Abstract
Aims To examine diabetic retinopathy in Asians and Caucasians attending a hospital diabetic clinic and to evaluate the impact of the significant risk factors on the probability of sight-threatening retinopathy.
Methods A total of 500 diabetic patients (268 Asians, 232 Caucasians) who attended a diabetic clinic within a defined time period were examined for severity of diabetic retinopathy. The existence of sight-threatening retinopathy (STR) was compared in the two groups. Significant risk factors such as age, duration and hypertension were analysed against the probability of STR in each of the two races.
Results Asians demonstrated significantly higher rates of STR. Univariate analysis showed age, duration, race, gender, and insulin-requiring status to be significantly associated with STR. Multivariate logistic regression showed a significant association of STR with race, age and duration of diabetes, with no significant interaction effects between variables. The logistic regression model predicted STR in Asians to be matched to that in Caucasians by a 12.5-year difference factor; that is, Caucasians were older by 12.5 years or had a 12.5-year longer duration than Asians for the same level of STR.
Conclusions After adjusting for age and duration of diabetes, the probability of STR in Asian diabetic patients attending the diabetic clinics in Bradford is significantly higher than that in Caucasians (odds ratio=3.184, P<0.05). The impact of age and duration was significantly higher in patients of South Asian origin compared to Caucasians.
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Acknowledgements
We thank Dr Mark Hurst for his invaluable advice and input during the earlier stages of the study and Mr Darcy Brown for collecting the data on the questionnaire.
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Appendix
Appendix
The goodness of fit was examined by means of χ2 for covariates,20 also referred to as the Model χ2, GM.20 This value provides a test of the null hypothesis that the regression coefficients are equal to zero and that inclusion of the independent variables in the model does not improve prediction of the outcome. The large GM value for the present model supports the conclusion that inclusion of the independent variables does improve prediction significantly. Table 3 also reports the Hosmer and Lemeshow21 Goodness-of-fit test. This test partitions the data into 10 deciles of risk, and compares observed with expected (model) frequencies of STR in each decile. In this case, a good model fit is confirmed by the small χ2 (large P-value) indicating no significant difference between observed and predicted outcomes over the deciles of risk. These statistics together indicate an acceptable goodness-of-fit of the logistic regression model for predicting the probability of STR from AGE, DURATION of diabetes, and RACE (Asian/Caucasian).
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Pardhan, S., Gilchrist, J. & Mahomed, I. Impact of age and duration on sight–threatening retinopathy in South Asians and Caucasians attending a diabetic clinic. Eye 18, 233–240 (2004). https://doi.org/10.1038/sj.eye.6700629
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DOI: https://doi.org/10.1038/sj.eye.6700629
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