Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysis
Abstract Background Previous studies suggest that olfactory dysfunction is associated with cognitive decline or dementia. Objective To find a potential association between the olfactory identification (OI) and dementia onset, and build a prediction model for dementia screening in the older populatio...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-11-01
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| Series: | Brain and Behavior |
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| Online Access: | https://doi.org/10.1002/brb3.1822 |
| _version_ | 1818218214199394304 |
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| author | Ding Ding Xiaoniu Liang Zhenxu Xiao Wanqing Wu Qianhua Zhao Yang Cao |
| author_facet | Ding Ding Xiaoniu Liang Zhenxu Xiao Wanqing Wu Qianhua Zhao Yang Cao |
| author_sort | Ding Ding |
| collection | DOAJ |
| description | Abstract Background Previous studies suggest that olfactory dysfunction is associated with cognitive decline or dementia. Objective To find a potential association between the olfactory identification (OI) and dementia onset, and build a prediction model for dementia screening in the older population. Methods Nine hundred and forty‐seven participants from the Shanghai Aging Study were analyzed. The participants were dementia‐free and completed OI test using the Sniffin’ Sticks Screening Test‐12 at baseline. After an average of 4.9‐year follow‐up, 75 (8%) of the participants were diagnosed with incident dementia. Discrete Bayesian network (DBN) and multivariable logistic regression (MLR) models were used to explore the dependencies of the incident dementia on the baseline demographics, lifestyles, and OI test results. Results In DBN analysis, odors of orange, cinnamon, peppermint, and pineapple, combined with age and Mini‐mental State Examination (MMSE), achieved a high predictive ability for incident dementia, with an area under the receiver operating characteristic curve (AUC) larger than 0.8. The odor cinnamon showed the highest AUC of 0.838 (95% CI: 0.731–0.946) and a high accuracy of 0.867. The DBN incorporating age, MMSE, and one odor test had an accuracy (0.760–0.872 vs. 0.835) comparable to that of the MLR model and revealed the dependency between the variables. Conclusion The DBN using OI test may have predictive ability comparable to MLR analysis and suggest potential causal relationship for further investigation. Identification of odor cinnamon might be a useful indicator for dementia screening and deserve further investigation. |
| first_indexed | 2024-12-12T07:20:12Z |
| format | Article |
| id | doaj.art-e730e225c7c94ec1a1895f8ff7649663 |
| institution | Directory Open Access Journal |
| issn | 2162-3279 |
| language | English |
| last_indexed | 2024-12-12T07:20:12Z |
| publishDate | 2020-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | Brain and Behavior |
| spelling | doaj.art-e730e225c7c94ec1a1895f8ff76496632022-12-22T00:33:24ZengWileyBrain and Behavior2162-32792020-11-011011n/an/a10.1002/brb3.1822Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysisDing Ding0Xiaoniu Liang1Zhenxu Xiao2Wanqing Wu3Qianhua Zhao4Yang Cao5Institute of Neurology Huashan Hospital Fudan University Shanghai ChinaInstitute of Neurology Huashan Hospital Fudan University Shanghai ChinaInstitute of Neurology Huashan Hospital Fudan University Shanghai ChinaInstitute of Neurology Huashan Hospital Fudan University Shanghai ChinaInstitute of Neurology Huashan Hospital Fudan University Shanghai ChinaClinical Epidemiology and Biostatistics, School of Medical Sciences Örebro University Örebro SwedenAbstract Background Previous studies suggest that olfactory dysfunction is associated with cognitive decline or dementia. Objective To find a potential association between the olfactory identification (OI) and dementia onset, and build a prediction model for dementia screening in the older population. Methods Nine hundred and forty‐seven participants from the Shanghai Aging Study were analyzed. The participants were dementia‐free and completed OI test using the Sniffin’ Sticks Screening Test‐12 at baseline. After an average of 4.9‐year follow‐up, 75 (8%) of the participants were diagnosed with incident dementia. Discrete Bayesian network (DBN) and multivariable logistic regression (MLR) models were used to explore the dependencies of the incident dementia on the baseline demographics, lifestyles, and OI test results. Results In DBN analysis, odors of orange, cinnamon, peppermint, and pineapple, combined with age and Mini‐mental State Examination (MMSE), achieved a high predictive ability for incident dementia, with an area under the receiver operating characteristic curve (AUC) larger than 0.8. The odor cinnamon showed the highest AUC of 0.838 (95% CI: 0.731–0.946) and a high accuracy of 0.867. The DBN incorporating age, MMSE, and one odor test had an accuracy (0.760–0.872 vs. 0.835) comparable to that of the MLR model and revealed the dependency between the variables. Conclusion The DBN using OI test may have predictive ability comparable to MLR analysis and suggest potential causal relationship for further investigation. Identification of odor cinnamon might be a useful indicator for dementia screening and deserve further investigation.https://doi.org/10.1002/brb3.1822Bayesian networkcohortdementiaelderlyolfactory functionolfactory identification test |
| spellingShingle | Ding Ding Xiaoniu Liang Zhenxu Xiao Wanqing Wu Qianhua Zhao Yang Cao Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysis Brain and Behavior Bayesian network cohort dementia elderly olfactory function olfactory identification test |
| title | Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysis |
| title_full | Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysis |
| title_fullStr | Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysis |
| title_full_unstemmed | Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysis |
| title_short | Can dementia be predicted using olfactory identification test in the elderly? A Bayesian network analysis |
| title_sort | can dementia be predicted using olfactory identification test in the elderly a bayesian network analysis |
| topic | Bayesian network cohort dementia elderly olfactory function olfactory identification test |
| url | https://doi.org/10.1002/brb3.1822 |
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