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1.  Depression as a Predictor of Weight Regain Among Successful Weight Losers in the Diabetes Prevention Program 
Diabetes Care  2013;36(2):216-221.
OBJECTIVE
To determine whether depression symptoms or antidepressant medication use predicts weight regain in overweight individuals with impaired glucose tolerance (IGT) who are successful with initial weight loss.
RESEARCH DESIGN AND METHODS
A total of 1,442 participants who successfully lost at least 3% of their baseline body weight after 12 months of participation in the randomized controlled Diabetes Prevention Program (DPP) continued in their assigned treatment group (metformin, intensive lifestyle, or placebo) and were followed into the Diabetes Prevention Program Outcome Study (DPPOS). Weight regain was defined as a return to baseline DPP body weight. Participant weight and antidepressant medication use were assessed every 6 months. Depression symptoms (Beck Depression Inventory [BDI] score ≥11) were assessed every 12 months.
RESULTS
Only 2.7% of the overall cohort had moderate to severe depression symptoms at baseline; most of the participants with BDI score ≥11 had only mild symptoms during the period of observation. In unadjusted analyses, both depression symptoms (hazard ratio 1.31 [95% CI 1.03–1.67], P = 0.03) and antidepressant medication use at either the previous visit (1.72 [1.37–2.15], P < 0.0001) or cumulatively as percent of visits (1.005 [1.002–1.008], P = 0.0003) were predictors of subsequent weight regain. After adjustment for multiple covariates, antidepressant use remained a significant predictor of weight regain (P < 0.0001 for the previous study visit; P = 0.0005 for the cumulative measure), while depression symptoms did not.
CONCLUSIONS
In individuals with IGT who do not have severe depression and who initially lose weight, antidepressant use may increase the risk of weight regain.
doi:10.2337/dc12-0293
PMCID: PMC3554307  PMID: 23002085
3.  Impact of Lifestyle Intervention and Metformin on Health-Related Quality of Life: the Diabetes Prevention Program Randomized Trial 
Journal of General Internal Medicine  2012;27(12):1594-1601.
ABSTRACT
BACKGROUND
Adults at high risk for diabetes may have reduced health-related quality of life (HRQoL).
OBJECTIVE
To assess changes in HRQoL after interventions aimed at diabetes risk reduction.
DESIGN, SETTING, AND PARTICIPANTS
A randomized clinical trial, the Diabetes Prevention Program, was conducted in 27 centers in the United States, in 3,234 non-diabetic persons with elevated fasting and post-load plasma glucose, mean age 51 years, mean BMI 34 Kg/m²; 68 % women, and 45 % members of minority groups.
INTERVENTIONS
Intensive lifestyle (ILS) program with the goals of at least 7 % weight loss and 150 min of physical activity per week, metformin (MET) 850 mg twice daily, or placebo (PLB).
MEASUREMENTS
HRQoL using the 36-Item Short-Form (SF-36) health survey to evaluate health utility index (SF-6D), physical component summaries (PCS) and mental component summaries (MCS). A minimally important difference (MID) was met when the mean of HRQoL scores between groups differed by at least 3 %.
RESULTS
After a mean follow-up of 3.2 years, there were significant improvements in the SF-6D (+0.008, p = 0.04) and PCS (+1.57, p < 0.0001) scores in ILS but not in MET participants (+0.002 and +0.15, respectively, p = 0.6) compared to the PLB group. ILS participants showed improvements in general health (+3.2, p < 0.001), physical function (+3.6, p < 0.001), bodily pain (+1.9, p = 0.01), and vitality (+2.1, p = 0.01) domain scores. Treatment effects remained significant after adjusting sequentially for baseline demographic factors, and for medical and psychological comorbidities. Increased physical activity and weight reduction mediated these ILS treatment effects. Participants who experienced weight gain had significant worsening on the same HRQoL specific domains when compared to those that had treatment-related (ILS or MET) weight loss. No benefits with ILS or MET were observed in the MCS score.
CONCLUSION
Overweight/obese adults at high risk for diabetes show small improvement in most physical HRQoL and vitality scores through the weight loss and increased physical activity achieved with an ILS intervention.
Electronic supplementary material
The online version of this article (doi:10.1007/s11606-012-2122-5) contains supplementary material, which is available to authorized users.
doi:10.1007/s11606-012-2122-5
PMCID: PMC3509296  PMID: 22692637
quality of life; lifestyle; metformin; diabetes risk; weight loss
4.  Predictors of Mortality Over 8 Years in Type 2 Diabetic Patients 
Diabetes Care  2012;35(6):1301-1309.
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.
doi:10.2337/dc11-2281
PMCID: PMC3357242  PMID: 22432119
6.  Getting Under the Skin of Clinical Inertia in Insulin Initiation: The Translating Research Into Action for Diabetes (TRIAD) Insulin Starts Project 
The Diabetes educator  2012;38(1):94-100.
Purpose
The purpose of this cross-sectional study is to explore primary care providers’ (PCPs) perceptions about barriers to initiating insulin among patients. Studies suggest that many patients with poorly controlled type 2 diabetes do not receive insulin initiation by PCPs.
Methods
As part of the TRIAD study, we conducted structured interviews in health systems in Indiana, New Jersey, and California, asking PCPs about the importance of insulin initiation and factors affecting this decision. We calculated proportions choosing each multiple-choice response option and listed the most frequently offered open-ended response categories.
Results
Among 83 PCPs, 45% were women, 60% were Caucasian, and they averaged 13.4 years in practice. Four-fifths of PCPs endorsed guideline-concordant glycemic targets, but 54% individualized targets based on patient age, life expectancy, medical co-morbidities, self-management capacity, and willingness. Most (64%) reported that many patients were resistant to new oral or insulin therapies due to fears about the therapy and what it meant about their disease progression. Two-thirds (64%) cited patient resistance as a barrier to insulin initiation, and 43% cited problems with patient self-management, including cognitive or mental health issues, dexterity, or ability to adhere.† Eighty percent felt that patient non-adherence would dissuade them from initiating insulin at least some of the time.
Conclusions
PCPs perceived that patient resistance and poor self-management skills were significant barriers to initiating insulin. Future studies should investigate whether systems-level interventions to improve patient-provider communication about insulin and enhance providers’ perceptions of patient self-management capacity can increase guideline-concordant, patient-centered insulin initiation.
doi:10.1177/0145721711432649
PMCID: PMC3557962  PMID: 22222513
diabetes; insulin therapy; clinical inertia; clinical decision-making
7.  Thiazolidinediones, Cardiovascular Disease and Cardiovascular Mortality: Translating Research Into Action For Diabetes (TRIAD) 
Background
Studies have associated thiazolidinedione (TZD) treatment with cardiovascular disease (CVD) and questioned whether the two available TZDs, rosiglitazone and pioglitazone, have different CVD risks. We compared CVD incidence, cardiovascular (CV) and all-cause mortality in type 2 diabetic patients treated with rosiglitazone or pioglitazone as their only TZD.
Methods
We analyzed survey, medical record, administrative, and National Death Index (NDI) data from 1999 through 2003 from Translating Research Into Action for Diabetes (TRIAD), a prospective observational study of diabetes care in managed care. Medications, CV procedures, and CVD were determined from health plan (HP) administrative data, and mortality was from NDI. Adjusted hazard rates (AHR) were derived from Cox proportional hazard models adjusted for age, sex, race/ethnicity, income, history of diabetic nephropathy, history of CVD, insulin use, and HP.
Results
Across TRIAD’s ten HPs, 1,815 patients (24%) filled prescriptions for a TZD, 773 (10%) for only rosiglitazone, 711 (10%) for only pioglitazone, and 331 (4%) for multiple TZDs. In the seven HPs using both TZDs, 1,159 patients (33%) filled a prescription for a TZD, 564 (16%) for only rosiglitazone, 334 (10%) for only pioglitazone, and 261 (7%) for multiple TZDs. For all CV events, CV and all-cause mortality, we found no significant difference between rosiglitazone and pioglitazone.
Conclusions
In this relatively small, prospective, observational study, we found no statistically significant differences in CV outcomes for rosiglitazone- compared to pioglitazone-treated patients. There does not appear to be a pattern of clinically meaningful differences in CV outcomes for rosiglitazone- versus pioglitazone-treated patients.
doi:10.1002/pds.1954
PMCID: PMC3548906  PMID: 20583206
Thiazolidinediones; rosiglitazone; pioglitazone; diabetes
8.  Evaluation of risk equations for prediction of short-term coronary heart disease events in patients with long-standing type 2 diabetes: the Translating Research into Action for Diabetes (TRIAD) study 
Background
To evaluate the U.K. Prospective Diabetes Study (UKPDS) and Framingham risk equations for predicting short-term risk of coronary heart disease (CHD) events among adults with long-standing type 2 diabetes, including those with and without preexisting CHD.
Methods
Prospective cohort of U.S. managed care enrollees aged ≥ 18 years and mean diabetes duration of more than 10 years, participating in the Translating Research into Action for Diabetes (TRIAD) study, was followed for the first occurrence of CHD events from 2000 to 2003. The UKPDS and Framingham risk equations were evaluated for discriminating power and calibration.
Results
A total of 8303 TRIAD participants, were identified to evaluate the UKPDS (n = 5914, 120 events), Framingham-initial (n = 5914, 218 events) and Framingham-secondary (n = 2389, 374 events) risk equations, according to their prior CHD history. All of these equations exhibited low discriminating power with Harrell’s c-index <0.65. All except the Framingham-initial equation for women and the Framingham-secondary equation for men had low levels of calibration. After adjsusting for the average values of predictors and event rates in the TRIAD population, the calibration of these equations greatly improved.
Conclusions
The UKPDS and Framingham risk equations may be inappropriate for predicting the short-term risk of CHD events in patients with long-standing type 2 diabetes, partly due to changes in medications used by patients with diabetes and other improvements in clinical care since the Frmaingham and UKPDS studies were conducted. Refinement of these equations to reflect contemporary CHD profiles, diagnostics and therapies are needed to provide reliable risk estimates to inform effective treatment.
doi:10.1186/1472-6823-12-12
PMCID: PMC3433369  PMID: 22776317
9.  Temporal Trends in Recording of Diabetes on Death Certificates 
Diabetes Care  2011;34(7):1529-1533.
OBJECTIVE
To determine the frequency that diabetes is reported on death certificates of decedents with known diabetes and describe trends in reporting over 8 years.
RESEARCH DESIGN AND METHODS
Data were obtained from 11,927 participants with diabetes who were enrolled in Translating Research into Action for Diabetes, a multicenter prospective observational study of diabetes care in managed care. Data on decedents (N = 2,261) were obtained from the National Death Index from 1 January 2000 through 31 December 2007. The primary dependent variables were the presence of the ICD-10 codes for diabetes listed anywhere on the death certificate or as the underlying cause of death.
RESULTS
Diabetes was recorded on 41% of death certificates and as the underlying cause of death for 13% of decedents with diabetes. Diabetes was significantly more likely to be reported on the death certificate of decedents dying of cardiovascular disease than all other causes. There was a statistically significant trend of increased reporting of diabetes as the underlying cause of death over time (P < 0.001), which persisted after controlling for duration of diabetes at death. The increase in reporting of diabetes as the underlying cause of death was associated with a decrease in the reporting of cardiovascular disease as the underlying cause of death (P < 0.001).
CONCLUSIONS
Death certificates continue to underestimate the prevalence of diabetes among decedents. The increase in reporting of diabetes as the underlying cause of death over the past 8 years will likely impact estimates of the burden of diabetes in the U.S.
doi:10.2337/dc10-2312
PMCID: PMC3120163  PMID: 21709292
10.  Contracting and Monitoring Relationships for Adolescents with Type 1 Diabetes: A Pilot Study 
Abstract
Background
Adolescents are developmentally in a period of transition—from children cared for by their parents to young adults capable of self-care, independent judgment, and self-directed problem solving. We wished to develop a behavioral contract for adolescent diabetes management that addresses some negotiable points of conflict within the parent–child relationship regarding self-monitoring and then assess its effectiveness in a pilot study as part of a novel cell phone–based glucose monitoring system.
Methods
In the first phase of this study we used semistructured interview techniques to determine the major sources of diabetes-related conflict in the adolescent–parent relationship, to identify factors that could facilitate or inhibit control, and to determine reasonable goals and expectations. These data were then used to inform development of a behavioral contract that addressed the negotiable sources of conflict between parents and their adolescent. The second phase of this research was a 3-month pilot study to measure how a novel cell phone glucose monitoring system would support the contract and have an effect on glucose management, family conflict, and quality of life.
Results
Interviews were conducted with 10 adolescent–caregiver pairs. The major theme of contention was nagging about diabetes management. Two additional themes emerged as points of negotiation for the behavioral contract: glucose testing and contact with the diabetes clinical team. Ten adolescent–parent pairs participated in the pilot test of the system and contract. There was a significant improvement in the Diabetes Self-Management Profile from 55.2 to 61.1 (P < 0.01). A significant reduction in hemoglobin A1c also occurred, from 8.1% at the start of the trial to 7.6% at 3 months (P < 0.04).
Conclusions
This study confirms previous findings that mobile technologies do offer significant potential in improving the care of adolescents with type 1 diabetes. Moreover, behavioral contracts may be an important adjunct to reduce nagging and improve outcomes with behavioral changes.
doi:10.1089/dia.2010.0181
PMCID: PMC3132067  PMID: 21406011
11.  Antidepressant Medicine Use and Risk of Developing Diabetes During the Diabetes Prevention Program and Diabetes Prevention Program Outcomes Study 
Diabetes Care  2010;33(12):2549-2551.
OBJECTIVE
To assess the association between antidepressant medicine use and risk of developing diabetes during the Diabetes Prevention Program (DPP) and Diabetes Prevention Program Outcomes Study (DPPOS).
RESEARCH DESIGN AND METHODS
DPP/DPPOS participants were assessed for diabetes every 6 months and for antidepressant use every 3 months in DPP and every 6 months in DPPOS for a median 10.0-year follow-up.
RESULTS
Controlled for factors associated with diabetes risk, continuous antidepressant use compared with no use was associated with diabetes risk in the placebo (adjusted hazard ratio 2.34 [95% CI 1.32–4.15]) and lifestyle (2.48 [1.45–4.22]) arms, but not in the metformin arm (0.55 [0.25–1.19]).
CONCLUSIONS
Continuous antidepressant use was significantly associated with diabetes risk in the placebo and lifestyle arms. Measured confounders and mediators did not account for this association, which could represent a drug effect or reflect differences not assessed in this study between antidepressant users and nonusers.
doi:10.2337/dc10-1033
PMCID: PMC2992187  PMID: 20805256
12.  Changes in Health State Utilities With Changes in Body Mass in the Diabetes Prevention Program 
Obesity (Silver Spring, Md.)  2009;17(12):2176-2181.
Health utilities are measures of health-related quality of life (HRQL) used in cost-effectiveness research. We evaluated whether changes in body weight were associated with changes in health utilities in the Diabetes Prevention Program (DPP) and whether associations differed by treatment assignment (lifestyle intervention, metformin, placebo) or baseline obesity severity. We constructed physical (PCS-36) and mental component summary (MCS-36) subscales and short-form-6D (SF-6D) health utility index for all DPP participants completing a baseline 36-item short form (SF-36) HRQL assessment (N = 3,064). We used linear regression to test associations between changes in body weight and changes in HRQL indicators, while adjusting for other demographic and behavioral variables. Overall differences in HRQL between treatment groups were highly statistically significant but clinically small after 1 year. In multivariable models, weight change was independently associated with change in SF-6D score (increase of 0.007 for every 5 kg weight loss; P < 0.001), but treatment effects independent of weight loss were not. We found no significant interaction between baseline obesity severity and changes in SF-6D with changes in body weight. However, increases in physical function (PCS-36) with weight loss were greater in persons with higher baseline obesity severity. In summary, improvements in HRQL are associated with weight loss but not with other effects of obesity treatments that are unrelated to weight loss. Although improvements in the SF-6D did not exceed commonly reported thresholds for a minimally important difference (0.04), these changes, if causal, could still have a significant impact on clinical cost-effectiveness estimates if sustained over multiple years.
doi:10.1038/oby.2009.114
PMCID: PMC3135001  PMID: 19390518
13.  Barriers to Insulin Initiation 
Diabetes Care  2010;33(4):733-735.
OBJECTIVE
Reasons for failing to initiate prescribed insulin (primary nonadherence) are poorly understood. We investigated barriers to insulin initiation following a new prescription.
RESEARCH DESIGN AND METHODS
We surveyed insulin-naïve patients with poorly controlled type 2 diabetes, already treated with two or more oral agents who were recently prescribed insulin. We compared responses for respondents prescribed, but never initiating, insulin (n = 69) with those dispensed insulin (n = 100).
RESULTS
Subjects failing to initiate prescribed insulin commonly reported misconceptions regarding insulin risk (35% believed that insulin causes blindness, renal failure, amputations, heart attacks, strokes, or early death), plans to instead work harder on behavioral goals, sense of personal failure, low self-efficacy, injection phobia, hypoglycemia concerns, negative impact on social life and job, inadequate health literacy, health care provider inadequately explaining risks/benefits, and limited insulin self-management training.
CONCLUSIONS
Primary adherence for insulin may be improved through better provider communication regarding risks, shared decision making, and insulin self-management training.
doi:10.2337/dc09-1184
PMCID: PMC2845015  PMID: 20086256
14.  Race and Medication Adherence and Glycemic Control: Findings from an Operational Health Information Exchange 
AMIA Annual Symposium Proceedings  2011;2011:1649-1657.
The Central Indiana Beacon Community leads efforts for improving adherence to oral hypoglycemic agents (OHA) to achieve improvements in glycemic control for patients with type 2 diabetes. In this study, we explored how OHA adherence affected hemoglobin A1C (HbA1c) level in different racial groups. OHA adherence was measured by 6-month proportion of days covered (PDC). Of 3,976 eligible subjects, 12,874 pairs of 6-month PDC and HbA1c levels were formed between 2002 and 2008. The average HbA1c levels were 7.4% for African-Americans and 6.5% for Whites. The average 6-month PDCs were 40% for African-Americans and 50% for Whites. In mixed effect generalized linear regression analyses, OHA adherence was inversely correlated with HbA1c level for both African-Americans (−0.80, p<0.0001) and Whites (−0.53, p<0.0001). The coefficient was −0.26 (p<0.0001) for the interaction of 6-month PDC and African-Americans. Significant risk factors for OHA non-adherence were race, young age, non-commercial insurance, newly-treated status, and polypharmacy.
PMCID: PMC3243292  PMID: 22195231
15.  Primary Language, Income and the Intensification of Anti-glycemic Medications in Managed Care: the (TRIAD) Study 
ABSTRACT
BACKGROUND
Patients who speak Spanish and/or have low socioeconomic status are at greater risk of suboptimal glycemic control. Inadequate intensification of anti-glycemic medications may partially explain this disparity.
OBJECTIVE
To examine the associations between primary language, income, and medication intensification.
DESIGN
Cohort study with 18-month follow-up.
PARTICIPANTS
One thousand nine hundred and thirty-nine patients with Type 2 diabetes who were not using insulin enrolled in the Translating Research into Action for Diabetes Study (TRIAD), a study of diabetes care in managed care.
MEASUREMENTS
Using administrative pharmacy data, we compared the odds of medication intensification for patients with baseline A1c ≥ 8%, by primary language and annual income. Covariates included age, sex, race/ethnicity, education, Charlson score, diabetes duration, baseline A1c, type of diabetes treatment, and health plan.
RESULTS
Overall, 42.4% of patients were taking intensified regimens at the time of follow-up. We found no difference in the odds of intensification for English speakers versus Spanish speakers. However, compared to patients with incomes <$15,000, patients with incomes of $15,000-$39,999 (OR 1.43, 1.07-1.92), $40,000-$74,999 (OR 1.62, 1.16-2.26) or >$75,000 (OR 2.22, 1.53-3.24) had increased odds of intensification. This latter pattern did not differ statistically by race.
CONCLUSIONS
Low-income patients were less likely to receive medication intensification compared to higher-income patients, but primary language (Spanish vs. English) was not associated with differences in intensification in a managed care setting. Future studies are needed to explain the reduced rate of intensification among low income patients in managed care.
Electronic supplementary material
The online version of this article (doi:10.1007/s11606-010-1588-2) contains supplementary material, which is available to authorized users.
doi:10.1007/s11606-010-1588-2
PMCID: PMC3077478  PMID: 21174165
16.  The Prevention of Type 2 Diabetes: An Overview 
Type 2 diabetes mellitus is one of the major public health threats in the United States today, reaching epidemic rates. Epidemiological evidence suggests a strong link between obesity and the risk of developing diabetes. Increasing evidence demonstrates that lifestyle interventions can significantly delay or possibly prevent the onset of type 2 diabetes in persons with increased risk. Despite these findings, there remain important barriers to the translation of this research to the public health. These include identifying persons with an increased risk for developing the disease and the lack of easily accessible, cost-effective intervention programs. At least one study, however, has effectively implemented an evidenced-based intervention in community settings, suggesting that it may be possible to develop a model for the national scalability of primary prevention in the United States.
PMCID: PMC2769939  PMID: 20144325
community programs; lifestyle interventions; primary prevention; review; type 2 diabetes
17.  Effect of Advanced Access Scheduling on Processes and Intermediate Outcomes of Diabetes Care and Utilization 
ABSTRACT
BACKGROUND
The impact of open access (OA) scheduling on chronic disease care and outcomes has not been studied.
OBJECTIVE
To assess the effect of OA implementation at 1 year on: (1) diabetes care processes (testing for A1c, LDL, and urine microalbumin), (2) intermediate outcomes of diabetes care (SBP, A1c, and LDL level), and (3) health-care utilization (ED visits, hospitalization, and outpatient visits).
METHODS
We used a retrospective cohort study design to compare process and outcomes for 4,060 continuously enrolled adult patients with diabetes from six OA clinics and six control clinics. Using a generalized linear model framework, data were modeled with linear regression for continuous, logistic regression for dichotomous, and Poisson regression for utilization outcomes.
RESULTS
Patients in the OA clinics were older, with a higher percentage being African American (51% vs 34%) and on insulin. In multivariate analyses, for A1c testing, the odds ratio for African-American patients in OA clinics was 0.47 (CI: 0.29-0.77), compared to non-African Americans [OR 0.27 (CI: 0.21-0.36)]. For urine microablumin, the odds ratio for non-African Americans in OA clinics was 0.37 (CI: 0.17-0.81). At 1 year, in adjusted analyses, patients in OA clinics had significantly higher SBP (mean 6.4 mmHg, 95% CI 5.4 – 7.5). There were no differences by clinic type in any of the three health-care utilization outcomes.
CONCLUSION
OA scheduling was associated with worse processes of care and SBP at 1 year. OA clinic scheduling should be examined more critically in larger systems of care, multiple health-care settings, and/or in a randomized controlled trial.
doi:10.1007/s11606-008-0888-2
PMCID: PMC2642566  PMID: 19132326
diabetes; open access; process of care; outcomes; utilization
18.  Value of Urinary Albumin-to-Creatinine Ratio as a Predictor of Type 2 Diabetes in Pre-Diabetic Individuals  
Diabetes Care  2008;31(12):2344-2348.
OBJECTIVE—The albumin-to-creatinine ratio (ACR) reflects urinary albumin excretion and is increasingly being accepted as an important clinical outcome predictor. Because of the great public health need for a simple and inexpensive test to identify individuals at high risk for developing type 2 diabetes, it has been suggested that the ACR might serve this purpose. We therefore determined whether the ACR could predict incident diabetes in a well-characterized cohort of pre-diabetic Americans.
RESEARCH DESIGN AND METHODS—A total of 3,188 Diabetes Prevention Program (DPP) participants with a mean BMI of 34 kg/m2 and elevated fasting glucose, impaired glucose tolerance, and baseline urinary albumin excretion measurements were followed for incident diabetes over a mean of 3.2 years.
RESULTS—Of the participants, 94% manifested ACR levels below the microalbuminuria range and 21% ultimately developed diabetes during follow-up. Quartiles of ACR (median [range] within quartiles: 1, 3.0 [0.7–3.7]; 2, 4.6 [3.7–5.5]; 3, 7.1 [5.5–9.7]; and 4, 16.5 [9.7–1,578]) were positively associated with age, markers of adiposity and insulin secretion and resistance, blood pressure, and use of antihypertensive agents with antiproteinuric effects and inversely related to male sex and serum creatinine. An elevated hazard rate for developing diabetes with doubling of ACR disappeared after adjustment for covariates. Within the DPP intervention groups (placebo, lifestyle, and metformin), we found no consistent trend in incident diabetes by quartile or decile of ACR.
CONCLUSIONS—An ACR at levels below the microalbuminuria range does not independently predict incident diabetes in adults at high risk of developing type 2 diabetes.
doi:10.2337/dc08-0148
PMCID: PMC2584193  PMID: 18796622
19.  Translating the Diabetes Prevention Program into the Community The DEPLOY Pilot Study 
Background
The Diabetes Prevention Program (DPP) found that an intensive lifestyle intervention can reduce the development of diabetes by more than half in adults with prediabetes, but there is little information about the feasibility of offering such an intervention in community settings. This study evaluated the delivery of a group-based DPP lifestyle intervention in partnership with the YMCA.
Methods
This pilot cluster-randomized trial was designed to compare group-based DPP lifestyle intervention delivery by the YMCA to brief counseling alone (control) in adults who attended a diabetes risk-screening event at one of two semi-urban YMCA facilities and who had a BMI ≥24 kg/m2, ≥2 diabetes risk factors, and a random capillary blood glucose of 110–199 mg/dL. Multivariate regression was used to compare between-group differences in changes in body weight, blood pressures, HbA1c, total cholesterol, and HDL-cholesterol after 6 and 12 months.
Results
Among 92 participants, controls were more often women (61% vs 50%) and of nonwhite race (29% vs 7%). After 6 months, body weight decreased by 6.0% (95% CI=4.7, 7.3) in intervention participants and 2.0% (95% CI=0.6, 3.3) in controls (p<0.001; difference between groups). Intervention participants also had greater changes in total cholesterol (−22 mg/dL vs +6 mg/dL controls; p<0.001). These differences were sustained after 12 months, and adjustment for differences in race and gender did not alter these findings. With only two matched YMCA sites, it was not possible to adjust for potential clustering by site.
Conclusions
The YMCA may be a promising channel for wide-scale dissemination of a low-cost approach to lifestyle diabetes prevention.
doi:10.1016/j.amepre.2008.06.035
PMCID: PMC2610485  PMID: 18779029
20.  Sex Differences in Diabetes Risk and the Effect of Intensive Lifestyle Modification in the Diabetes Prevention Program  
Diabetes Care  2008;31(7):1416-1421.
OBJECTIVE—In participants of the Diabetes Prevention Program (DPP) randomized to intensive lifestyle modification (ILS), meeting ILS goals strongly correlated with prevention of diabetes in the group as a whole. Men met significantly more ILS goals than women but had a similar incidence of diabetes. Therefore, we explored sex differences in risk factors for diabetes and the effect of ILS on risk factors.
RESEARCH DESIGN AND METHODS—Baseline risk factors for diabetes and percent change in risk factors over the first year in men versus women were compared using Wilcoxon's rank-sum tests.
RESULTS—At baseline, men were older and had a larger waist circumference; higher fasting plasma glucose concentration, caloric intake, and blood pressure; and lower HDL cholesterol and corrected insulin response than women, who were less physically active and had a higher BMI (P < 0.01 for all comparisons). Over the first year of the DPP, no sex difference in risk factors for diabetes was observed for those who lost <3% body weight. Weight loss of 3–7% body weight yielded greater decreases in 2-h glucose (P < 0.01), insulin concentration (P < 0.04), and insulin resistance (P < 0.03) in men than in women. Weight loss of >7% body weight resulted in greater decreases in 2-h glucose (P < 0.01), triglyceride level (P < 0.01), and A1C (P < 0.03) in men than in women.
CONCLUSIONS—Weight loss >3% body weight yielded greater reduction in risk factors for diabetes in men than in women. Despite the more favorable effects of ILS in men, baseline risk factors were more numerous in men and likely obscured any sex difference in incident diabetes.
doi:10.2337/dc07-2390
PMCID: PMC2453677  PMID: 18356403
21.  The prevention of type 2 diabetes 
SUMMARY
Type 2 diabetes mellitus (T2DM) affects more than 7% of adults in the US and leads to substantial personal and economic burden. In prediabetic states insulin secretion and action—potential targets of preventive interventions—are impaired. In trials lifestyle modification (i.e. weight loss and exercise) has proven effective in preventing incident T2DM in high-risk groups, although weight loss has the greatest effect. Various medications (e.g. metformin, thiazolidinediones and acarbose) can also prevent or delay T2DM. Whether diabetes-prevention strategies also ultimately prevent the development of diabetic vascular complications is unknown, but cardiovascular risk factors are favorably affected. Preventive strategies that can be implemented in routine clinical settings have been developed and evaluated. Widespread application has, however, been limited by local financial considerations, even though cost-effectiveness might be achieved at the population level.
doi:10.1038/ncpendmet0843
PMCID: PMC2573045  PMID: 18493227
impaired glucose tolerance; prediabetes; prevention; type 2 diabetes
22.  Sex Differences in Diabetes Risk and the Effect of Intensive Lifestyle Modification in the Diabetes Prevention Program 
Diabetes care  2008;31(7):1416-1421.
OBJECTIVE
In participants of the Diabetes Prevention Program (DPP) randomized to intensive lifestyle modification (ILS), meeting ILS goals strongly correlated with prevention of diabetes in the group as a whole. Men met significantly more ILS goals than women but had a similar incidence of diabetes. Therefore, we explored sex differences in risk factors for diabetes and the effect of ILS on risk factors.
RESEARCH DESIGN AND METHODS
Baseline risk factors for diabetes and percent change in risk factors over the first year in men versus women were compared using Wilcoxon’s rank-sum tests.
RESULTS
At baseline, men were older and had a larger waist circumference; higher fasting plasma glucose concentration, caloric intake, and blood pressure; and lower HDL cholesterol and corrected insulin response than women, who were less physically active and had a higher BMI (P < 0.01 for all comparisons). Over the first year of the DPP, no sex difference in risk factors for diabetes was observed for those who lost <3% body weight. Weight loss of 3–7% body weight yielded greater decreases in 2-h glucose (P < 0.01), insulin concentration (P < 0.04), and insulin resistance (P < 0.03) in men than in women. Weight loss of >7% body weight resulted in greater decreases in 2-h glucose (P < 0.01), triglyceride level (P < 0.01), and A1C (P < 0.03) in men than in women.
CONCLUSIONS
Weight loss >3% body weight yielded greater reduction in risk factors for diabetes in men than in women. Despite the more favorable effects of ILS in men, baseline risk factors were more numerous in men and likely obscured any sex difference in incident diabetes.
doi:10.2337/dc07-2390
PMCID: PMC2453677  PMID: 18356403
23.  Elevated Depression Symptoms, Antidepressant Medicine Use, and Risk of Developing Diabetes During the Diabetes Prevention Program 
Diabetes care  2007;31(3):420-426.
OBJECTIVE
To assess the association between elevated depression symptoms or antidepressant medicine use on entry to the Diabetes Prevention Program (DPP) and during the study and the risk of developing diabetes during the study.
RESEARCH DESIGN AND METHODS
DPP participants (n = 3,187) in three treatment arms (intensive lifestyle [ILS], metformin [MET], and placebo [PLB]) completed the Beck Depression Inventory (BDI) and reported their use of antidepressant medication at randomization and throughout the study (average duration in study 3.2 years).
RESULTS
When other factors associated with the risk of developing diabetes were controlled, elevated BDI scores at baseline or during the study were not associated with diabetes risk in any arm. Baseline antidepressant use was associated with diabetes risk in the PLB (hazard ratio 2.25 [95% CI 1.38–3.66]) and ILS (3.48 [1.93–6.28]) arms. Continuous antidepressant use during the study (compared with no use) was also associated with diabetes risk in the same arms (PLB 2.60 [1.37–4.94]; ILS 3.39 [1.61–7.13]), as was intermittent antidepressant use during the study in the ILS arm (2.07 [1.18–3.62]). Among MET arm participants, antidepressant use was not associated with developing diabetes.
CONCLUSIONS
A strong and statistically significant association between antidepressant use and diabetes risk in the PLB and ILS arms was not accounted for by measured confounders or mediators. If future research finds that antidepressant use independently predicts diabetes risk, efforts to minimize the negative effects of antidepressant agents on glycemic control should be pursued.
doi:10.2337/dc07-1827
PMCID: PMC2373986  PMID: 18071002
24.  Educational disparities in health behaviors among patients with diabetes: the Translating Research Into Action for Diabetes (TRIAD) Study 
BMC Public Health  2007;7:308.
Background
Our understanding of social disparities in diabetes-related health behaviors is incomplete. The purpose of this study was to determine if having less education is associated with poorer diabetes-related health behaviors.
Methods
This observational study was based on a cohort of 8,763 survey respondents drawn from ~180,000 patients with diabetes receiving care from 68 provider groups in ten managed care health plans across the United States. Self-reported survey data included individual educational attainment ("education") and five diabetes self-care behaviors among individuals for whom the behavior would clearly be indicated: foot exams (among those with symptoms of peripheral neuropathy or a history of foot ulcers); self-monitoring of blood glucose (SMBG; among insulin users only); smoking; exercise; and certain diabetes-related health seeking behaviors (use of diabetes health education, website, or support group in last 12 months). Predicted probabilities were modeled at each level of self-reported educational attainment using hierarchical logistic regression models with random effects for clustering within health plans.
Results
Patients with less education had significantly lower predicted probabilities of being a non-smoker and engaging in regular exercise and health-seeking behaviors, while SMBG and foot self-examination did not vary by education. Extensive adjustment for patient factors revealed no discernable confounding effect on the estimates or their significance, and most education-behavior relationships were similar across sex, race and other patient characteristics. The relationship between education and smoking varied significantly across age, with a strong inverse relationship in those aged 25–44, modest for those ages 45–64, but non-evident for those over 65. Intensity of disease management by the health plan and provider communication did not alter the examined education-behavior relationships. Other measures of socioeconomic position yielded similar findings.
Conclusion
The relationship between educational attainment and health behaviors was modest in strength for most behaviors. Over the life course, the cumulative effect of reduced practice of multiple self-care behaviors among less educated patients may play an important part in shaping the social health gradient.
doi:10.1186/1471-2458-7-308
PMCID: PMC2238766  PMID: 17967177
25.  A Critical Dialogue: Communicating with Type 2 Diabetes Patients about Cardiovascular Risk 
Patients with type 2 diabetes mellitus (DM) are at increased risk for cardiovascular disease (CVD), and many patients are inadequately treated for risk factors such as hyperglycemia, hyperlipidemia, hypertension, and smoking. Providing individualized risk information in a clear and engaging manner may serve to encourage both patients and their physicians to intensify risk-reducing behaviors and therapies. This review outlines simple and effective methods for making CVD risk infomation understandable to persons of all levels of literacy and mathematical ability. To allow the patient to understand what might happen and how, personal risk factors should be clearly communicated and the potential consequences of a CVD event should be presented in a graphic but factual manner. Risk calculation software can provide CVD risk estimates, and the resulting information can be made understandable by assigning risk severity (eg, “high”) by comparing clinical parameters with accepted treatment targets and by comparing the individual's risk with that of the “average” person. Patients must also be informed about how they might reduce their CVD risk and be supported in these efforts. Thoughtful risk communication using these techniques can improve access to health information for individuals of low literacy, especially when interactive computer technology is employed. Research is needed to find the best methods for communicating risk in daily clinical practice.
PMCID: PMC1993965  PMID: 17315602
cardiovascular disease; type 2 diabetes; cardiovascular risk; risk communication

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