Frontiers in Epidemiology (May 2023)

Attrition in the Gothenburg H70 birth cohort studies, an 18-year follow-up of the 1930 cohort

  • Lina Rydén,
  • Lina Rydén,
  • Hanna Wetterberg,
  • Hanna Wetterberg,
  • Felicia Ahlner,
  • Felicia Ahlner,
  • Hanna Falk Erhag,
  • Hanna Falk Erhag,
  • Pia Gudmundsson,
  • Pia Gudmundsson,
  • Xinxin Guo,
  • Xinxin Guo,
  • Xinxin Guo,
  • Erik Joas,
  • Erik Joas,
  • Lena Johansson,
  • Lena Johansson,
  • Silke Kern,
  • Silke Kern,
  • Silke Kern,
  • Madeleine Mellqvist Fässberg,
  • Madeleine Mellqvist Fässberg,
  • Jenna Najar,
  • Jenna Najar,
  • Jenna Najar,
  • Mats Ribbe,
  • Mats Ribbe,
  • Therese Rydberg Sterner,
  • Therese Rydberg Sterner,
  • Therese Rydberg Sterner,
  • Simona Sacuiu,
  • Simona Sacuiu,
  • Simona Sacuiu,
  • Jessica Samuelsson,
  • Jessica Samuelsson,
  • Robert Sigström,
  • Robert Sigström,
  • Robert Sigström,
  • Johan Skoog,
  • Johan Skoog,
  • Margda Waern,
  • Margda Waern,
  • Margda Waern,
  • Anna Zettergren,
  • Anna Zettergren,
  • Ingmar Skoog,
  • Ingmar Skoog,
  • Ingmar Skoog

DOI
https://doi.org/10.3389/fepid.2023.1151519
Journal volume & issue
Vol. 3

Abstract

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BackgroundLongitudinal 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.MethodsA 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.ResultsRefusal 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.ConclusionsIt 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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