Background: Logistic regression models are widely used to evaluate the association between a binary outcome and a set of covariates. However, when there are few study participants at the outcome and covariate levels, the models lead to bias of the odds ratio (OR) estimated using the maximum likelihood (ML) method. This bias is known as sparse data bias, and the estimated OR can yield impossibly large values because of data sparsity. However, this bias has been ignored in most epidemiological studies.

Methods: We review several methods for reducing sparse data bias in logistic regression. The primary aim is to evaluate the Bayesian methods in comparison with the classical methods, such as the ML, Firth’s, and exact methods using a simulation study. We also apply these methods to a real data set.

Results: Our simulation results indicate that the bias of the OR from the ML, Firth’s, and exact methods is considerable. Furthermore, the Bayesian methods with hyper-ɡ prior modeling of the prior covariance matrix for regression coefficients reduced the bias under the null hypothesis, whereas the Bayesian methods with log F-type priors reduced the bias under the alternative hypothesis.

Conclusion: The Bayesian methods using log F-type priors and hyper-ɡ prior are superior to the ML, Firth’s, and exact methods when fitting logistic models to sparse data sets. The choice of a preferable method depends on the null and alternative hypothesis. Sensitivity analysis is important to understand the robustness of the results in sparse data analysis.

Background: Limited data on electronic cigarette prevalence, patterns, and settings of use are available from several European countries.

Methods: Within the TackSHS project, a face-to-face survey was conducted in 2017–2018 in 12 European countries (Bulgaria, England, France, Germany, Greece, Ireland, Italy, Latvia, Poland, Portugal, Romania and Spain). Overall, 11,876 participants, representative of the population aged ⩾15 years in each country, provided information on electronic cigarette.

Results: 2.4% (95% confidence interval [CI], 2.2–2.7%) of the subjects (2.5% among men and 2.4% among women; 0.4% among never, 4.4% among current- and 6.5% among ex-smokers) reported current use of electronic cigarette, ranging from 0.6% in Spain to 7.2% in England. Of the 272 electronic cigarette users, 52.6% were dual users (ie, users of both electronic and conventional cigarettes) and 58.8% used liquids with nicotine. In all, 65.1% reported using electronic cigarette in at least one indoor setting where smoking is forbidden; in particular, at workplaces (34.9%) and bars and restaurants (41.5%). Multivariable logistic regression analysis showed that electronic cigarette use was lower among older individuals (P for trend <0.001) and higher among individuals with high level of education (P for trend = 0.040). Participants from countries with higher tobacco cigarette prices more frequently reported electronic cigarette use (odds ratio 3.62; 95% CI, 1.80–7.30).

Conclusion: Considering the whole adult population of these 12 European countries, more than 8.3 million people use electronic cigarettes. The majority of users also smoked conventional cigarettes, used electronic cigarettes with nicotine, and consumed electronic cigarettes in smoke-free indoor areas.

Background: Little is known about whether insufficient moderate-to-vigorous physical activity (MVPA) and longer sedentary behavior (SB) are independently associated with estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD), whether they interact with known risk factors for CKD, and the effect of replacing sedentary time with an equivalent duration of physical activity on kidney function.

Methods: We examined the cross-sectional association of MVPA and SB with eGFR and CKD in 66,603 Japanese cohort study in 14 areas from 2004 to 2013. MVPA and SB were estimated using a self-reported questionnaire, and CKD was defined as eGFR <60 mL/min/1.73 m². Multiple linear regression analyses, logistic regression analyses, and an isotemporal substitution model were applied.

Results: After adjusting for potential confounders, higher MVPA and longer SB were independently associated with higher eGFR (P for trend MVPA <0.0001) and lower eGFR (P for trend SB <0.0001), and a lower odds ratio (OR) of CKD (adjusted OR of MVPA ≥20 MET·h/day, 0.76; 95% confidence interval [CI], 0.68–0.85 compared to MVPA <5 MET·h/day) and a higher OR of CKD (adjusted OR of SB ≥16 h/day, 1.81; 95% CI, 1.52–2.15 compared to SB <7 h/day), respectively. The negative association between MVPA and CKD was stronger in men, and significant interactions between sex and MVPA were detected. Replacing 1 hour of SB with 1 hour of physical activity was associated with about 3 to 4% lower OR of CKD.

Conclusion: These findings indicate that replacing SB with physical activity may benefit kidney function, especially in men, adding to the possible evidence on CKD prevention.

Background: In Japan, ten percent of single-parent households are led by fathers. Taking care of children as a single father is very stressful and could put a strain on their health. It is very important to prevent and identify psychological distress among fathers for both their own health and to avoid negative impacts on children. This study aims to determine the prevalence of and factors associated with psychological distress among single fathers and understand how it is different from partnered fathers.

Methods: We used data from the Comprehensive Survey of Living Conditions 2016. Psychological distress, assessed using the K6 scale, was analyzed among 868 single and 43,880 partnered fathers. Logistic regression analysis was performed to assess the risk factors for psychological distress, such as employment type, sleep hours, and smoking and drinking habits.

Results: Single fathers had a higher proportion (8.5%) of psychological distress compared to partnered fathers (5.0%). A larger percentage of single fathers had a lower educational level and were more likely to be non-regular workers, self-employed, or unemployed than partnered fathers. Among single fathers, the crude and adjusted odds ratio for employment type and sleep hours were significantly associated with psychological distress.

Conclusion: As single parents who are self-employed or directors are likely to have significantly reduced psychological distress than those with regular jobs, measures are needed to improve the work-family balance for non-self-employed fathers. There is a need to provide greater financial assistance and other social welfare support to single parents to ensure their and their children’s good health.

Background: Leaving children alone at home is considered child neglect in some countries but is not prohibited in Japan. We investigated the association between being left alone at home and dental caries of children aged 6–7 years in Japan.

Methods: The data on first graders in all 69 public elementary schools in Adachi, Tokyo, obtained from repeated cross-sectional surveys in 2015, 2017, and 2019 were analyzed. Caregivers answered the questionnaire, and the data were linked to the information on children’s dental caries evaluated in school dental health checkups (N = 12,029). Poisson regression analysis with propensity score matching (PSM) was applied to account for confounders.

Results: Leaving children alone at home for ≥1 hour during the weekdays was reported by 46.4% of the caregivers, which did not vary across years. The PSM analysis showed that, compared with children never being left alone at home, children being left alone at home for ≥1 time per week had more dental caries (mean ratio [MR] 1.11; 95% confidence interval (CI), 1.02–1.21; P = 0.016), while <1 time per week was not associated (MR 0.97; 95% CI, 0.92–1.03; P = 0.345). The difference between those being left alone at home for <1 time per week and those being left alone for ≥1 time per week was not significant after applying Bonferroni correction (MR 1.12; 95% CI, 1.00–1.26; P = 0.041).

Conclusion: Leaving children alone at home for ≥1 hour every week might be a risk factor for dental caries of children aged 6–7 years.

Background: Metabolic syndrome (MetS) has been associated with various chronic diseases that may lead to long-term sickness absence (LTSA), but there is lacking information on the direct association between MetS and LTSA. The present study aimed to investigate the all-cause and cause-specific associations between MetS and the risk of medically certified LTSA among Japanese workers.

Methods: We recruited 67,403 workers (57,276 men and 10,127 women), aged 20–59 years from 13 companies in Japan during their health check-ups in 2011 (11 companies) and 2014 (2 companies), and we followed them for LTSA events (≥30 consecutive days) until March 31, 2020. MetS was defined according to the Joint Interim Statement. A Cox proportional hazards regression model was used to estimate hazard ratios (HRs) and its 95% confidence intervals (CIs) for LTSA associated with MetS and its components.

Results: During 408,324 person-years of follow-up, 2,915 workers experienced LTSA. The adjusted HR for all-cause LTSA was 1.54 (95% CI, 1.41–1.68) among those with MetS compared to those without MetS. In cause-specific analysis, HRs associated with MetS significantly increased for LTSA due to overall physical disorders (1.76); cardiovascular diseases (3.16); diseases of the musculoskeletal system and connective tissue (2.01); cancers (1.24); obesity-related cancers (1.35); mental, behavioral, and neurodevelopmental disorders (1.28); reaction to severe stress and adjustment disorders (1.46); and external causes (1.46). The number of MetS components were also significantly associated with increased LTSA risk.

Conclusion: MetS was associated with an increase in the risk of LTSA due to various diseases among Japanese workers.

Background: The EU LifeCycle Project was launched in 2017 to combine, harmonize, and analyze data from more than 250,000 participants across Europe and Australia, involving cohorts participating in the EU-funded LifeCycle Project. The purpose of this cohort description is to provide a detailed overview of the major measures within mental health domains that are available in 17 European and Australian cohorts participating in the LifeCycle Project.

Methods: Data on cognitive, behavioral, and psychological development has been collected on participants from birth until adulthood through questionnaire and medical data. We developed an inventory of the available data by mapping individual instruments, domain types, and age groups, providing the basis for statistical harmonization across mental health measures.

Results: The mental health data in LifeCycle contain longitudinal and cross-sectional data from birth throughout the life course, covering domains across a wide range of behavioral and psychopathology indicators and outcomes, including executive function, depression, ADHD, and cognition. These data span a unique combination of qualitative data collected through behavioral/cognitive/mental health questionnaires and examination, as well as data from biological samples and indices in the form of imaging (MRI, fetal ultrasound) and DNA methylation data. Harmonized variables on a subset of mental health domains have been developed, providing statistical equivalence of measures required for longitudinal meta-analyses across instruments and cohorts.

Conclusion: Mental health data harmonized through the LifeCycle project can be used to study life-course trajectories and exposure-outcome models that examine early life risk factors for mental illness and develop predictive markers for later-life disease.