Elsevier

Contemporary Clinical Trials

Volume 65, February 2018, Pages 76-86
Contemporary Clinical Trials

A randomized study of dietary composition during weight-loss maintenance: Rationale, study design, intervention, and assessment

https://doi.org/10.1016/j.cct.2017.12.004Get rights and content

Abstract

Background

While many people with overweight or obesity can lose weight temporarily, most have difficulty maintaining weight loss over the long term. Studies of dietary composition typically focus on weight loss, rather than weight-loss maintenance, and rely on nutrition education and dietary counseling, rather than controlled feeding protocols. Variation in initial weight loss and insufficient differentiation among treatments confound interpretation of results and compromise conclusions regarding the weight-independent effects of dietary composition. The aim of the present study was to evaluate three test diets differing in carbohydrate-to-fat ratio during weight-loss maintenance.

Design and dietary interventions

Following weight loss corresponding to 12 ± 2% of baseline body weight on a standard run-in diet, 164 participants aged 18 to 65 years were randomly assigned to one of three test diets for weight-loss maintenance through 20 weeks (test phase). We fed them high-carbohydrate (60% of energy from carbohydrate, 20% fat), moderate-carbohydrate (40% carbohydrate, 40% fat), and low-carbohydrate (20% carbohydrate, 60% fat) diets, controlled for protein content (20% of energy). During a 2-week ad libitum feeding phase following the test phase, we assessed the effect of the test diets on body weight.

Outcomes

The primary outcome was total energy expenditure, assessed by doubly-labeled water methodology. Secondary outcomes included resting energy expenditure and physical activity, chronic disease risk factors, and variables to inform an understanding of physiological mechanisms by which dietary carbohydrate-to-fat ratio might influence metabolism. Weight change during the ad libitum feeding phase was conceptualized as a proxy measure of hunger.

Introduction

In the US, about 50% of adults with overweight or obesity are trying to lose weight, often by following energy-restricted diets [1]. While many experience some initial success, most have difficulty maintaining clinically significant weight loss over the long term [2], [3]. A common explanation for weight regain relates to behavior, in that motivation to adhere to a dietary prescription typically diminishes with time. Indeed, behavioral intervention trials indicate a direct association between adherence and weight loss, regardless of dietary treatment [4], [5], [6]. An alternative explanation relates to biology, in that weight loss elicits adaptations that promote weight regain, including a decline in energy expenditure and an increase in hunger [7], [8]. Whether macronutrient composition influences these adaptations remains a subject of debate [9], [10].

For most of the last half century, dietary fat restriction was the primary focus of clinical practice guidelines and public health recommendations for weight loss and chronic disease risk management. Alternative strategies that focus on modifying carbohydrate amount and paying attention to carbohydrate source (choosing foods with a low glycemic index) have gained attention over the last two decades [11], [12]. Lowering dietary glycemic load [13], [14], [15] using these strategies may produce beneficial effects on metabolism and hunger compared to conventional low-fat (high-carbohydrate) diets. Acutely, beneficial effects may include hormonal changes that increase availability of metabolic fuels in the late postprandial period (attenuated insulin levels, for example), and thereby decrease hunger and voluntary food intake [16], [17]. Chronically, lowering glycemic load appears to lessen the fall in resting and total energy expenditure (TEE) that predictably occurs during weight loss [18], [19], [20], although the mechanisms for this effect remain speculative. While some nutrition experts advocate decreasing carbohydrate to reduce dietary glycemic load [21], others contend that substantial benefit can be achieved with a moderate decrease in carbohydrate intake so long as the carbohydrate source has a low glycemic index [22]. Still others argue that clinical care for patients with obesity and general public health messages should remain focused on lowering energy intake, pointing out that fat is an easily over-consumed and energy-dense macronutrient [23].

The primary aim of this study was to evaluate the effect of three diets varying widely in carbohydrate-to-fat ratio (high-carbohydrate, moderate-carbohydrate, low-carbohydrate) on energy expenditure during weight-loss maintenance, using a controlled feeding protocol. The primary outcome was TEE, assessed by doubly-labeled water methodology. Outcomes for additional specific aims are presented in Section 5 of this protocol paper.

Section snippets

Study design and infrastructure

The study was a randomized controlled trial (RCT) comprising run-in, test, and ad libitum feeding phases (Fig. 1). The purpose of the run-in phase was to obtain baseline measurements and restrict energy intake to achieve a 12 ± 2% decrease in body weight. Participants who were unable to achieve this level of weight loss were dismissed from the study prior to randomization. The purpose of the test phase was to compare the metabolic effects of high-, moderate-, and low- (HI-, MOD-, and LO-)

Eligibility criteria

We enrolled faculty, staff, students, and residents of communities surrounding FSU and AV who met the eligibility criteria listed in Table 1. We specified BMI  25 kg/m2, which corresponds to the conventional definition of overweight, as an inclusion criterion but did not enroll anybody who weighed > 350 lbs. (159 kg), to avoid exceeding upper weight limits for some assessment equipment. We excluded anyone who reported recent and substantial weight change or behaviors that could confound study

Dietary interventions

Targets for energy content and macronutrient composition of the run-in and test diets are summarized in Table 2. For all diets, energy was distributed throughout the day: 22.5% for breakfast, 32.5% for lunch, 32.5% for dinner, and 12.5% for an evening snack. The macronutrient composition of every meal and snack reflected the composition of each respective diet. We instructed participants to consume their meals at regularly scheduled times and not to skip meals. We advised participants to have

Study outcomes

Table 4 provides an overview of measurements, including the time point at which we assessed each outcome. We assessed outcomes under free-living conditions and during visits to a research center at FSU. Blood samples were collected following a 12-hour overnight fast, except where indicated otherwise. Biospecimens were frozen in a − 80°C freezer at FSU and then transferred to the Biobank Core Laboratory at BCH. Biochemical analyses, except where indicted otherwise, were done in the Clinical and

Covariates

Covariates or effect modifiers are listed in Table 4. Methods for assessing body weight, body composition, and insulin sensitivity and secretion are described above. We collected demographic data (sex, ethnicity, race, age) by self-report. We isolated and saved buffy coat from blood samples for extracting DNA from participants who “opted in” for genetic studies. These studies may include, but will not be limited to, candidate gene analysis and whole genome/exome sequencing. We have particular

Ancillary studies

The parent study, which is the focus of this protocol paper, provided an opportunity for data collection pertaining to several ancillary studies. These studies were led by faculty and trainees from HMS or FSU. Outcomes pertaining to lipoprotein particle subfraction distribution, sleep, psychological health, cognition, and weight bias are listed in the ClinicalTrials.gov registry for the parent study (NCT02068885). Two of the ancillary studies required substantial resources and effort, in terms

Analysis plan

We will follow an a priori analysis plan. The primary outcome measure will be TEE per kg body weight, measured at four time points: pre-weight loss (BSL), week 0 (PWL, pre-randomizaiton), week 10 (MID), and week 20 (END). According to the primary null hypothesis, the time course of TEE between week 0, week 10, and week 20 will be the same for all three diets.

The analytic framework for addressing both primary and secondary hypotheses will be repeated-measures analysis of variance (ANOVA), with

Discussion

Preventing weight regain following weight loss is a critical public health issue. Most randomized controlled trials of different macronutrient diets have focused on the period of active weight loss [4], [5], [6]. This protocol paper describes a novel study in which we compared diets during an extended period of weight-loss maintenance, directing attention to the potential effect of macronutrient composition on metabolic adaptations that may influence propensity for weight regain. We implemented

Acknowledgements

This work was conducted with grants from the Nutrition Science Initiative, New Balance Foundation, Many Voices Foundation, and Blue Cross Blue Shield. DSL was supported by a mid-career mentoring award from the National Institute of Diabetes and Digestive and Kidney Diseases (K24DK082730). The funding organizations played no role in the design and conduct of the study; preparation of the manuscript; and decision to submit the manuscript for publication. The content is solely the responsibility

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