The Health Belief Model is useful in identifying determinants of facemask wearing. Findings have significant implications in enhancing the effectiveness of SARS prevention programs.

The current global outbreak of the severe acute respiratory syndrome (SARS) poses an international public health threat. 1 Hong Kong, China, remains one of the most severely affected areas. We aimed to identify psychosocial factors associated with SARS preventive health behaviors and to assess whether preventive health behaviors increased after launching SARS community prevention activities. METHODSWe telephone interviewed 1002 adult Chinese in wave 1 (March 17-18, 2003), which represented the early stage of the SARS outbreak in Hong Kong. A separate sample of 1329 adult Chinese were also telephone interviewed in wave 2 (March 29-April 1, 2003), which represented a period of vigorous communitywide SARS prevention activities by local health authorities. Response rates of the participants, calculated as percentages of completes to completes plus refusals, were 53% and 65% for waves 1 and 2, respectively. These two samples were comparable in various demographic information. The overall age distribution was 20% for 18 to 29 years, 50% for 30 to 49 years, 15% for 50 to 59 years, and 15% for 60 years or older.We used key concepts of psychosocial models of health behaviors 2-4 to design our survey, which included the following measures. Practice of Preventive Health BehaviorsLocal health authorities have recommended the following preventive health behaviors to prevent the contracting and spreading of SARS: maintaining good personal hygiene, developing a healthy lifestyle, ensuring good ventilation, and wearing face masks. We asked participants in wave 1 to indicate how often in the past week they had practiced at least 1 of the above preventive health behaviors. In wave 2, we specifically asked participants how often they wore face masks to prevent contracting SARS during the last week. Participants responded with (1) never, (2) only a few times, (3) sometimes, or (4) almost all the time. We classified the first 3 responses as inconsistent preventive health behaviors (coded as 0) and "almost all the time" as consistent preventive health behaviors (coded as 1). Perceived Knowledge About SARS, Susceptibility to SARS, and Self-Efficacy in Performing the Suggested Preventive Health BehaviorsThese 3 psychosocial factors were each measured by 1 item. Participants indicated their perceptions on 4-point scales, with high scores representing high levels of these factors. Attitudes Toward SARS Prevention MeasuresParticipants in wave 2 were assessed on their attitudes toward SARS community prevention measures by 5 items (on 4-point scales): (1) whether enough information was provided, (2) whether health guidelines were clear, (3) whether they believed that the suggested preventive health behaviors were effective, (4) whether they were satisfied with the government, and (5) whether they had confidence in the government's ability to control the spread of SARS. High scores corresponded to very favorable attitudes. The α value for this scale was .73. DemographicsAll participants were asked about their age, education, income, and emplo...

Food effect, also known as food-drug interactions, is a common phenomenon associated with orally administered medications and can be defined as changes in absorption rate or absorption extent. The mechanisms of food effect and their consequences can involve multiple factors, including human post-prandial physiology, properties of the drug, and how the drug is administered. Therefore, it is essential to have a thorough understanding of these mechanisms when recommending whether a specific drug should be taken with or without food. Food-drug interactions can be clinically relevant, especially when they must be avoided to prevent undesirable effects or exploited to optimize medication therapy. This review conducts a literature search that examined studies on food effect. We summarized the literature and identified and discussed common food effect mechanisms. Furthermore, we highlighted drugs that have a clinically significant food effect and discussed the corresponding mechanisms. In addition, this review analyzes the effects of high-fat food or standard meals on the oral drug absorption rate and absorption extent for 229 drugs based on the Biopharmaceutics Drug Disposition Classification System and demonstrates an association between Biopharmaceutics Drug Disposition Classification System class and food effect.

This study supported the conceptual framework that specified perceived health threats and efficacy beliefs as the two core dimensions of motivating factors in adopting SARS preventive behaviors.

[1] We present measurements of trace gases and fine aerosols obtained from a rural site in eastern China during 18 February to 30 April 2001. The field program aimed to characterize the variations in aerosol and gaseous pollutant concentrations and the emission signatures from the inland region of eastern China in the spring season. The data included O 3 , CO, NO, NO y *, SO 2 , methane, C 2 -C 8 nonmethane hydrocarbons (NMHCs), C 1 -C 2 halocarbons, and the chemical composition of PM2.5. The average hourly mixing ratios (±standard deviation) of CO, SO 2 , and NO y * were 677 (±315) ppbv, 15.9 (±14.6) ppbv, and 13.8 (±7.2) ppbv, respectively. The mean daytime ozone mixing ratio was 41 (±19) ppbv. The most abundant NMHC was ethane (3189 ± 717 pptv), followed by ethyne (2475 ± 1395 pptv), ethene (1679 ± 1455 pptv), and toluene (1529 ± 1608 pptv). Methyl chloride was the most abundant halocarbon (1108 ± 653 pptv). The average concentrations of particulate organic matter (POM, as organic carbon, OC, times 1.4) and elemental carbon (EC) in PM2.5 were 21.5 (±7) mg/m 3 and 2.5 (±0.7) mg/m 3 , respectively, and sulfate and nitrate levels were 17.3 (±6.6) and 6.5 (±4) mg/m 3 , respectively. CO showed moderate to good correlation with NO y * (r 2 = 0.59), OC (r 2 = 0.65), CH 3 Cl (r 2 = 0.59), soluble potassium (r 2 = 0.53), and many NMHCs, indicating contributions from the burning of biofuel/biomass. CO also correlated with an industrial tracer, C 2 Cl 4 , indicative of some influence from industrial sources. SO 2 , on the other hand, correlated well with EC (r 2 = 0.56), reflecting the contribution from the burning of coal. Ammonium was sufficiently abundant to fully neutralize sulfate and nitrate, indicating that there were strong emissions of ammonia from agricultural activities. Silicon and calcium had poor correlations with iron and aluminum, revealing the presence of source(s) for Si and Ca other than from soil. Examination of C 2 H 2 /CO, C 3 H 8 /C 2 H 6 , nitrate/(nitrate + NO y *), and sulfate/(SO 2 + sulfate) suggested that relatively fresh air masses had been sampled at the study site in the spring season. Comparison of the observed ratios/slopes with those derived from emission inventories showed that while the observed SO 2 /NO y * ratio (1.29 ppbv/ppbv) in March was comparable (within 20%) to the inventory-derived ratio for the study region, the measured CO/NO y * slope (37 ppbv/ppbv) was about 200% larger. The observed slope of CO relative to NMHC (including ethane, propane, butanes, ethene, and ethyne) also indicated the presence of excess CO, compared to the ratios from the inventories. These results strongly suggest that emissions of CO in eastern China have been underrepresented. The findings of this study highlight the importance of characterizing trace gases and aerosols within source regions of the Asian continent. The springtime results were also compared with data previously collected at the site in 1999-2000 and with those obtained on the Transport and Chemical Evolution over the