The effect of body mass index (BMI) and waist:hip ratio (WHR) on plasma levels of organochlorines [i.e., 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE)] was investigated in a sample of black and white women drawn from a population-based study in North Carolina. Organochlorine levels were determined in plasma samples from 99 women selected on the basis of race (black versus white) and quartile of the WHR (1st versus 4th). Of a panel of 20 organochlorine compounds tested, only DDE was detectable in most study subjects. Measurements of height, weight, and waist and hip circumferences were taken during an in-person interview. Information was elicited regarding dietary, residential, and breast-feeding histories. Results of multiple regression analyses indicate that black women had significantly higher plasma levels of DDE than white women. These levels were independent of BMI and WHR. BMI but not WHR was also found to be an independent predictor of DDE plasma level. These results suggest that black/white differences should be considered in studies that explore the relationship between environmental contaminants and various disease outcomes, such as breast cancer risk. In addition, BMI may affect circulating levels of contaminants and should also be considered a potentially important modifying factor for exposure to lipophilic substances.

Chlorinated pesticides, such as DDT3 and its metabolite DDE, are stable, lipophilic substances that have been linked to increased incidence of breast cancer (1, 2, 3), although not all data have been consistent (4, 5, 6). In one study by Wolff et al.(3), serum levels of DDE were found to be significantly elevated in breast cancer cases, as compared to controls. In contrast, a nested case-control study by Krieger et al.(4) on 300 women from a cohort using prospectively collected blood samples showed no overall difference in serum levels of DDE and polychlorinated biphenyls between the 150 women who had developed breast cancer and a matched sample of 150 women who had not. When women were divided into racial subgroups, DDE and polychlorinated biphenyl levels were not associated with increased risk of breast cancer among white women but were modestly associated with risk among black women. Krieger et al.(4) concluded that additional research was needed to explore the biological mechanisms, variations in exposure levels, and interactions involved with “chemical pollutants and their potential impact on breast cancer among diverse groups of women.” Several recent studies, three retrospective (6, 7, 8) and one prospective (9), did not detect an association between organochlorine levels and breast cancer; however, the subjects from these studies were mostly white, with the majority residing in urban or suburban areas. Data on rural and minority populations are lacking.

Blacks have been shown to exhibit higher organochlorine levels than whites (4, 10). There are several reasons why blacks and whites may have differing levels of circulating organochlorines and why, ultimately, this may impact on breast cancer risk. First, African-Americans may have increased exposure to organochlorines. Factors that influence organochlorine turnover and excretion also may differ between racial groups, again leading to variation in circulating levels. The shunting of organochlorines into breast milk represents one of the primary excretory pathways, and there are some data to support that levels of organochlorines may be lowered by breastfeeding (4, 11, 12, 13, 14). Whether breastfeeding practices can explain different physiological levels of organochlorines between racial groups is a subject for further research. Additionally, differences between black and white women in area of residence, occupation, and/or diet may lead to variability in organochlorine exposure. Although contaminated ground and spring water can serve as a source for organochlorines, these lipophilic substances dissolve in fat and generally find their way into the food supply (15, 16, 17, 18). Fish, particularly fatty varieties caught in local tributaries, as well as other animal foods raised on contaminated soil, can be significant sources of exposure. Many, although not all, dietary surveys suggest that high-fat diets are more prevalent among blacks and, thus, may contribute to higher organochlorine levels (19, 20).

Finally, because pesticides are lipophilic and stored in the adipose tissue, there may be differences between racial groups due to differential degrees of adiposity and body fat patterning. It is well established that the prevalence of obesity is higher among black women than white women (21, 22). Speculation exists that these greater fat stores may increase the body’s capacity to accumulate lipophilic contaminants. In addition, the rate of body fat turnover also may influence circulating organochlorine levels. Several studies indicate that body fat turnover is regulated, in part, by fat patterning and that visceral fat [associated with upper body (android) obesity] turns over at a higher rate than peripheral fat [associated with lower body (gynoid) obesity; Refs. 23, 24, 25, 26, 27]. Body fat deposition also has been shown to differ between blacks and whites. Despite these associations, there has been no reported research that has explored the relationship between organochlorine levels and body fat (either degree of adiposity or fat patterning). Such research may be helpful to clarify the relationship between disease and exposure, especially in breast cancer, for which obesity and, in particular, upper body obesity have been declared independent risk factors (28, 29, 30, 31).

Using data from a population-based sample of black and white women residing in North Carolina, we embarked on a study to explore associations between body fat status and organochlorine levels in the plasma. We hypothesized that obesity and, especially, upper body obesity, as defined by a high WHR, would be associated with increased levels of circulating organochlorines. Furthermore, we analyzed data on DDE levels separately for black and white women to determine whether the higher plasma levels of organochlorines reported among black women could be accounted for by differences in body size or shape or other potentially relevant lifestyle characteristics.

Subjects.

Study subjects are control women enrolled in the Carolina Breast Cancer Study, a population-based, case-control study of breast cancer that oversampled younger (<50 years old) and African-American women (32). All study participants reside in a 24-county region encompassing central and eastern North Carolina. Women, ages ≤64 years, were identified from North Carolina Division of Motor Vehicles lists; 65–74-year-old women were identified from United States Health Care Financing Administrations lists. After consent was obtained, an appointment was scheduled for a home visit to complete an interview and to take a blood specimen. Each home visit was conducted by a trained nurse interviewer and took ≈1 h. Questionnaire items included reproductive and menstrual history, hormone use, alcohol consumption, occupational exposures, and socioeconomic characteristics. Subjects in this study were selected from control women without breast cancer on the basis of age (45–74 years), race, and distribution within the race-specific 1st or 4th quartiles of WHR (whites: 1st quartile, ≤0.736, 4th quartile, ≥0.830; blacks: 1st quartile, ≤0.758, 4th quartile, ≥0.877). These women are, on the basis of their age distribution, likely to be peri- or postmenopausal because most of all control women in this age range were either peri- or postmenopausal.

Sample Collection and Storage.

Blood samples were collected in three 8-ml vacutainer tubes containing acid, citrate, and dextrone. Most samples were centrifuged within 24 h (10 within 48 h and 1 within 36 h), and plasma was removed and frozen at −70°C. Samples were thawed at the time of organochlorine analysis. Upon examination, no correlation between days to processing, ranging from 1 to 3 days, and ln(DDE) levels was detected (r = −0.03, P = 0.77).

Laboratory Analyses.

Organochlorine analyses were conducted via high-resolution gas chromatography with electron capture using a Hewlett Packard 5890 gas chromatograph equipped with a Supelco SPB-608 fused silica capillary column (30 × 0.25 inner diameter). Plasma samples were analyzed for chlorinated pesticides (α- and γ-chlordane; oxychlordane; heptachlor; heptachlor epoxide; trans-nonachlor; α-, β-, δ-, and γ-lindane; aldrin; endrin; dieldrin; hexachlorobenzene; endosulfans I and II; DDE; DDT; methoxychlor; and mirex). The detection limit for all compounds was <0.3 ng/ml or ppb. Analyses for total lipid was conducted by a gravimetric procedure. Lipids were extracted by the method of Folch et al.(33) as modified by Ulman and McClure (34) using chloroform/methanol (2:1) as the initial solvent. Final concentrations of organochlorines were expressed in absolute terms, on the basis of whole plasma.

Statistical Analysis.

Organochlorine levels that registered <0.3 ng/ml or “undetectable” were assigned a value of 0.15 ng/ml for the purpose of analyses. This value was chosen because it represents the midpoint between a true zero reading, which is improbable, and the detectable limit of 0.3 ng/ml. It is, therefore, considered a conservative estimate. χ2 tests comparing frequencies in black versus white women and t tests for mean DDE levels within groups of covariates were computed. χ2 tests for trend were applied to ordinal variables. A natural log transformation to normalize the plasma DDE distribution was applied and used in the multivariate analyses. Multiple linear regression models using analysis of covariance were computed to determine the relationship between ln(DDE) plasma levels (dependent variable) and whether the subject was identified from either the 1st or 4th quartile of WHR, while simultaneously controlling for potential confounders, including age, race (white versus black), BMI (kg/m2), breastfeeding history (ever versus never), and weight loss in the past year (>5 pounds). Two-sided statistical tests were used to evaluate the data, and a significance level of P = 0.05 was applied.

We were able to retrieve and analyze plasma samples for 99 of 102 (97%) control women who fell in the 1st or 4th quartile of the WHR within their respective racial group. Although a panel of 20 organochlorine compounds was analyzed, only DDE was detected in a substantial number of the women in our sample, and it was, therefore, the only contaminant used in the statistical analyses. There were only five other compounds besides DDE for which there were measurable levels of residue. For each of these, however, detectable measures were found in fewer than 30 subjects. Only two samples did not have a detectable level of DDE and were assigned a level of 0.15 ppb. The overall mean DDE level for the 99 subjects in our sample was 10.5 ppb (SD = 12.8 ppb). Total lipids (mean = 583.2 ng/dl, SD = 302.3 ng/dl) were not found to be correlated with DDE level (r = 0.0025, P = 0.98) and, therefore, were not included in any further analyses.

Characteristics of the study subjects for the entire sample and according to race are presented in Table 1. Of the 99 women, 42 were black and 57 were white. DDE levels were significantly higher among black women than white women, with means of 16.3 ppb (SD = 16.0 ppb) and 6.2 ppb (SD = 7.2 ppb), respectively. Only BMI and fish consumption were found to be significantly different between blacks and whites. Black women had a higher average BMI and consumed a higher number of servings of freshly caught fish per year than whites.

Bivariate analyses of the relationships between the subjects’ characteristics and DDE levels, for all women combined and according to race, are presented in Table 2. No statistically significant difference was found for the mean DDE levels in the 1st versus 4th quartiles of WHR for all women combined, with mean levels of 9.5 ppb (SD = 12.0 ppb) and 13.5 ppb (SD = 16.0 ppb), respectively (P = 0.29). For all women combined, race, BMI (≥27.9 kg/m2), and positive breastfeeding history were significant, positive predictors of ln(DDE) levels. Regardless of race, mean plasma DDE levels were consistently higher among heavier women, women who breastfed their children, and women who reported farming or living in a rural area as a child, although the only statistically significant association was with breastfeeding among white women. For WHR, recent weight loss or weight gain, and consumption of fish, results were not statistically significant, and relationships with DDE levels varied between black and white women.

The results of the multiple regression analyses for all women combined, as well as those stratified by race, are presented in Table 3. Controlling for other covariates, including age, race, breastfeeding history, BMI (kg/m2), and weight loss and weight gain in the past year, no overall relationship was found between the 4th (highest) and 1st (lowest) quartile of the WHR and ln(DDE) plasma levels. Race-specific analyses yielded similar results. For all women combined, race, BMI, and a positive breastfeeding history were found to be significant positive predictors of ln(DDE) levels. Both BMI and breastfeeding history remained significantly associated with DDE levels among white women only when black and white subjects were analyzed separately.

Our results do not support the hypothesis that central obesity modifies plasma levels of DDE. However, our analyses did demonstrate that both BMI and race are independent predictors of DDE levels after controlling for other covariates. Differences in breastfeeding, farming history, childhood residence, and recent weight gain or loss do not appear to explain these associations. Although fish consumption was higher among blacks than whites, this does not explain the racial differences in DDE levels that were observed. It is possible that other food sources, such as animal fat consumption, or nonfood exposures, such as agricultural factors not captured by the data, might explain the differences in DDE levels among blacks and whites (15, 16). Although we found a positive relationship between DDE levels and breastfeeding, the means were higher among those who reported breastfeeding compared to those who never breastfed, which is not consistent with previous reports (13, 14). This discrepancy may be due, in part, to differences between our study subjects and those from previous reports with regard to metabolism, because our subjects were selected on the basis of WHR.

Limitations of our study include the possibility of misclassification of DDT exposure, which was measured indirectly by DDE levels in plasma. DDE is a stable metabolite and a good surrogate of DDT exposure. DDE measurement is considered more accurate when it is derived from adipose tissue (35). Adipose tissue, however, was not collected in the Carolina Breast Cancer Study, which was not originally designed to address associations with organochlorines. Despite these deficiencies, exposure misclassification of DDE would not be expected to differ according to the other variables of interest in this study, and therefore, the observed associations with DDE would likely be attenuated due to nondifferential misclassification error. In addition, our sample size may have limited our ability to detect some associations with DDE levels as well as differences between black versus white women.

We were unable to evaluate 19 of the organochlorine residues analyzed. These represented an assortment of compounds that were used less frequently than DDT, rare metabolites, or metabolites with shorter half-lives. Although plasma levels were detected in some women, the numbers were too few to support independent statistical analyses.

The results of this analysis suggest that black/white differences should be considered in future studies examining the relationship between DDT and disease risk, such as breast cancer, because exposure to DDT is significantly higher among black women. In addition, BMI may affect circulating levels of contaminants and should be considered as a potentially important modifying factor for exposure to lipophilic substances.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

        
1

The work reported here was supported by Duke University Medical Center Comprehensive Cancer Center Core Support Supplement (Environmental Contaminants and Body Fat, National Cancer Institute Grant P30-CA14236-21S2) and the University of North Carolina at Chapel Hill Specialized Program of Research Excellence (National Cancer Institute Grant P50-CA58223).

                
3

The abbreviations used are: DDT, 2,2-bis(p-chlorophenyl)-1,1,1-trichloroethane; DDE, 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene; WHR, waist:hip ratio; BMI, body mass index.

Table 1

Descriptive characteristics for all subjects combined and according to race

CharacteristicRacial group
Blacks and whites combined (n = 99)Blacks (n = 42)Whites (n = 57)
DDE (ppb), mean (SD) 10.5 (12.8) 16.3 (16.0)a 6.2 (7.2) 
WHR, mean (SD) 0.82 (0.11) 0.84 (0.12) 0.80 (0.12) 
BMI (kg/m2), mean (SD) 29.7 (7.5) 32.6 (7.4)b 27.6 (6.8) 
Age (yr), mean (SD) 57.4 (9.5) 57.4 (9.4) 57.3 (9.6) 
Fish consumption (servings/year), mean (SD) 8.9 (21) 14.7 (29)a 4.6 (12) 
% ever breastfed children 36 45 30 
% rural residence as a child 42 54 34 
% ever farmed 48 53 45 
% weight loss in the past year (>5 pounds) 17 17 18 
% weight gain in past year (>5 pounds) 32 38 28 
CharacteristicRacial group
Blacks and whites combined (n = 99)Blacks (n = 42)Whites (n = 57)
DDE (ppb), mean (SD) 10.5 (12.8) 16.3 (16.0)a 6.2 (7.2) 
WHR, mean (SD) 0.82 (0.11) 0.84 (0.12) 0.80 (0.12) 
BMI (kg/m2), mean (SD) 29.7 (7.5) 32.6 (7.4)b 27.6 (6.8) 
Age (yr), mean (SD) 57.4 (9.5) 57.4 (9.4) 57.3 (9.6) 
Fish consumption (servings/year), mean (SD) 8.9 (21) 14.7 (29)a 4.6 (12) 
% ever breastfed children 36 45 30 
% rural residence as a child 42 54 34 
% ever farmed 48 53 45 
% weight loss in the past year (>5 pounds) 17 17 18 
% weight gain in past year (>5 pounds) 32 38 28 
a

P < 0.05, black/white comparisons.

b

P < 0.001, black/white comparisons.

Table 2

Mean DDE levels (ppb) and SDs according to characteristics of the subjects by race and for all subjects combined

CharacteristicAll study subjects (n = 99)Blacks (n = 42)Whites (n = 57)
nMean (SD)nMean (SD)nMean (SD)
WHR (quartile)       
 1st quartile (<0.72) 49 9.5 (12.0) 21 18.6 (16.0) 28 6.3 (9.8) 
 4th quartile (≥0.90) 50 13.5 (16.0) 21 16.1 (19.0) 29 8.2 (5.0) 
BMI (kg/m2      
 <27.9 50 7.5 (8.4)a 13 13.4 (8.3) 37 5.4 (7.4) 
 ≥27.9 49 13.5 (16.0) 29 17.6 (19.0) 20 7.6 (6.7) 
Weight loss in past year       
 >5 pounds 17 7.5 (8.5) 8.9 (10.0) 10 6.4 (8.0) 
 ≤5 pounds 82 11.1 (13.0) 35 17.8 (17.0) 47 6.1 (7.0) 
Weight gain in past year       
 >5 pounds 32 10.6 (13.0) 16 13.1 (15.0) 16 8.0 (11.0) 
 ≤5 pounds 67 10.4 (13.0) 26 18.3 (17.0) 40 5.5 (5.0) 
 Missing data      
Breastfed children       
 Ever 36 14.7 (16.0)a 19 18.9 (19.0) 17 10.0 (10.8)a 
 Never 63 8.1 (9.7) 23 14.2 (13.0) 40 4.6 (4.2) 
Farming history       
 Ever 52 11.6 (14.0) 21 18.7 (17.0) 31 6.8 (9.3) 
 Never 45 9.1 (11.0) 19 14.2 (16.0) 26 5.2 (3.6) 
 Missing     
Residence as a child       
 Rural 47 12.5 (14.0) 24 17.2 (16.0) 23 7.7 (10.0) 
 Urban 52 8.6 (11.0) 18 15.2 (16.0) 34 5.2 (3.6) 
Fresh-caught fish consumption       
 ≥11 times/yr 19 13.8 (13.0) 16.4 (15.0) 11 10.3 (8.1) 
 1–10 times/yr 24 8.6 (12.0) 12 13.3 (15.0) 12 3.8 (4.1) 
 None 56 10.2 (13.0) 37 18.2 (18.0) 19 6.0 (7.6) 
 Test for trend 0.30  0.78  0.16  
CharacteristicAll study subjects (n = 99)Blacks (n = 42)Whites (n = 57)
nMean (SD)nMean (SD)nMean (SD)
WHR (quartile)       
 1st quartile (<0.72) 49 9.5 (12.0) 21 18.6 (16.0) 28 6.3 (9.8) 
 4th quartile (≥0.90) 50 13.5 (16.0) 21 16.1 (19.0) 29 8.2 (5.0) 
BMI (kg/m2      
 <27.9 50 7.5 (8.4)a 13 13.4 (8.3) 37 5.4 (7.4) 
 ≥27.9 49 13.5 (16.0) 29 17.6 (19.0) 20 7.6 (6.7) 
Weight loss in past year       
 >5 pounds 17 7.5 (8.5) 8.9 (10.0) 10 6.4 (8.0) 
 ≤5 pounds 82 11.1 (13.0) 35 17.8 (17.0) 47 6.1 (7.0) 
Weight gain in past year       
 >5 pounds 32 10.6 (13.0) 16 13.1 (15.0) 16 8.0 (11.0) 
 ≤5 pounds 67 10.4 (13.0) 26 18.3 (17.0) 40 5.5 (5.0) 
 Missing data      
Breastfed children       
 Ever 36 14.7 (16.0)a 19 18.9 (19.0) 17 10.0 (10.8)a 
 Never 63 8.1 (9.7) 23 14.2 (13.0) 40 4.6 (4.2) 
Farming history       
 Ever 52 11.6 (14.0) 21 18.7 (17.0) 31 6.8 (9.3) 
 Never 45 9.1 (11.0) 19 14.2 (16.0) 26 5.2 (3.6) 
 Missing     
Residence as a child       
 Rural 47 12.5 (14.0) 24 17.2 (16.0) 23 7.7 (10.0) 
 Urban 52 8.6 (11.0) 18 15.2 (16.0) 34 5.2 (3.6) 
Fresh-caught fish consumption       
 ≥11 times/yr 19 13.8 (13.0) 16.4 (15.0) 11 10.3 (8.1) 
 1–10 times/yr 24 8.6 (12.0) 12 13.3 (15.0) 12 3.8 (4.1) 
 None 56 10.2 (13.0) 37 18.2 (18.0) 19 6.0 (7.6) 
 Test for trend 0.30  0.78  0.16  
a

P < 0.05.

Table 3

Multiple regression analyses predicting 1n(DDE) levels (ppb) for all subjects combined and by race

All study subjects (n = 96)Blacks (n = 41)Whites (n = 57)
βSEPβSEPβSEP
WHR (4th vs. 1st quartile) 0.34 0.25 0.17 0.38 0.42 0.37 0.37 0.33 0.27 
Race (black vs. white) 0.58 0.24 0.02       
Age (yr) 0.003 0.012 0.81 0.005 0.02 0.82 0.008 0.01 0.60 
BMI (kg/m20.04 0.02 0.03 0.02 0.03 0.40 0.05 0.02 0.04 
Breastfed children (ever vs. never) 0.65 0.24 0.01 0.33 0.45 0.46 0.88 0.29 0.003 
Weight loss in past year (>5 pounds) −0.18 0.19 0.35 −0.49 0.36 0.18 0.02 0.22 0.92 
Weight gain in past year (>5 pounds) −0.16 0.16 0.31 −0.50 0.31 0.11 0.02 0.17 0.89 
All study subjects (n = 96)Blacks (n = 41)Whites (n = 57)
βSEPβSEPβSEP
WHR (4th vs. 1st quartile) 0.34 0.25 0.17 0.38 0.42 0.37 0.37 0.33 0.27 
Race (black vs. white) 0.58 0.24 0.02       
Age (yr) 0.003 0.012 0.81 0.005 0.02 0.82 0.008 0.01 0.60 
BMI (kg/m20.04 0.02 0.03 0.02 0.03 0.40 0.05 0.02 0.04 
Breastfed children (ever vs. never) 0.65 0.24 0.01 0.33 0.45 0.46 0.88 0.29 0.003 
Weight loss in past year (>5 pounds) −0.18 0.19 0.35 −0.49 0.36 0.18 0.02 0.22 0.92 
Weight gain in past year (>5 pounds) −0.16 0.16 0.31 −0.50 0.31 0.11 0.02 0.17 0.89 
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