Yao, Yingwei

Introduction The Florida-California Cancer Research, Education, and Engagement (CaRE 2 ) Health Equity Center is a triad partnership committed to increasing institutional capacity for cancer disparity research, the diversity of the cancer workforce, and community empowerment. This article provides an overview of the structure, process innovations, and initial outcomes from the first 4 years of the CaRE 2 triad partnership. Methods CaRE 2 serves diverse populations in Florida and California using a “molecule to the community and back” model. We prioritize research on the complex intersection of biological, environmental, and social determinants health, working together with scientific and health disparities communities, sharing expertise across institutions, bidirectional training, and community outreach. Partnership progress and outcomes were assessed using mixed methods and four Program Steering Committee meetings. Results Research capacity was increased through development of a Living Repository of 81 cancer model systems from minority patients for novel cancer drug development. CaRE 2 funded 15 scientific projects resulting in 38 publications. Workforce diversity entailed supporting 94 cancer trainees (92 URM) and 34 ESIs (32 URM) who coauthored 313 CaRE 2 -related publications and received 48 grants. Community empowerment was promoted via outreaching to more than 3000 individuals, training 145 community cancer advocates (including 28 Community Scientist Advocates), and publishing 10 community reports. CaRE 2 members and trainees together have published 639 articles, received 61 grants, and 57 awards. Conclusion The CaRE 2 partnership has achieved its initial aims. Infrastructure for translational cancer research was expanded at one partner institution, and cancer disparities research was expanded at the two cancer centers.

Abstract Purpose: Smoking rates are higher in rural regions compared to urban regions. Given the mobility within the United States, rural norms around tobacco use may persist even after individuals move to urban areas. Little research is available regarding the difference in smoking history by demographics and rural residence history. The purpose of the study was to examine the influence of age, race, gender, and rural residence history on smoking history. Methods: In a cross-sectional study, we surveyed 1,786 adults using two sampling approaches: representative panels and a community-engaged sample. Participants were asked to complete the Florida Health and Ancestry Study (FHAS) survey through a link or by the phone with a research assistant. The smoking history question asked whether participants had smoked 100 cigarettes in their lifetime (yes/no). The rural residence question asked participants to indicate (yes/no) whether they have lived in a rural or farming community, or on a farm. We examined associations of smoking history with demographic variables using the Chi-square test and logistic regression including as predictors age group (young=18-30, middle age=31-50, old=51+ years), gender, race, and rural living by gender. Results: Participants were mostly White (16% Black, 84% White), female (47% male) and with a mean age around 50 years (mean 47.9±17.5 years, ranged 18 to 91). 36% of the sample reported a history of rural residence, and 51% reported that they had not smoked 100 cigarettes in their lifetime. A larger proportion of males (61%) smoked at least 100 cigarettes compared to females (37%) (p<.001). A significantly larger proportion of White participants (50%) smoked at least 100 cigarettes in their lifetime than Black participants (39%) (p=.001). A larger proportion of participants who had lived in a rural place (53%) had smoked at least 100 cigarettes compared to those who had not lived in a rural place (46%) (p=.005). Difference in mean age for those with or without a history of smoking 100 cigarettes was not statistically significant in this sample (p=.12). Logistic regression analysis revealed that relative to the old age group, the young age group was less likely (p<.001) and the middle age group was more likely (p=.002) to have smoked 100 cigarettes. Males (p<.001) were more likely to have smoked 100 cigarettes than females. Rural residence was associated with smoking among females (p<.001) but not among males (p=.70). Adjusting for other predictors, the association with race was not statistically significant in this sample (p=.06). Conclusion: Findings that the age group 18-30 years is more likely to have avoided becoming smokers is encouraging but must be analyzed more thoroughly relative to possible use of e-cigarettes and other tobacco products. To reduce individuals becoming smokers, we recommend increased cancer control efforts targeted to males in general and to females with a rural residence history. Additional research is planned to examine additional smoking variables and compare them to national data. Citation Format: Tyra Reed, Destiny Gordon, Brenda W. Dyal, Keesha Powell-Roach, Miriam O. Ezenwa, Versie Johnson-Mallard, Janice L. Krieger, Folakemi T. Odedina, Yingwei Yao, Diana J. Wilkie. Demographic factors and rural residence history associated with smoking history [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-012.