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Quality of Life Research

, Volume 27, Issue 5, pp 1227–1235 | Cite as

Lifestyle-related attitudes: do they explain self-rated health and life-satisfaction?

  • A. Simon Pickard
  • Yash J. Jalundhwala
  • Helen Bewsher
  • Lisa K. Sharp
  • Surrey M. Walton
  • Glen T. Schumock
  • Rachel N. Caskey
Article

Abstract

Background

Strategies to improve public health may benefit from targeting specific lifestyles associated with poor health behaviors and outcomes. The aim of this study was to characterize and examine the relationship between health and lifestyle-related attitudes (HLAs) and self-rated health and life-satisfaction.

Methods

Secondary analyses were conducted on data from a 2012 community wellness survey in Kirklees, UK. Using a validated HLA tool, respondents (n = 9130) were categorized into five segments: health conscious realists (33%), balanced compensators (14%), live-for-todays (18%), hedonistic immortals (10%), and unconfident fatalists (25%). Multivariate regression was used to examine whether HLAs could explain self-rated health using the EQ-5D visual analog scale (EQ-VAS) and life-satisfaction. Health conscious realists served as the reference group.

Results

Self-rated health differed by HLA, with adjusted mean EQ-VAS scores being significantly higher (better) among balanced compensators (1.15, 95% CI 0.27, 2.03) and lower scores among unconfident fatalists (− 9.02, 95% CI − 9.85, − 8.21) and live-for-todays (− 1.96, 95% CI − 2.80, − 1.14). Balanced compensators were less likely to report low life-satisfaction (OR 0.75, 95% CI 0.62, 0.90), while unconfident fatalists were most likely to have low life-satisfaction (OR 3.51, 95% CI 2.92, 4.23).

Significance

Segmentation by HLA explained differences in self-rated health and life-satisfaction, with unconfident fatalists being a distinct segment with significantly worse health perceptions and life-satisfaction. Health promotion efforts may benefit from considering the HLA segment that predominates a patient group, especially unconfident fatalists.

Keywords

EQ-5D-5L Health attitudes Perception of health Life-satisfaction Lifestyle 

Notes

Acknowledgements

The authors gratefully acknowledge permission to publish the results generated from the analysis of the CLiK 2012 dataset granted by Helen Bewsher, Kirklees Council, UK.

Funding

This study was funded by a grant from the EuroQol Research Foundation.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This secondary data analysis was determined by the Institutional Review Board at the University of Illinois at Chicago (UIC IRB # 2014-0445) not to be an activity that represents human subject research.

References

  1. 1.
    Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA, 273(1), 59–65.CrossRefPubMedGoogle Scholar
  2. 2.
    Ferrans, C. E., Zerwic, J. J., Wilbur, J. E., & Larson, J. L. (2005). Conceptual model of health-related quality of life. The Journal of Nursing Research, 37(4), 336–342.Google Scholar
  3. 3.
    Williams, B., McVey, D., & Davies, L. (2011). The healthy foundations lifestage segmentation: Research Report No. 1: Creating the segmentation using a quantitative survey of the general population of England. In: London: Department of Health (DH)/National Social Marketing Centre (NSMC). Retrieved November 11, 2015 from http://www.thensmc.com/sites/default/files/301846_HFLSReport No1_ACC.pdf.
  4. 4.
    Smith, A., Humphreys, S., Heslington, L., La Placa, V., McVey, D., & MacGregor, E. (2011). The healthy foundations lifestage segmentation: Research Report No. 2: The qualitative analysis of the motivational segments. Retrieved November 11, 2015 from http://www.thensmc.com/sites/default/files/HFLSReport No2_ACC.pdf.
  5. 5.
    Sprangers, M. A. (2015). How recent health-related life events affected my perspective on quality-of-life research. Quality of Life Research, 24(5), 1157–1162.CrossRefPubMedGoogle Scholar
  6. 6.
    Jalundhwala, Y. J., Pickard, A. S., Walton, S. M., Sharp, L. K., Schumock, G. T., & Caskey, R. N. (2015). Explaining health behaviors and outcomes based on lifestyle-related attitudes: a comparison of approaches (in preparation).Google Scholar
  7. 7.
    World Health Organization. (2002). The World Health report 2002: Reducing risks, promoting healthy life. Geneva: World Health Organization.Google Scholar
  8. 8.
    Mokdad, A. H., Marks, J. S., Stroup, D. F., & Gerberding, J. L. (2004). Actual causes of death in the United States 2000. JAMA, 291(10), 1238–1245.CrossRefPubMedGoogle Scholar
  9. 9.
    Maibach, E. W., Maxfield, A., Ladin, K., & Slater, M. (1996). Translating health psychology into effective health communication: The American healthstyles audience segmentation project. Journal of Health Psychology, 1(3), 261–277.  https://doi.org/10.1177/135910539600100302.CrossRefPubMedGoogle Scholar
  10. 10.
    Dutta, M. J., & Youn, S. (1999). Profiling healthy eating consumers: A psychographic approach to social marketing. Soc Mark Q, 5(4), 4–21.  https://doi.org/10.1080/15245004.1999.9961078.CrossRefGoogle Scholar
  11. 11.
    Dutta-Bergman, M. J. (2004). A descriptive narrative of healthy eating: A social marketing approach using psychographics in conjunction with interpersonal, community, mass media and new media activities. Health Marketing Quarterly, 20(3), 81–101.CrossRefGoogle Scholar
  12. 12.
    Boslaugh, S. E., Kreuter, M. W., Nicholson, R. A., & Naleid, K. (2005). Comparing demographic, health status and psychosocial strategies of audience segmentation to promote physical activity. Health Education Research, 20(4), 430–438.  https://doi.org/10.1093/her/cyg138.CrossRefPubMedGoogle Scholar
  13. 13.
    Handler, R. M., Hynes, L. M., & Nease, R. F. Jr. (1997). Effect of locus of control and consideration of future consequences on time tradeoff utilities for current health. Quality of Life Research, 6(1), 54–60.CrossRefPubMedGoogle Scholar
  14. 14.
    Nicholson, N., Soane, E., Fenton-O’Creevy, M., & Willman, P. (2005). Personality and domain-specific risk taking. Journal of Risk Research, 8(2), 157–176.CrossRefGoogle Scholar
  15. 15.
    Anic, G. (2007). The association between personality and risk taking. Tampa: University of South Florida.Google Scholar
  16. 16.
    Turiano, N. A., Chapman, B. P., Agrigoroaei, S., Infurna, F. J., & Lachman, M. (2014). Perceived control reduces mortality risk at low, not high, education levels. Health Psychology, 33, 883CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Jerant, A., Chapman, B. P., & Franks, P. (2008). Personality and EQ-5D Scores among Individuals with chronic conditions. Quality of Life Research, 17(9), 1195–1204.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Koh, J. S., Ko, H. J., Wang, S. M., Cho, K. J., Kim, J. C., Lee, S. J., et al. (2014). The association of personality trait on treatment outcomes in patients with chronic prostatitis/chronic pelvic pain syndrome: An exploratory study. Journal of Psychosomatic Research, 76(2), 127–133.CrossRefPubMedGoogle Scholar
  19. 19.
    Milte, C. M., Luszcz, M. A., Ratcliffe, J., Masters, S., & Crotty, M. (2014). Influence of health locus of control on recovery of function in recently hospitalized frail older adults. Geriatr Gerontol Int (Milte C.M., catherine.milte@deakin.edu.au; Crotty, M.) Flinders University Department of Rehabilitation and Aged Care Repatriation General Hospital Daw Park, South Australia.Google Scholar
  20. 20.
    Whynes, D. K. (2008). Correspondence between EQ-5D health state classifications and EQ VAS scores. Health and Quality of Life Outcomes, 6, 94.  https://doi.org/10.1186/1477-7525-6-94.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Jerant, A., Chapman, B. P., Duberstein, P. R., & Franks, P. (2010). Effects of personality on self-rated health in a 1-year randomized controlled trial of chronic illness self-management. British Journal of Health Psychology, 15(2), 321–335.CrossRefPubMedGoogle Scholar
  22. 22.
    Chapman, B. P., Roberts, B., & Duberstein, P. R. (2011). Personality and longevity: Knowns, unknowns, and implications for public health and personalized medicine. Journal of Aging Research.  https://doi.org/10.4061/2011/759170.PubMedPubMedCentralGoogle Scholar
  23. 23.
    Chapman, B. P., Franks, P., Duberstein, P. R., & Jerant, A. (2009). Differences between individual and societal health state valuations: Any link with personality? Medical Care, 47(8), 902–907.  https://doi.org/10.1097/MLR.0b013e3181a8112e.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    NHS Kirklees and Kirklees Council. (2012). Technical report for the CLiK 2012 survey. Retrieved November 19, 2014 from http://www.kirklees.gov.uk/involve/publisheddoc.aspx?ref=om4zlaf5&e=353.
  25. 25.
    Bareham, A., Topping, A., McCluskey, S., Stephenson, J., & Butcher, P. (2012). Healthy foundations life-stage segmentation model toolkit: An effective tool for public health interventions?.Google Scholar
  26. 26.
    La Placa, V., McVey, D., MacGregor, E., Smith, A., & Scott, M. (2014). The contribution of qualitative research to the healthy foundations life-stage segmentation. Critical Public Health, 24(3), 266–282.CrossRefGoogle Scholar
  27. 27.
    Robinson, C. (2015). Healthy foundations segmentation. Retrieved October 24, 2015 from http://www.hscic.gov.uk/catalogue/PUB09300/HSE2011-Ch8-Health-Foundation.pdf.
  28. 28.
    Kirklees Council. (2013). Kirklees JSNA data source descriptions. Retrieved July 27, 2017 from http://www.kirklees.gov.uk/beta/public-health-partners/jsna/pdf/KirkleesJSNADatasourcedescriptions.pdf.
  29. 29.
    Rabin, R., & de Charro, F. (2001). EQ-5D: A measure of health status from the EuroQol Group. Annals of Medicine, 33(5), 337–343.CrossRefPubMedGoogle Scholar
  30. 30.
    Savoia, E., Fantini, M. P., Pandolfi, P. P., Dallolio, L., & Collina, N. (2006). Assessing the construct validity of the Italian version of the EQ-5D: preliminary results from a cross-sectional study in North Italy. Health and Quality of Life Outcome, 4, 47.  https://doi.org/10.1186/1477-7525-4-47.CrossRefGoogle Scholar
  31. 31.
    Kontodimopoulos, N., Pappa, E., Niakas, D., Yfantopoulos, J., Dimitrakaki, C., & Tountas, Y. (2008). Validity of the EuroQoL (EQ-5D) instrument in a Greek general population. Value in Health, 11(7), 1162–1169.  https://doi.org/10.1111/j.1524-4733.2008.00356.x.CrossRefPubMedGoogle Scholar
  32. 32.
    Badia, X., Schiaffino, A., Alonso, J., & Herdman, M. (1998). Using the EuroQoI 5-D in the Catalan general population: Feasibility and construct validity. Quality of Life Research, 7(4), 311–322.CrossRefPubMedGoogle Scholar
  33. 33.
    Chang, T. J., Tarn, Y. H., Hsieh, C. L., Liou, W. S., Shaw, J. W., & Chiou, X. G. (2007). Taiwanese version of the EQ-5D: Validation in a representative sample of the Taiwanese population. Journal of the Formosan Medical Association, 106(12), 1023–1031.  https://doi.org/10.1016/s0929-6646(08)60078-9.CrossRefPubMedGoogle Scholar
  34. 34.
    Shafie, A. A., Hassali, M. A., & Liau, S. Y. (2011). A cross-sectional validation study of EQ-5D among the Malaysian adult population. Quality of Life Research, 20(4), 593–600.  https://doi.org/10.1007/s11136-010-9774-6.CrossRefPubMedGoogle Scholar
  35. 35.
    Kind, P., Dolan, P., Gudex, C., & Williams, A. (1998). Variations in population health status: Results from a United Kingdom national questionnaire survey. BMJ, 316(7133), 736–741.CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Burstrom, K., Johannesson, M., & Diderichsen, F. (2001). Swedish population health-related quality of life results using the EQ-5D. Quality of Life Research, 10(7), 621–635.CrossRefPubMedGoogle Scholar
  37. 37.
    Bharmal, M., & 3rd Thomas, J. (2006). Comparing the EQ-5D and the SF-6D descriptive systems to assess their ceiling effects in the US general population. Value in Health, 9(4), 262–271.  https://doi.org/10.1111/j.1524-4733.2006.00108.x.CrossRefPubMedGoogle Scholar
  38. 38.
    Hinz, A., Klaiberg, A., Brahler, E., & Konig, H. H. (2006). The quality of life questionnaire EQ-5D: Modelling and norm values for the general population. Psychotherapie Psychosomatik Medizinische Psychologie, 56(2), 42–48.  https://doi.org/10.1055/s-2005-867061.CrossRefGoogle Scholar
  39. 39.
    Johnson, J. A., & Coons, S. J. (1998). Comparison of the EQ-5D and SF-12 in an adult US sample. Quality of Life Research, 7(2), 155–166.CrossRefPubMedGoogle Scholar
  40. 40.
    Johnson, J. A., & Pickard, A. S. (2000). Comparison of the EQ-5D and SF-12 health surveys in a general population survey in Alberta, Canada. Medical Care, 38(1), 115–121.  https://doi.org/10.2307/3767108.CrossRefPubMedGoogle Scholar
  41. 41.
    Konig, H. H., Bernert, S., Angermeyer, M. C., Matschinger, H., Martinez, M., Vilagut, G., et al. (2009). Comparison of population health status in six European countries: Results of a representative survey using the EQ-5D questionnaire. Medical Care, 47(2), 255–261.  https://doi.org/10.1097/MLR.0b013e318184759e.CrossRefPubMedGoogle Scholar
  42. 42.
    Herdman, M., Gudex, C., Lloyd, A., Janssen, M. F., Kind, P., Parkin, D., et al. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736.  https://doi.org/10.1007/s11136-011-9903-x.CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Kim, T. H., Jo, M. W., Lee, S., Kim, S. H., & Chung, S. M. (2013). Psychometric properties of the EQ-5D-5L in the general population of South Korea. Quality of Life Research, 22(8), 2245–2253.  https://doi.org/10.1007/s11136-012-0331-3.CrossRefPubMedGoogle Scholar
  44. 44.
    Hinz, A., Kohlmann, T., Stöbel-Richter, Y., Zenger, M., & Brähler, E. (2014). The quality of life questionnaire EQ-5D-5L: Psychometric properties and normative values for the general German population. Quality of Life Research, 23(2), 443–447.  https://doi.org/10.1007/s11136-013-0498-2.CrossRefPubMedGoogle Scholar
  45. 45.
    Szende, A., Janssen, B., Cabases, J., & Ramos Goñi, J. M. (2014). Self-reported population health: An international perspective based on EQ-5D. New York: Springer.CrossRefGoogle Scholar
  46. 46.
    Agborsangaya, C. B., Lahtinen, M., Cooke, T., & Johnson, J. A. (2014). Comparing the EQ-5D 3L and 5L: Measurement properties and association with chronic conditions and multimorbidity in the general population. Health and Quality of Life Outcomes, 12, 74.  https://doi.org/10.1186/1477-7525-12-74.CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Dolan, P., & Metcalfe, R. (2012). Valuing health: A brief report on subjective well-being versus preferences. Medical Decision Making, 32(4), 578–582.  https://doi.org/10.1177/0272989x11435173.CrossRefPubMedGoogle Scholar
  48. 48.
    Wu, M., Brazier, J. E., Relton, C., Cooper, C., Smith, C., & Blackburn, J. (2014). Examining the incremental impact of long-standing health conditions on subjective well-being alongside the EQ-5D. Health and Quality of Life Outcomes, 12(1), 61.CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Whynes, D. K. (2013). Does the correspondence between EQ-5D health state description and VAS score vary by medical condition? Health and Quality of Life Outcomes, 11, 155–155.  https://doi.org/10.1186/1477-7525-11-155.CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Pickard, A. S., Neary, M. P., & Cella, D. (2007). Estimation of minimally important differences in EQ-5D utility and VAS scores in cancer. Health and Quality of Life Outcomes, 5, 70.CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Walters, S. J., & Brazier, J. E. (2005). Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Quality of Life Research, 14(6), 1523–1532.CrossRefPubMedGoogle Scholar
  52. 52.
    Moksnes, U. K., & Espnes, G. A. (2013). Self-esteem and life satisfaction in adolescents: Gender and age as potential moderators. Quality of Life Research, 22(10), 2921–2928.  https://doi.org/10.1007/s11136-013-0427-4.CrossRefPubMedGoogle Scholar
  53. 53.
    Seligman, M. E., & Csikszentmihalyi, M. (2000). Positive psychology. An introduction. The American Psychologist, 55(1), 5–14.CrossRefPubMedGoogle Scholar
  54. 54.
    Lubetkin, E. I., Jia, H., Franks, P., & Gold, M. R. (2005). Relationship among sociodemographic factors, clinical conditions, and health-related quality of life: Examining the EQ-5D in the U.S. general population. Quality of Life Research, 14(10), 2187–2196.CrossRefPubMedGoogle Scholar
  55. 55.
    Shaw, J. W., Johnson, J. A., Chen, S., Levin, J. R., & Coons, S. J. (2007). Racial/ethnic differences in preferences for the EQ-5D health states: Results from the U.S. valuation study. Journal of Clinical Epidemiology, 60(5), 479–490.CrossRefPubMedGoogle Scholar
  56. 56.
    Dolan, P. (2000). Effect of age on health state valuations. Journal of Health Services Research & Policy, 5(1), 17–21.CrossRefGoogle Scholar
  57. 57.
    Wittenberg, E., Halpern, E., Divi, N., Prosser, L. A., Araki, S. S., & Weeks, J. C. (2006). The effect of age, race and gender on preference scores for hypothetical health states. Quality of Life Research, 15(4), 645–653.CrossRefPubMedGoogle Scholar
  58. 58.
    Hargreaves, D. S., James, D., Goddings, A. L., McVey, D., & Viner, R. M. (2014). Distinct patterns of health engagement among adolescents and young adults in England: Implications for health services. Perspectives in Public Health, 134, 81–84.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • A. Simon Pickard
    • 1
    • 2
  • Yash J. Jalundhwala
    • 1
  • Helen Bewsher
    • 3
  • Lisa K. Sharp
    • 1
    • 2
  • Surrey M. Walton
    • 1
    • 2
  • Glen T. Schumock
    • 1
    • 2
  • Rachel N. Caskey
    • 4
  1. 1.Department of Pharmacy Systems, Outcomes and Policy, College of PharmacyUniversity of Illinois at ChicagoChicagoUSA
  2. 2.Center for Pharmacoepidemiology and Pharmacoeconomic Research, College of PharmacyUniversity of Illinois at ChicagoChicagoUSA
  3. 3.Kirklees CouncilThe University of ManchesterHuddersfieldUnited Kingdom
  4. 4.Internal Medicine and Pediatrics, College of MedicineUniversity of Illinois at ChicagoChicagoUSA

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