679 research outputs found
Trends and socioeconomic inequalities in cancer survival in England and Wales up to 2001.
We examined national trends and socioeconomic inequalities in cancer survival in England and Wales during the 1990s, using population-based data on 2.2 million patients who were diagnosed with one of the 20 most common cancers between 1986 and 1999 and followed up to 2001. Patients were assigned to one of five deprivation categories (from 'affluent' to 'deprived') using characteristics of their electoral ward of residence at diagnosis. We estimated relative survival up to 5 years after diagnosis, adjusting separately in each deprivation category for background mortality by age, sex and calendar period. We estimated trends in survival and in the difference in survival between deprivation categories ('deprivation gap') over the periods 1986-90, 1991-95 and 1996-99. We used period analysis to examine likely survival rates in the near future. Survival improved for most cancers in both sexes during the 1990s, and appears likely to continue improving for most cancers in the near future. The deprivation gap in survival between rich and poor was wider for patients diagnosed in the late 1990s than in the late 1980s. Increases in cancer survival in England and Wales during the 1990s are shown to be significantly associated with a widening deprivation gap in survival
Correlation of Eastern Wild Turkey Poult:hen Ratios with Population Indices to Detect Reproductive Density Dependence
Knowledge of how density affects population growth is important for the harvest management of wild turkey. Unfortunately, available time-series are often too short for statistical detection of density dependence. The correlation between wild turkey recruitment and population size was assessed using data from 7 state wildlife agencies, circumventing the problem of short time-series by using multiple datasets. Correlation coefficients were calculated between surveyed poult:hen ratios and harvest-based population indices for 31 geographic or harvest management regions. Estimated correlation coefficients were tested for homogeneity to determine if an average correlation could be calculated. Correlation coefficients for the 29 regions ranged from -0.82 to 0.70. A Q-test for homogeneity indicated that correlation coefficients were similar enough to warrant averaging [Q=25.45, df = 28, P = 0.603]. The weighted average correlation coefficient (± standard error) was r = -0.30 ± 0.45. Population size accounted for little of the variation associated with production (r = 0.09). Graphical analysis indicated that a negative correlation between poult:hen ratios and population size tended to occur when the range of population sizes was large. Density dependence appears to have little effect on production. Density-independent models should have better success modeling wild turkey production, while density-dependent effects may have stronger influence on survival or immigration at low population sizes
Friendship activities of adults with intellectual disability in supported accommodation in northern England
Background Despite there being considerable evidence to suggest that friendships are central to health and well-being, relatively little attention had been paid to the friendships of people with intellectual disabilities. Methods Friendship activities involving people with and without intellectual disabilities were measured over the preceding month in a sample of 1542 adults with intellectual disabilities receiving supported accommodation in nine geographical localities in Northern England. Results The results of the study indicate: (1) low levels of friendship activities among people with intellectual disabilities in supported accommodation; (2) people with intellectual disabilities are more likely to be involved in activities with friends who also have intel lectual disabilities than with friends who do not have intellectual disabilities; (3) most friendship activities take place in the public domain rather than in more private settings (e.g. at home); (4) the setting in which a person lives is a more significant determinant of the form and content of activities with their friends than the characteristics of participants. Conclusions Further attention needs to be given to research and practice initiatives aimed at increasing the levels of friendship activities of people with intellectual disabilities
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Near-conformal window assembly for airborne payloads: improved time on-station and optical performance
Conventional windows for airborne payloads are often discontinuous with the aircraft or pod skin. A protruding structure or hollow cavity increases aerodynamic drag, which consumes more fuel and thus reduces the amount of time available on-station. These geometries give rise to turbulent aero-optical effects, which can reduce the payload's optical performance because it has to see through turbulence. This paper describes a multi-paned or segmented window concept that matches the local topology of the aircraft pod or skin. This approach is suitable for optical payloads having multiple fixed fields-of-view such as staring infrared search and track systems, but not scanning systems. This approach for creating a near-conformal window assembly should be particularly useful for rapid prototyping of windows for airborne optical payloads, providing a nearer-term alternative to monolithic windows that are ground and polished into complex shapes. In this paper, a 14-inch diameter pod faring with three window segments was chosen as a point design for a notional airborne optical payload. Fused silica planar windowpanes were fabricated with matching, mating mitered edges. The panes were chemically bonded directly to each other with a sodium-silicate solution. The bonding process and fixturing are described. The resulting glass bond is strong and minimizes the non-useable seam between panes. This approach increases the clear aperture of each pane compared with windowpanes bonded into individual mechanical bezels. Interferometric measurements of the prototype show no degradation in transmitted wavefront error after silicate bonding.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Clinical Reasoning and Case-Based Decision Making: The Fundamental Challenge to Veterinary Educators
Modelling survival : exposure pattern, species sensitivity and uncertainty
The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans
Smoking and Lung Cancer: Some Observations on Two Recent Reports,
EXPRESSING THE TREATMENT EFFECT of local recurrence of malignancy after the surgery. Patients were divided into two groups, depending upon the stage of the disease prior to surgery. Since both the risk and outcome variables are categorical, three measures of treatment effect-difference in recurrence rates, relative risk, and odds ratio-may be computed for each stage (see the calculations in Since the logarithm of the relative risk is equal to the difference of the log rates (log 19 = log r l -log r2), this is an example where an analysis in the original units (recurrence rates) show an interaction, whereas an analysis in a different scale (log -recurrence rates) does not. Often, however, interactions cannot be removed by changing the scale. If in the previous example, stage 1 patients had fewer recurrences with tylectomy than with mastectomy but the opposite had been true for stage 2 patients, there would be no way of avoiding interaction. Although it is desirable to avoid interaction since a single measure can then completely describe the treatment effect, sometimes, as we discussed in Section 3.1, because one measure of treatment effect is more useful than others, t p measure should be used even if it does result in interaction. Estimating a treatment effect requires the construction of a standard of comparison. As we have seen in Chapter 1, this involves a comparison group which does not receive the treatment of interest. In this chapter we will explore several ways of establishing such a comparison group, emphasizing the difference between randomization and other methods. It will be seen that a randomized allocation of subjects to a treatment and control group generally ensures that the latter is an adequate standard of comparison for the former. We will start by defining randomization and discussing the properties that make this method particularly attractive. We will then give reasons for doing nonrandomized studies, and distinguish the different types of studies involving a comparison group. For simplicity of presentation, this chapter will be confined mainly to studies with a dichotomous risk factor. 31 REFERENCE
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