A new approach to analyse longitudinal epidemiological data with an excess of zeros

<p>Background: Within longitudinal epidemiological research, 'count' outcome variables with an excess of zeros frequently occur. Although these outcomes are frequently analysed with a linear mixed model, or a Poisson mixed model, a two-part mixed model would be better in analysing outcome variables with an excess of zeros. Therefore, objective of this paper was to introduce the relatively 'new' method of two-part joint regression modelling in longitudinal data analysis for outcome variables with an excess of zeros, and to compare the performance of this method to current approaches.</p><p>Methods: Within an observational longitudinal dataset, we compared three techniques; two 'standard' approaches (a linear mixed model, and a Poisson mixed model), and a two-part joint mixed model (a binomial/Poisson mixed distribution model), including random intercepts and random slopes. Model fit indicators, and differences between predicted and observed values were used for comparisons. The analyses were performed with STATA using the GLLAMM procedure.</p><p>Results: Regarding the random intercept models, the two-part joint mixed model (binomial/Poisson) performed best. Adding random slopes for time to the models changed the sign of the regression coefficient for both the Poisson mixed model and the two-part joint mixed model (binomial/Poisson) and resulted into a much better fit.</p><p>Conclusion: This paper showed that a two-part joint mixed model is a more appropriate method to analyse longitudinal data with an excess of zeros compared to a linear mixed model and a Poisson mixed model. However, in a model with random slopes for time a Poisson mixed model also performed remarkably well.</p>

Correlates of fear of hypoglycemia among patients with type 1 and 2 diabetes mellitus in outpatient hospitals in Zambia

Background: Severe hypoglycemia is a burdensome complication of diabetes mellitus that can induce fear of hypoglycemia and contribute to suboptimal glycemic control. The challenge is to achieve and maintain adequate glycemic control while avoiding episodes of severe hypoglycemia. The purpose of the study was to determine how common fear of hypoglycemia was in Zambian out-patients with diabetes and also to explore correlates of fear of hypoglycemia. Methods: One hundred fifty-seven individuals with types 1 and 2 diabetes participated in the study. Fear of Hypoglycemia Scale, Diabetes Self-Care Inventory, Problem Areas in Diabetes, and the Major Depression Inventory were completed. Multiple linear regression models were computed to assess the association between fear of hypoglycemia and psychological factors. Results: About 19% [16.3% type 1 and 12.6% type 2] of individuals with diabetes based on item endorsement expressed fear of hypoglycemia especially among individuals with type 1 diabetes. After controlling for demographic variables, diabetes self-care (ß = 0.24, p \u3c 0.05), and diabetes specific distress (ß = 0.41, p \u3c 0.001) were associated with fear of hypoglycemia. Conclusion: Fear of hypoglycemia was common and was positively associated with diabetes specific emotional distress and diabetes self-care. Interventions to avert fear of hypoglycemia are needed while optimizing glycemic control through managing diabetes care and emotion distress in individuals with diabetes

Web-based self-management with and without coaching for type 2 diabetes patients in primary care:design of a randomized controlled trial

<p>Background: Self-management is recognized as the cornerstone of overall diabetes management. Web-based self-management programs have the potential of supporting type 2 diabetes patients with managing their diabetes and reducing the workload for the care provider, where the addition of online coaching could improve patient motivation and reduce program attrition. This study aims to test the hypothesis that a web-based self-management program with coaching will prove more effective on improving patient self-management behavior and clinical outcome measures than a web-based self-management program without coaching.</p><p>Methods: The effects of a web-based self-management program with and without coaching will be tested with a nested randomized controlled trial within a healthcare group in the Netherlands. In one year 220 type 2 diabetes patients will be randomized into an intervention group (n = 110) or a control group (n = 110). The control group will receive only the online self-management program. The intervention group will receive the online self-management program and additional online coaching. Participants will be followed for one year, with follow-up measurements at 6 and 12 months.</p><p>Discussion: The intervention being tested is set to support type 2 diabetes patients with their diabetes self-management and is expected to have beneficial effects on self-care activities, well being and clinical outcomes. When proven effective this self-management support program could be offered to other health care groups and their type 2 diabetes patients in the Netherlands.</p>