3,862 research outputs found
Measuring physical inactivity:do current measures provide an accurate view of "sedentary" video game time?
BACKGROUND: Measures of screen time are often used to assess sedentary behaviour. Participation in activity-based video games (exergames) can contribute to estimates of screen time, as current practices of measuring it do not consider the growing evidence that playing exergames can provide light to moderate levels of physical activity. This study aimed to determine what proportion of time spent playing video games was actually spent playing exergames. METHODS: Data were collected via a cross-sectional telephone survey in South Australia. Participants aged 18 years and above (n = 2026) were asked about their video game habits, as well as demographic and socioeconomic factors. In cases where children were in the household, the video game habits of a randomly selected child were also questioned. RESULTS: Overall, 31.3% of adults and 79.9% of children spend at least some time playing video games. Of these, 24.1% of adults and 42.1% of children play exergames, with these types of games accounting for a third of all time that adults spend playing video games and nearly 20% of children's video game time. CONCLUSIONS: A substantial proportion of time that would usually be classified as "sedentary" may actually be spent participating in light to moderate physical activity
The impact of socioeconomic status on arthritis and osteoporosis
Background: Low socioeconomic status has been shown to be associated with both osteoarthri s and rheumatoid arthri s, impac ng on outcomes and even the development of arthri s. However the associa on with osteoporosis has been less clear. The reasons for the associa on may be linked to socioeconomic status through educa onal aspects, income, employment type and even area of residence. Purpose: The purpose of this study was use a monthly surveillance and monitoring system to examine the prevalence of self-reported osteoarthri s, rheumatoid arthri  s and osteoporosis over  me and the associa  on with measures of socioeconomic status
Measuring social capital in a known disadvantaged urban community – health policy implications
BACKGROUND: To assess the social capital profile of a known disadvantaged area a large cross-sectional survey was undertaken. The social capital profile of this area was compared to data from the whole of the state. The overall health status of the disadvantaged area was assessed in relation to a wide variety of social capital related variables. Univariate and multivariate analysis were undertaken. RESULTS: In the univariate analysis many statistically significant differences were found between the respondents in the disadvantaged area and the state estimates including overall health status, perceived attributes of the neighbourhood, levels of trust, community involvement and social activities. In the multivariate analysis very few variables were found to be statistically significantly associated with poorer health status. The variables that jointly predicted poorer health status in the disadvantaged area were older age, lower income, low sport participation, non-seeking help from neighbours and non-attendance at public meetings. CONCLUSION: Measuring social capital on a population level is complex and the use of epidemiologically-based population surveys does not produce overly valuable results. The inter-relational/dependence dichotomy of social capital is not yet fully understood making meaningful measurement in the broader population extremely difficult and hence is of questionable value for policy decision making
The use of a chronic disease and risk factor surveillance system to determine the age, period and cohort effects on the prevalence of obesity and diabetes in South Australian adults--2003-2013
Age, period and cohort (APC) analyses, using representative, population-based descriptive data, provide additional understanding behind increased prevalence rates
A Population Study of 5 to 15 Year Olds: Full Time Maternal Employment not Associated with High BMI. The Importance of Screen-Based Activity, Reading for Pleasure and Sleep Duration in Children’s BMI
To describe the relationship between maternal full time employment and health-related and demographic variables associated with children aged 5–15 years, and the factors associated with child overweight/obesity. Data from a chronic disease and risk factor surveillance system were limited to children aged 5–15 years whose mothers responded on their behalf (n = 641). Univariate/multivariate analyses described the differences between mothers who did and did not work full time. The same data were analysed comparing children who are overweight/obese against those with a normal BMI. The children of mothers who worked full time are more likely to be older, live in a household with a higher household income, be an only child or have one sibling or other child in the household, have a sole mother family structure and not spend any time reading for pleasure. No relationship was found between maternal employment and BMI. Compared with children of normal weight, those who were overweight/obese were more likely to spend no time studying, spend more than 2 h per day in screen-based activity and sleep less than 10 h per night. Child BMI status was not related to maternal employment. Although this analysis included eight diet related variables none proved to be significant in the final models.This study has shown that mothers’ working status is not related to children’s BMI. The relationship between overweight/obesity of children and high levels of screen-based activity, low levels of studying, and short sleep duration suggests a need for better knowledge and understanding of sedentary behaviours of children
Associations between area socioeconomic status, individual mental health, physical activity, diet and change in cardiometabolic risk amongst a cohort of Australian adults: A longitudinal path analysis
Presumed pathways from environments to cardiometabolic risk largely implicate health behaviour although mental health may play a role. Few studies assess relationships between these factors. This study estimated associations between area socioeconomic status (SES), mental health, diet, physical activity, and 10-year change in glycosylated haemoglobin (HbA1c), comparing two proposed path structures: 1) mental health and behaviour functioning as parallel mediators between area SES and HbA1c; and 2) a sequential structure where mental health influences behaviour and consequently HbA1c. Three waves (10 years) of population-based biomedical cohort data were spatially linked to census data based on participant residential address. Area SES was expressed at baseline using an established index (SEIFA-IEO). Individual behavioural and mental health information (Wave 2) included diet (fruit and vegetable servings per day), physical activity (meets/does not meet recommendations), and the mental health component score of the 36-item Short Form Health Survey. HbA1c was measured at each wave. Latent variable growth models with a structural equation modelling approach estimated associations within both parallel and sequential path structures. Models were adjusted for age, sex, employment status, marital status, education, and smoking. The sequential path model best fit the data. HbA1c worsened over time. Greater area SES was statistically significantly associated with greater fruit intake, meeting physical activity recommendations, and had a protective effect against increasing HbA1c directly and indirectly through physical activity behaviour. Positive mental health was statistically significantly associated with greater fruit and vegetable intakes and was indirectly protective against increasing HbA1c through physical activity. Greater SES was protective against increasing HbA1c. This relationship was partially mediated by physical activity but not diet. A protective effect of mental health was exerted through physical activity. Public health interventions should ensure individuals residing in low SES areas, and those with poorer mental health are supported in meeting physical activity recommendations
Reading in Graduate School: A Survey of Doctoral Students in Clinical Psychology
To what extent do graduate students in clinical psychology complete assigned readings? A total of 744 graduate students in American Psychological Association-accredited doctoral programs completed an online survey regarding reading in graduate school (67% response rate, of those viewing the survey). The reported amount of assigned reading varied widely, with an average of 330 pages per week. Compliance ratings suggested that about half the assigned reading is completed thoroughly and that thorough reading is more common than skimming or not reading assigned material. Motivating and hindering factors for reading are reported, and implications for faculty are considered
Health Estimates Using Survey Raked-Weighting Techniques in an Australian Population Health Surveillance System
A challenge for population health surveillance systems using telephone methodologies is to maintain representative estimates as response rates decrease. Raked weighting, rather than conventional poststratification methodologies, has been developed to improve representativeness of estimates produced from telephone-based surveillance systems by incorporating a wider range of sociodemographic variables using an iterative proportional fitting process. This study examines this alternative weighting methodology with the monthly South Australian population health surveillance system report of randomly selected people of all ages in 2013 (n = 7,193) using computer-assisted telephone interviewing. Poststratification weighting used age groups, sex, and area of residence. Raked weights included an additional 6 variables: dwelling status, number of people in household, country of birth, marital status, educational level, and highest employment status. Most prevalence estimates (e.g., diabetes and asthma) did not change when raked weights were applied. Estimates that changed by at least 2 percentage points (e.g., tobacco smoking and mental health conditions) were associated with socioeconomic circumstances, such as dwelling status, which were included in the raked-weighting methodology. Raking methodology has overcome, to some extent, nonresponse bias associated with the sampling methodology by incorporating lower socioeconomic groups and those who are routinely not participating in population surveys into the weighting formula
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