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Mechanisms of Ageing and Development
journal homepage:www.elsevier.com/locate/mechagedev
Improving the comprehension of sarcopenic state determinants: An
multivariate approach involving hormonal, nutritional, lifestyle and genetic
variables
Jonas R. Dias da Silva
a, Ivna Vidal Freire
a,b,c, Ícaro J.S. Ribeiro
a,b, Caroline Silva dos Santos
a,
Cezar Augusto Casotti
b, Djanilson Barbosa dos Santos
d, Ana Angélica Leal Barbosa
c,
Rafael Pereira
a,b,c,⁎a
Integrative Physiology Research Center, Department of Biological Sciences, State University of Southwest Bahia (UESB), Jequie, 45210-506, Bahia, Brazil
bPostgraduate Program in Nursing & Health, State University of Southwest Bahia (UESB), Jequie, 45210-506, Bahia, Brazil
cHuman Genetics Laboratory, Department of Biological Sciences, State University of Southwest Bahia (UESB), Jequie, 45210-506, Bahia, Brazil
dCentro de Ciências da Saúde, Universidade Federal do Recôncavo Baiano, Av. Carlos Amaral, 1015 - Cajueiro, Santo Antônio de Jesus, 44.570-000, BA, Brazil
A R T I C L E I N F O
Keywords:
Muscle mass Muscle strength Aging
Gene polymphism Vitamin D
A B S T R A C T
It is known that sarcopenia is a multifaceted phenomenon, which involves genetic, nutritional, hormonal and living habits aspects. Then, an integrated analysis, as a multivariate approach, could improve the comprehension about the determinants of sarcopenic state in old adults. The present study aimed to investigate the interaction among serum vitamin D, daily caloric and protein intake, lifestyle habits, ACE I/D gene polymorphism and sarcopenic state in community-dwelling old adults. One hundred one community-dwelling old adults were clinically stratified as sarcopenic or non-sarcopenic. Serum vitamin D, daily caloric and protein intake, lifestyle habits (smoking, physical activity level and sedentary behavior) and ACE I/D gene polymorphism were recorded. A multivariate logistic regression technique was applied to investigate the interaction among the selected in-dependent variables and the sarcopenic state. The inin-dependent variables age, smoking, serum Vitamin D and ACE I/D polymorphism achieved the statistical criteria to be inserted in the multivariate analysis. After a stepwise procedure from the multivariate logistic regression, the variables age, serum Vitamin D and ACE I/D polymorphism remained, together, in thefinal model. Sarcopenic state was significantly associated to older age, II-genotype and low serum Vitamin D in old adults from 60 years old.
1. Introduction
Sarcopenia is a burden and a challenge for public health (Beaudart et al., 2014a;Morley et al., 2014;Sousa et al., 2016) due to significant clinical consequences as functional decline, higher rate of falls and in-cidence of hospitalizations, as well as higher rate of mortality among sarcopenic old adults, leading to economic impacts. (Beaudart et al., 2017). In fact, since 1989, when Irwin Rosenberg proposed this term to define a age-related decrease of muscle mass (Rosenberg, 1988), nu-merous studies have been developed to refine the diagnosis criteria and establish the associated factors, as well as the consequences of this condition (Cruz-Jentoft et al., 2010;Morley et al., 2014;Santilli et al., 2014;Studenski et al., 2014), aiming to develop strategies to deal with this global problem.
Prevention is an important cost-effective strategy in public health, but depends on the knowledge regarding the associated factors to a
specific outcome. In this context, it is known that sarcopenia is a multifaceted phenomenon, which involves genetic, nutritional, hor-monal and living habits aspects (Baumgartner et al., 1999;Curcio et al., 2016).
Age-related declines in anabolic hormones have been reported as an important determinant to the sarcopenic state in old adults (Morley, 2016;Swiecicka et al., 2017). Notably, a growing attention have been given to the serum vitamin D (25-hydroxyvitamin D) levels, owing to the basic and clinical evidences of the relationship between vitamin D deficiency (i.e., serum vitamin D levels below 20 ng/ml) and many negative outcomes, including greater age-related decline in muscle mass and function (Dretakis et al., 2010;Garcia et al., 2011; Girgis et al., 2013).
However, it is important to note that an adequate nutritional sup-port to the skeletal muscle cells is critical to allow an effective hormonal anabolic stimulus. Indeed, a great number of recommendations have
https://doi.org/10.1016/j.mad.2018.05.008
Received 17 March 2018; Received in revised form 4 May 2018; Accepted 24 May 2018
⁎Corresponding author at: Integrative Physiology Research Center, Department of Biological Sciences, State University of Southwest Bahia (UESB), Jequie, 45210-506, Bahia, Brazil.
E-mail address:rpfi[email protected](R. Pereira).
Available online 25 May 2018
0047-6374/ © 2018 Elsevier B.V. All rights reserved.
been published (Bauer et al., 2013;Jeejeebhoy, 2012;Millward, 2012), proposing cut-points for elderly's diet nutrients, especially for daily protein intake, to mitigate the age-related decline in muscle mass and function. For example, recommended daily protein intake range from 0.8 g/Kg to 1.2 g/Kg (Bauer et al., 2013;Deer and Volpi, 2015), was associated to a positive anabolic state, conferred by anabolic hormones and physical exercises, may provide an effective way to prevent the sarcopenic state in old adults.
Recognize the clear interaction between anabolic hormonal state and diet adequacy is essential when the aim is to improve the com-prehension of determinants of the sarcopenic state in old adults, but the influence of genetic aspects (Garatachea and Lucía, 2013; Tan et al., 2012) and lifestyle habits (Scott et al., 2011) could not be neglected together to these variables. In this context, an insufficiently active lifestyle (Scott et al., 2011), a sedentary behavior (Gianoudis et al., 2015) and the smoking habit (Rom et al., 2012) lead old adults to be prone to sarcopenic state. Notwithstanding, many candidate genes have been pointed as associated to the sarcopenic state (Garatachea and Lucía, 2013;Tan et al., 2012), and the ACE insertion/deletion (ACE I/ D) gene polymorphism is one among them.
The ACE I/D gene polymorphism is one of the most widely studied genetic variants, maybe owing to the wide association to many cardi-ovascular outcomes, as hypertension, left ventricular hypertrophy, heart failure, renal diseases (Duran et al., 2016; Normaznah et al., 2016). In fact, D allele is associated with higher ACE activity (Danser et al., 1992), leading to a greater angiotensin II production, which exert vascular effects (e.g., vasoconstriction), but also enhance skeletal muscle hypertrophy (Gordon et al., 2001).
The evidence of gene expression of RAS components, which
included ACE gene, in skeletal muscle, emphasizes the possible infl u-ence of over this tissue (Dietze and Henriksen, 2008;Jones and Woods, 2003). Angiotensin II may exert a direct hypertrophic effect on skeletal muscle, as well as, an indirect effect stimulating a local (i.e., skeletal muscle site) of others growth factors (Johnston et al., 2010;Jones and Woods, 2003; Westerkamp and Gordon, 2005), which justify the re-ported association of ACE I/D gene polymorphism and muscle mass and strength (Jones and Woods, 2003).
Indeed, many studies have suggesting a greater muscle mass, strength and hypertrophic response to resistance training in old adults carrying the D allele (Charbonneau et al., 2008; Rom et al., 2012; Vigano et al., 2009). In opposition, other studies have not confirmed these associations (Garatachea et al., 2012;McCauley et al., 2010). The source of divergence among these results could involve the ethnicity of studied populations, as well as, the absence of control for variables, as hormonal, nutritional and lifestyle variables, which is essential when studying old adults.
An integrated analysis, as with a multivariate approach, could im-prove the comprehension about the determinants of sarcopenic state in old adults. Thus, the present study aimed to investigate the interaction among serum vitamin D, daily caloric and protein intake, lifestyle ha-bits, ACE I/D gene polymorphism and sarcopenic state in community-dwelling old adults.
2. Methods
2.1. Sample
community-dwelling old adults (≥60 years old) from Aiquara, Bahia,
Brazil. All community-dwelling old adults were home-visited and in-vited to take part in this survey study. Then, 289 subjects were screened, however, bedridden individuals and/or those with severe cognitive impairment were excluded (n = 20). A health questionnaire, as well as a clinical and physical examination, was conducted in 289 old adults that volunteered, but only 101 old adults presented the complete data needed to the sarcopenic state classification, while only 91 old adults presented the complete data from the included in thefinal model of the multivariate logistic regression (see the results section). Fig. 1 presents theflow chart of the sample selection process andTable 1the characteristics of the participants. Data were collected between January and July 2015. Written informed consent was obtained from all sub-jects, and all procedures were approved by local ethics committee ac-cording to Helsinki Declaration. Each subject underwent the experi-mental procedures under the same instructions and conditions.
2.2. Sarcopenic classification
The stratification in sarcopenic and non-sarcopenic old adults was done as Freitas et al. (Freitas et al., 2018), which followed the criteria used by Pinheiro et al. (Pinheiro et al., 2015), which is based on the European Consensus on definition and diagnosis (Cruz-Jentoft et al., 2010). Thus, three elements were considered to classify the old adults: Muscle mass, muscle strength and performance. Aiming to facilitate the comprehension, the Table 2 compile the used criteria to stratify the studied population as sarcopenic and non-sarcopenic older adults.
2.2.1. Muscle mass component
The total muscle mass (TMM) was estimated through the equation proposed by Lee et al (Lee et al., 2000) and validated for use in Bra-zilians elderly (Rech et al., 2012): TMM (kg) = (0.244 x body weight) + (7.8 x height) - (0.098 x age) + (6.6 x sex) + (ethnicity - 3.3). For sex: women = 0 and men = 1; for ethnicity, self-reported and subse-quently categorized: white = 0, Asian = - 1.2 and Afro-descen-dent = 1.4.
From the TMM, the skeletal muscle index [SMI = TMM/height2] was calculated, which was subsequently classified according to the cut-off points proposed by Janssen et al (Janssen et al., 2004): SMI≤5.75 kg/m2 for women and ≤ 8.50 kg/m2 = high risk,
5.76 < SMI≤6.75 kg/m2for women and 8.51 < SMI≤10.75 kg/m2
for men = moderate risk, and SMI > 6.75 kg/m2 for women and > 10.75 kg/m2for men = low risk. For analysis purposes, the SMI was recategorized: SMI≤6.75 kg/m2 for women and ≤10.75 kg/m2 for
men = insufficient muscle mass; SMI≥6.75 kg/m2 for women and ≥10.75 kg/m2for men = adequate muscle mass.
2.2.2. Muscular strength component
Handgrip strength was recorded with a calibrated handgrip dy-namometer (SAEHAN Corporation, SH5001, Masan, South Korea). Volunteers were sitting in a chair with a backrest, and hips at 90°. The arms were kept at the side of the body, but with the elbow from the preferable arm (informed by each volunteer) at 90° and the forearm in neutral position (i.e., between pronation and supination).
The weakness was defined according to the body mass index [BMI = body mass (kg) / height2(m)], using the adapted criteria from Fried et al (Fried et al., 2001). Firstly, subjects were classified according to the BMI (National Council On The Aging, 2002): < 22 kg/m2 = underweight, 22.0≤BMI ≤27 kg/m2 = adequate; > 27 kg/m2 =
overweight. Then, for each BMI category, the cut-off value for the handgrip strength, indicative of weakness, wasfixed on the 25th per-centile (first quartile): category low weight = cut-offpoint of 24 kg for men and 18 Kg for women; adequate = 27 kg for men and 18 Kg for women; overweight = 25 kg for men and 23 Kg for women. Individuals who met the criteria of weakness, (i.e.fit below the cut-offpoint of their BMI category) were considered with insufficient muscle strength.
2.2.3. Physical performance component
Physical performance was assessed using the timed up and go (TUG) test, as described previously (Podsiadlo and Richardson, 1991). The poor performance was defined according to the elderly’s height, using an adapted criterion from Guralnik et al (Guralnik et al., 1994). Firstly, the subject’s height was classified into two categories, based on the Table 1
Characteristics of the studied populationΦ according to the sarcopenic state (i.e., sarcopenic or non-sarcopenic older adults).
Variable Sarcopenic (n = 21)
Non-Sarcopenic (n = 70)
P value
Age (years old)§ 74.0 ± 10.0 68.5 ± 10.3 0.001
BMI (Kg/cm2)§ 21.9 ± 6.7 27.2 ± 5.8 < 0.001
SMI (TMM/height2)* 7.2 ± 2.1 8.6 ± 1.7 0.005
Handgrip strength (Kgf)*
20.0 ± 6.1 27.5 ± 7.0 < 0.001
TUG test (s)§ 8.6 ± 4.1 6.0 ± 2.0 < 0.001
(Φ) Characteristics from the 91 old adults with complete data regarding the
sarcopenic state classification, ACE I/D gene polymorphism, serum Vitamin D concentration and age; (*) unpairedt-test, data presented as mean ± SD; (§) Mann-Whitney Test, data presented as median ± interquatile range.
Table 2
Compilation of the used criteria to stratify the studied population as sarcopenic and non-sarcopenic older adults.
Parameters Cut-off
Muscle mass component: skeletal muscle index (SMI = TMM/height2) [42] SMI
≤6.75 kg/m2for women and≤10.75 kg/m2for men Muscular strength component: Handgrip strength (Kg) ≤24 kg for men and 18 Kg for women if BMI < 22 kg/m2
≤27 kg for men and 18 Kg for women if BMI ranging from 22 to 27 kg/m2 ≤25 kg for men and 23 Kg for women if BMI ranging from > 27 kg/m2 Physical performance component: timed up and go (TUG) test 9 seconds for both sex, if height is≤1.51 m
7 seconds for both sex, if height is > 1.64 m
Classification according to categories proposed by Cruz-Jentoft et al. [5] Outcome
without sarcopenia adequate muscle mass, muscle strength and physical performance
pre-sarcopenia insufficient muscle mass, but adequate muscle strength and physical performance sarcopenia insufficient muscle mass + insufficient muscle strength or physical performance severe sarcopenia insufficient muscle mass + insufficient muscle strength and physical performance
Reclassification according to categories proposed by Pinheiro et al. [39] Outcome
non-sarcopenic without sarcopenia + pre-sarcopenia
median (50th percentile): ≤1.51 m for women and ≤1.64 m for
men = below or equal to median; > 1.51 for women and > 1.64 m for men (i.e., above the median). Thus, for each height category, the cut-off point for the test’s runtime indicative of poor performance was set in the 75th percentile (third quartile): ≤median height = 9 s for both
sex; > median height = 7 s for both sex. Individuals who met the cri-teria for poor performance were considered of insufficient physical performance.
2.3. Outcome (dependent variable)
After defining the three components of sarcopenia, the old adults were initially classified in four categories as proposed by Cruz-Jentoft et al (Cruz-Jentoft et al., 2010): without sarcopenia = adequate muscle mass, muscle strength and physical performance; pre-sarcopenia = in-sufficient muscle mass, but adequate muscle strength and physical performance; sarcopenia = insufficient muscle mass + insufficient muscle strength or physical performance; severe sarcopenia = in-sufficient muscle mass + insufficient muscle strength and physical performance. Following the classification proposed by Pinheiro et al. (Pinheiro et al., 2015), sarcopenia was recategorized as a dichotomous variable: without sarcopenia + pre-sarcopenia = non-sarcopenia; sar-copenia + severe sarsar-copenia = sarcopenic.
2.4. Gene polymorphism identification
Venous blood withdrawal (10 ml from the antecubital vein) was carried out, and used for DNA processing. Blood samples was submitted to ACE I/D gene polymorphism identification using polymerase chain reaction (PCR) amplification of the intron 16 region of ACE gene to determine if the Alu repeat sequences were present. Firstly, whole blood aliquots were submitted to a DNA extraction using the Qiagen QIAamp DNA Blood Mini Kit (QIAGEN Inc. Valencia, CA, USA) ac-cording to the procedure provided by manufacture.
DNA sequences were amplified using primers flanking the poly-morphic region (sense 5′CTG-GAG-ACC-ACT-CCC-ATC-CTT-TCT3′and antisense 5′GAT-GTG-GCC-ATC-ACA-TTC-GTC-AGA-T3′). PCR profiling and genotyping of I/D polymorphisms were conducted as described previously (Rigat et al., 1992). For each set of reactions, a negative control containing H2O instead of DNA was carried out to check for contaminations, and aleatory samples were analyzed to check if re-sults were identical for all samples.
To avoid the possibility of erroneous classification of ID hetero-zygotes as DD homohetero-zygotes (Shanmugam et al., 1993), all DD samples were reamplified by a second primer pair specific for the inserted se-quence (Sense: 5′- TGGGACCACAGCGCCCGCCACTAC-3′and Antisense: 5′- TCGCCAGCCCTCCCATGCCCATAA 3′).
The fragments resulting from the PCR reactions were stained with bromophenol blue and red gel, and then, detected by conventional agarose gel (2%) electrophoresis. The fragments in each gel were vi-sualized under ultraviolet light and the images were digitalized using a transluminator with the image capture software L-Pix Image version 1.21 (Loccus Biotecnologia- Locus do Brazil, Cotia, SP, Brazil). Differences in the electrophoretic profile were used to genotype the subjects.
All genotyping was performed by the same researcher who was blinded to subject data. The study design was a double-blind approach with respect to the participants’genotype.
Considering the hypothesis of an advantage in muscle mass con-ferred by the D allele (Garatachea and Lucía, 2013;Tan et al., 2012), subjects were grouped on the basis of D allele of ACE gene: those car-rying ID or DD genotype and those carcar-rying II genotype.
2.5. Serum vitamin D determination
Serum vitamin D (25-hydroxyvitamin D) concentration was
determined from blood samples using standard equipment and method (Hutchinson et al., 2017). Data was dichotomized as adequate (equal or > 20 ng/ml) or inadequate (< 20 ng/ml) according to the criteria for vitamin D deficiency (Holick et al., 2011). The cut-point of≥20 ng/
ml was also adopted in accordance to Mastaglia et al (Mastaglia et al., 2011), that showed that a serum vitamin D (25-hydroxyvitamin D) le-vels ≥ 20 ng/ml were found to be associated with better muscle
function and strength in old adults. Blood samples were taken in Jan-uary, when it is summer in the south hemisphere.
2.6. Estimated daily caloric and protein intakes
Daily foods and beverages consumed were recorded through a 24-hour recall, as recommended by Rutishauser (Rutishauser, 2005), and estimated daily caloric intake and estimated daily protein intake was calculated with the software DietPro®version 5.8.1. To adjust the es-timated daily caloric and protein intakes to each subject needs, these parameters were relativized to each volunteer. The estimated daily caloric intake was normalized by the Resting Energy Expenditure (REE) for each volunteer, then, values below 1.0 indicated that the estimated daily caloric intake was not adequate to the Resting Energy Expenditure (REE), indicating a deficit in the caloric intake. The estimated daily protein intake was dichotomized as adequate (equal or > 1.2 g/Kg) or inadequate (< 1.2 g/Kg) according to the recommendation for daily protein intake (Bauer et al., 2013).
2.7. Physical activity level and sedentary behavior
Physical activity level was obtained from the International Physical Activity Questionnaire (IPAQ) and data dichotomized according to the proposed cut-point of≥150 min/week of moderate and vigorous
ac-tivity (i.e., ≥150 min/wk, Sufficiently active; < 150 min/wk, Insufficiently active) (WHO, 2010).
Sedentary behavior was also determined from the IPAQ (fifth and last domains) (Benedetti et al., 2004), which considers the time (hours/ day) that the older adults remains seated in different places including at home, in the living group for older adults, medical office, as well as the time sitting while resting, watching TV, visiting friends and relatives, reading, making phone calls and eating. But it does not include time sitting during transport (e.g., bus or car). Data from sedentary behavior was dichotomized according to cut-point of 7 h/day (i.e.,≥7 h/day,
sedentary behavior; < 7 h/day, non-sedentary behavior) as proposed by Coqueiro et al (da Silva Coqueiro et al., 2017) as a cut-point asso-ciated to frailty in old adults.
2.8. Statistical analysis
After genotype analyses, subjects were classified according to allele frequency: II, ID or DD. A Chi-square test (χ2) was used to determine whether observed genotype frequency was in Hardy-Weinberg equili-brium (Crow et al., 1999).
In order to identify differences in proportions distributed between sarcopenic and non-sarcopenic group (dependent variable), the Chi-square test was used. Smoking habit (yes vs no), Diabetes Mellitus (yes vs no), physical activity level (Sufficiently active vs Insufficiently ac-tive), sedentary behavior (sedentary behavior vs non-sedentary beha-vior), estimated daily caloric intake (adequate vs inadequate), esti-mated daily protein intake (adequate vs inadequate), serum vitamin D concentration (adequate vs inadequate) were studied as independent variables. The variable age was used as continuous variable (years old), thus, Studentt-test was used to comparisons between sarcopenic and non-sarcopenic groups.
(i.e., sarcopenic state) was tested by a multivariate logistic regression model using the "Backward LR" method.
The variables that achieved a significance level of p < 0.1 in the univariate testes (i.e., Chi-square test for categorical variables and Student t-test for continuous variables) were included in multivariate
analysis as proposed by Conover (Conover, 1999). For all other ana-lyzes, significance level was 5% and completed using IBM SPSS V.21.0 (SPSS, IBM Corporation, Armonk, New York, USA).
3. Results
From 101 old adults, 61 were women (60.0%) and mean age was 70.6 ± 7.2 years old (60–95 ys old) and the prevalence of sarcopenia was 20.8%. When considering only the 91 old adults included in the final model of the multivariate logistic regression (see the methods section), the prevalence of sarcopenia in the studied population changed slightly (23.0%), and the sarcopenic group were older (p < 0.05), when compared to non-sarcopenic ones (see Table 1). Among studied variables smoking habit, low serum vitamin D con-centration and II genotype of ACE gene were significantly associated to the sarcopenic state (seeTable 3).
According to the established criteria for inclusion in the multi-variate regression model (p < 0.1 at unimulti-variate analysis), the variables age, smoking habit, low serum vitamin D concentration and II genotype of ACE gene were inserted in the multivariate logistic regression model using the "Backward LR" method, but the variable smoking habit was excluded along the statistical process. The others variables remained in thefinal model, which is presented inTable 4. The results from thefinal model of the multivariate regression indicated that older adults, II genotype carriers and with low serum Vitamin D concentration (< 20 ng/ml) are prone to present sarcopenic state. Since only 91 old adults had complete data from ACE I/D gene polymorphism and Serum Vitamin D concentration (seeTable 3), the sample size included in the final model of the multivariate regression were 91 old adults.
4. Discussion
This study aimed to investigate the interaction among serum vi-tamin D, daily caloric and protein intake, lifestyle habits, ACE I/D gene polymorphism and sarcopenic state in community-dwelling old adults. Our results showed an interesting interaction among biological factors to determine the sarcopenic state, since age, low vitamin D con-centration and II genotype of ACE gene were significantly associated to the sarcopenic state in the studied population.
It is proposed that muscle mass and size decrease by approximately 6% per decade in the average person beginning at approximately 45 years of age (Janssen and Ross, 2005), but this trend could be positive or negatively influenced by many factors, as race, age, sex, genetic background, hormonal status, nutritional and lifestyle habits, and others (Abellan van Kan, 2009;Garatachea and Lucía, 2013;Gianoudis et al., 2015;Scott et al., 2011;Tan et al., 2012).
The exposed fact, summed to the used assessment tool, contribute to explain the huge variance of prevalence of sarcopenia among different studies (Kalinkovich and Livshits, 2015). In our study we found a pre-valence of 20.8%, which was close to worldwide estimates (Beaudart et al., 2017;Berger and Doherty, 2010;Janssen, 2011;Morley, 2008), as well as for Brazilian old adults (da Silva Alexandre et al., 2014;Diz et al., 2017). Additionally, we found that sarcopenic group were older when compared to non-sarcopenic ones (76.0 ± 7.9 vs 69.2 ± 6.4 years old), reflecting a well-established association between age and sarcopenia (Berger and Doherty, 2010;Janssen, 2011;Morley, 2008).
Besides the significant association between age and sarcopenia, we found a significant association between ACE I/D gene polymorphism, as well as serum vitamin D concentration, and sarcopenia.
A greater proportion of II-genotype carriers (46.2%) were found among sarcopenic old adults, being found an odds ratio [95% CI] of 4.29 [1.24–14.85] for II-genotype carriers, pointing the old adults with this genetic background prone to develop sarcopenia. Numerous studies have reporting that the ACE I/D gene polymorphism seem to be a de-terminant of ACE at a cellular level (Danser et al., 1992;Davis et al., Table 3
Absolute and relative data of diabetes mellitus, smoking habit, physical activity level, sedentary behavior, estimated daily caloric intake, estimated daily protein intake, serum vitamin D concentration, and ACE I/D gene polymorphism of studied old adults according to the sarcopenic state (sarcopenic or non-sarcopenic). Aiquara, Bahia, Brazil (2015).
Variable Sarcopenic Non-Sarcopenic OR [95 CI] P value
Diabetes Mellitus Yes 4 (21.1%) 15 (20.8%) 1.01 [0.293–3.50] 0.983
No 15 (78.9%) 57 (79.2%)
Smoking habit Yes 3 (18.8%) 3 (4.5%) 4.85 [0.89–26.74] 0.085†
No 13 (81.3%) 63 (95.5%)
Physical activity level Sufficiently active 13 (76.5%) 41 (57.7%) 0.42 [0.12–1.42] 0.178
Insufficiently active 4 (23.5%) 30 (42.3%)
Sedentary behavior sedentary behavior 15 (78.9%) 52 (72.2%) 1.44 [0.43–4.87] 0.771
non-sedentary behavior 4 (21.1%) 20 (27.8%)
Estimated daily caloric intake adequate 3 (15.0%) 21 (29.2%) 2.33 [0.62–8.81] 0.258
inadequate 17 (85.0%) 51 (70.8%)
Estimated daily protein intake adequate 8 (38.1%) 34 (44.2%) 1.28 [0.48–3.45] 0.619
inadequate 13 (61.9%) 43 (55.8%)
Serum vitamin D concentration adequate 12 (57.1%) 64 (91.4%) 8.00 [2.40–26.64] < 0.001*
inadequate 9 (42.9%) 6 (8.6%)
ACE I/D gene polymorphism Homozygous II 6 (31.6%) 7 (9.7%) 4.29 [1.24–14.85] 0.015*
Allele D (ID + DD) 13 (68.4%) 65 (90.3%)
(†) Significant at p < 0.1; (*) Significant at p < 0.05.
Table 4
Regression coefficient, adjusted Odds Ratio (OR), 95% confidence interval of the OR and the p value of the variables included in thefinal model from the multivariate logistic regressionΦ. Aiquara, Bahia, Brazil (2015).
Variable Regression Coefficient
P value adjusted Odds Ratio
CI 95% Odds Ratio
ACE I/D gene polymorphism
2.32 0.008 10.21 [1.85–
56.47] Serum Vitamin D
concentration
2.40 0.002 10.99 [2.35–
51.46]
Age 0.16 0.002 1.17 [1.06–
1.30]
Constant −14.01 0.001 – –
(Φ) Results from the 91 old adults with complete data regarding the sarcopenic
2000; Mizuiri and Ohashi, 2015), influencing the Angiotensin II pro-duction at a cellular level. Thus, D allele carriers (i.e., ID and DD genotype carriers) exhibit a greater Angiotensin II production, favoring the skeletal muscle hypertrophy (Gordon et al., 2001).
Previous studies, involving old people, have not observed significant association between ACE I/D gene polymorphism and muscle mass and strength (Garatachea et al., 2012;McCauley et al., 2010), both used parameters to clinically classify old adults according to sarcopenia criteria, but an important point need to be highlighted: ethnicity, sex, age and environment are factors that could influence the phenotype, despite the same genetic background, and these studies have not con-sidered the interaction with other biological variables.
In line with this perspective, our results indicated a significant as-sociation of ACE I/D gene polymorphism and sarcopenia, and shed light over the interaction with other biological variables, since the interac-tion with low serum vitamin D concentrainterac-tion raised the odds ratio of II-genotype carriers to have sarcopenia from 4.29 [1.24–14.85] to 10.21 [1.85–56.47].
Our results from serum Vitamin D concentration corroborate pre-viousfinds regarding the influence of this hormone on muscle mass and function in both young and old adults (Beaudart et al., 2014b;Hirani et al., 2017;Marantes et al., 2011). In fact, this was the most influent variable found in our study and, alone, low serum vitamin D (< 20 ng/ ml) exhibited an odds ratio of 8.00 [2.40–26.64], which increase with the interaction with II-genotype, rising to 10.99 [2.35–51.46].
The mechanisms underlying this fact probably involve two ways: 1) an indirect way, involving serum calcium and phosphate and; 2) a di-rect way, involving the activation of the vitamin D receptor (VDR) on muscle cells, regulating the transcription of genes related to calcium handling and muscle cell differentiation and proliferation (Ceglia, 2009;Girgis et al., 2013). Then, considering the age-related changes in calcium metabolism and muscle protein synthesis, owing to the phy-siological decrease of sexual hormones (i.e., testosterone and estrogens) along the aging process, the decrease of serum vitamin D may have a substantial impact over the muscle mass and function, besides the possible influences on the neuromuscular function (Marantes et al., 2011).
Curiously, the studied lifestyle and nutritional variables did not compound the final model from the multivariate logistic regression. From lifestyle habits, only the smoking habit achieved the criteria to be inserted in the multivariate procedure, but was excluded by the sta-tistical model, characterized by "backward" steps, where variables that not contributing to the model’s ability to predict the studied outcome, are step by step excluded until the impossibility of exclude more vari-ables (Dawson and Trapp, 2004; Riffenburgh, 2005). Thus, the re-mained variables constitute the final model, and represent variables that, grouped, lead to a better statistical power to predict/explain a studied outcome, in our study, the sarcopenic state.
A physically active lifestyle and a high-protein intake diet are re-ported as protective factors against the sarcopenia (Bradlee et al., 2017), but these associations were not observed in our study. Limita-tions of used instruments to record physical active lifestyle and nutri-tional habits, which estimate the physical active level and daily protein intake, could explain this fact, and the use of other instruments, as accelerometers, to classify the physical active level, and direct measures of protein intake may improve the analysis.
Thus, it is suggested that further studies should consider the use of the suggested methods, as well as, the inclusion of other biological variables, as the quantification of anabolic hormones (e.g., androgens, GH, IGF-1 and others), hormones and cytokines involved in the muscle catabolism (e.g., glucocorticoids, TNF-α), and the analysis of other genetic polymorphisms (e.g., Vitamin D receptor [VDR], actinin alpha 3 [ACTN-3] and others), allowing to study the interaction of these factors that potentially lead old adults to a sarcopenic state. We reinforce the suggestion to further studies use multivariate approach in statistical methods, aiming to keep improving the comprehension of sarcopenic
state determinants.
It is important to note that there are an intense debate regarding to the diagnostic criterion of sarcopenia and some recommendations have been proposed. A universal criterion remains to be constructed, but a common aspect of the proposed recommendations is that the clinical diagnostic should involve/merge indicators of muscle mass and func-tion (i.e., physical performance). As showed in a very recent systematic review (Beaudart et al., 2017), gait speed have been widely used as a tool to assess physical performance, and then, to compose the criteria to classify the old adults as sarcopenic. In our study the gait speed was also used as a tool to assess physical performance, but we opt to use a cutoff based on the anthropometric characteristics and the performance of the studied population, as used by Pinheiro et al. (Pinheiro et al., 2015). This option allows to identify, among the studied old adults, those with a worse physical performance, rather than use cutoffparameters stan-dardized with samples from other countries and with different char-acteristics. We argue that this is an interesting approach when studying a specific population, as we did. Additionally, this option leads to a prevalence of sarcopenia close to worldwide estimates, as discussed previously.
5. Conclusion
In summary, in this study sarcopenic state was significantly asso-ciated to older age, II-genotype and low serum Vitamin D in old adults from 60 years old. The multivariate approach used seems able to im-prove the comprehension of sarcopenic state determinants, since re-inforce the ability of each determinant to predict/explain the studied outcome, when compared to the odds obtained from univariate ana-lysis.
Conflict of interest
The authors declare that there is no conflict of interest.
Acknowledgment
Authors thank the collaborators from the Integrative Physiology Research Center for the technical and scientific support.
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