Quality of Life Research

, Volume 26, Issue 6, pp 1521–1530 | Cite as

Lower educational level and unemployment increase the impact of cardiometabolic conditions on the quality of life: results of a population-based study in South Australia

  • David Alejandro  González-ChicaEmail author
  • Robert Adams
  • Eleonora Dal Grande
  • Jodie Avery
  • Phillipa Hay
  • Nigel Stocks



To investigate if sociodemographic characteristics increase the adverse effects of cardiovascular diseases (CVD) and cardiometabolic risk factors (CMRF) on health-related quality of life (HRQoL).


Cross-sectional, face-to-face survey investigating 2379 adults living in South Australia in 2015 (57.1 ± 14 years; 51.7% females). Questions included diagnosis of CMRF (obesity, diabetes, hypertension, dyslipidaemia) and CVD. Physical and mental HRQoL were assessed using the SF-12v1 questionnaire. Multiple linear regression models including confounders (sociodemographic, lifestyle, use of preventive medication) and interaction terms between sociodemographic variables and cardiometabolic conditions were used in adjusted analysis.


The prevalence of CMRF (one or more) was 54.6% and CVD was 13.0%. The physical HRQoL reduced from 50.8 (95%CI 50.2–51.4) in healthy individuals to 45.1 (95%CI 44.4–45.9) and 39.1 (95%CI 37.7–40.5) among those with CMRF and CVD, respectively. Adjustment for sociodemographic variables reduced these differences in 33%, remaining stable after controlling for lifestyle and use of preventive medications (p < 0.001). Differences in physical HRQoL according to cardiometabolic conditions were twice as high among those with lower educational level, or if they were not working. Among unemployed, having a CMRF or a CVD had the same impact on the physical HRQoL (9.7 lower score than healthy individuals). The inverse association between cardiometabolic conditions and mental HRQoL was subtle (p = 0.030), with no evidence of disparities due to sociodemographic variables.


A lower educational level and unemployment increase the adverse effects of cardiometabolic conditions on the physical HRQoL. Targeted interventions for reducing CMRF and/or CVD in these groups are necessary to improve HRQoL.


Quality of life Cardiovascular disease Metabolic disease Socioeconomic factors Health status disparities 



The author acknowledges the participants of the 2015 Spring Health Omnibus Survey for their participation in this study.

Compliance with ethical standards


D.A. González-Chica received a part Fellowship from the NHMRC Centre of Research Excellence to Reduce Inequality in Heart Disease to conduct this study.

Conflict of interest

All the authors declare they have no conflict of interest.

Ethical approval

This study was approved by the University of Adelaide Human Research Ethics Committee (project H-097-2010). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Participants provided verbal rather than written informed consent, due to the practicalities of carrying out a large-scale survey and the low-risk nature of the survey content.

Supplementary material

11136_2017_1503_MOESM1_ESM.docx (37 kb)
Supplementary material 1 (DOCX 36 KB)


  1. 1.
    Hunter, D. J., & Reddy, K. S. (2013). Noncommunicable diseases. The New England Journal of Medicine, 369(14), 1336–1343.CrossRefPubMedGoogle Scholar
  2. 2.
    WHO. (2011). WHO maps noncommunicable disease trends in all countries: Country profiles on noncommunicable disease trends in 193 countries. Central European Journal of Public Health, 19(3), 130–138.Google Scholar
  3. 3.
    AIHW. (2014). Australian Institute of Health and Welfare. Cardiovascular disease, diabetes and chronic kidney disease—Australian facts: Prevalence and incidence. Cardiovascular, diabetes and chronic kidney disease. Series No. 2. Cat. No. CDK 2. Canberra: AIHW. (Available at Accessed on 15 Mar 2016.
  4. 4.
    Eckel, R. H., & Cornier, M. A. (2014). Update on the NCEP ATP-III emerging cardiometabolic risk factors. BMC Medicine, 12, 115.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Begg, S. J. (2014). Health in a ‘post-transition’ Australia: Adding years to life or life to years? Australian health review: a publication of the Australian Hospital Association, 38(1), 1–5.CrossRefGoogle Scholar
  6. 6.
    Chowdhury, R., Khan, H., Heydon, E., Shroufi, A., Fahimi, S., Moore, C., Stricker, B., Mendis, S., Hofman, A., Mant, J., & Franco, O. H. (2013). Adherence to cardiovascular therapy: A meta-analysis of prevalence and clinical consequences. European Heart Journal, 34(38), 2940–2948.CrossRefPubMedGoogle Scholar
  7. 7.
    Conn, V. S., Ruppar, T. M., Maithe Enriquez, R., & Cooper, P. S. (2016). Patient-centered outcomes of medication adherence interventions: Systematic review and meta-analysis. Value in Health: The Journal of the International Society for Pharmacoeconomics and Outcomes Research, 19(2), 277–285.CrossRefGoogle Scholar
  8. 8.
    Mark, D. B. (2016). Assessing quality-of-life outcomes in cardiovascular clinical research. Nat Rev Cardiol.Google Scholar
  9. 9.
    Bakas, T., McLennon, S. M., Carpenter, J. S., Buelow, J. M., Otte, J. L., Hanna, K. M., Ellett, M. L., Hadler, K. A., & Welch, J. L. (2012). Systematic review of health-related quality of life models. Health and Quality of Life Outcomes, 10, 134.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Fortin, M., Lapointe, L., Hudon, C., Vanasse, A., Ntetu, A. L., & Maltais, D. (2004). Multimorbidity and quality of life in primary care: A systematic review. Health and Quality of Life Outcomes, 2, 51.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Hutchinson, A. F., Graco, M., Rasekaba, T. M., Parikh, S., Berlowitz, D. J., & Lim, W. K. (2015). Relationship between health-related quality of life, comorbidities and acute health care utilisation, in adults with chronic conditions. Health and Quality of Life Outcomes, 13, 69.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Gonzalez-Chica, D. A., Mnisi, Z., Avery, J., Duszynski, K., Doust, J., Tideman, P., Murphy, A., Burgess, J., Beilby, J., & Stocks, N. (2016). Effect of health literacy on quality of life amongst patients with Ischaemic heart disease in Australian General Practice. PLoS One, 11(3), e0151079.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Mello Ade, C., Engstrom, E. M., & Alves, L. C. (2014). Health-related and socio-demographic factors associated with frailty in the elderly: A systematic literature review. Cadernos de saude publica/Ministerio da Saude, Fundacao Oswaldo Cruz, Escola Nacional de Saude Publica, 30(6), 1143–1168.Google Scholar
  14. 14.
    Mielck, A., Vogelmann, M., & Leidl, R. (2014). Health-related quality of life and socioeconomic status: Inequalities among adults with a chronic disease. Health and Quality of Life Outcomes, 12, 58.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Stafford, M., Soljak, M., Pledge, V., & Mindell, J. (2012). Socio-economic differences in the health-related quality of life impact of cardiovascular conditions. European Journal of Public Health, 22(3), 301–305.CrossRefPubMedGoogle Scholar
  16. 16.
    Ludt, S., Wensing, M., Szecsenyi, J., van Lieshout, J., Rochon, J., Freund, T., Campbell, S. M., & Ose, D. (2011). Predictors of health-related quality of life in patients at risk for cardiovascular disease in European primary care. PLoS One, 6(12), e29334.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Taylor, A., Dal Grande, E., & Wilson, D. (2006). The South Australian Health Omnibus Survey 15 years on: has public health benefited? Public Health Bull (S Aust), 3(1), 30–32. Available at Accessed on 16 Jun 2016.
  18. 18.
    ABS. (2016). Australian Bureau of Statistics. Table Builder. Available at Accessed on 10 May 2016.
  19. 19.
    ABS. (2011). Australian Bureau of Statistics. Census of Population and Housing: Socio-economic indexes for areas (SEIFA), Australia. Available at Accessed on 01 Mar 2014 (Vol. cat. no. 2033.0.55.001).
  20. 20.
    Gandek, B., Ware, J. E., Aaronson, N. K., Apolone, G., Bjorner, J. B., Brazier, J. E., Bullinger, M., Kaasa, S., Leplege, A., Prieto, L., & Sullivan, M. (1998). Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: Results from the IQOLA Project. International Quality of Life Assessment. Journal of Clinical Epidemiology, 51(11), 1171–1178CrossRefPubMedGoogle Scholar
  21. 21.
    Wilson, D., Tucker, G., & Chittleborough, C. (2002). Rethinking and rescoring the SF-12. Sozial- und Präventivmedizin, 47(3), 172–177.PubMedGoogle Scholar
  22. 22.
    Mitchel, M. (2012). Interpreting and visualizing regression models using STATA, first ed (First ed.). Texas:Stata Press.Google Scholar
  23. 23.
    Taylor, A. W., Dal Grande, E., Wu, J., Shi, Z., & Campostrini, S. (2014). Ten-year trends in major lifestyle risk factors using an ongoing population surveillance system in Australia. Population Health Metrics, 12(1), 31CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Avery, J., Dal Grande, E., & Taylor, A. (2004). Quality of life in South Australia as measured by the SF-12 Health Status Questionnaire: Population norms for 2003: Trends from 1997 to 2003. ISBN 0730893294. Available at Accessed on 05 Jun 2015 (No. .). South Australia: South Australia. Dept. of Human Services. Population Research and Outcome Studies Unit.
  25. 25.
    Diaz-Toro, F., Verdejo, H. E., & Castro, P. F. (2015). Socioeconomic inequalities in heart failure. Heart Failure Clinics, 11(4), 507–513.CrossRefPubMedGoogle Scholar
  26. 26.
    Hawkins, N. M., Jhund, P. S., McMurray, J. J., & Capewell, S. (2012). Heart failure and socioeconomic status: Accumulating evidence of inequality. European Journal of Heart Failure: Journal of the Working Group on Heart Failure of the European Society of Cardiology, 14(2), 138–146.CrossRefGoogle Scholar
  27. 27.
    Schroder, S. L., Richter, M., Schroder, J., Frantz, S., & Fink, A. (2016). Socioeconomic inequalities in access to treatment for coronary heart disease: A systematic review. International Journal of Cardiology, 219, 70–78.CrossRefPubMedGoogle Scholar
  28. 28.
    Sommer, I., Griebler, U., Mahlknecht, P., Thaler, K., Bouskill, K., Gartlehner, G., & Mendis, S. (2015). Socioeconomic inequalities in non-communicable diseases and their risk factors: An overview of systematic reviews. BMC Public Health, 15, 914.CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Terraneo, M. (2015). Inequities in health care utilization by people aged 50+: Evidence from 12 European countries. Social Science & Medicine (1982), 126, 154–163.CrossRefGoogle Scholar
  30. 30.
    Cajita, M. I., Cajita, T. R., & Han, H. R. (2016). Health literacy and heart failure: A systematic review. The Journal of Cardiovascular Nursing, 31(2), 121–130.CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    AIHW. (2014). Australian Institute of Health and Welfare. Mortality inequalities in Australia 2009–2011. Bulletin no. 124. Cat. no. AUS 184. Canberra: AIHW. Available at Accessed on 03 Mar 2016.

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • David Alejandro  González-Chica
    • 1
    Email author
  • Robert Adams
    • 2
  • Eleonora Dal Grande
    • 3
  • Jodie Avery
    • 3
  • Phillipa Hay
    • 4
  • Nigel Stocks
    • 1
  1. 1.Discipline of General Practice, School of Medicine, NHMRC Centre of Research Excellence to Reduce Inequality in Heart DiseaseThe University of AdelaideAdelaideAustralia
  2. 2.The Health Observatory, Discipline of MedicineThe University of AdelaideWoodvilleAustralia
  3. 3.Population Research and Outcome Studies, Discipline of Medicine, School of MedicineThe University of AdelaideAdelaideAustralia
  4. 4.Centre for Health Research, School of MedicineUniversity of Western SydneySydneyAustralia

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