105 resultados para Physical activity counseling


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OBJECTIVE: Little is known regarding health-related quality of life and its relation with physical activity level in the general population. Our primary objective was to systematically review data examining this relationship. METHODS: We systematically searched MEDLINE, EMBASE, CINAHL, and PsycINFO for health-related quality of life and physical activity related keywords in titles, abstracts, or indexing fields. RESULTS: From 1426 retrieved references, 55 citations were judged to require further evaluation. Fourteen studies were retained for data extraction and analysis; seven were cross-sectional studies, two were cohort studies, four were randomized controlled trials and one used a combined cross sectional and longitudinal design. Thirteen different methods of physical activity assessment were used. Most health-related quality of life instruments related to the Medical Outcome Study SF-36 questionnaire. Cross-sectional studies showed a consistently positive association between self-reported physical activity and health-related quality of life. The largest cross-sectional study reported an adjusted odds ratio of "having 14 or more unhealthy days" during the previous month to be 0.40 (95% Confidence Interval 0.36-0.45) for those meeting recommended levels of physical activity compared to inactive subjects. Cohort studies and randomized controlled trials tended to show a positive effect of physical activity on health-related quality of life, but similar to the cross-sectional studies, had methodological limitations. CONCLUSION: Cross-sectional data showed a consistently positive association between physical activity level and health-related quality of life. Limited evidence from randomized controlled trials and cohort studies precludes a definitive statement about the nature of this association.

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In order to assess the contribution of the thermogenic effect of feeding and muscular activity to total energy expenditure, nine premature infants were studied for 2 consecutive days during which time repeated measurements of energy expenditure by indirect calorimetry were performed throughout the day, combined with a visual activity score based on body movement. The infants were growing at 16.6 +/- 4.0 g/kg/day (mean +/- SD) and received 110 +/- 8 kcal/kg/day metabolizable energy (milk formula) and 522 +/- 40 mgN/kg/day. Their total energy expenditure was 68 +/- 4 kcal/kg/day indicating that 41 +/- 7 kcal/kg/day was retained for growth. Based on the combination of energy + N balances it was estimated that 80% of the weight gain was fat-free tissue and 20% was fat tissue. The rate of energy expenditure measured minute-by-minute was significantly and linearly correlated with the activity score in both the premeal (r = 0.75;p less than 0.001) and the postmeal periods (r = 0.74; p less than 0.001) with no difference in the regression slope, but with a significant difference in intercept. In preset feeding schedules the latter allowed an estimation of the thermogenic effect without the confounding effect of activity. This was found to be 3.1 +/- 1.8% when expressed as a percentage of metabolizable energy intake. However when the "classical" approach was used as a comparison (integration of extra energy expenditure induced by the meal), the thermogenic effect was found to be greater, i.e. 9.5 +/- 3.8% of the meal's metabolizable energy, due to the superimposed effect of physical activity in the postprandial state.(ABSTRACT TRUNCATED AT 250 WORDS)

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BACKGROUND: Black women are at greater risk of obesity than are white women, perhaps because of their lower levels of physical activity. OBJECTIVE: We compared free-living activity energy expenditure (AEE) in sedentary white and black women (in overweight and normal-weight states) and in never-overweight control subjects. DESIGN: Subjects included 46 women (23 white, 23 black) studied while overweight and after reaching a normal weight and 38 female control subjects (23 white, 15 black). Diet, without exercise training, resulted in a mean weight loss of 13 kg and a body mass index (in kg/m(2)) < 25. Body composition, sleeping energy expenditure, free-living total energy expenditure, and the energy cost of activity and aerobic capacity were assessed before and after weight loss under 4-wk, diet-controlled, weight-stable conditions and in the control subjects. AEE was defined as above-sleep energy expenditure. RESULTS: No significant racial differences in body composition, before or after weight loss, were found. After weight loss, AEE and aerobic capacity increased in the white women and decreased in the black women (P < 0.05 and P < 0.02, respectively). After weight loss, but not before, the white women had a significantly higher mean AEE than did the black women (2448 +/- 979 and 1728 +/- 1373 kJ/d, respectively; P < 0.05), approximating AEEs in the white (2314 +/- 1105) and black (2310 +/- 1251) control subjects. CONCLUSIONS: Relative to the responses of the white women to diet-induced weight loss, the black women became less fit and less physically active. Induction of a normal body weight in overweight black women appeared to produce a more obesity-prone state, favoring weight relapse.

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OBJECTIVES: To compare daily energy expenditure between RA patients and matched controls, and to explore the relationship between daily energy expenditure or sedentariness and disease-related scores. METHODS: One hundred and ten patients with RA and 440 age- and sex-matched controls were included in this study. Energy expenditure was assessed using the validated physical activity (PA) frequency questionnaire. Disease-related scores included disease activity (DAS-28), functional status (HAQ), pain visual analogue scale (VAS) and fatigue VAS. Total energy expenditure (TEE) and the amount of energy spent in low- (TEE-low), moderate- (TEE-mod) and high-intensity (TEE-high) PAs were calculated. Sedentariness was defined as expending <10% of TEE in TEE-mod or TEE-high activities. Between-group comparisons were computed using conditional logistic regression. The effect of disease-related scores on TEE was investigated using linear regression. RESULTS: TEE was significantly lower for RA patients compared with controls [2392 kcal/day (95% CI 2295, 2490) and 2494  kcal/day (2446, 2543), respectively, P = 0.003]. A significant difference was found between groups in TEE-mod (P = 0.015), but not TEE-low (P = 0.242) and TEE-high (P = 0.146). All disease-related scores were significantly poorer in sedentary compared with active patients. TEE was inversely associated with age (P < 0.001), DAS-28 (P = 0.032) and fatigue VAS (P = 0.029), but not with HAQ and pain VAS. CONCLUSION: Daily energy expenditure is significantly lower in RA patients compared with matched controls, mainly due to less moderate-intensity PAs performed. Disease activity and fatigue are important contributing factors. These points need to be addressed if promoting PA in RA patients is a health goal. Trial registration. ClinicalTrials.gov, http://clinicaltrials.gov, NCT01228812.

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The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.

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BACKGROUND: As an important modifiable lifestyle factor in osteoporosis prevention, physical activity has been shown to positively influence bone mass accrual during growth. We have previously shown that a nine month general school based physical activity intervention increased bone mineral content (BMC) and density (aBMD) in primary school children. From a public health perspective, a major key issue is whether these effects persist during adolescence. We therefore measured BMC and aBMD three years after cessation of the intervention to investigate whether the beneficial short-term effects persisted. METHODS: All children from 28 randomly selected first and fifth grade classes (intervention group (INT): 16 classes, n=297; control group (CON): 12 classes, n=205) who had participated in KISS (Kinder-und Jugendsportstudie) were contacted three years after cessation of the intervention program. The intervention included daily physical education with daily impact loading activities over nine months. Measurements included anthropometry, vigorous physical activity (VPA) by accelerometers, and BMC/aBMD for total body, femoral neck, total hip, and lumbar spine by dual-energy X-ray absorptiometry (DXA). Sex- and age-adjusted Z-scores of BMC or aBMD at follow-up were regressed on intervention (1 vs. 0), the respective Z-score at baseline, gender, follow-up height and weight, pubertal stage at follow-up, previous and current VPA, adjusting for clustering within schools. RESULTS: 377 of 502 (75%) children participated in baseline DXA measurements and of those, 214 (57%) participated to follow-up. At follow-up INT showed significantly higher Z-scores of BMC at total body (adjusted group difference: 0.157 units (0.031-0.283); p=0.015), femoral neck (0.205 (0.007-0.402); p=0.042) and at total hip (0.195 (0.036 to 0.353); p=0.016) and higher Z-scores of aBMD for total body (0.167 (0.016 to 0.317); p=0.030) compared to CON, representing 6-8% higher values for children in the INT. No differences could be found for the remaining bone parameters. For the subpopulation with baseline VPA (n=163), effect sizes became stronger after baseline VPA adjustment. After adjustment for baseline and current VPA (n=101), intervention effects were no longer significant, while effect sizes remained the same as without adjustment for VPA. CONCLUSION: Beneficial effects on BMC of a nine month general physical activity intervention appeared to persist over three years. Part of the maintained effects may be explained by current physical activity.

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Purpose: The accurate estimation of total energy expenditure (TEE) is essential to allow the provision of nutritional requirements in patients treated by maintenance hemodialysis (MHD). The measurement of TEE and resting energy expenditure (REE) by direct or indirect calorimetry and doubly labeled water are complicated, timeconsuming and cumbersome in this population. Recently, a new system called SenseWear® armband (SWA) was developed to assess TEE, physical activity and REE. This device works by measurements of body acceleration in two axes, heat production and steps counts. REE measured by indirect calorimetry and SWA are well correlated. The aim of this study was to determine TEE, physical activity and REE on patients on MHD using this new device. Methods and materials: Daily TEE, REE, step count, activity time, intensity of activity and lying time were determined for 7 consecutive days in unselected stable patients on MHD and sex, age and weightmatched healthy controls (HC). Patients with malnutrition, cancer, use of immunosuppressive drugs, hypoalbumemia <35 g/L and those hospitalized in the last 3 months, were excluded. For MHD patients, separate analyses were conducted in dialysis and non-dialysis days. Relevant parameters known to affect REE, such as BMI, albumin, pre-albumin, hemoglobin, Kt/V, CRP, bicarbonate, PTH, TSH, were recorded. Results: Thirty patients on MHD and 30 HC were included. In MHD patients, there were 20 men and 10 women. Age was 60,13 years ± 14.97 (mean ± SD), BMI was 25.77 kg/m² ± 4.73 and body weight was 74.65 kg ± 16.16. There were no significant differences between the two groups. TEE was lower in MHD patients compared to HC (28.79 ± 5.51 SD versus 32.91 ± 5.75 SD kcal/kg/day; p <0.01). Activity time was significantly lower in patients on MHD (101.3 ± 12.6SD versus 50.7 ± 9.4 SD min; p = 0.0021). Energy expenditure during the time of activity was significantly lower in MHD patients. MHD patients walked 4543 ± 643 SD vs 8537 ± 744 SD steps per day (p <0.0001). Age was negatively correlated with TEE (r = -0.70) and intensity of activity (r = -0.61) in HC, but not in patients on MHD. TEE showed no difference between dialysis and non-dialysis days (29.92 ± 2.03 SD versus 28.44 ± 1.90 SD kcal/kg/day; p = NS), reflecting a lack of difference in activity (number of steps, time of physical activity) and REE. This finding was observed in MHD patients both older and younger than 60 years. However, age stratification appeared to have an influence on TEE, regardless of dialysis day, (29.92 ± 2.07 SD kcal/kg/day for <60 years-old versus 27.41 ± 1.04 SD kcal/kg/day for ≥60 years old), although failing to reach statistical significance. Conclusion: Using SWA, we have shown that stable patients on MHD have a lower TEE than matched HC. On average, a TEE of 28.79 kcal/kg/day, partially affected by age, was measured. This finding gives support to the clinical impression that it is difficult and probably unnecessary to provide an energy amount of 30-35 kcal/kg/day, as proposed by international guidelines for this population. In addition, we documented for the first time that MHD patients exert a reduced physical activity as compared to HC. There were surprisingly no differences in TEE, REE and physical activity parameters between dialysis and non-dialysis days. This observation might be due to the fact that patients on MHD produce a physical effort to reach the dialysis centre. Age per se did not influence physical activity in MHD patients, contrary to HC, reflecting the impact of co-morbidities on physical activity in this group of patients.

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Assessing the total energy expenditure (TEE) and the levels of physical activity in free-living conditions with non-invasive techniques remains a challenge. The purpose of the present study was to investigate the accuracy of a new uniaxial accelerometer for assessing TEE and physical-activity-related energy expenditure (PAEE) over a 24 h period in a respiratory chamber, and to establish activity levels based on the accelerometry ranges corresponding to the operationally defined metabolic equivalent (MET) categories. In study 1, measurement of the 24 h energy expenditure of seventy-nine Japanese subjects (40 (SD 12) years old) was performed in a large respiratory chamber. During the measurements, the subjects wore a uniaxial accelerometer (Lifecorder; Suzuken Co. Ltd, Nagoya, Japan) on their belt. Two moderate walking exercises of 30 min each were performed on a horizontal treadmill. In study 2, ten male subjects walked at six different speeds and ran at three different speeds on a treadmill for 4 min, with the same accelerometer. O2 consumption was measured during the last minute of each stage and was expressed in MET. The measured TEE was 8447 (SD 1337) kJ/d. The accelerometer significantly underestimated TEE and PAEE (91.9 (SD 5.4) and 92.7 (SD 17.8) % chamber value respectively); however, there was a significant correlation between the two values (r 0.928 and 0.564 respectively; P<0.001). There was a strong correlation between the activity levels and the measured MET while walking (r(2) 0.93; P<0.001). Although TEE and PAEE were systematically underestimated during the 24 h period, the accelerometer assessed energy expenditure well during both the exercise period and the non-structured activities. Individual calibration factors may help to improve the accuracy of TEE estimation, but the average calibration factor for the group is probably sufficient for epidemiological research. This method is also important for assessing the diurnal profile of physical activity.

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The present study tested the effect of a school-based physical activity (PA) program on quality of life (QoL) in 540 elementary school children. First and fifth graders were randomly assigned to a PA program or a no-PA control condition during one academic year. QoL was assessed by the Child Health Questionnaire at baseline and postintervention. Based on mixed linear model analyses, physical QoL in first graders and physical and psychosocial QoL in fifth graders were not affected by the intervention. In first graders, the PA intervention had a positive impact on psychosocial QoL (effect size [d], 0.32; p < .05). Subpopulation analyses revealed that this effect was caused by an effect in urban (effect size [d], 0.38; p < .05) and overweight first graders (effect size [d], 0.45; p < .05). In conclusion, a school-based PA intervention had little effect on QoL in elementary school children.

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The objectives of this study were to describe the different modalities of physical activity programs designed for moderate to severe dementia and to identify their impact on functional independence in activities of daily living (ADL). A critical review of randomized controlled trials related to the impact of physical activity programs in moderately to severely demented persons on ADL performance and meta-analysis of the identified studies were performed. Among the 303 identified articles, five responded to the selection criteria. Four out of the five studies demonstrated limited methodological quality. In one high-quality study, physical activity programs significantly delayed deterioration of ADL performance. The program components and ADL assessment tools vary widely across studies. Although the proposed treatments have not proven their efficiency in improving the ADL status of the patients, they were able to limit the decline in ADL functioning. Future research is warranted in order to identify clinically relevant modalities for physical activity programs for people with moderate to severe dementia.

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Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.