Particulate matter modifies the association between airborne pollen and daily medical consultations for pollinosis in Tokyo.

Pollen from Japanese cedar (sugi) and cypress (hinoki) trees is responsible for the growing prevalence of allergic rhinitis, especially pollinosis in Japan. Previous studies have suggested that air pollutants enhance the allergic response to pollen in susceptible individuals. We conducted a time-stratified case-crossover study to examine the potential modifying effects of PM2.5 and suspended particulate matter (SPM) on the association between pollen concentration and daily consultations for pollinosis. A total of 11,713 daily pollinosis cases (International Classification of Diseases, ICD-10, J30.1) from January to May, 2001-2011, were obtained from a clinic in Chiyoda, Tokyo. Daily pollen counts and the daily mean values of air pollutants (PM2.5, SPM, SO2, NO2, CO, and O3) were collected from monitoring stations across Tokyo. The effects of pollen were stratified by the level of PM2.5 and SPM to examine the interaction effect of pollen and particulate pollutants. We found a statistically significant interaction between pollen concentration and PM2.5/SPM. On days with a high level of PM2.5 (>95th percentile), an interquartile increase in the mean cumulative pollen count (an average of 28 pollen grains per cm(2) during lag-days 0 to 5) corresponded to a 10.30% (95%CI: 8.48%-12.16%) increase in daily new pollinosis cases, compared to 8.04% (95%CI: 7.28%-8.81%) on days with a moderate level of PM2.5 (5th-95th percentile). This interaction persisted when different percentile cut-offs were used and was robust to the inclusion of other air pollutants. A similar interaction pattern was observed between SPM and pollen when a less extreme cut-off for SPM was used to stratify the effect of pollen. Our study showed the acute effect of pollen was greater when the concentration of air particulate pollutant, specifically PM2.5 and SPM, was higher. These findings are consistent with the notion that particulate air pollution may act as an adjuvant that promotes allergic disease (i.e. pollinosis).

[Medical consultation dynamics in Japanese cedar pollinosis patients at an office building clinic in central Tokyo].

To clarify medical consultation dynamics in Japanese cedar pollinosis patients visiting an office building clinic in an office block in central Tokyo, we surveyed number of patient at a private ENT clinic in Chiyoda-ku, Tokyo, during the Japanese cedar pollen season from 1990 to 1999. Based on questionnaires and CAP RAST tests in 1995, we studied the profiles of Japanese cedar pollinosis patients and determined positive rates of noncedar antigens. The gender ratio in 1995 was 674 men versus 501 women, most frequently men in their 40s and women in their 20s. Of these, 79.2% worked in Chiyoda-ku and Chuo-ku, but only 1.9% lived in these districts. Positive rates of noncedar antigens in 232 who received simultaneous CAP RAST tests were 64.7% for Japanese cypress, 38.3% for house dust, 35.3% for Dermatophagoides pteronyssinus, 34.4% for Epidermoptidae spp, 19.8% for mixed grasses, and 10.3% for mixed weeds (asteraceous plants). Patients positive for cedar alone were 19.0% and positive for both cedar and cypress but negative for other antigens were 23.3%; about 60% of these were suspected of multiple sensitization to antigens other than cedar and cypress. The number of pollens and patients were summarized weekly and compared. Those paying a first visit were peaked with an increase in pollen in the first week of March almost every year; second visits peaked 1 or 2 weeks later than the first visit. Little increase in first visit was noted even with increasing pollen dissemination from the latter half of March. The relationship between the number of pollen and patients each year from 1990 to 1999 correlated highly with the linear regression equation y = 0.1005x + 547.07 with R2 = 0.7562. The relationship between square roots of the number of pollen and patients each year for 5 year from 1995 to 1999 correlated very highly with the linear regression equation y = 11.167x + 376.72 with R2 = 0.9941. We concluded that the number of patients may be predicted with substantially higher accuracy based on the estimated amount of pollen in a given year.