Poster Presentation Australian & New Zealand Obesity Society 2014 Annual Scientific Meeting

Age specific changes in BMI and BMI distribution among Australian adults using cross-sectional surveys from 1980 to 2008 (#231)

Alison Hayes 1 , Emma Gearon 2 3 , Kathryn Backholer 2 3 , Adrian Baumann 1 , Anna Peeters 2 3
  1. School of Public Health, University of Sydney, Sydney, NSW, Australia
  2. Baker IDI Heart and Diabetes Institute, Melbourne
  3. School of Public Health and Preventative Medicine , Monash University, Melbourne

Background: Research efforts globally have focused mainly on trends in obesity or overweight among populations, or changes in mean body mass index (BMI), without consideration of changes in BMI across the BMI spectrum.
Methods: Using a synthetic cohort approach (which matches members of cross-sectional surveys by birth year) we estimated nationally representative longitudinal BMI change in two time periods (1980 to 1989 and 1995 to 2008) by age, sex, socio-economic position and BMI quantiles. Our study population comprised 27349 participants from four Australian health surveys: the Risk Factor Prevalence Study surveys (1980 and 1989), the 1995 National Nutrition Survey and the 2007/8 National Health Survey.
Results: We found greater mean BMI increases in younger people, in those already overweight and in those with lower education. Between the 1980s and the early 2000s there was no evidence of a period effect in mean annual BMI gain among men (p=0.39) but a slowing down of annual BMI gain for older women (p<0.05). BMI change was not uniform across the BMI distribution, with different patterns by age and sex in different periods. For young adults there was greater BMI gain at higher BMI quantiles, thus adding to the increased right skew in BMI, whilst BMI gain for older adults was more even across the BMI distribution.
0>Conclusions: The synthetic cohort technique provided useful information from cross-sectional survey data and highlighted the importance of elucidating BMI changes across the entire BMI spectrum, as changes in mean BMI do not tell the full picture. The quantification of annual BMI change has contributed to understanding the epidemiology of obesity progression and identified key target groups for policy attention - young adults, the already overweight and those of lower socioeconomic status. The information may also be used in population models to project trajectories of BMI over time.