Our hypothesis was that moderate carbohydrate restriction may be easier to maintain, and thus more effective than greater degrees of carbohydrate restriction. The aim of the present study therefore, is to compare anthropometric and cardiometabolic outcomes between a VLCKD, LCD, and moderate-low carbohydrate diet (MCD), containing 5%, 15%, and 25% TE from carbohydrate, respectively, in healthy adults.

Few studies directly compare very LCDs with less extreme carbohydrate-restricted diets. Johnstone and colleagues compared the effects of a non-ketogenic LCD (fat 30% of total energy (TE); carbohydrate 40% of TE) to a ketogenic, LCD (fat 60% TE; carbohydrate 5%TE) in 20 adults over 6 weeks, finding that the diets were equally effective in reducing body weight and insulin resistance ( Johnston et al., 2006 ).

Effects of the dietary interventions on outcomes were determined for each participant by calculating the change in the various measures from baseline. The significance of these within-group changes from baseline was determined by a paired t -test. All between-group variations were compared using ANOVA. A 5% two-sided alpha level was used to determine significance. Further comparisons were made by undertaking multiple linear regression with adjustment made for variables recorded at baseline. A sensitivity analysis of the results was carried out using stabilised inverse-probability of completing weights for the BMI change outcome to check whether these results were likely to have been different had the whole group returned for followed-up.

Following an overnight fast, blood samples were obtained from participants, before the first meal, via venipuncture by a certified phlebotomist from an antecubital vein and collected into plasma separation tubes (PST) Vacutainer tubes using lithium-heparin as the anticoagulant (Becton Dickinson, Franklin Lakes, NJ, USA). Within 15 min of collection, tubes were centrifuged at 1,500× g revolutions per minute for 10 min at +4 °C, and plasma samples were transferred into clean polypropylene tubes and frozen at −80 °C until analyses were conducted using specific diagnostics assays on a Roche Modular analyser (P800 and E170). Blood samples were analysed for total cholesterol (Total-c), LDL-c, HDL-c, triglycerides (TG), C-reactive protein (CRP), gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase, alkaline phosphatase (ALP), glucose and uric acid on the P800 module. Insulin, and C-peptide concentrations were measured on the E170 module. All analytical biomarkers were measured at baseline and immediately following the 12-week intervention. The total duration of the assay for each analyte was less than 20 min based on the electrochemiluminescence principle (ruthenium-conjugated monoclonal antibodies) for the E170 module and specific enzyme assay methods for the P800 module. Quantitative results were determined via instrument-specific full point calibration curves and validated with specific controls. Additional information for analytes, lower limits of measurement, measuring range, and test principle can be found in Appendix 1.

The following measures were taken: height, weight, waist circumference at the narrowest point between the lowest rib and the iliac crest, and hip circumference at the widest point of the hips and buttocks. These measures were then used to derive BMI, waist-hip ratio, and the waist-height ratio at baseline and during follow-up.

Diet plans, which included macronutrient and calorie allocation and a sample menu plan, were individualised to the participant, with energy intake determined by the mean reported energy consumed per day in the lead-in dietary recording week. Advice was given to limit protein intake to 1.4 g/kg/day (weight at baseline testing), consistent with International Society of Sports Nutrition guidelines for optimal protein intake for performance ( Campbell et al., 2007 ). This was chosen as an appropriate protein intake that was not likely to unduly influence the study results, because the study participants were healthy people, who may also be engaged in physical activity and sports. Participants were advised to adhere as strictly as possible to the energy and macronutrient prescription for the first 3 weeks of the intervention. For the final 9 weeks of the intervention, they were advised to eat ad libitum but to adhere as closely as possible to the carbohydrate energy limit for their treatment group as a percentage of their TE intake. Usual exercise patterns were continued. Dietary intake was recorded by participants in a mobile application (Fat Secret) with the researchers able to obtain real time entry on a partner mobile application (Fat Secret Pro). Results were monitored for safety and compliance by the primary researcher and research assistants tasked with data-monitoring. Compliance to the dietary allocation was monitored daily by a data monitoring team. Where non-compliance to the dietary allocation, especially for carbohydrate, was noticed, the participant was notified and offered support and advice.

Participants completed baseline testing of blood and basic anthropometric measures and a lead-in dietary recording week to identify habitual calorie intake. Participants were randomised by the study statistician to one of three LCD plans which advised intakes of either 5%, 15%, or 25% of TE from carbohydrate. The randomisation was stratified by gender, using a pre-prepared sequence, with investigators blinded to treatment allocation at baseline and follow-up. Participants were assigned to the next treatment group according to their order of recruitment. The primary researcher responsible for initial statistical analysis was blinded to the treatment group allocation until this analysis had been completed.

The trial was registered by the Australia New Zealand Clinical Trial Registry. (ACTRN12617000421336p). Ethics approval for this study was granted by the Southern Committee of the Health and Disability Ethics Committee of New Zealand. 17/STH/60.

Participants were required to be healthy and between the ages of 25 and 49 years. Exclusion criteria were; underweight (<18.5 BMI kg/m 2 ), diagnosed with diabetes, diagnosed with any serious medical condition, having previously following a ketogenic diet, or being a current or former client of any of the researchers in clinical practice.

A total of 77 participants, 25 males, 52 females (mean age: 39 years, range: 25–49; mean body mass index (BMI) 27 kg/m 2 , range: 20–39) were recruited between the 7th and 19th of August 2017 and gave written, informed consent to participate in this 12-week, randomised, clinical intervention study. The study took place between 11th September and 10th December 2017. Collection of data and analysis was performed at AUT’s Human Potential Centre, Auckland, New Zealand.

Results

A total of 283 people were assessed for eligibility with 206 excluded and 77 included for randomisation to the trial groups (Fig. 2). A total of 10 participants withdrew after they were randomised. Two failed to comply with guidelines to submit baseline data and withdrew from the study (one male, one female), and three females withdrew due to changes in personal circumstances, including two who became pregnant. A further five withdrew due to challenges arising from following the diets. The reasons for withdrawals were as follows: two female participants found the dietary allocation of carbohydrate too difficult to sustain (one each in the 5% and 15% allocation groups); one did not want to continue tracking with the food app; one felt that she could not maintain her sports performance on 15% TE from carbohydrate; and one female in the 5% allocation group reported amenorrhea and reductions in strength and power, despite improved mental clarity. A further 28 did not book for or failed to present for post-intervention measurements. This left 39 participants with follow-up results available for analysis.

Figure 2: Participants included for participation, randomisation, allocation, and lost to follow up.

There were no significant differences in baseline characteristics between completers and non-completers and no meaningful difference in the number of non-completers by group with 50%, 50%, and 48% of participants not completing post-intervention measures in the MCD, LCD, and VLCKD groups respectively. Mean baseline levels of TG were, however, 36% higher at baseline in those lost to follow-up compared to those who were not, even though the difference between the two distributions was not significant (p = 0.08). There was also no significant variation for age, gender, or ethnicity between the groups, in the participants analysed. At baseline, blood measures were all within reference ranges except for Total-c which had an overall mean of 5.31 mmol/L (SD = 1.29) for completers, and a significant between-group difference (p = 0.005).

Baseline characteristics of those included for analysis are presented in Table 1, by randomised treatment group.

Treatment group Total Test p-value MCD LCD VLCKD 12 13 14 39 Age mean (SD) 39.1 (6.6) 38.9 (8.3) 38.7 (7.1) 38.9 (7.1) ANOVA 0.992 Gender (%) Fisher’s 0.198 Female 10 (83.3) 6 (46.2) 9 (64.3) 25 (64.1) Male 2 (16.67) 7 (53.85) 5 (35.71) 14 (35.9) Ethnicity (%) Fisher’s 0.733 Asian 1 (8.3) 0 (0.0) 1 (7.1) 2 (5.1) European 8 (66.7) 11 (84.6) 10 (71.4) 29 (74.4) Maori 2 (16.7) 1 (7.7) 3 (21.4) 6 (15.4) Other ethnicity 1 (8.3) 0 (0.0) 0 (0.0) 1 (2.6) Pacific peoples 0 (0.0) 1 (7.7) 0 (0.0) 1 (2.6) Total energy (Kcal) mean (SD) 1,435 (293) 1,567 (666) 1,805 (857) 1,603 (649) ANOVA 0.378 Weight (kg) mean (SD) 76.3 (14.9) 90.4 (20.0) 76.8 (11.2) 81.2 (16.6) ANOVA 0.046 Height (m) mean (SD) 1.70 (0.10) 1.76 (0.08) 1.74 (0.09) 1.73 (0.09) ANOVA 0.245 BMI (kg/m2) mean (SD) 26.4 (3.23) 29.1 (4.92) 25.5 (2.77) 27.0 (3.96) ANOVA 0.050 Glucose (mmol/L) mean (SD) 5.54 (0.43) 5.38 (0.47) 5.44 (0.44) 5.45 (0.44) ANOVA 0.673 Total cholesterol (mmol/L) mean (SD) 5.20 (1.3) 4.57 (0.61) 6.10 (1.37) 5.31 (1.29) ANOVA 0.005 Triglyceride (mmol/L) mean (SD) 0.79 (0.2) 0.99 (0.36) 0.92 (0.22) 0.90 (0.27) ANOVA 0.184 Insulin (pmol/L) mean (SD) 63.1 (37.3) 81.1 (39.4) 41.6 (17.6) 61.4 (35.8) ANOVA 0.012 DOI: 10.7717/peerj.6273/table-1

Anthropometry Mean weight and BMI at baseline differed between groups (p = 0.046 and 0.050, respectively). The LCD group had the highest starting BMI at baseline of 29.1 kg/m2 (SD = 4.9), followed by MCD (BMI = 26.4 kg/m2, SD = 3.2). The lowest starting BMI was in the VLCKD group with a mean BMI of 25.5 kg/m2 (SD = 2.8). Overall, there was a significant reduction in weight across all groups (p < 0.001). Mean weight loss increased with the magnitude of carbohydrate restriction, with 4.12 kg (SD = 2.54), 3.93 kg (SD = 3.71), and 2.97 kg (SD = 3.25) lost by the VLCKD, LCD, and MCD groups, respectively. However, the differences in weight loss between these groups were not statistically significant (p = 0.626). Similarly, a highly significant change in BMI of −1.22 kg/m2 (SD = 1.03, p < 0.001) was recorded overall. While the reduction in BMI was greater per magnitude of carbohydrate restriction, this difference was not significant (p = 0.686). All dietary interventions led to reductions in both waist and hip girth. There was an overall reduction in waist measurement of 2.85 cm (SD = 2.99) and hip girth reduced by 3.43 cm (SD = 4.67, p < 0.001 for both measures). The reduction in waist measurement girth did not differ significantly by group (p = 0.99) but the change in hip girth approached the threshold for significance (p = 0.06). There was a significant change overall to the waist-height ratio (−0.02, p < 0.001) but no significant difference between groups and no significant overall change in the waist-hip ratio. All changes in measures, both overall and by group, with 95% confidence intervals are reported in Table 2. Measure Overall change† Mean change from baseline [95% CI] Treatment group‡ Mean change from baseline [95% CI] Moderate-low carbohydrate diet Low carbohydrate diet Very low carbohydrate ketogenic diet Weight (kg) −3.70 [−4.72 to −2.68] p < 0.01 −2.97 [−5.03 to −0.90] −3.93 [−6.17 to −1.69] −4.12 [5.58 to −2.65] p = 0.63 Waist circumference (cm) −2.85 [−3.82 to −1.88] p < 0.01 −2.95 [−5.57 to −0.33] −2.80 [−4.62 to −0.98] −2.81 [−3.88 to −1.75] p = 0.99 Hip circumference (cm) −3.43 [−4.95 to −1.92] p < 0.01 −3.56 [−5.00 to −2.12] −1.19 [−4.29 to 1.91] −5.40 [−8.34 to −2.46] p = 0.06 Waist-height ratio −0.02 [−0.02 to −0.01] p < 0.001 −0.02 [−0.03 to −0.002] −0.02 [−0.03 to −0.006] −0.02 [−0.02 to −0.01] p = 0.98 Waist-hip ratio −0.003 [−0.016 to 0.010] p = 0.66 −0.004 [−0.026 to 0.018] −0.017 [−0.046 to 0.011] 0.011 [−0.008 to 0.030] p = 0.16 BMI (kg/m2) −1.223 [−1.556 to −0.889] p < 0.001 −1.031 [−1.757 to −0.306] −1.22 [−1.894 to −0.546] −1.39 [−1.899 to −0.881] p = 0.686 Total cholesterol (mmol/L) 0.58 [0.11–1.05] p = 0.02 0.08 [−0.57 to 0.72] 0.94 [0.08–1.80] 0.68 [−0.33 to 1.69] p = 0.33 LDL-c (mmol/L) 0.49 [0.06–0.92] p = 0.03 0.14 [−0.39 to 0.67] 0.80 [−0.02 to 1.62] 0.50 [−0.44 to 1.44] p = 0.47 HDL-c (mmol/L) 0.11 [0.00, 0.23] p = 0.05 −0.05 [−0.33 to 0.24] 0.13 [−0.02 to 0.27] 0.24 [0.07–0.42] p = 0.10 Triglycerides (mmol/L) −0.12 [0.20 to −0.02] p = 0.02 −0.04 [−0.22 to 0.15] −0.09 [−0.27 to 0.09] −0.18 [−0.32 to −0.04] p = 0.41 TG-HDL ratio −0.101 [−0.173 to −0.030] p = 0.006 −0.023 [−0.123 to 0.078] −0.118 [−0.294 to 0.058] −0.154 [−0.259 to −0.048] p = 0.31 Insulin (pmol/L) −13.58 [−21.61 to −5.56] p < 0.01 −6.45 [−23.38 to 10.48] −23.68 [−42.49 to −4.86] −10.33 [−17.03 to −3.62] p = 0.19 Glucose (mmol/L) −0.11 [−0.26 to 0.04] p = 0.14 −0.22 [−0.55 to 0.11] 0.08 [−0.19 to 0.34] −0.20 [−0.45 to 0.04] p = 0.20 c-reactive protein (mg/L) −2.16 [−4.55 to 0.22] p = 0.07 −3.90 [−11.90 to 4.10] −3.04 [−5.39 to −0.68] 0.14 [−0.50 to 0.77] p = 0.34 DOI: 10.7717/peerj.6273/table-2