There are well-established disparities in cancer incidence and outcomes by race/ethnicity that result from the interplay between structural, socioeconomic, socio-environmental, behavioural and biological factors. However, large research studies designed to investigate factors contributing to cancer aetiology and progression have mainly focused on populations of European origin. The limitations in clinicopathological and genetic data, as well as the reduced availability of biospecimens from diverse populations, contribute to the knowledge gap and have the potential to widen cancer health disparities. In this review, we summarise reported disparities and associated factors in the United States of America (USA) for the most common cancers (breast, prostate, lung and colon), and for a subset of other cancers that highlight the complexity of disparities (gastric, liver, pancreas and leukaemia). We focus on populations commonly identified and referred to as racial/ethnic minorities in the USA—African Americans/Blacks, American Indians and Alaska Natives, Asians, Native Hawaiians/other Pacific Islanders and Hispanics/Latinos. We conclude that even though substantial progress has been made in understanding the factors underlying cancer health disparities, marked inequities persist. Additional efforts are needed to include participants from diverse populations in the research of cancer aetiology, biology and treatment. Furthermore, to eliminate cancer health disparities, it will be necessary to facilitate access to, and utilisation of, health services to all individuals, and to address structural inequities, including racism, that disproportionally affect racial/ethnic minorities in the USA.

Background Diabetes group clinics can effectively control hypertension, but data to support glycemic control is equivocal. This study evaluated the comparative effectiveness of two diabetes group clinic interventions on glycosolated hemoglobin (HbA1c) levels in primary care. Methods Participants (n = 87) were recruited from a diabetes registry of a single regional VA medical center to participate in an open, randomized comparative effectiveness study. Two primary care based diabetes group interventions of three months duration were compared. Empowering Patients in Care (EPIC) was a clinician-led, patient-centered group clinic consisting of four sessions on setting self-management action plans (diet, exercise, home monitoring, medications, etc.) and communicating about progress with action plans. The comparison intervention consisted of group education sessions with a diabetes educator and dietician followed by an additional visit with one’s primary care provider. HbA1c levels were compared post-intervention and at one-year follow-up. Results Participants in the EPIC intervention had significantly greater improvements in HbA1c levels immediately following the active intervention (8.86 to 8.04 vs. 8.74 to 8.70, mean [SD] between-group difference 0.67±1.3, P=.03) and these differences persisted at 1 year follow-up (.59±1.4, P=.05). A repeated measures analysis using all study time points found a significant time-by-treatment interaction effect on HbA1c levels favoring the EPIC intervention (F(2,85) =3.55, P= .03). The effect of the time-by-treatment interaction appears to be partially mediated by diabetes self-efficacy (F(1,85) =10.39, P= .002). Conclusions Primary care based diabetes group clinics that include structured goal-setting approaches to self-management can significantly improve HbA1c levels post-intervention and maintain improvements for 1-year. Trial registration ClinicalTrials.gov Identifier: NCT00481286

Purpose Rural US adults have increased risk of poor outcomes after cancer, including increased cancer mortality. Rural-urban differences in health behaviors have been identified in the general population and may contribute to cancer health disparities, but have not yet been examined among US survivors. We examined rural-urban differences in health behaviors among cancer survivors and associations with self-reported health and health-related unemployment. Methods We identified rural (n=1,642) and urban (n=6,162) survivors from the cross-sectional National Health Interview Survey (2006–2010) and calculated the prevalence of smoking, physical activity, overweight/obesity, and alcohol consumption. Multivariable models were used to examine the associations of fair/poor health and health-related unemployment with health behaviors and rural-urban residence. Results The prevalence of fair/poor health (rural 36.7%, urban 26.6%), health-related unemployment (rural 18.5%, urban 10.6%), smoking (rural 25.3%, urban 15.8%), and physical inactivity (rural 50.7%, urban 38.7%) was significantly higher in rural survivors (all p<.05); alcohol consumption was lower (rural 46.3%, urban 58.6%), and there were no significant differences in overweight/obesity (rural 65.4%, urban 62.6%). All health behaviors were significantly associated with fair/poor health and health-related unemployment in both univariate and multivariable models. After adjustment for behaviors, rural survivors remained more likely than urban survivors to report fair/poor health (OR= 1.21, 95%CI 1.03–1.43) and health-related unemployment (OR= 1.49, 95%CI 1.18–1.88). Conclusions Rural survivors may need tailored, accessible health promotion interventions to address health compromising behaviors and improve outcomes after cancer.

Asian survivors report poorer follow-up care communication and care quality. More research is needed to identify contributing factors beyond PPC, such as cultural influences and medical system factors.