A greater understanding of factors associated with good health may help increase longevity and healthy life expectancy. Here we report associations between multiple health indicators and sociodemographic (age, sex, ethnicity, education, income and deprivation), psychosocial (loneliness and social isolation), lifestyle (smoking, alcohol intake, sleep, BMI, physical activity and stair climbing) and environmental (air pollution, noise and greenspace) factors, using data from 307,378 UK Biobank participants. Low income, being male, neighbourhood deprivation, loneliness, social isolation, short or long sleep duration, low or high BMI and smoking was associated with poor health. Walking, vigorous-intensity physical activity and more frequent alcohol intake was associated with good health. There was some evidence that airborne pollutants (PM
2.5</p>, PM10, and NO2) and noise (Lden) were associated with poor health, though findings were inconsistent in adjusted models. Our findings highlight the multifactorial nature of health, the importance of non-medical factors, such as loneliness, healthy lifestyle behaviours and weight management, and the need to examine efforts to improve health outcomes of individuals with low income.
Exploring predictors of healthy ageing in UK Biobank
Substantial improvements in human health and significant increases in life expectancy are amongst the main achievements of civilization in the 20th and 21st centuries. However, many people spend a significant part of their lives suffering from age-related illness and experience decreased levels of normal functioning which is often associated with lower quality of life. To increase our understanding of the processes and mechanisms that are associated with good health outcomes in old age, this research will investigate some of the key environmental risk factors, lifestyle and the biology underlying healthy ageing. Moreover, we will examine ageing trajectories in individuals diagnosed with common mental illnesses such as depression and in chronic pain as previous research has shown that individuals with these diagnoses have higher rates of morbidity and mortality. Facing up to the global challenges of an ageing population is one of today's most important undertakings and the UK Biobank cohort provides an unprecedented data resource to investigate how people age. We will incorporate data from the baseline assessment and follow-up data that are available through record linkage and repeat assessments. All available data relating to the variables of interest for the full cohort will be analysed using appropriate statistical and machine learning methods. We anticipate a project duration of 36 months. The findings of our research will inform public health policy aimed at promoting health in later life.
|Lead investigator:||Julian Mutz|
|Lead institution:||King's College London|