Utilization Management of High-Cost Imaging in an Outpatient Setting in a Large Stable Patient and Provider Cohort over 7 Years.

Purpose To quantify the effect of a comprehensive, long-term, provider-led utilization management (UM) program on high-cost imaging (computed tomography, magnetic resonance imaging, nuclear imaging, and positron emission tomography) performed on an outpatient basis. Materials and Methods This retrospective, 7-year cohort study included all patients regularly seen by primary care physicians (PCPs) at an urban academic medical center. The main outcome was the number of outpatient high-cost imaging examinations per patient per year ordered by the patient's PCP or by any specialist. The authors determined the probability of a patient undergoing any high-cost imaging procedure during a study year and the number of examinations per patient per year (intensity) in patients who underwent high-cost imaging. Risk-adjusted hierarchical models were used to directly quantify the physician component of variation in probability and intensity of high-cost imaging use, and clinicians were provided with regular comparative feedback on the basis of the results. Observed trends in high-cost imaging use and provider variation were compared with the same measures for outpatient laboratory studies because laboratory use was not subject to UM during this period. Finally, per-member per-year high-cost imaging use data were compared with statewide high-cost imaging use data from a major private payer on the basis of the same claim set. Results The patient cohort steadily increased in size from 88 959 in 2007 to 109 823 in 2013. Overall high-cost imaging utilization went from 0.43 examinations per year in 2007 to 0.34 examinations per year in 2013, a decrease of 21.33% (P < .0001). At the same time, similarly adjusted routine laboratory study utilization decreased by less than half that rate (9.4%, P < .0001). On the basis of unadjusted data, outpatient high-cost imaging utilization in this cohort decreased 28%, compared with a 20% decrease in statewide utilization (P = .0023). Conclusion Analysis of high-cost imaging utilization in a stable cohort of patients cared for by PCPs during a 7-year period showed that comprehensive UM can produce a significant and sustained reduction in risk-adjusted per-patient year outpatient high-cost imaging volume. © RSNA, 2017.

Prospective study of adolescent alcohol consumption and risk of benign breast disease in young women.

OBJECTIVE: To investigate prospectively, using alcoholic beverage consumption data collected in real time, the association between adolescent drinking and risk of biopsy-confirmed benign breast disease (BBD) in young women. PARTICIPANTS AND METHODS: The Growing Up Today Study is a prospective cohort study of US girls, aged 9 to 15 years at baseline, with annual questionnaires from 1996 through 2001, followed by questionnaires in 2003, 2005, and 2007. On the 2003 survey, the participants (then aged 16-23 years) provided information about their alcoholic beverage consumption in the previous year. On the 2005 and 2007 surveys, a total of 6899 women (aged 18-27 years) reported whether a health care provider had ever diagnosed them with BBD (n = 147 cases) and whether it was confirmed by biopsy (n = 67 cases); 6752 women reported never being diagnosed with BBD. RESULTS: Adjusted for age and BMI, quantity of alcohol consumed was associated with increased risk of biopsy-confirmed BBD (odds ratio: 1.50 per drink per day [95% confidence interval: 1.19-1.90]). Girls who typically drank 6 or 7 days/week were at higher risk (odds ratio: 5.50 [95% confidence interval: 1.23-24.53]) compared with those who never drank or who drank less than once per week. CONCLUSIONS: Higher amounts consumed, and more frequent consumption, of alcoholic beverages in adolescence may increase the occurrence of BBD in young women. Advising teenagers to avoid alcoholic beverages, along with smoking and sun exposure, may reduce cancer incidence in adulthood.

Dairy consumption and female height growth: prospective cohort study.

BACKGROUND: Because of its nutrients and anabolic hormones, cow's milk may promote height growth, which in turn has been related to breast cancer risk. We prospectively investigated associations between dairy intakes and height growth. METHODS: A cohort of 5,101 girls from throughout the United States completed annual surveys (1996-2001, 2003), providing height, weight, and past-year diet. At baseline, all were premenarchal, ages 9 years and above, with no serious medical conditions. We studied three outcomes: annual height growth, peak growth velocity, and adult height. Multivariate models estimated the effects of milk, cheese, yogurt, and energy on subsequent growth, adjusted for race/ethnicity, age, prior height, and body mass index. Other models studied fats and proteins. RESULTS: Premenarchal girls who drank >3 servings per day of milk grew 0.11 in. (P = 0.02) more the following year than girls consuming <1 serving per day. Yogurt (+0.13 in./cup; P = 0.02), but not cheese or total calories, predicted height growth. In a separate model, dairy protein (+0.034 in./10 g; P < 0.001) predicted height growth. Larger peak velocities were seen among girls reporting, at baseline, more milk (>3 glasses per day versus <1; +0.14 in., P = 0.01), more yogurt (+0.17 in./cup, P = 0.02), and, in a separate model, more dairy protein (+0.039 in./10 g; P = 0.003). Baseline milk and dairy protein predicted taller adults. Dairy protein was more important than dairy fat, for all outcomes. Nondairy animal protein and vegetable protein were never significant, nor were nondairy animal fat and vegetable fat. CONCLUSION: Of the foods/nutrients studied, dairy protein had the strongest association with height growth. These findings suggest that a factor in the nonlipid phase of milk, but not protein itself, has growth-promoting action in girls.

Sexual orientation disparities in weight status in adolescence: findings from a prospective study.

A growing number of studies among adult women have documented disparities in overweight adversely affecting lesbian and bisexual women, but few studies have examined sexual orientation-related patterns in weight status among men or adolescents. We examined sexual orientation group trends in BMI (kg/m(2)), BMI Z-scores, and overweight using 56,990 observations from 13,785 adolescent females and males in the Growing Up Today Study (GUTS), a large prospective cohort of US youth. Participants provided self-reported information from six waves of questionnaire data collection from 1998 to 2005. Gender-stratified linear regression models were used to estimate BMI and BMI Z-scores and modified Poisson regression models to estimate risk ratios for overweight, controlling for age and race/ethnicity, with heterosexuals as the referent group. Among females, we observed fairly consistently elevated BMI in all sexual orientation minority groups relative to heterosexual peers. In contrast, among males we documented a sexual-orientation-by-age interaction indicating steeper increases in BMI with age from early-to-late adolescence in heterosexuals relative to sexual orientation minorities. Additional prospective research is needed to understand the determinants of observed sexual orientation disparities and to inform appropriate preventive and treatment interventions. The long-term health consequences of overweight are well-documented and over time are likely to exact a high toll on populations with elevated rates.

Weight gain in older adolescent females: the internet, sleep, coffee, and alcohol.

OBJECTIVES: To examine whether excessive recreational Internet time, insufficient sleep, regular coffee consumption, or alcoholic beverages promote weight gain. STUDY DESIGN: A longitudinal cohort of >5000 girls (Growing Up Today Study), from all over the United States and aged 14 to 21 years, returned surveys in 2001 reporting typical past-year recreational Internet time, sleep, coffee (with caffeine), and alcohol consumption. We estimated correlations among these 4 exposures. Each girl also reported her height and weight in 2000 and again in 2001. Multivariate models investigated associations between 1-year change in body mass index and same-year exposures, adjusted for adolescent growth/development, activity, and inactivity. RESULTS: The exposures were highly (P < .0001) correlated with each other, except for coffee with Internet time (P > .50). More Internet time, more alcohol, and less sleep were all associated (P < .05) with same-year increases in body mass index. Females, aged 18+ years, who slept

Comparison of a short food frequency questionnaire with the Youth/Adolescent Questionnaire in the Growing Up Today Study.

INTRODUCTION: Our purpose was to design and evaluate a shorter version of our 126-item food frequency questionnaire (long FFQ) for use with adolescents. A shorter FFQ is needed that can reliably rank research subjects according to their intakes of energy, macronutrients and selected micronutrients. METHODS: Dietary data were collected annually, for 3 years, using the full-list FFQ from 16 882 participants of the Growing Up Today Study (GUTS). From this full-list FFQ data, the top ten food contributors for energy and each macronutrient, and the top five food contributors for eight other selected micronutrients were compiled to create a 26-item (short-list) FFQ. Arithmetic means and Pearson correlations were computed to assess relationships between nutrient intakes estimated from the short- and full-list FFQs. We further compared both FFQs with three 24-hour recalls (approximately every 4 months over a 1-year period). Linear regression models were fitted, using energy and nutrients estimated from the short-list FFQ and separately from the full-list FFQ, to see how results may differ. RESULTS: As expected, mean nutrient values from the short-list FFQ were substantially below those from the full-list FFQ. Pearson correlations >0.85 between the short- and full-list FFQs were found for most nutrients. However, correlations between nutrients from the short-list FFQ and the three 24-hour recalls were lower (mean correlation =0.40) than the full-list FFQ. Linear regression models suggested that the short-list FFQ performed nearly as well as the full-list FFQ, for studying associations between energy and several nutrients (trans fatty acids, saturated fat, and glycemic load) and the non-dietary factor, TV viewing. Model betas for energy and nutrients from the short-list FFQ were slightly smaller than betas obtained from the full-list FFQ, but all were statistically significant. CONCLUSION: The short-list FFQ can assess nutrient values of a population for analytic research purposes, such as studying associations between certain dietary intakes and non-dietary factors.

Validation of adolescent diet recalled by adults.

BACKGROUND: Few studies have examined the validity of adolescent diet as recalled by adults many years later. METHODS: In this investigation, we examined the validity of a 124-item food frequency questionnaire (HS-FFQ) completed by 80 young adults in the United States about their diet during high school. We compared the HS-FFQ with 3 24-hour recalls and 2 food-frequency questionnaires (YAQ) collected 10 years earlier in 1993, when the participants were in high school. We calculated Pearson correlation coefficients for 20 to 25 nutrients and corrected these correlations for within-person variation. RESULTS: The average corrected correlation for energy-adjusted nutrient intakes calculated from the HS-FFQ and the 24-hour recalls was 0.45 (range = 0.16-0.68). The mean corrected correlation between the HS-FFQ and YAQs was 0.58 (range = 0.40-0.88). CONCLUSION: Taken together with the results of our earlier work, this analysis suggests that the HS-FFQ can reasonably capture adolescent diet recalled by young adults.

Breast-feeding and overweight in adolescence: within-family analysis [corrected].

BACKGROUND: Previous reports have found associations between having been breast-fed and a reduced risk of being overweight. These associations may be confounded by sociocultural determinants of both breast-feeding and obesity. We addressed this possibility by assessing the association of breast-feeding duration with adolescent obesity within sibling sets. METHODS: We surveyed 5,614 siblings age 9 to 14 years and their mothers. These children were a subset of participants in the Growing Up Today Study, in which we had previously reported an inverse association of breast-feeding duration with overweight. We compared the prevalence of overweight (body mass index exceeding the age-sex-specific 85th percentile) in siblings who were breast-fed longer than the mean duration of their sibship with those who were breast-fed for a shorter period. Then we compared odds ratios from this within-family analysis with odds ratios from an overall (ie, not within-family) analysis. RESULTS: Mean +/- standard deviation breast-feeding duration was 6.4 +/- 4.0 months, and crude prevalence of overweight was 19%. On average, siblings who were breast-fed longer than their family mean had breast-feeding duration 3.7 months longer than their shorter-duration siblings. The adjusted odds ratio (OR) for overweight among siblings with longer breast-feeding duration, compared with shorter duration, was 0.92 (95% confidence interval = 0.76-1.11). In overall analyses, the adjusted OR was 0.94 (0.88-1.00) for each 3.7-month increment in breast-feeding duration. CONCLUSION: The estimated OR for the within-family analysis was close to the overall estimate, suggesting that the apparent protective effect of breast-feeding on later obesity was not highly confounded by unmeasured sociocultural factors. A larger study of siblings, however, would be needed to confirm this conclusion.

Use of a food frequency questionnaire in American Indian and Caucasian pregnant women: a validation study.

BACKGROUND: Food frequency questionnaires (FFQs) have been validated in pregnant women, but few studies have focused specifically on low-income women and minorities. The purpose of this study was to examine the validity of the Harvard Service FFQ (HSFFQ) among low-income American Indian and Caucasian pregnant women. METHODS: The 100-item HSFFQ was administered three times to a sample of pregnant women, and two sets of 24-hour recalls (six total) were collected at approximately 12 and 28 weeks of gestation. The sample included a total of 283 pregnant women who completed Phase 1 of the study and 246 women who completed Phase 2 of the study. Deattenuated Pearson correlation coefficients were used to compare intakes of 24 nutrients estimated from the second and third FFQ to average intakes estimated from the week-12 and week-28 sets of diet recalls. RESULTS: Deattenuated correlations ranged from 0.09 (polyunsaturated fat) to 0.67 (calcium) for Phase 1 and from 0.27 (sucrose) to 0.63 (total fat) for Phase 2. Average deattenuated correlations for the two phases were 0.48 and 0.47, similar to those reported among other groups of pregnant women. CONCLUSION: The HSFFQ is a simple self-administered questionnaire that is useful in classifying low-income American Indian and Caucasian women according to relative dietary intake during pregnancy. Its use as a research tool in this population may provide important information about associations of nutrient intakes with pregnancy outcomes and may help to identify groups of women who would benefit most from nutritional interventions.

Association of consumption of fried food away from home with body mass index and diet quality in older children and adolescents.

OBJECTIVES: Rates of overweight have increased dramatically among children in the United States. Although an increase in consumption of food prepared away from home has paralleled overweight trends, few data exist relating food prepared away from home to change in BMI in children. The goals of this study were to (1) examine the cross-sectional and longitudinal associations between consumption of fried foods away from home (FFA) and BMI and (2) examine the cross-sectional associations between intake of FFA and several measures of diet quality. METHODS: We studied a cohort of 7745 girls and 6610 boys, aged 9 to 14 years, at baseline in 1996. We obtained BMI from self-reported height and weight, measures of diet quality from a food frequency questionnaire, and weekly servings of FFA during the previous year. We performed linear regression analyses to assess the longitudinal associations between change in consumption of FFA on change in BMI, using data from three 1-year periods from 1996 through 1999. We also related consumption of FFA with intake of selected foods and nutrients at baseline. RESULTS: In cross-sectional analyses, adjusting for potential confounders, mean (SE) BMI was 19.1 (0.13) among children who ate FFA "never or <1/week," 19.2 (0.13) among those who responded "1 to 3 times/week," and 19.3 (0.18) among those who responded "4 to 7 times/week." In longitudinal multivariate models, increasing (over 1 year) consumption of FFA "never or <1/week" to "4 to 7/week" was associated with increasing BMI (beta = 0.21 kg/m2; 95% confidence interval: 0.03-0.39) compared with those with low consumption of FFA at baseline and 1 year later. At baseline, frequency of eating FFA was associated with greater intakes of total energy, sugar-sweetened beverages, and trans fat, as well as lower consumption of low-fat dairy foods and fruits and vegetables. CONCLUSIONS: These data suggest that older children who consume greater quantities of FFA are heavier, have greater total energy intakes, and have poorer diet quality. Furthermore, increasing consumption of FFA over time may lead to excess weight gain.

Milk, dairy fat, dietary calcium, and weight gain: a longitudinal study of adolescents.

BACKGROUND: Milk is promoted as a healthy beverage for children, but some researchers believe that estrone and whey protein in dairy products may cause weight gain. Others claim that dairy calcium promotes weight loss. OBJECTIVE: To assess the associations between milk, calcium from foods and beverages, dairy fat, and weight change over time.Design, Subjects, and Outcome Measure We followed a cohort of 12 829 US children, aged 9 to 14 years in 1996, who returned questionnaires by mail through 1999. Children annually reported their height and weight and completed food frequency questionnaires regarding typical past-year intakes. We estimated associations between annual change in body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) and our dietary factors, adjusted for adolescent growth and development, race, physical activity, inactivity, and (in some models) total energy intake. RESULTS: Children who drank more than 3 servings a day of milk gained more in BMI than those who drank smaller amounts (boys: beta +/- SE, 0.076 +/- 0.038 [P = .04] more than those who drank 1 to 2 glasses a day; girls: beta +/- SE, 0.093 +/- 0.034 [P = .007] more than those who drank 0 to 0.5 glass a day). For boys, milk intake was associated with small BMI increases during the year (beta +/- SE, 0.019 +/- 0.009 per serving a day; P = .03); results were similar for girls (beta +/- SE, 0.015 +/- 0.007 per serving a day; P = .04). Quantities of 1% milk (boys) and skim milk (girls) were significantly associated with BMI gain, as was total dietary calcium intake. Multivariate analyses of milk, dairy fat, calcium, and total energy intake suggested that energy was the most important predictor of weight gain. Analyses of year-to-year changes in milk, calcium, dairy fat, and total energy intakes provided generally similar conclusions; an increase in energy intake from the prior year predicted BMI gain in boys (P = .003) and girls (P = .03). CONCLUSIONS: Children who drank the most milk gained more weight, but the added calories appeared responsible. Contrary to our hypotheses, dietary calcium and skim and 1% milk were associated with weight gain, but dairy fat was not. Drinking large amounts of milk may provide excess energy to some children.

Family dinner and adolescent overweight.

OBJECTIVE: The purpose of this study was to examine both cross-sectional and longitudinal associations between frequency of family dinner and overweight status in a large sample of 9- to 14-year-old children. RESEARCH METHODS AND PROCEDURES: We studied a cohort of 7784 girls and 6647 boys, 9 to 14 years of age at baseline in 1996, participating in the Growing Up Today Study. From annual mailed surveys, we calculated BMI from self-reported height and weight and assessed frequency of family dinner over the previous year. We defined "overweight" as age- and sex-specific BMI >85th percentile. We performed multiple logistic regression analyses; the longitudinal analyses assessed the association of previous year family dinner consumption with 1-year incidence of becoming overweight, using prospective data from 1996 through 1999. RESULTS: At baseline in 1996, 16% of participants had family dinner "never or some days," 40% on "most days," and 44% "every day." Across these categories, overweight prevalence for girls was 19.4%, 16.6%, and 16.7% and for boys was 24.6%, 23.3%, and 22.7%, respectively. In cross-sectional analyses, adjusting for potential confounders, the odds of being overweight was 0.85 [95% confidence interval (CI): 0.76, 0.96] among children who ate family dinner on "most days" or "every day" compared with those who ate family dinner "never or some days." In longitudinal multivariate models, the odds ratios between previous year frequency of eating family dinner and 1-year incidence of becoming overweight were 0.95 (95% CI: 0.78, 1.16) and 1.04 (95% CI: 0.85, 1.27) for children who ate family dinner on "most days" and "every day," respectively, compared with those who ate family dinner "never or some days." DISCUSSION: The frequency of eating family dinner was inversely associated with overweight prevalence at baseline but not with likelihood of becoming overweight in longitudinal analyses.

Modifying the Healthy Eating Index to assess diet quality in children and adolescents.

OBJECTIVE: The Healthy Eating Index (HEI) is a scoring system used by the US government to assess adherence to the Dietary Guidelines for Americans. We examined the ability of the HEI to monitor diet quality among youth. DESIGN: We modified and simplified the HEI for use by older children and adolescents. The new Youth Healthy Eating Index (YHEI) focuses on food quality and assesses both healthful and unhealthful foods and eating behaviors. Both HEI and YHEI scores were calculated from a food frequency questionnaire that was mailed to participants in the Growing Up Today Study in 1996. SUBJECTS/SETTING: Girls (n=8,807) and boys (n=7,645) 9 to 14 years of age who are children of participants in the Nurses Health Study II cohort and who reside across the United States. STATISTICAL ANALYSIS: Mean HEI and YHEI scores were calculated by sex and age, and associations with age, body mass index, activity, inactivity, energy intake, and several nutrients were assessed with Pearson correlations. Linear regression was used to examine the contributions of the individual HEI and YHEI components toward the total scores. RESULTS: The HEI score was highly correlated with total energy intake ( r =0.67), indicating a strong association with quantity of food consumption. In contrast, the YHEI was not strongly correlated with energy intake ( r =0.12) but was inversely associated with time spent in inactive pursuits ( r =-0.27). The HEI component for variety in food selection accounted for 60% of the variation in the total score and several HEI components were highly correlated with each other, particularly those for total and saturated fat ( r =0.78). CONCLUSIONS: To successfully monitor diet in a population of children and adolescents, the HEI may benefit from modifications that focus on food quality and include assessments of unhealthful foods. Further research is needed to determine the dietary elements that are most related to health in diverse populations of youth.

Sugar-added beverages and adolescent weight change.

OBJECTIVE: The increase in consumption of sugar-added beverages over recent decades may be partly responsible for the obesity epidemic among U.S. adolescents. Our aim was to evaluate the relationship between BMI changes and intakes of sugar-added beverages, milk, fruit juices, and diet soda. RESEARCH METHODS AND PROCEDURES: Our prospective cohort study included >10,000 boys and girls participating in the U.S. Growing Up Today Study. The participants were 9 to 14 years old in 1996 and completed questionnaires in 1996, 1997, and 1998. We analyzed change in BMI (kilograms per meter squared) over two 1-year periods among children who completed annual food frequency questionnaires assessing typical past year intakes. We studied beverage intakes during the year corresponding to each BMI change, and in separate models, we studied 1-year changes in beverage intakes, adjusting for prior year intakes. Models included all beverages simultaneously; further models adjusted for total energy intake. RESULTS: Consumption of sugar-added beverages was associated with small BMI gains during the corresponding year (boys: +0.03 kg/m2 per daily serving, p = 0.04; girls: +0.02 kg/m2, p = 0.096). In models not assuming a linear dose-response trend, girls who drank 1 serving/d of sugar-added beverages gained more weight (+0.068, p = 0.02) than girls drinking none, as did girls drinking 2 servings/d (+0.09, p = 0.06) or 3+ servings/d (+0.08, p = 0.06). Analyses of year-to-year change in beverage intakes provided generally similar findings; boys who increased consumption of sugar-added beverages from the prior year experienced weight gain (+0.04 kg/m2 per additional daily serving, p = 0.01). Children who increased intakes by 2 or more servings/d from the prior year gained weight (boys: +0.14, p = 0.01; girls +0.10, p = 0.046). Further adjusting our models for total energy intake substantially reduced the estimated effects, which were no longer significant. DISCUSSION: Consumption of sugar-added beverages may contribute to weight gain among adolescents, probably due to their contribution to total energy intake, because adjustment for calories greatly attenuated the estimated associations.

Relation between dieting and weight change among preadolescents and adolescents.

OBJECTIVE: To assess whether dieting to control weight was associated with weight change among children and adolescents. METHODS: A prospective study was conducted of 8203 girls and 6769 boys who were 9 to 14 years of age in 1996, were in an ongoing cohort study, and completed at least 2 annual questionnaires between 1996 and 1999. Dieting to control weight, binge eating, and dietary intake were assessed annually from 1996 through 1998 with instruments designed specifically for children and adolescents. The outcome measure was age- and sex-specific z score of body mass index (BMI). RESULTS: In 1996, 25.0% of the girls and 13.8% of the boys were infrequent dieters and 4.5% of the girls and 2.2% of the boys were frequent dieters. Among the girls, the percentage of dieters increased over the following 2 years. Binge eating was more common among the girls, but in both sexes, it was associated with dieting to control weight (girls: infrequent dieters, odds ratio [OR]: 5.10; frequent dieters, OR: 12.4; boys: infrequent dieters, OR: 3.49; frequent dieters, OR: 7.30). During 3 years of follow-up, dieters gained more weight than nondieters. Among the girls, frequency of dieting was positively associated with increases in age- and sex-specific z scores of BMI (beta = 0.05 and beta = 0.04 for frequent and infrequent dieters vs nondieters). Among the boys, both frequent and infrequent dieters gained 0.07 z scores of BMI more than nondieters. In addition, boys who engaged in binge eating gained significantly more weight than nondieters. CONCLUSIONS: Although medically supervised weight control may be beneficial for overweight youths, our data suggest that for many adolescents, dieting to control weight is not only ineffective, it may actually promote weight gain.

Evaluation of dietary assessment instruments in adolescents.

PURPOSE OF REVIEW: The obesity epidemic, the increasing occurrence of adult diseases in childhood, and the growing awareness of a connection between adult diseases and the diet of children and adolescents have led to increased interest in what our youth are eating. Designing an instrument to evaluate adolescents' eating habits requires addressing not only the typical requirements for a diet assessment tool but also the unique concerns of the adolescent population. We reviewed current dietary instruments for adolescents. RECENT FINDINGS: New nutrient assessment methods fall into one of two groups: instruments limited to a specific nutrient/food or those designed for a specific population. The new tools range from Food Intake Recording Software System, a computer program to assist individuals under 10 years of age in reporting their diets, to short food-frequency questionnaires specifically designed to assess fruits and vegetables or fat. Another new instrument uses picture cards to evaluate the entire diet of low-income, overweight African-Americans. The Youth Adolescent Questionnaire, although not a new tool, has been evaluated in new populations (multi-ethnic, multi-income, and multi-education) and with doubly labeled water. SUMMARY: A limited number of dietary assessment instruments that are specifically designed for adolescents have been found to be reproducible and validated. There is a demand for a short, easily administered, inexpensive, accurate instrument that can be used in a broad range of adolescent subpopulations. Future tools will need to meet these criteria and evaluate the 'new' nutrients, foods, and other factors that lead our youth to eat the foods they do.

One-year changes in activity and in inactivity among 10- to 15-year-old boys and girls: relationship to change in body mass index.

OBJECTIVE: Cross-sectional studies have suggested that children who were less physically active and children who watched more television (TV) had more excess body weight, but no large nationwide longitudinal studies have addressed whether children who change their personal levels of activity or inactivity, from one year to the next, experience changes in adiposity. Our objective is to study the association between change in body mass index (BMI) over 1 year and same year change in recreational physical activity and change in recreational inactivity (TV/videos/video games). DESIGN: Cohort study using data from 2 mailed questionnaires, 1 year apart. PARTICIPANTS: A total of 11 887 boys and girls, aged 10 to 15, who returned questionnaires in both 1997 and 1998 as part of the Growing Up Today Study. Outcome Measure. Change in BMI from 1997-1998, accounting for increases in BMI associated with growth and development. RESULTS: An increase in physical activity from 1997-1998 was associated with decreasing relative BMI in girls (-0.06 kg/m2 per hour increase in daily activity; 95% confidence interval [CI]: -0.11, -0.01) and in overweight boys (-0.22 kg/m2; CI: -0.33, -0.10). An increase in inactivity was associated with increasing BMI in girls (+0.05 kg/m2 per hour increase in daily TV/videos/video games; CI: +0.02, +0.08). Effects were generally stronger among overweight children. Increasing time doing aerobics/dancing and walking were associated with BMI declines for some groups of children. CONCLUSIONS: Many children may benefit by increasing their physical activity and by reducing time watching TV or videos and playing video games. In particular, 2 activities accessible to most children, aerobics/dancing and walking, also appeared beneficial.