2 to 15.1; table 3). The least wealthy participant also had higher odds of diagnosis (ORs 1.1–4.5) and either no different or relatively small odds of treatment (ORs 0.9–2.6; table 3 and figure 1). Table 3 supplier Adriamycin Illness burden, self-reported medical diagnosis and treatment of angina, cataract, depression, diabetes and osteoarthritis, comparing the least wealthy with the most wealthy: logistic regression Figure 1
Illness burden (in blue), self-reported medical diagnosis (in green) and treatment (in red) of angina, cataract, depression, diabetes and osteoarthritis, comparing the least wealthy with the most wealthy: Overall ORs (adjusted for age and sex) and 95% … For angina, the overall OR for meeting the criteria for ‘illness burden’ was 7.6, indicating that the hypothetically least wealthy individual was seven times more likely to have angina symptoms (defined by the Rose Angina scale) than the wealthiest. The OR for self-reported medical diagnosis was 4.5, suggesting that some less wealthy people with angina symptoms had not received a diagnosis of angina, as the expected OR for equitably distributed diagnosis would have been 7.6. The OR for treatment was
3.2, and again the expected ORs for equitably distributed treatment would have been 7.6. For depression, the overall OR for illness burden was 6.4, for medical diagnosis was 3.3 and for treatment was 2.6, again suggesting that some poorer people with symptoms of depression were less likely to have received a diagnosis or indicated healthcare, as the expected ORs for equitably distributed treatment would have been 6.4. For diabetes, the overall OR for illness burden was 4.2 and 4.0 for diagnosis, suggesting that for diabetes, diagnosis was distributed equitably. However, the OR for treatment was 0.9 and not statistically significantly different from 1, again suggesting that some less wealthy people with medically diagnosed diabetes had not received treatment, as the expected OR for equitably distributed treatment would have been 4.2. The subsidiary analysis calculated the OR of receiving a diagnosis by a subsequent
wave only for those who had met the criteria for ‘illness burden’ for the relevant long-term condition in a previous wave, and then the likelihood of receiving GSK-3 treatment only for those who had received a medical diagnosis in a previous wave. The substantial inequalities in the illness burden of conditions by wealth are identical to table 3, as expected, and subsequently the numbers of eligible participants dwindle rapidly due to the nested nature of the analysis, with some wide CI and 9 out of 10 results not statistically significant (see online supplemental file 1). Discussion We found that while there were strong inverse associations between wealth and the burden of illness (based on validated scales, symptoms and biomarker) of a long-term condition, there were smaller or absent inequalities in receipt of self-reported medical diagnosis or treatment for the conditions considered.