Original Research Name analysis to classify populations by ethnicity in public health: Validation of Onomap in Scotland F. Lakha a , D.R. Gorman a, *, P. Mateos b a NHS Lothian, Waverley Gate, 2e4 Waterloo Place, Edinburgh EH1 3EG, UK b Department of Geography, University College London, London, UK article info Article history: Received 30 July 2010 Received in revised form 29 March 2011 Accepted 10 May 2011 Available online xxx Keywords: Health inequalities Ethnicity Name Scotland Onomap abstract Objectives: Health inequalities between ethnic minorities and the general population are persistent. Addressing them is hampered by the inability to classify individuals’ ethnicity accurately. This is addressed by a new name-based ethnicity classification methodology called ‘Onomap’. This paper evaluate the diagnostic accuracy of Onomap in identifying population groups by ethnicity, and discuss applications to public health practice. Study design: Onomap was applied to three independent reference datasets (birth regis- tration, pupil census and register of Polish health professionals) collected in Britain and Poland at individual level (n ¼ 260,748). Methods: Results were compared with the reference database ethnicity ‘gold standard’. Outcome measures included sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Ninety-five percent confidence intervals and Chi-squared tests were used. Results: Onomap identified the majority of those in the British participant group with high sensitivity and PPV (>95%), and low misclassification (<5%), although specificity and NPV were lowest in this group (56e87%). Outcome measures for all other non-British groupings were high for specificity and NPV (>98%), but variable for sensitivity and PPV (17e89%). Differences in misclassification by gender were statistically significant. Using maiden name rather than married name in women improved classification outcomes for those born in the British Isles (0.53%, 95% confidence interval 0.26e0.8%; P < 0.001) but not for South Asian or Polish groups. Conclusions: Onomap offers an effective methodology for identifying population groups in both health-related and educational datasets, categorizing populations into a variety of ethnic groups. This evaluation suggests that it can successfully assist health researchers, planners and policy makers in identifying and addressing health inequalities. ª 2011 Published by Elsevier Ltd on behalf of The Royal Society for Public Health. Background Health inequalities exist between ethnic minorities and indigenous populations. 1e7 In order to address the underlying causes of these inequalities, it is essential to systematically identify and classify individuals into population groups defined by ethnicity. To the authors’ knowledge, there are currently limited means by which to identify such groups * Corresponding author. Tel.: þ44 131 536 9165; fax: þ44 131 536 9164. E-mail address: Dermot.Gorman@lhb.scot.nhs.uk (D.R. Gorman). available at www.sciencedirect.com Public Health journal homepage: www.elsevier.com/puhe 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 public health xxx (2010) 1 e10 PUHE1481_proof ■ 26 May 2011 ■ 1/10 Please cite this article in press as: Lakha F, et al., Name analysis to classify populations by ethnicity in public health: Validation of Onomap in Scotland, Public Health (2010), doi:10.1016/j.puhe.2011.05.003 0033-3506/$ e see front matter ª 2011 Published by Elsevier Ltd on behalf of The Royal Society for Public Health. doi:10.1016/j.puhe.2011.05.003