Healthy Eating Index Research Articles

The effect of Internet use on nutritional intake and health outcomes: new evidence from rural China.

Internet use is changing nutritional intake and health outcomes, but the results are mixed, and less attention is given to the rural developing regions. Based on the China Health and Nutrition Survey (CHNS) data from 2004 to 2015, this study seeks to better understand the effect of Internet use on nutritional intake and health outcomes. An instrumental variable estimation is used to address endogeneity problem. The results show that Internet use improves the dietary knowledge of rural residents, and thus has a positive impact on dietary quality, such as healthy eating index (HEI) and dietary diversity score (DDS). The higher the dietary quality, the better the nutritional health status. However, results also show that Internet use increases the risk of overweight, and obesity among rural Chinese residents. Because Internet use has significantly reduced the physical activity of rural residents in China. Interestingly, we also find that the Internet increases the risk of chronic diseases such as diabetes and high blood pressure, but there is a positive causal relationship between Internet use and the self-assessment score of health. Our findings suggest that there may be a serious lack of awareness of the health risks of chronic diseases among Chinese rural residents. Therefore, policymakers are suggested to consider the possible negative effects when promoting digital development.

Effect of using the snackability app on snack quality among US college students with overweight and obesity: A randomized controlled trial

Objective To determine if using the Snackability app improves snack intake among college students. Participants US college students with overweight/obesity were recruited in June 2020-April 2021. Methods A randomized controlled trial was conducted to test the Snackability app use for 12 wk on snack scores (calculated from the app) compared to controls. We also explored the effect on diet quality (Healthy Eating Index-2015) and weight. Outcomes were compared between the intervention and the control groups at 4, 8, and 12 wk using repeated measures ANOVA. Results Participants in the app group significantly increased snack score at week 4 (p < 0.001) and week 8 (p = 0.015) and increased HEI-2020 score (p < 0.001) at week 4 compared to controls. The first 4 wk had the highest app usage. No significant differences were seen in body weight. Conclusions The Snackability app can be used as a tool to help improve snack and diet quality in this group.

Stability of child appetitive traits and association with diet quality at 5 years and 9–11 years old: Findings from the ROLO longitudinal birth cohort study

BackgroundWe explored change in child appetitive traits from 5 to 9–11 years old and examined associations between appetitive traits at both timepoints and child diet quality.MethodsThis is secondary analyses of the ROLO longitudinal birth cohort study, including mother-child dyads from the 5 and 9–11-year old follow-up. The Children’s Eating Behaviour Questionnaire measured child appetitive traits, with 167 children having matched data for both timepoints. The Healthy Eating Index (HEI) measured diet quality. Linear mixed models and multiple linear regression were completed.ResultsMean (SD) score for ‘Emotional Overeating’ (1.63 (0.51) vs. 1.99 (0.57), p = <0.001) and ‘Enjoyment of Food’ (3.79 (0.72) vs. 3.98 (0.66), p = <0.001) increased from 5 to 9–11 years. Mean score for ‘Desire to Drink’ (2.63 (0.94) vs. 2.45 (0.85), p = 0.01), ‘Satiety Responsiveness (3.07 (0.66) vs. 2.71 (0.66), p = <0.001), ‘Slowness Eating’ (3.02 (0.77) vs. 2.64 (0.78), p = <0.001), and ‘Food Fussiness’ (3.00 (1.04) vs. 2.81 (0.96), p = 0.001) decreased. At 5-years-old, ‘Food Responsiveness’ and ‘Enjoyment of Food’ were positively associated with HEI and ‘Desire to Drink’, ‘Satiety Responsiveness’ and ‘Food Fussiness’ were negatively associated with HEI. At 9–11-years, ‘Enjoyment of Food’ was positively and ‘Desire to Drink’ and ‘Food ‘Fussiness’ were negatively associated with HEI.ConclusionsFood approach appetitive traits increased over time, whereas food avoidant appetitive traits tended to decrease. At both time points ‘Food Fussiness’ and ‘Desire to Drink” were inversely associated with HEI. Further research on how appetitive traits track over childhood and how this relates to dietary quality and weight is warranted.

Dietary quality and dietary greenhouse gas emissions in the USA: a comparison of the planetary health diet index, healthy eating index-2015, and dietary approaches to stop hypertension

BackgroundThe Planetary Health Diet Index (PHDI) measures adherence to the dietary pattern presented by the EAT-Lancet Commission, which aligns health and sustainability targets. There is a need to understand how PHDI scores correlate with dietary greenhouse gas emissions (GHGE) and how this differs from the carbon footprints of scores on established dietary recommendations. The objectives of this study were to compare how the PHDI, Healthy Eating Index-2015 (HEI-2015) and Dietary Approaches to Stop Hypertension (DASH) relate to (a) dietary GHGE and (b) to examine the influence of PHDI food components on dietary GHGE.MethodsWe used life cycle assessment data from the Database of Food Recall Impacts on the Environment for Nutrition and Dietary Studies to calculate the mean dietary GHGE of 8,128 adult participants in the 2015–2016 and 2017–2018 cycles of the National Health and Nutrition Examination Survey (NHANES). Poisson regression was used to estimate the association of (a) quintiles of diet score and (b) standardized dietary index Z-scores with dietary GHGE for PHDI, HEI-2015, and DASH scores. In secondary analyses, we used Poisson regression to assess the influence of individual PHDI component scores on dietary GHGE.ResultsWe found that higher dietary quality on all three indices was correlated with lower dietary GHGE. The magnitude of the dietary quality-dietary GHGE relationship was larger for PHDI [-0.4, 95% CI (-0.5, -0.3) kg CO2 equivalents per one standard deviation change] and for DASH [-0.5, (-0.4, -0.6) kg CO2-equivalents] than for HEI-2015 [-0.2, (-0.2, -0.3) kg CO2-equivalents]. When examining PHDI component scores, we found that diet-related GHGE were driven largely by red and processed meat intake.ConclusionsImproved dietary quality has the potential to lower the emissions impacts of US diets. Future efforts to promote healthy, sustainable diets could apply the recommendations of the established DASH guidelines as well as the new guidance provided by the PHDI to increase their environmental benefits.

Diet in Food Insecurity: A Mediator of Metabolic Health?

Food insecurity (FI) is associated with poor metabolic health. It is assumed that energy intake and diet quality underlie this association. We tested the hypothesis that dietary factors (quantity and quality) mediate the association of FI with excess weight, waist circumference and glycemic control [glycohemoglobin (A1C)]. A mediation analysis was performed on data from the National Health And Nutrition Examination Survey using FI as an independent variable; body mass index (BMI), waist circumference, and A1C as metabolic outcome variables and total energy intake, macronutrients, and diet quality measured by the Healthy Eating Index-2015 (HEI-2015) as potential mediators. Despite a greater prevalence of obesity in participants experiencing FI, daily reported energy intake was similar in food-secure and -insecure subjects. In adjusted analyses of the overall cohort, none of the examined dietary factors mediated associations between FI and metabolic outcomes. In race-stratified analyses, total sugar consumption was a partial mediator of BMI in non-Hispanic Whites, while diet quality measures (HEI-2015 total score and added sugar subscore) were partial mediators of waist circumference and BMI, respectively, for those in the "other" ethnic group. Dietary factors are not the main factors underlying the association of FI with metabolic health. Future studies should investigate whether other social determinants of health commonly present in the context of FI play a role in this association.

Adherence to HEI-2010 and odds of breast cancer according to the menopause status: Evidence from Middle Eastern Country.

Majority of earlier studies have assessed the association between individual healthy eating index-2010 (HEI-2010) and the odds of breast cancer (BC). However, no study has been conducted on the effect of compliance with HEI-2010 and the odds of BC in the Iranian population with a large sample size. Therefore, we aimed to investigate the relationship between the HEI-2010 and the odds of BC in the Iranian population. This population-based case-control study included 350 newly diagnosed cases of BC and 700 healthy controls randomly selected from adult women. HEI-2010 was examined using validated questionnaires. The adherence to HEI-2010 among the participants was divided into four categories. The general characteristics of the participants in the quartiles of the HEI score for categorical variables and continuous variables were evaluated using chi-square and one-way analysis of variance, respectively. Also, using logistic regression analysis, dietary intakes were evaluated in HEI score quartiles. Also, confounding variables were adjusted in different models. People with the highest HEI score had 60% lower odds of BC (OR: 0.40; 95% CI: 0.27, 0.57) than those with the lowest score among post-menopause women. After controlling for age and energy intake, individuals with the highest HEI score were 78% less likely to have BC compared with those with the lowest score (OR: 0.22; 95% CI: 0.14, 0.33). Adjustments for other potential confounders including demographic factors made the association stronger (OR: 0.21; 95% CI: 0.13, 0.32). This association remained significant even after taking BMI into model (OR: 0.27; 95% CI: 0.17, 0.43). Finally, in this study we found an association between HEI-2010 and odds of breast cancer. This association was particularly seen in postmenopausal women. No significant association was found between adherence to HEI-2010 and odds of BC among pre-menopausal.

Food Insecurity and Changes in Diet Quality and Body Mass Index z-Scores Among Elementary School Students.

Background: Previous research has identified food insecurity as a risk factor for obesity but those studies employed cross-sectional designs and were largely focused on adults and young children. In addition, there is a paucity of studies examining the association between food insecurity and changes in children's overall diet quality. This study aimed to assess whether food insecurity is associated with subsequent changes in diet quality and BMI z-scores over 2 years among 7- to 12-year-old children. Methods: We used 2011-2019 secondary data (n = 404) from three randomized controlled trials in Minnesota. Food insecurity was identified using the U.S. Household Food Security Survey Module at baseline (Time 0). Diet quality was determined using the Healthy Eating Index (HEI)-2015 from 24-hour recalls, and BMI z-scores were calculated using measured height and weight. These two outcomes were measured at Time 0, Time 1 (10-12 months from Time 0), and Time 2 (15-24 months from Time 0). Results: Compared with children from food-secure households, those from food-insecure households experienced a 0.13 greater increase in BMI z-scores from Time 0 to Time 2 [95% confidence interval (CI): 0.04 to 0.21] and a 4.5 point increase in HEI-2015 from Time 0 to Time 1 (95% CI: 0.99 to 8.01). Conclusion: Household food insecurity may widen weight disparities among elementary school-aged children. Further studies are needed to identify the role of diet quality in weight changes among children with food insecurity. Clinical Trial Registration Number: NCT01538615, NCT02029976, NCT02973815.

Comparison of metabolic risk factors, lipid indices, healthy eating index, and physical activity among premenopausal, menopausal, and postmenopausal women.

In this study, we aimed to compare metabolic risk factors, lipid indices, healthy eating index, and physical activity among premenopausal, menopausal, and postmenopausal women. In this cross-sectional study, a total of 4,732 women participating in the Hoveyzeh Cohort Study were placed into three groups of premenopausal (n=736), menopausal (n=396), and postmenopausal (n=917) women, according to the inclusion and exclusion criteria . The prevalence of metabolic syndrome was 43.3%, 55.6%, and 62.8% in premenopausal, menopausal, and postmenopausal women, respectively. After menopause, the prevalence of hypertension (50.2%), dyslipidemia (61.2%), diabetes (37.7%), and abdominal obesity according to the Iranian guidelines (75.9%) was higher than before menopause. Based on the results, cardiovascular disease had the highest prevalence after menopause (23%). The weight-adjusted waist index (WWI) had the highest odds ratio (OR) among indices, with values of 2.94 and 1.93 in menopausal and postmenopausal women, respectively (P<0.001). According to the Healthy Eating Index-2015 (HEI-2015), the total consumption of fruits, vegetables, seafood, and protein was higher in premenopausal women than in postmenopausal women, and the consumption of foods containing sugar was higher in menopausal women than in premenopausal women. The results showed that the level of physical activity was the highest and the lowest in premenopausal and postmenopausal women, respectively (P<0.001). Menopause leads to an increase in the prevalence of metabolic syndrome. The Atherogenic Index of Plasma (AIP), Triglyceride Glucose (TyG) index, WWI, and physical activity index increased in postmenopausal women compared to premenopausal women. The TyG index, WWI, and HEI-2015 did not show significant differences between the groups, based on the multiple regression analysis.

Association between dietary patterns and periodontal disease: The OsteoPerio cohort study.

To examine the association of dietary patterns with periodontal disease (PD) and its progression over 5 years. Analyses involved 1197 post-menopausal women from the OsteoPerio cohort. Dietary patterns assessed include Healthy Eating Index-2015 (HEI), Alternative HEI (AHEI), Dietary Approaches to Stop Hypertension (DASH) and alternate Mediterranean Diet (aMed) at baseline (the average of two food frequency questionnaires administered between 1993 and 2001). At baseline and the 5-year follow-up, periodontal assessments evaluated alveolar crestal height (ACH), probing pocket depth (PPD), clinical attachment loss (CAL), percentage of gingival sites bleeding on probing (%BOP) and missing teeth due to PD. Linear and logistic regression were used to examine the associations. Cross-sectionally, HEI and aMed were associated with smaller CAL and %BOP; along with DASH, they were associated with a decreased odds of teeth missing due to PD. AHEI and aMed were associated with a decreased odds of severe PD. Prospectively, AHEI was associated with greater ACH progression. This association was attenuated to the null after loss of ACH was imputed for teeth lost due to PD over follow-up, or after excluding participants with diabetes, osteoporosis, hypertension or heart disease at baseline. Better adherence to healthy dietary patterns was associated with better PD measures cross-sectionally but greater progression of ACH over 5 years. The latter might be explained by incident tooth loss due to PD and pre-existing comorbidities.

Association of Combining Diet and Physical Activity on Sarcopenia and Obesity in Elderly Koreans with Diabetes.

This study aimed to identify the combined factors of physical activity and diet associated with non-sarcopenic non-obese status in 1586 diabetic patients aged ≥65 years from the Korean National Health and Nutrition Examination Survey (2016 to 2019). Participants were categorized into non-sarcopenic non-obesity (NSNO), sarcopenia non-obesity (SNO), non-sarcopenic obesity (NSO), and sarcopenic obesity (SO) groups. NSNO had lower insulin, HOMA-IR, and triglycerides compared to NSO and SO. NSNO had lower perceived stress, higher nutrition education and dietary supplement intake. As assessed by the Korean Healthy Eating Index, NSNO scored higher total than SNO and SO, in breakfast and energy balance compared to SO, and in the adequacy of vegetables and meat/fish/egg/bean compared to SNO. NSNO had significantly higher energy and protein intake and physical activity, with BMI/waist circumference lower than NSO, SO, and comparable to SNO. Physical activity was positively associated with NSNO. Low Total KHEI score and protein intake level reduced the odds ratio (OR) of NSNO, particularly when physical activity was insufficient, with OR = 0.38 for KHEI Q1 and OR = 0.32 for protein T1. In conclusion, physical activity, diet quality, and protein intake are associated with NSNO prevalence in Korean elderly with diabetes, and energy balance through active intake and expenditure may be effective.

The Association Between Diet Quality and Glycemic Outcomes Among People with Type 1 Diabetes

BackgroundThe amount and type of food consumed impacts the glycemic response and insulin needs of people with type 1 diabetes mellitus (T1DM). Daily variability in consumption, reflected in diet quality, may acutely impact glycemic levels and insulin needs. ObjectiveType 1 Diabetes Exercise Initiative (T1DEXI) data were examined to evaluate the impact of daily diet quality on near-term glycemic control and interaction with exercise. MethodsUsing the Remote Food Photography Method, ≤8 d of dietary intake data were analyzed per participant. Diet quality was quantified with the Healthy Eating Index-2015 (HEI), where a score of 100 indicates the highest-quality diet. Each participant day was classified as low HEI (≤57) or high HEI (>57) based on the mean of nationally reported HEI data. Within participants, the relationship between diet quality and subsequent glycemia measured by continuous glucose monitoring (CGM) and total insulin dose usage was evaluated using a paired t-test and robust regression models. ResultsTwo hundred twenty-three adults (76% female) with mean ± SD age, HbA1c, and body mass index (BMI) of 37 ± 14 y, 6.6% ± 0.7%, and 25.1 ± 3.6 kg/m2, respectively, were included in these analyses. The mean HEI score was 56 across all participant days. On high HEI days (mean, 66 ± 4) compared with low HEI days (mean, 47 ± 5), total time in range (70–180 mg/dL) was greater (77.2% ± 14% compared with 75.7% ± 14%, respectively, P = 0.01), whereas time above 180 mg/dL (19% ± 14% compared with 21% ± 15%, respectively, P = 0.004), mean glucose (143 ± 22 compared with 145 ± 22 mg/dL, respectively, P = 0.02), and total daily insulin dose (0.52 ± 0.18 compared with 0.54 ± 0.18 U/kg/d, respectively, P = 0.009) were lower. The interaction between diet quality and exercise on glycemia was not significant. ConclusionsHigher HEI scores correlated with improved glycemia and lower insulin needs, although the impact of diet quality was modest and smaller than the previously reported impact of exercise.

Abstract 754: Exploring the association among pain, gut microbiota, and dietary intake of macronutrients

Abstract Hematopoietic cell transplantation (HCT) is a potentially curative treatment for individuals diagnosed with hematological malignancies. As survival gains increase, symptom management is also being considered as an endpoint for treatment success yet there is paucity in the literature regarding biological correlates of symptoms. Pain is a major concern for patients undergoing HCT. Underlying inflammation has been suspected in the pathogenesis of symptoms including pain. Emerging evidence supports the gut microbiota (GM) as a potential pathway for the initiation of inflammation. Diet is a potentially modifiable factor demonstrating a significant impact on GM diversity and amenable to intervention. Understanding the interplay among pain, GM, and diet, particularly macronutrients, may inform the development of a targeted, dietary self-management intervention to mitigate pain symptoms in HCT patients. This investigation uses baseline data from a longitudinal descriptive study to explore associations among pain, GM composition (richness and evenness) using Shannon and Chao beta diversity indices, and macronutrients (protein, carbohydrates and fat), in 47 adults (&amp;gt; 18 years of age) receiving HCT for hematologic cancer. Pain was measured using the Brief Pain Inventory, GM was assessed using 16S ribosomal gene (V4 region) amplicons using Illumina MiSeq, and dietary information was collected using the Automated Self-Assessment 24-hour Dietary Assessment Tool (ASA-24). Data analysis was performed with the R ‘correlation’ package using Bayesian estimation of robust correlations and production of 95% Credibility Intervals (CI) and Bayes Factors (BF).The mean age of participants was 56.21 years + 14.67 years. Participants were diagnosed with myeloma (40%), lymphoma (29%) and leukemia (13%). The majority received autologous HCT (n=30). Macronutrient fat {r=-0.25, BF=1.72} had an inverse association with pain interference. Results provided at least anecdotal (BF &amp;gt; 1) support for a positive correlation between Healthy Eating Index (HEI) {r=0.21, BF=1.08}, total fat {r=0.32, BF=4.50}, carbohydrate {r=0.28, BF=2.47} and fat {r=0.32, BF=4.50}, and GM composition. Also, there was a positive association between the amount of protein {r=0.21, BF=1.03}, carbohydrate {r=0.27, BF=2.22}, and Chao Index. There was an inverse association between total HEI {r=-0.27, BF=1.87} and CRP levels. Taxonomic units {r=-0.41, BF=21.44}, Chao Index {r=-0.41, BF=20.28} and Shannon Index {r=-0.25, BF=1.47} had an inverse association with CRP level. This study associate pain, GM, and dietary macronutrients, suggesting potential GM targeted interventions. More research with larger sample size is needed to understand underlying dietary macronutrients' role in pain through GM diversity after HCT, aiming to ease symptoms and enhance survivorship. Citation Format: Elham Samami, Fan Yi, Michael Weaver, Angela Starkweather, Debra Lyon, Debra Lynch Kelly. Exploring the association among pain, gut microbiota, and dietary intake of macronutrients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 754.

Abstract 6151: Relationship between polygenic risk score, lifestyle factors, and colorectal cancer risk

Abstract Although heritable factors are estimated to explain up to 35% of colorectal cancers (CRC), most are diagnosed in people without a family history of CRC suggesting that inherited genetic variants, environmental factors, or a combination of both, contribute to CRC risk. We explored the relationship between a polygenic risk score (PRS) for CRC risk and lifestyle risk factors to understand whether individuals with higher genetic risk, who do not develop CRC, engage in healthier lifestyle behaviors, or conversely, whether those with lower genetic risk, who do develop CRC, engage in riskier behaviors in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Using summary statistics obtained from a large independent GWAS meta-analysis of CRC by the GECCO consortium, we developed a genome-wide PRS for CRC using SBayesR and applied it to participants of European ancestry genotyped in the PLCO Trial (n=74,396). For all subjects, we computed an environmental (E) score based on 19 lifestyle risk factors for CRC, a WCRF/AICR score that measured adherence to the 2018 Cancer Prevention recommendations, and a 2015 healthy eating index (HEI) with higher values indicating healthier lifestyle profiles. We used t-tests to evaluate differences in lifestyle scores between CRC-free participants in the highest quartile of PRS and incident CRC cases in the lowest quartile of PRS. To examine the correlations between the PRS and lifestyle scores, we performed multivariable linear regression models regressing PRS on each lifestyle score. We used multivariable Cox hazards regression models to compute hazard ratios and 95% confidence intervals for CRC risk; multiplicative interactions between PRS and lifestyle scores were evaluated using the Wald test for the interaction terms. During the 15 years follow-up period, a total of 1,052 CRC cases were diagnosed. Individuals in the highest quartile of PRS who remained cancer-free were more likely to engage in healthier behaviors than those in the lowest quartile of PRS who were diagnosed with incident CRC (E-score: -0.01 vs. -0.18, WCRF/AICR score: -0.05 vs. -0.32, HEI score: 0.06 vs. -0.13); however, differences were not statistically significant (P value: 0.1 to 0.4). PRS and lifestyle scores were significantly (all P &amp;lt;0.0001), albeit weakly (β: -0.02 to -0.03), associated among participants who remained CRC-free but not among CRC cases (P: 0.1 to 0.3). PRS-lifestyle score interactions were not statistically significant (P: 0.2 to 0.4). Although the differences and multiplicative interaction models were not statistically significant, we found that individuals with a higher PRS who remained CRC-free were slightly more likely to engage in healthier behaviors than those at a lower genetic score who developed CRC. Additional studies with larger sample size are warranted to further explore the interplay between genetic risk and lifestyle factors related to CRC risk. Citation Format: Wen-Yi Huang, Erikka Loftfield, Rebecca Landy, Difei Wang, Hormuzd A. Katki, Jianxin Shi, Lingxiao Wang, Mitchell J. Machiela, Neal D. Freedman, Sonja I. Berndt. Relationship between polygenic risk score, lifestyle factors, and colorectal cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6151.

Adherence to dietary guidelines associated with lower medical service utilization in preschoolers: a longitudinal study

ObjectiveWe aimed to evaluate the association between dietary guideline adherence and overall, outpatient, and emergency medical service utilization in Taiwanese preschoolers.MethodsWe selected 614 preschoolers (2–6 years) who had one day of 24-h dietary recall data from the 2013–2016 Nutrition and Health Survey in Taiwan. The Taiwanese Children Healthy Eating Index (TCHEI) was developed on the basis of Taiwanese Food-Based Dietary Guidelines; it assesses dietary adequacy and eating behavior. Data on the participants’ outpatient and emergency medical service utilization were obtained for 2013–2018 from the National Health Insurance Research Database. A multivariable generalized linear model was used to evaluate the association between the TCHEI and medical service utilization for all disease and respiratory diseases.ResultsAfter adjustment for confounding factors, children aged 2–3 years in the Tertile (T) 2 and T3 groups of the TCHEI exhibited 25% (95% CI 0.69–0.83) and 16% (95% CI 0.77–0.92) lower overall medical visits, respectively. The same pattern was noted in the outpatient and emergency visits for all diseases and respiratory diseases. The children aged 4–6 years in the T2 group exhibited 15% (95% CI 0.80–0.91) and 11% (95% CI 0.82–0.97) lower overall visits and visits for respiratory diseases, respectively. Moreover, preschoolers in the T2 group exhibited lower overall medical expenditures than did those in the T1 group.ConclusionsTCHEI score was positively correlated with better nutritional status. Optimal dietary intake associated with lower medical service utilization among Taiwan preschoolers.

Adult dietary patterns with increased bean consumption are associated with greater overall shortfall nutrient intakes, lower added sugar, improved weight-related outcomes and better diet quality

BackgroundLimited evidence is available that focuses on beans within American dietary patterns and health. The purpose of this study was to identify commonly consumed adult dietary patterns that included beans and compare shortfall nutrient intakes and diet quality, relative to adults whose typical dietary pattern did not include beans.MethodsThe analyses used data from the National Health and Nutrition Examination Survey, 2001–2018. Cluster analysis was used to identify bean patterns of consumption, while the USDA food coding system defined daily beans consumed. Five bean dietary patterns of consumption were identified, of which four patterns included both canned beans and dry beans, while one pattern had no bean consumption. Bean consumption was defined as those consuming kidney beans, black beans, chickpeas, and/or pinto beans.ResultsAdults consuming Bean Dietary Patterns 1, 2, 3 and 4 had significantly higher diet quality scores (as assessed by USDA’s Healthy Eating Index-2015) compared to the no-bean pattern (61.2 ± 0.5, 58.9 ± 0.5, 55.2 ± 0.4 and 56.5 ± 0.8 vs 48.8 ± 0.2 p’s < 0.0001). Bean consumers also had significantly higher intakes of several shortfall nutrients (choline, alpha-linolenic acid, folate, iron, magnesium and vitamin E) relative to non-consumers of beans. Similarly, intake of dietary fiber, potassium and calcium, all nutrients of public health concern were significantly higher in bean patterns compared to no-beans. Bean Dietary Pattern 1 (~ 13.5% of total daily kcal from beans or ~ 2 servings of beans/day) and 2 (~ 9.5% of total daily kcal from beans or ~ 1.7 servings of beans/day) were significantly associated with lower BMI, decreased body weight and improved waist circumference relative to no-beans.ConclusionsDietary patterns that are rich in canned and dry beans were associated with significantly higher diet quality scores and greater intake of shortfall nutrients, including nutrients of public health concern. Bean dietary patterns were also associated with improved weight-related outcomes. Dietary guidance should consider the nutrient and health benefits associated with the promotion of increased canned and dry bean consumption in American dietary patterns.

School Meal Nutrition Standards Reduce Disparities Across Income and Race/Ethnicity

Children's diets in the U.S. typically fail to meet dietary recommendations, contributing to associated adverse health outcomes. The Healthy, Hunger-Free Kids Act (HHFKA) of 2010 required the U.S. government to update nutrition standards for school meals to align with the Dietary Guidelines for Americans (DGAs). This study estimates the evolving impact of substituting school-prepared food for home-prepared food on overall daily diet quality and by subcomponents of diet quality. Subgroup analyses are performed by race/ethnicity and income. Two, nonconsecutive days of dietary recall data from the National Health and Nutrition Examination Survey (2005-March 2020) are used to calculate schoolchildren's Healthy Eating Index (HEI)-2020 scores. The study includes children with complete two-day dietary intakes who attend kindergarten through twelfth grade in a school offering lunch. An individual-level fixed effects regression is employed to examine the relationship of school food consumption on HEI-2020 scores before and after HHFKA-mandated changes in nutrition standards. Analyses were conducted on September 23, 2023. Prior to changes in standards (2005-2008), school food did not impact diet quality within the overall group of children. In 2009-2012, positive associations between school food and diet quality emerged for low-income students and for non-Hispanic Black students. By 2013-2020, improvements were seen across all groups. The association between school food and diet quality was most attributable to more favorable consumption of dairy, fruit, whole grains, refined grains, added sugars and saturated fats. HHFKA-based nutrition standards were associated with beneficial dietary changes and reduced dietary disparities for children across diverse backgrounds.

Abstract P197: Dietary Quality Determined by Healthy Eating Index-2015 and Endothelial Function in Healthy Adults

The Healthy Eating Index (HEI) is a measure of diet quality based on Dietary Guidelines for Americans and developed in collaboration with the US Department of Health and Human Services and the US Department of Agriculture. Clinical interest in HEI has increased due to its association with obesity, inflammatory biomarkers and risk of coronary heart disease and stroke. Indeed, higher HEI-2015 score has been linked with reduced cardiovascular risk, morbidity, and mortality. Endothelial dysfunction, particularly impaired endothelium-dependent vasodilation, is a central etiological factor underlying cardiovascular risk and events. We and others have previously demonstrated that diets high in saturated fat and other proatherogenic diets are associated with endothelial vasodilator dysfunction. It is currently unknown whether HEI-2015 dietary score is associated with endothelial function. If so, assessing dietary quality based on HEI-2015 may provide targeted nutritional guidance for enhancing vascular health and mitigating cardiovascular risk. The aim of this study was to determine whether HEI-2015 score is associated with endothelial vasodilator function in healthy adults. Using data from 4-day dietary records, HEI-2015 scores were determined in 103 adults (65 M/38 F; age 44-68 years) free of overt cardiometabolic disease. The HEI-2015 score is based on 13 components summed to yield a total score from 0 to 100; higher score representing higher diet quality. The adults were stratified by HEI-2015 score quartiles: Q1: HEI &lt; 52.5 (n=25; 23 M/2 F); Q2: HEI 52.6-59.1 (n=26; 14 M/12 F); Q3: HEI 59.2-66.0 (n=26; 15 M/11 F); and Q4: HEI &gt; 66.0 (n=26; 13 M/13 F). Endothelium-dependent vasodilation was determined by forearm blood flow (FBF) (via plethysmography) responses to intra-arterial infusion of acetylcholine (ACh: 4.0, 8.0, and 16.0 μg/100 mL tissue/min) and sodium nitroprusside (NTP: 1.0, 2.0, and 4.0 μg/100 mL tissue/min). There were no significant differences in endothelium-dependent vasodilation across the HEI-2015 score quartiles. FBF blood responses to ACh were remarkably similar between Q1 (5.1±0.2 to 13.0±0.7 mL/100 mL tissue/min), Q2 (4.3±0.2 to 12.1±0.7 mL/100 mL tissue/min), Q3 (4.4±0.2 to 13.0±0.7 mL/100 mL tissue/min) and Q4 (4.5±0.2 to 14.4±0.6 mL/100 mL tissue/min). Moreover, HEI scores were not significantly associated with the vasodilator response to either ACh (r=0.15, P=0.13) or NTP (r=-0.04; P=0.72). In summary, although diet quality determined by HEI-2015 score has been shown to be associated with increased risk of cardiovascular disease and events, HEI-2015 was not associated endothelial function in mid-life and older adults. Given the established experimental and pathophysiological evidence linking between diet, endothelial vasodilator function and cardiovascular risk, HEI-2015 score is not a sensitive dietary indicator/biomarker of vascular function.

Association between joint physical activity and healthy dietary patterns and hypertension in US adults: cross-sectional NHANES study

BackgroundLack of physical activity (PA), poor dietary habits, or other unhealthy lifestyle behaviors are potential modifiable risk factors for hypertension. It has been sufficiently demonstrated in previous studies that physical activity or healthy dietary patterns can reduce the risk of hypertension. However, no research focused on the joint effects of PA and healthy dietary patterns on hypertension in a representative sample of adults.MethodsWe used data collected from the 2007–2018 National Health and Nutrition Examination Survey. Healthy dietary patterns were assessed with the Healthy Eating Index 2015 (HEI-2015), and PA was measured using the metabolic equivalent minutes per week reported in questionnaires. We created four lifestyle categories based on the HEI-2015 and PA: (1) unhealthy diet and physically inactive (less than recommended PA), (2) healthy diet but physically inactive, (3) unhealthy diet but physically active (recommended PA), (4) healthy diet and physically active. Logistic regression was used to evaluate the association between joint PA and HEI-2015 and hypertension.ResultsA total of 24,453 participants were enrolled in the study. Compared with unhealthy diet and physically inactive individuals, only healthy diet and physically active participants (adjusted odds ratio [AOR]: 0.77, 95% CI 0.65–0.9) were negatively associated with hypertension, while healthy diet but physically inactive participants (AOR: 0.89, 95% CI 0.76–1.03) and unhealthy diet but physically active participants (AOR: 0.9, 95% CI 0.76–1.06) were not associated with hypertension.ConclusionIn a representative sample of US adults, our findings suggest that individuals with recommended PA and healthy dietary patterns have a lower risk of hypertension than those with an unhealthy diet or less than recommended PA. Healthy eating habits and regular PA are potential preventive precautions against hypertension.

Abstract P203: Healthy Diet Perception, Cardiovascular Disease, and Risk Factors in Americans

Introduction: Healthy diet perception may influence cardiovascular (CV) outcomes. Misperceptions on the healthfulness of one’s diet can interfere with the precontemplative and contemplative stages of behavioral change if individuals overestimate their diet quality. Using a nationally-representative sample, we explored the prevalence of healthy diet misperception in the general population and in those with CV diseases, as well as whether misperceptions are associated with clinical CV risk factors. Methods: We included adults≥20 years old from the National Health and Nutrition Examination Survey 2017-2020. Using survey data on participants’ perception of their own diet and diet recall data to calculate Healthy Eating Index-2015 (HEI), we divided participants into dietary quantiles. We categorized healthy diet perception (HDP) as overestimated (perceived&gt;HEI quantile), accurate (perceived=HEI quantile), or underestimated (perceived&lt;HEI quantile). We categorized those who self-reported hypertension, coronary heart disease, myocardial infarction, congestive heart failure, and stroke as having CV disease. Clinical CV risk factor measures were body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), hemoglobin A1c, total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL). We used multiple logistic regression to measure the association between CV disease and HDP and multiple linear regression for HDP and CV risk factors, stratified by presence of CV disease. Results: Of 7,710 adults, 4,470 (57.5 weighted %) overestimated HDP; 1,924 (25.6 weighted %) underestimated HDP; and 1,316 (16.9 weighted %) correctly estimated HDP. After adjusting for age, sex, and education level, having CV disease was not associated with incorrectly estimating HDP (adjusted OR 1.08; 95% CI 0.93, 1.26) or overestimating HDP (adjusted OR 1.21; 95% CI 1.00, 1.48), compared to correctly estimating HDP. Among those with CV disease, overestimating HDP was associated with higher BMI (adjusted difference 1.9 m/kg 2 ; 95% CI 0.8, 2.9) and lower HDL (adjusted difference -2.8 mg/dL; 95% CI -5.1, -0.5). Among those without CV disease, overestimating HDP was only associated with higher BMI (adjusted difference 1.9; 95% CI 0.8, 2.9) Conclusions: More than half of Americans overestimate their diet quality, and adults with CV disease do not estimate diet quality more accuracy than those without CV disease. Among adults with CV disease, misperceptions in diet quality were associated with worse CV risk factor profiles, highlighting the need to assess and educate patients with CV disease on personal diet quality as part of healthy lifestyle promotion. Among those without CV disease, dietary misperceptions were associated with higher BMI, suggesting that increasing awareness of one's diet is also important in CV disease prevention.

Abstract P476: Changes in Olive Oil Consumption and Weight Changes in US Men and Women

Background: Olive oil intake is inversely associated with the risk of chronic diseases and mortality. However, it is unclear whether there is an association between olive oil intake and weight changes; because it is an energy-dense food concerns have been raised that high intake may contribute to weight gain. Therefore, we aimed to determine the associations between long-term changes in olive oil consumption and changes in weight. Methods: We examined data from 116,243 women and men from the Nurses’ Health Study (NHS, 1990-2010), NHSII (1991-2015), and Health Professional Follow-up Study (HPFS, 1990-2014), who were free from chronic diseases at baseline. We applied multivariable linear regression models with robust variance estimators to assess the association of changes in olive oil intake within each 4-year interval with concurrent weight changes. Results across the three cohorts were pooled using inverse-variance weights. Results: At baseline, mean ± SD age was 54.8 ± 6.6 years in the NHS, 45.3 ± 8.0 years in the NHS2, and 53.9 ± 7.2 years in the HPFS. Mean body mass index was 25 kg/m2 at baseline across the three cohorts. The mean weight gain over each 4-year follow-up cycle was highest in the NHS2 (1.8; 95%CI -6.8 to 11.3 kg), followed by the NHS (1.0; 95%CI -6.8 to 9.1 kg), and lastly the HPFS (0.6; 95%CI -5.4 to 6.8 kg). Pooling across the cohorts after adjustment for sociodemographic, lifestyle, and set of dietary factors (fruits, vegetables, red and processed meat, sugar sweetened beverages, coffee, refined grains), each ½ Tablespoon (7 grams) serving per day increment in olive oil was associated with a slightly lower 4-year weight gain of -0.06 kg (95%CI -0.08 to -0.04 kg; p&lt;0.0001). This inverse association was observed in the three cohorts, with a greater magnitude of association in the NHS2 (-0.08; 95%CI -0.10 to -0.05 kg; p&lt;0.0001), followed by the HPFS (-0.07; 95%CI -0.12 to -0.02 kg; p=0.003) and lastly the NHS (-0.05; 95%CI -0.07 to -0.01 kg; p=0.02). Results were attenuated after adjustment for the Alternative Healthy Eating index (pooled -0.03; 95%CI -0.05 to -0.02; p=0.0003). Conclusions: Long-term habitual increase in olive oil consumption was not associated with increased weight gain in middle-aged and older adults.