The regional registry of gastro-intestinal cancer North Baden (2.2 million inhabitants)

Summary The advantages of a population-based registry are discussed. It is shown that a registry for gastro-intestinal cancer in a district with expert medical care based upon histo-pathological diagnosis, has the principal advantage that it limits the sites of material collection to a few effective contributors, thus providing highly accurate data. The disadvantage of collecting data by two separate steps should be tolerated. The geographic situation and the organization of the regional registry for gastro-intestinal cancer in North Baden are described and the incidences for these cancers for the years 1971–1975 are given for the population of 2.2 million.Supported by the DFG (SFB 136)     

Thymic masses on MR imaging

MR imaging is an excellent technique for identifying and defining the extent of thymic tumors. T1-weighted spin-echo MR images (e.g., 600/15 [TR/TE]) best demonstrate tumor extent, and T2-weighted images (e.g., 2500/90 [TR/TE]) help differentiate "cystic" from solid thymic masses. Cyst formation and/or hemorrhage appear as areas of high signal intensity (greater than that of fat) on T2-weighted images. Focal areas of low signal intensity (less than that of muscle) correspond pathologically to fibrous capsules and septa, air, or calcification. In this report, the MR appearance of the normal thymus is reviewed briefly, and the gamut of abnormal thymic masses on MR is illustrated.     

How do health care education and training professionals learn about the environment?

Preparing for the health care system of the future includes the ability to abstract information from relevant sectors of the environment. This study looked at the way health care educators scan the environment and the relationship of scanning behavior to management style. Results indicate that education and training professionals focus on the regulatory and customer sectors of the environment more than the technological and sociopolitical sectors.     

Obesity and subcutaneous fat patterning in relation to survival of postmenopausal breast cancer patients participating in the DOM-project

Summary The effect of obesity and fat distribution on survival of breast cancer patients was studied prospectively in 241 women with a natural menopause who participated in a breast cancer screening project, the DOM-project in Utrecht, The Netherlands. Mean follow-up time was 9.1 years and endpoint of interest was death from breast cancer. Fat distribution was assessed by contrasting groups of subscapular and triceps skinfold thickness.No significant differences in survival time between more obese (Quetelet's index 26 kg/m²) and leaner (Quetelet's index < 26 kg/m²) patients or between patients with central fat distribution and patients with peripheral fat distribution were observed. Analyses were stratified by axillary node status, estrogen receptor status, and way of detection (by first screening or afterwards). Results of the stratified analyses were suggestive of a modifying effect of these factors.The absence of an association between obesity and survival time might be explained by two counteracting mechanisms. On the one hand obesity might be related to impaired survival, due to a tumor growth promoting effect of extra-ovarian estrogens. On the other hand obesity might be related to improved survival in a screened population, because obese patients profit more from screening by earlier detection of tumors than leaner counterparts.     

The Burden of Obesity and Its Sequelae

Obesity [body mass index (BMI) ≥30 kg/m²] is common in many parts of the world, especially in the established market economies, formerly socialist economies of Europe and Latin America and the Caribbean, as well as the Middle Eastern Crescent. Worldwide, as many as 250 million people may be obese (7% of the adult population) and 2 to 3 times as many may be considered overweight (BMI 25 to 30 kg/m²). The prevalence of obesity seems to be increasing in most parts of the world, even in areas where obesity used to be rare.A waist circumference greater than 102cm in men and 88cm in women may be a more sensible classification than BMI to identify individuals who are at increased health risk because of obesity, but information on this point is still scarce.Increased fatness measured by a high BMI, large waist circumference or high waist/hip circumference ratio is associated with many chronic diseases as well as poor physical functioning. These all contribute to the costs associated with excess bodyweight. The economic costs of obesity can be broken down into 3 levels Direct costs: costs to the community related to the diversion of resources to the diagnosis and treatment of diseases directly related to obesity as well as the treatment of obesity itself. These costs have been estimated to account for 2 to 8% of total healthcare costs of various countries. Indirect (or societal) costs: these costs are related to the loss of productivity caused by absenteeism and premature death and disability pensions. There is a lack of good economic analysis in this area, although research from Sweden, Finland and The Netherlands has clearly shown that obesity is associated with increased sick leave and the need for disability pensions. Personal costs: obese individuals may earn less than their lean counterparts because of job discrimination (related to the stigma associated with obesity or because of diseases and disabilities caused by obesity). Many insurance companies (particularly life insurance) charge higher premiums with increasing degrees of overweight.In conclusion, there is much indirect information that obesity and overweight are important and growing public health concerns that contribute substantially to healthcare-related costs. Effective strategies for the prevention and management of obesity are needed.     

Model validation for external doses due to environmental contaminations by the Chernobyl accident

The objective of the present paper is to validate the deterministic JSP5 model for external exposures to population groups living in the areas contaminated with radionuclides after the Chernobyl accident. For this purpose inhabitants of contaminated areas wore TL-dosimeters for about 1 mo in the spring/summer periods of the years 1989 to 1994. External doses due to the Chernobyl accident were determined from the dosimeter readings by subtracting the natural background. 2,342 results for rural inhabitants and 420 results for inhabitants of the town Novozybkov passed reliability checks. These data show that the average dose in inhabitants of a rural settlement predicted by the model is in the range 0.69-1.55 of the measured values with a confidence level of 95%. Differences are attributed to settlement specific location factors, which are supported by the very good agreement of model and measurements in Novozybkov. In this case location factors of the model were obtained from Novozybkov directly.