Accepted Manuscript Title: Applicability and agreement of different diagnostic criteria for sarcopenia estimation in the elderly Author: Val´eria Pagotto Erika Aparecida Silveira PII: DOI: Reference:
S0167-4943(14)00089-2 http://dx.doi.org/doi:10.1016/j.archger.2014.05.009 AGG 3009
To appear in:
Archives of Gerontology and Geriatrics
Received date: Revised date: Accepted date:
18-6-2013 2-5-2014 8-5-2014
Please cite this article as: Pagotto, V., Silveira, E.A.,Applicability and agreement of different diagnostic criteria for sarcopenia estimation in the elderly, Archives of Gerontology and Geriatrics (2014), http://dx.doi.org/10.1016/j.archger.2014.05.009 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
*Manuscript - include tables in text
TITLE PAGE
Title: Applicability and agreement of different diagnostic criteria for sarcopenia estimation in the elderly
ip t
Short Title: Agreement diagnostic criteria sarcopenia
cr
Author and affiliations:
us
Valéria Pagotto Federal University of Goiás. Nursing School.
an
227th,Block.68,s/n,Leste Universitário,Goiânia,Goiás,Brazil [email protected]
M
+556281374549
Erika Aparecida Silveira
ed
Federal University of Goiás. Health Science Graduate Program. 227th,Block.68,s/n,Leste Universitário,Goiânia,Goiás,Brazil
+556281374549
ce pt
[email protected]
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
Page 1 of 23
1. Introduction Sarcopenia has been in the spotlight for the last two decades, as the losses of mass and muscle function are associated with the occurrence of adverse outcomes that can compromise quality of life and lead to precocious death (Landi et al., 2013) besides generating elevated costs for the health system (Janssen et al., 2004). Since sarcopenia
ip t
conception, one of the biggest challenges in its study has been the establishment of an
cr
operational definition for application in clinical and research settings (Baumgartner et al., 1998; Janssen et al., 2002; Newman et al., 2003).
us
Several criteria are recommended for sarcopenia diagnostic (Baumgartner et al., 1998; Janssen et al., 2002; Newman et al., 2003; Delmonico et al., 2007) as well as
an
different methods to obtain muscle mass (Janssen et al., 2000; Rolland et al., 2003; Chen
M
et al., 2007). The index most utilized is calculated by the ratio between muscle mass and the squared height, being the muscle mass obtained by dual energy X-ray absorptiometry
ed
(DXA) (Baumgartner et al., 1998) or bioelectrical impedance (BIA) (Janssen et al., 2000). When the value is lower than two standard deviations from the mean for a young reference
ce pt
population, sarcopenia is diagnosed. Other methods propose weight adjustments (Janssen et al., 2002), besides height+fat mass (Newman et al., 2003). In the last three years, sarcopenia has been defined as a geriatric syndrome, and muscle function (strength and/or muscle performance) was proposed to integrate its diagnosis in elderly
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
(Cruz-Jentoft et al., 2010; Fielding et al., 2011). The prevalence of sarcopenia in elderly has wide amplitude between countries (et al., 1998; Newman et al., 2003; Lau et al., 2005; Tichet et al., 2008; Woo et al., 2009; Sanada et al., 2010; Wen et al., 2011), including Brazil (Gobbo et al., 2012; Domiciano et al., 2013), due to the choice of method and diagnostic criteria, which, consequently, influences prevention and treatment. Studies evaluating prevalence and levels of agreement between these methods are important to recommend interventions, and to
Page 2 of 23
direct and standardize diagnostic criteria. Only one study (Bjlisma et al., 2012) compared the different diagnostic methods for sarcopenia, utilizing BIA to determine muscle mass and manual strength to evaluate muscle function. Therefore, the aim of this study was to estimate sarcopenia prevalence in community-dwelling older, according to gender and age, and analyze the agreement between different mass and muscle strength diagnostic
cr
ip t
criteria.
2. Methods
us
Data was obtained in the Elderly Project/Goiânia, a cross-sectional study whose primary purpose was to evaluate different aspects of health and nutrition of non-
an
institutionalized seniors in Goiânia/Brazil. Goiânia is located in the central-western region
M
of Brazil, 209 km from Brasilia, the nation’s capital, and is one of the main economic centers of the region. As of March/2013, population is 1,333,767 inhabitants (IBGE, 2010).
Goiás (Protocol n° 031/2007).
ed
The project was approved by the Research Ethics Committee of the Federal University of
ce pt
The sampling and data collection procedures were previously described in detail (Pagotto et al., 2011). Briefly, the study was carried out with a probabilistic sampling of 418 senior ≥60y, proportional to the number of elderly living in the nine health districts of Goiânia. We considered the following parameters to calculate this sample: outcome of
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
lower prevalence (type 2 diabetes), confidence level of 95%, statistical power 80%, prevalence ratio (RP) of 2. This amount, added to 10% to correct stratification, losses and refusals. This sample was selected by multistage random sampling and the health districts of Goiânia were the primary units. Further, we identified the Health Care Units of increased flow in each DS to draw up a list with name, age and address of the elderly. With the list of records, proceeded simple random allocation and addresses of the elderly were located on the map urban area. First, this sample was evaluated according to demographic,
Page 3 of 23
socioeconomic, health, nutrition, lifestyle and anthropometric characteristics. Then, in a second evaluation, a subsample of 132 seniors was randomly selected to evaluate sarcopenia, maintaining the same health district proportion. Pacemaker users or those presenting any type of metal embedded in the body were excluded which were requirements for BIA and DXA.
ip t
This subsample was contacted by telephone to explain the objectives of a new data
cr
collection, to schedule appointments and to inform on preparation for exams: absolute fasting for at least 4 hours and urinate 30 minutes before the tests, no consumption of
us
alcohol, caffeine and diuretics in the 24 hours and no exercise in the 12 hours preceding the tests. Data were collected in July/2009 in a specialized clinic, by a previously trained
an
team which followed standards.
M
Eleven different criteria were applied for sarcopenia diagnosis: nine of muscle mass and two of muscle strength (Table 1). DXA, BIA and Calf circumference (CC) were utilized
ed
to evaluate muscle mass, while muscle strength was obtained by hand grip strength. DXA was carried out by a total body scan, with a Lunar DPX–MD PLUS, version
ce pt
7.52.002, calibrated daily. DXA provided the Appendicular Muscle Mass (AMM), used to calculated the Appendicular Muscle Mass Index (AMMI), ratio between AMM and squared height (Baumgartner et al., 1998,10). According to this index, three cutoff points were analyzed (codes A, B and C) (Table1) (Baumgartner et al., 1998; Newman et al., 2003;
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
Lau et al., 2005; Delmonico et al., 2007; Woo et al., 2009; Cruz-Jentoft et al., 2010). For BIA, the Maltron BF906 equipment was utilized, with impedance range 2001000 Ohms. The following equation was used to estimate muscle mass: Skeletal Muscle Mass (SMM) (kg) = [Height2/ Resistance x 0,401) + (gender x 3,825) + (age x -0,071)] + 5,102 (Janssen et al., 2000). The Skeletal Muscle Index (SMI) was used to define sarcopenia in five criteria (from D to H), being criteria D and E the ratio between muscle mass and weight multiplied by 100 (SMI/Weight) (Janssen et al., 2002; Tichet et al., 2008)
Page 4 of 23
and criteria F, G and H were calculated as the ratio between muscle mass and squared height (SMI/height) (Janssen et al., 2002; Chien et al., 2008; Singh et al., 2009). CC (code I) was measured with non-elastic tape, with the senior sitting down, leg at 90⁰, at the greatest circumference. Three measurements were taken, on mean, with a cutoff point of 31 cm (Rolland et al., 2003).
ip t
Muscle strength was determined by hand-grip strength with a CROWN
cr
dynamometer (hydraulic), on dominant hand, with senior seated, with adducted shoulder, elbow flexed at 90º, forearm in neutral position, and fist extended between 0 and 30º
us
(Fess, 1992). The senior pulled the ring of the dynamometer, maintaining position for six seconds and then relaxing. Two measurements were taken, with an interval between
an
them. Two cutoff points were analyzed for GS (F1 and F2) (Table 1) (Fried et al., 2001;
measurements, resulting in 29 criteria. analyses
were
performed
using
STATA/SE
(12.0).
Sarcopenia
ed
Statistical
M
Lauretani et al., 2003). All muscle strength criteria were analyzed with these two strength
prevalence was estimated, by gender and age group with confidence intervals (CI) of 95%,
ce pt
and statistical differences were identified by the Wald Test. A simple Poisson regression was carried out, with the calculation of prevalence ratios (PR) and (CI95%). Agreement between methods was analyzed by the Kappa coefficient (k).
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
3. Results
One-hundred thirty-two seniors were evaluated (81 women and 52 men), with mean age 70.16 (±6.63) (Table 2) and 89.4% were using any medication. Morbidities were reported by the elderly, and the most prevalent were: hypertension (57.1%), diabetes mellitus (27.8%), osteoporosis (17.3%) and respiratory diseases (6.7%). Mean values of all muscle mass measurements obtained by DXA, BIA and anthropometry were highest in the male (p
S0167-4943(14)00089-2 http://dx.doi.org/doi:10.1016/j.archger.2014.05.009 AGG 3009
To appear in:
Archives of Gerontology and Geriatrics
Received date: Revised date: Accepted date:
18-6-2013 2-5-2014 8-5-2014
Please cite this article as: Pagotto, V., Silveira, E.A.,Applicability and agreement of different diagnostic criteria for sarcopenia estimation in the elderly, Archives of Gerontology and Geriatrics (2014), http://dx.doi.org/10.1016/j.archger.2014.05.009 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
*Manuscript - include tables in text
TITLE PAGE
Title: Applicability and agreement of different diagnostic criteria for sarcopenia estimation in the elderly
ip t
Short Title: Agreement diagnostic criteria sarcopenia
cr
Author and affiliations:
us
Valéria Pagotto Federal University of Goiás. Nursing School.
an
227th,Block.68,s/n,Leste Universitário,Goiânia,Goiás,Brazil [email protected]
M
+556281374549
Erika Aparecida Silveira
ed
Federal University of Goiás. Health Science Graduate Program. 227th,Block.68,s/n,Leste Universitário,Goiânia,Goiás,Brazil
+556281374549
ce pt
[email protected]
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
Page 1 of 23
1. Introduction Sarcopenia has been in the spotlight for the last two decades, as the losses of mass and muscle function are associated with the occurrence of adverse outcomes that can compromise quality of life and lead to precocious death (Landi et al., 2013) besides generating elevated costs for the health system (Janssen et al., 2004). Since sarcopenia
ip t
conception, one of the biggest challenges in its study has been the establishment of an
cr
operational definition for application in clinical and research settings (Baumgartner et al., 1998; Janssen et al., 2002; Newman et al., 2003).
us
Several criteria are recommended for sarcopenia diagnostic (Baumgartner et al., 1998; Janssen et al., 2002; Newman et al., 2003; Delmonico et al., 2007) as well as
an
different methods to obtain muscle mass (Janssen et al., 2000; Rolland et al., 2003; Chen
M
et al., 2007). The index most utilized is calculated by the ratio between muscle mass and the squared height, being the muscle mass obtained by dual energy X-ray absorptiometry
ed
(DXA) (Baumgartner et al., 1998) or bioelectrical impedance (BIA) (Janssen et al., 2000). When the value is lower than two standard deviations from the mean for a young reference
ce pt
population, sarcopenia is diagnosed. Other methods propose weight adjustments (Janssen et al., 2002), besides height+fat mass (Newman et al., 2003). In the last three years, sarcopenia has been defined as a geriatric syndrome, and muscle function (strength and/or muscle performance) was proposed to integrate its diagnosis in elderly
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
(Cruz-Jentoft et al., 2010; Fielding et al., 2011). The prevalence of sarcopenia in elderly has wide amplitude between countries (et al., 1998; Newman et al., 2003; Lau et al., 2005; Tichet et al., 2008; Woo et al., 2009; Sanada et al., 2010; Wen et al., 2011), including Brazil (Gobbo et al., 2012; Domiciano et al., 2013), due to the choice of method and diagnostic criteria, which, consequently, influences prevention and treatment. Studies evaluating prevalence and levels of agreement between these methods are important to recommend interventions, and to
Page 2 of 23
direct and standardize diagnostic criteria. Only one study (Bjlisma et al., 2012) compared the different diagnostic methods for sarcopenia, utilizing BIA to determine muscle mass and manual strength to evaluate muscle function. Therefore, the aim of this study was to estimate sarcopenia prevalence in community-dwelling older, according to gender and age, and analyze the agreement between different mass and muscle strength diagnostic
cr
ip t
criteria.
2. Methods
us
Data was obtained in the Elderly Project/Goiânia, a cross-sectional study whose primary purpose was to evaluate different aspects of health and nutrition of non-
an
institutionalized seniors in Goiânia/Brazil. Goiânia is located in the central-western region
M
of Brazil, 209 km from Brasilia, the nation’s capital, and is one of the main economic centers of the region. As of March/2013, population is 1,333,767 inhabitants (IBGE, 2010).
Goiás (Protocol n° 031/2007).
ed
The project was approved by the Research Ethics Committee of the Federal University of
ce pt
The sampling and data collection procedures were previously described in detail (Pagotto et al., 2011). Briefly, the study was carried out with a probabilistic sampling of 418 senior ≥60y, proportional to the number of elderly living in the nine health districts of Goiânia. We considered the following parameters to calculate this sample: outcome of
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
lower prevalence (type 2 diabetes), confidence level of 95%, statistical power 80%, prevalence ratio (RP) of 2. This amount, added to 10% to correct stratification, losses and refusals. This sample was selected by multistage random sampling and the health districts of Goiânia were the primary units. Further, we identified the Health Care Units of increased flow in each DS to draw up a list with name, age and address of the elderly. With the list of records, proceeded simple random allocation and addresses of the elderly were located on the map urban area. First, this sample was evaluated according to demographic,
Page 3 of 23
socioeconomic, health, nutrition, lifestyle and anthropometric characteristics. Then, in a second evaluation, a subsample of 132 seniors was randomly selected to evaluate sarcopenia, maintaining the same health district proportion. Pacemaker users or those presenting any type of metal embedded in the body were excluded which were requirements for BIA and DXA.
ip t
This subsample was contacted by telephone to explain the objectives of a new data
cr
collection, to schedule appointments and to inform on preparation for exams: absolute fasting for at least 4 hours and urinate 30 minutes before the tests, no consumption of
us
alcohol, caffeine and diuretics in the 24 hours and no exercise in the 12 hours preceding the tests. Data were collected in July/2009 in a specialized clinic, by a previously trained
an
team which followed standards.
M
Eleven different criteria were applied for sarcopenia diagnosis: nine of muscle mass and two of muscle strength (Table 1). DXA, BIA and Calf circumference (CC) were utilized
ed
to evaluate muscle mass, while muscle strength was obtained by hand grip strength. DXA was carried out by a total body scan, with a Lunar DPX–MD PLUS, version
ce pt
7.52.002, calibrated daily. DXA provided the Appendicular Muscle Mass (AMM), used to calculated the Appendicular Muscle Mass Index (AMMI), ratio between AMM and squared height (Baumgartner et al., 1998,10). According to this index, three cutoff points were analyzed (codes A, B and C) (Table1) (Baumgartner et al., 1998; Newman et al., 2003;
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
Lau et al., 2005; Delmonico et al., 2007; Woo et al., 2009; Cruz-Jentoft et al., 2010). For BIA, the Maltron BF906 equipment was utilized, with impedance range 2001000 Ohms. The following equation was used to estimate muscle mass: Skeletal Muscle Mass (SMM) (kg) = [Height2/ Resistance x 0,401) + (gender x 3,825) + (age x -0,071)] + 5,102 (Janssen et al., 2000). The Skeletal Muscle Index (SMI) was used to define sarcopenia in five criteria (from D to H), being criteria D and E the ratio between muscle mass and weight multiplied by 100 (SMI/Weight) (Janssen et al., 2002; Tichet et al., 2008)
Page 4 of 23
and criteria F, G and H were calculated as the ratio between muscle mass and squared height (SMI/height) (Janssen et al., 2002; Chien et al., 2008; Singh et al., 2009). CC (code I) was measured with non-elastic tape, with the senior sitting down, leg at 90⁰, at the greatest circumference. Three measurements were taken, on mean, with a cutoff point of 31 cm (Rolland et al., 2003).
ip t
Muscle strength was determined by hand-grip strength with a CROWN
cr
dynamometer (hydraulic), on dominant hand, with senior seated, with adducted shoulder, elbow flexed at 90º, forearm in neutral position, and fist extended between 0 and 30º
us
(Fess, 1992). The senior pulled the ring of the dynamometer, maintaining position for six seconds and then relaxing. Two measurements were taken, with an interval between
an
them. Two cutoff points were analyzed for GS (F1 and F2) (Table 1) (Fried et al., 2001;
measurements, resulting in 29 criteria. analyses
were
performed
using
STATA/SE
(12.0).
Sarcopenia
ed
Statistical
M
Lauretani et al., 2003). All muscle strength criteria were analyzed with these two strength
prevalence was estimated, by gender and age group with confidence intervals (CI) of 95%,
ce pt
and statistical differences were identified by the Wald Test. A simple Poisson regression was carried out, with the calculation of prevalence ratios (PR) and (CI95%). Agreement between methods was analyzed by the Kappa coefficient (k).
Ac
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
3. Results
One-hundred thirty-two seniors were evaluated (81 women and 52 men), with mean age 70.16 (±6.63) (Table 2) and 89.4% were using any medication. Morbidities were reported by the elderly, and the most prevalent were: hypertension (57.1%), diabetes mellitus (27.8%), osteoporosis (17.3%) and respiratory diseases (6.7%). Mean values of all muscle mass measurements obtained by DXA, BIA and anthropometry were highest in the male (p
