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Quality of life and risk of malnutrition in a home-dwelling population over 75 years old
Accepted Manuscript Quality of life and risk of malnutrition in a home-dwelling population over75 Ana Hernández-Galiot, Isabel Goñi PII:
S0899-9007(16)30236-2
DOI:
10.1016/j.nut.2016.10.013
Reference:
NUT 9864
To appear in:
Nutrition
Received Date: 19 April 2016 Revised Date:
10 October 2016
Accepted Date: 19 October 2016
Please cite this article as: Hernández-Galiot A, Goñi I, Quality of life and risk of malnutrition in a homedwelling population over75, Nutrition (2016), doi: 10.1016/j.nut.2016.10.013. 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.
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TITLE: Quality of life and risk of malnutrition in a home-dwelling population over75. Authors: Ana Hernández-Galiot 1, Isabel Goñi 1,2
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Department of Nutrition I. School of Pharmacy. University Complutense of Madrid. Spain.
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Corresponding author: Isabel Goñi, Research Professor. Departamento de Nutrición I. Facultad de Farmacia. Universidad Complutense de Madrid. Ciudad Universitaria s/n-28040-Madrid. Telephone:+34913941812 Email address: [email protected]
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Abbreviations: WHO: World Health Organization. MNA: Mini-Nutritional Assessment. EQ-5D: EuroQol-5D. VAS: Visual Analog Scale. BMI: Body Mass Index
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Place of work of the authors: Department of Nutrition I. School of Pharmacy. University Complutense of Madrid. Spain.
Shortened version of the title: Risk of malnutrition in the elderly over 75 years Keyword: Quality of life · Mini-Nutritional Assessment · Euroqol-5D · Aging · Health Status.
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Acknowledgements: The authors acknowledge the collaboration of honorable City Council of Garrucha, Almería, Spain. Financial Support: This work was supported by the Project GBR/14 University Complutense of Madrid, UCM-Santander 2014.
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Ethical standards disclosure statement: The study was conducted according to Declaration of Helsinki guidelines. All procedures were approved by the Ethics Review Board of the Complutense
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University in Madrid.
Conflict of interest: On behalf of all authors, the corresponding author that there is no conflict of interest. Authorship: A.H.-G was involved in fieldwork investigation and performed data determinations, analysed the results, and drafted and revised the manuscript. I.G. designed and conducted the study, and drafted and revised the manuscript.
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Introduction Populations worldwide are rapidly ageing, with major implications for health systems. According
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to the Spanish Statistical Office, life expectancy in Spain is the highest in Europe: 79.2 years for
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men and 85 years for women. It is estimated that by 2060, one third of Spaniards will be over 65
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[1]. In recent decades, reduced mortality rates at older ages have led to an increasing proportion
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living long enough to become centenarians [1].
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The positive side of living longer is evident, but it is also important to live for more years in good
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physical and mental health –that is, with good quality of life. Health-related quality of life is a
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multi-dimensional concept that includes domains related to physical, mental, emotional and social
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functioning [2]. Quality of life is therefore the result of a combination of personal resources, control
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of the environment, personal values and current living conditions [2].
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The aging process itself affects certain nutritional aspects such as sense perception (loss of taste
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and smell), ability to chew and swallow, impaired bowel function, decreased secretions and so on,
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which often alter the nutritional status of the elderly [3]. Inadequate food, poor social activities and
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physical inactivity can lead to an inability to perform everyday tasks, changes in quality of life,
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morbidity, and mortality [3]. This occurs in combination with the physiological changes inherent in
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the aging process, and increases the risk of nutritional problems that affect the quality of life. There
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is evidence of the influence of malnutrition on deteriorating physical and mental function, and the
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negative effect this has on the quality of life [3,4,5].
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There are relatively few studies linking nutritional status with quality of life in elderly autonomous
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non-institutionalised individuals [6], which –as noted above– is the group predicted to grow in
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coming years. The risk of malnutrition in these often apparently healthy individuals may go
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unnoticed [2,3].
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If the risk of malnutrition is not detected and treated early it can evolve into malnutrition, which is
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a serious pathological condition with very negative consequences for the health of older adults, not
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to mention the social and healthcare costs this situation entails [5]. The development of training
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programmes in nutrition education for the general population and for health professionals and
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carers, along with the use of instruments to detect nutritional risk in primary care centres, could be
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effective tools to reduce the prevalence of malnutrition, avoid its negative health consequences and
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improve the quality of life of elderly [7, 8].
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There is an evident need for routine monitoring of the overall health of the elderly population. We
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could hypothesise that healthy lifestyles are the environmental cause of increased life expectancy in
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the elderly.
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Strategies based on early detection of health problems through simple, reliable and fast
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instruments for measuring quality of life and well-being such as EuroQol-5D (EQ-5D) and Mini
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Nutritional Assessment (MNA) would encourage good health during aging and reduce social and
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healthcare consequences. EQ-5D, validated for use in Spanish population protocols, and MNA are
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instruments for detecting nutritional risk recommended for routine geriatric assessment by the
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European Society for Clinical Nutrition and Metabolism [9]. The aim of this work is therefore to evaluate the quality of life of an elderly home-dwelling
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population over 75, living independently, by determining nutritional and health status, and to
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investigate the relationship between nutritional risk and quality of life.
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Methods
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Study Design
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A pilot study, the Garrucha Old Age Health Study, was conducted in very old men and women
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living in Garrucha (8626 registered inhabitants), Almería (Spain), located on the Mediterranean
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coast. All non-institutionalised inhabitants aged 75 and over (n = 464) registered in the municipal
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census in 2014 were invited by letter to participate in the study, and the final sample comprised 102
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individuals aged over 75 (61 women and 41 men). Participants were divided into four age groups:
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75-79; 80-84; 85-89; ≥ 90.
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Data were collected by interview using comprehensive geriatric and nutritional assessment.
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Interviews were conducted by trained researchers. Informed written consent was obtained from all
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participants.
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The study was the result of a collaboration agreement between the University Complutense of
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Madrid and the Garrucha City Council, and it was conducted according to Declaration of Helsinki
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guidelines. All procedures were approved by the Ethics Review Board of the University
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Complutense of Madrid.
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Nutritional status
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The risk of malnutrition was assessed by the MNA tool [10], consisting of 18 sections, with
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questions on four aspects: overall evaluation, anthropometric assessment, dietary assessment and
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subjective assessment. The maximum score was 30 points. Three categories were identified based
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on the results: malnutrition, < 17; at risk of malnutrition, 17 to 23.5; and well nourished, > 24.
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Assessment of health-related quality of life
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This was determined using the EQ-5D [11,12], a standardised non-disease-specific instrument for
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describing and evaluating health-related quality of life. It consists of two parts: the EQ-5D
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descriptive system and the EQ-5D visual analogue scale (VAS). EQ-5D describes health status in 2
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terms of five dimensions: mobility, self-care, daily activities, pain or discomfort, and anxiety or
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depression. Each of these dimensions is divided into three levels of severity (no problems, some
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problems and extreme problems). These data are then converted to a single overall score (EQ-5D
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index) using a predefined table of values. The index ranges from a value of 1 (best state of health)
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and 0 (worst state of health). It is stratified into three categories: best health status, 0.5-1; regular
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health status, < 0.5; and poor health status, 0. The VAS is a scale marked 0-100 (zero represents the worst imaginable state of health, ≤ 40 poor,
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41-53, fair; 54-76, good; 77-80, very good; 81-90, excellent and 91-100, the best imaginable state).
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Other measurements
The baseline examination included specific questions about physical activity (time in minutes /
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day), educational level (none, primary studies, secondary studies, university studies), smoking (yes /
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no), and alcoholic habits daily (yes / no), use of medication (number of medication). History of
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illness was performed using the questionnaire of ENSE 2011-2012, [13].
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Statistical analysis
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A descriptive analysis was conducted on the frequencies, averages and percentages of the
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population segmented by sex and age groups. The results were stratified into categorical variables
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as the scoring criteria for each determination. The results for the categories were compared using
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contingency tables. Differences between categorical variables were analysed with the Chi-square
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Pearson test. The average score in each category in terms of sex and age was compared using
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analysis of variance (ANOVA). P values < 0.05 were considered statistically significant. V22 SPSS
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statistical software was used for data analysis and processing.
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Results
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Patient characteristics
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Table 1 shows the characteristics of the study population differentiated by gender. The mean age
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of subjects was 81.3 ± 4.6 years. Around 40.2% (n=41) of the population were men (mean age 81.1
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± 4.7) and 59.8% (n=61) women (mean age 81.4 ± 4.5).
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The mean BMI value was 27.5 ± 4.1. No difference between women and men was found.
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The population presented a mean of five diagnosed pathologies. Women had more pathologies
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than men. Almost 60% (n=60) of population consumed fewer than five drugs per day. Women
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consumed a greater number of medicines. It was noteworthy that only 2 subjects were smokers.
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Almost 25% (n=25) consumed alcohol usually. Most of population had secondary studies.
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Most of population practiced physical activity (73.5%, n=75). They had a moderate level of
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physical activity, with an average of over 50 minutes of activity a day, particularly walking, 3
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cycling, swimming, gymnastics and bodybuilding adapted to the elderly (Table 1). Notably more
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93% (n=95) of subjects had functional autonomy.
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Nutritional status Most of the population was well nourished according to the results of MNA (25.98 ± 3.4), (Table
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1). However, almost 21% (n=21) of the subjects were at risk of malnutrition and 2% (n=2) had
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malnutrition. Women generally showed more risk of malnutrition than men, although the
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differences were not statistically significant. However, significant differences by age were found.
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The group over-90 had the lowest average MNA score (21.5 ± 7.9), value corresponding with risk
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of malnutrition (Table 2). Although this group is very small and no clear conclusions can be drawn,
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it is significant that one of the three subjects was malnourished and the others two presented MNA
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values very close to the risk of malnutrition.
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Assessment of health-related quality of life
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The study population presented a good quality of life. The average EQ-5D index was 0.8 ± 0.3,
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close to the optimal quality of life. More than half the participants presented an index of ≥ 0.5.
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However, significant differences were found by age, (Table 2). The group over 90 years had the
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lowest average EQ-5D index (0.4 ± 0.3), denoting a regular health status (Table 2). The differences
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between men and women were not significant, although men showed a slightly higher EQ-5D. The mean VAS value was 76.2 ± 22.3, corresponding to very good state of health. Almost 42%
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(n=42) of the population rated their health as excellent or the best imaginable state of health. Only
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one of the subjects considered holding a worst health status and five judged their health status as
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poor. There were no significant differences due to age and sex, although men and the 80-84 age
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group obtained the lower mean VAS, values 75.5 and 71.8 respectively (Table 2).
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Relationship between risk of malnutrition and quality of life.
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Individuals who had better nutritional status also had a higher EQ-5D (p ≤ 0.001), coinciding with
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individuals who had a higher VAS score (p ≤ 0.05) (Table 3). The results were fairly consistent
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with the subjective assessment of state of health of participants. Only 6% of individuals who were
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at risk of malnutrition according to the MNA believed they had excellent or best health state when
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valued subjectively.
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The relationship between the three MNA categories and the five dimensions evaluated in the EQ-
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5D are shown in Table 4. A high significant correlation was found between MNA and all the
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dimensions evaluated in EQ-5D, except in the dimension assessing the state of anxiety and
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depression (Table 4). Malnourished individuals or those at risk of malnutrition also had problems
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with mobility, personal care, pain and discomfort, and daily activities (Table 4). 4
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Discussion
Early diagnosis of malnutrition and the evaluation of other factors associated with the aging
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process are the keys to avoiding a deterioration of health status and quality of life in this vulnerable
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population. Malnutrition is common in older people, and is associated with functional and cognitive
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impairment, which usually causes greater morbidity and reduced quality of life [4,14]. Quality of
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life is a multidimensional concept that includes some domains related with health status and life
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expectancy. Quality of life depends as much on physical as on psychological well-being, and both
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factors can be influenced by nutritional status [15]. Obviously, the nutritional status of elderly
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people plays an important role in protecting health, improving various aspects involved in quality of
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life and in slowing the ageing process for as long as possible [2].
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The low number of participants is an important limitation in this study. However, we must bear in
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mind that participants are the older elderly people, who have functional autonomy and they are
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living at home. It is not often find these characteristics in a study group [16].
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The study population presented a good quality of life, and also revealed an optimum nutritional
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status. The mean values of the EQ-5D index were higher than reported by other authors [17-19]. In
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contrast with other similar studies, we found no gender differences [17,18]. Most study participants (77.5%) were well nourished. However, some individuals (2%) presented
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malnutrition and 20.6% were at risk of malnutrition. The results were similar to those found in
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other studies in elderly over 75 years [6,15,20]. It is interesting to distinguish between risk of
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malnutrition and malnutrition because interventions required for each case are different. Nutritional
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risk is amenable to change and may reverse its course, while malnutrition is more likely to persist
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and have worse consequences [2]. A low MNA score has been found to be a strong predictor of
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long-term mortality in both free-living elderly and in those living in institutional care [21]. The
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results are widely heterogeneous and show very different figures for the prevalence of both
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malnutrition between 0 and 31.5% and risk of malnutrition between 4.5 and 57.5% [8]. It should be
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noted that in many of the nutritional studies referenced the functional characteristics of participants
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are not specified, and these can strongly determine the results of the nutritional status assessment.
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There is increasing evidence in the literature that nutritional status is closely related to functional
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status in older adults. Since a high level of functional status implies independence and quality of life
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[22], it is of crucial importance for this population to maintain their functionality in an optimal state
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of health.
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Disability in daily activities was shown to be associated with low BMI [23] and malnutrition
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according to the MNA. However, a high BMI could be a risk factor for decreased functionality, and
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is often accompanied by greater mobility-related disability, higher mortality and a poorer quality of 5
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life [3]. Other authors have shown that a higher BMI is associated with lower risk of malnutrition
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[20]. In this work, the mean BMI was 27.5 kg/m2. The interpretation of these numbers may lead to
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confusion. This BMI value corresponds to grade II overweight according to the WHO assessment
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scale. However, some authors presented similar values for people aged 60-69 and even BMI: 28.2
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for over 70s, who were not considered overweight. Similarly, the Australia and New Zealand
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Society for Geriatric Medicine (2011) developed a BMI classification based on the association
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between BMI and risk of chronic disease and mortality in healthy populations, and concluded that
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in practice, it may be appropriate to adjust the BMI classification for people aged > 65 to:
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underweight < 23 Kg/m2; healthy weight 24 – 30 Kg/m2; and overweight > 30 Kg/m2. In support of
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this information it should be noted that both low and high BMI values have been associated with
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increased mortality, suggesting that the most beneficial BMI value was 25-29.9 for older
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individuals [24]. However, after age 70, the association between high BMI values and mortality
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appears to weaken, while the association between low values and mortality persists. This changing
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pattern also seems to become more pronounced with increasing age in men compared with women
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[25]. A relationship between BMI and quality of life has been established by EQ-5D, with the
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highest score in the BMI category of 25-27 Kg/m2 [26]. Most of results from this study were in this
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range, so the participants cannot be said to be overweight; the mean BMI value did not differ
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between women and men (Table 1).
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Most of the population presented five or less than five pathologies, and women had a higher
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number of pathologies than men (Table 1). These results were similar to those of a study in a
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population with features similar to the one in this present research [15]. Polypharmacy is a risk
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factor for malnutrition according to several studies in the elderly [14], possibly due to the alterations
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in appetite or taste produced by certain drugs, or to drug interactions with food. If polypharmacy is
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considered to denote the consumption of more than five drugs, many of the participants in this study
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population were polymedicated. The results of other studies regarding the use of drugs are
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heterogeneous [14,17]. Notably, women took a greater number of drugs than men, this result is
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similar to the results findings of other studies [3,17,19].
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On the other hand, smoking is one of the lifestyle risk factors associated with loss of autonomy in elderly individuals living independently [3]. In this study only 2 subjects were smoking, Table 1.
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The aging process also implies an increase in the prevalence of cognitive deterioration and its
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impact on independence levels and quality of life. This deterioration may affect daily activities and
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result in a state of malnutrition that especially aggravates the ageing process and leads to a poorer
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quality of life in the elderly population.
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Most participants presented a best health status, assessed both by EQ-5D and VAS of each
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individual (Table 3). The VAS score in our study (76.3 ± 22.1) was 15 points higher than the values
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reported in other similar studies [17-19, 27]. It should be mentioned that the European Study of the Epidemiology of Mental Disorders [19]
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assessed representative population samples in six European countries, including Spain. They
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evaluated health status using the EQ-5D, and the results for the Spanish population were similar to
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those found in this work. 35.1% of European participants had problems in one or more of the
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dimensions evaluated in EQ-5D. The mean VAS score in the European Study of the Epidemiology
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of Mental Disorders was 77.1, ranging from 75.0 in Spain to 82.0 in the Netherlands. After
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adjusting for socio-demographic variables, the proportion of respondents reporting problems in any
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of the EQ-5D dimensions was significantly higher than the total mean in France, and lower in Spain
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and Italy.
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Over 50% of the subjects in our study showed a very good, excellent or best health state assessed
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by VAS (Table 3) and they had no problems in any of the five dimensions of the EQ-5D test (Table
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4). The problems detected in the evaluated dimensions and the severity levels were similar to those
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referenced by other authors [18], being the pain and discomfort the most frequently detected
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problems.
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The elderly comprise the most heterogeneous population group. It is therefore very important to
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identify individuals who either suffer from malnutrition or are at risk of malnutrition. This type of
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study must take into account not only the traditional risk factors directly related to food
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consumption, but also other functional impairments associated with aging such as greater cognitive
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impairment [3,14,28,29], depressive symptoms, greater dependence for basic and instrumental daily
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activities [24,25,28,29], a disadvantaged social situation [14,20], a large number of diseases [20],
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increased mortality [20], and low self-rated health [17,20], are strongly associated with the nutrient
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intake and nutritional status of subjects [15]. The results of this study support this association
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(Table 3). Similar results were found by other authors [4,14,18,30]. However, other authors indicate
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these variables were not related [31].
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Conclusion
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Be at risk of malnutrition was common among community-dwelling older people. Participants
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who were malnourished or were at high risk of malnutrition also had a lower rate of quality of life
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and greater loss of personal autonomy.
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Intervention studies on nutritional status in older adults comprise an important line of research that
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should be encouraged, since small well-targeted changes could bring significant improvements in
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health of the elderly. 7
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298 24. Soderstrom L, Rosenblad A, Adolfsson ET, Saletti A, Bergkvist L. Nutritional status predicts 299
preterm death in older people: A prospective cohort study. Clin Nutr 2014; 33(2); 354-9.
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300 25. Cuervo M, García A, Ansorena D, Sánchez-Villegas A, Martínez-González M, Astiasarán I, et al. 301
Nutritional assessment interpretation on 22.007 Spanish community-dwelling elders through the
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Mini Nutritional Assessment test. Public Health Nutr 2008; 12(1); 82-90.
303 26. Tsai AC, Chang TL, Yang TW, Chang-Lee SN, Tsay SF. A modified mini nutritional assessment 304
without BMI predicts nutritional status of community-living elderly in Taiwan. J Nutr Health
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Aging 2010; 14(3); 183-9.
307
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306 27. Badia X, Roset M, Herdman M, Kind P. A comparison of United Kingdom and Spanish general population time trade-off values for EQ-5D health states. Med Decis Making 2001; 21; 7-16.
308 28. Vaca-Bermejo R, Ancizu-García I, Moya-Galera D, de las Heras-Rodríguez M, PascualTorramadé P. Prevalencia de desnutrición en personas mayores institucionalizadas en España: un
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análisis multicéntrico nacional. Nutr Hosp 2015; 31(3); 1205-16.
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311 29. Granado de la Orden S, Serrano-Zarceño C, Belmonte-Cortés S. Quality of life, dependency and mental health scales of interest to nutritional studies in the population. Nutr Hosp 2015; 31(3);
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265-71.
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314 30. Doumit J, Nasser R. Quality of life and wellbeing of the elderly in Lebanese nursing homes. Int J 315
Health Care Qual Assur 2010; 23(1); 72-93.
316 31. Hickson M, Frost G. An investigation into the relationships between quality of life, nutritional
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status and physical function. Clin Nutr 2004; 23(2); 213-21.
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Table 1 Characteristics of study population Women n=61
Men n=41
p-valuea
81.4±4.5
81.1±4.7
0.684
25.9±3.3
26.1±3.6
0.807
0.7±0.3
0.8±0.3
0.115
76.2±22.3
76.7±22.1
75.5±22.9
0.788
27.5±4.1
27.4±4.6
27.8±3.3
0.614
5.1±3.9
5.25±4.1
4.7±3.7
0.480
51.1±55.4
39.4±50.6
68.5±58.2
0.008
14(13.7) 18(17.6) 45(44.1) 25(24.5)
8(7.8) 7(6.9) 18(17.6) 8(7.8)
6(5.9) 11(10.8) 27(26.5) 17(16.6)
0.496
42(41.2)
23(22.6)
19(18.6)
25(24.5)
10(9.8)
15(14.6)
81.3±4.6
Nutritional status (MNAb) , mean±SD
25.9±3.4
Quality of life (EQ-5Db), mean±SD
0.8±0.3
Body Mass Index (BMI) (Kg/m2), mean±SD Number of Diseases, mean±SD
Alcohol consumption, n(%)
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Polipharmacy (>5 medications), n(%)
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Educational level, n(%) None Primary studies Secundary studies University studies
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Physical Activity (min/person/day), mean±SD
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VAS b, mean±SD
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Age (years), mean±SD
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Total n=102
0.020
Tobacco consumption, n(%) 2(2) 2(2) 0 0.020 ANOVA and Chi-square Pearson test, p ≤ 0.05 corresponds to significant differences between women and men. b MNA, Mini Nutritional Assessment; EQ-5D Index of social values of Euroqol-5Dimensions, VAS, Visual Analogue Scale. a
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Table 2 Nutritional status and quality of life of a population over 75 year non-institutionalizeda Women Men 75-79 80-84 n=61 n=41 p-value n=40 n=32
p-value
0.807c 26.8±2.9 0.918d 0 7(6.9) 33(32.4)
25.5±3.2 0 10(9.8) 22(21.6)
25.7±3.3 1(1) 4(3.9) 22(21.6)
21.5±7.9 1(1) 0 2(2)
0.033c 0.002d
Worst health status Regular health status Best health status
0.7±0.3 1(1) 13(12.7) 47(46.1)
0.8±0.3 0 6(5.9) 35(34.3)
0.115c 0.480d
0.7±0.3 0 7(6.9) 25(24.5)
0.7±0.3 1(1) 8(7.8) 18(17.6)
0.4±0.3 0 1(1) 2(2)
0.001c 0.006d
76.3±22.1 0 4(3.9) 11(10.8) 10(9.8) 5(4.9) 10(9.8) 18(17.6)
75.5±22.9 1(1) 1(1) 7(6.9) 7(6.9) 11(10.8) 3(3) 11(10.8)
78.8±19.4 0 1(1) 3(3) 5(5.1) 6(6.1) 3(3) 7(7.1)
73.3±25.2 0 0 1(1) 1(1) 0 0 1(1)
0.591c 0.961d
Worst health status Poor Fair Good Very good Excellent Best health status
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VASb
0.9±0.2 0(0) 3(2.9) 37(36.3)
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Malnutrition Risk of malnutrition Well nourished
26.1±3.6 1(1) 9(8.8) 31(30.4)
EQ-5Db
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≥90 n=3
25.9±3.3 1(1) 12(11.8) 48(47.1)
0.788c 78.3±21.4 0.158d 0 2(2) 6(6.1) 6(6.1) 7(7.1) 7(7.1) 12(12.1)
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MNAb
85-89 n=27
71.8±25.6 1(1) 2(2) 8(8.1) 5(5.1) 3(3) 3(3) 9(9.1)
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Results were expressed as mean ± standard deviation and number and percentage respect to total population, n(%). MNA, Mini Nutritional Assessment; EQ-5D, Index of social values of Euroqol-5Dimensions; VAS, Visual Analog Scale. c ANOVA, p ≤ 0.05 were considered to be statistically significant. d Chi-square Pearson test, p ≤ 0.05 were considered to be statistically significant. b
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Worst health state Poor Fair Good
1(1)
0
2(2) 0
8(7.8) 12(11.8)
9(8.8) 70(68 .6)
0 0
1(1) 1(1)
1(1)
6(6.1)
0
4(4)
0
1(1)
0
3(3)
0 4(4) 11(11 .1) 13(13 .1) 15(15 .2) 10(10 .1) 26(26 .3)
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Very good Excellent
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Best health state
a
21(20.6)
n(%) 79(7 7.5)
0
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VAS (p<0.05)
Worst health state Regular health state Best health state
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2(2) EQ-5D (p<0.001)
n(%)
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n(%)
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Risk of Malnutrition malnutrition MNA<17 MNA, 17-23.5
Well nouri shed MN A>2 4
0 3(3) Chi-square of Pearson test, p ≤ 0.05 significant correlation.
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11(10.8) 7(6.9) 2(2)
No problems Some problems Dependent
0 0 2(2)
Personal Care (p < 0.001)
No problems Some problems Dependent
0 0 2(2)
Daily Activities (p < 0.001)
No problems Some problems Dependent
Pain/Discomfort (p < 0.05)
Absence Moderate High
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Mobility (p < 0.001)
Well nourished MNA>24
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Malnutrition MNA<17 n(%)
Risk of malnutrition MNA,17-23.5 n(%)
n(%)
57(55.9) 22(21.6) 0
68(66.7) 10(9.8) 1(1)
0 0 2(2)
11(10.8) 3(2.9) 6(5.9)
66(64.7) 12(11.8) 1(1)
1(1) 0 1(1)
12(11.8) 8(7.8) 0
48(47.1) 25(24.5) 6(5.9)
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11(10.8) 7(6.9) 2(2)
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Anxiety/Depression Absence 1(1) 13(12.7) 66(64.7) (p > 0.05) Moderate 0 5(4.9) 11(10.8) High 1(1) 2(2) a Chi-square of Pearson test, values p ≤ 0.05 were considered to be statistically significant.
ACCEPTED MANUSCRIPT Highlights - Results show the important role of nutrition and eating habits in the quality of life of elderly - Almost 21% of the collective were at risk of malnutrition, especially women and over 90y - A significant negative association between risk of malnutrition and quality of life was found
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- Contribution to improve knowledge in nutrition and aging process
S0899-9007(16)30236-2
DOI:
10.1016/j.nut.2016.10.013
Reference:
NUT 9864
To appear in:
Nutrition
Received Date: 19 April 2016 Revised Date:
10 October 2016
Accepted Date: 19 October 2016
Please cite this article as: Hernández-Galiot A, Goñi I, Quality of life and risk of malnutrition in a homedwelling population over75, Nutrition (2016), doi: 10.1016/j.nut.2016.10.013. 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.
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TITLE: Quality of life and risk of malnutrition in a home-dwelling population over75. Authors: Ana Hernández-Galiot 1, Isabel Goñi 1,2
1
Department of Nutrition I. School of Pharmacy. University Complutense of Madrid. Spain.
2
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Corresponding author: Isabel Goñi, Research Professor. Departamento de Nutrición I. Facultad de Farmacia. Universidad Complutense de Madrid. Ciudad Universitaria s/n-28040-Madrid. Telephone:+34913941812 Email address: [email protected]
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Abbreviations: WHO: World Health Organization. MNA: Mini-Nutritional Assessment. EQ-5D: EuroQol-5D. VAS: Visual Analog Scale. BMI: Body Mass Index
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Place of work of the authors: Department of Nutrition I. School of Pharmacy. University Complutense of Madrid. Spain.
Shortened version of the title: Risk of malnutrition in the elderly over 75 years Keyword: Quality of life · Mini-Nutritional Assessment · Euroqol-5D · Aging · Health Status.
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Acknowledgements: The authors acknowledge the collaboration of honorable City Council of Garrucha, Almería, Spain. Financial Support: This work was supported by the Project GBR/14 University Complutense of Madrid, UCM-Santander 2014.
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Ethical standards disclosure statement: The study was conducted according to Declaration of Helsinki guidelines. All procedures were approved by the Ethics Review Board of the Complutense
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University in Madrid.
Conflict of interest: On behalf of all authors, the corresponding author that there is no conflict of interest. Authorship: A.H.-G was involved in fieldwork investigation and performed data determinations, analysed the results, and drafted and revised the manuscript. I.G. designed and conducted the study, and drafted and revised the manuscript.
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Introduction Populations worldwide are rapidly ageing, with major implications for health systems. According
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to the Spanish Statistical Office, life expectancy in Spain is the highest in Europe: 79.2 years for
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men and 85 years for women. It is estimated that by 2060, one third of Spaniards will be over 65
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[1]. In recent decades, reduced mortality rates at older ages have led to an increasing proportion
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living long enough to become centenarians [1].
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The positive side of living longer is evident, but it is also important to live for more years in good
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physical and mental health –that is, with good quality of life. Health-related quality of life is a
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multi-dimensional concept that includes domains related to physical, mental, emotional and social
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functioning [2]. Quality of life is therefore the result of a combination of personal resources, control
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of the environment, personal values and current living conditions [2].
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The aging process itself affects certain nutritional aspects such as sense perception (loss of taste
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and smell), ability to chew and swallow, impaired bowel function, decreased secretions and so on,
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which often alter the nutritional status of the elderly [3]. Inadequate food, poor social activities and
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physical inactivity can lead to an inability to perform everyday tasks, changes in quality of life,
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morbidity, and mortality [3]. This occurs in combination with the physiological changes inherent in
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the aging process, and increases the risk of nutritional problems that affect the quality of life. There
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is evidence of the influence of malnutrition on deteriorating physical and mental function, and the
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negative effect this has on the quality of life [3,4,5].
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There are relatively few studies linking nutritional status with quality of life in elderly autonomous
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non-institutionalised individuals [6], which –as noted above– is the group predicted to grow in
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coming years. The risk of malnutrition in these often apparently healthy individuals may go
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unnoticed [2,3].
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If the risk of malnutrition is not detected and treated early it can evolve into malnutrition, which is
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a serious pathological condition with very negative consequences for the health of older adults, not
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to mention the social and healthcare costs this situation entails [5]. The development of training
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programmes in nutrition education for the general population and for health professionals and
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carers, along with the use of instruments to detect nutritional risk in primary care centres, could be
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effective tools to reduce the prevalence of malnutrition, avoid its negative health consequences and
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improve the quality of life of elderly [7, 8].
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There is an evident need for routine monitoring of the overall health of the elderly population. We
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could hypothesise that healthy lifestyles are the environmental cause of increased life expectancy in
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the elderly.
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Strategies based on early detection of health problems through simple, reliable and fast
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instruments for measuring quality of life and well-being such as EuroQol-5D (EQ-5D) and Mini
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Nutritional Assessment (MNA) would encourage good health during aging and reduce social and
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healthcare consequences. EQ-5D, validated for use in Spanish population protocols, and MNA are
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instruments for detecting nutritional risk recommended for routine geriatric assessment by the
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European Society for Clinical Nutrition and Metabolism [9]. The aim of this work is therefore to evaluate the quality of life of an elderly home-dwelling
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population over 75, living independently, by determining nutritional and health status, and to
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investigate the relationship between nutritional risk and quality of life.
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Methods
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Study Design
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A pilot study, the Garrucha Old Age Health Study, was conducted in very old men and women
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living in Garrucha (8626 registered inhabitants), Almería (Spain), located on the Mediterranean
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coast. All non-institutionalised inhabitants aged 75 and over (n = 464) registered in the municipal
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census in 2014 were invited by letter to participate in the study, and the final sample comprised 102
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individuals aged over 75 (61 women and 41 men). Participants were divided into four age groups:
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75-79; 80-84; 85-89; ≥ 90.
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Data were collected by interview using comprehensive geriatric and nutritional assessment.
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Interviews were conducted by trained researchers. Informed written consent was obtained from all
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participants.
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The study was the result of a collaboration agreement between the University Complutense of
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Madrid and the Garrucha City Council, and it was conducted according to Declaration of Helsinki
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guidelines. All procedures were approved by the Ethics Review Board of the University
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Complutense of Madrid.
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Nutritional status
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The risk of malnutrition was assessed by the MNA tool [10], consisting of 18 sections, with
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questions on four aspects: overall evaluation, anthropometric assessment, dietary assessment and
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subjective assessment. The maximum score was 30 points. Three categories were identified based
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on the results: malnutrition, < 17; at risk of malnutrition, 17 to 23.5; and well nourished, > 24.
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Assessment of health-related quality of life
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This was determined using the EQ-5D [11,12], a standardised non-disease-specific instrument for
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describing and evaluating health-related quality of life. It consists of two parts: the EQ-5D
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descriptive system and the EQ-5D visual analogue scale (VAS). EQ-5D describes health status in 2
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terms of five dimensions: mobility, self-care, daily activities, pain or discomfort, and anxiety or
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depression. Each of these dimensions is divided into three levels of severity (no problems, some
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problems and extreme problems). These data are then converted to a single overall score (EQ-5D
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index) using a predefined table of values. The index ranges from a value of 1 (best state of health)
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and 0 (worst state of health). It is stratified into three categories: best health status, 0.5-1; regular
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health status, < 0.5; and poor health status, 0. The VAS is a scale marked 0-100 (zero represents the worst imaginable state of health, ≤ 40 poor,
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41-53, fair; 54-76, good; 77-80, very good; 81-90, excellent and 91-100, the best imaginable state).
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Other measurements
The baseline examination included specific questions about physical activity (time in minutes /
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day), educational level (none, primary studies, secondary studies, university studies), smoking (yes /
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no), and alcoholic habits daily (yes / no), use of medication (number of medication). History of
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illness was performed using the questionnaire of ENSE 2011-2012, [13].
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Statistical analysis
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A descriptive analysis was conducted on the frequencies, averages and percentages of the
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population segmented by sex and age groups. The results were stratified into categorical variables
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as the scoring criteria for each determination. The results for the categories were compared using
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contingency tables. Differences between categorical variables were analysed with the Chi-square
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Pearson test. The average score in each category in terms of sex and age was compared using
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analysis of variance (ANOVA). P values < 0.05 were considered statistically significant. V22 SPSS
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statistical software was used for data analysis and processing.
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Results
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Patient characteristics
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Table 1 shows the characteristics of the study population differentiated by gender. The mean age
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of subjects was 81.3 ± 4.6 years. Around 40.2% (n=41) of the population were men (mean age 81.1
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± 4.7) and 59.8% (n=61) women (mean age 81.4 ± 4.5).
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The mean BMI value was 27.5 ± 4.1. No difference between women and men was found.
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The population presented a mean of five diagnosed pathologies. Women had more pathologies
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than men. Almost 60% (n=60) of population consumed fewer than five drugs per day. Women
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consumed a greater number of medicines. It was noteworthy that only 2 subjects were smokers.
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Almost 25% (n=25) consumed alcohol usually. Most of population had secondary studies.
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Most of population practiced physical activity (73.5%, n=75). They had a moderate level of
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physical activity, with an average of over 50 minutes of activity a day, particularly walking, 3
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cycling, swimming, gymnastics and bodybuilding adapted to the elderly (Table 1). Notably more
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93% (n=95) of subjects had functional autonomy.
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Nutritional status Most of the population was well nourished according to the results of MNA (25.98 ± 3.4), (Table
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1). However, almost 21% (n=21) of the subjects were at risk of malnutrition and 2% (n=2) had
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malnutrition. Women generally showed more risk of malnutrition than men, although the
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differences were not statistically significant. However, significant differences by age were found.
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The group over-90 had the lowest average MNA score (21.5 ± 7.9), value corresponding with risk
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of malnutrition (Table 2). Although this group is very small and no clear conclusions can be drawn,
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it is significant that one of the three subjects was malnourished and the others two presented MNA
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values very close to the risk of malnutrition.
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Assessment of health-related quality of life
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The study population presented a good quality of life. The average EQ-5D index was 0.8 ± 0.3,
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close to the optimal quality of life. More than half the participants presented an index of ≥ 0.5.
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However, significant differences were found by age, (Table 2). The group over 90 years had the
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lowest average EQ-5D index (0.4 ± 0.3), denoting a regular health status (Table 2). The differences
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between men and women were not significant, although men showed a slightly higher EQ-5D. The mean VAS value was 76.2 ± 22.3, corresponding to very good state of health. Almost 42%
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(n=42) of the population rated their health as excellent or the best imaginable state of health. Only
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one of the subjects considered holding a worst health status and five judged their health status as
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poor. There were no significant differences due to age and sex, although men and the 80-84 age
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group obtained the lower mean VAS, values 75.5 and 71.8 respectively (Table 2).
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Relationship between risk of malnutrition and quality of life.
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Individuals who had better nutritional status also had a higher EQ-5D (p ≤ 0.001), coinciding with
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individuals who had a higher VAS score (p ≤ 0.05) (Table 3). The results were fairly consistent
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with the subjective assessment of state of health of participants. Only 6% of individuals who were
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at risk of malnutrition according to the MNA believed they had excellent or best health state when
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valued subjectively.
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The relationship between the three MNA categories and the five dimensions evaluated in the EQ-
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5D are shown in Table 4. A high significant correlation was found between MNA and all the
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dimensions evaluated in EQ-5D, except in the dimension assessing the state of anxiety and
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depression (Table 4). Malnourished individuals or those at risk of malnutrition also had problems
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with mobility, personal care, pain and discomfort, and daily activities (Table 4). 4
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Discussion
Early diagnosis of malnutrition and the evaluation of other factors associated with the aging
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process are the keys to avoiding a deterioration of health status and quality of life in this vulnerable
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population. Malnutrition is common in older people, and is associated with functional and cognitive
137
impairment, which usually causes greater morbidity and reduced quality of life [4,14]. Quality of
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life is a multidimensional concept that includes some domains related with health status and life
139
expectancy. Quality of life depends as much on physical as on psychological well-being, and both
140
factors can be influenced by nutritional status [15]. Obviously, the nutritional status of elderly
141
people plays an important role in protecting health, improving various aspects involved in quality of
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life and in slowing the ageing process for as long as possible [2].
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The low number of participants is an important limitation in this study. However, we must bear in
144
mind that participants are the older elderly people, who have functional autonomy and they are
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living at home. It is not often find these characteristics in a study group [16].
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The study population presented a good quality of life, and also revealed an optimum nutritional
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status. The mean values of the EQ-5D index were higher than reported by other authors [17-19]. In
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contrast with other similar studies, we found no gender differences [17,18]. Most study participants (77.5%) were well nourished. However, some individuals (2%) presented
150
malnutrition and 20.6% were at risk of malnutrition. The results were similar to those found in
151
other studies in elderly over 75 years [6,15,20]. It is interesting to distinguish between risk of
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malnutrition and malnutrition because interventions required for each case are different. Nutritional
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risk is amenable to change and may reverse its course, while malnutrition is more likely to persist
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and have worse consequences [2]. A low MNA score has been found to be a strong predictor of
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long-term mortality in both free-living elderly and in those living in institutional care [21]. The
156
results are widely heterogeneous and show very different figures for the prevalence of both
157
malnutrition between 0 and 31.5% and risk of malnutrition between 4.5 and 57.5% [8]. It should be
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noted that in many of the nutritional studies referenced the functional characteristics of participants
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are not specified, and these can strongly determine the results of the nutritional status assessment.
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There is increasing evidence in the literature that nutritional status is closely related to functional
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status in older adults. Since a high level of functional status implies independence and quality of life
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[22], it is of crucial importance for this population to maintain their functionality in an optimal state
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of health.
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Disability in daily activities was shown to be associated with low BMI [23] and malnutrition
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according to the MNA. However, a high BMI could be a risk factor for decreased functionality, and
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is often accompanied by greater mobility-related disability, higher mortality and a poorer quality of 5
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life [3]. Other authors have shown that a higher BMI is associated with lower risk of malnutrition
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[20]. In this work, the mean BMI was 27.5 kg/m2. The interpretation of these numbers may lead to
169
confusion. This BMI value corresponds to grade II overweight according to the WHO assessment
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scale. However, some authors presented similar values for people aged 60-69 and even BMI: 28.2
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for over 70s, who were not considered overweight. Similarly, the Australia and New Zealand
172
Society for Geriatric Medicine (2011) developed a BMI classification based on the association
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between BMI and risk of chronic disease and mortality in healthy populations, and concluded that
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in practice, it may be appropriate to adjust the BMI classification for people aged > 65 to:
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underweight < 23 Kg/m2; healthy weight 24 – 30 Kg/m2; and overweight > 30 Kg/m2. In support of
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this information it should be noted that both low and high BMI values have been associated with
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increased mortality, suggesting that the most beneficial BMI value was 25-29.9 for older
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individuals [24]. However, after age 70, the association between high BMI values and mortality
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appears to weaken, while the association between low values and mortality persists. This changing
180
pattern also seems to become more pronounced with increasing age in men compared with women
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[25]. A relationship between BMI and quality of life has been established by EQ-5D, with the
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highest score in the BMI category of 25-27 Kg/m2 [26]. Most of results from this study were in this
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range, so the participants cannot be said to be overweight; the mean BMI value did not differ
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between women and men (Table 1).
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Most of the population presented five or less than five pathologies, and women had a higher
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number of pathologies than men (Table 1). These results were similar to those of a study in a
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population with features similar to the one in this present research [15]. Polypharmacy is a risk
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factor for malnutrition according to several studies in the elderly [14], possibly due to the alterations
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in appetite or taste produced by certain drugs, or to drug interactions with food. If polypharmacy is
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considered to denote the consumption of more than five drugs, many of the participants in this study
191
population were polymedicated. The results of other studies regarding the use of drugs are
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heterogeneous [14,17]. Notably, women took a greater number of drugs than men, this result is
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similar to the results findings of other studies [3,17,19].
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On the other hand, smoking is one of the lifestyle risk factors associated with loss of autonomy in elderly individuals living independently [3]. In this study only 2 subjects were smoking, Table 1.
196
The aging process also implies an increase in the prevalence of cognitive deterioration and its
197
impact on independence levels and quality of life. This deterioration may affect daily activities and
198
result in a state of malnutrition that especially aggravates the ageing process and leads to a poorer
199
quality of life in the elderly population.
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Most participants presented a best health status, assessed both by EQ-5D and VAS of each
201
individual (Table 3). The VAS score in our study (76.3 ± 22.1) was 15 points higher than the values
202
reported in other similar studies [17-19, 27]. It should be mentioned that the European Study of the Epidemiology of Mental Disorders [19]
204
assessed representative population samples in six European countries, including Spain. They
205
evaluated health status using the EQ-5D, and the results for the Spanish population were similar to
206
those found in this work. 35.1% of European participants had problems in one or more of the
207
dimensions evaluated in EQ-5D. The mean VAS score in the European Study of the Epidemiology
208
of Mental Disorders was 77.1, ranging from 75.0 in Spain to 82.0 in the Netherlands. After
209
adjusting for socio-demographic variables, the proportion of respondents reporting problems in any
210
of the EQ-5D dimensions was significantly higher than the total mean in France, and lower in Spain
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and Italy.
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Over 50% of the subjects in our study showed a very good, excellent or best health state assessed
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by VAS (Table 3) and they had no problems in any of the five dimensions of the EQ-5D test (Table
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4). The problems detected in the evaluated dimensions and the severity levels were similar to those
215
referenced by other authors [18], being the pain and discomfort the most frequently detected
216
problems.
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The elderly comprise the most heterogeneous population group. It is therefore very important to
218
identify individuals who either suffer from malnutrition or are at risk of malnutrition. This type of
219
study must take into account not only the traditional risk factors directly related to food
220
consumption, but also other functional impairments associated with aging such as greater cognitive
221
impairment [3,14,28,29], depressive symptoms, greater dependence for basic and instrumental daily
222
activities [24,25,28,29], a disadvantaged social situation [14,20], a large number of diseases [20],
223
increased mortality [20], and low self-rated health [17,20], are strongly associated with the nutrient
224
intake and nutritional status of subjects [15]. The results of this study support this association
225
(Table 3). Similar results were found by other authors [4,14,18,30]. However, other authors indicate
226
these variables were not related [31].
227
Conclusion
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Be at risk of malnutrition was common among community-dwelling older people. Participants
229
who were malnourished or were at high risk of malnutrition also had a lower rate of quality of life
230
and greater loss of personal autonomy.
231
Intervention studies on nutritional status in older adults comprise an important line of research that
232
should be encouraged, since small well-targeted changes could bring significant improvements in
233
health of the elderly. 7
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Table 1 Characteristics of study population Women n=61
Men n=41
p-valuea
81.4±4.5
81.1±4.7
0.684
25.9±3.3
26.1±3.6
0.807
0.7±0.3
0.8±0.3
0.115
76.2±22.3
76.7±22.1
75.5±22.9
0.788
27.5±4.1
27.4±4.6
27.8±3.3
0.614
5.1±3.9
5.25±4.1
4.7±3.7
0.480
51.1±55.4
39.4±50.6
68.5±58.2
0.008
14(13.7) 18(17.6) 45(44.1) 25(24.5)
8(7.8) 7(6.9) 18(17.6) 8(7.8)
6(5.9) 11(10.8) 27(26.5) 17(16.6)
0.496
42(41.2)
23(22.6)
19(18.6)
25(24.5)
10(9.8)
15(14.6)
81.3±4.6
Nutritional status (MNAb) , mean±SD
25.9±3.4
Quality of life (EQ-5Db), mean±SD
0.8±0.3
Body Mass Index (BMI) (Kg/m2), mean±SD Number of Diseases, mean±SD
Alcohol consumption, n(%)
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Polipharmacy (>5 medications), n(%)
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Educational level, n(%) None Primary studies Secundary studies University studies
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Physical Activity (min/person/day), mean±SD
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VAS b, mean±SD
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Age (years), mean±SD
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Total n=102
0.020
Tobacco consumption, n(%) 2(2) 2(2) 0 0.020 ANOVA and Chi-square Pearson test, p ≤ 0.05 corresponds to significant differences between women and men. b MNA, Mini Nutritional Assessment; EQ-5D Index of social values of Euroqol-5Dimensions, VAS, Visual Analogue Scale. a
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Table 2 Nutritional status and quality of life of a population over 75 year non-institutionalizeda Women Men 75-79 80-84 n=61 n=41 p-value n=40 n=32
p-value
0.807c 26.8±2.9 0.918d 0 7(6.9) 33(32.4)
25.5±3.2 0 10(9.8) 22(21.6)
25.7±3.3 1(1) 4(3.9) 22(21.6)
21.5±7.9 1(1) 0 2(2)
0.033c 0.002d
Worst health status Regular health status Best health status
0.7±0.3 1(1) 13(12.7) 47(46.1)
0.8±0.3 0 6(5.9) 35(34.3)
0.115c 0.480d
0.7±0.3 0 7(6.9) 25(24.5)
0.7±0.3 1(1) 8(7.8) 18(17.6)
0.4±0.3 0 1(1) 2(2)
0.001c 0.006d
76.3±22.1 0 4(3.9) 11(10.8) 10(9.8) 5(4.9) 10(9.8) 18(17.6)
75.5±22.9 1(1) 1(1) 7(6.9) 7(6.9) 11(10.8) 3(3) 11(10.8)
78.8±19.4 0 1(1) 3(3) 5(5.1) 6(6.1) 3(3) 7(7.1)
73.3±25.2 0 0 1(1) 1(1) 0 0 1(1)
0.591c 0.961d
Worst health status Poor Fair Good Very good Excellent Best health status
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VASb
0.9±0.2 0(0) 3(2.9) 37(36.3)
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Malnutrition Risk of malnutrition Well nourished
26.1±3.6 1(1) 9(8.8) 31(30.4)
EQ-5Db
a
≥90 n=3
25.9±3.3 1(1) 12(11.8) 48(47.1)
0.788c 78.3±21.4 0.158d 0 2(2) 6(6.1) 6(6.1) 7(7.1) 7(7.1) 12(12.1)
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MNAb
85-89 n=27
71.8±25.6 1(1) 2(2) 8(8.1) 5(5.1) 3(3) 3(3) 9(9.1)
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Results were expressed as mean ± standard deviation and number and percentage respect to total population, n(%). MNA, Mini Nutritional Assessment; EQ-5D, Index of social values of Euroqol-5Dimensions; VAS, Visual Analog Scale. c ANOVA, p ≤ 0.05 were considered to be statistically significant. d Chi-square Pearson test, p ≤ 0.05 were considered to be statistically significant. b
ACCEPTED MANUSCRIPT Table 3 Statistical relationship between the results of the Mini Nutritional Assessment (MNA) and Euroqol-5D Index (EQ-5D) and Visual Analog Scale (VAS) a MNA category
Worst health state Poor Fair Good
1(1)
0
2(2) 0
8(7.8) 12(11.8)
9(8.8) 70(68 .6)
0 0
1(1) 1(1)
1(1)
6(6.1)
0
4(4)
0
1(1)
0
3(3)
0 4(4) 11(11 .1) 13(13 .1) 15(15 .2) 10(10 .1) 26(26 .3)
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Very good Excellent
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Best health state
a
21(20.6)
n(%) 79(7 7.5)
0
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VAS (p<0.05)
Worst health state Regular health state Best health state
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2(2) EQ-5D (p<0.001)
n(%)
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n(%)
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Risk of Malnutrition malnutrition MNA<17 MNA, 17-23.5
Well nouri shed MN A>2 4
0 3(3) Chi-square of Pearson test, p ≤ 0.05 significant correlation.
ACCEPTED MANUSCRIPT Table 4 Dimensions distribution assessment in the Euroqol-5D, according to the category of Mini Nutritional Assessment (MNA) MNA Category
11(10.8) 7(6.9) 2(2)
No problems Some problems Dependent
0 0 2(2)
Personal Care (p < 0.001)
No problems Some problems Dependent
0 0 2(2)
Daily Activities (p < 0.001)
No problems Some problems Dependent
Pain/Discomfort (p < 0.05)
Absence Moderate High
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Mobility (p < 0.001)
Well nourished MNA>24
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Malnutrition MNA<17 n(%)
Risk of malnutrition MNA,17-23.5 n(%)
n(%)
57(55.9) 22(21.6) 0
68(66.7) 10(9.8) 1(1)
0 0 2(2)
11(10.8) 3(2.9) 6(5.9)
66(64.7) 12(11.8) 1(1)
1(1) 0 1(1)
12(11.8) 8(7.8) 0
48(47.1) 25(24.5) 6(5.9)
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11(10.8) 7(6.9) 2(2)
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Anxiety/Depression Absence 1(1) 13(12.7) 66(64.7) (p > 0.05) Moderate 0 5(4.9) 11(10.8) High 1(1) 2(2) a Chi-square of Pearson test, values p ≤ 0.05 were considered to be statistically significant.
ACCEPTED MANUSCRIPT Highlights - Results show the important role of nutrition and eating habits in the quality of life of elderly - Almost 21% of the collective were at risk of malnutrition, especially women and over 90y - A significant negative association between risk of malnutrition and quality of life was found
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- Contribution to improve knowledge in nutrition and aging process