医学部 公衆衛生学

HE YUPENG

ホー ウホウ  (YUPENG HE)

基本情報

所属
藤田医科大学 医学部 公衆衛生学 助教

ORCID ID
 https://orcid.org/0000-0003-3162-0176
J-GLOBAL ID
202201020817428608
researchmap会員ID
R000033736

論文

 15
  • Ryusei Okegawa, Yupeng He, Masaaki Matsunaga, May Thet Khine, Yuanying Li, Tsuyoshi Kitajima, Hiroshi Yatsuya, Atsuhiko Ota
    Archives of Public Health 82(1) 2024年11月8日  
  • Masaaki Matsunaga, Shinichi Tanihara, Yupeng He, Hiroshi Yatsuya, Atsuhiko Ota
    Geriatrics & Gerontology International 24(8) 773-781 2024年6月18日  
    Aim Japan faces a public health challenge of dementia, further complicated by the increasing complications from diabetes within its rapidly aging population. This study assesses the impact of diabetes on mortality and hospitalization among individuals aged ≥75 years with new dementia diagnoses. Methods We analyzed administrative claims data in Japan from 73 324 individuals aged ≥75 years with dementia, of whom 17% had comorbid diabetes. Dementia and diabetes were identified from the International Classification of Diseases, Tenth Revision codes. We used Kaplan–Meier survival analysis, Cox proportional hazards analysis, and population attributable fractions (PAFs) to evaluate the impact on mortality and hospitalization after dementia diagnosis. Results One‐year mortality and 1‐year hospitalization probabilities in individuals with dementia and diabetes (10.3% and 31.7%, respectively) were higher than those without diabetes (8.3% and 25.4%, respectively). The adjusted hazard ratios for individuals with diabetes, as compared to those without, were 1.126 (95% confidence interval [CI], 1.040–1.220) for mortality and 1.191 (95% CI, 1.140–1.245) for hospitalization. The PAFs from the comorbidity of dementia and diabetes were 2.2% for mortality and 3.1% for hospitalization. Subgroup analysis showed that the PAFs were highest in men aged 75–79 years and women aged 80–84 years for mortality and in individuals aged 75–79 for hospitalization. Conclusion During the early postdiagnosis period, comorbid diabetes increases mortality and hospitalization risks in older adults with dementia. The variation in disease burden across age groups underscores the need for age‐specific health care strategies to manage comorbid diabetes in individuals with dementia. Geriatr Gerontol Int 2024; 24: 773–781.
  • Young Jae Hong, Rei Otsuka, Zean Song, Chisato Fukuda, Rina Tajima, Jingyi Lin, Mizuho Hibino, Mei Kobayashi, Yupeng He, Masaaki Matsunaga, Atsuhiko Ota, Yoshihisa Nakano, Yuanying Li, Koji Tamakoshi, Hiroshi Yatsuya
    Geriatrics & Gerontology International 24(7) 700-705 2024年6月3日  
    Aim Several studies have shown that dairy consumption in old age is effective in preventing frailty. However, there is a lack of evidence regarding the association between milk consumption during middle age and the development of frailty in old age. Therefore, we carried out an investigation to explore the association between milk consumption during middle age and development of frailty examined after over 15 years of follow up in a long‐term cohort study in Japan. Methods We studied 265 participants aged 60–79 years (212 men and 53 women) in 2018, who participated in both the baseline survey in 2002 and the frailty assessment in 2018. The amount of milk consumption (g/day) at baseline was age‐ and energy‐adjusted, and classified into three categories (no, low and high consumption: 0 g/day, ≤135.86 g/day, >135.86 g/day in men and 0 g/day, ≤126.44 g/day, >126.44 g/day in women). Odds ratios (OR) and 95% confidence intervals (CI) for prefrailty/frailty after adjusting for lifestyles at baseline, stratified by sex, were estimated using logistic regression analysis. Results The prevalence of prefrailty/frailty in 2018 was 37.7% and 28.3% in men and women, respectively. Milk consumption categories were inversely associated with the prevalence of prefrailty/frailty in men (OR 0.34, 95% CI 0.14–0.84 in low consumption; OR 0.31, 95% CI 0.10–0.95 in high consumption; P < 0.05), but not in women (OR 0.53, 95% CI 0.11–2.65; P = 0.44). Conclusions In this study, milk intake in middle‐aged men was inversely associated with the prevalence of prefrailty/frailty later in life. Geriatr Gerontol Int 2024; 24: 700–705.
  • Yupeng He, Kenji Sakuma, Taro Kishi, Yuanying Li, Masaaki Matsunaga, Shinichi Tanihara, Nakao Iwata, Atsuhiko Ota
    Journal of Clinical Medicine 13(10) 2970-2970 2024年5月17日  
    Background and Objective: Excellent generalizability is the precondition for the widespread practical implementation of machine learning models. In our previous study, we developed the schizophrenia classification model (SZ classifier) to identify potential schizophrenia patients in the Japanese population. The SZ classifier has exhibited impressive performance during internal validation. However, ensuring the robustness and generalizability of the SZ classifier requires external validation across independent sample sets. In this study, we aimed to present an external validation of the SZ classifier using outpatient data. Methods: The SZ classifier was trained by using online survey data, which incorporate demographic, health-related, and social comorbidity features. External validation was conducted using an outpatient sample set which is independent from the sample set during the model development phase. The model performance was assessed based on the sensitivity and misclassification rates for schizophrenia, bipolar disorder, and major depression patients. Results: The SZ classifier demonstrated a sensitivity of 0.75 when applied to schizophrenia patients. The misclassification rates were 59% and 55% for bipolar disorder and major depression patients, respectively. Conclusions: The SZ classifier currently encounters challenges in accurately determining the presence or absence of schizophrenia at the individual level. Prior to widespread practical implementation, enhancements are necessary to bolster the accuracy and diminish the misclassification rates. Despite the current limitations of the model, such as poor specificity for certain psychiatric disorders, there is potential for improvement if including multiple types of psychiatric disorders during model development.
  • Masaaki Matsunaga, Yupeng He, May Thet Khine, Xuliang Shi, Ryusei Okegawa, Yuanying Li, Hiroshi Yatsuya, Atsuhiko Ota
    Journal of Cancer Survivorship 2024年2月28日  

MISC

 9

所属学協会

 1

共同研究・競争的資金等の研究課題

 2
  • 日本学術振興会 科学研究費助成事業 2013年10月 - 2018年3月
    青山 温子, 八谷 寛, 磯 博康, 平川 仁尚, 江 啓発, 長谷部 幸子, 松山 章子, 三田 貴, 本庄 かおり, Esayas Hilawe, 李 媛英, 上村 真由, 王 超辰, 大迫 礼佳, 張 燕, 何 宇鵬, 崔 仁哲, 佐田 みずき, 崔 美善, 大内 詩野
  • 日本学術振興会 科学研究費助成事業 2014年4月 - 2018年3月
    八谷 寛, 青山 温子, 玉腰 浩司, 平川 仁尚, 上村 真由, 太田 充彦, 内藤 久雄, 山田 宏哉, 李 媛英, 大塚 礼, 村田 千代栄, 埴淵 知哉, Esayas Hilawe, 柿崎 真沙子, 埴淵 知哉, 豊嶋 英明, 江 啓発, 山下 健太郎, 王 超辰, 張 燕, 金子 佳世, 何 宇鵬, 鈴木 康司, 加藤 善士, 藤澤 明子, 松永 眞章