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Advances in Nutrition logoLink to Advances in Nutrition
. 2013 May 6;4(3):356S–367S. doi: 10.3945/an.112.003509

White Vegetables: Glycemia and Satiety1,2

G Harvey Anderson 1,*, Chesarahmia Dojo Soeandy 1, Christopher E Smith 1
PMCID: PMC3650508  PMID: 23674805

Abstract

The objective of this review is to discuss the effect of white vegetable consumption on glycemia, satiety, and food intake. White vegetables is a term used to refer to vegetables that are white or near white in color and include potatoes, cauliflowers, turnips, onions, parsnips, white corn, kohlrabi, and mushrooms (technically fungi but generally considered a vegetable). They vary greatly in their contribution to the energy and nutrient content of the diet and glycemia and satiety. As with other foods, the glycemic effect of many white vegetables has been measured. The results illustrate that interpretation of the semiquantitative comparative ratings of white vegetables as derived by the glycemic index must be context dependent. As illustrated by using the potato as an example, the glycemic index of white vegetables can be misleading if not interpreted in the context of the overall contribution that the white vegetable makes to the carbohydrate and nutrient composition of the diet and their functionality in satiety and metabolic control within usual meals. It is concluded that application of the glycemic index in isolation to judge the role of white vegetables in the diet and, specifically in the case of potato as consumed in ad libitum meals, has led to premature and possibly counterproductive dietary guidance.

Introduction

Food guidelines in the United States and Canada recommend the consumption of at least 1 serving of dark green and 1 orange vegetable per day (1, 2). However, no such recommendation exists for white vegetables. The term white vegetables refers to vegetables that are white or near white in color (3) and include potatoes, cauliflowers, turnips, onions, parsnips, mushrooms, white corn, and kohlrabi (4, 5). They have been important vegetables in the North American diet for hundreds of years and have played an essential role in providing essential nutrients and energy during the years of settlement to present. Yet the current status of white vegetables, particularly the potato, in the diet of Americans, for whom obesity and its health consequences are of great concern, has become uncertain.

The objective of this review is to discuss the effect of white vegetable consumption on glycemia, satiety, and food intake. White vegetables, such as potatoes, onions, garlic, ginger, and corn, are discussed, with a focus on human studies. Additionally, although mushrooms are technically classified as fungi, they are commonly considered to be vegetables, and thus are discussed in this paper as such. Other papers in this supplement discuss the nutrient content of white vegetables. Therefore, this review is based on the hypothesis that a singular focus on the effects of carbohydrate in white vegetables on blood glucose, as measured by the glycemic index (GI)3, may lead to counterproductive dietary recommendations. It examines the question “what weight should be placed on GI or postmeal glycemia in vegetables that have high nutrient-to-energy density ratios, are low in energy density compared with other mealtime carbohydrate sources, and within a meal contribute to early satiation and lower food intake?” The conclusion is based primarily on the potato because there is very limited relevant information on other white vegetables.

The GI and the glycemic effect of white vegetables

Carbohydrates are chemically classified based on their structure and molecular size into categories such as sugars, oligosaccharides, polysaccharides, and polyols, which respectively refer to carbohydrates with 1–2 monomers, 3–9 monomers, >9 monomers and hydrogenated carbohydrates (6). The variability of the physiological effects of dietary carbohydrates was first reported in 1939 by Conn and Newburgh (7), who found that the consumption of different foods in isoglucogenic amounts resulted in different glycemic responses. For example, the consumption of potato with butter or bread with butter, both containing 68 g of available glucose, resulted in different blood glucose peaks and blood glucose AUCs (7). However, it was not until the 1970s that classifying carbohydrates based on physiological effects grew in popularity. Beginning with the concept of carbohydrate exchange for management of glucose excursions in individuals with diabetes (8), the approach became more quantitative through the development of the GI (9).

The GI of carbohydrates is determined and classified based on a standardized procedure recognized by the International Standards Organization (10) and by Standards Australia (11). It is defined as the incremental AUC of the 2-h blood glucose response after the consumption of a fixed amount, usually 50 g, of available carbohydrates of a test food expressed as a percentage of the response to the same amount of carbohydrates from either white bread or glucose, taken by each of a minimum of 10 participants (9, 1214). The mean responses among these participants constitute the reported GI value. The GI of foods is arbitrarily classified as low if it is <55, intermediate if the value is between 56 and 69, and high if >70, when compared with glucose as the reference (10). The GI is based on the consumption of a fixed amount of available carbohydrate, which may not be representative of the glycemic effect of the amount of carbohydrate usually consumed in a serving of a food in a meal.

However, because the GI compares the effect of equal amounts of available carbohydrates from the test food and white bread or glucose control, the effect of the test food on blood glucose is assumed to be related to the chemistry and structure of the carbohydrates that it contains. To date, the GIs of >2480 food items have been published (12). The GI of foods has been accepted as a useful research tool for understanding the physiological responses to carbohydrate composition in commonly consumed foods and has stimulated a plethora of experimental and epidemiological research.

However, at present, polarized views exist concerning whether the GI values of individual foods are relevant and applicable to clinical and public health when used in conjunction with existing food guides and guidelines. Promoters of the concept claim that quantitative knowledge of the effect of a food on blood glucose has wide applications because it allows for the selection of foods and the construction of diets that minimize fluctuations in blood glucose and insulin, improve glucose and lipid metabolism in diabetes, lower blood triglycerides if increased, and benefit weight control. The concept was endorsed and recommended by the FAO of the United Nations and the WHO in a report published in 1997 (15). Similarly, based on consensus evaluations of the benefits of the GI, some professional associations, such as those focused on diabetes (16, 17) and heart disease (18), have recommended its application to food selection. Food-labeling initiatives, in which the GI values of different foods are made publically discernible through food labels have occurred in Australia, Sweden, and South Africa (19). These recommendations and labeling initiatives from trusted organizations and government bodies provide strong support for the application of the GI to food selection for both prevention and management of chronic disease.

Conversely, critics of the concept suggest that use of the GI for the purpose of adding clarity to dietary advice is not grounded on sufficient scientific evidence. The often raised criticisms of the GI are its high variability within and between individuals, its inaccuracy in predicting mixed meal glycemic effects, its failure to take into account the effects of concurrent intake of fat and protein, its use of 50 g of available carbohydrate that is not representative of serving sizes, and the fact that it leads to dietary advice that ignores other beneficial physiological and dietary properties of foods. These criticisms are discussed briefly in the following.

A recent evidence-based review of epidemiological studies concluded that the mixed status of the results presented in the current literature renders it premature to include the GI in dietary recommendations for healthy populations (20). In addition, the authors suggest that the feasibility of reducing the dietary GI beyond that achieved with current dietary advice is questionable (20). They point to the confusion among the public caused by contrasting health messages and the complexity of the concept, and thus applying the GI may be a challenge for most (20).

Stronger criticism focuses on the implicit assumption that leads to giving this physiological measure equal status in precision to other analytical values of food. Critics argue that the variability of the GI is too large to give it this status. Indeed, this criticism has substantial justification. First, GI measurements differ not only between individuals but also within individuals (21). For example, the mean GI of white bread compared with glucose (n = 23) was 78, with a group SD of 72, a CV of 94%, and a range of 58 to 185 (21). However, when 14 of the 23 participants completed 2 additional replicates, totaling 3 sets of GI measurements per participant, the GI of white bread was determined to be 71 (SD = 24.5) with the source of variation allocated to both intraindividual (CV of 18%) and interindividual (CV of 43%) variation (21). Similarly, an interlaboratory study showed that GI measurements have low reproducibility of the mean GI among different laboratories, despite the use of the same protocol (Table 1).

Table 1.

Glycemic index assay variability: an interlaboratory study1

Food Glycemic index2 Range
Glucose 100
White bread 72 ± 36 0 to 144
Instant mashed potatoes 84 ± 33 18 to 150
Long grain rice 78 ± 38 2 to 154
White spaghetti 47 ± 27 −7 to 101
Pot barley 35 ± 25 −15 to 85
1

Data are from (99). Based on results from pooled values from venous (2 centers, 21 subjects) and capillary (5 centers, 47 subjects) samples.

2

Values are mean ± SD; reported SEM values were converted into SD values. The 95% CI for the glycemic index of white bread for all participants is 0–144. Estimated glycemic indexes for other foods show similarly wide ranges. Mean glycemic indexes for spaghetti and barley were lower (P < 0.05) than for white bread, instant mashed potatoes, and rice.

Another common criticism of the GI is the variability that arises in estimates of the glycemic effect of mixed meals based on their carbohydrate components. Although some reports show that the GI of individual components of a meal containing 50 g of carbohydrate may be appropriately used to predict the GI of the meal itself (22, 23), a recent study found that the calculated GI appreciably overestimates the measured GI of the meal (24). The study measured the GI of the each carbohydrate component of a meal when consumed alone, such as potato, rice, and spaghetti, in 30 participants. Then the GI of meals, each providing 50 g of available carbohydrate and containing one of the stated carbohydrate sources along with carrots, peas, and chicken was determined in the same individuals (24). The predicted GIs of the potato, rice, and spaghetti meals were found to be overestimated by 22%, 40%, and 50%, respectively, compared with the measured GIs for each participant; however, similar overestimations were found when published GI values of these meal components were used (24).

A criticism of the formula used to calculate the GI of mixed meals is that it addresses only the carbohydrate components of the foods (22). Specifically, the formula for calculating the GI of a mixed meal involves the following 3 steps: determining the proportion of total meal carbohydrate that each component contributes, multiplying each component’s GI by its respective proportion to determine the contribution of each component to the overall GI, and finally adding together the GI contributions of all the components to determine the overall GI of the meal (22). Thus, the formula, as originally designed, fails to take into account the effects of protein and fat consumption, which is now recognized as a weakness (25). The importance of protein and fat is illustrated by another study showing that the GI values of mixed meals, such as composite breakfast meals, correlated most closely with fat and protein content rather than carbohydrate content (26). This can be attributed to the postprandial physiological effects of protein and fat. Although carbohydrates strongly stimulate insulin, fat and protein affect blood glucose via several mechanisms (27). Fats reduce the rate of gastric emptying by stimulating the release of cholecystokinin (CCK) from enteroendocrine cells located in the proximal small intestine (28, 29). Protein induces the secretion of several gut hormones (27) that decrease the rate of gastric emptying (30) and promote glycemic control (31).

In support of the inaccuracy of the formula-based prediction of GI of mixed meals, another study found that when mixed meals predicted to have a high, medium, or low GI were tested, they had comparable plasma glucose and insulin responses in both normal and diabetic patients (23). However, it has also been argued that although the glycemic effect of a mixed meal is indeed different from the lone consumption of its individual components, the relative response between different carbohydrates within meals remains the same (32). For example, when lentils (low GI) are eaten as part of a mixed meal, the glycemic response is lower than that of a similar white bread–based mixed meal (32). However the net effect is a lower glycemic response (incremental AUC) over 2 h after meals than that obtained with the 50 g carbohydrate used in determining the GI, which identifies another area of confusion in the application of GI terminology to both foods and meals.

The terminology used in discussing the GI of individual foods compared with meals needs to be clarified. For example, the GI of the reference food (glucose or white bread) is primarily standardized at 50 g of available carbohydrate, which, like meals, may be expected to confound the stated goal of the GI. However, many foods with reported GI values have substantial amounts of protein and fat (33), to describe the characteristics of the carbohydrate in foods for the purpose of dietary guidance for the control of glycemia. For these foods then, it would seem to be more appropriate to discuss the relative glycemic response rather than the GI, as suggested for meal effects on glycemia (25). In addition, a recent study that used stable isotope tracers to track carbohydrate absorption from pasta and white bread showed slower uptake of glucose from pasta but a GI similar to that of white bread because of lower postprandial insulin and gastric inhibitory polypeptide (GIP) concentrations balanced by a slower glucose clearance rate (34). Thus, the GI may fail to classify starchy products correctly for the purpose of managing insulin requirements.

It is for these reasons that critics of the GI argue that current knowledge does not support its use as a refinement to dietary guidance or as a quantitative label on foods for public health advice or regulatory purposes. For example, an international group assembled in 2004 by the International Life Sciences Institute concluded that more research was needed for the discussion to move beyond personal beliefs to actual knowledge (35). Similarly, the macronutrient report published by the National Academy of Sciences in 2005 made no recommendations concerning the GI due to lack of sufficient evidence” (36). More recently, the dietary guidelines published by the USDA, and the Department of Health and Human Services in 2010 stated that it is not necessary to consider the GI when choosing carbohydrate foods for weight management, based on evidence that suggests that no correlation exists between the two (2). Furthermore, the advisory council of the 2010 USDA dietary guidelines concluded that “studies of carbohydrates and health outcomes on a macronutrient level are often inconsistent or ambiguous due to inaccurate measures and varying food categorizations and definitions. The science cannot progress without further advances in both methodology and theory” (37). Because of this, the Committee stated a need to “develop and validate carbohydrate assessment methods. Explore and validate new and emerging biomarkers to elucidate alternative mechanisms and explanations for observed effects of carbohydrates on health” (37).

Similar caution on the application of the GI for labeling purposes has been expressed by the European Food Safety Authority (38) and the Canadian Food Inspection Agency (39). Both suggest that more research is needed to examine postmeal glycemic responses rather than GI for application to health claims. The labeling of foods with the GI is thus not supported.

An examination of the application of the GI to dietary recommendations for potatoes and other white vegetables serves to illustrate the validity of these criticisms and cautionary messages. It demonstrates that it has potential to be misleading when applied to judge foods without taking into account the nutrient composition and functionality of the food, the effect of within-meal consumption, and the effect of its consumption in normally consumed amounts.

Potatoes

In the past 20 y, potatoes have had a steady stream of blame for contributing to obesity and its associated consequences. Thus, French fries have been banned from school cafeterias (40), quick service restaurants have decreased serving sizes (41), and per capita consumption of potatoes has decreased by 41% over the past 40 y (42) at the expense of alternative energy-dense starches such as pasta and rice, recommended as meal accompaniments (42, 43). These outcomes ignore the fact that the potato is rich in nutrient content (44) and, as one of the significant mealtime carbohydrate sources, is low in energy density (fresh, baked, and boiled contain 70, 85, and 80 kcal/g) compared with other most frequently consumed mealtime carbohydrate sources such as pasta and rice. Precooked, the latter average 3.7 kcal/g, and when cooked in water, contain ∼30%–50% more energy per gram as served. In addition, the potato has other functional and beneficial health components (45), as reviewed in these proceedings.

Although potatoes are commonly considered to be a high GI food, its reported GI values, standardized to glucose, range from 14 ± 2 (46) for potato noodles to 120 ± 79 (47) for boiled Sava potato served hot (Table 2). Similarly, the GI of potatoes commonly consumed in North America are reported to range from 56 to 89 (48), and those in Great Britain range from 56 to 94 (13). Some of this variation can be attributed to preparation. However, it is difficult to explain the large range in GI reported for 17 measures of boiled potatoes served hot (Table 2). Although the overall mean for boiled potatoes supports a high GI ranking, it ranges from a low of 56 (13) to a high of 120 (47) (Table 2). The source of this variation is not readily apparent, but leads to an obvious need to be cautious in applying a specific GI to the potato. Although mashed potatoes are stated to have the highest GI, reported values do not consistently demonstrate this, nor are there any statistically observable physiological differences between mashed and baked, microwaved, boiled, or new potatoes (Table 2). Baked French fries and potato crisps in fact have medium GI values. Similarly, serving boiled potatoes cold has been reported to reduce the GI to the medium range, but the results are not consistent (Table 2).

Table 2.

Summary of selected glycemic index and blood glucose responses by potato variety and preparation1

Preparation method Variety/type of potato (Reference) Glycemic index2 Blood glucose response3 Participants
Baked mmol · min/L n
 — Irish potato (100) 83 ± 20 10 (5 F, 5 M)
 With skin Old white potato (101) 69 ± 32 42 (33 F, 9 M)
 With out skin Old white potato (101) 98 ± 52 42 (33 F, 9 M)
 Served hot Pontiac (102) 93 ± 35 10 (8 F, 2 M)
Boiled
 Served hot Asterix (57) 79 ± 374 160 ± 67 14 (8 F, 6 M)
 Served hot Charlotte (13) 66 ± 21 134 ± 124 17 (14 F, 3 M)
 — Charlotte (101) 81 ± 71 42 (33 F, 9 M)
 Served hot Desiree (13) 77 ± 70 133 ± 74 17 (14 F, 3 M)
 Served hot Desiree (102) 101 ± 47 10 (8 F, 2 M)
 Served hot Estima (13) 66 ± 21 143 ± 54 17 (14 F, 3 M)
 — Irish potato (100) 59 ± 13 10 (5 F, 5 M)
 Served hot King Edward (13) 75 ± 41 166 ± 41 17 (14 F, 3 M)
 Served hot Marfona (13) 56 ± 12 93 ± 87 17 (14 F, 3 M)
 Served hot Maris Peer (13) 94 ± 66 182 ± 136 17 (14 F, 3 M)
 Served hot Maris Piper (13) 85 ± 16 167 ± 70 17 (14 F, 3 M)
 Served hot Nicola (13) 59 ± 29 130 ± 41 17 (14 F, 3 M)
 — Old white potato (101) 96 ± 65 42 (33 F, 9 M)
 Served hot Pontiac (102) 88 ± 28 10 (8 F, 2 M)
 Served hot Red potato (48) 89 ± 24 208 ± 69 12 (1 F, 11 M)
 Served hot Sava (47) 120 ± 794 150 ± 72 13 (10 F, 3 M)
 Served hot Sebago (102) 87 ± 22 10 (8 F, 2 M)
 Stored and served cold Red potato (48) 56 ± 17 135 ± 62 12 (1 F, 11 M)
 Stored and served cold Sava (47) 89 ± 434 119 ± 61 13 (10 F, 3 M)
 — New potato (101) 80 ± 97 42 (33 F, 9 M)
 Served hot New potato (102) 78 ± 38 10 (8 F, 2 M)
Mashed
 Served hot Pontiac (102) 91 ± 28 10 (8 F, 2 M)
 — Desiree (101) 102 ± 84 42 (33 F, 9 M)
 — Unspecified (46) 73 ± 9 10–12
Microwaved
 Served hot Pontiac (102) 79 ± 28 10 (8 F, 2 M)
 Served hot Prince Edward Island (48) 73 ± 17 178 ± 73 12 (1 F, 11 M)
 Served hot Russet Norkotah (48) 77 ± 31 178 ± 87 12 (1 F, 11 M)
Canned and served hot New potato (102) 65 ± 28 10 (8 F, 2 M)
Baked french fries
 Served hot Unspecified (57) 55 ± 15 116 ± 56 14 (8 F, 6 M)
 Served hot Unspecified (48) 64 ± 21 155 ± 66 12 (1 F, 11 M)
Instant mashed potato
 Served hot Unspecified (48) 88 ± 28 206 ± 80 12 (1 F, 11 M)
 Served hot Unspecified (101) 95 ± 104 42 (33 F, 9 M)
Potato crisp
 Oil-fried Unspecified (46) 60 ± 7 10–12
 Plain and salted Unspecified (12) 57 6
Roasted California white (48) 72 ± 28 165 ± 69 12 (1 F, 11 M)
Fried Irish potato (100) 70 ± 19 10 (5 F, 5 M)
Cooked Unspecified (46) 66 ± 4 10–12
Steamed Unspecified (46) 62 ± 6 10–12
Potato noodle Unspecified (46) 14 ± 2 10–12
1

Dashes indicate unmeasured or unreported values, although a graphic representation may be available. Values are based on test meals containing 50 g of available carbohydrate and tested on healthy participants. F, female; M, male.

2

Values are based on a glucose reference and represent mean ± SD; any reported SEM values were converted to SD values for consistency. Classification of the glycemic index (48): low, <55; intermediate, 55–69; high, 70–100.

3

Based on incremental AUC.

4

Divided by 1.4 to convert the values from a white bread reference index to glucose reference (99).

A decrease in GI of cold potatoes might be expected due to the retrogradation of starches to form resistant starch (49). Resistant starch is only partially digestible and absorbable in the small intestine; thus, its consumption would be expected to lower blood glucose and insulin responses. However, the amounts formed in cooked and cooled potatoes are very small, an increase of only 6% compared with hot potatoes (48), making it difficult to recommend cold potatoes as the solution. The proportion of total starch that is resistant to digestion in the small intestine in raw potato is much higher than when cooked, 54% compared with <12%, and its consumption by healthy subjects results in lower plasma concentrations of glucose, insulin, GIP, and glucagon-like peptide 1 (GLP-1) compared with the consumption of a fully digestible, pregelatinized potato starch meal (50). However, poor palatability will likely preclude the consumption of raw potato in appreciable amounts.

Other white vegetables

The GI values of other white vegetables are shown in Table 3. As was observed for potatoes, the range of values reported for each is large, depending on the preparation: boiled parsnip, for example, has values of 52 (12) to 97 (51), turnip has values of 30 and 85 for the raw and cooked form, respectively, and raw celery root has a GI of 35, but its cooked form has a GI of 85 (Table 3). Boiled whole corn has a GI of 37, and commonly consumed corn products, such as corn chips and cornflakes, have a GI in the 70–80 range (14). Values listed for other vegetables in Table 3 are of an unknown preparation, as they are based on online sources and could not be found in peer-reviewed publications.

Table 3.

Glycemic index values of other white vegetables

Vegetable Glycemic index1
Cauliflower 15–302
Celery root 35 (raw), 85 (cooked)2
Corn 37–68 (12)
Garlic 10–302
Ginger 10 (candied or spread) to 50 (marmalade) (12)
Mushroom 10–152
Onion 10–152
Parsnip 52 (12)–97 (9)3 (both boiled)
Turnip 30 (raw), 85 (cooked)2
1

Glycemic index based on a glucose reference. Values are mean or range of means. Classification of the glycemic index (48): low, <55; intermediate, 55–69; high, 70–100.

2

Values were obtained from online sources as they were not found in peer-reviewed publications or glycemic indextables. Thus, no specific methods of food preparations were found.

3

Test food was served in 25-g portions rather than the usual 50 g and was compared with 50-g portions of glucose.

In turn, this apparent variability may be caused by other factors that can markedly affect the glycemic response to carbohydrate foods, including white vegetables. These include growing conditions, variety, processing conditions, and the composition and amount of companion foods.

Satiety index of carbohydrate foods

After the publication of the first tables of the GIs of foods (9), tables of the satiety index (SI) of similar foods appeared (52), although the latter are no longer reported. The term satiety refers to a reduced subjective feeling of appetite or desire for food that arises after the consumption of food or beverage and is usually attributed to physiological signals (53). Levels of satiety can be assessed by means of a visual analogue scale and by measuring food intake. Visual analogue scales allow individuals to rate feelings of hunger, fullness, prospective food consumption, desire to eat, and other such descriptors of appetite. These subjective measures of satiety are highly variable, and large sample sizes are required to detect treatment effects. A more quantitative measure of the effect of foods on satiety is to measure food intake from an ad libitum meal at a later time after consumption of the test food (27).

Like the GI, the SI is expressed as the effect of the test food relative to white bread or glucose when 50 g of carbohydrates is consumed. The dependent measures are subjective satiety over the 2 h and food intake at a test meal 2 h later. There have been relatively few studies of satiety using white vegetables. However, in relation to the GI, available SI values indicate that interpretation must be context dependent. In Table 4, the SI and GI of several commonly consumed starchy foods are compared. Clearly, the higher the GI, the higher the SI will be, which is to be expected, because an increase in blood glucose is associated with satiety, and fluctuations in blood glucose concentrations are intimately linked to hypothalamic mechanisms regulating food intake (54, 55). Potatoes, for example, have a high satiety value when studied in the GI format, which is consistent with the physiological role of glucose in food intake regulation (56). That is, when food intake is measured 2 h after ∼50 g of available carbohydrate in 1000-kJ portions are fed, boiled potatoes have the highest indexes of satiety (323 ± 184) compared with other foods and compared with white bread, the usual reference (52). Boiled and mashed potatoes provide equivalent levels of satiety (57) but higher levels of satiety than baked French fries (116 ± 126), which have a GI of 55–64, when fed on an energy-equivalent basis (52, 57). However, when compared on a carbohydrate-equivalent basis, boiled potatoes and French fries were found to provide equivalent levels of satiety (57).

Table 4.

Satiety ratings of carbohydrate foods1

Food Satiety AUC2 Satiety index2 Glycemic index3
mm·min
White bread 77 ± 68 100 75 ± 6
French fries 89 ± 97 116 ± 126 63 ± 16
White pasta 91 ± 97 119 ± 126 49 ± 64
Brown rice 101 ± 97 132 ± 126 68 ± 13
White rice 106 ± 86 138 ± 112 73 ± 13
Grain bread 119 ± 112 154 ± 144 53 ± 65
Whole meal bread 121 ± 79 157 ± 104 74 ± 6
Brown pasta 145 ± 126 188 ± 162 48 ± 166
Boiled potatoes 248 ± 141 323 ± 184 78 ± 13
1

Values shown are mean ± SD

2

Values from Holt et al. (52), n = 13. Reported SEM values were converted to SD for consistency.

3

Values were obtained from Atkinson et al. (12). Values based on variable unreported number of subjects. Reported SEM converted to SD assuming n = 10.

4

The value for white spaghetti was used.

5

The value for specialty grain bread was used.

6

The value for whole wheat spaghetti was used.

In addition, higher levels of blood glucose are associated with higher subjective satiety (54), and thus meals that elicit a higher postprandial glycemic response would be expected to suppress short-term appetite to a greater extent compared with those with a lower glycemic response. Indeed, it was found that the consumption of a low glycemic raw potato starch meal high in resistant starch resulted in lower reported satiety and fullness compared with a highly digestible pregelatinized potato starch meal (50). Furthermore, the lower levels of satiety after the high resistance starch meal were concomitant with lower levels of GIP and GLP-1 (50). Therefore, due to the positive association between blood glucose concentrations and satiety (54) and the minimal glycemic effect of resistant starch (50), satiety is negatively affected by its consumption compared with a meal with readily digestible carbohydrates (54).

As well, the satiating effects of potatoes may be affected by the age of the individual. For example, in children, the consumption of a potato-based meal results in a lower satiety level than spaghetti-based meals, as based on energy intake (kcal) measured 3.5 h later (58). Conversely, in healthy elderly participants, potato meals were found to increase satiety and decrease food intake at a meal served 2 h later compared with a glucose drink, low GI barley meal, and a noncaloric control drink (59).

The SI of white vegetables other than potatoes has not been reported.

Glycemic response to ad libitum meals of usual serving sizes

The glycemic response to carbohydrate foods is reduced when they are consumed with other foods common to a mixed meal. As can be seen in Table 5, the GI of a fixed portion of potatoes with 50 g carbohydrate (the usual amount for GI testing) consumed as part of a mixed meal is often very different in magnitude of glycemic response from that observed when potatoes are consumed alone. For example, the consumption of baked Estima potatoes with 62 g of cheddar cheese reduced the GI from 93 to 39 (Table 5) (60). Similarly, serving mashed potatoes containing 50 g of carbohydrate with oil, chicken breast, and a salad to represent a meal reduced the GI of the potato from 108 to 54 (Table 5) (61). Many other examples of factors reducing the glycemic response to carbohydrate are shown in Table 5. Perhaps more important for dietary advice is that many self-determined meals consumed ad libitum may have >50 g or <50 g of available carbohydrate and may consist of infinite combinations of fat and protein-containing foods.

Table 5.

Glycemic index and blood glucose response (incremental AUC) of potato-based mixed meals 1

Variety/type of potato (Reference) Preparation method Glycemic index2 Blood glucose incremental AUC Participants
mmol·min/L n
Asterix (57) Boiled, served hot 79 ± 373 160 ± 67 14 (8 F, 6 M)
 Served hot with 15.4 g of sunflower oil 94 ± 373 194 ± 79
Estima (60) Microwaved then oven baked, served hot 93 ± 51 40 (29 F, 11 M)
 With 62 g of canned tuna 76 ± 44
 With 62 g of cheddar cheese 39 ± 32
 With 63 g of chilli con carne 75 ± 44
 With 89 g of baked beans 62 ± 38
Unspecified (61) Mashed potato 108 ± 48 197 ± 97 12 (9 F, 3 M)
 With 30 g of oil and 40 g of cucumber 71 ± 35 136 ± 76
 With 108 g of chicken breast and 40 g of cucumber 64 ± 35 113 ± 55
 With 120 g of salad4 108 ± 42 189 ± 76
 With 30 g of oil, 108 g of chicken breast and 120 g of salad1 54 ± 24 96 ± 45
 With 30 g of oil, 108 g of chicken breast, 120 g of salad, 6 g of margarine and 30 g of rye bread4 65 ± 38 105 ± 59
Sava (47) Boiled, stored cold for 24 h, served cold 89 ± 433 119 ± 61 13 (10 F, 3M)
 With 28 g of white vinegar and 8 g of olive oil 69 ± 403 89 ± 54
1

Dashes indicate unmeasured or unreported values, although a graphic representation may be available. Values are based on test meals containing 50 g of available carbohydrate and tested on healthy participants. F, female; M, male.

2

Values based on a glucose reference and are mean ± SD; any reported SEM values were converted to SD values for consistency. Classification of the glycemic index (48): low, <55; intermediate, 55–69; high, 70–100.

3

Divided by 1.4 to convert the values from a white bread reference index to glucose reference (99).

4

Meal provides ∼54 g of carbohydrate instead of 50 g, and 272 g of mashed potato were used instead of the 362 g used for other meals.

The GI is based on 50 g of available carbohydrate in the food. However, the amount of different foods required to provide the 50 g of available carbohydrates for GI determination varies greatly. For example, 225 g of potato but only 175 g of cooked rice, 165 g of cooked pasta, or 115 g of wheat bread (62) are needed to meet this level of available carbohydrates. The recommended serving sizes of potato, rice, pasta, and wheat bread, according to the USDA, are 105, 94, 70, and 28 g, respectively, which provide 23, 27, 22, and 12 g of available carbohydrate, respectively (62). Thus, to consume the required amount for GI determination, one would need to consume a larger amount (more than twice the recommended serving size in the case of potato) of food than the usual serving size. Therefore, as has been noted by Venn et al. (33), it is the measurement of the glycemic response to ad libitum meals, representing realistic consumption patterns and serving sizes, that is required if the goal is to provide dietary advice for reducing postmeal glucose excursions.

In addition to serving sizes not being considered in judging the glycemic impact of foods, the satiety value has not been considered. The lone consumption of boiled potato, pasta, and rice results in GI values of 65–91, 43–55, and 60–86, respectively and SI values of 323, 119, and 138, respectively (Table 4). It was expected that the addition of 50 g of available carbohydrate from the stated carbohydrate sources to a fixed portion (150 g) of pork would result in a similar ranking of the glycemic effect of potatoes (relative to rice and pasta) as predicted by their GI. However, this does not take into account the satiety value of these foods when consumed ad libitum with the pork (Table 6) (63). Although total meal weight was similar for all meals, the energy consumed at the potato meal was 31% and 23% lower compared with the pasta and rice meals, respectively, reflecting the satiating value of potatoes, although postmeal satiety was shorter lasting after the potato meal (63). Additionally, no differences among the treatments were found in food intake at an ad libitum meal served 4 h later; thus, the potato meal resulted in the lowest cumulative food intake over the study period. The consumption of the potato meal also resulted in lower levels of plasma insulin compared with the rice and pasta meals (Fig. 1), which is consistent with the lower carbohydrate intake. Thus, taken in isolation as a physiological characterization of the carbohydrate in foods, the GI is misleading as it undermines the functionality of the potato as a contributor to satiation in a meal.

Table 6.

Effects of consuming potato, pasta, or rice ad libitum with 150 g of pork1

Test meal Energy intake, first meal Energy intake, second meal
kJ
White pasta + pork steak 2829 ± 240 3305 ± 1804
White rice + pork steak 3174 ± 628 3746 ± 1098
Potato + pork steak 2177 ± 270* 3768 ± 1189
1

Values shown are mean ± SD (n = 11); reported SEM values were converted to SD values for consistency.

Adapted from (63) with permission.

*

Significant difference compared with pasta and rice meals.

Figure 1.

Figure 1

Change from baseline plasma glucose and insulin concentrations after consumption of a meal including ad libitum boiled potato, pasta, or rice, each served with a fixed 150-g portion of pork. M denotes the start of the test meals and S refers to the start of ad libitum sandwich meal provided 3 h later. n = 11 males. Values are mean ± SEM. Adapted from (63) with permission.

Functional components in white vegetables that contribute to regulation of food intake and metabolism

Members of the white vegetables category contain various functional components of interest to food intake and metabolic control, which may provide additional reasons to include them in the diet. However, the research is preliminary, and application is currently unclear. This aspect of white vegetables is reviewed briefly in the following.

Potatoes

Potatoes contain a protein inhibitor that inhibits trypsin’s proteolytic activity in the small intestine, which in turn extends the activity of the peptide satiety hormone CCK (6466). This inhibitor is often referred to as protease inhibitor II (PI2) (65, 66), although the term trypsin inhibitor is also used (64). CCK levels are negatively controlled by trypsin and chymotrypsin; thus, the inhibition of trypsin by PI2 promotes elevated levels of circulating CCK. Indeed, the consumption of 1.5 g of PI2 in a high-protein soup vehicle results in increased CCK levels and decreased energy intake in human subjects (65). However, when only 30 mg of PI2 is consumed in a minidrink, no such differences in appetite, food intake, and plasma CCK and glucose levels were observed (67). These studies suggest that large amounts of PI2 are needed to have physiological effects. However, on average, potato juice only contains ∼584 μg/mL of PI2, which, when added together with 2 other protease inhibitors (inhibitor I and carboxypeptidase inhibitor) makes up only 7% of the total soluble proteins present (68). Although the amount of PI2 in potatoes is significant, the potato may contain various other proteins that mask the function of PI2, and thus its function may be more apparent when extracted.

Onions

Onions (Allium cepa L.) have hypoglycemic properties and may have potential in diets for management of diabetes. This is based on the fact that onions are rich in dietary flavonoids (69). Although onions contain at least 25 different flavonoids, quercetin is one of the most important (69). It is not only the most common flavonoid in foods, but it has also been found to decrease oxidative stress and thus improve the diabetic status of those consuming it (69). Indeed onions, consumed as an extract (6971) and powder (72), have been found to promote hypoglycemia in streptozotocin (STZ)-induced diabetic Sprague-Dawley rats and alloxan-induced diabetic rabbits (6972). These hypoglycemic effects were correlated with increased expression of insulin receptors and GLUT4 transporters, as measured by quantitative reverse transcription PCR, in a STZ-induced diabetic rat model (69). However, high dietary fat was found to weaken the hypoglycemic effect of dietary onion in similarly induced diabetic rats (73), although the hypoglycemic effects remained when onion peel extracts were given to rats along with high-fat diets (69).

Clinical studies in humans also provide some evidence of the hypoglycemic properties of onions. In healthy adult subjects, the consumption of isolated allyl propyl disulfide from onions decreased blood glucose levels and increases insulin levels after 4 h of rest compared with a fasted baseline measurement (74). A hypoglycemic effect of onion fractions has also been observed in diabetic patients (71), suggesting that this vegetable does indeed have hypoglycemic properties and may potentially be used to manage diabetes.

Garlic

Based on currently available studies, garlic may contribute to insulin and glucose control (7578). In STZ-induced diabetic Wistar rats, the consumption of garlic oil and diallyl trisulfide, an aromatic compound found in garlic, by gavage resulted in lower plasma insulin and improved oral glucose tolerance test results (77), although this effect was not observed for the isolated garlic oil compound diallyl disulfide (75). Similar hypoglycemic effects of garlic have been observed in Sprague-Dawley rats fed a high-fructose diet consisting of a homogenized paste of 65% fructose and raw garlic (78). However, this effect was observed after only 4 wk of treatment in STZ-induced diabetic Wistar rats (75) and after 8 wk in fructose-induced insulin-resistant Sprague-Dawley rats (79).

One study showed that the effect achieved by the administration of an ethanol-based garlic extract through an orogastric tube is greater than antidiabetic drugs such as glibenclamide in STZ-induced diabetic Wistar rats (80). This, in turn, may be due to the diallyl trisulfide content of garlic, as discussed previously (77). In addition to the beneficial hypoglycemic properties of garlic, studies have also found that its consumption ameliorates fructose-induced weight gain in Sprague-Dawley rats (78, 81). There is, however, only 1 report on the glycemic effects of garlic in humans. The combined consumption of garlic tablets with the antidiabetic drug metformin, was found to lower blood glucose levels to a greater extent than metformin alone plus a placebo tablet in patients with type 2 diabetes (82). This is consistent with results observed previously in STZ-induced diabetic Wistar rats (80). Therefore, further examination of the use of garlic for its hypoglycemic and weight-management properties appears justified.

Ginger

Human studies on ginger (Zingiber officinale) indicate that it has no effect on blood glucose, insulin, lipids (83), or hormones including GLP-1, motilin, and ghrelin (84). However, it may have more positive benefits in controlling appetite and food intake. For example, when ginger was consumed as a beverage, satiety, measured via visual analogue scales, increased over a 6-h period (83); however, when ingested in tablet form preceding consumption of a low-nutrient soup, ginger increased gastric emptying rate but did not affect satiety (84). On the other hand, animal studies show that both the aqueous extract of raw ginger (85) and a specific component of ginger, [6]-gingerol (86), reduce fasting blood glucose and increase insulin levels in alloxan-induced diabetic and insulin-resistant rats (85) and in sodium arsenite–induced diabetic Swiss albino mice, whose insulin signaling is impaired through stress processes caused by sodium arsenite (86). In both cases, the authors attributed these observations to the action of the oxygen radical scavengers malonydealdehyde (85) and [6]-gingerol (86). Additionally, it was found that when Wistar rats fed high-fat diets were treated with an ethanolic extract of ginger, the development of parameters of metabolic syndrome, including increased body weight, serum glucose, insulin, and lipids, was significantly reduced (87). Therefore, although animal studies point to ginger as a potential treatment for diabetes and metabolic syndrome, human studies to date show otherwise. Additionally, in humans, ginger consumption may have a role in appetite control.

Mushrooms

Mushroom consumption affects body weight, satiety, insulin, and glucose control in experimental animals, but these effects are species dependent. For example, neither body weight gain nor food intake was affected by Bunashimeji mushroom powder in C57BL/6J mice (88) or Agaricus bisporus fiber in F344/DuCrj rats (89). However, including Shiitake, Hiratake, Eringi, and Hatakeshimeji mushroom powders (90) and the lectin component of Pleurotus ostreatus mushroom (91) in the diets of Sprague-Dawley rats (90) and Wistar rats (91), respectively, resulted in decreased food intake and body weight. This may be explained in part by the low energy density of the mushroom preparations. Normal weight, overweight, and obese adults who substituted low energy-dense white button mushrooms for high energy-dense foods, such as beef, reduced energy and fat intake while maintaining the same level of palatability, appetite, and satiety (92).

Improved glucose control has been observed after consumption of mushrooms and their coconsumption with substances such as vanadium (93), gliclazide, and metformin (94). The combination of both mushrooms and antidiabetic drugs improved the insulin status of alloxan-induced diabetic Kunming mice (93) and type 2 diabetic adults (94). In addition, mushroom species may be an important factor. For example, the glycoprotein fraction (SX fraction) of Maitake mushroom (95), Mukitake mushroom powder (96), and aqueous extracts of Agaricus blazei (97) and Cordyceps militaris (98) mushrooms all resulted in lower blood glucose concentrations in spontaneously hypertensive rats (95), hyperphagic db/db mice (96), STZ-induced diabetic Sprague-Dawley rats (97), and 90% pancreatectomized Sprague-Dawley rats (98), respectively. However, whereas Agaricus blazei (97) increased plasma insulin levels, Maitake (95) and Mukitake (96) mushrooms increased insulin sensitivity. Thus, mushrooms may contribute to blood glucose and satiety control, the mechanisms of which are dependent on the mushroom species consumed.

Conclusion

This review examined the question “what weight should be placed on GI or postmeal glycemia in vegetables that have high nutrient-to-energy density ratios, are low in energy density compared with other mealtime carbohydrate sources, and within a meal contribute to early satiation and lower food intake?” The observed results support the hypothesis that, when applied to potatoes, the GI has led to premature and possibly counterproductive dietary guidance and that post ad libitum meal responses are the better measure for dietary guidance.

Both GI and SI measured in standardized conditions in the laboratory have contributed to an understanding of the physiological functionality of carbohydrates. However, application of these measures in isolation, to judge the role of white vegetables in the diet and for dietary guidance, is inappropriate. The application of GI and SI should thus be in the context of the overall contribution that a carbohydrate source makes to the nutrient composition of the diet and to satiety and metabolic control in meals. The nutrient, satiety, and glycemic benefits of potatoes and other white vegetables in usual eating patterns require thorough examination and cannot be judged by the GI or postmeal glycemic effects alone. Therefore, further research is needed before the dietary relevance of the GI or postmeal glycemic responses of white vegetables can be judged in the context of ad libitum meals containing usual serving sizes.

Acknowledgments

All authors have read and approved the final manuscript.

Footnotes

3

Abbreviations used: CCK, cholecystokinin; GI, glycemic index; GIP, gastric inhibitory polypeptide; GLP-1, glucagon-like peptide 1; PI2, protease inhibitor II; SI, satiety index; STZ, streptozotocin

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