Specific Health Check-up and Specific Health Guidance have undergone several phases of review since fiscal year 2008. In developing the current Phase 4 (fiscal year 2024 onwards) standard program, update revisions were deliberated within the Ministry of Health, Labor and Welfare's review committee and working group. While retaining the previous 22 questionnaire items, modifications were made to items concerning smoking, alcohol consumption and so on. Smoking status was separated into non-smokers, ex-smokers and current smokers. For alcohol consumption, the "occasional" category was removed; additional subdivided frequency to allow more detailed assessment and "ex-drinkers" category was also added. It also enabled identification of heavy episodic drinking. The main revisions to health check-up items concerning the criteria for dyslipidemia. Aligned with the newest guidelines of the Japanese Society of Atherosclerosis, the health guidance threshold for triglycerides was separated into fasting and non-fasting measurements. Simultaneously, the referral recommendation criteria for HDL cholesterol to medical institutions, which had no treatment drugs, was removed. While revisions to blood pressure criteria were considered based on changes to the Japanese Society of Hypertension guidelines, these were not implemented due to concerns about increasing the number of individuals at risk for health guidance and practical operational reasons. Concerning Specific Health Guidance from Phase 4 onwards, alongside the existing process evaluation, an outcome evaluation for active support has been introduced. This employs a points system based on the contents of health guidance, such as improvement of nutrition and/or physical activity. Furthermore, the approach to managing individuals taking medication has been revised. By strengthening the coordination between health guidance and medical consultation recommendations, the program aims to prevent serious diseases and healthcare costs.

 In the 4^th phase of the Specific Health Guidance, which commenced in 2024, outcome evaluation was newly introduced. Performance evaluation now requires health guidance providers to demonstrate results by confirming reductions in abdominal circumference and body weight, as well as behavioral changes that prevent lifestyle-related diseases (improvements in dietary, exercise, smoking, rest, and other lifestyle habits). In response to the 4^th phase revisions, the Junpukai Foundation focused on three key considerations: (1) Review of the active support program, (2) Setting achievable goals during the initial interview, (3) Standardization of outcome evaluation methods. Consequently, for fiscal year 2024 (Phase 4) implementation, the percentage achieving a 2 cm reduction in abdominal circumference and a 2 kg reduction in body weight was 40.2% among those completing the active support program and 15.3% among those completing the motivational support program. Thus, both groups achieved a significant improvement rate compared with fiscal year 2023. However, only 147 participants—a mere 4.3% of those completing active support—earned additional points through outcome evaluation of behavioral change, posing a new challenge.

 Following the commencement of Phase 4, the extremely low number of outcome evaluations for behavioral change led to a significant number of additional support cases arising after the performance evaluation, resulting in the support period being extended by approximately two weeks. A survey of instructors revealed that approximately 60% were inexperienced, and it became clear that the high number of inexperienced instructors and their limited skills were affecting the outcome evaluation of behavioral change. Consequently, an "Action Plan Checklist" was created to supplement the skills of these instructors.

 This significant revision presents an opportunity for occupational health organizations to reassess their specific health guidance programs, and it is hoped that various measures will be implemented to achieve the objectives of Specific Health Guidance.

 In Japan, health promotion programs have traditionally focused on "implementation," with key performance indicators (KPIs) based on participation rates. However, demographic aging and social structural changes have made uniform implementation insufficient to meet diverse health needs. In response, the third phase of the Data Health Plan shifted its objective from "implementation" to "problem-solving," emphasizing data-driven identification of health issues and evidence-based program design. This paper examines strategies to enhance the effectiveness of Specific Health Checkups and Specific Health Guidance through data utilization, organized into three perspectives: (1) program design, (2) program evaluation, and (3) knowledge extraction, followed by considerations for building a data infrastructure to advance implementation science.

 For program design, analyzing medical expenditure and health checkup data enables targeted interventions. Our analysis of nine prefectures revealed that over 90% of identified health issues were linked to corresponding programs, indicating progress toward problem-solving approaches. At the individual level, higher understanding of checkup results was associated with improved adherence and subsequent health outcomes.

 Program evaluation has evolved through the introduction of standardized indicators in the third phase, supported by systems such as the KDB and the Data Health Portal, enabling objective comparisons and reducing administrative burden. Knowledge extraction requires strengthening the "Check" and "Act" phases of PDCA by incorporating scientific evaluation and evidence-based policy making (EBPM). Tools such as the "Health Program Chart" have facilitated structured documentation and sharing of effective practices.

 Finally, improving the effectiveness of Specific Health Checkups and Guidance requires data-driven strategies to clarify necessity and visualize benefits. Personalized risk projections, simulation of complication risk reduction, and indicators for productivity and resource optimization can drive behavioral change among individuals, employers, and municipalities. Data utilization thus serves as a foundation for enhancing health promotion program quality and promoting societal well-being.

 In contemporary medicine, collaboration between the medical and dental fields has evolved from a conceptual ideal to a practical necessity, driven by accumulating evidence on the links between oral and systemic health. ​This paper discusses the role of a novel dental health check system, centered on oral microbiome analysis and artificial intelligence (AI) technologies, in comprehensive systemic health management. ​Since Antony van Leeuwenhoek's observation of microorganisms in dental plaque in 1674, associations have been reported between the oral microbiome and various systemic diseases, including Alzheimer's disease, cardiovascular disease, diabetes, and inflammatory bowel disease. ​Concurrently, AI applications have demonstrated potential to enhance the accuracy and efficiency of dental imaging diagnostics, thereby improving the quality and standardization of national health screenings.​ Integrated medical-dental care is positioned as a holistic health management system that advances preventive medicine while curbing healthcare costs.

 Objective: To detect chronic kidney disease (CKD) at an early stage, we introduced the determination of urinary albumin/creatinine (A/C) as a basic item of a comprehensive medical check-up in 2023. This study aimed to compare A/C results with those of conventional qualitative urine protein test strips.

 Methods: The results obtained from both methods were compared based on (1) urine protein positive/negative test results, (2) concordance rate between the two in the CKD severity classification, and (3) the relationship between abnormalities in CKD-related items and urinary protein abnormalities judged by each method. A total of 18,310 individuals who underwent comprehensive medical checkups at our institution were examined.

 Results: (1) All cases of urine protein (3+) and (2+), excluding three cases, were positive for A/C. The positivity rates for (1+), (±), and (-) were 47.1%, 9.6%, and 3.3%, respectively. (2) In the comparison of the CKD severity classification, the concordance rate of the classification was 71.0%, and the proportion of false negatives and positives was 2.3% and 24.9%, respectively. (3) In the Chi-square test with abnormalities in CKD-related items and proteinuria judged by both methods, P was<0.0001 for all items by A/C. Test strip positivity was not significantly related to systolic blood pressure and blood glucose or HbA1c abnormalities. (P=0.1871 and 0.9960, respectively).

 There was a discrepancy between the A/C and urine protein qualitative results, and many false-positive and -negative cases were included in the test strip evaluation. Additionally, a study of CKD-related items showed that the A/C was more relevant than test strips.

 Conclusion: The introduction of A/C in comprehensive medical check-ups may contribute to the early detection of CKD.

 Purpose: The association between comprehensive health literacy (HL) and participation in mammography (MMG) screening remains unclear. This study aimed to explore the relationship between comprehensive HL and MMG screening participation.

 Methods: An online survey targeting women in their 40s without a history of breast cancer was conducted, and data were collected from 1,068 respondents. The survey included items on HL, the number of MMG screenings, demographic characteristics, self-rated health (SRH), and breast cancer risk factors. Multivariate logistic regression was conducted to analyze the association between HL and MMG screening. The dependent variables were 1) MMG screening history (0 times vs. one or more times) and 2) repeated MMG screenings (1 time vs. two or more times), and the independent variables included HL and other factors. Participants were also categorized into two groups based on their HL level, allowing for an examination of differences in screening-related factors.

 Results: The number of valid responses was 612, with HL levels of "insufficient" at 36%, "problematic" at 30%, and "adequate" at 35%. The adjusted odds ratios (aORs) for HL and screening attendance, with "adequate" as the reference category, were 1.28 (95% confidence interval [CI]: 0.82–2.00) for "inadequate" and 0.87 (95% CI: 0.55–1.36) for "problematic". For repeated screenings, the aORs were 0.72 (95% CI: 0.43–1.20) for "insufficient" and 1.04 (95% CI: 0.59–1.82) for "problematic". No significant association was found between HL and screening. When comparing HL levels, significant associations were observed between SRH and HL in the low HL group for screening participation, and between education and HL in the same group for participation in repeated screenings.

 Conclusions: Comprehensive HL did not directly affect MMG screening participation. However, different factors influenced participation based on HL levels, so tailored interventions targeting the characteristics of each HL level may enhance screening participation rates.

 Objective: Atrial fibrillation (AF) increases the risk of stroke, heart failure, and death, making early diagnosis and initiation of anticoagulation therapy crucial. However, AF is often asymptomatic, making early detection challenging. Therefore, the objective of this research is developing artificial intelligence (AI) for screening Japanese patients at high risk of AF onset based on electrocardiogram (ECG) features of sinus rhythm and examining clinical effectiveness of this AI.

 Methods: Using retrospective cohort data of adult individuals who underwent 12-lead ECG examinations from 2000 to 2019 (total 30,467 individuals, including 3,528 cases of AF), we developed an AI model to predict the risk of AF onset. The generalization performance of the AI was evaluated. Additionally, we analyzed ECG findings of cases of the pre-AF state and ECG findings which are bases of the AI prediction. To assess the clinical significance of the AI, we simulated the diagnosis of atrial fibrillation by AI in an undiagnosed population.

 Results: The generalization performance of the AI showed a specificity 95.7% and a sensitivity of 44.0%. In the analysis of findings, when AI identified high-risk cases, ST-T abnormalities were most common (15.5%) among cases in the pre-AF state. The use of this AI in health check-ups for individuals aged 40 and above in Japan suggests the potential for preventing an estimated 9,554 strokes per year through this simulation.

 Conclusions: The development of AI for predicting the comprehensive risk of AF onset from ECG features of sinus rhythm in the Japanese population demonstrated practical enough accuracy, as validated by cohort data. Furthermore, multiple ECG abnormalities were found to influence the onset of paroxysmal atrial fibrillation, and the AI also based its risk assessment on multiple ECG abnormalities. Simulation in an undiagnosed population suggested the potential effectiveness of AF screening AI in health checks.

 Objective: The results of a cytological diagnosis and high-risk (hr)HPV test in cervical cancer screening in our hospital from 2021 to 2023 are summarized and reviewed.

 Methods: Liquid-based cytology specimens were diagnosed according to The Bethesda System. The hrHPV test was performed by Aptima HPV.

 Results: The total number of cervical cancer screens performed was 18,220. The actual number of examinees was 10,129, with an age range from 18 to 90 years. Two specimens were not analyzed because of the small number of cells included. Among 18,218 specimens, 894 (4.9%) were diagnosed with ASC-US or higher. The actual number of hrHPV tests was 209, and hrHPV was positive in 19 (9.1%). The rates of the diagnosis of ASC-US or higher in hrHPV-negative and hrHPV-positive examinees were 6.3 and 57.9%, respectively. HSIL was noted in 5 out of 9 examinees <40 years and in 2 out of 10 examinees ≥40 years. In three hrHPV-positive examinees, the cytological diagnosis changed from NILM to LSIL or HSIL in three years.

 Conclusion: Based on the present results, a cytological diagnosis is recommended for young examinees. hrHPV-positive examinees need to be carefully followed up.