Although most children are spared from developing complications from SARS-CoV-2 infection, some may suffer consequences including Long Covid and multisystem inflammatory syndrome in children (MIS-C). Although the occurrence of these conditions has decreased over time, they can still occur, and recognition of symptoms and prompt diagnosis is imperative for early intervention.

BACKGROUND: Long COVID can lead to functional disabilities and decreased well-being and limit the ability to work. No study has yet assessed associations of SARS-CoV-2-infection and Long COVID with specific measures of well-being and functional disabilities among workers by employment status. METHODS: Using data from the U.S. Behavioral Risk Factor Surveillance System, we assessed the prevalence of functional disabilities and well-being measures among adults of prime working age (25-54 years) by employment status and self-reported COVID-19 and Long COVID history. Within each employment status, we generated adjusted prevalence ratios (aPRs) comparing respondents from each 2022 COVID-19/Long COVID category to respondents in that employment status before the pandemic (2019). RESULTS: In 2022, prevalences of each functional disability except vision and all adverse well-being measures were highest among the 9.2% of respondents reporting a history of Long COVID. For each outcome, prevalences were lowest for workers and highest among those unable to work. 2022 prevalence of cognitive disability (16.4% of employees, 21.4% of the self-employed) and depression (31.2% and 36.4%, respectively) among workers reporting a history of Long COVID were more than double 2019 levels. Increases in cognitive disability and depression were lower but statistically significant among workers not reporting a history of Long COVID. CONCLUSIONS: The high prevalence of functional disabilities and adverse well-being among workers reporting a history of Long COVID have implications for workers and employers. Also concerning are smaller increases among workers not reporting a history of Long COVID, given the large number of affected workers. Mitigating the effects of Long COVID on workers will involve efforts in multiple domains: reducing incidence, increasing healthcare practitioner awareness, improving diagnosis and treatments, and increasing employer awareness of best practices for accommodating workers with Long COVID.

BACKGROUND: Workers in healthcare and other essential occupations had elevated risks for COVID-19 infection early in the pandemic. No survey of U.S. workers to date has comprehensively assessed the prevalence of both COVID-19 and Long COVID across industries and occupations (I&O) at a detailed level. METHODS: Behavioral Risk Factor Surveillance System data for 2022 from 39 states, Guam, and the U.S. Virgin Islands were used to estimate prevalence of self-reported history of COVID-19 and Long COVID, as well as the prevalence of Long COVID among those reporting prior COVID-19, by broad and detailed I&O. Adjusted prevalence ratios were used to compare outcome prevalence in each I&O to prevalence among all other workers combined. RESULTS: By broad I&O, workers in healthcare, protective services, and education had elevated prevalences of COVID-19. The prevalence of Long COVID was elevated in healthcare and protective service but not education workers. Detailed I&O with significantly elevated prevalences of COVID-19 but not Long COVID included Dairy Product Manufacturing industry workers and subsets of mining workers. Both COVID-19 and Long COVID were elevated among bartenders/drinking places and personal care and appearance workers. The prevalence of Long COVID was elevated among farmworkers who reported having had COVID-19. CONCLUSIONS: Industries and occupations with elevated levels of COVID-19 or Long COVID in this study may warrant increased measures to prevent transmission of airborne respiratory viruses. Accommodations are a key component for supporting workers in all workplaces. This new information about the distribution of Long COVID by I&O suggests where employer understanding and implementation of tailored workplace supports and accommodations are most needed to support continued employment of affected workers.

PURPOSE: Limited information is known about the burden of Long COVID by occupation and industry. This study compares the occurrence of self-reported new long-term symptoms lasting 4 weeks or longer among blood donors with and without prior SARS-CoV-2 infection by occupation and industry. METHODS: The American Red Cross invited blood donors 18 years and older who donated during May 4-December 31, 2021 to participate in online surveys. New long-term symptoms lasting 4 weeks or longer were assessed by self-reported occurrence of any of 35 symptoms since March 2020. SARS-CoV-2 infection status was determined by serological testing and self-report. We describe the prevalence of new long-term symptoms by SARS-CoV-2 infection status. We calculate the difference in reported new long-term symptoms by SARS-CoV-2 infection status within occupation and industry categories. RESULTS: Data were collected from 27,907 employed adults - 9763 were previously infected and 18,234 were never infected with SARS-CoV-2. New long-term symptoms were more prevalent among those previously infected compared to the never-infected respondents (45% vs 24%, p < 0.05). Among all respondents, new long-term symptoms by occupation ranged from 26% (installation, maintenance, and repair) to 41% (healthcare support) and by industry ranged from 26% (mining) to 55% (accommodation and food services). New long-term neurological and other symptoms were commonly reported by those previously infected with SARS-CoV-2. DISCUSSION: New long-term symptoms are more prevalent among certain occupation and industry groups, which likely reflects differential exposure to SARS-CoV-2. These findings highlight potential need for workplace accommodations in a variety of occupational settings to address new long-term symptoms.

BACKGROUND: Track PCC includes five geographic surveillance sites to conduct standardized population-based surveillance to estimate and track Post-COVID Conditions (PCC) by age, sex, race/ethnicity, geographic area, severity of initial infection, and risk factors among persons with evidence of SARS-CoV-2 infection (based on the Council of State and Territorial Epidemiologist [CSTE] case definitions for confirmed cases or laboratory-confirmed evidence of infection). METHODS: The study will estimate the incidence, prevalence, including temporal trends, and duration and severity of PCC symptoms, among children, adolescents, and adults. PCCs include a broad range of symptoms and conditions that continue or develop after acute SARS-CoV-2 infection or COVID-19 illness. Surveillance includes both passive and active components for diverse populations in Arizona, Indiana, and Utah as well as the Bronx Borough, NY, and part of Philadelphia County, PA. Passive surveillance will utilize electronic health records and health information exchanges within each site catchment area to longitudinally follow persons with COVID-19 to estimate PCC occurring at least 30 days after acute COVID-19 illness. Active surveillance will utilize self-report of PCCs from detailed surveys of persons ages 7 years and older with evidence of SARS-CoV-2 infection in the past 3 months. Respondents will complete follow-up surveys at 6-, 12- and 18-months post-infection. DISCUSSION: These data can help identify which groups are most affected by PCC, and what health differences among demographic groups exist, as well as indicate potential barriers to care. These additional levels of granularity can inform public health action and help direct needed clinical care for patients.

IMPORTANCE: Long-term symptoms, lasting more than 4 consecutive weeks after acute COVID-19 disease, are an important consequence of SARS-CoV-2 infection. Many prior studies have lacked a non-SARS-CoV-2-infected control population to distinguish background prevalence of symptoms from the direct impact of COVID-19 disease. OBJECTIVE: To examine the prevalence of long-term physical and mental health symptoms associated with SARS-CoV-2 infection in a large population of blood donors based on self-report and serologic test results. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study included American Red Cross blood donors (aged ≥18 years) who were surveyed between February 22 and April 21, 2022, about new long-term symptoms arising after March 2020 and their SARS-CoV-2 infection status. All participants underwent at least 1 serologic test for antinucleocapsid antibodies between June 15, 2020, and December 31, 2021. EXPOSURES: SARS-CoV-2 infection as defined by a self-reported, confirmed acute infection or antinucleocapsid antibody positivity. MAIN OUTCOMES AND MEASURES: New long-term symptoms since March 2020, including 5 symptom categories (neurologic, gastrointestinal, respiratory and cardiac, mental health, and other). RESULTS: Among 818 361 individuals who received the survey, 272 965 (33.4%) responded, with 238 828 meeting the inclusion criteria (138 576 [58.0%] female; median [IQR] age, 59.0 [47.0-67.0] years). Of the 83 015 individuals with a history of SARS-CoV-2 infection, 43.3% reported new long-term symptoms compared with 22.1% of those without a history of SARS-CoV-2 infection. After controlling for age, sex, race and ethnicity, and number of underlying conditions, those with a history of SARS-CoV-2 infection had an increased odds of new long-term symptoms compared with those without (adjusted odds ratio [AOR], 2.55; 95% CI, 2.51-2.61). Female sex and a history of chronic conditions were associated with new long-term symptoms. Long-term symptoms in the other category (AOR, 4.14; 95% CI, 4.03-4.25), which included changes in taste or smell, and the respiratory and cardiac symptom categories (AOR, 3.21; 95% CI, 3.12-3.31) were most associated with prior SARS-CoV-2 infection. Mental health long-term symptoms were also associated with prior SARS-CoV-2 infection (AOR, 1.05; 95%, CI, 1.02-1.08). CONCLUSIONS AND RELEVANCE: This study's findings suggest that long-term symptoms lasting more than 4 weeks are common in the adult population, but there is a significantly higher prevalence among those with SARS-CoV-2 infection. Continued efforts to define and track long-term sequelae of SARS-CoV-2 using a control group without infection and serologic information to include those who had asymptomatic or unidentified infections are needed.

Importance: Although COVID-19 vaccines protect against infection and severe disease, the role of vaccination in preventing prolonged symptoms in those with subsequent infection is unclear. Objective(s): To determine differences in symptoms stratified by prior vaccination reported by healthcare personnel (HCP) 6 weeks after onset of COVID-19, and whether there were differences in timing of return to work. Design(s): Nested cohort study within a multicenter vaccine effectiveness study. HCP with COVID-19 between December 2020 and August 2021 were followed up 6 weeks after illness onset. Setting(s): Health systems in 12 U.S. states. Participant(s): HCP participating in a vaccine effectiveness study were eligible for inclusion if they had confirmed COVID-19 with either verified mRNA vaccination (symptom onset =14 days after two doses) or no prior COVID-19 vaccination. Among 681 eligible participants, 419 (61%) completed a follow-up survey approximately 6 weeks after illness onset. Exposures: Two doses of a COVID-19 mRNA vaccine compared with no COVID-19 vaccine. Main Outcomes and Measures: Presence of symptoms 6 weeks after onset of COVID-19 illness and days to return to work after COVID-19 illness. Result(s): Among 419 HCP with confirmed COVID-19, 298 (71%) reported one or more COVID-like symptoms 6 weeks after illness onset, with a lower prevalence among vaccinated participants (60.6%) compared with unvaccinated participants (60.6% vs. 79.1%; aRR 0.70, 95% CI 0.58-0.84). Vaccinated HCP returned to work a median 2.0 days (95% CI 1.0-3.0) sooner than unvaccinated HCP (aHR 1.37; 95% CI, 1.04-1.79). Conclusion(s): A history of two doses of COVID-19 mRNA vaccine among HCP with COVID-19 illness was associated with decreased risk of COVID-like symptoms at 6 weeks and earlier to return to work. Vaccination is associated with improved recovery from COVID-19, in addition to preventing symptomatic infection. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

BACKGROUND: Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimating incidence from prevalence using mathematical relationships may facilitate surveillance efforts. The aim of this study was to examine whether a partial differential equation (PDE) can be used to estimate diabetes incidence from prevalence in youth. METHODS: We used age-, sex-, and race/ethnicity-specific estimates of prevalence in 2001 and 2009 as reported in the SEARCH for Diabetes in Youth study. Using these data, a PDE was applied to estimate the average incidence rates of type 1 and type 2 diabetes for the period between 2001 and 2009. Estimates were compared to annual incidence rates observed in SEARCH. Precision of the estimates was evaluated using 95% bootstrap confidence intervals. RESULTS: Despite the long period between prevalence measures, the estimated average incidence rates mirror the average of the observed annual incidence rates. Absolute values of the age-standardized sex- and type-specific mean relative errors are below 8%. CONCLUSIONS: Incidence of diabetes can be accurately estimated from prevalence. Since only cross-sectional prevalence data is required, employing this methodology in future studies may result in considerable cost savings.

OBJECTIVES: Although COVID-19 vaccines offer protection against infection and severe disease, there is limited information on the effect of vaccination on prolonged symptoms following COVID-19. Our objective was to determine differences in prevalence of prolonged symptoms 6 weeks after onset of COVID-19 among healthcare personnel (HCP) by vaccination status, and to assess differences in timing of return to work. DESIGN: Cohort analysis of HCP with COVID-19 enrolled in a multicentre vaccine effectiveness study. HCP with COVID-19 between December 2020 and August 2021 were followed up 6 weeks after illness onset. SETTING: Health systems in 12 US states. PARTICIPANTS: HCP participating in a vaccine effectiveness study were eligible for inclusion if they had laboratory-confirmed symptomatic SARS-CoV-2 with mRNA vaccination (symptom onset ≥14 days after two doses) or no prior vaccination. Among 681 eligible participants, 419 (61%) completed a follow-up survey to assess symptoms reported 6 weeks after illness onset. EXPOSURES: Two doses of a COVID-19 mRNA vaccine compared with no COVID-19 vaccine. MAIN OUTCOME MEASURES: Prevalence of symptoms 6 weeks after onset of COVID-19 illness and days to return to work. RESULTS: Among 419 HCP with COVID-19, 298 (71%) reported one or more COVID-like symptoms 6 weeks after illness onset, with a lower prevalence among vaccinated participants compared with unvaccinated participants (60.6% vs 79.1%; adjusted risk ratio 0.70, 95% CI 0.58 to 0.84). Following their illness, vaccinated HCP returned to work a median 2.0 days (95% CI 1.0 to 3.0) sooner than unvaccinated HCP (adjusted HR 1.37, 95% CI 1.04 to 1.79). CONCLUSIONS: Receipt of two doses of a COVID-19 mRNA vaccine among HCP with COVID-19 illness was associated with decreased prevalence of COVID-like symptoms at 6 weeks and earlier return to work.

OBJECTIVE: To project the prevalence and number of youths with diabetes and trends in racial and ethnic disparities in the U.S. through 2060. RESEARCH DESIGN AND METHODS: Based on a mathematical model and data from the SEARCH for Diabetes in Youth study for calendar years 2002-2017, we projected the future prevalence of type 1 and type 2 diabetes among youth aged <20 years while considering different scenarios of future trends in incidence. RESULTS: The number of youths with diabetes will increase from 213,000 (95% CI 209,000; 218,000) (type 1 diabetes 185,000, type 2 diabetes 28,000) in 2017 to 239,000 (95% CI 209,000; 282,000) (type 1 diabetes 191,000, type 2 diabetes 48,000) in 2060 if the incidence remains constant as observed in 2017. Corresponding relative increases were 3% (95% CI -9%; 21%) for type 1 diabetes and 69% (95% CI 43%; 109%) for type 2 diabetes. Assuming that increasing trends in incidence observed between 2002 and 2017 continue, the projected number of youths with diabetes will be 526,000 (95% CI 335,000; 893,000) (type 1 diabetes 306,000, type 2 diabetes 220,000). Corresponding relative increases would be 65% (95% CI 12%; 158%) for type 1 diabetes and 673% (95% CI 362%; 1,341%) for type 2 diabetes. In both scenarios, substantial widening of racial and ethnic disparities in type 2 diabetes prevalence are expected, with the highest prevalence among non-Hispanic Black youth. CONCLUSIONS: The number of youths with diabetes in the U.S. is likely to substantially increase in future decades, which emphasizes the need for prevention to attenuate this trend.

BACKGROUND: There are limited data on the risk of SARS-CoV-2 infection in the U.S. by occupation. We identified occupations at higher risk for prior SARS-CoV-2 infection as defined by the presence of infection-induced antibodies among U.S. blood donors. METHODS: Using a nested case-control study design, blood donors during May-December 2021 with anti-nucleocapsid (anti-N) testing were sent an electronic survey on employment status, vaccination, and occupation. The association between previous SARS-CoV-2 infection and occupation-specific in-person work was estimated using multivariable logistic regression adjusting for sex, age, month of donation, race/ethnicity, education, vaccination, and telework. RESULTS: Among 85,986 included survey respondents, 9,504 (11.1%) were anti-N reactive. Healthcare support (20.3%), protective service (19.9%), and food preparation and serving related occupations (19.7%) had the highest proportion of prior infection. After adjustment, prior SARS-CoV-2 infection was associated with healthcare practitioners (adjusted OR [aOR] 2.10, 95% CI 1.74-2.54) and healthcare support (aOR 1.83, 95% CI 1.39-2.40) occupations compared with computer and mathematical occupations as the referent group. Lack of COVID-19 vaccination (aOR 16.13, 95% CI 15.01-17.34) and never teleworking (aOR 1.17, 95% CI 1.05-1.30) were also independently associated with prior SARS-CoV-2 infection. Protective service occupations had the highest proportion of unvaccinated workers (30.0%). CONCLUSIONS: Workers in healthcare, protective services, and food preparation had the highest prevalence of prior SARS-CoV-2 infection. Occupational risks for SARS-CoV-2 infection remained after adjusting for vaccination, telework, and demographic factors. These findings underscore the need for mitigation measures and personal protection in healthcare settings and other workplaces.

BACKGROUND: Although most adults infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of United States (US) adults with activity-limiting PCC on 1 November 2021. METHODS: We modeled the prevalence of PCC using reported infections occurring from 1 February 2020 to 30 September 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on 1 November 2021 as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for underascertainment of infections and uncertainty about symptom duration. RESULTS: On 1 November 2021, at least 3.0-5.0 million US adults, or 1.2%-1.9% of the US adult population, were estimated to have activity-limiting PCC of ≥1 month's duration. Population prevalence was higher in females (1.4%-2.2%) than males. The estimated prevalence after adjusting for underascertainment of infections was 1.7%-3.8%. CONCLUSIONS: Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the US population.

Although the availability of effective vaccines raises optimism for the control of SARS-CoV-2 transmission in the USA, public health systems must prepare to respond to all COVID-19 health impacts, particularly post-COVID conditions (PCCs).1,2 PCCs consist of new, returning, or ongoing health problems diagnosed in people with a history of SARS-CoV-2 infection, typically present at least 4 weeks after infection.3 While PCCs are still being defined and characterized, PCCs could potentially affect millions of Americans.1,2

OBJECTIVE: To estimate difference in population-level glycemic control and the emergence of diabetes complications given a theoretical scenario in which non-White youth and young adults (YYA) with type 1 diabetes (T1D) receive and follow an equivalent distribution of diabetes treatment regimens as non-Hispanic White YYA. RESEARCH DESIGN AND METHODS: Longitudinal data from YYA diagnosed 2002-2005 in the SEARCH for Diabetes in Youth Study were analyzed. Based on self-reported race/ethnicity, YYA were classified as non-White race or Hispanic ethnicity (non-White subgroup) versus non-Hispanic White race (White subgroup). In the White versus non-White subgroups, the propensity score models estimated treatment regimens, including patterns of insulin modality, self-monitored glucose frequency, and continuous glucose monitoring use. An analysis based on policy evaluation techniques in reinforcement learning estimated the effect of each treatment regimen on mean hemoglobin A(1c) (HbA(1c)) and the prevalence of diabetes complications for non-White YYA. RESULTS: The study included 978 YYA. The sample was 47.5% female and 77.5% non-Hispanic White, with a mean age of 12.8 ± 2.4 years at diagnosis. The estimated population mean of longitudinal average HbA(1c) over visits was 9.2% and 8.2% for the non-White and White subgroup, respectively (difference of 0.9%). Within the non-White subgroup, mean HbA(1c) across visits was estimated to decrease by 0.33% (95% CI -0.45, -0.21) if these YYA received the distribution of diabetes treatment regimens of the White subgroup, explaining ∼35% of the estimated difference between the two subgroups. The non-White subgroup was also estimated to have a lower risk of developing diabetic retinopathy, diabetic kidney disease, and peripheral neuropathy with the White youth treatment regimen distribution (P < 0.05), although the low proportion of YYA who developed complications limited statistical power for risk estimations. CONCLUSIONS: Mathematically modeling an equalized distribution of T1D self-management tools and technology accounted for part of but not all disparities in glycemic control between non-White and White YYA, underscoring the complexity of race and ethnicity-based health inequity.

OBJECTIVE: To examine short-term mortality and cause of death among youth and young adults (YYAs) with youth-onset diabetes. RESEARCH DESIGN AND METHODS: We included 19,717 YYAs newly diagnosed with diabetes before 20 years of age from 1 January 2002 to 31 December 2015 enrolled in the SEARCH for Diabetes in Youth Study. Of these, 14,721 had type 1; 4,141 type 2; and 551 secondary and 304 other/unknown diabetes type. Cases were linked with the National Death Index through 31 December 2017. We calculated standardized mortality ratios (SMRs) and 95% CIs based on age, sex, and race/ethnicity for state and county population areas and examined underlying causes of death. RESULTS: During 170,148 person-years (PY) (median follow-up 8.5 years), 283 individuals died: 133 with type 1 (103.0/100,000 PY), 55 with type 2 (161.5/100,000 PY), 87 with secondary (1,952/100,000 PY), and 8 with other/unknown diabetes type (312.3/100,000 PY). SMRs (95% CI) for the first three groups were 1.5 (1.2-1.8), 2.3 (1.7-3.0), and 28.0 (22.4-34.6), respectively. Diabetes was the underlying cause of death for 42.1%, 9.1%, and 4.6% of deaths, respectively. The SMR was greater for type 2 than for type 1 diabetes (P < 0.001). SMRs were significantly higher for individuals with type 1 diabetes who were <20 years of age, non-Hispanic White and Hispanic, and female and for individuals with type 2 diabetes who were <25 years of age, from all race/ethnic minority groups, and from both sexes. CONCLUSION: Excess mortality was observed among YYAs for each type of diabetes with differences in risk associated with diabetes type, age, race/ethnicity, and sex. The root causes of excess mortality among YYAs with diabetes merit further study.

OBJECTIVE: To examine changes in and the relationships between diabetes management and rural and urban residence. RESEARCH DESIGN AND METHODS: Using National Health and Nutrition Examination Survey (1999-2018) data from 6,372 adults aged ≥18 years with self-reported diagnosed diabetes, we examined poor ABCS: A1C >9% (>75 mmol/mol), Blood pressure (BP) ≥140/90 mmHg, Cholesterol (non-HDL) ≥160 mg/dL (≥4.1 mmol/L), and current Smoking. We compared odds of urban versus rural residents (census tract population size ≥2,500 considered urban, otherwise rural) having poor ABCS across time (1999-2006, 2007-2012, and 2013-2018), overall and by sociodemographic and clinical characteristics. RESULTS: During 1999-2018, the proportion of U.S. adults with diabetes residing in rural areas ranged between 15% and 19.5%. In 1999-2006, there were no statistically significant rural-urban differences in poor ABCS. However, from 1999-2006 to 2013-2018, there were greater improvements for urban adults with diabetes than for rural for BP ≥140/90 mmHg (relative odds ratio [OR] 0.8, 95% CI 0.6-0.9) and non-HDL ≥160 mg/dL (≥4.1 mmol/L) (relative OR 0.45, 0.4-0.5). These differences remained statistically significant after adjustment for race/ethnicity, education, poverty levels, and clinical characteristics. Yet, over the 1999-2018 time period, minority race/ethnicity, lower education attainment, poverty, and lack of health insurance coverage were factors associated with poorer A, B, C, or S in urban adults compared with their rural counterparts. CONCLUSIONS: Over two decades, rural U.S. adults with diabetes have had less improvement in BP and cholesterol control. In addition, rural-urban differences exist across sociodemographic groups, suggesting that efforts to narrow this divide may need to address both socioeconomic and clinical aspects of care.

INTRODUCTION: Defining type of diabetes using survey data is challenging, although important, for determining national estimates of diabetes. The purpose of this study was to compare the percentage and characteristics of US adults classified as having type 1 diabetes as defined by several algorithms. RESEARCH DESIGN AND METHODS: This study included 6331 respondents aged ≥18 years who reported a physician diagnosis of diabetes in the 2016-2017 National Health Interview Survey. Seven algorithms classified type 1 diabetes using various combinations of self-reported diabetes type, age of diagnosis, current and continuous insulin use, and use of oral hypoglycemics. RESULTS: The percentage of type 1 diabetes among those with diabetes ranged from 3.4% for those defined by age of diagnosis <30 years and continuous insulin use (algorithm 2) to 10.2% for those defined only by continuous insulin use (algorithm 1) and 10.4% for those defined as self-report of type 1 (supplementary algorithm 6). Among those defined by age of diagnosis <30 years and continuous insulin use (algorithm 2), by self-reported type 1 diabetes and continuous insulin use (algorithm 4), and by self-reported type 1 diabetes and current insulin use (algorithm 5), mean body mass index (BMI) (28.6, 27.4, and 28.5 kg/m(2), respectively) and percentage using oral hypoglycemics (16.1%, 11.1%, and 19.0%, respectively) were lower than for all other algorithms assessed. Among those defined by continuous insulin use alone (algorithm 1), the estimates for mean age and age of diagnosis (54.3 and 30.9 years, respectively) and BMI (30.9 kg/m(2)) were higher than for other algorithms. CONCLUSIONS: Estimates of type 1 diabetes using commonly used algorithms in survey data result in varying degrees of prevalence, characteristic distributions, and potential misclassification.

Since 2003, US hypertension guidelines have recommended ACE (angiotensin-converting enzyme) inhibitors or ARBs (angiotensin receptor blockers) as first-line antihypertensive therapy in the presence of albuminuria (urine albumin/creatinine ratio ≥300 mg/g). To examine national trends in guideline-concordant ACE inhibitor/ARB utilization, we studied adults participating in the National Health and Nutrition Examination Surveys 2001 to 2018 with hypertension (defined by self-report of high blood pressure, systolic blood pressure ≥140 mm Hg or diastolic ≥90 mm Hg, or use of antihypertensive medications). Among 20 538 included adults, the prevalence of albuminuria ≥300 mg/g was 2.8% in 2001 to 2006, 2.8% in 2007 to 2012, and 3.2% in 2013 to 2018. Among those with albuminuria ≥300 mg/g, no consistent trends were observed for the proportion receiving ACE inhibitor/ARB treatment from 2001 to 2018 among persons with diabetes, without diabetes, or overall. In 2013 to 2018, ACE inhibitor/ARB usage in the setting of albuminuria ≥300 mg/g was 55.3% (95% CI, 46.8%-63.6%) among adults with diabetes and 33.4% (95% CI, 23.1%-45.5%) among those without diabetes. Based on US population counts, these estimates represent 1.6 million adults with albuminuria ≥300 mg/g currently not receiving ACE inhibitor/ARB therapy, nearly half of whom do not have diabetes. ACE inhibitor/ARB underutilization represents a significant gap in preventive care delivery for adults with hypertension and albuminuria that has not substantially changed over time.

INTRODUCTION: The objective of this study was to examine recent trends in diagnosed diabetes prevalence for American Indian and Alaska Native (AI/AN) adults aged 18 years and older in the Indian Health Service (IHS) active clinical population. RESEARCH DESIGN AND METHODS: Data were extracted from the IHS National Data Warehouse for AI/AN adults for each fiscal year from 2006 (n=729 470) through 2017 (n=1 034 814). The prevalence of diagnosed diabetes for each year and the annual percentage change were estimated for adults overall, as well as by sex, age group, and geographic region. RESULTS: After increasing significantly from 2006 to 2013, diabetes prevalence for AI/AN adults in the IHS active clinical population decreased significantly from 2013 to 2017. Prevalence was 14.4% (95% CI 13.9% to 15.0%) in 2006; 15.4% (95% CI 14.8% to 16.0%) in 2013; and 14.6% (95% CI 14.1% to 15.2%) in 2017. Trends for men and women were similar to the overall population, as were those for all age groups. For all geographic regions, prevalence either decreased significantly or leveled off in recent years. CONCLUSIONS: Diabetes prevalence in AI/AN adults in the IHS active clinical population has decreased significantly since 2013. While these results cannot be generalized to all AI/AN adults in the USA, this study documents the first known decrease in diabetes prevalence for AI/AN people.

Importance: Timely eye care can prevent unnecessary vision loss. Objectives: To estimate the number of US adults 18 years or older at high risk for vision loss in 2017 and to evaluate use of eye care services in 2017 compared with 2002. Design, Setting, and Participants: This survey study used data from the 2002 (n = 30920) and 2017 (n = 32886) National Health Interview Survey, an annual, cross-sectional, nationally representative sample of US noninstitutionalized civilians. Analysis excluded respondents younger than 18 years and those who were blind or unable to see. Covariates included age, sex, race/ethnicity, marital status, educational level, income-to-poverty ratio, health insurance status, diabetes diagnosis, vision or eye problems, and US region of residence. Main Outcomes and Measures: Three self-reported measures were visiting an eye care professional in the past 12 months, receiving a dilated eye examination in the past 12 months, and needing but being unable to afford eyeglasses in the past 12 months. Adults at high risk for vision loss included those who were 65 years or older, self-reported a diabetes diagnosis, or had vision or eye problems. Multivariable logistic regression models incorporating sampling weights were used to investigate associations between measures and covariates. Temporal comparisons between 2002 and 2017 were derived from estimates standardized to the US 2010 census population. Results: Among 30 920 individuals in 2002, 16.0% were 65 years or older, and 52.0% were female; among 32 886 individuals in 2017, 20.0% were 65 years or older, and 51.8% were female. In 2017, more than 93 million US adults (37.9%; 95% CI, 37.0%-38.7%) were at high risk for vision loss compared with almost 65 million (31.5%; 95% CI, 30.7%-32.3%) in 2002, a difference of 6.4 (95% CI, 5.2-7.6) percentage points. Use of eye care services improved (56.9% [95% CI, 55.7%-58.7%] reported visiting an eye care professional annually, and 59.8% [95% CI, 58.6%-61.0%] reported receiving a dilated eye examination), but 8.7% (95% CI, 8.0%-9.5%) said they could not afford eyeglasses (compared with 51.1% [95% CI, 49.9%-52.3%], 52.4% [95% CI, 51.2%-53.6%], and 8.3% [95% CI, 7.7%-8.9%], respectively, in 2002). In 2017, individuals with lower income compared with high income were more likely to report eyeglasses as unaffordable (13.6% [95% CI, 11.6%-15.9%] compared with 5.7% [95% CI, 4.9%-6.6%]). Conclusions and Relevance: Compared with data from 2002, more US adults were at high risk for vision loss in 2017. Although more adults used eye care, a larger proportion reported eyeglasses as unaffordable. Focusing resources on populations at high risk for vision loss, increasing awareness of the importance of eye care, and making eyeglasses more affordable could promote eye health, preserve vision, and reduce disparities.

Importance: The prevalence of diabetes among Hispanic and Asian American subpopulations in the United States is unknown. Objective: To estimate racial/ethnic differences in the prevalence of diabetes among US adults 20 years or older by major race/ethnicity groups and selected Hispanic and non-Hispanic Asian subpopulations. Design, Setting, and Participants: National Health and Nutrition Examination Surveys, 2011-2016, cross-sectional samples representing the noninstitutionalized, civilian, US population. The sample included adults 20 years or older who had self-reported diagnosed diabetes during the interview or measurements of hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), and 2-hour plasma glucose (2hPG). Exposures: Race/ethnicity groups: non-Hispanic white, non-Hispanic black, Hispanic and Hispanic subgroups (Mexican, Puerto Rican, Cuban/Dominican, Central American, and South American), non-Hispanic Asian and non-Hispanic Asian subgroups (East, South, and Southeast Asian), and non-Hispanic other. Main Outcomes and Measures: Diagnosed diabetes was based on self-reported prior diagnosis. Undiagnosed diabetes was defined as HbA1c 6.5% or greater, FPG 126 mg/dL or greater, or 2hPG 200 mg/dL or greater in participants without diagnosed diabetes. Total diabetes was defined as diagnosed or undiagnosed diabetes. Results: The study sample included 7575 US adults (mean age, 47.5 years; 52% women; 2866 [65%] non-Hispanic white, 1636 [11%] non-Hispanic black, 1952 [15%] Hispanic, 909 [6%] non-Hispanic Asian, and 212 [3%] non-Hispanic other). A total of 2266 individuals had diagnosed diabetes; 377 had undiagnosed diabetes. Weighted age- and sex-adjusted prevalence of total diabetes was 12.1% (95% CI, 11.0%-13.4%) for non-Hispanic white, 20.4% (95% CI, 18.8%-22.1%) for non-Hispanic black, 22.1% (95% CI, 19.6%-24.7%) for Hispanic, and 19.1% (95% CI, 16.0%-22.1%) for non-Hispanic Asian adults (overall P < .001). Among Hispanic adults, the prevalence of total diabetes was 24.6% (95% CI, 21.6%-27.6%) for Mexican, 21.7% (95% CI, 14.6%-28.8%) for Puerto Rican, 20.5% (95% CI, 13.7%-27.3%) for Cuban/Dominican, 19.3% (95% CI, 12.4%-26.1%) for Central American, and 12.3% (95% CI, 8.5%-16.2%) for South American subgroups (overall P < .001). Among non-Hispanic Asian adults, the prevalence of total diabetes was 14.0% (95% CI, 9.5%-18.4%) for East Asian, 23.3% (95% CI, 15.6%-30.9%) for South Asian, and 22.4% (95% CI, 15.9%-28.9%) for Southeast Asian subgroups (overall P = .02). The prevalence of undiagnosed diabetes was 3.9% (95% CI, 3.0%-4.8%) for non-Hispanic white, 5.2% (95% CI, 3.9%-6.4%) for non-Hispanic black, 7.5% (95% CI, 5.9%-9.1%) for Hispanic, and 7.5% (95% CI, 4.9%-10.0%) for non-Hispanic Asian adults (overall P < .001). Conclusions and Relevance: In this nationally representative survey of US adults from 2011 to 2016, the prevalence of diabetes and undiagnosed diabetes varied by race/ethnicity and among subgroups identified within the Hispanic and non-Hispanic Asian populations.

OBJECTIVE: While diabetic ketoacidosis (DKA) is common in youth at the onset of the diabetes, the excess costs associated with DKA are unknown. We aimed to quantify the health care services use and medical care costs related to the presence of DKA at diagnosis of diabetes. RESEARCH DESIGN AND METHODS: We analyzed data from the U.S. MarketScan claims database for 4,988 enrollees aged 3-19 years insured in private fee-for-service plans and newly diagnosed with diabetes during 2010-2016. Youth with and without DKA at diabetes diagnosis were compared for mean health care service use (outpatient, office, emergency room, and inpatient visits) and medical costs (outpatient, inpatient, prescription drugs, and total) for 60 days prior to and 60 days after diabetes diagnosis. A two-part model using generalized linear regression and logistic regression was used to estimate medical costs, controlling for age, sex, rurality, health plan, year, presence of hypoglycemia, and chronic pulmonary condition. All costs were adjusted to 2016 dollars. RESULTS: At diabetes diagnosis, 42% of youth had DKA. In the 60 days prior to diabetes diagnosis, youth with DKA at diagnosis had less health services usage (e.g., number of outpatient visits: -1.17; P < 0.001) and lower total medical costs (-$635; P < 0.001) compared with youth without DKA at diagnosis. In the 60 days after diagnosis, youth with DKA had significantly greater health care services use and health care costs ($6,522) compared with those without DKA. CONCLUSIONS: Among youth with newly diagnosed diabetes, DKA at diagnosis is associated with significantly higher use of health care services and medical costs.

PURPOSE: Most surveillance efforts in childhood diabetes have focused on incidence, whereas prevalence is rarely reported. This study aimed to assess whether a mathematical illness-death model accurately estimated future prevalence from baseline prevalence and incidence rates in children. METHODS: SEARCH for Diabetes in Youth is an ongoing population-based surveillance study of prevalence and incidence of diabetes and its complications among youth in the United States. We used age-, sex-, and race/ethnicity-specific SEARCH estimates of the prevalence of type I and type II diabetes in 2001 and incidence from 2002 to 2008. These data were used in a partial differential equation to estimate prevalence in 2009 with 95% bootstrap confidence intervals. Model-based prevalence was compared with the observed prevalence in 2009. RESULTS: Most confidence intervals for the difference between estimated and observed prevalence included zero, indicating no evidence for a difference between the two methods. The width of confidence intervals indicated high precision for the estimated prevalence when considering all races/ethnicities. In strata with few cases, precision was reduced. CONCLUSIONS: Future prevalence of type I and type II diabetes in youth may be accurately estimated from baseline prevalence and incidence. Diabetes surveillance could benefit from potential cost savings of this method.

OBJECTIVE: We examined young adults with and young adults without diabetes by using demographic data and cardiometabolic risk profiles and compared the risk profiles of younger versus older (aged >/=45 years) adults with diabetes. RESEARCH DESIGN AND METHODS: Data were obtained from the National Health and Nutrition Examination Survey 2007-2016. Diabetes was defined by self-report of health care provider diagnosis or by A1C levels of 6.5% or higher among those without a self-reported diagnosis. The cardiometabolic risk profile included adiposity, blood pressure, serum lipids, healthy eating, physical activity (PA), and exposure to tobacco smoke. Adjusted difference in difference was calculated as the difference among younger adults with and younger adults without diabetes minus the difference among older adults with and older adults without diabetes. RESULTS: Adults with diabetes in both age-groups had higher levels of adiposity, hypertension, and cholesterol and lower levels of healthy eating and leisure-time PA. However, the differences in high cholesterol and adiposity by diabetes status were greater among young adults compared with older adults after adjustment for demographics and health insurance status. Elevated lipids were 9.6 percentage points higher (95% CI 4.6, 14.5) and obesity was 37.3 percentage points higher (95% CI 31.8, 42.7) among young adults with diabetes compared with those without diabetes than among older adults with diabetes compared with those without diabetes. CONCLUSIONS: Young adults with diabetes have high rates of cardiometabolic risk factors, which can lead to an increased prevalence of disease and mortality rate among these individuals as they age.

INTRODUCTION: Limited information is available on the health burden of diabetes at the state level. This study estimated state-specific attributable fractions and the number of cases attributable to diabetes for diabetes-related complications. METHODS: For each state, diabetes-attributable fractions for nine diabetes complications were estimated: three self-reported complications from the 2013 Behavioral Risk Factor Surveillance System, hospitalizations with three complications from 2011 to 2014 State Inpatient Databases, and three complications from 2013 Medicare data. Attributable fractions were calculated using RR and diabetes prevalence and the total number of cases using attributable fractions and total number of complications. Adjusted RR of each complication for people with and without diabetes by age and sex was estimated using a generalized linear model. Analyses were conducted in 2015-2016. RESULTS: Median state-level diabetes-attributable fractions for self-reported complications were 0.14 (range, 0.10-0.19) for mobility limitations; 0.13 (range, 0.04-0.21) for limitations in instrumental activities of daily living; and 0.12 (range, 0.06-0.20) for severe visual impairment or blindness. Median state-level diabetes-attributable fractions for diabetes-associated hospitalizations were 0.19 (range, 0.08-0.24) for congestive heart failure; 0.08 (range, 0.02-0.16) for myocardial infarction; and 0.62 (range, 0.46-0.73) for lower extremity amputations. Median state-level diabetes-attributable fractions for complications among Medicare beneficiaries were 0.17 (range, 0.14-0.23) for coronary heart disease; 0.28 (range, 0.24-0.33) for chronic kidney disease; and 0.22 (range, 0.08-0.32) for peripheral vascular disease. CONCLUSIONS: Diabetes carries a significant health burden, and results vary across states. Efforts to prevent or delay diabetes or to improve diabetes management could reduce the health burden because of diabetes.

BACKGROUND: Most people with chronic kidney disease (CKD) are not aware of their condition. OBJECTIVES: To assess screening criteria in identifying a population with or at high risk for CKD and to determine their level of control of CKD risk factors. METHOD: CKD Health Evaluation Risk Information Sharing (CHERISH), a demonstration project of the Centers for Disease Control and Prevention, hosted screenings at 2 community locations in each of 4 states. People with diabetes, hypertension, or aged >/=50 years were eligible to participate. In addition to CKD, screening included testing and measures of hemoglobin A1C, blood pressure, and lipids. -Results: In this targeted population, among 894 people screened, CKD prevalence was 34%. Of participants with diabetes, 61% had A1C < 7%; of those with hypertension, 23% had blood pressure < 130/80 mm Hg; and of those with high cholesterol, 22% had low-density lipoprotein < 100 mg/dL. CONCLUSIONS: Using targeted selection criteria and simple clinical measures, CHERISH successfully identified a population with a high CKD prevalence and with poor control of CKD risk factors. CHERISH may prove helpful to state and local programs in implementing CKD detection programs in their communities.

AIMS: To determine among adolescents and young adults with youth-onset type 1 diabetes and type 2 diabetes the rates and risk factors for albuminuria regression and progression. METHODS: Data from SEARCH, a longitudinal observational study of youth-onset type 1 diabetes (N=1316) and type 2 diabetes (N=143) were analyzed. Urine albumin:creatinine ratio (UACR) was measured from random urine specimens at baseline and follow-up visits (mean 7years later). Albuminuria regression was defined as halving of baseline UACR when baseline UACR was >/=30mug/mg; progression was defined as doubling of baseline UACR when follow-up UACR was >/=30mug/mg, respectively. Multivariable regression assessed risk factors associated with low-risk albuminuria category (combined persistently-low albuminuria and regression) versus moderate-risk albuminuria category (combined persistently-high albuminuria and progression). RESULTS: Albuminuria progression was more common in type 2 diabetes versus type 1 diabetes (15.4% versus 6.0%, p<0.001). Moderate-risk albuminuria was associated with increasing HbA1c (adjusted OR (aOR)=1.3, 95% CI 1.1-1.6) and lack of private health insurance (aOR=2.7, 95%CI 1.1-6.5) in type 1 diabetes; and African American race (OR=4.6, 95% CI 1.2-14.2), lower estimated insulin sensitivity score (aOR=2.1, 95% CI 1.4-3.3), baseline UACR (aOR=3.2, 95% CI 1.7-5.8), and follow-up estimated glomerular filtration rate (eGFR) (10-unit increase aOR=1.3, 95% CI 1.0, 1.5) in type 2 diabetes. CONCLUSIONS: In the first decade of diabetes duration, kidney complications in type 2 diabetes are significantly more aggressive than in type 1 diabetes and may be associated with less modifiable risk factors including race, insulin sensitivity, and eGFR. Early interventions may help reduce long-term kidney complications.

OBJECTIVE: Cardiovascular disease (CVD) mortality has declined substantially in the U.S. The aims of this study were to examine trends and demographic disparities in mortality due to CVD and CVD subtypes among adults with and without self-reported diabetes. RESEARCH DESIGN AND METHODS: We used the National Health Interview Survey (1985-2014) with mortality follow-up data through the end of 2015 to estimate nationally representative trends and disparities in major CVD, ischemic heart disease (IHD), stroke, heart failure, and arrhythmia mortality among adults >/=20 years of age by diabetes status. RESULTS: Over a mean follow-up period of 11.8 years from 1988 to 2015 of 677,051 adults, there were significant decreases in major CVD death (all P values <0.05) in adults with and without diabetes except adults 20-54 years of age. Among adults with diabetes, 10-year relative changes in mortality were significant for major CVD (-32.7% [95% CI -37.2, -27.9]), IHD (-40.3% [-44.7, -35.6]), and stroke (-29.2% [-40.0, -16.5]), but not heart failure (-0.5% [-20.7, 24.7]), and arrhythmia (-12.0% [-29.4, 77.5]); the absolute decrease of major CVD among adults with diabetes was higher than among adults without diabetes (P < 0.001). Men with diabetes had larger decreases in CVD death than women with diabetes (P < 0.001). CONCLUSIONS: Major CVD mortality in adults with diabetes has declined, especially in men. Large reductions were observed for IHD and stroke mortality, although heart failure and arrhythmia deaths did not change. All race and education groups benefitted to a similar degree, but significant gaps remained across groups.

RATIONALE & OBJECTIVE: Albuminuria and low estimated glomerular filtration rate (eGFR) define chronic kidney disease in adults and youth. Different from adults, the burden of abnormal kidney markers among youth in the general United States population is largely unknown. STUDY DESIGN: Serial cross-sectional national surveys. SETTING & PARTICIPANTS: Adolescents aged 12 to 18 years participating in the National Health and Nutrition Examination Surveys 1988 to 2014. Surveys were grouped into three 6-year periods. PREDICTORS: Demographic and clinical determinants of kidney markers. OUTCOME: Prevalence and trends in persistent albuminuria, low (< 60mL/min/1.73m(2)) and reduced (< 90mL/min/1.73m(2)) eGFRs. ANALYTICAL APPROACH: Outcomes defined as persistent albumin-creatinine ratio >/= 30mg/g (persistent albuminuria), eGFR < 90mL/min/1.73m(2) (reduced kidney function), and eGFR < 60mL/min/1.73m(2) (low kidney function). Multiple imputation analysis was used to estimate missing follow-up values of albuminuria. RESULTS: Prevalences of persistent albuminuria were 3.64% (95% CI, 1.82%-5.46%) in 1988-1994 and 3.29% (95% CI, 1.94%-4.63%) in 2009-2014 (adjusted prevalence ratio, 0.93; 95% CI, 0.53-1.62; P=0.8 for trend). Prevalences of reduced eGFR were 31.46% (95% CI, 28.42%-34.67%) and 34.58% (95% CI, 32.07%-37.18%), respectively (adjusted prevalence ratio, 1.21; 95% CI, 1.00-1.46; P < 0.001 for trend). Prevalences of low eGFR were 0.32% (95% CI, 0.12%-0.84%) in 1988-1994 and 0.91% (95% CI, 0.58%-1.42%) in 2009-2014 (adjusted prevalence ratio, 3.10; 95% CI, 1.10-9.01; P = 0.09 for trend). Prevalences of albuminuria and/or low eGFR remained at 4.0% in 1988-1994 and 2009-2014 (adjusted prevalence ratio, 1.06; 95% CI, 0.64-1.77; P = 0.8 for trend). LIMITATIONS: Persistent albuminuria data were based on imputed values (for second assessment of albuminuria) in 91% of participants; lack of second eGFR assessment to confirm sustained reduction in kidney function. CONCLUSIONS: Albuminuria prevalence has not changed significantly in the US adolescent population between 1988 and 2014. Prevalences of both reduced and low eGFRs were higher in the most recent study period; however, < 1% of adolescents had low eGFRs.

AIMS: To estimate short-term mortality rates for individuals with type 1 or type 2 diabetes diagnosed before age 20years from the SEARCH for Diabetes in Youth study. METHODS: We included 8358 individuals newly-diagnosed with type 1 (n=6840) or type 2 (n=1518) diabetes from 1/1/2002-12/31/2008. We searched the National Death Index through 12/31/2010. We calculated standardized mortality ratios (SMRs) based on age, sex, and race for the comparable US population in the geographic areas of the SEARCH study. RESULTS: During 44,893person-years (PY) of observation (median follow-up=5.3years), 41 individuals died (91.3 deaths/100,000PY); 26 with type 1 (70.6 deaths/100,000PY) and 15 with type 2 (185.6 deaths/100,000PY) diabetes. The expected mortality rate was 70.9 deaths/100,000PY. The overall SMR (95% CI) was 1.3 (1.0, 1.8) and was high among individuals with type 2 diabetes 2.4 (1.3, 3.9), females 2.2 (1.3, 3.3), 15-19year olds 2.7 (1.7,4.0), and non-Hispanic blacks 2.1 (1.2, 3.4). CONCLUSIONS: Compared to the state populations of similar age, sex, and race, our results show excess mortality in individuals with type 2 diabetes, females, older youth, and non-Hispanic blacks. We did not observe excess short-term mortality in individuals with type 1 diabetes.