Hepatic, adipocyte, enteric and pancreatic hormones: response to dietary macronutrient composition and relationship with metabolism

Background

We sought to characterize the effects of dietary macronutrient composition on various hormones implicated in the regulation of insulin sensitivity (IS) and energy expenditure (EE).

Methods

Following 10–15% weight loss, 21 overweight subjects consumed 3 weight-loss maintenance diets [low fat (LF), low glycemic index (LGI) and very low carbohydrate (VLC)] in random order, each for 4 weeks. At baseline and at the end of each treatment period, fasting samples for fibroblast growth factor (FGF)-21, heme-oxygenase-1 (HO-1), chemerin, irisin, secreted frizzle-related protein (SFRP-4), total bile acids, ghrelin, gastrin inhibitory peptide (GIP), peptide-Y, and amylin; hepatic and peripheral IS; and EE were obtained. Analyses were controlled for age, gender, baseline body mass index, and diet sequence.

Results

FGF-21 decreased (P < 0.0001), with differential effect by macronutrient composition (mean change from baseline ± SEM: LF −49.4 ± 16.6, LGI -58.6 ± 16.3, VLC -76.7 ± 18.2 pg/mL, P = 0.0002). Change in FGF-21 was inversely associated with change in hepatic IS [Beta = −0.565 units/log(ng/mL), P = 0.02], but not with peripheral IS or EE. Heme-oxygenase-1 (HO-1) increased (P = 0.003), without differential effect by macronutrient composition (LF 0.40 ± 0.26, LGI 0.98 ± 0.63, VLC 0.49 ± 0.29 ng/mL, P = 0.07). Ghrelin increased (P = 0.0003), while chemerin decreased (P = 0.001) without macronutrient effect. Total bile acid, irisin, SFRP-4, GIP, peptide-Y and amylin levels did not change.

Conclusions

FGF-21 levels decreased with dietary intervention in proportion to carbohydrate content, and correlated with hepatic insulin sensitivity, suggesting a pattern of improving FGF-21 resistance. HO-1 increased in response to dietary intervention, a tendency to greater increase in response to the LGI diet. Dietary intervention affected ghrelin and chemerin, independent of macronutrient composition. These findings may elucidate relationships between dietary composition, insulin sensitivity and metabolism.

Trial registration

NCT00315354.

Effects of Advice to Drink 8 Cups of Water per Day in Adolescents With Overweight or Obesity: A Randomized Clinical Trial

IMPORTANCE

Health care professionals commonly recommend increased water consumption, typically to 8 cups per day, as part of a weight-reducing diet. However, this recommendation is based on limited evidence and virtually no experimental data from the pediatric population.

OBJECTIVE

To compare 2 standardized weight-loss diets among adolescents with overweight or obesity, either with or without additional advice and behavioral support to increase habitual water intake to 8 cups per day.

DESIGN, SETTING, AND PARTICIPANTS

A randomized clinical, parallel-group trial was conducted between February 2, 2011, and June 26, 2014, at Boston Children's Hospital, Boston, Massachusetts, among 38 adolescents with overweight or obesity who reported drinking 4 cups or less of water per day.

INTERVENTIONS

All participants in both groups received similar weight-reducing interventions, differentiated by advice about water intake (the water group received advice to increase water intake to 8 cups per day; the control group did not receive such advice) but controlled for other dietary recommendations and treatment intensity. The interventions included dietary counseling, daily text messages, and a cookbook with health guides. To support adherence to 8 cups of water per day, the water group received well-defined messages about water through counseling and daily text messages, a water bottle, and a water pitcher with filters.

MAIN OUTCOMES AND MEASURES

The primary outcome was 6-month change in body mass index z score. Data analyses followed the intention-to-treat principle.

RESULTS

All 38 participants (27 girls and 11 boys; mean [SD] age, 14.9 [1.7] years) completed the study. Both groups reported drinking approximately 2 cups of water per day at baseline. Self-reported change in water intake at 6 months was greater in the water group (difference from baseline, 2.8 cups per day [95% CI, 1.8 to 3.8]; P < .001) compared with that in the control group (difference from baseline, 1.2 cups per day [95% CI, 0.2 to 2.2]; P = .02) (difference between groups, 1.6 cups per day [95% CI, 0.2 to 3.0 cups per day]; P = .03). The 6-month change in body mass index z score did not differ between the water group (difference from baseline, -0.1 [95% CI, -0.2 to -0.0]; P = .005) and the control group (difference from baseline, -0.1 [95% CI, -0.2 to -0.0]; P = .008) (difference between groups, -0.0 [95% CI, -0.1 to 0.1]; P = .88).

CONCLUSIONS AND RELEVANCE

Advice and behavioral supports to consume 8 cups of water per day in the context of a weight-reducing diet did not affect body weight among adolescents with overweight or obesity. Despite intensive behavior supports, few adolescents achieved the target of 8 cups of water per day. Environmental interventions to reduce barriers to water consumption at school may be necessary in future research of the feasibility and effectiveness to achieve the target of an intake of 8 cups of water per day in adolescents.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT01044134.

Calorically restricted diets decrease PCSK9 in overweight adolescents

BACKGROUND AND AIMS

Nutritional therapy is the first line approach to treatment of hyperlipidemia in childhood. Proprotein convertase subtilisin kexin type 9 (PCSK9) is a key regulator of plasma cholesterol levels and a target of novel lipid-lowering pharmacotherapies. We examined the effects of an intensive nutritional intervention on PCSK9 levels in overweight adolescents with cardiovascular disease (CVD) risk factors.

METHODS AND RESULTS

Twenty seven obese and overweight adolescents with CVD risk factors were assigned to either a low fat or low glycemic load diet. During an 8-week "Intensive Phase," assigned meals were delivered to the home, and all participants received weekly in-person home nutrition counseling and phone calls. The subjects then underwent a 4-month "Maintenance Phase" without food provision and with no in-person contact. Anthropometric measurements, laboratory data, and serum PCSK9 protein levels were measured at baseline, 8 weeks, and 6 months. PCSK9 decreased by 16.5% at 8 weeks (201.2 ± 56.3 vs 165.6 ± 58.4 ng/mL; p < 0.001); PCSK9 levels returned to baseline levels at 6 months, after the Maintenance Phase. Change in PCSK9 was associated with change in fasting insulin, HOMA-IR, and AUC insulin, independent of weight loss.

CONCLUSIONS

PCSK9 decreased in youth participating in an intensive dietary intervention. Change in HOMA-IR was associated with change in PCSK9, independent of weight loss, suggesting an important relationship with insulin sensitivity. ClinicalTrials.gov Identifier: NCT01080339.

Metabolomic profiles as reliable biomarkers of dietary composition

Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects.Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol.Design: Twenty-one adults with a high body mass index (in kg/m²; mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons.Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors.Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354.

Carbohydrate-last meal pattern lowers postprandial glucose and insulin excursions in type 2 diabetes

BACKGROUND

There are limited data regarding the timing of carbohydrate ingestion during a meal and postprandial glucose regulation.

METHODS

Sixteen subjects with type 2 diabetes mellitus (T2DM) consumed the same meal on 3 days in random order: carbohydrate first, followed 10 min later by protein and vegetables; protein and vegetables first, followed 10 min later by carbohydrate; or all components together. Blood was sampled for glucose, insulin, glucagon-like peptide-1 (GLP-1), and glucagon measurements at baseline (just before meal ingestion) and subsequently at 30 min intervals up to 180 min.

RESULTS

The incremental areas under the curve for glucose (iAUC_0-180) and incremental glucose peaks were 53% and 54% lower, respectively, when carbohydrate was consumed last compared with carbohydrate consumed first (3124.7±501.2 vs 6703.5±904.6 mg/dL×180min, p<0.001; 34.7±4.1 vs 75.0±6.5 mg/dL, p<0.001) and 44% and 40% lower, respectively, compared with the all components together condition (3124.7±501.2 vs 5587.1±828.7 mg/dL×180min, p=0.003; 34.7±4.1 vs 58.2±5.9 mg/dL, p<0.001). Postprandial insulin excursions were lower (iAUC_0-180: 7354.1±897.3 vs 9769.7±1002.1 µU/mL×min, p=0.003) and GLP-1 excursions higher (iAUC_0-180: 3487.56±327.7 vs 2519.11±494.8 pg/mL×min, p=0.019) following the carbohydrate-last meal order compared with carbohydrate first.

CONCLUSION

The carbohydrate-last meal pattern may be an effective behavioral strategy to improve postprandial glycemia.

Creating an integrated care model for childhood obesity: a randomized pilot study utilizing telehealth in a community primary care setting

In an integrated care model, involving primary care providers (PCPs) and obesity specialists, telehealth may be useful for overcoming barriers to treating childhood obesity. We conducted a pilot study comparing body mass index (BMI) changes between two arms (i) PCP in-person clinic visits plus obesity specialist tele-visits ( PCP visits + specialist tele-visits) and (ii) PCP in-person clinic visits only ( PCP visits only), with ongoing tele-consultation between PCPs and obesity specialists for both arms. Patients (N = 40, 10-17 years, BMI ≥ 95th percentile) were randomized to Group 1 or 2. Both groups had PCP visits every 3 months for 12 months. Using a cross-over protocol, Group 1 had PCP visits + specialist tele-visits during the first 6 months and PCP visits only during the second 6 months, and Group 2 followed the opposite sequence. Each of 12 tele-visits was conducted by a dietitian or psychologist with a patient and parent. Retention rates were 90% at 6 months and 80% at 12 months. BMI (z-score) decreased more for Group 1 (started with PCP visits + specialist tele-visits) vs. Group 2 (started with PCP visits only) at 3 months (-0.11 vs. -0.05, P = 0.049) following frequent tele-visits. At 6 months (primary outcome), BMI was lower than baseline within Group 1 (-0.11, P = 0.0006) but not Group 2 (-0.06, P = 0.08); however, decrease in BMI at 6 months did not differ between groups. After crossover, BMI remained lower than baseline for Group 1 and dropped below baseline for Group 2. An integrated care model utilizing telehealth holds promise for treating children with obesity.

Outcomes from an orientation model to reduce attrition in paediatric weight management

We aimed to reduce attrition of newly referred patients in a paediatric weight management programme by implementing an orientation to address families' expectations and screen for and support behavioural and mental health problems and psychosocial stressors at programme outset. Orientation impact was monitored with run charts with percentages of scheduled encounters completed. Long-term impact was assessed by comparing patients in the initial 6 months of the orientation to a baseline group of referred patients during the same 6-month time interval in the prior year (Pre-Orientation Group). The outcome measure was programme attrition within 15 months. Groups were compared using Kaplan-Meier survival analysis and Cox proportional hazards regression modelling. Patients in the Orientation Group had a 23% increased odds of attrition compared to patients in the Pre-Orientation group (adjusted Hazard ratio, aHR 1.23; 95% confidence interval, CI: 1.01, 1.51) and shorter median duration of follow-up (2.0 vs. 2.9 months, P = 0.004). An increase in body mass index z-score of 1 unit resulted in a nearly fivefold increased odds of attrition (aHR 5.24; 95% CI: 2.95, 9.3). An orientation for new patients did not reduce attrition within 15 months. We suggest that ongoing retention strategies should be embedded into the treatment phase of the programme.

Physical changes in the home environment to reduce television viewing and sugar-sweetened beverage consumption among 5- to 12-year-old children: a randomized pilot study

This study evaluated the feasibility of a home-based intervention to reduce sugar-sweetened beverage intake and television viewing among children. Lower income parents of overweight children aged 5-12 years (n = 40) were randomized to a home environment intervention to reduce television viewing with locking devices and displace availability of sugar-sweetened beverages with home delivery of non-caloric beverages (n = 25), or to a no-intervention control group (n = 15) for 6 months. Data were collected at baseline and 6 months. After 6 months, television viewing hours per day was significantly lower in the intervention group compared with the control group (1.7 [SE = .02] vs. 2.6 [SE = .25] hours/day, respectively, P < .01). Sugar-sweetened beverage intake was marginally significantly lower among intervention group compared to control group children (0.21 [SE = .09] vs. 0.45 [SE = .10], respectively, P < .09). Body mass index (BMI) z-score was not significantly lower among intervention compared to control children. Among a lower income sample of children, a home-based intervention reduced television viewing, but not sugar-sweetened beverage intake or BMI z-score.

A randomized pilot study of dietary treatments for polycystic ovary syndrome in adolescents

BACKGROUND

Evidence is lacking to recommend one diet over another when treating polycystic ovary syndrome (PCOS).

OBJECTIVES

To obtain preliminary data, comparing the impact of a low-glycaemic load (LGL) vs. low-fat (LF) diet on biochemical hyperandrogenism in overweight and obese adolescents with PCOS. To ascertain feasibility of recruiting study participants, in partnership with an adolescent clinic, and implementing dietary interventions.

METHODS

Randomized controlled trial of 19 overweight and obese adolescents with PCOS and not using hormonal contraceptives (HCs). Interventions comprised nutrition education, dietary counselling and cooking workshops to foster adherence to a LGL (45% carbohydrate, 35% fat, 20% protein) or LF (55% carbohydrate, 25% fat, 20% protein) diet over 6 months. Serum bioavailable testosterone was the primary outcome.

RESULTS

Sixteen (LGL, n = 7; LF, n = 9) participants completed the study. Body fat percentage decreased (P < 0.05) in response to the interventions, with no difference between the LGL and LF groups (-1.2% vs. -2.2%; P = 0.16). Bioavailable testosterone did not change for either group (-0.4 vs. -1.8 ng dL(-1) ; P = 0.35). Regarding feasibility, recruiting adolescents posed a challenge, and use of HCs was a main reason for ineligibility. Participants attended 5.9 of 6 in-person visits and 2.6 of 3 cooking workshops, completed 4.9 of 6 telephone counselling calls, and reported high satisfaction with the diets and cooking workshops (≥8 on a 10-cm scale).

CONCLUSIONS

Dietary interventions were beneficial for weight control but did not attenuate biochemical hyperandrogenism. Innovative strategies are needed to recruit adolescents for studies aimed at assessing independent effects of diet on features of PCOS.

Effect of low-fat diet interventions versus other diet interventions on long-term weight change in adults: a systematic review and meta-analysis

BACKGROUND

The effectiveness of low-fat diets for long-term weight loss has been debated for decades, with many randomised controlled trials (RCTs) and recent reviews giving mixed results. We aimed to summarise the large body of evidence from RCTs to determine whether low-fat diets contribute to greater weight loss than participants' usual diet, low-carbohydrate diets, and other higher-fat dietary interventions.

METHODS

We did a systematic review and random effects meta-analysis of RCTs comparing the long-term effect (≥1 year) of low-fat and higher-fat dietary interventions on weight loss by searching MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), and Cochrane Database of Systematic Reviews to identify eligible trials published from database inception up until July 31, 2014. We excluded trials if one intervention group included a non-dietary weight loss component but the other did not, and trials of dietary supplements or meal replacement drink interventions. Data including the main outcome measure of mean difference in weight change between interventions, and whether interventions were intended to lead to weight loss, weight maintenance, or neither, were extracted from published reports. We estimated the pooled weighted mean difference (WMD) with a DerSimonian and Laird random effects method.

FINDINGS

3517 citations were identified by the search and 53 studies met our inclusion criteria, including 68 128 participants (69 comparisons). In weight loss trials, low-carbohydrate interventions led to significantly greater weight loss than did low-fat interventions (18 comparisons; WMD 1·15 kg [95% CI 0·52 to 1·79]; I(2)=10%). Low-fat interventions did not lead to differences in weight change compared with other higher-fat weight loss interventions (19 comparisons; WMD 0·36 kg [-0·66 to 1·37; I(2)=82%), and led to a greater weight decrease only when compared with a usual diet (eight comparisons; -5·41 kg [-7·29 to -3·54]; I(2)=68%). Similarly, results of non-weight-loss trials and weight maintenance trials, for which no low-carbohydrate comparisons were made, showed that low-fat versus higher-fat interventions have a similar effect on weight loss, and that low-fat interventions led to greater weight loss only when compared with usual diet. In weight loss trials, higher-fat weight loss interventions led to significantly greater weight loss than low-fat interventions when groups differed by more than 5% of calories obtained from fat at follow-up (18 comparisons; WMD 1·04 kg [95% CI 0·06 to 2·03]; I(2)=78%), and when the difference in serum triglycerides between the two interventions at follow-up was at least 0·06 mmol/L (17 comparisons; 1·38 kg [0·50 to 2·25]; I(2)=62%).

INTERPRETATION

These findings suggest that the long-term effect of low-fat diet intervention on bodyweight depends on the intensity of the intervention in the comparison group. When compared with dietary interventions of similar intensity, evidence from RCTs does not support low-fat diets over other dietary interventions for long-term weight loss.

FUNDING

National Institutes of Health and American Diabetes Association.

Relationship of insulin dynamics to body composition and resting energy expenditure following weight loss

OBJECTIVE

To examine associations of baseline insulin dynamics with changes in body composition and resting energy expenditure (REE) following weight loss.

METHODS

Twenty-one participants with overweight or obesity achieved 10-15% weight loss and then received 3 weight loss maintenance diets (high-carbohydrate, moderate-carbohydrate, and low-carbohydrate) in random order, each for 4 weeks. Body composition was measured at baseline and after weight loss. Insulin 30 min after glucose consumption (insulin-30; insulin response), C-peptide deconvolution analysis, HOMA, hepatic insulin sensitivity (IS), and REE were assessed at baseline and after each maintenance diet.

RESULTS

Insulin-30, but not maximal insulin secretion, hepatic IS, or HOMA, predicted changes in fat mass (standardized β = 0.385, 1.7 kg difference between 10th and 90th centile of insulin-30, P = 0.04) after weight loss. Insulin-30 (β = -0.341, -312 kcal day(-1) , P = 0.008), maximal insulin secretion (β = -0.216, -95 kcal day(-1) , P = 0.0002), HOMA (β = -0.394, -350 kcal day(-1) , P = 0.002), and hepatic IS (β = 0.217, 225 kcal day(-1) , P = 0.0003) predicted change in REE during weight loss maintenance, independent of changes in body composition. The inverse relationship between insulin-30 and REE was substantially attenuated when the low-carbohydrate diet was consumed first.

CONCLUSIONS

These findings distinguish a novel phenotype, characterized by high insulin response, at risk for weight regain, and identify a dietary approach to ameliorate this risk.

Providing food to treat adolescents at risk for cardiovascular disease

OBJECTIVE

Diet modification is recommended to treat childhood cardiovascular (CV) risk factors; however, the optimal dietary strategy is unknown.

METHODS

In a randomized trial, the effect of a low-fat (LF) and a low-glycemic-load (LGL) reduced-calorie diet were examined in youth with overweight/obesity with CV risk factors. Using a novel intervention, we delivered LF or LGL meals and nutrition education to the home for 8 weeks (Intensive Phase), followed by 4 months Maintenance without food provision. Between-group differences in the change in insulin area under the curve (InsAUC) by oral glucose tolerance test and other risk factors were analyzed.

RESULTS

Overall, participants (n = 27) showed substantial improvement during the Intensive Phase, including InsAUC (-59 ± 18.2 µU/ml × 120 min, P = 0.004), total cholesterol (-9.9 ± 3.6 mg/dl, P = 0.01), weight (-2.7 ± 0.5 kg, P < 0.001), waist circumference (-3.1 ± 0.8 cm, P < 0.001), HOMA-IR (-1.7 ± 0.4, P < 0.001), systolic blood pressure (-5 ± 1.4 mm Hg, P = 0.002), and CRP (-0.1 ± 0.1 mg/dl, P = 0.04). There were minimal between-group differences; the LF group showed greater declines in HDL (P = 0.005) and fasting glucose (P = 0.01) compared to the LGL group. Improvements waned during Maintenance.

CONCLUSIONS

Home delivery of LF or LGL diets resulted in rapid and clinically important improvements in CV risk factors that diminished without food delivery and did not differ based on dietary intervention. If scalable, food provision may represent an alternative nutrition treatment strategy.

Changes in Intake of Fruits and Vegetables and Weight Change in United States Men and Women Followed for Up to 24 Years: Analysis from Three Prospective Cohort Studies

BACKGROUND

Current dietary guidelines recommend eating a variety of fruits and vegetables. However, based on nutrient composition, some particular fruits and vegetables may be more or less beneficial for maintaining or achieving a healthy weight. We hypothesized that greater consumption of fruits and vegetables with a higher fiber content or lower glycemic load would be more strongly associated with a healthy weight.

METHODS AND FINDINGS

We examined the association between change in intake of specific fruits and vegetables and change in weight in three large, prospective cohorts of 133,468 United States men and women. From 1986 to 2010, these associations were examined within multiple 4-y time intervals, adjusting for simultaneous changes in other lifestyle factors, including other aspects of diet, smoking status, and physical activity. Results were combined using a random effects meta-analysis. Increased intake of fruits was inversely associated with 4-y weight change: total fruits -0.53 lb per daily serving (95% CI -0.61, -0.44), berries -1.11 lb (95% CI -1.45, -0.78), and apples/pears -1.24 lb (95% CI -1.62, -0.86). Increased intake of several vegetables was also inversely associated with weight change: total vegetables -0.25 lb per daily serving (95% CI -0.35, -0.14), tofu/soy -2.47 lb (95% CI, -3.09 to -1.85 lb) and cauliflower -1.37 lb (95% CI -2.27, -0.47). On the other hand, increased intake of starchy vegetables, including corn, peas, and potatoes, was associated with weight gain. Vegetables having both higher fiber and lower glycemic load were more strongly inversely associated with weight change compared with lower-fiber, higher-glycemic-load vegetables (p < 0.0001). Despite the measurement of key confounders in our analyses, the potential for residual confounding cannot be ruled out, and although our food frequency questionnaire specified portion size, the assessment of diet using any method will have measurement error.

CONCLUSIONS

Increased consumption of fruits and non-starchy vegetables is inversely associated with weight change, with important differences by type suggesting that other characteristics of these foods influence the magnitude of their association with weight change.

Changes in intake of protein foods, carbohydrate amount and quality, and long-term weight change: results from 3 prospective cohorts

BACKGROUND

Dietary guidelines recommend interchanging protein foods (e.g., chicken for red meat), but they may be exchanged for carbohydrate-rich foods varying in quality [glycemic load (GL)]. Whether such exchanges occur and how they influence long-term weight gain are not established.

OBJECTIVE

Our objective was to determine how changes in intake of protein foods, GL, and their interrelationship influence long-term weight gain.

DESIGN

We investigated the association between 4-y changes in consumption of protein foods, GL, and their interaction with 4-y weight change over a 16- to 24-y follow-up, adjusted for other lifestyle changes (smoking, physical activity, television watching, sleep duration), body mass index, and all dietary factors simultaneously in 3 prospective US cohorts (Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-Up Study) comprising 120,784 men and women free of chronic disease or obesity at baseline.

RESULTS

Protein foods were not interchanged with each other (intercorrelations typically <|0.05|) but with carbohydrate (negative correlation as low as -0.39). Protein foods had different relations with long-term weight gain, with positive associations for meats, chicken with skin, and regular cheese (per increased serving/d, 0.13-1.17 kg; P = 0.02 to P < 0.001); no association for milk, legumes, peanuts, or eggs (P > 0.40 for each); and relative weight loss for yogurt, peanut butter, walnuts, other nuts, chicken without skin, low-fat cheese, and seafood (-0.14 to -0.71 kg; P = 0.01 to P < 0.001). Increases in GL were independently associated with a 0.42-kg greater weight gain per 50-unit increase (P < 0.001). Significant interactions (P-interaction < 0.05) between changes in protein foods and GL were identified; for example, increased cheese intake was associated with weight gain when GL increased, with weight stability when GL did not change, and with weight loss when exchanged for GL (i.e., decrease in GL).

CONCLUSION

Protein foods were commonly interchanged with carbohydrate, and changes in protein foods and GL interacted to influence long-term weight gain.

Multi-component molecular-level body composition reference methods: evolving concepts and future directions

Excess adiposity is the main phenotypic feature that defines human obesity and that plays a pathophysiological role in most chronic diseases. Measuring the amount of fat mass present is thus a central aspect of studying obesity at the individual and population levels. Nevertheless, a consensus is lacking among investigators on a single accepted 'reference' approach for quantifying fat mass in vivo. While the research community generally relies on the multi-component body volume class of 'reference' models for quantifying fat mass, no definable guide discerns among different applied equations for partitioning the four (fat, water, protein and mineral mass) or more quantified components, standardizes 'adjustment' or measurement system approaches for model-required labelled water dilution volumes and bone mineral mass estimates, or firmly establishes the body temperature at which model physical properties are assumed. The resulting differing reference strategies for quantifying body composition in vivo leads to small, but under some circumstances, important differences in the amount of measured body fat. Recent technological advances highlight opportunities to expand model applications to new subject groups and measured components such as total body protein. The current report reviews the historical evolution of multi-component body volume-based methods in the context of prevailing uncertainties and future potential.

Effects of sodium benzoate, a widely used food preservative, on glucose homeostasis and metabolic profiles in humans

Sodium benzoate is a widely used preservative found in many foods and soft drinks. It is metabolized within mitochondria to produce hippurate, which is then cleared by the kidneys. We previously reported that ingestion of sodium benzoate at the generally regarded as safe (GRAS) dose leads to a robust excursion in the plasma hippurate level [1]. Since previous reports demonstrated adverse effects of benzoate and hippurate on glucose homeostasis in cells and in animal models, we hypothesized that benzoate might represent a widespread and underappreciated diabetogenic dietary exposure in humans. Here, we evaluated whether acute exposure to GRAS levels of sodium benzoate alters insulin and glucose homeostasis through a randomized, controlled, cross-over study of 14 overweight subjects. Serial blood samples were collected following an oral glucose challenge, in the presence or absence of sodium benzoate. Outcome measurements included glucose, insulin, glucagon, as well as temporal mass spectrometry-based metabolic profiles. We did not find a statistically significant effect of an acute oral exposure to sodium benzoate on glucose homeostasis. Of the 146 metabolites targeted, four changed significantly in response to benzoate, including the expected rise in benzoate and hippurate. In addition, anthranilic acid, a tryptophan metabolite, exhibited a robust rise, while acetylglycine dropped. Although our study shows that GRAS doses of benzoate do not have an acute, adverse effect on glucose homeostasis, future studies will be necessary to explore the metabolic impact of chronic benzoate exposure.