Adolescents’ food choices as snacks typically consist of energy-dense and nutrient-poor foods, with fruits and dairy products contributing a smaller proportion.(1) This pattern may put adolescents at increase cardio metabolic risk. However, there is a lack of study examining the association between snack characteristics such as frequency, energy density (ED), and snack nutritional quality with cardio metabolic risk in adolescents. This study aims to examine the association between snack characteristics (snack frequency, ED and nutritional quality) with diet quality and cardiometabolic risks among a nationally representative sample U.S. adolescents.

Cross-sectional dietary data collected using a 24-hour dietary recall from the 2011-2016 National Health and Nutrition Examination Survey (1,999 boys and 1,897 girls aged 12–19 years) were analyzed. Snack frequency was measured as the number of snacks per day, self-reported by participants. Snack ED was calculated both with and without beverages. Snack nutritional quality was assessed using the Hybrid Nutrient Density Score. The associations for snack characteristics with diet quality (Healthy Eating Index-2015) and continuous cardiometabolic risk factors (fasting blood glucose, triglyceride, total cholesterol, high-density lipoprotein, low-density lipoprotein, blood pressure, waist circumference, metabolic syndrome risk score) were examined using multiple linear regression, stratified by sex and adjusted for important covariates.

Higher snack nutritional quality (β [95% CI]: boys 0.31 [0.09, 0.52]; girls 0.44 [0.30, 0.57]; p < 0.01, p < 0.001), and snack ED excluding beverages (β [95% CI]: boys -1.82 [-2.52, -1.12]; girls -1.75 [-2.69, -0.82]; p < 0.001) were associated with higher diet quality, in both sexes. Among girls, higher snack frequency was associated with lower waist circumference and lower fasting blood glucose. Additionally, higher snack ED and nutritional quality were associated with lower waist circumference and triglycerides, respectively. No associations between snack characteristics and cardiometabolic risks were observed for boys.

Findings suggest strategies to improve adolescent snack nutritional quality and ED may improve overall diet quality. However, few modest associations were observed between snack characteristics and cardiometabolic risk indicators among girls. Prospective studies are needed to further investigate the relationship between snack characteristics and adolescent health outcomes.

Malnutrition is a common but underrecognized clinical problem associated with sarcopenia, frailty, fragility fractures, and multiple long-term conditions (1). Malnutrition increases treatment costs, hospital stays, and secondary care recovery. Current methods of identifying malnutrition rely on direct measures of weight loss and BMI which are often less used and so malnutrition is often missed (2).

As the first step in developing a digital application the EAMIT (East Anglian Malnutrition Identification Tool) for identifying malnutrition, using factors recorded in routine clinical healthcare data, including combinations of demographic factors, health care data (e.g. medications) and clinical biochemistry (e.g. CRP), we examined the data for these factors in the CPRD (2).

Individuals screened with the MUST tool (Malnutrition Universal Screening Tool), older than 65 years, and a matched set of people according to age, sex and GP practice were identified within the CPRD Aurum datalink (Feasbility Study reference FS_002595).

Four groups were examined for demographic, health care and clinical biochemistry variables according to MUST screening category result: 1) low risk of malnutrition, 2) medium risk 3) high risk (MUST_H), 4) matched unscreened individuals (MUST_0), and either medians (IQR) or percentage of individuals per group were calculated.

The percentage of people over 85Y was 47% in in the MUST_H group, versus 43% in MUST_0. Median, IQR BMI ranged from MUST_0 26.3 kg/m2 (23.1-29.8) to 18.3 kg/m2 (16.7-20.9) in MUST_H. Median weight loss was -5.9% in MUST_H compared with 0.1% in MUST_ 0. As expected, 50% of people in MUST_H had a BMI <18.5 kg/m2 compared with 1% in MUST_0, though the percentage of missing values for BMI was 72%-80% in MUST categories, and 50% in MUST_0. The median number of GP visits (year before screening) was 12 (IQR 6-20) per year in MUST_H compared with 8 (IQR 4-16) in MUST_0. Number of people prescribed 5+ medications was 25% higher in MUST_H than MUST_0.

Clinical biochemistry data differed by group. The percentage with low albumin (<35g/L) was 6.5% in MUST_0 compared with 22.8% in MUST_H, iron deficiency as low Hb [<120g g/l (women); <130g/l (men)] ranged from 18% in MUST_0 to 36% in MUST_H. CRP, median IQR, was higher in MUST_H (7; 3-25) compared with MUST_0 (5;2-10).

Gradients were found across categories of MUST, and between matched individuals, of greater age, lower BMI, greater percentage of weight loss, lower concentrations of haemoglobin and albumin and higher concentrations of CRP. The number of medications and visits to GPs increased according to category of MUST screening. The proportion of missing BMI data indicates the need to develop a new tool but sufficient demographic, health care and clinical biochemistry data exists within the CPRD database to continue developing an algorithm for identifying risk of malnutrition in the community.

Long-COVID (LC) affects over 400 million individuals globally and is characterised by persistent fatigue, cognitive dysfunction, and gastrointestinal disturbances(1,2). The possible underlying immunological mechanisms associated with LC remain poorly understood. A possible mechanism would link gut dysbiosis and altered gut metabolic output- in particular with respect to the production of short-chain fatty acids (SCFAs)- to immune dysregulation in LC(3). SCFAs, primarily acetate, propionate, and butyrate, are key modulators of T-cell function(4). A deficiency in SCFAs due to prolonged dysbiosis and poor diet due to reduced mobility and fatigue may drive immune exhaustion and chronic low-grade inflammation commonly observed in LC patients. This study aims to characterise CD4+T cells in LC patients and explore the regulatory role of SCFAs on T-cell functionality under the context of LC.

Multiple flow cytometry panels were employed on PBMC from Long-COVID patients (LC, n=15) and matched No-Fatigue controls (CT, n=10), to quantify T-cell subsets (as % of CD4+T-Cells), assessing exhaustion (PD-1, CD44, LAG3, CD38, CD57), differentiation (CD45RO/RA, CD27, CD62L), activation markers (HLA-DR, CD25) and frequency of Treg (CD25high FOXP3highCD127low). Serum cytokine levels were quantified using a multiplex chemiluminescence-based assay platform. Stimulation assays were performed using CD3+ T-cells using CD3/CD28 activation-bead in the presence/absence of SCFAs (acetate, butyrate, propionate) at 0.125-2 mM/ml concentrations toward optimising inducible Treg assays in the future.

CD4+ T cells in LC showed elevated exhaustion markers: PD-1 (34%, p = 0.0001), CD44 (24%, p = 0.03), CD38 (43%, p = 0.07), and LAG3 (19%, p = 0.0063). CD8+ T cells had increased PD-1 expression in 15% of LC patients. CD57+ memory CD4+ T cells were reduced (p = 0.006), and CD62L+ naïve CD4+ T cells were higher in LC (p = 0.008). Naïve/memory balance in CD8+ T cells shifted (−21% memory, +32% naïve). Treg frequencies showed a lower median in LC, though not statistically significant. CRP levels were elevated in 73% of LC patients vs. 12% of controls (p < 0.0001). IL-4 and IL-6 were elevated in 44% and 41% of LC patients, respectively (p < 0.0001). Hierarchical clustering revealed six immune clusters, four dominated by LC with distinct inflammatory or Th2/Th17 profiles.

Preliminary SCFA assays showed butyrate (≥0.5 mM) suppressed CD3/CD28-induced proliferation in CD4+ and CD8+ T cells. Propionate was effective at ≥1 mg/mL; acetate had no effect up to 2 mM.

LC patients show marked immune changes on CD4+T-cells for exhaustion but on CD8+T- cells for differentiation and high cytokine levels in the circulation. The observed heterogeneity may relate to symptoms, which will be explored later. Preliminary SCFA functional assay data suggest SCFAs, especially butyrate, can regulate T-cell proliferation, supporting the idea of a link between the gut (dysbiosis) and the immune system in LC pathophysiology.