Heterogeneity in Subnational Mortality in The Context of The COVID-19 Pandemic: The Case of Belgian Districts

Abstract Background: The COVID-19 pandemic has caused major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shock at the sub-national level, rigorously accounting for the different sources of uncertainty.Methods: Using death registration data from Belgium, we first assess the change in the heterogeneity of subnational standardized mortality ratios in 2020, when compared to previous years. We then measure the shock of the pandemic using district-level values of life expectancy, comparing the observed and projected districts life expectancy, accounting for all sources of uncertainty (related to the life-table construction at district level and to the projection methods at country and district level). The Bayesian modelling approach makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts.Results: The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial, with some districts barely showing any impact whereas the Bruxelles-Capital and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33-3.05) and 2.10 (95% CI:0.86-3.30) years, respectively. The year 2020 was associated with an increase in mortality levels ' heterogeneity at a subnational level in comparison to past years measured by both the standardized mortality ratios and the life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results.Conclusion: Developing sub-national mortality estimates with their uncertainty is key to understanding why certain areas have been hard hit in comparison to others.

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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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How have changes in death by cause and age group contributed to the recent stalling of life expectancy gains in Scotland? Comparative decomposition analysis of mortality data, 2000–2002 to 2015–2017

BMJ Open ◽

10.1136/bmjopen-2019-036529 ◽

2020 ◽

Vol 10 (10) ◽

pp. e036529

Author(s):

Julie Ramsay ◽

Jon Minton ◽

Colin Fischbacher ◽

Lynda Fenton ◽

Maria Kaye-Bardgett ◽

...

Keyword(s):

Life Expectancy ◽

Cause Of Death ◽

Age Groups ◽

Decomposition Analysis ◽

Future Research ◽

Mortality Data ◽

Age Group ◽

Mortality Trends ◽

Life Expectancy At Birth ◽

The Impact

ObjectiveAnnual gains in life expectancy in Scotland were slower in recent years than in the previous two decades. This analysis investigates how deaths in different age groups and from different causes have contributed to annual average change in life expectancy across two time periods: 2000–2002 to 2012–2014 and 2012–2014 to 2015–2017.SettingScotland.MethodsLife expectancy at birth was calculated from death and population counts, disaggregated by 5 year age group and by underlying cause of death. Arriaga’s method of life expectancy decomposition was applied to produce estimates of the contribution of different age groups and underlying causes to changes in life expectancy at birth for the two periods.ResultsAnnualised gains in life expectancy between 2012–2014 and 2015–2017 were markedly smaller than in the earlier period. Almost all age groups saw worsening mortality trends, which deteriorated for most cause of death groups between 2012–2014 and 2015–2017. In particular, the previously observed substantial life expectancy gains due to reductions in mortality from circulatory causes, which most benefited those aged 55–84 years, more than halved. Mortality rates for those aged 30–54 years and 90+ years worsened, due in large part to increases in drug-related deaths, and dementia and Alzheimer’s disease, respectively.ConclusionFuture research should seek to explain the changes in mortality trends for all age groups and causes. More investigation is required to establish to what extent shortcomings in the social security system and public services may be contributing to the adverse trends and preventing mitigation of the impact of other contributing factors, such as influenza outbreaks.

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Human costs of the first wave of the COVID-19 pandemic in the major epicentres in Italy

10.1553/populationyearbook2022.res2.1 ◽

2021 ◽

Author(s):

Simone Ghislandi ◽

Raya Muttarak ◽

Markus Sauerberg ◽

Benedetta Scotti

Keyword(s):

Life Expectancy ◽

Excess Mortality ◽

National Level ◽

Death Registration ◽

Substantial Impact ◽

Registration Data ◽

Life Expectancy At Birth ◽

Human Costs ◽

The Impact ◽

Excess Deaths

Deaths from COVID-19 can be miscounted due to under-reporting and inaccurate death registration. Mortality is often reported at the national level, which can result in the underestimation of the true scale of the impact of the pandemic since outbreaks tend to be localised. This study exploits all-cause daily death registration data provided by the Italian Statistical Office (ISTAT) from 1 January to 31 October to estimate the excess mortality and the corresponding changes in life expectancy during the first wave of the COVID-19 pandemic. Focusing on the five most severely hit provinces in Italy (Bergamo, Brescia, Cremona, Lodi and Piacenza), we calculate the excess mortality in 2020 compared to the average mortality of the years 2015 to 2019. Moreover, we estimate the excess mortality in the first quadrimester of 2020, and the annual life expectancy at birth. The estimated excess deaths show that during this period, mortality was significantly higher than the official mortality statistics for COVID-19. According to our estimates for the first quadrimester, life expectancy in the five provinces declined by 5.4 to 8.1 for men and by 4.1 to 5.8 years for women. In addition, we find that annual life expectancy decreased by 2.4 to 4.1 years for men and by 1.9 to 2.8 years for women compared to the 2015–2019 average. Thus, we conclude that the first wave of the COVID-19 pandemic had a substantial impact on population health in the hardest hit areas in Italy.

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How have changes in death by cause and age group contributed to the recent stalling of life expectancy gains in Scotland? Comparative decomposition analysis of mortality data, 2000-02 to 2015-17

10.31235/osf.io/q8rme ◽

2019 ◽

Cited By ~ 3

Author(s):

Julie Ramsay ◽

Jonathan Minton ◽

Colin Fischbacher ◽

Lynda Fenton ◽

Maria Kaye-Bardgett ◽

...

Keyword(s):

Life Expectancy ◽

Cause Of Death ◽

Age Groups ◽

Decomposition Analysis ◽

Mortality Data ◽

Age Group ◽

Contributing Factors ◽

Mortality Trends ◽

Life Expectancy At Birth ◽

The Impact

BackgroundAnnual gains in life expectancy in Scotland were slower in recent years than in the previous two decades. This analysis investigates how deaths in different age groups and from different causes have contributed to annual average change in life expectancy across two time periods: 2000-02 to 2012-14 and 2012-14 to 2015-17. MethodsLife expectancy at birth was calculated from death and population counts, disaggregated by five-year age-group and by underlying cause of death. Arriaga’s method of life expectancy decomposition was applied to produce estimates of the contribution of different age-groups and underlying causes to changes in life expectancy at birth for the two periods.FindingsAverage annual life expectancy gains between 2012-14 to 2015-17 were markedly smaller than in the earlier period. Almost all age-groups saw worsening mortality trends, which deteriorated for most cause of death groups between 2012-14 and 2015-17. In particular, the previously observed substantial life expectancy gains due to reductions in mortality from circulatory causes, which most benefited those aged 55-84 years, more than halved. Mortality rates for those aged 30-54 years and 90+ years worsened, due in large part to increases in drug-related deaths, and dementia and Alzheimer’s disease respectively. InterpretationFuture research should seek to explain the changes in mortality trends for all age-groups and causes. More investigation is required to establish to what extent shortcomings in the social security system and public services may be contributing to the adverse trends and preventing mitigation of the impact of other contributing factors, such as influenza outbreaks.

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Effects of Technological Progress from Different Sources on Haze Pollution in China

Sustainability ◽

10.3390/su13052730 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2730

Author(s):

Yuan Zhao ◽

Tian Zhang ◽

Ting Wu ◽

Shujing Xu ◽

Shuwang Yang

Keyword(s):

Technological Progress ◽

Generalized Method Of Moments ◽

National Level ◽

Inhibitory Effect ◽

Dynamic Panel Model ◽

Independent Innovation ◽

Haze Pollution ◽

Technology Introduction ◽

The Impact ◽

Different Sources

Technological progress has always been regarded as an important factor affecting haze pollution. A large number of academic studies have focused on the effect of technological progress on haze pollution, but there are few discussions on the effects of technological progress from different sources. In view of this, a dynamic panel model is constructed, and a systematic generalized method of moments (GMM) method is applied to empirically test the overall impact of technological progress from different sources on haze pollution and the regional heterogeneity of the impact. The results show that the overall and regional impact of technological progress from different sources on haze pollution is entirely different. Among them, for the whole country, independent innovation has a significant inhibitory effect on haze pollution, and technology introduction has aggravated haze pollution to a certain extent. At the regional level, all types of technological progress in the east can effectively reduce haze, the central region having haze reduction results consistent with the overall national level, and in the west, independent innovation and direct introduction can effectively reduce haze, while reverse technology spillover is ineffective. Therefore, policy recommendations such as improving the ability of independent innovation, improving the quality of technology introduction, and coordinating regional technology against haze are put forward.

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Reductions in US life expectancy from COVID-19 by Race and Ethnicity: Is 2021 a repetition of 2020?

10.1101/2021.10.17.21265117 ◽

2021 ◽

Author(s):

Theresa Andrasfay ◽

Noreen Goldman

Keyword(s):

Life Expectancy ◽

Race And Ethnicity ◽

Ethnic Disparities ◽

White Population ◽

Widespread Distribution ◽

Life Expectancy At Birth ◽

The Us ◽

The Impact ◽

Racial Ethnic ◽

Black And Latino

COVID-19 had a huge mortality impact in the US in 2020 and accounted for the majority of the 1.5-year reduction in 2020 life expectancy at birth. There were also substantial racial/ethnic disparities in the mortality impact of COVID-19 in 2020, with the Black and Latino populations experiencing reductions in life expectancy at birth over twice the reduction experienced by the White population. Despite continued vulnerability of the Black and Latino populations, the hope was that widespread distribution of effective vaccines would mitigate the overall impact and reduce racial/ethnic disparities in 2021. In this study, we use cause-deleted life table methods to estimate the impact of COVID-19 mortality on 2021 US period life expectancy. Our partial-year estimates, based on provisional COVID-19 deaths for January-early October 2021 suggest that racial/ethnic disparities have persisted and that life expectancy at birth in 2021 has already declined by 1.2 years from pre-pandemic levels. Our projected full-year estimates, based on projections of COVID-19 deaths through the end of 2021 from the Institute for Health Metrics and Evaluation, suggest a 1.8-year reduction in US life expectancy at birth from pre-pandemic levels, a steeper decline than the estimates produced for 2020. The reductions in life expectancy at birth estimated for the Black and Latino populations are 1.6-2.4 times the impact for the White population.

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Beyond standardized mortality ratios; some uses of smoothed age-specific mortality rates on small areas studies

International Journal of Health Geographics ◽

10.1186/s12942-020-00251-z ◽

2020 ◽

Vol 19 (1) ◽

Author(s):

Jordi Perez-Panades ◽

Paloma Botella-Rocamora ◽

Miguel Angel Martinez-Beneito

Keyword(s):

Life Expectancy ◽

Age Groups ◽

Dependence Structure ◽

Risk Indicator ◽

Small Areas ◽

Life Expectancy At Birth ◽

First Case ◽

Wide Range ◽

Standardized Mortality Ratios

Abstract Background Most epidemiological risk indicators strongly depend on the age composition of populations, which makes the direct comparison of raw (unstandardized) indicators misleading because of the different age structures of the spatial units of study. Age-standardized rates (ASR) are a common solution for overcoming this confusing effect. The main drawback of ASRs is that they depend on age-specific rates which, when working with small areas, are often based on very few, or no, observed cases for most age groups. A similar effect occurs with life expectancy at birth and many more epidemiological indicators, which makes standardized mortality ratios (SMR) the omnipresent risk indicator for small areas epidemiologic studies. Methods To deal with this issue, a multivariate smoothing model, the M-model, is proposed in order to fit the age-specific probabilities of death (PoDs) for each spatial unit, which assumes dependence between closer age groups and spatial units. This age–space dependence structure enables information to be transferred between neighboring consecutive age groups and neighboring areas, at the same time, providing more reliable age-specific PoDs estimates. Results Three case studies are presented to illustrate the wide range of applications that smoothed age specific PoDs have in practice . The first case study shows the application of the model to a geographical study of lung cancer mortality in women. This study illustrates the convenience of considering age–space interactions in geographical studies and to explore the different spatial risk patterns shown by the different age groups. Second, the model is also applied to the study of ischaemic heart disease mortality in women in two cities at the census tract level. Smoothed age-standardized rates are derived and compared for the census tracts of both cities, illustrating some advantages of this mortality indicator over traditional SMRs. In the latest case study, the model is applied to estimate smoothed life expectancy (LE), which is the most widely used synthetic indicator for characterizing overall mortality differences when (not so small) spatial units are considered. Conclusion Our age–space model is an appropriate and flexible proposal that provides more reliable estimates of the probabilities of death, which allow the calculation of enhanced epidemiological indicators (smoothed ASR, smoothed LE), thus providing alternatives to traditional SMR-based studies of small areas.

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Health Care Public Sector Share and the U.S. Life Expectancy Lag: A Country-level Longitudinal Study

International Journal of Health Services ◽

10.1177/0020731417753673 ◽

2018 ◽

Vol 48 (2) ◽

pp. 328-348 ◽

Cited By ~ 1

Author(s):

Megan M. Reynolds

Keyword(s):

Health Care ◽

Political Economy ◽

Public Sector ◽

Life Expectancy ◽

Policy Implications ◽

The Political ◽

Life Expectancy At Birth ◽

Political Economy Of Health ◽

The Impact ◽

The U.S

Growing research on the political economy of health has begun to emphasize sociopolitical influences on cross-national differences in population health above and beyond economic growth. While this research investigates the impact of overall public health spending as a share of GDP (“health care effort”), it has for the most part overlooked the distribution of health care spending across the public and private spheres (“public sector share”). I evaluate the relative contributions of health care effort, public sector share, and GDP to the large and growing disadvantage in U.S. life expectancy at birth relative to peer nations. I do so using fixed effects models with data from 16 wealthy democratic nations between 1960 and 2010. Results indicate that public sector share has a beneficial effect on longevity net of the effect of health care effort and that this effect is nonlinear, decreasing in magnitude as levels rise. Moreover, public sector share is a more powerful predictor of life expectancy at birth than GDP per capita. This study contributes to discussions around the political economy of health, the growth consensus, and the American lag in life expectancy. Policy implications vis-à-vis the U.S. Affordable Care Act are discussed.

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Trends in Avoidable Mortality in Lithuania During 2001–2008 and Their Impact on Life Expectancy

Medicina ◽

10.3390/medicina47090067 ◽

2011 ◽

Vol 47 (9) ◽

pp. 504 ◽

Cited By ~ 2

Author(s):

Vilius Grabauskas ◽

Aldona Gaižauskienė ◽

Skirmantė Sauliūnė ◽

Rasa Mišeikytė

Keyword(s):

Life Expectancy ◽

Mortality Data ◽

Avoidable Mortality ◽

Average Life Expectancy ◽

Mortality Trends ◽

Annual Percent Change ◽

Increasing Trend ◽

Causes Of Deaths ◽

Changes Over Time ◽

The Impact

The process of the restructuring of health care system in Lithuania demonstrates the need to continue the monitoring of changes in avoidable mortality. Objective. To assess the level of avoidable mortality as well as its changes over time in Lithuania during 2001–2008 and to define the impact of avoidable mortality on life expectancy. Material and Methods. The mortality data were taken from the Lithuanian Department of Statistics. Twelve avoidable causes of deaths (treatable and preventable) were analyzed. Mortality trends were assessed by computing the average annual percent change (AAPC). The shortening of average life expectancy was computed from survival tables. Results. During the period 2001–2008, the avoidable mortality was increasing more significantly (AAPC 3.0%, P<0.05) than the overall mortality (AAPC 1.7%, P<0.05) in the population aged 5–64 years. The increasing trend was mainly determined by mortality from preventable diseases (AAPC 4.6%, P<0.05). The avoidable causes of death reduced the life expectancy by 1.77 years (preventable by 1.12 and treatable by 0.63 years). Diversity in trends in mortality of different avoidable causes was disclosed. A declining trend in mortality caused by chronic rheumatic heart disease and lung cancer was observed for males (AAPC –22.6% and –2.1%, respectively; P<0.05). However, the mortality caused by liver cirrhosis was increasing for both genders (AAPC 16.1% for males and 17.6% for females, P<0.01) and that caused by tuberculosis – only for females (AAPC 7.8%, P<0.05). Conclusions. An increasing trend in avoidable mortality was observed. Deaths caused by the diseases that could have been prevented had the greatest impact on the increasing mortality and decreasing life expectancy.

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How do ethnicity and deprivation impact on life expectancy at birth in people with serious mental illness? Observational study in the UK

Psychological Medicine ◽

10.1017/s0033291720001087 ◽

2020 ◽

pp. 1-9

Author(s):

Jayati Das-Munshi ◽

Chin-Kuo Chang ◽

Alex Dregan ◽

Stephani L. Hatch ◽

Craig Morgan ◽

...

Keyword(s):

General Population ◽

Life Expectancy ◽

Bipolar Disorders ◽

Mental Illnesses ◽

Schizophrenia Spectrum Disorders ◽

Life Expectancy At Birth ◽

Schizophrenia Spectrum ◽

Spectrum Disorders ◽

The Impact ◽

Deprived Areas

Abstract Background Across international contexts, people with serious mental illnesses (SMI) experience marked reductions in life expectancy at birth. The intersection of ethnicity and social deprivation on life expectancy in SMI is unclear. The aim of this study was to assess the impact of ethnicity and area-level deprivation on life expectancy at birth in SMI, defined as schizophrenia-spectrum disorders, bipolar disorders and depression, using data from London, UK. Methods Abridged life tables to calculate life expectancy at birth, in a cohort with clinician-ascribed ICD-10 schizophrenia-spectrum disorders, bipolar disorders or depression, managed in secondary mental healthcare. Life expectancy in the study population with SMI was compared with life expectancy in the general population and with those residing in the most deprived areas in England. Results Irrespective of ethnicity, people with SMI experienced marked reductions in life expectancy at birth compared with the general population; from 14.5 years loss in men with schizophrenia-spectrum and bipolar disorders, to 13.2 years in women. Similar reductions were noted for people with depression. Across all diagnoses, life expectancy at birth in people with SMI was lower than the general population residing in the most deprived areas in England. Conclusions Irrespective of ethnicity, reductions in life expectancy at birth among people with SMI are worse than the general population residing in the most deprived areas in England. This trend in people with SMI is similar to groups who experience extreme social exclusion and marginalisation. Evidence-based interventions to tackle this mortality gap need to take this into account.

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