Residential segregation and health in Northern Ireland

Patterns of residential segregation in Northern Ireland reflect historic sectarian conflict as well as current animosities. A number of indices of segregation are examined in this paper and their relative merits in capturing localised societal divisions are discussed.The implications of such divisions on health as mediated through conflict-related stress are then considered. Costed datasets of hospital, community and anxiety/depression prescribing data havebeen assembled and attributed to local geographies.The association between geographical variations in these costs and levels of segregation was modelled using regression analysis.It was found that the level of segregation does not help to explain variations in costed utilisation of acute and elderly services but does explain variations in the costs of prescribing for anxiety and depression with controls for socio-economic deprivation included. Results in this paper would indicate that strategies to promote good relations in Northern Ireland have positive implications for mental health.

Why is housing tenure associated with a lower risk of admission to a nursing or residential home? Wealth, health and the incentive to keep 'my home'

Background Previous research has shown that home ownership is associated with a reduced risk of admission to institutional care. The extent to which this reflects associations between wealth and health, between wealth and ability to buy in care or increased motivation to avoid admission related to policies on charging is unclear. Taking account of the value of the home, as well as housing tenure, may provide some clarification as to the relative importance of these factors.
Aims To analyse the probability of admission to residential and nursing home care according to housing tenure and house value.
Methods Cox regression was used to examine the association between home ownership, house value and risk of care home admissions over 6 years of follow-up among a cohort of 51 619 people aged 65 years or older drawn from the Northern Ireland Longitudinal Study, a representative sample of approximate to 28% of the population of Northern Ireland.
Results 4% of the cohort (2138) was admitted during follow-up. Homeowners were less likely than those who rented to be admitted to care homes (HR 0.77, 95% CI 0.70 to 0.85, after adjusting for age, sex, health, living arrangement and urban/rural differences). There was a strong association between house value/tenure and health with those in the highest valued houses having the lowest odds of less than good health or limiting long-term illness. However, there was no difference in probability of admission according to house value; HRs of 0.78 (95% CI 0.67 to 0.90) and 0.81 (95% CI 0.70 to 0.95), respectively, for the lowest and highest value houses compared with renters.
Conclusions The requirement for people in the UK with capital resources to contribute to their care is a significant disincentive to institutional admission. This may place an additional burden on carers.

Residential consumption of gas and electricity in the U.S.: The role of prices and income

We study the residential demand for electricity and gas, working with nationwide household-level data that cover recent years, namely 1997-2007. Our dataset is a mixed panel/multi-year cross-sections of dwellings/households in the 50 largest metropolitan areas in the United States as of 2008. We estimate static and dynamic models of electricity and gas demand. We find strong household response to energy prices, both in the short and long term. From the static models, we get estimates of the own price elasticity of electricity demand in the -0.860 to -0.667 range, while the own price elasticity of gas demand is -0.693 to -0.566. These results are robust to a variety of checks. Contrary to earlier literature (Metcalf and Hassett, 1999; Reiss and White, 2005), we find no evidence of significantly different elasticities across households with electric and gas heat. The price elasticity of electricity demand declines with income, but the magnitude of this effect is small. These results are in sharp contrast to much of the literature on residential energy consumption in the United States, and with the figures used in current government agency practice. Our results suggest that there might be greater potential for policies which affect energy price than may have been previously appreciated. (C) 2011 Elsevier B.V. All rights reserved.

Response of residential electricity demand to price: The effect of measurement error

In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured.

Antimicrobial prescribing in residential homes.

Objectives: Research in residential homes has been limited to date and the extent of systemic and topical antimicrobial prescribing is largely unknown. The aim of this study was to investigate antimicrobial prescribing in residential homes in Northern Ireland (NI).

Methods: Point prevalence studies (PPSs) were completed in November 2010 (PPS1) and April 2011 (PPS2) in 30 residential homes. Data were obtained from care plans, medication administration records and staff in relation to antimicrobial prescribing and facility and resident characteristics, and analysed descriptively.

Results: The point prevalence of systemic antimicrobial prescribing was 9.4% in PPS1 and 9.2% in PPS2 (range 0.0%–33.3% during both PPSs). Trimethoprim was the most commonly prescribed systemic antimicrobial and the main indication was the prevention of urinary tract infections. Almost 25% of systemic antimicrobials were prescribed at inappropriate doses. The point prevalence of topical antimicrobial prescribing was 6.4% (range 0.0%–22.2%) in PPS1 and 5.9% (range 0.0%–21.1%) in PPS2. The most commonly prescribed topical antimicrobials were chloramphenicol eye preparations in PPS1 and fusidic acid skin preparations in PPS2; treatment with these topical antimicrobials was generally prolonged. More than 25% of all systemic and 55% of all topical antimicrobials were initiated following telephone consultations as opposed to face-to-face consultations.

Conclusions: The prevalence of systemic antimicrobial prescribing in residential homes in NI is relatively high compared with care homes (particularly nursing homes) in other countries. Systemic and topical antimicrobial prescribing is not always appropriate in terms of the doses prescribed and the duration of use. It is apparent that current strategies employed in NI are insuf?cient to ensure prudent antimicrobial prescribing within this environment.

Smart meter devices and the effect of feedback on residential electricity consumption: Evidence from a natural experiment in Northern Ireland

Using a unique set of data and exploiting a large-scale natural experiment, we estimate the effect of real-time usage information on residential electricity consumption in Northern Ireland. Starting in April 2002, the utility replaced prepayment meters with advanced meters that allow the consumer to track usage in real-time. We rely on this event, account for the endogeneity of price and payment plan with consumption through a plan selection correction term, and find that the provision of information is associated with a decline in electricity consumption of 11-17%. We find that the reduction is robust to different specifications, selection-bias correction methods and subsamples of the original data. The advanced metering program delivers reasonably cost-effective reductions in carbon dioxide emissions, even under the most conservative usage reduction scenarios.

Introducing Automated Management Through Iteratively Increased Automation and Indicators

Introducing automation into a managed environment includes significant initial overhead and abstraction, creating a disconnect between the administrator and the system. In order to facilitate the transition to automated management, this paper proposes an approach whereby automation increases gradually, gathering data from the task deployment process. This stored data is analysed to determine the task outcome status and can then be used for comparison against future deployments of the same task and alerting the administrator to deviations from the expected outcome. Using a machinelearning
approach, the automation tool can learn from the administrator's reaction to task failures and eventually react to faults autonomously.