Carbohydrate Quantity and Quality in Relation to Body Mass Index

RESEARCH Review

Continuing Education Questionnaire, page 1782 Meets Learning Need Codes 2070, 5000, 5370, and 9020

Carbohydrate Quantity and Quality in Relation to Body Mass Index GLENN A. GAESSER, PhD

ABSTRACT The increased prevalence of overweight and obesity in the United States since approximately 1980 is temporally associated with an increase in carbohydrate intake, with no appreciable change in absolute intake of fat. Despite speculation that both carbohydrate quantity and quality have contributed significantly to excess weight gain, the relationship between carbohydrate intake and body mass index (BMI) is controversial. A review of relevant literature indicates that most epidemiologic studies show an inverse relationship between carbohydrate intake and BMI, even when controlling for potential confounders. These observational studies are supported by results from a number of dietary intervention studies wherein modest reductions in body weight were observed with an ad libitum, low-fat, high-carbohydrate diet without emphasis on energy restriction or weight loss. With few exceptions, high glycemic load is associated with lower BMI, even when adjusted for total energy intake. Data on the association between glycemic index and BMI are not as consistent, with more studies showing either no association or an inverse relationship, rather than a positive relationship. Whole-grain intake is generally inversely associated with BMI; refined grain intake is not. Because overall dietary quality tends to be higher for high-carbohydrate diets, a low-fat dietary strategy with emphasis on fiber-rich carbohydrates, particularly cereal fiber, may be beneficial for health and weight control. J Am Diet Assoc. 2007;107:1768-1780.

G. A. Gaesser is a professor of exercise physiology, Department of Human Services, University of Virginia, Charlottesville. Address correspondence to: Glenn A. Gaesser, PhD, 210 Emmet St S, PO Box 400407, Charlottesville, VA 22904-4407. E-mail: [email protected] Copyright © 2007 by the American Dietetic Association. 0002-8223/07/10710-0013$32.00/0 doi: 10.1016/j.jada.2007.07.011

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A

n estimated 66% of adult Americans are considered overweight, with a body mass index (BMI; calculated as kg/m2) of 25 to 29.9, or obese, with a BMI ⱖ30 (1). Average weights of American workers aged ⬎18 years increased at a rate of 0.61% per year from 1986 to 1995; from 1997 to 2002, the rate increased 0.95% per year (2). Contributing causes of this weight gain are largely environmental (3). Per capita food energy in the US food supply has increased steadily over the past 40 years, from about 3,100 kcal/day in 1965 to an all-time high of 3,900 kcal/day in 2000 (Figure 1) (4). This coincides with National Health and Nutrition Examination Surveys data that indicated an increase in reported daily energy intake between 1971 and 2000 of 168 kcal in men and 335 kcal in women (Figure 2) (5). Because levels of leisure-time physical activity among US adults remained stable or increased slightly between 1990 and 2004 (6,7), increased energy intake likely explains much of the weight gain experienced by Americans during this time. The increase in reported energy intake since 1970 occurred in conjunction with an increase in the consumption of carbohydrates, which rose by 60 to 70 g/day (5). By contrast, reported intake of fat remained relatively stable between 1971 and 2000 (Figure 3) (5). Consequently, fat intake, as a percentage of total energy, actually decreased slightly during this period. Because the increase in obesity prevalence occurred during a period in which public health messages encouraged low-fat eating, proponents of low-carbohydrate diets attributed Americans’ weight gain to carbohydrates. As a result, a variety of low-carbohydrate diets became popular in the past 10 years (8-11). However, popularity of low-carbohydrate diets has waned considerably since their peak in 2004, in much the same manner that interest in these diets all but disappeared in the mid-1970s after nearly a decade of popularity (12-14). Loss of enthusiasm for carbohydrate-restrictive eating plans most likely is attributable to their lack of sustainability (15,16). The role of diet composition in weight control and obesity remains controversial (17,18). Carbohydrate quality and quantity has received considerable attention (19-23). Several reports suggest that diets with a high glycemic index or glycemic load, or that are high in refined carbohydrates, increase risk of obesity and associated health problems (19-22), although the hypothesized link be-

© 2007 by the American Dietetic Association

Figure 1. Increase in daily food energy in the US food supply, per capita per day: 1909 to 2000. (Reprinted from reference 4.)

Figure 3. Mean intake of carbohydrate (CHO) and fat among adults aged 20 to 74 years from the National Health and Nutrition Examination Surveys, United States, 1971 to 2000. (Data from reference 5.)

Figure 2. Mean energy intake among adults aged 20 to 74 years by sex from the National Health and Nutrition Examination Surveys, United States, 1971 to 2000. (Data from reference 5.)

tween carbohydrate quality and quantity and either obesity and disease risk is controversial (23). To examine the relevant literature on the association between both carbohydrate quantity and quality and BMI, the Institute for Scientific Information’s Web of Science was searched using key words body mass index and body weight matched separately to carbohydrates, glycemic index, glycemic load, and grains (whole and refined). Bibliographies of extracted citations were also used to identify relevant publications. The primary focus was on epidemiological studies that provided information on BMI stratified across quartiles/quintiles of carbohydrate intake, glycemic index, glycemic load, and either whole- or refined-grains. Because several reviews of the influence of ad libitum, low-fat diets on body weight have been published (24-28), additional intervention studies wherein participants were assigned to an ad libitum, low-fat diet, without focus on energy restriction, were also examined. EPIDEMIOLOGIC EVIDENCE Carbohydrate Intake Most epidemiologic studies show an inverse association between carbohydrate consumption and BMI (29-41). In

the seven women cohorts presented in Table 1, the mean BMI of the group with the highest carbohydrate intake is between 0.5 and 3.0 BMI units lower than that of the group with the lowest carbohydrate intake. For the four male cohorts the mean BMI is between 0.6 and 1.3 BMI units lower for men with the highest compared to the lowest carbohydrate intake. Carbohydrate intake was found to be inversely related to body weight and percent body fat in Danish men and women (40). Among women in the Cancer Prevention Study II Nutrition Cohort, higher carbohydrate intake was associated with lower risk of obesity (41). The limitation of these observational data is that cause and effect cannot be established. However, longitudinal observational studies are consistent with these findings. In the Baltimore Longitudinal Study of Aging the dietary pattern characterized by the highest carbohydrate consumption (61.9% of total energy) had the lowest annual gain in BMI and waist circumference (37). Methodologic Considerations Underreporting of food intake is well documented (42). This is especially true for the semiquantitative food frequency questionnaire used in most studies (eg, 3136,39,41). Of additional concern is the observation that underreporting is inversely related to BMI (42). However, two of the studies listed in Table 1 used intervieweradministered 24-hour dietary recall (29,30), which minimizes underreporting (42). In the Continuing Survey of Food Intakes by Individuals (30), the US Department of Agriculture multiple-pass 24-hour recall method was used. An observational validation study of this method in men revealed no differences between actual and reported energy intake and that accuracy of recall was not related to BMI (43). Inasmuch as the inverse association between carbohydrate intake and BMI in the Continuing Survey of Food Intake by Individuals is similar to that of the other studies in Table 1 (that used the food frequency

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Table 1. Relationship between carbohydrate intake and body mass index among men and women in eight cohorts revieweda Quintile (Quartile) of Carbohydrate Intake Cohort

I

II

III

IV

V

Women NHANESb (29) n⫽6,125 CSFIIe (30) n⫽4,711 NHSf I (31) n⫽71,919 NHS II (34) n⫽90,655 WHSh (35) n⫽38,446 PLCOi (39) n⫽18,341 Canadian NBSSj (36) n⫽49,111

26.3⫾0.2c 35.6d 26.7⫾0.5c 0 to 30d 25.2⫾4.6g 34.8d 26 41.2d 26.7⫾5.4g 41.7d 27.4⫾5.6g 44.1d 25.2⫾10.2g 28.5d

26.4⫾0.3c 44.6d 26.0⫾0.2c 30 to 45d 25.2⫾4.6g 39.5d

26.1⫾0.4 50.4d 25.7⫾0.1c 45 to 55d 25.1⫾4.6g 42.2d 25 50.1d 26.1⫾5.0g 50.5d 27.2⫾5.6g 51.9d 24.7⫾10.2g 38.8d

25.9⫾0.2c 56.4d 25.2⫾0.2c ⬎55d 24.9⫾4.6g 46.5d

25.5⫾0.2c 66.8d

Men NHANES (29) n⫽5,730 CSFII (30) n⫽5,075 HPFSk (31) n⫽39,926 PLCO (39) n⫽20,172

26.8⫾0.3c 33.2d 26.8⫾0.4c 0 to 30d 26.1⫾3.4g 37.5d 28.1⫾4.4g 39.5d

26.5⫾0.2c 42.7d 26.8⫾0.2c 30 to 45d 25.9⫾3.3g 43.6d

26.4⫾0.2c 48.5d 26.3⫾0.1c 45 to 55d 25.6⫾3.2g 47.7d 27.6⫾4.1g 47.6d

26.3⫾0.2c 54.3d 26.0⫾0.2c ⬎55d 25.3⫾3.2g 52.5d

26.3⫾5.0g 46.8d 25.1⫾10.2g 35.3d

25.7⫾4.8g 54.6d 24.6⫾10.2g 42.1d

24.7⫾4.5g 55.1d 23 59.4d 25.2⫾4.7g 63.6d 26.5⫾5.2g 59.0d 24.3⫾10.2g 47.9d

26.2⫾0.3c 64.3d 24.8⫾3.2g 61.5d 26.8⫾3.9g 55.9d

a

Not all studies reported standard error of the mean or standard deviation. NHANES⫽National Health and Nutrition Examination Survey. c Body mass index⫾standard error of the mean. d Mean or range of carbohydrate intake as a percentage of total energy within each quintile/quartile. e CSFII⫽Continuing Survey of Food Intakes by Individuals. f NHS⫽Nurses’ Health Study. g Body mass index⫾standard deviation. h WHS⫽Women’s Health Study. i PLCO⫽Prostate, Lung, Colorectal, and Ovarian Screening Study. j NBSS⫽National Breast Screening Study. k HPFS⫽Health Professionals Follow-up Study. b

questionnaire), it is unlikely that underreporting would entirely undermine this relationship. Although some studies report that high carbohydrate consumption is associated with lower total energy intake (2931), most studies suggest that lower BMI among high-carbohydrate consumers is not related to lower total energy intake (32,34-37,44-46). In the Nurses’ Health Study (NHS) II cohort the highest quintile of carbohydrate consumption had a mean BMI three units lower (ie, 26 vs 23) than women in the lowest quintile of carbohydrate consumption, even when adjusted for total energy intake (34). Lower BMI in high-carbohydrate/energy consumers may be related to higher reported physical activity (35,46). However, in the Framingham Offspring Study the lower BMI associated with high carbohydrate and total energy consumption was not attributable to differences in physical activity (45). Furthermore, the lower BMI (1.1 units) among the highest quintile (compared to lowest quintile) of carbohydrate consumption in an anal-

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ysis of combined NHS I and II cohorts was not attributable to either lower reported energy intake or higher reported physical activity (32). High consumption of carbohydrates tends to be associated with higher intake of dietary fiber, which has been reported to a have a favorable effect on BMI (34,47-49). In the NHS II cohort, the difference in BMI between the highest and lowest quintiles of total fiber intake (one BMI unit) was much less than the difference between the highest and lowest quintiles of carbohydrate consumption (three BMI units) (34). This suggests that dietary fiber intake does not entirely explain the generally inverse relationship between carbohydrate consumption and BMI (Table 1). CARBOHYDRATE QUALITY Coincident with heightened interest in low-carbohydrate diets, a distinction between carbohydrates has been em-

phasized, with recommendations for increased consumption of complex, fiber-rich carbohydrates with a low glycemic index, and decreased consumption of highglycemic, refined carbohydrates (19-22). Although justification for consumption of fiber-rich carbohydrates is well documented, the relationship between carbohydrate quality (eg, glycemic index, refined grains) and BMI remains controversial. GLYCEMIC INDEX AND GLYCEMIC LOAD Glycemic index (GI) reflects carbohydrate quality, whereas the glycemic load (GL) reflects the total carbohydrate burden by considering both GI and the amount of carbohydrates ingested (19,20). Increased consumption of low-GI foods has been recommended to help prevent and treat obesity (19-21), and GI is a key feature of several diet books (eg, 9,50). Some studies have reported increased satiety with low-GI foods (19), but others have not (51). Intervention Studies Results from intervention studies are mixed (52-56). No difference in mean weight loss was noted in three studies comparing low-fat diets either low or high in GI (52-54). A comparison of four diets varying in carbohydrate, protein and GI revealed nonstatistically different weight losses after 12 weeks (55). In this study female subjects lost more weight and body fat after a low-GI (GI⫽40), moderately-high-carbohydrate diet compared to a high-GI (GI⫽70) diet equal in macronutrient composition (55). However, a low-GI (GI⫽44), high-protein diet resulted in less total weight and fat mass loss than a high-protein diet of equal macronutrient composition but much higher GI (GI⫽59), suggesting that GI per se may not have been the critical feature accounting for the weight loss differences (55). The effect of GI on body weight is complex, and in addition to possible gender differences (55), metabolic status may play a role (56). In the Comprehensive Assessment of Long-term Effects of Restricting Intake of Energy trial, a low-GI diet facilitated weight loss in overweight persons with high insulin secretion but not in overweight persons with low insulin secretion (56). Epidemiologic Studies GI. Some studies show higher BMI associated with increasing GI of the diet (57-61), although most do not (33,35,36,39,40,62-68). Three large cohorts of women (33,35,36), and one large (62) and one small (64) cohort of men, reveal an inverse association between GI and BMI, with BMI in the highest quintile of GI up to 1.5 BMI units lower (35) compared to the lowest quintile (Table 2). The one study of men and women combined (63) is confounded by disproportionately lower percentages of women across quintiles of increasing GI. Nevertheless, data from both whites and African Americans in this cohort provide no evidence that GI adversely affects BMI. Although within each study the range of GI across tertiles/quintiles is fairly small, when viewed collectively the data do not support the notion that a high-GI diet is predictive of higher BMI. To the contrary, several large cohort studies suggest the opposite (33,35,36,62).

GL. With few exceptions (58,60), most studies indicate that GL is either unrelated to BMI (59,61,65-68), or is inversely associated with BMI (31-36,39,69). In Table 3, all eight women cohorts, and two of three cohorts of men indicate inverse associations, with the BMI of the highest quintile being 0.3 to 2.1 BMI units lower than that of the lowest quintile. These differences are evident even after adjusting for total energy intake and other potentially confounding factors. In an analysis of data from both NHS I and II cohorts combined, mean BMI was 1.1 units lower among the highest quintile of GL (compared to the lowest quintile of GL), despite no difference in physical activity and a lower prevalence of smoking (32). The majority of epidemiologic evidence does not support the notion that GL is predictive of adiposity. Most studies suggest that higher-GL diets may be beneficial for weight control. Methodologic Considerations One major methodologic issue is the actual determination of GI and GL of diets. Researchers have used a variety of sources, ranging from the 2002 international table of GI and GL values (70) to various earlier published reports (71,72). Not all foods have published GI values, and some GI values have been modified to suit different populations (eg, Japanese [59]). Also, some of the studies used total carbohydrate rather than available carbohydrate, which can alter both dietary GI and GL values (68). It is also important to control for energy intake and possible confounding from low-energy reporters (60). Recent data from the Inter99 Study indicated a positive relationship between BMI and both GI and GL only when adjusted for total energy intake (60). In contrast, data from the Insulin Resistance Atherosclerosis Study demonstrated that GI was not related to adiposity even when adjusted for energy intake (65,66). Furthermore, the inverse relationship between GI/GL and BMI in the studies presented in Tables 2 and 3 was evident after adjusting for total energy intake. Most studies, however, have used the food frequency questionnaire, which is prone to underreporting, especially among those with a high BMI (42). Thus, studies demonstrating relationships between GI and/or GL and BMI should be interpreted with caution (60). WHOLE AND REFINED GRAINS With few exceptions (73), an inverse relationship between whole-grain intake and BMI has been reported (74-84) (Table 4). This is not unexpected, as whole-grain intake correlates with consumption of total carbohydrate and dietary fiber, both of which vary inversely with BMI (4749,75,76,78). The generally inverse relationship for the combined men and women cohorts in Table 4 likely underestimates the steepness of the gradient due to the lower percentage of women in the higher quintiles of whole-grain intake. Refined-grain intake is not consistently linked to higher BMI (44,45,73,76,79,83,84) (Table 5). Two cohorts of women (76,79) revealed a positive relationship between refined-grain consumption and BMI, although in one of these (79) the difference was only 0.2 BMI units between

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Table 2. Relationship between glycemic index and body mass index among men and women in eight cohorts revieweda Quintile (Tertile) of Glycemic Index Cohort

I

II

III

IV

V

Women NHSb I (57) n⫽65,173 NHS II (33) n⫽91,249 WHSe (35) n⫽38,446 Canadian NBSSf (36) n⫽49,111 JMETSg (59) n⫽1,354

24.7 62.9c 24.7⫾5.0d 69.9c 26.7⫾5.4d 50c 25.2⫾10.2d 72.5c 23.7⫾0.2h 61c

25.1 68.1c

25.3 73.4c

26.3⫾5.0d 52c 25.1⫾10.2d 78.4c 23.9⫾0.2h 65c

25.2 70.7c 24.6⫾5.3d 76.9c 26.1⫾5.0d 53c 24.7⫾10.2d 79.7c 23.8⫾0.2h 67c

25.7⫾4.8d 54c 24.6⫾10.2d 81.7c 24.2⫾0.2h 69c

25.4 77.9c 24.5⫾5.5d 83.1c 25.2⫾4.7d 55c 24.3⫾10.2d 84.3c 24.4⫾0.2h 72c

Men HPFSi (62) n⫽42,759 Zutphen (64) n⫽646

25.7 65.1c 26.0 77c

25.5 69.7c 25.1 82c

25.5 72.6c 24.9 85c

25.4 75.3c

25.3 79.3c

26.7⫾4.5d 69.1c 63.7k 29.8⫾6.2d 71.7c 76.6k

26.7⫾4.5d 74.5c 55.9k 29.0⫾5.8d 77.6c 66.2k

26.5⫾4.5d 77.2c 51.6k 28.9⫾6.0d 80.2c 61.0k

26.6⫾4.5d 79.7c 47.2k 29.0⫾5.7d 82.6c 57.9k

26.6⫾4.7d 83.4c 49.3k 28.9⫾6.3d 86.6c 52.3k

Men/Women ARICj (white) (63) n⫽9,529 ARIC (African American) (63) n⫽2,722 a

Not all studies reported standard error of the mean or standard deviation. NHS⫽Nurses’ Health Study. c Mean glycemic index within each glycemic index quintile/tertile. d Body mass index⫾standard deviation. e WHS⫽Women’s Health Study. f NBSS⫽National Breast Screening Study. g JMETS⫽Japanese Multicentered Environmental Toxicants Study. h Body mass index⫾standard error of the mean. i HPFS⫽Health Professionals Follow-up Study. j ARIC⫽Atherosclerosis Risk in Communities Study. k Percentage of women study participants. b

the lowest (four servings per week) and highest (30 servings per week) quintile of refined-grain intake. In the one male cohort refined-grain intake was unrelated to BMI (44) (Table 5). Data on combined men and women are confounded due to the decreasing percentage of women across higher quartiles/quintiles of refined-grain intake (Table 5) and, hence, should be interpreted with caution. Despite this bias toward finding a positive relationship, data from the Framingham Offspring Study revealed no trend between refined-grain intake and BMI (45). In the Physician’s Health Study (82), intake of refinedgrain (as well as whole-grain) breakfast cereal was associated with lower BMI and was inversely associated with body weight gain over 8 years. Similarly, in the Women’s Health Study (35), servings/day of refined grain was inversely related to BMI. Thus, current data from cohort studies are not sufficiently consistent to conclude that refined grain intake has a deleterious affect on BMI.

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DIETARY FIBER The inverse association between carbohydrate intake and BMI may be due in part to dietary fiber (33,34,44,4749,78,85-87). Cereal fiber, in particular, appears to play a beneficial role in weight control (33,85,87-92). In the NHS I and II cohorts, the highest quintile of cereal fiber consumption had a mean BMI 0.7 (NHS I) and 1.5 (NHS II) units less than that of the lowest quintile of cereal fiber consumption (33,85). Breakfast cereal consumption is predictive of lower BMI (81,88-91). The number of Americans who skipped breakfast between 1965 and 1991 rose from 14% to 25% (88). Since 30% of the US Department of Agriculture’s recommended three or more whole-grain servings per day are delivered in the form of breakfast foods, reversing the trend of skipping breakfast may also increase the low percentage of Americans who comply with the US Department of Agriculture’s recommendation (92).

Table 3. Relationship between glycemic load and body mass index among men and women in nine cohorts revieweda Quintile of Glycemic Load Cohort

I

II

III

IV

V

Women NHSb I (31) n⫽71,919 NHS II (33) n⫽91,249 WHSe (35) n⫽38,446 PLCOf (39) n⫽18,341 Canadian NBSSg (36) n⫽49,111 JMETSh (59) n⫽1,354 SMCj (69) n⫽61,433 Health ABCk (68) n⫽1,169

25.2⫾4.6c 107d 25.7⫾5.8c 133d 26.7⫾5.4c 92d 27.4⫾5.6c 89.7d 25.2⫾10.2c 98.6d 24.2⫾0.3i 69d 24.9 157d 27.4⫾5.4b 88.5d

25.2⫾4.6c 132d

25.1⫾4.6c 144d 24.5⫾5.1c 171d 26.1⫾5.0c 117d 27.2⫾5.6c 117.1d 24.7⫾10.2c 147.2d 24.0⫾0.2i 87d 24.7 179d 27.8⫾5.6 118.2d

24.9⫾4.6c 156d

24.7⫾4.5c 181d 23.6⫾4.8c 217d 25.2⫾4.7c 143d 26.5⫾5.2c 142.8d 24.3⫾10.2c 196.0d 23.8⫾0.3i 107d 24.6 207d 27.1⫾5.7 148.3d

Men HPFSl (31) n⫽39,926 PLCO (39) n⫽20,172 Health ABC (68) n⫽1,079

26.1⫾3.4c 131d 28.1⫾4.4c 106.6d 26.7⫾4.2c 107.4d

25.9⫾3.3c 163d

25.6⫾3.2c 181d 27.6⫾4.1c 144.7d 26.8⫾3.4c 143.9d

25.3⫾3.2 198d

26.3⫾5.0c 106d 25.1⫾10.2c 129.5d 23.8⫾0.2i 80d 24.7 167d 26.7⫾5.4 108.7d

26.8⫾4.0c 132.7d

25.7⫾4.8c 127d 24.6⫾10.2c 164.5d 24.2⫾0.2i 95d 24.6 190d 26.2⫾4.9 128.0d

26.6⫾4.2c 156.8d

24.8⫾3.2c 231d 26.8⫾3.9c 182.8d 26.7⫾3.4c 185.3d

a

Not all studies reported standard error of the mean or standard deviation. NHS⫽Nurses’ Health Study. c Body mass index⫾standard deviation. d Mean glycemic load within the quintile. e WHS⫽Women’s Health Study. f PLCO⫽Prostate, Lung, Colorectal, and Ovarian Screening Study. g NBSS⫽National Breast Screening Study. h JMETS⫽Japanese Multicentered Environmental Toxicants Study. i Body mass index⫾standard error of the mean. j SMC⫽Swedish Mammography Cohort. k Health ABC⫽Aging and Body Composition. l HPFS⫽Health Professionals Follow-up Study. b

INTERVENTION STUDIES A substantial body of literature on dietary intervention supports the role of carbohydrates in weight control. Several systematic reviews and meta-analyses have evaluated the effectiveness of ad libitum, low-fat diets on body weight (24-28). They include approximately 70 trials, and in a number of them participants were instructed to reduce dietary fat intake without emphasis on total energy restriction (see Astrup and colleagues [26,27] for reviews). The duration of these studies was relatively short (⬍1 year), but a consistent modest weight loss of 1 to 4 kg was evident in nearly all of them. These meta-analyses indicated that every 1% reduction in dietary fat was associated with about a 0.27- to 0.44-kg weight loss of over a period of ⬍1 year, with greater weight loss observed among initially overweight or obese subjects (24,26-28). Although this represents a relatively small degree of weight loss, a decrease of this magnitude could significantly reduce the prevalence of obesity (26,93).

An argument could be made that similar weight reductions can be observed with ad libitum, low-carbohydrate dietary approaches. However, in studies of low-carbohydrate diets lasting ⱖ6 months, the primary outcome measure has always been weight loss (15,94). Thus any study that has weight loss as a primary outcome measure might naturally be biased toward finding weight reduction after any dietary intervention, regardless of macronutrient composition. It is important to note that in 12 of the ad libitum, low-fat trials included in the systematic reviews cited above, weight loss was not a primary outcome measure (26,27). In these studies, the primary outcome measure was typically blood lipids. More recently, the large-scale Women’s Health Initiative (WHI) study also demonstrated weight loss on a low-fat diet, even though weight loss was not the focus of the study (95). It is unlikely that voluntary caloric restriction contributed to the observed weight loss in these studies (26,27). Yet in these studies ad libitum consumption of

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Table 4. Relationship between whole-grain intake and body mass index among men and women in nine cohorts revieweda Quintile (Quartile) of Whole-Grain Intake Cohort

I

Women NHSb I (76) n⫽74,091 NHS I (Diabetic) (78) n⫽902 NHS II (46) n⫽470 IWHSf (79) n⫽34,492 Men HPFSg (44) n⫽42,540

25.7 0.2 s/de

Men/Women FOSh (45) n⫽2,941 Finnish (74) n⫽4,316 Boston (83) n⫽535 TLGSj (84) n⫽827

II

III

IV

V

24.9⫾5c

24.9⫾5c

24.5⫾4c

30.9

29.8

28.4

24.9⫾0.5d 5.9 to 10.8 g/de 27.2 1.5 s/wke

24.3⫾0.4d 20.8 to 23.5 g/de 27.0 8.5 s/wke

23.9⫾0.5d 39.8 to 49.2 g/de 26.9 22.5 s/wke

27.0 0.9 s/wke 48i 26.7⫾4.3c 79 g/de 56i 26.4 0.31 s/de 69i 26.4⫾4.8c ⱕ10 g/de 58i

27.0 6.0 s/wke

26.6 13.0 s/wke

25.6 1.1 s/de

26.9 3.5 s/wke 52i 26.5⫾4.0c 136 g/de 48i 25.5 0.86 s/de 67i 25.8⫾5.1c 10 to ⬍71 g/de 61i

27.3 6.4 s/wke 59i 26.3⫾3.8c 198 g/de 43i 25.3 1.49 s/de 71i 25.1⫾4.8c 71 to ⬍143 g/de 54i

24.9 3.4 s/de

26.7 9.5 s/wke 58i 26.4⫾3.7c 303 g/de 41i 25.2 2.90 s/de 59i 24.7⫾4.9c ⱖ143 g/de 48i

26.6 20.5 s/wke 55i

a

Not all studies reported standard error of the mean or standard deviation. NHS⫽Nurses’ Health Study. c Body mass index⫾standard deviation. d Body mass index⫾standard error of the mean. e Mean or range of whole-grain intake, in g/d, servings/d (s/d), or servings/wk (s/wk). f IWHS⫽Iowa Women’s Health Study. g HPFS⫽Health Professionals Follow-up Study. h FOS⫽Framingham Offspring Study. i Percentage of women study participants. j TLGS⫽Tehran Lipids and Glucose Study. b

a low-fat diet consistently resulted in spontaneous weight loss. In a number of ad libitum, low-fat diet interventions in which weight loss was one of several outcome measures, weight loss was not encouraged (96-99). Some of these studies either discouraged weight loss or modified caloric intake in an effort to prevent weight loss (without success) (100,101). In the Carbohydrate Ratio Manipulation in European National Diets Study, subjects consuming an ad libitum, low-fat, complex-carbohydrate diet lost 4.5 kg after 6 months despite no encouragement to actively reduce caloric intake (96). In view of the concern about the potential contribution of simple carbohydrates to obesity, it is important to note that increasing consumption of simple carbohydrates over the 6-month trial did not lead to weight gain (96). Ad libitum, low-fat diets may result in weight loss despite efforts to prevent this from occurring. In a study

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of premenopausal women consuming an ad libitum, 20% fat diet, systematic adjustments in energy intake designed to prevent weight loss were unsuccessful (101). During a 20-week period, despite increases in energy intake to maintain weight throughout the study, women lost an average of 2.8% of body weight and 11.3% of fat weight. Thus, weight loss on a low-fat diet, even when not encouraged, may reflect imprecision in food-intake control when the energy density of the diet is altered (97,101104). WEIGHT MAINTENANCE Long-term weight-loss maintenance is poor (105). Because ad libitum, low-fat diets lead to only modest weight loss, the greatest potential advantage for advocating a low-fat, high-carbohydrate diet is in prevention of weight gain (95,106,107). In the WHI (95), 48,835 women were

Table 5. Relationship between refined grain intake and body mass index among men and women in six cohorts revieweda Quintile (Quartile) of Refined-Grain Intake Cohort

I

Women NHSb I (76) n⫽74,091 IWHSd (79) n⫽34,492

26.9 4.0 s/wke

Men HPFSf (44) n⫽42,540

25.4 0.6 s/de

Men/Women FOSg (45) n⫽2,941 Boston (83) n⫽535 TLGSi (84) n⫽827

II

24.6⫾4c

26.9 6.9 s/wke 61h 25.4 1.6 s/de 77h 24.9⫾4.2c ⬍125 g/de 62h

III

IV

24.9⫾5c 26.8 8.0 s/wke

26.9 12.0 s/wke

25.2⫾5c 27.0 18.0 s/wke

25.5 1.7 s/de

26.8 11.8 s/wke 58h 25.4 2.9 s/de 78h 25.5⫾4.7c 125 to ⬍203 g/de 64h

26.9 16.7 s/wke 57h 25.5 4.1 s/de 65h 26.2⫾5.2c 203 to ⬍281 g/de 53h

V

27.1 30.0 s/wke

25.4 4.3 s/de

27.0 23.6 s/wke 52h 26.2 6.1 s/de 45h 26.9⫾5.3c ⱖ281 g/de

26.8 38.9 s/wke 46h

45h

a

Not all studies reported standard error of the mean or standard deviation. NHS⫽Nurses’ Health Study. c Body mass index⫾standard deviation. d IWHS⫽Iowa Women’s Health Study. e Mean or range of refined grain intake, in g/d, servings/d (s/d), or servings/wk (s/wk). f HPFS⫽Health Professionals Follow-up Study. g FOS⫽Framingham Offspring Study. h Percentage of women study participants. i TGLS⫽Tehran Lipids and Glucose Study. b

randomized to assess the long-term benefits and risks of a low-fat dietary pattern on breast and colorectal cancers and cardiovascular disease. The intervention did not encourage weight loss or energy restriction. Average weight decreased by 2.2 kg during the first year, which was significantly more than that of the control group. Although the 2.2-kg difference in weight between intervention and control groups diminished during the 7.5-year follow-up, the difference in weight remained significant during the entire follow-up period. Because weight gain during adulthood is common in the United States, an ad libitum, low-fat diet could assist weight control by limiting weight gain. Behavioral Risk Factor Surveillance System surveys (108) indicated adult weight gain averaged about 1 lb/year during the 1990s (ie, during which time much of the WHI was conducted). Data from the WHI suggest that an ad libitum, low-fat diet might attenuate this weight gain (95). Low-fat, high-carbohydrate diets seem to be most common among people who successfully maintain weight loss (109). Lower fat intake was a predictor of both initial and sustained weight loss in persons with obesity consuming an ad libitum diet (110), and a low-fat, high-fiber diet predicted long-term (3 years) weight reduction in initially overweight persons with impaired glucose tolerance

(111). In addition, an ad libitum, low-fat, high-carbohydrate diet was more effective than a fixed-energy intake for maintaining weight after a major weight loss (112). Two years after a 12- to 13-kg weight loss, the ad libitum, low-fat, high-carbohydrate group maintained three times as much weight loss as the fixed-energy group (8.0 kg vs 2.5 kg), and more subjects maintained a weight loss of ⱖ5 kg (65% vs 40%). Ad libitum, low-fat diets may help those with unrestrained eating behavior maintain body weight (113). Whereas individuals who consume hypocaloric diets generally experience increased hunger, subjects consuming ad libitum, low-fat diets do not (26,96,100). This may be attributable in part to lower energy density of low-fat, high-carbohydrate diets (114,115). A low-fat, high-carbohydrate diet may also increase sensitivity to leptin and avoid the increase in ghrelin caused by energy restriction (116). Weigle and colleagues (116) reported that 12 weeks of an ad libitum, low-fat, high-carbohydrate diet resulted in a spontaneous decrease in energy intake without an increase in 24-hour area-under-curve for ghrelin. Although leptin 24-hour area-under-curve was decreased, there was an increase in the percentage change between nadir and peak 24-hour leptin levels, which was strongly correlated to the absolute change in both weight and fat

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mass. Thus, an ad libitum, low-fat, high-carbohydrate diet may result in hormonal adaptations that facilitate weight-loss maintenance (116). HEALTH IMPLICATIONS OF HIGH-CARBOHYDRATE DIETS Biomarkers Diets high in either GI or GL have been associated with increased levels of a number of cardiovascular disease biomarkers, including increased plasma triglycerides, glucose, insulin, glycated hemoglobin, and C-reactive protein, and reduced high-density lipoprotein cholesterol levels (59,117-119). Other studies have shown no association between GI or GL and fasting insulin (64,68), fasting glucose (64,66,68), glycated hemoglobin (66,68), and various blood lipids (59,64). Meta-analyses of the effect of low-GI diets on cardiovascular disease risk markers are inconclusive (120,121). One found that low-GI diets induced significant reductions in total and low-density lipoprotein cholesterol in patients with type 2 diabetes, but had no effect on triglycerides and high-density lipoprotein cholesterol (120). Another revealed no evidence for a favorable effect of low-GI diets on low-density lipoprotein or high-density lipoprotein cholesterol levels, triglyceride levels, fasting glucose or fasting insulin levels, and weak evidence for small reductions in total cholesterol and glycated hemoglobin levels (121). Disease Incidence and Mortality Diets high in GI, GL, and/or refined grains have been reported to be associated with increased risk for cardiovascular disease, type 2 diabetes, metabolic syndrome, and certain cancers (19-22,33,35,57,58,62,68,119,122). These findings contrast with reports suggesting no health risk associated with either GI or GL, or refined-grain intake. A number of large cohort studies have found that GI and GL were not predictive of type 2 diabetes (33,62,63, 65,66,86), insulin resistance (123), cardiovascular disease (64), stroke (124), eye cataracts (31), breast cancer (3436,41), stomach cancer (69), colorectal adenomas (39), or colorectal cancer (125,126). The American Diabetes Association contends that there are insufficient data to determine if there is a relationship between either GI or GL and the development of diabetes (127). Furthermore, a number of reports indicate no association between refined grain intake and risk of type 2 diabetes (44,73,86), insulin resistance (119), cardiovascular disease (45,74,79,82), ischemic stroke (128), breast cancer (80), and all-cause mortality (74). It may be premature to conclude that diets high in either GI or GL pose a health risk. In addition to their potential to facilitate weight control, high-carbohydrate diets tend to be associated with higher overall diet quality (29,30,129,130). Health benefits of fiber-rich carbohydrates are well established (131). Although the link between refined-grain intake and a number of health outcomes remains unclear, the positive health benefits of whole grains are well established (132). Grain consumption is associated with ingestion of many nutrients, including fiber, antioxidants, and vitamins (132,133), and grains are likely the most dependable source of phytoestrogens (134). High-carbohydrate diets are associated

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with higher intake of folate (30,75,85). Although folate comes from a variety of foods, including fruits and vegetables, breakfast cereal is one of the best food sources of folate (135), possibly helping to explain the lower homocysteine concentrations reported to be associated with both whole- and refined-grain intake (136). Total grain intake also has been reported to be associated with lower concentrations of C-reactive protein, thus possibly reducing risk of inflammation (137). Whole-grain consumption is associated with reduced progression of coronary artery atherosclerosis (138) and lower risk of type 2 diabetes (44-46,73,86), metabolic syndrome (83), cardiovascular disease (44,45,74,79,82,83), and all-cause mortality (139). CONCLUSIONS AND RECOMMENDATIONS A substantial body of epidemiologic evidence reveals an inverse relationship between carbohydrate intake and BMI. Data from ad libitum, low-fat diet interventions, without emphasis on energy restriction or weight loss, show modest “spontaneous” weight loss, and thus support the findings from observational studies and suggest that a nonenergy-restrictive, low-fat diet strategy may avoid adherence problems characteristic of energy-restricted diets. The greatest potential role for low-fat diets in weight control may be in the attenuation of unhealthful adult weight gain. Glycemic load is inversely associated with BMI, even when adjusted for total energy intake. The role of carbohydrate quality, reflected by dietary GI, is mixed; current evidence from cohort studies suggests that a high-GI diet is just as likely, if not more so, to be associated with lower BMI than higher BMI. Whole-grain, but not refinedgrain, intake is consistently associated with lower BMI. High-carbohydrate diets are frequently associated with higher intake of dietary fiber and greater overall diet quality. Cereal fiber in particular appears to be associated with lower BMI and reduced risk of type 2 diabetes and cardiovascular disease. Public health recommendations to increase consumption of whole-grain, fiber-rich foods should have multiple positive health benefits, facilitate weight-control efforts, and possibly reduce prevalence of overweight and obesity. Consuming sufficient quantities (ie, three or more servings per day) of whole-grain foods rich in cereal fiber may obviate the need to be cognizant of the glycemic properties of foods. Health benefits of whole-grain and cereal fiber consumption are seen despite being associated with high GI or GL (33,34,44,75-77). Diabetes risk associated with either high GI or GL is attenuated or eliminated by cereal fiber (33,57,62). Nevertheless, despite insufficient data to warrant universal recommendations for use of GI, it must be noted that low-GI diets (that are not low in carbohydrate) are not associated with adverse health effects. Certain populations, such as sedentary (33,40) and overweight/obese (34,55,122) women, and insulin resistant individuals (58), may benefit from low-GI diets. If carbohydrate-rich foods are not whole grain, it might be prudent to choose low-GI alternatives (118). Additional Research Needed Randomized controlled trials with proper control for confounding dietary variables (eg, total and cereal fiber) and

behavioral factors (eg, physical activity) are needed to elucidate the independent effect of GI/GL on BMI and health outcomes. The postprandial period may be important in the development of cardiovascular disease (117,140). This is especially relevant to GI and thus more research is needed on postprandial metabolic responses of meals varying in GI/GL. Physical activity may affect the relationship between GI and BMI, especially in women (40). Further research is needed to help explain possible sex differences (40,55), and to establish whether or not physical activity intervention modifies acute responses and chronic adaptations to diets differing in GI. Preparation of this manuscript was supported in part by a grant from the Grain Foods Foundation. The author is a member of the Grain Foods Foundation clinical advisory board. References 1. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA. 2006;295:1549-1555. 2. Caban AJ, Lee DJ, Fleming LE, Gomez-Marin O, LeBlanc W, Pitman T. Obesity in US workers: The National Health Interview Survey, 1986 to 2002. Am J Public Health. 2005;95:1614-1622. 3. Hill JO, Wyatt HR, Reed GW, Peters JC. Obesity and the environment: Where do we go from here? Science. 2003;299:853-855. 4. Gerrior S, Bente L, Hiza H. Nutrient Content of the US Food Supply. 1909-2000. Washington, DC: US Department of Agriculture, Center for Nutrition Policy and Promotion; November 2004. Home Economics Research Report No. 56. 5. Centers for Disease Control and Prevention. Trends in intake of energy and macronutrients—United States, 1971-2000. MMWR. 2004;53:80-82. 6. Centers for Disease Control and Prevention. Physical activity trends—United States, 1990-1998. MMWR. 2001;50:166-169. 7. Centers for Disease Control and Prevention. Trends in leisure-time physical inactivity by age, sex, and race/ethnicity—United States, 1994-2004. MMWR. 2005;54:991-994. 8. Atkins R. Dr. Atkins’ New Diet Revolution. New York, NY: Avon Books; 1998. 9. Agatston A. The South Beach Diet. Emmaus, PA: Rodale; 2003. 10. Eades MR, Eades MD. Protein Power. New York, NY: Bantam; 1997. 11. Steward HL, Bethea MC, Andrews S, Balart LA. Sugar Busters! New York, NY: Ballantine; 1995. 12. Atkins RC. Dr. Atkins’ Diet Revolution. New York, NY: Bantam Books; 1972. 13. Stillman IM, Baker SS. The Doctor’s Quick Weight Loss Diet. Englewood Cliffs, NJ: Prentice-Hall; 1967. 14. Taller H. Calories Don’t Count. New York, NY: Simon & Schuster; 1961. 15. Nordmann AJ, Nordmann A, Briel M, Keller U, Yancy WS Jr, Brehm BJ, Bucher HC. Effects of low-carbohydrate vs low-fat diets on weight loss and cardiovascular risk factors. Arch Intern Med. 2006; 166:285-293. 16. Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: A randomized trial. JAMA. 2005;293:43-53. 17. Jequier E, Bray GA. Low-fat diets are preferred. Am J Med 2002; 113(suppl 9B):41S-46S. 18. Willett WC, Leibel RL. Dietary fat is not a major determinant of body fat. Am J Med 2002;113(suppl 9B):47S-59S. 19. Ludwig DS. The glycemic index. Physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA. 2002;287: 2414-2423. 20. Brand-Miller JC. Glycemic load and chronic disease. Nutr Rev 2003; 61(suppl):S49-S55. 21. Liu S. Lowering dietary glycemic load for weight control and cardiovascular health. Arch Intern Med. 2006;166:1438-1439. 22. Gross LS, Li L, Ford ES, Liu S. Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: An ecologic assessment. Am J Clin Nutr. 2004;79:774-779.

23. Pi-Sunyer X. Do glycemic index, glycemic load, and fiber play a role in insulin sensitivity, disposition index, and type 2 diabetes? Diabetes Care. 2005;28:2978-2979. 24. Bray GA, Popkin BM. Dietary fat intake does affect obesity. Am J Clin Nutr. 1998;68:1157-1173. 25. Hill JO, Melanson EL, Wyatt HT. Dietary fat intake and regulation of energy balance: Implications for obesity. J Nutr 2000;130(suppl 2S):284S-288S. 26. Astrup A, Grunwald GK, Melanson EL, Saris WHM, Hill JO. The role of low-fat diets in body weight control: A meta-analysis of ad libitum dietary intervention studies. Int J Obes. 2000;24:1545-1552. 27. Astrup A, Ryan L, Grunwald GK, Storgaard M, Saris WHM, Melanson E, Hill JO. The role of dietary fat in body fatness: Evidence from a preliminary meta-analysis of ad libitum low-fat dietary intervention studies. Br J Nutr 2000;83(suppl 1):S25-S32. 28. Yu-Poth S, Zhao G, Etherton T, Naglak M, Jonnalagadda S, KrisEtherton PM. Effects of the National Cholesterol Education Programs step I and step II dietary intervention programs on cardiovascular disease risk factors: A meta-analysis. Am J Clin Nutr. 1999;69:632-646. 29. Yang EJ, Kerver JM, Park YK, Kayitsinga J, Allison DB, Song WO. Carbohydrate intake and biomarkers of glycemic control among US adults: The third National Health and Nutrition Examination Survey (NHANES III). Am J Clin Nutr. 2003;77:1426-1433. 30. Bowman SA, Spence JT. A comparison of low-carbohydrate vs highcarbohydrate diets: Energy restriction, nutrient quality and correlation to body mass index. J Am Coll Nutr. 2002;21:268-274. 31. Schaumberg DA, Liu S, Seddon JM, Willett WC, Hankinson SE. Dietary glycemic load and risk of age-related cataract. Am J Clin Nutr. 2004;80:489-495. 32. Wu T, Giovannucci E, Pischon T, Hankinson SE, Ma J, Rifai N, Rimm EB. Fructose, glycemic load, and quantity and quality of carbohydrate in relation to plasma C-peptide concentration in US women. Am J Clin Nutr. 2004;80:1043-1049. 33. Schulze MB, Liu S, Rimm EB, Manson JE, Willett WC, Hu FB. Glycemic index, glycemic load, and dietary fiber intake and incidence of type 2 diabetes in younger and middle-aged women. Am J Clin Nutr. 2004;80:348-356. 34. Cho E, Spiegelman D, Hunter DJ, Chen WY, Colditz GA, Willett WC. Premenopausal dietary carbohydrate, glycemic index, glycemic load, and fiber in relation to risk of breast cancer. Cancer Epidemiol Biomarkers Prev. 2003;12:1153-1158. 35. Higginbotham S, Zhang Z-F, Lee I-M, Cook NR, Buring JE, Liu S. Dietary glycemic load and breast cancer risk in the Women’s Health Study. Cancer Epidemiol Biomarkers Prev. 2004;13:65-70. 36. Navarro Silvera SA, Jain M, Howe GR, Miller AB, Rohan TE. Dietary carbohydrates and breast cancer risk: A prospective study of the roles of overall glycemic index and glycemic load. Int J Cancer. 2005;114:653-658. 37. Newby PK, Muller D, Hallfrisch J, Qiao N, Andres R, Tucker KL. Dietary patterns and changes in body mass index and waist circumference in adults. Am J Clin Nutr. 2003;77:1417-1425. 38. Macdiarmid JI, Cade JE, Blundell JE. High and low fat consumers, their macronutrient intake and body mass index: Further analysis of the National Diet and Nutrition survey of British Adults. Eur J Clin Nutr. 1996;50:505-512. 39. Flood A, Peters U, Jenkins DJA, Chatterjee N, Subar AF, Church TR, Bresalier R, Weissfeld JL, Hayes RB, Schatzkin A. Carbohydrate, glycemic index, and glycemic load and colorectal adenomas in the Prostate, Lung, Colorectal, and Ovarian Screening Study. Am J Clin Nutr. 2006;84:1184-1192. 40. Hare-Bruun H, Flint A, Heitmann BL. Glycemic index and glycemic load in relation to changes in body weight, body fat distribution, and body composition in adult Danes. Am J Clin Nutr. 2006;84:871-879. 41. Jonas CR, McCullough ML, Teras LR, Walker-Thurmond KA, Thun MJ, Calle EE. Dietary glycemic index, glycemic load, and risk of incident breast cancer in postmenopausal women. Cancer Epidemiol Biomarkers Prev. 2003;12:573-577. 42. Subar AF, Kipnis V, Troiano RP, Midthune D, Schoeller DA, Bingham S, Sharbaugh CO, Trabulsi J, Runswick S, Ballard-Barbash R, Sunshine J, Schatzkin A. Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: The OPEN Study. Am J Epidemiol. 2003;158:1-13. 43. Conway JM, Ingwersen LA, Moshfegh AJ. Accuracy of dietary recall using the USDA five-step multiple-pass method in men: An observational validation study. J Am Diet Assoc. 2004;104:595-603. 44. Fung TT, Hu FB, Pereira MA, Lui S, Stampfer MJ, Colditz GA, Willett WC. Whole-grain intake and the risk of type 2 diabetes: A prospective study in men. Am J Clin Nutr. 2002;76:535-540.

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45. McKeown NM, Meigs JB, Liu S, Wilson PWF, Jacques PF. Wholegrain intake is favorably associated with metabolic risk factors for type 2 diabetes and cardiovascular disease in the Framingham Offspring Study. Am J Clin Nutr. 2002;76:390-398. 46. Jensen MK, Koh-Banerjee P, Franz M, Sampson L, Gronbaek M, Rimm EB. Whole grains, bran, and germ in relation to homocysteine and markers of glycemic control, lipids, and inflammation. Am J Clin Nutr. 2006;83:275-283. 47. Ludwig D, Pereira M, Kroenke CH, Hilner JE, Van Horn L, Slattery ML, Jacobs DR Jr. Dietary fiber, weight gain, and cardiovascular disease risk factors in young adults. JAMA. 1999;282:1539-1546. 48. Roberts SB, McCrory MA, Saltzman E. The influence of dietary composition on energy intake and body weight. J Am Coll Nutr 2002;21(suppl 2):140S-145S. 49. Slavin JL. Dietary fiber and body weight. Nutrition. 2005;21:411418. 50. Brand-Miller J, Wolever TMS, Foster-Powell K, Colagiuri S. The New Glucose Revolution. New York, NY: Marlowe & Co; 2003. 51. Alfenas RCG, Mattes RD. Influence of glycemic index/load on glycemic response, appetite, and food intake in healthy humans. Diabetes Care. 2005;28:2123-2129. 52. Ebbeling CB, Leidig MM, Sinclair KB, Seger-Shippee LG, Feldman HA, Ludwig DS. Effects of an ad libitum low-glycemic load diet on cardiovascular disease risk factors in obese young adults. Am J Clin Nutr. 2005;81:976-982. 53. Raatz SK, Torkelson CJ, Redmon JB, Reck KP, Kwong CA, Swanson JE, Liu C, Thomas W, Bantle JP. Reduced glycemic index and glycemic load diets do not increase the effects of energy restriction on weight loss and insulin sensitivity in obese men and women. J Nutr. 2005;135:2387-2391. 54. Sloth B, Krog-Mikkelsen I, Flint A, Tetens I, Bjorck I, Vinoy S, Elmstahl H, Astrup A, Lang V, Raben A. No difference in body weight decrease between a low-glycemic-index and a high-glycemic index diet but reduced LDL cholesterol after 10-week ad libitum intake of the low-glycemic-index diet. Am J Clin Nutr. 2004;80:337347. 55. McMillan-Price J, Petocz P, Atkinson F, O’Neill K, Samman S, Steinbeck K, Caterson I, Brand-Miller J. Comparison of 4 diets of varying glycemic load on weight loss and cardiovascular risk reduction in overweight and obese young adults. Arch Intern Med. 2006; 166:1466-1475. 56. Pittas AG, Das SK, Hajduk CL, Golden J, Saltzman E, Stark PC, Greenberg AS, Roberts SB. A low-glycemic load diet facilitates greater weight loss in overweight adults with high insulin secretion but not in overweight adults with low insulin secretion in the CALERIE Trial. Diabetes Care. 2005;28:2939-2941. 57. Salmeron J, Manson JE, Stampfer MJ, Colditz GA, Wing AL, Willett WC. Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women. JAMA. 1997;277:472-477. 58. Hodge AM, English DR, O’Dea K, Giles GG. Glycemic index and dietary fiber and the risk of type 2 diabetes. Diabetes Care. 2004;27: 2701-2706. 59. Murakami K, Sasaki S, Takahashi Y, Okubo H, Hosoi Y, Horiguchi H, Oguma E, Kayama F. Dietary glycemic index and load in relation to metabolic risk factors in Japanese female farmers with traditional dietary habits. Am J Clin Nutr. 2006;83:1161-1169. 60. Lau C, Toft U, Tetens I, Richelsen B, Jorgensen T, Borch-Johnson K, Glumer C. Association between dietary glycemic index, glycemic load, and body mass index in the Inter99 study: Is underreporting a problem? Am J Clin Nutr. 2006;84:641-645. 61. Ma Y, Olendzki B, Chiriboga D, Hebert JR, Li Y, Lie W, Campbell M, Gendreau K, Ockene IS. Association between dietary carbohydrates and body weight. Am J Epidemiol. 2005;161:359-367. 62. Salmeron J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ, Stampfer MJ, Wing AL, Willett WC. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care. 1997;20:545-550. 63. Stevens J, Ahn K, Juhaeri, Houston D, Steffan L, Couper D. Dietary fiber intake and glycemic index and incidence of diabetes in AfricanAmerican and white adults. Diabetes Care. 2002;25:1715-1721. 64. van Dam RM, Visscher AWJ, Feskins EJM, Verhoef P, Kromhout D. Dietary glycemic index in relation to metabolic risk factors and incidence of coronary heart disease: The Zutphen Elderly Study. Eur J Clin Nutr. 2000;54:726-731. 65. Liese AD, Schulz M, Fang F, Wolever TMS, D’Agostino RB, Sparks KC, Mayer-Davis EJ. Dietary Glycemic Index and Glycemic Load, Carbohydrate and Fiber Intake, and Measures of Insulin Sensitivity, Secretion, and Adiposity in the Insulin Resistance Atherosclerosis Study. Diabetes Care. 2005;28:2832-2838. 66. Mayer-Davis EJ, Dhawan A, Liese AD, Teff K, Schulz M. Towards

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67.

68.

69.

70.

71. 72.

73.

74.

75.

76.

77.

78.

79.

80.

81.

82.

83.

84.

85.

86.

87.

88.

understanding of glycaemic index and glycaemic load in habitual diet: Associations with measures of glycaemia in the Insulin Resistance Atherosclerosis Study. Brit J Nutr. 2006;95:397-405. Marshall JA, Bessesen DH, Hamman RF. High saturated fat and low starch and fibre are associated with hyperinsulinemia in a nondiabetic population: The San Luis Valley Diabetes Study. Diabetalogia. 1997;40:430-438. Sahyoun NR, Anderson AL, Kanaya AM, Koh-Banerjee P, Kritchevsky SB, de Rekeneire N, Tylavsky FA, Schwartz AV, Lee JS, Harris TB. Dietary glycemic index and load, measures of glucose metabolism, and body fat distribution in older adults. Am J Clin Nutr. 2005;82:547-552. Larsson SC, Bergkvist L, Wolk A. Glycemic load, glycemic index and carbohydrate intake in relation to risk of stomach cancer: A prospective study. Int J Cancer. 2006;118;3167-3169. Foster-Powell K, Holt SH, Brand-Miller JC. International table of glycemic index and glycemic load values: 2002. Am J Clin Nutr. 2002;76:5-56. Wolever TMS. The glycemic index. World Rev Nutr Diet. 1990;62: 120-185. Miller JB, Pang E, Broomhead L. The glycemic index of foods containing sugars: Comparison of foods with naturally-occurring vs added sugars. Br J Nutr. 1995;73:613-623. Steffen LM, Jacobs DR Jr, Stevens J, Shahar E, Carithers T, Folsom AR. Associations of whole-grain, refined grain, and fruit and vegetable consumption with risks of all-cause mortality and incident coronary artery disease and ischemic stroke: the Atherosclerosis Risk in Communities Study. Am J Clin Nutr. 2003;78:383-390. Montonen J, Knekt P, Jarvinen R, Aromaa A, Reunanen A. Wholegrain and fiber intake and incidence of type 2 diabetes. Am J Clin Nutr. 2003;77:622-629. Koh-Banerjee P, Franz M, Sampson L, Liu S, Jacobs DR Jr, Spiegelman D, Willett W, Rimm E. Changes in whole-grain, bran, and cereal fiber consumption in relation to 8-year weight gain among men. Am J Clin Nutr. 2004;80:1237-1245. Liu SM, Willett WC, Manson JE, Hu FB, Rosner B, Colditz G. Relation between changes in intakes of dietary fiber and grain products and changes in weight and development of obesity among middle-aged women. Am J Clin Nutr. 2003;78:920-927. Jensen MK, Koh-Banerjee P, Hu FB, Franz M, Sampson L, Grønbæk M, Rimm EB. Intakes of whole grains, bran, and germ and the risk of coronary heart disease in men. Am J Clin Nutr. 2004;80:14921499. Qi L, van Dam RM, Liu S, Franz M, Mantzoros C, Hu FB. Wholegrain, bran, and cereal fiber intakes and markers of systemic inflammation in diabetic women. Diabetes Care. 2006;29:207-211. Jacobs DR Jr, Meyer KA, Kushi LH, Folsom AR. 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;68:248-257. Nicodemis KK, Jacobs DR Jr, Folsom AR. Whole and refined grain intake and risk of incident postmenopausal breast cancer (United States). Cancer Causes Control. 2001;12:917-925. Bazzano LA, Song Y, Bubes V, Good CK, Manson JE, Liu S. Dietary intake of whole and refined grain breakfast cereals and weight gain in men. Obes Res. 2005;13:1952-1960. Liu S, Sesso HD, Manson JE, Willett WC, Buring JE. Is intake of breakfast cereals related to total and cause-specific mortality in men? Am J Clin Nutr. 2003;77:594-599. Sahyoun NR, Jacques PF, Zhang XL, Juan W, Mckeown NM. Wholegrain intake is inversely associated with the metabolic syndrome and mortality in older adults. Am J Clin Nutr. 2006;83:124-131. Esmaillzadeh A, Mirmiran P, Azizi F. Whole-grain intake and the prevalence of hypertriglyceridemic waist phenotype in Tehranian adults. Am J Clin Nutr. 2005;81:55-63. Wolk A, Manson JE, Stampfer MJ, Colditz GA, Hu FB, Speizer FE, Hennekens CH, Willett WC. Long-term intake of dietary fiber and decreased risk of coronary heart disease among women. JAMA. 1999;281:1998-2004. Meyer KA, Kushi LH, Jacobs DR Jr, Slavin J, Sellers TA, Folsom AR. Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr. 2000;71:921-930. Lairon D, Arnault N, Bertrais S, Planells R, Clero E, Hercberg S, Boutron-Ruault M-C. Dietary fiber intake and risk factors for cardiovascular disease in French adults. Am J Clin Nutr. 2005;82:11851194. Cho S, Dietrich M, Brown CJP, Clark CA, Block G. The effect of breakfast type on total daily energy intake and body mass index:

89.

90.

91.

92. 93.

94.

95.

96.

97.

98.

99.

100.

101.

102.

103.

104.

105.

106.

107.

108.

109.

110.

Results from the Third National Health and Nutrition Examination Survey (NHANES III). J Am Coll Nutr. 2003;22:296-302. Barton BA, Eldridge AL, Thompson D, Affenito SG, Striegel-Moore RH, Franko DL, Albertson AM, Crockett SJ. The relationship of breakfast and cereal consumption to nutrient intake and body mass index: The National Heart, Lung, and Blood Institute Growth and Health Study. J Am Diet Assoc. 2005;105:1383-1389. Song WO, Chun OK, Obayashi S, Cho S, Chung CE. Is consumption of breakfast associated with body mass index in US adults? J Am Diet Assoc. 2005;105:1373-1382. Rampersaud GC, Periera MA, Girard BL, Adams J, Metzl JD. Review—Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. J Am Diet Assoc. 2005;105:743-760. Cleveland LE, Moshfegh AJ, Albertson AM, Goldman JD. Dietary intake of whole grains. J Am Coll Nutr. 2000;19(suppl):331S-338S. World Health Organization. Obesity: Preventing and managing the global epidemic. In: Report of a WHO Consultation on Obesity, Geneva, 3-5 June 1997. Geneva, Switzerland: WHO Publications; 1997. Bravata DM, Sanders L, Huang J, Krumholz HM, Olkin I, Gardner CD, Bravata DM. Efficacy and safety of low-carbohydrate diets: A systematic review. JAMA. 2003;289:1837-1850. Howard BV, Manson JE, Stefanick ML, Beresford SA, Frank G, Jones B, Rodabough RJ, Snetselaar L, Thomson C, Tinker L, Vitolins M, Prentice R. Low-fat dietary pattern and weight change over 7 years. The Women’s Health Initiative Dietary Modification Trial. JAMA. 2006;295:39-49. Poppitt SD, Keogh GF, Prentice AM, Williams DEM, Sonnemans HMW, Valk EEJ, Robinson E, Wareham NJ. Long-term effects of ad libitum low-fat, high-carbohydrate diets on body weight and serum lipids in overweight subjects with metabolic syndrome. Am J Clin Nutr. 2002;75:11-20. Schaefer EJ, Lichtenstein AH, Lamon-Fava S, McNamara JR, Schaefer MM, Rasmussen H, Ordovas JM. Body weight and lowdensity lipoprotein cholesterol changes after consumption of a lowfat ad libitum diet. JAMA. 1995;274:1450-1455. Hays NP, Starling RD, Liu X, Sullivan DH, Trappe TA, Fluckey JD, Evans WJ. Effects of an ad libitum low-fat, high-carbohydrate diet on body weight, body composition, and fat distribution in older men and women. Arch Intern Med. 2004;164:210-217. Sandstrom B, Marckmann P, Bindslev N. An eight-month controlled study of a low-fat high-fibre diet: Effects on blood lipids and blood pressure in healthy young subjects. Eur J Clin Nutr. 1992;46:95-109. Prewitt TE, Schmeisser D, Bowen PE, Aye P, Dolecek TA, Langenberg P, Cole T, Brace L. Changes in body weight, body composition, and energy intake in women fed high- and low-fat diets. Am J Clin Nutr. 1991;54:304-310. Kendall A, Levitsky DA, Strupp BJ, Lissner L. Weight loss on a low-fat diet: Consequence of the imprecision of the control of food intake in humans. Am J Clin Nutr. 1991;53:1124-1129. Lissner L, Levitsky DA, Strupp BJ, Kalkwarf HJ, Roe DA. Dietary fat and the regulation of energy intake in human subjects. Am J Clin Nutr. 1987;46:886-892. Raben A, Jensen ND, Marckmann P, Sandstrom B, Astrup A. Spontaneous weight loss during 11 weeks’ ad libitum intake of a low fat/high fiber diet in young, normal weight subjects. Int J Obes. 1995;19:916-923. Shah M, McGovern P, French S, Baxter J. Comparison of a low-fat, ad libitum complex-carbohydrate diet with a low-energy diet in moderately obese women. Am J Clin Nutr. 1994;59:980-984. Anderson JW, Konz EC, Frederich RC, Wood CL. Long-term weightloss maintenance: A meta-analysis of US studies. Am J Clin Nutr. 2001;74:579-584. Hall WD, Feng ZD, George VA, Lewis CE, Oberman A, Huber M, Fouad M, Cutler JA. Low-fat diet: Effect on anthropometrics, blood pressure, glucose, and insulin in older women. Ethn Dis. 2003;13: 337-343. Sheppard L, Kristal AR, Kushi LH. Weight loss in women participating in a randomized trial of low-fats diets. Am J Clin Nutr. 1991;54:821-828. Mokdad AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan JP. The spread of the obesity epidemic in the United States, 1991-1998. JAMA. 1999;282:1519-1522. Hill JO, Wyatt H, Phelan S, Wing R. The National Weight Control Registry: Is it useful in helping deal with our obesity epidemic? J Nutr Educ Behav. 2005;37:206-210. Carmichael HE, Swinburn BA, Wilson MR. Lower fat intake as a predictor of initial and sustained weight loss in obese subjects con-

111.

112.

113.

114.

115.

116.

117. 118. 119.

120. 121. 122.

123.

124.

125.

126. 127.

128. 129. 130.

131. 132.

suming an otherwise ad libitum diet. J Am Diet Assoc. 1998;98: 35-39. Lindstrom J, Peltonen M, Eriksson JG, Louheranta A, Fogelholm M, Uusitupa M, Tuomilehto J. High-fibre, low-fat diet predicts longterm weight loss and decreased type 2 diabetes risk: The Finnish Diabetes Prevention Study. Diabetologia. 2006;49:912-920. Toubro S, Astrup A. Randomized comparison of diets for maintaining obese subjects’ weight after major weight loss: Ad lib, low fat, high carbohydrate diet v fixed energy intake. Br Med J. 1997;314: 29-34. Westerterp-Plantenga MS, Wijckmans-Duijsens NEG, Verboeketvan de Venne WPG, de Graaf K, van het Hof KH, Weststrate JA. Energy intake and body weight effects of six months reduced or full fat diets, as a function of dietary restraint. Int J Obes. 1998;22:14-22. Howarth NC, Murphy SP, Wilkins LR, Hankin JH, Kolonel LN. Dietary energy density is associated with overweight status among five ethnic groups in the Multiethnic Cohort Study. J Nutr. 2006; 136:2243-2248. Ledikwe JH, Blanck HM, Kettel Khan L, Serdula MK, Seymour JD, Tohill BC, Rolls BJ. Dietary energy density is associated with energy intake and weight status in US adults. Am J Clin Nutr. 2006;83: 1362-1368. Weigle DS, Cummings DE, Newby PD, Breen PA, Frayo RS, Matthys CC, Callahan HS, Purnell JQ. Roles of leptin and ghrelin in the loss of body weight caused by a low fat, high carbohydrate diet. J Clin Endocrinol Metab. 2003;88:1577-1586. Dickinson S, Brand-Miller J. Glycemic index, postprandial glycemia and cardiovascular disease. Curr Opinion Lipidology. 2005;16:69-75. Flight I, Clifton P. Cereal grains and legumes in the prevention of coronary heart disease and stroke: A review of the literature. Eur J Clin Nutr. 2006;60:1145-1159. McKeown NM, Meigs JB, Liu S, Saltzman E, Wilson PWF, Jacques PF. Carbohydrate nutrition, insulin resistance, and prevalence of the metabolic syndrome in the Framingham Offspring Cohort. Diabetes Care. 2004;27:538-546. Opperman AM, Venter CS, Oosthuizen W, Thompson RL, Vorster HH. Meta-analysis of the health effects of using the glycaemic index in meal-planning. Br J Nutr. 2004;92:367-381. Kelly S, Frost G, Whittaker V, Summerbell C. Low glycaemic index diets for coronary heart disease. Cochrane Database System Rev. 2004;4:CD004467. Liu S, Willett WC, Stampfer MJ, Hu F, Franz M, Sampson L, Hennekens CH, Manson JE. A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. Am J Clin Nutr. 2000;71:1455-1461. Lau C, Faerch K, Glümer C, Tetens I, Pedersen O, Carstensen B, Jørgensen T, Borch-Johnsen K. Dietary glycemic index, glycemic load, fiber, simple sugars, and insulin resistance. The Inter99 Study. Diabetes Care. 2005;28:1397-1403. Oh K, Hu FB, Cho E, Rexrode KM, Stampfer MJ, Manson JE, Liu S, Willett WC. Carbohydrate intake, glycemic index, glycemic load, and dietary fiber in relation to risk of stroke in women. Am J Epidemiol. 2005;161:161-169. Michaud DS, Fuchs CS, Liu S, Willett WC, Colditz GA, Giovannucci E. Dietary glycemic load, carbohydrate, sugar, and colorectal cancer risk in men and women. Cancer Epidemiol Biomarkers Prev. 2005; 14:138-143. Terry PD, Jain M, Miller AB, Howe GR, Rohan TE. Glycemic load, carbohydrate intake, and risk of colorectal cancer in women: A prospective cohort study. J Nat Cancer Inst. 2003;95:914-916. Sheard NF, Clark NG, Brand-Miller JC, Franz MJ, Pi-Sunyer FX, Mayer-Davis E, Kulkarni K, Geil P. Dietary carbohydrate (amount and type) in the prevention and management of diabetes: A statement by the American Diabetes Association. Diabetes Care. 2004;27: 2266-2271. Liu SM, Manson JE, Stampfer MJ, Rexrode KM, Hu FB, Rimm EB, Willett WC. Whole grain consumption and risk of ischemic stroke in women: A prospective study. JAMA. 2000;284:1534-1540. Kennedy ET, Bowman SA, Spence JT, Freedman M, King J. Popular diets: Correlation to health, nutrition, and obesity. J Am Diet Assoc. 2001;101:411-420. Yang EJ, Chung HK, Kim WY, Kerver JM, Song WO. Carbohydrate intake is associated with diet quality and risk factors for cardiovascular disease in US adults: NHANES III. J Am Coll Nutr. 2002;22: 71-79. Davy B, Melby CL. The effect of fiber-rich carbohydrates on features of Syndrome X. J Am Diet Assoc. 2003;103:86-96. Anderson JW. Whole grains protect against atherosclerotic cardiovascular disease. Proc Nutr Soc. 2003;62:135-142.

October 2007 ● Journal of the AMERICAN DIETETIC ASSOCIATION

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133. McBurney MI. Candidate foods in the Asia-Pacific region for cardiovascular protection: Relevance of grains and grain-based foods to corollary heart disease. Asia Pacific J Clin Nutr. 2001;10:123127. 134. Slavin JL. Whole grains, refined grains and fortified grains: What’s the difference? Asia Pacific J Clin Nutr 2000;9(suppl S):S23-S27. 135. Cho S, Johnson G, Song WO. Folate content of foods: Comparison between databases compiled before and after new FDA fortification requirements. J Food Comp Anal. 2002;15:293-307. 136. Lutsey PL, Steffen LM, Feldman HA, Hoelscher DH, Webber LS, Luepker RV, Lytle LA, Zive M, Osganian SK. Serum homocysteine is related to food intake in adolescents: The Child and Adolescent Trial for Cardiovascular Health. Am J Clin Nutr. 2006;83:1380-1386.

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137. Ford ES, Mokdad AH, Liu S. Healthy eating index and C-reactive protein concentration: Findings from the National Health and Nutrition Examination Survey III, 1988-1994. Eur J Clin Nutr. 2005; 59:278-283. 138. Erkkila AT, Herrington DM, Mozaffarian D, Lichtenstein AH. Cereal fiber and whole-grain intake are associated with reduced progression of coronary-artery atherosclerosis in postmenopausal women with coronary artery disease. Am Heart J. 2005;150:94-101. 139. Jacobs DR Jr, Periera MA, Meyer KA, Kushi LH. Fiber from whole grains, but not refined grains, is inversely associated with all-cause mortality in older women: The Iowa Women’s Health Study. J Am Coll Nutr. 2000;19(suppl):326S-330S. 140. Zilversmit DB. Atherogenesis: A postprandial phenomenon. Circulation. 1979;60:473-485.