Latent Growth Mixture Modeling Research Articles

Understanding the transdiagnostic mechanisms underlying emerging psychopathology in adolescence: study protocol of a 1-year prospective epidemiological (EMERGE) study

IntroductionAdolescent mental health is a global public health challenge as most cases remain undetected and untreated, and consequently, have a high likelihood of persistence or recurrence. It is critical to...

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

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

Association between body mass index trajectories and type 2 diabetes incidence over an 18-year follow-up in the Tehran Lipid and Glucose Study.

Body mass index (BMI) is a well-known risk factor for type 2 diabetes mellitus (T2DM). We aimed to identify BMI trajectory patterns and evaluate their association with T2DM during 18 years of follow-up. We included 6026 participants aged 20 to 65 from the prospective population-based Tehran Lipid and Glucose Study (TLGS). The BMI trajectory patterns were identified using latent growth mixture modeling (LGMM) during the measurement period. The association between the BMI trajectory patterns and future T2DM was evaluated using the Cox proportional hazard regression models. Three BMI trajectory patterns of low-increasing (38.6%), medium-increasing (47.1%), and high-increasing (14.3%) were detected. The participants in the medium-increasing and high-increasing BMI trajectory groups had HRs of 1.87 (95% CI 1.53-2.28) and 3.41(95% CI 2.71-4.29) for T2DM incidence, respectively. Within the normoglycemic subpopulation, the high-increasing BMI group had an HR of 3.82 (95% CI 2.79-5.24) compared to the low-increasing BMI group, while in the prediabetic subpopulation, the high-increasing BMI group had an HR of 2.93 (95% CI 2.04-4.19) compared to the low-increasing BMI group. Body weight varies in a relatively stable pattern in adulthood over the long-term period. Medium and high-increasing BMI trajectory patterns have a significantly increased risk for future T2DM in both normoglycemic and prediabetic individuals. Identifying BMI trajectory patterns can help healthcare providers in early prediction, risk assessment, and monitoring strategies development for the prevention of T2DM.

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

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

Identifying transdiagnostic and multidimensional prognostic indicators among veterans with PTSD symptoms in brief integrated care settings.

Brief integrated care settings hold promise for accessible and effective trauma-informed interventions. However, clinicians often have difficulty efficiently forecasting who is most appropriate for interventions in such settings and how to target individualized care. Multidimensional and transdiagnostic evaluations may provide valuable information to improve stepped-care and treatment practices for veterans. A middle-out approach was used to concurrently evaluate self-reported posttraumatic stress disorder (PTSD) symptoms, depressive symptoms, and physical health problems using cross-sectional (latent profile analysis) and longitudinal (latent growth mixture modeling) analyses that identified unique symptom profiles, trajectories of traumatic stress reactions, and correlates of these health outcomes. Data from 234 veterans who participated in a randomized controlled trial of primary care PTSD intervention were analyzed at 0, 8, 16, and 24 weeks. Latent profile analysis identified two homogenous baseline profiles: global symptoms (33.8%); low dysphoria-lower negative cognitions, mood, and depressive symptoms (66.2%). Low dysphoria participants reported more social relationships (OR = 1.32) and fewer environmental (OR = 0.89) and financial (OR = 0.23-0.35) stressors. Latent growth mixture modeling identified three trajectories: (a) reducing symptoms ("responders"; 21.3%) and chronic symptoms of (b) moderate (59.6%) and (c) high (19.1%) severity. Low dysphoria participants were 4.35 times more likely to be responders over time compared to participants with moderate severity symptoms. Findings indicated that veterans with moderate PTSD symptoms and physical health problems but low dysphoria may respond best to trauma-informed intervention in brief integrated care settings, while others may require further individualized stepped care. Findings demonstrate unique traumatic stress reactions that support individualized stepped care and may offer greater treatment utilization, retention, and efficacy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring the developmental changes in and the relationship between resilience and anxiety and depression in older gastric cancer survivors: A latent growth mixture model and random intercept cross-lagged panel model analysis.

This study aims to investigate the independent and joint trajectories of resilience, anxiety, and depression symptoms and research the interaction between older gastric cancer survivors' resilience and anxiety-depression during the period of 1 year after surgery. The participants were 381 older gastric cancer survivors, with a mean age of 69 years. Resilience, anxiety, and depression symptoms were assessed immediately after surgery, and at 3, 6, and 12 months post-surgery, respectively. A longitudinal design was employed to capture the dynamic changes in resilience, anxiety, and depression levels among older gastric cancer survivors post-surgery. Latent growth mixture model and random intercept cross-lagged panel model were used to analyse the trajectories of resilience and anxiety-depression and the interaction between them. Two latent trajectories were identified for the resilience, four latent trajectories were identified for the anxiety, and five latent trajectories were identified for the depression, respectively, with three joint trajectories identified: gradual-increasing resilience, gradual-decreasing anxiety, and depression group (10.0%); gradual-decreasing resilience, gradual-increasing anxiety, and depression group (21.2%); and rapid-growth resilience, rapid-decline anxiety, and depression group (68.8%). Resilience among older gastric cancer survivors exhibits significant bidirectional and negative predictive effects on anxiety and depression. Individual differences in resilience, anxiety, and depression trajectories exist among older gastric cancer survivors, with heterogeneous joint progression patterns, and the relationship between resilience and anxiety-depression appears bidirectional. More sophisticated intervention programmes tailored to the unique characteristics of the relevant trajectories are necessary to enhance resilience and mitigate the risk of anxiety and depression.

The association of multi-system conditions on mental health trajectories during naval deployment

ABSTRACT This study seeks to enhance understanding of mental health trajectories across Navy deployments and the predictors of those trajectories by exploring a range of job design and individual-level factors. Personnel from the Royal Australian Navy were surveyed on pre-deployment, mid-deployment, and post-deployment. At pre-deployment, there were 559 (M age = 30.19; male = 75.5%) survey responses, N = 112 survey responses could be linked at all time points (retention rate of 20.04% across all time points), and 314 personnel (56.2%) responded at least twice. Latent class growth analyses and growth mixture models were used to determine the trajectories that best fit the data. Separate models were developed for each of the mental health outcomes studied (i.e. psychological distress, perceived resilience, and perceived stress), plus a latent outcome representing a summary measure of psychological ill-health. This latent outcome, estimated as the most comprehensive assessment approach, was used to evaluate all 33 predictors. Consistent with previous work, we identified between two and four trajectories reflecting resilient/low symptom trajectories and heterogeneous symptom trajectories. There were a greater proportion of personnel in the heterogeneous symptom trajectories than identified in previous research. A key contribution of this work is the thorough comparison and ranking of factors that influence the deployment experience. We emphasize the importance of role demands and resources in determining these trajectories when compared directly to self-regulation strategies. Study findings highlight important implications for job design for military personnel during deployment and underscore the importance of adopting a holistic system approach to well-being.

Association between blood glucose level trajectories and 30-day mortality risk in patients with acute ischemic stroke: analysis of the MIMIC database 2001–2019

BackgroundHyperglycemia is one of the most common comorbidities in patients with acute ischemic stroke (AIS). This study aimed to assess the impact of short-term longitudinal blood glucose level change trajectories on the 30-day mortality risk in patients with AIS.MethodsData for AIS patients were obtained from the 2001–2019 Medical Information Mart for Intensive Care (MIMIC) database. The latent growth mixture modeling (LGMM) was utilized to classify a patient’s blood glucose level trajectory within 24 h of admission. Cox regression analyses were applied to examine the relationship between blood glucose levels at admission and blood glucose level trajectories and the risk of 30-day mortality in patients with AIS.ResultsA total of 2,432 patients with AIS were included in this retrospective cohort study, with 30-day mortality occurring in 574 (23.60%) patients. The median glucose levels of all patients were 136.00 (110.00, 178.00) mg/dL. Four blood glucose level trajectories were identified: low level-stable trend (type 1), moderate level-stable trend (type 2), high level-decreasing-increasing trend (type 3), and moderate level-increasing-decreasing trend (type 4). Type 2 blood glucose level trajectory was associated with an increased risk of 30-day mortality compared with type 1 blood glucose level trajectory [hazard ratio (HR) = 1.28, 95% confidence interval (CI): 1.03–1.59), but there were no significant associations between type 3 (HR = 1.16, 95%CI: 0.77–1.74) and type 4 (HR = 1.44, 95%CI: 0.84–2.45) trajectories and 30-day mortality risk. Subgroup analysis demonstrated that the association between type 2 trajectory and 30-day mortality risk was observed in patients aged ≥ 65 years (HR = 1.37, 95%CI: 1.05–1.79), female (HR = 1.42, 95%CI: 1.05–1.94), with (HR = 1.44, 95%CI: 1.02–2.02) or without (HR = 1.42, 95%CI: 1.01–1.99) diabetes, and not using insulin (HR = 2.80, 95%CI: 1.43–5.49).ConclusionAIS patients with consistently high blood glucose levels within 24 h of admission increased the risk of 30-day mortality.

Trajectories of Short-Term Post-Traumatic Stress Disorder Symptoms in Patients with Post-Intensive Care Syndrome: A Longitudinal Observational Study.

Post-traumatic stress disorder (PTSD) is a major psychiatric health issue among intensive care unit (ICU) survivors with post-intensive care syndrome (PICS). Although early PTSD intervention has been demonstrated to decrease the risk of progression from acute to chronic PTSD, information on the progression trajectory of short-term PTSD symptoms and modifiable risk factors in PICS patients is limited. This study aimed to explore the clinical progression trajectories of short-term PTSD symptoms and the associated factors in PICS patients by conducting a prospective longitudinal observational study. This study was conducted at a tertiary hospital in China. The impact of event scale-revised was used to collect data on the PTSD symptoms of patients at 1, 2, 3, and 4 months post-discharge from the ICU. The latent growth mixture model was used to construct trajectory models for PTSD symptoms and multivariate logistic regression was used to determine the factors associated with the trajectories. A total of 130 ICU survivors with PICS completed the 4-month short-term follow-up. Our results showed that PTSD symptoms in PICS patients manifested as three trajectories, namely, moderate chronic (n = 17, 13.1%), recovery (n = 25, 19.2%), and resilience (n = 88, 67.7%). Compared with the resilience trajectory, age and female were identified as risk factors for the moderate chronic trajectory, while prolonged ICU stay was a risk factor for the recovery trajectory. Our study showed that short-term PTSD symptoms in PICS patients manifested as moderate chronic, recovery, and resilience trajectories. Additionally, our results showed that PTSD screening should be conducted for critically ill patients, especially younger, female, or long-term ICU patients, immediately after their discharge from the ICU.

Characterizing within-person variance in, and menstrual cycle associations with, event-related potentials associated with positive and negative valence systems: The reward positivity and the error-related negativity

Event-related potentials (ERPs) are widely employed as measures of transdiagnostic cognitive processes that are thought to underlie various clinical disorders (Hajcak et al., 2019). Despite their prevalent use as individual difference measures, the effects of within-person processes, such as the human menstrual cycle, on a broad range of ERPs are poorly understood. The present study leveraged a within-subject design to characterize between- and within-person variance in ERPs as well as effects of the menstrual cycle in two frequently studied ERPs associated with positive and negative valence systems underlying psychopathology—the Reward Positivity (RewP) and the Error- Related Negativity (ERN). Seventy-one naturally-cycling participants completed repeated EEG and ecological momentary assessments of positive and negative affect in the menstrual cycle's early follicular, periovulatory, and mid-luteal phases. We examined the mean degree of change between cycle phases in both ERPs, the between-person variability in the degree of change in both ERPs, and whether an individual’s degree of cyclical change in these ERPs show coherence with their degree of cyclical change in positive and negative affect recorded across the cycle. Results revealed no significant changes in positive and negative affect across the cycle and rather small changes in ERP amplitudes. Significant random slopes in our model revealed larger individual differences in trajectories of change in ERP amplitudes and affect, in agreement with prior evidence of heterogeneity in dimensional hormone sensitivity. Additionally, state-variance in these ERPs correlated with positive and negative affect changes across the cycle, suggesting that cycle-mediated ERP changes may have relevance for affect and behavior. Finally, exploratory latent class growth mixture modeling revealed subgroups of individuals that display disparate patterns of change in ERPs that should be further investigated.

Trajectories and predictors of gerontological service career adaptability among health science undergraduates: A longitudinal study

BackgroundIn response to the aging population, it is essential to examine gerontological service career adaptability among health science undergraduates. ObjectivesThis study aimed to clarify the trajectories and predictors of health science undergraduates' gerontological service career adaptability. DesignThis study adopted a longitudinal design. SettingsThis study was conducted at four universities in China. Participants and methodsHealth science undergraduates were recruited via convenience sampling. Data were collected in the third (Stage 1), sixth (Stage 2), and ninth (Stage 3) months of the participants' graduation year. A total of 471 undergraduates completed a three-stage self-report questionnaire that assessed gerontological service career adaptability, career motivation, proactive personality, and practice environment at Stage 1 and gerontological service career adaptability at Stages 2 and 3. The response rate was 76.84 %. Data analyses entailed multiple linear regression, a latent growth mixture model, and multiple logistic regression. ResultsThree subgroups representing different gerontological service career adaptability trajectories were identified: rapidly growing (6.16 %), stably growing (87.47 %), and decreasing (6.37 %). Changes were observed primarily from the third to sixth months of the participants' graduation year. Health science undergraduates with high career motivation and a strongly proactive personality were likely to be in the decreasing group, whereas those with a supportive practice environment were predisposed to belong to the decreasing and stably growing groups. ConclusionsThe health science undergraduates' gerontological service career adaptability trajectories are heterogeneous, with the critical period spanning the third to sixth months of their graduation year. Gerontological service career adaptability grows stably among most undergraduates who have a supportive practice environment. Additionally, gerontological service career adaptability changes easily among undergraduates with high career motivation and a strongly proactive personality. Educators should implement tailored interventions to enhance gerontological service career adaptability based on health science undergraduates' traits.

Latent growth mixture models as latent variable multigroup factor models: Comment on McNeish et al. (2023).

McNeish et al. argue for the general use of covariance pattern growth mixture models because these models do not involve the assumption of random effects, demonstrate high rates of convergence, and are most likely to identify the correct number of latent subgroups. We argue that the covariance pattern growth mixture model is a single random intercept model. It and other models considered in their article are special cases of a general model involving slope and intercept factors. We argue growth mixture models are multigroup invariance hypotheses based on unknown subgroups. Psychometric models in which trajectories are modeled using slope factor loadings which vary by latent subgroup are often conceptually preferable. Convergence rates for mixture models can be substantially improved by using a variance component start value taken from analyses with one fewer class and by specifying multifactor models in orthogonal form. No single latent growth model is appropriate across all research contexts and, instead, the most appropriate latent mixture model must be "right-sized" to the data under consideration. Reanalysis of a real-world longitudinal data set of posttraumatic stress disorder symptomatology reveals a three-group model involving exponential decline, further suggesting that the four-group "cat's cradle" pattern frequently reported is artefactual. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Trajectories of cognitive function development and predictive factors in disabled middle-aged and older adults.

To explore the trajectories of cognitive function development and predictive factors in disabled middle-aged and older adults. Utilizing data from 983 disabled middle-aged and older adults in the China Health and Retirement Longitudinal Study (CHARLS) from 2013 to 2020, latent growth mixture models were constructed to analyze the categories of cognitive function development trajectories and their predictive factors. The cognitive function trajectories of the disabled middle-aged and older adults were classified into three categories: rapid decline (32.6%), Slow decline (36.1%), and Stable (31.2%). Multinomial logistic regression analysis identified age, gender, residence, education, marital status, household income, sleep duration, depression, hearing ability, and social participation as predictors of these trajectories. There is heterogeneity in the cognitive function development trajectories among disabled middle-aged and older adults. Healthcare professionals can implement targeted health management based on the characteristics of different groups to prevent the deterioration of cognitive function in this population.

Trajectories of negative and positive marital quality during later life

This study aims to establish trajectories of later-life marital quality and assess predictors of trajectory membership. Although numerous studies examine marital quality across the early years of marriage, much less is known about older adults’ trajectories. Existing studies assess average patterns of stability or decline over the life course but have not explored the possibility of multiple trajectories during later life. This study uses nationally-representative data from the 2008–2018 waves of the Health and Retirement Study ( https://www.hrs.isr.umich.edu ). Latent growth mixture models are estimated to identify unique trajectories of positive and negative dimensions of marital quality over an eight-year time period among a sample of adults aged 51 to 97 ( n = 4,467). Results show two distinct patterns of marital quality during later life: (1) high, slightly increasing positive marital quality with low, slightly declining negative marital quality; and (2) moderate, sharply declining positive marital quality with moderate, stable negative marital quality. Significant predictors of trajectory membership include gender, household income, marital duration, remarriage, self-rated health, and depressive symptoms. Rather than patterns of stability or continual decline in marital quality over the later life course, we find the most common trajectory during later life is slight improvement. Only about 12% of older adults experience decline, and that decline is limited to the dimension of positive marital quality, with no uptick in negative marital quality.

Impact of adiposity indices changes across the lifespan on risk of diabetes in women: trajectory modeling approach

AimsThe impact of life-course different adiposity indices on diabetes mellitus (DM) is poorly understood. We aimed to do trajectory analysis with repeated measurements of adiposity indices in the development of DM among women across the lifespan.MethodsThis study prospectively investigated the 1,681 population of Tehran Lipid and Glucose Study. At baseline, all individuals were free of diabetes. Trajectory analysis was used to identify homogeneous distinct clusters of adiposity indices trajectories and assign individuals to unique clusters.ResultsOf the 1681 healthy women, 320 progressed to the DM. Three distinct body mass index (BMI) trajectories and 2 distinct trajectories of other adiposity indices (waist circumstance (WC), conicity index (C-index), and body roundness index (BRI)) were chosen as the best fitting of the latent class growth mixture model. In the adjusted model, total participants [HR (CI 95%): 2.83 (2.05, 3.91); p < 0.001], and menopause [1.35 (1.10, 2.11); p = 0.001] and reproductive-age women [2.93 (1.80, 4.78); p = 0.003] of the high BMI trajectory compared to the ones in the low trajectory of BMI were more likely to develop DM. The high BRI in menopause had a significantly higher risk of DM compared to the low trajectory. In menopause (1.80 (1.26, 2.58)) and reproductive-age women (4.32 (2.49, 7.47)) with high trajectory of C-index, the DM risk decreased after adjustment.ConclusionsThe risk of DM was greater for high BMI, WC, C-index, and BRI trajectories than for lower trajectories. Hence, the development of general, abdominal, and visceral obesity trajectories in the prevention of DM should be considered by clinicians.

A prospective longitudinal investigation of the trajectory of obsessive-compulsive symptoms during adolescence

Obsessive-compulsive symptoms (OCS) increase with age during childhood and adolescence, and subthreshold OCS in childhood associate with a higher probability of obsessive-compulsive disorder (OCD) diagnosis in adulthood. Additionally, average age of onset for OCD is in adolescence, with the majority of OCD cases emerging by early adulthood. Despite these trends, the specific course of OCS development in adolescence is relatively unknown. To this end, the present prospective longitudinal study used latent growth mixture modeling and a diverse community sample of 3,335 high schoolers to identify and characterize growth trajectories of OCS across middle to late adolescence. Results identified three trajectories: High-but-Remitting, Moderate-but-Escalating, and Low-and-Stable. Results also indicated age, gender, anxiety sensitivity, and distress tolerance as significant predictors of trajectory group membership, such that younger age and being female predicted classification in the High-but Remitting group, greater anxiety sensitivity predicted classification in both the High-but-Remitting and Moderate-but Escalating groups, and greater distress tolerance predicted a lower likelihood of classification in the High-but-Remitting and Moderate-but-Escalating groups. Taken together, these trajectories have illustrated the temporal course and development of OCS across key developmental years. Moreover, the trajectories and their corresponding predictors may help identify adolescents who are particularly vulnerable to developing OCD.

Extreme temperatures, PM2.5 and trajectories of impaired thyroid hormone sensitivity: A longitudinal study of patients with schizophrenia

BackgroundThe climate change scenario has witnessed an increase in extreme temperature events (ETEs), including heat waves and cold spells, and a heightened occurrence of compounding with fine particulate matter (PM2.5). However, the impact of this phenomenon on the sensitivity to thyroid hormones (THs) in humans is unclear, especially in a group as specific as schizophrenia. MethodsA longitudinal study was constructed using longitudinal measurements of thyroid function in schizophrenia in the Anhui Mental Health Center. The latent growth mixture model was applied to assess the optimal trajectory of change in impaired THs sensitivity. We then used logistic regression to explore associations between heat waves, cold spells, and PM2.5 with impaired THs sensitivity trajectories in the total population and different gender and age subgroups. Furthermore, the effect of the frequency, intensity, and duration of ETEs in the above associations was explored, as well as an assessment of the interaction between ETEs and PM2.5. ResultsAmong 931 participants, we identified two classifications of trajectories of impaired THs sensitivity: “Low-stable” (n = 836, 89.80 %) and “Rise-slight down” (n = 95, 10.20 %). Logistic regression showed significant associations between each additional day of heat waves (≥3 days with temperature thresholds above the 95th percentile) and cold spells (≥3 days with temperature thresholds below the 5th percentile) and “Rise-slight down” trajectory, with odds ratios (95 % confidence intervals) of 1.06 (1.02, 1.10) and 1.19 (1.14, 1.24), respectively, and the strength of this association increased with the intensity and duration of ETEs. Subgroup analyses indicated that the association was more pronounced in males and the age group above 40 years. Furthermore, PM2.5 was found to interact with heat waves, with high concentrations exacerbating the effects of heat waves. ConclusionsOur findings suggest that mitigating both ETEs and PM2.5 exposures may bring health co-benefits in preventing thyroid impairment in schizophrenia.

Using machine learning to explore the predictors of life satisfaction trajectories in older adults.

Life satisfaction is vital for older adults' well-being, impacting various life aspects. It is dynamic, necessitating nuanced approaches to capture its trajectories accurately. This study aimed to explore the diverse trajectories and predictors of life satisfaction among older adults in China using longitudinal data from the China Health and Retirement Longitudinal Study. Latent class growth modeling and growth mixture modeling were employed to identify distinct trajectories of life satisfaction. Machine learning (ML) models were developed to predict different trajectories and identify important predictors of different trajectories. Four distinct trajectories of life satisfaction were identified, showcasing nuanced patterns of life satisfaction that changed over time. ML models, especially random forest, effectively predicted these trajectories. Emotional experiences (particularly the frequency of happiness and loneliness), body mass index, and self-report health emerged as significant predictors of different life satisfaction trajectories. Our finding revealed the importance of focusing on individuals or groups with consistently low life satisfaction and paying more attention to mental and physical health predictors. Our models might guide future targeted preventative treatments.

Distinct Longitudinal Trajectories of Symptom Burden Predict Clinical Outcomes in End-Stage Liver Disease.

Little has been reported about the clinical relevance and trajectories of symptoms in end-stage liver disease (ESLD). The purpose of this prospective study was to identify trajectories of change in symptom burden over the course of 12 months in adults with ESLD. Patients were recruited from hepatology clinics at 2 healthcare systems. Validated measures were used to assess physical and psychological symptoms. Latent growth mixture modeling and survival and growth modeling were used to analyze the survey data. Data were available for 192 patients (mean age 56.5 ± 11.1 years, 64.1% male, mean Model for ESLD (MELD) 3.0 19.2 ± 5.1, ethyl alcohol as primary etiology 33.9%, ascites 88.5%, encephalopathy 70.8%); there were 38 deaths and 39 liver transplantations over 12 months. Two symptom trajectories were identified: 62 patients (32.3%) had high and unmitigated symptoms, and 130 (67.7%) had lower and improving symptoms. Patients with high and unmitigated symptoms had twice the hazard of all-cause mortality (subhazard ratio 2.53, 95% confidence interval: 1.32-4.83) and had worse physical ( P < 0.001) and mental quality of life ( P = 0.012) compared with patients with lower and improving symptoms. Symptom trajectories were not associated with MELD 3.0 scores ( P = 0.395). Female sex, social support, and level of religiosity were significant predictors of symptom trajectories ( P < 0.05 for all). There seems to be 2 distinct phenotypes of symptom experience in patients with ESLD that is independent of disease severity and associated with sex, social support, religiosity, and mortality. Identifying patients with high symptom burden can help optimize their care.

Association of physical activity trajectories over 8 years and risk of knee replacement: data from the osteoarthritis initiative

BackgroundTo identify physical activity (PA) trajectories in adults with or at risk of knee osteoarthritis and to evaluate the association of PA trajectories with incident knee replacement (KR).MethodsThis study used data from the Osteoarthritis Initiative. The Physical Activity Scale for the Elderly and the KR were assessed annually from baseline to 9 years. Individuals were included if they did not undergo KR surgery at baseline and had data on PA at ≥ 1 visit before KR. Latent class growth mixture Modeling was used to identify the optimal trajectories of PA before KR. Log-binomial regression models were used to assess the association between PA trajectories and the risk of KR. Data analyses were conducted in all individuals and those with radiographic osteoarthritis (ROA) and significant knee pain (Western Ontario and McMaster Osteoarthritis Index pain score of ≥ 5 on a 0–20 scale) at baseline, respectively.ResultsOf 4731 participants (mean age 61.1 years, 58.5% female), four distinct and slightly declined PA trajectories were identified. Compared to individuals with a “Low” PA trajectory, those with “Medium-low”, “Medium-high”, or “High” PA trajectories were not significantly associated with the risk of KR (risk ratios: 0.97–1.19, all p > 0.05). Similar PA trajectories and associations with the risk of KR were observed in the subgroups of individuals with radiographic osteoarthritis and those with significant knee pain at baseline, respectively.ConclusionIn participants with or at risk of knee osteoarthritis, PA slightly declines over time and may play no role in the risk of KR.