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The applicability of measures of socioeconomic position to different ethnic groups within the UK
被引:13
作者:
Kelaher, Margaret
[1
,4
]
Paul, Sheila
[2
,4
]
Lambert, Helen
[3
,4
]
Ahmad, Waqar
[2
,4
]
Smith, George Davey
[3
,4
]
机构:
[1] Univ Melbourne, Ctr Hlth Policy, Programs & Econ, Sch Populat Hlth, Carlton, Vic 3010, Australia
[2] UCL, Ctr Int Hlth & Dev, Inst Child Hlth, London WC1N 1EH, England
[3] Univ Bristol, Dept Social Med, Bristol BS8 2PR, Avon, England
[4] Middlesex Univ, Social Policy Res Ctr, London N14 4YZ, England
基金:
英国医学研究理事会;
关键词:
UNITED-STATES;
HEALTH;
DISCRIMINATION;
INEQUALITIES;
RACISM;
RACE;
D O I:
10.1186/1475-9276-8-4
中图分类号:
R1 [预防医学、卫生学];
学科分类号:
1004 ;
120402 ;
摘要:
Background: In this paper we seek to tease out differences in socioeconomic position between ethnic groups. There are 3 main reasons why conventional socioeconomic indicators and asset based measures may not be equally applicable to all ethnic groups: 1) Differences in response rate to conventional socioeconomic indicators 2) Cultural and social differences in economic priorities/opportunities 3) Differences in housing quality, assets and debt within socioeconomic strata Methods: The sample consisted of White (n = 227), African-Caribbean (n = 213) and Indian and Pakistani (n = 233) adults aged between 18 and 59 years living in Leeds as measured in a stratified population survey. Measures included income, education, employment, car ownership, home ownership, housing quality, household assets, investments, debt, perceived ability to obtain various sums and perceived level of financial support given and received. Results: Response rates to education and income questions were similar for the different ethnic groups. Overall response rates for income were much lower than those for education and biased towards wealthier people. There were differences between ethnic groups in economic priorities/opportunities particularly in relation to car ownership, home ownership, investment and debt. Differences in living conditions, household assets and debt between ethnic groups were dependent on differences in education; however differences in car ownership, home ownership, ability to obtain 10 pound 000, and loaning money to family/friends and income from employment/self employment persisted after adjustment for education. Conclusion: In the UK, education appears to be an effective variable for measuring variation in SEP across ethnic groups but the ability to account for SEP differences may be improved by the addition of car and home ownership, ability to obtain 10 pound 000, loaning money to family/friends and income from employment/self employment. Further research is required to establish the degree to which results of this study are generalisable.
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