Purpose The objective of this study was to assess perceptions, health behaviors, and disruptions related to the COVID‐19 pandemic in a largely rural, Midwestern state, and to examine differences between rural and urban respondents. Methods A questionnaire was mailed August 2020 to a sample of 10,009 registered voters in Iowa ages 18‐100 years, with oversampling from 6 select rural counties. Previously validated and tested items assessed COVID‐19 precautions, health care disruptions, emotional reactions, health behavior changes, telehealth and experiences with the internet, and demographic characteristics. Findings There were 4,048 respondents (40% response rate); 65% were rural and 35% were urban residents. The average age of respondents was 58.3 years and 45% of respondents identified as female. Rural respondents reported less concern about COVID‐19 in their community (29% vs 40%, P <.001) and lower perceived importance of social distancing (51% vs 64%, P <.001). Urban respondents more often reported experiencing disruption to daily living, stronger negative emotional reactions, and displayed more pronounced behavior change compared to their rural counterparts. For example, urban respondents reported more pandemic‐related job losses (6% vs 4%, P = .05), disruptions to daily activities (48% vs 35%, P <.001), and use of telehealth services during the pandemic (24% vs 16%, P <.001). Conclusions The majority of respondents reported disruptions to normal activities, medical appointment cancellations, and emotional distress during the first 6 months of the pandemic. The impact of the pandemic on urban residents appeared to be greater than for rural respondents. Timing of pandemic spread and varying beliefs are potential explanations.

ObjectiveTo determine if there is a difference in overall survival of patients with epithelial ovarian cancer in rural, urban, and metropolitan settings in the United States.MethodsWe performed a retrospective cohort study using 2004–2016 National Cancer Database (NCDB) data including high and low grade, stage I-IV disease. Bivariate analyses used Student’s t-test for continuous variables and χ2 test for dichotomous variables. Kaplan-Meier curves estimated survival of patients based on location of residence, and univariate analyses using Cox proportional HR assessed survival based on baseline characteristics. Multivariate analysis was performed to account for significant covariates. Propensity score matching was used to validate the multivariate survival model. For all tests, p<0.05 was considered statistically significant.ResultsA total of 111 627 patients were included with a mean age of 62.5 years for metroolitan (range 18–90), 64.0 years for rural (range 19–90) and 63.2 years for urban areas (range 18–90). Of all patients included, 94 290 were in a metropolitan area (counties >1 million population or 50 000–999 999), 15 386 were in an urban area (population of 10 000–49 999), and 1951 were in a rural area (non-metropolitan/non-core population). Univariate Cox proportional hazards models showed clinically significant differences in survival in patients from metropolitan, urban, and rural areas. Multivariate Cox proportional hazards models showed a clinically significant increase in HRs for patients in rural settings (HR 1.17; 95% CI 1.06 to 1.29). Increasing age and stage, non-insured status, non-white race, and comorbidity were also significant for poorer survival.ConclusionPatients with ovarian cancer who live in rural settings with small populations and greater distance to tertiary care centers have poorer survival. These differences hold after controlling for stage, age, and other significant risk factors related to poorer outcomes. To improve clinical outcomes, we need further studies to identify which of these factors are actionable.

Objectives: Rural ovarian cancer patients experience worse survival compared to urban patients. We assessed whether distance to gynecologic oncology specialists was associated with survival for patients in a rural state. Methods: Demographic, tumor, and treatment characteristics were extracted from the Iowa Cancer Registry for patients diagnosed between 1990 and 2018. Data were linked to the county-level 2018–2019 Area Health Resource File (number of surgeons and hospital beds per 100,000 population). Rurality was defined using 2013 Rural-Urban Continuum Codes; distance to the nearest gynecologic oncologist was calculated from the centroid of the county of residence to the centroid of the nearest county with a high volume health care center with a gynecologic oncologist. Associations with survival were assessed using multivariable Cox proportional hazards models. Results: Analyses included 1,562 ovarian cancer patients. Mean distance to gynecologic oncology was 60.8 miles, and median survival was 23 months. Unadjusted models showed increased distance from gynecologic oncology had progressively greater risk of death 30–49 miles (hazard ratio [HR] = 1.09, confidence interval [CI]: 1.04–1.15), 50–69 miles (HR = 1.19, CI: 1.07–1.32), 70+ miles (HR = 1.30, CI: 1.11–1.51). In adjusted models, association of distance to gynecologic oncology with risk of death was not significant; however, more advanced cancer stage and age, unmarried status, and higher county-level poverty were independently associated with increased risk of death. Conclusions: Above and beyond demographics and stage, distance to gynecologic oncology care was not an independent predictor of ovarian cancer survival. Further studies are needed to determine how to mitigate the factors contributing to worsened ovarian cancer survival among rural patients.

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