Low-stable Class Research Articles

Continuity and change in early material hardship domains on the development of children’s behavioral self-regulation in middle childhood

Child poverty adversely impacts children’s behavioral self-regulation; however, the extent to which this association varies across different forms of material hardship (i.e., food, housing, bill-paying, utility, and medical) from infancy to early childhood is not well understood. The current study aims to identify the longitudinal patterns of early material hardship in five domains, examine demographic factors to distinguish class membership, and assess how hardship class membership predicts children’s behavioral self-regulation in middle childhood. We used data from the Future of Families and Child Wellbeing Study (N = 4,677) across ages 1 to 9. The Multidimensional Growth Mixture Model identified four trajectory classes: Low Stable (n = 2,215, 47.4%), Increasing Bill and Utility Hardship (n = 1,180, 25.2%), High Infancy Bill Hardship (n = 799, 17.1%), and Persistent and Pervasive (n = 483, 10.3%). White, married mothers, mothers who were employed, families with income above 200% of the federal poverty threshold, and those who did not receive SNAP had higher odds of being in the Low Stable class than the three other classes. Children in the Persistent and Pervasive class exhibited the lowest levels of behavioral self-regulation in middle childhood compared to the other three classes. Children in the Increasing Bill and Utility Hardship and High Infancy Bill Hardship classes had lower behavioral self-regulation than those in the Low Stable class. These findings underscore the need for tailored interventions to alleviate the prolonged effects of financial adversity and exposure to early material deprivation experienced by children. Findings also highlight the importance of implementing intervention programs designed specifically to support the development of behavioral self-regulation among economically disadvantaged children.

Body mass index trajectories and time in target range after delivery and long-term type 2 diabetes risk in women with a history of gestational diabetes mellitus.

This study aims to determine whether postpartum body mass index (BMI) trajectories and its time in target range (TTR) are associated with long-term type 2 diabetes risk in women with a history of gestational diabetes mellitus (GDM). The present study included 1057 women with a history of GDM who participated in the Tianjin Gestational Diabetes Mellitus Prevention Program (TGDMPP). Oral glucose tolerance tests or physician-diagnosed information were used to diagnose type 2 diabetes after a median follow-up period of 8.47 years. Latent class modelling was applied to identify trajectories of BMI after delivery. TTR was defined as the proportion of time that BMI was within the standard range (18.5 ≤ BMI < 24.0 kg/m2). The associations of BMI trajectories and TTR with type 2 diabetes risk were analysed using multivariable Cox modelling. Five distinct trajectories of postpartum BMI were identified. Compared with low-stable class, the multivariable-adjusted hazard ratios of type 2 diabetes were 2.02 (95% confidence interval 0.99-4.10) for median-stable class, 3.01 (1.17-7.73) for high-stable class, 2.15 (0.63-7.38) for U-shape class and 7.15 (2.08-24.5) for inverse U-shape class (p for trend = 0.012), respectively. Multivariable-adjusted hazard ratios of type 2 diabetes associated with postpartum BMI TTR of 100%, >43.4%-<100%, >0%-≤43.4% and 0% were 1.00, 1.84 (0.72-4.73), 2.75 (1.23-6.15) and 2.31 (1.05-5.08) (p for trend = 0.039), respectively. Postpartum BMI trajectories of high-stable and inverse U-shape class as well as lower TTR were associated with an increased risk of type 2 diabetes among women with a history of GDM. Reducing BMI to a normal range in the early postpartum period and maintaining stable over time could attenuate the development of long-term type 2 diabetes.

Predicting the trajectory of non-suicidal self-injury among adolescents.

Non-suicidal self-injury (NSSI) is common among adolescents receiving inpatient psychiatric treatment and the months post-discharge is a high-risk period for self-injurious behavior. Thus, identifying predictors that shape the course of post-discharge NSSI may provide insights into ways to improve clinical outcomes. Accordingly, we used machine learning to identify the strongest predictors of NSSI trajectories drawn from a comprehensive clinical assessment. The study included adolescents (N = 612; females n = 435; 71.1%) aged 13-19-years-old (M = 15.6, SD = 1.4) undergoing inpatient treatment. Youth were administered clinical interviews and symptom questionnaires at intake (baseline) and before termination. NSSI frequency was assessed at 1-, 3-, and 6-month follow-ups. Latent class growth analyses were used to group adolescents based on their pattern of NSSI across follow-ups. Three classes were identified: Low Stable (n = 83), Moderate Fluctuating (n = 260), and High Persistent (n = 269). Important predictors of the High Persistent class in our regularized regression models (LASSO) included baseline psychiatric symptoms and comorbidity, past-week suicidal ideation (SI) severity, lifetime average and worst-point SI intensity, and NSSI in the past 30 days (bs = 0.75-2.33). Only worst-point lifetime suicide ideation intensity was identified as a predictor of the Low Stable class (b = -8.82); no predictors of the Moderate Fluctuating class emerged. This study found a set of intake clinical variables that indicate which adolescents may experience persistent NSSI post-discharge. Accordingly, this may help identify youth that may benefit from additional monitoring and support post-hospitalization.

Dynamic changes of serum α-fetoprotein predict the prognosis of bevacizumab plus immunotherapy in hepatocellular carcinoma.

Alpha-fetoprotein (AFP) has been established as a biomarker for hepatocellular carcinoma (HCC); however, whether its dynamic changes could predict the response to systemic therapy remains elusive. This study explored the AFP trajectory and the association with survival in patients received bevacizumab plus immunotherapy. We retrospectively enrolled 536 HCC patients received bevacizumab plus immunotherapy between February 2021 and February 2023. Patients were divided into two groups according to AFP values before treatment (400ng/ml). Dynamic changes of AFP were fitted using a latent class model to generate the AFP trajectories. Multivariable Cox models were utilized to compute hazard ratios (HRs) for survival. Inverse-probability-of-treatment weighted analyses were conducted to mitigate the influence of unmeasured confounding variables. The primary endpoint is progression free survival (PFS). The second endpoint is overall survival (OS). Three distinct trajectories were identified for AFP-low and AFP-high patients, respectively. In AFP-low group, compared with the high-rising class (25%; n=69), HRs of PFS were 0.39 and 0.2 for the low-stable class (59.1%; n=163) and sharp-falling class (15.9%; n=44), after adjusting by tumor diameter, tumor number, and extra-hepatic metastasis. In AFP-high group, compared with the high-stable class (18.5%; n=48), HRs of PFS were 0.3 and 0.04 for the middle-stable class (56.5%; n=147) and sharp-falling class (25%; n=65), after adjusting by tumor diameter, tumor number, and extra-hepatic metastasis. Furthermore, the AFP trajectories exhibited the utmost relative importance among all covariates regarding PFS and OS in the multivariable regression models. The AFP trajectories in HCC patients receiving bevacizumab and immunotherapy, constituted an independent biomarker indicative of clinical outcomes. Findings from this study hold potential clinical utility in dynamically forecasting the prognosis of systemic therapy in HCC patients and facilitating clinical decision-making. Rapid reduction of AFP post-treatment can lead to favorable patient prognoses.

Resourcefulness Among Initial Ischemic Stroke Patients: A Longitudinal Study of 12 Months.

To explore distinct longitudinal trajectories of resourcefulness among initial ischemic stroke patients from diagnosis to 12 months, and to identify whether sociodemographic factors, disease-related factors, self-efficacy, family function, and social support can predict patterns in the trajectories of resourcefulness. A prospective longitudinal study was conducted. Initial ischemic stroke patients who met inclusion and exclusion criteria were followed up when still in hospital (Preparing for discharge, Baseline, T1), at 1 month (T2), at 3 months (T3), at 6 months (T4), at 9 months (T5) and 12 months (T6) (±1 week) after discharge. General information, National Institute of Health Stroke Scale (NIHSS), Modified Rankin Scale (mRS), General Self-Efficacy Scale (GSES), General Family Functioning Subscale (FAD-GF), and Social Support Rate Scale (SSRS) were used in T1. The Resourcefulness Scale© was evaluated at 6 time points. Growth mixture modeling was used to identify trajectory patterns of resourcefulness. Logistic regression was used to identify predictors of resourcefulness trajectories. Three longitudinal trajectories of resourcefulness were identified and named as the high-stable class (38.9%, n=71), fluctuation class (41.2%, n=75), and low-stable class (19.9%, n=36), respectively. Dwelling areas (x2=6.805, P=0.009), education (x2=44.865, P=0.000), monthly income (x2=13.063, P=0.001), NIHSS scores (x2=44.730, P=0.000), mRS scores (x2=51.788, P=0.000), Hcy (x2=9.345, P=0.002), GSES (x2=56.933, P=0.000), FAD-GF (x2=41.305, P=0.000) and SSRS (x2=52.373, P=0.000) were found to be statistically significant for distinguishing between different resourcefulness trajectory patterns. Lower education (OR=0.404), higher NIHSS(OR=6.672) scores, and higher mRS(OR=21.418) scores were found to be risk factors for lower resourcefulness, whereas higher education(OR=0.404), GSES(OR=0.276), FAD-GF(OR=0.344), and SSRS(OR=0.358) scores were identified as protective factors enhancing resourcefulness. This study obtained three patterns of trajectories and identified their predictive factors in initial ischemic stroke. The findings will assist health care professionals in identifying subgroups of patients and when they may be at risk of low resourcefulness and provide timely targeted intervention to promote resourcefulness.

Is the change in longitudinal cognitive function in older adults with diabetes affected by trajectory classes of depressive symptoms?

This study aims to identify classes based on the trajectory of depressive symptoms and to examine the impact of trajectory classes of depressive symptoms on longitudinal changes in cognitive function in older adults with diabetes. This is a secondary data analysis of 572 older adults with diabetes using data from the 5th (2014) to 8th (2020) wave of the Korean longitudinal study of aging. Analysis of latent class growth and the effect of trajectories of depressive symptoms on cognitive function was examined using a latent growth curve model. This analysis has been found to be functional in change trajectories and in describing the direction of the trajectory. The trajectory of depressive symptoms was classified into four classes: low-stable (36.89%), high-decreasing (20.28%), low-increasing (18.71%), and high-persistent (24.13%). Compared with the high-persistent class, higher initial levels of cognitive function were observed in the high-decreasing and low-stable classes. Compared with the high-persistent class, a slower rate of cognitive decline was observed in the low-stable class (B=0.410, p=.021). Continuous monitoring of depressive symptoms and early management of depressive symptoms for community-dwelling older adults with diabetes can help prevent the cognitive decline and delay the deterioration of cognitive function.

Trajectories of Treatment Burden Among Primary Care Patients with Long-Term Conditions in Southern China: A Latent Class Growth Analysis.

Treatment burden is a patient-centred, dynamic concept. However, longitudinal data on the changing pattern of treatment burden among patients with one or more long-term conditions (LTCs) are relatively scanty. We aimed to explore the longitudinal trajectories of treatment burden and associated risk factors in a large, patient population in primary care settings. We analysed data from 5573 primary care patients with long-term conditions (LTCs) recruited using a multistage sampling method in Shenzhen, southern China. The treatment burden was assessed by the Mandarin Chinese version of the Treatment Burden Questionnaire (TBQ). We used latent class growth mixture modelling (LCGMM) to determine trajectories of treatment burden across four time points, ie, at baseline, and at 6, 12, and 18 months. Predictors of trajectory classes were explored using multivariable logistic regression analysis. The mean TBQ scores of patients with a single LTC (n = 2756), 2 LTCs (n = 1871), 3 LTCs (n = 699), and ≥4 LTCs (n = 247) were 18.17, 20.28, 21.32, and 26.10, respectively, at baseline. LCGMM identified three discrete classes of treatment burden trajectories over time, ie, a high-increasing class, a low-stable class, and a high-decreasing class. When controlling for individual-level factors including age, education, monthly household income per head, smoking, alcohol consumption, and attendance in health education, patients who had a clinical diagnosis of 3 LTCs (adjusted odds ratio [aOR] = 1.49, 95% CI = 1.21-1.86, P < 0.001) or ≥4 LTCs (aOR = 1.97, 95% CI = 1.44-2.72, P < 0.001) were more likely to belong to the high-increasing class. Sensitivity analysis using propensity score methods obtained similar results. Our study revealed the presence of discrete patterns of treatment burden over time in Chinese primary care patients with LTCs, providing directions for tailored interventions to optimise disease management. Patients with 3 or more LTCs should receive close attention in healthcare delivery as they tend to experience a greater treatment burden.

Trajectories of α-fetoprotein and unresectable hepatocellular carcinoma outcomes receiving atezolizumab plus bevacizumab: a secondary analysis of IMbrave150 study.

α-fetoprotein (AFP) response has been demonstrated as a biomarker for unresectable hepatocellular carcinoma (uHCC) patients receiving immunotherapy, but its definition is still unclear. This exploratory study investigated the AFP trajectory and clinical outcomes of receiving atezolizumab plus bevacizumab (Atez/Bev) therapy. This secondary analysis used the Atez/Bev arm data of phase III IMbrave150 study to distinguish potential AFP changing rate trajectories through latent class trajectory models. The multivariable Cox models were applied to calculate adjusted hazard ratios (HRs) and 95% CIs for clinical outcomes. Three distinct trajectories were identified among the uHCC patients with 7 times (range, 3 to 28) of AFP measurements: low-stable (50.0%, n = 132), sharp-falling (13.3%, n = 35), and high-rising (36.7%, n = 97). Compared with the high-rising class, HRs of disease progression were 0.52 (95% CI: 0.39, 0.70) and 0.26 (95% CI: 0.16, 0.43) for the low-stable class and sharp-falling class, respectively. In contrast, HRs of death were 0.59 (95% CI: 0.40, 0.81) and 0.30 (95% CI: 0.16, 0.57) for the two groups after propensity score adjustment. Besides, AFP trajectories had the highest relative importance of each covariate to survival. There are three distinct AFP trajectories in uHCC patients receiving Atez/Bev, and it is an independent biomarker for clinical outcomes.

Breastfeeding continuation is associated with trait mindfulness but not with trajectories of postpartum depressive symptoms

ObjectiveThe WHO recommends breastfeeding for at least six months as breastfeeding has many benefits for both infant and mother. The association of breastfeeding continuation with trait mindfulness during pregnancy and trajectories of postpartum depressive symptoms has not been examined yet. The current study aimed to assess this association using cox regression analysis. Design, setting and participantsThe current research is part of a large longitudinal prospective cohort study following women from 12 weeks of pregnancy onwards in the South-East part of the Netherlands. MeasurementsA total of 698 participants filled out the Three Facet Mindfulness Questionnaire-Short Form (TFMQ-SF) at 22 weeks of pregnancy and completed both the Edinburgh Postnatal Depression Scale (EPDS) and questions on breastfeeding continuation one week, six weeks, four months, and eight months postpartum. Breastfeeding continuation was defined as exclusive breastfeeding or both breastfeeding and formula. The assessment eight months postpartum was used as a proxy for the WHO recommendation to continue breastfeeding for at least six months. FindingsTwo trajectories (classes) of EPDS scores were determined using growth mixture modeling: 1) low stable (N = 631, 90.4%), and 2) increasing (N = 67, 9.6%). Cox regression analysis showed that the trait mindfulness facet non-reacting was significantly and inversely associated with the risk of breastfeeding discontinuation (HR = 0.96, 95% CI [0.94, 0.99], p = .002), while no significant association was found for belonging to the increasing EPDS class versus belonging to the low stable class (p = .735), adjusted for confounders. Key conclusionsThis study is the first to show that higher trait mindfulness non-reacting scores, but not persistently low levels of postpartum depressive symptoms, increase the likelihood of breastfeeding continuation. Implications for practiceImproving non-reacting in perinatal women by meditation practice as part of a mindfulness-based intervention may lead to better breastfeeding continuation outcomes. Several mindfulness-based programs may be suitable.

Social media use as a risk factor for depressive symptoms during pregnancy

BackgroundAccumulating research has shown associations between excessive social media use (SMU) with depressive symptoms. Depression is common during pregnancy, but it is not known whether SMU plays a role in the etiology and clinical course of depressive symptoms during pregnancy. MethodsThe current study is a prospective cohort study with Dutch-speaking pregnant women recruited at the first antenatal appointment (N = 697). Depressive symptoms were measured at each trimester of pregnancy using the Edinburgh Depression Scale. Growth mixture modeling was used to determine classes of women based on longitudinal trajectories of depressive symptoms. SMU was assessed at 12 weeks of pregnancy, specifically, intensity (time and frequency) and problematic SMU (Bergen Social Media Addiction Scale). Multinomial logistic regression analyses were used to examine the associations between SMU and trajectories of depressive symptoms. ResultsThree trajectories of depressive symptoms during pregnancy were identified: a low stable (N = 489, 70.2 %), intermediate stable (N = 183, 26.3 %), and high stable (N = 25, 3.6 %) class. SMU Time and Frequency were significantly associated with belonging to the high stable class. Problematic SMU was significantly associated with belonging to the intermediate or high stable class. LimitationsThe study does not allow to draw conclusions about causality. The group sizes of the three trajectories differed considerably. Data were collected during the COVID-19 pandemic which may have influenced the results. SMU was measured by self-report. ConclusionsThese results indicate that both higher intensity of SMU (time and frequency) and problematic SMU may be a risk factor for higher levels of prenatal depressive symptoms during pregnancy.

Co-development of attention deficit hyperactivity disorder and autistic trait trajectories from childhood to early adulthood.

Attention deficit hyperactivity disorder (ADHD) and autism, defined as traits or disorders, commonly co-occur. Developmental trajectories of ADHD and autistic traits both show heterogeneity in onset and course, but little is known about how symptom trajectories co-develop into adulthood. Using data from a population cohort, the Avon Longitudinal Study of Parents and Children, we examined correlations between ADHD and autistic traits across development, using the Social Communication Disorders Checklist and ADHD subscale of the Strengths and Difficulties Questionnaire. We modelled joint developmental trajectories of parent-reported ADHD and autistic traits between 4 and 25 years, then characterised trajectory classes based on sociodemographic, perinatal, psychopathology, cognition and social functioning variables and tested for associations with neurodevelopmental/psychiatric polygenic scores (PGS). Three classes of trajectories were identified; a typically developing majority with low-stable ADHD-autistic traits (87%), a male-predominant subgroup with child/adolescent-declining traits (6%) and a subgroup with late-emerging traits (6%). ADHD-autistic trait correlations were greatest in young adulthood for the two nontypically developing classes. There were higher rates of emotional and conduct problems, low IQ, childhood seizures and poor social functioning in the declining and late-emerging classes compared to the low-stable class. Emotional, conduct and peer problems were more prevalent during childhood in the childhood/adolescent-declining class compared to other classes, but were more prevalent in young adulthood in the late-emerging class. Neurodevelopmental/psychiatric PGS also differed: both nontypically developing classes showed elevated ADHD PGS compared to the low-stable group, and the late-emerging group additionally showed elevated schizophrenia PGS and decreased executive function PGS, whereas the declining group showed elevated broad depression PGS. Distinct patterns of ADHD-autism co-development are present across development in the general population, each with different characterising factors and genetic signatures as indexed by PGS.

Trait mindfulness facets as a protective factor for the development of postpartum depressive symptoms

BackgroundPostpartum depression has a prevalence rate of up to 17%. As there are many negative consequences of postpartum depressive symptoms, it is important to examine possible protective factors, such as trait mindfulness. Since postpartum depressive symptoms are variable over time between and within individuals, this study focused on the possible association between facets of trait mindfulness and trajectories of postpartum depressive symptoms throughout the first postpartum year. MethodsA subsample of 713 women that participated in the HAPPY study completed the Three Facet Mindfulness Questionnaire-Short Form at 22 weeks of pregnancy and the Edinburgh Postnatal Depression Scale (EPDS) at six weeks, four months, eight months, and twelve months postpartum. Possible different EPDS trajectories were obtained by means of growth mixture modeling. ResultsTwo EPDS trajectories (classes) were found: a low stable symptom class (N = 647, 90.7%) and an increasing-decreasing symptom class (N = 66, 9.3%). Women in the low stable class showed higher ‘acting with awareness’ and ‘non-judging’ scores. A higher score on the ‘non-judging’ facet of trait mindfulness was associated with a higher likelihood of belonging to the low stable class (OR = 0.79, 95% CI [0.72, 0.87], p < 0.001), adjusted for confounders and the other mindfulness facets. ConclusionsThe non-judging facet of trait mindfulness was associated with low stable levels of depressive symptoms during the first postpartum year. Mindfulness-based programs, focusing on enhancing non-judging may be of benefit for pregnant women to possibly decrease the risk of developing postpartum depressive symptoms after childbirth.

Developmental trajectories of internalizing distress among ethnic minoritized mothers following childbirth: Associations with early child psychological adjustment.

A substantial body of work has established that mothers' internalizing distress can negatively affect children's socioemotional development. Yet few studies have examined how distinct patterns of mothers' distress over time differentially impact child behaviors across early childhood. To address this gap, the current study explored developmental trajectories of mothers' internalizing distress and examined the associations of these patterns with child adjustment outcomes. Mexican immigrant, Dominican immigrant, and African American mothers (N = 272) were annually assessed for internalizing distress over the first 6 years following childbirth. Children's psychological adjustment (internalizing, externalizing, and hyperactivity behaviors) was measured at the last yearly assessment in first grade. A growth mixture model revealed two distinct classes of distress where mothers were classified as having low stable distress (82.4%) or moderate distress that began as stable then declined when their children were 64 months old (17.6%). Children of mothers in the moderate, late decline class showed greater internalizing, externalizing, and hyperactivity behaviors in the first grade compared to children of mothers in the low stable class. Findings highlight the necessity of supporting the mental health of ethnic minoritized mothers following childbirth and further expand our knowledge of family psychopathology to promote healthy psychological adjustment in children.

Couple Classes of Depressive Symptom Trajectories and Associations with Relationship Satisfaction

The literature indicates a robust negative relationship between depression and couple relationship satisfaction. However, less is known about the differential effects of romantic relationships on depression over time and whether one or both partners experience depression. Using data from 1215 couples across 4 years, we sought to examine couple classes of depressive symptom trajectories and investigate the degree to which relationship satisfaction predicted class membership. Using joint-probability growth mixture modeling, we found three couple classes of depressive symptom trajectories: women’s moderate, men’s low class, men’s moderate, women’s low class, and men’s and women’s low class. Logistic regression results revealed both men’s and women’s higher relationship satisfaction was associated with women’s moderate, men’s low class membership while both partners’ higher relationship satisfaction was not associated with men’s moderate, women’s low class membership, in comparison to the men’s and women’s low stable class. These findings contribute to the literature by identifying the heterogeneity of patterns of depressive symptom trajectories among couples and the association of relationship satisfaction with couple classes.

Chinese children’s heterogeneous friendship quality trajectories: Relations with school adjustment.

Friendships affect children's development and adjustment. This longitudinal study examined the possible heterogeneity and gender differences in the trajectories of children's friendship quality, as well as the relations between distinct friendship quality trajectories and school adjustment. A total of 3,779 Chinese elementary school students (45.5% girls, Mage = 9.94 years, SD = 0.72 at Time 1) completed measures of relevant constructs on five occasions at 6-month intervals. Latent class growth modeling revealed four heterogeneous developmental trajectory classes of friendship quality: high-increasing (49.6%), moderate-decreasing (5.1%), moderate-increasing (31.9%), and low-stable (13.4%). Girls were more likely than boys to fall into the higher friendship quality trajectory classes in reference to the low-stable class. Children in the high-increasing class and low-stable class showed the best and the worst school adjustment, respectively. The identification of four heterogeneous developmental trajectories of friendship quality with differential school adjustment outcomes highlights the importance of intervention programs tailored to specific groups for promoting children's friendship quality and school adjustment. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Resilience resources may buffer some middle-aged and older Black Americans from memory decline despite experiencing discrimination

RationaleExperiences of discrimination have been associated with poorer episodic memory in Black Americans. However, resilience resources at multiple levels (individual, social, and endowed) may act as a buffer to protect future memory decline, especially in the face of discrimination. ObjectiveUsing longitudinal data from the 2006–2016 Health and Retirement Study (N = 1862), we tested whether Black Americans aged 50 and older would show different trajectories of episodic memory depending on their reported experiences of discrimination (everyday and major lifetime) and resilience resources. MethodsAnalyses were conducted in three steps: (1) joint latent cluster mixed modeling (JLCMM) to estimate the number of classes, (2) barycentric discriminant analyses (BADA) to model the combined influence of discrimination and resilience resources between each memory class, and (3) multinomial regression analyses to explore interactions between discrimination and resilience resources. ResultsJLCMM resulted in three memory classes that differentiated baseline from longitudinal memory performance: “High Decliners,” “Low Decliners,” and “Low Stable.” Two independent patterns described the relationships between the three classes in the context of discrimination and resilience resources. First, compared with High Decliners, the two lower baseline memory classes (Low Decliners and Low Stable) reported more everyday discrimination and lower individual and endowed resilience resources. Second, although the Low Stable class did not report different levels of discrimination, they had more social resilience resources (greater social support and more social contact) than both declining classes. ConclusionsBlack Americans in later life have heterogeneous patterns of memory trajectories as demonstrated by the three memory classes identified. Those with lower baseline memory experienced more everyday discrimination and had fewer resilience resources compared to those with high baseline performance (High Decliners). Greater social resilience resources were associated with maintained episodic memory over time in Black Americans.

Trait mindfulness scores are related to trajectories of depressive symptoms during pregnancy

BackgroundExploring possible protective factors against antenatal depression is important since antenatal depression is common and affects both mother and child. The person characteristic trait mindfulness may be such a protective factor. Because of the high variability in depressive symptoms over time, we aimed to assess the association between trait mindfulness and trajectories of depressive symptoms during pregnancy. MethodsA subsample of 762 women participating in the HAPPY study completed the Three Facet Mindfulness Questionnaire-Short Form at 22 weeks of pregnancy. Possible different trajectories of Edinburgh Postnatal Depression Scale (EPDS) scores, assessed at each pregnancy trimester, were explored with growth mixture modeling. ResultsThree EPDS trajectories (classes) were identified: low stable symptom scores (N = 607, 79.7%), decreasing symptom scores (N = 74, 9.7%) and increasing symptom scores (N = 81, 10.6%). Compared to belonging to the low stable class (reference), women with higher scores on the trait mindfulness facets ‘acting with awareness’ and ‘non-judging’ were less likely to belong to the decreasing class (OR = 0.81, 95% CI [0.73, 0.90] and OR = 0.77, 95% CI [0.70, 0.84]) and increasing class (OR = 0.88, 95% CI [0.80, 0.97] and OR = 0.72, 95% CI [0.65, 0.79]). Women with higher scores on ‘non-reacting’ were less likely to belong to the increasing class (OR = 0.89, 95% CI [0.82, 0.97]), but not the decreasing class (OR = 0.96, 95% CI [0.87, 1.04]). All analyses were adjusted for confounders. ConclusionsCharacteristics of trait mindfulness predicted low stable levels of depressive symptoms throughout pregnancy. Mindfulness-based programs may be beneficial for pregnant women as a strategy to alleviate depression risks.

Trajectories of serum α-fetoprotein and intermediate-stage hepatocellular carcinoma outcomes after transarterial chemoembolization: A longitudinal, retrospective, multicentre, cohort study

SummaryBackgroundα-fetoprotein (AFP) response has been proven a key tumor marker for hepatocellular carcinoma (HCC), but its definition remains controversial. This study aims to characterize AFP trajectories after transarterial chemoembolization (TACE) and examine its impact on clinical outcomes.MethodsThis longitudinal, multicenter, retrospective, cohort study examined data from the electronic medical record system of four hospitals in China between January 1, 2007 to December 31, 2016. A latent class growth mixed model was applied to distinguish potential AFP dynamic changing trajectories. The multivariable Cox models were used to calculate adjusted hazard ratios (aHRs) and 95% CIs for overall survival. Inverse-probability-of-treatment weighted analyses were performed to eliminate unmeasured confounders through marginal structural models.FindingsA total of 881 patients, who had intermediate-stage HCC with AFP repeatedly measured 3 to 10 times, were included in the study. Three distinct trajectories were identified using the latent class growth mixture model: high-rising (25.7%; n = 226), low-stable (58.7%; n = 517), and sharp-falling (AFP serological response, 15.6%; n = 138). Compared with the low-stable class, the aHRs for death were 5.13 (3.71, 7.10) and 0.52 (0.33, 0.81) for the high-rising and sharp-falling class, adjusted by gender, baseline major tumor size, intrahepatic lesions number, and logAFP(smooth). Furthermore, high-rising class had a significantly higher HR in the subgroup of female patients (10.60, 95%CI: 6.29, 17.86), age<55 (6.78, 95%CI: 4.79, 9.59) and Child-Pugh class B (23.01, 95%CI:8.07, 65.63) (P = 0.014, 0.046 and 0.033 for interaction, respectively). Trajectories of AFP had the highest relative importance of each parameter to survival, including largest tumor size, intrahepatic lesions number, Child-Pugh class, and baseline AFP.InterpretationAFP trajectories were associated with overall survival for intermediate-stage HCC after TACE.FundingThe Natural Science Foundation of Fujian Province (Nos. 2018J01352, 2016J01576 and 2016J01586); the Science and Technology Innovation Joint Foundation of Fujian Province (Nos. 2017Y9125).

Developmental Trajectory of Depressive Symptoms in Chinese College Students: Latent Classes and Gender Effect

Depressive symptoms are prevalent in Chinese college students, but little is known about the heterogeneity in the developmental trajectory of depressive symptoms in China. This study examined heterogeneity in the development of depressive symptoms and examined the effect of gender on the developmental trajectories over a 14-month period among Chinese college students (N = 1163, mean age 20.18, 80.31% female). Three different trajectories, moderate-increasing, high-stable and low-stable, captured the heterogeneity in the development of depressive symptoms. Gender showed significant influence on class membership. Relative to the moderate-increasing class, males emerged as significantly more likely than females to be found in the low-stable class (odds ratio (OR) = 2.73, 95% CI = (1.21, 6.13), p = 0.015) and the high-stable class (OR = 5.10, 95% CI = (1.12, 23.18), p = 0.035). The results provide additional evidence for the conclusion that the trajectories of depressive symptoms are heterogeneous with Chinese samples. Moreover, cultural difference should be paid more attention to when examining the effect of gender and other predictors of the trajectories of depressive symptoms.

Trajectory Analysis of Orthostatic Hypotension in Parkinson's Disease: Results From Parkinson's Progression Markers Initiative Cohort.

Background: Orthostatic hypotension (OH) in Parkinson’s disease (PD) can lead to falls, impair quality of life, and increase mortality. A trajectory analysis of OH could be useful to predict and prevent the hypotension incidence early.Methods: The longitudinal data of 660 patients with PD with disease duration up to 12 years were extracted from an integrated PD database. We used latent class mixed modeling (LCMM) to identify patient subgroups, demonstrating trajectories of changes in orthostatic blood pressure (BP) over time. The optimal number of subgroups was selected by several criteria including the Bayesian Information Criterion. Baseline information comparison between groups and backward stepwise logistic regression were conducted to define the distinguishing characteristics of these subgroups and to investigate the predictors for BP trajectory.Results: We identified three trajectories for each orthostatic change of systolic blood pressure (ΔSBP), namely, Class 1 (i.e., the increasing class) consisted of 18 participants with low ΔSBP that increased continuously during the follow-up; Class 2 (i.e., the low-stable class) consisted of 610 participants with low ΔSBP that remained low throughout the follow-up; and Class 3 (i.e., the high-stable class) consisted of 32 participants with high ΔSBP at baseline that was relatively stable throughout the follow-up. Several parameters differed among subgroups, but only male sex [odds ratio (OR) = 4.687, 95% confidence interval (CI) = 1.024–21.459], lower supine diastolic blood pressure (DBP) (OR = 0.934, 95% CI = 0.876–0.996), and lower level of total protein at baseline (OR = 0.812, 95% CI = 0.700–0.941) were significant predictors of an increasing ΔSBP trajectory.Conclusion: This study provides new information on the longitudinal development of ΔSBP in patients with PD with distinct trajectories of rapidly increasing, low-stable, and high-stable class. The parameters such as male sex, lower supine DBP, and lower total proteins help to identify the rapidly increasing class.