Dietary Fat and Coronary Heart Disease: A Comparison of Approaches for Adjusting for Total Energy Intake and Modeling Repeated Dietary Measurements

Abstract

Previous cohort studies of fat intake and risk of coronary heart disease (CHD) have been inconsistent, probably due in part to methodological differences and various limitations, including inadequate dietary assessment and incomplete adjustment for total energy intake. The authors analyzed repeated assessment of diet from the Nurses' Health Study to examine the associations between intakes of four major types of fat (saturated, monounsaturated, polyunsaturated, and trans fats) and risk of CHD during 14 years of follow-up (1980-1994) by using alternative methods for energy adjustment. In particular, the authors compared four risk models for energy adjustment: the standard multivariate model, the energy-partition model, the nutrient residual model, and the multivariate nutrient density model. Within each model, the authors compared four different approaches for analyzing repeated dietary measurements: baseline diet only, the most recent diet, and two different algorithms for calculating cumulative average diets. The substantive results were consistent across all models; that is, higher intakes of saturated and trans fats were associated with increased risk of CHD, while higher intakes of monounsaturated and polyunsaturated fats were associated with reduced risk. When nutrients were considered as continuous variables, the four energy-adjustment methods yielded similar associationS. However, the interpretation of the relative risks differed across models. In addition, within each model, the methods using the cumulative averages in general yielded stronger associations than did those using either only baseline diet or the most recent diet. When the nutrients were categorized according to quintiles, the residual and the nutrient density models, which gave similar results, yielded statistically more significant tests for linear trend than did the standard and the partition models.

Processed meat intake and incidence of Type 2 diabetes in younger and middle-aged women

“…Imprecise dietary measurement and residual confounding are possible alternative explanations for some of the observed associations. However, errors in dietary assessment measures might have accounted for a lack of association but not the reverse [31]. The repeated dietary measurements made in this study were advantageous because they allowed for fewer measurement errors and changes in behavioural dietary patterns over time to be assessed [31].…”

“…However, errors in dietary assessment measures might have accounted for a lack of association but not the reverse [31]. The repeated dietary measurements made in this study were advantageous because they allowed for fewer measurement errors and changes in behavioural dietary patterns over time to be assessed [31]. Adjustment for the "Western" pattern might represent an overadjustment, since red and processed meats are components of the "Western" pattern.…”

“…Participants who were diagnosed with diabetes (Type 1 or Type 2) or who died during follow-up were censored at the date of diagnosis or death. The 1991 intake was used for the follow-up between 1991 and 1995, and the average of the 1991 and 1995 intakes for the follow-up between 1995 and 1999 to reduce within-subject variation and best represent long-term diet [31]. We used only the 1991 but not the 1995 intake data for those individuals who reported on the 1993 or 1995 questionnaire a diagnosis of cancer (except non-melanoma skin cancer) or cardiovascular disease because changes in diet after development of these conditions might confound the relationship between dietary intake and diabetes [31].…”

Crossing two types of implementation intentions with a protection motivation intervention for the reduction of saturated fat intake: A randomized trial

“…Consumption of bad fats (saturated fats, trans-fats) has been associated with increased risk of coronary heart disease (e.g., Hu, Stampfer, Rimm, Ascherio, Rosner, Spiegelman et al;Willett, Stampfer, Manson, Colditz, Speizer, Rosner et al, 1993) and there has been widespread call for their intake to be restricted (e.g., Institute of Medicine, 2002). When young people join university, or begin a new career, they are often leaving the family environment for the first time and begin to take greater responsibility for purchasing and preparing their own meals.…”

Dietary glycemic index in relation to metabolic risk factors and incidence of coronary heart disease: the Zutphen Elderly Study

“…We tested for monotonic trends with increasing levels of dietary factors by assigning each participant the median value for the category and modeling this value as a continuous variable. In additional prospective analyses, we updated exposure variables for the follow-up period after 1990; for the updated dietary variables the average of the 1985 and 1990 assessment was used to reduce measurement error (Hu et al, 1999). All P values are two-sided.…”