Pitfalls in subgroup analysis based on growth mixture models: a commentary on Van Leeuwen et al. (2012)

Comparing relationships between health-related behaviour clustering and episodic memory trajectories in the United States of America and England: a longitudinal study

Background

Health-related behaviours (HRBs) cluster within individuals. Evidence for the association between HRB clustering and cognitive functioning is limited. We aimed to examine and compare the associations between three HRB clusters: “multi-HRB cluster”, “inactive cluster” and “(ex-)smoking cluster” (identified in previous work based on HRBs including smoking, alcohol consumption, physical activity and social activity) and episodic memory trajectories among men and women, separately, in the United States of America (USA) and England.

Methods

Data were from the waves 10–14 (2010–2018) of the Health and Retirement Study in the USA and the waves 5–9 (2010–2018) of the English Longitudinal Study of Ageing in England. We included 17,750 US and 8,491 English participants aged 50 years and over. The gender-specific HRB clustering was identified at the baseline wave in 2010, including the multi-HRB (multiple positive behaviours), inactive and ex-smoking clusters in both US and English women, the multi-HRB, inactive and smoking clusters in US men, and only the multi-HRB and inactive clusters in English men. Episodic memory was measured by a sum score of immediate and delayed word recall tests across waves. For within country associations, a quadratic growth curve model (age-cohort model, allowing for random intercepts and slopes) was applied to assess the gender-stratified associations between HRB clustering and episodic memory trajectories, considering a range of confounding factors. For between country comparisons, we combined country-specific data into one pooled dataset and generated a country variable (0 = USA and 1 = England), which allowed us to quantify between-country inequalities in the trajectories of episodic memory over age across the HRB clusters. This hypothesis was formally tested by examining a quadratic growth curve model with the inclusion of a three-way interaction term (age × HRB clustering × country).

Results

We found that within countries, US and English participants within the multi-HRB cluster had higher scores of episodic memory than their counterparts within the inactive and (ex-)smoking clusters. Between countries, among both men and women within each HRB cluster, faster declines in episodic memory were observed in England than in the USA (e.g., b _{England versus the USA for men: multi-HRB cluster} = -0.05, 95%CI: -0.06, -0.03, b _{England versus the USA for women: ex-smoking cluster} = -0.06, 95%CI: -0.07, -0.04). Additionally, the range of mean memory scores was larger in England than in the USA when comparing means between two cluster groups, including the range of means between inactive and multi-HRB cluster for men (b _{England versus the USA} = -0.56, 95%CI: -0.85, -0.27), and between ex-smoking and multi-HRB cluster for women (b _{England versus the USA} = -1.73, 95%CI: -1.97, -1.49).

Conclusions

HRB clustering was associated with trajectories of episodic memory in both the USA and England. The effect of HRB clustering on episodic memory seemed larger in England than in the USA. Our study highlighted the importance of being aware of the interconnections between health behaviours for a better understanding of how these behaviours affect cognitive health. Governments, particularly in England, could pay more attention to the adverse effects of health behaviours on cognitive health in the ageing population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13785-7.

Neuropsychological latent classes at enrollment and postmortem neuropathology

INTRODUCTION

We classified individuals based on their baseline performance on cognitive measures and investigated the association between cognitive classifications and neuropathological findings ∼7 years later, as an external validator.

METHODS

Brain autopsies of 779 decedents were examined. Baseline latent class analysis on 10 neuropsychological measures was previously assigned: mixed-domains impairment (n = 39, 5%), memory-specific impairment (n = 210, 27%), frontal impairment (n = 113, 14.5%), average cognition (n = 360, 46.2%), and superior cognition (n = 57, 7.3%). Linear regressions and risks ratios were used to examine the relation of latent class assignment at enrollment with neuropathological indices.

RESULTS

Amyloid β, tau, and transactive response DNA-binding protein 43 were associated with mixed-domains impairment and memory-specific impairment classes ∼7 years before death. Moderate arteriolosclerosis was associated with membership in the frontal impairment class.

DISCUSSION

Our findings support the use of latent class models that incorporate more comprehensive neuropsychological measures to classify cognitive impairment.

Identifying patterns of adaptation in breast cancer patients with cancer-related fatigue using response shift analyses at subgroup level

Fatigue is the most prevalent symptom in breast cancer. It might be perceived differently among patients over time as a consequence of the differing patients’ adaptation and psychological adjustment to their cancer experience which can be related to response shift (RS). RS analyses can provide important insights on patients’ adaptation to cancer but it is usually assumed that RS occurs in the same way in all individuals which is unrealistic. This study aimed to identify patients’ subgroups in which different RS effects on self‐reported fatigue could occur over time using a combination of methods for manifest and latent variables. The FATSEIN study comprised 466 breast cancer patients followed over a 2‐year period. Fatigue was measured with the Multidimensional Fatigue Inventory questionnaire (MFI‐20) during 10 visits. A novel combination of Mixed Models, Growth Mixture Modeling, and Structural Equation Modeling was used to assess the occurrence of RS in fatigue changes to identify subgroups displaying different RS patterns over time. An increase in fatigue was evidenced over the 8‐month follow‐up, followed by a decrease between the 8‐ and 24‐month. Four latent classes of patients were identified. Different RS patterns were detected in all latent classes between the inclusion and 8 months (last cycle of chemotherapy). No RS was evidenced between 8‐ and 24‐month. Several RS effects were evidenced in different groups of patients. Women seemed to adapt differently to their treatment and breast cancer experience possibly indicating differing needs for medical/psychological support.

Trajectories of cannabis use disorder: risk factors, clinical characteristics and outcomes

AIMS

To estimate cannabis use disorder (CUD) trajectory classes from ages 14 to 30 years and compare classes on clinical characteristics, risk factors and psychosocial outcomes.

DESIGN

Four waves (T1-T4) of data from an epidemiological study of psychopathology among a regionally representative sample. Trajectory classes described risk for CUD as a function of age. The number of classes was determined by model fit.

SETTING

Participants were selected randomly from nine high schools in western Oregon, USA.

PARTICIPANTS

The sample included 816 participants [age at T1 mean = 16.6, standard deviation (SD) = 1.2; 44% male; 8% non-white].

MEASUREMENTS

Participants completed diagnostic interviews, Child Trauma Questionnaire, Social Adjustment Scale and items adapted from the Wisconsin Manual for Assessing Psychotic-Like Experiences.

FINDINGS

There were three CUD trajectory classes (Lo-Mendell-Rubin likelihood ratio test < 0.001): (1) persistent increasing risk; (2) maturing out, with increasing risk then decreasing risk; and (3) stable low risk. The persistent increasing class had later initial CUD onsets (η²  = 0.16, P < 0.001) and greater cumulative CUD durations (η²  = 0.26, P < 0.001). Male sex [odds ratio (OR) = 2.57, P = 0.018], externalizing disorders between ages 24 and 30 years (OR = 2.64, P < 0.001) and psychotic experiences during early adulthood (Cohen's d = 0.44, P = 0.016) discriminated between the persistent increasing and the maturing-out classes.

CONCLUSIONS

Evidence suggests three distinguishable types of trajectory for development of cannabis use disorder starting in early teens: (1) persistent increasing risk; (2) maturing out, with increasing risk then decreasing risk; and (3) stable low risk.

The Guttman errors as a tool for response shift detection at subgroup and item levels

PURPOSE

Statistical methods for identifying response shift (RS) at the individual level could be of great practical value in interpreting change in PRO data. Guttman errors (GE) may help to identify discrepancies in respondent's answers to items compared to an expected response pattern and to identify subgroups of patients that are more likely to present response shift. This study explores the benefits of using a GE-based method for RS detection at the subgroup and item levels.

METHODS

The analysis was performed on the SatisQoL study. The number of GE was determined for each individual at each time of measurement (at baseline T0 and 6 months after discharge M6). Individuals showing discrepancies (with many GE) were suspected to interpret the items differently from the majority of the sample. Patients having a large number of GE at M6 only and not at T0 were assumed to present RS. Patients having a small number of GE at T0 and M6 were assumed to present no RS. The RespOnse Shift ALgorithm in Item response theory (ROSALI) was then applied on the whole sample and on both groups.

RESULTS

Different types of RS (non-uniform recalibration, reprioritization) were more prevalent in the group composed of patients assumed to present RS based on GE. On the opposite, no RS was detected on patients having few GE.

CONCLUSIONS

Guttman errors and item response theory models seem to be relevant tools to discriminate individuals affected by RS from the others at the item level.

Trajectories of life satisfaction after traumatic brain injury: Influence of life roles, age, cognitive disability, and depressive symptoms

OBJECTIVES

(a) Identify life satisfaction trajectories after moderate to severe traumatic brain injury (TBI); (b) establish a predictive model for these trajectories across the first 5 years postinjury; and (c) describe differences in these life satisfaction trajectory groups, focusing on age, depressive symptoms, disability, and participation in specific life roles.

RESEARCH METHOD

Analysis of the longitudinal TBI Model Systems National Database was performed on data collected prospectively at 1-, 2-, and 5-years post-TBI. Participants (n = 3,012) had a moderate to severe TBI and were 16 years old and older.

RESULTS

Four life satisfaction trajectories were identified across the first 5 years postinjury, including: stable satisfaction, initial satisfaction declining, initial dissatisfaction improving, and stable dissatisfaction. Age, depressive symptoms, cognitive disability, and life role participation as a worker, leisure participant, and/ or religious participant at 1-year postinjury significantly predicted trajectory group membership. Life role participation and depressive symptoms were strong predictors of life satisfaction trajectories across the first 5 years post-TBI.

CONCLUSIONS

The previously documented loss of life roles and prevalence of depression after a moderate to severe TBI make this a vulnerable population for whom low or declining life satisfaction is a particularly high risk. Examining individual life role participation may help to identify relevant foci for community-based rehabilitation interventions or supports.

Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling

Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.

Multivariate clustering of progression profiles reveals different depression patterns in prodromal Huntington disease

OBJECTIVE

Although Huntington disease (HD) is caused by an autosomal dominant mutation, its phenotypic presentation differs widely. Variability in clinical phenotypes of HD may reflect the existence of disease subtypes. This hypothesis was tested in prodromal participants from the longitudinal Neurobiological Predictors of Huntington Disease (PREDICT-HD) study.

METHOD

We performed clustering using longitudinal data assessing motor, cognitive, and depression symptoms. Using data from 521 participants with 2,716 data points, we fit growth mixture models (GMM) that identify groups based on multivariate trajectories.

RESULTS

In various GMM, different phases of disease progression were partitioned by progression trajectories of motor and cognitive signs, and by overall level of depression symptoms. More progressed motor signs were accompanied by more progressed cognitive signs, but not always by higher levels of depressive symptoms. In several models, there were at least 2 groups with similar trajectories for motor and cognitive signs that showed different levels for depression symptoms-one with a very low level of depression and the other with a higher level of depression.

CONCLUSIONS

Findings indicate that at least intermediate HD progression might be associated with different levels of depression. Depression is one of the few symptoms that is treatable in HD and has implications for clinical care. Identification of potential depression subtypes may also help to select appropriate patients for clinical trials.

A person-centred analysis of the time-use, daily activities and health-related quality of life of Irish school-going late adolescents

PURPOSE

The health, well-being and quality of life of the world's 1.2 billion adolescents are global priorities. A focus on their patterns or profiles of time-use and how these relate to health-related quality of life (HRQoL) may help to enhance their well-being and address the increasing burden of non-communicable diseases in adulthood. This study sought to establish whether distinct profiles of adolescent 24-h time-use exist and to examine the relationship of any identified profiles to self-reported HRQoL.

METHOD

This cross-sectional study gathered data from a random sample of 731 adolescents (response rate 52%) from 28 schools (response rate 76%) across Cork city and county. A person-centred approach, latent profile analysis, was used to examine adolescent 24-h time-use and relate the identified profiles to HRQoL.

RESULTS

Three male profiles emerged, namely productive, high leisure and all-rounder. Two female profiles, higher study/lower leisure and moderate study/higher leisure, were identified. The quantitative and qualitative differences in male and female profiles support the gendered nature of adolescent time-use. No unifying trends emerged in the analysis of probable responses in the HRQoL domains across profiles. Females in the moderate study/higher leisure group were twice as likely to have above-average global HRQoL.

CONCLUSION

Distinct time-use profiles can be identified amongst adolescents, but their relationship with HRQoL is complex. Rich mixed-method research is required to illuminate our understanding of how quantities and qualities of time-use shape lifestyle patterns and how these can enhance the HRQoL of adolescents in the twenty-first century.