Metabolic syndrome (MetS) is closely associated with adverse cardiometabolic outcomes. The objective of this study was to identify practical methods that could enable the effective identification of MetS based on anthropometric indices. The basis of our study involved retrospective database obtained from routine medical prophylactic examinations. This was a cross-sectional study on the health status of male workers employed in hazardous working conditions at industrial enterprises in the Ural region conducted in 2019. A total of 347 male workers employed under hazardous working conditions were investigated. The presence of MetS was established by a healthcare professional in accordance with the guidelines of the International Diabetes Federation (IDF). Simple linear regression was used to evaluate the associations between anthropometric indices and MetS incidence. Logistic regression was used to determine the odds ratios of MetS in relation to increases in anthropometric indices. ROC curves were calculated to compare the ability of each anthropometric index to predict MetS and to determine the diagnostic thresholds of the indicators considered. According to the IDF criteria, 36.3% of the workers had MetS. A direct relationship was found between the individual components of MetS and the anthropometric indices studied. The highest OR was shown by the Body Roundness Index (BRI) of 2.235 (95% CI 1.796–2.781). For different age quartiles, the optimal cut-off values for predicting MetS were as follows: BRI, 4.1–4.4 r.u.; body shape index (ABSI), 0.080–0.083 m^11/6 kg^−2/3; and lipid accumulation product (LAP), 49.7–70.5 cm mmol/l. The most significant associations with MetS were observed where the values were greater than these cut-off points (Se = 97.4%). The results of this study demonstrated the rapid use of new anthropometric indicators, which have shown good predictive ability and are quite easy to use.

The aim of this study was to determine the effect of smoking on BMI in male adolescents and explore the relationship between smoking status and diet. Methods: A cross-sectional epidemiological study into the health and diet of adolescents was carried out based on a representative sample of 375 vocational school male students aged 16–17 in the city of Chelyabinsk (Russian Federation). The students and their parents filled out verified questionnaires on their socioeconomic status, diet, and smoking status. Students’ height and body weight were measured. A comparative analysis of diets was performed between groups of smokers and non-smokers (149 and 226 individuals, respectively), and the relationship between smoking, body mass index, and actual diet was estimated. The methods used included descriptive statistics, Student’s t-test, Mann–Whitney U test, comparison of proportions, and moving average. Results: Non-smoking adolescent boys tended to have excess body mass compared with smokers (19.0% and 12.1%, respectively). Smokers (adolescent boys) consumed less meat, cereals, beans, and cheeses and more sweet beverages, added sugar, coffee, and alcohol. The bulk of the smokers’ diet was composed of carbohydrates (p = 0.026) and, to a lesser extent, proteins (p = 0.006). Conclusions: Significant differences were discovered in the diet between smokers and non-smokers (among adolescent boys), and smoking was associated with several indicators of unhealthy diet patterns. This is an important conclusion for developing a future program that could additionally protect at-risk groups of adolescents.

Introduction: It is important to assess health impact of the entire set of heterogeneous risk factors and identify the key ones in order to develop personalized measures for prevention of non-occupational diseases in workers. Objective: To establish the major risk factors for circulatory and musculoskeletal disorders in employees of a metallurgical enterprise. Materials and methods: We used anonymized data from a special assessment of working conditions and production control of the forging departments of the forging-rod and forging-press shops of a metallurgical enterprise producing titanium alloys for the years 2016–2020. To determine the presence of personal biological and behavioral risk factors for diseases of the circulatory and musculoskeletal systems, we examined anonymized data of the periodic medical check-up conducted in 2020 of 146 male blacksmiths working with hammers and presses. The mean age of the workers was 35.9 ± 8.8 years (range: 21 to 57 years) and their mean length of current employment was 18.9 ± 9.7 years (range: 2 to 41 years). The method of simple and multiple logistic regression was used to build models for predicting the likelihood of a disease; odds ratios were calculated with a 95 % confidence interval. The quality of the models was assessed using the maximum likelihood estimation. Results: We determined the factors allowing prediction of the disease likelihood. The prevalence of circulatory diseases correlated with age, length of employment, and the body mass index, whole-body and hand-arm vibration, noise exposure, high ambient temperature, thermal radiation, and heavy physical work. The prevalence of musculoskeletal diseases, in its turn, had a somewhat weaker statistically significant association with the same risk factors. Models predicting the likelihood of circulatory and musculoskeletal diseases have been built. The best predictive model for circulatory diseases included the combined effect of the body mass index and heavy physical work while that for musculoskeletal disorders – of the body mass index and hand-arm vibration. Conclusion: Multiple logistic regression used to analyze statistical relationships between work-related risk factors and disease prevalence in employees in specific occupations allowed identification of the leading factors contributing the most to the disease development and can be recommended for solving practical problems in occupational medicine.

Aim. To evaluate the endometrial microbiota in patients with uterine scar defect after cesarean section. Materials and methods. The study included 80 women of reproductive age. The main group included 50 patients with a uterus scar defect due to cesarean section; the comparison group included 30 women with a competent uterus scar due to cesarean section. Patients underwent a Pipelle endometrial biopsy on days 2022 of the menstrual cycle using a double-lumen catheter that excludes sample contamination with vaginal and cervical microflora. A molecular genetic study of the endometrium was performed by real-time polymerase chain reaction using the Femoflor 16 reagent kit (DNA-Technology Moscow). The DNA content in the specimen was measured using software and expressed in genome equivalent (GE) proportional to the number of microorganisms. The statistical data were processed using the Exсel software package and SPSS Statistics 22.0. Results. The study showed the following statistically significant differences: lower count of Lactobacillus spp. 2.600 (1.4303.600) GE/mL vs 3.550 (2.8004.700) GE/mL in patients of the comparison group (p=0.02); higher count of Streptococcus and Staphylococcus spp. 3.270 (3.0003.700) GE/mL and 3.450 (3.2003.600) GE/mL vs 1.030 (0.7601.700) GE/mL and 0.560 (0.1201.200) GE/mL in the comparison group, respectively (p0.00001); higher count of Enterobacteriaceae 2.700 (1.7003.300) GE/mL vs 0.950 (0.6601.120) GE/mL in the comparison group (p0.00001); higher count of Gardnerella/Prevotellabivia/Porphyromonas spp. 2.310 (0.9303.480) GE/mL vs 1.000 (0.0001.860) GE/mL (p=0.003); higher count of Peptostreptococcus spp. 0.195 (0.0001.560) GE/mL vs 0.000 (0.000-0.000) GE/mL (p=0.032); Eubacterium spp. 1.355 (0.1002.460) GE/mL vs 0.000 (0.0001.560) GE/mL (p=0.040). Conclusion. Endometrial dysbiosis in patients with a uterus scar defect after cesarean section due to the possible effects of microorganisms can be considered one of the leading causes of the formation of a uterus scar defect in the postoperative period.

Introduction. According to the results of medical examinations of metallurgists, in the structure of newly identified somatic morbidity, circulatory system diseases (CSD) are one of the leading pathologies. To assess the prevalence of CSD in workers in harmful working conditions, it is possible to use various mathematical solutions as a tool. The objective of the study was to substantiate the possibility of using variance analysis and classification tree (CT) methods to assess the prevalence of circulatory diseases in industrial workers. Materials and methods. Data of medical examinations and a questionnaire-based survey of three hundred eight workers of steel production were input into a database. The interrelationship between CSD and individual and occupational risk factors was examined using a one- and two-way ANOVA. The classification tree method was used for a multivariate analysis. Results. The one- and two-way ANOVA revealed a statistically significant correlation between the CSD family history (p=0.001) and age, years of occupational exposure, overweight, blood glucose level, total cholesterol (p<0.05) and the CSD prevalence in the steel workers. We applied the classification tree method to make decisions on referring the subjects to potentially “healthy” and “sick” workers by determining the CSD prevalence in relation to various combinations of risk factors. Limitations. This study is limited to the results of medical examinations of the workers collected over a one-year period. Conclusions. Our experience in using the analysis of variance and classification tree to evaluate the CSD prevalence in ferrous industry employees allows recommending them for use in assessing the prevalence of various diseases in workers exposed to occupational hazards.

Background: Logistic regression is the most commonly used method for establishing statistical relationships between quantitative predictors X and a dichotomous response Y (Y=0 or Y=1). Therefore, it is relevant to develop new approaches to the analysis of relationships between X and Y of this type. Aim: To demonstrate the specific characteristics of the application of stratification, moving average and cumulative probability function methods in the construction and analysis of logistic regression models in the context of health risk assessment. Materials and methods: The analysis of logistic regression models employs a range of statistical methods, including the stratification, moving average, cumulative probability function, goodness-of-fit tests, and proportion comparison tests. Results: It is shown that the standard stratification methods are not sufficient for exploring the nature of the relationships between dichotomous Y and quantitative X. Additional methods, including moving average and cumulative likelihood function, facilitate the identification of features characterizing these relationships. The utility of graphical representations of logistic regression results in elucidating the statistical relationships between variables X and Y is demonstrated. The efficacy of the stratification, moving average and cumulative probability function methods is illustrated by examples from the field of epidemiology. Conclusion: The combination of moving average and cumulative probability function methods with stratification enables the reliable identification of the nature of the relationship between dichotomous Y and quantitative X, as well as the potential for deviations from the conditions of applicability of logistic regression models.