Background: In the United States, the COVID-19 pandemic has magnified the disproportionate and long-standing health disparities experienced by Black communities. Although it is acknowledged that social determinants of health (SDOH) rather than biological factors likely contribute to this disparity, few studies using rigorous analytic approaches in large, information-rich community-based data sets are dedicated to understanding the underlying drivers of these racial disparities. Objective: The overall aim of our study is to elucidate the mechanisms by which racial disparities in severe COVID-19 outcomes arise, using both quantitative and qualitative methods. Methods: In this protocol, we outline a convergent parallel mixed methods approach to identifying, quantifying, and contextualizing factors that contribute to the dramatic disparity in COVID-19 severity (ie, hospitalization, mortality) in Black versus white COVID-19 patients within the integrated health care system of Kaiser Permanente Georgia (KPGA). Toward this end, we will generate two quantitative cohorts of KPGA members with a confirmed COVID-19 diagnosis between January 1, 2020, and September 30, 2021: (1) an electronic medical record (EMR) cohort including routinely captured data on diagnoses, medications, and laboratory values, and a subset of patients hospitalized at Emory Healthcare to capture additional in-hospital data; and (2) a survey cohort, where participants will answer a range of questions related to demographics (eg, race, education), usual health behaviors (eg, physical activity, smoking), impact of COVID-19 (eg, job loss, caregiving responsibilities), and medical mistrust. Key outcomes of interest for these two cohorts include hospitalization, mortality, intensive care unit admission, hospital readmission, and long COVID-19. Finally, we will conduct qualitative semistructured interviews to capture perceptions of and experiences of being hospitalized with COVID-19 as well as related interactions with KPGA health care providers. We will analyze and interpret the quantitative and qualitative data separately, and then integrate the qualitative and quantitative findings using a triangulation design approach. Results: This study has been funded by a Woodruff Health Sciences grant from December 2020 to December 2022. As of August 31, 2022, 31,500 KPGA members diagnosed with COVID-19 have been included in the EMR cohort, including 3028 who were hospitalized at Emory Healthcare, and 482 KPGA members completed the survey. In addition, 20 KPGA members (10 Black and 10 white) have been interviewed about their experiences navigating care with COVID-19. Quantitative and qualitative data cleaning and coding have been completed. Data analysis is underway with results anticipated to be published in December 2022. Conclusions: Results from this mixed methods pilot study in a diverse integrated care setting in the southeastern United States will provide insights into the mechanisms underpinning racial disparities in COVID-19 complications. The quantitative and qualitative data will provide important context to generate hypotheses around the mechanisms for racial disparities in COVID-19, and may help to inform the development of multilevel strategies to reduce the burden of racial disparities in COVID-19 and its ongoing sequelae. Incorporating contextual information, elucidated from qualitative interviews, will increase the efficacy, adoption, and sustainability of such strategies.

Background: Few longitudinal data characterize kidney function decline among South Asians, one of the world's largest population groups. We aimed to identify estimated glomerular filtration rate (eGFR) trajectories in a population-based cohort from India and assess predictors of rapid kidney function decline. Methods: We used 6-year longitudinal data from participants of a population-representative study from Delhi and Chennai, India who had at least two serum creatinine measures and baseline CKD-EPI eGFR> 60 ml/min/1.73m2 (n=7779). We used latent class trajectory modeling to identify patterns of kidney function trajectory (CKD-EPI eGFR) over time. In models accounting for age, sex, education, and city, we tested the association between 15 hypothesized risk factors and rapid kidney function decline. Findings: Baseline mean eGFR was 108 (SD 16); median eGFR was 110 [IQR: 99-119] ml/min/1.73m2. Latent class trajectory modeling and functional characterization identified three distinct patterns of eGFR: class-1 (no decline; 58%) annual eGFR change 0.2 [0.1, 0.3]; class-2 (slow decline; 40%) annual eGFR change −0.2 [−0.4, −0.1], and class-3 (rapid decline; 2%) annual eGFR change −2.7 [−3.4, −2.0] ml/min/1.73m2. Albuminuria (>30 mg/g) was associated with rapid eGFR decline (OR for class-3 vs class-1: 5.1 [95% CI: 3.2; 7.9]; class-3 vs. class-2: 4.3 [95% CI:2.7; 6.6]). Other risk factors including self-reported diabetes, cardiovascular disease, peripheral arterial disease, and metabolic biomarkers such as HbA1c and systolic blood pressure were associated with rapid eGFR decline phenotype but potential ‘non-traditional’ risk factors such as manual labor or household water sources were not. Interpretation: Although mean and median eGFRs in our population-based cohort were higher than those reported in European cohorts, we found that a sizeable number of adults residing in urban India are experiencing rapid kidney function decline. Early and aggressive risk modification among persons with albuminuria could improve kidney health among South Asians. Funding: The CARRS study has been funded with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, under Contract No. HHSN2682009900026C and P01HL154996. Dr. Anand was supported by NIDDK K23DK101826 and R01DK127138.

According to the International Diabetes Federation, sub-Saharan Africa is experiencing the highest anticipate increase in the prevalence of type 2 diabetes (T2D) in the world and has the highest percent of people living with T2D who are undiagnosed. Therefore, diagnosis and treatment need prioritization. However, pharmacological hypoglycemics are often unavailable and bariatric surgery is not an option. Therefore, the ability to induce T2D remission through lifestyle intervention alone (LSI-alone) needs assessment. This scoping review evaluated trials designed to induce T2D remission by LSI-alone. PubMed, Embase, Cochrane, and CINAHL databases were searched for trials designed to induce T2D remission through LSI-alone. Of the 928 identified, 63 duplicates were removed. With abstract review, 727 irrelevant articles were excluded. After full-text review, 112 inappropriate articles were removed. The remaining 26 articles described 16 trials. These trials were published between 1984 and 2021 and were conducted in 10 countries, none of which were in Africa. Remission rates varied across trials. Predictors of remission were 10% weight loss and higher BMI, lower A1C and shorter T2D duration at enrollment. However, LSI-alone regimens for newly diagnosed and established T2D were very different. In newly diagnosed T2D, LSI-alone were relatively low-cost and focused on exercise and dietary counseling with or without calorie restriction (~1500 kcal/d). Presumably due to differences in cost, LSI-alone trials in newly diagnosed T2D had higher enrollments and longer duration. For established T2D trials, the focus was on arduous phased dietary interventions; phase 1: low-calorie meal replacement (<1000 kcal/day); phase 2: food re-introduction; phase 3: weight maintenance. In short, LSI-alone can induce remission in both newly diagnosed and established T2D. To demonstrate efficacy in Africa, initial trials could focus on newly diagnosed T2D. Insight gained could provide proof of concept and a foundation in Africa on which successful studies of LSI-alone in established T2D could be built.

Objective: Sparse data exist on population distributions of serum fibroblast growth factor-23 (FGF23) levels from developing, middle-income economies. FGF23 levels may differ substantially across regions based on differences in diet and urbanization. In a population-based study from North India, we tested the hypothesis that urinary phosphate excretion and FGF23 levels are lower among rural compared with urban participants, and among vegetarian compared with nonvegetarian participants. Methods: We measured 24-hour urinary phosphate, and serum parathyroid hormone and FGF23 in a subsample of the population-based Cardiometabolic Risk Reduction in South Asia and Indian Council of Medical Research Coronary Heart Disease surveys. We categorized participants according to diet and residence: urban nonvegetarians (n = 70), urban vegetarians (n = 564), and rural vegetarians (n = 558). Using least square means, we compared the groups' 24-hour urinary phosphate (with urban vegetarians as reference) and FGF23 levels after accounting for age, sex, diabetes, and body mass index. Results: Among 1,192 study participants, mean FGF23 was 41 ± 18 pg/mL, median parathyroid hormone was 44 (interquartile range [IQR] 31-60) pg/mL, and median 24-hour urinary phosphate excretion was 419 (IQR: 47-622) mg/day. Urinary phosphate was significantly higher in rural compared with urban vegetarians (median, 503; IQR, 334-543 versus 365; IQR, 199-399 mg/day), but adjusted mean FGF23 levels did not differ across study groups. Conclusion: In rural and urban India, urinary phosphate excretion was low, but FGF23 levels did not differ by residence or dietary preference. Homogenously low dietary phosphate intake across different settings and diets may partly explain the lack of differences in FGF23.

Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram oral glucose tolerance test (OGTT). Individuals with isolated IGT or combined IFG and IGT have increased risk for developing type 2 diabetes (T2D) and cardiovascular disease (CVD). Diagnosing prediabetes early and accurately is critical in order to refer high-risk individuals for intensive lifestyle modification. However, there is currently no international consensus for diagnosing prediabetes with HbA1c or glucose measurements based upon American Diabetes Association (ADA) and the World Health Organization (WHO) criteria that identify different populations at risk for progressing to diabetes. Various caveats affecting the accuracy of interpreting the HbA1c including genetics complicate this further. This review describes established methods for detecting glucose disorders based upon glucose and HbA1c parameters as well as novel approaches including the 1-hour plasma glucose (1-h PG), glucose challenge test (GCT), shape of the glucose curve, genetics, continuous glucose monitoring (CGM), measures of insulin secretion and sensitivity, metabolomics, and ancillary tools such as fructosamine, glycated albumin (GA), 1,5- anhydroglucitol (1,5-AG). Of the approaches considered, the 1-h PG has considerable potential as a biomarker for detecting glucose disorders if confirmed by additional data including health economic analysis. Whether the 1-h OGTT is superior to genetics and omics in providing greater precision for individualized treatment requires further investigation. These methods will need to demonstrate substantially superiority to simpler tools for detecting glucose disorders to justify their cost and complexity.

Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians, Inc., and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of Clinical Diabetes. The following article describes the establishment of a Diabetes Prevention Clinic for veterans with prediabetes.

The global incidence and prevalence of diabetes continue to rise [1]. Hence, identifying individuals at high risk for prediabetes and type 2 diabetes (T2D) is paramount. As glucose levels increase insidiously in the progression from normal glucose tolerance to prediabetes and T2D, early identification of high-risk individuals could result in the prescription of lifestyle interventions to decrease progression to T2D. HbA1c is widely used to screen for prediabetes (5.7–6.4% [39–46 mmol/mol]) and T2D (≥6.5% [48 mmol/mol]) [2]. However, HbA1c has poor sensitivity in identifying early pancreatic β-cell dysfunction [3]. Individuals with prediabetes, already on the accelerated slope of the glucose trajectory, are diagnosed too late in the progression to T2D when significant β-cell dysfunction has already occurred. Increased 1-hour plasma glucose (1-h PG) ≥ 155 mg/dL (8.6 mmol/L) during a 75-g oral glucose tolerance test (OGTT) is more predictive than HbA1c or 2-h PG for future development of diabetes, complications, and mortality [4–6]. However, measurement of the 1-h PG during the OGTT requires fasting. In addition, plasma glucose (PG) levels can become unstable if specimens are not properly handled [7]. A potential alternative approach for detecting early pancreatic β-cell dysfunction is implementation of continuous glucose monitoring (CGM) during an OGTT. CGM can identify increased glycemic variability (GV), an index of glucose fluctuation, in patients with T2D [8]. However, it is unclear if CGM can detect GV in high-risk subjects without diabetes or with HbA1c < 5.7% (39 mmol/mol).

Objective: Approximately 50% of obese Black patients with unprovoked diabetic ketoacidosis (DKA) or severe hyperglycemia (SH) at new-onset diabetes achieve near-normoglycemia remission with intensive insulin treatment. Despite the initial near-normoglycemia remission, most DKA/SH individuals develop hyperglycemia relapse after insulin discontinuation. Traditional biomarkers such as normal glucose tolerance at the time of remission were not predictive of hyperglycemia relapse. We tested whether 1-h plasma glucose (1-h PG) at remission predicts hyperglycemia relapse in Black patients with DKA/SH. Methods: Secondary analysis was performed of two prospective randomized controlled trials in 73 patients with DKA/SH at the safety net hospital with a median follow-up of 408 days. Patients with DKA/SH underwent a 5-point, 2-h 75-g oral glucose tolerance test after hyperglycemia remission. Hyperglycemia relapse is defined by fasting blood glucose (FBG) > 130 mg/dl, random blood glucose (BG) >180 mg/dl, or HbA1c > 7%. Results: During the median 408 (interquartile range: 110–602) days of follow-up, hyperglycemia relapse occurred in 28 (38.4%) participants. One-hour PG value ≥199 mg/dl discriminates hyperglycemia relapse (sensitivity: 64%; specificity: 71%). Elevated levels of 1-h PG (≥199 mg/dl) were independently associated with hyperglycemia relapse (adjusted hazard ratio: 2.40 [95% CI: 1.04, 5.56]). In a multivariable model with FBG, adding 1-h PG level enhanced the prediction of hyperglycemia relapse, with significant improvements in C-index (Δ: +0.05; p = 0.04), net reclassification improvement (NRI: 48.7%; p = 0.04), and integrated discrimination improvement (IDI: 7.8%; p = 0.02) as compared with the addition of 2-h PG (NRI: 20.2%; p = 0.42; IDI: 1.32%; p = 0.41) or HbA1c (NRI: 35.2%; p = 0.143; IDI: 5.8%; p = 0.04). Conclusion: One-hour PG at the time of remission is a better predictor of hyperglycemia relapse than traditional glycemic markers among obese Black patients presenting with DKA/SH. Testing 1-h PG at insulin discontinuation identifies individuals at high risk of developing hyperglycemia relapse.

Background Two coding risk variants in the Apo L1 gene (APOL1) underlie most of the excess risk for kidney diseases in recent African ancestry patients. Strength and consistency of the relationship between APOL1 high-risk genotypes and the risk of chronic kidney diseases (CKD) and end-stage renal disease (ESRD) are not uniform. Objective To conduct a systematic review and meta-analysis of prospective studies assessing the association of APOL1 genotypes and the risk of developing CKD, ESRD, and CKD to ESRD in adults. Methods Systematic search of MEDLINE, EMBASE, and Google Scholar was performed for prospective studies assessing the associations between APOL1 genotypes and CKD, ESRD, and progression from CKD to ESRD. Secondary analyses were to evaluate the annual kidney function change by APOL1 gene status. Random effects models were used to estimate pooled risk ratios (RRs) and weighted mean differences for outcomes of interest. Results The search yield 10 prospective during a follow-up period ranging from 4.4 to 25 years. The high-risk APOL1 genotype was associated with the incidence of CKD (RR:1.41[95% CI: 1.14–1.75]), the progression from CKD to ESRD (RR: 1.70[95% CI:1.44; 2.01]) compared with the low-risk APOL1 genotype. There was no appreciable association between high-risk APOL1 genotype with the incidence of ESRD. Furthermore, high-risk APOL1 genotype was associated with a marginal decrement in the annual eGFR decline (−0.55[95% CI: −0.94 to −0.16]) mL/min/1.73m2 compared with low-risk APOL1 genotype status. Conclusion In summary, African Americans carrying APOL1 high-risk genotypes are at increased risk of developing CKD and ESRD. Given that the APOL1 risk alleles are common among individuals with African ancestry, with ~18% of African Americans carrying high-risk alleles, these findings highlight the potential identification of subgroups of patients who may benefit from APOL1 screening and developing culturally-appropriate interventions.

To identify determinants of daily life stress in Africans in America, 156 African-born Blacks (Age: 40 ± 10 years (mean ± SD), range 22–65 years) who came to the United States as adults (age ≥ 18 years) were asked about stress, sleep, behavior and socioeconomic status. Daily life stress and sleep quality were assessed with the Perceived Stress Scale (PSS) and Pittsburgh Sleep Quality Index (PSQI), respectively. High-stress was defined by the threshold of the upper quartile of population distribution of PSS (≥16) and low-stress as PSS < 16. Poor sleep quality required PSQI > 5. Low income was defined as <40 k yearly. In the high and low-stress groups, PSS were: 21 ± 4 versus 9 ± 4, p < 0.001 and PSQI were: 6 ± 3 versus 4 ± 3, p < 0.001, respectively. PSS and PSQI were correlated (r = 0.38, p < 0.001). The odds of high-stress were higher among those with poor sleep quality (OR 5.11, 95% CI: 2.07, 12.62), low income (OR 5.03, 95% CI: 1.75, 14.47), and no health insurance (OR 3.01, 95% CI: 1.19, 8.56). Overall, in African-born Blacks living in America, daily life stress appears to be linked to poor quality sleep and exacerbated by low income and lack of health insurance.