title: Age and gender specific lung function predictive equations provide similar predictions for both a twin population and a general population from age 6 through adolescence.
abstract: BACKGROUND
  There have been numerous studies of asthma in twins, but no study has evaluated whether lung function predictive models yield similar results between twin and general populations. We sought to evaluate this in late childhood and adolescent subjects.
  
  
  METHODS
  We generated cross-sectional, sex- and age-specific regression models of FEV(1), and FVC, in a community-based cohort of 3140 healthy, non-smoking Chinese twins using generalized estimating equations to adjust for correlations within twin pairs. We applied the model to a healthy non-smoking general population cohort of 2187 subjects from the same region, and compared %predicted FEV(1) and FVC values between the two populations.
  
  
  RESULTS
  Stratified by age and sex, the associations of height with FEV(1) or FVC varied by age group. During the adolescent growth spurt (age 13 for girls and ages 14-16 for boys), the associations of height with FEV(1) or FVC were nonlinear and greater than that seen at other ages. During adolescence, FEV(1) and FVC for a given height increased with age. The percent predicted values of FEV(1) and FVC in the twin population were similar to that of the general population.
  
  
  CONCLUSIONS
  Twin and general populations have similar patterns of lung function change over middle childhood and adolescence. Similar equations may be used to estimate percent predicted values. Finally, a single prediction equation cannot completely describe patterns of lung function from childhood through adolescence due to puberty related changes.
authors.affiliation: Mary Ann and J Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Children's Memorial Hospital and Children's Memorial Research Center, Chicago, IL 60614, USA.
authors.forename: Yunxian
authors.initials: Y
authors.lastname: Yu
authors.forename: Rajesh
authors.initials: R
authors.lastname: Kumar
authors.forename: Scott
authors.initials: S
authors.lastname: Venners
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Pongracic
authors.forename: Binyan
authors.initials: B
authors.lastname: Wang
authors.forename: Jianhua
authors.initials: J
authors.lastname: Yang
authors.forename: Zhiping
authors.initials: Z
authors.lastname: Li
authors.forename: Liuliu
authors.initials: L
authors.lastname: Wang
authors.forename: Xue
authors.initials: X
authors.lastname: Liu
authors.forename: Genfu
authors.initials: G
authors.lastname: Tang
authors.forename: Houxun
authors.initials: H
authors.lastname: Xing
authors.forename: Xiping
authors.initials: X
authors.lastname: Xu
authors.forename: Xiaobin
authors.initials: X
authors.lastname: Wang
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D002648:Child; D002681:China; D003430:Cross-Sectional Studies; D005260:Female; D005541:Forced Expiratory Volume; D006801:Humans; D008297:Male; D015233:Models, Statistical; D011237:Predictive Value of Tests; D012737:Sex Factors; D014797:Vital Capacity