OBJECTIVE -To examine risk perception for diabetes among women with histories of gestational diabetes mellitus (GDM).RESEARCH DESIGN AND METHODS -We surveyed 217 women with histories of GDM who were enrolled in a managed-care plan and who did not currently have diabetes. In a cross-sectional design, we assessed the associations between risk perceptions and current lifestyle behavioral practices, plans to modify behaviors, and recent lifestyle behavior changes. Multivariable models included participant characteristics as well as potential modifiers of risk perception (knowledge of diabetes risk factors, optimistic bias, perceived personal control, and beliefs in the benefits and barriers of lifestyle modification).RESULTS -Ninety percent of women recognized that GDM was a risk factor for future diabetes, but only 16% believed that they themselves had a high chance of developing diabetes; perceived risk increased to 39% when women were asked to estimate their risk assuming they maintained their current lifestyle. Women who consumed three or more but less than five servings a day of fruits and vegetables reported lower odds of moderate/high risk perception (adjusted odds ratio [OR] 0.39 [95% CI 0.16 -0.92]) than women who consumed less than three servings a day, although this association was not significant after further adjustment for income. Women who perceived themselves to be at moderate/high risk more often planned to modify their future lifestyle behaviors (9.1 [0.16 -0.92]).CONCLUSIONS -Despite understanding the association between GDM and postpartum diabetes, women with histories of GDM usually do not perceive themselves to be at elevated risk. Diabetes Care 30:2281-2286, 2007G estational diabetes mellitus (GDM) is defined as glucose intolerance first identified during pregnancy (1,2). While glucose intolerance resolves with delivery ϳ90% of the time (3), it continues to affect women's health postpartum. Women with GDM are at increased risk for future episodes of GDM, pre-diabetes (impaired glucose tolerance and impaired fasting glucose), and type 2 diabetes (4,5). Despite these facts, women with histories of GDM may not perceive themselves to be at risk for future diabetes. Spirito et al. (6) found that among 67 women with GDM, two-thirds did not believe they would develop GDM during a future pregnancy, and one-fifth did not believe they were at risk for diabetes. Qualitative work in several high-risk groups such as the Pima Indians (7) and Mexican Americans (8) suggest that these women may believe that GDM does not pose a problem after delivery.Theoretical models suggest that risk perception may be an important determinant of behavioral change (9). In the case of diabetes prevention, higher and more accurate perceptions of risk might encourage a healthier lifestyle, including a healthy diet and adequate physical activity. In contrast, underestimates of risk might act as a barrier to preventive behaviors and could therefore be a target for behavioral interventions. However, the association between risk pe...
These findings suggest that most women with gestational diabetes mellitus are not screened for type 2 DM after delivery. Opportunities for DM prevention and early treatment are being missed.
OBJECTIVE— We sought to examine demographic, socioeconomic, and biological predictors of all-cause, cardiovascular, and noncardiovascular mortality in patients with diabetes. RESEARCH DESIGN AND METHODS— Survey, medical record, and administrative data were obtained from 8,733 participants in the Translating Research Into Action for Diabetes Study, a multicenter, prospective, observational study of diabetes care in managed care. Data on deaths (n = 791) and cause of death were obtained from the National Death Index after 4 years. Predictors examined included age, sex, race, education, income, duration, and treatment of diabetes, BMI, smoking, microvascular and macrovascular complications, and comorbidities. RESULTS— Predictors of adjusted all-cause mortality included older age (hazard ratio [HR] 1.04 [95% CI 1.03–1.05]), male sex (1.57 [1.35–1.83]), lower income (<$15,000 vs. >$75,000, HR 1.82 [1.30–2.54]; $15,000–$40,000 vs. >$75,000, HR 1.58 [1.15–2.17]), longer duration of diabetes (≥9 years vs. <9 years, HR 1.20 [1.02–1.41]), lower BMI (<26 vs. 26–30 kg/m2, HR 1.43 [1.13–1.69]), smoking (1.44 [1.20–1.74]), nephropathy (1.46 [1.23–2.73]), macrovascular disease (1.46 [1.23–1.74]), and greater Charlson index (≥2–3 vs. <1, HR 2.01 [1.04–3.90]; ≥3 vs. <1, HR 4.38 [2.26–8.47]). The predictors of cardiovascular and noncardiovascular mortality were different. Macrovascular disease predicted cardiovascular but not noncardiovascular mortality. CONCLUSIONS— Among people with diabetes and access to medical care, older age, male sex, smoking, and renal disease are important predictors of mortality. Even within an insured population, socioeconomic circumstance is an important independent predictor of health.
OBJECTIVETo examine demographic, socioeconomic, and biological risk factors for all-cause, cardiovascular, and noncardiovascular mortality in patients with type 2 diabetes over 8 years and to construct mortality prediction equations.RESEARCH DESIGN AND METHODSBeginning in 2000, survey and medical record information was obtained from 8,334 participants in Translating Research Into Action for Diabetes (TRIAD), a multicenter prospective observational study of diabetes care in managed care. The National Death Index was searched annually to obtain data on deaths over an 8-year follow-up period (2000–2007). Predictors examined included age, sex, race, education, income, smoking, age at diagnosis of diabetes, duration and treatment of diabetes, BMI, complications, comorbidities, and medication use.RESULTSThere were 1,616 (19%) deaths over the 8-year period. In the most parsimonious equation, the predictors of all-cause mortality included older age, male sex, white race, lower income, smoking, insulin treatment, nephropathy, history of dyslipidemia, higher LDL cholesterol, angina/myocardial infarction/other coronary disease/coronary angioplasty/bypass, congestive heart failure, aspirin, β-blocker, and diuretic use, and higher Charlson Index.CONCLUSIONSRisk of death can be predicted in people with type 2 diabetes using simple demographic, socioeconomic, and biological risk factors with fair reliability. Such prediction equations are essential for computer simulation models of diabetes progression and may, with further validation, be useful for patient management.
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