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With aging, regular changes develop in metabolism, first of all, these are changes in lipid and carbohydrate metabolism. With accelerated aging, metabolic disorders are more expressed, which leads to the development of metabolic syndrome. The purpose of the work was to develop a method for calculating metabolic age using available clinical tests and to assess the rate of metabolic aging in people with metabolic syndrome. Materials and methods. The study involved 283 apparently healthy people aged 20 to 80 years and 82 people with metabolic syndrome. Anthropometric parameters and biochemical tests were measured for all people included in the study. The formula for calculating metabolic age was obtained by the method of stepwise multiple regression.Results. The calculation of the metabolic age in healthy people according to the formula we obtained showed that the average absolute error is 6.01 years. In 20.5% of people with metabolic syndrome, metabolic age exceeds chronological age by more than 10 years. At the same time, in the group of healthy people, the share of such people was only 4.2%. Conclusions. The method we have developed for assessing the rate of metabolic aging has a sufficiently high accuracy and can be used to assess the risk of developing metabolic syndrome and other agerelated pathology.

Background. The problem of obesity in adolescents has gained its medical and social relevance since the incidence of the disease is steadily increasing. The purpose of the study is to improve the effectiveness of early diagnosis and prevention of obesity in adolescents. Materials and methods. To study the risk factors for obesity, a comparative assessment of lifestyle among adolescents aged 15–17 years with obesity, overweight and physiological body weight was conducted. In adolescents of the same age with comorbid obesity (basic group), overweight and physiological body weight (two comparison groups), the types of food behavior were determined using the Dutch eating behavior questionnaire (DEBQ). Bioelectrical indicators of bio-impedancemetric analysis were studied on a Tanita apparatus (Japan). The probability of differences in mean values was determined using Student’s t-test. Results. It was found that the frequency of imbalance of the food pyramid, movement disorders, sleep and rest, nervous tension, burdened heredity increased significantly among obese adolescents. Obesity was found to dominate by external type of eating behavior (57.2 %); at the excess weight — restrictive type (60 %); at physiological body weight — emotional type (40 %). Bio-impedancemetry showed that the reliable bioelectrical parameters of obesity were total fat (35.5 ± 4.5 % and 29 ± 2 % vs. 17.5 ± 2.5 %); visceral fat (17 ± 2 % and 12 ± 3 % vs. 8.5 ± 1.5 %); and metabolic age (33 ± 8 and 21.5 ± 1.5 years versus 16 ± 1 years). Conclusions. Risk factors for obesity include the imbalance of the food pyramid, movement disorders, sleep and rest, nervous tension, bad habits, burdened here­dity. The predominance of external type of eating behavior in obesity, restrictive — in overweight and emotional type in adolescents with physiological body weight should be taken into account when prescribing personalized lifestyle adjustments. The most informative bioelectrical parameters of bio-impedancemetry were total fat, visceral fat, and metabolic age. Bio-impedancemetry as a non-invasive predictive method of diagnosing obesity can be re­commended for widespread implementation in pediatric practice., Актуальність. Проблема ожиріння у підлітків набула своєї медико-соціальної актуальності, оскільки частота захворювання неухильно зростає. Мета дослідження: підвищення ефективності ранньої діагностики та профілактики ожиріння у підлітків. Матеріали та методи. Проводили порівняльну оцінку способу життя серед підлітків віком 15–17 років з ожирінням, надлишковою і фізіологічною масою тіла та визначали у них типи харчової поведінки за голландським опитувальником харчової поведінки DEBQ. Біоелектичні показники біоімпедансометричного аналізу вивчали на апараті «Tanita» (Японія). Визначення вірогідності відмінностей середніх величин здійснювали за t-критерієм Стьюдента. Результати. Виявили, що частота розбалансованості харчової піраміди, порушення рухового режиму, режимів сну і відпочинку, нервові перенапруження, шкідливі звички помітно зростали серед підлітків з ожирінням. Встановили, що при ожирінні мало місце переважання екстернального типу харчової поведінки (57,2 %); при надлишковій масі — обмежувального (60 %); при фізіологічній масі тіла — емоціогенного типу (40 %). Біоімпедансометрія показала, що вірогідними біоелектричними параметрам ожиріння були загальний жир (35,5 ± 4,5 % і 29 ± 2 % проти 17,5 ± 2,5 %), вісцеральний жир (17 ± 2 % і 12 ± 3 % проти 8,5 ± 1,5 %) та метаболічний вік (33 ± 8 років і 21,5 ± 1,5 року проти 16 ± 1 рік). Висновки. До факторів ризику розвитку ожиріння відносяться розбалансованість харчової піраміди, порушення рухового режиму, режимів сну і відпочинку, нервові перенапруження, шкідливі звички, обтяжена спадковість. Переважання екстернального типу харчової поведінки при ожирінні, обмежувального — при надлишковій масі та емоціогенного типу у підлітків з фізіологічною масою тіла необхідно враховувати, призначаючи персоніфіковану корекцію способу життя. Найбільш інформативними біоелектричними параметрами біоімпедансометрії були загальний жир, вісцеральний жир і метаболічний вік. Біоімпедансометрію як неінвазивно-предиктивний метод діагностики ожиріння можна рекомендувати для широкого впровадження в педіатричну практику.

Estimation of human metabolic age using regression and neural network analysis The aim is to develop the methods for assessing the rate of human aging by metabolic parameters (metabolic age). Materials and methods. The study examined 120 subjects aged 40–80 years. All the people included in the study underwent the determination of plasma glucose concentration, lipid profile – total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein, very low-density lipoprotein cholesterol and creatinine as well as the standard glucose tolerance test. Validation of the panel of indicators was carried out using regression and neural network analysis. Results. According to the study results, the standard error in determining the metabolic age using the multiple regression equation was 9.31 years, and using the neural network – 3.18 years. Conclusions. The methods that we have developed for assessing the rate of metabolic aging showed sufficient (regression analysis) and high (neural network analysis) accuracy and can be used to assess the risk of metabolic syndrome, cardiovascular disease, and type II diabetes. The implementation of the proposed methods would not only identify people at risk for pathology, but also assess the effectiveness of treatment, prevention and rehabilitation measures.

Every 10 years, an adult’s basal metabolic rate (BMR), independent of their BMI, decreases 1–2% due to skeletal muscle loss, thus decreasing an adult’s energy requirement and promoting obesity. Increased obesity augments the risk of developing Metabolic Syndrome (MetS); however, an adult’s healthy lifestyle, which increases BMR, can mitigate MetS development. To compare different BMRs for certain ages, Metabolic age (Met-age) was developed. To assess the association between Met-age and MetS and to determine if Met-age is an indicator of high-risk individuals for MetS. Four hundred thirty-five attendees at 2 clinics agreed to participate and gave signed informed consent. MetS risk was assessed by the ESF-I questionnaire. Met-age was determined using a TANITA bio-analyzer. Strengthen of association was determined by calculating Spearman’s rho and predictability was evaluated by the area-under-a-receiver-operating characteristic curve (AUC). Difference-in-age (DIA) = [chronological age − Met-age]. There was a difference between the low-risk (n = 155) and the high-risk (n = 280) groups’ Met-age (37.8±16.7 v. 62.9±17.3) and DIA (1.3±17.4 v. − 10.5±20.8, p

Obesity is a disease defined by excessive fat storage in the body. It is an energy balance problem; the increase in body fat is caused by an imbalance between energy intake and energy expenditure. Method/participants: The present study was a cross-sectional study conducted in 2019 in xxx University’s GETAT Center). Patients aged between 18–65 years with a BMI > 25 were included in the study. Exclusion Criteria: Pregnant women, breastfeeding patients , susceptible demographics (acute coronary insufficiency, immunodeficiency, severe psychotic disorder, liver and kidney failure), and those who could not give consent were not included in the study. Weight, BMI, and metabolic age values were measured with a Tanita device; the same diagnostic device was used for all patients. Both body and ear acupuncture were performed. Results: A t-test was applied to pre- and post-acupuncture measurement values. After acupuncture, the waist circumference of the participants decreased significantly (p < 0.005). The BMI of the participants also decreased significantly after acupuncture (p < 0.005).

Excessive fat accumulation in the obese body causes chronic low-grade inflammation. The continuous occurrence will affect health, which may lead to damage to cell metabolism related to metabolic age. Therefore, anthropometric application by measuring neck circumference (NC) and body mass index (BMI) was performed. The aim of this study was to determine NC cut-off which can be used to identify the increase of metabolic age in an individual. This study is a diagnostic study using cross sectional design using subjects who met the criteria needed for this study (n = 82). BMI and NC anthropometric measurements were performed in this study. Metabolic age was measured using Bioelectrical Impedance Analyzer (BIA). Data were analyzed using 2 x 2 diagnostic table and Receiver Operating Characteristic (ROC) curve to obtain Area Under Curve (AUC). The results showed that the highest BMI was obese (65.8%) with the most common age of 30-57 years old. The result of ROC-AUC NC on metabolic age showed that AUC value of NC measurement was 0.77, cut-off ≥ 33 cm, sensitivity 71.2%, and specificity 69.6%. This study concludes that the cut-off value of NC in predicting the increase of metabolic age had good sensitivity and specificity.

Programming of offspring life-course health by maternal nutrition and stress are well studied. At postnatal day 850, we evaluated male and female steroid levels and metabolism in aged offspring of primigravid sister rats bred at 70, 90, 150, or 300 days’ life. At 850 days life, male offspring corticosterone was similar regardless of maternal age. Female corticosterone was highest in offspring of 70- and 300-day mothers. Serum dehydroepiandrosterone:corticosterone was lowest in both sexes of offspring of 70- and 300-day mothers. Male and female fat depots were smaller in offspring of 150- than 70- and 90-day mothers. Insulin, glucose, and homeostatic model assessment were similar in all male offspring but higher in female offspring of 70-day mothers than other ages. We conclude, maternal age affects offspring aging in an offspring sex-dependent manner and merits consideration in designing and interpreting programming studies.

The aim of this study was to explore cardiac autonomic changes assessed by linear and nonlinear indexes of heart rate variability (HRV) and body composition modifications in breast cancer survivors and cancer-free control women. Women who were breast cancer survivors (BCS, n = 27) and without cancer with similar characteristics (Control, n = 31) were recruited for this study. We calculated some relevant linear and nonlinear parameters of 5 min of RR interval time series such as mean RR interval (RRave), the corrected Poincaré index (cSD1/SD2), the sample entropy (SampEn), the long-term fractal scaling exponent (α2) and 2UV from symbolic dynamics. Additionally, we indirectly assessed body composition measures such as body weight, fat mass, visceral fat rating (VFR), normalized VRF (nVFR), muscle mass, metabolic age, and total body water. We found that diverse HRV indexes and only one body composition measure showed statistical differences (p ave: 729 (648–802) vs. 795 (713–852) ms; cSD2/SD1: 3.4 (2.7–5.0) vs. 2.9 (2.3–3.5); SampEn: 1.5 (1.3–1.8) vs. 1.7 (1.5–1.8); α2: 0.6 (0.3–0.6) vs. 0.5 (0.4–0.5); 2UV: 7.1 (4.3–11.5) vs. 10.8 (6.4–15.7) and nVFR 0.12 (0.11–0.13) vs. 0.10 (0.08–0.12) points/kg, respectively. The nVFR was strongly significantly correlated with several indexes of HRV only in the BCS group.Our findings suggest that BCS exhibit lower parasympathetic cardiac activity and changes in HRV patterns compared to Controls. A concomitant increase of visceral fat, among other factors, may contribute to cardiac autonomic disturbances and changes in HRV patterns in BCS.

The aim of this study was to identify factors influencing maximal oxygen uptake (VO2max) and early identification of the profile of hypertensive women in the perimenopausal period at risk of heart failure. This study included 185 female patients. Regression analyses determined predictors of the lowest VO2max (quartile 1: VO2max &lt, 17 mL/kg/min). Females with the lowest oxygen consumption had a significantly higher level of high sensitive cardiac Troponin T (hs-cTnT) (p = 0.001), higher values of the left atrial (LA) volume, late diastolic mitral annulus velocity (A′), E/E′ (p = 0.0003, p = 0.02, p = 0.04, respectively), higher BMI and fat content (kg and %) (p &lt, 0.0001), higher fat free mass (FFM) (kg) (p &lt, 0.0001), total body water content (TBW) (p = 0.0002) as well as extracellular body water content (ECW) (p &lt, 0.0001) and intracellular body water content (ICW) (p = 0.005), ECW/TBW × 100% (p &lt, 0.0001) and metabolic age (p &lt, 0.0001) and lower E′ (p = 0.001) compared to controls. In a multiple logistic regression model independently associated with VO2max were: ECW/TBW × 100% (OR 4.45, 95% CI: 1.77–11.21, p = 0.002), BMI (OR 7.11, 95% CI: 2.01–25.11, p = 0.002) and hs-cTnT level (OR 2.69, 95% CI: 1.23–5.91, p = 0.013). High-sensitivity cardiac troponin may serve as an early biomarker of heart failure in hypertensive women. Hydration status should be considered in overall hypertensive women care. There is an importance of body mass compartments analysis in the early identification of hypertensive females at risk of heart failure. Optimization and personalization of body structure may be a preventive method for this disease. ClinicalTrials.gov Identifier: NCT04802369.

Red blood cell (RBC) storage in the blood bank is characterized by the progressive loss of metabolic regulation, a phenomenon that targets energy and antioxidant metabolism; While the progression of the storage lesion is inevitable, the rate at which this phenomenon occurs varies from donor to donor; Red blood cells from some donors at the end of storage are metabolically superior to RBCs from other donors at the beginning of storage, suggesting that the age of blood alone may not be a sufficiently accurate predictor of stored blood quality; and Animal studies and large-scale omics screening in blood donors have helped identify mechanistic contributors to the metabolic heterogeneity of stored blood units.

Objective:Psoriasis is a chronic inflammatory skin disease with a complex etiopathogenesis including genetic predisposition, immune dysfunction and environmental factors. Chronic inflammation leads to the development of vascular and metabolic disorders. The bioimpedance method is an easy and useful method for evaluating of body composition. In this study, it was aimed to investigate body composition, demographic, clinical and laboratory data in patients with psoriasis and to compare them with healthy controls. Material and Methods:Sociodemographic characteristics of the participants, duration of disease, concomitant systemic diseases, family history of psoriasis, presence of psoriatic arthritis and current treatments were questioned. Body composition of the participants was determined by Tanita Body Composition Analyzer type BC-418 (Tokyo, Japan), and in blood samples glucose, total cholesterol, HDL, LDL, triglyceride and insulin levels were determined by autoanalysers. Results:HOMA-IR, triglyceride, BMI, metabolic age and fat percentage were significantly higher in the psoriasis group, whereas the control group had higher body density, lean mass, mineral percentage and total body fluid. In this study, it was found that as the insulin resistance, BMI and fat ratio increased, the severity of the disease increased in patients with psoriasis. Also BMI increased in patients with longer disease duration. Topical and conventional therapies had no significant effect on laboratory and body composition parameters. Conclusion:In the light of the data obtained in this study, it was concluded that some metabolic markers and body composition parameters were negatively affected in patients with psoriasis and were associated with disease severity.

Body composition is closely related to the metabolic and biological functions of the body. Body composition and metabolic parameters were determined in 48 healthy women without an obesity, which underwent body shaping procedure – liposuction, with a usage of two types of body composition monitors.After liposuction, body weight significantly increased on average by 0.5 - 1.0 kg (p = 0.001). Body weight and body mass index correlated with all metabolic parameters.Body type was automatically calculated by "Tanita BC-542". Determination of body type when using "Tanita BC-601" was done manually. More than half of the patients on admission had a standard body type ("5" type) - 20 (54%), in 15 (41%) "hidden obesity" was found. After liposuction, 4 (14%) women improved their body type.The level of basal metabolic rate (BMR) in patients initially averaged 1340 ± 96 kcal when measured using a two-electrode analyzer, and 2128 ± 81 kcal - using a four-electrode analyzer (p = 0.0001), according to the literature – about 1000-1200 kcal. The average increase in BMR immediately after liposuction was 21 kcal, on the 7th day - 32 kcal.The metabolic age after body contouring became less than the actual one in 10 (56%) patients, by an average of 3.1 years (p = 0.0007).Four-electrode monitor revealed that an average decrease of fat on the abdomen was 5.4%. However, a decrease in its content in the hands and legs (in those zones that remained intact) was also detected. The analyzer also determined an increase in the content of muscles on the abdomen.In general, the bioelectrical impedance measurement in analysis of metabolic parameters in dynamics is simple and accessible, it has also a clinical importance. However, due to the identification of some errors, it requires repeated measurements and further improvement.

Over the last several years, increasing attention has been paid to abdominal adiposity and its association with increased mortality (Janssen I et al., 2004; Pischon T et al., 2008). Evidence for the positive effect of exercise on novel risk factors of the metabolic syndrome such as disturbances in adipokine secretion and low-grade inflammation confirms the importance of exercise in the treatment of the ‘new concept’ metabolic syndrome (You T, Nicklas BJ., 2008). Main objective of this paper was to compare the effects of traditional training and functional training on metabolic age and visceral fat in 18-30 years old subjects. 40 subjects: 20 in traditional training group (12 Males and 6 Females) & 20 in functional training group (12 Males and 6 Females), 18-30 years old were selected to take part in this 14-weeks intervention study. Subject underwent body composition parameters including visceral fat and metabolic age using BIA (Tanita BC 601). Data results pointed out that both training regimens produced a significant reduction (p < .05) in metabolic age and visceral fat but the subjects in the functional training group had better results. Normal 0 false false false en-150 X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-fareast-language:EN-US;}

Background: The blood metabolome incorporates cues from the environment and the host’s genetic background, potentially offering a holistic view of an individual’s health status. Methods: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts. Results: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual’s biological age. Exploration in independent cohorts demonstrates that being judged older by one’s metabolome, as compared with one’s chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge ( metaboage.researchlumc.nl ) allows easy incorporation in other epidemiological studies. Access to data can be requested at bbmri.nl/samples-images-data . Conclusions: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.

ISSUES ADDRESSED To determine cardiovascular health benefits in Indigenous men following short-duration small-sided games. METHODS Fourteen sedentary Indigenous males (35.6 SD 7.2 years), randomly assigned to a small-sided games (SSG) or a non-exercising control. Small-sided 20-minute (4 × 5 minute bouts) games of touch football were played 2 x/week for 9 weeks. Waist and hip circumferences, height, total body mass (kg), fat (%), fat free mass (kg), muscle mass (kg), resting heart rate (bpm), systolic blood pressure (mmHg), total cholesterol and high-density lipid concentrations were measured and waist-hip ratios, body mass index (BMI), heart rate variability (HRV), metabolic age and Framingham risk calculated before and after the exercise intervention. Between group differences were examined using unpaired t tests (welch corrected) and described using Cohen's effect size (ES) differences (corrected to determine hedges g). RESULTS Significant between group differences favouring the SSG group were observed in body mass (P = .039, ES = 0.18), BMI (P = .031, ES = 0.22) and metabolic age (P = .033, ES = 0.29) and in HRV parameters of approximate entropy (ApEN; P = .01, ES = 1.65) and sample entropy (SampEN; P = .0193, ES = 1.40). CONCLUSION Middle-aged Indigenous men can gain cardiovascular health benefits following short bouts of small-sided game play accumulating in 40-minutes of exercise each week. SO WHAT?: Short-duration SSG may address many exercise barriers, and offer a sustainable form of exercise to improve cardiovascular health amongst Indigenous men.

BACKGROUND Younger age at diagnosis of type 1 diabetes (T1D) may affect the clinical course and outcome. We examined whether age at diagnosis was associated with glycemic control and metabolic outcome in young adulthood. METHODS This observational study included 105 young adults with T1D (current mean age: 21.2 ± 3.0 years, mean age at diagnosis 12.0 ± 4.0 years) followed during 2012 to 2019. Data on HbA1c, glucose variability, continuous glucose monitoring (CGM) metrics, body mass index (BMI), blood pressure (BP), and body composition were collected from medical records from age 18 years until last visit, and the association between age at diagnosis and outcomes was assessed. RESULTS Age at T1D diagnosis was negatively associated with HbA1c levels (r = -0.368, P = .001), BMI (r = -0.218, P = .026), and diastolic BP (r = -0.215, P = .028). Younger age at diagnosis predicted poorer glycemic control after controlling for T1D duration, sex, socioeconomic status, BMI, and CGM use (r2 = 0.19, P = .002). There was a 0.1% greater HbA1c reduction for every yearly increase in age at diagnosis (β = -0.090, P = .042). The mean metabolic age of females diagnosed at

Chronological age confers an increased risk for cardiovascular disease; however, chronological age does not reflect the subject's current health status. Therefore, we assessed whether Metabolic age (Met-age), based on free fat mass, is a predictor of cardiovascular risk (CVR).Subjects attending either IMSS UMF-2 or CUSC-1 were asked to participate. CVR was assessed using the waist-to-height ratio (WHtR), whereas Met-age was determined using the TANITA bio-analyser (model: BC-545F Fitscan). The strengthen of association was determined by calculating Pearson's r and predictability was determined by the area-under-a-receiver-operating characteristic curve (AUC).284 subjects participated in this study, of which 61.6% had increased CVR. As expected, the chronological age was significantly higher in the CVR(+) group than the CVR(-) group (47.3±14.4 v. 35.2±12.7, respectively, p.001) as well as Met-age (59.3±15.5 v. 34.3±14.3, respectively, p.001). There was a strong association between WHtR and Met-age (r=.720, p.001) and a moderate association for chronological age (r=.407 p.001); however, the correlation between WHtR and Met-age was significantly better than chronological age (Z=-5.91, p.01). Met-age was a good predictor of CVR (AUC=.88, 95%CI: .83-.92, p.001), whereas chronological age was a fair predictor (AUC=.72, 95%CI: .66-.78, p.001). However, Met-age showed a higher discriminatory capacity for CVR than chronological age (z=-4.597, p.001).Here, we determined that Met-age correlated with a CVR index, WHtR, and was able to predict subjects with increased CVR better than chronological age.

Bottom waters of the Louisiana mid-continental shelf regularly become hypoxic with 64 mmol m−3) bottom waters. The field isotope measurements also showed that RP was above average and more important when and where river influences were larger, especially in the flood year 2008 and on the eastern shelf. In contrast, bottom water metabolic ages estimated as TSOS were above average and more important for hypoxia formation when and where river influences were smaller, especially in the average-flow year 2007 and on the western shelf.

This paper presents hydrodynamic lubrication of human skin by the thin layer sweat restricted on the tight fitting sportswear surface during the sport training. The aim of this paper is to determine the influence of the above mentioned lubrication of the skin by sweat during the training effort implemented with the electromagnetic field on the fat cells burning and loss body weight. To following are included in the research methods and materials used in this paper: tight fitting sportswear, pedometer (First Electronic Device FED), Second Electronic Device SED generating electro magnetic field, an analytical hydrodynamic model, the author’s experiences gained in German research institutes, the anamnesis and practical results after measurements. To the results obtained after sweat lubrication of movable skin demonstrate an influence of hydrodynamic pressure on metabolism increases and its stabilization. The main conclusions are concentrated in the decrements of the metabolism age in comparison with the human calendar age and the loss of human body weight during the slimming process.

Objectives To evaluate the long-term consequences of preterm birth on anthropometric parameters in women in adolescence and into adulthood. Methods Seventy girls born preterm (age 12.22 ± 1.52 years) and 48 born at term participated in the first stage. Eighteen years later, 13 of the same women participated in a follow-up and were compared with a control group of 27 women. We compared anthropometric results across the two examinations, and in the second stage, also assessed body composition using bioelectrical impedance analysis. Results No significant differences were found in anthropometric parameters or the content of individual components of the body between the preterm-born and control groups. However, the preterm-born group showed a tendency for higher average fat mass and lower fat-free and soft lean mass compared with the control group, and had a significantly higher mean waist–hip ratio. Conclusions Preterm birth does not adversely affect somatic development in girls during adolescence, but shows a correlation with an elevated waist–hip ratio in adulthood.

Background. The study aims to analyze the relationship between body posture and composition, as well as postural stability in Parkinson’s disease patients. Material and Methods. 32 people were evaluated. The study was conducted in the Laboratory of Posturology at Jan Kochanowski University in Kielce (Poland). Body posture was examined using the optoelectronic body posture Formetric Diers Method III 4D. Postural stability was evaluated using the Biodex Balance System platform. Body composition was assessed with the method of bioelectrical impedance analysis using the Tanita MC 780 MA analyzer. Results. 11 patients (34.37%) had hyperkyphosis, 10 (31.25%) hyperlordosis, and 3 (9.37%) hyperkyphosis-hyperlordosis posture. Scoliosis (>10°) was observed in 28 (87.5%) subjects, whereas 4 (12.5%) presented scoliotic body posture (1–9°). In the examined population, all parameters of postural stability were within normal limits. Conclusions. A significant positive correlation was observed between surface rotation (°), General Stability Index (r=0.4075, p=0.0206), and Anteroposterior Stability Index (r=0.3819, p=0.0310). There was also a significant positive correlation between surface rotation (+max) (°), General Stability Index (r=0.3526, p=0.0206), and Anteroposterior Stability Index (r=0.3873, p=0.0285). Metabolic age also presented a significant positive correlation between metabolic age and General Stability Index (r=0.4057, p=0.0212), as well as Anteroposterior Stability Index (r=0.3507, p=0.0490).

Daily sedentary working hours contribute negatively to body composition, cardiovascular and metabolic health, especially in women, who are usually less active than men. The objective of this study was to analyze the effect of two trending choreographed fitness group-workouts on the body composition and cardiovascular and metabolic health of sedentary female workers. A total of 98 physically inactive and working women (38.9 &plusmn, 6.4 years of age) were randomly assigned to three study groups: Control group (CG) = 31, Zumba Fitness&reg, with three one-hour classes per week (ZF) = 39, and Zumba Fitness with 20 minutes of additional Bodyweight strength training (ZF + BW) = 28. Measurements included body composition, blood pressure, cardiovascular risk by the Framingham Heart Study tools (10 yr cardiovascular risk and vascular age) and a metabolic blood panel. Post-intervention, both choreographed fitness group-workouts reached a similar significant loss of fat mass (ZF = 2.805 &plusmn, 0.48, p &lt, 0.0001, ZF + BW = 3.540 &plusmn, 0.04, p &lt, 0.0001), an increase in muscle mass (ZF = 1.70 &plusmn, 0.581, p = 0.005, ZF + BW = 3.237 &plusmn, 0.657, p &lt, 0.0001) and a decrease in SBP (ZF= 6.454 &plusmn, 1.70, p &lt, ZF + BW = 4.12 &plusmn, 1.95, p = 0.039). Only the ZF group significantly improved the 10 yr cardiovascular risk (p = 0.032) and metabolic age (p = 0.0025) post-intervention. No significant improvement was observed in the metabolic panel for both choreographed fitness group-workouts. In conclusion, the ZF program generated improvements in cardiovascular and metabolic risk variables compared to ZF + BW or CG. Both choreographed fitness group-workouts contributed similarly to the improvement in systolic blood pressure, fat mass, muscle mass, and also engendered a great adherence to exercise.

Background: Recent studies have suggested a strong association between sleep apnea (SA) and atrial fibrillation (AF). Aims and Objectives: In this study we aimed to examine clinical predictors to identify SA and the prevalence and type of SA in patients with paroxysmal AF. Methods: We prospectively studied 578 patients with paroxysmal AF. SA was diagnosed using portable polygraphy two nights at home. Sleep studies were analyzed by an experienced specialist, using standard American Academy of Sleep Medicine definitions. The degree of subjective daytime sleepiness was assessed by Epworth Sleepiness Scale (ESS). Body composition data were collected using a body composition analyzer (Tanita BC-545N). We calculated differences in variables between SA categories by Chi-Square Test or ANOVA as appropriate. Results: 158 women (27 %) and 420 men (73%) were enrolled. Mean age (SD) was 60 (10) years and mean BMI 29 (4) kg/m². 477 (83%) of the patients had an apnea-hypopnea index (AHI) ≥ 5/h, while moderate/severe SA (AHI ≥ 15/h) was diagnosed in 243 patients (42%). The type of SA was predominantly obstructive, with mean AHI 15.3/h (12) (range 0.4/h-85.8/h). Mean central apnea index was 0.8/h (2). AHI increased with age, BMI, weight, neck-and waist circumference, body fat, visceral fat and metabolic age. Mean ESS score was 7 (4). There was no association between ESS and AHI/h, r=0.08. Conclusions: In our AF population the prevalence of SA (AHI ≥ 5/h) was 83 %, which is several times higher than in the general population (16%). The high prevalence of SA detected in this study may indicate that SA is under-recognized in patients with AF. We found a positive correlation between body composition and SA severity.

OBJECTIVES: Metabolic age serves as an emerging marker for metabolic health. We investigated whether relative metabolic age, defined as an individual's metabolic age relative to their chronological age, was associated with markers of body composition, blood pressure, and dietary intake. METHODS: Adult men and women (18–70y, n = 19) participated in a fasted baseline health assessment to measure body composition, waist circumference, resting blood pressure, and metabolic age using a Tanita SC-240 scale and Health Ware software. Dietary analysis of 5-day diet records was performed using Nutrition Data System for Research (NDSR), and satiety was quantified using a subjective scale. Relative metabolic age was calculated as: metabolic age – chronological age. Subjects were subsequently divided into two groups: young relative metabolic age (n = 10) and advanced relative metabolic age (n = 9). RESULTS: Relative metabolic age was significantly greater in the advanced relative metabolic age (+5 years) compared to the younger relative metabolic age group (−12 years), whereas chronological age and non-adjusted metabolic age did not differ between groups. Individuals with younger relative metabolic age had significantly lower body weight, body mass index, body fat mass, and waist circumference on average. Systolic blood pressure was additionally lower in subjects with a younger relative metabolic age. In evaluating diet composition, individuals with advanced relative metabolic age reported greater cravings for fat-rich foods, and consumed greater amounts of pork and cold cuts/sausages. Conversely, individuals with a younger relative metabolic age consumed significantly more grains, lauric acid, meat alternative, a greater percentage of calories from polyunsaturated fatty acids, and trended toward consuming greater amounts of vegetable protein. CONCLUSIONS: These findings suggest that younger relative metabolic age is associated with a more favorable body composition, lower blood pressure, and a plant-based dietary pattern. FUNDING SOURCES: This study was funded by the Fairfield University College of Arts and Sciences.

Aim: Obesity degree is the ratio of current weight to standart weight of the individual. Metabolic age (MA) compares the individual’s basal metabolic rate to an average for the individual’s age group. In this study, considering the close association of obesity with chronic diseases, the aim is to evaluate the association between obesity degree and chronological age (CA) as well as MA and to derive a more descriptive index related to age. Materials and Methods: In this study, 287 adults between 18 and 79 years of age [10 underweight, 86 individuals with normal body mass index (BMI), 90 overweight, 81 obese ve 20 morbid obese] were evaluated. Anthropometric measurements were performed. The values for BMI were calculated. Obesity degree, MA, visceral adiposity values were recorded using TANITA body composition monitor. Differences between CA and MA were calculated. Statistical analyses were performed. Results: The mean±SD values for CA and MA for the study population were calculated as 43.2±16.0 and 46.3±16.3 years, respectively. This value for visceral adiposity was 8.2±4.8. A weak correlation was observed between obesity degree and CA. No correlation was observed between obesity degree and MA. However, a strong negative correlation was found between CA-MA and obesity degree. There was also a strong correlation between this index and visceral adiposity. Conclusions: It is concluded that during the evaluation of obesity degree, this new index, considering the difference between CA and MA, would give much more useful information rather than CA or MA. Amaç: Obezite derecesi, bireyin mevcut ağırlığının ideal ağırlığına olan oranıdır. Metabolik yaş (MY), bireyin bazal metabolik hız (BMH)’ının, bireyin kronolojik yaş grubunun ortalama BMH’ı ile kıyaslanmasını sağlayan bir parametredir. Bu çalışmada, obezitenin kronik hastalıklarla olan yakın ilişkisi gözönüne alınarak, obezite derecesi ile kronolojik yaş (KY) ve MY arasındaki ilişkinin değerlendirilmesi ve yaşla ilgili daha belirleyici bir indeksin türetilmesi amaçlanmıştır. Klinisyenlerin antenatal fetal hareketlerde azalma gördükleri gebelerde, fetal kayıp olabileceği için tedirgin olup olmamaları gerektiğine, perinatal sonuçlar değerlendirilerek farkındalık yaratmak amaçlanmıştır. Materyal ve Metot: Çalışmada 18 ile 79 yaş arasında 287 yetişkin birey [10 düşük kilolu, 86 normal vücut kitle indeksi (VKİ)’ne sahip, 90 fazla kilolu, 81 obez ve 20 morbid obez] değerlendirildi. Antropometrik ölçümler kaydedildi. VKİ değerleri hesaplandı. Obezite derecesi, MY, viseral adipozite değerleri TANITA body composition monitor kullanılarak kaydedildi. KY-MY hesaplandı. İstatistiksel analizler gerçekleştirildi. Bulgular: Çalışma populasyonunun KY ve MY ortalama±SS değerleri sırasıyla 43.2±16.0 yıl ve 46.3±16.3 yıl olarak hesaplandı. Viseral adiposite için bu değer 8.2±4.8 idi. Obezite derecesi ile KY arasında zayıf bir korelasyon gözlendi. Obezite derecesi ile MY arasında herhangi bir ilişki saptanamadı. Obezite derecesi ile KY-MY arasında güçlü bir negatif ilişki bulundu. Bu indeks ile viseral adipozite arasında da güçlü bir ilişki hesaplandı. Sonuç: Obezite derecesinin değerlendirilmesinde KY ya da MY’ın değil, aralarındaki farkı göz önüne alan bu yeni indeksin çok daha yararlı bilgiler vereceği saptandı.

Background Ageing can be classified in two different ways, chronological ageing and biological ageing. While chronological age is a measure of the time that has passed since birth, biological (also known as transcriptomic) ageing is defined by how time and the environment affect an individual in comparison to other individuals of the same chronological age. Recent research studies have shown that transcriptomic age is associated with certain genes, and that each of those genes has an effect size. Using these effect sizes we can calculate the transcriptomic age of an individual from their age-associated gene expression levels. The limitation of this approach is that it does not consider how these changes in gene expression affect the metabolism of individuals and hence their observable cellular phenotype. Results We propose a method based on poly-omic constraint-based models and machine learning in order to further the understanding of transcriptomic ageing. We use normalised CD4 T-cell gene expression data from peripheral blood mononuclear cells in 499 healthy individuals to create individual metabolic models. These models are then combined with a transcriptomic age predictor and chronological age to provide new insights into the differences between transcriptomic and chronological ageing. As a result, we propose a novel metabolic age predictor. Conclusions We show that our poly-omic predictors provide a more detailed analysis of transcriptomic ageing compared to gene-based approaches, and represent a basis for furthering our knowledge of the ageing mechanisms in human cells. Electronic supplementary material The online version of this article (10.1186/s12859-018-2383-z) contains supplementary material, which is available to authorized users.

Autophagy is a highly conserved homeostatic cellular mechanism that mediates the degradation of damaged organelles, protein aggregates, and invading pathogens through a lysosome-dependent pathway. Over the last few years, specific functions of autophagy have been discovered in many tissues and organs; however, abnormal upregulation or downregulation of autophagy has been depicted as an attribute of a variety of pathologic conditions. In this review, we will describe the current knowledge on the role of autophagy, from its regulation to its physiological influence, in metabolic age-related disorders. Finally, we propose to discuss the therapeutic potential of pharmacological and nutritional modulators of autophagy to treat metabolic diseases.

Background Anabolic-androgenic steroids (AAS) are said to be frequently used by both professional and amateur athletes. In addition to having a negative impact on health, steroids defy the concept of fair play. The aim of the study was to evaluate the scale of the problem related to using anabolic-androgenic steroids (AAS) by gym athletes and to analyze possible causes. Methods The study involved 435 participants aged between 18-66 (mean age 27.49±7.48). Out of them, 61.4% were male and 38.6% were female. The subjects were divided into two groups: Group A included 154 (35.4%) amateur and recreational athletes and group B included 281 (64.6%) professional athletes concerned with fitness, bodybuilding and powerlifting. A survey prepared by the authors was conducted in the study, and it consisted of 23 closed questions about AAS use, body confidence, and exercise dependence. In addition, a stadiometer and a body composition analyzer were utilized to take necessary measurements. Results Between 1-23% of group A participants admitted to using AAS. For group B, it was between 7-30%. Males were reported to use AAS more frequently than females in both groups. With regard to group A, differences in body confidence and exercise dependence were found between males using and not using AAS. Exercise dependence was reported to be different between group A and group B participants. This was true for both males and females. Also, it was shown that group A and group B females differed in terms of metabolic age, body mass and body composition (fat mass, fat-free mass, muscle mass, and total body water). Conclusions Most gym athletes do not use AAS. Amateur athletes tend to use AAS more frequently than professional athletes. Factors that contribute to AAS use are: male gender, low body confidence, young age, and long training.

Meeting energy requirements of children with chronic kidney disease (CKD) is paramount to optimising growth and clinical outcome, but little information on this subject has been published. In this study, we examined basal metabolic rate (BMR; a component of energy expenditure) with the aim to determine whether it is related to kidney function independently of weight, height and lean body mass (LBM).Twenty children with CKD and 20 healthy age- and gender-matched control children were studied on one occasion. BMR was measured by indirect open circuit calorimetry and predicted by the Schofield equation. Estimated glomerular filtration rate (eGFR) was related to BMR and adjusted for weight, height, age and LBM measured by skinfold thickness.The adjusted BMR of children with CKD did not differ significantly from that of healthy subjects (1296 ± 318 vs.1325 ± 178 kcal/day; p = 0.720). Percentage of predicted BMR also did not differ between the two groups (102 ± 12% vs. 99 ± 14%; p = 0.570). Within the CKD group, eGFR (mean 33.7 ± 20.5 mL/min/m(2)) was significantly related to BMR (β 0.3, r = 0.517, p = 0.019) independently of nutritional status and LBM.It seems reasonable to use estimated average requirement as the basis of energy prescriptions for children with CKD (mean CKD stage 3 disease). However, those who were sicker had significantly lower metabolic rates.

The aim of this work was to evaluate low bone mass using the feed-forward neural network (NN) with good accuracy taking into account the forearm and heel bone mineral density (BMD) as well as total body composition variables. A total number of 162 subjects including 88 women (mean ± SD age = 37.7 ± 15.2 years) and 74 men (mean ± SD age=31.3 ± 10.9 years) were studied. In each subject, BMD (g cm-2) at forearm and heel using peripheral dual-energy X-ray absorptiometry (pDXA) and total body composition variables by multifrequency bioelectrical impedance analyzer were measured. The measured forearm BMD was used to estimate femur neck BMD by DXA using the published formula. Based on its T-score value, subjects were classified as normal and low bone mineral mass groups separately. In women, it was found that the forearm BMD was positively correlated with body fat percentage (r=0.327; p