Health literacy and the determinants of obesity: a population-based survey of sixth grade school children in Taiwan

BACKGROUND: Health literacy has become an important health policy and health promotion agenda item in recent years. It had been seen as a means to reduce health disparities and a critical empowerment strategy to increase people's control over their health. So far, most of health literacy studies mainly focus on adults with few studies investigating associations between child health literacy and health status. This study aimed to investigate the association between health literacy and body weight in Taiwan's sixth grade school children.

METHODS: Using a population-based survey, 162,209 sixth grade (11-12 years old) school children were assessed. The response rate at school level was 83%, with 70% of all students completing the survey. The Taiwan child health literacy assessment tool was applied and information on sex, ethnicity, self-reported health, and health behaviors were also collected. BMI was used to classify the children as underweight, normal, overweight, or obese. A multinomial logit model with robust estimation was used to explore associations between health literacy and the body weight with an adjustment for covariates.

RESULTS: The sample consisted of 48.9% girls, 3.8% were indigenous and the mean BMI was 19.55 (SD = 3.93). About 6% of children self-reported bad or very bad health. The mean child health literacy score was 24.03 (SD = 6.12, scale range from 0 to 32). The overall proportion of obese children was 15.2%. Children in the highest health literacy quartile were less likely to be obese (12.4%) compared with the lowest quartile (17.4%). After controlling for gender, ethnicity, self-rated health, and health behaviors, children with higher health literacy were less likely to be obese (Relative Risk Ratio (RRR) = 0.94, p < 0.001) and underweight (RRR = 0.83, p < 0.001). Those who did not have regular physical activity, or had sugar-sweetened beverage intake (RRR > 1.10, p < 0.0001) were more likely to report being overweight or obese.

CONCLUSIONS: This study demonstrates strong links between health literacy and obesity, even after adjusting for key potential confounders, and provides new insights into potential intervention points in school education for obesity prevention. Systematic approaches to integrating a health literacy curriculum into schools may mitigate the growing burden of disease due to obesity.

The hidden permutation model and location-based activity recognition

Permutation modeling is challenging because of the combinatorial nature of the problem. However, such modeling is often required in many real-world applications, including activity recognition where subactivities are often permuted and partially ordered. This paper introduces a novel Hidden Permutation Model (HPM) that can learn the partial ordering constraints in permuted state sequences. The HPM is parameterized as an exponential family distribution and is flexible so that it can encode constraints via different feature functions. A chain-flipping Metropolis-Hastings Markov chain Monte Carlo (MCMC) is employed for inference to overcome the O(n!) complexity. Gradient-based maximum likelihood parameter learning is presented for two cases when the permutation is known and when it is hidden. The HPM is evaluated using both simulated and real data from a location-based activity recognition domain. Experimental results indicate that the HPM performs far better than other baseline models, including the naive Bayes classifier, the HMM classifier, and Kirshner's multinomial permutation model. Our presented HPM is generic and can potentially be utilized in any problem where the modeling of permuted states from noisy data is needed.

Internationalization and alliance formation : evidence from Turkish SMEs

This study explores the issue of internationalization through forming alliances with foreign capital in the small business sector in Turkey. Using a sample of 257 SMEs from this emerging market economy, collected via a field study, it finds that Turkish SMEs would like to form alliances with foreign capital for expanding their production capacity and accessing to world markets. Multivariate multinomial logit models are employed to analyse the survey data econometrically. Size-specific, sector-specific and management-specific factors are identified in the alliance motivation. The `market' and `finance' aspects of alliances prevail in the multivariate analysis with significant implications. There is also evidence that some conditional relationships offered by multivariate analysis differ from unconditional associations found in the survey, which implies that alliance motivation is partly a product of multidimensional decision-making process on behalf of SMEs.

Dividend policy choice : do earnings or investment opportunities matter?

The aim of this paper is to analyse the influence of a company's level of earnings and growth opportunities in determining the dividend policy choice of Malaysian-listed firms. The analysis is based on a sample of 136 firms listed on the Bursa Malaysia Index over a period of six years, from 1990 to 1996. The evidence suggests that the payers are more profitable than non-payers. Likewise, investment opportunity, which is measured by (∂At /At-1) and (Vt /At), differed for both payers and non-payers. The regression estimates from Logit model suggest that the average coefficient for EATA is a significant determinant for firm's dividend policy choice in Malaysia. This is consistent with the supposition that profitable firms are more likely to pay dividends than less profitable firms. Although investment opportunities, the firm's size and leverage were not found to be statistically significant, they provided some explanation for the dividend policy choice.

Insights into international travel by students

Although research on international travelers abounds in the literature, international travel by students remains a neglected area of research. This article reports the findings from a survey of 370 university students in New Zealand. The survey identified student motives for undertaking international travel, the planning process, and the preferred destinations and methods of financing international trips. Logit models were developed and estimated for two important aspects of international travel by students. In addition, the study also included cross-cultural comparisons of travel behavior. The findings indicate that students traveling overseas represent a distinct market with specific needs and preferences. Travel behaviors vary significantly for different cultures and the article shows that it is possible to model such behaviors.

A comparative analysis of decision trees vis-à-vis other computational data mining techniques in automotive insurance fraud detection

The development and application of computational data mining techniques in financial fraud detection and business failure prediction has become a popular cross-disciplinary research area in recent times involving financial economists, forensic accountants and computational modellers. Some of the computational techniques popularly used in the context of - financial fraud detection and business failure prediction can also be effectively applied in the detection of fraudulent insurance claims and therefore, can be of immense practical value to the insurance industry. We provide a comparative analysis of prediction performance of a battery of data mining techniques using real-life automotive insurance fraud data. While the data we have used in our paper is US-based, the computational techniques we have tested can be adapted and generally applied to detect similar insurance frauds in other countries as well where an organized automotive insurance industry exists.

Local population preferences toward restoring ecosystem services of a wetland in Thailand

This study reports the findings of a choice experiment designed to explore local population preferences toward wetland ecosystem restoration of Bung Khong Long Wetland in Thailand. By addressing ecological, socioeconomic and cultural dimensions of ecosystem services, the findings provide policy-makers with a richer insight into the interconnections among ecological, socioeconomic and cultural systems in explaining the value of ecosystem services. Gaining an understanding of the trade-offs associated with different interests in ecosystem uses in this community has the capacity to promote wetland management and enhance land use planning. The choice experiment application entails selecting attributes and their levels and developing an experimental design to create the choice sets or hypothetical scenarios for welfare assessment via the questionnaire. The study is based on household level data collected from 780 randomly drawn respondents living around the lake and the data are analysed using the Random Parameter Logit Model with interactions. The findings indicate that the local population derives positive and significant values from the restoration of wetland ecosystem services, indicating caution is needed in the decision-making processes involving sensitive environments faced with competing uses. Socioeconomic and attitudinal characteristics of respondents are important factors influencing willingness to pay, implying community preferences are important in the effectiveness of environmental conservation efforts in this community. The cultural values associated with the wetland are significant suggesting that incorporating culture preferences may be a key factor in supporting wetland conservation.

Patient and nurse preferences for nurse handover-using preferences to inform policy: a discrete choice experiment protocol

INTRODUCTION: Nursing bedside handover in hospital has been identified as an opportunity to involve patients and promote patient-centred care. It is important to consider the preferences of both patients and nurses when implementing bedside handover to maximise the successful uptake of this policy. We outline a study which aims to (1) identify, compare and contrast the preferences for various aspects of handover common to nurses and patients while accounting for other factors, such as the time constraints of nurses that may influence these preferences.; (2) identify opportunities for nurses to better involve patients in bedside handover and (3) identify patient and nurse preferences that may challenge the full implementation of bedside handover in the acute medical setting. METHODS AND ANALYSIS: We outline the protocol for a discrete choice experiment (DCE) which uses a survey design common to both patients and nurses. We describe the qualitative and pilot work undertaken to design the DCE. We use a D-efficient design which is informed by prior coefficients collected during the pilot phase. We also discuss the face-to-face administration of this survey in a population of acutely unwell, hospitalised patients and describe how data collection challenges have been informed by our pilot phase. Mixed multinomial logit regression analysis will be used to estimate the final results. ETHICS AND DISSEMINATION: This study has been approved by a university ethics committee as well as two participating hospital ethics committees. Results will be used within a knowledge translation framework to inform any strategies that can be used by nursing staff to improve the uptake of bedside handover. Results will also be disseminated via peer-reviewed journal articles and will be presented at national and international conferences.

What firm characteristics determine women's employment in manufacturing? evidence from Bangladesh

The purpose of this paper is to investigate the principal determinants of women's employment in the manufacturing sector of Bangladesh using a firm-level panel data from the World Bank's "Enterprise Survey" for the years 2007, 2011 and 2013. The paper sheds light on the demandside factors, mainly firm-level characteristics, which also influence this decision. Design/methodology/approach - The authors estimate a fractional logit model to model a dependent variable that is limited by zero from below and one from above. Findings - The results indicate that firm size, whether medium or large, and firms' export-oriented activities, have an important impact on women's employment in the manufacturing sector in Bangladesh. Moreover, the authors find that women are significantly more likely to work in unskilledlabour- intensive industries within the manufacturing sector. Research limitations/implications - The research is limited to Bangladesh; however, much of the evidence presented here has implications that are relevant to policymakers in other developing countries. Practical implications - The study identifies factors that affect female employment, that is, where the main constraints to increase female labour force participation. The study focuses on the demand-side factors, which has been somewhat neglected in recent years. As such, it has practical policy implications. Social implications - Focusing on female employment in Bangladesh also sheds light on the nexus between labour market opportunities and social change within a country that is characterised by extreme patriarchy, which has wide-reaching implications. Originality/value - This is an original and comprehensive paper by the authors.

Instructional strategies integrating cognitive style construct : a meta-knowledge processing model

The overarching goal of this dissertation was to evaluate the contextual components of instructional strategies for the acquisition of complex programming concepts. A meta-knowledge processing model is proposed, on the basis of the research findings, thereby facilitating the selection of media treatment for electronic courseware. When implemented, this model extends the work of Smith (1998), as a front-end methodology, for his glass-box interpreter called Bradman, for teaching novice programmers. Technology now provides the means to produce individualized instructional packages with relative ease. Multimedia and Web courseware development accentuate a highly graphical (or visual) approach to instructional formats. Typically, little consideration is given to the effectiveness of screen-based visual stimuli, and curiously, students are expected to be visually literate, despite the complexity of human-computer interaction. Visual literacy is much harder for some people to acquire than for others! (see Chapter Four: Conditions-of-the-Learner) An innovative research programme was devised to investigate the interactive effect of instructional strategies, enhanced with text-plus-textual metaphors or text-plus-graphical metaphors, and cognitive style, on the acquisition of a special category of abstract (process) programming concept. This type of concept was chosen to focus on the role of analogic knowledge involved in computer programming. The results are discussed within the context of the internal/external exchange process, drawing on Ritchey's (1980) concepts of within-item and between-item encoding elaborations. The methodology developed for the doctoral project integrates earlier research knowledge in a novel, interdisciplinary, conceptual framework, including: from instructional science in the USA, for the concept learning models; British cognitive psychology and human memory research, for defining the cognitive style construct; and Australian educational research, to provide the measurement tools for instructional outcomes. The experimental design consisted of a screening test to determine cognitive style, a pretest to determine prior domain knowledge in abstract programming knowledge elements, the instruction period, and a post-test to measure improved performance. This research design provides a three-level discovery process to articulate: 1) the fusion of strategic knowledge required by the novice learner for dealing with contexts within instructional strategies 2) acquisition of knowledge using measurable instructional outcome and learner characteristics 3) knowledge of the innate environmental factors which influence the instructional outcomes This research has successfully identified the interactive effect of instructional strategy, within an individual's cognitive style construct, in their acquisition of complex programming concepts. However, the significance of the three-level discovery process lies in the scope of the methodology to inform the design of a meta-knowledge processing model for instructional science. Firstly, the British cognitive style testing procedure, is a low cost, user friendly, computer application that effectively measures an individual's position on the two cognitive style continua (Riding & Cheema,1991). Secondly, the QUEST Interactive Test Analysis System (Izard,1995), allows for a probabilistic determination of an individual's knowledge level, relative to other participants, and relative to test-item difficulties. Test-items can be related to skill levels, and consequently, can be used by instructional scientists to measure knowledge acquisition. Finally, an Effect Size Analysis (Cohen,1977) allows for a direct comparison between treatment groups, giving a statistical measurement of how large an effect the independent variables have on the dependent outcomes. Combined with QUEST's hierarchical positioning of participants, this tool can assist in identifying preferred learning conditions for the evaluation of treatment groups. By combining these three assessment analysis tools into instructional research, a computerized learning shell, customised for individuals' cognitive constructs can be created (McKay & Garner,1999). While this approach has widespread application, individual researchers/trainers would nonetheless, need to validate with an extensive pilot study programme (McKay,1999a; McKay,1999b), the interactive effects within their specific learning domain. Furthermore, the instructional material does not need to be limited to a textual/graphical comparison, but could be applied to any two or more instructional treatments of any kind. For instance: a structured versus exploratory strategy. The possibilities and combinations are believed to be endless, provided the focus is maintained on linking of the front-end identification of cognitive style with an improved performance outcome. My in-depth analysis provides a better understanding of the interactive effects of the cognitive style construct and instructional format on the acquisition of abstract concepts, involving spatial relations and logical reasoning. In providing the basis for a meta-knowledge processing model, this research is expected to be of interest to educators, cognitive psychologists, communications engineers and computer scientists specialising in computer-human interactions.

Human behavior recognition with generic exponential family duration modeling in the hidden semi-Markov model

The ability to learn and recognize human activities of daily living (ADLs) is important in building pervasive and smart environments. In this paper, we tackle this problem using the hidden semi-Markov model. We discuss the state-of-the-art duration modeling choices and then address a large class of exponential family distributions to model state durations. Inference and learning are efficiently addressed by providing a graphical representation for the model in terms of a dynamic Bayesian network (DBN). We investigate both discrete and continuous distributions from the exponential family (Poisson and Inverse Gaussian respectively) for the problem of learning and recognizing ADLs. A full comparison between the exponential family duration models and other existing models including the traditional multinomial and the new Coxian are also presented. Our work thus completes a thorough investigation into the aspect of duration modeling and its application to human activities recognition in a real-world smart home surveillance scenario.

Activity recognition and abnormality detection with the switching hidden semi-Markov model

This paper addresses the problem of learning and recognizing human activities of daily living (ADL), which is an important research issue in building a pervasive and smart environment. In dealing with ADL, we argue that it is beneficial to exploit both the inherent hierarchical organization of the activities and their typical duration. To this end, we introduce the Switching Hidden Semi-Markov Model (S-HSMM), a two-layered extension of the hidden semi-Markov model (HSMM) for the modeling task. Activities are modeled in the S-HSMM in two ways: the bottom layer represents atomic activities and their duration using HSMMs; the top layer represents a sequence of high-level activities where each high-level activity is made of a sequence of atomic activities. We consider two methods for modeling duration: the classic explicit duration model using multinomial distribution, and the novel use of the discrete Coxian distribution. In addition, we propose an effective scheme to detect abnormality without the need for training on abnormal data. Experimental results show that the S-HSMM performs better than existing models including the flat HSMM and the hierarchical hidden Markov model in both classification and abnormality detection tasks, alleviating the need for presegmented training data. Furthermore, our discrete Coxian duration model yields better computation time and generalization error than the classic explicit duration model.

Efficient Coxian duration modelling for activity recognition in smart environment with the hidden semi-Markov model

In this paper, we exploit the discrete Coxian distribution and propose a novel form of stochastic model, termed as the Coxian hidden semi-Makov model (Cox-HSMM), and apply it to the task of recognising activities of daily living (ADLs) in a smart house environment. The use of the Coxian has several advantages over traditional parameterization (e.g. multinomial or continuous distributions) including the low number of free parameters needed, its computational efficiency, and the existing of closed-form solution. To further enrich the model in real-world applications, we also address the problem of handling missing observation for the proposed Cox-HSMM. In the domain of ADLs, we emphasize the importance of the duration information and model it via the Cox-HSMM. Our experimental results have shown the superiority of the Cox-HSMM in all cases when compared with the standard HMM. Our results have further shown that outstanding recognition accuracy can be achieved with relatively low number of phases required in the Coxian, thus making the Cox-HSMM particularly suitable in recognizing ADLs whose movement trajectories are typically very long in nature.

A new social-family model for eating disorders: A European multicentre project using a case-control design

OBJECTIVE: To examine a new socio-family risk model of Eating Disorders (EDs) using path-analyses. METHOD: The sample comprised 1264 (ED patients = 653; Healthy Controls = 611) participants, recruited into a multicentre European project. Socio-family factors assessed included: perceived maternal and parental parenting styles, family, peer and media influences, and body dissatisfaction. Two types of path-analyses were run to assess the socio-family model: 1.) a multinomial logistic path-model including ED sub-types [Anorexia Nervosa-Restrictive (AN-R), AN-Binge-Purging (AN-BP), Bulimia Nervosa (BN) and EDNOS)] as the key polychotomous categorical outcome and 2.) a path-model assessing whether the socio-family model differed across ED sub-types and healthy controls using body dissatisfaction as the outcome variable. RESULTS: The first path-analyses suggested that family and media (but not peers) were directly and indirectly associated (through body dissatisfaction) with all ED sub-types. There was a weak effect of perceived parenting directly on ED sub-types and indirectly through family influences and body dissatisfaction. For the second path-analyses, the socio-family model varied substantially across ED sub-types. Family and media influences were related to body dissatisfaction in the EDNOS and control sample, whereas perceived abusive parenting was related to AN-BP and BN. DISCUSSION: This is the first study providing support for this new socio-family model, which differed across ED sub-types. This suggests that prevention and early intervention might need to be tailored to diagnosis-specific ED profiles.