Nazmy Villarroel1,2, Emma Davidson1, Pamela Pereyra-Zamora3, Allan Krasnik4, Raj S Bhopal1. 1. Edinburgh Migration, Ethnicity and Health Research Group, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Scotland, UK. 2. Graduate Entry Medical School, University of Limerick, Ireland. 3. Research Unit for the Analysis of Mortality and Health Statistics, Department of Community Nursing, Preventive Medicine, Public Health and History of Science, University of Alicante, Spain. 4. Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
Abstract
BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: (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.
BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: (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.
Authors: Eva L van der Linden; Brandon N Couwenhoven; Erik J A J Beune; Joost G Daams; Bert-Jan H van den Born; Charles Agyemang Journal: J Hypertens Date: 2021-02-01 Impact factor: 4.776