Social Capital and Dietary Intakes Following the 2011 Great East Japan Earthquake and Tsunami.

BACKGROUND: Previous studies have identified poor dietary intake as a health risk affecting survivors of the 2011 Great East Japan Earthquake and Tsunami. We examined the association between different social factors (eg, living conditions and perceptions of community social capital) and dietary intakes among disaster-affected survivors. METHODS: We studied 6,724 survivors in four municipalities of Iwate Prefecture 3 years after the disaster. Social capital was assessed via four items inquiring about respondents' perceptions of social cohesion in their communities. Good dietary intake was defined according to the following criteria: intake of staple food ≥three times a day; intake of meat, fish and shellfish eggs, or soybean products ≥twice a day; vegetable intake ≥twice a day; and intake of fruit or dairy products ≥once a day. An individual who did not meet any of these criteria was defined as having poor dietary intake. We adjusted for covariates, including socioeconomic status, marital status, and residential area. RESULTS: Poor dietary intake was reported by 31.6% of respondents. Poisson regression analyses revealed that the following factors were related to poor dietary intake: age <65 years (men: prevalence ratio [PR] 1.48; 95% confidence interval [CI], 1.29-1.71 and women: PR 1.55; 95% CI, 1.36-1.77), difficulties in living conditions (men: PR 1.18; 95% CI, 1.00-1.39 and women: PR 1.19; 95% CI, 1.01-1.40), and low perceptions of community social capital (women: PR 1.20; 95% CI, 1.04-1.38). CONCLUSIONS: Our findings suggest that social capital plays a role in promoting healthy dietary intake among women in disaster-affected areas.

Differences in Lifestyle Improvements With the Intention to Prevent Cardiovascular Diseases by Socioeconomic Status in a Representative Japanese Population: NIPPON DATA2010.

BACKGROUND: The relationships among socioeconomic status and lifestyle improvements have not yet been examined in a representative Japanese population. METHODS: We analyzed data from 2,647 participants (1,087 men and 1,560 women) who participated in NIPPON DATA2010. This survey inquired about lifestyle improvements and socioeconomic status. Education was categorized as low (≤9 years), middle (10-12 years), and high (≥13 years). Marital status was categorized as married, divorced, widowed, and never married/other. A multivariable logistic regression model was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) of lifestyle improvements with the intention of preventing cardiovascular diseases for educational attainment and marital status, with adjustments for age and awareness of cardiovascular disease risk factors. RESULTS: Overall, 1,507 (56.9%) participants practiced prevention and improvements in hypertension, diabetes, elevated cholesterol, and metabolic syndrome, and the OR of lifestyle improvements was significantly higher with a high education than with a low education in men (OR 2.86; 95% CI, 1.96-4.17) and women (OR 2.36; 95% CI, 1.67-3.33). The number of participants who practiced prevention and improvements in hypertension, diabetes, elevated cholesterol, and metabolic syndrome was significantly lower in divorced than in married men (OR 0.46; 95% CI, 0.22-0.95) and women (OR 0.53; 95% CI, 0.33-0.86). CONCLUSIONS: Specific differences caused by educational attainment and marital status may exist in lifestyle improvements.

Construction of a simulation model and evaluation of the effect of potential interventions on the incidence of diabetes and initiation of dialysis due to diabetic nephropathy in Japan.

BACKGROUND: The prevalence of diabetes mellitus is a growing public health concern in Japan. We developed a simulation model to predict the number of people with diabetes and those on dialysis due to diabetic nephropathy. In addition, we used the model to simulate the impact of possible interventions on the number of people with diabetes and those on dialysis due to diabetic nephropathy in the near future. METHODS: A simulation model with aging chains for diabetes management was built using system dynamics. The model was calibrated to population data from 2000 to 2015 (sex- and age category-specific population, the prevalence of diabetes, and the number of patients on dialysis due to diabetic nephropathy). We extrapolated the model up to 2035 in order to predict future prevalence of diabetes and related dialysis (base run). We also ran the model, hypothesizing that incidence of diabetes and/or related dialysis would be reduced by half from 2015 to 2025 and that this rate would be maintained until 2035, in order to investigate the effects of hypothetical interventions on future prevalence. RESULTS: The developed model forecasted the population with diabetes to increase until 2028 (5.58 million males and 3.34 million females), and the population on dialysis due to diabetic nephropathy to increase until 2035 (113,000 males and 48,000 females). Simulation experiments suggested that diabetes prevention interventions would decrease the number of patients on dialysis in 2035 by 13.8% in males and 12.6% in females compared to the base run. In contrast, interventions aiming to avoid dialysis initiation for patients with diabetes would decrease the number of patients on dialysis by 37.8% in males and 38.1% in females. CONCLUSIONS: We successfully developed a simulation model to project the number of patients with diabetes and those on dialysis due to diabetic nephropathy. Simulation experiments using the model suggested that, as far as the perspective of the next 20 years, intervention to prevent dialysis is an important means of bending the increasing curve of dialysis in the population with diabetes. Simulation analysis may be useful when making and evaluating health policies related to diabetes and other chronic diseases.