RESUMO
BACKGROUND: Area differences in life expectancy (LE) and healthy life expectancy (HLE) in large geographical units have been monitored around the world. Area characteristics may be based on culture, history, socioeconomic status and discrimination in smaller geographical units, so it is important to consider these when looking at health inequality. We aimed to evaluate LE, HLE, and non-healthy life expectancy (NHLE) in 1707 municipalities using Areal Deprivation Index (ADI) in Japan for the first time. METHODS: We calculated the observed LE, HLE, and NHLE using death, population, and Long-term care insurance data for 2010-2014 and applied the variance weighted least squares model to estimate LE, HLE, and NHLE by 100 percentiles using the standardized ADI. FINDINGS: The estimated LE, HLE, and NHLE became lower as the deprivation index worsened: the differences between the most and least deprived areas for HLE were 2·49 years for LE and 2·32 years for HLE in males; 1·22 years for LE and 0·93 years for HLE in females. The observed LE and HLE in the most deprived areas were much lower than other areas. INTERPRETATION: Using ADI has enabled us to see the disparity within municipalities precisely. LE and HLE outlier for the 100th percentile might be linked to historical areal deprivation and marginalization. Precise monitoring of socioeconomic status-based health inequalities could help manage these inequalities by identifying the groups most in need of intervention. FUNDING: The Ministry of Education, Science and Culture of Japan (a Grant-in-Aid for Scientific Research [A] No. 20H00040 and 18H04071).
RESUMO
OBJECTIVES: In Japan, companies are required to implement a "stress check program" to prevent mental health problems in workers. To identify "high-stress" workers, the Brief Job Stress Questionnaire (BJSQ) is recommended. According to the stress check program manual issued by the government, high-stress can be defined using two criteria, either the "sum method" (simply summing the scores for each scales) or the "score converted method" (using converted scores according to the conversion table for each scales). In this study, we examined the differences in results found using these two criteria on "stress check program" data. METHODS: We used data of 71,422 workers in 117 companies and organizations who conducted stress checks in 2016. The prevalence of high-stress was calculated by applying the two criteria simultaneously, and the chi-square test was used to compare the proportion of workers with high-stress. We subsequently divided participants into the four following groups and calculated the proportion of each group: group A was defined as having high-stress by both criteria; group B, only by the sum method; group C, only by the score converted method; and group D, not defined as high-stress by either criterion. We compared the average values of stress response among four groups using the Kruskal-Wallis test, and further compared the average values between group B and group C using the Bonferroni method. RESULTS: The average age of participants was 43.7 ± 11.1, and 66.8% were males. The proportion of those defined as having high-stress were 11.7% using the sum method and 13.2% using the score converted method; the proportion of high-stress workers was thus significantly higher when using the score converted method (p <.001). Physical stress response was higher in group B; however, lack of vigor, irritation, fatigue, and depression were higher in group C (p <.01). CONCLUSIONS: Compared to the sum method, 1.5% more high-stress workers were observed using the converted method, and this result was similar for individual and employment-related factors. Furthermore, workers were more likely to be judged as having "high-stress" when the score of the physical stress response was higher in the sum method. Hereafter, it is important to consider which criteria are applied when discussing proportions of high-stress. Further research is needed to examine which criteria will predict health disorders.