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. 2025 Jun 18;50:bjaf020. doi: 10.1093/chemse/bjaf020

Olfaction and diabetes among older adults

Jingjing Xia 1, Yaqun Yuan 2, Chenxi Li 3, Anna Kucharska-Newton 4, Qu Tian 5, Jayant M Pinto 6, Jiantao Ma 7, Eleanor M Simonsick 8, Honglei Chen 9,✉
PMCID: PMC12228038  PMID: 40576410

Abstract

Both poor olfaction and diabetes are common in older adults. It is biologically plausible that they may be related and interact to affect the health of older adults. We examined the association between poor olfaction and diabetes and their joint associations with mortality among 2,416 older adults from the Health, Aging, and Body Composition Study. Olfaction was assessed at year 3 (1999 to 2000) using the Brief Smell Identification Test (B-SIT). We used year 4 (2000 to 2001) as the study baseline and followed participants to year 11 (2007 to 2008) to identify incident diabetes and year 14 (2010 to 2011) to assess mortality. We used logistic regression to analyze the association of poor olfaction with prevalent diabetes and Cox proportional hazard models to assess its relationship to incident diabetes and its joint association with diabetes on mortality. Of the 2,416 participants, 611 (25.3%) had diabetes at baseline and 138 (7.6%) developed incident diabetes during 6.4 ± 1.7 yr of follow-up. Compared to those with good olfaction, the odds ratio of prevalent diabetes was 1.11 (95% confidence interval/CI: 0.87 to 1.42) for those with poor olfaction, and the corresponding hazard ratio (HR) for incident diabetes was 1.01 (95%CI: 0.66 to 1.57). During 8.2 ± 2.8 yr of follow-up, 1007 (41.7%) participants died. Compared with participants without poor olfaction and diabetes, those with both were twice likely to die during the follow-up (HR = 2.16, 95%CI: 1.71 to 2.73). However, we found no evidence for synergistic interaction (P = 0.97). In conclusion, poor olfaction is not associated with the risk of diabetes, and these two conditions independently predict mortality in older adults.

Keywords: diabetes, mortality, older adults, olfaction

Introduction

Diabetes is a multifactorial chronic condition that has been associated with severe health consequences, including disability and premature death (Stratton 2000). This disease can affect people at any age, but the burden is particularly high in middle age to older adults. It is expected that approximately 700 million people will have diabetes worldwide by the end of 2045 (Tinajero and Malik 2021), presenting an urgent need for disease prevention and effective clinical management.

Poor olfaction is often an overlooked sensory deficit but may have a significant impact on an individual’s safety, health, and quality of life (Papazian and Pinto 2021). This is particularly concerning for older adults where poor olfaction affects a quarter of the population (Murphy 2002; Dong et al. 2017). In older adults, poor olfaction has been best studied as a prodromal symptom for neurodegenerative diseases including Parkinson’s (Chen et al. 2017) and dementia (Devanand et al. 2000) and as a robust predictor for all-cause mortality (Wilson et al. 2011; Schubert et al. 2016). Emerging evidence also suggests a link between olfaction to diabetes. Olfaction may play critical roles in food perception and intake which link to energy balance and diabetes development (Croy et al. 2014). Furthermore, insulin, ghrelin, and leptin receptors have been found in the olfactory mucosa and olfactory bulb, indicating the interplay of the olfactory system and these metabolic hormones (Prud’homme et al. 2009; Aimé et al. 2012; Palouzier-Paulignan et al. 2012). Therefore, one may hypothesize that poor olfaction may gradually alter an individual’s dietary habits and food choices, which may over time lead to a higher risk of developing diabetes. However, empirical evidence on this relationship is limited and inconsistent. While some researchers found significant positive associations between the two conditions (Gouveri et al. 2014; Rasmussen et al. 2018), others did not (Hawkins and Pearlson 2011). Furthermore, these studies are predominantly cross-sectional with small samples.

We therefore investigated the association of olfaction with both prevalent and incident diabetes in a well-established, community-based, biracial cohort of older US adults. Furthermore, as both conditions are associated with higher mortality, we also investigated their potential synergistic effect on mortality in older adults. Finally, as Black older adults were about twice as likely as whites to have both poor olfaction and diabetes and had a higher risk of diabetes-related death (Mansour et al. 2020; Mikhail et al. 2021; Cao et al. 2022), we further examined the associations by race.

Methods

Study population

The Health, Aging and Body Composition (Health ABC) study is a prospective cohort that was designed primarily to investigate the role of body composition changes in aging and the development of mobility limitation. At year 1 clinic visit (1997-1998), the study enrolled 3075 well-functioning individuals aged 70 to 79 (48.4% male and 41.6% Black participants) from Pittsburgh, Pennsylvania, and Memphis, Tennessee. Eligibility criteria included (i) free of functional difficulties in walking ¼ mile, climbing 1 flight of stairs, or performing activities of daily living, (ii) no active cancer treatment during the previous 3 yr, (iii) no intention to leave the study area in the next 3 yr. Participants were followed up annually through clinic visits in the first 6 yr, and subsequently in years 8, 10, 11, and 16, supplemented by semiannual or quarterly telephone calls to update health and functional status (Newman et al. 2023).

Olfaction was assessed at the year 3 visit (1999 to 2000) using the 12-item Brief Smell Identification Test (B-SIT) (Doty et al. 1996). Diabetes status was assessed from self-report of a diagnosis, medication records, fasting glucose measurements, and oral glucose tolerance test (OGTT) results which were available for some but not all years. In the current study, we used year 4 (2000 to 2001) as the study baseline because fasting glucose was not available in year 3. Diabetes status was assessed at each follow-up visit until year 11 (2007 to 2008)—the last visit with fasting glucose data. For mortality, the follow-up was through year 14 (2010 to 2011). Of the 3075 Health ABC participants, 2,500 had both B-SIT scores at year 3 and diabetes data at year 4. After excluding 84 participants with missing data on covariates or diabetes diagnosis before age 14 to minimize the inclusion of type-1 diabetes (Rogers et al. 2017), our analytic sample included 2416 participants. The Health ABC study protocol was approved by the institutional review boards at the University of Pittsburgh, the University of Tennessee, Memphis, and the coordinating center at the University of California, San Francisco. All participants provided written informed consent at enrollment. The institutional review board at Michigan State University granted an exemption for the present analysis.

Olfaction test

The B-SIT is a brief version of the 40-item Pennsylvania Smell Identification Test (Doty et al. 1984) and has been widely used in epidemiologic studies to screen for olfactory dysfunction in older adults (Menon et al. 2013; Doty 2015). Participants were shown 12 scent strips, one at a time, each containing a common odorant. They were asked to scratch and smell each odorant and then identify the presented scent from four possible answers in a forced-choice fashion. The B-SIT is scored as a number of correctly identified odors (0 to 12), with higher scores indicating better performance. In this study, we examined B-SIT scores both continuously and categorically using standard cutoffs: good (11 to 12), moderate (9 to 10), or poor (0 to 8) olfaction. When sample size allowed, we further separated hyposmia (7 to 8) from anosmia (0 to 6) (Yuan et al. 2021; Wang et al. 2022).

Outcome assessments

Participants were asked to report every diagnosis of diabetes at year 1 and then diagnosis in the past 12 mo at each follow-up visit. Prescription and over-the-counter medications used in the past 2 or 4 wk were recorded using the medication inventory forms at clinic visits, except years 4, 7, and 9. Fasting glucose was measured at years 4, 6, 10, and 11, and an OGTT was performed at year 1 only. Consistent with published protocols (Park et al. 2006; Doyle et al. 2013; Sacks et al. 2023), we defined diabetes using available data on self-reported diagnosis, antidiabetic medication use, OGTT 2-h postload glucose ≥ 200 mg/dL, or fasting glucose ≥ 126 mg/dL (Supplementary Fig. 1). In addition, diabetic participants were further categorized by treatments and the presence of peripheral neuropathy in cross-sectional exploratory analyses. Peripheral neuropathy was assessed in year 4, including monofilament sensitivity and average vibration detection threshold on the bottom of the great toe (VSA-3000 Vibratory Sensory Analyzer, Medoc, Ramat Yishi, Israel). Monofilament insensitivity was defined as an inability to detect light touch with 5.07 monofilament at least 3 of 4 times. Poor vibration sensation was defined as a vibration threshold > 130 µm (Strotmeyer et al. 2009; Lange-Maia et al. 2017).

The survival of study participants was closely monitored with comprehensive death surveillance. For each identified death event, the team conducted an exit interview with a knowledgeable proxy who provided detailed information on the death event and the participant’s physical functioning before death. In this study, we analyzed the cumulative all-cause mortality until year 14.

Covariates

We selected a range of covariates to control primarily based on literature. Age, sex, and race have well-established associations with olfactory function (Pinto et al. 2014, 2015; Dong et al. 2017). While data on other demographic and lifestyle factors are limited or inconsistent, poor olfaction has been found to be associated with smoking (Ajmani et al. 2017), obesity (Sollai and Crnjar 2023), lower physical activity (Cournoyer et al. 2024), alcohol consumption (Maurage et al. 2014), and lower education level (Fornazieri et al. 2019). Notably, most of these factors are also well-established risk factors for diabetes (Baliunas et al. 2009; Colberg et al. 2016; Walker et al. 2016; Maddatu et al. 2017; Naqvi et al. 2020; Cao et al. 2024). In addition, we also adjusted for having a cold in the week before the B-SIT testing to mitigate potential outcome measurement error. This variable was evidently associated with olfaction in our study population. Finally, we considered dementia in the analyses due to its well-documented association with poor olfaction (Yaffe et al. 2017).

All covariate information was from year 4 visit except for alcohol consumption from year 1 and smoking status and dementia from year 3, due to data availability. These covariates were defined as: age (≤ 76 yr or > 76 yr), sex (female or male), race (Black or white), education level (less than high school, high school, or beyond high school), body mass index (BMI) (< 25, 25 to 30, or > 30 kg/m2), smoking status (never, former, or current smokers), alcohol consumption (never, former, or current drinkers), brisk walking as a proxy for physical activity (< 90 min or ≥ 90 min/week), having cold a week before taking the B-SIT, and dementia. Dementia was defined as the Modified Mini-Mental State examination (3MS) score lower than 80 at year 1, a decline of equal or more than 1.5 race-specific standard deviation in the 3MS score compared to the previous measurement, use of dementia medications, or hospitalization records with a diagnosis of dementia.

Statistical analysis

To compare population characteristics at baseline by olfaction status, we used the unpaired Student’s t test for continuous variables and χ2 tests for categorical variables. We assessed the relationship between olfaction and diabetes both cross-sectionally and longitudinally. In the cross-sectional analyses, we further explored the potential associations between olfaction and prevalent diabetes categorized by treatments and by the presence of peripheral neuropathy. We used multivariable logistic regression or multinormal logistic regression models to estimate the odds ratio (OR) and 95% confidence intervals (CI), adjusting for age, sex, and race, education level, BMI, smoking status, alcohol consumption, brisk walking, and having cold within a week before the B-SIT test. In the prospective analysis on incident diabetes, we reported hazard ratios (HR) and 95%CI using Cox proportional hazard models with the same covariates described above. As diabetes is a chronic condition and we did not precisely assess the age of onset or diagnosis, we used the midpoint between study visits when the disease was first identified as a proxy for disease onset. In both analyses, we used the good olfaction group as the reference. Finally, we examined the potential joint effect and interactions between olfaction and diabetes on overall mortality, using Cox proportional hazard models with time to death as the outcome of interest. We first created six exposure categories of olfaction with prevalent diabetes into good olfaction without diabetes (reference), moderate olfaction without diabetes, poor olfaction without diabetes, and the other three groups of olfaction status with diabetes. We also tested potential interactions by including a multiplicative term in the model. As Black older adults are more likely to have both diabetes and poor olfaction than their white counterparts, we performed race-stratified analyses to explore potential racial disparity. Finally, we conducted sensitivity analyses excluding persons with dementia. All statistical analyses were performed with R, version 4.4.0 (R Foundation), and the “survival” R package (Therneau and Grambsch 2000) was used to fit the cox proportional hazard models, with a 2-sided α of 0.05.

Results

Compared with participants with good olfaction, individuals who exhibited poor olfaction were older and more likely to be male, Black, former smokers, former drinkers, and to report lower educational attainment, have dementia, engage in less physical activity, and reported having a cold in the week before the B-SIT test, but less likely to have obesity (Table 1).

Table 1.

Demographics by olfaction status among participants of the Health ABC study (N = 2416)

Characteristic Olfaction
Good
(11–12)		 Moderate
(9–10)		 Hyposmia
(7–8)		 Anosmia
(0–6)
N = 818 N = 836 N = 429 N = 333
Age (mean ± sd) 76.1 ± 2.7 76.6 ± 2.9 76.9 ± 2.9 77.3 ± 2.9
Sex
 Male 310 (37.9) 401 (48.0) 234 (54.5) 212 (63.7)
 Female 508 (62.1) 435 (52.0) 195 (45.5) 121 (36.3)
Race
 White 565 (69.1) 516 (61.7) 261 (60.8) 160 (48.0)
 Black 253 (30.9) 320 (38.3) 168 (39.2) 173 (52.0)
Education
 Less than high school 123 (15.0) 180 (21.5) 124 (28.9) 112 (33.6)
 High school 278 (34.0) 291 (34.8) 135 (31.5) 96 (28.8)
 After high school 417 (51.0) 365 (43.7) 170 (39.6) 125 (37.5)
Body mass index (kg/m2)
 < 25 210 (25.7) 231 (27.6) 140 (32.6) 103 (30.9)
 25–30 424 (51.8) 401 (48.0) 199 (46.4) 171 (51.4)
 > 30 184 (22.5) 204 (24.4) 90 (21.0) 59 (17.7)
Smoking status
 Never 412 (50.4) 369 (44.1) 188 (43.8) 131 (39.3)
 Former 366 (44.7) 405 (48.4) 196 (45.7) 172 (51.7)
 Current 40 (4.9) 62 (7.4) 45 (10.5) 30 (9.0)
Alcohol consumption
 Never 240 (29.3) 234 (28.0) 122 (28.4) 79 (23.7)
 Former 132 (16.1) 176 (21.1) 96 (22.4) 98 (29.4)
 Current 446 (54.5) 426 (51.0) 211 (49.2) 156 (46.8)
Brisk walking ≥ 90 min/week 88 (10.8) 69 (8.3) 34 (7.9) 19 (5.7)
Cold before Brief Smell Identification test 77 (9.4) 93 (11.1) 63 (14.7) 71 (21.3)
Diabetes 184 (22.5) 216 (25.8) 111 (25.9) 100 (30.0)
Dementia 47 (5.7) 99 (11.8) 94 (21.9) 95 (28.5)
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Olfaction and prevalent diabetes

The cross-sectional analyses included 2,416 participants, including 611 prevalent diabetes. The prevalence of diabetes was 22.5% in participants with good olfaction, 25.9% in those with hyposmia, and 30% in those with anosmia. However, the differences disappeared in multivariable analyses. The adjusted OR was 1.06 (95%CI: 0.80 to 1.42) for those with hyposmia and 1.17 (95%CI: 0.86 to 1.59) for those with anosmia, and 1.11 (0.87 to 1.42) for those with either (Table 2). Sensitivity analyses by diabetes treatment strategies or the presence or absence of peripheral neuropathology also showed null associations (Supplementary Table 1). As expected, Black participants (31.8%) were more likely to have diabetes than their white counterparts (21.3%), but in neither group did we find an association between poor olfaction and prevalent diabetes (Table 2). Sensitivity analyses showed similar results after excluding participants with dementia (Supplementary Table 2).

Table 2.

Olfaction in relation to prevalent diabetes (N = 2416)

Olfaction Overall
(N = 2416)		 Black
(N = 914)		 White
(N = 1,502)
Diabetes (%) ORa (95%CI) Diabetes (%) ORb (95%CI) Diabetes (%) ORb (95%CI)
B-SIT score, 1 unit increase 611 (25.3) 0.98 (0.94, 1.02) 291 (31.8) 0.97 (0.92, 1.03) 320 (21.3) 0.99 (0.93, 1.04)
Good (11–12) 184 (22.5) 1.00 74 (29.2) 1.00 110 (19.5) 1.00
Moderate (9–10) 216 (25.8) 1.08 (0.85, 1.36) 100 (31.2) 1.00 (0.69, 1.45) 116 (22.5) 1.11 (0.82, 1.50)
Poor (0–8) 211 (27.7) 1.11 (0.87, 1.42) 117 (34.3) 1.13 (0.77, 1.65) 94 (22.3) 1.06 (0.76, 1.47)
 Hyposmia (7-8) 111 (25.9) 1.06 (0.80, 1.42) 54 (32.1) 1.02 (0.65, 1.59) 57 (21.8) 1.07 (0.73, 1.56)
 Anosmia (0–6) 100 (30.0) 1.17 (0.86, 1.59) 63 (36.4) 1.25 (0.80, 1.95) 37 (23.1) 1.04 (0.66, 1.62)
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aModel adjusted for age, sex, race, education, body mass index, smoking status, alcohol consumption, brisk walking, cold before B-SIT.

bModel adjusted for age, sex, education, body mass index, smoking status, alcohol consumption, brisk walking, cold before B-SIT.

OR: Odds ratio; CI: Confidence interval; B-SIT: Brief Smell Identification Test.

Olfaction and incident diabetes

This analysis included 1,805 participants who were free of diabetes at baseline. During 6.4 ± 1.7 yr of follow-up, we identified 138 (7.6%) incident diabetic cases. As with the cross-sectional analyses, we did not identify any association between olfaction and incident diabetes (Table 3 and Supplementary Table 3).

Table 3.

Olfaction in relation to incident diabetes (N = 1,805)

Olfaction Overall
(N = 1,805)		 Black
(N = 623)		 White
(N = 1,182)
Diabetes (%) HRa (95%CI) Diabetes (%) HRb (95%CI) Diabetes (%) HRb (95%CI)
B-SIT score, 1 unit increase 138 (7.6) 0.99 (0.92, 1.07) 60 (9.6) 0.99 (0.89, 1.11) 78 (6.6) 0.99 (0.89, 1.10)
Good (11–12) 48 (7.6) 1.00 18 (10.1) 1.00 30 (6.6) 1.00
Moderate (9–10) 49 (7.9) 0.98 (0.66, 1.48) 21 (9.6) 0.92 (0.48, 1.76) 28 (7.0) 1.03 (0.61, 1.73)
Poor (0–8) 41 (7.4) 1.01 (0.66, 1.57) 21 (9.4) 1.06 (0.54, 2.07) 20 (6.1) 1.00 (0.56, 1.80)
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aModel adjusted for age, sex, race, education, body mass index, smoking status, alcohol consumption, brisk walking, cold before B-SIT.

bModel adjusted for age, sex, education, body mass index, smoking status, alcohol consumption, brisk walking, cold before B-SIT.

HR: Hazard ratio; CI: Confidence interval; B-SIT: Brief Smell Identification Test.

Joint effects of olfaction with diabetes on the risk of death

This analysis included 2,416 participants, 1,007 of whom died during 8.2 ± 2.8 yr of follow-up. As expected, both poor olfaction and diabetes were associated with higher mortality (Supplementary Table 4). In the joint-effect analyses, compared with participants with good olfaction and no diabetes, the adjusted HR of death was 1.54 (95%CI: 1.27 to 1.86) for those with poor olfaction only, 1.44 (95%CI: 1.10 to 1.89) for those with diabetes only, and 2.16 (95%CI: 1.71 to 2.73) for those with both (Fig. 1). There is no synergistic effect between these two conditions on mortality (P for interaction = 0.97). Results were essentially the same in the stratified analyses by race and sensitivity analyses (Supplementary Tables 5–6).

Fig. 1.

Fig. 1.

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The joint associations of olfaction and diabetes with mortality (N = 2416). We tested statistical interaction by adding the product term of olfaction with diabetes status, and the p for interaction was 0.97.

Discussion

Despite the biological plausibility, we found no empirical evidence that poor olfaction may play a role in diabetes development and progression. In this well-established community-based biracial cohort of older US adults, poor olfaction was not associated with diabetes either cross-sectionally or prospectively. Furthermore, while both conditions were associated with increased mortality, they evidently were independent of each other. Data were consistent in multiple sensitivity and subgroup analyses.

Both diabetes and poor olfaction are prevalent among older adults. While diabetes has been recognized as a major public health burden for decades, poor olfaction was largely an underrecognized sensory deficit until the COVID pandemic (Carfì et al. 2020). Olfactory loss accelerates with age in older adults (Murphy 2002; Cao et al. 2022), and it robustly predicts their risk of Parkinson’s disease(Chen et al. 2017), dementia(Yaffe et al. 2017), and mortality (Liu et al. 2019). Recent evidence suggests poor olfaction may have broader implications on the health of older adults, implicating physical functional decline (Yuan et al. 2024), frailty (Nagururu et al. 2023), cardiovascular (Chamberlin et al. 2024), and lung health (Yuan et al. 2021).

Olfaction is an essential human sense and may play a crucial role in food choices and nutrition. Notably, poor sense of smell may alter one’s flavor perception, appetite, and dietary habit, which may in turn affect their risk of diabetes over time (Croy et al. 2014; Faour et al. 2022; López et al. 2023). Further, diabetes-related metabolic hormones such as insulin, ghrelin, and their receptors are found in the olfactory mucosa and olfactory bulb (Jovanovic and Riera 2022). Animal experimental evidence suggests interplays between olfaction and energy metabolism, which again may have implications in the development of diabetes (Massolt et al. 2010; Tong et al. 2011; Riera et al. 2017). Finally, among diabetes patients, olfaction may interplay with dietary and metabolic changes to affect disease prognosis. These preliminary data and speculations implicate poor olfaction in both the development and management of diabetes. As both poor olfaction and diabetes are common in older adults, there is a public health importance to understand whether and how they may interact to affect the health of older adults.

Despite this biological plausibility, empirical data on olfaction and diabetes in older adults are limited. In 1993, Le Floch et al. found lower smell identification scores in diabetic patients than controls. While this finding was confirmed in several subsequent cross-sectional analyses (Naka et al. 2010; Brady et al. 2013; Gouveri et al. 2014; Chan et al. 2018; Li et al. 2022), others found a null association (Ekström et al. 2020; Kaya et al. 2020). One of the null association studies was conducted among African Americans, who are at higher risks of both poor olfaction and diabetes than whites (Hawkins and Pearlson 2011). Notably, three studies analyzed data from the National Health and Nutrition Examination Surveys (NHANES) and reported somewhat inconsistent results. Using 2011–2014 NHANES data, Li et al. (Li et al. 2022) found more self-reported poor olfaction among prediabetic and diabetic persons than individuals without diabetes. However, it is well-known that self-reported olfactory impairment has a very low sensitivity when evaluated against testing results (Cao et al. 2022). The other two studies analyzed the same 2013–2014 NHANES data where olfaction was assessed using the 8-item pocket olfaction identification test. While Rasmussen et al. (Rasmussen et al. 2018) reported a higher prevalence of poor olfaction in diabetic patients than non-diabetic controls, Chan et al. (Chan et al. 2018) failed to confirm the overall association but found a difference in olfaction between insulin-treated and untreated diabetes. Several other studies also examined poor olfaction with diabetes treatment, complications, and peripheral neuropathy (Duda-Sobczak et al. 2017; Yazla et al. 2018; Catamo et al. 2021; Mozzanica et al. 2022). Again, the findings are not consistent.

Evidently, data to date are predominantly cross-sectional with small sample sizes and mostly examine olfaction as a comorbidity of diabetic patients. Compared to most of the previous studies, the current study was conducted in a large, community-based, biracial, and well-established cohort. The study population had been followed for a relatively long time period. In addition, we systematically examined the potential links both cross-sectionally and prospectively. Furthermore, to our knowledge, we are the first to examine whether poor olfaction and diabetes synergistically affect the mortality in older adults. Overall, this study did not find any evidence that poor olfaction and diabetes are associated in older adults.

There are several notable limitations. First, the study population was relatively advanced in age at baseline, and thus our findings may not be generalizable to relatively younger populations. To this end, a previous study found a higher prevalence of olfaction impairment in diabetic patients under 70 yr old, but not in those over 70 (Rasmussen et al. 2018). Therefore, this association should be further evaluated in younger older adults. Second, olfaction loss accelerates with age in older adults. In the current study, we tested olfaction just once at the year 3 clinic visit and studied primarily whether poor olfaction signifies future risk of diabetes. As such, our study did not investigate whether diabetes may contribute to olfactory loss in older adults. Third, fasting glucose data was available only at year 4, 6, 10, and 11 clinic visits. Thus, for study visits with no fasting glucose data, identification of diabetes cases relied on self-reported diagnoses and antidiabetic medication use and was thus subject to case identification errors. However, similar approaches have been commonly used in identifying diabetic persons in other large cohort studies (Doyle et al. 2013; Larsen et al. 2016), and thus we do not feel the null association was due to non-differential outcome measurement error.

Conclusion

Our results suggest that poor olfaction is not associated with the development of diabetes in older adults but that both conditions independently contribute to the prediction of premature death. Further studies should investigate these associations in younger populations and evaluate whether diabetes contributes to olfactory loss using repeated measures of olfaction.

Supplementary Material

bjaf020_suppl_Supplementary_Figure_S1
bjaf020_suppl_supplementary_figure_s1.jpeg (719.9KB, jpeg)
bjaf020_suppl_Supplementary_Tables
bjaf020_suppl_supplementary_tables.docx (39.2KB, docx)

Acknowledgments

We thank the participants of the Health ABC study for their contributions and dedication to health research.

Contributor Information

Jingjing Xia, Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, United States.

Yaqun Yuan, Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, United States.

Chenxi Li, Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, United States.

Anna Kucharska-Newton, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.

Qu Tian, Translational Gerontology Branch, Intramural Research Program of National Institute on Aging, Baltimore, MD, United States.

Jayant M Pinto, Section of Otolaryngology-Head and Neck Surgery, Department of Surgery, The University of Chicago Medicine and Biological Sciences, Chicago, IL, United States.

Jiantao Ma, Division of Nutrition Epidemiology and Data Science, Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States.

Eleanor M Simonsick, Translational Gerontology Branch, Intramural Research Program of National Institute on Aging, Baltimore, MD, United States.

Honglei Chen, Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, United States.

Author contributions

HC and JX conceived the study. HC and EMS provided the data. JX, CL, and HC designed the study and conducted statistical analyses. JX and HC prepared the first draft of the manuscript, and all other coauthors provided critical revision comments. All authors accessed and verified data. All authors contributed to the interpretation of the results and approved the final version for submission. HC had final responsibility to submit for publication.

Conflict of interest

Dr. Jayant M. Pinto is on the speaker’s bureau for Sanofi, Regeneron, and Optinose; he also serves as a site investigator for Sanofi/Regeneron, Upstream Bio and Lyra Therapeutics. He has served on an advisory board for Connect Biopharma. Other coauthors have no conflicts of interest to disclose.

Funding

This project was supported by a grant from the National Institute on Aging (1R01AG071517). The Health ABC study was supported by the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), the Intramural Research Program of the NIA/NIH, and NIA contracts N01AG62101, N01AG62103, N01AG62106, NIA grant R01AG028050 and NINR grant R01NR012459. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the funding agency.

Data availability

Data used in this study are available from the National Institute on Aging (NIA) Health ABC Study. To access the data, investigators should submit an analytical proposal online at https://healthabc.nia.nih.gov/ancillary-biospecimen-proposals.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

bjaf020_suppl_Supplementary_Figure_S1
bjaf020_suppl_supplementary_figure_s1.jpeg (719.9KB, jpeg)
bjaf020_suppl_Supplementary_Tables
bjaf020_suppl_supplementary_tables.docx (39.2KB, docx)

Data Availability Statement

Data used in this study are available from the National Institute on Aging (NIA) Health ABC Study. To access the data, investigators should submit an analytical proposal online at https://healthabc.nia.nih.gov/ancillary-biospecimen-proposals.

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