To evaluate the relationship between urinary bisphenol A (BPA) levels and measures of adiposity and chronic disease risk factors for a nationally representative US pediatric sample.
We used the NHANES 2003–2010 to evaluate cross-sectional associations between urinary BPA and multiple measures of adiposity, cholesterol, insulin, and glucose for children aged 6 to 18 years, adjusting for relevant covariates (eg, demographics, urine creatinine, tobacco exposure, and soda consumption).
We found a higher odds of obesity (BMI ≥95th percentile) with increasing quartiles of BPA for quartiles 2 vs 1 (odds ratio [OR] 1.74, 95% confidence interval [CI] 1.17–2.60, P = .008), 3 vs 1 (OR 1.64, 95% CI 1.09–2.47, P = .02), and 4 vs 1 (OR 2.01, 95% CI 1.36–2.98, P = .001). We also found a higher odds of having an abnormal waist circumference–to–height ratio (quartiles 2 vs 1 [OR 1.37, 95% CI 0.98–1.93, P = .07], 3 vs 1 [OR 1.41, 95% CI 1.07–1.87, P = .02], and 4 vs 1 [OR 1.55, 95% CI 1.12–2.15, P = .01]). We did not find significant associations of BPA with any other chronic disease risk factors.
Higher levels of urinary BPA were associated with a higher odds of obesity (BMI >95%) and abnormal waist circumference–to–height ratio. Longitudinal analyses are needed to elucidate temporal relationships between BPA exposure and the development of obesity and chronic disease risk factors in children.
Comments
Continuous versus dichotomized outcomes: the case of BPA and chronic disease risk factors
We wish to thank Eng and colleagues for their thoughtful publication on the association between bisphenol A (BPA) and childhood chronic disease risk factors.1 This is an important contribution given the potential lifelong impact of chronic disease among children, yet the relative lack of information regarding the potential influence of environmental factors on childhood chronic disease.
We also have some experience using United States National Health and Nutrition Examination Survey (NHANES) data to explore this topic: our results are both similar2 and slightly different (Table) to Eng and colleagues. Although Eng and colleagues report no association between urinary BPA and cardiovascular and diabetic risk factors, our analyses of 12-18 year olds from NHANES 2003-2010 found associations of BPA with C-reactive protein (CRP), triglycerides and high density lipoprotein (HDL), as well as with some other factors not included by Eng et al: apolipoprotein (ApoB), lactate dehydrogenase (LDH) and alkaline phosphatase (AKP) (Table). Notably, the association with CRP was attenuated to borderline statistical significance when including 6-18 year olds (the age range used by Eng et al.). We also found no association between the other chronic disease risk factors examined by Eng and colleagues.
It is likely that these differences result from a different statistical strategy. Eng et al. used logistic regression models and defined dichotomous outcomes using previously established cutoffs; however, the effect of BPA on chronic disease risk factors may not be large enough to exceed these thresholds. In contrast, our analyses used linear regression models, examining outcomes as continuous variables, which may identify smaller effects of BPA.
There is some precedence for our results: in a similar study among adults Lang and colleagues also found a significant cross-sectional association of BPA with CRP (although not in the final model), LDH and AKP, using a linear model.3 We believe the results from both the logistic and linear models have important messages. Taken together, they suggest that while the effects of BPA may not be sufficiently large to result in a clinically-defined risk factor for chronic disease during childhood, more subtle changes may yet be occurring which could impact future cardiovascular health.
Even small changes may have clinical and public health relevance. Increases in risk factors on a continuous, graded scale have previously shown to impact cardiovascular health.4 Additionally, it is important to remember that children exposed to BPA are also exposed to other chronic disease risk factors. In this context, the additional risk provided by BPA could be an important factor in increasing a child's overall chronic disease risk. For these reasons we feel that is important to consider the impact of BPA's potential impact on chronic disease risk on continuous as well as dichotomized scales.
1. Eng DS, Lee JM, Gebremariam A, Meeker JD, Peterson K, Padmanabhan V: Bisphenol A and Chronic Disease Risk Factors in US Children. Pediatrics 2013. doi: 10.1542/peds.2013-0106.
2. Wells EM, Jackson LW, Koontz MB: Association between bisphenol A and waist-to-height ratio among children: National Health and Nutrition Examination Survey, 2003-2010. Ann Epidemiol 2013. doi: 10.1016/j.annepidem.2013.06.002.
3. Lang IA, Galloway TS, Scarlett A, Henley WE, Depledge M, Wallace RB, Melzer D: Association of urinary bisphenol A concentration with medical disorders and laboratory abnormalities in adults. JAMA 2008, 300(11):1303-1310.
4. Stamler J, Daviglus ML, Garside DB, Dyer AR, Greenland P, Neaton JD: Relationship of baseline serum cholesterol levels in 3 large cohorts of younger men to long-term coronary, cardiovascular, and all-cause mortality and to longevity. JAMA 2000, 284(3):311-318.
BPA = bisphenol A; Q1 = first quartile; Q2 = second quartile; Q3 = third quartile; Q4 = fourth quartile; LOD = limit of detection; CRP = C-reactive protein; TRIG = triglycerides; HDL = high density lipoprotein; ApoB=apolipoprotein B; LDH = lactate dehydrogenase; AKP = alkaline phosphatase. The analysis includes 12-18 year olds in the United States National Health and Nutrition Examination Survey 2003-2010 with complete information available; individuals were excluded due to pregnancy, self-report of diabetes, or taking diabetic medications/insulin. Values are change or percent change and 95% confidence interval, using appropriate survey weights and analysis methods. Bold type indicates p < 0.05. TRIG, ApoB results include only those fasting; data from 2003-4 not available for ApoB. Models control for urinary creatinine, child age, sex, race/ethnicity, head of household educational level, and smoking (based on serum cotinine). CRP, TRIG, LDH and AKP were natural log transformed for analyses, therefore results are presented as percent change instead of change.
Conflict of Interest:
None declared