Search
Close
Search
Advanced Search
Search Menu
AI Discovery Assistant

Abstract

Context

Impaired metabolic flexibility is associated with prediabetes. However, its assessment with reference methods is impractical in routine clinical practice.

Objective

This study investigates the relationship between fasting respiratory exchange ratio (RER), measured through indirect calorimetry, and glucose metabolism in individuals with prediabetes.

Methods

The study involved 2 cohorts: (1) a cross-sectional cohort of 10 176 individuals to assess the association between fasting RER and glucose metabolism parameters, and (2) a matched longitudinal cohort of 86 patients with impaired fasting glucose, categorized into fat oxidation (RER < 0.775) and glucose oxidation (RER > 0.925) groups, to evaluate the impact of fasting RER on impaired fasting glucose resolution and fasting glucose after a 1-year lifestyle intervention.

Results

In the cross-sectional cohort, a higher fasting RER was associated with higher fasting glucose, insulin, and Homeostatic Model Assessment for Insulin Resistance. In the longitudinal cohort, the fat oxidation group showed a greater reduction in fasting glucose (+5.9; 95% CI 1.4, 10; P = .011) and a higher probability of achieving normal fasting glycemia (log(odds ratio) −0.89; 95% CI −1.8, −0.03; P = .046) after the intervention, despite similar weight loss between groups.

Conclusion

Our findings suggest that fasting RER, a readily accessible clinical measure, can provide valuable insights into glucose metabolism and impaired fasting glucose resolution. A lower fasting RER, indicative of a greater capacity for fat oxidation, is associated with improved glycemic control after a lifestyle intervention.

fasting respiratory exchange ratio (RER), impaired fasting glucose (IFG), metabolic flexibility, glucose metabolism, lifestyle intervention, fat oxidation

Metabolic flexibility is the organism's adaptive capacity to adjust its fuel oxidation in response to fluctuations in fuel availability. It is the body's ability to efficiently switch between energy sources, primarily carbohydrates and fats, based on physiological circumstances or demands [1].

Impaired metabolic flexibility may be a key contributor to the development and progression of metabolic syndrome. Indeed, metabolic inflexibility and insulin resistance are tightly related [2]. As reviewed by Goodpaster and Sparks [3], the inability to efficiently utilize fats as a fuel source leads to an increased reliance on glucose, contributing to hyperglycemia and increasing the risk of type 2 diabetes. Impaired fat oxidation, coupled with excessive caloric intake, can promote fat accumulation, particularly in the abdominal region, a key characteristic of metabolic syndrome. Consequently, individuals with reduced metabolic flexibility face an elevated risk of cardiovascular disease, type 2 diabetes, and other complications associated with metabolic syndrome.

Metabolic flexibility is not easy to assess in clinical practice. Prior studies have combined a hyperinsulinemic–euglycemic clamp with indirect calorimetry to study metabolic flexibility under resting conditions [4]. It involves infusing human insulin to assess insulin sensitivity, while simultaneously measuring substrate utilization via indirect calorimetry. This method provides a direct assessment of insulin sensitivity and the capacity to switch from fat to carbohydrate oxidation. Although more recently indirect calorimetry alone has been used to assess metabolic flexibility of subjects undergoing a VO2 max test, an indicator of cardiovascular fitness and aerobic endurance, on a cycloergometer [5].

Fasting indirect calorimetry is widely used in the field of nutrition, allowing for precise and personalized assessment of an individual's metabolic rate, but it can also be used to analyze substrate utilization. The respiratory exchange ratio (RER) is calculated as the ratio of carbon dioxide produced (VCO2) to oxygen consumed (VO2) during indirect calorimetry. As different fuel sources have distinct RER values, by measuring RER one can estimate the proportion of carbohydrates and fats being oxidized for energy. A higher RER (closer to 1.0) signifies greater carbohydrate utilization, while a lower RER indicates a predominance of fat oxidation [6].

An overnight fast typically results in a RER of 0.80 to 0.85, signifying a predominant reliance on fat oxidation for energy production. This shift is due to hormonal changes and substrate availability [7, 8]. Nonetheless, individual fasting RER values may vary depending on factors like prior diet, metabolic health, and physical activity [1].

This study investigates the relationship between fasting glucose metabolism and fasting RER. We aim to:

  1. Explore the utility of fasting RER as an indicator of metabolic flexibility, despite its inherent limitations. We hypothesize that individuals with higher fasting RER, indicative of reduced fat oxidation, will exhibit similar glucose metabolism derangements as those observed in metabolically inflexible individuals.

  2. Evaluate the prognostic value of fasting RER in predicting the resolution of impaired fasting glucose and the degree of fasting glucose improvement in response to a lifestyle intervention. We anticipate that individuals with lower fasting RER, suggesting a greater capacity for fat oxidation, will experience greater improvements in fasting glucose after the intervention.

Materials and Methods

Study Design, Setting, and Participants

To address aim 1, we conducted a cross-sectional cohort study. Participants were self-referred individuals seeking a weight loss program at our center. Each participant underwent a comprehensive nutritional assessment, including anthropometric measurements, indirect calorimetry, a clinical evaluation, and laboratory examinations.

For aim 2, we used a matched longitudinal cohort design: patients with impaired fasting glucose following a prescribed hypocaloric diet with an RER indicative of glucose oxidation metabolism during fasting were matched to patients with an RER indicative of fat oxidation metabolism during fasting. Secondary endpoints were body weight, body mass index (BMI), waist circumference, and body fat percentage.

Both groups received a standardized diet with the following characteristics: caloric intake matched to resting energy expenditure; protein content aligned with the Italian recommended daily allowances [9]; similar percentages of carbohydrates (50.5% on average, of which 14.8% from sugars) and fats (30.5% on average); and similar fiber content (17.5 g/1000 kcal on average).

This standardization of macronutrient composition aimed to minimize the potential influence of dietary differences on the observed outcomes.

The study was conducted at the International Center for the Assessment of Nutritional Status (ICANS, University of Milan, Milan, Italy), as part of a large ongoing open-cohort nutritional study. Patients were recruited between January 2017 and January 2019. At baseline, patients received a full nutritional assessment; based on the assessment, a hypocaloric diet was provided, and a follow-up examination was scheduled. At follow-up, patients were interviewed by a registered dietitian, and the main and secondary outcomes were measured. In this ongoing cohort study, we evaluated the 1-year follow-up examination.

Patients included in this study were self-referring patients seeking a weight loss program, mainly resident in Milan or nearby cities. For aim 2, patients were required to have impaired fasting glucose (fasting glucose >100 mg/dL and <126 mg/dL) [10]. Eligibility criteria were age ≥18 years; not pregnant nor breastfeeding; no condition severely limiting movements and physical activity; no severe cardiovascular, neurological, endocrine, or psychiatric disorder (any condition that, in the opinion of the investigators, would preclude participation in the lifestyle intervention or could significantly affect the study outcomes).

Patients with impaired fasting glucose that showed an RER indicative of glucose oxidation metabolism during fasting were matched with patients with impaired fasting glucose that showed an RER indicative of fat oxidation metabolism during fasting. Patients were matched for key variables affecting the main outcome: age, sex, baseline BMI, baseline waist circumference, baseline arm muscle area, and baseline body fat mass fraction of total body weight.

The study complied with the principles established by the Declaration of Helsinki, and written informed consent was obtained from each subject. The ethics committee of the University of Milan (n. 6/2019) approved the study procedures.

Anthropometry

Body weight, body height, and body fat fraction of total body weight were assessed with anthropometric methods. The anthropometric measurements were collected by a well-trained registered dietitian at the ICANS center. Procedures used are detailed by Lohman and Roche [11].

Body weight was measured to the nearest 100 g with a mechanical column scale graduated to 100 g, and with a capacity of 160 kg (Seca 700, Seca GmbH, Hamburg, Germany). Body height was measured to the nearest 1 mm with a stadiometer graduated to 1 mm, and with a measuring range of 20 to 205 cm (Seca 217, Seca GmbH, Hamburg, Germany). Waist circumference was measured at the approximate midpoint between the lower margin of the last palpable rib and the top of the iliac crest, to the nearest 0.1 cm with an inextensible metric tape, 0.5 cm wide, and graduated to 1 mm (Gima 27341, Gima S.p.A., Gessate, Italy). Biceps, triceps, subscapular, and suprailiac skinfold thicknesses were measured to the nearest 0.1 mm using a skinfold caliper with a 35 mm2 jaw face area, exerting a 10 ± 2 g/mm2 pressure between the jaws, with a range of 0 to 40 mm, calibrated to 0.2 mm (Holtain Tanner/Whitehouse Skinfold Caliper, Croswell, UK).

BMI (kg/m2) was calculated as body weight in kilograms divided by the square of the body height in meters and classified according to the WHO guidelines [12]. Body density (kg/L) and body fat fraction of total body weight were estimated using formulas provided by Durnin and Womersley [13] and Siri [14], respectively.

Indirect Calorimetry

Resting energy expenditure and substrate utilization were measured at baseline with indirect calorimetry.

All measurements were performed early in the morning, after a 12-hour fast, with subjects lying supine, at rest but awake, in a quiet and thermally neutral environment (24 °C). After a 15-minute resting period, O2 consumption and CO2 production were measured using the canopy dilution technique [6], with the patient wearing a transparent ventilated canopy for 30 minutes, sampling gases every 30 seconds. To avoid gas leakages, the subject's head was carefully wrapped with a veil.

Technical details of the indirect calorimeter used (Q-NRG+, Cosmed srl, Rome, Italy) are detailed by Delsoglio et al [15]. Calibration of the flowmeter and gas analyzers was performed according to the manufacturer's instructions and schedule.

For each measurement, data collected during the first 5 minutes were discarded, while data collected during the remaining minutes were averaged (mean) and scaled to provide daily resting gas exchanges. Steady state was defined as the first 5 consecutive stable 30-second readings with a coefficient of variation <10% for VO2 and VCO2, and, when available, data in steady state were preferred. The Weir formula [16] was used to estimate resting energy expenditure from gas exchanges measured at rest by indirect calorimetry.

The RER was defined as the ratio of VCO2 and VO2, and an RER < 0.775 was considered indicative of fat oxidation metabolism, while an RER > 0.925 was considered indicative of glucose oxidation metabolism. The aim was to focus on individuals with a clear predominance of either fat or carbohydrate oxidation, respectively. By selecting these more extreme values, we aimed to minimize the confounding factor of protein metabolism, which can become more significant at intermediate RER values.

Study Size, Quantitative Variables

Sample size was calculated based on the expected difference in fasting glucose at follow-up between the fat oxidation and glucose oxidation groups (10 mg/dL). Considering a SD of fasting glucose in prediabetic patients of 15 mg/dL, we needed at least 37 patients per group with a power of 80%. We enrolled 43 patients per group.

While some quantitative data are presented also as groups defined in the literature (eg, classes of BMI, waist circumference, blood pressure, fasting glucose), we preferred to use continuous variables in the analyses. We did model the outcome as both a continuous and dichotomous variable, the latter to show the overall mean effect of the exposure and defined as reaching a fasting glucose <100 mg/dL at follow-up.

Statistical Methods

Matching with controls was performed using coarsened exact matching, and covariate balance between groups was evaluated by calculating the standardized mean differences across imputations.

Adjusted differences between patients with glucose oxidation RER and matched patients with fat oxidation RER were computed. The differences were adjusted for all matching variables. Adjustment was performed with ordinary least squares regression or logistic regression of the outcome variable, using as independent variables the RER group and the variables to adjust for. Linearity was assumed for all adjustment variables to conserve degrees of freedom in the model, but linearity was both a reasonable assumption in relation to the outcome variable, and matching reduced model dependence. When adjusting for all matching variables, we were less concerned with conserving degrees of freedom, and more with controlling for differences due to variable binning.

To address potential confounding factors, we conducted sensitivity analyses where we additionally matched participants for menopausal status (premenopausal or postmenopausal) and for the presence or absence of metabolic syndrome. The results of these sensitivity analyses are consistent with the primary analysis and are reported in the Supplemental Appendix [17].

Results

Fasting RER and Glucose Metabolism

Overall, we included 10 176 patients that performed both indirect calorimetry and a complete fasting glucose profile, inclusive of insulin and glycated hemoglobin, and their characteristics are reported in Table 1. The overall sample was mainly composed of female patients (7223 (71%), and had a median (quartiles) age of 46 (36, 55) years. The median BMI was 28.3 (25.0, 32.3) kg/m2, but the most prevalent BMI category was that of obesity (3879, 38%), and in particular central obesity (6173 (61%)) as highlighted by the waist circumference categories. In the overall sample, 1502 (15%) and 550 (5%) of patients showed a fat oxidation and glucose oxidation metabolism at rest, respectively. The unadjusted comparison of RER groups shows differences in sex and a general worsening going from a fat oxidation to a glucose oxidation metabolism of anthropometric indices, blood pressure, and fasting glucose metabolism parameters, blood lipid profile, and liver enzymes. To account for differences in sexes [18], we also included stratified analysis in the Supplemental Appendix [17].

Table 1.
Open in new tab

Patients’ characteristics of the overall sample, stratified by RER categories

CharacteristicOverall N = 10 176aFat oxidation RER N = 1502aMixed RER N = 8124aGlucose oxidation RER N = 550aP valueb
Sex<.001
 Female7223 (71%)1178 (78%)5719 (70%)326 (59%)
 Male2953 (29%)324 (22%)2405 (30%)224 (41%)
Age (years)46 (36, 55)46 (35, 55)46 (36, 55)46 (36, 55).10
BMI, kg/m2)28.3 (25.0, 32.3)28.2 (24.8, 32.4)28.3 (25.0, 32.3)28.9 (25.6, 32.9).029
BMI categories.012
 Underweight183 (1.8%)38 (2.5%)137 (1.7%)8 (1.5%)
 Normal weight2340 (23%)363 (24%)1874 (23%)103 (19%)
 Overweight3755 (37%)540 (36%)3011 (37%)204 (37%)
 Obesity class I2428 (24%)327 (22%)1958 (24%)143 (26%)
 Obesity class II996 (9.8%)150 (10%)777 (9.6%)69 (13%)
 Obesity class III455 (4.5%)80 (5.3%)352 (4.3%)23 (4.2%)
Waist circumference (cm)96 (86, 107)94 (84, 106)96 (86, 107)98 (89, 109)<.001
Waist circumference categories.10
 Normal1845 (18%)302 (20%)1459 (18%)84 (15%)
 Elevated2120 (21%)310 (21%)1697 (21%)113 (21%)
 Central obesity6173 (61%)885 (59%)4935 (61%)353 (64%)
Body fat percentage39 (34, 43)39 (35, 43)39 (34, 42)38 (33, 42)<.001
Systolic blood pressure (mmHg)120 (110, 130)120 (110, 130)120 (110, 130)120 (110, 130)<.001
Diastolic blood pressure (mmHg)80 (70, 80)80 (70, 80)80 (70, 82)80 (70, 85)<.001
Blood pressure categories<.001
 Normal5197 (57%)841 (61%)4102 (56%)254 (50%)
 Elevated386 (4.2%)56 (4.1%)314 (4.3%)16 (3.1%)
 Stage 12823 (31%)372 (27%)2274 (31%)177 (35%)
 Stage 2779 (8.5%)110 (8.0%)605 (8.3%)64 (13%)
RER0.83 (0.79, 0.87)0.75 (0.73, 0.77)0.84 (0.81, 0.87)0.94 (0.93, 0.95)<.001
Resting energy expenditure (kcal/day)1451 (1304, 1666)1462 (1313, 1648)1445 (1300, 1663)1504 (1318, 1759)<.001
Glucose (mg/dL)95 (89, 102)94 (88, 101)95 (89, 102)96 (90, 104)<.001
Glucose categories.008
 Normal6791 (70%)1035 (72%)5414 (70%)342 (65%)
 Prediabetes2721 (28%)368 (26%)2188 (28%)165 (31%)
 Diabetes196 (2.0%)25 (1.8%)153 (2.0%)18 (3.4%)
Insulin (mIU/L)10 (7, 15)9 (6, 14)10 (7, 15)11 (8, 17)<.001
HOMA-IR2.28 (1.54, 3.59)2.10 (1.40, 3.29)2.30 (1.55, 3.59)2.76 (1.80, 4.03)<.001
HbA1c (%5.44 (5.20, 5.71)5.41 (5.17, 5.67)5.44 (5.20, 5.71)5.49 (5.21, 5.74).078
Total cholesterol (mg/dL)205 (178, 234)205 (176, 233)205 (178, 234)207 (181, 234).4
High-density lipoprotein cholesterol (mg/dL)59 (49, 71)61 (50, 73)59 (49, 70)56 (46, 68)<.001
Low-density lipoprotein cholesterol (mg/dL)131 (107, 158)129 (104, 154)131 (107, 159)132 (110, 158).017
Triglycerides (mg/dL)87 (63, 124)82 (60, 117)87 (64, 124)97 (70, 145)<.001
AST/GOT (IU/L)18.4 (15.5, 22.4)18.2 (15.3, 22.6)18.4 (15.5, 22.3)18.9 (16.0, 23.1).10
ALT/GPT (IU/L)18 (14, 27)18 (13, 26)18 (14, 27)20 (15, 28)<.001
GGT (IU/L)18 (12, 27)17 (12, 26)18 (12, 27)18 (13, 30).004
CharacteristicOverall N = 10 176aFat oxidation RER N = 1502aMixed RER N = 8124aGlucose oxidation RER N = 550aP valueb
Sex<.001
 Female7223 (71%)1178 (78%)5719 (70%)326 (59%)
 Male2953 (29%)324 (22%)2405 (30%)224 (41%)
Age (years)46 (36, 55)46 (35, 55)46 (36, 55)46 (36, 55).10
BMI, kg/m2)28.3 (25.0, 32.3)28.2 (24.8, 32.4)28.3 (25.0, 32.3)28.9 (25.6, 32.9).029
BMI categories.012
 Underweight183 (1.8%)38 (2.5%)137 (1.7%)8 (1.5%)
 Normal weight2340 (23%)363 (24%)1874 (23%)103 (19%)
 Overweight3755 (37%)540 (36%)3011 (37%)204 (37%)
 Obesity class I2428 (24%)327 (22%)1958 (24%)143 (26%)
 Obesity class II996 (9.8%)150 (10%)777 (9.6%)69 (13%)
 Obesity class III455 (4.5%)80 (5.3%)352 (4.3%)23 (4.2%)
Waist circumference (cm)96 (86, 107)94 (84, 106)96 (86, 107)98 (89, 109)<.001
Waist circumference categories.10
 Normal1845 (18%)302 (20%)1459 (18%)84 (15%)
 Elevated2120 (21%)310 (21%)1697 (21%)113 (21%)
 Central obesity6173 (61%)885 (59%)4935 (61%)353 (64%)
Body fat percentage39 (34, 43)39 (35, 43)39 (34, 42)38 (33, 42)<.001
Systolic blood pressure (mmHg)120 (110, 130)120 (110, 130)120 (110, 130)120 (110, 130)<.001
Diastolic blood pressure (mmHg)80 (70, 80)80 (70, 80)80 (70, 82)80 (70, 85)<.001
Blood pressure categories<.001
 Normal5197 (57%)841 (61%)4102 (56%)254 (50%)
 Elevated386 (4.2%)56 (4.1%)314 (4.3%)16 (3.1%)
 Stage 12823 (31%)372 (27%)2274 (31%)177 (35%)
 Stage 2779 (8.5%)110 (8.0%)605 (8.3%)64 (13%)
RER0.83 (0.79, 0.87)0.75 (0.73, 0.77)0.84 (0.81, 0.87)0.94 (0.93, 0.95)<.001
Resting energy expenditure (kcal/day)1451 (1304, 1666)1462 (1313, 1648)1445 (1300, 1663)1504 (1318, 1759)<.001
Glucose (mg/dL)95 (89, 102)94 (88, 101)95 (89, 102)96 (90, 104)<.001
Glucose categories.008
 Normal6791 (70%)1035 (72%)5414 (70%)342 (65%)
 Prediabetes2721 (28%)368 (26%)2188 (28%)165 (31%)
 Diabetes196 (2.0%)25 (1.8%)153 (2.0%)18 (3.4%)
Insulin (mIU/L)10 (7, 15)9 (6, 14)10 (7, 15)11 (8, 17)<.001
HOMA-IR2.28 (1.54, 3.59)2.10 (1.40, 3.29)2.30 (1.55, 3.59)2.76 (1.80, 4.03)<.001
HbA1c (%5.44 (5.20, 5.71)5.41 (5.17, 5.67)5.44 (5.20, 5.71)5.49 (5.21, 5.74).078
Total cholesterol (mg/dL)205 (178, 234)205 (176, 233)205 (178, 234)207 (181, 234).4
High-density lipoprotein cholesterol (mg/dL)59 (49, 71)61 (50, 73)59 (49, 70)56 (46, 68)<.001
Low-density lipoprotein cholesterol (mg/dL)131 (107, 158)129 (104, 154)131 (107, 159)132 (110, 158).017
Triglycerides (mg/dL)87 (63, 124)82 (60, 117)87 (64, 124)97 (70, 145)<.001
AST/GOT (IU/L)18.4 (15.5, 22.4)18.2 (15.3, 22.6)18.4 (15.5, 22.3)18.9 (16.0, 23.1).10
ALT/GPT (IU/L)18 (14, 27)18 (13, 26)18 (14, 27)20 (15, 28)<.001
GGT (IU/L)18 (12, 27)17 (12, 26)18 (12, 27)18 (13, 30).004

Bold values indicate P-values < .05.

an (%); median (Q1, Q3).

bPearson's Chi-squared test; Kruskal–Wallis rank sum test.

Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; GGT, Gamma-glutamyl transferase; GOT, Glutamate oxaloacetate transaminase; GPT, Glutamate pyruvate transaminase; HbA1c, glycated hemoglobin; HOMA-IR, Homeostatic Model Assessment of Insulin Resistance; RER, respiratory exchange ratio.

Table 1.
Open in new tab

Patients’ characteristics of the overall sample, stratified by RER categories

CharacteristicOverall N = 10 176aFat oxidation RER N = 1502aMixed RER N = 8124aGlucose oxidation RER N = 550aP valueb
Sex<.001
 Female7223 (71%)1178 (78%)5719 (70%)326 (59%)
 Male2953 (29%)324 (22%)2405 (30%)224 (41%)
Age (years)46 (36, 55)46 (35, 55)46 (36, 55)46 (36, 55).10
BMI, kg/m2)28.3 (25.0, 32.3)28.2 (24.8, 32.4)28.3 (25.0, 32.3)28.9 (25.6, 32.9).029
BMI categories.012
 Underweight183 (1.8%)38 (2.5%)137 (1.7%)8 (1.5%)
 Normal weight2340 (23%)363 (24%)1874 (23%)103 (19%)
 Overweight3755 (37%)540 (36%)3011 (37%)204 (37%)
 Obesity class I2428 (24%)327 (22%)1958 (24%)143 (26%)
 Obesity class II996 (9.8%)150 (10%)777 (9.6%)69 (13%)
 Obesity class III455 (4.5%)80 (5.3%)352 (4.3%)23 (4.2%)
Waist circumference (cm)96 (86, 107)94 (84, 106)96 (86, 107)98 (89, 109)<.001
Waist circumference categories.10
 Normal1845 (18%)302 (20%)1459 (18%)84 (15%)
 Elevated2120 (21%)310 (21%)1697 (21%)113 (21%)
 Central obesity6173 (61%)885 (59%)4935 (61%)353 (64%)
Body fat percentage39 (34, 43)39 (35, 43)39 (34, 42)38 (33, 42)<.001
Systolic blood pressure (mmHg)120 (110, 130)120 (110, 130)120 (110, 130)120 (110, 130)<.001
Diastolic blood pressure (mmHg)80 (70, 80)80 (70, 80)80 (70, 82)80 (70, 85)<.001
Blood pressure categories<.001
 Normal5197 (57%)841 (61%)4102 (56%)254 (50%)
 Elevated386 (4.2%)56 (4.1%)314 (4.3%)16 (3.1%)
 Stage 12823 (31%)372 (27%)2274 (31%)177 (35%)
 Stage 2779 (8.5%)110 (8.0%)605 (8.3%)64 (13%)
RER0.83 (0.79, 0.87)0.75 (0.73, 0.77)0.84 (0.81, 0.87)0.94 (0.93, 0.95)<.001
Resting energy expenditure (kcal/day)1451 (1304, 1666)1462 (1313, 1648)1445 (1300, 1663)1504 (1318, 1759)<.001
Glucose (mg/dL)95 (89, 102)94 (88, 101)95 (89, 102)96 (90, 104)<.001
Glucose categories.008
 Normal6791 (70%)1035 (72%)5414 (70%)342 (65%)
 Prediabetes2721 (28%)368 (26%)2188 (28%)165 (31%)
 Diabetes196 (2.0%)25 (1.8%)153 (2.0%)18 (3.4%)
Insulin (mIU/L)10 (7, 15)9 (6, 14)10 (7, 15)11 (8, 17)<.001
HOMA-IR2.28 (1.54, 3.59)2.10 (1.40, 3.29)2.30 (1.55, 3.59)2.76 (1.80, 4.03)<.001
HbA1c (%5.44 (5.20, 5.71)5.41 (5.17, 5.67)5.44 (5.20, 5.71)5.49 (5.21, 5.74).078
Total cholesterol (mg/dL)205 (178, 234)205 (176, 233)205 (178, 234)207 (181, 234).4
High-density lipoprotein cholesterol (mg/dL)59 (49, 71)61 (50, 73)59 (49, 70)56 (46, 68)<.001
Low-density lipoprotein cholesterol (mg/dL)131 (107, 158)129 (104, 154)131 (107, 159)132 (110, 158).017
Triglycerides (mg/dL)87 (63, 124)82 (60, 117)87 (64, 124)97 (70, 145)<.001
AST/GOT (IU/L)18.4 (15.5, 22.4)18.2 (15.3, 22.6)18.4 (15.5, 22.3)18.9 (16.0, 23.1).10
ALT/GPT (IU/L)18 (14, 27)18 (13, 26)18 (14, 27)20 (15, 28)<.001
GGT (IU/L)18 (12, 27)17 (12, 26)18 (12, 27)18 (13, 30).004
CharacteristicOverall N = 10 176aFat oxidation RER N = 1502aMixed RER N = 8124aGlucose oxidation RER N = 550aP valueb
Sex<.001
 Female7223 (71%)1178 (78%)5719 (70%)326 (59%)
 Male2953 (29%)324 (22%)2405 (30%)224 (41%)
Age (years)46 (36, 55)46 (35, 55)46 (36, 55)46 (36, 55).10
BMI, kg/m2)28.3 (25.0, 32.3)28.2 (24.8, 32.4)28.3 (25.0, 32.3)28.9 (25.6, 32.9).029
BMI categories.012
 Underweight183 (1.8%)38 (2.5%)137 (1.7%)8 (1.5%)
 Normal weight2340 (23%)363 (24%)1874 (23%)103 (19%)
 Overweight3755 (37%)540 (36%)3011 (37%)204 (37%)
 Obesity class I2428 (24%)327 (22%)1958 (24%)143 (26%)
 Obesity class II996 (9.8%)150 (10%)777 (9.6%)69 (13%)
 Obesity class III455 (4.5%)80 (5.3%)352 (4.3%)23 (4.2%)
Waist circumference (cm)96 (86, 107)94 (84, 106)96 (86, 107)98 (89, 109)<.001
Waist circumference categories.10
 Normal1845 (18%)302 (20%)1459 (18%)84 (15%)
 Elevated2120 (21%)310 (21%)1697 (21%)113 (21%)
 Central obesity6173 (61%)885 (59%)4935 (61%)353 (64%)
Body fat percentage39 (34, 43)39 (35, 43)39 (34, 42)38 (33, 42)<.001
Systolic blood pressure (mmHg)120 (110, 130)120 (110, 130)120 (110, 130)120 (110, 130)<.001
Diastolic blood pressure (mmHg)80 (70, 80)80 (70, 80)80 (70, 82)80 (70, 85)<.001
Blood pressure categories<.001
 Normal5197 (57%)841 (61%)4102 (56%)254 (50%)
 Elevated386 (4.2%)56 (4.1%)314 (4.3%)16 (3.1%)
 Stage 12823 (31%)372 (27%)2274 (31%)177 (35%)
 Stage 2779 (8.5%)110 (8.0%)605 (8.3%)64 (13%)
RER0.83 (0.79, 0.87)0.75 (0.73, 0.77)0.84 (0.81, 0.87)0.94 (0.93, 0.95)<.001
Resting energy expenditure (kcal/day)1451 (1304, 1666)1462 (1313, 1648)1445 (1300, 1663)1504 (1318, 1759)<.001
Glucose (mg/dL)95 (89, 102)94 (88, 101)95 (89, 102)96 (90, 104)<.001
Glucose categories.008
 Normal6791 (70%)1035 (72%)5414 (70%)342 (65%)
 Prediabetes2721 (28%)368 (26%)2188 (28%)165 (31%)
 Diabetes196 (2.0%)25 (1.8%)153 (2.0%)18 (3.4%)
Insulin (mIU/L)10 (7, 15)9 (6, 14)10 (7, 15)11 (8, 17)<.001
HOMA-IR2.28 (1.54, 3.59)2.10 (1.40, 3.29)2.30 (1.55, 3.59)2.76 (1.80, 4.03)<.001
HbA1c (%5.44 (5.20, 5.71)5.41 (5.17, 5.67)5.44 (5.20, 5.71)5.49 (5.21, 5.74).078
Total cholesterol (mg/dL)205 (178, 234)205 (176, 233)205 (178, 234)207 (181, 234).4
High-density lipoprotein cholesterol (mg/dL)59 (49, 71)61 (50, 73)59 (49, 70)56 (46, 68)<.001
Low-density lipoprotein cholesterol (mg/dL)131 (107, 158)129 (104, 154)131 (107, 159)132 (110, 158).017
Triglycerides (mg/dL)87 (63, 124)82 (60, 117)87 (64, 124)97 (70, 145)<.001
AST/GOT (IU/L)18.4 (15.5, 22.4)18.2 (15.3, 22.6)18.4 (15.5, 22.3)18.9 (16.0, 23.1).10
ALT/GPT (IU/L)18 (14, 27)18 (13, 26)18 (14, 27)20 (15, 28)<.001
GGT (IU/L)18 (12, 27)17 (12, 26)18 (12, 27)18 (13, 30).004

Bold values indicate P-values < .05.

an (%); median (Q1, Q3).

bPearson's Chi-squared test; Kruskal–Wallis rank sum test.

Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; GGT, Gamma-glutamyl transferase; GOT, Glutamate oxaloacetate transaminase; GPT, Glutamate pyruvate transaminase; HbA1c, glycated hemoglobin; HOMA-IR, Homeostatic Model Assessment of Insulin Resistance; RER, respiratory exchange ratio.

Table 2 shows the adjusted association between RER and fasting glucose metabolism. In the overall sample, a higher RER was associated with higher fasting glucose (1.7; 95% CI 0.66, 2.8; P = .002), higher fasting insulin, (1.9; 95% CI 1.3, 2.6; P ≤ .001), and consequently higher Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) (0.52; 95% CI 0.34, 0.70; P ≤ .001).

Table 2.
Open in new tab

Linear regression models of glucose, insulin, and HOMA-IR

 Glucose (mg/dL)Insulin (mIU/L)Homeostatic model assessment
CharacteristicBeta95% CIP valueBeta95% CIP valueBeta95% CIP value
Age (years)0.240.23, 0.26<.001−0.04−0.05, −0.03<.0010.00−0.01, 0.00.005
Sex
 Female——————
 Male5.55.1, 6.0<.0012.32.1, 2.6<.0010.740.67, 0.82<.001
BMI, kg/m20.480.44, 0.52<.0010.690.67, 0.71<.0010.180.18, 0.19<.001
Respiratory Exchange Ratio1.70.66, 2.8.0021.91.3, 2.6<.0010.520.34, 0.70<.001
 Glucose (mg/dL)Insulin (mIU/L)Homeostatic model assessment
CharacteristicBeta95% CIP valueBeta95% CIP valueBeta95% CIP value
Age (years)0.240.23, 0.26<.001−0.04−0.05, −0.03<.0010.00−0.01, 0.00.005
Sex
 Female——————
 Male5.55.1, 6.0<.0012.32.1, 2.6<.0010.740.67, 0.82<.001
BMI, kg/m20.480.44, 0.52<.0010.690.67, 0.71<.0010.180.18, 0.19<.001
Respiratory Exchange Ratio1.70.66, 2.8.0021.91.3, 2.6<.0010.520.34, 0.70<.001

Bold values indicate P-values < .05.

Abbreviation: BMI, body mass index; HOMA-IR, Homeostatic Model Assessment of Insulin Resistance; RER, respiratory exchange ratio.

Table 2.
Open in new tab

Linear regression models of glucose, insulin, and HOMA-IR

 Glucose (mg/dL)Insulin (mIU/L)Homeostatic model assessment
CharacteristicBeta95% CIP valueBeta95% CIP valueBeta95% CIP value
Age (years)0.240.23, 0.26<.001−0.04−0.05, −0.03<.0010.00−0.01, 0.00.005
Sex
 Female——————
 Male5.55.1, 6.0<.0012.32.1, 2.6<.0010.740.67, 0.82<.001
BMI, kg/m20.480.44, 0.52<.0010.690.67, 0.71<.0010.180.18, 0.19<.001
Respiratory Exchange Ratio1.70.66, 2.8.0021.91.3, 2.6<.0010.520.34, 0.70<.001
 Glucose (mg/dL)Insulin (mIU/L)Homeostatic model assessment
CharacteristicBeta95% CIP valueBeta95% CIP valueBeta95% CIP value
Age (years)0.240.23, 0.26<.001−0.04−0.05, −0.03<.0010.00−0.01, 0.00.005
Sex
 Female——————
 Male5.55.1, 6.0<.0012.32.1, 2.6<.0010.740.67, 0.82<.001
BMI, kg/m20.480.44, 0.52<.0010.690.67, 0.71<.0010.180.18, 0.19<.001
Respiratory Exchange Ratio1.70.66, 2.8.0021.91.3, 2.6<.0010.520.34, 0.70<.001

Bold values indicate P-values < .05.

Abbreviation: BMI, body mass index; HOMA-IR, Homeostatic Model Assessment of Insulin Resistance; RER, respiratory exchange ratio.

Fasting RER and Impaired Fasting Glucose Resolution

Table 3 shows characteristics of the 86 matched impaired fasting glucose patients with a fat oxidation or glucose oxidation RER, while Table 4 shows unadjusted fasting glucose differences between baseline and follow-up in both groups. While both groups significantly reduced fasting glucose at follow-up, the fat oxidation group reduction was greater (+5.9; 95% CI 1.4, 10; P = .011). Consequently, the fat oxidation group showed a higher probability of normalizing fasting glycemia within 1-year of beginning the lifestyle intervention (log(odds ratio) −0.89 (95% CI −1.8, −0.03; P = .046)).

Table 3.
Open in new tab

Matched impaired fasting glucose patients with either fat oxidation or glucose oxidation RER

CharacteristicFat oxidation RER N = 43aGlucose oxidation RER N = 43a
Sex
 Female29 (67%)19 (44%)
 Male14 (33%)24 (56%)
Age (years)54 (44, 59)54 (43, 64)
Body mass index (kg/m2)34.1 (29.2, 37.0)31.3 (28.6, 35.4)
Waist circumference (cm)110 (100, 119)104 (99, 114)
Arm muscle area (cm2)56 (43, 65)61 (47, 69)
Body fat fraction of total body weight, as %42.7 (39.3, 45.9)39.3 (33.7, 44.3)
CharacteristicFat oxidation RER N = 43aGlucose oxidation RER N = 43a
Sex
 Female29 (67%)19 (44%)
 Male14 (33%)24 (56%)
Age (years)54 (44, 59)54 (43, 64)
Body mass index (kg/m2)34.1 (29.2, 37.0)31.3 (28.6, 35.4)
Waist circumference (cm)110 (100, 119)104 (99, 114)
Arm muscle area (cm2)56 (43, 65)61 (47, 69)
Body fat fraction of total body weight, as %42.7 (39.3, 45.9)39.3 (33.7, 44.3)

an (%); median (Q1, Q3).

Abbreviations: RER, respiratory exchange ratio.

Table 3.
Open in new tab

Matched impaired fasting glucose patients with either fat oxidation or glucose oxidation RER

CharacteristicFat oxidation RER N = 43aGlucose oxidation RER N = 43a
Sex
 Female29 (67%)19 (44%)
 Male14 (33%)24 (56%)
Age (years)54 (44, 59)54 (43, 64)
Body mass index (kg/m2)34.1 (29.2, 37.0)31.3 (28.6, 35.4)
Waist circumference (cm)110 (100, 119)104 (99, 114)
Arm muscle area (cm2)56 (43, 65)61 (47, 69)
Body fat fraction of total body weight, as %42.7 (39.3, 45.9)39.3 (33.7, 44.3)
CharacteristicFat oxidation RER N = 43aGlucose oxidation RER N = 43a
Sex
 Female29 (67%)19 (44%)
 Male14 (33%)24 (56%)
Age (years)54 (44, 59)54 (43, 64)
Body mass index (kg/m2)34.1 (29.2, 37.0)31.3 (28.6, 35.4)
Waist circumference (cm)110 (100, 119)104 (99, 114)
Arm muscle area (cm2)56 (43, 65)61 (47, 69)
Body fat fraction of total body weight, as %42.7 (39.3, 45.9)39.3 (33.7, 44.3)

an (%); median (Q1, Q3).

Abbreviations: RER, respiratory exchange ratio.

Table 4.
Open in new tab

Unadjusted glucose differences between baseline and follow-up in the glucose oxidation and fat oxidation group

CharacteristicBaselineaFollow-upaDifferenceb95% CIbP valueb
Glucose oxidation RER
 Glucose (mg/dL)108 (103, 113)101 (95, 111)5.71.9, 9.5.004
Fat oxidation RER
 Glucose (mg/dL)107 (102, 112)99 (91, 107)117.1, 15<.001
CharacteristicBaselineaFollow-upaDifferenceb95% CIbP valueb
Glucose oxidation RER
 Glucose (mg/dL)108 (103, 113)101 (95, 111)5.71.9, 9.5.004
Fat oxidation RER
 Glucose (mg/dL)107 (102, 112)99 (91, 107)117.1, 15<.001

Bold values indicate P-values < .05.

aMedian (Q1, Q3).

bWelch 2-sample t-test.

Abbreviation: RER, respiratory exchange ratio

Table 4.
Open in new tab

Unadjusted glucose differences between baseline and follow-up in the glucose oxidation and fat oxidation group

CharacteristicBaselineaFollow-upaDifferenceb95% CIbP valueb
Glucose oxidation RER
 Glucose (mg/dL)108 (103, 113)101 (95, 111)5.71.9, 9.5.004
Fat oxidation RER
 Glucose (mg/dL)107 (102, 112)99 (91, 107)117.1, 15<.001
CharacteristicBaselineaFollow-upaDifferenceb95% CIbP valueb
Glucose oxidation RER
 Glucose (mg/dL)108 (103, 113)101 (95, 111)5.71.9, 9.5.004
Fat oxidation RER
 Glucose (mg/dL)107 (102, 112)99 (91, 107)117.1, 15<.001

Bold values indicate P-values < .05.

aMedian (Q1, Q3).

bWelch 2-sample t-test.

Abbreviation: RER, respiratory exchange ratio

Finally, Table 5 show intragroup differences in anthropometric parameters between baseline and follow-up: both groups were able to reduce body weight, BMI, waist circumference, and body fat fraction of total body weight. Although comparing anthropometric parameters at follow-up between the RER groups (Table 6) shows that while differences in weight loss were similar in the 2 groups (−0.39; 95% CI −3.5, 2.7; P = .8), body fat was higher at follow-up in the glucose oxidation group (+1.2; 95% CI 0.07, 2.4; P = .038).

Table 5.
Open in new tab

Intragroup differences in anthropometric parameters between baseline and follow-up

CharacteristicBaselineaFollow-upaDifferenceb95% CIbP-valueb
Body weight (kg)
 Fat oxidation RER93 (80, 111)85 (70, 104)5.32.7, 8.0<.001
 Glucose oxidation RER88 (81, 106)82 (76, 99)5.73.9, 7.5<.001
Body mass index (kg/m2)
 Fat oxidation RER34.1 (29.2, 37.0)30.8 (26.5, 34.1)2.01.1, 2.9<.001
 Glucose oxidation RER31.3 (28.6, 35.4)29.4 (26.4, 32.7)2.11.4, 2.8<.001
Waist circumference (cm)
 Fat oxidation RER110 (100, 119)99 (90, 111)6.24.6, 7.8<.001
 Glucose oxidation RER104 (99, 114)100 (94, 108)5.43.7, 7.1<.001
Body fat fraction of total body weight, as %
 Fat oxidation RER43 (39, 46)40 (37, 44)2.61.7, 3.4<.001
 Glucose oxidation RER39 (34, 44)39 (30, 42)1.60.79, 2.4<.001
CharacteristicBaselineaFollow-upaDifferenceb95% CIbP-valueb
Body weight (kg)
 Fat oxidation RER93 (80, 111)85 (70, 104)5.32.7, 8.0<.001
 Glucose oxidation RER88 (81, 106)82 (76, 99)5.73.9, 7.5<.001
Body mass index (kg/m2)
 Fat oxidation RER34.1 (29.2, 37.0)30.8 (26.5, 34.1)2.01.1, 2.9<.001
 Glucose oxidation RER31.3 (28.6, 35.4)29.4 (26.4, 32.7)2.11.4, 2.8<.001
Waist circumference (cm)
 Fat oxidation RER110 (100, 119)99 (90, 111)6.24.6, 7.8<.001
 Glucose oxidation RER104 (99, 114)100 (94, 108)5.43.7, 7.1<.001
Body fat fraction of total body weight, as %
 Fat oxidation RER43 (39, 46)40 (37, 44)2.61.7, 3.4<.001
 Glucose oxidation RER39 (34, 44)39 (30, 42)1.60.79, 2.4<.001

Bold values indicate P-values < .05.

aMedian (Q1, Q3).

bPaired t-test.

Abbreviation: RER, respiratory exchange ratio.

Table 5.
Open in new tab

Intragroup differences in anthropometric parameters between baseline and follow-up

CharacteristicBaselineaFollow-upaDifferenceb95% CIbP-valueb
Body weight (kg)
 Fat oxidation RER93 (80, 111)85 (70, 104)5.32.7, 8.0<.001
 Glucose oxidation RER88 (81, 106)82 (76, 99)5.73.9, 7.5<.001
Body mass index (kg/m2)
 Fat oxidation RER34.1 (29.2, 37.0)30.8 (26.5, 34.1)2.01.1, 2.9<.001
 Glucose oxidation RER31.3 (28.6, 35.4)29.4 (26.4, 32.7)2.11.4, 2.8<.001
Waist circumference (cm)
 Fat oxidation RER110 (100, 119)99 (90, 111)6.24.6, 7.8<.001
 Glucose oxidation RER104 (99, 114)100 (94, 108)5.43.7, 7.1<.001
Body fat fraction of total body weight, as %
 Fat oxidation RER43 (39, 46)40 (37, 44)2.61.7, 3.4<.001
 Glucose oxidation RER39 (34, 44)39 (30, 42)1.60.79, 2.4<.001
CharacteristicBaselineaFollow-upaDifferenceb95% CIbP-valueb
Body weight (kg)
 Fat oxidation RER93 (80, 111)85 (70, 104)5.32.7, 8.0<.001
 Glucose oxidation RER88 (81, 106)82 (76, 99)5.73.9, 7.5<.001
Body mass index (kg/m2)
 Fat oxidation RER34.1 (29.2, 37.0)30.8 (26.5, 34.1)2.01.1, 2.9<.001
 Glucose oxidation RER31.3 (28.6, 35.4)29.4 (26.4, 32.7)2.11.4, 2.8<.001
Waist circumference (cm)
 Fat oxidation RER110 (100, 119)99 (90, 111)6.24.6, 7.8<.001
 Glucose oxidation RER104 (99, 114)100 (94, 108)5.43.7, 7.1<.001
Body fat fraction of total body weight, as %
 Fat oxidation RER43 (39, 46)40 (37, 44)2.61.7, 3.4<.001
 Glucose oxidation RER39 (34, 44)39 (30, 42)1.60.79, 2.4<.001

Bold values indicate P-values < .05.

aMedian (Q1, Q3).

bPaired t-test.

Abbreviation: RER, respiratory exchange ratio.

Table 6.
Open in new tab

Baseline adjusted differences in anthropometric parameters at follow-up between the glucose oxidation and fat oxidation group

 Body weight (kg)Body mass index (kg/m2)Waist circumference (cm)Body fat fraction of total body weight, as %
CharacteristicBeta95% CIP valueBeta95% CIP valueBeta95% CIP valueBeta95% CIP value
Baseline value0.980.89, 1.1<.0011.00.90, 1.1<.0010.930.85, 1.0<.0011.11.0, 1.2<.001
RER categories
 Fat oxidation RER————————
 Glucose oxidation RER−0.39−3.5, 2.70.8−0.09−1.2, 1.0.90.72−1.5, 2.9.51.20.07, 2.4.038
 Body weight (kg)Body mass index (kg/m2)Waist circumference (cm)Body fat fraction of total body weight, as %
CharacteristicBeta95% CIP valueBeta95% CIP valueBeta95% CIP valueBeta95% CIP value
Baseline value0.980.89, 1.1<.0011.00.90, 1.1<.0010.930.85, 1.0<.0011.11.0, 1.2<.001
RER categories
 Fat oxidation RER————————
 Glucose oxidation RER−0.39−3.5, 2.70.8−0.09−1.2, 1.0.90.72−1.5, 2.9.51.20.07, 2.4.038

Bold values indicate P-values < .05.

Abbreviation: RER, respiratory exchange ratio.

Table 6.
Open in new tab

Baseline adjusted differences in anthropometric parameters at follow-up between the glucose oxidation and fat oxidation group

 Body weight (kg)Body mass index (kg/m2)Waist circumference (cm)Body fat fraction of total body weight, as %
CharacteristicBeta95% CIP valueBeta95% CIP valueBeta95% CIP valueBeta95% CIP value
Baseline value0.980.89, 1.1<.0011.00.90, 1.1<.0010.930.85, 1.0<.0011.11.0, 1.2<.001
RER categories
 Fat oxidation RER————————
 Glucose oxidation RER−0.39−3.5, 2.70.8−0.09−1.2, 1.0.90.72−1.5, 2.9.51.20.07, 2.4.038
 Body weight (kg)Body mass index (kg/m2)Waist circumference (cm)Body fat fraction of total body weight, as %
CharacteristicBeta95% CIP valueBeta95% CIP valueBeta95% CIP valueBeta95% CIP value
Baseline value0.980.89, 1.1<.0011.00.90, 1.1<.0010.930.85, 1.0<.0011.11.0, 1.2<.001
RER categories
 Fat oxidation RER————————
 Glucose oxidation RER−0.39−3.5, 2.70.8−0.09−1.2, 1.0.90.72−1.5, 2.9.51.20.07, 2.4.038

Bold values indicate P-values < .05.

Abbreviation: RER, respiratory exchange ratio.

The sensitivity analyses, which included additional matching for menopausal status and metabolic syndrome status, yielded results similar to those of the primary analysis. These findings are detailed in the Supplemental Appendix [17].

Discussion

In this study, we demonstrate that extreme ranges of fasting RER (RER < 0.775 and RER > 0.925) are indicative of glucose metabolism and metabolic flexibility. Furthermore, we found that patients with impaired fasting glucose exhibiting a fat oxidation RER are more likely to normalize fasting glycemia within 1 year of being prescribed a lifestyle intervention than those with a glucose oxidation RER. While the fat oxidation group experienced greater fasting glucose reduction, weight loss was similar between the 2 groups, albeit with a greater fraction of lean mass loss in the glucose oxidation group.

The relationship between metabolic flexibility and glucose metabolism has already been established [19-21]. To our knowledge, the use of fasting RER to describe this relationship at an individual level has not yet been pursued. Fasting RER, an easily obtainable parameter routinely collected in nutritional clinical centers, has thus the potential to become a widely used tool for detecting a patient's metabolic flexibility status. Nonetheless, fasting RER has several shortcomings when compared with reference methods. Firstly, it can change in an individual due to factors other than metabolic flexibility. The duration of the fast is a major determinant, as prolonged fasting promotes a shift towards fat oxidation and a consequent decrease in RER [22]. Additionally, dietary habits, particularly a high-carbohydrate diet, can influence RER by initially sustaining glycogen stores and carbohydrate utilization [23]. Our findings from a large cohort of over 10 000 individuals show a clear association between higher fasting RER and glucose metabolism alterations commonly observed in metabolically inflexible patients. As detailed in Table 2, a higher RER was associated with higher fasting glucose, higher fasting insulin, and consequently higher HOMA-IR. These associations suggest that even a single fasting RER measurement can provide valuable insights into an individual's metabolic health and risk for prediabetes. This is consistent with other studies that have found a prognostic value of high fasting RER in relation to fat gain and metabolic health [24, 25].

Current research indicates a strong association between impaired metabolic flexibility and prediabetes. Prediabetic individuals often exhibit a reduced ability to switch between glucose and fatty acid oxidation, contributing to elevated blood glucose levels and insulin resistance [2]. This metabolic inflexibility arises from a complex interplay of factors, including insulin resistance, mitochondrial dysfunction, and lifestyle choices [26]. The inability to efficiently utilize both glucose and fatty acids not only increases the risk of progression to type 2 diabetes but also elevates the risk of other comorbidities [27]. Our study confirms that metabolic flexibility, as indicated by fasting RER, is associated with both impaired fasting glucose resolution and improvements in fasting glucose. We found that individuals with a lower fasting RER, suggesting a greater ability to utilize fats for energy, were more likely to achieve normal fasting glucose levels after a lifestyle intervention.

In this paper, we show that metabolic inflexibility can significantly impact the quality of weight loss, potentially leading to a greater loss of fat-free mass during a diet. Studies have shown that individuals with metabolic inflexibility exhibit reduced fat oxidation rates, even during fasting conditions or low-carbohydrate diets, leading to increased fat accumulation and difficulty losing weight [28]. This preference for glucose as the primary fuel source can also result in muscle protein breakdown, further compromising body composition and metabolic rate [29].

This study provides valuable insights into the relationship between metabolic flexibility and diabetes resolution. A key strength lies in the large sample size, which allowed for precise matching of impaired fasting glucose patients based on their metabolic profiles and enabled the investigation of clinically relevant outcomes like diabetes remission. Furthermore, the detailed characterization of participants' nutritional status at baseline strengthens the study's ability to identify factors associated with metabolic health. However, the lack of a reference method to directly assess metabolic flexibility, such as an insulin clamp or incremental exercise testing with indirect calorimetry, represents a limitation. Relying solely on fasting measures may not fully capture the dynamic changes in substrate utilization that characterize metabolic flexibility. Nonetheless, this pragmatic approach enabled the inclusion of a large cohort, providing valuable real-world data on the association between fasting metabolic profiles and long-term health outcomes. Moreover, we selected patients solely based on fasting glucose, and the assessment of glycated hemoglobin could have provided a greater understanding of the prediabetes phenotype [30]. The overnight fast was used to standardize the measurement condition, although diet prior the assessment was not standardized. RER and insulin were not systematically re-evaluated at follow-up, limiting our ability to assess changes in metabolic flexibility and glycemic control over time. Additionally, fatty acid levels were not analyzed in this study, precluding a more comprehensive assessment of metabolic profiles. Fat was estimated using anthropometric measurements rather than reference methods.

In conclusion, this study shows that fasting RER, a readily accessible clinical measure, is a valuable indicator of glucose metabolism and can predict the likelihood of impaired fasting glucose resolution with lifestyle intervention. While fasting RER may be associated with metabolic flexibility, further research is needed to directly assess this relationship. Nonetheless, our findings highlight the potential of fasting RER as a practical and scalable tool for assessing metabolic health and guiding personalized lifestyle interventions in large populations.

Disclosures

The authors of this article declare that they have no conflicts of interest.

Data Availability

Restrictions apply to the availability of some or all data generated or analyzed during this study to preserve patient confidentiality or because they were used under license. The corresponding author will on request detail the restrictions and any conditions under which access to some data may be provided.

References

1

Kelley
 
DE
,
Mandarino
 
LJ
.
Fuel selection in human skeletal muscle in insulin resistance: a reexamination
.
Diabetes
.
2000
;
49
(
5
):
677
‐
683
.

Google Scholar

Crossref
Search ADS
PubMed

 
2

Galgani
 
JE
,
Moro
 
C
,
Ravussin
 
E
.
Metabolic flexibility and insulin resistance
.
Am J Physiol Endocrinol Metab
.
2008
;
295
(
5
):
E1009
‐
E1017
.

Google Scholar

Crossref
Search ADS
PubMed

 
3

Goodpaster
 
BH
,
Sparks
 
LM
.
Metabolic flexibility in health and disease
.
Cell Metab
.
2017
;
25
(
5
):
1027
‐
1036
.

Google Scholar

Crossref
Search ADS
PubMed

 
4

Galgani
 
JE
,
Bergouignan
 
A
,
Rieusset
 
J
,
Moro
 
C
,
Nazare
 
J-A
.
Editorial: metabolic flexibility
.
Front Nutr
.
2022
;
9
:
946300
.

Google Scholar

Crossref
Search ADS
PubMed

 
5

San-Millán
 
I
,
Brooks
 
GA
.
Assessment of metabolic flexibility by means of measuring blood lactate, fat, and carbohydrate oxidation responses to exercise in professional endurance athletes and less-fit individuals
.
Sports Med
.
2018
;
48
(
2
):
467
‐
479
.

Google Scholar

Crossref
Search ADS
PubMed

 
6

Ferrannini
 
E
.
The theoretical bases of indirect calorimetry: a review
.
Metabolism
.
1988
;
37
(
3
):
287
‐
301
.

Google Scholar

Crossref
Search ADS
PubMed

 
7

Klein
 
S
,
Sakurai
 
Y
,
Romijn
 
JA
,
Carroll
 
RM
.
Progressive alterations in lipid and glucose metabolism during short-term fasting in young adult men
.
Am J Physiol Endocrinol Metab
.
1993
;
265
(
5
):
E801
‐
E806
.

Google Scholar

Crossref
Search ADS

 
8

Browning
 
JD
,
Baxter
 
J
,
Satapati
 
S
,
Burgess
 
SC
.
The effect of short-term fasting on liver and skeletal muscle lipid, glucose, and energy metabolism in healthy women and men
.
J Lipid Res
.
2012
;
53
(
3
):
577
‐
586
.

Google Scholar

Crossref
Search ADS
PubMed

 
9

Società Italiana di Nutrizione Umana
.
LARN: Livelli di Assunzione di Riferimento di Nutrienti ed Energia per la Popolazione Italiana
.
Società Italiana di Comunicazione Scientifica e Sanitaria
;
2014
.

Google Scholar

OpenURL Placeholder Text

 
10

Committee ADAPP
.
2. Diagnosis and classification of diabetes: standards of care in diabetes–2024
.
Diabetes Care
.
2023
;
47
(
Supplement_1
):
S20
‐
S42
.

OpenURL Placeholder Text

 
11

Lohman
 
TG
,
Roche
 
AF
.
Anthropometric Standardization Reference Manual
.
Human Kinetics
;
1988
.

Google Scholar

OpenURL Placeholder Text

 
12

World Health Organization
.
Obesity: Preventing and Managing the Global Epidemic
.
World Health Organization
;
2000
.

Google Scholar

OpenURL Placeholder Text

 
13

Durnin
 
JVGA
,
Womersley
 
J
.
Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years
.
Br J Nutr
.
1974
;
32
(
(01|1)
):
77
‐
97
.

Google Scholar

PubMed
OpenURL Placeholder Text

 
14

Siri
 
W
. Body composition from fluid spaces and density: analysis of methods. In:
Brozek
 
J
,
Henschel
 
A
, eds.
Techniques for Measuring Body Composition
.
National Academy of Sciences
;
1961
:
224
‐
244
.

Google Scholar

OpenURL Placeholder Text

 
15

Delsoglio
 
M
,
Dupertuis
 
YM
,
Oshima
 
T
,
van der Plas
 
M
,
Pichard
 
C
.
Evaluation of the accuracy and precision of a new generation indirect calorimeter in canopy dilution mode
.
Clin Nutr
.
2020
;
39
(
6
):
1927
‐
1934
.

Google Scholar

Crossref
Search ADS
PubMed

 
16

de B Weir
 
JB
.
New methods for calculating metabolic rate with special reference to protein metabolism
.
J Physiol
.
1949
;
109
(
1-2
):
1
‐
9
.

Google Scholar

Crossref
Search ADS
PubMed

 
17

Foppiani
 
A
,
Sileo
 
F
,
Menichetti
 
F
, et al.  Supplementary analysis for “Predicting Glycemic Control in Patients with Impaired Fasting Glucose with Fasting Respiratory Exchange Ratio”.
Zenodo
.
2025
.
10.5281/zenodo.15100654

18

Tarnopolsky
 
MA
.
Gender differences in substrate metabolism during endurance exercise
.
Can J Appl Physiol
.
2000
;
25
(
4
):
312
‐
327
.

Google Scholar

Crossref
Search ADS
PubMed

 
19

Shoemaker
 
ME
,
Gillen
 
ZM
,
Fukuda
 
DH
,
Cramer
 
JT
.
Metabolic flexibility and inflexibility: pathology underlying metabolism dysfunction
.
J Clin Med
.
2023
;
12
(
13
):
4453
.

Google Scholar

Crossref
Search ADS
PubMed

 
20

Corpeleijn
 
E
,
Saris
 
WHM
,
Blaak
 
EE
.
Metabolic flexibility in the development of insulin resistance and type 2 diabetes: effects of lifestyle
.
Obes Rev
.
2009
;
10
(
2
):
178
‐
193
.

Google Scholar

Crossref
Search ADS
PubMed

 
21

Lund
 
J
,
Tangen
 
DS
,
Wiig
 
H
, et al.  
Glucose metabolism and metabolic flexibility in cultured skeletal muscle cells is related to exercise status in young male subjects
.
Arch Physiol Biochem
.
2018
;
124
(
2
):
119
‐
130
.

Google Scholar

Crossref
Search ADS
PubMed

 
22

Mansell
 
PI
,
Fellows
 
IW
,
Macdonald
 
IA
.
Enhanced thermogenic response to epinephrine after 48-h starvation in humans
.
Am J Physiol Regul Integr Comp Physiol
.
1990
;
258
(
1
):
R87
‐
R93
.

Google Scholar

Crossref
Search ADS

 
23

Paoli
 
A
,
Marcolin
 
G
,
Zonin
 
F
,
Neri
 
M
,
Sivieri
 
A
,
Pacelli
 
QF
.
Exercising fasting or fed to enhance fat loss? Influence of food intake on respiratory ratio and excess postexercise oxygen consumption after a bout of endurance training
.
Int J Sport Nutr Exerc Metab
.
2011
;
21
(
1
):
48
‐
54
.

Google Scholar

Crossref
Search ADS
PubMed

 
24

Ellis
 
AC
,
Hyatt
 
TC
,
Hunter
 
GR
,
Gower
 
BA
.
Respiratory quotient predicts fat mass gain in premenopausal women
.
Obesity
.
2010
;
18
(
12
):
2255
‐
2259
.

Google Scholar

Crossref
Search ADS
PubMed

 
25

Marra
 
M
,
Scalfi
 
L
,
Contaldo
 
F
,
Pasanisi
 
F
.
Fasting respiratory quotient as a predictor of long-term weight changes in non-obese women
.
Ann Nutr Metab
.
2004
;
48
(
3
):
189
‐
192
.

Google Scholar

Crossref
Search ADS
PubMed

 
26

Petersen
 
KF
,
Dufour
 
S
,
Befroy
 
D
,
Garcia
 
R
,
Shulman
 
GI
.
Impaired mitochondrial activity in the insulin-resistant offspring of patients with type 2 diabetes
.
N Engl J Med
.
2004
;
350
(
7
):
664
‐
671
.

Google Scholar

Crossref
Search ADS
PubMed

 
27

Tsilingiris
 
D
,
Tzeravini
 
E
,
Koliaki
 
C
,
Dalamaga
 
M
,
Kokkinos
 
A
.
The role of mitochondrial adaptation and metabolic flexibility in the pathophysiology of obesity and insulin resistance: an updated overview
.
Curr Obes Rep
.
2021
;
10
(
3
):
191
‐
213
.

Google Scholar

Crossref
Search ADS
PubMed

 
28

Muoio
 
DM
.
Metabolic inflexibility: when mitochondrial indecision leads to metabolic gridlock
.
Cell
.
2014
;
159
(
6
):
1253
‐
1262
.

Google Scholar

Crossref
Search ADS
PubMed

 
29

Cleasby
 
ME
,
Jamieson
 
PM
,
Atherton
 
PJ
.
Insulin resistance and sarcopenia: mechanistic links between common co-morbidities
.
J Endocrinol
.
2016
;
229
(
2
):
R67
‐
R81
.

Google Scholar

Crossref
Search ADS
PubMed

 
30

Malin
 
SK
,
Liu
 
Z
,
Barrett
 
EJ
,
Weltman
 
A
.
Exercise resistance across the prediabetes phenotypes: impact on insulin sensitivity and substrate metabolism
.
Rev Endocr Metab Disord
.
2016
;
17
(
1
):
81
‐
90
.

Google Scholar

Crossref
Search ADS
PubMed

 

Abbreviations

     
  • BMI

    body mass index

    •  
  • HOMA-IR

    Homeostatic Model Assessment for Insulin Resistance

    •  
  • RER

    respiratory exchange ratio

    •  
  • VCO2

    carbon dioxide produced

    •  
  • VO2

    oxygen consumed

© The Author(s) 2025. Published by Oxford University Press on behalf of the Endocrine Society.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. See the journal About page for additional terms.
Subject
Diabetes, Pancreatic and Gastrointestinal Hormones
Issue Section:
Clinical Research Article
Download all slides