Structural equation model of coping and life satisfaction of community-dwelling older people during the COVID-19 pandemic.

BACKGROUND: COVID-19 put older individuals at high risk for morbidity and mortality, isolation, reduced coping, and lower satisfaction with life. Many older adults experienced social isolation, fear, and anxiety. We hypothesized that successful coping with these stressors would maintain or improve satisfaction with life, a crucial psychological outcome during the pandemic. Our study investigated relationships between older people's coping and life satisfaction during the pandemic and their optimism, sense of mastery, closeness with spouse, family, and friends, and vulnerabilities from frailty, comorbid diseases, memory problems, and dependencies in instrumental activities of daily living (IADL). METHODS: The study was based on a special COVID-19 sample of 1351 community-dwelling older adults who participated in the 2020 Health and Retirement Survey. A comprehensive structural equation modeling was used to test direct and indirect effects, with life satisfaction as the main outcome and coping as a mediator between the other variables and coping. RESULTS: Most survey respondents were female and between the ages of 65-74 years. They averaged 1.7 chronic conditions, one in seven was frail, about one-third rated their memory as fair or poor, and about one in seven reported one or more difficulties in IADL. As hypothesized-older people with increased sense of mastery and optimism were better able to cope and had greater life satisfaction. In addition, close relationships with friends and with other family members besides the spouse/partner or children contributed to more successful coping, while the interpersonal closeness of all types contributed directly to greater life satisfaction. Finally, older people with more IADL limitations reported greater difficulty coping and lower life satisfaction, and those older people who were frail or had multiple comorbid diseases reported lower life satisfaction. CONCLUSIONS: Optimism, sense of mastery and closeness with family/friends promotes coping and life satisfaction, whereas frailty and comorbidities make coping more challenging and lead to lower life satisfaction particularly during a pandemic. Our study improves on prior research because of its nationally representative sample and formal specification and testing of a comprehensive theoretical framework.

The impact of the COVID-19 pandemic on blood pressure control after a stroke or transient ischemic attack among patients at VA medical centers.

OBJECTIVE: To study factors associated with systolic blood pressure(SBP) control for patients post-discharge from an ischemic stroke or transient ischemic attack(TIA) during the early months of the COVID-19 pandemic compared to pre-pandemic periods within the Veterans Health Administration(VHA). MATERIALS AND METHODS: We analyzed retrospective data from patients discharged from Emergency Departments or inpatient admissions after an ischemic stroke or TIA. Cohorts consisted of 2,816 patients during March-September 2020 and 11,900 during the same months in 2017-2019. Outcomes included primary care or neurology clinic visits, recorded blood pressure readings and average blood pressure control in the 90-days post-discharge. Random effect logit models were used to compare clinical characteristics of the cohorts and relationships between patient characteristics and outcomes. RESULTS: The majority (73%) of patients with recorded readings during the COVID-19 period had a mean post-discharge SBP within goal (<140 mmHg); this was slightly lower than the pre-COVID-19 period (78%; p=0.001). Only 38% of the COVID-19 cohort had a recorded SBP in the 90-days post-discharge compared with 83% of patients during the pre-pandemic period (p=0.001). During the pandemic period, 29% did not have follow-up primary care or neurologist visits, and 33% had a phone or video visit without a recorded SBP reading. CONCLUSIONS: Patients with an acute cerebrovascular event during the initial COVID-19 period were less likely to have outpatient visits or blood pressure measurements than during the pre-pandemic period; patients with uncontrolled SBP should be targeted for follow-up hypertension management.

Are Frail Older People from Racial/Ethnic Minorities at Double Jeopardy of Putting off Healthcare during the Pandemic?

Given the differential impacts of COVID-19 on racial and ethnic groups, it is unclear how racial/ethnic status and frailty combine to influence pandemic-related healthcare disruptions. This study aimed to test the double jeopardy hypothesis: racial/ethnic minority older adults suffer a double disadvantage in access to health care during the pandemic due to the interactive effects of frailty and race. This study uses the linked National Health and Aging Trends Study (NHATS) and COVID-19 public use data files. A multivariate logistic regression model was performed. Overall, approximately two out of five (41%) older adults reported postponing care due to the pandemic. The likelihood of putting off care increased slightly by frailty status. We found no significant difference between Whites and non-Whites in putting off care. However, the simple comparison masked significant variation across frailty status. Robust non-White older people were less likely to put off care than robust Whites (robust non-Whites: 29% vs. robust Whites: 39%); in contrast, frail non-White older people were more likely to put off care (frail non-Whites: 55% vs. frail Whites: 42%). Being frail and non-White creates double jeopardy, which has a negative impact on access to healthcare. Timely access to care is essential for frail older people, particularly non-Whites, because of their complex health conditions accentuated by health and social disparities.

International Evidence on the COVID-19 Deaths of People Who Live in Long-Term Care Facilities

The COVID-19 pandemic has had a disproportionate impact, in terms of mortality, on people who live in Long-Term Care Facilities (LTCFs). This study involved compiling data on number of deaths of people who live in LTCFs and analyzing the extent to which differences between countries could be attributed to measures taken to control the spread of COVID-19 to LTCFs or to other factors. The study found that differences in how the data is collected make international comparisons difficult but that there is a clear correlation between number of COVID-19 deaths of residents in LTCFs and number of COVID-19 deaths of people living in the community. The study also found that countries that experienced a particularly high number of deaths in LTCFs during the first COVID-19 wave tended to have lower relative mortality in LTCFs in the subsequent waves, which potentially could be attributed to learning from the initial shock.

A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States.

Considering the potential for widespread adoption of social vulnerability indices (SVI) to prioritize COVID-19 vaccinations, there is a need to carefully assess them, particularly for correspondence with outcomes (such as loss of life) in the context of the COVID-19 pandemic. The University of Illinois at Chicago School of Public Health Public Health GIS team developed a methodology for assessing and deriving vulnerability indices based on the premise that these indices are, in the final analysis, classifiers. Application of this methodology to several Midwestern states with a commonly used SVI indicates that by using only the SVI rankings there is a risk of assigning a high priority to locations with the lowest mortality rates and low priority to locations with the highest mortality rates. Based on the findings, we propose using a two-dimensional approach to rationalize the distribution of vaccinations. This approach has the potential to account for areas with high vulnerability characteristics as well as to incorporate the areas that were hard hit by the pandemic.

Heterogeneity in COVID-19 patient volume, characteristics and outcomes across US Department of Veterans Affairs facilities: an observational cohort study.

OBJECTIVE: Studies describe COVID-19 patient characteristics and outcomes across populations, but reports of variation across healthcare facilities are lacking. The objectives were to examine differences in COVID-19 patient volume and mortality across facilities, and understand whether facility variation in mortality was due primarily to differences in patient versus facility characteristics. DESIGN: Observational cohort study with multilevel mixed effects logistic regression modelling. SETTING: The Veterans Health Administration (VA) is the largest healthcare system in the USA. PARTICIPANTS: Patients with COVID-19. MAIN OUTCOME: All-cause mortality within 45 days after COVID-19 testing (March-May, follow-up through 16 July 2020). RESULTS: Among 13 510 patients with COVID-19, 3942 (29.2%) were admitted (2266/3942 (57.5%) ward; 1676/3942 (42.5%) intensive care unit (ICU)) and 679/3942 (17.2%) received mechanical ventilation. Marked heterogeneity was observed across facilities in median age (range: 34.3-83.9 years; facility mean: 64.7, SD 7.2 years); patient volume (range: 1-737 at 160 facilities; facility median: 48.5, IQR 14-105.5); hospital admissions (range: 1-286 at 133 facilities; facility median: 11, IQR 1-26.5); ICU caseload (range: 1-85 at 115 facilities; facility median: 4, IQR 0-12); and mechanical ventilation (range: 1-53 at 90 facilities; facility median: 1, IQR 0-5). Heterogeneity was also observed in facility mortality for all patients with COVID-19 (range: 0%-29.7%; facility median: 8.9%, IQR 2.4%-13.7%); inpatients (range: 0%-100%; facility median: 18.0%, IQR 5.6%-28.6%); ICU patients (range: 0%-100%; facility median: 28.6%, IQR 14.3%-50.0%); and mechanical ventilator patients (range: 0%-100%; facility median: 52.7%, IQR 33.3%-80.6%). The majority of variation in facility mortality was attributable to differences in patient characteristics (eg, age). CONCLUSIONS: Marked heterogeneity in COVID-19 patient volume, characteristics and mortality were observed across VA facilities nationwide. Differences in patient characteristics accounted for the majority of explained variation in mortality across sites. Variation in unadjusted COVID-19 mortality across facilities or nations should be considered with caution.

Association of Intensive Care Unit Patient Load and Demand With Mortality Rates in US Department of Veterans Affairs Hospitals During the COVID-19 Pandemic.

Importance: Although strain on hospital capacity has been associated with increased mortality in nonpandemic settings, studies are needed to examine the association between coronavirus disease 2019 (COVID-19) critical care capacity and mortality. Objective: To examine whether COVID-19 mortality was associated with COVID-19 intensive care unit (ICU) strain. Design, Setting, and Participants: This cohort study was conducted among veterans with COVID-19, as confirmed by polymerase chain reaction or antigen testing in the laboratory from March through August 2020, cared for at any Department of Veterans Affairs (VA) hospital with 10 or more patients with COVID-19 in the ICU. The follow-up period was through November 2020. Data were analyzed from March to November 2020. Exposures: Receiving treatment for COVID-19 in the ICU during a period of increased COVID-19 ICU load, with load defined as mean number of patients with COVID-19 in the ICU during the patient's hospital stay divided by the number of ICU beds at that facility, or increased COVID-19 ICU demand, with demand defined as mean number of patients with COVID-19 in the ICU during the patient's stay divided by the maximum number of patients with COVID-19 in the ICU. Main Outcomes and Measures: All-cause mortality was recorded through 30 days after discharge from the hospital. Results: Among 8516 patients with COVID-19 admitted to 88 VA hospitals, 8014 (94.1%) were men and mean (SD) age was 67.9 (14.2) years. Mortality varied over time, with 218 of 954 patients (22.9%) dying in March, 399 of 1594 patients (25.0%) dying in April, 143 of 920 patients (15.5%) dying in May, 179 of 1314 patients (13.6%) dying in June, 297 of 2373 patients (12.5%) dying in July, and 174 of 1361 (12.8%) patients dying in August (P < .001). Patients with COVID-19 who were treated in the ICU during periods of increased COVID-19 ICU demand had increased risk of mortality compared with patients treated during periods of low COVID-19 ICU demand (ie, demand of ≤25%); the adjusted hazard ratio for all-cause mortality was 0.99 (95% CI, 0.81-1.22; P = .93) for patients treated when COVID-19 ICU demand was more than 25% to 50%, 1.19 (95% CI, 0.95-1.48; P = .13) when COVID-19 ICU demand was more than 50% to 75%, and 1.94 (95% CI, 1.46-2.59; P < .001) when COVID-19 ICU demand was more than 75% to 100%. No association between COVID-19 ICU demand and mortality was observed for patients with COVID-19 not in the ICU. The association between COVID-19 ICU load and mortality was not consistent over time (ie, early vs late in the pandemic). Conclusions and Relevance: This cohort study found that although facilities augmented ICU capacity during the pandemic, strains on critical care capacity were associated with increased COVID-19 ICU mortality. Tracking COVID-19 ICU demand may be useful to hospital administrators and health officials as they coordinate COVID-19 admissions across hospitals to optimize outcomes for patients with this illness.