Mahajan et al. available at http://www.aghealth.org/question- naires.html. Applicators who did not return a questionnaire were generally similar to those who did with respect to many characteristics including use of crop insecticides; however, small differences were observed with respect to education, age, family size, and vegetable con- sumption (Tarone et al. 1997). Because of changing pesticide exposure patterns over time, pesticide exposure information, pesticide han- dling practices, and other information was updated by computer-aided telephone inter- view from 1999 to 2003. However, because of the proximity of this interview period to the end of cancer incidence follow-up, it is unlikely that this exposure information was etiologically relevant, and we have not used the interview information here. We estimated phorate exposure using phorate lifetime exposure-days, calculated by multiplying the frequency of phorate use in an average year and the number of years of use, using the midpoints of the questionnaire cate- gories, and intensity-weighted exposure-days, calculated by multiplying lifetime exposure- days by an intensity score calculated using the following algorithm: intensity score = (mixing status + application status + equipment repair) × PPE (Dosemeci et al. 2002). This algorithm takes into account the effect of exposure-mod- ifying factors by assigning different weights to various activities based on the inverse of their potential contribution to total exposure. For example, because dermal absorption is often the most important exposure route for pesti- cide applicators (Maroni et al. 2000), the use of chemically resistant gloves was weighted to confer a greater reduction in intensity score than any other single item of PPE; the use of disposable outer clothing reduced the intensity score to a lesser degree. Statistical analysis. In contrast to the previ- ously published tumor-specific analysis of prostate cancer, which examined prostate can- cer risk with respect to the ever/never use of pesticides among all male pesticide applicators without a prior prostate cancer diagnosis, this analysis was limited to the subset of applicators who completed the take-home questionnaire. Prevalent cancer cases (n = 620) and applica- tors who did not provide information on phor- ate exposure or other variables (n = 3,655) were excluded from this analysis, leaving 5,903 exposed and 15,113 nonexposed applicators. Participants with missing information tended to be older and to live in North Carolina. They were also likely to have missing information for more than one of the variables listed above. Cancer sites were selected for analysis if there were 15 or more incident diagnoses among phorate-exposed subjects. Speciﬁcally, these sites were a) all cancers combined; b) cancers of the colon, lung, and prostate; and c) the grouping of lymphohematopoietic 1206 cancers, which contains both Hodgkin lym- phoma and NHL, leukemia, and multiple myeloma. All statistical analyses were con- ducted in AHS data release 0412.01 using Stata version 8 (StataCorp, College Station, TX; StataCorp 2003). Poisson regression was used to calculate incidence rate ratios (RR) and 95% conﬁdence intervals (CI). Both life- time exposure-days and intensity-weighted exposure-days for exposed applicators were categorized into tertiles based on the distribu- tion of the exposure metric among cancer cases. To improve resolution at high exposure levels, we further categorized lifetime exposure- days by splitting the top tertile at the median when the split left at least four exposed cases in each new category. With intensity-weighted exposure-days used as the exposure measure- ment, the highest tertile was not split because of a small number of cases. Finally, because measures of lifetime cumulative exposure do not distinguish between infrequent exposure over a long period of time and more frequent exposure over a short period of time, which could make a difference with respect to cancer, we examined cancer incidence in relation to average days of use per year categorized as none, low, and high (low and high categorized at the median) and stratiﬁed by low and high years of use (categorized at median). Both the lifetime and intensity-weighted exposure-days analyses used the nonexposed and lowest exposed categories as the reference group. Cancer-speciﬁc analyses were adjusted for age as a continuous variable; applicator type (private or commercial); state of residence (Iowa or North Carolina); education (≤ high school graduate, > high school graduate); pack- years of smoking categorized at the median (never, ≤ 12, > 12); history of the specific tumor in ﬁrst-degree relatives (yes or no); and use of the five most correlated pesticides [aldicarb, ethylene dibromide, aldrin, 2,4,5- trichlorophenoxy propionic acid (2,4,5-TP), and butylate]. Pearson correlation coefﬁcients ranged from 0.39 (aldicarb) to 0.36 (butylate). We categorized use of each correlated pesticide as never, low, and high usage, employing the median lifetime exposure-days of use to distin- guish between low and high usage. Although the results of these more fully adjusted analyses and the analyses adjusted for age and smoking Table 1. Characteristics of applicators by phorate exposure in the AHS (1993–1997) [no. (%)]. Lowest exposed n = 2,407 Other exposed n = 3,496 Characteristic Age (years) < 40 40–49 50–59 ≥ 60 Sex Male Female State of residence Iowa North Carolina Applicator type Commercial Private Smoking history Never Light (< 12 pack-years) High (≥ 12 pack-years) Education ≤ High school > High school Family history of cancera No Yes Alcohola,b No Yes Corn farming No Yes Use of correlated pesticides Aldicarb Ethylene dibromide Aldrin 2,4,5-TP Butylate No. of pesticides usedc Nonexposed n = 15,113 1,981 (13.1) 4,161 (27.5) 3,630 (24.0) 5,341 (35.3) 14,589 (96.5) 524 (3.5) 9,783 (64.7) 5,330 (35.3) 1,779 (11.8) 13,334 (88.2) 8,262 (54.7) 3,437 (22.7) 3,414 (22.6) 8,183 (54.2) 6,930 (45.9) 8,257 (58.7) 5,809 (41.3) 5,149 (34.8) 9,641 (65.2) 4,897 (32.4) 10,216 (67.6) 932 (6.2) 687 (4.6) 1,466 (9.7) 590 (3.9) 3,038 (20.1) 10.7 ± 5.9 167 (6.9) 581 (24.1) 666 (27.7) 993 (41.3) 2,387 (99.2) 20 (0.8) 2,261 (93.9) 146 (6.1) 101 (4.2) 2,306 (95.8) 1,429 (59.4) 542 (22.5) 436 (18.1) 1,273 (52.9) 1,134 (47.1) 1,225 (53.0) 1,084 (47.0) 593 (24.9) 1,789 (75.1) 149 (6.2) 2,258 (93.8) 111 (4.6) 42 (1.8) 674 (28.0) 122 (5.1) 940 (39.1) 16.0 ± 5.9 218 (6.2) 797 (22.8) 992 (28.4) 1,489 (42.6) 3,475 (99.4) 21 (0.6) 2,945 (84.2) 551 (15.8) 219 (6.3) 3,277 (93.7) 1,977 (56.6) 793 (22.7) 726 (20.8) 2,050 (58.6) 1,446 (41.4) 1,763 (53.0) 1,561 (47.0) 944 (27.4) 2,506 (72.6) 366 (10.5) 3,130 (89.5) 444 (12.7) 102 (2.9) 1,028 (29.4) 257 (7.4) 1,437 (41.1) 17.0 ± 6.5 aColumn numbers do not add up to total n because of missing information. bBased on reported alcohol consumption in the past 12 months. cMean ± SD. VOLUME 114 | NUMBER 8 | August 2006 • Environmental Health Perspectives