Nutrition Feeding and Eating

Nutrition 71 (2020) 110640

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Nutrition

journal homepage: www.nutr i t ionjrnl .com

Applied nutritional investigation

Malnutrition in older adults: Correlations with social, diet-related, and neuropsychological factors

Konstantinos Katsas M.Sc. a, Eirini Mamalaki M.Sc. a, Meropi D. Kontogianni Ph.D. a, Costas A. Anastasiou Ph.D. a,b, Mary H. Kosmidis Ph.D. c, Iraklis Varlamis Ph.D. d, Georgios M. Hadjigeorgiou M.D., Ph.D. e,f, Efthimios Dardiotis M.D., Ph.D. e, Paraskevi Sakka M.D., Ph.D. g, Nikolaos Scarmeas M.D., Ph.D. b,h, Mary Yannakoulia Ph.D. a,* a Department of Nutrition and Dietetics, Harokopio University, Athens, Greece b Department of Social Medicine, Psychiatry and Neurology, First Department of Neurology, Aeginition University Hospital, National and Kapodistrian University of Athens, Athens, Greece c Laboratory of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Greece d Department of Informatics and Telematics, Harokopio University, Athens, Greece eDepartment of Neurology, Medical School, University of Cyprus, Aglantzia, Cyprus f Department of Neurology, Faculty of Medicine, University of Thessaly, Larissa, Greece g Athens Association of Alzheimer’s disease and Related Disorders, Marousi, Greece h Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, The Gertrude H. Sergievsky Center, Department of Neurology, Columbia University, New York, New York

A R T I C L E I N F O

Article History: Received 24 March 2019 Received in revised form 20 September 2019 Accepted 2 November 2019

Sources of support: This study was supported 133014 from the Alzheimer’s Association; and 189 EU program Excellence Grant (ARISTEIA) and the Ministry for Health and Social Solidarity (Greece). C from the Greek State Scholarships Foundation (MIS sources had no involvement in the collection, anal the writing of the report; and in the decision to sub Conflicts of interest: None. *Corresponding author. Tel.: +30 210 9549175; f E-mail address:[email protected] (M. Yannako

https://doi.org/10.1016/j.nut.2019.110640 0899-9007/© 2019 Elsevier Inc. All rights reserved

A B S T R A C T

Background: The number of older adults is increasing rapidly. Malnutrition is a major problem in this age group, which may adversely affect health and quality of life. Several physiological, socioeconomic, and neuro- psychological factors can lead to malnutrition. Objectives: The aim of this study was to evaluate the nutritional status of community-dwelling older adults, and explore the associations of malnutrition risk with physiological, socioeconomic, and neuropsychological characteristics. Methods: This study is part of the Hellenic Longitudinal Investigation of Aging and Diet study, a cross- sectional observational study in Greece, and study participants were 1831 urban-dwelling elderly individuals (mean age: 73.1 § 5.9 y; 40.8% men). Risk for malnutrition was assessed with the Determine Your Nutritional Health checklist. Data on age, sex, level of education, marital status, depression, cognitive performance, body mass index, total energy intake, and adherence to the Mediterranean diet were recorded. Correlations and multivariate analyses were performed between these variables and risk for malnutrition. Results: The estimated prevalence of moderate and high nutritional risks was 34.8% and 29.4%, respectively. Risk for malnutrition was associated with marital status (unmarried), increased body mass index, male sex, lower level of education, lower cognitive performance, and lower adherence to the Mediterranean diet (P< 0.05). Conclusions: Nutritional screening should be performed frequently in all community-dwelling older adults. Health experts should perform nutritional screening in all community-dwelling older adults as part of sec- ondary prevention, and nutrition counselling and support should be offered in those at risk for malnutrition.

© 2019 Elsevier Inc. All rights reserved.

Keywords: Malnutrition

Nutritional status Elderly Community-dwelling Cognitive status Diet

by the following grants: IIRG-09- 10276/8/9/2011 from the ESPA-

DY2b/oik.51657/14.4.2009 of the AA has received financial support :5001552); however, the funding ysis, and interpretation of data; in mit the article for publication.

ax: +30 210 9549141. ulia).

.

Introduction

The number of older adults has been increasing over the years, and estimates predict that by 2050, the proportion of people age >60 y will double from 11% to 22% and the percentage of people of a very old age (age >80 y) will quadruple [1]. Yet, living a long life is typically associated with a decreased quality of life, mainly owing to poor health [2]. Malnutrition is a major problem in older age groups and can lead to further deterioration of health and quality of life [3]. Malnutrition is defined as a state of nutrition that

2 K. Katsas et al. / Nutrition 71 (2020) 110640

results from a lack of intake or uptake and leads to altered body composition and body cell mass [4]. As a significant predictor for both morbidity and mortality, malnutrition may cause muscle and immune dysfunction and lead to decreased bone mass, anemia, cognitive impairment, and poor healing of wounds [5]. Based on various studies, malnutrition prevalence rates vary from 20% to 30% in clinical settings and 2% to 8% in community-dwelling older adults [6,7], although studies that assess the risk of malnutrition indicate higher rates [8�10].

Several physiological, socioeconomic, and neuropsychological factors may contribute to insufficient dietary intake and thus lead to malnutrition [4,11]. With regard to physiological factors, anorexia of ageing and other biologic changes related to age (e.g., slower gastric emptying, altered responses to hormones, oral changes, and altered taste and smell) may induce reductions in total energy intake and increase the risk for malnutrition [4,5,11,12]. A number of diseases and medications may also predispose to malnutrition [4,5], as well as many unfavorable social conditions (e.g., loneliness, social isola- tion, and social exclusion) [13,14]. In addition, a higher educational level is frequently associated with a higher income and the con- sumption of better quality food [14,15]. With respect to neuropsy- chological factors, cognitive impairment and depression are positively related to the risk for malnutrition [4].

A variety of studies have evaluated the physical, social, and neuropsychological risk factors in relation to the risk for malnutri- tion in older adults [15�17]. However, these studies have method- ological and other limitations, including small samples that are not representative, main focus on hospitalized populations, and use of mostly nonvalidated measures. These studies are also somewhat limited in their scores because they evaluated only some of the possible risk factors for malnutrition (mainly physical and socio- economic factors), and less attention has been paid to date to diet- related (i.e., adherence to dietary patterns, such as the Mediterra- nean diet) and neuropsychological factors.

Thus, our aim was to evaluate the risk of malnutrition in a rep- resentative population sample of community dwelling older adults and assess potential associations with a range of social, diet- related, and neuropsychological factors.

Methods

The present analysis is part of the Hellenic Longitudinal Investigation of Aging and Diet, which is a cohort study in Greece forwhich the baseline assessmentwas completed in 2014 and a planned follow-up analysis occurred 3 y after the initial evaluation [18]. People aged �65 y were randomly selected from two municipalities in Greece: Larissa (small urban center) andMarousi (large urban center). The study ascertained exhaustive information pertaining to domains, including demographic characteristics; medical his- tory; neurological, psychiatric, and neuropsychological assessments; anthropometry; and lifestyle parameters (e.g., diet, physical activity, sleep, and social life). All procedures were approved by the Institutional Ethics Review Board of the University of Thessaly and the Institutional Ethics Review Board of the University of Athens. Informed consent was obtained from all individual participants included in the study.

Dietary assessment

For the assessment of dietary intake, we used a semiquantitative Food Fre- quency Questionnaire that was validated for the Greek population [19]. The ques- tionnaire consists of 76 questions on the frequency of consumption of the main food groups and beverages usually consumed (e.g., dairy products, starches, fruit, vegetables, meat, fish, legumes, fats and oils, eggs, sweets, alcoholic beverages, and stimulants) and other eating behaviors. We calculated the total energy intake in kcal/d from the responses to the questionnaire.

Furthermore, we assessed adherence to the Mediterranean dietary pattern with the Mediterranean diet questionnaire, which yields a MedDietScore [20]. The Med- DietScore evaluates the weekly consumption of 11 food groups: Nonrefined cereals, fruits, vegetables, legumes, potatoes, meat and meat products, poultry, fish, full fat dairy products, olive oil, and alcohol intake. Each food group is rated from 0 to 5 if close to the Mediterranean pattern (i.e., higher score for higher consumption of vege- tables) and the reverse if far from the pattern. The score ranges from 0 to 55, and the higher values indicate a greater adherence to the Mediterranean dietary pattern.

Risk for malnutrition: Determine Your Nutritional Health score

Risk for malnutrition was evaluated with the Determine Your Nutritional Health (DETERMINE) checklist [21]. This checklist was developed as a brief risk- appraisal questionnaire that could be self-administered and designed to identify individuals whose diets are relatively low in nutrient intake or who perceive themselves to be in fair or poor health. DETERMINE is not a clinical diagnostic tool, but appropriate for population-based research. DETERMINE consists of 10 ques- tions to evaluate age-related changes, comorbidity, polypharmacy, quantity of food intake, tooth loss or mouth pain, economic hardship, social contacts, involun- tary weight loss or gain, and need for assistance. Total score ranges from 0 to 21, and values from 0 to 2 indicate good nutritional status, 3 to 5 moderate nutritional risk, and �6 high nutritional risk.

Covariates

Age (in y), sex (dichotomous variable), and education (y of education) were recorded. Furthermore, participants were asked whether they lived with a partner or if they were single/divorced/widowed (marital status, coded as 0: living with a partner; 1: living without a partner). Height and weight were measured on a lev- elled platform scale and a wall-mounted stadiometer to the nearest 0.5 cm and 0.5 kg, respectively. Body mass index (BMI; kg/m2) was calculated by dividing the weight in kg by the height in m2.

Furthermore, trained psychometricians administered a complete set of neuropsy- chological tests to assess all major cognitive domains (i.e., orientation, memory, atten- tion and speed, executive functions, language, and visuospatial perception). The scores of each cognitive test were converted into z-scores using mean and standard deviation values of nondemented participants. Subsequently, cognitive domain z-scores were averaged to calculate a composite index of global cognitive functioning (GCF). Diagno- ses of dementia, Alzheimer’s disease, and mild cognitive impairment were set per the international criteria (Diagnostic and Statistical Manual of Mental Disorders Fourth Edition, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association, and International Working Group on mild cognitive impairment) [22] during consensus meetings of all study investigators. Depression was used as a dichotomous variable: Participants who scored >6 on the Geriatric Depression Scale, a 15-item self-report questionnaire [23,24] or those who were diagnosed with depression or were under antidepressant treatment were considered as suffering from amood disorder.

Statistical analysis

Descriptive statistics are presented as absolute and relative frequencies for qualitative variables and mean values and standard deviation for quantitative vari- ables. For the association between categorical variables, x2 tests were used. For the association between a categorical variable with >2 categories and a qualitative variable, analyses of variance were used. Finally, linear regression modeling was performed to determine the potential relationship between age, sex, years of edu- cation, marital status, GCF, depression, BMI, adherence to the Mediterranean diet, and total energy intake (independent variables) with the DETERMINE score as a continuous variable (dependent variable).

Specifically, we ran three models. In the first model, we included only the basic sociodemographic characteristics of the participants (i.e., age, sex, years of educa- tion, and marital status). In the second model, we also included neuropsychologi- cal characteristics (z-score of cognitive performance and depression), and in the third model we included diet-related characteristics (i.e., BMI, Mediterranean diet score, and total energy intake). We also repeated these models for men and women separately. An acceptable level of significance was established as a < 0.05.

Results

Of the total study population, 1831 participants completed the DETERMINE checklist in full. When comparing participants who com- pleted the DETERMINE checklist with those who did not, we found no differences in basic sociodemographic characteristics (i.e., age, sex, years of education, and marital status). Participants in the high nutri- tional risk group were of significantly higher age, had a higher BMI score, fewer years of education, and lower GCF and Mediterranean diet scores than the other two groups (Table 1; Supplementary Fig. 1).

Figure 1 represents the percentages of positive answers to each question of the DETERMINE checklist. More than half of the sample of participants reported taking �3 different drugs per day (57.4%). More than one third of the sample had an illness or condition that influenced food intake (33.1%) and dental or oral health problems (34.2%). A fifth of the sample reported eating few fruits or

Table 1 Demographic, anthropometric, and medical characteristics, and dietary intake of study participants per the nutritional risk status

Variables Total sample Well nourished Moderate nutritional risk High nutritional risk P value*

Percentage 35.8 34.8 29.4 Age 73.1 § 5.9 72.2 § 5.5 73.3 § 5.9y 73.9 § 6.2y < 0.001 Sex 40.8 40.1 45.0 36.8 0.012 Education 7.7 § 4.8 9.4 § 4.9 7.4 § 4.6 y,x 5.9 § 4.1y,x < 0.001 Marital status 72.0 77.5 73.9 61.1 < 0.001 Body mass index 29 § 4.7 28.2 § 4.4 29.2 § 4.7y 29.7 § 4.9y < 0.001 Global cognitive functioning -0.24 § 0.86 0.04 § 0.71 -0.29 § 0.83y,x -0.55 § 0.94y,z < 0.001 Depression 20.6 12.9 16.6y,x 34.7 y,z < 0.001 Total energy intake 1975 § 532 1984 § 500 1995 § 537 1934 § 566 0.140 Total energy intake 27 § 8 27 § 8 26 § 8 26 § 9 0.144 Mediterranean diet score � 33.3 § 4.6 34.2 § 4.2 33.3 § 4.6y,x 32.1 § 4.8y,z < 0.001

*Analysis of variance main effect of determine groups. Bold numbers indicate statistical significance. Results are presented as mean § standard error mean, and y, z, x indicate statistical significance compared with the groups of patients who are well nourished, have moderate nutritional risk, and have high nutritional risk, respectively

Fig. 1. Percentages of positive answers to each question of the DETERMINE checklist.

Table 2 Linear regression analyses of the DETERMINE score and sociodemographic, nutri- tional, and neuropsychological variables in the total sample

Model 1 Model 2 Model 3

B P B P B P

Age 0.005 0.847 -0.055 0.029 -0.050 0.050 Sex -0.050 0.044 -0.062 0.013 -0.081 0.001

K. Katsas et al. / Nutrition 71 (2020) 110640 3

vegetables or milk products (20.9%) and being alone most of the time (20.4%). The remaining questions received a positive response from a very small percentage of participants (Fig. 1).

Results from the fully adjusted models revealed that risk for mal- nutrition was positively associated with BMI and negatively associated with years of education, GCF, and adherence to the Mediterranean diet. Being a woman was associated with a lower DETERMINE score (Table 2; Supplementary Fig. 2). When total energy intake was added to the fully adjusted models model, the results did not change, but total energy intake was not significantly associated with DETERMINE scores (data not shown). When the analysis was performed in each sex separately, the associated variables did not change.

Education -0.318 < 0.001 -0.238 < 0.001 -0.214 < 0.001 Marital status 0.149 < 0.001 0.140 < 0.001 0.134 < 0.001 Global cognitive functioning -0.163 < 0.001 -0.148 < 0.001 Depression 0.089 < 0.001 0.083 < 0.001 Body mass index 0.076 0.001 Mediterranean diet score -0.102 < 0.001

Bold number indicates statistical significance.

Discussion

In the present population-based cohort study of older adults age �65 y, we examined the association between risk for malnutrition and a wide range of variables, including social, diet-related, and

neuropsychological characteristics. Our findings suggest that more years of education, lower BMI, being a woman, being married, and having a greater degree of adherence to the Mediterranean diet, as well as higher cognitive functioning were associated with a

4 K. Katsas et al. / Nutrition 71 (2020) 110640

decreased risk of malnutrition. We found that one third of partici- pants were well nourished, another third was at moderate nutri- tional risk, and the remaining third was at a high nutritional risk. The most frequent positive answers to questions on the DETERMINE questionnaire in the population under investigation were related to multidrug therapy, having an illness or condition that influences food intake, and having dental or oral health problems.

To the best of our knowledge, this is the first study in Greece to evaluate nutritional risk in community dwelling older adults using the DETERMINE checklist. Our results suggest that approximately 30% of this representative sample were at a high nutritional risk. Other studies in Greece examining the risk of malnutrition using the Mini Nutritional Assessment score have found similar results (i.e., 26%�36% of the pop- ulation under investigation was at risk for malnutrition) [25�27]. As expected, the questions with themost frequent positive response were those relevant to multidrug therapy, having an illness or condition that influences food intake, and having dental or oral health problems. Our sample consisted of older adults, a cohort that is at a high risk for chronic illness, which leads to an increased need for medications [5].

Additionally, studies have previously suggested that 30% of older adults have dry mouth, 50% have dental caries in at least one tooth, and in many countries >50% of older adults have no teeth [28]. Other studies have shown similar results with regard to multidrug therapy [8], having an illness or condition that influences food intake, and having dental [8,16] or oral health problems [16].

Impaired cognition and depression are well-established risk factors for malnutrition [4]. A possible explanation for this could be that weight loss as well as loss of appetite, which lead to malnu- trition, are signs of depression as well as early signs of dementia onset, which is indicated by impaired cognitive performance [29]. In addition, increased age may cause a decline in cognitive func- tioning and particularly memory. Memory relates to many aspects of everyday functioning, such as eating [30], and in turn may lead to an increased risk of malnutrition [10,31].

Of note, our data indicate that living without a partner and hav- ing a low educational level were related to an increased risk for malnutrition. Living without a partner often means living alone and having to cook and eat alone, which are well-known risk fac- tors for insufficient energy intake [32]. Moreover, a low level of education implies a lower socioeconomic level [33] and may lead to malnutrition [13]. Other studies have reported the same results [15,34]. On the other hand, close adherence to the Mediterranean diet was associated with a lower risk for malnutrition. Adherence to the Mediterranean dietary pattern may improve quality of life and total mortality, as well as lower the risk for many chronic dis- eases, such as coronary heart disease and cancer [35] that increase the risk for malnutrition [4]. However, owing to the cross-sectional design of the study, we cannot exclude the possibility that people in better nutritional status and general health may be more capa- ble of following a diet of a higher quality.

Interestingly, we found that women had a lower risk of malnu- trition than men. This finding is in contrast with the results from previous studies, which have shown an increased malnutrition risk among women relative to that of men [15,17,34]. A possible reason for this discrepancy could be the high percentage of men who answered positively to some questions of the DETERMINE checklist (i.e., 80% of those who answered positively to the question “I have 3 or more drinks of beer, liquor, or wine almost every day” were men). Alcohol overconsumption could partly explain the present results. Furthermore, women live longer and thus, have an increased possibility of living alone, which is a well-known risk factor for malnutrition [32]. However, this issue cannot be addressed by the DETERMINE questionnaire, and would be particu- larly interesting should these results be replicated in other studies.

Finally, a finding of note is the positive relationship between BMI and risk of malnutrition, which is contrary to what one may expect. However, previous studies have reported that BMI is not a sensitive indicator for changes in body composition [36] and is not recommended to be used as a potential criterion for malnutrition [37]. Indeed, in a recent meta-analysis, there was no statistically significant association between BMI and risk for malnutrition [38].

Limitations

The present study has both limitations and strengths. Among the limitations of this study was its inability to ascribe a direct cause-and-effect relationship between the examined characteris- tics and malnutrition due to its cross-sectional design. Moreover, the DETERMINE questionnaire has not been validated in the Greek population. Nevertheless, this questionnaire has been used widely in many different populations in the past [8�10,16,33].

With regard to the strengths of the study, we used a represen- tative sample of community-dwelling older adults, in contrast with other studies that used specific subgroups of older people. Furthermore, some studies use many age groups (i.e., individuals age >50 y) and consequently, conclusions cannot be drawn with regard to older people [6�8,10,15,16,33]. We collected most data by using validated tools that have been widely used in previous epidemiologic studies [39,40]. Skilled, trained, and closely super- vised personnel evaluated the sample, and a multidisciplinary con- sensus expert team set the final diagnoses based on the uniform application of widely accepted criteria.

Conclusions

According to the DETERMINE classification, only one third of this representative population sample of community-dwelling older adults waswell nourished, which is a small proportion. Health experts should perform nutritional screening for all community-dwelling older adults as part of secondary prevention, and nutrition counselling and support should be offered to those at risk for malnutrition. BMI was higher in the groupwith a high nutritional risk; therefore, we need to reconsider the sole use of this anthropometric tool as an indicator formalnutrition in older adults.

Declaration of Competing Interest

The authors declare that they have no known competing finan- cial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary materials

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.nut.2019.110640.

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