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Men’s poor health behaviors are an increasingly prevalent issue with long-term consequences. This study broadly samples Canadian men to obtain information regarding health behaviors as a predictor of downstream medical comorbidities. A survey of Canadian men included questions regarding demographics, comorbidities, and health behaviors (smoking and alcohol consumption, sleep and exercise behaviors, and dietary habits). Health behaviors were classified as either healthy or unhealthy based upon previous studies and questionnaire thresholds. Multivariate regression was performed to determine predictors for medical comorbidities. The 2,000 participants were aged 19–94 (median 48, interquartile range 34–60). Approximately half (47.4%) were regular smokers, 38.7% overused alcohol, 53.9% reported unhealthy sleep, 48.9% had low levels of exercise, and 61.8% had unhealthy diets. On multivariate analysis, regular smoking predicted heart disease (OR 2.08, p < .01), elevated cholesterol (OR 1.35, p = .02), type 2 diabetes (OR 1.57, p = .02), osteoarthritis (OR 1.43, p = .04), and depression (OR 1.62, p < .01). Alcohol overuse predicted hypertension (OR 1.40, p < .01) and protected against type 2 diabetes (OR 0.61, p < .01). Unhealthy sleep predicted hypertension (OR 1.46, p < .01), erectile dysfunction (OR 1.50, p = .04), and depression (OR 1.87, p < .01). Low levels of exercise predicted hypertension (OR 1.30, p = .03) and elevated cholesterol (OR 1.27, p = .05). Finally, unhealthy diet predicted depression (OR 1.65, p < .01). This study confirms the association of poor health behaviors and comorbidities common to middle-aged and older men. The results emphasize the potential scope of targeted gender-sensitized public awareness campaigns and interventions to reduce common male disease, morbidity, and mortality.

The relationship of social determinants of health, Appalachian residence, and prostate cancer treatment delay among Tennessee adults is relatively unknown. We used multivariate logistic regression on 2005–2015 Tennessee Cancer Registry data of adults aged ≥18 diagnosed with prostate cancer. The outcome of treatment delay was more than 90 days without surgical or nonsurgical intervention from date of diagnosis. Social determinants in the population-based registry were race (White, Black, Other) and marital status (single, married, divorced/separated, widow/widower). Tennessee residence was classified as Appalachian versus non-Appalachian (urban/rural). Covariates include age at diagnosis (18–54, 54–69, ≥70), health insurance type (none, public, private), derived staging of cancer (localized, regional, distant), and treatment type (non-surgical/surgical). We found that Black and divorced/separated patients had 32% (95% confidence interval [CI]: 1.22–1.42) and 15% (95% CI: 1.01–1.31) increased odds to delay prostate cancer treatment. Patients were at decreased odds of treatment delay when living in an Appalachian county, both urban (odds ratio [OR] = 0.89, 95% CI: 0.82–0.95) and rural (OR = 0.83, 95% CI: 0.78–0.89), diagnosed at ≥70 (OR = 0.59, 95% CI: 0.53–0.66), and received surgical intervention (OR = 0.72, 95% CI: 0.68–0.76). Our study was among the first to comprehensively examine prostate cancer treatment delay in Tennessee, and while we do not make clinical recommendations, there is a critical need to further explore the unique factors that may propagate disparities. Prostate cancer treatment delay in Black patients may be indicative of ongoing health and access disparities in Tennessee, which may further affect quality of life and survivorship among this racial group. Divorced/separated patients may need tailored interventions to improve social support.

Tobacco use is the leading lifestyle-related cause of death in the United States. We analyzed correlates of smoking and vaping tobacco in the National HIV Behavioral Surveillance (NHBS) among men who have sex with men (MSM) in San Francisco in 2014 ( n = 410) using multivariable logistic regression models. We found that more than two in five MSM (41%) smoked or vaped. Smoking was greater for men of color (46% vs. 35%; p = .02); those with annual income below $50,000 (47% vs. 34%; p = .01); those without a college education (51% vs. 30%; p < .01); and the uninsured (55% vs. 38%; p = .04). In multivariable analyses, greater odds of smoking were observed among men living with HIV (adjusted odds ratio [aOR] = 1.7; 95% CI [1.00, 2.8]); men who reported cocaine use (aOR = 3.1; 95% CI [1.9, 5.0]), and men who reported greater number of alcohol drinks on a drinking day (aOR = 1.2; 95% CI [1.05, 1.29]). Lower odds of smoking were observed for men who completed college (aOR = 0.57; 95% CI [0.36, 0.88]). Greater odds of vaping were observed among men who reported meth use (aOR = 3.01; 95% CI [1.65, 5.50]). Lower odds of vaping were observed among men who completed college (aOR = 0.55; 95% CI [0.32, 0.98]). In conclusion, the prevalence of smoking and vaping among MSM is extremely high, particularly HIV-positive MSM. MSM who smoked and vaped were more likely to be racial and ethnic minorities, have lower socioeconomic status, and report more substance and alcohol use. These findings highlight the need to develop strategies effectively addressing the high rates of cigarette smoking and vaping among MSM, particularly among minority MSM and MSM living with HIV.

Men continue to bear disproportionate accounts of HIV diagnoses. The Patient Protection and Affordable Care act aims to address health care disparities by recommending preventative services, including HIV screening, expanding community health centers, and increasing the healthcare workforce. This study examined the decision making of physician and primary care health providers to provide HIV screenings. A quasi-experimental design was used to estimate the effects of the Affordable Care Act on provider-initiated HIV screening. The National Ambulatory Medical Care Survey was used to examine HIV screening characteristic from two time periods: 2009 and 2012. Logistic regression indicated that patient and provider characteristics were associated with likelihood of being prescribed HIV screening. Non-Hispanic Black men were more likely to be prescribed HIV screening compared to non-Hispanic White men (odds ratio [OR] = 12.33, 95% confidence interval [CI; 4.42, 34.46]). Men who see primary care providers were more likely to be prescribed HIV screening compared to men not seeing a primary care provider (OR = 5.94, 95% CI [2.15, 16.39]). Men between the ages of 19 and 22 were more likely to be prescribed HIV screening compared to men between the ages of 15 and 18 (OR = 6.59, 95% CI [2.16, 20.14]). Men between the ages of 23 and 25 were more likely to be prescribed HIV screening compared with men between the ages of 15 and 18 (OR = 10.13, 95% CI [3.34, 30.69]). Health education programs identifying men at increased risk for contracting HIV may account for the increased screening rates in certain populations. Future research should examine age disparities surrounding adolescent and young men HIV screening.

Introduction: In our study, we aimed to investigate the association between a traumatic brain injury (TBI) and subsequent erectile dysfunction (ED). This is a population-based study using the claims dataset from The National Health Insurance Research Database. Methods: We included 72,642 patients with TBI aged over 20 years, retrospectively, selected from the longitudinal health insurance database during 2000–2010, according to the ICD-9-CM. The control group consisted of 217,872 patients without TBI that were randomly chosen from the database at a ratio of 1:3, with age- and index year matched. Cox proportional hazards analysis was used to estimate the association between the TBI and subsequent ED. Results: After a 10-year follow-up, the incidence rate of ED was higher in the TBI patients when compared with the non-TBI control group (24.66 and 19.07 per 100,000, respectively). Patients with TBI had a higher risk of developing ED than the non-TBI cohort after the adjustment of the confounding factors, such as age, comorbidity, residence of urbanization and locations, seasons, level of care, and insured premiums (adjusted hazard ratio (HR) = 2.569, 95% CI [1.890, 3.492], p < .001). Conclusion: This is the first study using a comprehensive nationwide database to analyze the association of ED and TBI in the Asian population. After adjusted the confounding factors, patients with TBI have a significantly higher risk of developing ED, especially organic ED, than the general population. This finding might remind clinicians that it’s crucial in early identification and treatment of ED in post-TBI patients.