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Association between the risk of malnutrition and functional capacity in patients with peripheral arterial disease: A cross-sectional study

Abstract

Introduction

The risk of malnutrition is an important predictor of functional capacity in the elderly population. However, whether malnutrition is associated with functional capacity in patients with peripheral artery disease (PAD) is poorly known.

Purpose

To analyse the association between the risk of malnutrition and functional capacity in patients with PAD.

Methods

This cross-sectional study included 135 patients with PAD of both genders, ≥50 years old, with symptomatic PAD (Rutherford stage I to III) in one or both limbs and with ankle-brachial index ≤0.90. The risk of malnutrition was assessed by the short form of the Mini Nutritional Assessment-Short Form and patients were classified as having normal nutritional status (n = 92) and at risk of malnutrition (n = 43). Functional capacity was objectively assessed using the six-minute walking test (6MWT, absolute maximal distance and relativized and expressed as a percentage of health subjects), short-physical performance battery (SPPB, balance, gait speed and the sit and stand test) and the handgrip test, and subjectively, using the Walking Impairment Questionnaire and Walking Estimated-Limitation Calculated by History. The association between the risk of malnutrition and functional capacity was analysed using bivariate and multivariate logistic regression adjustments for gender, age, ankle-brachial index, body mass index, use of statins, coronary arterial disease and stroke. For all statistical analyses, significance was accepted at p<0.05.

Results

Thirty-two per cent of our patients were classified with a risk of malnutrition. The risk of malnutrition was associated with the absolute 6MWT total distance (OR = 0.994, P = 0.031) relative 6MWT total distance (OR = 0.971, P = 0.038), lowest SPPB total score (OR = 0.682, P = 0.011), sit and stand (OR = 1.173, P = 0.003) and usual 4-meter walk test (OR = 1.757, P = 0.034).

Conclusion

In patients with PAD, the risk of malnutrition was associated with objective measurements of functional capacity.

Introduction

Peripheral artery disease (PAD) is characterised by a systemic arteriosclerotic process, which results in partial or total obstruction in the arteries of the lower limbs [1]. The most common symptom of PAD is claudication [2], consisting of pain or cramp during walking that is relieved at rest. The symptoms of claudication affect about 20 to 50% of patients with PAD, leading to reduced levels of physical activity [3], functional capacity [4] and quality of life [5].

Impaired nutritional status has been considered an additional risk factor for the severity of the PAD [6, 7]. A study by Thomas et al. [8] observed that approximately 78% of patients admitted for vascular surgery were classified as malnourished. Additionally, another study [7] found that 38% of patients submitted to endovascular surgery were malnourished. The risk of malnutrition can be evaluated through Mini Nutritional Assessment-Short Form (MNA-SF), a valid and simple nutritional screening tool [9, 10], which can be easily applied in clinical settings. The MNA-SF consists of six items related to food intake, weight loss, mobility, stress or acute illness, neuropsychological disorders and body-mass index values. The questionnaire score ranges from 0 to 14 points, and individuals are classified as: malnourished (MNA-SF score ≤7), at risk of malnutrition (MNA-SF score ≥8 ≤11) or normal nutritional status (MNA-SF score ≥ 12) [9, 11].

Interestingly, in previous studies risk of malnutrition, an intermediate classification of nutritional status, was associated with reduced functional capacity and lower limb strength in healthy elderly [12] and patients with long-term conditions such as stroke [13], renal failure [14], diabetes [15] and chronic obstructive pulmonary disease [16]. Thus, this study aimed to analyse the association between the risk of malnutrition and functional capacity in patients with symptomatic PAD. Our hypothesis is that malnutrition has an additional factor to functional impairments.

Methods

Study design

This observational cross-sectional study follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist [17]. Functional capacity was assessed using objective tests (six-minute walk test, Short-Physical Performance Battery and handgrip strength) and subjective tools such as the Walking Impairment Questionnaire (WIQ) and Walking Estimated-Limitation Calculated by History (WELCH). The sample was evaluated according to nutritional status using MAN-SF and was classified as “at risk of malnutrition" and "normal nutritional status". The functional capacity parameters were compared between groups.

Sample and data collection

Patients were recruited at a tertiary center specializing in vascular disease in São Paulo—Brazil. Data collection was carried out between September 2015 and October 2019. All patients were instructed regarding the experimental procedures and signed informed written consent before participation. This study was approved by the ethics committee of Hospital Israelita Albert Einstein, Brazil and Hospital das Clinicas, University of Sao Paulo, Brazil.

We included patients of both genders, ≥50 years old, with symptomatic PAD (Rutherford stage I to III) in one or both limbs, ankle-brachial index ≤0.90 [18]. Patients with non-compressible vessels, amputated limbs and/or ulcers, and low cognitive levels (<17 of the Montreal Cognitive Assessment) [19] were excluded.

Clinical data

A standardised interview was conducted, including an evaluation of sociodemographic information, such as age and gender (male or female) and conditions of comorbidities (doctor-diagnosed history and medications). Current smoking, obesity (body mass index ≥30 kg/m2), diabetes (doctor-diagnosed or use of drugs), hypertension (doctor-diagnosed or antihypertensive drugs), dyslipidaemia (doctor-diagnosed or use of medication) and coronary heart disease (doctor-diagnosed or use of drugs) were assessed.

Dependent variable: Risk of malnutrition

The risk of malnutrition was assessed through the MNA-SF [10], which consists of six questions based on conditions of self-visualization of food intake (0 to 2 points), weight loss (0 to 3 points), mobility (0 to 2 points), psychological stress (0 or 2 points), neuropsychological problems (0 to 2 points) and a measure of body mass index (0 to 3 points). The sum of the points provides scores ranging from 0 to 14. Patients were classified as: ≤ score 7 as "malnourished", score 8 to 11 as "at risk of malnutrition", and score ≥ 12 as "normal nutritional status" [15].

Independent variables

Objective measurements of functional capacity.

The six-minute walk test. The 6MWT [20] consists of walking for six minutes in a 30-meter long flat corridor, and patients were encouraged to "walk at the usual pace" and instructed to rest when necessary. The 6MWT total distance was defined as the maximum distance achieved by the patients at the end of the test. In addition, the 6MWT total distance was relativised based on the results of 6MWT performed by healthy individuals using Brito’s et al. equation [21], previously used in patients with PAD [22].

Short Physical Performance Battery. The SPPB [23] comprises a group of tests involving balance, gait speed and the sit and stand test. The balance consisted of the patient remaining in each timed foot position for 10 seconds (feet side by side, semi-tandem and tandem), and the evaluator demonstrated each position. The gait speed consisted of the patient walking for 4 meters twice in a usual and fast way, being the fastest time used for the analysis. The sit and stand test required the initially seated patient to get up from the chair five times with arms flexed over the chest as quickly as possible, and time recorded. Each test score ranged from 0 to 4, and the total score was calculated by adding scores of three tests, ranging from 0 to 12, being 0 in the worst function and 12 in the best function [24].

Handgrip Strength Test. The handgrip strength test was obtained through isometric contractions using a digital dynamometer (EH101, Camry, USA) adjusted and calibrated on a scale from 0 to 100 kgf. The patient was seated with feet resting on the ground, and elbows flexed to 90 degrees and forearms and wrists in a neutral position. Three maximum voluntary contractions of five seconds were performed in both arms with an interval of one minute between each attempt. We considered the highest value for the analysis [25].

Subjective measurements of functional capacity.

Walking Impairment Questionnaire. The WIQ [26] is an instrument that provides self-reported indicators of the walking capacity of patients with PAD and claudication symptoms in different situations, such as walking distance, walking speed and ability to climb stairs. The total score ranges from 0 to 100, where 0 represents extreme limitation, and 100 represents no walking difficulties.

Walking Estimated-Limitation Calculated by History. The WELCH [27] is a questionnaire that presents four questions related to the speed and time the patient can walk compared to relatives, friends or individuals of the same age without PAD. The total score ranges from 0 to 100, with 0 indicating a patient who can walk for 30 seconds slower than relatives, friends or colleagues in the same age group, and a score of 100 indicates who can walk for three hours compared to people in the same age group.

Statistical analysis

We describe the data in median (interquartile interval) or frequency. The association between the risk of malnutrition and functional capacity was analysed using bivariate and multivariate logistic regression analysis with adjustment for gender, age, ankle-brachial index, body mass index, use of statins, coronary arterial disease and stroke, which are classical confounders in PAD [28, 29]. The p<0.05 value was considered significant. All statistical analyses were performed with SPSS version 25.0 (IBM Corporation, SPPS Inc, Chicago, IL).

Results

Three hundred and two patients were recruited. However, 31 patients were excluded because they did not answer the MNA-SF questionnaire, and 112 patients were due to the low score on the cognitive assessment, since these patients were probably not able to answer the questionnaires correctly, and this could be a confounding fact in the analyses and 21 excluded for not performing the 6MWT. Furthermore, only three patients were classified as malnourished and were excluded due to the insufficient sample size. Thus, we analysed the data of 135 patients, 68% of patients were classified as having normal nutritional status, and 32% were classified as at risk of malnutrition. The flowchart of the study is shown in Fig 1.

The characteristics of the patients with normal nutritional status and risk of malnutrition are presented in Table 1.

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Table 1. Clinical characteristics of patients with peripheral arterial disease associated with the risk of malnutrition n = 135.

https://doi.org/10.1371/journal.pone.0273051.t001

The characteristics and prevalence of risk factors were similar between groups. Patients at risk of malnutrition presented more prevalence of psychological stress/acute diseases (P = 0.013), neuropsychological problems (P = 0.022) and a lower BMI classification (P = 0.005).

Table 2 shows the association between the risk of malnutrition and functional parameters in PAD patients.

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Table 2. Logistic regression bivariate and multivariate modelling, associations between at risk of malnutrition and functional parameters in PAD participants.

https://doi.org/10.1371/journal.pone.0273051.t002

We observed a significant association between the risk of malnutrition and functional capacity after adjustments in absolute (OR = 0.994; P = 0.031) and relative (OR = 0.971, P = 0.038) values of 6MWT, SPPB (OR = 0.682; P = 0.011) sit and stand test (OR = 1.173, P = 0.003), usual 4-meter (OR = 1.757, P = 0.034).

Discussion

The main findings of this study were; a) 32% of our sample were classified at risk of malnutrition, and; b) the risk of malnutrition was associated with lower walking distance and lower limb strength.

In the present study, we used the MNA-SF questionnaire to assess the risk of malnutrition in PAD patients. This questionnaire has been used in several populations, such as healthy individuals and patients with different chronic diseases [15, 16, 30]. Still, until the present study, MNA-SF was not explicitly used in PAD. Using this questionnaire, we demonstrated that 32% of our patients were classified as at risk of malnutrition. These values are similar to those observed in patients with diabetes mellitus [15] and heart failure [30], with a prevalence of 33% and 30%, respectively.

We demonstrated that the risk of malnutrition was associated with objective measurement of functional capacity analysed by the absolute and relative six-minute walking test, usual 4-meter and sit and stand test, independently of classical PAD confounders. These results demonstrated that nutritional status is related to walking distance and lower limb strength, both crucial components of overall health in PAD patients [31]. Our study did not examine the possible physiological mechanisms, but some hypotheses can explain these associations. Evidence indicates that inadequate nutrition may favour the progression of inflammation in the epithelium [32], due to high blood concentrations of LDL [33] and changes in the immune system [34], such as the release of cytokines and chemokines [35] that contribute to accelerating the atherosclerotic narrowing of the arteries. In addition, low intake of nutrients, especially vitamin D [36], fibers and antioxidants can promote mitochondrial dysfunction, leading to an alteration in ATP synthesis [37], causing impairment in muscle oxygen perfusion [38], altering skeletal muscle function in density, contractility and strength in the lower limbs, which would contribute to the greater functional decline [39].

In the present study, we did not observe the association between the risk of malnutrition with subjective measures of functional capacity using a specific questionnaire for PAD patients such as WIQ and WELCH. One possible explanation is that the subjective method may underestimate the values of functional capacity when compared to objective methods [40]. Furthermore, physical exertion performed in objective methods of function capacity (such as 6MWT and gait speed) can differ from the patient’s daily activity. This might explain the lack of association with self-perception of PAD-induced walking impairments.

Regarding practical implications, our results may draw attention to healthcare providers to determine the nutritional status of patients with PAD, since we observed a high prevalence of risk of malnutrition and being at risk of malnutrition can lead to a significant decline in walking capacity and lower limb strength. As a result, the MNA-SF could be easily applied in clinical practice to identify patients at risk of malnutrition with time efficiency (with an average application time of three minutes), helping to decide on better treatment strategies (nutrition, exercise, etc.) for these patients.

This study has some limitations. This is a cross-section study that does not allow us to establish causality. Due to the small number of cases, malnutrition was not analysed, which could provide information on the magnitude of the outcomes. The use of self-reported assessments is susceptible to information bias.

In conclusion, the risk of malnutrition was associated with lower functional capacity and lower limb strength. These results suggest that assessment of nutritional status could help define therapeutic approaches in symptomatic PAD patients.

References

  1. 1. Hardman RL, Jazaeri O, Yi J, Smith M, Gupta R. Overview of classification systems in peripheral artery disease. Semin Intervent Radiol. 2014;31(4):378–88. pmid:25435665
  2. 2. Dhaliwal G, Mukherjee D. Peripheral arterial disease: Epidemiology, natural history, diagnosis and treatment. Int J Angiol. 2007;16(2):36–44. pmid:22477268
  3. 3. Gerage AM, Correia M de A, de Oliveira PML, Palmeira AC, Domingues WJR, Zeratti AE, et al. Physical activity levels in peripheral artery disease patients. Arq Bras Cardiol. 2019;113(3):410–6. pmid:31365605
  4. 4. Batista LC, Assis CS, Wolosker N, Zerati AE SR. Association between fatigue and functional capacity with intermittent claudication. Rev Bras Enferm Bras Enferm. 2015;68(6):653–9.
  5. 5. Regensteiner JG, Hiatt WR, Coll JR, Criqui MH, Treat-Jacobson D, McDermott MM, et al. The impact of peripheral arterial disease on health-related quality of life in the Peripheral Arterial Disease Awareness, Risk, and Treatment: New Resources for Survival (PARTNERS) Program. Vasc Med. 2008;13(1):15–24. pmid:18372434
  6. 6. Gardner AW, Bright BC, Ort KA, Montgomery PS. Dietary intake of participants with peripheral artery disease and claudication. Angiology. 2011;62(3):270–5. pmid:21406424
  7. 7. Mizobuchi K, Jujo K, Hagiwara N, Minami Y, Ishida I, Nakao M. The baseline nutritional status predicts long-term mortality in patients undergoing endovascular therapy. Nutrients. 2019;11(8):1. pmid:31362417
  8. 8. Thomas J, Delaney C, Suen J, Miller M. Nutritional status of patients admitted to a metropolitan tertiary care vascular surgery unit. Asia Pac J Clin Nutr. 2019;28(1):64–70. pmid:30896416
  9. 9. Kaiser MJ, Bauer JM, Ramsch C, Uter W, Guigoz Y, Cederholm T, et al. Validation of the Mini Nutritional Assessment short-form (MNA®-SF): A practical tool for identification of nutritional status. J Nutr Heal Aging. 2009;13(9):782–8.
  10. 10. Rubenstein LZ, Harker JO, Salvà A, Guigoz Y, Vellas B. Screening for undernutrition in geriatric practice: Developing the Short-Form Mini-Nutritional Assessment (MNA-SF). Journals Gerontol—Ser A Biol Sci Med Sci. 2001;56(6):366–72.
  11. 11. Vellas B, Villars H, Abellan G, Soto ME, Rolland Y, Guigoz Y, et al. Overview of the MNA®—Its history and challenges. J Nutr Heal Aging. 2006;10(6):456–63.
  12. 12. Tramontano A, Veronese N, Giantin V, Manzato E, Rodriguez-Hurtado D, Trevisan C, et al. Nutritional status, physical performance and disability in the elderly of the Peruvian Andes. Aging Clin Exp Res. 2016;28(6):1195–201. pmid:27262950
  13. 13. Vahlberg B, Zetterberg L, Lindmark B, Hellström K, Cederholm T. Functional performance, nutritional status, and body composition in ambulant community-dwelling individuals 1–3 years after suffering from a cerebral infarction or intracerebral bleeding. BMC Geriatr [Internet]. 2016;16(1):1–9. Available from: pmid:26895855
  14. 14. Cupisti A, D’Alessandro C, Finato V, Del Corso C, Catania B, Caselli GM, et al. Assessment of physical activity, capacity and nutritional status in elderly peritoneal dialysis patients. BMC Nephrol. 2017;18(1):1–8.
  15. 15. Alfonso-Rosa RM, Del Pozo-Cruz B, Del Pozo-Cruz J, Del Pozo-Cruz JT, Sañudo B. The relationship between nutritional status, functional capacity, and health-related quality of life in older adults with type 2 diabetes: A pilot explanatory study. J Nutr Heal Aging. 2013;17(4):315–21.
  16. 16. Matkovic Z, Cvetko D, Rahelic D, Esquinas C, Zarak M, Miravitlles M, et al. Nutritional Status of Patients with Chronic Obstructive Pulmonary Disease in Relation to their Physical Performance. COPD J Chronic Obstr Pulm Dis [Internet]. 2017;14(6):626–34. Available from: pmid:29099635
  17. 17. Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. PLoS Med. 2007;4(10):1623–7.
  18. 18. Wolosker N, Rosoky RA, Nakano L, Basyches M, Puech-Leão P. Predictive value of the ankle-brachial index in the evaluation of intermittent claudication. Rev Hosp Clin Fac Med Sao Paulo. 2000;55(2):61–4. pmid:10959125
  19. 19. Nasreddine Z. S., Phillips N. A., Bédirian V., Charbonneau S., Whitehead V., Collin I., et al. Corrigendum to: The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment: MOCA: A BRIEF SCREENING TOOL FOR MCI (Journal of the American Geriatrics Society, 53, 4, (695–699), 10.1111/j.1532-5415.2005.53221.x). J Am Geriatr Soc. 2019;67(9):1991.
  20. 20. Montgomery PS, Gardner AW. The clinical utility of a six-minute walk test in peripheral arterial occlusive disease patients. J Am Geriatr Soc. 1998;46(6):706–11. pmid:9625185
  21. 21. Britto RR, Probst VS, Dornelas De Andrade AF, Samora GAR, Hernandes NA, Marinho PEM, et al. Reference equations for the six-minute walk distance based on a Brazilian multicenter study. Brazilian J Phys Ther. 2013;17(6):556–63. pmid:24271092
  22. 22. Ritti-Dias RM, Sant’anna F da S, Braghieri HA, Wolosker N, Puech-Leao P, Lanza FC, et al. Expanding the Use of Six-Minute Walking Test in Patients with Intermittent Claudication. Ann Vasc Surg [Internet]. 2020; Available from: pmid:32800882
  23. 23. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A Short Physical Performance Battery Assessing Lower Extremity Function: Association With Self-Reported Disability and Prediction of Mortality and Nursing Home Admission Energetic cost of walking in older adults View project IOM committee on cognitive agi. Artic J Gerontol. 1994;49(2):85–94.
  24. 24. Puthoff PT, PhD ML. Research Corner Outcome Measures in Cardiopulmonary Physical Therapy: Short Physical Performance Battery. Cardiopulm Phys Ther J. 2008;19(1):17–22.
  25. 25. Correia M de A, Cucato GG, Lanza FC, Peixoto RAO, Zerati AE, Puech-Leao P, et al. Relationship between gait speed and physical function in patients with symptomatic peripheral artery disease. Clinics. 2019;74(11):1–5.
  26. 26. Ritti-Dias RM, Gobbo LA, Cucato GG, Wolosker N, Jacob Filho W, Santarém JM, et al. Translation and validation of the walking impairment questionnaire in Brazilian subjects with intermittent claudication. Arq Bras Cardiol [Internet]. 2009;92(2):136–49. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19360247
  27. 27. Cucato GG, Correia M de A, Farah BQ, Saes GF, Lima AH de A, Ritti-Dias RM, et al. Validation of a Brazilian Portuguese version of the walking estimated-limitation calculated by history (WELCH). Arq Bras Cardiol. 2016;106(1):49–55. pmid:26647720
  28. 28. Farah BQ, Ritti-Dias RM, Cucato GG, Chehuen MDR, Barbosa JPDAS, Zerati AE, et al. Effects of clustered comorbid conditions on walking capacity in patients with peripheral artery disease. Ann Vasc Surg. 2014;28(2):279–83. pmid:24220650
  29. 29. Farah BQ, dos Anjos Souza Barbosa JP, Cucato GG, da Rocha Chehuen M, Gobbo LA Wolosker N, et al. Predictors of walking capacity in peripheral arterial disease patients. Clinics. 2013;68(4):537–41. pmid:23778336
  30. 30. Saitoh M, dos Santos MR, Ebner N, Emami A, Konishi M, Ishida J, et al. Nutritional status and its effects on muscle wasting in patients with chronic heart failure: insights from Studies Investigating Co-morbidities Aggravating Heart Failure. Wien Klin Wochenschr. 2016;128:497–504. pmid:27853883
  31. 31. Treat-Jacobson D, McDermott MM, Bronas UG, Campia U, Collins TC, Criqui MH, et al. Optimal Exercise Programs for Patients with Peripheral Artery Disease: A Scientific Statement from the American Heart Association. Circulation. 2019;139(4):E10–33. pmid:30586765
  32. 32. Libby P, Plutzky J. Atherosclerosis: An inflammatory disease. Int Congr Symp Ser—R Soc Med. 2000;(243):27–31.
  33. 33. Brostow DP, Hirsch AT, Collins TC, Kurzer MS. The role of nutrition and body composition in peripheral arterial disease. Nat Rev Cardiol [Internet]. 2012;9(11):634–43. Available from: pmid:22922595
  34. 34. Delaney CL, Smale MK, Miller MD. Nutritional considerations for peripheral arterial disease: A narrative review. Nutrients. 2019;11(6):1–15. pmid:31146408
  35. 35. Sugawara K, Takahashi H, Kasai C, Kiyokawa N, Watanabe T, Fujii S, et al. Effects of nutritional supplementation combined with low-intensity exercise in malnourished patients with COPD. Respir Med [Internet]. 2010;104(12):1883–9. Available from: pmid:20627502
  36. 36. McDermott MM, Liu K, Ferrucci L, Tian L, Guralnik J, Kopp P, et al. Vitamin D status and functional performance in peripheral artery disease. Vasc Med (United Kingdom). 2012;17(5):294–302. pmid:22814997
  37. 37. Hou XY, Green S, Askew CD, Barker G, Green A, Walker PJ. Skeletal muscle mitochondrial ATP production rate and walking performance in peripheral arterial disease. Clin Physiol Funct Imaging. 2002;22(3):226–32. pmid:12076351
  38. 38. McDermott MM, Ferrucci L, Gonzalez-Freire M, Kosmac K, Leeuwenburgh C, Peterson CA, et al. Skeletal muscle pathology in peripheral artery disease a brief review. Arterioscler Thromb Vasc Biol. 2020;(November):2577–85. pmid:32938218
  39. 39. Spark JI, Robinson JM, Gallavin L, Gough MJ, Homer-Vanniasinkam S, Kester RC, et al. Patients with chronic critical limb ischaemia have reduced total antioxidant capacity and impaired nutritional status. Eur J Vasc Endovasc Surg. 2002;24(6):535–9. pmid:12443751
  40. 40. Cucato GG, Zerati AE, Chehuen M da R, Ritti-Dias RM, Saez G, Ragazzo L, et al. Comparison between subjective and objective methods to assess functional capacity during clinical treatment in patients with intermittent claudication. Einstein (Sao Paulo). 2013;11(4):495–9. pmid:24488391