| Title: | Modifiable risk factors and excess mortality in depression: Data from the UK Biobank |
| Journal: | General Hospital Psychiatry |
| Published: | 22 Aug 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39244951/ |
| DOI: | https://doi.org/10.1016/j.genhosppsych.2024.08.010 |
Publication 12934
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Abstract
OBJECTIVE: To study the role of modifiable risk factors in explaining the excess mortality associated with depression using data from the UK Biobank, a middle-aged and elderly cohort recruited in 2006-2010.</p>
METHODS: We estimated the prevalence and relative mortality associated with modifiable risk factors and groups of risk factors (socioeconomic factors, diet and exercise, smoking and substance-related disorders, and cardiometabolic diseases) in a subsample of probable cases of lifetime/current depression (n = 51,302) versus non-cases. We also estimated the relative mortality associated with depression and the percentages of excess mortality associated with depression explained by modifiable risk factors in the total sample (499,762).</p>
RESULTS: In our depression subsample, all modifiable risk factors were associated with increased prevalence and mortality. In our total sample, depression was associated with an age and sex-adjusted mortality hazard ratio of 1.63 (95% CI = [1.58-1.68]). Modifiable risk factors explained 70.5% [66.9%-75.0%] of the excess mortality associated with depression.</p>
CONCLUSIONS: In the UK Biobank cohort, depression was associated with a higher prevalence of modifiable risk factors. These risk factors were associated with increased mortality in the depression subsample and explained most of the excess mortality risk associated with depression in the total sample.</p>
17 Keywords
- Adult
- Aged
- Biological Specimen Banks
- Cohort Studies
- Depression
- Depressive Disorder
- Exercise
- Female
- Humans
- Male
- Middle Aged
- Prevalence
- Risk Factors
- Smoking
- Substance-Related Disorders
- UK Biobank
- United Kingdom
2 Authors
- Vivian Boschesi Barros
- Alexandre Dias Porto Chiavegatto Filho
1 Application
| Application ID | Title |
|---|---|
| 30140 | Which causes of death are predictable? A machine learning analysis |
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