Is it necessary to classify developmental trajectories over time? A critical note

Trajectories of cardiorespiratory fitness from childhood to adolescence: Findings from the QUALITY cohort

Estimate the shape and number of cardiorespiratory fitness (CRF) trajectories from childhood to adolescence; and verify whether CRF trajectory membership can be predicted by sex, biological maturation, body weight, body composition and physical activity (PA) in childhood. Data from QUALITY were used. Participants attended baseline (8-10 y old, n = 630) and follow-ups 2 years (n = 564) and 7 years (n = 359) after baseline. Group-based trajectory analysis for relative peak oxygen consumption (VO2peak, ml·kg-1·min-1) was performed. A multinomial logistic regression model was used to estimate the associations between baseline predictors and trajectory membership. Mean age of the 454 participants was 9.7 ± 0.9 years at baseline. Three distinct VO2peak trajectories were identified and all tended to decrease. They were labelled according to the starting point and slope. High-Decreasers were mostly boys, had lower body weight and fat-free mass index and higher PA levels at baseline (p < 0.05). Female sex and higher weight were associated with higher odds of being classified in the Low-Decreaser trajectory (OR = 74.03, 95%CI = 27.06-202.54; OR = 1.48, 95%CI = 1.36-1.60). Those with higher PA were less likely to be Low-Decreasers (OR = 0.96, 95%CI = 0.94-0.97). Sex, body weight and PA in childhood are important influencing factors of VO2peak (ml·kg-1·min-1) trajectories across adolescence.

Conceptualizing and Measuring Appetite Self-Regulation Phenotypes and Trajectories in Childhood: A Review of Person-Centered Strategies

This review uses person-centered research and data analysis strategies to discuss the conceptualization and measurement of appetite self-regulation (ASR) phenotypes and trajectories in childhood (from infancy to about ages 6 or 7 years). Research that is person-centered provides strategies that increase the possibilities for investigating ASR phenotypes. We first examine the utility of examining underlying phenotypes using latent profile/class analysis drawing on cross-sectional data. The use of trajectory analysis to investigate developmental change is then discussed, with attention to phenotypes using trajectories of individual behaviors as well as phenotypes based on multi-trajectory modeling. Data analysis strategies and measurement approaches from recent examples of these person-centered approaches to the conceptualization and investigation of appetite self-regulation and its development in childhood are examined. Where relevant, examples from older children as well as developmental, clinical and educational psychology are drawn on to discuss when and how person-centered approaches can be used. We argue that there is scope to incorporate recent advances in biological and psychoneurological knowledge about appetite self-regulation as well as fundamental processes in the development of general self-regulation to enhance the examination of phenotypes and their trajectories across childhood (and beyond). The discussion and conclusion suggest directions for future research and highlight the potential of person-centered approaches to progress knowledge about the development of appetite self-regulation in childhood.

Psychosocial working characteristics before retirement and depressive symptoms across the retirement transition: a longitudinal latent class analysis

Objectives Retirement is a major life transition. However, previous evidence on its mental health effects has been inconclusive. Whether retirement is desirable or not may depend on pre-retirement work characteristics. We investigated trajectories of depressive symptoms across retirement and how a number of psychosocial working characteristics influenced these trajectories. Methods We included 1735 respondents from the Swedish Longitudinal Occupational Survey of Health (SLOSH), retiring during 2008-2016 (mean retirement age 66 years). They had completed biennial questionnaires reporting job demands, decision authority, workplace social support, efforts, rewards, procedural justice and depressive symptoms. We applied group-based trajectory modelling to model trajectories of depressive symptoms across retirement. Multinomial logistic regression analyses estimated the associations between -psychosocial working characteristics and depressive symptom trajectories. Results We identified five depression trajectories. In four of them, depressive symptoms decreased slightly around retirement. In one, the symptom level was initially high, then decreased markedly across retirement. Perceptions of job demands, job strain, workplace social support, rewards, effort-reward imbalance and procedural justice were associated with the trajectories, while perceptions of decision authority and work efforts were only partly related to the trajectories. Conclusions We observed a rather positive development of depressive symptoms across retirement in a sample of Swedish retirees. For a small group with poor psychosocial working characteristics, symptoms clearly decreased, which may indicate that a relief from poor working characteristics is associated with an improvement for some retirees. However, for other retirees poor working characteristics were associated with persistent symptoms, suggesting a long-term effect of these work stressors.

Distinct trajectories of physical activity and related factors during the life course in the general population: a systematic review

BACKGROUND

In recent years, researchers have begun applying a trajectory approach to identify homogeneous subgroups of physical activity (PA) in heterogeneous populations. This study systematically reviewed the articles identifying longitudinal PA trajectory classes and the related factors (e.g., determinants, predictors, and outcomes) in the general population during different life phases.

METHODS

The included studies used finite mixture models for identifying trajectories of PA, exercise, or sport participation. Three electronic databases, PubMed (Medline), Web of Science, and CINAHL, were searched from the year 2000 to 13 February 2018. The study was conducted according to the PRISMA recommendations.

RESULTS

Twenty-seven articles were included and organized into three age group: youngest (eleven articles), middle (eight articles), and oldest (eight articles). The youngest group consisted mainly of youth, the middle group of adults and the oldest group of late middle-aged and older adults. Most commonly, three or four trajectory classes were reported. Several trajectories describing a decline in PA were reported, especially in the youngest group, whereas trajectories of consistently increasing PA were observed in the middle and oldest group. While the proportion of persistently physically inactive individuals increased with age, the proportion was relatively high at all ages. Generally, male gender, being Caucasian, non-smoking, having low television viewing time, higher socioeconomic status, no chronic illnesses, and family support for PA were associated either with persistent or increasing PA.

CONCLUSIONS

The reviewed articles identified various PA subgroups, indicating that finite mixture modeling can yield new information on the complexity of PA behavior compared to studying population mean PA level only. The studies also provided novel information how different factors relate to changes in PA during life course. The recognition of the PA subgroups and their determinants is important for the more precise targeting of PA promotion and PA interventions.

TRIAL REGISTRATION

PROSPERO registration number: CRD42018088120 .

The 2-year course of Medically Unexplained Physical Symptoms (MUPS) in terms of symptom severity and functional status: results of the PROSPECTS cohort study

OBJECTIVE

We assessed the 2-year course of Medically Unexplained Physical Symptoms (MUPS) in terms of symptom severity, physical functioning and mental functioning.

METHODS

We used data of the PROSPECTS cohort study, consisting of 325 MUPS patients from several health care settings. Symptom severity (PHQ-15), physical functioning (RAND 36 PCS) and mental functioning (RAND 36 MCS) were assessed at baseline and 6, 12 and 24 months afterwards. We used Latent Class Growth Modeling (LCGM) to identify different course types, but as clinical usability of results was limited, we also analysed change scores and directions of change.

RESULTS

LCGM identified three course trajectories for all outcomes: a "stable severe", a "stable moderate" and an "improvement" trajectory. The greater majority of participants was assigned to the stable trajectories. However, we found high levels of within-trajectory heterogeneity. Based on total change scores (using only two measurement moments), physical symptoms of 27% of the participants deteriorated, while 63% improved. Based on Minimal Clinically Important Differences these proportions were 5% and 24%. Analyses of directions of change (using all measurement moments) showed that for all outcomes almost 80% reported a fluctuating course type, with clinically important fluctuations in 35-61% of participants.

CONCLUSION

Fluctuations in the course of MUPS were highly prevalent, but as fluctuations showed high interpersonal heterogeneity, these were not detected by LCGM. Improvement and deterioration rates based on change scores are in line with literature. However, based on the highly prevalent fluctuations, we conclude that temporal stability of these outcomes is limited.

Trajectories of job demands and control: risk for subsequent symptoms of major depression in the nationally representative Swedish Longitudinal Occupational Survey of Health (SLOSH)

Purpose

Depression is a global health concern. High job demands, low job control, and the combination (high strain) are associated with depression. However, few longitudinal studies have investigated changed or repeated exposure to demands and control related to depression. We investigated how trajectories of exposure to job demands and control jointly influence subsequent depression.

Methods

We included 7949 subjects from the Swedish Longitudinal Occupational Survey of Health, who completed questionnaires of perceived job demands and control, and depressive symptoms from 2006 to 2014. None of them were depressed between 2006 and 2012. Univariate and joint group-based trajectory models identified groups with similar development of demands and control across 2006–2012. Logistic regression estimated the risk for symptoms of major depression in 2014 according to joint trajectory groups.

Results

The joint trajectory model included seven groups, all with fairly stable levels of demands and control over time. Subjects in the high strain and active (high demands and high control) trajectories were significantly more likely to have subsequent major depressive symptoms compared to those having low strain, controlling for demographic covariates (OR 2.15; 95% Cl 1.24–3.74 and OR 2.04; 95% CI 1.23–3.40, respectively). The associations did not remain statistically significant after adjusting for previous depressive symptoms in addition to demographic covariates.

Conclusions

The results indicate that the levels of job demands and control were relatively unchanged across 6 years and suggest that long-term exposure to a high strain or active job may be associated with increased risk for subsequent depression.

Electronic supplementary material

The online version of this article (doi:10.1007/s00420-017-1277-0) contains supplementary material, which is available to authorized users.

Importance of characterizing growth trajectories

In the era of the obesity epidemic in children, characterizing childhood growth trajectories (weight, length/height, or body mass index/weight for length) is becoming essential for surveillance. Clinicians routinely use growth curves to identify abnormal growth trajectories. Clinical epidemiologists are interested in both the determinants of growth and the consequences of certain patterns of growth on later health and diseases. Characterizing growth trajectories is also helpful to predict future growth based on past growth and might be useful in the future to compare the impact of various interventions.