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Trajectories of perceived social support in acute coronary syndrome

  • Meng Wang
  • Colleen M. Norris
  • Michelle M. Graham
  • Maria Santana
  • Zhiying Liang
  • Oluwagbohunmi Awosoga
  • Danielle A. Southern
  • Matthew T. James
  • Stephen B. Wilton
  • Hude Quan
  • Mingshan Lu
  • William Ghali
  • Merril Knudtson
  • Tolulope T. Sajobi
Article

Abstract

Purpose

Perceived social support is known to be an important predictor of health outcomes in patients with acute coronary syndrome (ACS). This study investigates patterns of longitudinal trajectories of patient-reported perceived social support in individuals with ACS.

Methods

Data are from 3013 patients from the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease registry who had their first cardiac catheterization between 2004 and 2011. Perceived social support was assessed using the 19-item Medical Outcomes Study Social Support Survey (MOS) 2 weeks, 1 year, and 3 years post catheterization. Group-based trajectory analysis based on longitudinal multiple imputation model was used to identify distinct subgroups of trajectories of perceived social support over a 3-year follow-up period.

Results

Three distinct social support trajectory subgroups were identified, namely: “High” social support group (60%), “Intermediate” social support group (30%), and “Low” social support subgroup (10%). Being female (OR = 1.67; 95% CI = [1.18–2.36]), depression (OR = 8.10; 95% CI = [4.27–15.36]) and smoking (OR = 1.70; 95% CI = [1.23–2.35]) were predictors of the differences among these trajectory subgroups.

Conclusion

Although the majority of ACS patients showed increased or fairly stable trajectories of social support, about 10% of the cohort reported declining social support. These findings can inform targeted psycho-social interventions to improve their perceived social support and health outcomes.

Keywords

Perceived social support Patient-reported outcome Acute coronary syndrome Longitudinal trajectories 

Notes

Funding

This research was supported by the University of Calgary O’Brien Institute of Public Health.

Compliance with ethical standards

Conflict of interest

The authors declare that there’s no conflict of interest.

Ethical approval

Ethics approval was obtained from the University of Calgary Conjoint Health Research Ethics Board (REB14-1320).

Informed consent

Informed consent was obtained from all subjects included in the study.

References

  1. 1.
    Strike, P. C., & Steptoe, A. (2005). Behavioral and emotional triggers of acute coronary syndromes: A systematic review and critique. Psychosomatic Medicine, 67(2), 179–186.CrossRefGoogle Scholar
  2. 2.
    Chung, M. C., Berger, Z., & Rudd, H. (2008). Coping with posttraumatic stress disorder and comorbidity after myocardial infarction. Comprehensive Psychiatry, 49(1), 55–64.CrossRefGoogle Scholar
  3. 3.
    Kumar, A., & Cannon, C. P. (2009). Acute coronary syndromes: Diagnosis and management, part I. Mayo Clinic Proceedings, 84(10), 917–938,  https://doi.org/10.1016/S0025-6196(11)60509-0.CrossRefGoogle Scholar
  4. 4.
    Graven, L. J., & Grant, J. S. (2014). Social support and self-care behaviors in individuals with heart failure: An integrative review. International Journal of Nursing Studies, 51(2), 320–333.  https://doi.org/10.1016/j.ijnurstu.2013.06.013.CrossRefGoogle Scholar
  5. 5.
    Holt-Lunstad, J., Smith, T. B., & Layton, J. B. (2010). Social Relationships and mortality risk: A meta-analytic review. PLOS Medicine, 7(7), e1000316.CrossRefGoogle Scholar
  6. 6.
    Dekker, R. L., Peden, A. R., Lennie, T. A., Schooler, M. P., & Moser, D. K. (2009). Living with depressive symptoms: Patients with heart failure. American journal of critical care: An Official Publication. American Association of Critical-Care Nurses, 18(4), 310–318.  https://doi.org/10.4037/ajcc2009672.CrossRefGoogle Scholar
  7. 7.
    Valtorta, N. K., Kanaan, M., Gilbody, S., Ronzi, S., & Hanratty, B. (2016). Loneliness and social isolation as risk factors for coronary heart disease and stroke: Systematic review and meta-analysis of longitudinal observational studies. Heart, 102(13), 1009–1016.  https://doi.org/10.1136/heartjnl-2015-308790.CrossRefGoogle Scholar
  8. 8.
    Hakulinen, C., Pulkki-Raback, L., Virtanen, M., Jokela, M., Kivimaki, M., & Elovainio, M. (2018). Social isolation and loneliness as risk factors for myocardial infarction, stroke and mortality: UK Biobank cohort study of 479 054 men and women. Heart, 104(18), 1536–1542.  https://doi.org/10.1136/heartjnl-2017-312663.CrossRefGoogle Scholar
  9. 9.
    White, A. M., Philogene, G. S., Fine, L., & Sinha, S. (2009). Social support and self-reported health status of older adults in the United States. American Journal of Public Health, 99(10), 1872–1878.  https://doi.org/10.2105/AJPH.2008.146894.CrossRefGoogle Scholar
  10. 10.
    Simms, A. D., Batin, P. D., Kurian, J., Durham, N., & Gale, C. P. (2012). Acute coronary syndromes: An old age problem. Journal of Geriatric Cardiology: JGC, 9(2), 192–196.  https://doi.org/10.3724/SP.J.1263.2012.01312.CrossRefGoogle Scholar
  11. 11.
    Holden, L., Lee, C., Hockey, R., Ware, R. S., & Dobson, A. J. (2015). Longitudinal analysis of relationships between social support and general health in an Australian population cohort of young women. Quality of Life Research, 24(2), 485–492.  https://doi.org/10.1007/s11136-014-0774-9.CrossRefGoogle Scholar
  12. 12.
    Lett, H. S., Blumenthal, J. A., Babyak, M. A., Strauman, T. J., Robins, C., & Sherwood, A. (2005). Social support and coronary heart disease: Epidemiologic evidence and implications for treatment. Psychosomatic Medicine, 67(6), 869–878.CrossRefGoogle Scholar
  13. 13.
    Bosworth, H. B., Siegler, I. C., Olsen, M. K., Brummett, B. H., Barefoot, J. C., Williams, R. B., et al. (2000). Social support and quality of life in patients with coronary artery disease. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 9(7), 829–839.CrossRefGoogle Scholar
  14. 14.
    Norris, C. M., Spertus, J. A., Jensen, L., Johnson, J., Hegadoren, K. M., Ghali, W. A., et al. (2008). Sex and gender discrepancies in health-related quality of life outcomes among patients with established coronary artery disease. Circulation: Cardiovascular Quality and Outcomes, 1(2), 123–130.  https://doi.org/10.1161/CIRCOUTCOMES.108.793448 Google Scholar
  15. 15.
    Staniute, M., Brozaitiene, J., & Bunevicius, R. (2013). Effects of social support and stressful life events on health-related quality of life in coronary artery disease patients. The Journal of Cardiovascular Nursing, 28(1), 83–89.  https://doi.org/10.1097/JCN.0b013e318233e69d CrossRefGoogle Scholar
  16. 16.
    Leifheit-Limson, E. C., Reid, K. J., Kasl, S. V., Lin, H., Jones, P. G., Buchanan, D. M., et al. (2010). The role of social support in health status and depressive symptoms after acute myocardial infarction: Evidence for a stronger relationship among women. Circulation: Cardiovascular Quality and Outcomes, 3(2), 143–150.  https://doi.org/10.1161/CIRCOUTCOMES.109.899815.Google Scholar
  17. 17.
    Ghali, W. A., Knudtson, M. L., & on behalf of the APPROACH Investigators. (2000). Overview of the alberta provincial project for outcome assessment in coronary heart disease. The Canadian Journal of Cardiology, 16(10), 1225–1230.Google Scholar
  18. 18.
    Sherbourne, C. D., & Stewart, A. L. (1991). The MOS social support survey. Social Science & Medicine (1982), 32(6), 705–714.CrossRefGoogle Scholar
  19. 19.
    Gjesfjeld, C. D., Greeno, C. G., & Kim, K. H. (2008). A confirmatory factor analysis of an abbreviated social support instrument: The MOS-SSS. Research on Social Work Practice, 18(3), 231–237.  https://doi.org/10.1177/1049731507309830.CrossRefGoogle Scholar
  20. 20.
    Robitaille, A., Orpana, H., & McIntosh, C. N. (2011). Psychometric properties, factorial structure, and measurement invariance of the English and French versions of the Medical Outcomes Study social support scale. Health Reports, 22(2), 33–40.Google Scholar
  21. 21.
    Stafford, L., Berk, M., & Jackson, H. J. (2007). Validity of the Hospital Anxiety and Depression Scale and Patient Health Questionnaire-9 to screen for depression in patients with coronary artery disease. General Hospital Psychiatry, 29(5), 417–424.CrossRefGoogle Scholar
  22. 22.
    Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica, 67(6), 361–370.CrossRefGoogle Scholar
  23. 23.
    Stern, A. F. (2014). The hospital anxiety and depression scale. Occupational Medicine (Oxford, England), 64(5), 393–394.  https://doi.org/10.1093/occmed/kqu024.CrossRefGoogle Scholar
  24. 24.
    Harel, O., Mitchell, E. M., Perkins, N. J., Cole, S. R., Tchetgen Tchetgen, E. J., Sun, B., et al. (2018). Multiple imputation for incomplete data in epidemiologic studies. American Journal of Epidemiology, 187(3), 576–584.  https://doi.org/10.1093/aje/kwx349.CrossRefGoogle Scholar
  25. 25.
    Ma, J., Raina, P., Beyene, J., & Thabane, L. (2012). Comparing the performance of different multiple imputation strategies for missing binary outcomes in cluster randomized trials: A simulation study. Journal of Open Access Medical Statistics, 2, 93–103.Google Scholar
  26. 26.
    Faris, P. D., Ghali, W. A., Brant, R., Norris, C. M., Galbraith, P. D., Knudtson, M. L., et al. (2002). Multiple imputation versus data enhancement for dealing with missing data in observational health care outcome analyses. Journal of Clinical Epidemiology, 55(2), 184–191.CrossRefGoogle Scholar
  27. 27.
    Little, R. J., & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). New Yorkk: Wiley.CrossRefGoogle Scholar
  28. 28.
    Nagin, D. S. (2005). Group-based modelling of development. London: Harvard University Press.CrossRefGoogle Scholar
  29. 29.
    Jones, B. L., Nagin, D. S., & Roeder, K. (2001). A SAS procedure based on mixture models for estimating development trajectories. Sociological Methods & Research, 29(3), 374–393.CrossRefGoogle Scholar
  30. 30.
    Nagin, D. S., & Odgers, C. L. (2010). Group-based trajectory modeling in clinical research. Annual Review of Clinical Psychology, 6, 109–138.  https://doi.org/10.1146/annurev.clinpsy.121208.131413.CrossRefGoogle Scholar
  31. 31.
    Nagin, D. S. (2014). Group-based trajectory modeling: An overview. Annals of Nutrition & Metabolism, 65(2–3), 205–210.  https://doi.org/10.1159/000360229.CrossRefGoogle Scholar
  32. 32.
    Andruff, H., Carraro, N., Thompson, A., & Gaudreau, P. (2009). Latent class growth modelling: A tutorial. Tutorials Quantitative Methods for Psychology, 5, 11–24.CrossRefGoogle Scholar
  33. 33.
    Schafer, J. L. (1997). Analysis of incomplete multivariate data. New York: Chapman & Hall.CrossRefGoogle Scholar
  34. 34.
    SAS Institute Inc. (2013). Base SAS® 9.4 procedures guide: Statistical procedures. Cary: SAS Institute Inc.Google Scholar
  35. 35.
    Powers, S. M., Bisconti, T. L., & Bergeman, C. S. (2014). Trajectories of social support and well-being across the first two years of widowhood. Death Studies, 38(8), 499–509.  https://doi.org/10.1080/07481187.2013.846436.CrossRefGoogle Scholar
  36. 36.
    Dean, A., Matt, G. E., & Wood, P. (1992). The effects of widowhood on social support from significant others. Journal of Community Psychology, 20(4), 309–325.  https://doi.org/10.1002/1520-6629(199210)20:43.0.CO;2-V.CrossRefGoogle Scholar
  37. 37.
    Shankar, A., Mcmunn, A., Banks, J., & Steptoe, A. (2011). Loneliness, social isolation, and behavioral and biological health indicators in older adults. Health Psychology, 30(4), 377–385.  https://doi.org/10.1037/a0022826.CrossRefGoogle Scholar
  38. 38.
    Kristofferzon, M. L., Lofmark, R., & Carlsson, M. (2003). Myocardial infarction: Gender differences in coping and social support. Journal of Advanced Nursing, 44(4), 360–374.CrossRefGoogle Scholar
  39. 39.
    Ikeda, A., Iso, H., Kawachi, I., Yamagishi, K., Inoue, M., & Tsugane, S. (2008). Social support and stroke and coronary heart disease. Stroke, 39(3), 768–775.  https://doi.org/10.1161/STROKEAHA.107.496695.CrossRefGoogle Scholar
  40. 40.
    Garnefski, N., Kraaij, V., Schroevers, M. J., Aarnink, J., van der Heijden, D. J., van Es, S. M., et al. (2009). Cognitive coping and goal adjustment after first-time myocardial infarction: Relationships with symptoms of depression. Behavioral Medicine (Washington, D. C.), 35(3), 79–86,  https://doi.org/10.1080/08964280903232068.CrossRefGoogle Scholar
  41. 41.
    Son, H., Friedmann, E., Thomas, S. A., & Son, Y. J. (2016). Biopsychosocial predictors of coping strategies of patients postmyocardial infarction. International Journal of Nursing Practice, 22(5), 493–502.  https://doi.org/10.1111/ijn.12465.CrossRefGoogle Scholar
  42. 42.
    Helgeson, V. S. (2003). Social support and quality of life. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 12(Suppl 1), 25–31.CrossRefGoogle Scholar
  43. 43.
    McConnell, T. R., Trevino, K. M., & Klinger, T. A. (2011). Demographic differences in religious coping after a first-time cardiac event. Journal of Cardiopulmonary Rehabilitation and Prevention, 31(5), 298–302.  https://doi.org/10.1097/HCR.0b013e31821c41f0.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Meng Wang
    • 1
  • Colleen M. Norris
    • 2
    • 3
  • Michelle M. Graham
    • 2
  • Maria Santana
    • 1
  • Zhiying Liang
    • 1
  • Oluwagbohunmi Awosoga
    • 4
  • Danielle A. Southern
    • 1
  • Matthew T. James
    • 1
    • 5
  • Stephen B. Wilton
    • 5
    • 6
  • Hude Quan
    • 1
  • Mingshan Lu
    • 7
  • William Ghali
    • 1
    • 5
  • Merril Knudtson
    • 5
    • 6
  • Tolulope T. Sajobi
    • 1
  1. 1.Department of Community Health Sciences & O’Brien Institute for Public HealthUniversity of CalgaryCalgaryCanada
  2. 2.Faculty of Medicine & DentistryUniversity of AlbertaEdmontonCanada
  3. 3.Faculty of NursingUniversity of AlbertaEdmontonCanada
  4. 4.Faculty of Health SciencesUniversity of LethbridgeLethbridgeCanada
  5. 5.Department of MedicineUniversity of CalgaryCalgaryCanada
  6. 6.Department of Cardiac SciencesUniversity of CalgaryCalgaryCanada
  7. 7.Department of EconomicsUniversity of CalgaryCalgaryCanada

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