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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., Competing Interests: Potential conflicts of interest. This project was funded by the CDC, and CDC co-authors took part in the project design, conduct, analysis, and manuscript preparation. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2022.)

Background: There are limited data on the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the United States by occupation. We identified occupations at higher risk for prior SARS-CoV-2 infection as defined by the presence of infection-induced antibodies among US 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 and ethnicity, education, vaccination, and telework., Results: Among 85 986 included survey respondents, 9504 (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 odds ratio [aOR], 2.10; 95% confidence interval [CI], 1.74-2.54) and healthcare support (aOR, 1.82; 95% CI, 1.39-2.40) occupations compared with computer and mathematical occupations as the referent group. Lack of coronavirus disease 2019 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. Construction and extraction occupations had the highest proportion of unvaccinated workers (30.5%)., 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., Competing Interests: Potential conflicts of interest. S. S. reports grants or contracts from US Food and Drug Administration (FDA; TTIMS and Advance Study) unrelated to this work. B. S. reports grants or contracts from REDS-IV subcontract (support from the National Heart, Lung, and Blood Institute [NHLBI]) unrelated to this work. J. M. H. reports grants or contract from FDA (TTIMS) and NHLBI (REDS-IV). All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2022.)

Objective: To develop an efficient surveillance approach for childhood diabetes by type across 2 large US health care systems, using phenotyping algorithms derived from electronic health record (EHR) data., Materials and Methods: Presumptive diabetes cases <20 years of age from 2 large independent health care systems were identified as those having ≥1 of the 5 indicators in the past 3.5 years, including elevated HbA1c, elevated blood glucose, diabetes-related billing codes, patient problem list, and outpatient anti-diabetic medications. EHRs of all the presumptive cases were manually reviewed, and true diabetes status and diabetes type were determined. Algorithms for identifying diabetes cases overall and classifying diabetes type were either prespecified or derived from classification and regression tree analysis. Surveillance approach was developed based on the best algorithms identified., Results: We developed a stepwise surveillance approach using billing code-based prespecified algorithms and targeted manual EHR review, which efficiently and accurately ascertained and classified diabetes cases by type, in both health care systems. The sensitivity and positive predictive values in both systems were approximately ≥90% for ascertaining diabetes cases overall and classifying cases with type 1 or type 2 diabetes. About 80% of the cases with "other" type were also correctly classified. This stepwise surveillance approach resulted in a >70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods., Conclusion: EHR data may be used to establish an efficient approach for large-scale surveillance for childhood diabetes by type, although some manual effort is still needed., (Published by Oxford University Press on behalf of the American Medical Informatics Association 2016. This work is written by US Government employees and is in the public domain in the United States.)

Background: Albuminuria, defined as urine albumin/creatinine ratio (ACR) ≥30 mg/g, is a diagnostic component of chronic kidney disease (CKD). National estimates of ACR and CKD prevalence have been based on single random urine samples. Although 2 urine samples or a first morning void are known to produce different estimates of ACR, the impact of differing urine sampling schemes on nationally estimated rates of CKD is unknown., Methods: In 2009-2010, the National Health and Nutrition Examination Survey (NHANES) participants provided 2 untimed urine samples for sequential ACR measurement: an initial random urine collected in the NHANES mobile examination center and a subsequent first morning void collected at home. Rates of albuminuria were calculated in the overall population and broken down by demographics, diagnosed diabetes and hypertension status, and estimated glomerular filtration rate (eGFR)., Results: Overall, 43.5% of adults with increased ACR (≥30 mg/g) in a random urine also had increased ACR in a first morning urine. This percentage was higher among individuals ≥50 years old (48.9%), males (53.3%), participants with diagnosed diabetes (56.3%) and hypertension (51.5%), and eGFR <60 mL/min/1.72m(2) (56.9%). The use of confirmed increased ACR (defined as the presence of ACR ≥30 mg/g in both samples taken within 10 days) to define CKD resulted in a lower overall prevalence (11.6%) than first morning urine (12.7%) or random spot urine only (15.2%)., Conclusions: ACR measured on random urine samples appears to overestimate the prevalence of albuminuria compared to first morning urine collections., (© 2013 American Association for Clinical Chemistry)

Although abnormal glucose tolerance is a well-established risk factor for cardiovascular disease, its relation to cancer risk is less certain. Therefore, the authors performed a prospective cohort study using data from the Second National Health and Nutrition Examination Survey and the Second National Health and Nutrition Examination Survey Mortality Study to determine this relation. This analysis focused upon a nationally representative sample of 3,054 adults aged 30-74 years who underwent an oral glucose tolerance test at baseline (1976-1980). Deaths were identified by searching national mortality files through 1992. Adults were classified as having either previously diagnosed diabetes (n = 247), undiagnosed diabetes (n = 180), impaired glucose tolerance (n = 477), or normal glucose tolerance (n = 2250). There were 195 cancer deaths during 40,024 person-years of follow-up. Compared with those having normal glucose tolerance, adults with impaired glucose tolerance had the greatest adjusted relative hazard of cancer mortality (relative hazard = 1.87, 95% confidence interval (CI): 1.06, 3.31), followed by those with undiagnosed diabetes (relative hazard = 1.31, 95% CI: 0.48, 3.56) and diabetes (relative hazard = 1.13, 95% CI: 0.49, 2.62). These data suggest that, in the United States, impaired glucose tolerance is an independent predictor for cancer mortality.

Diabetes is a well-established cause of cardiovascular disease (CVD) and all-cause mortality. The burden of death attributable to diabetes in the United States is not well quantified, particularly with regard to age. The authors analyzed data from the Second National Health and Nutrition Examination Survey (NHANES II) (1976-1980) and the NHANES II Mortality Study, in which a nationally representative cohort of 9,250 adults aged 30-75 years was followed for 12-16 years, to determine all-cause and cause-specific mortality. Overall, between 1976 and 1980, the prevalence of diagnosed diabetes was 4.3%. By 1992, the relative hazard of all-cause mortality was 1.9 (95% confidence interval: 1.5, 2.3), and the population attributable risk (PAR) was 3.6%. The relative hazard of CVD mortality was 2.3 (95% confidence interval: 1.8, 2.8), and the PAR was 5.2%. Including participants with undiagnosed diabetes in the estimates increased the PAR for all-cause mortality to 5.1% and that for CVD mortality to 6.8%. Women had a higher prevalence of diagnosed diabetes than men and a greater relative hazard of death than nondiabetic women, leading to a higher PAR for women (3.8% for all causes and 7.3% for CVD) versus men (3.3% for all causes and 3.8% for CVD). These data suggest that diabetes accounts for at least 3.6% of all deaths and 5.2% of CVD deaths in US adults. Improvements in diabetes prevention and treatment should produce noticeable effects on US life expectancy.