Hisaaki Nishimura

Background Climate-related health impacts have been a global public health concern. Identifying vulnerable populations is critical in implementing adaptation strategies. This study aimed to examine how heat-related impacts on all-cause emergency hospitalisations differ by area deprivation and urbanicity. Methods All-cause emergency hospitalisations were identified in the Japanese nationwide administrative database during the warm season between 2011 and 2019. A time-stratified case-crossover study was conducted to examine short-term associations between daily mean temperature and hospitalisation. Days of heat exposure were defined as days when the daily mean temperature exceeded the minimum morbidity temperature (ie, temperature with the lowest relative risk between the 25th and the 75th percentiles of the daily mean temperature distribution). Analyses were stratified by area deprivation index and urbanicity. Heat-related excess hospitalisations were quantified using the population attributable fraction (PAF), derived as a fraction of heat-attributable emergency hospitalisations to the total number of emergency hospitalisations for all study subjects or within specific subgroups. Results We identified 5 914 084 hospitalisations. Among all study subjects, PAF for heat-related excess hospitalisations was 1.69% (95% CI 1.54% to 1.87%). PAF for heat-related excess hospitalisations was more pronounced in people living in the most deprived areas (1.87%, 95% CI 1.68% to 2.06%) than those in the least deprived (1.19%, 95% CI 0.98% to 1.41%) and in urban populations (2.03%, 95% CI 1.78% to 2.30%) than rural ones (1.42% (95%CI 1.24% to 1.60%)). When further stratified by deprivation and urbanicity simultaneously, PAF for heat-related excess hospitalisations was most significant among urban populations living in the most deprived areas (2.62%, 95% CI 2.26% to 3.03%). Conclusion These findings revealed that individuals living in the most deprived areas in urban settings were particularly vulnerable to heat exposure. Adaptation strategies tailored to socioeconomic and geographical inequalities can potentially reduce future heat-related health impacts.

Objective There is a need for public health strategies to address the negative psychological consequences of the COVID-19 pandemic, and the role of residential green exposure has gained prominence, particularly in the context of the ‘new normal’ and the prevailing ‘stay-at-home’ policies. This study aimed to evaluate the association between residential greenness and severe psychological distress during the COVID-19 pandemic in Japan. We also investigated the association stratified by ‘stay-at-home’ status, a proxy for exposure to residential greenness. Methods and analysis We used data from a population-based cohort study conducted in Utsunomiya City, Japan. Residential greenness was measured by the normalised difference vegetation index (NDVI) averaged over circular buffers around residence. Severe psychological distress was defined as a Kessler Psychological Distress Scale (K6) score ≥13. ‘Stay-at-home’ status was categorised as either ‘not stay-at-home’ (individuals working outside the home or self-employed) or ‘stay-at-home’ (working from home or not working), based on the working status. Logistic regression analysis was performed to examine the association between residential greenness and severe psychological distress. Results A total of 615 participants were analysed. Among the ‘stay-at-home’ group, an IQR increase in NDVI was inversely associated with severe psychological distress (100 m buffer: OR=0.27, 95% CI 0.10 to 0.77; 250 m buffer: OR=0.26, 95% CI 0.10 to 0.69; 500 m buffer: OR=0.33, 95% CI 0.11 to 0.95). However, no significant association was observed for the ‘not stay-at-home’ group. Conclusion Residential greenness was a protective factor for severe psychological distress among the ‘stay-at-home’ group, who were assumed to have spent more time in their residence.

An 87.7 mm² 1.6 GB/s 128 Mb chain FeRAM with 130 nm 4-metal CMOS process is demonstrated. In addition to small bitline capacitance inherent to chain FeRAM architecture, three new FeRAM scaling techniques - octal bitline architecture, small parasitic capacitance sensing scheme, and dual metal plateline scheme - reduce bitline capacitance from 100 fF to 60 fF. As a result, a cell signal of ±220 mV is achieved even with the small cell size of 0.252 ¿m². An 800 Mb/s/pin read/write bandwidth at 400 MHz clock is realized by installing SDRAM compatible DDR2 interface, and performance is verified by simulation. The internal power-line bounce noise due to 400 MHz clock operation is suppressed to less than 50 mV by an event-driven current driver, which supplies several hundreds of mA of current within 2 ns response. The precise timing and voltage controls are achieved by using the data stored in a compact FeRAM-fuse, which consists of extra FeRAM memory cells placed in edge of normal array instead of conventional laser fuse links. This configuration minimizes area penalty to 0.2% without cell signal degradation.