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Examining the SF-36 in an older population: analysis of data and presentation of Australian adult reference scores from the Dynamic Analyses to Optimise Ageing (DYNOPTA) project

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Abstract

Purpose

To examine the psychometric properties of, and present reference scores for the SF-36 using data from a large community sample of older adults.

Methods

Data are from the DYNOPTA project. We focus on data from five studies that included the SF-36, providing a sample of 41,338 participants aged 45–97 years. We examine the factor structure of the SF-36 and item-internal consistency.

Results

The psychometric properties of the eight scales of the SF-36 were largely consistent with previous research based on younger and/or smaller samples. However, the assumption of orthogonality between the second-order factors was not supported. In terms of age-related effects, most scales demonstrated a nonlinear effect with markedly poorer health evident for the oldest respondents. In addition, the scales measuring aspects of physical health (PH, BP, RP, GH) showed an overall linear decline in health with increasing age. There were, however, no consistent linear age-related differences in health evident for those scales most strongly associated with mental health (MH, RE, SF, VT).

Conclusions

The results confirm the structural validity and internal consistency of the eight scales from the SF-36 with an older population and support its use to assess the health of older Australian adults.

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Abbreviations

ALSWH:

Australian Longitudinal Study of Women’s Health

ASGC:

Australian Standard Geographic Classification

AusDiab:

Australian Diabetes, Obesity and Lifestyle Survey

BMES:

Blue Mountains Eye Study

CFA:

Confirmatory Factor Analysis

CFI:

Comparative Fit Index

DYNOPTA:

Dynamic Analyses to Optimise Ageing

HILDA:

Household, Income and Labour Dynamics of Australia

IQOLA:

International Quality of Life Assessment

RMSEA:

Root Mean Square Error of Approximation

SF-36:

Short-form 36 health survey

SRMR:

Standardized Root Mean-square Residual

TLI:

Tucker-Lewis Index

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Acknowledgments

The data on which this research is based were drawn from several Australian longitudinal studies including: the Australian Longitudinal Study of Aging (ALSA), the Australian Longitudinal Study of Women’s Health, the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), the Blue Mountain Eye Study (BMES), the Canberra Longitudinal Study of Aging (CLS), the Household, Income and Labour Dynamics in Australia study (HILDA), the Melbourne Longitudinal Studies on Healthy Aging (MELSHA), the Personality And Total Health Through Life Study (PATH), and the Sydney Older Persons Study (SOPS). These studies were pooled and harmonized for the Dynamic Analyses to Optimise Aging (DYNOPTA) project. DYNOPTA was funded by an NHMRC grant (# 410215). All studies would like to thank the participants for volunteering their time to be involved in the respective studies. Details of all studies contributing data to DYNOPTA, including individual study leaders, funding sources, and request forms for DYNOPTA data, are available on the DYNOPTA website (http://dynopta.anu.edu.au). The findings and views reported in this paper are those of the author(s) and not those of the original studies or their respective funding agencies.

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Authors and Affiliations

  1. Centre for Mental Health Research, Australian National University, Canberra, ACT, Australia

    Lauren J. Bartsch, Peter Butterworth & Kaarin J. Anstey

  2. Research Centre for Gender, Health and Aging, University of Newcastle, Newcastle, NSW, Australia

    Julie E. Byles

  3. Department of Ophthalmology, University of Sydney, Sydney, NSW, Australia

    Paul Mitchell

  4. Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia

    Jonathan Shaw

Authors
  1. Lauren J. Bartsch
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  2. Peter Butterworth
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  3. Julie E. Byles
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  4. Paul Mitchell
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  5. Jonathan Shaw
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  6. Kaarin J. Anstey
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Correspondence to Lauren J. Bartsch.

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Bartsch, L.J., Butterworth, P., Byles, J.E. et al. Examining the SF-36 in an older population: analysis of data and presentation of Australian adult reference scores from the Dynamic Analyses to Optimise Ageing (DYNOPTA) project. Qual Life Res 20, 1227–1236 (2011). https://doi.org/10.1007/s11136-011-9864-0

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