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242Exploring health in the UK Biobank: cross-sectional analyses of sociodemographic, psychosocial, lifestyle and environmental factors
Author(s) -
Julian Mutz,
Charlotte Roscoe,
Cathryn M. Lewis
Publication year - 2021
Publication title -
international journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.406
H-Index - 208
eISSN - 1464-3685
pISSN - 0300-5771
DOI - 10.1093/ije/dyab168.468
Subject(s) - psychosocial , loneliness , medicine , biobank , environmental health , gerontology , cross sectional study , body mass index , public health , logistic regression , psychological intervention , demography , psychiatry , sociology , nursing , biology , pathology , genetics
Background Our aim was to examine sociodemographic characteristics, psychosocial factors, lifestyle and environmental exposures associated with health. Methods The UK Biobank recruited >500,000 participants, aged 37-73, between 2006-2010. Data on 81 cancer and 443 non-cancer illnesses were used to classify participants by insurance health status (non-standard risk/standard risk). Long-standing illness (yes/no) and self-rated health (poor/fair/good/excellent) constituted secondary outcomes. Logistic and ordinal regression models were fit to estimate associations between explanatory variables and health. Results 307,378 participants (mean age=56.1; 51.9% female) were selected for cross-sectional analyses. Low household income, high levels of neighbourhood deprivation, being male, loneliness and social isolation were associated with poor health. Walking frequency and engaging in vigorous-intensity physical activity were associated with positive health, whereas long sleep duration, high body mass index and smoking were associated with poor health. Alcohol intake less frequent than 1-2 times per week was associated with poor health. There was some evidence that high levels of airborne pollutants (PM2.5, PM10 and NO2) and noise (Lden) were associated with poor health, although findings were inconsistent once other factors had been adjusted for. Neighbourhood greenspace was associated with positive self-rated health. Conclusions Public health could put greater focus on non-medical factors such as loneliness, further encourage healthy lifestyle behaviours and weight management, and examine efforts to improve health outcomes of individuals in the lowest income groups. Key message Multiple sociodemographic, psychosocial, lifestyle and environmental factors are associated with health.

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