Objectives: The aim of this study was to examine the geographic distribution of diabetes mortality in Japan and identify socioeconomic factors affecting differences in municipality-specific diabetes mortality. Methods: Diabetes mortality data by year and municipality from 2013 to 2017 were extracted from Japanese Vital Statistics, and the socioeconomic characteristics of municipalities were obtained from government statistics. We calculated the standardized mortality ratio (SMR) of diabetes for each municipality using the empirical Bayes method and represented geographic differences in SMRs in a map of Japan. Multiple linear regression was conducted to identify the socioeconomic factors affecting differences in SMR. Statistically significant socioeconomic factors were further assessed by calculating the relative risk of mortality of quintiles of municipalities classified according to the degree of each socioeconomic factor using Poisson regression analysis. Results: The geographic distribution of diabetes mortality differed by gender. Of the municipality-specific socioeconomic factors, high rates of single-person households and unemployment and a high number of hospital beds were associated with a high SMR for men. High rates of fatherless households and blue-collar workers were associated with a high SMR for women, while high taxable per-capita income was associated with a low SMR for women. Quintile analysis revealed a complex relationship between taxable income and mortality for women. The mortality risk of quintiles with the highest and lowest taxable per-capita income was significantly lower than that of the middle-income quintile. Conclusions Socioeconomic factors of municipalities in Japan were found to affect geographic differences in diabetes mortality.

Objectives: The aim of this study was to examine the geographic distribution of diabetes mortality in Japan and identify socioeconomic factors affecting differences in municipality-specific diabetes mortality. Methods: Diabetes mortality data by year and municipality from 2013 to 2017 were extracted from Japanese Vital Statistics, and the socioeconomic characteristics of municipalities were obtained from government statistics. We calculated the standardized mortality ratio (SMR) of diabetes for each municipality using the empirical Bayes method and represented geographic differences in SMRs in a map of Japan. Multiple linear regression was conducted to identify the socioeconomic factors affecting differences in SMR. Statistically significant socioeconomic factors were further assessed by calculating the relative risk of mortality of quintiles of municipalities classified according to the degree of each socioeconomic factor using Poisson regression analysis. Results: The geographic distribution of diabetes mortality differed by gender. Of the municipality-specific socioeconomic factors, high rates of single-person households and unemployment and a high number of hospital beds were associated with a high SMR for men. High rates of fatherless households and blue-collar workers were associated with a high SMR for women, while high taxable per-capita income was associated with a low SMR for women. Quintile analysis revealed a complex relationship between taxable income and mortality for women. The mortality risk of quintiles with the highest and lowest taxable per-capita income was significantly lower than that of the middle-income quintile. Conclusions Socioeconomic factors of municipalities in Japan were found to affect geographic differences in diabetes mortality.

OBJECTIVES: This study aimed to conduct an age-period-cohort (APC) analysis of smoking prevalence trends in urban and non-urban areas in Japan. METHODS: Data on smoking prevalence from 2004 to 2019 were extracted from the Comprehensive Survey of Living Conditions in Japan. Government ordinance-designated cities and special wards in Tokyo were defined as urban areas. The respondents ranged from 20 years to 79 years old, and were grouped in 5-year intervals. Cohorts were defined for each age group of each year, and those born between 1925-1929 and 1995-1999 were examined. We calculated the estimated smoking prevalence for each age, period, and cohort, as well as the smoking prevalence ratio of non-urban areas compared with urban areas from the APC analysis results. RESULTS: The magnitude of the decrease in the period effect on smoking prevalence was larger in urban areas than in non-urban areas for both men and women. The smoking prevalence ratio for non-urban areas compared with that of urban areas was above 1 for men at most time points, except in the older age groups. In addition, the prevalence ratio between the areas decreased, particularly as age increased. For women, the smoking prevalence ratio in non-urban areas compared to urban areas was below 1 until cohorts born in the 1970s, but the trend reversed thereafter. CONCLUSIONS The results of this study suggest that further smoking control and cessation measures are necessary, particularly for older cohorts in urban women and for younger ages in non-urban men.

OBJECTIVES: This study investigated differences in the perinatal mortality rate between white-collar and blue-collar workers. METHODS: Data from the “Report of Vital Statistics: Occupational and Industrial Aspects” in Japan covering the period from 1995 to 2015 were used. Five-year maternal age groups from 15-19 years to 45-49 years were analyzed according to work type, and the perinatal mortality rate for each age group and the age-standardized perinatal mortality rate according to maternal age were calculated in each analyzed year. A Bayesian age-period-cohort analysis was used to estimate age, period, and cohort effects for the perinatal mortality rate according to work type. Moreover, the perinatal mortality rate ratios between types of workers were estimated for each age group, period, and cohort. RESULTS: The estimated perinatal mortality rate ratios of blue-collar to white-collar workers were above 1 in most of the age groups and cohorts. The age effect for the perinatal mortality rate among white-collar workers was the largest in the 15-year to 19-year age group, whereas that among blue-collar workers was the largest in the 45-year to 49-year age group. Furthermore, the estimated perinatal rate ratio between white-collar and blue-collar workers tended to increase with maternal age. The magnitude of the decrease of the cohort effects on the perinatal mortality rate was rather larger in blue-collar workers in the cohorts born between 1946-1950 and 1996-2000. CONCLUSIONS The magnitude of the disparity markedly increased with maternal age. Thus, middle-aged blue-collar workers need more prenatal care and preventive measures for perinatal mortality than white-collar workers.

OBJECTIVES: This study aimed to conduct an age-period-cohort (APC) analysis of smoking prevalence trends in urban and non-urban areas in Japan. METHODS: Data on smoking prevalence from 2004 to 2019 were extracted from the Comprehensive Survey of Living Conditions in Japan. Government ordinance-designated cities and special wards in Tokyo were defined as urban areas. The respondents ranged from 20 years to 79 years old, and were grouped in 5-year intervals. Cohorts were defined for each age group of each year, and those born between 1925-1929 and 1995-1999 were examined. We calculated the estimated smoking prevalence for each age, period, and cohort, as well as the smoking prevalence ratio of non-urban areas compared with urban areas from the APC analysis results. RESULTS: The magnitude of the decrease in the period effect on smoking prevalence was larger in urban areas than in non-urban areas for both men and women. The smoking prevalence ratio for non-urban areas compared with that of urban areas was above 1 for men at most time points, except in the older age groups. In addition, the prevalence ratio between the areas decreased, particularly as age increased. For women, the smoking prevalence ratio in non-urban areas compared to urban areas was below 1 until cohorts born in the 1970s, but the trend reversed thereafter. CONCLUSIONS The results of this study suggest that further smoking control and cessation measures are necessary, particularly for older cohorts in urban women and for younger ages in non-urban men.

OBJECTIVES: This study investigated differences in the perinatal mortality rate between white-collar and blue-collar workers. METHODS: Data from the “Report of Vital Statistics: Occupational and Industrial Aspects” in Japan covering the period from 1995 to 2015 were used. Five-year maternal age groups from 15-19 years to 45-49 years were analyzed according to work type, and the perinatal mortality rate for each age group and the age-standardized perinatal mortality rate according to maternal age were calculated in each analyzed year. A Bayesian age-period-cohort analysis was used to estimate age, period, and cohort effects for the perinatal mortality rate according to work type. Moreover, the perinatal mortality rate ratios between types of workers were estimated for each age group, period, and cohort. RESULTS: The estimated perinatal mortality rate ratios of blue-collar to white-collar workers were above 1 in most of the age groups and cohorts. The age effect for the perinatal mortality rate among white-collar workers was the largest in the 15-year to 19-year age group, whereas that among blue-collar workers was the largest in the 45-year to 49-year age group. Furthermore, the estimated perinatal rate ratio between white-collar and blue-collar workers tended to increase with maternal age. The magnitude of the decrease of the cohort effects on the perinatal mortality rate was rather larger in blue-collar workers in the cohorts born between 1946-1950 and 1996-2000. CONCLUSIONS The magnitude of the disparity markedly increased with maternal age. Thus, middle-aged blue-collar workers need more prenatal care and preventive measures for perinatal mortality than white-collar workers.

Objectives: We investigated trends in the incidence rate of macrosomia and its association with parental nationalities using Vital Statistics data in Japan. Methods: We used singleton birth data every 5 years from 1995 to 2020. The incidence rate of macrosomia was calculated according to specific attributes (maternal age, infant’s sex, parental nationalities, parity, and household occupation) over time (years). In addition, a log-binomial model was used to investigate the relationship between the incidence of macrosomia and the attributes. This study compared Korea, China, the Philippines, Brazil, and other countries with Japan in terms of parental nationalities. “Other countries” indicates countries except for Japan, Korea, China, the Philippines, and Brazil. Results: The study included 6 180 787 births. The rate of macrosomia in Japan decreased from 1.43% in 1995 to 0.88% in 2020, and the decrease was observed across all parental nationalities. The rates for Japanese parents were the lowest values among parental nationalities during the timespan investigated. Multivariate regression analysis showed that mothers from Korea, China, the Philippines, Brazil, and other countries had a significantly higher risk of macrosomia than those from Japan (risk ratio, 1.91, 2.82, 1.59, 1.74, and 1.64, respectively). Furthermore, fathers from China, the Philippines, Brazil, and other countries had a significantly higher risk of macrosomia than those from Japan (risk ratio, 1.66, 1.38, 1.88, and 3.02, respectively). Conclusions The rate of macrosomia decreased from 1995 to 2020 in Japan for parents of all nationalities, and the risk of macrosomia incidence was associated with parental nationality.

Objectives: This study aimed to analyze the mortality of heart disease (HD), ischemic heart disease (IHD), and cerebrovascular disease (CeVD) through an age-period-cohort (APC) analysis. Methods: We used data on mortality due to cardiovascular disease from 1995 to 2018 in Japan, as determined by Vital Statistics. Age groups from 0 years to 99 years were defined by 5-year increments, and cohorts were defined for each age group of each year with a 1-year shift. We used Bayesian APC analysis to decompose the changes in the diseases’ mortality rates into age, period, and cohort effects. Results: The period effects for all diseases decreased during the analyzed periods for both men and women. The cohort effects for men increased substantially in cohorts born from around 1940 to the 1970s for all types of cardiovascular diseases. The cohort effects of HD decreased in the cohorts born in the 1970s or later for both men and women. Regarding IHD and CeVD, either a non-increase or decrease of cohort effects was confirmed for cohorts born in the 1970s or later for men, but the effects for women showed a continuously increasing trend in the cohorts born in the 1960s or later. Conclusions The cohort effects for IHD and CeVD showed increasing trends in younger generations of women. This suggests that preventive approaches against cardiovascular diseases are needed, particularly for women.

Objectives: This study conducted an age-period-cohort (APC) analysis of trends in healthy lifestyle behaviors in Japan. Methods: We used National Health and Nutrition Survey data on salt intake and prevalence of smoking, drinking, and physical activity between 1995 and 2018 in Japan. Age groups were defined from 20 years to 69 years old in 10-year increments. Cohorts were defined for each age group of each year with a 1-year shift, and cohorts born in 1926-1935 (first cohort) until 1989-1998 (last cohort) were examined. We conducted a Bayesian APC analysis, calculating estimated values for each behavior by age group, period, and cohort. Results: Estimated salt intake decreased from cohorts born in the 1930s to the 1960s, but increased thereafter in both genders, and the magnitude of increase was larger for men. Estimated smoking prevalence increased in the cohorts starting from the 1930s for men and the 1940s for women, and then decreased starting in the cohorts born in the 1970s for both genders. Although estimated drinking prevalence decreased starting in the cohorts born in approximately 1960 for men, for women it increased until the cohorts born in approximately 1970. Estimated physical activity prevalence decreased starting in the cohorts born in the 1940s in both genders, but the magnitude of decrease was larger for women. Conclusions Trends in cohort effects differed by gender, which might be related to changes in the social environment for women. Improvements in dietary and exercise habits are required in more recently born cohorts of both genders.

Objectives: No studies have examined the association between preterm birth rates and socioeconomic factors in Japan using nationwide statistical data. We analyzed the association between preterm birth rates and household occupation using Vital Statistics data. Methods: Aggregated Vital Statistics data from Japan from 2007 to 2019 were obtained from the Ministry of Health, Labour and Welfare. From the data, the number of births according to year, age group, gestational period, number of pregnancies, and household occupation were used in this study. Crude preterm birth rates and preterm birth rates adjusted by maternal age according to household occupation were calculated for each year. Poisson regression analysis was conducted to evaluate the association between household occupation and preterm births. Results: Unemployed households had the highest preterm birth rate, and households with an occupation classification of “full-time worker 2” (an employee at a large company, civil servant, or board member) had the lowest preterm birth rate throughout each period. Poisson regression analysis revealed that unemployed households were statistically significantly associated with a high preterm birth risk. In contrast, the preterm birth rate adjusted by maternal age remained stable throughout each period regardless of household occupation, and preterm birth rates were found not to have increased in recent years in Japan. Conclusions Unemployed households had higher preterm birth rates than other household occupations. Further studies investigating the characteristics of unemployed households are needed to identify the reasons for this disparity.