Regional and rural-urban patterns in the prevalence of diagnosed hypertension among older U.S. adults with diabetes, 2005-2017.

BACKGROUND: Hypertension prevalence among the overall US adult population has been relatively stable during the last two decades. However, whether this stabilization has occurred across rural-urban communities and across different geographic regions is unknown, particularly among older adults with diabetes who are likely to have concomitant cardiovascular risk factors. METHODS: This serial cross-sectional analysis used the 5% national sample of Medicare administrative claims data (n = 3,516,541) to examine temporal trends (2005-2017) in diagnosed hypertension among older adults with diabetes, across urban-rural communities and US census regions (Northeast, Midwest, South, and West). Joinpoint regression was used to obtain annual percent change (APC) in hypertension prevalence across rural-urban communities and geographic regions, and multivariable adjusted regression was used to assess associations between rural-urban communities and hypertension prevalence. RESULTS: The APC in the prevalence of hypertension was higher during 2005-2010, and there was a slowdown in the increase during 2011-2017 across all regions, with significant variations across rural-urban communities within each of the regions. In the regression analysis, in the adjusted model, older adults living in non-core (most rural) areas in the Midwest (PR = 0.988, 95% CI: 0.981-0.995) and West (PR = 0.935, 95% CI: 0.923-0.946) had lower hypertension prevalence than their regional counterparts living in large central metro areas. CONCLUSIONS: Although the magnitudes of these associations are small, differences in hypertension prevalence across rural-urban areas and geographic regions may have implications for targeted interventions to improve chronic disease prevention and management.

Associations between PM2.5 and O3 exposures and new onset type 2 diabetes in regional and national samples in the United States.

BACKGROUND: Exposure to particulate matter ≤2.5 µm in diameter (PM2.5) and ozone (O3) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM2.5 and O3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment. METHODS: Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM2.5 and O3. RESULTS: In two pollutant models, associations of PM2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 µg/m3 of PM2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type. CONCLUSIONS: Associations between PM2.5, O3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.

Prevalence of Testing for Diabetes Among US Adults With Overweight or Obesity, 2016-2019.

Introduction: Screening for prediabetes and type 2 diabetes may allow earlier detection, diagnosis, and treatment. The US Preventive Services Task Force recommends screening every 3 years for abnormal blood glucose among adults aged 40 to 70 years with overweight or obesity. Using IQVIA Ambulatory Electronic Medical Records, we estimated the proportion of adults aged 40 to 70 years with overweight or obesity who received blood glucose testing within 3 years from baseline in 2016. Methods: We identified 1,338,509 adults aged 40 to 70 years with overweight or obesity in 2016 and without pre-existing diabetes. We included adults whose records were present in the data set for at least 2 years before their index body mass index (BMI) in 2016 and 3 years after the index BMI (2017-2019), during which we examined the occurrence of blood glucose testing. We calculated the unadjusted and adjusted prevalence of receiving blood glucose testing. Results: The unadjusted prevalence of receiving blood glucose testing was 33.4% when it was defined as having a hemoglobin A1c or fasting plasma glucose measure. The unadjusted prevalence was 74.3% when we expanded the definition of testing to include random plasma glucose and unspecified glucose measures. Adults with obesity were more likely to receive the test than those with overweight. Men (vs women) and adults aged 50 to 59 years (vs other age groups) had higher testing rates. Conclusion: Our findings could inform clinical and public health promotion efforts to improve screening for blood glucose levels among adults with overweight or obesity.

Risk for Newly Diagnosed Diabetes >30 Days After SARS-CoV-2 Infection Among Persons Aged <18 Years - United States, March 1, 2020-June 28, 2021.

The COVID-19 pandemic has disproportionately affected people with diabetes, who are at increased risk of severe COVID-19.* Increases in the number of type 1 diabetes diagnoses (1,2) and increased frequency and severity of diabetic ketoacidosis (DKA) at the time of diabetes diagnosis (3) have been reported in European pediatric populations during the COVID-19 pandemic. In adults, diabetes might be a long-term consequence of SARS-CoV-2 infection (4-7). To evaluate the risk for any new diabetes diagnosis (type 1, type 2, or other diabetes) >30 days† after acute infection with SARS-CoV-2 (the virus that causes COVID-19), CDC estimated diabetes incidence among patients aged <18 years (patients) with diagnosed COVID-19 from retrospective cohorts constructed using IQVIA health care claims data from March 1, 2020, through February 26, 2021, and compared it with incidence among patients matched by age and sex 1) who did not receive a COVID-19 diagnosis during the pandemic, or 2) who received a prepandemic non-COVID-19 acute respiratory infection (ARI) diagnosis. Analyses were replicated using a second data source (HealthVerity; March 1, 2020-June 28, 2021) that included patients who had any health care encounter possibly related to COVID-19. Among these patients, diabetes incidence was significantly higher among those with COVID-19 than among those 1) without COVID-19 in both databases (IQVIA: hazard ratio [HR] = 2.66, 95% CI = 1.98-3.56; HealthVerity: HR = 1.31, 95% CI = 1.20-1.44) and 2) with non-COVID-19 ARI in the prepandemic period (IQVIA, HR = 2.16, 95% CI = 1.64-2.86). The observed increased risk for diabetes among persons aged <18 years who had COVID-19 highlights the importance of COVID-19 prevention strategies, including vaccination, for all eligible persons in this age group,§ in addition to chronic disease prevention and management. The mechanism of how SARS-CoV-2 might lead to incident diabetes is likely complex and could differ by type 1 and type 2 diabetes. Monitoring for long-term consequences, including signs of new diabetes, following SARS-CoV-2 infection is important in this age group.

Proximity to freshwater blue space and type 2 diabetes onset: the importance of historical and economic context.

Salutogenic effects of living near aquatic areas (blue space) remain underexplored, particularly in non-coastal and non-urban areas. We evaluated associations of residential proximity to inland freshwater blue space with new onset type 2 diabetes (T2D) in central and northeast Pennsylvania, USA, using medical records to conduct a nested case-control study. T2D cases (n=15,888) were identified from diabetes diagnoses, medication orders, and laboratory test results and frequency-matched on age, sex, and encounter year to diabetes-free controls (n=79,435). We calculated distance from individual residences to the nearest lake, river, tributary, or large stream, and residence within the 100-year floodplain. Logistic regression models adjusted for community socioeconomic deprivation and other confounding variables and stratified by community type (townships [rural/suburban], boroughs [small towns], city census tracts). Compared to individuals living ≥1.25 miles from blue space, those within 0.25 miles had 8% and 17% higher odds of T2D onset in townships and boroughs, respectively. Among city residents, T2D odds were 38-39% higher for those living 0.25 to <0.75 miles from blue space. Residing within the floodplain was associated with 16% and 14% higher T2D odds in townships and boroughs. A post-hoc analysis demonstrated patterns of lower residential property values with nearer distance to the region's predominant waterbody, suggesting unmeasured confounding by socioeconomic disadvantage. This may explain our unexpected findings of higher T2D odds with closer proximity to blue space. Our findings highlight the importance of historic and economic context and interrelated factors such as flood risk and lack of waterfront development in blue space research.

Diabetes Prevalence and Incidence Among Medicare Beneficiaries - United States, 2001-2015.

Diabetes affects approximately 12% of the U.S. adult population and approximately 25% of adults aged ≥65 years. From 2009 to 2017, there was no significant change in diabetes prevalence overall or among persons aged 65-79 years (1). However, these estimates were based on survey data with <5,000 older adults. Medicare administrative data sets, which contain claims for millions of older adults, afford an opportunity to explore both trends over time and heterogeneity within an older population. Previous studies have shown that claims data can be used to identify persons with diagnosed diabetes (2). This study estimated annual prevalence and incidence of diabetes during 2001-2015 using Medicare claims data for beneficiaries aged ≥68 years and found that prevalence plateaued after 2012 and incidence decreased after 2006. In 2015 (the most recent year estimated) prevalence was 31.6%, and incidence was 3.0%. Medicare claims can serve as an important source of data for diabetes surveillance for the older population, which can inform prevention and treatment strategies.

Prevalence of Diagnosed Diabetes in Adults by Diabetes Type - United States, 2016.

Currently 23 million U.S. adults have been diagnosed with diabetes (1). The two most common forms of diabetes are type 1 and type 2. Type 1 diabetes results from the autoimmune destruction of the pancreas's beta cells, which produce insulin. Persons with type 1 diabetes require insulin for survival; insulin may be given as a daily shot or continuously with an insulin pump (2). Type 2 diabetes is mainly caused by a combination of insulin resistance and relative insulin deficiency (3). A small proportion of diabetes cases might be types other than type 1 or type 2, such as maturity-onset diabetes of the young or latent autoimmune diabetes in adults (3). Although the majority of prevalent cases of type 1 and type 2 diabetes are in adults, national data on the prevalence of type 1 and type 2 in the U.S. adult population are sparse, in part because of the previous difficulty in classifying diabetes by type in surveys (2,4,5). In 2016, supplemental questions to help distinguish diabetes type were added to the National Health Interview Survey (NHIS) (6). This study used NHIS data from 2016 to estimate the prevalence of diagnosed diabetes among adults by primary type. Overall, based on self-reported type and current insulin use, 0.55% of U.S. adults had diagnosed type 1 diabetes, representing 1.3 million adults; 8.6% had diagnosed type 2 diabetes, representing 21.0 million adults. Of all diagnosed cases, 5.8% were type 1 diabetes, and 90.9% were type 2 diabetes; the remaining 3.3% of cases were other types of diabetes. Understanding the prevalence of diagnosed diabetes by type is important for monitoring trends, planning public health responses, assessing the burden of disease for education and management programs, and prioritizing national plans for future type-specific health services.

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

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.

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.

Novel Methods and Data Sources for Surveillance of State-Level Diabetes and Prediabetes Prevalence.

States bear substantial responsibility for addressing the rising rates of diabetes and prediabetes in the United States. However, accurate state-level estimates of diabetes and prediabetes prevalence that include undiagnosed cases have been impossible to produce with traditional sources of state-level data. Various new and nontraditional sources for estimating state-level prevalence are now available. These include surveys with expanded samples that can support state-level estimation in some states and administrative and clinical data from insurance claims and electronic health records. These sources pose methodologic challenges because they typically cover partial, sometimes nonrandom subpopulations; they do not always use the same measurements for all individuals; and they use different and limited sets of variables for case finding and adjustment. We present an approach for adjusting new and nontraditional data sources for diabetes surveillance that addresses these limitations, and we present the results of our proposed approach for 2 states (Alabama and California) as a proof of concept. The method reweights surveys and other data sources with population undercoverage to make them more representative of state populations, and it adjusts for nonrandom use of laboratory testing in clinically generated data sets. These enhanced diabetes and prediabetes prevalence estimates can be used to better understand the total burden of diabetes and prediabetes at the state level and to guide policies and programs designed to prevent and control these chronic diseases.

Using multi-year national survey cohorts for period estimates: an application of weighted discrete Poisson regression for assessing annual national mortality in US adults with and without diabetes, 2000-2006.

BACKGROUND: Monitoring national mortality among persons with a disease is important to guide and evaluate progress in disease control and prevention. However, a method to estimate nationally representative annual mortality among persons with and without diabetes in the United States does not currently exist. The aim of this study is to demonstrate use of weighted discrete Poisson regression on national survey mortality follow-up data to estimate annual mortality rates among adults with diabetes. METHODS: To estimate mortality among US adults with diabetes, we applied a weighted discrete time-to-event Poisson regression approach with post-stratification adjustment to national survey data. Adult participants aged 18 or older with and without diabetes in the National Health Interview Survey 1997-2004 were followed up through 2006 for mortality status. We estimated mortality among all US adults, and by self-reported diabetes status at baseline. The time-varying covariates used were age and calendar year. Mortality among all US adults was validated using direct estimates from the National Vital Statistics System (NVSS). RESULTS: Using our approach, annual all-cause mortality among all US adults ranged from 8.8 deaths per 1,000 person-years (95% confidence interval [CI]: 8.0, 9.6) in year 2000 to 7.9 (95% CI: 7.6, 8.3) in year 2006. By comparison, the NVSS estimates ranged from 8.6 to 7.9 (correlation = 0.94). All-cause mortality among persons with diabetes decreased from 35.7 (95% CI: 28.4, 42.9) in 2000 to 31.8 (95% CI: 28.5, 35.1) in 2006. After adjusting for age, sex, and race/ethnicity, persons with diabetes had 2.1 (95% CI: 2.01, 2.26) times the risk of death of those without diabetes. CONCLUSION: Period-specific national mortality can be estimated for people with and without a chronic condition using national surveys with mortality follow-up and a discrete time-to-event Poisson regression approach with post-stratification adjustment.

Modeling County-Level Rare Disease Prevalence Using Bayesian Hierarchical Sampling Weighted Zero-Inflated Regression.

Estimates of county-level disease prevalence have a variety of applications. Such estimation is often done via model-based small-area estimation using survey data. However, for conditions with low prevalence (i.e., rare diseases or newly diagnosed diseases), counties with a high fraction of zero counts in surveys are common. They are often more common than the model used would lead one to expect; such zeros are called 'excess zeros'. The excess zeros can be structural (there are no cases to find) or sampling (there are cases, but none were selected for sampling). These issues are often addressed by combining multiple years of data. However, this approach can obscure trends in annual estimates and prevent estimates from being timely. Using single-year survey data, we proposed a Bayesian weighted Binomial Zero-inflated (BBZ) model to estimate county-level rare diseases prevalence. The BBZ model accounts for excess zero counts, the sampling weights and uses a power prior. We evaluated BBZ with American Community Survey results and simulated data. We showed that BBZ yielded less bias and smaller variance than estimates based on the binomial distribution, a common approach to this problem. Since BBZ uses only a single year of survey data, BBZ produces more timely county-level incidence estimates. These timely estimates help pinpoint the special areas of county-level needs and help medical researchers and public health practitioners promptly evaluate rare diseases trends and associations with other health conditions.

Changes in health care utilization among Medicare beneficiaries with diabetes two years into the COVID-19 pandemic.

IMPORTANCE: The coronavirus 2019 (COVID-19) pandemic abruptly impacted health care service delivery and utilization. However, the impact on older adults with diabetes in the United States is unclear. OBJECTIVE: To estimate changes in health care utilization among older adults with diabetes during the initial 2 years of the COVID-19 pandemic compared to the 2 years before, and to examine the variation in utilization changes by demographic and socioeconomic characteristics. DESIGN SETTING AND PARTICIPANTS: In this study, we analyzed changes in utilization, measured by the average use of health care services per 1,000 persons with diabetes, using medical claims for Medicare fee-for-service beneficiaries aged 67 years and above. Utilization changes by setting (acute inpatient, emergency room [ER], hospital outpatient, physician office, and ambulatory surgery center [ASC]) and by media (telehealth and in-person) were examined for 22 months of the pandemic (03/2020-12/2021) compared with pre-pandemic period (03/2018-12/2019). We also estimated utilization changes by beneficiaries' age group, sex, race/ethnicity, and residential urbanicity. RESULTS: The study sample consisted of approximately 6 million beneficiaries with diabetes each month. In the first 2 years of the pandemic, the average use of health care services by setting was 5-17% lower than the pre-pandemic level for all types of services. Phase 1 (03/2020-05/2020) had the largest decrease in utilization: physician office visits changed by -51.2% (95% CI, -55.0% to -47.5%), ASC procedures by -45.1% (95% CI, -49.8% to -40.4%), ER visits by -36.9% (95% CI, -39.0% to -34.7%), acute inpatient stays by -31.5% (95% CI, -33.6% to -29.3%), and hospital outpatient visits by -27% (95% CI, -29.3% to -24.8%). The reduction in utilization varied by sociodemographic subgroup. During the pandemic, the use of telehealth visits increased by 511.1% (95% CI, 502.2% to 520.0%) compared to the pre-pandemic period. The increase was smaller among rural residents. CONCLUSIONS AND RELEVANCE: Medicare beneficiaries with diabetes experienced a reduction in the use of health care services during the COVID-19 pandemic, some of which persisted through two years into the pandemic. Telehealth visits increased, but not enough to overcome decreases in in-person visits. Understanding these patterns may help to optimize the use of health care resources for diabetes management in the post-pandemic era and during future emergencies.

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.

Risk of Cardiovascular Disease After COVID-19 Diagnosis Among Adults With and Without Diabetes.

Background Growing evidence suggests incident cardiovascular disease (CVD) may be a long-term outcome of COVID-19 infection, and chronic diseases, such as diabetes, may influence CVD risk associated with COVID-19. We evaluated the postacute risk of CVD >30 days after a COVID-19 diagnosis by diabetes status. Methods and Results We included adults ≥20 years old with a COVID-19 diagnosis from March 1, 2020 through December 31, 2021 in a retrospective cohort study from the IQVIA PharMetrics Plus insurance claims database. A contemporaneous control group comprised adults without recorded diagnoses for COVID-19 or other acute respiratory infections. Two historical control groups comprised patients with or without an acute respiratory infection. Cardiovascular outcomes included cerebrovascular disorders, dysrhythmia, inflammatory heart disease, ischemic heart disease, thrombotic disorders, other cardiac disorders, major adverse cardiovascular events, and any CVD. The total sample comprised 23 824 095 adults (mean age, 48.4 years [SD, 15.7 years]; 51.9% women; mean follow-up, 8.5 months [SD, 5.8 months]). In multivariable Cox regression models, patients with a COVID-19 diagnosis had a significantly greater risk of all cardiovascular outcomes compared with patients without a diagnosis of COVID-19 (hazard ratio [HR], 1.66 [1.62-1.71], with diabetes; HR, 1.75 [1.73-1.78], without diabetes). Risk was attenuated but still significant for the majority of outcomes when comparing patients with COVID-19 to both historical control groups. Conclusions In patients with COVID-19 infection, postacute risk of incident cardiovascular outcomes is significantly higher than among controls without COVID-19, regardless of diabetes status. Therefore, monitoring for incident CVD may be essential beyond the first 30 days after a COVID-19 diagnosis.

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.

Trends in diagnosed hypertension prevalence by geographic region for older adults with and without diagnosed diabetes, 2005-2017.

Given that the prevalence of hypertension increases with age and is more common among adults with diabetes than those without diabetes, the objective of this study was to examine trends in hypertension prevalence by geographic region among older adults with and without diabetes. Among older adults with diabetes, hypertension prevalence generally increased from 2005 to 2017 across all regions, although the annual percent change was lower from 2011 to 2017 than 2005-2011 for all regions.

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.

Urban and rural differences in new onset type 2 diabetes: Comparisons across national and regional samples in the diabetes LEAD network.

Introduction: Geographic disparities in diabetes burden exist throughout the United States (US), with many risk factors for diabetes clustering at a community or neighborhood level. We hypothesized that the likelihood of new onset type 2 diabetes (T2D) would differ by community type in three large study samples covering the US. Research design and methods: We evaluated the likelihood of new onset T2D by a census tract-level measure of community type, a modification of RUCA designations (higher density urban, lower density urban, suburban/small town, and rural) in three longitudinal US study samples (REGARDS [REasons for Geographic and Racial Differences in Stroke] cohort, VADR [Veterans Affairs Diabetes Risk] cohort, Geisinger electronic health records) representing the CDC Diabetes LEAD (Location, Environmental Attributes, and Disparities) Network. Results: In the REGARDS sample, residing in higher density urban community types was associated with the lowest odds of new onset T2D (OR [95% CI]: 0.80 [0.66, 0.97]) compared to rural community types; in the Geisinger sample, residing in higher density urban community types was associated with the highest odds of new onset T2D (OR [95% CI]: 1.20 [1.06, 1.35]) compared to rural community types. In the VADR sample, suburban/small town community types had the lowest hazard ratios of new onset T2D (HR [95% CI]: 0.99 [0.98, 1.00]). However, in a regional stratified analysis of the VADR sample, the likelihood of new onset T2D was consistent with findings in the REGARDS and Geisinger samples, with highest likelihood of T2D in the rural South and in the higher density urban communities of the Northeast and West regions; likelihood of T2D did not differ by community type in the Midwest. Conclusions: The likelihood of new onset T2D by community type varied by region of the US. In the South, the likelihood of new onset T2D was higher among those residing in rural communities.

Incremental Dental Expenditures Associated With Diabetes Among Noninstitutionalized U.S. Adults Aged ≥18 Years Old in 2016-2017.

OBJECTIVE: Diabetes is associated with poor oral health, but incremental expenditures for dental care associated with diabetes in the U.S. are unknown. We aimed to quantify these incremental expenditures per person and for the nation. RESEARCH DESIGN AND METHODS: We analyzed data from 46,633 noninstitutionalized adults aged ≥18 years old who participated in the 2016-2017 Medical Expenditure Panel Survey. We used two-part models to estimate dental expenditures per person in total, by payment source, and by dental service type, controlling for sociodemographic characteristics, health status, and geographic variables. Incremental expenditure was the difference in predicted expenditure for dental care between adults with and without diabetes. The total expenditure for the U.S. was the expenditure per person multiplied by the estimated number of people with diabetes. Expenditures were adjusted to 2017 USD. RESULTS: The mean adjusted annual diabetes-associated incremental dental expenditure was $77 per person and $1.9 billion for the nation. Of this incremental expenditure, 51% ($40) and 39% ($30) were paid out of pocket and by private insurance, 69% ($53) of the incremental expenditure was for restorative/prosthetic/surgical services, and adults with diabetes had lower expenditure for preventive services than those without (incremental, -$7). Incremental expenditures were higher in older adults, non-Hispanic Whites, and people with higher levels of income and education. CONCLUSIONS: Diabetes is associated with higher dental expenditures. These results fill a gap in the estimates of total medical expenditures associated with diabetes in the U.S. and highlight the importance of preventive dental care among people with diabetes.