Statistical Program to Automate the Creation of Healthy Eating Index Scores Using Nutrition Data System for Research Output

AbstractObjectiveTo develop and evaluate a method for calculating the Healthy Eating Index-2005 (HEI-2005) with the widely used Nutrition Data System for Research (NDSR) based on the method developed for use with the US Department of Agriculture’s (USDA) Food and Nutrient Dietary Data System (FNDDS) and MyPyramid Equivalents Database (MPED).DesignCross-sectional.SettingNon-institutionalized, community-dwelling adults aged 70 years and above.SubjectsTwo hundred and seventy-one adults participating in the Geisinger Rural Aging Study (GRAS) and 620 age- and race-matched adults from the National Health and Nutrition Examination Survey 2001–2002 (NHANES) were included in the analysis. The HEI-2005 scores were generated using NDSR in GRAS and compared to scores generated using FNDDS and MPED in NHANES.ResultsSimilar total HEI-2005 scores (mean 62·0 (se 0·75) in GRAS v. 57·4 (se 0·55) in NHANES) were estimated, and the individual components most strongly correlated with total score in both samples were compared. Cronbach’s coefficient α values of HEI-2005 were 0·52 in GRAS and 0·43 in NHANES.ConclusionsSince NDSR is commonly used for educational purposes, in clinical settings and in nutrition research, it is important to develop methodology for assessing diet quality through the use of HEI-2005 with this dietary analysis software application and its accompanying food and nutrient database. Results from the present study show that HEI-2005 scores can be generated with NDSR using the method described in the present study and the detailed USDA Center for Nutrition Policy and Promotion technical report as guidance.

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Correlations between the Youth Healthy Eating Index, Body Mass Index and the Salivary Nitric Oxide Concentration in Overweight/Obese Children

Endocrine Metabolic & Immune Disorders - Drug Targets ◽

10.2174/1871530314666140307095630 ◽

2014 ◽

Vol 14 (2) ◽

pp. 93-101 ◽

Cited By ~ 8

Author(s):

Elsa Vitale ◽

Emilio Jirillo ◽

Thea Magrone

Keyword(s):

Nitric Oxide ◽

Body Mass Index ◽

Body Mass ◽

Healthy Eating ◽

Healthy Eating Index ◽

Obese Children ◽

Oxide Concentration ◽

Nitric Oxide Concentration

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Mediterranean Diet and Healthy Eating in Subjects with Prediabetes from the Mollerussa Prospective Observational Cohort Study

Nutrients ◽

10.3390/nu13010252 ◽

2021 ◽

Vol 13 (1) ◽

pp. 252

Author(s):

Mireia Falguera ◽

Esmeralda Castelblanco ◽

Marina Idalia Rojo-López ◽

Maria Belén Vilanova ◽

Jordi Real ◽

...

Keyword(s):

Glucose Tolerance ◽

Mediterranean Diet ◽

Healthy Eating ◽

Dietary Patterns ◽

Normal Glucose Tolerance ◽

Healthy Eating Index ◽

Study Cohort ◽

Cross Sectional ◽

Normal Glucose ◽

Multivariable Analyses

We aimed to assess differences in dietary patterns (i.e., Mediterranean diet and healthy eating indexes) between participants with prediabetes and those with normal glucose tolerance. Secondarily, we analyzed factors related to prediabetes and dietary patterns. This was a cross-sectional study design. From a sample of 594 participants recruited in the Mollerussa study cohort, a total of 535 participants (216 with prediabetes and 319 with normal glucose tolerance) were included. The alternate Mediterranean Diet score (aMED) and the alternate Healthy Eating Index (aHEI) were calculated. Bivariable and multivariable analyses were performed. There was no difference in the mean aMED and aHEI scores between groups (3.2 (1.8) in the normoglycemic group and 3.4 (1.8) in the prediabetes group, p = 0.164 for the aMED and 38.6 (7.3) in the normoglycemic group and 38.7 (6.7) in the prediabetes group, p = 0.877 for the aHEI, respectively). Nevertheless, women had a higher mean of aMED and aHEI scores in the prediabetes group (3.7 (1.9), p = 0.001 and 40.5 (6.9), p < 0.001, respectively); moreover, they had a higher mean of aHEI in the group with normoglycemia (39.8 (6.6); p = 0.001). No differences were observed in daily food intake between both study groups; consistent with this finding, we did not find major differences in nutrient intake between groups. In the multivariable analyses, the aMED and aHEI were not associated with prediabetes (odds ratio (OR): 1.19, 95% confidence interval (CI): 0.75–1.87; p = 0.460 and OR: 1.32, 95% CI: 0.83–2.10; p = 0.246, respectively); however, age (OR: 1.04, 95% CI: 1.02–1.05; p < 0.001), dyslipidemia (OR: 2.02, 95% CI: 1.27–3.22; p = 0.003) and body mass index (BMI) (OR: 1.09, 95% CI: 1.05–1.14; p < 0.001) were positively associated with prediabetes. Physical activity was associated with a lower frequency of prediabetes (OR: 0.48, 95% CI: 0.31–0.72; p = 0.001). In conclusion, subjects with prediabetes did not show a different dietary pattern compared with a normal glucose tolerance group. However, further research is needed on this issue.

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Genetic and Environmental Influences of Dietary Indices in a UK Female Twin Cohort

Twin Research and Human Genetics ◽

10.1017/thg.2020.84 ◽

2020 ◽

Vol 23 (6) ◽

pp. 330-337

Author(s):

Olatz Mompeo ◽

Rachel Gibson ◽

Paraskevi Christofidou ◽

Tim D. Spector ◽

Cristina Menni ◽

...

Keyword(s):

Healthy Eating ◽

Menopausal Status ◽

Healthy Eating Index ◽

Healthy Diet ◽

Nutritional Epidemiology ◽

Best Fitting ◽

Heritability Estimates ◽

Fitting Model ◽

Dietary Indices ◽

Health Parameters

AbstractA healthy diet is associated with the improvement or maintenance of health parameters, and several indices have been proposed to assess diet quality comprehensively. Twin studies have found that some specific foods, nutrients and food patterns have a heritable component; however, the heritability of overall dietary intake has not yet been estimated. Here, we compute heritability estimates of the nine most common dietary indices utilized in nutritional epidemiology. We analyzed 2590 female twins from TwinsUK (653 monozygotic [MZ] and 642 dizygotic [DZ] pairs) who completed a 131-item food frequency questionnaire (FFQ). Heritability estimates were computed using structural equation models (SEM) adjusting for body mass index (BMI), smoking status, Index of Multiple Deprivation (IMD), physical activity, menopausal status, energy and alcohol intake. The AE model was the best-fitting model for most of the analyzed dietary scores (seven out of nine), with heritability estimates ranging from 10.1% (95% CI [.02, .18]) for the Dietary Reference Values (DRV) to 42.7% (95% CI [.36, .49]) for the Alternative Healthy Eating Index (A-HEI). The ACE model was the best-fitting model for the Healthy Diet Indicator (HDI) and Healthy Eating Index 2010 (HEI-2010) with heritability estimates of 5.4% (95% CI [−.17, .28]) and 25.4% (95% CI [.05, .46]), respectively. Here, we find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat. Future studies should explore genes underlying dietary indices to further understand the genetic disposition toward diet-related health parameters.

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Higher diet quality is associated with higher diet costs when eating at home and away from home: National Health and Nutrition Examination Survey, 2005-2016

Public Health Nutrition ◽

10.1017/s1368980021002810 ◽

2021 ◽

pp. 1-29

Author(s):

Zach Conrad ◽

Sarah Reinhardt ◽

Rebecca Boehm ◽

Acree McDowell

Keyword(s):

Healthy Eating ◽

National Health ◽

Diet Quality ◽

Healthy Eating Index ◽

Food Prices ◽

Nutrition Examination Survey ◽

Food Away From Home ◽

Health And Nutrition ◽

Food Consumed ◽

At Home

Abstract Objectives: To evaluate the association between diet quality and cost for foods purchased for consumption at home and away from home. Design: Cross-sectional analysis. Multivariable linear regression models evaluated the association between diet quality and cost for all food, food at home, and food away from home. Setting: Daily food intake data from the National Health and Nutrition Examination Survey (2005-2016). Food prices were derived using data from multiple, publicly available databases. Diet quality was assessed using the Healthy Eating Index-2015 and the Alternative Healthy Eating Index-2010. Participants: 30,564 individuals ≥20 y with complete and reliable dietary data. Results: Mean per capita daily diet cost was $14.19 (95% CI: $13.91-14.48), including $6.92 ($6.73-7.10) for food consumed at home and $7.28 ($7.05-7.50) for food consumed away from home. Diet quality was higher for food at home compared to food away from home (P<0.001). Higher diet quality was associated with higher food costs overall, at home, and away from home (P<0.001 for all comparisons). Conclusions: These findings demonstrate that higher diet quality is associated with higher costs for all food, food consumed at home, and food consumed away from home. This research provides policymakers, public health professionals, and clinicians with information needed to support healthy eating habits. These findings are particularly relevant to contemporary health and economic concerns that have worsened because of the COVID-19 pandemic.

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