In this study, we report nearest neighbor residue effects statistically determined from a chemical shift database. For an amino acid sequence XYZ, we define two correction factors, Delta(Y-x)n,s and Delta(Y-z)n,s, representing the effects on Y's chemical shifts from the preceding residue (X) and the following residue (Z), respectively, where X, Y, and Z are any of the 20 naturally occurring amino acids, n stands for H-1(N), N-15, H-1(alpha), C-13(alpha), C-13(beta), and C-13' nuclei, and s represents the three secondary structural types beta-strand, random coil, and alpha-helix. A total of similar to14400 Delta(Y-x)n,s and Delta(Y-z)n,s, representing nearly all combinations of X, Y, Z, n, and s, have been quantitatively determined. Our approach overcomes the limits of earlier experimental methods using short model peptides, and the resulting correction factors have important applications such as chemical shift prediction for the folded proteins. More importantly, we have found, for the first time, a linear correlation between the Delta(Y-x)n,s (n = N-15) and the C-13(alpha) chemical shifts of the preceding residue X. Since C-13(alpha) chemical shifts of the 20 amino acids, which span a wide range of 40-70 ppm, are largely dominated by one property, the electron density of the side chain, the correlation indicates that the same property is responsible for the effect on the following residue. The influence of the secondary structure on both the chemical shifts and the nearest neighbor residue effect are also investigated.