title: Risk of Cardiovascular Disease from Cumulative Cigarette Use and the Impact of Smoking Intensity.
abstract: BACKGROUND
  Relative risks (RRs) for cardiovascular disease (CVD) by smoking rate exhibit a concave pattern, with RRs in low rate smokers exceeding a linear extrapolation from higher rate smokers. However, cigarettes/day does not by itself fully characterize smoking-related risks. A reexamination of the concave pattern using a comprehensive representation of smoking may enhance insights.
  
  
  METHODS
  Data were from the Atherosclerosis Risk in Communities (ARIC) Study, a prospective cohort enrolled in four areas of the US in 1987-1989. Follow-up was through 2008. Analyses included 14,233 participants, 245,915 person-years, and 3,411 CVD events.
  
  
  RESULTS
  The concave RRs with cigarettes/day were consistent with cigarettes/day modifying a linear RR association of pack-years with CVD (i.e., strength of the pack-years association depended on cigarettes/day, indicating that the manner of pack-years accrual impacted risk). Smoking fewer cigarettes/day for longer duration was more deleterious than smoking more cigarettes/day for shorter duration (P < 0.01). For 50 pack-years (365,000 cigarettes), estimated RRs of CVD were 2.1 for accrual at 20 cigarettes/day and 1.6 for accrual at 50 cigarettes/day. Years since smoking cessation did not alter the diminishing strength of association with increasing cigarettes/day. Analyses that accounted for competing risks did not affect findings.
  
  
  CONCLUSIONS
  Pack-years remained the primary determinant of smoking-related CVD risk; however, accrual influenced RRs. For equal pack-years, smoking fewer cigarettes/day for longer duration was more deleterious than smoking more cigarettes/day for shorter duration. This observation provides clues to better understanding the biological mechanisms, and reinforces the importance of cessation rather than smoking less to reduce CVD risk.
authors.affiliation: From the aScientist Emeritus, Biostatistics Branch, Division of Cancer Epidemiology and Genetics, US National Cancer Institute, National Institutes of Health, Bethesda, MD; bClinical Professor and Deputy Director, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC; cAssistant Professor, Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN; dProfessor of Biostatistics, The George Institute for Global Health, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; eThe George Institute for Global Health, University of Sydney, Sydney, NSW, Australia; fDepartment of Epidemiology, Johns Hopkins University, Baltimore, MD; gProfessor, Department of Public Health, Fujita Health University School of Medicine Toyoake Aichi, Japan; and hProfessor, School of Public Health, Curtin University, Perth, Australia.
authors.forename: Jay H
authors.initials: JH
authors.lastname: Lubin
authors.forename: David
authors.initials: D
authors.lastname: Couper
authors.forename: Pamela L
authors.initials: PL
authors.lastname: Lutsey
authors.forename: Mark
authors.initials: M
authors.lastname: Woodward
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Yatsuya
authors.forename: Rachel R
authors.initials: RR
authors.lastname: Huxley
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016012:Poisson Distribution; D011446:Prospective Studies; D012044:Regression Analysis; D012306:Risk; D012307:Risk Factors; D012907:Smoking / Q000453:epidemiology*; D016540:Smoking Cessation; D013997:Time Factors; D062789:Tobacco Products / Q000706:statistics & numerical data*; D014481:United States / Q000453:epidemiology