Longitudinal study of variation in body mass index in middle-aged UK females

Gregory Livshits, Ida Malkin, Frances M.K. Williams, Deborah J. Hart, Alan Hakim, Timothy D. Spector

Research output: Contribution to journalArticlepeer-review

Abstract

The importance of changing patterns of obesity in society and its implications for public health are well recognized. However, the adult life course of body mass index (BMI) changes in individuals over time is largely unknown and has mostly been extrapolated from cross-sectional studies. The present study examines individual specific variation of BMI during a 15-year follow-up period in a community-based sample of UK females. We attempted to establish whether there is a common, generalized pattern which captures variation in BMI over time. The participants of this study belong to a prospective population cohort of British women studied intensively since 1989: the Chingford Study. The sample originally consisted of 1,003 women aged 45-68 years, who were assessed annually for BMI during follow-up period. Polynomial regression models were used to assess longitudinal BMI variation. We observed a great stability in individual BMI variation during the followup period, reflected by high correlations between the baseline BMI and follow-up BMI 10 and 15 years later (r=0.876, N=810, and r=0.824, N=638, respectively). We also found that three different major age-related patterns in BMI could be clearly identified: no change in 30.6% in 58% it increased and in 11.4% it decreased with age. Thus, our data suggest that individual agerelated changes in BMI are very different. Therefore, simply combining all individuals into groups by any other criteria (age, sex, etc.) and overlooking the distinctive patterns of BMI change may lead to biased inferences in epidemiologic and etiologic research of the future.

Original languageEnglish
Pages (from-to)1285-1294
Number of pages10
JournalAge
Volume34
Issue number5
DOIs
StatePublished - Oct 2012

Keywords

  • Agedependent patterns
  • BMI
  • Curve fitting
  • Follow-up
  • Longitudinal
  • Weight gain

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