Frequency distributions and other basic information were obtained in a spreadsheet program (Excel; Microsoft, Redmond, WA). All other statistical analyses were performed with another commercial program (SAS statistical software, ver. 8.1; SAS, Cary, NC). Unless otherwise specified, all analyses were conducted on a per-subject basis (i.e., averaging the MPOD estimates between the two eyes). For participants who could contribute an MPOD estimate from only one eye, the value from that eye was used. To determine whether there was a significant difference in the characteristics of participant subgroups, a two-tailed paired Student’s t-test was used for continuous variables (e.g., MPOD) and the χ2 test was used, or the odds ratio (OR) was calculated, for dichotomous variables, as appropriate (e.g., MPOD estimate obtained versus not obtained). Correlations between continuous variables (e.g., between-eye MPOD) were approached with a general linear model and characterized by means of the Pearson’s correlation coefficient (r). When appropriate, other potential confounding variables were included in and controlled for in the model. Furthermore, comparisons between multiple subgroups (e.g., by iris color) were analyzed by analysis of variance (ANOVA) and of covariance (ANCOVA), as appropriate. Preplanned analyses included the estimation of the MPOD interocular correlation; comparison of MPOD estimates between genders (male versus female), races (white versus black), lutein use (lutein supplement users versus non-users), and iris colors; and the correlation between MPOD and age. Because of the multiple additional comparisons performed in this study, we conservatively considered P < 0.01 to be statistically significant for all comparisons.