Diabetes Disparities in the United States: Trends by Educational Attainment from 2001 to 2020.

INTRODUCTION: Tracking changes in socioeconomic disparities in diabetes in the U.S. is important to evaluate progress in health equity and guide prevention efforts. Disparities in diabetes prevalence by educational attainment from 2001 to 2020 were investigated. METHODS: Using a serial cross-sectional design, data from 33,220 adults aged 30-79 assessed in nine rounds of the National Health and Nutrition Examination Surveys between 2001 and 2020 were analyzed in 2023-2024. Diabetes was defined as self-reported prior diagnosis, elevated glycated hemoglobin (HbA1c≥6.5%), or use of diabetes medications. Marginalized age- and covariate-adjusted prevalence differences (PD) and prevalence ratios (PR) of diabetes by educational attainment (less than high school graduation, high school graduation, some college education or associate degree, or college graduation [reference]) by calendar period (2001-2004, 2005-2008, 2009-2012, 2013-2016, 2017-2020) were derived from logistic regression models. RESULTS: From 2001 to 2020, age-adjusted diabetes prevalence was consistently higher among adults without a college degree. Adults without a high school diploma exhibited the largest disparities in both 2001-2004 (PD 8.0%; 95%CI 5.6-10.5 and PR 2.1; 95%CI 1.5-2.6) and 2017-20 (PD 11.0%; 95%CI 6.7-15.2 and PR 2.1; 95%CI 1.5-2.7). Between 2001-2004 and 2017-2020, the absolute disparity in diabetes changed only among adults with a high school diploma (increase from PD 1.7%; 95%CI -0.5- 3.9 to PD 8.8% 95%CI 4.1-13.4, respectively), while the PR did not change in any group. Education-related disparities in diabetes were attenuated after accounting for socio-demographic factors and BMI. CONCLUSIONS: From 2001 to 2020, national education-related disparities in diabetes prevalence have shown no signs of narrowing.

Cost-effectiveness analysis of interventional liver-directed therapies for downstaging of HCC before liver transplant.

Transarterial chemoembolization (TACE) and transarterial radioembolization (TARE) are the 2 most used modalities for patients with HCC while awaiting liver transplant. The purpose of this study is to perform a cost-effectiveness analysis comparing TACE and TARE for downstaging (DS) patients with HCC. A cost-effectiveness analysis was performed comparing TACE and TARE in DS HCC over a 5-year time horizon from a payer's perspective. The clinical course, including those who achieved successful DS leading to liver transplant and those who failed DS with possible disease progression, was obtained from the United Network for Organ Sharing. Costs and effectiveness were measured in US dollars and quality-adjusted life years (QALYs). Probabilistic and deterministic sensitivity analyses were performed. TARE achieved a higher effectiveness of 2.51 QALY (TACE: 2.29 QALY) at a higher cost of $172,162 (TACE: $159,706), with the incremental cost-effectiveness ratio of $55,964/QALY, making TARE the more cost-effective strategy. The difference in outcome was equivalent to 104 days (nearly 3.5 months) in compensated cirrhosis state. Probabilistic sensitivity analyses showed that TARE was more cost-effective in 91.69% of 10,000 Monte Carlo simulations. TARE was more effective if greater than 48.2% of patients who received TACE or TARE were successfully downstaged (base case: 74.6% from the pooled analysis of multiple published cohorts). TARE became more cost-effective when the cost of TACE exceeded $4,831 (base case: $12,722) or when the cost of TARE was lower than $43,542 (base case: $30,609). Subgroup analyses identified TARE to be the more cost-effective strategy if the TARE cohort required 1 fewer locoregional therapy than the TACE cohort. TARE is the more cost-effective DS strategy for patients with HCC exceeding Milan criteria compared to TACE.

Neighborhood-level Social Determinants of Health and Waitlist Mortality for Liver Transplantation: The Liver Outcomes and Equity Index.

BACKGROUND AND AIMS: To examine neighborhood-level disparities in waitlist mortality for adult liver transplantation (LT), we developed novel area-based social determinants of health (SDOH) index using a national transplant database. METHODS: ZIP Codes of individuals listed for or received LT in the Scientific Registry of Transplant Recipients database between June 18, 2013, and May 18, 2019, were linked to 36 American Community Survey (ACS) variables across 5 SDOH domains for index development. A step-wise principal component analysis was used to construct the Liver Outcomes and Equity (LOEq) index. We then examined the association between LOEq quintiles (Q1 = worst and Q5 = best neighborhood SDOH) and waitlist mortality with competing risk regression among listed adults in the study period and acuity circle (AC) era. RESULTS: The final LOEq index consisted of 13 ACS variables. Of 59 298 adults waitlisted for LT, 30% resided in LOEq Q5 compared with only 14% in Q1. Q1 neighborhoods with worse SDOH were disproportionately concentrated in transplant regions with low median Model for End-Stage Liver Disease at transplant (MMAT) and shorter wait times. Five years cumulative incidence of waitlist mortality was 33% in Q1 in high MMAT regions versus 16% in Q5 in low MMAT regions. Despite this allocation advantage, LOEq Q1-Q4 were independently associated with elevated risk of waitlist mortality compared with Q5, with highest increased hazard of waitlist deaths of 19% (95% CI, 11%-26%) in Q1. This disparity persisted in the AC era, with 24% (95% CI, 10%-40%) increased hazard of waitlist deaths for Q1 versus Q5. CONCLUSIONS: Neighborhood SDOH independently predicts waitlist mortality in adult LT.

In the wake of a crisis: Caught between housing and healthcare.

Objective: To measure the association between housing insecurity and foregone medication due to cost among Medicare beneficiaries aged 65+ during the Recession. Methods: Data came from Medicare beneficiaries aged 65+ years from the 2006-2012 waves of the Health and Retirement Study (HRS). Two-wave housing insecurity changes are evaluated as follows: (i) No insecurity, (ii) Persistent insecurity, (iii) Onset insecurity, and (iv) Onset security. We implemented a series of four weighted longitudinal General Estimating Equation (GEE) models, two minimally adjusted and two fully adjusted models, to estimate the probability of foregone medications due to cost between 2008 and 2012. Results: Our study sample was restricted to non-proxy interviews of non-institutionalized Medicare beneficiaries aged 65+ in the 2006 wave (n = 9936) and their follow up visits (n = 8753; in 2008; n = 7464 in 2010; and n = 6594 in 2012). Results from our fully adjusted model indicated that the odds of foregone medication was 64% higher among individuals experiencing Onset insecurity versus No insecurity in 2008, and also generally larger for individuals experiencing Onset Insecurity versus Persistent Insecurity. Odds of foregone medication was also larger among females, minority versus non-Hispanic white adults, those reporting a chronic condition, those with higher medical expenditures, and those living in the South versus Northeast. Conclusion: This study drew from nationally representative data to elucidate the disparate health and financial impacts of a crisis on Medicare beneficiaries who, despite health insurance coverage, displayed variability in foregone medication patterns. Our findings suggest that the onset of housing insecurity is most closely linked with unexpected acute economic shocks leading households with little time to adapt and forcing trade-offs in their prescription and other needs purchases. Both housing and healthcare policy implications exist from these findings including expansion of low-income housing units and rent relief post-recession as well as wider prescription drug coverage for Medicare adults.

Optimal treatment for small HCC (<3 cm): Resection, liver transplantation, or locoregional therapy?

Hepatocellular carcinoma (HCC) remains the most common form of liver cancer, accounting for 90% of all primary liver cancers. Up to 30% of HCC cases could be small (2-3 cm in diameter) at the time of diagnosis with advances in imaging techniques and surveillance programmes. Treating patients with early-stage HCC can be complex and often requires interdisciplinary care, owing to the wide and increasing variety of treatment options, which include liver resection, liver transplantation, and various locoregional therapies offered by interventional radiology and radiation oncology. Decisions regarding the optimal management strategy for a patient involve many considerations, including patient- and tumour-specific characteristics, as well as socioeconomic factors. In this review, we aim to comprehensively summarise the commonly used therapies for single, small HCC (<3 cm), with a focus on the impact of tumour size (<2 cm vs. 2-3 cm), as well as a brief discussion on the cost-effectiveness of the different treatment options.

Community-level social vulnerability and individual socioeconomic status on liver transplant referral outcome.

BACKGROUND: Recent endeavors emphasize the importance of understanding early barriers to liver transplantation (LT) by consistently collecting data on patient demographics, socioeconomic factors, and geographic social deprivation indices. METHODS: In this retrospective single-center cohort study of 1657 adults referred for LT evaluation, we assessed the association between community-level vulnerability and individual socioeconomic status measures on the rate of waitlisting and transplantation. Patients' addresses were linked to Social Vulnerability Index (SVI) at the census tract-level to characterize community-level vulnerability. Descriptive statistics were used to describe patient characteristics. Multivariable cause-specific HRs were used to assess the association between community-level vulnerability, individual measures of the socioeconomic status, and LT evaluation outcomes (waitlist and transplantation). RESULTS: Among the 1657 patients referred for LT during the study period, 54% were waitlisted and 26% underwent LT. A 0.1 increase in overall SVI correlated with an 8% lower rate of waitlisting (HR 0.92, 95% CI 0.87-0.96, p < 0.001), with socioeconomic status, household characteristics, housing type and transportation, and racial and ethnic minority status domains contributing significantly to this association. Patients residing in more vulnerable communities experienced a 6% lower rate of transplantation (HR 0.94, 95% CI 0.91- 0.98, p = 0.007), with socioeconomic status and household characteristic domain of SVI significantly contributing to this association. At the individual level, both government insurance and employment status were associated with lower rates of waitlisting and transplantation. There was no association with mortality prior to waitlisting or mortality while on the waitlist. CONCLUSION: Our findings indicate that both individual and community measures of the socioeconomic status (overall SVI) are associated with LT evaluation outcomes. Furthermore, we identified individual measures of neighborhood deprivation associated with both waitlisting and transplantation.

Cost-Effectiveness Analysis of Interventional Liver-Directed Therapies for a Single, Small Hepatocellular Carcinoma in Liver Transplant Candidates.

PURPOSE: To assess the cost effectiveness of 3 main locoregional therapies (LRTs) (transarterial chemoembolization [TACE], transarterial radioembolization [TARE], and percutaneous ablation) as bridging therapy. MATERIALS AND METHODS: A cost-effectiveness analysis was performed comparing the 3 LRTs for patients with a single hepatocellular carcinoma (HCC) with a diameter of 3 cm or less over a 5-year time horizon from a payer's perspective. The clinical courses, including transplantation, decompensation resulting in delisting, and the need for a second LRT, were based on data from the United Network for Organ Sharing (2016-2019). Costs and effectiveness were measured in U.S. dollars and quality-adjusted life-years, respectively. Probabilistic and deterministic sensitivity analyses were performed. RESULTS: A total of 2,594, 1,576, and 903 patients underwent TACE, ablation, and TARE, respectively. Ablation was the dominant strategy, with the lowest expected cost and highest effectiveness. The probabilistic sensitivity analysis demonstrated that ablation was the most cost-effective strategy in 93.9% of simulations. A subgroup analysis was performed for different wait times, with ablation remaining the most cost-effective strategy. The sensitivity analysis showed that ablation was most effective if the risk of waitlist dropout was less than 2.00% and the rate of transplantation was more than 15.1% quarterly. TARE was most effective if the risk of dropout was less than 1.19% and the rate of transplantation was more than 24.0%. TACE was most effective if the risk of dropout was less than 1.01% and the rate of transplantation was more than 45.7%. Ablation remained the most cost-effective modality until its procedural cost was more than $34,843. CONCLUSIONS: Ablation is the most cost-effective bridging strategy for patients with a single, small (≤3 cm) HCC prior to liver transplantation. The conclusion remained robust in multiple sensitivity analyses.

Climate Change and Medical Education: An Integrative Model.

Medical schools face a challenge when trying to include new topics, such as climate change and health (CCH), in their curricula because of competing demands from more traditional biomedical content. At the same time, an understanding of CCH topics is crucial for physicians as they have clear implications for clinical practice and health care delivery. Although some medical schools have begun to incorporate CCH into curricula, the inclusion usually lacks a comprehensive framework for content and implementation. The authors propose a model for integrating CCH into medical school curricula using a practical, multistakeholder approach designed to mitigate competition for time with existing content by weaving meaningful CCH examples into current curricular activities. After the authors identified stakeholders to include in their curricular development working group, this working group determined the goals and desired outcomes of the curriculum; aligned those outcomes with the school's framework of educational objectives, competencies, and milestones; and strove to integrate CCH goals into as many existing curricular settings as possible. This article includes an illustration of the proposed model for one of the curricular goals (understanding the impacts of climate change on communities), with examples from the CCH curriculum integration that began in the fall of 2020 at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University. The authors have found that this approach does minimize competition for time with existing content and allows mapping of content to existing curricular competencies and milestones, while encouraging a broad understanding of CCH in the context of individual patients, populations, and communities. This model for curricular integration can be applied to other topics such as social determinants of health, health equity, disability studies, and structural racism.

The Key Role of Staging Definitions for Assessment of Downstaging for Hepatocellular Carcinoma.

The success of liver transplant (LT) for hepatocellular carcinoma (HCC) is dependent on accurate tumor staging using validated imaging criteria, and adherence to acceptable criteria based on tumor size and number. Other factors including α-fetoprotein (AFP) and response to local regional therapy (LRT) have now played a larger role in candidate selection. Tumor downstaging is defined as reduction in the size of viable tumors using LRT to meet acceptable criteria for LT, and serves as a selection tool for a subgroup of HCC with more favorable biology. The application of tumor downstaging requires a structured approach involving three key components in tumor staging-initial tumor stage and eligibility criteria, tumor viability assessment following LRT, and target tumor stage prior to LT-and incorporation of AFP into staging and treatment response assessments. In this review, we provide in-depth discussions of the key role of these staging definitions in ensuring successful outcome.

Pathways to Educational Disparities in Disability Incidence: The Contributions of Excess Body Mass Index, Smoking, and Manual Labor Involvement.

OBJECTIVES: In the United States, educational disparities in disability are large and increasing, but the mechanisms underlying them are not well understood. We estimate the proportion of population-level educational disparities in disability incidence explained by excess body mass index (BMI), smoking, and manual labor. METHOD: We use waves 2003-2015 of the nationally representative Panel Study of Income Dynamics to calculate observed disability incidence and counterfactual incidence absent the key mediators (3,129 individuals; 13,168 observations). We take advantage of earlier-life measures, including childhood socioeconomic status, 1986 BMI, and occupational history between 1968 and 2001. To account for distinct processes in women and men at middle versus older ages, we stratify by gender and at age 65. RESULTS: Educational disparities in disability incidence were evident in women and men at younger and older ages, and were largest among older women. Together, the mediators of interest were estimated to explain roughly 60% of disparities in younger women, 65%-70% in younger men, 40% in older women, and 20%-60% in older men. The main contributors to disparities appeared to be excess BMI and smoking in younger women; manual labor and smoking in younger men; excess BMI in older women; and smoking in older men. DISCUSSION: These mediators explain much of disparities in earlier-age disability; successful interventions to address these factors may substantially reduce them. However, a considerable proportion of disparities remained unexplained, particularly at older ages, reflecting the myriad pathways by which educational attainment can influence disability status.

Digital Health and the Care of the Patient With Arrhythmia: What Every Electrophysiologist Needs to Know.

The field of cardiac electrophysiology has been on the cutting edge of advanced digital technologies for many years. More recently, medical device development through traditional clinical trials has been supplemented by direct to consumer products with advancement of wearables and health care apps. The rapid growth of innovation along with the mega-data generated has created challenges and opportunities. This review summarizes the regulatory landscape, applications to clinical practice, opportunities for virtual clinical trials, the use of artificial intelligence to streamline and interpret data, and integration into the electronic medical records and medical practice. Preparation of the new generation of physicians, guidance and promotion by professional societies, and advancement of research in the interpretation and application of big data and the impact of digital technologies on health outcomes will help to advance the adoption and the future of digital health care.

Epithelial vectorial ion transport in cystic fibrosis: Dysfunction, measurement, and pharmacotherapy to target the primary deficit.

Cystic fibrosis patients display multi-organ system dysfunction (e.g. pancreas, gastrointestinal tract, and lung) with pathogenesis linked to a failure of Cl- secretion from the epithelial surfaces of these organs. If unmanaged, organ dysfunction starts early and patients experience chronic respiratory infection with reduced lung function and a failure to thrive due to gastrointestinal malabsorption. Early mortality is typically caused by respiratory failure. In the past 40 years of newborn screening and improved disease management have driven the median survival up from the mid-teens to 43-53, with most of that improvement coming from earlier and more aggressive management of the symptoms. In the last decade, promising pharmacotherapies have been developed for the correction of the underlying epithelial dysfunction, namely, Cl- secretion. A new generation of systemic drugs target the mutated Cl- channels in cystic fibrosis patients and allow trafficking of the immature mutated protein to the cell membrane (correctors), restore function to the channel once in situ (potentiators), or increase protein levels in the cells (amplifiers). Restoration of channel function prior to symptom development has the potential to significantly change the trajectory of disease progression and their evidence suggests that a modest restoration of Cl- secretion may delay disease progression by decades. In this article, we review epithelial vectorial ion and fluid transport, its quantification and measurement as a marker for cystic fibrosis ion transport dysfunction, and highlight some of the recent therapies targeted at the dysfunctional ion transport of cystic fibrosis.

Cognitive impairment in the U.S.: Lifetime risk, age at onset, and years impaired.

Prior studies have analyzed the burden of cognitive impairment, but often use potentially biased prevalence-based methods or measure only years lived with impairment, without estimating other relevant metrics. We use the Health and Retirement Study (1998-2014; n = 29,304) and the preferred incidence-based Markov-chain models to assess three key measures of the burden of cognitive impairment: lifetime risk, mean age at onset, and number of years lived impaired. We analyze both mild and severe cognitive impairment (dementia) and gender, racial/ethnic, and educational variation in impairment. Our results paint a multi-dimensional picture of cognitive health, presenting the first comprehensive analysis of the burden of cognitive impairment for the U.S. population age 50 and older. Approximately two out of three Americans experience some level of cognitive impairment at an average age of approximately 70 years. For dementia, lifetime risk for women (men) is 37% (24%) and mean age at onset 83 (79) years. Women can expect to live 4.2 years with mild impairment and 3.2 with dementia, men 3.5 and 1.8 years. A critical finding is that for the most advantaged groups (i.e., White and/or higher educated), cognitive impairment is both delayed and compressed toward the very end of life. In contrast, despite the shorter lives of disadvantaged subgroups (Black and/or lower educated), they experience a younger age of onset, higher lifetime risk, and more years cognitively impaired. For example, men with at least an Associate degree have 21% lifetime dementia risk, compared to 35% among men with less than high school education. White women have 6 years of cognitively-impaired life expectancy, compared to 12 and 13 years among Black women and Latinas. These educational and racial/ethnic gradients highlight the very uneven burden of cognitive impairment. Further research is required to identify the mechanisms driving these disparities in cognitive impairment.

Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management.

PURPOSE OF REVIEW: Machine learning (ML) is increasingly being studied for the screening, diagnosis, and management of diabetes and its complications. Although various models of ML have been developed, most have not led to practical solutions for real-world problems. There has been a disconnect between ML developers, regulatory bodies, health services researchers, clinicians, and patients in their efforts. Our aim is to review the current status of ML in various aspects of diabetes care and identify key challenges that must be overcome to leverage ML to its full potential. RECENT FINDINGS: ML has led to impressive progress in development of automated insulin delivery systems and diabetic retinopathy screening tools. Compared with these, use of ML in other aspects of diabetes is still at an early stage. The Food & Drug Administration (FDA) is adopting some innovative models to help bring technologies to the market in an expeditious and safe manner. ML has great potential in managing diabetes and the future is in furthering the partnership of regulatory bodies with health service researchers, clinicians, developers, and patients to improve the outcomes of populations and individual patients with diabetes.

Disparities in exposure to surrounding greenness related to proportion of the population that were immigrants to the United States.

The proportion of the United States (US) population who are immigrants (i.e., foreign-born) has been rising. Compared to the US-born, immigrants have different health risks, and prior studies could not fully explain these differences by diet and socioeconomic status. Surrounding greenness, an environmental exposure linked to better health, potentially contributes to differences in health risks between immigrants and the US-born. Using satellite imagery, we assessed exposure to surrounding greenness, as estimated by the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), in US Census tracts in 2000 and 2010. We then investigated the association between the percentage of the population that were immigrants and greenness using spatial error regression. Adjusted for median household income, urbanicity, educational attainment, unemployment, elderly and youth population proportion, and ecozone, Census tracts with ~10% higher overall immigrant percentage points were, on average, ~0.06 NDVI/EVI interquartile range lower, indicating lower greenness. The pattern of negative associations was most consistent when the immigrant country of origin was in Latin America. Conversely, when the immigrant country of origin was in Europe, we found mostly positive associations. Our findings suggest an environmental exposure disparity by immigrant status, motivating future work on environmental contributions to health disparities between immigrants and the US-born.

Comparison of Liver Transplant Wait-List Outcomes Among Patients With Hepatocellular Carcinoma With Public vs Private Medical Insurance.

Importance: There are well-documented racial/ethnic and socioeconomic disparities in access to health care among patients with hepatocellular carcinoma (HCC); however, there are little data on the association of insurance type with liver transplant (LT) wait-list outcomes for patients with HCC. Objective: To examine LT wait-list outcomes for patients with HCC and public insurance compared with patients with private insurance. Design, Setting, and Participants: This single-center cohort study included 705 adult patients with HCC who had Model for End-Stage Liver Disease exceptions and were included on a waiting list for LT from January 1, 2010, to December 31, 2016. Patients with Kaiser Permanente medical insurance, other private medical insurance, or public medical insurance were included. Data analysis was conducted from May 2018 to October 2018. Main Outcomes and Measures: The main outcome was cumulative incidence of LT waiting list dropout within 2 years of waiting list enrollment (baseline). Secondary outcomes included competing-risks analysis to identify risk factors associated with wait-list outcomes. Results: Among 705 patients (median [interquartile range] age, 61 [57-65] years; 537 [76.2%] men) with HCC on an LT waiting list, 349 patients (49.5%) had Kaiser Permanente insurance, 157 patients (22.3%) had other private insurance, and 199 patients (28.2%) had public insurance. Median (interquartile range) follow-up was 13.2 (7.8-18.7) months. Tumor characteristics were similar among insurance types. The cumulative incidence of dropout owing to tumor progression or death within 2 years of baseline was 21.8% (95% CI, 17.2%-26.7%) among the Kaiser Permanente insurance group, 25.5% (95% CI, 18.6%-33.0%) among the other private insurance group, and 35.5% (95% CI, 28.3%-42.7%) among the public insurance group (P < .001). The cumulative incidence of LT within 2 years of baseline was 67.3% (95% CI, 61.2%-72.6%) among the Kaiser Permanente insurance group, 64.1% (95% CI, 55.2%-71.7%) among the other private insurance group, and 48.5% (95% CI, 40.4%-56.1%) among the public insurance group (P < .001). In competing-risks multivariable analysis compared with patients with Kaiser Permanente insurance, patients with public insurance were associated with increased risk of dropout (hazard ratio [HR], 1.69 [95% CI, 1.17-2.43]; P = .005), but patients with other private insurance were not (HR, 1.40 [95% CI, 0.94-2.08]; P = .10). Waiting list dropout was also significantly associated with an α-fetoprotein level 100 ng/mL or higher (HR, 2.8 [95% CI, 1.98-3.88]; P < .001), Model for End-Stage Liver Disease score at baseline (HR per point, 1.06 [95% CI, 1.03-1.09]; P < .001), and 3 or more lesions at baseline (HR vs 1 lesion of 2- to 3-cm diameter, 2.07 [95% CI, 1.27-3.37]; P = .004). Conclusions and Relevance: In this large cohort of patients with HCC on an LT waiting list, patients with public insurance were associated with worse wait-list outcomes compared with patients with Kaiser Permanente insurance or other private insurance, despite similar tumor-related characteristics at baseline. Improved health care coordination and delivery may be options to reduce these disparities.

How do age and major risk factors for mortality interact over the life-course? Implications for health disparities research and public health policy.

A critical question in life-course research is whether the relationship between a risk factor and mortality strengthens, weakens, or remains constant with age. The objective of this paper is to shed light on the importance of measurement scale in examining this question. Many studies address this question solely on the multiplicative (relative) scale and report that the hazard ratio of dying associated with a risk factor declines with age. A wide set of risk factors have been shown to conform to this pattern including those that are socioeconomic, behavioral, and physiological in nature. Drawing from well-known principles on interpreting statistical interactions, we show that evaluations on the additive (absolute) scale often lead to a different set of conclusions about how the association between a risk factor and mortality changes with age than interpretations on the multiplicative scale. We show that on the additive scale the excess death risks posed by key socio-demographic and behavioral risk factors increase with age. Studies have not generally recognized the additive interpretation, but it has relevancy for testing life-course theories and informing public health interventions. We discuss these implications and provide general guidance on choosing a scale. Data from the U.S. National Health Interview Survey are used to provide empirical support.

Changes in depressive symptoms over age among older Americans: Differences by gender, race/ethnicity, education, and birth cohort.

Despite concerns about recent trends in the health and functioning of older Americans, little is known about dynamics of depression among recent cohorts of U.S. older adults and how these dynamics differ across sociodemographic groups. This study examined sociodemographic differences in mid- and late-life depressive symptoms over age, as well as changes over time. Using nationally representative data from the Health and Retirement Study (1994-2014), we estimated mixed effects models to generate depressive symptoms over age by gender, race/ethnicity, education, and birth cohort in 33,280 adults ages 51-90 years. Depressive symptoms were measured using the 8-item Center for Epidemiological Studies Depression scale. Women compared to men, low compared to high education groups, and racial/ethnic minorities compared to whites exhibited higher depressive symptoms. The largest disparity resulted from education, with those without high school degrees exhibiting over two more predicted depressive symptoms in midlife compared to those with college degrees. Importantly, war babies and baby boomers (born 1942-1959) exhibited slightly higher depressive symptoms with more decreasing symptoms over age than their predecessors (born 1931-1941) at ages 51-65. We additionally observed an age-as-leveler pattern by gender, whereby females compared to males had higher depressive symptomology from ages 51-85, but not at ages 86-90. Our findings have implication for gauging the aging population's overall well-being, for public health policies aimed at reducing health disparities, and for anticipating demand on an array of health and social services.

Predictors of low risk for dropout from the liver transplant waiting list for hepatocellular carcinoma in long wait time regions: Implications for organ allocation.

All patients with hepatocellular carcinoma meeting United Network for Organ Sharing T2 criteria currently receive the same listing priority for liver transplant (LT). A previous study from our center identified a subgroup with a very low risk of waitlist dropout who may not derive immediate LT benefit. To evaluate this issue at a national level, we analyzed within the United Network for Organ Sharing database 2052 patients with T2 hepatocellular carcinoma receiving priority listing from 2011 to 2014 in long wait time regions 1, 5, and 9. Probabilities of waitlist dropout were 18.3% at 1 year and 27% at 2 years. In multivariate analysis, factors associated with a lower risk of waitlist dropout included Model for End-Stage Liver Disease-Na < 15, Child's class A, single 2- to 3-cm lesion, and α-fetoprotein ≤20 ng/mL. The subgroup of 245 (11.9%) patients meeting these 4 criteria at LT listing had a 1-year probability of dropout of 5.5% vs 20% for all others (P < .001). On explant, the low dropout risk group was more likely to have complete tumor necrosis (35.5% vs 24.9%, P = .01) and less likely to exceed Milan criteria (9.9% vs 17.7%, P = .03). We identified a subgroup with a low risk of waitlist dropout who should not receive the same LT listing priority.

Increasing Liver Transplantation Wait-List Dropout for Hepatocellular Carcinoma With Widening Geographical Disparities: Implications for Organ Allocation.

Given the increasing incidence of hepatocellular carcinoma (HCC) and regional variation in liver transplantation (LT) rates for HCC, we investigated temporal and geographic disparities in LT and wait-list dropout. LT candidates receiving Model for End-Stage Liver Disease (MELD) exception from 2005 to 2014 were identified from the United Network for Organ Sharing database (n = 14,320). Temporal differences were compared across 2 eras (2005-2009 and 2010-2014). Regional groups were defined based on median wait time as long-wait region (LWR; regions 1, 5, and 9), mid-wait region (MWR; regions 2, 4, 6, 7, and 8), and short-wait region (SWR; regions 3, 10, and 11). Fine and Gray competing risk regression estimated risk of wait-list dropout as hazard ratios (HRs). The cumulative probability of LT within 3 years was 70% in the LWR versus 81% in the MWR and 91% in the SWR (P < 0.001). From 2005-2009 to 2010-2014, median time to LT increased by 6.0 months (5.6 to 11.6 months) in the LWR compared with 3.8 months (2.6 to 6.4 months) in the MWR and 1.3 months (1.0 to 2.3 months) in the SWR. The cumulative probability of dropout within 3 years was 24% in the LWR versus 16% in the MWR and 8% in the SWR (P < 0.001). From 2005-2009 to 2010-2014, the LWR also had the greatest increase in probability of dropout. Risk of dropout was increased in the LWR (HR, 3.5; P < 0.001) and the MWR (HR, 2.2; P < 0.001) compared with the SWR, and year of MELD exception 2010-2014 (HR, 1.9; P < 0.001) compared with 2005-2009. From 2005-2009 to 2010-2014, intention-to-treat 3-year survival decreased from 69% to 63% in the LWR (P < 0.001), 72% to 69% in the MWR (P = 0.008), and remained at 74% in the SWR (P = 0.48). In conclusion, we observed a significant increase in wait-list dropout in HCC patients in recent years that disproportionately impacted LWR patients. Widening geographical disparities call for changes in allocation policy as well as enhanced efforts at increasing organ donation and utilization.