Association between body-mass index, patient characteristics, and obesity-related comorbidities among COVID-19 patients: A prospective cohort study.

OBJECTIVE: Obesity is a major risk factor for adverse outcomes after COVID-19 infection. However, it is unknown if the worse outcomes are due to the confounding effect of demographic and obesity-related comorbidities. The study objective is to analyze associations between body mass index, patient characteristics, obesity-related comorbidity, and clinical outcomes in COVID-19 patients. METHODS: In this prospective cohort study, we chose patient records between March 1st, 2020, and December 1st, 2022, in a large tertiary care center in southeast Wisconsin in the United States. Patients over the age of 18 who tested positive were included in the study. Clinical outcomes included hospitalization, intensive care unit (ICU) admission, mechanical ventilation, and mortality rates. We examined the characteristics of patients who had positive clinical outcomes. We created unadjusted logistic regression models, sequentially adjusting for demographic and comorbidity variables, to assess the independent associations between BMI, patient characteristics, obesity-related comorbidities, and clinical outcomes. RESULTS: From a record of 1.67 million inpatients and outpatients at Froedtert Health Center, 55,299 (BMI: 30.5 ± 7.4 kg/m2, 62.5 % female) tested COVID-19 positive during the study period. 17,580 (31.8 %) patients were admitted to hospitals, and of hospitalized patients required ICU admission. 1038 (36.3 %) required mechanical ventilation, and 462 (44.5 %) died after a positive test for COVID-19. We found female patients show a higher hospitalization rate, while male patients have a higher rate of ICU admission, mechanical ventilation, and mortality. Obesity-related comorbidities are associated with worse outcomes compared to simple obesity without comorbidities. In logistic regression models, we found four similar V-shaped associations between BMI and four clinical outcomes. Patients with a BMI of 25 kg/m2 are at the lowest risk for clinical outcomes. Patients with a BMI lower than 18 kg/m2 or higher than 30 kg/m2 are associated with a higher risk of hospitalization, ICU, mechanical ventilation, and death. After adjusting the model for demographic factors and hypertension and diabetes as two common comorbidities, we found that demographic factors do not significantly increase the risk. Obesity alone does not significantly increase the risk of severe clinical outcomes. Obesity-related comorbidities, on the other hand, resulted in a significantly higher risk of outcomes. CONCLUSION: Obesity alone does not increase the risk of worse clinical outcomes after COVID-19 infection. It may suggest that the worse clinical outcomes of patients with obesity are mediated via hypertension and type 2 diabetes. Patients with obesity and comorbidities have a higher risk of poor outcomes. Obesity-related comorbidities, including hypertension and diabetes, are independently associated with poorer clinical outcomes among COVID-19 patients. At a BMI of more than 30 kg/m2 or less than 18 kg/m2, we found an increase in the risk of severe COVID-19 outcomes leading to hospitalization, ICU, mechanical ventilation, and death. The increased risk of severe outcomes is not attributed to patient characteristics but can be attributed to hypertension and diabetes.

Telemedicine and Health Disparities: Association between Patient Characteristics and Telemedicine, In-person, Telephone and message-based Care During the COVID-19 Pandemic.

Telemedicine has been an essential form of care since the onset of the COVID-19 pandemic. However, telemedicine may exacerbate disparities for populations with limited digital literacy or access, such as older adults, racial minorities, patients of low income, rural residences, or limited English proficiency. From March 2020 to March 2022, this retrospective cohort study analyzed the use of in-person, phone/message, and telemedical care at a single tertiary care center in a oncology department. We investigated the association between economic, racial, ethnic, socioeconomic factors and forms of care, including in-person visit, telemedicine-based visit, and telephone/message. Study result shows that telemedicine utilization is lower among patients 65 and older, female patients, American Indian or Alaska Native patients, uninsured patients, and patients who require interpreters during clinical visits. As a result, it is unlikely that telemedicine will provide equal access to clinical care for all populations. On the other hand, In-person care utilization, remains low in low-income and rural-living patients compared to the general population, while telephone and message use remains high in low-income and rural-living patients. We conclude that telemedical care is currently unable to close the utilization gap for populations of low socioeconomic status. Patients with low socioeconomic status use in-person care less frequently. For the disadvantaged, unusually high telephone or message utilization is unlikely to provide the same quality as in-person or telemedical care. Understanding the causes of disparity and promoting a solution to improve equal access to care for all patients is critical.

Effects of Home Office Order on Ambient Particulate Matters Assessed by Interrupted-Time-Series Analysis: Evidence from Shanghai, China

Coronavirus Disease 2019 (COVID-19) has caused a pandemic globally since its outbreak in 2019. As an important port city with prosperous foreign trade, Shanghai has been under severe pressure to prevent the input of COVID-19. With this in mind, solid policies and measures have always been taken in Shanghai to control the input of COVID-19 strictly. In March 2022, the SARS-CoV-2 Omicron variant swept Shanghai, and then the home office order was rapidly carried out in most of the districts. This article focuses on quantifying the changes in concentrations of PM10 and PM2.5 in Shanghai after implementing the home office order and exploring the spatial-distribution characteristics and time trend of the impact of the home office order on airborne particulate matters (PMs) through an interrupted-time-series (ITS) analysis. This study found that PM10 and PM2.5 decreased by 31.40 μg/m3 (p = 0.028) and 10.33 μg/m3 (p = 0.276), respectively, with the fastest decrease speed in the first 10 days of the home office order. Meanwhile, the changes in PM concentrations in eastern areas such as Fengxian District and Chongming District are less than those in central and western areas of Shanghai. Therefore, it can be concluded that implementing the home office order for 10 days could effectively cut down PM concentrations, and the reduction values can be affected by spatial difference and time factor.

The occurrence of COVID-19 is associated with air quality and relative humidity.

The association between meteorological factors and COVID-19 is important for the prevention and control of COVID-19. However, similar studies are relatively rare in China. This study aims to investigate the association between COVID-19 and meteorological factors, such as average temperature, relative humidity, and air quality index (AQI), and average wind speed. We collected the daily confirmed cases of COVID-19 and meteorological factors in Shanghai China from January 10, 2020 to March 31, 2020. A generalized additive model was fitted to quantify the associations between meteorological factors and COVID-19 during the study period. A negative association between average temperature and daily confirmed cases of COVID-19 was found on lag 13 days. In addition, we observed a significant positive correlation between meteorological factors (AQI, relative humidity) and daily confirmed cases of COVID-19. A 10 increase in AQI (lag1/7/8/9/10 days) was correlated with a 4.2%-9.0% increase in the daily confirmed cases of COVID-19. A 1% increase in relative humidity (lag1/4/7/8/9/10 days) was correlated with 1.7%-3.7% increase in the daily confirmed cases of COVID-19. However, the associations between average wind speed and the daily confirmed cases of COVID-19 is complex in different lag days. In summary, meteorological factors could affect the occurrence of COVID-19. Reducing the effects of meteorological factors on COVID-19 may be an important public health action for the prevention and control of COVID-19.

Telemedicine Adoption during the COVID-19 Pandemic: Gaps and Inequalities.

BACKGROUND: The telemedicine industry has been experiencing fast growth in recent years. The outbreak of coronavirus disease 2019 (COVID-19) further accelerated the deployment and utilization of telemedicine services. An analysis of the socioeconomic characteristics of telemedicine users to understand potential socioeconomic gaps and disparities is critical for improving the adoption of telemedicine services among patients. OBJECTIVES: This study aims to measure the correlation of socioeconomic determinants with the use of telemedicine services in Milwaukee metropolitan area. METHODS: Electronic health record review of patients using telemedicine services compared with those not using telemedicine services within an academic-community health system: patient demographics (e.g., age, gender, race, and ethnicity), insurance status, and socioeconomic determinants obtained through block-level census data in Milwaukee area. The telemedicine users were compared with all other patients using regression analysis. The telemedicine adoption rates were calculated across regional ZIP codes to analyze the geographic patterns of telemedicine adoption. RESULTS: A total of 104,139 patients used telemedicine services during the study period. Patients who used video visits were younger (median age 48.12), more likely to be White (odds ratio [OR] 1.34; 95% confidence interval [CI], 1.31-1.37), and have private insurance (OR 1.43; CI, 1.41-1.46); patients who used telephone visits were older (median age 57.58), more likely to be Black (OR 1.31; CI 1.28-1.35), and have public insurance (OR 1.30; CI 1.27-1.32). In general, Latino and Asian populations were less likely to use telemedicine; women used more telemedicine services in general than men. In the multiple regression analysis of social determinant factors across 126 ZIP codes, college education (coefficient 1.41, p = 0.01) had a strong correlation to video telemedicine adoption rate. CONCLUSION: Adoption of telemedicine services was significantly impacted by the social determinant factors of health, such as income, education level, race, and insurance type. The study reveals the potential inequities and disparities in telemedicine adoption.

Interferon-α-2b aerosol inhalation is associated with improved clinical outcomes in patients with coronavirus disease-2019.

AIMS: Type 1 interferon (IFN) is used to treat patients with coronavirus disease-2019 (COVID-19) but robust supporting evidence is lacking. We investigated the association between IFN-α-2b and the clinical outcomes of patients with COVID-19. METHODS: A total of 1401 patients were enrolled, with 852 (60.8%) patients receiving 5 000 000 U of IFN-α-2b via aerosol inhalation twice daily. The primary outcome was a composite measure consisting of mechanical ventilation, intensive care unit (ICU) admission and death. A subgroup analysis was performed to investigate the impact of the IFN-α-2b initiation schedule on symptom onset. RESULTS: The risk probability for crude endpoints was lower in the IFN-α-2b group (3.8%) than in the non-IFN-α-2b group (9.3%, P < .001). After adjusting the confounding factors, IFN-α-2b therapy achieved a reduction of 64% in occurrence of endpoint events (hazard ratio, 0.36; 95% confidence interval [CI], 0.21-0.62). In the subgroup analysis, compared with patients who received IFN-α-2b treatment 0-2 days after symptom onset, the hazard ratio for endpoints was 2.2 (95% CI, 0.43-11.13) in patients who received the therapy 3-5 days after symptom onset, 5.89 (95% CI, 0.99-35.05) in patients who received the therapy 6-8 days after symptom onset, and remained at a high level thereafter. CONCLUSIONS: IFN-α-2b aerosol inhalation therapy may be associated with improved clinical outcomes in patients with COVID-19, and delayed IFN-α-2b intervention was associated with increased probabilities of risk events. Further randomized clinical trials are needed to validate the preliminary findings of this study.