consumption of sugars

178S Am J C/in Nutr 1995;62(suppl):178S-94S. Printed in USA. © 1995 American Society for Clinical Nutrition

Consumption of sugars1’2

Michael Gibnev, Madeleine Sigman-G rant, John L Stanton Jr, and Debra R Keast

ABSTRACT The mean percent of energy from total sugarsminus lactose is 18% in the United States, according to data from

the 1987-1988 US Department of Agriculture Nationwide Food

Consumption Survey. When sugars intake is distributed among

food pyramid groupings, the primary contributor is the “others”group (39%). The relationship between sugars intakes and micro-

nutrients was age and sex dependent. Consumers of high amounts

of sugars do not necessarily have poorer quality diets. In theEuropean Union, the mean percent energy from all sugars is

15.2%. The top five sources of sugar contributed 68% of sugarintake but only 11% of fat intake (UK data). Although sugars

intake varies among these major developed regions, the consistentinverse relation between fat and sugars intake and the scarcity of

individuals achieving dietary guidelines raises serious questions

regarding current dietary recommendations. Am J Clin Nutr

1995;62(suppl): 178S-94S.

KEY WORDS Sugar consumption, dietary intake, diet

surveys, nutrient intake

INTRODUCTION

Information on the consumption of any food or food com-ponent is dependent on both the sources from which the dataare obtained and the applicability of the information to thegeneral population. There are two primary methods for esti-

mating food consumption: conducting surveys of household

food consumption and individual food intake and using fooddisappearance data for per capita availability estimates (1).Each method has its own inherent limitations and introduces

potential bias for further interpretation and application. Theinformation presented in this chapter represents sugars intakefor the United States and the European Union from individual

food-consumption surveys.Although several problems have been associated with self-

reported food intake records, the primary concern relates to the

underreporting of foods by individuals (2-5) or for children bytheir parents (6). Of particular concern for dietary recalls are

the types of foods that are underreported. In a recent study,

Beerman and Dittus (5) demonstrated that foods less central to

the meal are significantly underreported. Side dishes (eg, po-tatoes, rice, vegetables, soups, fruit, salads, breads, and rolls)and condiments (eg, salad dressings, mayonnaise, croutons,gravy, margarine, and ketchup) are the foods less accurately

recalled.Comparison between studies using self-reported food intake

records is often difficult. Databases used to analyze nutrient

content may have limited product on recipe information or mayhave been updated on otherwise changed, making comparisons

oven time on between studies less meaningful. How informationis obtained (ie, food frequency, 24-h recall, or 3-7-d food

records) (2), differences in grouping of foods for analysis (7),response rates to surveys (8, 9), and interviewing and coding

procedures (7, 9) can affect the size of the contribution or theapparent amount of consumption of any nutrient or class ofnutrients.

SUGARS CONSUMPTION IN THE UNITED STATES

Intakes of sugars (mono- and disaccharides) in the United

States obtained from the 1987-1988 US Department of Agri-culture (USDA) Nationwide Food Consumption Survey(NFCS), comparison of sugars intake estimates from the 1977-1978 NFCS and the 1987-1988 NFCS, food sources of sugars

from the 1987-1988 NFCS, and nutrient intake in relation tovarious sugars intakes will be addressed.

Methods

The 1987-1988 NFCS data are the most current analyzedsource of information available on food intake in a nationwidesample of Americans. This database was selected and recentconcerns regarding its use, principally the rate of nonresponse,were taken into consideration (8, 10). The response rate of allhouseholds contacted in the 1987-1988 NFCS was 38% at thehousehold level and, at the individual level, 31% for 1-d and26% for 3-d records (9, 11). By comparison, 72% of house-

holds contacted in the 1977-1978 NFCS completed the house-hold questionnaire and, at the individual level, the responserates were 68% and 61% for 1-d and 3-d records, respectively(12, 13). The lower the participation rate, the greater the

potential for nonparticipation bias and the lower the potential

applicability to the general public. Other concerns regardingthe 1987-1988 survey include changes in interviewing, weightconversion, and food coding procedures along with changes inclassification of foods into groups and within the nutrient

1 From the Division of Nutritional Sciences, Department of Clinical

Medicine, Trinity College Medical School, St James’ Hospital, Dublin; the

Department of Food Science, Pennsylvania State University, University

Park; and St Joseph’s University, Philadelphia.

2 Address reprint requests to M Gibney, Division of Nutritional Sci-

ences, Department of Clinical Medicine, Trinity College Medical School,

St James’ Hospital, Dublin 8, Ireland, and to M Sigman-Grant, Departmentof Food Science, Pennsylvania State University, 203 Borland Laboratory,

University Park, PA 16802.

by guest on August 5, 2015

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CONSUMPTION OF SUGARS 179S

database. Additionally, the degree of respondent burden was

questioned.

Several reviews were conducted to determine the conse-

quences of these concerns (8-10, 14). The Human Nutrition

Information Service conducted a study to determine whetherdifferences in methodology and nutrient databases affectedestimated food and nutrient intakes (14). The Life SciencesResearch Office expert panel (8), the Human Nutrition Infor-mation Service (9), and the US General Accounting Office (10)investigated the nonresponse issue. Both the Life Sciences

Research Office and the General Accounting Office concludedthat it is not possible to determine whether nonnespondentswould have systematically differed from respondents. The LifeSciences Research Office report also expressed concern aboutthe estimates of intakes of small subgroups of people. Guenther

and Tippett (9) demonstrated that differences between respon-dents and nonnespondents were not caused by some unknown,nonrandom, unpredictable “response propensity.” Differencesin eating behavior results were caused by known socioeco-nomic variables that could be adjusted for by weighting or

accounted for by differences in methodology, design, andtarget samples.

Guenther et al (14) found that changes in interview and

coding procedures had little effect on estimates of nutrientvalue. However, weight conversion changes and improvements

in the quality of the database did affect values for iron, mag-nesium, vitamin B-6, and vitamin B-12. Adjusted values for

these nutrients were recently published (14). Generally, effects

of survey procedure changes were slight and tended to offseteach other.

The NFCS database provides detailed descriptions of foodsand quantities consumed. Food intake data for individuals from

the 4273 households responding to the 1987-1988 NFCS were

used (Table 1). Records for pregnant and lactating women andfor breast-fed infants were excluded and only records contain-ing 3 d of food intake data were used, resulting in records from

8296 persons of all ages and both sexes. Each of the 3 d ofrecords for each person, rather than the average of 3 d, wasmaintained and analyzed as a separate record. Comparisonswere made with estimates presented in the Food and Drug

Administration 1986 Sugars Task Force report (1) that assessed

the then-current sugars intake from food consumption patternsrecorded in the 1977-1978 USDA NFCS, which contains1-, 2-, or 3-d records for > 30 000 individuals (see Table 1).

To obtain individual sugar intakes for NFCS sample persons,sugar composition values for the 4283 food items reported inthe 1987-1988 NFCS first needed to be appended. The gram

amounts of mono- and disaccharides per 100 g were calculatedfor each food code in the nutrient database. Individual fooditems were entered into the Minnesota Nutrition Data System(software version 2.2; Nutrition Coordinating Center, Univer-sity of Minnesota). Recipe calculations were performed and

results were merged with the 1987-1988 NFCS nutrient com-position file. The resultant sugars database contains values forsucrose, galactose, glucose, fructose, and lactose, the sum ofwhich is called total sugars.

In this database, naturally occurring sugars and sugars added

to foods are not distinguished. Total sugars from all foodsources are included. Most lactose consumed in 1987-1988reflects consumption of milk and milk-containing foods.Fructose in this current analysis includes both fructose from

TABLE 1Age and sex groupings for the sugars analyses of the 1977-1978 and

1987-1988 US Department of Agriculture Nationwide Food

Consumption Survey’

Samp Ic size

Percentage of

representation

1977-1978 1987_19882 1977-l978� 1987-1988

%

Both sexes

< 1 y 465� 100 1.5 1.2

1-3 y 1716 402 5.6 4.8

4-6 y 1947 446 6.3 5.4

7-10 y 2788 538 9.1 6.5

Males

11-14y 1592 221 5.2 2.7

15-18 y 1510 216 4.9 2.6

19-22 y 738 182 2.4 2.2

23-50 y 3792 1537 12.4 18.5

�51 y 2677 942 8.7 11.4

Females

11-14y 1591 249 5.2 3.0

15-18 y 1596 240 5.2 2.9

19-22 y 922 190 3.0 2.3

23-50 y 5220 1771 17.0 21.3

� 51 y 4113 1262 13.4 15.2

Total 30667 8296 100.0 100.0‘ Age and sex groupings from Recommended Dietary Allowances (15).

2 Includes only individuals providing 3 d of records. Excludes breast-fed

infants of all ages. Excludes pregnant and lactating women.

3 Excludes breast-fed infants.

4 May not equal 100% because of rounding.

naturally occurring fruit, fruit juices, and concentrates, and

from high-fructose corn syrup added to processed foods.It is increasingly difficult to distinguish between natural and

added sources of sugars because of advances in ingredient

technology. Use of high-fructose corn syrups, crystalline fruc-tose, glucose syrups, and sugar alcohols for bulking and sweet-ening during manufacturing (16) is rapidly creating a morecomplex food supply. Additionally, lactose, in the form ofhydrolyzed lactose syrup, whey protein concentrate, and wheypermeate, is being used in confectionery and baked goods as asubstitute for nonfat dry milk solids and sucrose (17). Thesechanges raise questions for consumers regarding traditionalclassification schemes. Fruit juice concentrates added to jams,

yogurt, frozen desserts, cereals, cookies, and other baked prod-ucts are considered added sugars (18). However, consumersfrequently consider fruit juices and fructose to be naturally

occurring sugars. The establishment of reasonable consump-tion guidelines is impeded and the use of existing guidelines isprevented by such complications in classification. In 1977 the

US Select Committee on Nutrition and Human Needs (19)suggested that added sugars be consumed at � 10% of totalenergy intake. However, this criterion is not assessed in thisanalysis of estimates of intakes of total sugars. The classifica-tion of natural on added sugars is not feasible on necessarybecause they are indistinguishable with regard to chemical food

composition analysis on physiologic metabolism.Daily sugars intakes of survey respondents were calculated

from the weight (in grams) of food items consumed and the

respective sugar composition value. Respondents were grouped


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180S GIBNEY ET AL

TABLE 2Sugars analysis of the 1977-1978’ and 1987_19882 US Department of Agriculture Nationwide Food Consumption Surveys’

Average daily intake Perce ntage of energ y intake 90th Percentile

Total sugars Total sugars Total sugars

Total minus Total Total minus Total Total minus Total

Group3 sugars

gid

lactose

gid

fructose

gid

Energy

Mi (kcal)

sugars lactose

%

fructose sugars

gid

lactose

gid

fructose

gid

Energy

Mi (kcal)Both sexes4

<ly

1977(n = 465)� 62 31 8 3.29(787) 32 15 4 93 65 16 4.64(1110)

1987 (ii = 100) 65 29 7 3.21 (768) 35 14 3.3 103 71 21 5.08 (1214)

1-3 y

1977(n = 1716) 82 63 13 5.30(1266) 26 20 4 128 110 25 7.36(1759)

1987(n = 402) 76 55 14 4.91(1174) 26 19 4.8 136 105 30 7.12(1702)

4-6 y

1977 (n = 1947) 99 79 16 6.48 (1548) 26 20 4 149 126 27 8.74 (2088)

1987 (n = 446) 96 73 16 6.12 (1464) 26 20 4.3 165 141 33 9.04 (2161)

7-10 y

1977 (n = 2788) 1 14 91 17 7.83 (1871) 24 19 4 168 142 30 10.48 (2505)

1987(n = 538) 112 86 19 7.39(1765) 25 20 4.4 181 151 37 10.88 (2601)

Males

11-14 y

1977 (n = 1592) 133 106 20 9.42 (2252) 23 19 4 205 173 35 13.17 (3148)

1987 (n = 221) 139 1 11 25 9.18 (2195) 25 20 4.6 240 199 50 13.81 (3301)

15-18 y

1977 (n = 1510) 143 1 16 24 10.79 (2578) 22 18 4 230 193 43 15.50 (3705)

1987 (n = 216) 139 1 13 29 9.70 (2319) 23 19 4.9 235 216 58 14.33 (3424)

19-22 y

1977 (n = 738) 121 102 23 10.05 (2403) 20 17 4 201 171 42 14.86 (3551)

1987 (n = 182) 121 103 29 9.34 (2232) 22 19 5.4 221 208 61 14.73 (3520)

23-50 y

1977 (n = 3792) 105 92 19 9.75 (2330) 18 16 3 177 159 36 13.90 (3321)

1987 (n = 1537) 105 90 23 8.95 (2140) 20 17 4.5 190 169 49 13.78 (3294)

> 50 y

1977 (n = 2677) 92 80 14 8.54 (2042) 18 16 3 159 140 27 12.32 (2945)

1987 (n = 942) 91 76 18 7.94 (1897) 19 16 3.8 166 147 37 12.00 (2867)

Females611-14 y

1977 (n = 1591) 1 12 92 18 7.77 (1856) 24 20 4 174 147 32 10.66 (2548)

1987 (n = 249) 106 87 22 7.39 (1767) 24 20 5 179 156 46 11.43 (2731)

15-18 y

1977 (n = 1596) 103 87 19 7.31 (1746) 24 20 4 167 146 35 10.42 (2491)

1987(n = 240) 103 84 21 6.97(1667) 25 21 5.3 176 145 40 10.63 (2542)

19-22 y

1977 (n = 922) 86 75 18 6.69 (1600) 22 19 4 141 129 34 9.80 (2343)

1987 (n = 190) 91 78 18 6.32 (151 1) 24 21 5 166 150 40 9.66 (2308)

23-50 y

1977 (n = 5220) 78 69 15 6.48 (1548) 20 18 4 133 1 19 28 9.46 (2261)

1987 (n = 1771) 79 68 17 6.14 (1467) 22 19 4.7 149 135 37 9.71 (2322)

> 50 y

1977 (n = 4113) 74 64 12 6.15 (1470) 20 17 3 124 110 23 8.80 (2103)

1987(n = 1262) 74 62 15 5.85(1398) 21 18 4.6 133 116 33 8.76(2094)

Total

1977 (n = 30 677) 95 80 16 7.60 (1817) 21 18 4 160 139 31 1 1.53 (2756)

1987(n = 8296) 94 78 19 7.22(1726) 22 18 4.6 172 151 41 11.59 (2771)

I From Glinsmann ci al (1).

2 Includes data only from individuals providing 3 d of records.

3 Age and sex groupings from Recommended Dietary Allowances (15).

4 Data for 1987-1988 survey exclude breast-fed infants of all ages.

5 Excludes breast-fed infants.6 Data for 1987-1988 survey exclude pregnant and lactating women.


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TABLE 3Fructose ratios in the 1977-1978’ and 1987_19882 US Department of Agriculture Nationwide Food Consumption Surveys

Group3

Ratio of mean fructose

to total sugars (g)

(g)

Ratio of mean fructose (g)

to total sugars minus

lactose (g)

Ratio of mean glucose (g)

to mean fructose (g)

1977 1987 1977 1987 1977 1987

Both sexes4

< 1 y5 0.13 0.11 0.26 0.24 2.1 1.0

1-3 y 0.16 0.19 0.21 0.26 1.5 0.9

4-6y 0.16 0.17 0.20 0.22 1.5 1.1

7-10 y 0.15 0.17 0.19 0.22 1.4 1.1

Males

11-14y 0.15 0.18 0.19 0.22 1.4 1.1

15-18 y 0.17 0.21 0.21 0.26 1.4 1.1

19-22 y 0.19 0.24 0.23 0.28 1.4 1.1

23-50 y 0.18 0.22 0.21 0.25 1.3 1.0

�50y 0.15 0.19 0.18 0.23 1.4 1.0

Females6

11-14 y 0.16 0.20 0.20 0.25 1.4 1.0

15-18 y 0.18 0.20 0.22 0.25 1.4 1.1

19-22 y 0.21 0.20 0.24 0.23 1.3 1.0

23-50 y 0.19 0.21 0.22 0.24 1.3 1.0

�50y 0.16 0.21 0.19 0.25 1.4 1.0

Total 0.17 0.20 0.20 0.24 1.4 1.0

‘ From Glinsmann et al (1) and Park and Yetley (25).2 Compiled from 1987-1988 US Department of Agriculture Nationwide Food Consumption Survey (NFCS). Includes only individuals providing 3 d of

CONSUMPTION OF SUGARS 1815

records.

3 Age and sex groupings from Recommended Dietary Allowances (15).

4 Excludes breast-fed infants of all ages in 1987-1988 NFCS.

5 Excludes breast-fed infants in 1977-1978 NFCS.6 Excludes pregnant and lactating women in 1987-1988 NFCS.

according to the age and sex categories of the 1980 recom-

mended dietary allowances (RDAs) (15). Percentage changesfrom estimates presented in the 1986 Sugars Task Force report

(1) were calculated to compare the mean intake of total sugars,

total sugars minus lactose, and fructose (data not shown).After total sugars intake was analyzed, foods were classified

into the following USDA food guide pyramid groupings:bread, cereal, pasta, and rice (grains); vegetables and vegetable

juices; fruit and fruit juices; milk and milk products (including

cheese, yogurt, pudding, and ice cream); meat, fish, poultry,dried beans and lentils, and nuts (including peanut butter); and

others (20). The “others” group includes added fats, oils, dress-ings, sauces, sweet table accompaniments (sugar, honey, syr-ups, jelly, jams, toppings, frostings, etc), other table accompa-

niments (ie, mustard, relish, and ketchup), fruit drinks andfruitades, carbonated drinks, chewing gum, and candies. Cakes,cookies, pies, and pastries are included in the bread, cereal,pasta, and rice grouping (20). It was necessary to accommodatefor consumption of combination dishes such as pizza, sand-wiches, and salads. Except for peanut butter in sandwiches, the

primary component for sugars in these dishes was found in thegrain and not the meat portion. Therefore, all combination

foods except for peanut butter sandwiches were included in thebread, cereal, pasta, and rice grouping.

For nutrient intake analyses, three categories (high, moder-

ate, and low) were selected to reflect levels of sugars consump-tion in each age and sex grouping of 1987-1988 NFCS respon-dents. Total sugars minus lactose intake per 4.18 MJ, on 1000

kcal, (sugar density) was calculated for each day for each

individual. Percentiles of the sugar density distribution were

found such that low consumers (those in the lowest quartile)

had sugar densities < 26.4 g/4.18 Mi and high consumers

(those in the highest quartile) had sugar densities � 60.5 g/4.18

MJ. Moderate consumers fell between the 25th and the 75th

percentiles (between 26.5 and 60.5 g/4.18 MJ). For each sugar

intake category and each 1989 RDA age and sex category,

mean nutrient densities (amount of nutrient per 4. 18 Mi) were

calculated for protein, vitamin A (as netinol equivalents), vita-

mm E, vitamin C, thiamin, niacin, riboflavin, vitamin B-6,

vitamin B-12, folate, calcium, iron, and zinc (21). Categories

were compared for the following nutrient intake measures:

percentages below two-thirds of the RDA for the listed micro-nutrients and below 100% of the RDA for energy, percentages

below the carbohydrate and fiber dietary guidelines, and per-

centages exceeding the dietary guidelines for total fat, saturated

fat, cholesterol, and sodium. Differences across categories

were calculated for each age and sex group with a one-way

analysis of variance and a series of Student-Newman-Keuls

range tests. The statistical package used for the analysis was

SPSS release 4.0 (SPSS Inc, Chicago) for a Sun-4 computer

and a UNIX operating system. The USDA-calculated sampling

weight was applied for statistical analysis; however, the

weights were brought back to scale to reflect the actual number

of cases by dividing the respondent’s sampling weight by the

mean sampling weight for the group.


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Dothe:

U Meai� Fish, Poultry. Eggs. Nuts,

Beans

U Milk. Yogurt, Cheese, etc.

D Fruit and Fruit Juices

0 Vegetables and Vegetables Juices

IEIBread, ce:�l. Rice & Pasta (includes

cookies. cakes and pasuies)

0

l-3y 4-6y 7-lOy

D Other

U Meat, Fish, Poultry, Eggs,

Nuts, Beans

I Milk, Yogurt, cheese, etc.

� Fruit and Fruit Juices

0 Vegetables and Vegetables Juices

III Bread, Cereal, Rice & Pasta

(includes cookies, cakes and

pastries)

Male Female Male Female Male Female Male Female Male Female

ll-l4y lS.l8y l9-24y 25-SOy 5O+y

182S GIBNEY ET AL

FIGURE 2. Contribution of food groups to total sugars intake for Americans aged � 1 1 y. (See Note in Figure 1 legend.)

I.41

A1

100

90

80

70

60

50

40

30

20

10

Age

FIGURE 1. Contribution of food groups to total sugars intake for American children (males and females combined) aged 1-10 y. Note: based on gram

food consumption data from the 1987-1988 US Department of Agriculture (USDA) Nationwide Food Consumption Survey analyzed with sugar

contribution calculated from composition values determined from the Nutrient Data System developed by the Nutrition Coordinating Center, University

of Minnesota. Food groupings based on categories described by USDA (20). Numbers superimposed on bars indicate the mean daily intake (g) of total

sugars contributed by each food group. Bar heights are calculated from the pooled percentage of total sample intake of total sugars for each food group.

Individual sugars intake

The daily intake (mean and 90th percentile) and the percentof energy intake of total sugars, total sugars minus lactose, total

41

,�

41

100

90

80

70

60

50

40

30

20

10

0

Age

fructose, and food energy from the 1986 Sugars Task Force

report (the 1977-1978 USDA NFCS) (1) and the 1987-1988

USDA NFCS are presented in Table 2. Fructose ratio analyses


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1.3 years 44 years 7.10 years

Age

11.14y 15.lSy 19.24y 25-SOy 50+y

Age

Age


60

50

40

a.

I.aa

a.

20

10

O Candy & Gum

a� Miscellaneous Foods

FIGURE 3. Contribution of food from the others food group category

to total sugars consumption in the following age and sex groups in the

United States: A, children aged 1-10 y; B, males aged � 11 y; C, females

aged � 11 y. Miscellaneous foods include added fats, oils, dressings,

sauces, sweet table accompaniments (sugar, honey, syrups, jelly, jams,

toppings, frostings, etc) and other table accompaniments (eg, mustard,

relish, and ketchup). (See Note in Figure 1 legend.)

in the two surveys are shown in Table 3. For the population as

a whole, the mean consumption of total sugars (in grams) and

of total sugars minus lactose (in grams) decreased slightly,

whereas mean fructose intake (in grams) increased by > 18%.

There was a decrease in mean energy intake of 5% for the total

population accompanied by a decrease in fat intake from 84.1g in 1977-1978 to 71.4 g in 1987-1988. The decrease in fat

consumption accounts for the decrease in energy values and is

reflected in the decrease in fat as a percent of energy (from

40.1% to 36.3%). A concomitant increase in the percent of

energy from total sugars, total sugars minus lactose, and totalfructose has occurred. However, there was no change in the

90th percentile of energy intake between the two surveys,whereas there was an increase in the 90th percentile of total

sugars and total sugars minus lactose.

The values for energy intake in both the 1977-1978 and the1987-1988 USDA NFCSs suggest underreporting compared

with the RDAS for energy (15). For example, for women aged

19-22 y, mean energy intakes were 6.3 MJ (1511 kcal) corn-

pared with the RDA of 9.2 MJ (2200 kcal). If underreporting of

food consumption occurred, estimates presented for all micro-and macnonutnients, including sugars, could be lower than truevalues. It is difficult to predict which nutrients might be most

affected by underreporting, although, as stated above, certainfoods consumed as side dishes and accompaniments to mealsappear to be most frequently underreported (5).

Comparison of our results with other studies that reportintake of sugars is difficult because of differing age classifica-

tions, especially for children. Morgan and Zabik (22) reported

an average daily total sugars intake of 134.3 g for children aged

5-12 y. Albentson et al (23) reported decreases between 1978

and 1988 in energy intake, total sugars intake, and contribution

of sugars to total energy (1.2%, 10.2%, and 8.7%, respectively)for children aged 2-10 y. For 10-y-old children in the Bogalusa

Heart Study (24), an average energy intake of 9.31 MJ (2224kcal) in 1987-1988 was reported compared with 9.69 MJ (2316kcal) in 1976-1977 and 8.97 MJ (2145 kcal) in 1978-1979.

Average total consumption of sugars was reported to be 155 g

in 1976-1977, 134 g in 1978-1979, and 160 g in 1987-1988,

with a steady decrease in intake of sucrose (104 to 74 g), arelatively stable intake of lactose (28 to 26 g), and a highly

significant increase (P < 0.0001) in fructose consumption(from ‘�‘6 to 25 g). In the current analysis, average total sugarsintake by children aged 1-10 y decreased, although there wasan increase of �12% in total fructose intake for 7-10-y-old

children. When combined with the decrease in reported energyintake, there is an apparent increase of ‘�‘5% in the contribution

of sugars to total energy intake for this age group. There was asubstantial increase of 20% in the percent of energy fromfructose, with a 9% increase in mean fructose intake (g) for1-3-y-old children.

Food sources of sugars

Given the complexity of the American diet, either listing orranking sugar-containing foods might not accurately representsugars content. Therefore, as stated previously, foods were

placed into the USDA food guide pyramid groupings (20). AStudent’s t test was used to determine whether any sex differ-

ences existed for the mean percent of total daily gram intake of

sugars from each food group (data not shown). There were few

sex differences for children aged 1-10 y; therefore, data were


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184S GIBNEY ET AL

TABLE 4Daily mean nutrient density by sugar category for American children aged 1-10 y’

Nutrient

1-3y 4-fly 7-lOy

Low Moderate High Low Moderate High Low Moderate High

Protein (g)

Thiamin (mg)

Niacin (mg NE)

Riboflavin (mg)

Folacin (!.Lg)

Vitamin B-6 (mg)

Vitamin B-12 (pg)

Vitamin C (mg)

Calcium (mg)

Iron (mg)

Zinc (mg)

Vitamin A (RE)

Vitamin E (mg TE)

Total fat (g)

Saturated fat (g)

Carbohydrate (g)

Cholesterol (mg)

Fiber (g)

Sodium (mg)

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0.91

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151”

6.5

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0.8825b

68.6c437C

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3.535C

13C

142C

125C

6.4

1452C

‘ Mean daily intake per 4.18 Mi (1000 kcal). Categories of sugar consumption were determined by calculating daily total sugars minus lactose intake

per 4.18 MJ (sugar density) and then placing into percentiles. “Low” is below the 25th percentile (< 26.4 g), “moderate” between the 25th and 75th

percentiles (26.4-60.5 g) and “high” greater than the 75th percentile (� 60.5 g). Data compiled from the 1987-1988 US Department of Agriculture

Nationwide Food Consumption Survey. Numbers with differing superscripts are significantly different (P � 0.05).

collapsed and are presented in Figure 1. However, sex differ-

ences for some food groups did occur for olden children,

adolescents, and adults (subjects aged from 1 1 to > 50 y).

Accordingly, the percentages for contribution of foods from thesix food groups for these age groups are presented for males

and females separately (Figure 2).Not surprisingly, the meat, fish, poultry, eggs, nuts, and

beans group and the vegetable group contributed very little tototal intake of sugars for the total population (1.4% and 3.5%,respectively), although the proportion of sugars from vegeta-

bles increased with age (to 5.5% for subjects aged > 50 y). For

children, dairy foods were a major contributor of sugar in the

form of lactose (30.8% for those 1-3-y old); however, the

contribution from lactose diminished with age (to “'16% for

males and females aged 19-50 y). Fruit are a significantcontributor of sugars (16.9% for the total population), partic-

ularly in the youngest (23.8% for children aged 1-3 y) andoldest (24.9% for males and females aged > 50 y) populations.

The contribution of grain products to total sugars intake for theentire population is 19.2%, of which more than half (9.9%)comes from cookies, pies, cakes, and pastries. The relative

proportion of sugars from these foods remains fairly steady

throughout life. Not surprisingly, the “others” group is a pni-many contributor of sugars (39.2% for the total population).

To delineate the contribution of specific foods within theothers category, this food group was further analyzed by sexand age (Figure 3). Overall, chewing gum and candy are minor

contributors. Children aged 1-10 y consume 9% of their sugars

intake in the form of fruit drinks. This represents a shift fromthe study in 1977 by Morgan and Zabik (22) in which, after

milk and milk desserts (25.9%), the major contributors ofsugars in the diets of children aged 5-12 y were fruit and juices

(20.3%); sweetened beverages (13.8%); cakes, cookies, pies, and

pastries (12.8%); and dessert sauces, jellies, syrup, and sugar

(12.3%). These food groups contribute 29.4%, 17.2%, 18.9%,

10.9%, and 7.6%, respectively, of total sugars consumed by chil-

dren aged 7-10 y in 1987-1988. The contribution of sweetened

beverages increased by 5.1% between the two studies. More

recently, Taylor and Koblinsky (26) reported that carbonated

drinks were replacing milk in the diets of homeless children and

were the major contributors of sugars for preschoolers aged 2-5 y.

It would be interesting to know whether differences in sugarsconsumption between 1978 and 1988 simply reflect shifts in

manufacturing practices and food composition or reflect

changes in consumer food selection. For American males, use

of carbonated drinks may account for much of the large in-

crease in total fructose intake (see Figure 3B). However, it ismore difficult to explain the changes in sugars intake forAmerican women aged 19-22 y. Total sugars and total sugarsminus lactose increased in this group (by 5.3% and 4.5%,respectively) but consumption of total fructose increased by

only 1.3%. Our analysis for women aged 19-24 y suggests thatthis group is consuming “'“17% of their total sugars from the

bread, cereal, rice, and pasta group (with 7.9% from cakes,

cookies, and pastries); “��‘3% from vegetables and vegetable

juices; “'‘12% from fruit and fruitjuices; “'1% from meat, fish,

poultry, beans, nuts, and eggs; 15% from dairy products; and

52% from the others group (with 1 1% from fruit drinks and

26% from carbonated drinks) (see Figures 2 and 3C; note:numbers superimposed on bans in figures indicate the mean

daily intake in grams of total sugars contributed by each food

group). When Lewis et al (27) examined food selection andsugars intake for this database, males and females were

grouped together and frequency of selection rather than size ofservings was considered. There are few other published data

that could be used to determine where specific changes oc-


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TABLE 7Percentage of American children aged 1-10 y consuming various amounts of sugars not meeting recommended dietary allowances or dietary

guidelines for selected nutrients’

Nutrient

1-3y 4-fly 7-bOy

Low Moderate HighLow Moderate High Low Moderate High

%Protein Ia o.la 2” 1a�� 0.3� 2b

0.4” 2”

Energy 72” 68” 61b85” 77”

73h 74 67 70

Thiamin 8a 4b 9ab6� 8b 8” 3�

7a15”

Niacin b4� 8b 16” 20” 7” 13C 8” 6” 14”

Riboflavin ia 3a 9b 6 5 6 4” 4” 1 1”

Folacin 3 2 2 4 3 5 4” �a11”

Vitamin B-6 22” 14b28”

18a.b 14” 20” 22”” 19” 28”

Vitamin B-b2 ia o.3a 6b2 2

4 3� 2a6”

Vitamin C 38” 23b 22b 46� 24b29#{176} 18” 21”

Calcium 27” 36b 49C 22” 22” 37” l5� 16” 33”

Iron 47” 35b 44a 33a 20b 18” 14” 11” 21”

Zinc 52” 54” 73” 34L’27” 22” 37”

Vitamin A 9� 1 ia 19b is 16 17 20� 19” 34”Vitamin E 64 63 65 61” 44” 590 38 36 42Total fat 92” 87� 42h 96” 87” 49C 93) 85” 67’�

Saturated fat 93” 92� 63b 96” 92� 68” 92” 89” 74”

Carbohydrate 96” 82b 25C 96” 84b 25C 971 82h 45C

Cholesterol 32” 21b �oc 31” 25b b3C 43a29” 20c

Fiber 98 99 99 96 96 97 87a.h88” 92”

Sodium 23 23 19 48” 49” 34” 65” M� 48”

‘ Data compiled from the 1987-1988 US Department of Agriculture Nationwide Food Consumption Survey. Based on 66.67% of the recommended

dietary allowances for proteins, vitamins, and minerals and 100% for energy (21) and on the following dietary guidelines (29): < 30% of energy from total

fat, < 10% from saturated fat, � 55% from carbohydrate, < 300 mg cholesterol, � 20 g fiber, and < 2400 mg sodium. Categories of sugar consumption

were determined by calculating daily total sugars minus lactose intake by 4.18 MJ (1000 kcal) (sugar density) and then placing into percentiles. “Low”

is below the 25th percentile (< 26.4 g), “moderate” between the 25th and 75th percentiles (26.4-60.5 g), and “high” greater than the 75th percentile

(� 60.5 g). Numbers with differing superscripts are significantly different (P � 0.05).

curred. Therefore, 1977-1978 and 1987-1988 food sources ofsugars are not compared.

Nutrient intakes

To address the questions of how amounts of sugars andsugar-containing foods could affect health, comparisons withestablished standards or guidelines should be made. Tradition-ally, dietary recommendations have been based on studiesestablishing an acute deficiency on toxicity state associatedwith the nutrient in question (21). More recently, recommen-dations, most notably for macnonutrients, have been based on

the existence of chronic disease states (28). There is a paucity

of such studies in relation to dietary consumption of sugars.The primary concern regarding high sugar consumption in the

United States is reflected in Dietary Guidelines for Americans

(29), which suggests use of sugars in moderation, stating thatsugars (and many foods containing them) supply energy but arelimited in nutrients. This nutrient dilution question appearsparticularly relevant for children and those segments of the

population consuming large amounts of sugars.Two separate analyses that used the total sugars minus

lactose values to classify daily intake by sugar intake groupswere performed to address the issues of nutrient quality anddilution. First, daily mean nutrient densities (amounts per 4.18Mi, or 1000 kcal) were calculated for sugar intake groups.

Second, sugar intake groups were compared by percentages notmeeting nutrient criteria (below two-thirds of the RDA formicronutnients; below 100% of the RDA for energy; or below

carbohydrate, below fiber, and exceeding fat, cholesterol, andsodium USDA dietary guidelines). To accommodate individu-

als consuming unusually small or large energy intakes, sugarintakes were normalized by calculating sugar densities as thetotal sugars minus lactose per 4.18 MJ. Records were grouped

into age and sex categories, three levels of sugar consumptionwere identified, and nutrient intake analyses were performed.

Micronutnient densities for most of the population consum-ing high amounts of sugar (� 60.5 g/4.18 MJ) tended to belower than for those consuming either moderate or low

amounts (Tables 4-6). One exception is vitamin C because of

its association with fruit drinks. The relation between sugar and

micronutnients is less consistent when daily intakes are exam-

med as a percent of the RDA (Tables 7-9). In fact, dependingon age and sex, a greaten proportion of those consuming lowamounts of sugars (< 26.4 g/4.18 Mi) did not meet at leasttwo-thirds of the RDA for some micronutnients compared withconsumers of moderate amounts of sugars. The nutrient densitymay be statistically significant but the percent of the RDA

measured is more relevant. Of particular importance is the

number of women in the two childbearing age groups (19-24and 25-50 y) who failed to meet dietary recommendations.

Even more importantly, a greaten proportion of the consum-ens of low amounts of sugars tended to consume > 30% ofenergy from fat, > 10% of energy from saturated and monoun-

saturated fatty acids, < 55% of energy from carbohydrates, and

> 300 mg cholesterol. These results agree with those of Lewiset al (27), who reported that respondents consuming moderate


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GIBNEY ET AL

TABLE 10

16.2 10.4

14.4 9.5

13.2 9.0

12.8 8.8

12.9 8.5

11.8 8.1

11.4 8.0

106 68 10.5

67 52 8.7

62 42 7.5

55 47 6.9

65 45 8.0

60 45 8.1

70 43 9.8

Belgium’

25-34 y

35-44 y

45-54 y

55-.64 y

65-74 y

Denmark2

15-24 y

25-34 y

35-44 y

45-54 y

55-64 y

65-74 y

75-80 y

Germany3

18-24 y

25-34 y

35-44 y

45-54 y

55-64 y

> 65 y

Ireland4

8-12 y

12-15 y

15-18 y

18-25 y

25-40 y

40-60 y

> 60 y

Netherlands5

10-15 y

16-21 y

22-49 y

50-64 y

> 65 y

Basque, Spain6

25-34 y

35-44 y

45-54 y

55-60 y

United Kingdom7

16-24 y

25-34 y

35-49 y

50-64 y

16.7

16.4

15.8

16.2

17.1

10.4

7.4

7.4

8.5

8.4

8.8

8.6

19.1

15.6

14.3

14.3

14.3

15.4

15.4

17.9

17.1

15.4

14.3

14.9

14.0

24.8

24.8

19.8

19.8

20.3

9.7

11.3

14.0

13.7

12.7

10.6

9.5

10.6

12.7

11.9

10.7

10.3

12.5

12.2

11.3

10.5

10.5

10.4

10.7

10.2

20.2

19.2

19.2

18.3

‘ n = 10 971; method = 24-h recall. The term “sugars” were not used in thisreport; the above data therefore represent the difference between “carbohydrates” and“polysaccharides.” From Komitzer and Dramai.x (33).

2 � 2242; method = 7-d diet history. Sugars defined as refined sugars. FromHaraldsdottir Ct al (34).

3 n = 21 012; method = 7-day food record. Sugars was defined separately asmono- and disaccharides, which were summed for this table. From VERA (35).

4 n = 859; method = 7-d diet history. Sugars defined as total sugars. From Lee andCunningham (36).

5 n = 4598; method = 2-d diet history. Sugars defined as mono- and disacchar-ides. From TNO (37).

6 � 2348; method = 24-h recall. From Servico Vascode Salud-Osakidetza (38).7 n = 2197; method = 7-d weighted intake. 5ugars defined as total sugars. From

Gregory et al (39).

1905

amounts of added sugars (37-70 g/d) had a lower percent ofenergy as added sugar as well as a greater percent of energy

from fat than did those consuming high amounts of addedsugars.

When Murphy et al (30) examined the 1987-1988 NFCS

data, they found that only 2% of the total American adultpopulation (aged � 19 y) both met the RDAs for 15 nutrients

and consumed < 30% of energy as fat. When Nicklas et al (31)

stratified 871 10-y-old children, they reported that children

eating low amounts of sugar consumed higher amounts of fat in

total grams and as a percent of energy intake and vice versa.

Lewis et al (27) determined that persons consuming highamounts of added sugars when defined by percent of energy

intake consumed lower percentages of RDAs for 1 1 micronu-

tnients than did those consuming moderate amounts of added

sugars. However, when added sugar amount was defined by

grams of sugars consumed per kilogram body weight, high

consumers ingested greater percentages of RDAs than didmoderate consumers.

High sugars consumers in the 1987-1988 NFCS were not

necessarily those consuming the most energy for each age

group. Actually, moderate consumers tended to have higherenergy intakes. These moderate consumers on the whole ap-

peared to have the most adequate micronutnient profiles, withdiets that better approached dietary recommendations. In other

words, consuming less sugars did not necessarily guarantee

that a person met all dietary guidelines, nor did high sugarsconsumption automatically result in a diet of inadequate mi-cronutnient intakes. These observations support the dietary

adage of variety, balance, and moderation.

SUGARS CONSUMPTION IN THE EUROPEAN UNION

Unlike the United States, where nationwide nutritional sun-veys have been repeatedly carried out using standard methods

on nationally representative samples, the data available for theEuropean Union (EU) are characterized by greaten diversity inevery respect. Survey sizes differ, as does the range of ages

surveyed. The methods used include 24-h recalls, diet histories,

weighed intakes, and household inventory. Some surveys are

carried out at the level of individuals, others at the level of

households. How the data are reported varies in the listing ofnutrients, definition of categories, and classification of foods.

Notwithstanding this diversity of approaches, there is a wealth

of data on food and nutrient intakes in the European Union thatwas recently compiled in a database (32).

Nine of the 12 EU member states have carried out national

nutrition surveys (Ireland, Italy, Spain, Germany, Netherlands,

Belgium, Denmark, Portugal, and the United Kingdom). Notall provide age and sex breakdowns of data on sugars intake;however, age and sex variations in sugars consumption (in g/d

and percent of energy) and energy intakes for 7 countries arelisted in Table 10. All data are from nationally representativesamples except for the Spanish data, which are from the

Basque (northeastern) region of Spain. A major survey is nearcompletion in France, and of the two remaining countries,Luxembourg and Greece, the latter is conducting a very large

nutritional survey as part of the European Prospective Investi-gation of Cancer (EPIC), a multicenten study of diet and cancer.Other multicenter studies are available, the most comprehen-

Age and sex variation in energy and sugars consumption and in percent

of energy from sugars in seven European Union countries

Sugar

percent of

Energy Sugar energy

Male Female Male Female Male Female

Mild gid %

13.7 9.6 126 100 14.7

12.9 9.1 111 93 13.8

12.2 8.6 105 85 13.7

10.9 8.4 92 85 13.5

9.6 7.8 84 86 14.0

11.1 8.3 113 99 16.3

11.2 8.2 91 80 13.0

10.8 8.1 73 72 10.9

10.4 8.3 73 74 11.2

10.3 8.4 66 75 10.3

10.0 7.9 73 76 11.6

8.4 90 81 14.8

9.1 117 102 16.6

8.9 126 95 14.4

8.6 107 83 12.5

7.7 100 69 12.6

7.3 80 68 12.1

7.2 75 63 12.6

9.5 163 147 24.6

9.2 175 134 22.0

8.8 139 109 18.7

8.1 124 100 18.5

7.9 123 100 19.1

8.8 78 48 9.9 8.6

8.3 69 45 8.9 8.5

8.0 53 35 7.3 6.9

8.1 47 35 7.1 6.8

7.3 114 92 17.4

7.1 112 85 17.2

7.4 117 89 17.4

6.9 114 78 17.9


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AA

A% fatenergy

30

2 0 ‘ � � � ‘ I I . C . I I

S 10 15 20 25 30 35 40

% sugar energy

FIGURE 4. Reciprocal relation between percent of energy from sugars

(mono- and disaccharides) and percent of energy from fat in a cluster

analysis of the nutrient intakes of 3781 Dutch adults. From data in refer-

ence 44.


sive of which is the SENECA study of nutritional status anddietary habits in elderly people of 12 countries both inside and

outside EU. There are also several very large regional surveysthat provide extensive data and several smaller studies that help

to validate the larger surveys and the differences between them.In this review, we emphasize nationally representative surveys.When such data are not available on when the definitions of

food categories or nutrient groups are not useful in a review of

sugar intakes, regional and small surveys will be used.

Age and sex variation in sugars consumption

As can be seen from Table 10, considerable variation in

sugars intakes exists but no simple conclusions can be drawn

from the data. For example, “sugars” is defined as refined

sugars in the Danish data and therefore probably excludes milksugars; sugars in cereals, fruit, and vegetables; and possiblysome sugar in confectioneries. However, the other six countries

do define sugars in broadly similar terms and thus can be

compared without definition of sugars as a confounding factor(Table 11). Differences in absolute intakes of sugars may vary

because overall energy intakes vary (either truly or as a result

of methodology); therefore, sugar intakes are expressed both asg/d and as a percent of energy. However, such correction maynot be enough. The percent of energy from sugars is influencedby the absolute intakes of other energy-bearing nutrients. For

example, the average percent of energy from alcohol in the

Spanish study was 1 1% for males, which contrasts with thevalue of 3% for Dutch males. On balance, however, it may beaccepted that whereas alcohol and other nutrients may contnib-

ute somewhat to the variation in percent of energy from sugars(both upward and downward), a true variation does exist. Thisis supported by the much higher between-country coefficient of

variation for sugars intakes compared with energy intakes (see

Table 11).

One other approach to ensuring that variation is due todietary patterns that are truly qualitatively different is to seewhether previous studies have shown similar between-country

differences. In Germany, a survey of 20-40-y-old men inHeidelberg was carried out in the mid 1970s (40); the valuesreported in this survey for both energy intake and percent of

energy from sugar (see Table 10) were very close to thosereported in a recent national survey (35). Similarly, a compar-ison of nutrient intakes between 1980 and 1990 in Englishadolescent children aged 1 1-14 y showed no significant dif-fenences over time and gave values broadly comparable withthe national nutrition survey (41). These two previous and

independent studies confirm that the intake of sugars in the

United Kingdom is truly higher than that in Germany and inturn support the general conclusion of an EU-wide variation insugars intakes. The proportion of that variation truly attnibut-

able to differing gastronomic traditions and to differing re-search methodologies cannot be established.

Table 10 does not provide data for Italy and Portugal because

the national nutrition surveys in these countries did not report

on intakes of sugars. The Spanish national nutrition survey alsocould not be used for the same reason, hence the reliance on

data from the Basque region only. Limited data are availablefor these countries; several Italian studies indicate that theaverage value for percent of energy from sugars (10% ofenergy) is nearer the Spanish value than those of the northern

EU states (42, 43). Whether this implies a north-south EU

TABLE 11Comparative mean national intakes of sugars in six European Union

states using a broadly comparable definition of sugars in reported

national survey data’

Energy g/d % energy

Belgium 10.3 96 15.2

Germany 9.4 80 13.9

Ireland 9.9 90 14.6

Netherlands 10.0 131 21.2

Spain (Basque) 9.9 51 8.0

United Kingdom 8.8 100 18.4

Total2 9.7 ± 0.5 (5) 91 ± 28 (29) 15.2 ± 4.8 (32)

, Sugars defined as either total sugars, mono- and disaccharides, simple

carbohydrates, or carbohydrate minus polysaccharide.

2 ,� � SD, CV (%) in parentheses.

divide in sugars intakes is not known, but given the extent to

which this divide exists for other nutrients and foods, it wouldnot be surprising were it found to be true.

Sugar-fat relations

The proportion of energy derived from fat is a function of

absolute fat intake and intake of nonfat energy. At equal

intakes of fat (in g/d), groups differing in their intake of nonfat

energy differ in their percent of energy from fat. This has beenconsistently observed in comparisons of groups within coun-tries and between countries. The most elegant demonstration of

the inverse relation between sugar and fat comes from a cluster

analysis of the Dutch National Nutrition Survey of 3781 adults

aged 19-85 y. Eight clusters were identified (eg, high fat, high

alcohol; moderate fat, low alcohol; low fat, high ratio ofpolyunsaturated to saturated fatty acids; and so on). Valueswere reported for percent of energy from mono- and disaccha-

50

A

40 A


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192S GIBNEY ET AL

rides (44) and a clear inverse relation between percent of

energy from total fat and that from mono- and disaccharides

was evident (Figure 4). This inverse relation has several im-

plications. An analysis of food consumption patterns of sub-

populations with high and low intakes of fat (as percent of

energy) will likely be confounded by percent of energy from

sugars. First, subpopulations selected on the basis of a high

percent of energy from fat will automatically be those with a

low percent of energy from sugars, and vice versa. Second,

high-sugars diets that lead to low-fat diets may lead to a lower

tendency for the development of obesity. This is discussed in

more detail by Hill and Prentice (45). Finally, if sugars and fat

show an inverse relation, then it may not be possible to develop

quantitative guidelines for both, because the achievement of

one recommendation may lead to the failure to achieve theother.

Hulshof et al (46) compared nutrient intakes of the Dutchpopulation with the Dutch National Nutrition Guidelines. For

male and female adult subjects (aged > 19 y), it was clear thatthose achieving the guideline of < 35% of energy from fat

(12.8% of adults) only just achieved the very modest Dutch

goal for total sugars (25% of energy). Compared with the group

with a fat intake > 40% of energy, the group consuming< 35% of energy from fat consumed more total mono- and

disaccharides (25.8% compared with 17.7% of energy) and

more added mono- and disaccharides (12.6% compared with9.7% of energy). From these data it can be calculated that 35%

of the difference in sugars intake between groups with low- and

high-fat diets was due to added sugars, whereas 65% was due

to intrinsic sugars, including lactose. However, intakes ofpolysacchanides were not substantially different between the

two groups (22.3% compared with 20.3% of energy). In effect,

the generally cited goals of 35% of energy from fat and 10% of

energy from added sugars are not observed in practice in

Western diets. A reappraisal of the overall achievability of

dietary guidelines is clearly called for on the basis of this Dutch

study, which showed that only 0.9% of adults achieve the goal

for saturated fatty acid intake (10% of energy) and only 0.3%

achieved all five Dutch goals.

In the context of sugar-fat associations, it is often suggestedthat a nutritional disadvantage of sugars in the diet is that they

are used in association with high-fat foods. Although it is

perfectly possible to identify foods rich in both fat and sugars,

the significance of this must be considered in the context of the

diet as a whole. The data from the UK national dietary survey

of adults carried out in the 1980s show that foods that areprimary sources of sugars are only minor sources of fat, and

vice versa. Thus the five main purveyors of added sugars,

although providing 62% of sugars intake, only provide 16% offat intake. Equally, the top five sources of fat provide 70% of

dietary fat while providing only 15% of nonlactose sugars.

Micronutrient dilution

Sugars are a source of energy but of no other nutrient;

accordingly, their presence at high amounts in the diet leads to

micronutnient dilution. To some extent, this conclusion is con-

ceptually naive. For example, if an individual consumes 30 g

fat/d as spreadable fats and oils, with a total energy intake of

9.2 MJ/d (2200 kcal/d), then these foods alone contribute

12.3% of energy. Other foods with very high fat contents and

equally low micronutnient contents (excluding some fat-soluble

vitamins) could raise this figure (eg, ice cream, cream, certain

cheeses, and desserts). There is therefore a reasonable propor-

tion of dietary energy derived from fat that comes from foodsbearing little else but fat. The capacity therefore exists toexchange substantial quantities of fat for sugars without alter-

ing micnonutnient intakes. The supposition that sugars automat-

ically replace micronutnient-nich foods to the point of altering

micronutnient intake is therefore inherently wrong. It is not

surprising that this is borne out in detailed analyses of food

consumption data. The most recent refutation of this belief

comes from an analysis of the UK survey of food and nutrientintakes of British schoolchildren (47). Intakes of all nutrients

were ranked according to tertiles of percent of energy from

total sugars: low, < 20.7% of energy; medium, 20.7-25.2% of

energy; and high, > 25.2% of energy. Nutrient intakes were

not significantly lower and were often higher in the group withthe highest percent of energy from sugars.

CONCLUSION

The percent of energy from total sugars (minus lactose) inthe United States remained constant between 1977 and 1987 at

18%. EU values for energy from total sugars range from 8.0%

to 21.2%, with a mean value of 15.2%. This difference between

the United States and the European Union may be related to

differences in methodology but may also be related to a lower

energy from dietary fat in the United States.

The dietary survey data in both regions agree in areas thatmay affect the interpretation of data in the formulation of

nutrition policy. Both regions indicate an inverse relation be-

tween intakes of fats and sugars when expressed as a percent of

energy (see Tables 7-9 for the United States and references44-46 for the European Union). The data from both regionsindicate that across the range of sugars intakes there is no

consistent on nutritionally meaningful variation in micronutni-ent intake (see Tables 7-9 for the United States and reference

47 for the European Union). In both regions, the data show that

the proportion of individuals achieving specific dietary guidelines

is disturbingly low. Moreover, the proportion of individuals

achieving dietary guidelines for total and saturated fat is much

higher among subgroups with higher intakes of total sugars.Although the databases on food consumption have indicated

areas of nutrient intake that are important for devising dietary

guidelines, the definitive resolution of the issues raised can

only be achieved by new research designed specifically to

address these issues. In particular, to be clearly elucidated, the

observed reciprocal relation between fat and sugar needs to be

examined in studies designed to allow extensive nutnient-nu-tnient, nutrient-food, food-food, and meal-meal interactions and

subject variability. Furthermore, given the increasing use of

lower-fat foods for higher-fat equivalents and the changingformulation in lower-fat foods, there will be an increasing need

for more exact data on intakes of sugars, carbohydrate, fat,

fiber, and micronutnients. A

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1945 GIBNEY ET AL

COMMENTARY

Cottrell: Consideration of the available data comparing sugars

consumption and micronutnient intake in different population

groups might provide a basis for defining a safe upper limit ofsugar intake as a proportion of food energy. However, in this

paper and elsewhere (1 ; M Woodwand, C Bolton-Smith, pen-

sonal communication, 1994) the available data demonstratethat individuals who apparently consume a very low proportionof energy as sugars tend to have low intakes of the samemicronutnients as those reporting a very high intake of sugars.

Before concluding that this information allows the definitionof a safe range of intakes for sugars with defined lower andupper limits, it is worthwhile to reflect that these limits would

be determined by dietary history or recall records relating toindividuals with reportedly very unusual diets. It may be that

these individuals do indeed have bizarre dietary habits, in

which case the conclusions drawn will have some validity.

Other possible explanations, however, would invalidate anyconclusions drawn from these data. Among these explanations

are that these dietary records are generally unreliable, leadingto apparently extreme intakes of sugars; that the records are not

representative of the individual’s habitual diet; and that the

records have been specifically distorted by reporting preju-

dices. Each of these phenomena must be suspected more inrecords suggesting highly unusual eating habits than in more

normal records. Unless these explanations of the data can be

excluded, conclusions based on them must be considered in-secure.

Reference

1. Baghurst K!, Baghurst PA, Record SJ. Demographic and nutritional

profiles of people consuming varying levels of added sugars. Nutr Res

1992;12: 1455-65.


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consumption of sugars

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