National Population Growth Rate, Its Components, and Subnational Contributions: A Research Note.

A population's current growth rate is determined jointly by changes in fertility, mortality, and migration. This overall growth rate is also the average of age-specific growth rates, which can be decomposed into the result of historical changes in fertility, mortality, and migration. However, doing so requires more than 100 years of historical data, meaning that such analyses are possible only in a select few populations. In this research note, we propose an adapted version of the variable-r model to measure contributions to the population growth rate for countries with shorter demographic series. In addition, we extend this model to explore the contribution of subnational changes to the national population growth rate. Our results demonstrate that the age-specific growth rates obtained from short historical series, say 25 years, closely match those of the longer series. These abbreviated age-specific growth rates closely resemble the growth rate at birth of their respective cohorts, which is the major determinant of population growth, except at older ages where mortality becomes the main explanatory element. Exploring subnational populations, we find considerable heterogeneity in the age profile of the components of growth and find that the most populous regions tend to have an outsized impact on national-level growth.

Global health inequality: analyses of life disparity and healthy life disparity.

BACKGROUND: Alongside average health measures, namely, life expectancy (LE) and healthy life expectancy (HLE), we sought to investigate the inequality in lifespan and healthy lifespan at the worldwide level with an alternative indicator. METHODS: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, we evaluated the global distribution of life disparity (LD) and healthy life disparity (HLD) for 204 countries and territories in 2019 by sex and socio-demographic index (SDI), and also explored the relationships between average and variation health indicators. RESULTS: Substantial gaps in all observed health indicators were found across SDI quintiles. For instance, in 2019, for low SDI, female LE and HLE were 67.3 years (95% confidence interval 66.8, 67.6) and 57.4 years (56.6, 57.9), and their LD and HLD were 16.7 years (16.5, 17.0) and 14.4 years (14.1, 14.7). For high SDI, female LE and HLE were greater [83.7 years (83.6, 83.7) and 70.2 years (69.3, 70.7)], but their LD and HLD were smaller [10.4 years (10.3, 10.4) and 7.9 years (7.7, 8.0)]. Besides, all estimates varied across populations within each SDI quintile. There were also gaps in LD and HLD between males and females, as those found in LE and HLE. CONCLUSION: In addition to the disadvantaged LE and HLE, greater LD and HLD were also found in low SDI countries and territories. This reveals the serious challenge in achieving global health equality. Targeted policies are thus necessary for improving health performance among these populations.

Decomposition of Differentials in Health Expectancies From Multistate Life Tables: A Research Note.

Multistate modeling is a commonly used method to compute healthy life expectancy. However, there is currently no analytical method to decompose the components of differentials in summary measures calculated from multistate models. In this research note, we propose a derivative-based method to decompose the differentials in population-based health expectancies estimated via a multistate model into two main components: the proportion resulting from differences in initial health structure and the proportion resulting from differences in health transitions. We illustrate the method using data on activities of daily living from the U.S. Health and Retirement Study to decompose the sex differential in disability-free life expectancy (HLE) among older Americans. Our results suggest that the sex gap in HLE results primarily from differences in transition rates between disability states rather than from the initial health distribution of female and male populations. The methods introduced here will enable researchers, including those working in fields other than health, to decompose the relative contribution of initial population structure and transition probabilities to differences in state-specific life expectancies from multistate models.

The contribution of survival to changes in the net reproduction rate.

The net reproduction rate (NRR) is an alternative fertility measure to the more common total fertility rate (TFR) and accounts for the mortality context of the population studied. This study is the first to compare NRR trends in high- and low-income countries and to decompose NRR changes over time into fertility and survival components. The results show that changes in the NRR have been driven mostly by changes in fertility. Yet improvements in survival have also played an important role in explaining changes in the NRR over the last century and represent a substantial component of change in some low-income countries today. Furthermore, the decomposition of the survival component by age indicates that the survival effect on population reproduction is concentrated mostly in infancy, although the HIV/AIDS epidemic altered this age profile in some populations. The findings highlight the importance of mortality's effect on reproduction in specific periods and contexts.

Cross-sectional average length of life by parity: Country comparisons.

This study aims to present an alternative measure of fertility-cross-sectional average length of life by parity (CALP)-which: (1) is a period fertility indicator using all available cohort information; (2) captures the dynamics of parity transitions; and (3) links information on fertility quantum and timing together as part of a single phenomenon. Using data from the Human Fertility Database, we calculate CALP for 12 countries in the Global North. Our results show that women spend the longest time at parity zero on average, and in countries where women spend comparatively longer time at parity zero, they spend fewer years at parities one and two. The analysis is extended by decomposing the differences in CALPs between Sweden and the United States, revealing age- and cohort-specific contributions to population-level differences in parity-specific fertility patterns. The decomposition illustrates how high teenage fertility in the United States dominates the differences between these two countries in the time spent at different parities.

Educational composition effect on the sex gap in life expectancy: A research note based on evidence from Australia.

Life expectancy for females has exceeded that of males globally this century. There is considerable within-country variation in life expectancy related to education. Sex gaps in life expectancy can be decomposed into two components: sex differences in education-specific mortality and sex differences in educational composition. We illustrate this using Australian data for 2016, when the sex gap in life expectancy at age 25 was 3.8 years. The sex gap would be as large as 4.5 years if males and females had the same educational composition; however, it is reduced by 0.7 years, given the lower levels of education among women than men. In a hypothetical scenario accounting for recent increases in females' educational achievement (holding the educational composition at all ages constant at that observed at ages 25-39 for both sexes), we estimate a potential increase in the sex gap (to 4.1 years) in favour of females.

Comparing Cohort Survival in Good Health: A Research Note on Decomposing Sex Differentials in the United States.

We introduce a method for decomposing differences in healthy cross-sectional average length of life (HCAL). HCAL provides an alternative to the health expectancy (HE) indicator by including the health and mortality history of all cohorts present at a given time. While decompositions of HE differences account for contributions made by health and mortality, differences in HCAL are further disentangled into cohort-specific contributions. In this research note we illustrate the technique by analyzing the sex gap in health and mortality for the United States. We use the harmonized version of the Health and Retirement Survey data and define the health status in terms of activities of daily living. Our results suggest that the female advantage in cohort survival is partly compensated by women's lower cohort-specific health levels. At older ages, however, the sex differences in health are not large enough to compensate men's disadvantage in cohort survival.

The Components of Change in Population Growth Rates.

The demographic balance equation relates the population growth rate with crude rates of fertility, mortality, and net migration. All these rates refer to changes occurring between two time points, say, t and t + h. However, this fundamental balance equation overlooks the contribution of historical fertility, mortality, and migration in explaining these population counts. Because of this, the balance equation only partially explains a change in growth rate between time t and t + h as it does not include the contribution of historical population trends in shaping the population at time t. The overall population growth rate can also be expressed as the weighted average of age-specific growth rates. In this article, we develop a method to decompose the historical drivers of current population growth by recursively employing the variable-r method on the population's average age-specific growth rates. We illustrate our method by identifying the unique contributions of survival progress, migration change, and fertility decline for current population growth in Denmark, England and Wales, France, and the United States. Our results show that survival progress is mainly having an effect on population growth at older ages, although accounting for indirect historical effects illuminates additional contributions at younger ages. Migration is particularly important in Denmark and England and Wales. Finally, we find that across all populations studied, historical fertility decline plays the largest role in shaping recent reductions in population growth rates.

The Cross-sectional Average Inequality in Lifespan (CAL†): A Lifespan Variation Measure That Reflects the Mortality Histories of Cohorts.

Lifespan variation is a key metric of mortality that describes both individual uncertainty about the length of life and heterogeneity in population health. We propose a novel and timely lifespan variation measure, which we call the cross-sectional average inequality in lifespan, or CAL†. This new index provides an alternative perspective on the analysis of lifespan inequality by combining the mortality histories of all cohorts present in a cross-sectional approach. We demonstrate how differences in the CAL† measure can be decomposed between populations by age and cohort to explore the compression or expansion of mortality in a cohort perspective. We apply these new methods using data from 10 low-mortality countries or regions from 1879 to 2013. CAL† reveals greater uncertainty in the timing of death than the period life table-based indices of variation indicate. Also, country rankings of lifespan inequality vary considerably between period and cross-sectional measures. These differences raise intriguing questions as to which temporal dimension is the most relevant to individuals when considering the uncertainty in the timing of death in planning their life courses.

Data gaps and opportunities for comparative and conservation biology.

Biodiversity loss is a major challenge. Over the past century, the average rate of vertebrate extinction has been about 100-fold higher than the estimated background rate and population declines continue to increase globally. Birth and death rates determine the pace of population increase or decline, thus driving the expansion or extinction of a species. Design of species conservation policies hence depends on demographic data (e.g., for extinction risk assessments or estimation of harvesting quotas). However, an overview of the accessible data, even for better known taxa, is lacking. Here, we present the Demographic Species Knowledge Index, which classifies the available information for 32,144 (97%) of extant described mammals, birds, reptiles, and amphibians. We show that only 1.3% of the tetrapod species have comprehensive information on birth and death rates. We found no demographic measures, not even crude ones such as maximum life span or typical litter/clutch size, for 65% of threatened tetrapods. More field studies are needed; however, some progress can be made by digitalizing existing knowledge, by imputing data from related species with similar life histories, and by using information from captive populations. We show that data from zoos and aquariums in the Species360 network can significantly improve knowledge for an almost eightfold gain. Assessing the landscape of limited demographic knowledge is essential to prioritize ways to fill data gaps. Such information is urgently needed to implement management strategies to conserve at-risk taxa and to discover new unifying concepts and evolutionary relationships across thousands of tetrapod species.

Cross-Sectional Average Length of Life Childless.

Increases in the average age at first birth and in the proportion of women remaining childless have extended the total number of years that women spend childless during their reproductive lifetime in several countries. To quantify the number of years that reproductive-age women live without children, we introduce the cross-sectional average length of life childless (CALC). This measure includes all the age-specific first-birth information available for the cohorts present at time t; it is a period measure based on cohort data. Using the Human Fertility Database, CALC is calculated for the year 2015 for all countries with long enough histories of fertility available. Results show that women in the majority of the studied countries spend, on average, more than half of their reproductive lives childless. Furthermore, the difference between CALCs in two countries can be decomposed to give a clear visualization of how each cohort contributes to the difference in the duration of the length of childless life in those populations. Our illustration of the decomposition shows that (1) in recent years, female cohorts in Japan and Spain at increasingly younger ages have been contributing to more years of childless life compared with those in Sweden, (2) the United States continues to represent an exception among the high-income countries with a low expectation for childless life of women, and (3) Hungary experienced a strong period effect of the recent Great Recession. These examples show that CALC and its decomposition can provide insights into first-birth patterns.

Educational composition and parity contribution to completed cohort fertility change in low-fertility settings.

Extensive literature has documented the contribution of rising women's education to decreases in completed cohort fertility (CCF). A key question related to the education-fertility relationship is to what extent the decrease in fertility is the result of changes in educational composition vs changes in fertility behaviours within educational categories. This study quantified the effect of educational expansion on fertility levels by decomposing the overall change in CCF into educational composition and education-specific fertility, and explored the changes in parity-specific components of CCF by education for cohorts born between 1940 and 1970. The results show that, despite the decline in CCF being caused mostly by changes in fertility behaviours, educational composition had a considerable impact for some cohorts. The decline in third and higher-order births played a central role in the fall in CCF across educational groups, while the effects of transitions to first and second births varied substantially.

A comprehensive analysis of mortality-related health metrics associated with mental disorders: a nationwide, register-based cohort study.

BACKGROUND: Systematic reviews have consistently shown that individuals with mental disorders have an increased risk of premature mortality. Traditionally, this evidence has been based on relative risks or crude estimates of reduced life expectancy. The aim of this study was to compile a comprehensive analysis of mortality-related health metrics associated with mental disorders, including sex-specific and age-specific mortality rate ratios (MRRs) and life-years lost (LYLs), a measure that takes into account age of onset of the disorder. METHODS: In this population-based cohort study, we included all people younger than 95 years of age who lived in Denmark at some point between Jan 1, 1995, and Dec 31, 2015. Information on mental disorders was obtained from the Danish Psychiatric Central Research Register and the date and cause of death was obtained from the Danish Register of Causes of Death. We classified mental disorders into ten groups and causes of death into 11 groups, which were further categorised into natural causes (deaths from diseases and medical conditions) and external causes (suicide, homicide, and accidents). For each specific mental disorder, we estimated MRRs using Poisson regression models, adjusting for sex, age, and calendar time, and excess LYLs (ie, difference in LYLs between people with a mental disorder and the general population) for all-cause mortality and for each specific cause of death. FINDINGS: 7 369 926 people were included in our analysis. We found that mortality rates were higher for people with a diagnosis of a mental disorder than for the general Danish population (28·70 deaths [95% CI 28·57-28·82] vs 12·95 deaths [12·93-12·98] per 1000 person-years). Additionally, all types of disorders were associated with higher mortality rates, with MRRs ranging from 1·92 (95% CI 1·91-1·94) for mood disorders to 3·91 (3·87-3·94) for substance use disorders. All types of mental disorders were associated with shorter life expectancies, with excess LYLs ranging from 5·42 years (95% CI 5·36-5·48) for organic disorders in females to 14·84 years (14·70-14·99) for substance use disorders in males. When we examined specific causes of death, we found that males with any type of mental disorder lost fewer years due to neoplasm-related deaths compared with the general population, although their cancer mortality rates were higher. INTERPRETATION: Mental disorders are associated with premature mortality. We provide a comprehensive analysis of mortality by different types of disorders, presenting both MRRs and premature mortality based on LYLs, displayed by age, sex, and cause of death. By providing accurate estimates of premature mortality, we reveal previously underappreciated features related to competing risks and specific causes of death. FUNDING: Danish National Research Foundation.

What has contributed to improvements in the child sex ratio in select districts of India? A decomposition of the sex ratio at birth and child mortality.

Despite an overall downward trend in child sex ratios in India, some of the most imbalanced districts in 2001 (fewer girls than boys) showed signs of becoming more balanced in 2011. This analysis looked in depth at these districts to better understand the nature of the improvement in the child sex ratio using two rounds of data from the Census of India from 2001 and 2011. Data were used from the 153 districts that showed improvement in their child sex ratio between 2001 and 2011. The improvement was decomposed into: (1) less sex-selective abortion and (2) improved girl compared with boy mortality. Most of the improvement in child sex ratios were shown to be due to reductions in sex-selective abortion, although this still made up the majority of the cause of imbalanced sex ratios in 2011. Child sex ratio improvement has been happening in both rural and urban areas of India, and there is evidence of stagnation in mortality decline for urban girls.

Latin American convergence and divergence towards the mortality profiles of developed countries.

It is uncertain whether Latin America and Caribbean (LAC) countries are approaching a single mortality regime. Over the last three decades, LAC has experienced major public health interventions and the highest number of homicides in the world. However, these interventions and homicide rates are not evenly shared across countries. This study documents trends in life expectancy and lifespan variability for 20 LAC countries, 2000-14. By extending a previous method, we decompose differences in lifespan variability between LAC and a developed world benchmark into cause-specific effects. For both sexes, dispersion of amenable diseases through the age span makes the largest contribution to the gap between LAC and the benchmark. Additionally, for males, the concentration of homicides, accidents, and suicides in mid-life further impedes mortality convergence. Great disparity exists in the region: while some countries are rapidly approaching the developed regime, others remain far behind and suffer a clear disadvantage in population health.

The Mechanism Underlying Change in the Sex Gap in Life Expectancy at Birth: An Extended Decomposition.

The relationship between differential mortality rates and differences in life expectancy is well understood, but how changing differential rates translate into changing differences in life expectancy has not been fully explained. To elucidate the mechanism involved, this study extends existing decomposition methods. The extended method decomposes change in the sex gap in life expectancy at birth into three components capturing the effects of the sex difference in mortality improvement (ρ-effect), life table deaths density by age (f-effect), and remaining life expectancy by age (e-effect). These three effects oppose and augment each other, depending on relative change in sex-differential mortality rates. The new method is applied to period data for 35 countries and cohort data for 25 countries. The results demonstrate how the mechanism, involving the three effects, operates to determine change in the sex difference in life expectancy. We observe the pivotal importance of the f-effect, which is predominantly negative because of lower female mortality, in favoring narrowing rather than widening of the sex gap, in shifting the overall effect to younger ages, and in exaggerating fluctuations due to crisis mortality. The new decomposition provides a more detailed basis for substantive analyses examining change in differences in life expectancy.

Rise, stagnation, and rise of Danish women's life expectancy.

Health conditions change from year to year, with a general tendency in many countries for improvement. These conditions also change from one birth cohort to another: some generations suffer more adverse events in childhood, smoke more heavily, eat poorer diets, etc., than generations born earlier or later. Because it is difficult to disentangle period effects from cohort effects, demographers, epidemiologists, actuaries, and other population scientists often disagree about cohort effects' relative importance. In particular, some advocate forecasts of life expectancy based on period trends; others favor forecasts that hinge on cohort differences. We use a combination of age decomposition and exchange of survival probabilities between countries to study the remarkable recent history of female life expectancy in Denmark, a saga of rising, stagnating, and now again rising lifespans. The gap between female life expectancy in Denmark vs. Sweden grew to 3.5 y in the period 1975-2000. When we assumed that Danish women born 1915-1945 had the same survival probabilities as Swedish women, the gap remained small and roughly constant. Hence, the lower Danish life expectancy is caused by these cohorts and is not attributable to period effects.

The contribution of urbanization to changes in life expectancy in Scotland, 1861-1910.

During the nineteenth and early twentieth centuries, urban populations in Europe and North America continued to be afflicted by very high mortality as rapid urbanization and industrialization processes got underway. Here we measure the effect of population redistribution from (low-mortality) rural to (high-mortality) urban areas on changes in Scottish life expectancy at birth from 1861 to 1910. Using vital registration data for that period, we apply a new decomposition method that decomposes changes in life expectancy into the contributions of two main components: (1) changes in mortality; and (2) compositional changes in the population. We find that, besides an urban penalty (higher mortality in urban areas), an urbanization penalty (negative effect of population redistribution to urban areas on survival) existed in Scotland during the study period. In the absence of the urbanization penalty, Scottish life expectancy at birth could have attained higher values by the beginning of the twentieth century.

Potential support ratios: Cohort versus period perspectives.

The 'prospective potential support ratio' has been proposed by researchers as a measure that accurately quantifies the burden of ageing, by identifying the fraction of a population that has passed a certain measure of longevity, for example, 17 years of life expectancy. Nevertheless, the prospective potential support ratio usually focuses on the current mortality schedule, or period life expectancy. Instead, in this paper we look at the actual mortality experienced by cohorts in a population, using cohort life tables. We analyse differences between the two perspectives using mortality models, historical data, and forecasted data. Cohort life expectancy takes future mortality improvements into account, unlike period life expectancy, leading to a higher prospective potential support ratio. Our results indicate that using cohort instead of period life expectancy returns around 0.5 extra younger people per older person among the analysed countries. We discuss the policy implications implied by our cohort measures.

Truncated cross-sectional average length of life: A measure for comparing the mortality history of cohorts.

Period life expectancies are commonly used to compare populations, but these correspond to simple juxtapositions of current mortality levels. In order to construct life expectancies for cohorts, a complete historical series of mortality rates is needed, and these are available for only a subset of developed countries. The truncated cross-sectional average length of life (TCAL) is a new measure that captures historical information about all cohorts present at a given moment and is not limited to countries with complete cohort mortality data. The value of TCAL depends on the rates used to complete the cohort series, but differences between TCALs of two populations remain similar irrespective of the data used to complete the cohort series. This result is illustrated by a comparison of TCALs for the US with those for Denmark, Japan, and other high-longevity countries. Specific cohorts that account for most of the disparity in mortality between the populations are identified.