title: Sun damage in ultraviolet photographs correlates with phenotypic melanoma risk factors in 12-year-old children.
abstract: BACKGROUND
  Ultraviolet (UV) photography has been used to motivate sun safety in behavioral interventions. The relationship between sun damage shown in UV photographs and melanoma risk has not been systematically investigated.
  
  
  OBJECTIVE
  To examine the relationship between severity of sun damage in UV photographs and phenotypic melanoma risk factors in children.
  
  
  METHODS
  UV, standard visible and cross-polarized photographs were recorded for 585 children. Computer software quantified sun damage. Full-body nevus counts, skin color by colorimetry, facial freckling, hair and eye color were collected in skin examinations. Demographic data were collected in telephone interviews of parents.
  
  
  RESULTS
  Among 12-year-old children, sun damage shown in UV photographs correlated with phenotypic melanoma risk factors. Sun damage was greatest for children who were non-Hispanic white and those who had red hair, blue eyes, increased facial freckling, light skin and greater number of nevi (all P values < .001). Results were similar for standard visible and cross-polarized photographs. Freckling was the strongest predictor of sun damage in visible and UV photographs. All other phenotypic melanoma risk factors were also predictors for the UV photographs.
  
  
  CONCLUSIONS
  Differences in software algorithms used to score the photographs could produce different results.
  
  
  CONCLUSIONS
  UV photographs portray more sun damage in children with higher risk for melanoma based on phenotype. Therefore sun protection interventions targeting those with greater sun damage on UV photographs will target those at higher melanoma risk. This study establishes reference ranges dermatologists can use to assess sun damage in their pediatric patients.
authors.affiliation: Department of Dermatology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
authors.forename: Ryan G
authors.initials: RG
authors.lastname: Gamble
authors.forename: Nancy L
authors.initials: NL
authors.lastname: Asdigian
authors.forename: Jenny
authors.initials: J
authors.lastname: Aalborg
authors.forename: Victoria
authors.initials: V
authors.lastname: Gonzalez
authors.forename: Neil F
authors.initials: NF
authors.lastname: Box
authors.forename: Laura S
authors.initials: LS
authors.lastname: Huff
authors.forename: Anna E
authors.initials: AE
authors.lastname: Barón
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Morelli
authors.forename: Stefan T
authors.initials: ST
authors.lastname: Mokrohisky
authors.forename: Lori A
authors.initials: LA
authors.lastname: Crane
authors.forename: Robert P
authors.initials: RP
authors.lastname: Dellavalle
mesh_terms: D000465:Algorithms; D002648:Child; D015331:Cohort Studies; D005145:Face; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008545:Melanoma / Q000453:epidemiology* / Q000473:pathology / Q000517:prevention & control; D008548:Melanosis / Q000453:epidemiology / Q000473:pathology; D009506:Nevus / Q000453:epidemiology / Q000473:pathology; D010641:Phenotype; D010781:Photography / Q000379:methods*; D012307:Risk Factors; D012720:Severity of Illness Index; D015595:Skin Aging / Q000473:pathology*; D012878:Skin Neoplasms / Q000453:epidemiology* / Q000473:pathology / Q000517:prevention & control; D012880:Skin Pigmentation; D012984:Software; D013472:Sunlight / Q000009:adverse effects*; D014466:Ultraviolet Rays / Q000009:adverse effects