Environmental oestrogens and breast cancer: evidence for combined involvement of dietary, household and cosmetic xenoestrogens

Many environmental compounds with oestrogenic activity are measurable in the human breast and oestrogen is a known factor in breast cancer development. Exposure to environmental oestrogens occurs through diet, household products and cosmetics, but concentrations of single compounds in breast tissue are generally lower than needed for assayable oestrogenic responses. Results presented here and elsewhere demonstrate that in combination, chemicals can give oestrogenic responses at lower concentrations, which suggests that in the breast, low doses of many compounds could sum to give a significant oestrogenic stimulus. Updated incidence figures show a continued disproportionate incidence of breast cancer in Britain in the upper outer quadrant of the breast which is also the region to which multiple cosmetic chemicals are applied. CONCLUSION: If exposure to complex mixtures of oestrogenic chemicals in consumer products is a factor in breast cancer development, then a strategy for breast cancer prevention could become possible.

Household attributes and the future demand for retirement housing

Ageing populations provoke the question of how much bespoke housing should be provided for the elderly. Older people are generally reluctant to move but as they age health circumstances may encourage moves into specialised accommodation. This paper reports an exercise in estimating the future demand for specialised independent living housing and the extent to which that demand will be for owner occupied accommodation or renting, using data for England. The approach is based on a behavioral model related to health and housing issues. The forecasts indicate a substantial increase in demand, growing at a faster rate than the population as a whole. If supply does not rise to meet these demands, serious problems arise in the quality of life of, and cost of caring for, older people; with implications for health care and social services.

A spatial–temporal analysis of the impact of access restrictions on forest landscapes and household welfare in Tanzania

This paper explores the impact of the re-introduction of access restrictions to forests in Tanzania, through participatory forest management (PFM), that have excluded villagers from forests to which they have traditionally, albeit illegally, had access to collect non-timber forest products (NTFPs). Motivated by our fieldwork, and using a spatial–temporal model, we focus on the paths of forest degradation and regeneration and villagers' utility before and after an access restriction is introduced. Our paper illustrates a number of key points for policy makers. First, the benefits of forest conservation tend to be greatest in the first few periods after an access restriction is introduced, after which the overall forest quality often declines. Second, villagers may displace their NTFP collection into more distant forests that may have been completely protected by distance alone before access to a closer forest was restricted. Third, permitting villagers to collect limited amounts of NTFPs for a fee, or alternatively fining villagers caught collecting illegally from the protected forest, and returning the fee or fine revenue to the villagers, can improve both forest quality and villagers' livelihoods.

Rental depreciation and capital expenditure in the UK commercial real estate market, 1993–2009

This paper identifies the long-term rental depreciation rates for UK commercial properties and rates of capital expenditure incurred to offset depreciation over the same period. It starts by reviewing the economic depreciation literature and the rationale for adopting a longitudinal method of measurement, before discussing the data used and results. Data from 1993 to 2009 were sourced from Investment Property Databank and CB Richard Ellis real estate consultants. This is used to compare the change in values of new buildings in different locations with the change in values of individual properties in those locations. The analysis is conducted using observations on 742 assets drawn from all major segments of the commercial real estate market. Overall rental depreciation and capital expenditure rates are similar to those in other recent UK studies. Depreciation rates are 0.8% pa for offices, 0.5% pa for industrial properties and 0.3% pa for standard retail properties. These results hide interesting variations at a segment level, notably in retail where location often dominates value rather than the building. The majority of properties had little (if any) money spent on them over the last 16 years, but those subject to higher rates of expenditure were found to have lower depreciation rates.

Graph-based algorithms for comparison and prediction of household-level energy use profiles

We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

A new error measure for forecasts of household-level, high resolution electrical energy consumption

As low carbon technologies become more pervasive, distribution network operators are looking to support the expected changes in the demands on the low voltage networks through the smarter control of storage devices. Accurate forecasts of demand at the single household-level, or of small aggregations of households, can improve the peak demand reduction brought about through such devices by helping to plan the appropriate charging and discharging cycles. However, before such methods can be developed, validation measures are required which can assess the accuracy and usefulness of forecasts of volatile and noisy household-level demand. In this paper we introduce a new forecast verification error measure that reduces the so called “double penalty” effect, incurred by forecasts whose features are displaced in space or time, compared to traditional point-wise metrics, such as Mean Absolute Error and p-norms in general. The measure that we propose is based on finding a restricted permutation of the original forecast that minimises the point wise error, according to a given metric. We illustrate the advantages of our error measure using half-hourly domestic household electrical energy usage data recorded by smart meters and discuss the effect of the permutation restriction.