Association of Socioeconomic Status With Ischemic Stroke Survival

Rosa Maria Vivanco-Hidalgo, MD, PhD, MPH; Aida Ribera, PhD; Sònia Abilleira, MD, PhD

Disclosures

Stroke. 2019;50(12):3400-3407. 

In This Article

Results

From January 1, 2015, to December 31, 2016, 16 790 patients where admitted to public hospitals with the diagnosis of ischemic stroke. A total of 426 cases were excluded because of missing copayment data. We followed-up 16 344 patients for a median follow-up time of 18 months (interquartile range, 9.4–27.2), resulting in 24 638 person-years for the analyses. During hospitalization, 1826 cases died. Table 1 shows patients' characteristics at admission according to their individual socioeconomic status and by PCSA index quartiles. Patients in the lowest individual socioeconomic status category (exempts) were younger and had less comorbidities comparing to the other categories. Compared with patients in the least socioeconomically deprived PCSA (first quartile), patients in the most deprived PCSA (fourth quartile) were more likely to be younger, have more cardiovascular risk factors and comorbidities, and belong to the lowest individual socioeconomic category.

The crude 1-year case fatality rate for the whole cohort was 26% (95% CI, 25–27). Table 2 shows crude case fatality rates at 30 days and 1, 2, and 3 years according to individual socioeconomic status.

Figure 1 shows differences between individual socioeconomic status categories survival curves (adjusted by sex, age, and AMG). No differences were observed in survival curves when categorized for PCSA index quartiles (Figure 2).

Figure 1.

Kaplan-Meier curves of death after ischemic stroke by individual socioeconomic status categories (adjusted by age, sex, and Adjusted Morbidity Groups).

Figure 2.

Kaplan-Meier curves of death after ischemic stroke by primary care service area socioeconomic index quartiles (adjusted by age, sex, and Adjusted Morbidity Groups).

Table 3 and Table 4 show the adjusted odds ratios and hazard ratios for all-cause case fatality at 30 days and overall, respectively. In the short-term survival analysis, after adjusting for sex, age, and reperfusion therapies (model 1), we observed that patients with income <€18 000 had higher odds of death (odds ratio, 1.60; 95% CI, 1.19–1.55) than patients with income ≥€18 000. This association was attenuated after adjustment for comorbidities (model 2) and cardiovascular risk factors (model 3).We did not find a significant association between the lowest individual socioeconomic status (exempts) and survival. Conversely, we observed a PCSA index gradient effect, with those patients belonging to the most deprived areas presenting higher odds of death than the least socioeconomically deprived areas (odds ratio, 1.19; 95% CI, 1.03–1.37).

In the long-term survival analysis, after adjusting for sex, age, and reperfusion therapies (model 1), we observed a gradient in mortality risk with decreasing socioeconomic status, with the poorest patients having a 68% higher risk of death (hazard ratio, 1.68; 95% CI, 1.44–1.96). This gradient was mildly attenuated after adjustment for comorbidities (model 2) and cardiovascular risk factors (model 3). The addition of PCSA index, in this case, did not meaningfully change the magnitude of the association. The adjusted effect of the lowest individual socioeconomic status versus the highest was 1.52 (95% CI, 1.30–1.77).

We performed a sensitivity analysis (online-only Data Supplement) to overcome possible data limitations of variables that could eventually influence stroke survival (like stroke severity). We excluded those cases that died during hospitalization (assuming that more severe cases would die in the hospital). Results were similar to those showed in Table 4.

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