Journal of Epidemiology最新文献

Background: Menarche timing may affect female health. While previous studies evaluated self-reported age at menarche reproducibility, they did not assess types of respondents. This study compared the reproducibility of age at menarche among self-responders and proxy respondents and assessed proxy-respondent reproducibility by relationship and survey age.

Methods: Data on age at menarche reported in both the 1969 and 1978 mail questionnaires among 9,043 females from the Life Span Study cohort of atomic bomb survivors were analyzed. The reproducibility of menarcheal age was assessed by the type of respondents, by proxy's relationship to participant, and by age at the 1969 survey using Bland-Altman's method and the intraclass correlation coefficient (ICC).

Results: Reproducibility was moderate (95% limits of agreement, -2.3 to 2.4 years; ICC 0.72; 95% confidence interval, 0.71-0.73). Both self-respondents (N = 6,664) and the total study population (N = 9,043) maintained moderate reproducibility even at older ages. Groups with proxy reports showed lower reproducibility than self-respondents, with spouse proxy reports showing highest reproducibility and parent proxy reports showing lowest reproducibility among proxy reports, although the comparisons are based on different survey ages in 1969.

Conclusion: This is the first study to evaluate menarcheal-age reproducibility between self- and proxy-reports using appropriate measures. Mail questionnaires at 9-year interval showed moderate reproducibility across all ages, including elderly self-respondents. Reproducibility varied by the respondent-target relationship, with spouse proxies showing highest and parent proxies showing lowest reproducibility among proxy reports. Additional data are required to establish appropriate methods for handling specific proxy responses.

Background: Despite Japan's universal health insurance system, health disparities have increased since the 1990s. However, the impact of area deprivation on various aspects of child health remains understudied.

Methods: This population-based cohort study followed 38,554 children born in Japan (May 10-24, 2010) from birth to age 5.5 years. Using an outcome-wide approach, Bayesian three-level logistic regression models (individuals in municipalities within eight major regions) assessed associations between municipality-level Area Deprivation Index (ADI) at birth and multiple preschool health outcomes (hospitalizations for all causes; respiratory infections; gastrointestinal diseases; Kawasaki disease; medical visits for asthma, allergic rhinitis, atopic dermatitis, food allergy, injury, intussusception; prevalence of overweight/obesity), adjusting for individual-level factors.

Results: Higher ADI was associated with increased risk of all-cause hospitalization (adjusted odds ratio [aOR] per 1-standard-deviation increase in ADI, 1.04; 95% credible interval [CrI], 1.01-1.07), respiratory infections (aOR, 1.08; 95% CrI, 1.04-1.13), gastrointestinal diseases (aOR, 1.11; 95% CrI, 1.03-1.20), asthma (aOR, 1.10; 95% CrI, 1.01-1.19). Overweight/obesity at age 5.5 years also increased with higher ADI (aOR, 1.11; 95% CrI, 1.06-1.16). Higher ADI was inversely associated with Kawasaki disease (aOR, 0.86; 95% CrI, 0.77-0.96), though not robust in sensitivity analysis. Geographic clustering was observed for all outcomes, particularly at municipality level.

Conclusion: We found persistent municipal-level health inequalities across various childhood health outcomes in Japan, despite its universal health insurance system. These findings suggest that policymakers should address health inequalities through comprehensive strategies targeting broader social determinants beyond health care access.

Background: Older Japanese adults have the highest drowning mortality rates globally, likely due to in-home bathing customs. However, epidemiological evidence of preventive strategies based on national data is lacking. We aimed to describe the trends in bathtub drowning deaths (International Classification of Diseases, Tenth Revision code: W65) across Japan and explore factors that may reduce W65-coded deaths.

Methods: We collected the data of all W65-coded deaths that occurred at home from 1995 to 2020 using death certificates from the Ministry of Health, Labour and Welfare. The national age-adjusted mortality rates (AMRs) and prefecture-specific age-standardized mortality ratios (SMRs) were calculated. Data on demographic, socioeconomic, environmental factors, and nursing care services were obtained from the Japan Portal Site of Official Statistics. Mixed-effects analysis was used to examine the association between SMR and potential contributing factors at the prefecture level.

Results: We identified 99,930 W65-coded deaths at home, with the highest incidence among individuals aged 80-84 years, peaking in January. Since 2010, AMRs have consistently exceeded 3.0 per 100,000. An inverse association was found between SMR and the number of geriatric health service facilities and senior welfare centers per capita (coefficients per 1 standard deviation increase, -0.09; 95% confidence interval (CI), -0.13 to -0.05, P < 0.001 and -0.07; 95% CI, -0.11 to -0.02, P = 0.004, respectively), after adjusting for demographic, socioeconomic, and environmental factors.

Conclusion: Sustained high AMRs suggest that the rising death toll was not solely due to aging. Increased access to nursing care facilities may help prevent W65-coded deaths.

Background: Preventable behavioral risk factors account for approximately one third of mortality, morbidity, and disability worldwide. This study aims to quantify the interest in behavioral risk factors within major medical journals in 2022 and to derive trends over the past 30 years in the entire medical literature.

Methods: We analyzed the proportion of publications dealing with tobacco smoking, alcohol drinking, use of illicit drugs, excess body weight and physical activity among all the 1,128 articles published in the Journal of the American Medical Association, the British Medical Journal, the Lancet, and New England Journal of Medicine in 2022. A joinpoint analysis was conducted running in PubMed/MEDLINE specific search strings to evaluate trends over the last 30 years in the four journals and in the whole medical literature.

Results: In 2022, of all publications from the four considered medical journals, 2.8% dealt with tobacco smoking, 1.6% alcohol drinking, 1.1% use of illicit drugs, 3.8% excess body weight, 2.7% physical activity and 8.0% dealt with any behaviors. The joinpoint analysis on the whole medical literature showed that papers on modifiable risk factors significantly increased from 3.9% in 1993 to 6.2% in 2014 (annual percent change [APC]: between +1.83% and +4.09%), and subsequently decreased between 2014 and 2019 (APC -0.31%), with an acceleration thereafter (APC -2.41% in 2019-2022).

Conclusion: For the first time we quantified the volume of medical research focused on preventable behavioral risk factors. This appears to be limited and declining over the last decade. Research on primary prevention should be a priority to face the emergence of associated non-communicable diseases globally.

Background: In observational studies estimating the association between treatment and time-to-event outcomes, time-related biases can substantially impact results. Immortal time bias is one of such biases, and two types are known: misclassified immortal time bias and excluded immortal time bias. These biases often arise from incorrect time-zero definition, especially with non-user controls. This study aims to illustrate immortal time bias in non-user controls using formulas, simulations, and real-world data.

Methods: For our simulations, we considered two scenarios: one with no confounding and no treatment effect, and the other with time-dependent confounding. We compare three different settings of time-zero for treatment and control groups. Method 1: Both groups were followed from cohort entry date (CED). Method 2: The treatment group was followed from treatment initiation date (TID), while the non-user group was followed from CED. Method 3: The treatment group was followed from TID, and non-users were matched to treatment patients, followed from the corresponding TID of their matched patient.

Results: Our simulation showed that both Method 1 and Method 2 can exhibit large biases in the estimated treatment effect due to immortal time bias. The magnitude of the bias is greater for Method 1 than for Method 2. On the other hand, Method 3 showed almost no bias. Even in the presence of time-dependent confounding, Method 3 did not introduce bias.

Conclusions: To reduce time-related biases, it is crucial for researchers to carefully define an appropriate time-zero, especially when using a non-user control group.

Introduction: Evidence is scarce on cumulative SARS-CoV-2 infections among healthcare workers during the pandemic. This study aimed to describe cumulative infections, including undiagnosed cases, and identify factors associated with infection in healthcare workers in Japan.

Methods: Using serosurveys conducted across six national centers in Japan, we tracked COVID-19 cumulative infections. Seropositivity was defined as a positive result for SARS-CoV-2 nucleocapsid protein using the Roche assay, and cumulative infection was defined as the proportion of participants who tested positive for anti-nucleocapsid antibodies and/or self-reported a history of laboratory-confirmed or clinically diagnosed COVID-19 since the start of the pandemic. A robust Poisson regression model was used to investigate factors associated with infection risk as of September 2023.

Results: Cumulative infection, which was less than 5% until the end of 2021, increased after the emergence of the Omicron variant. Specifically, cumulative infection reached 14.6% in July 2022 (BA.1/2), 37.4% in December 2022 (BA.5), 53.3% in September 2023 (XBB subvariants), and 71.5% in December 2023 (JN.1 subvariant). The proportion of undiagnosed cases detected by antibody testing alone, without a prior diagnosis, decreased from 60.9% in December 2020 to 24.7% in December 2023. Individuals aged 50 to 59 years (PR: 0.73; 95% confidence interval: 0.67-0.79) and 60 years or older (PR: 0.67; confidence interval: 0.59-0.77) had lower cumulative infections than those aged under 30 years old. Physicians and nurses had significantly higher cumulative infections than administrative staff, with fully adjusted prevalence ratios of 1.09 (95% confidence interval: 1.01-1.18) and 1.18 (95% confidence interval: 1.08-1.30), respectively.

Conclusion: Among healthcare workers in Japan, cumulative SARS-CoV-2 infection markedly increased after the emergence of the Omicron variant, whereas the proportion of undiagnosed cases has decreased throughout the pandemic. Younger people (<50 years), as well as physicians and nurses, have faced a higher risk of infection.

Background: New long-term care insurance (LTCI) certifications and mortality are key outcomes in cohort studies involving older adults; however, the coronavirus disease 2019 (COVID-19)'s comprehensive impacts on these outcomes remain underexplored. We examined the pandemic's impact on new LTCI applications and all-cause mortality in a metropolitan cohort.

Methods: In 2016, 15,500 individuals aged 65-84 years were randomly selected through stratified sampling from Ota City, Tokyo. LTCI and death records were tracked through December 2023; the monthly LTCI applications and all-cause deaths per 10,000 people were calculated. The COVID-19 pandemic period was defined as beginning in March 2020, after the World Health Organization Director-General characterized the situation as a pandemic on March 11, 2020. Interrupted time-series segmented regression analysis was used to compare trends pre- (January 2018-February 2020) and post-pandemic onset (March 2020-December 2023).

Results: From January 2018 to December 2023, 4,083 new LTCI applications and 2,457 deaths were recorded. New monthly LTCI applications showed a modest upward trend pre-pandemic (0.4 per 10,000 people; 95% confidence interval [CI], 0.1-0.8), declined sharply at the pandemic's onset (-9.6 per 10,000 people; 95% CI, -16.0 to -3.2), and subsequently increased at a higher rate than pre-pandemic levels (0.8 per 10,000 people; 95% CI, 0.6-1.0). Monthly all-cause deaths remained stable before and immediately after the pandemic's onset but rose slightly in the post-pandemic period (0.3 per 10,000 people per month; 95% CI, 0.2-0.5).

Conclusion: The COVID-19 pandemic influenced both new LTCI applications and all-cause mortality in this study. These impacts should be carefully considered in cohort studies examining these outcomes.