Association between glycemic index and glycemic load and the risk of incident coronary heart disease among whites and African Americans with and without type 2 diabetes: The Atherosclerosis Risk in Communities study

Several studies have examined the association between high glycemic index (GI) and glycemic load (GL) diets and the risk for coronary heart disease (CHD). However, most of these studies were conducted primarily on white populations. The primary aim of this study was to examine whether high GI and GL diets are associated with increased risk for developing CHD in whites and African Americans, non-diabetics and diabetics, and within stratifications of body mass index (BMI) and hypertension (HTN). Baseline and 17-year follow-up data from ARIC (Atherosclerosis Risk in Communities) study was used. The study population (13,051) consisted of 74% whites, 26% African Americans, 89% non-diabetics, 11% diabetics, 43% male, 57% female aged 44 to 66 years at baseline. Data from the ARIC food frequency questionnaire at baseline were analyzed to provide GI and GL indices for each subject. Increases of 25 and 30 units for GI and GL respectively were used to describe relationships on incident CHD risk. Adjusted hazard ratios for propensity score with 95% confidence intervals (CI) were used to assess associations. During 17 years of follow-up (1987 to 2004), 1,683 cases of CHD was recorded. Glycemic index was associated with 2.12 fold (95% CI: 1.05, 4.30) increased incident CHD risk for all African Americans and GL was associated with 1.14 fold (95% CI: 1.04, 1.25) increased CHD risk for all whites. In addition, GL was also an important CHD risk factor for white non-diabetics (HR=1.59; 95% CI: 1.33, 1.90). Furthermore, within stratum of BMI 23.0 to 29.9 in non-diabetics, GI was associated with an increased hazard ratio of 11.99 (95% CI: 2.31, 62.18) for CHD in African Americans, and GL was associated with 1.23 fold (1.08, 1.39) increased CHD risk in whites. Body mass index modified the effect of GI and GL on CHD risk in all whites and white non-diabetics. For HTN, both systolic blood pressure and diastolic blood pressure modified the effect on GI and GL on CHD risk in all whites and African Americans, white and African American non-diabetics, and white diabetics. Further studies should examine other factors that could influence the effects of GI and GL on CHD risk, including dietary factors, physical activity, and diet-gene interactions. ^

Systematic review of genetic risk score in coronary heart disease and other diseases

In order to better take advantage of the abundant results from large-scale genomic association studies, investigators are turning to a genetic risk score (GRS) method in order to combine the information from common modest-effect risk alleles into an efficient risk assessment statistic. The statistical properties of these GRSs are poorly understood. As a first step toward a better understanding of GRSs, a systematic analysis of recent investigations using a GRS was undertaken. GRS studies were searched in the areas of coronary heart disease (CHD), cancer, and other common diseases using bibliographic databases and by hand-searching reference lists and journals. Twenty-one independent case-control studies, cohort studies, and simulation studies (12 in CHD, 9 in other diseases) were identified. The underlying statistical assumptions of the GRS using the experience of the Framingham risk score were investigated. Improvements in the construction of a GRS guided by the concept of composite indicators are discussed. The GRS will be a promising risk assessment tool to improve prediction and diagnosis of common diseases.^

POLYCHOTOMOUS LOGISTIC REGRESSION ANALYSIS (HYPERTENSION, CORONARY HEART DISEASE)

The history of the logistic function since its introduction in 1838 is reviewed, and the logistic model for a polychotomous response variable is presented with a discussion of the assumptions involved in its derivation and use. Following this, the maximum likelihood estimators for the model parameters are derived along with a Newton-Raphson iterative procedure for evaluation. A rigorous mathematical derivation of the limiting distribution of the maximum likelihood estimators is then presented using a characteristic function approach. An appendix with theorems on the asymptotic normality of sample sums when the observations are not identically distributed, with proofs, supports the presentation on asymptotic properties of the maximum likelihood estimators. Finally, two applications of the model are presented using data from the Hypertension Detection and Follow-up Program, a prospective, population-based, randomized trial of treatment for hypertension. The first application compares the risk of five-year mortality from cardiovascular causes with that from noncardiovascular causes; the second application compares risk factors for fatal or nonfatal coronary heart disease with those for fatal or nonfatal stroke. ^

Effect of smoking on the association between periodontitis and incidence of coronary heart disease: The Atherosclerosis Risk in Communities Study

Multiple studies have shown an association between periodontitis and coronary heart disease due to the chronic inflammatory nature of periodontitis. Also, studies have indicated similar risk factors and patho-physiologic mechanisms for periodontitis and CHD. Among these factors, smoking has been the most discussed common risk factor and some studies suggested the periodontitis - CHD association to be largely a result of confounding due to smoking or inadequate adjustment for it. We conducted a secondary data analysis of the Dental ARIC Study, an ancillary study to the ARIC Study, to evaluate the effect of smoking on the periodontitis - CHD association using three periodontitis classifications namely, BGI, AAP-CDC, and Dental-ARIC classification (Beck et al 2001). We also compared these results with edentulous ARIC participants. Using Cox proportional hazard models, we found that the individuals with the most severe form of periodontitis in each of the three classifications (BGI: HR = 1.56, 95%CI: 1.15 – 2.13; AAP-CDC: HR = 1.42, 95%CI: 1.13 – 1.79; and Dental-ARIC: HR = 1.49, 95%CI: 1.22 – 1.83) were at a significantly higher risk of incident CHD in the unadjusted models; whereas only BGI-P3 showed statistically significant increased risk in the smoking adjusted models (HR = 1.43, 95%CI: 1.04 – 1.96). However none of the categories in any of the classifications showed significant association when a list of traditional CHD risk factors was introduced into the models. On the other hand, edentulous participants showed significant results when compared to the dentate ARIC participants in the crude (HR = 1.56, 95%CI: 1.34 – 1.82); smoking adjusted (HR = 1.39, 95%CI: 1.18 – 1.64) age, race and sex adjusted (HR = 1.52, 95%CI: 1.30 – 1.77); and ARIC traditional risk factors (except smoking) adjusted (HR = 1.27, 95%CI: 1.02 – 1.57) models. Also, the risk remained significantly higher even when smoking was introduced in the age, sex and race adjusted model (HR = 1.38, 95%CI: 1.17 – 1.63). Smoking did not reduce the hazard ratio by more than 8% when it was included in any of the Cox models. ^ This is the first study to include the three most recent case definitions of periodontitis simultaneously while looking at its association with incident coronary heart disease. We found smoking to be partially confounding the periodontitis and coronary heart disease association and edentulism to be significantly associated with incident CHD even after adjusting for smoking and the ARIC traditional risk factors. The difference in the three periodontitis classifications was not found to be statistical significant when they were tested for equality of the area under their ROC curves but this should not be confused with their clinical significance.^

Analysis of interval -censored events in hypertension studies: Evaluation of treatment of coronary heart disease

Many statistical studies feature data with both exact-time and interval-censored events. While a number of methods currently exist to handle interval-censored events and multivariate exact-time events separately, few techniques exist to deal with their combination. This thesis develops a theoretical framework for analyzing a multivariate endpoint comprised of a single interval-censored event plus an arbitrary number of exact-time events. The approach fuses the exact-time events, modeled using the marginal method of Wei, Lin, and Weissfeld, with a piecewise-exponential interval-censored component. The resulting model incorporates more of the information in the data and also removes some of the biases associated with the exclusion of interval-censored events. A simulation study demonstrates that our approach produces reliable estimates for the model parameters and their variance-covariance matrix. As a real-world data example, we apply this technique to the Systolic Hypertension in the Elderly Program (SHEP) clinical trial, which features three correlated events: clinical non-fatal myocardial infarction, fatal myocardial infarction (two exact-time events), and silent myocardial infarction (one interval-censored event). ^