Dataset Information

UK ethnicity data collection for healthcare statistics: the South Asian perspective.

ABSTRACT:

Background

Ethnicity data collection has been proven to be important in health care but despite government initiatives remains incomplete and mostly un-validated in the UK. Accurate self-reported ethnicity data would enable experts to assess inequalities in health and access to services and help to ensure resources are targeted appropriately. The aim of this paper is to explore the reasons for the observed gap in ethnicity data by examining the perceptions and experiences of healthy South Asian volunteers. South Asians are the largest ethnic minority group accounting for 50% of all ethnic minorities in the UK 2001 census.

Methods

Five focus groups, conducted by trained facilitators in the native language of each group, recruited 36 South Asian volunteers from local community centres and places of worship. The topic guide focused on five key areas:1) general opinions on the collection of ethnicity, 2) experiences of providing ethnicity information, 3) categories used in practice, 4) opinions of other indicators of ethnicity e.g. language, religion and culture and 5) views on how should this information be collected. The translated transcripts were analysed using a qualitative thematic approach.

Results

The findings of this Cancer Research UK commissioned study revealed that participants felt that accurate recording of ethnicity data was important in healthcare with several stating the increased prevalence of certain diseases in minority ethnic groups as an appropriate justification to improve this data. The overwhelming majority raised no objections to providing this data when the purpose of data collection is fully explained.

Conclusions

This study confirmed that the collection of patients' ethnicity data is deemed important by potential patients but there remains uncertainty and unease as to how the data may be used. A common theme running through the focus groups was the willingness to provide these data, strongly accompanied by a desire to have more information with regard to its use.

SUBMITTER: Iqbal G

PROVIDER: S-EPMC3339513 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

UK ethnicity data collection for healthcare statistics: the South Asian perspective.

Iqbal Gulnaz G Johnson Mark Rd MR Szczepura Ala A Wilson Sue S Gumber Anil A Dunn Janet A JA

BMC public health 20120327

<h4>Background</h4>Ethnicity data collection has been proven to be important in health care but despite government initiatives remains incomplete and mostly un-validated in the UK. Accurate self-reported ethnicity data would enable experts to assess inequalities in health and access to services and help to ensure resources are targeted appropriately. The aim of this paper is to explore the reasons for the observed gap in ethnicity data by examining the perceptions and experiences of healthy Sout ...[more]

PMID: 22452827

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Project description:Aims/hypothesisExcess risks of type 2 diabetes in UK South Asians (SA) and African Caribbeans (AC) compared with Europeans remain unexplained. We studied risks and determinants of type 2 diabetes in first- and second-generation (born in the UK) migrants, and in those of mixed ethnicity.MethodsData from the UK Biobank, a population-based cohort of ~500,000 participants aged 40-69 at recruitment, were used. Type 2 diabetes was assigned using self-report and HbA1c. Ethnicity was both self-reported and genetically assigned using admixture level scores. European, mixed European/South Asian (MixESA), mixed European/African Caribbean (MixEAC), SA and AC groups were analysed, matched for age and sex to enable comparison. In the frames of this cross-sectional study, we compared type 2 diabetes in second- vs first-generation migrants, and mixed ethnicity vs non-mixed groups. Risks and explanations were analysed using logistic regression and mediation analysis, respectively.ResultsType 2 diabetes prevalence was markedly elevated in SA (599/3317 = 18%) and AC (534/4180 = 13%) compared with Europeans (140/3324 = 4%). Prevalence was lower in second- vs first-generation SA (124/1115 = 11% vs 155/1115 = 14%) and AC (163/2200 = 7% vs 227/2200 = 10%). Favourable adiposity (i.e. lower waist/hip ratio or BMI) contributed to lower risk in second-generation migrants. Type 2 diabetes in mixed populations (MixESA: 52/831 = 6%, MixEAC: 70/1045 = 7%) was lower than in comparator ethnic groups (SA: 18%, AC: 13%) and higher than in Europeans (4%). Greater socioeconomic deprivation accounted for 17% and 42% of the excess type 2 diabetes risk in MixESA and MixEAC compared with Europeans, respectively. Replacing self-reported with genetically assigned ethnicity corroborated the mixed ethnicity analysis.Conclusions/interpretationType 2 diabetes risks in second-generation SA and AC migrants are a fifth lower than in first-generation migrants. Mixed ethnicity risks were markedly lower than SA and AC groups, though remaining higher than in Europeans. Distribution of environmental risk factors, largely obesity and socioeconomic status, appears to play a key role in accounting for ethnic differences in type 2 diabetes risk.

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Dataset Information

UK ethnicity data collection for healthcare statistics: the South Asian perspective.

Background

Methods

Results

Conclusions

Publications

UK ethnicity data collection for healthcare statistics: the South Asian perspective.

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