The Hisayama Study is a population-based prospective cohort study designed to evaluate the risk factors for lifestyle-related diseases, such as stroke, coronary heart disease, hypertension, diabetes, and dementia, in a general Japanese population. The prospective follow-up surveys have been conducted in subjects aged 40 or older since 1961. Notable characteristics of this study include its high participation rate (70–80% of all residents aged 40 or older), high follow-up rate (99% or over), and high autopsy rate (approximately 75% of deceased cases). The Hisayama Study has provided valuable evidence of secular change in the prevalence and incidence of several lifestyle-related disease and their risk factors. The study has thereby contributed to elucidation of the preventive strategies for lifestyle-related disease. Research efforts in this cohort are ongoing and will provide additional data for the improvement of human health and longevity.

Background: Participation in community activities (eg, sports and hobby groups or volunteer organizations) is believed to be associated with better health status in the older population. We sought to (1) determine whether a greater diversity of group membership is associated with better self-rated health and (2) identify the key dimension of the membership diversity (eg, gender, residential area, or age).

Methods: We performed a cross-sectional study of 129,740 participants aged 65 years and older who were enrolled in the Japan Gerontological Evaluation Study in 2013. We assessed the diversity of group membership using (1) a continuous variable (range 0–4) accounting for the total degree of each diversity dimension or (2) dummy variables for each dimension. We estimated prevalence ratios (PRs) and 95% confidence intervals (CIs) for better self-rated health according to the diversity of group membership, using Poisson regression and robust variance with multiple imputation, adjusted for other covariates.

Results: The participants involved in social groups with greater diversity had better self-rated health: the PR per one point unit increase in diversity was 1.03 (95% CI, 1.02–1.04). Participation in gender-diverse groups was associated with the best profile of health (PR 1.07; 95% CI, 1.04–1.09).

Conclusions: Among the older population in Japan, higher group diversity is associated with better self-rated health. Gender is the key dimension of diversity that is associated with better self-rated health.

Background: Our objective in this study was to find determinants of high-school dropout in a deprived area of Japan using longitudinal data, including socio-demographic and junior high school-period information.

Methods: We followed 695 students who graduated the junior high school located in a deprived area of Japan between 2002 and 2010 for 3 years after graduation (614 students: follow-up rate, 88.3%). Multivariable log-binomial regression models were used to calculate the prevalence ratios (PRs) for high-school dropout, using multiple imputation (MI) to account for non-response at follow-up.

Results: The MI model estimated that 18.7% of students dropped out of high school in approximately 3 years. In the covariates-adjusted model, three factors were significantly associated with high-school dropout: ≥10 days of tardy arrival in junior high school (PR 6.44; 95% confidence interval [CI], 1.69–24.6 for “10–29 days of tardy arrival” and PR 8.01; 95% CI, 2.05–31.3 for “≥30 days of tardy arrival” compared with “0 day of tardy arrival”), daily smoking (PR 2.01; 95% CI, 1.41–2.86) and severe problems, such as abuse and neglect (PR 1.66; 95% CI, 1.16–2.39). Among students with ≥30 days of tardy arrival in addition to daily smoking or experience of severe problems, ≥50% high-school dropout rates were observed.

Conclusions: Three determinants of high-school dropout were found: smoking, tardy arrival, and experience of severe problems. These factors were correlated and should be treated as warning signs of complex behavioral and academic problems. Parents, educators, and policy makers should work together to implement effective strategies to prevent school dropout.

Background: We estimated the cumulative risk of type 2 diabetes from age 30 to 65 years in a large working population in Japan.

Methods: We used data from the Japan Epidemiology Collaboration on Occupational Health Study. Participants (46,065 men and 7,763 women) were aged 30–59 years, free of diabetes at baseline, and followed up for a maximum of 7 years. Incident type 2 diabetes was defined based on fasting and casual glucose, glycated hemoglobin, and current medical treatment for type 2 diabetes. We calculated the sex-specific cumulative risk of type 2 diabetes using the Practical Incidence Estimator macro, which was created to produce several estimates of disease incidence for prospective cohort studies based on a modified Kaplan-Meier method.

Results: During 274,349 person-years of follow-up, 3,587 individuals (3,339 men and 248 women) developed type 2 diabetes. The cumulative risk was 34.7% (95% confidence interval, 33.1–36.3%) for men and 18.6% (95% confidence interval, 15.5–21.7%) for women. In BMI-stratified analysis, obese (BMI ≥30 kg/m²) and overweight (BMI 25–29.9 kg/m²) men and women had a much higher cumulative risk of type 2 diabetes (obese: 77.3% for men and 64.8% for women; overweight: 49.1% and 35.7%, respectively) than those with BMI <25 kg/m² (26.2% and 13.4% for men and women, respectively).

Conclusions: The present data highlight the public health burden of type 2 diabetes in the working population. There is a need for effective programs for weight management and type 2 diabetes screening, especially for young obese employees, to prevent or delay the development of type 2 diabetes.

Background: There has been no nationwide analysis of travel time for hospital admission in Japan. Factors associated with travel time are also unknown. This study aimed to describe the distribution of travel time for hospital admission of cancer patients and identify underlying factors.

Methods: The individual data from the Patient Survey in 2011 were linked to those from the Survey of Medical Institutions in the same year, and GIS data were used to calculate driving travel time between the addresses of medical institutions and the population centers of municipalities where patients lived. Proportions of patients with travel time exceeding versus not exceeding 45 minutes were calculated. To analyze the data with consideration of both individual factors of patients and geographical characteristics of areas where patients lived, multilevel logistic model analysis was performed.

Results: The analysis included 50,845 cancer inpatients. The majority of the cancer patients (approximately 80%) were admitted to hospitals located less than a 45-minute drive from their residences. The travel time tended to be longer for younger patients. The proportion of patients with travel time ≥45 minutes was lower among those with stomach or colorectal cancer (approximately 15%) than those with cervical cancer or leukemia (approximately 30%). The lack of designated cancer care hospitals in the secondary healthcare service areas was significantly associated with travel time.

Conclusions: Selection of hospitals by cancer inpatients is affected by age, cancer sites, and availability of designated cancer care hospitals in the secondary healthcare service areas where patients live.