Cardiometabolic Disease Staging and Major Adverse Cardiovascular Event Prediction in 2 Prospective Cohorts.

BACKGROUND: Cardiometabolic risk prediction models that incorporate metabolic syndrome traits to predict cardiovascular outcomes may help identify high-risk populations early in the progression of cardiometabolic disease. OBJECTIVES: The purpose of this study was to examine whether a modified cardiometabolic disease staging (CMDS) system, a validated diabetes prediction model, predicts major adverse cardiovascular events (MACE). METHODS: We developed a predictive model using data accessible in clinical practice [fasting glucose, blood pressure, body mass index, cholesterol, triglycerides, smoking status, diabetes status, hypertension medication use] from the REGARDS (REasons for Geographic And Racial Differences in Stroke) study to predict MACE [cardiovascular death, nonfatal myocardial infarction, and/or nonfatal stroke]. Predictive performance was assessed using receiver operating characteristic curves, mean squared errors, misclassification, and area under the curve (AUC) statistics. RESULTS: Among 20,234 REGARDS participants with no history of stroke or myocardial infarction (mean age 64 ± 9.3 years, 58% female, 41% non-Hispanic Black, and 18% diabetes), 2,695 developed incident MACE (13.3%) during a median 10-year follow-up. The CMDS development model in REGARDS for MACE had an AUC of 0.721. Our CMDS model performed similarly to both the ACC/AHA 10-year risk estimate (AUC 0.721 vs 0.716) and the Framingham risk score (AUC 0.673). CONCLUSIONS: The CMDS predicted the onset of MACE with good predictive ability and performed similarly or better than 2 commonly known cardiovascular disease prediction risk tools. These data underscore the importance of insulin resistance as a cardiovascular disease risk factor and that CMDS can be used to identify individuals at high risk for progression to cardiovascular disease.

Linking Angelman and dup15q data for expanded research (LADDER) database: a model for advancing research, clinical guidance, and therapeutic development for rare conditions.

Angelman syndrome (AS) and duplication 15q (dup15q) syndrome are rare neurogenetic conditions arising from a common locus on the long arm of chromosome 15. Individuals with both conditions share some clinical features (e.g. intellectual disability, epilepsy) and often require lifelong care. Disease-modifying therapies for both conditions are emerging, resulting in a significant need for a better understanding of the natural history of both AS and dup15q. Patient advocacy groups for both conditions recognized a need for a data repository that would link data on individuals from multiple sources to expand research, increase understanding of natural history, and accelerate the development of treatments, resulting in the Linking Angelman and Dup15q Data for Expanded Research (LADDER) Database. This paper describes the development and functionality of the LADDER Database - including challenges, lessons learned, and preliminary feasibility - and how it can be used as a model for other rare conditions.

The LADDER database: a model for advancing research, clinical guidance, and therapeutic development for rare conditions This paper describes the development and functionality of the Linking Angelman and Dup15q Data for Expanded Research (LADDER) Database, which is a data repository for two rare neurogenetic conditions: Angelman syndrome (AS) and duplication 15q (dup15q) syndrome. AS and dup15q syndrome arise from genetic abnormalities on chromosome 15 and share some clinical features (e.g. intellectual disability, epilepsy). LADDER was developed by patient advocacy organizations representing each condition in partnership with RTI International. LADDER links data on individuals from multiple sources to expand research, increase understanding of natural history, and accelerate the development of treatments for both AS and dup15q syndrome. The LADDER Database can be used as a model for expanding research and enhancing clinical trial readiness in other rare conditions.

Associations between mitochondrial copy number, exercise capacity, physiologic cost of walking, and cardiac strain in young adult survivors of childhood cancer.

PURPOSE: Childhood cancer survivors are at risk for cardiac dysfunction and impaired physical performance, though underlying cellular mechanisms are not well studied. In this cross-sectional study, we examined the association between peripheral blood mitochondrial DNA copy number (mtDNA-CN, a proxy for mitochondrial function) and markers of performance impairment and cardiac dysfunction. METHODS: Whole-genome sequencing, validated by quantitative polymerase chain reaction, was used to estimate mtDNA-CN in 1720 adult survivors of childhood cancer (48.5% female; mean age = 30.7 years, standard deviation (SD) = 9.0). Multivariable logistic regression was performed to evaluate the associations between mtDNA-CN and exercise intolerance, walking inefficiency, and abnormal global longitudinal strain (GLS), adjusting for treatment exposures, age, sex, and race and ethnicity. RESULTS: The prevalence of exercise intolerance, walking inefficiency, and abnormal GLS among survivors was 25.7%, 10.7%, and 31.7%, respectively. Each SD increase of mtDNA-CN was associated with decreased odds of abnormal GLS (adjusted odds ratio (OR) = 0.88, p = 0.04) but was not associated with exercise intolerance (OR = 1.02, p = 0.76) or walking inefficiency (OR = 1.06, p = 0.46). Alkylating agent exposure was associated with increased odds of exercise intolerance (OR = 2.25, p < 0.0001), walking inefficiency (OR = 2.37, p < 0.0001), and abnormal GLS (OR = 1.78, p = 0.0002). CONCLUSIONS: Increased mtDNA-CN is associated with decreased odds of abnormal cardiac function in childhood cancer survivors. IMPLICATIONS FOR CANCER SURVIVORS: These findings demonstrate a potential role for mtDNA-CN as a biomarker of early cardiac dysfunction in this population.

Financial hardship and neighborhood socioeconomic disadvantage in long-term childhood cancer survivors.

BACKGROUND: Long-term survivors of childhood cancer face elevated risk for financial hardship. We evaluate whether childhood cancer survivors live in areas of greater deprivation and the association with self-reported financial hardships. METHODS: We performed a cross-sectional analysis of data from the Childhood Cancer Survivor Study between 1970 and 1999 and self-reported financial information from 2017 to 2019. We measured neighborhood deprivation with the Area Deprivation Index (ADI) based on current zip code. Financial hardship was measured with validated surveys that captured behavioral, material and financial sacrifice, and psychological hardship. Bivariate analyses described neighborhood differences between survivors and siblings. Generalized linear models estimated effect sizes between ADI and financial hardship adjusting for clinical factors and personal socioeconomic status. RESULTS: Analysis was restricted to 3475 long-term childhood cancer survivors and 923 sibling controls. Median ages at time of evaluation was 39 years (interquartile range [IQR] = 33-46 years and 47 years (IQR = 39-59 years), respectively. Survivors resided in areas with greater deprivation (ADI ≥ 50: 38.7% survivors vs 31.8% siblings; P < .001). One quintile increases in deprivation were associated with small increases in behavioral (second quintile, P = .017) and psychological financial hardship (second quintile, P = .009; third quintile, P = .014). Lower psychological financial hardship was associated with individual factors including greater household income (≥$60 000 income, P < .001) and being single (P = .048). CONCLUSIONS: Childhood cancer survivors were more likely to live in areas with socioeconomic deprivation. Neighborhood-level disadvantage and personal socioeconomic circumstances should be evaluated when trying to assist childhood cancer survivors with financial hardships.

An integrated action plan to fund and support drug development for Dup15q syndrome: a patient organization perspective.

Maternal 15q11.2-13.1 duplication syndrome, or Dup15q syndrome (Dup15q), is a rare neurodevelopmental disorder affecting as many as 1 in 5000 to 1 in 20,000 children worldwide. Autism and seizures are two of the most commonly observed phenotypes in Dup15q, with intellectual disability, hypotonia, gastrointestinal distress, and substantial fine and gross motor deficits also commonly reported. The community that is now known as the Dup15q Alliance started in 1994 as a small group of families raising children with chromosome 15q duplications. Originally named IsoDicentric 15 Exchange, Advocacy and Support (IDEAS), the group received official nonprofit organization status 10 years later and rebranded to its current name, Dup15q Alliance, shortly thereafter. Today, there are over 2200 families affiliated with Dup15q Alliance, with an average intake of 10 new families each month. Historically, Dup15q Alliance has provided the community with access to family and caregiver resources in addition to serving as a repository for basic educational information about Dup15q and research developments. The recent installation of a dedicated director of scientific and clinical initiatives alongside other infrastructural changes has now primed the Dup15q Alliance to expand its scientific footprint by funding cutting-edge research, supporting clinical sites and trials, and investing in novel therapeutics that have the potential to change the reality of a Dup15q syndrome diagnosis. To do this, we have developed the LEARN. TREAT. CURE. program to align initiatives, fast-track progress, and bring hope and reality into coexistence. Briefly, we seek to learn as much as we can about the syndrome through cutting-edge research, natural history studies, and patient registry utilization, identify and develop methods to treat the symptoms of our patient community, with the ultimate goal of developing a cure for the disease-causing symptoms of the syndrome.

A campaign to accelerate drug discovery in Dup15q Syndrome Patient advocacy groups aid in raising awareness and funding for specific disorders. Nearly three decades ago, Dup15q Alliance was founded by parents of individuals with maternal Duplication 15q Syndrome. This group has grown significantly and is now focused on funding programs to advance research. To do this, they have revised their infrastructure to include a part-time Director of Scientific and Clinical Initiatives and developed a fundraising campaign dedicated to scientific and clinical programming. They also emphasize collaboration and community engagement as key elements of the campaign.

Severe Sepsis During Treatment for Childhood Leukemia and Sequelae Among Adult Survivors.

Importance: Children undergoing treatment for leukemia are at increased risk of severe sepsis, a dysregulated immune response to infection leading to acute organ dysfunction. As cancer survivors, they face a high burden of long-term adverse effects. The association between sepsis during anticancer therapy and long-term organ dysfunction in adult survivors of childhood cancer has not been examined. Objective: To determine whether severe sepsis during therapy for leukemia in childhood is associated with subsequent chronic health conditions in adult survivors. Design, Setting, and Participants: This cohort study included 644 adult survivors of childhood leukemia who were diagnosed between January 1, 1985, and July 19, 2010, and participated in the St Jude Lifetime Cohort Study. Participants were excluded if they received hematopoietic cell transplant or had relapsed leukemia. Data collection ended June 30, 2017. Data were analyzed from July 1, 2020, to January 5, 2024. Exposures: Severe sepsis episodes, defined according to consensus criteria as septic shock, acute respiratory distress syndrome, or multiorgan dysfunction associated with infection occurring during anticancer therapy, were abstracted by medical record review for all participants. Main Outcomes and Measures: Common Terminology Criteria for Adverse Events-defined chronic health condition outcomes were independently abstracted. Associations between sepsis and cumulative incidence of chronic health conditions (eg, cardiovascular, pulmonary, kidney, neurological, and neurocognitive outcomes) were compared by adjusted hazard ratios from Cox proportional hazards logistic regression. Inverse propensity score weighting was used to adjust for potential confounders, including age, year of diagnosis, and leukemia type. Results: The study sample consisted of 644 adult survivors of pediatric leukemia (329 women [51.1%] and 315 men [48.9%]; including 56 with a history of acute myeloid leukemia and 585 with a history of acute lymphoblastic leukemia) who were most recently evaluated at a median age of 24.7 (IQR, 21.2-28.3) years at a median time after leukemia diagnosis of 17.3 (IQR, 13.7-21.9) years. Severe sepsis during treatment of acute childhood leukemia occurred in 46 participants (7.1%). Participants who experienced severe sepsis during treatment were more likely to develop moderate to severe neurocognitive impairment (29 of 46 [63.0%] vs 310 of 598 [51.8%]; adjusted hazard ratio, 1.86 [95% CI, 1.61-2.16]; P < .001) significantly affecting attention, executive function, memory and visuospatial domains. Sepsis was not associated with long-term risk of cardiovascular, pulmonary, kidney, or neurological chronic health conditions. Conclusions and Relevance: In this cohort study of long-term outcomes in survivors of pediatric leukemia, severe sepsis during anticancer therapy for leukemia was associated with a selectively increased risk for development of serious neurocognitive sequelae. Efforts to reduce the effects of anticancer therapy on long-term function and quality of life in survivors might include prevention of severe sepsis during therapy and early detection or amelioration of neurocognitive deficits in survivors of sepsis.

Analyzing Multiple Social Determinants of Health Using Different Clustering Methods.

Social determinants of health (SDoH) have become an increasingly important area to acknowledge and address in healthcare; however, dealing with these measures in outcomes research can be challenging due to the inherent collinearity of these factors. Here we discuss our experience utilizing three statistical methods-exploratory factor analysis (FA), hierarchical clustering, and latent class analysis (LCA)-to analyze data collected using an electronic medical record social risk screener called Protocol for Responding to and Assessing Patient Assets, Risks, and Experience (PRAPARE). The PRAPARE tool is a standardized instrument designed to collect patient-reported data on SDoH factors, such as income, education, housing, and access to care. A total of 2380 patients had complete PRAPARE and neighborhood-level data for analysis. We identified a total of three composite SDoH clusters using FA, along with four clusters identified through hierarchical clustering, and four latent classes of patients using LCA. Our results highlight how different approaches can be used to handle SDoH, as well as how to select a method based on the intended outcome of the researcher. Additionally, our study shows the usefulness of employing multiple statistical methods to analyze complex SDoH gathered using social risk screeners such as the PRAPARE tool.

Age and sex differences in the association between neighborhood socioeconomic environment and incident diabetes: Results from the diabetes location, environmental attributes and disparities (LEAD) network.

Objective: Worse neighborhood socioeconomic environment (NSEE) may contribute to an increased risk of type 2 diabetes (T2D). We examined whether the relationship between NSEE and T2D differs by sex and age in three study populations. Research design and methods: We conducted a harmonized analysis using data from three independent longitudinal study samples in the US: 1) the Veteran Administration Diabetes Risk (VADR) cohort, 2) the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, and 3) a case-control study of Geisinger electronic health records in Pennsylvania. We measured NSEE with a z-score sum of six census tract indicators within strata of community type (higher density urban, lower density urban, suburban/small town, and rural). Community type-stratified models evaluated the likelihood of new diagnoses of T2D in each study sample using restricted cubic splines and quartiles of NSEE. Results: Across study samples, worse NSEE was associated with higher risk of T2D. We observed significant effect modification by sex and age, though evidence of effect modification varied by site and community type. Largely, stronger associations between worse NSEE and diabetes risk were found among women relative to men and among those less than age 45 in the VADR cohort. Similar modification by age group results were observed in the Geisinger sample in small town/suburban communities only and similar modification by sex was observed in REGARDS in lower density urban communities. Conclusions: The impact of NSEE on T2D risk may differ for males and females and by age group within different community types.

Patient-level factors associated with hemoglobin A1C testing in Alabama Medicaid beneficiaries with diabetes.

AIM: We evaluated patient-level factors associated with receipt of hemoglobin A1c (HbA1c) testing among Alabama Medicaid beneficiaries with type 2 diabetes. METHODS: We conducted a retrospective analysis of person-year observations from Medicaid claims data from 2011 to 2020. Adults aged 19-64 years with type 2 diabetes and continuous enrollment in Medicaid for study year and year prior were included. Primary outcomes were ≥ 1 and ≥ 2 HbA1c test(s) per year. We conducted multivariable Poisson regression stratified by Medicaid eligibility reason (disability, poverty) examining the association of study year, demographics, clinical factors, and healthcare utilization with HbA1c testing. RESULTS: We analyzed 288,379 observations, 51% with disability-based, 49% poverty-based eligibility. Overall, 57% observations had ≥ 1 HbA1c, 35% had ≥ 2 HbA1c tests. More observations with disability-based than poverty-based eligibility had ≥ 1 (76% vs. 38%) and ≥ 2 HbA1c tests (49% vs. 20%). Patient-level factors were associated with a higher likelihood of having ≥ 1 HbA1c: Black race and older age (disability-based eligibility); year after 2011, female sex, and younger age (poverty-based eligibility); and rurality, insulin use, endocrinology care, diabetes complications, and ambulatory care visits (both groups). CONCLUSIONS: Just over one-third of adult Alabama Medicaid beneficiaries with diabetes had ≥ 2 HbA1c tests per year; testing frequency differed by Medicaid eligibility.

Trends and Predictors of Glycemic Control Among Adults With Type 2 Diabetes Covered by Alabama Medicaid, 2011-2019.

INTRODUCTION: Despite advances in diabetes management, only one-quarter of people with diabetes in the US achieve optimal targets for glycated hemoglobin A1c (HbA1c), blood pressure, and cholesterol. We sought to evaluate temporal trends and predictors of achieving glycemic control among adults with type 2 diabetes covered by Alabama Medicaid from 2011 through 2019. METHODS: We completed a retrospective analysis of Medicaid claims and laboratory data, using person-years as the unit of analysis. Inclusion criteria were being aged 19 to 64 years, having a diabetes diagnosis, being continuously enrolled in Medicaid for a calendar year and preceding 12 months, and having at least 1 HbA1c result during the study year. Primary outcomes were HbA1c thresholds of <7% and <8%. Primary exposure was study year. We conducted separate multivariable-adjusted logistic regressions to evaluate relationships between study year and HbA1c thresholds. RESULTS: We included 43,997 person-year observations. Mean (SD) age was 51.0 (9.9) years; 69.4% were women; 48.1% were Black, 42.9% White, and 0.4% Hispanic. Overall, 49.1% had an HbA1c level of <7% and 64.6% <8%. Later study years and poverty-based eligibility were associated with lower probability of reaching target HbA1c levels of <7% or <8%. Sex, race, ethnicity, and geography were not associated with likelihood of reaching HbA1c <7% or <8% in any model. CONCLUSION: Later study years were associated with lower likelihood of meeting target HbA1c levels compared with 2011, after adjusting for covariates. With approximately 35% not meeting an HbA1c target of <8%, more work is needed to improve outcomes of low-income adults with type 2 diabetes.

Measuring continuity of care for diabetes: which visits to include?

OBJECTIVES: Continuity of care measures are widely used to evaluate the quality of health care delivery, but which visits are included vary across studies. Our objective was to determine how the provider specialties included affect continuity values, year-to-year stability, and association with emergency department (ED) visits. STUDY DESIGN: Retrospective study of Alabama Medicaid administrative data. METHODS: We included beneficiaries with diabetes who had at least 3 outpatient visits in each of 2018 and 2019 (N = 9578). We defined 3 provider groupings: all providers, diabetes-broad (primary care, cardiology, neurology, endocrinology, ophthalmology, nephrology, and psychiatry), and diabetes-narrow (primary care and endocrinology). Continuity of care was calculated using the Continuity of Care Index (COCI) for each provider grouping. We compared correlation between measures and from year to year using Spearman correlations, and we used multivariable logistic regression to determine association with ED visits. RESULTS: The mean COCI was 0.54 using visits with all providers, 0.64 with diabetes-broad providers, and 0.83 with diabetes-narrow providers. COCI with diabetes-narrow providers was moderately correlated with the broader sets of providers (Spearman ρ, 0.52-0.65). Comparing each participant's COCI in 2018 with that in 2019, the mean intraperson difference was similar (0.16-0.22), and correlation was moderate (Spearman ρ, 0.41-0.47) for each measure. COCI had similar weak association with ED visits using each provider grouping (odds ratio, 0.99; 95% CI, 0.98-0.99 for each 0.1-unit difference in COCI). CONCLUSIONS: Continuity values differed substantially depending on which provider specialties were included. The importance of this variation is uncertain, as continuity was weakly associated with ED visits using each of the measures.

Cardiovascular Risk Factor Disparities in Adult Survivors of Childhood Cancer Compared With the General Population.

Background: It is unknown whether a history of childhood cancer modifies the established disparities in cardiovascular risk factors (CVRFs) observed in the general population. Objectives: We sought to determine if disparities in CVRFs by race/ethnicity are similar among childhood cancer survivors compared with the general population. Methods: The Childhood Cancer Survivor Study (CCSS) is a retrospective cohort with a longitudinal follow-up of 24,084 5-year survivors diagnosed between 1970 and 1999. Multivariable piecewise exponential regression estimated incidence rate ratios (IRRs) for hypertension, hyperlipidemia, diabetes, obesity, and ≥2 CVRFs by race/ethnicity. The CCSS sibling cohort and the National Health and Nutrition Examination Survey cohort were used to compare the sociodemographic-adjusted IRRs for same-race/same-ethnicity disparities. Results: Non-Hispanic Black (NHB) (n = 1,092) and Hispanic (n = 1,405) survivors compared with non-Hispanic White (NHW) (n = 13,960) survivors reported a higher cumulative incidence of diabetes (8.4%, 9.7%, and 5.1%, respectively); obesity (47.2%, 48.9%, and 30.2%, respectively); multiple CVRFs (17.7%, 16.6%, and 12.3%, respectively); and, for NHB survivors, hypertension (19.5%, 13.6%, and 14.3%, respectively) by 40 years of age (P < 0.001). Controlling for sociodemographic and treatment factors compared with NHW survivors, IRRs for NHB were increased for hypertension (IRR: 1.4; 95% CI: 1.1-1.8), obesity (IRR: 1.7; 95% CI: 1.4-2.1), and multiple CVRFs (IRR: 1.6; 95% CI: 1.2-2.1). IRRs for Hispanic survivors were increased for diabetes (IRR: 1.8; 95% CI: 1.2-2.6) and obesity (IRR: 1.4; 95% CI: 1.2-1.7). The pattern of IRRs for CVRF differences was similar among CCSS sibling and National Health and Nutrition Examination Survey cohorts. Conclusions: The higher burden of CVRFs among NHB and Hispanic survivors compared with NHW survivors was similar to the general population. The promotion of cardiovascular health equity is critical in this high-risk population.

Real-world integration of the protocol for responding to and assessing patients' assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center.

Objective: To describe the real-world deployment of a tool, the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE), to assess social determinants of health (SDoH) in an electronic medical record (EMR). Methods: We employed the collection of the PRAPARE tool in the EMR of a large academic health system in the ambulatory clinic and emergency department setting. After integration, we evaluated SDoH prevalence, levels of missingness, and data anomalies to inform ongoing collection. We summarized responses using descriptive statistics and hand-reviewed data text fields and patterns in the data. Data on patients who were administered with the PRAPARE from February to December 2020 were extracted from the EMR. Patients missing ≥ 12 PRAPARE questions were excluded. Social risks were screened using the PRAPARE. Information on demographics, admittance status, and health coverage were extracted from the EMR. Results: Assessments with N = 6531 were completed (mean age 54 years, female (58.6%), 43.8% Black). Missingness ranged from 0.4% (race) to 20.8% (income). Approximately 6% of patients were homeless; 8% reported housing insecurity; 1.4% reported food needs; 14.6% had healthcare needs; 8.4% needed utility assistance; and 5% lacked transportation related to medical care. Emergency department patients reported significantly higher proportions of suboptimal SDoH. Conclusions: Integrating the PRAPARE assessment in the EMR provides valuable information on SDoH amenable to intervention, and strategies are needed to increase accurate data collection and to improve the use of data in the clinical encounter.

The Association of Neighborhood Characteristics and Frailty in Childhood Cancer Survivors: A Report from the St. Jude Lifetime Cohort Study.

BACKGROUND: Childhood cancer survivors experience reduced physiologic reserve, or frailty, earlier and more frequently than peers. In other populations, frailty is impacted by one's neighborhood. This study's purpose was to evaluate associations between neighborhood characteristics and frailty in childhood cancer survivors. METHODS: Participants in the St. Jude Lifetime Cohort Study with geocoded residential addresses were analyzed. Pre-frailty/Frailty was defined as having 1-2/≥3 of sarcopenia, muscle weakness, poor endurance, slow walking speed, and exhaustion from direct assessments. Neighborhood characteristics [e.g., access to exercise opportunities and healthy food, neighborhood socioeconomic status (nSES), and rurality/urbanicity] were determined using publicly available geospatial data. Nested multivariable logistic regression models identified associations between neighborhood characteristics and pre-frailty/frailty, adjusting for chronic health conditions, individual health behaviors and socio-demographics, and high-risk cancer treatment exposures. RESULTS: For our cohort (N = 3,806, 46.79% female, 81.40% white, mean age 33.63±9.91 years), compared with non-frail survivors (n = 2,573; 67.6%), pre-frail (n = 900; 23.6%) and frail survivors (n = 333; 8.7%) were more likely to live in neighborhoods with decreased exercise opportunities (frail OR: 1.62, 1.26-2.09), reduced healthy food access (pre-frail OR: 1.28, 1.08-1.51; frail OR: 1.36, 1.06-1.75), and lower nSES (pre-frail OR: 1.31, 1.12-1.52; frail OR: 1.64, 1.30-2.07). Participants had 8% increased odds (95% confidence interval, 2%-14%) of being pre-frail/frail if they lived in "resource poor" neighborhoods as opposed to "resource rich" neighborhoods after adjusting for other pre-frailty/frailty risk factors. CONCLUSIONS: The neighborhood a childhood cancer survivor resides in as an adult is associated with pre-frailty/frailty. IMPACT: This study provides valuable information for creating interventions using neighborhood-level factors to mitigate frailty and improve health outcomes in survivors. See related commentary by Bhandari and Armenian, p. 997.

Perspective: Acknowledging a Hierarchy of Social Needs in Diabetes Clinical Care and Prevention.

The evidence of suboptimal social determinants of health (SDoH) on poor health outcomes has resulted in widespread calls for research to identify ways to measure and address social needs to improve health outcomes and reduce disparities. While assessing SDoH has become increasingly important in diabetes care and prevention research, little guidance has been offered on how to address suboptimal determinants in diabetes-related clinical care, prevention efforts, medical education and research. Not surprisingly, many patients experience multiple social needs - some that are more urgent (housing) than others (transportation/resources), therefore the order in which these needs are addressed needs to be considered in the context of diabetes care/outcomes. Here we discuss how conceptualizing diabetes related health through the lens of Maslow's hierarchy of needs has potential to help prioritize individual social needs that should be addressed to improve outcomes in the context of population-level determinants in the communities where people live.

Diabetes distress and self-reported health in a sample of Alabama Medicaid-covered adults before and during the COVID-19 pandemic.

Temporary closures of outpatient health facilities and transitions to virtual care during the COVID-19 pandemic interrupted the care of millions of patients with diabetes contributing to worsening psychosocial factors and enhanced difficulty in managing type 2 diabetes mellitus. We explored associations between COVID time period and self-reported diabetes distress on self-reported health among a sample of Alabama Medicaid-covered adults with diabetes pre-COVID (2017-2019) and during-COVID (2020-2021). Method: In this cross-sectional study, we surveyed a population-based sample of adults with type 2 diabetes covered by the Alabama Medicaid Agency. Participants were dichotomized into pre-COVID (March 2017 to October 2019) vs during-COVID (October 2020 to May 2021) groups. Participants with missing data were removed from analyses. We assessed diabetes related stress by the Diabetes Distress Scale. We measured self-reported health using a single item with a 5-point Likert scale. We ran logistic regressions modeling COVID time period on self-reported poor health controlling for demographics, severity of diabetes, and diabetes distress. Results: In this sample of 1822 individuals, median age was 54, 74.5% were female and 59.4% were Black. Compared to pre-COVID participants, participants surveyed during COVID were younger, more likely to be Black (64.1% VS 58.2%, p=0.01) and female (81.8% VS 72.5%, p<0.001). This group also had fewer individuals from rural areas (29.2% VS 38.4%, p<0.001), and shorter diabetes duration (7 years VS 9 years, p<0.001). During COVID individuals reported modestly lower levels of diabetes distress (1.2 VS 1.4, p<0.001) when compared to the pre-COVID group. After adjusting for demographic differences, diabetes severity, and diabetes distress, participants responding during COVID had increased odds of reporting poor health (Odds ratio [OR] 1.41, 95% Confidence Interval [CI] 1.11-1.80). Discussion: We found respondents were more likely to report poorer health during COVID compared to pre-COVID. These results suggest that increased outreach may be needed to address diabetes management for vulnerable groups, many of whom were already at high risk for poor outcomes prior to the pandemic.

Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction.

INTRODUCTION: Including race as a biological construct in risk prediction models may guide clinical decisions in ways that cause harm and widen racial disparities. This study reports on using race versus social determinants of health (SDoH) in predicting the associations between cardiometabolic disease severity (assessed using cardiometabolic disease staging) and COVID-19 hospitalization. METHODS: Electronic medical record data on patients with a positive COVID-19 polymerase chain reaction test in 2020 and a previous encounter in the electronic medical record where cardiometabolic disease staging clinical data (BMI, blood glucose, blood pressure, high-density lipoprotein cholesterol, and triglycerides) were available from 2017 to 2020, were analyzed in 2021. Associations between cardiometabolic disease staging and COVID-19 hospitalization adding race and SDoH (individual and neighborhood level [e.g., Social Vulnerability Index]) in different models were examined. Area under the curve was used to assess predictive performance. RESULTS: A total of 2,745 patients were included (mean age of 58 years, 59% female, 47% Black). In the cardiometabolic disease staging model, area under the curve was 0.767 vs 0.777 when race was included. Adding SDoH to the cardiometabolic model improved the area under the curve to 0.809 (p<0.001), whereas the addition of SDoH and race increased the area under the curve to 0.811. In race-stratified models, the area under the curve for non-Hispanic Blacks was 0.781, whereas the model for non-Hispanic Whites performed better with an area under the curve of 0.821. CONCLUSIONS: Cardiometabolic disease staging was predictive of hospitalization after a positive COVID-19 test. Adding race did not markedly increase the predictive ability; however, adding SDoH to the model improved the area under the curve to ≥0.80. Future research should include SDoH with biological variables in prediction modeling to capture social experience of race.

Associations between cardiometabolic disease severity, social determinants of health (SDoH), and poor COVID-19 outcomes.

OBJECTIVE: This study aimed to determine the ability of retrospective cardiometabolic disease staging (CMDS) and social determinants of health (SDoH) to predict COVID-19 outcomes. METHODS: Individual and neighborhood SDoH and CMDS clinical parameters (BMI, glucose, blood pressure, high-density lipoprotein, triglycerides), collected up to 3 years prior to a positive COVID-19 test, were extracted from the electronic medical record. Bayesian logistic regression was used to model CMDS and SDoH to predict subsequent hospitalization, intensive care unit (ICU) admission, and mortality, and whether adding SDoH to the CMDS model improved prediction was investigated. Models were cross validated, and areas under the curve (AUC) were compared. RESULTS: A total of 2,873 patients were identified (mean age: 58 years [SD 13.2], 59% were female, 45% were Black). CMDS, insurance status, male sex, and higher glucose values were associated with increased odds of all outcomes; area-level social vulnerability was associated with increased odds of hospitalization (odds ratio: 1.84, 95% CI: 1.38-2.45) and ICU admission (odds ratio 1.98, 95% CI: 1.45-2.85). The AUCs improved when SDoH were added to CMDS (p < 0.001): hospitalization (AUC 0.78 vs. 0.82), ICU admission (AUC 0.77 vs. 0.81), and mortality (AUC 0.77 vs. 0.83). CONCLUSIONS: Retrospective clinical markers of cardiometabolic disease and SDoH were independently predictive of COVID-19 outcomes in the population.

Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples.

OBJECTIVE: We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural. RESULTS: Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways. CONCLUSIONS: Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.