A total of 552 employees (Antwerp = 206; Cottage Grove = 131; Decatur = 215) participated from these facilities representing approximately 60% of Antwerp, 50% of Decatur and 65% of Cottage Grove eligible employees. Demographic characteristics of those eligible employees who did not participate are not known although substantial differences between participants and non-participants are unlikely given the routine practice of offering voluntary medical surveillance programs at these facilities for more than 20 years.
Of the 552 employee participants at these 3 facilities, 506 (92%) self-reported that they did not take cholesterol-lowering medications: 196 (95%) for Antwerp, 122 (93%) for Cottage Grove, and 188 (87%) for Decatur. Results will focus on these 506 participants.
Presented in Table 1 are measures of central tendency for the 506 participants for PFOA, PFOS, demographic factors and the clinical chemistries. The number and percent of employees by specific reference points for demographic factors and clinical chemistry findings are presented in Table 2. Besides their younger age, there were substantially fewer Antwerp employees (5%) who would be categorized as obese (BMI ≥ 30) compared to Cottage Grove (44%) or Decatur (32%) employees. More than 40% of Antwerp and Cottage Grove employees reported drinking one alcoholic beverage per day or more compared to only 1% of Decatur employees. There were regional cultural/lifestyle practices that likely account for this difference in alcohol consumption. Other statistically significant differences between the three locations were observed for blood glucose, HDL, triglycerides, alkaline phosphatase, ALT, total bilirubin, and the ‘metabolic syndrome’. The higher percentage of Antwerp male employees with total bilirubin >1.5 mg/dl has been attributed to the likely greater prevalence of Gilbert’s syndrome (Olsen et al. 1999). Only 1% of the Antwerp employees were categorized as having the ‘metabolic syndrome’ compared to 20 and 13% among the Cottage Grove and Decatur employees, respectively.
Serum PFOA concentrations for the 506 employees ranged from 0.007 to 92.03 μg/ml [arithmetic mean 2.21 μg/ml (95% confidence interval 1.66–2.77), median 1.10 μg/ml]. PFOA results are categorized by deciles in Table 3. Mean PFOA decile concentrations ranged from the lowest decile of 0.06 μg/ml (range 0.007–0.13 μg/ml) to the highest decile of 12.15 μg/ml (range 3.71–92.03 μg/ml) with corresponding median values of 0.06 and 4.94 μg/ml, respectively.
The distributions of demographic factors by PFOA decile are presented in Table 4. There were higher percentages of Antwerp employees in the first three deciles and lower percentages in the highest two deciles (9 and 10). Likewise, there were lower percentages of Decatur employees in the first three deciles and higher percentages in the upper deciles (6–10), in particular decile 9. Because of these disparities, mean BMI values were greater in the upper deciles and alcohol consumption was lower, reflecting the demographic differences seen across the three facilities in Tables 1 and 2.
Presented in Figs. 1 and 2 are scatterplots of the natural logs of the blood lipids and PFOA. Pearson correlation coefficients and P values (in parentheses) between PFOA and the lipid parameters were: cholesterol (r = 0.05, P = 0.32), LDL (r = 0.006, P = 0.90), HDL (r = −0.17, P < 0.0001), and triglycerides (r = 0.21, P < 0.0001). Unadjusted and adjusted coefficients for PFOA when regressed with total cholesterol, LDL, HDL, and triglycerides are presented in Table 5. Analyses are also presented for each location in Table 5. PFOA was not a statistically significant coefficient in the regression models for total cholesterol or LDL. In the regression model for HDL that contained all three locations, the adjusted PFOA coefficient was statistically significant (P = 0.01) but only explained 1% of the variance in the model. Separate models analyzed for each of the three locations showed no statistically significant findings between PFOA and HDL. The model for triglycerides for the combined three locations indicated a statistically significant positive coefficient (P < 0.0001) for PFOA which explained approximately 4% of the variance of the response variable. Stratified by location showed Antwerp with a statistically significant positive PFOA coefficient (P < 0.0004) and Decatur had a marginally positive coefficient for PFOA (P = 0.07). No statistically significant coefficient for PFOA (P = 0.38) was found with triglycerides for the Cottage Grove location.
Presented in Table 6 are the mean and 95% confidence intervals (CI) values for cholesterol, LDL, HDL, and triglycerides by PFOA deciles, adjusted for age, BMI, and alcohol. Mean serum triglyceride levels were highest in the upper three PFOA deciles.
Table 7 presents adjusted odds ratios and 95% confidence intervals by reference range cutoff points listed in Table 2, using the lowest PFOA decile as the reference. Serum PFOA concentrations were not associated, positively or negatively, with cholesterol or LDL. For HDL < 40 mg/dl, the non-adjusted odds ratio for the highest decile was 3.0 (95% CI 1.2–7.5). Adjusted for age, BMI and alcohol, the highest decile odds ratio became 2.6 (95% CI 1.0–6.8) (Table 5). Adjusted also for location, this odds ratio became 1.8 (95% CI 0.7–4.8). Adjusted odds ratios for triglyceride levels ≥150 mg/dl were also highest for PFOA deciles 8–10 as seen with adjusted mean triglyceride values reported in Table 7.
Presented in Figs. 3 and 4 are scatterplots of natural logs of hepatic clinical chemistries by PFOA. Pearson correlation coefficients and P values (in parentheses) between PFOA and the hepatic parameters were: alkaline phosphatase (r = 0.08, P = 0.06), AST (r = −0.01 P = 0.83), ALT (r = 0.005, P < 0.005), and GGT (r = 0.02, P < 0.02). Analyses presented in Table 8 of the regression models showed marginal statistically significant coefficients for PFOA when adjusted for age, BMI, and alcohol for ALT (P = 0.06) and GGT (P = 0.05) but not when adjusted for age, triglycerides, and alcohol for ALT (P = 0.40) and GGT (P = 0.55). Total bilirubin was statistically significantly negatively associated with PFOA regardless of covariates used. Stratified by location, Decatur had marginally statistically significant positive coefficients, regardless of covariates adjusted, ranging between 0.01 < P < 0.07 for alkaline phosphatase, ALT, GGT, and total bilirubin. The amount of variance of the hepatic response variables explained by PFOA in these models was minimal ranging from <1 to 3%. No statistically significant PFOA coefficients for the hepatic enzymes were observed in either the Antwerp or Cottage Grove regression models.
No discernable trends in adjusted mean hepatic enzyme values were apparent when analyzed by deciles (Table 9). There were no statistically significant odds ratios (non-adjusted or adjusted) for the reference points ALT ≥ 40 IU/l or GGT ≥ 40 IU/l when compared to decile 1 (Table 10). Odds ratios for alkaline phosphatase, AST, and total bilirubin are not shown because of the failure of the logistic models to converge because of the very few data points that were out-of-reference range (Table 2) for these clinical parameters.
Presented in Figs. 5 and 6 are scatterplots of natural logs of thyroid hormones by PFOA. Pearson correlation coefficients and P values (in parentheses) between PFOA and the thyroid hormones were: TSH (r = 0.08, P = 0.07), T4 (r = −0.04, P = 0.32), free T4 (r = −0.14, P < 0.002), and T3 (r = 0.07, P = 0.11). For all locations combined, there were no statistically significant adjusted coefficients for PFOA in the models except for Free T4 (negative coefficient for PFOA) and T3 (positive coefficient for PFOA) (Table 11). However, the full models only explained 5 and 2% of the variance of free T4 and T3, respectively. The thyroid results were considered not clinically relevant as results from these models were well within normal reference ranges for the four thyroid parameters when serum PFOA concentrations were predicted in a model to range between 0.005 and 100 μg/ml (Table 12). Presented in Table 13 are the mean thyroid hormone-related values adjusted for age, BMI and alcohol. The mean TSH value in the fourth decile of Table 13 is influenced by one subject whose TSH value was 65.3 μIU/ml (see overall results in Table 1) who was not diagnosed at the time as hypothyroid. If removed, the mean of the fourth decile became 2.15 μIU/ml and the decile statistically significant differences with this fourth decile in Table 13 disappear. The adjusted mean for the highest decile for free T4 was statistically significantly lower than that of the first decile. There were no statistically significant differences between decile-adjusted means for T3 in Table 13. Because so few thyroid values were out-of-reference range (Table 2), the findings from the logistic analyses are not presented because of the models’ lack of convergence.
PFOA was not associated with the metabolic syndrome. Age-adjusted odds ratios (95% CI in parentheses) for the 6th, 7th, 8th, 9th and 10th PFOA deciles were 1.0 (0.3–3.5), 0.5 (0.1–2.0), 0.9 (0.3–3.0), 1.1 (0.3–3.6) and 1.0 (0.3–3.6), respectively.
Other analyses included those subjects (n = 46) who self-reported cholesterol lowering medication usage. These 46 subjects, compared to the 506 non-prescribed subjects, had comparable mean PFOA concentrations (1.98 μg/ml vs. 2.21 μg/ml) but were statistically significantly older (49 vs. 40) and had higher mean BMI (28.8 vs. 27.4), serum glucose (103 vs. 91), triglycerides (226 vs. 159), and several liver enzyme results (alkaline phosphatase 73 vs. 66, ALT 36 vs. 30, GGT 36 vs. 28). Cholesterol (221 vs. 214), LDL (134 vs. 136), and HDL (47 vs. 49) were not statistically significantly different between the two groups. No significant differences were observed with thyroid hormones. Twenty percent of these 46 subjects were categorized as having the metabolic syndrome compared to 7% of those not prescribed cholesterol-lowering medication. Not unexpectedly based on the results already presented, a greater percentage of those prescribed cholesterol-lowering medications were Cottage Grove and Decatur employees (79%) than those not prescribed medications (61%). Analyses with the clinical chemistries were similar whether they excluded or included these 46 employees who self-reported cholesterol lowering medications (data not shown).