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The size, composition, and spatial distribution of both people and households have a substantial impact on the demand for and development and delivery of infrastructure required to support the population. Infrastructure encompasses a wide range of domains including energy, transport, and water, each of which has its own set of spatial catchments at differing scales. Demographic projections are required to assess potential future demand; however, official projections are usually not provided at a high level of spatial resolution required for infrastructure planning. Furthermore, generating bespoke demographic projections, often incorporating a range of scenarios of possible future demographic change is a specialist, resource intensive job and as such is often missing from infrastructure development projects. In this paper we make the case that such demographic projections should be at the heart of infrastructure planning and present a set of open-source models which can be used to undertake this demographic projection work, thus providing the tools needed to fill the identified gap. We make use of a case study for the United Kingdom to exemplify how a range of scenarios can be assessed using our model.

Many legislators around the word are offering the use of web based e-petitioning platforms to allow their electorate to influence government policy and action. A popular e-petition can gain much coverage, both in traditional media and social media. The task then becomes how to understand what features may make an e-petition popular and hence, potentially influential. One area of investigation is the linguistic and topical content of the supporting e-petition text. This study takes an existing methodology previously applied to the American government's e-petition platform and replicates the study for the United Kingdom's equivalent platform. This allows an insight into not only the United Kingdom's e-petition process but also a comparison with a similar platform. We find that when assessing an e-petition's popularity, the control variables are significant in both countries, e-petitions in the United Kingdom are more popular if some named entities are used in the text, and that topics are commonly more influential in America.

The future of the meat industry will require the management of important trade-offs between economic, environmental and health aspects of both humans and animals. Understanding the patterns and trends of meat expenditure and consumption is crucial for assessing the current resilience of the system and for economic, planning, health and environmental applications. Here, we show how the technique of geodemographic classification, combined with fine scale expenditure estimates can be used to explore temporal and spatial patterns of meat expenditure in Great Britain between 2008 and 2017. Whilst the expenditure patterns of some food categories such as sausages remained relatively consistent, others such as lamb show a trend towards a reduced proportion of expenditure and increased inequality of purchases. Short term changes in expenditure patterns also occurred, potentially due to product specific price variability, price elasticities or zoonotic disease scare. Environmental attitudes, financial constraints and the prominence of communities who do not eat meat for religious or cultural reasons are likely to be driving the differences between geodemographic groups. The methodology and results could be a valuable tool for policy makers in the meat industry and beyond.

To implement population projections by ethnicity requires input of ethnic fertility rates, which vary considerably across groups. In most countries in which ethnic projections are produced, populations and vital components are classified by ethnicity. In the UK ethnic classifications have been employed in the decennial population censuses since 1991 and in the annual Labour Force Survey since 1980. But at registration of births, ethnicity is not recorded, though some health authorities may add ethnicity to birth occurrence records completed by an attending health professional. Country of birth is recorded on the birth certificate. However, this only signals ethnicity for foreign born mothers when ethnic groups are also made up of native-born mothers. Therefore, we need to use indirect methods to make plausible estimates. Most researchers use official household surveys to estimate fertility rates from information about the composition of families with children resident in the households surveyed. Household surveys are samples and are rarely large enough to make reliable estimates of fertility rates for local areas. In our 2011-based projections, there is a need estimates for 389 local areas: 324 local authorities in England, 22 in Wales, 32 in Scotland and 11 in Northern Ireland. To achieve our estimated fertility rates, we employ a variety of data sources in addition to birth records and surveys, the most important of which is the decennial census which provides reliable counts of mother and infants by ethnicity at local scale.

This document provides additional information about the methods used to develop the international migration inputs to the projections described in the associated JEMS paper and discusses further methods that might be included in future projections of international migration by ethnicity. In order to project the population by ethnicity, it is necessary to estimate immigration and emigration for the starting baseline year (2011) for the 12 ethnic groups in our analysis. The estimates are required for the United Kingdom and for its constituent local authorities. This is a challenge because international migration is poorly measured in the United Kingdom through a survey, the International Passenger Survey (IPS), which does not include a question on migrant ethnicity. It is also necessary to decide on the model for forecasting immigration and emigration and to forecast those flows into the future to 2061.

Internal migration is one of the main drivers of local population change and therefore an important factor to consider in the provision of services across key domains such as housing, health and education. In recent years, the population of England and Wales has become increasingly ethnically diverse, with groups varying in age structure and time spent in the UK (whether at the group or individual level). However, relatively little is known about the internal migration patterns of these diverse groups, with research into internal migration propensity not accounting for the possible interplay between ethnicity, country of birth and age. Using micro-data from the 2011 Census for England and Wales, this paper addresses this gap in knowledge, exploring whether widely reported determinants of internal migration operate differently for different ethnic groups, stratified by age and country of birth. This paper also explores whether for ethnic minority groups born overseas, time spent in the UK matters for migration propensity. When stratifying ethnic groups by age and country of birth, differences in migration propensity do not appear to be explained by socio-economic differences, as previous research in the field suggests. However, for those born overseas, some of the differences are explained by time spent in the UK. From a policy perspective, it is evident that a more nuanced understanding of the way in which propensity to migrate may vary between ethnic groups differing in age and country of birth is needed to ensure sustained provision and equitable access across key service domains. Further research must examine the extent to which differences in migration propensity shapes the nature of migration events, whether in terms of distance or frequency of move.

Background There has been considerable interest in the role of access to unhealthy food options as a determinant of weight status. There is conflict across the literature as to the existence of such an association, partly due to the dominance of cross-sectional study designs and inconsistent definitions of the food environment. The aim of our study is to use longitudinal data to examine if features of the food environment are associated to measures of adolescent weight status. Methods Data were collected from secondary schools in Leeds (UK) and included measurements at school years 7 (ages 11/12), 9 (13/14), and 11 (15/16). Outcome variables, for weight status, were standardised body mass index and standardised waist circumference. Explanatory variables included the number of fast food outlets, supermarkets and ‘other retail outlets’ located within a 1 km radius of an individual’s home or school, and estimated travel route between these locations (with a 500 m buffer). Multi-level models were fit to analyse the association (adjusted for confounders) between the explanatory and outcome variables. We also examined changes in our outcome variables between each time period. Results We found few associations between the food environment and measures of adolescent weight status. Where significant associations were detected, they mainly demonstrated a positive association between the number of amenities and weight status (although effect sizes were small). Examining changes in weight status between time periods produced mainly non-significant or inconsistent associations. Conclusions Our study found little consistent evidence of an association between features of the food environment and adolescent weight status. It suggests that policy efforts focusing on the food environment may have a limited effect at tackling the high prevalence of obesity if not supported by additional strategies.

In a representative democracy it is important that politicians have knowledge of the desires, aspirations and concerns of their constituents. Opportunities to gauge these opinions are however limited and, in the era of novel data, thoughts turn to what alternative, secondary, data sources may be available to keep politicians informed about local concerns. One such source of data are signatories to electronic petitions (e-petitions). Such e-petitions have risen greatly in popularity over the past decade and allow members of the public to initiate and sign an e-petition online, with popular e-petitions resulting in media attention, a response from the government or ultimately a debate in parliament. These data are thus novel in their availability and have not yet been widely used for research purposes. In this article we will use the e-petition data to show how semantic classes of Westminster Parliamentary constituencies, fitted as Gaussian finite mixture models via EM algorithm, can be used to typify constituencies. We identify four classes: Domestic Liberals; International Liberals; Nostalgic Brits and Rural Concerns, and illustrate how they map onto electoral results. The findings and the utility of this approach to incorporate new e-petitions and adapt to changes in electoral geography are discussed.

This chapter discusses migration trends in the UK, a state that is middle ranking in migration intensity. It outlines the problems in constructing a consistent long-term time series across the constituent countries of the UK and considers the datasets that can be used to overcome these. The analysis explores trends in migration by distance of move and also by geographical area with a special focus on the North/South Divide and London. Its chief findings are that there is no evidence that the inter-regional migration rate has trended down since the 1970s but that it has varied cyclically according to the state of the economy. Flows across the North/South Divide and between London and the rest of the country exhibit similar cyclical patterns. However, there is evidence that the rate of shorter-distance moving has declined since the 1970s. Possible causes for the patterns observed across all spatial scales include stickiness in the housing market, the expansion of higher education, and the substitution of other types of mobility for address-changing. The economic fortunes of London also seem to be of key importance given its dominance within the UK. Further work to clarify the relationship between internal and international migration intensities is advocated.

This chapter describes the creation of new estimates of ethnic populations and components of change in local authority districts (LADs) in England for years between the 2001 and 2011 Censuses. Information on ethnic populations by age and gender is provided in censuses. In between censuses, information on ethnic population change is scarce. To fill the gap we used data from the two censuses with reconciled total population and component estimates published by the Office of National Statistics. This chapter outlines the sequence of steps used to produce a ten-year time series. These reconciled population and component estimates provide a firmer foundation for ethnic-specific projections than hitherto available. The role of the census in this work is vital.

This chapter describes the context, model, estimates and assumptions for projections of ethnic group populations in England at local authority scale, and in Wales, Scotland and Northern Ireland. A bi-regional cohort-component model is used; estimates of the component rates for ethnic groups are developed; assumptions are aligned to recent official projections with one exception. For international migration we assume higher immigration, emigration and net balances of 254 thousand in the long term compared with the most recent official assumption of 185 thousand. The projections show that the UK population grows significantly, from a population of 59.1 million in 2001 to 84.5 million in 2061. Black, Asian and other Minority ethnic groups expand their share of the UK population from 8 to 30 % in that period. This increasing diversity is greatest in the UK’s largest cities but ethnic minority groups grow fastest outside those cities. We show through a comparison of 2001 based and 2011 based projections that there is considerable uncertainty both nationally and locally in future diversity although the direction of travel to a more diverse future is certain.

This report responds to a request for advice by National Records of Scotland (NRS) on how to adapt and improve the methodology used for the Scotland Sub-National Population Projections (SNPP). The 2014- based Scotland SNPP are currently being prepared.