Latent Growth Mixture Modeling Research Articles

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

ObjectiveTo explore the trajectories of cognitive function development and predictive factors in disabled middle-aged and older adults.MethodsUtilizing 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.ResultsThe 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.ConclusionThere 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.

Symptoms of Posttraumatic Stress Disorder Among Japanese Peacekeepers Deployed in South Sudan

Peacekeepers in United Nations missions experience potentially traumatic events, resulting in increased risk for posttraumatic stress disorder (PTSD). Understanding the course and risk factors of PTSD symptom severity is crucial to ensure personnel safety. To investigate the incidence of PTSD, symptom severity trajectories, and potential risk factors associated with adverse trajectories among Japanese peacekeepers deployed in South Sudan. Data for this 6-year prospective cohort study were collected from December 2011 to December 2018 from Japan Ground Self-Defense Force personnel deployed at the United Nations Mission in South Sudan, corresponding to before and up to 78 months after deployment. Of 3799 potential participants, 80 were excluded because of multiple deployments and 757 because of missing data, incomplete responses, or not providing informed consent. Therefore, 2962 participants were included in the analysis. Data analysis was performed from February 2022 to February 2024. The participants were deployed to United Nations Mission in South Sudan for 6 months. The 22-item Impact of Event Scale-Revised was used to assess PTSD symptoms, with 25 or more points indicating probable PTSD (p-PTSD). Sociodemographic data were collected, and the 30-item General Health Questionnaire was administered before deployment to identify risk factors for PTSD symptom severity. In the 2962 participants studied (2901 [97.9%] male; mean [SD] age, 33.9 [7.2] years), the incidence of p-PTSD was 3.95%. Latent growth mixture models identified 4 symptom severity trajectories: resilient (2143 [72.3%]), recovery (479 [16.2%]), protracted (182 [6.1%]), and delayed (158 [5.3%]). Multinomial logistic regression showed that sleep disturbance was a common risk factor for the 2 most severe trajectories (protracted: odds ratio [OR], 1.29; 95% CI, 1.08-1.54; delayed: OR, 1.26; 95% CI, 1.03-1.53), whereas older age (OR, 1.25; 95% CI, 1.06-1.48), anxiety and dysphoria (OR, 1.45; 95% CI, 1.20-1.75), and general illness (OR, 1.30; 95% CI, 1.06-1.59) were associated with the protracted trajectory. This cohort study found that approximately 4% of the participants developed p-PTSD and identified 4 distinct PTSD symptom trajectories. The findings suggest that addressing sleep disturbance and general health issues could effectively prevent PTSD symptoms among peacekeepers.

Distinguishing sympathisers, philanthropists, rusted on activists and radicals: Using person‐centred analyses in collective action research

AbstractMany of our theories and models within social psychology implicitly refer to ‘types’ or subgroups of people who engage in collective action (activists, protestors), or do not (sympathisers, bystanders). Other frameworks differentiate between actors based on their adoption of tactics (benevolents, activists, radicals). How, empirically, do we distinguish sympathisers from activists? Activists from radicals? This paper describes recent research that adopts person‐centred statistical approaches (e.g., latent profile analysis, latent transition analysis, latent growth mixture models) to address three contemporary puzzles of collective action research. We present research showing that the methods are useful in identifying and explaining sub‐groups of people who seek to bring about change in qualitatively different ways. The methods are also useful for understanding volatility in collective action as well as identifying and understanding variation in how people sustain, increase, or diminish their commitment over time. There is nothing so practical as a good method and person‐centred statistical approaches are an important complement to variable‐centred approaches in social psychological research on collective action.

Return to Work Trajectories of Swedish Employees on Sick-Leave Due to Common Mental Disorders.

Recent research has emphasized that return to work (RTW) is a dynamic, gradual and often uneven process with a great degree of individual variation. This study aimed to identify RTW trajectories of Swedish employees on sick-leave due to common mental disorders (CMDs). The second aim was to explore which demographic, employment, health-related and work environment characteristics predicted RTW trajectory membership. Data comes from two 2-armed cluster-randomized controlled trials (RCT) with a 12-month follow-up. A participative problem-solving intervention aimed to reduce sick-leave was compared to care as usual (CAU) involving any kind of work-directed interventions. Participants on sick-leave due to CMDs at baseline (N = 197) formed the study sample. Latent growth mixture modeling and logistic regression were the main analytical approaches. Five distinct RTW trajectories of Swedish employees were identified: Early RTW (N = 65), Delayed RTW (N = 50), Late RTW (N = 39), Struggling RTW (N = 21) and No RTW (N = 22). RTW trajectories differed consistently with regard to previous sick-leave duration and social support at work. More unique predictors of RTW trajectories included gender, rewards at work, work performance impairment due to health problems, home-to-work interference and stress-related exhaustion disorder. The study may have important clinical implications for identifying patients belonging to a particular RTW trajectory. Knowledge on the modifiable work environment factors that differentiated between the RTW trajectories could be useful for designing effective workplace interventions, tailored to particular needs of employees with CMDs. However, in a first step, the results need to be replicated.

A preliminary study of latent trajectories of change in dietary restraint during CBT-E for bulimia-spectrum eating disorders and their associations with treatment response

ABSTRACT Objective Dietary restraint is a primary target of CBT-E. However, little research has examined how specific types of dietary restraint change during CBT-E for bulimia-spectrum eating disorders (BN-EDs) or the association between changes in dietary restraint and treatment response. This study examined latent trajectories of change in eating enough, eating a range of macronutrients, and following dietary rules during CBT-E for BN-EDs and the relationships between these trajectories and pre- to post-treatment change in BN symptoms and remission. Method Participants were 56 adults with BN-EDs who received 16 sessions of CBT-E and completed the Eating Disorder Examination and ecological momentary assessments (EMA) of eating behaviors and BN symptoms. Latent growth mixture modeling identified trajectories of change in dietary restraint, which were compared on pre- to post-treatment BN symptom change and remission. Results Three trajectories of change were identified for eating enough, eating a range of macronutrients, and food rules. Trajectories of change in eating enough were differentially associated with pre- to post-treatment change in BN symptoms, and trajectories of change in eating a range of macronutrients and food rules were differentially associated with remission. Conclusions CBT-E yields heterogeneous trajectories of change in dietary restraint, which are associated with treatment response.

Brain Connectomics Improve the Prediction of High-Risk Depression Profiles in the First Year following Breast Cancer Diagnosis

Background. Prediction of high-risk depression trajectories in the first year following breast cancer diagnosis with fMRI-related brain connectomics is unclear. Methods. The Be Resilient to Breast Cancer (BRBC) study is a multicenter trial in which 189/232 participants (81.5%) completed baseline resting-state functional magnetic resonance imaging (rs-fMRI) and four sequential assessments of depression (T0-T3). The latent growth mixture model (LGMM) was utilized to differentiate depression profiles (high vs. low risk) and was followed by multivoxel pattern analysis (MVPA) to recognize distinct brain connectivity patterns. The incremental value of brain connectomics in the prediction model was also estimated. Results. Four depression profiles were recognized and classified into high-risk (delayed and chronic, 14.8% and 12.7%) and low-risk (resilient and recovery, 50.3% and 22.2%). Frontal medial cortex and frontal pole were identified as two important brain areas against the high-risk profile outcome. The prediction model achieved 16.82-76.21% in NRI and 12.63-50.74% in IDI when brain connectomics were included. Conclusion. Brain connectomics can optimize the prediction against high-risk depression profiles in the first year since breast cancer diagnoses.

Association of longitudinal trajectories of fasting plasma glucose with all-cause and cardiovascular mortality among a Chinese older population: a retrospective cohort study

The association between fasting plasma glucose (FPG), an important indicator of overall glycemic status, and the risk of cardiovascular mortality has been well investigated. The longitudinal study can repeatedly collect measured results for the variables to be studied and then consider the potential effects of intraindividual changes in measurement. This study aimed to identify long-term FPG trajectories and investigate the association between trajectory groups and cardiovascular and all-cause mortality. A latent class growth mixture modeling (LCGMM) was used to identify FPG trajectories. Cox proportional hazard models were used to estimate associations between FPG trajectories and the risk of all-cause and cardiovascular mortality. A U-shaped relationship between FPG and all-cause and cardiovascular mortality was observed in the restricted cubic spline regression models. Two FPG longitudinal trajectories of low-level (mean FPG = 5.12mmol/L) and high-level (mean FPG = 6.74mmol/L) were identified by LCGMM. After being adjusted for potential confounders, compared with the low-level category, the hazard ratios (HRs) for all-cause and cardiovascular mortality were 1.23(1.16–1.30) and 1.25(1.16–1.35), respectively, for the high-level group. Long-term FPG trajectories are significantly associated with and potentially impact the risk of all-cause and cardiovascular mortality.

CARDIOVASCULAR RISK FACTOR TRAJECTORIES AND INCIDENT CARDIOVASCULAR DISEASE IN OLDER ADULTS: THE KAILUAN STUDY

Objective: Long-term condition and longitudinal accumulation of cardiovascular risk factor (CRF) may be associated with adverse outcomes in the elderly, but the previous evidence is scarce. We studied the associations of CRF trajectories, their accumulation, with incident cardiovascular disease (CVD) in older adults. Design and method: From 2006, a population-based cohort of 8505 older adults have been repeatedly followed up for 14 years (until 31 December 2020). Blood pressure, serum lipids, height and weight, and blood glucose were assessed in all follow-ups and their trajectories from 2006 to 2010 were identified using latent class growth mixture modeling. Main outcome was incident CVD, which was a composite of coronary revascularization, myocardial infarction, heart failure, or stroke. The associations of CRF trajectories and incident CVD were studied for individual CRF trajectory and their accumulation, using Cox proportional hazards regression models. Results: We identified 3, 4, 2, 2 trajectories for systolic blood pressure (SBP), body mass index (BMI), total cholesterol (TC), and fasting blood glucose (FBG), respectively. Compared with low-increasing SBP, the multivariable-adjusted hazard ratio (HR) and 95% CI were 1.35 (1.19-1.54) for moderate-increasing SBP and 1.54 (1.28-1.86) for high-increasing SBP. Compared with low-stable BMI, the HRs (95% CIs) were 1.30 (1.11-1.53), 1.41 (1.19-1.66), 1.35 (1.07-1.71) for moderate-stable, elevated-stable, and high-stable BMI, respectively. Compared with low-stable TC, the HR (95% CI) were 1.19 (1.06-1.33) for high-stable TC. Compared with low-stable FBG, the HR (95% CI) were 1.38 (1.17-1.63) for high-stable FBG. A positive association was observed for the CRF trajectory accumulation with incident CVD (P for trend &lt; 0.001), with HRs (95% CIs) of 1.54 (1.16-2.04), 2.15 (1.63-2.83), 2.58 (1.93-3.45) and 2.92 (1.95-4.36) for 1, 2, 3, 4 high CRF trajectories, respectively. Sensitivity analyses showed consistent results after excluding those who ever used antihypertensive, antidiabetic, or lipid-lowering drugs during 2006 to 2010, excluding events within the first year of follow-up, and considering death as competing risk. Conclusions: Longitudinal higher CRF trajectory was independently associated with higher CVD risk in older adults. Besides, the higher the number of adverse CRF trajectories, the higher was the observed CVD risk.

P062 Trust performance in managing inflammatory arthritis over time in England and Wales: a latent class analysis approach

Abstract Background/Aims To evaluate trust-level performance in time to initiation of disease-modifying antirheumatic drug (DMARD) therapy in patients with early inflammatory arthritis (EIA), with identification of change in performance trajectories over time and investigation of trust characteristics associated with this change. Methods We included 130 trusts from the UK contributing to the National Early Inflammatory Arthritis Audit (NEIAA) from 2018 to 2020. The primary outcome was days from referral to initiation of DMARD therapy in patients with EIA. Latent class growth mixture models were applied to identify distinct groups of trusts with similar trajectories of performance change over time. We used mixed-effects linear and multinomial logistic regression models to evaluate the association between delay in treatment and trust-level characteristics. Results The mean (SD) time to DMARD initiation was 53 (18) days, with an average 0.3-day decrease with each month over time. Four latent trajectories were identified in our cohort, with over 77% of individual trusts showing ongoing improvements in decreasing treatment waiting times. Prior to separating by latent class, time to DMARD initiation was shorter in trusts with higher rheumatology staffing, a local EIA treatment pathway and those with access to musculoskeletal ultrasound. Trusts with more nurses in the rheumatology department were less likely to be in the worse performance group (OR = 0.69 [95%CI 0.49, 0.93]). Conclusion In this cohort study, we observed a reduction in treatment waiting time over time. Trusts with better staffed and improved EIA clinical structure are likely to initiate definitive treatment earlier in patients with EIA. Disclosure Z. Yang: None. N. Arumalla: None. M.D. Russell: Honoraria; Lilly, Menarini, Galapagos. Grants/research support; NIHR. Other; Pfizer, Janssen, Biogen, and UCB. K. Bechman: Honoraria; Menarini, Galapagos. Grants/research support; NIHR,Versus Arthritis and Pfizer Global Medical Grants for Quality Improvement in Rheumatology Practice. Other; UCB. E. Alveyn: Other; UCB. S. Gallagher: None. E. Price: None. S. Norton: None. J. Galloway: Honoraria; AbbVie, Biovitrum, BMS, Celgene, Chugai, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Sanofi, Sobi and UCB.

Self-care trajectories of patients with coronary heart disease: a longitudinal, observational study.

To determine if distinct trajectories of coronary heart disease (CHD) self-care behaviours could be identified, linked to differences in quality of life (QoL), and predicted based on baseline characteristics. A secondary analysis of a prospective, longitudinal, observational study. Patients with CHD answered questionnaires at study enrolment and six months later: Self-Care of Coronary Heart Disease Inventory (three subscales: maintenance, management and confidence, scored 0-100, higher score = better self-care), Hospital Anxiety and Depression Scale, 12-Item Short Form Survey, 16-Item European Health Literacy Survey Questionnaire, CHD Education Questionnaire. Latent growth mixture modelling was used to identify distinct self-care trajectories over time.On average, patients (n = 430, mean age 64.3 ± 8.9, 79% male) reported inadequate self-care (maintenance 61.6 ± 15.4, management 53.5 ± 18.5) at enrolment. Two distinct trajectories of self-care behaviours were identified: First, an "inadequate-and-worsening" (IN-WORSE) trajectory (57.2%), characterised by inadequate self-care, improvement in maintenance (4.0 ± 14.5-point improvement, p < 0.001) and worsening of management over time (6.3 ± 24.4-point worsening, p = 0.005). Second, an "inadequate-but-maintaining" (IN-MAIN) trajectory (42.8%), characterised by inadequate self-care, improvement in maintenance (5.0 ± 16.2-point improvement, p < 0.001) and stability in management over time (0.8 ± 21.9-point worsening, p = 0.713). In comparison, patients in the IN-WORSE trajectory had less favourable characteristics (including lower health literacy, knowledge, confidence) and significantly lower QoL. Not attending rehabilitation (OR 2.175; CI 1.020-4.637, p = 0.044) and older age (OR 0.959; CI 0.924-0.994, p = 0.024) predicted (IN-WORSE) trajectory inclusion. Two self-care trajectories were identified, both suboptimal. Rehabilitation predicted membership in the more favorable trajectory and some positive characteristics were identified among patients in that group. Therefore, interventions supporting these factors may benefit patients' self-care and QoL.