An overview of mixture modelling for latent evolutions in longitudinal data: Modelling approaches, fit statistics and software

Identifying trajectories of change in sleep disturbance during psychological treatment for depression

BACKGROUND

Sleep disturbance may impact response to psychological treatment for depression. Understanding how sleep disturbance changes during the course of psychological treatment, and identifying the risk factors for sleep disturbance response may inform clinical decision-making.

METHOD

This analysis included 18,915 patients receiving high-intensity psychological therapy for depression from one of eight London-based Improving Access to Psychological Therapies (IAPT) services between 2011 and 2020. Distinct trajectories of change in sleep disturbance were identified using growth mixture modelling. The study also investigated associations between identified trajectory classes, pre-treatment patient characteristics, and eventual treatment outcomes from combined PHQ-9 and GAD-7 metrics used by the services.

RESULTS

Six distinct trajectories of sleep disturbance were identified: two demonstrated improvement, while one showed initial deterioration and the other three groups displayed only limited change in sleep disturbance, each with varying baseline sleep disturbance. Associations with trajectory class membership were found based on: gender, ethnicity, employment status, psychotropic medication use, long-term health condition status, severity of depressive symptoms, and functional impairment. Groups that showed improvement in sleep had the best eventual outcomes from depression treatment, followed by groups that consistently slept well.

LIMITATION

Single item on sleep disturbance used, no data on treatment adherence.

CONCLUSIONS

These findings reveal heterogeneity in the course of sleep disturbance during psychological treatment for depression. Closer monitoring of changes in sleep disturbance during treatment might inform treatment planning. This includes decisions about when to incorporate sleep management interventions, and whether to change or augment therapy with interventions to reduce sleep disturbance.

Trajectories of work disability and unemployment before and after a common mental disorder diagnosis among young private sector employees in Sweden-a register-based longitudinal study

PURPOSE

To identify trajectory groups of work disability (WD), including sick leave and disability pension, and unemployment three years before and six years (from Y-3 to Y + 6) after a common mental disorder (CMD) diagnosis and to investigate associations of socio-demographic, work-related and clinical factors with trajectory membership.

METHODS

A longitudinal nationwide register-based study was conducted including individuals aged 22-29 years, gainfully employed in the private sector, with a CMD diagnosis in specialised healthcare or prescribed antidepressant (N = 12,121) in 2014 (Year 0/Y0), with follow-up from Y-3 to Y + 6. Group-based trajectory analyses identified groups of individuals who followed similar trajectories of months of WD and unemployment, respectively. Multinomial logistic regression determined associations between socio-demographic, work-related and clinical factors and trajectory membership.

RESULTS

In the CMD group, we identified three trajectory groups, each for WD and unemployment. Only 7% individuals belonged to a 'Fluctuant high' trajectory group with four months of WD in Y0, which peaked at 7 months in Y + 3 and reduced to 5 months in Y + 6. For unemployment, 15% belonged to an 'Increasing medium' trajectory group that steadily increased from 1.3 months in Y0 to 2.6 months in Y + 6. Sex, educational level and musculoskeletal disorders for WD, and educational level, living area and occupational class for unemployment, influentially determined the variance across the CMD trajectory groups.

CONCLUSIONS

Specific vulnerable groups regarding unfavourable WD (women, low education and musculoskeletal disorders) and unemployment (manual work, low education and rural residence) trajectories require special attention regarding their return-to-work process following a CMD diagnosis.

Joint trajectories of pain, depression and frailty and associations with adverse outcomes among community-dwelling older adults: A longitudinal study

This study aimed to examine joint trajectories of pain, depression and frailty and their associations with adverse outcomes. Four waves of national data from the China Health and Retirement Longitudinal Study (CHARLS 2011-2018) were used, involving 4217 participants aged ≥60 years. Joint trajectories were fit using parallel-process latent class growth analysis, and their associations with adverse outcomes were evaluated using modified Poisson regression. Four joint trajectories were identified. Compared with most favorable group, other three joint trajectory groups had higher risk of functional disability and hospitalization. Slowly progressive pain, depression and frailty and persistent combination of pain, depression and frailty were also associated with cognitive decline, while slowly reduced pain and depression but persistent frailty was associated with all-cause mortality. The findings highlight unique characteristics and health impacts of concurrent changes in pain, depression and frailty over time, implicating the integrated physical and psychological care for older adults.

Validation of the Coach Behavior in Sports Questionnaire: Towards dynamic assessments using the circumplex model for coach behavior

The development of the circumplex model for coach behavior recently provided researchers an integrative model to assess coach behavior. While the circumplex model has currently only been deployed in cross-sectional research designs using the Situations in Sports questionnaire (SISQ), it has clear potential within research on dynamics of coach behavior. However, the SISQ consists of vignette-based situations and is too extensive for such frequent administrations. Within the present study we therefore developed the Coach Behavior in Sports Questionnaire (CBSQ), a 32-item alternative for the SISQ which consists of general items rather than vignette-based situations. First, content validity of 54 initial pilot CBSQ items was tested in a sample of 34 expert coaches. Second, construct validity, predictive validity, and reliability of the 32-item CBSQ was tested in a sample of 689 athletes and 420 coaches. Third, within-person variability of coach behavior was longitudinally assessed using the 32-item CBSQ during a five-week training and game period in a sample of 31 coach-athlete dyads. The 32-item CBSQ showed to be a valid and reliable alternative for the SISQ. Also, coach behavior showed considerable within-person variability over the five-week period in all coaching styles and approaches. Additionally, a 24, 16, and 12-item version were tested to provide even shorter alternatives. The CBSQ opens new horizons for future longitudinal research and coach reflection programs based on the circumplex model for coach behavior.

Trajectories of depression and predictors in lung cancer patients undergoing chemotherapy: growth mixture model

BACKGROUND

Depression is prevalent among lung cancer patients undergoing chemotherapy, and the symptom cluster of fatigue-pain-insomnia may influence their depression. Identifying characteristics of patients with different depression trajectories can aid in developing more targeted interventions. This study aimed to identify the trajectories of depression and the fatigue-pain-insomnia symptom cluster, and to explore the predictive factors associated with the categories of depression trajectories.

METHODS

In this longitudinal study, 187 lung cancer patients who were undergoing chemotherapy were recruited and assessed at the first (T1), second(T2), and fourth(T3) months using the Patient Health Questionnaire-9 (PHQ-9), the Brief Pain Inventory (BPI), the Brief Fatigue Inventory (BFI), and the Athens Insomnia Scale (AIS). Growth Mixture Model (GMM) and Latent Class Analysis (LCA) were used to identify the different trajectories of the fatigue-pain-insomnia symptom cluster and depression. Binary logistic regression was utilized to analyze the predictive factors of different depressive trajectories.

RESULTS

GMM identified two depressive trajectories: a high decreasing depression trajectory (40.64%) and a low increasing depression trajectory (59.36%). LCA showed that 48.66% of patients were likely members of the high symptom cluster trajectory. Binary logistic regression analysis indicated that having a history of alcohol consumption, a higher symptom cluster burden, unemployed, and a lower monthly income predicted a high decreasing depression trajectory.

CONCLUSIONS

Depression and fatigue-pain-insomnia symptom cluster in lung cancer chemotherapy patients exhibited two distinct trajectories. When managing depression in these patients, it is recommended to strengthen symptom management and pay particular attention to individuals with a history of alcohol consumption, unemployed, and a lower monthly income.

Social-ecological factors associated with trajectories of adolescent sexual and reproductive health stigma: longitudinal cohort findings with urban refugee youth in Kampala

Background Stigma towards sexually active young people presents profound barriers to uptake of sexual and reproductive health (SRH) services, including HIV testing and contraception. Yet, few studies have examined adolescent SRH stigma trajectories over time. To address this knowledge gap, we examined associations between social-ecological factors and trajectories of adolescent SRH stigma among urban refugee youth in Kampala, Uganda. Methods This longitudinal cohort study with refugee youth in Kampala collected data on adolescent SRH stigma at four time-points between 2022 and 2024. We used latent class growth analyses to examine distinct trajectories of adolescent SRH stigma, and examined baseline social-ecological and socio-demographic factors associated with class membership using multivariable logistic regression. Results Among the participants (n =164 with n =668 observations; mean age 19.9 years, standard deviation2.5 years; 52.8% cisgender women), we categorised two distinct adolescent SRH stigma trajectories: consistently high (n =496; 74.2%) and sustained low (n =172; 25.8%). In multivariable analyses, living in Uganda ≥1year at baseline assessment (1-5years: adjusted odds ratio [aOR]5.28, confidence interval [CI]2.29-12.19, P P 10years: aOR3.89, CI1.56-9.68, P P P P P Conclusions Social-ecological and socio-demographic factors were associated with consistently high levels of adolescent SRH stigma over 2years. Multi-level strategies can meaningfully engage youth in developing stigma reduction strategies for SRH service delivery.

[Dynamic Prediction of Recidivism in Violence in Community-Based Schizophrenia Spectrum Disorder Patients: A Joint Model]

Objective

To construct a model for predicting recidivism in violence in community-based schizophrenia spectrum disorder patients (SSDP) by adopting a joint modeling method.

Methods

Based on the basic data on severe mental illness in Southwest China between January 2017 and June 2018, 4565 community-based SSDP with baseline violent behaviors were selected as the research subjects. We used a growth mixture model (GMM) to identify patterns of medication adherence and social functioning. We then fitted the joint model using a zero-inflated negative binomial regression model and compared it with traditional static models. Finally, we used a 10-fold training-test cross validation framework to evaluate the models' fitting and predictive performance.

Results

A total of 157 patients (3.44%) experienced recidivism in violence. Medication compliance and social functioning were fitted into four patterns. In the counting model, age, marital status, educational attainment, economic status, historical types of violence, and medication compliance patterns were predictive factors for the frequency of recidivism of violence (P<0.05). In the zero-inflated model, age, adverse drug reactions, historical types of violence, medication compliance patterns, and social functioning patterns were predictive factors for the recidivism in violence (P<0.05). For the joint model, the average value of Akaike information criterion (AIC) for the train set was 776.5±9.4, the average value of root mean squared error (RMSE) for the testing set was 0.168±0.013, and the average value of mean absolute error (MAE) for the testing set was 0.131±0.018, which were all lower than those of the traditional static models.

Conclusion

Joint modeling is an effective statistical strategy for identifying and processing dynamic variables, exhibiting better predictive performance than that of the traditional static models. It can provide new ideas for promoting the construction of comprehensive intervention systems.

Immunometabolic Blood Biomarkers of Developmental Trajectories of Depressive Symptoms: Findings From the ALSPAC Birth Cohort

Studies of longitudinal trends of depressive symptoms in young people could provide insight into aetiologic mechanism, heterogeneity and origin of common cardiometabolic comorbidities for depression. Depression is associated with immunological and metabolic alterations, but immunometabolic characteristics of developmental trajectories of depressive symptoms remain unclear. Using depressive symptoms scores measured on 10 occasions between ages 10 and 25 years in the Avon Longitudinal Study of Parents and Children (n=7302), we identified four distinct trajectories: low-stable (70% of the sample), adolescent-limited (13%), adulthood-onset (10%) and adolescent-persistent (7%). We examined associations of these trajectories with: i) anthropometric, cardiometabolic and psychiatric phenotypes using multivariable regression (n=1709-3410); ii) 67 blood immunological proteins and 57 metabolomic features using empirical Bayes moderated linear models (n=2059 and n=2240 respectively); and iii) 28 blood cell counts and biochemical measures using multivariable regression (n=2256). Relative to the low-stable group, risk of depression and anxiety in adulthood was higher for all other groups, especially in the adolescent-persistent (ORdepression=22.80, 95% CI 15.25-34.37; ORGAD=19.32, 95% CI 12.86-29.22) and adulthood-onset (ORdepression=7.68, 95% CI 5.31-11.17; ORGAD=5.39, 95% CI 3.65-7.94) groups. The three depression-related trajectories vary in their immunometabolic profile, with evidence of little or no alterations in the adolescent-limited group. The adulthood-onset group shows widespread classical immunometabolic changes (e.g., increased immune cell counts and insulin resistance), while the adolescent-persistent group is characterised by higher BMI both in childhood and adulthood with few other immunometabolic changes. These findings point to distinct mechanisms and intervention opportunities for adverse cardiometabolic profile in different groups of young people with depression.

Twenty-year trajectories of morbidity in individuals with and without osteoarthritis

OBJECTIVES

To identify multimorbidity trajectories over 20 years among incident osteoarthritis (OA) individuals and OA-free matched references.

METHODS

Cohort study using prospectively collected healthcare data from the Skåne region, Sweden (~1.4 million residents). We extracted diagnoses for OA and 67 common chronic conditions. We included individuals aged 40+ years on 31 December 2007, with incident OA between 2008 and 2009. We selected references without OA, matched on birth year, sex, and year of death or moving outside the region. We employed group-based trajectory modelling to capture morbidity count trajectories from 1998 to 2019. Individuals without any comorbidity were included as a reference group but were not included in the model.

RESULTS

We identified 9846 OA cases (mean age: 65.9 (SD 11.7), female: 58%) and 9846 matched references. Among both cases and references, 1296 individuals did not develop chronic conditions (no-chronic-condition class). We identified four classes. At the study outset, all classes exhibited a low average number of chronic conditions (≤1). Class 1 had the slowest progression towards multimorbidity, which increased progressively in each class. Class 1 had the lowest count of chronic conditions at the end of the follow-up (mean: 2.9 (SD 1.7)), while class 4 had the highest (9.6 (2.6)). The presence of OA was associated with a 1.29 (1.12, 1.48) adjusted relative risk of belonging to class 1 up to 2.45 (2.12, 2.83) for class 4.

CONCLUSIONS

Our findings suggest that individuals with OA face an almost threefold higher risk of developing severe multimorbidity.

Assessing the performance of group-based trajectory modeling method to discover different patterns of medication adherence

It is well known that medication adherence is critical to patient outcomes and can decrease patient mortality. The Pharmacy Quality Alliance (PQA) has recognized and identified medication adherence as an important indicator of medication-use quality. Hence, there is a need to use the right methods to assess medication adherence. The PQA has endorsed the proportion of days covered (PDC) as the primary method of measuring adherence. Although easy to calculate, the PDC has however several drawbacks as a method of measuring adherence. PDC is a deterministic approach that cannot capture the complexity of a dynamic phenomenon. Group-based trajectory modeling (GBTM) is increasingly proposed as an alternative to capture heterogeneity in medication adherence. The main goal of this paper is to demonstrate, through a simulation study, the ability of GBTM to capture treatment adherence when compared to its deterministic PDC analogue and to the nonparametric longitudinal K-means. A time-varying treatment was generated as a quadratic function of time, baseline, and time-varying covariates. Three trajectory models are considered combining a cat's cradle effect, and a rainbow effect. The performance of GBTM was compared to the PDC and longitudinal K-means using the absolute bias, the variance, the c-statistics, the relative bias, and the relative variance. For all explored scenarios, we find that GBTM performed better in capturing different patterns of medication adherence with lower relative bias and variance even under model misspecification than PDC and longitudinal K-means.

Joint trajectories of physical frailty and social frailty and associations with adverse outcomes: A prospective cohort study

BACKGROUND

We examined joint trajectories of physical frailty and social frailty as well as their associations with adverse outcomes.

METHODS

We conducted a prospective cohort study by using five waves of national data from China Health and Retirement Longitudinal Study (CHARLS 2011-2020), involving 4531 participants aged ≥60 years. We identified 4-year trajectories at three examinations from 2011 to 2015 using parallel process latent class growth analysis. Adverse outcomes were obtained from 2015 to 2020 across two subsequent waves. We calculated hazard ratios (HR) using Cox proportional hazard models. We also conducted analyses by gender.

RESULTS

Three joint trajectories were identified, including persistent absence of physical and social frailty (58.5 %), no physical frailty but social frailty (28.1 %), and persistent combination of physical and social frailty (13.4 %). Compared with persistent absence of physical and social frailty, no physical frailty but social frailty and persistent combination of physical and social frailty were associated with higher risk of instrumental activities of daily living (IADL) disability (HR = 1.182-2.020, 95 % CI: 1.014-2.416) and all-cause mortality (HR = 1.440-2.486, 95 % CI: 1.211-3.009). The persistent combination of physical and social frailty was also associated with ADL disability (HR = 2.412, 95 % CI: 1.999-2.911) and falls (HR = 1.410, 95 % CI: 1.196-1.662). Gender differences were observed in relationships between joint trajectories and adverse outcomes.

CONCLUSION

Community-dwelling older adults exhibit distinct joint trajectories and those with persistent combination of physical and social frailty experience greatest risk of incident adverse outcomes. Clinical and public health measures targeting physical or social frailty should account for both and be gender-specific.

Posttraumatic cognition change trajectories in veterans with PTSD who completed an intensive Cognitive Processing Therapy treatment program

Negative posttraumatic cognitions (NPCs) have been linked to symptoms of PTSD and are an important target of cognitive behavioral treatments for PTSD, including Cognitive Processing Therapy (CPT). Yet to be explored are the different change trajectories of NPCs during CPT. Knowledge of such change trajectories could elucidate common NPC change processes within CPT and their relationship to PTSD symptom severity. We examined NPC change trajectories in a group of 443 veterans who completed a 2-week intensive CPT program. We identified four NPC trajectory groups termed start high end high, start high end moderate, start moderate end low, and start low end low. Most of the groups showed an increase in NPCs at the midpoint of treatment before ultimately decreasing. As predicted, baseline PTSD symptom severity predicted change trajectory group membership. Also, NPC change trajectories were associated with PTSD severity at the end of treatment such that individuals in smaller NPC change groups had higher PTSD symptoms at the end of treatment, and vice versa. Clinicians can use this knowledge to make predictions of a particular client's NPC change trajectory and set expectations for what progress in treatment may look like, including normalizing increases in NPCs from the start of treatment.

Recommendations on Methods for Assessing Multimorbidity Changes Over Time: Aligning the Method to the Purpose

BACKGROUND

The rapidly growing field of multimorbidity research demonstrates that changes in multimorbidity in mid- and late-life have far reaching effects on important person-centered outcomes, such as health-related quality of life. However, there are few organizing frameworks and comparatively little work weighing the merits and limitations of various quantitative methods applied to the longitudinal study of multimorbidity.

METHODS

We identify and discuss methods aligned to specific research objectives with the goals of (i) establishing a common language for assessing longitudinal changes in multimorbidity, (ii) illuminating gaps in our knowledge regarding multimorbidity progression and critical periods of change, and (iii) informing research to identify groups that experience different rates and divergent etiological pathways of disease progression linked to deterioration in important health-related outcomes.

RESULTS

We review practical issues in the measurement of multimorbidity, longitudinal analysis of health-related data, operationalizing change over time, and discuss methods that align with 4 general typologies for research objectives in the longitudinal study of multimorbidity: (i) examine individual change in multimorbidity, (ii) identify subgroups that follow similar trajectories of multimorbidity progression, (iii) understand when, how, and why individuals or groups shift to more advanced stages of multimorbidity, and (iv) examine the coprogression of multimorbidity with key health domains.

CONCLUSIONS

This work encourages a systematic approach to the quantitative study of change in multimorbidity and provides a valuable resource for researchers working to measure and minimize the deleterious effects of multimorbidity on aging populations.

Using latent class growth analysis to detect group developmental trajectories in preclinical medical education

Medical educators and programs are deeply interested in understanding and projecting the longitudinal developmental trajectories of medical students after these students are matriculated into medical schools so appropriate resources and interventions can be provided to support students' learning and progression during the process. As students have different characteristics and they do not learn and progress at the same pace, it is important to identify student subgroups and address their academic needs to create more equitable learning opportunities. Using latent class growth analysis, this study explored students' developmental trajectories and detected group differences based on their coursework performance in Anatomy within the two years of preclinical education in one medical school. Four subgroups were identified with various intercepts and slopes. There were significant group differences between these subgroups and their standardized scores in MCAT and UCMLE Step 1. The study provides evidence about the heterogeneity of the student population and points out future research directions.

Disease-specific health-related quality of life trajectories up to 15 years after curative treatment for esophageal cancer-a prospective cohort study

BACKGROUND

The presence of distinct long-term disease-specific HRQL trajectories after curative treatment for esophageal cancer and factors associated with such trajectories are unclear.

MATERIALS AND METHODS

This population-based and longitudinal cohort study included 425 esophageal cancer patients who underwent curative treatment, including esophagectomy, in Sweden in 2001-2005 and were followed up until 2020, that is, 15-year follow-up. The outcomes were 10 disease-specific HRQL symptoms, measured by the well-validated EORTC QLQ-OES18 questionnaire at 6 months (n = 402 patients), and 3 (n = 178), 5 (n = 141), 10 (n = 92), and 15 years (n = 52) after treatment. HRQL symptoms were examined for distinct trajectories by growth mixture models. Weighted logistic regression models provided odds ratios (OR) with 95% confidence intervals (95% CI) for nine factors in relation to HRQL trajectories: age, sex, education, proxy baseline HRQL, comorbidity, tumor histology, chemo(radio)therapy, pathological tumor stage, and postoperative complications.

RESULTS

Distinct HRQL trajectories were identified for each of the 10 disease-specific symptoms. HRQL trajectories with more symptoms tended to persist or alleviate over time, while trajectories with fewer symptoms were more stable. Eating difficulty had three trajectories: persistently less, persistently moderate, and persistently more symptoms. The OR of having a persistently more eating difficulty trajectory was decreased for adenocarcinoma histology (OR = 0.44, 95% CI 0.21-0.95), and increased for pathological tumor stage III-IV (OR = 2.19, 95% CI 0.99-4.82) and 30-day postoperative complications (OR = 2.54, 95% CI 1.26-5.12).

CONCLUSION

Distinct trajectories with long-term persistent or deteriorating disease-specific HRQL symptoms were identified after esophageal cancer treatment. Tumor histology, tumor stage, and postoperative complications may facilitate detection of high-risk patients for unwanted trajectories.

Metabolic Clusters of Early-Lactating Dairy Cows Based on Blood β-hydroxybutyrate Trajectories and Predicted from Milk Compounds

High-yielding dairy cows encounter metabolic challenges in early lactation. Typically, β-hydroxybutyrate (BHB), measured at a specific time point is employed to diagnose the metabolic status of cows based on a predetermined threshold. However, in early lactation, BHB is highly dynamic, and there is high interindividual variability in its time profile. This could limit the effectiveness of the single measurement and threshold-based diagnosis probably contributing to the disparities in reports linking metabolic status with productive and reproductive outcomes. This research delves into the examination of the trajectories of BHB to unveil inter-cow variations and identify latent metabolic groups. We compiled a data set from 2 observational studies involving a total of 195 lactations from multiparous Holstein Friesian cows. The data set encompasses measurements of BHB, NEFA, and insulin from blood samples collected at 3, 6, 9, and 21 d in milk (DIM), along with weekly determinations of milk composition and fatty acids (FA) proportions in milk fat. In both experiments, milk yield (MY) and feed intake were recorded daily during the first month of lactation. We explored interindividual and intraindividual variations in metabolic responses using the trajectories of blood BHB and evaluated the presence of distinct metabolic groups based on such variations. For this purpose, we employed the growth mixture model (GMM), a trajectory clustering technique. Our findings unveil novel insights into the diverse metabolic responses among cows, encompassing both trajectory patterns and the magnitude of blood BHB concentrations. Specifically, we identified 3 latent metabolic groups: the "QuiBHB" cluster (≈10%) exhibited a higher initial BHB concentration than other clusters, peaking on d 9 (average maximum BHB of 2.4 mM) and then declining by d 21; the "SloBHB" cluster (≈23%) started with a lower BHB concentration, gradually increasing until d 9, and at the highest BHB concentration at d 21 (1.6 mM serum BHB at the end of the experimental period); and the "LoBHB" cluster (≈67%) began with the lowest serum BHB concentration (serum BHB <0.75 mM), remaining relatively stable throughout the sampling period. Notably, the 3 metabolic groups exhibited significant physiological disparities, evident in blood NEFA and insulin concentrations. The QuiBHB and SloBHB cows exhibited higher NEFA and lower insulin concentrations as compared with the LoBHB cows. Interestingly, these metabolic differences extended to MY and DMI during the first month of lactation. The elevated BHB concentrations observed in QuiBHB cows were linked with lower DMI and MY as compared with SloBHB and LoBHB cows. Accordingly, these animals were considered metabolically impaired. Conversely, SloBHB cows displayed higher MY along with increased DMI, and thus the elevated BHB might be indicative of an adaptive response for these cows. The QuiBHB cows also displayed higher proportions of unsaturated FA (UFA), monounsaturated FA (MUFA), and total C18:1 FA in milk during the first week of lactation. Prediction of the QuiBHB cows using these FA and test day variables resulted in moderate predictive accuracy (ROCAUC > 0.7). Given the limited sample size for the development of prediction models, and the variation in DIM among samples in the same week, the result is indicative of the predictive potential of the model and room for model optimization. In summary, distinct metabolic groups of cows could be identified based on the trajectories of blood BHB in early lactation.

Predicting Post-Disaster Post-Traumatic Stress Disorder Symptom Trajectories: The Role of Pre-Disaster Traumatic Experiences

The mental health impact of disasters is substantial, with 30-40% of direct disaster victims developing post-traumatic stress disorder (PTSD). It is not yet clear why some people cope well with disaster-related trauma while others experience chronic dysfunction. Prior research on non-disaster trauma suggests that an individual's history of traumatic experiences earlier in the life course, prior to the disaster, may be a key factor in explaining variability in psychological responses to disasters. This study evaluated the extent to which pre-disaster trauma predicts PTSD trajectories in a sample of Hurricane Katrina survivors followed for 12 years after the storm. Four PTSD trajectories were identified using latent class growth analysis: Resistant (49.0%), Recovery (29.3%), Delayed-Onset (8.0%), and Chronic-High (13.7%). After adjusting for covariates, pre-Katrina trauma had only a small, positive impact on the probability of long-term, chronic Katrina-specific PTSD, and little effect on the probability of the Resistant and Delayed-Onset trajectories. Higher pre-Katrina trauma exposure moderately decreased the probability of being in the Recovery trajectory, in which Katrina-specific PTSD symptoms are initially high before declining over time. When covariates were added to the model one at a time, the association between pre-Katrina trauma and Chronic-High PTSD was attenuated most by the addition of Katrina-related trauma. Our findings suggest that while pre-disaster trauma exposure does not have a strong direct effect on chronic Katrina-specific PTSD, pre-Katrina trauma may impact PTSD through other factors that affect Katrina-related PTSD, such as by increasing the severity of Katrina-related trauma. These findings have important implications for the development of disaster preparedness strategies to diminish the long-term burden of disaster-related PTSD.

Group-Based Trajectory Modeling of Fluid Balance in Elderly Patients with Acute Ischemic Stroke: Analysis from Multicenter ICUs

INTRODUCTION

Acute ischemic stroke (AIS) significantly contributes to severe disability and mortality among the elderly. This study aims to explore the association between longitudinal fluid balance (FB) trajectories and clinical outcomes in elderly patients with AIS. Our hypothesis posits the existence of multiple latent trajectories of FB in patients with AIS during the initial 7 days following ICU admission.

METHODS

Patients (age ≥ 65 years) with AIS and continuous FB records were identified from two large databases. Group-based trajectory modeling identified latent groups with similar 7-day FB trajectories. Subsequently, multivariable logistic and quasi-Poisson regression were employed to evaluate the relationship between trajectory groups and outcomes. Additionally, nonlinear associations between maximum fluid overload (FO) and outcomes were analyzed using restricted cubic spline models. To further validate our findings, subgroup and sensitivity analysis were conducted.

RESULTS

A total of 1146 eligible patients were included in this study, revealing three trajectory patterns were identified: low FB (84.8%), decreasing FB (7.2%), and high FB (7.9%). High FB emerged as an independent risk factor for in-hospital mortality. Compared with those without FO, patients with FO had a 1.57-fold increased risk of hospital mortality (adjusted odd ratio (OR) 1.57, 95% confidence interval (CI) 1.08-2.27), 2.37-fold increased risk of adverse kidney event (adjusted OR 2.37, 95% CI 1.56-3.59), and 1.33-fold increased risk of prolonged ICU stay (adjusted incidence rate ratio (IRR) 1.33, 95% CI 1.19-1.48). The risk of hospital mortality and adverse kidney event increased linearly with rising maximum FO (P for non-linearity = 0.263 and 0.563, respectively).

CONCLUSION

Daily FB trajectories were associated with adverse outcomes in elderly patients with AIS. Regular assessment of daily fluid status and restriction of FO are crucial for the recovery of critically ill patients.

Long-term trajectories of depressive symptoms in deployed military personnel: A 10-year prospective study

BACKGROUND

Military missions, especially those involving combat exposure, are associated with an increased risk of depression. Understanding the long-term course of depressive symptoms post-deployment is important to improve decision-making regarding deployment and mental health policies in the military. This study investigates trajectories of depressive symptoms in the Dutch army, exploring the influence of factors such as demographics, early-life trauma, posttraumatic stress disorder (PTSD) symptoms, and deployment stressors.

METHODS

A cohort of 1032 military men and women deployed to Afghanistan (2005-2008) was studied from pre- to 10 years post-deployment. Depressive and PTSD symptoms were assessed using the Symptom CheckList-90 and the Self-Rating Inventory for PTSD. Demographics, early trauma, and deployment experiences were collected at baseline and after deployment, respectively. Latent Class Growth Analysis was used to explore heterogeneity in trajectories of depressive symptoms over time.

RESULTS

Four trajectories were found: resilient (65%), intermediate-stable (20%), symptomatic-chronic (9%), and late-onset-increasing (6%). The resilient group experienced fewer deployment stressors, while the symptomatic-chronic group reported more early life traumas. Trajectories with elevated depressive symptoms consistently demonstrated higher PTSD symptoms.

LIMITATIONS

Potential nonresponse bias and missing information due to the longitudinal design and extensive follow-up times.

CONCLUSIONS

This study identified multiple trajectories of depressive symptoms in military personnel up to 10 years post-deployment, associated with early trauma, deployment stressors, adverse life events and PTSD symptoms. The prevalence of the resilient trajectory suggests a substantial level of resilience among deployed military personnel. These findings provide valuable insights and a foundation for further research.

An Evaluation of Fit Indices Used in Model Selection of Dichotomous Mixture IRT Models

A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's information criterion (DIC), sample size adjusted BIC (SABIC), relative entropy, the integrated classification likelihood criterion (ICL-BIC), the adjusted Lo-Mendell-Rubin (LMR), and Vuong-Lo-Mendell-Rubin (VLMR). The accuracy of the fit indices was assessed for correct detection of the number of latent classes for different simulation conditions including sample size (2,500 and 5,000), test length (15, 30, and 45), mixture proportions (equal and unequal), number of latent classes (2, 3, and 4), and latent class separation (no-separation and small separation). Simulation study results indicated that as the number of examinees or number of items increased, correct identification rates also increased for most of the indices. Correct identification rates by the different fit indices, however, decreased as the number of estimated latent classes or parameters (i.e., model complexity) increased. Results were good for BIC, CAIC, DIC, SABIC, ICL-BIC, LMR, and VLMR, and the relative entropy index tended to select correct models most of the time. Consistent with previous studies, AIC and AICc showed poor performance. Most of these indices had limited utility for three-class and four-class mixture 3PL model conditions.

Trajectories of squamous cell carcinoma antigen and outcomes of patients with advanced penile cancer after chemotherapy based on paclitaxel, ifosfamid, and cisplatin regimen

INTRODUCTION

Penile cancer (PC) is a lethal malignancy with no effective prognostic biomarker. We aim to investigate associations between trajectories of squamous cell carcinoma antigen (SCC-A) and patient outcomes after chemotherapy based on paclitaxel, ifosfamid, and cisplatin (TIP) regimen.

METHODS

Consecutive AJCC staging III/IV PC patients who received TIP chemotherapy and repeated SCC-A measurements in 2014-2022 were analyzed. Latent class growth mixed (LCGM) models were employed to characterize patients' serum SCC-A trajectories. Patient survival, and clinical and pathological tumor responses were compared. Inverse probability treatment weighting was used to adjust confounding factors.

RESULTS

Eighty patients were included. LCGM models identified two distinct trajectories of SCC-A: low-stable (40%; n = 32) and high-decline (60%; n = 48). Overall survival (HR [95% CI]: 3.60 [1.23-10.53], p = 0.019), progression-free survival (HR [95% CI]: 11.33 [3.19-40.3], p < 0.001), objective response rate (37.5% vs. 62.5% p = 0.028), disease control rate (60.4% vs. 96.9% p < 0.00), and pathological complete response rate (21.2% vs. 51.9%, p = 0.014) were significantly worse in the high-decline arm.

CONCLUSION

PC patients' SCC-A change rate was associated with tumor response and patient survival after TIP chemotherapy. SCC-A might assist tumor monitoring after systemic therapies.

Trajectories and determinants of acute stress disorder during the COVID-19 centralized quarantine: A latent class growth analysis

COVID-19 centralized quarantine may cause acute stress disorder (ASD). However, it is unknown how individuals present heterogeneous ASD trajectories during the COVID-19 centralized quarantine and what factors contribute to these patterns. This study aimed to identify the ASD trajectories and their determinants during the centralized quarantine period, and the mediating effects of resilience on these associations. A longitudinal survey with three waves was conducted in a randomly selected quarantine hotel in Shenzhen, China from October to November 2020. A total of 273 participants completed online measures assessing ASD symptoms, Eysenck's personality constructs of extraversion (E), neuroticism (N), psychoticism (P), and resilience on Day 1, and reported ASD symptoms on Days 7 and 14 during their 14-day centralized quarantine periods. Latent class growth analysis identified three trajectories: constantly high symptoms (CHS, 4.76%), decreasing symptoms (DS, 11.72%), and constantly low symptoms (CLS, 83.52%). The CHS and DS subgroups both reported lower E and higher N scores, but not P, compared with the CLS subgroup. Resilience mediated the effects of three personality constructs on ASD trajectories, except for the association between N and DS membership. Our study highlights the heterogeneity in stress responses to the COVID-19 centralized quarantine. The high-risk subgroup with persistent ASD symptoms was characterized by lower E and higher N. The resilience process accounted for the effects of personality in shaping distinct ASD trajectories. Our findings have implications to detect the populations vulnerable to ASD and provide insights for developing timely resilience enhancement intervention programs.

10-Year Multimorbidity Trajectories in Older People Have Limited Benefit in Predicting Short-Term Health Outcomes in Comparison to Standard Multimorbidity Thresholds: A Population-Based Study

Purpose

To identify multimorbidity trajectories among older adults and to compare their health outcome predictive performance with that of cross-sectional multimorbidity thresholds (eg, ≥2 chronic conditions (CCs)).

Patients and Methods

We performed a population-based longitudinal study with a random sample of 99,411 individuals aged >65 years on April 1, 2019. Using health administrative data, we calculated for each individual the yearly CCs number from 2010 to 2019 and constructed the trajectories with latent class growth analysis. We used logistic regression to determine the increase in predictive capacity (c-statistic) of multimorbidity trajectories and traditional cross-sectional indicators (≥2, ≥3, or ≥4 CCs, assessed in April 2019) over that of a baseline model (including age, sex, and deprivation). We predicted 1-year mortality, hospitalization, polypharmacy, and frequent general practitioner, specialist, or emergency department visits.

Results

We identified eight multimorbidity trajectories, each representing between 3% and 25% of the population. These trajectories exhibited trends of increasing, stable, or decreasing number of CCs. When predicting mortality, the 95% CI for the increase in the c-statistic for multimorbidity trajectories [0.032-0.044] overlapped with that of the ≥3 indicator [0.037-0.050]. Similar results were observed when predicting other health outcomes and with other cross-sectional indicators.

Conclusion

Multimorbidity trajectories displayed comparable health outcome predictive capacity to those of traditional cross-sectional multimorbidity indicators. Given its ease of calculation, continued use of traditional multimorbidity thresholds remains relevant for population-based multimorbidity surveillance and clinical practice.

Joint trajectories of loneliness, social isolation and sarcopenia and associations with adverse outcomes: A prospective cohort study

This study aimed to examine joint trajectories of loneliness, social isolation and sarcopenia and their associations with adverse outcomes. A total of 4701 participants aged ≥60 years who had a baseline and at least one follow-up assessment of loneliness, social isolation and sarcopenia across 2011, 2013 and 2015 waves in China Health and Retirement Longitudinal Study. Adverse outcomes were obtained in 2018 wave. Joint trajectories were fit using the parallel process latent class growth analysis, and their associations with adverse outcomes were evaluated using modified Poisson regression. Joint trajectory patterns for social relationship and sarcopenia did not vary by the assessment for sarcopenia, but did vary by the assessment for social relationship. Older adults exhibit distinct joint trajectories and those with persistent combination of loneliness or social isolation and sarcopenia experience greatest risk of adverse outcomes. These findings implicate integration of health care and social care for community-dwelling older adults.

Weekly pain trajectories among people with knee or hip osteoarthritis participating in a digitally delivered first-line exercise and education treatment

OBJECTIVE

Digital self-management programs are increasingly used in the management of osteoarthritis (OA). Little is known about heterogeneous patterns in response to these programs. We describe weekly pain trajectories of people with knee or hip OA over up to 52-week participation in a digital self-management program.

METHODS

Observational cohort study among participants enrolled between January 2019 and September 2021 who participated at least 4 and up to 52 weeks in the program (n = 16 274). We measured pain using Numeric Rating Scale (NRS 0-10) and applied latent class growth analysis to identify classes with similar trajectories. Associations between baseline characteristics and trajectory classes were examined using multinomial logistic regression and dominance analysis.

RESULTS

We identified 4 pain trajectory classes: "mild-largely improved" (30%), "low moderate-largely improved" (34%), "upper moderate-improved" (24%), and "severe-persistent" (12%). For classes with decreasing pain, the most pain reduction occurred during first 20 weeks and was stable thereafter. Male sex, older age, lower body mass index (BMI), better physical function, lower activity impairment, less anxiety/depression, higher education, knee OA, no walking difficulties, no wish for surgery and higher physical activity, all measured at enrolment, were associated with greater probabilities of membership in "mild-largely improved" class than other classes. Dominance analysis suggested that activity impairment followed by wish for surgery and walking difficulties were the most important predictors of trajectory class membership.

CONCLUSIONS

Our results highlight the importance of reaching people with OA for first-line treatment prior to developing severe pain, poor health status and a wish for surgery.

Health-related quality of life trajectories up to 15 years after curative treatment for esophageal cancer: a prospective cohort study

BACKGROUND

The differentiation of specific, long-term health-related quality of life (HRQL) trajectories among esophageal cancer survivors remains unclear. The authors aimed to identify potentially distinctly different HRQL-trajectories and uncover the underlying factors of such trajectories in patients having undergone surgery (esophagectomy) for esophageal cancer.

MATERIALS AND METHODS

This nationwide, prospective, and longitudinal cohort study included 420 patients who underwent curative treatment for esophageal cancer, including esophageal cancer surgery, in Sweden from 2001to 2005. The main outcome was HRQL summary score trajectories, measured by the well-validated EORTC QLQ-C30 questionnaire at 6 months, 3, 5, 10, and 15 years after esophagectomy, and analyzed using growth mixture models. Potentially underlying factors for these trajectories (age, sex, education, proxy baseline HRQL, comorbidity, tumor histology, chemo(radio)therapy, pathological tumor stage, and postoperative complications) were analyzed using weighted logistic regression providing odds ratios (OR) with 95% CI.

RESULTS

Four distinct HRQL summary score trajectories were identified: Persistently good, improving, deteriorating, and persistently poor. The odds of belonging to a persistently poor trajectory were decreased by longer education (>12 years versus <9 years: OR 0.18, 95% CI: 0.05-0.66) and adenocarcinoma histology (adenocarcinoma versus squamous cell carcinoma: OR 0.37, 95% CI: 0.16-0.85), and increased by more advanced pathological tumor stage (III-IV versus 0-I: OR 2.82, 95% CI: 1.08-7.41) and postoperative complications (OR 2.94, 95% CI: 1.36-6.36).

CONCLUSION

Distinct trajectories with persistently poor or deteriorating HRQL were identified after curative treatment for esophageal cancer. Education, tumor histology, pathological tumor stage, and postoperative complications might influence HRQL trajectories. The results may contribute to a more tailored follow-up with timely and targeted interventions. Future research remains to confirm these findings.

Cancer-related fatigue trajectories up to 5 years after curative treatment for oesophageal cancer

BACKGROUND

Whether cancer-related fatigue develops differently after curative-intended oesophageal cancer treatment and the related modifiable factors are unclear.

METHODS

This population-based and longitudinal cohort included 409 oesophageal cancer patients who underwent curative oesophagectomy in 2013-2020 in Sweden. The main outcome was cancer-related fatigue trajectories with measurements at 1, 1.5, 2, 2.5, 3, 4 and 5 years postoperatively by validated EORTC QLQ-FA12 questionnaire, and analysed using growth mixture models. Weighted logistic regressions provided odds ratios (OR) with 95% confidence intervals (95% CI) for underlying sociodemographic, clinical, and patient-reported outcome factors in relation to the identified trajectories.

RESULTS

Two distinct overall cancer-related fatigue trajectories were identified: low level of persistent fatigue and high level of increasing fatigue, with 64% and 36% of patients, respectively. The odds of having high level of fatigue trajectory were increased by Charlson comorbidity index (≥ 2 versus 0: OR = 2.52, 95% CI 1.07-5.94), pathological tumour Stage (III-IV versus 0-I: OR = 2.52, 95% CI 1.33-4.77), anxiety (OR = 7.58, 95% CI 2.20-26.17), depression (OR = 15.90, 95% CI 4.44-56.93) and pain (continuous score: OR = 1.02, 95% CI 1.01-1.04).

CONCLUSIONS

Long-term trajectories with high level of increasing cancer-related fatigue and the associated modifiable factors were identified after oesophageal cancer treatment. The results may facilitate early identification and targeted intervention for such high-risk patients.

Work- and mental health-related events and body mass index trajectories during the Covid-19 lockdown. Evidence from the lifelines cohort study in the Netherlands

BACKGROUND

The aim of this study was to identify heterogeneity in trajectories of body mass index (BMI) during the Covid-19 pandemic in the Netherlands. Moreover, we aimed to investigate whether work- and mental health-related disruptive events experienced during the pandemic, such as job insecurity or depression, were associated with such BMI trajectories.

METHODS

Longitudinal data from the Lifelines Covid Questionnaire was used (21 waves between April 2020 and July 2021; n = 64,630). Different trajectories were identified using group-based trajectory models. Multinomial regression models were fitted to analyse the main determinants of experiencing changes in BMI during the pandemic.

RESULTS

Trajectories of increased BMI, and, to a lesser extent also trajectories of decreased BMI, were more common among those who experienced disruptive work-related events (e.g., being laid-off or having a temporary contract) and mental health-related events (e.g., anxiety or depression) during the pandemic. Those experiencing multiple events were particularly likely to show trajectories of increased or decreased BMI.

CONCLUSIONS

During the Covid-19 pandemic, strong heterogeneity was observed in BMI trajectories. This was partially related to work- and mental health-related events.

The role of self-compassion in loneliness during the COVID-19 pandemic: a group-based trajectory modelling approach

Research has suggested an increase in loneliness during the COVID-19 pandemic, but much of this work has been cross-sectional, making causal inferences difficult. In the present research, we employed a longitudinal design to identify loneliness trajectories within a period of twelve months during the COVID-19 pandemic in Belgium (N = 2106). We were particularly interested in the potential protective role of self-compassion in these temporal dynamics. Using a group-based trajectory modelling approach, we identified trajectory groups of individuals following low (11.0%), moderate-low (22.4%), moderate (25.7%), moderate-high (31.3%), and high (9.6%) levels of loneliness. Findings indicated that younger people, women, and individuals with poor quality relationships, high levels of health anxiety, and stress related to COVID-19, all had a higher probability of belonging to the highest loneliness trajectory groups. Importantly, we also found that people high in two of the three facets of self-compassion (self-kindness and common humanity) had a lower probability of belonging to the highest loneliness trajectory groups. Ultimately, we demonstrated that trajectory groups reflecting higher levels of loneliness were associated with lower life satisfaction and greater depressive symptoms. We discuss the possibility that increasing self-compassion may be used to promote better mental health in similarly challenging situations.

The Association Between Trajectories of Perceived Unmet Needs for Home and Community-Based Services and Life Satisfaction Among Chinese Older Adults: The Moderating Effect of Psychological Resilience

This study examined whether trajectories of perceived unmet needs for Home and Community-Based Services (HCBS) were associated with life satisfaction among Chinese older adults and whether the association was moderated by psychological resilience. Data came from five waves (2005-2018) of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Latent class growth analysis revealed three distinct trajectories of perceived unmet HCBS needs: "increasing" (n = 977, 36.24%), "persistent" (n = 570, 21.14%), and "decreasing" (n = 1149, 42.62%). Multiple regression estimates showed that the increasing group was associated with lower life satisfaction, and the association was moderated by psychological resilience, especially for older adults who were male, living in rural, and oldest-old. Results indicate that inequalities in cumulative exposure to perceived unmet HCBS needs may further lead to increasing inequalities in life satisfaction. Interventions focused on minimizing the provision-need gap of HCBS and enhancing personal resilience should be considered to improve the life satisfaction of older adults.

Joint developmental trajectories of internalizing and externalizing problems from mid-childhood to late adolescence and childhood risk factors: Findings from a prospective pre-birth cohort

There is limited evidence on heterogenous co-developmental trajectories of internalizing (INT) and externalizing (EXT) problems from childhood to adolescence and predictors of these joint trajectories. We utilized longitudinal data from Raine Study participants (n = 2393) to identify these joint trajectories from 5 to 17 years using parallel-process latent class growth analysis and analyze childhood individual and family risk factors predicting these joint trajectories using multinomial logistic regression. Five trajectory classes were identified: Low-problems (Low-INT/Low-EXT, 29%), Moderate Externalizing (Moderate-EXT/Low-INT, 26.5%), Primary Internalizing (Moderate High-INT/Low-EXT, 17.5%), Co-occurring (High-INT/High-EXT, 17%), High Co-occurring (Very High-EXT/High-INT, 10%). Children classified in Co-occurring and High Co-occurring trajectories (27% of the sample) exhibited clinically meaningful co-occurring problem behaviors and experienced more adverse childhood risk-factors than other three trajectories. Compared with Low-problems: parental marital problems, low family income, and absent father predicted Co-occurring and High Co-occurring trajectories; maternal mental health problems commonly predicted Primary Internalizing, Co-occurring, and High Co-occurring trajectories; male sex and parental tobacco-smoking uniquely predicted High Co-occurring membership; other substance smoking uniquely predicted Co-occurring membership; speech difficulty uniquely predicted Primary Internalizing membership; child's temper-tantrums predicted all four trajectories, with increased odds ratios for High Co-occurring (OR = 8.95) and Co-occurring (OR = 6.07). Finding two co-occurring trajectories emphasizes the importance of early childhood interventions addressing comorbidity.

Trajectories of self-kindness, common humanity, and mindfulness during the COVID-19 pandemic: A person-oriented multi-trajectory approach

The COVID-19 pandemic has produced unprecedented changes in the lives of many people. Although research has documented associations between concerns related to COVID-19 and poor mental health indicators, fewer studies have focused on positive factors that could help people better cope with this stressful social context. To fill this gap, the present research investigated the trajectories of self-compassion facets in times of dramatic social change. Using a longitudinal research design, we described the trajectories of self-kindness, common humanity, and mindfulness during the first eight months of the COVID-19 pandemic, in a representative sample of Canadian adults (N = 3617). Relying on a multi-trajectory group-based approach, we identified clusters of individuals following persistently low (4.0%), moderate-low (39.3%), moderate-high (46.7%), and high (10.0%) levels of self-kindness, common humanity, and mindfulness. Interestingly, we found that compassionate self-responding trajectories were mainly stable over time with minor fluctuations for some groups of individuals, in line with the epidemiological situation. In terms of covariates, we observed that older women were more likely to follow trajectories of high compassionate self-responding, as compared to the other age and gender groups. In terms of mental health indicators, we demonstrated that trajectory groups with high levels of compassionate self-responding were associated with greater life satisfaction, more happiness, better sleep quality, higher sleep quantity, and fewer negative emotions, as compared to lower trajectory groups. The results supported the idea that self-compassion during the COVID-19 pandemic could have favored better mental health indicators and could possibly be promoted as a psychological intervention in the general population.

Multisystemic supports and adolescent resilience to depression over time: A South African mixed methods study

In sub-Saharan countries, like South Africa, there is scant understanding of adolescent resilience to depression over time; the multisystemic resource combinations that support such resilience; and whether more diverse resource combinations yield better mental health dividends. In response, we conducted a longitudinal concurrent nested mixed methods study with 223 South African adolescents (mean age: 17.16 years, SD = 1.73; 64.60% girls; 81.60% Black). Using longitudinal mixture modeling, the quantitative study identified trajectories of depression and associations between trajectory membership and resource diversity. Using a draw-and-write methodology and reflexive thematic analyses, the qualitative study explored the resource diversity associated with each trajectory. Taken together, these studies identified four depression trajectories (Stable Low; Declining; Worsening; Chronic High) with varying resource diversity at baseline and over time. Resource diversity was inclusive of personal, relational, contextual, and culturally valued resources in both the Stable Low and Declining trajectories, with emphasis on relational supports. Personal resources were emphasized in the Worsening and Chronic High trajectories, and culturally valued and contextual resources de-emphasized. In summary, resource constellations characterized by within and across system diversity and cultural responsiveness are more protective and will be key to advancing sub-Saharan adolescent mental health.

Childhood emotional dysregulation paths for suicide-related behaviour engagement in adolescence

This study aimed at identifying the heterogeneous trajectories of emotional dysregulation across childhood and to study the relationship between specific trajectories and adolescent suicide-related behaviour (SRB). Data from the Millennium Cohort Study (N = 13,853 children; 49.07% female, M = 3.13 years at baseline, SD = 0.2) were used to identify the emotional dysregulation trajectories from 3 to 8 years old, using growth mixture modelling. Moreover, 1992 participants (52.86% female) from the initial sample were used to study the relationship between childhood emotional dysregulation trajectory and engagement in both self-harm and suicide attempt at age 17, using logistic regression. Some other time-invariant and proximal (adolescent) risk factors were incorporated into this analysis. Six emotional dysregulation trajectories were identified. Self-harm at age 17 was significantly associated with the history of self-harm and other proximal factors, but not with emotional dysregulation trajectory membership. Childhood trajectories featured by earlier emotional dysregulation were associated with higher risk of lifetime suicide attempt, as well as other proximal factors (concurrent self-harm). This study found differential risk profiles involved in both SRB forms. A relationship between early emotional dysregulation and suicide attempt engagement in adolescence was identified. Early interventions should be developed to deal with SRB risk factors from childhood.

Trajectories of health behaviors during the COVID-19 pandemic: a longitudinal analysis of handwashing, mask wearing, social contact limitations, and physical distancing

AIM

This study aimed to investigate the associations between health behavior adherence and psychological factors during the COVID-19 pandemic, with a particular focus on identifying trajectories of handwashing, mask wearing, social contact limitations, and physical distancing.

METHODS

We employed a multi-trajectory group-based approach to analyze data from 6026 Belgian residents, including 60% women, with an average age of 52.65. Data were collected over six waves spanning from April 2021 to December 2021.

RESULTS

Participants were categorized into trajectory groups based on persistently low (11.9%), moderate-low (20.9%), moderate-high (39.1%), and high (28.1%) levels of adherence to the specified health behaviors. Our findings indicate a declining trend in health behavior adherence over the study period. Additionally, we observed that females, older individuals, and those with prior COVID-19 infection had a higher likelihood of belonging to trajectory groups characterized by the highest levels of health behavior adherence. Similarly, individuals with positive vaccination intentions, a heightened perception of consequences, and increased health anxiety demonstrated greater adherence to health behaviors over time. Furthermore, our investigation into the relationship between health behaviors and mental health revealed that participants in trajectory groups with higher levels of adherence to social contact limitations and physical distancing reported increased feelings of loneliness and decreased life satisfaction.

CONCLUSIONS

The COVID-19 pandemic has reshaped our lives, and while vaccines have marked progress, maintaining health behaviors is crucial for virus prevention. To address potential mental health challenges from sanitary measures, policies and communication should promote health behaviors while acknowledging their psychological impact.

Venous bicarbonate and CKD progression: a longitudinal analysis by the group-based trajectory model

Background

Metabolic acidosis accelerates chronic kidney disease (CKD) progression towards kidney failure in animal models. Clinical trials testing the effect of bicarbonate on kidney outcomes are underpowered and/or of suboptimal quality. On the other hand, observational studies testing the same hypothesis are generally based on bicarbonate measured at a single time point.

Methods

We studied the longitudinal relationship between repeated venous bicarbonate levels and a predefined composite renal outcome (a ≥30% estimated glomerular filtration rate reduction, dialysis or transplantation) by using group-based trajectory model (GBTM) analysis. The GBTM analysis was used to classify patients based on individual bicarbonate levels over time. The relationship between trajectory groups and renal outcomes was investigated using crude and adjusted Cox regression models. A total of 528 patients with stage 2-5 CKD were included in the analysis.

Results

The GBTM analysis identified four distinct trajectories of bicarbonate levels: low, moderate, moderate-high and high. During the follow-up period, 126 patients experienced the combined renal endpoint. The hazard rate of renal events decreased dose-dependently from the lowest to the highest bicarbonate trajectory. After adjusting for potential confounders, there was a 63% risk reduction for the composite renal endpoint for patients in the high trajectory category compared with those in the low trajectory category.

Conclusion

The study found that higher bicarbonate trajectories were associated with a lower risk of adverse renal outcomes in CKD patients. These results suggest that strategies to maintain higher bicarbonate levels may benefit patients with CKD. However, further high-quality randomised trials are needed to confirm these findings and recommend bicarbonate supplementation as a strategy to delay CKD progression.

Marginal structural models with latent class growth analysis of treatment trajectories: Statins for primary prevention among older adults

Latent class growth analysis is increasingly proposed as a solution to summarize the observed longitudinal treatment into a few distinct groups. When latent class growth analysis is combined with standard approaches like Cox proportional hazards models, confounding bias is not properly addressed because of time-varying covariates that have a double role of confounders and mediators. We propose to use latent class growth analysis to classify individuals into a few latent classes based on their medication adherence pattern, then choose a working marginal structural model that relates the outcome to these groups. The parameter of interest is defined as a projection of the true marginal structural model onto the chosen working model. Simulation studies are used to illustrate our approach and compare it with unadjusted, baseline covariates adjusted, time-varying covariates adjusted, and inverse probability of trajectory groups weighted adjusted models. Our proposed approach yielded estimators with little or no bias and appropriate coverage of confidence intervals in these simulations. We applied our latent class growth analysis and marginal structural model approach to a database comprising information on 52,790 individuals from the province of Quebec, Canada, aged more than 65 and who were statin initiators to estimate the effect of statin-usage trajectories on a first cardiovascular event.

BELMM: Bayesian model selection and random walk smoothing in time-series clustering

MOTIVATION

Due to advances in measuring technology, many new phenotype, gene expression, and other omics time-course datasets are now commonly available. Cluster analysis may provide useful information about the structure of such data.

RESULTS

In this work, we propose BELMM (Bayesian Estimation of Latent Mixture Models): a flexible framework for analysing, clustering, and modelling time-series data in a Bayesian setting. The framework is built on mixture modelling: first, the mean curves of the mixture components are assumed to follow random walk smoothing priors. Second, we choose the most plausible model and the number of mixture components using the Reversible-jump Markov chain Monte Carlo. Last, we assign the individual time series into clusters based on the similarity to the cluster-specific trend curves determined by the latent random walk processes. We demonstrate the use of fast and slow implementations of our approach on both simulated and real time-series data using widely available software R, Stan, and CU-MSDSp.

AVAILABILITY AND IMPLEMENTATION

The French mortality dataset is available at http://www.mortality.org, the Drosophila melanogaster embryogenesis gene expression data at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121160. Details on our simulated datasets are available in the Supplementary Material, and R scripts and a detailed tutorial on GitHub at https://github.com/ollisa/BELMM. The software CU-MSDSp is available on GitHub at https://github.com/jtchavisIII/CU-MSDSp.

Multiple Trajectories of Cereal Consumption and Their Associations with Type 2 Diabetes in Chinese Adults - China, 1997-2018

What is already known about this topic?

Consuming refined grains, specifically white rice, elevates the risk of developing type 2 diabetes (T2D). Conversely, incorporating whole grains into the diet is linked to a reduced risk.

What is added by this report?

This study employed a novel multi-trajectory modeling technique to account for the intercorrelations among various cereal consumption patterns. Four distinct multi-trajectory groups of cereal intake, identified from 1997 to 2018 within the Chinese population, were associated with varying levels of T2D risk.

What are the implications for public health practice?

This research investigates the implications of evolving cereal consumption patterns on T2D in nondiabetic adults. This study delineates unique trajectories linked with cereal intake patterns, thereby providing a robust foundation for policymakers to craft initiatives to prevent T2D among adults in China.

Trajectories of depression symptoms, anxiety symptoms and functional impairment during internet-enabled cognitive-behavioural therapy

Underlying classes capture differences between patient symptom trajectories during psychological therapy. This has not been explored for one-to-one internet-delivered therapy or functional impairment trajectories. Patients experiencing depression or anxiety received cognitive-behavioural therapy with a therapist using an online chat platform (N = 52,029). Trajectory classes of depression symptoms (PHQ9), anxiety symptoms (GAD7) and functional impairment (WSAS) were investigated using growth mixture modelling. Multinomial regressions tested associations between baseline variables and trajectory class. A four-class trajectory model was selected for each outcome, and these were highly similar. Each outcome showed three classes with initially moderate-severe symptoms or impairment: one demonstrated no change, one gradual improvement and one fast improvement. A fourth class had mild baseline scores and minimal improvement. In the moderate-severe classes, patients in the two with improvement were more likely to be employed and not to have obsessive-compulsive disorder. Fast improvement was likelier than gradual improvement or no change for patients with older age, no disability (e.g., physical, learning), or lower comorbid symptom or impairment scores. Associations with functional impairment classes were more similar to associations with depression classes than anxiety classes. Results were largely consistent with findings from face-to-face therapy. This study is an important step towards personalising therapy in terms of suitability and continuation.

Sex-specific medication trajectories in older adults newly diagnosed with diabetes

Background

People with diabetes tend to use many medications to treat diabetes and comorbidities. Nevertheless, the evolution of polypharmacy in newly diagnosed males and females has been little studied.

Objective

The objective of this paper was to identify and describe medication trajectories in incident diabetes cases according to sex.

Methods

Data were obtained from the Quebec Integrated Chronic Disease Surveillance System. We built a population-based cohort of community-dwelling individuals aged >65 years diagnosed with diabetes in 2014 who were alive and covered with the public drug plan until March 31, 2019. Latent class models were used to identify medication trajectory groups in males and females separately.

Results

Of the 10,363 included individuals, 51.4% were males. Females were older and more likely to have more medication claims than males. Four trajectory groups were identified for males and five for females. Most trajectories showed sustained and stable number of medications over time. For each sex, only one of the trajectory groups included a mean annual number of medications lesser than five. Slight increasing trends of medication use were detected in the trajectories composed of very high users, which included older, more comorbid individuals frequently exposed to potentially inappropriate medications.

Conclusions

Most males and females with incident diabetes had a high burden of medication following the year of diagnosis and were classified in a group of sustained medication use over time. The largest increase in medication was among those who had higher level of polypharmacy of questionable quality at baseline, raising concerns about the innocuity of such medication trajectories.

Childhood body mass index trajectories and asthma and allergies: A systematic review

BACKGROUND

Previous systematic reviews have focused on associations between single time point measures of Body Mass Index (BMI) and asthma and allergic diseases. As BMI changes dynamically during childhood, examination of associations between longitudinal trajectories in BMI and allergic diseases is needed to fully understand the nature of these relationships.

OBJECTIVE

To systematically synthesise the association between BMI trajectories in childhood (0-18 years) and allergic diseases (asthma, eczema, allergic rhinitis, or food allergies outcomes).

DESIGN

We conducted a systematic review following the PRISMA guidelines, and two independent reviewers assessed the study quality using the ROBINS-E and GRADE tools. A narrative synthesis was performed as the statistical heterogeneity did not allow a meta-analysis.

DATA SOURCES

A search was performed on PubMed and EMBASE databases on 4th January 2023.

ELIGIBILITY CRITERIA

Longitudinal cohort studies assessing the associations between childhood BMI trajectories and allergic diseases were included.

RESULTS

Eleven studies met the inclusion criteria with a total of 37,690 participants between 0 and 53 years of age. Ten studies examined asthma outcomes, three assessed association with allergic rhinitis, two assessed eczema, and one assessed food allergy. High heterogeneity and high risk of bias were observed. Overall, the quality of evidence was very low. Nevertheless, two consistent findings were identified: (1) a persistently high BMI between 6 and 10 years of age may be associated with an increased risk of asthma at 18 years and (2) a rapid increase in BMI in the first 2 years of life may be associated with subsequent asthma.

CONCLUSIONS

Maintaining a normal BMI trajectory during childhood may reduce the risk of asthma. Future research that adequately addresses confounding and includes longer-term follow-up is needed. Moreover, additional studies examining potential associations with eczema, food allergies, and allergic rhinitis outcomes are needed.

Analysis of heterogeneous growth changes in longitudinal height of children

BACKGROUND

There have been methodologies developed for a wide range of longitudinal data types; nevertheless, the conventional growth study is restricted if individuals in the sample have heterogeneous growth trajectories across time. Using growth mixture modeling approaches, we aimed to investigate group-level heterogeneities in the growth trajectories of children aged 1 to 15 years.

METHOD

This longitudinal study examined group-level growth heterogeneities in a sample of 3401 males and 3200 females. Data were analyzed using growth mixture modeling approaches.

RESULTS

We examined different trajectories of growth change in children across four low- and middle-income countries using a data-driven growth mixture modeling technique. The study identified two-group trajectories: the most male samples group (n = 4260, 69.7%) and the most female samples group (n = 2341, 81.6%). The findings show that the two groups had different growth trajectories. Gender and country differences were shown to be related to growth factors; however, the association varied depending on the trajectory group. In both latent groups, females tended to have lower growth factors (initial height and rate of growth) than their male counterparts. Compared with children from Ethiopia, children from Peru and Vietnam tended to exhibit faster growth in height over time: In contrast, children from India showed a lower rate of change in both latent groups than that of children from Ethiopia.

CONCLUSIONS

The height of children in four low- and middle-income countries showed heterogeneous changes over time with two different groups of growth trajectories.

Trajectories of Meat Intake and Risk of Type 2 Diabetes: Findings from the China Health and Nutrition Survey (1997-2018)

Few articles have investigated the impact of long-term meat intake trends and their changes during follow-up on the risk of type 2 diabetes (T2D). We aimed to explore the long-term trajectories of meat intake and determine its association with T2D risk in Chinese adults. This study used seven rounds of data from the China Health and Nutrition Survey (1997, 2000, 2004, 2006, 2009, 2015, and 2018), and 4464 adults aged 18 years or older were analyzed. The group-based trajectory modeling was used to identify meat intake trajectories over 21 years. Multivariate Cox proportional hazard and restricted cubic spline models were used to analyze the association and dose-response relationship between meat intake and T2D. Four trajectory groups were identified: "low-increase intake group" (Group 1), "moderate-increase intake group" (Group 2), "medium-stable intake group" (Group 3), and "high intake group" (Group 4). Compared with Group 2, Group 4 was associated with a higher risk of developing T2D (hazard ratio 2.37 [95% CI 1.41-3.98]). After adjusting for demographic characteristics, lifestyle, total energy intake, waist circumference, and systolic blood pressure, and using the third quintile as a reference, the risk of T2D was increased by 46% in the lowest quintile with meat intake (hazard ratio 1.46 [95% CI 1.07-2.01]) and by 41% in the highest quintile with meat intake (HR 1.41 [95% CI 1.03-1.94]). A U-shape was observed between meat intake and T2D risk (p for nonlinear < 0.001). When the intake was lower than 75 g/day, the risk of T2D was negatively correlated with meat intake, while the risk of T2D was positively correlated with meat intake when the intake was higher than 165 g/day. We identified four trajectory groups of meat intake from 1997 to 2018, which were associated with different risks of developing T2D. A U-shaped association was observed between meat intake and T2D in Chinese adults.

Clustering of the causes of death in Northeast Iran: a mixed growth modeling

BACKGROUND

Processing and analyzing data related to the causes of mortality can help to clarify and monitor the health status, determine priorities, needs, deficiencies, and developments in the health sector in research and implementation areas. In some cases, the statistical population consists of invisible sub-communities, each with a pattern of different trends over time. In such cases, Latent Growth Mixture Models (LGMM) can be used. This article clusters the causes of individual deaths between 2015 and 2019 in Northeast Iran based on LGMM.

METHOD

This ecological longitudinal study examined all five-year mortality in Northeast Iran from 2015 to 2019. Causes of mortality were extracted from the national death registration system based on the ICD-10 classification. Individuals' causes of death were categorized based on LGMM, and similar patterns were placed in one category.

RESULTS

Out of the total 146,100 deaths, ischemic heart disease (21,328), malignant neoplasms (17,613), cerebrovascular diseases (11,924), and hypertension (10,671) were the four leading causes of death. According to statistical indicators, the model with three classes was the best-fit model, which also had an appropriate interpretation. In the first class, which was also the largest class, the pattern of changes in mortality due to diseases was constant (n = 98, 87.50%). Second-class diseases had a slightly upward trend (n = 10, 8.92%), and third-class diseases had a completely upward trend (n = 4, 3.57%).

CONCLUSIONS

Identifying the rising trends of diseases leading to death using LGMM can be a suitable tool for the prevention and management of diseases by managers and health policy. Some chronic diseases are increasing up to 2019, which can serve as a warning for health policymakers in society.

Associations between trajectories of adolescent conduct problems and psychological well-being in young women

INTRODUCTION

Despite the clinical relevance, little is known about variability in positive adult outcomes (i.e., flourishing, life satisfaction) of female adolescent conduct problems (CP), or interpersonal factors that promote these types of well-being. We hypothesized differential associations between adolescent CP trajectories and indicators of adult well-being due to level of positive relationships with caregivers during ages 12-17.

METHOD

Data were drawn from participants (N = 1965) of the Pittsburgh Girls Study, a longitudinal study of girls' development. Caregiver reported CP, adolescent reports of parental trust and positive parenting, and adolescent-reported peer delinquency were assessed annually between ages 12-17. Well-being in young adulthood was measured using self-reported flourishing and life satisfaction between ages 18-22.

RESULTS

Latent class growth analysis of adolescent CP revealed four trajectories characterized as low stable (20.0%), moderate stable (63.9%), adolescent-onset (8.1%), and high quadratic (8.0%). Main effects of trust and positive relationships with caregivers during adolescence on well-being in early adulthood were found. Positive parenting was found to moderate the association between CP trajectory and flourishing. The magnitude of the negative association between the high quadratic trajectory group and life satisfaction decreased as positive parenting increased.

CONCLUSION

These results support the importance of intervention in adolescence to focus on increasing trusting and positive relationships with caregivers for all females, as this may increase well-being in adulthood regardless of adolescent CP history.

Evaluation and interpretation of latent class modelling strategies to characterise dietary trajectories across early life: a longitudinal study from the Southampton Women's Survey

There is increasing interest in modelling longitudinal dietary data and classifying individuals into subgroups (latent classes) who follow similar trajectories over time. These trajectories could identify population groups and time points amenable to dietary interventions. This paper aimed to provide a comparison and overview of two latent class methods: group-based trajectory modelling (GBTM) and growth mixture modelling (GMM). Data from 2963 mother-child dyads from the longitudinal Southampton Women's Survey were analysed. Continuous diet quality indices (DQI) were derived using principal component analysis from interviewer-administered FFQ collected in mothers pre-pregnancy, at 11- and 34-week gestation, and in offspring at 6 and 12 months and 3, 6-7 and 8-9 years. A forward modelling approach from 1 to 6 classes was used to identify the optimal number of DQI latent classes. Models were assessed using the Akaike and Bayesian information criteria, probability of class assignment, ratio of the odds of correct classification, group membership and entropy. Both methods suggested that five classes were optimal, with a strong correlation (Spearman's = 0·98) between class assignment for the two methods. The dietary trajectories were categorised as stable with horizontal lines and were defined as poor (GMM = 4 % and GBTM = 5 %), poor-medium (23 %, 23 %), medium (39 %, 39 %), medium-better (27 %, 28 %) and best (7 %, 6 %). Both GBTM and GMM are suitable for identifying dietary trajectories. GBTM is recommended as it is computationally less intensive, but results could be confirmed using GMM. The stability of the diet quality trajectories from pre-pregnancy underlines the importance of promotion of dietary improvements from preconception onwards.

Self-reported life-space mobility in the first year after ischemic stroke: longitudinal findings from the MOBITEC-Stroke project

BACKGROUND

Life-space mobility is defined as the size of the area in which a person moves about within a specified period of time. Our study aimed to characterize life-space mobility, identify factors associated with its course, and detect typical trajectories in the first year after ischemic stroke.

METHODS

MOBITEC-Stroke (ISRCTN85999967; 13/08/2020) was a cohort study with assessments performed 3, 6, 9 and 12 months after stroke onset. We applied linear mixed effects models (LMMs) with life-space mobility (Life-Space Assessment; LSA) as outcome and time point, sex, age, pre-stroke mobility limitation, stroke severity (National Institutes of Health Stroke Scale; NIHSS), modified Rankin Scale, comorbidities, neighborhood characteristics, availability of a car, Falls Efficacy Scale-International (FES-I), and lower extremity physical function (log-transformed timed up-and-go; TUG) as independent variables. We elucidated typical trajectories of LSA by latent class growth analysis (LCGA) and performed univariate tests for differences between classes.

RESULTS

In 59 participants (mean age 71.6, SD 10.0 years; 33.9% women), mean LSA at 3 months was 69.3 (SD 27.3). LMMs revealed evidence (p ≤ 0.05) that pre-stroke mobility limitation, NIHSS, comorbidities, and FES-I were independently associated with the course of LSA; there was no evidence for a significant effect of time point. LCGA revealed three classes: "low stable", "average stable", and "high increasing". Classes differed with regard to LSA starting value, pre-stroke mobility limitation, FES-I, and log-transformed TUG time.

CONCLUSION

Routinely assessing LSA starting value, pre-stroke mobility limitation, and FES-I may help clinicians identify patients at increased risk of failure to improve LSA.

Exposure to Intimate-Partner Violence and Resilience Trajectories of Adolescents: A Two-Wave Longitudinal Latent Transition Analysis

Despite the serious emotional and social consequences of adolescents' exposure to intimate-partner violence (IPV) and the high prevalence of this exposure, few analyses have focused on person-centered models or considered psychological IPV. Studies that address exposure to violence tend to focus on physical IPV. Therefore, in this study, we examine (across two waves) the trajectories of resilience among adolescents who have witnessed psychological IPV by conducting a latent transition analysis and predicting class membership through socio-demographic and individual-level protective factors. Using a sample of 879 (T1, fall 2020) and 770 (T2, spring 2022) adolescent Swiss students with mean ages of 11.74 (SD = 0.64) and 13.77 (SD = 0.53), we identified four distinct time-invariant resilience classes: comorbid-frustrated, internalizing-frustrated, comorbid-satisfied, and resilient. The classes characterized by some level of psychopathological symptoms and basic psychological-needs frustration were the most stable over time. Furthermore, we found the four typical resilience trajectories: recovery, chronic, delayed, and improving. Gender, socioeconomic background, and protective factors showed a significant prediction of class membership in wave 1, highlighting the importance of increasing sensitivity to psychological-IPV exposure on the one hand, and reinforcing the relevance of prevention in schools regarding the promotion of protective factors on the other.