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Background: This study describes levels of self-reported physical activity, frequency of selected opportunistic nonsedentary behaviors, and preferences of leisure-time activities in a representative sample of Portuguese adults, using data from a national survey on diet and activity behaviors (National Food, Nutrition and Physical Activity Survey, IAN-AF, 2015–2016). Methods: Participants were 3873 Portuguese adults (1827 men). They were interviewed face to face, and the short version of the International Physical Activity Questionnaire was used. Regular leisure-time programmed activities, and 6 additional items, forming the activity choice index questionnaire, were used to assess 6 discrete nonsedentary behaviors. Results: Using the International Physical Activity Questionnaire categories, 42.3% of the sample were classified as low active, 30.6% as moderately active, and 27.1% as highly active. Walking, health/fitness activities, running, group gymnastics classes, swimming/pool activities, football/futsal, and cycling were the most popular leisure-time activities. Between 15% (parking further away from destinations) and 48% (using the stairs instead of elevators) of participants reported that they frequently adopted commonly recommended nonsedentary activities. Conclusions: This study updates self-reported physical activity prevalence for Portugal adults, including older adults. In addition, it uniquely describes leisure-time activity preferences in the population and also the relative frequency of several nonsedentary activities of daily living.

Background: This investigation aimed to analyze the agreement between the GT3X accelerometer and the ActivPAL inclinometer for estimating and detecting changes in sedentary behavior of different contexts among adolescents. Methods: Secondary data from an intervention using standing desks in the classroom conducted within 2 sixth-grade classes (intervention [n = 22] and control [n = 27]) were used. The intervention took place over 16 weeks, with activity assessments (ActivPAL and GT3X) being performed 7 days before and in the last week of the intervention. Baseline information from both groups was considered for cross-sectional analysis (209 valid days), while data from 20 participants (intervention group) were used for longitudinal analysis. Results: The authors observed that GT3X overestimated sedentary time at school (16.8%), after school (13.5%), and during weekends (7.3%) compared with ActivPAL (P < .05). Outside the school (after school [r = −.188] and on weekends [r = −.260]), there was a trend to higher overestimation among adolescents with less sedentary behavior. Longitudinally, the GT3X was unable to detect changes resulting from an intervention in school hours (ActivPAL = −34.7 min·9 h⁻¹ vs GT3X = +6.7 min·9 h⁻¹; P < .05). Conclusions: The authors conclude that GT3X (cut-point of <100 counts·min⁻¹) overestimated sedentary time of free-living activities and did not detect changes resulting from a classroom standing desk intervention in adolescents.

Purpose: To analyze the association between body fluid changes evaluated by bioelectrical impedance vector analysis and dilution techniques over a competitive season in athletes. Methods: A total of 58 athletes of both sexes (men: age 18.7 [4.0] y and women: age 19.2 [6.0] y) engaging in different sports were evaluated at the beginning (pre) and 6 months after (post) the competitive season. Deuterium dilution and bromide dilution were used as the criterion methods to assess total body water (TBW) and extracellular water (ECW), respectively; intracellular water (ICW) was calculated as TBW–ECW. Bioelectrical resistance and reactance were obtained with a phase-sensitive 50-kHz bioelectrical impedance analysis device; bioelectrical impedance vector analysis was applied. Dual-energy X-ray absorptiometry was used to assess fat mass and fat-free mass. The athletes were empirically classified considering TBW change (pre–post, increase or decrease) according to sex. Results: Significant mean vector displacements in the postgroups were observed in both sexes. Specifically, reductions in vector length (Z/H) were associated with increases in TBW and ICW (r = −.718, P < .01; r = −.630, P < .01, respectively) and decreases in ECW:ICW ratio (r = .344, P < .05), even after adjusting for age, height, and sex. Phase-angle variations were positively associated with TBW and ICW (r = .458, P < .01; r = .564, P < .01, respectively) and negatively associated with ECW:ICW (r = −.436, P < .01). Phase angle significantly increased in all the postgroups except in women in whom TBW decreased. Conclusions: The results suggest that bioelectrical impedance vector analysis is a suitable method to obtain a qualitative indication of body fluid changes during a competitive season in athletes.

Central accumulation and distribution of body fat (BF) is an important cardiometabolic risk factor. Waist-to-hip ratio (WHR), commonly elevated in nonalcoholic fatty liver disease (NAFLD) patients, has been endorsed as a risk related marker of central BF content and distribution, but no standardized waist circumference measurement protocol (WCmp) has been proposed. We aimed to investigate whether using different WCmp affects the strength of association between WHR and BF content and distribution in NAFLD patients. BF was assessed with dual energy X-ray absorptiometry (DXA) in 28 NAFLD patients (19 males, 51 ± 13 years, and 9 females, 47 ± 13 years). Waist circumference (WC) was measured using four different WCmp (WC1: minimal waist; WC2: iliac crest; WC3: mid-distance between iliac crest and lowest rib; WC4: at the umbilicus) and WHR was calculated accordingly (WHR1, WHR2, WHR3 and WHR4, respectively). High WHR was found in up to 84.6% of subjects, depending on the WHR considered. With the exception of WHR1, all WHR correlated well with abdominal BF (r = .47 for WHR1; r = .59 for WHR2 and WHR3; r = .58 for WHR4) and BF distribution (r = .45 for WHR1; r = .56 for WHR2 and WHR3; r = .51 for WHR4), controlling for age, sex and body mass index (BMI). WHR2 and WHR3 diagnosed exactly the same prevalence of high WHR (76.9%). The present study confirms the strong relation between WHR and central BF, regardless of WCmp used, in NAFLD patients. WHR2 and WHR3 seemed preferable for use in clinical practice, interchangeably, for the diagnosis of high WHR in NAFLD patients.

This cross-sectional study was designed to develop normative functional fitness standards for the Portuguese older adults, to analyze age and gender patterns of decline, to compare the fitness level of Portuguese older adults with that of older adults in other countries, and to evaluate the fitness level of Portuguese older adults relative to recently published criterion fitness standards associated with maintaining physical independence. A sample of 4,712 independent-living older adults, age 65–103 yr, was evaluated using the Senior Fitness Test battery. Age-group normative fitness scores are reported for the 10th, 25th, 50th, 75th, and 90th percentiles. Results indicate that both women and men experience age-related losses in all components of functional fitness, with their rate of decline being greater than that observed in other populations, a trend which may cause Portuguese older adults to be at greater risk for loss of independence in later years. These newly established normative standards make it possible to assess individual fitness level and provide a basis for implementing population-wide health strategies to counteract early loss of independence.

Background: This study aims to describe the regional prevalence and patterns of physical activity (PA) and sedentary behavior among Brazilian adolescents. Methods: Data from the Brazilian Scholar Health Survey, a nationally representative survey of ninth-grade adolescents [mean age: 14.29 y (14.27–14.29)] conducted in 2015 (n = 101,445), were used. Outcomes were television viewing, sitting time (ST), total PA, and active traveling collected via self-administered questionnaire. Information on frequency of physical education classes and type of school was collected from the school’s director. Frequencies with 95% confidence intervals were used to determine the prevalence and patterns of outcomes. Results: Higher prevalence of PA (≥300 min/wk) and ST (>4 h/d) was found in Midwest (PA = 38.0%; ST = 44.5%), South (PA = 37.6%; ST = 50.1%), and Southeast (PA = 36.1%; ST = 49.3%) compared with Northeast (PA = 29.7%; ST = 36.9%) and North (PA = 34.4%; ST = 34.8%) regions of Brazil. ST was higher among adolescents from private schools (51.5%) than public schools (42.9%), whereas active traveling was greater among students of public schools than private schools (62.0% vs 34.4%). Most inequalities in outcomes between capital and interior cities were in the poorest regions. Conclusions: The results indicate that national plans targeting regional inequalities are needed to improve PA and to reduce sedentary behavior among Brazilian adolescents.

Background: This study describes the levels and patterns of television (TV) viewing in Brazilian adults and investigates associations of TV viewing with hypertension, type 2 diabetes, and heart disease. Methods: Data from the Brazilian Health Survey, a nationally representative survey that was conducted in 2013 (N = 60,202 men and women aged ≥18 y), were used. Information regarding TV viewing, physician diagnoses of type 2 diabetes, hypertension, and heart disease was collected via interview-administered questionnaire. Data on covariables (including chronological age, educational status, skin color, sodium consumption, sugar consumption, tobacco smoking, alcohol consumption, and leisure-time physical activity) were also self-reported. Logistic regression models and population attributable fractions were used for the etiological analyses. Results: The prevalence (95% confidence interval) of >4 hours per day of TV viewing was 12.7% (12.0–13.4) in men and 17.5% (16.8–18.3) in women. Men and women being younger or older, moderately educated, living alone, smoking tobacco, and drinking alcohol were associated with higher reported TV viewing time. Odds ratios (95% confidence interval) revealed that >4 hours per day of TV viewing was associated with type 2 diabetes [male: 1.64 (1.23–2.17) and female: 1.33 (1.09–1.63)], hypertension [male: 1.36 (1.14–1.63) and female: 1.20 (1.05–1.37)], and heart disease [male: 1.96 (1.43–2.69) and female: 1.30 (1.00–1.68)]. Exceeding 4 hours per day of TV viewing was responsible for 6.8% of type 2 diabetes, 3.7% of hypertension, and 7.5% of heart disease cases. Conclusions: Independent of covariates, >4 hours per day of TV viewing was associated with type 2 diabetes, hypertension, and heart disease. High volumes of TV viewing are prevalent and appear to contribute to chronic disease burden.