Provider Preference for Growth Charts in Tracking Children with Obesity.

A web-based survey of pediatric care providers revealed differences in their preference for clinical charts that monitor growth in children with obesity. These findings are attributed to pediatric specialty training. Very few providers believe the currently available Centers for Disease Control and Prevention 2000 body mass index-for-age charts adequately track growth in children with obesity.

Short and long-term lifestyle coaching approaches used to address diverse participant barriers to weight loss and physical activity adherence.

BACKGROUND: Individual barriers to weight loss and physical activity goals in the Diabetes Prevention Program, a randomized trial with 3.2 years average treatment duration, have not been previously reported. Evaluating barriers and the lifestyle coaching approaches used to improve adherence in a large, diverse participant cohort can inform dissemination efforts. METHODS: Lifestyle coaches documented barriers and approaches after each session (mean session attendance = 50.3 ± 21.8). Subjects were 1076 intensive lifestyle participants (mean age = 50.6 years; mean BMI = 33.9 kg/m²; 68% female, 48% non-Caucasian). Barriers and approaches used to improve adherence were ranked by the percentage of the cohort for whom they applied. Barrier groupings were also analyzed in relation to baseline demographic characteristics. RESULTS: Top weight loss barriers reported were problems with self-monitoring (58%); social cues (58%); holidays (54%); low activity (48%); and internal cues (thought/mood) (44%). Top activity barriers were holidays (51%); time management (50%); internal cues (30%); illness (29%), and motivation (26%). The percentage of the cohort having any type of barrier increased over the long-term intervention period. A majority of the weight loss barriers were significantly associated with younger age, greater obesity, and non-Caucasian race/ethnicity (p-values vary). Physical activity barriers, particularly thought and mood cues, social cues and time management, physical injury or illness and access/weather, were most significantly associated with being female and obese (p < 0.001 for all). Lifestyle coaches used problem-solving with most participants (≥75% short-term; > 90% long term) and regularly reviewed self-monitoring skills. More costly approaches were used infrequently during the first 16 sessions (≤10%) but increased over 3.2 years. CONCLUSION: Behavioral problem solving approaches have short and long term dissemination potential for many kinds of participant barriers. Given minimal resources, increased attention to training lifestyle coaches in the consistent use of these approaches appears warranted.

The Impact of Physical Activity on the Prevention of Type 2 Diabetes: Evidence and Lessons Learned From the Diabetes Prevention Program, a Long-Standing Clinical Trial Incorporating Subjective and Objective Activity Measures.

OBJECTIVE: Across the Diabetes Prevention Program (DPP) follow-up, cumulative diabetes incidence remained lower in the lifestyle compared with the placebo and metformin randomized groups and could not be explained by weight. Collection of self-reported physical activity (PA) (yearly) with cross-sectional objective PA (in follow-up) allowed for examination of PA and its long-term impact on diabetes prevention. RESEARCH DESIGN AND METHODS: Yearly self-reported PA and diabetes assessment and oral glucose tolerance test results (fasting glucose semiannually) were collected for 3,232 participants with one accelerometry assessment 11-13 years after randomization (n = 1,793). Mixed models determined PA differences across treatment groups. The association between PA and diabetes incidence was examined using Cox proportional hazards models. RESULTS: There was a 6% decrease (Cox proportional hazard ratio 0.94 [95% CI 0.92, 0.96]; P < 0.001) in diabetes incidence per 6 MET-h/week increase in time-dependent PA for the entire cohort over an average of 12 years (controlled for age, sex, baseline PA, and weight). The effect of PA was greater (12% decrease) among participants less active at baseline (<7.5 MET-h/week) (n = 1,338) (0.88 [0.83, 0.93]; P < 0.0001), with stronger findings for lifestyle participants. Lifestyle had higher cumulative PA compared with metformin or placebo (P < 0.0001) and higher accelerometry total minutes per day measured during follow-up (P = 0.001 and 0.047). All associations remained significant with the addition of weight in the models. CONCLUSIONS: PA was inversely related to incident diabetes in the entire cohort across the study, with cross-sectional accelerometry results supporting these findings. This highlights the importance of PA within lifestyle intervention efforts designed to prevent diabetes and urges health care providers to consider both PA and weight when counseling high-risk patients.

Diet quality, weight loss, and diabetes incidence in the Diabetes Prevention Program (DPP).

BACKGROUND: We evaluated whether diet quality is a predictor of weight loss and reduced diabetes risk, independent of caloric intake in the Diabetes Prevention Program (DPP) cohort, a randomized clinical trial of adults at risk for diabetes. METHODS: This secondary analysis included 2914 participants with available data (964 intensive lifestyle (ILS), 977 metformin, 973 placebo). Dietary intake was assessed using a 117-item food frequency questionnaire. Diet quality was quantified using the Alternative Healthy Eating Index 2010 (AHEI). AHEI ranges from 0 to 110, with higher scores corresponding to higher quality diets. ILS participants had greater improvement (p < 0.001) in AHEI over 1-year (4.2 ± 9.0) compared to metformin (1.2 ± 8.5) and placebo (1.4 ± 8.4). We examined the association between AHEI change and weight change from baseline to 1-year using linear regression, and that between 1-year AHEI change and incident diabetes, using hazard models over an average 3 years follow-up. Models were evaluated within treatment group and adjusted for relevant characteristics including caloric intake, physical activity, BMI and AHEI. Models testing incident diabetes were further adjusted for baseline fasting and 2 h glucose. RESULTS: An increase in AHEI score was associated with weight loss in ILS [ß per 10-point increase (SE) -1.2 kg (0.3, p < 0.001)], metformin [- 0. 90 kg (0.2, p < 0.001)] and placebo [- 0.55 kg (0.2, p = 0.01)]. However, AHEI change was not associated with incident diabetes in any group before or after adjustment for weight change. CONCLUSIONS: Controlling for weight, diet quality was not associated with diabetes incidence but helps achieve weight loss, an important factor in diabetes prevention.

Dietary intake in the diabetes prevention program cohort: baseline and 1-year post randomization.

PURPOSE: To describe usual dietary intake assessment at baseline and 1-year post-randomization in the ethnically diverse Diabetes Prevention Program cohort. METHODS: Participants were randomized to Lifestyle Modification, Metformin, or Placebo. Usual diet was assessed by a modified, previously validated food frequency interview. RESULTS: Complete data were available for 2934 subjects (90.7% of those randomized). Baseline median estimated energy intake was 7676 kJ/d (1828 kcal/d) and 8585 kJ/d (2044 kcal/d) for women and men, respectively. The median percent of energy from fat ranged from 30.6% for Asian American men to 37.5% for American Indian men and women. After 1 year among the Lifestyle group, the median change in total energy and percent energy from fat was -1897 kJ/d (-452 kcal/d) and -6.6%, respectively. For the Metformin and Placebo groups, change in median total energy was -1235 kJ/d (-294 kcal/d) and-1051 kJ/d (-250 kcal/d), respectively, and change in median percent energy from fat was -0.8% and-0.8%, respectively (p < 0.001 for differences between groups, adjusted for gender and ethnicity). CONCLUSIONS: One-year post-randomization, significant differences in dietary intake were observed in the Lifestyle compared with the Metformin or Placebo group, and these were consistent with the general intent of the DPP lifestyle modification intervention.

Prevention of Diabetes Through the Lifestyle Intervention: Lessons Learned from the Diabetes Prevention Program and Outcomes Study and its Translation to Practice.

A number of strategies have been used to delay or prevent the development of type 2 diabetes mellitus (T2D) in high-risk adults. Among them were diet, exercise, medications and surgery. This report focuses on the nutritional lessons learned from implementation of the Intensive Lifestyle Intervention (ILI) in the DPP and its follow-up DPPOS that looked at weight loss through modification of diet and exercise. The Diabetes Prevention Program (DPP) is a large clinical trial, sponsored by the National Institutes of Health, designed to look at several strategies to prevent conversion to type 2 diabetes (T2D) by adults with prediabetes (IGT/IFG) including an Intensive Lifestyle Intervention (ILI). The ∼3800 ethnically diverse participants (46% reported non-white race) were overweight, had impaired glucose tolerance (IGT) and impaired fasting glucose (IFG). Treatments were assigned randomly. The Diabetes Prevention Program Outcomes Study (DPPOS) is a follow up study evaluating the long-term outcomes of the clinical trial.

Achieving weight and activity goals among diabetes prevention program lifestyle participants.

OBJECTIVE: The Diabetes Prevention Program (DPP) showed that intensive lifestyle intervention reduced the risk of diabetes by 58%. This paper examines demographic, psychosocial, and behavioral factors related to achieving weight loss and physical activity goals in the DPP lifestyle participants. RESEARCH METHODS AND PROCEDURES: Lifestyle participants (n = 1079; mean age = 50.6, BMI = 33.9, 68% female, and 46% from minority groups) had goals of 7% weight loss and 150 min/wk of physical activity. Goal achievement was assessed at the end of the 16-session core curriculum (approximately week 24) and the final intervention visit (mean = 3.2 years) as a function of demographic, psychosocial, and behavioral variables. RESULTS: Forty-nine percent met the weight loss goal and 74% met the activity goal initially, while 37% and 67%, respectively, met these goals long-term. Men and those with lower initial BMI were more likely to meet activity but not weight loss goals. Hispanic, Asian, and Native Americans were more likely to meet the long-term activity goals, and whites were more likely to meet the initial weight loss goal. In multivariate analyses, meeting the long-term weight loss goal and both activity goals increased with age, while psychosocial and depression measures were unrelated to goal achievement. Dietary self-monitoring was positively related to meeting both weight loss and activity goals, and meeting the activity goal was positively related to meeting the weight loss goal. Participants who met initial goals were 1.5 to 3.0 times more likely to meet these goals long-term. DISCUSSION: Success at meeting the weight loss and activity goals increased with age. Initial success predicted long-term success. Self-monitoring and meeting activity goals were related to achieving and sustaining weight loss.