Epidemiological surveys conducted in general populations have found that the prevalence of depression is about 9% in the United States. World Health Organization has projected that depression will be leading cause of disease burden by the year 2030. Growing evidence suggests that sedentary lifestyle is an important risk factor of depression among adults. The relationship between television watching/computer use and depression in US adults is still unknown. The objective of this study was to assess the relationship between television watching/computer use and depression. This is a cross-sectional study that used the secondary data from the National Health and Nutritional Examination Survey (NHANES) (2011/2012). Participants were 3201 US adults who were 20 years or more. Self-reported Patient Health Questionnaire-9 [PHQ-9] was used to classify depression level; self-reported hours of watching TV and use of computer/day, and demographic information were obtained from NHANES data set. SAS®9.4was used to perform all statistical analyses and final model selection procedure. Depression was found to be significantly higher among female. Results showed that moderate or severe depression level was associated with higher time spent on TV watching and use of computer (> 6 h/day) (adjusted odds ratio: 2.3, 95% CI: 1.602-3.442). Duration of screen time was significantly associated when all covariates were adjusted. TV watching and computer use can predict the depression level among adults. Prospective studies and measurement of factors such as: work place sitting, social relationship, and family history of depression are warranted.

Background: Louisiana in the summer of 2020 had the highest per capita case count for COVID-19 in the United States and COVID-19 deaths disproportionately affects the African American population. Neighborhood deprivation has been observed to be associated with poorer health outcomes. The purpose of this study was to examine the relationship between neighborhood deprivation and COVID-19 in Louisiana. Methods: The Area Deprivation Index (ADI) was calculated and used to classify neighborhood deprivation at the census tract level. A total of 17 US census variables were used to calculate the ADI for each of the 1148 census tracts in Louisiana. The data were extracted from the American Community Survey (ACS) 2018. The neighborhoods were categorized into quintiles as well as low and high deprivation. The publicly available COVID-19 cumulative case counts by census tract were obtained from the Louisiana Department of Health website on July 31, 2020. Descriptive and Poisson regression analyses were performed. Results: Neighborhoods in Louisiana were substantially different with respect to deprivation. The ADI ranged from 136.00 for the most deprived neighborhood and –33.87 in the least deprived neighborhood. We observed that individuals residing in the most deprived neighborhoods had almost a 40% higher risk of COVID-19 compared to those residing in the least deprived neighborhoods. Conclusion: While the majority of previous studies were focused on very limited socio-environmental factors such as crowding and income, this study used a composite area-based deprivation index to examine the role of neighborhood environment on COVID-19. We observed a positive relationship between neighborhood deprivation and COVID-19 risk in Louisiana. The study findings can be utilized to promote public health preventions measures besides social distancing, wearing a mask while in public and frequent handwashing in vulnerable neighborhoods with greater deprivation.

Background: The overall survival rate of prostate cancer (PCa) has improved over the past decades. However, huge socioeconomic and racial disparities in overall and prostate cancer‐specific mortality exist. The neighborhood‐level factors including socioeconomic disadvantage and lack of access to care may contribute to disparities in cancer mortality. This study examines the impact of neighborhood deprivation on mortality among PCa survivors.Methods: North Carolina–Louisiana Prostate Cancer Project (PCaP) data were used. A total of 2113 men, 1046 AA and 1067 EA, with PCa were included in the analysis. Neighborhood deprivation was measured by the Area Deprivation Index (ADI) at the census block group level using data from the US Census Bureau. Quintiles of ADI were created. Cox proportional hazards and competing risk models with mixed effects were performed to estimate the effect of neighborhood deprivation on all‐cause and PCa‐specific mortality adjusted for age, race, study site, insurance status, and comorbidities.Results: Participants living in the most deprived neighborhoods had an increased risk for all‐cause mortality (quintiles 4 + 5: adjusted hazard ratio [aHR] = 1.51, 95% confidence interval [CI] = 1.16–1.96) compared to those in the least deprived (quintile 1) neighborhoods. The risk of prostate cancer‐specific mortality was also higher among those living in the deprived neighborhoods (quintiles 4 + 5: aHR = 1.90, 95% CI = 1.10–3.50) than those in the least deprived neighborhood.Conclusions: The findings suggest neighborhood‐level resources or health interventions are essential to improve survival among men with PCa. Additional research should focus on the mechanisms of how the neighborhood environment affects mortality.

Background: Racial segregation is linked to poorer neighborhood quality and adverse health conditions among minorities, including worse cancer outcomes. We evaluated relationships between race, neighborhood social disadvantage, and cancer survival. Methods: We calculated overall and cancer-specific survival for 11,367 non-Hispanic Black (NHB) and 29,481 non-Hispanic White (NHW) individuals with breast, colorectal, lung, or prostate cancer using data from the Metropolitan Detroit Cancer Surveillance System. The area deprivation index (ADI) was used to measure social disadvantage at the census block group level, where higher ADI is associated with poorer neighborhood factors. Associations between ADI and survival were estimated using Cox proportional hazards mixed-effects models accounting for geographic grouping and adjusting for demographic and clinical factors. Results: Increasing ADI quintile was associated with increased overall mortality for all four cancer sites in multivariable-adjusted models. Stratified by race, these associations remained among breast (NHW: HR = 1.16, P < 0.0001; NHB: HR = 1.20, P < 0.0001), colorectal (NHW: HR = 1.11, P < 0.0001; NHB: HR = 1.09, P = 0.00378), prostate (NHW: HR = 1.18, P < 0.0001; NHB: HR = 1.18, P < 0.0001), and lung cancers (NHW: HR = 1.06, P < 0.0001; NHB: HR = 1.07, P = 0.00177). Cancer-specific mortality estimates were similar to overall mortality. Adjustment for ADI substantially attenuated the effects of race on mortality for breast [overall proportion attenuated (OPA) = 47%, P < 0.0001; cancer-specific proportion attenuated (CSPA) = 37%, P < 0.0001] prostate cancer (OPA = 51%, P < 0.0001; CSPA = 56%, P < 0.0001), and colorectal cancer (OPA = 69%, P = 0.032; CSPA = 36%, P = 0.018). Conclusions: Area-level socioeconomic disadvantage is related to cancer mortality in a racially diverse population, impacting racial differences in cancer mortality. Impact: Understanding the role of neighborhood quality in cancer survivorship could improve community-based intervention practices.

Background: The impact of ongoing efforts to decrease opioid use on patients with cancer remains undefined. Our objective was to determine trends in new and additional opioid use in patients with and without cancer. Methods: This retrospective cohort study used data from Surveillance, Epidemiology, and End Results program–Medicare for opioid-naive patients with solid tumor malignancies diagnosed from 2012 through 2017 and a random sample of patients without cancer. We identified 238 470 eligible patients with cancer and further focused on 4 clinical strata: patients without cancer, patients with metastatic cancer, patients with nonmetastatic cancer treated with surgery alone (“surgery alone”), and patients with nonmetastatic cancer treated with surgery plus chemotherapy or radiation therapy (“surgery+”). We identified new, early additional, and long-term additional opioid use and calculated the change in predicted probability of these outcomes from 2012 to 2017. Results: New opioid use was higher in patients with cancer (46.4%) than in those without (6.9%) (P < .001). From 2012 to 2017, the predicted probability of new opioid use was more stable in the cancer strata (relative declines: 0.1% surgery alone; 2.4% surgery+; 8.8% metastatic cancer), than in the noncancer stratum (20.0%) (P < .001 for each cancer to noncancer comparison). Early additional use declined among surgery patients (‒14.9% and ‒17.5% for surgery alone and surgery+, respectively) but was stable among patients with metastatic disease (‒2.8%, P = .50). Conclusions: Opioid prescribing declined over time at a slower rate in patients with cancer than in patients without cancer. Our study suggests important but tempered effects of the changing opioid climate on patients with cancer.

Introduction: Financial toxicity (FT) is a growing concern among cancer survivors that adversely affects the quality of life and survival. Individuals diagnosed with aggressive cancers are often at a greater risk of experiencing FT. The objectives of this study were to estimate FT among prostate cancer (PCa) survivors after 10−15 years of diagnosis, assess the relationship between PCa aggressiveness at diagnosis and FT, and examine whether current cancer treatment status mediates the relationship between PCa aggressiveness and FT.Methods: PCa patients enrolled in the North Carolina‐Louisiana Prostate Cancer Project (PCaP) were recontacted for long‐term follow‐up. The prevalence of FT in the PCaP cohort was estimated. FT was estimated using the COmprehensive Score for Financial Toxicity, a validated measure of FT. The direct effect of PCa aggressiveness and an indirect effect through current cancer treatment on FT was examined using causal mediation analysis.Results: More than one‐third of PCa patients reported experiencing FT. PCa aggressiveness was significantly independently associated with high FT; high aggressive PCa at diagnosis had more than twice the risk of experiencing FT than those with low or intermediate aggressive PCa (adjusted odds ratio [aOR] = 2.13, 95% CI = 1.14−3.96). The proportion of the effect of PCa aggressiveness on FT, mediated by treatment status, was 10%, however, the adjusted odds ratio did not indicate significant evidence of mediation by treatment status (aOR = 1.05, 95% CI = 0.95−1.20).Conclusions: Aggressive PCa was associated with high FT. Future studies should collect more information about the characteristics of men with high FT and identify additional risk factors of FT.