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This study aimed to investigate the association between simultaneity of leisure-time physical inactivity and high television time with the presence of chronic diseases in adults and older adults in Brazil. We analyzed secondary data from Vigitel 2013 database, a cross-sectional national survey. It was included 37 947 adults (18–59 years) and 14 982 older adults (≥60 years) living in Brazilian state capitals. The association was between simultaneity of risk behaviors considering leisure-time physical inactivity (<10 min/day) and high television time (≥2 h/day), with the presence of chronic diseases (diabetes, dyslipidemia, hypertension and obesity), measured according to the age group. We performed a binary logistic regression, crude and adjusted analysis, using weighted to reflect population estimates. In adults, there was an association between leisure-time physical inactivity and television time with the presence of diseases. In practice, the simultaneity of risk behaviors when compared with those without risk behavior had higher odds for diabetes (OR = 1.83), dyslipidemia (OR = 1.17), hypertension (OR = 1.54) and obesity (OR = 1.60). In older adults, the simultaneity was associated with diabetes (OR = 1.61), hypertension (OR = 1.33) and obesity (OR = 1.81). We concluded that for adults and older adults the simultaneity of leisure-time physical inactivity and high television time increased the odds for the presence of chronic disease, especially for diabetes and obesity. [ABSTRACT FROM AUTHOR]

Background: The association between GIS-based walkability and walking for transport is considered to be well established in USA and in Australia. Research on the association between walkability and cycling for transport in European cities is lacking. The aim of this study was to test the predictive validity of established walkability measures and to explore alternative walkability measures associated with walking and cycling for transport in a European context. Methods: Outcome data were derived from the representative cross-sectional survey (n = 843) 'Radfreundliche Stadt' of adults in the city of Graz (Austria). GIS-based walkability was measured using both established measures (e.g. gross population density, household unit density, entropy index, three-way intersection density, IPEN walkability index) and alternative measures (e.g. proportion of mixed land use, four-way intersection density, Graz walkability index). ANCOVAs were conducted to examine the adjusted association between walkability measures and outcomes. Results: Household unit density, proportion of mixed land use, three-way intersection density and IPEN walkability index were positively associated with walking for transport, but the other measures were not. All walkability measures were positively associated with cycling for transport. Conclusion: The established walkability measures were applicable to a European city such as Graz. The alternative walkability measures performed well in a European context. Due to measurement issues the association between these walkability measures and walking for transport needs to be investigated further. [ABSTRACT FROM AUTHOR]

We present a simple general method for combining two one-sample confidence procedures to obtain inferences in the two-sample problem. Some applications give striking connections to established methods; for example, combining exact binomial confidence procedures gives new confidence intervals on the difference or ratio of proportions that match inferences using Fisher's exact test, and numeric studies show the associated confidence intervals bound the type I error rate. Combining exact one-sample Poisson confidence procedures recreates standard confidence intervals on the ratio, and introduces new ones for the difference. Combining confidence procedures associated with one-sample t-tests recreates the Behrens-Fisher intervals. Other applications provide new confidence intervals with fewer assumptions than previously needed. For example, the method creates new confidence intervals on the difference in medians that do not require shift and continuity assumptions. We create a new confidence interval for the difference between two survival distributions at a fixed time point when there is independent censoring by combining the recently developed beta product confidence procedure for each single sample. The resulting interval is designed to guarantee coverage regardless of sample size or censoring distribution, and produces equivalent inferences to Fisher's exact test when there is no censoring. We show theoretically that when combining intervals asymptotically equivalent to normal intervals, our method has asymptotically accurate coverage. Importantly, all situations studied suggest guaranteed nominal coverage for our new interval whenever the original confidence procedures themselves guarantee coverage. [ABSTRACT FROM AUTHOR]