What happens to bone mineral density, strength and body composition of ex-elite female volleyball players: A cross sectional study

Diet and physical activity and metabolic disorders in patients with schizophrenia and bipolar affective disorder in the Polish population

Introduction

There are numerous reports of a higher prevalence of metabolic disorders in patients with schizophrenia and bipolar disorder (BD), yet its connections to diet and physical activity remain not fully explained. This article aimed to evaluate diet, physical activity and selected biochemical and anthropometric parameters associated with metabolism in patients with schizophrenia and BD and to analyse the relationships between these variables in the subjects.

Materials and Methods

A total of 126 adults participated in the study: 47 patients with schizophrenia, 54 patients with BD and 25 patients in mental illness remission (reference group). Data were collected on the underlying illness and concomitant illnesses, and the severity of symptoms of the current episode was assessed using the following scales: PANSS, MADRS and YMRS. An assessment of the subjects' diet (KomPAN questionnaire) and their physical activity (International Physical Activity Questionnaire) was carried out. Anthropometric and blood pressure measurements were taken and BMI and WHR were calculated. Serum concentrations of fasting glucose, TSH, total cholesterol, LDL and HDL fractions, triglycerides and leptin, ghrelin and resistin were determined. For statistical analysis, the significance level was set at 0.05. For multiple comparisons one way ANOVA or Kruskal Wallis were used with post hoc Tukey and Dunn tests, respectively. To determine correlation of variables, Pearson's linear correlation coefficient or Spearman's rank correlation coefficient were used.

Results

A total of 50.8% of the subjects had at least one metabolic disorder-most commonly excessive body weight (66.7%) and abdominal obesity (64.3%). Patients did not differ significantly in terms of physical activity, but they did differ in mean time spent sitting-with this being significantly longer for all groups than in the general population. The subjects differed in diet: patients with BD consumed less unhealthy foods than patients with schizophrenia. The highest correlations between physical activity, diet and variables defining metabolic disorders were found in patients with BD. Only in patients with schizophrenia were there significant correlations between the course of the disease and physical activity.

Discussion

The results suggest the existence of associations between diet, physical activity, and metabolic disorders in both BD and schizophrenia patients. They also suggest a tendency among those patients to spend long periods of time sitting.

Automatic Thoughts, Self-Stigma, and Resilience Among Schizophrenia Patients with Metabolic Syndrome: A Cross-Sectional Study

Purpose

The study aims to clarify the negative psychological state and resilience impairments of schizophrenia (SCZ) with metabolic syndrome (MetS) while evaluating their potential as risk factors.

Patients and Methods

We recruited 143 individuals and divided them into three groups. Participants were evaluated using the Positive and Negative Syndrome Scale (PANSS), Hamilton Depression Rating Scale (HAMD)-24, Hamilton Anxiety Rating Scale (HAMA)-14, Automatic Thoughts Questionnaire (ATQ), Stigma of Mental Illness scale and Connor-Davidson Resilience Scale (CD-RISC). Serum biochemical parameters were measured by automatic biochemistry analyzer.

Results

The score of ATQ was highest in the MetS group (F = 14.5, p < 0.001), and the total score of CD-RISC, subscale tenacity score and subscale strength score of CD-RISC were lowest in the MetS group (F = 8.54, p < 0.001; F = 5.79, p = 0.004; F = 10.9, p < 0.001). A stepwise regression analysis demonstrated that a negative correlation was observed among the ATQ with employment status, high-density lipoprotein (HDL-C), and CD-RISC (β=-0.190, t=-2.297, p = 0.023; β=-0.278, t=-3.437, p = 0.001; β=-0.238, t=-2.904, p = 0.004). A positive correlation was observed among the ATQ with waist, TG, WBC, and stigma (β=0.271, t = 3.340, p = 0.001; β=0.283, t = 3.509, p = 0.001; β=0.231, t = 2.815, p = 0.006; β=0.251, t=-2.504, p = 0.014). The area under the receiver-operating characteristic curve analysis showed that among all independent predictors of ATQ, the TG, waist, HDL-C, CD-RISC, and stigma presented excellent specificity at 0.918, 0.852, 0.759, 0.633, and 0.605, respectively.

Conclusion

Results suggested that the non-MetS and MetS groups had grievous sense of stigma, particularly, high degree of ATQ and resilience impairment was shown by the MetS group. The TG, waist, HDL-C of metabolic parameters, CD-RISC, and stigma presented excellent specificity to predict ATQ, and the waist showed excellent specificity to predict low resilience level.

Relationship Between Physical Exercise and Cognitive Impairment Among Older Adults with Type 2 Diabetes: Chain Mediating Roles of Sleep Quality and Depression

Objective

Although physical exercise has been shown to boost physical, psychological, and psychiatric conditions in older adults, there is a relative lack of research on the mechanisms involved in this process for older adults with type 2 diabetes mellitus (T2DM). We thus evaluated whether sleep quality and depression mediated the relationship between physical exercise and cognitive impairment in older adults with T2DM by focusing on the exercise-physiology-psychology and psychiatry connection.

Methods

Self-reported data were collected from 2646 older adults with T2DM in Weifang, Shandong, China. Regression and bootstrap analyses were conducted to explore the chain mediator model including physical exercise, cognitive impairment, sleep quality, and depression.

Results

Engaging in physical exercise (coefficient = -0.6858, p < 0.001), high levels of sleep quality (coefficient = -0.3397, p = 0.015), and low levels of depression (coefficient = 0.3866, p < 0.001) were significantly associated with a low level of cognitive impairment. Sleep quality and depression mediated the chain effect between physical exercise and cognitive impairment (total effect = -1.0732, 95% CI [-1.3652, -0.7862]; direct effect = -0.6858, 95% CI [-0.9702, -0.3974]; indirect effect = -0.3875, 95% CI [-0.5369, -0.2521]).

Conclusion

Physical exercise may improve sleep quality in older adults with T2DM, alleviating depression and delaying the development of cognitive impairment. Physical exercise can enhance patients' ability to resist depression and cognitive impairment, and creating comfortable sleep environments can also reinforce the effects of this process. These findings have important implications for promoting healthy aging in older adults with T2DM.

Volleyball practice increases bone mass in prepubescent boys during growth: A 1-yr longitudinal study

The aim of this longitudinal study was to examine the effects of 1-yr of volleyball practice on the bone mass development in the growing skeleton among prepubescent children. Twenty volleyball players and nine teen matched control boys (Tanner stage 1, at the start of the study) were followed over a 1-yr period. Bone mineral density (BMD, g/cm²), bone mineral content (BMC, g) were measured by dual-energy X-ray absorptiometry on the whole body, lumbar spine (L2–L4), legs, arms, femoral necks, hips and radii. At follow-up, in comparison with controls, volleyball players gained more BMD in whole body (4.5% vs 1.7%; p = 0.014), both nondominant and dominant arms (5.8% vs 1.1% p = 0.005, and 6% vs 2.1%; p = 0.003, respectively), both nondmoninat and dominant legs (9% vs 4.8%; p = 0.005 and 10.7% vs 6% p = 0.0025; respectively), dominant ultradistal radius (10.4% vs 0.9%; p = 0.005), dominant third distal radius (9.6% vs 3.71%; p = 0.023), dominant whole radius (7.4% vs 3.1%; p = 0.017), lumbar spine L2-L4 (9.9% vs 2.8%; p = 0.004), femoral neck (4.7% vs 1.6%; p = 0.034), trochanter (6% vs 1.5%; p<0.001) and total hip (6.1% vs 2.6%; p = 0.006). Volleyball players gained more BMC in both nondominant and dominant arms (25.1% vs 13.4%; p = 0.003, and 26.1% vs 15.6%; p<0.001 respectively), both nondominant and dominant legs (20.2% vs 14.5%; p = 0.004 and 23% vs 16%; p = 0.004, respectively), dominant ultradistal radius (22.4% vs 8.7%; p = 0.002), dominant third distal radius (20.9% vs 5.9%; p = 0.001), dominant whole radius (20% vs 13%), nondominant third distal radius (14.5% vs 5.9%; p = 0.001), nondominant whole radius (21.1% vs 12%; p = 0.002), lumbar spine L2-L4 (21.1% vs 13.7%; p = 0.007), femoral neck (25.9% vs 8.7%; p = 0.007), trochanter (23.5% vs 17.1%; p = 0.006), and total hip (16.3% vs 11.3%; p = 0.009) than controls. A close correlation was observed between the increment (Δ) of whole body lean mass and increased (Δ) BMD and BMC in whole body (r = 0.43, p<0.01, r = 0.73, p<0.001; respectively), lumbar spine (r = 0.54, r = 0.61, p<0.001; respectively), trochanter (r = 0.46, p<0.01, r = 0.35, p<0.05; respectively), and total hip (r = 0.53, p<0.01, r = 0.6, p<0.0001; respectively). In summary, 1-yr of volleyball practice has an osteogenic effect on bone mass in loaded sites in prepubescent boys.