4.8 Article

Exploring health in the UK Biobank: associations with sociodemographic characteristics, psychosocial factors, lifestyle and environmental exposures

Journal

BMC MEDICINE
Volume 19, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12916-021-02097-z

Keywords

Health status; Self-rated health; Long-standing illness; Lifestyle; Environmental exposures; Sociodemographic characteristics; Psychosocial factors; UK Biobank; Epidemiology; Public health

Funding

  1. Biotechnology and Biological Sciences Research Council (BBSRC) [2050702]
  2. Eli Lilly and Company Limited
  3. National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London
  4. BBSRC [2050702] Funding Source: UKRI

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This study examined factors associated with health indicators using data from over 500,000 participants in the UK Biobank. It found that factors such as low income, male gender, neighborhood deprivation, loneliness, social isolation, sleep duration, BMI, and smoking were associated with poor health, while walking, vigorous physical activity, and more frequent alcohol intake were associated with good health. Additionally, there was some evidence of a link between airborne pollutants and noise with poor health outcomes.
Background A greater understanding of the factors that are associated with favourable health may help increase longevity and healthy life expectancy. We examined sociodemographic, psychosocial, lifestyle and environmental exposures associated with multiple health indicators. Methods UK Biobank recruited > 500,000 participants, aged 37-73, between 2006 and 2010. Health indicators examined were 81 cancer and 443 non-cancer illnesses used to classify participants' health status; long-standing illness; and self-rated health. Exposures were sociodemographic (age, sex, ethnicity, education, income and deprivation), psychosocial (loneliness and social isolation), lifestyle (smoking, alcohol intake, sleep duration, BMI, physical activity and stair climbing) and environmental (air pollution, noise and residential greenspace) factors. Associations were estimated using logistic and ordinal logistic regression. Results In total, 307,378 participants (mean age = 56.1 years [SD = 8.07], 51.9% female) were selected for cross-sectional analyses. Low income, being male, neighbourhood deprivation, loneliness, social isolation, short or long sleep duration, low or high BMI and smoking were associated with poor health. Walking, vigorous-intensity physical activity and more frequent alcohol intake were associated with good health. There was some evidence that airborne pollutants (PM2.5, PM10 and NO2) and noise (L-den) were associated with poor health, though findings were not consistent across all models. Conclusions 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 the health outcomes of individuals on low incomes.

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