We quantify the degree to which LD differences exist in the human genome and investigates the consequences that variations in patterns of LD between populations can have on the power of case-control or family-trio association studies. Although only a small proportion of SNPs show significant LD differences (0.8-5%), these can introduce artificial signals of associations and reduce the power to detect true associations in case-control designs, even when meta-analytic approaches are used to account for stratification. We show that combining trios from different populations in the presence of significant LD differences can adversely affect power even though the number of trios has increased. Our results have implications on genetic studies conducted in populations with substantial population structure and show that the use of meta-analytic approaches or family-based designs to protect Type 1 error does not prevent loss of power due to differences in LD across populations.