In England, there has been fairly significant increase in the mean weight of the population over the last quarter-century. In 1998, the mean weight was under 81 kilograms for men and around 68 kilograms for women. By 2022, the mean weight of men was 85.8 kilograms and the mean weight of women was 72.8 kilograms.

In 2022, men aged 55 to 64 years had an average body mass index (BMI) of 29 kg/m2 and women in the same age group had a BMI of 28.8 kg/m2, the highest mean BMI across all the age groups. Apart from individuals aged 16 to 24 years, every demographic in England had an average BMI which is classified as overweight.An increasing problem It is shown that the mean BMI of individuals for both men and women has been generally increasing year-on-year in England. The numbers show in England, as in the rest of the United Kingdom (UK), that the prevalence of obesity is an increasing health problem. The prevalence of obesity in women in England has increased by around nine percent since 2000, while for men the share of obesity has increased by six percent. Strain on the health service Being overweight increases the chances of developing serious health problems such as diabetes, heart disease and certain types of cancers. In the period 2019/20, England experienced over 10.7 thousand hospital admissions with a primary diagnosis of obesity, whereas in 2002/03 this figure was only 1,275 admissions. Furthermore, the number of bariatric surgeries taking place in England, particularly among women, has significantly increased over the last fifteen years. In 2019/20, over 5.4 thousand bariatric surgery procedures were performed on women and approximately 1.3 thousand were carried out on men.

This statistic displays the breakdown of body weight class among men and women in the United Kingdom (UK) in 2015. Of respondents, 39 percent of men and 46 percent of women had a healthy body weight.

Abstract copyright UK Data Service and data collection copyright owner.

The National Child Measurement Programme (NCMP) was first established in 2005. It is an annual programme which measures the height and weight of children in Reception and Year 6 within state maintained schools. Some independent and special schools also choose to participate.

The measurement process is overseen by trained healthcare professionals in schools and not shared with school staff or pupils. Data are captured and validated by Primary Care Trusts (PCTs). The Health and Social Care Information Centre (HSCIC) (prior to 1 April 2013 the NHS Information Centre for Health and Social Care (NHS IC)) then collates the data at a national level, conducts further validation and analysis, and publishes an annual report. The National Obesity Observatory (NOO) also publish detailed analysis of the NCMP dataset annually. The validated national NCMP dataset is shared with Public Health Observatories (PHOs) in accordance with the terms of a data sharing agreement. The PCTs also undertake additional analyses at regional and local level to inform the work of the NHS and local authorities on the healthy weight agenda.

The NCMP was set up in line with the Government's strategy to tackle obesity and to:

• inform local planning and delivery of services for children
• gather population-level data to allow analysis of trends in growth patterns and obesity
• increase population and professional understanding of weight issues in children
• be a vehicle for engaging with children and families about healthy lifestyles and weight issues

Further information can be found at the Health and Social Care Information Centre National Child Measurement Programme webpage.


For the second edition (January 2013) a revised version of the database was deposited, with new additional tables included. The documentation has been updated accordingly.

Main Topics:
The database includes information on anthropometric measurements of Reception Year and Year 6 children in schools in England, collected during the school year as part of the NCMP.

The database comprises tables covering BMI classification (every pupil is classified into only one BMI category); Government Office Region codes; a range of NCMP data at Primary Care Trust level; a range of NCMP data at record level; information on primary schools that did and did not participate in the NCMP Programme; a description of the school type codes; a range of NCMP data at SHA level; and information on urban/rural indicators. For a full list of fields, and descriptions within the database please refer to the metadata documentation. The database is a ‘reduced’ version of the full NCMP dataset to ensure that the risk of disclosure is minimal. See documentation for details of omitted fields.

Standard Measures:
Since children’s height and weight are dependent on age and sex, height and weight measurements must be standardised to take these factors into account. The standardised value is a 'z-score' and indicates how far, and in what direction, the measurement deviates from the average (mean) for that age and sex. A formula ('Cole's method') is used to standardise height, weight and BMI (see Cole, T. (1997) 'Growth monitoring with the British 1990 growth reference', Archives of Disease in Childhood, 76(1), pp.47–49). For every measurement, age (in months) and sex, there is a growth curve based on the UK 1990 Growth Reference. This provides the values required by the formula to allow the height, weight and BMI z-score to be calculated. The z-scores are converted to p-scores and allow every child to be assigned to a BMI classification using defined cut-offs. Please see the 'NCMP Guidance for Analysis' in the documentation for further details.

This report presents information on obesity, physical activity and diet drawn together from a variety of sources for England. More information can be found in the source publications which contain a wider range of data and analysis. Each section provides an overview of key findings, as well as providing links to relevant documents and sources. Some of the data have been published previously by NHS Digital. A data visualisation tool (link provided within the key facts) allows users to select obesity related hospital admissions data for any Local Authority (as contained in the data tables), along with time series data from 2013/14. Regional and national comparisons are also provided. The report includes information on: Obesity related hospital admissions, including obesity related bariatric surgery. Obesity prevalence. Physical activity levels. Walking and cycling rates. Prescriptions items for the treatment of obesity. Perception of weight and weight management. Food and drink purchases and expenditure. Fruit and vegetable consumption. Key facts cover the latest year of data available: Hospital admissions: 2018/19 Adult obesity: 2018 Childhood obesity: 2018/19 Adult physical activity: 12 months to November 2019 Children and young people's physical activity: 2018/19 academic year

Observed and age-standardised proportion of adults with a Body Mass Index (BMI) greater than 30 kg/m2. To help reduce the prevalence of obesity. Legacy unique identifier: P00848

SUMMARYIdentifies Middle Layer Super Output Areas (MSOAs) with the greatest levels of excess weight in children (as measured in children in Reception and Year 6 respectively: three year average between academic years 2016/17, 2017/18, 2018/19).Although this layer is symbolised based on an overall score for excess weight, the underlying data, including the raw data for Reception and Year 6 children respectively, is included in the dataset.ANALYSIS METHODOLOGYThe following analysis was carried out using data for Reception and Year 6 children independently:Each MSOA was given a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the NUMBER of children in that year group with excess weight and;B) the PERCENTAGE of children in that year group with excess weight.An average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of children with excess weight, compared to other MSOAs, within that year group. In other words, those are areas where a large number of children have excess weight, and where those children make up a large percentage of the population of that age group, suggesting there is a real issue with childhood obesity in that area that needs addressing.The scores for the Reception and Year 6 analyses were added together then converted to relative scores between 1- 0 (1 = high levels of excess weight in children in both Reception and Year 6, 0 = very low levels of excess weight in either school year). The greater the total score, the greater the levels of excess weight in children within the local population, and the greater the benefits that could be achieved by investing in measures to reduce this issue in those areas.The data overall scores for Reception and Year 6 children, respectively, can be viewed via the following datasets:Excess weight in Reception children, England (three year average: academic years 2016-19)Excess weight in Year 6 children, England (three year average: academic years 2016-19)DATA SOURCESNational Child Measurement Programme: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. MSOA boundaries: © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021.COPYRIGHT NOTICEBased on data: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.; © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021. Data analysed and published by Ribble Rivers Trust © 2021.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

SUMMARYIdentifies Middle Layer Super Output Areas (MSOAs) with the greatest levels of excess weight in Reception age children (three year average between academic years 2016/17, 2017/18, 2018/19).Although this layer is symbolised based on an overall score for excess weight, the underlying data, including the raw data for Reception children, is included in the dataset.ANALYSIS METHODOLOGYEach MSOA was given a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the NUMBER of Reception children with excess weight and;B) the PERCENTAGE of Reception children with excess weight.An average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of Reception children with excess weight, compared to other MSOAs. In other words, those are areas where a large number of children have excess weight, and where those children make up a large percentage of the population of that age group, suggesting there is a real issue with childhood obesity in that area that needs addressing.DATA SOURCESNational Child Measurement Programme: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. MSOA boundaries: © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021.COPYRIGHT NOTICEBased on data: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.; © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021. Data analysed and published by Ribble Rivers Trust © 2021.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

Observed body mass index (BMI) of adults. To help reduce the prevalence of obesity. Legacy unique identifier: P00844

This statistic displays the mean body mass index of adults in Scotland in 2023, by gender and age. In that year, men in the age group 45 to 54 years had a mean BMI of 28.8, while women in the same age group had a mean BMI of 28.6. A BMI between 25 and 30 is classified as overweight.

Proportion of adults with a Body Mass Index (BMI) greater than 25 and under 30 kg/m2. To help reduce the prevalence of obesity. Legacy unique identifier: P00846

Values for anthropometry and lifestyle factors are inferred from the standardized scores (Table 1) that were adjusted for age, PCs in men and women separately). PC, principle component. (XLSX)

SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of obesity, inactivity and inactivity/obesity-related illnesses. Please read the below information to gain a full understanding of what the data shows and how it should be interpreted.The analysis incorporates data relating to the following:Obesity/inactivity-related illnesses (asthma, cancer, chronic kidney disease, coronary heart disease, depression, diabetes mellitus, hypertension, stroke and transient ischaemic attack)Excess weight in children and obesity in adults (combined)Inactivity in children and adults (combined)The analysis was designed with the intention that this dataset could be used to identify locations where investment could encourage greater levels of activity. In particular, it is hoped the dataset will be used to identify locations where the creation or improvement of accessible green/blue spaces and public engagement programmes could encourage greater levels of outdoor activity within the target population, and reduce the health issues associated with obesity and inactivity.ANALYSIS METHODOLOGY1. Obesity/inactivity-related illnessesThe analysis was carried out using Quality and Outcomes Framework (QOF) data, derived from NHS Digital, relating to:- Asthma (in persons of all ages)- Cancer (in persons of all ages)- Chronic kidney disease (in adults aged 18+)- Coronary heart disease (in persons of all ages)- Depression (in adults aged 18+)- Diabetes mellitus (in persons aged 17+)- Hypertension (in persons of all ages)- Stroke and transient ischaemic attack (in persons of all ages)This information was recorded at the GP practice level. However, GP catchment areas are not mutually exclusive: they overlap, with some areas covered by 30+ GP practices. Therefore, to increase the clarity and usability of the data, the GP-level statistics were converted into statistics based on Middle Layer Super Output Area (MSOA) census boundaries.For each of the above illnesses, the percentage of each MSOA’s population with that illness was estimated. This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of patients registered with each GP that have that illness The estimated percentage of each MSOA’s population with each illness was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of people in each MSOA with each illness, within the relevant age range.For each illness, each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have that illnessB) the NUMBER of people within that MSOA who are estimated to have that illnessAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA predicted to have that illness, compared to other MSOAs. In other words, those are areas where a large number of people are predicted to suffer from an illness, and where those people make up a large percentage of the population, indicating there is a real issue with that illness within the population and the investment of resources to address that issue could have the greatest benefits.The scores for each of the 8 illnesses were added together then converted to a relative score between 1 – 0 (1 = worst, 0 = best), to give an overall score for each MSOA: a score close to 1 would indicate that an area has high predicted levels of all obesity/inactivity-related illnesses, and these are areas where the local population could benefit the most from interventions to address those illnesses. A score close to 0 would indicate very low predicted levels of obesity/inactivity-related illnesses and therefore interventions might not be required.2. Excess weight in children and obesity in adults (combined)For each MSOA, the number and percentage of children in Reception and Year 6 with excess weight was combined with population data (up to age 17) to estimate the total number of children with excess weight.The first part of the analysis detailed in section 1 was used to estimate the number of adults with obesity in each MSOA, based on GP-level statistics.The percentage of each MSOA’s adult population (aged 18+) with obesity was estimated, using GP-level data (see section 1 above). This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of adult patients registered with each GP that are obeseThe estimated percentage of each MSOA’s adult population with obesity was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of adults in each MSOA with obesity.The estimated number of children with excess weight and adults with obesity were combined with population data, to give the total number and percentage of the population with excess weight.Each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have excess weight/obesityB) the NUMBER of people within that MSOA who are estimated to have excess weight/obesityAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA predicted to have excess weight/obesity, compared to other MSOAs. In other words, those are areas where a large number of people are predicted to suffer from excess weight/obesity, and where those people make up a large percentage of the population, indicating there is a real issue with that excess weight/obesity within the population and the investment of resources to address that issue could have the greatest benefits.3. Inactivity in children and adultsFor each administrative district, the number of children and adults who are inactive was combined with population data to estimate the total number and percentage of the population that are inactive.Each district was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that district who are estimated to be inactiveB) the NUMBER of people within that district who are estimated to be inactiveAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the district predicted to be inactive, compared to other districts. In other words, those are areas where a large number of people are predicted to be inactive, and where those people make up a large percentage of the population, indicating there is a real issue with that inactivity within the population and the investment of resources to address that issue could have the greatest benefits.Summary datasetAn average of the scores calculated in sections 1-3 was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer the score to 1, the greater the number and percentage of people suffering from obesity, inactivity and associated illnesses. I.e. these are areas where there are a large number of people (both children and adults) who are obese, inactive and suffer from obesity/inactivity-related illnesses, and where those people make up a large percentage of the local population. These are the locations where interventions could have the greatest health and wellbeing benefits for the local population.LIMITATIONS1. For data recorded at the GP practice level, data for the financial year 1st April 2018 – 31st March 2019 was used in preference to data for the financial year 1st April 2019 – 31st March 2020, as the onset of the COVID19 pandemic during the latter year could have affected the reporting of medical statistics by GPs. However, for 53 GPs (out of 7670) that did not submit data in 2018/19, data from 2019/20 was used instead. Note also that some GPs (997 out of 7670) did not submit data in either year. This dataset should be viewed in conjunction with the ‘Levels of obesity, inactivity and associated illnesses: Summary (England). Areas with data missing’ dataset, to determine areas where data from 2019/20 was used, where one or more GPs did not submit data in either year, or where there were large discrepancies between the 2018/19 and 2019/20 data (differences in statistics that were > mean +/- 1 St.Dev.), which suggests erroneous data in one of those years (it was not feasible for this study to investigate this further), and thus where data should be interpreted with caution. Note also that there are some rural areas (with little or no population) that do not officially fall into any GP catchment area (although this will not affect the results of this analysis if there are no people living in those areas).2. Although all of the obesity/inactivity-related illnesses listed can be caused or exacerbated by inactivity and obesity, it was not possible to distinguish from the data the cause of the illnesses in patients: obesity and inactivity are highly unlikely to be the cause of all cases of each illness. By combining the data with data relating to levels of obesity and inactivity in adults and children, we can identify where obesity/inactivity could be a contributing factor, and where interventions to reduce obesity and increase activity could be most beneficial for the health of the local population.3. It was not feasible to incorporate ultra-fine-scale geographic distribution of

Article abstractBackground: There is extensive evidence that rapid infant weight gain increases the risk of childhood obesity, but this is normally based on childhood body mass index (BMI) only and whether or not this is because infants with rapid weight gain accrue greater fat mass is unknown.Objective: The primary objective of our study was to test whether the proportion of infant weight gain due to concurrent increases in fat mass is greater in infants with rapid weight gain as compared to those with normal growth.Methods: Body composition was assessed by 1) air-displacement plethysmography (ADP) at 0 & 6 months in 342 infants from Australia, India, and South Africa and 2) deuterium dilution (DD) at 3 & 24 months in 555 infants from Brazil, Pakistan, South Africa, and Sri Lanka. Weight gain and length growth were each categorized as slow, normal, or rapid using cut-offs of < -0.67 or >+0.67 Z-scores. Regression was used to estimate and contrast the percentages of weight change due to fat mass change.Results: Approximately 40% of the average weight gain between 0-6 months and 20% of the average weight gain between 3-24 months was due to increase in fat mass. In both samples, compared to the normal group, the proportion of weight gain due to fat mass was higher on average among infants with rapid weight gain and lower among infants with slow weight gain, with considerable individual variability. Conversely, slow and rapid length growth was not associated with differential gains in fat mass.Conclusions: Pediatricians should monitor infant growth with the understanding that, while crossing upward through the weight centiles generally is accompanied by greater adiposity gains (not just higher BMI), upward crossing through the length centiles is not.

This statistic shows the results of a global survey that took place in October 2021 regarding cross-border e-commerce shopping around the world. During the survey, around 29 percent of respondents stated their cross-border deliveries weighed somewhere between 0.2 kg to 0.5 kg.

This statistic shows the average carcass weight of slaughtered sows and boars in the United Kingdom from 2003 to 2021. In 2021, the average carcass weight of slaughtered sows and boars increased with respect to last year's value to 140.8 kilograms per head, a weight similar the the 2019 average. Additionally, the total amount of annually slaughtered sows and boars in the United Kingdom can be found at the following.

In 2021, the average carcass weight of slaughtered clean pigs in the United Kingdom was 88.6 kilograms per head. The average weight of slaughtered clean pigs has grown by 14.5 kilograms per head since 2003. Approximately 11.1 million clean pigs were slaughtered in 2021.

Terminology

The term ‘clean pigs’ describes animals that are young or castrated, as opposed to mature boars or sows used for breeding and that are slaughtered at the end of their production lives. Carcass weight refers to the weight of the body of the animal after various body parts are removed following the animal’s slaughter.

Pork retail

UK consumers bought almost 162 thousand tons of fresh and frozen pork in the year ending in June 2021. Compared to a year earlier consumption dropped by roughly 2000 tons. Average purchases per consumer mirror this decrease and reveal a long-term downward trend.

This statistic displays the body mass index (BMI) distribution of pregnant women in England in 2018/19, by age group. In this period, 47.5 percent of pregnant women aged 30 to 39 years were classed as normal weight.

In 2021, the average weight of slaughtered sheep and lamb carcasses per head was 20 kilograms, a weight that has remained somewhat stable over a number of years. However, if we look at more historical data, we can see a very slow long-term increase. The last time carcass weight was below 18 kilograms was in December of 2000.

Carcass weight

Carcass weight is the weight of an animal after it was partially butchered. For sheep the skin is usually removed as well as other inedible or undesirable parts, which include the internal organs, tails, legs, and often the head. Bones and cartilage are included in the weight. The weight varies from animal to animal and the average is used for industrial calculations.

Sheep and lambs

The UK had a population of approximately 22.5 million sheep and lambs on agricultural holdings in 2018. During the same year 12.8 million animals were slaughtered, which increased slightly in 2017. Sheep are more commonly subjected to Halal slaughtering methods than other animals and not stunned when slaughtered in 25 percent of all cases. Approximately 750 thousand sheep slaughtered without prior stunning are then exported outside the UK.

More than 485,900 heavy goods vehicles (HGV) registered in Great Britain in 2020. Almost a quarter of this number were registrations of vehicles over 41 metric tons, which has been the leading weight class for HGV since 2014. It was followed by registration for vehicles between eight and 18 metric tons, which made up around 20 percent of registrations in 2020.