A total of 28,216 AMI patients met our eligibility criteria. Patients were more likely to be male across all income quintiles; however, this difference was more pronounced in higher income quintiles (Table ). This likely reflects the fact that female AMI patients are older and thus less likely to be earning employment income than their male counterparts. Patients in the highest income quintile were slightly younger than patients in other income quintiles. Those in the highest income quintile were also slightly more likely to live in urban areas and were generally in better health (as measured by their fewer number of ADGs) than those in lower income quintiles. It should be noted that for all sex-stratified analyses, sex-stratified income quintiles were used, so there were equal numbers of women in each income quintile, and our results were not affected by the sex differences across income quintiles reported in Table .
Distribution of Variables in the AMI Study Population
Crude rates of initiation of ACE-inhibitors, beta-blockers, statins and all three medicines as well as 95% confidence intervals are listed in Table . Table also notes the mean income in each quintile for both men and women. Men had higher mean incomes in each quintile than women. For male AMI patients, those in income quintiles 4 and 5 had significantly higher rates of initiation for all medicines following AMI than those in quintiles 1, 2 and 3. While the same was true for women with respect to initiating treatment with beta-blockers, there were generally fewer significant differences in initiation rates across the income gradient for women. However, F-statistics reject the null hypothesis that the mean rate of initiation is the same across income quintiles for both men and women and for all of the medicines studied (Table ).
Crude Rates of Initiation of ACE-Inhibitors, Beta-Blockers, Statins and All Three Medicines in the 120 Days Post-Discharge from Hospital for AMI
Tables and present adjusted odds ratios modeling the relationship between income quintile and likelihood of initiation of treatment with ACE-inhibitors, beta-blockers, statins and all three medicines in the 120 days post-discharge from hospital after first AMI in men and women, respectively. After age, general health status and urban residence were accounted for, men in the third income quintile or higher were significantly more likely to initiate ACE-inhibitors, beta-blockers and statins than men in the first income quintile. Men in the fifth income quintile had 37%, 50% and 71% higher odds of initiating ACE-inhibitors, beta-blockers and statins, respectively, than those in the lowest income quintile [OR = 1.37 95% CI (1.24, 1.51); OR = 1.50 95% CI (1.35, 1.68); and OR = 1.71 95% CI (1.53, 190)]. Adhering with treatment guidelines and initiating all three medicines was significantly more likely for men in the 4th and 5th income quintiles [OR = 1.12 95% CI (1.02, 1.24) and OR = 1.30 95% CI (1.18, 1.43)].
Men: Regression Results for Initiation of ACE-Inhibitors, Beta-Blockers and Statins in the 120 Days Post-AMI by Income Quintile
Women: Regression Results for Initiation of ACE-Inhibitors, Beta-Blockers and Statins in the 120 Days Post-AMI by Income Quintile
Table suggests that the adjusted relationship between household income and initiation of treatment is not as clear among women. Women in the fourth income quintile were more likely to initiate ACE-inhibitors than those in the lowest income quintile [OR = 1.15 95% CI (1.01, 1.32)]. Women in the highest income quintile were also significantly more likely to use beta-blockers and statins than those in the lowest income quintile [OR = 1.25 95% CI (1.06, 1.47) and OR = 1.32 95% CI (1.12, 1.54)]. There were no significant differences in initiation of treatment with all three medicines; however, the mean rate of initiation on all three medicines among women is a relatively low 36.0%.
As an example of the results found when examining the use of medicines before and after the policy change, Table contains results of sex-stratified models describing use of ACE-inhibitors and includes the policy change indicator and interaction terms. None of the interaction terms between the income quintiles and the policy change are significant in either of the sex-stratified models, suggesting that the relationship between income and initiation of treatment was not significantly affected by the policy change. These interactions between income and the policy change were insignificant in models for all dependent variables studied (results available in an online appendix
). Models run separately pre-policy and post-policy also demonstrated that income gradients existed before and after the policy change (results also available in an online appendix
Regression Results Examining Whether the Relationship Between Income and Initiation of ACE-Inhibitors Changed After the Policy Change