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Interventions and public health nutrition

Nutritional risk of European elderly



The elderly constitute a population group with a high prevalence of non-communicable chronic diseases and high risk of malnutrition. The aim of this study was to identify factors associated to nutritional risk in free-living European elderly.


The sample included 644 European citizens, free living in the community, aged 65 years or more. The sample was quota controlled for age groups (65–74, 75 years), gender (male/female) and living circumstances (living alone/with others). Logistic regression was performed to identify factors associated with nutritional risk.


Several variables regarding socio-demographic characteristics, food choice, health status and the satisfaction with food-related life were included in the analysis. According to the recoded score of the ‘Determine your nutritional health’ (NSI checklist), 53% of the elderly were at nutritional risk. Nutritional risk was more likely to occur in elderly who considered that it was more important to choose foods ‘easy to chew’; with lower average number of fruit and vegetables (F&V) intake episodes and lower score for general health. It was also found in non-married participants; those that did not identify changes in their appetite; and those that felt changes in health status. In this sample, the lowest nutritional risk was found for body mass index (BMI) around 18.5 kg/m2. Country of residence, gender and age were not found to have a significant effect on nutritional risk.


Attention should be drawn to the living circumstances, changes in appetite or health, the general heath perception, F&V intake, choice of foods easy to chew and having a low or high BMI.


Nutritional status of older adults is determined by physiological, socioeconomic and psychological changes occurring at older age. The elderly populations are more vulnerable to nutritional deficiencies due to a combination of factors, from physiological changes or deterioration of functions, such as appetite loss, changes in taste and drug–nutrient interactions, to social and economic factors such as income, living circumstances and lifestyle. Psychological factors such as depression and cognitive impairment, within environmental factors, may contribute to a higher nutritional risk.1 Two different groups of aging determinants with impact on the nutritional status are identified: the intrinsic (mostly biological) and extrinsic (society and environment).

Malnutrition can be defined as ‘any nutritional imbalance’, thus including people who suffer from overnutrition and those who present undernutrition.2 Although malnutrition has been well documented in institutionalized elders,3 it is less estimated and poorly understood in individuals living in the community.

Nutrition screening and evaluation of older people has been focused on anthropometric and biological parameters4 and some tools have been used to estimate malnutrition and nutritional risk. The ‘Determine your nutritional health’ questionnaire is a checklist based on warning signs of poor nutrition for: disease; eating poorly; tooth loss and mouth pain; economic hardship; reduced social contact; multiple medicines; involuntary weight loss or gain; needs assistance in self-care; and older than 80 years. The tool was developed as part of the Nutritional Screening Initiative (NSI) for professionals working with older people. Designed to be self-administrated or administrated by a health professional, it includes yes/no statements about dietary, general and social conditions.5 A modified version was used within a baseline survey and was proven to identify elders with an increased risk for several nutrition-related health problems.6 The limitations of this instrument are poor sensibility and specificity, suggesting it should be used more efficiently as an educational tool, promoting the awareness of older people at risk in the community.5, 7 The Mini Nutritional Assessment (MNA) has been used more commonly but presents limitations for the nutritional assessment of healthy elderly populations, as the NSI checklist.8 The MNA presented associations mainly for dietary-related items and less for age, gender and body mass index (BMI),9 being considered useful for daily clinical practice10 and detecting undernutrition in elderly in home-care programmes, nursing homes and hospitals.11 Screening tools should consider the age group of the population as well as risk factors to detect malnutrition or predict disease outcomes.12

Although nutritional status might be a determinant for health status, a good health condition is in turn a determinant for nutritional risk, as it affects daily routines, food habits and nutritional intake. To assess the health-related quality of life, the SF-364 has been useful in the surveys carried out with older people living in the community. The transformed scores can be computed and used to evaluate the different domains separately.13 Research found an inverse association between obesity and self-reported health14 in adult Europeans. Although BMI is a poor indicator of nutritional status, an association between well-being, health and body composition has been identified.

The association of socio-demographic and life conditions with nutritional status and other determinants of health have been explored. Constraints such as restricted mobility can affect nutritional status by interfering with the nutritional intake.15 Higher nutritional risk was associated with lower self-efficacy, difficulties in meal preparation and depression in older Japanese.16 The lack of resources such as financial, food storage facilities, access to food stores, cooking facilities and the presence of physical disabilities and loneliness15 were considered as determinants for food choice and nutritional intake. Older people experiencing changes in their living circumstances such as the loss of a partner can reduce their food intake owing to depression or difficulties in self-management of daily activities therefore increasing nutritional risk.17 A poor health, lack of economic resources, disability and social factors (place of birth, partner’s loss and loneliness) were associated with being at nutritional risk.18, 19 Age was found to be an inverse predictor of nutritional risk.17, 20

The present study was developed to identify factors associated with nutritional risk in a population of elderly people, free living in the community, from eight European countries.

Subjects and methods

The data presented in this study belonged to the European Project ‘Food in later life’ (, carried out from 2003 to 2005 in eight European countries: Denmark, Germany, Italy, Poland, Portugal, Spain, Sweden and the United Kingdom. The project was structured in several Workpackages in which data were collected to identify the most relevant factors included in the final questionnaire and for the development of a tool to measure satisfaction with food-related life.20 Face-to-face interviews were carried out as the questionnaires to collect general data were not self-administrated. The data used in the present study include variables from a general socio-demographic questionnaire, satisfaction with food-related life scale and the SF-36 questionnaire. Socio-demographic data, lifestyle, living arrangements, food habits, nutritional status and the ‘Determine your nutritional health’ checklist were also recorded. The latter is a tool used to screen for nutritional risk by obtaining a final score which allows the classification of individuals according to their answers to ten specific questions. The scores range from 0 to 6 or higher. The interpretation of scores is the following: 0–2, good nutritional status; 3–5, moderate nutritional risk; 6, high nutritional risk. The three scores were transformed in a new dichotomous variable, necessary for the next step of analysis. The new variable resulted in a classification of participants as being ‘at nutritional risk’ (moderate and high) or ‘without nutritional risk’ (good nutritional status). The database included the transformed scores from the original SF-36 questionnaire, which allowed a quick interpretation of the participants’ health status on the eight domains of this instrument. The scores range from 0 to 100, where highest scores mean ‘best possible health’ and the lower scores mean ‘worst possible health’.

Food consumption was recorded by 7-day non-weighed diaries. The food diaries provided data of the number of intakes of fruit and vegetable (F&V) and alcoholic beverages. Average consumption episodes were computed from the consumption recorded in the whole week. The ‘events’ were the times when people referred to have included F&V or alcoholic beverages during the day, isolated or as part of a meal.

The computed BMI and (BMI−18.5)2 were included in the analysis.

Statistical analysis

Mean (M), s.d., minimum (min) and maximum (max) values were calculated for the scale variables and frequencies were used to describe ordinal and nominal variables. The skewness and kurtosis coefficients were computed to evaluate the normality of the distributions. All the scale variables had a distribution close to the normal.

A backward stepwise logistic regression (using the likelihood ratio test) was computed to evaluate the relationship between a dichotomous variable and other variables. The null hypothesis was rejected when its critical significance level was below 0.05.

From the analysis of the relationship between the BMI and the nutritional risk, a nonlinear relation between these two variables, with a minimum for BMI near 18.5, was observed (data not shown). Therefore, it was decided to include both a linear term BMI and a quadratic term (BMI−18.5)2 in the logistic regression. Only the quadratic term remained in the last step.

All statistical analysis was performed using Statistical Package for Social Sciences (SPSS) version 17.0 for Windows (SPSS Inc., Chicago, IL, USA).


Sample characteristics

To enable cross-cultural comparisons, the sample was quota controlled for gender, country, living circumstances and age groups according to the initial recruitment methodology of the Project. From the ones that lived with other persons, 40.8% were married or living as married and only 8.6% lived with another adult.

Participants were aged between 65 and 98 years (mean 74.8 years) and most of them had completed primary or secondary school (Table 1). They lived either alone or in households up to six persons. There was a broad range of household monthly income with categories spanning from less than 366€ to above 3578€. Respondent’s BMI ranged from 17 to 41.9 with an average of 25.9 (s.d. 3.9).

Table 1 Socio-demographic characteristics of the European elderly

With respect to other variables, the average number of F&V events per day was of 2.57 (s.d. 1.28) and for alcoholic beverages a mean of 0.5 (s.d. 0.7) average beverages per day was registered (Table 1). The SF-36 questionnaire-transformed scores refer to eight health status domains ranging from a minimum of 0 and a maximum of 100. Results for mean and s.d. are presented in Table 2.

Table 2 Mean and s.d. for SF-36-transformed scores

Computed scores resulted in three ranges of nutritional risk: 47.3% (n=281) of the participants were not at risk, showing a good nutritional status, 27.3% (n=162) had a moderate risk and 25.4% (n=151) were at a high nutritional risk. After recoding the variable in two categories (‘without risk’ and ‘at risk’), we compared participants by gender and found that participants at nutritional risk were equally distributed by men (49.5%) and women (50.5%).

Analysis of factors that contribute to nutritional risk score showed that the more frequent conditions were multiple drug use and eating alone (Table 3).

Table 3 Determine your nutritional health questions: ‘yes’ (%)

Factors associated with nutritional risk

The logistic regression revealed seven factors with relevance to nutritional risk, as follows: a high nutritional risk was associated with a higher (BMI−18.5)2 (β=0.005, P=0.007), to consider important to choose foods easy to chew (β=0.324, P<0.001), having a lower average number of F&V daily events (β=−0.213, P=0.023) and with lower values in the scores of transformed scale for general health (β=−0.018, P=0.006) (Table 4).

Table 4 Nutritional risk factors

Living arrangement was also related to nutritional risk as unmarried subjects, namely elders living with another adult (odds ratio (OR)=2.82, P=0.011) and especially the ones who were single or living alone (OR=3.22, P<0.001), more likely to be at higher risk than married ones. Subjects who reported changes in their health status or suffered from health problems were much more likely to be at nutritional risk than their healthy counterparts (OR=7.74, P<0.001). On the other hand, reporting appetite changes was likely to be associated with a decreased risk (OR=0.41, P=0.016).

It is interesting to highlight the fact that higher or lower (BMI−18.5)2 were associated with higher nutritional risk. The expression (BMI−18.5)2 attempts to account for a possible nonlinear relation between the BMI and the nutritional risk, as both low and high values of BMI may be related to higher risk.


In the present cross-cultural research, the nutritional risk of European elderly was assessed. Our objective was to identify the factors underlying poor nutritional status in a free-living elderly population. The NSI checklist revealed associations with several life circumstances and older people’s perceptions about health and food. Previous studies showed this tool to be effective in identifying elderly populations at risk for certain nutrition-related health problems.6

Although half of our population (47.3%) had a good nutritional health, approximately one-fourth suffered from a moderate risk (27.3%) and a further 25.4% from a high risk. When compared with other elderly living in the community,17 we found less people with good nutritional state (47.3% vs 66.2%) and conversely, more at a moderate or high risk (52.7% vs 33.8%). Nevertheless, the comparisons between different studies should be made carefully as different instruments for nutritional assessment may have been used.

The average of our population had a BMI higher than normal values for adults which requires a careful interpretation. Concerning the use of BMI in elderly, it has been questioned if a higher cut-off point should be used, due to changes in body composition and an increased BMI-mortality curve.12 Given its limitations in evaluating body composition, BMI should be used as an indicator of health risk.21 The extremes of body weight (underweight and obesity) were associated with lower health perception and poorer physical functioning, thus enhancing the importance of normal body weight in older age.22 Results suggest that attention should be drawn to overweight as well as underweight as both might indicate poor nutritional status.

Factors such as choosing foods easy to chew were associated with nutritional risk. Difficulty in chewing was inversely associated with the best quality diet for older men.23 Ability to chew can affect older adults’ intake as mouth or teeth problems can influence food choices of the elderly and consequently the nutritional status. Choosing food easy to chew is a solution for elders with a poor oral health but it may have undesirable outcomes because it can lead to the exclusion of nutrient-dense foods, namely fruit and vegetables.

A low average number of F&V events per day were also associated with nutritional risk. Consumption of adequate amount of F&V is part of a healthy lifestyle, relevant to a good nutritional status and is associated with a reduced risk of chronic diseases that have a higher prevalence in older age.24 In previous studies, several associations were found for older men and women with different living circumstances with reference to food intake.25, 26 It is suggested that gender and living status affect the F&V consumption of elderly. Therefore, consumption of F&V should be promoted with particular interest in the elderly.

Considering the SF-36 questionnaire, the general health-transformed score had a significant inverse association with nutritional risk. As the lowest values mean poor health and the highest correspond to a better health status,27 this means poor general heath is associated with a higher nutritional risk. The associations between health-related quality of life and some domains in nutritional status were previously described. Our findings suggest that subject’s health-related quality of life can be compromised when nutritional status is poor and this association acts at a general level. Actions leading to an improvement in nutritional status should have a positive impact on the general health of the elderly.

The importance of life circumstances is emphasized as we found a nutritional risk almost three times higher for individuals living alone or single. Living circumstances have been considered relevant to food habits, namely to F&V consumption, as well as other socioeconomic determinants well described by the literature.25, 28 Gender, level of education and income was determinant of food intake of European adults.29, 30 In the present study, living alone was a predictor of nutritional risk suggesting that elderly who are not married or living with a partner, particularly those who live alone, require special attention. General changes in health status or health problems have shown to increase nutritional risk, although changes in appetite decreased nutritional risk. Changes in appetite might occur at earlier stages of risk, before affecting nutritional status. In other studies, the loss of appetite and the mode of feeding (eating with or without assistance and difficulties) were found to have a high influence to the MNA total score.9 Our instrument lacks sensitivity to detect acute situations but it is associated with more long-term changes in older people’s life that affect food intake. The instruments for nutritional screening should detect and evaluate changes in health or others that might determine nutritional status.

The present study strengthens the evidence on the determinants of nutritional risk and draws attention to factors less commonly explored. For nutritional status assessment, the choice of the instrument should reflect the objectives of the investigation and consider the specificities of populations. Although with some limitations, the NSI checklist can be useful to identify poor nutritional status in older people living in the community.


  1. 1

    Lee KS, Cheong H-K, Kim EA, Kim KR, Oh BH, Hong CH . Nutritional risk and cognitive impairment in the elderly. Arch Gerontol Geriatr 2009; 48: 95–99.

    Article  Google Scholar 

  2. 2

    White JV, Guenter P, Jensen G, Malone A, Schofield M . Consensus statement of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition: characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). J Acad Nutr Diet 2012; 112: 730–738.

    Article  Google Scholar 

  3. 3

    Amaral TF, Matos LC, Tavares MM, Subtil A, Martins R, Nazaré M et al. The economic impact of disease-related malnutrition at hospital admission. Clin Nutr 2007; 26: 778–784.

    Article  Google Scholar 

  4. 4

    Drewnowski A, Monsen E, Birkett D, Gunther S, Vendeland S, Su J et al. Health screening and health promotion programs for the elderly. Dis Manag Health Out 2003; 11: 299–309.

    Article  Google Scholar 

  5. 5

    Callen B . Understanding nutritional health in older adults: a pilot study. J Gerontol Nurs 2004; 30: 36–43.

    Article  Google Scholar 

  6. 6

    Beck AM, Ovesen L, Osler M . The 'mini Nutritional Assessment' (MNA) and the 'determine Your Nutritional Health' Checklist (NSI Checklist) as predictors of morbidity and mortality in an elderly Danish population. Br J Nutr 1999; 81: 31–36.

    CAS  Article  Google Scholar 

  7. 7

    Visvanathan R, Zaiton A, Sherina MS, Muhamad YA . The nutritional status of 1081 elderly people residing in publicly funded shelter homes in Peninsular Malaysia. Eur J Clin Nutr 2005; 59: 318–324.

    CAS  Article  Google Scholar 

  8. 8

    de Groot LC, Beck AM, Schroll M, van Staveren WA . Evaluating the DETERMINE Your Nutritional Health Checklist and the Mini Nutritional Assessment as tools to identify nutritional problems in elderly Europeans. Eur J Clin Nutr 1998; 52: 877–883.

    CAS  Article  Google Scholar 

  9. 9

    Cuervo M, Ansorena D, García A, Astiasarán I, Martínez JA . Food consumption analysis in Spanish elderly based upon the mini nutritional assessment test. Ann Nutr Metab 2008; 52: 299–307.

    CAS  Article  Google Scholar 

  10. 10

    Cuervo M, Ansorena D, Martínez-González MA, García A, Astiasarán I, Martínez JA . Impact of global and subjective mini nutritional assessment (MNA) questions on the evaluation of the nutritional status: the role of gender and age. Arch Gerontol Geriatr 2009; 49: 69–73.

    Article  Google Scholar 

  11. 11

    Kondrup J, Allison SP, Elia M, Vellas B, Plauth M . ESPEN guidelines for nutrition screening 2002. Clin Nutr 2003; 22: 415–421.

    CAS  Article  Google Scholar 

  12. 12

    Elia M, Stratton RJ . An analytic appraisal of nutrition screening tools supported by original data with particular reference to age. Nutrition 2012; 28: 477–494.

    Article  Google Scholar 

  13. 13

    Walters SJ, Munro JF, Brazier JE . Using the SF‐36 with older adults: a cross‐sectional community‐based survey. Age Ageing 2001; 30: 337–343.

    CAS  Article  Google Scholar 

  14. 14

    Pieniak Z, Pérez-Cueto F, Verbeke W . Association of overweight and obesity with interest in healthy eating, subjective health and perceived risk of chronic diseases in three European countries. Appetite 2009; 53: 399–406.

    Article  Google Scholar 

  15. 15

    Wylie C, Copeman J, Kirk SFL . Health and social factors affecting the food choice and nutritional intake of elderly people with restricted mobility. J Hum Nutr Diet 1999; 12: 375–380.

    Article  Google Scholar 

  16. 16

    Lizaka S, Tadaka E, Sanada H . Comprehensive assessment of nutritional status and associated factors in the healthy, community-dwelling elderly. Geriatr Gerontol Int 2008; 8: 24–31.

    Article  Google Scholar 

  17. 17

    Wham C, Teh R, Robinson M, Kerse N . What is associated with nutrition risk in very old age? J Nutr Health Aging 2011; 15: 247–251.

    CAS  Article  Google Scholar 

  18. 18

    Wham C, Carr R, Heller F . Country of origin predicts nutrition risk among community living older people. J Nutr Health Aging 2011; 15: 253–258.

    CAS  Article  Google Scholar 

  19. 19

    Payette H, Shatenstein B . Determinants of healthy eating in community-dwelling elderly people. Can J Public Health 2005; 96 (Suppl 3), S27–S31.

    PubMed  Google Scholar 

  20. 20

    Dean M, Grunert KG, Raats MM, Nielsen NA, Lumbers M . The impact of personal resources and their goal relevance on satisfaction with food-related life among the elderly. Appetite 2008; 50: 308–315.

    Article  Google Scholar 

  21. 21

    WHO. Obesity preventing and managing the global epidemic. Report of a WHO consultation. World Health Organization: Geneva, 2000.

  22. 22

    Anandacoomarasamy A, Caterson ID, Leibman S, Smith GS, Sambrook PN, Fransen M et al. Influence of BMI on health-related quality of life: comparison between an obese adult cohort and age-matched population norms. Obesity (Silver Spring) 2009; 17: 2114–2118.

    Article  Google Scholar 

  23. 23

    Holmes BA, Roberts CL . Diet quality and the influence of social and physical factors on food consumption and nutrient intake in materially deprived older people. Eur J Clin Nutr 2011; 65: 538–545.

    CAS  Article  Google Scholar 

  24. 24

    Bazzano LA . Dietary intake of fruit and vegetables and risk of diabetes mellitus and cardiovascular diseases [electronic resource]. Background paper for the joint FAO/WHO Workshop on Fruit and Vegetables for Health, 1-3 September 2004, Kobe, Japan.

  25. 25

    Donkin AJM, Johnson AE, Lilley JM, Morgan K, Neale RJ, Page RM et al. Gender and living alone as determinants of fruit and vegetable consumption among the elderly living at home in urban Nottingham. Appetite 1998; 30: 39–51.

    CAS  Article  Google Scholar 

  26. 26

    Johnson AE, Donkin AJM, Morgan K, Neale RJ, Pagf RM, Silburn RL . Fruit and vegetable consumption in later life. Age Ageing 1998; 27: 723–728.

    CAS  Article  Google Scholar 

  27. 27

    Ware JE Jr, Gandek B . Overview of the SF-36 Health Survey and the International Quality of Life Assessment (IQOLA) Project. J Clin Epidemiol 1998; 51: 903–912.

    Article  Google Scholar 

  28. 28

    Greene GW, Fey-Yensan N, Padula C, Rossi S, Rossi JS, Clark PG . Differences in psychosocial variables by stage of change for fruits and vegetables in older adults. J Am Diet Assoc 2004; 104: 1236–1243.

    Article  Google Scholar 

  29. 29

    Moreira P, Padrao P . Educational and economic determinants of food intake in Portuguese adults: a cross-sectional survey. BMC Public Health 2004; 4: 58.

    Article  Google Scholar 

  30. 30

    Naska A, Fouskakis D, Oikonomou E, Almeida MD, Berg MA, Gedrich K et al. Dietary patterns and their socio-demographic determinants in 10 European countries: data from the DAFNE databank. Eur J Clin Nutr 2006; 60: 181–190.

    CAS  Article  Google Scholar 

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The data used in this article belong to the European Project ‘Food in later life. Choosing foods, eating meals: sustaining independence and quality of life’ financed by the European Commission (QLK1CT200202447).

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Correspondence to C de Morais.

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de Morais, C., Oliveira, B., Afonso, C. et al. Nutritional risk of European elderly. Eur J Clin Nutr 67, 1215–1219 (2013).

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  • nutritional risk
  • health
  • living circumstances
  • elderly
  • NSI checklist

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