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It remains uncertain whether intake of fish or n-3 polyunsaturated fatty acids is preventive against allergic disorders. This cross-sectional study investigated the association of intake of selected high-fat foods and specific types of fatty acids with the prevalence of allergic rhinitis in Japan where intake of fish is high.Study subjects were 1002 Japanese pregnant females. Allergic rhinitis (including cedar pollinosis) was defined as present if subjects had received drug treatment at some point during the previous 12 months. Information on dietary factors was collected using a validated self-administered diet history questionnaire. Adjustment was made for age, gestation, parity, cigarette smoking, passive smoking at home and at work, indoor domestic pets, family history of asthma, atopic eczema, and allergic rhinitis, family income, education, mite antigen level in house dust, changes in diet in the previous month, season when data were collected, and body mass index.There was a tendency for an inverse dose-response association between fish intake and allergic rhinitis although the adjusted odds ratio for comparison of the highest with the lowest quartile was not statistically significant (p for trend = 0.09). Intake of eicosapentaenoic and docosahexaenoic acids was independently associated with a decreased prevalence of allergic rhinitis: the multivariate odds ratio for the highest quartile was 0.56 (95% confidence interval: 0.32-0.96, p for trend = 0.03). Intake of n-6 polyunsaturated fatty acids in the third quartile but not the second and fourth quartiles showed a tendency for an inverse association with the prevalence of allergic rhinitis. No measurable relationship was found between consumption of meat, eggs, dairy products, total fat, saturated, monounsaturated, and n-3 polyunsaturated fatty acids, and cholesterol or the ratio of n-3 to n-6 polyunsaturated fatty acids and allergic rhinitis.Our findings suggest that the intake of eicosapentaenoic and docosahexaenoic acids may be associated with a reduced prevalence of allergic rhinitis.

This study examined the degree of within-shift variability of short-term exposure concentrations for workers exposed to organic solvents in indoor workplaces. For this purpose, 117 exposure data sets of 15-minute time-weighted average (15-min TWA) and those of 60-min TWA were collected from 53 workers employed in the offset printing, gravure printing, screen printing, machine control board production, fiber-reinforced plastic production, hard metal production, electrical parts production, and chemical synthesizing industries. Data analysis showed that the tenth, fiftieth, and ninetieth percentiles of the geometric standard deviations of 15-min TWA values [GSD(15m)] were 1.4, 2.3, and 4.5, respectively; and those of GSD(60m) were 1.2, 1.7, and 3.4, respectively. Based on an assumption of lognormal exposure distribution, the maximum values of 15-min TWA (the 98.4th percentile) were estimated to be 4.3, 36, and 650 times as high as the minimum one (the 1.6th percentile) for the low, middle, and high exposure variabilities, respectively; and to be 2.0, 4.3, and 8.2 times the 8-hour TWA value, respectively. Consequently, when the 8-hour TWA exceeds 0.23 times (1/4.3) the short-term exposure limit value, the high short-term exposure condition should be evaluated. The maximum values of 60-min TWA (the 93.8th percentile) were estimated to be 1.8, 5.1 and 43 times as high as the minimum one, respectively; and to be 1.3, 2.0, and 3.1 times the 8-hour TWA value, respectively. The relationship between production factors and within-shift exposure variability was also examined. The intermittent solvent use group had significantly higher median values of GSD(15m) and GSD(60m) than the continuous group. The mobile pollutant source group had a significantly higher median value of GSD(60m) than the stationary group.

Using a physiologically based pharmacokinetic (PBPK) model, the effects of variation of exposure concentration of acetone on three biological indicators--acetone concentrations in blood, urine, and exhaled air--were investigated. The effect of the difference in work load was also examined. It was confirmed that the model could be used to estimate acetone concentrations during fluctuating exposure by comparing simulated acetone concentrations with the corresponding values observed in field surveys. By inputting the exposure situations into the PBPK model, the variabilities of the biological indicators were simulated. The variation of acetone exposure was expressed by seven 1-hour time-weighted averages (CEXPs). The arithmetic means of the CEXPS were 200 and 750 ppm. The geometric standard deviations (GSDs) were 1.5, 2.0, and 3.0, representing low, moderate, and high variations, respectively. Work loads were set at 15 and 50 W. Consequently, there were 12 exposure situations. The acetone concentrations in venous blood (CB) and exhaled alveolar air (CA) at 1 minute after the end of the work shift were selected as biological indicators of exposure because they were predicted to decrease rapidly at the end of exposure and become relatively stable after 1 minute. The acetone concentration in urine excreted during the last 2 hours of the work shift (CU) was also used as a biological indicator. Simulation was repeated 100 times with randomly permuting CEXPs for each situation. The mean values of CB, CU, and CA showed almost no variation regardless of the difference in the GSD of CEXPs. The coefficients of variation increased with the GSD of CEXPs but were less than 0.2. Consequently, these variables were acceptable as biological indicators of daily average exposure for the same work load. However, the difference in work load greatly changed the mean values of CB, CU, and CA, thus making it difficult to use these variables as indicators of daily average exposure for different work loads.

For 10 workers (16 worker-chemical combinations) exposed to organic solvents, the distributions of 7.5-min time-weighted average (TWA) concentrations, 15-min TWAs, 30-min TWAs, and 60-min TWAs were examined by the Shapiro-Wilk W test and by plotting the TWA values and logarithmic values on probability paper. The hypothesis of normality of 7.5-min TWA and 15-min TWA was rejected for almost all combinations, while the hypothesis of lognormality was rejected only for a few combinations. For 30-min TWAs and 60-min TWAs, the hypothesis of normality was rejected for five and two combinations, respectively, while the hypothesis of lognormality could not be rejected for any of the combinations. The probability plot also showed that TWA values with averaging times of 7.5 to 60 min were approximately distributed in a lognormal manner. Consequently, there was no evidence against using the lognormal distribution to describe the short-term exposure distribution. Results suggest that statistical methods proposed for evaluating exposure conditions based on lognormal distribution can be useful regardless of averaging time. The appropriateness of estimating exposure distribution with different averaging times by Larsen's equations was also examined using 16 combinations. The geometric mean and geometric standard deviation estimated by Larsen's equations were nearly equal to those estimated by the traditional equations' average, but the difference of the two estimates in each case tended to be large when the ratio of the new averaging time to the original one was large.

Event-related potentials were recorded for 29 patients with multiple cerebral infarcts (MCI) (mean age, 65.7 years) during visual discrimination tasks to clarify the relationship between computed tomographic findings (CT) and P300 component. P300 latency in patients with MCI was significantly longer than that of 15 age-matched normal subjects (mean age, 65.4 years), although no significant difference was found in P300 amplitude between the two groups. There was a significant negative correlation between P300 latency and mental status as determined by the Hasegawa's Dementia Scale. Significant correlation was also found between P300 latency and the degree of ventricular dilatation or severity of periventricular lucency (PVL) on CT scan. P300 latency was not significantly correlated with the number of infarcts. P300 latency in patients with MCI thus appears related to the severity of PVLs and degree of ventricular dilatation in addition to mental status.