Neighborhood Characteristics and Change in Depressive Symptoms Among Older Residents of New York City

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63031/1/beard_neighborhood characteristics_2009.pd

Comparison of two different physical activity monitors

<p>Abstract</p> <p>Background</p> <p>Understanding the relationships between physical activity (PA) and disease has become a major area of research interest. Activity monitors, devices that quantify free-living PA for prolonged periods of time (days or weeks), are increasingly being used to estimate PA. A range of different activity monitors brands are available for investigators to use, but little is known about how they respond to different levels of PA in the field, nor if data conversion between brands is possible.</p> <p>Methods</p> <p>56 women and men were fitted with two different activity monitors, the Actigraph™ (Actigraph LLC; AGR) and the Actical™ (Mini-Mitter Co.; MM) for 15 days. Both activity monitors were fixed to an elasticized belt worn over the hip, with the anterior and posterior position of the activity monitors randomized. Differences between activity monitors and the validity of brand inter-conversion were measured by <it>t</it>-tests, Pearson correlations, Bland-Altman plots, and coefficients of variation (CV).</p> <p>Results</p> <p>The AGR detected a significantly greater amount of daily PA (216.2 ± 106.2 vs. 188.0 ± 101.1 counts/min, P < 0.0001). The average difference between activity monitors expressed as a CV were 3.1 and 15.5% for log-transformed and raw data, respectively. When a conversion equation was applied to convert datasets from one brand to another, the differences were no longer significant, with CV's of 2.2 and 11.7%, log-transformed and raw data, respectively.</p> <p>Conclusion</p> <p>Although activity monitors predict PA on the same scale (counts/min), the results between these two brands are not directly comparable. However, the data are comparable if a conversion equation is applied, with better results for log-transformed data.</p

Understanding young adult physical activity, alcohol and tobacco use in community colleges and 4-year post-secondary institutions: A cross-sectional analysis of epidemiological surveillance data

<p>Abstract</p> <p>Background</p> <p>Young adults experience many adverse health behavior changes as they transition from adolescence into adulthood. A better understanding of the relationships between health promoting and risky health behaviors may aid in the development of health promotion interventions for various types of young adult post-secondary students. Therefore, the purpose of this study was to examine associations between alcohol and tobacco use and physical activity among 2-year and 4-year college students.</p> <p>Methods</p> <p>Cross-sectional analyses were conducted using 2007 survey data, collected as part of an on-going post-secondary health surveillance system in Minnesota. Students were randomly selected to participant from 14 Minnesota colleges and universities (six 2-year community and/or technical colleges, eight 4-year post-secondary institutions). The 2007 surveillance data included 9,931 respondents.</p> <p>Results</p> <p>The prevalence of demographic characteristics and health behaviors (e.g., physical activity, tobacco use) differed between young adults attending 2-year and 4-year post-secondary institutions; in general, those attending 2-year institutions are representative of more at-risk populations. Overall, higher levels of moderate, vigorous and strengthening physical activity were associated with higher levels of alcohol consumption and lower levels of smoking. In general, despite the disparities in the prevalence of these risk behaviors, the associations between the behaviors did not differ substantially between 2-year and 4-year post-secondary populations.</p> <p>Conclusions</p> <p>These findings illustrate links between leading risk behaviors. Interventions targeting multiple risk behaviors among young adults may warrant further consideration. Overall, future research is needed to support and inform young adult health promotion efforts that may be implemented in a wide array of post-secondary institutions.</p

Psychometric properties of two physical activity questionnaires, the AQuAA and the PASE, in cancer patients

Background: This study aimed to evaluate the reliability and validity of two self-report physical activity (PA) questionnaires - the AQuAA (Activity Questionnaire for Adults and Adolescents) and PASE (Physical Activity Scale for the Elderly) - in cancer patients. Methods: Test-retest reliability was determined by administering the questionnaires twice within 5 days. Intraclass correlation coefficient (ICC), standard error of measurement (SEM) and smallest detectable difference (SDD) were calculated. Construct validity was determined by comparing the questionnaire results with ActiGraph accelerometer scores using Spearman correlation coefficients (r(s)) and ICCs. Content validity was examined using the Three-Step Test-Interview (TSTI). Results: Reliability for the AQuAA scores were fair to excellent (ICC = 0.57 to 0.78). Reliability for the PASE scores ranged from good to excellent (ICC = 0.67 to 0.90). Correlations between the ActiGraph and the AQuAA and the PASE were low (r(s) = 0.05 and 0.16 respectively, and ICC = -0.001 to 0.44). The TSTI showed that participants experienced difficulties with the examples provided with the questions, the perceptions of intensity level of PA, and with recalling the time spent on PA. Conclusions: Both questionnaires showed good to excellent test-retest reliability for most scores. Construct validity of both questionnaires was low, as indicated by the low correlations with the ActiGraph. Except for a few difficulties that participants perceived when filling out the questionnaires, the content validity of both questionnaires was goo

Banks’ liquidity buffers and the role of liquidity regulation

We assess the determinants of banks’ liquidity holdings using data for nearly 7000 banks from 25 OECD countries. We highlight the role of several bank-specific, institutional and policy variables in shaping banks’ liquidity risk management. Our main question is whether liquidity regulation neutralizes banks’ incentives to hold liquid assets. Without liquidity regulation, the determinants of banks’ liquidity buffers are a combination of bank-specific and country-specific variables. While most incentives are neutralized by liquidity regulation, a bank’s disclosure requirements remain important. The complementarity of disclosure and liquidity requirements provides a strong rationale for considering them jointly in the design of regulation