A small area 8 bits 50 MHz CMOS DAC for Bluetooth transmitter

This paper presents a small-area CMOS current-steering segmented digital-to-analog converter (DAC) design intended for RF transmitters in 2.45 GHz Bluetooth applications. The current-source design strategy is based on an iterative scheme whose variables are adjusted in a simple way, minimizing the area and the power consumption, and meeting the design specifications. A theoretical analysis of static-dynamic requirements and a new layout strategy to attain a small-area current-steering DAC are included. The DAC was designed and implemented in 0.35 mu m CMOS technology, requiring an active area of just 200 mu m x 200 mu m. Experimental results, with a full-scale output current of 700 mu A and a 3.3 V power supply, showed a spurious-free dynamic range of 58 dB for a 1 MHz output sine wave and sampling frequency of 50 MHz, with differential and integral nonlinearity of 0.3 and 0.37 LSB, respectively.

Small area population disease burden

Small area health statistics has assumed increasing importance as the focus of population and public health moves to a more individualised approach of smaller area populations. Small populations and low event occurrence produce difficulties in interpretation and require appropriate statistical methods, including for age adjustment. There are also statistical questions related to multiple comparisons. Privacy and confidentiality issues include the possibility of revealing information on individuals or health care providers by fine cross-tabulations. Interpretation of small area population differences in health status requires consideration of migrant and Indigenous composition, socio-economic status and rural-urban geography before assessment of the effects of physical environmental exposure and services and interventions. Burden of disease studies produce a single measure for morbidity and mortality - disability adjusted life year (DALY) - which is the sum of the years of life lost (YLL) from premature mortality and the years lived with disability (YLD) for particular diseases (or all conditions). Calculation of YLD requires estimates of disease incidence (and complications) and duration, and weighting by severity. These procedures often mean problematic assumptions, as does future discounting and age weighting of both YLL and YLD. Evaluation of the Victorian small area population disease burden study presents important cross-disciplinary challenges as it relies heavily on synthetic approaches of demography and economics rather than on the empirical methods of epidemiology. Both empirical and synthetic methods are used to compute small area mortality and morbidity, disease burden, and then attribution to risk factors. Readers need to examine the methodology and assumptions carefully before accepting the results.

Briefing 15: Small area geography - MSOA vs Ward

In this briefing we compare and contrast different small areas, particularly in the context of their use for examining health inequalities.

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

Background 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. Methods It is a cross-sectional ecological design using mortality data (years 1996-2003). Units of analysis were the census tracts. A deprivation index was calculated for each census tract. In order to control the variability in estimating the risk of dying we used Bayesian models. We present the RR of the census tract with the highest deprivation vs. the census tract with the lowest deprivation. Results In the case of men, socioeconomic inequalities are observed in total cancer mortality in all cities, except in Castellon, Cordoba and Vigo, while Barcelona (RR = 1.53 95%CI 1.42-1.67), Madrid (RR = 1.57 95%CI 1.49-1.65) and Seville (RR = 1.53 95%CI 1.36-1.74) present the greatest inequalities. In general Barcelona and Madrid, present inequalities for most types of cancer. Among women for total cancer mortality, inequalities have only been found in Barcelona and Zaragoza. The excess number of cancer deaths due to socioeconomic deprivation was 16,413 for men and 1,142 for women. Conclusion This study has analysed inequalities in cancer mortality in small areas of cities in Spain, not only relating this mortality with socioeconomic deprivation, but also calculating the excess mortality which may be attributed to such deprivation. This knowledge is particularly useful to determine which geographical areas in each city need intersectorial policies in order to promote a healthy environment.

On the performance of small-area estimators: Fixed vs. random area parameters

Most methods for small-area estimation are based on composite estimators derived from design- or model-based methods. A composite estimator is a linear combination of a direct and an indirect estimator with weights that usually depend on unknown parameters which need to be estimated. Although model-based small-area estimators are usually based on random-effects models, the assumption of fixed effects is at face value more appropriate.Model-based estimators are justified by the assumption of random (interchangeable) area effects; in practice, however, areas are not interchangeable. In the present paper we empirically assess the quality of several small-area estimators in the setting in which the area effects are treated as fixed. We consider two settings: one that draws samples from a theoretical population, and another that draws samples from an empirical population of a labor force register maintained by the National Institute of Social Security (NISS) of Catalonia. We distinguish two types of composite estimators: a) those that use weights that involve area specific estimates of bias and variance; and, b) those that use weights that involve a common variance and a common squared bias estimate for all the areas. We assess their precision and discuss alternatives to optimizing composite estimation in applications.

Small-area estimation with spatial similarity

A class of composite estimators of small area quantities that exploit spatial (distancerelated)similarity is derived. It is based on a distribution-free model for the areas, but theestimators are aimed to have optimal design-based properties. Composition is applied alsoto estimate some of the global parameters on which the small area estimators depend.It is shown that the commonly adopted assumption of random effects is not necessaryfor exploiting the similarity of the districts (borrowing strength across the districts). Themethods are applied in the estimation of the mean household sizes and the proportions ofsingle-member households in the counties (comarcas) of Catalonia. The simplest version ofthe estimators is more efficient than the established alternatives, even though the extentof spatial similarity is quite modest.

Improving small area estimation by combining surveys: new perspectives in regional statistics

A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour Force Survey (EPA) and the Barometer in Spain for our study.

An empirical evaluation of small area estimators

This paper investigates the comparative performance of five small areaestimators. We use Monte Carlo simulation in the context of boththeoretical and empirical populations. In addition to the direct andindirect estimators, we consider the optimal composite estimator withpopulation weights, and two composite estimators with estimatedweights: one that assumes homogeneity of within area variance andsquare bias, and another one that uses area specific estimates ofvariance and square bias. It is found that among the feasibleestimators, the best choice is the one that uses area specificestimates of variance and square bias.

Life-course socioeconomic environment and health risk behaviours: a multilevel small-area analysis of young-old persons in an urban neighbourhood in Lausanne, Switzerland

With a life expectancy at the age of 65 of around 20 years, damaging health risk behaviours of young-old adults have become a target for preventive actions. Such risk factors necessitate an accurate understanding of the present and past socioeconomic conditions associated with health risk behaviours. The aim of our study is to assess the impact of certain life events as well as economic and environmental factors on health risk behaviours. We included 1309 participants of the Lausanne Cohort Lc65+ aged 65-70 years and employed logistic regression analyses, with individuals nested within areas. The results illustrate the influences of socioeconomic factors from childhood to young-old age. Life experiences in adulthood and economic resources in young-old age are both associated with unfavourable health behaviours. Neighbourhood is a modest determinant as well, particularly regarding alcohol consumption. Therefore, prevention against health risk behaviours should focus on population subgroups defined on the basis of their socioeconomic and living contexts.

A propos des "small area variations": opérations pour fracture de hanche dans le canton de Vaud. [Small area variations: surgery for hip fractures in the canton of Vaud].

OBJECTIVES: Studies of small area variations of health care utilization are more and more frequent. Such variations are often considered to be an indication of variations in the quality of medical care. The variations in the rate of operations for hip fractures are among the lowest studied to date, due to the fact that a consensus exists concerning this surgery. Our objective is to examine these variations within the context of relatively small and heterogeneous districts. METHOD: Based on anonymous computerized data on public hospital stays, this study describes the variations in population rates (crude and standardized) of operations for hip fracture among the health districts of the Canton of Vaud for the period from 1986 to 1991. District populations vary from 22,000 to 164,000. Using the extremal quotient (EQ), the importance of these variations was determined. RESULTS: The study population consists of 2363 cases, of which 78% are women. Mean age is 80.4 for women and 70.6 for men. Standardized rates of operation for hip fracture per 100,000 in the Canton Vaud for the years 1986 to 1991 are, respectively: 56; 67; 86; 91; 89 and 94. The EQ for the years 1986 to 1991 are respectively: 8.2; 4.0; 3.5; 2.7; 1.9 and 1.9. The high EQ, especially for the earlier years, are contrary to the initial premise of absence of variation. The progressive implementation in the Canton Vaud of VESKA medical statistics could play a role, as could the small size of many of the districts, with resultant instability of rates. CONCLUSIONS: Considering the wide variations shown here for an operation hardly regarded as subject to variations, it is important to exercise caution in interpreting published data of small area variations.

Empirical errors of small area estimates from the multisource National Forest Inventory in Eastern Finland

Abstract

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

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

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.