Background/Objectives: Ultra-processed food (UPF) consumption has been linked to type 2 diabetes mellitus (T2DM) incidence, but its association with glycemic control in individuals already living with T2DM remains less well characterized. We evaluated the relationship between UPF consumption, assessed with the Turkish version of the short Screening Questionnaire of Highly Processed Food Consumption (sQ-HPF), and HbA1c and poor glycemic control in adults with T2DM. Methods: In this single-centre, cross-sectional observational study, 425 adults aged 18–65 years with T2DM of at least 6 months’ duration were consecutively recruited at a tertiary general internal medicine outpatient clinic. UPF consumption was assessed with the Turkish sQ-HPF (range 0–11; scores ≥ 6 = high UPF consumption). HbA1c was the primary outcome (continuous and dichotomized at 7.0%). Multiple linear and binary logistic regression analyses were performed with hierarchical adjustment for age, sex, body mass index (BMI), diabetes duration, and insulin-based treatment. Results: Total UPF score was positively correlated with HbA1c (r = 0.423, p < 0.001). In the fully adjusted linear model, each one-point increase in total UPF score was associated with a 0.418% higher HbA1c (95% CI: 0.333–0.503; β = 0.413; p < 0.001), explaining 28.9% of HbA1c variance. In the fully adjusted logistic model, each one-point increase in total UPF score was associated with 25.0% higher odds of poor glycemic control (OR = 1.250, 95% CI: 1.110–1.408, p < 0.001). Insulin-based treatment and male sex were also independent predictors. UPF score was not significantly associated with lipid parameters or C-reactive protein. Conclusions: Higher UPF consumption, captured by a brief validated screener, was independently associated with poorer glycemic control in Turkish adults with T2DM. Brief UPF screening may help identify patients who would benefit from targeted nutritional intervention.

Background and Objectives: Chronotype and sleep quality are related but non-identical dimensions of sleep health. We examined whether later chronotype is associated with subclinical visceral adiposity and atherogenic dyslipidaemia independently of perceived sleep quality, and whether this association differs by sex, in adults without previously diagnosed chronic disease. Materials and Methods: This single-centre cross-sectional study included 282 adults without previously diagnosed chronic disease or regular medication use. Chronotype was assessed with the Morningness–Eveningness Questionnaire (MEQ) and sleep quality with the Pittsburgh Sleep Quality Index (PSQI). Composite cardiometabolic indices were calculated from routine anthropometric and biochemical data. Primary dependent variables were log-transformed Visceral Adiposity Index (log[VAI]) and Atherogenic Index of Plasma (AIP). Multivariable linear models used heteroscedasticity-consistent type 3 (HC3) robust standard errors and adjusted for age, sex, education, physical activity, and PSQI; body mass index (BMI) was additionally included in the AIP model. Sex × MEQ interactions, false-discovery-rate (FDR) correction, and glycaemic sensitivity analyses were performed. Results: Median age was 28.0 years; 50.4% were women, 25.9% were evening type, and 51.8% had poor sleep quality. Higher MEQ score (greater morningness) was independently associated with lower log(VAI) (B = −0.0096; 95% confidence interval (CI), −0.0159 to −0.0033; β = −0.190; p = 0.003) and AIP (B = −0.0035; 95% CI, −0.0063 to −0.0008; β = −0.160; p = 0.011), whereas PSQI was not independently associated with either outcome. Sex × MEQ interactions were nominally significant and estimates were stronger in women, but interaction terms did not survive FDR correction. Associations persisted after excluding diabetes-range glycaemia but attenuated in strictly normoglycaemic participants. Conclusions: Later chronotype was associated with a less favourable subclinical adiposity–atherogenic profile independently of perceived sleep quality. Findings are cross-sectional, and the sex-specific pattern is hypothesis-generating. Prospective studies with objective circadian, sleep, dietary-timing, behavioural, and hormonal measures are required.