Background and Aims: Potential bias because of attrition has received little attention in primary studies
on back pain. This study aims to identify those back pain related indicators most
susceptible to bias and to discuss practical consequences for back pain research.
Methods: Analyses were based on a population-based longitudinal multi-centre postal back pain
survey with two postal follow-up measurements within two years. The baseline sample
comprised 9,263 subjects. Different sets of measures at entry were used to predict
subsequent attrition: Socio-demographic variables, indicators of back pain, health
related measures, and response behaviour. Back pain related indicators comprised prevalence
estimates, pain intensity, disability, and radiating pain. Weighted and unweighted
back pain outcomes were compared at the first and second follow-up to assess bias.
Results: Little more than half of the eligible participants at baseline continued participation
till the second follow-up. Age and prior response behaviour were the best predictors
of attrition while health and back pain related variables were less important. Differences
between weighted and unweighted estimates of back pain related indicators were small
to negligible. Against our expectations, the reported back pain burden slightly declined
over time. Conclusion: Differenzial attrition over the different measurement points consecutively reduces
the representativeness of the sample. Despite this, bias due to attrition has a small
effect on the point estimates of most back pain related outcomes.
