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Much of what is known about childhood clusters of cardiovascular disease behavioural risk factors (RFs) comes from cross-sectional studies, providing little insight into the long-term health impacts of different behavioural cluster profiles. This study aimed to establish the longitudinal relationship between cluster patterns of childhood behavioural RFs and adult cardio-metabolic RFs. Data were from an Australian prospective cohort study of 1265 participants measured in 1985 (ages 9-15 yrs), and in 2004-06 (ages 26-36 yrs). At baseline, children self-reported smoking status, alcohol consumption, physical activity (PA), dietary behaviour and psychological well-being. At follow-up, participants completed questionnaires and attended study clinics where the following component indicators of the metabolic syndrome (MetS) score were measured: waist circumference, blood pressure, fasting blood glucose and lipids. TwoStep cluster analyses were carried out to identify clusters in childhood. Linear regression was used to examine the longitudinal associations between cluster patterns of childhood behavioural RFs and adult cardio-metabolic RFs. Four childhood cluster patterns of behavioural RFs labelled 'most healthy', 'high PA', 'most unhealthy', and 'breakfast skippers' were identified. The unhealthier childhood clusters predicted a significantly higher adult MetS score ('most unhealthy': β = 0.10, 95%CI = 0.01, 0.19) and adult waist circumference ('most unhealthy': β = 2.29, 95%CI = 0.90, 6.67; 'breakfast skippers': β = 2.15, 95%CI = 0.30, 4.00). These associations were independent of adult behavioural RFs and socio-economic position. These findings emphasise the impact of multiple childhood behavioural RFs on important adult health outcomes and may be useful for the development of early intervention strategies, where identification of children at higher risk of poorer adult cardio-metabolic health is vital.

Original publication

DOI

10.1016/j.ypmed.2019.105861

Type

Journal article

Journal

Prev Med

Publication Date

22/10/2019

Volume

130

Keywords

Cardio-metabolic risk, Cluster analysis, Metabolic syndrome, Prevention, Young adulthood, Youth