The effect of socioeconomic deprivation on the associationbetween an extended measurement of unhealthy lifestylefactors and health outcomes: a prospective analysis of theUK Biobank cohort
Hamish M E Foster*, Carlos A Celis-Morales*, Barbara I Nicholl, Fanny Petermann-Rocha, Jill P Pell, Jason M R Gill†, Catherine A O’Donnell†,
Frances S Mair†
Summary
Background Combinations of lifestyle factors interact to increase mortality. Combinations of traditional factors such
as smoking and alcohol are well described, but the additional effects of emerging factors such as television viewing
time are not. The effect of socioeconomic deprivation on these extended lifestyle risks also remains unclear. We
aimed to examine whether deprivation modifies the association between an extended score of lifestyle-related risk
factors and health outcomes.
Methods Data for this prospective analysis were sourced from the UK Biobank, a prospective population-based cohort
study. We assigned all participants an extended lifestyle score, with 1 point for each unhealthy lifestyle factor
(incorporating sleep duration and high television viewing time, in addition to smoking, excessive alcohol, poor diet
[low intake of oily fish or fruits and vegetables, and high intake of red meat or processed meats], and low physical
activity), categorised as most healthy (score 0–2), moderately healthy (score 3–5), or least healthy (score 6–9).
Cox proportional hazards models were used to examine the association between lifestyle score and health outcomes
(all-cause mortality and cardiovascular disease mortality and incidence), and whether this association was modified
by deprivation. All analyses were landmark analyses, in which participants were excluded if they had an event (death
or cardiovascular disease event) within 2 years of recruitment. Participants with non-communicable diseases (except
hypertension) and missing covariate data were excluded from analyses. Participants were also excluded if they
reported implausible values for physical activity, sleep duration, and total screen time. All analyses were adjusted for
age, sex, ethnicity, month of assessment, history of hypertension, systolic blood pressure, medication for
hypercholesterolaemia or hypertension, and body-mass index categories/.../
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