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Am J Public Health. 2002 May; 92(5): 844–851.
PMCID: PMC1447172

Overweight Status and Eating Patterns Among Adolescents: Where Do Youths Stand in Comparison With the Healthy People 2010 Objectives?

Dianne Neumark-Sztainer, PhD, MPH, RD, Mary Story, PhD, RD, Peter J. Hannan, MStat, and Jillian Croll, MPH, RD

Abstract

Objectives. This study determined the prevalence of Minnesota urban youths reaching the Healthy People 2010 objectives for obesity and intake of fat, calcium, fruits, vegetables, and grains and compared prevalence rates across sociodemographic characteristics.

Methods. The study sample included 4746 adolescents (aged 11–18 years) from the Minneapolis/St. Paul area who completed dietary surveys and participated in anthropometric measurements as part of a school-based population study.

Results. Considerable gaps were seen between the existing prevalence rates for obesity and nutrient and food patterns and the targeted Healthy People 2010 prevalence rates. For example, 12.5% of the girls and 16.6% of the boys had body mass index values at or greater than the 95th percentile (target = 5%). Only 29.5% of the girls and 42.5% of the boys were meeting the daily recommended intakes for calcium (target = 75%). Similarly, percentages of youths consuming the recommended amounts of fat, fruits, vegetables, and grains were lower than the targeted percentages. There were large sociodemographic disparities in obesity and eating patterns, particularly across race/ethnicity and socioeconomic status.

Conclusions. Concerted public health efforts are needed to achieve the Healthy People 2010 objectives for obesity and nutrition and to reduce racial/ethnic and socioeconomic disparities.

Dietary patterns developed during adolescence may contribute to obesity and eating disorders and may increase the risk for several important chronic diseases later in life.1 Being overweight as an adolescent is associated with being overweight as an adult.2 Fat intake during childhood and adolescence is associated with increased risk for coronary heart disease in adulthood.2 Low dietary calcium intake has been shown to lead to low bone density in adolescents and possibly to osteoporosis later in life.3 Furthermore, nutritional intake is of particular importance in adolescence because of rapid growth and development during this period.2,4,5 Despite the importance of nutrition during adolescence, not enough is known about the eating behaviors of young people.

Healthy People 2010 is a comprehensive, nationwide health promotion and disease prevention agenda that includes 467 objectives in 28 focus areas.6 It was developed by the US Department of Health and Human Services as a 10-year strategy for improving the health of the nation. Healthy People 2010 aims to achieve 2 overarching goals: (1) increase quality and years of healthy life and (2) eliminate health disparities. In light of the high prevalence of nutrition-related conditions and the strong potential for the prevention of these conditions, “nutrition and overweight” is one of the focus areas addressed.6 Healthy People 2010 objectives with particular relevance to the nutritional health of adolescents target levels of obesity, fat intake, intake of calcium-rich foods, and intake of fruits, vegetables, and grains (Table 1 [triangle]). In planning effectively for the achievement of the Healthy People 2010 objectives, an assessment of current eating patterns among youths is essential. Furthermore, in working toward decreasing disparities across racial/ethnic, socioeconomic, and other sociodemographic characteristics, baseline prevalence rates within different subgroups of the population need to be assessed.

TABLE 1
Healthy People 2010 Objectives for Overweight and Nutritional Health of Relevance to Youths Who Were Examined in This Study

Population-based studies of adolescent health have tended to be of a comprehensive nature with limited numbers of questions on eating behaviors. For example, the Youth Risk Behavior Survey, the Connecticut Youth Survey, the Commonwealth Fund Study, and the Minnesota Adolescent Health Survey have provided important information on eating behaviors among large and diverse adolescent populations, but questions assessing eating behaviors have been limited in scope and have not been adequately tested for reliability and validity.7–10 Furthermore, these larger studies relied on self-reported heights and weights; actual anthropometric measurements were not taken. Studies with more comprehensive assessments of nutritional intake typically have not included large numbers of adolescents,11 have not focused on identifying psychosocial and behavioral correlates of eating behaviors,12–15 and have been narrowly focused (e.g., calcium intake only).16 Even the Continuing Survey of Food Intakes by Individuals, which provided 2-day dietary intake data on a large representative sample of individuals within the United States, included only 1300 adolescents (aged 12–19 years), thus making comparisons across sociodemographic characteristics such as race/ethnicity somewhat difficult.17,18

Data for the current study were drawn from Project EAT (Eating Among Teens), a comprehensive study of adolescent eating patterns and weight concerns that was designed to address the limitations of previous studies on adolescent eating behaviors. The current study aimed to assess the prevalence of obesity and the eating behaviors targeted in Healthy People 2010 among a large populationbased sample of Minnesota urban youths. Percentages of adolescents reaching the Year 2010 objectives for obesity and intake of total fat, saturated fat, calcium, fruits, vegetables, and grains were examined and compared across sex, school level, race/ethnicity, and socioeconomic status (SES).

METHODS

Study Sample and Design

The study sample included 4746 adolescents from public middle schools and high schools in the Minneapolis, St. Paul, and Osseo school districts in Minnesota. Schools and school districts serving socioeconomically and racially/ethnically diverse communities were invited to participate in the study. Of the 53 schools that were contacted, 31 agreed to take part. Participants were equally divided by sex (50.2% boys, 49.8% girls). The mean age of participants in the study sample was 14.9 years (range = 11–18 years); 34.3% were in junior high school, and 65.7% were in high school. The racial/ethnic backgrounds of the participants were as follows: 48.5% White, 19.0% African American, 19.2% Asian American, 5.8% Hispanic, 3.5% Native American, and 3.9% mixed or other. Most of the Asian American population was from Southeast Asia; approximately two thirds of this group were Hmong.

The current study used student survey and anthropometric data that were collected within health, physical education, and science classrooms in one 90-minute period or two 50-minute periods. Trained research staff distributed the surveys within school classes for students to complete and assessed height and weight within a private area. Study procedures were approved by the University of Minnesota Human Subjects' Committee and by the research boards of the participating school districts. Consent procedures were done in accordance with the requests of the participating school districts; in some schools, passive consent procedures were used, whereas in others, active consent procedures were required. The response rate for student participation was 81.5%; the main reasons for lack of participation were absenteeism and failure to return consent forms within schools requiring active consent.

Measures

Overweight status was based on height and weight measurements taken by trained research staff in a private area with standardized equipment and procedures. Students were asked to remove shoes and outerwear (e.g., heavy sweaters). Body mass index (BMI) values were calculated according to the following formula: weight in kg/(height in m)2. Sex- and age-specific cutoff points based on reference data from the Centers for Disease Control and Prevention growth tables were used to classify respondents as overweight (BMI ≥95th percentile) or at risk for overweight (85th to <95th percentile).19,20

Dietary intake was assessed with the 149-item Youth and Adolescent Food Frequency Questionnaire. Validity and reliability of the Youth and Adolescent Food Frequency Questionnaire were tested among a random sample of children of participants in the Nurses' Health Study (primarily White) and found to be within acceptable ranges for dietary assessment tools.21,22 Among 261 youths aged 9 to 18 years, mean correlation for energy-adjusted nutrients between 2 Youth and Adolescent Food Frequency Questionnaires and three 24-hour recalls (implemented in 3 seasons) was 0.45. The mean energy for the Youth and Adolescent Food Frequency Questionnaire was higher than in the recalls but within 1% of them.21 In the current study, nutrient and food intake behaviors examined were total fat (% of total energy), saturated fat (% of total energy), calcium (mg), fruits (servings), vegetables (servings), deep yellow and green vegetables (servings), and grains (servings).

Sex, school level, race/ethnicity, and SES were based on self-report. School level was divided into middle school (grades 7–8) and high school (grades 9–12). Race/ethnicity was assessed with the following question: “Do you think of yourself as . . . (1) White; (2) Black or African American; (3) Hispanic or Latino; (4) Asian American; (5) Hawaiian or Pacific Islander; or (6) American Indian or Native American.” Youths were given the option of choosing multiple responses, and those reporting more than 1 response (other than White) were coded as “mixed or other.” Because few youths reported “Hawaiian or Pacific Islander” (n = 30), these youths were included with the “mixed or other” youths.

The prime determinant of SES was parental educational level, defined by the higher level of either parent. Response categories for questions on parental educational level were as follows: (1) did not finish high school, (2) finished high school or general equivalency diploma, (3) some college, (4) finished college, (5) master's or doctoral degree, and (6) don't know. Other variables used to assess SES included family eligibility for public assistance (yes/no/don't know), eligibility for free or reduced-cost school meals (yes/no/don't know), and employment status of mother and father (full-time/part-time/not working/don't know). An algorithm was developed to avoid classifying youths as high SES, based on parental education levels, if they were receiving public assistance, were eligible for free or reduced-cost school meals, or had 2 unemployed parents (or 1 unemployed parent if from a single-parent household). These variables were also used to assess SES in cases for which data were missing or “don't know” responses were given for both parents' educational level (n = 1058, 22.3%). The use of Classification and Regression Trees23 showed that these other variables were predictive of parental education and reduced the percentage of missing SES values to 4.1% (n = 196).

Data Analysis

Summary statistics (means and medians) for the various outcomes are presented in Table 2 [triangle], whereas the remaining tables focus on the percentage of the students meeting the Year 2010 objectives. Findings presented in the tables are from unadjusted bivariate analyses stratified by sex, thus allowing for interpretations as to which subgroups in the study sample were, or were not, achieving the Year 2010 objectives.

TABLE 2
Body Mass Index and Nutrient and Food Intakea Among Adolescents, by Sex: Means and Median Values

In Table 1 [triangle] and in tables 3–8 [triangle] [triangle] [triangle] [triangle] [triangle] [triangle], prevalence estimates were generated by linear mixed models in which school was included as a random effect to allow for similarities of measures within a school compared with between schools (the intraclass correlation of measures within schools). This process gives tests that are robust to generalization to similar schools. P values were not adjusted for multiple testing. Identification of falsepositive differences is unlikely when the P values are quite small (<.01). In a few places, differences carrying P values in the range of .01 to .05 are described because the differences seem to fit a consistent picture and appear meaningful in terms of their magnitudes. Linear trend across levels of SES was an a priori hypothesis, and P values for linear trend are given in Tables 7 and 8 [triangle] [triangle]. Stratified analyses also were conducted in which the effects of race/ethnicity, grade, and SES were mutually adjusted. In general, adjusted analyses showed patterns similar to those of unadjusted analyses; therefore, data are not shown. All analyses were conducted with SAS, Release 6.12.24

TABLE 3
Percentages of Adolescent Girls and Boys Meeting Year 2010 Targets for Overweight Status and Nutrient and Food Intake
TABLE 4
School-Level Differences in Percentages of Adolescents Meeting Year 2010 Targets for Overweight Status and Nutrient and Food Intake
TABLE 5
Racial/Ethnic Differences in Percentages of Adolescent Girls Meeting Year 2010 Targets for Overweight Status and Nutrient and Food Intake
TABLE 6
Racial/Ethnic Differences in Percentages of Adolescent Boys Meeting Year 2010 Targets for Overweight Status and Nutrient and Food Intake
TABLE 7
Socioeconomic Differences in Percentages of Adolescent Girls Meeting Year 2010 Targets for Overweight Status and Nutrient and Food Intake
TABLE 8
Socioeconomic Differences in Percentages of Adolescent Boys Meeting Year 2010 Targets for Overweight Status and Nutrient and Food Intake

RESULTS

Overweight Status and Nutrient and Food Intake Among Adolescent Girls and Boys

Mean and median values for BMI and nutrient and food intake among adolescent girls and boys are shown in Table 2 [triangle]. Percentages of youths meeting the Healthy People 2010 targeted prevalence rates for BMI and nutrient patterns and comparisons across sex are shown in Table 3 [triangle]. Considerable gaps were seen between the existing prevalence rates for overweight status and nutrient and food patterns and the targeted 2010 prevalence rates. A large percentage of the population was overweight, and the percentages of youths consuming the recommended amounts of fat, calcium, fruits, vegetables, and grains were considerably lower than the targeted percentages.

Sex differences in overweight status were statistically significant; higher percentages of the boys, compared with the girls, had BMI values at or greater than the 95th percentile. Higher percentages of the girls, compared with the boys, were consuming 30% or less of their total energy from total fat and 10% or less of their energy from saturated fat (Table 3 [triangle]). Lower percentages of the girls were consuming the recommended amounts of calcium and grains, perhaps because of a higher energy intake among the boys (mean = 2252 ± 1111 cal) than among the girls (mean = 2014 ± 1015 cal). Sex differences in fruit and vegetable intake were small and generally were not statistically significant.

Overweight Status and Nutrient and Food Intake Across School Level

Prevalence rates of overweight status and nutrient and food intake behaviors were compared across students in middle schools and high schools (Table 4 [triangle]). Middle-school girls reported higher intakes of calcium, fruit, vegetables, and grains than did high-school girls. Among boys, large differences were not noted across school level. The only noteworthy differences were for fruit intake and combined fruit and vegetable intake, with higher levels among the middle-school boys than among the high-school boys. School-level differences were not found for overweight status or for fat intake among either boys or girls.

Overweight Status and Nutrient and Food Intake Across Race/Ethnicity

Large racial/ethnic differences were noted for overweight status and nutrient and food intake patterns (Tables 5 and 6 [triangle] [triangle]). Large racial/ethnic differences in overweight status in girls were found, with the lowest prevalence among Asian Americans and the highest prevalence among African Americans. Among boys, the highest prevalence of overweight status was among Native Americans, followed by Hispanics. African American girls and boys were the least likely to consume 30% or less of their total energy from total fat and 10% or less of their energy from saturated fat. Calcium intake was lowest among Asian American girls and boys. Fruit and vegetable intake was lowest among White girls and boys. Grain intake was lower among Asian American, White, and Native American girls and among Asian American and Hispanic boys compared with the other races/ethnicities.

Overweight Status and Nutrient and Food Intake Across SES

Patterns in overweight status and nutrient and food intake across SES were examined for overall differences and for trends (Tables 7 and 8 [triangle] [triangle]). Among girls, overall differences in overweight status across SES were statistically significant. Inverse linear trends were statistically significant for BMI values at or greater than the 85th percentile and marginal for BMI values at or greater than the 95th percentile, with lower percentages of overweight girls in the higher socioeconomic groups. It is noteworthy that overweight status tended to be highest among girls from middle and low-middle socioeconomic groups. Among boys, inverse linear trends in overweight status across SES were apparent. Boys of low SES were almost twice as likely to have BMI values at or greater than the 95th percentile as were boys of high SES.

Among both boys and girls, overall and linear trends between SES and fat intake were statistically significant; proportionally fewer youths of low SES were consuming 30% or less of their total energy from total fat and 10% or less of their energy from saturated fat than were youths of high SES. However, it is noteworthy that the percentage of youths with recommended fat intakes decreased with decreasing socioeconomic levels but tended to increase among the youths with the lowest SES. Statistically significant overall associations and linear trends also were found for calcium intake; girls and boys from lower SES backgrounds were less likely to be consuming 1300 mg or greater of calcium per day than were adolescents from higher SES backgrounds. Statistically significant differences were found for fruit intake and for combined fruit and vegetable intake, with the highest consumption levels among youths of high SES. For combined fruit and vegetable intake, the lowest level of consumption was among middle-class youths. Finally, there were statistically significant trends in grain intake across SES among girls and boys; youths of lower SES were less likely to consume 6 or more servings of grains per day than were youths of higher SES.

DISCUSSION

The findings clearly indicate large gaps between current prevalence rates of overweight status and nutrient and food intake among adolescents and targeted levels in Healthy People 2010.6 Findings from the current study, as well as previous studies on youths,17,18,25–27 further showed large disparities in prevalence rates across sociodemographic characteristics and point to the importance of developing interventions that meet the needs of youths from different backgrounds.

The differences found across race/ethnicity and SES are of concern, particularly the large disparities found in weight status. Racial/ethnic differences in overweight status suggest the importance of developing interventions that take into account the racial/ethnic differences in social norms regarding body shape, financial resources, support systems, and eating and physical activity patterns.

Findings from the current study clearly show that youths from high socioeconomic backgrounds are at decreased risk for being overweight, suggesting the importance of social and environmental factors in contributing to obesity onset. Socioeconomic differences in fat intake point to a need for interventions that reach youths and families from lower socioeconomic backgrounds and equality of access to lower-fat foods that appeal to teenagers. It is noteworthy that for several outcomes, youths with the lowest SES seemed to follow a different trend from that of the other groups. For example, fruit and vegetable intake was highest among youths of high SES, but the second highest intake levels were reported by the youths with the lowest SES. Furthermore, the percentage of youths eating 10% or less of their energy from saturated fat decreased with decreasing socioeconomic levels but tended to increase among the youths with the lowest SES. These patterns are clearly worthy of further exploration.

The strong associations between race/ethnicity and calcium intake are noteworthy; both interventions and assessment tools need to address racial/ethnic-specific sources of calcium (e.g., for Asian Americans).

The large sex differences in nutrient and food intake patterns suggest that different factors may be influencing eating patterns among adolescent girls and boys. These sex differences indicate a need for interventions that take into account the differing needs of adolescent girls and boys and suggest that it is important to stratify by sex in examining most adolescent eating patterns. Girls were more likely than boys to be consuming 30% or less of their total energy from fat but were far less likely to be consuming the recommended amounts of calcium or grains. These sex differences may be the result of higher prevalence rates of dieting for weight-control purposes among the girls than among the boys.10

In both sexes, fruit and vegetable intake decreased among the older adolescents. The decline in fruit and vegetable intake from middle school to high school found in the current study is of concern, in that other studies have shown that there tends to be an earlier decline from elementary school to middle school. Lytle and colleagues28 found that fruit consumption decreased by 41% between third and eighth grades and vegetable consumption decreased by 25%.

In the current study, school-level differences tended to be larger among the girls than among the boys and may be related to increasing weight concerns, because older girls were more likely than younger girls to be consuming 30% or less of their total energy from fat but were less likely to be consuming the recommended amounts of calcium or grains.

To achieve and assess some of the Healthy People 2010 targets (e.g., for deep yellow or dark green vegetables and whole grains), changes may be necessary in both interventions and assessment tools. To date, most interventions for adolescents have not focused specifically on increasing consumption of deep yellow or green vegetables and whole grains. It may be enough to aim for overall increases in fruits and vegetables (or grains), or it may be more desirable to specifically target deep yellow or green vegetables (or whole grains). To assess intake, dietary assessment tools will need to ask about specific types of vegetables (and grains) being consumed.

Strengths of this study include the large and population-based sample composed of adolescents from diverse SES and racial/ethnic backgrounds, the use of actual height and weight measurements, and the comprehensive assessment of nutrient and food intake with a validated instrument. The vast majority of previous studies on weight-related conditions and eating patterns among large population-based samples of adolescents have relied on self-reported height and weight measures and have included minimal questions on eating patterns.7,29,30 Project EAT was designed to address these limitations and provide a better picture of adolescent eating patterns.

However, the study also had some limitations that should be taken into account in interpreting the findings. Although the study sample was large and diverse, it was not a statewide or nationally representative sample; therefore, implications for other adolescent populations should be made with caution. The response rate of 81.5% was reasonably high, but we suspect that the nonresponders may have differed from those who completed the survey (e.g., increased absenteeism from school, lower English competency). Problems associated with assessing dietary intake with a food frequency questionnaire also need to be considered. For example, the Youth and Adolescent Food Frequency Questionnaire does not adequately assess racial/ethnic-specific foods (although foods not included in the questionnaire may be written in as “other” foods) or vegetables that are hidden within foods or eaten as mixed dishes (e.g., within soups or stews). Finally, the Youth and Adolescent Food Frequency Questionnaire does not include questions about specific types of grains consumed; therefore, in the current study we were not able to report data on whole-grain consumption.

The findings clearly suggest that much work is needed if the Healthy People 2010 objectives for nutrition and overweight are to be achieved among adolescents and if disparities across race/ethnicity and SES are to be reduced. It is encouraging that behaviors outlined in Healthy People 2000: National Health Promotion and Disease Prevention Objectives31 that have been targeted through public health interventions, such as total fat and saturated fat intake, appear to be improving. However, the standards set by Healthy People 2010 are high, and significant changes in educational, environmental, and social structures will be needed so to achieve these objectives.

Acknowledgments

The study was supported by grant MCJ-270834 (D. Neumark-Sztainer, principal investigator) from the Maternal and Child Health Bureau (Title V, Social Security Act), Health Resources and Service Administration, US Department of Health and Human Services.

The authors would like to acknowledge students and staff from the St. Paul, Minneapolis, and Osseo school districts for participating in the study. The authors also acknowledge Scott Mulert for his role in coordinating Project EAT and all the Project EAT research staff.

Notes

D. Neumark-Sztainer was responsible for study design and implementation and wrote the report. M. Story assisted with study design and implementation. P. J. Hannan was responsible for data analysis. J. Croll was involved in data collection and was responsible for quality control. All authors assisted in preparation of the article.

Peer Reviewed

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