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Contribution title Independent association between socioeconomic status indicators and macro and micronutrients intake in Switzerland
  1. Carlos de Mestral Institut universitaire de médecine sociale et préventive (CHUV&UNIL) Presenter
  2. Pedro Marques-Vidal
  3. Jean-Michel Gaspoz
  4. Jean-Marc Theler
  5. Idris Guessous
Form of presentation Poster
  • Public health
Abstract Background: Socioeconomic differences in diet are rarely assessed with more than one indicator. We aimed to assess differences in macro- and micro-nutrient intake in both sexes according to education, income, and occupation.

Methods: We used data from validated food frequency questionnaire measured dietary intake in 5087 participants (2157 women) from yearly adult population-based cross-sectional surveys conducted from 2005 to 2012 in the canton of Geneva, Switzerland. We used two ANOVA models: age-adjusted and multivariable adjusted simultaneously for all three socioeconomic indicators.

Results: Low-education men consumed more calcium but less vitamin D than high-education men; low-income men consumed less total and animal protein (80.9±0.9 vs 84.0±0.6 g/d; 55.6±1.0 vs 59.5±0.7 g/d) and more total carbohydrates and sugars (246±2 vs 235±2 g/d; 108±2 vs 103±1 g/d) than high-income men. Occupation and diet showed no association. Low-education women consumed less vegetable protein (20.7±0.2 vs 21.6±0.2 g/d), fibre (15.7±0.3 vs 16.8±0.2 g/d), and carotene (4222±158 vs 4870±128 µg/d) than high-education women; low-income women consumed more total carbohydrates (206±2 vs 197±1 g/d) and less monounsaturated fat (27.7±0.4 vs 29.3±0.3 g/d) than high-income women. Finally, low-occupation women consumed more total energy (1792±27 vs 1714±15 kcal/d) and total carbohydrates (206±2 vs 200±1 g/d), but less saturated fat (23.0±0.3 vs 24.4±0.2 g/d), calcium (935±17 vs 997±10 mg/d) and vitamin D (2.5±0.1 vs 2.9±0.1 µg/d), than high-occupation women.

Conclusion: In Switzerland, the influence of socioeconomic factors on nutrient intake differs by sex; income and education, but not occupation, drive differences among men; among women, all three indicators seem to play a role. Interventions to reduce inequalities should consider the influence of education, income, and occupation in diet to be most effective.