after production stopped in Anniston. The frequency of diabetes reported in other studies is 5–20%. The estimated weighted prevalence of diabetes in the Anniston population (adjusted for age, race/ethnicity, sex, and over- sampling in west Anniston) was 16%, which corresponded to an unweighted prevalence in the study cohort of 27% in 2005–2007. The weighted prevalence for Anniston is comparable to the higher reported values from other PCB and diabetes studies and above the prevalence of self-reported diagnosed diabetes in Alabama in 2005 (9.8%) and in 2008 (11.2%) (CDC 2005, 2008). In the total group logistic and GAM mod- els, and in participants < 55 years of age, our analyses suggest an increase in the odds of diabetes with increasing PCB levels, although the increase does not appear to be monotonic. Our findings are suggestive of a relatively low- dose PCB effect in the Anniston study popu- lation because the ORs increase in the second quintile and remain elevated in all quintiles. Low-dose effects of PCBs were reported in the Coronary Artery Risk Development in Young Adults (CARDIA) study (Lee et al. 2010). In the present study, we observed an asso- ciation between PCBs and diabetes in younger participants, but not in those ≥ 55 years of age. Our observations in younger Anniston residents are consistent with findings from the CARDIA study in which the PCB–diabetes associations were noted in individuals between 36 and 52 years of age (Lee et al. 2010). The lack of association in older Anniston par- ticipants contrasts with findings from the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study (Lee et al. 2011a), a longitudinal study of elderly in Uppsala, Sweden. The Anniston study group was approximately 50% African American. Other demographic factors and/or differences in access to medical care between Anniston and Uppsala residents likely complicate comparison of the findings across these two populations. Additional strengths of our study include fasting glucose measurements and the ability to distinguish individuals with prediabetes from the normoglycemic. These participants had characteristics intermediate to those with and without diabetes. For example, 29% of partici- pants classed as having prediabetes self-reported heart disease, compared with 20% of those with normoglycemia and 40% with diabetes. Because of differences in these characteristics, exclusion of participants with prediabetes in the referent group was the physiologically and mechanistically preferable choice. Our observation that PCBs were positively associated with diabetes in women is similar to that reported for cohorts exposed to PCBs and furans in contaminated rice oil in Taiwan (Wang et al. 2008) and for women exposed to polybrominated biphenyls (PBBs) and PCBs through contaminated milk and animal feed in Michigan (Vasiliu et al. 2006). Results of these studies, however, were not adjusted for family history or prediabetes. Excess diabetes risk in exposed females may be secondary to a higher percentage of body fat, allowing for greater accumulation and retention of lipo- philic compounds. Other possible mecha- nisms include estrogenic activities found in PCB congeners and their metabolites possibly affecting glucose metabolism. There are several mechanisms that could provide biological plausibility to the observed associations between diabetes and PCBs, dioxins, and other organochlorines, including altered gene transcription, lipid metabolism, insulin production, changes in the insulin sig- naling pathway (Marchand et al. 2005), and altered glucose transport (Tonack et al. 2007). The association of diabetes and PCBs is also complicated by changes in lipid metabolism caused by diabetes, which may affect the dis- tribution and elimination of lipophilic PCBs, PCBs and diabetes in Anniston as perhaps suggested by lower PCBs in higher BMI categories in those with diabetes and prediabetes. Because repeated measurements of PCBs or lipids were not performed, these changes (or possible reverse causality) could not be evaluated. Although the slower elimi- nation of dioxin in participants with diabetes was not supported by findings in the Vietnam Veterans study (Michalek et al. 2003), the cross-sectional nature of our study precludes making inferences. PCBs were produced in Anniston from 1929 to 1971, and this study was under- taken in 2005–2006, at the same time that major remediation began in Anniston. The average duration of residency in Anniston among participants was 28.8 years. Congeners measured in our study participants included those with transient half-lives (e.g., PCB con- geners 18, 44, 101, 110, and 151) and those with half-lives of > 15 years (e.g., PCB con- geners 118, 138, 170) (Emond et al. 2005; Hansen 2001; Ogura 2004). PCB levels among 1,384 participants measured in 1976 in the Michigan PBB cohort were (from low to high, in quartiles) ≤ 5, 5.1–7.0, 7.1–10.0, and > 10 ppb (Vasiliu et al. 2006). These PCB quartile ranges are similar to those observed in Anniston in 2005, 35 years after PCB pro- duction ended; the Anniston quartile ranges, from low to high, were ≤ 1.43, 1.44–3.28, 3.29–7.42, and 7.43–171 ppb. It is likely that the PCB levels in most Anniston residents have decreased since the end of PCB production. In the Michigan PBB cohort, total PCB lev- els remained stable in 37.5% of participants, increased in 12.2%, and decreased in 50.3% over time in samples collected between 1975 and 1994 (Sweeney et al. 2001). Households were randomly selected for participation in the present study, as were individuals within households. Although selection bias cannot be ruled out, there were no significant differences by race or sex 20.0 10.0 tse 5.0 e b iad 2.0 fro 1.0 RO 0.5 0.2 0.1 0.1 0.5 1.0 5.0 10.0 50.0 100.0 ΣPCB concentration (ppb wet weight) F i g u r e 1 . G A M r e s u l t s f o r s e r u m Σ P C B concentration (ppb wet weight) and OR for diabetes, adjusted for age, sex, BMI (continuous), total lipids, race, family history of diabetes, and taking lipid- lowering medications. The OR referent is the lowest PCB measurement, and dashed lines represent the 95% pointwise confidence band. The tick marks on the x-axis represent PCB measurements for each person. Environmental Health Perspectives • volume 120 | number 5 | May 2012 Table 5. Logistic regression [OR (95% CI)] of ΣPCBs, PCB subsets, DDE, and diabetes in the total group and with stratification by sex: Anniston Community Health Survey. Exposure variable PCB quintile (ppb) Q1 (0.11–1.15) Q2 (1.16–2.42) Q3 (2.43–4.33) Q4 (4.34–9.33) Q5 (9.34–170) ΣPCBs per 1 SD increase PCB subsets per 1 SD increase Mono-ortho Estrogenic Di-, tri-, or tetra-ortho Ryanodine Mono-ortho TEQ DDE per 1 SD increase Total group (n = 580) 1.00 (reference) 2.18 (0.98, 4.82) 2.91 (1.24, 6.83) 1.64 (0.64, 4.19) 2.78 (1.00, 7.73) 1.21 (0.87, 1.69) 1.18 (0.86, 1.62) 1.08 (0.80, 1.46) 1.20 (0.86, 1.68) 1.19 (0.85, 1.66) 1.20 (0.87, 2.02) 1.22 (0.85, 1.46) Females (n = 427) 1.00 (reference) 3.14 (1.25, 7.89) 3.26 (1.21, 8.78) 2.47 (0.84, 7.30) 4.87 (1.47, 16.12) 1.52 (1.01, 2.28) 1.47 (0.99, 2.17) 1.28 (0.89, 1.84) 1.50 (1.00, 2.23) 1.49 (1.00, 2.23) 1.51 (1.02, 2.24) 1.42 (1.03, 1.95) PCB quintiles and the log-transformed PCB variable were derived from the ΣPCBs, wet weight. All congener subsets and DDE were log transformed. Individuals with prediabetes were excluded from all models. Covariables in adjusted models were age, BMI (continuous-PCB quintile models, categorical-log transformed models), total lipids, race/ethnicity, family history of diabetes, and taking lipid-lowering medication. Sex was included in total group models. Males (n = 153) 1.00 (reference) 0.45 (0.08, 2.63) 1.08 (0.15, 7.71) 0.30 (0.03, 2.76) 0.29 (0.03, 3.09) 0.68 (0.33, 1.41) 0.74 (0.38, 1.42) 0.74 (0.40, 1.38) 0.68 (0.33, 1.43) 0.66 (0.32, 1.337 0.71 (0.36, 1.39) 0.61 (0.32, 1.15) 731