Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-27T13:37:27.812Z Has data issue: false hasContentIssue false
  • English
  • Français

Dietary patterns, insulin sensitivity and adiposity in the multi-ethnic Insulin Resistance Atherosclerosis Study population

Published online by Cambridge University Press:  09 March 2007

Angela D. Liese ,
Mandy Schulz ,
Charity G. Moore  and
Elizabeth J. Mayer-Davis
Angela D. Liese*
Affiliation:
Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 800 Sumter street, Columbia, South Carolina 29208, USA
Mandy Schulz
Affiliation:
Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 800 Sumter street, Columbia, South Carolina 29208, USA German Institute of Human Nutrition, Department of Epidemiology, Potsdam-Rehbruecke, Germany
Charity G. Moore
Affiliation:
Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 800 Sumter street, Columbia, South Carolina 29208, USA
Elizabeth J. Mayer-Davis
Affiliation:
Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 800 Sumter street, Columbia, South Carolina 29208, USA Center for Research in Nutrition and Health Disparities, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
*
*Corresponding author: Dr Angela D. Liese, fax +1 803 777 2524, email, Liese@sc.edu
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Epidemiological investigations increasingly employ dietary-pattern techniques to fully integrate dietary data. The present study evaluated the relationship of dietary patterns identified by cluster analysis with measures of insulin sensitivity (SI) and adiposity in the multi-ethnic, multi-centre Insulin Resistance Atherosclerosis Study (IRAS, 1992–94). Cross-sectional data from 980 middle-aged adults, of whom 67% had normal and 33% had impaired glucose tolerance, were analysed. Usual dietary intake was obtained by an interviewer-administered, validated food-frequency questionnaire. Outcomes included SI, fasting insulin (FI), BMI and waist circumference. The relationship of dietary patterns to log(SI+1), log(FI), BMI and waist circumference was modelled with multivariable linear regressions. Cluster analysis identified six distinct diet patterns – ‘dark bread’, ‘wine’, ‘fruits’, ‘low-frequency eaters’, ‘fries’ and ‘white bread’. The ‘white bread’ and the ‘fries’ patterns over-represented the Hispanic IRAS population predominantly from two centres, while the ‘wine’ and ‘dark bread’ groups were dominated by non-Hispanic whites. The dietary patterns were associated significantly with each of the outcomes first at the crude, clinical level (P<0·001). Furthermore, they were significantly associated with FI, BMI and waist circumference independent of age, sex, race or ethnicity, clinic, family history of diabetes, smoking and activity (P<0.004), whereas significance was lost for SI. Studying the total dietary behaviour via a pattern approach allowed us to focus both on the qualitative and quantitative dimensions of diet. The present study identified highly consistent associations of distinct dietary patterns with measures of insulin resistance and adiposity, which are risk factors for diabetes and heart disease.

Keywords

DietEpidemiological studiesInsulin resistanceNutrition
Type
Review Article
Information
British Journal of Nutrition , Volume 92 , Issue 6 , December 2004 , pp. 973 - 984
Copyright
Copyright © The Nutrition Society 2004

References

Akin, JS, Guilkey, DK, Popkin, BM & Fanelli, MT (1986) Cluster analysis of food consumption patterns of older Americans. J Am Diet Assoc 86, 616–624.CrossRefGoogle ScholarPubMed
Bergman, RN, Finegood, DT & Ader, M (1985) Assessment of insulin sensitivity in vivo. Endocr Rev 6, 45–86.CrossRefGoogle ScholarPubMed
Borrud, LG, McPherson, RS, Nichaman, MZ, Pillow, PC & Newell, GR (1989) Development of a food frequency instrument: ethnic differences in food sources. Nutr Cancer 12, 201–211.CrossRefGoogle ScholarPubMed
Coates, RJ & Monteilh, CP (1997) Assessments of food-frequency questionnaires in minority populations. Am J Clin Nutr 65, 1108S–1115S.CrossRefGoogle ScholarPubMed
Dallongeville, J, Marecaux, N, Ducimetiere, P, Ferrieres, J, Arveiler, D, Bingham, A, Ruidavets, JB, Simon, C & Amouyel, P (1998) Influence of alcohol consumption and various beverages on waist girth and waist-to-hip ratio in a sample of French men and women. Int J Obes Relat Metab Disord 22, 1178–1183.CrossRefGoogle Scholar
Duncan, BB, Chambless, LE, Schmidt, MI, Folsom, AR, Szklo, M, Crouse, JR, III, Carpenter MA (1995) Association of the waist-to-hip ratio is different with wine than with beer or hard liquor consumption. Atherosclerosis Risk in Communities Study Investigators. Am J Epidemiol 142, 1034–1038.CrossRefGoogle ScholarPubMed
Fung, TT, Rimm, EB, Spiegelman, D, Rifai, N, Tofler, GH, Willett, WC & Hu, FB (2001) Association between dietary patterns and plasma biomarkers of obesity and cardiovascular disease risk. Am J Clin Nutr 73, 61–67.CrossRefGoogle ScholarPubMed
Herbert, V, Lau, KS, Gottlieb, CW & Bleicher, SJ (1965) Coated charcoal immunoassay of insulin. J Clin Endocrinol Metab 25, 1375–1384.CrossRefGoogle ScholarPubMed
Hu, FB, Rimm, E, Smith-Warner, SA, Feskanich, D, Stampfer, MJ, Ascherio, A, Sampson, L & Willett, WC (1999) Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire. Am J Clin Nutr 69, 243–249.CrossRefGoogle ScholarPubMed
Hu, FB, Rimm, EB, Stampfer, MJ, Ascherio, A, Spiegelman, D & Willett, WC (2000) Prospective study of major dietary patterns and risk of coronary heart disease in men. Am J Clin Nutr 72, 912–921.CrossRefGoogle ScholarPubMed
Hu, FB & Willett, WC (2001) Diet and coronary heart disease: findings from the Nurses' Health Study and Health Professionals' Follow-up Study. J Nutr Health Aging 5, 132–138.Google ScholarPubMed
Jacobs, DR, Jr, Steffen LM (2003) Nutrients, foods, and dietary patterns as exposures in research: a framework for food synergy. Am J Clin Nutr 78, 508S–513S.CrossRefGoogle ScholarPubMed
Kleinbaum, D, Kupper, LL & Muller, KE (1988) Applied Regression Analysis and Other Multivariable Methods. Boston, MA: PWS-KENT Publishing Company.Google Scholar
Liese, AD, Roach, AK, Sparks, KC, Marquart, L, D'Agostino, RB Jr & Mayer-Davis, EJ (2003) Whole-grain intake and insulin sensitivity: the Insulin Resistance Atherosclerosis Study. Am J Clin Nutr 78, 965–971.CrossRefGoogle ScholarPubMed
Manson, JE, Nathan, DM, Krolewski, AS, Stampfer, MJ, Willett, WC & Hennekens, CH (1992) A prospective study of exercise and incidence of diabetes among US male physicians. JAMA 268, 63–67.CrossRefGoogle ScholarPubMed
Maskarinec, G, Novotny, R & Tasaki, K (2000) Dietary patterns are associated with body mass index in multiethnic women. J Nutr 130, 3068–3072.CrossRefGoogle ScholarPubMed
Mayer-Davis, EJ, D'Agostino, R Jr, Karter, AJ, Haffner, SM, Rewers, MJ, Saad, M, Bergman, RN (1998) Intensity and amount of physical activity in relation to insulin sensitivity: the Insulin Resistance Atherosclerosis Study. JAMA 279, 669–674.CrossRefGoogle ScholarPubMed
Mayer-Davis, EJ, Vitolins, MZ, Carmichael, SL, Hemphill, S, Tsaroucha, G, Rushing, J & Levin, S (1999) Validity and reproducibility of a food frequency interview in a Multi-Cultural Epidemiology Study. Ann Epidemiol 9, 314–324.CrossRefGoogle Scholar
Millen, BE, Quatromoni, PA, Copenhafer, DL, Demissie, S, O'Horo, CE, D'Agostino, RB (2001) Validation of a dietary pattern approach for evaluating nutritional risk: the Framingham Nutrition Studies. J Am Diet Assoc 101, 187–194.CrossRefGoogle ScholarPubMed
Morrison, DF (1990) Multivariate Statistical Methods, 3rd ed. New York: McGraw-HillGoogle Scholar
Newby, PK, Muller, D, Hallfrisch, J, Qiao, N, Andres, R & Tucker, KL (2003) Dietary patterns and changes in body mass index and waist circumference in adults. Am J Clin Nutr 77, 1417–1425.CrossRefGoogle ScholarPubMed
Pacini, G & Bergman, RN (1986) MINMOD: a computer program to calculate insulin sensitivity and pancreatic responsivity from the frequently sampled intravenous glucose tolerance test. Comput Methods Programs Biomed 23, 113–122.CrossRefGoogle ScholarPubMed
Pryer, JA, Nichols, R, Elliot, P, Thakrar, B, Brunner, E & Marmot, M (2001) Dietary patterns among a national random sample of British adults. J Epidemiol Community Health 55, 29–37.CrossRefGoogle ScholarPubMed
Romesburg, HC (1984) Cluster Analysis for Researchers. Belmont, CA Lifetime Learning PublicationsGoogle Scholar
Rosner, B (2000) Fundamentals of Biostatistics 5th ed. Pacific Grove, CA Duxbury PressGoogle Scholar
Saad, MF, Anderson, RL, Laws, A, Watanabe, RM, Kades, WW, Chen, YD, Sands, RE, Pei, D, Savage, PJ & Bergman, RN (1994) A comparison between the minimal model and the glucose clamp in the assessment of insulin sensitivity across the spectrum of glucose tolerance. Insulin Resistance Atherosclerosis Study. Diabetes 43, 1114–1121.CrossRefGoogle ScholarPubMed
Togo, P, Osler, M, Sorensen, TI & Heitmann, BL (2001) Food intake patterns and body mass index in observational studies. Int J Obes Relat Metab Disord 25, 1741–1751.CrossRefGoogle ScholarPubMed
Tseng, M & DeVellis, RF (2001) Fundamental dietary patterns and their correlates among US whites. J Am Diet Assoc 101, 929–932.CrossRefGoogle ScholarPubMed
Tseng, M, DeVellis, RF, Maurer, KR, Khare, M, Kohlmeier, L, Everhart, JE & Sandler, RS (2000) Food intake patterns and gallbladder disease in Mexican Americans. Public Health Nutr 3, 233–243.CrossRefGoogle ScholarPubMed
Vadstrup, ES, Petersen, L, Sorensen, TI & Gronbaek, M (2003) Waist circumference in relation to history of amount and type of alcohol: results from the Copenhagen City Heart Study. Int J Obes Relat Metab Disord 27, 238–246.CrossRefGoogle ScholarPubMed
van Dam, RM, Grievink, L, Ocke, MC & Feskens, EJ (2003) Patterns of food consumption and risk factors for cardiovascular disease in the general Dutch population. Am J Clin Nutr 77, 1156–1163.CrossRefGoogle ScholarPubMed
van Dam, RM, Rimm, EB, Willett, WC, Stampfer, MJ & Hu, FB (2002) Dietary patterns and risk for type 2 diabetes mellitus in U. S. men. Ann Intern Med 136, 201–209.CrossRefGoogle ScholarPubMed
Wagenknecht, LE, Mayer, EJ & Rewers, M (1995) The Insulin Resistance Atherosclerosis Study (IRAS) objectives, design, and recruitment results. Ann Epidemiol 5, 464–472.CrossRefGoogle ScholarPubMed
Wirfält, E, Mattisson, I, Gullberg, B & Berglund, G (2000) Food patterns defined by cluster analysis and their utility as dietary exposure variables: a report from the Malmo Diet and Cancer Study. Public Health Nutr 3, 159–173.CrossRefGoogle Scholar
Wirfält, E, Hedblad, B, Gullberg, B, Mattisson, I, Andren, C, Rosander, U, Janzon, L & Berglund, G (2001) Food patterns and components of the metabolic syndrome in men and women: a cross-sectional study within the Malmo Diet and Cancer cohort. Am J Epidemiol 154, 1150–1159.CrossRefGoogle Scholar
World Health Organization (1985) Diabetes Mellitus. Technical Report Series no. 727 Geneva: WHO.Google Scholar
Yang, YJ, Youn, JH & Bergman, RN (1987) Modified protocols improve insulin sensitivity estimation using the minimal model. Am J Physiol 253, E595–E602.Google ScholarPubMed