969 resultados para healthy weight
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Small changes of diet may reduce CVD risk. One example is the inclusion of nuts. They are rich in fibre, unsaturated fatty acids and phytonutrients. However, their fat content and energy density raise concerns that chronic consumption will promote weight gain. Randomised intervention studies are required to evaluate whether this concern is well founded. This study's aim was to determine if the inclusion of a 1440 kJ serving of almonds in the daily diet results in positive energy balance, and body composition change. During a 23-week cross-over design study, participants were required to consume almonds for 10 weeks and were provided no advice on how to include them in their diet. For another 10 weeks (order counter-balanced), participants followed their customary diet and there was a 3-week washout between. The study group consisted of twenty women. Potential mechanisms of energy dissipation were measured. Ten weeks of daily almond consumption did not cause a change in body weight. This was predominantly due to compensation for the energy contained in the almonds through reduced food intake from other sources. Moreover, inefficiency in the absorption of energy from almonds was documented (P <0·05). No changes in resting metabolic rate, thermic effect of food or total energy expenditure were noted. A daily 1440 kJ serving of almonds, sufficient to provide beneficial effects on cardiovascular risk factors, may be included in the diet with limited risk of weight gain. Whether this can be generalised to other high-fat energy dense foods warrants evaluation.
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Background: Soy isoflavones show structural and functional similarities to estradiol. Available data indicate that estradiol and estradiol-like components may interact with gut "satiety hormones" such as peptide YY (PYY) and ghrelin, and thus influence body weight. In a randomized, double-blind, placebo-controlled, cross-over trial with 34 healthy postmenopausal women (59 ± 6 years, BMI: 24.7 ± 2.8 kg/m2), isoflavone-enriched cereal bars (50 mg isoflavones/day; genistein to daidzein ratio 2:1) or non-isoflavone-enriched control bars were consumed for 8 weeks (wash-out period: 8-weeks). Seventeen of the subjects were classified as equol producers. Plasma concentrations of ghrelin and PYY, as well as energy intake and body weight were measured at baseline and after four and eight weeks of each intervention arm. Results: Body weight increased in both treatment periods (isoflavone: 0.40 ± 0.94 kg, P < 0.001; placebo: 0.66 ± 0.87 kg, P = 0.018), with no significant difference between treatments. No significant differences in energy intake were observed (P = 0.634). PYY significantly increased during isoflavone treatment (51 ± 2 pmol/L vs. 55 ± 2 pmol/L), but not during placebo (52 ± 3 pmol/L vs. 50 ± 2 pmol/L), (P = 0.010 for treatment differences, independent of equol production). Baseline plasma ghrelin was significantly lower in equol producers (110 ± 16 pmol/L) than in equol non-producers (162 ± 17 pmol/L; P = 0.025). Conclusion: Soy isoflavone supplementation for eight weeks did not significantly reduce energy intake or body weight, even though plasma PYY increased during isoflavone treatment. Ghrelin remained unaffected by isoflavone treatment. A larger and more rigorous appetite experiment might detect smaller differences in energy intake after isoflavone consumption. However, the results of the present study do not indicate that increased PYY has a major role in the regulation of body weight, at least in healthy postmenopausal women.
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Background : Physical inactivity and insufficient fruit and vegetable consumption are key risk factors for obesity and noncommunicable diseases. Weight perceptions may affect physical activity and diet behaviors. We report current prevalence estimates of Australian adults meeting recommended levels of leisure-time physical activity (LTPA) (150 min/week or more of at least moderate-intensity physical activity (including walking) on 5 days/week) and fruit (2 servings/day) and vegetable (5 servings/day) consumption for health benefits, by weight status and perceptions.
Methods : We conducted a cross-sectional survey analysis of data for 16 314 adults from the Australian National Health Survey 2004–2005. All variables were collected by self-report. Weighted estimates were age- and gender-specific, and data were analyzed using logistic regression with acceptable weight referent categories, adjusting for covariates.
Results : Among acceptable, overweight and obese adults, the prevalence of LTPA was 26.8, 26.1 and 19.3% for men, and 27.7, 23.7 and 19.7% for women, respectively. Approximately 55 and 15% of adults consumed sufficient fruit servings/day and vegetable servings/day, respectively, and less than 5% of adults met combined LTPA and diet guidelines. Overweight decreased the odds ratio for LTPA among women but not men, and obesity decreased the odds ratio for LTPA among both men and women. Overweight perception conferred odds ratios of 0.83 (95% CI 0.70–0.97, P=0.021) for overweight men, and of 0.74 (95% CI 0.62–0.88, P=0.001) and 0.69 (95% CI 0.59–0.80, P<0.001) for obese men and women, respectively; for LTPA, whereas no significant associations were found for acceptable weight perception. No consistent associations between weight status or perceptions and diet behaviors were found.
Conclusions : Overweight perception may be another barrier to physical activity participation among men and women with excess body weight. Public health strategies might need to focus on overcoming weight perception as well as weight status barriers to adopting healthy physical activity behaviors.
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Obesity is a significant problem among adolescents in Pacific populations. This paper reports on the outcomes of a 3-year obesity prevention study, Healthy Youth Healthy Communities, which was part of the Pacific Obesity Prevention in Communities project, undertaken with Fijian adolescents. The intervention was developed with schools and comprised social marketing, nutrition and physical activity initiatives and capacity building designed to reduce unhealthy weight, and the individual exposure period was just over 2-year duration. The evaluation incorporated a quasi-experimental, longitudinal design in seven intervention secondary schools near Suva (n = 874) and a matched sample of 11 comparison secondary schools from western Viti Levu (n = 2,062). There were significant differences between groups at baseline; the intervention group was shorter, weighed less, had a higher proportion of underweight and lower proportion of overweight, and better quality of life (Pediatric Quality of Life Inventory only). At follow-up, the intervention group had lower percentage body fat (-1.17) but also a lower increase in quality of life (Assessment of Quality of Life instrument: -0.02; Pediatric Quality of Life Inventory: -1.94) than the comparison group. There were no other differences in anthropometry, and behaviours’ changes showed a mixed pattern. In conclusion, this school-based health promotion programme lowered percentage body fat but did not reduce unhealthy weight gain or influence most obesity-promoting behaviours among Fijian adolescents. Despite growing evidence supporting the efficacy of community-based approaches to reduce obesity among children of European descent, findings from this study failed to demonstrate the efficacy of a community capacity-building approach among an adolescent sample drawn from a different sociocultural, economic and geographical context. Additional ‘top–down’ or other innovative approaches may be needed to reduce adolescent obesity in the Pacific.
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BACKGROUND: Overweight, obesity and excess gestational weight gain (GWG) are associated with negative health outcomes for mother and child in pregnancy and across the life course. Interventions promoting GWG within guidelines report mixed results. Most are time and cost intensive, which limits scalability. Mobile technologies (mHealth) offer low cost, ready access and individually-tailored support. We aim to test the feasibility of an mHealth intervention promoting healthy nutrition, physical activity and GWG in women who begin pregnancy overweight or obese. METHODS/DESIGN: txt4two is a parallel randomised control trial pilot recruiting women with a singleton, live gestation between 10(+0) and 17(+6) weeks at the first hospital antenatal clinic visit. Inclusion criteria are pre-pregnancy BMI > 25 kg/m(2) and mobile phone ownership. One hundred consenting women will be randomised to intervention or control groups at a 1:1 ratio. All participants will receive standard antenatal care. In addition, the txt4two intervention will be delivered from baseline to 36 weeks gestation and consists of a tailored suite of theoretically-grounded, evidence-based intervention strategies focusing on healthy nutrition, physical activity and GWG. This includes: mobile phone interactive text messages promoting positive health behaviours, goal setting and self-monitoring; video messages; an information website; and a private moderated Facebook® chat forum. The primary outcome is the feasibility of the intervention. Secondary outcomes include GWG and participants' knowledge and behaviour regarding diet and physical activity during pregnancy. DISCUSSION: Findings will inform the development of larger-scale mHealth programmes to improve the delivery of healthy pregnancy nutrition, physical activity and GWG, that could be widely translated and disseminated. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRNU111111544397 . Date of registration: 19 March 2014.
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We assessed the 6-min walk distance (6MWD) and body weight x distance product (6MWw) in healthy Brazilian subjects and compared measured 6MWD with values predicted in five reference equations developed for other populations. Anthropometry, spirometry, reported physical activity, and two walk tests in a 30-m corridor were evaluated in 134 subjects (73 females, 13-84 years). Mean 6MWD and 6MWw were significantly greater in males than in females (622 ± 80 m, 46,322 ± 10,539 kg.m vs 551 ± 71 m, 36,356 ± 8,289 kg.m, P < 0.05). Four equations significantly overestimated measured 6MWD (range, 32 ± 71 to 137 ± 74 m; P < 0.001), and one significantly underestimated it (-36 ± 86 m; P < 0.001). 6MWD significantly correlated with age (r = -0.39), height (r = 0.44), body mass index (r = -0.24), and reported physical activity (r = 0.25). 6MWw significantly correlated with age (r = -0.21), height (r = 0.66) and reported physical activity (r = 0.25). The reference equation devised for walk distance was 6MWDm = 622.461 - (1.846 x Ageyears) + (61.503 x Gendermales = 1; females = 0); r2 = 0.300. In an additional group of 85 subjects prospectively studied, the difference between measured and the 6MWD predicted with the equation proposed here was not significant (-3 ± 68 m; P = 0.938). The measured 6MWD represented 99.6 ± 11.9% of the predicted value. We conclude that 6MWD and 6MWw variances were adequately explained by demographic and anthropometric attributes. This reference equation is probably most appropriate for evaluating the exercise capacity of Brazilian patients with chronic diseases.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Abstract Background We have searched if plasma high density lipoprotein-cholesterol (HDL-C) concentration interferes simultaneously with whole-body cholesterol metabolism and insulin sensitivity in normal weight healthy adult subjects. Methods We have measured the activities of several plasma components that are critically influenced by insulin and that control lipoprotein metabolism in subjects with low and high HDL-C concentrations. These parameters included cholesteryl ester transfer protein (CETP), phospholipid transfer protein (PLTP), lecithin cholesterol acyl transferase (LCAT), post-heparin lipoprotein lipase (LPL), hepatic lipase (HL), pre-beta-1HDL, and plasma sterol markers of cholesterol synthesis and intestinal absorption. Results In the high-HDL-C group, we found lower plasma concentrations of triglycerides, alanine aminotransferase, insulin, HOMA-IR index, activities of LCAT and HL compared with the low HDL-C group; additionally, we found higher activity of LPL and pre-beta-1HDL concentration in the high-HDL-C group. There were no differences in the plasma CETP and PLTP activities. Conclusions These findings indicate that in healthy hyperalphalipoproteinemia subjects, several parameters that control the metabolism of plasma cholesterol and lipoproteins are related to a higher degree of insulin sensitivity.
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Previous research has shown dietary intake self-monitoring, and culturally tailored weight loss interventions to be effective tools for weight loss. Technology can be used to tailor weight loss interventions to better suit adolescents. There is a lack of research to date on the use of personal digital assistants (PDAs) to self-monitor dietary intake among adolescents. The objective of this study was to determine the difference in dietary intake self-monitoring frequency between using a Personal Digital Assistant (PDA) or paper logs as a diet diary in obese adolescent females; and to describe differences in diet adherence, as well as changes in body size and self-efficacy to resist eating. We hypothesized dietary intake self-monitoring frequency would be greater during PDA use than during paper log use. This study was a randomized crossover trial. Participants recorded their diet for 4 weeks: 2 weeks on a PDA and 2 weeks on paper logs. Thirty-four obese females ages 12-20 were recruited for participation. Thirty were included in analyses. Participants recorded more entries/day while using the paper logs (4.10 entries/day ± 0.63) than while using the PDA (3.01 entries/day ±0.75) (p<0.001). Significantly more meals and snacks were skipped during paper log use (0.81/day ± 0.65) than during PDA use (0.23/day ± 0.22) (p=0.011). Changes in body size (BMI, weight, and waist circumference) and self-efficacy to resist eating did not differ significantly between PDA and paper log use. When compared to paper logs, participants felt the PDA was more convenient (p=0.020), looked forward to using the PDA more (p=0.008), and would rather continue using the PDA than the paper logs (p=0.020). The findings of this study indicate use of a PDA as a dietary intake self-monitoring tool among adolescents would not result in increased dietary intake self-monitoring to aid in weight loss. Use of paper logs would result in greater data returned to clinicians, though use of PDAs would likely get adolescents more excited about adhering to recommendations to record their diet. Future research should look at updated communication devices, such as cell phones and other PDAs with additional features, and the role they can play in increasing dietary intake self-monitoring among adolescents.^
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Introduction: Weight gain is a common concern following breast cancer and has been associated with negative health outcomes. As such, prevention of weight gain is of clinical interest. This work describes weight change between 6- and 18-months following a breast cancer diagnosis and explores the personal, treatment and behavioural characteristics associated with gains in weight. Methods: Body mass index was objectively assessed, at three-monthly intervals, on a population-based sample of women newly diagnosed with unilateral breast cancer (n=185). Changes in BMI between 6- and 18-months post-diagnosis were calculated, with gains of one or more being considered clinically detrimental to future health. Results: Approximately 60% of participants were overweight or obese at 6-months post-diagnosis. While BMI remained relatively stable across the testing period (range=27.3-27.8), 24% of participants experienced clinically relevant gains in BMI (median gains=1.9). Following adjustment for potential confounders, younger age (<45 years; Odds ratio, OR=9.8), being morbidly obese at baseline (OR=4.6) and receiving hormone therapy (OR=4.8) were characteristics associated with an increased odds (p<0.05) of gaining BMI. Other characteristics associated with gains in BMI were more extensive surgery and having a history of smoking, although these relationships were not supported statistically. In contrast, caring for younger children was associated with reduced risk of gaining BMI (OR=0.3, p=0.20). Conclusions: Clinically relevant weight gain between 6- and 18-months post-breast cancer diagnosis is an issue for one in four women, with certain subgroups being particularly susceptible. However, the majority of women diagnosed with breast cancer are overweight or obese and gains in body weight are common. Thus, interventions that address the importance of achieving and sustaining a healthy body weight, delivered to all women with breast cancer, may have greater public health impact than interventions targeting any specific breast cancer subgroup.
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Overweight and obesity are two of the most important emerging public health issues in our time and regarded by the World Health Organisation [WHO] (1998) as a worldwide epidemic. The prevalence of obesity in the USA is the highest in the world, and Australian obesity rates fall into second place. Currently, about 60% of Australian adults are overweight (BMI „d 25kg/m2). The socio-demographic factors associated with overweight and/or obesity have been well demonstrated, but many of the existing studies only examined these relationships at one point of time, and did not examine whether significant relationships changed over time. Furthermore, only limited previous research has examined the issue of the relationship between perception of weight status and actual weight status, as well as factors that may impact on people¡¦s perception of their body weight status. Aims: The aims of the proposed research are to analyse the discrepancy between perceptions of weight status and actual weight status in Australian adults; to examine if there are trends in perceptions of weight status in adults between 1995 to 2004/5; and to propose a range of health promotion strategies and furth er research that may be useful in managing physical activity, healthy diet, and weight reduction. Hypotheses: Four alternate hypotheses are examined by the research: (1) there are associations between independent variables (e.g. socio -demographic factors, physical activity and dietary habits) and overweight and/or obesity; (2) there are associations between the same independent variables and the perception of overweight; (3) there are associations between the same independent variables and the discrepancy between weight status and perception of weight status; and (4) there are trends in overweight and/or obesity, perception of overweight, and the discrepancy in Australian adults from 1995 to 2004/5. Conceptual Framework and Methods: A conceptual framework is developed that shows the associations identified among socio -demographic factors, physical activity and dietary habits with actual weight status, as well as examining perception of weight status. The three latest National Health Survey data bases (1995 , 2001 and 2004/5) were used as the primary data sources. A total of 74,114 Australian adults aged 20 years and over were recruited from these databases. Descriptive statistics, bivariate analyses (One -Way ANOVA tests, unpaired t-tests and Pearson chi-square tests), and multinomial logistic regression modelling were used to analyse the data. Findings: This research reveals that gender, main language spoken at home, occupation status, household structure, private health insurance status, and exercise are related to the discrepancy between actual weight status and perception of weight status, but only gender and exercise are related to the discrepancy across the three time point s. The current research provides more knowledge about perception of weight status independently. Factors which affect perception of overweight are gender, age, language spoken at home, private health insurance status, and diet ary habits. The study also finds that many factors that impact overweight and/or obesity also have an effect on perception of overweight, such as age, language spoken at home, household structure, and exercise. However, some factors (i.e. private health insurance status and milk consumption) only impact on perception of overweight. Furthermore, factors that are rel ated to people’s overweight are not totally related to people’s underestimation of their body weight status in the study results. Thus, there are unknown factors which can affect people’s underestimation of their body weight status. Conclusions: Health promotion and education activities should provide education about population health education and promotion and education for particular at risk sub -groups. Further research should take the form of a longitudinal study design ed to examine the causal relationship between overweight and/or obesity and underestimation of body weight status, it should also place more attention on the relationships between overweight and/or obesity and dietary habits, with a more comprehensive representation of SES. Moreover, further research that deals with identification of characteristics about perception of weight status, in particular the underestimation of body weight status should be undertaken.