The COVID-19 Pandemic and Life Expectancy: Decomposition Using Individual-Level Mortality Data

AbstractThough Switzerland has one of the highest life expectancies in the world, this global indicator may mask significant disparities at a local level. The present study used a spatial cluster detection approach based on individual death records to investigate the geographical footprint of life expectancy inequalities in the state of Geneva, Switzerland. Individual-level mortality data (n = 22,751) were obtained from Geneva’s official death notices (2009–2016). We measured life expectancy inequalities using the years of potential life lost or gained (YPLLG) metric, defined as the difference between an individual’s age at death and their life expectancy at birth. We assessed the spatial dependence of YPLLG across the state of Geneva using spatial autocorrelation statistics (Local Moran’s I). To ensure the robustness of the patterns discovered, we ran the analyses for ten random subsets of 10,000 individuals taken from the 22,751 deceased. We also repeated the spatial analysis for YPLLG before and after controlling for individual-level and neighborhood-level covariates. The results showed that YPLLG was not randomly distributed across the state of Geneva. The ten random subsets revealed no significant difference with the geographic footprint of YPLLG and the population characteristics within Local Moran cluster types, suggesting robustness for the observed spatial structure. The proportion of women, the proportion of Swiss, the neighborhood median income, and the neighborhood median age were all significantly lower for populations in low YPLLG clusters when compared to populations in high YPLLG clusters. After controlling for individual-level and neighborhood-level covariates, we observed a reduction of 43% and 39% in the size of low and high YPLLG clusters, respectively. To our knowledge, this is the first study in Switzerland using spatial cluster detection methods to investigate inequalities in life expectancy at a local scale and based on individual data. We identified clear geographic footprints of YPLLG, which may support further investigations and guide future public health interventions at the local level.

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The decomposition of life expectancy for age and cause of death in Tuscany, Italy

European Journal of Public Health ◽

10.1093/eurpub/ckz185.638 ◽

2019 ◽

Vol 29 (Supplement_4) ◽

Author(s):

N Nante ◽

L Kundisova ◽

F Gori ◽

A Martini ◽

F Battisti ◽

...

Keyword(s):

Life Expectancy ◽

Causes Of Death ◽

National Level ◽

Age Groups ◽

Resistant Bacteria ◽

Mortality Data ◽

Life Expectancy At Birth ◽

Icd 10 ◽

Reduction Of Mortality ◽

The Impact

Abstract Introduction Changing of life expectancy at birth (LE) over time reflects variations of mortality rates of a certain population. Italy is amongst the countries with the highest LE, Tuscany ranks fifth at the national level. The aim of the present work was to evaluate the impact of various causes of death in different age groups on the change in LE in the Tuscany region (Italy) during period 1987-2015. Material and methods Mortality data relative to residents that died during the period between 1987/1989 and 2013/2015 were provided by the Tuscan Regional Mortality Registry. The causes of death taken into consideration were cardiovascular (CVS), respiratory (RESP) and infective (INF) diseases and cancer (TUM). The decomposition of LE gain was realized with software Epidat, using the Pollard’s method. Results The overall LE gain during the period between two three-years periods was 6.7 years for males, with a major gain between 65-89, and 4.5 years for females, mainly improved between 75-89, <1 year for both sexes. The major gain (2.6 years) was attributable to the reduction of mortality for CVS, followed by TUM (1.76 in males and 0.83 in females) and RESP (0.4 in males; 0.1 in females). The major loss of years of LE was attributable to INF (-0.15 in females; -0.07 in males) and lung cancer in females (-0.13), for which the opposite result was observed for males (gain of 0.62 years of LE). Conclusions During the study period (1987-2015) the gain in LE was major for males. To the reduction of mortality for CVS have contributed to the tempestuous treatment of acute CVS events and secondary CVS prevention. For TUM the result is attributable to the adherence of population to oncologic screening programmes. The excess of mortality for INF that lead to the loss of LE can be attributed to the passage from ICD-9 to ICD-10 in 2003 (higher sensibility of ICD-10) and to the diffusion of multi-drug resistant bacteria, which lead to elevated mortality in these years. Key messages The gain in LE during the period the 1987-2015 was higher in males. The major contribution to gain in LE was due to a reduction of mortality for CVS diseases.

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On the Uses of Disinformation to Legitimize the Revival of the Cold War: Health in the U.S.S.R.

International Journal of Health Services ◽

10.2190/vnv7-yyy5-yan0-47ww ◽

1982 ◽

Vol 12 (3) ◽

pp. 481-496 ◽

Cited By ~ 1

Author(s):

Albert Szymanski

Keyword(s):

Child Care ◽

Soviet Union ◽

Infant Mortality ◽

Life Expectancy ◽

Public Health Education ◽

The United States ◽

Mortality Data ◽

The Soviet Union ◽

Employment Of Women ◽

Child Care Facilities

During the 1970s the Soviet Union experienced rising infant mortality rates and a corresponding levelling off of earlier increases in life expectancy. Several Western critics have misrepresented or exaggerated these statistics, suggesting that these trends indicate a general breakdown in the Soviet health care system as well as the failure of the Soviet form of socialism. This paper examines life expectancy and infant mortality data by Soviet republic, showing that rates are not uniform throughout the U.S.S.R. and in many cases compare favorably with those in Western European countries and the United States. It is suggested that the infant mortality problem in the U.S.S.R. is a temporary negative consequence of rapid progress in the areas of industrialization, employment of women, and socialization of child care. It is concluded that improvements in public health education, the quality of child care facilities, and the manufacture and distribution of infant formula will contribute to the rapid resolution of this problem.

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Partitioning mortality into growth-dependent and growth-independent hazards across 203 tropical tree species

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1721040115 ◽

2018 ◽

Vol 115 (49) ◽

pp. 12459-12464 ◽

Cited By ~ 7

Author(s):

James S. Camac ◽

Richard Condit ◽

Richard G. FitzJohn ◽

Lachlan McCalman ◽

Daniel Steinberg ◽

...

Keyword(s):

Wood Density ◽

Tree Species ◽

Total Mortality ◽

Species Traits ◽

Barro Colorado Island ◽

Maximum Diameter ◽

Mortality Data ◽

Individual Level ◽

Hazards Model ◽

Variation Explained

Tree death drives population dynamics, nutrient cycling, and evolution within plant communities. Mortality variation across species is thought to be influenced by different factors relative to variation within species. The unified model provided here separates mortality rates into growth-dependent and growth-independent hazards. This model creates the opportunity to simultaneously estimate these hazards both across and within species. Moreover, it provides the ability to examine how species traits affect growth-dependent and growth-independent hazards. We derive this unified mortality model using cross-validated Bayesian methods coupled with mortality data collected over three census intervals for 203 tropical rainforest tree species at Barro Colorado Island (BCI), Panama. We found that growth-independent mortality tended to be higher in species with lower wood density, higher light requirements, and smaller maximum diameter at breast height (dbh). Mortality due to marginal carbon budget as measured by near-zero growth rate tended to be higher in species with lower wood density and higher light demand. The total mortality variation attributable to differences among species was large relative to variation explained by these traits, emphasizing that much remains to be understood. This additive hazards model strengthens our capacity to parse and understand individual-level mortality in highly diverse tropical forests and hence to predict its consequences.

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Adequate life-expectancy reconstruction for adult human mortality data

PLoS ONE ◽

10.1371/journal.pone.0198485 ◽

2018 ◽

Vol 13 (6) ◽

pp. e0198485 ◽

Cited By ~ 2

Author(s):

László Németh ◽

Trifon I. Missov

Keyword(s):

Life Expectancy ◽

Mortality Data ◽

Human Mortality ◽

Adult Human

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An Association of Total Health Expenditure with GDP and Life Expectancy

Journal of Medical Research and Innovation ◽

10.15419/jmri.72 ◽

2017 ◽

Vol 1 (2) ◽

pp. AU7-AU12 ◽

Cited By ~ 5

Author(s):

Sojib Bin Zaman ◽

Naznin Hossain ◽

Varshil Mehta ◽

Shuchita Sharmin ◽

Shakeel Ahmed Ibne Mahmood

Keyword(s):

Developing Countries ◽

Life Expectancy ◽

Gross Domestic Product ◽

Health Expenditure ◽

Health Spending ◽

Domestic Product ◽

Fiscal Year ◽

Total Health Expenditure ◽

Registration System ◽

Individual Level

Introduction: Gradual total health expenditure (THE) has become a major concern. It is not only the increased THE, but also its unequal growth in overall economy, found among the developing countries. If increased life expectancy is considered as a leverage for an individual’s investment in health services, it can be expected that as the life expectancy increases, tendency of health care investment will also experience a boost up. Objective: The aim of the present study was to explore and identify the association of healthcare expenditure with the life expectancy and Gross Domestic Product (GDP) in developing countries, especially that of Bangladesh. Methodology: Data were retrospectively collected from “Health Bulletin 2011” and “Sample Vital Registration System 2010” of Bangladesh considering the fiscal year 1996 to fiscal year 2006. Using STATA, multivariable logistic regression was performed to find out the association of total health expenditure with GDP and life expectancy. Results: A direct relationship between GDP and total health expenditure was found through analysing the data. At the individual level, income had a direct influence on health spending. However, there was no significant relationship between total health expenditure with increased life expectancy. Conclusion: The present study did not find any association between life expectancy and total health expenditure. However, our analysis found out that total health expenditure is more sensitive to gross domestic product rather than life expectancy.

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Neighborhood Disadvantage and Active, Disabled and Total Life Expectancy Among Community-living Older Persons

10.1101/2021.02.05.21251217 ◽

2021 ◽

Author(s):

Thomas M. Gill ◽

Emma X. Zang ◽

Terrence E. Murphy ◽

Linda Leo-Summers ◽

Evelyne A. Gahbauer ◽

...

Keyword(s):

Prognostic Factors ◽

Life Expectancy ◽

Older Persons ◽

Neighborhood Disadvantage ◽

Community Living ◽

Remaining Life ◽

Disadvantaged Group ◽

Individual Level ◽

Total Life Expectancy ◽

Total Life

AbstractBackgroundNeighborhood disadvantage is a novel social determinant of health that could adversely affect the functional well-being and longevity of older persons. We evaluated whether estimates of active, disabled and total life expectancy differ on the basis of neighborhood disadvantage after accounting for individual-level socioeconomic characteristics and other prognostic factors.MethodsWe used data on 754 community-living older persons from South Central Connecticut, who completed monthly assessments of disability from 1998 to 2020. Scores on the area deprivation index were dichotomized at the 80th state percentile to distinguish neighborhoods that were disadvantaged (81-100) from those that were not (1-80).ResultsWithin 5-year age increments from 70 to 90, active and total life expectancy were consistently lower in participants from neighborhoods that were disadvantaged versus not disadvantaged, and these differences persisted and remained statistically significant after adjustment for individual-level race/ethnicity, education, income, and other prognostic factors. At age 70, adjusted estimates (95% CI) for active and total life expectancy (in years) were 12.3 (11.5-13.1) and 15.0 (13.8-16.1) in the disadvantaged group and 14.2 (13.5-14.7) and 16.7 (15.9-17.5) in the non-disadvantaged group. At each age, participants from disadvantaged neighborhoods spent a greater percentage of their projected remaining life disabled, relative to those from non-disadvantaged neighborhoods, with adjusted values (SE) ranging from 17.7 (0.8) vs. 15.3 (0.5) at age 70 to 55.0 (1.7) vs. 48.1 (1.3) at age 90.ConclusionsLiving in a disadvantaged neighborhood is associated with lower active and total life expectancy and a greater percentage of projected remaining life disabled.

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Health Status of Old Age Population in Bulgaria

European Journal of Interdisciplinary Studies ◽

10.26417/ejis.v2i4.p126-131 ◽

2016 ◽

Vol 2 (4) ◽

pp. 126

Author(s):

Mariana Mourgova

Keyword(s):

Health Status ◽

Life Expectancy ◽

European Countries ◽

Healthy Life Expectancy ◽

Mortality Data ◽

Healthy Life ◽

Healthy Life Years ◽

Demographic Indicators ◽

Life Years ◽

Different Levels

This article examines the health status of the population in Bulgaria at age 65 by gender during the period 2006-2014. The health status is examined by some of the most frequently used demographic indicators, namely life expectancy, based on mortality data and healthy life years and healthy life expectancy, based on mortality, life expectancy and self-perceived health. The main results show that despite of the observed increase in life expectancy at age 65 in Bulgaria during the period it is the lowest compared to other European countries. The share for both men and women reported their health status as without limitations in respect to daily activities decline, while those reported their health status as good increase. These contradictory facts reflect on the measures of health status. Thus, the trend in healthy life years for both sexes decline over the period, whereas the trend in healthy life expectancy increases. Compared with the other European countries, the expected number of years without limitations in Bulgaria is among the largest, while the healthy life expectancy is the lowest. These differences could be explained by the different levels in mortality and the nature of the measures of health status themselves.

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