Breastfeeding after Gestational Diabetes: Does Perceived Benefits Mediate the Relationship?

Introduction. Breastfeeding is recognized as one of the best ways to decrease infant mortality and morbidity. However, women with gestational diabetes mellitus (GDM) may have breastfeeding barriers due to the increased risk of neonatal and pregnancy complications. While the prevalence of GDM is increasing worldwide, it is important to understand the full implications of GDM on breastfeeding outcomes.The current study aims to investigate the (1) direct effect of GDM on breastfeeding duration and (2) indirect effect of GDM on breastfeeding duration through perceived benefits of breastfeeding. Methods. Prospective cohort data from the Infant Feeding and Practices Study II was analyzed (=4,902). Structural equation modeling estimated direct and indirect effects. Results. Perceived benefits of breastfeeding directly influenced breastfeeding duration ( = 0.392, ≤ 0.001). GDM was not directly associated with breastfeeding duration or perceived benefits of breastfeeding. Similarly, GDM did not have an indirect effect on breastfeeding duration through perceived benefits of breastfeeding. Conclusions. Perceived benefits of breastfeeding are an important factor associated with breastfeeding duration. Maternal and child health care professionals should enhance breastfeeding education efforts

Hybridizing two-step growth mixture model and exploratory factor analysis to examine heterogeneity in nonlinear trajectories

Empirical researchers are usually interested in investigating the impacts of baseline covariates have when uncovering sample heterogeneity and separating samples into more homogeneous groups. However, a considerable number of studies in the structural equation modeling (SEM) framework usually start with vague hypotheses in terms of heterogeneity and possible reasons. It suggests that (1) the determination and specification of a proper model with covariates is not straightforward, and (2) the exploration process may be computational intensive given that a model in the SEM framework is usually complicated and the pool of candidate covariates is usually huge in the psychological and educational domain where the SEM framework is widely employed. Following \citet{Bakk2017two}, this article presents a two-step growth mixture model (GMM) that examines the relationship between latent classes of nonlinear trajectories and baseline characteristics. Our simulation studies demonstrate that the proposed model is capable of clustering the nonlinear change patterns, and estimating the parameters of interest unbiasedly, precisely, as well as exhibiting appropriate confidence interval coverage. Considering the pool of candidate covariates is usually huge and highly correlated, this study also proposes implementing exploratory factor analysis (EFA) to reduce the dimension of covariate space. We illustrate how to use the hybrid method, the two-step GMM and EFA, to efficiently explore the heterogeneity of nonlinear trajectories of longitudinal mathematics achievement data.Comment: Draft version 1.6, 08/08/2020. This paper has not been peer reviewed. Please do not copy or cite without author's permissio

Identifying Attrition Phases in Survey Data: Applicability and Assessment Study

Background: Although Web-based questionnaires are an efficient, increasingly popular mode of data collection, their utility is often challenged by high participant dropout. Researchers can gain insight into potential causes of high participant dropout by analyzing the dropout patterns. Objective: This study proposed the application of and assessed the use of user-specified and existing hypothesis testing methods in a novel setting—survey dropout data—to identify phases of higher or lower survey dropout. Methods: First, we proposed the application of user-specified thresholds to identify abrupt differences in the dropout rate. Second, we proposed the application of 2 existing hypothesis testing methods to detect significant differences in participant dropout. We assessed these methods through a simulation study and through application to a case study, featuring a questionnaire addressing decision-making surrounding cancer screening. Results: The user-specified method set to a low threshold performed best at accurately detecting phases of high attrition in both the simulation study and test case application, although all proposed methods were too sensitive. Conclusions: The user-specified method set to a low threshold correctly identified the attrition phases. Hypothesis testing methods, although sensitive at times, were unable to accurately identify the attrition phases. These results strengthen the case for further development of and research surrounding the science of attrition

Diffusivity and Weak Clustering in a Quasi 2D Granular Gas

We present results from a detailed simulation of a quasi-2D dissipative granular gas, kept in a non-condensed steady state via vertical shaking over a rough substrate. This gas shows a weak power-law decay in the tails of its Pair Distribution Functions (PDF's), indicating fractality and therefore a tendency to form clusters over several size scales. This clustering depends monotonically on the dissipation coefficient, and disappears when the sphere-sphere collisions are conservative. Clustering is also sensitive to the packing fraction. This gas also displays the standard nonequilibrium characteristics of similar systems, including non-Maxwellian velocity distributions. The diffusion coefficients are calculated over all the conditions of the simulations, and it is found that diluted gases are more diffusive for smaller restitution coefficients.Comment: 14 pages, 11 figure

Modeling the non-recycled Fermi gamma-ray pulsar population

We use Fermi Gamma-ray Space Telescope detections and upper limits on non-recycled pulsars obtained from the Large Area Telescope (LAT) to constrain how the gamma-ray luminosity L depends on the period P and the period derivative \dot{P}. We use a Bayesian analysis to calculate a best-fit luminosity law, or dependence of L on P and \dot{P}, including different methods for modeling the beaming factor. An outer gap (OG) magnetosphere geometry provides the best-fit model, which is L \propto P^{-a} \dot{P}^{b} where a=1.36\pm0.03 and b=0.44\pm0.02, similar to but not identical to the commonly assumed L \propto \sqrt{\dot{E}} \propto P^{-1.5} \dot{P}^{0.5}. Given upper limits on gamma-ray fluxes of currently known radio pulsars and using the OG model, we find that about 92% of the radio-detected pulsars have gamma-ray beams that intersect our line of sight. By modeling the misalignment of radio and gamma-ray beams of these pulsars, we find an average gamma-ray beaming solid angle of about 3.7{\pi} for the OG model, assuming a uniform beam. Using LAT-measured diffuse fluxes, we place a 2{\sigma} upper limit on the average braking index and a 2{\sigma} lower limit on the average surface magnetic field strength of the pulsar population of 3.8 and 3.2 X 10^{10} G, respectively. We then predict the number of non-recycled pulsars detectable by the LAT based on our population model. Using the two-year sensitivity, we find that the LAT is capable of detecting emission from about 380 non-recycled pulsars, including 150 currently identified radio pulsars. Using the expected five-year sensitivity, about 620 non-recycled pulsars are detectable, including about 220 currently identified radio pulsars. We note that these predictions significantly depend on our model assumptions.Comment: 26 pages, 10 figures, Accepted by ApJ on 8 September 201

Diagnostic accuracy of X-ray versus CT in COVID-19: a propensity-matched database study

Objectives: To identify the diagnostic accuracy of common imaging modalities, chest X-ray (CXR) and CT, for diagnosis of COVID-19 in the general emergency population in the UK and to find the association between imaging features and outcomes in these patients. Design: Retrospective analysis of electronic patient records. Setting Tertiary: academic health science centre and designated centre for high consequence infectious diseases in London, UK. Participants 1198 patients who attended the emergency department with paired reverse transcriptase PCR (RT-PCR) swabs for SARS-CoV-2 and CXR between 16 March and 16 April 2020. Main outcome measures: Sensitivity and specificity of CXR and CT for diagnosis of COVID-19 using the British Society of Thoracic Imaging reporting templates. Reference standard was any RT-PCR positive naso-oropharyngeal swab within 30 days of attendance. ORs of CXR in association with vital signs, laboratory values and 30-day outcomes were calculated. Results: Sensitivity and specificity of CXR for COVID-19 diagnosis were 0.56 (95% CI 0.51 to 0.60) and 0.60 (95% CI 0.54 to 0.65), respectively. For CT scans, these were 0.85 (95% CI 0.79 to 0.90) and 0.50 (95% CI 0.41 to 0.60), respectively. This gave a statistically significant mean increase in sensitivity with CT of 29% (95% CI 19% to 38%, p<0.0001) compared with CXR. Specificity was not significantly different between the two modalities. CXR findings: were not statistically significantly or clinically meaningfully associated with vital signs, laboratory parameters or 30-day outcomes. Conclusions: Computed tomography has substantially improved diagnostic performance over CXR in COVID-19. CT should be considered in the initial assessment for suspected COVID-19 instead of CXR if capacity allows and balanced against radiation exposure risk

TIME ON THE MARKET OF RESIDENTIAL CONDOMINIUM UNITS WITH PRE-SALE ARRANGEMENT IN COLOMBO DISTRICT

The purpose of this paper is to study the time on market (TOM) for residential condominium units under pre sales arrangements and what key factors drive that TOM. The contextual understanding of previous studies on TOM for residential properties confined for properties sold either in the secondary market or properties where construction is completed. This study focuses on the relationships among TOM, listed price, and basic property characteristics of residential condominium units sold under the provisional condominium plan in Colombo, Sri Lanka. Following non-probability sampling technique, this study examines TOM of 189 pre-sale residential condominium units in Colombo district which came into market between 2016 January to 2019 January. Developers were approached to collect required data such as transaction price, transaction date, final listed date listed price, number of bedrooms, number of bathrooms, floor area, floor level, construction completion, discounting rates likewise. Data analysis followed descriptive statistics, Pearson Correlation, and multiple regression model. The analysis highlighted that from January-2016 to January-2019, TOM of provisional residential condominiums of Colombo varied from 12.76 to 5.51 months. The results further highlighted that the TOM of a pre-sale provisional residential condominium unit is a function of floor area, number of bathrooms, level of the unit, construction completion &amp; discount rate. The study highlights that during the period considered, the floor area units of 744sqft at the initial stage of construction with a discount rate between 10% to 20% from the listed price can predicted to have the lowest TOM.. Keywords: Time on the Market; Pre-sale; Residential Condominium Units; Listed Price; TransactionPrice

How to ensure success in environmental, social, and governance efforts

Businesses want to address environmental, social, and governance (ESG) challenges but often fail. While organisations’ policies may be well-meaning, they often become decoupled from actual practices. Organisational efforts at change continue to focus on crafting “new and better” policies, but without commensurate attention to the rest of the organisational landscape, which includes internal and external stakeholders. Sukhbir Sandhu, Carol T Kulik, Sanjeewa S Perera, and Sarah A Jarvis developed a framework that works as a roadmap to ensure that ESG change efforts succeed

DNA adducts in human urinary bladder and other tissues.

Tobacco smoking is associated with an increased risk of cancer in a number of organs, including bladder and lung. Tobacco smoke contains at least 50 known chemical carcinogens that exert their biological effects through their covalent binding to cellular DNA. Examining human DNA for the presence of altered nucleotides is a means of monitoring exposure to genotoxic chemicals. DNA isolated from 73 human bladder biopsies has been analyzed by 32P-postlabeling for the presence of aromatic/hydrophobic adducts. Butanol extraction of DNA digests resulted in up to a 3-fold greater recovery of adducts than nuclease P1 digestion. Among 16 nonsmokers, adduct levels were in the range 3.2-20.8/10(8) nucleotides (mean 9.7). Eight ex-smokers had values in the range 2.6-12.3 (mean 7.1). Thirteen smokers had adduct levels between 1.3 and 26.7 adducts/10(8) nucleotides (mean 9.5, not different from nonsmokers). Six cigar smokers had higher levels of adducts (mean 12.1, range 7.3-15.0), but pipe smokers did not (five samples, mean 8.6, range 2.9-12.7). A further 8 samples from nonsmokers and 17 from smokers were examined in more detail. Although most of the DNA binding appears not to be smoking related, the levels of one adduct were found to be on average 2-fold higher in smokers (p < 0.005, one-tailed t test). Studies on tissues of the respiratory tract demonstrate a correlation between DNA adduct levels and exposure to tobacco smoke. Evidence to date on the influence of smoking on adducts in peripheral blood cells is equivocal; some studies demonstrate a significant effect, whereas others do not.(ABSTRACT TRUNCATED AT 250 WORDS

How to ensure success in environmental, social, and governance efforts

Businesses want to address environmental, social, and governance (ESG) challenges but often fail. While organisations’ policies may be well-meaning, they often become decoupled from actual practices. Organisational efforts at change continue to focus on crafting “new and better” policies, but without commensurate attention to the rest of the organisational landscape, which includes internal and external stakeholders. Sukhbir Sandhu, Carol T Kulik, Sanjeewa S Perera, and Sarah A Jarvis developed a framework that works as a roadmap to ensure that ESG change efforts succeed