Risk Factors for Dementia Incidence Based on Previous Results of the Specific Health Checkups in Japan
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Alladi, S.; Hachinski, V. World dementia: One approach does not fit all. Neurology 2018, 91, 264–270. [Google Scholar] [CrossRef]
- World Health Organization; Alzheimer’s Disease International. Dementia: A Public Health Priority; WHO Press: Geneva, Switzerland, 2012. [Google Scholar]
- UK to host G8 dementia summit. Clin. Pharm. 2013. [CrossRef]
- Ninomiya, T. General Research Report to the Future Estimation of the Elderly Population of the Dementia of a Japanese. Available online: https://mhlw-grants.niph.go.jp/niph/search/NIDD00.do?resrchNum=201405037A (accessed on 14 October 2020).
- Keang, L.T.; Feng, L.; Nyunt, M.S.; Feng, L.; Gao, Q.; Lim, M.L.; Collinson, S.L.; Chong, M.S.; Lim, W.S.; Lee, T.-S.; et al. Metabolic Syndrome and the Risk of Mild Cognitive Impairment and Progression to Dementia. JAMA Neurol. 2016, 73, 456–463. [Google Scholar] [CrossRef] [Green Version]
- Biessels, G.J.; Staekenborg, S.; Brunner, E.; Brayne, C.; Scheltens, P. Risk of dementia in diabetes mellitus: A systematic review. Lancet Neurol. 2006, 5, 64–74. [Google Scholar] [CrossRef]
- Katon, W.; Lin, E.H.B.; Williams, L.H.; Ciechanowski, P.; Heckbert, S.R.; Ludman, E.; Rutter, C.; Crane, P.K.; Oliver, M.; Von Korff, M. Comorbid Depression is Associated with an Increased Risk of Dementia Diagnosis in Patients with Diabetes: A Prospective Cohort Study. J. Gen. Intern. Med. 2010, 25, 423–429. [Google Scholar] [CrossRef] [Green Version]
- Ma, F.; Wu, T.; Miao, R.; Xiao, Y.Y.; Zhang, W.; Huang, G. Conversion of Mild Cognitive Impairment to Dementia among Subjects with Diabetes: A Population-Based Study of Incidence and Risk Factors with Five Years of Follow-up. J. Alzheimer’s Dis. 2014, 43, 1441–1449. [Google Scholar] [CrossRef]
- Ninomiya, T. Epidemiological Evidence of the Relationship Between Diabetes and Dementia. Single Mol. Single Cell Seq. 2019, 1128, 13–25. [Google Scholar] [CrossRef]
- Bello-Chavolla, O.Y.; Antonio-Villa, N.E.; Vargas-Vázquez, A.; Ávila-Funes, J.A.; Aguilar-Salinas, C.A. Pathophysiological Mechanisms Linking Type 2 Diabetes and Dementia: Review of Evidence from Clinical, Translational and Epidemiological Research. Curr. Diabetes Rev. 2019, 15, 456–470. [Google Scholar] [CrossRef]
- Yokomichi, H.; Nagai, A.; Hirata, M.; Kiyohara, Y.; Muto, K.; Ninomiya, T.; Matsuda, K.; Kamatani, Y.; Tamakoshi, A.; Kubo, M.; et al. Serum glucose, cholesterol and blood pressure levels in Japanese type 1 and 2 diabetic patients: BioBank Japan. J. Epidemiol. 2017, 27, S92–S97. [Google Scholar] [CrossRef]
- Albanese, E.; Launer, L.J.; Egger, M.; Prince, M.J.; Giannakopoulos, P.; Wolters, F.J.; Egan, K. Body mass index in midlife and dementia: Systematic review and meta-regression analysis of 589,649 men and women followed in longitudinal studies. Alzheimer’s Dementia: Diagn. Assess. Dis. Monit. 2017, 8, 165–178. [Google Scholar] [CrossRef]
- Pedditizi, E.; Peters, R.; Beckett, N. The risk of overweight/obesity in mid-life and late life for the development of dementia: A systematic review and meta-analysis of longitudinal studies. Age Ageing 2016, 45, 14–21. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Stewart, R.; Masaki, K.; Xue, Q.-L.; Peila, R.; Petrovitch, H.; White, L.R.; Launer, L.J. A 32-Year Prospective Study of Change in Body Weight and Incident Dementia. Arch. Neurol. 2005, 62, 55–60. [Google Scholar] [CrossRef] [Green Version]
- Buchman, A.S.; Schneider, J.A.; Wilson, R.S.; Bienias, J.L.; Bennett, D.A. Body mass index in older persons is associated with Alzheimer disease pathology. Neurology 2006, 67, 1949–1954. [Google Scholar] [CrossRef] [PubMed]
- Johnson, D.K.; Wilkins, C.H.; Morris, J.C. Accelerated Weight Loss May Precede Diagnosis in Alzheimer Disease. Arch. Neurol. 2006, 63, 1312–1317. [Google Scholar] [CrossRef] [PubMed]
- van der Burg, J.M.; Pijl, H.; Campman, Y.J.; Roos, R.A.; Aziz, N.A. Does midlife obesity really lower dementia risk? Lancet Diabetes Endocrinol. 2015, 3, 499–500. [Google Scholar] [CrossRef]
- Yokomichi, H.; Kondo, K.; Nagamine, Y.; Yamagata, Z.; Kondo, N. Dementia risk by combinations of metabolic diseases and body mass index: Japan Gerontological Evaluation Study Cohort Study. J. Diabetes Investig. 2019, 11, 206–215. [Google Scholar] [CrossRef] [PubMed]
- Tamaki, Y.; Okamoto, E.; Hiratsuka, Y.; Kumakawa, T. Influence of Specific Health Guidance on the Consultation Rate of Metabolic-Related Diseases. Adv. Public Health 2019, 2019, 9735127. [Google Scholar] [CrossRef]
- Japanese Ministry of Health, Labour and Welfare. Long-Term Care, Health and Welfare Services for the Elderly. Available online: http://www.mhlw.go.jp/english/policy/care-welfare/care-welfare-elderly/ (accessed on 14 October 2020).
- Japanese Ministry of Health, Labour and Welfare. “Long-Term Care Insurance Business Situation,”. Available online: https://www.mhlw.go.jp/topics/kaigo/toukei/joukyou.html (accessed on 14 October 2020).
- Tamaki, Y.; Hiratsuka, Y.; Kumakawa, T.; Miura, H. Relationship between the Necessary Support Level for Oral Hygiene and Performance of Physical, Daily Activity, and Cognitive Functions. Int. J. Dent. 2018, 2018, 1542713. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Japanese Ministry of Health, Labour and Welfare. Ethical Guidelines for Epidemiological Research. Ministry of Education, Culture, Sports, Science and Technology. Available online: http://www.lifescience.mext.go.jp/files/pdf/n796_01.pdf (accessed on 14 October 2020).
- Japanese Ministry of Health, Labour and Welfare. Guideline for Provision of Database for National Health Insurance Claim and the Specific Medical Checkup and Specific Health Guidance. Available online: http://www.mhlw.go.jp/file/05-Shingikai-12401000-Hokenkyoku-Soumuka/0000064238_3.pdf (accessed on 14 October 2020).
- Japanese Ministry of Health, Labour and Welfare. Security Guidelines for Health Information Systems. Available online: http://www.mhlw.go.jp/file/05-Shingikai-12601000-Seisakutoukatsukan-Sanjikanshitsu_Shakaihoshoutantou/0000166260.pdf (accessed on 14 October 2020).
- Okamoto, E. Cost-Benefit of Health Promotion: Will it Pay Off? Japan’s Venture Against Metabolic Syndrome. In Asian Perspectives and Evidence on Health Promotion and Education; Springer: Tokyo, Japan, 2011; pp. 182–195. [Google Scholar] [CrossRef]
- Japanese Ministry of Health, Labour and Welfare. Estimated Medical Cost Database. Available online: http://www.mhlw.go.jp/bunya/iryouhoken/iryouhoken03/01.html (accessed on 14 October 2020).
- Qizilbash, N.; Gregson, J.; E Johnson, M.; Pearce, N.; Douglas, I.J.; Wing, K.; Evans, S.J.W.; Pocock, S.J. BMI and risk of dementia in two million people over two decades: A retrospective cohort study. Lancet Diabetes Endocrinol. 2015, 3, 431–436. [Google Scholar] [CrossRef]
- Nam, G.E.; Park, Y.G.; Han, K.; Kim, M.K.; Koh, E.S.; Kim, E.S.; Lee, M.-K.; Kim, B.; Hong, O.-K.; Kwon, H.-S. BMI, Weight Change, and Dementia Risk in Patients With New-Onset Type 2 Diabetes: A Nationwide Cohort Study. Diabetes Care 2019, 42, 1217–1224. [Google Scholar] [CrossRef]
- Kivimäki, M.; Luukkonen, R.; Batty, G.D.; Ferrie, J.E.; Pentti, J.; Nyberg, S.T.; Shipley, M.J.; Alfredsson, L.; Fransson, E.I.; Goldberg, M.; et al. Body mass index and risk of dementia: Analysis of individual-level data from 1.3 million individuals. Alzheimer’s Dement. 2018, 14, 601–609. [Google Scholar] [CrossRef] [PubMed]
- Hirabayashi, N.; Hata, J.; Ohara, T.; Mukai, N.; Nagata, M.; Shibata, M.; Gotoh, S.; Furuta, Y.; Yamashita, F.; Yoshihara, K.; et al. Association Between Diabetes and Hippocampal Atrophy in Elderly Japanese: The Hisayama Study. Diabetes Care 2016, 39, 1543–1549. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Matsuzaki, T.; Sasaki, K.; Tanizaki, Y.; Hata, J.; Fujimi, K.; Matsui, Y.; Sekita, A.; Suzuki, S.O.; Kanba, S.; Kiyohara, Y.; et al. Insulin resistance is associated with the pathology of Alzheimer disease: The Hisayama Study. Neurology 2010, 75, 764–770. [Google Scholar] [CrossRef] [PubMed]
- Ohara, T.; Doi, Y.; Ninomiya, T.; Hirakawa, Y.; Hata, J.; Iwaki, T.; Kanba, S.; Kiyohara, Y. Glucose tolerance status and risk of dementia in the community: The Hisayama Study. Neurology 2011, 77, 1126–1134. [Google Scholar] [CrossRef] [PubMed]
Category | Degree of Independence in Daily Living |
---|---|
Ⅰ | Can do on their own |
Ⅱa | Monitoring needed only outside home |
Ⅱb | Monitoring needed inside and outside home |
Ⅲa | Need support during day |
Ⅲb | Need support during night |
IV | Need support during day and night |
M | Need support in nursing home |
Item | Normal | Follow-Up | Requires Further Testing | Requires Treatment | Total |
---|---|---|---|---|---|
ALP | 568 | 38 | 0 | 0 | 606 |
93.7% | 6.3% | 0.0% | 0.0% | 100.0% | |
ALT(GPT) | 521 | 68 | 0 | 17 | 606 |
86.0% | 11.2% | 0.0% | 2.8% | 100.0% | |
Amylase | 570 | 36 | 0 | 0 | 606 |
94.1% | 5.9% | 0.0% | 0.0% | 100.0% | |
AST(GOT) | 521 | 71 | 0 | 14 | 606 |
86.0% | 11.7% | 0.0% | 2.3% | 100.0% | |
Blood glucose level | 374 | 161 | 0 | 71 | 606 |
61.7% | 26.6% | 0.0% | 11.7% | 100.0% | |
Creatinine | 539 | 67 | 0 | 0 | 606 |
88.9% | 11.1% | 0.0% | 0.0% | 100.0% | |
Erythrocyte | 420 | 165 | 0 | 21 | 606 |
69.3% | 27.2% | 0.0% | 3.5% | 100.0% | |
HbA1C | 285 | 237 | 0 | 84 | 606 |
47.0% | 39.1% | 0.0% | 13.9% | 100.0% | |
HDL-cholesterol | 579 | 20 | 0 | 7 | 606 |
95.5% | 3.3% | 0.0% | 1.2% | 100.0% | |
Hematocrit | 550 | 50 | 0 | 5 | 606 |
90.9% | 8.3% | 0.0% | 0.8% | 100.0% | |
Hemoglobin | 496 | 82 | 0 | 27 | 606 |
82.0% | 13.5% | 0.0% | 4.5% | 100.0% | |
LDL-cholesterol | 258 | 348 | 0 | 0 | 606 |
42.6% | 57.4% | 0.0% | 0.0% | 100.0% | |
Leucocyte | 584 | 22 | 0 | 0 | 606 |
96.4% | 3.6% | 0.0% | 0.0% | 100.0% | |
Neutral fat | 461 | 126 | 0 | 19 | 606 |
76.1% | 20.8% | 0.0% | 3.1% | 100.0% | |
Platelet | 590 | 15 | 0 | 0 | 606 |
97.5% | 2.5% | 0.0% | 0.0% | 100.0% | |
Total protein | 579 | 27 | 0 | 0 | 606 |
95.5% | 4.5% | 0.0% | 0.0% | 100.0% | |
Total-cholesterol | 326 | 237 | 0 | 0 | 606 |
53.8% | 39.1% | 0.0% | 0.0% | 100.0% | |
Urea nitrogen | 568 | 38 | 0 | 0 | 606 |
93.7% | 6.3% | 0.0% | 0.0% | 100.0% | |
Uric blood | 482 | 14 | 92 | 18 | 606 |
79.5% | 2.3% | 15.2% | 3.0% | 100.0% | |
Uric protein | 546 | 3 | 38 | 19 | 606 |
90.1% | 0.5% | 6.3% | 3.1% | 100.0% | |
Urinary acid | 547 | 59 | 0 | 0 | 606 |
90.3% | 9.7% | 0.0% | 0.0% | 100.0% | |
Urinary sugar | 586 | 0 | 6 | 14 | 606 |
96.7% | 0.0% | 1.0% | 2.3% | 100.0% | |
γGTP | 527 | 50 | 0 | 29 | 606 |
87.0% | 8.3% | 0.0% | 4.8% | 100.0% |
Item | Multivariate Adjusted Odds Ratio | 95% CI | p-Value | |
---|---|---|---|---|
Lower Limit | Upper Limit | |||
Age | 1.038 | 0.985 | 1.095 | 0.161 |
Sex (Women/Men) | 0.975 | 0.488 | 1.948 | 0.942 |
Height (cm) | 0.992 | 0.955 | 1.032 | 0.698 |
Abdominal circumference (cm) | 0.961 | 0.927 | 0.997 | 0.032 |
BMI | 1.039 | 0.934 | 1.156 | 0.484 |
Medicine to lower blood pressure (Yes/No) | 0.907 | 0.581 | 1.416 | 0.669 |
Insulin injections or oral hypoglycemic medications (Yes/No) | 2.635 | 1.294 | 5.365 | 0.008 |
Medicine to lower cholesterol (Yes/No) | 1.001 | 0.630 | 1.590 | 0.998 |
Systolic blood pressure (mmHg) | 1.007 | 0.990 | 1.025 | 0.396 |
Diastolic blood pressure (mmHg) | 0.973 | 0.946 | 1.001 | 0.063 |
ALP (+±/−) | 1.122 | 0.482 | 2.609 | 0.790 |
ALT(GPT) (+±/−) | 1.082 | 0.621 | 1.884 | 0.781 |
Amylase (+±/−) | 1.482 | 0.664 | 3.308 | 0.337 |
AST(GOT) (+±/−) | 0.883 | 0.473 | 1.646 | 0.695 |
Blood glucose level (+±/−) | 0.958 | 0.715 | 1.285 | 0.776 |
Creatinine (+±/−) | 0.854 | 0.418 | 1.747 | 0.666 |
Erythrocyte (+±/−) | 0.922 | 0.655 | 1.298 | 0.640 |
HbA1C (+±/−) | 0.857 | 0.631 | 1.164 | 0.322 |
HDL-cholesterol (+±/−) | 1.363 | 0.797 | 2.331 | 0.257 |
Hematocrit (+±/−) | 1.467 | 0.763 | 2.821 | 0.250 |
Hemoglobin (+±/−) | 0.893 | 0.618 | 1.289 | 0.545 |
LDL-cholesterol (+±/−) | 1.086 | 0.669 | 1.761 | 0.739 |
Leucocyte (+±/−) | 1.222 | 0.438 | 3.405 | 0.702 |
Neutral fat (+±/−) | 1.150 | 0.795 | 1.664 | 0.458 |
Platelet (+±/−) | 1.554 | 0.499 | 4.837 | 0.446 |
Total protein (+±/−) | 0.787 | 0.277 | 2.236 | 0.653 |
Total-cholesterol (+±/−) | 0.964 | 0.716 | 1.298 | 0.807 |
Urea nitrogen (+±/−) | 0.549 | 0.193 | 1.561 | 0.261 |
Uric blood (+±/−) | 1.130 | 0.897 | 1.423 | 0.301 |
Uric protein (+±/−) | 0.940 | 0.684 | 1.290 | 0.701 |
Urinary acid (+±/−) | 1.089 | 0.503 | 2.362 | 0.828 |
Urinary sugar (+±/−) | 0.973 | 0.600 | 1.579 | 0.913 |
γGPT (+±/−) | 1.048 | 0.725 | 1.515 | 0.804 |
Outpatient Medical Expenditures in 2008 | 1.000 | 1.000 | 1.000 | 0.609 |
_cons | 1.087 | 0.985 |
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Tamaki, Y.; Hiratsuka, Y.; Kumakawa, T. Risk Factors for Dementia Incidence Based on Previous Results of the Specific Health Checkups in Japan. Healthcare 2020, 8, 491. https://doi.org/10.3390/healthcare8040491
Tamaki Y, Hiratsuka Y, Kumakawa T. Risk Factors for Dementia Incidence Based on Previous Results of the Specific Health Checkups in Japan. Healthcare. 2020; 8(4):491. https://doi.org/10.3390/healthcare8040491
Chicago/Turabian StyleTamaki, Yoh, Yoshimune Hiratsuka, and Toshiro Kumakawa. 2020. "Risk Factors for Dementia Incidence Based on Previous Results of the Specific Health Checkups in Japan" Healthcare 8, no. 4: 491. https://doi.org/10.3390/healthcare8040491
APA StyleTamaki, Y., Hiratsuka, Y., & Kumakawa, T. (2020). Risk Factors for Dementia Incidence Based on Previous Results of the Specific Health Checkups in Japan. Healthcare, 8(4), 491. https://doi.org/10.3390/healthcare8040491