title: The effect of cardiorespiratory fitness on age-related lipids and lipoproteins.
abstract: BACKGROUND
  Evidence on the effect of cardiorespiratory fitness (CRF) on age-related longitudinal changes of lipids and lipoproteins is scarce.
  
  
  OBJECTIVE
  This study sought to assess the longitudinal aging trajectory of lipids and lipoproteins for the life course in adults and to determine whether CRF modifies the age-associated trajectory of lipids and lipoproteins.
  
  
  METHODS
  Data came from 11,418 men, 20 to 90 years of age, without known high cholesterol, high triglycerides, cardiovascular disease, and cancer at baseline and during follow-up from the Aerobics Center Longitudinal Study. There were 43,821 observations spanning 2 to 25 health examinations (mean 3.5 examinations) between 1970 and 2006. CRF was quantified by a maximal treadmill exercise test. Marginal models using generalized estimating equations were applied.
  
  
  RESULTS
  Total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides, and non-high-density lipoprotein cholesterol (non-HDL-C) presented similar inverted U-shaped quadratic trajectories with aging: gradual increases were noted until age mid-40s to early 50s, with subsequent declines (all p < 0.0001). Compared with men with higher CRF, those with lower CRF developed abnormal values earlier in life: TC (≥200 mg/dl), LDL-C (≥130 mg/dl), non-HDL-C (≥160 mg/dl), and triglycerides/HDL-C ratio (≥3.0). Notably, abnormal values for TC and LDL-C in men with low CRF were observed around 15 years earlier than in those with high CRF. After adjusting for time-varying covariates, a significant interaction was found between age and CRF in each trajectory, indicating that CRF was more strongly associated with the aging trajectories of lipids and lipoproteins in young to middle-age men than in older men.
  
  
  CONCLUSIONS
  Our investigation reveals a differential trajectory of lipids and lipoproteins with aging according to CRF in healthy men and suggests that promoting increased CRF levels may help delay the development of dyslipidemia.
authors.affiliation: Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina.
authors.forename: Yong-Moon Mark
authors.initials: YM
authors.lastname: Park
authors.affiliation: Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina. Electronic address: msui@mailbox.sc.edu.
authors.forename: Xuemei
authors.initials: X
authors.lastname: Sui
authors.affiliation: Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina.
authors.forename: Junxiu
authors.initials: J
authors.lastname: Liu
authors.affiliation: Department of Statistics, College of Arts and Sciences, University of South Carolina, Columbia, South Carolina.
authors.forename: Haiming
authors.initials: H
authors.lastname: Zhou
authors.affiliation: Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina; Cardiology Department, Veterans Affairs Medical Center, and Georgetown University School of Medicine, Washington, DC.
authors.forename: Peter F
authors.initials: PF
authors.lastname: Kokkinos
authors.affiliation: John Ochsner Heart and Vascular Institute, Ochsner Clinical School, University of Queensland School of Medicine, New Orleans, Louisiana.
authors.forename: Carl J
authors.initials: CJ
authors.lastname: Lavie
authors.affiliation: Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina.
authors.forename: James W
authors.initials: JW
authors.lastname: Hardin
authors.affiliation: Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina; Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina.
authors.forename: Steven N
authors.initials: SN
authors.lastname: Blair
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000097:blood*; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology / Q000517:prevention & control*; D006304:Health Status; D006801:Humans; D015994:Incidence; D008055:Lipids / Q000097:blood*; D008074:Lipoproteins / Q000097:blood*; D008297:Male; D008875:Middle Aged; D010809:Physical Fitness / Q000502:physiology*; D012189:Retrospective Studies; D012307:Risk Factors; D015996:Survival Rate / Q000639:trends; D013781:Texas / Q000453:epidemiology; D055815:Young Adult
chemical_list: D008055:Lipids; D008074:Lipoproteins
keywords: aging; lipid profile trajectories; longitudinal study