ArticleAmerican journal of epidemiology2021
Combining Longitudinal Data From Different Cohorts to Examine the Life-Course Trajectory.
Article in American journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- "We adjusted for race": now what? A systematic review of utilization and reporting of race in American Journal of Epidemiology and Epidemiology, 2020-2021.Epidemiologic reviews · 2023Pooled it
- Long-term cardiometabolic health in people born after assisted reproductive technology: a multi-cohort analysis.European heart journal · 2023Pooled it
- Statistical methods for retrospective harmonization of longitudinal epidemiological data: a scoping review.European journal of epidemiology · 2026Article
- Income Volatility During Early to Mid-adulthood and 10-year Memory Decline in a Longitudinal Synthetic Cohort.Epidemiology (Cambridge, Mass.) · 2026Article
- Gaps in Population Life Course Phenotype Trajectories Underlying Major Noncommunicable Diseases: A Scoping Review.International journal of population data science · 2026Article
- Longitudinal Examination of Loneliness and Smoking in Adolescents and Young Adults: A Multiple Dataset Study.International journal of mental health and addiction · 2026Article
- Article
- A scoping review of adult NCD-relevant phenotypes measured in today's large child cohort studies.Pediatric research · 2025Article
- An Introduction to Longitudinal Synthetic Cohorts for Studying the Life Course Drivers of Health Outcomes and Inequalities in Older Age.Current epidemiology reports · 2025Article
- Key research priorities in methodological approaches for measuring the exposome and studying its role in the development of dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Causal inference in multi-cohort studies using the target trial framework to identify and minimize sources of bias.American journal of epidemiology · 2025Article
- The relationship of changes in insulin demand and insulin adequacy over the life course.Diabetologia · 2025Article
- Overcoming Data Gaps in Life Course Epidemiology by Matching Across Cohorts.Epidemiology (Cambridge, Mass.) · 2024Article
- Associations of Maternal Educational Level, Proximity to Green Space During Pregnancy, and Gestational Diabetes With Body Mass Index From Infancy to Early Adulthood: A Proof-of-Concept Federated Analysis in 18 Birth Cohorts.American journal of epidemiology · 2024Article
- A General Primer for Data Harmonization.Scientific data · 2024Article
- REPRO_PL-Polish Mother and Child Cohort-Exposure, Health Status, and Neurobehavioral Assessments in Adolescents-Design and Cohort Update.International journal of environmental research and public health · 2022Article
- Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies.BMC medical research methodology · 2022Article
- LongITools: Dynamic longitudinal exposome trajectories in cardiovascular and metabolic noncommunicable diseases.Environmental epidemiology (Philadelphia, Pa.) · 2022Article
- Trajectory of body mass index and height changes from childhood to adolescence: a nationwide birth cohort in Japan.Scientific reports · 2021Article
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3 authors.
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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.
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