| Application: | 7155, Epidemiology of mental health, cognitive function, pain and cardiometabolic disease. |
| Title: | The association between driving time and unhealthy lifestyles: a cross-sectional, general population study of 386 493 UK Biobank participants |
| Size: | 19268 B |
| Archived: | 24 Nov 2020 |
| Stability: | Complete |
| Personal: | No individual-level data |
Return 2858
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Notes
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.
Application 7155
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 |
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1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 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) |
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