Changes in Utilization and Expenditures Among Commercially Insured U.S. Adults With Diabetes During the COVID-19 Pandemic: Preliminary Findings.

Introduction: People with diabetes were among the populations that experienced the most profound impacts during the COVID-19 pandemic. The authors estimated changes in healthcare utilization and expenditures for commercially insured adults aged 18-64 years with diabetes during the pandemic. Methods: Medical claims data were from IQVIA PharMetrics Plus. Linear regressions were used to estimate the changes in utilization (per 1,000 individuals) for inpatient stays, emergency room visits, physician office visits, and ambulatory surgery center procedures. Changes in expenditures, in total and out of pocket, were estimated using generalized linear models. Expenditures were adjusted to 2021 U.S. dollars using the Consumer Price Index. Results: Utilization was reduced significantly for all service types during the pandemic. Although the largest reduction occurred between March 2020 and May 2020, the decrease persisted throughout 2021. During March 2020-May 2020, ambulatory surgery center procedures were reduced by 4.7 visits per 1,000 individuals. The reduction ranged between 0.4 and 1.3 visits per 1,000 individuals subsequently. Expenditures declined for all service types during March 2020-May 2020. However, after May 2020, the reduction remained statistically significant only for physician office visits for all months, with varying changes in expenditures for other service types. Conclusions: Healthcare utilization and expenditures reduced among commercially insured adults with diabetes during the COVID-19 pandemic.

Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018.

INTRODUCTION: We investigated 2018 gestational diabetes mellitus (GDM) prevalence estimates in three surveillance systems (National Vital Statistics System, State Inpatient Database, and Pregnancy Risk Assessment Monitoring Survey). METHODS: We calculated GDM prevalence for jurisdictions represented in each system; a subset of data was analyzed for people 18-39 years old in 22 jurisdictions present in all three systems to observe dataset-specific demographics and GDM prevalence using comparable categories. RESULTS: GDM prevalence estimates varied widely by data system and within the data subset despite comparable demographics. DISCUSSION: Understanding the differences between GDM surveillance data systems can help researchers better identify people and places at higher risk of GDM.

Examination of Prediabetes and Diabetes Testing Among US Pediatric Patients With Overweight or Obesity Using an Electronic Health Record.

Background: Youth with excess weight are at risk of developing type 2 diabetes (T2DM). Guidelines recommend screening for prediabetes and/or T2DM after 10 years of age or after puberty in youth with excess weight who have ≥1 risk factor(s) for T2DM. Electronic health records (EHRs) offer an opportunity to study the use of tests to detect diabetes in youth. Methods: We examined the frequency of (1) diabetes testing and (2) elevated test results among youth aged 10-19 years with at least one BMI measurement in an EHR from 2019 to 2021. We examined the presence of hemoglobin A1C (A1C), fasting plasma glucose (FPG), or oral glucose tolerance test (2-hour plasma glucose [2-hrPG]) results and, among those tested, the frequency of elevated values (A1C ≥6.5%, FPG ≥126 mg/dL, or 2-hrPG ≥200 mg/dL). Patients with pre-existing diabetes (n = 6793) were excluded. Results: Among 1,024,743 patients, 17% had overweight, 21% had obesity, including 8% with severe obesity. Among patients with excess weight, 10% had ≥1 glucose test result. Among those tested, elevated values were more common in patients with severe obesity (27%) and obesity (22%) than in those with healthy weight (8%), and among Black youth (30%) than White youth (13%). Among patients with excess weight, >80% of elevated values fell in the prediabetes range. Conclusions: In youth with excess weight, the use of laboratory tests for prediabetes and T2DM was infrequent. Among youth with test results, elevated FPG, 2hrPG, or A1C levels were most common in those with severe obesity and Black youth.

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.

Leveraging Electronic Health Records to Construct a Phenotype for Hypertension Surveillance in the United States.

BACKGROUND: Hypertension is an important risk factor for cardiovascular diseases. Electronic health records (EHRs) may augment chronic disease surveillance. We aimed to develop an electronic phenotype (e-phenotype) for hypertension surveillance. METHODS: We included 11,031,368 eligible adults from the 2019 IQVIA Ambulatory Electronic Medical Records-US (AEMR-US) dataset. We identified hypertension using three criteria, alone or in combination: diagnosis codes, blood pressure (BP) measurements, and antihypertensive medications. We compared AEMR-US estimates of hypertension prevalence and control against those from the National Health and Nutrition Examination Survey (NHANES) 2017-18, which defined hypertension as BP ≥130/80 mm Hg or ≥1 antihypertensive medication. RESULTS: The study population had a mean (SD) age of 52.3 (6.7) years, and 56.7% were women. The selected three-criteria e-phenotype (≥1 diagnosis code, ≥2 BP measurements of ≥130/80 mm Hg, or ≥1 antihypertensive medication) yielded similar trends in hypertension prevalence as NHANES: 42.2% (AEMR-US) vs. 44.9% (NHANES) overall, 39.0% vs. 38.7% among women, and 46.5% vs. 50.9% among men. The pattern of age-related increase in hypertension prevalence was similar between AEMR-US and NHANES. The prevalence of hypertension control in AEMR-US was 31.5% using the three-criteria e-phenotype, which was higher than NHANES (14.5%). CONCLUSIONS: Using an EHR dataset of 11 million adults, we constructed a hypertension e-phenotype using three criteria, which can be used for surveillance of hypertension prevalence and control.

Trends in the Diagnosed Prevalence and Incidence of Major Eye Diseases in Medicare Part B Fee-for-Service Beneficiaries 68 Years of Age or Older.

PURPOSE: To study contemporary trends in the diagnosed prevalence and incidence of age-related eye diseases among Medicare Fee-for-Service (FFS) beneficiaries. DESIGN: Analysis of Medicare administrative claims data. PARTICIPANTS: Medicare FFS beneficiaries 68 years of age and older from 2005 through 2020 who were enrolled continuously in both Part A and Part B for 3 years, including the index year and a 2-year lookback period. METHODS: Annual cross-sectional diagnosed prevalence and incidence rates were calculated. Age standardization was performed using the direct standardization method to account for changes in the age structure of the study population. Rates stratified by demographics (age, sex, race, and ethnicity) also were calculated. MAIN OUTCOME MEASURES: Annual prevalence and incidence of diagnosed age-related macular degeneration (AMD), diabetic retinopathy (DR) (among those with diabetes), and glaucoma. RESULTS: At baseline, in 2005, 60% of included beneficiaries were female, 20% were 85 years of age or older, 86% were non-Hispanic White, and one-quarter had a diagnosis of diabetes. From 2005 through 2019, the prevalence of a diagnosis of any of the conditions studied increased from 16.4% (n = 3 628 996) to 17.9% (n = 3 731 281). Diagnosed incidence decreased over this period from 4.9% (n = 954 878) in 2005 to 4.2% in 2019 (n = 757 696). The diagnosed prevalence of AMD increased from 6.8% (n = 1 504 770) to 9.4% (n = 1 965 176); the diagnosed prevalence of any DR among those with diabetes decreased from 9.3% (n = 504 135) to 9.0% (n = 532 859), although the diagnosed prevalence of vision-threatening DR increased from 2.0% to 3.4%; and the diagnosed prevalence of any diagnosed glaucoma decreased from 8.8% (n = 1 951 141) to 8.1% (n = 1 692 837). In 2020, the diagnosed prevalence and incidence of all diagnoses decreased. During the study period, we detected demographic differences in the prevalence and incidence of diagnosis of each condition. CONCLUSIONS: This study presents updated data on the prevalence and incidence of diagnosed major chronic, age-related eye diseases among Medicare FFS beneficiaries. Compared with older epidemiologic estimates, we found that the diagnosed prevalence of each condition studied was higher in more recent years. These findings may inform public health and policy planning and resource allocation to address the eye health of an increasingly older United States population. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Prevalence of Diabetic Retinopathy in the US in 2021.

Importance: Diabetic retinopathy (DR) is a common microvascular complication of diabetes and a leading cause of blindness among working-age adults in the US. Objective: To update estimates of DR and vision-threatening diabetic retinopathy (VTDR) prevalence by demographic factors and US county and state. Data Sources: The study team included data from the National Health and Nutrition Examination Survey (2005 to 2008 and 2017 to March 2020), Medicare fee-for-service claims (2018), IBM MarketScan commercial insurance claims (2016), population-based studies of adult eye disease (2001 to 2016), 2 studies of diabetes in youth (2021 and 2023), and a previously published analysis of diabetes by county (2012). The study team used population estimates from the US Census Bureau. Study Selection: The study team included relevant data from the US Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System. Data Extraction and Synthesis: Using bayesian meta-regression methods, the study team estimated the prevalence of DR and VTDR stratified by age, a nondifferentiated sex and gender measure, race, ethnicity, and US county and state. Main Outcomes and Measures: The study team defined individuals with diabetes as those who had a hemoglobin A1c level at 6.5% or more, took insulin, or reported ever having been told by a physician or health care professional that they have diabetes. The study team defined DR as any retinopathy in the presence of diabetes, including nonproliferative retinopathy (mild, moderate, or severe), proliferative retinopathy, or macular edema. The study team defined VTDR as having, in the presence of diabetes, severe nonproliferative retinopathy, proliferative retinopathy, panretinal photocoagulation scars, or macular edema. Results: This study used data from nationally representative and local population-based studies that represent the populations in which they were conducted. For 2021, the study team estimated 9.60 million people (95% uncertainty interval [UI], 7.90-11.55) living with DR, corresponding to a prevalence rate of 26.43% (95% UI, 21.95-31.60) among people with diabetes. The study team estimated 1.84 million people (95% UI, 1.41-2.40) living with VTDR, corresponding to a prevalence rate of 5.06% (95% UI, 3.90-6.57) among people with diabetes. Prevalence of DR and VTDR varied by demographic characteristics and geography. Conclusions and Relevance: US prevalence of diabetes-related eye disease remains high. These updated estimates on the burden and geographic distribution of diabetes-related eye disease can be used to inform the allocation of public health resources and interventions to communities and populations at highest risk.

Validity of Administrative Claims and Electronic Health Registry Data From a Single Practice for Eye Health Surveillance.

Importance: Diagnostic information from administrative claims and electronic health record (EHR) data may serve as an important resource for surveillance of vision and eye health, but the accuracy and validity of these sources are unknown. Objective: To estimate the accuracy of diagnosis codes in administrative claims and EHRs compared to retrospective medical record review. Design, Setting, and Participants: This cross-sectional study compared the presence and prevalence of eye disorders based on diagnostic codes in EHR and claims records vs clinical medical record review at University of Washington-affiliated ophthalmology or optometry clinics from May 2018 to April 2020. Patients 16 years and older with an eye examination in the previous 2 years were included, oversampled for diagnosed major eye diseases and visual acuity loss. Exposures: Patients were assigned to vision and eye health condition categories based on diagnosis codes present in their billing claims history and EHR using the diagnostic case definitions of the US Centers for Disease Control and Prevention Vision and Eye Health Surveillance System (VEHSS) as well as clinical assessment based on retrospective medical record review. Main Outcome and Measures: Accuracy was measured as area under the receiver operating characteristic curve (AUC) of claims and EHR-based diagnostic coding vs retrospective review of clinical assessments and treatment plans. Results: Among 669 participants (mean [range] age, 66.1 [16-99] years; 357 [53.4%] female), identification of diseases in billing claims and EHR data using VEHSS case definitions was accurate for diabetic retinopathy (claims AUC, 0.94; 95% CI, 0.91-0.98; EHR AUC, 0.97; 95% CI, 0.95-0.99), glaucoma (claims AUC, 0.90; 95% CI, 0.88-0.93; EHR AUC, 0.93; 95% CI, 0.90-0.95), age-related macular degeneration (claims AUC, 0.87; 95% CI, 0.83-0.92; EHR AUC, 0.96; 95% CI, 0.94-0.98), and cataracts (claims AUC, 0.82; 95% CI, 0.79-0.86; EHR AUC, 0.91; 95% CI, 0.89-0.93). However, several condition categories showed low validity with AUCs below 0.7, including diagnosed disorders of refraction and accommodation (claims AUC, 0.54; 95% CI, 0.49-0.60; EHR AUC, 0.61; 95% CI, 0.56-0.67), diagnosed blindness and low vision (claims AUC, 0.56; 95% CI, 0.53-0.58; EHR AUC, 0.57; 95% CI, 0.54-0.59), and orbital and external diseases (claims AUC, 0.63; 95% CI, 0.57-0.69; EHR AUC, 0.65; 95% CI, 0.59-0.70). Conclusion and Relevance: In this cross-sectional study of current and recent ophthalmology patients with high rates of eye disorders and vision loss, identification of major vision-threatening eye disorders based on diagnosis codes in claims and EHR records was accurate. However, vision loss, refractive error, and other broadly defined or lower-risk disorder categories were less accurately identified by diagnosis codes in claims and EHR data.

Prevalence, Progression, and Modifiable Risk Factors for Diabetic Retinopathy in Youth and Young Adults With Youth-Onset Type 1 and Type 2 Diabetes: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To determine the prevalence, progression, and modifiable risk factors associated with the development of diabetic retinopathy (DR) in a population-based cohort of youth-onset diabetes. RESEARCH DESIGN AND METHODS: We conducted a multicenter, population-based prospective cohort study (2002-2019) of youth and young adults with youth-onset type 1 diabetes (n = 2,519) and type 2 diabetes (n = 447). Modifiable factors included baseline and change from baseline to follow-up in BMI z score, waist/height ratio, systolic and diastolic blood pressure z score, and A1C. DR included evidence of mild or moderate nonproliferative DR or proliferative retinopathy. Prevalence estimates were standardized to estimate the burden of DR, and inverse probability weighting for censoring was applied for estimating risk factors for DR at two points of follow-up. RESULTS: DR in youth-onset type 1 and type 2 diabetes is highly prevalent, with 52% of those with type 1 diabetes and 56% of those with type 2 diabetes demonstrating retinal changes at follow-up (mean [SD] 12.5 [2.2] years from diagnosis). Higher baseline A1C, increase in A1C across follow-up, and increase in diastolic and systolic blood pressure were associated with the observation of DR at follow-up for both diabetes types. Increase in A1C across follow-up was associated with retinopathy progression. BMI z score and waist/height ratio were inconsistently associated, with both positive and inverse associations noted. CONCLUSIONS: Extrapolated to all youth-onset diabetes in the U.S., we estimate 110,051 cases of DR developing within ∼12 years postdiagnosis. Tight glucose and blood pressure management may offer the opportunity to mitigate development and progression of DR in youth-onset diabetes.

Association Between Social Determinants of Health and Examination-Based Vision Loss vs Self-reported Vision Measures.

Importance: Recent evidence suggests that social determinants of health (SDOH) affect vision loss, but it is unclear whether estimated associations differ between clinically evaluated and self-reported vision loss. Objective: To identify associations between SDOH and evaluated vision impairment and to assess whether these associations hold when examining self-reported vision loss. Design, Setting, and Participants: This population-based cross-sectional comparison included participants 12 years and older in the 2005 to 2008 National Health and Nutrition Examination Survey (NHANES), participants of all ages (infants and older) in the 2019 American Community Survey (ACS), and adults 18 years and older in the 2019 Behavioral Risk Factor Surveillance System (BRFSS). Exposures: Five domains of SDOH that are based on Healthy People 2030: economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context. Main Outcomes and Measures: Presenting vision impairment of 20/40 or worse in the better-seeing eye (NHANES) and self-reported blindness or serious difficulty seeing, even with glasses (ACS and BRFSS). Results: Of 3 649 085 included participants, 1 873 893 were female (51.1%) and 2 504 206 were White (64.4%). SDOH across domains of economic stability, educational attainment, health care access and quality, neighborhood and built environment, and social context were significant predictors of poor vision. For example, higher income (poverty to income ratio [NHANES]: OR, 0.91; 95% CI, 0.85-0.98; [ACS]: OR, 0.93; 95% CI, 0.93-0.94; categorical income [BRFSS:<$15 000 reference]: $15 000-$24 999; OR, 0.91; 95% CI, 0.91-0.91; $25 000-$34 999: OR, 0.80; 95% CI, 0.80-0.80; $35 000-$49 999: OR, 0.71; 95% CI, 0.71-0.72; ≥$50 000: OR, 0.49; 95% CI, 0.49-0.49), employment (BRFSS: OR, 0.66; 95% CI, 0.66-0.66; ACS: OR, 0.55; 95% CI, 0.54-0.55), and owning a home (NHANES: OR, 0.85; 95% CI, 0.73-1.00; BRFSS: OR, 0.82; 95% CI, 0.82-0.82; ACS: OR, 0.79; 95% CI, 0.79-0.79) were associated with lower odds of vision loss. The study team identified no differences in the general direction of the associations when using either clinically evaluated or self-reported vision measures. Conclusions and Relevance: The study team found evidence that associations between SDOH and vision impairment track together when using either clinically evaluated or self-reported vision loss. These findings support the use of self-reported vision data in a surveillance system to track trends in SDOH and vision health outcomes within subnational geographies.

Comparing Telephone Survey Responses to Best-Corrected Visual Acuity to Estimate the Accuracy of Identifying Vision Loss: Validation Study.

BACKGROUND: Self-reported questions on blindness and vision problems are collected in many national surveys. Recently released surveillance estimates on the prevalence of vision loss used self-reported data to predict variation in the prevalence of objectively measured acuity loss among population groups for whom examination data are not available. However, the validity of self-reported measures to predict prevalence and disparities in visual acuity has not been established. OBJECTIVE: This study aimed to estimate the diagnostic accuracy of self-reported vision loss measures compared to best-corrected visual acuity (BCVA), inform the design and selection of questions for future data collection, and identify the concordance between self-reported vision and measured acuity at the population level to support ongoing surveillance efforts. METHODS: We calculated accuracy and correlation between self-reported visual function versus BCVA at the individual and population level among patients from the University of Washington ophthalmology or optometry clinics with a prior eye examination, randomly oversampled for visual acuity loss or diagnosed eye diseases. Self-reported visual function was collected via telephone survey. BCVA was determined based on retrospective chart review. Diagnostic accuracy of questions at the person level was measured based on the area under the receiver operator curve (AUC), whereas population-level accuracy was determined based on correlation. RESULTS: The survey question, "Are you blind or do you have serious difficulty seeing, even when wearing glasses?" had the highest accuracy for identifying patients with blindness (BCVA ≤20/200; AUC=0.797). The highest accuracy for detecting any vision loss (BCVA <20/40) was achieved by responses of "fair," "poor," or "very poor" to the question, "At the present time, would you say your eyesight, with glasses or contact lenses if you wear them, is excellent, good, fair, poor, or very poor" (AUC=0.716). At the population level, the relative relationship between prevalence based on survey questions and BCVA remained stable for most demographic groups, with the only exceptions being groups with small sample sizes, and these differences were generally not significant. CONCLUSIONS: Although survey questions are not considered to be sufficiently accurate to be used as a diagnostic test at the individual level, we did find relatively high levels of accuracy for some questions. At the population level, we found that the relative prevalence of the 2 most accurate survey questions were highly correlated with the prevalence of measured visual acuity loss among nearly all demographic groups. The results of this study suggest that self-reported vision questions fielded in national surveys are likely to yield an accurate and stable signal of vision loss across different population groups, although the actual measure of prevalence from these questions is not directly analogous to that of BCVA.

Trends in the Prevalence and Treatment of Diabetic Macular Edema and Vision-Threatening Diabetic Retinopathy Among Commercially Insured Adults Aged <65 Years.

OBJECTIVE: Examine the 10-year trend in the prevalence and treatment of diabetic macular edema (DME) and vision-threatening diabetic retinopathy (VTDR) among commercially insured adults with diabetes. RESEARCH DESIGN AND METHODS: We analyzed the 10-year trend (2009-2018) in health care claims for adults aged 18-64 years using the IBM MarketScan Database, a national convenience sample of employer-sponsored health insurance. We included patients continuously enrolled in commercial fee-for-service health insurance for 24 months who had a diabetes ICD-9/10-CM code on one or more inpatient or two or more different-day outpatient claims in the index year or previous calendar year. We used diagnosis and procedure codes to calculate the annual prevalence of patients with one or more claims for 1) any DME, 2) either DME or VTDR, and 3) antivascular endothelial growth factor (anti-VEGF) injections and laser photocoagulation treatment, stratified by any DME, VTDR with DME, and VTDR without DME. We calculated the average annual percent change (AAPC). RESULTS: From 2009 to 2018, there was an increase in the annual prevalence of patients with DME or VTDR (2.1% to 3.4%; AAPC 7.5%; P < 0.001) and any DME (0.7% to 2.6%; AAPC 19.8%; P < 0.001). There were sex differences in the annual prevalence of DME or VTDR and any DME, with men having a higher prevalence than women. Annual claims for anti-VEGF injections increased among patients with any DME (327%) and VTDR with DME (206%); laser photocoagulation decreased among patients with any DME (-68%), VTDR with DME (-54%), and VTDR without DME (-62%). CONCLUSIONS: Annual claims for DME or VTDR and anti-VEGF injections increased whereas those for laser photocoagulation decreased among commercially insured adults with diabetes.

Prevalence of Age-Related Macular Degeneration in the US in 2019.

Importance: Age-related macular degeneration (AMD) is a leading cause of vision loss and blindness. AMD prevalence has not been estimated for the US in over a decade and early-stage AMD prevalence estimates are scarce and inconsistently measured. Objective: To produce estimates of early- and late-stage AMD prevalence overall and by age, gender, race and ethnicity, county, and state. Design, Setting, and Participants: The study team conducted a bayesian meta-regression analysis of relevant data sources containing information on the prevalence of AMD among different population groups in the US. Data Sources: We included data from the American Community Survey (2019), the National Health and Nutrition Examination Survey (2005-2008), US Centers for Medicare & Medicaid Services claims for fee-for-service beneficiaries (2018), and population-based studies (2004-2016). Study Selection: We included all relevant data from the US Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System. Data Extraction and Synthesis: The prevalence of early- and late-stage AMD was estimated and stratified when possible by factors including county, age group, gender, and race and ethnicity. Data analysis occurred from June 2021 to April 2022. Main Outcomes or Measures: The prevalence of early- (defined as retinal pigment epithelium abnormalities or the presence of drusen 125 or more microns in diameter in either eye) and late-stage (defined as choroidal neovascularization and/or geographic atrophy in either eye) manifestations of AMD. Results: This study used data from nationally representative and local population-based studies that represent the populations in which they were conducted. For 2019, we estimated that there were 18.34 million people 40 years and older (95% uncertainty interval [UI], 15.30-22.03) living with early-stage AMD, corresponding to a crude prevalence rate of 11.64% (95% UI, 9.71-13.98). We estimated there were 1.49 million people 40 years and older (95% UI, 0.97-2.15) living with late-stage AMD, corresponding to a crude prevalence rate of 0.94% (95% UI, 0.62-1.36). Prevalence rates of early- and late-stage AMD varied by demographic characteristics and geography. Conclusions and Relevance: We estimated a higher prevalence of early-stage AMD and a similar prevalence of late-stage AMD as compared with earlier studies. State-level and county-level AMD estimates may help guide public health practice.

Health Care Access and Use Among Adults With and Without Vision Impairment: Behavioral Risk Factor Surveillance System, 2018.

INTRODUCTION: Adults with vision impairment may have unique needs when accessing health care to maintain good health. Our study examined the relationship between vision status and access to and use of health care. METHODS: We analyzed data on adults aged 18 years or older who participated in the 2018 Behavioral Risk Factor Surveillance System. Vision impairment was identified by a yes response to the question "Are you blind or do you have serious difficulty seeing, even when wearing glasses?" Survey questions assessed health care access over the past year (having health insurance coverage, a usual health care provider, or unmet health care needs because of cost) and use of health care during that period (routine checkup and dental visit). We estimated age-adjusted prevalence of our outcomes of interest and used bivariate analyses to compare estimates of the outcomes by vision impairment status. RESULTS: The prevalence of self-reported vision impairment was 5.3%. Compared with adults without impaired vision, adults with vision impairment had a lower prevalence of having health insurance coverage (80.6% vs 87.6%), a usual health care provider (71.9% vs 75.7%), or a dental visit in the past year (52.9% vs 67.2%) and a higher prevalence of having an unmet health care need in the past year because of cost (29.2% vs 12.6%). CONCLUSION: Adults with vision impairment reported lower access to and use of health care than those without. Further research can better identify and understand barriers to care to improve access to and use of health care among this population.

Differences in receipt of recommended eye examinations by comorbidity status and healthcare utilization among nonelderly adults with diabetes.

BACKGROUND: To evaluate the effect of diabetes comorbidities by baseline healthcare utilization on receipt of recommended eye examinations. METHODS: Retrospective analysis of 310 691 nonelderly adults with type 2 diabetes in the IBM MarketScan Commercial Database from 2016 to 2019. Patients were grouped based on diabetes-concordant (related) or -discordant (unrelated) comorbidities. Logistic regression was used to estimate the prevalence ratio (PR) for eye examinations by comorbidity status, healthcare utilization, and an interaction between comorbidities and utilization, controlling for age, sex, region, and major eye disease. RESULTS: Prevalence of biennial eye examinations varied by the four comorbidity groups: 43.5% (diabetes only), 52.7% (concordant + discordant comorbidities), 48.0% (concordant comorbidities only), and 45.3% (discordant comorbidities only). In the lowest healthcare utilization tertile, the concordant-only and concordant + discordant groups had lower prevalence of examinations compared to diabetes only (PR 0.95 [95% CI 0.92-0.98] and PR 0.91 [95% CI 0.88-0.95], respectively). In the medium utilization tertile, the discordant-only and concordant + discordant groups had lower prevalence of examinations (PR 0.89 [0.83-0.95] and PR 0.94 [0.90-0.98], respectively). In the highest utilization tertile, the concordant-only and concordant + discordant groups had higher prevalence of examinations. CONCLUSIONS: Among patients with low healthcare utilization, having comorbid conditions is associated with lower prevalence of eye examinations. Among those with medium healthcare utilization, patients with diabetes-discordant comorbidities are particularly vulnerable. This study highlights populations of diabetes patients who would benefit from increased assistance in receiving vision-preserving eye examinations.

Cardiovascular Disease Risk Factors in US Adults With Vision Impairment.

INTRODUCTION: Adults with vision impairment (VI) have a higher prevalence of cardiovascular disease (CVD) compared with those without VI. We estimated the prevalence of CVD and CVD risk factors by VI status in US adults. METHODS: We used nationally representative data from the 2018 National Health Interview Survey (N = 22,890 adults aged ≥18 years). We estimated the prevalence of self-reported diagnosis of CVD (coronary heart disease [including angina and myocardial infarction], stroke, or other heart disease) by VI status. We used separate logistic regression models to generate adjusted prevalence ratios (aPRs), controlling for sociodemographic covariates, for those with VI (reference group, no VI) for CVD and CVD risk factors: current smoking, physical inactivity, excessive alcohol intake, obesity, hypertension, high cholesterol, and diabetes. RESULTS: Overall, 12.9% (95% CI, 12.3-13.5) of the sample had VI. The prevalence of CVD was 26.6% (95% CI, 24.7-28.6) in people with VI versus 12.2% (95% CI, 11.7-12.8) in those without VI (aPR = 1.65 [95% CI, 1.51-1.80]). Compared with adults without VI, those with VI had a higher prevalence of all risk factors examined: current smoking (aPR = 1.40 [95% CI, 1.27-1.53]), physical inactivity (aPR = 1.14 [95% CI, 1.06-1.22]), excessive alcohol intake (aPR = 1.29 [95% CI, 1.08-1.53]), obesity (aPR = 1.28 [95% CI, 1.21-1.36]), hypertension (aPR = 1.29 [95% CI, 1.22-1.36]), high cholesterol (aPR = 1.21 [95% CI, 1.14-1.29]), and diabetes (aPR = 1.54 [95% CI, 1.38-1.72]). CONCLUSION: Adults with VI had a higher prevalence of CVD and CVD risk factors compared with those without VI. Effective clinical and lifestyle interventions, adapted to accommodate VI-related challenges, may help reduce CVD risk in adults with VI.

Trends in Prevalence and Treatment of Diabetic Macular Edema and Vision-Threatening Diabetic Retinopathy Among Medicare Part B Fee-for-Service Beneficiaries.

IMPORTANCE: While diabetes prevalence among US adults has increased in recent decades, few studies document trends in diabetes-related eye disease. OBJECTIVE: To examine 10-year trends (2009-2018) in annual prevalence of Medicare beneficiaries with diabetes with a diagnosis of diabetic macular edema (DME) or vision-threatening diabetic retinopathy (VTDR) and trends in treatment. DESIGN, SETTING, AND PARTICIPANTS: In this cross-sectional study using Centers for Medicare & Medicaid Services research identifiable files, data for patients 65 years and older were analyzed from claims. Beneficiaries were continuously enrolled in Medicare Part B fee-for-service (FFS) insurance for the calendar year and had a diagnosis of diabetes on 1 or more inpatient claims or 2 or more outpatient claims during the calendar year or a 1-year look-back period. MAIN OUTCOMES AND MEASURES: Using diagnosis and procedure codes, annual prevalence was determined for beneficiaries with 1 or more claims for (1) any DME, (2) either DME or VTDR, and (3) anti-vascular endothelial growth factor (VEGF) injections, laser photocoagulation, or vitrectomy, stratified by any DME, VTDR with DME, and VTDR without DME. Racial and ethnic disparities in diagnosis and treatment are presented for 2018. RESULTS: In 2018, 6 960 823 beneficiaries (27.4%) had diabetes; half were aged 65 to 74 years (49.7%), half (52.7%) were women, and 75.7% were non-Hispanic White. From 2009 to 2018, there was an increase in the annual prevalence of beneficiaries with diabetes who had 1 or more claims for any DME (1.0% to 3.3%) and DME/VTDR (2.8% to 4.3%). Annual prevalence of anti-VEGF increased, particularly among patients with any DME (15.7% to 35.2%) or VTDR with DME (20.2% to 47.6%). Annual prevalence of laser photocoagulation decreased among those with any DME (45.5% to 12.5%), VTDR with DME (54.0% to 20.3%), and VTDR without DME (22.5% to 5.8%). Among all 3 groups, prevalence of vitrectomy in 2018 was less than half that in 2009. Prevalence of any DME and DME/VTDR was highest among Hispanic beneficiaries (5.0% and 7.0%, respectively) and Black beneficiaries (4.5% and 6.2%, respectively) and lowest among non-Hispanic White beneficiaries (3.0% and 3.8%, respectively). Among those with DME/VTDR, anti-VEGF was most prevalent among non-Hispanic White beneficiaries (30.3%). CONCLUSIONS AND RELEVANCE: From 2009 to 2018, prevalence of DME or VTDR increased among Medicare Part B FFS beneficiaries alongside an increase in anti-VEGF treatment and a decline in laser photocoagulation and vitrectomy.

Diabetes Self-Management Education and Association With Diabetes Self-Care and Clinical Preventive Care Practices.

PURPOSE: The purpose of the study is to assess self-reported receipt of diabetes education among people with diabetes and its association with following recommended self-care and clinical preventive care practices. METHODS: We analyzed data from the 2017 and 2018 Behavioral Risk Factor Surveillance System for 61 424 adults (≥18 years) with self-reported diabetes in 43 states and Washington, DC. Diabetes education was defined as ever taking a diabetes self-management class. The association of diabetes education with self-care practices (daily glucose testing, daily foot checks, smoking abstention, and engaging in leisure-time physical activity) and clinical practices (pneumococcal vaccination, biannual A1C test, and an annual dilated eye exam, influenza vaccination, health care visit for diabetes, and foot exam by a medical professional) was assessed. Multivariable logistic regression with predicted margins was used to predict the probability of following these practices, by diabetes education, controlling for sociodemographic factors. RESULTS: Of adults with diabetes, only half reported receiving diabetes education. Results indicate that receipt of diabetes education is associated with following self-care and clinical preventive care practices. Those who did receive diabetes education had a higher predicted probability for following all 4 self-care practices (smoking abstention, daily glucose testing, daily foot check, and engaging in leisure-time physical activity) and all 6 clinical practices (pneumonia vaccination, biannual A1C test, and an annual eye exam, flu vaccination, health care visit, and medical foot exam). CONCLUSIONS: The prevalence of adults with diabetes receiving diabetes education remains low. Increasing receipt of diabetes education may improve diabetes-related preventive care.

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.