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Dietary intakes of fats, fish and nuts and olfactory impairment in older adults

Published online by Cambridge University Press:  16 June 2015

Bamini Gopinath*
Affiliation:
Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, NSW2145, Australia
Carolyn M. Sue
Affiliation:
Departments of Neurology and Neurogenetics, Kolling Institute, University of Sydney, Sydney, NSW, Australia
Victoria M. Flood
Affiliation:
Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia St Vincent's Hospital, Sydney, NSW, Australia
George Burlutsky
Affiliation:
Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, NSW2145, Australia
Paul Mitchell
Affiliation:
Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, NSW2145, Australia
*
*Corresponding author: B. Gopinath, fax +61 2 86273099, email bamini.gopinath@sydney.edu.au
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Abstract

It is unclear whether lifestyle modifications, such as dietary changes, should be advocated to prevent olfactory dysfunction. We investigated the association between dietary intakes of fats (saturated, mono-unsaturated and polyunsaturated fats, and cholesterol) and related food groups (nuts, fish, butter, margarine) with olfactory impairment. There were 1331 and 667 participants (older than 60 years) at baseline and 5-year follow-up, respectively, with complete olfaction and dietary data. Dietary data were collected using a validated semi-quantitative FFQ. Olfaction was measured using the San Diego Odor Identification Test. In a cross-sectional analysis of baseline data, those in the highest v. lowest quartile of n-6 PUFA intake had reduced odds of having any olfactory impairment, multivariable-adjusted OR 0·66 (95 % CI 0·44, 0·97), P for trend = 0·06. Participants in the highest v. lowest quartile of margarine consumption had a 65 % reduced odds of having moderate/severe olfactory impairment (P for trend = 0·02). Participants in the highest quartile compared to the lowest quartile (reference) of nut consumption had a 46 % (P for trend = 0·01) and 58 % (P for trend = 0·001) reduced odds of having any or mild olfactory impairment, respectively. Older adults in the highest v. lowest quartile of fish consumption had 35 % (P for trend = 0·03) and 50 % (P for trend = 0·01) reduced likelihood of having any or mild olfactory impairment, respectively. In longitudinal analyses, a marginally significant association was observed between nut consumption and incidence of any olfactory impairment, highest v. lowest quartile of nut consumption: OR 0·61 (95 % CI 0·37, 1·00). Older adults with the highest consumption of nuts and fish had reduced odds of olfactory impairment, independent of potential confounding variables.

Type
Full Papers
Copyright
Copyright © The Authors 2015 

A decrease in olfactory function with increasing age has been extensively reported( Reference Gopinath, Anstey and Kifley 1 Reference Murphy, Schubert and Cruickshanks 3 ). Unlike alterations in hearing and vision, age-related changes in olfaction often go unnoticed, and smell ability is rarely evaluated clinically( Reference Doty 4 ). There are several bases for age-related changes in smell function and include some of the following: (1) ossification and closure of the foramina of the cribriform plate( Reference Kalmey, Thewissen and Dluzen 5 ); (2) development of early neurodegenerative disease pathology( Reference Doty, Shaman and Applebaum 6 ); and (3) cumulative damage to the olfactory receptors from smoking and other insults throughout life( Reference Gopinath, Anstey and Kifley 1 , Reference Doty 4 ). There have been various tests developed to evaluate the sense of smell. Included in such procedures are tests of olfactory sensitivity (e.g. odour detection and recognition thresholds), odour discrimination, odour identification, odour memory and supra-threshold scaling of odour intensities and pleasantness( Reference Doty, McKeown and Lee 7 ).

We previously showed that among the Blue Mountains Eye Study (BMES) participants aged ≥ 60 years, the prevalence of olfactory impairment was 27·0 %( Reference Karpa, Gopinath and Rochtchina 2 ). This was comparable to the 24·5 % rate observed in the Wisconsin Epidemiology of Hearing Loss Study for persons aged 43–86 years( Reference Murphy, Schubert and Cruickshanks 3 ). In addition to its relatively high prevalence, olfactory loss impacts on a wide range of functions. Decreased olfaction results in reductions in appetite, leading to weight loss and malnutrition( Reference Boyce and Shone 8 ). In the presence of impaired smell, disability and diminished quality of life are observed( Reference Miwa, Furukawa and Tsukatani 9 Reference Gopinath, Anstey and Sue 11 ). Many studies have also shown a significant relationship between olfactory impairment and depressive symptoms and poor quality of life( Reference Gopinath, Anstey and Sue 11 , Reference Pollatos, Albrecht and Kopietz 12 ). In addition, the functional ability and independence of older adults is significantly impaired in the presence of olfactory impairment( Reference Gopinath, Anstey and Kifley 1 ). More recently, olfactory impairment has been shown to predict future cognitive decline( Reference Nordin, Monsch and Murphy 13 ), Parkinson's disease( Reference Ross, Petrovitch and Abbott 14 ) and increased mortality risk( Reference Gopinath, Sue and Kifley 15 ).

Apart from the effects of smoking, there are very few epidemiological data on modifiable risk factors associated with olfactory impairment. A better understanding of lifestyle risk factors will facilitate to identify and change at-risk behaviour, and help in implementing preventive strategies. Encouraging changes in the dietary intakes of individuals could be a potential preventive strategy for olfactory impairment. A recent animal study by Thiebaud et al. ( Reference Thiebaud, Johnson and Butler 16 ) showed that exposure to a high-fat diet, independent of the degree of adiposity, can impact on the general neuro-architecture of the olfactory system. Specifically, mice fed a high-fat diet showed a marked reduction in olfactory discrimination. The authors speculated that such reduction in sensory performance, which is precipitated by a chronic increase in fat in the diet, could be linked to the observed loss of olfactory sensory neurons in the study or just be one facet of the likely multiple changes in the different levels of the olfactory system attributed to the presence of fat( Reference Thiebaud, Johnson and Butler 16 ). However, to our best knowledge, no adult population-based study has specifically examined the association between dietary intakes of fats or the major fat-containing groups and the prevalence and incidence of olfactory impairment.

We therefore used a representative community-based cohort of older adults to investigate the following aims: (1) to establish whether cross-sectional and longitudinal associations exist between dietary fats (saturated, mono-unsaturated, polyunsaturated, cholesterol), certain food groups (e.g. nuts, butter, margarine and fish) and olfactory loss; and (2) to determine whether observed cross-sectional or longitudinal associations differed according to the severity of olfactory impairment.

Methods

Study population

The BMES is a population-based cohort study of common eye diseases and other health outcomes in a suburban Australian population located west of Sydney. Study methods and procedures have been described elsewhere( Reference Attebo, Mitchell and Smith 17 ). Baseline examinations of 3654 residents aged >49 years were conducted during 1992–4 (BMES-1, 82·4 % participation rate). Surviving baseline participants were invited to attend examinations after 5 years (1997–9, BMES-2), 10 years (2002–4, BMES-3) and 15 years (2007–9, BMES-4). At BMES-2, -3 and -4, 2334 participants (75·1 % of survivors), 1952 participants (75·6 % of survivors) and 1149 (55·4 % of survivors) with complete data were re-examined, respectively. The present study was conducted according to the Declaration of Helsinki and The University of Sydney and the Western Sydney Area Human Ethics Committees approved the study, and written, informed consent was obtained from all participants at each examination.

Olfaction examination

The San Diego Odor Identification Test (SDOIT)( Reference Morgan, Nordin and Murphy 18 ) and related olfactory questions were a component of the BMES-3 examination, and complete olfaction data were obtained from 1636 of 1952 (83·8 %) BMES-3 participants. Participants were tested individually with the SDOIT, an eight-item odour identification test with a test–retest reliability relatively similar to that for the forty-item University of Pennsylvania Smell Identification Test (UPSIT) (r 0·86 SDOIT; r 0·94 UPSIT)( Reference Doty 19 ). Odorants were presented to the participants in a random order, in an opaque container covered with gauze. These odorants are common odours in the household, that is, chocolate, cinnamon, talcum powder, chewing gum, coffee, mustard, peanut butter, and play-doh. An inter-stimulus pause of 45 s was used to prevent adaptation( Reference Ekman, Berglund and Berglund 20 ). The examiner would record on a score sheet ‘0’ (incorrect), ‘1’ (correct) or ‘9’ (don't know) beside each listed odorant. A picture board illustrating the odorants as well as distracters was used for participants to identify each odorant. Scores were calculated from the number of odorants identified correctly. We defined mild olfactory impairment as less than six but greater than three correct responses and moderate/severe as three or less correct responses out of a total of eight possible responses.

Dietary assessment

Dietary data were collected using a 145-item self-administered FFQ, modified for Australian diet and vernacular from an early Willett FFQ( Reference Willett, Sampson and Browne 21 ), and included reference portion sizes. Participants used a nine-category frequency scale to indicate the usual frequency of consuming individual food items during the past year( Reference Smith, Mitchell and Reay 22 ). The FFQ showed moderate to good agreement for ranking individuals according to their fat intakes (total fat r 0·68, SFA r 0·67, MUFA r 0·54, and PUFA r 0·44) and correctly classified more than 70 % of people within one quintile for all types of fat( Reference Smith, Mitchell and Reay 22 , Reference Lewis, Hunt and Milligan 23 ). Total dietary fat comprised dietary cholesterol, SFA, MUFA and PUFA.

Dietary intakes were estimated using the Australian Tables of Food Composition (NUTTAB95)( Reference Lewis, Hunt and Milligan 23 ). Additional fatty acid food composition data were added from the Royal Melbourne Institute of Technology database( Reference Mann, Pirotta and O'Connell 24 ), available on FoodWorks, version 3 (Xyris Software Private Limited). Dietary fat intakes were expressed as a contribution to percentage of energy intake. Long-chain n-3 PUFA was calculated from the sum of EPA (20 : 5 n-3), docosapentaenoic (22 : 5 n-3) and DHA (22 : 6 n-3). Total n-3 PUFA consumption was calculated by adding the intakes of long-chain n-3 PUFA and α-linolenic acid. All dietary sources of n-3 PUFA were included in the analyses. In previously published fatty acid food sources of this population( Reference Flood, Webb and Rochtchina 25 ), we have described the various food sources, for example, for total n-3 PUFA intake the main dietary sources were from fats and oils (27 %), fish and seafood (21 %), meat and meat products (13 %), breads and cereals (8 %), milk and milk products (8 %); the main food sources of long-chain n-3 PUFA were fish and seafood (69 %), meat and meat products (15 %), and eggs (15 %; includes n-3 fortified eggs). The FFQ includes specific questions about the type of oil and margarine, which were individually coded and included in the total PUFA analyses. This analysis of the baseline dietary intake does not include n-3 from supplements. Previous investigations have indicated supplement use of n-3/fish oils was not high in this cohort( Reference Gopinath, Flood and Rochtchina 26 ). The total n-6 PUFA consumption was calculated by adding the intakes of linoleic and arachidonic acid( Reference Gopinath, Buyken and Flood 27 ).

Assessment of covariates

At face-to-face interviews with trained interviewers, a comprehensive medical history that included information about hearing, demographic factors, socio-economic characteristics and lifestyle factors was obtained from all participants. Smoking status was determined from history as never smoked, past smoker and current smoker (which included those who had ceased smoking within the past 12 months). Information on all currently taken medications was considered to determine the use of cholesterol-lowering medication (i.e. statins). Diabetes was defined either by history or from fasting blood glucose ≥ 7·0 mmol/l. Subjects were defined as having hypertension if they had systolic blood pressure greater than 140 mmHg or diastolic blood pressure more than 90 mmHg or were on anti-hypertensive medications( Reference Whitworth 28 ). BMI was calculated as weight divided by height squared (kg/m2).

Results

Of the 1952 participants examined at BMES-3 (or baseline for the purpose of the present study), 1331 had complete information on dietary intakes and olfactory status (Fig. 1). Study participants with olfactory impairment compared to those with normal olfaction were more likely to be male, older and have a lower BMI and lower consumption of fish and nuts (Table 1). After multivariable adjustment, a marginally significant association was observed between increasing dietary intakes of saturated fats and increased odds of prevalent mild olfactory impairment, P for trend = 0·05 (Table 2). Participants in the highest compared to lowest quartile of total n-6 PUFA had a 34 % reduced odds of having any olfactory impairment (P for trend = 0·06). Non-significant associations were observed between dietary intakes of other types of fats and prevalence of olfactory impairment (Table 2).

Fig. 1 Flowchart of study participation in the Blue Mountains Eye Study from 2002–4 to 2007–9.

Table 1 Study characteristics of Blue Mountains Eye Study participants by presence of olfactory impairment (Mean values and standard deviations; number of participants and percentages)

Table 2 Association between dietary fats and prevalence of olfactory loss in the Blue Mountains Eye Study (Adjusted odds ratios and 95 % confidence intervals, n 1331)

* Adjusted for age, sex, energy intake, BMI, smoking, hypertension and history of diabetes.

Participants in the highest quartile compared to the lowest quartile of nut consumption had a 46 % (P for trend = 0·01) and 58 % (P for trend = 0·001) reduced odds of having any or mild prevalent olfactory impairment, respectively (Table 3). In addition, participants in the highest v. lowest quartile of margarine consumption had a 65 % reduced odds of having moderate/severe olfactory impairment (P for trend = 0·02). Participants who were in the highest compared to the lowest quartile of fish consumption had a 35 % (P for trend = 0·03) and 50 % (P for trend = 0·01) reduced likelihood of having any or mild olfactory impairment (Table 3).

Table 3 Association between food groups and prevalence of olfactory loss in the Blue Mountains Eye Study (Adjusted odds ratios and 95 % confidence intervals, n 1331)

* Adjusted for age, sex, energy intake, BMI, smoking, hypertension and history of diabetes.

Of the 1331 participants included for cross-sectional analyses, 667 participants had complete olfactory function data at the 5-year follow-up (Fig. 1). Of these, 174 (26 %) developed incident (i.e. new cases) of any olfactory impairment. Table 4 shows a marginally significant association between nut consumption, and 5-year incidence of any olfactory impairment was observed, that is, those in the highest v. lowest quartile of nut consumption at baseline had reduced risk of developing incident olfactory impairment, multivariable-adjusted OR 0·61 (95 % CI 0·37, 1·00). Significant associations were not observed with other food groups (Table 4) or dietary fats (data not shown) and incidence of olfactory impairment.

Table 4 Association between food groups and 5-year incidence of olfactory loss in the Blue Mountains Eye Study (Adjusted odds ratios and 95 % confidence intervals, n 667)

* Adjusted for age, sex, energy intake, BMI, smoking, hypertension and history of diabetes.

Discussion

This cohort study provides novel epidemiological evidence of an inverse cross-sectional association between nut and fish consumption and any or mild olfactory impairment in older adults, independent of the effects of potential confounders such as age, smoking, BMI, energy intake and a history of diabetes and hypertension. In cross-sectional analyses, study participants who had the highest v. lowest intake of total n-6 PUFA and margarine had significantly reduced odds of olfactory loss. Significant associations were not observed with any of the key nutritional variables and the 5-year incidence of olfactory impairment.

Our findings of a non-significant association between dietary intakes of total dietary fats with both prevalence and 5-year incidence of olfactory impairment contrasts with the findings of a previous animal study, which showed that mice fed a high-fat diet showed a marked reduction in olfactory discrimination( Reference Miwa, Furukawa and Tsukatani 9 ). One potential reason for this divergent finding could be the type of test used to determine olfaction; in the present study we used a test that involved odour identification, while the animal study involved olfactory discrimination. We did, however, observe a marginally significant association between increasing dietary intakes of saturated fats and increasing odds of having prevalent mild olfactory loss, but not incident olfactory loss. Previously, it was shown that adoption of a saturated fat-enriched diet over a 3-week period was associated with an impairment of flow-mediated dilation, suggestive of endothelial dysfunction( Reference Keogh, Grieger and Noakes 29 ). Given that endothelial dysfunction could contribute to the age-related decline in olfactory sensitivity observed in older adults( Reference Getchell, Shah and Buch 30 ), increased saturated fat intake via endothelial dysfunction could be responsible for increasing the likelihood of having impaired olfaction.

Increasing nut consumption was independently associated with a reduced likelihood of having prevalent olfactory loss. Further, a marginally significant association was observed between increasing nut consumption at baseline and reduced risk of developing any olfactory impairment 5 years later. Given that the present study is a correlational study, it is not possible to establish the mechanisms that underlie the protective influence of nut consumption on olfactory function. However, we hypothesise that nuts are rich in unsaturated fats and other nutrients, which could decrease levels of inflammatory markers( Reference Jiang, Jacobs and Mayer-Davis 31 ) and, hence, help in maintaining healthy olfaction in older adults. This is because sensorineural olfactory loss is caused by damage or destruction of the neuroepithelium as a result of toxic inflammatory mediators and tissue disruption from infiltrating inflammatory cells( Reference Kern 32 , Reference Yee, Pribitkin and Cowart 33 ). In the BMES, we previously showed that nut consumption protected against dying from chronic inflammation-related diseases( Reference Gopinath, Buyken and Flood 27 ). Several bioactive components in nuts, acting in isolation or most probably synergistically, could explain the beneficial effect against inflammation( Reference Gopinath, Buyken and Flood 27 , Reference Ros 34 ). It is likely that similar mechanisms could also mediate the association with olfactory impairment. For instance, Mg, a mineral found in nuts at higher amounts than in other edible plants( Reference Segura, Javierre and Lizarraga 35 ), could contribute to the reduction of inflammatory markers( Reference Ros 34 ). Moreover, dietary polyphenols present in nuts may have anti-inflammatory effects, mediated by both their antioxidant action and modulation of signal transduction pathways( Reference Gopinath, Buyken and Flood 27 , Reference Ros 34 ). Finally, nuts also contain PUFA, including α-linolenic acid and linoleic acid. α-Linolenic acid has been shown to exert favourable effects on cytokine production( Reference Gopinath, Buyken and Flood 27 , Reference Zhao, Etherton and Martin 36 ). This notion aligns with a previously hypothesised sensorineural mechanism in which olfactory dysfunction can occur with an intact neuroepithelium, as a consequence of direct interactions between olfactory sensory neurons and inflammatory cytokines( Reference Sultan, May and Lane 37 ).

Moreover, inflammation could also be a step in the pathway that links fish consumption and reduced prevalence of any and mild olfactory impairment observed in the BMES. This is because fish contain n-3 PUFA (particularly EPA and DHA), which are demonstrated to regulate inflammatory processes and responses( Reference Calder 38 ). Alternatively, we speculate that olfactory loss could be a surrogate marker of neurodegeneration( Reference Mesholam, Moberg and Mahr 39 , Reference Seo, Jeon and Hummel 40 ) that could be accompanied by lower nut and fish consumption. There is growing evidence from both animal and human studies showing that moderate-duration dietary supplementation with nuts is capable of altering cognitive performance in human subjects, perhaps forestalling or reversing the effects of neurodegeneration in ageing( Reference Pribis and Shukitt-Hale 41 ). Fish consumption could also confer a similar protective effect against neurodegeneration. For instance, there is epidemiological evidence showing that increased fish intake is associated with reduced Alzheimer's disease and reduced cognitive decline( Reference Cole, Ma and Frautschy 42 ). Surprisingly, total and long-chain n-3 PUFA intake were not independently associated with the prevalence or incidence of olfactory loss in the present study. Evidence of the clinical benefits of long-chain n-3 PUFA, for example, is strong in some settings (e.g. rheumatoid arthritis) and yet weak in others (e.g. in asthma and inflammatory bowel disease)( Reference Gopinath, Buyken and Flood 27 , Reference Calder 38 ). The reasons for these apparently divergent findings are not clear, and warrant confirmation by other large, population-based cohorts.

In cross-sectional analyses, margarine and total n-6 PUFA consumption were associated with reduced odds of olfactory dysfunction. Given that margarine is one of the most convenient and readily available sources of linoleic acid (the main dietary n-6 PUFA), it was not surprising to see similar inverse associations between n-6 PUFA intake and margarine consumption and prevalence of olfactory impairment. There is still some uncertainty regarding the benefits and risks of n-6 PUFA intake( Reference Czernichow, Thomas and Bruckert 43 , Reference Ramsden, Zamora and Leelarthaepin 44 ). n-6 PUFA have long been considered as pro-inflammatory molecules because they are the main precursors of eicosanoids, a family of mediator molecules that are involved in immune and inflammatory responses( Reference Czernichow, Thomas and Bruckert 43 , Reference Calder 45 ). However, in human subjects, higher intakes of n-6 fatty acids do not appear to be associated with elevated levels of inflammatory markers( Reference Czernichow, Thomas and Bruckert 43 , Reference Ferrucci, Cherubini and Bandinelli 46 ). Therefore, the pathways mediating the relationship between n-6 PUFA and margarine intake and olfactory loss currently remains unclear. We caution, however, that this could be a chance finding, particularly as we did not see this association persist at the 5-year follow-up. Additional longitudinal studies are required to confirm or refute our observed associations with olfactory impairment.

Strengths of the present study include its representative population-based sample with relatively high participation, longitudinal study design, availability of rich covariate/confounder information, and the use of standardised objective measures of olfaction and the use of a validated FFQ to collect dietary data. The ability to classify participants with mild or moderate/severe olfactory loss also added value to this cohort study( Reference Gopinath, Anstey and Kifley 1 ). However, there are some caveats, such as dietary assessment by FFQ in which respondents have to estimate typical intake frequencies of food items and their portion sizes, which can potentially introduce measurement error and bias. However, the overall validity of fatty acid categories compared to weighted food records was moderately good( Reference Smith, Mitchell and Reay 22 , Reference Lewis, Hunt and Milligan 23 , Reference Gopinath, Flood and Rochtchina 26 ). In addition, the number of odorants in the SDOIT may limit the ability to detect small decrements in odour identification or to distinguish hyposmia from anosmia( Reference Gopinath, Anstey and Kifley 1 , Reference Schubert, Cruickshanks and Fischer 47 ), and due to the nature of this test we cannot firmly establish whether an individual has olfactory dysfunction or not. Further, while the SDOIT has been validated in a US population, it has yet to be validated in an Australian population. Furthermore, persons with olfactory impairment compared to those with normal olfaction were shown to have lower survival( Reference Gopinath, Sue and Kifley 15 ), and also given the older age of our cohort, many study participants were unable to attend or complete the follow-up examination. These factors could have contributed to the substantial reduction in participant numbers at 5-year follow-up. Hence, we had a relatively small number of incident cases of any olfactory loss over the 5 years, which could have led to insufficient power to detect modest associations between intakes of dietary fats and related food groups and olfactory loss 5 years later. We also need to highlight that the duration of follow-up is short and that the average age of the cohort is relatively old, perhaps most of the protective or beneficial effects from intakes of nuts, total n-6 PUFA and margarine, and so on, may have already been exerted before the cohort began to be followed. Hence, this could explain the significant association with prevalent olfactory loss at baseline but the lack of association with the 5-year incidence of olfactory loss. Finally, we cannot exclude the possibility of residual confounding, although we have attempted to adjust for a number of potential confounders, there could be many unmeasured or unaccounted variables (e.g. lifestyle and behavioural factors) that are likely to have influenced the overall pattern of food intake.

In summary, we show that increased consumption of total n-6 PUFA, margarine, nuts, and fish could contribute to a modest reduction in the prevalence of olfactory impairment, independent of the potential confounding influences of age, sex, smoking, BMI and a history of hypertension and diabetes. Apart from a marginally significant inverse association between nut consumption and 5-year incidence of olfactory impairment, dietary intakes of fatty acids or related food groups did not influence risk of incident olfactory loss. The reasons for these observed associations are not clear and require confirmation in other large population-based studies. These further studies will also be useful in establishing whether consumption of nuts and fish might have a role in the prevention of olfactory dysfunction in older adults.

Acknowledgements

The Blue Mountains Eye and Hearing Studies were supported by the Australian National Health and Medical Research Council (grant nos. 974159, 991407, 211069, 262120).

The authors' contributions are as follows: B. G. and P. M. were involved in the study concept and design; P. M. was responsible for the acquisition of data; B. G., C. M. S., V. M. F. and P. M. were involved in the interpretation of data; B. G. was involved in the drafting of the manuscript; G. B. performed the analyses of data; B. G., C. M. S., V. M. F. and P. M. were involved in critical revision of the manuscript.

All authors have no conflict of interest and declare no financial interest.

References

1 Gopinath, B, Anstey, KJ, Kifley, A, et al. (2012) Olfactory impairment is associated with functional disability and reduced independence among older adults. Maturitas 72, 5055.Google Scholar
2 Karpa, MJ, Gopinath, B, Rochtchina, E, et al. (2010) Prevalence and neurodegenerative or other associations with olfactory impairment in an older community. J Aging Health 22, 154168.Google Scholar
3 Murphy, C, Schubert, CR, Cruickshanks, KJ, et al. (2002) Prevalence of olfactory impairment in older adults. JAMA 288, 23072312.Google Scholar
4 Doty, RL (2009) The olfactory system and its disorders. Semin Neurol 29, 074081.Google Scholar
5 Kalmey, JK, Thewissen, JGM & Dluzen, DE (1998) Age-related size reduction of foramina in the cribriform plate. Anat Rec 251, 326329.Google Scholar
6 Doty, RL, Shaman, P, Applebaum, SL, et al. (1984) Smell identification ability: changes with age. Science (New York, NY) 226, 14411443.Google Scholar
7 Doty, RL, McKeown, DA, Lee, WW, et al. (1995) A study of the test–retest reliability of ten olfactory tests. Chem Senses 20, 645656.Google Scholar
8 Boyce, JM & Shone, GR (2006) Effects of ageing on smell and taste. Postgrad Med J 82, 239241.Google Scholar
9 Miwa, T, Furukawa, M, Tsukatani, T, et al. (2001) Impact of olfactory impairment on quality of life and disability. Arch Otolaryngol Head Neck Surg 127, 497503.Google Scholar
10 Smeets, MAM, Veldhuizen, MG, Galle, S, et al. (2009) Sense of smell disorder and health-related quality of life. Rehabil Psychol 54, 404412.Google Scholar
11 Gopinath, B, Anstey, KJ, Sue, CM, et al. (2011) Olfactory impairment in older adults is associated with depressive symptoms and poorer quality of life scores. Am J Geriatr Psychiatry 19, 830834.CrossRefGoogle ScholarPubMed
12 Pollatos, O, Albrecht, J, Kopietz, R, et al. (2007) Reduced olfactory sensitivity in subjects with depressive symptoms. J Affect Disord 102, 101108.CrossRefGoogle ScholarPubMed
13 Nordin, S, Monsch, AU & Murphy, C (1995) Unawareness of smell loss in normal aging and Alzheimer's disease: discrepancy between self-reported and diagnosed smell sensitivity. J Gerontol B Psychol Sci Soc Sci 50, P187P192.Google Scholar
14 Ross, GW, Petrovitch, H, Abbott, RD, et al. (2008) Association of olfactory dysfunction with risk for future Parkinson's disease. Ann Neurol 63, 167173.CrossRefGoogle ScholarPubMed
15 Gopinath, B, Sue, CM, Kifley, A, et al. (2012) The association between olfactory impairment and total mortality in older adults. J Gerontol A Biol Sci Med Sci 67A, 204209.Google Scholar
16 Thiebaud, N, Johnson, MC, Butler, JL, et al. (2014) Hyperlipidemic diet causes loss of olfactory sensory neurons, reduces olfactory discrimination, and disrupts odor-reversal learning. J Neurosci 34, 69706984.CrossRefGoogle ScholarPubMed
17 Attebo, K, Mitchell, P & Smith, W (1996) Visual acuity and the causes of visual loss in Australia. The Blue Mountains Eye Study. Ophthalmology 103, 357364.Google Scholar
18 Morgan, CD, Nordin, S & Murphy, C (1995) Odor identification as an early marker for Alzheimer's disease: impact of lexical functioning and detection sensitivity. J Clin Exp Neuropsychol 17, 793803.CrossRefGoogle ScholarPubMed
19 Doty, RL (2007) Office procedures for quantitative assessment of olfactory function. Am J Rhinol 21, 460473.Google Scholar
20 Ekman, G, Berglund, B, Berglund, U, et al. (1967) Perceived intensity of odor as a function of time of adaptation. Scand J Psychol 8, 177186.CrossRefGoogle ScholarPubMed
21 Willett, WC, Sampson, L, Browne, ML, et al. (1988) The use of a self-administered questionnaire to assess diet four years in the past. Am J Epidemiol 127, 188199.Google Scholar
22 Smith, W, Mitchell, P, Reay, EM, et al. (1998) Validity and reproducibility of a self-administered food frequency questionnaire in older people. Aust N Z J Public Health 22, 456463.Google Scholar
23 Lewis, J, Hunt, A & Milligan, G (1995) NUTTAB95 Nutrient Data Table for Use in Australia. Canberra: Australian Government Publishing Service.Google Scholar
24 Mann, N, Pirotta, Y, O'Connell, S, et al. (2006) Fatty acid composition of habitual omnivore and vegetarian diets. Lipids 41, 637646.Google Scholar
25 Flood, VM, Webb, KL, Rochtchina, E, et al. (2007) Fatty acid intakes and food sources in a population of older Australians. Asia Pac J Clin Nutr 16, 322330.Google Scholar
26 Gopinath, B, Flood, VM, Rochtchina, E, et al. (2010) Consumption of ω-3 fatty acids and fish and risk of age-related hearing loss. Am J Clin Nutr 92, 416421.Google Scholar
27 Gopinath, B, Buyken, AE, Flood, VM, et al. (2011) Consumption of polyunsaturated fatty acids, fish, and nuts and risk of inflammatory disease mortality. Am J Clin Nutr 93, 10731079.Google Scholar
28 Whitworth, JA, World Health Organization & International Society of Hypertension Writing Group (2003) 2003 World Health Organization (WHO)/International Society of Hypertension (ISH) statement on management of hypertension. J Hypertens 21, 19831992.Google Scholar
29 Keogh, JB, Grieger, JA, Noakes, M, et al. (2005) Flow-mediated dilatation is impaired by a high-saturated fat diet but not by a high-carbohydrate diet. Arterioscler Thromb Vasc Biol 25, 12741279.Google Scholar
30 Getchell, ML, Shah, DS, Buch, SK, et al. (2003) 3-Nitrotyrosine immunoreactivity in olfactory receptor neurons of patients with Alzheimer's disease: implications for impaired odor sensitivity. Neurobiol Aging 24, 663673.Google Scholar
31 Jiang, R, Jacobs, DR, Mayer-Davis, E, et al. (2006) Nut and seed consumption and inflammatory markers in the multi-ethnic study of atherosclerosis. Am J Epidemiol 163, 222231.Google Scholar
32 Kern, RC (2000) Chronic sinusitis and anosmia: pathologic changes in the olfactory mucosa. Laryngoscope 110, 10711077.Google Scholar
33 Yee, KK, Pribitkin, EA, Cowart, BJ, et al. (2010) Neuropathology of the olfactory mucosa in chronic rhinosinusitis. Am J Rhinol Allergy 24, 110120.Google Scholar
34 Ros, E (2009) Nuts and novel biomarkers of cardiovascular disease. Am J Clin Nutr 89, 1649S1656S.Google Scholar
35 Segura, R, Javierre, C, Lizarraga, MA, et al. (2006) Other relevant components of nuts: phytosterols, folate and minerals. Br J Nutr 96, Suppl. 2, S36S44.Google Scholar
36 Zhao, G, Etherton, TD, Martin, KR, et al. (2007) Dietary α-linolenic acid inhibits proinflammatory cytokine production by peripheral blood mononuclear cells in hypercholesterolemic subjects. Am J Clin Nutr 85, 385391.Google Scholar
37 Sultan, B, May, LA & Lane, AP (2011) The role of TNF-α in inflammatory olfactory loss. The Laryngoscope 121, 24812486.Google Scholar
38 Calder, PC (2006) n-3 Polyunsaturated fatty acids, inflammation, and inflammatory diseases. Am J Clin Nutr 83, S15051519S.Google Scholar
39 Mesholam, RI, Moberg, PJ, Mahr, RN, et al. (1998) Olfaction in neurodegenerative disease: a meta-analysis of olfactory functioning in Alzheimer's and Parkinson's diseases. Arch Neurol 55, 8490.Google Scholar
40 Seo, H-S, Jeon, K, Hummel, T, et al. (2009) Influences of olfactory impairment on depression, cognitive performance, and quality of life in Korean elderly. Eur Arch Otorhinolaryngol 266, 17391745.Google Scholar
41 Pribis, P & Shukitt-Hale, B (2014) Cognition: the new frontier for nuts and berries. Am J Clin Nutr 100, 347S352S.Google Scholar
42 Cole, GM, Ma, Q-L & Frautschy, SA (2009) ω-3 Fatty acids and dementia. Prostaglandins Leukot Essent Fatty Acids 81, 213221.Google Scholar
43 Czernichow, S, Thomas, D & Bruckert, E (2010) n-6 Fatty acids and cardiovascular health: a review of the evidence for dietary intake recommendations. Br J Nutr 104, 788796.Google Scholar
44 Ramsden, CE, Zamora, D, Leelarthaepin, B, et al. (2013) Use of dietary linoleic acid for secondary prevention of coronary heart disease and death: evaluation of recovered data from the Sydney Diet Heart Study and updated meta-analysis. BMJ 346, e8707.Google Scholar
45 Calder, PC (2001) Polyunsaturated fatty acids, inflammation, and immunity. Lipids 36, 10071024.Google Scholar
46 Ferrucci, L, Cherubini, A, Bandinelli, S, et al. (2006) Relationship of plasma polyunsaturated fatty acids to circulating inflammatory markers. J Clin Endocrinol Metab 91, 439446.Google Scholar
47 Schubert, CR, Cruickshanks, KJ, Fischer, ME, et al. (2012) Olfactory impairment in an adult population: the Beaver Dam Offspring Study. Chem Senses 37, 325334.Google Scholar
Figure 0

Fig. 1 Flowchart of study participation in the Blue Mountains Eye Study from 2002–4 to 2007–9.

Figure 1

Table 1 Study characteristics of Blue Mountains Eye Study participants by presence of olfactory impairment (Mean values and standard deviations; number of participants and percentages)

Figure 2

Table 2 Association between dietary fats and prevalence of olfactory loss in the Blue Mountains Eye Study (Adjusted odds ratios and 95 % confidence intervals, n 1331)

Figure 3

Table 3 Association between food groups and prevalence of olfactory loss in the Blue Mountains Eye Study (Adjusted odds ratios and 95 % confidence intervals, n 1331)

Figure 4

Table 4 Association between food groups and 5-year incidence of olfactory loss in the Blue Mountains Eye Study (Adjusted odds ratios and 95 % confidence intervals, n 667)