14 research outputs found
Coffee, Alcohol, Smoking, Physical Activity and QT Interval Duration: Results from the Third National Health and Nutrition Examination Survey
Abnormalities in the electrocardiographic QT interval duration have been associated with an increased risk of ventricular arrhythmias and sudden cardiac death. However, there is substantial uncertainty about the effect of modifiable factors such as coffee intake, cigarette smoking, alcohol consumption, and physical activity on QT interval duration.We studied 7795 men and women from the Third National Health and Nutrition Survey (NHANES III, 1988-1994). Baseline QT interval was measured from the standard 12-lead electrocardiogram. Coffee and tea intake, alcohol consumption, leisure-time physical activities over the past month, and lifetime smoking habits were determined using validated questionnaires during the home interview.In the fully adjusted model, the average differences in QT interval comparing participants drinking ≥6 cups/day to those who did not drink any were -1.2 ms (95% CI -4.4 to 2.0) for coffee, and -2.0 ms (-11.2 to 7.3) for tea, respectively. The average differences in QT interval duration comparing current to never smokers was 1.2 ms (-0.6 to 2.9) while the average difference in QT interval duration comparing participants drinking ≥7 drinks/week to non-drinkers was 1.8 ms (-0.5 to 4.0). The age, race/ethnicity, and RR-interval adjusted differences in average QT interval duration comparing men with binge drinking episodes to non-drinkers or drinkers without binge drinking were 2.8 ms (0.4 to 5.3) and 4.0 ms (1.6 to 6.4), respectively. The corresponding differences in women were 1.1 (-2.9 to 5.2) and 1.7 ms (-2.3 to 5.7). Finally, the average differences in QT interval comparing the highest vs. the lowest categories of total physical activity was -0.8 ms (-3.0 to 1.4).Binge drinking was associated with longer QT interval in men but not in women. QT interval duration was not associated with other modifiable factors including coffee and tea intake, smoking, and physical activity
STILBENOID CONSTITUENTS IN WELWITSCHIA MIRABILIS
Welwitschia mirabilis is an endangered and unique gymnosperm of the Namibian Desert of South West Africa. It is a monotypic member of the Genus Welwitschia. Since its discovery about 140 years ago, very little is known about its chemical constituents. In the present study we report the isolation and structure elucidation of 10 new stilbenoids from the stem and root of the plant along with some known compounds. The structures of the compounds were assigned by spectroscopic analysi
Size distributions of polycyclic aromatic hydrocarbons in urban atmosphere: sorption mechanism and source contributions to respiratory deposition
Current knowledge on atmospheric particle-phase polycyclic aromatic
hydrocarbons (PAHs) size distribution remains
incomplete. Information is missing on sorption mechanisms and the
influence of the PAHs' sources on their transport in human
respiratory system. Here we present the studies systematically
investigating the modal distribution characteristics of the
size-fractioned PAHs and calculating the source contribution to
adverse health effects through inhalation. Aerosol samples with
nine size fractions were collected from Shanghai urban air over one
year period 2012–2013. A high correlation coefficient existed
between measured and predicted values (<i>R</i><sup>2</sup>= 0.87), indicated
that the data worked very well in current study. Most PAHs were
observed on the small particles followed with seasonality
differences. When normalized by PAHs across particle diameters, the
size distribution of PAHs exhibited bimodal patterns, with a peak
(0.4–2.1 μm) in fine mode and another peak
(3.3–9.0 μm) in coarse mode, respectively. Along with
the increasing ring number of PAHs, the intensity of the fine mode
peak increased, while coarse mode peak decreased. Plotting of
log(PAH/PM) against log(<i>D</i><sub><i>p</i></sub>) showed that all
slope values were above −1 with the increase towards less-ring
PAHs, suggesting that multiple mechanisms, i.e. adsorption and
absorption controlled the PAHs on particles, but adsorption played
a much stronger role for 5- and 6-ring than 3- and 4-ring PAHs. The
mode distribution behavior of PAHs showed that fine particles were
major carriers for the more-ring PAHs. Further calculations using
inhaling PAHs data showed the total deposition fluxes in respiratory
tract were 8.8 ± 2.0 ng h<sup>-1</sup>. Specifically, fine
particles contributed 10–40 % of PAHs deposition fluxes to the
alveolar region, while coarse particles contributed 80–95 % of
ones to the head region. Estimated lifetime cancer risk (LCR) for
people exercised in haze days (1.5 × 10<sup>-6</sup>) was bigger than
the cancer risk guideline value (10<sup>-6</sup>). The largest PAHs
contribution for LCR mainly came from the accumulation
particles. Based on source apportionment results generated by
positive matrix factorization (PMF), it was found that the cancer
risk caused in accumulated mode mainly resulted from biomass burning
(24 %), coal combustion (25 %) and vehicular emission
(27 %). The present results contribute to a mechanistic
understanding of PAHs size distribution causing adverse health
effects and will help develop some source control strategies or
policies by relying on respiratory assessment data