Aim. To study the epidemiological characteristics and changes of hypertension (HTN), as well as factors associated with HTN in the Russian population aged 35-74 years.Material and methods. The Epidemiology of Cardiovascular Diseases and their Risk Factors in Regions of Russian Federation-3 (ESSE-RF3) study examined a representative sample of the population aged 35-74 years of 15 Russian regions with a response >70% (n=28611). Modular design questionnaire was used. Blood pressure (BP) was measured twice after a 5-minute rest in a sitting position on the right arm with an Omron blood pressure monitor. There were following criteria for hypertension: systolic blood pressure (SBP) ≥140 mm Hg and/or diastolic blood pressure (DBP) ≥90 mm Hg, and/or antihypertensive therapy. The effectiveness of treatment was considered the proportion (%) of people who achieved target blood pressure values among those being treated, while the control was considered the proportion (%) of patients with a BP <140/90 mm Hg of the total number of hypertensive patients. HTN changes were studied in a single age range of 35-64 years with the inclusion of materials from the ESSE-RF (2012-14) and ESSE-RF2 (2017) studies, carried out using the same methodology as ESSE-RF3. Statistical analysis was carried out using the open-source R 3.6.1 environment. Analysis of the association between factors and a binary variable was performed using logistic regression. The significance level for all tested hypotheses was 0,05.Results. According to ESSE-RF3, the average levels of SBP and DBP in the population were 131,9±18,7 and 84,4±10,9 mm Hg, respectively, while the proportion of those with BP ≥140/90 mm Hg — 38,8% (men: 44,8%, women: 33,9%). Prevalence of hypertension was 53,9% (men: 56,0%, women: 52,1%), awareness — 77,7% (men: 71,5%, women: 82,3%), while the treatment received 63,4%, significantly higher among women than among men: 72,3 vs 53,3%. The effectiveness of treatment was 44,0%, higher among women compared to men (48,2 vs 37,4%). In addition, 27,9% of patients have controlled HTN.Conclusion. The problem of controlled HTN in Russia remains unresolved in the 21st century. The following significant sex differences remain: the prevalence of HTN is higher among men, but awareness of the disease, treatment rate and its effectiveness are lower compared to women.

Traumatic brain injury (TBI) heavily impacts the body: it damages the brain tissue and the peripheral nervous system and shifts homeostasis in many types of tissue. An acute brain injury compromises the “brain–gut-microbiome axis”, a well-balanced network formed by the brain, gastrointestinal tract, and gut microbiome, which has a complex effect: damage to the brain alters the composition of the microbiome; the altered microbiome affects TBI severity, neuroplasticity, and metabolic pathways through various bacterial metabolites. We modeled TBI in rats. Using a bioinformatics approach, we sought to identify correlations between the gut microbiome composition, TBI severity, the rate of neurological function recovery, and blood metabolome. We found that the TBI caused changes in the abundance of 26 bacterial genera. The most dramatic change was observed in the abundance of Agathobacter species. The TBI also altered concentrations of several metabolites, specifically citrulline and tryptophan. We found no significant correlations between TBI severity and the pre-existing gut microbiota composition or blood metabolites. However, we discovered some differences between the two groups of subjects that showed high and low rates of neurological function recovery, respectively. The present study highlights the role of the brain–gut-microbiome axis in TBI.

Aim. To study the prevalence of dyslipidemias and their association with various risk factors in the Russian population of men and women aged 35-74 years in 2020-2022.Material and methods. This work was carried out as part of the Epidemiology of Cardiovascular Diseases and their Risk Factors in Regions of Russian Federation-3 (ESSE-RF3) study. The sample included 28731 men and women aged 35-74 years living in 15 Russian regions. Hypercholesterolemia (HC) was diagnosed with total cholesterol (TC) ≥5,0 mmol/l, while elevated low-density lipoprotein cholesterol (LDL-C) was considered ≥3,0 mmol/l, hypertriglyceridemia — with triglyceride levels ≥1,7 mmol/l, reduced high-density lipoprotein cholesterol (HDL-C) <1,0 mmol/l in men and <1,2 mmol/l in women. Associations were assessed using logistic regression after adjustment for socio-demographic characteristics, drinking status, presence of hypertension (HTN) and stroke.Results. The prevalence of hypertriglyceridemia in the Russian Federation in 2020-2022 was 58,8%, hypertriglyceridemia — 32,2%. The incidence of lipid-lowering therapy increased with age from 1% in the group of 35-44 years to 16% in the group of 65-74 years. On average, only 7,6% of study participants received lipid-lowering therapy. Significant associations of HC with HTN, obesity and alcohol abuse were identified. Similar results were obtained for elevated LDL-C levels, with the exception of alcohol abuse. In turn, a reduced HDL-C level was significantly associated with the lack of higher education, marriage, physical activity, smoking and the presence of diseases.Conclusion. The prevalence of lipid disorders in the Russian Federation in 2020-2022 remained at a high level. These disorders occurred more often in women, and they were better informed about their cholesterol levels and more often received lipid-lowering therapy. HTN, obesity, and some behavioral and social risk factors were associated with dyslipidemia.

Aim. To study the problem of obesity at the national level.Material and methods. The ESSE-RF3 study examined a representative sample of the population of 15 Russian regions aged 35-74 years with a response >70% (n=28731). Modular design questionnaire was used. The study received approval from the Independent Ethics Committee of the National Medical Research Center for Therapy and Preventive Medicine. Signed informed consent was obtained from each participant. Body mass (BM) was measured once with an accuracy of 100 g. The height was measured with an accuracy of 0,5 cm once in a standing position without shoes. Waist circumference was measured with a standard measuring tape with an accuracy of 0,5 cm. There were following BM categories: insufficient (BM index (BMI) 40). Abdominal obesity (AO) was assessed using the following criteria: waist circumference ≥102 cm and ≥88 cm for men and women, respectively. The changes of obesity were studied with the inclusion of materials from the ESSE-RF (2012-14) and ESSE-RF2 (2017) studies, carried out using the same methodology with ESSE-RF3 in the same age range of 35-64 years. Statistical analysis was carried out using the open-source R 3.6.1 environment. Analysis of associations between factors and a binary variable was carried out using the logistic regression method. The significance level for all tested hypotheses was 0,05.Results. Mean BMI values is 28,2±4,6 kg/m² among men and 28,9±5,9 kg/m² among women. The prevalence of overweight is 44,0 and 33,7%, obesity — 30,0 and 39,5%, AO — 30,9 and 55,1% among men and women, respectively. In addition, 30,3% have a combination of obesity and AO; obesity and/or AO — 49,1%. Obesity statistics did not significantly change, but in each section the rates are higher among women. The closest associations were found between obesity and hypertension (men: odds ratio (OR) (95% confidence interval) 2,88 (2,66-3,12), women: OR 3,03 (2,81-3,27) (p<0,001) and hyperuricemia for women (OR 4,21 (3,74-4,75) (p<0,001).Conclusion. A third of the Russian population is obese, and half has obesity and/or AO. This severity of the problem requires the development and adoption of a strategy to monitor obesity at the national level.

There is no single universal biomarker yet to estimate overall health status and longevity prospects. Moreover, a consensual approach to the very concept of aging and the means of its assessment are yet to be developed. Markers of aging could facilitate effective health control, more accurate life expectancy estimates, and improved health and quality of life. Clinicians routinely use several indicators that could be biomarkers of aging. Duly validated in a large cohort, models based on a combination of these markers could provide a highly accurate assessment of biological age and the pace of aging. Biological aging is a complex characteristic of chronological age (usually), health-to-age concordance, and medically estimated life expectancy. This study is a review of the most promising techniques that could soon be used in routine clinical practice. Two main selection criteria were applied: a sufficient sample size and reliability based on validation. The selected biological age calculators were grouped according to the type of biomarker used: (1) standard clinical and laboratory markers; (2) molecular markers; and (3) epigenetic markers. The most accurate were the calculators, which factored in a variety of biomarkers. Despite their demonstrated effectiveness, most of them require further improvement and cannot yet be considered for use in standard clinical practice. To illustrate their clinical application, we reviewed their use during the COVID-19 pandemic.

Geriatric syndromes (GSs) and aging-associated diseases (AADs) are common side effects of aging. They are affecting the lives of millions of older adults and placing immense pressure on healthcare systems and economies worldwide. It is imperative to study the factors causing these conditions and develop a holistic framework for their management. The so-called long-lived individuals—people over the age of 90 who managed to retain much of their health and functionality—could be holding the key to understanding these factors and their health implications. We analyzed the health status and lifestyle of the long-lived individuals and identified risk factors for GSs. Family history greatly contributes to the health and prevention of cognitive decline in older adults. Lifestyle and certain socioeconomic factors such as education, the age of starting to work and retiring, job type and income level, physical activity, and hobby were also associated with certain GSs. Moreover, the levels of total protein, albumin, alpha-1 globulins, high-density lipoprotein, free triiodothyronine, and 25-hydroxyvitamin D were direct indicators of the current health status. The proposed mathematical model allows the prediction of successful aging based on family history, social and economic factors, and life-long physical activity (f1 score = 0.72, AUC = 0.68, precision = 0.83 and recall = 0.64).