Background/Objectives: Metabolic syndrome (MetS) is a combination of conditions including central obesity, high blood pressure, high glucose levels, and abnormal triglycerides and cholesterol, which together increase the chances of heart disease, diabetes, and even death. The rates of MetS are different around the world, with 20–30% in Europe and 21.8–23.9% in Kazakhstan. Because MetS changes over time, it is important to study the dynamics of their components to improve prevention and treatments. This work aims to obtain the incidence of MetS and to evaluate the specific components associated with the emergence of new MetS cases in this population. Methods: This is a longitudinal study with a 10-year follow-up in Turkestan city between 2012 and 2024. Information was collected through physical exams, blood tests, and anthropometric measurements. Logistic regression and ROC curve analysis were used to find which factors increase the incidence of MetS. Results: Among 434 participants analyzed (78.8% women, and mean age 40.87, 66% < 2 MetS components, 20% had MetS blood pressure, and 65.9% had MetS waist circumference), the incidence of MetS at follow-up was 40%. The key risk factors for newly diagnosed MetS included elevated blood pressure and increased waist circumference. Multivariate analyses highlighted these components as the strongest predictors of MetS, with significant associations observed for participants with two or more MetS components at baseline. Conclusions: Elevated blood pressure and central obesity were identified as pivotal contributors to MetS progression. Given the rising prevalence of Mets and its implications, these results show the need to start treatment and check these risks early to prevent serious health problems.

Introduction. Nowadays, metabolic syndrome continues to be a significant challenge in medicine. Experts from the World Health Organization have called metabolic syndrome (MetS) “the pandemic of the 21st century.” MetS is one of the cardiometabolic risk factors with a high prevalence in the adult population and a high cost to public health systems worldwide. The prevalence of MetS is very high: according to WHO, the incidence of MetS among adults is 20-40% and may increase by 50% in the next 20 years. The most threatening complications closely related to metabolic syndrome are cardiovascular diseases and type 2 diabetes mellitus. Due to the high prevalence of metabolic syndrome, its early detection is of great importance for the timely initiation of the prevention of complications. Aim. To study the association between the main lifestyle and socio-demographic factors and the risk of developing metabolic syndrome. Material’s and method. The present study is part of a large metabolic syndrome research project in Turkestan city (AP19676909) “Investigation of genetic aspects of nutrition, lifestyle and compliance of patients with metabolic syndrome in a 10-year prospective study”. The sample consisted of 552 patients from the attached population of the outpatient clinic of the H.A. Yasavi International Kazakh-Turkish University. Individuals with acute conditions requiring emergency care, chronic severe decompensated conditions were not included in the study. Results: The final patient sample was 549 patients, as study participants without data on any of the sociodemographic factors and any of the lipid and carbohydrate metabolism parameters were excluded from the analysis. The association between the presence of MetS and lifestyle indicators, including time spent sitting during the working day and physical activity, was assessed using multivariate logistic regression analysis. After adjusting for the potential confounding factors, such as gender, smoking, and alcohol consumption, the association between MetS and the sitting time during the working day was maintained statistical significance. In contrast, the adjusted logistic regression analysis revealed a statistically significant inverse relationship between the metabolic syndrome and level of physical activity. Сonclusion: The results of our study suggest a significant role for modifiable risk factors, such as a sedentary lifestyle and the level of physical activity, in the development of metabolic syndrome among our study participants. Personalized management tactics for patients with metabolic syndrome, by correcting modifiable lifestyle factors, can help prevent complications. Актуальность. На сегодняшний день метаболический синдром остается актуальной проблемой медицины. Эксперты Всемирной организации здравоохранения назвали метаболический синдром (МС) «пандемией XXI века». Метаболический синдром (МС) является одним из кардиометаболических факторов риска, имеющим высокую распространенность среди взрослого населения и высокую стоимость для систем общественного здравоохранения во всем мире. По данным ВОЗ частота МС среди взрослого населения составляет 20-40% и может увеличиться на 50% в ближайшие 20 лет. Наиболее грозными осложнениями, тесно связанными с метаболическим синдромом, являются сердечно-сосудистые заболевания и сахарный диабет 2 типа. В связи с высокой распространенностью метаболического синдрома его раннее выявление имеет большое значение для своевременной профилактики осложнений. Цель: Изучить связь между основными факторами образа жизни и социально-демографическими факторами с риском развития метаболического синдрома. Материалы и методы: Настоящее исследование является частью научного проекта по изучению метаболического синдрома в городе Туркестан «Изучение генетических аспектов питания, образа жизни и комплаентности пациентов с метаболическим синдромом в 10-летнем проспективном исследовании» (AP19676909). Выборку составили 552 пациента из прикрепленного населения поликлиники Международного казахско-турецкого университета имени Х.А. Ясави. В исследование не включались пациенты с острыми состояниями, требующими неотложной помощи, хроническими тяжелыми декомпенсированными состояниями. Результаты: Окончательная выборка пациентов составила 549 человек, так как участники, у которых отсутствовали данные по одному из социально-демографических факторов, либо по одному из параметров липидного и углеводного обмена были исключены...

Background: Metabolic syndrome (MetS), a cluster of cardiometabolic abnormalities including elevated blood pressure, impaired glucose regulation, dyslipidemia, and increased waist circumference is increasingly recognized as a condition linked to both physical and psychological health risks. This study aims to investigate genotype-specific differences in psychological distress between healthy individuals and those with metabolic disorders, as well as to examine potential gene metabolic status interactions. Methods: This study is a cross-sectional analysis conducted in Turkistan city in the Southern region of Kazakhstan. Participants (healthy and those with metabolic syndrome) were invited to take part in the study by random sampling from the Khoja Akhmet Yassawi Kazakh-Turkish International University Medical Center. Consenting individuals provided a genetic analysis. Psychosomatic indicators were assessed using the Perceived Stress Questionnaire (PSQ) and the Depression, Anxiety, and Stress Scale (DASS-21). Results: A total of 200 individuals participated, with an approximately 3:1 ratio of women to men. The mean age in years was 50.4 ± 9.5 and 48.8 ± 7.7 for men and women, respectively. Preliminary analyses showed variations in cognitive and psychosomatic measures among individuals with metabolic syndrome, but no associations with genetic variants, and no significant group differences across key psychosomatic indicators when stratified by metabolic or genetic factors. However, a significant difference in LPL-Anxiety between genotypes GA-GG (p < 0.05) was found. Conclusions: Variations in metabolic and genetic factors within the studied population were not associated with measurable differences in stress or depressive symptoms.

Background: Metabolic syndrome (MetS) is influenced by behavioral and genetic factors, yet evidence on eating behavior patterns and related genetic polymorphisms in Central Asian populations remains limited. Aim: The aim of this study was to assess eating behaviors among adults with and without MetS and evaluate their associations with clinical indicators and ADIPOQ rs266729 and MC4R rs17782313 variants. Methods: A cross-sectional study of 200 adults (115 non-MetS, 85 MetS) was conducted using Dutch Eating Behavior Questionnaire (DEBQ), standardized clinical measurements, and PCR-RFLP genotyping. Results: Participants with MetS were older than non-MetS adults (52 vs. 47 years; p = 0.004) and had substantially higher systolic blood pressure (126 vs. 114 mmHg; p < 0.001), diastolic blood pressure (83 vs. 74 mmHg; p < 0.001), and BMI (32.2 vs. 25.9 kg/m²; p < 0.001). Waist circumference, hip circumference, triglycerides, total cholesterol, and LDL were also significantly higher, while HDL was lower (1.13 ± 0.40 vs. 1.58 ± 1.50 mmol/L; p = 0.008). DEBQ restrained, emotional, and external eating scores showed no differences between groups (all p > 0.05). Eating behavior distribution was similar (p = 0.291). ADIPOQ genotypes (CC/CG/GG) did not differ by MetS status (p = 0.227), nor did MC4R variants (p = 0.679). Among MetS participants, clinical indicators did not vary across eating behavior categories, and no associations were observed between eating behavior and either polymorphism. Conclusions: Despite clear clinical and metabolic differences between MetS and non-MetS groups, neither eating behavior patterns nor ADIPOQ and MC4R variants were associated with metabolic measures among MetS group.

Background/Objectives: Metabolic syndrome (MetS) is a major global public health concern associated with an increased risk of cardiovascular disease and type 2 diabetes mellitus. Iron metabolism has been implicated, but the storage (ferritin) and functional (soluble transferrin receptor, sTfR) axes are rarely assessed within a single model. We aimed to determine whether both axes are independently associated with glycaemia and MetS and to evaluate their diagnostic value. Materials and Methods: A cross-sectional study was conducted in 297 adults (72.8% women) from Turkestan, Kazakhstan. Hierarchical regression models with sequential adjustment were applied for age, sex, body mass index (BMI), high-sensitivity C-reactive protein (hs-CRP), dietary inflammatory index (DII), HFE H63D genotype, and gamma-glutamyl transferase (GGT). Path analysis and receiver operating characteristic (ROC) analysis were also performed. Results: Ferritin and sTfR were independently associated with fasting glucose (β = 0.27 and 0.73, respectively) and metabolic syndrome (OR = 1.52 and 4.53, respectively). When analyzed separately, neither biomarker reached statistical significance for MetS (ferritin: OR = 1.20, p = 0.140; sTfR: OR = 1.93, p = 0.072). Ferritin demonstrated no discriminatory ability in men (AUC = 0.500, 95% CI 0.370–0.630) and modest discrimination in women (AUC = 0.652, 95% CI 0.571–0.732). GGT accounted for approximately 28% of the ferritin–glucose association in a path-analytic model. Ferritin, GGT, and HbA1c levels increased progressively even among individuals with 0–2 MetS components. Conclusions: Both the storage and functional axes of iron metabolism provide independent information on glycaemic status, but their associations become apparent only when assessed simultaneously. Ferritin alone is not suitable as a diagnostic marker for metabolic syndrome.