The rough draft of the human genome map has been used to identify most of the functional genes in the human genome, as well as to identify nucleotide variations, known as "single-nucleotide polymorphisms" (SNPs), in these genes. By use of advanced biotechnologies, researchers are beginning to genotype thousands of SNPs from biological samples. Among the many possible applications, one of them is the study of SNP associations with complex human diseases, such as cancers or coronary heart diseases, by using a case-control study design. Through the gathering of environmental risk factors and other lifestyle factors, such a study can be effectively used to investigate interactions between genes and environmental factors in their associations with disease phenotype. Earlier, we developed a method to statistically construct individuals' haplotypes and to estimate the distribution of haplotypes of multiple SNPs in a defined population, by use of estimating-equation techniques. Extending this idea, we describe here an analytic method for assessing the association between the constructed haplotypes along with environmental factors and the disease phenotype. This method is also robust to the model assumptions and is scalable to a large number of SNPs. Asymptotic properties of estimations in the method are proved theoretically and are tested for finite sample sizes by use of simulations. To demonstrate the use of the method, we applied it to assess the possible association between apolipoprotein CIII (six coding SNPs) and restenosis by using a case-control data set. Our analysis revealed two haplotypes that may reduce the risk of restenosis.