Abstract

Bhopal provides an important and timely paper. The census categories for ethnic groups have recently been revised, and there is now explicit emphasis on public health approaches to managing ethnic inequalities in health status and providing effective interventions to reduce inequalities. The shift of policy from addressing inequalities to social inclusion and a broader equalities agenda in which race is one component is also a relevant policy development that this paper challenges. The paper also proposes that the cultural histories and more recent experiences of individuals and groups should not be ignored in understanding inequalities. Bhopal argues that a shared understanding between professionals and public alike is desirable and necessary to reduce inequalities. Achieving such shared understanding on a topic that is often emotionally charged and not value neutral is difficult. The premise of the paper is that a racism-free social environment is a necessary backdrop to making use of routine data. This is unlikely to be achievable, as ever refined forms of individual and structural prejudice and racism have existed in societies far back into human history and are unlikely to disappear. A different approach is that racism and prejudice are part of the human condition and inevitable, and also emerge as inter-group tensions either in the face of scarce resources or simply when relatively isolated groups interact; isolation here may be cultural, linguistic, economic, psychological or geographical. Lack of knowledge and understanding and alienation of the ‘other’ may then be used to justify all sorts of well-intentioned treatment. Not only can social structures generate and sustain inequalities, but science, although it purports to be objective and value neutral, does not have an untarnished history; examples of scientific racism or failures of logic may still emerge. Therefore, it is a professional responsibility to manage such processes, where evident, in order to minimize inequalities. Professionals should also be active to improve the literacy around discrimination and prejudice, and investigate manifestations and mechanisms of inequalities and racism in health care. This debate has to be evidence based and challenge convenient but ineffective policy responses. Therein lies the challenge that evidence takes many forms, and must provide clinical and policy guidelines where the evidence is strong and practical; and the evidence has to relate to real-world situations rather than remaining in the form of complex statistical models with numerous methodological limitations including residual confounding, insufficient power to investigate interactions and poor definition of ethnic groups and factors that may explain ethnic inequalities. The issue of misclassification by ethnic group remains an important problem for researchers. Although there is a move to improve precision of ethnicity categorization, the balance between utility and ethnic misclassification is a major issue for routine data as well as hypotheses-driven research. No matter how many ethnic categories are generated on assumptions of approximating to ever complex ethnic identities, this process is fundamentally imperfect. New categories included in census options for ethnic coding are still ‘ascribed identities’ that are assumed to be meaningful to all in that category. These may never capture an individual’s experienced identity. The notion that we should aspire to minimize risk to those of the lowest risk group is a good one. However, acculturation influences health risks over time and is important for the resident host population as well as the migrant population. The process of classifying people on the basis of ethnicity alone neglects numerous variables, including identity, acculturation, religiosity, integration and acceptance of host values and lifestyle. Cultural identity influences consumption patterns, and can govern forms of social support, gender disadvantage and access to employment. These

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