23 research outputs found
Genetic Demography of an Urban Greek Immigrant Community
In a study in historical demographic anthropology conducted during 1976-77 on an urban Greek immigrant community in Columbus, Ohio, demographic and social data were obtained for 1,286 individuals through parish records, census information, 102 structured interviews with family units, and participant observation. The results show that the generations of immigrants differed from each other in rates of fertility, mortality, and migration. This generational variation affects the estimation of natural selection, genetic drift and gene flow. The population exhibited a trend showing differential fertility to be a more significant factor in natural selection than was mortality. However, microdifferentiation from natural selection as well as from genetic drift was low when compared with other human populations. Gene flow was deduced to have been the major evolutionary force operative in the Columbus Greek community
Factors Influencing Diabetes Self-Management Among Medically Underserved Patients With Type II Diabetes
In this study, researchers compare and contrast issues regarding diabetes self-management between persons in good versus poor glycemic control. The sample comprises low-income racially diverse adults with diabetes from four mid-western community health centers; 44 patients participated in eight focus groups divided by control status (HbA1c of > 9 [uncontrolled] or < 7 [controlled]). Themes common to both groups included the impact of dietary restrictions on social interactions, food cravings, the impact of mental health on self-management, and the importance of formal and informal (friends and family) support. Those in the uncontrolled groups described fear about being able to control their diabetes, confusion about self-management, and difficulty managing their diabetes while caring for family members. Although those in the controlled groups acknowledged difficulties, they discussed resisting cravings, making improvements with small changes, positive feelings about their ability to control their diabetes, and enjoying new foods and exercise. Interventions should include mental health support, incorporate formal and informal patient support structures, and address literacy issues. Health care providers and intervention personnel should be very concrete about how to do self-management tasks and guide patients on how to alter their diabetes regimens for social and other important life events
Explanatory models of diabetes: Patient practitioner variation
Most cases of diabetes, a complex disorder that requires many lifestyle changes, can be controlled if persons adhere to their prescribed regimen. However, compliance is difficult to attain. Differences in explanatory models between client and practitioner have been suggested as one reason for non-compliance in several disorders. In this ethnographic investigation, individual explanatory models were elicited from persons with diabetes and from health professionals working with these patients. Professionals described models of diabetes in general and their model of a particular patient's diabetes. A composite professional model was constructed and compared with each of the patients' models. The models were most congruent regarding treatment. Etiology, pathophysiology, and severity had less congruence, and time and mode of symptom onset were least congruent. The Spearman correlation coefficient showed a positive but non-significant association of explanatory model congruence between professionals and patients with normal glycosylated hemoglobin levels. Patients and professionals seem to emphasize different domains; patients emphasized difficulties in the social domain and the impact of diabetes on their lives while staff saw diabetes primarily as a pathophysiological problem with impact on patients' physical bodies. This study's importance rests on its clear articulation of significant differences between patients' and staffs' models even when they are similar in demographic characteristics.explanatory models diabetes