The relationship between socioeconomic status and trauma outcomes

The relationship between socioeconomic status and trauma outcomes Abstract Background The burden of trauma is not equally distributed among all groups of societies and often disproportionately affects poor populations. This study aimed to examine the relationship of socioeconomic status (SES) and trauma outcomes. Methods In this cohort study, 600 trauma patients in Kashan, Iran were studied. Data were gathered by demographic and trauma-related questionnaires, a socioeconomic assessment scale, the Hospital Care Index and the World Health Organization Disability Assessment Schedule-II. The concentration index was done for measuring socioeconomic inequalities. Results About 49.7% of the patients received high level of hospital care. After 3 months from trauma incidence, 64.2% of the patients reported some levels of disability and 71.4% returned to their work or activities of daily living. Most cases of high level of hospital care and return to work (RTW) were among patients with high SES while most instances of death and disability occurred among patients with low SES. Inequality analysis also revealed that patients with low and high SES differed significantly from each other in terms of hospital care and RTW. Conclusion Patients with low SES are at greater risk for receiving low level of hospital care and experiencing non-RTW and needs to stronger post-discharge social supports. disabilities, mortality, socioeconomics factors Introduction Trauma is among the major causes of morbidity and mortality throughout the world. It affects people in all countries, irrespective of their income levels and geographic locations. It is estimated that 16 000 trauma-induced deaths happen per day.1 About 90% of the burden of trauma pertains to low- and middle-income countries.2 In these countries, trauma is the commonest cause of death among people who are in age 15–59.3 Besides, as a major cause of morbidity, disability, and early mortality, trauma imposes an enormous burden on public health in terms of both disability-adjusted life years and social costs.4 The burden of trauma is not equally distributed among all groups of societies and it often disproportionately affects young and poor populations,5 resulting in socioeconomic inequalities in health. A socioeconomic inequality in health is defined as differences in the incidence or the prevalence of health problems among people with either lower or higher socioeconomic status (SES).2 Health inequalities of different types (including economic, gender-related and racial) exist all over the world both among and within communities6 so that it has recently received a considerable global attention.7 Understanding the extent and the characteristics of inequalities is a vital prerequisite to effective planning for change. In other words, health authorities need to know the extent to which their policies have caused or will cause inequalities in order to develop plans for revising policies and minimizing inequalities.8 One of the goals of healthy community programs is to eradicate health inequalities among people with different genders, ethnicities, races, educational status, levels of income and geographical locations.9 Nonetheless, despite the commitment of governments and health systems to promote health indices, there are still wide disparities among different social groups in terms of their health status. Such disparities may finally result in health injustice. Fortunately, health disparities can be prevented and managed through taking appropriate measures, thus different countries have devised strategies to manage them.10 For instance, in our country, Iran, equity in health is among the major aims of the Iranian healthcare delivery system.11 Trauma, due to its emergency nature, as well as apparently identical access to care services, seems to be protected from inequality.12 However, studies showed gender differences in terms of trauma incidence13–16 as well as socioeconomic differences regarding trauma incidence,14,15,17–19 trauma type19 trauma-induced death,12,15,20 trauma care,21,22 post-trauma disability,23–26 post-trauma RTW.27–30 Such differences are usually against people with low SES. Moreover, some studies revealed that there are inequalities among people with different insurance status in terms of mortality rate12,31,32 and access to diagnostic, therapeutic and rehabilitation services.31,33,34 The relationship between inequality and trauma outcomes is important to all countries. Understanding the determinants of inequalities can pave the way for fair care delivery to all people irrespective of their SES. Our literature review revealed that no study has been conducted so far in Iran with regard to inequalities in trauma care. The present study was made to examine the relationship of SES with trauma outcomes. Methods This cohort study was undertaken from March 2014 to March 2015 on 600 trauma patients hospitalized in Shahid Beheshti hospital, Kashan, Iran. Kashan is located in central part of Iran with more than 400 000 populations and Shahid Beheshti hospital is the main trauma center in Kashan with annually admission rate of 7000 trauma patients. The total number of adult trauma patients who are hospitalized more than 24 h is ~4000 per year. We invited 1000 patients who had inclusion criteria but 600 patients agreed to participate in study and follow-up assessment. The patients were assessed prospectively. They were included if they had any intentional or unintentional injury, lived in Kashan county, aged 15–64, agreed to participate in the study, had no mental problem or disability before experiencing trauma (according to the patients or their family statement of any mental retardation, mental illness, physical disabilities such as skeletal abnormalities or defects), and were hospitalized for at least 24 h before being recruited to the study. Patients who were not accessible during the 3-month follow-up period of the study or their medical records were incomplete were excluded. I. Instruments The data collection instruments were a questionnaire on the patients’ demographic characteristics, trauma-related characteristics, and trauma outcomes, Injury sevirity score (ISS), a socioeconomic assessment check list, the Hospital Care Index (HCI), and World Health Organization Disability Assessment Schedule-II (WHODAS-II). The items of the demographic and trauma-related questionnaire were age, gender, marital and educational status, nationality, place of residence, employment status, cigarette smoking, alcohol and drug abuse, patient transfer vehicle, severity of injury, mechanism of injury, injured organ(s) and type of injury. Trauma outcomes were hospital care level, in-hospital death, disability and RTW. The SES was assessed based on Asset Index that represents a durable economic status than does either income or expenditure. It determined through performing Principal Component Analysis as proposed by O’Donnell et al. and Vyas et al.35,36 Accordingly, the new variable of Asset Index was generated by using 10 variables related to household asset (including ownership of home, dishwasher, LCD TV, refrigerator, microwave oven, car, personal computer, laptop, Internet access and household surface area) and two social factors (including employment and educational status of the head of family). Then, based on the median score and the percentiles of the Asset Index, the participants were divided into three groups of low, middle and high SES. The level of hospital care provided to the patients was also assessed through calculating HCI by performing principal component analysis. Accordingly, variables such as the number of medical visits, the number of medical consultations, the amount of time waiting for being admitted to a hospital ward and intensive care unit (ICU), the length of stay in the emergency department and ICU, and hospitalization-related costs were entered into the analysis. All these variables had been adjusted based on trauma severity and duration of hospitalization. Then, variables with an Eigen value of >1 were identified. These variables included the total of hospitalization costs, the number of medical visits and consultations, the duration of stay in the emergency department, and the time period between physicians’ order for patient transfer to actual patient transfer (from the emergency room to a hospital ward). Finally, based on the median of the first component, the patients were divided into the two groups of high and low hospital care level. Mortality data included hospital death after 24 h. Therefore, deaths at the time of arrival and first day were not recorded. The levels of disability at 1 and 3 months after trauma were assessed by using the 12-item WHODAS-II. This scale contains six subscales which come into the two main domains of ‘activity limitation’ and ‘participation’. The 12 items of the scale are scored on a Likert-type scale from 1 (No problem) to 5 (Extremely disabled). Therefore, the possible range of the total WHODAS-II score is 12–60 which is converted to a 0–100 scale; the higher the score, the more severe the disability.37 The validity and the reliability of the Persian version of the WHODAS-II have been confirmed in Iran.38 Finally, RTW was measured by using the following two questions: Have you returned to your work or daily activities? How long did it take for you to return to your work or daily activities? The questionnaires were filled out through interviewing the patients. The data of patients with altered consciousness were collected by interviewing one of their family members. Besides, the patients or family members were re-interviewed 1 and 3 months after hospital discharge in order to collect disability- and RTW-related data. II. Ethical considerations Before recruiting them to the study, the patients or the family members were informed about the aims of the study and were ensured that their data (particularly the data on their SES) would remain confidential. Then, their verbal informed consent was obtained. Besides, this study was approved by the Ethics Committee of Kashan University of Medical Sciences, Kashan, Iran. III. Data analysis The SPSS (v. 16.0) and the STATA (v. 12.1) software were used for data analysis. The Kolmogorov–Smirnov test was used for assessing data normality. Participants with different SES were compared with each other in terms of trauma outcomes through running the Chi-square test. On the other hand, inequality assessment was performed through employing the concentration index technique. Accordingly, a dichotomous variable was generated for each of the variables that were significantly correlated with SES. Then, the concentration curve of each of the generated dichotomous variables was plotted against the distribution of the asset index. The concentration curve plots the cumulative percentage of the variable of health (Y axis) against the cumulative percentage of population, ranked based on economic status from poorest to richest (X axis). If all people, irrespective of their economic status, have exactly the same level of health, the concentration curve will be a 45° line which is called ‘the line of equality’. On the other hand, if the health variable has greater concentration among poor people, the concentration curve falls above the line of equality, denoting inequality; the greater the distance between the curve and the line, the greater the inequality.35 Concentration index is the surface area between the curve and the equality line multiplied by 2. Consequently, when the concentration curve lies exactly on the line of equality the concentration index is equal to zero; when it falls above or below the line of equality, the concentration index takes negative or positive values, respectively. The concentration index value can range between −1 and +1.39 Results The results of the Kolmogorov–Smirnov test illustrated that the distribution of the study variables was not normal. In total, 600 patients were approached from which, 11 patients did not respond to our follow-up phone contacts and thus, were excluded (a follow-up rate = 98.2%). In addition, 19 patients died during the study and hence, when we assessed the trauma outcomes of disability and RTW, the sample size was 570. The SES of the patients was as follows: low: 36.3%; middle: 30.5%; and high: 33.2%. The findings indicated that 59.3% of the participants aged <35, 85.8% were males, and 89.7% were urban dwellers. Besides, 88.8% of them were Iranian, 62.5% were married, 79.3% had below-diploma education, 66.3% were employed and 71.7% maintained insurance. In addition, 19% of the participants were cigarette smokers, 5.8% were drug abusers, and 1.8% reported with alcohol intake. The main mechanism of trauma was traffic accidents (64.5%) and most patients (74.2%) had been transferred to the hospital by Emergency Medical Service (EMS). Moreover, 59.8% of the traumas were single organ injury and the commonest injured organs were the extremities and the pelvis (76.5%). The mean (SD) and the median of the ISS were 10.2(7.2) and 9, respectively. The death rate among the participants was 3.2% and 49.7% of the participants received high level of hospital care. Three months after the incidence of trauma, 64.2% of the patients reported some levels of disability and 71.4% returned to their work or activities of daily living. As shown in Table 1, most cases of high-level hospital care and RTW were from patients with high SES while most cases of trauma-induced disability and death happened among patients with low SES. The results of the Chi-square test revealed that people with different SES significantly differed from each other concerning hospital care level, death and RTW. The risk ratio of trauma outcomes in different SES has been shown in Table 2. Table 1 The outcomes of trauma among patients with different SES SES outcome High Middle Low Total P valuea Hospital care level Low 85 (46.5) 125 (57.3) 302 (50.3) 92 (46.2) 0.03 High 98 (53.5) 93 (42.7) 298 (49.7) 107 (53.8) Death No 179 (97.8) 206 (94.5) 581 (96.8) 196 (98.5) 0.04 Yes 4 (2.2) 12 (5.5) 19 (3.2) 3 (1.5) Disability No 68 (38.6) 63 (31.3) 204 (35.8) 73 (37.8) 0.26 Yes 108 (61.4) 138 (68.7) 366 (64.2) 120 (62.2) RTW No 45 (25.6) 76 (37.8) 163 (28.6) 42 (21.8) 0.001 Yes 131 (74.4) 125 (62.2) 407 (71.4) 151 (78.2) SES outcome High Middle Low Total P valuea Hospital care level Low 85 (46.5) 125 (57.3) 302 (50.3) 92 (46.2) 0.03 High 98 (53.5) 93 (42.7) 298 (49.7) 107 (53.8) Death No 179 (97.8) 206 (94.5) 581 (96.8) 196 (98.5) 0.04 Yes 4 (2.2) 12 (5.5) 19 (3.2) 3 (1.5) Disability No 68 (38.6) 63 (31.3) 204 (35.8) 73 (37.8) 0.26 Yes 108 (61.4) 138 (68.7) 366 (64.2) 120 (62.2) RTW No 45 (25.6) 76 (37.8) 163 (28.6) 42 (21.8) 0.001 Yes 131 (74.4) 125 (62.2) 407 (71.4) 151 (78.2) aChi-square test. Table 1 The outcomes of trauma among patients with different SES SES outcome High Middle Low Total P valuea Hospital care level Low 85 (46.5) 125 (57.3) 302 (50.3) 92 (46.2) 0.03 High 98 (53.5) 93 (42.7) 298 (49.7) 107 (53.8) Death No 179 (97.8) 206 (94.5) 581 (96.8) 196 (98.5) 0.04 Yes 4 (2.2) 12 (5.5) 19 (3.2) 3 (1.5) Disability No 68 (38.6) 63 (31.3) 204 (35.8) 73 (37.8) 0.26 Yes 108 (61.4) 138 (68.7) 366 (64.2) 120 (62.2) RTW No 45 (25.6) 76 (37.8) 163 (28.6) 42 (21.8) 0.001 Yes 131 (74.4) 125 (62.2) 407 (71.4) 151 (78.2) SES outcome High Middle Low Total P valuea Hospital care level Low 85 (46.5) 125 (57.3) 302 (50.3) 92 (46.2) 0.03 High 98 (53.5) 93 (42.7) 298 (49.7) 107 (53.8) Death No 179 (97.8) 206 (94.5) 581 (96.8) 196 (98.5) 0.04 Yes 4 (2.2) 12 (5.5) 19 (3.2) 3 (1.5) Disability No 68 (38.6) 63 (31.3) 204 (35.8) 73 (37.8) 0.26 Yes 108 (61.4) 138 (68.7) 366 (64.2) 120 (62.2) RTW No 45 (25.6) 76 (37.8) 163 (28.6) 42 (21.8) 0.001 Yes 131 (74.4) 125 (62.2) 407 (71.4) 151 (78.2) aChi-square test. The results of inequality analysis showed that there were socioeconomic inequalities between patients with high and low SES in terms of hospital care and RTW. Moreover, the amount of inequality between these groups regarding the outcome of death was –0.190. Although the confidence interval of the concentration index indicates that this difference is not statistically significant, Figs. 1 and 2 show that inequality values for the two outcomes of hospital care and RTW are against people with low SES. In these two figures, the concentration curve is above the line of equality, i.e. in the area of negative values (Table 3). Table 2 The risk of trauma outcomes based on SES level SES Risk ratio CI 95% P value Low Hospital Care level High 1 Middle 0.89 0.74–1.06 0.2 Low 1.81 1.05–1.44 0.01 Death High 1 Middle 0.6 0.20–1.80 0.36 Low 3.12 1.20–7.51 0.01 Disability High 1 Middle 0.93 0.81–1.07 0.34 Low 1.11 0.98–1.25 0.1 Non-RTW High 1 Middle 0.71 0.50–1.01 0.05 Low 1.66 1.25–2.21 <0.001 SES Risk ratio CI 95% P value Low Hospital Care level High 1 Middle 0.89 0.74–1.06 0.2 Low 1.81 1.05–1.44 0.01 Death High 1 Middle 0.6 0.20–1.80 0.36 Low 3.12 1.20–7.51 0.01 Disability High 1 Middle 0.93 0.81–1.07 0.34 Low 1.11 0.98–1.25 0.1 Non-RTW High 1 Middle 0.71 0.50–1.01 0.05 Low 1.66 1.25–2.21 <0.001 Table 2 The risk of trauma outcomes based on SES level SES Risk ratio CI 95% P value Low Hospital Care level High 1 Middle 0.89 0.74–1.06 0.2 Low 1.81 1.05–1.44 0.01 Death High 1 Middle 0.6 0.20–1.80 0.36 Low 3.12 1.20–7.51 0.01 Disability High 1 Middle 0.93 0.81–1.07 0.34 Low 1.11 0.98–1.25 0.1 Non-RTW High 1 Middle 0.71 0.50–1.01 0.05 Low 1.66 1.25–2.21 <0.001 SES Risk ratio CI 95% P value Low Hospital Care level High 1 Middle 0.89 0.74–1.06 0.2 Low 1.81 1.05–1.44 0.01 Death High 1 Middle 0.6 0.20–1.80 0.36 Low 3.12 1.20–7.51 0.01 Disability High 1 Middle 0.93 0.81–1.07 0.34 Low 1.11 0.98–1.25 0.1 Non-RTW High 1 Middle 0.71 0.50–1.01 0.05 Low 1.66 1.25–2.21 <0.001 Table 3 Concentration index analysis Outcome Prevalence (%) Concentration index Standard error 95% Confidence interval Death 3.2 −0.190 0.119 0.042, −0.423 Low-level hospital care 50.3 −0.046 0.017 −0.012, −0.081 Non-RTW 32.8 −0.118 0.043 −0.202, −0.033 Outcome Prevalence (%) Concentration index Standard error 95% Confidence interval Death 3.2 −0.190 0.119 0.042, −0.423 Low-level hospital care 50.3 −0.046 0.017 −0.012, −0.081 Non-RTW 32.8 −0.118 0.043 −0.202, −0.033 Table 3 Concentration index analysis Outcome Prevalence (%) Concentration index Standard error 95% Confidence interval Death 3.2 −0.190 0.119 0.042, −0.423 Low-level hospital care 50.3 −0.046 0.017 −0.012, −0.081 Non-RTW 32.8 −0.118 0.043 −0.202, −0.033 Outcome Prevalence (%) Concentration index Standard error 95% Confidence interval Death 3.2 −0.190 0.119 0.042, −0.423 Low-level hospital care 50.3 −0.046 0.017 −0.012, −0.081 Non-RTW 32.8 −0.118 0.043 −0.202, −0.033 Fig. 1 View largeDownload slide Concentration index for Hospital Care. Fig. 1 View largeDownload slide Concentration index for Hospital Care. Fig. 2 View largeDownload slide Concentration index for death. Fig. 2 View largeDownload slide Concentration index for death. Discussion Main finding of this study The findings of the present study showed that most patients with low SES received low level of hospital care, also most cases of trauma-induced deaths happened among patients with low SES. Death rate among these patients was 3.6 times more than patients with high SES. Our findings also indicated that 3 months after trauma, disability rate was not statistically significant between low and high SES patients, but RTW rate in low SES group was significantly lower than high SES group. The concentration index analysis revealed slight inequality among patients with different SES regarding the outcomes of level of hospital care and RTW. Inequality in death outcome was not seen between different SES. What is already known on this topic To the best of our knowledge, this is the first study of its kind to assess SES among trauma patients. Numerous studies have been conducted in the world in order to assess inequalities in hospital care, trauma-related mortality and access to rehabilitation services among people with different genders, ethnicities, races or insurance status. Several population-based studies in Iran also showed the significant correlation of SES with the incidence and the mortality rate of trauma. Nonetheless, no study had yet assessed socioeconomic inequalities and its relationship with in-hospital death, hospital care, disability and RTW. What this study adds The difference in level of hospital care between low and high SES was significant and in favor of high SES patients (53.8 versus 42.7%). It is noteworthy that none of the previous studies has assessed hospital care so far, even though some of them evaluated care-related indicators such as the length of hospital stay, the availability of diagnostic or therapeutic care services, or the waiting time for undergoing surgeries. Some studies reported that SES has no significant effect on the waiting time for undergoing surgeries.40,41 However, the results of two studies illustrated inequalities in the waiting time for surgeries among patients with hip fracture.21,42 Colais et al.22 also found that people with low SES are more likely not to receive diagnostic and therapeutic interventions. In our study, patients with low SES also had significantly longer hospital stay than patients with high SES (6.9 ± 7.9 versus 5.4 ± 5.7 days). This difference may be due to insurance coverage during hospitalization especially for traffic-related injuries and implementation of health system reform plan in Iran, in which out of pocket payments for medical care are reduced. Therefore patients prefer stay at hospital to full recovery. One study demonstrated that people with high SES had longer hospital stay.43 On the contrary, another study in Canada revealed that people with low SES had longer stay in hospital due to lack of equipment and facilities for long-term care and lack of sources for covering post-discharge care-related costs.44 The results of a study in Sudan also illustrated longer hospital stay among patients with low SES.45 The findings of the present study also revealed a mortality rate of 3.2% among trauma patients. Previous studies have reported different in-hospital trauma-related mortality rate. For instance, Paravar et al.46 reported an in-hospital mortality rate of 6.1% in Kashan city. This value is higher than the rate found in our study probably due to the fact that they made their study on patients of all age groups who had been transferred to hospital by EMS. The severity of trauma among patients who are transferred by EMS is usually greater than other patients. Besides, our participants were trauma patients who stayed in hospital for more than 24 h while they studied the patients who had experienced death both during and after the first 24 h of their hospitalization. The results of another study in Philippine also revealed an in-hospital mortality rate of 4.7%.47 The higher mortality rate in this study compared with our study can also be attributed to the differences in the eligibility criteria in these two studies. In-hospital mortality rate in a study conducted in Shiraz, Iran, was as high as 11.2% which is much higher than the rate in our study due to the fact that the participants in that study were 18–80-year-old patients who suffered from multiple traumas and had an ISS of >9.48 However, a study in Tehran, Iran, showed an in-hospital mortality rate of 3. Like our study, the commonest mechanism of trauma and the commonest cause of death in that study were road traffic accidents and head injuries, respectively.49 Study findings also showed that death rate among patients with low SES was 3.6 times more than patients with high SES. Mays et al.20 reported SES as an independent predictor of post-trauma mortality. The results of two studies conducted in Italy on patients with hip fracture also illustrated a significant relationship between low SES and 30-day mortality.21,22 Results of a study in Canada showed that the chance of trauma-related mortality is higher among people with low SES, while people with high SES have longer hospital stay and are more likely to be transferred to other clinical settings.43 In our study, 64.2% of patients reported some levels of disability 3 months after hospital discharge. Previous studies reported disability rates of 20–80% among trauma patients.50–53 Such a wide range of disability rate can be attributed to the differences in the disability assessment instruments, the time of disability assessment, and the samples in these studies. For instance, Evans et al.51 reported that 1 year after experiencing major traumas; disability rate was 80% while we assessed patients with different types of traumas in a follow-up period of 3 months. In present study difference in disability between low and high SES was not statistically significant. Some previous studies demonstrated a significant relationship between disability and SES. Most of these studies were conducted at community level and on traffic accident traumas which are usually more severe than other types of trauma, are more prevalent among people with low SES, and are associated with higher disability rates.23,24,26 Safa et al.25 also reported a significant negative correlation between SES and dependency in daily living activities i.e. the lower the SES, the higher the dependency. The difference between our findings and findings reported by Safa et al. is probably due to the differences in the study population in these two studies in that while their participants were elderly people who are usually unemployed and financially and physically dependent, our participants were 15–64-year-old patients who are usually employed and have income. Besides, SES assessment instruments in these two studies were different. The results of a study showed that after eliminating the effects of confounders, disability was not significantly correlated with SES.45 In Iran, the Traffic Accident Victims Law has been implemented since 2008 by which, all hospitalization costs of these patients are paid by insurance companies. Moreover, according to the Iranian Health System Reform Plan, the hospitalization-related costs of other trauma victims have been reduced since 2014. In addition, most of our participants had insurance and were probably able to pay for their rehabilitation treatments costs. Our findings also revealed that 407 patients (71.4%) returned to their work or activities of daily living after 3 months. In other words, 28.6% of them had no RTW due to medical order for avoiding activities (24.4%), loss of employment (12.2%), incomplete recovery (59.3%) or other reasons (4%). Loss of employment is of paramount importance to trauma patients. In our study, from among 15 patients who lost their employment, 11 ones (73.3%) had low SES and two ones had high SES. These findings denote that patients with low SES are more at risk for post-trauma employment-related damages and thus, they need stronger social support. The results of a study made by El Tayeb et al.45 illustrated that the rate of employment loss was 9.3%, and in line with our findings, they showed a greater risk for post-trauma employment loss among people with low SES. Previous studies reported that the prevalence rate of return to work/education/activities of daily living is 15–80%.27,29,53–58 RTW rate in our study was different from other studies. An explanation for this difference in RTW rate in these studies is that some of them focused on certain traumas such as trauma to the extremities54 and others dealt with multiple traumas57 or major traumas.53,56 While, we assessed return to work/education/activities of daily living among patients with different types of trauma and thus, found a high RTW rate compared with most previous studies. Another explanation is the difference in the time of measuring post-trauma RTW.28,54,56,59,60 RTW rate among patients with low SES was significantly lower than patients with high SES (62.2 versus 78.2%). Some previous studies also reported SES as a predictor of RTW.27–30 Also in recent study by Abedzadeh et al. (2017) RTW time was significantly longer in low SES patients.61 People with higher SES are more likely to return to their work after trauma because they have higher income, greater job stability, better insurance status, and stronger social support. On the other hand, people with lower SES are more likely to lose their employment after trauma because they mostly do manual labors (such as farming) which need superior physical health status. Our findings revealed that even among patients with similar levels of disability, RTW rate was still higher among patients with high SES. In cases with moderate disability, RTW rate in low and high SES was respectively 13.6 and 17.6%; and in cases with mild disability this rate was 55.4 and 78.6%, respectively. The results of concentration index analysis revealed slight inequality among patients with different SES regarding the outcome of high-level hospital care (concentration index = –0.046 and SE = 0.017). As shown in Fig. 1, this slight inequality was against patients with low SES. Moreover, the findings revealed that although patients with low SES were more at risk for experiencing death, inequality analysis revealed no significant difference between patients with low and high SES. This finding denotes that at hospital level, other factors (such as the type of injured organ, the level of hospital care and the severity of trauma) may be the predictors of death. Concentration index analysis on the outcome of RTW also indicated an inequality value of –0.118 (SE = 0.043) which was against patients with low SES. Figure 3 also depicts that the concentration curve is above the line of equality, i.e. in the area of negative values. Fig. 3 View largeDownload slide Concentration Index for RTW. Fig. 3 View largeDownload slide Concentration Index for RTW. The outcomes which were assessed in the present study had not been subjected to inequality analysis in previous studies. Moreover, studies in this area are usually population-based and hence, their findings cannot be compared with our findings. For instance, Safari-Faramani et al. (2013) made a study in Tehran, Iran, in order to assess socioeconomic inequality in unintentional injuries among children and found that concentration index for all injuries was 0.40 while the index for traumas caused by traffic accidents, falls, burns and poisoning was equal to –0.41, –0.37, –0.62 and –0.35, respectively. Consequently, they concluded that there are substantial differences among different SES groups regarding unintentional injuries among children.18 Inequalities in patient outcomes may be due to different factors included differences in the approaches to care delivery. For instance, the results of a study revealed disparities in acute post-trauma care services.12 Care-related inequalities have been also reported to exist in the United States, England, Canada and many other western countries.22 Although healthcare workers aim at providing equal care services to all patients, heuristic and bias are usually inevitable, particularly in critical care units.20 Limitation and strength of this study One of the study limitations was that the data on the patients’ income and disability status were collected through self-reporting which is usually associated with measurement biases. Another limitation was the coincidence of the present study with the implementation of the Iranian Health System Reform Plan. The Plan significantly reduced patients’ healthcare costs and thus, it might have affected the findings of our study. In addition, we had no information about patients’ status before the implementation of this Plan and hence, before-after comparison was not feasible. Last but not the least; the follow-up period of the study was relatively short. On the other hand, one of the study strengths was its small attrition rate (a follow-up rate of 98.2%). In addition, this study was the first of its kind to assess SES at hospital level and the first cohort study to evaluate the outcomes of disability and RTW among trauma patients by using a valid and reliable instrument. Assessing HCI was other strength of the present study. Conclusion Some trauma outcomes are associated with socioeconomic inequalities. In other words, patients with low SES are more at risk for receiving low-level of hospital care and experiencing non-RTW. Consequently, greater attention and stronger social support needs to be paid to economically vulnerable patients who experience trauma. The findings revealed that SES affects trauma outcomes such as death. Therefore, providing better hospital care to patients with lower SES can play a significant role in reducing death rate among them. Moreover, these patients need to be provided with more efficient follow-up services because they usually have inadequate insurance and limited access to costly post-discharge rehabilitation services and thus, are at greater risk for delayed recovery, disabilities, non-RTW and employment loss. Future studies are recommended to examine the relationship of SES with trauma outcomes at national level, in both public and private hospitals, in larger and more homogenous populations (in terms of the type and the severity of trauma), and with longer follow-up periods. Acknowledgements We express our thanks to Deputy of Research of Kashan University of Medical Sciences for its financial support in this study and also staff of Trauma Research Center and Shahid Beheshti Hospital for their co operation. Funding This study was supported by deputy of research, Kashan University of Medical Sciences (Grant no. 9303). References 1 Krug EG , Sharma GK , Lozano R . The global burden of injuries . Am J Public Health 2000 ; 90 ( 4 ): 523 – 6 . Google Scholar CrossRef Search ADS PubMed 2 Hofman K , Primack A , Keusch G et al. . Addressing the growing burden of trauma and injury in low- and middle-income countries . Am J Public Health 2005 ; 95 ( 1 ): 13 – 7 . Google Scholar CrossRef Search ADS PubMed 3 World Health Organization .The Global burden of disease: 2004 Update. Geneva, 2008 4 Bonnie RJ , Fulco C , Liverman C . Reducing the Burden of Injury: Advancing Prevention and Treatment . Washington, DC : Natl. Acad. Press , 1999 . 5 Haddon W . 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The socioeconomic inequality in traffic-related disability among Chinese adults: the application of concentration index . Accid Anal Prev 2013 ; 55 ( 0 ): 101 – 6 . Google Scholar CrossRef Search ADS PubMed 24 Hyder AA , Peden M . Inequality and road-traffic injuries: call for action . Lancet 2003 ; 362 ( 9401 ): 2034 – 5 . Google Scholar CrossRef Search ADS PubMed 25 Safa A , Masoudi Alavi N , Abedzadeh-Kalahroudi M . Predictive factors of dependency in activities of daily living following limb trauma in elderly referred to Shahid Beheshti Hospital, Kashan, Iran, in 2013 . Trauma Mon 2016 ; 21 ( 5 ): e25091 . Google Scholar CrossRef Search ADS PubMed 26 Sethi D , Racioppi F , Baumgarten I et al. . Reducing inequalities from injuries in Europe . Lancet 2006 ; 368 ( 9554 ): 2243 – 50 . Google Scholar CrossRef Search ADS PubMed 27 Hou WH , Tsauo JY , Lin CH et al. . Worker’s compensation and return-to-work following orthopaedic injury to extremities . 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Google Scholar CrossRef Search ADS PubMed 32 Haider AH , Chang DC , Efron DT et al. . Race and insurance status as risk factors for trauma mortality . Arch Surg 2008 ; 143 ( 10 ): 945 – 9 . Google Scholar CrossRef Search ADS PubMed 33 Haas JS , Goldman L . Acutely injured patients with trauma in Massachusetts: differences in care and mortality, by insurance status . Am J Public Health 1994 ; 84 ( 10 ): 1605 – 8 . Google Scholar CrossRef Search ADS PubMed 34 White FA , French D , Zwemer FL et al. . Care without coverage: is there a relationship between insurance and ED care? J Emerg Med 2007 ; 32 ( 2 ): 159 – 65 . Google Scholar CrossRef Search ADS PubMed 35 O’Donnell O , Van Doorslaer E , Wagstaff A et al. . Analyzing health equity using household survey data: a guide to techniques and their implementation. In: Publications . Washington, DC : World Bank , 2008 . 36 Vyas S , Kumaranayake L . Constructing socio-economic status indices: how to use principal components analysis . Health Policy Plan 2006 ; 21 ( 6 ): 459 – 68 . Google Scholar CrossRef Search ADS PubMed 37 WHO Disability Assessment Schedule 2.0 (WHODAS2.0) [07/01/2014]. http://www.who.int/classifications/icf/whodasii/en/index4.html. 38 Abedzadeh-kalahroudi M , Razi E , Sehat M et al. . Psychometric properties of the world health organization disability assessment schedule II-12 Item (WHODAS II) in trauma patients . Injury 2016 ; 47 ( 5 ): 1104 – 8 . Google Scholar CrossRef Search ADS PubMed 39 Wagstaff A , Paci P , van Doorslaer E . On the measurement of inequalities in health . Soc Sci Med 1991 ; 33 ( 5 ): 545 – 57 . Google Scholar CrossRef Search ADS PubMed 40 Hamilton BH , Hamilton VH , Mayo NE . What are the costs of queuing for hip fracture surgery in Canada? J Health Econ 1996 ; 15 ( 2 ): 161 – 85 . Google Scholar CrossRef Search ADS PubMed 41 Shortt SE , Shaw RA . Equity in Canadian health care: does socioeconomic status affect waiting times for elective surgery? CMAJ 2003 ; 168 ( 4 ): 413 – 6 . Google Scholar PubMed 42 Bottle A , Aylin P . Mortality associated with delay in operation after hip fracture: observational study . BMJ (Clin Res Ed) 2006 ; 332 ( 7547 ): 947 – 51 . Google Scholar CrossRef Search ADS 43 Socio-Economic Status and Injury [cited 5/16/2016]. https://www.monash.edu/__data/assets/pdf_file/0003/218487/haz49.pdf. 44 Moore L , Cisse B , Batomen Kuimi BL et al. . Impact of socio-economic status on hospital length of stay following injury: a multicenter cohort study . BMC Health Serv Res 2015 ; 15 : 285 . Google Scholar CrossRef Search ADS PubMed 45 El Tayeb S , Abdalla S , Heuch I et al. . Socioeconomic and disability consequences of injuries in the Sudan: a community-based survey in Khartoum State . Injury Prev 2013 ; 21 : e56 – 62 . Google Scholar CrossRef Search ADS 46 Paravar M , Hosseinpour M , Mohammadzadeh M et al. . Prehospital care and in-hospital mortality of trauma patients in Iran . Prehosp Disaster Med 2014 ; 29 ( 5 ): 473 – 7 . Google Scholar CrossRef Search ADS PubMed 47 Consunji RJ , Serrato Marinas JP , Aspuria Maddumba JR et al. . A profile of deaths among trauma patients in a university hospital: the Philippine experience . J Inj Violence Res 2011 ; 3 ( 2 ): 85 – 9 . Google Scholar CrossRef Search ADS PubMed 48 Jelodar S , Jafari P , Yadollahi M et al. . Potential risk factors of death in multiple trauma patients . Emerg (Tehran) 2014 ; 2 ( 4 ): 170 – 3 . Google Scholar PubMed 49 Salimi J Nasaji Zavareh M Khaji A 2007 Trauma mortality in six university hospitals: Tehran, Iran Tehran Univ Med J 65 Suppl. 2 22 5 50 Baldry Currens JA , Coats TJ . The timing of disability measurements following injury . Injury 2000 ; 31 ( 2 ): 93 – 8 . Google Scholar CrossRef Search ADS PubMed 51 Evans SA , Airey MC , Chell SM et al. . Disability in young adults following major trauma: 5 year follow up of survivors . BMC Public Health 2003 Jan 27; 3 : 8 . 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Work status and disability trajectories over 12 months after injury among workers in New Zealand . N Z Med J 2014 ; 127 ( 1390 ): 53 – 60 . Google Scholar PubMed 61 Abedzadeh-Kalahroudi M , Razi E , Sehat M et al. . Return to work after trauma: a survival analysis . Chin J Traumatol 2017 ; 20 ( 2 ): 67 – 74 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Public Health Oxford University Press

The relationship between socioeconomic status and trauma outcomes

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Abstract

Abstract Background The burden of trauma is not equally distributed among all groups of societies and often disproportionately affects poor populations. This study aimed to examine the relationship of socioeconomic status (SES) and trauma outcomes. Methods In this cohort study, 600 trauma patients in Kashan, Iran were studied. Data were gathered by demographic and trauma-related questionnaires, a socioeconomic assessment scale, the Hospital Care Index and the World Health Organization Disability Assessment Schedule-II. The concentration index was done for measuring socioeconomic inequalities. Results About 49.7% of the patients received high level of hospital care. After 3 months from trauma incidence, 64.2% of the patients reported some levels of disability and 71.4% returned to their work or activities of daily living. Most cases of high level of hospital care and return to work (RTW) were among patients with high SES while most instances of death and disability occurred among patients with low SES. Inequality analysis also revealed that patients with low and high SES differed significantly from each other in terms of hospital care and RTW. Conclusion Patients with low SES are at greater risk for receiving low level of hospital care and experiencing non-RTW and needs to stronger post-discharge social supports. disabilities, mortality, socioeconomics factors Introduction Trauma is among the major causes of morbidity and mortality throughout the world. It affects people in all countries, irrespective of their income levels and geographic locations. It is estimated that 16 000 trauma-induced deaths happen per day.1 About 90% of the burden of trauma pertains to low- and middle-income countries.2 In these countries, trauma is the commonest cause of death among people who are in age 15–59.3 Besides, as a major cause of morbidity, disability, and early mortality, trauma imposes an enormous burden on public health in terms of both disability-adjusted life years and social costs.4 The burden of trauma is not equally distributed among all groups of societies and it often disproportionately affects young and poor populations,5 resulting in socioeconomic inequalities in health. A socioeconomic inequality in health is defined as differences in the incidence or the prevalence of health problems among people with either lower or higher socioeconomic status (SES).2 Health inequalities of different types (including economic, gender-related and racial) exist all over the world both among and within communities6 so that it has recently received a considerable global attention.7 Understanding the extent and the characteristics of inequalities is a vital prerequisite to effective planning for change. In other words, health authorities need to know the extent to which their policies have caused or will cause inequalities in order to develop plans for revising policies and minimizing inequalities.8 One of the goals of healthy community programs is to eradicate health inequalities among people with different genders, ethnicities, races, educational status, levels of income and geographical locations.9 Nonetheless, despite the commitment of governments and health systems to promote health indices, there are still wide disparities among different social groups in terms of their health status. Such disparities may finally result in health injustice. Fortunately, health disparities can be prevented and managed through taking appropriate measures, thus different countries have devised strategies to manage them.10 For instance, in our country, Iran, equity in health is among the major aims of the Iranian healthcare delivery system.11 Trauma, due to its emergency nature, as well as apparently identical access to care services, seems to be protected from inequality.12 However, studies showed gender differences in terms of trauma incidence13–16 as well as socioeconomic differences regarding trauma incidence,14,15,17–19 trauma type19 trauma-induced death,12,15,20 trauma care,21,22 post-trauma disability,23–26 post-trauma RTW.27–30 Such differences are usually against people with low SES. Moreover, some studies revealed that there are inequalities among people with different insurance status in terms of mortality rate12,31,32 and access to diagnostic, therapeutic and rehabilitation services.31,33,34 The relationship between inequality and trauma outcomes is important to all countries. Understanding the determinants of inequalities can pave the way for fair care delivery to all people irrespective of their SES. Our literature review revealed that no study has been conducted so far in Iran with regard to inequalities in trauma care. The present study was made to examine the relationship of SES with trauma outcomes. Methods This cohort study was undertaken from March 2014 to March 2015 on 600 trauma patients hospitalized in Shahid Beheshti hospital, Kashan, Iran. Kashan is located in central part of Iran with more than 400 000 populations and Shahid Beheshti hospital is the main trauma center in Kashan with annually admission rate of 7000 trauma patients. The total number of adult trauma patients who are hospitalized more than 24 h is ~4000 per year. We invited 1000 patients who had inclusion criteria but 600 patients agreed to participate in study and follow-up assessment. The patients were assessed prospectively. They were included if they had any intentional or unintentional injury, lived in Kashan county, aged 15–64, agreed to participate in the study, had no mental problem or disability before experiencing trauma (according to the patients or their family statement of any mental retardation, mental illness, physical disabilities such as skeletal abnormalities or defects), and were hospitalized for at least 24 h before being recruited to the study. Patients who were not accessible during the 3-month follow-up period of the study or their medical records were incomplete were excluded. I. Instruments The data collection instruments were a questionnaire on the patients’ demographic characteristics, trauma-related characteristics, and trauma outcomes, Injury sevirity score (ISS), a socioeconomic assessment check list, the Hospital Care Index (HCI), and World Health Organization Disability Assessment Schedule-II (WHODAS-II). The items of the demographic and trauma-related questionnaire were age, gender, marital and educational status, nationality, place of residence, employment status, cigarette smoking, alcohol and drug abuse, patient transfer vehicle, severity of injury, mechanism of injury, injured organ(s) and type of injury. Trauma outcomes were hospital care level, in-hospital death, disability and RTW. The SES was assessed based on Asset Index that represents a durable economic status than does either income or expenditure. It determined through performing Principal Component Analysis as proposed by O’Donnell et al. and Vyas et al.35,36 Accordingly, the new variable of Asset Index was generated by using 10 variables related to household asset (including ownership of home, dishwasher, LCD TV, refrigerator, microwave oven, car, personal computer, laptop, Internet access and household surface area) and two social factors (including employment and educational status of the head of family). Then, based on the median score and the percentiles of the Asset Index, the participants were divided into three groups of low, middle and high SES. The level of hospital care provided to the patients was also assessed through calculating HCI by performing principal component analysis. Accordingly, variables such as the number of medical visits, the number of medical consultations, the amount of time waiting for being admitted to a hospital ward and intensive care unit (ICU), the length of stay in the emergency department and ICU, and hospitalization-related costs were entered into the analysis. All these variables had been adjusted based on trauma severity and duration of hospitalization. Then, variables with an Eigen value of >1 were identified. These variables included the total of hospitalization costs, the number of medical visits and consultations, the duration of stay in the emergency department, and the time period between physicians’ order for patient transfer to actual patient transfer (from the emergency room to a hospital ward). Finally, based on the median of the first component, the patients were divided into the two groups of high and low hospital care level. Mortality data included hospital death after 24 h. Therefore, deaths at the time of arrival and first day were not recorded. The levels of disability at 1 and 3 months after trauma were assessed by using the 12-item WHODAS-II. This scale contains six subscales which come into the two main domains of ‘activity limitation’ and ‘participation’. The 12 items of the scale are scored on a Likert-type scale from 1 (No problem) to 5 (Extremely disabled). Therefore, the possible range of the total WHODAS-II score is 12–60 which is converted to a 0–100 scale; the higher the score, the more severe the disability.37 The validity and the reliability of the Persian version of the WHODAS-II have been confirmed in Iran.38 Finally, RTW was measured by using the following two questions: Have you returned to your work or daily activities? How long did it take for you to return to your work or daily activities? The questionnaires were filled out through interviewing the patients. The data of patients with altered consciousness were collected by interviewing one of their family members. Besides, the patients or family members were re-interviewed 1 and 3 months after hospital discharge in order to collect disability- and RTW-related data. II. Ethical considerations Before recruiting them to the study, the patients or the family members were informed about the aims of the study and were ensured that their data (particularly the data on their SES) would remain confidential. Then, their verbal informed consent was obtained. Besides, this study was approved by the Ethics Committee of Kashan University of Medical Sciences, Kashan, Iran. III. Data analysis The SPSS (v. 16.0) and the STATA (v. 12.1) software were used for data analysis. The Kolmogorov–Smirnov test was used for assessing data normality. Participants with different SES were compared with each other in terms of trauma outcomes through running the Chi-square test. On the other hand, inequality assessment was performed through employing the concentration index technique. Accordingly, a dichotomous variable was generated for each of the variables that were significantly correlated with SES. Then, the concentration curve of each of the generated dichotomous variables was plotted against the distribution of the asset index. The concentration curve plots the cumulative percentage of the variable of health (Y axis) against the cumulative percentage of population, ranked based on economic status from poorest to richest (X axis). If all people, irrespective of their economic status, have exactly the same level of health, the concentration curve will be a 45° line which is called ‘the line of equality’. On the other hand, if the health variable has greater concentration among poor people, the concentration curve falls above the line of equality, denoting inequality; the greater the distance between the curve and the line, the greater the inequality.35 Concentration index is the surface area between the curve and the equality line multiplied by 2. Consequently, when the concentration curve lies exactly on the line of equality the concentration index is equal to zero; when it falls above or below the line of equality, the concentration index takes negative or positive values, respectively. The concentration index value can range between −1 and +1.39 Results The results of the Kolmogorov–Smirnov test illustrated that the distribution of the study variables was not normal. In total, 600 patients were approached from which, 11 patients did not respond to our follow-up phone contacts and thus, were excluded (a follow-up rate = 98.2%). In addition, 19 patients died during the study and hence, when we assessed the trauma outcomes of disability and RTW, the sample size was 570. The SES of the patients was as follows: low: 36.3%; middle: 30.5%; and high: 33.2%. The findings indicated that 59.3% of the participants aged <35, 85.8% were males, and 89.7% were urban dwellers. Besides, 88.8% of them were Iranian, 62.5% were married, 79.3% had below-diploma education, 66.3% were employed and 71.7% maintained insurance. In addition, 19% of the participants were cigarette smokers, 5.8% were drug abusers, and 1.8% reported with alcohol intake. The main mechanism of trauma was traffic accidents (64.5%) and most patients (74.2%) had been transferred to the hospital by Emergency Medical Service (EMS). Moreover, 59.8% of the traumas were single organ injury and the commonest injured organs were the extremities and the pelvis (76.5%). The mean (SD) and the median of the ISS were 10.2(7.2) and 9, respectively. The death rate among the participants was 3.2% and 49.7% of the participants received high level of hospital care. Three months after the incidence of trauma, 64.2% of the patients reported some levels of disability and 71.4% returned to their work or activities of daily living. As shown in Table 1, most cases of high-level hospital care and RTW were from patients with high SES while most cases of trauma-induced disability and death happened among patients with low SES. The results of the Chi-square test revealed that people with different SES significantly differed from each other concerning hospital care level, death and RTW. The risk ratio of trauma outcomes in different SES has been shown in Table 2. Table 1 The outcomes of trauma among patients with different SES SES outcome High Middle Low Total P valuea Hospital care level Low 85 (46.5) 125 (57.3) 302 (50.3) 92 (46.2) 0.03 High 98 (53.5) 93 (42.7) 298 (49.7) 107 (53.8) Death No 179 (97.8) 206 (94.5) 581 (96.8) 196 (98.5) 0.04 Yes 4 (2.2) 12 (5.5) 19 (3.2) 3 (1.5) Disability No 68 (38.6) 63 (31.3) 204 (35.8) 73 (37.8) 0.26 Yes 108 (61.4) 138 (68.7) 366 (64.2) 120 (62.2) RTW No 45 (25.6) 76 (37.8) 163 (28.6) 42 (21.8) 0.001 Yes 131 (74.4) 125 (62.2) 407 (71.4) 151 (78.2) SES outcome High Middle Low Total P valuea Hospital care level Low 85 (46.5) 125 (57.3) 302 (50.3) 92 (46.2) 0.03 High 98 (53.5) 93 (42.7) 298 (49.7) 107 (53.8) Death No 179 (97.8) 206 (94.5) 581 (96.8) 196 (98.5) 0.04 Yes 4 (2.2) 12 (5.5) 19 (3.2) 3 (1.5) Disability No 68 (38.6) 63 (31.3) 204 (35.8) 73 (37.8) 0.26 Yes 108 (61.4) 138 (68.7) 366 (64.2) 120 (62.2) RTW No 45 (25.6) 76 (37.8) 163 (28.6) 42 (21.8) 0.001 Yes 131 (74.4) 125 (62.2) 407 (71.4) 151 (78.2) aChi-square test. Table 1 The outcomes of trauma among patients with different SES SES outcome High Middle Low Total P valuea Hospital care level Low 85 (46.5) 125 (57.3) 302 (50.3) 92 (46.2) 0.03 High 98 (53.5) 93 (42.7) 298 (49.7) 107 (53.8) Death No 179 (97.8) 206 (94.5) 581 (96.8) 196 (98.5) 0.04 Yes 4 (2.2) 12 (5.5) 19 (3.2) 3 (1.5) Disability No 68 (38.6) 63 (31.3) 204 (35.8) 73 (37.8) 0.26 Yes 108 (61.4) 138 (68.7) 366 (64.2) 120 (62.2) RTW No 45 (25.6) 76 (37.8) 163 (28.6) 42 (21.8) 0.001 Yes 131 (74.4) 125 (62.2) 407 (71.4) 151 (78.2) SES outcome High Middle Low Total P valuea Hospital care level Low 85 (46.5) 125 (57.3) 302 (50.3) 92 (46.2) 0.03 High 98 (53.5) 93 (42.7) 298 (49.7) 107 (53.8) Death No 179 (97.8) 206 (94.5) 581 (96.8) 196 (98.5) 0.04 Yes 4 (2.2) 12 (5.5) 19 (3.2) 3 (1.5) Disability No 68 (38.6) 63 (31.3) 204 (35.8) 73 (37.8) 0.26 Yes 108 (61.4) 138 (68.7) 366 (64.2) 120 (62.2) RTW No 45 (25.6) 76 (37.8) 163 (28.6) 42 (21.8) 0.001 Yes 131 (74.4) 125 (62.2) 407 (71.4) 151 (78.2) aChi-square test. The results of inequality analysis showed that there were socioeconomic inequalities between patients with high and low SES in terms of hospital care and RTW. Moreover, the amount of inequality between these groups regarding the outcome of death was –0.190. Although the confidence interval of the concentration index indicates that this difference is not statistically significant, Figs. 1 and 2 show that inequality values for the two outcomes of hospital care and RTW are against people with low SES. In these two figures, the concentration curve is above the line of equality, i.e. in the area of negative values (Table 3). Table 2 The risk of trauma outcomes based on SES level SES Risk ratio CI 95% P value Low Hospital Care level High 1 Middle 0.89 0.74–1.06 0.2 Low 1.81 1.05–1.44 0.01 Death High 1 Middle 0.6 0.20–1.80 0.36 Low 3.12 1.20–7.51 0.01 Disability High 1 Middle 0.93 0.81–1.07 0.34 Low 1.11 0.98–1.25 0.1 Non-RTW High 1 Middle 0.71 0.50–1.01 0.05 Low 1.66 1.25–2.21 <0.001 SES Risk ratio CI 95% P value Low Hospital Care level High 1 Middle 0.89 0.74–1.06 0.2 Low 1.81 1.05–1.44 0.01 Death High 1 Middle 0.6 0.20–1.80 0.36 Low 3.12 1.20–7.51 0.01 Disability High 1 Middle 0.93 0.81–1.07 0.34 Low 1.11 0.98–1.25 0.1 Non-RTW High 1 Middle 0.71 0.50–1.01 0.05 Low 1.66 1.25–2.21 <0.001 Table 2 The risk of trauma outcomes based on SES level SES Risk ratio CI 95% P value Low Hospital Care level High 1 Middle 0.89 0.74–1.06 0.2 Low 1.81 1.05–1.44 0.01 Death High 1 Middle 0.6 0.20–1.80 0.36 Low 3.12 1.20–7.51 0.01 Disability High 1 Middle 0.93 0.81–1.07 0.34 Low 1.11 0.98–1.25 0.1 Non-RTW High 1 Middle 0.71 0.50–1.01 0.05 Low 1.66 1.25–2.21 <0.001 SES Risk ratio CI 95% P value Low Hospital Care level High 1 Middle 0.89 0.74–1.06 0.2 Low 1.81 1.05–1.44 0.01 Death High 1 Middle 0.6 0.20–1.80 0.36 Low 3.12 1.20–7.51 0.01 Disability High 1 Middle 0.93 0.81–1.07 0.34 Low 1.11 0.98–1.25 0.1 Non-RTW High 1 Middle 0.71 0.50–1.01 0.05 Low 1.66 1.25–2.21 <0.001 Table 3 Concentration index analysis Outcome Prevalence (%) Concentration index Standard error 95% Confidence interval Death 3.2 −0.190 0.119 0.042, −0.423 Low-level hospital care 50.3 −0.046 0.017 −0.012, −0.081 Non-RTW 32.8 −0.118 0.043 −0.202, −0.033 Outcome Prevalence (%) Concentration index Standard error 95% Confidence interval Death 3.2 −0.190 0.119 0.042, −0.423 Low-level hospital care 50.3 −0.046 0.017 −0.012, −0.081 Non-RTW 32.8 −0.118 0.043 −0.202, −0.033 Table 3 Concentration index analysis Outcome Prevalence (%) Concentration index Standard error 95% Confidence interval Death 3.2 −0.190 0.119 0.042, −0.423 Low-level hospital care 50.3 −0.046 0.017 −0.012, −0.081 Non-RTW 32.8 −0.118 0.043 −0.202, −0.033 Outcome Prevalence (%) Concentration index Standard error 95% Confidence interval Death 3.2 −0.190 0.119 0.042, −0.423 Low-level hospital care 50.3 −0.046 0.017 −0.012, −0.081 Non-RTW 32.8 −0.118 0.043 −0.202, −0.033 Fig. 1 View largeDownload slide Concentration index for Hospital Care. Fig. 1 View largeDownload slide Concentration index for Hospital Care. Fig. 2 View largeDownload slide Concentration index for death. Fig. 2 View largeDownload slide Concentration index for death. Discussion Main finding of this study The findings of the present study showed that most patients with low SES received low level of hospital care, also most cases of trauma-induced deaths happened among patients with low SES. Death rate among these patients was 3.6 times more than patients with high SES. Our findings also indicated that 3 months after trauma, disability rate was not statistically significant between low and high SES patients, but RTW rate in low SES group was significantly lower than high SES group. The concentration index analysis revealed slight inequality among patients with different SES regarding the outcomes of level of hospital care and RTW. Inequality in death outcome was not seen between different SES. What is already known on this topic To the best of our knowledge, this is the first study of its kind to assess SES among trauma patients. Numerous studies have been conducted in the world in order to assess inequalities in hospital care, trauma-related mortality and access to rehabilitation services among people with different genders, ethnicities, races or insurance status. Several population-based studies in Iran also showed the significant correlation of SES with the incidence and the mortality rate of trauma. Nonetheless, no study had yet assessed socioeconomic inequalities and its relationship with in-hospital death, hospital care, disability and RTW. What this study adds The difference in level of hospital care between low and high SES was significant and in favor of high SES patients (53.8 versus 42.7%). It is noteworthy that none of the previous studies has assessed hospital care so far, even though some of them evaluated care-related indicators such as the length of hospital stay, the availability of diagnostic or therapeutic care services, or the waiting time for undergoing surgeries. Some studies reported that SES has no significant effect on the waiting time for undergoing surgeries.40,41 However, the results of two studies illustrated inequalities in the waiting time for surgeries among patients with hip fracture.21,42 Colais et al.22 also found that people with low SES are more likely not to receive diagnostic and therapeutic interventions. In our study, patients with low SES also had significantly longer hospital stay than patients with high SES (6.9 ± 7.9 versus 5.4 ± 5.7 days). This difference may be due to insurance coverage during hospitalization especially for traffic-related injuries and implementation of health system reform plan in Iran, in which out of pocket payments for medical care are reduced. Therefore patients prefer stay at hospital to full recovery. One study demonstrated that people with high SES had longer hospital stay.43 On the contrary, another study in Canada revealed that people with low SES had longer stay in hospital due to lack of equipment and facilities for long-term care and lack of sources for covering post-discharge care-related costs.44 The results of a study in Sudan also illustrated longer hospital stay among patients with low SES.45 The findings of the present study also revealed a mortality rate of 3.2% among trauma patients. Previous studies have reported different in-hospital trauma-related mortality rate. For instance, Paravar et al.46 reported an in-hospital mortality rate of 6.1% in Kashan city. This value is higher than the rate found in our study probably due to the fact that they made their study on patients of all age groups who had been transferred to hospital by EMS. The severity of trauma among patients who are transferred by EMS is usually greater than other patients. Besides, our participants were trauma patients who stayed in hospital for more than 24 h while they studied the patients who had experienced death both during and after the first 24 h of their hospitalization. The results of another study in Philippine also revealed an in-hospital mortality rate of 4.7%.47 The higher mortality rate in this study compared with our study can also be attributed to the differences in the eligibility criteria in these two studies. In-hospital mortality rate in a study conducted in Shiraz, Iran, was as high as 11.2% which is much higher than the rate in our study due to the fact that the participants in that study were 18–80-year-old patients who suffered from multiple traumas and had an ISS of >9.48 However, a study in Tehran, Iran, showed an in-hospital mortality rate of 3. Like our study, the commonest mechanism of trauma and the commonest cause of death in that study were road traffic accidents and head injuries, respectively.49 Study findings also showed that death rate among patients with low SES was 3.6 times more than patients with high SES. Mays et al.20 reported SES as an independent predictor of post-trauma mortality. The results of two studies conducted in Italy on patients with hip fracture also illustrated a significant relationship between low SES and 30-day mortality.21,22 Results of a study in Canada showed that the chance of trauma-related mortality is higher among people with low SES, while people with high SES have longer hospital stay and are more likely to be transferred to other clinical settings.43 In our study, 64.2% of patients reported some levels of disability 3 months after hospital discharge. Previous studies reported disability rates of 20–80% among trauma patients.50–53 Such a wide range of disability rate can be attributed to the differences in the disability assessment instruments, the time of disability assessment, and the samples in these studies. For instance, Evans et al.51 reported that 1 year after experiencing major traumas; disability rate was 80% while we assessed patients with different types of traumas in a follow-up period of 3 months. In present study difference in disability between low and high SES was not statistically significant. Some previous studies demonstrated a significant relationship between disability and SES. Most of these studies were conducted at community level and on traffic accident traumas which are usually more severe than other types of trauma, are more prevalent among people with low SES, and are associated with higher disability rates.23,24,26 Safa et al.25 also reported a significant negative correlation between SES and dependency in daily living activities i.e. the lower the SES, the higher the dependency. The difference between our findings and findings reported by Safa et al. is probably due to the differences in the study population in these two studies in that while their participants were elderly people who are usually unemployed and financially and physically dependent, our participants were 15–64-year-old patients who are usually employed and have income. Besides, SES assessment instruments in these two studies were different. The results of a study showed that after eliminating the effects of confounders, disability was not significantly correlated with SES.45 In Iran, the Traffic Accident Victims Law has been implemented since 2008 by which, all hospitalization costs of these patients are paid by insurance companies. Moreover, according to the Iranian Health System Reform Plan, the hospitalization-related costs of other trauma victims have been reduced since 2014. In addition, most of our participants had insurance and were probably able to pay for their rehabilitation treatments costs. Our findings also revealed that 407 patients (71.4%) returned to their work or activities of daily living after 3 months. In other words, 28.6% of them had no RTW due to medical order for avoiding activities (24.4%), loss of employment (12.2%), incomplete recovery (59.3%) or other reasons (4%). Loss of employment is of paramount importance to trauma patients. In our study, from among 15 patients who lost their employment, 11 ones (73.3%) had low SES and two ones had high SES. These findings denote that patients with low SES are more at risk for post-trauma employment-related damages and thus, they need stronger social support. The results of a study made by El Tayeb et al.45 illustrated that the rate of employment loss was 9.3%, and in line with our findings, they showed a greater risk for post-trauma employment loss among people with low SES. Previous studies reported that the prevalence rate of return to work/education/activities of daily living is 15–80%.27,29,53–58 RTW rate in our study was different from other studies. An explanation for this difference in RTW rate in these studies is that some of them focused on certain traumas such as trauma to the extremities54 and others dealt with multiple traumas57 or major traumas.53,56 While, we assessed return to work/education/activities of daily living among patients with different types of trauma and thus, found a high RTW rate compared with most previous studies. Another explanation is the difference in the time of measuring post-trauma RTW.28,54,56,59,60 RTW rate among patients with low SES was significantly lower than patients with high SES (62.2 versus 78.2%). Some previous studies also reported SES as a predictor of RTW.27–30 Also in recent study by Abedzadeh et al. (2017) RTW time was significantly longer in low SES patients.61 People with higher SES are more likely to return to their work after trauma because they have higher income, greater job stability, better insurance status, and stronger social support. On the other hand, people with lower SES are more likely to lose their employment after trauma because they mostly do manual labors (such as farming) which need superior physical health status. Our findings revealed that even among patients with similar levels of disability, RTW rate was still higher among patients with high SES. In cases with moderate disability, RTW rate in low and high SES was respectively 13.6 and 17.6%; and in cases with mild disability this rate was 55.4 and 78.6%, respectively. The results of concentration index analysis revealed slight inequality among patients with different SES regarding the outcome of high-level hospital care (concentration index = –0.046 and SE = 0.017). As shown in Fig. 1, this slight inequality was against patients with low SES. Moreover, the findings revealed that although patients with low SES were more at risk for experiencing death, inequality analysis revealed no significant difference between patients with low and high SES. This finding denotes that at hospital level, other factors (such as the type of injured organ, the level of hospital care and the severity of trauma) may be the predictors of death. Concentration index analysis on the outcome of RTW also indicated an inequality value of –0.118 (SE = 0.043) which was against patients with low SES. Figure 3 also depicts that the concentration curve is above the line of equality, i.e. in the area of negative values. Fig. 3 View largeDownload slide Concentration Index for RTW. Fig. 3 View largeDownload slide Concentration Index for RTW. The outcomes which were assessed in the present study had not been subjected to inequality analysis in previous studies. Moreover, studies in this area are usually population-based and hence, their findings cannot be compared with our findings. For instance, Safari-Faramani et al. (2013) made a study in Tehran, Iran, in order to assess socioeconomic inequality in unintentional injuries among children and found that concentration index for all injuries was 0.40 while the index for traumas caused by traffic accidents, falls, burns and poisoning was equal to –0.41, –0.37, –0.62 and –0.35, respectively. Consequently, they concluded that there are substantial differences among different SES groups regarding unintentional injuries among children.18 Inequalities in patient outcomes may be due to different factors included differences in the approaches to care delivery. For instance, the results of a study revealed disparities in acute post-trauma care services.12 Care-related inequalities have been also reported to exist in the United States, England, Canada and many other western countries.22 Although healthcare workers aim at providing equal care services to all patients, heuristic and bias are usually inevitable, particularly in critical care units.20 Limitation and strength of this study One of the study limitations was that the data on the patients’ income and disability status were collected through self-reporting which is usually associated with measurement biases. Another limitation was the coincidence of the present study with the implementation of the Iranian Health System Reform Plan. The Plan significantly reduced patients’ healthcare costs and thus, it might have affected the findings of our study. In addition, we had no information about patients’ status before the implementation of this Plan and hence, before-after comparison was not feasible. Last but not the least; the follow-up period of the study was relatively short. On the other hand, one of the study strengths was its small attrition rate (a follow-up rate of 98.2%). In addition, this study was the first of its kind to assess SES at hospital level and the first cohort study to evaluate the outcomes of disability and RTW among trauma patients by using a valid and reliable instrument. Assessing HCI was other strength of the present study. Conclusion Some trauma outcomes are associated with socioeconomic inequalities. In other words, patients with low SES are more at risk for receiving low-level of hospital care and experiencing non-RTW. Consequently, greater attention and stronger social support needs to be paid to economically vulnerable patients who experience trauma. The findings revealed that SES affects trauma outcomes such as death. Therefore, providing better hospital care to patients with lower SES can play a significant role in reducing death rate among them. Moreover, these patients need to be provided with more efficient follow-up services because they usually have inadequate insurance and limited access to costly post-discharge rehabilitation services and thus, are at greater risk for delayed recovery, disabilities, non-RTW and employment loss. Future studies are recommended to examine the relationship of SES with trauma outcomes at national level, in both public and private hospitals, in larger and more homogenous populations (in terms of the type and the severity of trauma), and with longer follow-up periods. Acknowledgements We express our thanks to Deputy of Research of Kashan University of Medical Sciences for its financial support in this study and also staff of Trauma Research Center and Shahid Beheshti Hospital for their co operation. Funding This study was supported by deputy of research, Kashan University of Medical Sciences (Grant no. 9303). References 1 Krug EG , Sharma GK , Lozano R . The global burden of injuries . Am J Public Health 2000 ; 90 ( 4 ): 523 – 6 . Google Scholar CrossRef Search ADS PubMed 2 Hofman K , Primack A , Keusch G et al. . Addressing the growing burden of trauma and injury in low- and middle-income countries . Am J Public Health 2005 ; 95 ( 1 ): 13 – 7 . Google Scholar CrossRef Search ADS PubMed 3 World Health Organization .The Global burden of disease: 2004 Update. Geneva, 2008 4 Bonnie RJ , Fulco C , Liverman C . Reducing the Burden of Injury: Advancing Prevention and Treatment . Washington, DC : Natl. Acad. Press , 1999 . 5 Haddon W . 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Published: Mar 1, 2018

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