Objectives. To estimate excess all-cause mortality in Philadelphia, Pennsylvania, during the COVID-19 pandemic and understand the distribution of excess mortality in the population. Methods. With a Poisson model trained on recent historical data from the Pennsylvania vital registration system, we estimated expected weekly mortality in 2020. We compared these estimates with observed mortality to estimate excess mortality. We further examined the distribution of excess mortality by age, sex, and race/ethnicity. Results. There were an estimated 3550 excess deaths between March 22, 2020, and January 2, 2021, a 32% increase above expectations. Only 77% of excess deaths (n=2725) were attributed to COVID-19 on the death certificate. Excess mortality was disproportionately high among older adults and people of color. Sex differences varied by race/ethnicity. Conclusions. Excess deaths during the pandemic were not fully explained by COVID-19 mortality; official counts significantly undercount the true death toll. Far from being a great equalizer, the COVID-19 pandemic has exacerbated preexisting disparities in mortality by race/ethnicity. Public Health Implications. Mortality data must be disaggregated by age, sex, and race/ethnicity to accurately understand disparities among groups. (Am J Public Health. Published online ahead of print June 10, 2021: e1–e6. https://doi.org/10.2105/AJPH.2021.306285 )
Religious affiliation at the time of death is changing globally, with distinct regional patterns. This could affect spatial variation in healthcare and social customs relating to death and dying.
Objectives. To estimate excess mortality from non–COVID-19 causes during the COVID-19 pandemic in Philadelphia, Pennsylvania, and understand disparities by race/ethnicity, age, and sex. Methods. We used Poisson regression models of weekly deaths using data from Pennsylvania’s vital registration system (2018–2021). Results. There was significant excess mortality as a result of heart disease, homicide, diabetes, drug overdoses, traffic crashes, and falls in 2020–2021; the burden of this excess non–COVID-19 mortality fell on non-Hispanic Black Philadelphians. Among younger non-Hispanic Black men, homicide and drug overdoses were responsible for 54% and 18% of excess deaths—more than COVID-19 (17%). For younger non-Hispanic Black women, drug overdoses accounted for 51% of excess deaths, whereas COVID-19 accounted for 40%. Conclusions. Excess mortality was not solely caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; the causative agent of COVID-19), particularly at younger ages. Indirect pandemic mortality exacerbated prepandemic disparities by race/ethnicity. Public Health Implications. Excess mortality as a result of non–COVID-19 causes may reflect indirect pandemic mortality. National cause-of-death data lag behind local cause-of-death data; local data should be examined as an early indication of trends and disparities. Public health practitioners must center health equity in pandemic response and planning. (Am J Public Health. 2022;112(12):1800–1803. https://doi.org/10.2105/AJPH.2022.307096 )
Falls among older adults cause acute injury, are associated with subsequent mortality, and cost billions of dollars in medical expenses each year. However, research on falls is lacking compared to other causes of morbidity. In our rapidly aging world, a better understanding of the populations at greatest risk is urgently needed. In this paper, we used 2018 data on every inpatient hospitalization in Philadelphia and from the American Community Survey to estimate the prevalence of serious falls among older adults (60+) by age, sex, and race/ethnicity. We further assessed the relationship between age, sex, and race/ethnicity and fall outcomes (length of hospital stay (LOS), total medical charges) with linear regression models. In 2018, the rate of falls serious enough to warrant a hospital stay in Philadelphians aged 60+ was 243 per 10,000. This rate increased dramatically with age, from 116 per 10,000 (60-64) to 649 per 10,000 (85+). Men were at higher risk than women for each 5-year age group except those top-coded at 85+. Compared to white older adults, black older adults had greater risk at younger ages (60-69) and lower risk at older ages (70+). In linear models we found that charges and LOS decreased with increasing age. Both charges and LOS were higher for men than women. Hispanic patients had significantly higher charges than non-Hispanic patients, despite having similar lengths of stay. Future work will attempt to explain differences in charges and LOS by examining mortality, discharge location (e.g., home, hospice, rehab), and co-morbidities.
Aims: This study aimed to estimate the size of the risk group for severe influenza and to describe the social patterning of the influenza risk group in Norway, defined as everyone ⩾65 years of age and individuals of any age with certain chronic conditions (medical risk group). Methods: Study data came from a nationally representative survey among 10,923 individuals aged 16–79 years. The medical risk group was defined as individuals reporting one or more relevant chronic conditions. The associations between educational attainment, employment status, age and risk of belonging to the medical risk group were studied with logistic regression. Results: Nearly a fifth (19.0%) of respondents reported at least one chronic condition, while 29.4% belonged to the influenza risk group due to either age or chronic conditions. Being older, having a low educational level (comparing compulsory education to higher education, odds ratio (OR)=1.4, 95% confidence interval (CI) 1.2–1.8 among women, and OR=1.3, 95% CI 1.1–1.7 among men) and a weaker connection to working life (comparing disability pension to working full-time, OR=6.8, 95% CI 5.3–8.7 among women, and OR=6.5, 95% CI 4.9–8.5 among men) was associated with a higher risk of belonging to the medical risk group for severe influenza. Conclusions: This study indicates that the prevalence of medical risk factors for severe influenza is disproportionally distributed across the socio-economic spectrum in Norway. These results should influence both public funding decisions regarding influenza vaccination and communication strategies towards the public and health professionals.
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