1 Research Unit for Dietary Studies and Danish Epidemiology Science Centre, Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark.
2 Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark.
3 Department of Clinical Epidemiology, Aalborg Hospital, Aalborg, Denmark.
4 Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.
5 Department of Epidemiology and Social Medicine, University of Aarhus, Aarhus, Denmark.
6 Department of Human Nutrition, Royal Veterinary and Agricultural University, Frederiksberg, Denmark.
Received for publication September 30, 2003; accepted for publication February 23, 2004.
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
carbohydrates; coronary disease; fatty acids
Abbreviations: Abbreviations: CI, confidence interval; HR, hazard ratio.
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The aims of the present study were to describe the associations between the energy intake from total dietary fat and the major types of dietary fat and the risk of coronary heart disease, while assessing the potential effect-modifying role of gender and age. The results from the models used may be interpreted as substituting a specific amount of energy from fat for the same amount of energy from carbohydrates, thus contributing to the understanding of the role of dietary fat intake in the prevention of heart disease. In other words, this study may contribute to clarifying whether dietary prevention of heart disease should focus on both the quantity and the quality of dietary fats or on only the quantity.
![]() |
MATERIALS AND METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
Dietary variables
A total of 3,553 participants were given comprehensive verbal and written instructions on how to complete a 7-day weighed food record and requested to complete it within 3 weeks. The remaining 244 participants underwent a dietary history interview by the same trained dietician. The interviews were conducted by asking nonleading, open-ended questions concerning dietary intake during the previous month. Quantities were explored by means of food models, photo series, and household measures. The dietary assessment methods have been described in detail previously, and it has been shown that the methods yield comparable data on habitual diet intake (18).
The reproducibility and validity of the 7-day weighed food record method, as used in the population studies at the Research Centre for Prevention and Health, have been documented previously, demonstrating that this method provides a reproducible description of dietary habits regarding macronutrients and that the validity of the method, as assessed using nitrogen excretions, is good (19).
Nutrient calculation into daily averages was done using the Micro Camp and DANKOST 1 computer programs (Danish Catering Center A/S, Herlev, Denmark) based on Danish food composition tables (20, 21).
Nondietary covariates
Information on family history of myocardial infarction, smoking habits, physical activity in leisure time, and education was obtained by a self-administered questionnaire. "Family history of myocardial infarction" was defined as persons reporting myocardial infarction in parents or siblings. Questions on smoking concerned current and previous habits and the kinds and average daily quantities of tobacco consumed. Smoking habits were classified into five categories: never smokers; former smokers; and current smokers of from 1 to less than 15 g of tobacco per day, from 15 to less than 25 g of tobacco per day, and 25 g of tobacco or more per day. Data on leisure-time physical activity were based on the participants marking of one of four alternatives: mostly sedentary; walking, bicycling, or otherwise active at a corresponding level at least 4 hours per week; doing jogging or demanding sports or doing heavy activity during leisure for at least 3 hours per week; and long-distance running or competitive sports several times per week. We defined people in group 1 as being sedentary and with the rest as being active. Education was assessed with questions about the highest grade or year of regular schooling and the highest degree earned, with classification in three categories: 07 years; 811 years; and 12 years or more.
Systolic blood pressure, height, and weight were measured at the clinical examination. Systolic blood pressure was measured after at least 5 minutes rest. Body mass index was calculated as weight (kg)/height (m)2.
Identification of events
Fatal and nonfatal coronary heart disease events were defined according to International Classification of Diseases, Eighth Revision, diagnosis codes 410414 until December 31, 1994, and subsequently by International Classification of Diseases, Tenth Revision, codes I20I25. Cases were identified by record linkage to the National Patient Registry, including all hospitalizations since 1977 (22), and the Cause of Death Registry (23), including all deaths since 1943. Events ascertainment was made by review of medical files for the participants from the 1914 cohort who were included before 1977 (24).
Documentation of the validity of the diagnosis of myocardial infarction (International Classification of Diseases, Eighth Revision, code 410) in the National Patient Registry and the Cause of Death Registry has been published earlier (25). The combination of the national registries was found to be a valid and powerful tool for monitoring the population incidence of myocardial infarction.
Statistical analysis
Analyses were carried out separately for women and men. Hazard ratios with 95 percent confidence intervals for fatal and nonfatal coronary heart disease were calculated using Coxs proportional hazard regression models with age as the underlying time variable and delayed entrance accordingly. The observation time for each participant was the period from the date of examination (participants from the 1936 cohort who underwent the examination in 1976 were followed from 1977) until the incidence of or mortality from coronary heart disease, death of another cause, date of emigration, or December 31, 1998, whichever came first. The analyses included the 3,686 persons (1,849 women and 1,837 men) who provided information on all potential confounding variables.
Three models were used for investigation of the associations between intake of total fat and major types of fatty acids and risk of coronary heart disease. Model 1 included fat intake expressed as the percentage of total energy intake, in other words, as a nutrient density term, and total energy intake as a separate term. This approach, referred to as the "nutrient density model" (26), eliminates the effect of energy intake when assessing the association between fat intake and coronary heart disease. This model also included cohort identification as a covariate. Model 2a included the variables of model 1 plus the percentage of energy derived from protein and the percentages of energy derived from the other major types of fatty acids (in analyses where the major types of fatty acids were the variables of interest). Model 2b included the variables of model 2a plus nondietary and dietary coronary heart disease risk factors: familial history of myocardial infarction (yes, no, do not know); smoking (never smokers, former smokers, and current smokers of 1<15 g of tobacco per day and 15 g of tobacco per day); leisure-time physical activity (sedentary, active); educational attainment (07 years, 8 years or more); alcohol (grams per day) (nondrinkers, drinkers by tertiles); dietary fiber (grams per megajoule per day) (as a continuous variable); and dietary cholesterol (mg per megajoule per day) (as a continuous variable). Adjustments of systolic blood pressure and body mass index were expanded beyond simple linear approaches to include flexible curves via spline regression (27) that make use of intracategory information. The knots were defined using equal events in each line segment. The actual values of systolic blood pressure knots were 122, 134, and 152 mmHg among women and 120, 132, and 150 mmHg among men. The actual values of body mass index knots were 22, 24, and 28 kg/m2 among women and 24, 26, and 28 kg/m2 among men.
A covariate (cohort identification and covariates in models 2a and 2b) was included if it changed the beta coefficient for the dietary variable of interest 10 percent or more. This strategy was chosen because of the limited number of cases. For every Cox model, we checked the proportional hazard assumption with a smoothed plot of scaled Schoenfeld residuals versus time. Statistical interaction between gender and fat intake was tested using the likelihood ratio test in a model stratified by gender.
The estimated hazard ratios for total fat and the major types of fatty acids in model 1 may be interpreted as the estimated differences in risk for a 5 percent higher level of energy from fat where, for a fixed total energy intake, the complementary 5 percent lower intake of energy comes from other nonspecified sources of energy. In contrast, the results of models 2a and 2b may be interpreted as the estimated differences in risk for a 5 percent higher level of energy from fat, where the lower intake of energy is due to a lower intake of energy from carbohydrates. In other words, the results may be interpreted as substituting 5 percent of energy from fat for the same amount of energy from carbohydrates. Further, when studying the risk associated with 5 percent higher intake of polyunsaturated fatty acids, we added the percentage of energy from carbohydrates to model 2a and model 2b, and we removed the percentage of energy from saturated fatty acids from the models. The results of models 2a and 2b may in this case be interpreted as the estimated differences in risk for a 5 percent higher level of energy from polyunsaturated fat, where the lower intake of energy is due to a lower intake of energy from saturated fat.
To evaluate the age-related differences in coronary heart disease, we added a time (age)-dependent variable to the models that allows for different associations between fat intake and risk of coronary heart disease for the two age bands of less than 60 years and 60 years or more. This variable was added because previous studies have shown an age-related difference (2, 3), and because the plot of scaled Schoenfeld residuals versus time suggested an age-related difference. Statistical interaction between age band and fat intake was tested using the likelihood ratio test.
Data analyses were performed using Stata statistical software, release 7.0 (Stata Corporation, College Station, Texas).
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
Among women, the percentage of energy derived from saturated fat was borderline significantly positively associated with the risk of coronary heart disease (hazard ratio (HR) = 1.36, 95 percent confidence interval (CI): 0.98, 1.88) (table 2). The hazard ratio for percentage of energy from monounsaturated fat was 1.01 (95 percent CI: 0.56, 1.83) (table 2). In age-dependent analyses (table 3), energy from total fat was associated with a 74 percent greater risk of coronary heart disease among the younger women (HR = 1.74, 95 percent CI: 1.15, 2.64), whereas there was no association between total fat and risk of coronary heart disease among the older women (HR = 1.05, 95 percent CI: 0.86, 1.28). The p value for effect modification by age was 0.02. Energy from saturated fat was strongly positively associated with risk of coronary heart disease among the younger (HR = 2.68, 95 percent CI: 1.40, 5.12), but not among the older (HR = 1.22, 95 percent CI: 0.86, 1.71), women (table 3). The p value for effect modification by age was 0.02. The percentage of energy derived from monounsaturated fat was positively associated with risk of coronary heart disease among the younger (HR = 2.56, 95 percent CI: 1.15, 5.73), but not among the older (HR = 0.75, 95% CI: 0.40, 1.41), women (table 3). The p value for effect modification by age was 0.01. There was an inverse trend between the percentage of energy derived from polyunsaturated fat and risk of coronary heart disease among women (table 2). This trend was stronger when the lower intake of energy was due to a lower intake of energy from saturated fat (HR = 0.71, 95 percent CI: 0.42, 1.18) than when the lower intake of energy was due to a lower intake of energy from carbohydrates (HR = 0.89, 95 percent CI: 0.42, 1.18) (table 2).
|
There was no effect modification by gender in the whole sample (p values not shown). However, in age-dependent analyses, the association between total fat and risk of coronary heart disease was modified by gender among the younger (p = 0.12) and among the older (p = 0.17) participants; for saturated fat, the p values were 0.10 among the younger and 0.19 among the older participants; for monounsaturated fat, the p values were 0.15 among the younger and 0.19 among the older participants.
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
A number of limitations should be noted. First, the small number of cases caused wide confidence intervals and limited the possibility to further assess possible effect modification. Second, a potential source of random error arises from the assessment of dietary intake. Seven days may be too short a period to give information on the habitual food intake. However, with regard to nutrients that are consumed in a relatively large amount daily (e.g., protein, fats, carbohydrates, and fiber), a 7-day weighed food record classifies about 80 percent in the top and bottom thirds of the distribution correctly (28). Finally, in the present study only baseline information regarding dietary habits was available. The effect of changes in dietary habits could therefore not be assessed.
Information bias is not likely to have affected the study, as cases were identified by record linkage to the National Patient Registry (22) and the Cause of Death Registry (23), and diagnoses were established independently of the dietary habits of the participants. Only 11.5 percent were lost to follow-up, and selection bias is therefore unlikely to have affected the study. Control for confounding did not change the estimates for total fat and the major types of fats considerably. Residual confounding is therefore unlikely. However, in observational studies, diets differing in fat contentboth quantitatively and qualitativelyinevitably differ in other dietary constituents that may influence coronary heart disease risk. We decided to respect the observational nature of this study and not to try to control for these potential confounders.
The gender-related difference in the association between saturated fat intake and risk of coronary heart disease found in the present study is to some extent supported by findings from a recent prospective cohort study among women and men (4) and from some prospective cohort studies examining women (9) or men (6, 8, 10, 13, 14) separately. However, in the study by Hu et al. (9), the positive association between saturated fat intake and risk of coronary heart disease among women was weak and not statistically significant. In contrast to the present findings, some others have found a positive association between saturated fat intake and coronary heart disease among men (1, 11, 12). Several explanations may account for the effect modification by gender. One explanation may be differences in baseline risk. Because the magnitude of the relative effect depends on the magnitude of the baseline risk, the same absolute effect in two populations can correspond to greatly differing relative associations (29). Another possibility is that intakes of complementary carbohydrates were qualitatively different between the genders. In the present study, only types of fat, but not types of carbohydrates, were considered. Finally, there may be a biologic interaction. Fats produce postprandial hypertriglyceridemia (15), and a raised nonfasting concentration of triglycerides seems to be a stronger risk factor for death from coronary heart disease among women than among men (16). However, the increased risk of coronary heart disease associated with high-fat diets causing postprandial hypertriglyceridemia may, in part, be counterbalanced by the cis-monounsaturated and n-6 polyunsaturated fatty acids positive effect on serum low-density lipoprotein cholesterol (30) and n-3 fatty acids positive effect on other risk factors for coronary heart disease (31, 32).
Epidemiologic studies on age-related differences in the association between fat intake and risk of coronary heart disease are sparse. Only two prospective studies have been published (2, 3). In agreement with the present study, these studies found that risk of coronary heart disease increased with higher intakes of total, saturated, and monounsaturated fat among the younger, but not among the older, participants. Differences in baseline risk may be an explanation. It is also possible that older participants may be a selected group (a large number of the study base has already died or has been excluded because of coronary heart disease) and may be less vulnerable to environmental factors.
A potentially important factor contributing to the discrepancies across the prospective studies is differences in the ways of expressing fat intake (as relative or absolute) and whether intake of total energy and other types of fat has been controlled for. The strategy used for the analyses in the present study has been used in only one previous study (9). We expressed fat intake as energy percentage and included total energy intake and percentages of energy from saturated, monounsaturated, and polyunsaturated fat in the models because of extraneous variation and potential confounding. This also allowed us to estimate the difference in risk for a higher level of energy from the major types of fat, where the lower intake of energy was due to a lower intake of energy from carbohydrates. As pointed out by Kipnis et al. (33) and Willett et al. (26), the beta coefficient of the macronutrient of interest in the energy-adjusted model has a substitution interpretation (in its continuous version): It represents the change in disease incidence associated with substitution of one unit of that macronutrient for an equivalent amount of energy from other macronutrients. Consequently, adjusting for total energy excludes the possibility of addressing hypotheses on the effects of increased intake of selected nutrients (34). The effect of one nutrient can be assessed only in relation to another. The present study showed that we may be able to provide evidence that saturated fat increases risk more than carbohydrates do, but we cannot, as also emphasized by Freedman et al. (34), predict whether fat promotes disease or whether carbohydrates prevent disease.
In the present study, monounsaturated fat intake seems to be associated with increased coronary heart disease risk among the younger participants. This relation is unclear. However, it may, in part, be due to intake of trans fatty acids, which is included in the sum of monounsaturated fatty acids. Trans fatty acids have a negative effect on the serum total:high density lipoprotein cholesterol ratio when dietary carbohydrates are replaced by trans fatty acids under isoenergetic conditions, whereas monounsaturated fatty acids have a positive effect on the total:high density lipoprotein cholesterol ratio when carbohydrates are replaced by monounsaturated fatty acids (30). Further, intake of trans fat has been shown to be positively associated with risk of coronary heart disease (35), whereas intake of monounsaturated fat has been shown to be inversely associated with risk of coronary heart disease (9). However, Rudel et al. (36) demonstrated that primates on a monounsaturated diet developed more atherosclerosis than those on a polyunsaturated diet (corresponding to those fed the saturated diet) despite a more favorable lipid profile.
That the estimated differences in risk for a 5 percent higher level of energy from polyunsaturated fat were the same, whether the lower intake of energy was from carbohydrates or saturated fat among men, may be due to the weak association between saturated fat and coronary heart disease found among men.
We estimated the difference in risk for a higher level of energy from fat, where the lower intake of energy was due to a lower intake of energy from carbohydrates. The usual mix of carbohydrates in the Western diet contains many high-glycemic foods, such as potatoes and baked goods. The possibility remains that the positive association between saturated fat intake and risk of coronary heart disease would have been even stronger if compared with a mix of carbohydrates from low-glycemic foods, such as whole grain cereals and vegetables. Future studies need to address this.
In conclusion, our data suggest that coronary heart disease risk relates to both the quantity and the quality of dietary fats rather than only the quantity of fat. In future studies, it is recommended that the study populations be subdivided according to gender and age to account for possible effect modification.
![]() |
ACKNOWLEDGMENTS |
---|
![]() |
NOTES |
---|
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|