Dataset

This dataset was created by Dilara Özcerit

Contents

This is a data set from the publication

Hatton, T. J., & Bray, B. E. (2010). Long run trends in the heights of European men, 19th–20th centuries. Economics & Human Biology, 8(3), 405–413. http://doi.org/10.1016/j.ehb.2010.03.001The data set represents average height of the men from several European countries born in the cohorts 1856-1980, 5-years averages.

In the shown time-period the mean height of men and women has generally increased in England. According to the survey, the average height of males rose slightly during the period in consideration, from 174.4 centimeters in 1998 to 176.2 centimeters (approximately 5'9") in 2022. In comparison, the mean height of women was 162.3 centimeters (5'4") in 2022, up from 161 in 1998. Reasons for height increasing While a large part of an adult’s final height is based on genetics, the environment in which a person grows up is also important. Improvements in nutrition, healthcare, and hygiene have seen the average heights increase over the last century, particularly in developed countries. Average height is usually seen as a barometer for the overall health of the population of a country, as the most developed are usually among the ‘tallest’ countries. Average waist circumference also increasing The prevalence of obesity among adults in England has generally been trending upward since 2000. In that year, 21 percent of men and women in England were classified as obese. By 2021, however, this share was 26 percent among women and 25 percent among men. Every adult age group in England had an average BMI which was classified as overweight, apart from those aged 16 to 24, indicating there is a problem with overweightness in England.

Dutch, French, Italian (1818-1940): http://www.nber.org/chapters/c7435.pdf Dutch (1955-2009): http://www.nature.com/pr/journal/v73/n3/pdf/pr2012189a.pdf Swedish (1841-1952): http://pediatrisk-endokrinologi.no/2008/1/Werner_2008_1.pdf Danish and Germans (1856-1980): http://privatewww.essex.ac.uk/~hatton/Tim_height_paper.pdf Americans (1710-1980): http://www.cambridge.org/us/academic/subjects/history/economic-history/changing-body-health-nutrition-and-human-development-western-world-1700 All 2013 heights: http://www.averageheight.co/average-male-height-by-country Means and medians are not too different (rarely more than 1 cm difference) because within-country heights for specific gender are generally normally distributed.

This dataset includes all children (n = 4,310) who were admitted to the North Surrey School District between 1881 and 1895. The record of children includes information about the children’s ages, heights and weights, parents’ occupations and addresses, their training in the school and their work and welfare after leaving the school. The heights and weights of children at discharge from the school were less frequently recorded (n = 173).This project will explore how improvements in nutrition, sanitation, and medical knowledge during Britain's long-run health transition from 1850 onwards influenced children's growth pattern in terms of height, weight and BMI. Studying children's growth pattern (velocity of growth and shape of the growth curve) rather than their height at a specific age is a significant methodological innovation. Adaptive theories of human development and growth stress how exposure to poor nutrition or disease, especially in utero, does not merely affect the child's current height but also the timing of the pubertal growth spurt, their velocity of growth and the length of the growing period: in other words, their growth pattern. This project will extend existing knowledge of children's growth in Britain in three ways: first, by reconstructing boys' longitudinal growth measurements from training ship records spanning the century and a half from 1865 onwards; second, by producing and analysing new growth profiles from historical sources; and third, by placing the change in Britain's growth pattern in international context using growth profiles (the average height and weight of children across a number of ages) collected from 1850 to the present from around the world. Four new datasets will be produced and deposited in the UK Data Archive as a part of the project: three individual-level datasets with the heights and weights of children and a dataset with growth profiles for a wide range of countries around the world from 1850 to the present. The data produced will supply a longer-run perspective on the immediate and intergenerational factors influencing children's growth patterns in Britain and internationally and indicate how the shift from an unhealthy to healthy growth pattern took place. The data will also assemble new evidence on historical BMI growth curves and child obesity rates, providing historical context for the current child obesity crisis. The project's findings are particularly relevant to the current discussion about a post-2015 development framework to replace the Millennium Development Goals and to understanding the childhood obesity crisis and will inform health interventions and development policy goals for improving the health of children in both the developing and developed worlds. The data were transcribed from the record of children kept by the North Surrey School District about the children who lived at the school. A detailed description of the transcription methods and process is provided in the documentation.

Supplementary files for article Maternal height-standardized prevalence of stunting in 67 low- and middle-income countries.Background: Prevalence of stunting is frequently used as a marker of population-level child undernutrition. Parental height varies widely in low- and middle-income countries (LMIC) and is also a major determinant of stunting. While stunting is a useful measure of child health, with multiple causal components, removing the component attributable to parental height may in some cases be helpful to identify shortcoming in current environments.Methods: We estimated maternal height-standardized prevalence of stunting (SPS) in 67 LMICs and parental height-SPS in 20 LMICs and compared with crude prevalence of stunting (CPS) using data on 575,767 children under-five from 67 Demographic and Health Surveys (DHS). We supplemented the DHS with population-level measures of other child health outcomes from the World Health Organization’s (WHO) Global Health Observatory and the United Nations’ Inter-Agency Group for Child Mortality Estimation. Prevalence of stunting was defined as percentage of children with height-for-age falling below −2 z-scores from the median of the 2006 WHO growth standard.Results: The average CPS across countries was 27.8% (95% confidence interval [CI], 27.5–28.1%) and the average SPS was 23.3% (95% CI, 23.0–23.6%). The rank of countries according to SPS differed substantially from the rank according to CPS. Guatemala, Bangladesh, and Nepal had the biggest improvement in ranking according to SPS compared to CPS, while Gambia, Mali, and Senegal had the biggest decline in ranking. Guatemala had the largest difference between CPS and SPS with a CPS of 45.2 (95% CI, 43.7–46.9%) and SPS of 14.1 (95% CI, 12.6–15.8%). Senegal had the largest increase in the prevalence after standardizing maternal height, with a CPS of 28.0% (95% CI, 25.8–30.2%) and SPS of 31.6% (95% CI, 29.5–33.8%). SPS correlated better than CPS with other population-level measures of child health.Conclusions: Our study suggests that CPS is sensitive to adjustment for maternal height. Maternal height, while a strong predictor of child stunting, is not amenable to policy interventions. We showed the plausibility of SPS in capturing current exposures to undernutrition and infections in children.

Data for a Brief Report/Short Communication published in Body Image (2021). Details of the study are included below via the abstract from the manuscript. The dataset includes online experimental data from 167 women who were recruited via social media and institutional participant pools. The experiment was completed in Qualtrics.Women viewed either neutral travel images (control), body positivity posts with an average-sized model (e.g., ~ UK size 14), or body positivity posts with a larger model (e.g., UK size 18+); which images women viewed is show in the ‘condition’ variable in the data.The data includes the age range, height, weight, calculated BMI, and Instagram use of participants. After viewing the images, women responded to the Positive and Negative Affect Schedule (PANAS), a state version of the Body Satisfaction Scale (BSS), and reported their immediate social comparison with the images (SAC items). Women then selected a lunch for themselves from a hypothetical menu; these selections are detailed in the data, as are the total calories calculated from this and the proportion of their picks which were (provided as a percentage, and as a categorical variable [as used in the paper analyses]). Women also reported whether they were on a special diet (e.g., vegan or vegetarian), had food intolerances, when they last ate, and how hungry they were.

Women also completed trait measures of Body Appreciation (BAS-2) and social comparison (PACS-R). Women also were asked to comment on what they thought the experiment was about. Items and computed scales are included within the dataset.This item includes the dataset collected for the manuscript (in SPSS and CSV formats), the variable list for the CSV file (for users working with the CSV datafile; the variable list and details are contained within the .sav file for the SPSS version), and the SPSS syntax for our analyses (.sps). Also included are the information and consent form (collected via Qualtrics) and the questions as completed by participants (both in pdf format).Please note that the survey order in the PDF is not the same as in the datafiles; users should utilise the variable list (either in CSV or SPSS formats) to identify the items in the data.The SPSS syntax can be used to replicate the analyses reported in the Results section of the paper. Annotations within the syntax file guide the user through these.

A copy of SPSS Statistics is needed to open the .sav and .sps files.

Manuscript abstract:

Body Positivity (or ‘BoPo’) social media content may be beneficial for women’s mood and body image, but concerns have been raised that it may reduce motivation for healthy behaviours. This study examines differences in women’s mood, body satisfaction, and hypothetical food choices after viewing BoPo posts (featuring average or larger women) or a neutral travel control. Women (N = 167, 81.8% aged 18-29) were randomly assigned in an online experiment to one of three conditions (BoPo-average, BoPo-larger, or Travel/Control) and viewed three Instagram posts for two minutes, before reporting their mood and body satisfaction, and selecting a meal from a hypothetical menu. Women who viewed the BoPo posts featuring average-size women reported more positive mood than the control group; women who viewed posts featuring larger women did not. There were no effects of condition on negative mood or body satisfaction. Women did not make less healthy food choices than the control in either BoPo condition; women who viewed the BoPo images of larger women showed a stronger association between hunger and calories selected. These findings suggest that concerns over BoPo promoting unhealthy behaviours may be misplaced, but further research is needed regarding women’s responses to different body sizes.

Additional data sets on river water quality in Great Britain collected by the Environment Agency under the Harmonised Monitoring Scheme. This provides information about nutrient and heavy metal loads entering the marine environment and contributes to our commitment to report figures to the OSPAR Convention for the Protection of the North Atlantic. Full details available at: OSPAR - Riverine Inputs and Direct Discharges

The full dataset will be available from the Environment Agency http://www.geostore.com/environment-agency/WebStore?xml=environment-agency/xml/dataLayers.xml" class="govuk-link">datashare site. From November 2013

Release statement - Following a review by Defra and the Environment Agency on reducing the monitoring programme where it is not required under the present regulatory regime, it has been decided that the monitoring under the Harmonised Monitoring Scheme will be discontinued. For further information please contact enviro.statistics Inbox.

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The dataset was collected to analyse changes in the growth pattern of children across the late nineteenth and twentieth century. Importantly for studying child growth, the ship recorded the heights and weights of the boys at admission to and discharge from the ship providing longitudinal measures of growth for a very large number of boys (c. 9,000 records). Longitudinal measures allow us to directly observe children’s growth rather than inferring growth by comparing the differences in height between different children at different ages. This project will explore how improvements in nutrition, sanitation, and medical knowledge during Britain's long-run health transition from 1850 onwards influenced children's growth pattern in terms of height, weight and BMI. Studying children's growth pattern (velocity of growth and shape of the growth curve) rather than their height at a specific age is a significant methodological innovation. Adaptive theories of human development and growth stress how exposure to poor nutrition or disease, especially in utero, does not merely affect the child's current height but also the timing of the pubertal growth spurt, their velocity of growth and the length of the growing period: in other words, their growth pattern. This project will extend existing knowledge of children's growth in Britain in three ways: first, by reconstructing boys' longitudinal growth measurements from training ship records spanning the century and a half from 1865 onwards; second, by producing and analysing new growth profiles from historical sources; and third, by placing the change in Britain's growth pattern in international context using growth profiles (the average height and weight of children across a number of ages) collected from 1850 to the present from around the world. Four new datasets will be produced and deposited in the UK Data Archive as a part of the project: three individual-level datasets with the heights and weights of children and a dataset with growth profiles for a wide range of countries around the world from 1850 to the present. The data produced will supply a longer-run perspective on the immediate and intergenerational factors influencing children's growth patterns in Britain and internationally and indicate how the shift from an unhealthy to healthy growth pattern took place. The data will also assemble new evidence on historical BMI growth curves and child obesity rates, providing historical context for the current child obesity crisis. The project's findings are particularly relevant to the current discussion about a post-2015 development framework to replace the Millennium Development Goals and to understanding the childhood obesity crisis and will inform health interventions and development policy goals for improving the health of children in both the developing and developed worlds. The data were transcribed from the register books kept by the training ship Exmouth about the boys that they trained. There are two files: one contains long-run anthropometric data and the other includes some personal characteristics of a subset of children. Detailed description of the transcription methods and process is provided in the documentation.

Average birth weight and height for sample population percentiles for males and females.

Estimated annual average wave height (metres) created by a Pelamis Wave Model for Accessible Wave Energy Resource Atlas. Wave height values are measured as lower and upper values in metres as calculated by the Pelamis wave model. Annual average wave height covers an area known as the Irish Exclusive Economic Zone (EEZ). Data model produced in 2005. The Pelamis Wave Model was an oceanographic model using the Pelamis wave energy converter device. The Accessible Wave Energy Resource Atlas was produced to provide data and information on the accessible wave energy resource potential around Ireland. Wave model developed by ESB International (ESBI) as part of the Accessible Wave Energy Atlas Ireland published by the Marine Institute and Sustainable Energy Authority Ireland. Model completed for time period run.

This dataset contains vascular plant species abundance, average sward height, and soil analysis data from Parsonage Down National Nature Reserve (NNR), in southern England, in 1970, 1990 and 2016. Vascular plant species abundance and average sward height were recorded for each quadrat located along one of four transects. The transects were located in a CG2 Festuca ovina – Avenula pratensis grassland which dominates the majority of the site. Soil samples were also taken from various points along each transect and subsequently analysed for pH, loss-on-ignition, exchangeable potassium, magnesium, calcium, phosphate and total nitrogen. The dataset was created for a study which examined long-term vegetation change at the nature reserve. Full details about this dataset can be found at https://doi.org/10.5285/ffc06839-e64c-4844-aae7-db3b0a012e2e

This data set describes the Medalpex Sea Level project which took place from September 1, 1981 to September 30, 1982. The main purpose of medalpex was to understand the effect of wind forcing on the dynamics of the western part of the mediterranean sea. Sea level data was submitted to the Marine Information and Advisory Service (MIAS) which is the UK's National Oceanographic Data Centre. There were 29 medalpex sites with contributions from Belgium, France, Monaco, Italy, Spain, Yugoslavia and the UK. The data is available in GF-3 format.

The dataset was collected to analyse changes in the growth pattern of children across the late nineteenth and twentieth century. Importantly for studying child growth, the ship recorded the heights and weights of the boys at admission to and discharge from the ship providing longitudinal measures of growth for a very large number of boys. Longitudinal measures allow us to directly observe children’s growth rather than inferring growth by comparing the differences in height between different children at different ages. There are also a number of individual characteristics available for the boys including birth place, last place of residence, parents’ occupation, orphan status, etc. This project will explore how improvements in nutrition, sanitation, and medical knowledge during Britain's long-run health transition from 1850 onwards influenced children's growth pattern in terms of height, weight and BMI. Studying children's growth pattern (velocity of growth and shape of the growth curve) rather than their height at a specific age is a significant methodological innovation. Adaptive theories of human development and growth stress how exposure to poor nutrition or disease, especially in utero, does not merely affect the child's current height but also the timing of the pubertal growth spurt, their velocity of growth and the length of the growing period: in other words, their growth pattern. This project will extend existing knowledge of children's growth in Britain in three ways: first, by reconstructing boys' longitudinal growth measurements from training ship records spanning the century and a half from 1865 onwards; second, by producing and analysing new growth profiles from historical sources; and third, by placing the change in Britain's growth pattern in international context using growth profiles (the average height and weight of children across a number of ages) collected from 1850 to the present from around the world. Four new datasets will be produced and deposited in the UK Data Archive as a part of the project: three individual-level datasets with the heights and weights of children and a dataset with growth profiles for a wide range of countries around the world from 1850 to the present. The data produced will supply a longer-run perspective on the immediate and intergenerational factors influencing children's growth patterns in Britain and internationally and indicate how the shift from an unhealthy to healthy growth pattern took place. The data will also assemble new evidence on historical BMI growth curves and child obesity rates, providing historical context for the current child obesity crisis. The project's findings are particularly relevant to the current discussion about a post-2015 development framework to replace the Millennium Development Goals and to understanding the childhood obesity crisis and will inform health interventions and development policy goals for improving the health of children in both the developing and developed worlds. The data were transcribed from the register books kept by the training ship Indefatigable about the boys that they trained. The registers have been split into those where no privacy restrictions hold because all individuals are dead, and those where privacy restrictions hold because individuals may still be alive. Detailed description of the transcription methods and process is provided in the documentation.

Estimated annual average wave period (seconds) created by a Pelamis Wave Model for Accessible Wave Energy Resource Atlas. Wave period values are measured as lower and upper values in seconds as calculated by the Pelamis wave model. Annual average wave period covers an area known as the Irish Exclusive Economic Zone (EEZ). Data model produced in 2005. The Pelamis Wave Model was an oceanographic model using the Pelamis wave energy converter device. The Accessible Wave Energy Resource Atlas produced to provide data and information on the accessible wave energy resource potential around Ireland. Wave model developed by ESB International (ESBI) as part of the Accessible Wave Energy Atlas Ireland published by the Marine Institute and Sustainable Energy Authority Ireland. Model completed for time period run.

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