1,757,625 research outputs found
A century of trends in adult human height
No full textBeing taller is associated with enhanced longevity, and higher education and earnings. We reanalysed 1472 population-based studies, with measurement of height on more than 18.6 million participants to estimate mean height for people born between 1896 and 1996 in 200 countries. The largest gain in adult height over the past century has occurred in South Korean women and Iranian men, who became 20.2 cm (95% credible interval 17.5–22.7) and 16.5 cm (13.3–19.7) taller, respectively. In contrast, there was little change in adult height in some sub-Saharan African countries and in South Asia over the century of analysis. The tallest people over these 100 years are men born in the Netherlands in the last quarter of 20th century, whose average heights surpassed 182.5 cm, and the shortest were women born in Guatemala in 1896 (140.3 cm; 135.8–144.8). The height differential between the tallest and shortest populations was 19-20 cm a century ago, and has remained the same for women and increased for men a century later despite substantial changes in the ranking of countries.peer-reviewe
Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure : a pooled analysis of 1018 population-based measurement studies with 88.6 million participants
No full textBACKGROUND: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure.METHODS: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20–29 years to 70–79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probit-transformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure.RESULTS: In 2005–16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the high-income Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association.CONCLUSIONS: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups.This work was supported by the Wellcome Trust [101506/Z/13/Z].peer-reviewe
Repositioning of the global epicentre of non-optimal cholesterol
No full textHigh blood cholesterol is typically considered a feature of wealthy western countries. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends ofHDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular risk-changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.This study was funded by a Wellcome Trust (Biomedical Resource &
Multi-User Equipment grant 01506/Z/13/Z) and the British Heart Foundation (Centre of
Research Excellence grant RE/18/4/34215). C.T. was supported by a Wellcome Trust Research
Training Fellowship (203616/Z/16/Z).peer-reviewe
Diminishing benefits of urban living for children and adolescents' growth and development
No full textNCD Risk Factor Collaboration (NCD-RisC) Code and Data Sharing
This repository contains code and data for generating estimates of mean height and mean body-mass index (BMI) of children and adolescents aged 5 to 19 years living in rural and urban areas in 200 countries and territories from 1990 to 2020, as reported in the publication "Diminishing benefits of urban living for children and adolescents’ growth and development" [1].
Contents Guide
data/ The list of data sources used in the study, together with input data used in the model from publicly available sources and contact information for other data sources.
model/ R code for the Bayesian hierarchical model used to analyse the data to estimate mean height and mean BMI by country, year, age and rural and urban place of residence. See methods section of publication [1] for details of the statistical methods.
figures/ R code to produce figures as appeared in publication [1].
utils/ Essential covariate files; functions for producing figures.
Contact
For more information about the paper or the NCD Risk Factor Collaboration, please see www.ncdrisc.org or contact [email protected].
Codes for producing publication figures are provided for transparency and in the spirit of scientific collaboration. We will not be able to answer questions about the details of these codes.
Acknowledgements
The shape file of the maps was based on Natural Earth [2].
Population data used in this analysis were obtained from the 2019 revision to the United Nations' World Population Prospects [3].
Data on percent national population living in urbanisation areas were obtained from the 2018 revision to the United Nations' World Urbanization Prospects [4].
References
NCD Risk Factor Collaboration (NCD-RisC). Diminishing benefits of urban living for children and adolescents’ growth and development. Nature, 2023.
https://www.naturalearthdata.com/
United Nations, Department of Economic and Social Affairs, Population Division (2019). World Population Prospects 2019: Highlights (ST/ESA/SER.A/423)
United Nations, Department of Economic and Social Affairs, Population Division (2018). World Urbanization Prospects: The 2018 Revision, Online Editio
Global variation in diabetes diagnosis and prevalence based on fasting glucose and haemoglobin A1c
No full textNCD Risk Factor Collaboration (NCD-RisC) Code and Data Sharing
This repository will contain code and data used in the paper "Global variation in diabetes diagnosis and prevalence based on fasting glucose and haemoglobin A1c" [1].
Contents Guide
NCD_RisC_Nature_Medicine_2023_input_data.xlsx The list of data sources used in the study, together with contact information for data access.
multi-bugs-logbin-model.odc BUGS model code for log-binomial regressions to examine what individual and study level factors were associated with whether participants with screen-detected diabetes were identified by elevated FPG, elevated HbA1c or elevated levels of both. See methods section of the publication [1] for details.
Contact
For more information about the paper or the NCD Risk Factor Collaboration, please see www.ncdrisc.org or contact [email protected].
Reference
NCD Risk Factor Collaboration (NCD-RisC). Global variation in diabetes diagnosis and prevalence based on fasting glucose and haemoglobin A1c. Nature Medicine. 2023.The research was additionally funded by UKRI Research England Policy Support and US Centers for Disease Control and Prevention
Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults
No full textBackground Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health
consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI)
and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to
compare trends with those of adults.
Methods We pooled 2416 population-based studies with measurements of height and weight on 128·9 million
participants aged 5 years and older, including 31·5 million aged 5–19 years. We used a Bayesian hierarchical model to
estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories
for children and adolescents aged 5–19 years: more than 2 SD below the median of the WHO growth reference for
children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below
the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to
2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity).
Findings Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change
(–0·01 kg/m2 per decade; 95% credible interval –0·42 to 0·39, posterior probability [PP] of the observed decrease being
a true decrease=0·5098) in eastern Europe to an increase of 1·00 kg/m2 per decade (0·69–1·35, PP>0·9999) in central
Latin America and an increase of 0·95 kg/m2 per decade (0·64–1·25, PP>0·9999) in Polynesia and Micronesia. The
range for boys was from a non-significant increase of 0·09 kg/m2 per decade (–0·33 to 0·49, PP=0·6926) in eastern
Europe to an increase of 0·77 kg/m2 per decade (0·50–1·06, PP>0·9999) in Polynesia and Micronesia. Trends in mean
BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions
for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls. By contrast, the rise in
BMI has accelerated in east and south Asia for both sexes, and southeast Asia for boys. Global age-standardised
prevalence of obesity increased from 0·7% (0·4–1·2) in 1975 to 5·6% (4·8–6·5) in 2016 in girls, and from 0·9%
(0·5–1·3) in 1975 to 7·8% (6·7–9·1) in 2016 in boys; the prevalence of moderate and severe underweight decreased
from 9·2% (6·0–12·9) in 1975 to 8·4% (6·8–10·1) in 2016 in girls and from 14·8% (10·4–19·5) in 1975 to 12·4%
(10·3–14·5) in 2016 in boys. Prevalence of moderate and severe underweight was highest in India, at 22·7% (16·7–29·6)
among girls and 30·7% (23·5–38·0) among boys. Prevalence of obesity was more than 30% in girls in Nauru, the Cook
Islands, and Palau; and boys in the Cook Islands, Nauru, Palau, Niue, and American Samoa in 2016. Prevalence of
obesity was about 20% or more in several countries in Polynesia and Micronesia, the Middle East and north Africa, the
Caribbean, and the USA. In 2016, 75 (44–117) million girls and 117 (70–178) million boys worldwide were moderately
or severely underweight. In the same year, 50 (24–89) million girls and 74 (39–125) million boys worldwide were obese
Repositioning of the global epicentre of non-optimal cholesterol
No full textBin Zhou
Imperial College London, London, UK/NCD Risk Factor Collaboration
Honor Bixby
Imperial College London, London, UK/NCD Risk Factor Collaboration
Rodrigo M. Carrillo-Larco
Imperial College London, London, UK/NCD Risk Factor Collaboration
Marisa K. Sophiea
Imperial College London, London, UK/NCD Risk Factor Collaboration
Maria Laura Caminia Iurilli
Imperial College London, London, UK/NCD Risk Factor Collaboration
Andrea Rodriguez Martinez
Imperial College London, London, UK/NCD Risk Factor Collaboration
James E. Bennett
Imperial College London, London, UK/NCD Risk Factor Collaboration
Gretchen A. Stevens
Imperial College London, London, UK/Independent researcher, Los Angeles, CA, USA/NCD Risk Factor Collaboration
Abbas Dehghan
Imperial College London, London, UK/NCD Risk Factor Collaboration
Ilpo Tapani Huhtaniemi
Imperial College London, London, UK/NCD Risk Factor Collaboration
Marjo-Riitta Jarvelin
Imperial College London, London, UK/University of Oulu, Oulu, Finland
Edward W. Gregg
Imperial College London, London, UK/NCD Risk Factor Collaboration
Majid Ezzati
Imperial College London, London, UK/NCD Risk Factor Collaboration
Goodarz Danaei
Harvard T. H. Chan School of Public Health, Boston, MA, USA
Yanping Li
Harvard T. H. Chan School of Public Health, Boston, MA, USA/NCD Risk Factor Collaboration
Rod T. Jackson
University of Auckland, Auckland, New Zealand/NCD Risk Factor Collaboration/NCD Risk Factor Collaboration
Robert Beaglehole
University of Auckland, Auckland, New Zealand
Patricia Metcalf
University of Auckland, Auckland, New Zealand/NCD Risk Factor Collaboration/NCD Risk Factor Collaboration
Farshad Farzadfar
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Naser Ahmadi
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Mehrdad Azmin, Sareh Eghtesad
Tehran University of Medical Sciences, Tehran, Iran
Ali Ghanbari, Erfan Ghasemi
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Rosa Haghshenas
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Reza Malekzadeh
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Parinaz Mehdipour
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Shahin Merat
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Sahar Saeedi Moghaddam
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Bahram Mohajer
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Kazem Mohammad
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Zahra Mohammadi
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Farnam Mohebi
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Shohreh Naderimagham
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Afshin Ostovar
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Hossein Poustchi
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Alireza Sadjadi
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Sadaf G. Sepanlou
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Ramin Shakeri
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Maryam Sharafkhah
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Amaneh Shayanrad
Tehran University of Medical Sciences, Tehran, Iran
Moein Yoosefi
Tehran University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Mariachiara Di Cesare
Middlesex University, London, UK/NCD Risk Factor Collaboration
Golaleh Asghari
Shahid Beheshti University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Davood Khalili
Shahid Beheshti University of Medical Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Amirabbas Momenan
Shahid Beheshti University of Medical Sciences, Tehran, Iran
Mohammad Reza Zali
Shahid Beheshti University of Medical Sciences, Tehran, Iran
Klodian Dhana
Rush University Medical Center, Chicago, IL, USA/NCD Risk Factor Collaboration
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina
Pablo Gulayin
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina/NCD Risk Factor Collaboration
Marilina Santero
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina/NCD Risk Factor Collaboration
Laura Gutierrez
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina/NCD Risk Factor Collaboration
Vilma E. Irazola
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina/NCD Risk Factor Collaboration
Adolfo Rubinstein
Institute for Clinical Effectiveness and Health Policy, Buenos Aires, Argentina/NCD Risk Factor Collaboration
Sujay Kakarmath
Harvard Medical School, Boston, MA, USA/NCD Risk Factor Collaboration
Trudy Voortman
Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands/NCD Risk Factor Collaboration
Oscar H. Franco
Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands/NCD Risk Factor Collaboration
Albert Hofman
Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands/NCD Risk Factor Collaboration
M. Arfan Ikram
Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands/NCD Risk Factor Collaboration
Maryam Kavousi
Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
Marileen L. P. Portegies
Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands/NCD Risk Factor Collaboration
Leanne M. Riley
World Health Organization, Geneva, Switzerland/NCD Risk Factor Collaboration
Melanie J. Cowan
World Health Organization, Geneva, Switzerland/NCD Risk Factor Collaboration
Stefan Savin
World Health Organization, Geneva, Switzerland/NCD Risk Factor Collaboration
Mohamed M. Ali
World Health Organization, Geneva, Switzerland/NCD Risk Factor Collaboration
Gretchen A. Stevens
Independent researcher, Los Angeles, CA, USA/NCD Risk Factor Collaboration
Christopher J. Paciorek
University of California Berkeley, Berkeley, CA, USA/NCD Risk Factor Collaboration
Wichai Aekplakorn
Mahidol University, Nakhon Pathom, Thailand
Paibul Suriyawongpaisal
Mahidol University, Nakhon Pathom, Thailand/NCD Risk Factor Collaboration
Renata Cifkova
Charles University in Prague, Prague, Czech Republic/Thomayer Hospital, Prague, Czech Republic/NCD Risk Factor Collaboration
Simona Giampaoli
Istituto Superiore di Sanità, Rome, Italy/NCD Risk Factor Collaboration
Chiara Donfrancesco
Istituto Superiore di Sanità, Rome, Italy
Luigi Palmieri
Istituto Superiore di Sanità, Rome, Italy/NCD Risk Factor Collaboration
Andre Pascal Kengne
South African Medical Research Council, Cape Town, South Africa/NCD Risk Factor Collaboration
Young-Ho Khang
Seoul National University, Seoul, Republic of Korea/NCD Risk Factor Collaboration
Kari Kuulasmaa
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Anne Juolevi
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Eero O. Kajantie
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Seppo Koskinen
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Tiina Laatikainen
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Annamari Lundqvist
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Teemu J. Niiranen
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Markku Peltonen
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Veikko Salomaa
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Hanna K. Tolonen
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Jaakko Tuomilehto
Finnish Institute for Health and Welfare, Helsinki, Finland/NCD Risk Factor Collaboration
Avula Laxmaiah
ICMR–National Institute of Nutrition, Hyderabad, India/NCD Risk Factor Collaboration
Nimmathota Arlappa
ICMR–National Institute of Nutrition, Hyderabad, India/NCD Risk Factor Collaboration
Nagalla Balakrishna
ICMR–National Institute of Nutrition, Hyderabad, India/NCD Risk Factor Collaboration
Rachakulla Hari Kumar
ICMR–National Institute of Nutrition, Hyderabad, India/NCD Risk Factor Collaboration
Kodavanti Mallikharjuna Rao
ICMR–National Institute of Nutrition, Hyderabad, India
Indrapal I. Meshram
ICMR–National Institute of Nutrition, Hyderabad, India/NCD Risk Factor Collaboration
Paula Margozzini
Pontificia Universidad Católica de Chile, Santiago, Chile/NCD Risk Factor Collaboration
Catterina Ferreccio
Pontificia Universidad Católica de Chile, Santiago, Chile/NCD Risk Factor Collaboration
Juan Francisco Miquel
Pontificia Universidad Católica de Chile, Santiago, Chile/NCD Risk Factor Collaboration
Flavio Nervi
Pontificia Universidad Católica de Chile, Santiago, Chile
Gonzalo Valdivia
Pontificia Universidad Católica de Chile, Santiago, Chile/NCD Risk Factor Collaboration
Prashant Mathur
ICMR–National Centre for Disease Informatics and Research, Bengaluru, India/NCD Risk Factor Collaboration
Børge G. Nordestgaard
Copenhagen University Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Marianne Benn
Copenhagen University Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Gorm B. Jensen
Copenhagen University Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Pia R. Kamstrup
Copenhagen University Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Anne Tybjaerg-Hansen
Copenhagen University Hospital, Copenhagen, Denmark
Anette Varbo
Copenhagen University Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Dong Zhao
Capital Medical University Beijing An Zhen Hospital, Beijing, China
Jing Liu
Capital Medical University Beijing An Zhen Hospital, Beijing, China
Mette Aadahl
Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Thomas M. Dantoft
Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Marie Eliasen
Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Torben Jørgensen
Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Allan Linneberg
Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Line T. Møllehave, Betina H. Thuesen
Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
Ulla Toft
Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark/NCD Risk Factor Collaboration
Leandra Abarca-Gómez
Caja Costarricense de Seguro Social, San José, Costa Rica
Roy A. Wong-McClure
Caja Costarricense de Seguro Social, San José, Costa Rica/NCD Risk Factor Collaboration
Hanan Abdul Rahim
Qatar University, Doha, Qatar
Zumin Shi
Qatar University, Doha, Qatar/NCD Risk Factor Collaboration
Niveen M. Abu-Rmeileh
Birzeit University, Birzeit, Palestine
Abdullatif S. Husseini
Birzeit University, Birzeit, Palestine
Benjamin Acosta-Cazares
Instituto Mexicano del Seguro Social, Mexico City, Mexico
Jorge Escobedo-de la Peña
Instituto Mexicano del Seguro Social, Mexico City, Mexico
Blanca Sandra Ruiz-Betancourt
Instituto Mexicano del Seguro Social, Mexico City, Mexico/NCD Risk Factor Collaboration
Robert J. Adams
Flinders University, Adelaide, South Australia, Australia/NCD Risk Factor Collaboration
Imelda A. Agdeppa
Food and Nutrition Research Institute, Taguig, The Philippines
Mario V. Capanzana
Food and Nutrition Research Institute, Taguig, The Philippines
Charmaine A. Duante
Food and Nutrition Research Institute, Taguig, The Philippines
Glen Gironella
Food and Nutrition Research Institute, Taguig, The Philippines/NCD Risk Factor Collaboration
Javad Aghazadeh-Attari
Urmia University of Medical Sciences, Urmia, Iran/NCD Risk Factor Collaboration
Iraj Mohebbi
Urmia University of Medical Sciences, Urmia, Iran/NCD Risk Factor Collaboration
Carlos A. Aguilar-Salinas
Instituto Nacional de Ciencias Médicas y Nutricion, Mexico City, Mexico/NCD Risk Factor Collaboration
Charles Agyemang
University of Amsterdam, Amsterdam, The Netherlands/NCD Risk Factor Collaboration
Lizzy M. Brewster
University of Amsterdam, Amsterdam, The Netherlands/NCD Risk Factor Collaboration
Marieke B. Snijder
University of Amsterdam, Amsterdam, The Netherlands/NCD Risk Factor Collaboration
Karien Stronks
University of Amsterdam, Amsterdam, The Netherlands/NCD Risk Factor Collaboration
Irene G. M. van Valkengoed
University of Amsterdam, Amsterdam, The Netherlands/NCD Risk Factor Collaboration
Tarunveer S. Ahluwalia
Steno Diabetes Center Copenhagen, Gentofte, Denmark/NCD Risk Factor Collaboration
Noor Ani Ahmad
Ministry of Health Malaysia, Kuala Lumpur, Malaysia/NCD Risk Factor Collaboration
Tahir Aris
Ministry of Health Malaysia, Kuala Lumpur, Malaysia/NCD Risk Factor Collaboration
Norazizah Ibrahim Wong
Ministry of Health Malaysia, Kuala Lumpur, Malaysia/NCD Risk Factor Collaboration
Muhammad Fadhli Mohd Yusoff
Ministry of Health Malaysia, Kuala Lumpur, Malaysia/NCD Risk Factor Collaboration
Balkish M. Naidu
Ministry of Health Malaysia, Kuala Lumpur, Malaysia/NCD Risk Factor Collaboration
Mohd Azahadi Omar
Ministry of Health Malaysia, Kuala Lumpur, Malaysia/NCD Risk Factor Collaboration
Ahmad Faudzi Yusoff
Ministry of Health Malaysia, Kuala Lumpur, Malaysia
Ahmad A. Zainuddin
Ministry of Health Malaysia, Kuala Lumpur, Malaysia/NCD Risk Factor Collaboration
Ali Ahmadi
Shahrekord University of Medical Sciences, Shahrekord, Iran
Majid Shirani
Shahrekord University of Medical Sciences, Shahrekord, Iran/NCD Risk Factor Collaboration
Soheir H. Ahmed
University of Oslo, Oslo, Norway/NCD Risk Factor Collaboration
Espen Bjertness
University of Oslo, Oslo, Norway/NCD Risk Factor Collaboration
Marius B. Bjertness
University of Oslo, Oslo, Norway/NCD Risk Factor Collaboration
Ahmed A. Madar
University of Oslo, Oslo, Norway
Haakon E. Meyer
University of Oslo, Oslo, Norway
Wolfgang Ahrens
University of Bremen, Bremen, Germany/NCD Risk Factor Collaboration
Kamel Ajlouni &
National Center for Diabetes, Endocrinology and Genetics, Amman, Jordan
Mohammad Khateeb
National Center for Diabetes, Endocrinology and Genetics, Amman, Jordan
Monira Alarouj
Dasman Diabetes Institute, Kuwait City, Kuwait
Abdullah Alkandari
Dasman Diabetes Institute, Kuwait City, Kuwait
Fadia AlBuhairan
Aldara Hospital and Medical Center, Riyadh, Saudi Arabia/NCD Risk Factor Collaboration
Shahla AlDhukair
King Abdullah International Medical Research Center, Riyadh, Saudi Arabia/NCD Risk Factor Collaboration
Ala’a Alkerwi
Luxembourg Institute of Health, Strassen, Luxembourg NCD Risk Factor Collaboration
Eman Aly
World Health Organization Regional Office for the Eastern Mediterranean, Cairo, Egypt NCD Risk Factor Collaboration
Heba M. Fouad
World Health Organization Regional Office for the Eastern Mediterranean, Cairo, Egypt NCD Risk Factor Collaboration
Deepak N. Amarapurkar
Bombay Hospital and Medical Research Centre, Mumbai, India NCD Risk Factor Collaboration
Philippe Amouyel
University of Lille, Lille, France NCD Risk Factor Collaboration
Luc Dauchet
University of Lille, Lille, France/ Lille University Hospital, Lille, France
Jonathan Giovannelli
University of Lille, Lille, France/ Lille University Hospital, Lille, France
Frederic Gottrand
University of Lille, Lille, France NCD Risk Factor Collaboration
Philippe Amouyel
Lille University Hospital, Lille, France
Lars Bo Andersen
Western Norway University of Applied Sciences, Sogndal, Norway NCD Risk Factor Collaboration
Sigmund A. Anderssen
Norwegian School of Sport Sciences, Oslo, Norway NCD Risk Factor Collaboration
Ulf Ekelund
Norwegian School of Sport Sciences, Oslo, Norway NCD Risk Factor Collaboration
Elin Kolle
Norwegian School of Sport Sciences, Oslo, Norway
Jostein Steene-Johannessen
Norwegian School of Sport Sciences, Oslo, Norway NCD Risk Factor Collaboration
Ranjit Mohan Anjana
Madras Diabetes Research Foundation, Chennai, India
Mohan Deepa
Madras Diabetes Research Foundation, Chennai, India
Viswanathan Mohan
Madras Diabetes Research Foundation, Chennai, India
Rajendra Pradeepa
Madras Diabetes Research Foundation, Chennai, India NCD Risk Factor Collaboration
Alireza Ansari-Moghaddam
Zahedan University of Medical Sciences, Zahedan, Iran
Seyed Mohammad Hashemi-Shahri
Zahedan University of Medical Sciences, Zahedan, Iran NCD Risk Factor Collaboration
Hajer Aounallah-Skhiri
National Institute of Public Health, Tunis, Tunisia
Nada Zoghlami
National Institute of Public Health, Tunis, Tunisia
Joana Araújo
Institute of Public Health of the University of Porto, Porto, Portugal
Ana Henriques
Institute of Public Health of the University of Porto, Porto, Portugal/NCD Risk Factor Collaboration
Inger Ariansen
Norwegian Institute of Public Health, Oslo, Norway
Sidsel Graff-Iversen
Norwegian Institute of Public Health, Oslo, Norway
Raphael E. Arku
University of Massachusetts, Amherst, MA, USA/NCD Risk Factor Collaboration
Krishna K. Aryal
Abt Associates, Kathmandu, Nepal/NCD Risk Factor Collaboration
Thor Aspelund
University of Iceland, Reykjavik, Iceland
Vilmundur Gudnason
University of Iceland, Reykjavik, Iceland/NCD Risk Factor Collaboration
Maria Cecília F. Assunção
Federal University of Pelotas, Pelotas, Brazil
Paula Duarte de Oliveira
Federal University of Pelotas, Pelotas, Brazil
Helen Gonçalves
Federal University of Pelotas, Pelotas, Brazil
Bernardo L. Horta
Federal University of Pelotas, Pelotas, Brazil
Ana Maria B. Menezes
Federal University of Pelotas, Pelotas, Brazil
Isabel O. Oliveira
Federal University of Pelotas, Pelotas, Brazil
Cesar G. Victora
Federal University of Pelotas, Pelotas, Brazil/NCD Risk Factor Collaboration
Juha Auvinen
University of Oulu, Oulu, Finland
Marjo-Riitta Jarvelin
University of Oulu, Oulu, Finland
Raija Korpelainen
University of Oulu, Oulu, Finland/Oulu Deaconess Institute Foundation, Oulu, Finland
Soile E. Puhakka
University of Oulu, Oulu, Finland/ Oulu Deaconess Institute Foundation, Oulu, Finland
Sylvain Sebert
University of Oulu, Oulu, Finland/NCD Risk Factor Collaboration
Juha Auvinen
Oulu University Hospital, Oulu, Finland/Oulu University Hospital, Oulu, Finland
Sauli Herrala
Oulu University Hospital, Oulu, Finland/NCD Risk Factor Collaboration
Marjo-Riitta Jarvelin
Oulu University Hospital, Oulu, Finland/NCD Risk Factor Collaboration
Jari J. Jokelainen
Oulu University Hospital, Oulu, Finland
Sirkka Keinänen-Kiukaanniemi
Oulu University Hospital, Oulu, Finland/NCD Risk Factor Collaboration
Mária Avdicová
Regional Authority of Public Health, Banska Bystrica, Slovakia
Jana Námešná
Regional Authority of Public Health, Banska Bystrica, Slovakia/NCD Risk Factor Collaboration
Ana Azevedo
University of Porto Medical School, Porto, Portugal/NCD Risk Factor Collaboration
Elisabete Ramos
University of Porto Medical School, Porto, Portugal/NCD Risk Factor Collaboration
Fereidoun Azizi
Research Institute for Endocrine Sciences, Tehran, Iran/NCD Risk Factor Collaboration
Mohamed Bamoshmoosh
University of Science and Technology, Sana’a, Yemen/NCD Risk Factor Collaboration
Medical University of Lodz, Lodz, Poland
Maciej Banach
Medical University of Lodz, Lodz, Poland/NCD Risk Factor Collaboration
Wojciech Drygas
Medical University of Lodz, Lodz, Poland/National Institute of Cardiology, Warsaw, Poland/NCD Risk Factor Collaboration
Elzbieta Dziankowska-Zaborszczyk
Medical University of Lodz, Lodz, Poland/NCD Risk Factor Collaboration
Jolanta Slowikowska-Hilczer
Medical University of Lodz, Lodz, Poland/NCD Risk Factor Collaboration
Piotr Bandosz
Medical University of Gdansk, Gdansk, Poland/NCD Risk Factor Collaboration
Marcin Rutkowski
Medical University of Gdansk, Gdansk, Poland
Tomasz Zdrojewski
Medical University of Gdansk, Gdansk, Poland
José R. Banegas
Universidad Autónoma de Madrid/CIBERESP, Madrid, Spain/NCD Risk Factor Collaboration
Pilar Guallar-Castillón
Universidad Autónoma de Madrid/CIBERESP, Madrid, Spain/NCD Risk Factor Collaboration
Esther Lopez-Garcia
Universidad Autónoma de Madrid/CIBERESP, Madrid, Spain/NCD Risk Factor Collaboration
Fernando Rodríguez-Artalejo
Universidad Autónoma de Madrid/CIBERESP, Madrid, Spain/NCD Risk Factor Collaboration
Carlo M. Barbagallo
University of Palermo, Palermo, Italy/NCD Risk Factor Collaboration
Davide Noto
University of Palermo, Palermo, Italy/NCD Risk Factor Collaboration
Alberto Barceló
Pan American Health Organization, Washington, DC, USA
Pedro Ordunez
Pan American Health Organization, Washington, DC, USA/NCD Risk Factor Collaboration
Amina Barkat
Mohammed V University de Rabat, Rabat, Morocco
Iqbal Bata
Dalhousie University, Halifax, Nova Scotia, Canada
Ronald D. Gregor
Dalhousie University, Halifax, Nova Scotia, Canada/NCD Risk Factor Collaboration
Anwar M. Batieha
Jordan University of Science and Technology, Irbid, Jordan/NCD Risk Factor Collaboration
Hashem Y. J
Diminishing benefits of urban living for children and adolescents’ growth and development
No full textA list of authors and their affiliations appears online.Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m–2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified.peer-reviewe
Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants
No full textNCD Risk Factor Collaboration (NCD-RisC): National Institute of Health Doutor Ricardo Jorge, Portugal (Baltazar Nunes and Marta Barreto)Erratum in: Department of Error. Lancet. 2022 Feb 5;399(10324):520. doi: 10.1016/S0140-6736(22)00061-7. NCD Risk Factor Collaboration (NCD-RisC). "In this Article, Marialaura Bonaccio, Maria Benedetta Donati, and Francesco Gianfagna have been added to the NCD Risk Factor Collaboration list, and Steinar Krokstad's name has been corrected. These corrections have been made to the online version as of Feb 3, 2022"Background: Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories.
Methods: We used data from 1990 to 2019 on people aged 30-79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age.
Findings: The number of people aged 30-79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306-359) million women and 317 (292-344) million men in 1990 to 626 (584-668) million women and 652 (604-698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55-62) of women and 49% (46-52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43-51) of women and 38% (35-41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20-27) for women and 18% (16-21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran.
Interpretation: Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings.Evidence before this study: We searched MEDLINE (via PubMed) for articles published from inception to Jan 15, 2021, using the search terms ((hypertension[Title] AND (((medication OR treatment) AND control) OR aware*) AND “blood pressure”) OR (cardiovascular[Title] AND risk factor*[Title] AND “blood pressure” AND (((medication OR treatment) AND control) OR aware*))) AND (trend* OR global OR worldwide) NOT patient*[Title]. No language restrictions were applied. We found a few multi-country studies that reported hypertension prevalence, treatment, and control. These studies used up to 135 data sources that had sampled from national or sub-national populations or data from small communities. Few multi-country studies reported trends over time. The largest of these analyses covered snapshots in 2000 and 2010 and grouped countries into high income versus low income and middle income. We also found several studies that analysed trends in individual countries. To our knowledge, there is no study on long-term trends in, nor the contemporary levels of, hypertension prevalence, detection, treatment, and control that covers the entire world.
Added value of this study: To our knowledge, this study is the first comprehensive global analysis of trends in hypertension prevalence, detection, treatment, and control that covers all countries worldwide. The data used in the study were from 184 countries, together covering 99% of the global population, and were subject to rigorous inclusion and exclusion criteria. Data were analysed using a standardised protocol and were pooled using a statistical model designed to incorporate how hypertension and its care and control vary in relation to age, geography, and time.
Implications of all the available evidence: Hypertension care—including detection, treatment, and control—varies substantially worldwide and even within the same region of the world. Sub-Saharan Africa, Oceania, and south Asia have the lowest rates of detection, treatment, and control and many countries in these regions have seen little improvement in these outcomes over the past 30 years. The large improvements observed in some upper-middle-income and recently high-income countries show that the expansion of universal health coverage and primary care can be leveraged to enhance hypertension care and reduce the health burden of this condition.World Health Organizationinfo:eu-repo/semantics/publishedVersio
Worldwide trends in diabetes prevalence and treatment from 1990 to 2022: a pooled analysis of 1108 population-representative studies with 141 million participants
No full textNCD Risk Factor Collaboration (NCD-RisC) - INSA: Marta Barreto (Departamento de Epidemiologia)Erratum in: Lancet. 2025 Apr 5;405(10485):1146. doi: 10.1016/S0140-6736(25)00620-8.Background: Diabetes can be detected at the primary health-care level, and effective treatments lower the risk of complications. There are insufficient data on the coverage of treatment for diabetes and how it has changed. We estimated trends from 1990 to 2022 in diabetes prevalence and treatment for 200 countries and territories.
Methods: We used data from 1108 population-representative studies with 141 million participants aged 18 years and older with measurements of fasting glucose and glycated haemoglobin (HbA1c), and information on diabetes treatment. We defined diabetes as having a fasting plasma glucose (FPG) of 7·0 mmol/L or higher, having an HbA1c of 6·5% or higher, or taking medication for diabetes. We defined diabetes treatment as the proportion of people with diabetes who were taking medication for diabetes. We analysed the data in a Bayesian hierarchical meta-regression model to estimate diabetes prevalence and treatment.
Findings: In 2022, an estimated 828 million (95% credible interval [CrI] 757-908) adults (those aged 18 years and older) had diabetes, an increase of 630 million (554-713) from 1990. From 1990 to 2022, the age-standardised prevalence of diabetes increased in 131 countries for women and in 155 countries for men with a posterior probability of more than 0·80. The largest increases were in low-income and middle-income countries in southeast Asia (eg, Malaysia), south Asia (eg, Pakistan), the Middle East and north Africa (eg, Egypt), and Latin America and the Caribbean (eg, Jamaica, Trinidad and Tobago, and Costa Rica). Age-standardised prevalence neither increased nor decreased with a posterior probability of more than 0·80 in some countries in western and central Europe, sub-Saharan Africa, east Asia and the Pacific, Canada, and some Pacific island nations where prevalence was already high in 1990; it decreased with a posterior probability of more than 0·80 in women in Japan, Spain, and France, and in men in Nauru. The lowest prevalence in the world in 2022 was in western Europe and east Africa for both sexes, and in Japan and Canada for women, and the highest prevalence in the world in 2022 was in countries in Polynesia and Micronesia, some countries in the Caribbean and the Middle East and north Africa, as well as Pakistan and Malaysia. In 2022, 445 million (95% CrI 401-496) adults aged 30 years or older with diabetes did not receive treatment (59% of adults aged 30 years or older with diabetes), 3·5 times the number in 1990. From 1990 to 2022, diabetes treatment coverage increased in 118 countries for women and 98 countries for men with a posterior probability of more than 0·80. The largest improvement in treatment coverage was in some countries from central and western Europe and Latin America (Mexico, Colombia, Chile, and Costa Rica), Canada, South Korea, Russia, Seychelles, and Jordan. There was no increase in treatment coverage in most countries in sub-Saharan Africa; the Caribbean; Pacific island nations; and south, southeast, and central Asia. In 2022, age-standardised treatment coverage was lowest in countries in sub-Saharan Africa and south Asia, and treatment coverage was less than 10% in some African countries. Treatment coverage was 55% or higher in South Korea, many high-income western countries, and some countries in central and eastern Europe (eg, Poland, Czechia, and Russia), Latin America (eg, Costa Rica, Chile, and Mexico), and the Middle East and north Africa (eg, Jordan, Qatar, and Kuwait).
Interpretation: In most countries, especially in low-income and middle-income countries, diabetes treatment has not increased at all or has not increased sufficiently in comparison with the rise in prevalence. The burden of diabetes and untreated diabetes is increasingly borne by low-income and middle-income countries. The expansion of health insurance and primary health care should be accompanied with diabetes programmes that realign and resource health services to enhance the early detection and effective treatment of diabetes.UK Medical Research Council, UK Research and Innovation (Research England), and US Centers for Disease Control and Prevention
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