Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine
Abstract
1. Introduction
2. Subjects and Methods
3. Results
3.1. General Characteristics of Subjects
3.2. The General Characteristics of Subjects According to the Level of the Swallowing Quality-of-Life
3.3. The Function Weights of Gaussian Kernel Algorithm-Based SVM
3.4. The Prediction Accuracy of the SVM-Based Swallowing Quality-of-Life
4. Discussion
5. Conclusions
Funding
Conflicts of Interest
References
- Clark, H.M.; Solomon, N.P. Age and sex differences in orofacial strength. Dysphagia 2011, 27, 2–9. [Google Scholar] [CrossRef] [PubMed]
- Akinari, I.; Ippei, T.; Sizuka, K.; Yuki, S.; Toshiaki, O.; Yoshihiro, T.; Takao, N.; Kouichi, M.; Shigeyuki, N.; Wataru, K. Oral conditions and dysphagia in Japanese, communitydwelling middle-and older-aged adults, independent in daily living. Clin. Interv. Aging 2017, 12, 515–521. [Google Scholar] [CrossRef] [PubMed]
- Korea Institute for Health and Social Affairs. Report on the Korean National Older Adults Life Survey 2014; Ministry of Health Welfare: Seoul, Korea, 2015. [Google Scholar]
- Sura, L.; Madhavan, A.; Carnaby, G.; Crary, M.A. Dysphagia in the elderly: Management and nutritional considerations. Clin. Interv. Aging 2012, 7, 287–298. [Google Scholar] [PubMed]
- Eslick, G.D.; Talley, N.J. Dysphagia: Epidemiology, risk factors and impact on quality of life—A population-based study. Aliment. Pharmacol. Ther. 2008, 27, 971–979. [Google Scholar] [CrossRef]
- Cho, M.J.; Lee, E.; Youm, Y.S.; Kim, H.C.; Jung, E.K.; Kim, J.K.; Song, K.B.; Choi, Y.H. Relationship between stress and subjective oral dryness in the elderly in a rural region: A pilot study. J. Korean Acad. Oral Health 2017, 41, 243–249. [Google Scholar] [CrossRef]
- Roy, N.; Stemple, J.; Merrill, R.M.; Thomas, L. Dysphagia in the elderly: Preliminary evidence of prevalence, risk factors, and socioemotional effects. Ann. Otol. Rhinol. Laryngol. 2007, 116, 858–865. [Google Scholar] [CrossRef]
- Byeon, H. Analysis of dysphagia risk using the modified dysphagia risk assessment for the community-dwelling elderly. J. Phys. Ther. Sci. 2016, 28, 2507–2509. [Google Scholar] [CrossRef][Green Version]
- Vogel, A.P.; Brown, S.E.; Folker, J.E.; Corben, L.A.; Delatycki, M.B. Dysphagia and swallowing-related quality of life in Friedreich ataxia. J. Neurol. 2014, 26, 392–399. [Google Scholar] [CrossRef]
- Ozden, F.O.; Ozgonenel, O.; Ozden, B.; Aydogdu, A. Diagnosis of periodontal diseases using different classification algorithms: A preliminary study. Niger. J. Clin. Pract. 2015, 18, 416–421. [Google Scholar] [CrossRef]
- Lin, H.T.; Lin, C.J. A study on sigmoid kernels for SVM and the training of non-PSD kernels by SMO-type methods. Submitt. Neural Comput. 2003, 3, 1–32. [Google Scholar]
- Mchorney, C.A.; Robbins, J.; Lomax, K.; Rosenbek, J.C.; Chignell, K.; Kramer, A.E.; Bricker, D.E. The SWAL-QOL and SWAL-CARE outcomes tool for oropharyngeal dysphagia in adults: III. documentation of reliability and validity. Dysphagia 2002, 17, 97–114. [Google Scholar] [CrossRef] [PubMed]
- Kim, S.Y.; Cha, Y.J. Reliability and validity of Korean version of the SWAL-QOL. J. Korea Acad. Ind. Cooper. Soc. 2014, 15, 2981–2988. [Google Scholar]
- Hong, D.G.; Yoo, D.H. A comparison of the swallowing function and quality of life by oral intake level in stroke patients with dysphagia. J. Phys. Ther. Sci. 2017, 29, 1552–1554. [Google Scholar] [CrossRef] [PubMed]
- Kang, Y.; Na, D.L.; Hahn, S. A validity study on the Korean Mini-Mental State Examination (K-MMSE) in dementia patients. J. Korean Neurol. Assoc. 1997, 15, 300–308. [Google Scholar]
- Kee, B.S. A preliminary study for the standardization of geriatric depression scale short form-Korea version. J. Korean Neuropsychiatr. Assoc. 1996, 131, 298–307. [Google Scholar]
- Kim, J.Y. Effect Factors on Psychological Well-Being in Elderly Women; Catholic University: Daegu, Korea, 2008. [Google Scholar]
- Raho, G.; Al-Shalabi, R.; Kanaan, G.; Nassar, A. Different classification algorithms based on Arabic text classification: Feature selection comparative study. Int. J. Adv. Comput. Sci. Appl. 2015, 6, 23–28. [Google Scholar] [CrossRef]
- Steinwart, I.; Christmann, A. Support Vector Machines; Springer Science & Business Media: Manhattan, NY, USA, 2008. [Google Scholar]
- Furey, T.S.; Cristianini, N.; Duffy, N.; Bednarski, D.W.; Schummer, M.; Haussler, D. Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 2000, 16, 906–914. [Google Scholar] [CrossRef] [PubMed]
- Fukada, J.; Kamakura, Y.; Manzai, T.; Kitaike, T. Development of dysphagia risk screening system for elderly persons. Jpn. J. Dysphagia Rehabilit. 2006, 10, 31–42. [Google Scholar]
- Chouinard, J. Dysphagia in Alzheimer disease: A review. J. Nutr. Health Aging 2000, 4, 214–217. [Google Scholar]
- Wieseke, A.; Bantz, D.; Siktberg, L.; Dillard, N. Assessment and Early Diagnosis of Dysphagia. Geriatr. Nurs. 2008, 29, 376–383. [Google Scholar] [CrossRef]
- Whang, S.A. Prevalence and influencing factors of dysphagia risk in the community-dwelling elderly. J. Kor. Gerontol. Soc. 2014, 34, 37–48. [Google Scholar]
- Holland, G.; Jayasekeran, V.; Pendleton, N.; Horan, M.; Jones, M.; Hamdy, S. Prevalence and symptom profiling of oropharyngeal dysphagia in a community dwelling of an elderly population: A self-reporting questionnaire survey. Dis. Esophagus 2011, 24, 476–480. [Google Scholar] [CrossRef] [PubMed]
- Kuo, B.C.; Ho, H.H.; Li, C.H.; Hung, C.C.; Taur, J.S. A kernel-based feature selection method for SVM with RBF kernel for hyperspectral image classification. J. Sel. Top. Appl. Earth Obs. Remote Sens. 2014, 7, 317–326. [Google Scholar]
- Byeon, H. Model Development for Predicting the Occurrence of Benign Laryngeal Lesions using Support Vector Machine: Focusing on South Korean Adults Living in Local Communities. Int. J. Adv. Comput. Sci. Appl. 2018, 9, 222–227. [Google Scholar] [CrossRef]
Variables | Subcategory | Total (n = 142) |
---|---|---|
Age | 65–74 | 30 (20.8) |
≥75 | 112 (79.2) | |
Gender | Male | 31 (21.7) |
Female | 111 (78.3) | |
Education level | Elementary school graduate and below | 84 (59.0) |
Middle school graduate | 29 (20.5) | |
High school graduate or above | 29 (20.5) | |
Living with a family | Living with a spouse and a child | 31 (22.1) |
Living only with a spouse | 28 (19.5) | |
Living only with a child | 23 (16.2) | |
Living alone | 60 (42.2) | |
Economy activity | Yes | 14 (10.1) |
No | 128 (89.9) | |
Mean monthly household income | <2 million KRW | 103 (72.8) |
2–4 million KRW | 27 (18.7) | |
>4 million KRW | 12 (8.5) | |
Experience of aspiration in the past 1 month | Yes | 88 (62.2) |
No | 54 (37.8) | |
Mean required time to finish a meal | ≤15 min | 43 (30.3) |
16–39 min | 94 (66.5) | |
≥40 min | 5 (3.2) | |
Denture use | Yes | 90 (63.7) |
No | 52 (36.3) | |
Cognitive level | Normal | 102 (72.0) |
Cognitive impairment | 40 (28.0) | |
Depression | Yes | 25 (17.7) |
No | 117 (82.3) | |
Life stress | Yes | 29 (20.5) |
No | 113 (79.5) | |
Swallowing Quality-of-Life | High | 94 (66.1) |
Low | 48 (33.9) |
Variables | Subcategory | Swallowing-Quality of Life | p | |
---|---|---|---|---|
Low (n = 48) | High (n = 94) | |||
Age | 65–74 | 9 (30.0) | 21 (70.0) | <0.001 |
≥75 | 43 (38.4) | 69 (61.6) | ||
Gender | Male | 10 (32.3) | 21 (67.7) | <0.001 |
Female | 45 (44.6) | 56 (55.4) | ||
Education level | Elementary school graduate and below | 30 (35.7) | 54 (64.3) | <0.001 |
Middle school graduate | 9 (31.0) | 20 (69.0) | ||
High school graduate or above | 6 (20.7) | 23 (79.3) | ||
Living with a family | Living with a spouse and a child | 5 (16.1) | 26 (83.9) | <0.001 |
Living only with a spouse | 6 (17.6) | 28 (82.4) | ||
Living only with a child | 5 (17.9) | 23 (82.1) | ||
Living alone | 19 (31.7) | 41 (68.3) | ||
Economy activity | Yes | 4 (28.6) | 10 (71.4) | 0.415 |
No | 39 (30.5) | 89 (69.5) | ||
Mean monthly household income | <2 million KRW | 20 (19.4) | 83 (80.6) | 0.153 |
2–4 million KRW | 5 (18.5) | 22 (81.5) | ||
>4 million KRW | 2 (16.7) | 10 (83.3) | ||
Experience of aspiration in the past 1 month | Yes | 35 (39.8) | 53 (60.2) | <0.001 |
No | 12 (22.2) | 42 (77.8) | ||
Mean required time to finish a meal | ≤15 min | 13 (30.2) | 30 (69.8) | <0.001 |
16–39 min | 10 (10.6) | 84 (89.4) | ||
≥40 min | 2 (40.0) | 3 (60.0) | ||
Denture use | Yes | 36 (40.0) | 54 (60.0) | <0.001 |
No | 11 (21.2) | 41 (78.8) | ||
Cognitive level | Normal | 13 (12.7) | 89 (87.3) | <0.001 |
Cognitive impairment | 18 (45.0) | 22 (55.0) | ||
Depression | Yes | 5 (20.0) | 20 (80.0) | 0.583 |
No | 24 (20.5) | 93 (79.5) | ||
Life stress | Yes | 8 (8.5) | 86 (91.5) | 0.830 |
No | 4 (8.3) | 44 (91.7) |
65–74 years old | −0.008 |
≥75 years old | 0.017 |
Male | −0.011 |
Female | 0.015 |
Elementary school graduate and below | 0.019 |
Middle school graduate | −0.007 |
High school graduate or above | −0.030 |
Living with a spouse and a child | −0.018 |
Living only with a spouse | −0.011 |
Living only with a child | −0.007 |
Living alone | 0.008 |
Economy activity | 0.011 |
Economy inactivity | −0.031 |
Mean monthly household income: <2 million KRW | 0.029 |
Mean monthly household income: 2–4 million KRW | −0.015 |
Mean monthly household income: >4 million KRW | −0.021 |
Experience of aspiration in the past 1 month: Yes | 0.054 |
Experience of aspiration in the past 1 month: No | −0.009 |
Mean required time to finish a meal: ≤15 min | 0.034 |
Mean required time to finish a meal: 16–39 min | −0.011 |
Mean required time to finish a meal: ≥40 min | 0.023 |
Denture use: Yes | 0.045 |
Denture use: No | −0.030 |
Cognitive level: Normal | −0.009 |
Cognitive impairment | −0.028 |
Depression: Yes | 0.005 |
Depression: No | −0.003 |
Life stress: Yes | 0.011 |
Life stress: No | −0.019 |
Number of Support Vector: 435 |
Type of SVM | Type of Kernel | |||
---|---|---|---|---|
Linear | Polynomial | Gaussian | Sigmoid | |
C-SVM | 90.95 | 90.31 | 91.08 | 89.75 |
Nu-SVM | 90.43 | 90.28 | 91.03 | 89.66 |
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Byeon, H. Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine. Int. J. Environ. Res. Public Health 2019, 16, 4269. https://doi.org/10.3390/ijerph16214269
Byeon H. Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine. International Journal of Environmental Research and Public Health. 2019; 16(21):4269. https://doi.org/10.3390/ijerph16214269
Chicago/Turabian StyleByeon, Haewon. 2019. "Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine" International Journal of Environmental Research and Public Health 16, no. 21: 4269. https://doi.org/10.3390/ijerph16214269
APA StyleByeon, H. (2019). Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine. International Journal of Environmental Research and Public Health, 16(21), 4269. https://doi.org/10.3390/ijerph16214269