Skip to main content

Single living predicts a higher mortality in both women and men with chronic heart failure

Shan Mard1 & Finn Erland Nielsen2, 3,

1. sep. 2016
14 min.

Faktaboks

Fakta

Approximately 1-2% of the adult population has heart failure (HF) [1]. Almost 50% of patients with HF die
within four years [1].

Several prognostic determinants have been identified in patients with HF [1]. Social support has a significant impact on health and well-being in general [2], and it has been associated with better self-care and good treatment adherence among patients with HF [3]. Single living is an easy-to-measure proxy for a low level of social support in a wide variety of patient populations, and several studies have shown a negative impact of single living on survival [4, 5]. Although studies suggest an association between social support and outcome among patients with HF, there are conflicting results [6-9]. Furthermore, there are also conflicting data regarding differences in relative risk between genders [5, 10-12].

Hence, we examined the prognostic impact of single living on all-cause long-term mortality among patients with chronic HF and whether the association between single living and mortality varied by gender.

METHODS

Patients referred to the outpatient clinic (OPC) and HF clinic (HFC) or admitted to the ward of the Department of Cardiology, Herlev Hospital, Denmark, during the
period from 1 July 2005 to 30 June 2007 and discharged with a HF diagnosis were identified through the Danish National Registry of Patients (DNRP). The first hospital contact for HF within that period was registered as the index hospital contact. The positive predictive value of the HF diagnosis in the DNRP is relatively high [13]. Information about the diagnoses was coded according to the International Classification of Diseases, tenth edition (ICD-10). The codes used for identification of patients with HF were I11.0, I13.0, I13.2, I42.0, I42.6-9, I50.0-1 and I50.9.

Medical records were reviewed during the period from 1 October 2009 to 23 March 2010. We obtained information on age, gender, single living or living with a partner, weight, height, tobacco use and alcohol consumption, results of laboratory tests, whether the patients fulfilled the HF criteria [14], New York Heart Association functional class, history of ischaemic heart disease, history of valve disease and other co-morbidities at the time of the index hospital contact. All descriptions of the first echocardiographic examination performed either in the ward, the OPC or the HFC at the index hospital contact were reviewed for information on left ventricular ejection fraction (LVEF) and severity of valve diseases. LVEF was usually assessed visually by the operators. Mitral valve regurgitation (MVR) was most often measured semi-quantitatively by assessing the regurgitation jet area by colour Doppler and was classified as either absent or as one of the three progressive degrees of severity of mild, moderate or severe MVR. The degree of aortic stenosis (AS) was classified as absent, mild, moderate or severe depending on the reported figures for the maximum transaortic pressure gradient and the aortic valve area. Pulmonary hypertension was suspected when the maximum velocity of the tricuspid regurgitation jet exceeded 36 mmHg.

Information on pulmonary congestion was obtained from the descriptions of the chest X-ray. From records we obtained information on medical treatment, whether the patients were referred to the HFC or the OPC after discharge, and readmissions during the following year. The patients were registered as having been treated with angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, beta-blockers or aldosterone antagonists if they were treated with at least one of the agents at the index hospital contact or if the treatment was initiated within a period of three months after their index hospital contact. Data on death during the follow-up period were obtained from the Danish Civil Registration System. The study was performed as a part of a quality assurance HF project [13], and was registered and approved by the Danish Data Protection Agency (2008-41-2889).

Statistics

Data were analysed using Stata 13.1 (StataCorp, College Station, Texas, USA).

All patients were observed from the date of index hospital contact until death or end of follow-up, whichever came first. End of follow-up was the day patients’ records were reviewed. The assumption of normality of continuous data was evaluated by normal probability plots. Normally distributed data were summarised as mean and standard deviation (SD); others were summarised as median, interquartile range (IQR) and range. Categorical variables were reported as frequencies and percentages. Differences in baseline variables were estimated by Fisher’s test (categorical variables), Wilcoxon rank-sum test (non-normally distributed variables) and t-test (normally distributed variables). The relation between the hazard function and the covariates was modelled by Cox proportional-hazard regression. Selection of the variables in the models was based on an a priori decision of important variables in combination with the results of the crude associations between the variables and death. Initially, a model containing all baseline variables associated with death at the 25% level in the crude analyses was fitted. The model selection procedure also allowed for variable selection based on hypothesised importance, e.g., gender. Various models were compared by examining changes produced in the value of minus twice the logarithm of the maximised likelihood, –2logL, by adding or deleting variables in the model. The smaller the value of –2logL, the better the model. Schoenfeld and Cox-Snell residuals were used to check the assumptions and the overall model fit. A plot of Martingale residuals against covariates was used to detect nonlinearity.

Trial registration: not relevant.

RESULTS

Of 758 patients treated during the study period, 637 (84%) fulfilled the HF criteria [14]. There were 385 (60.4%) men with a mean age of 72.1 years (SD: ± 11.5), and 252 (39.6%) women with a mean age of 76.0 years (SD: ± 11.7) (p < 0.001). A total of 364 (57.1%) patients had a history of ischaemic heart disease, and 303 (47.6%) patients lived alone.

Differences in patient characteristics by single living are provided in Table 1. Single-living patients were older, were more likely to be female and were more likely to have pulmonary congestion. Less single-living patients were examined by echocardiography. However, there were no differences in LVEF. Single-living patients were more likely to have pulmonary hypertension and less likely to be referred to the OPC or the HFC. There were no significant differences in medical treatments. All-cause hospitalisation during the first 12 months after discharge was more frequent among single-living patients; however, this difference was not significant (Table 1). The median follow-up time was 2.8 years (IQR: 1.1-3.7 years, range: 1 day to 4.7 years).

Unadjusted analyses

A total of 323 (50.7%) patients died during the follow-up period. Survival was significantly decreased among single-living patients (Figure 1).

The unadjusted hazard ratios (HR) are given in Table 2. After stratification of living arrangements by gender, it was found that both single-living men and women had a significantly increased risk of death with either men living with a partner (model I) or women
living with a partner (model II) as reference (Table 3). Other variables associated with shorter survival in unadjusted analyses were old age, diabetes, hypertension, stroke, atrial fibrillation, pulmonary congestion, reduced LVEF, moderate and severe MVR, AS, pulmonary hypertension and increasing creatinine (Table 2). Follow-up in the OPC or the HFC clinics, increasing values of body mass index and treatment with angiotensin-converting enzyme inhibitors and angiotensin receptor II blockers were associated with better post-discharge survival (Table 2).

Adjusted analyses

After controlling for potential confounders, single living was found to be associated with all-cause mortality (HR = 1.53 (95% CI: 1.19-1.96)). A Cox proportional model (Table 3) that included living arrangements, stratified by gender, as well as age, diabetes, stroke, LVEF and b was found to be the best model. The risk of death in single-living patients was increased in both men and women.
In a model with men living with a partner as reference, it was found that for both women and men, living alone were associated with mortality (Table 3). For women, living alone was associated with mortality in a model with women living with a partner as reference. The interaction between single living and gender was not significant (p = 0.661) and was therefore not included in the model.

DISCUSSION

We found that single living, used as a proxy for lack of social support, was associated with increased long-term all-cause mortality among patients with HF. Furthermore, single living was a predictive factor for mortality in both sexes.

Other studies

Evidence on the role of social support in the prognosis among patients with HF is conflicting [6-9, 15-17]. This may be explained by the different methods used to measure social support and missing consensus on the best definition of social support [4, 6, 18]. In a review of the role of social support on prognosis in HF, two of six studies showed a relation between social support constructs (social isolation, a lower degree of interaction with relatives, friends and community) and mortality among inpatients. The relation was independent of potential confounders [6]. Among outpatients, constructs related to social support were related to mortality in two out of four studies, independently of biomedical factors [6].

Our finding that single living was associated with a greater risk of death among patients with HF is in accordance with the literature describing the association between social support, marital status, living arrangements and outcome among patients with ischaemic heart disease [4, 10-11], and other conditions such as cancer, chronic pulmonary disease, stroke and alcohol consumption [19]. Living with a partner has been associated with longer survival in patients with diastolic HF [9], and in a smaller study of patients with HF recruited from an outpatient clinic [20]. In contrast hereto, marital status was not a significant variable for in-hospital death or for time to readmission for HF in one study of HF [8].

The hazard ratios for women and men were relatively imprecise in our study. Therefore, we could not conclude if the association between single living and mortality was stronger for one of the sexes. However, recent meta-analyses of the mortality for singles have shown that the risk of death has become approximately equal for men and women and that the historical gender difference in risk has decreased slightly because the risk for women has increased at a faster rate than the risk for men [5].

Pathophysiological mechanisms

Mechanisms whereby social support and single living can influence the outcome in patients with HF are not well defined. Potential biological and psychosocial pathophysiological mechanisms described in the literature include cardiovascular, immune and endocrine processes, psychological distress and inappropriate health behaviour [6]. A poor social network may generate anxiety and stress, which stimulates the sympathetic nervous, hypothalamus-pituitary-adrenal and renin-angiotensin-aldosterone systems and causes damage to the arterial wall and to the myocardium [6]. A poor social network and poor social support are also associated with a higher frequency of depression, leading to a
poorer prognosis in HF, and influences access to health services and treatment compliance and thereby influences progression of the disease [6]. Social support has impact on self-care and behaviours among patients with HF, which in turn has an impact on prognosis [3, 6].

Clinical implications

Our findings have potentially important clinical implications. Living arrangement is a simple measure that can identify patients with HF who have a higher risk of mortality. Although there are no interventions for living arrangements with a documented effect on adverse
outcomes among patients with HF, we emphasise the importance of assessing living arrangements as a part of risk stratification. More research is needed to identify interventions that might minimise the negative effects of single living. Identification of those at increased risk of worsening outcomes may lead to improved intervention strategies, thereby reducing the negative effects of single living on outcome.

Limitations

This study has several limitations. Due to the historical cohort design, we have no control over the quality of the baseline measurements. The control for confounding might therefore have been incomplete. We have not measured socioeconomic status or depressive symptoms, which are common in patients with HF [4, 6]. Both factors are potential causal pathways and mediating factors with potential confounding properties. The duration of single living was not known in our study. The living arrangements of patients could have changed during the follow-up period, causing misclassification of the social status. In addition, the quality of the living arrangements and social support were not studied and could have contributed to the risk of cardiovascular disease. Finally, the small sample size increased the risk of limited precision of the estimates. Despite these limitations, the results of the present study strongly indicated that social isolation, defined as single living, was a risk for death in patients with HF.

CONCLUSION

Single living is associated with increased mortality in male and female patients with chronic HF. Further
studies should confirm our findings and define the underlying mechanisms responsible for this association.

Correspondence: Finn Erland Nielsen. E-mail: fien@regionsjaelland.dk

Accepted: 6 June 2016

Conflicts of interest:Disclosure forms provided by the authors are available with the full text of this article at www.danmedj.dk

Referencer

REFERENCES

  1. McMurray JJ, Adamopoulos S, Anker SD et al. ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure 2012. Eur Heart J 2012;33:1787-47.

  2. House JS, Landis KR, Umberson D. Social relationships and health. Science 1988;241:540-5.

  3. Sayers SL, Riegel B, Pawlowski S et al. Social support and self-care of patients with heart failure. Ann Behav Med 2008;35:70-9.

  4. Schmaltz HN, Southern D, Ghali WA et al. Living alone, patient sex and mortality after acute myocardial infarction. J Gen Intern Med 2007;22:
    572-8.

  5. Roelfs DJ, Shor E, Kalish R et al. The rising relative risk of mortality for singles: meta-analysis and meta-regression. Am J Epidemiol 2011;174:379-89.

  6. Pelle AJM, Gidron YY, Szabo BM et al. Psychological predictors of prognosis in chronic heart failure. J Cardiac Fail 2008;14:341-50.

  7. Chung ML, Lennie TA, Riegel B et al. Marital status is an independent predictor of event-free survival of patients with heart failure. Am J Crit Care 2009;18:562-70.

  8. Watkins T, Mansi M, Thompson J et al. Effect of marital status on clinical outcome of heart failure. J Investig Med 2013;61:835-41.

  9. Schockmel M, Agrinier N, Jourdain P et al. Socioeconomic factors and mortality in diastolic heart failure. Eur J Clin Invest 2014;44:372-83.

  10. Kitamura T, Sakata Y, Nakatani D et al. Living alone and risk of cardiovascular events following discharge after acute myocardial infarction in Japan. J Cardiol 2013;62:257-62.

  11. Lammintausta A, Airaksinen JK, Immonen-Räihä P et al. Prognosis of acute coronary events is worse in patients living alone: the FINAMI myocardial infarction register. Eur J Prev Cardiol 2014;21:889-96.

  12. Manzoli L, Villari P, M Pirone G et al. Marital status and mortality in the elderly: a systematic review and meta-analysis. Soc Sci Med 2007;64:77-94.

  13. Mard S, Nielsen FE. Positive predictive value and impact of misdiagnosis of a heart failure diagnosis in administrative registers among patients admitted to a University Hospital cardiac care unit. Clin Epidemiol 2010;2:235-9.

  14. Dickstein K, Cohen-Solal A, Filippatos G et al. ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2008: The Task Force for Diagnosis and Treatment of Acute and Chronic Heart Failure 2008 of the European Society of Cardiology. Eur J Heart Fail 2008:933-89.

  15. Heo S, Moser DK, Chung ML et al. Social status, health-related quality of life, and event-free survival in patients with heart failure. Eur J Cardiovasc Nurs 2012;11:141-9.

  16. Chin MH, Goldman L. Correlates of early hospital readmission or death in patients with congestive heart failure. Am J Cardiol 1997;79:1640-4.

  17. Metayer CM, Coughlin SS, McCarthy EP. Marital status as a predictor of survival in idiopathic dilated cardiomyopathy: The Washington, DC dilated cardiomyopathy study. Eur J Epidemiol 1996;12:573-82.

  18. Tsuchihashi-Makaya M, Kato N, Chishaki A et al. Anxiety and poor social support are independently associated with adverse outcomes in patients with mild heart failure. Circ J 2009;73:280-7.

  19. Ng TP, Jin A, Feng L et al. Mortality of older persons living alone: Singapore Longitudinal Ageing Studies. BMC Geriatrics 2015;15:126.

  20. Chung ML, Lennie TA, Riegel B et al. Marital status is an independent predictor of event-free survival of patients with heart failure. Am J Crit Care 2009;18:562.