The role of structural racism and geographical inequity in diabetes outcomes.

Diabetes is pervasive, exponentially growing in prevalence, and outpacing most diseases globally. In this Series paper, we use new theoretical frameworks and a narrative review of existing literature to show how structural inequity (structural racism and geographical inequity) has accelerated rates of diabetes disease, morbidity, and mortality globally. We discuss how structural inequity leads to large, fixed differences in key, upstream social determinants of health, which influence downstream social determinants of health and resultant diabetes outcomes in a cascade of widening inequity. We review categories of social determinants of health with known effects on diabetes outcomes, including public awareness and policy, economic development, access to high-quality care, innovations in diabetes management, and sociocultural norms. We also provide regional perspectives, grounded in our theoretical framework, to highlight prominent, real-world challenges.

Interventions to address global inequity in diabetes: international progress.

Diabetes is a serious chronic disease with high associated burden and disproportionate costs to communities based on socioeconomic, gender, racial, and ethnic status. Addressing the complex challenges of global inequity in diabetes will require intentional efforts to focus on broader social contexts and systems that supersede individual-level interventions. We codify and highlight best practice approaches to achieve equity in diabetes care and outcomes on a global scale. We outline action plans to target diabetes equity on the basis of the recommendations established by The Lancet Commission on Diabetes, organising interventions by their effect on changing the ecosystem, building capacity, or improving the clinical practice environment. We present international examples of how to address diabetes inequity in the real world to show that approaches addressing the individual within a larger social context, in addition to addressing structural inequity, hold the greatest promise for creating sustainable and equitable change that curbs the global diabetes crisis.

Addressing Structural Inequalities, Structural Racism, and Social Determinants of Health: a Vision for the Future.

Significant national discourse has focused on the idea of structural inequalities and structural racism within a variety of societal sectors, including healthcare. This perspective provides an understanding of the historic and pervasive nature of structural inequalities and structural racism; uses well-known frameworks in health equity research for conceptualizing structural inequality and structural racism; offers a summary of the consequences of structural inequalities and structural racism on modern-day health outcomes; and concludes with strategies and suggestions for a way forward. Recommended strategies across different sectors of influence include (a) employment and economic empowerment sector: creating capacity for individuals to earn livable wages; (b) education sector: developing new funding structures to ensure equal opportunities are offered to all; (c) healthcare sector: prioritizing universal access to high-quality health care, including mental health treatment; (d) housing sector: improving access to affordable, safe housing through public-private partnerships; (e) criminal justice sector: focusing reform on restorative justice that is people-centric instead of punitive; and (f) environmental sector: creating sustainable systems that alleviate downstream consequences of climate change. The recommended strategies account for the mutually reinforcing and pervasive nature of structural inequalities/structural racism and target key sectors of influence to enhance overall health outcomes and achieve equity regardless of race, ethnicity, or socioeconomic status.

Differential Effect of Patient- and Provider-Level Factors on Patient Satisfaction Scores in Academic General Internal Medicine Clinics.

OBJECTIVE: Determine whether patient-level or provider-level factors have greater influence on patient satisfaction scores in an academic general internal medicine clinic. METHODS: Two years of data (2017-2019) from the Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CGCAHPS) surveys from ambulatory internal medicine clinic visits in an academic health center located in the Midwest United States were used. Patient satisfaction was measured using the overall provider satisfaction score (0-10), dichotomized with 9-10 defined as satisfactory and 0-8 as unsatisfactory. Provider-level independent variables included age, sex, race/ethnicity, provider type, service type, clinical effort, academic rank, and years since graduation. Patient-level factors included age, sex, race/ethnicity, education, and Epic Risk Score. Generalized mixed-effects logistic regression models were used to investigate associations between top-box satisfaction score and patient- and provider-level factors, accounting for the nesting of patients within providers. RESULTS: Thirty-three providers and 4597 patients were included in the analysis. Male providers (OR, 1.57; 95% CI, 1.00, 2.47), minority group 2 (OR, 3.54; 95% CI, 1.24, 10.07) and minority group 3 (OR, 6.04; 95% CI, 1.45, 25.12), faculty (OR, 3.83; 95% CI, 1.56, 9.36), and primary care providers (OR, 5.60; 95% CI, 1.62, 19.34) had increased odds of having a top-box rating compared with females, minority group 1, advanced practice providers, and perioperative providers respectively. Age was the only patient independent correlate of top-box rating with a 3% increased odds of top-box rating for every year increase in age (OR, 1.03; 95% CI 1.02, 1.03). CONCLUSIONS: In this academic general internal medicine clinic, top-box satisfaction scores were more strongly associated with provider-level factors, including provider race/ethnicity, provider type, and service type, as opposed to patient-level factors. Further research is needed to confirm these findings and identify potential system-level interventions.

Identifying Individuals with Highest Social Risk in Adults with Type 2 Diabetes Using Item Response Theory.

OBJECTIVE: The aim of this analysis was to create a parsimonious tool to screen for high social risk using item response theory to discriminate across social risk factors in adults with type 2 diabetes. METHODS: Cross-sectional data of 615 adults with diabetes recruited from two primary care clinics were used. Participants completed assessments including validated scales on economic instability (financial hardship), neighborhood and built environment (crime, violence, neighborhood rating), education (highest education, health literacy), food environment (food insecurity), social and community context (social isolation), and psychological risk factors (perceived stress, depression, serious psychological distress, diabetes distress). Item response theory (IRT) models were used to understand the association between a participant's underlying level of a particular social risk factor and the probability of that response. A two-parameter logistic IRT model was used with each of the 12 social determinant factors being added as a separate parameter in the model. Higher values in item discrimination indicate better ability of a specific social risk factor in differentiating participants from each other. RESULTS: Rate of crime reported in a neighborhood (discrimination 3.13, SE 0.50; item difficulty - 0.68, SE 0.07) and neighborhood rating (discrimination 4.02, SE 0.87; item difficulty - 1.04, SE 0.08) had the highest discrimination. CONCLUSIONS: Based on these findings, crime and neighborhood rating discriminate best between individuals with type 2 diabetes who have high social risk and those with low social risk. These two questions can be used as a parsimonious social risk screening tool to identify high social risk.

The Associations Between Medical and Mental Health Conditions and Health Care Utilization in US Adults with Past-Year Criminal Legal Involvement.

BACKGROUND: Every year, millions of US adults return home from prison or jail, and they visit the emergency department and experience hospitalizations at higher rates than the general population. Little is known about the primary conditions that drive this acute care use. OBJECTIVE: To determine the individual and combined associations between medical and mental health conditions and acute health care utilization among individuals with recent criminal legal involvement in a nationally representative sample of US adults. DESIGN: We examined the association between having medical or mental, or both, conditions (compared to none), and acute care utilization using negative binomial regression models adjusted for relevant socio-demographic covariates. PARTICIPANTS: Adult respondents to the National Survey of Drug Use and Health (2015-2019) who reported past year criminal legal involvement. MAIN MEASURES: Self-reported visits to the emergency department and nights spent hospitalized. RESULTS: Among 9039 respondents, 12.4% had a medical condition only, 34.6% had a mental health condition only, and 19.2% had both mental and medical conditions. In adjusted models, incident rate ratio (IRR) for ED use for medical conditions only was 1.32 (95% CI 1.05, 1.66); for mental conditions only, the IRR was 1.36 (95% CI 1.18, 1.57); for both conditions, the IRR was 2.13 (95% CI 1.81, 2.51). For inpatient use, IRR for medical only: 1.73 (95% CI 1.08, 2.76); for mental only, IRR: 2.47 (95% CI 1.68, 3.65); for both, IRR: 4.26 (95% CI 2.91, 6.25). CONCLUSION: Medical and mental health needs appear to contribute equally to increased acute care utilization among those with recent criminal legal involvement. This underscores the need to identify and test interventions which comprehensively address both medical and mental health conditions for individuals returning to the community to improve both health care access and quality.

Understanding the relationship between social risk factors and functional limitation among stroke survivors in the US.

BACKGROUND: Stroke is the fifth leading cause of death and disability in the United States. Social risk factors contribute to recovery from stroke, however the relationship between social risk factors and functional limitation among stroke survivors remains unknown. METHODS: Data on 2,888 adults with stroke from the National Health Interview Survey from 2016-2018 was analyzed. The primary independent variables included six social risk factors: economic instability, lack of community, educational deficit, food insecurity, social isolation, and inadequate access to care. The outcome measure was functional limitation count. Negative binomial regression models were run to test the relationship between the independent and dependent variables adjusting for covariates. RESULTS: Overall, 56% of the study participants were aged 65+, 70% were Non-Hispanic White, and 95% had at least one comorbidity. The mean functional limitation count was 1.8. In the unadjusted model, each social risk factor was significantly associated with functional limitation. In the fully adjusted model, significant association with functional limitation was found in individuals reporting economic instability (Incidence rate ratio [IRR] 1.65, 95% CI 1.33, 2.06), food insecurity (IRR 1.28, 95% CI 1.15, 1.42), and social isolation (IRR 1.64, 95% CI 1.48, 1.82). CONCLUSIONS: Social risk factors such as economic instability, food insecurity and social isolation are significantly associated with functional limitation in adults with stroke. Interventions designed to address both social and medical needs have the potential to improve physical functioning and other clinical outcomes in stroke survivors.

Historic Residential Redlining and Present-Day Social Determinants of Health, Home Evictions, and Food Insecurity within US Neighborhoods.

OBJECTIVE: Examine the association between historic residential redlining and present-day racial/ethnic composition of neighborhoods, racial/ethnic differences in social determinant of health domains, and risk of home evictions and food insecurity. RESEARCH DESIGN AND METHODS: We examined data on 12,334 (for eviction sample), and 8996 (for food insecurity sample), census tracts in 213 counties across 37 states in the USA with data on exposure to historic redlining. First, we examined relationships between Home Owners' Loan Corporation (HOLC) redlining grades (A="Best", B="Still Desirable", C="Definitely Declining", D="Hazardous") and present-day racial/ethnic composition and racial/ethnic differences in social determinant of health domains of neighborhoods. Second, we examined whether historic redlining is associated with present-day home eviction rates (measured across eviction filings rates, and eviction judgment rates for 12,334 census tracts in 2018) and food insecurity (measured across low supermarket access, low supermarket access and income, low supermarket access and low car ownership for 8996 census tracts in 2019). Multivariable regression models were adjusted for census tract population, urban/rural designation, and county level fixed effects. RESULTS: Relative to areas with a historic HOLC grading of "A (Best)", areas with a "D (Hazardous)" grading had a 2.59 (95%CI=1.99-3.19; p-value<0.01) higher rate of eviction filings, and a 1.03 (95%CI=0.80-1.27; p-value<0.01) higher rate of eviction judgments. Compared to areas with a historic HOLC grading of "A (Best)", areas rated with a "D (Hazardous)" had a 16.20 (95%CI=15.02-17.79; p-value<0.01) higher rate of food insecurity based on supermarket access and income, and a 6.15 (95%CI =5.53-6.76; p-value<0.01) higher rate of food insecurity based on supermarket access and car ownership. CONCLUSIONS: Historic residential redlining is significantly associated with present-day home evictions and food insecurity, highlighting persistent associations between structural racism and present-day social determinants of health.

Modern Day Consequences of Historic Redlining: Finding a Path Forward.

There is emerging evidence that structural racism is a major contributor to poor health outcomes for ethnic minorities. Structural racism captures upstream historic racist events (such as slavery, black code, and Jim Crow laws) and more recent state-sanctioned racist laws in the form of redlining. Redlining refers to the practice of systematically denying various services (e.g., credit access) to residents of specific neighborhoods, often based on race/ethnicity and primarily within urban communities. Historical redlining is linked to increased risk of diabetes, hypertension, and early mortality due to heart disease with evidence suggesting it impacts health through suppressing economic opportunity and human capital, or the knowledge, skills, and value one contributes to society. Addressing structural racism has been a rallying call for change in recent years-drawing attention to the racialized impact of historical policies in the USA. Unfortunately, the enormous scope of work has also left people feeling incapable of effecting the very change they seek. This paper highlights a path forward by briefly discussing the origins of historical redlining, highlighting the modern-day consequences both on health and at the societal level, and suggest promising initiatives to address the impact.

Relationship between mental health diagnoses and COVID-19 test positivity, hospitalization, and mortality in Southeast Wisconsin.

BACKGROUND: There is a paucity of literature on the relationship between pre-existing mental health conditions and coronavirus disease-2019 (COVID-19) outcomes. The aim was to examine the association between pre-existing mental health diagnosis and COVID-19 outcomes (positive screen, hospitalization, mortality). METHODS: Electronic medical record data for 30 976 adults tested for COVID-19 between March 2020 and 10th July 2020 was analyzed. COVID-19 outcomes included positive screen, hospitalization among screened positive, and mortality among screened positive and hospitalized. Primary independent variable, mental health disorders, was based on ICD-10 codes categorized as bipolar, internalizing, externalizing, and psychoses. Descriptive statistics were calculated, unadjusted and adjusted logistic regression and Cox proportional hazard models were used to investigate the relationship between each mental health disorder and COVID-19 outcomes. RESULTS: Adults with externalizing (odds ratio (OR) 0.67, 95%CI 0.57-0.79) and internalizing disorders (OR 0.78, 95% CI 0.70-0.88) had lower odds of having a positive COVID-19 test in fully adjusted models. Adults with bipolar disorder had significantly higher odds of hospitalization in fully adjusted models (OR 4.27, 95% CI 2.06-8.86), and odds of hospitalization were significantly higher among those with externalizing disorders after adjusting for demographics (OR 1.71, 95% CI 1.23-2.38). Mortality was significantly higher in the fully adjusted model for patients with bipolar disorder (hazard ratio 2.67, 95% CI 1.07-6.67). CONCLUSIONS: Adults with mental health disorders, while less likely to test positive for COVID-19, were more likely to be hospitalized and to die in the hospital. Study results suggest the importance of developing interventions that incorporate elements designed to address smoking cessation, nutrition and physical activity counseling and other needs specific to this population to improve COVID-19 outcomes.

Dose response relationship between food insecurity and quality of life in United States adults: 2016-2017.

BACKGROUND: Food insecurity is associated with worse general health rating, but little research exists investigating whether there is a dose response relationship across levels of food security and mental and physical health domains at the population level. METHODS: Data from the Medical Expenditure Panel Survey (2016-2017) with US adults aged 18 years and older was used. The physical component score (PCS) and mental component score (MCS) of Quality of Life, served as the outcome measures. Four categories of food insecurity (high, marginal, low, very low food security) served as the primary independent variable. Linear regression was used to run unadjusted followed by adjusted models. Separate models were run for PCS and MCS. RESULTS: In a sample of US adults, 16.1% reported some degree of food insecurity. For PCS, marginal (ß = - 2.54 (p < 0.001), low (ß = - 3.41, (p < 0.001), and very low (ß = - 5.62, (p < 0.001) food security was associated with worse PCS scores, compared to adults with high food security. For MCS, marginal (ß = - 3.90 (p < 0.001), low (ß = - 4.79, (p < 0.001), and very low (ß = - 9.72, (p < 0.001) food security was associated with worse MCS scores, compared to adults with high food security. CONCLUSION: Increasing levels of food insecurity were associated with decreased physical and mental health quality of life scores. This relationship was not explained by demographic factors, socioeconomic factors, insurance, or comorbidity burden. This study suggests work is needed to mitigate the impact of social risk, such as food insecurity, on quality of life in adults, and understand pathways and mechanisms for this relationship.

Racial/ethnic differences in social determinants of health and health outcomes among adolescents and youth ages 10-24 years old: a scoping review.

INTRODUCTION: With the recent emergence of the Healthy People 2030 goals there is a need to understand the role of SDOH on health inequalities from an upstream perspective. This review summarizes the recent body of evidence on the impact of SDOH across adolescence and youth health outcomes by race/ethnicity using the Health People 2030 Framework. METHODS: A systematic, reproducible search was performed using PubMed, Academic Search Premier, PsychInfo, and ERIC. A total of 2078 articles were screened for inclusion. A total of 263 articles met inclusion criteria, resulting in 29 articles included for final synthesis. RESULTS: Across the 29 articles, 11 were cross-sectional, 16 were cohort, and 2 were experimental. Across SDOH categories (economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context), 1 study examined self-efficacy, 6 educational attainment, 10 behavior, 5 smoking, 11 alcohol use, 10 substance use, and 1 quality of life. The majority of outcomes represented in this search included health behaviors such as health risk behavior, smoking, alcohol use, and substance use. Across the 29 articles identified, significant differences existed across outcomes by race/ethnicity across SDOH factors, however magnitude of differences varied by SDOH category. DISCUSSION: SDOH differentially affect adolescents and youth across race/ethnicity. The lived adverse experiences, along with structural racism, increase the likelihood of adolescents and youth engaging in risky health behaviors and negatively influencing health outcomes during adolescence and youth. Research, public health initiatives, and policies integrating SDOH into interventions at early stage of life are needed to effectively reduce social and health inequalities at a population level.

Understanding the relationship between perceived discrimination and mortality in United States adults.

OBJECTIVE: To understand the relationship between mortality and three types of perceived discrimination (lifetime, daily, chronic job) using a nationally representative sample of U.S. adults. METHODS: Data from 4562 adults in the Midlife in the United States (MIDUS) between 2004 and 2006 (MIDUS II and MIDUS African American sample) were analyzed. Unadjusted associations between primary independent discrimination variables (lifetime, chronic job, daily) and mortality were analyzed using univariate Cox's proportional hazards regression models. Covariates were added to the models by group: predisposing (sex, age, race/ethnicity, education, marital status); enabling (household income, employment status, insurance status); and need factors (body mass index, diabetes, hypertension, stroke, cancer) to estimate hazard ratios. RESULTS: After adjusting for all covariates, hazard ratios for lifetime discrimination (HR: 1.09, p = 0.034) and daily discrimination (HR: 1.03, p = 0.030) were statistically significant. There was no relationship between mortality and chronic job discrimination (HR:1.03, p = 0.15). CONCLUSIONS: Adults experiencing lifetime and daily discrimination had significantly increased risk of mortality after adjusting for predisposing, enabling, and need factors. The findings highlight the importance of screening patients during clinical encounters for experiences of discrimination and providing appropriate resources to mitigate the negative impact of discriminatory events on mortality. Future research should work to fully understand the mechanism by which discrimination increases risk of mortality. These future findings should be used to develop targets for interventions designed to decrease mortality among adults who have experienced discrimination.

Examining the Relationship between Social Determinants of Health and Adverse Pregnancy Outcomes in Black Women.

OBJECTIVE: Our objective was to examine associations between social determinants of health (cultural, neighborhood, and psychosocial factors) and adverse pregnancy outcomes (gestational age at birth [GAB], preterm birth [PTB], and preeclampsia) in Black women. STUDY DESIGN: Cross-sectional data (n = 204) comprised adult Black women aged ≥18 years who delivered between 2013 and 2022 in Milwaukee,Wisconsin. Sequential unadjusted linear and logistic regression models were run to evaluate associations between social determinants of health and pregnancy outcomes. Stepwise regressions with forward selection were run to test the contribution of the social determinants of health to adverse pregnancy outcomes, independent of the contribution of established risk factors. RESULTS: Mean GAB was 37.9 weeks, 19.6% had a PTB and 17.7% had preeclampsia. In all fully adjusted models, education (ß0.15, 95% confidence interval [CI]: 0.005, 0.29), nulliparity (ß -1.26, 95%CI: -2.08, -0.44), multifetal gestation (ß -2.67, 95% CI: -4.29, -1.05), and exposure to neighborhood violence (ß -0.13, 95%CI: -0.25, -0.005) were associated with shortened GAB. Education (adjusted odds ratio [aOR]: 0.83, 95%CI: 0.69, 0.99), provider trust (aOR: 0.94, 95%CI: 0.88, 0.99), chance health locus of control (aOR: 0.88, 95%CI: 0.78, 0.99), and anxiety (aOR: 0.81, 95%CI: 0.69, 0.95) were associated with reduced odds of PTB. Powerful others health locus of control (aOR: 1.16, 95%CI: 1.03, 1.32), depression (aOR: 1.17, 95%CI: 1.01, 1.34), nulliparity (aOR: 4.73, 95%CI: 1.79, 12.55), multifetal gestation (aOR: 17.78, 95%CI: 3.49, 90.50), diabetes (aOR: 4.71, 95%CI: 1.17, 19.00), and obstructive sleep apnea (aOR: 44.28, 95%CI: 2.50, 783.12) were associated with increased odds of PTB. Internal health locus of control (aOR: 1.13, 95%CI: 1.01, 1.25), depression (aOR: 1.09, 95%CI: 1.01, 1.17), preeclampsia in a previous pregnancy (aOR: 5.96, 95% CI: 2.22, 16.01), and kidney disease (aOR: 34.27, 95% CI: 1.54, 763.75) were associated with preeclampsia. CONCLUSION: Provider trust, health locus of control, neighborhood violence, depression, and anxiety were associated with adverse pregnancy outcomes in Black women, independent of demographic and clinical risk factors. KEY POINTS: · We identified associations between exposure to neighborhood violence and gestational age at birth.. · Trust, locus of control, depression, and anxiety were associated with preterm birth and preeclampsia.. · Future research should focus on interventions that address social and clinical factors..

Do Chargemaster Prices Matter?: An Examination of Acute Care Hospital Profitability.

BACKGROUND: It remains widely debated whether chargemaster price markups are tied to hospital profitability. OBJECTIVE: To evaluate the effect of chargemaster markups on hospital profitability in the presence of unobserved hospital-specific (time-invariant) confounders, and cross-sectional dependence due to latent (common) policy shocks. DESIGN: We use interactive fixed effects methods to address concerns of unobserved hospital-specific (time-invariant) confounders, and cross-sectional dependence. SETTING: US acute care hospitals, 1996 through 2017 (ie, 22 y). PARTICIPANTS: Using primarily Medicare cost report data, we construct an unbalanced panel of 3499 acute care hospitals per year, or a total of 76,972 hospital-year observations. MEASUREMENTS: Chargemaster markups (above cost), profits per hospital inpatient discharge. RESULTS: Between 1996 and 2017, chargemaster markups increased (on average) by 155%, and the SD of the chargemaster markup distribution increased by 324%-indicating growing variability in the average markup strategies pursued by hospitals. Our preferred model specification implies that a unit increase of the hospital chargemaster markup is associated with a $261 ( P <0.01; 95% confidence interval: $232-$291) increase in profits per hospital inpatient discharge. These results are robust to a wide set of model specifications, the use of alternative profitability measurements, and the use of an alternative instrumental variable identification strategy. Additional subsample analysis that controls for a rich set of hospital quality measures and system affiliation information also yields similar results. CONCLUSION: We show that higher chargemaster markups are associated with higher hospital profitability. Additional research is needed to understand how chargemaster pricing impact health outcomes and health care disparities.

Hospital Price Transparency in the United States: An Examination of Chargemaster, Cash, and Negotiated, Price Variation for 14 Common Procedures.

BACKGROUND: Effective January 1, 2021, US hospitals were required to upload information on their chargemaster prices (database of list prices), discounted cash prices (commonly charged to self-pay patients), and payer-specific negotiated prices. OBJECTIVE: Examine how prices vary and are associated with hospital characteristics, market competition, and hospital quality. DESIGN SETTING AND PARTICIPANTS: This observational study used data on 14 common medical services across 1599 hospitals in 2021. Descriptive and regression analyses were used to study price variation. Analyses adjust for hospital characteristics, market competition and state fixed effects. RESULTS: Ninetieth -to-10th-percentile price markups factors (ratios) range between 3.2 and 11.5 for chargemaster; 6.1 and 19.7 for cash; and 6.6 and 30.0 for negotiated prices. Adjusted regression results indicate that hospitals' cash prices are on average 60% ( P <0.01) higher, and list prices are on average 164% ( P <0.01) higher, than negotiated prices. Systematic pricing differences across hospitals were noted, with urban hospitals having 14% ( P <0.01) lower prices than rural hospitals, teaching hospitals having 3% ( P <0.01) higher prices than nonteaching hospitals, and nonprofit hospitals pricing 9% ( P <0.01), and for-profit hospitals 39% ( P <0.01), higher than government owned hospitals. In addition, hospitals that contract with more insurance plans have higher prices, hospitals in more competitive markets have lower prices, and higher quality hospitals have on average 5% ( P <0.01) lower prices than lower quality hospitals. CONCLUSIONS: Prices all vary considerably across US hospitals. High quality hospitals are associated with lower pricing across all three sets of prices examined. Hospital price transparency may help consumers better identify hospitals that provide both high quality, and low cost, care.

Provider Network Structure and Black-to-White Disparity Gaps for Medicare Patients with Diabetes: County-Level Analysis of Cost, Utilization, and Clinical Care.

BACKGROUND: Prior work has shown that provider network structures correlate with outcomes such as patient costs, utilization, and care. However, it remains unknown whether certain provider networks are associated with reduced disparity gaps. METHODS: We study the population of Medicare beneficiaries with diabetes who were continuously enrolled in Medicare FFS in 2016. Using multivariable regression analysis of county-level risk adjusted cost, hospitalization, emergency department visits, A1c testing, and preventable diabetes-related hospitalizations, we measure the effect that the relative network connectivity of primary care providers (PCPs) in relation to medical and surgical specialists (PCP/Specialist degree centrality ratio), derived from Medicare patient sharing data, has on non-Hispanic black-to-white disparity gaps controlling for county-level socioeconomic and demographic variables and state fixed effects. RESULTS: Relative to non-Hispanic white, our adjusted results show that non-Hispanic black beneficiaries have $1673 (p<0.001) higher risk adjusted total costs, 2.6 (p<0.001) more hospitalizations (per 1000 beneficiaries), 11.6 (p<0.001) more ED visits (per 1000 beneficiaries), receive 2.2% (p<0.001) less A1c testing, and have 69.4 (p<0.01) more (per 100,000) avoidable diabetes-related hospital admissions. Our main results show that increasing the PCP/Specialist degree centrality ratio by one standard deviation is associated with a disparity gap decrease of 25.3% (p<0.01) in hospitalizations, 8.3% (p<0.05) in ED visits, 2.8% (p<0.01) in A1c testing, and 26.9% (p<0.1) in the volume of preventable diabetes-related hospital admissions. CONCLUSIONS: Network structures where PCPs are more central relative to medical and surgical specialists are associated with reduced non-Hispanic black-to-white disparity gaps, suggesting that how we organize and structure our health systems has implications for disparity gaps between non-Hispanic black and white Medicare beneficiaries with diabetes.

Gender Differences in the Relationship Between Food Insecurity and Body Mass Index Among Adults in the USA.

BACKGROUND: In the USA, nearly 40% of adults ≥ 20 years have a body mass index (BMI) ≥ 30, and 11% of households are reported as food insecure. In adults, evidence shows women are more likely than men to be food insecure. Among adults with food insecurity, differences in BMI exist between men and women with women reporting higher BMI. Factors associated with this difference in BMI between genders are less understood. OBJECTIVE: The aim of this study was to assess gender differences in the relationship between food insecurity and BMI. DESIGN: Hierarchical models were analyzed using a general linear model by entering covariates sequentially in blocks (demographics, lifestyle behaviors, comorbidities, and dietary variables) and stratified by gender. PARTICIPANTS: The sample included 25,567 adults in the USA from the National Health and Nutrition Examination Survey (NHANES), 2005-2014. MAIN MEASURES: The dependent variable was BMI, and food insecurity was the primary predictor. KEY RESULTS: Approximately 51% of the sample was women. Food insecure women were significantly more likely to have higher BMI compared to food secure women in the fully adjusted model after controlling for demographics (ß = 1.79; 95% CI 1.17, 2.41); demographic and lifestyle factors (ß = 1.79; 95% CI 1.19, 2.38); demographic, lifestyle, and comorbidities (ß = 1.21; 95% CI 0.65, 1.77); and demographic, lifestyle, comorbidities, and dietary variables (ß = 1.23; 95% CI 0.67, 1.79). There were no significant associations between food insecure and food secure men in the fully adjusted model variables (ß = 0.36; 95% CI - 0.26, 0.98). CONCLUSION: In this sample of adults, food insecurity was significantly associated with higher BMI among women after adjusting for demographics, lifestyle factors, comorbidities, and dietary variables. This difference was not observed among men. More research is necessary to understand this relationship among women.

Individual and Combined Effect of Diabetes and Lifetime Criminal Justice Involvement on Healthcare Utilization in US Adults, 2015-2019.

BACKGROUND: Diabetes and criminal justice involvement (CJI) are both associated with poor health outcomes and increased healthcare utilization. However, little is known about the additive effects of these risk factors when combined. This study examined the individual and combined effects of diabetes and CJI on healthcare utilization. METHODS: Data from the National Survey of Drug Use and Health (2015-2019) was used to create a cross-sectional, nationally representative sample of US adults with diabetes, CJI, combination of both, or neither. Negative binomial regression was used to test the association between those with CJI and diabetes (compared to diabetes alone) and three utilization types (outpatient, ED, and inpatient) controlling for relevant sociodemographic and clinical covariates. RESULTS: Of 212,079 respondents, representing 268,893,642 US adults, 8.8% report having diabetes alone, 15.2% report having CJI alone, and 1.8 % report both diabetes and lifetime CJI. After adjustment, those with diabetes and CJI had increased acute care utilization compared to those with diabetes alone (ED visits: IRR 1.13; 95% CI 1.00-1.28; nights hospitalized: IRR 1.34; 95% CI 1.08-1.67). There was no difference in outpatient utilization between those with both diabetes and CJI compared to those with diabetes alone (IRR 1.04, 95% CI 0.99-1.10). CONCLUSION: Individuals with complex social and health risks such as diabetes and lifetime CJI experience increased acute healthcare utilization but no difference in outpatient utilization. Tailored interventions that target both diabetes and CJI are needed to reduce unnecessary utilization in this population.

Factors associated with the double burden of malnutrition at the household level: A scoping review.

The double burden of malnutrition (DBM) at the household level has been defined as the coexistence of underweight children and overweight mothers within the same household. The objective of the scoping review was to identify and understand factors associated with DBM. We conducted the scoping review of published, peer-reviewed journal articles in two major databases used in public health research (PubMed and Web of Science). A total of 70 articles met the eligibility criteria. The following factors were identified: mother's age, height, educational level, occupation, food intake, breastfeeding, family income, family size, and urbanization type. Overall, results were heterogeneous. Two scenarios have been identified. The first scenario is those obese women with a job, having a sufficient income, a high educational level, the ability to purchase food, and live either in rural or urban areas. The second scenario is obese women without a job, having an insufficient income, a low educational level, without the ability to purchase food, and live either in rural or urban areas. The DBM at the household level is a complex public health problem. There is a need for target-specific interventions to address child undernutrition and maternal overweight/obesity simultaneously.