Overweight and obesity are a global epidemic, with over one billion overweight adults worldwide (300+ million of whom are obese). Obesity is linked to several serious health problems and medical conditions. Medical experts agree that physical activity is critical to maintaining fitness, reducing weight, and improving health, yet many people have difficulty increasing and maintaining physical activity in everyday life. Clinical studies have shown that health benefits can occur from simply increasing the number of steps one takes each day and that social support can motivate people to stay active. In this paper, we describe Houston, a prototype mobile phone application for encouraging activity by sharing step count with friends. We also present four design requirements for technologies that encourage physical activity that we derived from a threeweek long in situ pilot study that was conducted with women who wanted to increase their physical activity. Author Keywords design requirements, fitness, physical activity, pedometer,

Background: Nearly half of Americans do not meet the Surgeon General’s recommendation of �30 minutes of physical activity daily. Some transit users may achieve 30 minutes of physical activity daily solely by walking to and from transit. This study estimates the total daily time spent walking to and from transit and the predictors of achieving 30 minutes of physical activity daily by doing so. Methods: Transit-associated walking times for 3312 transit users were examined among the 105,942

Abstract — Logistic regression is an important technique for analyzing and predicting data with categorical attributes. In this paper, we consider supporting online analytical processing (OLAP) of logistic regression analysis for multi-dimensional data in a data cube where it is expensive in time and space to build logistic regression models for each cell from the raw data. We propose a novel scheme to compress the data in such a way that we can reconstruct logistic regression models to answer any OLAP query without accessing the raw data. Based on a first-order approximation to the maximum likelihood estimating equations, we develop a compression scheme that compresses each base cell into a small compressed data block with essential information to support the aggregation of logistic regression models. Aggregation formulae for deriving high-level logistic regression models from lower level component cells are given. We prove that the compression is asymptotically lossless in the sense that the aggregated estimator deviates from the true model by an error that is bounded and approaches to zero when the data size increases. The results show that the proposed compression and aggregation scheme can make feasible OLAP of logistic regression in a data cube. Further, it supports realtime logistic regression analysis of stream data which can only be scanned once and cannot be permanently retained. Experimental results validate our theoretical analysis and demonstrate that our method can dramatically save time and space costs with almost no degradation of the modelling accuracy. Index Terms — data cubes, online analytical processing, logistic regression, compression, aggregation I.

Research article Racial/Ethnic and social class differences in preventive care practices among persons with diabetes

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A partnership to promote public health The Healthy States Initiative provides information state policymakers need to make decisions on public health issues. The Council of State Governments ’ partners in the initiative are the National Black Caucus of State Legislators (NBCSL) and the National Hispanic Caucus of State Legislators (NHCSL). The initiative brings state legislators together with public health experts and officials from the Centers for Disease Control and Prevention (CDC) and state health departments to share information and identify innovative policy solutions. Healthy States Resources for State Policymakers nnHealthy States Web site. This unique Web site offers information and resources on many public health issues. Visit

Five insights that will shape healthcare

We are pleased to share the Medco 2009 Drug Trend Report, which chronicles an unprecedented year and identifies solutions for the historic challenges ahead. As predicted, specialty drug trend accelerated dramatically, from 12.4 % in 2007 to 15.8 % in 2008. In addition, the price inflation of branded pharmaceuticals increased more than 8%. Despite these trends, Medco clients in 2008 realized an average drug trend of 3.3%—a small increase from our all-time low in 2007. Among the insights revealed in this year’s report: • The weak economy drove renewed interest in generics, as the generic dispensing rate increased 4.4 % to 64.1%. • About 30 % to 40 % of the medicines currently in the pipeline are specialty drugs, with nearly 25 % of those targeting very rare conditions. • Biologic or protein-based drug therapies account for about 16 % of prescription drug spending and are growing at a much faster rate than other drug categories. • Branded drug price inflation and unit-cost growth will be moderated by the wave of first-time generics in high-cost categories, which is expected to peak after 2011. We would like to underscore a finding that reinforces mail as a successful quality and cost strategy: Clients with 40 % or greater mail penetration had an average trend of-0.7%, while clients with less than 40 % mail penetration had an average