Association between sitting time at work and the onset of major depressive episode: a 1-year prospective cohort study using the Bayesian regression

Background Although sedentary behavior is associated with the onset of major depressive disorder, it remains unclear whether sedentary behavior at work increases the risk of depression. The present study used the Bayesian approach to investigate the association between sitting time at work and the onset of major depressive episode (MDE). Methods A 1-year prospective cohort study was conducted among 233 Japanese workers without MDE (response rate: 4.3%). MDE onset was assessed using the self-reported WHO Composite International Diagnostic Interview version 3.0. A Bayesian Cox proportional hazard model was used to estimate the hazard ratio (HR) between long sitting time at work and MDE onset. Results A total of 231 workers were included in the analysis. During the follow-up, 1621 person-months were observed, and six participants experienced MDE onset. Incident rates per months were 0.34, 0.11, and 1.02% in short (< 7.2 h per day), medium (7.2–9.5 h), and long (9.5+ h) sitting time at work, respectively. The estimated median posterior probability distribution of the HR of long sitting time was 3.00 (95% highest density interval [HDI]: 0.73–12.03). The estimated median remained positive after adjustment for physical activity level and other covariates (HR = 2.11, 95% HDI: 0.42–10.22). The 10-base Bayesian factor for H1 (HR = 1.00) compared with the alternatives (H0, HR = 1.00) was 0.68 in the adjusted model. The analysis, which treated sitting time at work as a continuous variable, estimated that the median of the posterior probability distribution of the HR of sitting time was 0.79 (95% HDI: 0.58–1.07. The 10-base Bayesian factor was 2.73 in the linear association. Conclusions Long sitting time at work (9.5+ h per day) might be associated with MDE onset among workers. However, the linear association indicated conflicting results. Non-linear associations between sitting time and MDE onset might explain this inconsistency. The evidence for an adverse association between sitting time at work and MDE onset remains inconclusive.

A methodological review protocol of the use of Bayesian factor analysis in primary care research

Background The development of questionnaires for primary care practice and research is of increasing interest in the literature. In settings where valuable prior knowledge or preliminary data is available, Bayesian factor analysis can be used to incorporate such information when conducting questionnaire construct validation. This protocol outlines a methodological review that will summarize evidence on the current use of Bayesian factor analysis in the primary care literature. Methods A comprehensive search strategy has been developed and will be used to identify relevant literature (research studies in primary care) indexed in MEDLINE, Scopus, EMBASE, CINAHL, and Cochrane Library. The search strategy includes terms and synonyms for Bayesian factor analysis and primary care. The reference lists of relevant articles being identified will be screened to find further relevant studies. At least two reviewers will independently extract data and resolve discrepancies through consensus. Descriptive analyses will summarize the use and reporting of Bayesian factor analysis approaches for validating questionnaires applicable to primary care. Discussion This methodological review will provide a comprehensive overview of the current use and reporting of Bayesian factor analysis in primary care and will provide recommendations for its proper future use. Systematic review registration PROSPERO CRD42018114978

A methodological review protocol of the use of Bayesian factor analysis in primary care research

Background : The development of questionnaires for primary care practice and research is of increasing interest in the literature. In settings where valuable prior knowledge or preliminary data is available, Bayesian factor analysis can be used to incorporate such information when conducting questionnaire construct validation. This protocol outlines a methodological review that will summarize evidence on the current use of Bayesian factor analysis in the primary care literature. Methods : A comprehensive search strategy has been developed and will be used to identify relevant literature (research studies in primary care) indexed in Medline, Scopus, EMBASE, CINAHL and Cochrane Library. The search strategy includes terms and synonyms for Bayesian factor analysis and primary care. The reference lists of relevant articles being identified will be screened to find further relevant studies. At least two reviewers will independently extract data and resolve discrepancies through consensus. Descriptive analyses will summarize the use and reporting of Bayesian factor analysis approaches for validating questionnaires applicable to primary care. Discussion: This methodological review will provide a comprehensive overview of the current use and reporting of Bayesian factor analysis in primary care and will provide recommendations for its proper future use.

A Bayesian Approach for Large Asset Allocation

The Black-Litterman model combines investor&rsquo;s personal views with historical data and gives optimal portfolio weights. In (Andrei &amp; Hsu, 2020), they reviewed the original Black-Litterman model and modified it in order to fit it into a Bayesian framework, when a certain number of assets is considered. They used the idea by (Leonard &amp; Hsu, 1992) for a multivariate normal prior on the logarithm of the covariance matrix. When implemented and applied to a large number of assets such as all the S&amp;P500 companies, they ran into memory allocation and running time issues. In this paper, we reduce the dimensions by considering Bayesian factor models, which solve the asset allocation problems for a large number of assets. In addition, we will conduct sensitivity analysis for the confidence levels that the investors have to input.