Womens Occupations and Risks from Chemicals (WORC) Robert - PowerPoint PPT Presentation

Women’s Occupations and Risks from Chemicals (WORC) Robert Harrison, MD and Peggy Reynolds, PhD California Depart ment of Public Healt h and Cancer Prevent ion Inst it ut e of California California Breast Cancer Research Council Meet ing – March 9, 2018 Funded by CBCRP #21ZB0901

Background  Funded by California Breast Cancer Research Program (CBCRP , Grant#21ZB-0901; Co-PIs=Robert Harrison, Peggy Reynolds)  Response to CBCRP’s California Breast Cancer Prevention Initiative (CBCPI) RFP on “ Occupat ional Chemical Exposures in Calif ornia and Breast Cancer Risk”  5-year proj ect (2016-2020), 3 phases  Overarching obj ective: advance our understanding of the degree to which workplace chemical exposures may increase breast cancer risk among California working women 2

Phase I (Y ear 1)  Identify where women are employed in California.  Identify workplace chemicals of concern (CoC) for breast cancer risk.  Identify the overlap between where women are employed in California and workplace exposures to groupings of CoC for breast cancer risk. 3

Phase 2 (Y ear 2)  Identify key available data and any gaps in occupational chemical exposures for women working in California.  Create a database and data visualization tool of women’s occupational exposures to known and suspected mammary gland carcinogens, mammary gland toxicants, and/ or endocrine disrupting chemicals in California. 4

Phase 3 (Y ears 3-5) Conduct a more in-depth pilot investigation into one or more key industries in California that appear to pose the greatest breast cancer risk to women, based on the findings of Phase 2. 5

Community Engagement: WORC Advisory Commit t ee Knowledge Gap

WORC Research S taff • Robert Harrison (Co-PI, OHB/ CDPH) • Peggy Reynolds (Co-PI, CPIC) • S usan Hurley (Proj ect Manager/ Epidemiologist, CPIC) • S tella Beckman (Environmental Health S cientist, CPIC) • Jackie Chan (Industrial Hygienist, OHB/ CDPH) • Matt Frederick (Data S pecialist, OHB/ CDPH) • Paula Johnson (Epidemiologist, OHB/ CDPH) • Minhthu Le (Administrative Assistant, CPIC) • Thu Quach (Consultant/ Epidemiologist, CPIC/ Asian Health S ervices) • Marcel Reynolds (Communications S pecialist, OHB/ CDPH) • Elana S ilver (Epidemiologist/ Data Visualization Liaison, Consultant) • Julie Von Behren (Epidemiologist, CPIC) • Justine Weinberg (Industrial Hygienist, OHB/ CDPH) • Carmela Lomonaco/ Judy Thai/ S enaida Poole (CBCRP) 7

Phase I Methods – where women work Reviewed variety of data sources for California workforce  American Community S urvey (ACS ) data from US Census identified as most complete S ummarized and compiled data on ~ 8 million women employed in CA  For all industries and occupations (~ 500 occupations)  Includes sociodemographic characterist ics (age, race/ ethnicity, education, income, citizenship, language, presence/ age of children in home)  Based on compilation of 2010 ACS data from US Census  Included approximate estimates of informal workforce derived by modeling data 8

Phase I Results – where women work California Women: Top Ten Largest Occupations Number Occupation of Women Secretaries & administrative assistants 310,470 Cashiers 282,052 Elementary & middle school teachers 252,404 Registered nurses 243,053 Retails salespersons 220,713 Personal care aides 205,666 Maids and housekeeping cleaners 197,778 Customer service representatives 173,840 Managers 157,700 Accountants and auditors 154,899 Source: ACS 2010-2014 US Census data. 9

Phase I Results – where women work 10

Methods: Estimating Informal Workforce  Not documented in existing data resources  Methods to generate estimates using existing data resources • S ome researchers have developed methods for limited geographic areas but these are: - Quite variable depending on assumptions - Not well-suited to statewide estimations • Adapting these methods, we generated two estimates of informal workers: - estimate X – based on self-employed in ACS data - estimate Y - based on non-citizens in ACS data  Input from Advisory Committee  Given these limitations, caution for interpretation from the Data Visualization Tool 11

Phase I Results – Informal Workforce 12

Chemical Concerns for Occupations with Informal Employment from WORC AC Workforce Chemical Concerns Domestic Workers Chemicals in cleaning products Restaurant Workers Disinfectants, indoor air pollutants (e.g. P AHs) Agriculture Workers Pesticides Makeup Artists and Hairdressers Chemicals in cosmetics Janitors and Custodians Chemicals in cleaning products Day Laborers Formaldehyde, wood preservatives, paints, pesticides Garment Workers Flame retardants and fabric preservatives Artists S olvents, paints S treet Vendors Air pollutants from traffic 13

Phase I – Chemicals of Concern  Evaluated multiple data resources, final list based primarily on: • S ilent S pring Institute’s list of mammary gland carcinogens and mammary gland toxicants • TEDX list of endocrine disruptors  Created a list of 1,000+ chemicals-of-concern (CoC) for breast cancer • Includes indicators for mammary gland carcinogens, endocrine disruptors, mammary gland toxicants, and high production volume chemicals • Categorized in 27 groups based on chemical properties and/ or usage  Constructed another dataset summarizing workplace sampling data (OS HA) – data sparse by chemical and industry 14

Phase I Results: Chemicals-of-Concern Chemicals-of-concern (n=1,082) in 27 categories Category # Chemicals Alkyphenols/ethoxylates 15 Antimicrobials 32 Biogenic substances 54 Combustion products 62 Dioxins 121 Dyes 34 Flame retardants 52 Food constituents and additives 49 Fragrance ingredients 62 Household products 28 Industrial chemicals 172 Metabolites and degradates 20 Metals 27 Natural hormones 5 Other 6 Parabens 12 Perfluorinated compounds 13 Personal care products 74 Pesticides 308 Pharmaceuticals - antineoplastic 20 Pharmaceuticals - other 57 Phthalates 16 Plastics 61 Research chemicals 58 Solvents 31 Synthetic hormones 13 Unclassified 70 15

Phase I – Estimating Chemical Exposures  Created Job Exposure Matrix (JEM) to identify overlap of occupations with exposures to Chemicals-of-Concern for: • 145 occupations (representing ~ 85% of CA female workforce) • 9 broad occupational groups identified by our AC as likely to have high proportion of informal workers (domestic workers, restaurant workers, agricultural workers, make-up artists and hairdressers, day laborers, garment workers, artists, street vendors)  Based on expert review by two industrial hygienists • Tie-breaking review by Dr. Harrison 16

Progress: Phase II (Data Visualization Tool)  Obj ective  to create an interactive online tool to: • Characterize the California female workforce: o By occupation, race/ ethnicity, age group • S ummarize groups of chemicals of concern • Identify potential chemical exposures by occupation • Highlight data gaps • Be useful to multiple stakeholder groups  Contract with external vendor  Will be hosted on CBCRP website  Work is in progress  goal for completion in S pring 2018 NOTE: still in draft form! 17

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Phase II: Data Gaps – where women work  Capturing Informal Workforce • Low income, limited literacy and English proficiency • More likely to be exposed to workplace chemicals (? ) • More vulnerable to health effects associated with exposures (? )  S OC codes used by US Census – heterogeneous mix of j obs, difficult to estimate probabilities of chemical exposures by industry/ occupation  Lack of information on occupational history – limits ability to characterize exposures by industry/ occupation • Chronic exposures • Exposures during windows of susceptibility 19

Phase II: Data Gaps – workplace chemicals Lack of systematically-collected quantitative chemical exposure data: • in contemporary workplaces that represent current patterns of employment • for occupations that employ many women, especially in the informal sectors • include exposure assessments that consider specific j obs (not j ust broad occupational groups), in conj unction with industry • data on chemicals-of-concern for breast cancer, particularly endocrine disruptors 20

Phase II: Data Gaps – other  Incomplete and inaccurate information on occupation and industry in cancer surveillance databases (e.g. CCR, S EER)  Dearth of simultaneously-collected information on cancer and occupation/ industry in national and statewide population surveys  Limited biomonitoring data from nationally-representative workforces 21

Recommendations to fill gaps – research  Exploratory analyses that link existing cancer outcome data, occupation/ industry data, sociodemographic data, national and statewide survey data, and biomonitoring data  Expand and improve WORC-JEM • S pecific chemicals, rather than categories • More detailed targeted occupations/ industries (rather than ACS -defined)  Apply JEM approach to identify & prioritize occupations/ industries for targeted exposure surveillance and/ or biomonitoring 22