79 A Life Course Approach to Standing Balance: Risk Factors Across Life

Abstract

Abstract Introduction Poor balance ability in mid and later life is associated with increased risk of adverse health outcomes. Understanding what factors across life contribute to balance ability in the ageing population is important in order to prevent, delay or minimise balance decline. Our aim was to identify socioeconomic indicators, health behaviours, health status indicators and cognition that are associated with balance and identify how these associations varied by age and sex. Methods Data from the MRC National Survey of Health and Development, a British birth cohort study, were utilised (n=3111). Multilevel models examined associations between twelve different factors across life (maternal education, paternal occupational class, education, own occupational class, physical activity, smoking, diabetes, respiratory symptoms, cardiovascular events, knee pain, depression and verbal memory) and one-legged standing balance (assessed at ages 53, 60-64 and 69). Results Men had better balance than women at age 53 (b=18.8% (95%CI: 13.6, 23.9), although this difference decreased with age (11.8% at age 60-64 and 7.6% at age 69). Low socioeconomic position, poor health behaviours, poor health status and lower cognition were associated with poorer balance at all three ages. For example, those from the lowest paternal occupational class had 29.6% (95% CI: 22.2, 38.8%) worse balance than those from the highest class. There were no sex differences in patterns of associations. Associations of balance with socioeconomic indicators, cognition and physical activity got smaller with age, while the associations with knee pain and depression increased. Discussion Factors across life that contribute to balance are multifaceted and complex. A multifactorial intervention to minimise balance decline and falls could be more appropriate than a single factor approach. Due to different patterns of association with age (i.e. knee pain or depression), different factors should be targeted depending on age.