Author: Airi

Aims/introduction: Poverty is an important social determinant of diabetes. Poverty is a multidimensional concept including non-financial difficulties, such as social isolation and exclusion from communities. Many countries provide financial social assistance programs for those in need. This study aimed to explore non-financial social determinants of diabetes among public assistance recipients in Japan, by using linkage data of two municipal public assistance databases and medical assistance claim data.

Materials and methods: We carried out a retrospective cohort study. Public assistance is provided to households below the poverty line to ensure their income security. We extracted recipients’ sociodemographic factors of January 2016 (household number and employment status as non-financial social determinants of diabetes) and identified the incidence of diabetes diagnosis until December 2016 as the outcome.

Results: We included the data of 2,698 younger individuals (aged <65 years) and 3,019 older individuals (aged >65 years). A multivariable Poisson regression, with a robust standard error estimator, showed that among 2,144 younger recipients at risk, unemployment and living alone were slightly associated with 1-year cumulative incidence of diabetes diagnosis (adjusted incidence ratio 1.20, 95% confidence interval 0.93-1.54 and adjusted incidence ratio 1.15, 95% confidence interval 0.89-1.48, respectively). Among 2,181 older recipients at risk, there was no strong association between their sociodemographic factors and incidence of diabetes diagnosis.

Conclusions: Unemployment and living alone might be additional risk factors for diabetes among younger public assistance recipients. Multidimensional supports assuring financial and non-financial securities are required to prevent diabetes among people living in poverty.

This study aimed to determine the impact of physical activity on the cumulative cost of long-term care insurance (LTCI) services in a cohort of community-dwelling people (65 years and older) in Japan. Using cohort data from the Japan Gerontological Evaluation Study (JAGES) on those who were functionally independent as of 2010/11, we examined differences in the cumulative cost of LTCI services by physical activity. We followed 38,875 participants with LTCI service costs for 59 months. Physical activity was assessed by the frequency of going out and time spent walking. We adopted a generalized linear model with gamma distribution and log-link function, and a classical linear regression with multiple imputation. The cumulative LTCI costs significantly decreased with the frequency of going out and the time spent walking after adjustment for baseline covariates. LTCI’s cumulative cost for those who went out once a week or less was USD 600 higher than those who went out almost daily. Furthermore, costs for those who walked for less than 30 min were USD 900 higher than those who walked for more than 60 min. Physical activity among older individuals can reduce LTCI costs, which could provide a rationale for expenditure intervention programs that promote physical activity.

We evaluated differences in the cumulative benefit costs of public long-term care (LTC) insurance services by employment status and frequency of community activities. A baseline survey was conducted on functionally independent older people from 12 municipalities as a nationwide survey from 2010 to 2011. Employment status was dichotomized, and community activity was assessed based on the frequency of participation in hobbies, sports clubs, or volunteering. We followed the respondents’ LTC service costs over a period of 6 years using public LTC claim records (n = 46,616). We adopted a classical linear regression analysis and an inverse probability weighting estimation with multiple imputation for missing values. Compared with non-participation in each community activity, the cumulative LTC costs among individuals who participated in hobbies or sports group activities at least twice a week were 1.23 (95% confidence interval: 0.73-1.72) to 1.18 (0.68-1.67) thousand USD lower per person over the 6-year period (28.7% to 30.1% lower, respectively). Similarly, the costs for employed persons were 0.55 (0.20-0.90) to 0.64 (0.29-0.99) thousand USD per person lower than among retirees (14.5% to 16.9% lower). Promoting employment opportunities and frequent participation in community activities among older adults may help reduce future LTC costs by around 20% as a result of extending healthy longevity.

It is plausible that the coronavirus disease pandemic and related changes in work and life patterns affected dietary patterns, but existing studies have limitations owing to a cross-sectional design. Using longitudinal data, we examined dietary changes in people due to the pandemic and work and life patterns. We conducted an online survey on changes in work and life patterns during the pandemic from April 30, 2020, to May 8, 2020, among users of a health app called CALO mama provided in Japan. We retrieved and linked the dietary data for 5,929 participants from January 1, 2020, to May 13, 2020. Generalized linear mixed models were used to estimate the frequencies of food intake associated with the pandemic and work and life patterns. During the state of emergency, the frequency of intake of vegetables, beans, seaweeds, fish, meats, dairy products, and snacks increased, whereas alcohol intake decreased. Working from home was associated with increased intake of vegetables, fruits, dairy products, and snacks but decreased intake of seaweeds, meats, and alcohol. Time spent on childcare was associated with decreased intake of vegetables and fruits but increased intake of meats. Probable depressive symptoms were negatively associated with the frequency of food intake other than snacks and alcohol. We conclude that diet quality improved during the pandemic in general, but attention must be paid to overconsumption of snacks and negative factors such as increased burden of childcare and depression for healthy eating.

Objectives: The purpose of this study was to examine the relationship between social participation (type/pattern) and mortality according to company size of the longest-held job among older men in Japan who have worked in the company.

Methods: Longitudinal data from the Japan Gerontological Evaluation Study were used in this study. Functionally independent individuals aged 65 years and older in Japan were surveyed. Work and community organizations (local community, hobbies, and sports) were used as social participation. A Cox proportional hazards model was used to calculate mortality hazard ratios.

Results: Analysis was carried out on 19 260 participants. A total of 2870 deaths occurred during the 6-year follow-up period. Those in companies with 49 or fewer employees had the highest prevalence of work participation and the lowest participation in any community organization. Regardless of company size, the mortality risk was significantly lower for participants in any social participation (eg, the hazard ratio for participation in a hobby organization among those with a company size of 49 employees or fewer was 0.74, 95% CI: 0.65-0.85) compared to nonparticipants whose company size was 49 or fewer employees.

Conclusions: In Japan, although older men who have worked for small companies may have fewer benefits, their social participation may reduce their mortality risks. To avoid increasing health inequalities, it is necessary to create an environment in which they are more likely to participate in social activities.

Background: The Free/Low-Cost Medical Care Program (FLCMC) can subsidize the payment (exempt/lower) in designated institutions in Japan. Given that poverty is a multidimensional concept including social isolation, the FLCMC applicants may need social support over and above financial aid to improve their quality of life. However, there was no data to discuss what services should be provided and to whom. Hence, we aimed to describe the changes in health-related quality of life scores among users of the FLCMC, with respect to their socioeconomic backgrounds.

Methods: This cohort study included patients who newly used FLCMC from July 2018 to April 2019. We used patients’ social work records, obtained at baseline, and self-report questionnaires on the Medical Outcomes Study 8 Items Short Form Health Survey (SF-8), measured both at baseline and six-month-after the application. We used the change in physical and mental health component summary score (PCS-8 and MCS-8) as outcome variables.

Results: Multiple linear regression analyses, adjusting for age, sex, healthcare institute, and baseline PCS-8 and MCS-8, showed that lower income was associated with an increase in PCS-8 (coef. -0.09; 95% CI, -0.15 to, -0.03) and MCS-8 (coef. -0.04; 95% CI, -0.11, to 0.03). Living alone (versus. living with someone) was potentially associated with a decrease in both PCS-8 (coef. -1.58; 95% CI, -7.26 to 4.09) and MCS-8 (coef. -3.62; 95% CI, -9.19 to 1.95).

Conclusions: Among patients using FLCMC, those who live alone may need additional support. Further study testing the generalizability of the findings is required.

Two frequently encountered but underrecognized challenges for causal inference in studying the long-term health effects of disasters among survivors include: (a) time-varying effects of disasters on a time-to-event outcome and (b) selection bias due to selective attrition. We review approaches to overcome these challenges and show application of the approaches to a real-world longitudinal data of older adults who were directly impacted by the 2011 earthquake and tsunami (n=4,857). To illustrate the problem of time-varying effects of disasters, we examined the association between degree of damage due to the tsunami and all-cause mortality. We compared results from Cox regression assuming proportional hazards versus adjusted parametric survival curves allowing for time-varying hazard ratios. To illustrate the problem of selection bias, we examined the association between proximity to the coast (a proxy for housing damage from the tsunami) and depressive symptoms. We corrected for selection bias due to attrition in the two post-disaster follow-up surveys (conducted in 2013 and 2016) using multivariable adjustment, inverse probability censoring weighting, and survivor average causal effect estimation. Our results demonstrate that the analytic approaches ignoring time-varying effects on mortality and selection bias due to selective attrition may underestimate the long-term health effects of disasters.