Diode laser pumped, KERR phase-shifting and switching of a diode laser signal in a small area optical fibre

In this paper authors report the first demonstration of a diode laser powered Kerr effect device, consisting of a single birefringent fiber, able to phase-shift and switch an optical signal generated by a second laser diode. They have obtained fast, stable phase-shifting of 90° in a single fiber, at a coupled pump power of only 20 mW. Using this phase shift to induce polarization switching with resultant gating, 25% modulation of the diode laser signal has been observed, with a detection limited-rise time of 10ns.

Higher incidence of childhood-onset type 1 diabetes mellitus in remote areas: a UK regional small-area analysis

Aims/hypothesis: We investigated the association between the incidence of type 1 diabetes mellitus and remoteness (a proxy measure for exposure to infections) using recently developed techniques for statistical analysis of small-area data.

Subjects, materials and methods: New cases in children aged 0 to 14 years in Northern Ireland were prospectively registered from 1989 to 2003. Ecological analysis was conducted using small geographical units (582 electoral wards) and area characteristics including remoteness, deprivation and child population density. Analysis was conducted using Poisson regression models and Bayesian
hierarchical models to allow for spatially correlated risks that were potentially caused by unmeasured explanatory variables.

Results: In Northern Ireland between 1989 and 2003, there were 1,433 new cases of type 1 diabetes, giving a directly standardised incidence rate of 24.7 per 100,000 personyears. Areas in the most remote fifth of all areas had a significantly (p=0.0006) higher incidence of type 1 diabetes mellitus (incidence rate ratio=1.27 [95% CI 1.07, 1.50]) than those in the most accessible fifth of all areas. There was also a higher incidence rate in areas that were less deprived (p<0.0001) and less densely populated (p=0.002). After adjustment for deprivation and additional adjustment for child population density the association between diabetes and remoteness remained significant (p=0.01 and p=0.03, respectively).

Conclusions/interpretation: In Northern Ireland, there is evidence that remote areas experience higher rates of type 1 diabetes mellitus. This could reflect a reduced or delayed exposure to infections, particularly early in life, in these areas.

Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.

Small area estimation using linear mixed models with heterogeneous covariance structures of random effects

The problem of Small Area Estimation is about how to produce reliable estimates of domain characteristics when the sample sizes within the domain is very small ou even zero.

Small Area Estimation of the Mean Price of the Habitation Transaction in Portugal: Methodological and Practical Issues

The Portuguese National Statistical Institute intends to produce estimations for the mean price of the habitation transation.

Small area estimation for the price of habitation transaction: comparison of different uncertainty measures of temporal EBLUP

Local level planning requires statistics for small areas, but normally due to cost or logistic constraints, sample surveys are often planned to provide reliable estimates only for large geographical regions and large subgroups of a population.

Small-area variation in health care affecting the choice of cesarean delivery: the case of a Colombian health insurer

In the midst of health care reform, Colombia has succeeded in increasing health insurance coverage and the quality of health care. In spite of this, efficiency continues to be a matter of concern, and small-area variations in health care are one of the plausible causes of such inefficiencies. In order to understand this issue, we use individual data of all births from a Contributory-Regimen insurer in Colombia. We perform two different specifications of a multilevel logistic regression model. Our results reveal that hospitals account for 20% of variation on the probability of performing cesarean sections. Geographic area only explains 1/3 of the variance attributable to the hospital. Furthermore, some variables from both demand and supply sides are found to be also relevant on the probability of undergoing cesarean sections. This paper contributes to previous research by using a hierarchical model and by defining hospitals as cluster. Moreover, we also include clinical and supply induced demand variables.

Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities

Intra-urban inequalities in mortality have been infrequently analysed in European contexts. The aim of the present study was to analyse patterns of cancer mortality and their relationship with socioeconomic deprivation in small areas in 11 Spanish cities

Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities [correcció]

After publication of this work in 'International Journal of Health Geographics' on 13 january 2011 was wrong. The map of Barcelona in Figure two (figure 1 here) was reversed. The final correct Figure is presented here

Distribution of physical activity facilities in Scotland by small area measures of deprivation and urbanicity

Background The aim of this study was to examine the distribution of physical activity facilities by area-level deprivation in Scotland, adjusting for differences in urbanicity, and exploring differences between and within the four largest Scottish cities. Methods We obtained a list of all recreational physical activity facilities in Scotland. These were mapped and assigned to datazones. Poisson and negative binomial regression models were used to investigate associations between the number of physical activity facilities relative to population size and quintile of area-level deprivation. Results The results showed that prior to adjustment for urbanicity, the density of all facilities lessened with increasing deprivation from quintiles 2 to 5. After adjustment for urbanicity and local authority, the effect of deprivation remained significant but the pattern altered, with datazones in quintile 3 having the highest estimated mean density of facilities. Within-city associations were identified between the number of physical activity facilities and area-level deprivation in Aberdeen and Dundee, but not in Edinburgh or Glasgow. Conclusions In conclusion, area-level deprivation appears to have a significant association with the density of physical activity facilities and although overall no clear pattern was observed, affluent areas had fewer publicly owned facilities than more deprived areas but a greater number of privately owned facilities.