, D., Fox , K., Guy, G., Seidenberg, A., Sampson, B., & ... Lazovich, D. (2013). Preventing skin cancer through reduction of indoor tanning: current evidence. American Journal of Preventive Medicine, 44(6), 682 689. doi:10.1016/j.amepre.2013.02.015. Weinstock, M. A ., Rossi, J. S., Redding, C. A., Maddock, J. E., & Cottrill, S. D. (2000). Sun protection behaviors and stages of change for the primary prevention of skin cancers among beachgoers in southeastern New England. Annual of Behavioral Medicine, 22(4), 286293. Weir, H., Marrett, L., Cokkinides, V., Barnholtz Sloan, J., Patel, P., Tai, E., & ... Ekwueme, D. (2011). Melanoma in adolescents and young adults (ages 1539 years): United States, 19992006. Journal of the American Academy of Dermatology, 65(5 Suppl 1 ), S38 S49. doi:10.1016/j.jaad.2011.04.038 White, K., Robinson, N., Young, R., Anderson, P., Hyde, M., Greenbank, S., Baskerville, D. (2008). Exploring young people's beliefs and images about sun safety. Youth Studies Australia, 27(4), 43 49. Whitloc k, E. P., Orleans, T., Pender, N. & Allan, J. (2002). Evaluating primary care behavioral counseling interventions: An evidencebased approach. American Journal of Preventive Medicine, 22(4), 267284. Whitmore, S. E., Morison, W. L., Potten, C. S., Chadw ick, C. (2001). Tanning salon exposure and molecular alterations. Journal of American Academy of Dermatology, 44, 775 780. Wichstrm, L. (1994). Predictors of Norwegian adolescents' sunbathing and use of sunscreen. Health Psychology, 13(5), 412420. doi : 10.1037/02786133.13.5.412 World Health Organization. (1995). Physical status: The use and interpretation of anthropometry. Retrieved from http://www.who.int/childgrowth/ publications/physical_status/en/ 102

PAGE 103

Yoo, J., & Kim, H. (2012). Adolescents' body ta nning behaviours: Influences of gender, body mass index, sociocultural attitudes towards appearance and body satisfaction. International Journal of Consumer Studies, 36(3), 360 366. doi:10.1111/j.14706431.2011.01009.x Zhang, M., Qureshi, A. A., Geller , A. C., Frazier, L., Hunter, D. J., & Han, J. (2012). Use of tanning beds and incidence of skin cancer. Journal of Clinical Oncology, 30(14), 15881593. doi: 10.1200/jco.2011.39.3652 103

PAGE 104

BIOGRAPHICAL SKETCH Julie Williams Merten is an Assistant Professor i n the Department of Public Health at the University of North Florida. Her primary appointment is directing the undergraduate Community Health Internship program. She served as the Faculty Advisor for Eta Sigma Gamma, the National Professional Health Educ ation Honorary for seven years and received the national Faculty Sponsor of the Year Award in 2011. She served on the Board of Associate Editors for the American Journal of Health Education and is currently working with undergraduate students on a Transformational Learning Opportunity (TLO) funded research project, Our Campus, Our Health: A College Health Assessment analyzing the health risk behaviors of the UNF student body. She was the 2008 recipient of the Brooks College of Health Teaching Award and received a 2010 Community Scholar Award through the Center for Community Based Learning . Her current research includes skin cancer prevention and sun safety education. She chairs the Northeast Florida Cancer Control Collaborative Sun Safety workgroup to im prove skin cancer prevention efforts in the Northeast Florida community. 104