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• W2893433731 abstract "Identifying ethnic inequalities in health requires data with sufficiently ‘granular’ (fine detailed) classifications of ethnicity to capture sub-group variation in healthcare use, risk factors and health behaviors. The Robert Wood Johnson Foundation (RWJF), in the USA, commissioned us to explore granular approaches to ethnicity data collection outside of the USA, commencing with the European Union. We examined official data sources (population censuses/registers) within the EU-28 to determine the granularity of their approach to ethnicity. When ethnic information was not available, related variables were sought (e.g. country of birth). Within the EU-28, we found 55% of countries collected data on ethnicity. However, only 26% of these countries (England, Wales, Northern Ireland, Scotland, Republic of Ireland, Hungary, Poland and Slovakia) had a granular approach, with half of these being within the UK. Estonia, Lithuania, Croatia, Bulgaria, Republic of Cyprus and Slovenia collected one to six categories. A ‘write-in’ option only was found in Latvia, Romania and the Czech Republic. Forty-five percent of countries did not collect ethnicity data but collected other related variables. (i) Although there is reasonable attention to the diversity of ethnic groups in data collection, a granular approach does not predominate within EU-28 classifications. (ii) Where ethnicity is collected, it is conceptualized in different ways and diverse terminology is used. (iii) A write-in option provides the most granular approach. (iv) Almost half of the countries did not collect data on ethnicity, but did collect related variables that could be used as a proxy." @default.
• W2893433731 created "2018-10-05" @default.
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• W2893433731 date "2018-09-26" @default.
• W2893433731 modified "2023-10-17" @default.
• W2893433731 title "Heterogeneity/granularity in ethnicity classifications project: the need for refining assessment of health status" @default.
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• W2893433731 doi "https://doi.org/10.1093/eurpub/cky191" @default.
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