Kyushu University Academic Staff Educational and Research Activities Database
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Honda Takanori Last modified date:2022.10.05

Graduate School
Undergraduate School

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 Reseacher Profiling Tool Kyushu University Pure
Academic Degree
Field of Specialization
Epidemiology, Public Health, Physical activity, Behavioral Science
ORCID(Open Researcher and Contributor ID)
Research Interests
  • Development and evaluation of risk prediction models for chronic diseases and its
    keyword : risk prediction, epidemiology, chonic diseases
  • Commuting and chronic diseases
    keyword : physical activity
  • Physical activity epidemiology on diabetes and metabolic diseases
    keyword : physical activity; epidemiology
  • Nutritional epidemiology
    keyword : epidemiology
  • Effects of physical activity on cognitive health
    keyword : epidemiology
Academic Activities
1. Honda T, Ohara T, Yoshida D, Shibata M, Ishida Y, Furuta Y, Oishi E, Hirakawa Y, Sakata S, Hata J, Nakao T, Ninomiya T, Development of a dementia prediction model for primary care: The Hisayama Study. , Alzheimer’s Dement (Amst), 10.1002/dad2.12221., 13, e12221, 2021.05, Introduction: We aimed to develop a risk prediction model for incident dementia using predictors that are available in primary-care settings.

Methods: A total of 795 subjects aged 65 years or over were prospectively followed-up from 1988 to 2012. A Cox proportional-hazards regression was used to develop a multivariable prediction model. The developed model was translated into a simplified scoring system based on the beta-coefficient. The discrimination of the model was assessed by Harrell's C statistic, and the calibration was assessed by a calibration plot.

Results: During the follow-up period, 364 subjects developed dementia. In the multivariable model, age, female sex, low education, leanness, hypertension, diabetes, history of stroke, current smoking, and sedentariness were selected as predictors. The developed model and simplified score showed good discrimination and calibration.

Discussion: The developed risk prediction model is feasible and practically useful in primary-care settings to identify individuals at high risk for future dementia.

Keywords: dementia; general population; primary prevention; prospective study; risk prediction model..
2. Takanori Honda, Tomoyuki Ohara, Masakazu Shinohara, Jun Hata, Ryuji Toh, Daigo Yoshida, Mao Shibata, Tatsuro Ishida, Yoichiro Hirakawa, Yasuhiro Irino, Satoko Sakata, Kazuhiro Uchida, Takanari Kitazono, Shigenobu Kanba, Ken Ichi Hirata, Toshiharu Ninomiya, Serum elaidic acid concentration and risk of dementia
The Hisayama Study, Neurology, 10.1212/WNL.0000000000008464, 93, 22, e2053-e2064, 2019.11, OBJECTIVE: The associations between trans fatty acids and dementia have been unclear. We investigated the prospective association between serum elaidic acid (trans 18:1 n-9) levels, as an objective biomarker for industrial trans fat, and incident dementia and its subtypes. METHODS: In total, 1,628 Japanese community residents aged 60 and older without dementia were followed prospectively from when they underwent a screening examination in 2002-2003 to November 2012 (median 10.3 years, interquartile range 7.2-10.4 years). Serum elaidic acid levels were measured using gas chromatography/mass spectrometry and divided into quartiles. The Cox proportional hazards model was used to estimate the hazard ratios for all-cause dementia, Alzheimer disease (AD), and vascular dementia by serum elaidic acid levels. RESULTS: During the follow-up, 377 participants developed some type of dementia (247 AD, 102 vascular dementia). Higher serum elaidic acid levels were significantly associated with greater risk of developing all-cause dementia (p for trend = 0.003) and AD (p for trend = 0.02) after adjustment for traditional risk factors. These associations remained significant after adjustment for dietary factors, including total energy intake and intakes of saturated and polyunsaturated fatty acids (both p for trend <0.05). No significant associations were found between serum elaidic acid levels and vascular dementia. CONCLUSIONS: The findings suggest that higher serum elaidic acid is a possible risk factor for the development of all-cause dementia and AD in later life. Public health policy to reduce industrially produced trans fatty acids may assist in the primary prevention of dementia..
3. Honda T, Yoshida D, Hata J, Hirakawa Y, Ishida Y, Shibata M, Sakata S, Kitazono T, Ninomiya Toshiharu, Development and validation of modified risk prediction models for cardiovascular disease and its subtypes: The Hisayama Study, Atherosclerosis, 10.1016/j.atherosclerosis.2018.10.014, 85, 38-44, 2018.10, Background and aims:
Predicting cardiovascular events is of practical benefit for disease prevention. The aim of this study was to develop and evaluate an updated risk prediction model for cardiovascular diseases and its subtypes.

A total of 2,462 community residents aged 40-84 were followed up for 24 years. A Cox’s proportional hazards regression model was used to develop risk prediction models for cardiovascular diseases, and separately for stroke and coronary heart diseases. The risk assessment ability of the developed model was evaluated, and a bootstrapping method was used for internal validation. The predicted risk was translated into a simplified scoring system. A decision curve analysis was used to evaluate clinical usefulness.

The multivariable model for cardiovascular diseases included age, sex, systolic blood pressure, hemoglobin A1c, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, smoking habits, and regular exercise as predictors. The models for stroke and for coronary heart diseases incorporated both shared and unique variables. The developed models showed good discrimination with little evidence of overfitting (optimism-corrected Harrell’s C statistics 0.726-0.777) and calibrations (Hosmer-Lemeshow test, p = 0.44 – 0.90). The decision curve analysis revealed that the predicted risk-based decision-making would have higher net benefit than either a CVD intervention strategy for all individuals or no individuals.

The developed risk prediction models showed a good performance and satisfactory internal validity, which may help in understanding individual risk and setting personalized goals, and in promoting risk stratification in public health strategies for CVD prevention..
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