title: Dietary factors associated with metabolic risk score in Finnish children aged 6-8 years: the PANIC study.
abstract: OBJECTIVE
  Previous evidence for the associations of eating frequency and food consumption with clustering of metabolic risk factors among children is limited. We therefore investigated association of the daily number of main meals and snacks and food consumption with a metabolic risk score and individual metabolic risk factors in primary school children.
  
  
  METHODS
  The subjects were a population sample of Finnish girls and boys 6-8 years of age. Dietary factors were measured by a four-day food record. Metabolic risk score was calculated summing up the Z-scores of waist circumference, systolic and diastolic blood pressure, and concentrations of fasting serum insulin and fasting plasma glucose, triglycerides and high-density lipoprotein cholesterol, the latest multiplying by -1.
  
  
  RESULTS
  Skipping main meals (standardized regression coefficient β = -0.18, P < 0.001), a higher consumption of non-root vegetables (β = 0.18, P < 0.01), low-fat vegetable-oil-based margarine (β = 0.13, P < 0.01) and sugar-sweetened beverages (β = 0.11, P < 0.05) and a lower consumption of vegetable oils (β = -0.10, P < 0.05) were associated with a higher metabolic risk score after adjustment for age, sex, total physical activity, electronic media time, energy intake and other dietary factors. The consumption of red meat was directly related to the metabolic risk score, but the association was not statistically significant after adjustment for energy intake.
  
  
  CONCLUSIONS
  Eating main meals regularly, decreasing the consumption of sugar-sweetened beverages and low-fat margarine and increasing the consumption of vegetable oils should be emphasized to reduce metabolic risk among children.
authors.affiliation: Physiology, Institute of Biomedicine, University of Eastern Finland, PO Box 1627, 70211, Kuopio, Finland, aino-maija.eloranta@uef.fi.
authors.forename: A M
authors.initials: AM
authors.lastname: Eloranta
authors.forename: V
authors.initials: V
authors.lastname: Lindi
authors.forename: U
authors.initials: U
authors.lastname: Schwab
authors.forename: S
authors.initials: S
authors.lastname: Kiiskinen
authors.forename: T
authors.initials: T
authors.lastname: Venäläinen
authors.forename: H M
authors.initials: HM
authors.lastname: Lakka
authors.forename: D E
authors.initials: DE
authors.lastname: Laaksonen
authors.forename: T A
authors.initials: TA
authors.lastname: Lakka
mesh_terms: D001628:Beverages; D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure / Q000502:physiology; D001823:Body Composition; D002648:Child; D008078:Cholesterol, LDL / Q000097:blood; D003430:Cross-Sectional Studies; D004040:Dietary Carbohydrates / Q000032:analysis; D002149:Energy Intake; D005215:Fasting; D005247:Feeding Behavior; D005260:Female; D005387:Finland; D006801:Humans; D007328:Insulin / Q000097:blood; D016014:Linear Models; D008075:Lipoproteins, HDL / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000517:prevention & control*; D009043:Motor Activity; D015596:Nutrition Assessment; D012307:Risk Factors; D014280:Triglycerides / Q000097:blood; D014675:Vegetables; D055105:Waist Circumference; D044465:White People
chemical_list: D001786:Blood Glucose; D008078:Cholesterol, LDL; D004040:Dietary Carbohydrates; D007328:Insulin; D008075:Lipoproteins, HDL; D014280:Triglycerides