Search

BACKGROUND: COVID-19 and diabetes both contribute to large global disease burdens. PURPOSE: To quantify the prevalence of diabetes in various COVID-19 disease stages and calculate the population attributable fraction (PAF) of diabetes to COVID-19–related severity and mortality. DATA SOURCES: Systematic review identified 729 studies with 29,874,938 COVID-19 patients. STUDY SELECTION: Studies detailed the prevalence of diabetes in subjects with known COVID-19 diagnosis and severity. DATA EXTRACTION: Study information, COVID-19 disease stages, and diabetes prevalence were extracted. DATA SYNTHESIS: The pooled prevalence of diabetes in stratified COVID-19 groups was 14.7% (95% CI 12.5–16.9) among confirmed cases, 10.4% (7.6–13.6) among nonhospitalized cases, 21.4% (20.4–22.5) among hospitalized cases, 11.9% (10.2–13.7) among nonsevere cases, 28.9% (27.0–30.8) among severe cases, and 34.6% (32.8–36.5) among deceased individuals, respectively. Multivariate metaregression analysis explained 53–83% heterogeneity of the pooled prevalence. Based on a modified version of the comparative risk assessment model, we estimated that the overall PAF of diabetes was 9.5% (7.3–11.7) for the presence of severe disease in COVID-19–infected individuals and 16.8% (14.8–18.8) for COVID-19–related deaths. Subgroup analyses demonstrated that countries with high income levels, high health care access and quality index, and low diabetes disease burden had lower PAF of diabetes contributing to COVID-19 severity and death. LIMITATIONS: Most studies had a high risk of bias. CONCLUSIONS: The prevalence of diabetes increases with COVID-19 severity, and diabetes accounts for 9.5% of severe COVID-19 cases and 16.8% of deaths, with disparities according to country income, health care access and quality index, and diabetes disease burden. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Evidence is limited regarding the associations between vitamin D status and microvascular complications in individuals with type 2 diabetes (T2D), among whom vitamin D deficiency or insufficiency is particularly common. In this study we aimed to prospectively investigate the associations of serum 25-hydroxyvitamin D [25(OH)D] and vitamin D receptor (VDR) polymorphisms with risk of diabetic microvascular complications. RESEARCH DESIGN AND METHODS: This analysis included 14,709 participants with T2D who were free of microvascular complications from the UK Biobank. Incidence of diabetic microvascular complications was ascertained via electronic health records. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% CIs. RESULTS: Median serum 25(OH)D concentration was 40.7 nmol/L (interquartile range 27.5, 56.4). During a median of 11.2 years of follow-up, 1,370 people developed diabetic microvascular complications. Compared with participants with 25(OH)D <25 nmol/L, individuals with 25(OH)D ≥75 nmol/L had a multivariable-adjusted HR of 0.65 (95% CI 0.51, 0.84) for composite diabetic microvascular complications, 0.62 (0.40, 0.95) for diabetic retinopathy, 0.56 (0.40, 0.79) for diabetic nephropathy, and 0.48 (0.26, 0.89) for diabetic neuropathy. In addition, in comparisons with participants with 25(OH)D <25 nmol/L and minor allele homozygotes (TT of rs1544410 and GG of rs731236), the multivariable-adjusted HRs of composite diabetic microvascular complications were 0.54 (0.38, 0.78) and 0.55 (0.38, 0.80) for participants with serum 25(OH)D ≥50 nmol/L and major allele homozygotes (CC and AA), respectively, although no significant interaction was observed. CONCLUSIONS: Higher serum 25(OH)D concentrations were significantly associated with lower risk of diabetic microvascular complications, including diabetic retinopathy, diabetic nephropathy, and diabetic neuropathy. Our findings suggest a potential beneficial role of maintaining adequate vitamin D status in the prevention of diabetic microvascular complications. [ABSTRACT FROM AUTHOR]

Objective: To assess national trends in out-of-pocket (OOP) costs among adults aged 18-64 years with diabetes in the U.S.Research Design and Methods: Using data from the 2001-2017 Medical Expenditure Panel Survey, we estimated total per person annual OOP costs (insurance premiums, prescription drug costs, inpatient and outpatient deductibles, copays, and other payments not covered by insurance) and high OOP cost rate, defined as the percentage of people with OOP spending >10% of their family's pretax income. We examined trends overall, by subgroup (insurance type, income level, insulin use, size of patient's employer, and whether the patient was enrolled in a high deductible health plan), and by type of service. Changes in trends were identified using joinpoint analysis; costs were adjusted to 2017 U.S. dollars.Results: From 2001 to 2017, OOP costs decreased 4.3%, from $4,328 to $4,139, and the high OOP cost rate fell 32%, from 28 to 19% (P < 0.001). Changes in the high OOP cost rate varied by subgroup, declining among those with public or no insurance and those with an income <200% of the federal poverty level (P < 0.001) but remaining stable among those with private insurance and higher income. Drug prescription OOP costs decreased among all subgroups (P < 0.001). Decreases in total (-$58 vs. -$37, P < 0.001) and prescription (-$79 vs. -$68, P < 0.001) OOP costs were higher among insulin users than noninsulin users.Conclusions: OOP costs among U.S. nonelderly adults with diabetes declined, especially among those least able to afford them. Future studies may explore factors contributing to the decline in OOP costs and the impact on the quality of diabetes care and complication rates. [ABSTRACT FROM AUTHOR]

Objective: We examined the proportion of American adults without type 2 diabetes that engages in lifestyle behaviors known to reduce type 2 diabetes risk.Research Design and Methods: We conducted a cross-sectional analysis of 3,679 nonpregnant, nonlactating individuals aged ≥20 years without diabetes (self-reported diagnosis or glycated hemoglobin ≥6.5% [8 mmol/mol] or fasting plasma glucose ≥126 mg/dL) and who provided 2 days of reliable dietary data in the 2007-2012 National Health and Nutrition Examination Surveys (NHANES). We used the average of 2 days of dietary recall and self-reported leisure-time physical activity to assess whether participants met type 2 diabetes risk reduction goals (meeting four or more MyPlate recommendations [adequate consumption of fruits, vegetables, dairy, grains, meat, beans, and eggs]; not exceeding three maximum allowances for alcoholic beverages, added sugars, fat, and cholesterol; and meeting physical activity recommendations [≥150 min/week]).Results: Approximately 21%, 29%, and 13% of individuals met fruit, vegetable, and dairy goals, respectively. Half (51.6%) met the goal for total grains, compared with 18% for whole grains, and 54.2% met the meat/beans goal and 40.6% met the oils goal. About one-third (37.8%) met the physical activity goal, and 58.6% met the weight loss/maintenance goal. Overall, 3.1% (95% CI 2.4-4.0) of individuals met the majority of type 2 diabetes risk reduction goals. Younger age and lower educational attainment were associated with lower probability of meeting goals.Conclusions: A small proportion of U.S. adults engages in risk reduction behaviors. Research and interventions targeted at young and less-educated segments of the population may help close gaps in risk reduction behaviors. [ABSTRACT FROM AUTHOR]

Objective: To determine the impact of a health system-wide primary care diabetes management system, which included targeted guidelines for type 2 diabetes (T2DM) and prediabetes (dysglycemia) screening, on detection of previously undiagnosed dysglycemia cases.Research Design and Methods: Intervention included electronic health record (EHR)-based decision support and standardized providers and staff training for using the American Diabetes Association guidelines for dysglycemia screening. Using EHR data, we identified 40,456 adults without T2DM or recent screening with a face-to-face visit (March 2011-December 2013) in five urban clinics. Interrupted time series analyses examined the impact of the intervention on trends in three outcomes: 1) monthly proportion of eligible patients receiving dysglycemia testing, 2) two negative comparison conditions (dysglycemia testing among ineligible patients and cholesterol screening), and 3) yield of undiagnosed dysglycemia among those tested.Results: Baseline monthly proportion of eligible patients receiving testing was 7.4-10.4%. After the intervention, screening doubled (mean increase + 11.0% [95% CI 9.0, 13.0], proportion range 18.6-25.3%). The proportion of ineligible patients tested also increased (+5.0% [95% CI 3.0, 8.0]) with no concurrent change in cholesterol testing (+0% [95% CI -0.02, 0.05]). About 59% of test results in eligible patients showed dysglycemia both before and after the intervention.Conclusions: Implementation of a policy for systematic dysglycemia screening including formal training and EHR templates in urban academic primary care clinics resulted in a doubling of appropriate testing and the number of patients who could be targeted for treatment to prevent or delay T2DM. [ABSTRACT FROM AUTHOR]