Characteristics of eyes with and without prior cataract surgery were compared with analysis of covariance for continuous variables and with logistic regression analysis for discrete variables adjusting for age and sex (SPSS, ver. 11.0; SPSS Inc., Chicago, IL). To exploit the data in an optimal way, all available data were combined into one analysis. The unit in the incidence analysis was one eye (left or right) per period (baseline to second follow-up visit, second follow-up to third follow-up visit). Thus, each participant yielded a maximum of four units in the data set: (1) the left eye in first period, (2) the left eye in second period, (3) the right eye in first period, and (4) the right eye in second period. The association between determinants and incident AMD was studied by logistic regression. To adjust for the correlation of the units corresponding to the same subject, the generalized estimating equation (GEE) approach was followed, with an independent or unstructured working correlation matrix (SAS, ver. 8.2; SAS Institute, Inc., Cary, NC). Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) are provided. The unit in the cross-sectional analyses was one eye (left or right) per time point (baseline and second follow-up visit). Thus, each participant yielded a maximum of four units in the dataset: (1) the left eye at baseline, (2) the left eye at second follow-up visit, (3) the right eye at baseline, and (4) the right eye at second follow-up visit. The association between determinants and prevalent AMD at either time point was also studied by the GEE approach.