In the year 1500, the share of Western Europe's population living in urban areas was just six percent, but this rose to 31 percent by the end of the 19th century. Despite this drastic change, development was quite slow between 1500 and 1800, and it was not until the industrial revolution when there was a spike in urbanization. As Britain was the first region to undergo the industrial revolution, from around the 1760s until the 1840s, these areas were the most urbanized in Europe by 1890. The Low Countries Prior to the 19th century, Belgium and the Netherlands had been the most urbanized regions due to the legacy of their proto-industrial areas in the medieval period, and then the growth of their port cities during the Netherlands' empirical expansion (Belgium was a part of the Netherlands until the 1830s). Belgium was also quick to industrialize in the 1800s, and saw faster development than its larger, more economically powerful neighbors, France and Germany. Least-urban areas Ireland was the only Western European region with virtually no urbanization in the 16th and 17th century, but the industrial growth of Belfast and Dublin (then major port cities of the British Empire) saw this change by the late-1800s. The region of Scandinavia was the least-urbanized area in Western Europe by 1890, but it saw rapid economic growth in Europe during the first half of the following century.

It is only in the past two centuries where demographics and the development of human populations has emerged as a subject in its own right, as industrialization and improvements in medicine gave way to exponential growth of the world's population. There are very few known demographic studies conducted before the 1800s, which means that modern scholars have had to use a variety of documents from centuries gone by, along with archeological and anthropological studies, to try and gain a better understanding of the world's demographic development. Genealogical records One such method is the study of genealogical records from the past; luckily, there are many genealogies relating to European families that date back as far as medieval times. Unfortunately, however, all of these studies relate to families in the upper and elite classes; this is not entirely representative of the overall population as these families had a much higher standard of living and were less susceptible to famine or malnutrition than the average person (although elites were more likely to die during times of war). Nonetheless, there is much to be learned from this data. Impact of the Black Death In the centuries between 1200 and 1745, English male aristocrats who made it to their 21st birthday were generally expected to live to an age between 62 and 72 years old. The only century where life expectancy among this group was much lower was in the 1300s, where the Black Death caused life expectancy among adult English noblemen to drop to just 45 years. Experts assume that the pre-plague population of England was somewhere between four and seven million people in the thirteenth century, and just two million in the fourteenth century, meaning that Britain lost at least half of its population due to the plague. Although the plague only peaked in England for approximately eighteen months, between 1348 and 1350, it devastated the entire population, and further outbreaks in the following decades caused life expectancy in the decade to drop further. The bubonic plague did return to England sporadically until the mid-seventeenth century, although life expectancy among English male aristocrats rose again in the centuries following the worst outbreak, and even peaked at more than 71 years in the first half of the sixteenth century.

In the past four centuries, the population of the Thirteen Colonies and United States of America has grown from a recorded 350 people around the Jamestown colony in Virginia in 1610, to an estimated 346 million in 2025. While the fertility rate has now dropped well below replacement level, and the population is on track to go into a natural decline in the 2040s, projected high net immigration rates mean the population will continue growing well into the next century, crossing the 400 million mark in the 2070s. Indigenous population Early population figures for the Thirteen Colonies and United States come with certain caveats. Official records excluded the indigenous population, and they generally remained excluded until the late 1800s. In 1500, in the first decade of European colonization of the Americas, the native population living within the modern U.S. borders was believed to be around 1.9 million people. The spread of Old World diseases, such as smallpox, measles, and influenza, to biologically defenseless populations in the New World then wreaked havoc across the continent, often wiping out large portions of the population in areas that had not yet made contact with Europeans. By the time of Jamestown's founding in 1607, it is believed the native population within current U.S. borders had dropped by almost 60 percent. As the U.S. expanded, indigenous populations were largely still excluded from population figures as they were driven westward, however taxpaying Natives were included in the census from 1870 to 1890, before all were included thereafter. It should be noted that estimates for indigenous populations in the Americas vary significantly by source and time period. Migration and expansion fuels population growth The arrival of European settlers and African slaves was the key driver of population growth in North America in the 17th century. Settlers from Britain were the dominant group in the Thirteen Colonies, before settlers from elsewhere in Europe, particularly Germany and Ireland, made a large impact in the mid-19th century. By the end of the 19th century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. It is also estimated that almost 400,000 African slaves were transported directly across the Atlantic to mainland North America between 1500 and 1866 (although the importation of slaves was abolished in 1808). Blacks made up a much larger share of the population before slavery's abolition. Twentieth and twenty-first century The U.S. population has grown steadily since 1900, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. Since WWII, the U.S. has established itself as the world's foremost superpower, with the world's largest economy, and most powerful military. This growth in prosperity has been accompanied by increases in living standards, particularly through medical advances, infrastructure improvements, clean water accessibility. These have all contributed to higher infant and child survival rates, as well as an increase in life expectancy (doubling from roughly 40 to 80 years in the past 150 years), which have also played a large part in population growth. As fertility rates decline and increases in life expectancy slows, migration remains the largest factor in population growth. Since the 1960s, Latin America has now become the most common origin for migrants in the U.S., while immigration rates from Asia have also increased significantly. It remains to be seen how immigration restrictions of the current administration affect long-term population projections for the United States.

Between 1500 and 1800, London grew to be the largest city in Western Europe, with its population growing almost 22 times larger in this period. London would eventually overtake Constantinople as Europe's largest in the 1700s, before becoming the largest city in the world (ahead of Beijing) in the early-1800s.

The most populous cities in this period were the capitals of European empires, with Paris, Amsterdam, and Vienna growing to become the largest cities, alongside the likes of Lisbon and Madrid in Iberia, and Naples or Venice in Italy. Many of northwestern Europe's largest cities in 1500 would eventually be overtaken by others not shown here, such as the port cities of Hamburg, Marseilles or Rotterdam, or more industrial cities such as Berlin, Birmingham, and Munich.

BackgroundIt is not known whether equity-oriented primary care investment that seeks to scale up the delivery of effective care in disadvantaged communities can reduce health inequality within high-income settings that have pre-existing universal primary care systems. We provide some non-randomised controlled evidence by comparing health inequality trends between two similar jurisdictions–one of which implemented equity-oriented primary care investment in the mid-to-late 2000s as part of a cross-government strategy for reducing health inequality (England), and one which invested in primary care without any explicit equity objective (Ontario, Canada).MethodsWe analysed whole-population data on 32,482 neighbourhoods (with mean population size of approximately 1,500 people) in England, and 18,961 neighbourhoods (with mean population size of approximately 700 people) in Ontario. We examined trends in mortality amenable to healthcare by decile groups of neighbourhood deprivation within each jurisdiction. We used linear models to estimate absolute and relative gaps in amenable mortality between most and least deprived groups, considering the gradient between these extremes, and evaluated difference-in-difference comparisons between the two jurisdictions.ResultsInequality trends were comparable in both jurisdictions from 2004–6 but diverged from 2007–11. Compared with Ontario, the absolute gap in amenable mortality in England fell between 2004–6 and 2007–11 by 19.8 per 100,000 population (95% CI: 4.8 to 34.9); and the relative gap in amenable mortality fell by 10 percentage points (95% CI: 1 to 19). The biggest divergence occurred in the most deprived decile group of neighbourhoods.DiscussionIn comparison to Ontario, England succeeded in reducing absolute socioeconomic gaps in mortality amenable to healthcare from 2007 to 2011, and preventing them from growing in relative terms. Equity-oriented primary care reform in England in the mid-to-late 2000s may have helped to reduce socioeconomic inequality in health, though other explanations for this divergence are possible and further research is needed on the specific causal mechanisms.

The earliest point where scientists can make reasonable estimates for the population of global regions is around 10,000 years before the Common Era (or 12,000 years ago). Estimates suggest that Asia has consistently been the most populated continent, and the least populated continent has generally been Oceania (although it was more heavily populated than areas such as North America in very early years). Population growth was very slow, but an increase can be observed between most of the given time periods. There were, however, dips in population due to pandemics, the most notable of these being the impact of plague in Eurasia in the 14th century, and the impact of European contact with the indigenous populations of the Americas after 1492, where it took almost four centuries for the population of Latin America to return to its pre-1500 level. The world's population first reached one billion people in 1803, which also coincided with a spike in population growth, due to the onset of the demographic transition. This wave of growth first spread across the most industrially developed countries in the 19th century, and the correlation between demographic development and industrial or economic maturity continued until today, with Africa being the final major region to begin its transition in the late-1900s.

Site indices, as a relative measure of the actual population size, for UK butterfly species calculated from data from the UK Butterfly Monitoring Scheme (UKBMS). Site indices are a relative rather than an absolute measure of the size of a population, and have been shown to relate closely to other, more intensive, measures of population size such as mark, release, recapture (MRR) methods. The site index can be thought of as a relative measure of the actual population size, being a more or less constant proportion of the number of butterflies present. The proportion seen is likely to vary according to species; some butterfly species are more conspicuous and thus more easily detected, whereas others are much less easy to see. Site indices are only calculated at sites with sufficient monitoring visits throughout the season, or for targeted reduced effort surveys (timed observations, larval web counts and egg counts) where counts are generally obtained as close to the peak of the flight period as possible and are subsequently adjusted for the time of year and size of the site (area of suitable habitat type for a given species). Wider Countryside Butterfly Survey (WCBS) sites are thus excluded because they are based on very few visits from which accurate indices of abundance cannot currently be calculated. For transect sites a statistical model (a General Additive Model, 'GAM') is used to impute missing values and to calculate a site index. Each year most transect sites (over 90%) produce an index for at least one species and in recent years site indices are calculated for almost 1,500 sites across the UK. Site indices are subsequently collated to contribute to the overall 'Collated Index' for each species, which are relative measures of the abundance of each species across a geographical area, for example, across the whole UK or at country level in England, Scotland, Wales or Northern Ireland. Individual site indices are important in informing conservation management as not all sites show the same patterns for each species and likely reflect a combination of local climate and habitat management at the site. Although the Centre for Ecology & Hydrology (CEH) and Butterfly Conservation (BC) are responsible for the calculation and interpretation of site indices, the collection of the data used in its creation is ultimately reliant on a large volunteer community. The UKBMS is run by Butterfly Conservation (BC), the Centre for Ecology & Hydrology (CEH) and the British Trust for Ornithology (BTO), in partnership with the Joint Nature Conservation Committee (JNCC), and supported and steered by Forestry Commission (FC), Natural England(NE), Natural Resources Wales (NRW), Northern Ireland Environment Agency (NIEA), and Scottish Natural Heritage (SNH). The UKBMS is indebted to all volunteers who contribute data to the scheme. Full details about this dataset can be found at https://doi.org/10.5285/378f0f77-1842-4789-ba15-6fbdf7d02299

While the European colonization and settlement of other world regions largely began in the 16th and 17th centuries, it was not until the 19th century when the largest waves of migration began to take place. In early years, migration rates were comparatively low; in all of the Americas, the slave population actually outnumbered that of Europeans for most of the given period. Then, with the development of steam ships, intercontinental travel became more affordable and accessible to the masses, and voluntary migration from Europe rose significantly. Additionally, larger numbers of Asian migrants, especially from India and China, migrated to Australia, the Caribbean, and U.S. from the mid-1800s; although the U.S. and Australia both introduced policies that limited or prevented Asian immigration throughout most of the early 1900s. International migration between 1913 and 1950 was also comparatively low due to the tumultuous nature of the period, which involved both World Wars and the Great Depression.

For a case study of England, global principal component analysis (PCA) is applied to a suite of neighborhood-scale energy vulnerability indicators.

PCA reduces a large multivariate set of vulnerability factors into a reduced number of principal components, retaining key statistical information and spatial patterns. The components have loading values associated with each of the vulnerability indicators in the input data set. Loadings tell us about the type (negative or positive) and strength of the relationship between an indicator and a principal component, providing information about the patterns of vulnerability within the data set that each component is likely to represent. These global component loadings can be mapped to provide an understanding of the spatial distribution of the vulnerability represented by each principal component and the locales in which vulnerability is likely to be enhanced as a result.

This dataset contains three principal components which account for 62.4 percent of the variance in the 21 energy vulnerability indicators identified. The first component has strong positive association with precarious and transient families but a strong inverse relationship with retirement and older age groups. The second component has a strong positive relationship with disability, illness, and the provision of care. The third component has a positive relationship with the energy efficiency and availability of networked and domestic energy infrastructures. The principal components are mapped at the Lower Super Output Area (LSOA) scale, an administrative area unit with a mean population of 1,500 persons.

Background Low birthweight (LBW) is associated with increased mortality in infancy, but its association with mortality in later childhood and adolescence is less clear. We investigated the association between birthweight and all-cause mortality and identified major causes of mortality for different birthweight groups. Methods and findings We conducted a population study of all live births occurring in England and Wales between 1 January 1993 and 31 December 2011. Following exclusions, the 12,355,251 live births were classified by birthweight: 500-1,499 g (very LBW [VLBW], n = 139,608), 1,500-2,499 g (LBW, n = 759,283), 2,500-3,499 g (n = 6,511,411), and ?3,500 g (n = 4,944,949). The association of birthweight group with mortality in infancy (<1 y of age) and childhood/adolescence (1-18 y of age) was quantified, with and without covariates, through hazard ratios using Cox regression. International Classification of Diseases codes identified causes of death. In all, 74,890 (0.61%) individuals died between birth and 18 y of age, with 23% of deaths occurring after infancy. Adjusted hazard ratios for infant deaths were 145 (95% CI 141, 149) and 9.8 (95% CI 9.5, 10.1) for the VLBW and LBW groups, respectively, compared to the ?3,500 g group. The respective hazard ratios for death occurring at age 1-18 y were 6.6 (95% CI 6.1, 7.1) and 2.9 (95% CI 2.8, 3.1). Male gender, the youngest and oldest maternal age bands, multiple births, and deprivation (Index of Multiple Deprivation score) also contributed to increased deaths in the VLBW and LBW groups in both age ranges. In infancy, perinatal factors, particularly respiratory issues and infections, explained 84% and 31% of deaths in the VLBW and LBW groups, respectively; congenital malformations explained 36% and 23% in the LBW group and ?2,500 g groups (2,500-3,499 g and ?3,500 g groups combined), respectively. Central nervous system conditions explained 20% of deaths in childhood/adolescence in the VLBW group, with deaths from neoplasms and external conditions increasingly prevalent in the 1,500-2,499 g and ?2,500 g birthweight groups. The study would have benefited had we had access to information on gestational age and maternal smoking, but since the former is highly correlated with birthweight and the latter with deprivation, we believe that our findings remain robust despite these shortcomings. Conclusions LBW is associated with infant and later child and adolescent mortality, with perinatal factors and congenital malformations explaining many of the deaths. By understanding and ameliorating the influences of upstream exposures such as maternal smoking and deprivation, later mortality can be decreased by reducing the delivery of vulnerable infants with LBW.

Definition and categorisation of demographic and clinical data extracted from the electronic health records of early-onset UI (< 8.5 years) case and control bitches attending primary-care veterinary practices in the VetCompass™ Programme in the UK (n = 1500).

During the eighteenth century, it is estimated that France's population grew by roughly fifty percent, from 19.7 million in 1700, to 29 million by 1800. In France itself, the 1700s are remembered for the end of King Louis XIV's reign in 1715, the Age of Enlightenment, and the French Revolution. During this century, the scientific and ideological advances made in France and across Europe challenged the leadership structures of the time, and questioned the relationship between monarchial, religious and political institutions and their subjects. France was arguably the most powerful nation in the world in these early years, with the second largest population in Europe (after Russia); however, this century was defined by a number of costly, large-scale conflicts across Europe and in the new North American theater, which saw the loss of most overseas territories (particularly in North America) and almost bankrupted the French crown. A combination of regressive taxation, food shortages and enlightenment ideologies ultimately culminated in the French Revolution in 1789, which brought an end to the Ancien Régime, and set in motion a period of self-actualization.

War and peace

After a volatile and tumultuous decade, in which tens of thousands were executed by the state (most infamously: guillotined), relative stability was restored within France as Napoleon Bonaparte seized power in 1799, and the policies of the revolution became enforced. Beyond France's borders, the country was involved in a series of large scale wars for two almost decades, and the First French Empire eventually covered half of Europe by 1812. In 1815, Napoleon was defeated outright, the empire was dissolved, and the monarchy was restored to France; nonetheless, a large number of revolutionary and Napoleonic reforms remained in effect afterwards, and the ideas had a long-term impact across the globe. France experienced a century of comparative peace in the aftermath of the Napoleonic Wars; there were some notable uprisings and conflicts, and the monarchy was abolished yet again, but nothing on the scale of what had preceded or what was to follow. A new overseas colonial empire was also established in the late 1800s, particularly across Africa and Southeast Asia. Through most of the eighteenth and nineteenth century, France had the second largest population in Europe (after Russia), however political instability and the economic prioritization of Paris meant that the entire country did not urbanize or industrialize at the same rate as the other European powers. Because of this, Germany and Britain entered the twentieth century with larger populations, and other regions, such as Austria or Belgium, had overtaken France in terms of industrialization; the German annexation of Alsace-Lorraine in the Franco-Prussian War was also a major contributor to this.

World Wars and contemporary France

Coming into the 1900s, France had a population of approximately forty million people (officially 38 million* due to to territorial changes), and there was relatively little growth in the first half of the century. France was comparatively unprepared for a large scale war, however it became one of the most active theaters of the First World War when Germany invaded via Belgium in 1914, with the ability to mobilize over eight million men. By the war's end in 1918, France had lost almost 1.4 million in the conflict, and approximately 300,000 in the Spanish Flu pandemic that followed. Germany invaded France again during the Second World War, and occupied the country from 1940, until the Allied counter-invasion liberated the country during the summer of 1944. France lost around 600,000 people in the course of the war, over half of which were civilians. Following the war's end, the country experienced a baby boom, and the population grew by approximately twenty million people in the next fifty years (compared to just one million in the previous fifty years). Since the 1950s, France's economy quickly grew to be one of the strongest in the world, despite losing the vast majority of its overseas colonial empire by the 1970s. A wave of migration, especially from these former colonies, has greatly contributed to the growth and diversity of France's population today, which stands at over 65 million people in 2020.

This file contains the boundaries, names and codes for 2021 Census Lower Layer Super Output Areas (LSOA) in Cheshire East as at 31 December 2021. These boundaries are created by the Office for National Statistics. Nationally, Lower Layer Super Output Areas have an average population of 1500 people or 650 households. They were updated following the 2021 Census, to reflect changes in local population. In Cheshire East, the 234 former LSOAs were updated - 11 LSOAs were abolished to become 21 new LSOAs, which were sub-divisions of the former LSOA boundaries.The whole of England and Wales can be broken down into these constituent areas. Output areas (OAs) nestle within the boundaries of Lower Super Output Areas (LSOAs), LSOAs nestle within the boundaries of Middle Layer Super Output Areas (MSOAs) and MSOAs nestle within the boundaries of Local Authorities.Boundary data sources used by permission of relevant providers © Crown Copyright Ordnance Survey and National Statistics.

The share of households owning a pet in the United Kingdom remained relatively stable between 2012 and 2018, hovering around an estimated percentage of 47 to 45 percent. However, pet ownership levels peaked to an unprecedented high of 62 percent in 2022, likely as a result of the coronavirus pandemic and increased time spent at home. In 2023, this figure shrank to 57 percent.

Pet ownership in the UK With more than half of UK households owning at least one pet in 2021/22, dogs and cats were the most common household pets in that year, with an estimated 13 million dogs and 12 million cats living in homes. As of 2020, the United Kingdom was the second highest-ranking European country in terms of its dog population, preceded only by Germany.

Consumer spending on pets in the UK As the pet population in the United Kingdom increased in size, so did consumer spending on pet food and pet-related products and services. Spending on pets and related products reached almost eight billion British pounds in 2020, a notable increase from a mere 2.9 billion British pounds in 2005. Among the most expensive pet-related expenditures are veterinary and pet services, which constituted almost four billion British pounds in 2020.