Methodological examination of the 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) Score.

The objective of this study was to examine the impact of methodological changes to the 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) Score on associations with risk for all-cause mortality, cancer mortality, and cancer risk jointly among older adults in the NIH-AARP Diet and Health Study. Weights were incorporated for each Score component; a continuous point scale was developed in place of the Score's fully discrete cut-points; and cut-point values were changed for physical activity and red meat based on evidence-based recommendations. Exploratory aims also examined the impact of separating components with more than one sub-component and whether all components were necessary to retain within this population utilizing a penalized scoring approach. Findings suggested weighting the original 2018 WCRF/AICR Score improved the score's predictive performance in association with all-cause mortality and provided more precise estimates in relation to cancer risk and mortality outcomes. The importance of healthy weight, physically activity, and plant-based foods in relation to cancer and overall mortality risk were highlighted in this population of older adults. Further studies are needed to better understand the consistency and generalizability of these findings across other populations.

Differences in Intakes of Select Nutrients by Urbanization Level in the United States Population 2 Years and Older, NHANES 2013-2018.

BACKGROUND: Differences in nutrient intakes by urbanization level in the Unites States is not well understood. OBJECTIVE: Describe, by urbanization level: 1) intake of protein, fiber, percent of energy from added sugars (AS) and saturated fat (SF), calcium, iron, potassium, sodium, and vitamin D; 2) the percent of the population meeting nutrient recommendations. METHODS: Twenty-four-hour dietary recalls from 23,107 participants aged 2 y and over from the 2013-2018 National Health and Nutrition Examination Surveys were analyzed. Usual intakes were estimated, and linear regression models adjusted for age, sex, race and Hispanic origin, and whether family income met the 130% threshold examined intake differences by urbanization levels-large urban areas (LUA), small to medium metro areas (SMMA), and rural areas (RA). RESULTS: A small percentage of the population met the nutrient recommendations, except for protein (92.8%) and iron (70.5%). A higher percentage of the population met recommendations than SMMA and RA for fiber (11.8% compared with 8.1% and 5.3%, P < 0.001), AS (40.2% compared with 33.4% and 31.3%, P < 0.001), SF (26.8% compared with 18.2% and 20.1%, P < 0.001), and potassium (31.5% compared with 25.5% and 22.0%, P < 0.001). Mean protein intake were also higher in LUA than RA (80.0 g compared with 77.7 g, P = 0.003) and fiber intake higher in LUA than SMMA (16.5 g compared with 15.9 g, P = 0.01) and RA (16.5 g compared with 15.2 g, P = 0.001). In addition, contributions to energy intake were lower in LUA than SMMA for AS (11.3% compared with 12.0%, P < 0.001) and SF (11.5% compared with 11.7%, P < 0.001), and for LUA than RA for AS (11.3% compared with 12.9%, P < 0.001) and SF (11.5% compared with 11.8%, P < 0.001). CONCLUSIONS: RA had some markers of poorer diet quality-lower protein and fiber intake and higher AS intake-compared with LUA, and these differences persisted in adjusted regression models. These results may inform public health efforts to address health disparities by urbanization levels in the Unites States.

A Decade of Dietary Assessment Methodology Research at the National Institutes of Health, 2012-2021.

BACKGROUND: Assessment of individual and population-level dietary intake is critical for public health surveillance, epidemiology, and dietary intervention research. In recognition of that need, the National Insitutes of Health (NIH) has a history of funding research projects designed to support the development, implementation, and refinement of tools to assess dietary intake in humans. OBJECTIVES: This report provides data and information on NIH-funded dietary intake assessment methodological research over the period of 2012-2021. METHODS: Data were extracted from an internal NIH data system using the Research, Condition, and Disease Categorization (RCDC) spending category for Nutrition. Data were then examined to identify research focused on dietary assessment tools or methods to capture or analyze dietary intake. RESULTS: Over the decade of 2012-2021, NIH supported 46 grants and 2 large contracts specific to dietary assessment methods development. The top 6 Institutes and Offices funding dietary assessment methods research were identified. Most projects were limited to adults. Projects ranged from novel methods to capture dietary intake, and refinement of analytical methods, to biomarkers of dietary intake. One key contract supported the automated self-administered 24-h dietary assessment tool (ASA24), a widely used, free tool available to the research community for assessing dietary intake. CONCLUSIONS: NIH's support for dietary assessment methods development over this 10-y period was small but grew over time with an expanding number and variety of methods, data sources, and technological advancements in the assessment of dietary intake. NIH remains committed to supporting research seeking to advance the field of dietary assessment methods research.

Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial.

BACKGROUND: Objective markers of ultraprocessed foods (UPF) may improve the assessment of UPF intake and provide insight into how UPF influences health. OBJECTIVES: To identify metabolites that differed between dietary patterns (DPs) high in or void of UPF according to Nova classification. METHODS: In a randomized, crossover, controlled-feeding trial (clinicaltrials.govNCT03407053), 20 domiciled healthy participants (mean ± standard deviation: age 31 ± 7 y, body mass index [kg/m2] 22 ± 11.6) consumed ad libitum a UPF-DP (80% UPF) and an unprocessed DP (UN-DP; 0% UPF) for 2 wk each. Metabolites were measured using liquid chromatography with tandem mass spectrometry in ethylenediaminetetraacetic acid plasma, collected at week 2 and 24-h, and spot urine, collected at weeks 1 and 2, of each DP. Linear mixed models, adjusted for energy intake, were used to identify metabolites that differed between DPs. RESULTS: After multiple comparisons correction, 257 out of 993 plasma and 606 out of 1279 24-h urine metabolites differed between UPF-DP and UN-DP. Overall, 21 known and 9 unknown metabolites differed between DPs across all time points and biospecimen types. Six metabolites were higher (4-hydroxy-L-glutamic acid, N-acetylaminooctanoic acid, 2-methoxyhydroquinone sulfate, 4-ethylphenylsulfate, 4-vinylphenol sulfate, and acesulfame) and 14 were lower following the UPF-DP; pimelic acid, was lower in plasma but higher in urine following the UPF-DP. CONCLUSIONS: Consuming a DP high in, compared with 1 void of, UPF has a measurable impact on the short-term human metabolome. Observed differential metabolites could serve as candidate biomarkers of UPF intake or metabolic response in larger samples with varying UPF-DPs. This trial was registered at clinicaltrials.gov as NCT03407053 and NCT03878108.

Adherence to 5 Diet Quality Indices and Pancreatic Cancer Risk in a Large US Prospective Cohort.

Few prospective studies have examined associations between diet quality and pancreatic ductal adenocarcinoma (PDAC), or comprehensively compared diet quality indices. We conducted a prospective analysis of adherence to the Healthy Eating Index (HEI)-2015, alternative HEI-2010, alternate Mediterranean diet (aMed), and 2 versions of Dietary Approaches to Stop Hypertension (DASH; Fung and Mellen) and PDAC within the National Institutes of Health (NIH)-AARP Diet and Health Study (United States, 1995-2011). The dietary quality indices were calculated using responses from a 124-item food frequency questionnaire completed by 535,824 participants (315,780 men and 220,044 women). We used Cox proportional hazards regression models to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for each diet quality index and PDAC. During follow-up through 2011 (15.5-year median), 3,137 incident PDAC cases were identified. Compared with those with the lowest adherence quintile, participants with the highest adherence to the HEI-2015 (HR = 0.84, 95% CI: 0.75, 0.94), aMed (HR = 0.82, 95% CI: 0.73, 0.93), DASH-Fung (HR = 0.85, 95% CI: 0.77, 0.95), and DASH-Mellen (HR = 0.86, 95% CI: 0.77, 0.96) had a statistically significant, lower PDAC risk; this was not found for the alternative HEI-2010 (HR = 0.93, 95% CI: 0.83, 1.04). This prospective observational study supports the hypothesis that greater adherence to the HEI-2015, aMed, and DASH dietary recommendations may reduce PDAC.

Circadian timing of eating and BMI among adults in the American Time Use Survey.

BACKGROUND/OBJECTIVES: Experimental studies of time-restricted eating suggest that limiting the daily eating window, shifting intake to the biological morning, and avoiding eating close to the biological night may promote metabolic health and prevent weight gain. SUBJECTS/METHODS: We used the Eating & Health Module of the 2006-2008 and 2014-2016 American Time Use Survey to examine cross-sectional associations of timing of eating in relation to sleep/wake times as a proxy for circadian timing with body mass index (BMI). The analytical sample included 38 302 respondents (18-64 years; BMI 18.5-50.0 kg/m2). A single 24-hour time use diary was used to calculate circadian timing of eating variables: eating window (time between first and last eating activity); morning fast (time between end of sleep and start of eating window); and evening fast (time between end of eating window and start of sleep). Multinomial logistic regression and predictive margins were used to estimate adjusted population prevalences (AP) by BMI categories and changes in prevalences associated with a one-hour change in circadian timing of eating, controlling for sociodemographic and temporal characteristics. RESULTS: A one-hour increase in eating window was associated with lower adjusted prevalence of obesity (AP = 27.1%, SE = 0.1%). Conversely, a one-hour increase in morning fast (AP = 28.7%, SE = 0.1%) and evening fast (AP = 28.5%, SE = 0.1%) were each associated with higher prevalence of obesity; interactions revealed differing patterns of association by combination of eating window with morning/evening fast (p < 0.0001). CONCLUSIONS: Contrary to hypotheses, longer eating windows were associated with a lower adjusted prevalence of obesity and longer evening fasts were associated with a higher prevalence of obesity. However, as expected, longer morning fast was associated with a higher adjusted prevalence of obesity. Studies are needed to disentangle the contributions of diet quality/quantity and social desirability bias in the relationship between circadian timing of eating and BMI.

A Standardized Assessment of Processed Red Meat and Processed Poultry Intake in the US Population Aged ≥2 Years Using NHANES.

BACKGROUND: Standardized methods are needed to investigate intake patterns of processed meat subtypes, considering health concerns surrounding processed meat intake. OBJECTIVES: The objectives of this study were to create a standardized method of disaggregating processed meat into processed red meat and processed poultry and describe intake patterns of the US population aged ≥2 y. METHODS: Two researchers independently manually disaggregated processed meat from the Food Patterns Equivalents Database into processed red meat and processed poultry based on available information from the Foods and Nutrient Database for Dietary Studies. We created an SAS program (called Processed Meat Categories) to mimic the manual coding. We used the program to describe intake patterns and trends over time of processed red meat and processed poultry using 24-h recalls from 2007-2008 through 2017-2018 NHANES data with SAS survey-weighted procedures for complex surveys. RESULTS: The SAS program had high agreement with the manual code (Pearson concordance correlation ≥0.95). Of the US population aged ≥2 y, 46.8% (95% CI: 45.3, 48.2%) reported consuming any processed meat, 42.5% (95% CI: 41.0, 43.9%) reported consuming processed red meat, and 11.3% (95% CI: 10.2, 12.4%) reported consuming processed poultry. Most [74.1 ± 0.13% (SEM)] processed meat reported was red meat compared with poultry, and 32.1 ± 0.01% of total red meat and 13.7 ± 0.01% of total poultry reported were processed. Prevalence of processed poultry intake increased from 9.5% (95% CI: 8.9, 10.1%) in 2007-2010 to 11.3% (95% CI: 10.2, 12.4%) in 2015-2018 (P < 0.0001), but mean intake amount did not change. Prevalence of processed red meat intake did not change over time, but mean intake decreased from 0.8 ± 0.03 ounce-equivalents in 2007-2010 to 0.7 ± 0.02 ounce-equivalents (P = 0.0058) in 2015-2018. CONCLUSIONS: The Processed Meat Categories SAS program is a tool available for researchers to standardize estimates of processed meat subtypes for future dietary patterns research. Intake of total processed meat did not change in the United States, but intake amount of processed red meat decreased and the prevalence of processed poultry consumers increased.

A qualitative exploration of facilitators and barriers of adherence to time-restricted eating.

Time-restricted eating (TRE), a dietary strategy that involves limiting daily energy intake to a window of ≤12 h is appealing for weight management and metabolic health due to its relative simplicity and the ability to consume ad libitum diet during eating windows. Despite the potential utility of TRE for improving health and reducing disease, the feasibility of adherence depends upon a variety of multilevel factors which are largely unexplored. The primary aim of our study was to explore facilitators and barriers of adherence to TRE among community-dwelling individuals. Semi-structured qualitative interviews were conducted among 24 individuals (50% male; M age: 34, range: 18-57; 58% overweight/obese) who currently or formerly practiced TRE. Thematic analysis identified facilitators of and barriers to TRE adherence at multiple levels of influence (i.e., biological, behavioral, psychosocial, environmental). Key facilitators of adherence included improvements in physical health and energy levels, alignment with other aspects of diet, exercise and sleep patterns, self-monitoring and positive psychological impacts, social support, and busy or regular schedules. Key barriers included negative physical health effects, feelings of hunger and sluggishness, difficulty in skipping valued baseline eating routines or inadequate diet quality during the eating window, misalignment of TRE with 24-h activity behaviors, difficulties with self-monitoring, the need to mitigate negative feelings, social situations that discourage TRE, and irregular or idle schedules. Results illustrate that key drivers of adherence differ across individuals and their unique settings and that multiple drivers of behavior should be considered in the successful implementation of TRE. Findings may inform interventions seeking to tailor TRE schedules to fit individuals' diverse behavioral patterns and preferences, thereby optimizing adherence.

Novel Application of Nutritional Biomarkers From a Controlled Feeding Study and an Observational Study to Characterization of Dietary Patterns in Postmenopausal Women.

Dietary guidance emphasizes healthy dietary patterns, but supporting evidence comes from self-reported dietary data, which are prone to measurement error. We explored whether nutritional biomarkers from the Women's Health Initiative Nutrition and Physical Activity Assessment Study Feeding Study (NPAAS-FS) (n = 153; 2010-2014) and the Women's Health Initiative Nutrition and Physical Activity Assessment Study Observational Study (NPAAS-OS) (n = 450; 2006-2009) could identify biomarker signatures of dietary patterns for development of corresponding regression calibration equations to help mitigate measurement error. Fasting blood samples were assayed for a specific panel of vitamins, carotenoids, and phospholipid fatty acids; 24-hour urine samples were assayed for nitrogen, sodium, and potassium levels. Intake records from the NPAAS-FS were used to calculate Healthy Eating Index 2010 (HEI-2010), Alternative Healthy Eating Index 2010 (AHEI-2010), alternative Mediterranean diet (aMED), and Dietary Approaches to Stop Hypertension (DASH) scores. Scores were regressed on blood and urine nutritional measures for discovery of dietary pattern biomarkers using a cross-validated model R2 ≥ 36% criterion (stage 1). Next, stepwise models (P ≤ 0.10 for entry/removal) using NPAAS-OS data were used to regress stage 1 dietary pattern biomarkers on NPAAS-OS self-reported dietary pattern scores using a food frequency questionnaire, a 4-day food record, and a 24-hour recall (stage 2). HEI-2010 and aMED analyses met the cross-validated R2 ≥ 36% criterion in stage 1, while AHEI-2010 and DASH analyses did not. The R2 values for HEI-2010 stage 2 calibration equations were as follows: food frequency questionnaire, 63.5%; 4-day food record, 83.1%; and 24-hour recall, 77.8%. Stage 2 aMED R2 values were 34.9%-46.8%. Dietary pattern biomarkers have potential for calibrating self-reports to enhance studies of diet-disease associations.

Alignment of Dietary Patterns With the Dietary Guidelines for Americans 2015-2020 and Risk of All-Cause and Cause-Specific Mortality in the Women's Health Initiative Observational Study.

Poor diet quality is a leading risk factor for death in the United States. We examined the association between Healthy Eating Index-2015 (HEI-2015) scores and death from all causes, cardiovascular disease (CVD), cancer, Alzheimer disease, and dementia not otherwise specified (NOS) among postmenopausal women in the Women's Health Initiative Observational Study (1993-2017). This analysis included 59,388 participants who completed a food frequency questionnaire and were free of cancer, CVD, and diabetes at enrollment. Stratified Cox proportional hazards models were fit using person-years from enrollment as the underlying time metric. We estimated multivariable adjusted hazard ratios and 95% confidence intervals for risk of death associated with HEI-2015 quintiles, with higher scores reflecting more optimal diet quality. Over a median of 18.2 years, 9,679 total deaths 3,303 cancer deaths, 2,362 CVD deaths, and 488 deaths from Alzheimer disease and dementia NOS occurred. Compared with those with lower scores, women with higher HEI-2015 scores had an 18% lower risk of all-cause death and 21% lower risk of cancer death. HEI-2015 scores were not associated with death due to CVD, Alzheimer disease, and dementia NOS. Consuming a diet aligned with 2015-2020 US dietary guidelines may have beneficial impacts for preventing overall causes of death and death from cancer.

Prevalence and correlates of US adult public opinion on restricting junk food advertising to children on social media: 2020 Health Information National Trends Survey.

OBJECTIVE: To describe US adults' levels of support, neutrality and opposition to restricting junk food advertising to children on social media and explore associations with socio-demographic and health-related characteristics. DESIGN: In 2020-2021, we used cross-sectional data from the National Cancer Institute's 2020 Health Information National Trends Survey to estimate the prevalence of opinions towards advertising restrictions and correlates of neutrality and opposition using weighted multivariable logistic regression. SETTING: United States. PARTICIPANTS: Adults aged 18+ years. RESULTS: Among the analytic sample (n 2852), 54 % of adults were neutral or opposed to junk food advertising restrictions on social media. The odds of being neutral or opposed were higher among Non-Hispanic Black adults (v. non-Hispanic White; OR: 2·03 (95 % CI 1·26, 3·26)); those completing some college (OR: 1·68 (95 % CI 1·20, 2·34)) or high school or less (OR: 2·62 (95 % CI 1·74, 3·96)) (v. those with a college degree); those who were overweight (v. normal weight; OR: 1·42 (95 % CI: 1·05, 1·93)) and those reporting a moderate (OR: 1·45 (95 % CI 1·13, 1·88)) or conservative (OR: 1·71 (95 % CI 1·24, 2·35)) political viewpoint (v. liberal). Having strong (v. weaker) weight and diet-related cancer beliefs was associated with 53 % lower odds of being neutral or opposed to advertising restrictions (OR: 0·47 (95 % CI 0·36, 0·61)). CONCLUSIONS: The current study identified subgroups of US adults for whom targeted communication strategies may increase support for policies to improve children's food environment.

The application of six dietary scores to a Middle Eastern population: a comparative analysis of mortality in a prospective study.

Background The associations between dietary indices and mortality have not been evaluated in populations from the Middle East, which have different dietary patterns compared to the US and Europe. In this study, we evaluated the association between six dietary indices and mortality in the Golestan Cohort Study (GCS) in Iran, which is the largest prospective study in the Middle East with 50,045 participants. Methods The six dietary indices, namely the Healthy Eating Index (HEI-2015), Alternative Healthy Eating Index (AHEI-2010), Alternative Mediterranean Diet (AMED), Dietary Approach to Stop Hypertension created by Fung (DASH-Fung) and Mellen (DASH-Mellen), and the World Cancer Research Fund (WCRF/AICR) index, were applied to data from a food frequency questionnaire, computed and divided into quintiles. Adjusted Cox models were used to estimate hazards ratio (HR) and 95% confidence intervals (CI) for overall and cause-specific mortality, using the lowest quintile as a reference group. Results Among 42,373 participants included in the current analyses, 4424 subjects died during 10.6 years of follow-up. Participants with the highest quintile dietary scores, compared with the lowest quintile dietary scores, had significantly decreased overall mortality in the AHEI-2010, AMED, DASH-Fung, and WCRF/AICR indices (HR 0.88, 95% CI = 0.80-0.97; 0.80, 0.70-0.91; 0.77, 0.70-0.86; and 0.79, 0.70-0.90, respectively). A reduced cardiovascular mortality was found for high AHEI-2010 and DASH-Fung scores (17% and 23%, respectively), and a reduced cancer mortality for high HEI-2015, AMED, and DASH-Fung scores (21, 37 and 25%, respectively). Conclusion Various indices of dietary quality are inversely associated with overall mortality, and selectively with cancer and cardiovascular mortality in the GCS, which contribute to the generalizability and validity of dietary guidelines.

Clustering in General Measurement Error Models.

This paper is dedicated to the memory of Peter G. Hall. It concerns a deceptively simple question: if one observes variables corrupted with measurement error of possibly very complex form, can one recreate asymptotically the clusters that would have been found had there been no measurement error? We show that the answer is yes, and that the solution is surprisingly simple and general. The method itself is to simulate, by computer, realizations with the same distribution as that of the true variables, and then to apply clustering to these realizations. Technically, we show that if one uses K-means clustering or any other risk minimizing clustering, and a multivariate deconvolution device with certain smoothness and convergence properties, then, in the limit, the cluster means based on our method converge to the same cluster means as if there is no measurement error. Along with the method and its technical justification, we analyze two important nutrition data sets, finding patterns that make sense nutritionally.

Addressing Current Criticism Regarding the Value of Self-Report Dietary Data.

Recent reports have asserted that, because of energy underreporting, dietary self-report data suffer from measurement error so great that findings that rely on them are of no value. This commentary considers the amassed evidence that shows that self-report dietary intake data can successfully be used to inform dietary guidance and public health policy. Topics discussed include what is known and what can be done about the measurement error inherent in data collected by using self-report dietary assessment instruments and the extent and magnitude of underreporting energy compared with other nutrients and food groups. Also discussed is the overall impact of energy underreporting on dietary surveillance and nutritional epidemiology. In conclusion, 7 specific recommendations for collecting, analyzing, and interpreting self-report dietary data are provided: (1) continue to collect self-report dietary intake data because they contain valuable, rich, and critical information about foods and beverages consumed by populations that can be used to inform nutrition policy and assess diet-disease associations; (2) do not use self-reported energy intake as a measure of true energy intake; (3) do use self-reported energy intake for energy adjustment of other self-reported dietary constituents to improve risk estimation in studies of diet-health associations; (4) acknowledge the limitations of self-report dietary data and analyze and interpret them appropriately; (5) design studies and conduct analyses that allow adjustment for measurement error; (6) design new epidemiologic studies to collect dietary data from both short-term (recalls or food records) and long-term (food-frequency questionnaires) instruments on the entire study population to allow for maximizing the strengths of each instrument; and (7) continue to develop, evaluate, and further expand methods of dietary assessment, including dietary biomarkers and methods using new technologies.

The Dietary Patterns Methods Project: synthesis of findings across cohorts and relevance to dietary guidance.

The Dietary Patterns Methods Project (DPMP) was initiated in 2012 to strengthen research evidence on dietary indices, dietary patterns, and health for upcoming revisions of the Dietary Guidelines for Americans, given that the lack of consistent methodology has impeded development of consistent and reliable conclusions. DPMP investigators developed research questions and a standardized approach to index-based dietary analysis. This article presents a synthesis of findings across the cohorts. Standardized analyses were conducted in the NIH-AARP Diet and Health Study, the Multiethnic Cohort, and the Women's Health Initiative Observational Study (WHI-OS). Healthy Eating Index 2010, Alternative Healthy Eating Index 2010 (AHEI-2010), alternate Mediterranean Diet, and Dietary Approaches to Stop Hypertension (DASH) scores were examined across cohorts for correlations between pairs of indices; concordant classifications into index score quintiles; associations with all-cause, cardiovascular disease (CVD), and cancer mortality with the use of Cox proportional hazards models; and dietary intake of foods and nutrients corresponding to index quintiles. Across all cohorts in women and men, there was a high degree of correlation and consistent classifications between index pairs. Higher diet quality (top quintile) was significantly and consistently associated with an 11-28% reduced risk of death due to all causes, CVD, and cancer compared with the lowest quintile, independent of known confounders. This was true for all diet index-mortality associations, with the exception of AHEI-2010 and cancer mortality in WHI-OS women. In all cohorts, survival benefit was greater with a higher-quality diet, and relatively small intake differences distinguished the index quintiles. The reductions in mortality risk started at relatively lower levels of diet quality. Higher scores on each of the indices, signifying higher diet quality, were associated with marked reductions in mortality. Thus, the DPMP findings suggest that all 4 indices capture the essential components of a healthy diet.

Comparing indices of diet quality with chronic disease mortality risk in postmenopausal women in the Women's Health Initiative Observational Study: evidence to inform national dietary guidance.

Poor diet quality is thought to be a leading risk factor for years of life lost. We examined how scores on 4 commonly used diet quality indices-the Healthy Eating Index 2010 (HEI), the Alternative Healthy Eating Index 2010 (AHEI), the Alternate Mediterranean Diet (aMED), and the Dietary Approaches to Stop Hypertension (DASH)-are related to the risks of death from all causes, cardiovascular disease (CVD), and cancer among postmenopausal women. Our prospective cohort study included 63,805 participants in the Women's Health Initiative Observational Study (from 1993-2010) who completed a food frequency questionnaire at enrollment. Cox proportional hazards models were fit using person-years as the underlying time metric. We estimated multivariate hazard ratios and 95% confidence intervals for death associated with increasing quintiles of diet quality index scores. During 12.9 years of follow-up, 5,692 deaths occurred, including 1,483 from CVD and 2,384 from cancer. Across indices and after adjustment for multiple covariates, having better diet quality (as assessed by HEI, AHEI, aMED, and DASH scores) was associated with statistically significant 18%-26% lower all-cause and CVD mortality risk. Higher HEI, aMED, and DASH (but not AHEI) scores were associated with a statistically significant 20%-23% lower risk of cancer death. These results suggest that postmenopausal women consuming a diet in line with a priori diet quality indices have a lower risk of death from chronic disease.

Higher diet quality is associated with decreased risk of all-cause, cardiovascular disease, and cancer mortality among older adults.

Increased attention in dietary research and guidance has been focused on dietary patterns, rather than on single nutrients or food groups, because dietary components are consumed in combination and correlated with one another. However, the collective body of research on the topic has been hampered by the lack of consistency in methods used. We examined the relationships between 4 indices--the Healthy Eating Index-2010 (HEI-2010), the Alternative Healthy Eating Index-2010 (AHEI-2010), the alternate Mediterranean Diet (aMED), and Dietary Approaches to Stop Hypertension (DASH)--and all-cause, cardiovascular disease (CVD), and cancer mortality in the NIH-AARP Diet and Health Study (n = 492,823). Data from a 124-item food-frequency questionnaire were used to calculate scores; adjusted HRs and 95% CIs were estimated. We documented 86,419 deaths, including 23,502 CVD- and 29,415 cancer-specific deaths, during 15 y of follow-up. Higher index scores were associated with a 12-28% decreased risk of all-cause, CVD, and cancer mortality. Specifically, comparing the highest with the lowest quintile scores, adjusted HRs for all-cause mortality for men were as follows: HEI-2010 HR: 0.78 (95% CI: 0.76, 0.80), AHEI-2010 HR: 0.76 (95% CI: 0.74, 0.78), aMED HR: 0.77 (95% CI: 0.75, 0.79), and DASH HR: 0.83 (95% CI: 0.80, 0.85); for women, these were HEI-2010 HR: 0.77 (95% CI: 0.74, 0.80), AHEI-2010 HR: 0.76 (95% CI: 0.74, 0.79), aMED HR: 0.76 (95% CI: 0.73, 0.79), and DASH HR: 0.78 (95% CI: 0.75, 0.81). Similarly, high adherence on each index was protective for CVD and cancer mortality examined separately. These findings indicate that multiple scores reflect core tenets of a healthy diet that may lower the risk of mortality outcomes, including federal guidance as operationalized in the HEI-2010, Harvard's Healthy Eating Plate as captured in the AHEI-2010, a Mediterranean diet as adapted in an Americanized aMED, and the DASH Eating Plan as included in the DASH score.

The Healthy Eating Index-2010 is a valid and reliable measure of diet quality according to the 2010 Dietary Guidelines for Americans.

The Healthy Eating Index (HEI), a measure of diet quality, was updated to reflect the 2010 Dietary Guidelines for Americans and the accompanying USDA Food Patterns. To assess the validity and reliability of the HEI-2010, exemplary menus were scored and 2 24-h dietary recalls from individuals aged ≥2 y from the 2003-2004 NHANES were used to estimate multivariate usual intake distributions and assess whether the HEI-2010 1) has a distribution wide enough to detect meaningful differences in diet quality among individuals, 2) distinguishes between groups with known differences in diet quality by using t tests, 3) measures diet quality independently of energy intake by using Pearson correlation coefficients, 4) has >1 underlying dimension by using principal components analysis (PCA), and 5) is internally consistent by calculating Cronbach's coefficient α. HEI-2010 scores were at or near the maximum levels for the exemplary menus. The distribution of scores among the population was wide (5th percentile = 31.7; 95th percentile = 70.4). As predicted, men's diet quality (mean HEI-2010 total score = 49.8) was poorer than women's (52.7), younger adults' diet quality (45.4) was poorer than older adults' (56.1), and smokers' diet quality (45.7) was poorer than nonsmokers' (53.3) (P < 0.01). Low correlations with energy were observed for HEI-2010 total and component scores (|r| ≤ 0.21). Cronbach's coefficient α was 0.68, supporting the reliability of the HEI-2010 total score as an indicator of overall diet quality. Nonetheless, PCA indicated multiple underlying dimensions, highlighting the fact that the component scores are equally as important as the total. A comparable reevaluation of the HEI-2005 yielded similar results. This study supports the validity and the reliability of both versions of the HEI.

Perceived and objective diet quality in US adults: a cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES).

OBJECTIVE: The Dietary Approaches to Stop Hypertension (DASH) dietary pattern has been shown to reduce cardiometabolic risk. Little is understood about the relationship between objective diet quality and perceived diet quality (PDQ), a potential psychosocial barrier to appropriate dietary intake. We compared PDQ and diet quality measured by a nutrient-based DASH index score in the USA. DESIGN: Cross-sectional study. Participants in the 2005-2006 National Health and Nutrition Examination Survey (NHANES) rated diet quality on a 5-point Likert scale and PDQ scores were generated (low, medium, high). A single 24 h dietary recall was used to estimate DASH index scores (range 0-9 points) by assigning 0, 0·5 or 1 point (optimal) for nine target nutrients: total fat, saturated fat, protein, cholesterol, fibre, Ca, Mg, K and Na. SETTING: Nationally representative sample of the US population. SUBJECTS: Adults aged ≥19 years in 2005-2006 NHANES (n 4419). RESULTS: Participants with high PDQ (33 %) had higher DASH index scores (mean 3·0 (sd 0·07)) than those with low PDQ (mean 2·5 (sd 0·06), P < 0·001), but average scores did not align with targets for intermediate or optimal DASH accordance. Adults with high PDQ reported higher total fat, saturated fat and Na intakes compared with optimal DASH nutrient goals. Differences between those with high v. low PDQ were similar for Whites and Blacks, but there was no difference between PDQ groups for Mexican Americans. CONCLUSIONS: Among Whites and Blacks, but not Mexican Americans, high PDQ may be associated with higher diet quality, but not necessarily a diet meeting DASH nutrient goals. This disconnect between PDQ and actual diet quality may serve as a target in obesity prevention.

Fast-food menu offerings vary in dietary quality, but are consistently poor.

OBJECTIVE: To evaluate five popular fast-food chains' menus in relation to dietary guidance. DESIGN: Menus posted on chains' websites were coded using the Food and Nutrient Database for Dietary Studies and MyPyramid Equivalents Database to enable Healthy Eating Index-2005 (HEI-2005) scores to be assigned. Dollar or value and kids' menus and sets of items promoted as healthy or nutritious were also assessed. SETTING: Five popular fast-food chains in the USA. SUBJECTS: Not applicable. RESULTS: Full menus scored lower than 50 out of 100 possible points on the HEI-2005. Scores for Total Fruit, Whole Grains and Sodium were particularly dismal. Compared with full menus, scores on dollar or value menus were 3 points higher on average, whereas kids' menus scored 10 points higher on average. Three chains marketed subsets of items as healthy or nutritious; these scored 17 points higher on average compared with the full menus. No menu or subset of menu items received a score higher than 72 out of 100 points. CONCLUSIONS: The poor quality of fast-food menus is a concern in light of increasing away-from-home eating, aggressive marketing to children and minorities, and the tendency for fast-food restaurants to be located in low-income and minority areas. The addition of fruits, vegetables and legumes; replacement of refined with whole grains; and reformulation of offerings high in sodium, solid fats and added sugars are potential strategies to improve fast-food offerings. The HEI may be a useful metric for ongoing monitoring of fast-food menus.