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U.S. Teens and the Nutrient Contribution and Differences of Their Selected Meal Patterns
Anna Maria Siega-RizAdolescence is a period of great transitions. Nutrient requirements are increased from childhood because of physical growth, and behaviors acquired during this period persist into adulthood (1,11, 17,22). While many subsets of adolescents engage in behaviors that have wide public health attention, some adolescents may also follow pathways of poor food choices and reduced physical activity--both of which can also have deleterious effects on health (10,25). Among the health consequences of following these pathways have been rapid increases in obesity and adult-onset diabetes (13,23,26). Members of this age group are influenced strongly by their peers, the media, and family situation and less by their knowledge of risky behaviors (6,21,22).
Skipping meals is a common practice among adolescents: about 20 percent do not eat breakfast, and about half as many do not eat lunch (3,5,10,18,19). Skipping meals may lead to more snacking; for those who do not view skipping meals as a method of weight loss, snacks often compensate for missed calories and other key nutrients. The literature indicates that, on average, most children and adolescents average four eating occasions a day, with an upper range of 13 occasions among Mexican children who consumed as much as 45 percent of their energy from snacks (4,7,8). Research on the meal patterns of U.S. adolescents showed that most consume at least two meals (plus or minus snacks) on a consistent basis while some follow a highly inconsistent meal pattern: one meal and/or snacks all day (18).
Compared with adolescents with inconsistent meal patterns, those with consistent meal patterns consumed a diet that was adequate in calories and more nutrient dense (with respect to calcium, iron, vitamin E, and fiber) (11). Our study examines in more detail the types of food consumed by adolescents at each eating occasion and the nutrient contributions provided by each eating occasion to adolescents' total daily intakes. This study is unique: we examine snacking behaviors by using a nationally representative sample, and we determine the nutrient contributions of snacks. Previous studies have examined only the nutrient density of meals versus snacks without considering their contribution to the total diet, or previous studies have used very small samples to examine this research question (2,16).
Methods
Survey Design
Food consumption data were provided by the 1989-91 Continuing Survey of Food Intakes by Individuals (CSFII), a survey conducted by the U.S. Department of Agriculture's Agriculture Research Service. A nationally representative sample was collected by using a multistage, stratified sample design of the 48 coterminous States and Washington, DC. Data were collected in four waves during each year: one in each season, between April 1989 and May 1991. In each wave, a different sample of participants was selected. The total number of participants in all age groups sampled was 15,192.
Dietary data were collected for each individual in selected households. Using a 24-hour recall and two 1-day food records, individuals reported 3 consecutive days of intake. The female head of the household reported dietary intake for individuals less than 12 years old. We were interested in the eating patterns of adolescents, thus our analysis was restricted to 11- to 18-year-olds who reported 3 days of dietary intake (n=1,310). The classification of individuals into meal-pattern categories did not differ between 11and 12-year-olds, and the differences in nutrient composition of reported intakes of 11- and 12-year-olds were similar in magnitude to the differences between 12- and 13-year-olds. Therefore, 11-year-olds were included in the analysis despite differences in methods of data collection for dietary intake.
Variables
Meal Patterns
Survey data include descriptors of eating occasion (breakfast, lunch, dinner, supper, snack, brunch, and extended consumption) as well as the time of day each food was consumed. To identify meal patterns, we first developed clear and invariable terminology for eating occasions: Breakfast, lunch, brunch, dinner, or snack. Respondents provided the name for each meal. When respondents reported consuming either supper or dinner, the eating occasion was designated as dinner; when the respondent reported consuming both supper and dinner, dinner was designated as lunch and supper designated as dinner. This categorization was based on analysis of the data, which indicated that dinner was consumed primarily as an evening meal (85 to 87 percent between 4 and 8 p.m.). When both supper and dinner were consumed, dinner was the midday meal (56 to 69 percent between 11 a.m. and 3 p.m.) and supper was the evening meal (70 to 81 percent between 4 and 8 p.m.). Eating occasions for 1.3 percent of foods were unknown or identified as extended consumption and therefore not included in our analysis.
Three meal-pattern categories were created based on their ability to provide meaningful comparison of eating behaviors: Consistent, moderately consistent, and inconsistent. These categories are mutually exclusive and include all possible combinations of eating occasions. Respondents with a consistent meal pattern (n=538) consumed two or three meals (plus or minus snacks) on all 3 days of reported intake. Those with a moderately consistent meal pattern (n=726) consumed two or three meals (plus or minus snacks) on 2 of the 3 days of reported intake. And respondents with an inconsistent meal pattern (n=46) consumed only one meal (plus or minus snacks) or snacks only on all 3 days of reported intake.
Personal, Household, and Demographic Characteristics
Population characteristics available directly from the CSFII were age, gender, race, region of residence, supplement use, school attendance, educational and employment status of the female head of the household, income status, and household size. Our derived variables were consumption of school-based meals and single- versus dual-parent households. Respondents who reported consuming at least one school-based lunch per week were classified as consumers of school lunch. This method was repeated for school breakfast. Classification as a single- or dual-parent household was based on the presence of a male or female head of household or female and male heads of household, respectively.
Nutrient and Food-Grouping System
The nutrient database was provided by USDA Survey Nutrient Data Base, Release #7 and was developed for the 1991 CSFII. For this analysis, we used nutrient information provided as the total average intake or as the average percentage of the Recommended Dietary Allowances (RDA) for all nutrients (12) consumed over 3 days.
The age- and gender-appropriate RDA values were used to calculate the average percentage of the RDA consumed. Grams of food consumed at each eating occasion were calculated by using the University of North Carolina at Chapel Hill food-grouping system. This system disaggregates major USDA food groups into 56 more distinct nutrient-based groups based on the composition of fat and dietary fiber. The University of North Carolina at Chapel Hill's food-grouping system covered all foods that respondents reported eating (14,15).[1]
Statistical Methods
We used Student's t test and a chi-square test to compare the sociodemographic characteristics among the groups based on their meal patterns. Statistical testing, however, was not performed on the proportion of the nutrients or the grams of food contributed by each meal. To do so would have required many comparisons, resulting in our having to use a very stringent p value. Hence our analysis is descriptive. The results provide estimates representative of the U.S. population in the coterminous 48 States. We weighted the statistics for nonresponse and corrected the standard errors for the complex multistage design. We used the STATA survey option that allows for the effects of the complex sample design (20).
Results
Sociodemographic Characteristics
Forty-one percent of the adolescents had consistent meal patterns; only 4 percent had inconsistent meal patterns (table 1). The 15- to 18-year-olds were more likely to have inconsistent meal patterns. The consistent meal-pattern category had a higher percentage of respondents who were male, white, and who attended school. Adolescents with a consistent meal pattern were less likely to be from a single-parent household and more likely to be from a household in which the female head attended college. Neither the mean percentage of poverty nor years of education of the female head of household differed significantly by meal-pattern category.
Table 1. Descriptive characteristics of 15- to 18-year-olds and their
households, by meal-pattern category, 1989-91 CSFII
Meal pattern
Sociodemographic Moderately
characteristic Consistent consistent
Sample 538 726
Percent
Female 47.0 52.6(1)
Block 14.1 19.0(1)
Attends school 93.1 87.2(1)
Single-parent household 27.3 31.4(1)
Female head of household
attended college 34.9 31.1(1)
Female head of household
has < 12 years of education 26.9 31.1(1)
Region
Northeast 18.0 17.2
Midwest 30.9 26.5(1)
South 31.2 35.4(1)
West 19.9 20.9
Mean ([+ or -] S.D.)
Percentage of poverty 329 (264) 326 (249)
Household size 4.7 (1.9) 4.2 (1.4)(3)
Meal pattern
Sociodemographic
characteristic Inconsistent
Sample 46
Percent
Female 60.9(1,2)
Block 23.9(1,2)
Attends school 75.6(1)
Single-parent household 34.8(1)
Female head of household
attended college 27.3(1,2)
Female head of household
has < 12 years of education 31.8(1)
Region
Northeast 10.9(1,2)
Midwest 28.3
South 34.8
West 26.1(1,2)
Mean ([+ or -] S.D.)
Percentage of poverty 330 (209)
Household size 4.2 (1.5)(3,4)
(1) Significantly different from the consistent meal pattern,
chi-square analysis, p < 0.05.
(2) Significantly different from moderately consistent meal pattern,
chi-square analysis, p < 0.05.
(3) Significantly different from consistent meal pattern, weighted t
test, p < 0.05.
(4) Significantly different from moderately consistent meal pattern,
weighted t test, p < 0.05.
Nutrient Profiles Based on Adolescents' Meal Pattern
Adolescents with a consistent or moderately consistent meal pattern consumed 37 to 38 percent of their total energy from dinner. For adolescents in the inconsistent group, 43 percent of their total energy was consumed at dinner. Even more important is the difference in the role of snacks in their diet. Snacks comprised about 23 percent of the total day's energy for those following an inconsistent meal pattern but only 11 to 16 percent for those following the other two meal patterns. In total, the dinner meal and total snacks together provided more than two-thirds of the day's total energy for adolescents with an inconsistent meal pattern.
Differences by age group were noted (figs. 1 and 3). For instance, 11- to 14-year-olds in the inconsistent group obtained 24 percent of energy from lunch while older adolescents in the same group obtained 9 percent of energy from lunch. For 11- to 14-year-olds with inconsistent meal patterns, breakfast provided 5 percent of energy, compared with almost twice that amount for the older adolescents. Brunch was more common for older adolescents with inconsistent meal patterns. Among older adolescents (15- to 18-year-olds) following an inconsistent meal pattern, dinner and snacks were far more important than they were for younger adolescents (11- to 14-year-olds).
Figure 1. Distribution of energy obtained, by meal-pattern of 11-to
18-year-olds, 1989-91 CSFII
Meal-pattern groups
Consistent
Total snacks 11%
Brunch 1%
Breakfast 19%
Lunch 31%
Dinner 38%
Moderately consistent
Total snacks 16%
Brunch 2%
Missing 1%
Breakfast 18%
Lunch 25%
Dinner 38%
Inconsistent
Total snacks 23%
Brunch 9%
Missing 6%
Breakfast 8%
Lunch 12%
Dinner 43%
Note: Table made from pie chart.
Figure 2. Distribution of energy obtained, by meal-pattern of 11-to
14-year-olds, 1989-91 CSFII
Meal-pattern groups
Consistent
Total snacks 10%
Brunch 1%
Breakfast 19%
Lunch 32%
Dinner 38%
Moderately consistent
Total snacks 16%
Brunch 3%
Missing 2%
Breakfast 19%
Lunch 23%
Dinner 37%
Inconsistent
Total snacks 19%
Brunch 3%
Missing 9%
Breakfast 6%
Lunch 24%
Dinner 40%
Note: Table made from pie chart.
Figure 3. Distribution of energy obtained, by meal-pattern of 15-to
18-year-olds, 1989-91 CSFII
Meal-pattern groups
Consistent
Total snacks 12%
Brunch 0.01%
Breakfast 20%
Lunch 30%
Dinner 38%
Moderately consistent
Total snacks 15%
Brunch 1.44%
Missing 0.56%
Breakfast 18%
Lunch 25%
Dinner 40%
Inconsistent
Total snacks 24%
Brunch 10%
Missing 5%
Breakfast 9%
Lunch 9%
Dinner 43%
Note: Table made from pie chart.
Most nutrients follow the same pattern as that for energy (table 2). Breakfast provided the same proportion of nutrients for adolescents with consistent and moderately consistent meal patterns; whereas, lunch appeared to have lower proportions of fat, protein, carbohydrates, calcium, fiber, and sodium for adolescents with moderately consistent meal patterns. The proportions of nutrients from brunch were very low (no more than 3.5 percent) for adolescents with the consistent and moderately consistent meal patterns but closer to 10 percent for their counterparts with inconsistent meal patterns. Dinner provided similar proportions of nutrients for all three groups.
Table 2. Proportion of nutrients provided by each meal among 11 - to
18-year-olds, by meal-pattern consumption(1)
Consistent meal pattern Moderately consistent
meal pattern
Nutrient Mean Standard deviation Mean Standard deviation
Breakfast
Energy 19.23 9.69 18.24 10.62
Fat 16.07 11.76 15.66 11.56
Saturated fat 17.92 12.87 17.03 12.20
Protein 17.27 9.95 16.15 10.60
Carbohydrate 21.95 10.28 20.81 11.93
Calcium 28.94 16.53 26.31 16.81
Cholesterol 23.35 20.16 21.35 20.82
Iron 29.24 17.26 27.47 19.01
Folate 39.11 19.16 35.90 22.16
Zinc 20.70 13.16 18.63 15.20
Fiber 14.68 10.40 16.51 13.05
Sodium 16.23 9.54 16.17 10.40
Brunch
Energy 0.47 3.48 2.11 5.80
Fat 0.51 3.92 2.44 7.85
Saturated fat 0.58 3.93 2.47 7.88
Protein 0.45 3.16 2.05 6.84
Carbohydrate 0.46 3.60 2.04 5.39
Calcium 0.60 3.76 2.26 7.36
Cholesterol 0.39 2.88 3.50 12.84
Iron 0.36 2.52 2.12 6.87
Folate 0.40 2.69 2.41 7.76
Zinc 0.43 3.04 1.87 5.76
Fiber 0.57 5.12 2.13 6.84
Sodium 0.39 2.88 2.11 6.30
Lunch
Energy 31.22 11.64 24.52 12.58
Fat 33.29 14.11 26.10 14.56
Saturated fat 32.43 14.53 26.33 15.62
Protein 30.46 12.04 24.69 14.14
Carbohydrate 30.03 12.02 23.48 12.39
Calcium 30.46 15.74 24.82 16.11
Cholesterol 26.65 14.67 22.49 17.68
Iron 26.36 12.03 21.56 13.00
Folate 22.88 12.70 19.90 14.38
Zinc 27.74 12.99 23.75 14.88
Fiber 33.16 15.87 25.26 14.25
Sodium 32.26 12.70 25.06 14.12
Dinner
Energy 37.72 10.53 38.01 14.60
Fat 40.17 13.68 39.79 16.77
Saturated fat 38.54 14.52 37.87 17.10
Protein 45.23 12.33 45.90 16.52
Carbohydrate 33.61 10.92 33.92 14.65
Calcium 29.86 14.20 30.84 17.28
Cholesterol 43.29 18.86 40.97 20.76
Iron 36.81 12.84 37.00 17.46
Folate 29.93 13.59 30.53 16.87
Zinc 43.80 14.72 43.86 18.95
Fiber 41.84 15.89 41.61 18.22
Sodium 44.83 12.15 44.52 16.40
Total snacks
Energy 10.92 9.69 15.50 13.74
Fat 9.65 10.06 14.40 15.01
Saturated fat 10.16 10.94 14.78 15.44
Protein 6.38 7.17 9.85 11.30
Carbohydrate 13.35 11.53 18.06 15.16
Calcium 9.71 11.97 14.24 15.90
Cholesterol 6.05 8.59 10.09 13.08
Iron 7.06 8.62 10.45 11.87
Folate 7.48 9.93 9.79 12.26
Zinc 7.09 8.33 10.53 11.81
Fiber 9.39 10.96 13.11 13.41
Sodium 6.12 6.92 10.74 13.18
Inconsistent meal pattern
Nutrient Mean Standard deviation
Breakfast
Energy 7.94 8.51
Fat 6.31 7.94
Saturated fat 7.67 8.79
Protein 9.63 11.86
Carbohydrate 8.70 9.38
Calcium 15.81 18.04
Cholesterol 10.46 17.45
Iron 19.72 25.64
Folate 22.66 25.07
Zinc 10.51 14.33
Fiber 7.92 12.93
Sodium 8.86 10.52
Brunch
Energy 8.58 13.69
Fat 9.82 16.16
Saturated fat 9.07 15.41
Protein 7.02 11.39
Carbohydrate 7.97 12.99
Calcium 8.05 16.38
Cholesterol 7.97 12.93
Iron 8.00 12.84
Folate 9.30 16.49
Zinc 8.65 15.52
Fiber 8.14 15.44
Sodium 9.89 17.09
Lunch
Energy 11.94 18.98
Fat 12.52 20.91
Saturated fat 11.94 19.99
Protein 10.32 18.14
Carbohydrate 12.39 19.05
Calcium 10.32 19.26
Cholesterol 10.41 18.49
Iron 9.54 16.59
Folate 8.88 18.33
Zinc 10.42 18.25
Fiber 12.65 22.14
Sodium 11.52 20.20
Dinner
Energy 43.21 26.07
Fat 46.58 26.58
Saturated fat 44.04 28.06
Protein 55.07 25.52
Carbohydrate 37.49 26.89
Calcium 42.09 29.05
Cholesterol 49.50 28.39
Iron 44.53 30.34
Folate 38.64 26.11
Zinc 49.59 28.25
Fiber 46.14 27.62
Sodium 52.51 26.52
Total snacks
Energy 23.16 19.02
Fat 21.41 20.34
Saturated fat 23.38 21.52
Protein 15.36 15.93
Carbohydrate 26.91 20.41
Calcium 19.52 17.71
Cholesterol 17.83 21.74
Iron 15.82 17.82
Folate 18.75 19.36
Zinc 17.37 17.92
Fiber 22.09 19.26
Sodium 14.26 14.47
(1) The percentage may not total to 100 for each nutrient because
of rounding and the small percentage of foods with a missing
eating-occasion classification.
For adolescents with inconsistent meal patterns, the proportion of nutrients provided by total snacks was nearly double the nutrients provided to adolescents with consistent meal patterns. The proportion of nutrients coming from snacks for the moderately consistent group falls between those of the other two groups.
Food Consumed Based on Adolescents' Meal Patterns
Interesting differences were noted in the types of foods consumed at each eating occasion across meal-pattern groups. At breakfast, adolescents with a consistent meal pattern, compared with adolescents in the other groups, had higher per capita consumption of both low- and medium-fat milk, egg items, low-fiber breads, cooked and ready-to-eat cereals, high-fat desserts, and juices (fig. 4). In contrast, adolescents with moderate and inconsistent meal patterns consumed more soft drinks. At lunch, adolescents with consistent meal patterns consumed more milk and higher amounts of total poultry, high-fat desserts, vegetables, fruits, and high-fat grain-based mixed dishes (pizza and macaroni and cheese, etc.), compared with other adolescents (fig. 5). There was no difference in beef/ pork consumption between adolescents with consistent and moderately consistent meal patterns, which were, however, higher than that for adolescents with inconsistent meal patterns. The inconsistent and consistent groups had the same quantity of high-fat potato consumption.
Figure 4. Grams consumed at breakfast by adolescents
following a consistent, moderately consistent, or
inconsistent meal pattern, by selected food groups(1)
Breakfast food items (grams)
Consistent 98
Low-fat milk Moderately consistent 70
Inconsistent 68
Consistent 85
Medium fat milk Moderately consistent 54
Inconsistent 13
Consistent 11
Eggs and egg dishes Moderately consistent 10
Inconsistent 5
Consistent 6
Low-fat/low-fiber bread Moderately consistent 6
Inconsistent 1
Consistent 2
Low-fat/high-fiber bread Moderately consistent 3
Inconsistent 0.06
Consistent 14
High-fat/low-fiber bread Moderately consistent 9
Inconsistent 4
Consistent 10
High-fat desserts Moderately consistent 7
Inconsistent 0.7
Pasta, rice, and Consistent 14
cooked cereals Moderately consistent 12
Inconsistent 0
Consistent 19
Ready-to-eat cereals Moderately consistent 17
Inconsistent 8
Consistent 58
Citrus fruits and juices Moderately consistent 37
Inconsistent 12
Consistent 21
Other fruits and juices Moderately consistent 11
Inconsistent 3
Consistent 9
Sugar and jellies Moderately consistent 6
Inconsistent 2
Consistent 11
Coffee and Tea Moderately consistent 11
Inconsistent 3
Consistent 4
Softdrinks Moderately consistent 15
Inconsistent 12
Consistent 10
Fruit drinks Moderately consistent 11
Inconsistent 0.47
(1) University of North Carolina at Chapel Hill food-grouping system.
Note: Table made from bar graph.
Figure 5. Grams consumed at lunch by adolescents
following a consistent, moderately consistent, or
inconsistent meal pattern, by selected food groups(1)
Lunch food items (grams)
Consistent 54
Low-fat milk Moderately consistent 28
Inconsistent 1
Consistent 68
Medium fat milk Moderately consistent 39
Inconsistent 1
Consistent 9
Low fat beef and pork Moderately consistent 10
Inconsistent 3
Medium-fat beef Consistent 14
and pork Moderately consistent 15
Inconsistent 3
Consistent 5
Low-fat poultry Moderately consistent 3
Inconsistent 0.41
Consistent 7
Medium-fat poultry Moderately consistent 3
Inconsistent 4
Low-/medium-fat Consistent 3
luncheon meats/hot dogs Moderately consistent 3
Inconsistent 0
High-fat Consistent 5
luncheon meats/hot dogs Moderately consistent 4
Inconsistent 0
Consistent 11
High-fat desserts Moderately consistent 6
Inconsistent 4
High-fat grain-based Consistent 30
mixed dishes Moderately consistent 21
Inconsistent 21
Consistent 7
Citrus fruits and juices Moderately consistent 8
Inconsistent 0
Consistent 37
Other fruits/juices Moderately consistent 18
Inconsistent 7
Consistent 15
High-fat potatoes Moderately consistent 9
Inconsistent 15
Consistent 32
Vegetables Moderately consistent 14
Inconsistent 4
Consistent 88
Soft drinks Moderately consistent 82
Inconsistent 43
(1) University of North Carolina at Chapel Hill food-grouping system.
Note: Table made from bar graph.
For dinner, teens with an inconsistent meal pattern had higher intakes of poultry, green/orange vegetables, high-fat grain-based mixed dishes, high-fat breads, and soft drinks and a lower intake of low- and medium-fat milk, soy and legumes, and fruits, compared with their other adolescent counterparts (fig. 6). In contrast, snacks for the inconsistent group contained more grams per capita of milk items, in particular medium-fat milk items (whole milk and milk shakes) and soft drinks than was the case for the consistent group (fig. 7). All three groups of adolescents had similar intakes of fruits, high-fat desserts, high-fat salty snack items (chips, salty crackers, etc.) and high-fat grain-based mixed dishes.
Figure 6. Grams consumed at dinner by adolescents
following a consistent, moderately consistent, or
inconsistent meal pattern, by selected food groups(1)
Dinner food items (grams)
Consistent 56
Low-fat milk Moderately consistent 36
Inconsistent 42
Consistent 30
Medium-fat milk Moderately consistent 16
Inconsistent 5
Consistent 26
Low-fat beef/pork Moderately consistent 25
Inconsistent 14
Consistent 12
Low-fat poultry Moderately consistent 11
Inconsistent 28
High grain-based Consistent 45
mixed dishes Moderately consistent 35
Inconsistent 72
Consistent 14
Soy and legumes Moderately consistent 9
Inconsistent 3
Consistent 10
High-fat/low-fiber bread Moderately consistent 9
Inconsistent 22
Green and orange Consistent 6
vegetables Moderately consistent 8
Inconsistent 23
Consistent 6
Citrus fruits/juices Moderately consistent 7
Inconsistent 0.3
Consistent 13
Other fruits Moderately consistent 6
Inconsistent 8
Consistent 18
High-fat potatoes Moderately consistent 19
Inconsistent 31
Consistent 12
High-fat desserts Moderately consistent 11
Inconsistent 5
Consistent 93
Regular soft drinks Moderately consistent 96
Inconsistent 112
Consistent 9
Diet soft drinks Moderately consistent 17
Inconsistent 2
(1) University of North Carolina at Chapel Hill food-grouping system.
Note: Table made from bar graph.
Figure 7. Grams consumed at snack by adolescents
following a consistent, moderately consistent, or
inconsistent meal pattern, by selected food groups(1)
Snack food items (grams)
Consistent 23
Low-fat milk Moderately consistent 26
Inconsistent 31
Consistent 20
Medium-fat milk Moderately consistent 18
Inconsistent 32
Consistent 5
Low-fat desserts Moderately consistent 5
Inconsistent 6
Consistent 20
High-fat desserts Moderately consistent 25
Inconsistent 20
Consistent 0.67
Low-fat snack items Moderately consistent 0.55
Inconsistent 0.8
Consistent 5
High-fat, salty snacks Moderately consistent 8
Inconsistent 7
Consistent 4
High-fat grain-based mix Moderately consistent 7
Inconsistent 5
Consistent 6
Citrus fruits/juices Moderately consistent 8
Inconsistent 7
Consistent 13
Other fruits Moderately consistent 13
Inconsistent 12
Consistent 4
Candy Moderately consistent 4
Inconsistent 3
Consistent 22
Fruit drinks Moderately consistent 26
Inconsistent 18
Consistent 62
Regular soft drinks Moderately consistent 88
Inconsistent 161
Consistent 10
Diet soft drinks Moderately consistent 13
Inconsistent 4
(1) University of North Carolina at Chapel Hill food-grouping system.
Note: Table made from bar graph.
Patterns within each group revealed that the amount of soft drink consumed per capita at lunch, dinner, and total snacks was higher than the amount of milk consumed (figs. 4-7). High-fat, low-fiber bread is more commonly eaten at breakfast, compared with other bread options available. Low-fiber cereal is consumed more than high fiber, and citrus juices are consumed more than noncitrus juices or fruit drinks at breakfast. At lunch, medium fat beef/pork and poultry were eaten more than the low- or high-fat option. The grams per capita for luncheon meats was equally distributed among each fat option. In contrast to breakfast, the low-fat, low-fiber bread option and fruit drinks were eaten in greater amounts at lunch for the consistent and moderately consistent groups. And for all three groups, there was a higher per capita consumption of the high-fat versus the low-fat of grain-based mixed dishes. The type of bread consumed at the dinner meal was similar to that seen at breakfast. And the higher fat version of grain-based meals was once again consumed more than the low-fat version at dinner for all three groups. Patterns within groups for the different types of foods consumed as snacks were similar.
Discussion
Dietary intake patterns of U.S. adolescents are poor. Skipping meals, excessive snacking, and consumption of excessive high-fat, poor nutritionally dense foods are many of the issues raised in the literature. However, few studies have used nationally representative samples to examine the meal and food patterns of U.S. adolescents. This study highlights the large variation in eating patterns among U.S. adolescents.
In particular, we show that teens differ markedly by the proportion of food intake from each meal and the types of foods eaten, based on consistent, moderately consistent, or inconsistent meal patterns.
Regarding snacks, our results differ from the few published studies on this topic. Our study finds that snacks contribute much less to the total diet than reported previously. For most adolescents (97 percent), meals contribute, on average, 20 to 40 percent of the total day's energy, compared with 10 to 15 percent contributed by snacks. One study has found that about 25 to 33 percent of the total day's energy comes from snacks (16). Other published studies have focused more on the frequency of snacking and the snack foods adolescents like to eat (4,5,8).
Our study shows that for all the adolescents, a higher proportion of the total day's intake of fat is consumed at dinner. Otherwise, meals and snacks provide similar proportions of the other macronutrients. Our results regarding macronutrients offer a different view of examining macronutrient intake; others who have examined the nutrient density of meals and snacks have found that meals are higher in fat and lower in carbohydrates than are snacks (8).
The nutrient contribution of snacks is more significant for those adolescents following an inconsistent meal pattern, compared with adolescents following other meal patterns. This occurs simply by how this group was defined, those consuming one meal plus or minus snacks on 3 days of intake. The nutrient contribution of snacks for this adolescent group is similar to that reported by Ruxton et al. (16) in a study of 7- to 8-year-olds (n=136), from five schools in Scotland). In our study, snacks for the inconsistent group provided more of most nutrients than did breakfast or lunch with the exception of iron and folate, which were higher at breakfast. By using the 1977 Nationwide Food Consumption Survey (NFCS), researchers found that for most adolescents, snacks compared with meals contributed significantly more magnesium, calcium, vitamin A, and vitamin C to the diet (2). For the only nutrient on which we overlapped, calcium, this was not found in the 1989-91 USDA survey. Because of the frequency of snacking and the significant proportion of energy and other nutrients that snacks provide adolescents with an inconsistent meal pattern, we believe the nutritional quality of snacks has important implications for the health status of these adolescents.
Another nutritionally important issue is adolescents' high intake of soft drinks and lower intake of milk [also noted in the 1977 NFCS survey (9)]. These consumption patterns apply to adolescents regardless of meal-pattern group. Even though adolescents with a consistent meal pattern consume the most milk, their calcium intakes are lower than recommended. Also, adolescents appear to be consuming more high-fat and low-fiber foods than the more healthful alternatives. Consuming more high-fat and low-fiber foods may have serious health consequences (i.e., obesity, osteoporosis, and cardio-vascular diseases) if they are consumed in high amounts throughout life. The reasons for the high consumption of these types of foods may be directly related to their source (home vs. away-from-home food sources) as well as the taste preferences of adolescents. A Minnesota survey of 900 adolescents reported a strong preference for high-fat foods that related to taste appeal despite the health consequences associated with consumption of these foods (21).
A limitation of this study is the small sample size for the group with an inconsistent meal pattern. However, there were 27 million adolescents in the United States (24) around the time of this survey. Thus 950,000 U.S. adolescents are represented as following an inconsistent meal pattern for 3 days. In general, adolescents are consuming a large quantity of carbonated beverages and few fruits and vegetables. And for adolescents who follow an inconsistent meal pattern, dinner and snacks provide a disproportionate amount of nutrients. Differences are also noted in food selection: adolescents following an inconsistent meal-pattern group consume more types of fast foods. Both meal-pattern and food-selection behaviors should be used to target future public health messages to adolescents. More research is warranted on the determinants of adolescent eating patterns. Information on the determinants could help guide interventions for changing eating-pattern behaviors noted in this study.
Acknowledgments
We thank the Nestle Research Center for providing financial support for this study. We thank Dr. Henri Dirren for initiating the collaboration between Nestle and the University of North Carolina at Chapel Hill. We also thank Dan Blanchette, Terri Carson, Claire Zizza, Lynn Igoe, and Frances Dancy for their assistance.
[1] This information is available upon request.
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Anna Maria Siega-Riz, PhD Department of Nutrition School of Public Health University of North Carolina at Chapel Hill, NC, USA Claude Cavadini Nestle Research Center Lausanne, Switzerland Barry M. Popkin, PhD Department of Nutrition School of Public Health University of North Carolina at Chapel Hill, NC, USA
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