Changes In Age-specific Mortality Research Articles

COVID-19 and All-Cause Mortality by Race, Ethnicity, and Age Across Five Periods of the Pandemic in the United States

Racial/ethnic and age disparities in COVID-19 and all-cause mortality during 2020 are well documented, but less is known about their evolution over time. We examine changes in age-specific mortality across five pandemic periods in the United States from March 2020 to December 2022 among four racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Asian) for ages 35+. We fit Gompertz models to all-cause and COVID-19 death rates by 5-year age groups and construct age-specific racial/ethnic mortality ratios across an Initial peak (Mar–Aug 2020), Winter peak (Nov 2020–Feb 2021), Delta peak (Aug–Oct 2021), Omicron peak (Nov 2021–Feb 2022), and Endemic period (Mar–Dec 2022). We then compare to all-cause patterns observed in 2019. The steep age gradients in COVID-19 mortality in the Initial and Winter peak shifted during the Delta peak, with substantial increases in mortality at working ages, before gradually returning to an older age pattern in the subsequent periods. We find a disproportionate COVID-19 mortality burden on racial and ethnic minority populations early in the pandemic, which led to an increase in all-cause mortality disparities and a temporary elimination of the Hispanic mortality advantage at certain age groups. Mortality disparities narrowed over time, with racial/ethnic all-cause inequalities during the Endemic period generally returning to pre-pandemic levels. Black and Hispanic populations, however, faced a younger age gradient in all-cause mortality in the Endemic period relative to 2019, with younger Hispanic and Black adults in a slightly disadvantageous position and older Black adults in a slightly advantageous position, relative to before the pandemic.

A Study of Influences of Mortality Change on the Life Expectancy at Birth in Korea and Japan, 2000-2019

Objectives: To determine the contribution of specific age groups and causes of death contributing to the changes in the Korea-Japan life expectancy gap from 2000-2019.Methods: Standard life table techniques were used decompose the change in the Korea-Japan life expectancy gap by combing absolute changes in age-specific mortality with relative changes in the distribution of causes of death.Results: Among males, the Korea-Japan life expectancy gap increased 4.2 years in the period 2000-2019. The decline in the life expectancy gap was lager among males, declining by 21.53% (5.289 to 1.139). Nearly all of the 2.07-year decline among males was due to relative mortality improvement among korea at ages 65 to 74 years. primarily due to increased mortality from malignant neoplasms. The gap among females increased by 3.8 years in the period 2000-2019, primarily due to increased mortality from cerebrobascular disease. The decline in the life expectancy gap was larger among males at older ages.Conclusions: The Korea-Japan life expectancy gap has declined because of relative mortality improvements in malignant neoplasms and cerebrobascular diseases. Further narrowing of the gap will require concerted efforts in public health and health care to address the major causes of th remaining gap from malignant neoplasms, cerebrobascular diseases, hypertension diseases.

Time Trends in Stroke and Subtypes Mortality Attributable to Household Air Pollution in Chinese and Indian Adults: An Age-Period-Cohort Analysis Using the Global Burden of Disease Study 2019.

Household air pollution (HAP) exposure is recognized as a major health concern in areas relied on residential burning of solid fuels for cooking and heating. However, previous study has focused on mortality across time and reported changes in age-specific mortality globally but failed to distinguish cohort from period effects. Therefore, this study aimed to differentiate the relative contributions of period and cohort effects to overall time trends of HAP-attributable stroke mortality between the most presentative East and South Asia countries. Data were obtained from the Global Burden of Disease (GBD) database. The age, period, and cohort effects were estimated using the age-period-cohort (APC) model. The overall age-standardized mortality rates (ASMRs) of stroke in China decreased by 39.8% compared with 35.8% in India, while stroke subtypes in both the sexes and countries showed consecutive significant declines from 1990 to 2019. The age-specific and cohort-specific HAP-attributable stroke mortality declined over time in China and India. By APC analysis, substantially increasing age effects were presented for stroke and subtypes from 25 to 84 years. China had a rapid reduction in the independent period and cohort effects. Also, the risk of death for subarachnoid hemorrhage (SAH) had the most striking decline for both sexes in period and cohort effects. Reductions of India were less favorable than China, but the independent period and cohort effects progressively decreased during the entire period for both the sexes. Males experienced a slightly higher mortality risk than females in both countries. Although prominent reductions were observed in HAP-attributable stroke and subtypes mortality during the past 30 years, China and India still suffered uneven HAP-attributable stroke burden. Thus, it is of high significance to introduce advanced solid fuels replace technology and knowledge regarding clean fuel use.

Life expectancy loss due to the COVID-19 pandemic exemplified by Moscow

Abstract There is high excess mortality against the background of the pandemic in Moscow (an increase of 36.2% against 18.1% on the national average). According to preliminary data, the loss of life expectancy is 3.1 years for Muscovites (from 78.9 years in 2019 to 76.2 years in 2020) and 1.9 years for the Russian population (from 73.4 to 71.5 years). As in other countries, elderly people suffering from chronic diseases were the most affected. The age-specific mortality rates in 2020 are significantly higher than those of 2019 in the age interval of 45 years and older as well as among children 10-14 years old and young people 25-29 years old. The maximum increase in mortality was recorded in age groups over 80 years old in males and 25-29 years in females. At the same time, infant mortality in Moscow has significantly decreased which is associated with a sharp decrease in the share of births among nonresidents (it exceeded a quarter of all births in the capital in 2019). The reduction in labor migration due to the closure of borders has led to a decrease in births among nonresidents. Using the decomposition method, it was shown that the greatest negative contribution to the loss of life expectancy in both sexes was made by mortality in the age group of 70-74 years which reduced life expectancy by 0.36 years for men and 0.27 years for women. Life expectancy decreased by 0.25 and 0.19 years due to death of men and women aged 75-79 years and by 0.09 and 0.02 years due to death of people aged 25-29 years. Reducing infant mortality yielded a life expectancy gain of 0.15 years for men and 0.11 years for women. These results changed the assessment of the significance of shifts in mortality in age groups. Analysis of changes in age-specific mortality and evaluation of its impact on changes in life expectancy shows different perspectives of the problem, which is important for making adequate decisions in health. Key messages The reduction in labor migration due to the closure of borders has led to a decrease in births among nonresidents. Analysis of changes in age-specific mortality and evaluation of its impact on changes in life expectancy shows different perspectives of the problem.

Assessing the Diversity of the Form of Age-Specific Changes in Adult Mortality from Captive Mammalian Populations

Actuarial senescence (i.e., the age-specific increase in mortality rate) is pervasive across mammalian species, but our current understanding of the diversity of forms that actuarial senescence displays across species remains limited. Although several mathematical models have been proposed to model actuarial senescence, there is still no consensus on which model to use, especially when comparing mortality patterns among species. To fill this knowledge gap, we fitted and compared different forms of increase using models commonly used in senescence studies (i.e., Gompertz, Weibull, and logistic) across 61 species of mammalian captive populations using the Bayesian Survival Trajectory Analysis (BaSTA) approach. For as much as 79% of the species, a Gompertz increase of mortality with age was the most parsimonious model that satisfactorily described the shape of age-specific mortality changes in adults. This highlights that the form of the increase in mortality is mostly consistent across mammalian species and follows the Gompertz rule with some rare exceptions. The implications of that result are twofold. First, the Gompertz rate of mortality increase should be used in cross-species comparative analyses of mammals, as already done in some studies. Second, although the Gompertz model accurately describes actuarial senescence in most mammals, there are notable exceptions, and the factors causing this deviation from an exponential mortality increase during the adult stage warrant further investigation.

The impact of proportional changes in age-specific mortality on life expectancy when the mortality rate is a log-linear function of age

The impact of proportional changes in age-specific mortality on life expectancy when the mortality rate is a log-linear function of age

Grandmotherhood across the demographic transition.

Grandmothers provide key care to their grandchildren in both contemporary and historic human populations. The length of the grandmother-grandchild relationship provides a basis for such interactions, but its variation and determinants have rarely been studied in different contexts, despite changes in age-specific mortality and fertility rates likely having affected grandmotherhood patterns across the demographic transition. Understanding how often and long grandmothers have been available for their grandchildren in different conditions may help explain the large differences between grandmaternal effects found in different societies, and is vital for developing theories concerning the evolution of menopause, post-reproductive longevity, and family living. Using an extensive genealogical dataset from Finland spanning the demographic transition, we quantify the length of grandmotherhood and its determinants from 1790–1959. We found that shared time between grandmothers and grandchildren was consistently low before the demographic transition, only increasing greatly during the 20th century. Whilst reduced childhood mortality and increasing adult longevity had a role in this change, grandmaternal age at birth remained consistent across the study period. Our findings further understanding of the temporal context of grandmother-grandchild relationships, and emphasise the need to consider the demography of grandmotherhood in a number of disciplines, including biology (e.g. evolution of the family), sociology (e.g. changing family structures), population health (e.g. changing age structures), and economics (e.g. workforce retention).

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016

Entropy of the Gompertz-Makeham mortality model

Life table entropy is a quantity frequently used in demography; e.g., as a measure of heterogeneity in age at death, or as the elasticity of life expectancy with regards to proportional changes in age-specific mortality. It is therefore instructive to cal

Divergence in Age Patterns of Mortality Change Drives International Divergence in Lifespan Inequality

In the past six decades, lifespan inequality has varied greatly within and among countries even while life expectancy has continued to increase. How and why does mortality change generate this diversity? We derive a precise link between changes in age-specific mortality and lifespan inequality, measured as the variance of age at death. Key to this relationship is a young-old threshold age, below and above which mortality decline respectively decreases and increases lifespan inequality. First, we show for Sweden that shifts in the threshold's location have modified the correlation between changes in life expectancy and lifespan inequality over the last two centuries. Second, we analyze the post-World War II (WWII) trajectories of lifespan inequality in a set of developed countries-Japan, Canada, and the United States-where thresholds centered on retirement age. Our method reveals how divergence in the age pattern of mortality change drives international divergence in lifespan inequality. Most strikingly, early in the 1980s, mortality increases in young U.S. males led to a continuation of high lifespan inequality in the United States; in Canada, however, the decline of inequality continued. In general, our wider international comparisons show that mortality change varied most at young working ages after WWII, particularly for males. We conclude that if mortality continues to stagnate at young ages yet declines steadily at old ages, increases in lifespan inequality will become a common feature of future demographic change.

Perturbation Analysis of Indices of Lifespan Variability

A number of indices exist to calculate lifespan variation, each with different underlying properties. Here, we present new formulae for the response of seven of these indices to changes in the underlying mortality schedule (life disparity, Gini coefficient, standard deviation, variance, Theil's index, mean logarithmic deviation, and interquartile range). We derive each of these indices from an absorbing Markov chain formulation of the life table, and use matrix calculus to obtain the sensitivity and the elasticity (i.e., the proportional sensitivity) to changes in age-specific mortality. Using empirical French and Russian male data, we compare the underlying sensitivities to mortality change under different mortality regimes to determine the conditions under which the indices might differ in their conclusions about the magnitude of lifespan variation. Finally, we demonstrate how the sensitivities can be used to decompose temporal changes in the indices into contributions of age-specific mortality changes. The result is an easily computable method for calculating the properties of this important class of longevity indices.

Estimating threshold age between early deaths and late deaths for a developing country

The increase in life expectancy, from under 40 years in all areas of the world two centuries ago to over 80 years to-day in many developed countries, has fundamentally improved the human condition. Though life expectancy is a well known measure for longevity of a population, period life expectancy is affected by age-specific mortality in-tensely. Early aged mortality creates disparity in life expectancies, which is very common for many under developed and developing countries. Adequate link exists between changes in age-specific mortality and lifespan inequality, and key to this relationship is a young–old threshold age, below and above which mortality decline respectively de-creases and increases lifespan inequality. Besides socio-economic importance, this threshold’s location modifies the correlation between changes in life expectancy and lifespan inequality. Zhang-Vaupel’s theorem of estimating threshold age is applied to estimate the threshold age for a developing country Bangladesh, using the data of Matlab Health and Demographic Surveillance System. The graphical estimate of threshold age was found to be 70 to 72 years for male and 72 to 75 years for female of Matlab HDSS-2010. These findings imply the imminent longevity for the population of Matlab HDSS. DOI: http://dx.doi.org/10.3329/seajph.v2i2.15947 South East Asia J Public Health | Jul-Dec 2012 | Vol 2 Issue 2 | 48-54

Trends in the black-white life expectancy gap in the United States, 1983-2003.

Since the early 1980s, the black-white gap in life expectancy at birth increased sharply and subsequently declined, but the causes of these changes have not been investigated. To determine the contribution of specific age groups and causes of death contributing to the changes in the black-white life expectancy gap from 1983-2003. US vital statistics data from the US National Vital Statistics System, maintained by the National Center for Health Statistics. Standard life table techniques were used to decompose the change in the black-white life expectancy gap by combining absolute changes in age-specific mortality with relative changes in the distribution of causes of death. The gap in life expectancy at birth between blacks and whites. Among females, the black-white life expectancy gap increased 0.5 years in the period 1983-1993, primarily due to increased mortality from human immunodeficiency virus (HIV) (0.4 years) and slower declines in heart disease (0.1 years), which were somewhat offset by relative improvements in stroke (-0.1 years). The gap among males increased by 2 years in the period 1983-1993, principally because of adverse changes in HIV (1.1 years), homicide (0.5 years), and heart disease (0.3 years). Between 1993 and 2003, the female gap decreased by 1 year (from 5.59 to 4.54 years). Half of the total narrowing of the gap among females was due to relative mortality improvement among blacks in heart disease (-0.2 years), homicide (-0.2 years), and unintentional injuries (-0.1 years). The decline in the life expectancy gap was larger among males, declining by 25% (from 8.44 to 6.33 years). Nearly all of the 2.1-year decline among males was due to relative mortality improvement among blacks at ages 15 to 49 years (-2.0 years). Three causes of death accounted for 71% of the narrowing of the gap among males (homicide [-0.6 years], HIV [-0.6 years], and unintentional injuries [-0.3 years]), and lack of improvement in heart disease at older ages kept the gap from narrowing further. After widening during the late 1980s, the black-white life expectancy gap has declined because of relative mortality improvements in homicide, HIV, unintentional injuries, and, among females, heart disease. Further narrowing of the gap will require concerted efforts in public health and health care to address the major causes of the remaining gap from cardiovascular diseases, homicide, HIV, and infant mortality.

Lifespan extension by dietary restriction in female Drosophila melanogaster is not caused by a reduction in vitellogenesis or ovarian activity

Dietary restriction (DR) extends lifespan in a wide range of organisms. DR also reduces daily and lifetime fecundity. The latter may be an evolutionary adaptation to survive periods of food shortage. Reproductive rate is often negatively correlated with lifespan, and a reduced cost of reproduction could be the mechanism by which DR extends lifespan. We tested this hypothesis in Drosophila melanogaster females, by directly suppressing different aspects of reproduction and measuring the effect on the response of lifespan and age-specific mortality to DR. DR resulted in lifespan extension in females kept with males, in females kept without males, in females with vitellogenesis blocked by the mutant ovo D1 and in females with no germline as a result of X-irradiation. Moreover, rapid (48 h) changes in age-specific mortality, previously seen in fertile females switched between full feeding and DR, were also seen in ovo D1 females. Furthermore, these rapid changes in age-specific mortality in cohorts of fertile wild type females were not accompanied by concurrent changes in egg-production. These results indicate either that reduced reproduction is not necessary for lifespan extension by DR in Drosophila females, or that the relevant aspects of reproduction act upstream of our interventions and were therefore not blocked in our experiments.

Mitigating the tithonus error: genetic analysis of mortality phenotypes.

Summarizing an organism's age at death in terms of the mean or maximum life-span is the most popular way to describe genetic effects on aging. In this Perspective, the author describes a new study with the fly Drosophila melanogaster, in which another type of measure is also used: the age-dependent risk of death, or age-specific mortality. Changes in age-specific mortality reflect the underlying physiological deterioration of an organism as it ages. Thus, the author argues that these changes provide a phenotype that is ideal for the genetic analysis of aging.

Mating opportunity and the evolution of sex-specific mortality rates in a butterfly.

Life history theory predicts that organisms should only invest resources into intrinsic components of life span to the degree that it pays off in terms of reproductive success. Here, we investigate if the temporal distribution of mating opportunities may have influenced the evolution of intrinsic mortality rates in the butterfly Pararge aegeria (Satyrinae). In this species, females mate only once and the frequency of male mating opportunities depends on the temporal emergence pattern of virgin females. As expected, in a population from Madeira where females emerge continuously throughout the year, there was no sex difference in adult life span, while in a Swedish population with synchronised female emergence, males had significantly shorter life spans compared to females. A logistic mortality model provided the best fit to the observed change in age-specific mortality and all categories reached an asymptotic mortality rate of a similar magnitude. However, the Swedish males reached this mortality plateau more rapidly than the other categories. External mortality, due to water and food limitation, affected the pattern of sex-specific mortality but males from Sweden still had higher rates of mortality compared to all other categories. We argue that selection on male longevity is likely to be weaker in Sweden because under synchronised emergence, all females emerge and mate within a short period of time, after which male reproductive value will quickly approach zero. On Madeira, however, male reproductive value decrease more slowly with age since the probability of finding a receptive female is constant over the year.

Why is the death rate from lung cancer falling in the Russian Federation?

Age standardised death rates (European standard population) from lung cancer in the Russian Federation, have been rising since at least 1965, levelled out in the late 1980s and have subsequently decreased. The reasons for this decline are not apparent. This study seeks to identify the reasons for the decline in mortality from lung cancer in the Russian Federation in the 1990s. Changes in age-specific mortality from lung cancer in the Russian Federation between 1990 are described and age-cohort analysis, based on age-specific death rates for lung cancer is undertaken for the period 1965 to 1995. As other work has shown that any recent deterioration in coding of cause of death has been confined largely to the elderly, this suggests that the trend is not a coding artefact. Age-period-cohort analysis demonstrates the existence of a marked birth cohort effect, with two major peaks corresponding to those born around 1926 and 1938. These groups would have reached their early teens during the second world war and the period immediately after the death of Stalin, respectively. The present downward trend in death rates from lung cancer in the Russian Federation is partly due to a cohort effect and it is expected that this will soon reverse, with a second peak occurring in about 2003.

Life table transformations and inequality measures: Some noteworthy formal relationships

The conventional entropy expresses how proportional age-specific mortality changes affect the life expectancy. It may also be interpreted as an inequality measure of ages at death in the stationary population. Other transformations describing other age patterns of mortality change yield alternative generalized entropies. Most are also inequality measures Theils index is the generalized entropy of the exponential accelerated failure time model whereas Brasss logit transformation is associated with the Gini index. Where relative mortality gradients diminish with age Brasss logit transformation more accurately describes mortality change than proportional hazards and the Gini index forms the most appropriate entropy concept. (EXCERPT)

Life Tables in the Measurement of Mortality and Longevity

THE LIFE table, which provides detailed information on survival, has numerous applications. In public health, the life table may be used in assessing the health status, health trends, and health needs of communities. In addition, the life table is a basic tool in demography and is frequently used in estimating, projecting, and analyzing population changes. The data contained in the life table may also be applied in planning services for the population, such as prediction of markets, location of schools, extension of pipelines, and construction of hospitals. By providing statis-tical values of expectation of life and probability of death and survivorship, the life table performs two basic functions. Not only does it summarize the mortality experience of a selected population group during a specific calendar period, but it makes possible the comparison of mortality experiences in two or more population groups. Such comparisons may be of two types: on the one hand, it is possible to compare the mortality experiences of a particular population group during two, or more, calendar periods, for example, U.S. white males in 1900 and 1958; on the other hand, two, or more, different population groups may be contrasted on the basis of their mortality experiences during the same calendar period, for example, U.S. white males and white females in 1958. Two types of life tables-the generation life table and the current life table-should be distinguished. The former provides a longitudinal perspective by following an actual generation of births, or a cohort, from the moment of birth through consecutive ages in successive calendar years. Based on the age-specific mortality rates of the cohort, which are observed during individual calendar years of exposure, the generation life table reflects actual mortality experience of the cohort throughout its lifetime. This article is concerned only with the better known current life table, which is built upon the assumption of a hypothetical cohort, born during a particular calendar period and subject to the age-specific mortality rates observed in an actual population during the same period. Thus, for example, a life table for 1958 assumes a hypothetical cohort born in 1958 to be subject throughout its lifetime to the identical agespecific mortality rates prevailing in the actual population in 1958. No allowances are made for year-to-year changes in age-specific mortality as the hypothetical cohort passes through life. In the life table, except for the purpose of computing mortality rates, the age distribution of the actual population is disregarded. No provision is made for such factors as migration and fertility, which affect age distribution in an actual population. These stipulations are desirable from the point of view of comparing mortality experiences in two or more population groups. Elimination of factors other than mortality keeps to a minimum the number of variables which may limit comparability of mortality experiences.