Impact of social factors on patients on peritoneal dialysis

Kai Ming Chow, Cheuk Chun Szeto, Chi Bon Leung, Man Ching Law and Philip Kam-Tao Li

Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, China

Correspondence and offprint requests to: Dr K. M. Chow, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong, China. Email: Chow_Kai_Ming{at}alumni.cuhk.net



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. Clinical outcomes among patients on peritoneal dialysis (PD) might not be linked to medical factors alone. We studied the clinical impact of various social factors among patients on PD.

Methods. In a cohort of 102 consecutive patients who started PD in a single centre between 2003 and 2004, we evaluated the effects of social factors on the development of peritonitis and risk of hospitalization after initiation of PD.

Results. Of 102 incident PD patients, 35 subjects (34.3%) were referred to nephrologists more than 3 months before dialysis initiation. During 85.7 patient-years of observation (median follow-up, 10.7 months), four subjects died and six underwent kidney transplantation. Patients receiving social security assistance and those younger than 40 years fared worse than others in terms of their risk of peritonitis. Mean peritonitis-free time for subjects who were on social security assistance was 2.7 months, and for those who were not, 16.4 months (P = 0.045). In the Cox proportional hazards analysis, need for social security assistance and illiteracy were the only statistically significant factors associated with the time to a first peritonitis, after adjustment for social characteristics and relevant coexisting medical factors. Dependence on social security assistance prior to PD was associated with a >2-fold increased likelihood of peritonitis, with an adjusted risk ratio of 2.69 (95% confidence interval, 1.10 to 6.54; P = 0.029). The total number of hospitalization days was similar between those who received social security assistance and those who did not: 17.4±14.6 days (range, 4–50 days) vs 17.9±14.0 days (range, 0–60 days) (P = 0.89).

Conclusions. Our results confirm that socioeconomic status is closely associated with the rate of peritonitis among PD patients. The long-term reliability of these social predictors remains to be validated.

Keywords: illiteracy; peritoneal dialysis; peritonitis; social security assistance; social support; socioeconomic status



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Clinical outcomes among the peritoneal dialysis (PD) population have long been linked to medical factors, but most previous studies have not considered the influence of social factors. Increasing evidence points to the role, at least partial, of those factors in the clinical course of various chronic illnesses [1,2]. In particular, factors such as family or social support and financial status have been shown to predict mortality among end-stage renal disease patients on haemodialysis [3–7]. Although all of them concern haemodialysis patients, these observations suggest that there may be a relationship between social factors and patients’ clinical outcomes in the dialysis setting. As opposed to haemodialysis, PD is a home-based renal replacement therapy; and it might intuitively be suspected to be much more influenced by the social background. Nonetheless, there is a lack of data in this regard. To examine the clinical impact of various social factors on PD outcomes, we undertook this retrospective observational cohort study and evaluated 102 consecutive incident PD patients. Better understanding of such social, non-medical factors will pinpoint the future targets of the multidisciplinary management of chronic kidney disease.



   Subjects and methods
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
The population of this retrospective observational study consisted of all incident patients who began PD at our unit between May 2003 and December 2004. To minimize potential bias, we restricted our analysis to those patients for whom PD was the primary renal replacement therapy, i.e. patients starting or returning to PD after a failed transplant were excluded.

Patients were followed until death or 31st December 2004, after which point their data were censored. Data were obtained from patient records, the electronic databases of renal replacement therapy registries and medical social worker reports. The data collected covered demographic characteristics, patients’ primary renal diseases, comorbidities (coronary artery disease, peripheral artery disease, cerebrovascular disease, hypertension, hepatitis B surface antigen status, liver cirrhosis, systemic lupus erythematosus, diabetes mellitus), and anthropometric data at the start of dialysis. Patients were further categorized according to whether they attended the low clearance clinic for at least 3 months (early referral) or for less than 3 months (late referral) before starting PD. The normalized protein equivalent of total nitrogen appearance (nPNA) of a patient was assessed by standard methods within 30 days of the start of PD. Residual kidney function was measured by urinary creatinine clearance within the first month after initiation of dialysis. PD was performed using disconnect systems [Baxter, SpA (Deerfield, IL) and Fresenius Medical Care (Deutschland GmbH) with lactate-buffered glucose-containing dialysate solutions]. In all cases, a prophylactic antibiotic, cefazolin, was administered prior to the surgical placement of the Tenckhoff catheter. Dialysis was initiated after a break-in period of 4 weeks after catheter placement. The standard continuous ambulatory peritoneal dialysis training program lasted for 4–5 days. Topical mupirocin, with or without oral rifampin, was administered to patients who were nasal carriers of Staphylococcus aureus or who had S.aureus exit-site infections or peritonitis.

The social variables of interest included marital status, living arrangement (living alone vs living with family), educational level (illiteracy, less than high school graduate, high-school diploma, tertiary education), occupational status (working full-time vs unemployment or retirement) and living condition (government subsidized rental housing vs ownership of housing). In addition, residential surface area (based on patients’ reports and home visit observations) was analyzed as a socioeconomic indicator. We also defined patients’ socioeconomic status according to whether or not they needed social security assistance at the time they started dialysis. The Comprehensive Social Security Assistance Scheme, the mainstay of Hong Kong's social security system, enables us to determine the financial status of our subjects without regard to any physical disability they may have. As mandated, this scheme provides cash assistance to individuals in financial hardship, who meet stipulated supplementary household income criteria (including properties, cash, savings, investments and other assets) and residency requirements. Eligibility for the social security allowance is taken to indicate that the total assessable monthly income of the patient and his or her family is insufficient to meet their household's total needs; and thus in this study it is chosen as a proxy indicator of poverty. Notwithstanding the theoretical advantages of using household income as a quantified marker of socioeconomic status, the dependence on social security assistance provides another convenient and relatively reliable indicator of the patients’ social support and socioeconomic well-being.

Statistical analysis
In terms of dialysis outcomes, we measured the chance of developing dialysis-related peritonitis and the risk of hospitalization. Time intervals to the first peritonitis episode were examined using standard survival methodology. Hospitalizations were recorded, and they were expressed as total days in hospital per patient-year after the start of renal replacement therapy.

Statistical analysis was performed by the SPSS software for Windows, version 11.5 (SPSS Inc., Chicago, IL). All data were expressed as mean±SD for normally distributed data and as median or range for skewed data. Statistical comparisons were performed using the unpaired Student's t-test; comparisons of percentages between groups were made with the {chi}-square test or Fisher's exact test, as appropriate. A multivariate logistic regression model was built to test for the predictors of delayed nephrologist referral, after adjusting for an a priori set of co-variables. Actuarial survival curves were determined according to the Kaplan–Meier life table method. Analyses were censored at death, transplantation and transfer to haemodialysis or another modality of renal replacement therapy. Stepwise Cox proportional hazards regression was used to predict the risk of developing dialysis-related peritonitis. The dependent variable was the time to a first dialysis-related peritonitis. Significant co-variables, identified in our univariate analysis, and variables shown by previous studies [8,9] to be more likely to influence the risk of peritonitis were entered into the model. The variables used for modelling were patient age, diabetes, baseline serum albumin level, level of literacy and dependence on social security assistance. All probabilities were two-tailed and the level of significance (P) was set at 0.05.



   Results
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
We studied a total of 102 incident PD patients (mean age 57±13 years, range 20–87 years) contributing to a total observation period of 85.7 patient years. The median follow-up was 10.7 months. All patients were Asian, and nearly all of them (98%) were Chinese. During the study, four patients died and six of them underwent kidney transplantation.

In the cohort, 35 incident patients had been referred early to the nephrologist, with a median period of 10.6 months (range 3.1–43 months) before the start of PD. There were significant differences with respect to marital status between those patients referred early to nephrologists vs those referred late. All patients in the early-referred group were married, compared with 88% in the late-referred group, P = 0.048. All of those referred early were older than 40 years; compared with them, 12% of the patients referred late were younger than 40, P = 0.048. Age, sex, primary renal disease, educational level, employment status and housing condition were otherwise similar in the two subgroups. In a multivariate logistic regression model, after controlling for age, gender, literacy, need for social security assistance and primary renal disease, the patients who were not married had a significantly higher odds of being referred late to a nephrologist (odds ratio, 2.66; 95% confidence interval, 1.39–30.30; P = 0.032).

Overall, 31 episodes of peritonitis occurred in 22 of our patients during the study. The peritonitis rate was 0.36 episodes per patient-year, and Gram-positive organisms accounted for 16 episodes of peritonitis (52%). To further evaluate dialysis outcomes, the risk of developing the first peritonitis was estimated taking into consideration various social parameters. The Kaplan–Meier method was used to generate unadjusted estimates of peritonitis-free survival. The time to an initial episode of peritonitis varied significantly in relation to need for social security assistance (Figure 1). Mean peritonitis-free time for the subjects on social security assistance was 16.4 months, worse than for the subjects not on social security assistance, who had a mean peritonitis-free time of 12.7 months (log rank test, P = 0.045). Subjects receiving social security assistance at the time they started dialysis were more likely to reside in rental housing with government subsidy, although their living areas were comparable to those of the patients not requiring social security assistance. Other characteristics of the 20 patients who depended on social security assistance (22%) are shown in Table 1. In particular, there was no statistical difference between the subjects with and without social security assistance in terms of nutritional markers, including serum albumin, nPNA and body mass index. Residual renal function, haematocrit and total Kt/V also did not differ with respect to social security assistance status. There was no difference in the incidence of Gram-positive and Gram-negative peritonitis between the group of patients that did and the ones that did not receive social security assistance (P = 0.60).



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Fig. 1. Probability that PD patients will remain free of peritonitis, according to social security assistance status.

 

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Table 1. Characteristics of the study population, according to dependence on social security assistance

 
In addition, an age less than 40 years at the start of dialysis was associated with an increased risk of developing the first peritonitis (Figure 2). Illiterate subjects showed a trend towards an increased peritonitis risk (Figure 3), although that fell short of statistical significance (mean peritonitis-free time of 11.2 months vs 16.6 months, P = 0.08).



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Fig. 2. Probability that PD patients will remain free of peritonitis, according to patient age.

 


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Fig. 3. Probability that PD patients will remain free of peritonitis, according to educational background.

 
Table 2 lists the results of the Cox proportional hazards analysis for independent predictors of peritonitis. From this model, the two independent predictors of peritonitis were dependence on social security assistance and illiteracy. Dependence on social security assistance prior to PD significantly increased the likelihood of subsequent dialysis-related peritonitis (adjusted risk ratio, 2.69; 95% confidence interval, 1.10–6.54; P = 0.029). Educational level also independently predicted peritonitis after dialysis: the relative risk of peritonitis was 2.73 (95% confidence interval, 1.04–7.20; P = 0.041) among illiterate subjects. Diabetes mellitus was not a significant predictor of peritonitis rates (risk ratio, 2.08; 95% confidence interval, 0.88–4.95; P = 0.096).


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Table 2. Independent predictors of dialysis-associated peritonitis, according to a multivariate Cox regression analysis

 
Finally, the total number of days of hospitalization after starting maintenance PD was similar between the group of patients who did and those who did not receive social security assistance: 17.4±14.6 days (range, 4–50 days) vs 17.9±14.0 days (range, 0–60 days; P = 0.89). Other factors, including marital status, employment state, educational level and social isolation (living alone), did not affect the risk of hospitalization.



   Discussion
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
In a cohort of 102 new PD patients, we found that those patients who required social security assistance prior to PD and illiterate patients had a >2-fold increased risk of developing dialysis-related peritonitis, even after adjusting for several socioeconomic and medical factors. However, none of the previously implicated medical factors, such as baseline serum albumin level and diabetes mellitus [8,9], appear, in multivariate analysis, to contribute to the risk of peritonitis. The relatively short follow-ups of our cohort, however, do not allow us to reliably estimate their risk of hospitalization and mortality.

Our univariate analysis findings regarding the timing of referral to a nephrologist prior to dialysis are consistent with those in the United Kingdom, where patients under the age of 40 years were more likely to be referred late [10]. Although we did not categorize our patients according to their medical insurance coverages [11], there was no apparent statistical difference between the early- and later-referred groups of our cohort in terms of socioeconomic status. Similar to other studies, gender did not influence the differences between these two groups [10,11]. Interestingly, however, in the multivariate analysis, we demonstrated that married subjects had significantly higher odds of early referral to a nephrologist than single subjects. Whether a dyadic relationship (being married) might enhance a chronic kidney disease patient's attention to his or her physical health is a question that obviously deserves further attention [12]. Yet, the inclusion criteria of the present study raise the question of selection bias. For instance, those who were referred late to nephrologists and who opted for conservative management or other modality of renal replacement therapy were excluded from our study.

Most important of all, our study is the first to report a strong relationship between social factors and the risk of dialysis-related peritonitis. These findings have important clinical implications because of the hitherto lack of well-established strategies to prevent peritonitis [13]. Apart from confirming the putative role of educational background on the incidence of peritonitis (that two previous studies in the United States found [14,15]), our results substantiate the hypothesis that socioeconomic status is an important predictor of PD-related peritonitis. Our work was unique in that, unlike previous reports, it did not base the determination of socioeconomic status simply on zip code analyses [3,12]. The need to use more comprehensive measures in the study of social factors has been stressed [7]. In particular, we delineated the financial status of individuals by considering their need for social security assistance (a means-tested scheme to provide support for people in financial hardship, as defined by stipulated residency requirement and income) and controlling for household size and type, employment status, marital status, educational background, nutritional status and medical diagnosis.

The limitations of the present study include the inability to control for certain patient characteristics—including compliance, visual impairment or manual dexterity—that might influence the risk of peritonitis. Another drawback of our study is that instruments to quantify perceived social support, such as the Medical Outcomes Study Social Support Survey [16] derived for chronically ill subjects, were not incorporated into our assessment. Although we have not examined conditions that might explain the impact of social factors, such as health-related behaviour or symptoms of depression, our results suggest that such conditions warrant further attention, as they influence outcomes in PD patients. One plausible explanation for the association of social deprivation and risk of peritonitis is that we may in fact have indirectly measured the presence of depression in our cohort, or even its severity. It is noteworthy that depression (Beck Depression Inventory score ≥11) has been shown to predict the development of peritonitis in a cohort of 281 prevalent multi-ethnic PD subjects [17]; the magnitude of the odds associated with it (risk ratio, 2.7; 95% confidence interval, 1.2–6.0) was similar to that of receiving social security assistance in our study (risk ratio, 2.7; 95% confidence interval, 1.1–6.5). An important issue remains whether the association of socioeconomic disadvantage and peritonitis risk is mediated by behavioural factors (such as depression or dissatisfaction with one's health, or non-compliance with dialysis exchange procedures) or is influenced by the patients’ social setting. It should also be re-emphasized that nutritional parameters and medical conditions did not differ between the group that relies on social security assistance and the one that does not. This argues against any significant effects of physical fitness on peritonitis outcome.

Finally, because our study captured information on incident PD patients from a single centre, further work will be needed to determine if its results can be generalized to populations of other geographic regions or ethnicity. The overall similarity of the baseline demographic and socioeconomic parameters of our cohort to those reported by other dialysis units in our society [18,19] suggest that centre effect is not a major confounder in this case. Nonetheless, it is likely that there is residual confounding arising from limited characterization, in particular for the psychological status of our subjects. A relatively higher percentage of our study population was married, higher, than in other reported series [20]. Also, our results do not apply to patients undergoing automated PD, because of the limited number of such cases in our cohort. As with all epidemiologic analyses, external validity depends on the chosen cohort's profile. In particular, the majority of end-stage renal disease patients in Hong Kong commenced renal replacement therapy with PD [21]. Despite these limitations, this large sample provides a reliable estimate of the impact of social factors on peritoneal dialysis during a specific observation period.

In conclusion, we have found that the risk of peritonitis varied substantially with social background among new PD subjects. In particular, we showed that socioeconomic status was associated with an increased rate of peritonitis among PD subjects. This provides important information for policy makers, researchers and nephrologists. Given the limited resources for the care of the dialysis population, our efforts should be focused on the high-risk groups. Further work is warranted to determine if the implicated social factors affect the mortality of PD patients.



   Acknowledgments
 
We thank our team in the pre-dialysis clinic and dialysis unit, and our medical social workers, Ms So Hau Ping, Ms Cheng Yuet Hung and Ms Ho Yuk Han, for their contributions.

Conflict of interest statement. None declared.



   References
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 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 25. 2.05
Accepted in revised form: 15. 7.05





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