Estimating Older Adult Mortality From COVID-19.

OBJECTIVES: The purpose of this study was to employ simulations to model the probability of mortality from COVID-19 (i.e., coronavirus) for older adults in the United States given at best and at worst cases. METHODS: This study first examined current epidemiological reports to better understand the risk of mortality from COVID-19. Past epidemiological studies from severe acute respiratory syndrome were also examined given similar virology. Next, at best and at worst mortality cases were considered with the goal of estimating the probability of mortality. To accomplish this for the general population, microdata from the National Health Interview Survey pooled sample (2016, 2017, and 2018 public-use NHIS with a sample of 34,881 adults at least 60 years of age) were utilized. Primary measures included age and health status (diabetes, body mass index, and hypertension). A logit regression with 100,000 simulations was employed to derive the estimates and probabilities. RESULTS: Age exhibited a positive association for the probability of death with an odds ratio (OR) of 1.22 (p < .05, 95% confidence interval [CI]: 1.05-1.42). A positive association was also found for body mass index (BMI) (OR 1.03, p < .01, 95% CI: 1.02-1.04) and hypertension (OR 1.36, p < .01, 95% CI: 1.09-1.66) for the at best case. Diabetes was significant but only for the at best case. DISCUSSION: This study found mortality increased with age and was notable for the 74-79 age group for the at best case and the 70-79 age group of the at worst case. Obesity was also important and suggested a higher risk for mortality. Hypertension also exhibited greater risk but the increase was minimal. Given the volume of information and misinformation, these findings can be applied by health professionals, gerontologists, social workers, and local policymakers to better inform older adults about mortality risks and, in the process, reestablish public trust.

Older Adult Mortality From COVID-19: Food Access as a Determinant Within a Socio-ecological Framework.

BACKGROUND AND OBJECTIVES: Low access to food can have an adverse impact on health yet there is limited research on how it is related to coronavirus disease 2019 (COVID-19). The objective of this study was to (a) better understand how inadequate food access was associated with older adult mortality from COVID-19 and (b) determine the spatial distribution of mortality from low food access utilizing a socio-ecological framework. RESEARCH DESIGN AND METHODS: This study area was the larger Midwest, a region of the United States, which included the following states: Minnesota, Wisconsin, Iowa, Illinois, Indiana, Michigan, Ohio, and Pennsylvania. Data were aggregated from multiple sources at the county-level. Because the spatial data used in this study violated several assumptions of the global regression framework, geographically weighted regression (GWR) was employed. RESULTS: Results from GWR revealed low access to food was positively associated with mortality from COVID-19 for older adults but the association varied in (a) magnitude and (b) significance across the larger Midwest. More specifically, the socio-ecological framework suggested low access to food, female-headed households, and percentage Hispanic played a meaningful role in explaining older adult mortality for the western region of the larger Midwest. This was not as evident for the eastern portion. DISCUSSION AND IMPLICATIONS: Such a finding calls attention to the importance of capturing the local context when devising policies to reduce mortality for older adults from COVID-19. Regional policymakers can collaborate with public health professionals when applying these results to formulate local action plans that recognize variations across geographic space.

Estimating older adult mortality from COVID-19

OBJECTIVE: The purpose of this study was to employ simulations to model the probability of mortality from COVID-19 (i.e., coronavirus) for older adults in the United States (U.S.) given at best and at worst cases. METHODS: This study first examined current epidemiological reports to better understand the risk of mortality from COVID-19. Past epidemiological studies from severe acute respiratory syndrome or SARS were also examined given similar virology. Next, at best and at worst mortality cases were considered with the goal of estimating the probability of mortality. To accomplish this for the general population, microdata from the National Health Interview Survey pooled sample (2016, 2017, and 2018 IPUMS NHIS with a sample of 34,881 adults at least 60 years of age) were utilized. Primary measures included age and health status (diabetes, body mass index, and hypertension). A logit regression with 100,000 simulations was employed to derive the estimates and probabilities. RESULTS: Age exhibited a positive association for the probability of death with an odds ratio (OR) of 1.22 (p<0.05, 1.05-1.42, 95% C.I.). A positive association was also found for obesity (OR 1.03, p<0.01, 1.02-1.04 95% C.I.) and hypertension (OR 1.36, p<0.01, 1.09-1.66 95% C.I.) for the at best case. Diabetes was significant but only for the at best case. DISCUSSION: This study found mortality increased with age and was notable for the 74-79 age group for the at best case and the 70-79 age group of the at worst case. Obesity was also important and suggested a higher risk for mortality. Hypertension also exhibited greater risk but the increase was minimal. Given the volume of information and misinformation, these findings can be applied by health professionals, gerontologists, social workers, and local policymakers to better inform older adults about mortality risks and, in the process, re-establish public trust.