• Deriving the Dietary Approaches to Stop Hypertension (DASH) Score in Women from Seven Pregnancy Cohorts from the European ALPHABET Consortium.

      Aubert, Adrien M; Forhan, Anne; de Lauzon-Guillain, Blandine; Chen, Ling-Wei; Polanska, Kinga; Hanke, Wojciech; Jankowska, Agnieszka; Mensink-Bout, Sara M; Duijts, Liesbeth; Suderman, Matthew; et al. (2019-11-08)
      The ALPHABET consortium aims to examine the interplays between maternal diet quality, epigenetics and offspring health in seven pregnancy/birth cohorts from five European countries. We aimed to use the Dietary Approaches to Stop Hypertension (DASH) score to assess diet quality, but different versions have been published. To derive a single DASH score allowing cross-country, cross-cohort and cross-period comparison and limiting data heterogeneity within the ALPHABET consortium, we harmonised food frequency questionnaire (FFQ) data collected before and during pregnancy in ≥26,500 women. Although FFQs differed strongly in length and content, we derived a consortium DASH score composed of eight food components by combining the prescriptive original DASH and the DASH described by Fung et al. Statistical issues tied to the nature of the FFQs led us to re-classify two food groups (grains and dairy products). Most DASH food components exhibited pronounced between-cohort variability, including non-full-fat dairy products (median intake ranging from 0.1 to 2.2 servings/day), sugar-sweetened beverages/sweets/added sugars (0.3–1.7 servings/day), fruits (1.1–3.1 servings/day), and vegetables (1.5–3.6 servings/day). We successfully developed a harmonized DASH score adapted to all cohorts being part of the ALPHABET consortium. This methodological work may benefit other research teams in adapting the DASH to their study’s specificities.
    • Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.

      Carreras-Torres, Robert; Johansson, Mattias; Haycock, Philip C; Wade, Kaitlin H; Relton, Caroline L; Martin, Richard M; Davey Smith, George; Albanes, Demetrius; Aldrich, Melinda C; Andrew, Angeline; et al. (2017)
      Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer.