ABSTRACT
BACKGROUND: Few diet quality indices have been developed and validated for use among children and adolescents. Additionally, many available indices require completion of burdensome dietary assessments. OBJECTIVES: We aimed to calculate and evaluate the performance of a modified version of the food-based Prime Diet Quality Score (PDQS) derived from different diet assessment methods conducted at 4 time points in a single study population from childhood through adolescence. METHODS: Among 1460 child participants in the Project Viva cohort, we calculated the PDQS in early and mid-childhood and early and mid-adolescence using dietary data obtained from food frequency questionnaire (early childhood: parent report), PrimeScreen (mid-childhood: parent report; early adolescence: self-report) and 24-h recall (mid-adolescence: self-report). We evaluated construct and relative validity and internal reliability of the score in each life stage. RESULTS: The PDQS showed a range of scores at all life stages and higher scores were associated with intake of many health-promoting macronutrients and micronutrients (e.g., protein, fiber, and vitamins) in early childhood and mid-adolescence. The PDQS performed similarly to the Youth Healthy Eating Index/Healthy Eating Index (Spearman r = 0.63-0.85) in various assessments. Higher PDQS was associated with expected characteristics including more frequent breakfast eating, family dinners, and vigorous physical activity; with less frequent TV viewing and fast food intake; and with more sleep and higher maternal diet scores during pregnancy. Cross-sectional associations of the PDQS with various anthropometric measurements and biomarkers were inconsistent but generally in the expected directions (e.g., higher PDQS associated with lower triglycerides and insulin and higher HDL cholesterol). Internal reliability was consistent with what has been found for other diet quality indices. CONCLUSIONS: The PDQS can be calculated from data collected using different and brief dietary assessment methods and appears to be a valid and useful measure of overall diet quality in children and adolescents. Project Viva was registered at clinicaltrials.gov as NCT02820402.
Subject(s)
Diet , Adolescent , Child , Child, Preschool , Female , Humans , Male , Cohort Studies , Diet Surveys , Diet, Healthy , Nutrition Assessment , Reproducibility of Results , Self Report , Surveys and QuestionnairesABSTRACT
BACKGROUND: While dietary salt intake has been linked with gastric cancer risk in Asian studies, findings from Western populations are sparse and limited to case-control studies. Our aim was to evaluate the frequency of adding salt to food at table in relation to gastric cancer risk among UK adults. METHODS: We evaluated associations between the frequency of adding salt to food and the risk of gastric cancer in the UK Biobank (N = 471,144) using multivariable Cox regression. Frequency of adding salt to food was obtained from a touchscreen questionnaire completed at baseline (2006-2010). 24-h urinary sodium excretion was estimated using INTERSALT formulae. Cancer incidence was obtained by linkage to national cancer registries. RESULTS: During a median follow-up period of 10.9 years, 640 gastric cancer cases were recorded. In multivariable models, the gastric cancer risk among participants reporting adding salt to food at table "always" compared to those who responded "never/rarely" was HR = 1.41 (95% CI: 1.04, 1.90). There was a positive linear association between estimated 24-h urinary sodium levels and the frequency of adding salt to food (p-trend <0 .001). However, no significant association between estimated 24-h urinary sodium with gastric cancer was observed (HR = 1.19 (95% CI: 0.87, 1.61)). CONCLUSIONS: "Always adding salt to food" at table was associated with a higher gastric cancer risk in a large sample of UK adults. High frequency of adding salt to food at table can potentially serve as a useful indicator of salt intake for surveillance purposes and a basis for devising easy-to-understand public health messages.
Subject(s)
Sodium Chloride, Dietary , Stomach Neoplasms , Humans , Stomach Neoplasms/epidemiology , Male , Female , Middle Aged , Prospective Studies , Sodium Chloride, Dietary/administration & dosage , Sodium Chloride, Dietary/adverse effects , Adult , Risk Factors , Aged , Follow-Up Studies , United Kingdom/epidemiology , Surveys and Questionnaires , IncidenceABSTRACT
BACKGROUND: Plant-based diets are not inherently healthy. Similar to omnivorous diets, they may contain excessive amounts of sugar, sodium, and saturated fats, or lack diversity. Moreover, vegans might be at risk of inadequate intake of certain vitamins and minerals commonly found in foods that they avoid. We developed the VEGANScreener, a tool designed to assess the diet quality of vegans in Europe. METHODS: Our approach combined best practices in developing diet quality metrics with scale development approaches and involved the following: (a) narrative literature synthesis, (b) evidence evaluation by an international panel of experts, and (c) translation of evidence into a diet screener. We employed a modified Delphi technique to gather opinions from an international expert panel. RESULTS: Twenty-five experts in the fields of nutrition, epidemiology, preventive medicine, and diet assessment participated in the first round, and nineteen participated in the subsequent round. Initially, these experts provided feedback on a pool of 38 proposed items from the literature review. Consequently, 35 revised items, with 17 having multiple versions, were suggested for further consideration. In the second round, 29 items were retained, and any residual issues were addressed in the final consensus meeting. The ultimate screener draft encompassed 29 questions, with 17 focusing on foods and nutrients to promote, and 12 addressing foods and nutrients to limit. The screener contained 24 food-based and 5 nutrient-based questions. CONCLUSIONS: We elucidated the development process of the VEGANScreener, a novel diet quality screener for vegans. Future endeavors involve contrasting the VEGANScreener against benchmark diet assessment methodologies and nutritional biomarkers and testing its acceptance. Once validated, this instrument holds potential for deployment as a self-assessment application for vegans and as a preliminary dietary screening and counseling tool in healthcare settings.
Subject(s)
Diet, Vegan , Humans , Europe , Delphi Technique , Nutrition AssessmentABSTRACT
BACKGROUND: Dietary pattern is a determinant of chronic disease, but nonregistered dietitian nutritionist (non-RDN) clinicians rarely assess diet because of barriers such as time constraints and lack of valid, brief diet quality assessment tools. OBJECTIVE: The study aimed to evaluate the relative validity of a brief diet quality screener using both a numeric scoring system and a simple traffic light scoring system. DESIGN: A cross-sectional study was conducted using the CloudResearch online platform to compare participants' responses to the 13-item rapid Prime Diet Quality Score screener (rPDQS) and the Automated Self-Administered 24-hour (ASA24) Dietary Assessment Tool. PARTICIPANTS/SETTING: The study was conducted in July and August 2021 and included 482 adults ≥18 years of age or older sampled to be representative of the US population. MAIN OUTCOME MEASURES: All participants completed the rPDQS and an ASA24; of these, 190 completed a second ASA24 and rPDQS. Responses to rPDQS items were coded using both traffic light (eg, green = healthiest intake, red = least healthy intake) and numeric (eg, consume < 1 time a week, consume ≥ 2 times per day) scoring methods and were compared with food group equivalents and Healthy Eating Index-2015 (HEI-2015) scores estimated from ASA24s. STATISTICAL ANALYSES: Deattenuated Pearson correlation coefficients were calculated to account for within-person variation in 24-hour diet recalls. RESULTS: Overall, 49% of participants were female, 62% were ≥35 years, and 66% were non-Hispanic White, 13% non-Hispanic Black, 16% Hispanic/Latino, and 5% Asian. For both food groups to encourage (eg, vegetables, whole grains) and to consume in moderation (eg, processed meats, sweets), there were statistically significant associations with intakes assessed by rPDQS, using both traffic light and numeric scoring methods. Total rPDQS scores correlated with the HEI-2015, r = 0.75 (95% confidence interval [CI] = 0.65, 0.82). CONCLUSIONS: The rPDQS is a valid, brief diet quality screener that identifies clinically relevant patterns of food intake. Future research is needed to test whether the simple traffic light scoring system is an effective tool that can help non-RDN clinicians provide brief dietary counseling or make referrals to registered dietitian nutritionists, as needed.
ABSTRACT
BACKGROUND: Food insecurity is a critical public health problem in the United States that has been associated with poor diet quality. Cooking dinner more frequently is associated with better diet quality. OBJECTIVE: This study aimed to examine how food insecurity and dinner cooking frequency are associated with diet quality during the initial months of the coronavirus disease 2019 pandemic. DESIGN: This cross-sectional study analyzed data from a national web-based survey (June 23 to July 1, 2020). PARTICIPANTS/SETTING: Participants were 1,739 low-income (<250% of the federal poverty level) adults in the United States. MAIN OUTCOME MEASURES: The outcome was diet quality, measured by the Prime Diet Quality Score (PDQS-30D). The PDQS-30D is a food frequency questionnaire-based, 22-component diet quality index. STATISTICAL ANALYSES PERFORMED: Food security status (high, marginal, low, or very low) and frequency of cooking dinner (7, 5 to 6, 3 to 4, or 0 to 2 times/week) were evaluated in relation to PDQS-30D scores (possible range = zero to 126) in age- and sex and gender-, and fully adjusted linear regression models. Postestimation margins were used to predict mean PDQS-30D score by food security status and dinner cooking frequency. The interaction between food security status and frequency of cooking dinner was also tested. RESULTS: Overall, the mean PDQS-30D score was 51.9 ± 11 points (possible range = zero to 126). The prevalence of food insecurity (low/very low) was 43%, 37% of the sample cooked 7 times/week and 15% cooked 0 to 2 times/week. Lower food security and less frequent cooking dinner were both associated with lower diet quality. Very low food security was associated with a 3.2-point lower PDQS-30D score (95% CI -4.6 to -1.8) compared with those with high food security. Cooking dinner 0 to 2 times/week was associated with a 4.4-point lower PDQS-30D score (95% CI -6.0 to -2.8) compared with cooking 7 times/week. The relationship between food insecurity and diet quality did not differ based on cooking dinner frequency. CONCLUSIONS: During the initial months of the coronavirus disease 2019 pandemic food insecurity and less frequently cooking dinner at home were both associated with lower diet quality among low-income Americans. More research is needed to identify and address barriers to low-income households' ability to access, afford and prepare enough nutritious food for a healthy diet.
Subject(s)
COVID-19 , Pandemics , Adult , COVID-19/epidemiology , Cooking , Cross-Sectional Studies , Diet , Female , Food Insecurity , Food Supply , Humans , Male , Meals , Poverty , United States/epidemiologyABSTRACT
BACKGROUND: Access to high-quality dietary intake data is central to many nutrition, epidemiology, economic, environmental, and policy applications. When data on individual nutrient intakes are available, they have not been consistently disaggregated by sex and age groups, and their parameters and full distributions are often not publicly available. OBJECTIVES: We sought to derive usual intake distributions for as many nutrients and population subgroups as possible, use these distributions to estimate nutrient intake inadequacy, compare these distributions and evaluate the implications of their shapes on the estimation of inadequacy, and make these distributions publicly available. METHODS: We compiled dietary data sets from 31 geographically diverse countries, modeled usual intake distributions for 32 micronutrients and 21 macronutrients, and disaggregated these distributions by sex and age groups. We compared the variability and skewness of the distributions and evaluated their similarity across countries, sex, and age groups. We estimated intake inadequacy for 16 nutrients based on a harmonized set of nutrient requirements and bioavailability estimates. Last, we created an R package-nutriR-to make these distributions freely available for users to apply in their own analyses. RESULTS: Usual intake distributions were rarely symmetric and differed widely in variability and skewness across nutrients and countries. Vitamin intake distributions were more variable and skewed and exhibited less similarity among countries than other nutrients. Inadequate intakes were high and geographically concentrated, as well as generally higher for females than males. We found that the shape of usual intake distributions strongly affects estimates of the prevalence of inadequate intakes. CONCLUSIONS: The shape of nutrient intake distributions differs based on nutrient and subgroup and strongly influences estimates of nutrient intake inadequacy. This research represents an important contribution to the availability and application of dietary intake data for diverse subpopulations around the world.
Subject(s)
Diet , Energy Intake , Diet Surveys , Eating , Female , Humans , Male , Micronutrients , Nutritional RequirementsABSTRACT
BACKGROUND: Valid and efficient tools for measuring and tracking diet quality globally are lacking. OBJECTIVE: The objective of the study was to develop and evaluate a new tool for rapid and cost-efficient diet quality assessment. DESIGN: Two screener versions were designed using Prime Diet Quality Score (PDQS), one in a 24-hour recall (PDQS-24HR) and another in a 30-day (PDQS-30D) food frequency format. Participants completed two 24-hour diet recalls using the Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24) and 2 web-based diet quality questionnaires 7 to 30 days apart in April and May 2019. Both dichotomous/trichotomous and granular scoring versions were tried for each screener. PARTICIPANTS/SETTING: The study included 290 nonpregnant, nonlactating US women (mean age ± standard deviation 41 ± 11 years) recruited via Amazon Mechanical Turk. MAIN OUTCOME MEASURES: The main outcome measures were Spearman rank correlation coefficients and linear regression beta-coefficients between ASA24 nutrient intakes from foods and beverages and PDQS values. STATISTICAL ANALYSES PERFORMED: The Spearman rank correlation and linear regression were used to evaluate associations of the PDQS values with ASA24 nutrient intakes from food, both crude and energy-adjusted. Correlations were de-attenuated for within-person variation in 24-hour recalls. Wolfe's test was used to compare correlations of the 2 screening instruments (PDQS-24HR and PDQS-30D) with the ASA24. Associations between the ASA24 Healthy Eating Index 2015 and the PDQS values were also evaluated. RESULTS: Positive, statistically significant rank correlations between the PDQS-24HR values and energy-adjusted nutrients from ASA24 for fiber (r = 0.53), magnesium (r = 0.51), potassium (r = 0.48), vitamin E (r = 0.40), folate (r = 0.37), vitamin C (r = 0.36), vitamin A (r = 0.33), vitamin B6 (r = 0.31), zinc (r = 0.25), and iron (r = 0.21); and inverse correlations for saturated fatty acids (r = -0.19), carbohydrates (r = -0.22), and added sugar (r = -0.34) were observed. Correlations of nutrient intakes assessed by ASA24 with the PDQS-30D were not significantly different from those with the PDQS-24HR. Positive, statistically significant correlations between the ASA24 Healthy Eating Index 2015 and the PDQS-24HR (r = 0.61) and the PDQS-30D (r = 0.60) were also found. CONCLUSIONS: The results of an initial evaluation of the PDQS-based diet quality screeners are promising. Correlations and associations between the PDQS values and nutrient intakes were of acceptable strength and in the expected directions, and the PDQS values had moderately strong correlations with the total Healthy Eating Index 2015 score. Future work should include evaluating the screeners in other population groups, including men, and piloting it across low- and middle-income countries.