About this dataset

Context

The dataset tabulates the Non-Hispanic population of New England by race. It includes the distribution of the Non-Hispanic population of New England across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of New England across relevant racial categories.

Key observations

Of the Non-Hispanic population in New England, the largest racial group is White alone with a population of 565 (86.26% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the New England
• Population: The population of the racial category (for Non-Hispanic) in the New England is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of New England total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New England Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in New England. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of New England population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 86.32% of the total residents in New England. Notably, the median household income for White households is $79,167. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $79,167.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in New England.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New England median household income by race. You can refer the same here

Many residents of New York City speak more than one language; a number of them speak and understand non-English languages more fluently than English. This dataset, derived from the Census Bureau's American Community Survey (ACS), includes information on over 1.7 million limited English proficient (LEP) residents and a subset of that population called limited English proficient citizens of voting age (CVALEP) at the Community District level. There are 59 community districts throughout NYC, with each district being represented by a Community Board.

National and subnational mid-year population estimates for England and Wales by administrative area, age and sex (including components of population change, median age and population density).

This dataset provides information about the number of properties, residents, and average property values for New England Drive cross streets in Chattanooga, TN.

This data set represents the average population density, in number of people per square kilometer multiplied by 10 for the year 2000, compiled for every catchment of NHDPlus for the conterminous United States. The source data set is the 2000 Population Density by Block Group for the Conterminous United States (Hitt, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

A dataset listing Massachusetts cities by population for 2024.

Introduction

Welcome to the New Zealand Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.

Speech Data

This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.

Dataset Diversity

Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.

Metadata

The dataset provides comprehensive metadata for each audio recording and participant:

This dataset provides information about the number of properties, residents, and average property values for New England Ridge Road cross streets in Washington, WV.

This data set represents the average population density, in number of people per square kilometer multiplied by 10 for the year 2000, compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data set is the 2000 Population Density by Block Group for the Conterminous United States (Hitt, 2003). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) RF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).

Virtual wards (VW) provide care at home with remote monitoring for people who do not need admission to hospital, but require hospital-led care. NHS England (NHSE) has requested an extension of a VW model of care,with a national ambition of developing 40-50 VW ‘beds’ per 100,000 population. It is important that these new models of care benefit older adults,as they make up the majority of unplanned hospital admissions.

​The Surgical Assessment Unit VW manages patients who are clinically suitable for home while waiting for investigation or treatment for an acute surgical condition.

To support a better evidence base for surgical VW, PIONEER has curated a highly granular dataset of 451,306 spells for patients aged 65 and older, eligible for the Virtual Surgical Assessment Unit (VSAU). The dataset includes a proportion of patients admitted to the VSAU and those remaining in traditional care pathways. It covers demography, comorbidities, presenting symptoms, serial physiology, diagnoses, investigations, treatments (including procedures), and outcomes. Admissions span from 2018 to 2023, with potential for expansion to other timelines of interest.

Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & > 120 ITU bed capacity. UHB runs a fully electronic healthcare record (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details. Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements. Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

This dataset represents ethnic group (19 tick-box level) by highest level qualification, for England and Wales combined. The data are also broken down by age and by sex.

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021. This dataset shows population counts for usual residents aged 16+ Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.

These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.

For quality information in general, please read more from here.

Ethnic Group (19 tick-box level)

These are the 19 ethnic group used in this dataset:

• Asian, Asian British or Asian Welsh
  • Bangladeshi
  • Chinese
  • Indian
  • Pakistani
  • Other Asian
• Black, Black British, Black Welsh, Caribbean or African
  • African
  • Caribbean
  • Other Black
• Mixed or Multiple ethnic groups
  • White and Asian
  • White and Black African
  • White and Black Caribbean
  • Other Mixed or Multiple ethnic groups
• White
  • English, Welsh, Scottish, Northern Irish or British
  • Gypsy or Irish Traveller
  • Irish
  • Roma
  • Other White
• Other ethnic group
  • Arab
  • Any other ethnic group

No qualifications

No qualifications

Level 1

Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills

Level 2

5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma

Apprenticeship

Apprenticeship

Level 3

2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma

Level 4 +

Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)

Other

Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2023-24, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2024. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019, the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fifth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with a breakdown for the mother's smoking status at the booking appointment by age group. It also provides counts of live born term babies with breakdowns for the general condition of newborns (via Apgar scores), skin-to-skin contact and baby's first feed type - all immediately after birth. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. For the first time information on 'Smoking at Time of Delivery' has been presented using annual data from the MSDS. This includes national data broken down by maternal age, ethnicity and deprivation. From 2025/2026, MSDS will become the official source of 'Smoking at Time of Delivery' information and will replace the historic 'Smoking at Time of Delivery' data which is to become retired. We are currently undergoing dual collection and reporting on a quarterly basis for 2024/25 to help users compare information from the two sources. We are working with data submitters to help reconcile any discrepancies at a local level before any close down activities begin. A link to the dual reporting in the SATOD publication series can be found in the links below. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

Super Bowl Game Records

2019 Super Bowl Game Records

By Throwback Thursday [source]

About this dataset

This dataset provides comprehensive information about Super Bowl games that took place in 2019, including game details such as the winning team, losing team, venue, city, attendance, network that broadcasted the game, average number of viewers in the United States who watched the game, rating (representing the percentage of households with televisions that were tuned into the game), share (representing the percentage of households with televisions in use that were tuned into the game), and cost per 30-second advertisement. Additionally, this dataset includes specific details about each Super Bowl game such as the final score (in terms of winning team points minus losing team points), conference affiliations of both winning and losing teams, and any additional notes or information about each respective Super Bowl. All of these data points collectively provide a comprehensive overview of each recorded Super Bowl game from 2019

How to use the dataset

• Game details: The 'Game' column represents the number or identifier of the Super Bowl game. For example, '1' indicates it is the first Super Bowl game.

• Winning team: The 'Winning team' column lists the name of the team that won the Super Bowl game. For example, 'New England Patriots'.

• Winning Team Points: The 'Winning Team Points' column shows the number of points scored by the winning team in that particular game.

• Winning Team Conference: The 'Winning Team Conference' column indicates which conference (e.g., AFC or NFC) the winning team belongs to.

• Score: The 'Score' column displays a summary of the final score in each game, showcasing how many points were scored by both teams in this format - Winning Team Points - Losing Team Points.

• Losing team: Similar to winning teams, losing teams are listed under the 'Losing team' column.

• Losing Team Conference: This column represents which conference (e.g., AFC or NFC)the losing team belongs to.

• Venue and city: The columns 'Venue' and 'City' show where each Super Bowl game was played, respectively.

• Attendance : This column shows numbers associated with how many people attended a particular super bowl event

• Network : Indicates Television network for broadcasted super bowl

11.Average U.S viewers : It denotes average number of viewers in United States who watched a specific super bowl

12.Rating & Share : These represent data associated with watching percentage (Rating)and households televisions percanton tuned into a particular event(Share).

13.Cost Per 30s Ad: The 'Cost Per 30s Ad' column specifies the cost of a 30-second advertisement during the Super Bowl game in dollars.

14.Notes: The 'Notes' column includes additional notes or information about each Super Bowl game.

This dataset provides a comprehensive record of every Super Bowl game that took place in 2019. By analyzing these attributes, you can gain insights into team performance, viewer interest, and commercial aspects of the games. Use this guide to explore and analyze the dataset effectively for your analysis or research purposes

Research Ideas

• Analyzing the popularity and reach of the Super Bowl: With data on average U.S. viewers, rating, share, and cost per 30-second ad, this dataset can be used to analyze the Super Bowl's popularity and reach. By comparing these metrics across different games, one can assess how the viewership and interest in the Super Bowl has changed over time.
• Evaluating advertising effectiveness during the Super Bowl: The dataset includes information on the cost per 30-second ad during each Super Bowl game. This data can be used to analyze whether there is a correlation between ad costs and viewer ratings or share. It can also help marketers and advertisers understand how effective their advertisements were in reaching a wide audience during past Super Bowls.
• Studying game attendance trends: The dataset provides information on attendance at each Super Bowl game. By analyzing this data, one can identify trends in game attendance over the years and evaluate factors that may impact ticket sales such as venue location or teams competing in the game. This analysis could be useful for event organizers and stadium operators looking to optimize future hosting decisions for large-scale events like sports championships or music festivals

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset descrip...

Academics for Land Protection in New England (ALPINE) is a network of academic institutions committed to increasing the pace of land protection in New England to address the region’s environmental challenges and to support nature and people. ALPINE seeks to expand the role that academic institutions play in conserving the New England landscape by sharing experiences and resources among faculty and staff, students, administrations, and alumni. This dataset contains point locations of colleges that are participants in ALPINE and parcels of natural land owned by participating schools who submitted data to the ALPINE coordinator.

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2022-23, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2023. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019 the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fourth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with breakdowns including the baby's first feed type, birthweight, place of birth, and breastfeeding activity; and the mothers' ethnicity and age at booking. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. The count of Total Babies includes both live and still births, and previous changes to how Total Babies and Total Deliveries were calculated means that comparisons between 2019-20 MSDS data and later years should be made with care. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

Request I believe the above scheme needs to be put in place urgently. Can you please answer the following questions: 1. How many people have applied to you for Ill Health Retirement with Long Covid? 2. How many people have been rejected for Tier One and/or Tier Two levels of IHR when applying with Long Covid? 3. What evidence (listing guidance and research evidence) are being used to reject or confirm applications for IHR with Long Covid? Response Question 1 & 2 A copy of the information is attached. Question 3 Each Scheme Medical Adviser (SMA) is expected to adopt evidence-based practice in arriving at a decision. They do this by combining the following: Medical evidence provided in the Scheme member’s application, Further medical evidence that the SMA may have requested from the Scheme member’s treating healthcare professionals, Information that the employer may have provided in Part A of Form AW33E (e.g. demands of the work duties, any workplace adjustments tried, and the effectiveness of such adjustments), Information that the Scheme member may have provided in Part B of Form AW33E (for example, how long COVID affects them), Current medical literature on long COVID, And the SMA’s occupational health expertise. When assessing ill-health retirement applications from scheme members who have long COVID, the SMA might consult the following guidance and research evidence: • The Society of Occupational Medicine (SOM): ‘Long COVID and Return to Work – What Works?’ (https://www.som.org.uk/sites/som.org.uk/files/Long_COVID_and_Return_to_Work_What_Works_0.pdf) • The Faculty of Occupational Medicine (FOM): ‘Guidance for healthcare professionals on return to work for patients with post-COVID syndrome’ (https://www.fom.ac.uk/wp-content/uploads/FOM-Guidance-post-COVID_healthcare-professionals.pdf) • Occupational and Environmental Medicine (academic journal of the FOM: https://oem.bmj.com) • Occupational Medicine (academic journal of the SOM: https://academic.oup.com/occmed?login=false) • Industrial Injuries Advisory Council publication: ‘COVID-19 and Occupational Impacts’ (https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1119955/covid-19-and-occupational-impacts.pdf) • NICE: https://cks.nice.org.uk/topics/long-term-effects-of-coronavirus-long-covid • Nature. An example of a recent publication in this journal is Davis, H., McCorkell, L., Vogel, J. M., & Topol, E. J. (2023). Long covid: major findings, mechanisms and recommendations. Nature Reviews Microbiology, 21(3), 133-146. Full text available at https://www.nature.com/articles/s41579-022-00846-2 • British Medical Journal (BMJ) • Journal of the American Medical Association (JAMA) • The Lancet • New England Journal of Medicine In summary, the SMA is expected to adopt an individual approach to each case and use careful clinical judgement when applying the medical research literature and guidance to the specific medical circumstances of a Scheme member with long COVID.

Mid-year (30 June) estimates of the usual resident population for Westminster Parliamentary constituencies in England and Wales.