Evidence map›Paper›PMID 31363299›Full record

ArticleSocial indicators research2019

Dimensions of Social Stratification and Their Relation to Mortality: A Comparison Across Gender and Life Course Periods in Finland.

Rasmus Hoffmann, Hannes Kröger, Lasse Tarkiainen, Pekka Martikainen

Abstract read
In one paragraph

Article in Social indicators research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rasmus Hoffmann1European University Institute, Via Dei Roccettini 9, 50014 San Domenico di Fiesole, Italy.ORCID 0000-0002-9007-3144
Hannes Kröger1European University Institute, Via Dei Roccettini 9, 50014 San Domenico di Fiesole, Italy.
Lasse Tarkiainen4Department of Social Research, Sociology, Center for Population, Health and Society (CPHS), University of Helsinki, PL 18, Unioninkatu 35, Helsinki, Finland.
Pekka Martikainen2Max Planck Institute for Demographic Research, Konrad-Zuse-Straße 1, 18057 Rostock, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Differences in mortality between groups with different socioeconomic positions (SEP) are well-established, but the relative contribution of different SEP measures is unclear. This study compares the correlation between three SEP dimensions and mortality, and investigates differences between gender and age groups (35-59 vs. 60-84). We use an 11% random sample with an 80% oversample of deaths from the Finnish population with information on education, occupational class, individual income, and mortality (n = 496,658; 274,316 deaths between 1995 and 2007). We estimate bivariate and multivariate Cox proportional hazard models and population attributable fractions. The total effects of education are substantially mediated by occupation and income, and the effects of occupation is mediated by income. All dimensions have their own net effect on mortality, but income shows the steepest mortality gradient (HR 1.78, lowest vs. highest quintile). Income is more important for men and occupational class more important among elderly women. Mortality inequalities are generally smaller in older ages, but the relative importance of income increases. In health inequality studies, the use of only one SEP indicator functions well as a broad marker of SEP. However, only analyses of multiple dimensions allow insights into social mechanisms and how they differ between population subgroups.

Indexed as

EducationHealth inequalityIncomeMortalityOccupationRegister dataSocial inequalitySocioeconomic position

Identifiers

PMID31363299
PMCPMC6620240

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.