Despite knowledge of classical coronary artery disease (CAD) risk factors, the morbidity and mortality associated with this disease remain high. Therefore, new factors that may affect the development of CAD, such as the gut microbiome, are extensively investigated. This study aimed to evaluate gut microbiome composition in CAD patients in relation to the control group. We examined 169 CAD patients and 166 people in the control group, without CAD, matched in terms of age and sex to the study group. Both populations underwent a detailed health assessment. The microbiome analysis was based on the V3–V4 region of the 16S rRNA gene (NGS method). Among 4074 identified taxonomic units in the whole population, 1070 differed between study groups. The most common bacterial types were Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Furthermore, a higher Firmicutes/Bacteroidetes ratio in the CAD group compared with the control was demonstrated. Firmicutes/Bacteroidetes ratio, independent of age, sex, CAD status, LDL cholesterol concentration, and statins treatment, was related to altered phosphatidylcholine concentrations obtained in targeted metabolomics. Altered alpha-biodiversity (Kruskal–Wallis test, p = 0.001) and beta-biodiversity (Bray–Curtis metric, p < 0.001) in the CAD group were observed. Moreover, a predicted functional analysis revealed some taxonomic units, metabolic pathways, and proteins that might be characteristic of the CAD patients’ microbiome, such as increased expressions of 6-phospho-β-glucosidase and protein-N(pi)-phosphohistidine-sugar phosphotransferase and decreased expressions of DNA topoisomerase, oxaloacetate decarboxylase, and 6-beta-glucosidase. In summary, CAD is associated with altered gut microbiome composition and function.

Background: The aim of this study was to assess risk factors for tooth loss in the population of the city of Bialystok, in north-eastern Poland, taking into account the entire population and different age groups. The study included 1138 subjects divided into three subgroups: 20–44 years, 45–64 years, and 65–79 years. Participants were classified according to the number of teeth lost (0–8 vs. 9–28). Socio-economic variables, smoking history, and dental habits were collected through a questionnaire. Medical examinations provided data on the body mass index and the fasting blood glucose level. Data were statistically analysed using Mann-Whitney U, Student’s t, chi² tests, and binary logistic regression, p < 0.05. Results: For the general population, being female (OR 1.38, 1.07–1.79, p = 0.015), having secondary education (OR 4.18, Cl 2.97–5.87, p < 0.000), higher body mass index (OR 1.13, Cl 1.10–1.17, p < 0.000), higher fasting blood glucose level (OR 1.03 1.03–1.04, p < 0.000), being former smoker (OR 1.72, Cl 1.29–2.31, p < 0.000), ever smoker (OR 1.69, Cl 1.29–2.20, p < 0.000), current smoker (OR 1.62, Cl 1.15–2.29, p < 0.006), longer smoking period (OR 1.11, Cl 1.09–1.14, p < 0.000), last visit to the dentist over a year ago (OR 1.92, Cl 0.44–2.58, p < 0.000) and tooth brushing less than two times a day (OR 1.6, Cl 1.14–2.23, p < 0.006) were associated with losing more than 8 teeth. In the subgroup aged 20–44 years, only smoking duration was a risk factor for tooth loss (p = 0.02). For the middle-aged and oldest groups, education level (respectively p < 0.001, and p = 0.001), body mass index (respectively, p < 0.001, and p = 0.037), smoking status ever/former/current (respectively p < 0.001 and p = 0.002), smoking status never/ever (respectively p < 0.001 and p = 0.009), smoking duration (p < 0.001) were related to tooth loss. Additionally, in the elderly group, fasting blood glucose level (p = 0.044) and frequency of dental visits (p = 0.007) were related to tooth loss. We concluded that in the evaluated population, tooth loss was associated with socio-demographic, medical, and behavioural factors.

The aim of this study was to assess the relationship between the dietary total antioxidant capacity (DTAC) and occurrence of prediabetes, diabetes and insulin resistance in the Bialystok PLUS (Polish Longitudinal University Study) population. Daily food consumption was estimated by 3-days 24-h dietary recalls. DTAC was calculated using the date of food consumption and antioxidant potential of foods measured by FRAP (ferric ion reducing antioxidant potential) method. The following measurements were performed to identify prediabetes, diabetes and HOMA-IR: fasting glucose (FG), 2h postprandial glucose level (2h-PG), fasting insulin (FI), glycated hemoglobin HbA1c. Logistic regression models were used to assess the relationship between DTAC and prediabetes and diabetes. This study demonstrated that higher quartile of DTAC, after adjustment for confounding variables, was significantly associated with a reduced odds ratio for the prevalence of prediabetes in Bialystok PLUS population aged 35–65 years. DTAC was also significantly inversely associated with HOMA-IR in multivariate linear regression model. DTAC was positively related to individual dietary antioxidants (polyphenols, antioxidant vitamins and minerals). Reduced DTAC may be considered as an additional risk factor for the development of diabetes. Therefore, dietary recommendations for prevention and therapy of diabetes should take into account the high DTAC.

The aim of the study was to determine oral health–related quality of life (OHRQoL) using the measures Geriatric/General Oral Health Assessment (GOHAI) and Oral Health Impact Profile (OHIP-14) in relation to missing teeth in the Polish population aged 20–79. This was a cross-sectional study carried out among 1112 randomly selected participants. The mean age was 48.72 and mean number of teeth was 20.12. Altogether, in the GOHAI, the percentage that gave a positive response to each question ranged from 3.3% to 48.0%; in the OHIP-14, these answers ranged from 2.4% to 25.1%. The GOHAI measure was statistically significant, with more grouping variables than the OHIP-14 measure. Both measures showed significant associations with gender, age, dry mouth, education, professional status, number of teeth, and upper and lower total dentures. We detected a significant relationship between oral health–related quality of life and the factors influencing the presence or absence of dentition. Missing teeth were statistically associated with GOHAI, OHIP-14, advanced age, self-reported dry mouth, lower education, higher Body Mass Index (BMI), lower professional status, diabetes, myocardial infraction, and total dentures in upper or/and lower jaws. However, edentulous individuals had two times higher risk of having an OHIP-14 score above the median. This suggests that oral health practitioners should work to prevent oral diseases that lead to tooth loss in their patients, starting from an early age.

Body composition, especially an increased amount of fat mass and decreased lean body mass, is connected with metabolic complications. Thyroid hormones can influence body composition pattern. To date, scarce data defining the relationships between thyroid hormones and parameters of body composition using dual-energy X-ray absorptiometry (DXA), especially in cohort studies, are available. Therefore, the aim of the present study was to investigate the relationships among serum concentrations of (thyroid-stimulating hormone (TSH), thyroid hormones, and distribution of fat tissue assessed using the DXA method in a euthyroid cohort from the Białystok PLUS study. We examined 582 euthyroid subjects who were divided into lean (body mass index (BMI) < 25 kg/m²) and overweight/obese (BMI ≥ 25 kg/m²) (84 lean men, 182 overweight/obese men, 160 lean women, and 156 overweight/obese women). Serum concentrations of TSH, free T3 (fT3), and free T4 (fT4) were assessed, and DXA was performed. We observed lower serum levels of fT4 (p = 0.03) and higher serum levels of fT3 (p = 0.04) in overweight/obese vs. lean men, whereas serum levels of TSH did not differ between these groups (p = 0.38). In lean men, we only observed a relationship between serum levels of TSH and visceral adipose tissue (VAT) (r = −0.24, p = 0.02). In overweight/obese men, we found that serum levels of fT3 were positively connected with total fat mass (r = 0.16, p = 0.02), android fat mass (r = 0.15, p = 0.03), and gynoid fat mass (r = 0.17, p = 0.01), but not with VAT (r = 0.03, p = 0.63). We did not observe differences in serum levels of TSH, fT3, and fT4 between lean and overweight/obese women. Additionally, we did not notice relationships between serum levels of thyroid hormones and fat in different regions estimated by DXA in lean and overweight/obese women (all p > 0.05). We concluded that the serum concentration of TSH is connected with VAT in lean men, whereas, in overweight/obese men, higher fT3 is connected with an increased fat amount. These associations are absent in women.

Background: Natriuretic peptides (NPs), including brain natriuretic peptide (BNP), are neurohormones involved in the regulation of water-sodium balance and the maintenance of cardiovascular homeostasis. A higher concentration of NPs is observed in females, but the mechanism behind this difference has not been fully elucidated. Methods: Randomly chosen 255 volunteers from the general population were examined. Overall, 196 people without severe cardiovascular disease were included (mean age 48 years, 35.7% male). A comprehensive assessment was performed, including anthropometric measurements, N-terminal pro-brain natriuretic peptide (NT-proBNP), total testosterone (TT) and sex hormone-binding globulin (SHBG) concentration, transthoracic echocardiography (ECHO), and body composition analysis by direct dual-energy X-ray absorptiometry (DEXA). The univariate analysis adjusted by the known affecting factors determined which measurements were independently associated with NT-proBNP concentration. Results: NT-proBNP concentration was positively associated with gynoid fat mass, gynoid/total fat (G/TF) mass index, SHBG and negatively with android/gynoid (A/G) fat mass index, TT and calculated free testosterone (CFT) concentrations. Furthermore, body composition parameters remained independently associated with NT-proBNP levels even after adjusting for CFT and SHBG. Conclusion: In the population without severe cardiovascular disease, the NT-proBNP concentration is independently associated with lower availability of testosterone and higher gynoid fat distribution, which may explain higher NPs levels in females.