Journal of Metabolic Health

ISSN: (Online) 2960-0391

Page 1 of 9 Original Research

Evaluation of metabolic changes in clinic attendees with

therapeutic carbohydrate restriction

Authors: Background: Obesity and related metabolic health disorders are major clinical problems that
Kirsty Woods1,2
have become increasingly prevalent worldwide.
Hilmi S. Rathomi3,4
Thomas L. Smith1 Aim: This before-after study examined the impact of therapeutic carbohydrate restriction
Nahal Mavaddat5
Judith Katzenellenbogen3
(TCR) in managing metabolic health and promoting weight loss in a clinical setting using
indirect calorimetry (IC).
Affiliations:
1
Metabolic Health Solutions, Setting: Data were collected from medical records obtained from a specialised allied health
Perth, Australia clinic focusing on metabolic health.

2
School of Medical and Methods: The study analysed retrospective data from 202 overweight or obese participants
Health Sciences, Ralph and (77% female, mean age 47.3) who received TCR as part of a behavioural modification
Patricia Sarich Neuroscience programme involving multiple visits where their lifestyle, body composition and respiratory
Research Institute, Edith
quotient (RQ), a key indicator of fat oxidation were recorded.
Cowan University, Perth,
Australia Results: The study found that TCR improved fat oxidation in 84% of participants at short term
visit (around 2 weeks), with an average weight loss of 1.8 kg. At medium term visit (around 12
3
School of Population and
Global Health, Faculty of weeks), 82% of participants maintained an increase in fat oxidation rate, with an average
Health and Medical Science, weight loss of 3.9 kg. In addition, among those with recorded body composition and waist
University of Western circumference, 71% of weight lost was from fat, with an average reduction of 4.9 cm in waist
Australia, Perth, Australia
measurements.
4
Department of Public Conclusion: This real-world study suggests that personalised TCR guided by IC can be an
Health, Faculty of Medicine, effective strategy for improving metabolic flexibility to help manage excess weight and related
Universitas Islam Bandung,
Bandung, Indonesia co-morbidities in a free-living population. Further research is needed to examine the long-term
effects of TCR using this approach.
5
Medical School, Faculty of
Health and Medical Science, Contribution: The utilisation of IC allows for the examination of individual shifts and
University of Western improvements in metabolism among patients undergoing TCR.
Australia, Perth, Australia
Keywords: carbohydrate restriction; fat oxidation; indirect calorimetry; obesity; weight loss;
Corresponding author: metabolic flexibility; lifestyle.
Kirsty Woods,
kirsty.woods@
metabolichealthsolutions.org
Introduction
Dates:
Obesity and related metabolic health disorders are major clinical problems that have become
Received: 19 Dec. 2023
Accepted: 04 Apr. 2024 increasingly prevalent worldwide and are associated with numerous health risks and costs.1,2,3,4
Published: 10 May 2024 Current approaches to assessing and managing these conditions appear inadequate, with
innovative interventions to prevent and reduce their prevalence and complications continuing to
How to cite this article:
Woods K, Rathomi HS, Smith be sought.
TL, Mavaddat N,
Katzenellenbogen J. One crucial aspect of metabolic health is metabolic flexibility, which refers to the ability to
Evaluation of metabolic
efficiently adapt metabolism to varying metabolic demands.5 Impairments in metabolic flexibility
changes in clinic attendees
with therapeutic are associated with reduced fat oxidation and development of conditions such obesity, diabetes
carbohydrate restriction. and metabolic syndrome.6,7 Understanding these impairments can help to explain individual fat
J. metab. health. 2024;7(1), loss from diet and exercise.8,9
a94. https://doi.org/10.4102/
jmh.v7i1.94
Indirect calorimetry (IC) is regularly used to assess metabolic flexibility in individuals in
intervention studies and can provide the basis for individualised care.10,11 It is a non-invasive
Read online:
method that measures oxygen consumption and carbon dioxide production in the breath to
Scan this QR
code with your determine the body’s energy expenditure and fuel utilisation.10 One valuable output from IC is the
smart phone or
mobile device respiratory quotient (RQ), a metabolic ratio indicating the cellular level metabolism of substrates
to read online.
Copyright: © 2024. The Authors. Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License.

http://www.journalofmetabolichealth.org Open Access

 Page 2 of 9 Original Research

at rest, specifically fat versus glucose. Importantly, fasting RQ In this article, we aim to investigate the short- and medium-
can provide insights into the metabolic characteristics that term impact of TCR on the metabolic health status of
differentiate individuals, ultimately influencing their unique individuals who were overweight or obese that attended a
responses to dietary interventions. community-based clinic, specifically in relation to weight
loss and fat oxidation. We used IC to measure RQ as a marker
However, IC has faced limitations in widespread adoption of metabolic flexibility8,19 and study the clinical benefits of
within clinical settings because of the associated costs and integrating TCR into a lifestyle management strategy within
technological complexity. These challenges have hindered a clinical setting.
the utilisation of this gold standard approach in real-world
clinical practice, despite a growing interest in its application.8,10 Research methods and design
Notably, most studies using RQ have had relatively short
Study design and setting
durations, spanning from 24 hours to 4 weeks and long-term
information regarding different individuals is lacking.9 This study followed a single-arm, before-after design,
involving a retrospective chart review. Data were collected
from medical records obtained from a specialised allied
One lifestyle management strategy that has gained popularity
health clinic, Metabolic Health Solutions Pty Ltd (MHS),
in recent years is therapeutic carbohydrate restriction
based in Perth, Western Australia. This clinic concentrates on
(TCR).12 Emerging evidence suggests that TCR can result in a
addressing metabolic health concerns and specialised testing
significant reduction in fat mass and improvement in disease
to assist individuals dealing with weight and metabolic
management outcomes. For example, a systematic review
health disorders. Their approach includes lifestyle-based
that assessed the effects of carbohydrate-restricted diets
interventions, including TCR.
found that carbohydrate-restricted diets could be offered to
people living with diabetes as part of an individualised Services are delivered face-to-face by qualified allied
management plan.13 It can also help to reduce body weight health professionals (Dietitian or Exercise Physiologist) using
and help manage heart disease risk factors such as cholesterol standardised clinical care models. Patients who present with
and raised blood pressure.14 For weight loss and body a higher than expected RQ for that of a standard Western diet
composition, TCR with adequate protein has been shown to ≥0.81 corresponding to a fuel utilisation ratio of 62% Fat and
be at least as effective or even more effective than low-fat 38% CHO 20 or with a metabolic condition that could benefit
diets in the short term with additional metabolic benefits in such as fatty liver, T2DM, or PCOS, were prescribed TCR.
terms of hunger and metabolic risk factors.9,15,16,17 This nutritional strategy focuses on whole foods to reduce
the insulin response of the participants diet to help to improve
Given the promising outcomes of TCR, it is important to metabolic flexibility and fat oxidation, weight loss and health.
explore opportunities for its broader adoption. According to Many participants continue with subsequent testing and
a review conducted by Rathomi and colleagues, many long-term support. Patients who attend the clinic (with or
General Practitioners (GP’s) globally find what messages to without a GP referral) are required to pay an out-of-pocket
give their patients around the most effective ways to lose expense. In 2019, the MHS clinic moved to online collection
weight confusing.18 The review also highlights that some GPs of clinical data, facilitating ongoing analysis of data.
already prescribe TCR or low carbohydrate diets in practice,
despite these not frequently being advised in dietary Participants
guidelines, as a result of their own personal or family
The study included self-selected individuals with excess
experiences of success with these methods. Therapeutic
weight (body mass index [BMI] ≥ 25 kg/m²) who received
carbohydrate restriction could therefore be a valuable option
care at the clinic from 2019 to 2022 and were recommended
to be offered to patients seeking weight loss advice were it to
TCR. Study patients were adults (≥18 years old) who had
be found to be effective in the real world.
signed consent and agreed to their data being used for audit
and/or research purposes. Participants with incomplete key
Indeed, while most human studies on TCR have tended to data points were excluded. The participant selection process
follow ketogenic dietary patterns and been conducted in is illustrated in Figure 1.
research settings, there is limited evidence from individuals
who have applied this strategy in their daily lives.9 There also Out of the 202 patients included in the initial visit, 144
appears to be little research evaluating the degree of attended further follow-up visits. As a result of the variation
carbohydrate restriction necessary for beneficial outcomes in follow-up intervals, we have defined specific timeframes
and a lack of clinical tools for enhancing motivation, for inclusion in both short-term and medium-term analysis.
education and evaluating the effectiveness of these regimes Short-term analysis criteria include those who came for a
at an individual level. Hence, it is necessary to explore second visit within a 4-week period, while medium-term
technologies such as IC to help measure physiological analysis includes patients who attended additional follow-
mechanisms such as fat oxidation and enhance personalisation up visits within a 10–16 week timeframe from the initial visit.
of such strategies in real-world settings. This can add to the With these criteria, 111 patients were eligible for short-term
growing evidence regarding the effectiveness of TCR. follow-up (STFU) evaluation, and 34 patients were eligible

http://www.journalofmetabolichealth.org Open Access

 Page 3 of 9 Original Research

Calculating substrate oxidation (RER):

Identifiction

262 online patient records

Excluded those before 2019 CHO metabolism: C6H12O6 + 6O2 → 6CO2 + 6H2O + energy
75% sub-optimal fat before data was digitised Fat Metabolism: C16H32O2 + 23O2 → 16CO2 + 16H2O + energy
oxidation (RQ > 0.81)

Source: Katch M. Exercise physiology: Nutrition, energy, and human performance. 7th ed.
Philadelphia, PA: Lippincott Williams & Wilkins, 2009; 1136 p.
246 were overweight or obese FIGURE 2: Calculating substrate oxidation (RER).
Eligibility

Excluded those who were

76% sub-optimal fat not overweight or obese
oxidation (RQ > 0.81)
conjunction with the results from metabolic health testing –
IC (ECAL by Metabolic Health Solutions Pty Ltd) and
202 recommended TCR
Excluded those who anthropometric measurements (weight [scales], waist
Included

84% sub-optimal fat were not advised TCR [measuring tape] and body composition [bio-electrical
oxidation (RQ > 0.81) impedance]) were used to develop personalised dietary and
exercise advice, including TCR.
111 eligible for short Follow up results excluded
Sub-analysis

term evaluation those who did not meet Respiratory exchange ratio (RER) was measured with IC at
STFU (visit interval < 4 weeks)
34 eligible for medium or MTFU (visit interval rest, and in this state is equivalent to RQ and fuel utilisation
term evaluation 10–16 weeks) at a cellular level8,20 and as such may be referred to as RQ in
previous sections for simplicity – see Figure 2.19 A modified
STFU, short-term follow-up; MTFU, medium-term follow-up; TCR, therapeutic carbohydrate
restriction; RQ, respiratory quotient. Weir equation was used in calculations, as measuring
FIGURE 1: Flow chart of patients on the database included in the study. nitrogen in ambulant patients is generally not necessary.21

for medium-term follow-up (MTFU) evaluation. In the case Outcome measures

of medium-term evaluation, the data points utilised were
derived from the latest visit that occurred during the 10–16 Calorimetry and weight were measured at every visit. In
week timeframe. addition, body composition and anthropometry measurements
were performed based on clinicians’ judgement. All data
points for the short-term analysis come from patients’ second
Intervention visit, while data for the medium-term analysis were derived
All participants received personalised counselling and were from the latest follow-up visit within the defined time frame
prescribed TCR based on their medical history and test (10–16 weeks). According to this criterion, 18% of data points
results. The TCR consisted of advice to limit carbohydrates were from patients’ third visits, 47% from the fourth visit and
and emphasised the consumption of whole foods, healthy 35% from the fifth visit. The median duration of short-term
fats and non-starchy vegetables. A general prescription follow-up is 14 days (range: 6–28 days), while for MTFU, it is
methodology was used in line with MHS’ protocols to ensure 85 days (range: 70–112 days).
interventions were appropriate, safe and personalised.
Those recommended TCR may have also had changes in
exercise, time of feeding and other correctional prescriptions
Statistical analysis
such as sleep if indicated, but were generally not instructed Descriptive statistics, including means, medians, percentages
to reduce or restrict calories. Where appropriate, protein and their confidence intervals were used to characterise the
consumption and ensuring adequate essential fatty acids study population and examine changes in outcomes over time.
(EFAs) with TCR were discussed during consultation. Paired t-tests were used to compare changes in RQ, weight
and body composition from baseline to the defined follow-up
A review consultation was provided at the end of each visit, period. To address multiple testing, we applied a Bonferroni
which also included motivational intervening techniques correction, setting the level of statistical significance at 0.008
to assist in the adoption of appropriate lifestyle change (0.05/6 tests). In the secondary analysis, we used multivariable
adoption. The time periods between visits and interventions linear regression to examine factors associated with changes in
were not rigid but individualised for each patient based on primary outcomes (weight and RQ) among patients with TCR.
results, practitioner insight and scheduling. Covariates included age, gender and medical conditions such
as diabetes and cardiovascular problems. All statistical
Baseline measures analyses were performed using STATA 13 (StataCorp, LP).

Before their initial visits, patients completed an online

questionnaire and received pre-test instructions advising Ethical considerations
them to observe a minimum of 4 hours of fasting before their This study was approved by the Institutional Review Board
visit following a protocol developed for using IC in clinical of the University of Western Australia (Project number 2021/
practice.10 During their initial visit, patients provided a ET000993). Metabolic Health Solutions is an evidence-based
detailed case history focusing on key areas of their pre-test metabolic testing and management programme. Patients are
questionnaire as determined by the practitioners. This, in informed of intentions to publish data collected during

http://www.journalofmetabolichealth.org Open Access

 Page 4 of 9 Original Research

testing procedures, to further extend the evidence base. prevalent conditions. In addition, 13% of patients had
Thus, all participants provided written informed consent polycystic ovary syndrome (PCOS), which may have
prior to participation. These data were anonymised and used implications for weight management. Notably, the mean
in accordance with our privacy policy and accepted clinical waist circumference was higher in the older age group,
practice. suggesting age-related influences on weight and metabolic
health (Table 1).
Results Overall, 202 of the participants were prescribed TCR as a
The vast majority of patients providing baseline measures part of a behavioural modification programme. Among
were females (77%) and predominantly identified as Caucasian the 111 patients who had complete data records in the
(92%). The age distribution indicated that over half of patients short-term follow-up visit, 84.1% showed improved fat
were between 45 and 65 years old (54%), with over a third oxidation. On average, there was a 63% relative increase in
under 45 years (38%) and relatively few over 65 years (8%), fat oxidation from baseline. Moreover, the participants
mean ± standard deviation (s.d.) of age is 47.3 ± 12.4. exhibited an average weight loss of 1.8 kg (95% confidence
interval [CI] = 1.6 kg – 2.1 kg) during the same period,
On initial presentation, a significant portion of the patients representing a 2% relative change. Data for body
were categorised as obese (76%) with 24% falling into the fat analysis were not available at this follow-up period
overweight category. The majority (70%) of patients (Table 2).
reported gaining weight over the previous year. At least
one medical condition was self-reported in 83% of patients At the MTFU period (n = 34), approximately 80% of the
highlighting the potential influence of underlying health patients maintained an increase in fat oxidation rates,
issues on weight-related challenges. Moreover, two thirds with a mean relative change of 70% from baseline. This
(67%) were on multiple medications. improvement was accompanied by an average weight
loss of 3.9 kg (95% CI = 2.6 kg – 5.3 kg). Among those
Regarding metabolic health, 84% of the patients had a sub- with waist measurements recorded at this visit, there
optimal fat oxidation, represented by a RQ > 0.81. High blood was an average reduction of 4.9 cm (95% CI = 2.9 cm –
pressure, diabetes and sleep apnoea were among the most 5.8 cm), as well as a significant reduction of 2.7 kg

TABLE 1: Patients’ characteristics.

Characteristics Age group
< 45 years (N = 78) 45–65 years (N = 108) > 65 years (N = 16) Total (N = 202)
n % mean ± s.d. n % mean ± s.d. n % mean ± s.d. n % mean ± s.d.
Gender
Female 67 89 - 78 72 - 10 63 - 155 77 -
Ethnicity
Caucasian 70 90 - 100 93 - 16 100 - 186 92 -
Other 8 10 - 8 7 - - 0 - 16 8 -
Medical problems
Has at least 1 problem 56 75 - 96 89 - 15 94 - 167 83 -
High blood pressure 10 13 - 23 21 - 10 63 - 43 21 -
Diabetes 19 25 - 24 22 - 6 38 - 49 24 -
Heart condition 7 9 - 8 7 - 5 31 - 20 10 -
Sleep apnoea 7 9 - 22 20 - 5 31 - 34 17 -
Fatty liver 10 13 - 23 21 - 4 25 - 37 18 -
Polycystic ovary syndrome (PCOS) 15 22 - 5 6 - - 0 - 20 13 -
Bariatric surgery 5 7 - 3 3 - - 0 - 8 4 -
Weight change over past year
Decreased 8 11 - 7 6 - - 0 - 15 7 -
Stable 16 21 - 24 22 - 8 50 - 48 24 -
Increased 54 72 - 77 71 - 8 50 - 139 69 -
BMI category
Overweight 18 24 - 27 25 - 3 19 - 48 24 -
Obese 60 80 - 81 75 - 13 81 - 154 76 -
RQ level (cutoff 0.81)
Optimal RQ (< 0.81) 10 13 - 18 17 - 5 31 - 33 16 -
Weight - - 96.8 ± 22.5 - - 99.5 ± 20.1 - - 98.7 ± 20.8 - - 98.4 ± 21.1
Waist circumference (n = 201) - - 100.9 ± 15.4 - - 108.8 ± 18.0 - - 111.8 ± 15.3 - - 105.9 ± 17.3
BMI - - 34.7 ± 6.7 - - 34.9 ± 6.7 - - 34.4 ± 4.9 - - 34.8 ± 6.5
Body fat in kg (n = 193) - - 38.9 ± 13.1 - - 38.7 ± 12.9 - - 38.1 ± 10.5 - - 38.7 ± 12.7
RQ - - 0.92 ± 0.11 - - 0.89 ± 0.09 - - 0.88 ± 0.11 - - 0.91 ± 0.10
Fat oxidation - - 30.7 ± 25.9 - - 35.9 ± 24.5 - - 43.9 ± 24.3 - - 34.5 ± 25.2
s.d., standard deviation; BMI, body mass index; RQ, respiratory quotient.

http://www.journalofmetabolichealth.org Open Access

 Page 5 of 9 Original Research

TABLE 2: Short term (< 4 weeks) outcome changes (N = 111).

Measurement Mean at baseline Mean at STFU Mean 95% CI % relative p
difference changes
Mean s.d. Mean s.d.
Respiratory quotient 0.91 0.89–0.93 0.83 0.82–0.85 0.07 0.06–0.09 8 0.0000*
Fat oxidation (%) 32.7 28.2–37.1 53.2 48.8–57.6 20.5 16.1–24.9 63 0.0000*
Weight (kg) 100.4 96.2–104.6 98.6 94.5–102.8 1.8 1.5–2.2 2 0.0000*
Waist circumference (cm) (n = 11) 111.8 101.2–122.3 108.5 98.3–118.7 3.2 1.8–4.7 3 0.0003*
BMI 35.3 34.0–36.6 34.7 33.4–35.9 0.6 0.5–0.7 2 0.0000*
Body fat (kg) (n = 0) - - - - - - - -
STFU, Short term follow up (2 weeks on average, ranging from 6 to 28 days); CI, confidence interval.
*, statistically significant difference using the t-test.

TABLE 3: Medium-term (10–16 weeks) outcome changes (N = 34).

Measurement Mean at baseline Mean at MTFU Mean 95% CI % relative p
difference changes
Mean s.d. Mean s.d.
Respiratory quotient 0.92 0.88–0.96 0.84 0.81–0.87 0.08 0.04–0.11 9 0.0000*
Fat oxidation (%) 32.1 22.8–41.4 52.1 43.1–61.2 20.0 11.0–29.0 62 0.0000*
Weight (kg) 100.4 92.2–108.5 96.4 87.9–104.8 3.9 2.6–5.3 4 0.0000*
Waist circumference (cm) (n = 14) 115.0 103.3–126.8 110.0 98.0–122.1 4.9 2.3–7.7 4 0.0001*
BMI 35.5 33.1–37.9 34.1 31.6–36.5 1.4 0.9–1.9 4 0.0000*
Body fat (kg) (n = 14) 35.0 26.9–43.0 32.4 24.8–39.9 2.7 1.2–4.1 8 0.0000*
MTFU, Medium term follow-up (12 weeks on average, ranging from 10 to 16 weeks); CI, confidence interval; BMI, body mass index.
*, statistically significant difference using the t-test.

Fat oxidation level (%) Weight (kg) a Fat oxidation level (%) Weight (kg) b

60 101.0 60 101
53.2 100.6 55.9
100.4 52.1
50 100.5 50
Fat oxidation level
Fat oxidation level

99
100.0 40
40

Weight
Weight

99.5 98.4
30 30 97
32.7 99.0 32.1
20 20
98.5 95
98.6 95.8
10 98.0 10

0 97.5 0 93
Baseline STFU Baseline STFU MTFU
Fat oxidation Level (%) 32.7 53.2 Fat oxidation Level (%) 32.1 55.9 52.1
Weight (kg) 100.4 98.6 Weight (kg) 100.6 98.4 95.8

STFU, short-term follow-up; MTFU, medium-term follow-up.

FIGURE 3: Comparison of changes in weight and fat oxidation levels from baseline to the follow-up period: (a) Among patients eligible for short-term analysis (N = 111).
(b) Among patients eligible for medium-term analysis (N = 34).

(95% CI = 2.4–5.1) in fat mass (equivalent to 8%). There changes, 88% experienced a reduction in weight in both the
was still a significant improvement fat oxidation from the short and medium terms, with the highest reductions being
baseline, resulting in a 4% decrease in body weight and 6.1 kg or 5% of body weight in the short term and 13.6 kg or
BMI (Table 3). 14% of body weight in the medium term. Individual changes
in fat oxidation and weight among patients are illustrated in
In both the short and medium term, patients experienced an Figure 4.
increase in fat oxidation levels and a decrease in weight.
Among potential covariates in the multivariable linear
Improved fat oxidation is maintained in the medium term,
regression analysis, including age, gender, diabetes and
and despite having similar fat oxidation levels between the
cardiovascular problem, gender was the only factor
STFU and MTFU, patients continued to experience ongoing associated with short-term weight changes, with weight
weight loss (see Figure 3). loss being higher in male patients (β = −1.11, 95% CI
[−1.84, −0.39], p = 0.003). However, for the MTFU, this
On an individual level, there was considerable variation difference disappeared, as there was no significant
observed in both fat oxidation level and weight changes. The difference of weight changes between genders after
prevalence of improvements in fat oxidation levels was adjusting for age, diabetes and cardiovascular problems
similar in both the short term (84%) and medium term (82%), (β = 0.63, 95% CI [−3.93, 5.19], p = 0.779). In addition, no
with the highest observed change being 100% in the short covariates were associated with either short- or medium-
term and 87% in the medium term. Regarding weight term changes of RQ.

http://www.journalofmetabolichealth.org Open Access

 Page 6 of 9 Original Research

Individual changes in the short-term Individual changes in the medium-term

a d

Changes in fat oxidation level (%)

Change in fat oxidation level (%)

100 100
84% improved fat oxidation level 82% improved fat oxidation levela
80 80
60 60
40 40
20 20
0 0
–20 –20
–40 –40
Individual responses (N = 111) Individual responses (N = 34)

b e
10 10
Weight changes (kg)

Weight changes (kg)

5 5

0 0

–5 –5
88% lost weight
–10 –10
88% lost weight
–15 –15
Individual responses (N = 111) Individual responses (N = 34)

c f
5 5
Relative weight changes (%)

Relative weight changes (%)

0 0

–5 –5
88% lost weight
–10 –10

88% lost weight

–15 –15
Individual responses (N = 111) Individual responses (N = 34)

FIGURE 4: Short- and medium-term changes in fat oxidation levels (a, d), absolute weight (b, e) and relative weight changes (c, f) among individual patients who underwent
therapeutic carbohydrate restriction.

Discussion with obesity; this degree of weight loss is also required for
the approval of novel antiobesity medications by the US
The results of this clinical analysis suggest that TCR, when Food and Drug Administration.23 These changes may also
combined with a behavioural modification programme and have the potential to help to enhance adherence to physical
metabolism testing, can lead to significant improvements in
activity and improve the ease of daily tasks. It may also be
metabolic flexibility, health and weight. These findings are
important to observe that the health benefits of diet-induced
consistent with previous studies that have shown TCR to be
weight loss are thought to be compromised by loss of lean
an effective dietary approach for promoting weight loss and
body mass, which could increase the risk of sarcopenia (low
improving metabolic health.9,13,15,16,17,21,22
muscle mass and impaired muscle function). In this data set,
Specifically, we observed that the majority of participants it was shown that 71% of weight loss was from fat mass,
experienced improvements in fat oxidation levels during the which is congruent with previous research highlighting an
short-term follow-up (84%), and this improvement was expected 20% – 30% loss from fat-free mass.24
sustained in the medium term (82%). Regarding weight loss,
our study found that 88% of patients experienced weight The improvement in fat oxidation levels observed in this
loss, with an average reduction of 1.8 kg (2% of body weight) study is particularly noteworthy, as it suggests that TCR may
in the short term and 3.9 kg (4%) in the medium term. help to improve metabolic flexibility in non-research setting
Individual variation in these changes was also evident, and helps to contribute the understanding of the physiological
suggesting a personalised response influenced by multiple changes that can occur by implementing TCR. Other studies
factors. Weight loss of around 5% results in significant have explored the impact on anthropometric data of such
improvements in cardiometabolic risk factors associated diets in those with chronic disease, without looking at these

http://www.journalofmetabolichealth.org Open Access

 Page 7 of 9 Original Research

successful for weight loss and chronic disease management;

Evaluation of metabolic changes in clinic attendees however, further feasibility studies are required to explore
with therapeutic carbohydrate restriction (TCR)
the direct impact on the quality of life (i.e. sleep, pain, energy)
TCR ↑ fat oxidaon in 84% and the role of IC in adoption, motivation and adherence,
of parcipants short specifically in regard to TCR. There is potential for using this
term (2 weeks)
metabolic approach to provide a new, innovative approach to
82% maintained an obesity and related conditions, which may have implications
increased fat oxidaon
N = 202 for standard practice and reducing healthcare costs and
rate medium term
Diabetes (12 weeks) with average disease burden. In clinical care, IC could be used to measure
PCOS weight ↓ of 3.9kg the impact of carbohydrate restriction on metabolism and
Fay liver (clinically significant) identify personalised dietary recommendations that are
Obesity
71% of weight lost was individually beneficial.
from fat, with an average
↓ of 4.9cm in waist While the results of this study are promising, there are some
Conclusion limitations that should be considered. Firstly, this was a
This real-world study suggests that personalised TCR guided by IC can be single-arm, before-and-after study with a relatively small
an effective strategy for improving metabolic flexibility to help manage
excess weight and related co-morbidities in a free-living population. sample size. As such, it is possible that the improvements
observed were because of factors other than the TCR
K.Woods, H.Rathomi, T.Smith, N. Mavaddat, & J. Katzenellenbogen (2023)
intervention, such as exercise, meal timings and sleep.
Woods K, Rathomi HS, Smith TL, Mavaddat N, Katzenellenbogen J. Evaluation of metabolic
Moreover, the small samples may have precluded statistical
changes in clinic attendees with therapeutic carbohydrate restriction. journal of metabolic significance when investigating factors associated with
health. 2024;7(1), a94. https://doi.org/10.4102/jmh.v7i1.94
PCOS, polycystic ovary syndrome. improvements. Additionally, the lack of a control group
FIGURE 5: Visual abstract. limits our ability to draw conclusions about the efficacy of
TCR compared to other dietary approaches. Baseline and
metabolic parameters.17 Our results of 3.9 kg weight loss in follow-up pathology were not readily available for many
medium term are at least comparable to those found by participants and visit time frames varied for each
purely measuring anthropometrics and meet the minimal participant. The retrospective nature of the data collection
clinically important difference (MCID) threshold for meant that the study relied on data not designed for
cardiovascular risk factors in patients with type 2 diabetes23 statistical analysis, with missing data limiting the number
and the threshold of clinically relevant weight loss for health of people that could be included. Furthermore, there may
outcomes reported by the Obesity Medicine Association.25 be a potential for selection bias given that participants were
Another TCR lifestyle programme in primary care for a free- self-selected to receive care at the specialised clinic who
living population resulted in a 5% weight change and a 2% could afford to fund out-of-pocket expenses for the service.
change in waist circumference over an average follow-up of The incomplete follow-up of the cohort means that those
period 15 months.26 In our study, we observed a similar for whom we have follow-up measurements may have
outcome in a shorter follow-up period, highlighting the differed from those who were excluded from the before-
potential role for measuring metabolism in a clinical setting. after analysis, introducing a potential bias. The findings of
this study also do not apply to long-term outcomes. Finally,
Given no intentional calorie restriction was generally the personalised nature of the TCR diet limits the
observed in our cohort, the weight loss can likely be attributed generalisability of these findings to other dietary
to these changes in fat oxidation. The improvements in fat approaches, particularly given adherence was not strictly
oxidation levels were accompanied by expected weight loss monitored. Despite these limitations, this cohort represents
and reductions in waist circumference. It is reasonable the real-world clinical constraints in allied health situations
(although not measured in this group) to presume that and may provide insight into the multifactorial challenges
endogenous insulin levels would have reduced in our in this setting, which clinical trials may miss.
patients as observed in other TCR-focused research9,12,27 and
is likely a contributing mechanism to these changes. Further research, including randomised controlled trials
with larger sample sizes, is needed to confirm the findings
Notably, despite having a similar fat oxidation level between of this study and explore the potential benefits of TCR in
short term and medium term follow-up visit, the patients more detail. Measurement of patient engagement, having
continued to experience ongoing weight loss. This finding supervised exercise sessions with compulsory baseline and
suggests that continued increases in fat oxidation are not follow-up pathology at regular intervals would also be
required for weight loss to persist, likely because of an upper beneficial. Exploration of the potential of medication as an
physiological limit. The results reinforce the significance of adjunct therapy using IC is also warranted. Importantly,
maintaining fat oxidation in the weight loss process. improvements in data quality and completeness have the
potential to increase the utility of the routinely collected
Data provided by this study and others28,29 show that data, thereby allowing ongoing real-world reporting on
integrating IC into practice (and the data it provides) can be outcomes.

http://www.journalofmetabolichealth.org Open Access

 Page 8 of 9 Original Research

Conclusion References
In conclusion, our study provides evidence to support the 1. Jaacks LM, Vandevijvere S, Pan A, et al. The obesity transition: Stages of the
global epidemic. Lancet Diabetes Endocrinol. 2019;7(3):231–240. https://doi.
use of TCR as a viable dietary approach and treatment option org/10.1016/S2213-8587(19)30026-9
for promoting weight loss and improving metabolic health in 2. National Health Survey: First results, 2017–18 financial year [homepage on the
Internet]. Australian Bureau of Statistics; 2018 [cited 2023 Jul 26]. Available from:
those with excess weight and accompanying chronic disease https://www.abs.gov.au/statistics/health/health-conditions-and-risks/national-
in a clinical setting, particularly when paired with IC. health-survey-first-results/latest-release
3. WA Healthy Weight Action Plan [homepage on the Internet]. [cited 2023 Jul 26].
Available from: https://www.health.wa.gov.au/Articles/U_Z/WA-healthy-weight-
Future research should aim to replicate these findings in action-plan#:~:text=The%20WA%20Healthy%20Weight%20Action,end%20
of%20the%20healthy%20weight
larger, more diverse populations and explore the mechanisms
4. Lonardo A, Byrne CD, Targher G. Precision medicine approaches in metabolic
underlying the observed improvements in metabolic flexibility disorders and target organ damage: Where are we now, and where are we going?
Metab Target Organ Damage. 2021;1(1):3. https://doi.org/10.20517/mtod.2021.03
and weight loss, including the role of metabolism-specific
5. Smith RL, Soeters MR, Wüst RCI, Houtkooper RH. Metabolic flexibility as an
data for enhancing motivation and improving outcomes. adaptation to energy resources and requirements in health and disease. Endocr
Rev. 2018;39(4):489–517. https://doi.org/10.1210/er.2017-00211
6. Pujia A, Gazzaruso C, Ferro Y, et al. Individuals with metabolically healthy
We hope to provide insight into the effectiveness and overweight/obesity have higher fat utilization than metabolically unhealthy
applicability of using this metabolic approach combining individuals. Nutrients. 2016;8(1):2. https://doi.org/10.3390/nu8010002
TCR and IC to improve weight loss and metabolic health 7. Pujia A, Mazza E, Ferro Y, et al. Lipid oxidation assessed by indirect calorimetry
predicts metabolic syndrome and type 2 diabetes. Front Endocrinol (Lausanne).
outcomes in patients to help bridge the gap between research 2019;9:806. https://doi.org/10.3389/fendo.2018.00806
and practice. 8. Gupta RD, Ramachandran R, Venkatesan P, Anoop S, Joseph M, Thomas N. Indirect
calorimetry: From bench to bedside. Indian J Endocrinol Metab. 2017;21(4):​
594–599. https://doi.org/10.4103/ijem.IJEM_484_16

Acknowledgements 9. Goldenshluger A, Constantini K, Goldstein N, et al. Effect of dietary strategies on

respiratory quotient and its association with clinical parameters and organ fat
loss: A randomized controlled trial. Nutrients. 2021;13(7):2230. https://doi.
Competing interests org/10.3390/nu13072230
10. Haugen HA, Chan LN, Li F. Indirect calorimetry: A practical guide for clinicians. Nutr
K.W. and T.L.S. work with the company that owns the Clin Pract. 2007;22(4):377–388. https://doi.org/10.1177/0115426507022004377
technology mentioned in the article. 11. Lam YY, Ravussin E. Indirect calorimetry: An indispensable tool to understand and
predict obesity. Eur J Clin Nutr. 2017;71(3):318–322. https://doi.org/10.1038/
ejcn.2016.220
Authors’ contributions 12. Oh R, Gilani B, Uppaluri KR. Low carbohydrate diet. Treasure Island, FL: StatPearls
Publishing; 2023 [cited 2023 Jul 26]. Available from: http://www.ncbi.nlm.nih.
gov/books/NBK537084/
K.W. initiated the project and conducted testing with
13. Sainsbury E, Kizirian NV, Partridge SR, Gill T, Colagiuri S, Gibson AA. Effect of
interventions for this analysis and authored the first draft, dietary carbohydrate restriction on glycemic control in adults with diabetes: A
subsequently revising and reviewing the article. H.S.R. co- systematic review and meta-analysis. Diabetes Res Clin Pract. 2018;139:239–252.
https://doi.org/10.1016/j.diabres.2018.02.026
initiated the study, developed the methodology, conducted 14. Volek JS, Sharman MJ. Cardiovascular and hormonal aspects of very-low-
data curation and statistical analysis, authored the initial carbohydrate ketogenic diets. Obes Res. 2004;12 Suppl 2:115S–123S. https://doi.
org/10.1038/oby.2004.276
draft and contributed in article review. K.W. and H.S.R. 15. Ebbeling CB, Swain JF, Feldman HA, et al. Effects of dietary composition on energy
contributed equally to this work. T.L.S. contributed to data expenditure during weight-loss maintenance. JAMA. 2012;307(24):2627–2634.
https://doi.org/10.1001/jama.2012.6607
acquisition and/or curation and reviewed the article. N.M.
16. Myshak-Davis AT, Evans J, Howay H, Sakakibara BM. The effects of a primary care
provided guidance on conceptualisation and methodology low-carbohydrate, high-fat dietary educational intervention on laboratory and
anthropometric data of patients with chronic disease: A retrospective cohort
and reviewed the article. J.K. provided guidance in chart review. Fam Pract. 2022;39(5):819–825. https://doi.org/10.1093/fampra/
cmac003
conceptualisation, methodology and data analysis and
17. Volek JS, Fernandez ML, Feinman RD, Phinney SD. Dietary carbohydrate restriction
contributed to the article review. All authors participated in induces a unique metabolic state positively affecting atherogenic dyslipidemia,
result discussions and approved the final article. fatty acid partitioning, and metabolic syndrome. Prog Lipid Res. 2008;47(5):
307–318. https://doi.org/10.1016/j.plipres.2008.02.003
18. Rathomi HS, Dale T, Mavaddat N, Thompson SC. General practitioners’ knowledge,
attitudes, and practices of dietary advice for weight control in their overweight
Funding information patients: A scoping review. Nutrients. 2023;15(13):2920. https://doi.org/10.3390/
nu15132920
This research received no specific grant from any funding 19. Katch M. Exercise physiology: Nutrition, energy, and human performance. 7th ed.
agency in the public, commercial or not-for-profit sectors. Philadelphia, PA: Lippincott Williams & Wilkins, 2009; 1136 p.
20. Indirect calorimetry: Principles and applications for managing critically ill patients
[homepage on the Internet]. Medscape. [cited 2023 Jul 26]. Available from:
http://www.medscape.org/viewarticle/515891
Data availability 21. Virta Health clinical trial patients showed lasting type 2 diabetes reversal and
remission at 5 years homepage on the Internet. Virta Health, 2023 [cited 2023 Jul
The data that support the findings of this study are available 26]. Available from: https://www.virtahealth.com/press-releases/virta-sustainable-
on request from the corresponding author, K.W. health-improvements-5-year-diabetes-reversal-study
22. Jayedi A, Zeraattalab-Motlagh S, Jabbarzadeh B, et al. Dose-dependent effect of
carbohydrate restriction for type 2 diabetes management: A systematic review
and dose-response meta-analysis of randomized controlled trials. Am J Clin Nutr.
Disclaimer 2022;116(1):40–56. https://doi.org/10.1093/ajcn/nqac066
23. Horn DB, Almandoz JP, Look M. What is clinically relevant weight loss for your
The views and opinions expressed in this article are those patients and how can it be achieved? A narrative review. Postgrad Med. 2022 May
of the authors and are the product of professional research. 19;134(4):359–375. https://doi.org/10.1080/00325481.2022.2051366

It does not necessarily reflect the official policy or position 24. Cava E, Yeat NC, Mittendorfer B. Preserving healthy muscle during weight loss
123. Adv Nutr. 2017;8(3):511–519.
of any affiliated institution, agency or that of the publisher. 25. Bays HE, Golden A, Tondt J. Thirty obesity myths, misunderstandings, and/or
The authors are responsible for this article’s results, oversimplifications: An Obesity Medicine Association (OMA) Clinical Practice
Statement (CPS) 2022. Obes Pillars. 2022;3:100034. https://doi.org/10.1016/j.
findings and content. obpill.2022.100034

http://www.journalofmetabolichealth.org Open Access

 Page 9 of 9 Original Research

26. Cummings PJ, Noakes TD, Nichols DM, Berchou KD, Kreher MD, Washburn PJ. 28. Programme overview [homepage on the Internet]. ICO, 2022 [cited 2023 Feb 24].
Lifestyle therapy targeting hyperinsulinemia normalizes hyperglycemia and Available from: https://www.icocongress.org/programme/programme-overview/
surrogate markers of insulin resistance in a large, free-living population. AJPM
Focus. 2022;1(2):100034. https://doi.org/10.1016/j.focus.2022.100034 29. Beckers S. Use of an ECAL indirect calorimeter measuring resting metabolic rate
and fat burning capacity in a lifestyle medicine clinic for adults with diabetes,
27. Volek JS, Sharman MJ, Love DM, et al. Body composition and hormonal responses pre-diabetes and unwanted obesity [homepage on the Internet]. OB, 2019
to a carbohydrate-restricted diet. Metabolism. 2002;51(7):864–870. https://doi. [cited 2023 Jul 26]. Available from: http://www.obesity-abstracts.org/ob/0001/
org/10.1053/meta.2002.32037 ob0001p28.htm

http://www.journalofmetabolichealth.org Open Access