title: Anthropometric reference data for elderly Swedes and its disease-related pattern.
abstract: OBJECTIVE
  Anthropometric measurement is a noninvasive and cost-efficient method for nutritional assessment. The study aims to present age- and gender-specific anthropometric reference data for Swedish elderly in relation to common medical conditions, and also formulate prediction equations for such anthropometric measurements.
  
  
  METHODS
  A cross-sectional study among random heterogeneous sample of 3360 subjects, aged 60-99 years, from a population study 'Good Aging in Scania. Means (±s.d.) and percentiles for height, weight, waist-, hip-, arm-, calf circumferences, triceps- (TST) and subscapular skinfold thickness (SST), body mass index (BMI), waist-hip ratio (WHR) and arm muscle circumference (AMC) were presented. The values were estimated based on the prevalence of myocardial infarction (MI), cardiac failure (CHF), stroke, cognitive impairment, dementia and dependence in daily living activities (ADL). Linear regression analysis was used to formulate the prediction equations.
  
  
  RESULTS
  Mean BMI was 27.5±5.8 kg/m(2) (men) and 27.2±8.1 kg/m(2) (women). WHR was higher among men (Men: 0.98±0.3, women: 0.87±0.2), except at age 85+ (women: 0.91±0.6). TST was 6.7±0.4 mm higher among women. Men with MI had BMI: 28.6±4.8 kg/m(2) and SST: 21±9.2 mm, whereas subjects with dementia had lower weight (by 9.5±2.9 kg) compared with the non-demented. ADL-dependent women had BMI= 29.0±3.9 kg/m(2), TST=19.2±1.3 mm.
  
  
  CONCLUSIONS
  New normative data on gender- and age-specific anthropometrics on the general elderly population are presented. Cardiovascular diseases are associated with subcutaneous and central adiposity opposed to fat loss with dementia. ADL dependence indicates inadequate physical activity. The prediction models could be used as possible indicators monitoring physical activity and adiposity among the general elderly population hence potential health indicators in health promotion.
authors.affiliation: Division of Geriatric Medicine, Department of Health Sciences, Lund University, Skåne University Hospital, Malmö, Sweden.
authors.forename: N N
authors.initials: NN
authors.lastname: Gavriilidou
authors.affiliation: Division of Geriatric Medicine, Department of Health Sciences, Lund University, Skåne University Hospital, Malmö, Sweden.
authors.forename: M
authors.initials: M
authors.lastname: Pihlsgård
authors.affiliation: Division of Geriatric Medicine, Department of Health Sciences, Lund University, Skåne University Hospital, Malmö, Sweden.
authors.forename: S
authors.initials: S
authors.lastname: Elmståhl
mesh_terms: D000203:Activities of Daily Living; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D000886:Anthropometry / Q000379:methods*; D001823:Body Composition; D015992:Body Mass Index; D003072:Cognition Disorders / Q000453:epidemiology; D003430:Cross-Sectional Studies; D003704:Dementia / Q000453:epidemiology; D005260:Female; D006333:Heart Failure / Q000453:epidemiology; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000453:epidemiology; D012016:Reference Values; D017678:Sex Distribution; D020521:Stroke / Q000453:epidemiology; D013548:Sweden / Q000453:epidemiology