Dataset Information

Obesity and Mortality Among Patients Diagnosed With COVID-19: Results From an Integrated Health Care Organization.

ABSTRACT:

Background

Obesity, race/ethnicity, and other correlated characteristics have emerged as high-profile risk factors for adverse coronavirus disease 2019 (COVID-19)-associated outcomes, yet studies have not adequately disentangled their effects.

Objective

To determine the adjusted effect of body mass index (BMI), associated comorbidities, time, neighborhood-level sociodemographic factors, and other factors on risk for death due to COVID-19.

Design

Retrospective cohort study.

Setting

Kaiser Permanente Southern California, a large integrated health care organization.

Patients

Kaiser Permanente Southern California members diagnosed with COVID-19 from 13 February to 2 May 2020.

Measurements

Multivariable Poisson regression estimated the adjusted effect of BMI and other factors on risk for death at 21 days; models were also stratified by age and sex.

Results

Among 6916 patients with COVID-19, there was a J-shaped association between BMI and risk for death, even after adjustment for obesity-related comorbidities. Compared with patients with a BMI of 18.5 to 24 kg/m², those with BMIs of 40 to 44 kg/m² and greater than 45 kg/m² had relative risks of 2.68 (95% CI, 1.43 to 5.04) and 4.18 (CI, 2.12 to 8.26), respectively. This risk was most striking among those aged 60 years or younger and men. Increased risk for death associated with Black or Latino race/ethnicity or other sociodemographic characteristics was not detected.

Limitation

Deaths occurring outside a health care setting and not captured in membership files may have been missed.

Conclusion

Obesity plays a profound role in risk for death from COVID-19, particularly in male patients and younger populations. Our capitated system with more equalized health care access may explain the absence of effect of racial/ethnic and socioeconomic disparities on death. Our data highlight the leading role of severe obesity over correlated risk factors, providing a target for early intervention.

Primary funding source

Roche-Genentech.

SUBMITTER: Tartof SY

PROVIDER: S-EPMC7429998 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Obesity and Mortality Among Patients Diagnosed With COVID-19: Results From an Integrated Health Care Organization.

Tartof Sara Y SY Qian Lei L Hong Vennis V Wei Rong R Nadjafi Ron F RF Fischer Heidi H Li Zhuoxin Z Shaw Sally F SF Caparosa Susan L SL Nau Claudia L CL Saxena Tanmai T Rieg Gunter K GK Ackerson Bradley K BK Sharp Adam L AL Skarbinski Jacek J Naik Tej K TK Murali Sameer B SB

Annals of internal medicine 20200812 10

<h4>Background</h4>Obesity, race/ethnicity, and other correlated characteristics have emerged as high-profile risk factors for adverse coronavirus disease 2019 (COVID-19)-associated outcomes, yet studies have not adequately disentangled their effects.<h4>Objective</h4>To determine the adjusted effect of body mass index (BMI), associated comorbidities, time, neighborhood-level sociodemographic factors, and other factors on risk for death due to COVID-19.<h4>Design</h4>Retrospective cohort study.< ...[more]

PMID: 32783686

Similar Datasets

Project description:BackgroundReports have suggested an association between the development of myocarditis and the receipt of messenger RNA (mRNA) vaccines against coronavirus disease 2019 (Covid-19), but the frequency and severity of myocarditis after vaccination have not been extensively explored.MethodsWe searched the database of Clalit Health Services, the largest health care organization (HCO) in Israel, for diagnoses of myocarditis in patients who had received at least one dose of the BNT162b2 mRNA vaccine (Pfizer-BioNTech). The diagnosis of myocarditis was adjudicated by cardiologists using the case definition used by the Centers for Disease Control and Prevention. We abstracted the presentation, clinical course, and outcome from the patient's electronic health record. We performed a Kaplan-Meier analysis of the incidence of myocarditis up to 42 days after the first vaccine dose.ResultsAmong more than 2.5 million vaccinated HCO members who were 16 years of age or older, 54 cases met the criteria for myocarditis. The estimated incidence per 100,000 persons who had received at least one dose of vaccine was 2.13 cases (95% confidence interval [CI], 1.56 to 2.70). The highest incidence of myocarditis (10.69 cases per 100,000 persons; 95% CI, 6.93 to 14.46) was reported in male patients between the ages of 16 and 29 years. A total of 76% of cases of myocarditis were described as mild and 22% as intermediate; 1 case was associated with cardiogenic shock. After a median follow-up of 83 days after the onset of myocarditis, 1 patient had been readmitted to the hospital, and 1 had died of an unknown cause after discharge. Of 14 patients who had left ventricular dysfunction on echocardiography during admission, 10 still had such dysfunction at the time of hospital discharge. Of these patients, 5 underwent subsequent testing that revealed normal heart function.ConclusionsAmong patients in a large Israeli health care system who had received at least one dose of the BNT162b2 mRNA vaccine, the estimated incidence of myocarditis was 2.13 cases per 100,000 persons; the highest incidence was among male patients between the ages of 16 and 29 years. Most cases of myocarditis were mild or moderate in severity. (Funded by the Ivan and Francesca Berkowitz Family Living Laboratory Collaboration at Harvard Medical School and Clalit Research Institute.).

Project description:Coronavirus disease 2019 (COVID-19) has already raised serious concern globally as the number of confirmed or suspected cases have increased rapidly. Epidemiological studies reported that obesity is associated with a higher rate of mortality in patients with COVID-19. Yet, to our knowledge, there is no comprehensive systematic review and meta-analysis to assess the effects of obesity and mortality among patients with COVID-19. We, therefore, aimed to evaluate the effect of obesity, associated comorbidities, and other factors on the risk of death due to COVID-19. We did a systematic search on PubMed, EMBASE, Google Scholar, Web of Science, and Scopus between January 1, 2020, and August 30, 2020. We followed Cochrane Guidelines to find relevant articles, and two reviewers extracted data from retrieved articles. Disagreement during those stages was resolved by discussion with the main investigator. The random-effects model was used to calculate effect sizes. We included 17 articles with a total of 543,399 patients. Obesity was significantly associated with an increased risk of mortality among patients with COVID-19 (RRadjust: 1.42 (95%CI: 1.24-1.63, p < 0.001). The pooled risk ratio for class I, class II, and class III obesity were 1.27 (95%CI: 1.05-1.54, p = 0.01), 1.56 (95%CI: 1.11-2.19, p < 0.01), and 1.92 (95%CI: 1.50-2.47, p < 0.001), respectively). In subgroup analysis, the pooled risk ratio for the patients with stroke, CPOD, CKD, and diabetes were 1.80 (95%CI: 0.89-3.64, p = 0.10), 1.57 (95%CI: 1.57-1.91, p < 0.001), 1.34 (95%CI: 1.18-1.52, p < 0.001), and 1.19 (1.07-1.32, p = 0.001), respectively. However, patients with obesity who were more than 65 years had a higher risk of mortality (RR: 2.54; 95%CI: 1.62-3.67, p < 0.001). Our study showed that obesity was associated with an increased risk of death from COVID-19, particularly in patients aged more than 65 years. Physicians should aware of these risk factors when dealing with patients with COVID-19 and take early treatment intervention to reduce the mortality of COVID-19 patients.

Project description:BackgroundThe demands for healthcare resources following a COVID-19 diagnosis are substantial, but not currently quantified.ObjectiveTo describe trends in healthcare utilization within 180 days for patients diagnosed with COVID-19 and identify patient factors associated with increased healthcare use.DesignObservational cohort study.PatientsA total of 64,011 patients with a test-confirmed COVID-19 diagnosis from March to September 2020 in a large integrated healthcare system in Southern California.Main measuresOverall healthcare utilization during the 180 days following COVID-19 diagnosis, as well as encounter types and reasons for visits during the first 30 days. Poisson regression was used to identify patient factors associated with higher utilization. Analyses were performed separately for patients who were and were not hospitalized for COVID-19.Key resultsHealthcare utilization was about twice as high for hospitalized patients compared to non-hospitalized patients in all time periods. The average number of visits was highest in the first 30 days (hospitalized: 12.3 visits/30 person-days; non-hospitalized: 6.6) and gradually decreased over time. In the first 30 days, the majority of healthcare visits were telehealth encounters (hospitalized: 9.0 visits; non-hospitalized: 5.6 visits), and the most prevalent reasons for visits were COVID-related diagnoses, COVID-related symptoms, and respiratory-related conditions. For hospitalized patients, older age (≥65: RR 1.27, 95% CI 1.15-1.41), female gender (RR 1.07, 95% CI 1.05-1.09), and higher BMI (≥40: RR 1.07, 95% CI 1.03-1.10) were associated with higher total utilization. For non-hospitalized patients, older age, female gender, higher BMI, non-white race/ethnicity, former smoking, and greater number of pre-existing comorbidities were all associated with increased utilization.ConclusionsPatients with COVID-19 seek healthcare frequently within 30 days of diagnosis, placing high demands on health systems. Identifying ways to support patients diagnosed with COVID-19 while adequately providing the usual recommended care to our communities will be important as we recover from the pandemic.

Project description:BackgroundDramatic decreases in outpatient visits and sudden increases in telehealth visits were observed during the COVID-19 pandemic, but it was unclear whether these changes differed by patient demographics and socioeconomic status.ObjectiveThis study aimed to assess the impact of the pandemic on in-person outpatient and telehealth visits (telephone and video) by demographic characteristics and household income in a diverse population.MethodsWe calculated weekly rates of outpatient and telehealth visits by age, sex, race/ethnicity, and neighborhood-level median household income among members of Kaiser Permanente Southern California (KPSC) from January 5, 2020, to October 31, 2020, and the corresponding period in 2019. We estimated the percentage change in visit rates during the early pandemic period (March 22 to April 25, 2020) and the late pandemic period (October 4 to October 31, 2020) from the prepandemic period (January 5 to March 7, 2020) in Poisson regression models for each subgroup while adjusting for seasonality using 2019 data. We examined if the changes in visit rates differed by subgroups statistically by comparing their 95% CIs.ResultsAmong 4.56 million KPSC members enrolled in January 2020, 15.0% (n=682,947) were ≥65 years old, 51.5% (n=2,345,020) were female, 39.4% (n=1,795,994) were Hispanic, and 7.7% (n=350,721) lived in an area of median household income <US $40,000. Increases in telehealth visits during the pandemic varied across subgroups, while decreases in outpatient visits were similar, except by age. Among age groups, the ≥65 years population had the least increase in telehealth visits (236.6%, 95% CI 228.8%-244.5%), with 4.9 per one person-year during the early pandemic period versus 1.5 per one person-year during the prepandemic period. During the same periods, across racial/ethnic groups, Hispanic individuals had the largest increase in telehealth visits (295.5%, 95% CI 275.5%-316.5%). Across income levels, telehealth visits in the low-income group increased the most (313.5%, 95% CI 294.8%-333.1%). The rate of combined outpatient and telehealth visits in the Hispanic, non-Hispanic Black, and low-income groups returned to prepandemic levels by October 2020.ConclusionsThe Hispanic group and low-income group had the largest percentage increase in telehealth utilization in response to the COVID-19 pandemic. The use of virtual care potentially mitigated the impact of the pandemic on health care utilization in these vulnerable populations.

Dataset Information

Obesity and Mortality Among Patients Diagnosed With COVID-19: Results From an Integrated Health Care Organization.

Background

Objective

Design

Setting

Patients

Measurements

Results

Limitation

Conclusion

Primary funding source

Publications

Obesity and Mortality Among Patients Diagnosed With COVID-19: Results From an Integrated Health Care Organization.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets