Random Slope Research Articles

Utilization of reproductive health services among undergraduate regular class students in Assosa University, BGRS: a comparison among three varieties of multilevel binary logistic regression models

IntroductionReproductive health service (RHS) helps for people to have a delighted and safe sex through their life journey. It enables especially for women to go safely through pregnancy and childbirth and provide couples with the best chance of having a healthy infant. Therefore, this study aimed to identify the significant determinants of RHS utilization among undergraduate regular class students in Assosa University by using advanced methodology.MethodsWe used cross-sectional study design to collect RHS data from 362 students in Assosa University from 5 to 16, may 2021. These students were selected using stratified random sampling technique. We also used cross-tabulation to summarize the extents of RHS utilization across all predictors in terms of percentage and three varieties of multilevel binary logistic regression model to model the determinants of RHS.Results42.27% of undergraduate regular class students in Assosa University utilize at least one type of RHS during their time at Assosa University whereas, 57.73% of undergraduate regular class students in this University are not utilized it. Among three varieties of multilevel binary logistic regression models, the random slopes two-level model was selected as a best fitted model for the datasets. At 5% level of significance, awareness about RHS, gender, preference of service fees and student’s monthly average income were significant predictor variables in this model. In addition, the covariates; age, gender and preference of service fees have a significant random effects on utilization of RHS across all colleges/school.ConclusionStudents who; preferred service fee as usual rate, have awareness about RHS, are females and have high monthly average income were more likely to utilize RHS. RHS utilization among undergraduate regular students in Assosa University is likely to increase more effectively with interventions that address these factors.

#376 Self-efficacy, social support and hemodiafiltration are independently associated with better Self-Reported Health Status over time

Abstract Background and Aims Patients with kidney disease receiving dialysis are a highly vulnerable population. Psychosocial determinants of Self-Efficacy (SE) and Social Support (SS) have been suggested as potentially important outcomes for people with end stage kidney disease. We investigated whether these variables could explain differences in Health-Related Quality of Life (HRQL) outcome domains over time independently or in interaction with treatment modality of high-flux hemodialysis (HD) versus high-dose hemodiafiltration (HDF). Method HRQL in 1264 participants from the international multi-centre, prospective, randomized, open label, controlled CONVINCE trial were assessed, using screening and quarterly follow-up data up to 24 months. Measures included the MOS Social Support Scale, General Self-Efficacy Scale, and PROMIS short forms for fatigue, physical function, pain interference and intensity, sleep disturbance, anxiety, cognitive function, depression, ability to participate in social roles. SE, SS and interactions with modality were included as independent variables and HRQL domains as dependent variables in a linear mixed effects model with random intercept and slope for SE and SS. Results Participants were 20-92 (M=62.33, SD=13.50) years old, 62.9% were male. Linear mixed effect regression models showed significant main effects for self-efficacy (β = −0.15-1.09, all p < .0001) on all HRQL domains. Significant SE × time interactions were found for all variables (β = −0.02-0.04, all p < .01) but pain intensity. Main effects for SS were found for cognition (β = 0.31, p = .00) and sleep disturbance (β = −0.21, p = .00). A significant SS × time interaction was found for anxiety (β = 0.01, p = .02) and sleep disturbance (β = 0.02, p = .00). Plots for these associations can be found in Figs 1 and 2. Marginal means were plotted and 25%, 50% and 75% quantiles were used to separate the different levels of SE and SS. There were no significant interactions between treatment modality (HDF vs. HD) and SE/SS. Conclusion Our results indicate that higher SE and better SS are independently associated with higher HRQL of dialysis patients over time, showing no significant interactions with HDF. SE had the largest effects on HRQL. This bears the chance to develop targeted psychosocial interventions to improve health outcomes when introducing new therapy options for patients. However, patients achieving higher HRQL over the course of the treatment may also experience higher SE and SS over time. Future research should include longitudinal assessments on these psychosocial determinants to evaluate their effect further.

Intersectional inequalities in the transition to grandparenthood and cognitive functioning: A longitudinal Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA).

In aging societies, more people become vulnerable to experiencing cognitive decline. Simultaneously, the role of grandparenthood is central for older adults and their families. Our study investigates inequalities in the level and trajectories of cognitive functioning among older adults, focusing on possible intersectional effects of social determinants and grandparenthood as a life course transition that may contribute to delaying cognitive decline. Using longitudinal data from the Survey of Health, Ageing and Retirement in Europe, we analyzed a sample of 19,953 individuals aged 50-85 without grandchildren at baseline. We applied Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy to investigate variation in cognitive functioning across 48 intersectional strata, defined by sex/gender, migration, education, and occupation. We allowed the impact of becoming a grandparent on cognitive functioning trajectories to vary across strata by including random slopes. Intersectional strata accounted for 17.43% of the overall variance in cognitive functioning, with most of the stratum-level variation explained by additive effects of the stratum-defining characteristics. Transition to grandparenthood was associated with higher cognitive functioning, showing a stronger effect for women. Stratum-level variation in the grandparenthood effect was modest, especially after accounting for interactions between grandparenthood and the stratum-defining variables. This study highlights the importance of social determinants for understanding heterogeneities in older adults' level of cognitive functioning and its association with the transition to grandparenthood. Cumulative disadvantages negatively affect cognitive functioning, hence adopting an intersectional lens is useful to decompose inequalities and derive tailored interventions to promote equal healthy aging.

Spatial Heterogeneity and Subjective Wellbeing: Exploring the Role of Social Capital in Metropolitan Areas Using Multilevel Modelling

The role of social capital, the social networks that influence human wellbeing has been explored by empirical research in the US and Europe, however no study so far has undertaken a systematic investigation of the impact of the various dimensions of social capital in metropolitan areas. Addressing this gap in knowledge can have practical and policy-oriented implications by contributing to more informed decision-making processes in metro areas, better targeted interventions and ultimately an improved quality of life for residents. This study adopts a multi-level modelling approach to investigate life satisfaction and social capital heterogeneity within metropolitan areas in Australia. Our dataset was collected by the Household Income and Labour Dynamics in Australia survey and includes almost 4,000 individual respondents. Our results show that social trust, social engagement and connection, and a psychological sense of community measured at an individual level have a strong positive influence on individual life satisfaction. Conversely negative individual perceptions about neighbourhood criminality and shabbiness are associated with a lower level of life satisfaction. The application of a model using random slope coefficients for social capital variables suggests that most of the spatial heterogeneity between census districts is explained by between-individual (compositional) variations, rather than contextual differences. Only social connection and engagement appeared to have a distinctive contextual influence. These findings confirm the importance of social inclusion in enhancing wellbeing for everyone and may inform social policy on how to promote social networks in urban areas by all levels of government.

Unveiling ecological/evolutionary insights in HIV viral load dynamics: Allowing random slopes to observe correlational changes to CpG-contents and other molecular and clinical predictors

In the context of infectious diseases, the dynamic interplay between ever-changing host populations and viral biology demands a more flexible modeling approach than common fixed correlations. Embracing random-effects regression models allows for a nuanced understanding of the intricate ecological and evolutionary dynamics underlying complex phenomena, offering valuable insights into disease progression and transmission patterns. In this article, we employed a random-effects regression to model an observed decreasing median plasma viral load (pVL) among individuals with HIV in Mexico City during 2019–2021. We identified how these functional slope changes (i.e. random slopes by year) improved predictions of the observed pVL median changes between 2019 and 2021, leading us to hypothesize underlying ecological and evolutionary factors. Our analysis involved a dataset of pVL values from 7325 ART-naïve individuals living with HIV, accompanied by their associated clinical and viral molecular predictors. A conventional fixed-effects linear model revealed significant correlations between pVL and predictors that evolved over time. However, this fixed-effects model could not fully explain the reduction in median pVL; thus, prompting us to adopt random-effects models. After applying a random effects regression model—with random slopes and intercepts by year—, we observed potential "functional changes" within the local HIV viral population, highlighting the importance of ecological and evolutionary considerations in HIV dynamics: A notably stronger negative correlation emerged between HIV pVL and the CpG content in the pol gene, suggesting a changing immune landscape influenced by CpG-induced innate immune responses that could impact viral load dynamics. Our study underscores the significance of random effects models in capturing dynamic correlations and the crucial role of molecular characteristics like CpG content. By enriching our understanding of changing host-virus interactions and HIV progression, our findings contribute to the broader relevance of such models in infectious disease research. They shed light on the changing interplay between host and pathogen, driving us closer to more effective strategies for managing infectious diseases. Significance of the studyThis study highlights a decreasing trend in median plasma viral loads among ART-naïve individuals living with HIV in Mexico City between 2019 and 2021. It uncovers various predictors significantly correlated with pVL, shedding light on the complex interplay between host-virus interactions and disease progression. By employing a random-slopes model, the researchers move beyond traditional fixed-effects models to better capture dynamic correlations and evolutionary changes in HIV dynamics. The discovery of a stronger negative correlation between pVL and CpG content in HIV-pol sequences suggests potential changes in the immune landscape and innate immune responses, opening avenues for further research into adaptive changes and responses to environmental shifts in the context of HIV infection. The study's emphasis on molecular characteristics as predictors of pVL adds valuable insights to epidemiological and evolutionary studies of viruses, providing new avenues for understanding and managing HIV infection at the population level.

Identifying Population-Level and Within-Hospital Disparities in Surgical Care.

The lack of consensus on equity measurement and its incorporation into quality-assessment programs at the hospital and system levels may be a barrier to addressing disparities in surgical care. This study aimed to identify population-level and within-hospital differences in the quality of surgical care provision. The analysis included 657 NSQIP participating hospitals with more than 4 million patients (2014 to 2018). Multilevel random slope, random intercept modeling was used to examine for population-level and in-hospital disparities. Disparities in surgical care by Area Deprivation Index (ADI), race, and ethnicity were analyzed for 5 measures: all-case inpatient mortality, all-case urgent readmission, all-case postoperative surgical site infection, colectomy mortality, and spine surgery complications. Population-level disparities were identified across all measures by ADI, 2 measures for Black race (all-case readmissions and spine surgery complications), and none for Hispanic ethnicity. Disparities remained significant in the adjusted models. Before risk adjustment, in all measures examined, within-hospital disparities were detected in: 25.8% to 99.8% of hospitals for ADI, 0% to 6.1% of hospitals for Black race, and 0% to 0.8% of hospitals for Hispanic ethnicity. After risk adjustment, in all measures examined, less than 1.1% of hospitals demonstrated disparities by ADI, race, or ethnicity. After risk adjustment, very few hospitals demonstrated significant disparities in care. Disparities were more frequently detected by ADI than by race and ethnicity. The lack of substantial in-hospital disparities may be due to the use of postoperative metrics, small sample sizes, the risk adjustment methodology, and healthcare segregation. Further work should examine surgical access and healthcare segregation.

How the association of time pressure with work engagement and affect depends on workers’ sensation seeking: a daily diary study

ABSTRACT Drawing upon the challenge-hindrance framework and activation theory, this study investigated the quadratic relationship of daily time pressure with daily work engagement and daily affect. Moreover, the moderating role of sensation seeking in these relationships was investigated. Over two consecutive work weeks (10 work days), participants answered questionnaires on their time pressure, work engagement, positive affect, and negative affect. Data of 133 workers were analysed using hierarchical linear modelling. Random slopes analyses revealed a linear main effect of time pressure on work engagement after controlling for other variables. A linear main effect was also identified for negative affect. For work engagement and negative affect, cross-level interactions of time pressure and sensation seeking were found. The relationship between time pressure and work engagement was positive for high sensation seekers, whereas no relationship was found for low sensation seekers. Moreover, the results revealed a positive linear relationship between time pressure and negative affect for low sensation seekers and a U-shaped relationship for high sensation seekers. The findings contribute to the ongoing discussion on the challenging and hindering effects of time pressure, highlighting that it may depend on employees’ sensation seeking disposition whether time pressure acts as a challenge or a hindrance demand.

Annihilating Branching Brownian Motion

Abstract We study an interacting system of competing particles on the real line. Two populations of positive and negative particles evolve according to branching Brownian motion. When opposing particles meet, their charges neutralize and the particles annihilate, as in an inert chemical reaction. We show that, with positive probability, the two populations coexist and that, on this event, the interface is asymptotically linear with a random slope. A variety of generalizations and open problems are discussed.

A joint penalized spline smoothing model for the number of positive and negative COVID-19 tests.

One of the key tools to understand and reduce the spread of the SARS-CoV-2 virus is testing. The total number of tests, the number of positive tests, the number of negative tests, and the positivity rate are interconnected indicators and vary with time. To better understand the relationship between these indicators, against the background of an evolving pandemic, the association between the number of positive tests and the number of negative tests is studied using a joint modeling approach. All countries in the European Union, Switzerland, the United Kingdom, and Norway are included in the analysis. We propose a joint penalized spline model in which the penalized spline is reparameterized as a linear mixed model. The model allows for flexible trajectories by smoothing the country-specific deviations from the overall penalized spline and accounts for heteroscedasticity by allowing the autocorrelation parameters and residual variances to vary among countries. The association between the number of positive tests and the number of negative tests is derived from the joint distribution for the random intercepts and slopes. The correlation between the random intercepts and the correlation between the random slopes were both positive. This suggests that, when countries increase their testing capacity, both the number of positive tests and negative tests will increase. A significant correlation was found between the random intercepts, but the correlation between the random slopes was not significant due to a wide credible interval.

169 The impact of corn-based fiber on intestinal morphology and disaccharidase activity in growing pigs

Abstract Dietary changes can modify gastrointestinal architecture and function; thus, our experimental objective was to evaluate how different insoluble corn-based fiber sources (CBF) impact intestinal morphology and brush-border disaccharidases. Two replicates of 28 gilts [26.7 ± 2.5 kg body weight (BW); PIC800 x Camborough; n = 56], were randomly assigned to one of 7 semi-synthetic diets, including a control (CTL) diet with a formulated total dietary fiber (TDF) value of < 1% and 6 diets with a CBF replacing 30% of the corn starch in CTL: dehulled degermed corn (DHDG; TDF = 1.09%), ground corn (COR; TDF = 3.24%), high protein dried distillers grains (HP; TDF = 8.79%), dried distiller’s grains (DDGS; TDF = 9.35%), corn gluten meal (CGM; TDF = 9.88%), and corn bran (BRN; TDF = 13.15%). Pigs were individually housed, and limit-fed 2.4 times maintenance. On d 31, pigs were necropsied, and duodenum, jejunum, ileum, cecum, and colon tissue were collected for histological analysis. Data were analyzed as a linear mixed model with treatment as a fixed effect, replicate as a random slope or fixed effect, where appropriate, using the mixed procedure of SAS. In the duodenum, DHDG, COR, and CGM had the least (P = 0.04) levels of maltase production. Duodenal sucrase production was least in BRN and HP, and DHDG had the greatest (P = 0.04). Duodenal villi height was shortest (P < 0.01) in CTL and BRN compared with HP, DDGS, and CGM, which had the tallest (P < 0.01; Table). Similarly, CTL and BRN had the shallowest duodenal crypt depth (P < 0.01) and tended (P = 0.08) to have a lesser duodenal villus:crypt ratio compared with the other treatments. There were no differences (P > 0.10) among treatments for ileal sucrase or lactase production, but maltase production was greatest in CTL, DDGS, and CGM (P = 0.03). Relative to CTL and BRN, gilts fed HP, DDGS, and CGM, had the tallest (P = 0.01) villus height in the ileum. However, neither ileal villi:crypt ratio nor crypt depth differed (P > 0.10). Cecal crypt depth for BRN increased 32% compared with CTL (P < 0.01). Cecal crypt width was narrowest (P < 0.01) in CTL and DHDG and widest in HP, DDGS, CGM, and CB (P < 0.01). Colon crypt width was narrowest (P < 0.01) in CTL and DHDG and widest in DDGS, CGM, and CB (P < 0.01). Collectively, these data demonstrate that different fiber types have a significant impact on intestinal morphology and disaccharidase production in the growing pig.

253 The influence of corn-based fiber on digesta short chain fatty acid composition and pH in growing pigs

Abstract Pigs can obtain energy from fibrous feedstuffs through a symbiotic relationship with their gastrointestinal microbiome, which results in the production of metabolites, such as short chain fatty acids (SCFA). An experiment was conducted with the objective of investigating how different insoluble corn-based fiber sources influence changes in SCFA composition along the digestive tract of growing pigs. Two replicates of 28 gilts [n = 56; initial body weight (BW) = 26.7 ± 2.5 kg; PIC800 x Camborough], were randomly assigned to one of 7 semi-synthetic diets. Dietary treatments included a control (CTL) diet with a formulated total dietary fiber (TDF) value of < 1% and 6 diets with a CBF replacing 30% of the corn starch in CTL: dehulled degermed corn (DHDG; TDF = 1.09%), ground corn (COR; TDF = 3.24%), high protein dried distiller’s grains (HP; TDF = 8.79%), dried distiller’s grains (DDGS; TDF = 9.35%), corn gluten meal (CGM; TDF = 9.88%), and corn bran (BRN; TDF = 13.15%). Pigs were individually housed, and limit-fed at 2.4 times maintenance. On d 31, pigs were necropsied, and ileal, cecal, and colonic digesta were collected for immediate SCFA analysis and stomach, jejunal, ileal, and cecal digesta pH was measured. Data were analyzed as a linear mixed model with treatment as a fixed effect, replicate as a random slope or fixed effect, where appropriate, using the mixed procedure of SAS. There were no differences in jejunal nor stomach pH (P ≥ 0.51). Ileal pH was greatest (P = 0.01) in HP, DDGS, and CGM diets. Cecal pH was greatest (P < 0.01) in the BRN diet and lowest in COR and HP. Molar proportions of ileal SCFAs did not differ (P ≥ 0.74) among treatments. In the cecum, molar proportions of butyrate production did not differ (P = 0.74). Cecal acetate proportions were less (P = 0.03) in CTL, COR, and HP compared with all other treatments (51.54, 61.09, 51.92, 52.89, 59.16, 63.87, and 63.32%, for CTL, DHDG, COR, HP, DDGS, CGM, and BRN, respectively). Cecal propionate proportions were greatest (P = 0.01) in BRN and least in DHDG, COR, and CGM (30.85, 27.67, 27.67, 30.91, 30.47, 24.03, and 35.86% for CTL, DHDG, COR, HP, DDGS, CGM, and BRN, respectively). Relative to CTL, isobutyrate proportions in the cecum for COR, HP, and DDGS were reduced by 65%, 52%, and 53%, respectively (P < 0.01). In the colon, there were no differences in molar proportions of acetate, butyrate, nor isobutyrate (P ≥ 0.254). However, HP and CGM had a smaller (P = 0.04) proportion of propionate in the colon and COR and BRN had the greatest proportion of colonic propionate (33.92, 29.68, 38.41, 25.3, 30.00, 26.76, and 37.94% for CTL, DHDG, COR, HP, DDGS, CGM, and BRN, respectively). Collectively, the different fibrous components of CBFs can influence SCFA proportions in the growing pig.

Prenatal ochratoxin A exposure, birth outcomes and infant growth in rural Burkina Faso: A human biomonitoring sub-study from the MISAME-III trial

Mycotoxin exposure during pregnancy has been associated with adverse birth outcomes and poor infant growth in low- and middle-income countries. We assessed multiple biomarkers and metabolites of exposure to mycotoxins during pregnancy and their associations with birth outcomes and infant growth in 305 pregnant participants, between 30 and 34 completed weeks of gestation, in rural Burkina Faso. In this study, whole blood microsamples were analyzed for mycotoxin concentrations using ultra-performance liquid chromatography coupled to tandem mass spectrometry. Unadjusted and adjusted associations between mycotoxin exposure, and birth outcomes and infant growth at 6 months were estimated using linear regression models for continuous outcomes and linear probability models with robust variance estimation for binary outcomes. Infant growth trajectories from birth to 6 months were compared by exposure status using mixed-effects models with random intercept for the individual infant and random slope for the infant's age. Ochratoxin A (OTA) exposure was detected in 50.8 % of the study participants, with aflatoxin G1, aflatoxin M1, cyclopiazonic acid, deoxynivalenol and T-2-toxin being detected in the range of 0.33 % and 2.31 % of the population. We found no statistically significant (p ≥ 0.05) associations between OTA exposure, and birth outcomes and infant growth. Despite this, the findings indicate a significant presence of ochratoxin A among pregnant participants. Public health policies and nutrition-sensitive interventions must ensure that OTA exposure is reduced in Burkina Faso.

Negative variance components and intercept-slope correlations greater than one in magnitude: How do such "non-regular" random intercept and slope models arise, and what should be done when they do?

Statistical models with random intercepts and slopes (RIAS models) are commonly used to analyze longitudinal data. Fitting such models sometimes results in negative estimates of variance components or estimates on parameter space boundaries. This can be an unlucky chance occurrence, but can also occur because certain marginal distributions are mathematically identical to those from RIAS models with negative intercept and/or slope variance components and/or intercept-slope correlations greater than one in magnitude. We term such parameters "pseudo-variances" and "pseudo-correlations," and the models "non-regular." We use eigenvalue theory to explore how and when such non-regular RIAS models arise, showing: (i) A small number of measurements, short follow-up, and large residual variance increase the parameter space for which data (with a positive semidefinite marginal variance-covariance matrix) are compatible with non-regular RIAS models. (ii) Non-regular RIAS models can arise from model misspecification, when non-linearity in fixed effects is ignored or when random effects are omitted. (iii) A non-regular RIAS model can sometimes be interpreted as a regular linear mixed model with one or more additional random effects, which may not be identifiable from the data. (iv) Particular parameterizations of non-regular RIAS models have no generality for all possible numbers of measurements over time. Because of this lack of generality, we conclude that non-regular RIAS models can only be regarded as plausible data-generating mechanisms in some situations. Nevertheless, fitting a non-regular RIAS model can be acceptable, allowing unbiased inference on fixed effects where commonly recommended alternatives such as dropping the random slope result in bias.

Generalized Linear Mixed Effects Modeling (GLMM) of Functional Analysis Graphical Construction Elements on Visual Analysis

Multielement designs are the quintessential design tactic to evaluate outcomes of a functional analysis in applied behavior analysis. Protecting the credibility of the data collection, graphing, and visual analysis processes from a functional analysis increases the likelihood that optimal intervention decisions are made for individuals. Time-series graphs and visual analysis are the most prevalent method used to interpret functional analysis data. The current project included two principal aims. First, we tested whether the graphical construction manipulation of the x-to-y axes ratio (i.e., data points per x- axis to y-axis ratio [DPPXYR]) influenced visual analyst’s detection of a function on 32 multielement design graphs displaying functional analyses. Second, we investigated the alignment between board certified behavior analysts (BCBAs; N = 59) visual analysis with the modified visual inspection criteria (Roane et al., Journal of Applied Behavior Analysis, 46, 130-146, 2013). We found that the crossed GLMM that included random slopes, random intercepts, and did not include an interaction effect (AIC = 1406.1, BIC = 1478.2) performed optimally. Second, alignment between BCBAs decisions and the MVI appeared to be low across data sets. We also leveraged current best practices in Open Science for raw data and analysis transparency.

Momentary stress-induced food craving: An ecological momentary assessment study comparing perceived interpersonal and non-interpersonal stressors.

Daily-life stressors and food cravings are dynamic and vary within and across persons. Some evidence suggests interpersonal stressors increase appetite. However, little is known about the association of food craving with different types of stressors at the momentary level in the general population. We aimed to explore the momentary relationships between daily-life stressful events and food craving in a non-clinical community sample, and to compare the associations with food craving when the most stressful event was perceived as interpersonal versus non-interpersonal. We used ecological momentary assessment (EMA) to collect reports on the most stressful event, perceived stressor type, stressor appraisal, and food craving from 123 adults three times a day scheduled at fixed intervals over 10 days. Mixed effects random intercepts and slopes models examined the within- and between-person associations. Experiencing a stressor was significantly positively associated with within-person food craving at the same measurement. No differences in momentary food craving were found when the most stressful event was perceived as interpersonal or non-interpersonal (within-person level). However, frequently reporting the most stressful event as interpersonal (vs. non-interpersonal) was positively associated with food craving across the study (between-person level), particularly when the stressor was appraised as more unpleasant. Daily-life stressors were associated with momentary food craving. Individuals who generally perceived interpersonal stressors as their most stressful event tended to experience food cravings. Future research could further investigate the role of interpersonal stressors as a factor for overeating in daily life and the potential benefits of stress management in interventions.

Stability of neurodevelopmental trajectories in moderately late and early preterm children born 15 years apart.

Neurodevelopmental trajectories of preterm children may have changed due to changes in care and in society. We aimed to compare neurodevelopmental trajectories in early and moderately late preterm children, measured using the Developmental (D)-score, in two cohorts born 15 years apart. We included early preterm and moderately late preterm children from two Dutch cohorts (LOLLIPOP, 2002-2003 and ePREM, 2016-2017). ePREM counterparts were matched to LOLLIPOP participants by gestational age and sex. D-score trajectories were summarized by a multilevel model with random intercepts and random slopes, and multigroup analyses were used to test if the intercepts and slopes differed across cohorts. We included 1686 preterm children (1071 moderately late preterm, 615 early preterm) from LOLLIPOP, and matched these with 1686 ePREM counterparts. The neurodevelopmental trajectories of the two cohorts were mostly similar. For early preterm children, we found no statistically significant differences. For moderately late preterm children, both the intercept (43.0 vs. 42.3, p < 0.001) and slope (23.5 vs. 23.9, p = 0.002) showed some, but only clinically minor, differences. Developmental trajectories, measured using the D-score, in the first four years of life are comparable and stable across a period of 15 years for both early and moderately late preterm children. Neurodevelopmental trajectories are similar for early and moderately late preterm children born 15 years apart and thus seem quite stable in time. The validated Developmental score visualizes these trajectories based on developmental milestone attainment Because of its stability over time, the Developmental score trajectory may aid clinicians in neurodevelopmental assessment of preterm children as this simplifies monitoring and interpretation, similar to a growth chart.

Comparing various Bayesian random‐effects models for pooling randomized controlled trials with rare events

AbstractThe meta‐analysis of rare events presents unique methodological challenges owing to the small number of events. Bayesian methods are often used to combine rare events data to inform decision‐making, as they can incorporate prior information and handle studies with zero events without the need for continuity corrections. However, the comparative performances of different Bayesian models in pooling rare events data are not well understood. We conducted a simulation to compare the statistical properties of four parameterizations based on the binomial‐normal hierarchical model, using two different priors for the treatment effect: weakly informative prior (WIP) and non‐informative prior (NIP), pooling randomized controlled trials with rare events using the odds ratio metric. We also considered the beta‐binomial model proposed by Kuss and the random intercept and slope generalized linear mixed models. The simulation scenarios varied based on the treatment effect, sample size ratio between the treatment and control arms, and level of heterogeneity. Performance was evaluated using median bias, root mean square error, median width of 95% credible or confidence intervals, coverage, Type I error, and empirical power. Two reviews are used to illustrate these methods. The results demonstrate that the WIP outperforms the NIP within the same model structure. Among the compared models, the model that included the treatment effect parameter in the risk model for the control arm did not perform well. Our findings confirm that rare events meta‐analysis faces the challenge of being underpowered, highlighting the importance of reporting the power of results in empirical studies.

E-cigarette use reasons and associated e-cigarette use dependence among college students: A longitudinal examination

ObjectivePrevious studies have established an understanding of reasons for e-cigarette use and associated e-cigarette use patterns such as use frequency, yet the critical extension to associated e-cigarette dependence outcome remains under-researched. This study used longitudinal data to examine whether the reasons for e-cigarette use predict a higher/lower level of e-cigarette dependence. MethodsThis study recruited college students who were current e-cigarette users from Fall 2019 to Fall 2020 (four semesters) at three public universities in the Midwest and South of the U.S. Those who participated for at least two semesters were included (N = 366). Data were collected using a structured questionnaire. E-cigarette use dependence was assessed using the Penn State Electronic Cigarette Dependence Index. A linear mixed model with a random intercept and a random slope was conducted to examine the longitudinal association between reasons for e-cigarette use and dependence, controlling for demographics and other covariates. ResultsParticipants who used e-cigarettes for relaxation (β = 0.63, p < 0.05) and due to their good taste (β = 0.63, p < 0.05) had a higher level of e-cigarette dependence. Participants using e-cigarettes for experimental purposes had a lower level of e-cigarette dependence (β = -1.21, p < 0.01). ConclusionsThese findings highlight the importance of addressing e-cigarette use reasons and their relationship to e-cigarette dependence. Prevention and intervention efforts aimed at developing more effective strategies should consider the various e-cigarette use reasons associated with dependence risks, such as enhancing awareness of the use dependence risk related to good taste of e-cigarettes and use for relaxation, as well as incorporating early screenings for use.

It’s time for change: inequities and determinants of health-related quality of life among gender and sexually diverse young people in Australia

PurposeThis study was guided by three research aims: firstly, to examine the longitudinal trends of health-related quality of life (HR-QoL) among gender and sexuality diverse (LGBTQA2S+) young people through adolescence (ages 14–19); secondly, to assess longitudinal associations between poor mental health and HR-QoL among LGBTQA2S+ young people through adolescence; and thirdly, to examine differences in HR-QoL among LGBTQA2S+ young people during early adolescence (ages 14 and 15) depending on select school-, peer-, and parent-level factors.MethodsThis study used three of nine available waves of data from a large population-level, probability sample-based, longitudinal cohort study, namely the K′ cohort: children aged 4–5 years old at time of study enrolment followed-up biennially (~ 61% retention rate). HR-QoL weighted means and standard deviations were calculated using Child Health Utility 9D (CHU-9D) scores for LGBTQA2S+ participants at ages 14 and 15 (Wave 6), ages 16 and 17 (Wave 7), and ages 18 and 19 (Wave 8). To strategically identify policy-relevant modifiable behavioural factors suitable for prevention and early intervention, non-parametric Wilcoxon signed-rank tests tested differences in mean CHU-9D ranks at ages 14 and 15 (Wave 6) between groups (gender identity: trans vs. cis; identity-level sexuality: gay, lesbian, bisexual, or other diverse sexuality vs. heterosexual; group-level sexuality: sexually diverse vs. not sexually diverse) and selected school factors (school acceptance, belonging, freedom of expression), peer factors (peer relationship quality, trust, respect), and family factors (parental acceptance, understanding, trust), with Hedge’s g correction statistics computed for effect sizes. Longitudinal associations between gender, sexuality, and poor mental health (depressive symptoms, anxiety, symptoms, self-harm thoughts/behaviour, and suicidal thoughts/behaviour) and HR-QoL were tested using mixed-effects models with random intercepts and random slopes for nested clustering (participants within postcodes).ResultsHR-QoL disparities disproportionately affecting LGBTQA2S+ groups relative to their cisgender, heterosexual peers, were well-established by age 14 to 15 relatively steeper reductions in HR-QoL were observed throughout adolescence among all LGBTQA2S+ groups, with HR-QoL widening the most for trans participants. Poor mental health was significantly associated with HR-QoL declines. LGBTQA2S+ participants with positive school- and parent factors related to feelings of acceptance, belonging, and freedom of self-expression, reported significantly higher HR-QoL during early adolescence.ConclusionEvidence-based public health policy responses are required to address the dire HR-QoL inequities among LGBTQA2S+ young people, particularly trans young people. Prioritising the promotion of school- and family-based interventions which foster LGBTQA2S+ inclusivity, acceptance, and a sense of belonging from early adolescence through young adulthood, represents a feasible, evidence-based, and cost-effective response to address these HR-QoL disparities

Urban structure types and students’ academic performance

ABSTRACT In this study, we propose a novel approach for estimating the relationship between neighborhood characteristics and students’ academic performance. We propose the concept of urban morphology by Urban Structure Types (USTs). USTs are spatial indicators that describe the urban system through its physical, environmental, and functional characteristics. Our academic performance data includes 344,175 students from 256 public schools in the Federal District (FD), Brazil. This is student-level academic achievement data from 2017 to 2020. We performed the UST mapping in the FD by using visual interpretation. We classified 21 different types of UST. We fit mixed-effects regression models with a student-specific random intercept and slope. The model was adjusted for temporal factors, SES factors, and variables representing the characteristics and the location of each school. Our findings suggest associations between several types of USTs surrounding schools and academic performance. Overall, areas characterized as low population density, with high green index, and high standard residences were associated with an increase in student performance. In contrast, areas that include old buildings near streets, with significant traffic density, and areas with significant exposed soil (areas devasted) were associated with a decrease in student performance. The results of our study support the creation of effective educational and urban planning policies for local interventions. These interventions are likely to translate into healthier schools and improvements in children's behavioral development and learning performance.