Does the choice of neighbourhood supermarket access measure influence associations with individual-level fruit and vegetable consumption? A case study from Glasgow

Background
Previous studies have provided mixed evidence with regards to associations between food store access and dietary outcomes. This study examines the most commonly applied measures of locational access to assess whether associations between supermarket access and fruit and vegetable consumption are affected by the choice of access measure and scale.

Method
Supermarket location data from Glasgow, UK (n = 119), and fruit and vegetable intake data from the 'Health and Well-Being' Survey (n = 1041) were used to compare various measures of locational access. These exposure variables included proximity estimates (with different points-of-origin used to vary levels of aggregation) and density measures using three approaches (Euclidean and road network buffers and Kernel density estimation) at distances ranging from 0.4 km to 5 km. Further analysis was conducted to assess the impact of using smaller buffer sizes for individuals who did not own a car. Associations between these multiple access measures and fruit and vegetable consumption were estimated using linear regression models.

Results
Levels of spatial aggregation did not impact on the proximity estimates. Counts of supermarkets within Euclidean buffers were associated with fruit and vegetable consumption at 1 km, 2 km and 3 km, and for our road network buffers at 2 km, 3 km, and 4 km. Kernel density estimates provided the strongest associations and were significant at a distance of 2 km, 3 km, 4 km and 5 km. Presence of a supermarket within 0.4 km of road network distance from where people lived was positively associated with fruit consumption amongst those without a car (coef. 0.657; s.e. 0.247; p0.008).

Conclusions
The associations between locational access to supermarkets and individual-level dietary behaviour are sensitive to the method by which the food environment variable is captured. Care needs to be taken to ensure robust and conceptually appropriate measures of access are used and these should be grounded in a clear a priori reasoning.

Cross-sectional analysis of association between socioeconomic status and utilization of primary total hip joint replacements 2006-7 : Australian orthopaedic association national joint replacement registry

Background The utilization of total hip replacement (THR) surgery is rapidly increasing, however few data examine whether these procedures are associated with socioeconomic status (SES) within Australia. This study examined primary THR across SES for both genders for the Barwon Statistical Division (BSD) of Victoria, Australia.

Methods Using the Australian Orthopaedic Association National Joint Replacement Registry data for 2006–7, primary THR with a diagnosis of osteoarthritis (OA) among residents of the BSD was ascertained. The Index of Relative Socioeconomic Disadvantage was used to measure SES; determined by matching residential addresses with Australian Bureau of Statistics census data. The data were categorised into quintiles; quintile 1 indicating the most disadvantaged. Age- and sex-specific rates of primary THR per 1,000 person years were reported for 10-year age bands using the total population at risk.

Results Females accounted for 46.9% of the 642 primary THR performed during 2006–7. THR utilization per 1,000 person years was 1.9 for males and 1.5 for females. The highest utilization of primary THR was observed in those aged 70–79 years (males 6.1, and females 5.4 per 1,000 person years). Overall, the U-shaped pattern of THR across SES gave the appearance of bimodality for both males and females, whereby rates were greater for both the most disadvantaged and least disadvantaged groups.

Conclusions Further work on a larger scale is required to determine whether relationships between SES and THR utilization for the diagnosis of OA is attributable to lifestyle factors related to SES, or alternatively reflects geographic and health system biases. Identifying contributing factors associated with SES may enhance resource planning and enable more effective and focussed preventive strategies for hip OA.

The development of the Melbourne low vision ADL index : a measure of vision disability

PURPOSE. To develop a new test of activities of daily living (ADLs) appropriate for the low-vision population: the Melbourne Low-Vision ADL Index (MLVAI).

METHODS. The MLVAI was designed as a desk-based clinical assessment, comprising 18 observed items on complex ADLs in part (a) and 9 questions on broad self-care ADLs in part (b). Each item was rated on a five-level descriptive scale from 0 to 4, based on independence, speed, and accuracy of performance. It was designed to be administered under standardized conditions with regard to the instructions, illumination, and working distances. The validity and reliability of the new MLVAI was determined for 122 subjects who were representative of the general low-vision population, in a cross-sectional study.

RESULTS. Two items were found to be redundant and were eliminated from the test. Thus, the final test comprised 25 items, with 100 being the highest possible score. Cronbach’s α indicated an internal reliability of 0.96, and an intraclass correlation coefficient indicated an overall reliability of 0.95. The SE of measurement was 4.5. According to Spearman’s correlation coefficient, the test–retest reliability was 0.94 (P < 0.001), and the interpractitioner reliability for five different pairs of practitioners was 0.90 or higher (P < 0.001). With regard to validity, there was a moderately high correlation with vision impairment (r = −0.68, P < 0.001). Using Rasch analysis, content validity was also demonstrated by good separation indexes (4.70 and 9.88) and high reliability scores (0.96 and 0.99) for the person and items parameters, respectively. Separate calculation of indexes and reliability scores for parts (a) and (b) indicated high content validity and reliability of each part. However, the separation indexes and reliability scores were higher for part (a) than for part (b). The correlation coefficient for part (a) and part (b) was 0.68.

CONCLUSIONS. The MLVAI is a highly valid and reliable standardized test of ADL performance for the general low-vision population. It may be used to assess patients with low vision and has the potential to be used as a measure of low-vision rehabilitation outcomes.

A weighted version of the Melbourne low-vision ADL index : a measure of disability impact

Objective. To develop a version of the Melbourne Low-Vision ADL Index that measures the personal impact of disability in activities of daily living (ADL's). Also, to determine the relationship between clinical measures of vision impairment and disability impact.

Methods. The Melbourne Low-Vision ADL Index (MLVAI) is a desk-based clinical assessment of disability in ADL's. Ability to perform each item is rated on a five-level descriptive scale from zero to four. In this study, the original version of the MLVAI was modified to measure disability impact. The simple modification involved weighting each item by the importance of that item to the person being tested. Importance was also rated on a five-level scale from zero to four. The validity and reliability of the Weighted Melbourne Low-Vision ADL Index (MLVAIW) was determined for 97 vision-impaired subjects in a cross-sectional study.

Results. Cronbach's alpha coefficient indicated an internal reliability of 0.94, and an intraclass correlation coefficient indicated an overall reliability of 0.88. The standard error of measurement was 24.7 points (out of a possible score of 400). There was a statistically significant difference in test scores between normal subjects and vision-impaired subjects. All vision measures had a high, statistically significant correlation with MLVAIW score. Near-word acuity had the strongest correlation (rs = 0.78, p < 0.001), followed by Melbourne Edge Test contrast sensitivity (rs = -0.72, p < 0.001). Visual field had the weakest correlation (rs = -0.52, p < 0.001). The best predictive model of MLVAIW score incorporated the variables age, near-word acuity, and visual field. Together, these variables accounted for 65.1% of the variance in MLVAIW score.

Conclusions. The MLVAI is highly valid and reliable when weighted by a scale that reflects the personal importance of ADL's. The MLVAIW can provide information over and above that obtained with the usual clinical vision measures and may be used to assess low-vision patients and to measure low-vision rehabilitation outcomes. It is suggested that the assessment of disability using the original MLVAI and the assessment of the impact of disability using the MLVAIW should be kept separate to facilitate the clear interpretation of the outcomes of low-vision rehabilitation.

A similarity measure on tree structured business data

In many business situations, products or user profile data are so complex that they need to be described by use of tree structures. Evaluating the similarity between tree-structured data is essential in many applications, such as recommender systems. To evaluate the similarity between two trees, concept corresponding nodes should be identified by constructing an edit distance mapping between them. Sometimes, the intension of one concept includes the intensions of several other concepts. In that situation, a one-to-many mapping should be constructed from the point of view of structures. This paper proposes a tree similarity measure model that can construct this kind of mapping. The similarity measure model takes into account all the information on nodes’ concepts, weights, and values. The conceptual similarity and the value similarity between two trees are evaluated based on the constructed mapping, and the final similarity measure is assessed as a weighted sum of their conceptual and value similarities. The effectiveness of the proposed similarity measure model is shown by an illustrative example and is also demonstrated by applying it into a recommender system.

Document clustering in correlation similarity measure space

This paper presents a new spectral clustering method called correlation preserving indexing (CPI), which is performed in the correlation similarity measure space. In this framework, the documents are projected into a low-dimensional semantic space in which the correlations between the documents in the local patches are maximized while the correlations between the documents outside these patches are minimized simultaneously. Since the intrinsic geometrical structure of the document space is often embedded in the similarities between the documents, correlation as a similarity measure is more suitable for detecting the intrinsic geometrical structure of the document space than euclidean distance. Consequently, the proposed CPI method can effectively discover the intrinsic structures embedded in high-dimensional document space. The effectiveness of the new method is demonstrated by extensive experiments conducted on various data sets and by comparison with existing document clustering methods.

Nonnegative blind source separation by sparse component analysis based on determinant measure

The problem of nonnegative blind source separation (NBSS) is addressed in this paper, where both the sources and the mixing matrix are nonnegative. Because many real-world signals are sparse, we deal with NBSS by sparse component analysis. First, a determinant-based sparseness measure, named D-measure, is introduced to gauge the temporal and spatial sparseness of signals. Based on this measure, a new NBSS model is derived, and an iterative sparseness maximization (ISM) approach is proposed to solve this model. In the ISM approach, the NBSS problem can be cast into row-to-row optimizations with respect to the unmixing matrix, and then the quadratic programming (QP) technique is used to optimize each row. Furthermore, we analyze the source identifiability and the computational complexity of the proposed ISM-QP method. The new method requires relatively weak conditions on the sources and the mixing matrix, has high computational efficiency, and is easy to implement. Simulation results demonstrate the effectiveness of our method.

An improved physarum centrality measure for weighted networks

Identification of the most central node within a network is one of the primary problems in network analysis. Among various centrality measures for weighted networks, most are based on the assumption that information only spreads through the shortest paths. Then, a mathematical model of an amoeboid organism has been used by Physarum centrality to relax the assumption. However, its computational complexity is relatively high by finding competing paths between all pairs of nodes in networks. In this paper, with the idea of a ground node, an improved Physarum centrality is proposed by maintaining the feature of original measure with the performance is greatly enhanced. Examples and applications are given to show the efficiency and effectiveness of our proposed measure in weighted networks.

Preventive strategies in depression : gathering evidence for risk factors and potential interventions

This editorial critiques the recent literature concerning both vitamin D deficiency in major depression and supplementation as a treatment strategy, and contextualises it within a broader approach to the prevention of depression, based on the recent evidence for lifestyle as a risk factor for depression and anxiety.

Utilising self-report data to measure racial discrimination in the labour market

Although economists have developed a series of approaches to modelling the existence of labour market discrimination, rarely is this topic examined by analysing self-report survey data. After reviewing theories and empirical models of labour market discrimination, we examine self-reported experience of discrimination at different stages in the labour market, among three racial groups utilising U.S. data from the 2001-2003 National Survey of American Life. Our findings indicate that African Americans and Caribbean blacks consistently report more experience of discrimination in the labour market than their non-Hispanic white counterparts. At different stages of the labour market, including hiring, termination and promotion, these groups are more likely to report discrimination than non-Hispanic whites. After controlling for social desirability bias and several human capital and socio-demographic covariates, the results remain robust for African Americans. However, the findings for Caribbean blacks were no longer significant after adjusting for social desirability bias. Although self-report data is rarely utilised to assess racial discrimination in labour economics, our study confirms the utility of this approach as demonstrated in similar research from other disciplines. Our results indicate that after adjusting for relevant confounders self-report survey data is a viable approach to estimating racial discrimination in the labour market. Implications of the study and directions for future research are provided.