Differences Between Reported COVID-19 Deaths and Estimated Excess Deaths in Counties Across the United States, March 2020 to February 2022.

Accurate and timely tracking of COVID-19 deaths is essential to a well-functioning public health surveillance system. The extent to which official COVID-19 death tallies have captured the true toll of the pandemic in the United States is unknown. In the current study, we develop a Bayesian hierarchical model to estimate monthly excess mortality in each county over the first two years of the pandemic and compare these estimates to the number of deaths officially attributed to Covid-19 on death certificates. Overall, we estimated that 268,176 excess deaths were not reported as Covid-19 deaths during the first two years of the Covid-19 pandemic, which represented 23.7% of all excess deaths that occurred. Differences between excess deaths and reported COVID-19 deaths were substantial in both the first and second year of the pandemic. Excess deaths were less likely to be reported as COVID-19 deaths in the Mountain division, in the South, and in nonmetro counties. The number of excess deaths exceeded COVID-19 deaths in all Census divisions except for the New England and Middle Atlantic divisions where there were more COVID-19 deaths than excess deaths in large metro areas and medium or small metro areas. Increases in excess deaths not assigned to COVID-19 followed similar patterns over time to increases in reported COVID-19 deaths and typically preceded or occurred concurrently with increases in reported COVID-19 deaths. Estimates from this study can be used to inform targeting of resources to areas in which the true toll of the COVID-19 pandemic has been underestimated.

Monthly excess mortality across counties in the United States during the Covid-19 pandemic, March 2020 to February 2022.

Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the overall impact of the Covid-19 pandemic that is not biased by differences in testing or cause-of-death assignment. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating and mitigating factors, and inform response efforts, including allocating resources to affected communities. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,159,580 excess deaths occurred during the first two years of the pandemic (first: 620,872; second: 538,708). Overall, excess mortality decreased in large metropolitan counties, but increased in nonmetro counties, between the first and second years of the pandemic. Despite the initial concentration of mortality in large metropolitan Northeast counties, beginning in February 2021, nonmetro South counties had the highest cumulative relative excess mortality. These results highlight the need for investments in rural health as the pandemic's disproportionate impact on rural areas continues to grow.

Extended maternal age at birth of last child and women's longevity in the Long Life Family Study.

OBJECTIVE: This study investigated the association between maternal age at birth of last child and likelihood of survival to advanced age. METHODS: This was a nested case-control study using Long Life Family Study data. Three hundred eleven women who survived past the oldest 5th percentile of survival (according to birth cohort-matched life tables) were identified as cases, and 151 women who died at ages younger than the top 5th percentile of survival were identified as controls. A Bayesian mixed-effect logistic regression model was used to estimate the association between maternal age at birth of last child and exceptional longevity among these 462 women. RESULTS: We found a significant association for older maternal age, whereby women who had their last child beyond age 33 years had twice the odds for survival to the top 5th percentile of survival for their birth cohorts compared with women who had their last child by age 29 years (age between 33 and 37 y: odds ratio, 2.08; 95% CI, 1.13 to 3.92; older age: odds ratio, 1.92; 95% CI, 1.03 to 3.68). CONCLUSIONS: This study supports findings from other studies demonstrating a positive association between older maternal age and greater odds for surviving to an unusually old age.

Weight histories and mortality among finnish adults: the role of duration and peak body mass index.

BACKGROUND: Many studies use information on weight histories to examine the association between body weight and mortality. A recent paper in Epidemiology (2013;25:707-710) developed a typology of the most common weight-history specifications. METHODS: We use data from a sample of Finnish adults to explore the associations of body weight and mortality, using existing specifications and also peak body mass index (BMI), a new specification. RESULTS: We confirm earlier findings that longer time in a high BMI state is predictive of mortality. Peak BMI (the highest BMI attained in life or available in the data) is also positively associated with mortality. CONCLUSIONS: The specifications of duration in a high BMI state and peak BMI are both valuable for understanding the relationship between lifetime weight dynamics and mortality. The collection of information on peak body weight may be useful when collection of more detailed weight histories is not feasible.

Do early-life conditions predict functional health status in adulthood? The case of Mexico.

Relatively few researchers have investigated early antecedents of adult functional limitations in developing countries. In this study, we assessed associations between childhood conditions and adult lower-body functional limitations (LBFL) as well as the potential mediating role of adult socioeconomic status, smoking, body mass index, and chronic diseases or symptoms. Based on data from the Mexican Health and Aging Study (MHAS) of individuals born prior to 1951 and contacted in 2001 and 2003, we found that childhood nutritional deprivation, serious health problems, and family background predict adult LBFL in Mexico. Adjustment for the potential mediators in adulthood attenuates these associations only to a modest degree.

The Impact of Salmon Bias on the Hispanic Mortality Advantage: New Evidence from Social Security Data.

A great deal of research has focused on factors that may contribute to the Hispanic mortality paradox in the United States. In this paper, we examine the role of the salmon bias hypothesis - the selective return of less-healthy Hispanics to their country of birth - on mortality at ages 65 and above. These analyses are based on data drawn from the Master Beneficiary Record and NUMIDENT data files of the Social Security Administration. These data provide the first direct evidence regarding the effect of salmon bias on the Hispanic mortality advantage. Although we confirm the existence of salmon bias, it is of too small a magnitude to be a primary explanation for the lower mortality of Hispanic than NH white primary social security beneficiaries. Longitudinal surveys that follow individuals in and out of the United States are needed to further explore the role of migration in the health and mortality of foreign-born US residents and factors that contribute to the Hispanic mortality paradox.