PMCCPMCCPMCC

Search tips
Search criteria 

Advanced


 
Formats
Article sections
Authors
Related links
Logo of heartHeartCurrent TOCInstructions to authors
 
Heart. 2003 July; 89(7): 722–726.
PMCID: PMC1767713
Copyright © Copyright 2003 by Heart
Carbohydrates, dietary glycaemic load and glycaemic index, and risk of acute myocardial infarction
A Tavani,1 C Bosetti,1 E Negri,1 L S Augustin,2 D J A Jenkins,3 and C La Vecchia4
1Istituto di Ricerche Farmacologiche “Mario Negri”, Milan, Italy
2Servizio di Epidemiologia, Centro di Riferimento Oncologico, Aviano, Italy
3Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
4Istituto di Statistica Medica e Biometria, Università degli Studi di Milano, Milan, Italy
Correspondence to:
Dr Alessandra Tavani, Istituto di Ricerche Farmacologiche “Mario Negri”, Via Eritrea 62, 20157 Milan, Italy;
tavani/at/marionegri.it
Accepted January 22, 2003.
Small right arrow pointing to: This article has been cited by other articles in PMC.
Abstract
Objectives: To assess the relation between selected carbohydrate foods, dietary glycaemic load and glycaemic index, and the risk of non-fatal acute myocardial infarction in a population with a high intake of refined carbohydrates.
Design and setting: Hospital based case–control study conducted in Milan, Italy, between 1995 and 1999.
Patients: 433 non-diabetic subjects with a first episode of non-fatal acute myocardial infarction, and 448 controls admitted to hospital for a wide spectrum of acute conditions unrelated to known or potential risk factors for acute myocardial infarction.
Methods: Information was collected by interviewer administered questionnaires. Multivariate odds ratios (OR) and 95% confidence intervals (CI) were obtained by multiple logistic regression models.
Results: Compared with patients in the lowest tertile of intake, the multivariate OR for those in the highest tertile was 1.00 for bread, 1.27 for pasta and rice, 1.38 for soups, 0.78 for potatoes, 0.97 for desserts, and 1.00 for sugar. The OR for the highest tertile of score was 1.08 for glycaemic load and 1.38 for glycaemic index. None of the estimates was significant. A significant association with acute myocardial infarction risk was found for glycaemic index in patients aged [gt-or-equal, slanted] 60 years (OR 1.81, 95% CI 1.07 to 3.07 for the highest tertile of score compared with the lowest) and in those with a body mass index [gt-or-equal, slanted] 25 kg/m2 (OR 2.02, 95% CI 1.21 to 3.34).
Conclusions: In this Italian population high glycaemic load and glycaemic index were not strongly associated with acute myocardial infarction risk, but slightly increased odds ratios were observed for glycaemic index in elderly people and in association with overweight.
Keywords: acute myocardial infarction, carbohydrate intake, glycaemic index, glycaemic load
 
The potential role of carbohydrates on the risk of coronary heart disease is still unclear and several mechanisms may be involved.1 A high carbohydrate intake can raise serum concentrations of very low density lipoproteins and triglycerides and decrease those of high density lipoproteins, thus favouring a lipid profile at higher risk for coronary heart disease.2,3 However, carbohydrate foods contain several nutrients that may reduce risk factors for coronary heart disease such as fibre, linoleic acid, vitamin E, phyto-oestrogens, and several phenolic acids with antioxidant properties. Dietary carbohydrates consumed in the form of whole grains have been shown to be protective against ischaemic heart disease.4–6 Two prospective studies—the Puerto Rico Heart Health Program7 and the Honolulu Heart Program8—found a weak inverse association of carbohydrate intake with coronary heart disease risk, which disappeared after adjustment for total energy intake. Most epidemiological studies considering the relation between cereal fibre and coronary heart disease have reported that it is protective.1
Another way of exploring the role of carbohydrates on coronary heart disease risk is through the glycaemic response that follows their ingestion.4,9 Carbohydrate foods can produce different glycaemic responses depending on their chemical structure, particle size, amount and type of dietary fibre, fats, proteins, antinutrients, and food processing.10 The glycaemic response can be quantified by the glycaemic index, which is a measure of the rate of carbohydrate absorption from the gastrointestinal tract and the postprandial blood glucose response.11,12 Foods with a low glycaemic index, such as legumes and whole grains, reduce the rate of glucose absorption, resulting in lower postprandial rises in blood glucose and insulin compared with high glycaemic index foods (for example, white bread).13 High insulin concentrations are risk factors for insulin resistance, type 2 diabetes,9,14 and increased coronary heart disease.9,15 Diets with a high glycaemic index and glycaemic load (the product of the average daily glycaemic index and total carbohydrate intake—that is, a measure of quality and amount of carbohydrates consumed) have been shown to increase the risk of type 2 diabetes9,16,17 and coronary heart disease.4,9
There is very little epidemiological evidence on the relation between glycaemic index, glycaemic load, and the risk of coronary heart disease. The Nurses’ Health Study, based on 761 incident cases, found that dietary glycaemic load was associated with risk for the disease, particularly among women with the highest body mass index, and that carbohydrate foods with the highest glycaemic index increased the risk of coronary heart disease.4 However, the Zutphen Elderly Study, based on 94 non-diabetic men with incident coronary heart disease, found no relation between the disease and a high glycaemic index diet.18
To provide further information on the relation of carbohydrate foods, glycaemic load and glycaemic index, and the risk of acute myocardial infarction, we have analysed the results of a case–control study conducted in Italy, where carbohydrate consumption is high and contains foods with both high glycaemic index (white bread) and intermediate glycaemic index (pasta al dente).
METHODS
The data were derived from a case–control study of non-fatal acute myocardial infarction conducted in the greater Milan, Italy, between 1995 and 1999.19 Cases were 507 patients (378 men, 129 women; median age 61 years, range 25–79 years) with a first episode of non-fatal acute myocardial infarction, defined according to the World Health Organization criteria,20 admitted to a network of teaching and general hospitals in the area. Controls were 478 patients (297 men, 181 women; median age 59 years, range 25–79 years) from the same geographical area, admitted to the same hospitals for a wide spectrum of acute conditions unrelated to known risk factors for acute myocardial infarction. Among controls, 34% had trauma, 30% non-traumatic orthopaedic disorders, 14% acute surgical conditions, and 22% miscellaneous other illnesses. Fewer than 5% of cases and controls approached refused to participate. Cases and controls reporting a diagnosis of diabetes were excluded, thus leaving 448 cases and 433 controls in the present analysis.
Interviews were conducted in hospital using a structured questionnaire, including information on sociodemographic factors, anthropometric variables, smoking, alcohol, and coffee consumption, and other lifestyle habits, a problem oriented medical history, physical activity, and a history of acute myocardial infarction in relatives. Cholesterol concentrations were obtained from clinical records.
Information on diet was based on a food frequency questionnaire, tested for reproducibility21,22 and validity,23 which included questions on 78 foods or food groups and 15 questions aimed at assessing patterns of fat intake and meal frequency. Energy and nutrient intakes were computed using an Italian food composition database.24
We expressed glycaemic index as a percentage of the glycaemic response elicited by white bread.25 For each subject we calculated the average daily glycaemic index by summing the products of the carbohydrate content per serving in grams for each food or recipe, by the average number of servings per week and by its glycaemic index, all divided by the total amount of available weekly carbohydrate intake.26 A score for the daily average glycaemic load was computed as the average daily glycaemic index, but without dividing by the total amount of available carbohydrate. We assigned glycaemic index values to 50 foods or recipes present in the questionnaire, as 28 of them—mainly meat, cheese, and fish based foods—contained only negligible amounts of carbohydrate.27 Glycaemic index values were derived primarily from international tables25 and from Italian sources for a few local recipes.28 Particular attention was paid to Italian cooking habits (for example, pasta “al dente”) which may influence the rate of carbohydrate absorption. Food items for which a glycaemic index was not determined were assigned the glycaemic index of the nearest comparable food (for example, tangerines were assigned the glycaemic index of oranges).
Data analysis
Odds ratios (OR) of acute myocardial infarction, and the corresponding 95% confidence intervals (CI), for subsequent tertiles of food intake, glycaemic load, and glycaemic index were derived using unconditional multiple logistic regression models,29 including terms for age, sex, education, body mass index, cholesterol, tobacco smoking, alcohol drinking, physical activity, hyperlipidaemia, diabetes, hypertension, and a family history of ischaemic heart disease in first degree relatives. Adjustment for energy was made using the residual method.30 Tests for trend were based on the likelihood ratio test between the models with and without a linear term for each variable of interest.
RESULTS
Table 1​1 gives the distribution of cases and controls and the corresponding OR according to intake of selected carbohydrate-rich foods. Compared with the lowest tertile of consumption, the OR of acute myocardial infarction for the highest was 1.00 for bread, 1.27 for pasta and rice, 1.38 for soups, 0.78 for potatoes, 0.97 for desserts, and 1.00 for sugar. Compared with non-consumers, subjects eating whole grain bread had an OR of 0.77. Neither these estimates nor their corresponding trends in risk were significant.
Table 1
Table 1
Odds ratios* and corresponding 95% confidence intervals according to energy adjusted intake of carbohydrate foods among 433 non-diabetic cases of acute myocardial infarction and 448 controls, Milan, Italy, 1995 to 1999
The relation of glycaemic index and glycaemic load with acute myocardial infarction risk is shown in table 2​2.. The OR in the highest tertile compared to the lowest was 1.38 for glycaemic index and 1.08 for glycaemic load. None of the estimates was significant.
Table 2
Table 2
Odds ratios* and corresponding 95% confidence intervals according to energy adjusted glycaemic index and glycaemic load among 433 non-diabetic cases of acute myocardial infarction and 448 controls, Milan, Italy, 1995 to 1999
Table 3​3 shows the relation of glycaemic index and glycaemic load with acute myocardial infarction risk in strata of sex, age at diagnosis, and body mass index. A significant association was found for glycaemic index in patients aged [gt-or-equal, slanted] 60 years (OR 1.81, 95% CI 1.07 to 3.07 for the highest tertile of score compared with the lowest) and in those with a body mass index [gt-or-equal, slanted] 25 kg/m2 (OR 2.02, 95% CI 1.21 to 3.34). No different pattern of risk between men and women was found.
Table 3
Table 3
Odds ratios* and 95% confidence intervals of acute myocardial infarction according to glycaemic index and glycaemic load in strata of selected covariates, Milan, Italy, 1995 to 1999
DISCUSSION
In this study there was no consistent relation between consumption of various carbohydrate foods and risk of acute myocardial infarction. Carbohydrate intake in the Italian population is peculiar, as Italy shows the highest consumption of carbohydrates from refined cereals among affluent countries31—that is, up to more than 300 g/day in the highest quintile of consumption. The main sources of carbohydrates in the Italian population are white bread and its substitutes (such as crackers, grissini, and melba toasts) and various types of pasta or rice dishes, accounting altogether for almost 40% of the total carbohydrate intake.32 Consumption of sugar and cakes is relatively low in Italy32 and was not associated with risk for acute myocardial infarction in this study. We found no significant association of myocardial infarction risk with whole grain food consumption, although a tendency for a decreased odds ratio emerged. An inverse association between whole grain intake and risk of ischaemic heart disease has been reported in the Iowa Women’s Health Study cohort, which was attributed to the phytochemicals, fibre, and antioxidants contained in such foods.5 However, in this Italian population only 6.2% of cases and 8.5% of controls consumed whole grains and in relatively low amounts, potentially explaining the lack of a significant protection in this study.
Diets with a high consumption of refined carbohydrates (high glycaemic index foods) tend to raise blood glucose and insulin concentrations to a greater extent than slowly absorbed carbohydrates (low glycaemic index foods), such as legumes and whole grains,33,34 and have been directly associated with risk of coronary heart disease,4,9 type 2 diabetes,9,16,17 and obesity.9,35 Our data do not support the hypothesis of a strong effect of glycaemic index and glycaemic load on the risk of acute myocardial infarction, although a moderately increased odds ratio associated with high glycaemic index foods was found in selected categories of subjects, such as people over 60 years of age and in people with a body mass index > 25 kg/m2. This latter result can be related to impaired insulin resistance in elderly overweight subjects and is in agreement with the results of the Nurses’ Health Study, which found a doubled risk of coronary heart disease with a high glycaemic load in women with a body mass index of [gt-or-equal, slanted] 23 kg/m2, but not in those with lower body mass index.4 No differences by sex were found in our study for the relation of glycaemic index and glycaemic load to risk of acute myocardial infarction. In this analysis we excluded subjects with diabetes. However, if the glycaemic load is related to type 2 diabetes, as several investigators have suggested,16,17 then there may still be a link between glycaemic load and coronary heart disease, albeit indirect.
With regard to potential sources of bias, in this study cases and controls were interviewed in the same hospitals and came from the same geographical area; participation was almost complete; and patients admitted for chronic conditions or diseases related to known or potential risk factors for acute myocardial infarction or modification of diet were excluded from the comparison group. The potential confounding of covariates associated with acute myocardial infarction risk in this study,36,37 including energy intake, was allowed for in the analysis. The food frequency questionnaire was satisfactorily valid and reproducible21–23 and there is no reason to assume different recall of intake of bread, pasta, and other carbohydrates on the basis of the disease status, because the possibility of a relation between these foods and acute myocardial infarction was unknown to most subjects.
Glycaemic index estimates have some limitations, as some of them derive from small samples and their variability is unclear.25,26,38 Statistics on the average glycaemic index and glycaemic load in the Italian population are not available; however, intake of bread and pasta were similar in our controls and in the general population.32,39 Another limitation of this study is its relatively small sample size, which is inadequate to investigate moderate associations in subgroups or interactions. However, these data are of considerable interest given the paucity of available information on glycaemic index, glycaemic load, and coronary heart disease risk, and the originality of the population studied in terms of carbohydrate amount and carbohydrate composition of diet.32
Conclusions
Although no overall relation with glycaemic index or glycaemic load and acute myocardial infarction risk was found in this Italian population, there was a positive association between glycaemic index and acute myocardial infarction in subgroups most likely to have insulin resistance—the older and more overweight subjects. More studies in these high risk subgroups are needed to confirm these observations and to identify foods or classes of foods with specific effects.
Acknowledgments
This study was partly supported by “Ministero della Salute” (contract No 177, RF 2001).
REFERENCES
1. Truswell AS. Cereal grains and coronary heart disease. Eur J Clin Nutr 2002;56:1–14. [PubMed]
2. Nestel PJ, Carroll KF, Havenstein N. Plasma triglyceride response to carbohydrates, fats and caloric intake. Metab Clin Exp 1970;19:1–18. [PubMed]
3. Stampfer MJ, Krauss RM, Ma J, et al. A prospective study of triglyceride level, low-density lipoprotein particle diameter, and risk of myocardial infarction. JAMA 1996;276:882–8. [PubMed]
4. Liu S, Willett WC, Stampfer MJ, et al. A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. Am J Clin Nutr 2000;71:1455–61. [PubMed]
5. Jacobs DR Jr, Meyer KA, Kushi LH et al. Whole-grain intake may reduce the risk of ischemic heart disease death in postmenopausal women: the Iowa women’s health study. Am J Clin Nutr 1998;68:248–57. [PubMed]
6. Slavin JL, Martini MC, Jacobs DR, et al. Plausible mechanisms for the protectiveness of whole grains. Am J Clin Nutr 1999;70(suppl 3):459S–63S. [PubMed]
7. Garcia-Palmieri MR, Sorlie P, Tillotson J, et al. Relationship of dietary intake to subsequent coronary heart disease incidence: the Puerto Rico heart health program. Am J Clin Nutr 1980;33:1818–27. [PubMed]
8. McGee DL, Reed DM, Yano K, et al. Ten-year incidence of coronary heart disease in the Honolulu heart program. Relationship to nutrient intake. Am J Epidemiol 1984;119:667–76. [PubMed]
9. Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA 2002;287:2414–23. [PubMed]
10. Jenkins DJ, Kendall CW, Axelsen M, et al. Viscous and nonviscous fibres, nonabsorbable and low glycaemic index carbohydrates, blood lipids and coronary heart disease. Curr Opin Lipidol 2000;11:49–56. [PubMed]
11. Jenkins DJ, Wolever TM, Taylor RH, et al. Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr 1981;34:362–6. [PubMed]
12. Jenkins DJ, Wolever TM, Jenkins AL, et al. The glycaemic response to carbohydrate foods. Lancet 1984;2:388–91. [PubMed]
13. Jenkins DJ, Wolever TM, Collier GR, et al. Metabolic effects of a low-glycemic-index diet. Am J Clin Nutr 1987;46:968–75. [PubMed]
14. Virkamaki A, Ueki K, Kahn CR. Protein–protein interaction in insulin signaling and the molecular mechanisms of insulin resistance. J Clin Invest 1999;103:931–43. [PMC free article] [PubMed]
15. Lakka HM, Lakka TA, Tuomilehto J, et al. Hyperinsulinemia and the risk of cardiovascular death and acute coronary and cerebrovascular events in men: the Kuopio Ischaemic heart disease risk factor study. Arch Intern Med 2000;160:1160–8. [PubMed]
16. Salmeron J, Ascherio A, Rimm EB, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 1997;20:545–50. [PubMed]
17. Salmeron J, Manson JE, Stampfer MJ, et al. Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women. JAMA 1997;277:472–7. [PubMed]
18. Van Dam RM, Visscher AWJ, Feskens EJM, et al. Dietary glycemic index in relation to metabolic risk factors and incidence of coronary heart disease: the Zutphen elderly study. Eur J Clin Nutr 2000;54:726–31. [PubMed]
19. Tavani A, Pelucchi C, Negri E, et al. n-3 polyunsaturated fatty acids, fish, and nonfatal acute myocardial infarction. Circulation 2001;104:2269–72. [PubMed]
20. World Health Organization. Ischemic heart disease registers. Report of the Fifth working group. Copenhagen: WHO, 1971.
21. Franceschi S, Barbone F, Negri E, et al. Reproducibility of an Italian food frequency questionnaire for cancer studies: results for specific nutrients. Ann Epidemiol 1995;5:69–75. [PubMed]
22. Franceschi S, Negri E, Salvini S, et al. Reproducibility of an Italian food frequency questionnaire for cancer studies: results for specific food items. Eur J Cancer 1993;29A:2298–305. [PubMed]
23. Decarli A, Franceschi S, Ferraroni M, et al. Validation of a food-frequency questionnaire to assess dietary intakes in cancer studies in Italy. Results for specific nutrients. Ann Epidemiol 1996;6:110–18. [PubMed]
24. Salvini S, Gnagnarella P, Parpinel M T, et al. The food composition database for an Italian food frequency questionnaire. J Food Composition Anal 1996;9:57–71.
25. Foster-Powell K, Miller JB. International tables of glycemic index. Am J Clin Nutr 1995;62:871S–90S. [PubMed]
26. Wolever TM, Nguyen PM, Chiasson JL, et al. Determinants of diet glycemic index calculated retrospectively from diet records of 342 individuals with non-insulin-dependent diabetes mellitus. Am J Clin Nutr 1994;59:1265–9. [PubMed]
27. Salvini S, Parpinel M, Gnagnarella P, et al. Banca Dati di Composizione degli Alimenti per Studi Epidemiologici in Italia. Milano: Istituto Europeo di Oncologia, 1998. (WWW.IEO.IT).
28. Brighenti F, Casiraghi MC. Influenza dei processi di trasformazione sulla risposta glicemica ad alimenti amidacei. G Ital Nutr Clin Prev 1992;1:79–87.
29. Breslow NE, Day NE. Statistical methods in cancer research. Vol I. The analysis of case–control studies (IARC Scientific Publications No 32). Lyon: IARC, 1980.
30. Willett W, Stampfer MJ. Total energy intake: implications for epidemiologic analyses. Am J Epidemiol 1986;124:17–27. [PubMed]
31. WCRF/AICR. World Cancer Research Fund in association with American Institute for Cancer Research. Food nutrition and the prevention of cancer: a global perspective. Washington DC: American Institute for Cancer Research, 1997.
32. Favero A, Salvini S, Russo A, et al. Sources of macro- and micronutrients in Italian women: results from a food frequency questionnaire for cancer studies. Eur J Cancer Prev 1997;6:277–87. [PubMed]
33. Jenkins DJ, Wesson V, Wolever TM, et al. Wholemeal versus wholegrain breads: proportion of whole or cracked grain and the glycaemic response. BMJ 1988;297:958–60. [PMC free article] [PubMed]
34. Jenkins DJ, Wolever TM, Jenkins AL. Starchy foods and glycemic index. Diabetes Care 1988;11:149–59. [PubMed]
35. Ludwig DS, Majzoub JA, Al-Zahrani A, et al. High glycemic index foods, overeating, and obesity [abstract]. Pediatrics 1999;103:E26. [PubMed]
36. Tavani A, Bertuzzi M, Gallus S, et al. Diabetes mellitus as a contributor to the risk of acute myocardial infarction. J Clin Epidemiol 2002;55:1082–7. [PubMed]
37. Tavani A, Bertuzzi M, Negri E, et al. Alcohol, smoking, coffee and risk of non-fatal acute myocardial infarction in Italy. Eur J Epidemiol 2001;17:1131–7. [PubMed]
38. Wolever TM, Jenkins DJ, Jenkins AL, et al. The glycemic index: methodology and clinical implications. Am J Clin Nutr 1991;54:846–54. [PubMed]
39. Turrini A, Leclercq C, D’Amicis A. Patterns of food and nutrient intakes in Italy and their application to the development of food-based dietary guidelines. Br J Nutr 1999;81(suppl 2):S83–9. [PubMed]
Articles from Heart are provided here courtesy of
BMJ Group