COVID-19 Outcomes Stratified by Control Status of Hypertension and Diabetes: Preliminary Findings From PCORnet, U.S

INTRODUCTION: Hypertension and diabetes are associated with increased COVID-19 severity, yet less is known about COVID-19 outcomes across levels of disease control for these conditions. METHODS: All adults aged ≥20 years with COVID-19 between March 1, 2020 and March 15, 2021 in 42 healthcare systems in National Patient-Centered Clinical Research Network were identified. RESULTS: Among 656,049 adults with COVID-19, 41% had hypertension, and 13% had diabetes. Of patients with classifiable hypertension, 35% had blood pressure <130/80 mmHg, 40% had blood pressure of 130‒139/80‒89 mmHg, 21% had blood pressure of 140‒159/90‒99 mmHg, and 6% had blood pressure ≥160/100 mmHg. Severe COVID-19 outcomes were more prevalent among those with blood pressure of ≥160/100 than among those with blood pressure of 130-139/80-89, including hospitalization (23.7% [95% CI=23.0, 24.4] vs 11.7% [95% CI=11.5, 11.9]), receipt of critical care (5.5% [95% CI=5.0, 5.8] vs 2.4% [95% CI=2.3, 2.5]), receipt of mechanical ventilation (3.0% [95% CI=2.7, 3.3] vs 1.2% [95% CI=1.1, 1.3]), and 60-day mortality (4.6% [95% CI=4.2, 4.9] vs 1.8% [95% CI=1.7, 1.9]). Of patients with classifiable diabetes, 44% had HbA1c <7%, 35% had HbA1c 7% to <9%, and 21% had HbA1c ≥9%. Hospitalization prevalence was 31.3% (95% CI=30.7, 31.9) among those with HbA1c <7% vs 40.2% (95% CI=39.4, 41.1) among those with HbA1c ≥9%; other outcomes did not differ substantially by HbA1c. CONCLUSIONS: These findings highlight the importance of appropriate management of hypertension and diabetes, including during public health emergencies such as the COVID-19 pandemic

Association Between Hypertension and Diabetes Control and COVID‐19 Severity: National Patient‐Centered Clinical Research Network, United States, March 2020 to February 2022

Background Hypertension and diabetes are associated with increased COVID‐19 severity. The association between level of control of these conditions and COVID‐19 severity is less well understood. Methods and Results This retrospective cohort study identified adults with COVID‐19, March 2020 to February 2022, in 43 US health systems in the National Patient‐Centered Clinical Research Network. Hypertension control was categorized as blood pressure (BP) <130/80, 130 to 139/80 to 89, 140 to 159/90 to 99, or ≥160/100 mm Hg, and diabetes control as glycated hemoglobin <7%, 7% to <9%, ≥9%. Adjusted, pooled logistic regression assessed associations between hypertension and diabetes control and severe COVID‐19 outcomes. Among 1 494 837 adults with COVID‐19, 43% had hypertension and 12% had diabetes. Among patients with hypertension, the highest baseline BP was associated with greater odds of hospitalization (adjusted odds ratio [aOR], 1.30 [95% CI, 1.23–1.37] for BP ≥160/100 versus BP <130/80), critical care (aOR, 1.30 [95% CI, 1.21–1.40]), and mechanical ventilation (aOR, 1.32 [95% CI, 1.17–1.50]) but not mortality (aOR, 1.08 [95% CI, 0.98–1.12]). Among patients with diabetes, the highest glycated hemoglobin was associated with greater odds of hospitalization (aOR, 1.61 [95% CI, 1.47–1.76] for glycated hemoglobin ≥9% versus <7%), critical care (aOR, 1.42 [95% CI, 1.31–1.54]), mechanical ventilation (aOR, 1.12 [95% CI, 1.02–1.23]), and mortality (aOR, 1.18 [95% CI, 1.09–1.27]). Black and Hispanic adults were more likely than White adults to experience severe COVID‐19 outcomes, independent of comorbidity score and control of hypertension or diabetes. Conclusions Among 1.5 million patients with COVID‐19, higher BP and glycated hemoglobin were associated with more severe COVID‐19 outcomes. Findings suggest that adults with poorest control of hypertension or diabetes might benefit from efforts to prevent and initiate early treatment of COVID‐19

Comparison of surveillance-based metrics for the assessment and monitoring of disease detection: simulation study about type 2 diabetes

BACKGROUND: Screening and detection of cases are a common public health priority for treatable chronic conditions with long subclinical periods. However, the validity of commonly-used metrics from surveillance systems for rates of detection (or case-finding) have not been evaluated. METHODS: Using data from a Danish diabetes register and a recently developed illness-death model of chronic diseases with subclinical conditions, we simulate two scenarios of different performance of case-finding. We report different epidemiological indices to assess case-finding in both scenarios and compare the validity of the results. RESULTS: The commonly used ratio of detected cases over total cases may lead to misleading conclusions. Instead, the ratio of undetected cases over persons without a diagnosis is a more valid index to distinguish the quality of case-finding. However, incidence-based measures are preferable to prevalence based indicators. CONCLUSION: Prevalence-based indices for assessing case-finding should be interpreted with caution. If possible, incidence-based indices should be preferred

Income-related inequalities in diagnosed diabetes prevalence among US adults, 2001−2018

Aims The overall prevalence of diabetes has increased over the past two decades in the United States, disproportionately affecting low-income populations. We aimed to examine the trends in income-related inequalities in diabetes prevalence and to identify the contributions of determining factors. Methods We estimated income-related inequalities in diagnosed diabetes during 2001−2018 among US adults aged 18 years or older using data from the National Health Interview Survey (NHIS). The concentration index was used to measure income-related inequalities in diabetes and was decomposed into contributing factors. We then examined temporal changes in diabetes inequality and contributors to those changes over time. Results Results showed that income-related inequalities in diabetes, unfavorable to low-income groups, persisted throughout the study period. The income-related inequalities in diabetes decreased during 2001−2011 and then increased during 2011−2018. Decomposition analysis revealed that income, obesity, physical activity levels, and race/ethnicity were important contributors to inequalities in diabetes at almost all time points. Moreover, changes regarding age and income were identified as the main factors explaining changes in diabetes inequalities over time. Conclusions Diabetes was more prevalent in low-income populations. Our study contributes to understanding income-related diabetes inequalities and could help facilitate program development to prevent type 2 diabetes and address modifiable factors to reduce diabetes inequalities

Projection of the future diabetes burden in the United States through 2060

Abstract Background In the United States, diabetes has increased rapidly, exceeding prior predictions. Projections of the future diabetes burden need to reflect changes in incidence, mortality, and demographics. We applied the most recent data available to develop an updated projection through 2060. Methods A dynamic Markov model was used to project prevalence of diagnosed diabetes among US adults by age, sex, and race (white, black, other). Incidence and current prevalence were from the National Health Interview Survey (NHIS) 1985–2014. Relative mortality was from NHIS 2000–2011 follow-up data linked to the National Death Index. Future population estimates including birth, death, and migration were from the 2014 Census projection. Results The projected number and percent of adults with diagnosed diabetes would increase from 22.3 million (9.1%) in 2014 to 39.7 million (13.9%) in 2030, and to 60.6 million (17.9%) in 2060. The number of people with diabetes aged 65 years or older would increase from 9.2 million in 2014 to 21.0 million in 2030, and to 35.2 million in 2060. The percent prevalence would increase in all race-sex groups, with black women and men continuing to have the highest diabetes percent prevalence, and black women and women of other race having the largest relative increases. Conclusions By 2060, the number of US adults with diagnosed diabetes is projected to nearly triple, and the percent prevalence double. Our estimates are essential to predict health services needs and plan public health programs aimed to reduce the future burden of diabetes

Additional file 1 of Comparison of surveillance-based metrics for the assessment and monitoring of disease detection: simulation study about type 2 diabetes

Scripts for the statistical software R. The zip-file contains the analysis for the simulation. For detailed instructions unzip the file and refer to the readme.txt file. (ZIP 4 kb

S1 File -

AimsThe overall prevalence of diabetes has increased over the past two decades in the United States, disproportionately affecting low-income populations. We aimed to examine the trends in income-related inequalities in diabetes prevalence and to identify the contributions of determining factors.MethodsWe estimated income-related inequalities in diagnosed diabetes during 2001−2018 among US adults aged 18 years or older using data from the National Health Interview Survey (NHIS). The concentration index was used to measure income-related inequalities in diabetes and was decomposed into contributing factors. We then examined temporal changes in diabetes inequality and contributors to those changes over time.ResultsResults showed that income-related inequalities in diabetes, unfavorable to low-income groups, persisted throughout the study period. The income-related inequalities in diabetes decreased during 2001−2011 and then increased during 2011−2018. Decomposition analysis revealed that income, obesity, physical activity levels, and race/ethnicity were important contributors to inequalities in diabetes at almost all time points. Moreover, changes regarding age and income were identified as the main factors explaining changes in diabetes inequalities over time.ConclusionsDiabetes was more prevalent in low-income populations. Our study contributes to understanding income-related diabetes inequalities and could help facilitate program development to prevent type 2 diabetes and address modifiable factors to reduce diabetes inequalities.</div

Decomposition of changes in diabetes inequalities during 2001−2011 and 2011−2018.

Decomposition of changes in diabetes inequalities during 2001−2011 and 2011−2018.</p

Decompositions of income-related inequalities in diabetes in 2001, 2011, and 2018.

Decompositions of income-related inequalities in diabetes in 2001, 2011, and 2018.</p