Flavia Moura Malini; Virgílio Garcia Moreira; Janaina Santos Nascimento; Roberto Alves Lourenço
OBJECTIVE: The prevalence of falls and associated factors were determined in a large cohort of community-dwelling older adults.
METHODS: The sample included adults at least 65 years old who resided in the city of Rio de Janeiro, Brazil. A total of 742 individuals were investigated by inverse random sampling and were stratified by gender and age. The prevalence of falls was calculated by the history of falls in the last year. Data on clinical, psychosocial, sociodemographic and functional characteristics were also gathered. After bivariate analysis, statistically relevant variables were included in groups in 4 models for multivariate analyses.
RESULTS: The prevalence of falls was 29%. The mean age was 76.7; 70.2% were female; 43.4% were married; 80.3% had ≥ 5 years of education;48.3% had an income, of which ≥ 5.1 were minimum wage. All of the variables were associated with falls, except fair self-rated "health. In contrast, when all these variables were adjusted (model 2), almost all lost the statistical significance, except for functional dependency-IADL (OR = 1.51; 95%CI 1.02-2.21) and poor/very poor self-rated health (OR = 2.36; 95%CI 1.06-5.25). For psychosocial variables in model 1, only fear of falling and activity level were significantly associated with falls. However, when these variables were adjusted (model 3), only fear of falling remained significant. In the final model, functional dependency (OR = 1.48; 95%CI 1.01-2.17), poor/very poor self-rated health (OR = 2.33; 95%CI 1.05-5.21) and fear of falling (OR = 2.14; 95%CI = 1.47-3.12) were associated with falls.
CONCLUSION: The prevalence of falls is high among community-dwelling older adults. Associations with socio-demographic and biological factors have been identified and confirmed in the literature. Social activities were considered a protective factor.
Keywords: falls; prevalence; elderly
OBJETIVO: Analisar a prevalência de quedas e fatores associados em uma ampla coorte de idosos na comunidade.
MÉTODO: Indivíduos com 65 anos de idade ou mais, residentes na cidade do Rio de Janeiro, Brasil. Um total de 742 indivíduos foram investigados e estratificados por sexo e idade em uma amostra aleatória inversa. A prevalência de quedas foi calculada pelo histórico de quedas no último ano. Também foram coletadas outras variáveis como: características clínicas, psicossociais, sociodemográficas e funcionais. Após análise bivariada, aqueles estatisticamente relevantes foram incluídos nos grupos em 4 modelos para análises multivariadas.
RESULTADOS: A prevalência de quedas foi de 29%. A idade média foi de 76,7; 70,2% do sexo feminino; 43,4% eram casados; 80,3% tinham ≥ 5 anos de estudo; 48,3% tinham renda ≥ 5,1 salários mínimos. Todas as variáveis foram associadas a quedas, com exceção da categoria de autoavaliação de saúde. Por outro lado, quando todas essas variáveis foram ajustadas (modelo 2), quase todas perderam a significância estatística, exceto a AIVD (OR = 1,51; IC95% 1,02-2,21) e a avaliação de saúde ruim/muito ruim (OR = 2,36; IC95% 1,06-5,25). Para as variáveis psicossociais, no modelo 1, apenas o medo de cair e o nível de atividade foram associados significativamente. Porém, quando essas variáveis foram ajustadas (modelo 3), o medo de cair persistiu de forma significativa. No modelo final, a dependência em AIVD (OR = 1,48; IC95% 1,01-2,17), a autoavaliação de saúde ruim/muito ruim (OR = 2,33; IC95% 1,05-5,21) e o medo de cair (OR = 2,14; IC95% 1,47-3,12) foram associados a quedas.
CONCLUSÃO: A prevalência de queda é alta nos idosos que vivem em comunidade. A associação com fatores sociodemográficos e biológicos foi identificada e confirmada pela literatura. As atividades sociais foram consideradas um fator de proteção.
Palavras-chave: quedas; prevalência; idoso.
A fall can be defined as a sudden and unintended change of body position, commonly towards a bottom level, often the ground.1 Both the prevalence and incidence of falls are high among older adults. In the European Union, 105,000 cases of fatal injuries of all kinds occur annually, of which 85,000 are caused by falls.2 Due to their relevance and multiple associated risk factors, falls are considered part of geriatric syndrome.
Nachreiner et al.3 reported that approximately 30% of community-dwelling adults aged 65 and older have had at least one fall in the past year. Among those aged 75 and older, this ratio increases to 50%, with 16% having fallen in the past three months. Recurrent falls are common; a study conducted with a representative sample of older Brazilian adults found that of those who fell in the past year, 53.5% fell once, 21.2% fell twice, 13.3% fell 3 times and 12% fell 4 or more times.4 In Brazil, the prevalence of falls in older people in different settings varies from 29-60%.4-6
Approximately 40-60% of falls result in injuries; 30-50% are less severe, 5-6% are severe injuries (excluding fractures), and 5% result in fractures. About 1% of falls result in hip fractures, which have a high impact on morbidity, mortality and health care costs.7
Falling is a multidimensional phenomenon that usually appears as a consequence of the interaction between environmental or extrinsic factors and increased individual susceptibility or intrinsic factors. The previous occurrence of a fall, balance disorders, decreased muscle strength, visual impairment, polypharmacy, psychoactive drugs, gait disorders, depression, dizziness, functional limitations, urinary and fecal incontinence, cognitive impairment, arthritis, diabetes, pain and fear of falling are only a few of the long list of factors associated with falls. Many of these factors are related to the individual’s physical or clinical condition.8,9
This study aimed to determine the prevalence falls and associated factors in a large cohort of community-dwelling older adults from the city of Rio de Janeiro.
Study design and population
This cross-sectional study analyzed data from the Frailty in Brazilian Older People — Rio de Janeiro (FIBRA-RJ) study’s baseline assessment. The methods of FIBRA-RJ have been described elsewhere.10 The baseline data were obtained through home interviews conducted between January 2009 and January 2010. The inclusion criteria were: age ≥ 65 years and residency in the North Zone of the city of Rio de Janeiro. The exclusion criteria were neuropsychiatric disorders, a Mini-Mental State Examination score < 14, and severe hearing or visual limitations that prevented responding to the questionnaire.11
An inversion sampling strategy was used. Each sample unit was assigned a factor of expansion according to basic weight and a correction factor, which combined the non-response model fit and adjustment for missing data. A total of 847 individuals were included the sample; 81 were excluded due to functional impairment or neuropsychiatric changes and 24 were excluded due to providing incomplete information on the questionnaires. Thus, a total of 742 individuals were analyzed.
The dependent variable: falls
The participants’ history of falls was ascertained by 12-month recall; the answer was dichotomized.
Cl, nical and functional variables
Each participant reported the number of comorbidities (0-1, 2-3, ≥ 4) and the number of regularly used medications (0-3, 4-6, ≥ 7). Visual and hearing impairment was self-reported by asking participants whether they "had difficulty in seeing or hearing" (no/yes). The participants were also asked whether they used a walking aid (No/Yes).
The functional state was determined according to basic activities of daily living (BADL)12 and instrumental activities of daily living (IADL).13 Participants who required help or did not perform at least one of the evaluated activities were considered dependent. Handgrip strength was tested with a manual dynamometer (JAMAR Model J00105, Lafayette Instrument Co., Lafayette, IN, USA) by three repetitions in the dominant hand. The average of these three measures, adjusted for sex and body mass index, was used to determine muscle strength. Participants in the first quintile (after adjusting for gender and body mass index) were considered abnormal (weak).14 A chronometer was used to measure gait speed (the time taken to walk 4.6 meters). Participants in the first quintile, after adjusting for their respective heights and sex, were also considered abnormal.14
Self-perceived health was assessed by asking, "in general, how would you say your health is?" Responses were categorized as very good/good, fair, and poor/very poor.
The fear of falling was assessed using the Brazilian version of the Falls Efficacy Scale International (FES-I-BR).15 This variable was dichotomized according to a cutoff of 23 points.
The Mini-Mental State Examination was used to assess the presence of cognitive impairment;11 the cut-offs for illiterate individuals and those with > 1 year of school education were 18/19 and 24/25 points, respectively. The Geriatric Depression Scale was used to determine the presence of depressive symptoms;16 the cutoff was 5/6 points. We determined whether individuals were living alone (Yes/No). Instrumental social support was evaluated with the following question: "Do you have a relative, friend, or neighbor who could take care you if necessary?", whose responses were yes or no. The partic-ipants’ activity level in the last year was categorized as better/same or worse than the previous year.
Covariates: socioeconomic and demographic variables
The following covariates were assessed: sex, age (65-74; 75-84 and ≥ 85 years), marital status (married, divorced/separated, single, widowed), education (illiterate, 1-4 and ≥ 5 years of schooling), and individual income as multiples of the minimum monthly salary (0-2; 2.1-5 and ≥5.1).
The relevance of this study lies in its population (individuals with private health insurance) and its large random sample. This sample differs from the average Brazilian population due to its better access to health care services, including emergency and clinical assistance, complementary exams and hospitalization.
Bivariate analyses were performed to calculate the absolute and relative frequencies of falls with respect to socioeconomic, demographic, clinical, functional, and psychosocial characteristics. The independence of the bivariate relationships was tested with the Pearson χ2 test. Multivariate analyses were performed with logistic regression, and the crude and adjusted odds ratios (OR) with 95% confidence intervals (CI) were calculated as measures of association. Variables with p < 0.10 in the bivariate analysis were included in groups in the following models; model 1: all variables adjusted for age and education level; model 2: clinical and functional variables adjusted for age and education level; model 3: psychosocial variables adjusted for age and education level and model 4 (final): clinical, functional and psychosocial variables. All analyses were performed in SPSS 19.9 (IBM software, Chicago, IL, USA).
The FIBRA-RJ study was approved by the Ethics Research Committee of the Pedro Ernesto University Hospital (number 1850). All participants provided informed consent.
Of the 742 analyzed participants (70.2% female), 215 (29%) had fallen in the past 12 months. The mean ± SD age was 76.7 ± 7 years; 319 (43.0%), 330 (44.5%), and 93 (12.5%) were aged 65-74, 75-84, and ≥ 85 years, respectively. In addition, 43.4% were married or cohabiting. Most of the participants (80.3%) had ≥ 5 years of education; 342 (48.3%) had an income ≥ 5.1 time the minimum monthly salary (Table 1).
Table 1 presents the prevalence of falls according to socioeconomic and demographic variables. Since the association was significant (p < 0.10) for age (older), and years of schooling (illiterate), these variables were included in the models as covariates.
Tables 2 and 3 present the prevalence of falls according to the clinical, functional and psychosocial characteristics. To reduce de number of variables in the multivariate models, only the most significant variables were selected. All of the clinical and functional variables were significantly associated with falls except hearing impairment. Of the psychosocial variables, only instrumental social support and living alone were not included in the multivariate model.
Table 3 presents the results of the multivariate analysis. In model 1 (i.e., clinical and functional variables, adjusted for covariates), all the variables were associated with falls except fair self-rated health. In contrast, when these variables were adjusted (model 2), almost all lost statistical significance except for functional dependency-IADL (OR = 1.51; 95%CI 1.02-2.21) and poor/very poor self-rated health (OR = 2.36; 95%CI 1.06-5.25). For the psychosocial variables, in model 1 only fear of falling and activity level were significantly associated with falls. However, when these variables were adjusted (model 3), fear of falling remained significant but activity level was not. In model 4 (i.e., all independent variables), functional dependency-IADL (OR = 1.48; 95%CI 1.01-2.17), poor/very poor self-rated health (OR = 2.33; 95%CI 1.05-5.21) and fear of falling (OR = 2.14; 95%CI 1.47-3.12) were associated with falls.
In the present study, the prevalence of falls among older adults was 29%. Age, functional dependency-IADL, visual impairment and the number of medications in use were associated with falling. On the other hand, participation in social activities was considered a protective fac-tor against falling.
The prevalence of falls among older adults varies according to where it occurs, e.g. in the neighborhood, general hospital, emergency unit or long-stay unit. Among community-dwelling older adults, it has been estimated that falls are approximately 30%, more frequent in women (34.8%) and in individuals of advanced age. Together with comorbidities, this rate reaches 54% and increases with the use of psychotropic medications or time in long-stay institutions, where the chance of falls increases up to 300%.1
In a sample of 675 Spanish community-dwellers aged 75 and older, Lavedán Santamaria et al.17 found that the prevalence of falls was 25% and was associated with functional limitations, depressive symptoms and fear of falling. In a recent systematic review on the prevalence of falls in community-dwelling older adults in Brazil, Elias Filho et al.18 found a prevalence of 27% in a total of 58,597 participants from the 37 included studies. In addition, their data also indicate that age and female gender are more associated with falls, which was very similar to what was observed in the present study.
Studying risk factors for falls is complex due to the multifactorial nature of the event, i.e. the characteristics of the study population, environment and comorbidities, as well as the measurement tools used for individual assessment.19,20
Age-related impairments are associated with a reduced ability to respond rapidly and effectively to adverse situations, which could lead to increased risk of falls.21 Age has been pointed out by several authors as a risk factor for falls.1,22
In present study, the association between functional dependency in BADL and falls persisted until the final multivariate model. Compromised BADL has been shown to be a risk factor for falls in other studies1,23 and has been used to identify the frail elderly. Interestingly, Dionyssiotis21 pointed out that exposure and risk of falls can be described as a Ushaped curve, with inactive and the most active individuals being at higher risk. This shows the complexity of the relationship between falls and activities of daily living.
Another essential factor for falls was the number of drugs in use by the participants.24 In the present study, this number varied from zero (37 patients, 4.37%) to 21 (1 patient, 0.12%), and 65% of the sample used more than four drugs. This variable was significant in the preliminary bivariate analysis, with a difference of 1 medication between those who had fallen (5.42 ± 0.21) and those who had not (4.38 ± 0.1119; p < 0.001). Some authors have considered a cut-off point of four psychoactive drugs as a risk factor for falls.24,25 In the final analysis of the present study, the association with falls remained significant only with seven or more medications (OR = 1.6; 95%CI 1.08-2.38; p = 0.0018), which suggests a different characteristic in our population, i.e. a high prevalence of comorbidities that requires multiple medications (four or more medications than what was considered significant in the intermediate analysis).
Visual impairment was also an important factor, increasing the chance of falling by 40%, even after controlling for other risk factors.26-28 The role of vision loss in falls can be explained by loss of visual acuity, contrast sensitivity, depth perception and field of vison.29 In our study, only self-reported visual impairment was explored.
On the other hand, some factors reported to be associated with falls in the literature were not significant in the present study, such as female gender, systemic hypertension, use of walking aids and low gait speed.30,31 Thus, although female gender should have been excluded from the model (confidence interval between 0.95 and 1.93 despite OR = 1.35), due to its epidemiologic relevance in previous studies, it was tested in a multivariate model but was not significant. Still, it is possible that a larger sample could improve the quality of this measure.
Although considered significant in the preliminary analysis, the use of walking aids and gait speed were not included in the final model. Other authors have questioned the need to evaluate these variables. In systematic reviews, Thrane et al.32 and Beauchet et al.33 have questioned the relevance of gait speed and balance as predictors of falls.
Finally, hypertension was collinear with the number of medications. When considered separately, hypertension was significant, but less so than the number of medications. However, when the number of medicines was introduced into the logistic model, hypertension became non-significant.
This study found that the prevalence of falls is high among community-dwelling older adults. The association identified with socio-demographic and biological factors is confirmed by the literature and can contribute to the development of fall prevention programs for communi ty-dwelling older adults.
1. Panel On Prevention Of Falls In Older Persons, British Geriatrics Society, British Geriatrics Society. Summary Of The Updated American Geriatrics Society/British Geriatrics Society Clinical Practice Guideline For Prevention Of Falls In Older Persons. J Am Geriatr Soc. 2011;59(1):148-57. https://doi.org/10.1111/j.1532-5415.2010.03234.x
2. Scott D, Johansson J, McMillan LB, Ebeling PR, Nordstrom P, Nordstrom A. Associations Of Sarcopenia And Its Components With Bone Structure And Incident Falls In Swedish Older Adults. Calcif Tissue Int. 2019;105(1):26-36. https://doi.org/10.1007/s00223-019-00540-1
3. Nachreiner NM, Findorff MJ, Wyman JF, McCarthy TC. Circumstances And Consequences Of Falls In Community-Dwelling Older Women. J Womens Health (Larchmt). 2007;16(10):1437-46. https://doi.org/10.1089/jwh.2006.0245
4. Siqueira FV, Facchini LA, Silveira DS, Piccini RX, Tomasi E, Thumé E, et al. Prevalence Of Falls In Elderly In Brazil: A Countrywide Analysis. Cad Saúde Pública. 2011;27(9):1819-26. http://dx.doi.org/10.1590/S0102-311X2011000900015
5. Rozenfeld S, Camacho LA, Veras P Medication As A Risk Factor For Falls In Older Women In Brazil. Rev Panam Salud Publica. 2003;13(6):369-75. https://doi.org/10.1590/s1020-49892003000500005
6. Siqueira FV, Facchini LA, Piccini RX, Tomasi E, Thumé E, Silveira DS, et al. [Prevalence Of Falls And Associated Factors In The Elderly]. Rev Saúde Pública. 2007;41(5):749-56. http://dx.doi.org/10.1590/S0034-89102007000500009
7. Masud T, Morris RO. Epidemiology Of Falls. Age Ageing. 2001;30(Suppl. 4):3-7. https://doi.org/10.1093/ageing/30.suppl_4.3
8. Delbaere K, Close JC, Heim J, Sachdev PS, Brodaty H, Slavin MJ, et al. A Multifactorial Approach To Understanding Fall Risk In Older People. J Am Geriatr Soc. 2010;58(9):1679-85. https://doi.org/10.1111/jl532-5415.2010.03017.x
9. Rubenstein LZ. Falls In Older People: Epidemiology, Risk Factors And Strategies For Prevention. Age Ageing. 2006;35(Suppl. 2):ii37-ii41. https://doi.org/10.1093/ageing/afl084
10. Lourenco RA, Sanchez MA, Moreira VG, Ribeiro PCC, Perez M, Campos GC, et al. Frailty In Older Brazilians - FIBRA-RJ: Research Methodology On Frailty, Cognitive Disorders And Sarcopenia. Ver Hospital Pedro Ernesto. 2015;4(14):21. https://doi.org/10.12957/rhupe.2015.20066
11. Brucki SM, Nitrini R, Caramelli P, Bertolucci PH, Okamoto IH. [Suggestions For Utilization Of The Mini-Mental State Examination In Brazil]. Arq Neuropsiquiatr. 2003;61(3B):777-81. http://dx.doi.org/10.1590/S0004-282X2003000500014
12. Katz S, Downs TD, Cash HR, Grotz RC. Progress In Development Of The Index Of AdL. Gerontologist. 1970;10(1):20-30. https://doi.org/10.1093/geront/10.1_part_1.20
13. Lino VT, Pereira SR, Camacho LA, Ribeiro Filho ST, Buksman S. [Cross-Cultural Adaptation Of The Independence In Activities Of Daily Living Index (Katz Index)]. Cad Saúde Pública. 2008;24(1):103-12. http://dx.doi.org/10.1590/S0102-311X2008000100010
14. Moreira VG, Lourenco RA. Prevalence And Factors Associated With Frailty In An Older Population From The City Of Rio De Janeiro, Brazil: The FIBRA-RJ Study. Clinics (Sao Paulo). 2013;68(7):979-85. http://dx.doi.org/10.6061/clinics/2013(07)15
15. Figueiredo D, Santos S. Cross-Cultural Validation Of The Falls Efficacy Scale-International (FES-I) In Portuguese Community-Dwelling Older Adults. Arch Gerontol Geriatr. 2017;68:168-73. https://doi.org/10.1016/j.archger.2016.10.010
16. Paradela EM, Lourenço RA, Veras RP [Validation Of Geriatric Depression Scale In A General Outpatient Clinic]. Rev Saúde Pública. 2005;39(6):918-23. http://dx.doi.org/10.1590/S0034-89102005000600008
17. Lavedán Santamaria A, Jurschik Giménez P, Botigué Satorra T, Nuin Orrio C, Viladrosa Montoy M. [Prevalence And Associated Factors Of Falls In Community-Dwelling Elderly]. Aten Primária. 2015;47(6):367-75. https://doi.org/10.1016/j.aprim.2014.07.012
18. Elias Filho J, Borel WP, Diz JBM, Barbosa AWC, Britto RR, Felicio DC. Prevalence Of Falls And Associated Factors In Community-Dwelling Older Brazilians: A Systematic Review And Meta-Analysis. Cad Saúde Pública. 2019;35(8):E00115718. http://dx.doi.org/10.1590/0102-311x00115718
19. Peeters G, Van Schoor NM, Lips P. Fall Risk: The Clinical Relevance Of Falls And How To Integrate Fall Risk With Fracture Risk. Best Pract Res Clin Rheumatol. 2009;23(6):797-804. https://doi.org/10.1016/j.berh.2009.09.004
20. Deandrea S, Lucenteforte E, Bravi F, Foschi R, La Vecchia C, Negri E. Risk Factors For Falls In Community-Dwelling Older People: A Systematic Review And Meta-Analysis. Epidemiology. 2010;21(5):658-68. https://doi.org/10.1097/EDE.0b013e3181e89905
21. Dionyssiotis Y. Analyzing The Problem Of Falls Among Older People. Int J Gen Med. 2012;5:805-13. https://dx.doi.org/10.2147%2FIJGM.S32651
22. Lusardi MM, Fritz S, Middleton A, Allison L, Wingood M, Phillips E, et al. Determining Risk Of Falls In Community Dwelling Older Adults: A Systematic Review And Meta-Analysis Using Posttest Probability. J Geriatr Phys Ther. 2017;40(1):1-36. https://doi.org/10.1519/JPT.0000000000000099
23. Antes DL, d'Orsi E, Benedetti TRB. Circunstâncias E Consequências Das Quedas Em Idosos De Florianopolis. Epi Floripa Idoso 2009. Rev Bras Epidemiol. 2013;16(2):469-81. http://dx.doi.org/10.1590/S1415-790X2013000200021
24. Chaimowicz F, Ferreira TJXM, Miguel DFA. Use Of Psychoactive Drugs And Related Falls Among Older People Living In A Community In Brazil. Rev Saúde Pública. 2000;34(6):631-5. http://dx.doi.org/10.1590/S0034-89102000000600011
25. Guideline For The Prevention Of Falls In Older Persons. American Geriatrics Society, British Geriatrics Society, and American Academy of Orthopaedic Surgeons Panel on Falls Prevention. J Am Geriatrics Soc. 2001;49(5):664-72.
26. Dillon L, Clemson L, Ramulu P, Sherrington C, Keay L. A Systematic Review And Meta-Analysis Of Exercise-Based Falls Prevention Strategies In Adults Aged 50+ Years With Visual Impairment. Ophthalmic Physiol Opt. 2018;38(4):456-67. https://doi.org/10.1111/opo.12562
27. Labreche T, Nandakumar K, Althomali M, Leat SJ. Development And Validation Of Visual Impairment As A Risk For Falls Questionnaire. Age Ageing. 2018;47(3):444-50. https://doi.org/10.1093/ageing/afx202
28. Brundle C, Waterman HA, Ballinger C, Olleveant N, Skelton DA, Stanford P, et al. The Causes Of Falls: Views Of Older People With Visual Impairment. Health Expect. 2015;18(6):2021-31. https://dx.doi.org/10.1111%2Fhex.12355
29. De Boer MR, Pluijm SM, Lips P, Moll AC, Volker-Dieben HJ, Deeg DJ, et al. Different Aspects Of Visual Impairment As Risk Factors For Falls And Fractures In Older Men And Women. J Bone Miner Res. 2004;19(9):1539-47. https://doi.org/10.1359/JBMR.040504
30. Zhang X, Huang P, Dou Q, Wang C, Zhang W, Yang Y, et al. Falls Among Older Adults With Sarcopenia Dwelling In Nursing Home Or Community: A Meta-Analysis. Clin Nutr. 2019. https://doi.org/10.1016/j.clnu.2019.01.002
31. Yeung SSY, Reijnierse EM, Pham VK, Trappenburg MC, Lim WK, Meskers CGM, et al. Sarcopenia And Its Association With Falls And Fractures In Older Adults: A Systematic Review And Meta-Analysis. J Cachexia Sarcopenia Muscle. 2019;10(3):485-500. https://dx.doi.org/10.1002%2Fjcsm.12411
32. Thrane G, Joakimsen RM, Thornquist E. The Association Between Timed Up And Go Test And History Of Falls: The Tromso Study. BMC Geriatr. 2007;7:1. https://doi.org/10.1186/1471-2318-7-1
33. Beauchet O, Fantino B, Allali G, Muir SW, Montero-Odasso M, Annweiler C. Timed Up And Go Test And Risk Of Falls In Older Adults: A Systematic Review. J Nutr Health Aging. 2011;15(10):933-8.
September 3 2019.
Accepted em September 19 2019.
Conflict of interests: The authors declare no conflict of interests.