HLA alleles and haplotypes among the Lakota Sioux: report of the ASHI minority workshops, part III

Human leukocyte antigen (HLA) class I and II alleles were defined for 302 Lakota Sioux American Indians as part of the American Society for Histocompatibility and Immunogenetics coordinated studies on minority populations. The study group was comprised of adult volunteers from the Cheyenne River and Ogala Sioux tribes residing, respectively, on the Cheyenne River and Pine Ridge Reservations in South Dakota. Of the participants, 263 (87%) claimed full American Indian ancestry through both maternal and paternal grandparents. The study group included 25 nuclear families that were informative for genotyping. HLA phenotypes from 202 adults with no other known first-degree relative included in the study were used for calculation of allele and haplotype frequencies by maximum likelihood estimation. HLA-A, -B, and -Cw alleles were found to be in Hardy Weinberg equilibrium. Deviation from equilibrium was observed for DRB1 alleles (p=0.01), but could be attributed to the sample size and the occurrence of some genotypes with low expected frequencies. Polymorphism among the Sioux was limited with four to seven alleles comprising >80% of those observed at each locus. Several alleles were found at high frequency (0.05-0.30) among the Sioux that are also prevalent in other Native Americans and Alaska Natives, including: A*2402, *3101, and *0206; B*3501,*3901, *5101, and *2705; Cw*0702, *0404, and *03041; DRB1*0407, *0404, *1402, and *16021; and DQB1*0301, *0302, and *0402. DRB1*0811, which has been only previously described in Navajo and Tlingit Indians, was found to occur at a frequency of 0.119 among the Sioux. Two new alleles were defined among the Sioux: Cw*0204 and DRB1*040703, which were found in two and four individuals, respectively. In the haplotype analyses, significant linkage disequilibrium (p<0.00001) was seen in all pairwise comparisons of loci and numerous two and three locus haplotypes were found to have strong, positive linkage disequilibrium values. The two most common extended haplotypes among the Sioux, determined by maximum likelihood estimation and genotyping were: A*31012, B*3501, Cw*0404, DRB1*0407; and A*24021, B*3501, Cw*0404, DRB1*0404.     

Working conditions and health behavior as causes of educational inequalities in self-rated health: an inverse odds weighting approach

Objective:Using a novel mediation method that presents unbiased results even in the presence of exposure–mediator interactions, this study estimated the extent to which working conditions and health behaviors contribute to educational inequalities in self-rated health in the workforce.Methods:Respondents of the longitudinal Survey of Health, Ageing, and Retirement in Europe (SHARE) in 16 countries were selected, aged 50–64 years, in paid employment at baseline and with information on education and self-rated health (N=15 028). Education, health behaviors [including body mass index (BMI)] and working conditions were measured at baseline and self-rated health at baseline and two-year follow-up. Causal mediation analysis with inverse odds weighting was used to estimate the total effect of education on self-rated health, decomposed into a natural direct effect (NDE) and natural indirect effect (NIE).Results:Lower educated workers were more likely to perceive their health as poor than higher educated workers [relative risk (RR) 1.48, 95% confidence interval (CI) 1.37–1.60]. They were also more likely to have unfavorable working conditions and unhealthy behaviors, except for alcohol consumption. When all working conditions were included, the remaining NDE was RR 1.30 (95% CI 1.15–1.44). When BMI and health behaviors were included, the remaining NDE was RR 1.40 (95% CI 1.27–1.54). Working conditions explained 38% and health behaviors and BMI explained 16% of educational inequalities in health. Including all mediators explained 64% of educational inequalities in self-rated health.Conclusions:Working conditions and health behaviors explain over half of the educational inequalities in self-rated health. To reduce health inequalities, improving working conditions seems to be more important than introducing health promotion programs in the workforce.