Latent Model Research Articles

Using large administrative data for mining patients’ trajectories for risk stratification: An example from urological diseases

Objective To identify latent clusters among urological patients by examining hospitalisation rate trajectories and their association with risk factors and outcome quality indicators. Materials and methods Victorian Admitted Episodes Dataset, containing information on all hospital admissions in Victoria from 2009 to 2019. The top twenty ICD-10 primary diagnosis codes in urology were used to select patients (n = 98,782) who were included in the study. Latent class trajectory modelling (LCTM) was used to cluster urological patient hospitalisation trajectories. Logistic regression was used to find baseline factors that influence cluster membership, the variables tested included comorbidities, baseline diagnosis codes, and socio-demographic factors. The analysis was further stratified into non-surgical procedures and surgical procedures. Results Five clusters of hospitalisation trajectories were identified based on clustering hospitalisation rates over time. Higher hospitalisation clusters were strongly associated with longer length of stay, higher readmission rates and higher complication rates. Higher-risk groups were strongly associated with comorbidities such as renal disease and diabetes. For surgical procedures, urological cancers (kidney, prostate and bladder cancer) and irradiation cystitis were associated with higher-risk groups. For non-surgical procedures, calculus of the bladder, urethral stricture and bladder neck obstruction were associated with higher-risk groups. For patients with two or more admissions, liver cardiovascular disease and being diagnosed with benign prostatic hyperplasia were also associated with higher risk groups. Conclusion A novel statistical approach to cluster hospitalisation trajectories for urological patients was used to explore potential clusters of patient risks and their associations with outcome quality indicators. This study supports the observation that baseline comorbidities and diagnosis can be predictive of higher hospitalisation rates and, therefore, poorer health outcomes. This demonstrates that it is possible to identify patients at risk of developing complications, higher length of stay and readmissions by using baseline comorbidities and diagnosis from administrative data.

Corrigendum: Investigating the influencing factors of vaccination decisions for newly-developed and established vaccines: a comparative study based on latent class logit models in China

Corrigendum: Investigating the influencing factors of vaccination decisions for newly-developed and established vaccines: a comparative study based on latent class logit models in China

Abstract 4121890: Resting Heart Rate Trajectories over 25 Years: Patterns, Predictors, and Prognostic Impact in the Atherosclerosis Risk in Communities (ARIC) Study

Background: Abnormal resting heart rate (RHR) is associated with cardiovascular events and mortality. Longitudinal RHR trajectories may offer unique prognostic, but research exploring these trajectories over extended periods and their prognostic implications is limited. Methods: Using data from 5,794 participants in the Atherosclerosis Risk in Communities (ARIC) study, we first characterized RHR trajectories over 25 years (from visit 1 [1987-89] to visit 5 [2011-13]) with latent class growth mixture models. Then, we determined the predictors of those trajectories using multinomial logistic regression (n=5,432 with data on predictors of interest). We ran Cox models to quantify the associations between RHR trajectories with cardiovascular outcomes (coronary heart disease, heart failure, stroke) and all-cause mortality (n=4,329 free of cardiovascular disease at baseline). Results: We identified one typical pattern (stable/slight decline, 88.4%) and three atypical patterns (stable-slight increase, 9.2%; increase-decrease, 2.0%; stable-sharp increase, 0.4%) (Figure-Left panel). Obesity, ever smoking, a history of heart failure, and lower education levels predicted the atypical patterns. The stable-increase (combined for slight and sharp) trajectory was significantly and robustly associated with heart failure and all-cause mortality (Figure-Right panel). The increase-decrease trajectory showed a hazard ratio of ~2 for coronary heart disease, although statistical significance was restricted in the demographically adjusted model. Conclusions: We identified one typical (stable/slight decline) and three atypical (increase-decrease, stable-slight increase, and stable-sharp increase) RHR trajectories over 25 years. The atypical trajectories, particularly the stable-increase pattern, were associated with poorer prognosis. These findings highlight the value of monitoring long-term RHR trajectories for cardiovascular risk assessment.

Concurrent Mentions of Vaping and Alcohol on Twitter: Latent Dirichlet Analysis

Background Co-use of alcohol and e-cigarettes (often called vaping) has been linked with long-term health outcomes, including increased risk for substance use disorder. Co-use may have been exacerbated by the COVID-19 pandemic. Social networking sites may offer insights into current perspectives on polysubstance use. Objective The aims of this study were to investigate concurrent mentions of vaping and alcohol on Twitter (subsequently rebranded X) during a time of changing vaping regulations in the United States and the emergence of the COVID-19 pandemic. Methods Tweets including both vape- and alcohol-related terms posted between October 2019 and September 2020 were analyzed using latent Dirichlet allocation modeling. Distinct topics were identified and described. Results Three topics were identified across 6437 tweets: (1) flavors and flavor ban (n=3334, 51.8% of tweets), (2) co-use discourse (n=1119, 17.4%), and (3) availability and access regulation (n=1984, 30.8%). Co-use discussions often portrayed co-use as positive and prosocial. Tweets focused on regulation often used alcohol regulations for comparison. Some focused on the perceived overregulation of vaping (compared to alcohol), while others supported limiting youth access but not at the expense of adult access (eg, stronger age verification over product bans). Across topics, vaping was typically portrayed as less harmful than alcohol use. The benefits of flavors for adult smoking cessation were also discussed. The distribution of topics across time varied across both pre– and post–regulatory change and pre– and post–COVID-19 pandemic declaration periods, suggesting shifts in topic focus salience across time. Conclusions Co-use discussions on social media during this time of regulatory change and social upheaval typically portrayed both vaping and alcohol use in a positive light. It also included debates surrounding the differences in regulation of the 2 substances—particularly as it related to limiting youth access. Emergent themes from the analysis suggest that alcohol was perceived as more harmful but less regulated and more accessible to underage youth than vaping products. Frequent discussions and comparisons of the 2 substances as it relates to their regulation emphasize the still-evolving vaping policy landscape. Social media content analyses during times of change may help regulators and policy makers to better understand and respond to common concerns and potential misconceptions surrounding drug-related policies and accessibility.

Abstract 4127413: High-normal Blood Pressure (130-139/85-89mmHg) is Associated with an Increased Risk of Mortality

Background: The relationship between high-normal blood pressure (BP) and mortality lacks high-quality evidence based on large population cohort. The aim of this study was to comprehensively investigate the association of high-normal BP and its trajectory with all-cause and cause-specific mortality. Methods: In a community-based population cohort from the China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) project, 3,598,940 participants aged 35-75 years with baseline BP were included. High-normal BP was defined as a systolic blood pressure (SBP) of 130-139 mmHg and/or a diastolic blood pressure (DBP) of 85-89 mmHg at baseline. Four trajectories of BP change were identified in 105,894 participants included in the study, who had more than 2 follow-up BP measurements, using latent mixture modeling. Among them, high-normal-increasing was defined as an increase in SBP from 130-139 at baseline to over 140 at the last follow-up. Findings: Compared with the optimal BP group (SBP < 120 mmHg and DBP < 80 mmHg, [18.1%]), participants with high-normal BP (18.7%) had a 4% increase in all-cause mortality risk (hazard ratio [HR] 1.04, 95% confidence interval [CI]: 1.01-1.07) and a 28% increase in CVD mortality risk (HR 1.28, 95% CI: 1.21-1.34), with the greatest increase in mortality risk observed from hemorrhagic stroke (HR 1.75, 95% CI: 1.55-1.98). Among BP trajectories, compared with participants with optimal-stable BP (25.3%), those with high-normal-increasing BP (3.5%) had a 25% increase in all-cause mortality risk (HR 1.25, 95% CI: 1.00-1.54) and a 67% increase in CVD mortality risk (HR 1.66, 95% CI: 1.21-2.30), with the greatest increase in mortality risk also observed from hemorrhagic stroke (HR 3.15, 95% CI: 1.38-7.20). In our study cohort, approximately 0.7% and 1.3% of all-cause mortality was attributable to the high-normal BP at baseline and high-normal-increasing BP trajectory, respectively. Interpretation: Individuals presenting high-normal BP at baseline or high-normal-increasing BP trajectory afterward exhibited a significantly elevated mortality risk, which is most pronounced for hemorrhagic stroke. Early management of BP in patients with high-normal BP is crucial for the prevention and treatment of hypertension.

Detection and Correction of Likert Scale Multiplicative Response-Style Bias

Individuals may differ in their tendency to fully use the range of a Likert scale. Such individual response styles may have an effect on estimates of correlations. It is shown with simulated data that a relatively simple nonlinear latent model can be used to detect and correct (to some extent) for the bias introduced by differences in multiplicative response styles. A real-world dataset is examined to show that the effect may occur in reality and may lead to biased conclusions.

Long‐term characterization of behavior phenotypes in children with seizures: Analytic approach matters

AbstractObjectiveBehavioral problems in children with new onset epilepsies have been well established in the literature. More recently, the literature indicates the presence of unique behavioral patterns or phenotypes in youth with epilepsy that vary significantly in vulnerability and resilience to behavioral problems. This study contrasts the interpretation of behavioral risk as inferred from cross‐sectional versus latent group analytic perspectives, as well as the presence, consistency, stability, and progression of behavioral phenotypes in youth with new onset epilepsy and sibling controls over 3 years.MethodsThree hundred twelve participants (6–16 years old) were recruited within 6 weeks of their first recognized seizure along with 223 unaffected siblings. Each child's behavior was recorded by parents and teachers frequently over 36 months using the Child Behavior Checklist (CBCL), and each child completed self‐report measures of depression symptoms over 36 months. Measures were evaluated cross‐sectionally and longitudinally to identify clusters with prototypical behavioral trajectories.ResultsCross‐sectional analyses exhibited a pattern of generalized and undifferentiated behavioral problems compared to sibling controls at baseline and prospectively. In contrast, latent trajectory modeling identified three distinct behavior phenotype clusters across all raters (parents, teachers, and youth) over baseline and longitudinal assessments. CBCL Cluster 1 (~30% of youth with epilepsy) exhibited behavior similar to/better than controls, Cluster 2 (~50%) exhibited moderate behavior issues, and Cluster 3 (~20%) exhibited the most pronounced/problematic behavior, falling into Achenbach's clinically relevant behavior range. Behavior within clusters remained stable and consistent. Teachers' and children's behavior assessments corresponded to these cluster groupings consistently over 36 months. Predictors of cluster membership include seizure syndrome type and social determinants of health.SignificanceThis study demonstrates the varying public health perspectives of behavioral risk in youth with epilepsy that result as a function of analytic approach as well as the presence of distinct latent behavioral trajectory phenotypes over time in youth with new onset epilepsy.

Adolescent mental time travel predicting meaning in life: The potential mediating role of self‐continuity

AbstractIntroductionKnowing who we are and what we are living for helps us to better adjust in everyday life and confront negative life events, especially for adolescents who are going through critical developmental periods when changes in life could bring both psychopathology risk yet opportunity to achieve a better self. The current study focused on mental time travel, the mental visit to the past or future, and examined the impact on adolescents' perceived meaning in life, with the potential mediating factor of self‐continuity.MethodsA total of 1543 high school students aged 12 to 18 years old (Mage = 15.02, SDage = 1.58, 52% girls) from Jiangsu Province, China were recruited in a two‐wave longitudinal survey that separated by an interval of 6 months. Participants reported their proneness to engage in nostalgia or future prospection at T1 and sense of self‐continuity at T2, while the perceived meaning in life were reported at both time points. The latent structural equation models were established with items as indicators for all study variables.ResultsMental time travel, including both nostalgia and future prospection, facilitated adolescent meaning in life via increased self‐continuity, except that future prospection showed only positive indirect effect, while nostalgia demonstrated direct yet negative impact on meaning in life after accounting for the positive mediation effect.ConclusionsFindings highlighted the distinct effects of the past‐ and future‐oriented mental time travel on adolescent meaning in life, and provided insights for promoting adolescent psychological adjustment.

Multimodal sensor-to-machined surface image diffusion for defect detection in industrial processes

Generative models, particularly diffusion-based approaches, have gained significant attention recently due to their ability to create realistic outputs. Despite their potential, the application of these models in manufacturing remains largely unexplored. This work presents a framework that addresses this gap by generating machined surface images guided by multiple sensor inputs in manufacturing. The proposed model integrates information from multiple sensors with varying sampling rates using multimodal embedding and employs a latent diffusion model to translate the fused sensor embedding into an image embedding, which is then converted into a machined surface image. The effectiveness of the framework is validated using real-world time-series data, including force, torque, acceleration, and sound, collected from various industrial processes, such as a carbon-fiber-reinforced plastic drilling process. The results demonstrate the model’s ability to predict defects from the generated machined surface images. The proposed approach can potentially revolutionize prognostics and health management (PHM) in smart manufacturing by enabling sensor-guided visual inspection, defect detection, process monitoring, and predictive maintenance.

Recidivism risk factors among Mississippi justice-involved youth: latent class analysis of the SAVRY

ABSTRACT The Structured Assessment of Violence Risk in Youth (SAVRY) instrument is a popular risk-need-responsivity tool for justice-involved youth. This study conducted a multi-group (based on sex) latent class analysis model of the SAVRY items to explore heterogeneity in risk/needs among youths involved in the juvenile court in Mississippi between 2017 and 2021. Results indicated a three-class solution best with the data, with Very Low, Low, and Bimodal classes. Generally, these groups were similar across sex, though the Bimodal subgroup was proportionally larger for females than males. Subsequent analyses indicated the Bimodal group was significantly younger and more involved in future one-year recidivism. These findings suggest subgroups of risk exist and should be examined further to assess future recidivism and other risks.

Profiles of Nonpharmacologic Treatment Receipt in the First 10 Weeks Following a New Back Pain Diagnosis Among Active Duty Soldiers: A Latent Class Analysis

ABSTRACT Introduction US service members experience high rates of back pain. Guidelines prioritize nonpharmacologic treatment (NPT) as first-line pain treatments; however, NPT utilization patterns research is limited. This study examined NPT patterns of care within the first 10 weeks following an index back pain diagnosis. Materials and Methods Data were from the Substance Use and Psychological Injury Combat Study and included 222,427 active duty soldiers with an index back pain diagnosis following return from Afghanistan/Iraq deployment in 2008–2014. We fit a series of latent class analysis models to identify homogenous subgroups of soldiers with NPT utilization during the 10-week period and measured associations with soldier characteristics and clinical characteristics within 90 days before the back pain diagnosis, with the distinct NPT utilization classes. Approval for this study was granted by the Brandeis University Committee for Protection of Human Subjects (Institutional Review Board #14153) and the Uniformed Services University Institutional Review Board. Results Only half of the soldiers received any NPT within their 10-week early treatment window. Latent class analysis identified 4 classes over the 10-week early treatment window: Class 1 (None/Low NPT, 65%); Class 2 (High and Decreasing NPT, 15%); Class 3 (Low and Increasing NPT, 13%), and Class 4 (Sustained NPT, 7%). Soldier clinical characteristics from the 90-day preperiod window were most important in distinguishing class membership in relation to Class 1, particularly comorbid pain conditions, diagnosis of traumatic brain injury, receipt of prescription opioids, and receipt of invasive surgery. Conclusions Patterns of weekly NPT utilization during an early treatment window following a new back pain diagnosis varied temporally, with approximately half of soldiers using NPT. Half of the soldiers did not receive any NPT within their 10-week early treatment window, which highlights opportunities for increasing use of NPT utilization among military members with a new back pain episode. Future research is needed in the Military Health System to examine the extent to which NPT patterns are associated with pain management outcomes.

Advancements in Diffusion Models for Image Generation: A Comparative Analysis of DDPM, LDM, and DDIM

Abstract. This research provides a thorough exploration of diffusion models in image generation, comparing various methodologies to assess their efficacy and efficiency. The study begins with an introduction to foundational technologies and key concepts, progressing through an analysis of basic and advanced models, including Latent Diffusion Models (LDMs), Denoising Diffusion Implicit Models (DDIMs), and control models. The research evaluates these models based on their performance, computational efficiency, and future development potential. The review details the evolution of diffusion models from early stochastic processes to their current status as advanced generative models. Key principles, such as iterative noise addition and removal, are examined to understand the transformation from simple distributions to complex data representations. Innovations enhancing model efficiency, including advancements in score matching and neural network integration, are discussed. A thorough comparative analysis highlights the strengths and limitations of each model. The study identifies ongoing challenges such as interpretability and computational cost and proposes future research directions to address these issues. The findings aim to guide researchers and practitioners in advancing diffusion model technologies, offering insights into their impact on image generation and potential future developments.

Building Narratives Through Empathy: The Role of Empathy Mechanisms and Associative Thinking in Creative Writing

ABSTRACTEmpathy emerges as a pivotal skill in creative writing, yet previous studies lack an understanding of empathy's multidimensionality and specific impact of its facets on the capacity to generate narrative stories. This cross‐sectional study delved into the various cognitive and affective empathy facets—that is, perspective‐taking, online simulation, emotion contagion, proximal responsivity, and peripheral responsivity—and their contributions to creative writing. Further, it examined the mediating effects of associative thinking—conceptualized as a common empathy‐creativity resource—on the relationship between empathy facets and creative writing. Two‐hundred twenty participants (university students) completed performance‐based tasks and self‐report measures of creative writing, associative thinking, and empathy. A latent mediation model implemented in Structural Equation Modeling indicated two effects of empathy facets on creative writing, with perspective‐taking emerging as a positive predictor. Additionally, peripheral responsivity (i.e., affect sharing in indirect contexts) exhibited an indirect positive influence on creative writing, mediated by associative thinking. In summary, associative thinking appears to be an important ingredient in both empathy and creative writing, while cognitive empathy, specifically intuitive perspective‐taking, contributes significantly to creative writing skills. Future studies should further explore these connections and their causalities, possibly using experimental or longitudinal approaches.

Examining what works for whom and how in mindfulness-based cognitive therapy (MBCT) for recurrent depression: moderated-mediation analysis in the PREVENT trial.

Personalised management of recurrent depression, considering individual patient characteristics, is crucial. This study evaluates the potentially different mediating role of mindfulness skills in managing recurrent depression using mindfulness-based cognitive therapy (MBCT) among people with varying depression severity. Data from the Prevention of Depressive Relapse or Recurrence (PREVENT) trial, comparing MBCT (with antidepressant medication (ADM) tapering support, MBCT-tapering support) versus maintenance-ADM, were used. The study included pre, post, 9-, 12-, 18- and 24-month follow-ups. Adults with ≥3 previous major depressive episodes, in full/partial remission (below threshold for a current episode), on ADM, were assessed for eligibility in primary care practices in the UK. People were randomised (1:1) to MBCT-tapering support or maintenance-ADM. We used the Beck Depression Inventory-II to evaluate depressive symptom changes over the six time points. Pre-post treatment, we employed the Five Facets of Mindfulness Questionnaire to gauge mindfulness skills. Baseline symptom and history variables were used to identify individuals with varying severity profiles. We conducted Latent Profile Moderated-Mediation Growth Mixture Models. A total of 424 people (mean (s.d.) age = 49.44 (12.31) years; with 325 (76.7%) self-identified as female) were included. A mediating effect of mindfulness skills, between trial arm allocation and the linear rate of depressive symptoms change over 24 months, moderated by depression severity, was observed (moderated-mediation index = -0.27, 95% CI = -0.66, -0.03). Conditional indirect effects were -0.42 (95% CI = -0.78, -0.18) for higher severity (expected mean BDI-II reduction = 10 points), and -0.15 (95% CI = -0.35, -0.02) for lower severity (expected mean BDI-II reduction = 3.5 points). Mindfulness skills constitute a unique mechanism driving change in MBCT (versus maintenance-ADM). Individuals with higher depression severity may benefit most from MBCT-tapering support for residual symptoms. It is unclear if these effects apply to those with a current depressive episode. Future research should investigate individuals who are not on medication. This study provides preliminary evidence for personalised management of recurrent depression. ISRCTN26666654.

Transactional development of science and mathematics knowledge and reading proficiency for multilingual students across languages of instruction.

This longitudinal study explored the reciprocal relations between students' domain-specific knowledge (science and mathematics) and reading proficiency from kindergarten to Grade 5. We compared these relational trajectories across both domains in the overall sample and examined the domain specificity of these relations within a multilingual subsample with varying language instruction backgrounds. Using latent curve modeling with structured residuals on a nationally representative data set, we identified two key patterns. In the overall sample, higher reading proficiency at kindergarten was associated with greater growth in science and mathematics knowledge, with a particularly pronounced effect in science. The predictive power of science knowledge on reading proficiency strengthened significantly from Grades 2 to 5, while reciprocal relations in mathematics intensified over time. For multilingual students, outcomes varied by the language of instruction. Those receiving English-only instruction showed early correlations between science and mathematics knowledge and reading proficiency; however, initial science and mathematics knowledge did not predict long-term growth in reading proficiency. Conversely, multilingual students who received instruction in their native language showed no immediate correlations at kindergarten. Nonetheless, their early science and mathematics knowledge significantly predicted later growth in reading proficiency. The findings underscore the critical role of native-language instruction in providing an accessible, vital cognitive and linguistic foundation that supports deeper domain knowledge building, highlighting the enduring benefits of native-language scaffolding. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Improvement of Optimal Human Resource Allocation Algorithm Based on Deep Latent Semantic Model

With the advances of technology, the banking industry faces the challenge of processing large-scale, heterogeneous human resource data. Traditional methods have difficulties in providing efficient and accurate analysis and prediction. This paper proposes an optimized human resource allocation algorithm based on deep latent Semantic Model (DLSM), which improves the accuracy and efficiency of data analysis by integrating deep neural network (DNN) and transfer learning technology. The experimental results show that the DLSM model performs well in text classification and information retrieval tasks, with the accuracy, accuracy, recall and F1 scores improving by 7.5%, 5.5%, 6.0% and 5.8%, respectively. This study confirms the excellent performance of DLSM model in HR data processing, provides an efficient and scientifically based solution for recruitment optimization in the banking industry, and enhances the competitiveness of enterprises.

Exploring the Psychological Mechanism of How the Multidimensional Service Quality of Fitness Centers Affects Consumer Satisfaction and Loyalty Depending on the Level of Exercise Involvement

This study aimed to examine the influence of core services and the physical servicescape and social servicescape on consumer satisfaction and loyalty via perceived price fairness, flow experience, and rapport in fitness centers. Additionally, the present study explored how exercise involvement moderates the relationship between perceived price fairness, flow experience, rapport, and consumer satisfaction. For these purposes, targeting adults using fitness centers in South Korea, a total of 763 participants were sampled based on a cross-sectional design and used for data analyses involving confirmatory factor analysis for measurement validation and latent moderated structural equation modeling for hypothesis testing. The results showed that the core services, physical servicescape, and social servicescape enhance perceived price fairness, flow experiences, and rapport between staff and consumers, respectively. The study findings also indicated that exercise involvement significantly moderates the effect of price fairness and flow experience on satisfaction but not rapport. These insights offer practical and theoretical implications for fitness center management, emphasizing the importance of tailored service strategies in retaining loyal customers.

Teacher epistemic curiosity: how principal–teacher conversation supports it

PurposeThe purpose of this study was to introduce teacher epistemic curiosity for student learning into the leadership literature and to determine if school principals can support it. The inquiry was organized by the following research question: In what ways can principal–teacher conversations support teacher epistemic curiosity for student learning? The research question guided the review of literature on epistemic curiosity, eventually leading to the leadership practice of transformative leadership conversation (TLC). A hypothesized model on the relationship between TLC and epistemic curiosity for student learning was advanced from research on student and employee curiosity and self-determination theory.Design/methodology/approachThe hypothesized model was tested with a correlational research design. Teacher survey data were collected in December 2023 from a random sample of certified public school teachers from a metropolitan area in a southwestern state of the USA. Usable survey responses were received from 2,022 teachers, resulting in a 55% response rate. The hypothesized model was tested with structural equation modeling in AMOS 28 using robust maximum likelihood estimation. The latent models include measurement and structural components.FindingsResults confirm the hypothesized relationships among TLC, need-satisfaction and teacher epistemic curiosity. TLC and need-satisfaction both had strong, direct relationships with teacher epistemic curiosity for student learning. TLC explained approximately 20% of the variance in teacher curiosity and need-satisfaction explained approximately 18%. The combined model accounted for approximately 55% of the variance in teacher epistemic curiosity.Originality/valueThe study emerged from robust evidence on the essential function of curiosity for knowing, learning, performance and life well-being, as well as limited research on social processes that leaders can leverage to stimulate teachers’ motivation to understand how their students learn. Curiosity is an inner energy behind learning; it fuels an innate drive to explore, know, create, design and adapt to our surroundings. Schools and classrooms come to life when teachers and students engage in learning from a place of curiosity, making this motivational resource worthy of leadership attention.

BMI trajectories from birth to young adulthood associate with distinct cardiometabolic profiles.

Numerous studies have investigated links between body mass index (BMI) trajectories and cardiovascular risk, yet discrepancies in BMI measurement duration and timing of the cardiovascular-related outcome evaluation have led to inconsistent findings. We included participants from the Swedish birth cohort (BAMSE) and applied latent class mixture modeling to identify BMI trajectories using data of multiple BMI measures (≥ 4 times) from birth until 24-year follow-up (n = 3204). Subsequently, we analyzed the associations of BMI trajectories with lipids (n = 1974), blood pressure (n = 2022), HbA1c (n = 941), and blood leukocytes (n = 1973) using linear regression. We also investigated the circulating levels of 92 inflammation-related proteins (n = 1866) across BMI trajectories. Six distinct BMI groups were identified, denoted as increasing-persistent high (n = 74; 2.3%), high-accelerated increasing (n = 209; 6.5%), increasing-accelerated resolving (n = 142; 4.4%), normal-above normal (n = 721; 22.5%), stable normal (n = 1608; 50.2%), and decreasing-persistent low (n = 450; 14.1%) BMI groups. The increasing-persistent high and high-accelerated increasing BMI groups had higher levels of total cholesterol [mean difference (95% confidence intervals): 0.30 (0.04-0.56) and 0.16 (0.02-0.31) mmol/L], triglyceride, low-density lipoprotein, hemoglobin A1C [3.61 (2.17-5.54) and 1.18 (0.40-1.98) mmol/mol], and low-density lipoprotein/high-density lipoprotein ratios, but a lower level of high-density lipoprotein than the stable normal BMI group. These two groups also had higher leukocyte cell counts and higher circulating levels of 28 inflammation-related proteins. No increased cardiometabolic markers were observed in the increasing-accelerated resolving BMI group. Participants with persistently high or accelerated increasing BMI trajectories from birth to young adulthood have elevated levels of cardiometabolic risk markers at young adulthood than those with stable normal BMI. However, a raised BMI in childhood may not be inherently harmful to cardiometabolic health, provided it does not persist into adulthood.

Longitudinal bidirectional relations between psychological maltreatment by teachers and psychosocial adjustment during early adolescence

This study examined three models (relationship-driven model, symptom-driven model and transactional model) testing the across-time bidirectional relations between psychological maltreatment by teachers and early adolescents' psychosocial adjustment (i.e., internalizing problems, externalizing problems, and academic achievement) during early adolescence. A total of 4169 Chinese early adolescents (Mage = 9.93 years, SD = 0.73, 54% males) completed assessments across five waves, every six months. Employing autoregressive latent trajectory models with structured residuals (ALT-SR), the results revealed that adolescents’ internalizing problems and academic achievement were predicted by psychological maltreatment by teachers (supporting the relationship-driven model), whereas externalizing problems and psychological maltreatment by teachers were bidirectionally related (supporting the transactional model). Moreover, sex moderated the relations between psychological maltreatment by teachers and psychosocial adjustment. The finding of differential relations between psychological maltreatment by teachers and three components of psychosocial adjustment (i.e., internalizing problems, externalizing problems, and academic achievement) indicated that prevention and interventions should be tailored to different psychosocial adjustment difficulties.