title: Predicting adult metabolic syndrome from childhood body mass index: follow-up of the New Delhi birth cohort.
abstract: OBJECTIVE
  To assess whether serial measurements of childhood body mass index (BMI) give clinically useful predictions of the risk of developing adult metabolic syndrome and impaired glucose tolerance or type 2 diabetes.
  
  
  METHODS
  Follow-up of a community-based birth cohort in Delhi, India.
  
  
  METHODS
  1492 men and women aged 26-32 years whose BMI was recorded 6-monthly throughout childhood.
  
  
  METHODS
  The predictive value of childhood BMI for adult metabolic syndrome and impaired glucose tolerance (IGT) and diabetes mellitus.
  
  
  RESULTS
  25% of subjects had metabolic syndrome and 15% had IGT/diabetes mellitus. Both outcomes were associated with greater childhood BMI gain (metabolic syndrome: OR 1.63 (95% CI 1.44 to 1.85); IGT/diabetes mellitus: 1.39 (1.20 to 1.60) per unit increase in within-cohort BMI SD score between 5 and 14 years). The best predictions of adult disease were obtained using a combined test comprising (i) any increase in BMI SD score between 5 and 14 years and (ii) a BMI SD score >0 at 14 years (metabolic syndrome: sensitivity 45%, specificity 78%; IGT/diabetes mellitus: 37%, 73%). Likelihood ratios were low (metabolic syndrome: 1.4-2.0; IGT/diabetes mellitus: 1.2-1.4). A single high BMI measurement at 14 years (overweight or obese, according to International Obesity Task Force criteria) was highly specific but insensitive (metabolic syndrome: sensitivity 7%, specificity 97%; IGT/diabetes mellitus: 8%, 97%). Charts for plotting BMI SD scores through childhood were produced.
  
  
  CONCLUSIONS
  Serial measurements of childhood BMI give useful predictions of adult risk and could guide advice to children and parents on preventing later disease.
authors.affiliation: Department of Paediatrics, Sitaram Bhartia Institute of Science and Research, New Delhi, India. hpssachdev@gmail.com
authors.forename: H P S
authors.initials: HP
authors.lastname: Sachdev
authors.forename: C
authors.initials: C
authors.lastname: Osmond
authors.forename: C H D
authors.initials: CH
authors.lastname: Fall
authors.forename: R
authors.initials: R
authors.lastname: Lakshmy
authors.forename: S
authors.initials: S
authors.lastname: Ramji
authors.forename: S K
authors.initials: SK
authors.lastname: Dey Biswas
authors.forename: D
authors.initials: D
authors.lastname: Prabhakaran
authors.forename: N
authors.initials: N
authors.lastname: Tandon
authors.forename: K S
authors.initials: KS
authors.lastname: Reddy
authors.forename: D J P
authors.initials: DJ
authors.lastname: Barker
authors.forename: S K
authors.initials: SK
authors.lastname: Bhargava
mesh_terms: D000328:Adult; D000375:Aging / Q000502:physiology; D000886:Anthropometry / Q000379:methods; D015992:Body Mass Index; D003906:Developing Countries; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology / Q000209:etiology / Q000503:physiopathology; D004812:Epidemiologic Methods; D005260:Female; D018149:Glucose Intolerance / Q000453:epidemiology / Q000209:etiology / Q000503:physiopathology; D006801:Humans; D007194:India / Q000453:epidemiology; D007231:Infant, Newborn; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology / Q000209:etiology* / Q000503:physiopathology; D009765:Obesity / Q000150:complications / Q000453:epidemiology / Q000503:physiopathology; D011379:Prognosis; D015430:Weight Gain / Q000502:physiology