| Application: | 7155, Epidemiology of mental health, cognitive function, pain and cardiometabolic disease. |
| Title: | Cannabis use and risk of schizophrenia: a Medelian randomization study |
| Size: | 1693 B |
| Archived: | 29 Jul 2019 |
| Stability: | Complete |
| Personal: | No individual-level data |
Return 1683
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Notes
Based on a genetic approach, use of cannabis was associated with increased risk of schizophrenia (odds ratio (OR) of schizophrenia for users vs nonusers of cannabis: 1.37; 95% confidence interval (CI), 1.09 1.67; P-value=0.007). The corresponding estimate from observational analysis was 1.43 (95% CI, 1.19 1.67; P-value for heterogeneity =0.76). The genetic markers did not show evidence of pleiotropic effects and accounting for tobacco exposure did not alter the association (OR of schizophrenia for users vs nonusers of cannabis, adjusted for ever vs never smoker: 1.41; 95% CI, 1.09 1.83). This adds to the substantial evidence base that has previously identified cannabis use to associate with increased risk of schizophrenia, by suggesting that the relationship is causal. Such robust evidence may inform public health messages about cannabis use, especially regarding its potential mental health consequences.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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Enabling scientific discoveries that improve human health