In 2020, the population of Tokyo Metropolis amounted to over 6,402 inhabitants per square kilometer. The number increased from approximately 5,517 inhabitants per square kilometer in 2000.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

The statistic presents the population density in the Greater Tokyo Area in Japan from 1985 to 2015. In 1985, Greater Tokyo's population amounted to ***** inhabitants per square kilometer. This number increased to almost ***** inhabitants per square kilometer in 2015.

In 1800, the population of Japan was just over 30 million, a figure which would grow by just two million in the first half of the 19th century. However, with the fall of the Tokugawa shogunate and the restoration of the emperor in the Meiji Restoration of 1868, Japan would begin transforming from an isolated feudal island, to a modernized empire built on Western models. The Meiji period would see a rapid rise in the population of Japan, as industrialization and advancements in healthcare lead to a significant reduction in child mortality rates, while the creation overseas colonies would lead to a strong economic boom. However, this growth would slow beginning in 1937, as Japan entered a prolonged war with the Republic of China, which later grew into a major theater of the Second World War. The war was eventually brought to Japan's home front, with the escalation of Allied air raids on Japanese urban centers from 1944 onwards (Tokyo was the most-bombed city of the Second World War). By the war's end in 1945 and the subsequent occupation of the island by the Allied military, Japan had suffered over two and a half million military fatalities, and over one million civilian deaths.

The population figures of Japan were quick to recover, as the post-war “economic miracle” would see an unprecedented expansion of the Japanese economy, and would lead to the country becoming one of the first fully industrialized nations in East Asia. As living standards rose, the population of Japan would increase from 77 million in 1945, to over 127 million by the end of the century. However, growth would begin to slow in the late 1980s, as birth rates and migration rates fell, and Japan eventually grew to have one of the oldest populations in the world. The population would peak in 2008 at just over 128 million, but has consistently fallen each year since then, as the fertility rate of the country remains below replacement level (despite government initiatives to counter this) and the country's immigrant population remains relatively stable. The population of Japan is expected to continue its decline in the coming years, and in 2020, it is estimated that approximately 126 million people inhabit the island country.

Comprehensive socio-economic dataset for Japan including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

In the past decade, Japan’s degree of urbanization has leveled off at around 92.04 percent. This means that less than 10 percent of Japan’s population of 126 million inhabitants do not live in an urban setting. Japan is well above the degree of urbanization worldwide, which is 55 percent. Japan is also known for its high population density: In 2017, it amounted to an eye-watering 347.78 inhabitants per square kilometer - however, it is not even among the top twenty countries with the highest population density worldwide. That ranking is lead by Monaco, followed by China, and Singapore. Japan’s aging population The main demographic challenge that Japan currently faces is an aging population, as the number of inhabitants over 65 years old is an increasing percentage of the population. As of 2018, Japan is the country with the largest percentage of total population over 65 years, and life expectancy at birth there is about 84 years. Simultaneously, the birth rate in Japan is declining, resulting in negative population growth in recent years. One method Japan is using to address these demographic shifts is by investing in automated work processes; it's one of the top countries interested in collaborative robots.

dataplor specializes in delivering highly precise, actionable intelligence tailored for businesses operating within the complex Japanese market. Our in-depth Point of Interest and foot traffic dataset for Japan is a cornerstone for businesses seeking to optimize operations and expand their footprint across the country.

Unlocking Japan's Potential with dataplor's POI Data Third-party Logistics / Order Fulfillment: Leverage our dataset to optimize delivery routes, identify optimal warehouse locations in bustling cities like Tokyo, Osaka, and Nagoya, and enhance last-mile delivery efficiency in densely populated urban areas.

Consumer Product Goods (CPGs): Gain a competitive edge by identifying ideal store locations in high-traffic areas, understanding consumer preferences across different regions and optimizing product distribution strategies. Telecommunication: Identify areas with high smartphone penetration, analyze competitor tower locations, and optimize network coverage in major cities and rural prefectures.

Finance and Investment: Evaluate potential investment opportunities by analyzing POI density and distribution in different regions (Tokyo, Osaka, Fukuoka), identifying affluent neighborhoods, and assessing the competitive landscape.

Store Location Data: Identify ideal store locations based on factors such as population density, competition, and consumer spending patterns in cities like Tokyo, Osaka, and Nagoya. Real Estate Intelligence: Assess property values based on location and surrounding amenities in major cities and regional areas.

Audience Targeting Data: Create highly targeted marketing campaigns through targeted marketing placement in high-density POI areas across Tokyo, Osaka, and Kyoto.

Travel Booking Data: Identify popular tourist destinations, analyze hotel and accommodation availability, and optimize travel itineraries for domestic and international visitors. dataplor's Japan POI dataset offers unparalleled granularity and accuracy, empowering businesses to make informed decisions and achieve sustainable growth in this dynamic market.

The ongoing multi-wave COVID-19 pandemic has disproportional impacts on people with different demographic and socioeconomic background, and their access to healthcare facilities. Vulnerable neighborhoods with low healthcare access are places most needed for the enhancement of medical resources and services. Measuring vulnerability to COVID-19 and healthcare accessibility at the fine-grained level serves as the foundation for spatially explicit health planning and policy making in response to future public health crisis. Despite of its importance, the evaluation of vulnerability and healthcare accessibility is insufficient in Japan—a nation with high population density and super-aging challenge. Drawing on the latest 2022 census data at the smallest statistical unit, as well as transport network, medical and digital cadastral data, land use maps, and points of interest data, our study reformulates the concept of vulnerability in the context of COVID-19 and constructs the first fine-grained measure of vulnerability and healthcare accessibility in Tokyo Metropolis, Japan—the most popular metropolitan region in the world. We delineate the vulnerable neighborhoods with low healthcare access and further evaluate the disparity in healthcare access and built environment of areas at different levels of vulnerability. Our outcome datasets and findings provide nuanced and timely evidence to government and health authorities to have a holistic and latest understanding of social vulnerability to COVID-19 and healthcare access at a fine-grained level. Our analytical framework can be employed to different geographic contexts, guiding through the place-based health planning and policy making in the post-COVID era and beyond.

The cardiac surgery instruments market in Japan size was valued at USD 141.3 million in 2024 and is anticipated to surpass USD 357.1 million by the end of 2036, expanding at a CAGR of 8% during the forecast period, i.e., 2025-2036. Tokyo is the largest healthcare market in Japan due to the high population density that puts pressure on the healthcare delivery systems for cardiac surgery instruments.

As of 2025, Tokyo-Yokohama in Japan was the largest world urban agglomeration, with 37 million people living there. Delhi ranked second with more than 34 million, with Shanghai in third with more than 30 million inhabitants.

Body size often declines with increasing temperature. Although there is ample evidence for this effect to be adaptive, it remains unclear whether size shrinking at warmer temperatures is driven by specific properties of being smaller (e.g. surface to volume ratio) or by traits that are correlated with size (e.g. metabolism, growth). We used 290 generations (22 months) of artificial selection on a unicellular phytoplankton species to evolve a 13-fold difference in volume between small-selected and large-selected cells and tested their performance at 22°C (usual temperature), 18°C (-4), and 26°C (+4). Warmer temperatures increased fitness in small-selected individuals and reduced fitness in large-selected ones, indicating changes in size alone are sufficient to mediate temperature-dependent performance. Our results are incompatible with the often-cited geometric argument of warmer temperature intensifying resource limitation. Instead, we find evidence that is consistent with larger cells being more vulnerable to reactive oxygen species (ROS). By engineering cells of different sizes, our results suggest that smaller-celled species are pre-adapted for higher temperatures. We discuss the potential repercussions for global carbon cycles and the biological pump under climate warming.

Methods Materials and Methods

  Study species and culturing conditions

As a model species, we chose the green microalgal species Dunaliella tertiolecta (Butcher) because it is cosmopolitan, tolerates a wide range of climates (from tropical to sub-polar), has an intermediate body size compared to other phytoplankton species, and grows well in the laboratory (Guiry 2019). We sourced this species from the Australian National Algae Culture Collection (ANACC; strain code CS-14) and started cultures from multiple cells per independent lineage (i.e. not clonal), cultured in autoclaved F/2 medium (with no silica) from 0.45µm-filtered seawater (Guillard 1975). We kept the environment constant using a temperature-controlled room at 21±1 °C, under a photoperiod of 14-10 h day-night and a light intensity of 150 µM photos m-2 s-1, using low-heat 50 W LED flood lights (Power-liteTM, Nedlands Group, Bedfordale, Australia).

  Artificial selection for size

For details on the artificial selection methods, see Malerba et al. (2018c). Briefly, the method relies on larger cells forming a pellet at the bottom of test tubes at lower centrifugal forces compared to smaller cells, which instead will remain in solution (i.e. differential centrifugation). On 25th April 2016, we inoculated 72 lineages with the same ancestral population of D. tertiolecta into aseptic 75 cm2 plastic cell culture flasks (Corning, Canted Neck, Nonpyrogenic). Since then, we selected lineages twice a week, each Monday and Thursday: 30 lineages were large-selected, 30 small-selected and 12 were the control. The selection differential for both larger and smaller cells was approx. 10% shift between cell volume before and after artificial selection. Control cultures experienced identical conditions (including centrifugation) without being size-selected. At the end of selection, all cultures were diluted approx. 3-5 times in fresh F/2 medium. Lineages were not axenic, but we kept bacterial loads to minimal levels by resuspending pelleted cells in autoclaved medium twice a week and by handling samples using sterile materials under a laminar-flow cabinet (Gelman Sciences Australia, CF23S, NATA certified).

For this experiment, we used cells sampled from 12 randomly selected lineages for each of the three size-selection treatments after 290 generations (22 months) of artificial selection. To remove any environmental effects and non-genetic phenotypic differences from artificial selection, before starting trials all cells grew for three generations (a week) under common garden conditions with no centrifugation (neutral selection). Following neutral selection, we measured the mean cell volume for all 36 lineages, using optic light microscopy at 400x after staining cells with lugol’s iodine at 2%. We calculated cell volume from at least 200 cells per culture in Fiji v2.0 (Schindelin et al. 2012) assuming prolate spheroid shape, as recommended for this species by Sun and Liu (2003).

  Temperature trials

After neutral selection at 21±1 °C, we diluted samples from the 36 lineages ten-fold, resuspended into fresh F/2 medium and standardized for initial total biovolume (i.e. population density × mean cell volume; unit µm3 µL-1) – which is a better predictor for resource use than population density. We submerged all cultures inside transparent and side-illuminated water baths at a controlled temperature of either 22°C (usual temperature), 18°C (-4), and 26°C (+4; see Fig. 2 for experimental design). This temperature range mirrors usual yearly fluctuations in sub-tropical regions where this species is often found. Each temperature included three independent water baths, each holding 12 lineages (four per size-selection treatment; see Fig. 2). We manipulated the temperature of each water bath using a submergible aquarium heater placed behind the samples so as not to affect light exposure. We ensured that daily temperature fluctuations were within ±1°C. The experiment took place in a temperature-controlled room and samples experienced identical light conditions of 14-10 h day-night photoperiod with a light intensity of ca. 100 µM photos m-2 s-1.

We monitored all samples for mean cell volume, population density and total biovolume at day 0, 3 and 6. We recorded population density (i.e. cells µL-1) with a flow cytometer (FlowCore, BD LSRII; BD Biosciences, Franklin Lakes, NJ, USA) using a blue laser (488 nm) and CountBright absolute counting beads (Thermo Fisher, Waltham MA, USA) as internal standards in each sample. We inferred the mean cell volume (µm3) of a population using a calibration curve between the mean of the cytometric histogram for the forward scatter (after standardizing for the mean of the beads) and the mean cell volume measured using optical light microscopy (R2 = 0.84, F1,106 = 540.9, p < 0.001). Finally, we calculated the total biovolume (µm3 µL-1) by multiplying the population density by the mean cell volume. In total, the dataset included 972 observations (3 artificial selections x 3 temperatures x 3 baths x 4 replicates x 3 times x 3 demographic parameters).

  ROS assays

We adopted the methods for quantifying intracellular Reactive Oxygen Species (ROS) from Dao and Beardall (2016). After three generations of neutral selection (i.e. no centrifugation), we standardized six lineages per size-selection treatment to the same total biovolume and washed three times all populations into saline 40mM TRIS-HCl buffer (pH 7 and 35 ppt). Then, we dark-incubated cells in 50µM of fluorescent probe 2’,7’ dichlorodihydrofluorescein diacetate (DCFH-DA) for 90 minutes at 37°C. After resuspending the pellet in buffer, we sonicated cells for 10 minutes. We measured the fluorescence of the supernatant in a spectrophotometer (Hitachi F-7000, Tokyo, Japan) at wavelengths of 485 nm (excitation) and 525 nm (emission). Values were converted into fluorescence units of dichloro-fluorescein (nM) using a 7-point calibration curve (2nd degree polynomial: R2 = 0.999). The buffer was the negative control and dichlorofluorescein (DCF) from 5 to 75 nM was the positive control. We standardized ROS fluorescence in a sample for cell density and for the volume of the cell’s nucleus. Nucleus size was estimated from fluorescent microscopy (excitation at 325-375nm and emission at 435-485nm) with Leica DMi8 at 400x after fixing cells with 2% glutaraldehyde and resuspending the biomass in DAPI at 0.1 µg mL-1. The allometric relationship was: log10 nucleus volume = 0.479× log10 cell volume-0.122.

  Data analysis

We calculated three parameters that estimate the species short-term fitness from each time-series. The daily cell production (cells µL-1 day-1) of a lineage indicates rate of change in population densities between day 0 and 3. The daily biovolume production (µm3 µL-1 day-1) is the slope of total biovolume between day 0 and 3. The population carrying capacity (cells µL-1) was the final cell density of each lineage after the time-series reached a stable state (6 days). Finally, we analysed the effects of temperature on mean cell volumes (µm3) between day 0 and 3 among size-selection treatments.

We used linear mixed models to estimate the effects of temperature at each artificial selection treatment on mean cell size and the three fitness parameters. In all models, fixed effects included Temperature (continuous, from 18 to 26) and Artificial Selection Treatment (discrete, either small-selected, large-selected or control). We ensured that treating Temperature as a discrete categorical factor did not change any of the conclusions (see Fig. S1). For mean cell size, we monitored cultures for 6 days: to focus on phenotypic plasticity and exclude evolutionary effects, we only analysed observations at the start of the experiment and after 3 days of growth, with Time (continuous, from 0 to 3) as an additional fixed factor in the model. Initial models included all interaction terms. If not significant, higher-order interaction terms were removed from the model. Final models also included a random intercept for each lineage nested within treatment. We initially included a random slope with temperature, but was later removed from the final models after being consistently selected against by model selection with Akaike Information Criterion (Burnham and Anderson 2002). We calculated probability values for the linear mixed-models using an analysis of deviance with type II Wald chi-square test and Kenward-Roger approximation to calculate the degrees of freedom (see Table S1).

We

As of October 2023, the prefecture with the highest density of dental practices in Japan was Tokyo Prefecture, with around **** facilities per 100,000 inhabitants. Osaka ranked second with about **** clinics per 100,000 of the population. Dental clinics in Japan Before the European treatment technique for tooth decay was introduced during the westernization movement in the Meiji Era (*********), dental problems were commonly treated by doctors of internal medicine or surgery. The use of dentures improved with time, as bad teeth were mainly extracted instead of treated. The first Japanese dentistry-specialized clinic was opened in 1878 by a man who was licensed as the first 'dentist' in history in Japan. Following the establishment of the Dentist Law in 1948, dentistry in the country further expanded. In the past decade, the total number of dental clinics across the country has remained consistent at close to ** thousand. Most dental practices in Japan are founded by private individuals, followed by clinics owned and operated as medical corporations. Additionally, there were over 1,000 general hospitals with dentistry departments. National expenses on dental treatment Along with the increasing national medical expenditure for medical treatments, national medical expenses for dental treatments have indicated continuous growth. This is said to be due to the rapidly aging social structure of the country. As a result, treatments for the population aged 65 years and over accounted for the highest share of dental care-related investments. To reduce the dental-related medical expenditure, the health ministry and the Japan Dental association conducted the "8020" project and promoted proper dental care to the nation to maintain more than ** teeth at the age of **. In 2017, the rate of Japanese nationals over 80 years old with ** teeth exceeded ** percent. This was the set goal by the health ministry in the second version of the general health policy "Health Japan 21" enacted in 2013.