title: Strategies for combining and scaling sexual maturity indicators: the Heartfelt Study.
abstract: OBJECTIVE
  To identify the best variable or combination of sexual maturity variables to use in investigations of adolescent health, and explore possible re-scaling of five-stage sexual maturity stages into dummy variables' ('advanced'/'delayed').
  
  
  METHODS
  Cross-sectional.
  
  
  METHODS
  Tri-ethnic sample of 384 US adolescents 11-16 years of age (Heartfelt Study).
  
  
  METHODS
  Sexual maturity variables are genital. breast and pubic hair stages obtained by clinical examination by nurse practitioners, testes size, menarche and age at menarche.
  
  
  RESULTS
  Principal factor analysis of sexual maturity variables, height and age, revealed high commonality among the variables, as no more than a single factor appeared in 27 of 28 factor analyses (by sex and age groups). Genital stage (boys) and breast stage (girls) were most highly related to the first principal factor independent of age and ethnicity. ANOVA of 'key variables' indirectly reflecting endocrine function suggested that some stages could be combined.
  
  
  CONCLUSIONS
  A single variable should suffice to describe sexual maturity at the studied ages, or variables could be combined in a (unstandardized) sexual maturity index (SMI): SMI (Girls)=0.998 x BREAST+0.900 x PUBIC HAIR + 1.815 x YEARS SINCE MENARCHE. SMI (Boys)= 1.104 x GENITAL + 1.328 x PUBIC HAIR + 5.997 x TESTES SIZE (mL).
authors.affiliation: University of Texas Health Science Center-Houston, School of Public Health and School of Nursing, 77225, USA. wmueller@sph.uth.tmc.edu
authors.forename: W H
authors.initials: WH
authors.lastname: Mueller
authors.forename: S D
authors.initials: SD
authors.lastname: Cho
authors.forename: J C
authors.initials: JC
authors.lastname: Meininger
authors.forename: P
authors.initials: P
authors.lastname: Liehr
authors.forename: W
authors.initials: W
authors.lastname: Chan
mesh_terms: D000293:Adolescent; D000367:Age Factors; D000704:Analysis of Variance; D001827:Body Height / Q000502:physiology; D001940:Breast / Q000254:growth & development; D002648:Child; D003430:Cross-Sectional Studies; D005163:Factor Analysis, Statistical; D005260:Female; D005836:Genitalia, Female / Q000254:growth & development; D005837:Genitalia, Male / Q000254:growth & development; D006197:Hair / Q000254:growth & development; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D008432:Mathematical Computing; D008572:Menarche / Q000502:physiology; D012737:Sex Factors; D012741:Sexual Maturation / Q000502:physiology*