Operationalizing environmental indicators for physical activity in older adults

This qualitative study describes environmental supports and barriers to physical activity in an older adult sample drawn from low- and high-walkable neighborhoods. Thirty-seven individuals age 55 and over were recruited and answered open-ended survey questions, with a subsample invited back to partake in a semistructured interview. Content analysis identified categories and themes linking perceptions of neighborhood-environment characteristics to activity. Emerging categories and themes did not differ across neighborhood walkability, so results are presented for both groups combined. Infrastructure was the most common category identified to encourage activity, specifically, well-maintained sidewalks, bike paths or lanes, and traffic control. Other categories of land use, landscape, and aesthetics were reported. Poorly maintained or missing sidewalks, crosswalks, bike paths or lanes, and traffic safety were categories that discouraged activity. In conclusion, the information obtained is helpful in solidifying which environmental characteristics are important to measure as they relate to activity behavior in an older adult population.     

Complexities in attracting and retaining direct support professionals

Recruiting and retaining direct support professionals (DSPs) remains essential to the full inclusion for persons with disabilities. Using a mixed-evaluation model, we measured DSPs' views versus those of their supervisors. DSPs expressed lower perceptions concerning their supervisors, satisfaction with their work situation, and environmental and safety factors. Focus groups provided insights into resolving issues related to compensation, work environment, and recruiting and retaining future DSPs. Motivating factors included wanting to be part of a helping community where all are valued. To improve their performance, DSPs stated their desire to understand the roles of managers and of the consumer. DSPs indicated that having career paths that provided advancement opportunities and direct contact with persons with disabilities were primary motivators.     

Multivariate process dispersion monitoring without subgrouping

The memory-type adaptive and non-adaptive control charts are among the best control charts for detecting small-to-moderate changes in the process parameter(s). In this paper, we propose the Crosier CUSUM (CCUSUM), EWMA, adaptive CCUSUM (ACCUSUM) and adaptive EWMA (AEWMA) charts for efficiently monitoring the changes in the covariance matrix of a multivariate normal process without subgrouping. Using extensive Monte Carlo simulations, the length characteristics of these control charts are computed. It turns out that the ACCUSUM and AEWMA charts perform uniformly and substantially better than the CCUSUM and EWMA charts when detecting a range of shift sizes in the covariance matrix. Moreover, the AEWMA chart outperforms the ACCUSUM chart. A real dataset is used to explain the implementation of the proposed control charts.     

Factors associated with 'feeling suicidal': the role of sexual identity

This paper examines factors associated with feeling suicidal in a large sample of urban men in Sydney and Melbourne, aged 18-50, including heterosexual, gay and bisexual men, HIV antibody positive and HIV antibody negative. As in previous research, sexuality (being homosexual or bisexual) was found to be a major predictor of suicidality. The research went some way towards explaining the close relationship between feeling suicidal and sexual orientation. Sexuality interacts with feeling bad in that, once men feel moderately bad/depressed, they are more likely to feel suicidal if they are homosexual or bisexual than if they are heterosexual. In addition, the research found that experience of verbal abuse and physical assault (harassment) increased feeling suicidal for both heterosexual and gay/bisexual men, not just for homosexual men as suggested by previous research, and that social isolation in the form of living alone is a further risk factor. Seeking counseling help and taking sexual risks were also independently associated with feeling suicidal. These actions may result from feeling suicidal rather than the reverse, and their association with feeling suicidal warrants further research. Many of the 46 independent variables examined in the research, including HIV antibody status and closeness to the HIV/ AIDS epidemic, were related to feeling suicidal only through their association with being gay/bisexual. Celibacy and general risk taking were not related to feeling suicidal in this study.     

Urinary Excretion of Chromium Following Ingestion of Chromite-Ore Processing Residues in Humans: Implications for Biomonitoring

Biomonitoring programs for urinary chromium (Cr) typically attempt to evaluate occupational exposure via the inhalation route. This study investigated whether Cr can be detected in the urine of people following the ingestion of soils that contain relatively high concentrations of chromium in chromite ore processing residue (COPR). To evaluate the reasonableness of using urinary monitoring to assess environmental exposure, six volunteers ingested 400 mg of soil/day (low-dose group), two others ingested 2.0 g of soil/day (high-dose group) for 3 consecutive days, and one person ingested a placebo on each of 3 days. The soil and COPR mixture contained concentrations of total chromium (Cr) and hexavalent chromium [Cr(VI)] of 103 ± 20 and 9.3 ± 3.8 mg/kg, respectively. Therefore, the low-dose group ingested 41 μg Cr/day [including 3.7 μg Cr(VI)] and the high-dose group ingested 206 μg Cr/day [including 18.6 μg Cr(VI)] on each of 3 consecutive days. All urine samples were collected and analyzed individually for total Cr on the day prior to dosing, during the 3 days of dosing, and up to the first void 48 h after the last dose. No significant increases in urinary Cr excretion were found when background excretion data were compared with data following each of the 3 days of dosing or in daily mean urine concentrations of the high- vs the low-dose groups. It appears that Cr present in a soil and COPR mixture at Cr doses up to 200 μg/day is not sufficiently bioavailable for biomonitoring of urine to be informative. These results are consistent with previously published findings suggesting that incidental exposure to dusts and soils containing comparable levels of Cr will not result in increased concentrations of Cr in urine.     

Two-Group Classification Using Neural Networks*

Artificial neural networks are new methods for classification. We investigate two important issues in building neural network models; network architecture and size of training samples. Experiments were designed and carried out on two-group classification problems to find answers to these model building questions. The first experiment deals with selection of architecture and sample size for different classification problems. Results show that choice of architecture and choice of sample size depend on the objective: to maximize the classification rate of training samples, or to maximize the generalizability of neural networks. The second experiment compares neural network models with classical models such as linear discriminant analysis and quadratic discriminant analysis, and nonparametric methods such as k-nearest-neighbor and linear programming. Results show that neural networks are comparable to, if not better than, these other methods in terms of classification rates in the training samples but not in the test samples.     

What’s in a yardscape? A case study of emergent ecosystem services and disservices within resident yardscape discourses in Minnesota

Urban Ecosystems - Residential yardscapes are at the forefront of human interaction with nature for those living in urban areas across Europe and North America. In recent years a significant amount...     

Palm snags are a critical nesting resource for woodpeckers in an urbanized tropical region

Urban Ecosystems - Critical resources for birds nesting in cities can support populations in spite of the challenges imposed by urbanization, and the identification of such resources can shed light...     

Model-based clustering with sparse covariance matrices

Statistics and Computing - Finite Gaussian mixture models are widely used for model-based clustering of continuous data. Nevertheless, since the number of model parameters scales quadratically with...