Material needs security and cardiovascular risk factors in rural South Africa.

BACKGROUND: The prevalence of cardiovascular disease is burgeoning in low- and middle-income countries (LMICs). In sub-Saharan Africa, the prevalence of cardiovascular risk factors is increasing, though rates of CVD diagnosis and management remain low. Awareness of the influence of social determinants of health (SDOH) on cardiovascular outcomes is growing, however, most work focuses on high-income countries. Material needs security is a measure of SDOH that may be particularly relevant for LMICs. This study investigated the relationship between material needs security and cardiovascular risk in older adults living in South Africa. METHODS: The analysis included 5059 respondents age ≥ 40 in the Health and Aging in Africa survey, an observational cohort study administered in 2014 in Mpumalanga Province, South Africa. Linear regression models tested the association between material needs and eight cardiovascular risk factors (waist-to-hip ratio, body mass index, blood pressure, glucose, cholesterol, LDL, and triglycerides). Adjusted linear regression models controlled for sociodemographic confounders. RESULTS: There were significant adjusted associations found between increased material needs security and four cardiovascular risk factors, including waist-to-hip ratio (ß = 0.001; 95% CI [0.00002,0.002]), BMI (ß = 0.19; 95%CI=[0.14,0.24]), glucose (ß = 0.46; 95%CI=[0.02,0.90]), and triglycerides (ß = 0.26; 95%CI=[0.02,0.49]). CONCLUSION: Increased material needs security was associated with significantly increased cardiovascular risk in older adults in rural South Africa. These findings can inform the approach to treatment and management of cardiovascular disease in South Africa and similar LMICs. Future investigations should evaluate the implementation and efficacy of interventions that recognize the role of material needs security in cardiovascular risk.

Relationship Between Delay Discounting and Clinical Diabetes Outcomes: A Systematic Review.

OBJECTIVE: To evaluate the evidence on the relationship between delay discounting and clinical diabetes outcomes, identify current measures, and recommend areas for future work. METHODS: A reproducible search using OVID Medline, PsycINFO, PubMed, Science Direct, and Scopus was conducted. Articles published from database creation up to March 2024 were searched. Medical Subject Heading (MeSH) terms and keywords representing delay discounting and diabetes were used. Outcomes included hemoglobin A1c (HbA1c), LDL, body mass index (BMI), blood pressure, quality of life (QOL), psychosocial factors, self-care behaviors, and diabetes complications. RESULTS: A total of 15 articles met the inclusion criteria and were included for final synthesis. Overall, 14 studies included in this review found a significant relationship between delay discounting and diabetes-related outcomes, such that higher delay discounting is significantly related to worse diabetes outcomes for HbA1c, self-care behaviors, BMI, stress, and quality of life across self-reported measures of delay discounting and delay discounting tasks. CONCLUSIONS: Evidence supports the relationship between delay discounting and diabetes-related outcomes and self-care behaviors across measures of delay discounting and type of diabetes. To understand delay discounting as a mechanism driving diabetes outcomes and to develop targeted interventions, additional work using a multidisciplinary approach is needed to validate the construct, identify pathways, and refine intervention approaches that can be tested to improve population health.

A Regional Survey of Attitudes and Experiences in Determining When to Prescribe Intranasal Naloxone for Patients Seen in Palliative Care Clinics in the United States of America.

Background: Published guidelines that help clinicians identify patients who would benefit from the co-prescription of intranasal naloxone (IN) exclude "palliative care patients." In the absence of clear care standards, palliative care (PC) clinicians may experience uncertainty in how to approach IN co-prescriptions. Objective: Explore the attitudes of PC clinicians in the United States of America who work at regional health care institutions regarding IN prescriptions for patients they prescribe opioids for. Methods: An 18-question electronic survey was distributed to PC clinicians that practice at institutions in Wisconsin or Minnesota with at least 10 other PC clinicians between February and May 2023. The survey explored clinical scenarios in which respondents would and would not prescribe IN. Results: Fifty-six PC clinicians responded to the survey-response rate 41%. Most respondents (90.9%) did not feel IN prescriptions should be reserved for patients with a full code status; 67.9% of respondents felt that IN prescriptions are reasonable for certain patients with a terminal illness and comfort goals of care. Neither prognosis, duration of opioid therapy, nor dose of opioid therapy were significant factors in determining whether most respondents prescribed IN for their patients. Most respondents (81.8%) felt clinician counseling and patient consent were essential before prescribing IN. Conclusion: Most PC clinicians in our survey felt that IN prescriptions can be appropriate for patients they prescribe opioids for. Bystander safety was an emerging rationale for why respondents chose to prescribe IN for their patients. Despite public health efforts to make IN more freely available, most respondents felt clinician counseling was essential before prescribing IN for their patients.

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.

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.

Historic Redlining and Impact of Structural Racism on Diabetes Prevalence in a Nationally Representative Sample of U.S. Adults.

OBJECTIVE: We investigated direct and indirect relationships between historic redlining and prevalence of diabetes in a U.S. national sample. RESEARCH DESIGN AND METHODS: Using a previously validated conceptual model, we hypothesized pathways between structural racism and prevalence of diabetes via discrimination, incarceration, poverty, substance use, housing, education, unemployment, and food access. We combined census tract-level data, including diabetes prevalence from the Centers for Disease Control and Prevention PLACES 2019 database, redlining using historic Home Owners' Loan Corporation (HOLC) maps from the Mapping Inequality project, and census data from the Opportunity Insights database. HOLC grade (a score between 1 [best] and 4 [redlined]) for each census tract was based on overlap with historically HOLC-graded areas. The final analytic sample consisted of 11,375 U.S. census tracts. Structural equation modeling was used to investigate direct and indirect relationships adjusting for the 2010 population. RESULTS: Redlining was directly associated with higher crude prevalence of diabetes within a census tract (r = 0.01; P = 0.008) after adjusting for the 2010 population (χ2(54) = 69,900.95; P < 0.001; root mean square error of approximation = 0; comparative fit index = 1). Redlining was indirectly associated with diabetes prevalence via incarceration (r = 0.06; P < 0.001), poverty (r = -0.10; P < 0.001), discrimination (r = 0.14; P < 0.001); substance use (measured by binge drinking: r = -0.65, P < 0.001; and smoking: r = 0.35, P < 0.001), housing (r = 0.06; P < 0.001), education (r = -0.17; P < 0.001), unemployment (r = -0.17; P < 0.001), and food access (r = 0.14; P < 0.001) after adjusting for the 2010 population. CONCLUSIONS: Redlining has significant direct and indirect relationships with diabetes prevalence. Incarceration, poverty, discrimination, substance use, housing, education, unemployment, and food access may be possible targets for interventions aiming to mitigate the impact of structural racism on diabetes.

COVID-19 Information, Trust, and Risk Perception Across Diverse Communities in the United States: Initial Findings from a Multistate Community Engagement Alliance (CEAL).

Objectives. To provide initial findings from Community Engagement Alliance (CEAL), a multistate effort funded by the National Institutes of Health, to conduct urgent community-engaged research and outreach focused on COVID-19 awareness, education, and evidence-based response. Methods. We collected survey data (November 2020-November 2022) from 21 CEAL teams from 29 state and regional CEAL sites spanning 19 US states, the District of Columbia, and Puerto Rico, which covered priority populations served and trusted sources of information about COVID-19, including prevention behaviors, vaccination, and clinical trials. Results. A disproportionate number of respondents were Latino (45%) or Black (40%). There was considerable variability between CEAL sites regarding trusted sources of information, COVID-19 prevention, and COVID-19 vaccination. For example, more respondents (70%) reported health care providers as a trusted source of COVID-19 information than any other source (ranging from 6% to 87% by site). Conclusions. CEAL rapidly developed novel infrastructure to engage academic, public health, and community organizations to address COVID-19's impacts on underserved communities. CEAL provides an example of how to respond in future public health emergencies to quickly promote trustworthy, evidence-based information in ways that advance health equity. (Am J Public Health. 2024;114(S1):S112-S123. https://doi.org/10.2105/AJPH.2023.307504).