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.

Perceived discrimination in primary care: Does Payer mix matter?

INTRODUCTION: Previous literature has explored patient perceptions of discrimination by race and insurance status, but little is known about whether the payer mix of the primary care clinic (i.e., that is majority public insurance vs. majority private insurance clinics) influences patient perceptions of race- or insurance-based discrimination. METHODS: Between 2015-2017, we assessed patient satisfaction and perceived race- and insurance-based discrimination using a brief, anonymous post-clinic visit survey. RESULTS: Participants included 3,721 patients from seven primary care clinics-three public clinics and four private clinics. Results from unadjusted logistic regression models suggest higher overall reports of race- and insurance-based discrimination in public clinics compared with private clinics. In mulvariate analyses, increasing age, Black race, lower education and Medicaid insurance were associated with higher odds of reporting race- and insurance-based discrimination in both public and private settings. CONCLUSION: Reports of race and insurance discrimination are higher in public clinics than private clinics. Sociodemographic variables, such as age, Black race, education level, and type of insurance also influence reports of race- and insurance-based discrimination in primary care.

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.

Associations of Obesity and Neighborhood Factors With Urinary Stone Parameters.

INTRODUCTION: Obesity is associated with kidney stone disease, but it is unknown whether this association differs by SES. This study assessed the extent to which obesity and neighborhood characteristics jointly contribute to urinary risk factors for kidney stone disease. METHODS: This was a retrospective analysis of adult patients with kidney stone disease evaluated with 24-hour urine collection (2001-2020). Neighborhood-level socioeconomic data were obtained for a principal component analysis, which identified 3 linearly independent factors. Associations between these factors and 24-hour urine measurements were assessed using linear regression as well as groupings of 24-hour urine results using multivariable logistic regression. Finally, multiplicative interactions were assessed testing effect modification by obesity, and analyses stratified by obesity were performed. Analyses were performed in 2021. RESULTS: In total, 1,264 patients met the study criteria. Factors retained on principal component analysis represented SES, family structure, and housing characteristics. On linear regression, there was a significant inverse correlation between SES and 24-hour urine sodium (p=0.0002). On multivariable logistic regression, obesity was associated with increased odds of multiple stone risk factors (OR=1.61; 95% CI=1.15, 2.26) and multiple dietary factors (OR=1.33; 95% CI=1.06, 1.67). No significant and consistent multiplicative interactions were observed between obesity and quartiles of neighborhood SES, family structure, or housing characteristics. CONCLUSIONS: Obesity was associated with the presence of multiple stone risk factors and multiple dietary factors; however, the strength and magnitude of these associations did not vary significantly by neighborhood SES, family structure, and housing characteristics.

Area deprivation and respiratory morbidities in children with bronchopulmonary dysplasia.

INTRODUCTION: Infants and children diagnosed with bronchopulmonary dysplasia (BPD) have a higher likelihood of recurrent hospitalizations and asthma-like symptoms. Socio-environmental factors that influence the frequency and severity of pulmonary symptoms in these children during the preschool age are poorly understood. In this study, we used the Area Deprivation Index (ADI) to evaluate the relationship between the socio-environmental exposures in children with BPD and respiratory outcomes during the first few years of life. METHODS: A registry of subjects recruited from outpatient BPD clinics at Johns Hopkins University (n = 909) and the Children's Hospital of Philadelphia (n = 125) between January 2008 and October 2021 was used. Subjects were separated into tertiles by ADI scores aggregated to ZIP codes. Caregiver questionnaires were used to assess the frequency of respiratory morbidities and acute care usage for respiratory symptoms. RESULTS: The mean gestational age of subjects was 26.8 ± 2.6 weeks with a mean birthweight of 909 ± 404 g. The highest tertile (most deprived) of ADI was significantly associated with emergency department visits (aOR 1.72; p = 0.009), hospital readmissions (aOR 1.66; p = 0.030), and activity limitations (aOR 1.55; p = 0.048) compared to the lowest tertile. No association was seen with steroid, antibiotic or rescue medication use, trouble breathing, or nighttime symptoms. CONCLUSION: In this study, children with BPD who lived in areas of higher deprivation were more likely to be rehospitalized and have ED visits for respiratory reasons. Identifying socio-environmental factors that contribute to adverse pulmonary outcomes in children with BPD may provide opportunities for earlier interventions to improve long-term pulmonary outcomes.

The Mediating Role of Self-Efficacy in the Association Between Diabetes Education and Support and Self-Care Management.

RESULTS: A total of 1,318 participants were included in the study (mean age = 52.9 years, SD = 9.6; 72.5% female, 56.4% Black, 3.1% Hispanic). Diabetes education was associated with increases in self-care activity scores related to general diet, physical activity, glucose self-monitoring, and foot care; care coordination was associated with glucose self-monitoring. In addition, mediation analysis models confirmed that improvements in self-efficacy led to improved self-care activities scores, mediating the association of diabetes education and self-care activities. CONCLUSIONS: Diabetes education and self-efficacy were associated with better self-care. Receiving diabetes education led to a higher likelihood of engaging in self-care activities, driven in part by increases in self-efficacy. Future interventions that aim to improve diabetes self-management behaviors can benefit from targeting self-efficacy constructs and from the integration of diabetes education in the care coordination structure.

The Association Between Neighborhood Social Vulnerability and COVID-19 Testing, Positivity, and Incidence in Alabama and Louisiana.

Racial/ethnic and socioeconomic disparities in COVID-19 burden have been widely reported. Using data from the state health departments of Alabama and Louisiana aggregated to residential Census tracts, we assessed the relationship between social vulnerability and COVID-19 testing rates, test positivity, and incidence. Data were cumulative for the period of February 27, 2020 to October 7, 2020. We estimated the association of the 2018 Social Vulnerability Index (SVI) overall score and theme scores with COVID-19 tests, test positivity, and cases using multivariable negative binomial regressions. We adjusted for rurality with 2010 Rural-Urban Commuting Area codes. Regional effects were modeled as fixed effects of counties/parishes and state health department regions. The analytical sample included 1160 Alabama and 1105 Louisiana Census tracts. In both states, overall social vulnerability and vulnerability themes were significantly associated with increased COVID-19 case rates (RR 1.57, 95% CI 1.45-1.70 for Alabama; RR 1.36, 95% CI 1.26-1.46 for Louisiana). There was increased COVID-19 testing with higher overall vulnerability in Louisiana (RR 1.26, 95% CI 1.14-1.38), but not in Alabama (RR 0.95, 95% CI 0.89-1.02). Consequently, test positivity in Alabama was significantly associated with social vulnerability (RR 1.66, 95% CI 1.57-1.75), whereas no such relationship was observed in Louisiana (RR 1.05, 95% CI 0.98-1.12). Social vulnerability is a risk factor for COVID-19 infection, particularly among racial/ethnic minorities and those in disadvantaged housing conditions without transportation. Increased testing targeted to vulnerable communities may contribute to reduction in test positivity and overall COVID-19 disparities.

A System for Phenotype Harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program.

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.

Social support and diabetes distress among adults with type 2 diabetes covered by Alabama Medicaid.

AIMS: Diabetes distress affects approximately 36% of adults with diabetes and is associated with worse diabetes self-management and poor glycaemic control. We characterized participants' diabetes distress and studied the relationship between social support and diabetes distress. METHODS: In this cross-sectional study, we surveyed a population-based sample of adults with type 2 diabetes covered by Alabama Medicaid. We used the Diabetes Distress Scale assessing emotional burden, physician-related, regimen-related and interpersonal distress. We assessed participants' level of diabetes-specific social support and satisfaction with this support, categorized as low or moderate-high. We performed multivariable logistic regression of diabetes distress by level of and satisfaction with social support, adjusting for demographics, disease severity, self-efficacy and depressive symptoms. RESULTS: In all, 1147 individuals participated; 73% were women, 41% White, 58% Black and 3% Hispanic. Low level of or satisfaction with social support was reported by 11% of participants; 7% of participants had severe diabetes distress. Participants with low satisfaction with social support were statistically significantly more likely to have severe diabetes distress than those with moderate-high satisfaction, adjusted odds ratio 2.43 (95% CI 1.30, 4.54). CONCLUSIONS: Interventions addressing diabetes distress in adults with type 2 diabetes may benefit from a focus on improving diabetes-specific social support.

Social Risk Factors for Medication Nonadherence: Findings from the CARDIA Study.

Objectives: Nonadherence to medications has been documented, but the combined effect of social risk factors on medication nonadherence has not been investigated. Methods: We conducted a cross-sectional analysis of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a population-based prospective cohort. The sample (N = 1506) included subjects who at Year 20 (2005-06) were taking prescription medications and completed a 4-item Medication Adherence Scale. Social risk factors were education of high school or less, annual household income <$25,000, high financial strain, high chronic stress, low social support, and high social strain. Results: In a fully adjusted logistic regression model, income <$25,000 (OR = 2.37 [95% CI 1.12-4.98], p < .05) and high chronic stress (OR = 2.07 [95% CI 1.09-3.94], p < .05) were significantly associated with medication nonadherence. Individuals with ≥3 social risk factors had >3 times higher odds of nonadherence than counterparts with no social risk factors (OR = 3.26 [95% CI 1.72-6.19], p < .001). Conclusion: Low income and chronic stress are associated with medication nonadherence, and the odds of nonadherence increase with the accumulation of social risk factors. Findings may be used to develop risk prediction tools to identify individuals who can benefit from adherence-promoting interventions.

Diabetes risk scores for Hispanics living in the United States: A systematic review.

AIM: Undiagnosed diabetes is more prevalent among racial/ethnic minorities in the United States (U.S.). Despite the proliferation of risk scores, few have been validated in Hispanics populations. The aim of this study is to systematically review published studies that developed risk scores to identify undiagnosed Type 2 Diabetes Mellitus based on self-reported information that were validated for Hispanics in the U.S. METHODS: The search included PubMed, EMBASE, Cochrane and CINAHL from inception to 2016 without language restrictions. Risk scores whose main outcome was undiagnosed Type 2 diabetes reporting performance measures for Hispanics were included. RESULTS: We identified three studies that developed and validated risk scores for undiagnosed diabetes based on questionnaire data. Two studies were conducted in Latin America and one in the U.S. All three studies reported adequate performance (area under the receiving curve (AUC) range between0.68and 0.78). The study conducted in the U.S. reported a higher sensitivity of their risk score for Hispanics than whites. The limited number of studies, small size and heterogeneity of the combined cohorts provide limited evidence of the validity of risk scores for Hispanics. CONCLUSIONS: Efforts to develop and validate risk prediction models in Hispanic populations in the U.S are needed, particularly given the diversity of thisfast growing population. Healthcare professionals should be aware of the limitations of applying risk scores developed for the general population on Hispanics.