Laura N. McEwen

Missed Opportunities for Type 2 Diabetes Mellitus Screening Among Women With a History of Gestational Diabetes Mellitus

OBJECTIVES We sought to determine rates and factors associated with screening for type 2 diabetes mellitus (DM) in women with a history of gestational diabetes mellitus. METHODS We retrospectively studied women with diagnosed gestational diabetes mellitus who delivered at a university-affiliated hospital (n=570). Data sources included medical and administrative record review. Main outcome measures were the frequency of any type of glucose testing at least 6 weeks after delivery and the frequency of recommended glucose testing. We assessed demographic data, past medical history, and prenatal and postpartum care characteristics. RESULTS Rates of glucose testing after delivery were low. Any type of glucose testing was performed at least once after 38% of deliveries, and recommended glucose testing was performed at least once after 23% of deliveries. Among women with at least 1 visit to the health care system after delivery (n=447), 42% received any type of glucose test at least once, and 35% received a recommended glucose test at least once. Factors associated with testing were being married, having a visit with an endocrinologist after delivery, and having more visits after delivery. CONCLUSIONS 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.

Risk Factors for Mortality among Patients with Diabetes: The Translating Research Into Action for Diabetes (TRIAD) Study

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 (<

Thiazolidinediones and fractures: evidence from translating research into action for diabetes.

15,000 vs. >

Self-Efficacy, Social Support, and Associations With Physical Activity and Body Mass Index Among Women With Histories of Gestational Diabetes Mellitus

75,000, HR 1.82 [1.30–2.54];

Predictors of Mortality Over 8 Years in Type 2 Diabetic Patients Translating Research Into Action for Diabetes (TRIAD)

15,000–

Are health-related quality-of-life and self-rated health associated with mortality? Insights from Translating Research Into Action for Diabetes (TRIAD)

40,000 vs. >

Predictors and impact of intensification of antihyperglycemic therapy in type 2 diabetes: Translating Research into Action for Diabetes (TRIAD)

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.

Antibiotic prescribing for cystitis: How well does it match published guidelines?

BACKGROUND Thiazolidinedione (TZD) treatment has been associated with fractures. The purpose of this study was to examine the association between TZD treatment and fractures in type 2 diabetic patients. METHODS Using data from Translating Research into Action for Diabetes, a multicenter prospective observational study of diabetes care in managed care, we conducted a matched case-control study to assess the odds of TZD exposure in patients with type 2 diabetes with and without fractures. We identified 786 cases based on fractures detected in health plan administrative data. Up to four controls without any fracture diagnoses were matched to each case. Controls were matched on health plan, date of birth within 5 yr, sex, race/ethnicity, and body mass index within 5 kg/m(2). We performed conditional logistic regression for premenopausal and postmenopausal women and men to assess the odds of exposure to potential risk factors for fracture, including medications, self-reported limited mobility, and lower-extremity amputations. RESULTS We found statistically significant increased odds of exposure to TZDs, glucocorticoids, loop diuretics, and self-reported limited mobility for women 50 yr of age and older with fractures. Exposure to both loop diuretics and TZDs, glucocorticoids, and insulin and limited mobility and lower-extremity amputation were associated with fractures in men. CONCLUSION Postmenopausal women taking TZDs and the subset of men taking both loop diuretics and TZDs were at increased risk for fractures. In postmenopausal women, risk was associated with higher TZD dose. No difference between rosiglitazone and pioglitazone was apparent.

Temporal trends in recording of diabetes on death certificates: results from Translating Research Into Action for Diabetes (TRIAD).

PURPOSE To examine the associations between 2 potential facilitators of healthy behaviors (self-efficacy and social support), and both physical activity and body mass index (BMI) among women with histories of gestational diabetes mellitus (GDM). METHODS Two hundred and twenty-eight women with histories of GDM who were enrolled in a managed care plan were surveyed. A cross-sectional analysis was used to assess the association between womens social support from family and friends for physical activity and self-efficacy for physical activity with womens physical activity levels. The association between womens social support from family and friends for healthy diet and self-efficacy for not overeating and their dietary habits also were examined. Finally, the association between all of these psychosocial constructs and body mass index (BMI) were assessed before and after adjustment for covariates. RESULTS Participants reported low to moderate social support and self-efficacy scores, suboptimal performance of physical activity, suboptimal dietary scores, and high BMIs. Self-efficacy and social support from family and friends for physical activity were associated with physical activity. Social support from family and friends for a healthy diet was associated with better dietary scores, and the association between self-efficacy for not overeating and healthy diet bordered on significance. No significant associations existed between psychosocial constructs and BMI. CONCLUSIONS Psychosocial constructs such as social support and self-efficacy are associated with physical activity and dietary habits. However, associations with BMI are weak. Further exploration of constructs associated with BMI may be needed to design effective weight-loss interventions in this population.

Investing time in health: do socioeconomically disadvantaged patients spend more or less extra time on diabetes self‐care?

OBJECTIVE To 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 METHODS Beginning 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. RESULTS There 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. CONCLUSIONS Risk 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.