METHODS: Mosquito collections were carried out using human landing catches at ground and canopy levels in the Tawau Division of Sabah. Collections were conducted along an anthropogenic disturbance gradient (primary forest, lightly logged virgin jungle reserve and salvage logged forest) between 18:00 and 22:00 h.
RESULTS: Anopheles balabacensis, a vector of P. knowlesi, was the predominant species in all collection areas, accounting for 70 % of the total catch, with a peak landing time of 18:30-20:00 h. Anopheles balabacensis had a preference for landing on humans at ground level compared to the canopy (p
METHODS: Logistic regression analysis was used to distinguish associated current smoking characteristics. Five-year predictive risks of CVD, CHD and MI and the impact of simulated interventions were calculated utilizing the Data Collection on Adverse Effects of Anti-HIV Drugs Study (D:A:D) algorithm.
RESULTS: Smoking status data were collected from 4274 participants and 1496 of these had sufficient data for simulated intervention calculations. Current smoking prevalence in these two groups was similar (23.2% vs. 19.9%, respectively). Characteristics associated with current smoking included age > 50 years compared with 30-39 years [odds ratio (OR) 0.65; 95% confidence interval (CI) 0.51-0.83], HIV exposure through injecting drug use compared with heterosexual exposure (OR 3.03; 95% CI 2.25-4.07), and receiving antiretroviral therapy (ART) at study sites in Singapore, South Korea, Malaysia, Japan and Vietnam in comparison to Thailand (all OR > 2). Women were less likely to smoke than men (OR 0.11; 95% CI 0.08-0.14). In simulated interventions, smoking cessation demonstrated the greatest impact in reducing CVD and CHD risk and closely approximated the impact of switching from abacavir to an alternate antiretroviral in the reduction of 5-year MI risk.
CONCLUSIONS: Multiple interventions could reduce CVD, CHD and MI risk in Asian HIV-positive patients, with smoking cessation potentially being the most influential.
SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.