Reeder Sams Senior Science Advisor National Center for Environmental Assessment (NCEA) Office of Research and Development (ORD) U.S. Environmental Protection Agency Evaluating Susceptible Populations: Perspectives from Conducting Human Health Risk Assessments Office of Research and Development National Center for Environmental Assessment, Research Triangle Park, NC December 16, 2014 Disclaimer: The views expressed are those of the authors and do not necessarily reflect the views or policies of the U.S. EPA.

1 Presentation Outline Background / Context for Presentation Defining Susceptible Populations Qualitative Consideration of Susceptible Populations

Integrated Science Assessments (ISAs) Particulate Matter (PM), Ozone (O3), Oxides of Nitrogen (NO2), Sulfur Oxides (SO2), Carbon Monoxide (CO), and Lead (Pb) Purpose: critically evaluate and integrate evidence from multiple disciplines on health and welfare effects Utilizes principles of systematic review

Inorganic Arsenic IRIS Toxicological Review of Inorganic Arsenic Purpose: critically evaluate and integrate evidence for cancer and noncancer health effects associated with exposure to inorganic arsenic and estimate potential risk Methods: Implementing systematic review approaches 3

National Research Council (NRC) publications on risk assessment –2009: Science and Decisions – the “Silver Book” –2011: Review of the Formaldehyde Assessment – Roadmap for Revision –2013 / 2014:Critical Aspects of EPA’s IRIS Assessment of Inorganic Arsenic (An Interim Report) –2014: Review of EPA’s Integrated Risk Information System (IRIS) Process Recent NRC Recommendations for Risk Assessment at EPA … all included suggestions for considering susceptible populations 4

Inorganic Arsenic: Assessment Development Plan (ADP) Provided EPA’s conceptual model and analysis plan to guide the development of the assessment Submitted to NRC (May 2013) and a revised version in April 2014 – preliminary_draft_materials.pdf Some of the key components highlighted in this presentation 5

6 Documents clearly reflect previous NRC recommendations and outline an improved approach Materials reflect input collected from program and regional offices and public stakeholders NRC supported approach for causal determination and susceptibility framework Provided specific recommendations for dose-response NRC agreed with proposal to use probabilistic approaches to consider uncertainty and variability (including for susceptible populations) Feedback from the NRC 2013 Interim Report-Inorganic Arsenic

7 Defining Susceptible Populations DefinitionReference Susceptible: Predisposed to develop a noninfectious disease Vulnerable: Capable of being hurt: susceptible to injury or disease. Merriam-Webster (2009) Susceptible: Greater likelihood of an adverse outcome given a specific exposure, in comparison with the general population. Includes both host and environmental factors (e.g., genetics, diet, physiologic state, age, gender, social, economic, and geographic attributes). Vulnerable: Periods during an individual’s life when they are more susceptible to environmental exposures. American Lung Association (2001) Susceptible: Intrinsic (e.g., age, gender, pre-existing disease [e.g., asthma] and genetics) and extrinsic (previous exposure and nutritional status) factors. Kleeberger and Ohtsuka (2005) Susceptible: Characteristics that contribute to increased risk of PM-related health effects (e.g., genetics, pre-existing disease, age, gender, race, socioeconomic status, healthcare availability, educational attainment, and housing characteristics). Pope and Dockery (2006)

8 Evaluation of the Scientific Evidence Integration of evidence across disciplines Epidemiology, toxicology, controlled human exposure When possible, bringing in dosimetry, mode of action, and exposure science Focus on specific study designs: Epidemiology: stratified analyses (e.g., male vs. female, 65, etc) Toxicological: e.g., animal models of disease and aging, genetic predisposition Controlled human exposure: e.g., underlying disease, age, genetic polymorphisms

9 Evaluation of the Scientific Evidence Identification of factors that potentially result in increased (or decreased risk) is comprised of: Intrinsic factors (i.e., biological factors) Extrinsic factors (i.e., non-biological factors) Increased dose Differential exposure

10 Defining factors that may potentially lead to increased risk All-encompassing term (i.e., susceptible?) Sacks et al. Particulate Matter-Induced Health Effects: Who Is Susceptible? Environ Health Perspect 119: (2011). Vinikoor-Imler et al. Evaluating Potential Response-Modifying Factors for Associations… Environ Health Perspect 119: (2014). Continued evolution of how we define these populations At-risk

11 At Risk Framework Source: U.S. EPA. Integrated Science Assessment for Ozone and Related Photochemical Oxidants (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-10/076F, …substantial, consistent evidence …insufficient quantity, quality, consistency and/or statistical power …some inconsistency

12 Genetics Epidemiologic studies: evidence that polymorphisms in specific genes associated with anti-oxidant function (i.e., glutathione S-transferase [GST] genes) lead to O 3 -induced increases in respiratory symptoms and decreases in lung function Controlled human exposure studies: providing coherence for the same effects observed in epidemiologic studies Toxicological studies: mice with KOs of genes in the GST family had O 3 -induced inflammation and airways hyperreactivity providing biological plausibility Example from the Ozone ISA: Adequate Evidence

13 Source: U.S. EPA. Integrated Science Assessment for Ozone and Related Photochemical Oxidants (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-10/076F, Summary of Evidence for Potential Increased Risk of Ozone-Induced Health Effects Evidence ClassificationPotential At Risk Factor Adequate EvidenceGenetic factors (Section 8.1) Asthma (Section 8.2.2) Children (Section ) Older Adults (Section ) Diet (Section 8.4.1) Outdoor workers (Section 8.4.4) Suggestive EvidenceSex (Sections 8.3.2) Socioeconomic Status (SES) (Section 8.3.3) Obesity (Section 8.4.2) Inadequate EvidenceInfluenza/Infection (Section 8.2.1) COPD (Section 8.2.3) CVD (Section 8.2.4) Diabetes (Section 8.2.5) Hyperthyroidism (Section 8.2.6) Race/ethnicity (Section 8.3.4) Smoking (Section 8.4.3) Air conditioning use (Section 8.4.5) Evidence of No Effect---

14 Example from the Lead (Pb) ISA: Suggestive Evidence Stress Epidemiologic studies: a few studies demonstrated increased Pb-induced health effects among individuals with higher stress Toxicological studies: animal models of stress (viral and maternal) provide biological plausibility for greater effects among individuals with greater stress levels Evidence for coherence was limited by the small number of studies with varied measures of stress and different Pb- induced outcomes.

15 Source: Table 5-5, U.S. EPA. Integrated Science Assessment for Lead (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-10/075F, Evidence ClassificationPotential At Risk Factor Adequate EvidenceChildhood (Sections 5.2.1, 5.3.1) Race/Ethnicity (Sections 5.2.3, 5.3.7) Proximity to Pb Sources (Section 5.2.5) Residential Factors (Section 5.2.6) Nutrition (Section ) Suggestive EvidenceOlder Adulthood (Sections 5.2.1, 5.3.1) Sex (Sections 5.2.2, 5.3.2) Genetics (Section 5.3.3) Pre-existing Disease (Section 5.3.4) Socioeconomic Status (SES) (Section 5.2.4, 5.3.6) Stress (Section ) Other Metals (Section ) Inadequate EvidenceSmoking Status (Section 5.3.5) Body Mass Index (BMI) (Section 5.3.8) Alcohol Consumption (Section 5.3.9) Maternal Self-Esteem (Section ) Cognitive Reserve (Section ) Evidence of No Effect--- Summary of Evidence for Potential Increased Risk of Lead (Pb)-Induced Health Effects

16 Conclusions Use of At Risk Framework provides clear communication of scientific evidence o Reduces speculation  Data availability Unique At Risk factors will likely exist for specific pollutants / chemicals Conducting an assessment for an At Risk (susceptible population) would be dependent on a quantitative risk estimate comparison

17 Acknowledgements John Cowden Jason Sacks Janice Lee John Vandenberg Geniece Lehmann Debra Walsh