Sarcopenic Obesity Among Community Dwelling Elderly

Sarcopenic Obesity Clinical Trial

Official title: Prevalence of Sarcopenic Obesity Among Community Dwelling Elderly: A Pilot Study

Status Completed

Clinical Trial Summary

Sarcopenic obesity (SO) is a geriatric syndrome, characterized by reduced muscle mass and function, and increase in body fat. It is classified as a new category of obesity in elderly. It found to be associated with higher risk of physical disability, hospitalization, metabolic syndrome, cardiovascular disorders and mortality. According to the United Nations Economic and Social Commission for Asia and The Pacific's (UNESCAP) 2016 population data, Malaysians aged sixty and above contribute to 9.5% of the population. The aging individuals are estimated to reach 23.5% of the population by 2050. In the matter of human health, SO increases the risk of falls and fracture, deteriorates the performance of activities of daily living, enhances the risk of getting multiple health-related outcomes and results in physical disability. Eventually, the quality of life is adversely affected. In financial terms, SO cause significant burden to health care systems. Both hospitalization and cost of care during hospitalization are increased. Therefore, study of SO has experienced a revitalized research interest due to its negative impact on public health. In addition, there is significant lack of literature related to prevalence of SO in community-dwelling elderly in Malaysia, hence, a need to investigate this phenomenon.

Clinical Trial Description

Pilot study design was employed to determine the prevalence of sarcopenic obesity among community-dwelling elderly living in Kajang, Selangor. The sampling method used for recruitment of subjects was non-probability, convenient sampling. Sample size was calculated based on the work carrrid by Viechtbauer in 2015.

n=(In (1-y))/(In (1-π) ) where n = sample size π = problem probability y = level of confidence

The population of Kajang is approximately 428,131. The elderly population made up of about 9.5% of the total population in Malaysia based on the UNESCAP's 2016 population data. With confidence interval of 95% and margin of error 5%, The targeted sample size for this research study was set to be 59. Investigators recruited 65 subjects.

Measurements of the four diagnostic criteria for sarcopenic obesity were:

1. Muscle mass (skeletal muscle index - SMI) 2. Body Fat (percent body fat). Bioelectrical Impedance Analysis (BIA) device was used to measure muscle mass and percent body fat 3. Muscle strength (handgrip strength), and 4. Physical performance (usual gait speed).

The weight and height of all subjects were measured as BIA needed this data to quantify the muscle mass. Body weight and height were measured to the nearest 0.1kg and 0.01m using the calibrated stadiometer with electronic weighing scale. Before the measurements, the subjects were required to remove their footwear, accessories and excessive clothing, if any. After getting the readings for weight and height, body mass index (BMI) was calculated, to the nearest 0.01kg/m². Next, bioelectrical impedance analysis (BIA) device was utilized to analyze the subjects' body composition (SMI & percent body fat). Before body composition analysis, all subjects were informed to fast overnight and not to eat and drink anything before analyzing was carried out. All the respective subjects weight and height was inserted into the BIA device (Inbody S10 Body Composition Analyzer). The device operates with six different frequencies (1kHz, 5kHz, 50kHz, 250kHz, 500kHz, 1000kHz) at five segments of body, which are right arm, left arm, trunk, right leg and left leg. SMI, which is the height-adjusted appendicular skeletal muscle mass (ASM) of an individual was used to detect sarcopenia in the study subjects from the aspect of muscle mass. SMI (kg/m2) was calculated by dividing ASM (kg) with subject's height (m2). For ASM, the lean muscle mass of four limbs were added up. Scientific calculator was used to obtain the ASM and SMI of the subjects as these were not provided in the body analysis result sheet. Both the ASM and SMI were quantified to the nearest 0.01kg and 0.01 kg/m2 respectively.

Before starting body composition analysis, subjects were positioned in seated posture and touch type electrodes were fixed on their four limbs. They were asked to rest their forearms on the arm rest and kept their legs apart. Their feet must be flat on the floor. For electrode placements, hand electrodes will be placed over the index (black) and middle (red) fingers for both hands, whereas foot electrodes will be placed over the ankles (red for medial side; black for lateral side) for both feet. Alcohol swap was used to wipe subjects' ankles to moisture the skin over that area. Once the analysis began, the subjects were instructed to avoid any body movement and not to fall asleep throughout the process. The entire analysis process normally took 2-3 minutes.

Handgrip dynamometer (HGD) was used to evaluate the subjects' handgrip strength (HS). The model of HGD equipped was Jamar® Hydraulic Hand Dynamometer. The measurements were done for 3 times to get the average readings. HS was measured to the nearest 0.01kg. Standardized positioning recommended by the American Society of Hand Therapies (ASHT) were employed: subjects in sitting position with back supported, shoulders adducted, elbow flexed at 90°, forearm and wrist in neutral position. Subjects were instructed to hold the dynamometer and exert maximum force by dominant hand forcefully for 3 seconds. Demonstration was given before participants performed the maneuver. 1 minutes rest interval was given between each trial to prevent muscle fatigue.

Usual gait speed (GS) was measured by 6 meters walk test (6 MWT), as suggested by EWGSOP to assess the subjects' physical performance. Gait speed (GS) (meters/second) was calculated by dividing distance walked (m) with the time taken to finish the walkway (in seconds). Subjects were required to repeat the test for three times to obtain average reading. Time taken to complete the walkway was measured using timer in mobile phone to the nearest 0.1 seconds, whereas GS was measured to the nearest 0.1m/s. A walkway with distance of 10 meters was measured using measuring tape. Green colour cones were being positioned at the both end points of the walkway, with 2 and 8 meters marked with yellow colour cones. The first and last 2 meters were used as acceleration and deceleration phase respectively. The subjects were instructed to walk at their usual and comfortable pace. The timing was being started when the toes of leading foot cross 2-meter mark, and stopped once 8-meter mark was crossed. . The subjects were allowed to use assistive device, if any, during the gait test. Demonstration was given before the test. Several precautions were taken throughout the test; one of the researcher was walking half step behind the participants so their speed of walking will not be influenced, both researcher and subject were not allowed to talk and researcher must by the side of subjects to prevent them from falling. Besides, subjects were free to stop the test if they felt any discomfort but no such instance was reported.

Diagnostic algorithm was used as the principal guideline for diagnosis of sarcopenia adapted from Asian Working Group for Sarcopenia (AWGS) and European Working Group on Sarcopenia in Older People 2 (EWGSOP2). According to recommendations by AWGS, the cut-off values for SMI (kg/m2) are 7.00kg/m2 and 5.70 kg/m2 for male and female respectively were used to identify low muscle mass. For muscle strength, values of <26.00kg for male and <18.00kg were considered as low. In addition, poor physical performance was evaluated when the value for gait speed is <0.8m/s and it is not gender-specific. To define obesity, American Society of Bariatric Physicians (ASBP) suggested to use percent body fat of ≥25% for male and ≥30% for female. ;

Related Conditions & MeSH terms

• Obesity
• Sarcopenic Obesity

• NCT number: NCT04140864
• Study type: Observational
• Source: Universiti Tunku Abdul Rahman
• Status: Completed
• Start date: December 3, 2018
• Completion date: May 14, 2019