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RESEARCH AND PRACTICE |
The authors are with the Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis.
Correspondence: Requests for reprints should be sent to Dianne NeumarkSztainer, PhD, MPH, RD, Division of Epidemiology, School of Public Health, University of Minnesota, 1300 S Second St, Suite 300, Minneapolis, MN 55454 (e-mail: neumark{at}epi.umn.edu).
| ABSTRACT |
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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 1118 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.
| INTRODUCTION |
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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
). 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.
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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 |
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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 78) and high school (grades 912). 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
, 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.
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| RESULTS |
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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
). 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
). 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![]()
). 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![]()
). 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 |
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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 |
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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.
| Footnotes |
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Peer Reviewed
Accepted for publication January 28, 2001.
| References |
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2. The Surgeon General's Report on Nutrition and Health. Washington, DC: US Public Health Service, Office of the Surgeon General; 1988.
3.
Sandler RB, Slemenda CW, LaPorte RE, et al. Postmenopausal bone density and milk consumption in childhood and adolescence. Am J Clin Nutr. 1985;42:270274.
4. Rees JM. Eating disorders. In: Mahan LK, Rees JM, eds. Nutrition in Adolescence. St. Louis, Mo: Times Mirror/Mosby College Publisher; 1984:104137.
5. Story M, Neumark-Sztainer D. School-based nutrition education programs and services for adolescents. Adolesc Med State Art Rev. 1996;7:287302.
6. Healthy People 2010. Washington, DC: US Dept of Health and Human Services; 2000.
7. Neumark-Sztainer D, Story M, Resnick MD, Blum RW. Lessons learned about adolescent nutrition from the Minnesota Adolescent Health Survey. J Am Diet Assoc. 1998;98:14491456.[Medline]
8. Neumark-Sztainer D, Story M, Hannan PJ, Beuhring T, Resnick MD. Disordered eating among adolescents: associations with sexual/physical abuse and other familial/psychosocial factors. Int J Eat Disord. 2000;28:249258.[Medline]
9. Centers for Disease Control and Prevention. Youth risk behavior surveillanceUnited States, 1999. MMWR Morb Mortal Wkly Rep.2000;49:189.[Medline]
10. Neumark-Sztainer D, Story M, Falkner NH, Beuhring T, Resnick MD. Sociodemographic and personal characteristics of adolescents engaged in weight loss and weight/muscle gain behaviors: who is doing what? Prev Med. 1999;28:4050.[Medline]
11. Cusatis DC, Shannon BM. Influences on adolescent eating behavior. J Adolesc Health. 1996;18:2734.[Medline]
12. Sweeting H, Anderson A, West P. Sociodemographic correlates of dietary habits in mid-to-late adolescence. Eur J Clin Nutr. 1994;48:736748.[Medline]
13. Kenney MA, McCoy JH, Kirby AL, et al. Nutrients supplied by food groups in diets of teenaged girls. J Am Diet Assoc. 1986;86:15491555.[Medline]
14. Anderson AS, MacIntyre S, West P. Dietary patterns among adolescents in the west of Scotland. Br J Nutr. 1994;71:111122.[Medline]
15. Crawley HF. The energy, nutrient and food intakes of teenagers aged 1617 years in Britain, 1: energy, macronutrients and non-starch polysaccharides. Br J Nutr. 1993;70:1526.[Medline]
16. Barr SI. Associations of social and demographic variables with calcium intakes of high school students. J Am Diet Assoc. 1994;94:260266, 269.[Medline]
17. US Dept of Agriculture. Food and Nutrient Intakes by Children 199496, 1998. Beltsville, Md: ARS Food Surveys Research Group; 1999.
18.
Munoz KA, Krebs-Smith SM, Ballard-Barbash R, Cleveland LE. Food intakes of US children and adolescents compared with recommendations [published erratum appears in Pediatrics.1998;101:952953]. Pediatrics. 1997;100:323329.
19.
Himes JH, Dietz WH. Guidelines for overweight in adolescent preventive services: recommendations from an expert committee. Am J Clin Nutr. 1994;59:307316.
20. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, et al. CDC Growth Charts: United States. Hyattsville, Md: National Center for Health Statistics; 2000. Advance Data From Vital and Health Statistics, No. 314.
21. Rockett HRH, Breitenbach MA, Frazier AL, et al. Validation of a youth/adolescent food frequency questionnaire. Prev Med. 1997;26:808816.[Medline]
22. Rockett HR, Wolf AM, Colditz GA. Development and reproducibility of a food frequency questionnaire to assess diets of older children and adolescents. J Am Diet Assoc. 1995;95:336340.[Medline]
23. Breiman L, Friedman J, Olshen R, Stone C. Classification and Regression Trees. Belmont, Calif: Wadsworth International Group; 1984.
24. SAS/STAT Software: Changes and Enhancements, Release 6.12. Cary, NC: SAS Institute Inc; 1997.
25.
Troiano RP, Flegal KM. Overweight children and adolescents: description, epidemiology, and demographics. Pediatrics. 1998;101:497504.
26. Neumark-Sztainer D, Story M, Resnick MD, Blum RW. Correlates of inadequate fruit and vegetable consumption among adolescents. Prev Med. 1996;25:497505.[Medline]
27. Neumark-Sztainer D, Story M, Dixon LB, Resnick M, Blum R. Correlates of inadequate consumption of dairy products among adolescents. J Nutr Educ. 1997;29:1220.
28. Lytle LA, Seifert S, Greenstein J, McGovern P. How do children's eating patterns and food choices change over time? Results from a cohort study. Am J Health Promot. 2000;14:222228.[Medline]
29. Story M, Neumark-Sztainer D, Sherwood N, Stang J, Murray D. Dieting status and its relationship to eating and physical activity behaviors in a representative sample of US adolescents. J Am Diet Assoc. 1998;98:11271135, 1255.[Medline]
30. Neumark-Sztainer D, Story M, French S, Hannan P, Resnick M, Blum RW. Psychosocial concerns and health compromising behaviors among overweight and non-overweight adolescents. Obes Res. 1997;5:237249.[Medline]
31. Healthy People 2000: National Health Promotion and Disease Prevention Objectives. Washington, DC: US Dept of Health and Human Services; 1991. DHHS publication PHS 91-50212.
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