scholarly journals Neural Substrates of Food Valuation and Its Relationship With BMI and Healthy Eating in Higher BMI Individuals

2020 ◽  
Vol 14 ◽  
Author(s):  
Junaid S. Merchant ◽  
Danielle Cosme ◽  
Nicole R. Giuliani ◽  
Bryce Dirks ◽  
Elliot T. Berkman
Keyword(s):  
Eating Behavior ◽  
Healthy Eating ◽  
Bayes Factor ◽  
Assessment Tool ◽  
Community Sample ◽  
Healthy Eating Index ◽  
Unhealthy Food ◽  
Potential Mechanism ◽  
Imaging Data ◽  
Subjective Valuation

Considerable evidence points to a link between body mass index (BMI), eating behavior, and the brain's reward system. However, much of this research focuses on food cue reactivity without examining the subjective valuation process as a potential mechanism driving individual differences in BMI and eating behavior. The current pre-registered study (https://osf.io/n4c95/) examined the relationship between BMI, healthy eating, and subjective valuation of healthy and unhealthy foods in a community sample of individuals with higher BMI who intended to eat more healthily. Particularly, we examined: (1) alterations in neurocognitive measures of subjective valuation related to BMI and healthy eating; (2) differences in the neurocognitive valuation for healthy and unhealthy foods and their relation to BMI and healthy eating; (3) and whether we could conceptually replicate prior findings demonstrating differences in neural reactivity to palatable vs. plain foods. To this end, we scanned 105 participants with BMIs ranging from 23 to 42 using fMRI during a willingness-to-pay task that quantifies trial-by-trial valuation of 30 healthy and 30 unhealthy food items. We measured out of lab eating behavior via the Automated Self-Administered 24 H Dietary Assessment Tool, which allowed us to calculate a Healthy Eating Index (HEI). We found that our sample exhibited robust, positive linear relationships between self-reported value and neural responses in regions previously implicated in studies of subjective value, suggesting an intact valuation system. However, we found no relationship between valuation and BMI nor HEI, with Bayes Factor indicating moderate evidence for a null relationship. Separating the food types revealed that healthy eating, as measured by the HEI, was inversely related to subjective valuation of unhealthy foods. Imaging data further revealed a stronger linkage between valuation of healthy (compared to unhealthy) foods and corresponding response in the ventromedial prefrontal cortex (vmPFC), and that the interaction between healthy and unhealthy food valuation in this region is related to HEI. Finally, our results did not replicate reactivity differences demonstrated in prior work, likely due to differences in the mapping between food healthiness and palatability. Together, our findings point to disruptions in the valuation of unhealthy foods in the vmPFC as a potential mechanism influencing healthy eating.

scholarly journals Neural Substrates of Food Valuation and Its Relationship With BMI and Healthy Eating in Higher BMI Individuals

2020 ◽  
Author(s):  
Junaid Salim Merchant ◽  
Danielle Cosme ◽  
Elliot Berkman ◽  
Nicole Giuliani ◽  
Bryce Dirks
Keyword(s):  
Eating Behavior ◽  
Healthy Eating ◽  
Bayes Factor ◽  
Assessment Tool ◽  
Community Sample ◽  
Healthy Eating Index ◽  
Unhealthy Food ◽  
Potential Mechanism ◽  
Imaging Data ◽  
Subjective Valuation

Considerable evidence points to a link between body mass index (BMI), eating behavior, and the brain's reward system. However, much of this research focuses on food cue reactivity without examining the subjective valuation process as a potential mechanism driving individual differences in BMI and eating behavior. The current pre-registered study (https://osf.io/n4c95/) examined the relationship between BMI, healthy eating, and subjective valuation of healthy and unhealthy foods in a community sample of individuals with higher BMI who intended to eat more healthily. Particularly, we examined: (1) alterations in neurocognitive measures of subjective valuation related to BMI and healthy eating; (2) differences in the neurocognitive valuation for healthy and unhealthy foods and their relation to BMI and healthy eating; (3) and whether we could conceptually replicate prior findings demonstrating differences in neural reactivity to palatable vs. plain foods. To this end, we scanned 105 participants with BMIs ranging from 23 to 42 using fMRI during a willingness-to-pay task that quantifies trial-by-trial valuation of 30 healthy and 30 unhealthy food items. We measured out of lab eating behavior via the Automated Self-Administered 24 H Dietary Assessment Tool, which allowed us to calculate a Healthy Eating Index (HEI). We found that our sample exhibited robust, positive linear relationships between self-reported value and neural responses in regions previously implicated in studies of subjective value, suggesting an intact valuation system. However, we found no relationship between valuation and BMI nor HEI, with Bayes Factor indicating moderate evidence for a null relationship. Separating the food types revealed that healthy eating, as measured by the HEI, was inversely related to subjective valuation of unhealthy foods. Imaging data further revealed a stronger linkage between valuation of healthy (compared to unhealthy) foods and corresponding response in the ventromedial prefrontal cortex (vmPFC), and that the interaction between healthy and unhealthy food valuation in this region is related to HEI. Finally, our results did not replicate reactivity differences demonstrated in prior work, likely due to differences in the mapping between food healthiness and palatability. Together, our findings point to disruptions in the valuation of unhealthy foods in the vmPFC as a potential mechanism influencing healthy eating.

scholarly journals Investigating Items to Improve the Validity of the Five-Item Healthy Eating Score Compared with the 2015 Healthy Eating Index in a Military Population

Nutrients ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 251 ◽  
Author(s):  
Marissa Shams-White ◽  
Kenneth Chui ◽  
Patricia Deuster ◽  
Nicola McKeown ◽  
Aviva Must
Keyword(s):  
Healthy Eating ◽  
Military Personnel ◽  
Assessment Tool ◽  
Pearson Correlation ◽  
Healthy Eating Index ◽  
Military Population ◽  
Sugar Sweetened Beverage ◽  
Post Exercise Recovery ◽  
Serving Sizes ◽  
Future Work

Military researchers utilize a five-item healthy eating score (HES-5) in the Global Assessment Tool (GAT) questionnaire to quickly assess the overall diet quality of military personnel. This study aimed to modify the HES-5 to improve its validity relative to the 2015 Healthy Eating Index (HEI-2015) in active duty military personnel (n = 333). A food frequency questionnaire was used to calculate HEI-2015 scores and to assess sugar-sweetened beverage (SSB) intake in 8-oz (SSB-8) and 12-oz servings. GAT nutrition questions were used to calculate HES-5 scores and capture breakfast and post-exercise recovery fueling snack (RFsnack) frequencies. Two scoring options were considered for the highest RFsnack category: “4” vs. “5” (RFsnack-5). Potential candidates were added alone and in combination to the HES-5 and compared to the HEI-2015 with a Pearson correlation coefficient. Scores with the highest correlations were compared via a z-score equation to identify the simplest modification to the HES-5. Correlations between HES-5 and HEI-2015 scores in total participants, males, and females were 0.41, 0.45 and 0.32, respectively. Correlations were most significantly improved in total participants by adding RFsnack-5, SSB-8, RFsnack-5 + SSB-8, and RFsnack-5 + SSB-8 + breakfast, though the addition of SSB-8 + RFsnack-5 performed best (r = 0.53). Future work should consider scoring mechanisms, serving sizes, and question wording.

scholarly journals Diet Quality Assessment in Wheelchair Users with Multiple Sclerosis

Nutrients ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 4352
Author(s):  
Stephanie L. Silveira ◽  
Brenda Jeng ◽  
Gary Cutter ◽  
Robert W. Motl
Keyword(s):  
Multiple Sclerosis ◽  
Healthy Eating ◽  
Diet Quality ◽  
Assessment Tool ◽  
Dietary Assessment ◽  
Healthy Eating Index ◽  
Normative Values ◽  
Future Research ◽  
Cross Sectional ◽  
Wheelchair Users

Background: Diet quality has not been distinctively examined in wheelchair users with multiple sclerosis (MS). Methods: This cross-sectional study examined the Diet History Questionnaire (DHQ) III and the Automated Self-Administered 24-h (ASA24) Dietary Assessment Tool in 128 wheelchair users with MS. Participants were prompted to complete the DHQ-III and 3 ASA24 recalls during a seven-day data collection period. Healthy Eating Index (HEI)-2015 scores were calculated for DHQ-III and ASA24, and scores were compared with normative values. Spearman’s correlation analyses (rs) estimated the associations between DHQ-III and ASA24 HEI-2015 total and component scores with supportive paired sample t-tests. Results: HEI-2015 scores for DHQ-III and ASA24 were significantly higher than normative values for total score, total protein foods, and added sugar. Correlations between HEI-2015 scores generated using ASA24 and DHQ-III were all statistically significant (range rs = 0.23–0.69); however, significant differences between ASA24 and DHQ-III values were noted for HEI-2015 total score, total fruits, whole fruit, total vegetable, greens and beans, whole grains, seafood and plant protein, refined grains, and saturated fats. Conclusion: This study provided a novel description of diet quality in wheelchair users with MS for guiding future research promoting healthy eating in this population.

Parent Food and Eating Behavior Assessments Predict Targeted Healthy Eating Index Components

2019 ◽  
Vol 51 (6) ◽  
pp. 711-718 ◽  
Author(s):  
Elizabeth H. Ruder ◽  
Barbara Lohse ◽  
Diane C. Mitchell ◽  
Leslie Cunningham-Sabo
Keyword(s):  
Eating Behavior ◽  
Healthy Eating ◽  
Healthy Eating Index ◽  
Index Components

scholarly journals Attitudes, norms and behaviors enhancing unhealthy food choices of high school students in Armenia

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
L A Aslanyan ◽  
A D Demirchyan
Keyword(s):  
High School ◽  
High School Students ◽  
Eating Behavior ◽  
Healthy Eating ◽  
Eating Behaviors ◽  
Food Choices ◽  
Unhealthy Food ◽  
School Students ◽  
And Behaviors ◽  
School Cafeterias

Abstract Background Negative attitudes towards healthy eating behaviors are common among school-aged children. Given the scarcity of studies investigating eating behaviors among adolescents in Armenia, the current study sought to explore eating behaviors among high school students and assess the attitudes, norms and behaviors enhancing unhealthy food choices among them. Theory of Planned Behavior (TPB) was applied as a theoretical framework. Methods A qualitative study with focus group discussions and in-depth interviews was conducted using semi structured interview guides developed based on TPB framework. The study covered high school students aged 15-18 years old, their parents, teachers and school canteen staff, residing in cities and villages of Shirak province, Armenia. Direct content analysis with deductive approach was used for data analysis. Results The most preferred foods by the adolescents were fast foods, sweets, salads and sugar sweetened beverages. Taste was the most powerful attitudinal factor influencing their food choices. Friends and advertisements were the main role models affecting adolescents’ eating behaviors. Knowledge on unhealthy food choices and the consequences of unhealthy diet on one’s health were adequate among all participants, but unlike rural participants, this factor did not result in healthy eating behavior among urban participants. Lack of time, high cost of food, seasonal changes in food availability, limited food choices in school canteens and low coverage of schools with canteens, especially in the villages, had considerable impact on adolescent’s food choices. Conclusions According to the study results, most of the TPB constructs played role in shaping unhealthy eating behaviors among adolescents. Based on the findings, recommendations were made to conduct social advertising of healthy food choices and healthy eating behaviors among adolescents, empower school cafeterias and increase the coverage of schools with cafeterias. Key messages In Armenia, adolescents’ eating behaviors are mainly influenced by taste, availability, and affordability of food choices, eating behavior of peers and advertisements. Government needs to increase the coverage of schools with cafeterias and empower school cafeterias, so that they suggest healthy, tasty and affordable food choices.

The study of the informativeness and reliability of the healthy eating index for assessing of dietary peculiarity and eating behavior of Russian population

2021 ◽  
Vol 90 (5) ◽  
pp. 77-86
Author(s):  
A.N. Martinchik ◽  
◽  
N.A. Mikhaylov ◽  
E.E. Keshabyants ◽  
K.V. Kudryavtseva ◽  
...  
Keyword(s):  
Eating Behavior ◽  
Healthy Eating ◽  
Healthy Eating Index ◽  
Russian Population

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

Nutrients ◽  
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.

scholarly journals Relative validity and reliability of a diet risk score (DRS) for clinical practice

2020 ◽  
pp. bmjnph-2020-000134
Author(s):  
Emily A Johnston ◽  
Kristina S Petersen ◽  
Jeannette M Beasley ◽  
Tobias Krussig ◽  
Diane C Mitchell ◽  
...  
Keyword(s):  
Risk Score ◽  
Assessment Tool ◽  
High Reliability ◽  
Clinical Care ◽  
Random Order ◽  
Healthy Eating Index ◽  
Validity And Reliability ◽  
Relative Validity ◽  
Dietary Choices ◽  
Diet Assessment

IntroductionAdherence to cardioprotective dietary patterns can reduce risk for developing cardiometabolic disease. Rates of diet assessment and counselling by physicians are low. Use of a diet screener that rapidly identifies individuals at higher risk due to suboptimal dietary choices could increase diet assessment and brief counselling in clinical care.MethodsWe evaluated the relative validity and reliability of a 9-item diet risk score (DRS) based on the Healthy Eating Index (HEI)-2015, a comprehensive measure of diet quality calculated from a 160-item, validated food frequency questionnaire (FFQ). We hypothesised that DRS (0 (low risk) to 27 (high risk)) would inversely correlate with HEI-2015 score. Adults aged 35 to 75 years were recruited from a national research volunteer registry (ResearchMatch.org) and completed the DRS and FFQ in random order on one occasion. To measure reliability, participants repeated the DRS within 3 months.ResultsIn total, 126 adults (87% female) completed the study. Mean HEI-2015 score was 63.3 (95% CI: 61.1 to 65.4); mean DRS was 11.8 (95% CI: 10.8 to 12.8). DRS and HEI-2015 scores were inversely correlated (r=−0.6, p<0.001; R2=0.36). The DRS ranked 37% (n=47) of subjects in the same quintile, 41% (n=52) within ±1 quintile of the HEI-2015 (weighted κ: 0.28). The DRS had high reliability (n=102, ICC: 0.83). DRS mean completion time was 2 min.ConclusionsThe DRS is a brief diet assessment tool, validated against a FFQ, that can reliably identify patients with reported suboptimal intake. Future studies should evaluate the effectiveness of DRS-guided diet assessment in clinical care.Trial registration detailsClinicalTrials.gov (NCT03805373).

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

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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