Treatment Approaches- Food First For Weight Management And Health

Treatment Approaches: Food First for Weight Management and Health George L. Blackburn

Abstract BLACKBURN, GEORGE L. Treatment approaches: food first for weight management and health. Obes Res. 2001;9:223S–227S. Many genetic, environmental, behavioral, and cultural factors affect health. Diet is as vital as any of them for preventing disease and promoting well-being. We know that what we eat can lead to premature disability and mortality: to obesity, coronary heart disease, type 2 diabetes, degenerative arthritis, sleep apnea, and other illnesses. Now scientific evidence points to links between dietary patterns and illness. The study of these links is a new approach to understanding the role that diet plays in chronic disease. Initial studies include those on eating patterns and risk of colon cancer. More recently, researchers have investigated all-cause mortality and leading causes of chronic disease. Novel epidemiological approaches include factorial analysis to evaluate dietary patterns and cluster analysis to examine nutrient intake, gender, and weight status across food-pattern clusters. These methods work best within groups to identify major dietary patterns, but not necessarily ideal diets. They may also differ across population groups. The success of the Dietary Approaches to Stop Hypertension and Lyon Diet Heart studies supports the value of dietary pattern analysis. At the same time, the relative failure of single-nutrient studies underscores the need for new methodologies and directions in research. Key words: food section, dietary patterns, weight control, health

Introduction The study of dietary patterns is a new frontier in our efforts to understand the powerful role of food in health promotion and disease prevention. Although evidence from

Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts. Address correspondence to Dr. George L. Blackburn, Beth Israel Deaconess Medical Center, 1 Autumn Street, Kennedy 152, Boston, MA 02215. E-mail: [email protected] Copyright © 2001 NAASO

Dietary Approaches to Stop Hypertension (DASH) and similar control trials proves the value of scientifically sound food selection, there is a lack of evidence-based guidelines on which community strategies or individual interventions can be based. This article reviews the trends and innovations in food pattern study and considers their public health implications.

Food First Many genetic, environmental, behavioral, and cultural factors affect health (1). Diet is as important as any of them for preventing disease and promoting well-being. What we eat can make food one of life’s greatest pleasures or a prelude to illness, disability, and death. Appropriate diets are, by definition, adequate and balanced. They reflect age, stage of development, taste preferences, food habits, and other individual traits. They take into account socioeconomic conditions, the availability of foods, storage and preparation facilities, and cooking skills. They help reduce the risk of developing chronic degenerative diseases and conditions. That last statement, the outgrowth of our increasing insight into the links between diet and disease, is a critical one. We know that what we eat can lead to premature disability and mortality and to diseases such as obesity, heart disease, stroke, type 2 diabetes, degenerative arthritis, and sleep apnea. Now we need further study into the relationship between food patterns and health.

Growing Insight DASH (2,3) was among the first clinical trials to provide evidence linking dietary patterns to health (4 – 8). Designed to assess the relationship between the modification of food patterns and hypertension, it showed that existing dietary recommendations can produce concrete health results in a relatively healthy but sedentary population in which 50% of the participants were women and 60% were African American. Obarzanek et al. (9) applied the Framingham risk equation (10) to the results of their study to estimate 10-year risk of coronary heart disease (CHD) in subjects consuming the recommended DASH diet. The results showed a 12.1% OBESITY RESEARCH Vol. 9 Suppl. 4 November 2001

223S

Food First for Weight Management and Health, Blackburn

decreased risk of CHD in the participants consuming the DASH diet, compared with a slightly increased risk in those consuming the control diet. The decrease was achieved in the absence of changes in weight or physical activity. Reductions in blood lipids were greater in men than in women, whereas the lipid response to diet did not differ significantly between African American and nonAfrican American participants. The DASH study was not designed to assess the effect of a specific nutrient or cluster of nutrients on blood pressure. Still, data from DASH and other clinical trials (5–7) offer the most significant evidence to support the role of dietary patterns in health promotion as well as disease prevention and treatment.

Methodologies Initial studies of the role of dietary patterns in health promotion include use of cluster analysis by Tucker et al. (11) to describe the relations between whole-grain consumption with vegetables, fruit, and fish and the inverse association with meat. Their study of the dietary patterns of elderly Boston-area residents found four major food patterns corresponding to high consumption of the following: alcohol; milk, cereals, and fruits; bread and poultry; and meat and potatoes. In the alcohol group, the dominant fuel source (mean percentage of energy) was alcoholic beverages (19.5%). In the milk, cereal, and fruit food pattern, milk and milk products accounted for a mean of 18.8% of energy, fruits accounted for an average of 13.9% of energy, and breakfast cereals accounted for an average of 5% of energy. The dominant energy source in the bread and poultry group, an average of 22%, came from grains/breads and a mean of 6.6% of energy came from poultry. In the meat and potatoes group, a mean of 20.1% of energy came from meat and 16.6% came from grains/breads. More recently, Wirfalt and Jeffery (12) used cluster analysis to examine nutrient intake, gender, and weight status across the following six food-pattern clusters: soft drinks (soft drinks, fatty meat, snacks, pastry, cheese, chocolate, and spaghetti), pastry (pastry, fatty meat, snacks, chocolate, white bread, spaghetti, and salad dressing), skim milk (skim milk, fatty meat, dark bread, cereals, spaghetti, cheese, and snacks), meat (fatty meat, salad dressing, pastries, snacks, cheese, spaghetti, cereals, and soft drinks), meat/cheese (fatty meat, cheese, fruit juice, snacks, dark bread, salad dressing, spaghetti, and chicken), and white bread (white bread, fatty meat, salad dressing, cereals, snacks, pastry, margarine, and spaghetti). Data showed that body mass index (BMI) differed significantly across food-pattern clusters, with the highest average BMIs found in the soft drinks (30 kg/m2), meat (29.4 kg/m2), and white bread (29.3 kg/m2) food clusters. The BMIs in the remaining three groups were as follows: 28.5 kg/m2 (meat/cheese), 28.6 kg/m2 (pastry), and 28.9 kg/m2 (skim milk). 224S

OBESITY RESEARCH Vol. 9 Suppl. 4 November 2001

Early studies using factor analysis include the research of Slattery et al. (13) on eating patterns and the risk of colon cancer. Recently, Hu et al. (14) used factor analysis to examine whether overall dietary patterns derived from a food-frequency questionnaire predict the risk of diet-related chronic disease. Two major dietary patterns emerged: prudent, characterized by high intake of vegetables, fruit, legumes, whole grains, fish, and poultry and Western, characterized by high intake of red meat, processed meat, refined grains, sweets and desserts, French fries, and highfat dairy products. The analysis showed declining relative risk from the lowest to the highest quintiles of the prudent pattern score and increasing relative risk across quintiles of the Western pattern. Fung et al. (15) also used factor analysis to examine the relationship between dietary patterns (prudent and Western) and biomarkers of obesity and cardiovascular disease risk in a prospective cohort of 44,875 men 40 to 75 years old without diagnosed cardiovascular disease or cancer. The prudent pattern was characterized by higher intake of fruits, vegetables, whole grains, and poultry, i.e., healthy choices from the five major food groups: dairy (milk, yogurt, cheese, and buttermilk; excluding butter, cream cheese, and dairy desserts), fruit (fresh, frozen, dried, canned, and fruit juices), grains (breads, cereals, pastas, and rice; excluding pastries), meat and beans (poultry, fish, eggs, and meat alternatives, i.e., dried beans, nuts, and seeds), and vegetables (raw/cooked, fresh, frozen, canned, and juices). The Western pattern was characterized by higher intake of red meats, high-fat dairy products, and refined grains. Data showed significant positive correlations between the Western pattern and insulin, C-peptide, leptin, and homocysteine concentrations, and an inverse correlation with plasma folate concentrations. The prudent pattern was positively correlated with plasma folate and inversely correlated with insulin and homocysteine concentrations. The Healthy Eating Index, another approach to the study of dietary patterns, is a comprehensive measure of diet quality that combines multiple aspects of diet in relation to guidelines into a single score (16). The Healthy Eating Index is based on a 10-component (grain, vegetables, fruits, milk, meat, total fat, saturated fat, cholesterol, sodium, and variety) system of five food groups, four nutrients, and a measure of variety in food intake. The Interactive Health Eating Index (available at: www.usda.gov.cnpp) is an online dietary assessment tool for consumers. It compares types of foods and amounts eaten to the Food Guide Pyramid (17) and provides a score for each day that dietary information is entered. These approaches provide evidence that dietary patterns can be related to measures of health. Other studies that used cluster analysis have reached the same conclusion, particularly when the cohort was well-defined and restricted to one population. Based on such evidence, the revised dietary

Food First for Weight Management and Health, Blackburn

guidelines of the American Heart Association (18) place increased emphasis on foods and an overall eating pattern to achieve and maintain a healthy body weight. In identifying specific dietary approaches to conditions, such as dyslipidemia, diabetes, obesity, and hypertension, the current guidelines also have begun to incorporate an awareness of genetic and metabolic heterogeneity in optimizing population-based nutritional guidelines for individuals.

Genetic Advances Advances in genomic research have reinforced evidence that genetically influenced traits contribute to risk for cardiovascular disease as well as many other illnesses. In part, these influences operate through effects on nutritional and metabolic pathways that normally act to maintain physiological homeostasis and overall health. Many genes are involved, and a large number of variants of these genes exist among individuals and population subgroups. In recent years, there has been emerging evidence that this genetic variation can result in differing biological responses to specific nutrients, and, hence, in differing optimum requirements for these nutrients among individuals. Genetic influences have been identified for plasma lipoprotein responses (19 –23) to dietary fatty acids, cholesterol, and fiber; blood pressure responses to sodium; and homocysteine responses to folic acid. In addition, there is increasing evidence, primarily from animal models, for the roles of specific genes in influencing susceptibility to diet-induced obesity. More information, ultimately on a genomic scale, is needed before meaningful genetic algorithms can be developed for modifying dietary guidelines for individuals. Likewise, it may be that wider availability of methodology for detecting functionally important gene variants will make it possible to tailor dietary recommendations for individuals on the basis of this information. Although the prospects for this remain uncertain, there is already reason to infer that genetic variants predispose individuals to common conditions, such as dyslipidemia, diabetes, obesity, and hypertension, and may contribute to greater resistance or responsiveness to dietary prevention and management of these conditions. Individualized treatment from a knowledgeable health care provider should lead to a long and healthy life.

Public Health Food choices that form dietary patterns can guide the development of healthy diets for individuals, families, communities, and populations. Ecological observations show that distinct eating patterns are associated with different diet-related disease rates. Greece and Japan both have extremely low rates of diet-related chronic disease. Mediterranean and Asian diets, in turn, have attracted considerable interest as alternatives to the Western diet. Compared with

the typical American diet, traditional Mediterranean and Asian fare contains substantially more grains, legumes, vegetables, fruit, and fish. It also contains substantially less red meat, high-fat dairy, and other animal products. The DASH diet and similar diet patterns that include low-fat dairy products and a high intake of fruits, vegetables, and fiber, provide important guidelines for public health policy (24). They also underscore the recommendations in the new Dietary Guidelines for Americans (25) to eat a variety of foods from the five major food groups, i.e., a balanced and nutritious dietary pattern (26,27). Other lifestyle factors—such as activity levels, annual physical exams, and immunizations, monitoring of vital signs, and other preventive health measures—might also affect outcomes. This might be particularly true for exercise, which can be expected to raise high-density lipoprotein cholesterol and lower triglycerides, results not achieved by the DASH diet alone. Weight loss can also be expected to potentiate those outcomes. The lipid profile biomarkers of CHD risk are well-established (6,7,10), as are the salubrious effects of diets that include lower-fat milk products and certain fruits and vegetables, including legumes, potatoes, juices, apples, bananas, oranges, lettuce, spinach, string beans, and tomatoes. Dark green and orange vegetables and orange fruit are particularly healthful, as are whole and enriched grain products; the same holds true for leaner meats, poultry, and fish, as well as dried peas, beans, and lentils. Absence of information on various fruits and vegetables, however, may be problematic if only certain types and diversities confer protection, e.g., spinach, Brussel sprouts, broccoli, and string beans. These vegetables are particularly nutrient-dense and require little insulin for their digestion and metabolism.

Junk Food According to the Healthy Eating Index, important public health issues center on food energy, total fat, saturated fat, cholesterol, alcohol, iron, calcium, and sodium. Junk food, however, presents the greatest risk to the health and wellbeing of Americans. Kant (24) used data from the National Health and Nutrition Examination Survey III to study the intake of energy-dense, nutrient-poor foods among ⬎15,000 American adults. Energy-dense, nutrient-poor products fell into four food groups: visible fat (butter, margarine, oils, dressings, and gravies), sweeteners (sugars, syrup, candy, and carbonated and noncarbonated sweetened drinks), desserts (cookies, cakes, pies, pastries, ice cream, puddings, and cheesecake), salty snacks (potato, corn, and tortilla chips), and miscellaneous (coffee, tea, broth, and spices). Junk foods were defined as food products not included in the five major food groups, i.e., dairy, fruit, grains, meat and beans, and vegetables. OBESITY RESEARCH Vol. 9 Suppl. 4 November 2001

225S

Food First for Weight Management and Health, Blackburn

The data show that 33% of Americans consume 45% of their daily energy from junk food; that the average American consumes 27% of total daily energy from junk food, with an additional 4% from alcoholic beverages; and that women who eat fewer recommended foods are more likely to die from diet-related illnesses. According to Kant, highcalorie, high-fat junk foods are displacing healthier foods and are fueling the epidemic of obesity.

Outlook Dietary patterns are influenced by cultural, ethnic, and environmental factors, including the availability of foods, the ability to purchase and prepare foods, and food industry advertising. These patterns are not readily altered. The DASH diet, for example, requires twice the average daily servings of fruit, vegetables, and dairy products; onethird of the usual intake of pork, beef, and ham; one-half of the typical use of fats, oils, and salad dressings; and onefourth of the ordinary number of snacks and sweets. It also requires education for lactose-intolerant individuals on the use of lactase enzyme products and behavior modification to help change lifelong eating habits. The volume of food consumed from the five major food groups of the DASH diet is 1.94 kg (68.5 oz), whereas only 51 g (1.8 oz) comes from fats and sugars. This is twice the volume of healthful food and a fraction of the energy-dense, nutrient-poor junk food found in a typical Western diet. According to public-health researchers, those who make small incremental changes in their diets over time have the highest probability of success. Recommendations include the following: considering meat just one part of a meal; centering food choices around carbohydrates, such as pasta, rice, beans, or vegetables; and replacing traditional snacks and desserts with fruit or low-fat, low-energy foods, such as sugar-free gelatin. Adoption of these recommendations, together with other healthy practices, such as regular physical exercise and abstention from smoking, can contribute substantially to reducing the burden of dietrelated disease in the population. Portion-controlled foods and liquid meal replacements represent new approaches to healthful eating (3,5,7). Metz et al. (5) found that prepared meal plans improved weight loss and cardiovascular risk factors in overweight and obese patients. Other research indicates that the diets with the lowest percentage of calories from fat achieve the largest reductions in lipids (8). Schaefer et al. (28) studied lipid lowering and weight reduction in coronary heart patients taking statins. Results were based on 29 subjects (19 men and 10 postmenopausal women, mean age of 61 ⫾ 9 years, mean baseline (BMI of 32.4 ⫾ 5.4 kg/m2). Subjects received prepared foods that were delivered to their homes either once or twice a day. Menus averaged 67% carbohydrate, 16% protein, 17% fat, 4% saturated fat, 128 mg/d dietary cholesterol, 25 g/d fiber, and 2457 mg/d sodium. 226S

OBESITY RESEARCH Vol. 9 Suppl. 4 November 2001

Meals were individualized, with calorie levels adjusted by a dietitian to achieve weight loss (1 to 2 lb/wk) or maintenance (BMI goal of 23 kg/m2). After 4 weeks of the dietary modification program, there were significant reductions in weight, waist and hip circumferences, waist-to-hip ratio, BMI, total cholesterol, ( p ⬍ 0.001), and blood pressure ( p ⬍ 0.05). Additional reductions in weight, waist and hip circumferences, waist-to-hip ratio, and BMI ( p ⬍ 0.001) were seen at the end of 8 weeks. Mean weight after 8 weeks was 4% lower than at baseline, or 93.0 ⫾ 13.6 kg; mean high-density lipoprotein was 4% higher; and mean low-density lipoprotein 8% lower. At 8 weeks, the very-low-density lipoprotein triglyceride returned to the baseline value of a mean of 163 ⫾ 69 mg/dl. Subjects who had prepared meals delivered to their homes once a day were less likely to adhere to a self-selected meal plan; those who had meals delivered twice a day achieved the best outcomes. Current clinical studies targeted to changes in diet and exercise patterns stress the importance of community and individual challenges. Achieving the dietary pattern of DASH will require comprehensive therapeutic lifestyle changes (1). The Lyon Heart Study demonstrated that it is possible to achieve continued high adherence over the entire 46 months of mean follow-up per patient (29). This research and other dietary pattern trials provide significant and compelling evidence of the role of diet in promoting health and preventing chronic disease. It is incumbent on us to use that knowledge in the interest of public health (27). Blundell and Gillett (30) reported that a number of obese individuals show erratic patterns of food intake with little or no synchronism between feelings of hunger/fullness and eating. Because food provides one of life’s most accessible and potent forms of pleasure, food choices can be seen as behavior governed by hedonism within a permissive system for energy balance. Mela (31) noted that repeated dieting and a rigid all-or-nothing style contribute toward increasing susceptibility to breakdown of dietary restraint. An erratic pattern of food intake also seems to disrupt appropriate appetite regulation. Programs that provide a degree of structuring of the personal food environment while allowing flexibility of choices offer promising treatment options as well as the possibility of longer-term weight maintenance solutions. By better understanding why and where weight control efforts break down in the food choice process, steps can be taken to arm individuals against the causes of failure.

Acknowledgments Dr. Blackburn worked as a consultant and/or received research grants from food companies whose products are discussed in this article.

Food First for Weight Management and Health, Blackburn

References 1. Adult Treatment Panel III. Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. J Am Med Assoc. 2001;285: 2486 –97. 2. Appel LJ, Moore TJ, Obarzanek E, et al. A clinical trial of the effects of dietary patterns on blood pressure. DASH Collaborative Research Group. N Engl J Med. 1997;336:1117–24. 3. Sacks FM, Svetkey LP, Vollmer WM, et al. Effects on blood pressure of reduced dietary sodium and the Dietary Approaches to Stop Hypertension (DASH) diet. DASH-Sodium Collaborative Research Group. N Engl J Med. 2001;344:3–10. 4. Blackburn GL. The public health implications of the Dietary Approaches to Stop Hypertension Trial. Am J Clin Nutr. 2001;74:1–2. 5. Metz JA, Stern JS, Kris-Etherton P, et al. A randomized trial of improved weight loss with a prepared meal plan in overweight and obese patients: impact on cardiovascular risk reduction. Arch Intern Med. 2000;160:2150 – 8. 6. Chait A, Malinow MR, Nevin DN, et al. Increased dietary micronutrients decrease serum homocysteine concentrations in patients at high risk of cardiovascular disease. Am J Clin Nutr. 1999;70:881–7. 7. Haynes RB, Kris-Etherton P, McCarron DA, et al. Nutritionally complete prepared meal plan to reduce cardiovascular risk factors: a randomized clinical trial. J Am Diet Assoc. 1999;99:1077– 83. 8. McCarron DA, Oparil S, Chait A, et al. Nutritional management of cardiovascular risk factors: a randomized clinical trial. Arch Intern Med. 1997;157:169 –77. 9. Obarzanek E, Sacks FM, Vollmer WM, et al. Effects on blood lipids of a blood pressure-lowering diet: the Dietary Approaches to Stop Hypertension (DASH) trial. Am J Clin Nutr. 2001;74:1–100. 10. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837– 47. 11. Tucker KL, Dallal GE, Rush D. Dietary patterns of elderly Boston-area residents defined by cluster analysis. J Am Diet Assoc. 1992;92:1487–91. 12. Wirfalt AK, Jeffery RW. Using cluster analysis to examine dietary patterns: nutrient intakes, gender, and weight status differ across food pattern clusters. J Am Diet Assoc. 1997;97: 272–9. 13. Slattery ML, Boucher KM, Caan BJ, Potter JD, Ma KN. Eating patterns and risk of colon cancer. Am J Epidemiol. 1998;148:4 –16. 14. Hu FB, Rimm EB, Stampfer MJ, Ascherio A, Spiegelman D, Willett WC. Prospective study of major dietary patterns and risk of coronary heart disease in men. Am J Clin Nutr. 2000;72:912–21. 15. Fung TT, Rimm EB, Spiegelman D, et al. Association between dietary patterns and plasma biomarkers of obesity

16.

17.

18.

19.

20.

21. 22. 23.

24.

25.

26.

27.

28.

29. 30. 31.

and cardiovascular disease risk. Am J Clin Nutr. 2001;73: 61–7. Kennedy ET, Ohls J, Carlson S, Fleming K. The Healthy Eating Index: design and applications. J Am Diet Assoc. 1995; 95:1103– 8. U.S. Department of Agriculture. USDA Food Guide Pyramid. Home and Garden Bulletin. Washington, DC: U.S. Department of Agriculture Human Nutrition Information Service; 1992. Krauss RM, Eckel RH, Howard B, et al. AHA Dietary Guidelines: revision 2000: a statement for healthcare professionals from the Nutrition Committee of the American Heart Association. Circulation. 2000;102:2284 –99. Beynen AC, Katan MB, Van Zutphen LF. Hypo- and hyperresponders: individual differences in the response of serum cholesterol concentration to changes in diet. Adv Lipid Res. 1987;22:115–71. Schaefer EJ, Lamon-Fava S, Ausman LM, et al. Individual variability in lipoprotein cholesterol response to National Cholesterol Education Program Step 2 diets. Am J Clin Nutr. 1997;65:823–30. Dreon DM, Krauss RM. Diet-gene interactions in human lipoprotein metabolism. J Am Coll Nutr. 1997;16:313–24. Ordovas JM. The genetics of serum lipid responsiveness to dietary interventions. Proc Nutr Soc. 1999;58:171– 87. Tikkanen MJ, Huttunen JK, Ehnholm C, Pietinen P. Apolipoprotein E4 homozygosity predisposes to serum cholesterol elevation during high fat diet. Arteriosclerosis. 1990;10:285– 8. Kant AK, Schatzkin A, Graubard BI, Schairer C. Consumption of energy-dense, nutrient-poor foods by adult Americans: nutritional and health implications: the third National Health and Nutrition Examination Survey, 1988 –1994. Am J Clin Nutr. 2000;72:929 –36. U.S. Department of Health and Human Services. Dietary Guidelines for Americans. 5th ed. Washington, DC: U.S. Government Printing Office; 2000. French SA, Jeffery RW, Story M, et al. Pricing and promotion effects on low-fat vending snack purchases: the CHIPS Study. Am J Public Health. 2001;91:112–7. Blackburn GL. Functional foods in the prevention and treatment of disease: significance of the Dietary Approaches to Stop Hypertension Study. Am J Clin Nutr. 1997;66:1067–71. Schaefer E, Augustin J, McNamara J, et al. Lipid lowering and weight reduction by home-delivered dietary modification in coronary heart disease patients taking statins. Am J Cardiol. 2001;87:1000 –3. Leaf A. Dietary prevention of coronary heart disease: the Lyon Diet Heart Study. Circulation. 1999;99:733–5. Blundell JE, Gillett AA. Control of food intake in the obese. Obes Res. 2001;9(suppl):263S–70. Mela DJ. Determinants of food choice: relationships with obesity and weight control. Obes Res. 2001;9(suppl):249S–55.

OBESITY RESEARCH Vol. 9 Suppl. 4 November 2001

227S