Decomposing Current Mortality Differences Into Initial Differences and Differences in Trends: The Contour Decomposition Method

The Urban Bias in Latin American Avoidable Mortality

In 1977, Michael Lipton introduced the Urban Bias Thesis as a framework for understanding how most economic policy initiatives have contributed to the overdevelopment of urban areas and the underdevelopment of rural areas. In Latin America, there has historically been a positive correlation between urbanization and mortality decline, as the region's health transition generally began in the main cities and tended to proceed more rapidly in countries with higher levels of urbanization. This paper seeks evidence of a residual urban bias in the region's mortality patterns. Using a sample of Latin American countries over the 2000-2010 period, I analyse the disparities in mortality patterns and avoidable causes of death by looking closely at urban and rural areas using continuum categories. The results indicate that the urban advantage does persist and that rural-urban mortality differentials have consistently favoured the largest cities. The metropolitan advantage in mortality is an outcome of lower mortality in causes of death that are avoidable through primary interventions. Even in scenarios of high mortality at younger adult ages (15-44), the metropolitan advantage remains, due primarily to unsuccessful efforts to reduce mortality in populations aged 45 years and over outside the main and large cities.

The Lifespan Disparity Dataset: An open repository on inequality and polarization in length of life (1950-2021)

Monitoring health is key for identifying priorities in public health planning and improving healthcare services. Life expectancy has conventionally been regarded as a valuable indicator to compare the health status of different populations. However, this measure is simply the mean of the distribution of the length of life and, as such, neglects individual disparities in health outcomes. In this paper, we use life tables from the UN World Population Prospects to develop the most comprehensive dataset of lifespan inequality and polarization for 258 countries and areas for the period 1950-2021. These extensive series on lifespan distributions provide access to crucial information for researchers, practitioners, and the general public, thus contributing to a better understanding of health differences within and between nations.

Cause-of-Death Determinants of Lifespan Inequality

We propose a novel decomposition approach that breaks down the levels and trends of lifespan inequality as the sum of cause-of-death contributions. The suggested method shows whether the levels and changes in lifespan inequality are attributable to the levels and changes in (1) the extent of inequality in the cause-specific age-at-death distribution (the "Inequality" component), (2) the total share of deaths attributable to each cause (the "Proportion" component), or (3) the cause-specific mean age at death (the "Mean" component). This so-called Inequality-Proportion-Mean (or IPM) method is applied to 10 low-mortality countries in Europe. Our findings suggest that the most prevalent causes of death (in our setting, "circulatory system" and "neoplasms") do not necessarily contribute the most to overall levels of lifespan inequality. In fact, "perinatal and congenital" causes are the strongest drivers of lifespan inequality declines. The contribution of the IPM components to changes in lifespan inequality varies considerably across causes, genders, and countries. Among the three components, the Mean one explains the least lifespan inequality dynamics, suggesting that shifts in cause-specific mean ages at death alone contributed little to changes in lifespan inequality.

Widening rural-urban gap in life expectancy in China since COVID-19

INTRODUCTION

Disparities in life expectancy between rural and urban populations are well established but how it varies with epidemics and pandemics remains poorly understood. We aimed to quantify the rural-urban differences in the mortality burden of COVID-19 and to contribute to understanding the disparity trends in life expectancy between 1987 and 2021 in China.

METHODS

We used monthly death counts from death registration systems. Rural-urban gap estimation and decomposition were carried out using period life tables to calculate life expectancy, the Arriaga decomposition technique to break down into age-specific and cause-specific mortality, and the Lee-Carter forecasts to estimate the expected gap.

RESULTS

The rural-urban gap increased to 22.7 months (95% credible interval (CI) 19.6 to 25.8) in 2020 and further to 23.7 months (95% CI 19.6 to 26.7) in 2021, and was larger than expected under the continuation of the prepandemic trends. Compared with that in the recent 2003 SARS-CoV-2 epidemic and the 2009 influenza epidemic, excess rural-urban gaps in the COVID-19 pandemic changed from urban disadvantage to rural disadvantage, and the contributions shifted toward old age groups and circulatory diseases. Variations in the rural-urban gap since 1987 were positively correlated with the rural-urban disparity in public health expenditures, especially among ages <60 (p values <0.005).

CONCLUSIONS

Our findings identified a widening rural-urban gap in life expectancy since COVID-19, and a shifting trend towards old ages and circulatory diseases, disrupting the diminishing trend of the gap over 35 years. The findings highlight the unequal impact of the pandemic on different communities in terms of mortality burdens.

Contributions of the life expectancy gap reduction between urban and rural areas to the increase in overall life expectancy in South Korea from 2000 to 2019

BACKGROUND

This study aimed to quantify the contribution of narrowing the life expectancy gap between urban and rural areas to the overall life expectancy at birth in Korea and examine the age and death cause-specific contribution to changes in the life expectancy gap between urban and rural areas.

METHODS

We used the registration population and death statistics from Statistics Korea from 2000 to 2019. Assuming two hypothetical scenarios, namely, the same age-specific mortality change rate in urban and rural areas and a 20% faster decline than the observed decline rate in rural areas, we compared the increase in life expectancy with the actual increase. Changes in the life expectancy gap between urban and rural areas were decomposed into age- and cause-specific contributions.

RESULTS

Rural disadvantages of life expectancy were evident. However, life expectancies in rural areas increased more rapidly than in urban areas. Life expectancy would have increased 0.3-0.5 less if the decline rate of age-specific mortality in small-to-middle urban and rural areas were the same as that of large urban areas. Life expectancy would have increased 0.7-0.9 years further if the decline rate of age-specific mortality in small-to-middle urban and rural areas had been 20% higher. The age groups 15-39 and 40-64, and chronic diseases, such as neoplasms and diseases of the digestive system, and external causes significantly contributed to narrowing the life expectancy gap between urban and rural areas.

CONCLUSION

Pro-health equity interventions would be a good strategy to reduce the life expectancy gap and increase overall life expectancy, particularly in societies where life expectancies have already increased.

Why we should monitor disparities in old-age mortality with the modal age at death

Indicators based a fixed “old” age threshold have been widely used for assessing socioeconomic disparities in mortality at older ages. Interpretation of long-term trends and determinants of these indicators is challenging because mortality above a fixed age that in the past would have reflected old age deaths is today mixing premature and old-age mortality. We propose the modal (i.e., most frequent) age at death, M, an indicator increasingly recognized in aging research, but which has been infrequently used for monitoring mortality disparities at older ages. We use mortality and population exposure data by occupational class over the 1971-2017 period from Finnish register data. The modal age and life expectancy indicators are estimated from mortality rates smoothed with penalized B-splines. Over the 1971-2017 period, occupational class disparities in life expectancy at 65 and 75 widened while disparities in M remained relatively stable. The proportion of the group surviving to the modal age was constant across time and occupational class. In contrast, the proportion surviving to age 65 and 75 has roughly doubled since 1971 and showed strong occupational class differences. Increasing socioeconomic disparities in mortality based on fixed old age thresholds may be a feature of changing selection dynamics in a context of overall declining mortality. Unlike life expectancy at a selected fixed old age, M compares individuals with similar survival chances over time and across occupational classes. This property makes trends and differentials in M easier to interpret in countries where old-age survival has improved significantly.

The growing rural-urban divide in US life expectancy: contribution of cardiovascular disease and other major causes of death

BACKGROUND

The US rural disadvantage in life expectancy (LE) relative to urban areas has grown over time. We measured the contribution of cardiovascular disease (CVD), drug-overdose deaths (DODs) and other major causes of death to LE trends in rural and urban counties and the rural-urban LE gap.

METHODS

Counterfactual life tables and cause-of-death decompositions were constructed using data on all US deaths in 1999-2019 (N = 51 998 560) from the Centers for Disease Control and Prevention.

RESULTS

During 1999-2009, rural and urban counties experienced robust LE gains, but urban LE increased by 1.19 years more in women and 0.86 years more in men compared with rural LE. During 2010-2019, rural counties experienced absolute declines in LE (women -0.20, men -0.30 years), whereas urban counties experienced modest increases (women 0.55, men 0.29 years). Counterfactual analysis showed that slowed CVD-mortality declines, particularly in ages 65+ years, were the main reason why rural LE stopped increasing after 2010. However, slow progress in CVD-mortality influenced LE trends more in urban areas. If CVD-mortality had continued to decline at its pre-2010 pace, the rural-urban LE gap would have grown even more post 2010. DODs and other causes of death also contributed to the LE trends and differences in each period, but their impact in comparison to that of CVD was relatively small.

CONCLUSIONS

Rural disadvantage in LE continues to grow, but at a slower pace than pre 2010. This slowdown is more attributable to adverse trends in CVD and DOD mortality in urban areas than improvements in rural areas.

Declining regional disparities in mortality in the context of persisting large inequalities in economic conditions: the case of Germany

BACKGROUND

Subnational regional mortality inequalities are large and appear to be mostly increasing within industrialized countries, although comparative studies across high-income countries are scarce. Germany is an important country to examine because it continues to experience considerable economic disparities between its federal states, in part resulting from its former division.

METHODS

We analyse state-level mortality in Germany utilizing data from a newly constructed regional database based on the methodology of the Human Mortality Database. We compare time trends (1991-2015) in the German state-level standard deviation in life expectancy to that of other large, wealthy countries and examine the association between mortality and economic inequalities at the regional level. Finally, using contour-decomposition methods, we investigate the degree to which age patterns of mortality are converging across German federal states.

RESULTS

Regional inequalities in life expectancy in Germany are comparatively low internationally, particularly among women, despite high state-level inequalities in economic conditions. These low regional mortality inequalities emerged 5-10 years after reunification. Mortality is converging over most ages between the longest- and shortest-living German state populations and across the former East-West political border, with the exception of an emerging East-West divergence in mortality among working-aged men.

CONCLUSIONS

The German example shows that large regional economic inequalities are not necessarily paralleled with large regional mortality disparities. Future research should investigate the factors that fostered the emergence of this unusual pattern in Germany.

Use of Counterfactual Population Projections for Assessing the Demographic Determinants of Population Ageing

Counterfactual population projections have been used to estimate the contributions of fertility and mortality to population ageing, a method recently designated as the gold standard for this purpose. We analyse projections with base years between 1850 and 1950 for 11 European countries with long-run demographic data series to estimate the robustness of this approach. We link this approach with stable population theory to derive quantitative indicators of the role of fertility and mortality; consider ways of incorporating net migration; and examine the effect of using alternative indicators of population ageing. A number of substantive and technical weaknesses in the counterfactual projection approach are identified: (1) the conclusions are very sensitive to the choice of base year. Specifically, the level of base year fertility has a major influence on whether fertility or mortality is considered the main driver of population ageing. (2) The method is not transitive: results for two adjacent intervals are unrelated to results for the combined period. Therefore, overall results cannot be usefully allocated between different sub-intervals. (3) Different ageing indices tend to produce similar qualitative conclusions, but quantitative results may differ markedly. (4) Comparisons of alternative models should be with a fixed fertility and mortality projection model rather than with the baseline values as usually done. (5) The standard counterfactual projections approach concatenates the effects of initial age structure and subsequent fertility and mortality rates: methods to separate these components are derived.

Trends in life expectancy and age-specific mortality in England and Wales, 1970-2016, in comparison with a set of 22 high-income countries: an analysis of vital statistics data

BACKGROUND

Since 2010, the rate of improvement in life expectancy in the UK has slowed. We aimed to put this trend in the context of changes over the long term and in relation to a group of other high-income countries.

METHODS

We compared sex-specific trends in life expectancy since 1970 and age-specific mortality in England and Wales with median values for 22 high-income countries (in western Europe, Australia, Canada, New Zealand, Japan, and the USA). We used annual mortality data (1970-2016) from the Human Mortality Database.

FINDINGS

Until 2011-16, male life expectancy in England and Wales followed the median life expectancy of the comparator group. By contrast, female life expectancy was below the median and is among the lowest of the countries considered. In 2011-16, the rate of improvement in life expectancy slowed sharply for both sexes in England and Wales, and slowed more moderately in the comparator group because of negative trends in all adult age groups. This deceleration resulted in a widening gap between England and Wales and the comparators from 2011 onwards. Since the mid-2000s, for the first time, mortality rates in England and Wales among people aged 25-50 years were appreciably higher than in the comparator group.

INTERPRETATION

Although many countries have seen slower increases in life expectancy since 2011, trends in England and Wales are among the worst. The poor performance of female life expectancy over the long-term is in part driven by the relative timing of the smoking epidemic across countries. The previously overlooked higher mortality among young working-age adults in England and Wales relative to other countries deserves urgent attention.

FUNDING

None.