OBJECTIVE: Polypharmacy serves as a quality indicator in residential aged care facilities (RACFs) due to concerns about inappropriate medication use. However, aggregated polypharmacy rates at a single time offer limited value. Longitudinal analysis of polypharmacy patterns provides valuable insights into identifying potential overuse of medicines. We aimed to determine long-term trajectories of polypharmacy (≥9 medicines) and factors associated with each polypharmacy trajectory group.
METHODS: This was a longitudinal cohort study using electronic data from 30 RACFs in New South Wales, Australia. We conducted group-based trajectory modelling to identify and characterize polypharmacy trajectories over 3 years. We evaluated the model fitness using the Bayesian Information Criterion, entropy (with a value of ≥0.8 considered ideal) and several other metrics.
RESULTS: The study included 2837 permanent residents (median age = 86 years, 61.7% female and 47.4% had dementia). We identified five polypharmacy trajectory groups: group 1 (no polypharmacy, 46.0%); group 2 (increasing polypharmacy, 9.4%); group 3 (decreasing polypharmacy, 9.2%); group 4 (increasing-then decreasing polypharmacy, 10.0%), and group 5 (persistent polypharmacy, 25.4%). The model showed excellent performance (e.g., entropy = 0.9). Multinomial logistic regressions revealed the profile of each trajectory group (e.g., group 5 residents had higher odds of chronic respiratory disease compared with group 1).
CONCLUSIONS: Our study identified five polypharmacy trajectory groups, including one with over a quarter of residents following a persistently high trajectory, signalling concerning medication overuse. Quality indicator programs should adopt tailored metrics to monitor diverse polypharmacy trajectory groups, moving beyond the current one-size-fits-all approach and better capturing the evolving dynamics of residents\' medication regimens.

Chronic diseases contribute to 68% of global mortality, highlighting the importance of early detection and management of conditions such as metabolic syndrome. Effective lifestyle interventions, particularly through mobile health (mHealth), have shown potential in promoting health and reducing cardiometabolic risk. This study utilized mHealth data from public health centers in South Korea, targeting adults with risk factors for metabolic syndrome. The Intervention-Motivation-Behavioral skills (IMB) theoretical model was applied to categorize participants\' practice patterns over time using the Group-Based Trend Model (GBTM). And the Generalized Estimating Equations (GEE) methodology was applied to confirm the effective practice patterns for improving metabolic syndrome. Data were collected over 24 weeks. The dataset encompasses life-log data capable of capturing changes in intervention, self-report surveys, and clinical measurements, all linked to personal identification keys and thereby integrated. Participants demonstrated improved health behaviors, with the healthy eating score increasing from 5.0 to 6.4 and physical activity rates rising from 41.5% to 59%. Health risk factors decreased significantly, with the mean number of risk factors dropping from 2.4 to 1.4. The percentage of subjects with three or more metabolic syndrome components decreased from 42.3% in the initial period to 19.2% in the final period. Practice patterns by IMB components were classified into three categories: continuous type, late decline type, and early decline type. Improvements in health behavior and metabolic syndrome were observed in the continuous type of each IMB component. The mHealth interventions were confirmed to be positively associated with improved health behavior and management of metabolic syndrome in the continuous practice patterns of IMB.

BACKGROUND: Research on health-related quality of life (HRQoL) trajectory patterns for people with disabilities (PwD) is scant. Understanding the HRQoL trajectory patterns for PwDs and investigating their relationship with disability types and socioeconomic factors can have important implications for Australia\'s welfare policy.
METHODS: We analysed data from waves 11 to 21 of the Household, Income and Labour Dynamics in Australia (HILDA) survey of respondents aged 15 + years of the PwDs. The analytic sample consists of 3724 self-reported disabled individuals and 34,539 observations in total. The SF-6D utility score is our HRQoL measure. Group-based trajectory modelling was utilised to identify trajectory groups, and multinomial logistic regression was employed to determine the baseline factors associated with trajectory group membership.
RESULTS: The study identified four distinct types of HRQoL trajectories (high, moderate improving, moderate deteriorating and low HRQoL trajectories). Psychosocial disability types followed by physical disability types had a high Relative Risk Ratio (RRR) in the low group compared with high trajectory group membership of PwDs (psychosocial: 6.090, physical: 3.524). Similar, results followed for the moderate improving group albeit with lower RRR (psychosocial: 2.868, Physical: 1.820). In the moderate deteriorating group, the disability types were not significant as this group has a similar profile to high group at the baseline. Compared with males, females had a higher RRR in low and moderate versus high improving HRQoL trajectories (low: 1.532, moderate improving: 1.237). Comparing the richest class to the poorest class, socioeconomic factors (income and education) predicted significantly lower exposure for the richer class to the low and medium HRQoL trajectories groups (RRR < 1).
CONCLUSIONS: Different forms of disability, demographic and socioeconomic factors have distinct effects on the HRQoL trajectories of disabled individuals. Healthcare and economic resource efficiency might be improved with targeted government policy interventions based on disability trajectories.

Individuals age at vastly different rates resulting in significant within-population heterogeneity in health and aging outcomes. This diversity in health and aging trajectories has rarely been investigated among low-income aging populations that have experienced substantial hardships throughout their lifecourses. Utilizing 2006-2018 data from the Malawi Longitudinal Study of Families and Health (MLSFH) and estimating group-based trajectory models (GBTM), our analyses identified three distinct lifecourse health trajectories: (1) comparatively good initial mental and physical health that persisted throughout the lifecourse (\"resilient aging\"); (2) relatively good initial mental and physical health that started to deteriorate during mid-adulthood (\"accelerated aging\"); and (3) poor initial mental and physical health that further declined over the lifecourse (\"aging with persistently poor health\"). For both physical and mental health, men were more likely to enjoy resilient aging than women. Predictors other than gender of trajectory membership sometimes confirmed, and sometimes contradicted, hypotheses derived from high-income country studies. Our analyses highlight the long arm of early life conditions and gender in determining aging trajectories and show that a non-trivial sub-population is characterized by aging with persistently poor health. The study uncovers widening gaps in health outcomes between those who age with resilience and those who experience accelerated aging.

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.

We investigate the roles of genetic predispositions, childhood SES and adult educational attainment in shaping trajectories for three important components of the overall health of older adults -- BMI, depressive symptoms and cognition. We use the Health & Retirement Study (HRS) and group-based trajectory modeling (GBTM) to identify subgroups of people who share the same underlying trajectories ages 51-94 years. After identifying common underlying health trajectories, we use fractional multinomial logit models to estimate associations of (1) polygenic scores for BMI, depression, ever-smoked, education, cognition and subjective wellbeing, (2) childhood SES and (3) educational attainment with the probabilities of trajectory group memberships. While genetic predispositions do play a part in predicting trajectory group memberships, our results highlight the long arm of socioeconomic factors. Educational attainment is the most robust predictor-it predicts increased probabilities of belonging to trajectories with BMI in the normal range, low depressive symptoms and very-high initial cognition. Childhood circumstances are manifested in trajectories to a lesser extent, with childhood SES predicting higher likelihood of being on the low depressive symptoms and very-high initial cognition trajectories. We also find suggestive evidence that associations of educational attainment on the probabilities of being on trajectories with BMI in the normal range, low depressive symptoms and very-high initial cognition vary with genetic predispositions. Our results suggest that policies to increase educational attainment may improve population health by increasing the likelihood of belonging to \"good\" aging trajectories.

The association between the instrumental activities of daily living (IADL) score and the risk of initial cognitive function impairment is inconclusive. We aimed to identify distinctive IADL trajectories and examine their relationship with the onset of mild cognitive impairment (MCI) among Chinese older people.
The study used six-wave longitudinal data from the Chinese Longitudinal Healthy Longevity Survey conducted between 2002 and 2018. It included a total of 11,044 Chinese people aged 65 years or older. A group-based trajectory model was used to identify distinctive trajectories of the IADL score, and the Cox proportional hazards model was used to explore the hazard ratio of various trajectories at the onset of MCI. Interaction analysis was used to analyze individual modification between the IADL trajectories and the onset of MCI. Finally, we adopted four types of sensitivity analysis to verify the robustness of the results.
During a median follow-up of 16 years, the incidence of MCI was 6.29 cases per 1,000 person-years (95% confidence interval [CI] 5.92-6.68). Three distinct IADL trajectory groups were identified: a low-risk IADL group (41.4%), an IADL group with increasing risk (28.5%), and a high-risk IADL group (30.4%). Using the Cox proportional hazards model after adjusting for covariates, we found that compared with the low risk IADL group, the hazard ratio of the IADL group with increasing risk was 4.49 (95% CI = 3.82-5.28), whereas that of the high-risk IADL group was 2.52 (95% CI 2.08-3.05). Treating the IADL group with increasing risk as the reference, the hazard ratio for the high-risk IADL group was 0.56 (95% CI 0.48-0.66). Interaction analyses showed that age and residence were significant moderators (P for interaction <0.05).
A group-based trajectory model was developed to classify older people into three distinct trajectory groups of the IADL score. The IADL group with increasing risk had a greater risk of MCI than the high-risk IADL group. In the IADL group with increasing risk, city residents of ≥80 years were the most likely to develop MCI.

The group-based trajectory modeling (GBTM) method is increasingly used in pharmacoepidemiologic studies to describe medication adherence trajectories over time. However, assessing the associations between these medication adherence trajectories and health-related outcomes remains challenging. The purpose of this review is to identify and systematically review the methods used to assess the association between medication adherence trajectories, estimated from the GBTM method, and health-related outcomes.
We will conduct a systematic review according to the recommendations of the Cochrane handbook for systematic reviews of interventions 6.2. Results will be reported following PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-analyses) recommendations. We will search in the following databases: PubMed, Embase, PsycINFO, Web of Science, CINAHL, and Cochrane Library. Two reviewers will independently select articles and extract data. Discrepancies at every step will be resolved through discussion, and consensus will be reached for all disagreed articles. A third reviewer will act as a referee if needed. We will produce tables to synthesize the modalities used to estimate medication adherence trajectories with GBTM. We will also synthesize the modalities used to assess the association between these medication adherence trajectories and health-related outcomes by identifying the types of health-related outcomes studied and how they are defined, the statistical models used, and how the medication adherence trajectories were used in these models, and the effect measure yield. We will also review the limitations and biases reported by the authors and their attempts to mitigate them. We will provide a narrative synthesis.
This review will provide a thorough exploration of the strategies and methods used in medication adherence research to estimate the associations between medication adherence trajectories, estimated with GBTM, and the different health-related outcomes. It will represent the first crucial steps toward optimizing these methods in adherence studies.
Prospero CRD42021213503 .

Post-traumatic stress disorder and depression have high comorbidity. Understanding their relationship is of clinical and theoretical importance. A comprehensive way to understand post-trauma psychopathology is through symptom trajectories. This study aims to look at the developmental courses of PTSD and depression symptoms and their interrelationship in the initial months post-trauma in children and adolescents.
Two-hundred-and-seventeen children and adolescents aged between eight and 17 exposed to single-event trauma were included in the study. Post-traumatic stress symptoms (PTSS) and depression symptoms were measured at 2 weeks, 2 months and 9 months, with further psychological variables measured at the 2-week assessment. Group-based trajectory modelling (GBTM) was applied to estimate the latent developmental clusters of the two outcomes. Logistic regression was used to identify predictors associated with high symptom groups.
The GBTM yielded a three-group model for PTSS and a three-group model for depression. PTSS trajectories showed symptoms reduced to a non-clinical level by 9 months for all participants (if they were not already in the non-clinical range): participants were observed to be resilient (42.4%) or recovered within 2 months (35.6%), while 21.9% experienced high level PTSS but recovered by 9 months post-trauma. The depression symptom trajectories predicted a chronic non-recovery group (20.1%) and two mild symptom groups (45.9%, 34.0%). Further analysis showed high synchronicity between PTSS and depression groups. Peri-event panic, negative appraisals, rumination and thought suppression at 2 weeks predicted slow recovery from PTSS. Pre-trauma wellbeing, post-trauma anxiety and negative appraisals predicted chronic depression.
Post-trauma depression was more persistent than PTSS at 9 months in the sampled population. Cognitive appraisal was the shared risk factor to high symptom groups of both PTSS and depression.
Objetivo: El trastorno de estrés postraumático y la depresión tienen una alta comorbilidad. Comprender su relación es de importancia clínica y teórica. Una forma integral de comprender la psicopatología postraumática es a través de las trayectorias de los síntomas. Este estudio tiene como objetivo observar los cursos de desarrollo del TEPT y los síntomas de depresión y su interrelación en los primeros meses posteriores al trauma en niños/ñas y adolescentes.Métodos: Se incluyeron en el estudio 217 niños/ñas y adolescentes de ocho a diecisiete años expuestos a un evento traumático único. Los síntomas de estrés postraumático (SEPT) y los síntomas de depresión se midieron a las 2 semanas, 2 meses y 9 meses, con otras variables psicológicas medidas en la evaluación de 2 semanas. Se aplicó un modelo de trayectoria basado en grupos (MTBG) para estimar los grupos de desarrollo latentes de los dos resultados. Se utilizó la regresión logística para identificar predictores asociados con grupos de síntomas elevados.Resultados: El MTBG arrojó un modelo de tres grupos para SEPT y un modelo de tres grupos para depresión. Las trayectorias de SEPT mostraron síntomas reducidos a un nivel no clínico en 9 meses para todos los participantes (si ellos aún no estaban en el rango no clínico): se observó que los participantes eran resilientes (42,4%) o se recuperaron en 2 meses (35,6%), mientras que el 21,9% experimentó un SEPT de alto nivel pero se recuperó a los 9 meses después del trauma. Las trayectorias de los síntomas de depresión predijeron un grupo crónico de no-recuperación (20,1%) y dos grupos de síntomas leves (45,9%, 34,0%). Un análisis posterior mostró una alta sincronicidad entre los grupos de SEPT y depresión. El pánico peri-evento, las evaluaciones negativas, la rumiación y la supresión del pensamiento a las 2 semanas predijeron una recuperación lenta del SEPT. El bienestar pre-traumático, la ansiedad post-traumática y las valoraciones negativas predijeron la depresión crónica.Conclusiones: La depresión post-traumática fue más persistente que el SEPT a los 9 meses en la población muestreada. La evaluación cognitiva fue el factor de riesgo compartido para los grupos de síntomas altos tanto de SEPT como de depresión.
目的: 创伤后应激障碍和抑郁的共病率较高。了解它们的关系具有临床和理论意义。了解创伤后精神病理学的一种综合方法是通过症状轨迹。本研究旨在研究儿童和青少年创伤后最初几个月内 PTSD 和抑郁症状的发展过程及其相互关系。方法: 本研究纳入了 217 名遭受单次创伤的8 至 17 岁儿童和青少年。在 2 周, 2 个月和 9 个月时测量了创伤后应激症状 (PTSS) 和抑郁症状, 并在 2 周评估时测量了进一步的心理变量。应用基于组别的轨迹模型 (GBTM) 来估计两种结果的潜在发展簇。使用逻辑回归来识别与高症状组相关的预测因子。结果: GBTM 产生了 PTSS 三组模型和抑郁三组模型。 PTSS 轨迹显示所有参与者的症状在 9 个月内减少到非临床水平 (如果他们并非已在非临床范围内):观察到参与者有韧性 (42.4%) 或在 2 个月内恢复 (35.6%), 而 21.9% 的人经历了高水平 PTSS, 但在创伤后 9 个月内恢复。抑郁症状轨迹预测慢性非恢复组 (20.1%) 和两个轻度症状组 (45.9%, 34.0%) 。进一步分析显示 PTSS 和抑郁组之间的高度同步性。 2 周时的事件相关恐慌, 负性评价, 反刍和思想抑制预测了 PTSS 恢复缓慢。创伤前的幸福感, 创伤后的焦虑和负性评价预测了慢性抑郁。结论: 在样本人群中, 创伤后抑郁在 9 个月时比 PTSS 更持久。认知评估是 PTSS 和抑郁高症状组的共同风险因素。.

OBJECTIVE: The aim of this study is to estimate differences in health-promoting behaviour levels throughout the pregnancy trimesters, to identify distinct patterns of health-promoting behaviour trajectories during pregnancy and to evaluate predictors of these trajectory group memberships.
BACKGROUND: Promoting healthy lifestyle behaviours during pregnancy could decrease devastating outcomes for the mother and foetus. However, there is currently limited insight into the dynamics of health-promoting behaviours during pregnancy.
METHODS: An observational longitudinal study.
METHODS: 158 pregnant women were recruited from June 2020 to June 2021 in Qingdao, China. The Health-Promoting Lifestyle Profile was used to assess health-promoting behaviours. Latent growth model was performed to compare health-promoting behaviours at different time points. Group-based trajectory model was applied to identify health-promoting behaviour trajectories. Multinomial logistic regression was adopted to determine the predictors of trajectory group memberships. We used the STROBE checklist to report this study.
RESULTS: The entire sample of pregnant women experienced a significant increase in health-promoting behaviours during pregnancy. Three trajectories were identified including a \'low-increase behaviour trajectory (20.1% of sample)\', a \'moderate-increase behaviour trajectory (58.0% of sample)\' and a \'stable then increased behaviour trajectory (21.9% of sample)\'. Low maternal sense of coherence, lack of pre-pregnancy exercise habit, artificial insemination and low monthly family income were significantly associated with the low-increase behaviour trajectory. High self-efficacy and pre-pregnancy exercise habit were significantly associated with the stable then increased behaviour trajectory.
CONCLUSIONS: Pregnant women exhibit different health-promoting behaviours throughout the pregnancy trimesters. Meanwhile, three trajectories were identified among pregnant women. Thus, more attentions should be paid on early identification and targeted intervention in a future study.
UNASSIGNED: Healthcare providers should pay closer and earlier attention to identify women in the low-increase trajectory subgroup at the outset of pregnancy. Similarly, increased efforts should be made to improve maternal self-efficacy and develop good pre-pregnancy exercise habit in future study.