Association analyses between gene variability and human longevity carried out by comparing gene frequencies between population samples of different ages (case/control design) may provide information on genes and pathways playing a role in modulating survival at old ages. However, by dealing with cross-sectional data, the gene-frequency (GF) approach ignores cohort effects in population mortality changes. The genetic-demographic (GD) approach adds demographic information to genetic data and allows the estimation of hazard rates and survival functions for candidate alleles and genotypes. Thus mortality changes in the cohort to which the cross-sectional sample belongs are taken into account. In this work, we applied the GD method to a dataset relevant to two genes, APOE and HSP70.1, previously shown to be related to longevity by the GF method. We show that the GD method reveals sex- and age-specific allelic effects not shown by the GF analysis. In addition, we provide an algorithm for the implementation of a non-parametric GD analysis.