7 resultados para European Populations

em Deakin Research Online - Australia


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A WHO expert consultation addressed the debate about interpretation of recommended body-mass index (BMI) cut-off points for determining overweight and obesity in Asian populations, and considered whether population-specific cut-off points for BMI are necessary. They reviewed scientific evidence that suggests that Asian populations have different associations between BMI, percentage of body fat, and health risks than do European populations. The consultation concluded that the proportion of Asian people with a high risk of type 2 diabetes and cardiovascular disease is substantial at BMIs lower than the existing WHO cut-off point for overweight (25 kg/m2). However, available data do not necessarily indicate a clear BMI cut-off point for all Asians for overweight or obesity. The cut-off point for observed risk varies from 22kg/m2 to 25kg/m2 in different Asian populations; for high risk it varies from 26kg/m2 to 31kg/m2. No attempt was made, therefore, to redefine cut-off points for each population separately. The consultation also agreed that the WHO BMI cut-off points should be retained as international classifications. The consultation identified further potential public health action points (23·0, 27·5, 32·5, and 37·5 kg/m2) along the continuum of BMI, and proposed methods by which countries could make decisions about the definitions of increased risk for their population.

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BACKGROUND: Accurate dietary assessment is key to understanding nutrition-related outcomes and is essential for estimating dietary change in nutrition-based interventions. OBJECTIVE: The objective of this study was to assess the pan-European reproducibility of the Food4Me food-frequency questionnaire (FFQ) in assessing the habitual diet of adults. METHODS: Participants from the Food4Me study, a 6-mo, Internet-based, randomized controlled trial of personalized nutrition conducted in the United Kingdom, Ireland, Spain, Netherlands, Germany, Greece, and Poland, were included. Screening and baseline data (both collected before commencement of the intervention) were used in the present analyses, and participants were included only if they completed FFQs at screening and at baseline within a 1-mo timeframe before the commencement of the intervention. Sociodemographic (e.g., sex and country) and lifestyle [e.g., body mass index (BMI, in kg/m(2)) and physical activity] characteristics were collected. Linear regression, correlation coefficients, concordance (percentage) in quartile classification, and Bland-Altman plots for daily intakes were used to assess reproducibility. RESULTS: In total, 567 participants (59% female), with a mean ± SD age of 38.7 ± 13.4 y and BMI of 25.4 ± 4.8, completed both FFQs within 1 mo (mean ± SD: 19.2 ± 6.2 d). Exact plus adjacent classification of total energy intake in participants was highest in Ireland (94%) and lowest in Poland (81%). Spearman correlation coefficients (ρ) in total energy intake between FFQs ranged from 0.50 for obese participants to 0.68 and 0.60 in normal-weight and overweight participants, respectively. Bland-Altman plots showed a mean difference between FFQs of 210 kcal/d, with the agreement deteriorating as energy intakes increased. There was little variation in reproducibility of total energy intakes between sex and age groups. CONCLUSIONS: The online Food4Me FFQ was shown to be reproducible across 7 European countries when administered within a 1-mo period to a large number of participants. The results support the utility of the online Food4Me FFQ as a reproducible tool across multiple European populations. This trial was registered at clinicaltrials.gov as NCT01530139.

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Aims To investigate body size and body fat relationships and fat distribution in young healthy men drawn from New Zealand European, Pacific Island, and Asian Indian populations.
Method A total of 114 healthy men (64 European, 31 Pacific Island, 19 Asian Indian) aged 17–30 years underwent measurements of height, weight, and body composition by total body dual-energy X-ray absorptiometry (DXA). Body mass index (BMI) was then calculated. Percent body fat (%BF), fat-free mass, bone mineral content, bone mineral density, abdominal fat, thigh fat, and appendicular skeletal muscle mass (ASMM) were obtained from the DXA scans.
Results For the same BMI, %BF for Pacific Island men was 4% points lower and for Asian Indian men was 7–8% points higher compared to Europeans. Compared to European men for the same %BF, BMI was 2–3 units higher for Pacific Island, and 3–6 units lower for Asian Indian. The ratio of abdominal fat to thigh fat, adjusted for height, weight, and %BF, was significantly higher for Asian Indian men than European (p=0.022) and Pacific Island (p=0.002) men. ASMM, adjusted for height and weight, was highest in Pacific Island and lowest in Asian Indian men.
Conclusions The relationship between %BF and BMI is different for European, Pacific Island, and Asian Indian men which may, at least in part, be due to differences in muscularity. Asian Indians have more abdominal fat deposition than their European and Pacific Island counterparts. Use of universal BMI cut-off points are not appropriate for comparison of obesity prevalence between these ethnic groups.

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Objective: To investigate the sources of cross-national variation in disability-adjusted life-years (DALYs) in the European Disability
Weights Project.

Methods
: Disability weights for 15 disease stages were derived empirically in five countries by means of a standardized procedure and the cross-national differences in visual analogue scale (VAS) scores were analysed. For each country the burden of dementia in women, used as an illustrative example, was estimated in DALYs. An analysis was performed of the relative effects of cross-national variations in demography, epidemiology and disability weights on DALY estimates.

Findings
: Cross-national comparison of VAS scores showed almost identical ranking orders. After standardization for population size and age structure of the populations, the DALY rates per 100 000 women ranged from 1050 in France to 1404 in the Netherlands. Because of uncertainties in the epidemiological data, the extent to which these differences reflected true variation between countries was difficult to estimate. The use of European rather than country-specific disability weights did not lead to a significant change in the burden of disease estimates for dementia.

Conclusions
: Sound epidemiological data are the first requirement for burden of disease estimation and relevant between-countries comparisons. DALY estimates for dementia were relatively insensitive to differences in disability weights between European countries.

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Western women are experiencing increases in the prevalence of overweight and obesity despite valuing slimness as ideal and equating thinness with attractiveness and beauty. Pacific populations are also experiencing high prevalence rates of overweight and obesity. A lage body size, however, has many positive connotations among pacific populations that stem from rich cultural practices such as feasts and deliberate fattening of women. There appears to be many sociocultural factors however, such as images of the slim ideal portrayed in Western media, influencing body image concerns that are shared between the two groups. A qualitative study involving semi-structured interviews was conducted to examine and compare the sociocultural influences on body size perceptionsand values. Participants include 16 European Australian and 16 Indigenous Fijian adolescent girls aged between 15 and 17 years. Inductive thematic analysis and analytical induction were qualitativemethods employed to facilitate interpretation of the findings. Preliminary findings suggest that Fijian adolescent girls experience greater conflict than European Australian girls about the desired body size endorsed in their community. Results also suggest that Indigenous Fijian girls place less importance than Australian girls on manipulating their body to achieve a specific ideal. Specific results of this study are reviewed and recommendations for future research are discussed.

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Understanding of the movements of species at multiple scales is essential to appreciate patterns of population connectivity and in some cases, the potential for pathogen transmission. The serotine bat (Eptesicus serotinus) is a common and widely distributed species in Europe where it frequently harbours European bat lyssavirus type 1 (EBLV-1), a virus causing rabies and transmissible to humans. In the United Kingdom, it is rare, with a distribution restricted to south of the country and so far the virus has never been found there. We investigated the genetic structure and gene flow of E. serotinus across the England and continental Europe. Greater genetic structuring was found in England compared with continental Europe. Nuclear data suggest a single population on the continent, although further work with more intensive sampling is required to confirm this, while mitochondrial sequences indicate an east-west substructure. In contrast, three distinct populations were found in England using microsatellite markers, and mitochondrial diversity was very low. Evidence of nuclear admixture indicated strong male-mediated gene flow among populations. Differences in connectivity could contribute to the high viral prevalence on the continent in contrast with the United Kingdom. Although the English Channel was previously thought to restrict gene flow, our data indicate relatively frequent movement from the continent to England highlighting the potential for movement of EBLV-1 into the United Kingdom.

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This paper seeks to explore the potential of a newly developed, grounded and participatory approach to development of health-literacy and health-care access interventions for equity – the Ophelia (OPtimising HEalth LIteracy and Access) process (Batterham et al., 2014). The methodology involves undertaking a needs assessment of the target population using intensive qualitative and quantitative methods, developing vignettes of key sub-groups within the population based on their health literacy profile of strengths and weaknesses, and then engaging with frontline practitioners and community membersin developing realistic solutions (Batterham et al., 2014).