Body composition and frailty profiles in Brazilian older people: Frailty in Brazilian Older People Study-FIBRA-BR

Accepted Manuscript Title: Body composition and frailty profiles in Brazilian older people: Frailty in Brazilian Older People Study-FIBRA-BR Authors: Eduardo Ferriolli, Fernanda Pinheiro Amador dos Santos Pessanha, Virg´ılio Garcia Moreira, Rosˆangela Corrˆea Dias, Anita Liberalesso Neri, Roberto Alves Lourenc¸o PII: DOI: Reference:

S0167-4943(17)30206-6 http://dx.doi.org/doi:10.1016/j.archger.2017.03.008 AGG 3468

To appear in:

Archives of Gerontology and Geriatrics

Received date: Revised date: Accepted date:

25-8-2016 25-1-2017 25-3-2017

Please cite this article as: Ferriolli, Eduardo, dos Santos Pessanha, Fernanda Pinheiro Amador, Moreira, Virg´ılio Garcia, Dias, Rosˆangela Corrˆea, Neri, Anita Liberalesso, Lourenc¸o, Roberto Alves, Body composition and frailty profiles in Brazilian older people: Frailty in Brazilian Older People Study-FIBRA-BR.Archives of Gerontology and Geriatrics http://dx.doi.org/10.1016/j.archger.2017.03.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Body composition and frailty profiles in Brazilian older people: Frailty in Brazilian Older People Study-FIBRA-BR Running Title: Body composition and frailty: FIBRA-BR study Eduardo Ferriolli1([email protected]) Fernanda Pinheiro Amador dos Santos Pessanha1([email protected]) VirgílioGarcia Moreira2 ([email protected]) Rosângela Corrêa. Dias3 ([email protected]) Anita Liberalesso Neri 4([email protected]) Roberto Alves Lourenço 2 ([email protected])

1

Division of General Internal and Geriatric Medicine, Ribeirao Preto Medical School, University

of São Paulo, Ribeirão Preto, SP, Brazil, 2

GeronLab, Internal Medicine Department, Health Science School, Rio de Janeiro State

University, Rio de Janeiro, RJ, Brazil 3

Division of Physiotherapy, School of Physiotherapy, Minas Gerais Federal University, Belo

Horizonte, MG, Brazil, 4

Department of Internal Medicine, Faculty of Medical Sciences, Campinas State University,

Campinas, SP, Brazil.

Contact Info: Fernanda Pinheiro Amador dos Santos Pessanha Address: School of Medicine of Ribeirao Preto, University of São Paulo, Avenida Bandeirantes, 3900, Ribeirão Preto, São Paulo 14049-900, Brazil. Telephone number: +55(16)3315-3370 E-mail address: [email protected]

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Alternative Corresponding author: Eduardo Ferriolli Address: School of Medicine of Ribeirao Preto, University of São Paulo, Avenida Bandeirantes, 3900, Ribeirão Preto, São Paulo 14049-900, Brazil. Telephone number: +55(16)3315-3370 Fax number: +55 (16)3633-6695 E-mail address: [email protected] Highlights 

Undernutrition is associated with pre-frail and frailty in Brazilian elderly subjects, whereas obesity is associated only with pre-frailty



Overweight seems to have a protective effect against the syndrome.



The lowest prevalence of frailty and were observed in subjects with BMI between 25.0 to 29.9 kg/m2.



The excess of abdominal fat is associated with both profiles independent of the BMI

ABSTRACT: Objective: To determine the association between body composition and frailty in older Brazilian subjects. Material and Methods: This is a Cross-sectional study called FIBRA-BR and developed in community Brazilian aged ≥65 (n= 5638). Frailty was assessed according to Fried et al. definition and body composition was determined by BMI, waist circumference and waist-hip ratio. Results: The lowest prevalence of frailty and were observed in subjects with BMI between 25.0 to 29.9 kg/m2. Subjects with a BMI ≤18.5 and those with elevated WC presented a higher risk of frailty compared to eutrophic subjects (odds ratio (OR) =3.10; 95% CI: 2.06-4.67) and (OR=1.15; 95% CI: 1.03-1.27), respectively. Being overweight was protective for pre-frailty (OR=0.48; 95% CI: 0.4-0.58) and frailty profile (OR=0.77; 95% CI: 0.67- 0.9). Obese older people presented a higher risk of pre-frailty only (OR=1.29; 95% CI: 1.09-1.51). Older people with high WC showed a greater proportion of frailty regardless of the BMI range.

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Conclusion: undernutrition is associated with pre-frail and frailty in Brazilian elderly subjects, whereas obesity is associated only with pre-frailty. Overweight seems to have a protective effect against the syndrome. The excess of abdominal fat is associated with both profiles independent of the BMI.

Keywords: frailty, body composition, BMI, waist circumference

1. Introduction Unlike the general belief, frailty is not present in all elderly subjects, but rather in a small, although significant, proportion of this population (1). Albeit the concept of frailty is still being constructed, there is a consensus about frailty being a biological syndrome characterized by reduced energy reserves and by the accumulation of multiple system deficits (2). Frail older persons show a decline in physical function and growing vulnerability that increases the incidence of adverse outcomes – falls, functional disability, hospitalization, comorbidities, and death (3). The causes of frailty have not been fully elucidated and the frequent coexistence of acute events, chronic diseases, and functional disability hinders the detection of the physiological changes that could be strictly related to the syndrome (4). Despite being conceptualized as a multisystem syndrome, nowadays it is hypothesized that the development of frailty is based mainly on a triad of causal changes related to sarcopenia, neuroendocrine dysregulation, and immunological dysfunction (2). It is estimated that 10 to 27% of the population over 65 years is frail that this prevalence is even bigger in the older population (5). Although considered a biological syndrome characterized by decreased functional reserve associated with chronological aging, frailty may be produced or has its appearance accelerated by other pathological factors. Amongst others, the literature has appointed anemia, orthostasis, weight loss, sarcopenia, anorexia, polypharmacy, congestive heart failure, diabetes mellitus, osteopenia, hypovitaminosis D, testosterone deficiency, low protein intake, deficits in protein trafficking, declines in cognitive functioning, inflammation with increased cytokine production, and decreased regulatory peptides (6). Among the main factors correlated with frailty, a healthy body composition seems to exert a major role (7). Weight loss is one of the five criteria of the frailty phenotype proposed by Fried et al. (2), and malnutrition is constantly pointed out as a marker of the syndrome. Notwithstanding, the association between obesity and frailty has also been observed in some studies (8,9). Strandberg et al. (2012) suggested that overweight/obesity and a high risk for cardiovascular diseases were associated with the development of frailty (10). This association, 3

although less obvious once frailty is considered a syndrome of energy loss, is mainly based on pathophysiological hypotheses related to the inflammatory process that seems to be potentiated in frail older subjects (11). Furthermore, both extremes of BMI are associated with disability in the elderly. An important cause of disability in older adults is weight loss associated with sarcopenia, as well as sarcopenic obesity, a particularly deleterious condition that associates low muscle mass and strength with obesity (12). The objective of the present study was to determine the association between body composition and frailty profiles in a large sample of Brazilian older people.

2. Materials and Methods 2.1 Study design and sample The FIBRA study was a cross-sectional multi-center and interdisciplinary epidemiological study performed in Brazil for the characterization and profiling of frailty among Brazilian older people living in the community, including different regions and cities with various sociodemographic characteristics. The cities were chosen by the convenience of research coordinators* and the sample in each city was selected according to probabilistic sampling strategy among community dwelling adults aged 65 years or older stratified by sex and age (13). Nonparticipation criteria were: being chair or bed-ridden even if transiently; having sequel of cerebrovascular accidents, decreased strength that could affect performance on tests, advanced Parkinson’s disease, terminal state of cancer and other chronic diseases, and significant cognitive deficit – Mini-Mental State Examination ≤ 14. Participants with missing anthropometric values were excluded from this analysis.

2.2 Instruments and Procedures The Frailty in Brazilian Older People Study (FIBRA-BR) was a cross sectional study. The older subjects were recruited at home and invited to participate. Data were collected from 2009 to 2010 using a standard multidimensional questionnaire containing sociodemographic data, health habits, self reported comorbidities (e.g. heart disease, lung disease arterial hypertension, stroke, diabetes, cancer, depression, osteoporosis and osteoarthritis), functional capacity (14,15), cognitive evaluation (MMSE)(16), anthropometric variables and the frailty criteria of the Cardiovascular Health Study (CHS)(2). All participants signed the informed consent form and the research ethics committees of the four universities involved in the study approved the research protocol (17-19).

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2.3 Anthropometric measurements Weight was measured with a standardized electronic scale, with the subject barefoot, preferentially fasting and with empty bladder; the subjects were instructed to stand up barefoot in the erect position, looking at the horizon. Height was measured with a fixed graduation rule in wall, without shoes. BMI was calculated as weight divided by height squared. The subjects were classified according to the stratification proposed by the WHO (20); moderate and severe obesity were assigned to a single category: underweight: BMI < 18.5 kg/m2; normal weight: 18.5 ≥BMI<25.0 kg/m2; overweight: 25 kg/m ≥ BMI <30.0; obesity ≥ 30 kg/m2. The circumferences were determined with a single measurement using a metric tape. The waist circumference (WC) was measured between the ribs and the iliac crest, and the subjects were classified as having normal or high waist (≥88 cm for women and ≥ 102 cm for men)(20) The hip circumference (HC) was measured in the level of the greatest protuberance of the hip. The waist-to-hip ratio (WHR) was determined as the quotient between WC and HC. The method for the assessment of frailty in the Brazilian population was published elsewhere (13, 17, 21-22). Briefly, the criteria proposed by Fried et al.(2) were adopted for the diagnosis of frailty and the cut-off points were based on the sample characteristics. It was composed by: unintentional weight loss; exhaustion; slow walk; low grip strength; and low activity. Subjects with no positive items were classified as non-frail, with one or two as pre-frail and with three or more as frail.

2.4 Statistical analyses Descriptive statistical analysis was performed using proportions according to the nature of the variables. The normal BMI group (eutrophic) was used as reference for the analysis of association (multinomial logistic regression) between body composition – assessed by BMI, WC and WHR – and frailty profiles. The analyses of all variables were calculated with a 95% confidence interval (CI) and P < .05 was considered a statistically significant. The data were analyzed using the SAS® software, version 9.0 (SAS Institute, Inc., Cary, NC). Frailty and BMI divided by WC (Figure 2.) was created according to Hubbard et al. (8) and plotted using the R software.

3. Results From 6.876 participants, 1238 was excluded from analysis due to: missing data (n =1028) –weight, height or incomplete frailty criteria in the database. Participants registered with age <65

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years (n=55) were excluded, as well as those with height recorded below 1.3 (n= 9), and those with MMSE below 14 (n=146) (Figure 1). A total of 5638 participants (women = 66.2%) were, therefore, included in this analysis. Mean age was 73.1 ± 6.2 years (range: 65-102 years), 34.2% of the participants being aged from 65 to 69 years. Most participants had low educational level (54.8%). Mean BMI was 27.0 ± 4.8 kg/m2 and 39.6% were considered to be overweight. Mean WC was 92.6 ± 11.8, and mean WHR was 0.91 ± 0.08. Most of the participants were classified as pre-frail (52.7%) and 8% as frail. Table 1 presents the sociodemographic characteristics and the frailty profile of the sample. Frailty was associated with advanced age, low income, comorbidities, functional dependence, falls and lower score in MMSE. The association between frailty and BMI, WC and WHR was analyzed by multinomial logistic regression (Table 2). After adjustment for sex, income, educational level, advanced age and dependence in BADL, low weight was associated with frailty and high WC to pre-frailty and frailty. Conversely, overweight was a protective factor for both profiles. Obesity and high WHR were not associated with any condition. After adjustment, the associations remained similar except for the obesity range that became associated with the pre-frail profile. The association between frailty and body composition is also illustrated in Figure 2. For this analysis, only the frail participants were classified according to BMI and WC (8). Noteworthy, most of the frail participants were in the group with BMI <18.5 kg/m2, and the lowest proportion were in the group with BMI range from 25 to 29.9 kg/m2. The prevalence of frailty increased slightly in those with BMI≥30 kg/m2. Independent of the BMI observed, older individuals with high WC had higher prevalence of frailty when compared with those who were classified as having a normal WC.

4. Discussion The authors understand frailty as a state of vulnerability associated with ageing that results from a reduction of homeostatic reserve. Many factors influence directly frailty: lifestyle, comorbidities, socio-demographic characteristics and others (23). For instance, the higher prevalence of frailty among women, suggested by some studies (3), may be explained by lower muscle mass, longer life expectancy or higher number of comorbidities (6). In the present study, frailty was more prevalent in the extremes of BMI, predominantly in the lower range. The lowest prevalence of frailty was detected among subjects classified as overweight (9%) and the highest prevalence among those classified as underweight (34.6%). Among participants with obesity, 12.9% were frail. Blaum et al. (2005) also detected a similar relation, showing a significant association between low BMI and frailty (OR; CI = 1.6; 0.7-3.8), high BMI and pre-frailty (OR; CI = 2.5; 1.5-4.1), and frailty (OR; CI = 5.6; 2.4-13.2)(9). Hubbard 6

et al. (2010) also observed this phenomenon, graphically represented as a U-shaped curve (8). In addition, in the present study, regardless of the BMI category, the proportion of frailty was higher among subjects with a high WC (Figure 2). This fact, also observed by other authors, suggests that the accumulation of abdominal fat, which can be measured indirectly by means of the WC, may be one of the main factors that connect obesity with frailty (8, 24). Ramsay et al., (2015) show that, in men, the average circumference values were higher in frail older people when compared to nonfrail, and the prevalence of high WC was 46% versus 31% for frail and non-frail older subjects, respectively (25). According to Moretto et al. (2012), the relation between frailty and abdominal adiposity is based on the sharing of some physiological mechanisms such as metabolic syndrome (26). This relation seems to be directly linked to the production of IL-6, a pro-inflammatory cytokine responsible for increased lipolysis and fatty acid expression and for the reduced expression of the substrate of the insulin-1 and Glut-4 receptors (27). High WC is also related to increased risk of death independently of BMI and has been used with a predictive measure of disability in the elderly (28). Fat distribution, especially abdominal fat, was related to the risk of cardiovascular disease and also frailty. Garcia-Garcia et al. (2011) proposed the inclusion of WC ≥102 in men and 88 in women as a component to frailty screening (29). However, studies that have set out to evaluate the association between WC and frailty are still contradictory. Although high WHR values seem to be associated with the frail group (30), this index, when compared to other anthropometric indicators such as WC, proved to be a worse indicator of adiposity(20). Thus, the present results support the idea that the association between body composition and frailty develops through two pathways. The first is related to low weight and may be triggered by the development of sarcopenia and its physical consequences in addition to the greater vulnerability of low weight individuals for the risk of death (31). The second, is related to extreme obesity and abdominal hyper adiposity, possibly involving inflammation and insulin resistance as the primary causes (32). In this respect, exacerbated inflammation is also related to greater functional disability, multimorbidities and sarcopenia, generated by the loss of muscle fibers (33). On the other hand, overweight proved to be a protective factor against pre-frailty and frailty in both genders. Indeed, there is a paradox regarding the apparent risk of developing cardiovascular diseases and greater morbidity and the lower risk of mortality in overweight older subjects (34). Thus, the risk-associated BMI values applied to the young and adult population do not seem to apply to the older population (35). Systematic reviews and meta-analyses have indicated that the BMI involving the lowest risk of death for elders is actually represented by overweight and even by mild obesity (36, 37). A higher BMI in advanced ages can actually be considered a protective factor against malnutrition, fractures and cognitive decline (35). In this 7

respect, Bowen et al. (2012) suggested that in pre-frail and frail subjects some excess weight may be beneficial, reducing functional disability (38). Specifically, in the frail elderly, being underweight, eutrophic or obese was related with poorer survival, while being overweight tended to have no influence in frailty or mortality (39). However, it is essential to point out that, regarding body composition, muscle mass is more associated with survival of the older person than simply BMI, while very low or very high BMI is associated with higher mortality (40). The present study has some limitations and its results should be viewed with caution. The method used in the present study to assess body composition of older persons is a target of intense debate. This is mainly due to the redistribution of body fat and to the compensation between the reduction of lean mass and the increase of fat mass, which may influence the real estimate of BMI. Nevertheless, using the method in combination with circumference measurements attenuated this limitation. Also, this is a cross-sectional study, and the associations observed could not establish a causal nexus between the studied variables and frailty. In addition it is important to consider height and weight are considered in three of the five criteria of the frailty classification used in this study which could cause a bias of information since the frailty phenotype is dependent on body composition. Nevertheless, the findings presented are interesting to reflect on how and in what manner set this troubling issue. Another issue to be considered is the items proposed by CHS. There were problems in the MLTPA, where many reference activities are atypical in the Brazilian culture leading to bias in the estimation of caloric expenditure. To overcome this limitation, we used only those activities that have been properly applied throughout the sample: carpentry in workshop, cycling, dancingballroom, home exercises, exercises in club or gym, football, weight lifting, swimming at pool or beach, painting inside or outside the house, cut the grass with manual or electric mower, moderate to heavy housework, using stairs when elevator is avaiable, take the bush with rake, mowing lawn with riding mower, running and all kinds of walking. In conclusion, body composition, particularly underweight, was associated with the frail and pre-frail profiles in this study. Abdominal adiposity was associated with the frail profile regardless of BMI range, and therefore the WC may be an important measure of assessment in older persons. Overweight may be considered a protective factor against frailty, being the BMI within 25.0 to 29.9 the range with the lowest prevalence. We believe that new studies using more accurate methods for the evaluation of body composition essential for a better understanding of the “frailty-body composition” relationship.

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Disclosure: The funding played no role in study design, collection, analysis, interpretation of data, writing of manuscript, or the decision to submit for publication. The authors declared no conflict of interest.

Authors contributions:

Ferriolli, Neri, Dias and Lourenço: study concept and design, data

interpretation, critical review of the manuscript; Pessanha: data interpretation, acquisition of data, drafting the manuscript; Moreira: data analysis, data interpretation and drafting the manuscript. All authors revised the manuscript for important intellectual content and read and approved the final manuscript.

Funding Source: This work was supported by two Brazilian funding agencies: the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq - 555087/2006-9), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ - E-26/171.489/2006), Fundação de Amparo à Pesquisa de Minas Gerais (FAPEMIG- 572/2006-02).

Ethical standards: The study was approved by the appropriate Ethics Committee on Human Research and was in accordance with the Declaration of Helsinki for human studies.

Conflicts of interest: There are no financial or personal conflicts of interest associated with this study. All authors declare that they have no conflicts of interest.

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Figure 1. Flow Chart sample selection of individuals aged 65 or older Frailty in Brazilian Older People Study – FIBRA-BR.

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Figure 2. Proportion of frail older adults according to BMI category (WHO) and divided into groups according to waist circumference. (Cut-off point for waist circumference: > 88 cm for women and > 102 cm for men) (N=5307).

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TABLE 1. Demographic, Clinical and Anthropometric Characteristics of the Participants (Total Sample), According to the Brazilian Geographic Region, 2010. (N = 5638) Non Frail

Gender

Age (years)

Marital status

Schooling (years)

Ethnicity

Diseases

BADL†

IADL‡

BMI*

WC**

Pre Frail

Frail

Total

n

%

n

%

n

%

n

%

Male

823

37.1

953

32.1

127

28.1

1903

33.8

Female

1394

62.9

2016

67.9

325

71.9

3735

66.2

65 - 69

872

39.4

959

32.4

91

20.2

1922

34.2

70 - 74

706

31.9

849

28.7

99

22.0

1654

29.4

75 – 79

394

17.8

610

20.6

128

28.4

1132

20.1

80 +

243

11.0

544

18.4

133

29.5

920

16.3

Married

1196

54.0

1430

48.3

181

40.2

2807

49.9

Widower

681

30.8

1047

35.3

196

43.6

1924

34.2

Single

188

8.5

297

10.0

47

10.4

532

9.5

Divorced

148

6.7

189

6.4

26

5.8

363

6.5

Illiterate

366

16.5

590

19.9

125

27.8

1081

19.2

1–5

1223

55.3

1623

54.8

235

52.3

3081

54.8

6 - 11

439

19.8

535

18.1

71

15.8

1045

18.6

> 12

185

8.4

214

7.2

18

4.0

417

7.4

White

1205

55.4

1502

51.8

222

50.0

2929

53.1

Black

194

8.9

288

9.9

42

9.5

524

9.5

Mixed

763

35.1

1090

37.6

176

39.6

2029

36.8

Indigenous

13

0.6

22

0.8

4

0.9

39

0.7

None

430

21.2

474

17.9

46

11.1

950

18.7

1-2

1081

53.3

1315

49.6

183

44.3

2579

50.6

3-4

318

15.7

463

17.5

92

22.3

873

17.1

>4

199

9.8

400

15.1

92

22.3

691

13.6

Independent

1819

82.0

2316

78.0

309

68.4

4444

78.8

Dependent

398

18.0

653

22.0

143

31.6

1194

21.2

Independent

1363

61.5

1469

49.5

106

23.5

2938

52.1

Dependent

854

38.5

1500

50.5

346

76.5

2700

47.9


33

1.5

72

2.4

34

7.5

139

2.5

18.5-24.99

711

32.1

1045

35.2

156

34.5

1912

33.9

25-29.99

929

41.9

1152

38.8

149

33.0

2230

39.6

30-34.99

415

18.7

525

17.7

82

18.1

1022

18.1

>35

129

5.8

175

5.9

31

6.9

335

5.9

Normal

1128

51.0

1481

50.1

211

46.9

2820

50.2

High

1084

49.0

1477

49.9

239

53.1

2800

49.8

Legend: † BADL=Basic Activities of Daily Living,(Katz Index); ‡IADL= Instrumental Basic Activities of Daily Living (Lawton & Brody Scale); Dependence in one or more activities was identified as dependent *BMI= Body Mass Index according to WHO; **WC= Waist Circumference

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TABLE 2. Association Between BMI, Circumferences and Frailty by Multinomial Logistic Regression. FIBRA/BR Study (N=5307)

Unadjusted Model OR(95% CI)

Adjusted Model a OR (95% CI)

Pre Frail

Frail

Pre Frail

Frail

1.17 (0.81-1.68)

3.32 (2.26-4.88)*

1.10 (0.76-1.60)

3.10 (2.06-4.67)*

Ref.

Ref.

Ref.

Ref.

0.76(0.66-0.88)*

0.47(0.39-0.56)*

0.77 (0.67-0.90)*

0.48 (0.40-0.58)*

1.17(1.00-1.37)

0.93(0.76-1.13)

1.29 (1.09-1.51)*

1.07 (0.87-1.32)

High WC

1.08 (1.02-1.15)*

1.17 (1.07-1.29)*

1.09 (1.02-1.17)*

1.15 (1.03-1.27)*

High WHR

1.02 (0.95-1.10)

0.99 (0.89-1.10)

1.04 (0.96-1.11)

1.01 (0.90-1.13)

Underweight < 18.5

Normal weight 18.5- 24.9

Overweight 25.0- 29.9

Obesity ≥30.0

Legend: OR= Odds Ratio; CI= Confidence Interval a

Multinomial logistic regression models adjusted for age, sex, low income, low schooling and disability

16