Vaccinations and childhood type 1 diabetes mellitus: a meta-analysis of observational studies

Aims/hypothesis The aim of this study was to investigate the association between routine vaccinations and the risk of childhood type 1 diabetes mellitus by systematically reviewing the published literature and performing meta-analyses where possible.

Methods A comprehensive literature search was performed of MEDLINE and EMBASE to identify all studies that compared vaccination rates in children who subsequently developed type 1 diabetes mellitus and in control children. ORs and 95% CIs were obtained from published reports or derived from individual patient data and then combined using a random effects meta-analysis.

Results In total, 23 studies investigating 16 vaccinations met the inclusion criteria. Eleven of these contributed to meta-analyses which included data from between 359 and 11,828 childhood diabetes cases. Overall, there was no evidence to suggest an association between any of the childhood vaccinations investigated and type 1 diabetes mellitus. The pooled ORs ranged from 0.58 (95% CI 0.24, 1.40) for the measles, mumps and rubella (MMR) vaccination in five studies up to 1.04 (95% CI 0.94, 1.14) for the haemophilus influenza B (HiB) vaccination in 11 studies. Significant heterogeneity was present in most of the pooled analyses, but was markedly reduced when analyses were restricted to study reports with high methodology quality scores. Neither this restriction by quality nor the original authors’ adjustments for potential confounding made a substantial difference to the pooled ORs.

Conclusions/interpretation This study provides no evidence of an association between routine vaccinations and childhood type 1 diabetes.

Does childhood bullying lead to the development of psychotic symptoms? A meta-analysis and review of prospective studies

Purpose: Researchers have demonstrated associations between trauma and psychosis. Childhood trauma, in particular, appears to be an important determinant. Recently, bullying has become considered a traumatic experience in its own right. This review aims to analyse research with prospective designs, which will enable conclusions about whether or not bullying causes psychosis.

Methods: A systematic review of the literature was carried out independently by two reviewers. Eligibility and quality assessment criteria were applied. A meta-analysis and narrative synthesis were then completed.

Results: Ten studies met inclusion criteria. Four used data from the same large database, and were combined as one. The majority provided confirmation that bullying appears to cause later development of psychosis. A meta-analysis yielded an unadjusted odds ratio (OR) of 2.148 [95% confidence interval (CI) 1.140–4.044].

Conclusions: The studies reviewed here suggest that bullying does predict the later development of psychotic symptoms. What is lacking from the literature is adequate investigation into other potential mediating factors. The current review highlights the significant role of bullying within this complex interaction. Potential mediating variables are explored, including a dose–response effect for the severity and frequency of victimization. Suggestions for targeting intervention are also suggested alongside clinical implications and recommendations for future research.

Parallel Time Series Analysis and Income Inequality: A New Approach to Comparative Case Studies

This case study deals with the role of time series analysis in sociology, and its relationship with the wider literature and methodology of comparative case study research. Time series analysis is now well-represented in top-ranked sociology journals, often in the form of ‘pooled time series’ research designs. These studies typically pool multiple countries together into a pooled time series cross-section panel, in order to provide a larger sample for more robust and comprehensive analysis. This approach is well suited to exploring trans-national phenomena, and for elaborating useful macro-level theories specific to social structures, national policies, and long-term historical processes. It is less suited however, to understanding how these global social processes work in different countries. As such, the complexities of individual countries - which often display very different or contradictory dynamics than those suggested in pooled studies – are subsumed. Meanwhile, a robust literature on comparative case-based methods exists in the social sciences, where researchers focus on differences between cases, and the complex ways in which they co-evolve or diverge over time. A good example of this is the inequality literature, where although panel studies suggest a general trend of rising inequality driven by the weakening power of labour, marketisation of welfare, and the rising power of capital, some countries have still managed to remain resilient. This case study takes a closer look at what can be learned by applying the insights of case-based comparative research to the method of time series analysis. Taking international income inequality as its point of departure, it argues that we have much to learn about the viability of different combinations of policy options by examining how they work in different countries over time. By taking representative cases from different welfare systems (liberal, social democratic, corporatist, or antipodean), we can better sharpen our theories of how policies can be more specifically engineered to offset rising inequality. This involves a fundamental realignment of the strategy of time series analysis, grounding it instead in a qualitative appreciation of the historical context of cases, as a basis for comparing effects between different countries.