Objectives A heat-not-burn (HNB) tobacco product, IQOS, was first launched in Japan and Italy as test markets and is currently in commerce in 30 countries. Using two data sources, we examined interest in HNB tobacco (IQOS, Ploom and glo), its prevalence, predictors of its use and symptoms from exposure to secondhand HNB tobacco aerosol in Japan, where HNB tobacco has been sold since 2014. Methods Population interest in HNB tobacco was explored using Google search query data. Prevalence of HNB tobacco current use (ie, use in the previous 30 days) was calculated using a longitudinal internet survey of 8240 individuals (15–69 years old in 2015) followed up to 2017. Rates of perceived symptoms from exposure to exhaled aerosol of others’ HNB tobacco were also calculated. Results The largest internet search volume for IQOS occurred in April 2016 in the week after a popular national entertainment TV show introduced IQOS. For Ploom and glo, search volumes have remained limited since their launch. Prevalence of IQOS users increased from 0.3% in January–February 2015 to 0.6% in January–February 2016 and up to 3.6% in January–February 2017, while estimated rates of use of other HNB tobacco products remained low in 2017. Respondents who had seen the TV programme in 2016 were more likely to have used IQOS than those who had not seen it (10.3% vs 2.7%). Among never-smokers who had been exposed to secondhand HNB tobacco aerosol, nearly half reported at least one acute symptom, although these symptoms were not serious. Conclusions A popular TV programme triggered IQOS diffusion in Japan. Extrapolating from survey results to the general population, around 3.1 million people currently use IQOS in Japan. Tobacco control organisations and governments should closely monitor HNB tobacco and consider how to regulate it.

Vaccination could be a key protective measure against coronavirus disease 2019 (COVID-19), and it is important to understand the acceptability of the COVID-19 vaccine among the general public. However, there is no study on the acceptance of a COVID-19 vaccine in Japan. Therefore, this study aimed to describe the COVID-19 vaccine acceptance and hesitancy situation in Japan and assess the factors associated with such issues. This was a cross-sectional study based on an internet survey completed by 2956 people. Participants were asked to indicate how likely they were to get vaccinated for COVID-19. In addition, the participants responded to questions regarding sociodemographic factors, attitudes, and beliefs regarding COVID-19 infection and vaccination. The proportion of participants with a high likelihood of getting a COVID-19 vaccine was 62.1%. Multiple logistic regression analysis showed that vaccine acceptance was lower among several sociodemographic groups, such as women, adults aged 20–49 years, and those with a low-income level. Several psychological factors, especially the perceived effectiveness of the COVID-19 vaccine, and willingness to protect others by getting oneself vaccinated, were associated with vaccine acceptance. Our results indicate that the perceived effectiveness of the vaccine and willingness to protect others may play an important role in the acceptance of the COVID-19 vaccine.

Although the pedestrian-friendly qualities of streetscapes promote walking, quantitative understanding of streetscape functionality remains insufficient. This study proposed a novel automated method to assess streetscape walkability (SW) using semantic segmentation and statistical modeling on Google Street View images. Using compositions of segmented streetscape elements, such as buildings and street trees, a regression-style model was built to predict SW, scored using a human-based auditing method. Older female active leisure walkers living in Bunkyo Ward, Tokyo, are associated with SW scores estimated by the model (OR = 3.783; 95% CI = 1.459 to 10.409), but male walkers are not.

Geographically Weighted Regression (GWR) is increasingly used in spatial analyses of social and environmental data. It allows spatial heterogeneities in processes and relationships to be investigated through a series of local regression models rather than a single global one. Standard GWR assumes that relationships between the response and predictor variables operate at the same spatial scale, which is frequently not the case. To address this, several GWR variants have been proposed. This paper describes a route map to decide whether to use a GWR model or not, and if so which of three core variants to apply: a standard GWR, a mixed GWR or a multiscale GWR (MS‐GWR). The route map comprises 3 primary steps that should always be undertaken: (1) a basic linear regression, (2) a MS‐GWR, and (3) investigations of the results of these in order to decide whether to use a GWR approach, and if so for determining the appropriate GWR variant. The paper also highlights the importance of investigating a number of secondary issues at global and local scales including collinearity, the influence of outliers, and dependent error terms. Code and data for the case study used to illustrate the route map are provided.