April 2009
Volume 50, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2009
Identification of Direct and Indirect Pathways From Visual Impairment to Mortality Using Structural Equation Modelling: The Blue Mountains Eye Study
Author Affiliations & Notes
  • M. J. Karpa
    Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute,
    University of Sydney, Sydney, Australia
  • K. Beath
    Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute,
    University of Sydney, Sydney, Australia
  • E. Rochtchina
    Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute,
    University of Sydney, Sydney, Australia
  • R. G. Cumming
    School of Public Health,
    University of Sydney, Sydney, Australia
  • P. Mitchell
    Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute,
    University of Sydney, Sydney, Australia
  • J. J. Wang
    Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute,
    University of Sydney, Sydney, Australia
    Centre for Eye Research Australia, University of Melbourne, Melbourne, Australia
  • Blue Mountains Eye Study
    University of Sydney, Sydney, Australia
  • Footnotes
    Commercial Relationships  M.J. Karpa, None; K. Beath, None; E. Rochtchina, None; R.G. Cumming, None; P. Mitchell, None; J.J. Wang, None.
  • Footnotes
    Support  Australian NHMRC grant nos 974159 and 211069
Investigative Ophthalmology & Visual Science April 2009, Vol.50, 5213. doi:https://doi.org/
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      M. J. Karpa, K. Beath, E. Rochtchina, R. G. Cumming, P. Mitchell, J. J. Wang, Blue Mountains Eye Study; Identification of Direct and Indirect Pathways From Visual Impairment to Mortality Using Structural Equation Modelling: The Blue Mountains Eye Study. Invest. Ophthalmol. Vis. Sci. 2009;50(13):5213. doi: https://doi.org/.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : Visual impairment has been found in many studies to independently predict mortality, after adjusting for confounding factors. It is unclear whether these "confounders" are intermediate variables lying on the pathway from visual impairment to mortality, adjustment for which may underestimate the overall impact of visual impairment on mortality. We aimed to assess both direct and indirect effects of visual impairment on mortality risk in the Blue Mountains Eye Study cohort.

Methods: : 3654 participants aged 49+ years were examined in 1992-4. We obtained mortality and causes of death by data linkage with the Australian National Death Index. Visual impairment was defined from visual acuity in the better eye, subdivided as correctable and non-correctable forms of impairment. Associations between mortality and baseline visual impairment were estimated using Cox regression and structural equation models (SEM).

Results: : Over 13 years, 1273 participants died. After adjusting for age, sex, and other mortality risk markers, higher mortality was not associated with correctable impairment, but was associated with non-correctable visual impairment, using Cox models (hazard ratio [HR] 1.35, 95% confidence interval [CI] 1.04-1.75). This association was stronger in persons aged <75 years (HR, 2.58; CI 1.42-4.69). Analysis using SEM conferred a substantially higher impact of visual impairment on mortality risk (HR, 5.25, CI 1.97-14.01 for persons aged <75 years and with non-correctable visual impairment), including direct (HR, 2.16; CI 1.11-4.23) and indirect effects (HR, 2.43, CI 1.17-5.03). Of the mortality risk markers examined, only walking disability was a significant indirect pathway for the link between visual impairment and mortality risk.

Conclusions: : Our population-based findings indicate that non-correctable visual impairment influences mortality risk via both direct and indirect pathways - the strongest effect was found in persons with baseline age <75. Walking disability was a major indirect pathway for the link between visual impairment and mortality risk. Reasons behind this link are unknown, but could include difficulties in accessing health services, obtaining medications, reduced exercise and poorer diet.

Keywords: low vision • quality of life 
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