Molecular analysis reveals tighter social regulation of immigration in patrilocal populations than in matrilocal populations

Human social organization can deeply affect levels of genetic diversity. This fact implies that genetic information can be used to study social structures, which is the basis of ethnogenetics. Recently, methods have been developed to extract this information from genetic data gathered from subdivided populations that have gone through recent spatial expansions, which is typical of most human populations. Here, we perform a Bayesian analysis of mitochondrial and Y chromosome diversity in three matrilocal and three patrilocal groups from northern Thailand to infer the number of males and females arriving in these populations each generation and to estimate the age of their range expansion. We find that the number of male immigrants is 8 times smaller in patrilocal populations than in matrilocal populations, whereas women move 2.5 times more in patrilocal populations than in matrilocal populations. In addition to providing genetic quantification of sex-specific dispersal rates in human populations, we show that although men and women are exchanged at a similar rate between matrilocal populations, there are far fewer men than women moving into patrilocal populations. This finding is compatible with the hypothesis that men are strictly controlling male immigration and promoting female immigration in patrilocal populations and that immigration is much less regulated in matrilocal populations.

Poverty and the economic effects of TB in rural China

OBJECTIVE: To investigate the economic effects of illness on individual tuberculosis (TB) cases in rural China and to use a case-control study to show a strong TB-poverty link. SETTING: In 2002-2004 we studied 160 new smear-positive pulmonary tuberculosis (PTB) cases and 320 age- and sex-matched controls living in neighbouring houses in four rural counties of Henan Province. DESIGN: Cases and controls were interviewed 1-3 months after patients were diagnosed. We used matched multivariate logistic regression to compare cases with controls for poverty status using household income, household assets and relative wealth within the village. We conducted follow-up interviews of patients 10-12 months later to assess economic effects by collecting data on treatment costs, income losses, coping strategies and treatment completion. RESULTS: Poverty is strongly associated with TB incidence even after controlling for smoking and other risk factors. Excluding income losses, direct out-of-pocket treatment costs (medical and non-medical) accounted for 55.5 % of average annual household income, and most TB cases fell into heavy debt. The DOTS cure rate was 91 %. When DOTS was incomplete or not done, mortality was high. CONCLUSIONS: Poverty is both a cause and a devastating outcome of TB. Ongoing poverty reduction schemes in China must also include reducing TB.