Weight Change Trajectories Research Articles

Cardiometabolic characteristics of weight cycling: results from a mid-South regional comprehensive health care system.

The objective of this study was to determine the unique clinical and cardiometabolic risk characteristics of weight-cyclers and identify differences between weight-cyclers and individuals with other weight-change trajectories. A deidentified database of 1,428,204 Vanderbilt University Medical Center patients from 1997 to 2020 was included based on having ≥5 years of recorded weights. Patients with a history of malignant neoplasm, bariatric surgery, implausible BMI (e.g., <15 or >80 kg/m2), or missing documented height were excluded, yielding 83,261 participants categorized by weight trajectory, i.e., weight-stable, weight-gainer, weight-loser, or weight-cycler, based on criteria of ≥5% weight-change thresholds. Additionally, quartiles of average successive weight variability were evaluated to determine the effect of absolute differences among successive weight values. Over half (55%) of participants were weight-cyclers, 23% were weight-gainers, 12% were weight-losers, and 10% were weight-stable over 5 years. Although baseline BMI did not differ among groups, weight-cyclers were more likely to have lower high-density lipoprotein cholesterol and higher blood glucose and triglyceride levels and to have been prescribed antihypertensive, dyslipidemia, and/or antidiabetic therapies. They were also younger and more likely to be smokers. Participants with the greatest weight variability (i.e., highest quartile of average successive weight variability) had higher cardiometabolic risk scores. Weight cycling was highly prevalent but yielded no meaningful overall change in body weight after 5 years. These findings support a paradigm shift in weight management in individuals with overweight/obesity toward reducing cardiometabolic risk with or without weight loss.

Switching diets after 6-months does not result in renewed weight loss: a secondary analysis of a 12-month crossover randomized trial.

Weight change trajectory from diet and lifestyle interventions typically involves rapid weight loss followed by a weight plateau after approximately 6months. Changing from one weight-loss diet to another at the time of the plateau could instigate renewed weight loss. Therefore, our secondary analysis aimed to assess trajectory of weight loss in a 12-month, randomized, cross-over study. Forty-two adults were randomized to eat a healthy low-fat or healthy low-carbohydrate diet for 6months then switched to the opposite diet for an additional 6months. Regardless of diet assignment, participants experienced rapid initial weight loss, which slowed between 3 to 6months. After switching diets at 6months, weight modestly decreased until 9months, but at a rate slower than the initial 3months and slower than the rate from 3 to 6months. This suggests that the weight loss plateau typically seen at 6months is physiological and cannot be overcome by simply switching to a different weight-loss diet.

Weight Loss Trajectories and Short-Term Prediction in an Online Weight Management Program.

The extent to which early weight loss in behavioral weight control interventions predicts long-term success remains unclear. In this study, we developed an algorithm aimed at classifying weight change trajectories and examined its ability to predict long-term weight loss based on weight early change. We utilized data from 667 de-identified individuals who participated in a commercial weight loss program (Instinct Health Science), comprising 69,363 weight records. Sequential polynomial regression models were employed to classify participants into distinct weight trajectory patterns based on key model parameters. Next, we applied multinomial logistic models to evaluate if early weight loss in the first 14 days and prolonged duration of participation were significantly associated with long-term weight loss patterns. The mean percentage of weight loss was 7.9 ± 5.1% over 133 ± 69 days. Our analysis revealed four main weight loss trajectory patterns: a steady decrease over time (30.6%), a decrease to a plateau with subsequent decline (15.8%), a decrease to a plateau with subsequent increase (46.9%), and no substantial decrease (6.7%). Early weight change rate and total participating duration emerged as significant factors in differentiating long-term weight loss patterns. These findings contribute to support the provision of tailored advice in the early phase of behavioral interventions for weight loss.

Pre-surgical factors related to latent trajectories of 5-year weight loss for a diverse bariatric surgery population

BackgroundAnalyzing trajectories of weight loss may address how particular groups of patients respond to metabolic and bariatric surgery. ObjectivesThe Bariatric Experience Long Term (BELONG) study was designed to use a theoretical model to examine determinants of weight loss and recurrence. SettingLarge integrated health system in Southern California with 11 surgical practices and 23 surgeons. MethodsA total of n = 1338 patients who had metabolic and bariatric surgery were surveyed before surgery to measure factors related to median percent total weight loss (%TWL) over 5 years. Longitudinal weight data were available for n = 1024 (76.5% of the sample). Data were analyzed using latent growth mixture models (GMM) to estimate trajectories of weight change separately for gastric sleeve and bypass operations. These trajectories were then described using relevant variables from the baseline survey. ResultsFor both gastric sleeve (n = 733) and bypass (n = 291) operations, 3 latent trajectories of median %TWL were found corresponding to most, moderate, and least %TWL. Sleeve trajectories were distinguished by body mass index at surgery and geocoded environmental factors. Bypass trajectories varied by self-reported and geocoded environmental factors, comorbidity burden, race, experiential avoidance, and weight control strategies. ConclusionsFuture research should examine the role of the built and perceived environment in surgical weight loss. Bariatric practices should focus less on the presurgical period for predictors of long-term weight loss and begin efforts to monitor real-time patient-reported outcomes to help tailor intervention strategies for patients who either do not lose an expected amount of weight or who begin to experience weight recurrence.

Impact of weight loss and weight gain trajectories on body composition in a population at high risk of type 2 diabetes: A prospective cohort analysis.

In a primary care population at high risk of type 2 diabetes, 24-month weight change trajectories were used to investigate the impact of weight cycling on fat mass (FM) and fat-free mass (FFM). Cohort data from the Walking Away from Type 2 Diabetes trial was used, which recruited adults at-risk of type 2 diabetes from primary care in 2009/10. Annual weight change trajectories based on weight loss/gain of ≥5% were assessed over two 24-month periods. Body composition was measured by bioelectrical impedance analysis. Repeated measures were analysed using generalized estimating equations with participants contributing up to two 24-month observation periods. In total, 622 participants were included (average age = 63.6 years, body mass index = 32.0 kg/m2 , 35.4% women), contributing 1163 observations. Most observations (69.2%) were from those that maintained their body weight, with no change to FM or FFM. A minority (4.6% of observations) lost over 5% of body weight between baseline and 12 months, which was then regained between 12 and 24 months. These individuals regained FM to baseline levels, but lost 1.50 (0.66, 2.35) kg FFM, adjusted for confounders. In contrast, those that gained weight between baseline and 12 months but lost weight between 12 and 24 months (5.5% of observations) had a net gain in FM of 1.70 (0.27, 3.12) kg with no change to FFM. Weight cycling may be associated with a progressive loss in FFM and/or gain in FM in those with overweight and obesity at-risk of type 2 diabetes.

Impact of Weight Change on Glycemic Control and Metabolic Parameters in T2D: A Retrospective US Study Based on Real-World Data.

Weight loss has been identified as a key strategy for improving glycemic and metabolic outcomes in people with type2 diabetes (T2D). However, the long-term, real-world impact of weight loss on these outcomes remains unclear. This study aimed to investigate (1) the association between weight loss and glycemic control, (2) association between weight loss and metabolic parameters, and (3) predictors of weight loss and how weight change trajectory varies based on index body mass index (BMI). A retrospective, longitudinal cohort study using the linked IQVIA Ambulatory electronic medical records and PharMetrics® Plus databases was performed from January1, 2010 through December31, 2019 in adults with T2D. Participants were categorized into 1-year and 5-year follow-up cohorts based on their observed weight change over time. Longitudinal values for vital signs and laboratory parameters, including BMI, weight, glycated hemoglobin (HbA1c), and metabolic parameters (liver enzymes and cholesterol), were reported at index date and every 6months post index date. Multivariable logistic regression analysis was used to evaluate the factors associated with weight loss. Of 1,493,964 people evaluated, 1,061,354 (71%) and 308,320 (20.6%) were classified into the 1-year and 5-year follow-up cohorts. Average HbA1c reductions of 1.2% and 0.5% were observed among people who lost ≥ 15% of index weight in the 1-year and 5-year follow-up cohorts, respectively. Higher weight loss percentages were associated with numerically greater improvements in metabolic parameters. The presence of bariatric surgery and higher index BMIs were identified as the strongest predictors of ≥ 15% and ≥ 10% weight loss in both follow-up cohorts. Results from this study suggest that modest and sustained weight loss can lead to clinically meaningful improvements in glycemic and metabolic parameters among people with T2D. These findings highlight the importance of weight management in managing T2D and preventing its associated complications.

Longitudinal trajectories of weight changes among people living with HIV on antiretroviral therapy: A group-based study

Weight changes vary among people living with HIV (PLHIV) on different antiretroviral therapy (ART) regimens. Here, we performed multi-trajectory modeling fitting growth mixture models (GMM) to identify longitudinal weight change trajectories of PLHIV. Multiple logistic regression was used to assess correlates of rapid weight gains; 12,683 PLHIV (median age: 34 years [interquartile range 29-42], 91.1% male) who initiated ART at the Third People's Hospital of Shenzhen, China, between January 2003 and September 2022 were included. We identified two trajectories: slow (70.5%) and rapid weight gains (29.5%). PLHIV who initiated ART with dolutegravir- (adjusted odds ratio [aOR] 2.46, 1.92-3.15), raltegravir- (2.74, 1.96-3.82), and lopinavir (1.62, 1.36-1.94)-based regimens were more likely to have rapid weight gains compared with efavirenz-based regimen. The monitoring of nutritional status should be strengthened for PLHIV who initiated these regimens during regular ART follow-ups.

Antipsychotic effects on anthropometric outcomes in anorexia nervosa: a retrospective chart review of hospitalized children and adolescents

BackgroundOff-label antipsychotic use is not uncommon in youth with anorexia nervosa (AN), aiming to enhance suboptimal weight restoration, yet its efficacy remains debated, especially in youth.MethodsRetrospective chart review of consecutively admitted inpatients (ages 8–18 years) with restricting/binge-purge AN, comparing youth with versus without antipsychotic treatment regarding baseline factors, treatment, and anthropometric outcome characteristics including all patients and matched subgroups. Matched subsamples were also compared regarding faster versus slower weight change (median split). Furthermore, within-subject analyses compared weight gain trajectories before versus after antipsychotic use in antipsychotic-treated youth. These results were then compared in a pre-/post design with the matched control group without antipsychotic treatment, using the mean duration until antipsychotic use in the antipsychotic-treated group as the dividing timeline, controlling for a potential order effect, in that later rather than earlier antipsychotic treatment for AN may be more successful.ResultsOf 294 youth with AN (median age = 15.2 (interquartile range = 14.0, 16.6) years, females = 96.6%, restricting subtype = 81.0%, hospitalization duration = 98.2 ± 43.2 days), 44 (15.0%) underwent 52 antipsychotic trials (olanzapine = 63.5%). In multivariable analyses, antipsychotic use was independently associated with younger age, childhood physical abuse history, comorbid borderline personality traits, and lower pre-antipsychotic weight gain (p < 0.0001). In unmatched groups, antipsychotic-treated versus non-treated youth had significantly lower discharge anthropometric parameters, longer inpatient treatment, and lower weight change/week (p < 0.001–p = 0.005), without significant differences between olanzapine and non-olanzapine antipsychotics (p = 0.27–0.44). Non-significant antipsychotic effects on weight outcomes were confirmed in (1) matched subgroups of antipsychotic-treated versus non-treated youth (n = 43 each), (2) youth with faster versus slower weight gain (n = 21 vs. n = 22), and (3) antipsychotic-treated youth when comparing weight change before versus after antipsychotic use (n = 31). Moreover, in antipsychotic-treated youth, weight change/week remained significantly lower versus matched non-antipsychotic-treated youth (n = 31) both before (p = 0.053) and after (p = 0.006) the median time (5 weeks) until antipsychotic use.ConclusionsIn this naturalistic study, clinician's antipsychotic choice, given to a more severely ill subgroup of adolescents with AN, did not significantly improve overall worse weight change trajectories during inpatient treatment, even in matched subgroups. Randomized trials in individuals reflecting real-world samples are needed to evaluate the utility of antipsychotic treatment in youth with AN.

Newborn weight nomograms in selected low and middle-income countries

Growth impairment is common in low- and middle-income countries (LMIC) and may begin during early infancy, increasing morbidity and mortality. To ensure healthy infant growth, healthcare providers in high-income countries (HIC) track newborn weight change using tools developed and validated in HIC. To understand the utility of these tools for LMIC, we conducted a secondary analysis to compare weight trajectories in the first 5 days of life among newborns born in our LMIC cohort to an existing HIC newborn weight tool designed to track early weight change. Between April 2019 and March 2020, a convenience sample of 741 singleton healthy breastfeeding newborns who weighed ≥ 2000 g at birth were enrolled at selected health facilities in Guinea-Bissau, Nepal, Pakistan, and Uganda. Using a standardized protocol, newborn weights were obtained within 6 h of birth and at 1, 2, 3, 4, and 5 days, and nomograms depicting newborn weight change were generated. The trajectories of early newborn weight change in our cohort were largely similar to published norms derived from HIC infants, with the exceptions that initial newborn weight loss in Guinea-Bissau was more pronounced than HIC norms and newborn weight gain following weight nadir was more pronounced in Guinea-Bissau, Pakistan, and Uganda than HIC norms. These data demonstrate that HIC newborn weight change tools may have utility in LMIC settings.

Initial weight loss and early intervention adherence predict long-term weight loss during the Promoting Successful Weight Loss in Primary Care in Louisiana lifestyle intervention.

This study tested whether initial weight change (WC), self-weighing, and adherence to the expected WC trajectory predict longer-term WC in an underserved primary-care population with obesity. Data from the intervention group (n = 452; 88% women; 74% Black; BMI 37.3 kg/m2 [SD: 4.6]) of the Promoting Successful Weight Loss in Primary Care in Louisiana trial were analyzed. Initial (2-, 4-, and 8-week) percentage WC was calculated from baseline clinic weights and daily at-home weights. Weights were considered adherent if they were on the expected WC trajectory (10% at 6 months with lower [7.5%] and upper [12.5%] bounds). Linear mixed-effects models tested whether initial WC and the number of daily and adherent weights predicted WC at 6, 12, and 24 months. Percentage WC during the initial 2, 4, and 8 weeks predicted percentage WC at 6 (R2 = 0.15, R2 = 0.28, and R2 = 0.50), 12 (R2 = 0.11, R2 = 0.19, and R2 = 0.32), and 24 (R2 = 0.09, R2 = 0.11, and R2 = 0.16) months (all p < 0.01). Initial daily and adherent weights were significantly associated with WC as individual predictors, but they only marginally improved predictions beyond initial weight loss alone in multivariable models. These results highlight the importance of initial WC for predicting long-term WC and show that self-weighing and adherence to the expected WC trajectory can improve WC prediction.

Prenatal Weight Change Trajectories and Perinatal Outcomes among Twin Gestations.

Despite an increase in twin pregnancies in recent decades, the Institute of Medicine twin weight gain recommendations remain provisional and provide no guidance for the pattern or timing of weight change. We sought to characterize gestational weight change trajectory patterns and examine associations with birth outcomes in a cohort of twin pregnancies. Prenatal and delivery records were examined for 320 twin pregnancies from a maternal-fetal medicine practice in Austin, TX 2011-2019. Prenatal weights for those with >1 measured weight in the first trimester and ≥3 prenatal weights were included in analyses. Trajectories were estimated to 32 weeks (mean delivery: 33.7 ± 3.3 weeks) using flexible latent class mixed models with low-rank thin-plate splines. Associations between trajectory classes and infant outcomes were analyzed using multivariable Poisson or linear regression. Weight change from prepregnancy to delivery was 15.4 ± 6.3 kg for people with an underweight body mass index, 15.4 ± 5.8 kg for healthy weight, 14.7 ± 6.9 kg for overweight, and 12.5 ± 6.4 kg for obesity. Three trajectory classes were identified: low (Class 1), moderate (Class 2), or high gain (Class 3). Class 1 (24.7%) maintained weight for 15 weeks and then gained an estimated 6.6 kg at 32 weeks. Class 2 (60.9%) exhibited steady gain with 13.5 kg predicted total gain, and Class 3 (14.4%) showed rapid gain across pregnancy with 21.3 kg predicted gain. Compared to Class 1, Class 3 was associated with higher birth weight z-score (β = 0.63, 95% confidence interval [CI]: 0.31,0.96), increased risk for large for gestational age (IRR = 5.60, 95% CI: 1.59, 19.67), and birth <32 weeks (IRR = 2.44, 95% CI: 1.10, 5.4) that was attenuated in sensitivity analyses. Class 2 was associated with moderately elevated birth weight z-score (β = 0.24, 95% CI: 0.00, 0.48, p = 0.050). Gestational weight change followed a low, moderate, or high trajectory; both moderate and high gain patterns were associated with increased infant size outcomes. Optimal patterns of weight change that balance risk during the prenatal, perinatal, and neonatal periods require further investigation, particularly in high-risk twin pregnancies. · A majority gained weight below IOM twin recommendations.. · Three patterns of GWC across pregnancy were identified.. · Moderate or high GWC was associated with infant size..

Association between screen time, weight trajectory, and perception of weight change during the COVID-19 pandemic

Association between screen time, weight trajectory, and perception of weight change during the COVID-19 pandemic

Weight Changes in Young Service Members After Lower Limb Amputation: Insights From Group-Based Trajectory Modeling.

Weight gain can contribute to osteoarthritis, cardiovascular disease, low back pain, and poor health-related quality of life. Weight trajectory patterns have been described in older veterans with limb loss; however, there is limited evidence of changes in weight in younger veterans with limb loss. Service members with unilateral or bilateral lower limb amputations (LLAs) (and without an upper limb amputation) were included in this retrospective cohort analysis (n = 931). The mean postamputation baseline weight was 78.0 ± 14.1 kg. Bodyweight and sociodemographic data were extracted from clinical encounters within electronic health records. Group-based trajectory modeling assessed weight change patterns 2 years postamputation. Three weight change trajectory groups were identified: 58% (542 of 931) of the cohort had stable weight, 38% (352 of 931) had weight gain (mean gain = 19.1 kg), and 4% (31 of 931) had weight loss (mean loss = 14.5 kg). Individuals with bilateral amputations were more frequently noted in the weight loss group compared with those with unilateral amputations. Individuals with LLAs because of trauma other than blasts were more frequently found in the stable weight group compared with those with amputations because of disease or a blast. Younger individuals (<20 years old) with amputations were more likely to be in the weight gain group compared with older individuals. More than half the cohort maintained a stable weight for two years after amputation, and more than a third experienced weight gain during the same time frame. Knowledge of underlying factors that were associated with weight gain could inform preventative strategies for young individuals with LLAs.

Weight gain trajectories patterns from pregnancy to early postpartum: identifying women at risk and timing to prevent weight regain

BackgroundWoman's weight changes during pregnancy and postpartum contribute to obesity and health outcomes later in life. This study aimed to identify and characterize weight change trajectories from pregnancy to one year postpartum among adult women.MethodsWe used data from an ongoing cohort of healthy adult women (n = 819) with singleton pregnancies from 2007 – 2011. Sociodemographic data, pre-pregnancy body weight, and sedentary and breastfeeding practices were collected using questionaries applied by trained professionals. We applied a group-based trajectory modeling to distinguish weight change measured in the second and third trimesters of pregnancy and at one month, six, and 12 months postpartum. Multinomial regression models were run to characterize each trajectory.ResultsWe identified six weight change trajectories with the main difference in the patterns followed after one month of delivery. One in three women (36.7%) was classified in some of the three postpartum weight gain trajectories and regained weight from the second trimester of the first year postpartum. Women who followed some of these trajectories were more likely to have higher age, obesity before pregnancy, < 10 years of schooling, and partner, compared with women (10.7%, n = 87) in a postpartum sustained-fast-lost-weight trajectory (p < 0.05).ConclusionsWomen with obesity before pregnancy have higher odds of regaining gestational weight after delivery without reaching their pre-pregnancy weight. The first six months postpartum are crucial to establishing obesity prevention strategies. Further research is needed to evaluate the effect of the interventions that prevent substantial weight gain through reproductive years in high-risk women.

Ramadan fasting and weight change trajectories: Time-varying association of weight during and after Ramadan in low-income and refugee populations.

Obesity is a significant driver of the global burden of non-communicable diseases. Fasting is one approach that has been shown to improve health outcomes. However, the effects of Ramadan fasting differ in that the type, frequency, quantity, and time of food consumption vary. This phenomenon requires in-depth evaluation considering that 90% of Muslims (~2 billion people) fast during Ramadan. To address this issue, we evaluated the pattern of weight change during and following Ramadan for a total of 52 weeks. The study was conducted in Amman, Jordan. Between 2012 and 2015, 913 participants were recruited as part of a trial investigating the efficacy of a weight loss intervention among those with or at risk for diabetes. Weight was measured weekly starting at the beginning of Ramadan, and changes were analyzed using discrete and spline models adjusted for age, sex, and trial group. Results show slight weight gain within the first two weeks and weight loss in the subsequent weeks. During the first week of Ramadan, the estimate for a weight reduction was 0·427 kg, (95% CI: -0·007, 0·861), increasing to 1·567 kg, (95% CI: 2·547, 3·527) at week 26. There was clear evidence of gradual weight gain from about 4 to 15 weeks and a drop towards the end of the investigation at week 28 (-0·12kg, 95% CI: -0·89, 0·56). Our results show that weight changes occurred during and after Ramadan. Weight fluctuations may affect health risks, and thus, findings from this study can inform interventions. Public health agencies could leverage this period of dietary change to sustain some of the benefits of fasting. The authors (DEZ, EFD) acknowledge the Mulago Foundation, the Horace W. Goldsmith Foundation, Robert Wood Johnson Foundation, and the World Diabetes Foundation. TRIAL REGISTRATION. Clinicaltrials.gov registry identifier: NCT01596244.

Weight loss strategies, weight change, and type 2 diabetes in US health professionals: A cohort study.

BackgroundWeight loss is crucial for disease prevention among individuals with overweight or obesity. This study aimed to examine associations of weight loss strategies (WLSs) with weight change and type 2 diabetes (T2D) risk among US health professionals.Methods and findingsThis study included 93,110 participants (24 to 60 years old; 11.6% male) from the Nurses’ Health Study (NHS), NHSII, and Health Professionals Follow-Up Study (HPFS) cohorts who were free of T2D, cardiovascular disease, and cancer at baseline (1988 for NHS/HPFS and 1989 for NHSII) for analyses of weight change and 104,180 (24 to 78 years old; 14.2% male) for T2D risk assessment. WLSs used to achieve an intentional weight loss of 4.5+ kg were collected in 1992 (NHS/HPFS)/1993 (NHSII) and grouped into 7 mutually exclusive categories, including low-calorie diet, exercise, low-calorie diet and exercise, fasting, commercial weight loss program (CWLP), diet pills, and FCP (selected at least 2 methods from fasting, CWLP, and pill). The reference group was participants who did not attempt to lose weight. Generalized estimating equations and Cox regression were applied to estimate up to 10-year weight change trajectory and incident T2D risk through 2016 (NHS/HPFS)/2017 (NHSII), respectively.The associations of WLSs with weight change and T2D risk were differential by baseline body weight (Pinteraction < 0.01). Among individuals with obesity, all WLSs tended to associate with less weight gain [ranging from −4.2% (95% confidence interval (CI), −5.1% to −3.2%; P < 0.001) for exercise to −0.3% (−1.2% to 0.7%; P > 0.99) for FCP] and a lower T2D risk [hazard ratios (HRs) ranging from 0.79 (0.66 to 0.95; P = 0.04) for exercise to 0.87 (0.66 to 1.13; P = 0.30) for pill]. Such a pattern was less clear among overweight individuals: the difference of weight change varied from −2.5% (−3.0% to −2.1%; P < 0.001) for exercise to 2.0% (1.3% to 2.7%; P < 0.001) for FCP, and HRs of T2D varied from 0.91 (0.77 to 1.07; P = 0.29) for exercise to 1.42 (1.11 to 1.81; P = 0.02) for pill. The pattern was further inverted among lean individuals in that weight change ranged from −0.4% (−0.6% to −0.1%; P = 0.02) for exercise to 3.7% (3.1% to 4.3%; P < 0.001) for FCP, and the HRs of T2D ranged from 1.09 (0.91 to 1.30; P = 0.33) for exercise to 1.54 (1.13 to 2.10; P = 0.008) for pill. Approximately 15.6% to 46.8% of the association between WLSs and the T2D risk was attributed to weight changes. This study was limited by a single assessment of WLSs, heterogeneity within each WLS, and potential misclassification of the timing of weight loss and weight regain.ConclusionsThe current study showed that individuals with obesity who attempted to lose weight, regardless of the WLSs used, tended to gain less body weight and have a lower diabetes risk. In contrast, lean individuals who intentionally lost weight tended to gain more weight and have a higher diabetes risk. These data support the notion that intentional weight loss may not be beneficial for lean individuals and the use of WLSs for achieving weight loss shall be guided by medical indications only.

Trajectories of body weight change and survival among patients with mCRC treated with systemic therapy: Pooled analysis from the ARCAD database

BackgroundHigher body mass index is associated with a higher incidence of colorectal cancer (CRC) but also with improved survival in metastatic CRC (mCRC). Whether weight change after mCRC diagnosis is associated with survival remains largely unknown. MethodsWe analysed individual patient data for previously untreated patients enrolled in five phase 3 randomised trials conducted between 1998 and 2006. Weight measurements were prospectively collected at baseline and up to 59.4 months after diagnosis. We used stratified multivariable Cox models to assess the prognostic associations of weight loss with overall and progression-free survival, adjusting for other factors. The primary end-point was a difference in overall survival (OS) between populations with weight loss and stable or increasing weight. FindingsData were available for 3504 patients. The median weight change at 3 months was −0.54% (IQR −3.9 … +1.5%). We identified a linear trend of increasing risk of death associated with progressive weight loss. Unstratified median OS was 20.5, 18.0, and 11.9 months (p < 0.001) for stable weight or gain, <5% weight loss, and ≥5% weight loss at 3 months, respectively. Weight loss was associated with a higher risk of death (<5% loss: aHR 1.18 [1.06–1.30], p < 0.002; ≥5% loss: aHR 1.87 [1.67–2.1], p < 0.001) as compared to stable or increasing weight at 3 months post-baseline (reference), while adjusting for age, sex, performance, and a number of metastatic sites. InterpretationPatients losing weight during systemic therapy for metastatic colorectal cancer have significantly shorter OS. The degree of weight loss is proportional to the observed increased risk of death and remains evident among underweight, normal weight, and obese individuals. On-treatment weight change could be used as an intermediate end-point. FundingThe creation and management of the database containing the individual patient data from the original randomised trials is supported by the Aide et Recherche en Cancérologie Digestive Foundation.

Association between long-term weight-change trajectory and cardiovascular disease risk by physical activity level

Using data from the Korean Genome and Epidemiology Study, we identified weight-change patterns during midlife using a group-based trajectory model, and evaluated their associations with the incidence of cardiovascular disease (CVD). At baseline, there were 8774 CVD-free participants. Group-based modeling was used to analyze patterns of weight change over about 16 years. Using multiple model, we evaluated the association between weight-change patterns and CVD risk. During the follow-up period, 741 new CVD cases were identified. The weight-change patterns were characterized as ‘gradual weight gain’, ‘stable weight’, ‘slight weight loss’, and ‘gradual weight loss’. The association between weight-change patterns and CVD risk differed depending on the level of physical activity (PA) at baseline (pinteraction < 0.05). Compared with the stable-weight group, the risk of all CVD (HR 2.5, 95% CI 1.5–4.3) and non-fatal CVD (HR 2.8, 95% CI 1.6–4.9) among the gradual-weight-loss group was apparent in the lowest PA quartile. In addition, on average, a decrease in skeletal-muscle-mass (SMM) levels was observed during the follow-up period, but the decrease in SMM in the gradual-weight-loss group was greater than in the gradual-weight-gain group. Our findings show that gradual weight loss was associated with CVD risk, which was dependent on PA levels.

Metabolic Syndrome and Prostate Cancer Risk: A Population Case-control Study

Metabolic syndrome (MS) with mixed dyslipidemia and prostate cancer (PC) are relevant health problems among Mexican men. However, there is no information regarding the association between MS and PC for this population. To evaluate this association in a population case-control study in Mexico City. We analyzed the information from 394 incident PC-cases and 793 population age-matched (± 5 years) controls, identified in Mexico City (2011-2014). For cases, Gleason score at diagnosis was available. We defined MS history based on the self-report of hypertension, hypercholesterolemia, hypertriglyceridemia, and diabetes; obesity was evaluated using weight-change trajectories throughout life. In addition, the four MS-typologies described for Mexican population were used. The association between MS with PC and histological PC differentiation was evaluated using independent multivariate logistic regression models. MS history was associated with a high PC probability (OR 1.94; 95% CI 1.37-2.75). Lipid alterations, arterial hypertension, and a marked weight increase throughout life were associated with increased PC probability; however, only the marked weight increase was associated with more poorly differentiated PC (Gleason ≥8) (OR 2.79; 95% CI 1.50-5.17). Like other populations, in this Mexican study, MS and some of its components were identified as potential PC risk factors. MS-lipid alteration typology seems to be relevant; however, the novelty of this approach together with the retrospective nature of this study, indicate that a prospective evaluation of the MS typologies and PC association must be performed.

Weight-change trajectory in relation to cancer risk: findings from a nationwide cohort study in South Korea.

This study examined relationships between weight-change trajectories and all cancers and obesity-related cancer risks. A total of 1,882,304 men and 899,912 women from the 2002 to 2017 National Health Insurance Service cohort were included. Weight-change trajectories in 2002 to 2009, according to BMI, were determined using group-based trajectory modeling. Cox proportional hazards regression assessed associations between trajectories and cancer incidence. Overall, >50% of individuals maintained stable weight, as did two-thirds of those in the overweight and obesity groups. A total of 64,725 men and 37,608 women developed incident cancer. Weight stability in overweight or obesity groups was associated with greater cancer risk. In both sexes, higher weight across BMI groups increased risks of all cancers, obesity-related cancers and thyroid, colorectal, stomach, liver, prostate, and postmenopausal breast cancer. Stratified by BMI, weight gain increased risks of all cancers and obesity-related cancers in men with obesity class I and women with overweight. Weight loss decreased risks of obesity-related cancers, thyroid cancer, and kidney cancer among men with overweight, premenopausal breast, endometrial, and ovarian cancer in women with overweight, and obesity-related cancers and thyroid cancer in women with class I obesity. Maintaining weight and avoiding weight gain are crucial for reducing cancer risk, but achieving a stable, normal BMI optimizes cancer prevention.