Dataset Information

Combining Longitudinal Data From Different Cohorts to Examine the Life-Course Trajectory.

ABSTRACT: Longitudinal data are necessary to reveal changes within an individual as he or she ages. However, rarely will a single cohort study capture data throughout a person's entire life span. Here we describe in detail the steps needed to develop life-course trajectories from cohort studies that cover different and overlapping periods of life. Such independent studies are probably from heterogenous populations, which raises several challenges, including: 1) data harmonization (deriving new harmonized variables from differently measured variables by identifying common elements across all studies); 2) systematically missing data (variables not measured are missing for all participants in a cohort); and 3) model selection with differing age ranges and measurement schedules. We illustrate how to overcome these challenges using an example which examines the associations of parental education, sex, and race/ethnicity with children's weight trajectories. Data were obtained from 5 prospective cohort studies (carried out in Belarus and 4 regions of the United Kingdom) spanning data collected from birth to early adulthood during differing calendar periods (1936-1964, 1972-1979, 1990-2012, 1996-2016, and 2007-2015). Key strengths of our approach include modeling of trajectories over wide age ranges, sharing of information across studies, and direct comparison of the same parts of the life course in different geographical regions and time periods. We also introduce a novel approach of imputing individual-level covariates of a multilevel model with a nonlinear growth trajectory and interactions.

SUBMITTER: Hughes RA

PROVIDER: S-EPMC8634562 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Combining Longitudinal Data From Different Cohorts to Examine the Life-Course Trajectory.

Hughes Rachael A RA Tilling Kate K Lawlor Deborah A DA

American journal of epidemiology 20211201 12

Longitudinal data are necessary to reveal changes within an individual as he or she ages. However, rarely will a single cohort study capture data throughout a person's entire life span. Here we describe in detail the steps needed to develop life-course trajectories from cohort studies that cover different and overlapping periods of life. Such independent studies are probably from heterogenous populations, which raises several challenges, including: 1) data harmonization (deriving new harmonized ...[more]

PMID: 34215868

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Project description:BackgroundMost research on prescription drug misuse (PDM) focuses on the misuse of specific classes of psychoactive prescription drugs among adolescents or young adults. The current research addressed important gaps in the literature by assessing poly-prescription drug misuse (poly-PDM), the misuse of more than one class of psychoactive prescription drug, across different adult age cohorts.MethodsWe used the 2015-2018 National Survey on Drug Use and Health to examine the prevalence of past-year poly-PDM and specific combinations of PDM. Multinomial logistic regression was used to identify demographic, health-related factors, and substance use behaviors that were significantly associated with poly-PDM.ResultsThe prevalence of poly-PDM decreases with age and is common among individuals who engage in PDM. Slightly more than one in four respondents in age cohorts 18-25 (31.66%, 95% CI = 30.35, 33.00) and 26-34 (29.92%, 95% CI = 25.82, 30.12) who engage in PDM, misused more than one class of prescription drug. Additionally, poly-PDM was identified as a high-risk type of PDM as roughly 60% of adults younger than 65 who endorse poly-PDM reported having a substance use disorder (SUD). While certain characteristics (i.e., race/ethnicity, marital status, depression, suicidal ideation, illegal drug use, and SUD) were consistently associated with poly-PDM across age cohorts, other characteristics (i.e., sexual identity, income, and justice involvement) varied across age cohorts. Finally, a comparison of poly-PDM to single PDM showed, in all age cohorts, that having an SUD was associated with an increased likelihood of poly-PDM, while Black adults were less likely than whites to report poly-PDM.ConclusionsBy identifying prevalence and correlates of poly-PDM across adult age cohorts, the current research has significant implications. Understanding stability and heterogeneity in the characteristics associated with poly-PDM should inform interventions, identify at-risk groups, and shape public health approaches to dealing with high-risk substance use behavior.

Dataset Information

Combining Longitudinal Data From Different Cohorts to Examine the Life-Course Trajectory.

Publications

Combining Longitudinal Data From Different Cohorts to Examine the Life-Course Trajectory.

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