972 resultados para C30 - General-Sectional Models


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Background
Lifestyle behaviours, such as healthy diet, physical activity and sedentary behaviour, are key elements of healthy ageing and important modifiable risk factors in the prevention of chronic diseases. Little is known about the relationship between these behaviours in older adults. The purpose of this study was to explore the relationship between fruit and vegetable (F&V) intake, leisure-time physical activity (LTPA) and sitting time (ST), and their association with self-rated health in older adults.

Methods
This cross-sectional study comprised 3,644 older adults (48% men) aged 55-65 years, who participated in the Wellbeing, Eating and Exercise for a Long Life ("WELL") study. Respondents completed a postal survey about their health and their eating and physical activity behaviours in 2010 (38% response rate). Spearman's coefficient (rho) was used to evaluate the relationship between F&V intake, LTPA and ST. Their individual and shared associations with self-rated health were examined using ordinal logistic regression models, stratified by sex and adjusted for confounders (BMI, smoking, long-term illness and socio-demographic characteristics).

Results
The correlations between F&V intake, LTPA and ST were low. F&V intake and LTPA were positively associated with self-rated health. Each additional serving of F&V or MET-hour of LTPA were associated with approximately 10% higher likelihood of reporting health as good or better among women and men. The association between ST and self-rated health was not significant in the multivariate analysis. A significant interaction was found (ST*F&V intake). The effect of F&V intake on self-rated health increased with increasing ST in women, whereas the effect decreased with increasing ST in men.

Conclusion
This study contributes to the scarce literature related to lifestyle behaviours and their association with health indicators among older adults. The findings suggest that a modest increase in F&V intake, or LTPA could have a marked effect on the health of older adults. Further research is needed to fully understand the correlates and determinants of lifestyle behaviours, particularly sitting time, in this age group.

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Background Medication side effects are an important cause of morbidity, mortality and costs in older people. The aim of our study was to examine prevalence and risk factors for self-reported medication side effects in an older cohort living independently in the community.

Methods The Melbourne Longitudinal Study on Healthy Ageing (MELSHA), collected information on those aged 65 years or older living independently in the community and commenced in 1994. Data on medication side effects was collected from the baseline cohort (n = 1000) in face-to-face baseline interviews in 1994 and analysed as cross-sectional data. Risk factors examined were: socio-demographics, health status and medical conditions; medication use and health service factors. Analysis included univariate logistic regression to estimate unadjusted risk and multivariate logistic regression analysis to assess confounding and estimate adjusted risk.

Results Self-reported medication side effects were reported by approximately 6.7% (67/1000) of the entire baseline MELSHA cohort, and by 8.5% (65/761) of those on medication. Identified risk factors were increased education level, co-morbidities and health service factors including recency of visiting the pharmacist, attending younger doctors, and their doctor's awareness of their medications. The greatest increase in risk for medication side effects was associated with liver problems and their doctor's awareness of their medications. Aging and gender were not risk factors.

Conclusion Prevalence of self-reported medication side effects was comparable with that reported in adults attending General Practices in a primary care setting in Australia. The prevalence and identified risk factors provide further insight and opportunity to develop strategies to address the problem of medication side effects in older people living independently in the community setting.

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Issue addressed: Many children consume excessive amounts of energy-dense, nutrient-poor (EDNP) or 'extra' foods and low intakes of fruit and vegetables. The aim of this study was to examine the associations between EDNP foods and ascertain whether certain EDNP foods and beverages are more likely to be eaten in association with other EDNP foods.

Methods: A cross-sectional representative population survey of children in preschool (n=764), and of school students in Years K, 2 and 4 (n=1,560) and in Years 6, 8 and 10 (n=1,685) residing in the Hunter New England region of New South Wales, Australia. Dietary data were collected using a short food frequency questionnaire. Multivariate logistic regression models examined the association between EDNP foods and fruit and vegetable intake. Data were stratified by sex and age cohort.

Results: More frequent consumption of some EDNP food types was significantly associated with more frequent consumption of other EDNP foods. Fast food and soft drinks consumption were associated with each other as well as with fried potato and salty snacks; and with lower intakes of fruit and vegetables in some but not all age groups.

Conclusion: The positive associations found between EDNP foods point towards the existence of a high-risk group of children who frequently consume a variety of EDNP foods and drinks.

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Hemodynamic models have a high potential in application to understanding the functional differences of the brain. However, full system identification with respect to model fitting to actual functional magnetic resonance imaging (fMRI) data is practically difficult and is still an active area of research. We present a simulation based Bayesian approach for nonlinear model based analysis of the fMRI data. The idea is to do a joint state and parameter estimation within a general filtering framework. One advantage of using Bayesian methods is that they provide a complete description of the posterior distribution, not just a single point estimate. We use an Auxiliary Particle Filter adjoined with a kernel smoothing approach to address this joint estimation problem.

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Background
Gender differences in cycling are well-documented. However, most analyses of gender differences make broad comparisons, with few studies modeling male and female cycling patterns separately for recreational and transport cycling. This modeling is important, in order to improve our efforts to promote cycling to women and men in countries like Australia with low rates of transport cycling. The main aim of this study was to examine gender differences in cycling patterns and in motivators and constraints to cycling, separately for recreational and transport cycling.

Methods
Adult members of a Queensland, Australia, community bicycling organization completed an online survey about their cycling patterns; cycling purposes; and personal, social and perceived environmental motivators and constraints (47% response rate). Closed and open-end questions were completed. Using the quantitative data, multivariable linear, logistic and ordinal regression models were used to examine associations between gender and cycling patterns, motivators and constraints. The qualitative data were thematically analyzed to expand upon the quantitative findings.

Results
In this sample of 1862 bicyclists, men were more likely than women to cycle for recreation and for transport, and they cycled for longer. Most transport cycling was for commuting, with men more likely than women to commute by bicycle. Men were more likely to cycle on-road, and women off-road. However, most men and women did not prefer to cycle on-road without designed bicycle lanes, and qualitative data indicated a strong preference by men and women for bicycle-only off-road paths. Both genders reported personal factors (health and enjoyment related) as motivators for cycling, although women were more likely to agree that other personal, social and environmental factors were also motivating. The main constraints for both genders and both cycling purposes were perceived environmental factors related to traffic conditions, motorist aggression and safety. Women, however, reported more constraints, and were more likely to report as constraints other environmental factors and personal factors.

Conclusion
Differences found in men’s and women’s cycling patterns, motivators and constraints should be considered in efforts to promote cycling, particularly in efforts to increase cycling for transport.

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Background: Objective The study aimed to determine the prevalence of malnutrition risk in a population of older people (aged 75 years and over) attending a community general practice and identify characteristics of those classified as malnourished or at risk of malnutrition.

Design Cross-sectional study of nutritional risk screen conducted over a six month period.

Participants and setting Patients attending a general practice clinic in Victoria, Australia, who attended for the “75 plus” health assessment check.

Measurements The Mini Nutritional Assessment Short Form (MNA®-SF) was included as part of the health assessment. Information was collected on living situation, co-morbidities, independence with meal preparation and eating, number of medications. Height and weight was measured and MNA®-SF score recorded.

Results Two hundred and twenty five patients attending a general practice for a health assessment with a mean age of 81.3(4.3)(SD) years, 52% female and 34% living alone. Only one patient was categorised by the MNA®-SF as malnourished, with an additional 16% classified as at risk of malnutrition. The mean Body Mass Index (BMI) of the at-risk group was significantly lower than the well-nourished group (23.6 ± 0.8 (SEM) vs 27.4 ± 0.3; p=0.0001). However, 34% of the at-risk group had a BMI of 25 or more with only 13% in the underweight category.

Conclusion In this population of older adults attending their general practitioner for an annual health assessment, one in six were identified as being at nutritional risk which is an additional risk factor for a severe health issue. Importantly, one third of the at-risk group had a BMI in the overweight or obese category, highlighting that older people can be at nutritional risk although they may be overweight or obese.

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Computational Intelligence (CI) models comprise robust computing methodologies with a high level of machine learning quotient. CI models, in general, are useful for designing computerized intelligent systems/machines that possess useful characteristics mimicking human behaviors and capabilities in solving complex tasks, e.g., learning, adaptation, and evolution. Examples of some popular CI models include fuzzy systems, artificial neural networks, evolutionary algorithms, multi-agent systems, decision trees, rough set theory, knowledge-based systems, and hybrid of these models. This special issue highlights how different computational intelligence models, coupled with other complementary techniques, can be used to handle problems encountered in image processing and information reasoning.

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To achieve valid conclusions, studies exploring associations of the built environment with residents' physical activity and health-related outcomes need to employ statistical approaches accounting for clustered data. This article discusses the following main statistical approaches: analysis of covariance, regression models with robust standard errors, generalized estimating equations, and multilevel generalized linear models. The choice of a statistical method depends on the characteristics of the study and research questions. While the first three approaches are employed to account for clustering in the data, multilevel models can also help unravel more substantive issues within a social ecological theoretical framework of health behavior.

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Introduction

Osteoarthritis (OA) has traditionally been considered a condition of older age. However, younger people are also affected by hip and knee OA, often as a result of sporting and work-related injuries. As OA studies have generally focused on older individuals, little is known about the experience of younger adults with hip or knee OA who can face a distinct set of pressures including work responsibilities and parenting roles. This study aims to investigate well-being and work participation among younger people with hip or knee OA, as well as preferences for OA education and support.

Methods and analysis:
200 people aged 20–55 years with a diagnosis of hip and/or knee OA will be recruited for this cross-sectional study. Participants will be recruited from three major public hospitals in the state of Victoria, Australia following screening of orthopaedic outpatient clinic lists and referrals, and through community-based advertisements. A study questionnaire will be mailed to all participants and written informed consent obtained. Validated measures of Health-Related Quality of Life (HRQoL), health status, psychological distress and work limitations will be used. Information on health services use will be collected, in addition to information on the perceived utility and accessibility of a range of existing and proposed education and peer support models. HRQoL data will be compared with Australian population norms using independent t tests, and associations between HRQoL, health status, psychological distress, work limitations and demographic factors will be evaluated using univariate and multivariate analyses. Data on the perceived utility and accessibility of education and peer support models will be analysed descriptively. 

Ethics and dissemination:
Ethics approval for the study has been obtained. The study findings will be submitted to peer-reviewed journals and arthritis consumer organisations for broader dissemination, and presented at national and international scientific meetings.

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Neurocomputational models of reaching indicate that efficient purposive correction of movement midflight (e.g., online control) depends on one's ability to generate and monitor an accurate internal (neural) movement representation. In the first study to test this empirically, the authors investigated the relationship between healthy young adults’ implicit motor imagery performance and their capacity to correct their reaching trajectory. As expected, after controlling for general reaching speed, hierarchical regression demonstrated that imagery ability was a significant predictor of hand correction speed; that is, faster and more accurate imagery performance associated with faster corrections to reaching following target displacement at movement onset. They argue that these findings provide preliminary support for the view that a link exists between an individual's ability to represent movement mentally and correct movement online efficiently.

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Article focus
▪ This article is a protocol of a study that involves offering fragile X syndrome carrier screening to pregnant and non-pregnant women in the general population. We are undertaking a programme evaluation approach using mixed methods to collect data about informed decisionmaking and predictors of test uptake, with a focus on psychosocial measures. We are also undertaking an economic appraisal.


Key messages
▪ Carrier screening for fragile X syndrome is the subject of debate because of concerns around education and counselling for this complex condition
and the potential for psychosocial harms.
▪ This study will inform policy and practice in the area of population carrier screening by examining psychosocial aspects of screening, including informed decision-making; models of screening, through antenatal care or other access points and health economics of carrier screening for fragile X syndrome.

Strengths and limitations of this study
▪ This study seeks to recruit 1000 women in total. This large sample size will give us sufficient power to address the aims of the study.
▪ Collecting quantitative and qualitative data will provide a more in-depth picture of screening for fragile X syndrome.
▪ A limitation of the study is that the data on models of screening may not be applicable to other countries that have different healthcare systems.

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Involvement in meal preparation and eating meals with the family are associated with better dietary patterns in adolescents, however little research has included older children or longitudinal study designs. This 3-year longitudinal study examines cross-sectional and longitudinal associations between family food involvement, family dinner meal frequency and dietary patterns during late childhood. Questionnaires were completed by parents of 188 children from Greater Melbourne, Australia at baseline in 2002 (mean age = 11.25 years) and at follow-up in 2006 (mean age = 14.16 years). Principal components analysis (PCA) was used to identify dietary patterns. Factor analysis (FA) was used to determine the principal factors from six indicators of family food involvement. Multiple linear regression models were used to predict the dietary patterns of children and adolescents at baseline and at follow-up, 3 years later, from baseline indicators of family food involvement and frequency of family dinner meals. PCA revealed two dietary patterns, labeled a healthful pattern and an energy-dense pattern. FA revealed one factor for family food involvement. Cross-sectionally among boys, family food involvement score (β = 0.55, 95% CI: 0.02, 1.07) and eating family dinner meals daily (β = 1.11, 95% CI: 0.27, 1.96) during late childhood were positively associated with the healthful pattern. Eating family dinner meals daily was inversely associated with the energy-dense pattern, cross-sectionally among boys (β = −0.56, 95% CI: −1.06, −0.06). No significant cross-sectional associations were found among girls and no significant longitudinal associations were found for either gender. Involvement in family food and eating dinner with the family during late childhood may have a positive influence on dietary patterns of boys. No evidence was found to suggest the effects on dietary patterns persist into adolescence.

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A method for combining a proportional-hazards survival time model with a bioassay model where the log-hazard function is modelled as a linear or smoothing spline function of log-concentration combined with a smoothing spline function of time is described. The combined model is fitted to mortality numbers, resulting from survival times that are grouped due to a common set of observation times, using Generalized Additive Models (GAMs). The GAM fits mortalities as conditional binomials using an approximation to the log of the integral of the hazard function and is implemented using freely-available, general software for fitting GAMs. Extensions of the GAM are described to allow random effects to be fitted and to allow for time-varying concentrations by replacing time with a calibrated cumulative exposure variable with calibration parameter estimated using profile likelihood. The models are demonstrated using data from a studies of a marine and a, previously published, freshwater taxa. The marine study involved two replicate bioassays of the effect of zinc exposure on survival of an Antarctic amphipod, Orchomenella pinguides. The other example modelled survival of the daphnid, Daphnia magna, exposed to potassium dichromate and was fitted by both the GAM and the process-based DEBtox model. The GAM fitted with a cubic regression spline in time gave a 61 % improvement in fit to the daphnid data compared to DEBtox due to a non-monotonic hazard function. A simulation study using each of these hazard functions as operating models demonstrated that the GAM is overall more accurate in recovering lethal concentration values across the range of forms of the underlying hazard function compared to DEBtox and standard multiple endpoint probit analyses.

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We investigate the relationship between consensus measures used in different settings depending on how voters or experts express their preferences. We propose some new models for single-preference voting, which we derive from the evenness concept in ecology, and show that some of these can be placed within the framework of existing consensus measures using the discrete distance. Finally, we suggest some generalizations of the single-preference consensus measures allowing the incorporation of more general notions of distance.

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Predictive frameworks for understanding and describing how animals respond to habitat fragmentation, particularly across edges, have been largely restricted to terrestrial systems. Abundances of zooplankton and meiofauna were measured across seagrasssand edges and the patterns compared with predictive models of edge effects. Artificial seagrass patches were placed on bare sand, and zooplankton and meiofauna were sampled with tube traps at five positions (from patch edges: 12, 60 and 130 cm into seagrass; and 12 and 60 cm onto sand). Position effects consisted of the following three general patterns: (1) increases in abundance around the seagrasssand edge (total abundance and cumaceans); (2) declining abundance from seagrass onto sand (calanoid copepods, harpacticoid copepods and amphipods); and (3) increasing abundance from seagrass onto sand (crustacean nauplii and bivalve larvae). The first two patterns are consistent with resource-distribution models, either as higher resources at the confluence of adjacent habitats or supplementation of resources from high-quality to low-quality habitat. The third pattern is consistent with reductions in zooplankton abundance as a consequence of predation or attenuation of currents by seagrass. The results show that predictive models of edge effects can apply to aquatic animals and that edges are important in structuring zooplankton and meiofauna assemblages in seagrass. © 2010 CSIRO.