Per our selection criteria, of the 30 boys with serum samples analyzed for dioxin-like compounds, fifteen boys had congenital abnormalities (six hypospadias and nine cryptorchidism). No boy had both malformations. The 15 control boys did not have either hypospadias or cryptorchidism. The distances the boys lived from the Khimprom factory at the time of the study, along with other demographic characteristics, are presented in Table . The mean (sd) distance the boys lived from the Khimprom factories was 4.45 (1.76) km. During the pregnancy with her son, of the 29 mothers, 8 (27%) lived less than 2 km, 8 (27%) lived 2–6 km, and14 (45%) lived greater than 6 km from the Khimpron factory. One subject was missing questionnaire data, including distance from Khimprom, medical history, and local food consumption. Only three of the boys' fathers worked at the Khimprom factory during the year prior to the child's birth. While pregnant, two of the boys' mothers reported alcohol intake and one smoked.
Demographic characteristics of adolescent boys from Chapaevsk, Russia (N = 30)
Since the PCDD, PCDF and PCB distributions were skewed, percentile distributions for serum concentrations and WHO-TEQs for 7 PCDD congeners, 9 PCDF congeners, 3 non-ortho (coplanar) PCBs and 6 mono-ortho PCBs are shown in Table . The median (25th, 75th percentile) concentrations for total PCDDs, PCDFs and coplanar PCBs were 95.8 pg/g lipids (40.9, 144), 33.9 pg/g lipids (20.4, 61.8), and 120 pg/g lipids (77.6, 157), respectively. The median (25th, 75th percentile) concentration for total mono-ortho PCBs was 47.7 ng/g lipids (39.2, 78.4); as expected more than two orders of magnitude larger than for the other compounds. For WHO-TEQs, the median (25th, 75th percentile) for total PCDDs, PCDFs, and coplanar PCBs were 0.29 (0.1, 9.14), 7.98 (5.27, 12.3), and 7.39 (4.51, 11.9), respectively. For total mono-ortho PCBs, the median (25th, 75th percentile) WHO-TEQ was 8.80 (7.16, 15.5). The total WHO-TEQ for dioxins, furans and PCBs had a median (25th, 75th percentile) of 30.9 (18.4, 46.8).
Distribution of concentrations and WHO-TEQs of PCDD/Fs and PCBs in adolescent boys from Chapaevsk, Russia
Although means and standard deviations do not appropriately describe skewed distributions, to allow for comparisons with other studies we briefly present them. The mean (sd) of total PCDDs, PCDFs, and coplanar PCBs were 104 pg/g lipids (78.0), 63.8 pg/g lipid (89.9) and 123 pg/g lipid (53.1), respectively. The mean of the TEQs for PCDDs, PCDFs, and coplanar PCBs were 5.51, 13.9 and 8.35 pg TEQ/g lipid, respectively.
PCDDs, PCDFs, and coplanar PCBs accounted for a mean percent of total serum dioxin concentrations of 34.3% (range 8.4 to 80.1%), 18.0% (range 4.4 to 57.5%), and 47.7% (range 15.5 to 73.9%), respectively. The relatively high concentrations of mono-ortho PCBs contributed significantly to TEQs and were therefore also included in the total TEQs. PCDDs, PCDFs, coplanar PCBs, and mono-ortho PCBs accounted for a mean percent of total TEQs of 11.9% (range 0.14 to 59.0%), 30.4% (range 3.9 to 71.3%), 25% (range 8.1 to 43.0%), and 32.8% (range 0 to 60.1%), respectively.
Figure displays the percent contribution of each PCDD, PCDF and PCB congener to the total TEQ/g lipid for the thirty boys. Based on serum concentrations, the predominant dibenzo-p
-dioxin congeners were OCDD and 1,2,3,4,6,7,8-HpCDD (mean percents of 73.8% and 22.2%, respectively), while 1,2,3,7,8-PeCDD and 1,2,3,4,6,7,8-HpCDD were the predominant congeners based on mean TEQs (mean percents of 56.2% and 37.0%, respectively). For PCDFs, 2,3,4,7,8-PeCDF and 1,2,3,4,7,8-HxCDF accounted for the majority of the total PCDF concentrations (means of 35.5% and 32.4%, respectively), and these same two congeners accounted for the majority of the total PCDF TEQs (75.2% and 16.7%, respectively). For coplanar PCBs, 3,3',4,4',5-PeCB (#126) and 3,3',4,4',5,5'-HxCB (#169) accounted for the majority of the total coplanar PCB concentrations (means of 63.4 and 35.3%, respectively), and 3,3',4,4',5-PeCB (#126) accounted for 94.1% of the total coplanar PCB TEQs. For mono-ortho PCBs, 2,3',4,4',5-PeCB (#118) and 2,3,3',4,4',5-HxCB (#156) accounted for the majority of the total mono-ortho PCB concentrations (means of 56.0% and 19.7%, respectively), while 2,3,3',4,4',5-HxCB (#156) accounted for 48.3% of the total mono-ortho PCB TEQs and 2,3',4,4',5-PeCB (#118) for 30.3%. The concentrations of six prevalent PCB congeners, or so-called indicator PCBs [23
], are presented in Table . Here the largest contributors to the sum of the 6 congeners were PCB 153 (34.6%) and PCB138 (20.4%).
Percent contribution of PCDDFs and PCBs to TEQs (pg TEQ/g lipid) among boys from Chapaevsk.
Concentrations (ng/g lipid) of six PCB congenersa in blood of adolescent boys from Chapaevsk, Russia
Only two of the 30 boys had levels of 2,3,7,8-TCDD greater than the detection limits; levels for these two boys were 17.9 and 21.7 pg/g lipid. Because all samples had different weights (4.1 to 12.1 g), different percent lipids, and percent recoveries, the DLs for TCDD in our study samples ranged from 1.5 to 16.5 pg/g lipid. We were unable to identify unique characteristics of the two boys with detectable levels of 2,3,7,8-TCDD. There were no differences in sum of PCDDs, PCDFS, and PCBs between the group of boys with cryptorchidism or hypospadias and the comparison boys. The smallest difference we could detect however, in the sum of dioxin concentrations given the small size of this study is 175 pg/g lipid (with 80% power) or 200 pg/g lipid (with 90% power). In other words, we can only detect differences that are larger than the observed standard deviation in sum of dioxin-like compounds.
Of the 29 boys with lifetime food consumption data, 86% (n = 25) had consumed local meat products (in particular, 83% had consumed non-chicken meat and 52% had consumed local chicken), 83% (n = 24) had consumed local fish, 93% (n = 27) had consumed locally produced dairy products or eggs, and 97% (n = 28) had consumed locally grown fruits and/or vegetables.
Using regression models adjusting for age, associations were found between the log sum of dioxin concentrations and several characteristics of the thirty boys (Table ). Increasing age, local non-chicken meat and fish consumption, and log of lipid-adjusted PCB congener 118 were associated with increases in the sum of the dioxin concentrations. For instance, a one- year increase in age increased the mean sum of dioxin-like compounds (291 pg/g lipids) by 30% and consumption of local non-chicken meat increased dioxin-like compounds by 75%. Gestational age in weeks was inversely associated with the sum of the dioxin concentrations, multiplicative factor of 0.92. Although the coefficient for the relationship between log sum of dioxin-like compounds and current residential distance from the Khimprom factory was less than 1.0 (which would support a decrease in dioxin levels with increasing distance from the factory), it was not statistically significant. We also explored the relationship between the sum of dioxin-like compounds and categories of GIS distances from Khimprom plants (<2 km, 2–6 km, >6 km) and found an inverse association, though it too was not statistically significant. Duration of breast-feeding, distance from Khimprom during pregnancy, maternal parity, and parental occupation were unrelated to sum of dioxin-like compounds or sum of dioxin TEQs.
Individual predictors of log sum of dioxin-like compoundsa, adjusted for age in years
Models predicting the log of the sum of dioxin TEQ's (Table ) were generally similar in magnitude and direction for the predictors shown in Table , but suggested weaker effects of age (multiplicative factor = 1.30, p = 0.14) and local fish consumption (multiplicative factor = 1.43, p = 0.32), and a stronger effect of maximal parental education (multiplicative factor = 1.50, p = 0.086) and log of PCB 118 TEQ (multiplicative factor = 2.61, p < 0.001).
Predictors of log dioxin TEQsa among boys in Chapaevsk, Russia (adjusted for age).
The best fitting multivariate models for predicting the sum of dioxin concentrations are summarized in Table . Even after accounting for the strong relationship between PCB 118 concentration and the sum of dioxin concentrations on the log scale, consumption of local non-chicken meat showed a significant association with increased dioxin levels. Similarly, the best fitting multivariate model for predicting the sum of dioxin TEQs also included PCB 118 and consumption of local non-chicken meat (R-square = 0.63). The best-fitting model for sum of dioxin concentrations, excluding log PCB 118, included age, weeks of gestation, income level, and consumption of local non-chicken meat and local dairy products, with an R-square of 0.56. The best fitting multivariate model for predicting the sum of dioxin TEQs, excluding log PCB 118 TEQ, included the same five predictors as those shown in Table with similar magnitudes and significance of effects (R-square = 0.56).
Multivariate models for predicting log sum of dioxina concentrations among adolescent boys in Chapaevsk, Russia