Journal of Immunology Research
Volume 2019 (2019), Article ID 3128231, 8 pages
https://doi.org/10.1155/2019/3128231

Research Article

The Association of Olfactory Dysfunction, Frailty, and Mortality Is Mediated by Inflammation: Results from the InCHIANTI Study

Alice Laudisio,¹ Luca Navarini,² Domenico Paolo Emanuele Margiotta,² Davide Onofrio Fontana,¹ Irene Chiarella,¹ Daniele Spitaleri,¹ Stefania Bandinelli,³ Antonella Gemma,⁴ Luigi Ferrucci,⁵ and Raffaele Antonelli Incalzi¹

¹Unit of Geriatrics, Department of Medicine, Università Campus Bio-Medico, Rome, Italy
²Unit of Allergology, Immunology, Rheumatology, Department of Medicine, Università Campus Bio-Medico, Rome, Italy
³Geriatric Rehabilitation Unit, Azienda Sanitaria di Firenze, Florence, Italy
⁴Department of Homecare Service, Azienda Sanitaria Locale Roma E, Rome, Italy
⁵Longitudinal Studies Section, Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, USA

Correspondence should be addressed to Alice Laudisio; lavoralice@gmail.com

Received 25 May 2018; Accepted 29 November 2018; Published 20 February 2019

Academic Editor: Ilaria Roato

Copyright © 2019 Alice Laudisio et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Background. Olfactory dysfunction might unveil the association between ageing and frailty, as it is associated with declining cognitive function, depression, reduced physical performance, reduced dietary intake, and mortality; all these conditions are characterized by increased levels of inflammatory parameters. The present study is aimed at evaluating the association between olfactory dysfunction, frailty, and mortality and whether such association might be mediated by inflammation. Methods. We analysed data of 1035 participants aged 65+ enrolled in the “InCHIANTI” study. Olfactory function was tested by the recognition of the smells of coffee, mint, and air. Olfactory dysfunction was defined as lack of recognition of at least two smells. Considering the items “shrinking,” “exhaustion,” “sedentariness,” “slowness,” and “weakness” included in the Fried definition, frailty was defined as the presence of at least three criteria, prefrailty of one or two, and robustness of none. Serum interleukin-6 (IL-6) was measured in duplicate by high-sensitivity enzyme-linked immunosorbent assays. Logistic regression was adopted to assess the association of frailty with olfactory function, as well as with the increasing number of olfactory deficits. Cox regression was used to test the association between olfactory dysfunction and 9-year survival. Results. Olfactory dysfunction was associated with frailty, after adjusting (OR 1.94, 95% -3.51; ); analysis of the interaction term indicated that the association varied according to interleukin-6 levels ( for ). Increasing levels of olfactory dysfunction were associated with increasing probability of being frail. Also, olfactory dysfunction was associated with reduced survival (HR 1.52, 95% -1.98; ); this association varied according to the presence of frailty ( for ) and prefrailty status ( for ), as well as increased interleukin-6 levels ( for interaction = .011). Conclusions. Impairment of olfactory function might represent a marker of frailty, prefrailty, and consequently reduced survival in an advanced age. Inflammation might represent the possible link between these conditions.

1. Introduction

Due to its prevalence rates exceeding 50% among individuals aged 65-80 years and reaching 80% above the age of 80, olfaction dysfunction is considered a very common problem in older populations [1]. This sensory deficit has important implications for safety, nutrition, quality of life, and social relationships [2]. Olfactory impairment is partially age-related and reflects either central neurodegenerative mechanisms or peripheral cumulative damage of olfactory receptors [1]. In fact, the olfactory system is the only sense which depends upon stem cell turnover, and the olfactory nerve is the only cranial nerve directly exposed to the environment [1].

Frailty is an age-related condition of increased vulnerability, associated with higher risk of several adverse outcomes, including mortality [3]. Among different criteria proposed to define frailty, the frailty phenotype proposed by Fried and colleagues is among the most commonly adopted [4]; also, prefrailty status has been associated with reduced survival, as compared with robustness [3]. Indeed, frailty can be attenuated and even reversed, so that this syndrome has to be considered a dynamic process, mainly for subjects in their intermediate stage [5]. In an Italian cohort of elderly people, although most participants tended to retain their baseline frailty status, more than one-third of the sample experienced a transition (with either improvement or worsening) in their frailty status over a four-year follow-up [6].

It has been documented that sensory perception, including smell perception, is associated with several components of frailty [7]. On the other hand, it has been acknowledged that both frailty and olfactory loss are associated with reduced survival [3, 8]. Furthermore, both olfactory impairment and frailty are characterized by subclinical inflammation, which could partially explain the adverse outcomes associated with these two conditions.

Olfactory impairment, but not hearing or visual impairment, has been associated with decreased survival in older subjects [9]. However, to our knowledge, neither the association of olfactory impairment with prefrailty nor the impact of frailty phenotypes on the association between olfactory dysfunction and mortality has been so far investigated.

The aim of this study was to assess in an older population the association, if any, of olfactory dysfunction with frailty and mortality and whether such an association might be mediated by frailty status.

2. Methods

2.1. Study Design and Participants

The present study is based upon the data from the “Invecchiare in Chianti” study, a prospective population-based study of older persons in Tuscany, Italy, that is aimed at identifying risk factors for late-life disability [10]. The Italian National Research Council on Aging Ethical Committee ratified the study protocol, and participants provided written consent to participate.

Analyses for this study included all 1035 subjects aged 65+.

2.2. Frailty

Frailty was defined according to the Fried criteria [4]: unintended weight loss, self-reported exhaustion, muscle weakness, slowness, and sedentariness. Weight loss was defined as self-reported unintentional weight within the past year. Exhaustion was defined as a response of “occasionally,” “often,” or “always” to the statement “I felt that everything was an effort.” Muscle weakness was defined as grip strength in the lowest quintile, stratified by sex and BMI quartiles. Grip strength was measured by a handheld dynamometer (Nicholas Muscle Tester, Sammons Preston Inc.). Slowness was defined as the time to walk 4.57 meters or 15 ft (the mean of 2 repetitions) in the slowest quintile, stratified by sex and height. Sedentariness was defined as either complete inactivity or spending <1 h/wk performing low-intensity activities. “Frailty” was defined as the presence of at least three criteria, “prefrailty” of one or two criteria, and “robustness” of none.

This syndrome is thought to emerge from multisystem dysregulation that is common in older adults and characterized by increased vulnerability to stressors and increased risk of disease, disability, and death. Also, frailty is linked to multimorbidity and inflammation.

2.3. Mortality

Data on 9-year mortality were collected using the data from the Mortality General Registry maintained by the Tuscany Region, as well as death certificates delivered immediately after death to the registry office of the municipality of residence.

2.4. Olfactory Function

Olfactory function was self-reported and explored during the medical visit according to the questions: “Does he/she recognize mint?”, “does he/she recognize coffee?”, and “does he/she recognize air?”. Olfactory dysfunction was defined when at least two smells were not recognized. Increasing levels of olfactory impairment (0 to 3 smell losses) were also considered.

2.5. Inflammation

Blood samples were drawn in the morning after a 12-hour overnight fast and resting period. Aliquots of serum were stored at −80°C. Serum interleukin-6 (IL-6) was measured in duplicate by high-sensitivity enzyme-linked immunosorbent assays (ELISAs; kits from BioSource, Camarillo, CA) with a sensitivity of 0.1 pg/mL and an intra-assay coefficient of variations less than 6%.

2.6. Covariates

Data on dietary intake were collected by the questionnaire created for the European Prospective Investigation into Cancer and Nutrition (EPIC) study [11]. Adjudicated disease diagnoses were based on self-reported history, clinical documentation, and medication use, as well as standardized criteria derived from the Women’s Health and Aging Study protocol [12]. Comorbidity was quantified using the Charlson Comorbidity Index score [13]. All drugs assumed by participants were coded according to the Anatomical Therapeutic Chemical codes [14]. Functional ability was estimated using Katz’s activities of daily living [15], depressive symptoms by the original 20-item version of the Center for Epidemiological Studies Depression Scale (CES-D) [16], and cognitive performance by the Mini Mental State Examination [17]. Blood samples were obtained from participants after 12-hour fasting and after resting for at least 15 minutes. Aliquots of serum were stored at –80°C and were not thawed until analysis. Interleukin-6 concentrations were determined by high-sensitivity ELISA using commercial kits (Human Ultrasensitive, BioSource International Inc., Camarillo, CA, USA). Glomerular filtration rate was estimated using the Cockcroft-Gault equation.

2.7. Statistical Analyses

Data were recorded using dedicated software. Statistical analyses were performed using Statistical Package for the Social Sciences (SPSS for Mac version 20.0, 2011, SPSS Inc., Chicago, IL); differences were considered significant at the level.

Data of continuous variables are presented as mean deviation or medians and interquartile ranges. Normally distributed variables according to olfactory dysfunction, as well as to mortality, were assessed by the analysis of variance (ANOVA) or the nonparametric Mann–Whitney test if appropriate. The two-tailed Fisher exact test was used for dichotomous variables.

Multivariable logistic regression was used to evaluate the association of the frailty phenotype with age, sex, and all those variables which differed significantly in univariate analysis, including olfactory dysfunction.

The fully adjusted model was also adopted to evaluate the association of increasing levels of olfactory dysfunction with frailty. Also, the analysis of the interaction terms “olfactory dysfunctioninterleukin-6” was performed to assess whether the association of frailty with olfactory dysfunction varied according to inflammation.

In addition, to evaluate the whole spectrum of the frailty phenotype, the same summary model was analysed in multinomial logistic regression having robustness, prefrailty, and frailty as the dependent variables.

Also, Cox proportional hazard regression analysis was used to estimate the association of mortality with age, sex, and all those variables which differed significantly in univariate analysis, including olfactory dysfunction. Eventually, in Cox regression, the analysis of the interaction terms “olfactory dysfunctionfrailty,” “olfactory dysfunctionprefrailty,” and “olfactory dysfunctioninterleukin-6,” was performed to assess whether the association between reduced survival and olfactory dysfunction varied according to the presence of frailty, prefrailty, and inflammatory status.

3. Results

The main characteristics of 1035 participants according to olfactory dysfunction are depicted in Table 1. Frailty was diagnosed in 111 (11%) subjects, prefrailty in 420 (41%) participants, and robustness in 504 (48%). The main characteristics of subjects according to frailty are shown in Table 2.

Table 1: Characteristics of 1035 participants according to olfactory dysfunction.

Presence of olfactory dysfunction ()
Absence of olfactory dysfunction ()

Demographics & lifestyle habits, (%), mean (SD), or median (IQR)

Age (years)
76 (8)
73 (7)
<.001

Sex (female)
315 (53)
262 (59)
.088

Education (years)
5 (3)
6 (3)
.003

Living alone
241 (41)
164 (37)
.199

Smoking (former and current)
253 (43)
170 (38)
.142

Dietary intake

Alcohol (g/day/kg)
0.11 (0–0.29)
0.10 (0–0.31)
.594

Total protein intake (g/day/kg)
1.12 (0.33)
1.13 (0.31)
.657

Total lipid intake (g/day/kg)
0.96 (0.31)
0.98 (0.31)
.310

Available carbohydrate intake (g/day/kg)
3.73 (1.17)
3.72 (1.29)
.913

Fibre (g/day/kg)
0.29 (0.08)
0.29 (0.08)
.551

Energy intake (kcal/day/kg)
28.60 (8.25)
28.71 (8.50)
.829

Comorbid conditions, (%) or median (IQR)

Diabetes
67 (11)
47 (11)
.764

Heart failure
39 (7)
20 (4)
.176

Chronic pulmonary disease
52 (9)
37 (8)
.823

Parkinson’s disease
15 (2)
12 (3)
.999

Stroke
37 (6)
23 (5)
.503

Hip fracture
19 (3)
19 (4)
.406

Peripheral arterial disease
80 (14)
41 (9)
.032

Malignancy
28 (5)
36 (8)
.036

Frailty phenotype
85 (14)
26 (6)
<.001

Charlson Comorbidity Index
1 (0-2)
1 (0-1)
.489

Medications, (%), mean (SD), or median (IQR)

Neuroleptics
18 (3)
15 (3)
.859

Selective serotonin reuptake inhibitors
13 (2)
3 (1)
.072

ACE inhibitors
92 (16)
49 (11)
.035

Antiplatelets
73 (12)
40 (9)
.088

Anticoagulants
8 (1)
5 (1)
.787

Benzodiazepines
112 (19)
61 (14)
.029

Loop diuretics
53 (9)
32 (7)
.306

Corticosteroids
8 (1)
10 (2)
.339

Biohumoral, physical, and cognitive parameters, (%) or

Glomerular filtration rate (mL/min)
62.6 (19.3)
68.1 (19.2)
<.001

Total serum proteins (g/dL)
7.2 (0.4)
7.1 (0.5)
.308

Interleukin 6 (pg/mL)
1.49 (0.84-2.32)
1.44 (0.88-2.27)
.582

Hemoglobin (g/dL)
13.6 (1.4)
13.8 (1.4)
.112

CES-D
13 (9)
12 (8)
.035

Mini Mental State Examination
24.3 (4.3)
24.7 (5.5)
.160

Katz’s activities of daily living
5 (1)
4 (2)
.107

Body mass index (kg/m²)
27.3 (4.0)
27.6 (4.2)
.183

Table 2: Characteristics of 1035 participants according to the presence of frailty.

Positive for frailty ()
Negative for frailty ()

Demographics & lifestyle habits, (%), mean (SD), or median (IQR)

Age (years)
81 (7)
74 (7)
<.001

Sex (female)
70 (63)
507 (55)
.106

Education (years)
4 (3)
5 (3)
<.001

Living alone
68 (61)
337 (36)
<.001

Smoking (former and current)
38 (34)
385 (42)
.153

Dietary intake

Alcohol (g/day/kg)
0.04 (0–0.25)
0.11 (0–0.31)
.021

Total protein intake (g/day/kg)
1.04 (0.30)
1.12 (0.32)
.009

Total lipid intake (g/day/kg)
0.87 (0.28)
0.97 (0.31)
.002

Available carbohydrates intake (g/day/kg)
3.41 (1.11)
3.76 (1.23)
.008

Fibre (g/day/kg)
0.27 (0.09)
0.30 (0.09)
.006

Energy intake (kcal/day/kg)
26.0 (7.5)
29.0 (8.4)
.001

Comorbid conditions, (%) or median (IQR)

Diabetes
16 (14)
98 (11)
.259

Heart failure
19 (17)
40 (4)
<.001

Chronic pulmonary disease
18 (16)
71 (8)
.006

Parkinson’s disease
8 (7)
19 (2)
.002

Stroke
16 (14)
44 (5)
<.001

Hip fracture
11 (10)
27 (3)
.001

Peripheral arterial disease
23 (21)
98 (11)
.004

Malignancy
8 (7)
56 (6)
.675

Olfactory dysfunction
85 (77)
505 (55)
<.001

Charlson Comorbidity Index
1 (1-2)
0 (0-1)
<.001

Medications, (%), mean (SD), or median (IQR)

Neuroleptics
10 (9)
23 (5)
.001

Selective serotonin reuptake inhibitors
7 (6)
9 (1)
.001

ACE inhibitors
24 (22)
117 (13)
.013

Antiplatelets
18 (16)
95 (10)
.075

Anticoagulants
2 (2)
11 (1)
.641

Benzodiazepines
32 (29)
141 (15)
.001

Loop diuretics
21 (19)
64 (7)
<.001

Corticosteroids
4 (4)
14 (1)
.118

Biohumoral, physical, and cognitive parameters, (%) or

Glomerular filtration rate (mL/min)
54.8 (20.5)
66.0 (19.0)
<.001

Total serum proteins (g/dL)
7.2 (0.6)
7.1 (0.4)
.838

Interleukin 6 (pg/mL)
2.21 (1.35 – 4.09)
1.40 (0.83–2.07)
<.001

Hemoglobin (g/dL)
13.1 (1.6)
13.8 (1.3)
<.001

CES-D
20 (9)
12 (8)
<.001

Mini Mental State Examination
21 (6)
25 (4)
<.001

Katz’s activities of daily living
6 (0-1)
6 (0–0)
<.001

Body mass index (kg/m²)
27.9 (5.1)
27.4 (4.0)
.289

Over the 9-year follow-up, 393 (38%) subjects died. The main characteristics of participants according to survival are depicted in Table 3.

Table 3: Characteristics of 1035 participants according to survival status.

Dead ()
Alive ()

Demographics & lifestyle habits, (%), mean (SD), or median (IQR)

Age (years)
80 (7)
72 (5)
<.001

Sex (female)
200 (51)
377 (59)
.014

Education (years)
5 (3)
6 (3)
<.001

Living alone
206 (52)
199 (31)
<.001

Smoking (former and current)
172 (44)
251 (39)
.152

Dietary intake

Alcohol (g/day/kg)
0.10 (0–0.26)
0.10 (0–0.32)
.021

Total protein intake (g/day/kg)
1.14 (0.32)
1.11 (0.32)
.262

Total lipid intake (g/day/kg)
0.97 (0.30)
0.96 (0.32)
.582

Available carbohydrate intake (g/day/kg)
3.82 (1.26)
3.67 (1.20)
.066

Fibre (g/day/kg)
0.29 (0.09)
0.29 (0.08)
.654

Energy intake (kcal/day/kg)
29.08 (8.33)
28.40 (8.37)
.227

Comorbid conditions, (%) or median (IQR)

Diabetes
52 (13)
62 (10)
.082

Heart failure
46 (12)
13 (2)
<.001

Chronic pulmonary disease
63 (16)
26 (4)
<.001

Parkinson’s disease
21 (5)
6 (1)
<.001

Stroke
44 (11)
16 (2)
<.001

Hip fracture
24 (6)
14 (2)
.002

Peripheral arterial disease
86 (22)
35 (5)
<.001

Malignancy
28 (7)
36 (6)
.353

Olfactory dysfunction
249 (63)
341 (53)
.001

Frailty
90 (23)
21 (3)
<.001

Charlson Comorbidity index
1 (0-2)
0 (0-1)
<.001

Medications, (%), mean (SD), or median (IQR)

Neuroleptics
17 (4)
16 (2)
.143

Selective serotonin reuptake inhibitors
11 (3)
5 (1)
.017

ACE inhibitors
72 (18)
69 (11)
.001

Antiplatelets
65 (16)
48 (7)
<.001

Anticoagulants
11 (3)
2 (1)
.001

Benzodiazepines
81 (21)
92 (14)
.010

Loop diuretics
55 (14)
30 (5)
<.001

Corticosteroids
11 (3)
7 (1)
.050

Biohumoral, physical, and cognitive parameters, (%) or

Glomerular filtration rate (mL/min)
56.4 (19.5)
69.5 (17.8)
<.001

Total serum proteins (g/dL)
7.1 (0.5)
7.1 (0.4)
.680

Interleukin 6 (pg/mL)
1.89 (1.14–3.31)
1.22 (0.78–1.84)
<.001

Hemoglobin (g/dL)
13.4 (1.6)
13.9 (1.2)
<.001

CES-D
14 (9)
12 (9)
<.001

Mini Mental State Examination
22 (6)
26 (3)
<.001

Katz’s activities of daily living
5 (1)
6 (0)
<.001

Body mass index (kg/m²)
27.0 (4.3)
27.7 (4.0)
.016

Olfactory dysfunction was reported by 590/1035 (57%) participants; specifically, lack of recognition of one smell was recorded in 190 (18%) subjects, two smells in 243 (23%), and three smells in 347 (33%). In particular, failure to recognize air was found in 638 (62%) subjects, failure to recognize mint was found in 574 (55%), and failure to recognize coffee was found in 505 (49%).

In multivariable logistic regression, olfactory dysfunction was associated with increased probability of being frail (OR 1.94, 95% -3.51; ), after adjusting (Table 4). Analysis of the interaction term indicated that the association of frailty with olfactory dysfunction varied according to interleukin-6 levels ( for ).

Table 4: Association (odds ratios (OR) and 95% confidence intervals (CI)) of frailty with the variables of interest, including olfactory dysfunction, according to the logistic regression model. All the covariates were entered simultaneously into the regression model.

OR
95% CI

Age (each year)
1.15
1.09-1.21
<.001

Sex (female)
.92
.52-1.64
.778

Education (years)
.95
.86-1.05
.306

Malignancy
1.72
.65-4.57
.279

Peripheral arterial disease
2.46
1.29-4.69
.006

ACE inhibitors
1.65
.87-3.12
.122

Benzodiazepines
1.15
.63-2.10
.653

Glomerular filtration rate (mL/min)
1.02
1.01-1.04
.018

CES-D
1.11
1.07-1.14
.000

Olfactory dysfunction
1.94
1.07-3.51
.028

Also, increasing levels of olfactory dysfunction were associated with increasing probability of frailty ( for ).

Both frailty (OR 2.60, 95% -4.85) and prefrailty (OR 1.59, 95% -2.16) were associated with olfactory dysfunction in multinomial logistic having robustness as the reference.

According to Cox regression analysis, olfactory dysfunction was associated with reduced survival (HR 1.52, 95% -1.98; ), after adjusting (Figure 1); analysis of the interaction term indicated that this association varied according to the presence of frailty (), prefrailty (), and increased interleukin-6 levels ( for ).

Figure 1: Nine-year survival curves of participants stratified for olfactory dysfunction. The model was simultaneously adjusted for age, sex, education level, glomerular filtration rate, hemoglobin levels, CES-D, Mini Mental State Examination, ADLs, diagnosis of malignancy, peripheral arterial disease, use of ACE inhibitors and benzodiazepines, and frailty.

4. Discussion

Results of the present study indicate that in older subjects, olfactory dysfunction is associated not only with frailty, but even with prefrailty. This association seems to be mediated by subclinical inflammation.

This association was independent of several confounders, including comorbid conditions, medication use, and lifestyle habits; this finding indicates that olfactory dysfunction might represent an early marker of increased risk for adverse outcomes. In fact, in this population, olfactory dysfunction represented a risk factor for reduced survival, and both frailty and prefrailty seemed to mediate this association.

Several factors might explain the association of olfactory dysfunction with frailty and mortality.

Olfactory dysfunction is among the earliest findings which predict the development of mild cognitive impairment [18]. Also, olfactory dysfunction heralds several neurodegenerative disorders, including Parkinson’s disease, which is a paradigm of frailty [2]; of notice, olfactory loss has been included as a marker of prodromal Parkinson’s disease by the Movement Disorders Society [19]. Among patients with Parkinson’s disease, the severity of olfactory dysfunction seems to correlate with the severity of ensuing dementia [2].

In experimental as well as human models, olfactory dysfunction has been linked with the expression of the apolipoprotein e4 allele and of tau protein and amyloid-β deposits [20, 21]; all these findings, in turn, are associated with several adverse clinical outcomes, including cardiovascular diseases and Alzheimer’s disease [20]. Olfactory dysfunction has also been associated with depression, probably due to the damage of the hippocampal pathways [22]. In turn, late-life depression has been associated with increased risk of dementia [23].

Systemic diseases, such as diabetes, iron deficiency, and autoimmune diseases, might cause central and peripheral olfactory dysfunction and disrupt the peripheral olfactory pathways [24, 25]. The olfactory deficit represents a preclinical marker of alpha-synucleinopathies and a risk factor for delirium [2, 26]. Also, impairment in olfactory function has been related to the intake of macro- and micronutrients and directly affects food intake behaviour [27]. Eventually, olfactory dysfunction represents a risk factor for reduced survival [8]. Even better, olfactory dysfunction is the only sense which has been associated with mortality, when compared with hearing or visual impairment [9]. With special regard to the frailty components, olfactory function is associated with mobility, balance, fine motor function, and manual dexterity and independent of cognitive function, with challenging upper- and lower-extremity motor function tasks [28]. Also, olfactory loss represents a risk factor for weight loss, while aerobic exercise might preserve olfactory function in selected populations, such as patients with Parkinson’s disease [2, 29].

Furthermore, our finding of a potential role of IL-6 serum levels in the association between olfactory loss and frailty is of interest. Increased IL-6 levels have been found in serum and nasal mucus of hyposmic patients [30]. On the other hand, increased IL-6 serum levels have also been associated with frailty, as well as mortality, in older populations [31, 32]. Thus, inflammation represents a common pathophysiological pathway that links hyposmia, frailty, and mortality in the elderly.

In this study, olfactory dysfunction was self-assessed. Self-assessed tools for evaluating olfactory function might underestimate the dysfunction, as compared with objective evaluation. Nevertheless, this would represent a conservative bias, which further supports our findings. Also, regarding the association of olfactory dysfunction with frailty, due to its cross-sectional design, this study does not allow establishing any cause-effect relationship. Nonetheless, this study enrolled a representative community-dwelling population, with high participation rate and with extensive information on risk factors, comorbid conditions, and objective parameters.

In conclusion, olfactory loss represents a correlate of frailty and even of prefrailty; this association seems to affect the role of olfactory dysfunction as a predictor of mortality in older populations. Thus, olfaction seems worth testing in geriatric practice for both clinical and epidemiological purposes.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Ethical Approval

The Italian National Research Council on Aging Ethical Committee ratified the study protocol, and informed consent was obtained from all individual participants included in the study. The present study has been performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Disclosure

None of the sponsoring institutions interfered with the design, methods, subject recruitment, data collections, analysis, and preparation of the paper.

Conflicts of Interest

The authors declare that they have no conflict of interest in this study.

Acknowledgments

The InCHIANTI study baseline (1998–2000) was supported as a targeted project (ICS110.1/RF97.71) by the Italian Ministry of Health and in part by the U.S. National Institute on Aging (Contracts 263 MD 9164 and 263 MD 821336); the InCHIANTI Follow-Up 1 (2001–2003) was funded by the U.S. National Institute on Aging (Contracts N.1-AG-1-1 and N.1-AG-1-2111), Baltimore, Maryland.

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