Developing a model of links between general and workplace belongingness and depressive symptoms

Given the high prevalence of depression in the community there is urgent need to understand the interpersonal predictors of this disorder. Data from large community samples indicates that a diminished sense of belonging appears to be the most salient and immediate antecedent of a rapid depressive response. Belongingness in the workplace is also very important and associated with depressive symptoms over and above associations attributable to general or community belongingness. Finally it appears that the personality factor of interpersonal sensitivity moderates the relationship between belongingness and depressive symptoms. Results have extensive future implications for the prevention and treatment of depression.

Associations between area-level disadvantage and DMFT among a birth cohort of Indigenous Australians

Background Individual-level factors influence DMFT, but little is known about the influence of community environment. This study examines associations between community-level influences and DMFT among a birth cohort of Indigenous Australians aged 16–20 years. Methods Data were collected as part of Wave 3 of the Aboriginal Birth Cohort study. Fifteen community areas were established and the sample comprised 442 individuals. The outcome variable was mean DMFT with explanatory variables including diet and community disadvantage (access to services, infrastructure and communications). Data were analysed using multilevel regression modelling. Results In a null model, 13.8% of the total variance in mean DMFT was between community areas, which increased to 14.3% after adjusting for sex, age and diet. Addition of the community disadvantage variable decreased the variance between areas by 4.8%, indicating that community disadvantage explained one-third of the area-level variance. Residents of under-resourced communities had significantly higher mean DMFT (β=3.86, 95% CI 0.02¬, 7.70) after adjusting for sex, age and diet. Conclusions Living in under-resourced communities was associated with greater DMFT among this disadvantaged population, indicating that policies aiming to reduce oral health-related inequalities among vulnerable groups may benefit from taking into account factors external to individual-level influences.

Associations between individual and workplace risk factors for self-reported neck pain and disability among female office workers

A cross-sectional survey of female office workers (n=333) was undertaken to determine the level of neck pain and disability (Neck Disability Index—NDI) and to explore the relationship between individual and workplace risk factors with the NDI score and the presence of pain. Workers reported nil (32%), mild (53%), moderate (14%) and severe (1%) neck pain. There were more risk factors associated with the NDI score than the presence of neck pain. The presence of neck pain was associated with a history of neck trauma (OR: 4.8), using a graduated lens (OR: 4.6), and negative affectivity (OR: 2.7) in the multiple regression model. Factors associated with higher NDI score were using the computer mouse for more than 6 h per day, higher negative affectivity, older age and an uncomfortable workstation. These results suggest that measuring the level of neck pain and disability rather than just the presence of neck pain provides more specific directives for the prevention and management of this disorder.

Confirmatory factor analysis of the baby eating behaviour questionnaire and associations with infant weight, gender and feeding mode in an Australian sample

The aim of this study was to evaluate the factor structure of the Baby Eating Behaviour Questionnaire (BEBQ) in an Australian community sample of mother-infant dyads. A secondary aim was to explore the relationship between the BEBQ subscales and infant gender, weight and current feeding mode. Confirmatory factor analysis (CFA) utilising structural equation modelling examined the hypothesised 4-factor model of the BEBQ. Only mothers (N=467) who completed all items on the BEBQ (infant age: M=17 weeks, SD=3 weeks) were included in the analysis. The original 4-factor model did not provide an acceptable fit to the data due to poor performance of the Satiety responsiveness factor. Removal of this factor (3 items) resulted in a well-fitting 3-factor model. Cronbach’s α was acceptable for the Enjoyment of food (α=0.73), Food responsiveness (α=0.78) and Slowness in eating (α=0.68) subscales but low for the Satiety responsiveness (α=0.56) subscale. Enjoyment of food was associated with higher infant weight whereas Slowness in eating and Satiety responsiveness were both associated with lower infant weight. Differences on all four subscales as a function of feeding mode were observed. This study is the first to use CFA to evaluate the hypothesised factor structure of the BEBQ. Findings support further development work on the Satiety responsiveness subscale in particular, but confirm the utility of the Enjoyment of food, Food responsiveness and Slowness in eating subscales.

Associations between extreme precipitation and childhood hand, foot and mouth disease in urban and rural areas in Hefei, China

Background Understanding the relationship between extreme weather events and childhood hand, foot and mouth disease (HFMD) is important in the context of climate change. This study aimed to quantify the relationship between extreme precipitation and childhood HFMD in Hefei, China, and further, to explore whether the association varied across urban and rural areas. Methods Daily data on HFMD counts among children aged 0–14 years from 2010 January 1st to 2012 December 31st were retrieved from Hefei Center for Disease Control and Prevention. Daily data on mean temperature, relative humidity and precipitation during the same period were supplied by Hefei Bureau of Meteorology. We used a Poisson linear regression model combined with a distributed lag non-linear model to assess the association between extreme precipitation (≥ 90th precipitation) and childhood HFMD, controlling for mean temperature, humidity, day of week, and long-term trend. Results There was a statistically significant association between extreme precipitation and childhood HFMD. The effect of extreme precipitation on childhood HFMD was the greatest at six days lag, with a 5.12% (95% confident interval: 2.7–7.57%) increase of childhood HFMD for an extreme precipitation event versus no precipitation. Notably, urban children and children aged 0–4 years were particularly vulnerable to the effects of extreme precipitation. Conclusions Our findings indicate that extreme precipitation may increase the incidence of childhood HFMD in Hefei, highlighting the importance of protecting children from forthcoming extreme precipitation, particularly for those who are young and from urban areas.

Genetic associations and functional characterization of M1 aminopeptidases and immune-mediated diseases

Endosplasmic reticulum aminopeptidase 1 (ERAP1), endoplasmic reticulum aminopeptidase 2 (ERAP2) and puromycin-sensitive aminopeptidase (NPEPPS) are key zinc metallopeptidases that belong to the oxytocinase subfamily of M1 aminopeptidase family. NPEPPS catalyzes the processing of proteosome-derived peptide repertoire followed by trimming of antigenic peptides by ERAP1 and ERAP2 for presentation on major histocompatibility complex (MHC) Class I molecules. A series of genome-wide association studies have demonstrated associations of these aminopeptidases with a range of immune-mediated diseases such as ankylosing spondylitis, psoriasis, Behçet's disease, inflammatory bowel disease and type I diabetes, and significantly, genetic interaction between some aminopeptidases and HLA Class I loci with which these diseases are strongly associated. In this review, we highlight the current state of understanding of the genetic associations of this class of genes, their functional role in disease, and potential as therapeutic targets.

Postnatal depressive symptoms amongst women in Central Vietnam: A cross-sectional study investigating prevalence and associations with social, cultural and infant factors

Background This study investigated the prevalence and socio-cultural correlates of postnatal mood disturbance amongst women 18–45 years old in Central Vietnam. Son preference and traditional confinement practices were explored as well as factors such as poverty, parity, family and intimate partner relationships and infant health. Methods A cross-sectional study was conducted in twelve randomly selected Commune Health Centres from urban and rural districts of Thua Thien Hue Province, Vietnam. Mother-infant dyads one to six months postpartum were invited to participate. Questionnaires from 431 mothers (urban n = 216; rural n = 215) assessed demographic and family characteristics, traditional confinement practices, son preference, infant health and social capital. The Edinburgh Postnatal Depression Scale (EPDS) and WHO5 Wellbeing Index indicated depressive symptoms and emotional wellbeing. Data were analysed using general linear models. Results Using an EPDS cut-off of 12/13, 18.1 % (n = 78, 95 % CI 14.6 - 22.1) of women had depressive symptoms (20.4 % urban; 15.8 % rural). Contrary to predictions, infant gender and traditional confinement were unrelated to depressive symptoms. Poverty, food insecurity, being frightened of family members, and intimate partner violence increased both depressive symptoms and lowered wellbeing. The first model accounted for 30.2 % of the variance in EPDS score and found being frightened of one’s husband, husband’s unemployment, breastfeeding difficulties, infant diarrhoea, and cognitive social capital were associated with higher EPDS scores. The second model had accounted for 22 % of the variance in WHO5 score. Living in Hue city, low education, poor maternal competence and a negative family response to the baby lowered maternal wellbeing. Conclusions Traditional confinement practices and son preference were not linked to depressive symptoms among mothers, but were correlates of family relationships and wellbeing. Poverty, food insecurity, violence, infant ill health, and discordant intimate and family relationships were linked with depressive symptoms in Central Vietnam.

Statistical analysis of the associations of hereditary factors with the risk of Type 1 diabetes and Diabetic Nephropathy based on the familial data collected through ascertaiment from population-based registers

In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.

Associations between personality traits and sleep quality and quantity in young adults

This thesis examines the associations between personality traits and sleep quantity and quality in young adults. Additionally the possible effects of birth status on these associations are examined. The data used in this thesis is part of a birth cohort study (Helsinki Study of Very Low Birth Weight Adults). The personality traits are based on the five-factor model of personality. The sleep quantity and quality are based on actigraphy assessments. Four hypothesis were made about the personality and sleep associations: (1) neuroticism is related to a lesser quality of sleep, (2) there will be more significant associations between personality traits and sleep quality than between personality traits and sleep quantity, (3) the Very Low Birth Weight (VLBW) as well as, (4) the Small for Gestational Age (SGA) status will affect the associations. Linear regressions were used to study the associations between personality traits and sleep quality and quantity. Whenever an association was significant, it was tested whether this association was moderated first, by the VLBW and second, by the SGA status of the participant. The results were mostly in line with previous research especially demonstrating the negative association between neuroticism and the quality of sleep and suggesting that vulnerability to stress decreases sleep quality. Also it was found that agreeableness and conscientiousness were associated with better sleep quality and extraversion was associated with lower sleep quantity. In addition SGA status moderated the personality and sleep associations. It is proposed that there are two factors behind the interaction. First, prenatally developing mechanisms have an effect on the development of sleep as well as personality. Second, differences in the postnatal environment, for instance the parenting practices, can account for this finding. Future research could focus especially on what kind of prenatal disturbances SGA infants have in the development of mechanisms related to sleep and personality. Also focusing on the differences in parental interaction might shed more light on the results.

A modified least squares algorithm to treat associations in liquid alloys

The associated model for binary systems has been modified to include volume effects and excess entropy arising from preferential interactions between the associate and the free atoms or between the free atoms. Equations for thermodynamic mixing functions have been derived. An optimization procedure using a modified conjugate gradient method has been used to evaluate the enthalpy and entropy interaction energies, the free energy of dissociation of the complex, its temperature dependance and the size of the associate. An expression for the concentration—concentration structure factor [Scc (0)] has been deduced from the modified associated solution model. The analysis has been applied to the thermodynamic mixing functions of liquid Ga-Te alloys at 1120 K, believed to contain Ga2Te3 associates. It is observed that the modified associated solution model incorporating volume effects and terms for the temperature dependance of interaction energies, describes the thermodynamic properties of Ga-Te system satisfactorily.

Volume effects and associations in liquid alloys

The regular associated solution model for binary systems has been modified by incorporating the size of the complex as an explicit variable. The thermodynamic properties of the liquid alloy and the interactions between theA ?B type of complex and the unassociated atoms in anA-B binary have been evaluated as a function of relative size of the complex using the activity coefficients at infinite dilution and activity data at one other composition in the binary. The computational procedure adopted for determining the concentration of clusters and interaction energies in the associated liquid is similar to that proposed by Lele and Rao. The analysis has been applied to the thermodynamic mixing functions of liquid Al-Ca alloys believed to contain Al2Ca associates. It is found that the size of the cluster significantly affects the interaction energies between the complex and the unassociated atoms, while the equilibrium constant and enthalpy change for the association reaction exhibit only minor variation, when the equations are fitted to experimental data. The interaction energy between unassociated free atoms remains virtually unaltered as the size of the complex is varied between extreme values. Accurate data on free energy, enthalpy, and volume of mixing at the same temperature on alloy systems with compound forming tendency would permit a rigorous test of the proposed model.

Active learning in keyword search-based data integration

The problem of scaling up data integration, such that new sources can be quickly utilized as they are discovered, remains elusive: Global schemas for integrated data are difficult to develop and expand, and schema and record matching techniques are limited by the fact that data and metadata are often under-specified and must be disambiguated by data experts. One promising approach is to avoid using a global schema, and instead to develop keyword search-based data integration-where the system lazily discovers associations enabling it to join together matches to keywords, and return ranked results. The user is expected to understand the data domain and provide feedback about answers' quality. The system generalizes such feedback to learn how to correctly integrate data. A major open challenge is that under this model, the user only sees and offers feedback on a few ``top-'' results: This result set must be carefully selected to include answers of high relevance and answers that are highly informative when feedback is given on them. Existing systems merely focus on predicting relevance, by composing the scores of various schema and record matching algorithms. In this paper, we show how to predict the uncertainty associated with a query result's score, as well as how informative feedback is on a given result. We build upon these foundations to develop an active learning approach to keyword search-based data integration, and we validate the effectiveness of our solution over real data from several very different domains.

Ontologies for representation of folk song metadata

The digital management of collections in museums, archives, libraries and galleries is an increasingly important part of cultural heritage studies. This paper describes a representation for folk song metadata, based on the Web Ontology Language (OWL) implementation of the CIDOC Conceptual Reference Model. The OWL representation facilitates encoding and reasoning over a genre ontology, while the CIDOC model enables a representation of complex spatial containment and proximity relations among geographic regions. It is shown how complex queries of folk song metadata, relying on inference and not only retrieval, can be expressed in OWL and solved using a description logic reasoner.

User’s Guide to ADMB2R: A Set of AD Model Builder Output Routines Compatible with the R Statistics Language

ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

Self-reported sitting time and physical activity: interactive associations with mental well-being and productivity in office employees

Background: Little is known about how sitting time, alone or in combination with markers of physical activity (PA), influences mental well-being and work productivity. Given the need to develop workplace PA interventions that target employees' health related efficiency outcomes; this study examined the associations between self-reported sitting time, PA, mental well-being and work productivity in office employees. Methods: Descriptive cross-sectional study. Spanish university office employees (n = 557) completed a survey measuring socio-demographics, total and domain specific (work and travel) self-reported sitting time, PA (International Physical Activity Questionnaire short version), mental well-being (Warwick-Edinburg Mental Well-Being Scale) and work productivity (Work Limitations Questionnaire). Multivariate linear regression analyses determined associations between the main variables adjusted for gender, age, body mass index and occupation. PA levels (low, moderate and high) were introduced into the model to examine interactive associations. Results: Higher volumes of PA were related to higher mental well-being, work productivity and spending less time sitting at work, throughout the working day and travelling during the week, including the weekends (p < 0.05). Greater levels of sitting during weekends was associated with lower mental well-being (p < 0.05). Similarly, more sitting while travelling at weekends was linked to lower work productivity (p < 0.05). In highly active employees, higher sitting times on work days and occupational sitting were associated with decreased mental well-being (p < 0.05). Higher sitting times while travelling on weekend days was also linked to lower work productivity in the highly active (p < 0.05). No significant associations were observed in low active employees. Conclusions: Employees' PA levels exerts different influences on the associations between sitting time, mental well-being and work productivity. The specific associations and the broad sweep of evidence in the current study suggest that workplace PA strategies to improve the mental well-being and productivity of all employees should focus on reducing sitting time alongside efforts to increase PA.