Exhaustive Categories Research Articles

Cascade of diabetes care in Bangladesh, Bhutan and Nepal: identifying gaps in the screening, diagnosis, treatment and control continuum

Diabetes has become a major cause of morbidity and mortality in South Asia. Using the data from the three STEPwise approach to Surveillance (STEPS) surveys conducted in Bangladesh, Bhutan, and Nepal during 2018–2019, this study tried to quantify the gaps in diabetes screening, awareness, treatment, and control in these three South Asian countries. Diabetes care cascade was constructed by decomposing the population with diabetes (diabetes prevalence) in each country into five mutually exclusive and exhaustive categories: (1) unscreened and undiagnosed, (2) screened but undiagnosed, (3) diagnosed but untreated, (4) treated but uncontrolled, (5) treated and controlled. In Bangladesh, Bhutan, and Nepal, among the participants with diabetes, 14.7%, 35.7%, and 4.9% of the participants were treated and controlled, suggesting that 85.3%, 64.3%, and 95.1% of the diabetic population had unmet need for care, respectively. Multivariable logistic regression models were used to explore factors associated with awareness of the diabetes diagnosis. Common influencing factors for awareness of the diabetes diagnosis for Bangladesh and Nepal were living in urban areas [Bangladesh-adjusted odd ratio (AOR):2.1; confidence interval (CI):1.2, 3.6, Nepal-AOR:6.2; CI:1.9, 19.9].

Urinary Symptoms Among People With Neurogenic Lower Urinary Tract Dysfunction (NLUTD) Vary by Bladder Management.

To determine whether assessment and decision-making around urinary symptoms in people with neurogenic lower urinary tract dysfunction (NLUTD) should depend on bladder management. Three surveys of urinary symptoms associated with NLUTD (USQNBs) were designed specific to bladder management method for those who manage their bladders with indwelling catheter (IDC), intermittent catheter (IC), or voiding (V). Each was deployed one time to a national sample. Subject matter experts qualitatively assessed the wording of validated items to identify potential duplicates. Clustering by unsupervised structural learning was used to analyze duplicates. Each item was classified into mutually exclusive and exhaustive categories: clinically actionable ("fever"), bladder-specific ("suprapubic pain"), urine quality ("cloudy urine"), or constitutional ("leg pain"). A core of 10 "NLUTD urinary symptoms" contains three clinically actionable, bladder-specific, and urine quality items plus one constitutional item. There are 9 (IDC), 11 (IC), and 8 (V) items unique to these instruments. One decision-making protocol applies to all instruments. Ten urinary symptoms in NLUTD are independent of bladder management, whereas a similar number depend on bladder management. We conclude that assessment of urinary symptoms for persons with NLUTD should be specific to bladder management method, like the USQNBs are.

Prone to Agreement: Does Context Matter for Men and Women in Political Discussions?

ABSTRACT In contemporary discourse, context matters for how people converse with one another about political topics. Discussion may occur face-to-face or online, topics of conversation may be controversial or less so, and gender dynamics may vary. We argue that men and women are affected differently by various contextual discussion factors. We employ a unique quasi-experiment that varies these factors and uses discourse analysis to examine patterns of gendered agreement and disagreement across seven exhaustive categories of response. These factors affect the likelihood of agreement by women and men, though gender-based differences are not dramatic. We do, however, find conditions that prompt men to be less agreeable than women. We also identify seven discrete rhetorical approaches to expressing agreement or disagreement in political discussion. Of these, three show evidence of gender-based patterns of usage. These findings have implications for how men and women use agreement strategies to cope with potential divisiveness in political discussion.

Evaluation of the NANDA International, Inc. diagnostic classification in Spain: Development and validation of the EVALUAN-I tool.

To develop and validate a tool to evaluate the NANDA International, Inc. diagnostic classification. The tool, EVALUAN-I, was validated in a non-probabilistic sample (N = 460) on Spanish Registered Nurses (September-December 2019) in two phases. First, design and construct the instrument in three steps: (1) literature review to define the construct focusing on the orientation toward nursing concepts and theoretical foundations, the level of scientific evidence, the structural configuration, the applicability, the nurses' clinical reasoning skills, and the attitudes toward nursing diagnosis, (2) substantiation of the questionnaire items and design according to the criteria for a diagnostic classification, (3) expert test to establish the face validity and content validity. The second phase revolved around (4) conducting a pilot test and measuring the temporal stability (test-retest) and Cohen's kappa coefficient; assessing psychometric properties by measuring (5) reliability (internal consistency using Cronbach alpha and interfactor correlation) and (6) construct validity (exploratory and confirmatory factor analysis). The manuscript follows the STROBE checklist. The study was approved by the Research Ethics Committee with registration number 2019-190-1. EVALUAN-I displayed moderate test-retest stability, adequate construct validity, and excellent reliability. The confirmatory factor analysis provided evidence about the configuration of EVALUAN-I in relation to nine analytical dimensions: clinical competence, nurses' reasoning skills, attitudes towards nursing diagnosis, discipline's central concepts, classification's contents, physiopathological attributes, level of scientific evidence, diagnostic precision, and conceptual correspondence between terminologies. EVALUAN-I is a valid and reliable instrument, which can be used to improve the epistemological, normative, and intuitive configuration of NANDA International, Inc. in a structured, systematic manner. Comprehensive evaluation of NANDA International, Inc. in different clinical settings around the world using a validated instrument, like EVALUAN-I, would allow strengths and weaknesses to be identified and contribute to the classification's development and practical application.

The Determination of Sample Size in a Bayesian Estimation of Population Proportions: How and Why to Do It in a Regression Framework

Principally to reduce the cost by reducing the sample size required to conduct survey research, this article presents and illustrates the use of a method to determine the sample sizes required to obtain Bayesian estimates of population proportions with specified margins of error. The development proceeds within a regression framework derived from mental test theory. Specifically, building on prior work, the development presented here enables a researcher to conduct a survey to obtain pure Bayes estimates of the proportion of all members of a defined population choosing each one of a number of mutually exclusive and exhaustive options or falling into each one of a number of mutually exclusive and exhaustive categories, including two. The regression framework not only provides useful insight into Bayesian and classical statistics but also enables the development to proceed without explicit reference to the differing parent distributions of the sample and population proportions, both being asymptotically normal. In addition to the sample-size advantage, which is substantial, this article identifies other practical advantages that Bayesian has over classical estimation of population proportions and, in a somewhat in-depth comparison of the two, discusses other reasons a Bayesian method may be a powerful substitute for the classical method of estimating population proportions via independent random sampling.

Consumer Perception of the Circular Economy Concept Applied to the Food Domain: An Exploratory Approach

Every year, agri-food industries in industrialised countries produce approximately 1.3 billion tonnes of food loss and waste. The adoption of a circular economy policy has received special attention by the agri-food industries, allowing for the creation and development of new food products made of by-products that would otherwise be wasted or used for secondary applications. The present work, of an exploratory nature, aims to assess how consumers conceptualise the circular economy in order to identify consumer recognition of the use of by-products from the food industry to upcycle food products and to evaluate attitudes towards the circular economy. To this end, a mixed-methodology was applied to 340 participants. The first part was qualitative and used free word association to evaluate consumers’ conceptualisation of the circular economy and use of by-products as foods. Data were analysed by grouping the responses into exclusive and exhaustive categories and a correspondence analysis was also performed to originate perceptual maps. Additionally, a questionnaire was designed to evaluate major concepts and attitudes correlated with the circular economy. Data were reduced by principal component analysis (PCA) and participants grouped through clustering. Results showed that consumers understand circular economy as related mainly into Sustainability, Economy, and Circularity dimensions. Participants had great difficulty identifying the by-products used as foods or as food ingredients. From the quantitative data, four groups were identified based on the associations to the six principal components originated by the PCA. However, the results highlighted a very low association with all clusters of the Food Valorisation dimension within the concept of the circular economy, and also a lack of a clear understanding of consumers’ attitudes towards food products from the circular economy. Greater promotion and dissemination by the competent entities aimed at the general public may contribute towards greater integration, participation and acceptance of the circular economy concept for the upscaling of food by-products.

A multivariate statistical approach to predict COVID-19 count data with epidemiological interpretation and uncertainty quantification.

For the analysis of COVID‐19 pandemic data, we propose Bayesian multinomial and Dirichlet‐multinomial autoregressive models for time‐series of counts of patients in mutually exclusive and exhaustive observational categories, defined according to the severity of the patient status and the required treatment. Categories include hospitalized in regular wards (H) and in intensive care units (ICU), together with deceased (D) and recovered (R). These models explicitly formulate assumptions on the transition probabilities between these categories across time, thanks to a flexible formulation based on parameters that a priori follow normal distributions, possibly truncated to incorporate specific hypotheses having an epidemiological interpretation. The posterior distribution of model parameters and the transition matrices are estimated by a Markov chain Monte Carlo algorithm that also provides predictions and allows us to compute the reproduction number Rt. All estimates and predictions are endowed with an accuracy measure obtained thanks to the Bayesian approach. We present results concerning data collected during the first wave of the pandemic in Italy and Lombardy and study the effect of nonpharmaceutical interventions. Suitable discrepancy measures defined to check and compare models show that the Dirichlet‐multinomial model has an adequate fit and provides good predictive performance in particular for H and ICU patients.

Sitting, standing and moving during work and leisure among male and female office workers of different age: a compositional data analysis

BackgroundGendered patterns of physical activity behaviours may help explaining health inequalities between men and women. However, evidence on such patterns in the working population is sparse. This study aimed at documenting and comparing compositions of sitting, standing and moving at work and during leisure among male and female office workers of different age.MethodsSitting (including lying), standing and moving were measured using accelerometry for, on average, four working days in 55 male and 57 female Swedish office workers. Behaviours were described in terms of time spent in four exhaustive categories: sitting in short (< 30 min) and long (≥30 min) bouts, standing, and moving. In a compositional data analysis approach, isometric log-ratios (ilr) were calculated for time sitting relative to non-sitting, time in short relative to long sitting bouts, and time in standing relative to moving. Differences between genders (men vs. women), domains (work vs. leisure), and according to age were examined for each ilr using ANOVA.ResultsAt work, time spent sitting in short bouts, sitting in long bouts, standing, and moving was, on average, 29, 43, 21 and 7% among men, and 28, 38, 26 and 7% among women. Corresponding proportions during leisure were 34, 27, 27 and 13% among men and 28, 27, 32 and 13% among women. Men spent more time sitting relative to non-sitting ( {eta}_p^2 =0.04, p = 0.03) than women, and less time standing relative to moving ( {eta}_p^2 =0.07, p = 0.01). At work compared to during leisure, both genders spent more time sitting relative to non-sitting ( {eta}_p^2 =0.47, p < 0.01); within sitting more time was spent in long relative to short sitting bouts ( {eta}_p^2 =0.26, p < 0.01), and within non-sitting, more time was spent standing than moving ( {eta}_p^2 =0.12, p < 0.01). Older workers spent less of their non-sitting time moving than younger workers ( {eta}_p^2 =0.07, p = 0.01).ConclusionMale office workers spent more time sitting relative to non-sitting than female workers, and more time moving relative to standing. Both genders were sitting more at work than during leisure. Older workers moved less than younger. These workers could likely benefit from interventions to reduce or break up prolonged sitting time, preferably by moving more.

Semiparametric Bayesian Markov analysis of personalized benefit–risk assessment

The development of systematic and structured approaches to assess benefit–risk of medical products is a major challenge for regulatory decision makers. Existing benefit–risk methods depend only on the frequencies of mutually exclusive and exhaustive categories in which the subjects fall, and the responses of individuals are allowed to belong to any of the other categories during their postwithdrawal visits. In this article we introduce a semiparametric Bayesian Markov model (SBMM) that treats the withdrawal category as an absorbing state and analyzes subject-level data for multiple visits, accounting for any within-patient dependencies in the response profiles. A log-odds ratio model is used to model the subject-level effects by assuming a ratio of transition probabilities with respect to a “reference” category. A Dirichlet process is used as a semiparametric model for the subject-level effects to flexibly capture the underlying distributions of the personalized response profiles without making strong parametric assumptions. This also allows the borrowing of strength between the patients and achieves dimension reduction by allocating similar response profiles patterns into an unknown number of latent clusters. We analyze a motivating clinical trial dataset to assess the personalized benefit–risks in each arm and evaluate the aggregated benefits and risks associated with the drug Exalgo.

Barriers to Optimal Maternal and Child Feeding Practices in Pastoralist Areas of Somali Region, Eastern Ethiopia: A Qualitative Study

Maternal and child nutrition is critical for child health and survival. Appropriate feeding practices are of fundamental importance for health, nutrition, survival and development of infants and children. In pastoral areas of Ethiopia, barriers related to culture, knowledge, social norms, beliefs, behaviors, decision making in the household and burden of other responsibilities contribute to nutritional status of women and children to deteriorate. Policies and strategies are recommending assessment of barriers for designing programs and interventions to improve maternal and child nutrition practices. This study is aimed to assess barriers of optimal maternal and child feeding practices in Pastoralist areas of Somali region, Eastern Ethiopia. A qualitative community based research method was used involving 17 focus group discussions and 20 in-depth interviews with mothers, grandmothers, health professionals and religious leaders from three districts. Data from FGDs and interviews were transcribed and coded. The agreed upon codes were synthesized and grouped into exhaustive categories. The categories were then merged into themes representing the most common barriers on maternal and child feeding practice that emerged from the FGDs and interviews. We found that traditional beliefs, myths, culture custodian influence, low accessibility and availability of nutritional foods, pattern and burden of other responsibilities, poor knowledge and health seeking behavior, perceived milk insufficiency as main barriers for optimal maternal and child feeding practices. Barriers on optimal maternal and child feeding are very common in the study areas. More work needs to be done to strengthen community-based nutrition with strong social behavioral change communication with emphasis on age-specific counselling on maternal and child nutrition at health facilities, during antenatal and early postnatal visits in the study areas through different media channels, particularly, Somali Region TV and FMs to promote optimal nutrition in the region.

The influence of selection modality, display dynamics and error feedback on patterns of human foraging

ABSTRACTIn previous studies, we have used an iPad task to explore how humans “forage” through static displays containing multiple targets from two categories. When demands on attention were increased, foraging patterns tended to shift from random category selection to exhaustive category selection. Here, we used the same task on a vertically oriented touch-screen. In separate blocks, static or dynamic target items were selected using different modalities, specifically: (a) mouse (b) touchscreen or (c) infrared hand tracker. Although the different selection modalities varied considerably in terms of familiarity and difficulty of use, there was a minimal effect on the patterns of foraging. While there was a consistent reduction in the number of category switches with increased attentional load, the tendency to use exhaustive runs was much reduced, particularly with dynamic displays. We suggest that this pattern is a consequence of generally slowed response times. These findings indicate that in addition to capacity limits, temporal constraints are likely to be an important determinant of foraging patterns in humans. We introduce the term “foraging tempo” to capture this latter notion and to emphasize the probable role played by the overall pace of the regular, repetitive selections required during multi-target search tasks.

Supply Chain Contracts That Prevent Information Leakage

This paper determines categories of contracts that facilitate vertical information sharing in a supply chain while precluding horizontal information leakage among competing newsvendors. We consider a supply chain in which retailers replenish inventory from a common supplier to satisfy uncertain demand and are engaged in newsvendor competition. Each retailer has imperfect demand information. Yet one of the retailers (the incumbent) has a more accurate demand forecast than the other (the entrant). Information leakage among such competing retailers precludes vertical information sharing and is often the reason for many retailers to abandon collaborative forecast-sharing initiatives, leading to suboptimized supply chains. We show that whether a contract can prevent information leakage depends on how the inventory risk (i.e., cost of supply–demand mismatch) is allocated among the supplier and retailers in conjunction with the allocation of profits. We categorize contracts according to how they allocate inventory risk among firms when compared with a wholesale‐price contract. This comparison yields four mutually exclusive and collectively exhaustive categories of contracts. A downside-protection contract is one that effectively reduces retailers’ cost of excess inventory by shifting some of their overage cost to the supplier. Examples of such contracts include buy-back and revenue-sharing contracts. An upside-protection contract is one that effectively increases retailers’ cost of inventory shortage by shifting some of the supplier’s underage cost to retailers. Examples of such contracts include penalty and rebate contracts. A two-sided protection contract combines the properties of the previous two categories. A no-protection contract is one that fails to shift firms’ cost of inventory shortage or excess from one to the other. Examples of such contracts include wholesale-price and two-part tariff contracts. We show that no-protection contracts, which are extensively used in practice, cannot prevent information leakage, whereas others may do so. We also show that preventing information leakage could be costly for the supply chain (i.e., low channel efficiency). We conclude by illustrating how our unified framework to study a variety of contracts can enable a firm to determine the best-performing contract (among many) that precludes information leakage while almost coordinating the channel. For example, we show why buy‐back contracts perform significantly better than revenue‐sharing or rebate contracts. This paper was accepted by Serguei Netessine, operations management.

Small Area Estimation of Proportions with Constraint for National Resources Inventory Survey

Motivated by the need to produce small area estimates for the National Resources Inventory survey, we develop a spatial hierarchical model based on the generalized Dirichlet distribution to construct small area estimators of compositional proportions in several mutually exclusive and exhaustive landcover categories. At the observation level, the standard design-based estimators of the proportions are assumed to follow the generalized Dirichlet distribution. After proper transformation of the design-based estimators, beta regression is applicable. We consider a logit mixed model for the expectation of the beta distribution, which incorporates covariates through fixed effects and spatial effect through a conditionally autoregressive process. In a design-based evaluation study, the proposed model-based estimators are shown to have smaller root-mean-square error and relative root-mean-square error than design-based estimators and multinomial model-based estimators. Supplementary materials accompanying this paper appear online.

Ranking the risk categories in international projects using the TOPSIS method

PurposeThe purpose of this paper is to review the risk categories which are predominant in international projects and to rank them according to their effect on project success.Design/methodology/approachA literature survey of peer-reviewed journal articles, survey reports and books on project management is used as the research methodology. One among the various multi-criteria decision making methods named as Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) has been used to rank the risk categories according to their importance. The data for TOPSIS were collected through questionnaire as the research instrument.FindingsThe findings derived from evaluation of the publications led to the identification of eight different types of risk categories associated with international projects. The TOPSIS method resulted into political risks, technical risks and design-related risks as the top three risk categories in international projects. Contractual and legal risks and fraudulent practices-related risks are relatively low-ranked risk category.Research limitations/implicationsThe findings will be useful in successful implementation of international projects as the knowledge of risk categories and their ranking will help project manager to plan the risk response strategies. A larger sample size for decision makers and more variety of projects can give more exhaustive risk categories and their ranking.Practical implicationsThis paper explores eight different risk categories in international projects. It represents the ranking of risk categories according to their importance in project success. This will be helpful to project managers for developing a general framework for planning the appropriate risk response strategies.Social implicationsGovernments of many countries around the world are encouraging their industries to undertake and successfully complete projects in foreign countries. However, many industries experience failure in projects as they fail to implement the risk management (RM) effectively in international projects. This research work provides the risk categories in international projects and their ranking which can assist in developing strategies to respond the risk appropriately.Originality/valueThis paper uses the TOPSIS method for ranking major types of risk categories in international projects. It might represent new opportunities for rigorous and relevant research that would contribute to an in-depth knowledge of RM methodologies.

Using Description to Convey Mathematics Content in Visual Images to Students who Are Visually Impaired

Introduction Because of the preponderance of visual images, many mathematics texts are wholly or largely inaccessible to students who are blind. This study investigated how much description is sufficient to communicate math content in different types of images. Methods Representative math textbooks from grades five, eight, and 11, aligned to the Common Core, were selected. Mutually exclusive and exhaustive image categories were identified. Clear examples of each image category were chosen, and digital files were created containing the examples and surrounding textual material. Files replicated the printed page as closely as possible, and all elements (words, math expressions, and descriptions of images) were readable by JAWS. Forty-four students who are visually impaired (that is, those who are blind or had low vision) listened to the math pages and answered questions related to the content contained in the images. Results Students answered content-related questions better with more description, but across four description conditions with varying amounts of description the highest correct rate was low (29%). In looking at individual image categories, students had the most correct answers for number lines (41.0%). Rates of 20% to 33% correct were demonstrated for image categories of shapes, tables, line graphs, bar graphs, and ray diagrams. Correct rates for equations, pie charts, and maps were inconsistent or lower than 15%. Students were positive about math and did not indicate many problems with math texts. Discussion Descriptions of visual images can communicate important math information, but there are images for which no level of description is sufficient. Many students in the study were not aware of how much visual math content to which they were not provided access. Implications for practitioners Math texts need to be more accessible for students who are visually impaired. Although describing visual images can improve access to content, that may not be sufficient. Materials should be provided in several formats simultaneously so students can approach material in the mode that fits their needs in a variety of contexts.

A comparative study on nutritional status of ICDS and non- ICDS children of Ganjam district

The rich experience of ICDS has brought about a welcome transition from welfare orientation to a new challenging perspective of social change. The evaluation of nutritional and immunisation services was undertaken in the rural and urban ICDS centres of Ganjam district. The socio-economic development of the country depends on the health status of it’s children. So the opportunities for early childhood development determine the present and future of the country. The present research is an attempt to study the nutritional status of ICDS and Non-ICDS children (3-6 yrs) in urban and rural areas of Ganjam district. A sample of 300 children was selected. The tool consisted of an anthropometric measurement (Weight, Height, Arm-circumferences and Head circumference). Data were analysed of 300 children with the help of WHO anthropometric Software. Z Scores of malnutrition were calculated by this software. The Z-score data of children obtained were systematically tabulated and coded according to exhaustive categories. Analysis of the data was done qualitatively and quantitatively using simple numbers and percentage and Chi- square with the help of statistical software SPSS. The study indicated towards the nutritional status of children.

Bayesian Approach to Personalized Benefit-Risk Assessment

ABSTRACTBenefit-risk assessment is critical in evaluating the effectiveness of a new drug before and after the approval. Some benefit-risk measures depend on the probabilities of benefit-risk categories in which the subject-level benefit and risk outcomes are characterized. The existing benefit-risk methods for analyzing the categorical data depend only on the frequencies of mutually exclusive and collectively exhaustive categories that the subjects fall in, and thus ignore the subject-level differences. We propose a Bayesian method for analyzing the subject-level data with multiple visits. A generalized linear model is used to model the subject-level response probability, with respect to a “reference” category, assuming a logit model with subject-level category effects and multiple visit effects. The random longitudinal visit effects are modeled by a multivariate normal distribution with zero means and first-order autoregressive structured variance-covariance matrices. In the proposed Bayesian setup, a Dirichlet process is used as a prior for the subject-level category effect to catch the similarity among the subject responses. We develop an efficient Markov chain Monte Carlo algorithm for implementing the proposed method, and illustrate the estimation of individual benefit-risk profiles through simulation. The performance of the proposed model fit is evaluated using two model selection approaches, namely, the deviance information criterion (DIC) and the log-pseudo marginal likelihood (LPML). We analyze a clinical trial data using the proposed method to assess the subject-level or personalized benefit-risk in each arm, and to evaluate the aggregated benefit-risk difference between the treatments at different visits.

Global burden of diseases, injuries, and risk factors for young people's health during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Young people's health has emerged as a neglected yet pressing issue in global development. Changing patterns of young people's health have the potential to undermine future population health as well as global economic development unless timely and effective strategies are put into place. We report the past, present, and anticipated burden of disease in young people aged 10-24 years from 1990 to 2013 using data on mortality, disability, injuries, and health risk factors. The Global Burden of Disease Study 2013 (GBD 2013) includes annual assessments for 188 countries from 1990 to 2013, covering 306 diseases and injuries, 1233 sequelae, and 79 risk factors. We used the comparative risk assessment approach to assess how much of the burden of disease reported in a given year can be attributed to past exposure to a risk. We estimated attributable burden by comparing observed health outcomes with those that would have been observed if an alternative or counterfactual level of exposure had occurred in the past. We applied the same method to previous years to allow comparisons from 1990 to 2013. We cross-tabulated the quantiles of disability-adjusted life-years (DALYs) by quintiles of DALYs annual increase from 1990 to 2013 to show rates of DALYs increase by burden. We used the GBD 2013 hierarchy of causes that organises 306 diseases and injuries into four levels of classification. Level one distinguishes three broad categories: first, communicable, maternal, neonatal, and nutritional disorders; second, non-communicable diseases; and third, injuries. Level two has 21 mutually exclusive and collectively exhaustive categories, level three has 163 categories, and level four has 254 categories. The leading causes of death in 2013 for young people aged 10-14 years were HIV/AIDS, road injuries, and drowning (25·2%), whereas transport injuries were the leading cause of death for ages 15-19 years (14·2%) and 20-24 years (15·6%). Maternal disorders were the highest cause of death for young women aged 20-24 years (17·1%) and the fourth highest for girls aged 15-19 years (11·5%) in 2013. Unsafe sex as a risk factor for DALYs increased from the 13th rank to the second for both sexes aged 15-19 years from 1990 to 2013. Alcohol misuse was the highest risk factor for DALYs (7·0% overall, 10·5% for males, and 2·7% for females) for young people aged 20-24 years, whereas drug use accounted for 2·7% (3·3% for males and 2·0% for females). The contribution of risk factors varied between and within countries. For example, for ages 20-24 years, drug use was highest in Qatar and accounted for 4·9% of DALYs, followed by 4·8% in the United Arab Emirates, whereas alcohol use was highest in Russia and accounted for 21·4%, followed by 21·0% in Belarus. Alcohol accounted for 9·0% (ranging from 4·2% in Hong Kong to 11·3% in Shandong) in China and 11·6% (ranging from 10·1% in Aguascalientes to 14·9% in Chihuahua) of DALYs in Mexico for young people aged 20-24 years. Alcohol and drug use in those aged 10-24 years had an annual rate of change of >1·0% from 1990 to 2013 and accounted for more than 3·1% of DALYs. Our findings call for increased efforts to improve health and reduce the burden of disease and risks for diseases in later life in young people. Moreover, because of the large variations between countries in risks and burden, a global approach to improve health during this important period of life will fail unless the particularities of each country are taken into account. Finally, our results call for a strategy to overcome the financial and technical barriers to adequately capture young people's health risk factors and their determinants in health information systems. Bill & Melinda Gates Foundation.

Shedding light on a dark past: representations of slavery at UK heritage tourism sites

Prior research has pointed out that plantation-related heritage tourism sites have not adequately represented historical connections to slavery, often using strategies to downplay or hide this part of their history. However few studies evaluate how the memories of enslavement are constructed and presented in locations where large numbers of slave trade voyages embarked. Accordingly, this study examines the representations of slavery at historical tourist destinations in three UK port cities with strong connections to the trans-Atlantic slave trade. Using a textual analysis of ten data sources, including seven publications and three museum websites, the researchers explore the key conceptual themes that are incorporated into the tourism narratives. By establishing recording units to code and categorise the data content, the research team identified five key mutually exclusive and exhaustive categories that frequently arose within the context of slavery. While the theme of the trans-Atlantic slave trade had the highest relative frequency, the data sources used for this study show there is still ambiguity surrounding memories of slavery and its connection to British wealth and prosperity.

A generic model of dyadic social relationships.

We introduce a model of dyadic social interactions and establish its correspondence with relational models theory (RMT), a theory of human social relationships. RMT posits four elementary models of relationships governing human interactions, singly or in combination: Communal Sharing, Authority Ranking, Equality Matching, and Market Pricing. To these are added the limiting cases of asocial and null interactions, whereby people do not coordinate with reference to any shared principle. Our model is rooted in the observation that each individual in a dyadic interaction can do either the same thing as the other individual, a different thing or nothing at all. To represent these three possibilities, we consider two individuals that can each act in one out of three ways toward the other: perform a social action X or Y, or alternatively do nothing. We demonstrate that the relationships generated by this model aggregate into six exhaustive and disjoint categories. We propose that four of these categories match the four relational models, while the remaining two correspond to the asocial and null interactions defined in RMT. We generalize our results to the presence of N social actions. We infer that the four relational models form an exhaustive set of all possible dyadic relationships based on social coordination. Hence, we contribute to RMT by offering an answer to the question of why there could exist just four relational models. In addition, we discuss how to use our representation to analyze data sets of dyadic social interactions, and how social actions may be valued and matched by the agents.