AUTHOR=Rydén Lina , Wetterberg Hanna , Ahlner Felicia , Falk Erhag Hanna , Gudmundsson Pia , Guo Xinxin , Joas Erik , Johansson Lena , Kern Silke , Mellqvist Fässberg Madeleine , Najar Jenna , Ribbe Mats , Rydberg Sterner Therese , Sacuiu Simona , Samuelsson Jessica , Sigström Robert , Skoog Johan , Waern Margda , Zettergren Anna , Skoog Ingmar TITLE=Attrition in the Gothenburg H70 birth cohort studies, an 18-year follow-up of the 1930 cohort JOURNAL=Frontiers in Epidemiology VOLUME=3 YEAR=2023 URL=https://www.frontiersin.org/journals/epidemiology/articles/10.3389/fepid.2023.1151519 DOI=10.3389/fepid.2023.1151519 ISSN=2674-1199 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 (N = 524). The sample was followed up and extended to increase sample size at age 75 (N = 767). Subsequent follow-ups were conducted at ages 79, 85, and 88. Logistic regression was used to analyze baseline characteristics in relation to participation status at follow-up.

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.