Despair on disparities.

In this issue of Annals of the Rheumatic Diseases, Sokka et al (see page 1666), by analysing the data from the Quantitative Standard Monitoring of Rheumatoid Arthritis (QUEST-RA) cohort, with over 6000 patients from 25 countries, warn us of possible disparities in the health of patients with rheumatoid arthritis. This international team of researchers found a clear association between gross domestic product and the average status of the patients. We believe it is imperative to review some concepts that may help to understand the implications of these results. Health inequalities, disparities, or variability in health, may be defined as differences in health status or in the distribution of health determinants between different population groups (ie, differences in mobility between older individuals and younger ones, or differences in death rates between social classes). It is important to distinguish them from inequities. Inequity means that the difference is unfair, a matter of injustice. Some health inequalities are attributable to biological variations or even to the free choice of individuals, while others may be attributable to external sources, mainly outside the control of those concerned. In the first case it may be impossible, or ethically or ideologically unacceptable to modify the health determinants and so the health inequalities are inevitable. In the second, the uneven distribution may be unnecessary and avoidable as well as unjust and unfair, so that the resulting health inequalities also lead to inequity in health. 3 Reports on health inequalities exist between countries, within countries, between regions, health systems (including hospitals and doctors), individuals, etc, for which different explanatory reasons have been proposed (socioeconomical, political, cultural, etc.). Differences in death rate are some of the most relevant health inequalities reported and, with regard to socioeconomic factors, some of the most important associated factors. According to the World Health Organization (WHO), life expectancy in high-income countries is 79.4 years whereas it barely reaches 49.2 years in low-income African countries. In poor countries, more than 80% of deaths are related to infections, an avoidable cause that is related to only 4% of the deaths in rich countries. In addition, 7 out of 10 child deaths occur in Africa and South East Asia. These data clearly highlight that health inequalities all around the world are largely caused by economic differences. Political conflicts, weak health systems, barriers to access, inadequate human resources, poor infrastructures, as well as cultural beliefs and learnt behaviours continue to be major obstacles in low-income countries. Although probably not to the extent of what has been observed in poor countries, we may also find health inequities in developed countries. In a recent publication, 22 European countries exhibited differences in death rate from selected causes, the authors suggesting that some variations could be attributable to differences in smoking, alcohol intake and access to health care. Also, geographic variability in the same country has been recognised as a major factor in prescribing for chronic diseases in older people, or in attitudes towards elective caesarean section on maternal request, etc. Inequalities are unfair. Distinguishing between health inequalities and health inequities can be contentious. Our view is that inequalities become ‘‘unfair’’ when poor health is itself the consequence of an unjust distribution of the underlying social determinants of health (for example, unequal opportunities in education or employment). Sometimes it is unknown to what extent health variability or inequalities are modifiable or due to biology. But often, investigations into the health of groups and the determinants of health inequities that lie outside the control of the individual have received a much smaller share of research resources. Even with these limitations, unfortunately, several health inequities are present in the world. Gender inequities, for instance, have extensively been reported. It is estimated that blindness and severe visual impairment from cataracts could be reduced by around 11% in the low-income and middle-income countries if women were to receive cataract surgery at the same rate as men. In Chile, in the private health sector women pay higher insurance premiums than men, and among children, boys aged 2 years or less have 2.5 times more preventive consultations than girls. There are plenty of examples of variability in rheumatology, such as those in lupus, with poorer patients having poorer outcomes, in scleroderma, juvenile idiopathic arthritis, or osteoarthritis. In rheumatoid arthritis (RA) there are examples of variability in drug utilisation, in access to specialist services, 20 and in outpatient consultation, hospitalisation, or surgical rates, including joint replacement procedures, with poorer patients faring lower in all rates. Interestingly, socioeconomic features are documented as a main factor in health inequalities in patients with musculoskeletal disorders in health systems with universal insurance coverage and in those without it. This is what Sokka et al’s article is mainly related to: socioeconomic or related factors underlying differences in health status. Furthermore, some authors preclude collecting measures of deprivation for patients enrolled in clinical trials, longitudinal observational studies and in the clinical setting, as they may be sound confounders. Besides socioeconomic factors, other sources of health disparities in rheumatology are at play: patients’ preferences, 30 age and ethnicity, factors related to the doctor or the centre, 33 and other cultural or economic factors that may interfere with, for instance, the return to work in patients with the same disease severity. How could we identify opportunities for reducing inequalities in health? First of all, measuring disparities should advise us on where to start with. For this purpose, there are many efforts now within European rheumatology, such as the European Musculoskeletal Conditions Surveillance and Information Network (eumusc.net) joint European League Against Rheumatism (EULAR)/European Union (EU) sponsored dynamic database covering the best available data on the occurrence, impact and availability of health care resources relevant to musculoskeletal disorders in the different member European countries (http://www.eular. org/), and at a larger level, such as the International World Bank initiative updating data used in the Global Burden of Disease project. Secondly, there is a need to improve performance by reviewing Research Unit, Fundación Española de Reumatologı́a, Madrid, Spain