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Objective To examine factors associated with water filter use (WFU) for drinking tap water at home and its association with consuming plain water and sugar-sweetened beverages (SSBs). Design Quantitative, cross-sectional study. Setting The 2018 SummerStyles survey data. Subjects U.S. adults (≥18 years; N=4042). Measures Outcomes were intake of plain water (tap/bottled water) and SSBs. Exposure was WFU (yes, no, not drinking tap water at home). Covariates included sociodemographics, weight status, Census regions, and home ownership status. Analysis We used multivariable logistic regressions to estimate adjusted odds ratios (AOR) and 95% confidence interval (CI) for consuming tap water, bottled water, or total plain water >3 cups/day (vs. ≤3 cups) and SSBs ≥1 time/day (vs. Results Overall, 36% of adults reported using a filter for drinking tap water at home; 14% did not drink tap water at home. Hispanics had significantly higher odds of using a water filter (AOR=1.50, 95% CI=1.14-1.98) vs non-Hispanic White. Factors significantly associated with lower odds of WFU were lower education (AOR=.69, 95% CI=.55-.86 for ≤high school; AOR=.78, 95% CI=.64-.95 for some college, vs college graduate), not being married (AOR=.81, 95% CI=.66-.98, vs married/domestic partnership), and lower household income (AOR=.68, 95% CI=.68-.90 for 3 cups/day of tap water (AOR=1.33, 95% CI=1.13-1.56) and lower odds of SSBs ≥1 time/day (AOR=.76, 95% CI=.62-.92). Not drinking tap water at home was associated with higher odds of drinking >3 cups/day bottled water (AOR=3.46, 95% CI=2.70-4.44). Conclusions WFU was associated with higher tap water intake and lower SSB intake among U.S. adults. WFU was higher among Hispanics, but lower among those with lower education and income and not married adults. Although WFU was associated with healthful beverage habits, additional considerations for WFU may include source water quality, oral health, cost, and proper use.

Long-term symptoms often associated with COVID-19 (post-COVID conditions or long COVID) are an emerging public health concern that is not well understood. Prevalence of post-COVID conditions has been reported among persons who have had COVID-19 (range = 5%-80%), with differences possibly related to different study populations, case definitions, and data sources (1). Few studies of post-COVID conditions have comparisons with the general population of adults with negative test results for SARS-CoV-2, the virus that causes COVID-19, limiting ability to assess background symptom prevalence (1). CDC used a nonprobability-based Internet panel established by Porter Novelli Public Services* to administer a survey to a nationwide sample of U.S. adults aged ≥18 years to compare the prevalence of long-term symptoms (those lasting >4 weeks since onset) among persons who self-reported ever receiving a positive SARS-CoV-2 test result with the prevalence of similar symptoms among persons who reported always receiving a negative test result. The weighted prevalence of ever testing positive for SARS-CoV-2 was 22.2% (95% confidence interval [CI] = 20.6%-23.8%). Approximately two thirds of respondents who had received a positive test result experienced long-term symptoms often associated with SARS-CoV-2 infection. Compared with respondents who received a negative test result, those who received a positive test result reported a significantly higher prevalence of any long-term symptom (65.9% versus 42.9%), fatigue (22.5% versus 12.0%), change in sense of smell or taste (17.3% versus 1.7%), shortness of breath (15.5% versus 5.2%), cough (14.5% versus 4.9%), headache (13.8% versus 9.9%), and persistence (>4 weeks) of at least one initially occurring symptom (76.2% versus 69.6%). Compared with respondents who received a negative test result, a larger proportion of those who received a positive test result reported believing that receiving a COVID-19 vaccine made their long-term symptoms better (28.7% versus 15.7%). Efforts to address post-COVID conditions should include helping health care professionals recognize the most common post-COVID conditions and optimize care for patients with persisting symptoms, including messaging on potential benefits of COVID-19 vaccination.

Background Late sequelae of COVID-19 have been reported; however, few studies have investigated the time course or incidence of late new COVID-19–related health conditions (post-COVID conditions) after COVID-19 diagnosis. Studies distinguishing post-COVID conditions from late conditions caused by other etiologies are lacking. Using data from a large administrative all-payer database, we assessed type, association, and timing of post-COVID conditions following COVID-19 diagnosis. Methods Using the Premier Healthcare Database Special COVID-19 Release (release date, 20 October 2020) data, during March–June 2020, 27 589 inpatients and 46 857 outpatients diagnosed with COVID-19 (case-patients) were 1:1 matched with patients without COVID-19 through the 4-month follow-up period (control-patients) by using propensity score matching. In this matched-cohort study, adjusted ORs were calculated to assess for late conditions that were more common in case-patients than control-patients. Incidence proportion was calculated for conditions that were more common in case-patients than control-patients during 31–120 days following a COVID-19 encounter. Results During 31–120 days after an initial COVID-19 inpatient hospitalization, 7.0% of adults experienced ≥1 of 5 post-COVID conditions. Among adult outpatients with COVID-19, 7.7% experienced ≥1 of 10 post-COVID conditions. During 31–60 days after an initial outpatient encounter, adults with COVID-19 were 2.8 times as likely to experience acute pulmonary embolism as outpatient control-patients and also more likely to experience a range of conditions affecting multiple body systems (eg, nonspecific chest pain, fatigue, headache, and respiratory, nervous, circulatory, and gastrointestinal symptoms) than outpatient control-patients. Conclusions These findings add to the evidence of late health conditions possibly related to COVID-19 in adults following COVID-19 diagnosis and can inform healthcare practice and resource planning for follow-up COVID-19 care.

Health consequences that persist beyond the acute infection phase of COVID-19, termed post-COVID-19 condition (also commonly known as long COVID), vary widely and represent a growing global health challenge. Research on post-COVID-19 condition is expanding but, at present, no agreement exists on the health outcomes that should be measured in people living with the condition. To address this gap, we conducted an international consensus study, which included a comprehensive literature review and classification of outcomes for post-COVID-19 condition that informed a two-round online modified Delphi process followed by an online consensus meeting to finalise the core outcome set (COS). 1535 participants from 71 countries were involved, with 1148 individuals participating in both Delphi rounds. Eleven outcomes achieved consensus for inclusion in the final COS: fatigue; pain; post-exertion symptoms; work or occupational and study changes; survival; and functioning, symptoms, and conditions for each of cardiovascular, respiratory, nervous system, cognitive, mental health, and physical outcomes. Recovery was included a priori because it was a relevant outcome that was part of a previously published COS on COVID-19. The next step in this COS development exercise will be to establish the instruments that are most appropriate to measure these core outcomes. This international consensus-based COS should provide a framework for standardised assessment of adults with post-COVID-19 condition, aimed at facilitating clinical care and research worldwide.

Coronavirus disease 2019 (COVID-19) is a complex clinical illness with potential complications that might require ongoing clinical care (1-3). Few studies have investigated discharge patterns and hospital readmissions among large groups of patients after an initial COVID-19 hospitalization (4-7). Using electronic health record and administrative data from the Premier Healthcare Database,* CDC assessed patterns of hospital discharge, readmission, and demographic and clinical characteristics associated with hospital readmission after a patient's initial COVID-19 hospitalization (index hospitalization). Among 126,137 unique patients with an index COVID-19 admission during March-July 2020, 15% died during the index hospitalization. Among the 106,543 (85%) surviving patients, 9% (9,504) were readmitted to the same hospital within 2 months of discharge through August 2020. More than a single readmission occurred among 1.6% of patients discharged after the index hospitalization. Readmissions occurred more often among patients discharged to a skilled nursing facility (SNF) (15%) or those needing home health care (12%) than among patients discharged to home or self-care (7%). The odds of hospital readmission increased with age among persons aged ≥65 years, presence of certain chronic conditions, hospitalization within the 3 months preceding the index hospitalization, and if discharge from the index hospitalization was to a SNF or to home with health care assistance. These results support recent analyses that found chronic conditions to be significantly associated with hospital readmission (6,7) and could be explained by the complications of underlying conditions in the presence of COVID-19 (8), COVID-19 sequelae (3), or indirect effects of the COVID-19 pandemic (9). Understanding the frequency of, and risk factors for, readmission can inform clinical practice, discharge disposition decisions, and public health priorities such as health care planning to ensure availability of resources needed for acute and follow-up care of COVID-19 patients. With the recent increases in cases nationwide, hospital planning can account for these increasing numbers along with the potential for at least 9% of patients to be readmitted, requiring additional beds and resources.

New symptoms and conditions can develop following SARS-CoV-2 infection. Whether they occur more frequently among persons with SARS-CoV-2 infection compared with those without is unclear.To compare the prevalence of new diagnoses of select symptoms and conditions between 31 and 150 days after testing among persons who tested positive vs negative for SARS-CoV-2.This cohort study analyzed aggregated electronic health record data from 40 health care systems, including 338 024 persons younger than 20 years and 1 790 886 persons aged 20 years or older who were tested for SARS-CoV-2 during March to December 2020 and who had medical encounters between 31 and 150 days after testing.International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes were used to capture new symptoms and conditions that were recorded 31 to 150 days after a SARS-CoV-2 test but absent in the 18 months to 7 days prior to testing. The prevalence of new symptoms and conditions was compared between persons with positive and negative SARS-CoV-2 tests stratified by age (20 years or older and young than 20 years) and care setting (nonhospitalized, hospitalized, or hospitalized and ventilated).A total of 168 701 persons aged 20 years or older and 26 665 younger than 20 years tested positive for SARS-CoV-2, and 1 622 185 persons aged 20 years or older and 311 359 younger than 20 years tested negative. Shortness of breath was more common among persons with a positive vs negative test result among hospitalized patients (≥20 years: prevalence ratio [PR], 1.89 [99% CI, 1.79-2.01];20 years: PR, 1.72 [99% CI, 1.17-2.51]). Shortness of breath was also more common among nonhospitalized patients aged 20 years or older with a positive vs negative test result (PR, 1.09 [99% CI, 1.05-1.13]). Among hospitalized persons aged 20 years or older, the prevalence of new fatigue (PR, 1.35 [99% CI, 1.27-1.44]) and type 2 diabetes (PR, 2.03 [99% CI, 1.87-2.19]) was higher among those with a positive vs a negative test result. Among hospitalized persons younger than 20 years, the prevalence of type 2 diabetes (PR, 2.14 [99% CI, 1.13-4.06]) was higher among those with a positive vs a negative test result; however, the prevalence difference was less than 1%.In this cohort study, among persons hospitalized after a positive SARS-CoV-2 test result, diagnoses of certain symptoms and conditions were higher than among those with a negative test result. Health care professionals should be aware of symptoms and conditions that may develop after SARS-CoV-2 infection, particularly among those hospitalized after diagnosis.

INTRODUCTION: Hypertension and diabetes are associated with increased COVID-19 severity, yet less is known about COVID-19 outcomes across levels of disease control for these conditions. METHODS: All adults aged ≥20 years with COVID-19 between March 1, 2020 and March 15, 2021 in 42 healthcare systems in National Patient-Centered Clinical Research Network were identified. RESULTS: Among 656,049 adults with COVID-19, 41% had hypertension, and 13% had diabetes. Of patients with classifiable hypertension, 35% had blood pressure

In July 2019, the Illinois Department of Public Health and the Wisconsin Department of Health Services launched a coordinated epidemiologic investigation after receiving reports of several cases of lung injury in previously healthy persons who reported electronic cigarette (e-cigarette) use, or vaping (1). This report describes features of e-cigarette product use by patients in Illinois and Wisconsin. Detailed patient interviews were conducted by telephone, in person, or via the Internet with 86 (68%) of 127 patients. Overall, 75 (87%) of 86 interviewed patients reported using e-cigarette products containing tetrahydrocannabinol (THC), and 61 (71%) reported using nicotine-containing products. Numerous products and brand names were identified by patients. Nearly all (96%) THC-containing products reported were packaged, prefilled cartridges, and 89% were primarily acquired from informal sources (e.g., friends, family members, illicit dealers, or off the street). In contrast, 77% of nicotine-containing products were sold as prefilled cartridges, and 83% were obtained from commercial vendors. The precise source of this outbreak is currently unknown (2); however, the predominant use of prefilled THC-containing cartridges among patients with lung injury associated with e-cigarette use suggests that they play an important role. While this investigation is ongoing, CDC recommends that persons consider refraining from using e-cigarette, or vaping, products, particularly those containing THC. Given the diversity of products reported and frequency of patients using both THC- and nicotine-containing e-cigarette products, additional methods such as product testing and traceback could help identify the specific cause of this outbreak.

As of June 30, 2021, 33.5 million persons in the United States had received a diagnosis of COVID-19 (1). Although most patients infected with SARS-CoV-2, the virus that causes COVID-19, recover within a few weeks, some experience post-COVID-19 conditions. These range from new or returning to ongoing health problems that can continue beyond 4 weeks. Persons who were asymptomatic at the time of infection can also experience post-COVID-19 conditions. Data on post-COVID-19 conditions are emerging and information on rehabilitation needs among persons recovering from COVID-19 is limited. Using data acquired during January 2020-March 2021 from Select Medical* outpatient rehabilitation clinics, CDC compared patient-reported measures of health, physical endurance, and health care use between patients who had recovered from COVID-19 (post-COVID-19 patients) and patients needing rehabilitation because of a current or previous diagnosis of a neoplasm (cancer) who had not experienced COVID-19 (control patients). All patients had been referred to outpatient rehabilitation. Compared with control patients, post-COVID-19 patients had higher age- and sex-adjusted odds of reporting worse physical health (adjusted odds ratio [aOR] = 1.8), pain (aOR = 2.3), and difficulty with physical activities (aOR = 1.6). Post-COVID-19 patients also had worse physical endurance, measured by the 6-minute walk test† (6MWT) (p

INTRODUCTION: Severe COVID-19 illness in adults has been linked to underlying medical conditions. This study identified frequent underlying conditions and their attributable risk of severe COVID-19 illness. METHODS: We used data from more than 800 US hospitals in the Premier Healthcare Database Special COVID-19 Release (PHD-SR) to describe hospitalized patients aged 18 years or older with COVID-19 from March 2020 through March 2021. We used multivariable generalized linear models to estimate adjusted risk of intensive care unit admission, invasive mechanical ventilation, and death associated with frequent conditions and total number of conditions. RESULTS: Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27-1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25-1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24-1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41-1.67) for patients with 1 condition to 3.82 (95% CI, 3.45-4.23) for patients with more than 10 conditions (compared with patients with no conditions). CONCLUSION: Certain underlying conditions and the number of conditions were associated with severe COVID-19 illness. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, and anxiety disorders were the strongest risk factors for severe COVID-19 illness. Careful evaluation and management of underlying conditions among patients with COVID-19 can help stratify risk for severe illness.

Importance Information on underlying conditions and severe COVID-19 illness among children is limited. Objective To examine the risk of severe COVID-19 illness among children associated with underlying medical conditions and medical complexity. Design, setting, and participants This cross-sectional study included patients aged 18 years and younger with International Statistical Classification of Diseases, Tenth Revision, Clinical Modification code U07.1 (COVID-19) or B97.29 (other coronavirus) during an emergency department or inpatient encounter from March 2020 through January 2021. Data were collected from the Premier Healthcare Database Special COVID-19 Release, which included data from more than 800 US hospitals. Multivariable generalized linear models, controlling for patient and hospital characteristics, were used to estimate adjusted risk of severe COVID-19 illness associated with underlying medical conditions and medical complexity. Exposures Underlying medical conditions and medical complexity (ie, presence of complex or noncomplex chronic disease). Main outcomes and measures Hospitalization and severe illness when hospitalized (ie, combined outcome of intensive care unit admission, invasive mechanical ventilation, or death). Results Among 43 465 patients with COVID-19 aged 18 years or younger, the median (interquartile range) age was 12 (4-16) years, 22 943 (52.8%) were female patients, and 12 491 (28.7%) had underlying medical conditions. The most common diagnosed conditions were asthma (4416 [10.2%]), neurodevelopmental disorders (1690 [3.9%]), anxiety and fear-related disorders (1374 [3.2%]), depressive disorders (1209 [2.8%]), and obesity (1071 [2.5%]). The strongest risk factors for hospitalization were type 1 diabetes (adjusted risk ratio [aRR], 4.60; 95% CI, 3.91-5.42) and obesity (aRR, 3.07; 95% CI, 2.66-3.54), and the strongest risk factors for severe COVID-19 illness were type 1 diabetes (aRR, 2.38; 95% CI, 2.06-2.76) and cardiac and circulatory congenital anomalies (aRR, 1.72; 95% CI, 1.48-1.99). Prematurity was a risk factor for severe COVID-19 illness among children younger than 2 years (aRR, 1.83; 95% CI, 1.47-2.29). Chronic and complex chronic disease were risk factors for hospitalization, with aRRs of 2.91 (95% CI, 2.63-3.23) and 7.86 (95% CI, 6.91-8.95), respectively, as well as for severe COVID-19 illness, with aRRs of 1.95 (95% CI, 1.69-2.26) and 2.86 (95% CI, 2.47-3.32), respectively. Conclusions and relevance This cross-sectional study found a higher risk of severe COVID-19 illness among children with medical complexity and certain underlying conditions, such as type 1 diabetes, cardiac and circulatory congenital anomalies, and obesity. Health care practitioners could consider the potential need for close observation and cautious clinical management of children with these conditions and COVID-19.

This cohort study uses data from the Premier Healthcare Database Special COVID-19 Release to assess the association of demographic and clinical characteristics with severe COVID-19 illness among hospitalized US pediatric patients with COVID-19.

Frequent intake of sugar-sweetened beverages (SSBs) is associated with adverse health outcomes, including obesity, type 2 diabetes, and cardiovascular disease. We used combined data from the 2010 and 2015 National Health Interview Survey to examine the prevalence of SSB intake among US adults in all 50 states and the District of Columbia. Approximately two-thirds of adults reported consuming SSBs at least daily, including more than 7 in 10 adults in Hawaii, Arkansas, Wyoming, South Dakota, Connecticut, and South Carolina, with significant differences in sociodemographic characteristics. Efforts to decrease SSB consumption could consider the sociodemographic and geographic differences in SSB intake when designing equitable interventions.

Background Older adults and people from certain racial and ethnic groups are disproportionately represented in coronavirus disease 2019 (COVID-19) hospitalizations and deaths. Methods Using data from the Premier Healthcare Database on 181 813 hospitalized adults diagnosed with COVID-19 during March–September 2020, we applied multivariable log-binomial regression to assess the associations between age and race/ethnicity and COVID-19 clinical severity (intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], and death) and to determine whether the impact of age on clinical severity differs by race/ethnicity. Results Overall, 84 497 (47%) patients were admitted to the ICU, 29 078 (16%) received IMV, and 27 864 (15%) died in the hospital. Increased age was strongly associated with clinical severity when controlling for underlying medical conditions and other covariates; the strength of this association differed by race/ethnicity. Compared with non-Hispanic White patients, risk of death was lower among non-Hispanic Black patients (adjusted risk ratio, 0.96; 95% CI, 0.92–0.99) and higher among Hispanic/Latino patients (risk ratio [RR], 1.15; 95% CI, 1.09–1.20), non-Hispanic Asian patients (RR, 1.16; 95% CI, 1.09–1.23), and patients of other racial and ethnic groups (RR, 1.13; 95% CI, 1.06–1.21). Risk of ICU admission and risk of IMV were elevated among some racial and ethnic groups. Conclusions These results indicate that age is a driver of poor outcomes among hospitalized persons with COVID-19. Additionally, clinical severity may be elevated among patients of some racial and ethnic minority groups. Public health strategies to reduce severe acute respiratory syndrome coronavirus 2 infection rates among older adults and racial and ethnic minorities are essential to reduce poor outcomes.

OBJECTIVES: While drinking plain water instead of sugar-sweetened beverages (SSB) may improve diet and prevent diseases, bottled water is more costly than tap water and typically does not contain fluoride for oral health benefits. We explored bottled water acquisition among US households and its relationship with SSB acquisition. METHODS: We used data from the USDA Food Acquisition and Purchasing Survey, which collected 7 days of data on all foods purchased or obtained for free in a nationally representative sample of 4826 households during 2012. Data were collected using food record books and bar code scanners. We assessed the prevalence of acquiring bottled water to bring home and for immediate consumption away from home, volume of water acquired, money spent on water, and the association of water acquisition with SSB acquisition. Differences in prevalence according to race/ethnicity, Census region, education level, rural status, and income/SNAP status were assessed using Chi-square tests. Adjusted linear models were used to assess the association of acquiring water for home or away from home with per-capita household total SSB calories acquired. RESULTS: A quarter (24.6%) of households acquired any bottled water during the study week with 16.2% acquiring water for home and 11.1% away from home. Prevalence of acquiring any bottled water differed by region and race/ethnicity and was highest among households in the South and West (each 26.8%) and among Hispanic households (35.2%). Among those that acquired each type, households spent $4.13 acquiring 14.1 liters of water for home, while households spent $1.65 acquiring 2.0 liters for away from home. In regression models, households that acquired bottled water for home had greater per capita SSB calorie acquisition than households that did not (adjusted mean: 1203 vs. 734 kcal/week; P = 0.0005); acquiring water for away from home was not associated with greater per capita SSB calorie acquisition (adjusted means: 931 vs. 1005 kcal; P = 0.34). CONCLUSIONS: One quarter of US households acquire bottled water though acquisition differs according to demographic factors. Although plain water can reduce caloric intake when substituted for SSB, findings suggest that households that acquire bottled water for home also acquire more SSB calories than households that do not. FUNDING SOURCES: Solely for authors time from their institutions.

West Nile virus (WNV) and St. Louis encephalitis virus (SLEV) are closely related mosquito-borne flaviviruses that can cause neuroinvasive disease. No concurrent WNV and SLEV disease outbreaks have previously been identified. When concurrent outbreaks occurred in 2015 in Maricopa County, Arizona, we collected data to describe the epidemiology, and to compare features of patients with WNV and SLEV neuroinvasive disease. We performed enhanced case finding, and gathered information from medical records and patient interviews. A case was defined as a clinically compatible illness and laboratory evidence of WNV, SLEV, or unspecified flavivirus infection in a person residing in Maricopa County in 2015. We compared demographic and clinical features of WNV and SLEV neuroinvasive cases; for this analysis, a case was defined as physician-documented encephalitis or meningitis and a white blood cell count >5 cells/mm(3) in cerebrospinal fluid. In total, we identified 82 cases, including 39 WNV, 21 SLEV, and 22 unspecified flavivirus cases. The comparative analysis included 21 WNV and 14 SLEV neuroinvasive cases. Among neuroinvasive cases, the median age of patients with SLEV (63 years) was higher than WNV (52 years). Patients had similar symptoms; rash was identified more frequently in WNV (33%) neuroinvasive cases than in SLEV (7%) cases, but this difference was not statistically significant (p = 0.11). In summary, during the first known concurrent WNV and SLEV disease outbreaks, no specific clinical features were identified that could differentiate between WNV and SLEV neuroinvasive cases. Health care providers should consider both infections in patients with aseptic meningitis or encephalitis.