This study included 110 elderly patients admitted to the City hospital, a multi-specialty hospital providing care for patients from both the public and supplementary health systems, located in the city of Salvador, Bahia, Brazil. The study was conducted in the period from August 2013 to January 2014. The inclusion criteria were hospitalized individuals aged ≥60 years, examined in the time between the first and fifth day of hospitalization, who were not under treatment with vasoactive and inotropic drugs, able to walk without external assistance or auxiliary devices, who had medical permission to walk, who had no pain, dyspnea or cardiopulmonary change that prevented them from performing physical activity.
The primary variables were anthropometric measurements, handgrip strength, gait speed, cognitive function, history of falls in the last year and smoking status. The secondary variables obtained were medical admission diagnosis, admission profile (clinical or surgical), length of stay hospital during data collection, and the Charlson index to assess comorbidities. On a daily basis, the researchers checked the electronic medical record system to find patients who met the criteria for inclusion in the study. The Research Ethics Committee of the Bahia School of Medicine and Public Health approved the project under Protocol Number 336.469 / 2013. After being duly informed about the research, all patients signed a term of free and informed consent to participate in the study.
Measurement
For the diagnosis of sarcopenia, muscle mass, handgrip strength and physical performance were measured. Skeletal muscle mass was estimated (SMM) using the Lee equation [
17] for patients with BMI <30: (0.244 * body weight) + (7.8 * height) + (6.6 * gender) − (0.098 * age) + (race − 3.3); with body weight in kilograms and height in meters. The value 0 must be used for women, 1 for men, then 0 for whites, 1.4 for blacks and −1.2 for Asians [
17]. A recent Brazilian study demonstrated strong agreement between DEXA and this predictive equation for muscle mass (k = 0.74; p <0.001), with a high specificity (89%) and sensitivity (86%) [
14]. For elderly patients with BMI ≥30 kg/m
2, the specific anthropometric equation [
17]: {height * (0.007444 * CAG
2 + 0.00088 * CTG
2 + 0.00441 * CCG
2) + 2.4 * gender – 0.048 * age + race + 7.8} was used.
The skinfold thickness measurements (S) in the arm, thigh and medial part of the calf were performed by trained evaluators; and the circumferences of the limbs (C
limb) in the mid upper arm, mid thigh and mid calf were also measured to the nearest 1 mm, according to anthropometric standardization [
19]. We used the
Lange caliper (USA) to measure the skinfold thickness. Three measurements were performed and the mean of the measurements was obtained for analysis. To remove the fat component, the corrected value of the circumference (C
m: Climb - π.S) was obtained [
17]. Subsequently, the SSM was divided by height squared to obtain the skeletal muscle mass index (MMI). The criteria used to assess the reduction in skeletal muscle mass were values ≤6.37 kg/m
2 for female patients and ≤8.90 kg/m
2 for male patients, which are equivalent to 20% of lowest percentile distribution reported by Alexandre et al. [
16], according to the studies by Newman et al. [
20] and Delmonico et al. [
21].
Body mass index (BMI) was also calculated by dividing the weight (in kg) by the square of height (in m). The values established by the Lipschitz et al. [
22] recommendation, which allows for changes in body composition owing to aging, were used to classify the following: underweight, BMI <22 kg/m
2; normal weight, BMI between 22 and 27 kg/m
2 and excess weight, BMI >27 kg/m
2 [
22].
To assess handgrip strength, the participants were asked to sit on a chair with elbows positioned at a 90° angle and exert maximum force, using a
Saehan hydraulic dynamometer (Saehan Corporation, 973, Yangdeok-Dong, Masan 630–728, Korea). This dynamometer presented high reliability in comparison with the gold standard, which is the Jamar dynamometer [
23]. This measurement was performed three times, with a 1-min rest interval between measurements, and the highest values were considered. For assessing muscle weakness, values <20 kg and <30 kg were considered for female and males, respectively [
24].
The parameter used to evaluate physical performance was the 6-m gait speed test. For this purpose, participants were asked to walk a distance of 10 m on a flat surface, in a straight line, as fast as they could, and the time taken to walk the middle 6 m was measured. The highest values were considered, and values ≤0.8 m/s indicated poor physical performance [
25].
Cognitive function was assessed using the mini-mental state examination (MMSE), which quantifies various domains of cognition, with a score ranging from 0 to 30 [
26]. The report of low physical activity pre-admission was graded positive for elderly people who were inactive or who performed physical activity <2 times a week [
27]. To evaluate the severity of the patients’ comorbidities, data were collected by means of the Charlson comorbidity index within the first 24 hours of admission [
28]. The elderly who reported having smoked at least one cigarette per day in the last month were considered smokers [
29]. Self-reports of falls in the past year were also evaluated.
Statistical analysis
The numerical variables were expressed as means and standard deviations, and the categorical data were expressed in percentages with their respective confidence intervals. The association between sarcopenia and length of stay at the time of data collection, and the Charlson index were analyzed using the chi-square test (Length of hospital stay during data collection: ≤3 days and 3–5 days, Charlson index: ≤4 and ≥5). The intergroup comparisons of the variables age, BMI, Charlson index, cognitive function, handgrip strength, and gait speed were performed using the Student’s
t-test for independent variables. Multivariate analysis of factors associated with sarcopenia was performed by the logistic regression (backward method), which included the six most significant variables: age, cognitive function, admission profile (clinical or surgical), smoking, age ≥80 years and reports of physical inactivity pre-hospitalization (less than 2x per week). One hundred patients were evaluated, considering an estimated error of 7%, a significance level of 5%, and an expected rate of sarcopenia of 15%, based on previous studies [
15,
16,
30]. The analyses were performed using the SPSS software version 14.0, and p-values of <0.05 were considered significant.