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Many research questions focused on characterizing usual, or long-term average, dietary intake of populations and subpopulations rely on short-term intake data. The objective of this paper is to review key assumptions, statistical techniques, and considerations underpinning the use of short-term dietary intake data to make inference about usual dietary intake. The focus is on measurement error and strategies to mitigate its effects on estimated characteristics of population-level usual intake, with attention to relevant analytic issues such as accounting for survey design. Key assumptions are that short-term assessments are subject to random error only (i.e., unbiased for individual usual intake) and that some aspects of the error structure apply to all respondents, allowing estimation of this error structure in data sets with only a few repeat measures per person. Under these assumptions, a single 24-hour dietary recall per person can be used to estimate group mean intake; and with as little as one repeat on a subsample and with more complex statistical techniques, other characteristics of distributions of usual intake, such as percentiles, can be estimated. Related considerations include the number of days of data available, skewness of intake distributions, whether the dietary components of interest are consumed nearly daily by nearly everyone or episodically, the number of correlated dietary components of interest, time-varying nuisance effects related to day of week and season, and variance estimation and inference. Appropriate application of assumptions and recommended statistical techniques allows researchers to address a range of research questions, though it is imperative to acknowledge systematic error (bias) in short-term data and its implications for conclusions., (Copyright © 2022 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Background: Socioeconomic inequities in diet quality are stable or widening in the United States; however, these trends have not been well characterized in other nations. Moreover, purpose-developed indices of inequities that can provide a more comprehensive and precise perspective of trends in absolute and relative dietary gaps and gradients using multiple indicators of socioeconomic position (SEP) have not yet been used, and can inform strategies to narrow dietary inequities., Objectives: We quantified nationally representative trends in absolute and relative gaps and gradients in diet quality between 2004 and 2015 according to 3 indicators of SEP among adults in Canada., Methods: Adults (≥18 y old) who participated in the nationally representative, cross-sectional Canadian Community Health Survey-Nutrition in 2004 (n = 20,880) or 2015 (n = 13,970) were included. SEP was classified using household income (quintiles), education (5 categories), and neighborhood deprivation (quintiles). Dietary intake data from 24-h recalls were used to derive Healthy Eating Index-2015 (HEI-2015) scores. Dietary inequities were quantified using absolute and relative gaps (between the most and least disadvantaged) and absolute [Slope Index of Inequality (SII)] and relative gradients (Relative Index of Inequality). Overall and sex-stratified multivariable linear regression and generalized linear models examined trends in HEI-2015 scores between 2004 and 2015., Results: Mean HEI-2015 scores improved from 55.3 to 59.0 (maximum: 100); however, these trends were not consistently equitable. Whereas inequities in HEI-2015 scores were stable in the total population and in females, the absolute gap [from 1.60 (95% CI: 0.09, 3.10) to 4.27 (95% CI: 2.20, 6.34)] and gradient [from SII = 2.09 (95% CI: 0.45, 3.73) to SII = 4.84 (95% CI: 2.49, 7.20)] in HEI-2015 scores for household income, and the absolute gradient for education [from SII = 8.06 (95% CI: 6.41, 9.71) to SII = 10.52 (95% CI: 8.73, 12.31)], increased in males., Conclusions: Absolute and relative gaps and gradients in overall diet quality remained stable or widened between 2004 and 2015 among adults in Canada., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Interventions are urgently needed to transform the food system and shift population eating patterns toward those consistent with human health and environmental sustainability. Postsecondary campuses offer a naturalistic setting to trial interventions to improve the health of students and provide insight into interventions that could be scaled up in other settings. However, the current state of the evidence on interventions to support healthy and environmentally sustainable eating within postsecondary settings is not well understood. A scoping review of food- and nutrition-related interventions implemented and evaluated on postsecondary campuses was conducted to determine the extent to which they integrate considerations related to human health and/or environmental sustainability, as well as to synthesize the nature and effectiveness of interventions and to identify knowledge gaps in the literature. MEDLINE (via PubMed), CINAHL, Scopus, and ERIC were searched to identify articles describing naturalistic campus food interventions published in English from January 2015 to December 2019. Data were extracted from 38 peer-reviewed articles, representing 37 unique interventions, and synthesized according to policy domains within the World Cancer Research Foundation's NOURISHING framework. Most interventions were focused on supporting human health, whereas considerations related to environmental sustainability were minimal. Interventions to support human health primarily sought to increase nutrition knowledge or to make complementary shifts in food environments, such as through nutrition labeling at point of purchase. Interventions to support environmental sustainability often focused on reducing food waste and few emphasized consumption patterns with lower environmental impacts. The implementation of integrated approaches considering the complexity and interconnectivity of human and planetary health is needed. Such approaches must go beyond the individual to alter the structural determinants that shape our food system and eating patterns., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Intervention: This study examined whether the impacts of sugar taxes and front-of-pack (FOP) nutrition labels differ across socio-demographic subgroups., Research Question: What are the main and moderating effects of individual-level characteristics on the nutrient content of participants' purchases in response to varying taxation levels and FOP labels?, Methods: Data from an experimental marketplace were analyzed. A sample of 3584 Canadians aged 13 years and older received $5 to purchase an item from a selection of 20 beverages and 20 snack foods. Participants were shown products with one of five FOP labels and completed eight within-subject purchasing tasks with different tax conditions. Linear mixed models were used to estimate the main and moderating effects of 11 individual-level variables on the sugars, sodium, saturated fats, and calorie content of participants' purchases., Results: Participants who were younger, male, and more frequent consumers of sugary drinks purchased products containing more sugars, sodium, saturated fats, and calories. Sex and age moderated the relationship between tax condition and sugars or calories purchased: female participants were more responsive than males to a tax that included fruit juice, and younger participants were more responsive to all sugar tax conditions than older participants. Reported thirst and education level also moderated the relationship between tax condition and calories purchased. No individual-level characteristics moderated the effects of FOP labels., Conclusion: A small proportion (7 of 176) of the moderating effects tested in this study were significant. Sugar taxes and FOP labelling policies may therefore produce similar effects across key socio-demographic groups.

Objective: This study explored associations between socio-demographic characteristics, self-reported health, and household food security among young adults., Methods: National cohort study participants from Toronto, Montreal, Vancouver, Edmonton, and Halifax, Canada, aged 16-30 years (n = 2149) completed online surveys. Multinomial logistic regression, weighted to reflect age and sex proportions from the 2016 census, was conducted to examine associations between food security status and covariates., Results: Almost 30% of respondents lived in food-insecure households, with 19% in "moderately" food-insecure and 10% in "severely" food-insecure households. Respondents identifying as Black or Indigenous were more likely to live in moderately (AOR = 1.96, CI: 1.10, 3.50; AOR = 3.15, CI: 1.60, 6.20) and severely (AOR = 4.25, CI: 2.07, 8.74; AOR = 6.34, CI: 2.81, 14.30) food-insecure households compared with those identifying as mixed/other ethnicity. Respondents who found it "very difficult" to make ends meet were more likely to be moderately (AOR = 20.37, CI: 11.07, 37.46) and severely (AOR = 101.33, CI: 41.11, 249.77) food insecure. Respondents classified as "normal" weight (AOR = 0.64, CI: 0.43, 0.96) or overweight (AOR = 0.53, CI: 0.34, 0.83) were less likely to be moderately food insecure compared with those affected by obesity. Compared with "very good or excellent," "poor" health, diet quality, and mental health were each positively associated with severe food insecurity (AOR = 7.09, CI: 2.44, 20.61; AOR = 2.63, CI: 1.08, 6.41; AOR = 2.09, CI: 1.03, 4.23, respectively)., Conclusion: The high prevalence of correlates of food insecurity among young adults suggests the need for policies that consider the unique challenges (e.g., precarious income) and vulnerability associated with this life stage.

Background: Existing nutrition knowledge measures tend to be lengthy or tailored for specific contexts, making them unsuitable for population-based surveys. Given the growing emphasis within country-specific dietary guidelines on reducing consumption of highly processed foods, consumers' ability to understand and apply principles related to level of food processing could serve as a proxy measure of general nutrition knowledge., Objective: To examine the content validity of the Food Processing Knowledge (FoodProK) score based on subject matter expert consultation with Registered dietitian nutritionists (RDNs)., Methods: RDNs in Canada (n = 64) completed an online survey, including the FoodProK, in January 2020. Participants rated the "healthiness" of 12 food products from four categories (fruit, meat, dairy, and grains) on a scale from 1 to 10. FoodProK scores were assigned based on concordance of ratings within each food category, with rankings according to the NOVA classification system, with less processed foods representing higher healthiness. For each category, one-way repeated-measures analysis of variance models tested whether the three product ratings were significantly different from one another. Descriptive statistics compared ratings and FoodProK scores across categories. Open-ended feedback was solicited to assess face validity of the score., Results: RDNs' FoodProK scores were strongly associated with level of food processing. Almost one in three RDNs received perfect FoodProK scores, and the mean score was 7.0 of 8.0 possible points. Within each category, the three foods received significantly different healthiness ratings, in the same order as the NOVA system (P < 0.001 for all contrasts). Open-ended responses showed that RDNs did not perceive meaningful differences between the processed meat products, suggesting the need to change one of the products in the meat category. Overall, 80% of RDNs reported level of processing as an important indicator of the healthiness of foods., Conclusions: Level of food processing represents a promising framework for assessing general nutrition knowledge in population-based surveys., (Copyright © 2021 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Background: All self-reported dietary intake data are characterized by measurement error, and validation studies indicate that the estimation of energy intake (EI) is particularly affected., Methods: Using self-reported food frequency and physical activity data from Alberta's Tomorrow Project participants (n = 9847 men 16,241 women), we compared the revised-Goldberg and the predicted total energy expenditure methods in their ability to identify misreporters of EI. We also compared dietary patterns derived by k-means clustering under different scenarios where misreporters are included in the cluster analysis (Inclusion); excluded prior to completing the cluster analysis (ExBefore); excluded after completing the cluster analysis (ExAfter); and finally, excluded before the cluster analysis but added to the ExBefore cluster solution using the nearest neighbor method (InclusionNN)., Results: The predicted total energy expenditure method identified a significantly higher proportion of participants as EI misreporters compared to the revised-Goldberg method (50% vs. 47%, p < 0.0001). k-means cluster analysis identified 3 dietary patterns: Healthy, Meats/Pizza and Sweets/Dairy. Among both men and women, participants assigned to dietary patterns changed substantially between ExBefore and ExAfter and also between the Inclusion and InclusionNN scenarios (Hubert and Arabie's adjusted Rand Index, Kappa and Cramer's V statistics < 0.8)., Conclusions: Different scenarios used to account for EI misreporters influenced cluster analysis and hence the composition of the dietary patterns. Continued efforts are needed to explore and validate methods and their ability to identify and mitigate the impact of EI misestimation in nutritional epidemiology.

Language focused on individual dietary behaviors, or alternatively, lifestyle choices or decisions, suggests that what people eat and drink is primarily a choice that comes down to free will. Referring to and intervening upon food consumption as though it were a freely chosen behavior has an inherently logical appeal due to its simplicity and easily defined targets of intervention. However, despite decades of behavioral interventions, population-level patterns of food consumption remain suboptimal. This debate paper interrogates the manner in which language frames how problems related to poor diet quality are understood and addressed within society. We argue that referring to food consumption as a behavior conveys the idea that it is primarily a freely chosen act that can be ameliorated through imploring and educating individuals to make better selections. Leveraging practice theory, we subsequently propose that using the alternative language of eating practices and patterns better conveys the socially situated nature of food consumption. This language may therefore point to novel avenues for intervention beyond educating and motivating individuals to eat more healthfully, to instead focus on creating supportive contexts that enable sustained positive dietary change. Clearly, shifting discourse will not on its own transform the science and practice of nutrition. Nevertheless, the seeds of change may lie in aligning our terminology, and thus, our framing, with desired solutions.

When causal inference is of primary interest, a range of target parameters can be chosen to define the causal effect, such as average treatment effects (ATEs). However, ATEs may not always align with the research question at hand. Furthermore, the assumptions needed to interpret estimates as ATEs, such as exchangeability, consistency, and positivity, are often not met. Here, we present the incremental propensity score (PS) approach to quantify the effect of shifting each person's exposure propensity by some predetermined amount. Compared with the ATE, incremental PS may better reflect the impact of certain policy interventions and do not require that positivity hold. Using the Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-be (nuMoM2b), we quantified the relationship between total vegetable intake and the risk of preeclampsia and compared it to average treatment effect estimates. The ATE estimates suggested a reduction of between two and three preeclampsia cases per 100 pregnancies for consuming at least half a cup of vegetables per 1,000 kcal. However, positivity violations obfuscate the interpretation of these results. In contrast, shifting each woman's exposure propensity by odds ratios ranging from 0.20 to 5.0 yielded no difference in the risk of preeclampsia. Our analyses show the utility of the incremental PS effects in addressing public health questions with fewer assumptions., Competing Interests: The authors report no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Careful consideration of the validity and reliability of methods intended to assess dietary intake is central to the robustness of nutrition research. A dietary assessment method with high validity is capable of providing useful measurement for a given purpose and context. More specifically, a method with high validity is well grounded in theory; its performance is consistent with that theory; and it is precise, dependable, and accurate within specified performance standards. Assessing the extent to which dietary assessment methods possess these characteristics can be difficult due to the complexity of dietary intake, as well as difficulties capturing true intake. We identified challenges and best practices related to the validation of self-report dietary assessment methods. The term validation is used to encompass various dimensions that must be assessed and considered to determine whether a given method is suitable for a specific purpose. Evidence on the varied concepts of validity and reliability should be interpreted in combination to inform judgments about the suitability of a method for a specified purpose. Self-report methods are the focus because they are used in most studies seeking to measure dietary intake. Biomarkers are important reference measures to validate self-report methods and are also discussed. A checklist is proposed to contribute to strengthening the literature on the validation of dietary assessment methods and ultimately, the nutrition literature more broadly., (Copyright © 2019 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Background: Caffeine is a widely consumed stimulant, and caffeine-containing products are increasingly available on the market. Few tools are available to capture caffeine intake, particularly among young adults. To estimate caffeine consumption in the previous 24 hours, the 24-Hour Caffeine Intake Recall (CIR-24) was modeled after the Automated Self-Administered 24-Hour Dietary Assessment Tool, using a brand-specific database of caffeine-containing foods, beverages, and supplements., Objective: To evaluate the accuracy of the CIR-24 compared with caffeine concentration biomarkers in urine and a caffeinated beverage intake frequency screener (CBQ) designed to assess usual intake among a young adult population in Canada., Design/participants: In all, 79 young adults, aged 18 to 29 years, provided 24-hour urine samples and completed the CIR-24 and CBQ., Main Outcome Measures: Excretion for caffeine and eight caffeine metabolites were quantified from urine samples using high-performance liquid chromatography-polarity switching electrospray ionization-tandem quadrupole mass spectrometry with stable isotope-labeled internal standards., Statistical Analyses Performed: Pearson correlations and weighted κ coefficients were calculated for the self-report tools and caffeine biomarkers., Results: The CIR-24 was significantly positively associated with all caffeine biomarkers (r p =0.28 to 0.52, κ=0.39 to 0.59), and the CBQ was significantly positively associated with all but one biomarker (r p =0.21 to 0.40, κ=0.32 to 0.45). The CIR-24 yielded a higher mean intake of caffeine than the CBQ. There was strong linear correlation between the CIR-24 and CBQ (r p =0.60, P<0.001), but poor agreement in absolute caffeine consumed (t=2.83, P=0.006); quartile ranking concordance was 0.44 (P<0.001). The CIR-24 performed better than the CBQ across all biomarkers in both linear correlation and quartile ranking., Conclusions: Although both the CIR-24 and CBQ performed reasonably well in capturing caffeine intake compared with urinary biomarkers of caffeine consumption, the CIR-24 had stronger agreement than the CBQ. The results suggest that the CIR-24 is a promising tool for evaluating caffeine intake among this population., (Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

The Healthy Eating Index (HEI) is a measure for assessing whether a set of foods aligns with the Dietary Guidelines for Americans (DGA). An updated HEI is released to correspond to each new edition of the DGA, and this article introduces the latest version, which reflects the 2015-2020 DGA. The HEI-2015 components are the same as in the HEI-2010, except Saturated Fat and Added Sugars replace Empty Calories, with the result being 13 components. The 2015-2020 DGA include explicit recommendations to limit intakes of both Added Sugars and Saturated Fats to <10% of energy. HEI-2015 does not account for excessive energy from alcohol within a separate component, but continues to account for all energy from alcohol within total energy (the denominator for most components). All other components remain the same as for HEI-2010, except for a change in the allocation of legumes. Previous versions of the HEI accounted for legumes in either the two vegetable or the two protein foods components, whereas HEI-2015 counts legumes toward all four components. Weighting approaches are similar to those of previous versions, and scoring standards were maintained, refined, or developed to increase consistency across components; better ensure face validity; follow precedent; cover a range of intakes; and, when applicable, ensure the DGA level corresponds to a score >7 out of 10. HEI-2015 component scores can be examined collectively using radar graphs to reveal a pattern of diet quality and summed to represent overall diet quality., (Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Background: The Healthy Eating Index (HEI), a diet quality index that measures alignment with the Dietary Guidelines for Americans, was updated with the 2015-2020 Dietary Guidelines for Americans., Objective and Design: To evaluate the psychometric properties of the HEI-2015, eight questions were examined: five relevant to construct validity, two related to reliability, and one to assess criterion validity., Data Sources: Three data sources were used: exemplary menus (n=4), National Health and Nutrition Examination Survey 2011-2012 (N=7,935), and the National Institutes of Health-AARP (formally known as the American Association of Retired Persons) Diet and Health Study (N=422,928)., Statistical Analyses: Exemplary menus: Scores were calculated using the population ratio method. National Health and Nutrition Examination Survey 2011-2012: Means and standard errors were estimated using the Markov Chain Monte Carlo approach. Analyses were stratified to compare groups (with t tests and analysis of variance). Principal components analysis examined the number of dimensions. Pearson correlations were estimated between components, energy, and Cronbach's coefficient alpha. National Institutes of Health-AARP Diet and Health Study: Adjusted Cox proportional hazards models were used to examine scores and mortality outcomes., Results: For construct validity, the HEI-2015 yielded high scores for exemplary menus as four menus received high scores (87.8 to 100). The mean score for National Health and Nutrition Examination Survey was 56.6, and the first to 99th percentile were 32.6 to 81.2, respectively, supporting sufficient variation. Among smokers, the mean score was significantly lower than among nonsmokers (53.3 and 59.7, respectively) (P<0.01), demonstrating differentiation between groups. The correlation between diet quality and diet quantity was low (all <0.25) supporting these elements being independent. The components demonstrated multidimensionality when examined with a scree plot (at least four dimensions). For reliability, most of the intercorrelations among the components were low to moderate (0.01 to 0.49) with a few exceptions, and the standardized Cronbach's alpha was .67. For criterion validity, the highest vs the lowest quintile of HEI-2015 scores were associated with a 13% to 23% decreased risk of all-cause, cancer, and cardiovascular disease mortality., Conclusions: The results demonstrated evidence supportive of construct validity, reliability, and criterion validity. The HEI-2015 can be used to examine diet quality relative to the 2015-2020 Dietary Guidelines for Americans., (Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

The Healthy Eating Index (HEI) is a measure of diet quality that can be used to examine alignment of dietary patterns with the Dietary Guidelines for Americans. The HEI is made up of multiple adequacy and moderation components, most of which are expressed relative to energy intake (ie, as densities) for the purpose of calculating scores. Due to these characteristics and the complexity of dietary intake data more broadly, calculating and using HEI scores can involve unique statistical considerations and, depending on the particular application, intensive computational methods. The objective of this article is to review potential applications of the HEI, including those relevant to surveillance, epidemiology, and intervention research, and to summarize available guidance for appropriate analysis and interpretation. Steps in calculating HEI scores are reviewed and statistical methods described. Consideration of salient issues in the calculation and interpretation of scores can help researchers avoid common pitfalls and reviewers ensure that articles reporting on the use of the HEI include sufficient details such that the work is comprehensible and replicable, with the overall goal of contributing to knowledge on dietary patterns and health among Americans., (Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Evidence suggests associations between weight management intentions, weight perceptions, and health-compromising behaviours among adolescent girls. Drawing on cross-sectional data for 21,456 girls, we employed multinomial logistic regression to examine whether smoking, binge drinking, and breakfast-skipping were associated with weight management intentions and weight perceptions. According to self-reported heights and weights, 61.4% of girls were in the healthy weight category. However, most reported trying to manage their weight, with 58% trying to lose, 4.5% trying to gain, and 18% trying to maintain their weight. Smokers were more likely than non-smokers to report intentions to lose, gain, or maintain weight versus to do nothing. However, smokers were less likely than non-smokers to perceive themselves as underweight or overweight versus about the right weight. Binge drinkers were more likely than other girls to report an intention to gain and less likely to be trying to maintain their weight versus doing nothing, and breakfast-skippers were more likely to report trying to lose or gain weight but less likely to report trying to maintain weight versus doing nothing. Binge drinkers and breakfast-skippers were more likely than non-binge drinkers and non-breakfast-skippers, respectively, to perceive themselves as underweight, overweight or very overweight versus about the right weight. In sum, the majority of girls reported trying to manage their weight, and those engaging in other health-compromising behaviours were more likely to do so, though the exact nature of the associations differed by behaviour. Recognition of shared underlying risk factors for this clustering of behaviours may inform comprehensive health promotion efforts.

Background: The Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24) includes a highly standardized multipass web-based recall that, like the Automated Multiple Pass Method (AMPM), captures detailed information about dietary intake using multiple probes and reminders to enhance recall of intakes. The primary distinction between ASA24 and AMPM is that the ASA24 user interface guides participants, thus removing the need for interviewers., Objective: The objective of this study was to compare dietary supplement use reported on self-administered (ASA24-2011) vs interviewer-administered (AMPM) 24-hour recalls., Design: The Food Reporting Comparison Study was an evaluation study designed to compare self-reported intakes captured using the self-administered ASA24 vs data collected via interviewer-administered AMPM recalls. Between 2010 and 2011, 1081 women and men were enrolled from three integrated health care systems that belong to the National Cancer Institute-funded Cancer Research Network: Security Health Plan Marshfield Clinic, Wisconsin; Henry Ford Health System, Michigan; and Kaiser Permanente Northern California, California. Quota sampling was used to ensure a balance of age, sex, and race/ethnicity. Participants were randomly assigned to four groups, and each group was asked to complete two dietary recalls: group 1, two ASA24s; group 2, two AMPMs; group 3, ASA24 first and AMPM second; and group 4, AMPM first and ASA24 second. Dietary supplements were coded using the 2007-2008 National Health and Nutrition Examination Survey Dietary Supplement Database. Analyses used the two one-sided tests, known as TOST, to assess equivalence of reported supplement use between methods., Results: Complete 24-hour dietary recalls that included both dietary and supplement intake data were available for 1076 participants (507 men and 569 women). The proportions reporting supplement use via ASA24 and AMPM were 46% and 43%, respectively. These proportions were equivalent, with a small effect size of less than 20%. There were two exceptions in subgroup analyses: reported use among those 40 to 59 years of age and reported use by non-Hispanic black subjects were higher for ASA24 than AMPM., Conclusions: This study provides evidence that there is little difference in reported supplement use by mode of administration (ie, interview-administered vs self-administered recall)., (Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Objectives: We investigated associations between dieting and other health-compromising behaviours among adolescent girls, both cross-sectionally and longitudinally. The behaviours considered included smoking, binge drinking, and breakfast-skipping, and clusters of these., Methods: Data for 3386 adolescent Ontario girls were drawn from COMPASS, a school-based study, which collects self-reported measures of weight, dieting, and other health-related factors. Multilevel logistic regression models were used to investigate relationships between dieting at baseline and smoking, binge drinking, and breakfast-skipping, as well as clusters of these behaviours at baseline and 2 years later., Results: Baseline dieters were at an elevated risk of smoking and binge drinking (RR = 1.8 and 1.5, respectively) by follow-up compared to non-dieters. Further, dieting was associated with combinations of these behaviours, with the highest risks for smoking/breakfast-skipping (RR = 1.64) and smoking/binge drinking (RR = 1.55). Over one in two (58%) girls reported dieting at baseline and four in five baseline dieters reported dieting 2 years later. Seven in ten girls were dieting at one or both time points. Baseline dieters were more likely to engage in a greater number of risky behaviours, regardless of what the actual behaviours were., Conclusion: Dieting is longitudinally associated with engagement in other risky behaviours among adolescent girls. These findings suggest that dieting may be an early risk factor for engagement in other risky behaviours and highlight the need for comprehensive prevention strategies to target shared underlying drivers. In addition, attention is needed to the potential for well-meaning weight-related initiatives to promote dieting.

Background: The Automated Self-Administered 24-hour (ASA24) dietary recall system enhances the feasibility of collecting high-quality intake data in population-based studies., Objective: The aim of this study was to assess the accuracy of portion size reporting in the ASA24 compared with interviewer-administered recalls., Methods: True intake for 3 meals was ascertained in 81 adults aged 20-70 y from the Washington, DC area. Participants were randomly assigned to complete an unannounced ASA24 or an interviewer-administered Automated Multiple-Pass Method (AMPM) recall the following day. An adapted Bland-Altman approach was used to assess agreement between true and reported portion sizes. Linear regression was used to assess log-scale differences between true and reported portion sizes by recall mode. The proportions of reported portion sizes within 10% and 25% of truth were estimated. Analyses were conducted for all foods and drinks and predetermined categories., Results: Mean differences between true and reported portion sizes were 3.7 g for the ASA24 and 11.8 g for the AMPM. According to the Bland-Altman-type plots, between 92% and 100% (depending on food or drink category and recall mode) of observations fell within the limits of agreement. After adjustment for multiple testing, the mean ratio of reported to true portion sizes was significantly >1 for the categories of all foods and drinks, all foods excluding liquids, amorphous or soft foods, and small pieces among AMPM respondents. Misestimation in the AMPM was significantly different from that in the ASA24 for all foods and drinks and for all foods excluding liquids. Small proportions of reported portions fell within 10% (16.2% for the ASA24 and 14.9% for the AMPM) and 25% (37.5% for the ASA24 and 33.2% for the AMPM) of truth., Conclusions: The results raise the possibility that digital images tailored to different types and formats of foods may facilitate improved estimation of amounts eaten but highlight the need for continued work in this aspect of dietary assessment. This trial was registered at clinicaltrials.gov as NCT00978406., Competing Interests: 2 Author disclosures: SI Kirkpatrick, N Potischman, KW Dodd, D Douglass, TP Zimmerman, LL Kahle, FE Thompson, SM George, and AF Subar, no conflicts of interest., (© 2016 American Society for Nutrition.)