ECSS Paris 2023: CP-MH08
INTRODUCTION: Overall health is a multifaceted construct in which physical activity level (PAL), nutritional status, and perceived well-being are essential pillars in adulthood. However, the current epidemiological scenario is marked by a high prevalence of physical inactivity and excess weight/obesity, conditions strongly associated with mental health disorders such as depression, stress, and anxiety. Purposse: To analyze the association between physical activity level, excess weight, sedentary behavior, and the severity of depressive, stress, and anxiety symptoms in adults of both sexes. METHODS: A total of 76 adults (mean age = 52.85 ± 10.51 years), of both sexes, were evaluated using a quantitative cross-sectional analytical design with an exploratory-descriptive approach. Sociodemographic characteristics (city of residence, occupation, education level, marital status, and family income), perceived health, and PAL—assessed using the short version of the International Physical Activity Questionnaire (IPAQ; METs/week)—were collected. Symptoms of depression, anxiety, and stress were assessed using the Depression, Anxiety and Stress Scale (DASS-21). Anthropometric measurements included body mass, height, and body mass index (BMI = 30.85 ± 10.51 kg/m²). Data normality was tested using the Shapiro–Wilk test. Associations between METs/week and depressive, anxiety, and stress symptoms; sitting time and stress; and BMI and depression were examined using Spearman’s correlation coefficient (rho). Statistical analyses were performed using SPSS version 24.0, with a significance level set at p < 0.05. RESULTS: No normal distribution was observed for BMI, METs/week, sedentary behavior, or DASS-21 subscales (p < 0.05). Overall, 71% of participants presented PAL below recommended levels (METs/week ≤ 480), including 54.3% of men and 85.4% of women. Additionally, 80.3% of participants were classified as having excess weight or obesity according to BMI criteria. Significant inverse associations were identified between METs/week and symptoms of depression (rho = −0.68), anxiety (rho = −0.70), and stress (rho = −0.72) (p < 0.001). A strong positive correlation was found between sitting time and stress (rho = 0.65), while a moderate positive association was observed between BMI and depressive symptoms (rho = 0.45). Individuals with sedentary behavior (≥ 9 h/day and/or low PAL) exhibited greater symptom severity. Notably, the prevalence of severe or extremely severe depression decreased from 42.1% in individuals with low PAL to 7.9% among those who were more physically active, with similar patterns observed for anxiety and stress. CONCLUSION: Adults with higher physical activity levels demonstrated lower severity of depressive, anxiety, and stress symptoms. In contrast, greater sedentary time and higher BMI were associated with increased symptom severity, reinforcing PAL as an important protective factor for mental health.
Read CV Alexandre GomesECSS Paris 2023: CP-MH08
INTRODUCTION: Body mass index (BMI) is one of the most widely used methods for assessing a person's physical condition. This is mainly due to its simplicity, as it only requires the subject's weight and height. Whilevery practical, it also has its limitations, such as not knowing which components (predominantly fat and muscle mass), make up that weight. Therefore, when assessing body composition or health status based on a person's weight, it is advisable to use complementary techniques such as anthropometry, Dual-Energy X-ray Absorptiometry (DXA) or bioelectrical impedance analysis, among others (1). Furthermore, the literature has already described a direct, but not proportional, relationship between BMI and body fat percentage (2). This has allowed for the creation of weight status classifications associated not only with BMI but also with body fat percentage (3). Therefore, this study aimed to examine the relationship between body weight and muscle mass across different classification criteria, including body mass index and body fat percentage. METHODS: A total of 1,126 participants [433 women (45.9±16 years, 71.5±14 kg, and 162±7 cm) and 693 men (43.6±14 years, 83.0±15 kg, and 175±7 cm)] underwent DXA; (GE Lunar Prodigy) to assess body composition. The device was calibrated every two days using the manufacturer-provided phantom. The total sample was classified according to the World Health Organization BMI criteria (4), adiposity was classified using DXA-derived percent body fat (%BF) according to the cut-points proposed by Potter et al. (3). RESULTS: A strong correlation was observed between body weight and BMI (women: r=0.903, p<0.001; men: r=0.903, p<0.001). The correlation was moderate with fat-free mass (FFM) (women: r=0.554, p<0.001; men: r=0.541, p<0.001) and appendicular muscle mass (AMM) (women: r=0.597, p<0.001; men: r=0.505, p<0.001). The ANCOVA showed that a higher BMI classification was associated with increases in FFM (F(4)=37.4, p=0.01, η_p^2=0.972) and AMM (F(4)=42.6, p=0.01, η_p^2=0.975), adjusted for age and height; however, when body weight was included as a covariate, the association disappeared for both FFM (F(4)=1.9, p=0.184, η_p^2=0.434) and AMM (F(4)=0.414, p=0.794, η_p^2=0.220). Similar results were obtained when using FFM and AMM in relation to body fat percentage classification. CONCLUSION: In summary, individuals with a higher BMI tended to have greater FFM and AMM, primarily because they weighed more. When body weight was considered, BMI no longer showed a clear relationship with lean mass. Therefore, BMI should not be used as an indicator of muscle mass, and results based on BMI categories should be interpreted in conjunction with body weight and, ideally, with direct measurements of body composition (e.g., DXA).
Read CV Pedro José Benito PeinadoECSS Paris 2023: CP-MH08
INTRODUCTION: Hatha yoga is practiced worldwide as a complementary or alternative exercise, with a range of low- to moderate exercise intensities. In this regard, low-intensity exercise (LIE) is increasingly recognized for its role in enhancing the aerobic base by metabolic flexibility, including efficient fat and carbohydrate oxidation as well as metabolic recovery. However, the distinct metabolic profiles of its various yoga sequences are unclear. Therefore, this study aimed to compare yoga-specific exercise intensities and metabolic contributions among Ashtanga (AS), Sivananda (SI), and Surya Namaskar (SN) sequences. METHODS: Thirty experienced yoga practitioners completed three standardized 60-min sessions of AS, SI, and SN yoga in randomized order. Heart rate, oxygen uptake (VO2peak and VO2mean), fat and carbohydrate oxidations (FATox and CHOox), and blood lactate concentrations (Peak La⁻ and delta [Δ] La⁻) were measured during each session. Moreover, metabolic contributions were analyzed using the PCr-La⁻-O2 method (oxidative; WOxi, glycolytic; WGly, and WPCr). RESULTS: No significant differences were observed in VO2peak among 60-min different yoga sequences, whereas VO2mean was significantly higher in SN compared with AS and SI (p < 0.0001). Peak La⁻ and ΔLa⁻ were significantly lower in SN compared with AS and SI (p < 0.0001). Furthermore, higher values of fat and carbohydrate oxidation rates and WOxi demand in kilojoules during SN were observed compared with AS and SI (p < 0.0001). CONCLUSION: The SN sequence may be an alternative LIE form for improving aerobic base, according to lower levels of Peak La⁻, ΔLa⁻, higher oxidative contribution, and fat oxidation compared to AS and SI. These findings indicate that SN may also be recommended as a low-intensity yoga-specific practice for metabolic improvements compared to popular low-intensity jogging.
Read CV seurun sungECSS Paris 2023: CP-MH08