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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" xml:lang="en" article-type="research-article"><?properties manuscript?><processing-meta base-tagset="archiving" mathml-version="3.0" table-model="xhtml" tagset-family="jats"><restricted-by>pmc</restricted-by></processing-meta><front><journal-meta><journal-id journal-id-type="nlm-journal-id">9918470988406676</journal-id><journal-id journal-id-type="pubmed-jr-id">51990</journal-id><journal-id journal-id-type="nlm-ta">Community Sci</journal-id><journal-id journal-id-type="iso-abbrev">Community Sci</journal-id><journal-title-group><journal-title>Community science</journal-title></journal-title-group><issn pub-type="epub">2692-9430</issn></journal-meta><article-meta><article-id pub-id-type="pmid">39494040</article-id><article-id pub-id-type="pmc">11525921</article-id><article-id pub-id-type="doi">10.1029/2024csj000088</article-id><article-id pub-id-type="manuscript">NIHMS2028198</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Environmental Health Assessment by Local Environmental Justice Experts for Evidence-based Decision-making in an Agricultural Community of Northern California</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Aranda</surname><given-names>A. A.</given-names></name><xref rid="A1" ref-type="aff">1</xref><xref rid="A2" ref-type="aff">2</xref><xref rid="A3" ref-type="aff">3</xref><xref rid="FN1" ref-type="author-notes">*</xref></contrib><contrib contrib-type="author"><name><surname>Kelty</surname><given-names>J. S.</given-names></name><xref rid="A1" ref-type="aff">1</xref><xref rid="A4" ref-type="aff">4</xref><xref rid="FN1" ref-type="author-notes">*</xref></contrib><contrib contrib-type="author"><name><surname>Manukian</surname><given-names>S.</given-names></name><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Pardo</surname><given-names>E.</given-names></name><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Jabbari</surname><given-names>K.</given-names></name><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Schmidt</surname><given-names>R. J.</given-names></name><xref rid="A5" ref-type="aff">5</xref></contrib><contrib contrib-type="author"><name><surname>Dabritz</surname><given-names>H. A.</given-names></name><xref rid="A6" ref-type="aff">6</xref></contrib><contrib contrib-type="author"><name><surname>London</surname><given-names>J. K.</given-names></name><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Van Winkle</surname><given-names>L. S.</given-names></name><xref rid="A4" ref-type="aff">4</xref></contrib><contrib contrib-type="author"><name><surname>Deeb-Sossa</surname><given-names>N.</given-names></name><xref rid="A1" ref-type="aff">1</xref><xref rid="A3" ref-type="aff">3</xref></contrib><contrib contrib-type="author"><collab>Knights Landing Promotoras</collab><xref rid="A1" ref-type="aff">1</xref></contrib></contrib-group><aff id="A1"><label>1</label>UC Davis Knights Landing One Health Center</aff><aff id="A2"><label>2</label>UC Davis Human Ecology Department</aff><aff id="A3"><label>3</label>UC Davis Chicana/o Studies Department</aff><aff id="A4"><label>4</label>UC Davis School of Veterinary Medicine, Department of Anatomy, Physiology and Cell Biology and Center for Health and the Environment</aff><aff id="A5"><label>5</label>UC Davis Department of Public Health Sciences</aff><aff id="A6"><label>6</label>Yolo County Health and Human Services Agency</aff><author-notes><corresp id="CR1">Corresponding author: Jacklyn Kelty (<email>jkelty@ucdavis.edu</email>)</corresp><fn fn-type="equal" id="FN1"><label>*</label><p id="P1">Equally contributed</p></fn></author-notes><pub-date pub-type="nihms-submitted"><day>15</day><month>10</month><year>2024</year></pub-date><pub-date pub-type="ppub"><month>9</month><year>2024</year></pub-date><pub-date pub-type="epub"><day>13</day><month>9</month><year>2024</year></pub-date><pub-date pub-type="pmc-release"><day>13</day><month>9</month><year>2025</year></pub-date><volume>3</volume><issue>3</issue><elocation-id>e2024CSJ000088</elocation-id><abstract id="ABS1"><p id="P2">Environmental justice research driven by academics and policymakers often overlooks the valuable insights and leadership of the communities most impacted by environmental hazards. When institution-led research approaches are employed, inadequate community ownership and limited institutional accountability hinder the effectiveness of environmental public health interventions. In contrast, a community-owned and -managed approach to environmental justice research can guide community members in developing evidence-based interventions. This paper outlines a community-led environmental health assessment survey (sample= 100) and resulting community actions over six years (2017 to 2023) in a Northern California farmworker community with a perceived high prevalence of cancer and exposure to environmental hazards in households, neighborhoods, and job sites. Local resident experts in Knights Landing, CA, documented community risk factors and exposures in collaboration with interdisciplinary undergraduate and graduate student-researchers. The survey instrument focused on environmental hazards identified by local resident experts including vehicular and agricultural pollution, occupational pesticide contact, and sun exposure. Survey findings highlighted the need for targeted interventions to reduce environmental health risks, such as academic outreach programs, county investments in public services, and community-led mutual aid initiatives. Despite academic reservations about our non-random sampling method and data collection by local resident experts, our project sparked substantial actions and investments with minimal personnel and financial resources. Local leaders working with student-researchers developed more effective environmental public health interventions through a community-owned and -managed approach that went beyond the efforts of local regulatory and research institutions.</p></abstract><abstract id="ABS2" abstract-type="summary"><title>Plain Language Summary</title><p id="P3">Agricultural communities in California experience environmental injustice related to toxic exposures in environmental, household, and occupational settings. Environmental justice movements seek to ensure a clean and healthy environment for all communities by mitigating these toxic exposures and amplifying community voices to remove social, economic, and political barriers to healthy environments. This research project started in 2016 when Knights Landing residents revealed their suspicions that environmental carcinogens were potentially causing a high prevalence of cancer in their neighborhood. The community leaders and university researchers partnered to conduct a community survey. The survey results were used by community leaders to establish the following action priorities: household pesticide exposure, addictive substance misuse, access to cancer screening, occupational safety, housing quality, and neighborhood isolation from health services. Feasible and prompt actions were implemented from 2017 to 2023 within the limited resources of this unincorporated community. Communities can initiate a swift, customized, representative environmental health assessment to serve as a starting point when seeking institutional support, funding, or larger research initiatives. Our approach may serve as a model for environmental justice researchers striving to promptly reduce environmental health risks in marginalized communities.</p></abstract><kwd-group><kwd>Environmental justice</kwd><kwd>agricultural</kwd><kwd>rural</kwd><kwd>community health assessment survey</kwd><kwd>community-based participatory action research</kwd><kwd>carcinogen</kwd></kwd-group></article-meta></front><body><sec id="S1"><label>1</label><title>Introduction</title><p id="P4">Environmental justice is a social movement of scholarship, policy, and activism that seeks to ensure a clean and healthy environment for all communities (<xref rid="R8" ref-type="bibr">Bullard 2021</xref>; <xref rid="R25" ref-type="bibr">Holifield, Chakraborty, and Walker 2018</xref>). Environmental health disparities are amplified by limited access to resources and decision-making processes among poor people, immigrants, and people of color (<xref rid="R30" ref-type="bibr">Perkins and Pulido 2022</xref>). California&#x02019;s CalEnviroScreen and the national EJSCREEN are useful tools for revealing communities most burdened by environmental pollution and vulnerability to associated health effects (<xref rid="R21" ref-type="bibr">Faust et al. 2017</xref>; <xref rid="R43" ref-type="bibr">U.S. Environmental Protection Agency 2019</xref>). To ensure reproducibility and replicability, both tools rely on public databases such as health registries, census data, emitting facility and toxic release violation reports, cleanup site tracking, and environmental monitoring (<xref rid="R21" ref-type="bibr">Faust et al. 2017</xref>; <xref rid="R43" ref-type="bibr">U.S. Environmental Protection Agency 2019</xref>). However, these tools tend to lose statistical relevance when considering low-density rural areas. The value of regulatory assessment tools for agricultural communities is diluted by inadequate environmental monitoring infrastructure and extensive environmental transport of industrial agrochemicals. Californian agricultural communities need targeted public health and cumulative exposure assessments to develop effective environmental justice interventions. Our project co-developed solutions that address the specific community needs (<xref rid="R36" ref-type="bibr">Schuller et al. 2019</xref>) and countered attempts to just provide local decision-makers with extrapolations from regulatory datasets.</p><p id="P5">Our community-university partnership in Knights Landing (KL) followed community-based participatory action research (CBPAR) approaches to supplement local knowledge about environmental health. This project operated in close collaboration with the university student-run One Health Center and the Chicana/o Studies Department (<xref rid="R41" ref-type="bibr">Sweeney et al. 2018</xref>). Community-based participatory action research (CBPAR) is a research approach that engages community members as equal partners in the research process to address community-identified problems and develop solutions that are relevant to the community (<xref rid="R17" ref-type="bibr">Deeb-Sossa et al. 2022</xref>; <xref rid="R27" ref-type="bibr">Manzo et al. 2020</xref>). Local resident experts can use targeted health assessments and interventions to improve public health through measures such as educating community members about environmental risk, developing mutual aid systems, and advocating for policy changes by local businesses and regulatory authorities (<xref rid="R20" ref-type="bibr">Edgren et al. 2005</xref>; <xref rid="R24" ref-type="bibr">Heaney et al. 2011</xref>; <xref rid="R28" ref-type="bibr">Mutiga-Waititu 2021</xref>; <xref rid="R31" ref-type="bibr">Quandt et al. 2013</xref>; <xref rid="R33" ref-type="bibr">Ram&#x000ed;rez et al. 2015</xref>; <xref rid="R35" ref-type="bibr">Sansom et al. 2016</xref>; <xref rid="R40" ref-type="bibr">Svendsen et al. 2010</xref>; <xref rid="R42" ref-type="bibr">Thompson et al. 2003</xref>). Local resident experts recruited student-researchers to study environmental health factors that could elevate cancer risks. Local resident experts included cancer survivors, fire fighters, parents, grandparents, local service providers, immigrants, community organizers, and experienced farm workers. Local resident experts volunteered to serve as <italic toggle="yes">promotora-researchers</italic> for this project with temporary university affiliation and hourly compensation for research design and data collection. A <italic toggle="yes">promotora-researcher</italic> is a community member who is trained to conduct research. They are often bilingual and have a deep understanding of the community's culture and values. <italic toggle="yes">Promotora-researchers</italic> can play a key role in CBPAR research by building trust with community members, recruiting participants, and collecting data (<xref rid="R9" ref-type="bibr">Bustillos and Sharkey 2015</xref>; <xref rid="R17" ref-type="bibr">Deeb-Sossa et al. 2022</xref>; <xref rid="R31" ref-type="bibr">Quandt et al. 2013</xref>). In our study, <italic toggle="yes">promotora-researchers</italic> included four Latinas and two white women. Through patchwork funding, the Knights Landing Environmental Health Project (2016-2023) built community partnerships while conducting qualitative and quantitative research (<xref rid="R17" ref-type="bibr">Deeb-Sossa et al. 2022</xref>).</p><p id="P6">KL is an agricultural community in Yolo County located in northern California with a predominantly Latina/o/x population of approximately 1,000 residents (<xref rid="R47" ref-type="bibr">US Census Bureau 2017</xref>). The growing season is year-round in the region which allowed most residents to remain in KL year-round without entering migrant farmwork. Despite the wealth produced by the local agricultural industry (<xref rid="R53" ref-type="bibr">Yolo County Department of Agriculture &#x00026; Cooperative Extension 2022</xref>), nearly a quarter of the population lived below the poverty line (<xref rid="R47" ref-type="bibr">US Census Bureau 2017</xref>). The lack of environmental monitoring data and small population size made environmental justice research in KL particularly challenging. Further, state-mandated community health assessments often overlooked the specific needs of vulnerable communities like KL (<xref rid="R6" ref-type="bibr">Becker 2015</xref>; <xref rid="R19" ref-type="bibr">Diaz, Ainsworth, and Schmidtlein 2019</xref>; <xref rid="R33" ref-type="bibr">Ram&#x000ed;rez et al. 2015</xref>; <xref rid="R36" ref-type="bibr">Schuller et al. 2019</xref>). For example, the eight surveys collected from KL residents for Yolo County&#x02019;s 2014 Community Health Assessment were marginal compared to the 85% of 812 total respondents who reported a urban or suburban city of residence (<xref rid="R50" ref-type="bibr">Yolo County Community Health Branch 2014</xref>).</p><p id="P7">County public health reports aligned with KL community perceptions about a high cancer risk in their neighborhood but lacked ground-truthed data and tangible pathways to prevent toxic exposures. Yolo County vital records, for example, showed the highest unadjusted frequency of cancer fatalities in the northeastern census tract including KL (<xref rid="F1" ref-type="fig">Figure 1</xref>) (<xref rid="R51" ref-type="bibr">Yolo County Community Health Branch 2015</xref>, <xref rid="R52" ref-type="bibr">2018</xref>). Cancer was the leading cause of premature death in Yolo County with lung, colorectal, breast, and pancreatic cancers making up most deaths (<xref rid="R51" ref-type="bibr">Yolo County Community Health Branch 2015</xref>, <xref rid="R52" ref-type="bibr">2018</xref>). Unlike the county disparities in mortality, the 5-year estimates of age-adjusted cancer incidence rates per 100,000 population in the California Health Map zones that represent KL were similar to the county and state rates for 2015-2019 (<xref rid="T1" ref-type="table">Table 1</xref>) (<xref rid="R46" ref-type="bibr">University of California San Francisco n.d.</xref>). Health indicators in CalEnviroscreen and the national EJSCREEN tool indicated higher environmentally-influenced disease burden in KL (<xref rid="T2" ref-type="table">Table 2</xref>).</p><p id="P8">After preliminary discussions between KL residents, the research team decided to identify which potential environmental risk factors for cancer should be prioritized for community-led interventions to reduce exposures to carcinogens. Additionally, the team considered some barriers to early diagnostics and healthy lifestyle options that are protective against cancer and are known to improve prognosis for those diagnosed with cancer. CBPAR was used to evaluate KL residents&#x02019; contact with potential carcinogens, which informed community-led efforts to reduce toxic exposures and increase access to cancer screenings for early detection and prevention. Community-owned and -managed research approaches enabled the development of culturally- and structurally-relevant assessment tools and weight of evidence strategies to assess environmental contributions to cancer risk for rural agricultural residents (<xref rid="R17" ref-type="bibr">Deeb-Sossa et al. 2022</xref>). This manuscript describes the community survey process, key results as interpreted by the <italic toggle="yes">promotora-researchers</italic>, and the actions in the community that were facilitated using this data.</p></sec><sec id="S2"><label>2</label><title>Materials and Methods</title><p id="P9">Our first response to the perceived high prevalence of cancer among KL residents was developing a cross-sectional survey documenting household, occupational, and behavioral exposures to potential carcinogens. Following a community-owned and -managed approach (<xref rid="R23" ref-type="bibr">Heaney, Wilson, and Wilson 2007</xref>), six <italic toggle="yes">promotora-researchers</italic> assumed leadership of the research process, focusing on identifying and implementing solutions to community concerns. Undergraduate and graduate student-researchers volunteered, completed graduation requirements, and secured grants and fellowships to support project aims. <italic toggle="yes">Promotora-researchers</italic> took on the day-to-day management of the research. Weekly team meetings enabled identification of community priorities before developing research instruments. <italic toggle="yes">Promotora-researchers</italic> also engaged with new and existing stakeholders to ensure representative recruitment and analysis. For example, they periodically updated and integrated feedback from residents, community development organizations, faith-based organizations, and community health centers. As our project unfolded, the composition of <italic toggle="yes">promotora-researchers</italic> fluctuated slightly. Following data collection, for example, one Latina <italic toggle="yes">promotora-researcher</italic> left the project for personal reasons while two additional residents joined (Latina and white, respectively). The research was determined by the university Institutional Review Board to be exempt from full review due to minimal risk to participants.</p><sec id="S3"><label>2.1</label><title>Environmental Health Survey Development</title><p id="P10">Surveys were derived by graduate student-researchers from the English and Spanish versions of the following standardized questionnaires: American Community Survey (<xref rid="R47" ref-type="bibr">US Census Bureau 2017</xref>), California Health Interview Survey (UCLA Center for Health Policy Research n.d.), Behavioral Risk Factor Surveillance System (<xref rid="R13" ref-type="bibr">Centers for Disease Control and Prevention n.d.</xref>), and World Health Organization Tobacco Survey (<xref rid="R48" ref-type="bibr">US World Health Organization and Centers for Disease Control 2011</xref>). We also incorporated a smaller-scale Agricultural Safety and Acculturation survey (<xref rid="R39" ref-type="bibr">Stoecklin-Marois, Hennessy-Burt, and Schenker 2011</xref>) and a Mexican-origin community-validated nutrition survey (<xref rid="R5" ref-type="bibr">Banna et al. 2010</xref>). The process of selecting survey questions involved multiple steps. First, graduate student-researchers drafted questionnaires under mentorship from university and county experts in Public Health. <italic toggle="yes">Promotora-researchers</italic> then thoroughly reviewed each question for content, scope, comprehensibility, and appropriateness during a series of team meetings spanning over three months. Subsequently, <italic toggle="yes">Promotora-researchers</italic> conducted internal testing and sought input from eight additional community members to assess the survey duration, question readability, and administration techniques. Finally, the <italic toggle="yes">promotora-researchers</italic> and student-researchers reconvened to review and confirm the appropriateness of the survey content and length. The final survey consisted of 62 questions available in both English and Spanish (<xref rid="SD1" ref-type="supplementary-material">Supplements 1</xref> and <xref rid="SD1" ref-type="supplementary-material">2</xref>). The scope included demographics, health indicators, health behaviors, lifestyle and behavioral factors, and environmental factors such as sunlight exposure, pesticide exposure, and housing conditions.</p></sec><sec id="S4"><label>2.2</label><title>Sampling and Data Collection Methodology</title><p id="P11">A goal sample size of 89 was calculated by setting parameters for achieving point estimates with 95% confidence intervals and a maximum tolerated margin of error of +/&#x02212; 10% for an estimated total KL population of 1,208 (<xref rid="R47" ref-type="bibr">US Census Bureau 2017</xref>). Several sampling options were considered including randomized door-to-door sampling, convenience sampling at community centers, and targeted convenience sampling in geographic zones. Ultimately, <italic toggle="yes">promotora-researchers</italic> implemented snowball recruitment in downtown and periphery zones which included potentially vulnerable subpopulations in migrant farm-worker labor camps, farmhouses, and trailer parks (<xref rid="F2" ref-type="fig">Figure 2</xref>). Individuals without housing reported their primary sleeping location as their geographic zone. Many residences housed multiple families, so <italic toggle="yes">promotora-researchers</italic> restricted sampling to two surveys per household to minimize clustering. Recruitment primarily occurred outside of agricultural business hours at community events and door-to-door. Safety measures were taken during survey recruitment sessions including <italic toggle="yes">promotora-researchers</italic> checking in with on-duty student researchers upon initiating and finishing deployment (<xref rid="SD1" ref-type="supplementary-material">Supplements 3</xref> and <xref rid="SD1" ref-type="supplementary-material">4</xref>). <italic toggle="yes">Promotora-researchers</italic>&#x02019; field logs documented homes attempted, homes surveyed, and the zone of each participant. Weekly meetings enabled coordination of targeted convenience sampling and prevention of multiple responses from any individual.</p><p id="P12"><italic toggle="yes">Promotora-researchers</italic> administered 100 surveys to adult KL residents from July 30 to September 2, 2017, when migrant and seasonal farm-worker populations were present (season spans May to October). Verbal informed consent was administered by <italic toggle="yes">promotora-researchers</italic> before survey administration. Screening questions confirmed that participants were adult residents of KL. Research excluded identifying information although a separate log was required by the university to document receipt of participant gift cards ($10 for about 30 minutes). Interview-style administration by <italic toggle="yes">promotora-researchers</italic> was typically the most effective, especially for participants with limited literacy. We conducted the initial 50 surveys in six days. The alcohol consumption question was clarified for subsequent surveys after preliminary assessment revealed inaccurate question administration (<xref rid="SD1" ref-type="supplementary-material">Supplement 5</xref>). The second half was completed in another six days.</p><p id="P13">Paper surveys and field logs were collected by student researchers. Appointments with residents and social groups (like the farm-worker labor camp) arranged by promotora-researchers before deployment enabled our 100% recorded response rate. This was achieved by assigning each promotora-researcher a specific geographic zone and a target number of surveys based on our calculated sample size of 89. While we exceeded this target, no participant declined to participate once contacted, contributing to the perfect response rate. The efficiency and effectiveness of promotora-researcher sampling is demonstrated by the brief two-week deployment to recruit 100 participants. Survey administration by promotora-researchers was thorough with few non-responses (&#x0201c;Missing&#x0201d;, &#x0201c;I don&#x02019;t know&#x0201d;, or &#x0201c;Prefer not to state''). The highest non-response rates were 8% to 11% of participants for cannabis consumption, frequency of electronic cigarette consumption, produce consumption, years in agriculture, and years working with pesticides; 18% for hours working outside; and 22% for the modified alcohol use question.</p></sec><sec id="S5"><label>2.3</label><title>Data Analysis</title><p id="P14">Student researchers entered survey responses into Microsoft Excel from the paper survey copies and a separate student researcher double-checked entries. Microsoft Access was used for data management and cleaning to ensure uniform coding. For the alcohol consumption question, only the 50 responses after modification were analyzed. For all other questions, the full data set was included in cleaning and analysis. Non-responses were excluded from numeric variable averages, categorical frequencies, and proportions. Statistical Analysis System 9.4 was used to generate descriptive results of the survey. Data were reported as prevalence estimates or mean values with 95% binomial confidence intervals. KL sample results were compared to the publicly-available state or federal health monitoring and census data that corresponded to each question in our survey at the finest geographic scale available (KL Census Designated Place (<xref rid="R47" ref-type="bibr">US Census Bureau 2017</xref>), Yolo County (UCLA Center for Health Policy Research n.d.), or Sacramento-Roseville-Arden-Arcade Metropolitan Statistical Area (<xref rid="R13" ref-type="bibr">Centers for Disease Control and Prevention n.d.</xref>)). Chi-squared tests or Fisher&#x02019;s exact tests were performed for comparisons of categorical variables and two-sample t-tests were performed for continuous variables (&#x003b1;= 0.05). When our question modifications or differences in sampling invalidated direct comparisons, governmental health monitoring and census data was presented for reference with limitations noted and without statistical interpretations.</p></sec></sec><sec id="S6"><label>3</label><title>Survey Results</title><sec id="S7"><label>3.1</label><title>Survey respondent demographics</title><p id="P15">Overall, the demographic distributions of our targeted sample were similar to the demographic distribution of the American Community Survey (<xref rid="T3" ref-type="table">Table 3</xref>). The only significant demographic difference was a higher proportion of individuals with low annual household incomes in our sample relative to the American Community Survey estimates (<xref rid="T3" ref-type="table">Table 3</xref>). 74 surveys were collected from downtown KL, while 26 were collected from periphery zones (<xref rid="F2" ref-type="fig">Figure 2</xref>). Respondents primarily live in KL year-round (91%) with 44% owning their home and 56% renting. Although our proportions of Latina/o/x participants were consistent with the American Community Survey, the different proportions of foreign-born individuals in our sample could be explained by our exclusion of children who are more likely to be born in the United States compared to adults. Our snowball sampling included more individuals without any college education, more low-income individuals, more unemployed individuals, and less individuals that are not in the labor force than were represented in the American Community Survey. The American Community Survey was not necessarily limited to peak agricultural season when migrant individuals were present while our recruitment was exclusively within this window, which may have contributed to a difference in the number of included agricultural workers.</p></sec><sec id="S8"><label>3.2</label><title>Household exposures to potential carcinogens</title><p id="P16">The respondents&#x02019; contact with hazardous household exposures was addressed for indoor pollutants and adjacent neighborhood environmental pollution sources. At the neighborhood level, over 63% of respondents reported living within one block (100 meters) of a highway or a farm and these proportions reached over 90% living within a 500-meter radius (<xref rid="T4" ref-type="table">Table 4</xref>). Indoor residential pesticide application was reported by 55% of respondents and 41% used pesticides on their home&#x02019;s exterior (<xref rid="T4" ref-type="table">Table 4</xref>). About a third of respondents used combustible energy sources to cook which may contribute to indoor air pollution, especially since 90% of respondents reported cooking most of their meals at home (<xref rid="T4" ref-type="table">Table 4</xref>). Bottled water was the main drinking source for 66% of respondents, while 18% drank water primarily from the public system, and 12% used private wells (<xref rid="T4" ref-type="table">Table 4</xref>). Point-of-use water treatment was used by 33% of respondents that primarily drink from the public system or private wells (<xref rid="T4" ref-type="table">Table 4</xref>). As an indicator of poor housing quality, chipped paint was reported by 18% of respondents with housing (<xref rid="T4" ref-type="table">Table 4</xref>). Opportunities for residential carcinogen exposures were common for respondents although the magnitude or frequency were not cataloged.</p></sec><sec id="S9"><label>3.3</label><title>Occupational exposures to potential carcinogens</title><p id="P17">Census data and input from <italic toggle="yes">promotora-researchers</italic> established agricultural labor as our primary focus. Sun exposure was concerning for agricultural and non-agricultural workers since 77% of respondents worked outside over an hour a day and 39% exceeded 9 hours (<xref rid="T5" ref-type="table">Table 5</xref>). Sun protection was used more than half of the time by only 53% of respondents that worked over an hour a day outdoors (<xref rid="T5" ref-type="table">Table 5</xref>). For the 70% of respondents that worked in agriculture during their lifetime, the mean employment duration was 12 years (<xref rid="T5" ref-type="table">Table 5</xref>). For the 24% of respondents that occupationally contacted pesticides, the mean number of years handling pesticides was 8 years (<xref rid="T5" ref-type="table">Table 5</xref>). Among individuals who worked with pesticides, 35% used protective clothing less than half of the time when handling pesticides and 19% did not change clothes or shoes before entering their home on days they handled pesticides (<xref rid="T5" ref-type="table">Table 5</xref>). Safe-handling training was completed in the previous year by 78% of respondents who worked with pesticides primarily in their native language (89% of trained respondents) from an organization unrelated to their employer (89% of trained respondents) (<xref rid="T5" ref-type="table">Table 5</xref>). Of respondents that worked with pesticides, 9% reported going to the doctor for pesticide exposure during their career (<xref rid="T5" ref-type="table">Table 5</xref>). Most KL residents worked in agriculture, and some lacked occupational safety training or best practices.</p></sec><sec id="S10"><label>3.4</label><title>Cancer-associated behaviors</title><p id="P18">Assessment of behavioral cancer risks included smoking history, alcohol consumption, dietary choices, and cancer screenings. Relative to Yolo County, the prevalence of current smokers (21%) in KL was significantly higher and former smokers (10%) was significantly lower (<xref rid="T6" ref-type="table">Table 6</xref>). The burden of smoking was also evident with 25% of respondents reporting current smoking by other household members (<xref rid="T6" ref-type="table">Table 6</xref>). The summed proportion of current and former cannabis smokers in KL was significantly lower by half compared to the 50% of Yolo County residents that ever-used cannabis (<xref rid="T6" ref-type="table">Table 6</xref>). Chewing tobacco or electronic cigarette usage was reported by less than 6% of respondents (<xref rid="T6" ref-type="table">Table 6</xref>). The prevalence of monthly binge drinking reported by KL adults (45%) was not significantly different from county levels (<xref rid="T6" ref-type="table">Table 6</xref>). For the protective behavior of eating fruits and vegetables, only 19% of respondents consumed at least the recommended 5 servings per day and the mean daily consumption for all respondents was 3 servings (<xref rid="T6" ref-type="table">Table 6</xref>). In the most recent 2005 data (UCLA Center for Health Policy Research n.d.), Yolo County respondents met daily produce consumption recommendations at double the level we found in KL (<xref rid="T6" ref-type="table">Table 6</xref>). Challenges to achieving a healthy lifestyle were apparent in KL.</p><p id="P19">In KL, the prevalence of some diseases potentially exacerbated by environmental pollution were close to county levels: diabetes (14%) and asthma (22%) (<xref rid="T7" ref-type="table">Table 7</xref>). Obesity was significantly more prevalent in the KL sample (38%) compared to the county (23%) (<xref rid="T7" ref-type="table">Table 7</xref>). Consistent with asthma rates, breathing issues in the past year were noted by 25% of respondents (<xref rid="T7" ref-type="table">Table 7</xref>). Half of the respondents reported a family history of cancer (<xref rid="T7" ref-type="table">Table 7</xref>). While this result is uncertain due to statistical limitations of small sample sizes, cancer diagnosis was reported by less KL respondents (2%) relative to Yolo County (9%) (<xref rid="T7" ref-type="table">Table 7</xref>). The abundance of cancer survivors that responded to the KL survey could be impacted by individuals moving away for more convenient or affordable treatment as well as potentially poor survival rates in the KL community for those diagnosed with cancer. For individuals within recommended ages for cancer screenings, the proportions of respondents that ever accessed a mammogram (71%) or pap smear (68%) were similar to county residents that accessed these services according to the recommended schedule (<xref rid="T7" ref-type="table">Table 7</xref>). Conversely, the proportion of KL respondents within recommended age ranges that ever-accessed colonoscopy (38%) was lower than the county residents that received colonoscopy according to the recommended schedule (64%) (<xref rid="T7" ref-type="table">Table 7</xref>). Most respondents completed a regular medical checkup within the past two years (93%) which is significantly higher than the Yolo County rate (83%) (<xref rid="T7" ref-type="table">Table 7</xref>). Respondents&#x02019; health insurance coverage (84%) was similar to county levels (<xref rid="T7" ref-type="table">Table 7</xref>). Health care access challenges were less substantial compared to behavioral risks in KL.</p></sec></sec><sec id="S11"><label>4</label><title>Community-led Interventions</title><p id="P20"><italic toggle="yes">Promotora-researchers</italic> distributed survey results through word-of-mouth with an infographic handout (<xref rid="SD1" ref-type="supplementary-material">Supplement 6</xref>), collected residents&#x02019; feedback, and invited community members to directly advise academic-researchers at our annual One Health Festival (September 2017). Residents overwhelmingly confirmed the consistency of survey results with their own lived experiences. Further documentation of environmental health and cancer risk perceptions was completed in 2018 through five focus groups and accompanying photovoice projects led by <italic toggle="yes">promotora-researchers</italic>. During weekly meetings, <italic toggle="yes">promotora-researchers</italic> prioritized concerns for further community-led action and research. They decided against using our limited resources to address regional issues like traffic or agricultural sources of pollution on account of the high likelihood of conflict within the community regarding action plans; high barriers to reaching and mobilizing regulators and industry; and the perceived threat to the local economy if structural solutions were proposed. As a result, the action priorities became household environmental carcinogen exposure, addictive substance misuse, access to cancer screening, occupational safety, and housing quality including neighborhood isolation from health services (<xref rid="T8" ref-type="table">Table 8</xref>). The research team built open communication and trust with community members to sustain a partnership that was responsive to existing and emerging needs (<xref rid="R17" ref-type="bibr">Deeb-Sossa et al. 2022</xref>). The project was also carefully designed to minimize and mitigate any negative impacts caused by the research.</p><p id="P21"><italic toggle="yes">Promotora-researchers</italic> prioritized pesticides for further investigation based on occupational exposure risks (<xref rid="R15" ref-type="bibr">Cockburn et al. 2011</xref>; <xref rid="R18" ref-type="bibr">Deziel et al. 2015</xref>; <xref rid="R42" ref-type="bibr">Thompson et al. 2003</xref>) and potential for drift into residential areas (<xref rid="R18" ref-type="bibr">Deziel et al. 2015</xref>; <xref rid="R22" ref-type="bibr">Harrison 2011</xref>). California Rural Legal Assistance Foundation and Western Center for Agricultural Health and Safety provided strategies to interrupt the occupational pesticide take-home pathway (<xref rid="R15" ref-type="bibr">Cockburn et al. 2011</xref>; <xref rid="R18" ref-type="bibr">Deziel et al. 2015</xref>; <xref rid="R42" ref-type="bibr">Thompson et al. 2003</xref>). Residential use of consumer pesticides in our sample was similar to other urban and farmworker households in California (<xref rid="R32" ref-type="bibr">Quir&#x000e1;s-Alcal et al. 2011</xref>). <italic toggle="yes">Promotora-researchers</italic> shared strategies to reduce pest and pesticide entry with residents, acknowledging that housing quality and maintenance may be more important than knowledge of pesticide exposure prevention. Student-researchers mapped state-monitored potentially carcinogenic pesticide applications by industrial farms in KL and a neighboring organic region. Seasonal application and active ingredient patterns in these two growing regions were validated by quantifying potentially carcinogenic pesticides in household dust and tap water. Moving forward, we aim to evaluate the feasibility of collaboratively developing agricultural pesticide fate and transport models with farm-operators, applicators, and irrigators. In combination with regulatory monitoring, farm-operator tools and protective residential practices could reduce carcinogenic pesticide exposures.</p><p id="P22">KL drinking water contamination concerns were amplified after two of three public wells failed during a recent drought (2014-2017). In shallow, unregulated private wells further water quality concerns include septic system leakage and agrochemical percolation. KL also has a history of natural toxic metal leaching (<xref rid="R3" ref-type="bibr">Ayotte, Nolan, and Gronberg 2016</xref>). A neighboring town where many KL children attend elementary school received a state grant for bottled drinking water deliveries due to arsenic contamination of their community well. A follow-up sampling study, launched in collaboration with a neighboring organic agricultural community, investigated potential carcinogen contamination in private drinking water and irrigation wells. <italic toggle="yes">Promotora-researchers</italic> provided precautionary advice about effective drinking water treatment strategies and a public water bottle refill station is now being considered (<xref rid="R3" ref-type="bibr">Ayotte et al. 2016</xref>). Many residents of KL rely on bottled water due to uncertainty about water quality. Additionally, the research team stayed involved in KL Community Service District strategies to improve water infrastructure and security.</p><p id="P23"><italic toggle="yes">Promotora-researchers</italic> intend to address concerns about cumulative exposures to potentially carcinogenic combustion byproducts in KL (<xref rid="R10" ref-type="bibr">California Air Resources Board 2021</xref>; <xref rid="R29" ref-type="bibr">Noth et al. 2020</xref>; <xref rid="R37" ref-type="bibr">Stampfer et al. 2020</xref>). The COVID-19 pandemic delayed plans to partner with farm-operators and local organizations to reduce diesel exhaust, promote household appliance electrification and ventilation, and partner with the Air Quality Management District to address recreational wood and agricultural burning (<xref rid="R11" ref-type="bibr">California Mobile Source Control Division n.d.</xref>; <xref rid="R14" ref-type="bibr">Chen et al. 2007</xref>; <xref rid="R34" ref-type="bibr">Ross 2015</xref>). In response to smoking disparities (<xref rid="R2" ref-type="bibr">American Lung Association in California 2018</xref>; <xref rid="R26" ref-type="bibr">Liu et al. 2016</xref>; <xref rid="R38" ref-type="bibr">Stillman et al. 2018</xref>), <italic toggle="yes">promotora-researchers</italic> initiated research interviews with smokers and nonsmokers, which revealed a lack of sustainable mental/emotional health services and smoking cessation treatments. The student-run KL One Health Center was tasked to provide services for residents interested in reducing addictive substance dependence or recreational consumption. <italic toggle="yes">Promotora-researchers</italic> founded peer support groups for residents interested in reducing consumption of addictive substances and seeded youth-focused programs to provide healthy recreational alternatives. They also responded to the community&#x02019;s food desert status and shortage of safe exercise spaces by constructing a community garden and piloting a micro-transit program to urgently increase access to neighboring city resources (<xref rid="R17" ref-type="bibr">Deeb-Sossa et al. 2022</xref>).</p></sec><sec id="S12"><label>5</label><title>Discussion</title><p id="P24">Environmental justice is a social movement that seeks to address the disproportionate exposure of marginalized communities to environmental health hazards. Academic research plays a critical role in the movement by raising awareness of environmental risks, providing evidence to support claims of environmental injustice, and helping to develop effective interventions (<xref rid="R23" ref-type="bibr">Heaney et al. 2007</xref>). However, criticisms of institution-led research often spotlight a lack of shared power and a focus on scientific priorities rather than community needs. A community-owned and -managed approach for conducting environmental justice research in marginalized communities is ideal because leadership of community members is emphasized throughout the research process, from the development of research questions to the dissemination of findings (<xref rid="R23" ref-type="bibr">Heaney et al. 2007</xref>). As such, community control over the research process ensures that the research focuses on finding successful solutions that benefit the community.</p><p id="P25">In this study, a cross-section of local experts assumed the role of <italic toggle="yes">promotora-researchers</italic> to conduct environmental justice research alongside interdisciplinary student-researchers in an agricultural community with a perceived high prevalence of environmental hazards and cancer. Background research revealed that national-, state-, and county-level reporting corroborated residential perceptions but was not actionable with limited community resources. A cross-sectional survey and community review process was agreed upon to document environmental health risks while refining environmental justice priorities within the resources of residents and local levels of government to affect. Despite the absence of local environmental public health data, our community-owned and -managed approach to environmental justice research sparked concentrated follow-up research that aligned with community needs and community-led interventions that were prompt and feasible (<xref rid="R1" ref-type="bibr">Abara et al. 2014</xref>; <xref rid="R7" ref-type="bibr">Brody et al. 2009</xref>; <xref rid="R17" ref-type="bibr">Deeb-Sossa et al. 2022</xref>; <xref rid="R35" ref-type="bibr">Sansom et al. 2016</xref>).</p><p id="P26">The research presented in this paper has several limitations. First, sampling was not randomized although <italic toggle="yes">promotora-researchers</italic> minimized clustering, so results may not be generalizable to other communities. Second, the data was collected by local experts and relied on participant self-reporting, which may have introduced response and recall bias into our results. Third, the research was conducted over a short period of time, which makes long-term trends difficult to identify such as the health impacts of chronic exposure to air pollution. Fourth, while our study was powered to document community-level patterns, the small sample size limited our ability to run statistical analyses. As a result, qualitative research was designed to subsequently document and address disparities within the KL population. Lastly, the research did not assess the cost effectiveness of the community-led environmental health assessment survey. Overall, this study provides valuable insights into the potential benefits of a community-owned and -managed approach to environmental justice research. However, our community-specific data, with modified questions, may limit both the ability to replicate our survey findings and the comparability of our community action results to other environmental health monitoring and environmental justice interventions.</p><p id="P27">Our study demonstrates the value of community-owned and -managed research to develop effective environmental public health interventions that reflect community needs. This approach can help identify and address environmental hazards that are disproportionately impacting California's rural agricultural communities. Findings from this study are analytically generalizable (<xref rid="R49" ref-type="bibr">Yin 2018</xref>) to other rural communities with similar population sizes, levels of environmental health information availability, and patterns of environmental risk (<xref rid="R12" ref-type="bibr">Cannon 2021</xref>). Details of the history of this community-university partnership and the resources that were available to this research team are detailed in <xref rid="R17" ref-type="bibr">Deeb-Sossa, 2022</xref>. Likewise, our approach may serve as a model for environmental justice researchers striving to promptly reduce environmental health risks in marginalized communities.</p></sec><sec id="S13"><label>6</label><title>Conclusions</title><p id="P28">Community ownership and management, in combination with CBPAR, increased the rigor, reach, relevance, and representativeness of our environmental justice study in a small, agricultural community (<xref rid="R4" ref-type="bibr">Balazs and Morello-Frosch 2013</xref>; <xref rid="R23" ref-type="bibr">Heaney et al. 2007</xref>; <xref rid="R35" ref-type="bibr">Sansom et al. 2016</xref>). Local experts helped to overcome community-specific research challenges (<xref rid="R1" ref-type="bibr">Abara et al. 2014</xref>; <xref rid="R20" ref-type="bibr">Edgren et al. 2005</xref>; <xref rid="R31" ref-type="bibr">Quandt et al. 2013</xref>) and they provided critical context as community priorities advanced in response to interventions and current events (<xref rid="R5" ref-type="bibr">Banna et al. 2010</xref>; <xref rid="R31" ref-type="bibr">Quandt et al. 2013</xref>; <xref rid="R35" ref-type="bibr">Sansom et al. 2016</xref>). Likewise, student-researchers provided university resources to sustain research activity in the form of technical assistance and fundraising (<xref rid="R7" ref-type="bibr">Brody et al. 2009</xref>; <xref rid="R35" ref-type="bibr">Sansom et al. 2016</xref>). Student-researchers embraced CBPAR despite pressures to follow established extractive research routes and many academic sacrifices were made to prevent delays in community action (<xref rid="R17" ref-type="bibr">Deeb-Sossa et al. 2022</xref>). The survey process and results steered by local experts led to expanded research directions and implementation of feasible community actions over six years despite shortcomings in our sustained efforts to achieve structural change (<xref rid="R16" ref-type="bibr">Davis and Ram&#x000ed;rez-Andreotta 2021</xref>).</p><p id="P29">CBPAR is a powerful tool for advancing environmental justice and improving environmental public health in the absence of local, representative data. Our team cautions that communities without existing institutional partnerships may struggle to replicate the scale and pace of action demonstrated here (survey was completed in 4 months with under $5,000 in pilot funding) (<xref rid="R1" ref-type="bibr">Abara et al. 2014</xref>; <xref rid="R4" ref-type="bibr">Balazs and Morello-Frosch 2013</xref>; <xref rid="R35" ref-type="bibr">Sansom et al. 2016</xref>). Such approaches are necessary to address multifactorial environmental justice concerns like cancer within a specific neighborhood or community context, even if statistical and other research limitations limit the academic utility of the data generated. Communities can initiate a swift, customized, representative environmental health assessment to serve as a starting point when seeking institutional support, funding, or larger research initiatives.</p></sec><sec sec-type="supplementary-material" id="SM1"><title>Supplementary Material</title><supplementary-material id="SD1" position="float" content-type="local-data"><label>Supinfo</label><media xlink:href="NIHMS2028198-supplement-Supinfo.docx" id="d67e794" position="anchor"/></supplementary-material></sec></body><back><ack id="S14"><title>Acknowledgments</title><p id="P30">Accomplishments described here were only possible due to the actions of promotora-researchers, survey participants, and community organizers. Promotora-researchers are Knights Landing residents and they preferred collective acknowledgment to respect their privacy. California Rural Legal Assistance Foundation, Yolo County Community Services Environmental Health Division, Yolo County Health and Human Services Agency Community Health Branch, KL Community Service District, and Environmental Justice Coalition for Water contributed to our understanding of community and existing environmental health monitoring.</p><sec id="S15"><title>Funding:</title><p id="P31">University fellowships; National Institutes of Health: <italic toggle="yes">T32HL007013,</italic> Environmental Health Science Center Exposure Core Seed Funds and Idea Pitch <italic toggle="yes">P30ES023513</italic>; National Cancer Institute: Geographic Management of Cancer Health Disparities Program Region 4 Research Stimulus Award <italic toggle="yes">P30CA015704</italic>; Western Center for Agricultural Health and Safety Fellowship and Rapid Response Grant <italic toggle="yes">2U54OH007550</italic>; and Achievement Rewards for College Scientists.</p></sec></ack><fn-group><fn fn-type="COI-statement" id="FN2"><p id="P32">Conflict of Interest Statement</p><p id="P33">The authors do not have any conflict of interest to disclose that is not already apparent in our funding or affiliations.</p></fn><fn id="FN3"><p id="P34">Open Research</p><p id="P35">Data supporting this research is owned by community leaders and is not accessible to the public. Based on community-university research partnership agreements, data access and usage are restricted to projects that are approved by the community leaders (<italic toggle="yes">promotora-researchers</italic>). 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Cooperative Extension</collab>. <year>2022</year>. &#x0201c;<source>Crop Statistics</source>.&#x0201d; <date-in-citation>Retrieved February 15, 2023</date-in-citation> (<comment><ext-link xlink:href="https://www.yolocounty.org/government/general-government-departments/agriculture-cooperative-extension/agriculture-and-weights-measures/crop-statistics" ext-link-type="uri">https://www.yolocounty.org/government/general-government-departments/agriculture-cooperative-extension/agriculture-and-weights-measures/crop-statistics</ext-link></comment>).</mixed-citation></ref></ref-list></back><floats-group><fig position="float" id="F1"><label>Figure 1:</label><caption><title>Map of Cancer Fatalities per 100,000 Residents in Yolo County.</title><p id="P36">Cancer fatality rates per 100,000 persons are separated into census tracts for A) 2011-2014 and B) 2015-2018. The highest cancer burden was in the northeastern census tract including Knights Landing. Fatality data were retrieved from California Department of Public Health Vital Records Business and Information System. This map was reproduced using ArcGIS Online with permission from Yolo County Community Health Branch (<xref rid="R51" ref-type="bibr">Yolo County Community Health Branch 2015</xref>, <xref rid="R52" ref-type="bibr">2018</xref>).</p></caption><graphic xlink:href="nihms-2028198-f0001" position="float"/></fig><fig position="float" id="F2"><label>Figure 2.</label><caption><title>Map of Knights Landing Environmental Health Survey recruitment zones.</title><p id="P37">Promotora-researchers designated geographic zones to represent the sub-populations of Knights Landing. The downtown residential area (D) which covers the Knights Landing Census Designated Place (<xref rid="R47" ref-type="bibr">US Census Bureau 2017</xref>) was split along major roads to include quadrants of approximately equal numbers of residents. The periphery zones (P) include a migrant farm-worker labor camp, trailer homes, and farmhouses considered to be underrepresented subpopulations. Representative map was rendered using ArcGIS Online.</p></caption><graphic xlink:href="nihms-2028198-f0002" position="float"/></fig><table-wrap position="float" id="T1"><label>Table 1:</label><caption><title>Age-adjusted cancer incidence rates of Knights Landing.</title><p id="P38">5-year estimates of age-adjusted cancer incidence rates (2015 - 2019) for the two California Health Map zones that represent Knights Landing, Yolo County, and the state of California (<xref rid="R46" ref-type="bibr">University of California San Francisco n.d.</xref>). Incidence rates include all invasive cancers cases. The California Health Map calculates incidence rates using case counts from the California Cancer Registry or the National Cancer Institute&#x02019;s Surveillance, Epidemiology, and End Results Program.</p></caption><table frame="box" rules="all"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th rowspan="2" align="left" valign="top" colspan="1">California Health Map zone</th><th colspan="2" align="left" valign="top" rowspan="1">Age-adjusted cancer incidence rates (2015 - 2019)</th></tr><tr><th align="left" valign="top" rowspan="1" colspan="1">5-year estimates per 100,000<break/>population</th><th align="left" valign="top" rowspan="1" colspan="1">95% CI</th></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Knights Landing zone &#x0201c;Yolo 1 (A0766)&#x0201d;</td><td align="left" valign="top" rowspan="1" colspan="1">399</td><td align="left" valign="top" rowspan="1" colspan="1">(378, 420)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Knights Landing zone &#x0201c;Sutter (B0403)&#x0201d;</td><td align="left" valign="top" rowspan="1" colspan="1">402</td><td align="left" valign="top" rowspan="1" colspan="1">(385, 419)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Yolo County</td><td align="left" valign="top" rowspan="1" colspan="1">398</td><td align="left" valign="bottom" rowspan="1" colspan="1">(385, 410)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">California</td><td align="left" valign="top" rowspan="1" colspan="1">399</td><td align="left" valign="top" rowspan="1" colspan="1">(378, 420)</td></tr></tbody></table></table-wrap><table-wrap position="float" id="T2"><label>Table 2:</label><caption><title>Environmental Exposure and Susceptibility Rankings of Knights Landing.</title><p id="P39">CalEnviroScreen (<xref rid="R21" ref-type="bibr">Faust et al. 2017</xref>) and EJScreen (<xref rid="R43" ref-type="bibr">U.S. Environmental Protection Agency 2019</xref>) tools rank the two census areas representing Knights Landing for the following metrics according to available data in 2018 with higher percentages representing more risk of health damages due to pollution. EJScreen was used for National-Scale Air Toxics Assessment (NATA) (units: percentile ranks of 217,740 United States Census Block Groups) since this indicator was not available in CalEnviroScreen (units: percentile ranks of 8,057 California census tracts).</p></caption><table frame="box" rules="all"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th rowspan="2" align="left" valign="middle" colspan="1">Category</th><th rowspan="2" align="left" valign="middle" colspan="1">Metric</th><th colspan="2" align="left" valign="middle" rowspan="1">Knights Landing Percentile Ranks in<break/>CalEnviroScreen or EJScreen</th></tr><tr><th align="left" valign="middle" rowspan="1" colspan="1">Census Area 1</th><th align="left" valign="middle" rowspan="1" colspan="1">Census Area 2</th></tr></thead><tbody><tr><td rowspan="3" align="left" valign="top" colspan="1">Environmentally Influenced Disease</td><td align="left" valign="top" rowspan="1" colspan="1">Asthma prevalence</td><td align="left" valign="top" rowspan="1" colspan="1">75</td><td align="left" valign="top" rowspan="1" colspan="1">85</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Low birth weight prevalence</td><td align="left" valign="top" rowspan="1" colspan="1">18</td><td align="left" valign="top" rowspan="1" colspan="1">25</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Cardiovascular disease prevalence</td><td align="left" valign="top" rowspan="1" colspan="1">48</td><td align="left" valign="top" rowspan="1" colspan="1">74</td></tr><tr><td rowspan="5" align="left" valign="top" colspan="1">Air Quality</td><td align="left" valign="top" rowspan="1" colspan="1">NATA Toxic Air Pollution Cancer index</td><td align="left" valign="top" rowspan="1" colspan="1">56</td><td align="left" valign="top" rowspan="1" colspan="1">71</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NATA Toxic Air Respiratory Health index</td><td align="left" valign="top" rowspan="1" colspan="1">51</td><td align="left" valign="top" rowspan="1" colspan="1">90</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Ozone</td><td align="left" valign="top" rowspan="1" colspan="1">61</td><td align="left" valign="top" rowspan="1" colspan="1">61</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Diesel Particulate Matter</td><td align="left" valign="top" rowspan="1" colspan="1">8</td><td align="left" valign="top" rowspan="1" colspan="1">14</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Particulate Matter (PM 2.5)</td><td align="left" valign="top" rowspan="1" colspan="1">12</td><td align="left" valign="top" rowspan="1" colspan="1">20</td></tr><tr><td rowspan="3" align="left" valign="top" colspan="1">Water Quality</td><td align="left" valign="top" rowspan="1" colspan="1">Drinking Water Threats</td><td align="left" valign="top" rowspan="1" colspan="1">60</td><td align="left" valign="top" rowspan="1" colspan="1">80</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Groundwater Threats</td><td align="left" valign="top" rowspan="1" colspan="1">91</td><td align="left" valign="top" rowspan="1" colspan="1">93</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Impaired Surface Water</td><td align="left" valign="top" rowspan="1" colspan="1">96</td><td align="left" valign="top" rowspan="1" colspan="1">98</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Potentially Toxic Pesticide Use</td><td align="left" valign="top" rowspan="1" colspan="1">Pesticides</td><td align="left" valign="top" rowspan="1" colspan="1">84</td><td align="left" valign="top" rowspan="1" colspan="1">84</td></tr></tbody></table></table-wrap><table-wrap position="float" id="T3"><label>Table 3:</label><caption><title>Demographic summary.</title><p id="P40">The 2017 Environmental Health Survey used community-based participatory action research strategies and snowball sampling of 100 adults in Knights Landing, California. American Community Survey results are 2017 5-year estimates for Knights Landing Census Designated Place (<xref rid="R47" ref-type="bibr">US Census Bureau 2017</xref>). Categorical data are presented as the proportion of respondents with 95% binomial confidence intervals (CI). Significant differences between the Knights Landing and American Community Survey samples are noted as: * p = 0.05.</p></caption><table frame="box" rules="none"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th rowspan="3" align="left" valign="top" style="border-right: solid 1px; border-bottom: solid 1px" colspan="1">Demographics</th><th colspan="3" align="left" valign="top" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1">Environmental Health Survey</th><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">American Community Survey</th></tr><tr><th colspan="3" align="left" valign="top" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Sample (n)= adults in Knights</italic>
<break/>
<italic toggle="yes">Landing recruitment zones</italic>
</th><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Sample= randomly contacted</italic>
<break/>
<italic toggle="yes">households in Knights Landing</italic>
<break/>
<italic toggle="yes">Census Designated Place</italic>
</th></tr><tr><th align="left" valign="top" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">%</th><th align="left" valign="top" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">95% CI</th><th align="left" valign="top" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">n</th><th align="left" valign="top" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">%</th><th align="left" valign="top" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">95% CI</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">n</th></tr></thead><tbody><tr><td colspan="7" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1"><bold>Age</bold>
<xref rid="TFN1" ref-type="table-fn">#</xref><break/>sample = age &#x02265;18 for Environmental Health Survey or all ages American Community Survey</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">18 - 19</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">3%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 7)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">3</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="middle" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">20 - 24</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">5%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(1, 10)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">5</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">11%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(2, 20)</td><td align="left" valign="middle" rowspan="1" colspan="1">110</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">25 - 44</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">43%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(32, 52)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">42</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">18%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(8, 28)</td><td align="left" valign="middle" rowspan="1" colspan="1">187</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">45 - 64</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">36%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(25, 45)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">35</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">25%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(12, 38)</td><td align="left" valign="middle" rowspan="1" colspan="1">259</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">65 and older</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">12%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(5, 19)</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">12</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">18%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(5, 31)</td><td align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1" colspan="1">187</td></tr><tr><td colspan="7" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1"><bold>Gender</bold><break/>Sample = age &#x02265;18 for Environmental Health Survey and American Community Survey</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Male</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">44%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(34, 54)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">44</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">41%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(31, 51)</td><td align="left" valign="middle" rowspan="1" colspan="1">311</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">Female</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">56%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(46, 66)</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">56</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">59%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(49, 69)</td><td align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1" colspan="1">441</td></tr><tr><td colspan="7" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1"><bold>Race/Ethnicity</bold>
<xref rid="TFN1" ref-type="table-fn">#</xref><break/>sample = age &#x02265;18 for Environmental Health Survey and all ages American Community Survey</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">White/Caucasian</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">26%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(17, 35)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">25</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">25%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(8, 42)</td><td align="left" valign="middle" rowspan="1" colspan="1">252</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Latino/a or Hispanic</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">68%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(59, 77)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">67</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">70%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(50, 90)</td><td align="left" valign="middle" rowspan="1" colspan="1">715</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Asian</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">3%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 7)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">3</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">6%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 15)</td><td align="left" valign="middle" rowspan="1" colspan="1">61</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">African-American, Black</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">1%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 3)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">1</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">0%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 2)</td><td align="left" valign="middle" rowspan="1" colspan="1">0</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">Native American, American Indian, or Alaska Native</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">1%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(0, 3)</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">1</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">0%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(0, 2)</td><td align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1" colspan="1">0</td></tr><tr><td colspan="7" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1"><bold>Education Attainment</bold>
<xref rid="TFN1" ref-type="table-fn">#</xref><break/>sample = age &#x02265;25 for Environmental Health Survey and American Community Survey</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">No Formal Education</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">2%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 5)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">2</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="middle" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Grade or Middle School (Grades 1-8)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">32%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(23, 41)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">31</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">27%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(9, 45)</td><td align="left" valign="middle" rowspan="1" colspan="1">169</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">High School or Equivalent</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">35%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(26, 45)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">34</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">22%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(15, 29)</td><td align="left" valign="middle" rowspan="1" colspan="1">141</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Some College or Associate&#x02019;s Degree</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">18%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(10, 25)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">17</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">24%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(10, 38)</td><td align="left" valign="middle" rowspan="1" colspan="1">153</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">4-year College or University Graduate</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">3%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 7)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">3</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">10%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 20)</td><td align="left" valign="middle" rowspan="1" colspan="1">62</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Graduate or Professional School</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">1%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 3)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">1</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">4%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 9)</td><td align="left" valign="middle" rowspan="1" colspan="1">26</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">Vocational, Business, or Trade School</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">1%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(0, 3)</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">1</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td colspan="7" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1"><bold>Annual Household Income</bold> *</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Less than $15,000</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">32%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(22, 42)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">30</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">17%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(2, 32)</td><td align="left" valign="middle" rowspan="1" colspan="1">59</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">$15,000 - $24,999</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">22%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(14, 30)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">20</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">15%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(0, 30)</td><td align="left" valign="middle" rowspan="1" colspan="1">51</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">$25,000 - $49,999</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">29%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(20, 38)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">27</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">39%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(22, 56)</td><td align="left" valign="middle" rowspan="1" colspan="1">132</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">$50,000 - $99,999</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">10%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(4, 16)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">9</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">20%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(2, 38)</td><td align="left" valign="middle" rowspan="1" colspan="1">69</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">$100,000 or more</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">7%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(2, 12)</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">6</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">8%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(0, 16)</td><td align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1" colspan="1">28</td></tr><tr><td colspan="7" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1"><bold>Country of Birth</bold>
<xref rid="TFN1" ref-type="table-fn">#</xref><break/>sample = age &#x02265;18 for Environmental Health Survey or all ages American Community Survey</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Native-born (US)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">46%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(36, 56)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">46</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">64%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(50, 78)</td><td align="left" valign="middle" rowspan="1" colspan="1">663</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">Foreign-born</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">54%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(43, 65)</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">53</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">36%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(22, 50)</td><td align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1" colspan="1">365</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">&#x02003;Latin America <italic toggle="yes">% of foreign-born</italic></td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">94% <xref rid="TFN2" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(88, 100)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">50</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">93%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(82, 100)</td><td align="left" valign="middle" rowspan="1" colspan="1">338</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Asia <italic toggle="yes">% of foreign-born</italic></td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">6%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(0, 12)</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">3</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">7%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(0, 18)</td><td align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1" colspan="1">27</td></tr><tr><td colspan="7" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1"><bold>Occupations</bold>
<xref rid="TFN1" ref-type="table-fn">#</xref><break/>sample = age &#x02265;18 for Environmental Health Survey or age&#x02265;16 for American Community Survey</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Unemployed</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">22%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(14, 30)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">21</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">10%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(3, 17)</td><td align="left" valign="middle" rowspan="1" colspan="1">81</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">Not in Labor Force <italic toggle="yes">Includes retirees and those with disabilities</italic></td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">12%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(5, 19)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">11</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">40%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(26, 54)</td><td align="left" valign="middle" rowspan="1" colspan="1">319</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">Employed</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">66%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(56, 76)</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">63</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">50%</td><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">(36, 64)</td><td align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1" colspan="1">386</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">&#x02003;Agricultural Labor</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">41%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(31, 51)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">34</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">9%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(6, 12)</td><td align="left" valign="middle" rowspan="1" colspan="1">36</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;<italic toggle="yes">% of employed</italic></td><td colspan="3" align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Agriculture</italic>
</td><td colspan="3" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Agriculture, fishing, forestry, hunting, and mining</italic>
</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">&#x02003;Non-Agricultural Labor</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">18%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(10, 26)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">14</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">27%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(8, 46)</td><td align="left" valign="middle" rowspan="1" colspan="1">104</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;<italic toggle="yes">% of employed</italic></td><td colspan="3" align="center" valign="middle" style="border-right: solid 1px; border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Custodial and construction</italic>
</td><td colspan="3" align="center" valign="middle" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Construction, manufacturing, transportation, warehousing, and utilities</italic>
</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">&#x02003;Other</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">41%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(31, 51)</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">25</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">64%</td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">(59, 69)</td><td align="left" valign="middle" rowspan="1" colspan="1">246</td></tr><tr><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1">&#x02003;<italic toggle="yes">% of employed</italic></td><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1"/><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1"/><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1"/><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1"/><td align="left" valign="middle" style="border-right: solid 1px" rowspan="1" colspan="1"/><td align="left" valign="middle" rowspan="1" colspan="1"/></tr></tbody></table><table-wrap-foot><fn id="TFN1"><label>#</label><p id="P41">Direct comparisons could not be made for variables with different age thresholds for the Environmental Health Survey responses and the American Community Survey.</p></fn><fn id="TFN2"><label>&#x022a5;</label><p id="P42">The only Latin America country of origin was Mexico for the Knights Landing foreign-born respondents.</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="T4"><label>Table 4:</label><caption><title>Cancer-Associated Environmental Exposures.</title><p id="P43">The 2017 Environmental Health Survey used community-based participatory action research strategies and snowball sampling of 100 adults in Knights Landing, California. Categorical data are presented as the proportion of respondents with 95% binomial confidence intervals (CI). These survey questions were developed primarily from an agricultural health survey adapted to this community by <italic toggle="yes">promotora-researchers,</italic> so they are not comparable to data regularly collected by public health agencies.</p></caption><table frame="box" rules="cols"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th rowspan="3" align="left" valign="top" style="border-bottom: solid 1px" colspan="1">Cancer-Associated Environmental Exposures</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Environmental Health Survey</th></tr><tr><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Sample (n)= adults in Knights Landing</italic>
<break/>
<italic toggle="yes">recruitment zones</italic>
</th></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">%</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">95% CI</th></tr></thead><tbody><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Type of Housing Unit (n=100)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">House</td><td align="left" valign="top" rowspan="1" colspan="1">62%</td><td align="left" valign="top" rowspan="1" colspan="1">(52, 72)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Apartment</td><td align="left" valign="top" rowspan="1" colspan="1">26%</td><td align="left" valign="top" rowspan="1" colspan="1">(18, 36)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Mobile Home or Trailer</td><td align="left" valign="top" rowspan="1" colspan="1">6%</td><td align="left" valign="top" rowspan="1" colspan="1">(2, 13)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Farm-worker Labor Camp</td><td align="left" valign="top" rowspan="1" colspan="1">4%</td><td align="left" valign="top" rowspan="1" colspan="1">(1, 10)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Houseless/Automobile</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">2%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 7)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Proximity to nearest highway or major road (n=100)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Less than one block (100 meters or one soccer field)</td><td align="left" valign="top" rowspan="1" colspan="1">68%</td><td align="left" valign="top" rowspan="1" colspan="1">(58, 77)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Between 1 and 5 blocks</td><td align="left" valign="top" rowspan="1" colspan="1">29%</td><td align="left" valign="top" rowspan="1" colspan="1">(20, 39)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">More than 5 blocks</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">3%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(1, 9)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Proximity to nearest farm (n=98)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Less than one block (100 meters or one soccer field)</td><td align="left" valign="top" rowspan="1" colspan="1">63%</td><td align="left" valign="top" rowspan="1" colspan="1">(53, 73)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Between 1 and 5 blocks</td><td align="left" valign="top" rowspan="1" colspan="1">27%</td><td align="left" valign="top" rowspan="1" colspan="1">(18, 36)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">More than 5 blocks</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">10%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(5, 18)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Do you or anyone in your housing unit use insect control sprays inside your home? (n=96)</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes (excludes respondents without housing)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">55%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(45, 65)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Do you or anyone in your housing unit use insect control sprays outside your home? (n=97)</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes (excludes respondents without housing)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">41%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(31, 52)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Where meals are typically cooked (n=95)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Home</td><td align="left" valign="top" rowspan="1" colspan="1">90%</td><td align="left" valign="top" rowspan="1" colspan="1">(85, 96)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Restaurant</td><td align="left" valign="top" rowspan="1" colspan="1">3%</td><td align="left" valign="top" rowspan="1" colspan="1">(0, 7)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Cafeteria</td><td align="left" valign="top" rowspan="1" colspan="1">3%</td><td align="left" valign="top" rowspan="1" colspan="1">(0, 7)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Fast-food restaurant or food truck</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">3%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 7)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Fuel used to cook (check all that apply) (n=70)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Electricity</td><td align="left" valign="top" rowspan="1" colspan="1">63%</td><td align="left" valign="top" rowspan="1" colspan="1">(51, 74)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Gas</td><td align="left" valign="top" rowspan="1" colspan="1">16%</td><td align="left" valign="top" rowspan="1" colspan="1">(8, 26)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Microwave</td><td align="left" valign="top" rowspan="1" colspan="1">7%</td><td align="left" valign="top" rowspan="1" colspan="1">(2, 16)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Kerosene Stove</td><td align="left" valign="top" rowspan="1" colspan="1">3%</td><td align="left" valign="top" rowspan="1" colspan="1">(0, 10)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Propane Stove</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">21%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(12, 32)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Fuel used to heat the home (check all that apply) (n=96)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Electricity</td><td align="left" valign="top" rowspan="1" colspan="1">72%</td><td align="left" valign="top" rowspan="1" colspan="1">(62, 81)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Gas</td><td align="left" valign="top" rowspan="1" colspan="1">4%</td><td align="left" valign="top" rowspan="1" colspan="1">(1, 10)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Wood or Charcoal-burning Stove</td><td align="left" valign="top" rowspan="1" colspan="1">5%</td><td align="left" valign="top" rowspan="1" colspan="1">(2, 12)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Kerosene Stove</td><td align="left" valign="top" rowspan="1" colspan="1">6%</td><td align="left" valign="top" rowspan="1" colspan="1">(2, 13)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Propane Stove</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">10%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(5, 18)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Main Drinking Water Source (n=100)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Public system/Service District</td><td align="left" valign="top" rowspan="1" colspan="1">18%</td><td align="left" valign="top" rowspan="1" colspan="1">(11, 27)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Well water/Private well</td><td align="left" valign="top" rowspan="1" colspan="1">12%</td><td align="left" valign="top" rowspan="1" colspan="1">(6, 20)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Bottled Water</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">66%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(56, 75)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">If the public system or well water is the main source, do you filter your drinking water? (n=30)</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">33%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(17, 53)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Have you noticed chipped paint where you are living? (n=97)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Yes (excludes respondents without housing)</td><td align="left" valign="top" rowspan="1" colspan="1">18%</td><td align="left" valign="top" rowspan="1" colspan="1">(10, 26)</td></tr></tbody></table></table-wrap><table-wrap position="float" id="T5"><label>Table 5:</label><caption><title>Cancer-Associated Occupational Exposures.</title><p id="P44">The 2017 Environmental Health Survey used community-based participatory action research strategies and snowball sampling of 100 adults in Knights Landing, California. Categorical data are presented as the proportion of respondents with 95% binomial confidence intervals (CI) and numerical data are presented as mean with CI. These survey questions were developed primarily from an agricultural health survey adapted to this community by <italic toggle="yes">promotora-researchers,</italic> so they are not comparable to data regularly collected by public health agencies.</p></caption><table frame="box" rules="cols"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th rowspan="3" align="left" valign="top" style="border-bottom: solid 1px" colspan="1">Cancer-Associated Occupational Exposures</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Environmental Health Survey</th></tr><tr><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Sample (n)= adults in Knights</italic>
<break/>
<italic toggle="yes">Landing recruitment zones</italic>
</th></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">% or Mean</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">95% CI</th></tr></thead><tbody><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">On an average working day, how many hours do you spend outside? (n=82) <xref rid="TFN3" ref-type="table-fn">#</xref></th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Up to 1 hour</td><td align="left" valign="top" rowspan="1" colspan="1">23%</td><td align="left" valign="top" rowspan="1" colspan="1">(14, 32)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">2 hours to 5 hours</td><td align="left" valign="top" rowspan="1" colspan="1">20%</td><td align="left" valign="top" rowspan="1" colspan="1">(11, 29)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">5 hours to 9 hours</td><td align="left" valign="top" rowspan="1" colspan="1">18%</td><td align="left" valign="top" rowspan="1" colspan="1">(10, 26)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">10 hours to 15 hours</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">39%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(28, 50)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">If over an hour is spent outside at work, how often do you use sun protection? (n=80)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">More than half of the time</td><td align="left" valign="top" rowspan="1" colspan="1">53%</td><td align="left" valign="top" rowspan="1" colspan="1">(42, 64)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Half or less of the time</td><td align="left" valign="top" rowspan="1" colspan="1">19%</td><td align="left" valign="top" rowspan="1" colspan="1">(10, 28)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Rarely or never</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">29%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(19, 39)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Ever worked in an agricultural setting? (n=100)</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">70%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(60, 79)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean number of years worked in agricultural setting (n=59)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">12</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(9, 15)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Ever handled pesticides at work? (n=97)</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">24%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(16, 33)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean number of years handling pesticides (n=18)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">8</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(4, 12)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">If ever handled pesticides at work, how often protective clothing was used? (n=23)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">More than half the time</td><td align="left" valign="top" rowspan="1" colspan="1">65%</td><td align="left" valign="top" rowspan="1" colspan="1">(43, 84)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Half or less than half the time</td><td align="left" valign="top" rowspan="1" colspan="1">17%</td><td align="left" valign="top" rowspan="1" colspan="1">((5, 39)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Rarely or never</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">17%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(5, 39)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">If ever handled pesticides at work, on days you handled, did you change your clothes or shoes before<break/>entering your home? (n=21)</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">81%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(58, 95)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">If ever handled pesticides at work, did you receive pesticide safety training in past year? (n=23)</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">78%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(56, 93)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">If received training (n=18), was the training in native language? Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">89%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(65, 99)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">If received training (n=18), was training offered by an entity unrelated to the employer? Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">89%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(65, 99)</td></tr><tr><th colspan="3" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">If ever handled pesticides at work, ever been to the doctor for pesticide exposure? (n=23)</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" rowspan="1" colspan="1">9%</td><td align="left" valign="top" rowspan="1" colspan="1">(1, 28)</td></tr></tbody></table><table-wrap-foot><fn id="TFN3"><label>#</label><p id="P45">During survey administration of questions about sun exposure, <italic toggle="yes">promotora-researchers</italic> expanded the concept of &#x0201c;working day&#x0201d; beyond employment leading to 82 respondents which is greater than the 63 respondents who reported employment (<xref rid="T3" ref-type="table">Table 3</xref>). <italic toggle="yes">Promotora-researcher&#x02019;s</italic> choice allowed inclusion of participants who volunteer, home-makers, or retired people who conduct substantial work on their own rural properties.</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="T6"><label>Table 6:</label><caption><title>Cancer-Associated Behaviors.</title><p id="P46">The 2017 Environmental Health Survey used community-based participatory action research strategies and snowball sampling of 100 adults in Knights Landing, California. Yolo County results were from random samples collected through the California Health Interview Survey (CHIS) (UCLA Center for Health Policy Research n.d.). Categorical data are presented as the proportion of respondents with 95% binomial confidence intervals (CI) and numerical data are presented as mean with CI. Significant differences between the Knights Landing and county samples are noted as * p &#x0003c; 0.05.</p></caption><table frame="box" rules="cols"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th rowspan="3" align="left" valign="top" style="border-bottom: solid 1px" colspan="1">Cancer-Associated Behaviors</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Environmental Health<break/>Survey</th><th colspan="2" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1">CHIS</th></tr><tr><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Sample (n)= adults in</italic>
<break/>
<italic toggle="yes">Knights Landing</italic>
<break/>
<italic toggle="yes">recruitment zones</italic>
</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Sample= randomly</italic>
<break/>
<italic toggle="yes">called adults in Yolo</italic>
<break/>
<italic toggle="yes">County</italic>
</th></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">% or Mean</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">95% CI</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">%</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">95% CI</th></tr></thead><tbody><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Tobacco Use</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 97</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 242, 2016- 2017</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1"><bold>Current Tobacco Smokers</bold> *</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">21%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(13, 30)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">6% <xref rid="TFN4" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(2, 9)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Years Smoked (n=19)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">15</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(10, 19)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Cigarettes per Day (n=19)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">16</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(7, 24)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1"><bold>Former Tobacco Smokers</bold> *</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">10%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(5, 18)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">17%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(10, 25)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Years Smoked (n=9)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">13</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(4, 23)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Other Smokers in Home or Housing Unit</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 96</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">--</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02002;Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">25%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(17, 35)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Cannabis Use</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 93</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 381, 2015- 2016</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">
<bold>Current Cannabis Smokers</bold>
</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">19%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(12, 29)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Years Smoked (n=17)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">19</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(12, 27)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Days of Use in Past 30 Days (n=16)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">23</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(17, 29)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">
<bold>Former Cannabis Smokers</bold>
</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">5%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(2, 12)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Years Smoked (n=3)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">7</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 19)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Days of Use in 30 Days (n=3)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">11</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 52)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1"><bold>Ever Smoked Cannabis</bold> *</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">25%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(17, 34)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">50%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(33, 67)</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Electronic Cigarette or Vaporizer Use</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 97</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 242, 2016- 2017</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">
<bold>Current Electronic Cigarette User</bold>
</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">5%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(2, 12)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">3% <xref rid="TFN4" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 6)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Years of Use (n=5)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">1</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(1, 2)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">
<bold>Former Electronic Cigarette User</bold>
</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">4%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(1, 10)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean Years of Use (n=4)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">1</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 2)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Chewing Tobacco Frequency</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 97</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">--</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Every day</td><td align="left" valign="top" rowspan="1" colspan="1">1%</td><td align="left" valign="top" rowspan="1" colspan="1">(0, 6)</td><td align="left" valign="top" rowspan="1" colspan="1">--</td><td align="left" valign="top" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Some days</td><td align="left" valign="top" rowspan="1" colspan="1">2%</td><td align="left" valign="top" rowspan="1" colspan="1">(0, 7)</td><td align="left" valign="top" rowspan="1" colspan="1">--</td><td align="left" valign="top" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Not at all</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">97%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(91, 99)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Alcohol Use</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n=42</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 252, 2017- 2018</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">
<bold>Binge-drink at least once in an average month</bold>
</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">45%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(30, 61)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">48%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(32, 65)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">&#x02003;Mean number of days binge-drink in average month</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">5</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(3, 7)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Daily Fruit and Vegetable Consumption</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 91</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">--</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">
<bold>Consume 5 or more servings of vegetables a day</bold>
</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">19%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(11, 28)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Mean servings of fruits and vegetables per day</td><td align="left" valign="top" rowspan="1" colspan="1">3</td><td align="left" valign="top" rowspan="1" colspan="1">(3, 4)</td><td align="left" valign="top" rowspan="1" colspan="1">--</td><td align="left" valign="top" rowspan="1" colspan="1">--</td></tr></tbody></table><table-wrap-foot><fn id="TFN4"><label>&#x022a5;</label><p id="P47">Publicly available 2016 AskCHIS Neighborhood Edition (UCLA Center for Health Policy Research n.d.) estimates are included here for reference for the two census tracts that represent Knights Landing and are not recommended for statistical comparisons: current smoker 9% (7, 11) and current electronic cigarette user 3% (2, 4). Conversely, publicly available 2020 California Health Maps data (<xref rid="R46" ref-type="bibr">University of California San Francisco n.d.</xref>) reveals a discrepancy in health agency monitoring estimates of adults who are current smokers: 7% for region Yolo 1 (A0766) and 16% for region Sutter (B0403).</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="T7"><label>Table 7:</label><caption><title>Environmentally Influenced Disease Burden and Health Care Utilization.</title><p id="P48">The 2017 Environmental Health Survey used community-based participatory action research strategies and snowball sampling of 100 adults in Knights Landing, California. Yolo County results were from random samples covered by the 2016 - 2017 California Health Interview Survey (CHIS, &#x02020;) (UCLA Center for Health Policy Research n.d.) or 2016 Behavioral Risk Factor Surveillance System (BRFSS, &#x02021;) data representing the Sacramento--Roseville--Arden-Arcade Metropolitan Statistical Area (<xref rid="R13" ref-type="bibr">Centers for Disease Control and Prevention n.d.</xref>). Categorical data are presented as the proportion of respondents with 95% binomial confidence intervals (CI). Significant differences between the Knights Landing and county samples are noted as * p &#x0003c; 0.5.</p></caption><table frame="box" rules="cols"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th rowspan="3" align="left" valign="top" style="border-bottom: solid 1px" colspan="1">Environmentally Influenced Disease Burden and<break/>Health Care Utilization</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Environmental Health<break/>Survey</th><th colspan="2" align="left" valign="middle" style="border-bottom: solid 1px" rowspan="1">CHIS or BRFSS</th></tr><tr><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Sample (n)= adults in KL</italic>
<break/>
<italic toggle="yes">recruitment zones</italic>
</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">
<italic toggle="yes">Sample= randomly</italic>
<break/>
<italic toggle="yes">called adults</italic>
</th></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">%</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">95% CI</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">%</th><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">95% CI</th></tr></thead><tbody><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Obesity *</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 96</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 242 &#x02020;</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">BMI (kg/m<sup>2</sup>) of 30 (obese) or more</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">38%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(28, 48)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">23% <xref rid="TFN5" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(18, 28)</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Diabetes diagnosed by medical professional</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 99</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 242 &#x02020;</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">14%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(7, 21)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">14% <xref rid="TFN5" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(10, 18)</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Asthma diagnosed by medical professional</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 99</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 242 &#x02020;</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">22%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(14, 30)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">21% <xref rid="TFN5" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(16, 26)</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Breathing issues in the past year</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 91</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">--</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Not at all</td><td align="left" valign="top" rowspan="1" colspan="1">75%</td><td align="left" valign="top" rowspan="1" colspan="1">(66, 84)</td><td align="left" valign="top" rowspan="1" colspan="1">--</td><td align="left" valign="top" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Less than every month</td><td align="left" valign="top" rowspan="1" colspan="1">5%</td><td align="left" valign="top" rowspan="1" colspan="1">(1, 10)</td><td align="left" valign="top" rowspan="1" colspan="1">--</td><td align="left" valign="top" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Every month</td><td align="left" valign="top" rowspan="1" colspan="1">10%</td><td align="left" valign="top" rowspan="1" colspan="1">(4, 16)</td><td align="left" valign="top" rowspan="1" colspan="1">--</td><td align="left" valign="top" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Every week</td><td align="left" valign="top" rowspan="1" colspan="1">7%</td><td align="left" valign="top" rowspan="1" colspan="1">(1, 12)</td><td align="left" valign="top" rowspan="1" colspan="1">--</td><td align="left" valign="top" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Every day</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">3%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 7)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Cancer Diagnosed by medical professional *</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 100</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 242 &#x02020;</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">2%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 5)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">9%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(5, 12)</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Family History of Cancer</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 96</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">--</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">49%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(39, 59)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">--</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Ever accessed colonoscopy <xref rid="TFN10" ref-type="table-fn">#</xref></th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 26</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 297 &#x02021;</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes -- Among respondents aged 50 - 75 years old</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">38%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(20, 57)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">64% <xref rid="TFN5" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(58, 71)</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Ever accessed mammogram <xref rid="TFN10" ref-type="table-fn">#</xref></th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 38</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 271 &#x02021;</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes -- Among women 40 years old and over</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">71%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(57, 85)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">74% <xref rid="TFN5" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(68, 81)</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Ever accessed pap smear <xref rid="TFN10" ref-type="table-fn">#</xref></th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 50</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 238 &#x02021;</th></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Yes -- Among women 21 - 65 years old</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">68%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(55, 81)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">78% <xref rid="TFN5" ref-type="table-fn">&#x022a5;</xref></td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(72, 84)</td></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Last regular medical checkup *</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 99</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 813 &#x02021;</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">One year ago or less</td><td align="left" valign="top" rowspan="1" colspan="1">83%</td><td align="left" valign="top" rowspan="1" colspan="1">(75, 90)</td><td align="left" valign="top" rowspan="1" colspan="1">66%</td><td align="left" valign="top" rowspan="1" colspan="1">(61, 70)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">More than 1 up to 2 years ago</td><td align="left" valign="top" rowspan="1" colspan="1">10%</td><td align="left" valign="top" rowspan="1" colspan="1">(4, 16)</td><td align="left" valign="top" rowspan="1" colspan="1">17%</td><td align="left" valign="top" rowspan="1" colspan="1">(13, 20)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">More than 2 years up to 5 years ago</td><td align="left" valign="top" rowspan="1" colspan="1">3%</td><td align="left" valign="top" rowspan="1" colspan="1">(0, 6)</td><td align="left" valign="top" rowspan="1" colspan="1">9%</td><td align="left" valign="top" rowspan="1" colspan="1">(7, 12)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">More than 5 years ago</td><td align="left" valign="top" rowspan="1" colspan="1">1%</td><td align="left" valign="top" rowspan="1" colspan="1">(0, 3)</td><td align="left" valign="top" rowspan="1" colspan="1">8%</td><td align="left" valign="top" rowspan="1" colspan="1">(6, 10)</td></tr><tr><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Never</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">3%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">(0, 6)</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">0%</td><td align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1"/></tr><tr><th align="left" valign="top" style="border-bottom: solid 1px" rowspan="1" colspan="1">Health insurance coverage</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 98</th><th colspan="2" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">n= 822 &#x02021;</th></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Yes -- Insurance, Medicare, or Medicaid coverage</td><td align="left" valign="top" rowspan="1" colspan="1">84%</td><td align="left" valign="top" rowspan="1" colspan="1">(76, 91)</td><td align="left" valign="top" rowspan="1" colspan="1">93%</td><td align="left" valign="top" rowspan="1" colspan="1">(91, 95)</td></tr></tbody></table><table-wrap-foot><fn id="TFN5"><label>&#x022a5;</label><p id="P49">Publicly available 2016 AskCHIS Neighborhood Edition (UCLA Center for Health Policy Research n.d.) estimates are included here for reference for the two census tracts that represent Knights Landing and are not recommended for statistical comparisons: obese 35% (29, 41), diabetes 12% (8, 15), and asthma 19% (13, 26). The publicly available 2020 California Health Maps data (<xref rid="R46" ref-type="bibr">University of California San Francisco n.d.</xref>) that follows demonstrates the consistency of health agency monitoring data:</p></fn><fn id="TFN6"><p id="P50"><italic toggle="yes">1)</italic> Adult obesity = 28% for both region Yolo 1 (A0766) and region Sutter (B0403).</p></fn><fn id="TFN7"><p id="P51"><italic toggle="yes">2)</italic> Percent of adults aged 50 - 75 years who have received a fecal occult blood test (FOBT) within the past year, a sigmoidoscopy within the past 5 years and a FOBT within the past 3 years, or a colonoscopy within the past 10 years = 64% for region Yolo 1 (A0766) and 62 % for region Sutter (B0403).</p></fn><fn id="TFN8"><p id="P52"><italic toggle="yes">3)</italic> Percent of women aged 50 - 74 years who have received a mammogram in the past 2 years = 77% for region Yolo 1 (A0766) and 74% for region Sutter (B0403).</p></fn><fn id="TFN9"><p id="P53"><italic toggle="yes">4)</italic> Percent of women aged 21 - 65 years who have not received a hysterectomy and have received a cervical screening test = 83% for region Yolo 1 (A0766) and 81% for region Sutter (B0403).</p></fn><fn id="TFN10"><label>#</label><p id="P54">Environmental Health Survey data cannot be compared to county data since the BRFSS data was narrowed respectively to colonoscopy in the past 10 years, mammogram in the past 2 years, and pap test in the past 3 years.</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="T8"><label>Table 8:</label><caption><title>Actions Toward KL Environmental Health Project Priorities from 2017 to 2023.</title><p id="P55">Dates of successful implementation indicate when enough resources were secured to initiate a service/program and do not include the community organizing time that predated this project.</p></caption><table frame="box" rules="rows"><colgroup span="1"><col align="left" valign="middle" span="1"/></colgroup><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Household exposures to environmental carcinogens:</bold><list list-type="bullet" id="L2"><list-item><p id="P56"><italic toggle="yes"><bold>2018</bold></italic> Research study to model pesticide exposure and sample households to fill regulatory monitoring data gaps. Samples were also collected after the Camp Fire in the neighboring organic region.</p></list-item><list-item><p id="P57"><italic toggle="yes"><bold>2021</bold></italic> One Health Center implemented pulmonary health monitoring program.</p></list-item><list-item><p id="P58"><italic toggle="yes"><bold>2021</bold></italic> County cleaned up environmental hazards found along river road that provided shelters to residents experiencing houselessness.</p></list-item><list-item><p id="P59"><italic toggle="yes"><bold>2021</bold></italic> Youth participatory action research documented the intersection of the COVID-19 pandemic and environmental justice in Knights Landing and Firebaugh agricultural communities.</p></list-item><list-item><p id="P60"><italic toggle="yes"><bold>2022</bold></italic> Community leaders partnered with UC Davis wildfire research group to inform studies of wildfire smoke exposures for pregnant people and to deploy do-it-yourself air filters into agricultural communities.</p></list-item></list>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Consumption of addictive substances:</bold><list list-type="bullet" id="L3"><list-item><p id="P61"><italic toggle="yes"><bold>2019</bold></italic> One Health Center launched smoking cessation services and cost-effective mental/emotional health resources.</p></list-item><list-item><p id="P62"><italic toggle="yes"><bold>2019</bold></italic> Research interviews with local smokers and non-smokers compared their experiences and goals for a healthier town.</p></list-item><list-item><p id="P63"><italic toggle="yes"><bold>2021</bold></italic> Support groups were strengthened for those experiencing addiction and their loved ones.</p></list-item><list-item><p id="P64"><italic toggle="yes"><bold>2021</bold></italic> One Health Center initiated a Mental Health Program.</p></list-item><list-item><p id="P65"><italic toggle="yes"><bold>2022</bold></italic> Research interviews focused on mental/emotional health for elderly people and their needs to connect with services and community.</p></list-item></list>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Cancer detection access:</bold><list list-type="bullet" id="L4"><list-item><p id="P66"><italic toggle="yes"><bold>2018</bold></italic> One Health Center developed an annual mammogram program.</p></list-item><list-item><p id="P67"><italic toggle="yes"><bold>2018</bold></italic> Research team conducted follow up community health assessment survey.</p></list-item><list-item><p id="P68"><italic toggle="yes"><bold>2019</bold></italic> Research team volunteered to encourage more engagement with rural communities for the UC Davis Cancer Center needs assessment.</p></list-item><list-item><p id="P69"><italic toggle="yes"><bold>2023</bold></italic> Research team conducted follow up community health assessment survey and formally committed to a 5-year cycle.</p></list-item></list>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Occupational safety:</bold>
<list list-type="bullet" id="L5"><list-item><p id="P70"><italic toggle="yes"><bold>2017</bold></italic>
<italic toggle="yes">Promotora-researcher</italic> word-of-mouth campaign encouraged farmworkers to keep their potentially contaminated work clothes away from their cars and homes.</p></list-item><list-item><p id="P71"><italic toggle="yes"><bold>2018</bold></italic> and <italic toggle="yes"><bold>2021</bold></italic> Western Center for Agricultural Health and Safety partnership brought occupational health resources to residents including pandemic essential worker resources.</p></list-item><list-item><p id="P72"><italic toggle="yes"><bold>2018, 2020, 2021</bold></italic> One Health Center promptly distributed personal protective equipment to essential workers during hazardous wildfire smoke periods and the COVID-19 pandemic.</p></list-item><list-item><p id="P73"><italic toggle="yes"><bold>2021</bold></italic> One Health Center and UC Davis Medical School launched monthly farmworker lung health monitoring with special consideration for working conditions, smoke, heat, and COVID-19 exposure.</p></list-item></list>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Housing quality including neighborhood isolation from health resources and services:</bold>
<list list-type="bullet" id="L6"><list-item><p id="P74"><italic toggle="yes"><bold>2017</bold></italic> Community- and student-volunteers conducted a food access health assessment, completed a community-led design process, and built a community garden.</p></list-item><list-item><p id="P75"><italic toggle="yes"><bold>2018</bold></italic> One Health Center created a health education program including healthy cooking classes.</p></list-item><list-item><p id="P76"><italic toggle="yes"><bold>2019</bold></italic>
<italic toggle="yes">Promotora-researchers</italic> partnered with local organizations to successfully lobby for a park revitalization and increased access to public transportation.</p></list-item><list-item><p id="P77"><italic toggle="yes"><bold>2020 - 2023</bold></italic> One Health Center and local nonprofits increased resource tables for residents (for example: food pantry, pet food, toiletries, and personal protective equipment).</p></list-item></list>
</td></tr></tbody></table></table-wrap><boxed-text id="BX1" position="float"><caption><title>Key Points:</title></caption><list list-type="bullet" id="L7"><list-item><p id="P78">Agricultural community residents led a low-budget environmental health survey to develop evidence-based public health interventions.</p></list-item><list-item><p id="P79">Communities can use a carcinogen exposure survey to prioritize and develop actions that reduce cancer burdens in their neighborhood.</p></list-item><list-item><p id="P80">When residents&#x02019; priorities drive research directions, community solutions can be promptly launched within limited resource communities.</p></list-item></list></boxed-text></floats-group></article>