Low back pain and disability in community-based women : prevalence and association factors

Objective: Although low back pain is characterized by both pain and disability, there is a paucity of studies that have concurrently examined risk factors for these features in community-dwelling women. We aimed to investigate the prevalence and identify factors associated with both back pain and disability.

Design: A questionnaire was mailed to 542 women from a community-based research database. Detailed demographic data were collected, including participants' menopause, relationship, and employment status. Point and period prevalence estimates for back pain were derived. Participants were classified based on pain intensity and disability scores calculated from the Chronic Pain Grade Questionnaire, and factors associated with high levels of pain and disability were examined.

Results: A total of 506 (93.4%) women completed the questionnaire. More than 90% of participants had experienced low back pain, with 75.1% and 22.5% reporting pain in the past 12 months and currently, respectively. Seven percent of women reported a high level of disability and 16% reported high-intensity pain. Women with higher levels of disability were more likely to have a higher body mass index and to have pain currently, whereas those with greater pain intensity were more likely to be younger, have a higher body mass index, not be employed outside the home, drink alcohol, and have current pain.

Conclusions: Low back pain is a common problem for community-based women. A high body mass index and current pain were factors independently associated with both high pain intensity and disability. Longitudinal investigation is required to determine the predictive nature of these factors and their potential role in preventing pain and disability.

Professionalism and accounting rules

Through its emphasis on compliance with processing rules, the accounting profession remains beset by an inferior notion of 'quality' in financial reporting. The capacity of financial reports to provide a reliable guide for financial choice and action is instead shown to be dependent on establishing correspondence with up-to-date commercial phenomena.

A tale of two footballs : the origins of Australian football and association football revisited

 Comparison of the origins of Australian football and Association football

Finding footy : female fan socialization and Australian rules football

The question of how, irrespective of gender, a person becomes a sports fan has been absent in sociological studies of sports supporters. Distinct from other studies of sport spectatorship that focus on the practices of already existing (and overwhelmingly male) fans, our research is the first to consider how women become supporters, and in doing so, it begins to redress the significant under-representation of women in sports fan research. From interviews with female supporters of the Australian Football League (AFL), this article identifies and critically assesses the modes by which women come to support sport. We propose four categories to explain the different ways women accomplish fandom, focusing on the importance of strong social ties and doxic actions in this process. The events, experiences and social relations that inform women's first encounters with AFL offers a template for the wider consideration of women as social agents in the sporting landscape.

Analysis of genome-wide association study data using the protein knowledge base

Article 98

Patient and business rules extraction and formalisation using SVN and SBVR for automated healthcare

This paper describes advances in automated health service selection and composition in the Ambient Assisted Living (AAL) domain. We apply a Service Value Network (SVN) approach to automatically match medical practice recommendations to health services based on sensor readings in a home care context. Medical practice recommendations are extracted from National Health and Medical Research Council (NHMRC) guidelines. Service networks are derived from Medicare Benefits Schedule (MBS) listings. Service provider rules are further formalised using Semantics of Business Vocabulary and Business Rules (SBVR), which allows business participants to identify and define machine-readable rules. We demonstrate our work by applying an SVN composition process to patient profiles in the context of Type 2 Diabetes Management.

Active commuting to school and association with physical activity and adiposity among US youth

Background: Walking or bicycling to school (ie, active commuting) has shown promise for improving physical activity and preventing obesity in youth. Our objectives were to examine, among US youth, whether active commuting was inversely associated with adiposity and positively associated with moderate-to-vigorous physical activity (MVPA). We also examined whether MVPA mediated the relationships between active commuting and adiposity.

Methods: Using data of participants aged 12 to 19 years from the US National Health and Nutrition Examination Survey 2003 to 2004 (n = 789 unweighted), we constructed multiple linear regression models that controlled for dietary energy intake and sociodemographics. The main exposure variable was active commuting. The outcomes were BMI z-score, waist circumference, skinfolds and objectively measured MVPA. The product-of-coefficients method was used to test for mediation.

Results: Active commuting was inversely associated with BMI z-score (β = –0.07, P = .046) and skinfolds (β = –0.06, P = .029), and positively associated with overall daily (β = 0.12, P = .024) and before- and after-school (β = 0.20, P < .001) MVPA. Greater before- and after-school MVPA explained part of the relationship between active commuting and waist circumference (Sobel z = –1.98, P = .048).

Conclusions: Active commuting was associated with greater MVPA and lower measures of adiposity among US youth. Before- and after-school MVPA mediated the relationships between active commuting and waist circumference.

Reliability of the nociceptive flexor reflex (RIII) threshold and association with pain threshold

The purpose of this study was to assess the reliability of the RIII reflex threshold and Pain threshold in three repeated trials using electrocutaneous stimuli. Each trial was separated by a mean of 4.3 +/- 2.9 days (between-trials) and included two repeated measurements (within-trial) of the RIII reflex threshold (RIII-T) and the Pain threshold (PT) separated by 20 min. The participants were 14 healthy males (mean age +/- SD, 23.5 +/- 5.3 years). There was a significant difference between the RIII-T and PT. The reliability of the RIII-T and PT shows a between-trials coefficient of variance (CV(SEM)) of 16.1 and 16.9%, respectively. The within-trial CV(SEM) for RIII-T and PT was 5.4 and 4.3%, respectively. There was a significant correlation between the RIII-T threshold and PT. The parallel association and correlation of the RIII-T with the PT suggests that the RIII-T is valid in experimental pain studies under standardised resting conditions.

Preterm birth prediction : deriving stable and interpretable rules from high dimensional data

Preterm births occur at an alarming rate of 10-15%. Preemies have a higher risk of infant mortality, developmental retardation and long-term disabilities. Predicting preterm birth is difficult, even for the most experienced clinicians. The most well-designed clinical study thus far reaches a modest sensitivity of 18.2-24.2% at specificity of 28.6-33.3%. We take a different approach by exploiting databases of normal hospital operations. We aims are twofold: (i) to derive an easy-to-use, interpretable prediction rule with quantified uncertainties, and (ii) to construct accurate classifiers for preterm birth prediction. Our approach is to automatically generate and select from hundreds (if not thousands) of possible predictors using stability-aware techniques. Derived from a large database of 15,814 women, our simplified prediction rule with only 10 items has sensitivity of 62.3% at specificity of 81.5%.

An incremental FP-growth web content mining and its application in preference identification

This paper presents a real application of Web-content mining using an incremental FP-Growth approach. We firstly restructure the semi-structured data retrieved from the web pages of Chinese car market to fit into the local database, and then employ an incremental algorithm to discover the association rules for the identification of car preference. To find more general regularities, a method of attribute-oriented induction is also utilized to find customer’s consumption preferences. Experimental results show some interesting consumption preference patterns that may be beneficial for the government in making policy to encourage and guide car consumption.

A comparative analysis of opinions of Americans, Australians and Malaysians on the use of biometric devices in workplaces for security and monitoring of worker productivity

Since the September 11, 2001 terrorist attacks in New York, the use of biometric devices such as fingerprint scans, retina and iris scans and facial recognition in everyday situations for national security and border control, have become commonplace. This has resulted in the biometric industry moving from being a niche technology to one that is ubiquitous. As a result. more and more employers are using biometrics to secure staff access to their facilities as well as for tracking staff work hours, maintaining 'discipline' and carry out surveillance against thefts. detecting work hour abuses and fraud. However, the data thus collected and the technologies themselves are feared of having the potential for and actually being misused - both in terms of the violating staff privacy and discrimination and oppression of targeted workers. This paper examines the issue of using biometric devices in organisational settings their advantages, disadvantages and actual and potential abuses from the point of view of critical theory. From the perspectives of Panoptic surveillance and hegemonic organisational control, the paper examines the issues related to privacy and identification, biometrics and privacy, biometrics and the 'body', and surveillance and modernity. The paper also examines the findings ofa survey carried out in Australia. Malaysia and the USA on respondents' opinions on the use of biometric devices in everyday life including at workplaces. The paper concludes that along with their applications in border control and national security, the use of biometric devices should be covered by relevant laws and regulations. guidelines and codes of practice. in order to balance the rights to privacy and civil liberties of workers with employers' need for improved productivity, reduced costs, safeguards related to occupational health and safety, equal opportunity, and workplace harassment of staff and other matters, that employers are legally responsible for.

Using bioinformatics techniques for gene identification in drug discovery and development

As more and more evidence has become available, the link between gene and emergent disease has been made including cancer, heart disease and parkinsonism. Analyzing the diseases and designing drugs with respect to the gene and protein level obviously help to find the underlying causes of the diseases, and to improve their rate of cure. The development of modern molecular biology, biochemistry, data collection and analysis techniques provides the scientists with a large amount of gene data. To draw a link between genes and their relation to disease outcomes and drug discovery is a big challenge: How to analyze large datasets and extract useful knowledge? Combining bioinformatics with drug discovery is a promising method to tackle this issue. Most techniques of bioinformatics are used in the first two phases of drug discovery to extract interesting information and find important genes and/or proteins for speeding the process of drug discovery, enhancing the accuracy of analysis and reducing the cost. Gene identification is a very fundamental and important technique among them. In this paper, we have reviewed gene identification algorithms and discussed their usage, relationships and challenges in drug discovery and development.