|
| |
 |
|
| ORIGINAL ARTICLE |
|
| Year : 2019 | Volume
: 1
| Issue : 1 | Page : 15-19 |
|
Association of social support and myocardial infarction: A case-control study
MT Manoj1, KA Joseph2, Govindan Vijayaraghavan1, A Joseph1
1 Society for Continuing Medical Education & Research (SOCOMER), Kerala Institute of Medical Sciences, Thiruvananthapuram, Kerala, India
2 Department of Social Work, Loyola College of Social Sciences, Thiruvananthapuram, Kerala, India
| Date of Submission | 02-Nov-2019 |
| Date of Acceptance | 06-Nov-2019 |
| Date of Web Publication | 13-Dec-2019 |
Correspondence Address:
Dr. M T Manoj
Senior Manager, SOCOMER, Kerala Institute of Medical Sciences, Anayara P.O., Thiruvananthapuram - 695 029, Kerala
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/ACCJ.ACCJ_8_19
Background: Social support plays an important role in the promotion and maintenance of our health. Lack of social support leads to various health issues including heart diseases, especially myocardial infarction (MI). Studies investigating the association between lack of social support and MI are very limited among our population. Therefore, the current study was carried out for determining the effect of social support on the incidence of MI. Materials and Methods: We using convenient sampling method recruited a total of 150 each case (with MI) and controls (without MI) who were matched for age and gender during September 2016 and August 2017 into the study from a tertiary care hospital in Kerala. The design we employed for this study was a case–control study design. Results: Among the cases, 35.3% reported low levels of social support as against 21.3% among controls. Multivariate logistic regression analysis after adjusting for the confounders indicated that low level of social support is positively and statistically significantly associated with MI (odds ratio 2.541; 95% confidence interval: 1.121–5.761, P = 0.026). Conclusion: Low social support is associated with the incidence of MI. Keywords: Coronary heart disease, myocardial infarction, psychosocial risk, social support
How to cite this article:
Manoj M T, Joseph K A, Vijayaraghavan G, Joseph A. Association of social support and myocardial infarction: A case-control study. Ann Clin Cardiol 2019;1:15-9 |
How to cite this URL:
Manoj M T, Joseph K A, Vijayaraghavan G, Joseph A. Association of social support and myocardial infarction: A case-control study. Ann Clin Cardiol [serial online] 2019 [cited 2023 Mar 24];1:15-9. Available from: http://www.onlineacc.org/text.asp?2019/1/1/15/273005 |
| Introduction | |  |
Cardiovascular diseases (CVD) refer to any disease that affects the cardiovascular system, principally cardiac diseases, vascular diseases of the heart, brain and kidney, and peripheral arterial diseases.[1] The major and more common CVD are atherosclerosis, cardiovascular inflammation, rheumatic heart disease, and coronary heart disease (CHD).
CHD does not inevitably occur with age, but is the result of biological, behavioral and environmental factors and thus can be viewed as a disorder of lifestyle.[2] Several known risk factors for CHD have been identified, and they are divided into modifiable and nonmodifiable risk factors. The common modifiable risk factors are dyslipidemias, hypertension, smoking, diabetes, abdominal obesity, irregular consumption of fruits and vegetables, physical inactivity, alcohol intake, and psychosocial factors[3] and the nonmodifiable risk factors are sex, age, family history, and genetic factors.[4],[5],[6] The focus of the current study was social factors with special reference to social support associated with the incidence of CHD.
Social support is an individual's self-perception of his or her degree and quality of intimate social ties, such as marital status, cohabitation, availability and size of the social network, the regularity of social activities, and group association.[7] Accordingly, it is concerned with a person's interactions, interpersonal relationships, and other extracurricular activities. Increased perceived social support is found to be beneficial in mitigating the incidence and outcome of myocardial infarction (MI), a serious type of CHD. Decreased social support plays a major role in both the incidence and the outcome of MI.[7]
Various types of social support are: esteemed support (emotional, expressive, or close support), informational support (advice, appraisal support or cognitive guidance), social companionship (spending time and sharing leisure activities with others), and instrumental/tangible support (having material assistance such as financial support, material resources, and other services and facilities.[8] These psychological and material supports have an effect on our health through neuroendocrine, emotional, cardiovascular, and immune-inflammatory pathways or help the individuals to take on effective lifestyle models and balance of the physiological process.[9],[10]
Social support offers also a protective effect against CHD progression and death by increased adherence to medical therapies and lifestyle modifications, reducing the negative emotional interfaces.[11] Furthermore, it provides a cushioning effect against stress, disengages people from risky behaviors such as excessive consumption of nicotine, alcohol, or narcotics and reinforcing healthy behaviors, thereby preventing health problems.[12]
Loneliness or poor social relationships account for a 29% increase of CHD among healthy people.[13] Individuals who lack in social support will be likely to remain lonely. Loneliness has a potentially negative effect on our biological stress responses and would be injurious to one's health.[14] Patients with low social support have higher fibrinogen and D-dimer levels.[15] D-dimer is a small protein fragment present in the blood after a blood clot is broken up and is degraded by fibrinolysis,[16] which is the enzymatic breakdown of the fibrin in blood clots. Higher fibrinogen and D-dimer levels expose people to a higher incidence of MI events.[17]
Studies on the influence of psychosocial risk factors on the incidence of MI have been going on in the Western countries over several years, and they have clearly identified and established a link between psychosocial factors and MI in their population. There is a paucity of information on the association between the two in our population. The data from the Western population may not be relevant to our population as there are differences between the two populations in socio-demographic and political conditions, cultural values, living environment, nutrition intake, etc., In order to fill up this lacuna, the current study was undertaken with the objective of assessing the effect of social support on the incidence of MI.
| Materials and Methods | | |
Study design and setting
The study is a case–control study and the setting for the study was Kerala Institute of Medical Sciences (KIMS), which is a 650-bedded hospital located in Trivandrum District of Kerala.
Selection of participants
We used a convenient sampling method and recruited patients (n = 150) with first episode of MI (incident cases) diagnosed with per the hospital protocol[18] and those satisfying the inclusion criteria (between the age of 25 and 65 years, both males and females living in-and-around Trivandrum District) admitted to the inpatient wards of the Department of Cardiology during the study period (from August 2016 to September 2017) were enrolled into the study as “cases.” An equal number of age- and gender-matched consecutive patients (n = 150), who satisfied the inclusion criteria (in-patients admitted to the General Medicine Department during the study period, between the age of 25 and 65 years, both males and females and living in-and-around Trivandrum District), were selected as controls. Patients with unproven MI, history of any other cardiac disease, current or past history of psychiatric illness, those on antipsychotic medications, other major diseases (AIDS, cancer, chronic obstructive pulmonary disease, and physical deformations), and nonconsenting patients were excluded from the study. Controls were matched on age and sex of the cases as both age and sex are commonly matched factors.[19] We recruited the controls that were similar in age and sex to the cases around the same date and evaluated the risk factors to ensure that the underlying exposures were not affected by the time of recruitment of both cases and controls.
Study variables
A standard demographic questionnaire was designed for recording details on gender, domicile, age, religion, marital status, living status, details of consumption of alcohol, smoking, and regular physical exercise. Details on education, occupation and monthly income were obtained using Updated Kuppuswamy's socioeconomic scale.[20]
Social support was evaluated using a multidimensional scale of perceived social support (MSPSS).[21] It addresses the subjective assessment of social support adequacy from three specific sources: family, friends, and significant others. The MSPSS consists of 12 items that are rated by the study participants on a 7-point Likert scale, with scores ranging from very strongly disagree (1) to very strongly agree (7). The scoring pattern the scale (very strongly disagree, strongly disagree, mildly disagree, neutral, mildly agree, strongly agree, and very strongly agree) was divided into three categories: low support (clubbing very strongly disagree + strongly disagree), moderate (mildly disagree + neutral + mildly agree), and high (strongly agree + very strongly agree) for facilitating the analysis in this study. A benefit of using the MSPSS is that it includes psychometric qualities. Cronbach's alpha calculated was α = 0.88. Test-retest reliability was at r = 0.85.[21] Prior permission for usage of the instrument was obtained from the Author, Greg Zimet.
The reliability of the questionnaires in the current study was not tested among the study population (MI patients) earlier, and therefore, we validated the questionnaires in the study population. We used the test-retest reliability method to check the reliability of the English and Malayalam questionnaires, and both scales (both English version and translated version) had good reliability scores (“r” >0.70).
Sample size
Based on the proportion of cases and controls with low social support (39.3 and 60.7, respectively) found in a previous study in a comparable setting,[22] the sample size estimated for the present study was 150 in each group with 90% confidence interval (CI) and 80% power. Therefore, a total of 150 cases and 150 controls were included in the study.
Data collection methodology
The details of the medical conditions of the patients admitted to the in-inpatient wards of Cardiology department (cases) and Medicine Department (controls) were obtained from the electronic medical records (EMR) of the Hospital. Permission for accessing the EMR was obtained from the Hospital Management and permission for including the patient in the study was taken from the treating physicians. The Institutional Human Ethics Committee of the hospital approved the study protocol and documents before starting the enrollment of the study participants.
The first author approached the patients who satisfied the inclusion criteria and described the purpose of the study as well as risks and benefits of participating in the study after giving the patient information sheet. He explained that they could decide not to take part in the study without any penalty or loss of benefits. Participants were given time to decide on their participation and also asked questions. After clarifying the doubts of the patients, consent was obtained on an informed consent form from all the patients and the study questionnaires were handed over to them with the request to return the completed questionnaires within 3–4 h. The methodology adopted for collecting data was self-administration by the patients. The median time of administration of the questionnaires to the patients was within 1 week of presentation at the hospital.
Data analysis
We carried out a descriptive analysis (frequencies and percentages for categorical variables) of all the demographical and clinical variables of cases and controls to obtain a clear picture of the study variables.
Conditional logistic regression was used as the statistical analysis method since the current research design is a retrospective, matched case–control study. First, the association of psychosocial factors and MI was measured using the Chi-square test. Subsequently, the variables found significantly associated with MI were analyzed using univariate logistic regression analysis (also known as bivariate analysis). The adjusting of variables, which were found to be associated (confounding) to MI from the analysis of sociodemographical, was not possible with univariate logistic regression analysis. Hence, multivariate logistic regression analysis was performed to find the strength of the association of variables after adjusting for confounding variables. Statistical significance was determined by estimating the odds ratio (OR) and P value.
We used the imputation method for replacing the missing data using, Statistical Package for Social Sciences (SPSS), version 16.0 (Chicago, SPSS Inc). Imputation is a process of replacing the missing data with the estimated value of the actual existing data.
| Results | | |
Majority of the cases were from urban areas (56.0%), whereas the majority of the controls (62.7%) belonged to rural areas. Among the cases, 79.3% were married as against 89.3% of the controls and 14.7% of cases were divorced as against 10.7% of the controls and 6.0% of the cases were unmarried as against none in the control group. Only 69.3% of controls were living with their family as compared to 84.7% of the controls, and 21.7% of controls were living with others (friends, distant relatives, shelter homes, etc.,) as against 6.0% of the controls.
Statistically, more proportion of cases were seen to be consuming alcohol (36.7% of cases vs. 24.0% of controls) and were smoking (59.3% of cases vs. 26.0% of controls) as well. Only 32.0% of cases had regular exercise as against 60.7% controls). However, the cases and controls were comparable with regard to the history of cardiac diseases.
Association of social support and myocardial infarction
Among the cases, 36.0% had moderate social support as compared to 32.7% of the controls, and 35.3% of cases had low social support as compared to 21.3% of the controls (P = 0.003) [Table 1].
Univariate and multivariate regression analyses
Univariate logistic regression analysis revealed that moderate and low levels of social support were positively and significantly associated with MI: OR 1.768; 95% CI: 1.028–3.043, P = 0.040 and OR 2.658; 95% CI: 1.487–4.751, P = 0.001, respectively [Table 2].
Multivariate logistic regression analysis after adjusting for confounders indicated a positive association between moderate level of social support and MI, but the association was not statistically significant (OR 1.602; 95% CI: 0.754–3.402, P = 0.220). A low level of social support was positively and significantly associated with MI: (OR 2.541; 95% CI: 1.121–5.761, P = 0.026) [Table 3].
| Discussion | | |
There are evidence to suggest that social support provides a protective effect against cardiac events,[11] by reducing stress, refraining people from the usage of alcohol and addictive drugs, and reinforcing healthy behaviors.[12] An unfailing support system from family and friends also reduces the risk from mental and physical illnesses.[23] The study also found that individuals with low social support have higher odds of having an MI when compared to the controls (univariate analysis), and this finding remained significant even after adjusting for confounders in multivariate analysis.
Our results are in concordance with the findings of several previous studies,[24],[25],[26] which also found that socially isolated people are at a higher risk of having MI. Epidemiological studies[27],[28],[29],[30] also provide evidence that low social support is associated with increased cardiovascular mortality and other risks.
However, better social support alone does not lessen the risk for heart diseases; the quality of the relationships also matters. It is most likely that individuals who are influenced negatively by his or her social network are likely to have habits such as smoking and alcoholism or poor dietary habits,[31],[32] suggesting that social relationships can influence individuals negatively or positively. Socially isolated individuals are also at risk of developing CHD risk factors such as smoking and alcoholism,[33] indicating that lack of social ties may promote detrimental behaviors.
Steptoe et al.[14] observed that socially isolated people would remain lonely and this loneliness influences their biological stress responses and neuroendocrine and inflammatory processes. Low social support increases the blood levels of fibrinogen and D-dimer[15] and aids in the development of atherosclerosis,[33] which subsequently leads to cardiac events.
Our study is probably the first well-designed study in India, assessing the effect of social support on the incidence of MI. We have used a demographically matched comparison group controlling for age and sex. We have also used a standardized questionnaire which was validated in our population in this study. Although the sample size was small, this study has a robust sample size necessary to demonstrate an association between psychosocial factors and MI. The retrospective nonrandomized design and usage of the convenient sampling method were limitations in our study. Recall bias is an important issue in case–control studies and our study also has the same problem. Although the questionnaire was validated using a small sample size in our study, the validity is yet to be established with a large sample size.
| Conclusion | | |
Low social support was found to be a risk factor for the incidence of MI.
Acknowledgement
We are grateful to Dr. C. C. Kartha, Sr. Advisor, SOCOMER, Dr. P. M. Saffia, Vice Dean, Academics, and Mrs. Shyla Shaji, Deputy Manager, Academics, Kerala Institute of Medical Sciences, Trivandrum, Kerala, for their unwavering support and sharing pearls of wisdom with us during the drafting of this article. Also, thankful to Ms. Anju Eldhose, Biostatistician, KIMS, Trivandrum for the great support in statistical matters.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Institute of Medicine (US) Committee on Preventing the Global Epidemic of Cardiovascular Disease: Meeting the Challenges in Developing Countries. Fuster V, Kelly BB, editors. Promoting Cardiovascular Health in the Developing World: A Critical Challenge to Achieve Global Health. The National Academies Collection: Reports funded by National Institutes of Health. Washington (DC): National Academies Press (US); 2010. Available from: http://www.ncbi.nlm.nih.gov/books/NBK45693/. [Last accessed on 2018 Mar 20].  |
| 2. | Krantz DS, Contrada RJ, Hill DR, Friedler E. Environmental stress and biobehavioral antecedents of coronary heart disease. J Consult Clin Psychol 1988;56:333-41. |
| 3. | Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): Case-control study. Lancet 2004;364:937-52. |
| 4. | Lerner DJ, Kannel WB. Patterns of coronary heart disease morbidity and mortality in the sexes: A 26-year follow-up of the Framingham population. Am Heart J 1986;111:383-90. |
| 5. | Samani NJ, Erdmann J, Hall AS, Hengstenberg C, Mangino M, Mayer B, et al. Genomewide association analysis of coronary artery disease. N Engl J Med 2007;357:443-53. |
| 6. | Yoon PW, Scheuner MT, Peterson-Oehlke KL, Gwinn M, Faucett A, Khoury MJ. Can family history be used as a tool for public health and preventive medicine? Genet Med 2002;4:304-10. |
| 7. | Burg MM, Barefoot J, Berkman L, Catellier DJ, Czajkowski S, Saab P, et al. Low perceived social support and post-myocardial infarction prognosis in the enhancing recovery in coronary heart disease clinical trial: The effects of treatment. Psychosom Med 2005;67:879-88. |
| 8. | Uchino BN. Social support and health: A review of physiological processes potentially underlying links to disease outcomes. J Behav Med 2006;29:377-87. |
| 9. | Cohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol Bull 1985;98:310-57. |
| 10. | Uchino BN. Understanding the links between social support and physical health: A life-span perspective with emphasis on the separability of perceived and received support. Perspect Psychol Sci 2009;4:236-55. |
| 11. | Krumholz HM, Butler J, Miller J, Vaccarino V, Williams CS, Mendes de Leon CF, et al. Prognostic importance of emotional support for elderly patients hospitalized with heart failure. Circulation 1998;97:958-64. |
| 12. | Umberson D. Family status and health behaviors: Social control as a dimension of social integration. J Health Soc Behav 1987;28:306-19. |
| 13. | Valtorta NK, Kanaan M, Gilbody S, Ronzi S, Hanratty B. Loneliness and social isolation as risk factors for coronary heart disease and stroke: Systematic review and meta-analysis of longitudinal observational studies. Heart 2016;102:1009-16. |
| 14. | Steptoe A, Owen N, Kunz-Ebrecht SR, Brydon L. Loneliness and neuroendocrine, cardiovascular, and inflammatory stress responses in middle-aged men and women. Psychoneuroendocrinology 2004;29:593-611. |
| 15. | Wirtz PH, Redwine LS, Ehlert U, von Känel R. Independent association between lower level of social support and higher coagulation activity before and after acute psychosocial stress. Psychosom Med 2009;71:30-7. |
| 16. | Furie B, Furie BC. Mechanisms of thrombus formation. N Engl J Med 2008;359:938-49. |
| 17. | Woodward M, Rumley A, Welsh P, MacMahon S, Lowe G. A comparison of the associations between seven hemostatic or inflammatory variables and coronary heart disease. J Thromb Haemost 2007;5:1795-800. |
| 18. | Cannon CP, Brindis RG, Chaitman BR, Cohen DJ, Cross JT Jr., Drozda JP Jr., et al. 2013 ACCF/AHA key data elements and definitions for measuring the clinical management and outcomes of patients with acute coronary syndromes and coronary artery disease: A report of the American College of Cardiology Foundation/American Heart Association task force on clinical data standards (Writing committee to develop acute coronary syndromes and coronary artery disease clinical data standards). Circulation 2013;127:1052-89. |
| 19. | Rothman KJ. Modern Epidemiology. Vol. 6. Boston, Mass: Little, Brown; 1986. p. 358. |
| 20. | |
| 21. | Zimet GD, Dahlem NW, Zimet SG, Farley GK. The multidimensional scale of perceived social support. J Pers Assess 1988;52:30-41. Available from: https://doi.org/10.1207/s15327752jpa5201_2. [Last accessed on 2018 May 04]. |
| 22. | Angerer P, Siebert U, Kothny W, Mühlbauer D, Mudra H, von Schacky C. Impact of social support, cynical hostility and anger expression on progression of coronary atherosclerosis. J Am Coll Cardiol 2000;36:1781-8. |
| 23. | |
| 24. | Ali SM, Merlo J, Rosvall M, Lithman T, Lindström M. Social capital, the miniaturisation of community, traditionalism and first time acute myocardial infarction: A prospective cohort study in Southern Sweden. Soc Sci Med 2006;63:2204-17. |
| 25. | Orth-Gomér K, Rosengren A, Wilhelmsen L. Lack of social support and incidence of coronary heart disease in middle-aged Swedish men. Psychosom Med 1993;55:37-43. |
| 26. | van den Broek KC, Martens EJ, Nyklícek I, van der Voort PH, Pedersen SS. Increased emotional distress in type-D cardiac patients without a partner. J Psychosom Res 2007;63:41-9. |
| 27. | Berkman LF, Syme SL. Social networks, host resistance, and mortality: A nine-year follow-up study of Alameda county residents. Am J Epidemiol 1979;109:186-204. |
| 28. | Blazer DG. Social support and mortality in an elderly community population. Am J Epidemiol 1982;115:684-94. |
| 29. | House JS, Landis KR, Umberson D. Social relationships and health. Science 1988;241:540-5. |
| 30. | Manoj M, Joseph K, Vijayaraghavan G. Association of depression, anxiety, and stress with myocardial infarction: A case – Control study. J Clin Prev Cardiol 2018;7:86. Available from: http://www.jcpconline.org/text.asp?2018/7/3/86/236330. [Last accessed on 2018 Jul 21]. |
| 31. | Antonucci TC, Ajrouch KJ, Birditt KS. The convoy model: Explaining social relations from a multidisciplinary perspective. Gerontologist 2014;54:82-92. |
| 32. | Fiori KL, Jager J. The impact of social support networks on mental and physical health in the transition to older adulthood: A longitudinal, pattern-centered approach. Int J Behav Dev 2012;36:117-29. Available from: http://journals.sagepub.com/doi/10.1177/0165025411424089. [Last accessed on 2018 Nov 09]. |
| 33. | |
[Table 1], [Table 2], [Table 3]
|
Search Pubmed for