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PP33 A N Age-Period-Cohort Analysis for Trends in Body Mass Index in the Republic of Ireland in 18,016 Participants in Slan (Surveys of Lifestyle, Attitudes and Nutrition) 1998-2007
  1. Jiang T1,
  2. M S Gilthorpe1,
  3. F Shiely2,
  4. J Harrington2,
  5. I J Perry2,
  6. C C Kelleher3,
  7. Y K Tu4
  1. 1Division of Biostatistics, University of Leeds, Leeds, UK
  2. 2Department of Epidemiology and Public Health, University College Cork, Cork, Republic of Ireland
  3. 3School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Republic of Ireland
  4. 4Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan

Abstract

Background Obesity has increased in prevalence worldwide in the last 20 years and is associated with a variety of adverse health outcomes. It is valuable to examine these trends in relation to age, period and birth cohort, in conjunction with several evolving environmental factors. Age-period-cohort (APC) analysis is a popular analytic approach, since knowing the separate effects of age, period and cohort allows for a better understanding of the different risk groups based on age and generation cohort, separately, and cohort effects can identify individuals who are particularly at high risk of obesity, to allow for effective public intervention measures.

Methods Data were obtained in the Republic of Ireland via three consecutive waves of the Surveys of Lifestyle, Attitudes and Nutrition (SLAN), all of which are now publicly available. Data were collected in 1998, 2002 and 2007 through standardised protocols. Participants with missing values were excluded from the analyses. Those over the age of 75 were excluded due to sparse data. Of the original 22,895 participants, we performed analyses on 18,016 participants: 7,796 men and 10,220 women. We applied partial least squares (PLS) methodology to estimate the separate effects of age, period and cohort on the trends in obesity as measured by body mass index (BMI). We also explore and model nonlinear relationships of BMI with age, period and cohort.

Results PLS analysis revealed a positive period effect. Additionally, men born later tended to have lower BMI (-0.026 kgm-2yr-1 [95% CI -0.030, -0.024]) and older men had in general higher BMI (-0.029 kgm-2yr-1 [-0.026, -0.033]) Similarly for women, those born later had lower BMI (-0.025 kgm-2yr-1 [-0.029, -0.022]) and older women in general had higher BMI (0.029 kgm-2yr-1 [0.022, 0.033]) Nonlinear analyses revealed that BMI has a substantial curvilinear relationship with age, though less so with birth cohort.

Discussion Through the use of PLS we are able to estimate the separate contributions to obesity of age, period and cohort. Consequently, PLS produces more interpretable results than other approaches. Men and women born in Ireland during the period 1924-1989 experienced a steady increase in BMI by year of age, which became more pronounced throughout the study period, mitigated only slightly by improved maternal nutrition of successive cohorts, which would potentially have given rise to better ‘programming’ of children in preparation for an increasingly obesogenic environment experienced in childhood and adulthood.

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