Factors Associated with Health-Related Quality of Life in Older Persons Residing in Nursing Homes

Anne-Marie Boström,1 Tommy Cederholm,2 Gerd Faxén-Irving,3 Erika Franzén,4 Helena Grönstedt,5 Åke Seiger,3 Sofia Vikström,6 Anders Wimo7

1Division of Nursing, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Stockholm, Medical Unit Aging, Theme Inflammation and Aging, Karolinska University Hospital, Stockholm and R&D Unit, Stockholms Sjukhem, Stockholm, Sweden; 2Medical Unit Aging, Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Division of Clinical Geriatrics, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Stockholm and Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden; 3Division of Clinical Geriatrics, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Stockholm, Sweden; 4Division of Physiotherapy, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Stockholm, Medical Unit Occupational Therapy and Physiotherapy, Theme Women’s Health and Allied Health Professionals, Karolinska University Hospital, Stockholm and Stockholms Sjukhem R&D Unit, Stockholm, Sweden; 5Medical Unit Occupational therapy and Physiotherapy, Women´s Health and Allied Health Professionals Theme, Karolinska University Hospital, Stockholm, Sweden; 6Division of Occupational Therapy, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Stockholm, Sweden; 7Division of Neurogeriatrics, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Stockholm, Sweden

Correspondence: Anne-Marie Boström, Division of Nursing, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Stockholm, Alfred Nobels allé 23, Huddinge, Stockholm, S 141 83, Sweden, Tel +468524 839 19, Email [email protected]

Purpose: Health-related quality of life (HRQoL) is an important patient-related outcome for the assessment of interventions and treatments in older people. Understanding underlying mechanisms for HRQoL is crucial for improving care, rehabilitation and symptom relief. This study examined the associations between HRQoL and frailty, sarcopenia, dependence of ADL, physical function and nutritional status in older nursing home (NH) residents.
Patients and Methods: This is a cross-sectional study employing baseline data from the Older Person’s Exercise and Nutrition (OPEN) study. Residents ≥ 75 years and able to stand up from seated position, residing in eight nursing homes in Sweden, were recruited. The EuroQoL 5-dimension Questionnaire (EQ-5D-5L, 0– 1) was used to assess HRQoL. For exposure, the FRAIL and SARC-F questionnaires, Bergs Balance Scale, Functional Independence Measure (FIM), and Mini Nutritional Assessment-Short Form (MNA-SF) were used, including chair-stand test, walking speed and some biochemical markers. Descriptive and inferential statistics including linear regression models were applied.
Results: Data from 113 residents (59% women, mean age 85 years) revealed a mean EQ-5D index of 0.76. After relevant adjustments, factors associated with low HRQoL were sarcopenia (p 0.001), cognitive function (p 0.001), dependence in ADL (p=0.002), low plasma-albumin (p=0.002) and impaired nutritional status (p=0.038).
Conclusion: This study displays evidence that modifiable conditions like sarcopenia and malnutrition are related to HRQoL in older NH residents. Such findings indicate a potential for physical exercise, including muscle training, and improved nutritional routines, including protein supplementation, to enhance nursing home care. Future studies, in larger NH populations, on exercise and nutrition for effects on HRQoL are needed.

Keywords: quality of life, EQ5D-5L, sarcopenia, physical function, nutritional status


Health-related quality of life (HRQoL) is an important patient-related outcome for the improvement of care for older people, and for assessing the impact of interventions and treatments.1 Patient-reported outcomes capture the patient’s perspective of care and may reflect the quality of communication between patients and staff.2 Factors such as a high symptom burden, depressive symptoms, and lower activities of daily living (ADL) are reported to be negatively associated with HRQoL in community-dwelling older people with high healthcare consumption.3 Understanding underlying mechanisms for HRQoL is crucial for improving care, rehabilitation and symptom relief.

Nursing home (NH) residents often suffer from physical and cognitive decline and need assistance in completing ADL due to increasing frailty.4 Frailty is estimated to be present in 25% of people >85 years and is strongly related to functional decline and early mortality. HRQoL is associated with maintained independence in ADL.5 Malnutrition contributes to frailty, and a systematic review has reported a prevalence of malnutrition in 18% of older NH residents and 48% “at risk of malnutrition”.6 Nutrition has an essential impact on HRQoL among older NH residents.7

Sarcopenia is defined by reduced muscle strength and impaired muscle mass and physical function according to the European Working Group on Sarcopenia in Older People (EWGSOP2).8 Sarcopenia is a growing concern among older populations. There are substantial overlaps between malnutrition and sarcopenia and between frailty and sarcopenia in older NH residents.9 The link between sarcopenia and HRQoL among older people is fairly well established, but further research is warranted.10 Based on current knowledge we hypothesized that frailty, sarcopenia, dependence of ADL, reduced physical function, and impaired nutritional status are associated with low HRQoL in older NH residents.

Material and Methods

In this cross-sectional study, baseline data from the Older Person’s Exercise and Nutrition (OPEN) study were used. The setting was 62 units in eight NH in Stockholm County, Sweden. The study is registered under ClinicalTrials.gov; Identifier: NCT02702037. For details, see the study protocol.11

Study Sample

Eligible residents were 75 years or older and able to rise from seated position. Exclusion criteria were treatment with protein-rich oral supplementation, body mass index (BMI) exceeding 30 kg/m2, dysphagia, tube-feeding, being bedridden, and suffering from severe kidney disease. None of them were in a terminal stage of life. The eligible residents were able to follow instructions and did not display anxiety or risk for behavioral problems due to challenges of everyday life. Screening for potential participants was performed by registered nurses in collaboration with the research staff.


Outcome Variable

HRQoL was measured by the EQ-5D-5L, comprising five items (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression), and each item is scored in five levels. EQ-5D was administered to the participants for their self-rating. Based on the algorithm developed by the EuroQol-group, the scoring was expressed in terms of utilities between 0 and 1, where 0 represents dead and 1 a perfect health-related quality of life (0–1).12

Exposure Variables

Frailty was screened using the FRAIL questionnaire screening tool consisting of five items assessing fatigue, resistance, ambulation, illness and loss of weight (0–5p; 0=robust; 1–2=pre-frail and 3–5=frail).13 Sarcopenia was assessed by the SARC-F questionnaire estimating strength, assistance with walking, rise from a chair, climb stairs and accidental falls; (0–10p; ≥4=increased risk).14 Furthermore, we used the EWGSOP2 sarcopenia diagnosis set-up combining impaired chair stand capacity (probable sarcopenia) and low fat free mass index (FFMI) (confirmed sarcopenia).8 The residents performed a modified timed chair-stand test with arms folded over the chest or with support from the chair arm rests or walking aid.15 The test was considered impaired when <10 and <8 chair stands were performed in 30 sec in residents <85 years and >85 years, respectively.8 Severity of sarcopenia was graded by gait speed (m/sec), measured over a distance of 10 m indoors. Gait speed below ≤0.8 m/sec indicated severe sarcopenia.8

Physical function was assessed using the chair-stand test described previously.16 Functional balance was measured by the Berg Balance scale,17 which consists of 14 tasks of relevance for everyday life. Each item is scored from 0 to 4 points providing a maximum score of 56 points. ADL was measured with the 13 motor items of self-care, transfer and locomotion from the Functional Independence Measure (FIM) tool.18 Each item is scored on a 7-point scale from 1 (dependent) to 7 (independent), providing a total sum ranging from 13 to 91 points.

Nutritional status was assessed according to the Mini Nutritional Assessment-Short Form (MNA-SF) (0–14; 12–14=normal nutritional status; 8–11=at risk for malnutrition; 0–7=malnourished).19 We also used the two-step procedure as suggested by the GLIM consortium.20 Then MNA-SF was used for screening, and the diagnosis of malnutrition was confirmed accordingly by the fulfilment of at least one phenotypic criterion; ie, weight loss, underweight or low muscle mass, combined with at least one etiologic criterion; ie, reduced food intake or severe disease burden. Underweight is indicated by BMI <22kg/m2, whereas <20kg/m2 indicates severe malnutrition. Bioelectric impedance analysis (BIA) (ImpediMed SFB7) was performed to estimate FFMI (in kg/m2). An FFMI of 17 kg/m2 for men and 15 kg/m2 for women indicated reduced lean body mass.17 Plasma albumin was analyzed according to routine methods at the Laboratory of Clinical Chemistry, Karolinska University Hospital, Stockholm, Sweden. Plasma albumin is a negative acute phase reactant where low values indicate inflammation, catabolism and disease severity, as well as potential renal losses or reduced synthesis in the liver.

Demographic data on age and sex were collected. Cognitive function was assessed by Short Portable Mental Status Questionnaire (SPMSQ)21 for nine participants (in the pilot-test), and by Mini Mental State Examination (MMSE; 0–30p)22 for the remaining participants. The scores from SPMSQ and MMSE were categorized into four groups; ie, normal cognition defined by SPMSQ>7 or MMSE 24–30, mild cognitive dysfunction by SPMSQ 6–7 or MMSE 20–23; moderate cognitive dysfunction by SPMSQ 3–5 or MMSE 11–19; and severe cognitive dysfunction by SPMSQ 0–2 or MMSE 0–10.22,23

Statistical Analysis

Data are presented as mean (SD), or absolute numbers and percentage, as appropriate. Correlation analysis by Pearson was performed to identify factors correlated with the outcome variable HRQoL, as measured by the EQ-5D-5L index. Since the residuals were normally distributed, relevant and significantly correlated variables for HRQoL were included in a linear regression (backward method) to identify factors independently related with HRQoL. A multi-collinearity analysis was performed to rule out collinearity between variables in the regression (using variance inflation factor range). A p-value of <0.05 was considered as statistically significant. Data analyses were performed using IBM SPSS (version 27, Chicago, Illinois, USA).

Ethical Considerations

The study complies with the Declaration of Helsinki, and the study was approved by the Regional Ethical Review Board in Stockholm, Sweden (2013/1659-31/2, 2015/1994-32 and 2016/1223-32). Verbal informed consent was obtained before study inclusion, and in few cases, strengthened by a legal representative, which was approved by the Regional Ethical Review Board.


The original sample consisted of 120 participants. Seven residents lacked data for the outcome variable HRQoL, leaving an analytic sample of 113 participants (Table 1). The mean age was 86 years, and the majority were women. On average the participants rated a relatively high HRQoL; ie, 0.76. Three quarters of the sample displayed either probable or confirmed sarcopenia, and 17% were identified as malnourished.

Table 1 Sociodemographic and Clinical Characteristics in Older Nursing Home Residents (Total Sample) as Well as Men and Women and Differences Between Sex

Table 2 presents bivariate correlations with HRQoL. Eight variables were significantly associated with HRQoL, ie, sarcopenia by SARC-F, frailty, functional balance, activities of daily life, cognitive function, plasma albumin, chair-stand test, and nutritional status according to MNA-SF. These variables together with sex and age were included in the linear regression model.

Table 2 Correlation Between Independent Variables and Health-Related Quality of Life (HRQoL), Measured by EuroQoL EQ-5D-5L Index in Older Nursing Home Residents

Table 3 shows the results of the linear regression model which indicate that the following conditions were significantly and independently associated with reduced HRQoL; ie, occurrence of sarcopenia (SARC-F) (p<0.001), cognitive function (p<0.001), low activities of daily life (p=0.002), low plasma albumin (p=0.002) and undernutrition (MNA-SF) (p=0.038). Altogether, the five variables explained 66.9% of the variance in the model.

Table 3 Linear Regression Model (Backwards Model) Showing Variables That Were Independently Associated with Health-Related Quality of Life


Our hypothesis that sarcopenia, dependence in ADL and impaired nutritional status are associated with low HRQoL was confirmed, whereas a corresponding association for frailty and reduced physical function (by chair-stand test) with HRQoL was not confirmed. However, we observed that cognitive function and low plasma albumin were significantly associated with low HRQoL. The unexpected finding of no association for frailty and reduced physical function with HRQoL may be explained by the possible overlap between these two conditions with sarcopenia and independence in ADL. Still, the five variables significantly associated with HRQoL were able to explain two thirds of the variance in the model.

Independence in ADL is reported to be associated with high HRQoL in older persons.3 We used FIM to assess independence that reflects physical function and capability of the assessed person. Sarcopenia, ie, loss of muscle strength and mass, threatens the older person’s physical function and independence.24 To prevent sarcopenia in older persons, increased physical activity and exercise is vital. Such activities promote healthy aging in older adults and has the potential to play an important role in improving HRQoL.25

In older NH residents, malnutrition or risk of malnutrition is common. Especially deficiency of protein may negatively affect physical functioning and reduce effects of exercise and strength training. In the OPEN study, high adherence to protein-rich oral nutritional supplement increased the odds for response in the primary outcome that was chair-stand test.26 Other studies have also shown that nutrition is important for physical function.27

EQ-5D was utilized for self-report and not proxy report, which has pros and cons. When proxies are used for rating HRQoL it can be difficult to discriminate whether the rating reflects the person’s views or the proxy rater’s perception.28 The validity of self-reported ratings by people with dementia may be questioned. However, there are patterns in ratings by people with dementia that are rather consistent: they tend to rate HRQoL higher than their proxies.29,30 In line with this assumption is the fact that lower scores in the cognitive functional tests are independently related to better HRQoL. Otherwise, it is interesting that the results indicate associations of domains that are in line with corresponding research among people without dementia.

Strengths of this study are the use of tests and screening instruments validated for the NH population. However, we were limited to the data collected in the OPEN study, and variables regarding depression and pain, which could be of interest in assessing factors associated with HRQoL, were not collected. Also, data regarding contextual factors related to the NH and NH staff were not collected. The inclusion of such factors might have increased the explanatory value of the model to even higher levels. Another limitation is that the study criteria excluded nearly 65% of the residents in the eight NH for eligibility, mainly due to lack of ability to rise from a chair. Thus, the generalizability of the findings to the NH population at large should be interpreted with caution.


This study displays evidence that the modifiable conditions of sarcopenia and malnutrition are associated with reduced HRQoL in older NH residents. Such findings indicate a potential for physical exercise, including muscle training, and improved nutritional routines, including protein supplementation, to enhance nursing home care. Studies, in larger NH populations, on exercise and nutrition for effects on HRQoL are needed.


ADL, Activities of daily living; BIA, Bioelectric impedance analysis; BMI, Body mass index; EWGSOP, European Working Group on Sarcopenia in Older People; FFMI, Fat free mass index; FIM, Functional Independence Measure; HRQoL, Health-Related Quality of Life; MMSE, Mini Mental State Examination; MNA-SF, Mini Nutritional Assessment – Short Form; NH, Nursing home; OPEN, Older Person’s Exercise and Nutrition study; SPMSQ, Short Portable Mental State Questionnaire.

Data Sharing Statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.


We are thankful to all participating residents and staff in the eight NHs. We are also grateful to Ms Elin Linde for support regarding data collection, and Ms Frida Eriksson for data management.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.


This study was supported by Gamla Tjänarinnor as well as the Danone Nutricia Research, Utrecht, the Netherlands, who also provided the study products.


AMB, GFI, EF, HG, ÅS, and SV declare no potential conflicts of interest in this study. TC has previously received unconditioned research funding as well as honoraria for lectures from the sponsoring agent (Nutricia) and personal fees from Abbott, Nestle, and Fresenius Kabi, outside the submitted work. AW reports personal fees from EISAI, outside the submitted work. In addition, AW has a patent RUD-instrument licensed to RUD-instrument.


1. Haraldstad K, Wahl A, Andenæs R, et al. A systematic review of quality-of-life research in medicine and health sciences. Qual Life Res. 2019;28:2641–2650. doi:10.1007/s11136-019-02214-9

2. Antunes B, Harding R, Higginson IJ. Implementing patient-reported outcome measures in palliative care clinical practice: a systematic review of facilitators and barriers. Palliat Med. 2014;28(2):158–175. doi:10.1177/0269216313491619

3. Klompstra L, Ekdahl AW, Krevers B, et al. Factors related to health-related quality of life in older people with multimorbidity and high health care consumption over a two-year period. BMC Geriatr. 2019;19(1):187. doi:10.1186/s12877-019-1194-z

4. Reber KC, Lindlbauer I, Schulz C, et al. Impact of morbidity on care need increase and mortality in nursing homes: a retrospective longitudinal study using administrative claims data. BMC Geriatr. 2020;20(1):439. doi:10.1186/s12877-020-01847-7

5. Salminen K, Suominen M, Kautiainen H, Pitkälä K. Associations between nutritional status, frailty and health-related quality of life among older long-term care residents in Helsinki. J Nutr Health Aging. 2020;24(3):319–324. doi:10.1007/s12603-019-1320-9

6. Guigoz Y, Vellas B. Nutritional assessment in older adults: MNA 25 years of a screening tool & a reference standard for care and research; what next? J Nutr Health Aging. 2021;25(4):528–583. doi:10.1007/s12603-021-1601-y

7. Salminen KS, Suominen M, Soini H, et al. Associations between nutritional status and health-related quality of life among long-term care residents in Helsinki. J Nutr Health Aging. 2019;23(5):474–478. doi:10.1007/s12603-019-1182-1

8. Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16–31. doi:10.1093/ageing/afy169

9. Faxén-Irving G, Luiking Y, Grönstedt H, et al. Do malnutrition, sarcopenia and frailty overlap in nursing-home residents? J Frailty Aging. 2020;10:17–21. doi:10.14283/jfa.2020.45

10. Beaudart C, Locquet M, Reginster JY, et al. Quality of life in sarcopenia measured with the SarQoL®: impact of the use of different diagnosis definitions. Aging Clin Exp Res. 2018;30(4):307–313. doi:10.1007/s40520-017-0866-9

11. Grönfeldt H, Vikström S, Cederholm T, et al. A study protocol of Older Person’s Exercise and Nutrition Study (OPEN) – A sit-to-stand activity combined with oral protein supplement – effects on physical function and Independence: a cluster randomized clinical trial. BMC Geriatr. 2018;18(1):138. doi:10.1186/s12877-018-0824-1

12. The EuroQol Group. EuroQol – a new facility for the measurement of health-related quality of life. Health Policy (New York). 1990;16(3):199–208. doi:10.1016/0168-8510(90)90421-9.

13. Morley JE, Malmstrom TK, Miller DK. A simple frailty questionnaire (FRAIL) predicts outcomes in middle aged African Americans. J Nutr Health Aging. 2012;16(7):601–608. doi:10.1007/s12603-012-0084-2

14. Malmstrom TK, Morley JE. SARC-F: a simple questionnaire to rapidly diagnose sarcopenia. J Am Med Dir Assoc. 2013;14(8):531–532. doi:10.1016/j.jamda.2013.05.018

15. Grönstedt H, Vikström S, Cederholm T, et al. Effect of sit-to-stand exercises combined with protein-rich oral supplementation in older persons: the OPEN Study. J Am Med Dir Assoc. 2020;21(9):1229–1237. doi:10.1016/j.jamda.2020.03.030

16. Jones CJ, Rikli RE, Beam WC. A 30-s chair-stand test as a measure of lower body strength in community-residing older adults. Res Q Exerc Sport. 1999;70(2):113–119. doi:10.1080/02701367.1999.10608028

17. Berg K, Wood-Dauphinee S, Williams JI, Gayton D. Measuring balance in the elderly: preliminary development of an instrument. Physiother Can. 1989;41(6):304–311. doi:10.3138/ptc.41.6.304

18. Cohen ME, Marino RJ. The tools of disability outcomes research functional status measures. Arch Phys Med Rehabil. 2000;81:S21–9. doi:10.1053/apmr.2000.20620

19. Kaiser MJ, Bauer JM, Ramsch C, et al. Validation of the mini nutritional assessment short-form (MNA-SF): a practical tool for identification of nutritional status. J Nutr Health Aging. 2009;13(9):782–788. doi:10.1007/s12603-009-0214-7

20. Cederholm T, Jensen GL, Correia MITD, et al.; GLIM Core Leadership Committee, GLIM Working Group. GLIM criteria for the diagnosis of malnutrition – A consensus report from the global clinical nutrition community. Clin Nutr. 2018;38(1):1–9. doi:10.1016/j.clnu.2018.08.002

21. Pfeiffer E. A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc. 1975;23(10):433–441. doi:10.1111/j.1532-5415.1975.tb00927.x

22. Folstein MF, Folstein SE, McHugh PR. ”Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–198. doi:10.1016/0022-3956(75)90026-6

23. Aguero-Torres H, Qiu C, Winblad B, Fratiglioni L. Dementing disorders in the elderly: evolution of disease severity over 7 years. Alzheimer Dis Assoc Disord. 2002;16(4):221–227. doi:10.1097/00002093-200210000-00003

24. Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet. 2019;393(10191):2636–2646. doi:10.1016/S0140-6736(19)31138-9

25. World Health Organization. Guidelines on physical activity and sedentary behaviour: at a glance. Geneva: World Health Organization; 2020.

26. Karlsson E, Grönstedt H, Faxen-Irving G, et al. Response and adherence of nursing home residents to a nutrition/exercise intervention. J Am Med Dir Assoc. 2021;22(9):1939–1945. doi:10.1016/j.jamda.2021.04.001

27. Azhar G, Wei JY, Schutzler SE, et al. Daily consumption of a specially formulated essential amino acid-based dietary supplement improves physical performance in older adults with low physical functioning. J Gerontol A Biol Sci Med Sci. 2021;79(7):1184–1191. doi:10.1093/gerona/glab019

28. O’Shea E, Hopper L, Marques M, et al. A comparison of self and proxy quality of life ratings for people with dementia and their carers: a European prospective cohort study. Aging Ment Health. 2020;24(1):162–170. doi:10.1080/13607863.2018.1517727

29. Jonsson L, Andreasen N, Kilander L, et al. Patient- and proxy-reported utility in Alzheimer disease using the EuroQoL. Alzheimer Dis Assoc Disord. 2006;20(1):49–55. doi:10.1097/01.wad.0000201851.52707.c9

30. Kisvetrová H, Školoudík D, Herzig R, et al. Psychometric validation of the czech version of the quality of life – Alzheimer’s disease scale in patients with early-stage dementia. Dement Geriatr Cogn Disord. 2018;46(1–2):109–118. doi:10.1159/000492490

Leave a Reply

Your email address will not be published. Required fields are marked *