title: Does overall diet in midlife predict future aging phenotypes? A cohort study.
abstract: BACKGROUND
  The impact of diet on specific age-related diseases has been studied extensively, but few investigations have adopted a more holistic approach to determine the association of diet with overall health at older ages. We examined whether diet, assessed in midlife, using dietary patterns and adherence to the Alternative Healthy Eating Index (AHEI), is associated with aging phenotypes, identified after a mean 16-year follow-up.
  
  
  METHODS
  Data were drawn from the Whitehall II cohort study of 5350 adults (age 51.3±5.3 years, 29.4% women). Diet was assessed at baseline (1991-1993). Mortality, chronic diseases, and functioning were ascertained from hospital data, register linkage, and screenings every 5 years and were used to create 5 outcomes at follow-up: ideal aging (free of chronic conditions and high performance in physical, mental, and cognitive functioning tests; 4%), nonfatal cardiovascular event (12.7%), cardiovascular death (2.8%), noncardiovascular death (7.3%), [corrected] and normal aging (73.2%).
  
  
  RESULTS
  Low adherence to the AHEI was associated with an increased risk of cardiovascular and noncardiovascular death. In addition, participants with a "Western-type" diet (characterized by high intakes of fried and sweet food, processed food and red meat, refined grains, and high-fat dairy products) had lower odds of ideal aging (odds ratio for top vs bottom tertile: 0.58; 95% confidence interval, 0.36-0.94; P=.02), independently of other health behaviors.
  
  
  CONCLUSIONS
  By considering healthy aging as a composite of cardiovascular, metabolic, musculoskeletal, respiratory, mental, and cognitive function, the present study offers a new perspective on the impact of diet on aging phenotypes.
authors.affiliation: Department of Epidemiology and Public Health, University College London, London, UK. tasnime.akbaraly@inserm.fr
authors.forename: Tasnime
authors.initials: T
authors.lastname: Akbaraly
authors.forename: Séverine
authors.initials: S
authors.lastname: Sabia
authors.forename: Gareth
authors.initials: G
authors.lastname: Hagger-Johnson
authors.forename: Adam G
authors.initials: AG
authors.lastname: Tabak
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Shipley
authors.forename: Markus
authors.initials: M
authors.lastname: Jokela
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Brunner
authors.forename: Mark
authors.initials: M
authors.lastname: Hamer
authors.forename: G David
authors.initials: GD
authors.lastname: Batty
authors.forename: Archana
authors.initials: A
authors.lastname: Singh-Manoux
authors.forename: Mika
authors.initials: M
authors.lastname: Kivimaki
mesh_terms: D000328:Adult; D000368:Aged; D000375:Aging; D002318:Cardiovascular Diseases / Q000401:mortality*; D015331:Cohort Studies; D004032:Diet; D005247:Feeding Behavior; D005260:Female; D005500:Follow-Up Studies; D015438:Health Behavior; D006801:Humans; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D010349:Patient Compliance; D010641:Phenotype; D012306:Risk