Nutritional perspectives of children with Crohn's disease: a single-centre cohort observation of disease activity, energy expenditure and dietary intake.

BACKGROUND/OBJECTIVES: Children with Crohn's disease often demonstrate nutritional recovery during primary therapy at diagnosis, but long-term nutritional support is sometimes necessary. Evidence to inform best nutritional practice including energy and micronutrient requirements is limited. The principal objective of this study was to determine how energy expenditure and physical activity vary with disease activity over the first year following diagnosis. SUBJECTS/METHODS: Twenty children were studied at diagnosis with Crohn's disease and were followed up over 1 year while receiving treatment according to national guidelines. The majority of children (13) were treated with exclusive enteral nutrition. At study visits, height, weight, bioelectrical impedance, resting energy expenditure by indirect calorimetry, tri-axial accelerometer and blood investigations were performed alongside clinical assessment. RESULTS: There was no significant effect of disease activity on resting energy expenditure (REE). Physical activity was greater after primary therapy (Z=3.31, P<0.01). Median wPCDAI fell from 58 at diagnosis to 7.5 after primary therapy and was 7.5 at 1 year. Weight s.d.s increased from -1.67 to -0.86 and lean index s.d.s increased from -2.93 to -1.64, although the increase was mostly in the first 2 months. Median height s.d.s was unchanged throughout this study. There was a significant association between dietary intake and weight gain (r=0.8 P<0.01) but not height gain. Persistent micronutrient deficits beyond diagnosis were seen for both iron and vitamin D. CONCLUSIONS: This study has demonstrated that REE does not change significantly through different phases of disease activity, but physical activity is low at diagnosis. Children with Crohn's disease should be screened for deficiencies of iron and vitamin D.

Spatially weighted functional clustering of river network data.

Incorporating spatial covariance into clustering has previously been considered for functional data to identify groups of functions which are similar across space. However, in the majority of situations that have been considered until now the most appropriate metric has been Euclidean distance. Directed networks present additional challenges in terms of estimating spatial covariance due to their complex structure. Although suitable river network covariance models have been proposed for use with stream distance, where distance is computed along the stream network, these models have not been extended for contexts where the data are functional, as is often the case with environmental data. The paper develops a method of calculating spatial covariance between functions from sites along a river network and applies the measure as a weight within functional hierarchical clustering. Levels of nitrate pollution on the River Tweed in Scotland are considered with the aim of identifying groups of monitoring stations which display similar spatiotemporal characteristics.

Spatiotemporal statistical modelling of long-term change in river nutrient concentrations in England & Wales.

Concentrations of nutrient nitrogen (N) and phosphorus (P) are elevated in rivers across large areas of Europe (European Nitrogen Assessment (ENA), Sutton et al., 2011). Environmental policies have been implemented over the past 20 years with the aim of reducing nitrogen inputs to surface waters. However, environmental and ecological status is still below set targets (ENA, Sutton et al., 2011). Identification of patterns in long-term change for nutrient trends in hydrological catchments in England & Wales is required to assess impacts of nutrient management policy and provide better evidence for future policy. Such information could provide essential evidence for supporting policy by combining information from the wider catchment, rather than relying on the analysis of data from individual sites. Surface water quality is subject to considerable spatial and short-period temporal variability, reflecting variability in loading and dilution. This makes it difficult to determine temporal trends at individual monitoring sites with relatively sparse sampling. Here we apply spatiotemporal statistical additive models for both nitrogen and phosphorus in river networks across England & Wales to investigate the overall pattern of nutrient concentrations in these river surface waters over the past 20-40 years. Concentrations of Orthophosphate (OP) have generally decreased over time for many of the Large Hydrological Areas with a seasonal pattern highlighting one peak in the summer months. Over the past ten years, Total Oxidised Nitrogen (Nitrate+Nitrite, TON) concentrations have generally been slowly decreasing or fairly constant. However, prior to 2000, concentrations were generally on an upward trend. The seasonal pattern highlights one trough in the summer months. The highest levels for OP and TON broadly occur in the same general areas across England & Wales. On average, over time, the lowest values are evident in the north-west and south-west (particularly for OP) and highest values are evident in the Midlands, Anglian and Southern regions.

Extreme value theory applied to the definition of bathing water quality discounting limits.

The European Community Bathing Water Directive (European Parliament, 2006) set compliance standards for bathing waters across Europe, with minimum standards for microbiological indicators to be attained at all locations by 2015. The Directive allows up to 15% of samples affected by short-term pollution episodes to be disregarded from the figures used to classify bathing waters, provided certain management criteria have been met, including informing the public of short-term water pollution episodes. Therefore, a scientifically justifiable discounting limit is required which could be used as a management tool to determine the samples that should be removed. This paper investigates different methods of obtaining discounting limits, focusing in particular on extreme value methodology applied to data from Scottish bathing waters. Return level based limits derived from threshold models applied at a site-specific level improved the percentage of sites which met at least the minimum required standard. This approach provides a method of obtaining limits which identify the samples that should be removed from compliance calculations, although care has to be taken in terms of the quantity of data which is removed.