2-year Weight Change Research Articles

Length of Overnight Fasting and 6-year Weight Change in the Cancer Prevention Study-3

BackgroundLonger overnight fasting (ONF) is a potential strategy for weight control. Although promising, the evidence from large population-based studies is limited. ObjectivesTo examine the association of self-reported ONF duration with 3- and 6-y weight change in the American Cancer Society’s Cancer Prevention Study-3 prospective cohort. MethodsUnited States adult Cancer Prevention Study-3 participants completed a 24-h validated meal and snack timing and frequency grid (weekday and weekend) in 2015, from which weighted ONF hours were calculated. Participants reported body weight in 2015, 2018, and 2021. Three- and 6-y weight change (kg, and % body weight) were assessed. ResultsAmong 104,420 mostly female (78.5%) participants aged 52.7 ± 9.5 (standard deviation) y followed for 6 y, a 1-h increase in ONF length was associated with a small but statistically significant reduction in weight gain over 3- and 6-y periods [multivariable-adjusted mean difference in % body weight = −0.02, 95% confidence interval (CI): −0.05, −0.00, P = 0.03 and −0.04, 95% CI: −0.07, −0.01, P < 0.01, respectively]. The mean difference of 6-y % reduction in weight gain was slightly greater among individuals with overweight (−0.05, 95% CI: −0.10, 0.00, P = 0.05) and obesity (−0.06, 95% CI: −0.12, 0.01, P = 0.08) compared with those with healthy body mass index (−0.03, 95% CI:−0.07, 0.01, P = 0.13) or underweight (0.16, 95% CI: −0.04, 0.36, P = 0.13, Pinteraction < 0.0001). Stronger associations were observed among those ≤55 y than 56+ (P < 0.001), and those with higher waist circumference (Pinteraction < 0.0001) but not by sex or earlier/later fasting period. ConclusionsLonger ONF was associated with slightly lower body weight in adult males and females over 6 y that was stronger among those with overweight or obesity, higher waist circumference, and those aged ≤55 y. The magnitude of weight change, although in the hypothesized direction, suggests that prolonged ONF may have modest impact on weight control over time.

Association between a national behavioral weight management program and real-world weight change

ObjectiveIn a national cohort of Veterans, weight change was compared between participants in a US Department of Veterans Affairs (VA) behavioral weight management program (MOVE!) and matched non-participants, and between high-intensity and low-intensity participants. MethodsRetrospective cohort study of Veterans with 1 + MOVE! visits in 2008–2017 were matched to MOVE! non-participants via sequential stratification. Percent weight change up to two years after MOVE! initiation of participants and non-participants was modeled using generalized additive mixed models, and 1-year weight change of high-intensity or low-intensity participants was also compared. ResultsMOVE! participants (n = 499,696) and non-participant controls (n = 1,336,172) were well-matched, with an average age of 56 years and average BMI of 35. MOVE! participants lost 1.4 % at 12 months and 1.2 % at 24 months, which was 0.89 % points (95 % CI: 0.83–0.96) more at 12 months than non-participants and 0.55 % points (95 % CI: 0.41–0.68) more at 24 months. 9.1 % of MOVE! participants had high-intensity use in one year, and they had 2.38 % point (95 % CI: 2.25–2.52) greater weight loss than low-intensity participation at 12 months (2.8 % vs 0.4 %). ConclusionsParticipation in VA’s system-wide behavioral weight management program (MOVE!) was associated with modest weight loss, suggesting that program modifications are needed to increase Veteran engagement and program effectiveness. Future research should further explore how variations in program delivery and the use of newer anti-obesity medications may impact the program’s effectiveness.

Perceived Body Size in Relation to 10-Year Weight Change in the Swedish Obese Subjects Intervention Study

Introduction: Body size underestimation in patients with obesity may be associated with long-term weight increase. In the current report, we analyse changes in body size perception in patients with obesity undergoing either bariatric surgery or usual obesity care, and in subgroups of patients who gain weight or maintain their body weight over 10 years. Materials and Methods: A total of 2,504 patients with obesity from the prospective, controlled Swedish Obese Subjects (SOS) intervention study were included in this report, 1,370 patients underwent bariatric surgery and 1,134 patients were usual care controls. Weight was measured and body size was self-estimated using the Stunkard’s figure rating scale at baseline and after 0.5, 1, 2, 3, 4, 6, 8 and 10 years of follow-up. A body perception index (BPI) was calculated as estimated/measured BMI. Weight (re)gain was defined as ≥10% increase between 1 and 10 years of follow-up. Results: Body size was underestimated by 12% in the surgery and 14% in the control group (i.e., >5 BMI units) at baseline and underestimation largely persisted over 10 years in both intervention groups. When stratified by long-term weight development, weight regainers from the surgery group underestimated their body size to a larger degree compared to weight maintainers (12 vs. 9%, p < 0.001) after 10 years. Likewise weight gainers in the control group also underestimated their body size to a larger degree (17% vs. 13%, p < 0.001). In both groups, the change in BPI was significantly different between weight regainers and maintainers during follow-up (time-BPI interactions both p < 0.001). Conclusion: Patients with obesity underestimate their body size and this underestimation remains long-term even after major weight loss induced by bariatric surgery. In patients with obesity who maintain their weight, regardless of treatment, underestimation of body size persists but body size perception is slightly more accurate compared to patients who gain or regain weight long-term.

10-year Weight Change Is Predictive Of Biological Aging In 3,059 U.S. Adults

10-year Weight Change Is Predictive Of Biological Aging In 3,059 U.S. Adults

Associations between sleep health and obesity and weight change in adults: The Daily24 Multisite Cohort Study

ObjectivesTo examine cross-sectional and longitudinal associations of individual sleep domains and multidimensional sleep health with current overweight or obesity and 5-year weight change in adults. MethodsWe estimated sleep regularity, quality, timing, onset latency, sleep interruptions, duration, and napping using validated questionnaires. We calculated multidimensional sleep health using a composite score (total number of “good” sleep health indicators) and sleep phenotypes derived from latent class analysis. Logistic regression was used to examine associations between sleep and overweight or obesity. Multinomial regression was used to examine associations between sleep and weight change (gain, loss, or maintenance) over a median of 1.66 years. ResultsThe sample included 1016 participants with a median age of 52 (IQR = 37-65), who primarily identified as female (78%), White (79%), and college-educated (74%). We identified 3 phenotypes: good, moderate, and poor sleep. More regularity of sleep, sleep quality, and shorter sleep onset latency were associated with 37%, 38%, and 45% lower odds of overweight or obesity, respectively. The addition of each good sleep health dimension was associated with 16% lower adjusted odds of having overweight or obesity. The adjusted odds of overweight or obesity were similar between sleep phenotypes. Sleep, individual or multidimensional sleep health, was not associated with weight change. ConclusionsMultidimensional sleep health showed cross-sectional, but not longitudinal, associations with overweight or obesity. Future research should advance our understanding of how to assess multidimensional sleep health to understand the relationship between all aspects of sleep health and weight over time.

Legume Intake, Body Weight, and Abdominal Adiposity: 10-Year Weight Change and Cross-Sectional Results in 15,185 U.S. Adults.

There were three objectives: (1) evaluate the relationship between legume intake and weight change across the previous 10 years, (2) examine the cross-sectional associations between legume consumption, BMI, and abdominal adiposity, and (3) determine if the relationship between legume intake and the outcomes were influenced by multiple covariates, particularly fiber intake. The sample included 15,185 randomly selected adults representative of the U.S. population. Percent change in weight was used as the outcome measure for the 10-year analysis. BMI, and waist circumference, corrected for height, were employed as the outcomes for the cross-sectional analyses. Legume, fiber, and energy intakes were measured using the average of two 24-h dietary recalls. Legume intake was divided into three categories. Five demographic and five lifestyle covariates were controlled statistically. There was an inverse dose-response relationship between legume intake and percent weight change over the previous 10 years after adjusting for 9 of the covariates (F = 6.5, p = 0.0028). However, after controlling for fiber with the other covariates, there were no differences across the three legume intake groups (F = 1.9, p = 0.1626). The cross-sectional findings showed similar inverse dose-response results until fiber intake was controlled. Then the associations became non-significant. In conclusion, legume intake is a good predictor of percent weight change over the previous 10 years, and it is also a significant predictor of BMI and abdominal adiposity cross-sectionally. These relationships are strongly influenced by fiber consumption. Evidently, legumes have dietary advantages, especially high fiber levels, that seem to be valuable in the battle against weight gain and obesity.

Consistent and changing consumption of fast-food and full-service meals and 3-year weight change in a large population cohort study

BackgroundAn average American consumes 3 meals weekly from fast-food or full-service restaurants, which contain more calories, fat, sodium, and cholesterol than meals prepared at home. ObjectivesThis study examined whether consistent and changing fast-food or full-service consumption was associated with weight change over a 3-y period. MethodsAmong 98,589 US adults from the American Cancer Society’s Cancer Prevention Study-3, self-reported weight and fast-food and full-service consumption from 2015 and 2018 were examined using a multivariable-adjusted linear regression analysis to assess the association of consistent and changing consumption on 3-y weight change. ResultsIndividuals who made no changes to their fast-food or full-service intake over the study period gained weight regardless of consumption frequency, although low consumers gained less weight than high consumers (low fast-food: β = −1.08; 95% CI: −1.22, −0.93; low full-service: β = −0.35; 95% CI: −0.50, −0.21; P < 0.001). Decreased fast-food intake during the study period (e.g., from high [>1 meal/wk] to low [≤0.5 meal/wk], high to medium [>0.5 to ≤1 meal/wk], or medium to low) and decreased full-service intake from high (≥1 meal/wk) to low (<1 meal/mo) were significantly associated with weight loss (high–low: β = −2.77; 95% CI: −3.23, −2.31; high–medium: β = −1.53; 95% CI: −1.72, −1.33; medium–low: β = −0.85; 95% CI: −1.06, −0.63; high–low full-service: β = −0.92; 95% CI: −1.36, −0.49; P < 0.001). Decreased consumption of both fast-food and full-service restaurant meals was associated with greater weight loss than decreasing fast-food alone (both: β = −1.65; 95% CI: −1.82, −1.37; fast-food only: β = −0.95; 95% CI: −1.12, −0.79; P < 0.001). ConclusionsDecreased consumption of fast-food and full-service meals over 3 y, particularly among high consumers at baseline, was associated with weight loss and may be an effective approach to weight loss. Moreover, decreasing both fast-food and full-service meal consumption was associated with a greater weight loss than decreasing only fast-food meal consumption.

Dietary Intake of 91 Individual Polyphenols and 5-Year Body Weight Change in the EPIC-PANACEA Cohort.

Polyphenols are bioactive compounds from plants with antioxidant properties that may have a protective role against body weight gain, with adipose tissue and systemic oxidative stress as potential targets. We aimed to investigate the dietary intake of individual polyphenols and their association with 5-year body weight change in a sub-cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC). This study included 349,165 adult participants from nine European countries. Polyphenol intake was estimated through country-specific validated dietary questionnaires and the Phenol-Explorer database. Body weight was obtained at recruitment and after a mean follow-up time of 5 years. Associations were estimated using multilevel mixed linear regression models. From 91 polyphenols included, the majority (n = 67) were inversely associated with 5-year body weight change after FDR-correction (q < 0.05). The greatest inverse associations were observed for quercetin 3-O-rhamnoside (change in weight for doubling in intake: −0.071 (95% CI: −0.085; −0.056) kg/5 years). Only 13 polyphenols showed positive associations with body weight gain, mainly from the subclass hydroxycinnamic acids (HCAs) with coffee as the main dietary source, such as 4-caffeoylquinic acid (0.029 (95% CI: 0.021; 0.038) kg/5 years). Individual polyphenols with fruit, tea, cocoa and whole grain cereals as the main dietary sources may contribute to body weight maintenance in adults. Individual HCAs may have different roles in body weight change depending on their dietary source.

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.

Increases in physical activity are associated with a faster rate of weight loss during dietary energy restriction in women with overweight and obesity.

This secondary analysis examined the influence of changes in physical activity (PA), sedentary time and energy expenditure (EE) during dietary energy restriction on the rate of weight loss (WL) and 1-year follow-up weight change in women with overweight/obesity.Measurements of body weight and composition (air-displacement plethysmography), resting metabolic rate (indirect calorimetry), total daily (TDEE) and activity EE (AEE), minutes of PA and sedentary time (PA monitor) were taken at baseline, after 2 weeks, after ≥5% WL or 12 weeks of continuous (25% daily energy deficit) or intermittent (75% daily energy deficit alternated with ad libitum day) energy restriction, and at 1-year post-WL. The rate of WL was calculated as total %WL/number of dieting weeks. Data from both groups were combined for analyses.Thirty-seven participants (age=35±10y; BMI=29.1±2.3kg/m2) completed the intervention (WL=-5.9±1.6%) and 18 returned at 1-year post-WL (weight change=+4.5±5.2%). Changes in sedentary time at 2 weeks were associated with the rate of WL during energy restriction (r=-0.38; p=0.03). Changes in total (r=0.54; p<0.01), light (r=0.43; p=0.01) and moderate-to-vigorous PA (r=0.55; p<0.01), sedentary time (r=-0.52; p<0.01), steps per day (r=0.39; p=0.02), TDEE (r=0.46; p<0.01) and AEE (r=0.51; p<0.01) during energy restriction were associated with the rate of WL. Changes in total (r=-0.50; p=0.04) and moderate-to-vigorous PA (r=-0.61; p=0.01) between post-WL and follow-up were associated with 1-year weight change (r=-0.51; p=0.04).These findings highlight that PA and sedentary time could act as modifiable behavioural targets to promote better weight outcomes during dietary energy restriction and/or weight maintenance.

Moderate And Vigorous Physical Activity Predict 10-year Weight Change In 12,974 U.S. Adults

Moderate And Vigorous Physical Activity Predict 10-year Weight Change In 12,974 U.S. Adults

Differences in 5-year weight change between younger and older US firefighters

BackgroundResearch consistently finds that, on average, firefighters gain weight over time and some data indicate that younger firefighters are more likely to gain weight than older firefighters. The purpose of this study was to estimate the 5-year weight change among younger and older US firefighters.MethodsData from two occupational medical exams separated by 5 years (2009–2016) were examined from a cohort of US career firefighters in Virginia (males, n = 589; females, n = 67). The cohort was grouped into two age categories (< 45 years and ≥ 45 years). Weight change subgroups were Loss (decrease of > 3% body weight), Stable (within ±3% body weight) and Gain (increase of > 3% body weight). Multinomial logistic regression models and linear regression models were conducted to examine differences in the probability of being in a particular weight change category, weight change overall and by weight change category between younger and older firefighters.ResultsAt baseline, 25 and 35% of younger (< 45 years) and older (≥ 45 years) were obese, respectively. Younger firefighters gained significantly (P < 0.05) more weight (3.0 ± 0.2 kg) than older firefighters (0.8 ± 0.5 kg). Younger firefighters were more likely to gain weight (53% versus 39%) and less likely (10% versus 20%) to lose weight as compared to older firefighters. Smaller weight gains were associated with age and BMI with the smallest increases observed in overweight and obese firefighters ≥45 years of age.ConclusionsHealth care providers should be attentive to weight gain, even among young non-obese firefighters, and counsel firefighters to avoid the additive risks of being older and heavier. In addition, weight loss/management programs should be promoted in the fire service to encourage healthy body weight and to prevent unhealthy weight gain among both young and old firefighters alike.

Halo effect of a Mediterranean-lifestyle weight-loss intervention on untreated family members' weight and physical activity: a prospective study.

Obesity is subject to strong family clustering. The relatives of participants in weight-loss interventions may also modify their lifestyle and lose weight. The aim of this study was to examine the presence and magnitude of a halo effect in untreated family members of participants enrolled in a randomized, multi-component, lifestyle intervention. A total of 148 untreated adult family members of participants in an intensive weight-loss lifestyle intervention (the PREDIMED-Plus study) were included. Changes at 1 and 2 years in body weight, physical activity, and adherence to a traditional Mediterranean diet (MedDiet) were measured. Generalized linear mixed models were used to assess whether the change differed between family members of the intervention group compared to the control. Untreated family members from the intervention group displayed a greater weight loss than those from the control after 1 and 2 years: adjusted 2-year weight change difference between groups was -3.98 (SE 1.10) kg (p < 0.001). There was a halo effect with regard to adherence to the MedDiet at one year which was sustained at two years: 2-year adjusted difference in MedDiet score change +3.25 (SE 0.46) (p < 0.001). In contrast, no halo effect was observed with regard to physical activity, as the untreated family members did not substantially modify their physical activity levels in either group, and the adjusted difference at two years between the 2 groups was -272 (SE 624) METs.min/week (p = 0.665). In the first prospective study to assess the influence on untreated family members of a diet and physical activity weight-loss intervention, we found evidence of a halo effect in relatives on weight loss and improvement in adherence to a MedDiet, but not on physical activity. The expansion of MedDiet changes from individuals involved in a weight-loss intervention to their family members can be a facilitator for obesity prevention.

Weight change during middle age and risk of stroke and coronary heart disease: The Japan Public Health Center–based Prospective Study

Background and aimsThe impact of weight changes in middle age on the incidence of cardiovascular disease has not been well elucidated. We investigated whether a 5-year weight change was associated with risk of stroke and coronary heart disease (CHD) in middle-aged individuals. MethodsWe analyzed data of 74,928 participants aged 40–69 years who provided responses to the baseline and 5-year follow-up questionnaires in the Japan Public Health Center–based Prospective Study. Weight change was calculated by subtracting self-reported weight at baseline from that at 5-year follow-up. Stroke and CHD events were confirmed by reviewing hospital records. ResultsDuring 997,406 person-years of follow-up, we documented 3,975 stroke and 914 CHD events. The multivariable HRs of stroke for losing ≥5 kg compared to stable weight (change ≤2 kg) was 1.17 (95% CI, 1.01–1.37) in men versus 1.33 (1.13–1.57) for losing ≥5 kg and 1.61 (1.36–1.92) for gaining ≥5 kg in women (U-shaped association). These associations did not change after the exclusion of early events. The multivariable HR of CHD for gaining ≥5 kg was 1.22 (0.95–1.58) in men. After exclusion of early events within another 5 years, that positive association became stronger [multivariable HR 1.34 (1.00–1.82)]. ConclusionsWeight gain during middle age was associated with an increased risk of stroke in women and an increased risk of CHD in men. Weight loss was associated with an increased risk of stroke in both men and women.

The association between weight-promoting medication use and weight gain in postmenopausal women: findings from the Women's Health Initiative

With the rise in obesity, there has been a concomitant increase in prescription medications associated with weight gain. The objective of this study is to quantify the magnitude of association between putative weight-promoting medications and 3-year weight change in a diverse cohort of postmenopausal women in the Women's Health Initiative (WHI). This is a prospective observational cohort study, considering 40 sites in the WHI and a cohort of seventy six thousand two hundred fifty-two postmenopausal women aged 50-79 years, with weight measured at both baseline and 3 years, in the WHI-Observational Study. Body mass index (BMI) and waist circumference (WC) were measured at baseline and 3 years. An in-clinic medication inventory identified prescribed medications, including antidepressants, beta-blockers, insulin, and/or glucocorticosteroids. Generalized linear models evaluated if intermittent or persistent use of weight-promoting drugs was associated with increased BMI and WC during a 3-year follow up. Women with overweight or obesity at baseline were more likely to be taking antidepressants, beta-blockers, and/or insulin. Taking at least one putative weight-promoting medication was associated with a greater increase in BMI (0.37 vs 0.27 kg/m, P = 0.0045) and WC (1.10 cm vs 0.89 cm, P = 0.0077) over the course of 3 years compared to women not on these medications. Both BMI and WC increased with the number of weight-promoting drugs prescribed (P for trend per medication used < 0.00001 for both variables). Those who took either antidepressants or insulin, or a combination of antidepressants and beta-blockers, were most likely to have a significant increase in BMI compared to nonusers. Antidepressants, beta-blockers, and insulin were associated with weight gain in postmenopausal women. This information may help to inform clinical decision-making and efforts to mitigate medication-related weight gain. : Video Summary:http://links.lww.com/MENO/A617.

Evaluation of Prediction Models for Type 2 Diabetes Relapse After Post-bariatric Surgery Remission: a Post hoc Analysis of 15-Year Follow-up Data from the Swedish Obese Subjects (SOS) Study

PurposeMany patients achieve type 2 diabetes (T2D) remission after bariatric surgery, but relapse after post-surgery remission is common. Scoring models accurately predict remission up to 5 years after surgery but have not been tested for prediction of long-term T2D relapse. The aim of this work was to test the ability of prediction models and single predictors to identify patients at risk of long-term relapse (10–15 years) after post-surgery T2D remission.MethodsWe identified 222 individuals with T2D from the surgically treated group in the prospective Swedish Obese Subjects study, who were in remission at the 2-year follow-up and had data available for prediction of long-term T2D relapse. T2D remission/relapse was assessed after 10 and 15 years. Model performance (discrimination) was evaluated by the area under the receiver operating characteristic (AUROC) curves.ResultsPreoperative prediction of relapse using scores DiaRem, Ad-DiaRem, and DiaBetter and T2D duration alone was poor, as indicated by AUROC curves between 0.61–0.64 at 10 years and 0.62–0.66 at 15 years. Likewise, the 5y-Ad-DiaRem score, which includes early postoperative measures, resulted in AUROC curves of 0.65 and 0.70 for relapse at 10 and 15 years, respectively. Two-year weight change alone had higher discriminatory capacity than the 5y-Ad-DiaRem model at 10 years (AUROC = 0.70; p = 0.036) and similar capacity at 15 years (AUROC = 0.78; p = 0.188).ConclusionsPredictive performance of all tested models is low for T2D relapse. By contrast, a single measure of 2-year weight change after surgery was associated with relapse, supporting a key role for initial weight reduction in long-term T2D control.

Abstract P209: Sugar and Artificially-sweetened Beverages and 6-year Weight Change: Results From The Hispanic Community Health Study, Study of Latinos

Background: Sugar sweetened beverages (SSBs) are the largest contributor to added sugars and calories in the U.S. diet with highest intake among US Hispanics. The prevalence of obesity in adults in the US is much higher in Hispanics compared to non-Hispanic whites (47% and 38% respectively). Improving our understanding of the association between SSB and artificially sweetened beverage (ASB) consumption and measures of adiposity can inform interventions targeting overweight and obesity. Aim: Examine the independent associations of daily SSB and ASB consumption with 6-year changes in weight, waist circumference (WC) and body mass index (BMI) in Hispanics in the US. Methods: We examined 7402 adults without diabetes aged 18-74yrs at baseline (2008-11) from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multi-site community-based cohort in the US. Baseline exposures of daily SSB and ASB consumption were estimated combining two 24-hour dietary recalls and a Food Propensity Questionnaire using the NCI method to correct for measurement error and account for episodically consumed foods. Complex survey linear regression models were used to examine associations of SSBs and ASBs with 6-year change in weight (kg), WC (cm) and BMI. Models were adjusted for age, gender, center, background, education, employment, marital status, cigarette use, physical activity, healthy eating index, depressive symptoms, non-SSB sugar intake, years in the US and years between visits. Interactions of SSB and ASB with gender and years lived in the U.S. (US born, &gt;10yr, ≤10 yr) were assessed. Results: Overall, 3326 [male=49.7%] and 1244 [male=35.7%] reported daily intake of &gt;2 servings of SSBs and ASBs respectively whereas 2203 [male=26.1%] and 4318 [male=41.2%] reported daily intake &lt; 1 servings of SSBs and ASBs respectively. Daily energy intake (kcal) was higher among those with higher daily SSB consumption [means=14768 and 2008 kcals; &lt;1 serving and &gt;2 servings, respectively] and lower with higher ASB consumption (means=1836 and 1773 kcals; &lt;1 serving and &gt;2 servings, respectively). Daily sugar intake independent of SSBs was higher with daily consumption of both SSB and ASB (&lt;1 serving vs. 2 servings). Non-significant associations were found for daily SSB and ASB intake and changes in adiposity for all measures in males and females. Interaction between years in the U.S. and ASB consumption were significant only for change in weight and BMI [p&lt;0.05]. Among those consuming &lt;1 serving per day of ASBs, there was a larger mean change in weight and BMI for those who spent &lt; 10yr in the U.S. compared to U.S. born. Conclusion: In this diverse Hispanic cohort, 6-year changes in measures of adiposity are not associated with daily SSB or ASB consumption. Modification of the association of ASB and measures of adiposity by years in US suggests further exploration is needed to discern its relationship among Hispanics.

Frequency and variety of usual intakes of healthy foods, fruit, and vegetables predicts lower 6-year weight gain in young women.

We previously demonstrated that fruit and vegetable consumption, was associated with less weight gain over 6 years in young women for all body mass index (BMI) categories. This study evaluated the relationship between diet quality and 6-year weight change, in Australian women initially in the healthy weight range (≥18.5 BMI <25 kg/m2) at baseline. A total of 4083 young women (27-31 years) in the healthy weight range (≥18.5 BMI <25 kg/m2) enroled in the Australian Longitudinal study on Women's Health (ALSWH) were analysed. Diet quality was measured by the Australian Recommended Food Score (ARFS) and the Fruit and Vegetable Index (FAVI) using dietary data derived from a validated food frequency questionnaire. Weight change was calculated as the difference between baseline and 6-year follow-up weight (kg). Multiple linear regression models were used to analyse the association between baseline ARFS and FAVI and 6-year weight change. At baseline, mean diet quality was low for both indices [ARFS (maximum 72) = 29.9 and FAVI (maximum 333) = 94.2] and women gained 3.7 kg of weight during 6 years of follow-up. Regression modelling revealed that every one point increase over 6 years in either the ARFS or FAVI score was associated with statistically significantly less weight gain over 6 years, although the amount was small (33 and 12 g, respectively). Higher diet quality predicts lower prospective weight gain in young women however, further research is needed over a longer follow-up period and in diverse population groups.

The Risks of Cardiovascular Disease and Mortality Following Weight Change in Adults with Diabetes: Results from ADVANCE.

Weight loss is strongly recommended for overweight and obese adults with type 2 diabetes. Unintentional weight loss is associated with increased risk of all-cause mortality, but few studies have examined its association with cardiovascular outcomes in patients with diabetes. To evaluate 2-year weight change and subsequent risk of cardiovascular events and mortality in established type 2 diabetes. The Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation was an international, multisite 2×2 factorial trial of intensive glucose control and blood pressure control. We examined 5 categories of 2-year weight change: >10% loss, 4% to 10% loss, stable (±<4%), 4% to 10% gain, and >10% gain. We used Cox regression with follow-up time starting at 2 years, adjusting for intervention arm, demographics, cardiovascular risk factors, and diabetes medication use from the 2-year visit. Among 10 081 participants with valid weight measurements, average age was 66 years. By the 2-year examination, 4.3% had >10% weight loss, 18.4% had 4% to 10% weight loss, and 5.3% had >10% weight gain. Over the following 3 years of the trial, >10% weight loss was strongly associated with major macrovascular events (hazard ratio [HR], 1.75; 95% confidence interval [CI], 1.26-2.44), cardiovascular mortality (HR, 2.76; 95% CI, 1.87-4.09), all-cause mortality (HR, 2.79; 95% CI, 2.10-3.71), but not major microvascular events (HR, 0.91; 95% CI, 0.61-1.36), compared with stable weight. There was no evidence of effect modification by baseline body mass index, age, or type of diabetes medication. In the absence of substantial lifestyle changes, weight loss may be a warning sign of poor health meriting further workup in patients with type 2 diabetes.

Perfluoroalkyl substances and changes in bone mineral density: A prospective analysis in the POUNDS-LOST study

BackgroundRecent studies suggested an inverse association between exposures to perfluoroalkyl substances (PFASs) and bone mineral density (BMD). Whether exposures to PFASs are also associated with changes in BMD has not been examined. MethodsFive major PFASs (perfluorooctanesulfonic acid, PFOS; perfluorooctanoic acid, PFOA; perfluorohexanesulfonic acid, PFHxS; perfluorononanoic acid, PFNA; perfluorodecanoic acid, PFDA) and BMD (g/cm2) at six bone sites (spine, total hip, femoral neck, hip intertrochanteric area, hip trochanter, and hip Ward's triangle area) were measured at baseline among 294 participants in the POUNDS-LOST study, a weight-loss trial, of whom a total of 175 participants had BMD measured at both baseline and year 2. Linear regression was used to model the differences or changes in BMD for each SD increment of PFAS concentrations. In a secondary analysis, interactions between PFASs and baseline body mass index (BMI), as well as a BMI-related genetic risk score (GRS) derived from 97 BMI-predicting SNPs were examined in relation to changes in BMD. ResultsAt baseline, both PFOS and PFOA were significantly associated with lower BMD at several sites. For each SD increase of PFOS, the βs (95% CIs) for BMD were −0.020(-0.037, −0.003) for spine, −0.013(-0.026, 0.001) for total hip, −0.014(-0.028, 0.000) for femoral neck, and −0.013(-0.026, 0.000) for hip trochanter. For PFOA, the corresponding figures were −0.021(-0.038, −0.004) for spine, −0.015(-0.029, −0.001) for total hip, and −0.015(-0.029, −0.002) for femoral neck. After adjusting for baseline covariates and 2-year weight change, higher baseline plasma concentrations of PFOS, PFNA, and PFDA were associated with greater reduction in BMD in the hip; the βs (95% CIs) were −0.005(-0.009, −0.001), −0.006(-0.010, −0.001), and −0.005(-0.009, −0.001), respectively. Similar associations were found in hip intertrochanteric area for all PFASs except PFHxS, with βs ranging from −0.006 for PFOA to −0.008 for PFOS and PFNA. Participants with a higher GRS tended to have less PFAS-related BMD decline in total hip (Pinteraction = 0.005) and the hip intertrochanteric area (Pinteraction = 0.021). There were similar PFAS-related BMD changes by baseline BMI levels, although the interactions did not achieve statistical significance. ConclusionsThis study demonstrated that higher plasma PFAS concentrations were not only associated with a lower BMD at baseline, but also a faster BMD loss in a weight-loss trial setting. Genetic predisposition to larger body size may somewhat attenuate the deleterious effects of PFASs on BMD. Further exploration of the possible impact of PFAS exposures on bone density is warranted.