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High levels of gamma glutamyltransferase (gamma-GT) and alanine aminotransferase (ALT), as well as fatty liver index (FLI) has been associated with higher cardiovascular disease risk factors in adults. The aim of this study was to examine the relationship between gamma-GT, ALT, and fatty liver index FLI levels across a gradient number of ideal cardiovascular health metrics in a representative sample of adults from the Chilean National Health Survey 2009–2010. Data from 1,023 men and 1,449 women (≥ 15 years) from the Chilean Health Survey 2009–2010 were analyzed. Ideal cardiovascular health was defined as meeting ideal levels of the following components: four behaviours (smoking, body mass index, physical activity and diet adherence) and three factors (total cholesterol, blood pressure and fasting glucose). Adults were grouped into three categories according to their number of ideal cardiovascular health metrics: ideal (5–7 metrics), intermediate (3–4 metrics), and poor (0–2 metrics). Blood levels of gamma-GT and ALT were measured and the FLI was calculated. A higher number of ideal cardiovascular health index metric was associated with lower gamma-GT, ALT and FLI (p from trend analysis <0.001). Also, adults meeting at least 3–4 metrics were predicted less likely to have prevalence of abnormal levels of gamma-GT and FLI (p<0.001) compared to adults who met only 0–2 metrics. These findings reinforce the usefulness of the ideal cardiovascular health metrics proposed by the American Heart Association as a tool to identify target subjects and promote cardiovascular health in South-American adults. [ABSTRACT FROM AUTHOR]

Context: Military service members commonly sustain lower extremity stress fractures (SFx). How SFx risk factors influence bone metabolism is unknown. Understanding how SFx risk factors influence bone metabolism may help to optimize risk-mitigation strategies. Objective: To determine how SFx risk factors influence bone metabolism. Design: Cross-sectional study. Setting: Military service academy. Patients or other participants: Forty-five men (agepre = 18.56 ± 1.39 years, heightpre = 176.95 ± 7.29 cm, masspre = 77.20 ± 9.40 kg; body mass indexpre = 24.68 ± 2.87) who completed Cadet Basic Training (CBT). Individuals with neurologic or metabolic disorders were excluded. Intervention(s): We assessed SFx risk factors (independent variables) with (1) the Landing Error Scoring System (LESS), (2) self-reported injury and physical activity questionnaires, and (3) physical fitness tests. We assessed bone biomarkers (dependent variables; procollagen type I amino-terminal propeptide [PINP] and cross-linked collagen telopeptide [CTx-1]) via serum. Main outcome measure(s): A markerless motion-capture system was used to analyze trunk and lower extremity biomechanics via the LESS. Serum samples were collected post-CBT; enzyme-linked immunosorbent assays determined PINP and CTx-1 concentrations, and PINP : CTx-1 ratios were calculated. Linear regression models demonstrated associations between SFx risk factors and PINP and CTx-1 concentrations and PINP : CTx-1 ratio. Biomarker concentration mean differences with 95% confidence intervals were calculated. Significance was set a priori using α ≤ .10 for simple and α ≤ .05 for multiple regression analyses. Results: The multiple regression models incorporating LESS and SFx risk factor data predicted the PINP concentration (R2 = 0.47, P = .02) and PINP : CTx-1 ratio (R2 = 0.66, P = .01). The PINP concentration was increased by foot internal rotation, trunk flexion, CBT injury, sit-up score, and pre- to post-CBT mass changes. The CTx-1 concentration was increased by heel-to-toe landing and post-CBT mass. The PINP : CTx-1 ratio was increased by foot internal rotation, lower extremity sagittal-plane displacement (inversely), CBT injury, sit-up score, and pre- to post-CBT mass changes. Conclusions: Stress fracture risk factors accounted for 66% of the PINP : CTx-1 ratio variability, a potential surrogate for bone health. Our findings provide insight into how SFx risk factors influence bone health. This information can help guide SFx risk-mitigation strategies. [ABSTRACT FROM AUTHOR]

Objectives: The aims of this study were to investigate the effects of a six-week in-season period of soccer training and games (congested period) on plasma volume variations (PV), hematological parameters, and physical fitness in elite players. In addition, we analyzed relationships between training load, hematological parameters and players’ physical fitness. Methods: Eighteen elite players were evaluated before (T1) and after (T2) a six-week in-season period interspersed with 10 soccer matches. At T1 and T2, players performed the Yo-Yo intermittent recovery test level 1 (YYIR1), the repeated shuttle sprint ability test (RSSA), the countermovement jump test (CMJ), and the squat jump test (SJ). In addition, PV and hematological parameters (erythrocytes [M/mm3], hematocrit [%], hemoglobin [g/dl], mean corpuscular volume [fl], mean corpuscular hemoglobin content [pg], and mean hemoglobin concentration [%]) were assessed. Daily ratings of perceived exertion (RPE) were monitored in order to quantify the internal training load. Results: From T1 to T2, significant performance declines were found for the YYIR1 (p<0.001, effect size [ES] = 0.5), RSSA (p<0.01, ES = 0.6) and SJ tests (p< 0.046, ES = 0.7). However, no significant changes were found for the CMJ (p = 0.86, ES = 0.1). Post-exercise, RSSA blood lactate (p<0.012, ES = 0.2) and PV (p<0.01, ES = 0.7) increased significantly from T1 to T2. A significant decrease was found from T1 to T2 for the erythrocyte value (p<0.002, ES = 0.5) and the hemoglobin concentration (p<0.018, ES = 0.8). The hematocrit percentage rate was also significantly lower (p<0.001, ES = 0.6) at T2. The mean corpuscular volume, mean corpuscular hemoglobin content and the mean hemoglobin content values were not statistically different from T1 to T2. No significant relationships were detected between training load parameters and percentage changes of hematological parameters. However, a significant relationship was observed between training load and changes in RSSA performance (r = -0.60; p<0.003). Conclusions: An intensive period of “congested match play” over 6 weeks significantly compromised players’ physical fitness. These changes were not related to hematological parameters, even though significant alterations were detected for selected measures. [ABSTRACT FROM AUTHOR]

Context: Individuals with an anterior cruciate ligament reconstruction (ACLR) are at an increased risk of developing posttraumatic osteoarthritis. How osteoarthritis risk factors, such as increased body mass index (BMI), may influence early changes in joint tissue metabolism is unknown. Objective: To determine the association between BMI and type 2 cartilage turnover in individuals with an ACLR. Design: Cross-sectional study. Setting: Research laboratory. Patients or Other Participants: Forty-five individuals (31 women, 14 men) with unilateral ACLR at least 6 months earlier who were cleared for unrestricted physical activity. Main Outcome Measure(s): Body mass index (kg/m²) and type 2 collagen turnover were the primary outcomes. Body mass index was calculated from objectively measured height and mass. Serum was obtained to measure type 2 collagen turnover, quantified as the ratio of degradation (collagen type 2 cleavage product [C2C]) to synthesis (collagen type 2 C-propeptide [CP2]; C2C : CP2). Covariate measures were physical activity level before ACLR (Tegner score) and current level of disability (International Knee Documentation Committee Index score). Associations of primary outcomes were analyzed for the group as a whole and then separately for males and females. Results: Overall, greater BMI was associated with greater C2C : CP2 (r = 0.32, P = .030). After controlling for covariates (Tegner and International Knee Documentation Committee Index scores), we identified a similar association between BMI and C2C: CP2 (partial r = 0.42, P = .009). Among women, greater BMI was associated with greater C2C : CP2 before (r = 0.47, P=.008) and after (partial r=0.50, P=.008) controlling for covariates. No such association occurred in men. Conclusions: Greater BMI may influence greater type 2 collagen turnover in those with ACLR. Individuals, especially women, who maintain or reduce BMI may be less likely to demonstrate greater type 2 collagen turnover ratios after ACLR. [ABSTRACT FROM AUTHOR]