Lack of adherence to recommended therapy will reduce its effectiveness and can subsequently lead to disease progression, disabilities or even death. A vast number of research studies have emphasized the magnitude of medication nonadherence and its effect on treatment outcomes, patient’s health, healthcare providers and the associated costs; medication nonadherence remains a major concern that is believed to be widely practiced amongst medication taking patients. The current systemic review aims to cohere the available evidence regarding medication nonadherence rate, practices, and potential affecting factors and predictors. A search through different databases was conducted, including PubMed, Medline, and CINHAL for recently published research articles, within five years. The terms used for the search include medication nonadherence, medication nonadherence, factors affecting medication nonadherence and predictors of medication nonadherence. The search was limited to human subjects, English language journal articles and exclusion of review articles, case studies, and data from clinical trials as patient adherence is closely observed. The search resulted in 667 articles and only 65 articles were included and further screened. However, according to our exclusion criteria, 15 articles only were included in this review. The three most reported practices of medication nonadherence are prescription abandonment, nonconforming, and non-persistence. There are five reported factors that may lead to nonadherence practices such as socioeconomic-related factors, healthcare system-related factors, patient-related factors, disease-related factors, and therapy-related factors. In conclusion, medication nonadherence practice is a multi-dimensional phenomenon that requires a multi-targeted solution.

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.

Cardiovascular risk factors aggregate in determined individuals. Patients with Type 2 diabetes mellitus (T2DM) have higher cardiovascular This study aimed to investigate insulinresistance (IR) and β-cell function using the homeostasis model assessment (HOMA) indexes in a general Kazakh population and determine the effect he effect that cardiovascular factors may have on those indexes. We conducted a cross-sectional study among employees of the Khoja Akhmet Yassawi International Kazakh-Turkish University (Turkistan, Kazakhstan) aged between 27 and 69 years. Sociodemographic variables, anthropometric measurements (body mass, height, waist circumference, hip circumference), and blood pressure were obtained. Fasting blood samples were collected to measure insulin, glucose, total cholesterol (TC), triglycerides (TG), and high- (HDL) andlow-density lipoprotein (LDL) levels. Oral glucose tolerance tests were performed. Hierarchical and K-means cluster analyses were obtained. The final sample was composed of 427 participants. Spearmen correlation analysis showed that cardiovascular parameters were statistically associated with HOMA-β (p < 0.001) and not with HOMA IR. Participants were aggregated into the three clusters where the cluster with a higher age and cardiovascular risk revealed deficient β-cell functioning, but not IR (p < 0.000 and p = 0.982). Common and easy to obtain biochemical and anthropometric measurements capturing relevant cardiovascular risk factors have been demonstrated to be associated with significant deficiency in insulin secretion. Although further longitudinal studies of the incidence of T2DM are needed, this study highlights that cardiovascular profiling has a significant role not just for risk stratification of patients for cardiovascular prevention but also for targeted vigilant glucose monitoring.

Background/Objectives: Prediabetes (PreDM) is a heterogeneous condition, impacting hundreds of millions worldwide, associated with a substantially high risk of Type 2 Diabetes Mellitus (T2DM) and cardiovascular complications. Early identification of subgroups within the PreDM population may support tailored prevention strategies. Methods: We conducted a cross-sectional study using data from annual health check-ups of 419 university staff (aged 27–69) in Kazakhstan. Latent Class Analysis (LCA) was applied to identify subgroups of individuals with PreDM based on cardiovascular risk factors. Differences in glucose metabolism markers (fasting glucose, OGTT, HOMA-IR, HOMA-β) were compared across identified classes. Results: PreDM prevalence was 43.4%. LCA revealed four distinct classes: Class 1: healthy, low-risk individuals; Class 2: overweight with moderate metabolic risk; Class 3: older, overweight individuals with high cardio-metabolic risk; and Class 4: obese, middle-aged to older individuals with very high cardio-metabolic risk. Significant differences were found in glucose metabolism profiles across the classes. IFG predominated in Class 1 (95%), while Classes 3 and 4 had higher rates of β-cell dysfunction and combined IFG/IGT patterns. HOMA-β differed significantly between classes (p < 0.001), while HOMA-IR did not. Conclusions: PreDM is highly prevalent in this working-age Kazakh population and demonstrates marked heterogeneity. Based on easily obtainable cardiovascular risk factors, we have identified four subgroups with distinct glucose profiles that may inform personalized interventions. These distinct subgroups may require differentiated prevention strategies, moving beyond a one-size-fits-all approach.

Introduction: The objective of this study was to analyze the psychometric properties of the Kazakh translation of the Short Form-36 (SF-36) v2 Health Survey and evaluate its suitability for assessing health-related quality of life (QoL) in the Kazakh population. Methods: The SF-36 Health Survey version 2 (SF-36 v2) was administered to a sample of 632 Kazakh adults (442 women and 190 men) ranging in age from 27 to 69 years. Internal consistency reliability was evaluated using Cronbach’s alpha. Scaling assumptions were examined through item-scale correlations. Scale scores were computed, and norm-based scoring was applied. The 2-week test–retest reliability was assessed in a subsample (n = 100) using intraclass correlations (ICCs). Results: Cronbach’s alpha for the eight SF-36 v2 scales ranged from 0.760 to 0.947, indicating good to excellent internal consistency. All scales met scaling assumptions. Scaling success rates, where item-scale correlations exceeded 0.40, were 100% across scales. The physical component summary and mental component summary scores demonstrated high reliability (ICC = 0.94 and 0.91). The mean scale scores ranged from 66.6 (vitality) to 82.2 (physical functioning), with negative skewness observed for most scales. Conclusion: The Kazakh version of the SF-36 v2 demonstrated strong psychometric performance, with results supporting score reliability and construct validity in the Kazakh general population sample. This study provides evidence for the usability of the adapted SF-36 v2 in assessing health-related QoL among Kazakhs.

Background/Objectives: This study examined the metabolic, oxidative, immunological, and histomorphological effects of the multicomponent fermented biological product derived from camel milk, Inullact-Fito, in comparison to metformin in a rat model of alloxan-induced diabetes resulting from insulin insufficiency. The model was chosen as an experimental system that replicates pancreatic β-cell damage induced by oxidative stress rather than insulin resistance. Methods: Alloxan-induced diabetes was used to evaluate metabolic, oxidative, immunological, and histomorphological alterations. Metformin was utilized as a pharmacological comparator. Blood glucose levels, circulating insulin concentrations, markers of oxidative stress and lipid peroxidation, immunoglobulin levels, CD4⁺/CD8⁺ T cell balance, and pancreatic histostructure were assessed. Results: Alloxan administration led to substantial hyperglycemia, oxidative stress, immunological imbalance, and structural damage to pancreatic tissue. Following therapy with Inullact-Fito, blood glucose levels reduced dramatically (from 21.9 ± 0.22 to 9.85 ± 0.10 mmol/L, p < 0.05), circulating insulin concentrations were largely corrected, oxidative stress and lipid peroxidation markers decreased. Immunological evaluation revealed decreased serum immunoglobulin M and IgG levels (p < 0.05) and partial normalization of the CD4⁺/CD8⁺ T cell balance. Metformin showed comparative effects; however, its activity in this model is limited by its primary mechanism related to insulin resistance. Conclusions: Overall, the data reveal that Inullact-Fito combines metabolic, antioxidant, and immunomodulatory actions under experimental oxidative and metabolic stress conditions. Further research using models of insulin resistance and type 2 diabetes, as well as long-term clinical trials, is needed to fully evaluate the therapeutic potential, safety profile, and translational importance of this fermented dairy product as a functional nutritional intervention.