Globally, human immune deficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) continues to be a major public health issue. With improved survival, the number of people living with HIV/AIDS is increasing, with over 2 million among pregnant women. Investigating adverse pregnant outcomes of HIV-infected population and associated factors are of great importance to maternal and infant health. A cross-sectional data collected from hospital delivery records of 4397 mother–infant pairs in southwestern China were analysed. Adverse pregnant outcomes (including low birthweight/preterm delivery/low Apgar score) and maternal HIV status and other characteristics were measured. Two hundred thirteen (4.9%) mothers were HIV positive; maternal HIV infection, rural residence and pregnancy history were associated with all three indicators of adverse pregnancy outcomes. This research suggested that maternal population have high prevalence in HIV infection in this region. HIV-infected women had higher risks of experiencing adverse pregnancy outcomes. Rural residence predisposes adverse pregnancy outcomes. Findings of this study suggest social and medical support for maternal-infant care needed in this region, selectively towards rural areas and HIV-positive mothers.

BackgroundPrevious studies have shown inconsistent or even contradictory results for some risk factors associated with HIV infection among drug users, and these may be partially explained by geographical variations.MethodsData were collected from 11 methadone clinics in the Liangshan Yi Autonomous Prefecture from 2004 to 2012. A non-spatial logistical regression model and a geographically weighted logistic regression model were fitted to analyze the association between HIV infection and specific factors at the individual level.ResultsThis study enrolled 6,458 patients. The prevalence of HIV infection was 25.1 %. The non-spatial model indicated that being divorced was positively associated with HIV infection. The spatial model also showed that being divorced was positively associated with HIV infection, but only for 49.4 % of individuals residing in some northern counties. The non-spatial model suggested that service sector work was negatively associated with HIV infection. However, the spatial model indicated that service work was associated with HIV infection, but only for 23.0 % of patients living in some western counties. The non-spatial model did not show that being married was associated with HIV infection in our study field, but the spatial model indicated that being married was negatively associated with HIV infection for 12.0 % of individuals living in some western counties. For other factors, the non-spatial and spatial models showed similar results.ConclusionThe spatial model may be useful for improving understanding of geographical heterogeneity in the relationship between HIV infection and individual factors. Spatial heterogeneity may be useful for tailoring intervention strategies for local regions, which can consequently result in a more efficient allocation of limited resources toward the control of HIV transmission.Electronic supplementary materialThe online version of this article (doi:10.1186/s40249-015-0073-x) contains supplementary material, which is available to authorized users.

Hepatitis C virus (HCV) has become a global public health problem. Many studies have been conducted to identify risk factors for HCV infection. However, some of these studies reported inconsistent results. Using data collected from 11 methadone clinics, we fit both a non-spatial logistical regression and a geographically weighted logistic regression to analyse the association between HCV infection and some factors at the individual level. This study enrolled 5401 patients with 30·0% HCV infection prevalence. The non-spatial logistical regression found that injection history, drug rehabilitation history and senior high-school education or above were related to HCV infection; and being married was negatively associated with HCV infection. Using the spatial model, we found that Yi ethnicity was negatively related to HCV infection in 62·0% of townships, and being married was negatively associated with HCV infection in 81·0% of townships. Senior high-school education or above was positively associated with HCV infection in 55·2% of townships of the Yi Autonomous Prefecture. The spatial model offers better understanding of the geographical variations of the risk factors associated with HCV infection. The geographical variations may be useful for customizing intervention strategies for local regions for more efficient allocation of limited resources to control transmission of HCV.