Customize your JAMA Network experience by selecting one or more topics from the list below.
Navar AM, Peterson ED, Wojdyla D, et al. Temporal Changes in the Association Between Modifiable Risk Factors and Coronary Heart Disease Incidence. JAMA. 2016;316(19):2041–2043. doi:10.1001/jama.2016.13614
Diagnosis and control of coronary heart disease (CHD) risk factors have received particular emphasis in guidelines issued since 1977 (blood pressure) and 1985 (lipids).1,2 Yet on a population level, little is known about how these efforts have altered CHD incidence and its association with modifiable risk factors. This study explored (1) how the associations between modifiable risk factors and CHD events changed from 1983 through 1995 and from 1996 through 2011, and (2) during this timeframe, whether the population attributable fractions (PAFs) of CHD due to modifiable risk factors were altered.
Individual patient-level data from 5 observational cohort studies (Table) available in the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) were pooled.3 Two analytic data sets were created: 1 set with baseline data collected from 1983 through 1990 (early era) with follow-up from 1996 through 2001 and 1 set with baseline data collected from 1996 through 2002 (late era) with follow-up from 2007 through 2011. Participants aged 40 to 79 years who were free of cardiovascular disease were selected from each era and matched on age (within 2 years), race (black vs nonblack), and sex. Each cohort was followed for up to 12 years for new-onset CHD (ie, myocardial infarction, coronary death, angina, coronary insufficiency) using outcomes available in BioLINCC. A piecewise constant hazards model adjusted for age, sex, and race was used to estimate the hazard ratios (HRs) of CHD due to systolic blood pressure (SBP), diabetes, smoking (current or within past year), and total to high-density lipoprotein cholesterol (total:HDL-C) ratio.4 Blood pressure and total cholesterol were adjusted for treatment using a nonparametric approach.5 HRs were compared by testing the interaction between risk factor and era. PAFs were computed and compared using 10-year survival probabilities from the model with CIs derived using the delta method and log transformation.6 Analysis was approved by the Duke University institutional review board and conducted using SAS (SAS Institute), version 9.4. Statistical significance used 2-sided α of .05.
Create a personal account or sign in to: