Denisa Janíčková Žďárská

Fear of driving license withdrawal in patients with insulin-treated diabetes mellitus negatively influences their decision to report severe hypoglycemic events to physicians

Background Under current European Union legislation, two severe hypoglycemic events within 12 months is grounds for driving license withdrawal. The aim of the study reported here was to determine whether fear of such a withdrawal could lead to patients concealing severe hypoglycemia from physicians, which could negatively impact further treatment decisions. Methods A total of 663 patients with insulin-treated diabetes were anonymously surveyed about whether they would conceal severe hypoglycemic events from their physicians, if revealing them could result in driving license withdrawal. This investigation utilized an adapted and expanded questionnaire by Graveling et al. Results Of all diabetic patients surveyed, 26.17% would most likely not report hypoglycemia, and 25.86% were undecided. In a group of patients with type 1 diabetes, 31.83% would likely not report hypoglycemic events, and 25.06% were undecided. The patients least likely to report severe hypoglycemic events were those who indicated that vehicles were partly essential for work, and who also had more than two hypoglycemic events monthly. Conclusion A considerable percentage of diabetic patients would likely conceal severe hypoglycemic events from their physicians due to fear of driving license withdrawal. Patient failure to report severe hypoglycemic events can potentially lead to physicians being misinformed regarding the patient’s condition, which could lead to inadequate monitoring and treatment.

Incidence of Diabetes Mellitus Narrowly Correlates with Unemployment Rate during 2000-2012 in the Czech Republic

There is a documented association between higher unemployment rates in inner cities and a higher risk of type 2 diabetes mellitus (DM) (1). Higher unemployment at regional level is also associated with a higher prevalence of diabetes mellitus (2). Possible causes for the relationship between unemployment and diabetes mellitus include, for example, limited financial resources, which can lead to underfunded support of physical activity and healthy diets (3, 4). Results from the DIAB-CORE Consortium, a study that examined, among other issues, the relationship between type 2 diabetes mellitus and various social aspects including unemployment in Germany (1, 2, 5), led us to question whether the relationship between unemployment rates and the incidence of diabetes mellitus could be confirmed for larger areas and over longer periods of time in the Czech Republic. We also wanted to determine whether previous findings of a study involving a relatively small sample of patients could be verified using a different methodology based on population data (official unemployment figures) from all 14 administrative regions of the Czech Republic.We analyzed the relationship between the incidence of diabetes mellitus and unemployment in the Czech Republic, wherein 10,509,286 inhabitants resided during 2012 and the prevalence of diabetes mellitus was 8.0%. The country is divided into 14 higher-level territorial administrative units (regions): in 2012 the least populous was inhabited by 301,726 residents, while the most populous by 1,291,816 residents (6). Data pertaining to patients with diabetes mellitus (more specifically, the number of new diabetes patients per calendar year) were obtained from a register that is maintained by the Institute of Health Information and Statistics of the Czech Republic, to which all physicians are legally obliged to annually report data for diabetes patients in their care (7). Unemployment figures were obtained from a register kept by the Ministry of Labour and Social Affairs, which is managed in accordance with Eurostat/International Labour Office methods (8). At the time this study was conducted, available data from both registers spanned the period from 2000 to 2012.Given that the unemployment rates among individual regions vary both instantaneously and continuously, we compared the relationship between unemployment rates and the incidence of diabetes mellitus, while taking into account time and inter-regional differences in both population totals and background diabetes incidence. Using the Generalized Additive Model (GAM) (9), regions were represented by i and calendar year was represented by t:(ProQuest: ... denotes formula omitted.)wherein the modeled quantity (the left side of the equation) is a proxy for the regionally-specific incidence. For this, the effect of unemployment was tested (regional and time-specific); coefficient β is estimated from the data, after an adjustment for regionallyspecific average incidence (μi) and time trend s(t) , estimated as a spline, and [varepsilon] it represents homoscedastic random error.Thus, we compared the incidence of diabetes mellitus and unemployment rate, while taking into account separate values for individual regions, over the aforementioned period of 2000-2012. The effect of unemployment on DM incidence adjusted for spatial and temporal differences was positive (the estimate of the β coefficient was 4.173.10-3, its standard error was 7.688.10-4 ) and highly statistically significant (p Unfortunately, the diabetes mellitus patient registry does not distinguish types of disease in the annual new patient reports. However, the number of patients registered according to different types of diabetes mellitus in the years 2000 and 2012 was 44,870 and 56,514 individuals, respectively, with type 1 diabetes mellitus: 8,299 and 12,128, respectively, with secondary diabetes; and 599,782 and 772,585, respectively, with type 2 diabetes mellitus. …

Prediabetes, diabetes and unemployment

e read with interest the article by Rautio et al. which as been recently published online in the journal Primary are Diabetes [1]. This article objectively quantifies the relaionship between varying exposure to unemployment and mpaired glucose metabolism, suggesting a relation of unemloyment and type 2 diabetes in men. In our recent work [2] e have, through a different type of data (extensive population ata from official registers, without a longitudinal structure), etected a relationship between unemployment and the incience of diabetes in the Czech Republic. This type of data id not allow us to analyse differences between men and omen with this diagnosis. When thinking about the results f the work Rautio et al., we came up with four questions hich we would like to respectfully pose to the authors. (1) hether the authors had information on the weight gain of ndividual subjects, at least in recent years just before the tudy. It would be interesting to test whether higher weight ain is associated with the prediabetes and diabetes status weight history can be a valuable proxy or predictor for changng diabetes status, but it is certainly possible that its effect nteracts with the effect of unemployment). (2) Whether they ave data available on the nature of employment that each ubject last held before the study. Knowledge of this data ould help estimate the likely differences in physical workload etween previous employment and current unemployment. 3) Whether it would be worthwhile to study the interaction ffects of unemployment not only with gender, but also with ther explanatory variables such as physical activity level, ody mass index, smoking history, education effects interct with uneployment. (4) Whether it would be valuable to ttempt to quantify the impact of the unemployment period n more detail (e.g. via modern regression methods like GAM”). e recognize that, that in each group of “unemployed”, as they re defined in the article, there may be included individuals ith a diametrically different number of unemployed days (for nstance in the group of ≤1 year there can be an individual with day, but also 268 days spent unemployed, that is, people with ompletely different probable impact of unemployment). We