Lexis fields

Riffe, Tim; Aburto, José Manuel

doi:10.4054/demres.2020.42.24

Cited by 3 publications

(1 citation statement)

References 25 publications

(27 reference statements)

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“…Afterwards we used standard life table techniques to calculate life expectancy [23] for both sexes and each quintile of socioeconomic deprivation. Finally, we used the stepwise decomposition approach [24] and the function stepwise_replacement of R package DemoDecomp [25] to decompose the difference in life expectancy between the most and least deprived quintiles of German districts into age- and cause-specific contributions. In addition, we calculated the deprivation-specific standardised mortality rate for the different cause-of-death groups for broader overviews of mortality developments by socioeconomic deprivation.…”

Section: Methodsmentioning

confidence: 99%

The socioeconomic gap in life expectancy in Germany: a decomposition of age- and cause-specific mortality contributions, 2003–2021

Tetzlaff,

Sauerberg,

Grigoriev

et al. 2023

Preprint

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SummaryBackgroundEarlier death among people in socioeconomically deprived circumstances has been found internationally and for various causes of death, resulting in a considerable life expectancy gap between socioeconomic groups. This study examines how age- and cause-specific mortality contributions to the socioeconomic gap in life expectancy have changed in Germany over time.MethodsOfficial German population and cause-of-death statistics from 2003 to 2021 were linked to the district-level German Index of Socioeconomic Deprivation. Life-table and decomposition methods were applied to calculate life expectancy by deprivation quintile and decompose the life expectancy gap (ΔLE) between the most and least deprived quintiles into age- and cause-specific mortality contributions.FindingsFrom 2003 to 2019, the ΔLE between the most and least deprived quintiles of districts increased from 1.1 to 1.8 years among women and from 3.0 to 3.1 years among men. Thereafter, in the COVID-19 pandemic, it increased more rapidly to 2.2 and 3.5 years respectively in 2021. The causes of death contributing most to the ΔLE were cardiovascular diseases (CVD) and cancer, with declining contributions of CVD deaths at age 70 and above and increasing contributions of cancer deaths at ages 40–74 over time. COVID-19 mortality at ages 45+ was the strongest contributor to the increase in ΔLE after 2019.InterpretationTo reduce the socioeconomic gap in life expectancy, effective efforts are needed to prevent early deaths from CVD and cancer in deprived populations, with cancer prevention and control becoming an increasingly important field of action in this respect.

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Section: Methodsmentioning

confidence: 99%

The socioeconomic gap in life expectancy in Germany: a decomposition of age- and cause-specific mortality contributions, 2003–2021

Tetzlaff,

Sauerberg,

Grigoriev

et al. 2023

Preprint

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MBTIviz: A Visualization System for Research on Psycho-Demographics and Personality

Yang,

Dong,

Tian

et al. 2023

Communications in Computer and Information Science

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Editorial to the Special Issue on Demographic Data Visualization: Getting the point across – Reaching the potential of demographic data visualization

Riffe¹,

Sander²,

Kluesener³

2021

DemRes

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BACKGROUNDDemography is full of data visualization challenges, such as age-period-cohort effects or life course trajectories. Innovative approaches to visualizing such complex data structures have been proposed from within and outside the discipline. However, demographic data visualizations presented in the scientific literature often fall short of the state-of-the-art. OBJECTIVEWe discuss what makes a good data visualization and why it is worthwhile to strive for state-of-the-art visualization. We highlight the distinction between exploratory and explanatory graphics, and relate the seven papers that comprise the Demographic Research special collection on data visualization to the broader endeavor of data visualization in demography. CONTRIBUTIONWe suggest a set of best practice rules that are intended to provide general guidance for researchers attempting to produce meaningful and coherently designed figures from their data.

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Lexis fields

Cited by 3 publications

References 25 publications

The socioeconomic gap in life expectancy in Germany: a decomposition of age- and cause-specific mortality contributions, 2003–2021

The socioeconomic gap in life expectancy in Germany: a decomposition of age- and cause-specific mortality contributions, 2003–2021

MBTIviz: A Visualization System for Research on Psycho-Demographics and Personality

Editorial to the Special Issue on Demographic Data Visualization: Getting the point across – Reaching the potential of demographic data visualization

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