Historical dataset of population level and growth rate for the Kingston upon Hull, UK metro area from 1950 to 2025.

Kingston Upon Hull 012, Kingston Upon Hull, City Of demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Kingston Upon Hull 002, Kingston Upon Hull, City Of demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

The data collection contains population projections for UK ethnic groups and all local area by age (single year of age up to 100+) and sex. Included in the data set are also input data to the cohort component model that was used to project populations into the future-fertility rates, mortality rates, international migration flows and internal migration probabilities. Also included in data set are output data: Number of deaths, births and internal migrants. All data included are for the years 2011 to 2061. We have produced two ethnic population projections for UK local authorities, based on information on 2011 Census ethnic populations and 2010-2011-2012 ethnic components. Both projections align fertility and mortality assumptions to ONS assumptions. Where they differ is in the migration assumptions. In LEEDS L1 we employ internal migration rates for 2001 to 2011, including periods of boom and bust. We use a new assumption about international migration anticipating that the UK may leave the EU (BREXIT). In LEEDS L2 we use average internal migration rates for the 5 year period 2006-11 and the official international migration flow assumptions with a long term balance of +185 thousand per annum.

This project aims to understand and to forecast the ethnic transition in the United Kingdom's population at national and sub-national levels. The ethnic transition is the change in population composition from one dominated by the White British to much greater diversity. In the decade 2001-2011 the UK population grew strongly as a result of high immigration, increased fertility and reduced mortality. Both the Office for National Statistics (ONS) and Leeds University estimated the growth or decline in the sixteen ethnic groups making up the UK's population in 2001. The 2011 Census results revealed that both teams had over-estimated the growth of the White British population and under-estimated the growth of the ethnic minority populations. The wide variation between our local authority projected populations in 2011 and the Census suggested inaccurate forecasting of internal migration. We propose to develop, working closely with ONS as our first external partner, fresh estimates of mid-year ethnic populations and their components of change using new data on the later years of the decade and new methods to ensure the estimates agree in 2011 with the Census. This will involve using population accounting theory and an adjustment technique known as iterative proportional fitting to generate a fully consistent set of ethnic population estimates between 2001 and 2011.

We will study, at national and local scales, the development of demographic rates for ethnic group populations (fertility, mortality, internal migration and international migration). The ten year time series of component summary indicators and age-specific rates will provide a basis for modelling future assumptions for projections. We will, in our main projection, align the assumptions to the ONS 2012-based principal projection. The national assumptions will need conversion to ethnic groups and to local scale. The ten years of revised ethnic-specific component rates will enable us to study the relationships between national and local demographic trends. In addition, we will analyse a consistent time series of local authority internal migration. We cannot be sure, at this stage, how the national-local relationships for each ethnic group will be modelled but we will be able to test our models using the time series.

Of course, all future projections of the population are uncertain. We will therefore work to measure the uncertainty of component rates. The error distributions can be used to construct probability distributions of future populations via stochastic projections so that we can define confidence intervals around our projections. Users of projections are always interested in the impact of the component assumptions on future populations. We will run a set of reference projections to estimate the magnitude and direction of impact of international migrations assumptions (net effect of immigration less emigration), of internal migration assumptions (the net effect of in-migration less out-migration), of fertility assumptions compared with replacement level, of mortality assumptions compared with no change and finally the effect of the initial age distribution (i.e. demographic potential).

The outputs from the project will be a set of technical reports on each aspect of the research, journal papers submitted for peer review and a database of projection inputs and outputs available to users via the web. The demographic inputs will be subject to quality assurance by Edge Analytics, our second external partner. They will also help in disseminating these inputs to local government users who want to use them in their own ethnic projections. In sum, the project will show how a wide range of secondary data sources can be used in theoretically refined demographic models to provide us with a more reliable picture of how the UK population is going to change in ethnic composition.

In England, the Environment Agency (EA) estimates that over 3 million properties in England are at risk of surface water flooding. Heavy and prolonged rainfall that drives surface water flooding is projected to increase in the future due to climate change. This paper presents a quantitative secondary analysis of a cross-sectional household flood survey in a disadvantaged city in England heavily impacted by surface water flooding in 2007 and at severe risk of flooding in the future. The aim of this study was to examine how previous experience of flooding, demographic factors, and behaviours impact on feelings of protection against flooding and perceived ability to recover from flooding. Survey data were collected from residents in Hull in northern England in 2018, in areas impacted by major floods in 2007 when over 8,600 households were flooded. Valid responses were received from 453 households, of whom 37.3% were flooded or flooding damaged their house (n = 169), 14.6% had been disrupted by flooding (n = 66), 9.3% had been exposed to flooding (n = 42) and 176 (38.9%) had not experienced flooding. Over 22% felt they had very low protection against flooding, and over 25% would make a very slow recovery if they were flooded. Associations were found between gender and both low levels of protection against flooding. Females were less likely to feel confident in their recovery from flooding than males (OR 0.551). The findings support a need to focus on women’s perceptions of flood vulnerability and capacity to cope and recover from flooding in flood and disaster management policy and practice, including providing effective support before, during and after flooding.

Kingston Upon Hull 013, Kingston Upon Hull, City Of demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

Kingston Upon Hull 029f, East Riding Of Yorkshire demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

Kingston Upon Hull 015, Kingston Upon Hull, City Of demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.