Importance of Understanding Food Consumption Patterns

Importance of Understanding Food Consumption Patterns

46. Zemel MB, Miller SL. Dietary calcium and dairy modulation of adiposity and obesity risk. Nutr Rev. 2004;62:125-131. 47. Johnston CS, Tjonn SL, Swa...

65KB Sizes 0 Downloads 14 Views

46. Zemel MB, Miller SL. Dietary calcium and dairy modulation of adiposity and obesity risk. Nutr Rev. 2004;62:125-131. 47. Johnston CS, Tjonn SL, Swan PD. High-protein, lowfat diets are effective for weight loss and favorably alter biomarkers in healthy adults. J Nutr. 2004;134: 586-591. 48. Tucker KL. Dietary intake and coronary heart disease: A variety of nutrients and phytochemicals are important. Curr Treat Options Cardiovasc Med. 2004;6:291-302. 49. Hallfrisch J, Behall KM. Mechanisms of the effects of grains on insulin and glucose responses. J Am Coll Nutr. 2000;19(suppl 3):320S-325S. 50. Dietary Guidelines for Americans 2005. Available at: http://www.healthierus.gov/dietaryguidelines/. Accessed November 10, 2006. 51. Sanchez-Villegas A, Martinez-Gonzalez MA, Toledo E, de Irala-Estevez J, Martinez JA. Relative role of physical inactivity and snacking between meals in weight gain. Med Clin (Barc). 2002;119:46-52. 52. Breslow RA, Smothers BA. Drinking patterns and body mass index in never smokers: National Health Interview Survey, 1997-2001. Am J Epidemiol. 2005; 161:368-376. 53. Colhoun, Prescott-Clarke. Health survey for England 1994. Cited by: McLaren L, Kuh D. Women’s body dissatisfaction, social class, and social mobility. Soc Sci Med. 2004;58:1575-1584. 54. Neumark-Sztainer D, Story M, Perry C, Casey MA. Factors influencing food choices of adolescents: Findings from focus-group discussions with adolescents. J Am Diet Assoc. 1999;99:929-937. 55. Moore AA, Gould R, Reuben DB, Greendale GA, Carter MK, Zhou K, Karlamangla A. Longitudinal patterns and predictors of alcohol consumption in the United States. Am J Public Health. 2005;95:458-465. 56. Sacco RL, Kargman DE, Zamanillo MC. Race-ethnic differences in stroke risk factors among hospitalized patients with cerebral infarction: The Northern Manhattan Stroke Study. Neurology. 1995;45:659-663. 57. Stockwell T, Donath S, Cooper-Stanbury M, Chikritzhs T, Catalano P, Mateo C. Under-reporting of alcohol consumption in household surveys: A com-

58.

59. 60. 61. 62.

63. 64.

65.

66. 67.

68.

parison of quantity-frequency, graduated-frequency, and recent recall. Addiction. 2004;99:1024-1033. Goodman E, Adler NE, Daniels SR, Morrison JA, Slap GB, Dolan LM. Impact of objective and subjective social status on obesity in a biracial cohort of adolescents. Obes Res. 2003;11:1018-1026. Block JP, Scribner RA, DeSalvo KB. Fast food, race/ ethnicity, and income: A geographic analysis. Am J Prev Med. 2004;27:211-217. Reedy J, Haines PS, Campbell MK. The influence of health behavior clusters on dietary change. Prev Med. 2005;41:268-275. Case control and cross-sectional studies. In: Gordis L. Epidemiology. 2nd ed. Philadelphia, PA: WB Saunders; 2000:153-155. Willett WC, Sampson L, Stampfer MJ, Rosner B, Bain C, Witschi J, Hennekens CH, Speizer FE. Reproducibility and validity of a semiquantitative food frequency questionnaire. Am J Epidemiol 1985;122:51-65. Nicklas TA. Dietary studies of children and young adults (1973-1988): The Bogalusa Heart Study. Am J Med Sci. 1995;310(suppl 1):S101-S108. Yoo S, Nicklas T, Baranowski T, Zakeri IF, Yang SJ, Srinivasan SR, Berenson GS. Comparison of dietary intakes associated with metabolic syndrome risk factors in young adults: The Bogalusa Heart Study. Am J Clin Nutr. 2004;80:841-848. US Department of Agriculture, Human Nutrition Information Service, Nutrition Monitoring Division. Nationwide Food Consumption Survey, Continuing Survey of Food Intake by Individuals, Women 19-50 Years and Children 1-5 Years, 1986. Hyattsville, MD: US Department of Agriculture; 1988. NFCS-CSFII Report No. 86-93. Willett WC. Nutritional Epidemiology. New York, NY: Oxford University Press; 1998. Mendez MA, Wynter S, Wilks R, Forrester T. Underand overreporting of energy is related to obesity, lifestyle factors, and food group intakes in Jamaican adults. Public Health Nutr. 2004;7:9-19. Melanson EL Jr, Freedson PS. Physical activity assessment: A review of methods. Crit Rev Food Sci Nutr. 1996;36:385-396.

APPLICATION

Importance of Understanding Food Consumption Patterns

I

dentifying significant relationships between food group consumption and socio-economic, demographic, and lifestyle variables in the US young adult population has important considerations for the clinical practitioner.

This article was written by Hope Barkoukis, PhD, RD, assistant professor, Nutrition Department, School of Medicine, Case Western Reserve University, Cleveland, OH. doi: 10.1016/j.jada.2006.12.024

234

February 2007 Volume 107 Number 2

Food consumption patterns are relevant to disease risk (1-3), reflect ethnic differences in eating behaviors (4,5), and form the basis for how we approach assessment of dietary intake (6). Examining patterns of food group consumption has emerged as an important focal point for understanding the role of diet in disease risk (3,7,8). Attention to food groups, instead of singular nutrients, is more likely to reflect habitual food intake (1,4,7), and embody charac-

teristics of the total diet, including all nutrient interactions (7). Accordingly, nutritional epidemiology has recently linked consumption of various food groups, or dietary patterns, to differences in disease outcomes. Dietary patterns characterized by high intakes of fruits, vegetables, legumes, fish, poultry, whole grains, and lowfat dairy products have been associated with lower risks of cancer (9), coronary heart disease (1,2,7,10,11), reduced total mortality, (12), and inversely associated with C-reactive protein (8,13). Conversely, high consumption of carbohydrates classified as high glycemic index have been associated with an increased risk of type 2 diabetes (1,10,14,15), and coronary heart disease (16). Thus, dietary intake patterns appear to be relevant to disease risk. Dietary patterns reflect different ethnic eating traditions (4,17). Mediterranean and Asian diets are widely known to incorporate higher intakes of legumes, fish, vegetables, and fruits, contrasted with the American dietary pattern consisting of higher intakes of deep-fried fast foods, refined grains, processed meats, commercially baked products, and sweets (1). Understanding these ethnic differences in food group consumption becomes increasingly significant in the United States as the US Census Bureau reported that between 1990 to 2000, the foreign-born population increased by 57% to represent 13% of the US population (18). Moreover, ethnic differences in food consumption have significant health implications. Ethnicity has been identified as a factor in the prevalence disparity in chronic diseases including type 2 diabetes mellitus and cardiovascular disease that persists in all age groups (19). Risk of obesity, type 2 diabetes mellitus, and cardiovascular disease is increased in children and adolescents of African-American, Hispanic, and Native American ethnicities as contrasted to whites (20). Therefore, since it will become the rule and not the exception for practitioners to counsel widely diverse populations, their nutrition education strategies will need to be tailored to reflect these ethnic dietary patterns. Focusing on food group consumption as a method of assessing dietary intake is an expanding frontier for nutrition research (21). Dietary intake data collected via food frequency questionnaires (FFQs) are classified into food groups on the basis of similarity in nutrient composition or their dominant foods (1,7,21,22). These data are then further analyzed using a variety of statistical techniques such as factor or cluster analysis to identify food group patterns, or dietary patterns, of food consumption (3,21). Accurate representation of dietary intake is achieved when the FFQ reflects the target population being investigated (4,5). This study utilized an FFQ specifically targeted to youth/adolescents (23), and noted support for assessment tools that have been validated for the populations being studied. As we learn more about the influence of various sociodemographic factors differentiating food consumption patterns, it becomes critical to ensure that the design of the FFQ captures these variables adequately (4) and can be subsequently validated in the target population studied. Accordingly, the findings of differences in food group intake influenced by ethnicity in this study should, therefore, also be extrapolated to highlight the value of designing and utilizing

culture-specific FFQs when studying diverse populations, as has been also described by others (4,5). Understanding food consumption patterns will increasingly play an important role in shaping nutrition education strategies for the practitioner and guiding the development of public health interventions for the US population. The identification of relationships between food group consumption to socioeconomic, demographic, and lifestyle characteristics in young adults in Bogalusa, LA as described will facilitate this process. References 1. Hu F, Rimm E, Stampfer M, Ascherio A, Spiegelman D, Willett W. Prospective study of major dietary patterns and risk of coronary heart disease in men. Am J Clin Nutr. 2000;72:912-921. 2. Jacobs DR, Steffen LM. Nutrients, foods, and dietary patterns as exposures in research: A framework for food synergy. Am J Clin Nutr. 2003;78(suppl 3):508S513S. 3. Kant AK. Dietary patterns and health outcomes. J Am Diet Assoc. 2004;104:615-635. 4. Teufel NI. Development of culturally competent food frequency questionnaires. Am J Clin Nutr. 1997; 65(suppl 4):1173S-1178S. 5. Jerome NW. Culture-specific strategies for capturing local dietary intake patterns. Am J Clin Nutr. 1997; 65(suppl 4):1166S-1167S. 6. Krebs-Smith S, Cleveland L, Ballard-Barbash R, Cook D, Kahle L. Characterizing food intake patterns of American adults. Am J Clin Nutr. 1997:65(suppl); 1264S-1268S. 7. Kerver JM, Yang EJ, Bianchi L, Song WO. Dietary patterns associated with risk factors for cardiovascular disease healthy US adults. Am J Clin Nutr. 2003; 78: 1103-1110. 8. Schulze MB, Hoffmann KH, Manson JE, Willett WC, Meigs J, Weikert C, Heidemann C, Colditz GA, Hu FB. Dietary pattern, inflammation, and incidence of type 2 diabetes in women. Am J Clin Nutr. 2005;82: 675-684. 9. Slattery ML, Bouher KM, Caan BJ, Potter JD, Ma KN. Eating patterns and risk of colon cancer. Am J Epidemiol. 1998:148:4-16. 10. Fraser GE, Sabate J, Beeson WL, Strahan TM. A possible protective effect of nut consumption on risk of coronary heart disease. The Adventist Health Study. Arch Intern Med. 1992;152:1416-1424. 11. Liu S, Stampfer MJ, Hu FB, Giovannucci E, Rimm E, Manson JE, Hennekens CH, Willett WC. Whole grain consumption and risk of coronary heart disease: Results from the Nurses’ Health Study. Am J Clin Nutr. 1999;70:412-419. 12. Trichopoulou A, Kouris-Blazos A, Wahlqvist M. Diet and over-all survival in elderly people. BMJ. 1995; 311;1457-1460. 13. Lopez-Garcia E, Schulze M, Fung T, Meigs J, Rifai N, Manson J. Major dietary patterns are related to plasma concentrations of markers of inflammation and endothelial dysfunction. Am J Clin Nutr. 2004; 80:1029-1035. 14. Salmeron J, Manson JE, Stampfer MJ, Colditz GA, Wing AL, Willett WC. Dietary fiber, glycemic load,

February 2007 ● Journal of the AMERICAN DIETETIC ASSOCIATION

235

15. 16. 17.

18.

19.

236

and risk of non-insulin-dependent diabetes mellitus in women. JAMA. 1997;277:472-477. Salmeron J, Ascherio A, Rimm EB. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care. 1997;20:545-550. Leeds AR. Glycemic index and heart disease. Am J Clin Nutr. 2002;76(suppl 1):286S-289S. Satia-Abouta J, Patterson RE, Neuhouser ML, Elder J. Dietary Acculturation: Applications to nutrition research and dietetics. J Am Diet Assoc. 2002;102: 1105-1118. US Census Bureau. United States Foreign-Born Population. Available at: http://www.census.gov/ www/socdemo/foreign.html. Accessed October 9, 2006. Lindquist C, Gorver B, Goran M. Role of dietary factors in ethnic differences in early risk of coronary vascular disease and type 2 diabetes mellitus. Am J Clin Nutr. 2000;71:725-732.

February 2007 Volume 107 Number 2

20. Goran M, Ball G, Cruz M. Obesity and risk of type 2 diabetes mellitus and cardiovascular disease in children and adolescents. J Clin Endocrinol Metab. 2003; 88:1417-1427. 21. Newby PK, Muller D, Hallfrisch J, Andres R, Tucker K. Food patterns measured by factor analysis and anthropometric changes in adults. Am J Clin Nutr. 2004;80:413-504. 22. Dixon LB, Balder JF, Virtanen MJ, Rashidkhani B, Mannisto S, Krogh V, van Den Brandt PA, Hartman AM, Pietinen P, Tan F, Virtamo J, Wolk A. Dietary patterns associated with colon and rectal cancer: Results from the dietary patterns and cancer (DIETSCAN) project. Am J Clin Nutr. 2004;80:10031011. 23. Willett WC, Sampson L, Stampfer MJ. Reproducibility and validity of a semi-quantitative food frequency questionnaire. Am J Epidemiol. 1985;122: 51-65.