Ten frequently asked questions about latent transition analysis.

Nylund‐Gibson, Karen; Garber, Adam C; Carter, Delwin; Chan, Meiki; Arch, Dina A N; Simon, Odelia; Whaling, Kelly; Tartt, Erica; Lawrie, Smaranda Ioana

doi:10.1037/met0000486

Cited by 61 publications

(35 citation statements)

References 70 publications

(124 reference statements)

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“…We used latent transition analysis (LTA) to extract common sleep health phenotypes over time. LTA extends cross-sectional clustering techniques like latent class analysis to a longitudinal context (37). Latent class analysis explores how multiple dimensions of sleep health co-occur within a person and, as a result, potential subgroups within an overall population (i.e., sleep health phenotypes indicated by common within-person patterns of sleep health dimensions), whereas LTA additionally describes how a person’s membership to a subgroup may be stable or change over time.…”

Section: Methodsmentioning

confidence: 99%

10-year Stability of an Insomnia Sleeper Phenotype and Its Association with Chronic Conditions

Lee,

Smith,

Wallace

et al. 2024

Psychosom Med

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Objective To identify distinct sleep health phenotypes in adults, examine transitions in sleep health phenotypes over time and subsequently relate these to the risk of chronic conditions. Methods A national sample of adults from the Midlife in the United States study (N = 3,683) provided longitudinal data with two timepoints (T1:2004-2006, T2:2013-2017). Participants self-reported on sleep health (regularity, satisfaction, alertness, efficiency, duration) and the number and type of chronic conditions. Covariates included age, sex, race, education, education, partnered status, number of children, work status, smoking, alcohol, and physical activity. Results Latent transition analysis identified four sleep health phenotypes across both timepoints: good sleepers, insomnia sleepers, weekend catch-up sleepers, and nappers. Between T1 to T2, the majority (77%) maintained their phenotype, with the nappers and insomnia sleepers being the most stable. In fully adjusted models with good sleepers at both timepoints as the reference, being an insomnia sleeper at either timepoint was related to having an increased number of total chronic conditions by 28-81% at T2, adjusting for T1 conditions. Insomnia sleepers at both timepoints were at 72-188% higher risk for cardiovascular disease, diabetes, depression, and frailty. Being a napper at any timepoint related to increased risks for diabetes, cancer, and frailty. Being a weekend catch-up sleeper was not associated with chronic conditions. Those with lower education and unemployed were more likely to be insomnia sleepers; older adults and retirees were more likely to be nappers. Conclusion Findings indicate heightened risk of chronic conditions involved in suboptimal sleep health phenotypes, mainly insomnia sleepers.

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Section: Methodsmentioning

confidence: 99%

10-year Stability of an Insomnia Sleeper Phenotype and Its Association with Chronic Conditions

Lee,

Smith,

Wallace

et al. 2024

Psychosom Med

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“…Latent class analysis (LCA), 6 a classical modelling approach for discrete data developed more than 70 years ago by Lazarsfeld, 7 has been applied to identify a set of discrete, mutually exclusive latent (i.e., unobserved) classes representing exposure profiles based on the observed pattern of a set of 23 dichotomous variables representing occupational exposures (see Table 1). Variables representing occupational tasks were included in two versions: one, if gloves were worn regularly when the task is executed, two, if this was not the case—except for application of deep conditioner where generally no gloves are worn.…”

Section: Methodsmentioning

confidence: 99%

Aetiology of occupational hand eczema in hairdressers: Tackling the complexity of exposure combinations to identify patterns associated with increased risk of hand eczema

et al. 2022

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Introduction: Hairdressers are exposed to wet work and manifold allergens at work, rendering exposure complex and the aetiology of occupational hand eczema (OHE) often multifactorial in this occupational group. Objectives: To identify exposure patterns associated with increased risk of hand eczema in hairdressers. Methods: All hairdressers graduating from 2004 to 2007 and 2015 to 2018 received a questionnaire in 2009 and 2020, respectively. Current exposures (with or without regular glove use) and OHE were self-reported, and their association examined. Patterns of exposure were identified by latent class analysis (LCA).Results: A total response of 39.9% (668/1675) was obtained. Six exposure profiles (#1-6) were identified by LCA across 11 tasks performed with or without gloves as well as deep conditioning, that is, 23 task items. Compared to profile #1 with the lowest OHE risk (reference) an increased risk of current OHE were seen in profile #4[adjusted odds ratio [aOR] 6.5, 95% confidence interval [CI] 1. ] in logistic regression analysis. Profile #1 and #6 had performed the same tasks, but in profile #6 regular glove use was performed in 9.1%(1/ 11) of tasks compared to 72.7% (8/11) of tasks in profile #1 (p = 0.002). Conclusion:Although occupational exposures in hairdressing are complex, meaningful patterns associated with a wide range of OHE risk can be identified by LCA. The increase of OHE risk seems predominantly to be due to poor compliance with protective gloves. LCA could be applied to further fields of complex (skin) exposures.

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“…While we are interested in how adversity changes over time, and therefore expect the construct of adversity to be noninvariant over time by design, using an RI-LTA model could address some concerns about measurement noninvariance by accounting for between-individual variation in response probabilities for a given latent class indicator. Furthermore, recent work has indicated that longitudinal measurement invariance is not required for LTA models unless the assumption (or imposition) is that latent classes will be similar over time (Nylund-Gibson et al, 2023).…”

Section: Current Studymentioning

confidence: 99%

Longitudinal patterns of adversity from childhood to adolescence: Examining associations with mental health through emerging adulthood using a random-intercept latent transition analysis.

Raghunathan,

Johnson,

Voegtline

et al. 2024

Developmental Psychology

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Childhood adversity can have detrimental impacts on life course mental and physical health. Timing, nature, severity, and chronicity of adversity are thought to explain much of the variability in health and developmental outcomes among exposed individuals. The current study seeks to characterize heterogeneity in adverse experiences over time at the individual, family, and neighborhood domains in a cohort of predominantly Black children (85% Black and 15% White, 46.2% girls, 67.2% free/reduced lunch in first grade), and to examine associations with mental health from sixth grade to age 26. Participants were part of a randomized universal preventive interventions trial in first grade with prospective follow-up through early adulthood. Separate models characterized heterogeneity in adversity in elementary, middle, and high schools. Changes in adversity over time and relationships with mental health (anxiety, depression, suicidal behaviors) were investigated using a random-intercept latent transition analysis (RI-LTA). We identified three-class solutions in early childhood, middle school, and high school. Generally, both a higher and a lower poly-adversity class were observed at each time point, with varying nature of adversity characterized by the third class. RI-LTA indicated prevalent within-individual changes in adverse exposure over time and differential associations with mental health and suicidal behaviors. Results suggest that treating adverse exposures as a static construct may limit the ability to characterize salient variation over time. Identifying complexity in adverse experiences and their relation to health and well-being is key for developing and implementing effective prevention and early intervention efforts to mitigate negative effects through the life course. Public Significance StatementChildren are exposed to changing forms of adversity across development with differential impacts on mental health. Focusing on repeated, adaptive, coordinated, and multilevel preventive mental health efforts will be crucial to support the well-being of children and adolescents throughout the life course.

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Ten frequently asked questions about latent transition analysis.

Cited by 61 publications

References 70 publications

10-year Stability of an Insomnia Sleeper Phenotype and Its Association with Chronic Conditions

10-year Stability of an Insomnia Sleeper Phenotype and Its Association with Chronic Conditions

Aetiology of occupational hand eczema in hairdressers: Tackling the complexity of exposure combinations to identify patterns associated with increased risk of hand eczema

Longitudinal patterns of adversity from childhood to adolescence: Examining associations with mental health through emerging adulthood using a random-intercept latent transition analysis.

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