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Objective: This study sought to determine whether demographic and clinical factors for suicidal ideation (SI) and suicide attempts (SA) in adults vary across different census divisions in the US., Methods: A nationwide cohort was constructed using commercial health insurance claims data of adults aged 25-64 years with at least one mental health or substance use disorder-related outpatient visit between 2014 and 2015. Survival analysis was used to study how the association of demographic and clinical factors on SI and SA vary by geographic divisions., Results: The Mountain Division had the highest rates of SI and SA in almost all observed time intervals after the index visit. The Northeast region and the West coast had the lowest rates. For both SI and SA, we observed strong interaction effects between geographic division and urbanicity (χ2(152) = 188.14, p = 0.02; χ2(152) = 196.20, p = 0.01, respectively). In particular, urbanicity was a risk factor for SI in the West North Central (HR = 0.71, 95% CI: [0.50, 0.99]) and the Pacific (HR = 0.54, 95% CI: [0.40, 0.74]) Divisions. Urbanicity was also a risk factor for SA in the West North Central Division (HR = 0.39, 95% CI: [0.16, 0.95]), but a protective factor for SA in the Mountain Division (HR = 1.71, 95% CI: [1.11, 2.63])., Conclusions: The association between urbanicity and SI and SA varied by US geography. Future suicide prevention efforts should include a focus on urban adults in the West North Central and the Pacific Divisions, and rural adults in the Mountain Division., Competing Interests: Declaration of competing interest Dr. Pathak is the Cofounder of Iris OB Health Inc., New York and has equity ownership. The other authors have nothing to declare., (Copyright © 2025 Elsevier Ltd. All rights reserved.)

Background: A significant number of late middle-aged adults with depression have a high illness burden resulting from chronic conditions which put them at high risk of hospitalization. Many late middle-aged adults are covered by commercial health insurance, but such insurance claims have not been used to identify the risk of hospitalization in individuals with depression. In the present study, we developed and validated a non-proprietary model to identify late middle-aged adults with depression at risk for hospitalization, using machine learning methods., Methods: This retrospective cohort study involved 71,682 commercially insured older adults aged 55-64 years diagnosed with depression. National health insurance claims were used to capture demographics, health care utilization, and health status during the base year. Health status was captured using 70 chronic health conditions, and 46 mental health conditions. The outcomes were 1- and 2-year preventable hospitalization. For each of our two outcomes, we evaluated seven modelling approaches: four prediction models utilized logistic regression with different combinations of predictors to evaluate the relative contribution of each group of variables, and three prediction models utilized machine learning approaches - logistic regression with LASSO penalty, random forests (RF), and gradient boosting machine (GBM)., Results: Our predictive model for 1-year hospitalization achieved an AUC of 0.803, with a sensitivity of 72% and a specificity of 76% under the optimum threshold of 0.463, and our predictive model for 2-year hospitalization achieved an AUC of 0.793, with a sensitivity of 76% and a specificity of 71% under the optimum threshold of 0.452. For predicting both 1-year and 2-year risk of preventable hospitalization, our best performing models utilized the machine learning approach of logistic regression with LASSO penalty which outperformed more black-box machine learning models like RF and GBM., Conclusions: Our study demonstrates the feasibility of identifying depressed middle-aged adults at higher risk of future hospitalization due to burden of chronic illnesses using basic demographic information and diagnosis codes recorded in health insurance claims. Identifying this population may assist health care planners in developing effective screening strategies and management approaches and in efficient allocation of public healthcare resources as this population transitions to publicly funded healthcare programs, e.g., Medicare in the US., (© 2023. The Author(s).)

We used US nationwide commercial insurance claims data (2011-2015) to study the effect of social deprivation on clinical and demographic risk factors for suicidal ideation (SI) and suicide attempts (SA) among US youth and adults < 65 years, after having a mental health or substance use disorder-related outpatient encounter. Neighborhood social deprivation level was summarized by the quintile of social deprivation index (SDI) at individuals' zip code level. Cox proportional hazard models were used to evaluate the effect of social deprivation on demographic and clinical risk factors for SI and SA. The study cohort consisted of 317,383 individuals < 65 years, with 124,424 aged < 25 (youth) and 192,959 aged between 25 and 64 (adults). Neighborhood social deprivation impacted risk factors for SI and SA differently for youth and adults. Among youth, SDI interacted with multiple risk factors for both SI and SA. The effects of the risk factors were larger on youth from middle socioeconomic neighborhoods. Among adults, risk of SI was the strongest in the most deprived neighborhoods, but risk of SA did not vary by neighborhood deprivation level. Our findings suggest community-based suicide prevention initiatives should be tailored according to neighborhood deprivation level and the targeted individual's age to maximize the impact., (© 2023. The Author(s).)

Objectives: Optimistic bias refers to the phenomenon that individuals believe bad things are less likely to happen to themselves than to others. However, whether optimistic bias could vary across age and culture is unknown. The present study aims to investigate (a) whether individuals exhibit optimistic bias in the context of coronavirus disease 2019 (COVID-19) pandemic, and (b) whether age and culture would moderate such bias., Method: 1,051 participants recruited from China, Israel, and the United States took the online survey. Risk perceptions consist of 3 questions: estimating the infected probability of different social distance groups (i.e., self, close others, and nonclose others), the days that it would take for the number of new infections to decrease to zero and the trend of infections in regions of different geographical distances (i.e., local place, other places inside participants' country, and other countries). Participants in China and the United States also reported their personal communal values measured by Schwartz's Value Survey., Results: Results from Hierarchical Linear Modeling generally confirmed that (a) all participants exhibited optimistic bias to some extent, and (b) with age, Chinese participants had a higher level of optimistic bias than the Israeli and U.S. participants. Compared to their younger counterparts, older Chinese are more likely to believe that local communities are at lower risk of COVID-19 than other countries., Discussion: These findings support the hypothesis that age differences in risk perceptions might be influenced by cultural context. Further analysis indicated that such cultural and age variations in optimistic bias were likely to be driven by age-related increase in internalized cultural values., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: Rural Americans are particularly vulnerable to tobacco price reducing promotions are known to be directed to and used by vulnerable populations. Tobacco purchasing decisions, such as unit quantity purchased, may vary by rurality, by price promotion use, and possibly by the interaction between the two. Purchase decisions are likely to affect tobacco use behavior. Therefore, explanation of variation in tobacco purchase quantity by factors associated with rural vulnerability and factors that fall under the regulatory scope of the Tobacco Control Act (TCA) of 2009 could be of value to regulatory proposals intended to equitably benefit public health., Methods: Our sample included 54 combustible tobacco users (298 purchase events) and 27 smokeless tobacco users (112 purchase events), who were asked to report all tobacco purchases on a smartphone application. We used an ecological momentary assessment methodology to collect data about tobacco users' purchasing patterns, including products, quantity purchased, and use of price promotions. A parent cohort study provided relevant data for home-outlet distance calculation and covariates. Our analysis examined associations between our outcome-purchase quantity per purchase event-and distance from participant's home to the nearest outlet, whether a price reducing promotion was used, and the interaction of these two factors., Results: Combustible users showed an increased cigarette pack purchase quantity if they lived further from an outlet and used a price promotion (i.e., an interaction effect; RR = 1.70, 95% CI [1.11, 2.62]). Smokeless users purchased more units of snuff when they used price promotions (RR = 1.81, 95% CI [1.02, 3.20])., Conclusions: Regulatory action that imposes restrictions on the availability or use of price promotions could alter the purchasing behavior of rural Americans in such a way that makes it easier to reduce tobacco use or quit. Such action would also restrict flexibility in the price of tobacco products, which is known as a powerful tobacco control lever., (Copyright © 2018. Published by Elsevier Ltd.)

Understanding healthcare providers' preferences, values, and beliefs around AVF eligibility is important to explain variability in practice. We conducted a survey of international surgeons, using hypothetical patient scenarios, to assess resources used, variables, perceived barriers, and absolute contraindications to access creation. A total of 134 surgeons completed the survey. Venous duplex ultrasound mapping (VDUM) was offered to all patients by 90% of US, 68% Canadian, and 63% European respondents. VDUM altered clinical decision less than 25% of the time for 33% American, 48% Canadian, and 85% European surgeons. Increased comorbidities and previous failed access were deterrents to AVF creation as was vessel size. Second choice access was the AV graft in the US and Europe and the catheter in Canada. Absolute contraindications to AVF creation included patient life expectancy <1 year, left ventricular ejection fraction (LVEF) <15%, and a history of dementia, while 42% surgeons reported no absolute contraindications. Perceived barriers included patient preferences, long wait times for surgery, and late referral to a Nephrologist. Significant variability exists in the surgical preoperative assessment of patients, and the eligibility criteria used for fistula creation. Understanding surgeons' preferences can aid in establishing standardization for VA access eligibility, including surgical assessment., (© 2013 Wiley Periodicals, Inc.)