The study objective was to conduct a pilot study continuing the research on the potential mediating effects of insulin resistance status on weight loss responses to LF vs. LC diets. Particular emphasis was placed on maximizing the fat vs. carbohydrate differentials on the two diets and on overall nutritional quality.

Several weight loss diet studies have examined whether differences in glucose and insulin dynamics (e.g., differential insulin secretion or insulin resistance status) are a mediating factor for successful weight loss on LF vs. LC diets ( 8 - 12 ). These studies have consistently observed that overweight adults with higher insulin secretion or insulin resistance lose more weight on LC than LF diets. In contrast, lower insulin secretion or the more insulin sensitive (IS) individuals in these trials had more or comparable success with an LF diet. McClain et al. ( 10 ) observed that participants with higher baseline fasting insulin concentrations had lower adherence than participants with lower fasting insulin concentrations when assigned LF, even when unaware of their baseline fasting insulin status. Several proposed mechanisms support the plausibility of greater weight loss on an LC diet among IR individuals, including increased fatty acid uptake, inhibition of lipolysis, and effects on hunger, snacking, and energy intake ( 12 - 18 ).

Obesity is related to increased risk of heart disease, stroke, type 2 diabetes, and some cancers ( 1 ). Individuals with moderate obesity with insulin resistance have a greater metabolic risk profile for these chronic diseases than those with greater insulin sensitivity, even at the same weight ( 2 ). Weight loss improves insulin sensitivity and lowers cardiovascular risk ( 3 ). However, most people find successful weight loss challenging. The weight loss diet traditionally recommended by health professionals has been a low‐fat (LF), calorie‐restricted diet ( 4 ), which may be particularly inappropriate for insulin resistant (IR) individuals, and has been challenged by proponents of alternative dietary strategies, particularly low‐carbohydrate (LC) ( 5 - 7 ).

We also explored longitudinal differences between risk factors across the four diet × IR‐IS groups (e.g., LF‐IR, LC‐IR, LF‐IS, and LC‐IS). For each risk factor, a mixed effect model was fit with the corresponding risk factor as the outcome and group, time point and group time point interaction as predictors. Models were either linear or logistic, depending on the nature of the risk factor. For risk factors with significant interaction term P ‐values, additional pairwise comparisons among the four groups were made using Tukey's HSD test. All statistical tests were two‐tailed using a significance level of 0.05.

For the main analysis, data were multiply imputed with the MICE package in R 3.0 using five imputation steps and five imputed data sets. Each imputed data set was fit to a linear regression model using change in weight at 6 months as the outcome and with subject height, diet, insulin resistance‐insulin sensitivity (IR‐IS) status, and an interaction term between diet and IR‐IS status as predictors. Resulting variance estimates were pooled to account for the additional variability induced by the imputation process. In a sensitivity analysis, we repeated these models after replacing the dichotomous IR‐IS status with continuous baseline insulin AUC. Other exploratory analyses included the use of INS‐30, INS‐120, and Glu‐AUC 0‐30 × Ins‐AUC 0‐30. We also fit models where, instead of adjusting for baseline height, we adjusted for baseline BMI.

The primary objective was to test whether there was a significant interaction in weight loss on LF vs. LC diets by insulin resistance status as estimated by AUC‐INS. Dietary composition data (energy, % carbohydrate, fat, and protein, and grams of fiber, added sugars, and saturated fat) are presented as raw, unadjusted mean (±SD) (i.e., no imputation for missing data).

Blood samples were collected after ≥10 h fast. Plasma total cholesterol and triglycerides (free glycerol blank subtracted) were measured enzymatically using established clinical chemistry laboratory methods (Northwest Lipid Laboratory, Seattle, WA) ( 20 , 21 ). High‐density lipoprotein cholesterol (HDL‐C) was measured by liquid selective detergent followed by enzymatic determination of cholesterol ( 22 ). Low‐density lipoprotein cholesterol (LDL‐C) was calculated according to Friedewald et al. ( 23 ). Total plasma insulin in serum was measured by radioimmunoassay ( 24 ), and blood glucose was measured using a modification of the glucose oxidase/peroxidase method ( 25 , 26 ) (Diabetes Research Center, Washington University, St Louis, MO). Resting blood pressure was assessed three times at 2‐min intervals as described elsewhere ( 27 ); the initial reading was discarded, and the last two readings were averaged.

All participants were encouraged to be physically active. Participants who were already physically active at baseline were encouraged to maintain or increase their activity. Those who were sedentary at baseline were encouraged to begin moderate exercise. All participants were given pedometers (Omron HJ‐112 Digital Pocket Pedometer).

Notably, there were no calorie restriction targets in the intervention. Participants were encouraged to track their intake using daily food journals and computer tracking programs. Although the first 8 weeks of classes focused specifically on separate strategies to lower fat or carbohydrate intake, the subsequent 4 months of classes addressed more global topics for both diet groups, similarly, such as mindful eating, adequate sleep, body acceptance, and sugar addiction.

There were four central components to the dietary strategy. The first was “how low can you go” (Limbo). LF participants were instructed to cut back to 20 g/day of total fat, and for LC to 20 g/day of digestible carbohydrate. The goal was to achieve the lowest level of fat or carbohydrate intake within the first 8 weeks. The second stage (Titrate) was to slowly add fat or carbohydrate back to the diet in increments of 5 g/day (e.g., from 20 to 25 g/day) and then hold it at that amount for 1‐4 weeks before adding another 5 g/day. The third component was to identify the lowest level of fat or carbohydrate intake participants felt could be maintained long term, potentially for the rest of their lives. The fourth strategy was to promote high nutrient density (Quality). Other Quality concepts included “real food,” “minimally processed,” “seasonal,” “organic,” “grass‐fed,” “whole grain,” and “pasture‐raised,” depending on diet assignment. Both diet groups received similar instructions to drink water, maximize vegetable intake, and to minimize added sugars, refined white flour products, and sources of trans fats. Participants on the LC diet were asked to consume half an avocado each day (approximately 160 kcal), as well choosing other sources of plant‐based fats, including olive oil, nuts and seeds, and nut butters. Hass avocados were provided by the Hass Avocado board and were distributed to the participants. All participants were encouraged to take an active role in making food choices; by preparing their own foods at home, reading labels, and asking for appropriate modifications for restaurant menu items.

The intervention was a class‐based education program led by a single health educator (RC). Participants were assigned to groups of 14‐16 per class to follow either an LF or an LC diet. There were 14 one‐hour classes over 6 months; once every week for 8 weeks, then once every other week for 8 weeks, and then once every month for 8 weeks.

The study employed a 2 × 2 design: LF vs. LC diets and more IR vs. more IS. We suggest the terms “insulin resistance” and “insulin sensitivity” here be interpreted cautiously as we used a proxy measure for this, rather than a direct measure (expanded discussion in Section 1 of Supporting Information). The method of determining relative insulin resistance was to calculate an area under the curve of insulin concentrations (AUC‐INS) from four blood samples taken during an oral glucose tolerance test (OGTT) (time 0, 30, 60, and 120 min) conducted prior to randomization. Median AUC‐INS was determined separately for women and men. Those above the median were considered to be relatively more IR, and those below were considered relatively more IS.

Participants were recruited from the local community primarily through media advertisements. Premenopausal women and men aged 18‐50 years were invited to enroll if BMI was 28‐40 kg/m 2 , body weight was stable over the previous 2 months, and medications were stable for ≥3 months. Potential participants were excluded if they self‐reported: hypertension (except for those stable on antihypertension medications), type 1 or 2 diabetes mellitus, heart, renal, or liver disease, cancer or active neoplasms, hyperthyroidism unless treated and under control, taking any medications known to affect weight/energy expenditure or blood lipids, smoking, alcohol intake ≥ 3 drinks/day, pregnancy, lactation, no menstruation for the previous 12 months, or plans to become pregnant within the next year. Race/ethnicity data were collected by self‐report. All study participants provided written informed consent. The study was approved by the Stanford University Human Subjects Committee.

Six‐month changes in LDL‐C concentrations were statistically different among groups, with decreases for LF and increases for LC, regardless of IR‐IS status. Fasting insulin concentrations dropped significantly more for the two IR groups than the two IS groups, although by definition the IR groups had higher baseline insulin levels and thus greater capacity for improvement. Overall average fasting insulin concentrations decreased for all four groups. This same pattern was observed for INS‐AUC.

With few exceptions, risk factors changed in a beneficial way across all groups (Table 3 ). Triglyceride concentrations dropped by ∼25% across the four groups combined. Both diastolic and systolic blood pressure decreased for all four groups. HDL‐C concentrations increased by almost 10% in three of the four groups, with a negligible overall change in the LF‐IS group. Fasting glucose decreased modestly, on average, in three of the four groups, with a negligible 6‐month change in the LC‐IS group. At baseline 40% of participants met metabolic syndrome criteria, which was down to 15% overall at 6 months. No significant 6‐month change differences were detected among groups for any of the above risk factors.

Average weight loss after 6 months for the n = 49 that completed the protocol was 9.0 ± 6.5 kg (19.8 ± 14.3 lbs), which represented 8.9 ± 5.7% of baseline weight. The 6‐month weight loss results by diet type and IR‐IS status group were 7.5 ± 6.0 kg for LF‐IR, 10.4 ± 7.8 kg for LF‐IS, 9.6 ± 6.6 kg for LC‐IR, and 8.6 ± 5.6 kg for LC‐IS (Figure 3 ). A significant interaction between diet assignment and IR‐IS status was not detected, and there were no significant main effect differences in weight loss detected by diet group or by IR‐IS status. We found no meaningful differences in estimate direction or significance between the models where baseline height was a confounder and models where baseline BMI was a confounder or when using INS‐30, INS‐120, or Glu‐AUC 0‐30 × Ins‐AUC 0‐30 in the models.

Energy expenditure increased modestly and similarly for both diet groups. Baseline energy expenditure for the LF group was 33.7 ± 1.4 kcal/kg/day, which increased at 3 and 6 months to 34.2 ± 1.6 and 34.6 ± 2.6 kcal/kg/day, respectively. In parallel, baseline energy expenditure for the LC group was 32.7 ± 0.9 kcal/kg/day, which increased at 3 and 6 months to 33.5 ± 1.3 and 33.8 ± 1.9 kcal/kg/day, respectively.

On average, the LF group decreased absolute amounts (grams) of added sugar intake by ∼50% and saturated fat by ∼66% while increasing fiber intake by ∼25% relative to baseline; the LC group decreased added sugar intake by ∼70%, fiber by ∼40%, and increased saturated fat by ∼10% (Table 2 ). These were changes of absolute intake amounts in the context of a general ∼30% reduction of overall energy intake.

Participants in both LF and LC made substantial dietary changes as assessed at 3‐ and 6‐months, relative to baseline (Figure 2 ). With average baseline energy intake percentages of 44:38:18 from carbohydrate:fat:protein, the two diet groups shifted to an average ratio of approximately 58:22 carbohydrate:fat for LF, and 21:53 for LC (average at 6 months), with protein being relatively similar, particularly at 6 months. Between the 3‐ and 6‐month time points, there was modest recidivism in the LC group whereas macronutrient ratios were more stable for LF during this phase. Average energy intake from alcohol ranged from 1% to 4% of energy in the four LF and LC classes (energy intake from alcohol excluded from Figure 2 data). Reported energy intake suggested an average ∼600 kcal/day decrease at 3 and 6 months relative to baseline (∼30% energy). An expanded presentation of macronutrient distribution for all four subgroups at all three time points is available in the Supporting Information Section 2 and Supporting Information Table S1.

Participants were enrolled from February to April, 2012. Sixty‐one eligible participants were randomized into four groups—two classes of LF and two classes of LC, with approximately 50% IR and 50% IS in each class (Figure 1 ). Baseline characteristics are presented in Table 1 . By design, INS‐AUC (and the highly correlated fasting insulin) was higher for IR vs. IS. As expected, BMI was higher among the more IR vs. IS participants, with a trend for higher triglycerides and blood pressure, lower HDL‐C, and a higher percentage of metabolic syndrome in the IR group.

Discussion

In this pilot study, we investigated whether there was a differential weight loss response to LF vs. LC diets by baseline IR‐IS status, using INS‐AUC as a proxy measure, among nondiabetic overweight adults and adults with obesity who were otherwise in general good health. Overall, participants experienced substantial weight loss: an average of 9.0 ± 6.5 kg, which represented 8.9 ± 5.7% of baseline weight. However, a significant interaction between diet assignment and IR‐IS status was not detected for weight loss. Dietary assessment indicated substantial diet differentiation between the LF and LC groups, which was supported by observed changes in secondary metabolic outcomes, including fasting insulin, LDL‐C, HDL‐C, and triglycerides. In addition, the dietary assessment data indicate that the substantial dietary changes achieved by mid‐study were largely maintained to the end of the study at 6 months.

Several other studies have reported a statistically significant interaction in weight loss between diet type and IR‐IS status, including a previous investigation by our own research group (8-10, 12). Two of the studies were feeding studies, of 4‐6 month duration with small sample sizes of four to eight per treatment arm (8, 12). These studies, perhaps because of the more rigorous control of diet, and the 30% restriction of energy intake, achieved greater weight loss overall than the two free‐living studies which used an ad libitum approach (9, 10). However, the free‐living studies had larger sample sizes and longer durations than the feeding studies. Notably, the four previous studies used three different methods to assess insulin and glucose dynamics. Compared with this set of four previous studies, in this free‐living study, the magnitude of overall weight loss was comparable to the feeding studies and substantially higher than the other two free‐living studies while using an ad libitum approach to energy intake. The INS‐AUC method used in this study to differentiate greater IR from greater IS individuals was different than all of the other studies, and was more a measure of hyperinsulinemia than a direct measure of insulin resistance. In absolute numbers, the average weight loss results in this study paralleled the findings from the other studies—the more IR group lost slightly more weight on LC, and the IS group lost slightly more weight on LF, but the differences were not statistically or clinically significant. With so many differences among the previous four studies and this study, which all address the same general research question, we are not able to determine whether we failed to detect a true effect that the other studies correctly identified, or if we truly and accurately identified no effect in our study population using the design described.

There are multiple mechanisms that could be responsible for a potential differential weight loss response to LF vs. LC diets by variability in insulin and glucose dynamics, including differential hunger/satiety, energy expenditure, fatty‐acid metabolism, lipolysis, and adipogenesis. Several groups of investigators have observed one or more factors along a continuum that suggest LF relative to LC diets cause greater excursions in postprandial glucose and insulin metabolism, may increase 24‐h hunger, and may subsequently increase overall energy intake due to their higher glycemic load (11, 28-31). Related research suggests that diets with a higher glycemic index can affect hormones regulating metabolism (13-15). Under these conditions, IR individuals may feel less satiated and experience stronger physiologically driven urges to consume more food after consuming a lower fat/higher carbohydrate meal compared with IS individuals.

In separate experiments with humans, one a parallel design and another a cross‐over, the lab group of Ludwig and coworkers found that substantial weight loss achieved by or followed by isocaloric diets differing in glycemic load led to differential changes in resting energy expenditure and total energy expenditure; the observed results favored greater energy expenditure on the lower glycemic load/lower carbohydrate diets (17, 32). Although IR‐IS status was not addressed as a potential covariate in these analyses, it is plausible that the more IR individuals who were on higher glycemic load/higher carbohydrate diets would experience an even greater decrease in energy expenditure than the more IS individuals on the same diet, making it more difficult to achieve or maintain weight loss.

Further discussion of the observed changes and lack of changes in some of the risk factors in Table 3 is presented in the Supporting Information Section 3.

The study design and conduct included several important strengths. One was the high degree of dietary differentiation achieved for those assigned to LF vs. LC. In many weight loss diet studies, the combination of modest dietary goals and substantial recidivism over time (i.e., weak treatment fidelity) can lead to a lack of physiologically meaningful dietary differences between treatment arms. The differences in proportions of energy intake from fat vs. carbohydrate achieved and maintained out to 6 months in the two diet groups of this study involved a substantial shift of approximately 25% of energy intake. The use of three unannounced 24‐h recalls and NDS‐R for dietary assessment at three time points, and the high rate of completion of these assessments was an important methodological strength. Other strengths included the relatively high retention rate of 80% and the identical drop‐out rates in both diets. Stratifying the randomization by IR‐IS status was an important design component, and the use of INS‐AUC from OGTTs to identify and differentiate participants who were more IR vs. more IS was superior to fasting measures that could have been used (e.g., fasting insulin or TG/HDL‐C ratio).

The major limitations of this pilot study were the duration and sample size. Given a consistent pattern of maximal weight loss at 6 months followed by weight stabilization and often regain across a range of published studies, it is more optimal to include follow‐ups of a year or more in weight loss studies. Also, given the substantial heterogeneity of intergroup weight loss typical of these types of trials, large sample sizes are a preferred design component; the null finding for an interaction between IR‐IS status and diet assignment for weight loss difference in this study may have been attributable to a lack of adequate statistical power. However, a primary objective of this pilot study was to test the approach undertaken to achieve greater differentiation of diets and treatment fidelity for the purpose of incorporating this approach in a future, larger, longer trial; that follow‐up trial, with a sample size of 600 and duration of 1 year is currently underway. An expanded discussion of study limitations is presented in the Supporting Information Section 4. Despite the limitations of the pilot study, we believe the high degree of apparent treatment diet differentiation, the relatively high average weight loss across both treatment arms, and the interesting findings of risk factor changes at 3 and 6 months are results worthy of dissemination.

In conclusion, our pilot study achieved substantial differentiation of LF vs. LC study diets in a free‐living population that led to an average weight loss of 9% body weight over 6 months in overweight adults and adults with obesity. Our findings did not detect differential effects by diet, by IR‐IS status, or the interaction of these conditions. Further research on a larger study population for a longer period of time is warranted using the novel dietary intervention approach developed here.