Impact of participant attrition on child injury outcome estimates: a longitudinal birth cohort study in Australia

doi:10.1136/bmjopen-2016-015584

. 2017 Jun 30;7(6):e015584.

doi: 10.1136/bmjopen-2016-015584.

Impact of participant attrition on child injury outcome estimates: a longitudinal birth cohort study in Australia

Cate M Cameron¹, Jodie M Osborne¹, Anneliese B Spinks², Tamzyn M Davey³, Neil Sipe⁴, Roderick J McClure⁵

Affiliations

¹ The Hopkins Centre, Menzies Health Institute Queensland, Griffith University, Meadowbrook, Queensland, Australia.
² Commonwealth Scientific and Industrial Research Organisation (CSIRO), Dutton Park, Brisbane, Queensland, Australia.
³ School of Public Health, The University of Queensland, Herston, Brisbane, Queensland, Australia.
⁴ School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, Queensland, Australia.
⁵ Harvard Injury Control Research Center, Harvard School of Public Health, Boston, Massachusetts, USA.

PMID: 28667218
PMCID: PMC5734245
DOI: 10.1136/bmjopen-2016-015584

Impact of participant attrition on child injury outcome estimates: a longitudinal birth cohort study in Australia

Cate M Cameron et al. BMJ Open. 2017.

. 2017 Jun 30;7(6):e015584.

doi: 10.1136/bmjopen-2016-015584.

Authors

Cate M Cameron¹, Jodie M Osborne¹, Anneliese B Spinks², Tamzyn M Davey³, Neil Sipe⁴, Roderick J McClure⁵

Affiliations

¹ The Hopkins Centre, Menzies Health Institute Queensland, Griffith University, Meadowbrook, Queensland, Australia.
² Commonwealth Scientific and Industrial Research Organisation (CSIRO), Dutton Park, Brisbane, Queensland, Australia.
³ School of Public Health, The University of Queensland, Herston, Brisbane, Queensland, Australia.
⁴ School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, Queensland, Australia.
⁵ Harvard Injury Control Research Center, Harvard School of Public Health, Boston, Massachusetts, USA.

PMID: 28667218
PMCID: PMC5734245
DOI: 10.1136/bmjopen-2016-015584

Abstract

Background: Longitudinal research is subject to participant attrition. Systemic differences between retained participants and those lost to attrition potentially bias prevalence of outcomes, as well as exposure-outcome associations. This study examines the impact of attrition on the prevalence of child injury outcomes and the association between sociodemographic factors and child injury.

Methods: Participants were recruited as part of the Environments for Healthy Living (EFHL) birth cohort study. Baseline data were drawn from maternal surveys. Child injury outcome data were extracted from hospital records, 2006-2013. Participant attrition status was assessed up to 2014. Rates of injury-related episodes of care were calculated, taking into account exposure time and Poisson regression was performed to estimate exposure-outcome associations.

Results: Of the 2222 participating families, 799 families (36.0%) had complete follow-up data. Those with incomplete data included 137 (6.2%) who withdrew, 308 (13.8%) were lost to follow-up and 978 families (44.0%) who were partial/non-responders. Families of lower socioeconomic status were less likely to have complete follow-up data (p<0.05). Systematic differences in attrition did not result in differential child injury outcomes or significant differences between the attrition and non-attrition groups in risk factor effect estimates. Participants who withdrew were the only group to demonstrate differences in child injury outcomes.

Conclusion: This research suggests that even with considerable attrition, if the proportion of participants who withdraw is minimal, overall attrition is unlikely to affect the population prevalence estimate of child injury or measures of association between sociodemographic factors and child injury.

Keywords: Attrition; child injury; data linkage; epidemiology; longitudinal research; methods.

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Conflict of interest statement

Competing interests: None declared.

Figures

**Figure 1**
Flow diagram of Environments for Healthy Living cohort attrition status, Queensland participants 2006–2010 (n=2222 households and n=2245 children).

See this image and copyright information in PMC

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References

1. Western M, Haynes M, Baffour B, et al. ; The case for a New Australian Birth Cohort Study: institute for Social Science Research, University of Queensland, 2015.
1. Ahern K, Le Brocque R. Methodological Issues in the effects of Attrition: simple Solutions for Social scientists. Field methods 2005;17:53–69. 10.1177/1525822X04271006 - DOI
1. Wolke D, Waylen A, Samara M, et al. . Selective drop-out in longitudinal studies and non-biased prediction of behaviour disorders. Br J Psychiatry 2009;195:249–56. 10.1192/bjp.bp.108.053751 - DOI - PMC - PubMed
1. Osler M, Kriegbaum M, Christensen U, et al. . Loss to follow up did not Bias associations between early life factors and adult depression. J Clin Epidemiol 2008;61:958–63. 10.1016/j.jclinepi.2007.11.005 - DOI - PubMed
1. Greene N, Greenland S, Olsen J, et al. . Estimating Bias from loss to follow-up in the Danish National Birth Cohort. Epidemiology 2011;22:1–22. 10.1097/EDE.0b013e31822939fd - DOI - PubMed

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[1] Western M, Haynes M, Baffour B, et al. ; The case for a New Australian Birth Cohort Study: institute for Social Science Research, University of Queensland, 2015.

[2] Western M, Haynes M, Baffour B, et al. ; The case for a New Australian Birth Cohort Study: institute for Social Science Research, University of Queensland, 2015.

[3] Ahern K, Le Brocque R. Methodological Issues in the effects of Attrition: simple Solutions for Social scientists. Field methods 2005;17:53–69. 10.1177/1525822X04271006 - DOI

[4] Ahern K, Le Brocque R. Methodological Issues in the effects of Attrition: simple Solutions for Social scientists. Field methods 2005;17:53–69. 10.1177/1525822X04271006 - DOI

[5] Wolke D, Waylen A, Samara M, et al. . Selective drop-out in longitudinal studies and non-biased prediction of behaviour disorders. Br J Psychiatry 2009;195:249–56. 10.1192/bjp.bp.108.053751 - DOI - PMC - PubMed

[6] Wolke D, Waylen A, Samara M, et al. . Selective drop-out in longitudinal studies and non-biased prediction of behaviour disorders. Br J Psychiatry 2009;195:249–56. 10.1192/bjp.bp.108.053751 - DOI - PMC - PubMed

[7] Osler M, Kriegbaum M, Christensen U, et al. . Loss to follow up did not Bias associations between early life factors and adult depression. J Clin Epidemiol 2008;61:958–63. 10.1016/j.jclinepi.2007.11.005 - DOI - PubMed

[8] Osler M, Kriegbaum M, Christensen U, et al. . Loss to follow up did not Bias associations between early life factors and adult depression. J Clin Epidemiol 2008;61:958–63. 10.1016/j.jclinepi.2007.11.005 - DOI - PubMed

[9] Greene N, Greenland S, Olsen J, et al. . Estimating Bias from loss to follow-up in the Danish National Birth Cohort. Epidemiology 2011;22:1–22. 10.1097/EDE.0b013e31822939fd - DOI - PubMed

[10] Greene N, Greenland S, Olsen J, et al. . Estimating Bias from loss to follow-up in the Danish National Birth Cohort. Epidemiology 2011;22:1–22. 10.1097/EDE.0b013e31822939fd - DOI - PubMed

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Impact of participant attrition on child injury outcome estimates: a longitudinal birth cohort study in Australia

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Impact of participant attrition on child injury outcome estimates: a longitudinal birth cohort study in Australia

Authors

Affiliations

Abstract

Conflict of interest statement

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Associated data

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