Trends in inequalities in premature mortality: a study of 3.2 million deaths in 13 European countries

Mackenbach, Johan P.; Kulhánová, Ivana; Menvielle, Gwenn; Bopp, Matthias; Borrell, Carme; Costa, Giuseppe; Deboosere, Patrick; Esnaola, Santiago; Kalèdiené, Ramuné; Kovács, Katalin; Leinsalu, Mall; Martikainen, Pekka; Regidor, Enrique; Rodríguez-Sanz, Maica; Strand, Bjørn Heine; Hoffmann, Rasmus; Eikemo, Terje Andreas; Östergren, Olof; Lundberg, Olle

doi:10.1136/jech-2014-204319

Cited by 216 publications

(210 citation statements)

References 34 publications

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“…Relative disparities in mortality by occupational class have also been stable since the 1980s, whereas absolute differences in life expectancy among both men and women at age 35 have fluctuated with no clear trend (13). Between the mid-1990s and mid-2000s, mortality ratios by education for both men and women rose slightly, but absolute differences fell (38).…”

Section: Empirical Evidence On the Effects Of Income Inequalitymentioning

confidence: 95%

“…Trends in the United Kingdom may also have reversed recently. From the mid-1990s to the mid-2000s, educational disparities in mortality between ages 30 and 74 fell for both men and women in both relative and absolute terms (38), even though income inequality continued to rise.…”

Section: Empirical Evidence On the Effects Of Income Inequalitymentioning

confidence: 99%

“…By the mid-2000s, the north-south gradient was even more notable, as relative mortality disparities continued to increase in the north but stayed fairly steady in the south (38). Relative disparities in mortality from preventable causes, which should be especially sensitive to income inequality if the rich and well-educated take the most advantage of prevention and treatment (15,45,48,49), follow the same north-south gradient (37).…”

Section: Cross-sectional Data: At a Single Point In Time Does The Lementioning

confidence: 99%

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The Health Effects of Income Inequality: Averages and Disparities

Truesdale¹,

Jencks

2016

Annu. Rev. Public Health

117

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Much research has investigated the association of income inequality with average life expectancy, usually finding negative correlations that are not very robust. A smaller body of work has investigated socioeconomic disparities in life expectancy, which have widened in many countries since 1980. These two lines of work should be seen as complementary because changes in average life expectancy are unlikely to affect all socioeconomic groups equally. Although most theories imply long and variable lags between changes in income inequality and changes in health, empirical evidence is confined largely to short-term effects. Rising income inequality can affect individuals in two ways. Direct effects change individuals' own income. Indirect effects change other people's income, which can then change a society's politics, customs, and ideals, altering the behavior even of those whose own income remains unchanged. Indirect effects can thus change both average health and the slope of the relationship between individual income and health.

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Section: Empirical Evidence On the Effects Of Income Inequalitymentioning

confidence: 95%

Section: Empirical Evidence On the Effects Of Income Inequalitymentioning

confidence: 99%

Section: Cross-sectional Data: At a Single Point In Time Does The Lementioning

confidence: 99%

See 1 more Smart Citation

The Health Effects of Income Inequality: Averages and Disparities

Truesdale¹,

Jencks

2016

Annu. Rev. Public Health

117

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“…W 2011 r. w Polsce wskaźnik aktywności zawodowej w grupie osób z wykształceniem wyższym wynosił 78,6%, natomiast w grupie osób z wykształceniem podstawowym -21,6% [17]. W większości prowadzonych w Europie badań dotyczących społeczno-ekonomicznych nierówności w zdrowiu używa się poziomu edukacji jako zmiennej syntetycznej, przyjmując założenie, że inne charakterystyki społeczne, takie jak wykonywany zawód oraz poziom dochodów, są w dużym stopniu wyjaśniane przez róż-nice w poziomie wykształcenia [6,8,9,18].…”

Section: Omówienieunclassified

“…W krajach Europy Północnej i Zachodniej wzrost nierówności był spowodowany wolniejszym tempem spadku współ-czynników umieralności w grupach osób z niższym wykształceniem niż wśród osób z wyższym wykształ-ceniem, natomiast na Litwie i w Estonii nierówności zwiększyły się na skutek rozbieżnych kierunków zmian w umieralności w grupie najlepiej i najgorzej wykształ-conych [18].…”

Section: Omówienieunclassified

Socioeconomic inequalities in mortality due to all causes in the working age population of Poland in 2002 and 2011

Pikala

Maniecka-Bryła

2017

Med Pr

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Educational Attainment and Lifetime Risk of Cardiovascular Disease

Magnani,

Ning,

Wilkins

et al. 2024

JAMA Cardiol

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ImportanceEducation is a social determinant of health. Quantifying its association with lifetime cardiovascular disease (CVD) risk has public health importance.ObjectiveTo calculate lifetime risk estimates of incident CVD and CVD subtypes and estimate years lived with and without CVD by education.Design, Setting, and ParticipantsIncluded community-based cohort studies with adjudicated cardiovascular events used pooled individual-level data from 1985 to 2015 of 6 prospective cohort studies. The study team assessed the association between education and lifetime CVD risk with modified Kaplan-Meier and Cox models accounting for competing risk of noncardiovascular death. The study team estimated years lived with and without CVD by education with the Irwin restricted mean and the utility of adding educational attainment to CVD risk assessment. Participants (baseline 40 to 59 years old and 60 to 79 years old) were without CVD at baseline and had complete education, cardiovascular risk factors, and prospective CVD outcomes data. Data were analyzed from January 2022 to September 2022.ExposuresEducational attainment (less than high school, high school completion, some college, or college graduate).Main outcome and measuresCardiovascular events (fatal and nonfatal coronary heart disease, heart failure, and stroke; CVD-related deaths; and total CVD encompassing any of these events).ResultsThere were 40 998 participants (23 305 female [56.2%]) with a mean (SD) age of 58.1 (9.7) years for males and 58.3 (9.9) years for females. Compared with college graduates, those with less than high school or high school completion had higher lifetime CVD risks. Among middle-aged men, the competing hazard ratios (HRs) for a CVD event were 1.58 (95% CI, 1.38-1.80), 1.30 (95% CI, 1.10-1.46), and 1.16 (95% CI, 1.00-1.34) in those with less than high school, high school, and some college, respectively, compared with those with college completion. Among women, these competing HRs were 1.70 (95% CI, 1.49-1.95), 1.19 (95% CI, 1.05-1.35), and 0.98 (95% CI, 0.83-1.15). Individuals with higher education had longer duration of life prior to incident CVD. Education provided limited contribution toward enhancing CVD risk prediction.Conclusions and relevanceLower education was associated with lifetime CVD risk across adulthood; higher education translated to healthy longevity. Educational policy initiatives may associate with long-term health benefits.

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Trends in inequalities in premature mortality: a study of 3.2 million deaths in 13 European countries

Cited by 216 publications

References 34 publications

The Health Effects of Income Inequality: Averages and Disparities

The Health Effects of Income Inequality: Averages and Disparities

Socioeconomic inequalities in mortality due to all causes in the working age population of Poland in 2002 and 2011

Educational Attainment and Lifetime Risk of Cardiovascular Disease

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