Weight Change Trajectories Research Articles

Latent class growth analysis successfully identified subgroups of participants during a weight loss intervention trial

IntroductionWeight loss interventions often present small mean weight changes over time, despite the fact that a substantial proportion of the participants lost more weight. This effect is often leveled out by the substantial proportion of participants who gained weight during the trial. The aim of this study is to identify and describe distinct subgroups of participants with different weight change trajectories during and after a weight loss intervention. MethodsWe used data from a weight loss intervention that was part of a randomized controlled trial on the preventive effect of a tailor-made weight loss intervention and oral glucosamine sulfate on the incidence of knee osteoarthritis in 407 overweight women aged 50 to 60 years. Latent class growth analysis (LCGA) was used to identify subgroups of participants with different weight change trajectories over time. ResultsUsing LCGA, we identified three subgroups with different trajectories of weight change, one large group (n = 298) with almost no change over time, and two smaller groups (both n = 48), of which one represents participants who steadily gained weight over time, whereas the other represents participants who steadily lost weight over time. Participants that had relatively low body weight around their 40th year of life and that gained weight in the year preceding the study were most likely to belong to the group that lost weight. ConclusionLCGA was a suitable method to identify three distinct groups of participants with different trajectories of weight change. Low body weight at age 40 and weight gain in the year preceding the study were associated with a higher chance of membership of the group that lost weight. It seems weight loss that occurred during this weight loss intervention was mostly recently gained weight.

Abstract 07: Trajectories of Weight Change and Their Association with Barriers to Healthy Eating during 18-month Weight Loss Treatment

Introduction: Obesity research has typically focused on the overall weight change pattern in randomized clinical trials (RCTs), ignoring the clustering of individuals with distinct weight change patterns (e.g., continuing to lose, maintain weight loss, or regain weight). The study aim was to identify trajectories of weight change and their associated predictors. Methods: This was a secondary analysis of longitudinal weight data pooled from two RCTs using standard behavioral treatment for weight loss. Weight was measured using a digital scale at baseline, 6, 12 and 18 mos. Group-based trajectory modeling was used to identify distinct classes of trajectories of percent weight change. Percent change in Barriers to Healthy Eating (BHE) subscale scores (emotions, daily mechanics and social support) were simultaneously added in the final trajectory model to examine their associations with weight change trajectories. Results: The pooled sample included 338 adults, which was mostly female (85.2%), White (73.7 %), 45.7±9.0 years old with 15.6±2.8 years of education, and a BMI of 33.9±4.3 kg/m2. As shown in the graph, three trajectory groups were identified: maintainers, regainers, and non-responders. Percent weight change was associated with BHE emotions (b=.053, p<.001) as well as social support (b=0.029, p=.003) for maintainers, emotions for regainers (b=0.071, p<.001), and daily mechanics for nonresponders (b=0.059, p <.001). Conclusions: This is the first study to identify distinct weight loss trajectories during active weight loss treatment for adults. What distinguished the maintainers from the regainers was the level of perceived barriers related to managing emotions and the availability of social support, while the group that was unsuccessful at achieving a clinically significant weight loss was challenged by the daily mechanics of adopting a healthy diet. The dimensions of barriers to healthy eating associated with weight change trajectories vary and should be considered in future weight loss programs.

Weight change trajectory in women with breast cancer receiving chemotherapy and the effect of different regimens

To investigate the trajectory of weight change in Taiwanese women with breast cancer after starting chemotherapy and the impact of chemotherapy regimens on weight change while controlling for age, menopausal status, body mass index, lymph node involvement and changes in habits of dietary fat intake and exercise. Weight gain after adjuvant chemotherapy in women with breast cancer has negative impact on health outcomes. Longitudinal, clinical observational study. Weights were repeatedly measured in 147 women with breast cancer stages I-III. Hierarchical linear modelling was used to analyse these longitudinal data. The overall pattern of weight change was a cubic form beginning with a mean of 56·9 kg before chemotherapy. It gradually increased to 59·4 kg at 8·5 months after the first chemotherapy followed by a decrease to 58·5 kg at 21·5 months. During the last 2·5 months, weight increased slightly and never returned to the initial level. After controlling for confounders, steeper weight change was observed among women receiving cyclophosphamide, methotrexate and fluorouracil. The highest weight gain in the cyclophosphamide, methotrexate and fluorouracil group was 2·9 kg (5%) vs. 0·9 kg (1%) in the anthracycline-based group. The trajectory of body weight change within two years after chemotherapy shows a trend of gradual ascent, followed by a small decline and a slight increase in the last 2·5 months. The chemotherapy regimen can predict the trend after controlling for other confounders; women on cyclophosphamide, methotrexate and fluorouracil have a steeper weight change. Nurses can inform women with breast cancer about the expected changes in body weight after chemotherapy to reduce their uncertainty. Future studies on effective interventions to minimise chemotherapy-induced weight gain are needed.

Weight Change and Health Outcomes at 3 Years After Bariatric Surgery Among Individuals With Severe Obesity

Severe obesity (body mass index [BMI] ≥35) is associated with a broad range of health risks. Bariatric surgery induces weight loss and short-term health improvements, but little is known about long-term outcomes of these operations. To report 3-year change in weight and select health parameters after common bariatric surgical procedures. The Longitudinal Assessment of Bariatric Surgery (LABS) Consortium is a multicenter observational cohort study at 10 US hospitals in 6 geographically diverse clinical centers. PARTICIPANTS AND EXPOSURE: Adults undergoing first-time bariatric surgical procedures as part of routine clinical care by participating surgeons were recruited between 2006 and 2009 and followed up until September 2012. Participants completed research assessments prior to surgery and 6 months, 12 months, and then annually after surgery. Three years after Roux-en-Y gastric bypass (RYGB) or laparoscopic adjustable gastric banding (LAGB), we assessed percent weight change from baseline and the percentage of participants with diabetes achieving hemoglobin A1c levels less than 6.5% or fasting plasma glucose values less than 126 mg/dL without pharmacologic therapy. Dyslipidemia and hypertension resolution at 3 years was also assessed. At baseline, participants (N = 2458) were 18 to 78 years old, 79% were women, median BMI was 45.9 (IQR, 41.7-51.5), and median weight was 129 kg (IQR, 115-147). For their first bariatric surgical procedure, 1738 participants underwent RYGB, 610 LAGB, and 110 other procedures. At baseline, 774 (33%) had diabetes, 1252 (63%) dyslipidemia, and 1601 (68%) hypertension. Three years after surgery, median actual weight loss for RYGB participants was 41 kg (IQR, 31-52), corresponding to a percentage of baseline weight lost of 31.5% (IQR, 24.6%-38.4%). For LAGB participants, actual weight loss was 20 kg (IQR, 10-29), corresponding to 15.9% (IQR, 7.9%-23.0%). The majority of weight loss was evident 1 year after surgery for both procedures. Five distinct weight change trajectory groups were identified for each procedure. Among participants who had diabetes at baseline, 216 RYGB participants (67.5%) and 28 LAGB participants (28.6%) experienced partial remission at 3 years. The incidence of diabetes was 0.9% after RYGB and 3.2% after LAGB. Dyslipidemia resolved in 237 RYGB participants (61.9%) and 39 LAGB participants (27.1%); remission of hypertension occurred in 269 RYGB participants (38.2%) and 43 LAGB participants (17.4%). Among participants with severe obesity, there was substantial weight loss 3 years after bariatric surgery, with the majority experiencing maximum weight change during the first year. However, there was variability in the amount and trajectories of weight loss and in diabetes, blood pressure, and lipid outcomes. clinicaltrials.gov Identifier: NCT00465829.

Abstract P296: Genome Wide Association Study of Weight Change Among Post-Menopausal African Americans: The Women’s Health Initiative Study

Genome wide association studies (GWAS) have identified numerous loci associated with BMI, a major risk factor for cardiometabolic disease. Yet, genetic associations with trajectory of weight change have been less studied, particularly in highly vulnerable populations such as racially diverse older women. We conducted a GWAS analysis on longitudinal weight among African American participants in the Women’s Health Initiative SNP Health Association Resource (WHI SHARe) study to better understand the genetic architecture of weight change during the post-menopausal period of the life course. Between 1993 and 2005, we collected longitudinal data on weight in 6,852 African American women between the ages of 50 and 79 at baseline. The average weight at first measure was 81 kg (16) with a range of 46 to 129 kg. The average change in weight per year was 0.09 kg (0.36) ranging from -3.3 to 5.7 kg. The average follow-up duration was 5.3 years (range: 1 to 11). We used time-varying, repeated weight measures across the trial period to perform a growth curve analysis for weight change. Using a mixed model with an unstructured covariance matrix, weight was regressed on year since randomization for both fixed and random effects to derive each individual’s weight change slope. Individuals were genotyped using Affymetrix 6.0 array and ~ 3.2 million SNPs were imputed using MACH (v1.0.16) and a 50(CEU):50(YRI) HapMap 2 reference panel. We performed association analyses with weight change residuals adjusted for clinical covariates and principal components, using an additive genetic model. While no associations reached genome wide significance (p<5E-8), several SNPs reached suggestive significance. Our three most significant signals at 5q22.1, 10q22.1, and 12q15 (all p<8E-7), lie near likely candidate genes involved in lipid breakdown, transport, and/or cholesterol homeostasis (e.g. STARD4, PSAP, IFNG). Interestingly, we observed a high level of phenotypic variance, which we attribute to complex weight fluctuation among post-menopausal women. We are currently conducting sensitivity analyses incorporating information on age since menopause and investigating different methods of longitudinal modeling in an attempt to minimize our trait variability, thereby improving our power to detect genetic effects. Also, we are replicating our top findings in other large longitudinal studies of African American women. While our preliminary analyses did not detect genome-wide significant associations with weight change among the participants of WHI SHARe, many SNPs with near genome wide significance are close to strong biological candidate genes and warrant further exploration. Future studies are needed to further characterize the genetic architecture of weight change at this vulnerable period of the life cycle for women so that effective interventions to prevent weight gain can be implemented.

Trajectories of childhood weight gain: the relative importance of local environment versus individual social and early life factors.

ObjectiveTo determine the association between local environmental factors with child weight status in a longitudinal study, using a semi-parametric, group-based method, while also considering social and early life factors.MethodsStandardized, directly measured BMI from 4–10 y of age, and group-based trajectory modeling (PROC TRAJ) were used to estimate developmental trajectories of weight change in a Québec birth cohort (n = 1,566). Associations between the weight trajectories and living location, social cohesion, disorder, and material and social deprivation were estimated after controlling for social and early life factors.ResultsFour weight trajectory groups were estimated: low-increasing (9.7%); low-medium, accelerating (36.2%); medium-high, increasing (43.0%); and high-stable (11.1%). In the low-increasing and medium-high trajectory groups, living in a semi-urban area was inversely related to weight, while living in a rural area was positively related to weight in the high-stable group. Disorder was inversely related to weight in the low-increasing group only. Other important risk factors for high-stable weight included obesity status of the mother, smoking during pregnancy, and overeating behaviors.ConclusionsIn this study, associations between local environment factors and weight differed by trajectory group. Early life factors appear to play a more consistent role in weight status. Further work is needed to determine the influence of place on child weight.

Patterns of Weight Change Associated With Long‐Term Weight Change and Cardiovascular Disease Risk Factors in the Look AHEAD Study

This article provides an assessment of the associations that weight-loss patterns during the first year of an intensive lifestyle intervention have with 4-year maintenance and health outcomes. Two components described patterns of weight change during the first year of intervention: one reflected the typical pattern of weight loss over the 12 months, but distinguished those who lost larger amounts across the monthly intervals from those who lost less. The second component reflected the weight change trajectory, and distinguished a pattern of initial weight loss followed by regain vs. a more sustained pattern of weight loss. Two thousand four hundred and thirty eight individuals aged 45-76 years with type 2 diabetes mellitus, who enrolled in the weight-loss intervention of a randomized clinical trial, were assigned scores according to how their weight losses reflected these patterns. Relationships these scores had with weight losses and health outcomes (glycosolated hemoglobin--hemoglobin A1c (HbA1c); systolic blood pressure, high-density lipoprotein (HDL)-cholesterol, and triglycerides) over 4 years were described. When compared to those with lower scores on the two components, both individuals who had larger month-to-month weight losses in year 1 and whose weight loss was more sustained during the first year had better maintenance of weight loss over 4 years, independent of characteristics traditionally linked to weight loss success (P < 0.001). While relationships with year 4 weight loss were stronger, the pattern of larger monthly weight loss during year 1 was also independently predictive of year 4 levels of HbA1c, HDL-cholesterol, and systolic blood pressure.

The psychological consequences of weight change trajectories: Evidence from quantitative and qualitative data

We use quantitative and qualitative data to explore the psychological impact of weight change among American adults. Using data from the Midlife Development in the United States (MIDUS) study, a survey of more than 3000 adults ages 25–74 in 1995, we contrast underweight, normal weight, overweight, obese I, and obese II/III persons along five psychosocial outcomes: positive mood, negative mood, perceived interpersonal discrimination, self-acceptance, and self-satisfaction. We further assess whether these relationships are contingent upon one's body mass index (BMI) at age 21. We find a strong inverse association between adult BMI and each of the five outcomes, reflecting the stigma associated with high body weight. However, overweight adults who were also overweight at age 21 are more likely than persons who were previously slender to say they were “very satisfied” with themselves. Results from 40 in-depth semi-structured interviews reveal similarly that persons who were persistently overweight or obese accept their weight as part of their identity, whereas those who experienced substantial weight increases (or decreases) struggle between two identities: the weight they actually are, and the weight that they believe exemplifies who they are. We discuss implications for stigma theory, and the ways that stigma exits and entries affect psychological well-being.

P1-107 Contextual circumstances and patterns of childhood weight change

IntroductionWorldwide, the prevalence of childhood obesity has not abated, indicating that prevention strategies, traditionally implemented at the individual- level, may not be effective. Conceptualising childhood obesity within multiple levels of...

Development of adherence metrics for caloric restriction interventions

objective measures are needed to quantify dietary adherence during caloric restriction (CR) while participants are freeliving. One method to monitor adherence is to compare observed weight loss to the expected weight loss during a prescribed level of CR. Normograms (graphs) of expected weight loss can be created from mathematical modeling of weight change to a given level of CR, conditional on the individual's set of baseline characteristics. These normograms can then be used by counselors to help the participant adhere to their caloric target. (1) To develop models of weight loss over a year of caloric restriction-given demographics, and well-defined measurements of body mass index, total daily energy expenditure (TDEE) and %CR. (2) To utilize these models to develop normograms, given the level of caloric restriction prescribed, and measures of these variables. Seventy-seven individuals completing a 6-12-month caloric restriction intervention (CALERIE) at three sites (Pennington Biomedical Research Center, Tufts University, and Washington University) and had body weight and body composition measured frequently. Energy intake (and %CR) was estimated from TDEE (by doubly labeled water) and body composition (by DXA) at baseline and months 1, 3, 6, and 12. Bodyweight was modeled to determine the predictors and distribution of the expected trajectory of percent weight change over 12 months of CR. As expected, CR was related to change in body weight. Controlling for time-varying measures, initially simple models of the functional form indicated that the trajectory of percent weight change was predicted by a nonlinear function of age, TDEE, %CR, and sex. Using these estimates, normograms for the weight change were developed. Our model estimates that the mean weight loss (% change from baseline weight) for an individual adherent to a 25% CR regimen is -10.9 ± 6.3% for females and -13.9 + 6.4% for men after 12 months. There are several limitations. Sample sizes are small (n = 77), and, by design, the protocols, including prescribed CR, for the interventions differed by site, and not all subjects completed a year of follow-up. In addition, the inclusion of subjects by age and initial BMI was constricted, so that these results may not generalize to other populations including older and obese subjects. The trajectory of percent weight change during CR interventions in the presence of well-measured covariates can be modeled using simple nonlinear functions, and is related level of CR, the percent change in TDEE, gender, and age. Displayed on a normogram, individually tailored trajectories can be used by counselors and participants to monitor weight loss and adherence to a CR regimen.

Transformation of neural network weight trajectories on a 2D plane for a learning-type neural network direct controller

Through a simulation of the tracking method for a neural network weight change on a 2D plane, we noticed that in some cases it was hard for untrained users to observe the neural network weight performance. To overcome this problem, we applied a transformation of the neural network weight trajectories on a 2D plane to the direct controller of a learning-type neural network. The simulation results confirmed that if the trajectory of the neural network weight change on a 2D plane had a simple structure, we could easily determine whether the learning of the neural network had terminated or not. However, if it had a more complex structure, we could not make this determination. The proposed transformation of the neural network weight trajectories to one-dimensional values will be useful for such cases.

Gestational weight gain and subsequent postpartum weight loss among young, low-income, ethnic minority women

Document weight change trajectories that lead to gestational weight gain or postpartum weight loss outside clinical recommendations established by the Institute of Medicine. Women aged 14-25 receiving prenatal care and delivering singleton infants at term (n = 427). Medical record review and 4 structured interviews conducted: second and third trimester, 6- and 12-months postpartum. Longitudinal mixed modeling to evaluate weight change trajectories. Only 22% of participants gained gestational weight within Institute of Medicine guidelines. There were 62% that exceeded maximum recommendations-more common among those overweight/obese (body mass index ≥25.0; P < .0001). 52% retained ≥10 lb 1-year postpartum. Increased weight gain and retention documented among smokers and women with pregnancy-induced hypertension; breastfeeding promoted postpartum weight loss (all P < .02). Body mass index by race interaction suggested healthier outcomes for Latinas (P = .02). Excessive pregnancy weight gain and inadequate postpartum weight loss are highly prevalent among young low-income ethnic minority women. Pregnancy and postpartum are critical junctures for weight management interventions.

Trajectories of weight change from late adolescence to late middle age for lean and obese individuals

To identify and better understand trajectories of individual weight change associated with increasing age, we analyzed longitudinal data from a cohort of older Americans (171,711 men and 122,563 women). Subjects entered the cohort in 1996 at a mean age of 62.5 years and they reported current height and weight, and weight at ages 18, 35, and 50 years. At study entry in 1996, prevalences of overweight and obesity among men were 49.6% and 19.9%, respectively. Across 9 categories of current BMI (from &lt;18.5 kg/m2 to ≥35 kg/m2) there was no difference in mean BMI at age 18 (all categories of current BMI had a mean BMI at age 18 of between 21.4 and 21.6 kg/m2). Likewise, mean BMI at age 35 was almost identical across the 9 categories of current BMI. However, BMI at age 50 was strongly associated with current BMI (19.8 kg/m2 in the bottom category with a monotonic increase to 33.2 kg/m2 in the top category). Results for women were essentially identical to those in men. In this cohort of subjects that was primarily lean at late adolescence, neither BMI at age 18 nor BMI at age 35 were associated with current BMI despite high prevalences of overweight and obesity at late middle age. Weight gain between ages 35 and 50, however, was highly predictive of overweight and obesity in late middle age.Funding: NIH K07 CA108910‐01A1 to A.F., and NCI Intramural Research Program.

Adult Obesity Does Not Predict 6‐Year Weight Gain in Men: The Aerobics Center Longitudinal Study

To determine the longitudinal relation between history of adult obesity and the 6-year trajectory of weight change in men. Subjects were healthy, affluent men (n = 761) between the ages of 20 and 78 years who completed at least four comprehensive medical exams at the Cooper Clinic between 1987 and 2003. Maximum adult weight was reported, and current height was measured at baseline. Body weight and cardiorespiratory fitness were measured at all examinations. Adult obesity status was determined from self-reported maximum weight and measured height at baseline as BMI > or = 30 kg/m(2). Weight at all examinations was regressed on a history of adult obesity using linear mixed effects modeling. At baseline, men reporting a history of adult obesity were significantly heavier than men reporting no such history (BMI 29.8 vs. 25.0 kg/m(2); p < 0.05). However, the rate of weight gain among men with a history of obesity was slower than among men without a history of adult obesity (0.04 vs. 0.18 kg/yr; p = 0.09), although this difference was only marginally significant. Fitness modulated the relationship between history of obesity and weight change over time, and both higher levels of fitness and greater frequency of dieting were associated with attenuated weight gain. In contrast, chronic disease and depression were associated with accelerated weight gain. Although a history of obesity was associated with higher weight, it did not seem to result in accelerated weight gain over time. Additionally, dieting and fitness were important for minimizing weight gain.

Trajectory of Weight Changes in the First 6 Weeks Postpartum

To determine the trajectory of postpartum weight changes and to examine associations between weight change in the first 6 weeks postpartum and demographic, clinical, psychosocial, and behavioral variables. Prospective, longitudinal design. Community hospital and university research setting. 26 low-income women (9 White, 8 Black, and 9 Hispanic) with uncomplicated term pregnancies. Body mass index measured weekly. Among White women, body mass index decreased significantly for the first 3 weeks of the postpartum period. Black women experienced a significant reduction in body mass index for only the first 2 postpartum weeks. Similarly, the postpartum body mass index decreased for the first 2 weeks for Hispanic women. Prepregnancy body mass index and gestational weight gain each had a significant positive effect on postpartum body mass index. Perception of social support at 4 weeks had a significant positive effect on postpartum body mass index in Black women. The trajectory of weight change was nonlinear with large initial weight losses during the first 2 to 3 weeks postpartum followed by weight plateaus for the remainder of the first 6 weeks postpartum.

Estimated change in physical activity level (PAL) and prediction of 5-year weight change in men: the Aerobics Center Longitudinal Study

To determine the relation between the average daily physical activity level (PAL) and the trajectory of weight change in men at risk for weight gain. Clinic-based cohort study over an average of 5 y. Healthy men (N=2501) ages 20-55 y participating in the Aerobics Center Longitudinal Study who had received at least four medical examinations at the Cooper Clinic between 1970 and 1998. Daily leisure-time physical activity was reported and body weight was measured at all four examinations. The average daily PAL (METs 24 h(-1)) was estimated from all activities, as well as from other incidental active and passive activities. Weight change over four examinations was regressed on the change in PAL between the first and third examinations. Random coefficient regression modeling indicated a curvilinear slope for weight gain over the follow-up among those maintaining the same PAL between the first and third examinations. Weight gain was further accelerated among men who decreased their activity. A shift from a low PAL (<1.45 METs 24 h(-1)) to a moderate (1.45-1.60 METs 24 h(-1)) or high (>1.60 METs 24 h(-1)) PAL was necessary for weight loss over time. Men with initially the lowest PAL had the greatest benefit from increasing activity. Daily PAL was inversely related to weight gain in this cohort. Increasing to or maintaining a daily PAL at least 60% above the resting metabolic rate (ie, PAL >1.60 METs 24 h(-1)) may be necessary to maintain body weight in middle-age and can be achieved by incorporating 45-60 min of brisk walking, gardening/yardwork, or cycling into the daily routine.

Can Physical Activity Attenuate Aging-related Weight Loss in Older People?: The Yale Health and Aging Study, 1982-1994

The purpose of this analysis was to determine the longitudinal relation between physical activity and the trajectory of weight change in an older cohort (> or =65 years) living in New Haven, Connecticut, who participated in the Established Populations for the Epidemiologic Study of the Elderly between 1982 and 1994 (n=2,812). The authors hypothesized that body weight would decline over the follow-up and that physical activity would play an important role in minimizing weight loss over time. Physical activity and other covariables were self-reported at baseline, while body weight was self-reported annually over 12 years. Multivariable random effects regression demonstrated a curvilinear trajectory of weight loss per year with an accelerated loss at older ages. Baseline body weight was 155 (standard deviation, 30) pounds (70 (standard deviation, 14) kg) for those who survived the entire follow-up and was 153 (standard deviation, 32) pounds (70 (standard deviation, 15) kg) for those who did not. Each 1-unit increase in baseline total activity score minimized this aging-related weight loss, but this relation was most pronounced among those with chronic disease who did not survive the entire follow-up period (n=973; 0.15 pounds (0.07 kg) per year). These data suggest that, among frail older people, even modest levels of physical activity can attenuate the rate of aging- and disease-related weight loss.