Faculty Bibliography

To determine whether statin use leads to dietary indiscretion, this longitudinal cohort study examined the impact of statin initiation on saturated fat intake. We interviewed 71 patients who had received a new prescription for statins for primary prevention of cardiovascular disease, first at the time of prescription and then again 3 and 6 months later. Patients were asked about their beliefs regarding diet and medications as well as their diet during the past 24 hours in all interviews and about their adherence to statins in the 3- and 6-month follow-up interviews. At the time of statin prescription, 54 participants (76 percent) wanted to reduce dietary fat, 50 (70 percent) believed statin use could cure their hyperlipidemia, and 31 (44 percent) thought that physicians prescribed statins to them despite their preference to continue to try dietary changes. After 6 months of statin use, no significant change in saturated fat intake was noted

Methods to assess uncertainty in the estimated population attributable risk (PAR) by calculating 95 per cent confidence intervals (CIs) are not readily available in software for complex sample surveys. Using the Bonferroni inequality, a simple method to obtain CIs for the PAR is developed. The method is demonstrated using a simulation in a (2 x 2) table as well as a cohort study to calculate CIs for PAR of coronary heart disease death (using proportional hazards regression). This article demonstrates a straightforward, theoretically valid method of determining CIs for the PAR. Using this method, researchers analysing complex surveys can routinely provide a population perspective and a valid measure of the uncertainty for these estimates.

in a regression setting, the partial correlation coefficient is often used as a measure of 'standardized' partial association between the outcome y and each of the covariates in x' = [x(1),...,xk]. a linear regression model estimated using ordinary least squares, with y as the response, the estimated partial correlation coefficient between y and x(k) can be shown to be a monotone function, denoted f(z), of the Z-statistic for testing if the regression coefficient Of x(k) is 0. When y is non-normal and the data are clustered so that y and x are obtained from each member of a cluster, generalized estimating equations are often used to estimate the regression parameters of the model for y given x. In this paper, when using generalized estimating equations, we propose using the above transformation f (z) of the GEE Z-statistic as a measure of partial association. Further, we also propose a coefficient of determination to measure the strength of association between the outcome variable and all of the covariates. To illustrate the method, we use a longitudinal study of the binary outcome heart toxicity from chemotherapy in children with leukaemia or sarcoma

BACKGROUND: While lipid-lowering drugs reduce cardiovascular risk, there is concern that their use may discourage dietary restriction of saturated fat (SF). The purpose of this analysis was to evaluate the association between taking lipid-lowering drugs and SF intake. MATERIALS AND METHODS: We analyzed cross-sectional data on cholesterol and diet from 6,473 adult respondents in the National Health and Nutrition Examination Survey, 1999-2002. Respondents were classified into three groups: (1) no history of high cholesterol (Desirable Cholesterol or DC), (2) history of high cholesterol without current drug treatment (Non-Drug Treated or NDT), and (3) history of high cholesterol with active lipid-lowering medication use (Drug-Treated or DT). Regression models were used to compare the mean percentage of daily kilocalories from SF among the three groups while controlling for confounders. RESULTS: Unadjusted analyses revealed significantly lower mean daily intake of SF (% of Kcal/day) among DT respondents compared to both DC (-.40 SF; 95% Confidence Interval [CI], -0.71 to -0.08) and NDT respondents [-.36 SF; CI, -0.79 to 0.06]. The complete multivariate model controlling for all covariates (age, sex, education, race/ethnicity, current smoking, alcohol use, BMI, physical activity, cardiovascular disease, diabetes, hypertension) attenuated the relationship compared to D (-.35 SF, CI -0.7 to -0.01) and NDT (-.25 SF, CI -0.62 to 0.12) individuals. CONCLUSION: Taking lipid-lowering medications is associated with a lower intake of SF. However, a prospective study of diet and medication use is needed to definitively evaluate the relationship between lipid-lowering medications and SF intake

BACKGROUND: Randomized clinical trials have demonstrated that strict blood pressure (BP) control in diabetes reduces cardiovascular morbidity and mortality. Previous observational studies have confirmed that hypertension is inadequately controlled in the general population of the United States. In this study we evaluated the prevalence and determinants of severe, sustained, uncontrolled hypertension in a national cohort of persons with diabetes. METHODS: We identified 64,105 veterans from the national Veterans Administration diabetes registry for whom BP, survey, laboratory, and medication data were available. Using mean BP from three visits in fiscal year 2000, we determined the prevalence of sustained BP readings >/=160/100, >/=140/90, or >/=130/80 mm Hg. We determined predictors of the three thresholds using demographic variables, self-reported medical comorbidities, estimated glomerular filtration rate, and number of BP-lowering medications. RESULTS: Over a mean interval of 131.0 days (+/-81.4), we found that 6,347 (9.9%) of the 64,105 veterans with diabetes had mean BP >/=160/100 mm Hg. Similarly 25,924 (40.4%) had a mean BP >/=140/90 mm Hg, and 38,296 (59.7%) had a mean BP >/=130/80 mm Hg. Independent predictors of mean BP >/=160/100 mm Hg included age, ethnicity, education level, cardiovascular comorbidities, alcohol use, and number of BP-lowering medications. CONCLUSIONS: Administrative databases can be used to identify patients with sustained uncontrolled hypertension within health care systems. Our findings suggest important patient-level factors that can be targeted for quality improvement programs in diabetes

BACKGROUND.: It is unclear whether the coronary heart disease (CHD) mortality risk associated with obesity is mediated only through traditional CHD risk factors. This analysis evaluated the independent CHD mortality risk due to obesity and determined its population attributable risk (PAR). METHODS.: Using the NHANES I Epidemiologic Follow-up Study (1971-1992, n = 10,582), a diabetes-body mass index (BMI) variable was constructed. The hazard ratios (HR) for fatal CHD in the diabetes-BMI categories (adjusting for age, sex, race, exercise, education level, smoking, hypertension, cholesterol, and alcohol use) were determined and the PARs subsequently estimated. RESULTS.: Compared to lean non-diabetics, the HR (95% CI) for fatal CHD is 0.8 (0.7, 1.1) in overweight non-diabetics, 1.4 (1.3, 2.0) in obese non-diabetics, 2.2 (1.2, 4.0) in lean diabetics, 2.3 (1.4, 3.9) in overweight diabetics, and 3.3 (1.9, 8.9) in obese diabetics. The PAR% is -6.8 (-15.7, 1.8) in overweight non-diabetics, 6.1 (1.7, 11.1) in obese non-diabetics, 2.0 (0.3, 4.0) in lean diabetics, 2.2 (0.6, 4.3) in overweight diabetics, and 2.2 (0.8, 3.8) in obese diabetics. CONCLUSIONS.: Obesity is an independent risk factor for CHD mortality even after controlling for traditional CHD risk factors. The PAR for CHD death in obese non-diabetics is significant. Obesity should be aggressively treated in those without traditional CHD risk factors

BACKGROUND: It is not known whether the coronary heart disease (CHD) mortality risk associated with recent (RDM; <10 years) or long-standing diabetes mellitus (LDM; > or =10 years) varies by sex. METHODS: The relationship between diabetes duration and CHD mortality was evaluated among 10 871 adults (aged 35-74 years at baseline) using the 1971-1992 National Health and Nutrition Examination Survey Epidemiologic Follow-up Study. RESULTS: The CHD mortality rates per 1000 person-years in men with no myocardial infarction (MI) or diabetes, MI only, RDM only, LDM only, MI and RDM, and MI and LDM were 5.5 (95% confidence interval, 4.8-6.2), 15.2 (11.6-20.0), 13.2 (7.9-22.1), 11.4 (6.4-20.3), 36.0 (16.7-77.7), and 35.4 (14.0-89.7), respectively. The corresponding rates in women were 2.9 (2.5-3.3), 7.3 (5.0-10.8), 5.2 (3.5-7.7), 10.7 (7.5-15.5), 9.3 (4.3-19.9), and 21.6 (6.1-76.0), respectively. Compared with MI, the multivariate hazard ratios and their 95% confidence intervals (adjusted for age, race, smoking, hypertension, total cholesterol level, and body mass index) for fatal CHD in men with RDM, LDM, MI and RDM, and MI and LDM were 0.7 (0.3-1.3), 0.8 (0.4-1.4), 3.2 (1.4-7.4), and 2.4 (0.8-6.7), respectively. The corresponding ratios in women were 0.9 (0.6-1.3), 1.8 (1.1-3.2), 1.3 (0.5-3.5), and 1.6 (0.2-10.9), respectively. CONCLUSIONS: In men, RDM and LDM were associated with as high a risk for CHD death as MI. In women, although RDM had a CHD mortality risk similar to MI, LDM had an even greater risk. Because women with LDM are at very high risk for CHD mortality, current guidelines may need to be further refined to match intensity of treatment to risk in these women