Socio-Economic Status and Health: Evaluation of Human Biomonitored Chemical Exposure to Per- and Polyfluorinated Substances across Status

Abstract

Research on the environment, health, and well-being nexus (EHWB) is shifting from a silo toward a systemic approach that includes the socio-economic context. To disentangle further the complex interplay between the socio-exposome and internal chemical exposure, we performed a meta-analysis of human biomonitoring (HBM) studies with internal exposure data on per-and polyfluoroalkyl substances (PFASs) and detailed information on risk factors, including descriptors of socio-economic status (SES) of the study population. PFASs are persistent in nature, and some have endocrine-disrupting properties. Individual studies have shown that HBM biomarker concentrations of PFASs generally increase with SES indicators, e.g., for income. Based on a meta-analysis (five studies) of the associations between PFASs and SES indicators, the magnitude of the association could be estimated. For the SES indicator income, changes in income were expressed by a factor change, which was corrected by the Gini coefficient to take into account the differences in income categories between studies, and the income range between countries. For the SES indicator education, we had to conclude that descriptors (<college, x years of study, etc.) differed too widely between studies to perform a meta-analysis. Therefore, the use of the uniform ISCED (International Standard Classification of Education) is recommended in future studies. The meta-analysis showed that a higher income is associated with a higher internal exposure to PFASs (PFOS or perfluorooctanesulfonic acid, PFOA or perfluorooctanoic acid, PFNA or perfluorononanoic acid, PFHxS or perfluorohexane sulfonate). This is opposite to the environmental justice hypothesis, referring to an inequitable distribution of detrimental environmental effects toward poor and minority communities by a practice or policy. With a doubling of the income, internal exposure increased on average by 10%⁻14%. Possible explanations for this difference are given, e.g., underlying differences in diet. However, other sources can also contribute, and the exact causes of SES-related differences in PFAS concentrations remain unclear. Studies are needed that include social descriptors together with lifestyle and dietary information as explanatory variables for internal chemical exposure levels. This will help clarify the underlying factors that link SES with inequity to environmental exposures, and will raise awareness and knowledge to strengthen the capacities of people and communities to advocate chemical exposure reduction in order to reduce this health inequity.

Keywords: HBM; HBM4EU; PFAS; SES; education; health inequity; human biomonitoring; income; socio-economic status.

Figure 1

Interaction between health inequalities, environmental exposure inequality, different biological and physiological susceptibility and social vulnerability. Figure based on study of Morello-Frosch et al. [22] and Frumkin [23].

Figure 2

Association between factor change in household income/Gini coefficient and percent change in adult PFAS concentrations in plasma or serum (a: PFOS, b: PFOA, c: PFNA and d: PFHxS). Factor change calculated from uniform distribution of household incomes over three to four income categories with lowest income category as denominator. Gini coefficient retrieved from the Organization for Economic Cooperation and Development (OECD) (scale 0–1; USA: 0.40, Belgium: 0.27, Norway: 0.25). A change on the X-axis of 10 for the US study of Kato et al. [57] means an increase in income factor of 10 × 0.40 = 4, which corresponds with an increase in percentage in PFOS concentration of 37%. Error bars indicate 95% CI. The straight line is based on a weighted least squares (WLS) with weights equal to the inverse of the standard deviation on the percent changes in PFAS concentrations and intersection with the X-axis equal to (2.5,0). Slopes were 3.5 (p < 0.001) for PFOS, 2.7 for PFOA (p < 0.001), 3.0 for PFNA (0.01 > p > 0.001) and 4.1 for PFHxS (0.05 > p > 0.01).