Physical activity, television viewing time and 12 year changes in waist circumference

PURPOSE: Both moderate-to-vigorous physical activity (MVPA) and sedentary behavior can be associated with adult adiposity. Much of the relevant evidence is from cross-sectional studies or from prospective studies with relevant exposure measures at a single time point prior to weight gain or incident obesity. This study examined whether changes in MVPA and television (TV) viewing time are associated with subsequent changes in waist circumference, using data from three separate observation points in a large population-based prospective study of Australian adults. METHODS: Data were obtained from the Australian Diabetes, Obesity and Lifestyle study collected in 1999-2000 (baseline), 2004-05 (Wave 2), and 2011-12 (Wave 3). The study sample consisted of adults aged 25 to 74 years at baseline who also attended site measurement at three time points (n=3261). Multilevel linear regression analysis examined associations of initial five-year changes in MVPA and TV viewing time (from baseline to Wave 2) with 12-year change in waist circumference (from baseline to Wave 3), adjusting for well-known confounders. RESULTS: As categorical predictors, increases in MVPA significantly attenuated increases in waist circumference (p for trend< 0.001). TV viewing time change was not significantly associated with changes in waist circumference (p for trend =0.06). Combined categories of MVPA and TV viewing time changes were predictive of waist circumference increases; compared to those who increased MVPA and reduced TV viewing time, those who reduced MVPA and increased TV viewing time had a 2cm greater increase in waist circumference (p=0.001). CONCLUSION: Decreasing MVPA emerged as a significant predictor of increases in waist circumference. Increasing TV viewing time was also influential, but its impact was much weaker than MVPA.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially.

Occupational class differences in suicide: evidence of changes over time and during the global financial crisis in Australia

BACKGROUND: Previous research showed an increase in Australian suicide rates during the Global Financial Crisis (GFC). There has been no research investigating whether suicide rates by occupational class changed during the GFC. The aim of this study was to investigate whether the GFC-associated increase in suicide rates in employed Australians may have masked changes by occupational class.

METHODS: Negative binomial regression models were used to investigate Rate Ratios (RRs) in suicide by occupational class. Years of the GFC (2007, 2008, 2009) were compared to the baseline years 2001-2006.

RESULTS: There were widening disparities between a number of the lower class occupations and the highest class occupations during the years 2007, 2008, and 2009 for males, but less evidence of differences for females.

CONCLUSIONS: Occupational disparities in suicide rates widened over the GFC period. There is a need for programs to be responsive to economic downturns, and to prioritise the occupational groups most affected.

Autism blogs: expressed emotion, language styles and concerns in personal and community settings

The Internet has provided an ever increasingly popular platform for individuals to voice their thoughts, and like-minded people to share stories. This unintentionally leaves characteristics of individuals and communities, which are often difficult to be collected in traditional studies. Individuals with autism are such a case, in which the Internet could facilitate even more communication given its social-spatial distance being a characteristic preference for individuals with autism. Previous studies examined the traces left in the posts of online autism communities (Autism) in comparison with other online communities (Control). This work further investigates these online populations through the contents of not only their posts but also their comments. We first compare the Autism and Control blogs based on three features: topics, language styles and affective information. The autism groups are then further examined, based on the same three features, by looking at their personal (Personal) and community (Community) blogs separately. Machine learning and statistical methods are used to discriminate blog contents in both cases. All three features are found to be significantly different between Autism and Control, and between autism Personal and Community. These features also show good indicative power in prediction of autism blogs in both personal and community settings.