Association between Ag-RP, alpha-MSH and cardiovascular risk factors regarding adherence to Diet Quality Index- International (DQI-I) among obese individuals

Introduction: Obesity is a strong promoter of cardiometabolic risk factors and is associated with several chronic comorbidities. Recently, the role of α-melanocyte stimulating hormone (α-MSH) and agouti related peptide (Ag-RP) in regulation of energy balance has attracted much attention. In current study, we evaluated the association between α-MSH and Ag-RP with cardiometabolic factors among obese individuals with different adherence to Diet Quality Index-International (DQI-I) values. Methods: In this research, 188 obese adults aged between 20 and 50 years old and body mass index (BMI) between 30 and 40 kg/m2 were recruited. Dietary intakes of participants and DQI-I calculation was performed using a semi-quantitative food frequency questionnaire (FFQ) with 132 food items. Serum glucose, lipids, insulin, and plasma α-MSH and Ag-RP levels were measured using ELISA kits. Homeostasis model assessment for insulin resistance index (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI) were also calculated. Results: Among those with the lowest adherence to DQI-I, Ag-RP was positively associated with systolic blood pressure (SBP) (P = 0.03) among males, which was associated with waist circumference (WC) (P = 0.01) and diastolic blood pressure (DBP) (P = 0.01). Moreover, among males with low and moderate adherence to DQI-I, α-MSH was positively associated with insulin (P = 0.04), weight (P = 0.03), WC (P < 0.01), SDP (P = 0.02) and DBP (P = 0.01). Also, Ag-RP showed a positive association with BMI values (R2 = 0.03; P = 0.03). Conclusion: According to our findings, in obese subjects with poor to moderate adherence to DQI-I, Ag-RP and α-MSH were in positive correlation with cardiometabolic risk factors. These findings further clarify the clinical importance of these parameters as prognostic factors of cardiometabolic abnormalities.

Association between Stress and Metabolic Syndrome and its Mediating Factors in University Students

Objectives: In this study, we evaluated the association between perceived stress and indicators of metabolic syndrome and how this association is mediated by sleep problems, unhealthy eating habits, and night eating syndrome, in addition to serum levels of ghrelin and cortisol in university students. Methods: We recruited 192 students from a public university in Mexico. Weight, height, waist circumference and blood pressure were taken in accordance with standard protocols. Validated questionnaires were used to assess perceived stress, sleep quality and eating habits. Fasting blood samples were taken to measure ghrelin, cortisol, triglycerides, glucose and HDL-C. Results: Path Analysis indicated direct positive effects of stress over PSQI (β = 0.341) and NES (β = 0.443); PSQI over NES (β = 0.233) and NES over glucose (β = 0.170), triglycerides over LDL-C (β = 0.215), waist circumference over SBP (β = 0.259). Likewise, standardized negative regression weights of PSQI over Diet Quality Index (β = -0.239) and ghrelin concentrations (β = -0.132), ghrelin over Diet Quality Index (β = -0.188) and waist circumference (β = -0.147). Diet Quality Index over triglycerides (β = -0.184); sleep duration over systolic blood pressure (β = -0.242); waist circumference over HDL-C (β = -0.256). Conclusion: Psychological stress leads to increased indicators of MetS via decreased sleep quality, inadequate eating habits and eating behavior in university students.

Association between diet quality index, food and nutrient intake, and metabolic parameters in adolescents from Recife, northeastern Brazil

Nutritional studies shifted the focus of attention to the analysis of food quality, addressing general diet considering the foods, food groups, and nutrients included. This study evaluates the association between diet quality index, food and nutrient intake, and metabolic parameters of adolescents from Recife, northeastern Brazil. It is a cross-sectional study involving adolescents aged 12 to 19 years. Food intake was assessed using the Food Frequency Questionnaire to estimate the adapted Diet Quality Index for Adolescents for Brazilians (DQIA-BR-A). The analysis included metabolic parameters (glucose, lipid profile, apolipoprotein A1 and B, 𝛼-1-acid glycoprotein, retinol, 𝛽-carotene, 𝛼-tocopherol, 25(OH)D, and parathormone). Multiple linear regression analysis between the DQIA-BR-A and daily nutrient intake showed a positive correlation (R2adjusted = 0.29) for linoleic fatty acid, calcium, and folate, and a negative correlation for oleic fatty acid, carbohydrates, and vitamin B2 and C, in addition to a low correlation (R2adjusted < 0.07) with all metabolic parameters. However, the DQIA-BR-A correlated significantly (R2adjusted = 0.62; p < 0.001) with food intake. In this way, the DQIA-BR-A can be considered as an accurate and useful instrument for assessing the overall quality of adolescent diets. The diet of the adolescents was considered to be of moderate quality. Changes are required to ensure a balanced diet, considering the high sugar intake and consumption of sweets as well as the low consumption of vegetables, milk and dairy products, oils, fats, and seeds. Such changes should prioritize the consumption of foods rich in essential fatty acids and poor in saturated fat.

Nutrition knowledge, food choices and diet quality of genotyped and non-genotyped individuals during the COVID-19 pandemic

Background: Severe obesity (body mass index ≥ 40 kg/m2) and non-communicable diseases, both influenced by diet, have been associated with COVID-19. Genotype-based personalised nutrition advice may improve nutrition knowledge and enhance behaviour change towards better diet quality compared with conventional recommendations. Aim: To investigate the nutrition knowledge, food choices and diet quality in genotyped and non-genotyped individuals during the COVID-19 pandemic. Methods: One hundred and twenty-three healthy UK adults were recruited using convenience sampling through social networks. The online questionnaire consisted of the General Nutrition Knowledge Questionnaire, the Food Choices Questionnaire, and the EPIC-Norfolk Food Frequency Questionnaire (FFQ). FFQ was used to calculate participant diet quality with the Diet Quality Index-International and socio-demographic and anthropometric data. Results: Median general nutrition knowledge, diet variety and diet balance scores were higher in genotyped compared with non-genotyped individuals (71.0 ± 11.0 vs. 61.0 ± 15.0, p = <.001, 18.00 ± 5.00 vs. 15.00 ± 5.00, p = .007 and 2.00 ± 4.00 vs. 0.00 ± 2.00, p = .025, respectively). Pooled sample multiple regression showed that health motive positively influenced while familiarity motive negatively influenced diet quality index scores ( β = .428, t = 4.822, p = <.001 and β = –.356, t = –4.021, p = .001, respectively). Conclusions: Nutrition knowledge and diet quality indices of balance and variety were higher among genotyped compared with non-genotyped individuals; overall diet quality was similar between groups. This may be due to pandemic-specific factors, such as altered motives of food choice and availability.

Development and Application of a Total Diet Quality Index for Toddlers

For the first time, the 2020–2025 Dietary Guidelines for Americans include recommendations for infants and toddlers under 2 years old. We aimed to create a diet quality index based on a scoring system for ages 12 to 23.9 months, the Toddler Diet Quality Index (DQI), and evaluate its construct validity using 24 h dietary recall data collected from a national sample of children from the Feeding Infants and Toddlers Study (FITS) 2016. The mean (standard error) Toddler DQI was 49 (0.6) out of 100 possible points, indicating room for improvement. Toddlers under-consumed seafood, greens and beans, and plant proteins and over-consumed refined grains and added sugars. Toddler DQI scores were higher among children who were ever breastfed, lived in households with higher incomes, and who were Hispanic. The Toddler DQI performed as expected and offers a measurement tool to assess the dietary quality of young children in accordance with federal nutrition guidelines. This is important for providing guidance that can be used to inform public health nutrition policies, programs, and practices to improve diets of young children.

Use of the Infant Diet Quality Index Score (DQIS) for the Identification of Targets for Nutritional Intervention Among Infants of 4 to 6 Months at Risk of Childhood Obesity

Objectives Healthcare providers have been called to intervene during the first 1000 days of life to reduce childhood obesity. Screening instruments that facilitate the identification of targets for intervention are not currently available. A Diet Quality Index Score (DQIS) was created and measured for its validity in predicting excessive weight gain in a sample of Latino infants. Evidence that infants with BMI percentiles ≥85th at 2 months developed early childhood obesity demands strategies to detect targets for intervention in a systems-based approach. Methods Secondary database analysis using data sourced from a lifestyle intervention project implemented among WIC participants. Assessments were completed on baseline while the infant was 0–2 months of age and follow up at 4–6 months. Socio-demographic and anthropometric characteristics of infants and their caregivers were evaluated. DQIS was calculated using an infant food frequency questionnaire. Descriptive analysis of the variables of interest was conducted. Correlation analysis between the numeric DQIS and categorical assessment of the scale was performed to determine the degree of association of values or risk category associated with a BMI z score percentile at or above 85th according to the age and gender appropriate WHO growth standards. Results 169 dyads were included in this study (Puerto Rico 54.4%), mean caregiver age was 27 y (4.94). 41.4% had achieved an educational level high school or less. In infants: 52% received care in health centers, 82.2% where up to date on vaccinations, 99.4% had an excellent DQIS score at baseline. At follow up 19.5% were found in good and 8.9% needs improvement to poor range. Mean BMI z scores increased from -0.52 (1.35) at birth to 0.9 (1.46) at follow up. Conclusions The infant DQIS used between 4 to 6 months of life as a screening tool could assist non nutritional healthcare providers in the identification of intervention targets while a more detailed assessment is completed. Funding Sources This study was supported by the National Institute of Minority Health and Health Disparities (NIMHD), of the NIH, award number U54MD008149. Infrastructure support also provided by the National Institute on Minority Health and Health Disparities RCMI Grant: 8G12MD007600. This research was also supported by grant U54MD007584 (RMATRIX) from the NIMHD of the NIH.

Variedad en la calidad de la dieta en adultos españoles y mexicanos

Introducción: La pérdida de patrones de alimentación tradicionales a favor de otros más occidentales redunda en un descenso de calidad de la dieta alrededor del mundo. Muchos aspectos determinan la calidad dietética, aunque en general pueden resumirse en una dieta moderada, variada, equilibrada y adecuada para cada individuo. Estos aspectos son evaluados por el Diet Quality Index-International (DQI-I). Objetivo: Comparar la calidad de la dieta de población mexicana y española mediante un índice de calidad internacional de la dieta, determinando que factores son en mayor medida responsables de la pérdida de calidad. Material y métodos: Estudio observacional transversal sobre una muestra representativa de sujetos adultos residentes en Querétaro (México) y de sujetos de la misma franja de edad procedentes de la Región de Murcia, en la cuenca mediterránea española. Se recogieron datos sociodemográficos, antropométricos, de frecuencia de consumo de alimentos y de ingesta con 3 recuerdos de 24 horas y se valoró el DQI-I en la población. Resultados: Se encontraron diferencias para el gasto energético y el DQI-I en todos sus aspectos con valores de calidad superiores para la población mexicana. La variedad fue la dimensión más castigada para todos los sujetos, presentando los mexicanos mejores cifras de consumo de vegetales pero peores para las fuentes proteicas. Conclusiones: La muestra mexicana mejoró las cifras de calidad de la española, tal vez por una mayor influencia de conocimientos en nutrición. El 86% de la población podría mejorar sus puntajes de calidad en el DQI-I ajustando sus frecuencias de consumo de alimentos.

MO598COMPARISON OF GUT MICROBIOTA COMPOSITION BETWEEN PERITONEAL DIALYSIS PATIENTS AND HEALTHY HOUSEHOLD CONTACTS

Background and Aims According to some studies, it seems that advanced chronic kidney disease (CKD) has the potential to cause alterations in the composition of patients gut microbiota. Most of these data have been provided by comparing the microbiota profile between patients and healthy individuals. However, well-known factors that influence the microbiota composition such as age, environment and diet were not considered in the majority of these comparative studies. In the present study, we aimed to compare the gut microbiota composition between patients on peritoneal dialysis (PD) and age-paired healthy household contacts. Method This is a cross-sectional study. Patients undergoing automated PD for at least 3 months, aged 18 to 75 years and clinically stable were enrolled. Those who were using prebiotics, probiotics, symbiotics and antibiotics within a period of 30 days before the study, were not included. A healthy control group was composed by individuals living in the same home and with similar age of the patients. Participants received sterile materials to collect the feces sample and were instructed to keep it refrigerated and bring to the clinic within a period of 12h. To evaluate the microbial profile, 16S ribosomal DNA was PCR-amplified and sequenced on an IlluminaMiSeq platform. Diet was evaluated using a 3-day food record and the diet quality was analyzed by a Brazilian Diet Quality Index. Rome IV questionnaire was applied to diagnose constipation. Nutritional status was assessed by 7-point subjective global assessment (SGA) and body mass index (BMI). Fasting blood samples were collected and clinical data were obtained from interviewing the participants and from the patient’s charts. Data are presented in percentage, mean ± standard deviation or median (interquartile range). Results Twenty patients (PD group) and 20 healthy household contacts (control group) were studied. In PD group: 70% were men, 53.5 (48.2 - 66) years old, 50% had diabetes, BMI 25.9 ± 4.8 kg/m², 95% well-nourished, 40% constipated, 14 (5.2 – 43.5) months on dialysis and 80% had residual diuresis. In control group: 30% were men, 51.5 (46.2 - 59.7) years old, BMI 28.7 ± 3.5 kg/m² and 20% constipated. Except of sex (p = 0.01) and BMI (p = 0.04), there were no other differences between groups. Comparing dietary intake between groups, no difference was found in daily energy [PD: 20.8 ± 5.4 kcal/kg/d vs. control: 22.0 ± 5.6 kcal/kg/d, p = 0.51], protein (PD: 0.8 ± 0.2 g/kg/d vs. control: 0.9 ± 0.2 g/kg/d, p = 0.23) and fiber [PD: 14.1 (10.7 – 21.1) g/d vs. 13.7 (10.4 – 18.0) g/d, p = 0.85]. In addition, the Diet Quality Index was also not different between groups (PD: 52.3 ± 15.6 vs. control: 54.5 ± 14.8, p = 0.65). Regarding microbiota composition, no difference was found between groups in alfa diversity (Figure 1), beta diversity (p&gt;0.05), and genera differential abundance (Figure 2). Conclusion In the present study, no difference in the gut microbiota composition was found between patients on PD and healthy household contacts sharing a similar environment and diet. This result suggests that CKD and PD seem not to alter significantly gut microbiota composition.