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Fruit and vegetable consumption and its contribution to inequalities in life expectancy and disability-free life expectancy in ten European countries.


ABSTRACT: OBJECTIVES:To assess to what extent educational differences in total life expectancy (TLE) and disability-free life expectancy (DFLE) could be reduced by improving fruit and vegetable consumption in ten European countries. METHODS:Data from national census or registries with mortality follow-up, EU-SILC, and ESS were used in two scenarios to calculate the impact: the upward levelling scenario (exposure in low educated equals exposure in high educated) and the elimination scenario (no exposure in both groups). Results are estimated for men and women between ages 35 and 79 years. RESULTS:Varying by country, upward levelling reduced inequalities in DFLE by 0.1-1.1 years (1-10%) in males, and by 0.0-1.3 years (0-18%) in females. Eliminating exposure reduced inequalities in DFLE between 0.6 and 1.7 years for males (6-15%), and between 0.1 years and 1.8 years for females (3-20%). CONCLUSIONS:Upward levelling of fruit and vegetable consumption would have a small, positive effect on both TLE and DFLE, and could potentially reduce inequalities in TLE and DFLE.

SUBMITTER: Baars AE 

PROVIDER: S-EPMC6614160 | biostudies-other | 2019 Jul

REPOSITORIES: biostudies-other

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Fruit and vegetable consumption and its contribution to inequalities in life expectancy and disability-free life expectancy in ten European countries.

Baars Adája E AE   Rubio-Valverde Jose R JR   Hu Yannan Y   Bopp Matthias M   Brønnum-Hansen Henrik H   Kalediene Ramune R   Leinsalu Mall M   Martikainen Pekka P   Regidor Enrique E   White Chris C   Wojtyniak Bogdan B   Mackenbach Johan P JP   Nusselder Wilma J WJ  

International journal of public health 20190611 6


<h4>Objectives</h4>To assess to what extent educational differences in total life expectancy (TLE) and disability-free life expectancy (DFLE) could be reduced by improving fruit and vegetable consumption in ten European countries.<h4>Methods</h4>Data from national census or registries with mortality follow-up, EU-SILC, and ESS were used in two scenarios to calculate the impact: the upward levelling scenario (exposure in low educated equals exposure in high educated) and the elimination scenario  ...[more]

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