What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality

Abstract Background Material and behavioural factors play an important role in explaining educational inequalities in mortality, but gender differences in these contributions have received little attention thus far. We examined the contribution of a range of possible mediators to relative educationa...

Full description

Bibliographic Details
Main Authors: Karen van Hedel, Frank J. van Lenthe, Joost Oude Groeniger, Johan P. Mackenbach
Format: Article
Language:English
Published: BMC 2018-09-01
Series:BMC Public Health
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12889-018-5940-5
id doaj-d03b2f7b23344d979c932c60d9a692c1
record_format Article
spelling doaj-d03b2f7b23344d979c932c60d9a692c12020-11-25T02:45:49ZengBMCBMC Public Health1471-24582018-09-0118111410.1186/s12889-018-5940-5What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortalityKaren van Hedel0Frank J. van Lenthe1Joost Oude Groeniger2Johan P. Mackenbach3Department of Public Health, Erasmus MCDepartment of Public Health, Erasmus MCDepartment of Public Health, Erasmus MCDepartment of Public Health, Erasmus MCAbstract Background Material and behavioural factors play an important role in explaining educational inequalities in mortality, but gender differences in these contributions have received little attention thus far. We examined the contribution of a range of possible mediators to relative educational inequalities in mortality for men and women separately. Methods Baseline data (1991) of men and women aged 25 to 74 years participating in the prospective Dutch GLOBE study were linked to almost 23 years of mortality follow-up from Dutch registry data (6099 men and 6935 women). Cox proportional hazard models were used to calculate hazard ratios with 95% confidence intervals, and to investigate the contribution of material (financial difficulties, housing tenure, health insurance), employment-related (type of employment, occupational class of the breadwinner), behavioural (alcohol consumption, smoking, leisure and sports physical activity, body mass index) and family-related factors (marital status, living arrangement, number of children) to educational inequalities in all-cause and cause-specific mortality, i.e. mortality from cancer, cardiovascular disease, other diseases and external causes. Results Educational gradients in mortality were found for both men and women. All factors together explained 62% of educational inequalities in mortality for lowest educated men, and 71% for lowest educated women. Yet, type of employment contributed substantially more to the explanation of educational inequalities in all-cause mortality for men (29%) than for women (− 7%), whereas the breadwinner’s occupational class contributed more for women (41%) than for men (7%). Material factors and employment-related factors contributed more to inequalities in mortality from cardiovascular disease for men than for women, but they explained more of the inequalities in cancer mortality for women than for men. Conclusions Gender differences in the contribution of employment-related factors to the explanation of educational inequalities in all-cause mortality were found, but not of material, behavioural or family-related factors. A full understanding of educational inequalities in mortality benefits from a gender perspective, particularly when considering employment-related factors.http://link.springer.com/article/10.1186/s12889-018-5940-5EducationGender differencesSocioeconomic inequalitiesMortality
collection DOAJ
language English
format Article
sources DOAJ
author Karen van Hedel
Frank J. van Lenthe
Joost Oude Groeniger
Johan P. Mackenbach
spellingShingle Karen van Hedel
Frank J. van Lenthe
Joost Oude Groeniger
Johan P. Mackenbach
What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality
BMC Public Health
Education
Gender differences
Socioeconomic inequalities
Mortality
author_facet Karen van Hedel
Frank J. van Lenthe
Joost Oude Groeniger
Johan P. Mackenbach
author_sort Karen van Hedel
title What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality
title_short What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality
title_full What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality
title_fullStr What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality
title_full_unstemmed What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality
title_sort what’s the difference? a gender perspective on understanding educational inequalities in all-cause and cause-specific mortality
publisher BMC
series BMC Public Health
issn 1471-2458
publishDate 2018-09-01
description Abstract Background Material and behavioural factors play an important role in explaining educational inequalities in mortality, but gender differences in these contributions have received little attention thus far. We examined the contribution of a range of possible mediators to relative educational inequalities in mortality for men and women separately. Methods Baseline data (1991) of men and women aged 25 to 74 years participating in the prospective Dutch GLOBE study were linked to almost 23 years of mortality follow-up from Dutch registry data (6099 men and 6935 women). Cox proportional hazard models were used to calculate hazard ratios with 95% confidence intervals, and to investigate the contribution of material (financial difficulties, housing tenure, health insurance), employment-related (type of employment, occupational class of the breadwinner), behavioural (alcohol consumption, smoking, leisure and sports physical activity, body mass index) and family-related factors (marital status, living arrangement, number of children) to educational inequalities in all-cause and cause-specific mortality, i.e. mortality from cancer, cardiovascular disease, other diseases and external causes. Results Educational gradients in mortality were found for both men and women. All factors together explained 62% of educational inequalities in mortality for lowest educated men, and 71% for lowest educated women. Yet, type of employment contributed substantially more to the explanation of educational inequalities in all-cause mortality for men (29%) than for women (− 7%), whereas the breadwinner’s occupational class contributed more for women (41%) than for men (7%). Material factors and employment-related factors contributed more to inequalities in mortality from cardiovascular disease for men than for women, but they explained more of the inequalities in cancer mortality for women than for men. Conclusions Gender differences in the contribution of employment-related factors to the explanation of educational inequalities in all-cause mortality were found, but not of material, behavioural or family-related factors. A full understanding of educational inequalities in mortality benefits from a gender perspective, particularly when considering employment-related factors.
topic Education
Gender differences
Socioeconomic inequalities
Mortality
url http://link.springer.com/article/10.1186/s12889-018-5940-5
work_keys_str_mv AT karenvanhedel whatsthedifferenceagenderperspectiveonunderstandingeducationalinequalitiesinallcauseandcausespecificmortality
AT frankjvanlenthe whatsthedifferenceagenderperspectiveonunderstandingeducationalinequalitiesinallcauseandcausespecificmortality
AT joostoudegroeniger whatsthedifferenceagenderperspectiveonunderstandingeducationalinequalitiesinallcauseandcausespecificmortality
AT johanpmackenbach whatsthedifferenceagenderperspectiveonunderstandingeducationalinequalitiesinallcauseandcausespecificmortality
_version_ 1724759888738910208