Sarcopenia and its association with changes in socioeconomic, behavioral, and health factors: the EpiFloripa Elderly Study

Susana Cararo Confortin Lariane Mortean Ono Aline Rodrigues Barbosa Eleonora d’Orsi About the authors

Abstract:

This study aimed to verify the prevalence of sarcopenia and its association with changes in socioeconomic, behavioral, and health factors in the elderly. The longitudinal population-based study included 598 elderly (≥ 60 years) in Florianópolis, Santa Catarina State, in the South of Brazil. Sarcopenia was defined on the basis of appendicular skeletal mass index (ASMI) according to gender (ASMI < 7.26kg/m² for men and < 5.5kg/m² for women). We assessed changes that occurred between the two study waves (2009/2010 and 2013/2014) in relation to socioeconomic, behavioral, and health factors. Crude and adjusted logistic regression analyses were performed. Prevalence of sarcopenia was 17% in women (95%CI: 12.4-22.9) and 28.8% in men (95%CI: 21.3-37.7). In the final model, women that continued to consume or that started consuming alcohol (OR = 0.31; 95%CI: 0.11-0.91) showed lower odds of sarcopenia. Women who continued to smoke or that started smoking (OR = 2.55; 95%CI: 1.16-5.58) and/or that remained inactive or became insufficiently active (OR = 2.90; 95%CI: 1.44-5.84) showed higher odds of sarcopenia. For men, no change variable was associated with sarcopenia. The results suggest that continuing or starting to smoke and remaining or becoming physically inactive are preventable and modifiable risk factors for sarcopenia.

Keywords:
Sarcopenia; Health of the Elderly; Aged; Behavior; Socioeconomic Factors

Introduction

Sarcopenia was originally defined nearly three decades ago as a gradual reduction in skeletal muscle mass with advancing age 11. Rosenberg IH. Summary comments: epidemiological and methodological problems in determining nutritional status of older persons. Am J Clin Nutr 1989; 50:1231-3.. The European Working Group on Sarcopenia in Older People 22. Cruz-Jentoft JA, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010; 39:412-23. recently incorporated into the loss of muscle mass the reduction in physical strength and function that occurs with the aging process. However, there is no universal working definition or diagnostic criterion for sarcopenia 22. Cruz-Jentoft JA, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010; 39:412-23.. Since loss of muscle mass and strength may not be simultaneous in the same individual 33. Visser M, Schaap LA. Consequences of sarcopenia. Clin Geriatr Med 2011; 27:387-99., some studies disaggregate these characteristics 33. Visser M, Schaap LA. Consequences of sarcopenia. Clin Geriatr Med 2011; 27:387-99.,44. Clark BC, Manini TM. Sarcopenia ? dynapenia. J Gerontol A Biol Sci Med Sci 2008; 63:829-34., with loss of muscle mass verified by the appendicular skeletal mass index 55. Batsis JA, Mackenzie TA, Lopez-Jimenez F, Bartels SJ. Sarcopenia, sarcopenic obesity, and functional impairments in older adults: National Health and Nutrition Examination Surveys 1999-2004. Nutr Res (New York, NY) 2015; 35:1031-9.,66. Dufour AB, Hannan MT, Murabito JM, Kiel DP, McLean RR. Sarcopenia definitions considering body size and fat mass are associated with mobility limitations: the Framingham Study. J Gerontol A Biol Sci Med Sci 2013; 68:168-74. (ASMI = appendicular skeletal mass (ASM) /height²), used as the diagnostic criterion for sarcopenia in population-based studies 77. Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998; 147:755-63.,88. Janssen I. Influence of sarcopenia on the development of physical disability: the Cardiovascular Health Study. J Am Geriatr Soc 2006; 54:56-62.,99. Delmonico MJ, Harris TB, Lee J-S, Visser M, Nevitt M, Kritchevsky SB, et al. Alternative definitions of sarcopenia, lower extremity performance, and functional impairment with aging in older men and women. J Am Geriatr Soc 2007; 55:769-74.. Regardless of the working definition, sarcopenia should be assessed to determine its natural course and develop effective treatments for this syndrome.

Sarcopenia contributes to adverse health outcomes such as functional incapacity, frailty, declining quality of life, and premature death 1010. Landi F, Liperoti R, Russo A, Giovannini S, Tosato M, Barillaro C, et al. Association of anorexia with sarcopenia in a community-dwelling elderly population: results from the ilSIRENTE study. Eur J Clin Nutr 2013; 52:1261-8.,1111. Lang T, Streeper T, Cawthon P, Baldwin K, Taaffe DR, Harris T. Sarcopenia: etiology, clinical consequences, intervention, and assessment. Osteoporos Int 2010; 21:543-59.. It can be considered a public health problem 77. Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998; 147:755-63. due to its social implications including loneliness and need for care and its health policy impact 1212. Veras RP. Estratégias para o enfrentamento das doenças crônicas: um modelo em que todos ganham. Rev Bras Geriatr Gerontol 2011; 14:779-86., besides generating high costs for the health system 1313. Janssen I, Shepard DS, Katzmarzyk PT, Roubenoff R. The healthcare costs of sarcopenia in the United States. J Am Geriatr Soc 2004; 52:80-5..

The prevalence of sarcopenia depends on the methodology employed in its identification and the characteristics of the study population, and it is more prevalent in men and in older individuals 1414. Pagotto V, Silveira EA. Applicability and agreement of different diagnostic criteria for sarcopenia estimation in the elderly. Arch Gerontol Geriatr 2014; 59:288-94.. In the elderly, prevalence of sarcopenia varies from 13% to 22.6% in women and from 19% to 26.8% in men 66. Dufour AB, Hannan MT, Murabito JM, Kiel DP, McLean RR. Sarcopenia definitions considering body size and fat mass are associated with mobility limitations: the Framingham Study. J Gerontol A Biol Sci Med Sci 2013; 68:168-74.,1515. Iannuzzi-Sucich M, Prestwood KM, Kenny AM. Prevalence of sarcopenia and predictors of skeletal muscle mass in healthy, older men and women. J Gerontol A Biol Sci Med Sci 2002; 57:M772-7., according to the method and cutoff proposed by Baumgartner et al. 77. Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998; 147:755-63.. In Brazil, data from a systematic review 1616. Diz JBM, Leopoldino AAO, Moreira BS, Henschke N, Dias RC, Pereira LSM, et al. Prevalence of sarcopenia in older Brazilians: a systematic review and meta-analysis. Geriatr Gerontol Int 2017; 17:5-16. on the topic showed that prevalence of sarcopenia was 20% in women and 12% in men.

The etiology of sarcopenia is known to be multifactorial, that is, dependent on and resulting from multiple causes, probably interconnected, that intervene in its development and progression. These causes feature aging itself, genetic factors, sociodemographic factors, lifestyle, and certain health conditions 66. Dufour AB, Hannan MT, Murabito JM, Kiel DP, McLean RR. Sarcopenia definitions considering body size and fat mass are associated with mobility limitations: the Framingham Study. J Gerontol A Biol Sci Med Sci 2013; 68:168-74.,77. Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998; 147:755-63.. This complex causal model that combines diverse components dynamically constitutes the syndrome’s determinants. Technical and methodological differences in establishing the diagnosis also hinder the syndrome’s assessment, the comparison between studies, and the development of policies for the prevention and treatment of sarcopenia.

The effects of changes in the socioeconomic, behavioral, and health-related factors on the syndrome have received relatively little attention in the population over 60 years of age. The analysis of changes in factors over a given time period can allow the identification of their impact on the health of the elderly and determine whether it is still possible to intervene in this stage of life in order to delay or reverse negative effects, allowing these individuals to live longer with independence, autonomy, and quality of life. The study also aims to verify the prevalence of sarcopenia and its association with changes over the course of three years in socioeconomic, behavioral, and health factors in elderly residents of Florianópolis, Santa Catarina State, Brazil.

Methods

Reference area and population

The current study used as the reference population the elderly in the epidemiological survey entitled Health Conditions of the Elderly in Florianópolis: the EpiFloripa Elderly Study, using the EpiFloripa Elderly data for 2009/2010 as the baseline and with follow-up in 2013/2014 and the inclusion of complementary clinical exams in the study follow-up in 2014/2015.

Details on the study site, population, and sampling have been published previously and will be presented here briefly 1717. Confortin SC, Schneider IJC, Antes DL, Cembranel F, Ono LM, Marques LP, et al. Life and health conditions among elderly: results of the EpiFloripa Idoso cohort study. Epidemiol Serv Saúde 2017; 26:305-17.. The sample consisted of 1,705 elderly in 2009/2010. Of these, 220 were excluded (217 deaths, 2 duplicates, and 1 with inconsistent age). Of the 1,485 elderly individuals eligible in 2013/2014, 159 were considered losses and there were 129 refusals. A total of 1,197 (80.6%) were interviewed at home, and of these, 604 (50.38%) completed the clinical exams. The analytical sample for this study was 598 elderly (6 excluded because they were bedridden and lacked adequate information from the DXA imaging tests).

Data collection

Data were collected with a structured instrument in face-to-face interviews. A personal digital assistant (PDA) was used in 2009/2010 and a netbook in 2013/2014, in which the data were recorded and stored. Data were collected from September 2009 to June 2010, a total of ten months. The study’s second wave was from December 2013 to October 2014. The interviewers received prior training to test the instrument and refine and calibrate the tests (precision and accuracy).

The data’s consistency was verified weekly using simple frequencies and comparisons with the expected values. Noncongruent answers were identified, corrected by the supervisor and interviewer, and then returned to the person responsible for the final databank. Quality control used a short version of the questionnaire applied by telephone to 10% of the interviewees, randomly selected.

Dependent variable

Sarcopenia (yes or no) was identified by analysis of skeletal muscle mass using dual-energy X-ray absorptiometry or DXA (Model Lunar Prodigy Advance, General Electric, Diegem, Belgium) and defined by calculating the ASMI as proposed by Baumgartner et al. 77. Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998; 147:755-63.. The following formula was used: ASMI (kg/m2) = [lean muscle mass of the arms (kg) + lean muscle mass of the legs (kg)]/height2 (m). The criterion adopted for identifying sarcopenia was ASMI ≤ 2 standard deviations (SD) from the mean for the reference population (young adults from the Rosetta Study), by gender, as in Baumgartner et al. 77. Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998; 147:755-63., with cutoff points for inadequate ASMI (kg/m2) (loss of muscle mass) defined as < 7.26kg/m² for men and < 5.5kg/m² for women.

Independent variables (change)

The independent variables were characterized as change variables, and baseline and follow-up data were used to categorize them, verifying how many elders remained in the same baseline category, how many changed, and to which categories they moved.

(a) Socioeconomic: (i) work status (remained or started working, remained not working, or stopped working).

(b) Behavioral: (i) consumption of alcoholic beverages [continued to not drink (never drank) or stopped consuming alcoholic beverages; continued or started consuming alcohol (non-abusive and abusive consumption)]. These data were verified by the first three questions from the Alcohol Use Disorders Identification Test (AUDIT) 1818. Lima CT, Freire ACC, Silva APB, Teixeira RM, Farrell M, Prince M. Concurrent and construct validity of the AUDIT in an urban Brazilian sample. Alcohol Alcohol 2005; 40:584-89.; (ii) smoking (continued not smoking or stopped smoking; continued or started smoking); (iii) leisure-time physical activity and commuting (yes: ≥ 150 minutes of physical activity per week; no: < 150 minutes of physical activity per week). Physical activity was measured by the long version of the International Physical Activity Questionnaire (IPAQ) 1919. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003; 35:1381-95. (remained or became physically active; remained or became physically inactive); and (iv) daily consumption of fruits and vegetables 2020. World Health Organization. Global Strategy on diet, physical activity and health. Fifty seventy world health assembly. http://www.who.int/dietphysicalactivity/strategy/eb11344/en/ (acessado em 22/Out/2015).
http://www.who.int/dietphysicalactivity/...
(continued or started to consume < 5 portions per day; continued or started to consume ≥ 5 portions per day).

(c) Health: (i) diseases (maintained the same number of diseases, developed one or more diseases, decreased the number of diseases) verified with the following question: “Has some physician or other health professional told you that you have ...?”. There were twelve options for diseases (questionnaire of the Brazilian National Household Sample Survey - PNAD); (ii) cognitive decline (no/yes), verified with the Mini-Mental State Examination (MMSE), was assessed as a decrease in the MMSE score from 2009 to 2013, where cognitive decline was defined as a reduction of four points or more 2121. Stein J, Luppa M, Maier W, Wagner M, Wolfsgruber S, Scherer M, et al. Assessing cognitive changes in the elderly: Reliable change indices for the Mini-Mental State Examination. Acta Psychiat Scand 2012; 126:208-18.; (iii) history of falls (no falls or stopped suffering falls versus continued or started to suffer falls), verified with the question, “Did you suffer any falls in the last year?”; (iv) depressive symtoms 2222. Ramos LR. Fatores determinantes do envelhecimento saudável em idosos residentes em centro urbano: Projeto Epidoso, São Paulo. Cad Saúde Pública 2003; 19:793-97. (absence of depressive symptoms or stopped having depressive system; continued or started having depressive symptoms); and (v) mobility (perceived capacity for locomotion), identified by use of part of the Brazilian Questionnaire for Multidimensional Functional Assessment, adapted from the Old Americans Resources and Services questionnaire (BOMFAQ/OARS) 2323. Blay SL, Ramos LR, Mari JJ. Validity of a Brazilian version of the Older Americans Resources and Services (OARS) mental health screening questionnaire. J Am Geriatr Soc 1988; 36:687-92.. The questions asked about difficulty in performing three activities of daily living - walking on a level surface, climbing one flight of stairs, and walking near home - divided into four categories of possible answers: no difficulty, little difficulty, great difficulty, and does not perform the activity. For the analysis, the options were divided into two categories: some degree of difficulty with mobility (those with some or great difficulty or who cannot perform any of the activities) versus no difficulty with mobility, categorized as a change variable (continued or started not to have any difficulty versus continued or started to have some degree of difficulty).

More details on the change variables prior to grouping (due to the low number in some categories) can be seen in a previous descriptive study 1717. Confortin SC, Schneider IJC, Antes DL, Cembranel F, Ono LM, Marques LP, et al. Life and health conditions among elderly: results of the EpiFloripa Idoso cohort study. Epidemiol Serv Saúde 2017; 26:305-17..

Adjustment variables (2013/2014)

The adjustment variables were: age bracket (60-69; 70-79; or ≥ 80 years), years of schooling (none; 1-4; 5-8; 9-11; or ≥ 12); per capita income (≤ 1 minimum wage [MW]; > 1-3 MW; > 3-5 MW; > 5-10 MW; or > 10 MW [MW 2010: BRL 510.00]); marital status (married, single, divorced, or widow/widower); family arrangement (living alone, living with others of his/her generation, living with others of another generation); self-rated health status (obtained with the question “In general, would you say that your health is very good, good, fair, bad, or very bad?”) 2424. Ware Jr JE, Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care 1996; 34:220-33., categorized as negative (fair, bad, or very bad) versus positive (very good or good); social support (no or yes), investigated on the basis of an affirmative answer to one of these questions: “Has some friend or neighbor invited you to walk, cycle, or practice sports in your neighborhood?” and/or “Has someone in your family invited you to walk, cycle, or practice sports in your neighborhood?”; functional dependence in 15 activities of daily living (ADL) (no - difficulty in zero to three activities; yes - difficulty in four or more activities) 2323. Blay SL, Ramos LR, Mari JJ. Validity of a Brazilian version of the Older Americans Resources and Services (OARS) mental health screening questionnaire. J Am Geriatr Soc 1988; 36:687-92..

Data analysis

Descriptive analyses were performed for all the variables. Prevalence rates and respective 95% confidence intervals (95%CI) were calculated for sarcopenia, based on the nature of exposures and according to gender. Crude and adjusted analyses used logistic regression, estimating the crude and adjusted odds ratios and respective 95%CI. In the adjusted analysis, the association between each independent variable and sarcopenia was controlled by the adjustment variables, considering three analytical models: Model 1 - adjusted by age, income, marital status, family income; Model 2 - adjusted by age, income, marital status, family income, smoking, alcohol intake, physical activity, and social support; Model 3 - adjusted by age, income, marital status, family income, smoking, alcohol intake, physical activity, social support, self-related health, functional dependence, cognitive decline, depressive symptoms, and diseases.

Data analysis used Stata 13.0 (https://www.stata.com). All analyses considered the cluster sampling design effect, incorporating sampling weights with the svy command.

Ethical issues

The study project was approved by the Ethics Committee for Research in Human Subjects at Federal University of Santa Catarina, case review 526.123/2013, and participants signed a free and informed consent form. The authors had no conflicts of interest.

Results

The current study’s sample consisted of 598 individuals (63 to 93 years), of whom 391 women and 207 men, with mean ages of 72.5 years (± 6.24) and 72 years (± 6.35), respectively. The proportion of sarcopenia was 17% in women (95%CI: 12.4-22.9) and 28.8% in men (95%CI: 21.3-37.7).

There were differences between the interviewees in the follow-up and those who had undergone the clinical tests. Individuals that appeared for the exams were younger (mean of 72.3 years versus 75.5 years; p ≤ 0.001), working at the time of the assessment (17% versus 7.6%; p ≤ 0.001), more physically active (30.4% versus 23.5%; p = 0.028), and less dependent (26% versus 34.6%; p = 0.046) and showed better cognitive function (78.6% versus 71.7%; p = 0.017) and lower prevalence of depressive symptoms (78.2% versus 83.5%; p = 0.035). There were no differences between the groups in the following variables: gender (p = 0.802), schooling (p = 0.125), income (p = 0.288), marital status (p = 0.188), and number of diseases (p = 0.609).

Table 1 shows the distribution of women and men according to sociodemographic, behavioral, and health characteristics. The women were predominantly 70 to 79 years of age, with one to four years of schooling, with income > 1 to 3 times the minimum wage, widows, living with others of their own generation, with positive self-rated health, without functional dependence, and without social support. The men were predominantly younger (60-69 years), with 12 or more years of schooling, with income greater than ten times the minimum wage, married, living with others from their own generation, with positive self-rated health, without functional dependence, and without social support.

Table 1
Description of the sample and prevalence of sarcopenia according to demographic, socioeconomic, behavioral, and health characteristics in the elderly. Florianópolis, Santa Catarina State, Brazil, 2013/2014.

For the change variables, in both women and men, the highest prevalence was of elderly that continued not to work or that stopped working, remained or became physically active, and continued or started to consume fewer than 5 portions a day of fruits and vegetables. Proportionally more elderly had not experienced cognitive decline, either had no falls or no longer suffered falls, and had either shown no depressive symptoms or no longer had them. Proportionally more elders had developed one or more new chronic conditions. There were higher prevalence rates of women who continued not to consume alcohol or who stopped consuming alcohol and who continued not to smoke or who stopped smoking. Men showed the opposite pattern to that of women for both drinking and smoking (Table 1).

Tables 2 and 3 show the results of the associations between sarcopenia and socioeconomic, behavioral, and health characteristics for women and men, respectively. In the crude analysis, continuing or starting to consume alcohol (OR = 0.34; 95%CI: 0.16-0.73) reduced the odds of women having sarcopenia. Continuing to be inactive or becoming insufficiently active (OR = 2.10; 95%CI: 1.07-4.12) and reduction in the number of diseases (OR = 2.10; 95%CI: 1.02-4.34) were associated with higher odds of sarcopenia. In Models 1 and 2, for women, continuing not to consume alcohol or stopping alcohol consumption and remaining inactive or becoming insufficiently active continued to be associated with sarcopenia. The number of diseases was only associated with sarcopenia in Model 1.

Table 2
Crude and adjusted analysis of factors associated with sarcopenia in women. Florianópolis, Santa Catarina State, Brazil, 2013/2014.
Table 3
Crude and adjusted analysis of factors associated with sarcopenia in men. Florianópolis, Santa Catarina State, Brazil, 2013/2014.

In Model 3, women who continued or began to consume alcohol showed 0.69 times lower odds (OR = 0.31; 95%CI: 0.11-0.91) of presenting sarcopenia. Those who remained or became insufficiently active showed 2.90 times higher odds (95%CI: 1.44-5.84) of sarcopenia. Those who continued to smoke or started smoking showed 2.55 higher odds (95%CI: 1.16-5.58) of sarcopenia, only in Model 3.

In the crude analysis, men that remained inactive or that stopped working (OR = 3.63; 95%CI: 1.22-10.79) and those with cognitive decline (OR = 4.65; 95%CI: 1.01-21.57) showed higher odds of sarcopenia. After applying the adjustment variables in Models 1, 2, and 3, these variables did not remain associated (Table 3).

Discussion

In the current study, the prevalence rates for sarcopenia in women and men were 17% (95%CI: 12.40-22.87) and 28.8% (95%CI: 21.35-37.67), respectively. The estimated prevalence of sarcopenia was thus higher in men, corroborating a previous study 66. Dufour AB, Hannan MT, Murabito JM, Kiel DP, McLean RR. Sarcopenia definitions considering body size and fat mass are associated with mobility limitations: the Framingham Study. J Gerontol A Biol Sci Med Sci 2013; 68:168-74. using the same criteria and cutoff points as our study. Dufour et al. 66. Dufour AB, Hannan MT, Murabito JM, Kiel DP, McLean RR. Sarcopenia definitions considering body size and fat mass are associated with mobility limitations: the Framingham Study. J Gerontol A Biol Sci Med Sci 2013; 68:168-74. assessed 274 men and 493 women in Framingham, Massachusettsm USA (72-92 years of age), in whom the prevalence of sarcopenia was 19% and 13%, respectively. The higher prevalence of sarcopenia in men can be explained by the fact that the decline in muscle strength and muscle mass is more severe in men than in women 2525. Hughes VA, Frontera WR, Wood M, Evans WJ, Dallal GE, Roubenoff R, et al. Longitudinal muscle strength changes in older adults influence of muscle mass, physical activity, and health. J Gerontol A Biol Sci Med Sci 2001; 56:B209-B17..

Despite the selective loss of participants, which may have resulted in underestimation of sarcopenia, the prevalence rates were higher than those observed in another Brazilian study of the elderly in São Paulo 2626. Alexandre TS, Duarte YAO, Santos JLF, Wong R, Lebrão ML. Prevalence and associated factors of sarcopenia among elderly in Brazil: findings from the SABE study. J Nutr Health Aging 2014; 18:284-90.. This difference may result from the use of different criteria to assess sarcopenia, besides individual characteristics and/or behavioral and social aspects in each location.

In the current study, women that continued or started to consume alcohol showed lower odds of sarcopenia. Some studies 2727. Tyrovolas S, Koyanagi A, Olaya B, Ayuso-Mateos JL, Miret M, Chatterji S, et al. Factors associated with skeletal muscle mass, sarcopenia, and sarcopenic obesity in older adults: a multi-continent study. J Cachexia Sarcopenia Muscle 2016; 7:312-21.,2828. Steffl M, Bohannon RW, Petr M, Kohlikova E, Holmerova I. Alcohol consumption as a risk factor for sarcopenia-a meta-analysis. BMC Geriatrics 2016; 16:99. have shown that alcohol consumption is not a risk factor for sarcopenia, and even that it acts as a protective factor, as in the current study. However, Domiciano et al. 2929. Domiciano D, Figueiredo C, Lopes J, Caparbo V, Takayama L, Menezes P, et al. Discriminating sarcopenia in community-dwelling older women with high frequency of overweight/obesity: the São Paulo Ageing & Health Study (SPAH). Osteoporos Int 2013; 24:595-603. found that elderly in São Paulo that consumed alcohol had 4.1 times higher odds of sarcopenia.

The beneficial effect of alcohol intake may be due to a pattern of low use (amount and frequency). Among the women in the current study that already consumed or started to consume alcohol (n = 121; 30.95%), only 6.1% reported abusive use, while 24.81% reported non-abusive consumption. In addition, the observed alcohol consumption may be associated with greater social interaction and better living conditions among women that consume, thus representing a small percentage of healthier elderly women who are less prone to sarcopenia.

In relation to smoking, women that continued or started to smoke showed higher odds of sarcopenia. Previous studies 3030. Castillo EM, Goodman-Gruen D, Kritz-Silverstein D, Morton DJ, Wingard DL, Barrett-Connor E. Sarcopenia in elderly men and women: the Rancho Bernardo study. Am J Prev Med 2003; 25:226-31.,3131. Szulc P, Duboeuf F, Marchand F, Delmas PD. Hormonal and lifestyle determinants of appendicular skeletal muscle mass in men: the MINOS study. Am J Clin Nutr 2004; 80:496-503.,3232. Lee JS, Auyeung TW, Kwok T, Lau EM, Leung PC, Woo J. Associated factors and health impact of sarcopenia in older chinese men and women: a cross-sectional study. Gerontol 2007; 53:404-10. have shown that smoking is a risk factor for sarcopenia and that elderly smokers have less appendicular skeletal mass when compared to those who have never smoked. This may be explained by the fact that smoking causes breakdown of skeletal muscle proteins 3333. Rom O, Kaisari S, Aizenbud D, Reznick AZ. Sarcopenia and smoking: a possible cellular model of cigarette smoke effects on muscle protein breakdown. Ann N Y Acad Sci 2012; 1259:47-53., with a direct effect on muscle or vascular function 3434. Kilaru S, Frangos SG, Chen AH, Gortler D, Dhadwal AK, Araim O, et al. Nicotine: a review of its role in atherosclerosis. J Am Coll Surg 2001; 193:538-46.. Smoking’s sarcopenic effect 3535. Petersen AMW, Magkos F, Atherton P, Selby A, Smith K, Rennie MJ, et al. Smoking impairs muscle protein synthesis and increases the expression of myostatin and MAFbx in muscle. Am J Physiol Endocrinol Metab 2007; 293:E843-E8. is related to a substantial decline in muscle mass and strength 3636. Kok MO, Hoekstra T, Twisk JW. The longitudinal relation between smoking and muscle strength in healthy adults. Eur Addict Res 2012; 18:70-5.,3737. Stenholm S, Tiainen K, Rantanen T, Sainio P, Heliövaara M, Impivaara O, et al. Long-term determinants of muscle strength decline: prospective evidence from the 22-year mini-Finland follow-up survey. J Am Geriatr Soc 2012; 60:77-85.,3838. Taekema DG, Ling CH, Kurrle SE, Cameron ID, Meskers CG, Blauw GJ, et al. Temporal relationship between handgrip strength and cognitive performance in oldest old people. Age Ageing 2012; 41:506-12., leading to functional decline and loss of independence.

As for physical activity, women that remained or became insufficiently active showed higher odds of sarcopenia. Physical inactivity induces alterations in systemic and cellular characteristics, resulting in muscle atrophy and declining muscle contractility 3939. Thompson LV. Age-related muscle dysfunction. Exp Gerontol 2009; 44:106-11., which can combine with the aging to lead to muscle atrophy 4040. Derbré F, Gratas-Delamarche A, Gómez-Cabrera MC, Viña J. Inactivity-induced oxidative stress: A central role in age-related sarcopenia? Eur J Sport Sci 2014; 14 Supp 1:S98-108.. Previously active women that became inactive showed higher odds of sarcopenia, highlighting the importance of physical activity throughout the aging process.

The study has some limitations. First, it used characteristics of change that did not allow determining the exact moment in which a given activity was started or stopped by the individual. Second, the losses pertaining to tests may have led to a selection bias, since only the elderly in better health appeared for testing, which may have underestimated the prevalence of sarcopenia. Another limitation was the use of self-reported measures, potentially entailing an information bias. Finally, the fact that participants were not asked about types of alcoholic beverages prevents a clearer explanation of the observed association.

The study’s strengths feature the use of validated and standardized instruments and training of the fieldwork team. The study also used a population database of elderly of the city of Florianópolis, where sarcopenia was assessed with the gold standard established in the literature, rarely used in population studies in Brazil. The change variables studied here were living conditions or habits that are amenable to interventions and change. Smoking, physical inactivity, and underweight, considered risk factors for sarcopenia, are important targets for the development of health promotion strategies.

Conclusion

For women, continuing or starting to consume alcohol was associated with lower odds of sarcopenia. Meanwhile, continuing or starting to smoke and remaining or becoming insufficiently active were associated with higher odds of sarcopenia. For men, no factor was associated with sarcopenia.

These results indicate that preventive strategies against the observed risk factors may reduce the loss of muscle mass and thus mitigate or control the prevalence of sarcopenia in the elderly. These preventive approaches should start earlier in adulthood, since aging involves alterations in body composition.

Health policies and intervention programs based on physical activity and the promotion of healthy habits can protect against the harms caused by sarcopenia in the elderly population, who can thus remain more independent and autonomous and enjoy better quality of life longer.

The study’s results in terms of public health can back measures to increase physical activity in all age and schooling groups (with specific approaches for various groups). The study found that 48.5% of the women and 27.3% of the men in the sample remained or became insufficiently active (with less than 150 minutes of physical activity per week, which is below the recommended level).

Physical activities or physical exercise aimed at recovering muscle strength and skeletal mass, such as bodybuilding and resistance training, should be publicized and encouraged among the elderly. Meanwhile, aerobic exercises do not present the same significant benefits.

Acknowledgments

The authors wish to thank the staff of the Brazilian Institute of Geography and Statistics (IBGE) and the Florianópolis Municipal Health Department for their assistance with the study, the study participants, the Brazilian Graduate Studies Coordinating Board (Capes-REUNI) for the PhD scholarship to S. C. Confortin, and the Brazilian National Research Council (CNPq, grant number 569834/2008-2) for the financial support.

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History

  • Received
    07 Nov 2017
  • Reviewed
    23 Mar 2018
  • Accepted
    02 May 2018
  • Online publication
    29 Nov 2018
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz Rio de Janeiro - RJ - Brazil
E-mail: cadernos@ensp.fiocruz.br