Rena R. Wing

Association of an Intensive Lifestyle Intervention With Remission of Type 2 Diabetes

CONTEXTnThe frequency of remission of type 2 diabetes achievable with lifestyle intervention is unclear.nnnOBJECTIVEnTo examine the association of a long-term intensive weight-loss intervention with the frequency of remission from type 2 diabetes to prediabetes or normoglycemia.nnnDESIGN, SETTING, AND PARTICIPANTSnAncillary observational analysis of a 4-year randomized controlled trial (baseline visit, August 2001-April 2004; last follow-up, April 2008) comparing an intensive lifestyle intervention (ILI) with a diabetes support and education control condition (DSE) among 4503 US adults with body mass index of 25 or higher and type 2 diabetes.nnnINTERVENTIONSnParticipants were randomly assigned to receive the ILI, which included weekly group and individual counseling in the first 6 months followed by 3 sessions per month for the second 6 months and twice-monthly contact and regular refresher group series and campaigns in years 2 to 4 (n=2241) or the DSE, which was an offer of 3 group sessions per year on diet, physical activity, and social support (n=2262).nnnMAIN OUTCOME MEASURESnPartial or complete remission of diabetes, defined as transition from meeting diabetes criteria to a prediabetes or nondiabetic level of glycemia (fasting plasma glucose <126 mg/dL and hemoglobin A1c <6.5% with no antihyperglycemic medication). RESULTS Intensive lifestyle intervention participants lost significantly more weight than DSE participants at year 1 (net difference, -7.9%; 95% CI, -8.3% to -7.6%) and at year 4 (-3.9%; 95% CI, -4.4% to -3.5%) and had greater fitness increases at year 1 (net difference, 15.4%; 95% CI, 13.7%-17.0%) and at year 4 (6.4%; 95% CI, 4.7%-8.1%) (P < .001 for each). The ILI group was significantly more likely to experience any remission (partial or complete), with prevalences of 11.5% (95% CI, 10.1%-12.8%) during the first year and 7.3% (95% CI, 6.2%-8.4%) at year 4, compared with 2.0% for the DSE group at both time points (95% CIs, 1.4%-2.6% at year 1 and 1.5%-2.7% at year 4) (P < .001 for each). Among ILI participants, 9.2% (95% CI, 7.9%-10.4%), 6.4% (95% CI, 5.3%-7.4%), and 3.5% (95% CI, 2.7%-4.3%) had continuous, sustained remission for at least 2, at least 3, and 4 years, respectively, compared with less than 2% of DSE participants (1.7% [95% CI, 1.2%-2.3%] for at least 2 years; 1.3% [95% CI, 0.8%-1.7%] for at least 3 years; and 0.5% [95% CI, 0.2%-0.8%] for 4 years).nnnCONCLUSIONSnIn these exploratory analyses of overweight adults, an intensive lifestyle intervention was associated with a greater likelihood of partial remission of type 2 diabetes compared with diabetes support and education. However, the absolute remission rates were modest. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00017953.

Physical activity patterns in the National Weight Control Registry.

Objective: The National Weight Control Registry (NWCR) was established in 1993 to examine the characteristics of those who are successful at weight loss: individuals maintaining a 13.6‐kg weight loss for >1 year. The size of the registry has increased substantially since the early descriptions of this group a decade ago. The purpose of this study was to describe in detail the weekly physical activity habits of NWCR members, to examine the relationship between amount of activity and demographic characteristics, and to determine if changes in activity parameters have occurred over time.

Maintaining large weight losses: the role of behavioral and psychological factors.

Few studies have examined predictors of weight regain after significant weight losses. This prospective study examined behavioral and psychological predictors of weight regain in 261 successful weight losers who completed an 18-month trial of weight regain prevention that compared a control condition with self-regulation interventions delivered face-to-face or via the Internet. Linear mixed effect models were used to examine behavioral and psychological predictors of weight regain, both as main effects and as interactions with treatment group. Decreases in physical activity were related to weight regain across all 3 groups, and increased frequency of self-weighing was equally protective in the 2 intervention groups but not in the control group. Increases in depressive symptoms, disinhibition, and hunger were also related to weight regain in all groups. Although the impact of changes in restraint was greatest in the Internet group and weakest in the face-to-face group, the latter was the only group with increases in restraint over time and consequent decreases in magnitude of weight regain. Future programs should focus on maintaining physical activity, dietary restraints, and frequent self-weighing and should include stronger components to modify psychological parameters.

Obesity susceptibility loci and dietary intake in the Look AHEAD Trial

BACKGROUNDnGenome-wide association studies (GWAS) have identified consistent associations with obesity. However, the mechanisms remain unclear.nnnOBJECTIVEnThe objective was to determine the association between obesity susceptibility loci and dietary intake.nnnDESIGNnThe association of GWAS-identified obesity risk alleles (FTO, MC4R, SH2B1, BDNF, INSIG2, TNNI3K, NISCH-STAB1, MTIF3, MAP2K5, QPCTL/GIPR, and PPARG) with dietary intake, measured through food-frequency questionnaires, was investigated in 2075 participants from the Look AHEAD (Action for Health in Diabetes) clinical trial. We adjusted for age, sex, population stratification, and study site.nnnRESULTSnObesity risk alleles at FTO rs1421085 significantly predicted more eating episodes per day (P = 0.001)-an effect that persisted after adjustment for body weight (P = 0.004). Risk variants within BDNF were significantly associated with more servings from the dairy product and the meat, eggs, nuts, and beans food groups (P ≤ 0.004). The risk allele at SH2B1 rs4788099 was significantly associated with more servings of dairy products (P = 0.001), whereas the risk allele at TNNI3K rs1514176 was significantly associated with a lower percentage of energy from protein (P = 0.002).nnnCONCLUSIONnThese findings suggest that obesity risk loci may affect the pattern and content of food consumption among overweight or obese individuals with type 2 diabetes. The Look AHEAD Genetic Ancillary Study was registered at clinicaltrials.gov as NCT01270763 and the Look AHEAD study as NCT00017953.

Cluster analysis of the national weight control registry to identify distinct subgroups maintaining successful weight loss.

The National Weight Control Registry (NWCR) is the largest ongoing study of individuals successful at maintaining weight loss; the registry enrolls individuals maintaining a weight loss of at least 13.6 kg (30 lb) for a minimum of 1 year. The current report uses multivariate latent class cluster analysis to identify unique clusters of individuals within the NWCR that have distinct experiences, strategies, and attitudes with respect to weight loss and weight loss maintenance. The cluster analysis considers weight and health history, weight control behaviors and strategies, effort and satisfaction with maintaining weight, and psychological and demographic characteristics. The analysis includes 2,228 participants enrolled between 1998 and 2002. Cluster 1 (50.5%) represents a weight‐stable, healthy, exercise conscious group who are very satisfied with their current weight. Cluster 2 (26.9%) has continuously struggled with weight since childhood; they rely on the greatest number of resources and strategies to lose and maintain weight, and report higher levels of stress and depression. Cluster 3 (12.7%) represents a group successful at weight reduction on the first attempt; they were least likely to be overweight as children, are maintaining the longest duration of weight loss, and report the least difficulty maintaining weight. Cluster 4 (9.9%) represents a group less likely to use exercise to control weight; they tend to be older, eat fewer meals, and report more health problems. Further exploration of the unique characteristics of these clusters could be useful for tailoring future weight loss and weight maintenance programs to the specific characteristics of an individual.

Evaluation of early weight loss thresholds for identifying nonresponders to an intensive lifestyle intervention

Weight losses in lifestyle interventions are variable, yet prediction of long‐term success is difficult. The utility of using various weight loss thresholds in the first 2 months of treatment for predicting 1‐year outcomes was examined.

Limiting variety in non-nutrient-dense, energy-dense foods during a lifestyle intervention: a randomized controlled trial

BACKGROUNDnDietary variety is a factor that influences consumption but has received little attention in obesity treatment.nnnOBJECTIVEnThis study examined the effect of limiting the variety of different non-nutrient-dense, energy-dense foods (NND-EDFs) (i.e., chips, ice cream, cookies) on dietary intake and weight loss during an 18-mo lifestyle intervention.nnnDESIGNnTwo hundred two adults aged 51.3 ± 9.5 y with a BMI (in kg/m2) of 34.9 ± 4.3 (57.8% women, 92.2% white) were randomly assigned to 1 of 2 interventions: Lifestyle (1200-1500 kcal/d, ≤30% of energy as fat; n = 101) or Lifestyle + limited variety (LV) (limit variety of NND-EDFs, i.e., 2 choices; n = 101). Both interventions involved 48 group sessions. Dietary intake, NND-EDF hedonics, NND-EDF variety in the home, and weight were assessed at 0, 6, 12, and 18 mo.nnnRESULTSnIntent-to-treat analyses showed that the Lifestyle+LV group consumed less variety (P < 0.01) and energy daily (P < 0.05) from NND-EDFs than did the Lifestyle group at 6, 12, and 18 mo. The Lifestyle+LV group consumed less total energy daily (P < 0.05) at 6 mo than did the Lifestyle group. The Lifestyle+LV group reported less (P < 0.05) NND-EDF variety in the home at 6 and 18 mo than did the Lifestyle group. The hedonics of one chosen NND-EDF decreased more (P < 0.05) in the Lifestyle+LV group. Despite these effects, no difference in percentage weight loss occurred at 18 mo (Lifestyle+LV: -9.9 ± 7.6%; Lifestyle: -9.6 ± 9.2%).nnnCONCLUSIONSnLimitations in dietary variety decreased intakes in the targeted area but did not affect weight loss. Limiting variety in more areas may be needed to improve weight loss and weight-loss maintenance. This trial was registered at clinicaltrials.gov as NCT01096719.

Describing Patterns of Weight Changes Using Principal Components Analysis: Results from the Action for Health in Diabetes (Look AHEAD) Research Group

PURPOSEnTo demonstrate how principal components analysis can be used to describe patterns of weight changes in response to an intensive lifestyle intervention.nnnMETHODSnPrincipal components analysis was applied to monthly percent weight changes measured on 2,485 individuals enrolled in the lifestyle arm of the Action for Health in Diabetes (Look AHEAD) clinical trial. These individuals were 45 to 75 years of age, with type 2 diabetes and body mass indices greater than 25 kg/m(2). Associations between baseline characteristics and weight loss patterns were described using analyses of variance.nnnRESULTSnThree components collectively accounted for 97.0% of total intrasubject variance: a gradually decelerating weight loss (88.8%), early versus late weight loss (6.6%), and a mid-year trough (1.6%). In agreement with previous reports, each of the baseline characteristics we examined had statistically significant relationships with weight loss patterns. As examples, males tended to have a steeper trajectory of percent weight loss and to lose weight more quickly than women. Individuals with higher hemoglobin A(1c) (glycosylated hemoglobin; HbA(1c)) tended to have a flatter trajectory of percent weight loss and to have mid-year troughs in weight loss compared to those with lower HbA(1c).nnnCONCLUSIONSnPrincipal components analysis provided a coherent description of characteristic patterns of weight changes and is a useful vehicle for identifying their correlates and potentially for predicting weight control outcomes.

Three-year weight change in successful weight losers who lost weight on a low-carbohydrate diet.

Objective: The purpose of this study was to evaluate long‐term weight loss and eating and exercise behaviors of successful weight losers who lost weight using a low‐carbohydrate diet.

Brain and White Matter Hyperintensity Volumes After 10 Years of Random Assignment to Lifestyle Intervention

OBJECTIVE Type 2 diabetes increases the accumulation of brain white matter hyperintensities and loss of brain tissue. Behavioral interventions to promote weight loss through dietary changes and increased physical activity may delay these adverse consequences. We assessed whether participation in a successful 10-year lifestyle intervention was associated with better profiles of brain structure. RESEARCH DESIGN AND METHODS At enrollment in the Action for Health in Diabetes clinical trial, participants had type 2 diabetes, were overweight or obese, and were aged 45–76 years. They were randomly assigned to receive 10 years of lifestyle intervention, which included group and individual counseling, or to a control group receiving diabetes support and education through group sessions on diet, physical activity, and social support. Following this intervention, 319 participants from three sites underwent standardized structural brain magnetic resonance imaging and tests of cognitive function 10–12 years after randomization. RESULTS Total brain and hippocampus volumes were similar between intervention groups. The mean (SE) white matter hyperintensity volume was 28% lower among lifestyle intervention participants compared with those receiving diabetes support and education: 1.59 (1.11) vs. 2.21 (1.11) cc (P = 0.02). The mean ventricle volume was 9% lower: 28.93 (1.03) vs. 31.72 (1.03) cc (P = 0.04). Assignment to lifestyle intervention was not associated with consistent differences in cognitive function compared with diabetes support and education. CONCLUSIONS Long-term weight loss intervention may reduce the adverse impact of diabetes on brain structure. Determining whether this eventually delays cognitive decline and impairment requires further research.