Aim: Driving is a common type of sedentary behaviour and an independent risk factor for poor health. In this study, we explored whether driving was also associated with other unhealthy lifestyle factors. Methods: In a cross-sectional study of UK Biobank participants, driving time was treated as an ordinal variable and other lifestyle factors split into low/high risk based on guidelines. The associations were explored using chi-square tests for trend and binary logistic regression.
Results: Of the 386,493 participants who drove, 153,717 (39.8%) drove <1 hour/day; 140,140 (36.3%) 1 hour/day; 60,973 (15.8%) 2 hours/day; and 31,663 (8.2%) =3 hours/day. When we adjusted for potential confounders, driving =3 hours/day was associated with being overweight/obese (OR 1.74, 95% CI 1.64-1.85), smoking (OR 1.48, 95% CI 1.37-1.63), insufficient sleep (1.70, 95% CI 1.61-1.80), low fruit/vegetable intake (OR 1.26, 95% CI 1.18-1.35) and low physical activity (OR 1.05, 95% CI 1.00-1.11), with dose relationships for the first three, but was not associated with higher alcohol consumption (OR 0.94, 95% CI 0.87-1.02). Conclusions. Sedentary behaviour, such as driving, is known to have an independent association with adverse health outcomes. Additionally, it may have an impact on other aspects of lifestyle. This study suggests that people with long driving times are at higher risk and might benefit from targeted interventions.
Epidemiology of mental health, cognitive function, pain and cardiometabolic disease.
Mental health problems place a large burden on the health service. As life expectancy increases, understanding cognitive decline is increasingly important. Identifying high risk groups enables us to detect problems early and target resources. Understanding the distribution of disease between groups can help elucidate the causes of disease and help identify new methods of prevention and treatment.
Aim: To study the epidemiology of mental health, cognitive function, pain and cardiometabolic disease.
Objectives: To examine the frequency, distribution, determinants and outcomes of these conditions, in relation to: demographics, lifestyle, comorbidity and medication UKB is representative of the general population in terms of age, sex and ethnicity but unrepresentative in terms of lifestyle. Therefore, it is not suitable to determine the overall prevalence of any condition but can, nonetheless, be used to compare the distribution of diseases between sub-groups and therefore determine associations between risk factors and disease frequency and outcome. This project builds on our ongoing study (774) which examines ethnic differences in cardiometabolic disease. We seek to extend the focus to examine other determinants of cardiometabolic disease as well as determinants of mood disorder, cognitive impairment and pain. We will compare participants with and without mood disorder, pain, cognitive impairment and cardiometabolic diease and participants with varying severity of these conditions in relation to a series of demographic and lifestyle factors in order to determine the factors associated with the conditions. We will also examine the association between these conditions and other diseases. The findings will help to identify individual at increased risk and modifiable factors that may help to prevent or alleviate these conditions. all participants
|Lead investigator:||Professor Jill Pell|
|Lead institution:||University of Glasgow|
15 related Returns
|Return ID||App ID||Description||Archive Date|
|1681||7155||Association of Body Mass Index With Cardiometabolic Disease in the UK Biobank: A Mendelian Randomization Study||29 Jul 2019|
|3267||7155||Association of injury related hospital admissions with commuting by bicycle in the UK: prospective population based study||31 Mar 2021|
|1846||7155||Associations Between Diabetes and Both Cardiovascular Disease and All-Cause Mortality Are Modified by Grip Strength: Evidence From UK Biobank, a Prospective Population-Based Cohort Study||2 Dec 2019|
|1480||7155||Associations between active commuting and incident cardiovascular disease, cancer and mortality: prospective cohort study||5 Jul 2018|
|1843||7155||Associations of discretionary screen time with mortality, cardiovascular disease and cancer are attenuated by strength, fitness and physical activity: findings from the UK Biobank||2 Dec 2019|
|1842||7155||Associations of grip strength with cardiovascular, respiratory, and cancer outcomes and all cause mortality: prospective cohort study of half a million UK Biobank participants||2 Dec 2019|
|3376||7155||BMI and future risk for COVID-19 infection and death across sex, age and ethnicity: Preliminary findings from UK biobank||23 Apr 2021|
|1683||7155||Cannabis use and risk of schizophrenia: a Medelian randomization study||29 Jul 2019|
|3721||7155||Child maltreatment and cardiovascular disease quantifying mediation pathways using UK Biobank||2 Aug 2021|
|1476||7155||Chronic multisite pain in major depression and bipolar disorder: cross-sectional study of 149, 611 participants in UK Biobank||5 Jul 2018|
|2830||7155||Impact of major depression on cardiovascular outcomes for individuals with hypertension: prospective survival analysis in UK Biobank||18 Nov 2020|
|1682||7155||PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study||29 Jul 2019|
|1781||7155||Red and processed meat consumption and breast cancer: UK Biobank cohort study and meta-analysis||30 Sep 2019|
|3675||7155||Vitamin D and COVID-19 infection and mortality in UK Biobank||27 Jul 2021|
|3674||7155||Vitamin D concentrations and COVID-19 infection in UK Biobank||27 Jul 2021|
|2859||The association between driving time and unhealthy lifestyles: a cross-sectional, general population study of 386 493 UK Biobank participants||Mackay A et al.||2019||J Public Health (Oxf)|