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Proceedings paper #45390

Hirani, V; Primatesta, P; (2006) UNSPECIFIED In: (Proceedings) Social Science Medicine conference.

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Abstract

Objectives: To identify whether men and women from different minority ethnic groups show similar clustering of multiple risk factors for cardiovascular disease (CVD). Design: Nationally representative cross-sectional population survey: the Health Survey for England 1999. Participants: 592 non-institutionalised men and women aged 35 years and over of Black Caribbean, Indian, Pakistani, Bangladeshi, Chinese and White (including Irish) origin. Main outcome measures: Clusters grouping individuals with similar multiple risk factors for CVD. Statistical analysis: Statistical analyses were carried out in SPSS using k- means cluster analysis. This multivariate technique organised variables into relatively homogeneous groups, or "clusters", so that the degree of association was strong between members of the same cluster and weak between members of different clusters. Results: In 1999, the overall pattern of risk factors for CVD between Caribbean and White men was very similar. Indian men also had similarities to these two groups with the exception of heavy alcohol intake and high blood pressure, which were much lower for Indian men. Caribbean, Indian, Pakistani and White men had similar patterns of cigarette smoking and fat intake. A higher proportion of Pakistani and Bangladeshi men were in the ‘high risk for CVD’ cluster compared with the other ethnic groups. Risk factors for CVD clustered differently among South Asian groups. Among women, there were similarities between ethnic groups for certain risk factors e.g. Caribbean and White women for heavy smoking, high alcohol intakes and highest fat intakes. Differences between the South Asian women were not as obvious as in men. Conclusions: Cluster analysis is a useful method of identifying ‘multiple risk factors’ common to certain minority ethnic groups. Differences in risk factors among Indians, Pakistanis and Bangladeshis was further confirmed using this statistical technique, which has not been previously used in this area of research, suggesting that there is a complex interplay of factors (genetic, lifestyle, socioeconomic and environmental). To improve health outcomes in the long term, the strategy of tackling the underlying issues such as inequalities in health seems the most appropriate.

Type: Proceedings paper
Event: Social Science Medicine conference
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Epidemiology and Health > Epidemiology and Public Health
URI: http://discovery.ucl.ac.uk/id/eprint/45390
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