Study subjects
This study was designed and reported according to the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) Statement providing all sections suggested to cross-sectional studies.
Study setting
This cross-sectional study was conducted in outpatients with type 2 diabetes at the Endocrinology Division, Hospital de Clínicas de Porto Alegre, Brazil.
Participants
Patients with type 2 diabetes who had not received any dietary counselling by a registered dietitian during the previous 6 months were eligible. Other inclusion criteria were age <70 years, serum creatinine <2 mg/dL, normal thyroid function tests, and absence of severe liver disease, decompensated heart failure, or any acute disease. Patients underwent clinical, laboratory, and nutritional evaluation. All medications in use were maintained during the study. Diabetes was defined as onset of hyperglycemia over 30 years of age, with no previous episode of ketoacidosis or documented ketonuria and treatment with insulin only after 5 years of diagnosis. All procedures involving patients were approved by Ethics Committee and written informed consent was obtained from all patients.
Eligibility
The patients' eligibility was verified from the Endocrinology Division database, where all patients meeting the eligibility criteria were selected. Of 1132 patients medical records screened, 973 were automatically excluded due to receive dietary counseling from a registered dietitian during the previous 6 months (n = 332), age > 70 years old (n = 365), serum creatinine > 2 mg/dl (n = 72), altered liver and thyroid function tests (n = 147), and presence of renal disease, cardiac failure, or any acute or consumptive disease (n = 57). Of 159 eligible screened patients, 97 were excluded because declined to participate. Final analyses were performed per protocol, and we included 62 patients patients with type 2 diabetes (31 men and 31 women). Of these 62 patients, data from 21 patients were used according to a study previously published by our research group [35].The flow diagram of patient selection is shown in Fig. 1
Data sources / measurements
Clinical evaluation
Blood pressure was measured with a digital sphygmomanometer (Blood Pressure Monitor, model HEM-705CP, Omron Healthcare Inc., Bannockburn, IL). Two measurements were obtained, 2 minutes apart, and the mean recorded for analysis. Patients were considered hypertensive in case of systolic blood pressure ≥140 mmHg on at least two occasions, history of hypertension, or current use of antihypertensive drugs.
The anthropometric parameters used to assess nutritional status were body mass (with participants barefoot and wearing lightweight clothing) and height, both measured with a calibrated anthropometric scale (Filizola®). The body mass index (BMI) was calculated as the body mass (in kg) divided by the height (in m) squared. Body composition analysis by electrical bioimpedance (InBody® 230, Seoul, South Korea) was performed for determination of fat mass (FM) and fat-free mass (FFM), both in kg.
Habitual physical activity was measured objectively by step counting with a pedometer (HJ-321, Omron Healthcare Inc.) and classified into five levels: sedentary (< 5000 steps/day), low active (5000–7499 steps/day), somewhat active (7500–9999 steps/day), active (≥10000–12499 steps/day) and highly active (≥12500 steps/day) [36]. Participants wore the pedometer for 7 days, attached to the waistband of their clothing during waking hours, except when bathing or swimming. Participants were encouraged not to alter their usual physical habits during the protocol.
Laboratory evaluation
Blood samples were obtained after a 12-hour fast. Plasma glucose level was determined by the glucose-peroxidase enzymatic colorimetric method (Bio Diagnóstica), HbA1C by high-performance liquid chromatography (Merck-Hitachi L-9100, Merck Diagnostica, Darmstadt, Germany; reference range, 4.8–6.0%), total cholesterol and triglycerides by enzymatic colorimetric methods (Merck; Boehringer Mannheim, Buenos Aires, Argentina), and high-density lipoprotein (HDL) by a homogeneous direct method (AutoAnalyzer, ADVIA 1650). Low-density lipoprotein (LDL) cholesterol was calculated using the Friedewald formula (LDL cholesterol = total cholesterol – HDL cholesterol – triglycerides/5).
Resting energy expenditure measurement
Objective measurement of REE was performed by IC. The IC protocol consisted of 10 min of rest on a gurney in the supine position, followed by 30 min of collection of exhaled gases using the canopy dilution technique and a coupled collection device. An open-circuit calorimeter (QUARK RMR, Cosmed, Rome, Italy) was used to determine VO2 (oxygen consumption) and VCO2 (carbon dioxide production). To calibrate the equipment, the volume of the turbine flowmeter was first calibrated electronically by the system, followed by calibration of the collector plates using a known gas concentration. This process was repeated for each test to standardize measurement. The first 10 min of gas collection were excluded from the analysis; thus, VO2 and VCO2 (L/min) obtained during the final 20 min of each collection (mean value) were used for REE calculation. The equation proposed by Weir [37], which incorporates a correction factor and thus obviates the need to consider protein metabolism, was used to obtain values in kcal/min: [(3.9 x VO2) + (1.1 x VCO2)]. The result in kcal/min was multiplied by 1,440 min to obtain the 24-hour REE. Subjects were asked to refrain from all moderate- or high-intensity physical activity during the 24 h preceding the test, and not to consume alcohol or caffeine. Smokers were instructed not to consume any tobacco products for at least 12 h before the day of REE measurement. Additionally, the subjects were instructed to fast for 12 h prior to the test (water freely allowed) and to have a good night’s sleep (at least 8 hours). Finally, all subjects either drove or were driven to the test site to avoid any energy expenditure before determination of REE. All tests were performed between 06:30 and 08:00, in a temperature-controlled (23 °C) and sound-controlled room, under low luminosity. All participants continued to take their usual medications during the study period; those who had morning doses to take received them after IC.
Selection of equations for estimating resting energy expenditure
The REE was estimated by eleven predictive equations, which were selected after a search of previous publications on the them: Harris-Benedict [4], Bernstein [5], Schofield [6], FAO/WHO/UNO [7], Mifflin-St. Jeor [8], Gougeon [9], Huang [10], Martin [11], Dietary Reference Intakes (DRIs) proposed by Institute Of Medicine [12], Oxford [13] and Ikeda [14]. To be included, the equations had to have been developed for adult men and women and should be based on body weight, height, age, sex, and/or FM. Equations derived only for specific ethnic groups or for individuals with BMI ≥40 kg/m² were not included (Supplement 1).
Sample size
Sample size calculation was based on a study wherein the variability of REE in relation to glycemic control, weight, age, and sex—particularly in male patients—demonstrated a multiple correlation coefficient of 0.9 [25]. Considering a study power of 80%, alpha error of 5%, and 20% attrition rate, 62 patients would be required.
Statistical analysis
Data were analyzed using SPSS version 23.0, while Bland–Altman plot values were analyzed in R version 3.3.3 (R Project for Statistical Computing, Vienna, Austria).
The Shapiro-Wilk normality test was used to determine the distribution of the variables. The bias was calculated by subtracting the measured REE from the estimated REE. For each predictive equation, the percentage of deviation of estimated REE from measured REE was calculated as [(estimated REE − measured REE) / measured REE] × 100.
The means of estimated REE and measured REE were compared by a paired Student’s t-test. Agreement between estimated and measured REE was examined graphically by plotting the differences between the predicted and the measured REE against their mean values, with 95% limits of agreement (mean difference ± 1.96 standard deviation) [38]. Pearson's correlation coefficients were used to assess the correlation between the estimated and measured REE and to assess the correlation between the dependent variable (REE) and the independent variables of sex, age, weight, height, FFM, FM, BMI, fasting plasma glucose and glycated hemoglobin. Results are expressed as means and standard deviations or medians and interquartile ranges. For all tests, a p value <0.05 was considered statistically significant.