Does attrition affect estimates of association: A longitudinal study

J Psychiatr Res. 2019 Mar:110:127-142. doi: 10.1016/j.jpsychires.2018.12.022. Epub 2018 Dec 24.

Abstract

Survey research frequently involves missing cases attributable to refusals to participate, lack of success in accessing all potential respondents or loss to follow-up in longitudinal studies. There is concern that those not recruited or those lost are a select group whose absence from a study may bias the findings of the study. This study provides a test of the extent to which selective loss to follow-up in a longitudinal study may lead to biased findings. The Mater-University Study of Pregnancy collected baseline information for 7718 pregnant women. Follow-ups occurred five years, 14 years, 21 years and 27 years after the birth, for 6753 eligible women. Participants at baseline were partitioned according to follow-up status for each follow-up. We compare baseline (at recruitment) measures of association, with these same measures of association for those retained in the study (Group A) and those lost to follow-up (Group B) at each phase of data. Using univariate logistic regression we compared the strength of association between maternal mental health and various baseline socio-demographic factors for different rates of loss to follow-up. Estimates of association at baseline, and at each follow-up are similar irrespective of the rate of loss to follow-up and whether the comparison is with those retained in the study or those lost to follow-up. There were no statistically significant differences in 90.8% of baseline comparisons with Group A, and 96.9% of comparisons with Group B measures of association. We conclude that differential loss to follow-up rarely affects estimates of association. We suggest that loss to follow-up may produce misleading findings only in circumstances where loss to follow-up is combined with a number of other sources of bias.

Keywords: Disadvantage; Loss to follow-up; Magnitude of bias; Mental disorder; Socio-economic.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Data Interpretation, Statistical*
  • Female
  • Health Status*
  • Humans
  • Longitudinal Studies*
  • Lost to Follow-Up*
  • Mental Disorders / epidemiology
  • Middle Aged
  • Outcome Assessment, Health Care / standards*
  • Pregnancy
  • Pregnancy, Unplanned
  • Risk Factors
  • Smoking / epidemiology
  • Socioeconomic Factors
  • Young Adult