ArticlePloS one2017
Life course epidemiology: Modeling educational attainment with administrative data.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Child Health Research Using linked Multi-domain Canadian Administrative Data: A Scoping Review.International journal of population data science · 2026Article
- Profiling Vulnerability in Youth and Predicting Educational Attainment in Young Adulthood.Journal of adolescence · 2026Article
- Capturing the diversity of working age life-courses: A European perspective on cohorts born before 1945.PloS one · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding the processes across childhood and adolescence that affect later life inequalities depends on many variables for a large number of individuals measured over substantial time periods. Linkable administrative data were used to generate birth cohorts and to study pathways of inequity in childhood and early adolescence leading to differences in educational attainment. Advantages and disadvantages of using large administrative data bases for such research were highlighted.
methodsChildren born in Manitoba, Canada between 1982 and 1995 were followed until age 19 (N = 89,763), with many time-invariant measures serving as controls. Five time-varying predictors of high school graduation-three social and two health-were modelled using logistic regression and a framework for examining predictors across the life course. For each time-varying predictor, six temporal patterns were tested: full, accumulation of risk, sensitive period, and three critical period models.
resultsPredictors measured in early adolescence generated the highest odds ratios, suggesting the importance of adolescence. Full models provided the best fit for the three time-varying social measures. Residence in a low-income neighborhood was a particularly influential predictor of not graduating from high school. The transmission of risk across developmental periods was also highlighted; exposure in one period had significant implications for subsequent life stages.
conclusionThis study advances life course epidemiology, using administrative data to clarify the relationships among several measures of social behavior, cognitive development, and health. Analyses of temporal patterns can be useful in studying such other outcomes as educational achievement, teen pregnancy, and workforce participation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.