Abstract
Purpose
A poor appetite affects up to 27% of community-dwelling older adults in Europe and is an early predictor of malnutrition. Little is known about the factors associated with poor appetite. The present study, therefore, aims to characterise older adults with poor appetite.
Methods
As part of the European JPI project APPETITE, data from 850 participants, aged ≥ 70 years of the Longitudinal Ageing Study Amsterdam (LASA) from 2015/16 were analysed. Appetite during the last week was assessed with a five-point scale and dichotomised into "normal" and "poor". Binary logistic regression was used to examine associations between 25 characteristics from 5 domains—physiological, emotional, cognitive, social, and lifestyle—and appetite. First, domain-specific models were calculated using stepwise backward selection. Second, all variables contributing to poor appetite were combined in a multi-domain model.
Results
The prevalence of self-reported poor appetite was 15.6%. Fourteen parameters from all five single-domain models contributed to poor appetite and were entered into the multi-domain model. Here, female sex (total prevalence: 56.1%, odds ratio: 1.95 [95% confidence interval 1.10–3.44]), self-reported chewing problems (2.4%, 5.69 [1.88–17.20]), any unintended weight loss in the last 6 months (6.7%, 3.07 [1.36–6.94]), polypharmacy defined as ≥ 5 medications in the past 2 weeks (38.4%, 1.87 [1.04–3.39]), and depressive symptoms (Centre for Epidemiologic Studies Depression Scale without appetite item) (1.12 [1.04–1.21]) were associated with an increased likelihood of having poor appetite.
Conclusion
According to this analysis, older people with the characteristics described above are more likely to have a poor appetite.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Ageing is often accompanied by a decline in appetite, referred to as anorexia of ageing [1]. Poor appetite is, thus, widespread in the older population and reported in up to 27% of community-dwelling older adults [2,3,4,5]. It is associated with a lower energy and protein intake [2], subsequent weight loss [6], and malnutrition [7]. Poor appetite is also related to adverse health outcomes including impaired physical performance, sarcopenia, frailty, disability, and mortality [8]. These adverse consequences reduce the health and quality of life of older adults and place a burden on the healthcare system [9,10,11].
So far, there is little understanding of the complex network of physiological and non-physiological factors associated with anorexia of ageing. Previous studies reported various cross-sectional associations with variables from five domains: physical, emotional, cognitive, social, and lifestyle. Accordingly, physical factors which can affect appetite include polypharmacy [12, 13], chewing problems [14, 15], functional [16] and sensory impairment [17], poor oral health [16, 18] and chronic pain [19]. Depression is an emotional factor associated with poor appetite in older adults [15, 20,21,22,23]. Cognitive factors such as cognitive impairment and dementia [16, 22] as well as the social factor “living alone” [16] and the lifestyle factors “current smoking” [23] and “poor sleep quality” [24] have also been described in relation to a poor appetite in older adults.
These reported associations are based mainly on group comparisons between normal and poor appetite or are restricted to only a limited number of factors and domains. To the best of our knowledge, only one multivariate analysis regarding the association of a broad range of factors from different domains with appetite in community-dwelling older adults is available [18]. As part of the Health, Ageing and Body Composition Study, Lee et al. (2006) investigated the prevalence of self-reported poor appetite and possible cross-sectional associations with 37 factors in 2,169 well-functioning community-dwelling adults aged 70–79 years in the United States. Poor appetite was reported by 12.0% and significantly associated with symptomatic depression, poor self-reported health status, current smoking, chewing problems, visual impairment, weight loss since age 50 and higher plasma concentration of tumour necrosis factor-α (TNF-α).
A careful characterisation of older community-dwelling adults with a poor appetite will help to identify high-risk groups for poor appetite and develop strategies to improve appetite and prevent malnutrition in older adults. Thus, the present study aimed to characterise community-dwelling older adults with poor appetite comprehensively by examining the associations of poor appetite with a range of factors from the physical, emotional, cognitive, social and lifestyle domains.
Methods
Study design
For the present analyses, existing data from the Longitudinal Ageing Study Amsterdam (LASA) were used. LASA is a prospective cohort study, based on a nationally representative sample of older adults aged 55 to 85 years, which started in 1992 and is still ongoing. The first cohort sample (n = 3805) was randomly selected from municipal registries in three regions in the Netherlands (around Zwolle, Oss, Amsterdam), with an oversampling of the oldest old and men. A second and third cohort were recruited from the same sampling frames 10 and 20 years after the baseline measurements of the first cohort: the second cohort in 2002–2003 (n = 1002), the third in 2012–2013 (n = 1023). The main objective of LASA is to investigate the determinants and consequences of ageing in community-dwelling Dutch older adults [25]. Since the first measurement wave in 1992, information on different themes (biomaterial, care, physical functioning, emotional functioning, cognitive functioning, social functioning, demographics and work) was collected every 3 years. At each measurement wave, the main interview followed by a medical interview after 4–6 weeks were both conducted in the participant’s home. Participants also completed a self-administered questionnaire between the interviews. Commitment to the study was sustained through continuous contact with the participants as well as invitations to lectures and participation in ancillary studies. Details of the study are described elsewhere [25].
Study sample
In the latest LASA wave available (wave I: 2015–2016), 2024 older adults (at least 57 years) participated, 13.1% of the original first cohort (1992), 67.0% of the second (2002–2003) and 83.4% of the third cohort (2012–2013). The reasons for drop-out were mainly mortality and to a lesser extent refusal, ineligibility or no contact [25]. Of the 2,024 participants, 1,012 were aged 70 years or older, of whom 850 had appetite information and were included in the present analysis.
Appetite
Appetite during the last week was assessed during the main interview as part of the Centre for Epidemiologic Studies Depression Scale (CES-D; second item) [26]: “I did not feel like eating, my appetite was poor”. Based on four answer categories (1 “rarely or never”, 2 “some of the time”, 3 “often”, and 4 “most of the time or always”), appetite was dichotomized as normal appetite (1) and poor appetite (2–4) [27].
Participants’ characteristics
Participants’ characteristics were obtained during the main and medical interviews, except chewing problems, present pain, satisfaction with life, and sleep quality, which were asked in the self-administered questionnaire.
Socio-demographic data
Socio-demographic data included age, sex, and education. Education was categorised as high (university, college, or higher vocational education), middle (general secondary education, intermediate and lower vocational education, and general intermediate education), and low (elementary education completed or not completed).
Physical domain
Polypharmacy was defined as the use of ≥ 5 medicines in the past 2 weeks [28]. Based on self-reports of chronic diseases, multimorbidity was defined as the presence of ≥ 2 out of 7 chronic diseases (cardiac disease, peripheral atherosclerosis, stroke, diabetes mellitus, obstructive lung disease, arthritis, cancer). Chewing problems affecting food intake were assessed using the question “Due to chewing or swallowing problems, I eat less” (yes/no). Present pain was asked by a subscale of the Nottingham Health Profile, ranging from 5 to 10 [29], with a score of 5 considered as no pain and 6–10 as pain. Hearing problems were assessed by asking the question “Can you hear well enough?” with four possible answers: 1 “yes, without difficulty”, 2 “yes, with some difficulty”, 3 “yes, with much difficulty”, 4 “no, I cannot” and was dichotomized into no hearing problems (1) and hearing problems (2–4). Self-perceived health was assessed with the question ‘How do you rate your health in general?’ with five answer categories 1 “excellent”, 2 “good”, 3 “fair”, 4 “sometimes good/sometimes poor” and 5 “poor”. Categories were summarised into good (1,2) and fair/poor (3–5). Functional limitations were assessed with a validated questionnaire regarding difficulties with performing activities of daily living (ADL: climbing stairs, dressing, rising from a chair, cutting toenails, walking 5 min outside, using public transportation and bathing) [30] and categorised into none, 1 and ≥ 2 limitations. Physical performance was examined using the Short Physical Performance Battery (SPPB) including a chair stand, tandem stand, and walk test. The scores of each test range from 0 to 4, resulting in a sum score of 0 to 12 [31]. Body weight and height were measured and Body Mass Index (BMI) was calculated as weight (kg) divided by height (m) squared. Unintended weight loss in the last 6 months was derived from the question: “Did your weight change in the last 6 months?” (no change/weight gain/weight loss) and combined with the declaration of an unintentional reason for the weight loss. Hospital admission was assessed by asking “Have you been hospitalised in the last six months?” (yes/no).
Emotional domain
Anxiety symptoms were measured with the Anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A) ranging from 0 to 21 [32], and depressive symptoms were measured using the CES-D excluding the appetite item in the total score resulting in a possible score ranging from 0 to 57, with higher scores representing more symptoms [26, 33]. To assess satisfaction with life, the question “How satisfied are you with your life lately?” was asked. The answer categories 1 “very dissatisfied”, 2 “dissatisfied”, 3 “not dissatisfied/satisfied”, 4 “satisfied”, 5 “very satisfied” were summarised into dissatisfied (1,2), not dissatisfied/satisfied (3) and satisfied (4–5).
Cognitive domain
Cognitive functioning was measured using the Mini-Mental State Examination (MMSE). The MMSE score ranges from 0 to 30 with scores of ≤ 23 indicating cognitive impairment [34]. Memory complaints were assessed by self-report “Do you have complaints about your memory?” (yes/no).
Social domain
Loneliness was assessed by asking the question “I sometimes feel lonely” with the answer categories “no”, “more or less” and “yes”. Household size was asked by the questions “Besides yourself, how many other people are part of your household?” and dichotomised to “living with others” (≥ 1 person/s in the household) and “living alone” (no other person in the household). Further, social network size (count of “the people with whom you are in touch regularly and who are important to you”) was asked. The emotional support received is the mean of the stated support by each person identified in the social network (“you told … about your personal experiences and feelings”; a score of 0: no support to 3: often supported), and the number of confidants identified from the persons in the social network were assessed as well.
Lifestyle domain
Current smoking (yes/no) was recorded by asking the question “Do you smoke?”. The consumption of alcohol was assessed according to the Garretsen Indication of present alcohol use: 0 “does not drink”, 1 “light”, 2 “moderate”, 3 “excessive”, 4 “very excessive” [35] and categorised into non-drinker and drinker. Data on physical activity were obtained using the LASA Physical Activity Questionnaire, where physical activity is reported in min/day [36]. Sleep quality was assessed by asking the question “How would you assess the quality of your sleep over the last month?” with the answer categories 1 “very good”, 2 “somewhat good”, 3 “somewhat bad” or 4 “very bad”. The variable was dichotomised into good (1,2) or poor (3,4) sleeping quality.
Statistical analysis
All variables are described as the median and interquartile range (P25, P75) (continuous variables) or relative frequencies (categorical variables) according to appetite. Differences between participants with normal and poor appetite were analysed using Mann–Whitney U test or Chi2-test. In addition, the percentage of participants with poor appetite in each variable category was calculated.
In an exploratory approach, associations between participants’ characteristics within each of the five domains and poor appetite were examined by logistic regression analyses. Complete-case analysis was used to cope with missing data. First, for each domain, a binary logistic regression model was established with all potential domain-specific explanatory variables and adjusted for sex, age and education. Backward elimination was employed to find the most parsimonious model based on the likelihood ratio test (variable entry with p-value < 0.05, variable removal with p-value < 0.10). By nature of this method, only variables that contribute to the outcome remained in the final models. These variables were then combined in one multi-domain model without variable selection. A p-value of < 0.05 was considered a statistically significant result. Statistical analysis was performed using SPSS version 26.0 (IBM, Munich, Germany).
Results
Prevalence of poor appetite
Of the 850 participants, 6 reported a poor appetite "mostly or always", 27 "occasionally" and 100 "some of the time" in the last week. The overall prevalence of poor appetite was 15.6%.
Participants’ characteristics
The median age of the sample was 77.4 (73.7, 83.3) years, the median BMI was 26.7 (24.4, 29.5) kg/m2; 56.1% were female, 47.9% were multimorbid, 36.9% perceived their health as fair/poor, 38.4% reported memory complaints and 39.6% were living alone.
Participants´ characteristics are presented in Table 1 by appetite. Participants with normal and poor appetite differed significantly in all characteristics except BMI, social network size, emotional support received, number of confidants and physical activity level (Table 1). Poor appetite was particularly common amongst those who reported chewing problems (55.0%), unintentional weight loss in the last 6 months (35.1%) and sometimes feeling lonely (33.9%). In addition, more than one-fourth of participants with reduced cognitive function, hospitalisation in the last 6 months, dissatisfaction with life, poor self-perceived health, poor sleep quality and smoking reported poor appetite.
Factors associated with poor appetite
From 25 variables from 5 domains plus 3 covariates, 14 variables and 2 covariates were explanatory of poor appetite and were entered into the final, multi-domain model. From each domain, at least one variable went into the final model. Amongst the covariates, female sex was explanatory of reduced appetite in all single-domain models, age in the emotional and lifestyle domain models, and education in none of the models. Detailed results of the single-domain models can be found in the supplementary table S1.
In the multi-domain model, female sex, polypharmacy, chewing problems, unintended weight loss in the last 6 months, and depressive symptoms were associated with poor appetite (Table 2). The odds of poor appetite were over five times higher in those reporting chewing problems and three times higher in those reporting unintentional weight loss in the last 6 months. Due to missing values, 181 participants had to be excluded from this model. Participants excluded from the final model were significantly more likely to report poor appetite, were significantly older, and reported sometimes feeling lonely, poor subjective health as well as poor cognitive and functional status more often than those included (table S2).
Discussion
In the current cross-sectional analysis of data from Dutch community-dwelling adults aged 70 years and older, out of 25 variables from 5 domains and 3 covariates female sex, the variables polypharmacy, chewing problems, unintended weight loss in the last 6 months, and depressive symptoms were significantly associated with poor appetite.
Poor appetite was present in 15.6% of the participants with the majority reporting this feeling only some of the time and less than 1% mostly or always. This overall prevalence lies in the middle of the range of prevalence rates previously reported in community-dwelling older adults in Europe [15, 37]. Differences between the above-mentioned studies may be due to different population characteristics or different appetite assessment methods.
In group difference tests, 22 of 28 variables from all domains were associated with poor appetite (Table 1). Interestingly, BMI was not associated with poor appetite. An association between poor appetite and lower BMI was described in community-dwelling older adults which disappeared, however, after age adjustment [38]. Lee et al. reported a significant group difference, but no association in the multivariate analysis [18]. Notably, poor appetite does not necessarily lead to reduced food intake and consequently to a lower BMI. Similarly, physical activity levels did not differ between participants with normal and poor appetite although one might assume a mutual influence, and an association was observed in previous studies [18, 23, 38]. This might be partly explained by the complexity of assessing physical activity. Regarding social factors, social network characteristics did not differ between the groups with poor and normal appetite, whilst sometimes feeling lonely as well as living alone were associated with poor appetite. Thus, the subjective feeling of loneliness and lack of company whilst eating seem more relevant to appetite than the size of the social network.
In the multi-domain model, as in all single-domain models, female sex was significantly associated with poor appetite, which is in line with previous research in community-dwelling older adults [18, 22, 37] and institutionalised older adults [39]. The sex difference could not be explained by older age or higher prevalence of depression in women in our study. In contrast to our results, in a mixed population from different settings, males more often reported having a poor appetite [15]. The association of polypharmacy and poor appetite in the present study has not been reported before in community-dwelling older adults. Poor appetite is a known side effect of some drugs [39] that could be magnified by polypharmacy [40]. In contrast, Landi et al. reported no significant association of poor appetite with the number of drugs taken by nursing home residents aged 65+ years [41]. Future research needs to further examine the possible link between polypharmacy and poor appetite in community-dwelling older adults. Participants with chewing problems were most likely to have poor appetite (Table 2). This is in line with results from previous studies reporting associations between chewing pain [15], chewing efficiency [18] as well as chewing capacity [14] and poor appetite; however, the low prevalence of chewing problems in our sample must be taken into account. More important, when interpreting this association, the assessment method and the consequent possible overlap of the variable with poor appetite should be kept in mind. Chewing problems were assessed via the statement “Due to chewing or swallowing problems, I eat less” and are, therefore, not assessed independently, but in the context of eating less. The resulting possible overlap with the question on poor appetite may lead to an overestimation of the association between the two variables. Unintended weight loss in the last 6 months was also associated with poor appetite. Lee et al. reported an association between weight loss since the age of 50 with poor appetite [18]. Further studies are needed to better understand both the link and the direction of the association. Depressive symptoms were also associated with poor appetite, which is plausible since poor appetite is a well-known concomitant of depression and is one of the 20 criteria to assess depressive symptoms according to the CES-D. In the present analysis, the appetite item was removed from the CES-D score to avoid overlap and methodological interrelations. In the group with poor appetite, without the appetite item included in the scale, the median score was exactly the cut-point of 16, reflecting individuals at risk for clinical depression. The association of depression and depressive symptoms with poor appetite has been reported in several previous studies in community-dwelling [15, 18, 22, 23] and institutionalised [20, 21, 41] older adults.
Interestingly, age, multimorbidity, present pain, fair/poor self-perceived health, anxiety symptoms, reduced cognitive function and memory complaints, sometimes feeling lonely, alcohol consumption, smoking and poor sleep quality were all significantly associated with poor appetite in the single-domain models, but no longer in the final multi-domain model, despite plausible theoretical connections and some evidence of associations with poor appetite in previous studies [18, 19, 22, 24, 42, 43]. Data on anxiety in the context of anorexia of ageing are largely lacking. In the present study, the multivariate analysis showed a borderline significant association. In the group comparison and the single-domain model, higher anxiety symptoms were significantly associated with poor appetite. Lee et al. also observed a significant group difference in anxiety; however, an association was not observed in the multivariate analysis [18]. According to previous research, community-dwelling older adults of a higher age are more likely to report poor appetite [18, 22, 23]. A meta-analysis from Gienzaar et al. of the associations between ageing and decreases in appetite and energy intake in 2016 reported that appetite is reduced in healthy older adults compared with younger adults [43]. However, this association was neither evident in the regression analysis of the final model of the present study nor the regression analysis of Lee et al. [18]. Since these were restricted to people aged at least 70 years, it could be that the association diminishes or disappears at older ages or that the association disappeared due to the adjustment for a variety of age-related variables which might be more relevant than age per se. Cognitive, social and lifestyle factors were not associated with poor appetite in the final multivariate analysis of the present study (Table 2), and therefore seem to be less relevant according to our analyses. Regarding cognitive function, however, there is evidence from group comparisons [15, 22, 23] and one multivariate analysis [42] suggesting a link between reduced cognitive function and poor appetite. Possibly, this association may be dependent on the severity of cognitive impairments. Loneliness might adversely affect appetite via depressed mood [44]. In the present study, sometimes feeling lonely was significantly associated with poor appetite in the group difference test and the social domain model, but no longer associated in the multi-domain model. Previous studies observed that older adults who always eat alone [18] or live alone [45] are more likely to report poor appetite. Regarding lifestyle factors, consistent with the results of the present analysis, no significant association between alcohol consumption and poor appetite has been found so far [2, 23]. A possible link between sleep quality and appetite in older adults has only been examined in a study from Japan [24].
Overall, it can be summarised that despite different variables, domains and statistical approaches, our results are largely consistent with the multivariable analysis from Lee et al. [18]: female sex, weight loss, fair/poor self-perceived health and chewing problems from the physical domain, as well as depression from the emotional domain, were significantly associated with poor appetite in both analyses. In addition, we found polypharmacy associated with poor appetite and Lee et al. smoking, TNF-α, and visual impairment, the latter two variables unfortunately not being available in our dataset.
Strengths and limitations
The analysis conducted had notable strengths. A large number of variables from important areas of life were assessed in a large sample of European older adults. Five different domains were analysed separately to allow the identification of relevant domain-specific factors. The analysis also evaluated more recent data compared to the only comparable multivariate analysis from Lee et al., 2006 [18].
Several potential limitations of this study should, however, also be addressed. First, in this secondary data analysis, available information was restricted to a limited number of variables with given answer categories that were not tailored to our research question. Further, due to missing values and the nature of the complete case analysis, we were not able to analyse the full sample of 850 participants in the final logistic regression model and a selection bias must be assumed. The subpopulation excluded from the single-domain models as well as the final model due to missing values was significantly older, and more functionally impaired, and thus our sample was not representative of all community-dwelling older adults. Our prevalence rate of poor appetite and the observed associations may have been underestimated. Further, this cross-sectional analysis does not allow any conclusions about intra-individual variations or the causality of the associations. Lastly, in this analysis, appetite was assessed with a single, self-reported and oriented question with only four answer categories, addressing the frequency of poor appetite in the last week. In older adults, Likert Scale or Visual Analogue Scale methods are mostly used [46]. Unfortunately, data from these methods were not included in the LASA dataset. It is up to future studies to assess appetite more comprehensively, e.g. via SNAQ and potentially add objective measures (appetite-related hormones, ad-libitum test meal). Comparisons of the present study with other studies on appetite in older adults must be interpreted cautiously due to the different ways in which appetite is assessed.
Conclusion
The prevalence of self-reported poor appetite in the present analysis was 15.6%. The multivariate analysis of 28 variables from several domains contributes to the limited knowledge in the field of poor appetite in community-dwelling older adults in Europe. Older persons with a poor appetite were characterised by female sex, polypharmacy, chewing problems, unintentional weight loss in the last 6 months and depressive symptoms. The results highlight the complexity of appetite regulation in older people, where factors from different domains are involved.
In clinical practice, the nutritional status of patients with at least one of the above-mentioned characteristics should be closely monitored as these characteristics may indicate a poor appetite, and thus an increased risk of malnutrition.
Data availability
Data from the Longitudinal Ageing Study Amsterdam (LASA) are available for use for specific research questions, provided that an agreement is made up. Research proposals should be submitted to the LASA Steering Group, using a standard analysis proposal form that can be obtained from the LASA website: www.lasa-vu.nl. Files with data published in this publication are freely available for replication purposes and can be obtained using the same analysis proposal form. The LASA Steering Group will review all requests for data to ensure that proposals for the use of LASA data do not violate privacy regulations and are in keeping with informed consent that is provided by all LASA participants.
Abbreviations
- ADL:
-
Activities of daily living
- BMI:
-
Body Mass Index
- CES-D:
-
Centre for Epidemiologic Studies Depression Scale
- HADS-A:
-
Hospital Anxiety and Depression Scale
- LASA:
-
Longitudinal Ageing Study Amsterdam
- MMSE:
-
Mini-Mental State Examination
- SNAQ:
-
Simplified Nutritional Appetite Questionnaire
- SPPB:
-
Short Physical Performance Battery Test (SPPB)
- TNF-α:
-
Tumour Necrosis Factor alpha
References
Morley JE, Silver AJ (1988) Anorexia in the elderly. Neurobiol Aging 9:9–16. https://doi.org/10.1016/s0197-4580(88)80004-6
van der Meij BS, Wijnhoven HAH, Lee JS et al (2017) Poor appetite and dietary intake in community-dwelling older adults. J Am Geriatr Soc 65:2190–2197. https://doi.org/10.1111/jgs.15017
van der Meij BS, Wijnhoven HAH, Finlayson GS et al (2015) Specific food preferences of older adults with a poor appetite. A forced-choice test conducted in various care settings. Appetite 90:168–175. https://doi.org/10.1016/j.appet.2015.03.011
Cox NJ, Morrison L, Ibrahim K et al (2020) New horizons in appetite and the anorexia of ageing. Age Ageing 49:526–534. https://doi.org/10.1093/ageing/afaa014
Hung Y, Wijnhoven HAH, Visser M et al (2019) Appetite and Protein Intake Strata of Older Adults in the European Union: Socio-Demographic and Health Characteristics. Nutrients, Diet-Related and Physical Activity Behaviours. https://doi.org/10.3390/nu11040777
Wilson M-MG, Thomas DR, Rubenstein LZ et al (2005) Appetite assessment: simple appetite questionnaire predicts weight loss in community-dwelling adults and nursing home residents. Am J Clin Nutr 82:1074–1081. https://doi.org/10.1093/ajcn/82.5.1074
Malafarina V, Uriz-Otano F, Gil-Guerrero L et al (2013) The anorexia of ageing: physiopathology, prevalence, associated comorbidity and mortality. A syst review Mat 74:293–302. https://doi.org/10.1016/j.maturitas.2013.01.016
Landi F, Calvani R, Tosato M et al (2016) Anorexia of aging: risk factors, consequences, and potential treatments. Nutrients 8:69. https://doi.org/10.3390/nu8020069
Buckinx F, Rolland Y, Reginster J-Y et al (2015) Burden of frailty in the elderly population: perspectives for a public health challenge. Arch Public Health 73:19. https://doi.org/10.1186/s13690-015-0068-x
Cruz-Jentoft AJ, Bahat G, Bauer J et al (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48:16–31. https://doi.org/10.1093/ageing/afy169
Rodríguez-Sánchez B, Sulo S, Carnicero JA et al (2020) Malnutrition Prevalence and Burden on Healthcare Resource Use Among Spanish Community-Living Older Adults: Results of a Longitudinal Analysis. Clin Outcom Res 12:355–367. https://doi.org/10.2147/CEOR.S256671
Kose E, Wakabayashi H, Yasuno N (2021) Polypharmacy and malnutrition management of elderly perioperative patients with cancer a systematic review. Nutrients. https://doi.org/10.3390/nu13061961
Morley JE (2012) Anorexia of aging: a true geriatric syndrome. J Nutr Health Aging 16:422–425. https://doi.org/10.1007/s12603-012-0061-9
Takehara S, Hirani V, Wright FAC et al (2021) Appetite, oral health and weight loss in community-dwelling older men: an observational study from the Concord Health and ageing in Men Project (CHAMP). BMC Geriatr 21:255. https://doi.org/10.1186/s12877-021-02169-y
Donini LM, Dominguez LJ, Barbagallo M et al (2011) Senile anorexia in different geriatric settings in Italy. J Nutr Health Aging 15:775–781. https://doi.org/10.1007/s12603-011-0048-y
Landi F, Liperoti R, Lattanzio F et al (2012) Effects of anorexia on mortality among older adults receiving home care: an observation study. J Nutr Health Aging 16:79–83. https://doi.org/10.1007/s12603-011-0064-y
Seubert J, Laukka EJ, Rizzuto D et al (2017) Prevalence and Correlates of Olfactory Dysfunction in Old Age: A Population-Based Study. J Gerontol A Biol Sci Med Sci 72:1072–1079. https://doi.org/10.1093/gerona/glx054
Lee JS, Kritchevsky SB, Tylavsky F et al (2006) Factors associated with impaired appetite in well-functioning community-dwelling older adults. J Nutr Elder 26:27–43. https://doi.org/10.1300/J052v26n01_02
Bosley BN, Weiner DK, Rudy TE et al (2004) Is chronic nonmalignant pain associated with decreased appetite in older adults? Preliminary evidence. J Am Geriatr Soc 52:247–251. https://doi.org/10.1111/j.1532-5415.2004.52063.x
Engel JH, Siewerdt F, Jackson R et al (2011) Hardiness, depression, and emotional well-being and their association with appetite in older adults. J Am Geriatr Soc 59:482–487. https://doi.org/10.1111/j.1532-5415.2010.03274.x
Aprahamian I, Romanini CV, Lima NA et al (2021) The concept of anorexia of aging in late life depression: A cross-sectional analysis of a cohort study. Arch Gerontol Geriatr 95:104410. https://doi.org/10.1016/j.archger.2021.104410
Vázquez-Valdez OE, Aguilar-Navarro S, Avila-Funes JA (2010) Association between anorexia of aging and disability in older community-dwelling Mexicans. J Am Geriatr Soc 58:2044–2046. https://doi.org/10.1111/j.1532-5415.2010.03095.x
Tsutsumimoto K, Doi T, Nakakubo S et al (2020) Association between anorexia of ageing and sarcopenia among Japanese older adults. J Cachexia Sarcopenia Muscle 11:1250–1257. https://doi.org/10.1002/jcsm.12571
Yamamoto K, Motokawa K, Yoshizaki T et al (2020) Association of dietary variety and appetite with sleep quality in urban-dwelling older Japanese adults. J Nutr Health Aging 24:152–159. https://doi.org/10.1007/s12603-019-1297-4
Hoogendijk EO, Deeg DJH, de Breij S et al (2020) The longitudinal aging study Amsterdam: cohort update 2019 and additional data collections. Eur J Epidemiol 35:61–74. https://doi.org/10.1007/s10654-019-00541-2
Radloff LS (1977) The CES-D Scale. Appl Psychol Meas 1:385–401. https://doi.org/10.1177/014662167700100306
Wijnhoven HAH, Schilp J, van Bokhorst-de Schueren MAE et al (2012) Development and validation of criteria for determining undernutrition in community-dwelling older men and women: the short nutritional assessment questionnaire 65+. Clin Nutr 31:351–358. https://doi.org/10.1016/j.clnu.2011.10.013
Masnoon N, Shakib S, Kalisch-Ellett L et al (2017) What is polypharmacy? A systematic review of definitions. BMC Geriatr 17:230. https://doi.org/10.1186/s12877-017-0621-2
Heim N, Snijder MB, Deeg DJH et al (2008) Obesity in older adults is associated with an increased prevalence and incidence of pain. Obesity (Silver Spring) 16:2510–2517. https://doi.org/10.1038/oby.2008.407
Kriegsman DM, Deeg DJ, van Eijk JT et al (1997) Do disease specific characteristics add to the explanation of mobility limitations in patients with different chronic diseases? A study in The Netherlands. J Epidemiol Communi Health 51:676–685. https://doi.org/10.1136/jech.51.6.676
Guralnik JM, Simonsick EM, Ferrucci L et al (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 49:M85-94. https://doi.org/10.1093/geronj/49.2.m85
de Koning EJ, Verweij L, Lips P et al (2017) The relationship between serum 25(OH)D levels and anxiety symptoms in older persons: results from the longitudinal aging study Amsterdam. J Psychosom Res 97:90–95. https://doi.org/10.1016/j.jpsychores.2017.04.005
Brailean A, Comijs HC, Aartsen MJ et al (2016) Late-life depression symptom dimensions and cognitive functioning in the Longitudinal Aging Study Amsterdam (LASA). J Affect Disord 201:171–178. https://doi.org/10.1016/j.jad.2016.05.027
Wind AW, Schellevis FG, van Staveren G et al (1997) Limitations of the mini-mental state examination in diagnosing dementia in general practice. Int J Geriat Psychiatry 12:101–108. https://doi.org/10.1002/(sici)1099-1166(199701)12:1%3c101:aid-gps469%3e3.0.co;2-r
Bongers IM, van Oers HA, van de Goor IA et al (1997) Alcohol use and problem drinking: prevalences in the general Rotterdam population. Subst Use Misuse 32:1491–1512. https://doi.org/10.3109/10826089709055874
Stel VS, Smit JH, Pluijm SMF et al (2004) Comparison of the LASA Physical activity questionnaire with a 7-day diary and pedometer. J Clin Epidemiol 57:252–258. https://doi.org/10.1016/j.jclinepi.2003.07.008
Reijnierse EM, Trappenburg MC, Leter MJ et al (2015) The association between parameters of malnutrition and diagnostic measures of sarcopenia in geriatric outpatients. PLoS ONE 10:0135933. https://doi.org/10.1371/journal.pone.0135933
Chang M, Geirsdottir OG, Launer LJ et al (2021) A poor appetite or ability to eat and its association with physical function amongst community-dwelling older adults: age, gene/environment susceptibility-Reykjavik study. Eur J Ageing 18:405–415. https://doi.org/10.1007/s10433-020-00588-1
Visvanathan R, Chapman IM (2009) Undernutrition and anorexia in the older person. Gastroenterol Clin North Am 38:393–409. https://doi.org/10.1016/j.gtc.2009.06.009
Fitzgerald SP, Bean NG (2010) An analysis of the interactions between individual comorbidities and their treatments–implications for guidelines and polypharmacy. J Am Med Dir Assoc 11:475–484. https://doi.org/10.1016/j.jamda.2010.05.008
Landi F, Lattanzio F, Dell’Aquila G et al (2013) Prevalence and potentially reversible factors associated with anorexia among older nursing home residents: results from the ULISSE project. J Am Med Dir Assoc 14:119–124. https://doi.org/10.1016/j.jamda.2012.10.022
Potter GG, McQuoid DR, Steffens DC (2015) Appetite loss and neurocognitive deficits in late-life depression. Int J Geriatr Psychiatry 30:647–654. https://doi.org/10.1002/gps.4196
Giezenaar C, Chapman I, Luscombe-Marsh N et al (2016) ageing is associated with decreases in appetite and energy intake–a meta-analysis in healthy adults. Nutrients. https://doi.org/10.3390/nu8010028
Eskelinen K, Hartikainen S, Nykänen I (2016) Is loneliness associated with malnutrition in older people? Int J Gerontol 10:43–45. https://doi.org/10.1016/j.ijge.2015.09.001
Ramic E, Pranjic N, Batic-Mujanovic O et al (2011) The effect of loneliness on malnutrition in elderly population. Med Arh 65:92–95
Cox NJ, Ibrahim K, Sayer AA et al (2019) Assessment and treatment of the anorexia of aging: a systematic review. Nutrients. https://doi.org/10.3390/nu11010144
Acknowledgements
Preliminary results of this analysis have been presented as posters at the European Society of Clinical Nutrition and Metabolism (ESPEN) congress in Vienna (03.-06.09.2022), publication in Clinical Nutrition ESPEN is pending, and in German at the online congress of the German Nutrition Society (DGE) (16.-18.03.2022) https://www.dge.de/fileadmin/public/doc/wk/2022/DGE-Proc-Germ-Nutr-Soc-Vol-28-2022.pdf. The present work was performed in partial fulfilment of the requirements for obtaining the degree Dr. rer. biol. hum (Doctoral Degree in Human Biology) for Pia Scheufele.
Funding
Open Access funding is enabled and organised by Projekt DEAL. None of the authors of this study received extra funding. This study is part of the Joint Programming Initiative (JPI) project APPETITE. This work was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE), grant number 2820ERA18E. The Longitudinal Ageing Study Amsterdam is supported by a grant from the Netherlands Ministry of Health Welfare and Sports, Directorate of Long-Term Care.
Author information
Authors and Affiliations
Contributions
PS was the lead author of the manuscript, analysed, and interpreted the data. AR, MV, EK and DV contributed to the data analysis plan and interpretation of findings and critically reviewed and approved the final manuscript version. DV supervised the project.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval and consent to participate
The LASA study has been approved by the Medical Ethics Committee of the Vrije University Medical Centre (VUmc) (IRB numbers: 92/138, 2002/141, 2012/361, and 2016.301) and has, therefore, been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. All participants gave their informed consent prior to their inclusion in the LASA study.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Scheufele, P., Rappl, A., Visser, M. et al. Characterisation of community-dwelling older adults with poor appetite. Eur J Nutr 62, 1991–2000 (2023). https://doi.org/10.1007/s00394-023-03129-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00394-023-03129-5