ArticleFrontiers in epidemiology2023
Attrition in the Gothenburg H70 birth cohort studies, an 18-year follow-up of the 1930 cohort.
Article in Frontiers in epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Pooled it
- Polygenic risk scores for atrial fibrillation and heart failure and the risk of stroke and dementia.Brain communications · 2025Article
- Cumulative blood pressure load and cognitive decline in older adults: An observational analysis of two large cohorts.Cerebral circulation - cognition and behavior · 2025Article
- Sociodemographic characteristics and predictive factors of attrition: comparison in two final waves of a birth cohort study in Ecuador.Frontiers in reproductive health · 2025Article
- Online46: Online cognitive assessments in elderly cohorts-The British 1946 birth cohort case study.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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Authors and funding
20 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Longitudinal studies are essential to understand the ageing process, and risk factors and consequences for disorders, but attrition may cause selection bias and impact generalizability. We describe the 1930 cohort of the Gothenburg H70 Birth Cohort Studies, followed from age 70 to 88, and compare baseline characteristics for those who continue participation with those who die, refuse, and drop out for any reason during follow-up. Methods: A population-based sample born 1930 was examined with comprehensive assessments at age 70 ( Results: Refusal to participate in subsequent examinations was related to lower educational level, higher blood pressure, and lower scores on cognitive tests. Both attrition due to death and total attrition were associated with male sex, lower educational level, smoking, ADL dependency, several diseases, poorer lung function, slower gait speed, lower scores on cognitive tests, depressive symptoms, and a larger number of medications. Attrition due to death was also associated with not having a partner. Conclusions: It is important to consider different types of attrition when interpreting results from longitudinal studies, as representativeness and results may be differently affected by different types of attrition. Besides reducing barriers to participation, methods such as imputation and weighted analyses can be used to handle selection bias.
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